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Vahdat-Lasemi F, Farhoudi L, Hosseinikhah SM, Santos RD, Sahebkar A. Angiopoietin-like protein inhibitors: Promising agents for the treatment of familial hypercholesterolemia and atherogenic dyslipidemia. Atherosclerosis 2025; 405:119235. [PMID: 40344904 DOI: 10.1016/j.atherosclerosis.2025.119235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2025] [Revised: 04/23/2025] [Accepted: 05/01/2025] [Indexed: 05/11/2025]
Abstract
BACKGROUND AND AIMS This review examines the physiological functions of Angiopoietin-like proteins (ANGPTLs) in lipid metabolism and the epidemiology of atherosclerotic cardiovascular disease (ASCVD), while discussing their potential as therapies for dyslipidemias. METHODS A review of contemporary literature on ANGPTLs was conducted. RESULTS ANGPTLs comprise eight secreted proteins that share structural similarities with the angiopoietin family and serve as key regulators of various physiological and biochemical functions. Notably, ANGPTL3, ANGPTL4, and ANGPTL8 act as physiological inhibitors of lipoprotein lipase (LPL), playing a crucial role in lipoprotein and triglyceride metabolism in response to the body's nutritional status. A deficiency in these proteins is linked to hypolipidemia, characterized by a decrease in all lipid fractions, and genetic studies indicate a reduced risk of ASCVD in individuals with loss-of-function variants in ANGPTL3 and ANGPTL4. Conversely, elevated levels of ANGPTL3, ANGPTL4, and ANGPTL8 seem to increase the risk of cardiovascular disease. The role of ANGPTLs in regulating lipid metabolism underscores their potential in targeted therapies for managing dyslipidemias and lowering ASCVD risk, particularly in patients with difficult-to-control dyslipidemia phenotypes, such as homozygous Familial Hypercholesterolemia and mixed dyslipidemia. CONCLUSIONS The development of ANGPTL inhibitors could provide an effective strategy for preventing ASCVD.
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Affiliation(s)
- Fatemeh Vahdat-Lasemi
- Department of Medical Biotechnology and Nanotechnology, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Leila Farhoudi
- Nanotechnology Research Center, Pharmaceutical Technology Institute, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Seyedeh Maryam Hosseinikhah
- Nanotechnology Research Center, Pharmaceutical Technology Institute, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Raul D Santos
- Academic Research Organization, Hospital Israelita Albert Einstein, Sao Paulo, Brazil; Lipid Clinic Heart Institute (InCor) University of Sao Paulo Medical School Hospital, Sao Paulo, Brazil
| | - Amirhossein Sahebkar
- Biotechnology Research Center, Pharmaceutical Technology Institute, Mashhad University of Medical Sciences, Mashhad, Iran; Centre for Research Impact & Outcome, Chitkara College of Pharmacy, Chitkara University, Rajpura, 140401, Punjab, India; Applied Biomedical Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
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Khan TG, Bragazzi Cunha J, Raut C, Burroughs M, Vyas HS, Leix K, Goonewardena SN, Smrcka AV, Speliotes EK, Emmer BT. Functional interrogation of cellular Lp(a) uptake by genome-scale CRISPR screening. Atherosclerosis 2025; 403:119174. [PMID: 40174266 PMCID: PMC12011201 DOI: 10.1016/j.atherosclerosis.2025.119174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2024] [Revised: 02/04/2025] [Accepted: 03/07/2025] [Indexed: 04/04/2025]
Abstract
BACKGROUND AND AIMS An elevated level of lipoprotein(a), or Lp(a), in the bloodstream has been causally linked to the development of atherosclerotic cardiovascular disease and calcific aortic valve stenosis. Steady state levels of circulating lipoproteins are modulated by their rate of clearance, but the identity of the Lp(a) uptake receptor(s) has been controversial. METHODS We performed a genome-scale CRISPR screen to functionally interrogate all potential Lp(a) uptake regulators in HuH7 cells. Screen validation was performed by single gene disruption and overexpression. Direct binding between purified lipoproteins and recombinant protein was tested using biolayer interferometry. An association between human genetic variants and circulating Lp(a) levels was analyzed in the UK Biobank cohort. RESULTS The top positive and negative regulators of Lp(a) uptake in our screen were LDLR and MYLIP, encoding the LDL receptor and its ubiquitin ligase IDOL, respectively. We also found a significant correlation for other genes with established roles in LDLR regulation. No other gene products, including those previously proposed as Lp(a) receptors, exhibited a significant effect on Lp(a) uptake in our screen. We validated the functional influence of LDLR expression on HuH7 Lp(a) uptake, confirmed in vitro binding between the LDLR extracellular domain and purified Lp(a), and detected an association between loss-of-function LDLR variants and increased circulating Lp(a) levels in the UK Biobank cohort. CONCLUSIONS Our findings support a central role for the LDL receptor in mediating Lp(a) uptake by hepatocytes.
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Affiliation(s)
- Taslima G Khan
- Program in Chemical Biology, University of Michigan, Ann Arbor, MI, USA
| | - Juliana Bragazzi Cunha
- Division of Hospital Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Chinmay Raut
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA; Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Michael Burroughs
- Department of Pharmacology, University of Michigan, Ann Arbor, MI, USA
| | - Hitarthi S Vyas
- Division of Hospital Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Kyle Leix
- Division of Hospital Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Sascha N Goonewardena
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA; Frankel Cardiovascular Center, University of Michigan, Ann Arbor, MI, USA
| | - Alan V Smrcka
- Department of Pharmacology, University of Michigan, Ann Arbor, MI, USA
| | - Elizabeth K Speliotes
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA; Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Brian T Emmer
- Division of Hospital Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA; Frankel Cardiovascular Center, University of Michigan, Ann Arbor, MI, USA.
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Sachan V, Susan-Resiga D, Lam K, Seidah NG. The Biology and Clinical Implications of PCSK7. Endocr Rev 2025; 46:281-299. [PMID: 39661471 PMCID: PMC11894536 DOI: 10.1210/endrev/bnae031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2024] [Accepted: 12/09/2024] [Indexed: 12/13/2024]
Abstract
Discovered in 1996, PCSK7 is the seventh of the 9-membered proprotein convertase subtilisin-kexin (PCSK) family. This article reviews the various aspects of the multifaceted biology of PCSK7 and what makes it an exciting new target for metabolic dysfunction-associated steatotic liver disease (MASLD), affecting ∼30% of the population globally, dyslipidemia, cardiovascular disease, and likely cancer/metastasis. We will systematically review and discuss all the available epidemiological data, and structural, cell biology, and in vivo evidence that eventually led to the discovery of PCSK7 as a novel post-translational regulator of apolipoprotein B. Interestingly, PCSK7 is the only convertase, other than PCSK9, that exhibits noncanonical/nonenzymatic functions, which will be amply described in this review. The data so far have suggested that PCSK7 is a potential safe target in MASLD treatment. This was based on human epidemiological data, as well as mouse Pcsk7 knockout and mRNA translation inhibition using hepatocyte-targeted antisense oligonucleotides following a diet-induced MASLD. Additionally, of all the 9 convertases only the gene deletion of Pcsk7 and/or Pcsk9 in mice leads to healthy and fertile animals with no apparent deleterious consequences, suggesting that their pharmacological targeting is likely safe. Accordingly, the synergistic effects of inhibiting both PCSK7 and PCSK9 in a clinical setting may represent a novel therapy for various diseases. We believe that the current surge in oligonucleotide therapy, with many Food and Drug Administration-approved oligonucleotide-based drugs now available in clinics, and the urgent need for novel MASLD therapeutics present an opportune moment for this timely review article.
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Affiliation(s)
- Vatsal Sachan
- Laboratory of Biochemical Neuroendocrinology, Montreal Clinical Research Institute (IRCM, affiliated to the University of Montreal), Montreal, QC H2W 1R7, Canada
| | - Delia Susan-Resiga
- Laboratory of Biochemical Neuroendocrinology, Montreal Clinical Research Institute (IRCM, affiliated to the University of Montreal), Montreal, QC H2W 1R7, Canada
| | - Kalista Lam
- Laboratory of Biochemical Neuroendocrinology, Montreal Clinical Research Institute (IRCM, affiliated to the University of Montreal), Montreal, QC H2W 1R7, Canada
| | - Nabil G Seidah
- Laboratory of Biochemical Neuroendocrinology, Montreal Clinical Research Institute (IRCM, affiliated to the University of Montreal), Montreal, QC H2W 1R7, Canada
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Martin SS, Aday AW, Allen NB, Almarzooq ZI, Anderson CAM, Arora P, Avery CL, Baker-Smith CM, Bansal N, Beaton AZ, Commodore-Mensah Y, Currie ME, Elkind MSV, Fan W, Generoso G, Gibbs BB, Heard DG, Hiremath S, Johansen MC, Kazi DS, Ko D, Leppert MH, Magnani JW, Michos ED, Mussolino ME, Parikh NI, Perman SM, Rezk-Hanna M, Roth GA, Shah NS, Springer MV, St-Onge MP, Thacker EL, Urbut SM, Van Spall HGC, Voeks JH, Whelton SP, Wong ND, Wong SS, Yaffe K, Palaniappan LP. 2025 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association. Circulation 2025; 151:e41-e660. [PMID: 39866113 DOI: 10.1161/cir.0000000000001303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/28/2025]
Abstract
BACKGROUND The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2025 AHA Statistical Update is the product of a full year's worth of effort in 2024 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. This year's edition includes a continued focus on health equity across several key domains and enhanced global data that reflect improved methods and incorporation of ≈3000 new data sources since last year's Statistical Update. RESULTS Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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Ispir E, Saruhan E, Topcu DI, Varol B, Akbaba E, Cakmak T. Relationship between serum levels of ANGPTL8, Apo C2, and human placental lactogen (hPL) in patients with gestational diabetes mellitus: Interaction of LPL regulators with hPL, a possible contributing factor to insulin resistance. Placenta 2025; 159:119-125. [PMID: 39700905 DOI: 10.1016/j.placenta.2024.12.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Revised: 11/05/2024] [Accepted: 12/11/2024] [Indexed: 12/21/2024]
Abstract
INTRODUCTION Gestational diabetes mellitus (GDM) is defined as glucose intolerance during pregnancy. We aimed to investigate the potential effects of betatrophin and ApoC2 in GDM, focusing on their roles in LPL (lipoprotein lipase) regulation and their relationship with hPL to elucidate the possible impact of hPL on lipid metabolism and its potential contribution to the development of GDM. METHODS Thirty pregnant women with normal glucose tolerance and 29 with gestational diabetes mellitus (diagnosed by 75g OGTT between 24 and 28 weeks) were included in the study. Serum betatrophin, hPL, and ApoC2 were measured by Elisa and HOMA-IR was calculated. RESULTS In the GDM group, hPL levels correlated with betatrophin and ApoC2 (r = 0.552, p < 0.05; r = 0.588, p < 0.05 respectively) while betatrophin correlated with the ApoC2 (r = 0.584, p < 0.05). A linear relationship between hPL and betatropin and also between hPL and ApoC2 values in the control group (r = 0.454, p < 0.05; r = 0.779, p < 0.01 respectively) were observed. ApoC2 levels in the GDM group (n = 20) with HOMA-IR cut-off >2.5 were significantly higher than the control group (n = 10) (p < 0.05). There was also a positive relationship between betatrophin and ApoC2 (r = 0.591) (p < 0.05). DISCUSSION GDM patients may have impaired LPL enzyme regulation in addition to insulin resistance, with hPL potentially contributing to this disruption. Impaired lipoprotein lipase activity and its dysregulation secondary to genetic disorders may play a role in the etiopathogenesis of GDM. Further investigation into the correlation between betatrophin, ApoC2, and other LPL modulators in patients with various forms of diabetes could be beneficial for understanding this interaction more comprehensively.
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Affiliation(s)
- Emre Ispir
- Department of Medical Biochemistry, Bozyaka Research and Training Hospital, Izmir, Turkey.
| | - Ercan Saruhan
- Department of Medical Biochemistry, Faculty of Medicine, Mugla Sitki Kocman University, Mugla, Turkey.
| | - Deniz Ilhan Topcu
- Department of Medical Biochemistry, Izmir City Hospital, Izmir, Turkey.
| | - Bugra Varol
- Adnan Menderes University, Institute of Health Sciences, Division of Biostatistics, Aydin, Turkey.
| | - Eren Akbaba
- Department of Obstetrics and Gynecology, Faculty of Medicine, Mugla Sitki Kocman University, Mugla, Turkey.
| | - Tuba Cakmak
- Department of Medical Biochemistry, Bozyaka Research and Training Hospital, Izmir, Turkey.
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Opsasnick LA, Zhao W, Ratliff SM, Du J, Faul JD, Schmitz LL, Zhou X, Needham BL, Smith JA. Epigenome-wide mediation analysis of the relationship between psychosocial stress and cardiometabolic risk factors in the Health and Retirement Study (HRS). Clin Epigenetics 2024; 16:180. [PMID: 39695878 DOI: 10.1186/s13148-024-01799-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2024] [Accepted: 12/02/2024] [Indexed: 12/20/2024] Open
Abstract
BACKGROUND Exposure to psychosocial stress is linked to a variety of negative health outcomes, including cardiovascular disease and its cardiometabolic risk factors. DNA methylation has been associated with both psychosocial stress and cardiometabolic disease; however, little is known about the mediating role of DNA methylation on the association between stress and cardiometabolic risk. Thus, using the high-dimensional mediation testing method, we conducted an epigenome-wide mediation analysis of the relationship between psychosocial stress and ten cardiometabolic risk factors in a multi-racial/ethnic population of older adults (n = 2668) from the Health and Retirement Study (mean age = 70.4 years). RESULTS A total of 50, 46, 7, and 12 CpG sites across the epigenome mediated the total effects of stress on body mass index, waist circumference, high-density lipoprotein cholesterol, and C-reactive protein, respectively. When reducing the dimensionality of the CpG mediators to their top 10 uncorrelated principal components (PC), the cumulative effect of the PCs explained between 35.8 and 46.3% of these associations. CONCLUSIONS A subset of the mediating CpG sites were associated with the expression of genes enriched in pathways related to cytokine binding and receptor activity, as well as neuron development. Findings from this study help to elucidate the underlying mechanisms through which DNA methylation partially mediates the relationship between psychosocial stress and cardiometabolic risk factors.
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Affiliation(s)
- Lauren A Opsasnick
- Department of Epidemiology, School of Public Health, University of Michigan, 1415 Washington Heights, Ann Arbor, MI, 48109, USA.
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, 1415 Washington Heights, Ann Arbor, MI, 48109, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Scott M Ratliff
- Department of Epidemiology, School of Public Health, University of Michigan, 1415 Washington Heights, Ann Arbor, MI, 48109, USA
| | - Jiacong Du
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Jessica D Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Lauren L Schmitz
- Robert M. La Follette School of Public Affairs, University of Wisconsin-Madison, Madison, WI, USA
| | - Xiang Zhou
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Belinda L Needham
- Department of Epidemiology, School of Public Health, University of Michigan, 1415 Washington Heights, Ann Arbor, MI, 48109, USA
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, 1415 Washington Heights, Ann Arbor, MI, 48109, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
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Figueiredo I, Farinha C, Barreto P, Coimbra R, Pereira P, Marques JP, Pires I, Cachulo ML, Silva R. Nutritional Genomics: Implications for Age-Related Macular Degeneration. Nutrients 2024; 16:4124. [PMID: 39683519 DOI: 10.3390/nu16234124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2024] [Revised: 11/24/2024] [Accepted: 11/26/2024] [Indexed: 12/18/2024] Open
Abstract
Background: Age-related macular degeneration (AMD) is a leading cause of vision loss in older individuals, driven by a multifactorial etiology involving genetic, environmental, and dietary factors. Nutritional genomics, which studies gene-nutrient interactions, has emerged as a promising field for AMD prevention and management. Genetic predispositions, such as variants in CFH, C3, C2/CFB, APOE, and oxidative stress pathways, significantly affect the risk and progression of AMD. Methods: This narrative review synthesizes findings from randomized controlled trials and recent advances in nutritional genomics research. It examines the interplay between genetic predispositions and dietary interventions, exploring how personalized nutritional strategies can optimize AMD management. Results and Discussion: The AREDS and AREDS2 trials demonstrated that supplements, including vitamins C, E, zinc, copper, lutein, and zeaxanthin, can reduce the progression to advanced AMD. Nutritional interventions tailored to genetic profiles show promise: CFH risk alleles may enhance zinc supplementation's anti-inflammatory effects, while APOE variants influence the response to omega-3 fatty acids. Adjusting carotenoid intake, such as lutein and zeaxanthin, based on genetic susceptibility exemplifies emerging precision nutritional approaches. Ongoing research seeks to integrate nutrigenomic testing into clinical settings, enabling clinicians to tailor interventions to individual genetic profiles. Conclusions: Further studies are needed to assess the long-term effects of personalized interventions, investigate additional genetic variants, and develop tools for clinical implementation of nutrigenomics. Advancing these strategies holds the potential to improve patient outcomes, optimize AMD management, and pave the way for precision nutrition in ophthalmology.
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Affiliation(s)
- Inês Figueiredo
- Ophthalmology Department, Unidade Local de Saúde Coimbra, 3004-561 Coimbra, Portugal
| | - Cláudia Farinha
- Ophthalmology Department, Unidade Local de Saúde Coimbra, 3004-561 Coimbra, Portugal
- AIBILI-Association for Innovation and Biomedical Research on Light and Image, 3000-548 Coimbra, Portugal
- Clinical Academic Center of Coimbra (CACC), 3000-548 Coimbra, Portugal
- Coimbra Institute for Clinical and Biomedical Research, Faculty of Medicine (iCBR-FMUC), University of Coimbra, 3004-531 Coimbra, Portugal
| | - Patrícia Barreto
- AIBILI-Association for Innovation and Biomedical Research on Light and Image, 3000-548 Coimbra, Portugal
- Coimbra Institute for Clinical and Biomedical Research, Faculty of Medicine (iCBR-FMUC), University of Coimbra, 3004-531 Coimbra, Portugal
| | - Rita Coimbra
- AIBILI-Association for Innovation and Biomedical Research on Light and Image, 3000-548 Coimbra, Portugal
| | - Pedro Pereira
- Ophthalmology Department, Unidade Local de Saúde Coimbra, 3004-561 Coimbra, Portugal
- Clinical Academic Center of Coimbra (CACC), 3000-548 Coimbra, Portugal
| | - João Pedro Marques
- Ophthalmology Department, Unidade Local de Saúde Coimbra, 3004-561 Coimbra, Portugal
- AIBILI-Association for Innovation and Biomedical Research on Light and Image, 3000-548 Coimbra, Portugal
- Clinical Academic Center of Coimbra (CACC), 3000-548 Coimbra, Portugal
- Coimbra Institute for Clinical and Biomedical Research, Faculty of Medicine (iCBR-FMUC), University of Coimbra, 3004-531 Coimbra, Portugal
| | - Isabel Pires
- Ophthalmology Department, Unidade Local de Saúde Coimbra, 3004-561 Coimbra, Portugal
- AIBILI-Association for Innovation and Biomedical Research on Light and Image, 3000-548 Coimbra, Portugal
- Clinical Academic Center of Coimbra (CACC), 3000-548 Coimbra, Portugal
- Coimbra Institute for Clinical and Biomedical Research, Faculty of Medicine (iCBR-FMUC), University of Coimbra, 3004-531 Coimbra, Portugal
| | - Maria Luz Cachulo
- Ophthalmology Department, Unidade Local de Saúde Coimbra, 3004-561 Coimbra, Portugal
- AIBILI-Association for Innovation and Biomedical Research on Light and Image, 3000-548 Coimbra, Portugal
- Clinical Academic Center of Coimbra (CACC), 3000-548 Coimbra, Portugal
- Coimbra Institute for Clinical and Biomedical Research, Faculty of Medicine (iCBR-FMUC), University of Coimbra, 3004-531 Coimbra, Portugal
| | - Rufino Silva
- Ophthalmology Department, Unidade Local de Saúde Coimbra, 3004-561 Coimbra, Portugal
- AIBILI-Association for Innovation and Biomedical Research on Light and Image, 3000-548 Coimbra, Portugal
- Clinical Academic Center of Coimbra (CACC), 3000-548 Coimbra, Portugal
- Coimbra Institute for Clinical and Biomedical Research, Faculty of Medicine (iCBR-FMUC), University of Coimbra, 3004-531 Coimbra, Portugal
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Moore A, Ritchie MD. Is the Relationship Between Cardiovascular Disease and Alzheimer's Disease Genetic? A Scoping Review. Genes (Basel) 2024; 15:1509. [PMID: 39766777 PMCID: PMC11675426 DOI: 10.3390/genes15121509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2024] [Revised: 11/20/2024] [Accepted: 11/22/2024] [Indexed: 01/11/2025] Open
Abstract
BACKGROUND/OBJECTIVES Cardiovascular disease (CVD) and Alzheimer's disease (AD) are two diseases highly prevalent in the aging population and often co-occur. The exact relationship between the two diseases is uncertain, though epidemiological studies have demonstrated that CVDs appear to increase the risk of AD and vice versa. This scoping review aims to examine the current identified overlapping genetics between CVDs and AD at the individual gene level and at the shared pathway level. METHODS Following PRISMA-ScR guidelines for a scoping review, we searched the PubMed and Scopus databases from 1990 to October 2024 for articles that involved (1) CVDs, (2) AD, and (3) used statistical methods to parse genetic relationships. RESULTS Our search yielded 2918 articles, of which 274 articles passed screening and were organized into two main sections: (1) evidence of shared genetic risk; and (2) shared mechanisms. The genes APOE, PSEN1, and PSEN2 reportedly have wide effects across the AD and CVD spectrum, affecting both cardiac and brain tissues. Mechanistically, changes in three main pathways (lipid metabolism, blood pressure regulation, and the breakdown of the blood-brain barrier (BBB)) contribute to subclinical and etiological changes that promote both AD and CVD progression. However, genetic studies continue to be limited by the availability of longitudinal data and lack of cohorts that are representative of diverse populations. CONCLUSIONS Highly penetrant familial genes simultaneously increase the risk of CVDs and AD. However, in most cases, sets of dysregulated genes within larger-scale mechanisms, like changes in lipid metabolism, blood pressure regulation, and BBB breakdown, increase the risk of both AD and CVDs and contribute to disease progression.
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Affiliation(s)
- Anni Moore
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA;
| | - Marylyn D. Ritchie
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA;
- Division of Informatics, Department of Biostatistics, Epidemiology & Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Penn Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
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Chan DC, Watts GF. Inhibition of the ANGPTL3/8 Complex for the Prevention and Treatment of Atherosclerotic Cardiovascular Disease. Curr Atheroscler Rep 2024; 27:6. [PMID: 39565562 DOI: 10.1007/s11883-024-01254-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/02/2024] [Indexed: 11/21/2024]
Abstract
PURPOSE OF REVIEW Dyslipidemia is a casual risk factor for atherosclerotic cardiovascular disease (ASCVD). There is an unmet need for more effective treatments for patients with dyslipidemias. Angiopoietin-like protein 3 (ANGPTL3) and ANGPTL8 play key roles in triglyceride trafficking and energy balance in humans. We review the functional role of these ANGPTL proteins in the regulation of lipoprotein metabolism, and recent clinical trials targeting ANGPTL3 and ANGPTL3/8 with monoclonal antibody and/or nucleic acid therapies, including antisense oligonucleotides and small interfering RNA. RECENT FINDINGS Cumulative evidence supports the roles of ANGPTL3 and ANGPTL8 in lipid metabolism through inhibition of lipoprotein lipase and endothelial lipase activity. ANGPTL3 and ANGPTL3/8 inhibitors are effective in lowering plasma triglycerides and low-density lipoprotein (LDL)-cholesterol, with the possible advantage of raising high-density lipoprotein (HDL)-cholesterol with the inhibition of ANGPTL3/8. Therapeutic inhibition of ANGPTL3 and ANGPTL3/8 can lower plasma triglyceride and LDL-cholesterol levels possibly by lowering production and upregulating catabolism of triglyceride-rich lipoprotein and LDL particles. However, the effect of these novel agents on HDL metabolism remains unclear. The cardiovascular benefits of ANGPTL3 and ABGPTL3/8 inhibitors may also include improvement in vascular inflammation, but this requires further investigation.
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Affiliation(s)
- Dick C Chan
- Medical School, University of Western Australia, Perth, Australia
| | - Gerald F Watts
- Medical School, University of Western Australia, Perth, Australia.
- Department of Cardiology and Internal Medicine, Royal Perth Hospital, Perth, Australia.
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Clarke B, Holtkamp E, Öztürk H, Mück M, Wahlberg M, Meyer K, Munzlinger F, Brechtmann F, Hölzlwimmer FR, Lindner J, Chen Z, Gagneur J, Stegle O. Integration of variant annotations using deep set networks boosts rare variant association testing. Nat Genet 2024; 56:2271-2280. [PMID: 39322779 PMCID: PMC11525182 DOI: 10.1038/s41588-024-01919-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 08/20/2024] [Indexed: 09/27/2024]
Abstract
Rare genetic variants can have strong effects on phenotypes, yet accounting for rare variants in genetic analyses is statistically challenging due to the limited number of allele carriers and the burden of multiple testing. While rich variant annotations promise to enable well-powered rare variant association tests, methods integrating variant annotations in a data-driven manner are lacking. Here we propose deep rare variant association testing (DeepRVAT), a model based on set neural networks that learns a trait-agnostic gene impairment score from rare variant annotations and phenotypes, enabling both gene discovery and trait prediction. On 34 quantitative and 63 binary traits, using whole-exome-sequencing data from UK Biobank, we find that DeepRVAT yields substantial gains in gene discoveries and improved detection of individuals at high genetic risk. Finally, we demonstrate how DeepRVAT enables calibrated and computationally efficient rare variant tests at biobank scale, aiding the discovery of genetic risk factors for human disease traits.
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Affiliation(s)
- Brian Clarke
- Division of Computational Genomics and Systems Genetics, German Cancer Research Center (DKFZ), Heidelberg, Germany.
- AI Health Innovation Cluster, German Cancer Research Center (DKFZ), Heidelberg, Germany.
| | - Eva Holtkamp
- TUM School of Computation, Information and Technology, Technical University of Munich, Garching, Germany
- Helmholtz Association-Munich School for Data Science (MUDS), Munich, Germany
- Computational Health Center, Helmholtz Center Munich, Neuherberg, Germany
| | - Hakime Öztürk
- Division of Computational Genomics and Systems Genetics, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Marcel Mück
- AI Health Innovation Cluster, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Magnus Wahlberg
- AI Health Innovation Cluster, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Kayla Meyer
- AI Health Innovation Cluster, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Felix Munzlinger
- AI Health Innovation Cluster, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Felix Brechtmann
- TUM School of Computation, Information and Technology, Technical University of Munich, Garching, Germany
- Munich Center for Machine Learning, Munich, Germany
| | - Florian R Hölzlwimmer
- TUM School of Computation, Information and Technology, Technical University of Munich, Garching, Germany
| | - Jonas Lindner
- TUM School of Computation, Information and Technology, Technical University of Munich, Garching, Germany
| | - Zhifen Chen
- Department of Cardiology, Deutsches Herzzentrum München, Technical University Munich, Munich, Germany
- Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Julien Gagneur
- TUM School of Computation, Information and Technology, Technical University of Munich, Garching, Germany.
- Computational Health Center, Helmholtz Center Munich, Neuherberg, Germany.
- Munich Center for Machine Learning, Munich, Germany.
- Institute of Human Genetics, School of Medicine and Health, Technical University of Munich, Munich, Germany.
| | - Oliver Stegle
- Division of Computational Genomics and Systems Genetics, German Cancer Research Center (DKFZ), Heidelberg, Germany.
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany.
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, UK.
- Wellcome Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK.
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11
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Chen SM, Huang TY, Lee WJ, Chuang LM, Chang TJ. Positive correlation of ANGPTL8 expression in human visceral adipose tissue with body mass index. J Formos Med Assoc 2024; 123:860-865. [PMID: 38191275 DOI: 10.1016/j.jfma.2023.12.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2023] [Revised: 12/21/2023] [Accepted: 12/27/2023] [Indexed: 01/10/2024] Open
Abstract
BACKGROUND Angiopoietin-like protein 8 (ANGPTL8) is an important regulator of lipid metabolism. We aimed to investigate the difference of ANGPTL8 expression in different depots of adipose tissues between individuals with and without obesity, and its correlation with various metabolic parameters. METHODS Subcutaneous (SAT) and visceral adipose tissue (VAT) samples were collected from patients who underwent bariatric or intra-abdominal surgery. Expression levels of ANGPTL8, monoglyceride lipase (MGL), monocyte chemoattractant protein-1 (MCP-1), leptin and adiponectin (APM1) were determined using real-time quantitative polymerase chain reaction. The correlation of ANGPTL8 expression with various metabolic parameters and other gene expression levels was analyzed using Person's correlation analysis. Logistic regression was used to establish a prediction model of obesity. RESULTS Totally 330 subjects (obese: 281, non-obese: 49) were recruited. ANGPTL8 expression in VAT was significantly higher in the obesity group than in the non-obesity group (P = 0.0096). ANGPTL8 expression in VAT was positively correlated with body mass index (BMI) (r = 0.1169, P < 0.05) and was independently associated with obesity (O.R., 1.246; 95 % C.I. 1.013-21.533, P = 0.038). We also found the gene expression of ANGPTL8 in SAT and VAT was negatively correlated with APM1 expression in respective SAT and VAT. CONCLUSION ANGPTL8 expression levels in VAT were higher in subjects with obesity, and positively correlated with BMI. This suggests a role of ANGPTL8 in the pathophysiology of obesity and may pave the way for novel treatment target of obesity.
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Affiliation(s)
- Shiau-Mei Chen
- Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | - Tse-Ying Huang
- Department of Internal Medicine, National Taiwan University Hospital, Hsin-Chu Branch, Taiwan
| | - Wei-Jei Lee
- Department of Surgery, Taoyuan Min-Sheng General Hospital, Taoyuan, Taiwan
| | - Lee-Ming Chuang
- Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan; School of Medicine, National Taiwan University, Taipei, Taiwan; Graduate Institute of Molecular Medicine, National Taiwan University, Taipei, Taiwan; Graduate Institute of Clinical Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan; Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Tien-Jyun Chang
- Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan; School of Medicine, National Taiwan University, Taipei, Taiwan.
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12
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Zhang R, Zhang K. A unified model for regulating lipoprotein lipase activity. Trends Endocrinol Metab 2024; 35:490-504. [PMID: 38521668 PMCID: PMC11663433 DOI: 10.1016/j.tem.2024.02.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/25/2023] [Revised: 02/16/2024] [Accepted: 02/20/2024] [Indexed: 03/25/2024]
Abstract
The regulation of triglyceride (TG) tissue distribution, storage, and utilization, a fundamental process of energy homeostasis, critically depends on lipoprotein lipase (LPL). We review the intricate mechanisms by which LPL activity is regulated by angiopoietin-like proteins (ANGPTL3, 4, 8), apolipoproteins (APOA5, APOC3, APOC2), and the cAMP-responsive element-binding protein H (CREBH). ANGPTL8 functions as a molecular switch, through complex formation, activating ANGPTL3 while deactivating ANGPTL4 in their LPL inhibition. The ANGPTL3-4-8 model integrates the roles of the aforementioned proteins in TG partitioning between white adipose tissue (WAT) and oxidative tissues (heart and skeletal muscles) during the feed/fast cycle. This model offers a unified perspective on LPL regulation, providing insights into TG metabolism, metabolic diseases, and therapeutics.
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Affiliation(s)
- Ren Zhang
- Center for Molecular Medicine and Genetics, Wayne State University School of Medicine, Detroit, MI 48201, USA.
| | - Kezhong Zhang
- Center for Molecular Medicine and Genetics, Wayne State University School of Medicine, Detroit, MI 48201, USA
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13
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Khan TG, Cunha JB, Raut C, Burroughs M, Goonewardena SN, Smrcka AV, Speliotes EK, Emmer BT. Functional interrogation of cellular Lp(a) uptake by genome-scale CRISPR screening. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.11.593568. [PMID: 38766193 PMCID: PMC11100788 DOI: 10.1101/2024.05.11.593568] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
An elevated level of lipoprotein(a), or Lp(a), in the bloodstream has been causally linked to the development of atherosclerotic cardiovascular disease and calcific aortic valve stenosis. Steady state levels of circulating lipoproteins are modulated by their rate of clearance, but the identity of the Lp(a) uptake receptor(s) has been controversial. In this study, we performed a genome-scale CRISPR screen to functionally interrogate all potential Lp(a) uptake regulators in HuH7 cells. Strikingly, the top positive and negative regulators of Lp(a) uptake in our screen were LDLR and MYLIP, encoding the LDL receptor and its ubiquitin ligase IDOL, respectively. We also found a significant correlation for other genes with established roles in LDLR regulation. No other gene products, including those previously proposed as Lp(a) receptors, exhibited a significant effect on Lp(a) uptake in our screen. We validated the functional influence of LDLR expression on HuH7 Lp(a) uptake, confirmed in vitro binding between the LDLR extracellular domain and purified Lp(a), and detected an association between loss-of-function LDLR variants and increased circulating Lp(a) levels in the UK Biobank cohort. Together, our findings support a central role for the LDL receptor in mediating Lp(a) uptake by hepatocytes.
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Affiliation(s)
- Taslima G. Khan
- Program in Chemical Biology, University of Michigan, Ann Arbor MI
| | - Juliana Bragazzi Cunha
- Division of Hospital Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor MI
| | - Chinmay Raut
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, University of Michigan, Ann Arbor MI
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor MI
| | | | - Sascha N. Goonewardena
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor MI
- Frankel Cardiovascular Center, University of Michigan, Ann Arbor MI
| | - Alan V. Smrcka
- Department of Pharmacology, University of Michigan, Ann Arbor MI
| | - Elizabeth K. Speliotes
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, University of Michigan, Ann Arbor MI
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor MI
| | - Brian T. Emmer
- Division of Hospital Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor MI
- Frankel Cardiovascular Center, University of Michigan, Ann Arbor MI
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14
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Wen Y, Chen YQ, Konrad RJ. Angiopoietin-like protein 8: a multifaceted protein instrumental in regulating triglyceride metabolism. Curr Opin Lipidol 2024; 35:58-65. [PMID: 37962908 DOI: 10.1097/mol.0000000000000910] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
PURPOSE OF REVIEW The angiopoietin-like (ANGPTL) proteins ANGPTL3 and ANGPTL4 are critical lipoprotein lipase (LPL) inhibitors. This review discusses the unique ability of the insulin-responsive protein ANGPTL8 to regulate triglyceride (TG) metabolism by forming ANGPTL3/8 and ANGPTL4/8 complexes that control tissue-specific LPL activities. RECENT FINDINGS After feeding, ANGPTL4/8 acts locally in adipose tissue, has decreased LPL-inhibitory activity compared to ANGPTL4, and binds tissue plasminogen activator (tPA) and plasminogen to generate plasmin, which cleaves ANGPTL4/8 and other LPL inhibitors. This enables LPL to be fully active postprandially to promote efficient fatty acid (FA) uptake and minimize ectopic fat deposition. In contrast, liver-derived ANGPTL3/8 acts in an endocrine manner, has markedly increased LPL-inhibitory activity compared to ANGPTL3, and potently inhibits LPL in oxidative tissues to direct TG toward adipose tissue for storage. Circulating ANGPTL3/8 levels are strongly correlated with serum TG, and the ANGPTL3/8 LPL-inhibitory epitope is blocked by the TG-lowering protein apolipoprotein A5 (ApoA5). SUMMARY ANGPTL8 plays a crucial role in TG metabolism by forming ANGPTL3/8 and ANGPTL4/8 complexes that differentially modulate LPL activities in oxidative and adipose tissues respectively. Selective ANGPTL8 inhibition in the context of the ANGPTL3/8 complex has the potential to be a promising strategy for treating dyslipidemia.
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Affiliation(s)
- Yi Wen
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana, USA
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15
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Ghosh A, Leung YH, Yu J, Sladek R, Chénier I, Oppong AK, Peyot ML, Madiraju SRM, Al-Khairi I, Thanaraj TA, Abubaker J, Al-Mulla F, Prentki M, Abu-Farha M. Silencing ANGPTL8 reduces mouse preadipocyte differentiation and insulin signaling. Biochim Biophys Acta Mol Cell Biol Lipids 2024; 1869:159461. [PMID: 38272177 DOI: 10.1016/j.bbalip.2024.159461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 01/12/2024] [Accepted: 01/19/2024] [Indexed: 01/27/2024]
Abstract
ANGPTL8, expressed mainly in the liver and adipose tissue, regulates the activity of lipoprotein lipase (LPL) present in the extracellular space and triglyceride (TG) metabolism through its interaction with ANGPTL3 and ANGPTL4. Whether intracellular ANGPTL8 can also exert effects in tissues where it is expressed is uncertain. ANGPTL8 expression was low in preadipocytes and much increased during differentiation. To better understand the role of intracellular ANGPTL8 in adipocytes and assess whether it may play a role in adipocyte differentiation, we knocked down its expression in normal mouse subcutaneous preadipocytes. ANGPTL8 knockdown reduced adipocyte differentiation, cellular TG accumulation and also isoproterenol-stimulated lipolysis at day 7 of differentiation. RNA-Seq analysis of ANGPTL8 siRNA or control siRNA transfected SC preadipocytes on days 0, 2, 4 and 7 of differentiation showed that ANGPTL8 knockdown impeded the early (day 2) expression of adipogenic and insulin signaling genes, PPARγ, as well as genes related to extracellular matrix and NF-κB signaling. Insulin mediated Akt phosphorylation was reduced at an early stage during adipocyte differentiation. This study based on normal primary cells shows that ANGPTL8 has intracellular actions in addition to effects in the extracellular space, like modulating LPL activity. Preadipocyte ANGPTL8 expression modulates their differentiation possibly via changes in insulin signaling gene expression.
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Affiliation(s)
- Anindya Ghosh
- Departments of Nutrition, Biochemistry and Molecular Medicine, University of Montreal, and Montreal Diabetes Research Center, Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada
| | - Yat Hei Leung
- Departments of Nutrition, Biochemistry and Molecular Medicine, University of Montreal, and Montreal Diabetes Research Center, Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada
| | - Jeffrey Yu
- Department of Medicine, McGill University, Montréal, QC, Canada
| | - Robert Sladek
- Department of Medicine, McGill University, Montréal, QC, Canada
| | - Isabelle Chénier
- Departments of Nutrition, Biochemistry and Molecular Medicine, University of Montreal, and Montreal Diabetes Research Center, Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada
| | - Abel K Oppong
- Departments of Nutrition, Biochemistry and Molecular Medicine, University of Montreal, and Montreal Diabetes Research Center, Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada
| | - Marie-Line Peyot
- Departments of Nutrition, Biochemistry and Molecular Medicine, University of Montreal, and Montreal Diabetes Research Center, Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada
| | - S R Murthy Madiraju
- Departments of Nutrition, Biochemistry and Molecular Medicine, University of Montreal, and Montreal Diabetes Research Center, Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada
| | | | | | | | | | - Marc Prentki
- Departments of Nutrition, Biochemistry and Molecular Medicine, University of Montreal, and Montreal Diabetes Research Center, Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada.
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16
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Aghasizadeh M, Ahmadi Hoseini A, Sahebi R, Kazemi T, Asadiyan‐Sohan P, Esmaily H, Samadi S, Avan A, Ferns GA, Khosravi S, Ghazizadeh H, Miri‐Moghaddam E, Ghayour‐Mobarhan M. Association of a genetic variant in angiopoietin-like 3 with serum HDL-C and risk of cardiovascular disease: A study of the MASHAD cohort over 6 years. Mol Genet Genomic Med 2024; 12:e2418. [PMID: 38634215 PMCID: PMC11024632 DOI: 10.1002/mgg3.2418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2023] [Revised: 01/17/2024] [Accepted: 03/19/2024] [Indexed: 04/19/2024] Open
Abstract
BACKGROUND Loss-of-function (LOF) variants of the angiopoietin-like 3 (ANGPTL3) gene are reported to be associated with serum triglyceride (TG) and high-density lipoprotein cholesterol (HDL-C) concentrations and thereby affect the risk of cardiovascular disease (CVD). OBJECTIVE In the present study, we examined the association of rs10789117 in the ANGPTL 3 gene locus and the risk of CVD in the group of people who were part of the Mashhad-Stroke and Heart-Atherosclerotic-Disorders (MASHAD) cohort. METHODS One thousand and two healthy individuals enrolled in this study of whom 849 subjects were healthy and 153 subjects developed CVD outcomes after 6 years of follow-up. After a 12-h overnight fasting, 20 mL of blood samples were collected for the measurement of fasting blood glucose and lipid profile. DNA was extracted, and the Tetra-ARMS PCR (amplification refractory mutation system) was used for genotyping of rs10789117 in the ANGPTL3 gene. The genotype frequencies of the variant of rs10789117 in the ANGPTL3 gene were estimated using χ2 tests. Eventually, the statistical analysis was done by SPSS version 20. RESULTS Individuals with AC/CC genotypes (rs10789117) were found to have to greater risk of CVD events compared to AA genotype (OR = 1.43, 95%CI = 1.01-2.02, p = 0.041). There was a 1.3-fold increase in cardiovascular events in individuals carrying the C allele of rs10789117 variant compared to non-carriers (OR = 1.32, 95%CI = 1.06-1.72, p value = 0.038). There were significant differences between different genotypes for serum triglyceride levels within the control group, but this difference was not significant in the group with CVD. Moreover, there was a significant association between CC genotype and CVD risk in the individuals with a normal serum HDL-C. CONCLUSION We have found that a rs10789117 C>A in ANGPTL3 gene polymorphism was associated with incident CVD events, and this may be of value as a risk stratification biomarker in CVD in the Iranian population.
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Affiliation(s)
- Malihe Aghasizadeh
- Student Research Committee, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, IranMashhad University of Medical SciencesMashhadIran
| | - Asieh Ahmadi Hoseini
- Department of Nutrition, Ghaem HospitalMashhad University of Medical SciencesMashhadIran
| | - Reza Sahebi
- Student Research Committee, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, IranMashhad University of Medical SciencesMashhadIran
- Department of Modern Sciences and Technologies, Faculty of MedicineMashhad University of Medical SciencesMashhadIran
| | - Tooba Kazemi
- Cardiovascular Diseases Research CenterBirjand University of Medical SciencesBirjandIran
- Razi Clinical Research Development Unit (RCRDU)Birjand University of Medical SciencesBirjandIran
| | - Parisa Asadiyan‐Sohan
- Student Research Committee, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, IranMashhad University of Medical SciencesMashhadIran
| | - Habibollah Esmaily
- Social Determinants of Health Research CenterMashhad University of Medical SciencesMashhadIran
- Department of Biostatistics, School of HealthMashhad University of Medical SciencesMashhadIran
| | - Sara Samadi
- Department of Modern Sciences and Technologies, Faculty of MedicineMashhad University of Medical SciencesMashhadIran
| | - Amir Avan
- Student Research Committee, Faculty of MedicineMashhad University of Medical SciencesMashhadIran
- Metabolic Syndrome Research CenterMashhad University of Medical SciencesMashhadIran
| | - Gordon A. Ferns
- Division of Medical EducationBrighton & Sussex Medical SchoolBrightonUK
| | - Saeede Khosravi
- Cardiovascular Diseases Research CenterBirjand University of Medical SciencesBirjandIran
| | - Hamideh Ghazizadeh
- Department of Modern Sciences and Technologies, Faculty of MedicineMashhad University of Medical SciencesMashhadIran
| | - Ebrahim Miri‐Moghaddam
- Cardiovascular Diseases Research CenterBirjand University of Medical SciencesBirjandIran
| | - Majid Ghayour‐Mobarhan
- Student Research Committee, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, IranMashhad University of Medical SciencesMashhadIran
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17
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Akbarzadeh M, Riahi P, Saeidian AH, Zarkesh M, Masjoudi S, Asgarian S, Guity K, Moheimani H, Masoudi H, Roudbar MA, Khalili D, Hosseinpanah F, Barzin M, Hogan CT, Hakonarson H, Hedayati M, Daneshpour MS, Azizi F. The Tehran longitudinal family-based cardiometabolic cohort study sheds new light on dyslipidemia transmission patterns. Sci Rep 2024; 14:4739. [PMID: 38413617 PMCID: PMC10899171 DOI: 10.1038/s41598-024-53504-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Accepted: 02/01/2024] [Indexed: 02/29/2024] Open
Abstract
Dyslipidemia, as a metabolic risk factor, with the strongest and most heritable independent cause of cardiovascular diseases worldwide. We investigated the familial transmission patterns of dyslipidemia through a longitudinal family-based cohort, the Tehran Cardiometabolic Genetic Study (TCGS) in Iran. We enrolled 18,729 individuals (45% were males) aged > 18 years (mean: 38.15 (15.82)) and observed them over five 3-year follow-up periods. We evaluated the serum concentrations of total cholesterol, triglyceride, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol with the first measurement among longitudinal measures and the average measurements (AM) of the five periods. Heritability analysis was conducted using a mixed-effect framework with likelihood-based and Bayesian approaches. The periodic prevalence and heritability of dyslipidemia were estimated to be 65.7 and 42%, respectively. The likelihood of an individual having at least one dyslipidemic parent reveals an OR = 6.94 (CI 5.28-9.30) compared to those who do not have dyslipidemic parents. The most considerable intraclass correlation of family members was for the same-sex siblings, with ICC ~ 25.5%. For serum concentrations, heritability ranged from 33.64 to 60.95%. Taken together, these findings demonstrate that familial transmission of dyslipidemia in the Tehran population is strong, especially within the same-gender siblings. According to previous reports, the heritability of dyslipidemia in this population is considerably higher than the global average.
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Affiliation(s)
- Mahdi Akbarzadeh
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Parisa Riahi
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Amir Hossein Saeidian
- Center for Applied Genomics (CAG), Children's Hospital of Philadelphia, 3615 Civic Center Blvd, Abramson Building, Philadelphia, PA, 19104, USA
| | - Maryam Zarkesh
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Sajedeh Masjoudi
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Sara Asgarian
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Kamran Guity
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Hamed Moheimani
- Department of Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Homayoon Masoudi
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mahmoud Amiri Roudbar
- Department of Animal Science, Safiabad-Dezful Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education & Extension Organization (AREEO), Dezful, Iran
| | - Davood Khalili
- Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Farhad Hosseinpanah
- Obesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Maryam Barzin
- Obesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Carolyn T Hogan
- Division of Hepatology, Temple University Hospital, Philadelphia, PA, USA
| | - Hakon Hakonarson
- Center for Applied Genomics (CAG), Children's Hospital of Philadelphia, 3615 Civic Center Blvd, Abramson Building, Philadelphia, PA, 19104, USA
- Department of Pediatrics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Division of Pulmonary Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Mehdi Hedayati
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Maryam S Daneshpour
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Fereidoun Azizi
- Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
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18
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Konaklieva MI, Plotkin BJ. Targeting host-specific metabolic pathways-opportunities and challenges for anti-infective therapy. Front Mol Biosci 2024; 11:1338567. [PMID: 38455763 PMCID: PMC10918472 DOI: 10.3389/fmolb.2024.1338567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 01/24/2024] [Indexed: 03/09/2024] Open
Abstract
Microorganisms can takeover critical metabolic pathways in host cells to fuel their replication. This interaction provides an opportunity to target host metabolic pathways, in addition to the pathogen-specific ones, in the development of antimicrobials. Host-directed therapy (HDT) is an emerging strategy of anti-infective therapy, which targets host cell metabolism utilized by facultative and obligate intracellular pathogens for entry, replication, egress or persistence of infected host cells. This review provides an overview of the host lipid metabolism and links it to the challenges in the development of HDTs for viral and bacterial infections, where pathogens are using important for the host lipid enzymes, or producing their own analogous of lecithin-cholesterol acyltransferase (LCAT) and lipoprotein lipase (LPL) thus interfering with the human host's lipid metabolism.
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Affiliation(s)
| | - Balbina J. Plotkin
- Department of Microbiology and Immunology, Midwestern University, Downers Grove, IL, United States
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Martin SS, Aday AW, Almarzooq ZI, Anderson CAM, Arora P, Avery CL, Baker-Smith CM, Barone Gibbs B, Beaton AZ, Boehme AK, Commodore-Mensah Y, Currie ME, Elkind MSV, Evenson KR, Generoso G, Heard DG, Hiremath S, Johansen MC, Kalani R, Kazi DS, Ko D, Liu J, Magnani JW, Michos ED, Mussolino ME, Navaneethan SD, Parikh NI, Perman SM, Poudel R, Rezk-Hanna M, Roth GA, Shah NS, St-Onge MP, Thacker EL, Tsao CW, Urbut SM, Van Spall HGC, Voeks JH, Wang NY, Wong ND, Wong SS, Yaffe K, Palaniappan LP. 2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association. Circulation 2024; 149:e347-e913. [PMID: 38264914 DOI: 10.1161/cir.0000000000001209] [Citation(s) in RCA: 804] [Impact Index Per Article: 804.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/25/2024]
Abstract
BACKGROUND The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains. RESULTS Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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Sachan V, Le Dévéhat M, Roubtsova A, Essalmani R, Laurendeau JF, Garçon D, Susan-Resiga D, Duval S, Mikaeeli S, Hamelin J, Evagelidis A, Chong M, Paré G, Chernetsova E, Gao ZH, Robillard I, Ruiz M, Trinh VQH, Estall JL, Faraj M, Austin RC, Sauvageau M, Prat A, Kiss RS, Seidah NG. PCSK7: A novel regulator of apolipoprotein B and a potential target against non-alcoholic fatty liver disease. Metabolism 2024; 150:155736. [PMID: 37967646 DOI: 10.1016/j.metabol.2023.155736] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Revised: 10/17/2023] [Accepted: 11/08/2023] [Indexed: 11/17/2023]
Abstract
BACKGROUND Epidemiological evidence links the proprotein convertase subtilisin/kexin 7 (PCSK7) to triglyceride (TG) metabolism. We associated the known PCSK7 gain-of-function non-coding SNP rs236918 with higher levels of plasma apolipoprotein B (apoB) and the loss-of-function coding variant p.Pro777Leu (SNP rs201598301) with lower apoB and TG. Herein, we aimed to unravel the in vivo role of liver PCSK7. METHODS We biochemically defined the functional role of PCSK7 in lipid metabolism using hepatic cell lines and Pcsk7-/- mice. Our findings were validated following subcutaneous administration of hepatocyte-targeted N-acetylgalactosamine (GalNAc)-antisense oligonucleotides (ASOs) against Pcsk7. RESULTS Independent of its proteolytic activity, membrane-bound PCSK7 binds apoB100 in the endoplasmic reticulum and enhances its secretion. Mechanistically, the loss of PCSK7/Pcsk7 leads to apoB100 degradation, triggering an unfolded protein response, autophagy, and β-oxidation, eventually reducing lipid accumulation in hepatocytes. Non-alcoholic fatty liver disease (NAFLD) was induced by a 12-week high fat/fructose/cholesterol diet in wild type (WT) and Pcsk7-/- mice that were then allowed to recover on a 4-week control diet. Pcsk7-/- mice recovered more effectively than WT mice from all NAFLD-related liver phenotypes. Finally, subcutaneous administration of GalNAc-ASOs targeting hepatic Pcsk7 to WT mice validated the above results. CONCLUSIONS Our data reveal hepatic PCSK7 as one of the major regulators of apoB, and its absence reduces apoB secretion from hepatocytes favoring its ubiquitination and degradation by the proteasome. This results in a cascade of events, eventually reducing hepatic lipid accumulation, thus supporting the notion of silencing PCSK7 mRNA in hepatocytes for targeting NAFLD.
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Affiliation(s)
- Vatsal Sachan
- Biochemical Neuroendocrinology, Institut de Recherches Cliniques de Montréal (IRCM), affiliated to the Université de Montréal, Montréal, QC, Canada
| | - Maïlys Le Dévéhat
- Biochemical Neuroendocrinology, Institut de Recherches Cliniques de Montréal (IRCM), affiliated to the Université de Montréal, Montréal, QC, Canada
| | - Anna Roubtsova
- Biochemical Neuroendocrinology, Institut de Recherches Cliniques de Montréal (IRCM), affiliated to the Université de Montréal, Montréal, QC, Canada
| | - Rachid Essalmani
- Biochemical Neuroendocrinology, Institut de Recherches Cliniques de Montréal (IRCM), affiliated to the Université de Montréal, Montréal, QC, Canada
| | - Jean-Francois Laurendeau
- RNA and Noncoding Mechanisms of Disease, Institut de Recherches Cliniques de Montréal (IRCM), affiliated to the Université de Montréal, Montréal, QC, Canada
| | - Damien Garçon
- Biochemical Neuroendocrinology, Institut de Recherches Cliniques de Montréal (IRCM), affiliated to the Université de Montréal, Montréal, QC, Canada
| | - Delia Susan-Resiga
- Biochemical Neuroendocrinology, Institut de Recherches Cliniques de Montréal (IRCM), affiliated to the Université de Montréal, Montréal, QC, Canada
| | - Stéphanie Duval
- Biochemical Neuroendocrinology, Institut de Recherches Cliniques de Montréal (IRCM), affiliated to the Université de Montréal, Montréal, QC, Canada
| | - Sahar Mikaeeli
- Biochemical Neuroendocrinology, Institut de Recherches Cliniques de Montréal (IRCM), affiliated to the Université de Montréal, Montréal, QC, Canada
| | - Josée Hamelin
- Biochemical Neuroendocrinology, Institut de Recherches Cliniques de Montréal (IRCM), affiliated to the Université de Montréal, Montréal, QC, Canada
| | - Alexandra Evagelidis
- Biochemical Neuroendocrinology, Institut de Recherches Cliniques de Montréal (IRCM), affiliated to the Université de Montréal, Montréal, QC, Canada
| | - Michael Chong
- Department of Biochemistry & Biomedical Sciences, McMaster University Faculty of Health Sciences, Hamilton, Ontario, Canada
| | - Guillaume Paré
- Department of Biochemistry & Biomedical Sciences, McMaster University Faculty of Health Sciences, Hamilton, Ontario, Canada
| | | | - Zu-Hua Gao
- Department of Pathology, McGill University Health Centre, Montréal, QC, Canada
| | - Isabelle Robillard
- Montreal Heart Institute, Metabolomics Platform, Montreal, Quebec, Canada; Department of Nutrition, Université de Montréal, Montréal, QC, Canada
| | - Matthieu Ruiz
- Montreal Heart Institute, Metabolomics Platform, Montreal, Quebec, Canada; Department of Nutrition, Université de Montréal, Montréal, QC, Canada
| | - Vincent Quoc-Huy Trinh
- Departement of Pathology and Cellular Biology, Institut de Recherche en Immunologie et Cancérologie, Université de Montréal, Montréal, QC, Canada
| | - Jennifer L Estall
- Molecular Mechanisms of Diabetes, Institut de Recherches Cliniques de Montréal (IRCM), affiliated to the Université de Montréal, Montréal, QC, Canada
| | - May Faraj
- Nutrition Department, Université de Montréal, Research Unit on Nutrition, Lipoproteins and Cardiometabolic Diseases, Institut de Recherches Cliniques de Montréal (IRCM), Montréal, QC, Canada
| | - Richard C Austin
- Department of Medicine, Division of Nephrology, McMaster University, The Research Institute of St. Joe's Hamilton and the Hamilton Center for Kidney Research, Hamilton, ON, Canada
| | - Martin Sauvageau
- RNA and Noncoding Mechanisms of Disease, Institut de Recherches Cliniques de Montréal (IRCM), affiliated to the Université de Montréal, Montréal, QC, Canada
| | - Annik Prat
- Biochemical Neuroendocrinology, Institut de Recherches Cliniques de Montréal (IRCM), affiliated to the Université de Montréal, Montréal, QC, Canada
| | - Robert S Kiss
- McGill University Health Centre Research Institute, Montréal, QC, Canada
| | - Nabil G Seidah
- Biochemical Neuroendocrinology, Institut de Recherches Cliniques de Montréal (IRCM), affiliated to the Université de Montréal, Montréal, QC, Canada.
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Thorin E, Labbé P, Lambert M, Mury P, Dagher O, Miquel G, Thorin-Trescases N. Angiopoietin-Like Proteins: Cardiovascular Biology and Therapeutic Targeting for the Prevention of Cardiovascular Diseases. Can J Cardiol 2023; 39:1736-1756. [PMID: 37295611 DOI: 10.1016/j.cjca.2023.06.002] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 05/27/2023] [Accepted: 06/02/2023] [Indexed: 06/12/2023] Open
Abstract
Despite the best pharmacologic tools available, cardiovascular diseases (CVDs) remain a major cause of morbidity and mortality in developed countries. After 2 decades of research, new therapeutic targets, such as angiopoietin-like proteins (ANGPTLs), are emerging. ANGPTLs belong to a family of 8 members, from ANGPTL1 to ANGPTL8; they have structural homology with angiopoietins and are secreted in the circulation. ANGPTLs display a multitude of physiological and pathologic functions; they contribute to inflammation, angiogenesis, cell death, senescence, hematopoiesis, and play a role in repair, maintenance, and tissue homeostasis. ANGPTLs-particularly the triad ANGPTL3, 4, and 8-have an established role in lipid metabolism through the regulation of triacylglycerol trafficking according to the nutritional status. Some ANGPTLs also contribute to glucose metabolism. Therefore, dysregulation in ANGPTL expression associated with abnormal circulating levels are linked to a plethora of CVD and metabolic disorders including atherosclerosis, heart diseases, diabetes, but also obesity and cancers. Because ANGPTLs bind to different receptors according to the cell type, antagonists are therapeutically inadequate. Recently, direct inhibitors of ANGPTLs, mainly ANGPTL3, have been developed, and specific monoclonal antibodies and antisense oligonucleotides are currently being tested in clinical trials. The aim of the current review is to provide an up-to-date preclinical and clinical overview on the function of the 8 members of the ANGPTL family in the cardiovascular system, their contribution to CVD, and the therapeutic potential of manipulating some of them.
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Affiliation(s)
- Eric Thorin
- Montreal Heart Institute, Université de Montréal, Montréal, Québec, Canada; Faculty of Medicine, Department of Pharmacology, Université de Montréal, Montréal, Québec, Canada; Faculty of Medicine, Department of Surgery, Université de Montréal, Montréal, Québec, Canada.
| | - Pauline Labbé
- Montreal Heart Institute, Université de Montréal, Montréal, Québec, Canada
| | - Mélanie Lambert
- Montreal Heart Institute, Université de Montréal, Montréal, Québec, Canada; Faculty of Medicine, Department of Pharmacology, Université de Montréal, Montréal, Québec, Canada
| | - Pauline Mury
- Montreal Heart Institute, Université de Montréal, Montréal, Québec, Canada; Faculty of Medicine, Department of Pharmacology, Université de Montréal, Montréal, Québec, Canada
| | - Olina Dagher
- Montreal Heart Institute, Université de Montréal, Montréal, Québec, Canada; Faculty of Medicine, Department of Surgery, Université de Montréal, Montréal, Québec, Canada; Department of Cardiac Sciences, Libin Cardiovascular Institute, Calgary, Alberta, Canada
| | - Géraldine Miquel
- Montreal Heart Institute, Université de Montréal, Montréal, Québec, Canada
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Ølnes ÅS, Teigen M, Laerdahl JK, Leren TP, Strøm TB, Bjune K. Variants in the CETP gene affect levels of HDL cholesterol by reducing the amount, and not the specific lipid transfer activity, of secreted CETP. PLoS One 2023; 18:e0294764. [PMID: 38039300 PMCID: PMC10691695 DOI: 10.1371/journal.pone.0294764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Accepted: 10/31/2023] [Indexed: 12/03/2023] Open
Abstract
BACKGROUND Cholesteryl ester transfer protein (CETP) transfers cholesteryl esters in plasma from high density lipoprotein (HDL) to very low density lipoprotein and low density lipoprotein. Loss-of-function variants in the CETP gene cause elevated levels of HDL cholesterol. In this study, we have determined the functional consequences of 24 missense variants in the CETP gene. The 24 missense variants studied were the ones reported in the Human Gene Mutation Database and in the literature to affect HDL cholesterol levels, as well as two novel variants identified at the Unit for Cardiac and Cardiovascular Genetics, Oslo University Hospital in subjects with hyperalphalipoproteinemia. METHODS HEK293 cells were transiently transfected with mutant CETP plasmids. The amounts of CETP protein in lysates and media were determined by Western blot analysis, and the lipid transfer activities of the CETP variants were determined by a fluorescence-based assay. RESULTS Four of the CETP variants were not secreted. Five of the variants were secreted less than 15% compared to the WT-CETP, while the other 15 variants were secreted in varying amounts. There was a linear relationship between the levels of secreted protein and the lipid transfer activities (r = 0.96, p<0.001). Thus, the secreted variants had similar specific lipid transfer activities. CONCLUSION The effect of the 24 missense variants in the CETP gene on the lipid transfer activity was mediated predominantly by their impact on the secretion of the CETP protein. The four variants that prevented CETP secretion cause autosomal dominant hyperalphalipoproteinemia. The five variants that markedly reduced secretion of the respective variants cause mild hyperalphalipoproteinemia. The majority of the remaining 15 variants had minor effects on the secretion of CETP, and are considered neutral genetic variants.
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Affiliation(s)
- Åsa Schawlann Ølnes
- Unit for Cardiac and Cardiovascular Genetics, Oslo University Hospital, Oslo, Norway
| | - Marianne Teigen
- Unit for Cardiac and Cardiovascular Genetics, Oslo University Hospital, Oslo, Norway
| | - Jon K. Laerdahl
- Department of Microbiology, Oslo University Hospital, Oslo, Norway
- Department of Informatics, ELIXIR Norway, University of Oslo, Oslo, Norway
| | - Trond P. Leren
- Unit for Cardiac and Cardiovascular Genetics, Oslo University Hospital, Oslo, Norway
| | - Thea Bismo Strøm
- Unit for Cardiac and Cardiovascular Genetics, Oslo University Hospital, Oslo, Norway
| | - Katrine Bjune
- Unit for Cardiac and Cardiovascular Genetics, Oslo University Hospital, Oslo, Norway
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23
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de las Fuentes L, Schwander KL, Brown MR, Bentley AR, Winkler TW, Sung YJ, Munroe PB, Miller CL, Aschard H, Aslibekyan S, Bartz TM, Bielak LF, Chai JF, Cheng CY, Dorajoo R, Feitosa MF, Guo X, Hartwig FP, Horimoto A, Kolčić I, Lim E, Liu Y, Manning AK, Marten J, Musani SK, Noordam R, Padmanabhan S, Rankinen T, Richard MA, Ridker PM, Smith AV, Vojinovic D, Zonderman AB, Alver M, Boissel M, Christensen K, Freedman BI, Gao C, Giulianini F, Harris SE, He M, Hsu FC, Kühnel B, Laguzzi F, Li X, Lyytikäinen LP, Nolte IM, Poveda A, Rauramaa R, Riaz M, Robino A, Sofer T, Takeuchi F, Tayo BO, van der Most PJ, Verweij N, Ware EB, Weiss S, Wen W, Yanek LR, Zhan Y, Amin N, Arking DE, Ballantyne C, Boerwinkle E, Brody JA, Broeckel U, Campbell A, Canouil M, Chai X, Chen YDI, Chen X, Chitrala KN, Concas MP, de Faire U, de Mutsert R, de Silva HJ, de Vries PS, Do A, Faul JD, Fisher V, Floyd JS, Forrester T, Friedlander Y, Girotto G, Gu CC, Hallmans G, Heikkinen S, Heng CK, Homuth G, Hunt S, Ikram MA, Jacobs DR, Kavousi M, Khor CC, Kilpeläinen TO, Koh WP, Komulainen P, Langefeld CD, Liang J, et alde las Fuentes L, Schwander KL, Brown MR, Bentley AR, Winkler TW, Sung YJ, Munroe PB, Miller CL, Aschard H, Aslibekyan S, Bartz TM, Bielak LF, Chai JF, Cheng CY, Dorajoo R, Feitosa MF, Guo X, Hartwig FP, Horimoto A, Kolčić I, Lim E, Liu Y, Manning AK, Marten J, Musani SK, Noordam R, Padmanabhan S, Rankinen T, Richard MA, Ridker PM, Smith AV, Vojinovic D, Zonderman AB, Alver M, Boissel M, Christensen K, Freedman BI, Gao C, Giulianini F, Harris SE, He M, Hsu FC, Kühnel B, Laguzzi F, Li X, Lyytikäinen LP, Nolte IM, Poveda A, Rauramaa R, Riaz M, Robino A, Sofer T, Takeuchi F, Tayo BO, van der Most PJ, Verweij N, Ware EB, Weiss S, Wen W, Yanek LR, Zhan Y, Amin N, Arking DE, Ballantyne C, Boerwinkle E, Brody JA, Broeckel U, Campbell A, Canouil M, Chai X, Chen YDI, Chen X, Chitrala KN, Concas MP, de Faire U, de Mutsert R, de Silva HJ, de Vries PS, Do A, Faul JD, Fisher V, Floyd JS, Forrester T, Friedlander Y, Girotto G, Gu CC, Hallmans G, Heikkinen S, Heng CK, Homuth G, Hunt S, Ikram MA, Jacobs DR, Kavousi M, Khor CC, Kilpeläinen TO, Koh WP, Komulainen P, Langefeld CD, Liang J, Liu K, Liu J, Lohman K, Mägi R, Manichaikul AW, McKenzie CA, Meitinger T, Milaneschi Y, Nauck M, Nelson CP, O’Connell JR, Palmer ND, Pereira AC, Perls T, Peters A, Polašek O, Raitakari OT, Rice K, Rice TK, Rich SS, Sabanayagam C, Schreiner PJ, Shu XO, Sidney S, Sims M, Smith JA, Starr JM, Strauch K, Tai ES, Taylor KD, Tsai MY, Uitterlinden AG, van Heemst D, Waldenberger M, Wang YX, Wei WB, Wilson G, Xuan D, Yao J, Yu C, Yuan JM, Zhao W, Becker DM, Bonnefond A, Bowden DW, Cooper RS, Deary IJ, Divers J, Esko T, Franks PW, Froguel P, Gieger C, Jonas JB, Kato N, Lakka TA, Leander K, Lehtimäki T, Magnusson PKE, North KE, Ntalla I, Penninx B, Samani NJ, Snieder H, Spedicati B, van der Harst P, Völzke H, Wagenknecht LE, Weir DR, Wojczynski MK, Wu T, Zheng W, Zhu X, Bouchard C, Chasman DI, Evans MK, Fox ER, Gudnason V, Hayward C, Horta BL, Kardia SLR, Krieger JE, Mook-Kanamori DO, Peyser PA, Province MM, Psaty BM, Rudan I, Sim X, Smith BH, van Dam RM, van Duijn CM, Wong TY, Arnett DK, Rao DC, Gauderman J, Liu CT, Morrison AC, Rotter JI, Fornage M. Gene-educational attainment interactions in a multi-population genome-wide meta-analysis identify novel lipid loci. Front Genet 2023; 14:1235337. [PMID: 38028628 PMCID: PMC10651736 DOI: 10.3389/fgene.2023.1235337] [Show More Authors] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Accepted: 09/27/2023] [Indexed: 12/01/2023] Open
Abstract
Introduction: Educational attainment, widely used in epidemiologic studies as a surrogate for socioeconomic status, is a predictor of cardiovascular health outcomes. Methods: A two-stage genome-wide meta-analysis of low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), and triglyceride (TG) levels was performed while accounting for gene-educational attainment interactions in up to 226,315 individuals from five population groups. We considered two educational attainment variables: "Some College" (yes/no, for any education beyond high school) and "Graduated College" (yes/no, for completing a 4-year college degree). Genome-wide significant (p < 5 × 10-8) and suggestive (p < 1 × 10-6) variants were identified in Stage 1 (in up to 108,784 individuals) through genome-wide analysis, and those variants were followed up in Stage 2 studies (in up to 117,531 individuals). Results: In combined analysis of Stages 1 and 2, we identified 18 novel lipid loci (nine for LDL, seven for HDL, and two for TG) by two degree-of-freedom (2 DF) joint tests of main and interaction effects. Four loci showed significant interaction with educational attainment. Two loci were significant only in cross-population analyses. Several loci include genes with known or suggested roles in adipose (FOXP1, MBOAT4, SKP2, STIM1, STX4), brain (BRI3, FILIP1, FOXP1, LINC00290, LMTK2, MBOAT4, MYO6, SENP6, SRGAP3, STIM1, TMEM167A, TMEM30A), and liver (BRI3, FOXP1) biology, highlighting the potential importance of brain-adipose-liver communication in the regulation of lipid metabolism. An investigation of the potential druggability of genes in identified loci resulted in five gene targets shown to interact with drugs approved by the Food and Drug Administration, including genes with roles in adipose and brain tissue. Discussion: Genome-wide interaction analysis of educational attainment identified novel lipid loci not previously detected by analyses limited to main genetic effects.
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Affiliation(s)
- Lisa de las Fuentes
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine, St. Louis, MO, United States
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States
| | - Karen L. Schwander
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States
| | - Michael R. Brown
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Amy R. Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, United States
| | - Thomas W. Winkler
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Yun Ju Sung
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
| | - Patricia B. Munroe
- Clinical Pharmacology, Queen Mary University of London, London, United Kingdom
- National Institute for Health Research Barts Cardiovascular Biomedical Research Unit, Queen Mary University of London, London, United Kingdom
| | - Clint L. Miller
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, United States
- Biochemistry and Molecular Genetics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, United States
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, United States
| | - Hugo Aschard
- Department of Epidemiology, Harvard School of Public Health, Boston, MA, United States
- Département de Génomes et Génétique, Institut Pasteur de Lille, Université de Lille, Lille, France
| | - Stella Aslibekyan
- School of Public Health, Epidemiology, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Traci M. Bartz
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, United States
- Department of Biostatistics, University of Washington, Seattle, WA, United States
| | - Lawrence F. Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Jin Fang Chai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Ching-Yu Cheng
- Ocular Epidemiology, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program, Medical School, Duke-National University of Singapore, Singapore, Singapore
| | - Rajkumar Dorajoo
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | - Mary F. Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States
| | - Xiuqing Guo
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Los Angeles, CA, United States
| | - Fernando P. Hartwig
- Postgraduate Programme in Epidemiology, Faculty of Medicine, Federal University of Pelotas, Pelotas, RS, Brazil
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
| | - Andrea Horimoto
- Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of Sao Paulo Medical School, Sao Paulo, SP, Brazil
| | - Ivana Kolčić
- University of Split School of Medicine, Split, Croatia
- Algebra University College, Zagreb, Croatia
| | - Elise Lim
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | - Yongmei Liu
- Division of Cardiology, Department of Medicine, Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC, United States
| | - Alisa K. Manning
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, United States
- Department of Medicine, Harvard Medical School, Boston, MA, United States
| | - Jonathan Marten
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Solomon K. Musani
- Jackson Heart Study, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, United States
| | - Raymond Noordam
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, Netherlands
| | - Sandosh Padmanabhan
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom
| | - Tuomo Rankinen
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, United States
| | - Melissa A. Richard
- Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Paul M. Ridker
- Division of Preventive Medicine, Brigham and Women’s Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Albert V. Smith
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, United States
- Icelandic Heart Association, Kopavogur, Iceland
| | - Dina Vojinovic
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, Netherlands
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands
| | - Alan B. Zonderman
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States
- National Institutes of Health, Baltimore, MD, United States
| | - Maris Alver
- Estonian Genome Center, Insititute of Genomics, University of Tartu, Tartu, Estonia
| | - Mathilde Boissel
- European Genomic Institute for Diabetes, Institut Pasteur de Lille, Lille, France
- University of Lille, Lille University Hospital, Lille, France
| | - Kaare Christensen
- Unit of Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Barry I. Freedman
- Nephrology Division, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, United States
| | - Chuan Gao
- Molecular Genetics and Genomics Program, Wake Forest School of Medicine, Winston-Salem, NC, United States
| | - Franco Giulianini
- Division of Preventive Medicine, Brigham and Women’s Hospital, Boston, MA, United States
| | - Sarah E. Harris
- Department of Psychology, The University of Edinburgh, Edinburgh, United Kingdom
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, United Kingdom
| | - Meian He
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Fang-Chi Hsu
- Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, United States
| | - Brigitte Kühnel
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Federica Laguzzi
- Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Xiaoyin Li
- Department of Population and Quantitative Health Sciences, Cleveland, OH, United States
- Department of Mathematics and Statistics, St. Cloud State University, St. Cloud, MN, United States
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, University of Tampere, Tampere, Finland
- Finnish Cardiovascular Research Center, University of Tampere, Tampere, Finland
| | - Ilja M. Nolte
- Unit of Genetic Epidemiology and Bioinformatics, Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Alaitz Poveda
- Genetic and Molecular Epidemiology Unit, Department of Clinical Sciences, Skåne University Hospital, Lund University, Malmö, Sweden
| | - Rainer Rauramaa
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Muhammad Riaz
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom
| | - Antonietta Robino
- Institute for Maternal and Child Health-IRCCS Burlo Garofolo, Trieste, Italy
| | - Tamar Sofer
- Biostatistics, Department of Medicine, Brigham and Women’s Hospital, Harvard University, Boston, MA, United States
| | - Fumihiko Takeuchi
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Bamidele O. Tayo
- Department of Public Health Sciences, Loyola University Chicago, Maywood, IL, United States
| | - Peter J. van der Most
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Niek Verweij
- Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Erin B. Ware
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, United States
| | - Stefan Weiss
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald and University of Greifswald, Greifswald, Germany
- German Center for Cardiovascular Research, Greifswald, Germany
| | - Wanqing Wen
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Lisa R. Yanek
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Yiqiang Zhan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Najaf Amin
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, Netherlands
| | - Dan E. Arking
- Department of Genetic Medicine, McKusick-Nathans Institute, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Christie Ballantyne
- Section of Cardiovascular Research, Baylor College of Medicine, Houston, TX, United States
- Houston Methodist Debakey Heart and Vascular Center, Houston, TX, United States
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, United States
| | - Jennifer A. Brody
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, United States
| | - Ulrich Broeckel
- Section on Genomic Pediatrics, Department of Pediatrics, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics & Cancer, University of Edinburgh, Edinburgh, United Kingdom
- Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom
| | - Mickaël Canouil
- European Genomic Institute for Diabetes, Institut Pasteur de Lille, Lille, France
- University of Lille, Lille University Hospital, Lille, France
| | - Xiaoran Chai
- Data Science Unit, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Yii-Der Ida Chen
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Los Angeles, CA, United States
| | - Xu Chen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Kumaraswamy Naidu Chitrala
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States
| | - Maria Pina Concas
- Institute for Maternal and Child Health-IRCCS Burlo Garofolo, Trieste, Italy
| | - Ulf de Faire
- Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Renée de Mutsert
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, Netherlands
| | - H. Janaka de Silva
- Department of Medicine, Faculty of Medicine, University of Kelaniya, Ragama, Sri Lanka
| | - Paul S. de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Ahn Do
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States
| | - Jessica D. Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, United States
| | - Virginia Fisher
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | - James S. Floyd
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, United States
| | - Terrence Forrester
- Tropical Medicine Research Institute, University of the West Indies, Mona, Jamaica
| | - Yechiel Friedlander
- Braun School of Public Health, Hadassah Medical Center, Hebrew University, Jerusalem, Israel
| | - Giorgia Girotto
- Institute for Maternal and Child Health-IRCCS Burlo Garofolo, Trieste, Italy
| | - C. Charles Gu
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States
| | - Göran Hallmans
- Section for Nutritional Research, Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Sami Heikkinen
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio, Finland
| | - Chew-Kiat Heng
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Khoo Teck Puat National University Children’s Medical Institute, National University Health System, Singapore, Singapore
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald and University of Greifswald, Greifswald, Germany
| | - Steven Hunt
- Department of Internal Medicine, University of Utah, Salt Lake City, UT, United States
- Department of Genetic Medicine, Weill Cornell Medicine in Qatar, Doha, Qatar
| | - M. Arfan Ikram
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, Netherlands
| | - David R. Jacobs
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, United States
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, Netherlands
| | - Chiea Chuen Khor
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | - Tuomas O. Kilpeläinen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Environmental Medicine and Public Health, The Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Woon-Puay Koh
- Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research (A*STAR), Singapore, Singapore
| | | | - Carl D. Langefeld
- Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, United States
| | - Jingjing Liang
- Department of Population and Quantitative Health Sciences, Cleveland, OH, United States
| | - Kiang Liu
- Epidemiology, Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
| | - Jianjun Liu
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | - Kurt Lohman
- Division of Cardiology, Department of Medicine, Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC, United States
| | - Reedik Mägi
- Estonian Genome Center, Insititute of Genomics, University of Tartu, Tartu, Estonia
| | - Ani W. Manichaikul
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, United States
| | - Colin A. McKenzie
- Tropical Medicine Research Institute, University of the West Indies, Mona, Jamaica
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Human Genetics, Technische Universität München, Munich, Germany
| | | | - Matthias Nauck
- German Center for Cardiovascular Research, Greifswald, Germany
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Christopher P. Nelson
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom
| | - Jeffrey R. O’Connell
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD, United States
- Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Nicholette D. Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, United States
| | - Alexandre C. Pereira
- Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of Sao Paulo Medical School, Sao Paulo, SP, Brazil
| | - Thomas Perls
- Geriatrics Section, Department of Medicine, Boston University School of Medicine, Boston, MA, United States
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Cardiovascular Research, Neuherberg, Germany
| | - Ozren Polašek
- University of Split School of Medicine, Split, Croatia
- Algebra University College, Zagreb, Croatia
| | - Olli T. Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Kenneth Rice
- Department of Biostatistics, University of Washington, Seattle, WA, United States
| | - Treva K. Rice
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States
| | - Stephen S. Rich
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, United States
| | - Charumathi Sabanayagam
- Ocular Epidemiology, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program, Medical School, Duke-National University of Singapore, Singapore, Singapore
| | - Pamela J. Schreiner
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, United States
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Stephen Sidney
- Division of Research, Kaiser Permanente of Northern California, Oakland, CA, United States
| | - Mario Sims
- Jackson Heart Study, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, United States
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, United States
| | - John M. Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, United Kingdom
- Alzheimer Scotland Dementia Research Centre, The University of Edinburgh, Edinburgh, United Kingdom
| | - Konstantin Strauch
- German Research Center for Environmental Health, Helmholtz Zentrum München, Institute of Genetic Epidemiology, Neuherberg, Germany
- Institute of Medical Informatics Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - E. Shyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
- Duke-National University of Singapore Medical School, Singapore, Singapore
| | - Kent D. Taylor
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Los Angeles, CA, United States
| | - Michael Y. Tsai
- Department of Laboratory Medicine and Pathology, Minneapolis, MN, United States
| | - André G. Uitterlinden
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center, Rotterdam, Netherlands
| | - Diana van Heemst
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, Netherlands
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Ya-Xing Wang
- Beijing Ophthalmology and Visual Science Key Lab, Beijing Tongren Eye Center, Beijing Tongren Hospital, Beijing Institute of Ophthalmology, Capital Medical University, Beijing, China
| | - Wen-Bin Wei
- Beijing Ophthalmology and Visual Science Key Lab, Beijing Tongren Eye Center, Beijing Tongren Hospital, Beijing Institute of Ophthalmology, Capital Medical University, Beijing, China
| | - Gregory Wilson
- Jackson Heart Study Graduate Training Center, School of Public, Jackson State University, Jackson, MS, United States
| | - Deng Xuan
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | - Jie Yao
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Los Angeles, CA, United States
| | - Caizheng Yu
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jian-Min Yuan
- Department of Epidemiology, School of Public Health, University of Pittsburgh, Pittsburgh, PA, United States
- Division of Cancer Control and Population Sciences, University of Pittsburgh Medical Center (UPMC) Hillman Cancer Center, Pittsburgh, PA, United States
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Diane M. Becker
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Amélie Bonnefond
- European Genomic Institute for Diabetes, Institut Pasteur de Lille, Lille, France
- University of Lille, Lille University Hospital, Lille, France
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, United Kingdom
| | - Donald W. Bowden
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, United States
| | - Richard S. Cooper
- Department of Public Health Sciences, Loyola University Chicago, Maywood, IL, United States
| | - Ian J. Deary
- Department of Psychology, The University of Edinburgh, Edinburgh, United Kingdom
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, United Kingdom
| | - Jasmin Divers
- Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, United States
| | - Tõnu Esko
- Estonian Genome Center, Insititute of Genomics, University of Tartu, Tartu, Estonia
- Broad Institute, Massachusetts Institute of Technology and Harvard University, Boston, MA, United States
| | - Paul W. Franks
- Genetic and Molecular Epidemiology Unit, Department of Clinical Sciences, Skåne University Hospital, Lund University, Malmö, Sweden
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
- Department of Nutrition, Harvard Chan School of Public Health, Boston, MA, United States
| | - Philippe Froguel
- European Genomic Institute for Diabetes, Institut Pasteur de Lille, Lille, France
- University of Lille, Lille University Hospital, Lille, France
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, United Kingdom
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research, Neuherberg, Germany
| | - Jost B. Jonas
- Beijing Ophthalmology and Visual Science Key Lab, Beijing Tongren Eye Center, Beijing Tongren Hospital, Beijing Institute of Ophthalmology, Capital Medical University, Beijing, China
- Department of Ophthalmology, Medical Faculty Mannheim, University Heidelberg, Mannheim, Germany
- Institute of Molecular and Clinical Ophthalmology, Basel, Switzerland
| | - Norihiro Kato
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Timo A. Lakka
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
| | - Karin Leander
- Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Terho Lehtimäki
- Department of Clinical Chemistry, University of Tampere, Tampere, Finland
- Finnish Cardiovascular Research Center, University of Tampere, Tampere, Finland
| | - Patrik K. E. Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Kari E. North
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Ioanna Ntalla
- Clinical Pharmacology, Queen Mary University of London, London, United Kingdom
- Celgene, Bristol Myers Squibb, Mississauga, ON, Canada
| | | | - Nilesh J. Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom
| | - Harold Snieder
- Unit of Genetic Epidemiology and Bioinformatics, Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Beatrice Spedicati
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy
| | - Pim van der Harst
- Division Heart and Lungs, Department of Cardiology, University Medical Center Utrecht, University of Utrecht, Utrecht, Netherlands
| | - Henry Völzke
- German Center for Cardiovascular Research, Greifswald, Germany
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Lynne E. Wagenknecht
- Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, United States
| | - David R. Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, United States
| | - Mary K. Wojczynski
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States
| | - Tangchun Wu
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Xiaofeng Zhu
- Department of Population and Quantitative Health Sciences, Cleveland, OH, United States
| | - Claude Bouchard
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, United States
| | - Daniel I. Chasman
- Division of Preventive Medicine, Brigham and Women’s Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Michele K. Evans
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States
- National Institute on Aging, National Institutes of Health, Bethesda, MD, United States
| | - Ervin R. Fox
- Division of Cardiology, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, United States
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Bernardo L. Horta
- Postgraduate Programme in Epidemiology, Faculty of Medicine, Federal University of Pelotas, Pelotas, RS, Brazil
| | - Sharon L. R. Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Jose Eduardo Krieger
- Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of Sao Paulo Medical School, Sao Paulo, SP, Brazil
| | - Dennis O. Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, Netherlands
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, Netherlands
| | - Patricia A. Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Michael M. Province
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, United States
- Department of Epidemiology, University of Washington, Seattle, WA, United States
- Department of Health Systems and Population Health, University of Washington, Seattle, WA, United States
| | - Igor Rudan
- Centre for Global Health, The Usher Institute, The University of Edinburgh, Edinburgh, United Kingdom
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Blair H. Smith
- Division of Population Health and Genomics, Ninewells Hospital and Medical School, University of Dundee, Dundee, United Kingdom
| | - Rob M. van Dam
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Department of Exercise and Nutrition Sciences, Milken Institute School of Public Health, The George Washington University, Washington, DC, United States
| | - Cornelia M. van Duijn
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, Netherlands
- Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Tien Yin Wong
- Ocular Epidemiology, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program, Medical School, Duke-National University of Singapore, Singapore, Singapore
| | - Donna K. Arnett
- College of Public Health, Dean’s Office, University of Kentucky, Lexington, KY, United States
| | - Dabeeru C. Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States
| | - James Gauderman
- Division of Biostatistics, Population and Public Health Sciences, University of Southern California, Los Angeles, CA, United States
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | - Alanna C. Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Jerome I. Rotter
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Los Angeles, CA, United States
| | - Myriam Fornage
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States
- Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX, United States
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24
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Urbut SM, Koyama S, Hornsby W, Bhukar R, Kheterpal S, Truong B, Selvaraj MS, Neale B, O’Donnell CJ, Peloso GM, Natarajan P. Bayesian multivariate genetic analysis improves translational insights. iScience 2023; 26:107854. [PMID: 37766997 PMCID: PMC10520309 DOI: 10.1016/j.isci.2023.107854] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 05/15/2023] [Accepted: 09/05/2023] [Indexed: 09/29/2023] Open
Abstract
While lipid traits are known essential mediators of cardiovascular disease, few approaches have taken advantage of their shared genetic effects. We apply a Bayesian multivariate size estimator, mash, to GWAS of four lipid traits in the Million Veterans Program (MVP) and provide posterior mean and local false sign rates for all effects. These estimates borrow information across traits to improve effect size accuracy. We show that controlling local false sign rates accurately and powerfully identifies replicable genetic associations and that multivariate control furthers the ability to explain complex diseases. Our application yields high concordance between independent datasets, more accurately prioritizes causal genes, and significantly improves polygenic prediction beyond state-of-the-art methods by up to 59% for lipid traits. The use of Bayesian multivariate genetic shrinkage has yet to be applied to human quantitative trait GWAS results, and we present a staged approach to prediction on a polygenic scale.
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Affiliation(s)
- Sarah M. Urbut
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA 02114, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA
| | - Satoshi Koyama
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA 02114, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA
- Department of Medicine Harvard Medical School, Boston, MA 02115, USA
| | - Whitney Hornsby
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA 02114, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA
- Department of Medicine Harvard Medical School, Boston, MA 02115, USA
| | - Rohan Bhukar
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA 02114, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA
- Department of Medicine Harvard Medical School, Boston, MA 02115, USA
| | - Sumeet Kheterpal
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA 02114, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA
| | - Buu Truong
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA 02114, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA
- Department of Medicine Harvard Medical School, Boston, MA 02115, USA
| | - Margaret S. Selvaraj
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA 02114, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA
- Department of Medicine Harvard Medical School, Boston, MA 02115, USA
| | - Benjamin Neale
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA
- Department of Medicine Harvard Medical School, Boston, MA 02115, USA
- Analytic Translational and Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Christopher J. O’Donnell
- Department of Medicine Harvard Medical School, Boston, MA 02115, USA
- VA Boston Department of Veterans Affairs, Boston, MA 02130, USA
| | - Gina M. Peloso
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02218, USA
| | - Pradeep Natarajan
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA 02114, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA
- Department of Medicine Harvard Medical School, Boston, MA 02115, USA
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25
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Hai Y, Zhao W, Meng Q, Liu L, Wen Y. Bayesian linear mixed model with multiple random effects for family-based genetic studies. Front Genet 2023; 14:1267704. [PMID: 37928242 PMCID: PMC10620972 DOI: 10.3389/fgene.2023.1267704] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 09/25/2023] [Indexed: 11/07/2023] Open
Abstract
Motivation: Family-based study design is one of the popular designs used in genetic research, and the whole-genome sequencing data obtained from family-based studies offer many unique features for risk prediction studies. They can not only provide a more comprehensive view of many complex diseases, but also utilize information in the design to further improve the prediction accuracy. While promising, existing analytical methods often ignore the information embedded in the study design and overlook the predictive effects of rare variants, leading to a prediction model with sub-optimal performance. Results: We proposed a Bayesian linear mixed model for the prediction analysis of sequencing data obtained from family-based studies. Our method can not only capture predictive effects from both common and rare variants, but also easily accommodate various disease model assumptions. It uses information embedded in the study design to form surrogates, where the predictive effects from unmeasured/unknown genetic and environmental risk factors can be modelled. Through extensive simulation studies and the analysis of sequencing data obtained from the Michigan State University Twin Registry study, we have demonstrated that the proposed method outperforms commonly adopted techniques. Availability: R package is available at https://github.com/yhai943/FBLMM.
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Affiliation(s)
- Yang Hai
- Department of Statistics, University of Auckland, Auckland, New Zealand
| | - Wenxuan Zhao
- Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, China
| | - Qingyu Meng
- Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, China
| | - Long Liu
- Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, China
| | - Yalu Wen
- Department of Statistics, University of Auckland, Auckland, New Zealand
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26
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Wang Y, Selvaraj MS, Li X, Li Z, Holdcraft JA, Arnett DK, Bis JC, Blangero J, Boerwinkle E, Bowden DW, Cade BE, Carlson JC, Carson AP, Chen YDI, Curran JE, de Vries PS, Dutcher SK, Ellinor PT, Floyd JS, Fornage M, Freedman BI, Gabriel S, Germer S, Gibbs RA, Guo X, He J, Heard-Costa N, Hildalgo B, Hou L, Irvin MR, Joehanes R, Kaplan RC, Kardia SL, Kelly TN, Kim R, Kooperberg C, Kral BG, Levy D, Li C, Liu C, Lloyd-Jone D, Loos RJ, Mahaney MC, Martin LW, Mathias RA, Minster RL, Mitchell BD, Montasser ME, Morrison AC, Murabito JM, Naseri T, O'Connell JR, Palmer ND, Preuss MH, Psaty BM, Raffield LM, Rao DC, Redline S, Reiner AP, Rich SS, Ruepena MS, Sheu WHH, Smith JA, Smith A, Tiwari HK, Tsai MY, Viaud-Martinez KA, Wang Z, Yanek LR, Zhao W, Rotter JI, Lin X, Natarajan P, Peloso GM. Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed whole-genome sequencing study. Am J Hum Genet 2023; 110:1704-1717. [PMID: 37802043 PMCID: PMC10577076 DOI: 10.1016/j.ajhg.2023.09.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 09/01/2023] [Accepted: 09/01/2023] [Indexed: 10/08/2023] Open
Abstract
Long non-coding RNAs (lncRNAs) are known to perform important regulatory functions in lipid metabolism. Large-scale whole-genome sequencing (WGS) studies and new statistical methods for variant set tests now provide an opportunity to assess more associations between rare variants in lncRNA genes and complex traits across the genome. In this study, we used high-coverage WGS from 66,329 participants of diverse ancestries with measurement of blood lipids and lipoproteins (LDL-C, HDL-C, TC, and TG) in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program to investigate the role of lncRNAs in lipid variability. We aggregated rare variants for 165,375 lncRNA genes based on their genomic locations and conducted rare-variant aggregate association tests using the STAAR (variant-set test for association using annotation information) framework. We performed STAAR conditional analysis adjusting for common variants in known lipid GWAS loci and rare-coding variants in nearby protein-coding genes. Our analyses revealed 83 rare lncRNA variant sets significantly associated with blood lipid levels, all of which were located in known lipid GWAS loci (in a ±500-kb window of a Global Lipids Genetics Consortium index variant). Notably, 61 out of 83 signals (73%) were conditionally independent of common regulatory variation and rare protein-coding variation at the same loci. We replicated 34 out of 61 (56%) conditionally independent associations using the independent UK Biobank WGS data. Our results expand the genetic architecture of blood lipids to rare variants in lncRNAs.
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Affiliation(s)
- Yuxuan Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Margaret Sunitha Selvaraj
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Xihao Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Zilin Li
- School of Mathematics and Statistics, Northeast Normal University, Changchun, Jilin, China; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jacob A Holdcraft
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Donna K Arnett
- Provost Office, University of South Carolina, Columbia, SC, USA; Department of Epidemiology and Biostatistics, University of South Carolina Arnold School of Public Health, Columbia, SC, USA
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Donald W Bowden
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Brian E Cade
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA; Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Jenna C Carlson
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA; Department of Biostatistics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - April P Carson
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Joanne E Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Susan K Dutcher
- The McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Patrick T Ellinor
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA; Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - James S Floyd
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA; Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Myriam Fornage
- Center for Human Genetics, University of Texas Health at Houston, Houston, TX, USA
| | - Barry I Freedman
- Department of Internal Medicine, Nephrology, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | | | | | - Richard A Gibbs
- Baylor College of Medicine Human Genome Sequencing Center, Houston, TX, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jiang He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA; Tulane University Translational Science Institute, New Orleans, LA, USA
| | - Nancy Heard-Costa
- Framingham Heart Study, Framingham, MA, USA; Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Bertha Hildalgo
- Department of Epidemiology, University of Alabama at Birmingham School of Public Health, Birmingham, AL, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - Marguerite R Irvin
- Department of Epidemiology, University of Alabama at Birmingham School of Public Health, Birmingham, AL, USA
| | - Roby Joehanes
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Robert C Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA; Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Sharon Lr Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Tanika N Kelly
- Department of Medicine, Division of Nephrology, University of Illinois Chicago, Chicago, IL, USA
| | - Ryan Kim
- Psomagen, Inc. (formerly Macrogen USA), Rockville, MD, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Brian G Kral
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Daniel Levy
- Framingham Heart Study, Framingham, MA, USA; Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Changwei Li
- Tulane University Translational Science Institute, New Orleans, LA, USA; Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Chunyu Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA; Framingham Heart Study, Framingham, MA, USA
| | - Don Lloyd-Jone
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - Ruth Jf Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA; NNF Center for Basic Metabolic Research, University of Copenhagen, Cophenhagen, Denmark
| | - Michael C Mahaney
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Lisa W Martin
- George Washington University School of Medicine and Health Sciences, Washington, DC, USA
| | - Rasika A Mathias
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ryan L Minster
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Braxton D Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - May E Montasser
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Joanne M Murabito
- Framingham Heart Study, Framingham, MA, USA; Department of Medicine, Boston Medical Center, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | - Take Naseri
- Naseri & Associates Public Health Consultancy Firm and Family Health Clinic, Apia, Samoa; International Health Institute, School of Public Health, Brown University, Providence, RI, USA
| | - Jeffrey R O'Connell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Nicholette D Palmer
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Michael H Preuss
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA; Department of Epidemiology, University of Washington, Seattle, WA, USA; Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Dabeeru C Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Susan Redline
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | | | - Wayne H-H Sheu
- Institute of Molecular and Genomic Medicine, National Health Research Institute (NHRI), Miaoli County, Taiwan
| | - Jennifer A Smith
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Albert Smith
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Hemant K Tiwari
- Department of Biostatistics, University of Alabama, Birmingham, AL, USA
| | - Michael Y Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | | | - Zhe Wang
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Lisa R Yanek
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Wei Zhao
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Xihong Lin
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Statistics, Harvard University, Cambridge, MA, USA
| | - Pradeep Natarajan
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Gina M Peloso
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
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27
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Gouni-Berthold I, Schwarz J, Berthold HK. Updates in Drug Treatment of Severe Hypertriglyceridemia. Curr Atheroscler Rep 2023; 25:701-709. [PMID: 37642858 PMCID: PMC10564803 DOI: 10.1007/s11883-023-01140-z] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/15/2023] [Indexed: 08/31/2023]
Abstract
PURPOSE OF REVIEW To provide an insight into the new pharmacological options for the treatment of severe hypertriglyceridemia (sHTG). RECENT FINDINGS sHTG is difficult to treat. The majority of the traditional pharmacological agents available have limited success in both robustly decreasing triglyceride levels and/or in reducing the incidence of acute pancreatitis (AP), the most severe complication of sHTG. Therapeutic options with novel mechanisms of action have been developed, such as antisense oligonucleotides (ASO) and small interfering RNA (siRNA) targeting APOC3 and ANGPTL3. The review discusses also 2 abandoned drugs for sHTG treatment, evinacumab and vupanorsen. The ASO targeting APOC3, volanesorsen, is approved for use in patients with familial chylomicronemia syndrome (FCS) in Europe. Olezarsen, an N-acetylgalactosamine (GalNAc)-conjugated ASO with the same target, seems to have a better safety and efficacy profile. siRNA targeting APOC3 and ANGPTL3, namely ARO-APOC3 and ARO-ANG3, are also promising for the treatment of sHTG. However, the ultimate clinical goal of any sHTG treatment, the decrease in the risk of AP, has not been definitively achieved till now by any pharmacotherapy, either approved or in development.
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Affiliation(s)
- Ioanna Gouni-Berthold
- Center for Endocrinology, Diabetes and Preventive Medicine, University of Cologne, Faculty of Medicine and University Hospital, Kerpener Str. 6, 50937 Cologne, Germany
| | - Jonas Schwarz
- Center for Endocrinology, Diabetes and Preventive Medicine, University of Cologne, Faculty of Medicine and University Hospital, Kerpener Str. 6, 50937 Cologne, Germany
| | - Heiner K. Berthold
- Department of Internal Medicine and Geriatrics, Bethel Clinic (EvKB) and Medical School EWL, University of Bielefeld, Bielefeld, Germany
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28
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Saghafi S, Chamani E, Salmani F, Fadaei R, Shafiei E, Moradi N, Tavakoli T. Genetic predisposition to nonalcoholic fatty liver disease: insights from ANGPTL8 gene variants in Iranian adults. Lipids Health Dis 2023; 22:147. [PMID: 37679750 PMCID: PMC10483745 DOI: 10.1186/s12944-023-01905-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 08/15/2023] [Indexed: 09/09/2023] Open
Abstract
Nonalcoholic fatty liver disease (NAFLD) is a prevalent chronic liver disease with a global prevalence, and modulation of ANGPTL8 expression has emerged as a promising predictor of NAFLD susceptibility. This research was conducted to scrutinize ANGPTL8 protein expression in NAFLD patients and elucidate the interplay between ANGPTL8 gene polymorphisms and their lipid profiles, thus shedding new light on the pathophysiology of this complex disease. The study comprised 423 unrelated participants, including 222 healthy controls and 201 individuals with NAFLD, screened using FibroScan/ultrasonography and laboratory tests. The main goal focused on the genotype and allele frequency distribution in the ANGPTL8 gene, specifically analyzing two genetic variations: rs737337 (T/C) and rs2278426 (C/T). The participants diagnosed with NAFLD were slightly younger (P ≥ 0.05) and had a higher body mass index (BMI) than the individuals in the control group. Notably, there was a significant difference in the occurrence of the rs737337 polymorphism between the NAFLD and control groups, with a lower frequency observed in the NAFLD group. Our results indicated that individuals with the TC + CC genotype and C allele of rs737337 (T/C) had a decreased risk of higher levels of ALT and AST. Conversely, those with the CT, CT + TT genotype, and T allele of rs2278426 (C/T) exhibited an increased risk of higher levels of ALT and AST. The results imply that the rs2278426 (C/T) variant of the ANGPTL8 gene is more strongly linked to an increased risk of NAFLD compared to the rs737337 polymorphism. However, additional research is needed to understand the specific molecular mechanisms responsible for the upregulation of ANGPTL8 in individuals with NAFLD.
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Affiliation(s)
- Samira Saghafi
- Student Research Committee, Birjand University of Medical Sciences, Birjand, Iran
| | - Elham Chamani
- Department of Clinical Biochemistry, Faculty of Medicine, Birjand University of Medical Sciences, Birjand, Iran
| | - Fatemeh Salmani
- Department of Epidemiology and Biostatistics, Social Determinants of Health Research Center, Faculty of Health, Birjand University of Medical Sciences, Birjand, Iran
| | - Reza Fadaei
- Sleep Disorders Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Efat Shafiei
- Student Research Committee, Kurdistan University of Medical Sciences, Sanandaj, Iran
| | - Nariman Moradi
- Cellular and Molecular Research Center, Research Institute for Health Development, Kurdistan University of Medical Sciences, Sanandaj, Iran.
| | - Tahmine Tavakoli
- Student Research Committee, Birjand University of Medical Sciences, Birjand, Iran.
- Cardiovascular Research Center, Birjand University of Medical Sciences, Birjand, Iran.
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29
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McCaw ZR, O'Dushlaine C, Somineni H, Bereket M, Klein C, Karaletsos T, Casale FP, Koller D, Soare TW. An allelic-series rare-variant association test for candidate-gene discovery. Am J Hum Genet 2023; 110:1330-1342. [PMID: 37494930 PMCID: PMC10432147 DOI: 10.1016/j.ajhg.2023.07.001] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 06/30/2023] [Accepted: 07/01/2023] [Indexed: 07/28/2023] Open
Abstract
Allelic series are of candidate therapeutic interest because of the existence of a dose-response relationship between the functionality of a gene and the degree or severity of a phenotype. We define an allelic series as a collection of variants in which increasingly deleterious mutations lead to increasingly large phenotypic effects, and we have developed a gene-based rare-variant association test specifically targeted to identifying genes containing allelic series. Building on the well-known burden test and sequence kernel association test (SKAT), we specify a variety of association models covering different genetic architectures and integrate these into a Coding-Variant Allelic-Series Test (COAST). Through extensive simulations, we confirm that COAST maintains the type I error and improves the power when the pattern of coding-variant effect sizes increases monotonically with mutational severity. We applied COAST to identify allelic-series genes for four circulating-lipid traits and five cell-count traits among 145,735 subjects with available whole-exome sequencing data from the UK Biobank. Compared with optimal SKAT (SKAT-O), COAST identified 29% more Bonferroni-significant associations with circulating-lipid traits, on average, and 82% more with cell-count traits. All of the gene-trait associations identified by COAST have corroborating evidence either from rare-variant associations in the full cohort (Genebass, n = 400,000) or from common-variant associations in the GWAS Catalog. In addition to detecting many gene-trait associations present in Genebass by using only a fraction (36.9%) of the sample, COAST detects associations, such as that between ANGPTL4 and triglycerides, that are absent from Genebass but that have clear common-variant support.
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Affiliation(s)
| | | | | | | | | | | | - Francesco Paolo Casale
- Institute of AI for Health, Helmholtz Munich, Neuherberg, Germany; Helmholtz Pioneer Campus, Helmholtz Munich, Neuherberg, Germany; School of Computation, Information and Technology, Technical University of Munich, Munich, Germany
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30
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He S, McArdle PF, Ryan KA, Daue M, Xu H, Barry KH, Magder LS, Shuldiner AR, Pollin TI, Mitchell BD. Association of parity with body mass index and cardiometabolic risk in high-parous women. Menopause 2023; 30:703-708. [PMID: 37159869 PMCID: PMC10313795 DOI: 10.1097/gme.0000000000002194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
OBJECTIVE Postpregnancy weight retention contributes to obesity, but the long-term effect of parity on body mass index (BMI) and other cardiometabolic risk factors is unclear. We aimed to evaluate the relationship between parity and BMI among highly parous Amish women, both before and after menopause, and to evaluate the associations of parity with glucose, blood pressure, and lipids. METHODS We conducted a cross-sectional study among 3,141 Amish women 18 years or older from Lancaster County, PA, who participated in our community-based Amish Research Program between 2003 and 2020. We evaluated the association between parity and BMI across different age groups, both before and after the menopausal transition. We further assessed associations between parity and cardiometabolic risk factors among the 1,128 postmenopausal women. Finally, we evaluated the association of change in parity with change in BMI in 561 women followed longitudinally. RESULTS Approximately 62% of women in this sample (mean age, 45.2 y) reported having four or more children, and 36% reported having seven or more. A one-child increase in parity was associated with increased BMI in both premenopausal women (estimate [95% confidence interval], 0.4 kg/m 2 [0.2-0.5]) and to a lesser degree in postmenopausal women (0.2 kg/m 2 [0.02-0.3], Pint = 0.02), suggesting that the impact of parity on BMI decreases over time. Parity was not associated with glucose, blood pressure, total cholesterol, low-density lipoprotein, or triglycerides ( Padj > 0.05). CONCLUSIONS Higher parity was associated with increased BMI in both premenopausal and postmenopausal women, but more so in younger/premenopausal women. Parity was not associated with other indices of cardiometabolic risk.
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Affiliation(s)
- Shisi He
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine and Program for Personalized Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Patrick F. McArdle
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine and Program for Personalized Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Kathleen A. Ryan
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine and Program for Personalized Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD
| | - Melanie Daue
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine and Program for Personalized Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD
| | - Huichun Xu
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine and Program for Personalized Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD
| | - Kathryn Hughes Barry
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, USA
- Program in Oncology, University of Maryland Marlene and Stewart Greenebaum Comprehensive Cancer Center, Baltimore, MD
| | - Laurence S. Magder
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Alan R. Shuldiner
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine and Program for Personalized Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD
| | - Toni I. Pollin
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine and Program for Personalized Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Braxton D. Mitchell
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine and Program for Personalized Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD
- Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore, MD, USA
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, USA
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31
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Wang Y, Selvaraj MS, Li X, Li Z, Holdcraft JA, Arnett DK, Bis JC, Blangero J, Boerwinkle E, Bowden DW, Cade BE, Carlson JC, Carson AP, Chen YDI, Curran JE, de Vries PS, Dutcher SK, Ellinor PT, Floyd JS, Fornage M, Freedman BI, Gabriel S, Germer S, Gibbs RA, Guo X, He J, Heard-Costa N, Hildalgo B, Hou L, Irvin MR, Joehanes R, Kaplan RC, Kardia SLR, Kelly TN, Kim R, Kooperberg C, Kral BG, Levy D, Li C, Liu C, Lloyd-Jone D, Loos RJF, Mahaney MC, Martin LW, Mathias RA, Minster RL, Mitchell BD, Montasser ME, Morrison AC, Murabito JM, Naseri T, O’Connell JR, Palmer ND, Preuss MH, Psaty BM, Raffield LM, Rao DC, Redline S, Reiner AP, Rich SS, Ruepena MS, Sheu WHH, Smith JA, Smith A, Tiwari HK, Tsai MY, Viaud-Martinez KA, Wang Z, Yanek LR, Zhao W, Rotter JI, Lin X, Natarajan P, Peloso GM. Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed Whole Genome Sequencing Study. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.28.23291966. [PMID: 37425772 PMCID: PMC10327287 DOI: 10.1101/2023.06.28.23291966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Long non-coding RNAs (lncRNAs) are known to perform important regulatory functions. Large-scale whole genome sequencing (WGS) studies and new statistical methods for variant set tests now provide an opportunity to assess the associations between rare variants in lncRNA genes and complex traits across the genome. In this study, we used high-coverage WGS from 66,329 participants of diverse ancestries with blood lipid levels (LDL-C, HDL-C, TC, and TG) in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program to investigate the role of lncRNAs in lipid variability. We aggregated rare variants for 165,375 lncRNA genes based on their genomic locations and conducted rare variant aggregate association tests using the STAAR (variant-Set Test for Association using Annotation infoRmation) framework. We performed STAAR conditional analysis adjusting for common variants in known lipid GWAS loci and rare coding variants in nearby protein coding genes. Our analyses revealed 83 rare lncRNA variant sets significantly associated with blood lipid levels, all of which were located in known lipid GWAS loci (in a ±500 kb window of a Global Lipids Genetics Consortium index variant). Notably, 61 out of 83 signals (73%) were conditionally independent of common regulatory variations and rare protein coding variations at the same loci. We replicated 34 out of 61 (56%) conditionally independent associations using the independent UK Biobank WGS data. Our results expand the genetic architecture of blood lipids to rare variants in lncRNA, implicating new therapeutic opportunities.
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Affiliation(s)
- Yuxuan Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Margaret Sunitha Selvaraj
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Xihao Li
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Zilin Li
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, USA
- Center for Computational Biology & Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Jacob A. Holdcraft
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Donna K. Arnett
- Provost Office, University of South Carolina, Columbia, SC, USA
- Department of Epidemiology and Biostatistics, University of South Carolina Arnold School of Public Health, Columbia, SC, USA
| | - Joshua C. Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Donald W. Bowden
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Brian E. Cade
- Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Jenna C. Carlson
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Biostatistics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - April P. Carson
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Joanne E. Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Paul S. de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Susan K. Dutcher
- The McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Patrick T. Ellinor
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - James S. Floyd
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Myriam Fornage
- Center for Human Genetics, University of Texas Health at Houston, Houston, TX, USA
| | - Barry I. Freedman
- Department of Internal Medicine, Nephrology, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | | | | | - Richard A. Gibbs
- Baylor College of Medicine Human Genome Sequencing Center, Houston, TX, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jiang He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
- Tulane University Translational Science Institute, New Orleans, LA, USA
| | - Nancy Heard-Costa
- Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Bertha Hildalgo
- Department of Epidemiology, University of Alabama at Birmingham School of Public Health, Birmingham, AL, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - Marguerite R. Irvin
- Department of Epidemiology, University of Alabama at Birmingham School of Public Health, Birmingham, AL, USA
| | - Roby Joehanes
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Robert C. Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Sharon LR. Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Tanika N. Kelly
- Department of Medicine, Division of Nephrology, University of Illinois Chicago, Chicago, IL, USA
| | - Ryan Kim
- Psomagen, Inc. (formerly Macrogen USA), Rockville, MD, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Brian G. Kral
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Daniel Levy
- Framingham Heart Study, Framingham, MA, USA
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Changwei Li
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
- Tulane University Translational Science Institute, New Orleans, LA, USA
| | - Chunyu Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Don Lloyd-Jone
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - Ruth JF. Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- NNF Center for Basic Metabolic Research, University of Copenhagen, Cophenhagen, Denmark
| | - Michael C. Mahaney
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Lisa W. Martin
- George Washington University School of Medicine and Health Sciences, Washington, DC, USA
| | - Rasika A. Mathias
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ryan L. Minster
- Department of Human Genetics and Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Braxton D. Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - May E. Montasser
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Alanna C. Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Joanne M. Murabito
- Framingham Heart Study, Framingham, MA, USA
- Department of Medicine, Boston Medical Center, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | | | - Jeffrey R. O’Connell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Nicholette D. Palmer
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Michael H. Preuss
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Laura M. Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Dabeeru C. Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Susan Redline
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | | | | | - Jennifer A. Smith
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Albert Smith
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Hemant K. Tiwari
- Department of Biostatistics, University of Alabama, Birmingham, AL, USA
| | - Michael Y. Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | | | - Zhe Wang
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Lisa R. Yanek
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Wei Zhao
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | | | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Xihong Lin
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Statistics, Harvard University, Cambridge, MA, USA
| | - Pradeep Natarajan
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Gina M. Peloso
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
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Jääskeläinen I, Petäistö T, Mirzarazi Dahagi E, Mahmoodi M, Pihlajaniemi T, Kaartinen MT, Heljasvaara R. Collagens Regulating Adipose Tissue Formation and Functions. Biomedicines 2023; 11:biomedicines11051412. [PMID: 37239083 DOI: 10.3390/biomedicines11051412] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 04/28/2023] [Accepted: 05/03/2023] [Indexed: 05/28/2023] Open
Abstract
The globally increasing prevalence of obesity is associated with the development of metabolic diseases such as type 2 diabetes, dyslipidemia, and fatty liver. Excess adipose tissue (AT) often leads to its malfunction and to a systemic metabolic dysfunction because, in addition to storing lipids, AT is an active endocrine system. Adipocytes are embedded in a unique extracellular matrix (ECM), which provides structural support to the cells as well as participating in the regulation of their functions, such as proliferation and differentiation. Adipocytes have a thin pericellular layer of a specialized ECM, referred to as the basement membrane (BM), which is an important functional unit that lies between cells and tissue stroma. Collagens form a major group of proteins in the ECM, and some of them, especially the BM-associated collagens, support AT functions and participate in the regulation of adipocyte differentiation. In pathological conditions such as obesity, AT often proceeds to fibrosis, characterized by the accumulation of large collagen bundles, which disturbs the natural functions of the AT. In this review, we summarize the current knowledge on the vertebrate collagens that are important for AT development and function and include basic information on some other important ECM components, principally fibronectin, of the AT. We also briefly discuss the function of AT collagens in certain metabolic diseases in which they have been shown to play central roles.
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Affiliation(s)
- Iida Jääskeläinen
- ECM-Hypoxia Research Unit, Faculty of Biochemistry and Molecular Medicine, University of Oulu, 90014 Oulu, Finland
| | - Tiina Petäistö
- ECM-Hypoxia Research Unit, Faculty of Biochemistry and Molecular Medicine, University of Oulu, 90014 Oulu, Finland
| | - Elahe Mirzarazi Dahagi
- Department of Anatomy and Cell Biology, Faculty of Medicine and Health Sciences, McGill University, Montréal, QC H3A 0C7, Canada
| | - Mahdokht Mahmoodi
- Faculty of Dental Medicine and Oral Health Sciences, McGill University, Montréal, QC H3A 0C7, Canada
| | - Taina Pihlajaniemi
- ECM-Hypoxia Research Unit, Faculty of Biochemistry and Molecular Medicine, University of Oulu, 90014 Oulu, Finland
| | - Mari T Kaartinen
- Department of Anatomy and Cell Biology, Faculty of Medicine and Health Sciences, McGill University, Montréal, QC H3A 0C7, Canada
- Faculty of Dental Medicine and Oral Health Sciences, McGill University, Montréal, QC H3A 0C7, Canada
- Division of Experimental Medicine, Faculty of Medicine and Health Sciences, McGill University, Montréal, QC H3A 0C7, Canada
| | - Ritva Heljasvaara
- ECM-Hypoxia Research Unit, Faculty of Biochemistry and Molecular Medicine, University of Oulu, 90014 Oulu, Finland
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Gelemanović A, Ćatipović Ardalić T, Pribisalić A, Hayward C, Kolčić I, Polašek O. Genome-Wide Meta-Analysis Identifies Multiple Novel Rare Variants to Predict Common Human Infectious Diseases Risk. Int J Mol Sci 2023; 24:7006. [PMID: 37108169 PMCID: PMC10138356 DOI: 10.3390/ijms24087006] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 04/02/2023] [Accepted: 04/05/2023] [Indexed: 04/29/2023] Open
Abstract
Infectious diseases still threaten global human health, and host genetic factors have been indicated as determining risk factors for observed variations in disease susceptibility, severity, and outcome. We performed a genome-wide meta-analysis on 4624 subjects from the 10,001 Dalmatians cohort, with 14 infection-related traits. Despite a rather small number of cases in some instances, we detected 29 infection-related genetic associations, mostly belonging to rare variants. Notably, the list included the genes CD28, INPP5D, ITPKB, MACROD2, and RSF1, all of which have known roles in the immune response. Expanding our knowledge on rare variants could contribute to the development of genetic panels that could assist in predicting an individual's life-long susceptibility to major infectious diseases. In addition, longitudinal biobanks are an interesting source of information for identifying the host genetic variants involved in infectious disease susceptibility and severity. Since infectious diseases continue to act as a selective pressure on our genomes, there is a constant need for a large consortium of biobanks with access to genetic and environmental data to further elucidate the complex mechanisms behind host-pathogen interactions and infectious disease susceptibility.
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Affiliation(s)
- Andrea Gelemanović
- Department of Public Health, University of Split School of Medicine, 21000 Split, Croatia
| | | | - Ajka Pribisalić
- Department of Public Health, University of Split School of Medicine, 21000 Split, Croatia
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh EH4 2XU, UK
| | - Ivana Kolčić
- Department of Public Health, University of Split School of Medicine, 21000 Split, Croatia
- Department of General Courses, Algebra University College, 10000 Zagreb, Croatia
| | - Ozren Polašek
- Department of Public Health, University of Split School of Medicine, 21000 Split, Croatia
- Department of General Courses, Algebra University College, 10000 Zagreb, Croatia
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Wang N, Yu B, Jun G, Qi Q, Durazo-Arvizu RA, Lindstrom S, Morrison AC, Kaplan RC, Boerwinkle E, Chen H. StocSum: stochastic summary statistics for whole genome sequencing studies. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.06.535886. [PMID: 37066281 PMCID: PMC10104122 DOI: 10.1101/2023.04.06.535886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Genomic summary statistics, usually defined as single-variant test results from genome-wide association studies, have been widely used to advance the genetics field in a wide range of applications. Applications that involve multiple genetic variants also require their correlations or linkage disequilibrium (LD) information, often obtained from an external reference panel. In practice, it is usually difficult to find suitable external reference panels that represent the LD structure for underrepresented and admixed populations, or rare genetic variants from whole genome sequencing (WGS) studies, limiting the scope of applications for genomic summary statistics. Here we introduce StocSum, a novel reference-panel-free statistical framework for generating, managing, and analyzing stochastic summary statistics using random vectors. We develop various downstream applications using StocSum including single-variant tests, conditional association tests, gene-environment interaction tests, variant set tests, as well as meta-analysis and LD score regression tools. We demonstrate the accuracy and computational efficiency of StocSum using two cohorts from the Trans-Omics for Precision Medicine Program. StocSum will facilitate sharing and utilization of genomic summary statistics from WGS studies, especially for underrepresented and admixed populations.
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Affiliation(s)
- Nannan Wang
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Bing Yu
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Goo Jun
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Qibin Qi
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Ramon A. Durazo-Arvizu
- The Saban Research Institute, Children’s Hospital Los Angeles, Los Angeles, California
- Department of Pediatrics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Sara Lindstrom
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Epidemiology, School of Public Health, University of Washington, 3980 15th Ave NE, Seattle, WA, USA
| | - Alanna C. Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Robert C. Kaplan
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Han Chen
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA
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35
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Update of a Genetic Risk Score Predictive of the Plasma Triglyceride Response to an Omega-3 Fatty Acid Supplementation in the FAS Study. Nutrients 2023; 15:nu15051156. [PMID: 36904157 PMCID: PMC10005670 DOI: 10.3390/nu15051156] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Revised: 02/17/2023] [Accepted: 02/22/2023] [Indexed: 03/03/2023] Open
Abstract
A genetic risk score (GRS) predictive of the plasma triglyceride (TG) response to an omega-3 fatty acid (n-3 FA) supplementation has been previously developed in the Fatty Acid Sensor (FAS) Study. Recently, novel single nucleotide polymorphisms (SNPs) interacting with a fish oil supplementation and associated with plasma lipid levels have been identified in the UK Biobank. The aim of this study was to verify whether the addition of SNPs identified in the UK Biobank to the GRS built in the FAS Study improves its capacity to predict the plasma TG response to an n-3 FA supplementation. SNPs interacting with fish oil supplementation in the modulation of plasma lipid levels in the UK Biobank and associated with plasma TG levels have been genotyped in participants of the FAS Study (n = 141). Participants have been supplemented with 5 g fish oil/day for six weeks. Plasma TG concentrations were measured before and after the supplementation. Based on the initial GRS of 31 SNPs (GRS31), we computed three new GRSs by adding new SNPs identified in the UK Biobank: GRS32 (rs55707100), GRS38 (seven new SNPs specifically associated with plasma TG levels), and GRS46 (all 15 new SNPs associated with plasma lipid levels). The initial GRS31 explained 50.1% of the variance in plasma TG levels during the intervention, whereas GRS32, GRS38, and GRS46 explained 49.1%, 45.9%, and 45%, respectively. A significant impact on the probability of being classified as a responder or a nonresponder was found for each of the GRSs analyzed, but none of them outperformed the predictive capacity of GRS31 in any of the metrics analyzed, i.e., accuracy, area under the response operating curve (AUC-ROC), sensitivity, specificity and McFadden's pseudo R2. The addition of SNPs identified in the UK Biobank to the initial GRS31 did not significantly improve its capacity to predict the plasma TG response to an n-3 FA supplementation. Thus, GRS31 still remains the most precise tool so far by which to discriminate the individual responsiveness to n-3 FAs. Further studies are needed in the field to increase our knowledge of factors underlying the heterogeneity observed in the metabolic response to an n-3 FA supplementation.
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Tsao CW, Aday AW, Almarzooq ZI, Anderson CAM, Arora P, Avery CL, Baker-Smith CM, Beaton AZ, Boehme AK, Buxton AE, Commodore-Mensah Y, Elkind MSV, Evenson KR, Eze-Nliam C, Fugar S, Generoso G, Heard DG, Hiremath S, Ho JE, Kalani R, Kazi DS, Ko D, Levine DA, Liu J, Ma J, Magnani JW, Michos ED, Mussolino ME, Navaneethan SD, Parikh NI, Poudel R, Rezk-Hanna M, Roth GA, Shah NS, St-Onge MP, Thacker EL, Virani SS, Voeks JH, Wang NY, Wong ND, Wong SS, Yaffe K, Martin SS. Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association. Circulation 2023; 147:e93-e621. [PMID: 36695182 DOI: 10.1161/cir.0000000000001123] [Citation(s) in RCA: 2246] [Impact Index Per Article: 1123.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
BACKGROUND The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains. RESULTS Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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Abstract
Atherosclerotic cardiovascular disease is the leading cause of death globally. Despite its important risk of premature atherosclerosis and cardiovascular disease, familial hypercholesterolemia (FH) is still largely underdiagnosed worldwide. It is one of the most frequently inherited diseases due to mutations, for autosomal dominant forms, in either of the LDLR, APOB, and PCSK9 genes or possibly a few mutations in the APOE gene and, for the rare autosomal forms, in the LDLRAP1 gene. The discovery of the genes implicated in the disease has largely helped to improve the diagnosis and treatment of FH from the LDLR by Brown and Goldstein, as well as the introduction of statins, to PCSK9 discovery in FH by Abifadel et al., and the very rapid availability of PCSK9 inhibitors. In the last two decades, major progress has been made in clinical and genetic diagnostic tools and the therapeutic arsenal against FH. Improving prevention, diagnosis, and treatment and making them more accessible to all patients will help reduce the lifelong burden of the disease.
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Affiliation(s)
- Marianne Abifadel
- UMR1148, Inserm, Hôpital Bichat-Claude Bernard, 46 rue Henri Huchard, F-75018 Paris, France.,Laboratory of Biochemistry and Molecular Therapeutics (LBTM), Faculty of Pharmacy, Pôle Technologie-Santé, Saint Joseph University of Beirut, Beirut, Lebanon
| | - Catherine Boileau
- UMR1148, Inserm, Hôpital Bichat-Claude Bernard, 46 rue Henri Huchard, F-75018 Paris, France.,Département de Génétique, AP-HP, Hôpital Bichat-Claude Bernard, Paris, France
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38
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Landfors F, Chorell E, Kersten S. Genetic Mimicry Analysis Reveals the Specific Lipases Targeted by the ANGPTL3-ANGPTL8 Complex and ANGPTL4. J Lipid Res 2023; 64:100313. [PMID: 36372100 PMCID: PMC9852701 DOI: 10.1016/j.jlr.2022.100313] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 10/14/2022] [Accepted: 11/06/2022] [Indexed: 11/13/2022] Open
Abstract
Angiopoietin-like proteins, ANGPTL3, ANGPTL4, and ANGPTL8, are involved in regulating plasma lipids. In vitro and animal-based studies point to LPL and endothelial lipase (EL, LIPG) as key targets of ANGPTLs. To examine the ANGPTL mechanisms for plasma lipid modulation in humans, we pursued a genetic mimicry analysis of enhancing or suppressing variants in the LPL, LIPG, lipase C hepatic type (LIPC), ANGPTL3, ANGPTL4, and ANGPTL8 genes using data on 248 metabolic parameters derived from over 110,000 nonfasted individuals in the UK Biobank and validated in over 13,000 overnight fasted individuals from 11 other European populations. ANGPTL4 suppression was highly concordant with LPL enhancement but not HL or EL, suggesting ANGPTL4 impacts plasma metabolic parameters exclusively via LPL. The LPL-independent effects of ANGPTL3 suppression on plasma metabolic parameters showed a striking inverse resemblance with EL suppression, suggesting ANGPTL3 not only targets LPL but also targets EL. Investigation of the impact of the ANGPTL3-ANGPTL8 complex on plasma metabolite traits via the ANGPTL8 R59W substitution as an instrumental variable showed a much higher concordance between R59W and EL activity than between R59W and LPL activity, suggesting the R59W substitution more strongly affects EL inhibition than LPL inhibition. Meanwhile, when using a rare and deleterious protein-truncating ANGPTL8 variant as an instrumental variable, the ANGPTL3-ANGPTL8 complex was very LPL specific. In conclusion, our analysis provides strong human genetic evidence that the ANGPTL3-ANGPTL8 complex regulates plasma metabolic parameters, which is achieved by impacting LPL and EL. By contrast, ANGPTL4 influences plasma metabolic parameters exclusively via LPL.
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Affiliation(s)
- Fredrik Landfors
- Department of Public Health and Clinical Medicine, Section of Medicine, Umeå University, Umeå, Sweden.
| | - Elin Chorell
- Department of Public Health and Clinical Medicine, Section of Medicine, Umeå University, Umeå, Sweden
| | - Sander Kersten
- Nutrition, Metabolism and Genomics group, Division of Human Nutrition and Health, Wageningen University, Wageningen, the Netherlands
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Ouidir M, Chatterjee S, Wu J, Tekola-Ayele F. Genomic study of maternal lipid traits in early pregnancy concurs with four known adult lipid loci. J Clin Lipidol 2023; 17:168-180. [PMID: 36443208 PMCID: PMC9974591 DOI: 10.1016/j.jacl.2022.10.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Revised: 10/10/2022] [Accepted: 10/18/2022] [Indexed: 11/19/2022]
Abstract
BACKGROUND Blood lipids during pregnancy are associated with cardiovascular diseases and adverse pregnancy outcomes. Genome-wide association studies (GWAS) in predominantly male European ancestry populations have identified genetic loci associated with blood lipid levels. However, the genetic architecture of blood lipids in pregnant women remains poorly understood. OBJECTIVE Our goal was to identify genetic loci associated with blood lipid levels among pregnant women from diverse ancestry groups and to evaluate whether previously known lipid loci in predominantly European adults are transferable to pregnant women. METHODS The trans-ancestry GWAS were conducted on serum levels of total cholesterol, high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL) and triglycerides during first trimester among pregnant women from four population groups (608 European-, 623 African-, 552 Hispanic- and 235 East Asian-Americans) recruited in the NICHD Fetal Growth Studies cohort. The four GWAS summary statistics were combined using trans-ancestry meta-analysis approaches that account for genetic heterogeneity among populations. RESULTS Loci in CELSR2 and APOE were genome-wide significantly associated (p-value < 5×10-8) with total cholesterol and LDL levels. Loci near CETP and ABCA1 approached genome-wide significant association with HDL (p-value = 2.97×10-7 and 9.71×10-8, respectively). Less than 20% of previously known adult lipid loci were transferable to pregnant women. CONCLUSION This trans-ancestry GWAS meta-analysis in pregnant women identified associations that concur with four known adult lipid loci. Limited replication of known lipid-loci from predominantly European study populations to pregnant women underlines the need for genomic studies of lipids in ancestrally diverse pregnant women. CLINICAL TRIAL REGISTRATION ClinicalTrials.gov, NCT00912132.
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Affiliation(s)
- Marion Ouidir
- Epidemiology Branch, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Suvo Chatterjee
- Epidemiology Branch, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Jing Wu
- Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Fasil Tekola-Ayele
- Epidemiology Branch, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA.
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Kanoni S, Graham SE, Wang Y, Surakka I, Ramdas S, Zhu X, Clarke SL, Bhatti KF, Vedantam S, Winkler TW, Locke AE, Marouli E, Zajac GJM, Wu KHH, Ntalla I, Hui Q, Klarin D, Hilliard AT, Wang Z, Xue C, Thorleifsson G, Helgadottir A, Gudbjartsson DF, Holm H, Olafsson I, Hwang MY, Han S, Akiyama M, Sakaue S, Terao C, Kanai M, Zhou W, Brumpton BM, Rasheed H, Havulinna AS, Veturi Y, Pacheco JA, Rosenthal EA, Lingren T, Feng Q, Kullo IJ, Narita A, Takayama J, Martin HC, Hunt KA, Trivedi B, Haessler J, Giulianini F, Bradford Y, Miller JE, Campbell A, Lin K, Millwood IY, Rasheed A, Hindy G, Faul JD, Zhao W, Weir DR, Turman C, Huang H, Graff M, Choudhury A, Sengupta D, Mahajan A, Brown MR, Zhang W, Yu K, Schmidt EM, Pandit A, Gustafsson S, Yin X, Luan J, Zhao JH, Matsuda F, Jang HM, Yoon K, Medina-Gomez C, Pitsillides A, Hottenga JJ, Wood AR, Ji Y, Gao Z, Haworth S, Yousri NA, Mitchell RE, Chai JF, Aadahl M, Bjerregaard AA, Yao J, Manichaikul A, Hwu CM, Hung YJ, Warren HR, Ramirez J, Bork-Jensen J, Kårhus LL, Goel A, Sabater-Lleal M, Noordam R, Mauro P, et alKanoni S, Graham SE, Wang Y, Surakka I, Ramdas S, Zhu X, Clarke SL, Bhatti KF, Vedantam S, Winkler TW, Locke AE, Marouli E, Zajac GJM, Wu KHH, Ntalla I, Hui Q, Klarin D, Hilliard AT, Wang Z, Xue C, Thorleifsson G, Helgadottir A, Gudbjartsson DF, Holm H, Olafsson I, Hwang MY, Han S, Akiyama M, Sakaue S, Terao C, Kanai M, Zhou W, Brumpton BM, Rasheed H, Havulinna AS, Veturi Y, Pacheco JA, Rosenthal EA, Lingren T, Feng Q, Kullo IJ, Narita A, Takayama J, Martin HC, Hunt KA, Trivedi B, Haessler J, Giulianini F, Bradford Y, Miller JE, Campbell A, Lin K, Millwood IY, Rasheed A, Hindy G, Faul JD, Zhao W, Weir DR, Turman C, Huang H, Graff M, Choudhury A, Sengupta D, Mahajan A, Brown MR, Zhang W, Yu K, Schmidt EM, Pandit A, Gustafsson S, Yin X, Luan J, Zhao JH, Matsuda F, Jang HM, Yoon K, Medina-Gomez C, Pitsillides A, Hottenga JJ, Wood AR, Ji Y, Gao Z, Haworth S, Yousri NA, Mitchell RE, Chai JF, Aadahl M, Bjerregaard AA, Yao J, Manichaikul A, Hwu CM, Hung YJ, Warren HR, Ramirez J, Bork-Jensen J, Kårhus LL, Goel A, Sabater-Lleal M, Noordam R, Mauro P, Matteo F, McDaid AF, Marques-Vidal P, Wielscher M, Trompet S, Sattar N, Møllehave LT, Munz M, Zeng L, Huang J, Yang B, Poveda A, Kurbasic A, Lamina C, Forer L, Scholz M, Galesloot TE, Bradfield JP, Ruotsalainen SE, Daw EW, Zmuda JM, Mitchell JS, Fuchsberger C, Christensen H, Brody JA, Vazquez-Moreno M, Feitosa MF, Wojczynski MK, Wang Z, Preuss MH, Mangino M, Christofidou P, Verweij N, Benjamins JW, Engmann J, Tsao NL, Verma A, Slieker RC, Lo KS, Zilhao NR, Le P, Kleber ME, Delgado GE, Huo S, Ikeda DD, Iha H, Yang J, Liu J, Demirkan A, Leonard HL, Marten J, Frank M, Schmidt B, Smyth LJ, Cañadas-Garre M, Wang C, Nakatochi M, Wong A, Hutri-Kähönen N, Sim X, Xia R, Huerta-Chagoya A, Fernandez-Lopez JC, Lyssenko V, Nongmaithem SS, Bayyana S, Stringham HM, Irvin MR, Oldmeadow C, Kim HN, Ryu S, Timmers PRHJ, Arbeeva L, Dorajoo R, Lange LA, Prasad G, Lorés-Motta L, Pauper M, Long J, Li X, Theusch E, Takeuchi F, Spracklen CN, Loukola A, Bollepalli S, Warner SC, Wang YX, Wei WB, Nutile T, Ruggiero D, Sung YJ, Chen S, Liu F, Yang J, Kentistou KA, Banas B, Nardone GG, Meidtner K, Bielak LF, Smith JA, Hebbar P, Farmaki AE, Hofer E, Lin M, Concas MP, Vaccargiu S, van der Most PJ, Pitkänen N, Cade BE, van der Laan SW, Chitrala KN, Weiss S, Bentley AR, Doumatey AP, Adeyemo AA, Lee JY, Petersen ERB, Nielsen AA, Choi HS, Nethander M, Freitag-Wolf S, Southam L, Rayner NW, Wang CA, Lin SY, Wang JS, Couture C, Lyytikäinen LP, Nikus K, Cuellar-Partida G, Vestergaard H, Hidalgo B, Giannakopoulou O, Cai Q, Obura MO, van Setten J, Li X, Liang J, Tang H, Terzikhan N, Shin JH, Jackson RD, Reiner AP, Martin LW, Chen Z, Li L, Kawaguchi T, Thiery J, Bis JC, Launer LJ, Li H, Nalls MA, Raitakari OT, Ichihara S, Wild SH, Nelson CP, Campbell H, Jäger S, Nabika T, Al-Mulla F, Niinikoski H, Braund PS, Kolcic I, Kovacs P, Giardoglou T, Katsuya T, de Kleijn D, de Borst GJ, Kim EK, Adams HHH, Ikram MA, Zhu X, Asselbergs FW, Kraaijeveld AO, Beulens JWJ, Shu XO, Rallidis LS, Pedersen O, Hansen T, Mitchell P, Hewitt AW, Kähönen M, Pérusse L, Bouchard C, Tönjes A, Chen YDI, Pennell CE, Mori TA, Lieb W, Franke A, Ohlsson C, Mellström D, Cho YS, Lee H, Yuan JM, Koh WP, Rhee SY, Woo JT, Heid IM, Stark KJ, Zimmermann ME, Völzke H, Homuth G, Evans MK, Zonderman AB, Polasek O, Pasterkamp G, Hoefer IE, Redline S, Pahkala K, Oldehinkel AJ, Snieder H, Biino G, Schmidt R, Schmidt H, Bandinelli S, Dedoussis G, Thanaraj TA, Kardia SLR, Peyser PA, Kato N, Schulze MB, Girotto G, Böger CA, Jung B, Joshi PK, Bennett DA, De Jager PL, Lu X, Mamakou V, Brown M, Caulfield MJ, Munroe PB, Guo X, Ciullo M, Jonas JB, Samani NJ, Kaprio J, Pajukanta P, Tusié-Luna T, Aguilar-Salinas CA, Adair LS, Bechayda SA, de Silva HJ, Wickremasinghe AR, Krauss RM, Wu JY, Zheng W, Hollander AI, Bharadwaj D, Correa A, Wilson JG, Lind L, Heng CK, Nelson AE, Golightly YM, Wilson JF, Penninx B, Kim HL, Attia J, Scott RJ, Rao DC, Arnett DK, Hunt SC, Walker M, Koistinen HA, Chandak GR, Mercader JM, Costanzo MC, Jang D, Burtt NP, Villalpando CG, Orozco L, Fornage M, Tai ES, van Dam RM, Lehtimäki T, Chaturvedi N, Yokota M, Liu J, Reilly DF, McKnight AJ, Kee F, Jöckel KH, McCarthy MI, Palmer CNA, Vitart V, Hayward C, Simonsick E, van Duijn CM, Jin ZB, Qu J, Hishigaki H, Lin X, März W, Gudnason V, Tardif JC, Lettre G, Hart LM', Elders PJM, Damrauer SM, Kumari M, Kivimaki M, van der Harst P, Spector TD, Loos RJF, Province MA, Parra EJ, Cruz M, Psaty BM, Brandslund I, Pramstaller PP, Rotimi CN, Christensen K, Ripatti S, Widén E, Hakonarson H, Grant SFA, Kiemeney LALM, de Graaf J, Loeffler M, Kronenberg F, Gu D, Erdmann J, Schunkert H, Franks PW, Linneberg A, Jukema JW, Khera AV, Männikkö M, Jarvelin MR, Kutalik Z, Francesco C, Mook-Kanamori DO, van Dijk KW, Watkins H, Strachan DP, Grarup N, Sever P, Poulter N, Chuang LM, Rotter JI, Dantoft TM, Karpe F, Neville MJ, Timpson NJ, Cheng CY, Wong TY, Khor CC, Li H, Sabanayagam C, Peters A, Gieger C, Hattersley AT, Pedersen NL, Magnusson PKE, Boomsma DI, Willemsen AHM, Cupples LA, van Meurs JBJ, Ghanbari M, Gordon-Larsen P, Huang W, Kim YJ, Tabara Y, Wareham NJ, Langenberg C, Zeggini E, Kuusisto J, Laakso M, Ingelsson E, Abecasis G, Chambers JC, Kooner JS, de Vries PS, Morrison AC, Hazelhurst S, Ramsay M, North KE, Daviglus M, Kraft P, Martin NG, Whitfield JB, Abbas S, Saleheen D, Walters RG, Holmes MV, Black C, Smith BH, Baras A, Justice AE, Buring JE, Ridker PM, Chasman DI, Kooperberg C, Tamiya G, Yamamoto M, van Heel DA, Trembath RC, Wei WQ, Jarvik GP, Namjou B, Hayes MG, Ritchie MD, Jousilahti P, Salomaa V, Hveem K, Åsvold BO, Kubo M, Kamatani Y, Okada Y, Murakami Y, Kim BJ, Thorsteinsdottir U, Stefansson K, Zhang J, Chen YE, Ho YL, Lynch JA, Rader DJ, Tsao PS, Chang KM, Cho K, O'Donnell CJ, Gaziano JM, Wilson PWF, Frayling TM, Hirschhorn JN, Kathiresan S, Mohlke KL, Sun YV, Morris AP, Boehnke M, Brown CD, Natarajan P, Deloukas P, Willer CJ, Assimes TL, Peloso GM. Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis. Genome Biol 2022; 23:268. [PMID: 36575460 PMCID: PMC9793579 DOI: 10.1186/s13059-022-02837-1] [Show More Authors] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 12/06/2022] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. RESULTS To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. CONCLUSIONS Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.
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Affiliation(s)
- Stavroula Kanoni
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
| | - Sarah E Graham
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Yuxuan Wang
- Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Ave, Boston, MA, 02118, USA
| | - Ida Surakka
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Shweta Ramdas
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Xiang Zhu
- Department of Statistics, The Pennsylvania State University, University Park, PA, USA
- Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA, USA
- VA Palo Alto Health Care Systems, Palo Alto, CA, USA
- Department of Statistics, Stanford University, Stanford, CA, USA
| | - Shoa L Clarke
- VA Palo Alto Health Care Systems, Palo Alto, CA, USA
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Konain Fatima Bhatti
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
| | - Sailaja Vedantam
- Boston Children's Hospital, EndocrinologyBoston, MA, 02115, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Thomas W Winkler
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Adam E Locke
- McDonnell Genome Institute and Department of Medicine, Washington University, St. Louis, MO, 63108, USA
| | - Eirini Marouli
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
| | - Greg J M Zajac
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Kuan-Han H Wu
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Ioanna Ntalla
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Qin Hui
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
- Atlanta VA Health Care System, Decatur, GA, USA
| | - Derek Klarin
- VA Palo Alto Health Care Systems, Palo Alto, CA, USA
- Department of Surgery, Stanford University School of Medicine, Stanford, CA, USA
| | | | - Zeyuan Wang
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
- Atlanta VA Health Care System, Decatur, GA, USA
| | - Chao Xue
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | | | - Anna Helgadottir
- deCODE Genetics/Amgen, Inc. Sturlugata 8, Reykjavik, 102, Iceland
| | - Daniel F Gudbjartsson
- deCODE Genetics/Amgen, Inc. Sturlugata 8, Reykjavik, 102, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Sæmundargötu 2, Reykjavik, 102, Iceland
| | - Hilma Holm
- deCODE Genetics/Amgen, Inc. Sturlugata 8, Reykjavik, 102, Iceland
| | - Isleifur Olafsson
- Department of Clinical Biochemistry, Landspitali - National University Hospital of Iceland, Hringbraut, Reykjavik, 101, Iceland
| | - Mi Yeong Hwang
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Chungcheongbuk-Do, South Korea
| | - Sohee Han
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Chungcheongbuk-Do, South Korea
| | - Masato Akiyama
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Ophthalmology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Saori Sakaue
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Masahiro Kanai
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Wei Zhou
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Ben M Brumpton
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Clinic of Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Humaira Rasheed
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Division of Medicine and Laboratory Sciences, University of Oslo, Oslo, Norway
| | - Aki S Havulinna
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Tukholmankatu 8, 00014, Helsinki, Finland
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Yogasudha Veturi
- Department of Genetics, Institute for Biomedical Informatics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Jennifer Allen Pacheco
- Center for Genetic Medicine, Northwestern University, Feinberg School of Medicine, Chicago, IL, 60618, USA
| | - Elisabeth A Rosenthal
- Department of Medicine (Medical Genetics), University of Washington, Seattle, WA, USA
| | - Todd Lingren
- Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - QiPing Feng
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Iftikhar J Kullo
- Department of Cardiovascular Medicine and the Gonda Vascular Center, Mayo Clinic, Rochester, MN, USA
| | - Akira Narita
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, 980-8573, Japan
| | - Jun Takayama
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, 980-8573, Japan
| | | | - Karen A Hunt
- Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Bhavi Trivedi
- Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Jeffrey Haessler
- Fred Hutchinson Cancer Center, Division of Public Health Sciences, Seattle, WA, 9810, USA
| | - Franco Giulianini
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, 02215, USA
| | - Yuki Bradford
- Department of Genetics, Institute for Biomedical Informatics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Jason E Miller
- Department of Genetics, Institute for Biomedical Informatics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, EH4 2XU, UK
- Usher Institute, The University of Edinburgh, Nine, Edinburgh Bioquarter, 9 Little France Road, Edinburgh, EH16 4UX, UK
| | - Kuang Lin
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - Iona Y Millwood
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - Asif Rasheed
- Center for Non-Communicable Diseases, Karachi, Sindh, Pakistan
| | - George Hindy
- Department of Population Medicine, Qatar University College of Medicine, QU Health, Doha, Qatar
| | - Jessica D Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, 48104, USA
| | - Wei Zhao
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, 48104, USA
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - David R Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, 48104, USA
| | - Constance Turman
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA
| | - Hongyan Huang
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA
| | - Mariaelisa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Ananyo Choudhury
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Dhriti Sengupta
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Anubha Mahajan
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
| | - Michael R Brown
- Human Genetics Center, Department of Epidemiology, School of Public Health, Human Genetics, and Environmental Sciences, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Weihua Zhang
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK
- Department of Cardiology, Ealing Hospital, London North West University Healthcare NHS Trust, Middlesex, UB1 3HW, UK
| | - Ketian Yu
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Ellen M Schmidt
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Anita Pandit
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Stefan Gustafsson
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Xianyong Yin
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Jian'an Luan
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | - Jing-Hua Zhao
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Wort's Causeway, Cambridge, CB1 8RN, UK
| | - Fumihiko Matsuda
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Hye-Mi Jang
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Chungcheongbuk-Do, South Korea
| | - Kyungheon Yoon
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Chungcheongbuk-Do, South Korea
| | - Carolina Medina-Gomez
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Achilleas Pitsillides
- Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Ave, Boston, MA, 02118, USA
| | - Jouke Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam UMC, the Netherlands
| | - Andrew R Wood
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, EX2 5DW, UK
| | - Yingji Ji
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, EX2 5DW, UK
| | - Zishan Gao
- Nanjing University of Chinese Medicine, Nanjing, 210029, Jiangsu, China
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Simon Haworth
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Bristol Dental School, University of Bristol, Lower Maudlin Street, Bristol, BS1 2LY, UK
| | - Noha A Yousri
- Department of Genetic Medicine, Weill Cornell Medicine-Qatar, Doha, Qatar
- Department of Computer and Systems Engineering, Alexandria University, Alexandria, Egypt
| | - Ruth E Mitchell
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Jin Fang Chai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, 117549, Singapore
| | - Mette Aadahl
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Anne A Bjerregaard
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark
| | - Jie Yao
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovations (Formerly LABioMed) at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Ani Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, 22903, USA
| | - Chii-Min Hwu
- Section of Endocrinology and Metabolism, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Yi-Jen Hung
- Institute of Preventive Medicine, National Defense Medical Center, Postbox 90048~700, Sanhsia Dist, New Taipei City, 237101, Taiwan
| | - Helen R Warren
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, John Vane Science Centre, Charterhouse Square, London, EC1M 6BQ, UK
- NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Julia Ramirez
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, John Vane Science Centre, Charterhouse Square, London, EC1M 6BQ, UK
- Aragon Institute of Engineering Research, University of Zaragoza and Centro de Investigación Biomédica en Red - Bioingeniería, Biomateriales Y Nanomedicina, Spain
| | - Jette Bork-Jensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Line L Kårhus
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark
| | - Anuj Goel
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, John Radcliffe Hospital, University of Oxford, Oxford, OX3 9DU, UK
| | - Maria Sabater-Lleal
- Unit of Genomics of Complex Diseases, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Barcelona, Spain
- Cardiovascular Medicine Unit, Department of Medicine, Karolinska Institutet, Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Pala Mauro
- Istituto Di Ricerca Genetica E Biomedica, Consiglio Nazionale Delle Ricerche, Rome, Italy
| | - Floris Matteo
- Istituto Di Ricerca Genetica E Biomedica, Consiglio Nazionale Delle Ricerche, Rome, Italy
- Dipartimento Di Scienze Biomediche, Università Degli Studi Di Sassari, Sardinia, Italy
| | - Aaron F McDaid
- University Center for Primary Care and Public Health, University of Lausanne, Rte de Berne 113, 1010, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland
| | - Pedro Marques-Vidal
- Department of Medicine, Internal Medicine, Lausanne University Hospital and University of Lausanne, Rue du Bugnon 46, 1011, Lausanne, Switzerland
| | - Matthias Wielscher
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Stella Trompet
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
- Dept of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Naveed Sattar
- BHF Glasgow Cardiovascular Research Centre, Faculty of Medicine, Glasgow, UK
| | - Line T Møllehave
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark
| | - Matthias Munz
- Institute for Cardiogenetics, University of Lübeck, DZHK (German Research Centre for Cardiovascular Research), Partner Site Hamburg/Lübeck/Kiel, University Heart Center Lübeck, Lübeck and Charité - University Medicine Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität Zu Berlin and Berlin Institute of Health, Institute for Dental and Craniofacial Sciences, Department of Periodontology and Synoptic Dentistry, Berlin, Germany
| | - Lingyao Zeng
- Deutsches Herzzentrum München, Klinik Für Herz- Und Kreislauferkrankungen, Technische Universität München, Munich, Germany
- Deutsches Zentrum Für Herz-Kreislauf-Forschung (DZHK) E.V., Partner Site Munich Heart Alliance, Munich, Germany
| | - Jianfeng Huang
- Key Laboratory of Cardiovascular Epidemiology and Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100037, China
| | - Bin Yang
- Key Laboratory of Cardiovascular Epidemiology and Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100037, China
| | - Alaitz Poveda
- Lund University Diabetes Center, Lund University, Malmö, Sweden
| | - Azra Kurbasic
- Lund University Diabetes Center, Lund University, Malmö, Sweden
| | - Claudia Lamina
- Institute of Genetic Epidemiology, Department of Genetics, Medical University of Innsbruck, Innsbruck, Austria
- German Chronic Kidney Disease Study, Berlin, Germany
| | - Lukas Forer
- Institute of Genetic Epidemiology, Department of Genetics, Medical University of Innsbruck, Innsbruck, Austria
- German Chronic Kidney Disease Study, Berlin, Germany
| | - Markus Scholz
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Haertelstrasse 16-18, 04107, Leipzig, Germany
- LIFE Research Centre for Civilization Diseases, University of Leipzig, Philipp-Rosenthal-Straße 27, 04103, Leipzig, Germany
| | - Tessel E Galesloot
- Radboud University Medical Center, Radboud Institute for Health Sciences, Nijmegen, The Netherlands
| | | | - Sanni E Ruotsalainen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Tukholmankatu 8, 00014, Helsinki, Finland
| | - EWarwick Daw
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Joseph M Zmuda
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jonathan S Mitchell
- Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Via Galvani 31, 39100, Bolzano, Italy
| | - Christian Fuchsberger
- Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Via Galvani 31, 39100, Bolzano, Italy
| | - Henry Christensen
- Department of Clinical Biochemistry, Lillebaelt Hospital, Vejle, Denmark
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, 98101, USA
| | - Miguel Vazquez-Moreno
- Unidad de Investigacion Medica en Bioquimica, Hospital de Especialidades, Centro Medico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Mary F Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Mary K Wojczynski
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Zhe Wang
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Michael H Preuss
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, King's College London, London, SE1 7EH, UK
- NIHR Biomedical Research Centre at Guy's and St Thomas' Foundation Trust, London, SE1 9RT, UK
| | - Paraskevi Christofidou
- Department of Twin Research and Genetic Epidemiology, King's College London, London, SE1 7EH, UK
| | - Niek Verweij
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Jan W Benjamins
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Jorgen Engmann
- Institute of Cardiovascular Sciences, University College London, Gower Street, London, WC1E 6BT, UK
- Department of Epidemiology and Public Health, University College London, 1-19 Torrington Place, London, WC1E 6BT, UK
| | - Noah L Tsao
- Department of Surgery, University of Pennsylvania, Philadelphia, PA, USA
| | - Anurag Verma
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Roderick C Slieker
- Amsterdam UMC, Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam, 1081HV, the Netherlands
- Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, 2333ZA, The Netherlands
| | - Ken Sin Lo
- Montreal Heart Institute, Université de Montréal, 5000 Belanger Street, Montreal, PQ, H1T1C8, Canada
| | - Nuno R Zilhao
- Icelandic Heart Association, 201, Kopavogur, Iceland
| | - Phuong Le
- Department of Anthropology, University of Toronto at Mississauga, Mississauga, ON, L5L 1C6, Canada
| | - Marcus E Kleber
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, 68167, Mannheim, Germany
- SYNLAB MVZ Humangenetik Mannheim GmbH, 68163, Mannheim, Germany
| | - Graciela E Delgado
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, 68167, Mannheim, Germany
| | - Shaofeng Huo
- Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Daisuke D Ikeda
- Biomedical Technology Research Center, Tokushima Research Institute, Otsuka Pharmaceutical Co., Ltd, Tokushima, Japan
| | - Hiroyuki Iha
- Biomedical Technology Research Center, Tokushima Research Institute, Otsuka Pharmaceutical Co., Ltd, Tokushima, Japan
| | - Jian Yang
- School of Life Sciences, Westlake University, Hangzhou, 310024, Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, 310024, Zhejiang, China
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Jun Liu
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Ayşe Demirkan
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Section of Statistical Multi-Omics, Department of Clinical and Experimental Research, University of Surrey, Guildford, Surrey, UK
| | - Hampton L Leonard
- Laboratory of Neurogenetics, National Institute On Aging, NIH, Bethesda, MD, USA
- Data Tecnica International, Glen Echo, MD, USA
| | - Jonathan Marten
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, Scotland
| | - Mirjam Frank
- Institute for Medical Informatics, Biometry and Epidemiology, University of Duisburg-Essen, Essen, Germany
| | - Börge Schmidt
- Institute for Medical Informatics, Biometry and Epidemiology, University of Duisburg-Essen, Essen, Germany
| | - Laura J Smyth
- Centre for Public Health, Queen's University of Belfast, Belfast, Northern Ireland
| | - Marisa Cañadas-Garre
- Centre for Public Health, Queen's University of Belfast, Belfast, Northern Ireland
- Genomic Oncology Area, GENYO, Centre for Genomics and Oncological Research: Pfizer-University of Granada-Andalusian Regional Government, Granada, Spain
- Hematology Department, Hospital Universitario Virgen de Las Nieves, Granada, Spain
- Instituto de Investigación Biosanitaria de Granada (Ibs.GRANADA), Granada, Spain
| | - Chaolong Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | - Masahiro Nakatochi
- Public Health Informatics Unit, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, 461-8673, Japan
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, 1-19 Torrington Place, London, WC1E 7HB, UK
| | - Nina Hutri-Kähönen
- Tampere Centre for Skills Training and Simulation, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, 117549, Singapore
| | - Rui Xia
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Alicia Huerta-Chagoya
- CONACYT, Instituto Nacional de Ciencias Médicas Y Nutrición Salvador Zubirán, Ciudad de Mexico, Mexico
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Departamento de Medicina Genómica Y Toxicología Ambiental, Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Coyoacán, 04510, Mexico City, Mexico
| | | | - Valeriya Lyssenko
- Lund University Diabetes Center, Lund University, Malmö, Sweden
- Center for Diabetes Research, University of Bergen, Bergen, Norway
| | | | - Swati Bayyana
- Genomic Research On Complex Diseases (GRC Group), CSIR-Centre for Cellular and Molecular Biology, Hyderabad, Telangana, India
- Academy of Scientific and Innovative Research (AcSIR), New Delhi, India
| | - Heather M Stringham
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Marguerite R Irvin
- Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | | | - Han-Na Kim
- Medical Research Institute, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, 03181, Korea
- Department of Clinical Research Design & Evaluation, SAIHST, Sungkyunkwan University, Seoul, 06355, Korea
| | - Seungho Ryu
- Center for Cohort Studies, Total Healthcare Center, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, 04514, Korea
- Department of Occupational and Environmental Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, 03181, Korea
| | - Paul R H J Timmers
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, Scotland
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland
| | - Liubov Arbeeva
- Thurston Arthritis Research Center, University of North Carolina, Chapel Hill, NC, USA
| | - Rajkumar Dorajoo
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
- Duke-NUS Medical School, Health Services and Systems Research, Singapore, 169857, Singapore
| | - Leslie A Lange
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, Anschutz Medical Campus, University of Colorado, Denver, Aurora, CO, 80045, USA
| | - Gauri Prasad
- Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, 110020, India
- Academy of Scientific and Innovative Research, CSIR-Human Resource Development Centre, Ghaziabad, Uttar Pradesh, India
| | - Laura Lorés-Motta
- Departments of Ophthalmology and Human Genetics, Radboud University Nijmegen Medical Center, Philips Van Leydenlaan 15, Nijmegen, 6525 EX, the Netherlands
| | - Marc Pauper
- Departments of Ophthalmology and Human Genetics, Radboud University Nijmegen Medical Center, Philips Van Leydenlaan 15, Nijmegen, 6525 EX, the Netherlands
| | - Jirong Long
- Vanderbilt Epidemiology Center, Division of Epidemiology, Vanderbilt University Medical Center, Nashville, USA
| | - Xiaohui Li
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovations (Formerly LABioMed) at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Elizabeth Theusch
- Department of Pediatrics, University of California San Francisco, Oakland, CA, 94609, USA
| | - Fumihiko Takeuchi
- National Center for Global Health and Medicine, Tokyo, 1628655, Japan
| | - Cassandra N Spracklen
- Department of Genetics, University of North Carolina, Chapel Hill, NC, 27599, USA
- Department of Biostatistics and Epidemiology, University of Massachusetts-Amherst, Amherst, MA, 01003, USA
| | - Anu Loukola
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Tukholmankatu 8, 00014, Helsinki, Finland
| | - Sailalitha Bollepalli
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Tukholmankatu 8, 00014, Helsinki, Finland
| | - Sophie C Warner
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Ya Xing Wang
- Beijing Institute of Ophthalmology, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, 17 Hougou Lane, Chong Wen Men, Beijing, 100005, China
| | - Wen B Wei
- Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, 1 Dong Jiao Min Xiang, Beijing, 100730, Dong Cheng District, China
| | - Teresa Nutile
- Institute of Genetics and Biophysics "Adriano Buzzati-Traverso" - CNR, Naples, Italy
| | - Daniela Ruggiero
- Institute of Genetics and Biophysics "Adriano Buzzati-Traverso" - CNR, Naples, Italy
- IRCCS Neuromed, Pozzilli, Isernia, Italy
| | - Yun Ju Sung
- Division of Biostatistics, Washington University, St. Louis, MO, 63110, USA
| | - Shufeng Chen
- Key Laboratory of Cardiovascular Epidemiology and Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100037, China
| | - Fangchao Liu
- Key Laboratory of Cardiovascular Epidemiology and Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100037, China
| | - Jingyun Yang
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Katherine A Kentistou
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland
| | - Bernhard Banas
- Dept of Nephrology, University Hospital Regensburg, Regensburg, Germany
| | | | - Karina Meidtner
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
| | - Lawrence F Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Jennifer A Smith
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, 48104, USA
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Prashantha Hebbar
- Department of Genetics and Bioinformatics, Dasman Diabetes Institute, Kuwait City, Kuwait
| | - Aliki-Eleni Farmaki
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University of Athens, Athens, Greece
- Department of Clinical Epidemiology, Institute of Health Informatics, University College London, London, UK
| | - Edith Hofer
- Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Graz, Austria
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria
| | - Maoxuan Lin
- Massachusetts General Hospital Cancer Center, Charlestown, MA, 02129, USA
| | - Maria Pina Concas
- Institute for Maternal and Child Health, IRCCS Burlo Garofolo, Trieste, Italy
| | - Simona Vaccargiu
- Institute of Genetic and Biomedical Research, National Research Council of Italy, UOS of Sassari, Sassari, Italy
| | - Peter J van der Most
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, the Netherlands
| | - Niina Pitkänen
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | - Brian E Cade
- Sleep Medicine and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, 02115, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, 02115, USA
| | - Sander W van der Laan
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Kumaraswamy Naidu Chitrala
- Laboratory of Epidemiology and Population Sciences, National Institute On Aging, NIH, Baltimore, MD, 20892-9205, USA
- Department of Engineering Technology, University of Houston-Sugarland, Houston, TX, USA
| | - Stefan Weiss
- Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, University of Greifswald and University Medicine Greifswald, Greifswald, Germany
| | - Amy R Bentley
- Center for Research On Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive, Room 1025, Bethesda, MD, 20892, USA
| | - Ayo P Doumatey
- Center for Research On Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive, Room 1025, Bethesda, MD, 20892, USA
| | - Adebowale A Adeyemo
- Center for Research On Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive, Room 1025, Bethesda, MD, 20892, USA
| | - Jong Young Lee
- , Oneomics. Co. Ltd. 2F, Soonchunhyang Mirai Medical Center 173, Buheuyng-Ro, Bucheon-Si Gyeonggi-Do, 14585, Korea
| | - Eva R B Petersen
- Department of Clinical Biochemistry and Immunology, Hospital of Southern Jutland, Kresten Philipsens Vej 15, 6200, Aabenraa, Denmark
| | - Aneta A Nielsen
- Department of Clinical Biochemistry, Lillebaelt Hospital, Kolding, Denmark
| | - Hyeok Sun Choi
- Department of Biomedical Science, Hallym University, Chuncheon, 24252, Gangwon-Do, Korea
| | - Maria Nethander
- Centre for Bone and Arthritis Research, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Bioinformatics Core Facility, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Sandra Freitag-Wolf
- Institute of Medical Informatics and Statistics, Kiel University, Kiel, Germany
| | - Lorraine Southam
- Wellcome Trust Sanger Institute, Hinxton, CB10 1SA, UK
- Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Nigel W Rayner
- Wellcome Trust Sanger Institute, Hinxton, CB10 1SA, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
- Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
| | - Carol A Wang
- School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, NSW, 2308, Australia
| | - Shih-Yi Lin
- Center for Geriatrics and Gerontology, Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
- School of Medicine, National Yang-Ming University, Taipei, Taiwan
- School of Medicine, National Defense Medical Center, Taipei, Taiwan
| | - Jun-Sing Wang
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
- Department of Medicine, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | | | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories, 33520, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, 33014, Tampere, Finland
| | - Kjell Nikus
- Department of Cardiology, Heart Center, Tampere University Hospital, 33521, Tampere, Finland
- Department of Cardiology, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, 33014, Tampere, Finland
| | - Gabriel Cuellar-Partida
- University of Queensland Diamantina Institute, Translational Research Institute, Kent St, Woolloongabba, Brisbane, QLD, 4102, Australia
| | - Henrik Vestergaard
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Medicine, Bornholms Hospital, Rønne, Denmark
| | - Bertha Hidalgo
- Department of Epidemiology, Ryals School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Olga Giannakopoulou
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
| | - Qiuyin Cai
- Vanderbilt Epidemiology Center, Division of Epidemiology, Vanderbilt University Medical Center, Nashville, USA
| | - Morgan O Obura
- Amsterdam UMC, Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam, 1081HV, the Netherlands
| | - Jessica van Setten
- Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Xiaoyin Li
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Jingjing Liang
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Hua Tang
- Department of Genetics, Stanford University School of Medicine Stanford, Palo Alto, CA, 94305, USA
| | - Natalie Terzikhan
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Jae Hun Shin
- Department of Biomedical Science, Hallym University, Chuncheon, 24252, Gangwon-Do, Korea
| | - Rebecca D Jackson
- Division of Endocrinology, Ohio State University, Columbus, OH, 43210, USA
| | - Alexander P Reiner
- Department of Epidemiology, University of Washington, Seattle, WA, 98195, USA
| | - Lisa Warsinger Martin
- School of Medicine and Health Sciences, George Washington University, Washington, DC, 20037, USA
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - Liming Li
- Department of Epidemiology, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Takahisa Kawaguchi
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Joachim Thiery
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Haertelstrasse 16-18, 04107, Leipzig, Germany
- Institute for Laboratory Medicine, University Hospital Leipzig, Paul-List-Strasse 13/15, 04103, Leipzig, Germany
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, 98101, USA
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, National Institute On Aging, NIH, Baltimore, MD, 20892-9205, USA
| | - Huaixing Li
- Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Mike A Nalls
- Center for Alzheimer's and Related Dementias, NIH, Bethesda, MD, USA
- Data Tecnica International, Washington, DC, USA
| | - Olli T Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Sahoko Ichihara
- Department of Environmental and Preventive Medicine, Jichi Medical University School of Medicine, Shimotsuke, 329-0498, Japan
| | - Sarah H Wild
- Centre for Population Health Sciences, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland
| | - Christopher P Nelson
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Harry Campbell
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland
| | - Susanne Jäger
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
| | - Toru Nabika
- Department of Functional Pathology, Shimane University School of Medicine, Izumo, 6938501, Japan
| | - Fahd Al-Mulla
- Department of Genetics and Bioinformatics, Dasman Diabetes Institute, Kuwait City, Kuwait
| | - Harri Niinikoski
- Department of Pediatrics and Adolescent Medicine, Turku University Hospital and University of Turku, Turku, Finland
- Department of Physiology, University of Turku, Turku, Finland
| | - Peter S Braund
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Ivana Kolcic
- University of Split School of Medicine, Šoltanska 2, HR-21000, Split, Croatia
| | - Peter Kovacs
- University of Leipzig Medical Center, Liebigstr. 18, 04103, Medical Department III - Endocrinology, Nephrology, RheumatologyLeipzig, Germany
| | - Tota Giardoglou
- Department of Nutrition-Dietetics, Harokopio University, Eleftheriou Venizelou, 17676, Athens, Greece
| | - Tomohiro Katsuya
- Department of Clinical Gene Therapy, Osaka University Graduate School of Medicine, Suita, 5650871, Japan
- Department of Geriatric and General Medicine, Osaka University Graduate School of Medicine, Suita, 5650871, Japan
| | - Dominique de Kleijn
- Department of Vascular Surgery, Division of Surgical Specialties, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Gert J de Borst
- Department of Vascular Surgery, Division of Surgical Specialties, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Eung Kweon Kim
- Corneal Dystrophy Research Institute, Yonsei University College of Medicine, Saevit Eye Hospital, SeoulIlsan, 03722, Korea
| | - Hieab H H Adams
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Dept of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Xiaofeng Zhu
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Folkert W Asselbergs
- Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Adriaan O Kraaijeveld
- Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Joline W J Beulens
- Amsterdam UMC, Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam, 1081HV, the Netherlands
- Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, 3584CG, Utrecht, the Netherlands
| | - Xiao-Ou Shu
- Vanderbilt Epidemiology Center, Division of Epidemiology, Vanderbilt University Medical Center, Nashville, USA
| | - Loukianos S Rallidis
- Second Department of Cardiology, Medical School, National and Kapodistrian University of Athens, Attikon University Hospital, Athens, Greece
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Paul Mitchell
- Center for Vision Research, Department of Ophthalmology and The Westmead Institute, University of Sydney, Hawkesbury Rd, Sydney, NSW, 2145, Australia
| | - Alex W Hewitt
- School of Medicine, Menzies Institute for Medical Research, University of Tasmania, Liverpool St, Hobart, TAS, 7000, Australia
- Centre for Eye Research Australia, University of Melbourne, Melbourne, VIC, 3002, Australia
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, 33521, Tampere, Finland
- Department of Clinical Physiology, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, 33014, Tampere, Finland
| | - Louis Pérusse
- Department of Kinesiology, Université Laval, Québec, Canada
- Centre Nutrition, Santé Et Société (NUTRISS), Institute of Nutrition and Functional Foods (INAF), Québec, Canada
| | - Claude Bouchard
- Pennington Biomedical Research Center, Baton Rouge, LA, 70808, USA
| | - Anke Tönjes
- University of Leipzig Medical Center, Liebigstr. 18, 04103, Medical Department III - Endocrinology, Nephrology, RheumatologyLeipzig, Germany
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovations (Formerly LABioMed) at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Craig E Pennell
- School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, NSW, 2308, Australia
| | - Trevor A Mori
- Discipline of Internal Medicine, Medical School, The University of Western Australia, Perth, WA, Australia
| | - Wolfgang Lieb
- Institute of Epidemiology, Kiel University, Kiel, Germany
| | - Andre Franke
- Institute of Clinical Molecular Biology, Kiel University, Kiel, Germany
| | - Claes Ohlsson
- Centre for Bone and Arthritis Research, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Drug Treatment, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Dan Mellström
- Centre for Bone and Arthritis Research, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Geriatric Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Yoon Shin Cho
- Department of Biomedical Science, Hallym University, Chuncheon, 24252, Gangwon-Do, Korea
| | - Hyejin Lee
- Department of Internal Medicine, EwhaWomans University School of Medicine, Seoul, Korea
| | - Jian-Min Yuan
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, 15232, USA
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, 15232, USA
| | - Woon-Puay Koh
- Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117545, Singapore
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research (A*STAR), Singapore, 117609, Singapore
| | - Sang Youl Rhee
- Department of Endocrinology and Metabolism, Kyung Hee University School of Medicine, Seoul, 02447, Korea
| | - Jeong-Taek Woo
- Department of Endocrinology and Metabolism, Kyung Hee University School of Medicine, Seoul, 02447, Korea
| | - Iris M Heid
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Klaus J Stark
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Martina E Zimmermann
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, University of Greifswald and University Medicine Greifswald, Greifswald, Germany
| | - Michele K Evans
- Laboratory of Epidemiology and Population Science, National Institute On Aging Intramural Research Program, NIH Biomedical Research Center, NIH 251 Bayview Blvd, Baltimore, MD, 21224, USA
| | - Alan B Zonderman
- Laboratory of Epidemiology and Population Science, National Institute On Aging Intramural Research Program, NIH Biomedical Research Center, NIH 251 Bayview Blvd, Baltimore, MD, 21224, USA
| | - Ozren Polasek
- University of Split School of Medicine, Šoltanska 2, HR-21000, Split, Croatia
- Algebra University College, Ilica 242, Zagreb, Croatia
| | - Gerard Pasterkamp
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Imo E Hoefer
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Susan Redline
- Sleep Medicine and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, 02115, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, 02115, USA
| | - Katja Pahkala
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Department of Physical Activity and Health, Paavo Nurmi Centre, Sports and Exercise Medicine Unit, University of Turku, Turku, Finland
| | - Albertine J Oldehinkel
- Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, the Netherlands
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, the Netherlands
| | - Ginevra Biino
- Institute of Molecular Genetics, National Research Council of Italy, Pavia, Italy
| | - Reinhold Schmidt
- Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Graz, Austria
| | - Helena Schmidt
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Medical University of Graz, Graz, Austria
| | | | - George Dedoussis
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University of Athens, Athens, Greece
| | | | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Norihiro Kato
- National Center for Global Health and Medicine, Tokyo, 1628655, Japan
| | - Matthias B Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
- Institute of Nutritional Science, University of Potsdam, Nuthetal, Germany
| | - Giorgia Girotto
- Institute for Maternal and Child Health, IRCCS Burlo Garofolo, Trieste, Italy
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Strada Di Fiume 447, 34149, Trieste, Italy
| | - Carsten A Böger
- Dept of Nephrology, University Hospital Regensburg, Regensburg, Germany
- Department of Nephrology, , Traunstein Hospital, Diabetology, RheumatologyTraunstein, Germany
- KfH Kidney Center Traunstein, Traunstein, Germany
| | - Bettina Jung
- Dept of Nephrology, University Hospital Regensburg, Regensburg, Germany
- Department of Nephrology, , Traunstein Hospital, Diabetology, RheumatologyTraunstein, Germany
- KfH Kidney Center Traunstein, Traunstein, Germany
| | - Peter K Joshi
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Philip L De Jager
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Neurology, Center for Translational and Systems Neuroimmunology, Columbia University Medical Center, New York, NY, USA
| | - Xiangfeng Lu
- Key Laboratory of Cardiovascular Epidemiology and Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100037, China
| | - Vasiliki Mamakou
- Medical School, National and Kapodistrian University Athens, 75 M. Assias Street, 115 27, Athens, Greece
- Dromokaiteio Psychiatric Hospital, 124 61, Athens, Greece
| | - Morris Brown
- NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
- Clinical Pharmacology, William Harvey Research Institute, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Mark J Caulfield
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, John Vane Science Centre, Charterhouse Square, London, EC1M 6BQ, UK
- NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Patricia B Munroe
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, John Vane Science Centre, Charterhouse Square, London, EC1M 6BQ, UK
- NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovations (Formerly LABioMed) at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Marina Ciullo
- Institute of Genetics and Biophysics "Adriano Buzzati-Traverso" - CNR, Naples, Italy
- IRCCS Neuromed, Pozzilli, Isernia, Italy
| | - Jost B Jonas
- Beijing Institute of Ophthalmology, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, 17 Hougou Lane, Chong Wen Men, Beijing, 100005, China
- Department of Ophthalmology, Medical Faculty Mannheim, Heidelberg University, Kutzerufer 1, 68167, Mannheim, Germany
- Institute of Molecular and Clinical Ophthalmology, Basel, Switzerland
- Privatpraxis Prof Jonas Und Dr Panda-Jonas, Heidelberg, Germany
| | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Tukholmankatu 8, 00014, Helsinki, Finland
| | - Päivi Pajukanta
- Department of Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, CA, USA
| | - Teresa Tusié-Luna
- Unidad de Biología Molecular Y Medicina Genómica, Instituto de Investigaciones Biomédicas UNAM/ Instituto Nacional de Ciencias Médicas Y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Carlos A Aguilar-Salinas
- Departamento de Endocrinología Y Metabolismo, Instituto Nacional de Ciencias Médicas Y Nutrición Salvador Zubirán, 14080, Mexico, Mexico
| | - Linda S Adair
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, 27599, USA
- Carolina Population Center, University of North Carolina, Chapel Hill, NC, 27516, USA
| | - Sonny Augustin Bechayda
- USC-Office of Population Studies Foundation, University of San Carlos, 6000, Cebu City, Philippines
- Department of Anthropology, Sociology, and History, University of San Carlos, 6000, Cebu City, Philippines
| | - H Janaka de Silva
- Department of Medicine, Faculty of Medicine, University of Kelaniya, Ragama, 11010, Sri Lanka
| | - Ananda R Wickremasinghe
- Department of Public Health, Faculty of Medicine, University of Kelaniya, Ragama, 11010, Sri Lanka
| | - Ronald M Krauss
- Children's Hospital Oakland Research Institute, Oakland, CA, 94609, USA
| | - Jer-Yuarn Wu
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Wei Zheng
- Vanderbilt Epidemiology Center, Division of Epidemiology, Vanderbilt University Medical Center, Nashville, USA
| | - Anneke Iden Hollander
- Departments of Ophthalmology and Human Genetics, Radboud University Nijmegen Medical Center, Philips Van Leydenlaan 15, Nijmegen, 6525 EX, the Netherlands
| | - Dwaipayan Bharadwaj
- Academy of Scientific and Innovative Research, CSIR-Human Resource Development Centre, Ghaziabad, Uttar Pradesh, India
- Systems Genomics Laboratory, School of Biotechnology, Jawaharlal Nehru University, New Delhi, 110067, India
| | - Adolfo Correa
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, 39216, USA
| | - James G Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS, 39216, USA
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Chew-Kiat Heng
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore and Khoo Teck Puat - National University Children's Medical Institute, National University Health System, Singapore, Singapore
| | - Amanda E Nelson
- Thurston Arthritis Research Center, University of North Carolina, Chapel Hill, NC, USA
- Department of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Yvonne M Golightly
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
- Thurston Arthritis Research Center, University of North Carolina, Chapel Hill, NC, USA
- Injury Prevention Research Center, University of North Carolina, Chapel Hill, NC, USA
- Division of Physical Therapy, University of North Carolina, Chapel Hill, NC, USA
| | - James F Wilson
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, Scotland
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland
| | - Brenda Penninx
- Amsterdam Public Health Research Institute, Amsterdam UMC, the Netherlands
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Hyung-Lae Kim
- Department of Biochemistry, College of Medicine, Ewha Womans University, Seoul, 07804, Korea
| | - John Attia
- Hunter Medical Research Institute, Newcastle, Australia
- Faculty of Health and Medicine, University of Newcastle, Callaghan, Australia
| | - Rodney J Scott
- Hunter Medical Research Institute, Newcastle, Australia
- Faculty of Health and Medicine, University of Newcastle, Callaghan, Australia
| | - D C Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, USA
| | - Donna K Arnett
- Office of the Provost, University of South Carolina, Columbia, SC, USA
| | - Steven C Hunt
- Department of Genetic Medicine, Weill Cornell Medicine-Qatar, Doha, Qatar
- Department of Internal Medicine, University of Utah, Salt Lake City, Utah, 84132, USA
| | - Mark Walker
- Institute of Cellular Medicine (Diabetes), The Medical School, Newcastle University, Framlington Place, Newcastle Upon Tyne, NE2 4HH, UK
| | - Heikki A Koistinen
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
- Department of Medicine, Helsinki University Hospital, University of Helsinki, Haartmaninkatu 4, P.O.Box 340, 00029, Helsinki, Finland
- Minerva Foundation Institute for Medical Research, Biomedicum 2U, Tukholmankatu 8, 00290, Helsinki, Finland
| | - Giriraj R Chandak
- Academy of Scientific and Innovative Research (AcSIR), New Delhi, India
- JSS Academy of Higher Education and Research, Mysuru, India
| | - Josep M Mercader
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Maria C Costanzo
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Dongkeun Jang
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Noël P Burtt
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - Lorena Orozco
- Laboratorio de Inmunogenómica Y Enfermedades Metabólicas, Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - EShyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, 117549, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, 119228, Singapore
| | - Rob M van Dam
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, 117549, Singapore
- Department of Exercise and Nutrition Sciences, Milken Institute School of Public Health, George Washington University, Washington, DC, 20052, USA
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, 33520, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, 33014, Tampere, Finland
| | - Nish Chaturvedi
- MRC Unit for Lifelong Health and Ageing at UCL, 1-19 Torrington Place, London, WC1E 7HB, UK
| | | | - Jianjun Liu
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | - Dermot F Reilly
- Genetics, Merck Sharp & Dohme Corp., Kenilworth, NJ, 07033, USA
| | - Amy Jayne McKnight
- Centre for Public Health, Queen's University of Belfast, Belfast, Northern Ireland
| | - Frank Kee
- Centre for Public Health, Queen's University of Belfast, Belfast, Northern Ireland
| | - Karl-Heinz Jöckel
- Institute for Medical Informatics, Biometry and Epidemiology, University of Duisburg-Essen, Essen, Germany
| | - Mark I McCarthy
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
| | - Colin N A Palmer
- Population Health and Genomics, University of Dundee, Ninwells Hospital and Medical School, Dundee, DD1 9SY, UK
| | - Veronique Vitart
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, Scotland
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, Scotland
| | - Eleanor Simonsick
- Intramural Research Program, National Institute On Aging, 3001 S. Hanover St., Baltimore, MD, 21225, USA
| | - Cornelia M van Duijn
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Zi-Bing Jin
- Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology and Visual Sciences Key Laboratory, Beijing, 100730, China
- The Eye Hospital, School of Ophthalmology and Optometry, Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China
| | - Jia Qu
- The Eye Hospital, School of Ophthalmology and Optometry, Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China
| | - Haretsugu Hishigaki
- Biomedical Technology Research Center, Tokushima Research Institute, Otsuka Pharmaceutical Co., Ltd, Tokushima, Japan
| | - Xu Lin
- Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Winfried März
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, 68167, Mannheim, Germany
- Synlab Academy, SYNLAB Holding Deutschland GmbH, Mannheim and Augsburg, Germany
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria
| | - Vilmundur Gudnason
- Icelandic Heart Association, 201, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, 101, Reykjavik, Iceland
| | - Jean-Claude Tardif
- Montreal Heart Institute, Université de Montréal, 5000 Belanger Street, Montreal, PQ, H1T1C8, Canada
| | - Guillaume Lettre
- Montreal Heart Institute, Université de Montréal, 5000 Belanger Street, Montreal, PQ, H1T1C8, Canada
| | - Leen M 't Hart
- Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, 2333ZA, The Netherlands
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, 2333ZA, The Netherlands
- Department of Epidemiology and Data Science, Amsterdam UMC, Amsterdam, 1081HV, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam Cardiovascular Sciences, Amsterdam, 1081HV, the Netherlands
| | - Petra J M Elders
- Department of General Practice, Amsterdam UMC, Amsterdam, 1081HV, the Netherlands
- Amsterdam Public Health Research Institute, Health Behaviours and Chronic Diseases, Amsterdam, 1081HV, the Netherlands
| | - Scott M Damrauer
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Surgery, University of Pennsylvania, Philadelphia, PA, USA
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, 19104, USA
| | - Meena Kumari
- Institute of Social and Economic Research, University of Essex, Wivenhoe Park, Colchester, CO4 3SQ, UK
| | - Mika Kivimaki
- Department of Epidemiology and Public Health, University College London, 1-19 Torrington Place, London, WC1E 6BT, UK
| | - Pim van der Harst
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, SE1 7EH, UK
| | - Ruth J F Loos
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Michael A Province
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Esteban J Parra
- Department of Anthropology, University of Toronto at Mississauga, Mississauga, ON, L5L 1C6, Canada
| | - Miguel Cruz
- Unidad de Investigacion Medica en Bioquimica, Hospital de Especialidades, Centro Medico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, 98101, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Ivan Brandslund
- Department of Clinical Biochemistry, Lillebaelt Hospital, Vejle, Denmark
- Institute of Regional Health Research, University of Southern Denmark, Odense, Denmark
| | - Peter P Pramstaller
- Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Via Galvani 31, 39100, Bolzano, Italy
| | - Charles N Rotimi
- Center for Research On Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive, Room 1025, Bethesda, MD, 20892, USA
| | - Kaare Christensen
- Danish Aging Research Center, University of Southern Denmark, Odense C, Denmark
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Tukholmankatu 8, 00014, Helsinki, Finland
- Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Elisabeth Widén
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Tukholmankatu 8, 00014, Helsinki, Finland
| | - Hakon Hakonarson
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Department of Pediatrics, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Struan F A Grant
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Pediatrics, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Lambertus A L M Kiemeney
- Radboud University Medical Center, Radboud Institute for Health Sciences, Nijmegen, The Netherlands
| | - Jacqueline de Graaf
- Radboud University Medical Center, Radboud Institute for Health Sciences, Nijmegen, The Netherlands
| | - Markus Loeffler
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Haertelstrasse 16-18, 04107, Leipzig, Germany
- LIFE Research Centre for Civilization Diseases, University of Leipzig, Philipp-Rosenthal-Straße 27, 04103, Leipzig, Germany
| | - Florian Kronenberg
- Institute of Genetic Epidemiology, Department of Genetics, Medical University of Innsbruck, Innsbruck, Austria
- German Chronic Kidney Disease Study, Berlin, Germany
| | - Dongfeng Gu
- Key Laboratory of Cardiovascular Epidemiology and Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100037, China
- School of Medicine, Southern University of Science and Technology, Shenzhen, China
| | - Jeanette Erdmann
- Institute for Cardiogenetics, University of Lübeck, DZHK (German Research Centre for Cardiovascular Research), Partner Site Hamburg/Lübeck/Kiel, and University Heart Center Lübeck, Lübeck, Germany
| | - Heribert Schunkert
- Deutsches Herzzentrum München, Klinik Für Herz- Und Kreislauferkrankungen, Technische Universität München, Munich, Germany
- Deutsches Zentrum Für Herz-Kreislauf-Forschung (DZHK) E.V., Partner Site Munich Heart Alliance, Munich, Germany
| | - Paul W Franks
- Lund University Diabetes Center, Lund University, Malmö, Sweden
| | - Allan Linneberg
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
- Netherlands Heart Institute, Utrecht, the Netherlands
| | - Amit V Khera
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Division of Cardiology, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Verve Therapeutics, Cambridge, MA, USA
| | - Minna Männikkö
- Northern Finland Birth Cohorts, Infrastructure for Population Studies, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Marjo-Riitta Jarvelin
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Biocenter of Oulu, University of Oulu, Oulu, Finland
| | - Zoltan Kutalik
- University Center for Primary Care and Public Health, University of Lausanne, Rte de Berne 113, 1010, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland
| | - Cucca Francesco
- Institute for Genetic and Biomedical Research, Italian National Council of Research (IRGB CNR), Cagliari, Italy
- University of Sassari, Sassari, Italy
| | - Dennis O Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, the Netherlands
| | - Ko Willems van Dijk
- Department of Internal Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, the Netherlands
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - Hugh Watkins
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, John Radcliffe Hospital, University of Oxford, Oxford, OX3 9DU, UK
| | - David P Strachan
- Population Health Research Institute, St George's, University of London, London, SW17 0RE, UK
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Peter Sever
- National Heart and Lung Institute, Imperial College London, London, W12 0NN, UK
| | - Neil Poulter
- School of Public Health, Imperial College London, London, W12 7RH, UK
| | - Lee-Ming Chuang
- Department of Internal Medicine, National Taiwan University Hospital, No. 7, Chung-Shan South Road, Taipei, Taiwan
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovations (Formerly LABioMed) at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Thomas M Dantoft
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark
| | - Fredrik Karpe
- OCDEM, University of Oxford, Churchill Hospital, Oxford, OX3 7LE, UK
- NIHR Oxford Biomedical Research Centre, Churchill Hospital, Oxford, UK
| | - Matt J Neville
- OCDEM, University of Oxford, Churchill Hospital, Oxford, OX3 7LE, UK
- NIHR Oxford Biomedical Research Centre, Churchill Hospital, Oxford, UK
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Ching-Yu Cheng
- Ocular Epidemiology, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 168751, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, 169857, Singapore
| | - Tien-Yin Wong
- Ocular Epidemiology, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 168751, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, 169857, Singapore
| | - Chiea Chuen Khor
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | - Hengtong Li
- Data Science, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 168751, Singapore
| | - Charumathi Sabanayagam
- Ocular Epidemiology, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 168751, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, 169857, Singapore
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Deutsches Zentrum Für Herz-Kreislauf-Forschung (DZHK) E.V., Partner Site Munich Heart Alliance, Munich, Germany
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
| | - Andrew T Hattersley
- Medical School, University of Exeter, University of Exeter, Exeter, EX2 5DW, UK
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam UMC, the Netherlands
| | - Allegonda H M Willemsen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam UMC, the Netherlands
| | - LAdrienne Cupples
- Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Ave, Boston, MA, 02118, USA
- Framingham Heart Study, National Heart, Lung, and Blood Institute, US National Institutes of Health, Bethesda, MD, USA
| | - Joyce B J van Meurs
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Genetics, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Penny Gordon-Larsen
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, 27599, USA
- Carolina Population Center, University of North Carolina, Chapel Hill, NC, 27516, USA
| | - Wei Huang
- Department of Genetics, Shanghai-MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center at Shanghai, Shanghai, 201203, China
| | - Young Jin Kim
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Chungcheongbuk-Do, South Korea
| | - Yasuharu Tabara
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Nicholas J Wareham
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
- Computational Medicine, Berlin Institute of Health at Charité - Universitätsmedizin, Berlin, Germany
| | - Eleftheria Zeggini
- Wellcome Trust Sanger Institute, Hinxton, CB10 1SA, UK
- Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Technical University of Munich (TUM) and Klinikum Rechts Der Isar, TUM School of Medicine, Munich, Germany
| | - Johanna Kuusisto
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Erik Ingelsson
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, 94305, USA
- Stanford Diabetes Research Center, Stanford University, Stanford, CA, 94305, USA
| | - Goncalo Abecasis
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
- Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - John C Chambers
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK
- Department of Cardiology, Ealing Hospital, London North West University Healthcare NHS Trust, Middlesex, UB1 3HW, UK
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore
- Imperial College Healthcare NHS Trust, Imperial College London, London, W12 0HS, UK
| | - Jaspal S Kooner
- Department of Cardiology, Ealing Hospital, London North West University Healthcare NHS Trust, Middlesex, UB1 3HW, UK
- School of Public Health, Imperial College London, London, W12 7RH, UK
- Imperial College Healthcare NHS Trust, London, W12 0HS, UK
- MRC-PHE Centre for Environment and Health, Imperial College London, London, W2 1PG, UK
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, School of Public Health, Human Genetics, and Environmental Sciences, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, School of Public Health, Human Genetics, and Environmental Sciences, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Scott Hazelhurst
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- School of Electrical and Information Engineering, University of the Witwatersrand, Johannesburg, South Africa
| | - Michèle Ramsay
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Martha Daviglus
- Institute for Minority Health Research, University of Illinois College of Medicine, Chicago, IL, USA
| | - Peter Kraft
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA
| | - Nicholas G Martin
- QIMR Berghofer Medical Research Institute, 300 Herston Road, Brisbane, QLD, 4006, Australia
| | - John B Whitfield
- QIMR Berghofer Medical Research Institute, 300 Herston Road, Brisbane, QLD, 4006, Australia
| | - Shahid Abbas
- Center for Non-Communicable Diseases, Karachi, Sindh, Pakistan
- Faisalabad Institute of Cardiology, Faislabad, Pakistan
| | - Danish Saleheen
- Center for Non-Communicable Diseases, Karachi, Sindh, Pakistan
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
- Department of Cardiology, Columbia University Irving Medical Center, New York, NY, USA
| | - Robin G Walters
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
- Big Data Institute, University of Oxford, Oxford, OX3 7LF, UK
| | - Michael V Holmes
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
- National Institute for Health Research Oxford Biomedical Research Centre, Oxford University Hospitals, Oxford, UK
| | - Corri Black
- Aberdeen Centre for Health Data Science,1:042 Polwarth Building School of Medicine, Medical Science and Nutrition University of Aberdeen, Foresterhill, Aberdeen, AB25 2ZD, UK
| | - Blair H Smith
- Division of Population Health and Genomics, Ninewells Hospital and Medical School, University of Dundee, Dundee, DD1 9SY, UK
| | - Aris Baras
- Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Anne E Justice
- Department of Population Health Sciences, Geisinger Health, Danville, PA, 17822, USA
| | - Julie E Buring
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, 02215, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, 02215, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, 02215, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Charles Kooperberg
- Fred Hutchinson Cancer Center, Division of Public Health Sciences, Seattle, WA, 9810, USA
| | - Gen Tamiya
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, 980-8573, Japan
| | - Masayuki Yamamoto
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, 980-8573, Japan
| | - David A van Heel
- Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Richard C Trembath
- School of Basic and Medical Biosciences, Faculty of Life Sciences and Medicine, King's College London, London, UK
| | - Wei-Qi Wei
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Gail P Jarvik
- Departments of Medicine (Medical Genetics) and Genome Sciences, University of Washington, Washington, USA
| | - Bahram Namjou
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center (CCHMC), Cincinnati, OH, USA
| | - M Geoffrey Hayes
- Center for Genetic Medicine, Northwestern University, Feinberg School of Medicine, Chicago, IL, 60618, USA
- Division of Endocrinology, Metabolism, and Molecular Medicine, Department of Medicine, Northwestern University, Feinberg School of Medicine, Chicago, IL, 60618, USA
- Department of Anthropology, Northwestern University, Evanston, IL, 60208, USA
| | - Marylyn D Ritchie
- Department of Genetics, Institute for Biomedical Informatics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Pekka Jousilahti
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Veikko Salomaa
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Kristian Hveem
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Public Health and Nursing, HUNT Research Centre, NTNU, Norwegian University of Science and Technology, 7600, Levanger, Norway
- Department of Research, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Bjørn Olav Åsvold
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Public Health and Nursing, HUNT Research Centre, NTNU, Norwegian University of Science and Technology, 7600, Levanger, Norway
- Department of Endocrinology, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Michiaki Kubo
- RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Yoichiro Kamatani
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
- Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan
| | - Yoshinori Murakami
- Division of Molecular Pathology, Institute of Medical Science, The University of Tokyo, Tokyo, Japan
| | - Bong-Jo Kim
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Chungcheongbuk-Do, South Korea
| | - Unnur Thorsteinsdottir
- deCODE Genetics/Amgen, Inc. Sturlugata 8, Reykjavik, 102, Iceland
- Faculty of Medicine, University of Iceland, Sæmundargötu 2, Reykjavik, 102, Iceland
| | - Kari Stefansson
- deCODE Genetics/Amgen, Inc. Sturlugata 8, Reykjavik, 102, Iceland
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Sciences, The University of Manchester, Manchester, UK
| | - Jifeng Zhang
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - YEugene Chen
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Yuk-Lam Ho
- VA Boston Healthcare System, Boston, MA, USA
| | - Julie A Lynch
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- University of Massachusetts, Boston, MA, USA
| | - Daniel J Rader
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Philip S Tsao
- VA Palo Alto Health Care Systems, Palo Alto, CA, USA
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Kyong-Mi Chang
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Kelly Cho
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham Women's Hospital, Boston, MA, USA
| | - Christopher J O'Donnell
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham Women's Hospital, Boston, MA, USA
| | - John M Gaziano
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham Women's Hospital, Boston, MA, USA
| | - Peter W F Wilson
- Atlanta VA Health Care System, Decatur, GA, USA
- Division of Cardiology, Emory University School of Medicine, Atlanta, GA, USA
| | - Timothy M Frayling
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, EX2 5DW, UK
| | - Joel N Hirschhorn
- Boston Children's Hospital, EndocrinologyBoston, MA, 02115, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Departments of Pediatrics and Genetics, Harvard Medical School, Boston, MA, USA
| | - Sekar Kathiresan
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medicine, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - Yan V Sun
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
- Atlanta VA Health Care System, Decatur, GA, USA
| | - Andrew P Morris
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Sciences, The University of Manchester, Manchester, UK
| | - Michael Boehnke
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Christopher D Brown
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Pradeep Natarajan
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Cardiology Division, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Panos Deloukas
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
- Princess Al-Jawhara Al-Brahim Centre of Excellence in Research of Hereditary Disorders (PACER-HD), King Abdulaziz University, Jeddah, Saudi Arabia
| | - Cristen J Willer
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, 48109, USA.
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA.
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, 48109, USA.
| | - Themistocles L Assimes
- VA Palo Alto Health Care Systems, Palo Alto, CA, USA
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Gina M Peloso
- Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Ave, Boston, MA, 02118, USA.
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Li Z, Li X, Zhou H, Gaynor SM, Selvaraj MS, Arapoglou T, Quick C, Liu Y, Chen H, Sun R, Dey R, Arnett DK, Auer PL, Bielak LF, Bis JC, Blackwell TW, Blangero J, Boerwinkle E, Bowden DW, Brody JA, Cade BE, Conomos MP, Correa A, Cupples LA, Curran JE, de Vries PS, Duggirala R, Franceschini N, Freedman BI, Göring HHH, Guo X, Kalyani RR, Kooperberg C, Kral BG, Lange LA, Lin BM, Manichaikul A, Manning AK, Martin LW, Mathias RA, Meigs JB, Mitchell BD, Montasser ME, Morrison AC, Naseri T, O'Connell JR, Palmer ND, Peyser PA, Psaty BM, Raffield LM, Redline S, Reiner AP, Reupena MS, Rice KM, Rich SS, Smith JA, Taylor KD, Taub MA, Vasan RS, Weeks DE, Wilson JG, Yanek LR, Zhao W, Rotter JI, Willer CJ, Natarajan P, Peloso GM, Lin X. A framework for detecting noncoding rare-variant associations of large-scale whole-genome sequencing studies. Nat Methods 2022; 19:1599-1611. [PMID: 36303018 PMCID: PMC10008172 DOI: 10.1038/s41592-022-01640-x] [Citation(s) in RCA: 54] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2021] [Accepted: 09/06/2022] [Indexed: 02/07/2023]
Abstract
Large-scale whole-genome sequencing studies have enabled analysis of noncoding rare-variant (RV) associations with complex human diseases and traits. Variant-set analysis is a powerful approach to study RV association. However, existing methods have limited ability in analyzing the noncoding genome. We propose a computationally efficient and robust noncoding RV association detection framework, STAARpipeline, to automatically annotate a whole-genome sequencing study and perform flexible noncoding RV association analysis, including gene-centric analysis and fixed window-based and dynamic window-based non-gene-centric analysis by incorporating variant functional annotations. In gene-centric analysis, STAARpipeline uses STAAR to group noncoding variants based on functional categories of genes and incorporate multiple functional annotations. In non-gene-centric analysis, STAARpipeline uses SCANG-STAAR to incorporate dynamic window sizes and multiple functional annotations. We apply STAARpipeline to identify noncoding RV sets associated with four lipid traits in 21,015 discovery samples from the Trans-Omics for Precision Medicine (TOPMed) program and replicate several of them in an additional 9,123 TOPMed samples. We also analyze five non-lipid TOPMed traits.
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Grants
- R01 DK078616 NIDDK NIH HHS
- U01 HG007417 NHGRI NIH HHS
- KL2 TR001100 NCATS NIH HHS
- R01 HL112064 NHLBI NIH HHS
- N01-HC-95160 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- R35 HG010692 NHGRI NIH HHS
- U01-HL054472 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- R01-HL142711 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- R01-DK071891 U.S. Department of Health & Human Services | NIH | National Institute of Diabetes and Digestive and Kidney Diseases (National Institute of Diabetes & Digestive & Kidney Diseases)
- F30 HL149180 NHLBI NIH HHS
- R01 NR019628 NINR NIH HHS
- R01 HL113323 NHLBI NIH HHS
- N01-HC-95166 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- UL1RR033176 U.S. Department of Health & Human Services | NIH | National Center for Research Resources (NCRR)
- R01 HL132947 NHLBI NIH HHS
- P30 DK040561 NIDDK NIH HHS
- U01 HL137183 NHLBI NIH HHS
- R01-HL127564 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- P30 CA016672 NCI NIH HHS
- R01-HL071051 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- R01 HL104135 NHLBI NIH HHS
- T32 HL144442 NHLBI NIH HHS
- R35 CA197449 NCI NIH HHS
- P30 ES010126 NIEHS NIH HHS
- DP5 OD029586 NIH HHS
- R01-NS058700 U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke (NINDS)
- R01 HL123915 NHLBI NIH HHS
- R01 HL120393 NHLBI NIH HHS
- R01HL071259 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- R01 HL046380 NHLBI NIH HHS
- R01HL071251, R01HL071258, R01HL071259 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- U54 HG003067 NHGRI NIH HHS
- 75N92020D00003 NHLBI NIH HHS
- K01 AG059898 NIA NIH HHS
- U01 DK085524 NIDDK NIH HHS
- KL2 TR002542 NCATS NIH HHS
- R01-HL055673-18S1 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- R03 HL141439 NHLBI NIH HHS
- HHSN268201500001I NHLBI NIH HHS
- R01-MH078143, R01-MH078111, R01-MH083824 U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH)
- U01 DK062413 NIDDK NIH HHS
- R01 HL109946 NHLBI NIH HHS
- U01-HL054495 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- K01 HL136700 NHLBI NIH HHS
- U19 CA203654 NCI NIH HHS
- R01-DK078616 U.S. Department of Health & Human Services | NIH | National Institute of Diabetes and Digestive and Kidney Diseases (National Institute of Diabetes & Digestive & Kidney Diseases)
- U01 HL080295 NHLBI NIH HHS
- NO1-HC-25195 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- R01 HG006703 NHGRI NIH HHS
- UL1-TR-001420 U.S. Department of Health & Human Services | NIH | National Center for Advancing Translational Sciences (NCATS)
- U01 HG012064 NHGRI NIH HHS
- R35-CA197449 U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)
- P30 ES005605 NIEHS NIH HHS
- R01 AR042742 NIAMS NIH HHS
- R21 HL140385 NHLBI NIH HHS
- HHSN268201800015I NHLBI NIH HHS
- U01 HL130114 NHLBI NIH HHS
- R01 HL117191 NHLBI NIH HHS
- R01 HG009974 NHGRI NIH HHS
- U01-HL054473 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- R01 DK113003 NIDDK NIH HHS
- UL1RR033176 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- R01 HL059367 NHLBI NIH HHS
- R24 AG047115 NIA NIH HHS
- U01-HL137181 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- P01 HL107202 NHLBI NIH HHS
- NR0224103 U.S. Department of Health & Human Services | NIH | National Institute of Nursing Research (NINR)
- P50 HL118006 NHLBI NIH HHS
- U01-HL72518, HL087698, HL49762, HL59684, HL58625, HL071025, HL112064 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- U01 HL120393 NHLBI NIH HHS
- R01 DK117445 NIDDK NIH HHS
- R01-AG058921 U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging)
- R03-HL154284 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- UL1-TR-000040, UL1-TR-001079, UL1-TR-001420, UL1-TR-001881 U.S. Department of Health & Human Services | NIH | National Center for Advancing Translational Sciences (NCATS)
- R01 AG058921 NIA NIH HHS
- R01 HL129132 NHLBI NIH HHS
- R01 HL113338 NHLBI NIH HHS
- HHSN268201800012I NHLBI NIH HHS
- R01 HL153805 NHLBI NIH HHS
- R01 DK072193 NIDDK NIH HHS
- R01 HL137922 NHLBI NIH HHS
- R01 AI079139 NIAID NIH HHS
- N01-HC-95164 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- U01-DK085524 U.S. Department of Health & Human Services | NIH | National Institute of Diabetes and Digestive and Kidney Diseases (National Institute of Diabetes & Digestive & Kidney Diseases)
- U19 AI111224 NIAID NIH HHS
- R35 HL135824 NHLBI NIH HHS
- 75N92019D00031 NHLBI NIH HHS
- R01 DK110113 NIDDK NIH HHS
- N01-HC-95159, N01-HC-95160, N01-HC-95161, N01-HC-95162 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- N01-HC-95165 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- R01 HL138737 NHLBI NIH HHS
- P30 DK079626 NIDDK NIH HHS
- R01 NS058700 NINDS NIH HHS
- R01 HL127564 NHLBI NIH HHS
- T32 HG000040 NHGRI NIH HHS
- DK063491 U.S. Department of Health & Human Services | NIH | National Institute of Diabetes and Digestive and Kidney Diseases (National Institute of Diabetes & Digestive & Kidney Diseases)
- R01 HL141845 NHLBI NIH HHS
- R01 DK075787 NIDDK NIH HHS
- R01 AR072199 NIAMS NIH HHS
- R01 HL120854 NHLBI NIH HHS
- R01 HL163560 NHLBI NIH HHS
- R01HL071258 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- U01-HG009088 U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute (NHGRI)
- R01 HL163972 NHLBI NIH HHS
- K23 HL123778 NHLBI NIH HHS
- U01 HL137181 NHLBI NIH HHS
- R01 MH078111 NIMH NIH HHS
- HHSN268201700005I NHLBI NIH HHS
- N01-HC-95159 U.S. Department of Health & Human Services | National Institutes of Health (NIH)
- R01-HL113323 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- R01 HL141944 NHLBI NIH HHS
- R01 HL119443 NHLBI NIH HHS
- R01-HL071051, R01-HL071205, R01HL071250 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- P60-AG10484 U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging)
- 75N92020D00007 NHLBI NIH HHS
- UM1 AI068634 NIAID NIH HHS
- HHSN268201500003I NHLBI NIH HHS
- HHSN268201700004I NHLBI NIH HHS
- N01-HC-95163 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- R01-HL071205 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- F30 HL107066 NHLBI NIH HHS
- R01-HL153805 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- R01 HL105756 NHLBI NIH HHS
- K01 HL125751 NHLBI NIH HHS
- R01 HL067348 NHLBI NIH HHS
- T32 HL007208 NHLBI NIH HHS
- R01 HL142711 NHLBI NIH HHS
- R35 HL135818 NHLBI NIH HHS
- R01-HL92301 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- T32 GM074897 NIGMS NIH HHS
- I01 BX005295 BLRD VA
- 75N92020D00001 NHLBI NIH HHS
- R01 HL113326 NHLBI NIH HHS
- R00 HL129045 NHLBI NIH HHS
- UL1-TR-000040 U.S. Department of Health & Human Services | NIH | National Center for Advancing Translational Sciences (NCATS)
- UL1-TR-001079 U.S. Department of Health & Human Services | NIH | National Center for Advancing Translational Sciences (NCATS)
- U01 HL072524 NHLBI NIH HHS
- R35-HL135818 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- K08 HL140203 NHLBI NIH HHS
- N01-HC-95162 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- K08 HL141601 NHLBI NIH HHS
- 75N92020D00005 NHLBI NIH HHS
- R01-DK117445 U.S. Department of Health & Human Services | NIH | National Institute of Diabetes and Digestive and Kidney Diseases (National Institute of Diabetes & Digestive & Kidney Diseases)
- R01-AR48797 U.S. Department of Health & Human Services | NIH | National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
- R56 AG058543 NIA NIH HHS
- U19 AI077439 NIAID NIH HHS
- R01 HL142028 NHLBI NIH HHS
- 75N92020D00004 NHLBI NIH HHS
- HHSN268201800011I NHLBI NIH HHS
- R35 GM127131 NIGMS NIH HHS
- U01 HL137880 NHLBI NIH HHS
- R01 HG010869 NHGRI NIH HHS
- R01-HL133040 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- HHSN268201700003I NHLBI NIH HHS
- R01HL071250 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- N01-HC-95168 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- R01 HL148239 NHLBI NIH HHS
- U01-HL137162 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- R01 AI132476 NIAID NIH HHS
- T32 GM007205 NIGMS NIH HHS
- HHSN268201800010I NHLBI NIH HHS
- R01-HL092577-06S1 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- UL1-TR-001881 U.S. Department of Health & Human Services | NIH | National Center for Advancing Translational Sciences (NCATS)
- R01-HL104135-04S1 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- R01 HL132320 NHLBI NIH HHS
- U01 DK078616 NIDDK NIH HHS
- HHSN268201700001I NHLBI NIH HHS
- R01-HL141944 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- U01 HL137162 NHLBI NIH HHS
- R01 HG005701 NHGRI NIH HHS
- 75N92020D00001, 75N92020D00002, 75N92020D00003, 75N92020D00004 U.S. Department of Health & Human Services | National Institutes of Health (NIH)
- R01 HL143221 NHLBI NIH HHS
- R01 HL142992 NHLBI NIH HHS
- K01 HL129039 NHLBI NIH HHS
- R01 HL133870 NHLBI NIH HHS
- R01 DA037904 NIDA NIH HHS
- R21 HL123677 NHLBI NIH HHS
- R01 DK071891 NIDDK NIH HHS
- HHSN268201800001I U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- 75N92020D00002 NHLBI NIH HHS
- K01 HL130609 NHLBI NIH HHS
- N01-HC-95167 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- T32 HL007374 NHLBI NIH HHS
- N01-HC-95169 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- U01-DK078616 U.S. Department of Health & Human Services | NIH | National Institute of Diabetes and Digestive and Kidney Diseases (National Institute of Diabetes & Digestive & Kidney Diseases)
- R01 AR063611 NIAMS NIH HHS
- KL2TR002490 U.S. Department of Health & Human Services | NIH | National Center for Advancing Translational Sciences (NCATS)
- R03 HL154284 NHLBI NIH HHS
- M01-RR000052 U.S. Department of Health & Human Services | NIH | National Center for Research Resources (NCRR)
- 75N92020D00006 NHLBI NIH HHS
- S10 OD020069 NIH HHS
- R01 MD012765 NIMHD NIH HHS
- N01-HC-95161 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- HHSN268201700002I NHLBI NIH HHS
- R01 HL151855 NHLBI NIH HHS
- K23 HL138461 NHLBI NIH HHS
- U01 CA182913 NCI NIH HHS
- UG3 HL151865 NHLBI NIH HHS
- F32 HL150992 NHLBI NIH HHS
- R01-MD012765 U.S. Department of Health & Human Services | NIH | National Institute on Minority Health and Health Disparities (NIMHD)
- 75N92020D00005, 75N92020D00006, 75N92020D00007 U.S. Department of Health & Human Services | National Institutes of Health (NIH)
- R01 MH101244 NIMH NIH HHS
- U01 HG009088 NHGRI NIH HHS
- N01-HC-95163, N01-HC-95164, N01-HC-95165, N01-HC-95166 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- P42 ES016454 NIEHS NIH HHS
- UM1 DK078616 NIDDK NIH HHS
- U01-HL054509 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- R35-HL135824 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- M01-RR07122 U.S. Department of Health & Human Services | NIH | National Center for Research Resources (NCRR)
- U01 DK105561 NIDDK NIH HHS
- U01-HL072524 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- P20 GM121334 NIGMS NIH HHS
- N01-HC-95167, N01-HC-95168, N01-HC-95169 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- R01 HL131565 NHLBI NIH HHS
- R01HL071251 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- R13 CA124365 NCI NIH HHS
- R01-HL045522 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- P01 HL132825 NHLBI NIH HHS
- R01 HL118267 NHLBI NIH HHS
- HHSN268201800013I NIMHD NIH HHS
- R01-HL67348 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- U54 GM115428 NIGMS NIH HHS
- R01 HL055673 NHLBI NIH HHS
- HHSN268201600018C, HHSN268201600001C, HHSN268201600002C, HHSN268201600003C, and HHSN268201600004C U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- UM1-DK078616 U.S. Department of Health & Human Services | NIH | National Institute of Diabetes and Digestive and Kidney Diseases (National Institute of Diabetes & Digestive & Kidney Diseases)
- R01 HL149683 NHLBI NIH HHS
- R01 HL092301 NHLBI NIH HHS
- P30 DK020595 NIDDK NIH HHS
- R01 HL149836 NHLBI NIH HHS
- K08 HL145095 NHLBI NIH HHS
- K01 HL135405 NHLBI NIH HHS
- R03 OD030608 NIH HHS
- HHSN268201800014I NHLBI NIH HHS
- R01-HL113338 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- F32-HL085989 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- UM1 AI068636 NIAID NIH HHS
- R01 AG057381 NIA NIH HHS
- U19-CA203654 U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)
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Affiliation(s)
- Zilin Li
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, USA.
| | - Xihao Li
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Hufeng Zhou
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Sheila M Gaynor
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Margaret Sunitha Selvaraj
- Center for Genomic Medicine and Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Theodore Arapoglou
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Corbin Quick
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Yaowu Liu
- School of Statistics, Southwestern University of Finance and Economics, Chengdu, China
| | - Han Chen
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Ryan Sun
- Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Rounak Dey
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Donna K Arnett
- Dean's Office, University of Kentucky, College of Public Health, Lexington, KY, USA
| | - Paul L Auer
- Division of Biostatistics, Institute for Health & Equity and Cancer Center, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Lawrence F Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Thomas W Blackwell
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, The University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Donald W Bowden
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Brian E Cade
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Matthew P Conomos
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Adolfo Correa
- Jackson Heart Study, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - L Adrienne Cupples
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Framingham Heart Study, National Heart, Lung, and Blood Institute and Boston University, Framingham, MA, USA
| | - Joanne E Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, The University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Ravindranath Duggirala
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, The University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - Nora Franceschini
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Barry I Freedman
- Department of Internal Medicine, Nephrology, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Harald H H Göring
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, The University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Rita R Kalyani
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Brian G Kral
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Leslie A Lange
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Bridget M Lin
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC, USA
| | - Ani Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Alisa K Manning
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Metabolism Program, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital, Boston, MA, USA
| | - Lisa W Martin
- Division in Cardiology, George Washington School of Medicine and Health Sciences, Washington, DC, USA
| | - Rasika A Mathias
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - James B Meigs
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Braxton D Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Geriatrics Research and Education Clinical Center, Baltimore VA Medical Center, Baltimore, MD, USA
| | - May E Montasser
- Division of Endocrinology, Diabetes, and Nutrition, Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Take Naseri
- Ministry of Health, Government of Samoa, Apia, Samoa
| | - Jeffrey R O'Connell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Nicholette D Palmer
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Departments of Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
- Division of Pulmonary, Critical Care, and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Alexander P Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | | | - Kenneth M Rice
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Margaret A Taub
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Ramachandran S Vasan
- Framingham Heart Study, National Heart, Lung, and Blood Institute and Boston University, Framingham, MA, USA
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Daniel E Weeks
- Department of Human Genetics and Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA
| | - James G Wilson
- Division of Cardiology, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Lisa R Yanek
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Cristen J Willer
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Pradeep Natarajan
- Center for Genomic Medicine and Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Gina M Peloso
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Framingham Heart Study, National Heart, Lung, and Blood Institute and Boston University, Framingham, MA, USA
| | - Xihong Lin
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
- Department of Statistics, Harvard University, Cambridge, MA, USA.
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Pleiotropic Effects of APOB Variants on Lipid Profiles, Metabolic Syndrome, and the Risk of Diabetes Mellitus. Int J Mol Sci 2022; 23:ijms232314963. [PMID: 36499290 PMCID: PMC9735756 DOI: 10.3390/ijms232314963] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 11/18/2022] [Accepted: 11/23/2022] [Indexed: 12/03/2022] Open
Abstract
Apolipoprotein B (ApoB) plays a crucial role in lipid and lipoprotein metabolism. The effects of APOB locus variants on lipid profiles, metabolic syndrome, and the risk of diabetes mellitus (DM) in Asian populations are unclear. We included 1478 Taiwan Biobank participants with whole-genome sequence (WGS) data and 115,088 TWB participants with Axiom genome-wide CHB array data and subjected them to genotype-phenotype analyses using APOB locus variants. Five APOB nonsynonymous mutations, including Asian-specific rs144467873 and rs13306194 variants, were selected from participants with the WGS data. Using a combination of regional association studies, a linkage disequilibrium map, and multivariate analysis, we revealed that the APOB locus variants rs144467873, rs13306194, and rs1367117 were independently associated with total, low-density lipoprotein (LDL), and non-high-density lipoprotein (non-HDL) cholesterol levels; rs1318006 was associated with HDL cholesterol levels; rs13306194 and rs35131127 were associated with serum triglyceride levels; rs144467873, rs13306194, rs56213756, and rs679899 were associated with remnant cholesterol levels; and rs144467873 and rs4665709 were associated with metabolic syndrome. Mendelian randomization (MR) analyses conducted using weighted genetic risk scores from three or two LDL-cholesterol-level-associated APOB variants revealed significant association with prevalent DM (p = 0.0029 and 8.2 × 10-5, respectively), which became insignificant after adjustment for LDL-C levels. In conclusion, these results indicate that common and rare APOB variants are independently associated with various lipid levels and metabolic syndrome in Taiwanese individuals. MR analyses supported APOB variants associated with the risk of DM through their associations with LDL cholesterol levels.
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Wen Y, Chen YQ, Konrad RJ. The Regulation of Triacylglycerol Metabolism and Lipoprotein Lipase Activity. Adv Biol (Weinh) 2022; 6:e2200093. [PMID: 35676229 DOI: 10.1002/adbi.202200093] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 05/03/2022] [Indexed: 01/28/2023]
Abstract
Triacylglycerol (TG) metabolism is tightly regulated to maintain a pool of TG within circulating lipoproteins that can be hydrolyzed in a tissue-specific manner by lipoprotein lipase (LPL) to enable the delivery of fatty acids to adipose or oxidative tissues as needed. Elevated serum TG concentrations, which result from a deficiency of LPL activity or, more commonly, an imbalance in the regulation of tissue-specific LPL activities, have been associated with an increased risk of atherosclerotic cardiovascular disease through multiple studies. Among the most critical LPL regulators are the angiopoietin-like (ANGPTL) proteins ANGPTL3, ANGPTL4, and ANGPTL8, and a number of different apolipoproteins including apolipoprotein A5 (ApoA5), apolipoprotein C2 (ApoC2), and apolipoprotein C3 (ApoC3). These ANGPTLs and apolipoproteins work together to orchestrate LPL activity and therefore play pivotal roles in TG partitioning, hydrolysis, and utilization. This review summarizes the mechanisms of action, epidemiological findings, and genetic data most relevant to these ANGPTLs and apolipoproteins. The interplay between these important regulators of TG metabolism in both fasted and fed states is highlighted with a holistic view toward understanding key concepts and interactions. Strategies for developing safe and effective therapeutics to reduce circulating TG by selectively targeting these ANGPTLs and apolipoproteins are also discussed.
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Affiliation(s)
- Yi Wen
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, 46285, USA
| | - Yan Q Chen
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, 46285, USA
| | - Robert J Konrad
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, 46285, USA
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Kim K, Ginsberg HN, Choi SH. New, Novel Lipid-Lowering Agents for Reducing Cardiovascular Risk: Beyond Statins. Diabetes Metab J 2022; 46:517-532. [PMID: 35929170 PMCID: PMC9353557 DOI: 10.4093/dmj.2022.0198] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Accepted: 07/20/2022] [Indexed: 11/24/2022] Open
Abstract
Statins are the cornerstone of the prevention and treatment of atherosclerotic cardiovascular disease (ASCVD). However, even under optimal statin therapy, a significant residual ASCVD risk remains. Therefore, there has been an unmet clinical need for novel lipid-lowering agents that can target low-density lipoprotein cholesterol (LDL-C) and other atherogenic particles. During the past decade, several drugs have been developed for the treatment of dyslipidemia. Inclisiran, a small interfering RNA that targets proprotein convertase subtilisin/kexin type 9 (PCSK9), shows comparable effects to that of PCSK9 monoclonal antibodies. Bempedoic acid, an ATP citrate lyase inhibitor, is a valuable treatment option for the patients with statin intolerance. Pemafibrate, the first selective peroxisome proliferator-activated receptor alpha modulator, showed a favorable benefit-risk balance in phase 2 trial, but the large clinical phase 3 trial (PROMINENT) was recently stopped for futility based on a late interim analysis. High dose icosapent ethyl, a modified eicosapentaenoic acid preparation, shows cardiovascular benefits. Evinacumab, an angiopoietin-like 3 (ANGPTL3) monoclonal antibody, reduces plasma LDL-C levels in patients with refractory hypercholesterolemia. Novel antisense oligonucleotides targeting apolipoprotein C3 (apoC3), ANGPTL3, and lipoprotein(a) have significantly attenuated the levels of their target molecules with beneficial effects on associated dyslipidemias. Apolipoprotein A1 (apoA1) is considered as a potential treatment to exploit the athero-protective effects of high-density lipoprotein cholesterol (HDL-C), but solid clinical evidence is necessary. In this review, we discuss the mode of action and clinical outcomes of these novel lipid-lowering agents beyond statins.
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Affiliation(s)
- Kyuho Kim
- Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam,
Korea
- Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul,
Korea
| | - Henry N. Ginsberg
- Department of Preventive Medicine and Nutrition, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY,
USA
| | - Sung Hee Choi
- Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam,
Korea
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul,
Korea
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Post-Transcriptional Effects of miRNAs on PCSK7 Expression and Function: miR-125a-5p, miR-143-3p, and miR-409-3p as Negative Regulators. Metabolites 2022; 12:metabo12070588. [PMID: 35888711 PMCID: PMC9323720 DOI: 10.3390/metabo12070588] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 06/17/2022] [Accepted: 06/20/2022] [Indexed: 12/14/2022] Open
Abstract
The regulatory mechanism of PCSK7 gene is still unknown, although its encoded protein PC7 is the most ancient and highly conserved of all proprotein convertases and exhibits enzymatic and non-enzymatic functions in liver triglyceride regulation. Bioinformatics algorithms were used to predict regulatory microRNAs (miRNAs) of PCSK7 expression. This led to the identification of four miRNAs, namely miR-125a-5p, miR-143-3p, miR-409-3p, and miR-320a-3p, with potential binding sites on the 3′-untranslated region (3′-UTR) of human PCSK7 mRNA. The expression patterns of these miRNAs and PCSK7 mRNA were assessed in three different cell lines with quantitative polymerase chain reaction (qPCR), which revealed reciprocal expression patterns between the expression levels of the four selected miRNAs and PCSK7. Next, the interactions and effects of these miRNAs on PCSK7 expression levels were investigated via cell-based expression analysis, dual-luciferase assay, and Western blot analysis. The data revealed that PCSK7 mRNA levels decreased in cells transfected with vectors overexpressing miR-125a-5p, miR-143-3p, and miR-409-3p, but not miR-320a-3p. The dual-luciferase assay demonstrated that the above three miRNAs could directly interact with putative target sites in PCSK7 3′-UTR and regulate its expression, whereas miR-320-3p exhibited no interaction. Western blot analysis further revealed that the overexpression of miR-125a-5p in Huh7 cells inhibits the expression and ability of PC7 to cleave human transferrin receptor 1. Our results support a regulatory role of these miRNAs on PCSK7 expression and function and open the way to assess their roles in the regulation of PC7 activity in vivo in the development of hepatic steatosis.
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Ma J, Hao X, Nie X, Yang S, Zhou M, Wang D, Wang B, Cheng M, Ye Z, Xie Y, Wang C, Chen W. Longitudinal relationships of polycyclic aromatic hydrocarbons exposure and genetic susceptibility with blood lipid profiles. ENVIRONMENT INTERNATIONAL 2022; 164:107259. [PMID: 35500530 DOI: 10.1016/j.envint.2022.107259] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/03/2021] [Revised: 03/22/2022] [Accepted: 04/20/2022] [Indexed: 06/14/2023]
Abstract
OBJECTIVE We aim to analyze the effects of polycyclic aromatic hydrocarbons (PAHs) exposure and genetic predisposition on blood lipid through a longitudinal epidemiological study. METHODS We enrolled 4,356 observations who participated at baseline (n = 2,435) and 6-year follow-up (n = 1,921) from Wuhan-Zhuhai cohort. Ten urinary PAHs metabolites and blood lipid (i.e., total cholesterol [TC], triglycerides [TG], low-density lipoprotein cholesterol [LDL-C], and high-density lipoprotein cholesterol [HDL-C]) were measured at both baseline and follow-up. The polygenic risk scores (PRS) of blood lipid were constructed by the corresponding genome-wide association studies. Linear mixed models were fit to identify associations between urinary PAHs metabolites, blood lipid, and lipid-PRSs in the repeated-measure analysis. Besides, longitudinal relationships of blood lipid with urinary PAHs metabolites and respective lipid-PRSs were examined by using linear regression models. RESULTS Compared with subjects who had persistently low urinary total hydroxyphenanthrene (ΣOHPh), those with persistently high levels had an average increase of 0.137 mmol/l for TC and 0.129 mmol/l for LDL-C over 6 years. Each 1-unit increase of TC-, TG-, LDL-C-, and HDL-C-specific PRS were associated with an average increase of 0.438 mmol/l for TC, 0.264 mmol/l for TG, 0.198 mmol/l for LDL-C, and 0.043 mmol/l for HDL-C over 6 years, respectively. Compared with subjects who had low genetic risk and persistently low ΣOHPh, subjects with high LDL-specific PRS and persistently high ΣOHPh had an average increase of 0.652 mmol/l for LDL-C. CONCLUSIONS Our results suggest that high-level ΣOHPh exposure is associated with an average increase of LDL-C over 6 years, and those relationships can be aggravated by a higher LDL-C-genetic risk. No significant relationships were observed between other PAHs metabolites (including hydroxynaphthalene, hydroxyfluorene, and hydroxypyrene) and blood lipid changes over 6 years. Our findings emphasize the importance of preventing PAHs exposure, particularly among those with a higher genetic predisposition of hyperlipidemia.
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Affiliation(s)
- Jixuan Ma
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Xingjie Hao
- Department of Epidemiology & Statistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Xiuquan Nie
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Shijie Yang
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Min Zhou
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Dongming Wang
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Bin Wang
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Man Cheng
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Zi Ye
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Yujia Xie
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Chaolong Wang
- Department of Epidemiology & Statistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China.
| | - Weihong Chen
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China.
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Choudhury A, Brandenburg JT, Chikowore T, Sengupta D, Boua PR, Crowther NJ, Agongo G, Asiki G, Gómez-Olivé FX, Kisiangani I, Maimela E, Masemola-Maphutha M, Micklesfield LK, Nonterah EA, Norris SA, Sorgho H, Tinto H, Tollman S, Graham SE, Willer CJ, Hazelhurst S, Ramsay M. Meta-analysis of sub-Saharan African studies provides insights into genetic architecture of lipid traits. Nat Commun 2022; 13:2578. [PMID: 35546142 PMCID: PMC9095599 DOI: 10.1038/s41467-022-30098-w] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Accepted: 04/18/2022] [Indexed: 12/30/2022] Open
Abstract
Genetic associations for lipid traits have identified hundreds of variants with clear differences across European, Asian and African studies. Based on a sub-Saharan-African GWAS for lipid traits in the population cross-sectional AWI-Gen cohort (N = 10,603) we report a novel LDL-C association in the GATB region (P-value=1.56 × 10-8). Meta-analysis with four other African cohorts (N = 23,718) provides supporting evidence for the LDL-C association with the GATB/FHIP1A region and identifies a novel triglyceride association signal close to the FHIT gene (P-value =2.66 × 10-8). Our data enable fine-mapping of several well-known lipid-trait loci including LDLR, PMFBP1 and LPA. The transferability of signals detected in two large global studies (GLGC and PAGE) consistently improves with an increase in the size of the African replication cohort. Polygenic risk score analysis shows increased predictive accuracy for LDL-C levels with the narrowing of genetic distance between the discovery dataset and our cohort. Novel discovery is enhanced with the inclusion of African data.
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Affiliation(s)
- Ananyo Choudhury
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
| | - Jean-Tristan Brandenburg
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Tinashe Chikowore
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- South African Medical Research Council/University of the Witwatersrand Developmental Pathways for Health Research Unit, Department of Paediatrics, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Dhriti Sengupta
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Palwende Romuald Boua
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Clinical Research Unit of Nanoro, Institut de Recherche en Sciences de la Santè, Nanoro, Burkina Faso
| | - Nigel J Crowther
- Department of Chemical Pathology, National Health Laboratory Service, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Godfred Agongo
- Navrongo Health Research Centre, Ghana Health Service, Navrongo, Ghana
- C.K. Tedam University of Technology and Applied Sciences, Navrongo, Ghana
| | - Gershim Asiki
- African Population and Health Research Center, Nairobi, Kenya
| | - F Xavier Gómez-Olivé
- MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | | | - Eric Maimela
- Department of Public Health, School of Health Care Sciences, Faculty of Health Sciences, University of Limpopo, Polokwane, South Africa
| | - Matshane Masemola-Maphutha
- Department of Pathology and Medical Sciences, School of Health Care Sciences, Faculty of Health Sciences, University of Limpopo, Polokwane, South Africa
| | - Lisa K Micklesfield
- South African Medical Research Council/University of the Witwatersrand Developmental Pathways for Health Research Unit, Department of Paediatrics, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | | | - Shane A Norris
- South African Medical Research Council/University of the Witwatersrand Developmental Pathways for Health Research Unit, Department of Paediatrics, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Hermann Sorgho
- Clinical Research Unit of Nanoro, Institut de Recherche en Sciences de la Santè, Nanoro, Burkina Faso
| | - Halidou Tinto
- Clinical Research Unit of Nanoro, Institut de Recherche en Sciences de la Santè, Nanoro, Burkina Faso
| | - Stephen Tollman
- MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Sarah E Graham
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Cristen J Willer
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, 48019, USA
| | - Scott Hazelhurst
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- School of Electrical and Information Engineering, University of the Witwatersrand, Johannesburg, South Africa
| | - Michèle Ramsay
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
- Division of Human Genetics, National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
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An Amish founder population reveals rare-population genetic determinants of the human lipidome. Commun Biol 2022; 5:334. [PMID: 35393526 PMCID: PMC8989972 DOI: 10.1038/s42003-022-03291-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 03/17/2022] [Indexed: 12/02/2022] Open
Abstract
Identifying the genetic determinants of inter-individual variation in lipid species (lipidome) may provide deeper understanding and additional insight into the mechanistic effect of complex lipidomic pathways in CVD risk and progression beyond simple traditional lipids. Previous studies have been largely population based and thus only powered to discover associations with common genetic variants. Founder populations represent a powerful resource to accelerate discovery of previously unknown biology associated with rare population alleles that have risen to higher frequency due to genetic drift. We performed a genome-wide association scan of 355 lipid species in 650 individuals from the Amish founder population including 127 lipid species not previously tested. To the best of our knowledge, we report for the first time the lipid species associated with two rare-population but Amish-enriched lipid variants: APOB_rs5742904 and APOC3_rs76353203. We also identified novel associations for 3 rare-population Amish-enriched loci with several sphingolipids and with proposed potential functional/causal variant in each locus including GLTPD2_rs536055318, CERS5_rs771033566, and AKNA_rs531892793. We replicated 7 previously known common loci including novel associations with two sterols: androstenediol with UGT locus and estriol with SLC22A8/A24 locus. Our results show the double power of founder populations and detailed lipidome to discover novel trait-associated variants. A GWAS of 355 lipid species in the Old Order Amish founder population reveals associations between Amish-enriched loci and several sphingolipids.
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49
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Balasubramaniam D, Schroeder O, Russell AM, Fitchett JR, Austin AK, Beyer TP, Chen YQ, Day JW, Ehsani M, Heng AR, Zhen EY, Davies J, Glaesner W, Jones BE, Siegel RW, Qian YW, Konrad RJ. An anti-ANGPTL3/8 antibody decreases circulating triglycerides by binding to a LPL-inhibitory leucine zipper-like motif. J Lipid Res 2022; 63:100198. [PMID: 35307397 PMCID: PMC9036128 DOI: 10.1016/j.jlr.2022.100198] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 02/24/2022] [Accepted: 03/11/2022] [Indexed: 12/20/2022] Open
Abstract
Triglycerides (TG) are required for fatty acid transport and storage and are essential for human health. Angiopoietin-like-protein 8 (ANGPTL8) has previously been shown to form a complex with ANGPTL3 that increases circulating TG by potently inhibiting LPL. We also recently showed that the TG-lowering apolipoprotein A5 (ApoA5) decreases TG levels by suppressing ANGPTL3/8-mediated LPL inhibition. To understand how LPL binds ANGPTL3/8 and ApoA5 blocks this interaction, we used hydrogen-deuterium exchange mass-spectrometry and molecular modeling to map binding sites of LPL and ApoA5 on ANGPTL3/8. Remarkably, we found that LPL and ApoA5 both bound a unique ANGPTL3/8 epitope consisting of N-terminal regions of ANGPTL3 and ANGPTL8 that are unmasked upon formation of the ANGPTL3/8 complex. We further used ANGPTL3/8 as an immunogen to develop an antibody targeting this same epitope. After refocusing on antibodies that bound ANGPTL3/8, as opposed to ANGPTL3 or ANGPTL8 alone, we utilized bio-layer interferometry to select an antibody exhibiting high-affinity binding to the desired epitope. We revealed an ANGPTL3/8 leucine zipper-like motif within the anti-ANGPTL3/8 epitope, the LPL-inhibitory region, and the ApoA5-interacting region, suggesting the mechanism by which ApoA5 lowers TG is via competition with LPL for the same ANGPTL3/8-binding site. Supporting this hypothesis, we demonstrate that the anti-ANGPTL3/8 antibody potently blocked ANGPTL3/8-mediated LPL inhibition in vitro and dramatically lowered TG levels in vivo. Together, these data show that an anti-ANGPTL3/8 antibody targeting the same leucine zipper-containing epitope recognized by LPL and ApoA5 markedly decreases TG by suppressing ANGPTL3/8-mediated LPL inhibition.
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Affiliation(s)
| | - Oliver Schroeder
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA
| | - Anna M Russell
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA
| | | | - Aaron K Austin
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA
| | - Thomas P Beyer
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA
| | - Yan Q Chen
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA
| | - Jonathan W Day
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA
| | - Mariam Ehsani
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA
| | - Aik Roy Heng
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA
| | - Eugene Y Zhen
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA
| | - Julian Davies
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA
| | - Wolfgang Glaesner
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA
| | - Bryan E Jones
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA
| | - Robert W Siegel
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA
| | - Yue-Wei Qian
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA
| | - Robert J Konrad
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA.
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50
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Tsao CW, Aday AW, Almarzooq ZI, Alonso A, Beaton AZ, Bittencourt MS, Boehme AK, Buxton AE, Carson AP, Commodore-Mensah Y, Elkind MSV, Evenson KR, Eze-Nliam C, Ferguson JF, Generoso G, Ho JE, Kalani R, Khan SS, Kissela BM, Knutson KL, Levine DA, Lewis TT, Liu J, Loop MS, Ma J, Mussolino ME, Navaneethan SD, Perak AM, Poudel R, Rezk-Hanna M, Roth GA, Schroeder EB, Shah SH, Thacker EL, VanWagner LB, Virani SS, Voecks JH, Wang NY, Yaffe K, Martin SS. Heart Disease and Stroke Statistics-2022 Update: A Report From the American Heart Association. Circulation 2022; 145:e153-e639. [PMID: 35078371 DOI: 10.1161/cir.0000000000001052] [Citation(s) in RCA: 3143] [Impact Index Per Article: 1047.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
BACKGROUND The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy. RESULTS Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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