1
|
Gagnon E, Gill D, Chabot D, Cronjé HT, Yuan S, Brennan S, Thériault S, Burgess S, Arsenault BJ, Dib MJ. Evaluating the Cardiometabolic Efficacy and Safety of Lipoprotein Lipase Pathway Targets in Combination With Approved Lipid-Lowering Targets: A Drug Target Mendelian Randomization Study. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2025; 18:e004933. [PMID: 40052268 PMCID: PMC7617573 DOI: 10.1161/circgen.124.004933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2024] [Accepted: 01/29/2025] [Indexed: 04/11/2025]
Abstract
BACKGROUND Therapies targeting the LPL (lipoprotein lipase) pathway are under development for cardiometabolic disease. Insights into their efficacy-both alone and in combination with existing lipid-lowering therapies-modes of action, and safety of these agents are essential to inform clinical development. Using Mendelian randomization, we aimed to (1) evaluate efficacy, (2) explore shared mechanisms, (3) assess additive effects with approved lipid-lowering drugs, and (4) identify secondary indications and potential adverse effects. METHODS We selected triglyceride-lowering genetic variants located in the genes encoding ANGPTL3 (angiopoietin-like 3), ANGPTL4 (angiopoietin-like 4), APOC3 (apolipoprotein C3), and LPL and conducted drug target Mendelian randomization on primary outcomes including coronary artery disease and type 2 diabetes, and secondary outcomes, including apolipoprotein B, waist-to-hip ratio, body mass index, and 233 metabolic biomarkers. We conducted interaction Mendelian randomization analyses in 488 139 UK Biobank participants to test the effect of combination therapy targeting the LPL and LDLR (low-density lipoprotein receptor) pathways. Finally, we investigated potential secondary indications and adverse effects by leveraging genetic association data on 1204 disease end points. RESULTS Genetically predicted triglyceride lowering through the perturbation of LPL pathway activation targets ANGPTL4, APOC3, and LPL was associated with a lower risk of coronary artery disease and type 2 diabetes and lower apolipoprotein B. Genetically predicted triglyceride lowering through ANGPTL4 was associated with a lower waist-to-hip ratio, suggestive of a favorable body fat distribution. There was no evidence of a multiplicative interaction between genetically proxied perturbation of ANGPTL4, APOC3, and LPL and that of HMGCR (HMG-CoA reductase) and PCSK9 (proprotein convertase subtilisin/kexin type 9) on coronary artery disease and type 2 diabetes, consistent with additive effects. Finally, associations of genetically predicted LPL pathway targeting were supportive of the broad safety of these targets. CONCLUSIONS Our findings provide genetic evidence supporting the efficacy and safety of LPL pathway activation therapies for the prevention of coronary artery disease and type 2 diabetes, alone or in combination with statins or PCSK9 inhibitors.
Collapse
Affiliation(s)
- Eloi Gagnon
- Centre de recherche de l’Institut universitaire de cardiologie et de pneumologie de Québec, Université Laval, Québec (QC), Canada
| | - Dipender Gill
- Sequoia Genetics LTD., Translation & Innovation Hub, 84 Wood Lane, London, England
| | - Dominique Chabot
- Department of Medicine, Faculty of Medicine, Université Laval, Québec (QC), Canada
| | - Héléne T. Cronjé
- Department of Public Health, Section of Epidemiology, University of Copenhagen, Denmark
| | - Shuai Yuan
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Stephen Brennan
- Department of Neurology, Mater Misericordiae University Hospital, Dublin, Ireland
| | - Sébastien Thériault
- Centre de recherche de l’Institut universitaire de cardiologie et de pneumologie de Québec, Université Laval, Québec (QC), Canada
- Department of Molecular Biology, Medical Biochemistry and Pathology, Faculty of Medicine, Université Laval, Québec (QC), Canada
| | - Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Benoit J. Arsenault
- Centre de recherche de l’Institut universitaire de cardiologie et de pneumologie de Québec, Université Laval, Québec (QC), Canada
- Department of Medicine, Faculty of Medicine, Université Laval, Québec (QC), Canada
| | - Marie-Joe Dib
- Cardiovascular Division, Perelman School for Advanced Medicine, University of Pennsylvania, Philadelphia, USA
| |
Collapse
|
2
|
Ao L, van Heemst D, Jukema JW, Rensen PCN, Willems van Dijk K, Noordam R. Potential causal evidence for an ApoB-independent and HDL-related risk profile associated with coronary artery disease. J Lipid Res 2025; 66:100778. [PMID: 40089107 PMCID: PMC12000745 DOI: 10.1016/j.jlr.2025.100778] [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: 05/14/2024] [Revised: 02/09/2025] [Accepted: 03/12/2025] [Indexed: 03/17/2025] Open
Abstract
Plasma 1H-NMR metabolomic measures have yielded significant insight into the pathophysiology of cardiometabolic disease, but their inter-related nature complicates causal inference and clinical interpretation. This study aimed to investigate the associations of unrelated 1H-NMR metabolomic profiles with coronary artery disease (CAD) and ischemic stroke (IS). Principal component (PC) analysis was performed on 168 1H-NMR metabolomic measures in 56,712 unrelated European participants from UK Biobank to retrieve uncorrelated PCs, which were used in Cox-proportional hazard models. For each outcome, two-sample Mendelian randomization analyses were then conducted based on three nonoverlapping databases, followed by a meta-analysis. The first six PCs collectively explaining 88% of the total variance were identified. For CAD, results from Cox and Mendelian randomization analyses were generally directionally consistent. The pooled odds ratios (95% CI) for CAD per one-SD increase in genetically influenced PC1 and PC3 (both characterized by distinct apolipoprotein B [ApoB]-associated lipoprotein profiles) were 1.04 (1.03, 1.05) and 0.94 (0.93, 0.96), respectively. Besides, the pooled odds ratio (95% CI) for CAD per one-SD increase in genetically influenced PC4, characterized by simultaneously decreased small HDL and increased large HDL, and independent of ApoB, was 1.05 (1.03, 1.07). For IS, increases of PC3 and PC5 (characterized by increased amino acids) were associated with a lower risk and a higher risk, respectively. This study confirms associations of ApoB-associated lipoprotein profiles with CAD and IS, and highlights the possible existence of an ApoB-independent lipoprotein profile, characterized by a distinctive HDL subparticle distribution, driving CAD.
Collapse
Affiliation(s)
- Linjun Ao
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands.
| | - Diana van Heemst
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands; Netherlands Heart Institute, Utrecht, the Netherlands
| | - Patrick C N Rensen
- Division of Endocrinology, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands; Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Ko Willems van Dijk
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands; Division of Endocrinology, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands; Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Raymond Noordam
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| |
Collapse
|
3
|
Hu Y, Cui X, Lu M, Guan X, Li Y, Zhang L, Lin L, Zhang Z, Zhang M, Hao J, Wang X, Huan J, Li Y, Li C. Body Fat Distribution and Ectopic Fat Accumulation as Mediator of Diabetogenic Action of Lipid-Modifying Drugs: A Mediation Mendelian Randomization Study. Mayo Clin Proc 2025; 100:424-439. [PMID: 39918451 DOI: 10.1016/j.mayocp.2024.10.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Revised: 10/06/2024] [Accepted: 10/25/2024] [Indexed: 05/08/2025]
Abstract
OBJECTIVE To investigate the causal relationship between various lipid-modifying drugs and new-onset diabetes, as well as the mediators contributing to this relationship. METHODS Mediation Mendelian randomization was performed to investigate the causal effect of lipid-modifying drug targets on type 2 diabetes (T2D) outcomes and the proportion of this association that is mediated through ectopic fat accumulation traits. Specific sets of variants in or near genes that encode 11 lipid-modifying drug targets (LDLR, HMGCR, NPC1L1, PCSK9, APOB, ABCG5/ABCG8, LPL, PPARA, ANGPTL3, APOC3, and CETP; for expansion of gene symbols, use search tool at www.genenames.org) were extracted. Random effects inverse variance weighted were performed to evaluate the causal effects among outcomes. Mediation analyses were performed to identify the mediators of the association between lipid-modifying drugs and T2D. The study was conducted from November 10, 2023, to April 2, 2024 RESULTS: The genetic mimicry of HMGCR and APOB inhibition was associated with an increased T2D risk, whereas the genetic mimicry of LPL enhancement was linked to a lower T2D risk. Gluteofemoral adipose tissue volume was a mediator for explaining 9.52% (P=.002), 16.90% (P=.03), and 10.50% (P=.003) of the total effect of HMGCR, APOB, and LPL on T2D susceptibility, respectively. Liver fat was a mediator for explaining 21.12% (P=.005), 12.28% (P=.03), and 9.84% (P=.005) of the total effect of HMGCR, APOB, and LPL on T2D susceptibility, respectively. CONCLUSION Our findings support the hypothesis that liver fat and gluteofemoral adipose tissue play a mediating role in the prodiabetic effects of HMGCR and APOB inhibition, as well as in the antidiabetic effects of LPL enhancement.
Collapse
Affiliation(s)
- Yuanlong Hu
- First Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Xinhai Cui
- College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Mengkai Lu
- Innovation Research Institute of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Xiuya Guan
- Innovation Research Institute of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Yuan Li
- Experimental Center, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Lei Zhang
- College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Lin Lin
- Innovation Research Institute of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Zhiyuan Zhang
- Innovation Research Institute of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Muxin Zhang
- First Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Jiaqi Hao
- First Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Xiaojie Wang
- Faculty of Chinese Medicine, Macau University of Science and Technology, Taipa, Macau, China
| | - Jiaming Huan
- Innovation Research Institute of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Yunlun Li
- First Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China; Department of Cardiovascular, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China.
| | - Chao Li
- Innovation Research Institute of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China.
| |
Collapse
|
4
|
Fu L, Liu Q, Cheng H, Zhao X, Xiong J, Mi J. Insights Into Causal Effects of Genetically Proxied Lipids and Lipid-Modifying Drug Targets on Cardiometabolic Diseases. J Am Heart Assoc 2025; 14:e038857. [PMID: 39868518 DOI: 10.1161/jaha.124.038857] [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: 09/13/2024] [Accepted: 12/13/2024] [Indexed: 01/28/2025]
Abstract
BACKGROUND The differential impact of serum lipids and their targets for lipid modification on cardiometabolic disease risk is debated. This study used Mendelian randomization to investigate the causal relationships and underlying mechanisms. METHODS Genetic variants related to lipid profiles and targets for lipid modification were sourced from the Global Lipids Genetics Consortium. Summary data for 10 cardiometabolic diseases were compiled from both discovery and replication data sets. Expression quantitative trait loci data from relevant tissues were employed to evaluate significant lipid-modifying drug targets. Comprehensive analyses including colocalization, mediation, and bioinformatics were conducted to validate the results and investigate potential mediators and mechanisms. RESULTS Significant causal associations were identified between lipids, lipid-modifying drug targets, and various cardiometabolic diseases. Notably, genetic enhancement of LPL (lipoprotein lipase) was linked to reduced risks of myocardial infarction (odds ratio [OR]1, 0.65 [95% CI, 0.57-0.75], P1=2.60×10-9; OR2, 0.59 [95% CI, 0.49-0.72], P2=1.52×10-7), ischemic heart disease (OR1, 0.968 [95% CI, 0.962-0.975], P1=5.50×10-23; OR2, 0.64 [95% CI, 0.55-0.73], P2=1.72×10-10), and coronary heart disease (OR1, 0.980 [95% CI, 0.975-0.985], P1=3.63×10-14; OR2, 0.64 [95% CI, 0.54-0.75], P2=6.62×10-8) across 2 data sets. Moreover, significant Mendelian randomization and strong colocalization associations for the expression of LPL in blood and subcutaneous adipose tissue were linked with myocardial infarction (OR, 0.918 [95% CI, 0.872-0.967], P=1.24×10-3; PP.H4, 0.99) and coronary heart disease (OR, 0.991 [95% CI, 0.983-0.999], P=0.041; PP.H4=0.92). Glucose levels and blood pressure were identified as mediators in the total effect of LPL on cardiometabolic outcomes. CONCLUSIONS The study substantiates the causal role of lipids in specific cardiometabolic diseases, highlighting LPL as a potent drug target. The effects of LPL are suggested to be influenced by changes in glucose and blood pressure, providing insights into its mechanism of action.
Collapse
Affiliation(s)
- Liwan Fu
- Center for Non-Communicable Disease Management Beijing Children's Hospital, Capital Medical University, National Center for Children's Health Beijing China
| | - Qin Liu
- Department of Ultrasound Children's Hospital of the Capital Institute of Pediatrics Beijing China
| | - Hong Cheng
- Department of Epidemiology Capital Institute of Pediatrics Beijing China
| | - Xiaoyuan Zhao
- Department of Epidemiology Capital Institute of Pediatrics Beijing China
| | - Jingfan Xiong
- Child and Adolescent Chronic Disease Prevention and Control Department Shenzhen Center for Chronic Disease Control Shenzhen China
| | - Jie Mi
- Center for Non-Communicable Disease Management Beijing Children's Hospital, Capital Medical University, National Center for Children's Health Beijing China
- Key Laboratory of Major Diseases in Children, Ministry of Education China
| |
Collapse
|
5
|
Koohi F, Harshfield EL, Gill D, Ge W, Burgess S, Markus HS. Optimizing treatment of cardiovascular risk factors in cerebral small vessel disease using genetics. Brain 2024:awae399. [PMID: 39661645 PMCID: PMC7617411 DOI: 10.1093/brain/awae399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2024] [Revised: 10/18/2024] [Accepted: 12/10/2024] [Indexed: 12/13/2024] Open
Abstract
Cerebral small vessel disease (cSVD) causes lacunar stroke (LS), intracerebral haemorrhage, and is the most common pathology underlying vascular dementia. However, there are few trials examining whether treating conventional cardiovascular risk factors reduce stroke risk in cSVD, as opposed to stroke as a whole. We used Mendelian randomization techniques to investigate which risk factors are causally related to cSVD and to evaluate whether specific drugs may be beneficial in cSVD prevention. We identified genetic proxies for blood pressure traits, lipids, glycaemic markers, anthropometry measures, smoking, alcohol consumption, and physical activity from large-scale genome-wide association studies of European ancestry. We also selected genetic variants as proxies for drug target perturbation in hypertension, dyslipidaemia, hyperglycaemia, and obesity. Mendelian randomization was performed to assess their associations with LS from the GIGASTROKE Consortium (n = 6811) and in a sensitivity analysis in a cohort of patients with MRI-confirmed LS (n = 3306). We also investigated associations with three neuroimaging features of cSVD, namely, white matter hyperintensities (n = 55 291), fractional anisotropy (n = 36 460), and mean diffusivity (n = 36 012). Genetic predisposition to higher systolic and diastolic blood pressure was associated with LS and cSVD imaging markers. Genetically predicted liability to diabetes, obesity, smoking, higher triglyceride levels, and the ratio of triglycerides to high density lipoprotein (HDL) also showed detrimental associations with LS risk, while genetic predisposition to higher HDL concentrations and moderate-to-vigorous physical activity showed protective associations. Genetically proxied blood pressure-lowering through calcium channel blockers (CCBs) was associated with cSVD imaging markers, while genetically proxied HDL-raising through Cholesteryl Ester Transfer Protein (CETP) inhibitors, triglyceride-lowering through lipoprotein lipase (LPL), and weight-lowering through gastric inhibitory polypeptide receptor (GIPR) were associated with lower risk of LS. Our findings highlight the importance of some conventional cardiovascular risk factors, including blood pressure and BMI, in cSVD, but not other e.g. LDL. The findings further demonstrate the potential beneficial effects of CCBs on cSVD imaging markers and CETP inhibitors, LPL enhancement, and GIPR obesity-targeted drugs on LS. They provide useful information for initiating future clinical trials examining secondary prevention strategies in cSVD.
Collapse
Affiliation(s)
- Fatemeh Koohi
- Stroke Research Group, Department of Clinical Neurosciences, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Eric L Harshfield
- Stroke Research Group, Department of Clinical Neurosciences, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, W12 0BZ, UK
| | - Wenjing Ge
- Stroke Research Group, Department of Clinical Neurosciences, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge, CB2 0SR, UK
| | - Hugh S Markus
- Stroke Research Group, Department of Clinical Neurosciences, University of Cambridge, Cambridge, CB2 0QQ, UK
| |
Collapse
|
6
|
Xie Y, Liu S, Wang X, Huang H, Wang M, Qu W, Yu Z, Wang W, Luo X. Lipids, Apolipoproteins, Lipid-Lowering Drugs, and the Risk of Cerebral Small Vessel Disease: A Mendelian Randomization Study. J Am Heart Assoc 2024; 13:e032409. [PMID: 39158561 PMCID: PMC11963954 DOI: 10.1161/jaha.123.032409] [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: 12/15/2023] [Accepted: 07/16/2024] [Indexed: 08/20/2024]
Abstract
BACKGROUND Serum lipids are causally involved in the occurrence of atherosclerosis, but their roles in cerebral small vessel disease remain unclear. This study aimed to investigate the causal roles of lipid or apolipoprotein traits in cerebral small vessel disease and to determine the effects of lipid-lowering interventions on this disease. METHODS AND RESULTS Data on genetic instruments of lipids/apolipoproteins, as well as characteristic cerebral small vessel disease manifestations, including small vessel stroke (SVS) and white matter hyperintensity (WMH), were obtained from publicly genome-wide association studies. Through 2-sample Mendelian randomization analyses, it was found that decreased levels of high-density lipoprotein cholesterol (odds ratio [OR], 0.85, P=0.007) and apolipoprotein A-I (OR, 0.83, P=0.005), as well as increased level of triglycerides (OR, 1.16, P=0.025) were associated with a higher risk of SVS. A low level of high-density lipoprotein cholesterol (OR, 0.93, P=0.032) was associated with larger WMH volume. Specifically, the genetically determined expressions of lipid fractions in various size-defined lipoprotein particles were more closely related to the risk of SVS than WMH. Moreover, it was found that the hypertension trait ranked at the top in mediating the causal effect of hyperlipidemia on SVS and WMH by using Mendelian randomization-based mediation analysis. For drug-target Mendelian randomization, the low-density lipoprotein cholesterol-reducing genetic variation alleles at HMGCR and NL1CL1 genes and the high-density lipoprotein cholesterol-raising genetic variation alleles at the CETP gene were predicted to decrease the risk of SVS. CONCLUSIONS The present Mendelian randomization study indicates that genetically determined hyperlipidemia is closely associated with a higher risk of cerebral small vessel disease, especially SVS. Lipid-lowering drugs could be potentially considered for the therapies and preventions of SVS rather than WMH.
Collapse
Affiliation(s)
- Yi Xie
- Department of Neurology, Tongji Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
- Hubei Key Laboratory of Neural Injury and Functional ReconstructionHuazhong University of Science and TechnologyWuhanChina
| | - Shuai Liu
- Reproductive Medicine Center, Tongji Hospital, Tongji Medicine CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Xinyue Wang
- Department of Neurology, Tongji Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
- Hubei Key Laboratory of Neural Injury and Functional ReconstructionHuazhong University of Science and TechnologyWuhanChina
| | - Hao Huang
- Department of Neurology, Tongji Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
- Hubei Key Laboratory of Neural Injury and Functional ReconstructionHuazhong University of Science and TechnologyWuhanChina
| | - Minghuan Wang
- Department of Neurology, Tongji Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
- Hubei Key Laboratory of Neural Injury and Functional ReconstructionHuazhong University of Science and TechnologyWuhanChina
| | - Wensheng Qu
- Department of Neurology, Tongji Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
- Hubei Key Laboratory of Neural Injury and Functional ReconstructionHuazhong University of Science and TechnologyWuhanChina
| | - Zhiyuan Yu
- Department of Neurology, Tongji Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
- Hubei Key Laboratory of Neural Injury and Functional ReconstructionHuazhong University of Science and TechnologyWuhanChina
| | - Wei Wang
- Department of Neurology, Tongji Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
- Hubei Key Laboratory of Neural Injury and Functional ReconstructionHuazhong University of Science and TechnologyWuhanChina
- Key Laboratory of Neurological Diseases of the Chinese Ministry of Education, School of Basic Medicine, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Xiang Luo
- Department of Neurology, Tongji Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
- Hubei Key Laboratory of Neural Injury and Functional ReconstructionHuazhong University of Science and TechnologyWuhanChina
| |
Collapse
|
7
|
Ao L, Noordam R, Rensen PCN, van Heemst D, Willems van Dijk K. The role of genetically-influenced phospholipid transfer protein activity in lipoprotein metabolism and coronary artery disease. J Clin Lipidol 2024; 18:e579-e587. [PMID: 38906750 DOI: 10.1016/j.jacl.2024.03.007] [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: 10/17/2023] [Revised: 02/20/2024] [Accepted: 03/26/2024] [Indexed: 06/23/2024]
Abstract
BACKGROUND Phospholipid transfer protein (PLTP) transfers surface phospholipids between lipoproteins and as such plays a role in lipoprotein metabolism, but with unclear effects on coronary artery disease (CAD) risk. We aimed to investigate the associations of genetically-influenced PLTP activity with 1-H nuclear magnetic resonance (1H-NMR) metabolomic measures and with CAD. Furthermore, using factorial Mendelian randomization (MR), we examined the potential additional effect of genetically-influenced PLTP activity on CAD risk on top of genetically-influenced low-density lipoprotein-cholesterol (LDL-C) lowering. METHODS Using data from UK Biobank, genetic scores for PLTP activity and LDL-C were calculated and dichotomised based on the median, generating four groups with combinations of high/low PLTP activity and high/low LDL-C levels for the factorial MR. Linear and logistic regressions were performed on 168 metabolomic measures (N = 58,514) and CAD (N = 318,734, N-cases=37,552), respectively, with results expressed as β coefficients (in standard deviation units) or odds ratios (ORs) and 95% confidence interval (CI). RESULTS Irrespective of the genetically-influenced LDL-C, genetically-influenced low PLTP activity was associated with a higher high-density lipoprotein (HDL) particle concentration (β [95% CI]: 0.03 [0.01, 0.05]), smaller HDL size (-0.14 [-0.15, -0.12]) and higher triglyceride (TG) concentration (0.04 [0.02, 0.05]), but not with CAD (OR 0.99 [0.97, 1.02]). In factorial MR analyses, genetically-influenced low PLTP activity and genetically-influenced low LDL-C had independent associations with metabolomic measures, and genetically-influenced low PLTP activity did not show an additional effect on CAD risk. CONCLUSIONS Low PLTP activity associates with higher HDL particle concentration, smaller HDL particle size and higher TG concentration, but no association with CAD risk was observed.
Collapse
Affiliation(s)
- Linjun Ao
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands (MMed Ao and Dr Willems van Dijk).
| | - Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands (Drs Noordam and van Heemst)
| | - Patrick C N Rensen
- Department of Internal Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, the Netherlands (Drs Rensen and Willems van Dijk); Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands (Drs Rensen and Willems van Dijk)
| | - Diana van Heemst
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands (Drs Noordam and van Heemst)
| | - Ko Willems van Dijk
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands (MMed Ao and Dr Willems van Dijk); Department of Internal Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, the Netherlands (Drs Rensen and Willems van Dijk); Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands (Drs Rensen and Willems van Dijk)
| |
Collapse
|
8
|
Yao P, Iona A, Pozarickij A, Said S, Wright N, Lin K, Millwood I, Fry H, Kartsonaki C, Mazidi M, Chen Y, Bragg F, Liu B, Yang L, Liu J, Avery D, Schmidt D, Sun D, Pei P, Lv J, Yu C, Hill M, Bennett D, Walters R, Li L, Clarke R, Du H, Chen Z. Proteomic Analyses in Diverse Populations Improved Risk Prediction and Identified New Drug Targets for Type 2 Diabetes. Diabetes Care 2024; 47:1012-1019. [PMID: 38623619 PMCID: PMC7615965 DOI: 10.2337/dc23-2145] [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: 11/13/2023] [Accepted: 03/09/2024] [Indexed: 04/17/2024]
Abstract
OBJECTIVE Integrated analyses of plasma proteomics and genetic data in prospective studies can help assess the causal relevance of proteins, improve risk prediction, and discover novel protein drug targets for type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS We measured plasma levels of 2,923 proteins using Olink Explore among ∼2,000 randomly selected participants from China Kadoorie Biobank (CKB) without prior diabetes at baseline. Cox regression assessed associations of individual protein with incident T2D (n = 92 cases). Proteomic-based risk models were developed with discrimination, calibration, reclassification assessed using area under the curve (AUC), calibration plots, and net reclassification index (NRI), respectively. Two-sample Mendelian randomization (MR) analyses using cis-protein quantitative trait loci identified in a genome-wide association study of CKB and UK Biobank for specific proteins were conducted to assess their causal relevance for T2D, along with colocalization analyses to examine shared causal variants between proteins and T2D. RESULTS Overall, 33 proteins were significantly associated (false discovery rate <0.05) with risk of incident T2D, including IGFBP1, GHR, and amylase. The addition of these 33 proteins to a conventional risk prediction model improved AUC from 0.77 (0.73-0.82) to 0.88 (0.85-0.91) and NRI by 38%, with predicted risks well calibrated with observed risks. MR analyses provided support for the causal relevance for T2D of ENTR1, LPL, and PON3, with replication of ENTR1 and LPL in Europeans using different genetic instruments. Moreover, colocalization analyses showed strong evidence (pH4 > 0.6) of shared genetic variants of LPL and PON3 with T2D. CONCLUSIONS Proteomic analyses in Chinese adults identified novel associations of multiple proteins with T2D with strong genetic evidence supporting their causal relevance and potential as novel drug targets for prevention and treatment of T2D.
Collapse
Affiliation(s)
- Pang Yao
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Andri Iona
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Alfred Pozarickij
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Saredo Said
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Neil Wright
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Kuang Lin
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Iona Millwood
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Hannah Fry
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Christiana Kartsonaki
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Mohsen Mazidi
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Yiping Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Fiona Bragg
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Bowen Liu
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Ling Yang
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Junxi Liu
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Daniel Avery
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Dan Schmidt
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Pei Pei
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Michael Hill
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Derrick Bennett
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Robin Walters
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Robert Clarke
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Huaidong Du
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| |
Collapse
|
9
|
Zhao Y, Zhuang Z, Li Y, Xiao W, Song Z, Huang N, Wang W, Dong X, Jia J, Clarke R, Huang T. Elevated blood remnant cholesterol and triglycerides are causally related to the risks of cardiometabolic multimorbidity. Nat Commun 2024; 15:2451. [PMID: 38503751 PMCID: PMC10951224 DOI: 10.1038/s41467-024-46686-x] [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: 05/17/2023] [Accepted: 02/28/2024] [Indexed: 03/21/2024] Open
Abstract
The connection between triglyceride-rich lipoproteins and cardiometabolic multimorbidity, characterized by the concurrence of at least two of type 2 diabetes, ischemic heart disease, and stroke, has not been definitively established. We aim to examine the prospective associations between serum remnant cholesterol, triglycerides, and the risks of progression from first cardiometabolic disease to multimorbidity via multistate modeling in the UK Biobank. We also evaluate the causality of these associations via Mendelian randomization using 13 biologically relevant SNPs as the genetic instruments. Here we show that elevated remnant cholesterol and triglycerides are significantly associated with gradually higher risks of cardiometabolic multimorbidity, particularly the progression of ischemic heart disease to the multimorbidity of ischemic heart disease and type 2 diabetes. These results advocate for effective management of remnant cholesterol and triglycerides as a potential strategy in mitigating the risks of cardiometabolic multimorbidity.
Collapse
Affiliation(s)
- Yimin Zhao
- Department of Sports Medicine, Peking University Third Hospital, Peking University, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Zhenhuang Zhuang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Yueying Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Wendi Xiao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Zimin Song
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Ninghao Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Wenxiu Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Xue Dong
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Jinzhu Jia
- Department of Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Robert Clarke
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Tao Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China.
- Center for Intelligent Public Health, Academy for Artificial Intelligence, Peking University, Beijing, China.
| |
Collapse
|
10
|
Huang A, Wu X, Lin J, Wei C, Xu W. Genetic insights into repurposing statins for hyperthyroidism prevention: a drug-target Mendelian randomization study. Front Endocrinol (Lausanne) 2024; 15:1331031. [PMID: 38425755 PMCID: PMC10902122 DOI: 10.3389/fendo.2024.1331031] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 02/01/2024] [Indexed: 03/02/2024] Open
Abstract
Background Current therapeutic measures for thyroid dysfunction are limited and often accompanied by adverse effects. The use of lipid-lowering drugs like statins has recently been associated with lower thyroid eye diseases risk. Objective To investigate the implications of genetically proxied lipid-lowering drugs on thyroid dysfunction. Methods In this drug-target Mendelian randomization (MR) study, we utilized genetic variants within drug target genes associated with low-density lipoprotein (LDL) or triglyceride (TG), derived from a genome-wide association study (GWAS) meta-analysis (N ≤ 188,577), to simulate lifelong drug interventions. Genetic summary statistics for thyroid dysfunction outcomes were retrieved from GWAS datasets of Thyroid Omics Consortium (N ≤ 54,288) and UK Biobank (N = 484,598). Inverse-variance-weighted MR (IVW-MR) method was performed as primary analysis, followed by validation in colocalization analysis. A subsequent two-step MR analysis was conducted to identify biomarkers mediating the identified drug-outcome association. Results In IVW-MR analysis, genetic mimicry of 3-hydroxy-3-methylglutarylcoenzyme reductase (HMGCR) inhibitors (e.g. statins) was significantly associated with lower risk of hyperthyroidism in two independent datasets (OR1, 0.417 per 1-mmol/L lower in LDL-C; 95% CI 0.262 to 0.664; P1 = 2.262 × 10-4; OR2 0.996; 95% CI 0.993-0.998; P2 = 0.002). Two-step MR analysis revealed eighteen biomarkers linked to genetic mimicry of HMGCR inhibition, and identified insulin-like growth factor 1 (IGF-1) levels mediating 2.108% of the negative causal relationship between HMGCR inhibition and hyperthyroidism. Conclusion This study supports HMGCR inhibition as a promising therapeutic strategy for hyperthyroidism and suggests its underlying mechanisms may extend beyond lipid metabolism. Further investigations through laboratory studies and clinical trials are necessary to confirm and elucidate these findings.
Collapse
Affiliation(s)
- Anqi Huang
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Shantou University Medical College, Shantou, China
- Shantou University Medical College, Shantou, China
| | - Xinyi Wu
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Shantou University Medical College, Shantou, China
- Shantou University Medical College, Shantou, China
| | - Jiaqi Lin
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Shantou University Medical College, Shantou, China
- Shantou University Medical College, Shantou, China
| | - Chiju Wei
- Multidisciplinary Research Center, Shantou University, Shantou, China
| | - Wencan Xu
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Shantou University Medical College, Shantou, China
| |
Collapse
|
11
|
Alves M, Laranjeira F, Correia-da-Silva G. Understanding Hypertriglyceridemia: Integrating Genetic Insights. Genes (Basel) 2024; 15:190. [PMID: 38397180 PMCID: PMC10887881 DOI: 10.3390/genes15020190] [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: 12/06/2023] [Revised: 01/24/2024] [Accepted: 01/25/2024] [Indexed: 02/25/2024] Open
Abstract
Hypertriglyceridemia is an exceptionally complex metabolic disorder characterized by elevated plasma triglycerides associated with an increased risk of acute pancreatitis and cardiovascular diseases such as coronary artery disease. Its phenotype expression is widely heterogeneous and heavily influenced by conditions as obesity, alcohol consumption, or metabolic syndromes. Looking into the genetic underpinnings of hypertriglyceridemia, this review focuses on the genetic variants in LPL, APOA5, APOC2, GPIHBP1 and LMF1 triglyceride-regulating genes reportedly associated with abnormal genetic transcription and the translation of proteins participating in triglyceride-rich lipoprotein metabolism. Hypertriglyceridemia resulting from such genetic abnormalities can be categorized as monogenic or polygenic. Monogenic hypertriglyceridemia, also known as familial chylomicronemia syndrome, is caused by homozygous or compound heterozygous pathogenic variants in the five canonical genes. Polygenic hypertriglyceridemia, also known as multifactorial chylomicronemia syndrome in extreme cases of hypertriglyceridemia, is caused by heterozygous pathogenic genetic variants with variable penetrance affecting the canonical genes, and a set of common non-pathogenic genetic variants (polymorphisms, using the former nomenclature) with well-established association with elevated triglyceride levels. We further address recent progress in triglyceride-lowering treatments. Understanding the genetic basis of hypertriglyceridemia opens new translational opportunities in the scope of genetic screening and the development of novel therapies.
Collapse
Affiliation(s)
- Mara Alves
- Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal;
| | - Francisco Laranjeira
- CGM—Centro de Genética Médica Jacinto de Magalhães, Centro Hospitalar Universitário de Santo António (CHUdSA), 4099-028 Porto, Portugal;
- UMIB—Unit for Multidisciplinary Research in Biomedicine, ICBAS—School of Medicine and Biomedical Sciences, University of Porto, 4050-346 Porto, Portugal
- ITR—Laboratory for Integrative and Translational Research in Population Health, 4050-600 Porto, Portugal
| | - Georgina Correia-da-Silva
- UCIBIO Applied Molecular Biosciences Unit and Associate Laboratory i4HB—Institute for Health and Bioeconomy Laboratory of Biochemistry, Department of Biological Sciences, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal
| |
Collapse
|
12
|
Jiang S, Ren Z, Yang Y, Liu Q, Zhou S, Xiao Y. The GPIHBP1-LPL complex and its role in plasma triglyceride metabolism: Insights into chylomicronemia. Biomed Pharmacother 2023; 169:115874. [PMID: 37951027 DOI: 10.1016/j.biopha.2023.115874] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 11/06/2023] [Accepted: 11/07/2023] [Indexed: 11/13/2023] Open
Abstract
GPIHBP1 is a protein found in the endothelial cells of capillaries that is anchored by glycosylphosphatidylinositol and binds to high-density lipoproteins. GPIHBP1 attaches to lipoprotein lipase (LPL), subsequently carrying the enzyme and anchoring it to the capillary lumen. Enabling lipid metabolism is essential for the marginalization of lipoproteins alongside capillaries. Studies underscore the significance of GPIHBP1 in transporting, stabilizing, and aiding in the marginalization of LPL. The intricate interplay between GPIHBP1 and LPL has provided novel insights into chylomicronemia in recent years. Mutations hindering the formation or reducing the efficiency of the GPIHBP1-LPL complex are central to the onset of chylomicronemia. This review delves into the structural nuances of the GPIHBP1-LPL interaction, the consequences of mutations in the complex leading to chylomicronemia, and cutting-edge advancements in chylomicronemia treatment.
Collapse
Affiliation(s)
- Shali Jiang
- Department of Cardiovascular Medicine, Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, PR China; Xiangya School of Medicine, Central South University, Changsha, Hunan 410013, PR China
| | - Zhuoqun Ren
- Department of Cardiovascular Medicine, Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, PR China; Xiangya School of Medicine, Central South University, Changsha, Hunan 410013, PR China
| | - Yutao Yang
- Department of Cardiovascular Medicine, Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, PR China; Xiangya School of Medicine, Central South University, Changsha, Hunan 410013, PR China
| | - Qiming Liu
- Department of Cardiovascular Medicine, Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, PR China
| | - Shenghua Zhou
- Department of Cardiovascular Medicine, Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, PR China
| | - Yichao Xiao
- Department of Cardiovascular Medicine, Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, PR China.
| |
Collapse
|
13
|
Björnson E, Adiels M, Taskinen MR, Burgess S, Rawshani A, Borén J, Packard CJ. Triglyceride-rich lipoprotein remnants, low-density lipoproteins, and risk of coronary heart disease: a UK Biobank study. Eur Heart J 2023; 44:4186-4195. [PMID: 37358553 PMCID: PMC10576615 DOI: 10.1093/eurheartj/ehad337] [Citation(s) in RCA: 71] [Impact Index Per Article: 35.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 03/04/2023] [Accepted: 05/16/2023] [Indexed: 06/27/2023] Open
Abstract
AIMS The strength of the relationship of triglyceride-rich lipoproteins (TRL) with risk of coronary heart disease (CHD) compared with low-density lipoprotein (LDL) is yet to be resolved. METHODS AND RESULTS Single-nucleotide polymorphisms (SNPs) associated with TRL/remnant cholesterol (TRL/remnant-C) and LDL cholesterol (LDL-C) were identified in the UK Biobank population. In a multivariable Mendelian randomization analysis, TRL/remnant-C was strongly and independently associated with CHD in a model adjusted for apolipoprotein B (apoB). Likewise, in a multivariable model, TRL/remnant-C and LDL-C also exhibited independent associations with CHD with odds ratios per 1 mmol/L higher cholesterol of 2.59 [95% confidence interval (CI): 1.99-3.36] and 1.37 [95% CI: 1.27-1.48], respectively. To examine the per-particle atherogenicity of TRL/remnants and LDL, SNPs were categorized into two clusters with differing effects on TRL/remnant-C and LDL-C. Cluster 1 contained SNPs in genes related to receptor-mediated lipoprotein removal that affected LDL-C more than TRL/remnant-C, whereas cluster 2 contained SNPs in genes related to lipolysis that had a much greater effect on TRL/remnant-C. The CHD odds ratio per standard deviation (Sd) higher apoB for cluster 2 (with the higher TRL/remnant to LDL ratio) was 1.76 (95% CI: 1.58-1.96), which was significantly greater than the CHD odds ratio per Sd higher apoB in cluster 1 [1.33 (95% CI: 1.26-1.40)]. A concordant result was obtained by using polygenic scores for each cluster to relate apoB to CHD risk. CONCLUSION Distinct SNP clusters appear to impact differentially on remnant particles and LDL. Our findings are consistent with TRL/remnants having a substantially greater atherogenicity per particle than LDL.
Collapse
Affiliation(s)
- Elias Björnson
- Department of Molecular and Clinical Medicine, University of Gothenburg, Sahlgrenska University Hospital, 41345 Gothenburg, Sweden
| | - Martin Adiels
- Department of Molecular and Clinical Medicine, University of Gothenburg, Sahlgrenska University Hospital, 41345 Gothenburg, Sweden
- School of Public Health and Community Medicine, University of Gothenburg, Medicinaregatan 18A, 41390 Gothenburg, Sweden
| | - Marja-Riitta Taskinen
- Research Program for Clinical and Molecular Metabolism, University of Helsinki, Biomedicum 1, Haartmanninkatu 8, 00290 Helsinki, Finland
| | - Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Robinson Way, Cambridge, CB2 0SR, UK
- Cardiovascular Epidemiology Unit, Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Papworth Road, Cambridge, CB2 0BD, UK
| | - Aidin Rawshani
- Department of Molecular and Clinical Medicine, University of Gothenburg, Sahlgrenska University Hospital, 41345 Gothenburg, Sweden
| | - Jan Borén
- Department of Molecular and Clinical Medicine, University of Gothenburg, Sahlgrenska University Hospital, 41345 Gothenburg, Sweden
| | - Chris J Packard
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, 126 University Place, G12 8TA Glasgow, UK
| |
Collapse
|
14
|
Gill D, Woolf B, Zagkos L, Cronjé HT, Tzoulaki I. Cardiovascular Efficacy of Lipid-Lowering Drug Targets Is Not Entirely Explained by Apolipoprotein B Reduction: Mendelian Randomization Evidence. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2023; 16:490-492. [PMID: 37577833 DOI: 10.1161/circgen.123.004204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Affiliation(s)
- Dipender Gill
- Department of Epidemiology and Biostatistics (D.G., L.Z., I.T.), School of Public Health, Imperial College London, United Kingdom
- British Heart Foundation Centre of Excellence (D.G., I.T.), School of Public Health, Imperial College London, United Kingdom
| | - Benjamin Woolf
- School of Psychological Science (B.W.), University of Bristol, United Kingdom
- Medical Research Council Integrative Epidemiology Unit (B.W.), University of Bristol, United Kingdom
- Medical Research Council Biostatistics Unit at the University of Cambridge, United Kingdom (B.W.)
| | - Loukas Zagkos
- Department of Epidemiology and Biostatistics (D.G., L.Z., I.T.), School of Public Health, Imperial College London, United Kingdom
| | - Héléne T Cronjé
- Department of Public Health, Section of Epidemiology, University of Copenhagen, Denmark (H.T.C.)
| | - Ioanna Tzoulaki
- Department of Epidemiology and Biostatistics (D.G., L.Z., I.T.), School of Public Health, Imperial College London, United Kingdom
- British Heart Foundation Centre of Excellence (D.G., I.T.), School of Public Health, Imperial College London, United Kingdom
- Centre for Systems Biology, Biomedical Research Foundation of the Academy of Athens, Greece (I.T.)
| |
Collapse
|
15
|
Luo H, Bauer A, Nano J, Petrera A, Rathmann W, Herder C, Hauck SM, Sun BB, Hoyer A, Peters A, Thorand B. Associations of plasma proteomics with type 2 diabetes and related traits: results from the longitudinal KORA S4/F4/FF4 Study. Diabetologia 2023; 66:1655-1668. [PMID: 37308750 DOI: 10.1007/s00125-023-05943-2] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 04/12/2023] [Indexed: 06/14/2023]
Abstract
AIMS/HYPOTHESIS This study aimed to elucidate the aetiological role of plasma proteins in glucose metabolism and type 2 diabetes development. METHODS We measured 233 proteins at baseline in 1653 participants from the Cooperative Health Research in the Region of Augsburg (KORA) S4 cohort study (median follow-up time: 13.5 years). We used logistic regression in the cross-sectional analysis (n=1300), and Cox regression accounting for interval-censored data in the longitudinal analysis (n=1143). We further applied two-level growth models to investigate associations with repeatedly measured traits (fasting glucose, 2 h glucose, fasting insulin, HOMA-B, HOMA-IR, HbA1c), and two-sample Mendelian randomisation analysis to investigate causal associations. Moreover, we built prediction models using priority-Lasso on top of Framingham-Offspring Risk Score components and evaluated the prediction accuracy through AUC. RESULTS We identified 14, 24 and four proteins associated with prevalent prediabetes (i.e. impaired glucose tolerance and/or impaired fasting glucose), prevalent newly diagnosed type 2 diabetes and incident type 2 diabetes, respectively (28 overlapping proteins). Of these, IL-17D, IL-18 receptor 1, carbonic anhydrase-5A, IL-1 receptor type 2 (IL-1RT2) and matrix extracellular phosphoglycoprotein were novel candidates. IGF binding protein 2 (IGFBP2), lipoprotein lipase (LPL) and paraoxonase 3 (PON3) were inversely associated while fibroblast growth factor 21 was positively associated with incident type 2 diabetes. LPL was longitudinally linked with change in glucose-related traits, while IGFBP2 and PON3 were linked with changes in both insulin- and glucose-related traits. Mendelian randomisation analysis suggested causal effects of LPL on type 2 diabetes and fasting insulin. The simultaneous addition of 12 priority-Lasso-selected biomarkers (IGFBP2, IL-18, IL-17D, complement component C1q receptor, V-set and immunoglobulin domain-containing protein 2, IL-1RT2, LPL, CUB domain-containing protein 1, vascular endothelial growth factor D, PON3, C-C motif chemokine 4 and tartrate-resistant acid phosphatase type 5) significantly improved the predictive performance (ΔAUC 0.0219; 95% CI 0.0052, 0.0624). CONCLUSIONS/INTERPRETATION We identified new candidates involved in the development of derangements in glucose metabolism and type 2 diabetes and confirmed previously reported proteins. Our findings underscore the importance of proteins in the pathogenesis of type 2 diabetes and the identified putative proteins can function as potential pharmacological targets for diabetes treatment and prevention.
Collapse
Affiliation(s)
- Hong Luo
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Pettenkofer School of Public Health, Munich, Germany
| | - Alina Bauer
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Jana Nano
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Pettenkofer School of Public Health, Munich, Germany
| | - Agnese Petrera
- Metabolomics and Proteomics Core, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Wolfgang Rathmann
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine Universität Düsseldorf, Düsseldorf, Germany
- German Center for Diabetes Research (DZD), Partner Düsseldorf, Neuherberg, Germany
| | - Christian Herder
- German Center for Diabetes Research (DZD), Partner Düsseldorf, Neuherberg, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine Universität Düsseldorf, Düsseldorf, Germany
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine Universität Düsseldorf, Düsseldorf, Germany
| | - Stefanie M Hauck
- Metabolomics and Proteomics Core, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- German Center for Diabetes Research (DZD), Partner München-Neuherberg, Neuherberg, Germany
| | - Benjamin B Sun
- Translation Sciences, Research & Development, Biogen Inc., Cambridge, MA, USA
| | - Annika Hoyer
- Biostatistics and Medical Biometry, Medical School OWL, Bielefeld University, Bielefeld, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Pettenkofer School of Public Health, Munich, Germany
- German Center for Diabetes Research (DZD), Partner München-Neuherberg, Neuherberg, Germany
| | - Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany.
- German Center for Diabetes Research (DZD), Partner München-Neuherberg, Neuherberg, Germany.
| |
Collapse
|
16
|
Noordam R, Brochard TA, Drewes YM, Gussekloo J, Mooijaart SP, Willems van Dijk K, Trompet S, Jukema JW, van Heemst D. Cardiovascular risk factors and major recurrent coronary events: A genetic liability study in patients with coronary artery disease in the UK Biobank. Atherosclerosis 2023; 376:19-25. [PMID: 37257353 DOI: 10.1016/j.atherosclerosis.2023.05.011] [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: 12/15/2022] [Revised: 05/14/2023] [Accepted: 05/16/2023] [Indexed: 06/02/2023]
Abstract
BACKGROUND AND AIMS Mendelian randomization confirmed multiple risk factors for primary events of coronary artery disease (CAD), but no such studies have been performed on recurrent major coronary events despite interesting insights derived from other designs. We examined the associations between genetically-influenced classical cardiovascular risk factors and the risk of recurrent major coronary events in a cohort of CAD patients. METHODS We included all first-time CAD cases (defined as angina pectoris, chronic ischemic heart disease or acute myocardial infarction) of European ancestry from the UK Biobank. Cases were followed till the end of follow-up, death or when they developed a recurrent major coronary event (chronic ischemic heart disease or acute myocardial infarction). Standardized weighted genetic risk scores were calculated for body mass index (BMI), systolic blood pressure, LDL cholesterol and triglycerides. RESULTS From a total of 22,949 CAD patients (mean age at first diagnosis 59.8 (SD 7.3) years, 71.1% men), 12,539 (54.6%) reported a recurrent major coronary event within a period of maximum 17.8 years. One standard deviation higher genetically-determined LDL cholesterol was associated with a higher risk of a recurrent major coronary event (odds ratio: 1.08 [95% confidence interval: 1.05, 1.11]). No associations were observed for genetically-influenced BMI (1.00 [0.98, 1.03]), systolic blood pressure (1.01 [0.98, 1.03]) and triglycerides (1.02 [0.995, 1.05]). CONCLUSIONS Despite the use risk-reducing medications following a first coronary event, this study provided genetic evidence that, of the classical risk factors, mainly high LDL cholesterol was associated with a higher risk of developing recurrent major coronary events.
Collapse
Affiliation(s)
- Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands.
| | - Thomas Ag Brochard
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Yvonne M Drewes
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands; Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, the Netherlands
| | - Jacobijn Gussekloo
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands; Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, the Netherlands
| | - Simon P Mooijaart
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Ko Willems van Dijk
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands; Department of Internal Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, the Netherlands; Leiden Laboratory of Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Stella Trompet
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands; Netherlands Heart Institute, Utrecht, the Netherlands
| | - Diana van Heemst
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| |
Collapse
|
17
|
Zuo Y, He Z, Chen Y, Dai L. Dual role of ANGPTL4 in inflammation. Inflamm Res 2023:10.1007/s00011-023-01753-9. [PMID: 37300585 DOI: 10.1007/s00011-023-01753-9] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 05/24/2023] [Accepted: 05/26/2023] [Indexed: 06/12/2023] Open
Abstract
BACKGROUND Angiopoietin-like 4 (ANGPTL4) belongs to the angiopoietin-like protein family and mediates the inhibition of lipoprotein lipase activity. Emerging evidence suggests that ANGPTL4 has pleiotropic functions with anti- and pro-inflammatory properties. METHODS A thorough search on PubMed related to ANGPTL4 and inflammation was performed. RESULTS Genetic inactivation of ANGPTL4 can significantly reduce the risk of developing coronary artery disease and diabetes. However, antibodies against ANGPTL4 result in several undesirable effects in mice or monkeys, such as lymphadenopathy and ascites. Based on the research progress on ANGPTL4, we systematically discussed the dual role of ANGPTL4 in inflammation and inflammatory diseases (lung injury, pancreatitis, heart diseases, gastrointestinal diseases, skin diseases, metabolism, periodontitis, and osteolytic diseases). This may be attributed to several factors, including post-translational modification, cleavage and oligomerization, and subcellular localization. CONCLUSION Understanding the potential underlying mechanisms of ANGPTL4 in inflammation in different tissues and diseases will aid in drug discovery and treatment development.
Collapse
Affiliation(s)
- Yuyue Zuo
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
- Department of Dermatology, Wuhan No. 1 Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Zhen He
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
- Hubei Provincial Engineering Research Center of Vascular Interventional Therapy, Wuhan, 430030, Hubei, China
| | - Yu Chen
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
- Hubei Provincial Engineering Research Center of Vascular Interventional Therapy, Wuhan, 430030, Hubei, China
| | - Lei Dai
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.
- Hubei Provincial Engineering Research Center of Vascular Interventional Therapy, Wuhan, 430030, Hubei, China.
| |
Collapse
|
18
|
Kumari A, Grønnemose AL, Kristensen KK, Winther AML, Young SG, Jørgensen TJD, Ploug M. Inverse effects of APOC2 and ANGPTL4 on the conformational dynamics of lid-anchoring structures in lipoprotein lipase. Proc Natl Acad Sci U S A 2023; 120:e2221888120. [PMID: 37094117 PMCID: PMC10160976 DOI: 10.1073/pnas.2221888120] [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] [Received: 01/03/2023] [Accepted: 03/28/2023] [Indexed: 04/26/2023] Open
Abstract
The lipolytic processing of triglyceride-rich lipoproteins (TRLs) by lipoprotein lipase (LPL) is crucial for the delivery of dietary lipids to the heart, skeletal muscle, and adipose tissue. The processing of TRLs by LPL is regulated in a tissue-specific manner by a complex interplay between activators and inhibitors. Angiopoietin-like protein 4 (ANGPTL4) inhibits LPL by reducing its thermal stability and catalyzing the irreversible unfolding of LPL's α/β-hydrolase domain. We previously mapped the ANGPTL4 binding site on LPL and defined the downstream unfolding events resulting in LPL inactivation. The binding of LPL to glycosylphosphatidylinositol-anchored high-density lipoprotein-binding protein 1 protects against LPL unfolding. The binding site on LPL for an activating cofactor, apolipoprotein C2 (APOC2), and the mechanisms by which APOC2 activates LPL have been unclear and controversial. Using hydrogen-deuterium exchange/mass spectrometry, we now show that APOC2's C-terminal α-helix binds to regions of LPL surrounding the catalytic pocket. Remarkably, APOC2's binding site on LPL overlaps with that for ANGPTL4, but their effects on LPL conformation are distinct. In contrast to ANGPTL4, APOC2 increases the thermal stability of LPL and protects it from unfolding. Also, the regions of LPL that anchor the lid are stabilized by APOC2 but destabilized by ANGPTL4, providing a plausible explanation for why APOC2 is an activator of LPL, while ANGPTL4 is an inhibitor. Our studies provide fresh insights into the molecular mechanisms by which APOC2 binds and stabilizes LPL-and properties that we suspect are relevant to the conformational gating of LPL's active site.
Collapse
Affiliation(s)
- Anni Kumari
- Finsen Laboratory, Copenhagen University Hospital-Rigshospitalet, DK-2200Copenhagen N, Denmark
- Finsen Laboratory, Biotech Research and Innovation Centre, University of Copenhagen, DK-2200Copenhagen N, Denmark
| | - Anne Louise Grønnemose
- Finsen Laboratory, Copenhagen University Hospital-Rigshospitalet, DK-2200Copenhagen N, Denmark
- Finsen Laboratory, Biotech Research and Innovation Centre, University of Copenhagen, DK-2200Copenhagen N, Denmark
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, DK–5320Odense, Denmark
| | - Kristian K. Kristensen
- Finsen Laboratory, Copenhagen University Hospital-Rigshospitalet, DK-2200Copenhagen N, Denmark
- Finsen Laboratory, Biotech Research and Innovation Centre, University of Copenhagen, DK-2200Copenhagen N, Denmark
| | - Anne-Marie L. Winther
- Finsen Laboratory, Copenhagen University Hospital-Rigshospitalet, DK-2200Copenhagen N, Denmark
- Finsen Laboratory, Biotech Research and Innovation Centre, University of Copenhagen, DK-2200Copenhagen N, Denmark
| | - Stephen G. Young
- Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA90095
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA90095
| | - Thomas J. D. Jørgensen
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, DK–5320Odense, Denmark
| | - Michael Ploug
- Finsen Laboratory, Copenhagen University Hospital-Rigshospitalet, DK-2200Copenhagen N, Denmark
- Finsen Laboratory, Biotech Research and Innovation Centre, University of Copenhagen, DK-2200Copenhagen N, Denmark
| |
Collapse
|
19
|
Gomes D, Sobolewski C, Conzelmann S, Schaer T, Lefai E, Alfaiate D, Tseligka ED, Goossens N, Tapparel C, Negro F, Foti M, Clément S. ANGPTL4 is a potential driver of HCV-induced peripheral insulin resistance. Sci Rep 2023; 13:6767. [PMID: 37185283 PMCID: PMC10130097 DOI: 10.1038/s41598-023-33728-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 04/18/2023] [Indexed: 05/17/2023] Open
Abstract
Chronic hepatitis C (CHC) is associated with the development of metabolic disorders, including both hepatic and extra-hepatic insulin resistance (IR). Here, we aimed at identifying liver-derived factor(s) potentially inducing peripheral IR and uncovering the mechanisms whereby HCV can regulate the action of these factors. We found ANGPTL4 (Angiopoietin Like 4) mRNA expression levels to positively correlate with HCV RNA (r = 0.46, p < 0.03) and HOMA-IR score (r = 0.51, p = 0.01) in liver biopsies of lean CHC patients. Moreover, we observed an upregulation of ANGPTL4 expression in two models recapitulating HCV-induced peripheral IR, i.e. mice expressing core protein of HCV genotype 3a (HCV-3a core) in hepatocytes and hepatoma cells transduced with HCV-3a core. Treatment of differentiated myocytes with recombinant ANGPTL4 reduced insulin-induced Akt-Ser473 phosphorylation. In contrast, conditioned medium from ANGPTL4-KO hepatoma cells prevented muscle cells from HCV-3a core induced IR. Treatment of HCV-3a core expressing HepG2 cells with PPARγ antagonist resulted in a decrease of HCV-core induced ANGPTL4 upregulation. Together, our data identified ANGPTL4 as a potential driver of HCV-induced IR and may provide working hypotheses aimed at understanding the pathogenesis of IR in the setting of other chronic liver disorders.
Collapse
Affiliation(s)
- Diana Gomes
- Department of Pathology and Immunology, University of Geneva, Geneva, Switzerland
- Koch Institute for Integrative Cancer Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Cyril Sobolewski
- Cell Physiology and Metabolism, University of Geneva, Geneva, Switzerland
- U1286-INFINITE-Institute for Translational Research in Inflammation, CHU Lille, Inserm, University Lille, 59000, Lille, France
| | - Stéphanie Conzelmann
- Department of Pathology and Immunology, University of Geneva, Geneva, Switzerland
| | - Tifany Schaer
- Department of Pathology and Immunology, University of Geneva, Geneva, Switzerland
| | - Etienne Lefai
- Unité de Nutrition Humaine, INRAE, Université Clermont Auvergne, 63000, Clermont-Ferrand, France
| | - Dulce Alfaiate
- Department of Pathology and Immunology, University of Geneva, Geneva, Switzerland
- Department of Infectious Diseases, Hôpital de la Croix Rousse, Lyon University Hospitals, Lyon, France
| | - Eirini D Tseligka
- Department of Pathology and Immunology, University of Geneva, Geneva, Switzerland
| | - Nicolas Goossens
- Gastroenterology and Hepatology Division, University Hospitals, Geneva, Switzerland
| | - Caroline Tapparel
- Department of Microbiology and Molecular Medicine, University of Geneva, Geneva, Switzerland
| | - Francesco Negro
- Gastroenterology and Hepatology Division, University Hospitals, Geneva, Switzerland
- Clinical Pathology Division, University Hospitals, Geneva, Switzerland
| | - Michelangelo Foti
- Cell Physiology and Metabolism, University of Geneva, Geneva, Switzerland
| | - Sophie Clément
- Department of Microbiology and Molecular Medicine, University of Geneva, Geneva, Switzerland.
- Clinical Pathology Division, University Hospitals, Geneva, Switzerland.
| |
Collapse
|
20
|
Li Z, Zhang B, Liu Q, Tao Z, Ding L, Guo B, Zhang E, Zhang H, Meng Z, Guo S, Chen Y, Peng J, Li J, Wang C, Huang Y, Xu H, Wu Y. Genetic association of lipids and lipid-lowering drug target genes with non-alcoholic fatty liver disease. EBioMedicine 2023; 90:104543. [PMID: 37002989 PMCID: PMC10070091 DOI: 10.1016/j.ebiom.2023.104543] [Citation(s) in RCA: 59] [Impact Index Per Article: 29.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 03/09/2023] [Accepted: 03/13/2023] [Indexed: 04/03/2023] Open
Abstract
BACKGROUND Some observational studies found that dyslipidaemia is a risk factor for non-alcoholic fatty liver disease (NAFLD), and lipid-lowering drugs may lower NAFLD risk. However, it remains unclear whether dyslipidaemia is causative for NAFLD. This Mendelian randomisation (MR) study aimed to explore the causal role of lipid traits in NAFLD and evaluate the potential effect of lipid-lowering drug targets on NAFLD. METHODS Genetic variants associated with lipid traits and variants of genes encoding lipid-lowering drug targets were extracted from the Global Lipids Genetics Consortium genome-wide association study (GWAS). Summary statistics for NAFLD were obtained from two independent GWAS datasets. Lipid-lowering drug targets that reached significance were further tested using expression quantitative trait loci data in relevant tissues. Colocalisation and mediation analyses were performed to validate the robustness of the results and explore potential mediators. FINDINGS No significant effect of lipid traits and eight lipid-lowering drug targets on NAFLD risk was found. Genetic mimicry of lipoprotein lipase (LPL) enhancement was associated with lower NAFLD risks in two independent datasets (OR1 = 0.60 [95% CI 0.50-0.72], p1 = 2.07 × 10-8; OR2 = 0.57 [95% CI 0.39-0.82], p2 = 3.00 × 10-3). A significant MR association (OR = 0.71 [95% CI, 0.58-0.87], p = 1.20 × 10-3) and strong colocalisation association (PP.H4 = 0.85) with NAFLD were observed for LPL expression in subcutaneous adipose tissue. Fasting insulin and type 2 diabetes mediated 7.40% and 9.15%, respectively, of the total effect of LPL on NAFLD risk. INTERPRETATION Our findings do not support dyslipidaemia as a causal factor for NAFLD. Among nine lipid-lowering drug targets, LPL is a promising candidate drug target in NAFLD. The mechanism of action of LPL in NAFLD may be independent of its lipid-lowering effects. FUNDING Capital's Funds for Health Improvement and Research (2022-4-4037). CAMS Innovation Fund for Medical Sciences (CIFMS, grant number: 2021-I2M-C&T-A-010).
Collapse
Affiliation(s)
- Ziang Li
- State Key Laboratory of Cardiovascular Disease, Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Bin Zhang
- State Key Laboratory of Cardiovascular Disease, Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Qingrong Liu
- Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Zhihang Tao
- State Key Laboratory for Oncogenes and Related Genes, Key Laboratory of Gastroenterology and Hepatology, Ministry of Health, Division of Gastroenterology and Hepatology, Shanghai Institute of Digestive Disease, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Lu Ding
- Department of Endocrinology, Key Laboratory of Endocrinology, Ministry of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Bo Guo
- Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Erli Zhang
- Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Haitong Zhang
- Department of Cardiology, the Third-Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Zhen Meng
- Department of Cardiology, China-Japan Friendship Hospital, Beijing, China
| | - Shuai Guo
- State Key Laboratory of Cardiovascular Disease, Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Yang Chen
- State Key Laboratory of Cardiovascular Disease, Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Jia Peng
- Department of Cardiology, the First-Affiliated Hospital, Xiangya Hospital Central South University, Changsha, China
| | - Jinyue Li
- Key Laboratory of Cardiovascular Epidemiology & 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, China
| | - Can Wang
- State Key Laboratory of Cardiovascular Disease, Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Yingbo Huang
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Haiyan Xu
- Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China.
| | - Yongjian Wu
- Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China.
| |
Collapse
|
21
|
Li H, Xie X, Liu H, Zhang L, Qiang D, Li L, He YT, Bai G. Analysis of protein expression changes in patients with prediabetes using proteomics approaches. RAPID COMMUNICATIONS IN MASS SPECTROMETRY : RCM 2023; 37:e9448. [PMID: 36460301 DOI: 10.1002/rcm.9448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 11/11/2022] [Accepted: 11/25/2022] [Indexed: 06/17/2023]
Abstract
RATIONALE Proteomics and metabolomics are widely used in the study of diabetes, but rarely in prediabetes research. This study aimed to explore the mechanisms of early-onset type 2 diabetes mellitus (T2DM) by analyzing proteomic changes at different stages of glucose metabolism. METHODS A total of 40 individuals undergoing routine physical health examinations between December 2016 and April 2017 were enrolled. Subjects were divided into four groups based on fasting blood glucose (FPG) levels: FPG < 5.6 mmol/L (group A); FPG ≥ 5.6 mmol/L and <6.1 mmol/L (group B); FPG ≥ 6.1 mmol/L and <7.0 mmol/L (group C); and FPG ≥ 7.0 mmol/L (group D). Each group had 10 cases. Sera from these 40 subjects were analyzed by label-free quantitative liquid chromatography coupled with tandem mass spectrometry (LC/MS/MS). LC/MS/MS with selected reaction monitoring mode was also performed for qualitative and quantitative metabolomics analysis. Differentially expressed proteins were identified. Partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to analyze the differentially expressed metabolites. RESULTS A total of 202 differentially expressed proteins were screened and were identified as mainly secreted proteins. Comparing group A with group B, 32 proteins were up-regulated and 18 proteins were down-regulated. Comparing group A with group C, 24 proteins were up-regulated and 24 proteins were down-regulated. Comparing group A with group D, 19 proteins were up-regulated and 17 proteins were down-regulated. The fold change for up-regulated proteins was >1.2, p < 0.05, while the fold change for down-regulated proteins was <-1.2, p < 0.05. PLS-DA and OPLS-DA revealed 113 differentially expressed metabolites. Correlation analysis of differentially expressed metabolites of group A versus group B revealed that among the down-regulated differential proteins, transforming growth factor β-induced protein ig-h3 correlated negatively with metabolite L-saccharin, while among the up-regulated differential proteins, apolipoprotein C-IV correlated negatively with metabolite 3-methyloxindole. Among all differentially expressed proteins, 19 proteins were associated with early initiation of chronic inflammation, including CD14 and CSF-1R, which were newly identified in the early onset of T2DM. CONCLUSIONS Many proteins are differentially expressed between prediabetes and after T2DM diagnosis, although the specific mechanism remains unclear. The expression level of CD14 was significantly up-regulated and that of CSF-1R was significantly down-regulated when FPG was ≥5.6 mmol/L, suggesting that CD14 and CSF-1R may be important markers for early-onset T2DM and may serve as new targets for T2DM treatment.
Collapse
Affiliation(s)
- Huan Li
- Department of Endocrinology, First People's Hospital of Yinchuan, Yinchuan, China
| | - Xiaomin Xie
- Department of Endocrinology, First People's Hospital of Yinchuan, Yinchuan, China
| | - Huili Liu
- Department of Endocrinology, First People's Hospital of Yinchuan, Yinchuan, China
| | - Li Zhang
- Department of Endocrinology, First People's Hospital of Yinchuan, Yinchuan, China
| | - Dan Qiang
- Department of Endocrinology, First People's Hospital of Yinchuan, Yinchuan, China
| | - Ling Li
- Department of Endocrinology, First People's Hospital of Yinchuan, Yinchuan, China
| | - Yan Ting He
- Department of Endocrinology, First People's Hospital of Yinchuan, Yinchuan, China
| | - Guirong Bai
- Department of Endocrinology, First People's Hospital of Yinchuan, Yinchuan, China
| |
Collapse
|
22
|
Burgess S, Mason AM, Grant AJ, Slob EAW, Gkatzionis A, Zuber V, Patel A, Tian H, Liu C, Haynes WG, Hovingh GK, Knudsen LB, Whittaker JC, Gill D. Using genetic association data to guide drug discovery and development: Review of methods and applications. Am J Hum Genet 2023; 110:195-214. [PMID: 36736292 PMCID: PMC9943784 DOI: 10.1016/j.ajhg.2022.12.017] [Citation(s) in RCA: 59] [Impact Index Per Article: 29.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
Evidence on the validity of drug targets from randomized trials is reliable but typically expensive and slow to obtain. In contrast, evidence from conventional observational epidemiological studies is less reliable because of the potential for bias from confounding and reverse causation. Mendelian randomization is a quasi-experimental approach analogous to a randomized trial that exploits naturally occurring randomization in the transmission of genetic variants. In Mendelian randomization, genetic variants that can be regarded as proxies for an intervention on the proposed drug target are leveraged as instrumental variables to investigate potential effects on biomarkers and disease outcomes in large-scale observational datasets. This approach can be implemented rapidly for a range of drug targets to provide evidence on their effects and thus inform on their priority for further investigation. In this review, we present statistical methods and their applications to showcase the diverse opportunities for applying Mendelian randomization in guiding clinical development efforts, thus enabling interventions to target the right mechanism in the right population group at the right time. These methods can inform investigators on the mechanisms underlying drug effects, their related biomarkers, implications for the timing of interventions, and the population subgroups that stand to gain the most benefit. Most methods can be implemented with publicly available data on summarized genetic associations with traits and diseases, meaning that the only major limitations to their usage are the availability of appropriately powered studies for the exposure and outcome and the existence of a suitable genetic proxy for the proposed intervention.
Collapse
Affiliation(s)
- Stephen Burgess
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK; Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
| | - Amy M Mason
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Andrew J Grant
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Eric A W Slob
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | | | - Verena Zuber
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK; UK Dementia Research Institute at Imperial College, Imperial College London, London, UK
| | - Ashish Patel
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Haodong Tian
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Cunhao Liu
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - William G Haynes
- Novo Nordisk Research Centre Oxford, Novo Nordisk, Oxford, UK; Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - G Kees Hovingh
- Department of Vascular Medicine, Academic Medical Center, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, the Netherlands; Global Chief Medical Office, Novo Nordisk, Copenhagen, Denmark
| | - Lotte Bjerre Knudsen
- Chief Scientific Advisor Office, Research and Early Development, Novo Nordisk, Copenhagen, Denmark
| | - John C Whittaker
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; Chief Scientific Advisor Office, Research and Early Development, Novo Nordisk, Copenhagen, Denmark
| |
Collapse
|
23
|
Timasheva Y, Balkhiyarova Z, Avzaletdinova D, Rassoleeva I, Morugova TV, Korytina G, Prokopenko I, Kochetova O. Integrating Common Risk Factors with Polygenic Scores Improves the Prediction of Type 2 Diabetes. Int J Mol Sci 2023; 24:ijms24020984. [PMID: 36674502 PMCID: PMC9866792 DOI: 10.3390/ijms24020984] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 12/12/2022] [Accepted: 12/22/2022] [Indexed: 01/07/2023] Open
Abstract
We tested associations between 13 established genetic variants and type 2 diabetes (T2D) in 1371 study participants from the Volga-Ural region of the Eurasian continent, and evaluated the predictive ability of the model containing polygenic scores for the variants associated with T2D in our dataset, alone and in combination with other risk factors such as age and sex. Using logistic regression analysis, we found associations with T2D for the CCL20 rs6749704 (OR = 1.68, PFDR = 3.40 × 10-5), CCR5 rs333 (OR = 1.99, PFDR = 0.033), ADIPOQ rs17366743 (OR = 3.17, PFDR = 2.64 × 10-4), TCF7L2 rs114758349 (OR = 1.77, PFDR = 9.37 × 10-5), and CCL2 rs1024611 (OR = 1.38, PFDR = 0.033) polymorphisms. We showed that the most informative prognostic model included weighted polygenic scores for these five loci, and non-genetic factors such as age and sex (AUC 85.8%, 95%CI 83.7-87.8%). Compared to the model containing only non-genetic parameters, adding the polygenic score for the five T2D-associated loci showed improved net reclassification (NRI = 37.62%, 1.39 × 10-6). Inclusion of all 13 tested SNPs to the model with age and sex did not improve the predictive ability compared to the model containing five T2D-associated variants (NRI = -17.86, p = 0.093). The five variants associated with T2D in people from the Volga-Ural region are linked to inflammation (CCR5, CCL2, CCL20) and glucose metabolism regulation (TCF7L, ADIPOQ2). Further studies in independent groups of T2D patients should validate the prognostic value of the model and elucidate the molecular mechanisms of the disease development.
Collapse
Affiliation(s)
- Yanina Timasheva
- Institute of Biochemistry and Genetics, Ufa Federal Research Centre of Russian Academy of Sciences, 450054 Ufa, Russia
- Department of Medical Genetics and Fundamental Medicine, Bashkir State Medical University, 450008 Ufa, Russia
- Correspondence:
| | - Zhanna Balkhiyarova
- Section of Statistical Multi-Omics, Department of Clinical & Experimental Medicine, School of Biosciences & Medicine, University of Surrey, Guildford GU2 7XH, UK
- Department of Endocrinology, Bashkir State Medical University, 450008 Ufa, Russia
| | - Diana Avzaletdinova
- Department of Endocrinology, Bashkir State Medical University, 450008 Ufa, Russia
| | - Irina Rassoleeva
- Department of Endocrinology, Bashkir State Medical University, 450008 Ufa, Russia
| | - Tatiana V. Morugova
- Department of Endocrinology, Bashkir State Medical University, 450008 Ufa, Russia
| | - Gulnaz Korytina
- Institute of Biochemistry and Genetics, Ufa Federal Research Centre of Russian Academy of Sciences, 450054 Ufa, Russia
| | - Inga Prokopenko
- Section of Statistical Multi-Omics, Department of Clinical & Experimental Medicine, School of Biosciences & Medicine, University of Surrey, Guildford GU2 7XH, UK
| | - Olga Kochetova
- Institute of Biochemistry and Genetics, Ufa Federal Research Centre of Russian Academy of Sciences, 450054 Ufa, Russia
| |
Collapse
|
24
|
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.
Collapse
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
| |
Collapse
|
25
|
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.
Collapse
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
| |
Collapse
|
26
|
Obesity and cancer-extracellular matrix, angiogenesis, and adrenergic signaling as unusual suspects linking the two diseases. Cancer Metastasis Rev 2022; 41:517-547. [PMID: 36074318 PMCID: PMC9470659 DOI: 10.1007/s10555-022-10058-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 07/29/2022] [Indexed: 12/24/2022]
Abstract
Obesity is an established risk factor for several human cancers. Given the association between excess body weight and cancer, the increasing rates of obesity worldwide are worrisome. A variety of obesity-related factors has been implicated in cancer initiation, progression, and response to therapy. These factors include circulating nutritional factors, hormones, and cytokines, causing hyperinsulinemia, inflammation, and adipose tissue dysfunction. The impact of these conditions on cancer development and progression has been the focus of extensive literature. In this review, we concentrate on processes that can link obesity and cancer, and which provide a novel perspective: extracellular matrix remodeling, angiogenesis, and adrenergic signaling. We describe molecular mechanisms involved in these processes, which represent putative targets for intervention. Liver, pancreas, and breast cancers were chosen as exemplary disease models. In view of the expanding epidemic of obesity, a better understanding of the tumorigenic process in obese individuals might lead to more effective treatments and preventive measures.
Collapse
|
27
|
Ghouse J, Ahlberg G, Skov AG, Bundgaard H, Olesen MS. Association of Common and Rare Genetic Variation in the 3-Hydroxy-3-Methylglutaryl Coenzyme A Reductase Gene and Cataract Risk. J Am Heart Assoc 2022; 11:e025361. [PMID: 35703387 PMCID: PMC9238641 DOI: 10.1161/jaha.122.025361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 04/14/2022] [Indexed: 12/03/2022]
Abstract
Background Results from animal models and observational studies have raised concerns regarding the potential cataractogenic effects of statin treatment. We investigated whether common and rare genetic variants in HMGCR are associated with cataract risk, to gauge the likely long-term effects of statin treatment on lenticular opacities. Methods and Results We used genotyping data and exome sequencing data of unrelated European individuals in the UK Biobank to test the association between genetically proxied inhibition of HMGCR and cataract risk. First, we constructed an HMGCR genetic score consisting of 5 common variants weighted by their association with low-density lipoprotein cholesterol. Second, we analyzed exome sequencing data to identify carriers of predicted loss-of-function mutations in HMGCR. Common and rare variants in aggregate were then tested for association with cataract and cataract surgery. In an analysis of >402 000 individuals, a 38.7 mg/dL (1 mmol/L) reduction in low-density lipoprotein C by the HMGCR genetic score was associated with higher risk for cataract (odds ratio, 1.14 [95% CI, 1.00-1.39], P=0.045) and cataract surgery (odds ratio, 1.25 [95% CI, 1.06-1.48], P=0.009). Among 169 172 individuals with HMGCR sequencing data, we identified 32 participants (0.02%), who carried a rare HMGCR predicted loss-of-function variant. Compared with noncarriers, heterozygous carriers of HMGCR predicted loss-of-function had a higher risk of developing cataract (odds ratio, 4.54 [95% CI, 1.96-10.53], P=0.001) and cataract surgery (odds ratio, 5.27 [95% CI, 2.27-12.25], P=5.37×10-4). In exploratory analyses, we found no significant association between genetically proxied inhibition of PCSK9, NPC1L1, or circulating low-density lipoprotein cholesterol levels (P>0.05 for all) and cataract risk. Conclusions We found that genetically proxied inhibition of the HMGCR gene mimicking long-term statin treatment associated with higher risk of cataract. Clinical trials with longer follow-up are needed to confirm these findings.
Collapse
Affiliation(s)
- Jonas Ghouse
- Laboratory for Molecular CardiologyDepartment of CardiologyCopenhagen University Hospital, RigshospitaletCopenhagenDenmark
- Laboratory for Molecular CardiologyDepartment of Biomedical SciencesUniversity of CopenhagenDenmark
| | - Gustav Ahlberg
- Laboratory for Molecular CardiologyDepartment of CardiologyCopenhagen University Hospital, RigshospitaletCopenhagenDenmark
- Laboratory for Molecular CardiologyDepartment of Biomedical SciencesUniversity of CopenhagenDenmark
| | - Anne Guldhammer Skov
- Department of OphthalmologyCopenhagen University HospitalRigshospitalet‐GlostrupUniversity of CopenhagenDenmark
| | - Henning Bundgaard
- Department of CardiologyCopenhagen University Hospital, RigshospitaletUniversity of CopenhagenDenmark
| | - Morten S. Olesen
- Laboratory for Molecular CardiologyDepartment of CardiologyCopenhagen University Hospital, RigshospitaletCopenhagenDenmark
- Laboratory for Molecular CardiologyDepartment of Biomedical SciencesUniversity of CopenhagenDenmark
| |
Collapse
|
28
|
Deng M, Kutrolli E, Sadewasser A, Michel S, Joibari MM, Jaschinski F, Olivecrona G, Nilsson SK, Kersten S. ANGPTL4 silencing via antisense oligonucleotides reduces plasma triglycerides and glucose in mice without causing lymphadenopathy. J Lipid Res 2022; 63:100237. [PMID: 35667416 PMCID: PMC9270256 DOI: 10.1016/j.jlr.2022.100237] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 04/30/2022] [Accepted: 05/31/2022] [Indexed: 11/17/2022] Open
Abstract
Angiopoietin-like 4 (ANGPTL4) is an important regulator of plasma triglyceride (TG) levels and an attractive pharmacological target for lowering plasma lipids and reducing cardiovascular risk. Here, we aimed to study the efficacy and safety of silencing ANGPTL4 in the livers of mice using hepatocyte-targeting GalNAc-conjugated antisense oligonucleotides (ASOs). Compared with injections with negative control ASO, four injections of two different doses of ANGPTL4 ASO over 2 weeks markedly downregulated ANGPTL4 levels in liver and adipose tissue, which was associated with significantly higher adipose LPL activity and lower plasma TGs in fed and fasted mice, as well as lower plasma glucose levels in fed mice. In separate experiments, injection of two different doses of ANGPTL4 ASO over 20 weeks of high-fat feeding reduced hepatic and adipose ANGPTL4 levels but did not trigger mesenteric lymphadenopathy, an acute phase response, chylous ascites, or any other pathological phenotypes. Compared with mice injected with negative control ASO, mice injected with ANGPTL4 ASO showed reduced food intake, reduced weight gain, and improved glucose tolerance. In addition, they exhibited lower plasma TGs, total cholesterol, LDL-C, glucose, serum amyloid A, and liver TG levels. By contrast, no significant difference in plasma alanine aminotransferase activity was observed. Overall, these data suggest that ASOs targeting ANGPTL4 effectively reduce plasma TG levels in mice without raising major safety concerns.
Collapse
Affiliation(s)
- Mingjuan Deng
- Nutrition, Metabolism and Genomics Group, Division of Human Nutrition and Health, Wageningen University, the Netherlands
| | - Elda Kutrolli
- Lipigon Pharmaceuticals AB, Tvistevägen 48C, 907 36, Umeå, Sweden
| | - Anne Sadewasser
- Secarna Pharmaceuticals GmbH & Co. KG, Am Klopferspitz 19, 82152 Planegg, Germany
| | - Sven Michel
- Secarna Pharmaceuticals GmbH & Co. KG, Am Klopferspitz 19, 82152 Planegg, Germany
| | | | - Frank Jaschinski
- Secarna Pharmaceuticals GmbH & Co. KG, Am Klopferspitz 19, 82152 Planegg, Germany
| | - Gunilla Olivecrona
- Lipigon Pharmaceuticals AB, Tvistevägen 48C, 907 36, Umeå, Sweden; Department of Medical Biosciences, Umeå University, SE-901 87, Umeå, Sweden
| | - Stefan K Nilsson
- Lipigon Pharmaceuticals AB, Tvistevägen 48C, 907 36, Umeå, Sweden
| | - Sander Kersten
- Nutrition, Metabolism and Genomics Group, Division of Human Nutrition and Health, Wageningen University, the Netherlands.
| |
Collapse
|
29
|
Yu Z, Zhang L, Zhang G, Xia K, Yang Q, Huang T, Fan D. Lipids, Apolipoproteins, Statins and
ICH
: A Mendelian Randomization Study. Ann Neurol 2022; 92:390-399. [PMID: 35655417 DOI: 10.1002/ana.26426] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 05/25/2022] [Accepted: 05/27/2022] [Indexed: 11/10/2022]
Affiliation(s)
- Zhou Yu
- Department of Neurology Peking University Third Hospital Beijing China
| | - Linjing Zhang
- Department of Neurology Peking University Third Hospital Beijing China
| | - Gan Zhang
- Department of Neurology Peking University Third Hospital Beijing China
| | - Kailin Xia
- Department of Neurology Peking University Third Hospital Beijing China
| | - Qiong Yang
- Department of Neurology Peking University Third Hospital Beijing China
| | - Tao Huang
- Department of Epidemiology & Biostatistics, School of Public Health Peking University Beijing China
- Department of Global Health, School of Public Health Peking University China
- Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education China
| | - Dongsheng Fan
- Department of Neurology Peking University Third Hospital Beijing China
- Beijing Key Laboratory of Biomarker and Translational Research in Neurodegenerative Diseases Beijing China
- Key Laboratory for Neuroscience, National Health Commission/Ministry of Education Peking University Beijing China
| |
Collapse
|
30
|
Apolipoprotein A-V is a potential target for treating coronary artery disease: evidence from genetic and metabolomic analyses. J Lipid Res 2022; 63:100193. [PMID: 35278410 PMCID: PMC9062431 DOI: 10.1016/j.jlr.2022.100193] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 02/14/2022] [Accepted: 02/28/2022] [Indexed: 11/22/2022] Open
Abstract
Triglyceride (TG)-lowering LPL variants in combination with genetic LDL-C-lowering variants are associated with reduced risk of coronary artery disease (CAD). Genetic variation in the APOA5 gene encoding apolipoprotein A-V also strongly affects TG levels, but the potential clinical impact and underlying mechanisms are yet to be resolved. Here, we aimed to study the effects of APOA5 genetic variation on CAD risk and plasma lipoproteins through factorial genetic association analyses. Using data from 309,780 European-ancestry participants from the UK Biobank, we evaluated the effects of lower TG levels as a result of genetic variation in APOA5 and/or LPL on CAD risk with or without a background of reduced LDL-C. Next, we compared lower TG levels via APOA5 and LPL variation with over 100 lipoprotein measurements in a combined sample from the Netherlands Epidemiology of Obesity study (N = 4,838) and the Oxford Biobank (N = 6,999). We found that lower TG levels due to combined APOA5 and LPL variation and genetically-influenced lower LDL-C levels afforded the largest reduction in CAD risk (odds ratio: 0.78 (0.73-0.82)). Compared to patients with genetically-influenced lower TG via LPL, genetically-influenced lower TG via APOA5 had similar and independent, but notably larger, effects on the lipoprotein profile. Our results suggest that lower TG levels as a result of APOA5 variation have strong beneficial effects on CAD risk and the lipoprotein profile, which suggest apo A-V may be a potential novel therapeutic target for CAD prevention.
Collapse
|
31
|
Wu P, Moon JY, Daghlas I, Franco G, Porneala BC, Ahmadizar F, Richardson TG, Isaksen JL, Hindy G, Yao J, Sitlani CM, Raffield LM, Yanek LR, Feitosa MF, Cuadrat RR, Qi Q, Arfan Ikram M, Ellervik C, Ericson U, Goodarzi MO, Brody JA, Lange L, Mercader JM, Vaidya D, An P, Schulze MB, Masana L, Ghanbari M, Olesen MS, Cai J, Guo X, Floyd JS, Jäger S, Province MA, Kalyani RR, Psaty BM, Orho-Melander M, Ridker PM, Kanters JK, Uitterlinden A, Davey Smith G, Gill D, Kaplan RC, Kavousi M, Raghavan S, Chasman DI, Rotter JI, Meigs JB, Florez JC, Dupuis J, Liu CT, Merino J. Obesity Partially Mediates the Diabetogenic Effect of Lowering LDL Cholesterol. Diabetes Care 2022; 45:232-240. [PMID: 34789503 PMCID: PMC8753762 DOI: 10.2337/dc21-1284] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2021] [Accepted: 10/15/2021] [Indexed: 02/03/2023]
Abstract
OBJECTIVE LDL cholesterol (LDLc)-lowering drugs modestly increase body weight and type 2 diabetes risk, but the extent to which the diabetogenic effect of lowering LDLc is mediated through increased BMI is unknown. RESEARCH DESIGN AND METHODS We conducted summary-level univariable and multivariable Mendelian randomization (MR) analyses in 921,908 participants to investigate the effect of lowering LDLc on type 2 diabetes risk and the proportion of this effect mediated through BMI. We used data from 92,532 participants from 14 observational studies to replicate findings in individual-level MR analyses. RESULTS A 1-SD decrease in genetically predicted LDLc was associated with increased type 2 diabetes odds (odds ratio [OR] 1.12 [95% CI 1.01, 1.24]) and BMI (β = 0.07 SD units [95% CI 0.02, 0.12]) in univariable MR analyses. The multivariable MR analysis showed evidence of an indirect effect of lowering LDLc on type 2 diabetes through BMI (OR 1.04 [95% CI 1.01, 1.08]) with a proportion mediated of 38% of the total effect (P = 0.03). Total and indirect effect estimates were similar across a number of sensitivity analyses. Individual-level MR analyses confirmed the indirect effect of lowering LDLc on type 2 diabetes through BMI with an estimated proportion mediated of 8% (P = 0.04). CONCLUSIONS These findings suggest that the diabetogenic effect attributed to lowering LDLc is partially mediated through increased BMI. Our results could help advance understanding of adipose tissue and lipids in type 2 diabetes pathophysiology and inform strategies to reduce diabetes risk among individuals taking LDLc-lowering medications.
Collapse
Affiliation(s)
- Peitao Wu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Jee-Young Moon
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY
| | - Iyas Daghlas
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
| | - Giulianini Franco
- Division of Preventive Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Bianca C. Porneala
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA
| | - Fariba Ahmadizar
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Tom G. Richardson
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, U.K
- Novo Nordisk Research Centre Oxford, Old Road Campus, Oxford, U.K
| | - Jonas L. Isaksen
- Laboratory of Experimental Cardiology, Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Georgy Hindy
- Department of Clinical Sciences, Skåne University Hospital Malmo Clinical Research Center, Lund University, Malmo, Sweden
| | - Jie Yao
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Colleen M. Sitlani
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA
| | - Laura M. Raffield
- Department of Genetics, The University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Lisa R. Yanek
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Mary F. Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO
| | - Rafael R.C. Cuadrat
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
- German Center for Diabetes Research, Neuherberg, Germany
| | - Qibin Qi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY
| | - M. Arfan Ikram
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Christina Ellervik
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
- Department of Research, Region Zealand, Sorø, Denmark
| | - Ulrika Ericson
- Department of Clinical Sciences, Skåne University Hospital Malmo Clinical Research Center, Lund University, Malmo, Sweden
| | - Mark O. Goodarzi
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Jennifer A. Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA
| | - Leslie Lange
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Josep M. Mercader
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
| | - Dhananjay Vaidya
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Ping An
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO
| | - Matthias B. Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
- German Center for Diabetes Research, Neuherberg, Germany
- Institute of Nutritional Science, University of Potsdam, Nuthetal, Germany
| | - Lluis Masana
- Vascular Medicine and Metabolism Unit, Research Unit on Lipids and Atherosclerosis, Sant Joan University Hospital, Rovira i Virgil University, IISPV, Reus, Spain
- Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM), Madrid, Spain
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Morten S. Olesen
- Danish National Research Foundation Centre for Cardiac Arrhythmia, Copenhagen, Denmark
- Laboratory for Molecular Cardiology, Department of Cardiology, The Heart Centre, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Jianwen Cai
- Collaborative Studies Coordinating Center, Department of Biostatistics, The University of North Carolina at Chapel Hill, NC
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - James S. Floyd
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA
- Department of Epidemiology, University of Washington, Seattle, WA
| | - Susanne Jäger
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
- German Center for Diabetes Research, Neuherberg, Germany
| | - Michael A. Province
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO
| | - Rita R. Kalyani
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA
- Department of Epidemiology, University of Washington, Seattle, WA
- Department of Health Services, University of Washington, Seattle, WA
| | - Marju Orho-Melander
- Department of Clinical Sciences, Skåne University Hospital Malmo Clinical Research Center, Lund University, Malmo, Sweden
| | - Paul M. Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
| | - Jørgen K. Kanters
- Laboratory of Experimental Cardiology, Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Andre Uitterlinden
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, U.K
| | - Dipender Gill
- Novo Nordisk Research Centre Oxford, Old Road Campus, Oxford, U.K
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, U.K
- Clinical Pharmacology and Therapeutics Section, Institute of Medical and Biomedical Education and Institute for Infection and Immunity, St George’s, University of London, London, U.K
- Clinical Pharmacology Group, Pharmacy and Medicines Directorate, St George’s University Hospitals NHS Foundation Trust, London, U.K
| | - Robert C. Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle WA
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Sridharan Raghavan
- Department of Veterans Affairs Medical Center, Eastern Colorado Health Care System, Denver, CO
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado School of Medicine, Denver, CO
| | - Daniel I. Chasman
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
| | - Jerome I. Rotter
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - James B. Meigs
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
| | - Jose C. Florez
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
| | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Jordi Merino
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
- Vascular Medicine and Metabolism Unit, Research Unit on Lipids and Atherosclerosis, Sant Joan University Hospital, Rovira i Virgil University, IISPV, Reus, Spain
| |
Collapse
|
32
|
Ma Y, Zhou Z, Li X, Ding K, Xiao H, Wu Y, Wu T, Chen D. Linear and nonlinear analyses of the association between low-density lipoprotein cholesterol and diabetes: The spurious U-curve in observational study. Front Endocrinol (Lausanne) 2022; 13:1009095. [PMID: 36465637 PMCID: PMC9714469 DOI: 10.3389/fendo.2022.1009095] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 11/02/2022] [Indexed: 11/18/2022] Open
Abstract
OBJECTIVE Hyperlipidemia is traditionally considered a risk factor for diabetes. The effect of low-density lipoprotein cholesterol (LDL-C) is counterintuitive to diabetes. We sought to investigate the relationship between LDL-C and diabetes for better lipid management. METHODS We tested the shape of association between LDL-C and diabetes and created polygenic risk scores of LDL-C and generated linear Mendelian randomization (MR) estimates for the effect of LDL-C and diabetes. We evaluated for nonlinearity in the observational and genetic relationship between LDL-C and diabetes. RESULTS Traditional observational analysis suggested a complex non-linear association between LDL-C and diabetes while nonlinear MR analyses found no evidence for a non-linear association. Under the assumption of linear association, we found a consistently protective effect of LDL-C against diabetes among the females without lipid-lowering drugs use. The ORs were 0.84 (95% CI, 0.72-0.97, P=0.0168) in an observational analysis which was more prominent in MR analysis and suggested increasing the overall distribution of LDL-C in females led to an overall decrease in the risk of diabetes (P=0.0258). CONCLUSIONS We verified the liner protective effect of LDL-C against diabetes among the females without lipid-lowering drug use. Non-linear associations between LDL-C against diabetes in observational analysis are not causal.
Collapse
|
33
|
Jansen SA, Huiskens B, Trompet S, Jukema JW, Mooijaart SP, Willems van Dijk K, van Heemst D, Noordam R. Classical risk factors for primary coronary artery disease from an aging perspective through Mendelian Randomization. GeroScience 2021; 44:1703-1713. [PMID: 34932184 PMCID: PMC9213623 DOI: 10.1007/s11357-021-00498-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 12/11/2021] [Indexed: 11/25/2022] Open
Abstract
The significance of classical risk factors in coronary artery disease (CAD) remains unclear in older age due to possible changes in underlying disease pathologies. Therefore, we conducted Mendelian Randomization approaches to investigate the causal relationship between classical risk factors and primary CAD in different age groups. A Mendelian Randomization study was conducted in European-ethnicity individuals from the UK Biobank population. Analyses were performed using data of 22,313 CAD cases (71.6% men) and 407,920 controls (44.5% men). Using logistic regression analyses, we investigated the associations between standardized genetic risk score and primary CAD stratified by age of diagnosis. In addition, feature importance and model accuracy were assessed in different age groups to evaluate predictive power of the genetic risk scores with increasing age. We found age-dependent associations for all classical CAD risk factors. Notably, body mass index (OR 1.22 diagnosis < 50 years; OR 1.02 diagnosis > 70 years), blood pressure (OR 1.12 < 50 years; OR 1.04 > 70 years), LDL cholesterol (OR 1.16 < 50 years; OR 1.02 > 70 years), and triglyceride levels (OR 1.11 < 50 years; 1.04 > 70 years). In line with the Mendelian Randomization analyses, model accuracy and feature importance of the classical risk factors decreased with increasing age of diagnosis. Causal determinants for primary CAD are age dependent with classical CAD risk factors attenuating in relation with primary CAD with increasing age. These results question the need for (some) currently applied cardiovascular disease risk reducing interventions at older age.
Collapse
Affiliation(s)
- Swetta A Jansen
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, PO Box 9600, 2300RC, Leiden, The Netherlands
- Data Science Lab, Amsterdam, the Netherlands
| | | | - Stella Trompet
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, PO Box 9600, 2300RC, Leiden, The Netherlands
| | - JWouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
- Netherlands Heart Institute, Utrecht, the Netherlands
| | - Simon P Mooijaart
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, PO Box 9600, 2300RC, Leiden, The Netherlands
| | - Ko Willems van Dijk
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
- Department of Internal Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, the Netherlands
- Leiden Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - Diana van Heemst
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, PO Box 9600, 2300RC, Leiden, The Netherlands
| | - Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, PO Box 9600, 2300RC, Leiden, The Netherlands.
| |
Collapse
|
34
|
Abstract
PURPOSE OF REVIEW Elevated LDL-C and triglycerides are important risk factors for the development of atherosclerotic cardiovascular disease. Although effective therapies for lipid lowering exist, many people do not reach their treatment targets. In the last two decades, ANGPTL3 has emerged as a novel therapeutic target for lowering plasma LDL-C and triglycerides. Here, an overview of the recent literature on ANGPTL3 is provided, focusing on the therapeutic benefits of inactivation of ANGPTL3 via monoclonal antibodies, antisense oligonucleotides, and other more nascent approaches. In addition, the potential mechanisms by which ANGPTL3 inactivation lowers plasma LDL-C are discussed. RECENT FINDINGS ANGPTL3 is a factor secreted by the liver that inhibits lipoprotein lipase and other lipases via the formation of a complex with the related protein ANGPTL8. Large-scale genetic studies in humans have shown that carriers of loss-of-function variants in ANGPTL3 have lower plasma LDL-C and triglyceride levels, and are at reduced risk of atherosclerotic cardiovascular disease. Clinical studies in patients with different forms of dyslipidemia have demonstrated that inactivation of ANGPTL3 using monoclonal antibodies or antisense oligonucleotides markedly lowers plasma LDL-C and triglyceride levels. SUMMARY Anti-ANGPTL3 therapies hold considerable promise for reducing plasma LDL-C and triglycerides in selected patient groups.
Collapse
Affiliation(s)
- Sander Kersten
- Nutrition, Metabolism and Genomics Group, Division of Human Nutrition and Health, Wageningen University, the Netherlands
| |
Collapse
|
35
|
Role and mechanism of the action of angiopoietin-like protein ANGPTL4 in plasma lipid metabolism. J Lipid Res 2021; 62:100150. [PMID: 34801488 PMCID: PMC8666355 DOI: 10.1016/j.jlr.2021.100150] [Citation(s) in RCA: 79] [Impact Index Per Article: 19.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Revised: 10/27/2021] [Accepted: 10/29/2021] [Indexed: 11/24/2022] Open
Abstract
Triglycerides are carried in the bloodstream as the components of very low-density lipoproteins and chylomicrons. These circulating triglycerides are primarily hydrolyzed in muscle and adipose tissue by the enzyme lipoprotein lipase (LPL). The activity of LPL is regulated by numerous mechanisms, including by three members of the angiopoietin-like protein family: ANGPTL3, ANGPTL4, and ANGPTL8. In this review, we discuss the recent literature concerning the role and mechanism of action of ANGPTL4 in lipid metabolism. ANGPTL4 is a fasting- and lipid-induced factor secreted by numerous cells, including adipocytes, hepatocytes, (cardio)myocytes, and macrophages. In adipocytes, ANGPTL4 mediates the fasting-induced repression of LPL activity by promoting the unfolding of LPL, leading to the cleavage and subsequent degradation of LPL. The inhibition of LPL by ANGPTL4 is opposed by ANGPTL8, which keeps the LPL active after feeding. In macrophages and (cardio)myocytes, ANGPTL4 functions as a lipid-inducible feedback regulator of LPL-mediated lipid uptake. In comparison, in hepatocytes, ANGPTL4 functions as a local inhibitor of hepatic lipase and possibly as an endocrine inhibitor of LPL in extra-hepatic tissues. At the genetic level, loss-of-function mutations in ANGPTL4 are associated with lower plasma triglycerides and higher plasma HDL-C levels, and a reduced risk of coronary artery disease, suggesting that ANGPTL4 is a viable pharmacological target for reducing cardiovascular risk. Whole-body targeting of ANGPTL4 is contraindicated because of severe pathological complications, whereas liver-specific inactivation of ANGPTL4, either as monotherapy or coupled to anti-ANGPTL3 therapies might be a suitable strategy for lowering plasma triglycerides in selected patient groups. In conclusion, the tissue-specific targeting of ANGPTL4 appears to be a viable pharmacological approach to reduce circulating triglycerides.
Collapse
|
36
|
Bhori M, Rastogi V, Tungare K, Marar T. A review on interplay between obesity, lipoprotein profile and nutrigenetics with selected candidate marker genes of type 2 diabetes mellitus. Mol Biol Rep 2021; 49:687-703. [PMID: 34669123 DOI: 10.1007/s11033-021-06837-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Accepted: 10/12/2021] [Indexed: 12/06/2022]
Abstract
BACKGROUND Type 2 diabetes mellitus, a rapidly growing epidemic, and its frequently related complications demand global attention. The two factors commonly attributed to the epidemic are genetic factors and environmental factors. Studies indicate that the genetic makeup at an individual level and the environmental aspects influence the occurrence of the disease. However, there is insufficiency in understanding the mechanisms through which the gene mutations and environmental components individually lead to T2DM. Also, discrepancies have often been noted in the association of gene variants and type 2 diabetes when the gene factor is examined as a sole attribute to the disease. STUDY In this review initially, we have focused on the proposed ways through which CAPN10, FABP2, GLUT2, TCF7L2, and ENPP1 variants lead to T2DM along with the inconsistencies observed in the gene-disease association. The article also emphasizes on obesity, lipoprotein profile, and nutrition as environmental factors and how they lead to T2DM. Finally, the main objective is explored, the environment-gene-disease association i.e. the influence of each environmental factor on the aforementioned specific gene-T2DM relationship to understand if the disease-causing capability of the gene variants is exacerbated by environmental influences. CONCLUSION We found that environmental factors may influence the gene-disease relationship. Reciprocally, the genetic factors may alter the environment-disease relationship. To precisely conclude that the two factors act synergistically to lead to T2DM, more attention has to be paid to the combined influence of the genetic variants and environmental factors on T2DM occurrence instead of studying the influence of the factors separately.
Collapse
Affiliation(s)
- Mustansir Bhori
- School of Biotechnology and Bioinformatics, D. Y. Patil Deemed To Be University, Navi Mumbai, 400614, India
| | - Varuni Rastogi
- School of Biotechnology and Bioinformatics, D. Y. Patil Deemed To Be University, Navi Mumbai, 400614, India
| | - Kanchanlata Tungare
- School of Biotechnology and Bioinformatics, D. Y. Patil Deemed To Be University, Navi Mumbai, 400614, India.
| | - Thankamani Marar
- School of Biotechnology and Bioinformatics, D. Y. Patil Deemed To Be University, Navi Mumbai, 400614, India
| |
Collapse
|
37
|
Sylvers-Davie KL, Davies BSJ. Regulation of lipoprotein metabolism by ANGPTL3, ANGPTL4, and ANGPTL8. Am J Physiol Endocrinol Metab 2021; 321:E493-E508. [PMID: 34338039 PMCID: PMC8560382 DOI: 10.1152/ajpendo.00195.2021] [Citation(s) in RCA: 71] [Impact Index Per Article: 17.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Revised: 07/14/2021] [Accepted: 07/26/2021] [Indexed: 01/28/2023]
Abstract
Triglyceride-rich lipoproteins deliver fatty acids to tissues for oxidation and for storage. Release of fatty acids from circulating lipoprotein triglycerides is carried out by lipoprotein lipase (LPL), thus LPL serves as a critical gatekeeper of fatty acid uptake into tissues. LPL activity is regulated by a number of extracellular proteins including three members of the angiopoietin-like family of proteins. In this review, we discuss our current understanding of how, where, and when ANGPTL3, ANGPTL4, and ANGPTL8 regulate lipoprotein lipase activity, with a particular emphasis on how these proteins interact with each other to coordinate triglyceride metabolism and fat partitioning.
Collapse
Affiliation(s)
- Kelli L Sylvers-Davie
- Department of Biochemistry, Fraternal Order of Eagles Diabetes Research Center, and Obesity Research and Education Initiative, University of Iowa, Iowa City, Iowa
| | - Brandon S J Davies
- Department of Biochemistry, Fraternal Order of Eagles Diabetes Research Center, and Obesity Research and Education Initiative, University of Iowa, Iowa City, Iowa
| |
Collapse
|
38
|
Kristensen KK, Leth-Espensen KZ, Kumari A, Grønnemose AL, Lund-Winther AM, Young SG, Ploug M. GPIHBP1 and ANGPTL4 Utilize Protein Disorder to Orchestrate Order in Plasma Triglyceride Metabolism and Regulate Compartmentalization of LPL Activity. Front Cell Dev Biol 2021; 9:702508. [PMID: 34336854 PMCID: PMC8319833 DOI: 10.3389/fcell.2021.702508] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Accepted: 06/23/2021] [Indexed: 12/12/2022] Open
Abstract
Intravascular processing of triglyceride-rich lipoproteins (TRLs) is crucial for delivery of dietary lipids fueling energy metabolism in heart and skeletal muscle and for storage in white adipose tissue. During the last decade, mechanisms underlying focal lipolytic processing of TRLs along the luminal surface of capillaries have been clarified by fresh insights into the functions of lipoprotein lipase (LPL); LPL's dedicated transporter protein, glycosylphosphatidylinositol-anchored high density lipoprotein-binding protein 1 (GPIHBP1); and its endogenous inhibitors, angiopoietin-like (ANGPTL) proteins 3, 4, and 8. Key discoveries in LPL biology include solving the crystal structure of LPL, showing LPL is catalytically active as a monomer rather than as a homodimer, and that the borderline stability of LPL's hydrolase domain is crucial for the regulation of LPL activity. Another key discovery was understanding how ANGPTL4 regulates LPL activity. The binding of ANGPTL4 to LPL sequences adjacent to the catalytic cavity triggers cooperative and sequential unfolding of LPL's hydrolase domain resulting in irreversible collapse of the catalytic cavity and loss of LPL activity. Recent studies have highlighted the importance of the ANGPTL3-ANGPTL8 complex for endocrine regulation of LPL activity in oxidative organs (e.g., heart, skeletal muscle, brown adipose tissue), but the molecular mechanisms have not been fully defined. New insights have also been gained into LPL-GPIHBP1 interactions and how GPIHBP1 moves LPL to its site of action in the capillary lumen. GPIHBP1 is an atypical member of the LU (Ly6/uPAR) domain protein superfamily, containing an intrinsically disordered and highly acidic N-terminal extension and a disulfide bond-rich three-fingered LU domain. Both the disordered acidic domain and the folded LU domain are crucial for the stability and transport of LPL, and for modulating its susceptibility to ANGPTL4-mediated unfolding. This review focuses on recent advances in the biology and biochemistry of crucial proteins for intravascular lipolysis.
Collapse
Affiliation(s)
- Kristian Kølby Kristensen
- Finsen Laboratory, Rigshospitalet, Copenhagen, Denmark.,Biotech Research and Innovation Centre, University of Copenhagen, Copenhagen, Denmark
| | - Katrine Zinck Leth-Espensen
- Finsen Laboratory, Rigshospitalet, Copenhagen, Denmark.,Biotech Research and Innovation Centre, University of Copenhagen, Copenhagen, Denmark
| | - Anni Kumari
- Finsen Laboratory, Rigshospitalet, Copenhagen, Denmark.,Biotech Research and Innovation Centre, University of Copenhagen, Copenhagen, Denmark
| | - Anne Louise Grønnemose
- Finsen Laboratory, Rigshospitalet, Copenhagen, Denmark.,Biotech Research and Innovation Centre, University of Copenhagen, Copenhagen, Denmark
| | - Anne-Marie Lund-Winther
- Finsen Laboratory, Rigshospitalet, Copenhagen, Denmark.,Biotech Research and Innovation Centre, University of Copenhagen, Copenhagen, Denmark
| | - Stephen G Young
- Departments of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Michael Ploug
- Finsen Laboratory, Rigshospitalet, Copenhagen, Denmark.,Biotech Research and Innovation Centre, University of Copenhagen, Copenhagen, Denmark
| |
Collapse
|
39
|
Abstract
BACKGROUND Beyond their success in cardiovascular disease prevention, statins are increasingly recognized to have sex-specific pleiotropic effects. To gain additional insight, we characterized associations of genetically mimicked statins across the phenotype sex-specifically. We also assessed whether any apparently non-lipid effects identified extended to genetically mimicking other widely used lipid modifiers (proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors and ezetimibe) or were a consequence of low-density lipoprotein cholesterol (LDL-c). METHODS We performed a sex-specific phenome-wide association study assessing the association of genetic variants in HMGCR, mimicking statins, with 1701 phenotypes. We used Mendelian randomization (MR) to assess if any non-lipid effects found were evident for genetically mimicked PCSK9 inhibitors and ezetimibe or for LDL-c. RESULTS As expected, genetically mimicking statins was inversely associated with LDL-c, apolipoprotein B (ApoB), and total cholesterol (TC) and positively associated with glycated hemoglobin (HbA1c) and was related to body composition. Genetically mimicking statins was also inversely associated with serum calcium, sex hormone-binding globulin (SHBG), and platelet count and positively associated with basal metabolic rate (BMR) and mean platelet volume. Stronger associations with genetically mimicked statins were evident for women than men for lipid traits (LDL-c, ApoB, and TC), calcium, and SHBG, but not for platelet attributes, body composition, or BMR. Genetically mimicking PCSK9 inhibitors or ezetimibe was also associated with lower lipids, but was not related to calcium, SHBG, BMR, or body composition. Genetically higher LDL-c increased lipids and decreased BMR, but did not affect calcium, HbA1c, platelet attributes, or SHBG with minor effects on body composition. CONCLUSIONS Similar inverse associations were found for genetically mimicking statins on lipid traits in men and women as for other lipid modifiers. Besides the positive associations with HbA1c, BMI (which may explain the higher BMR), and aspects of body composition in men and women, genetically mimicking statins was additionally associated with platelet attributes in both sexes and was inversely associated with serum calcium and SHBG in women. This genetic evidence suggests potential pathways that contribute to the effects of statins particularly in women. Further investigation is needed to confirm these findings and their implications for clinical practice.
Collapse
|
40
|
Bos MM, van Vliet NA, Mooijaart SP, Noordam R, van Heemst D. Genetically Determined Higher TSH Is Associated With a Lower Risk of Diabetes Mellitus in Individuals With Low BMI. J Clin Endocrinol Metab 2021; 106:e2502-e2511. [PMID: 33901276 PMCID: PMC8208661 DOI: 10.1210/clinem/dgab277] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Indexed: 11/23/2022]
Abstract
CONTEXT Thyroid status is hypothesized to be causally related with the risk of diabetes mellitus (DM), but previous results were conflicting possibly because of a complex interaction between thyrotropin (TSH), body mass index (BMI) and DM. OBJECTIVE This work aims to investigate the causal association between thyroid status with DM and glucose homeostasis and to what extent this association is dependent on BMI. METHODS A mendelian randomization study was conducted of European-ancestry participants from the UK Biobank population. The present study involved 408 895 individuals (mean age 57.4 years [SD 8.0], 45.9% men), of whom 19 773 had DM. Genetic variants for circulatory TSH, free thyroxine (fT4) concentrations and BMI to calculate weighted genetic risk scores. The main outcome measures included self-reported DM-stratified analyses by BMI. Analyses were repeated for nonfasting glucose and glycated hemoglobin A1c (HbA1c) among individuals without DM. RESULTS Genetically determined TSH and fT4 levels were not associated with risk of DM in the total UK Biobank population. However, in analyses stratified on genetically determined BMI, genetically determined higher TSH, and not fT4, was associated with a lower risk for DM only in the low BMI group (odds ratio 0.91; 95% CI, 0.85-0.98 in low BMI; P value for interaction = .06). Similar results were observed for glucose and HbA1c among individuals without DM. CONCLUSION TSH, but not fT4, is a potential causal risk factor for DM in individuals with genetically determined low BMI highlighting potential protective effects of TSH only in low-risk populations.
Collapse
Affiliation(s)
- Maxime M Bos
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, 2300RC Leiden, the Netherlands
| | - Nicolien A van Vliet
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, 2300RC Leiden, the Netherlands
| | - Simon P Mooijaart
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, 2300RC Leiden, the Netherlands
| | - Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, 2300RC Leiden, the Netherlands
- Correspondence: Raymond Noordam, PhD, Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, P.O. Box 9600, 2300RC Leiden, the Netherlands.
| | - Diana van Heemst
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, 2300RC Leiden, the Netherlands
| |
Collapse
|
41
|
Wang Q, Oliver-Williams C, Raitakari OT, Viikari J, Lehtimäki T, Kähönen M, Järvelin MR, Salomaa V, Perola M, Danesh J, Kettunen J, Butterworth AS, Holmes MV, Ala-Korpela M. Metabolic profiling of angiopoietin-like protein 3 and 4 inhibition: a drug-target Mendelian randomization analysis. Eur Heart J 2021; 42:1160-1169. [PMID: 33351885 PMCID: PMC7982288 DOI: 10.1093/eurheartj/ehaa972] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Revised: 07/09/2020] [Accepted: 11/16/2020] [Indexed: 12/11/2022] Open
Abstract
Aims Angiopoietin-like protein 3 (ANGPTL3) and 4 (ANGPTL4) inhibit lipoprotein lipase (LPL) and represent emerging drug targets to lower circulating triglycerides and reduce cardiovascular risk. To investigate the molecular effects of genetic mimicry of ANGPTL3 and ANGPTL4 inhibition and compare them to the effects of genetic mimicry of LPL enhancement. Methods and results Associations of genetic variants in ANGPTL3 (rs11207977-T), ANGPTL4 (rs116843064-A), and LPL (rs115849089-A) with an extensive serum lipid and metabolite profile (208 measures) were characterized in six cohorts of up to 61 240 participants. Genetic associations with anthropometric measures, glucose-insulin metabolism, blood pressure, markers of kidney function, and cardiometabolic endpoints via genome-wide summary data were also explored. ANGPTL4 rs116843064-A and LPL rs115849089-A displayed a strikingly similar pattern of associations across the lipoprotein and lipid measures. However, the corresponding associations with ANGPTL3 rs11207977-T differed, including those for low-density lipoprotein and high-density lipoprotein particle concentrations and compositions. All three genotypes associated with lower concentrations of an inflammatory biomarker glycoprotein acetyls and genetic mimicry of ANGPTL3 inhibition and LPL enhancement were also associated with lower C-reactive protein. Genetic mimicry of ANGPTL4 inhibition and LPL enhancement were associated with a lower waist-to-hip ratio, improved insulin-glucose metabolism, and lower risk of coronary heart disease and type 2 diabetes, whilst genetic mimicry of ANGPTL3 was associated with improved kidney function. Conclusions Genetic mimicry of ANGPTL4 inhibition and LPL enhancement have very similar systemic metabolic effects, whereas genetic mimicry of ANGPTL3 inhibition showed differing metabolic effects, suggesting potential involvement of pathways independent of LPL. Genetic mimicry of ANGPTL4 inhibition and LPL enhancement were associated with a lower risk of coronary heart disease and type 2 diabetes. These findings reinforce evidence that enhancing LPL activity (either directly or via upstream effects) through pharmacological approaches is likely to yield benefits to human health.
Collapse
Affiliation(s)
- Qin Wang
- Systems Epidemiology, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia.,Computational Medicine, Faculty of Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland.,Center for Life Course Health Research, University of Oulu, Oulu, Finland
| | - Clare Oliver-Williams
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.,Homerton College, University of Cambridge, Cambridge, UK
| | - Olli T Raitakari
- 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.,Centre for Population Health Research, University of Turku, Turku, Finland.,Turku University Hospital, Turku, Finland
| | - Jorma Viikari
- Department of Medicine, University of Turku, Turku, Finland.,Division of Medicine, Turku University Hospital, Turku, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, and Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Marjo-Riitta Järvelin
- Center for Life Course Health Research, University of Oulu, Oulu, Finland.,Unit of Primary Health Care, Oulu University Hospital, OYS, Oulu, Finland.,Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK.,Department of Life Sciences, College of Health and Life Sciences, Brunel University London, UK
| | - Veikko Salomaa
- National Institute for Health and Welfare, Helsinki, Finland
| | - Markus Perola
- National Institute for Health and Welfare, Helsinki, Finland.,Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland.,Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - John Danesh
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.,National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK.,Wellcome Trust Sanger Institute, Hinxton, UK.,British Heart Foundation Cambridge Centre of Excellence, Department of Medicine, University of Cambridge, Cambridge, UK
| | - Johannes Kettunen
- Computational Medicine, Faculty of Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland.,Center for Life Course Health Research, University of Oulu, Oulu, Finland.,National Institute for Health and Welfare, Helsinki, Finland
| | - Adam S Butterworth
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.,National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK
| | - Michael V Holmes
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK.,Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Big Data Institute Building, Old Road Campus, Roosevelt Drive, Oxford OX3 7LF, UK.,National Institute for Health Research, Oxford Biomedical Research Centre, Oxford University Hospital, Oxford, UK.,Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Mika Ala-Korpela
- Computational Medicine, Faculty of Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland.,Center for Life Course Health Research, University of Oulu, Oulu, Finland.,NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland
| |
Collapse
|
42
|
Triglyceride-lowering LPL alleles combined with LDL-C-lowering alleles are associated with an additively improved lipoprotein profile. Atherosclerosis 2021; 328:144-152. [PMID: 34053745 DOI: 10.1016/j.atherosclerosis.2021.04.015] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Revised: 04/13/2021] [Accepted: 04/28/2021] [Indexed: 11/20/2022]
Abstract
BACKGROUND AND AIMS Mendelian randomization studies have shown that triglyceride (TG)- lowering lipoprotein lipase (LPL) alleles and low-density lipoprotein-cholesterol (LDL-C)-lowering alleles have independent beneficial associations on cardiovascular disease (CVD) risk. We aimed to provide further insight into this observation by applying Mendelian randomization analyses of genetically-influenced TG and LDL-C levels on plasma metabolomic profiles. METHODS We quantified over 100 lipoprotein metabolomic measures in the Netherlands Epidemiology of Obesity (NEO) study (N = 4838) and Oxford Biobank (OBB) (N = 6999) by nuclear magnetic resonance (NMR) spectroscopy. Weighted genetic scores for TG via five LPL alleles and LDL-C via 19 alleles were calculated and dichotomized by the median, resulting in four genotype combinations of high/low TG and high/low LDL-C. We performed linear regression analyses using a two × two design with the group with genetically-influenced high TG and LDL-C as a reference. RESULTS Compared to the individual groups with genetically-influenced lower TG or lower LDL-C only, the group with combined genetically-influenced lower TG and LDL-C showed an overall independent and additive pattern of changes in metabolomic measures. Over 100 measures were different (p < 1.35 × 10-3) compared to the reference, with effect sizes and directionality being similar in NEO and OBB. Most notably, levels of all very-low density lipoprotein (VLDL) and LDL sub-particles were lower. CONCLUSIONS Our findings provide evidence that TG-lowering on top of LDL-C-lowering has additive beneficial effects on the lipoprotein profile compared to TG-lowering or LDL-C-lowering only, which is in accordance with reported additive genetic effects on CVD risk reduction.
Collapse
|
43
|
Natarajan P, Pampana A, Graham SE, Ruotsalainen SE, Perry JA, de Vries PS, Broome JG, Pirruccello JP, Honigberg MC, Aragam K, Wolford B, Brody JA, Antonacci-Fulton L, Arden M, Aslibekyan S, Assimes TL, Ballantyne CM, Bielak LF, Bis JC, Cade BE, Do R, Doddapaneni H, Emery LS, Hung YJ, Irvin MR, Khan AT, Lange L, Lee J, Lemaitre RN, Martin LW, Metcalf G, Montasser ME, Moon JY, Muzny D, O'Connell JR, Palmer ND, Peralta JM, Peyser PA, Stilp AM, Tsai M, Wang FF, Weeks DE, Yanek LR, Wilson JG, Abecasis G, Arnett DK, Becker LC, Blangero J, Boerwinkle E, Bowden DW, Chang YC, Chen YDI, Choi WJ, Correa A, Curran JE, Daly MJ, Dutcher SK, Ellinor PT, Fornage M, Freedman BI, Gabriel S, Germer S, Gibbs RA, He J, Hveem K, Jarvik GP, Kaplan RC, Kardia SLR, Kenny E, Kim RW, Kooperberg C, Laurie CC, Lee S, Lloyd-Jones DM, Loos RJF, Lubitz SA, Mathias RA, Martinez KAV, McGarvey ST, Mitchell BD, Nickerson DA, North KE, Palotie A, Park CJ, Psaty BM, Rao DC, Redline S, Reiner AP, Seo D, Seo JS, Smith AV, Tracy RP, Vasan RS, Kathiresan S, Cupples LA, Rotter JI, Morrison AC, Rich SS, Ripatti S, Willer C, et alNatarajan P, Pampana A, Graham SE, Ruotsalainen SE, Perry JA, de Vries PS, Broome JG, Pirruccello JP, Honigberg MC, Aragam K, Wolford B, Brody JA, Antonacci-Fulton L, Arden M, Aslibekyan S, Assimes TL, Ballantyne CM, Bielak LF, Bis JC, Cade BE, Do R, Doddapaneni H, Emery LS, Hung YJ, Irvin MR, Khan AT, Lange L, Lee J, Lemaitre RN, Martin LW, Metcalf G, Montasser ME, Moon JY, Muzny D, O'Connell JR, Palmer ND, Peralta JM, Peyser PA, Stilp AM, Tsai M, Wang FF, Weeks DE, Yanek LR, Wilson JG, Abecasis G, Arnett DK, Becker LC, Blangero J, Boerwinkle E, Bowden DW, Chang YC, Chen YDI, Choi WJ, Correa A, Curran JE, Daly MJ, Dutcher SK, Ellinor PT, Fornage M, Freedman BI, Gabriel S, Germer S, Gibbs RA, He J, Hveem K, Jarvik GP, Kaplan RC, Kardia SLR, Kenny E, Kim RW, Kooperberg C, Laurie CC, Lee S, Lloyd-Jones DM, Loos RJF, Lubitz SA, Mathias RA, Martinez KAV, McGarvey ST, Mitchell BD, Nickerson DA, North KE, Palotie A, Park CJ, Psaty BM, Rao DC, Redline S, Reiner AP, Seo D, Seo JS, Smith AV, Tracy RP, Vasan RS, Kathiresan S, Cupples LA, Rotter JI, Morrison AC, Rich SS, Ripatti S, Willer C, Peloso GM. Chromosome Xq23 is associated with lower atherogenic lipid concentrations and favorable cardiometabolic indices. Nat Commun 2021; 12:2182. [PMID: 33846329 PMCID: PMC8042019 DOI: 10.1038/s41467-021-22339-1] [Show More Authors] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Accepted: 03/02/2021] [Indexed: 02/01/2023] Open
Abstract
Autosomal genetic analyses of blood lipids have yielded key insights for coronary heart disease (CHD). However, X chromosome genetic variation is understudied for blood lipids in large sample sizes. We now analyze genetic and blood lipid data in a high-coverage whole X chromosome sequencing study of 65,322 multi-ancestry participants and perform replication among 456,893 European participants. Common alleles on chromosome Xq23 are strongly associated with reduced total cholesterol, LDL cholesterol, and triglycerides (min P = 8.5 × 10-72), with similar effects for males and females. Chromosome Xq23 lipid-lowering alleles are associated with reduced odds for CHD among 42,545 cases and 591,247 controls (P = 1.7 × 10-4), and reduced odds for diabetes mellitus type 2 among 54,095 cases and 573,885 controls (P = 1.4 × 10-5). Although we observe an association with increased BMI, waist-to-hip ratio adjusted for BMI is reduced, bioimpedance analyses indicate increased gluteofemoral fat, and abdominal MRI analyses indicate reduced visceral adiposity. Co-localization analyses strongly correlate increased CHRDL1 gene expression, particularly in adipose tissue, with reduced concentrations of blood lipids.
Collapse
Affiliation(s)
- Pradeep Natarajan
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA.
- Department of Medicine, Harvard Medical School, Boston, MA, USA.
| | - Akhil Pampana
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Sarah E Graham
- Department of Internal Medicine: Cardiology, University of Michigan, Ann Arbor, MI, USA
| | - Sanni E Ruotsalainen
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - James A Perry
- University of Maryland School of Medicine, Division of Endocrinology, Diabetes and Nutrition and Program for Personalized and Genomic Medicine, Baltimore, MD, 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
| | - Jai G Broome
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - James P Pirruccello
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Michael C Honigberg
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Krishna Aragam
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Brooke Wolford
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Lucinda Antonacci-Fulton
- The McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
- Department of Genetics, Washington University in St. Louis, St. Louis, MO, USA
| | - Moscati Arden
- The Charles Bronfman Institute for Personalized Medicine, Ichan School of Medicine at Mount Sinai, New York, NY, USA
| | - Stella Aslibekyan
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Themistocles L Assimes
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- VA Palo Alto Health Care System, Palo Alto, CA, USA
| | - Christie M Ballantyne
- Section of Cardiovascular Research, Baylor College of Medicine, Houston, TX, USA
- Houston Methodist Debakey Heart and Vascular Center, Houston, TX, 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
| | - Brian E Cade
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ron Do
- The Charles Bronfman Institute for Personalized Medicine, Ichan School of Medicine at Mount Sinai, New York, NY, USA
| | - Harsha Doddapaneni
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Leslie S Emery
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Yi-Jen Hung
- Division of Endocrine and Metabolism, Tri-Service General Hospital Songshan branch, Taipei, Taiwan
| | - Marguerite R Irvin
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Alyna T Khan
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Leslie Lange
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Jiwon Lee
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Rozenn N Lemaitre
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Lisa W Martin
- Division of Cardiology, George Washington University School of Medicine and Healthcare Sciences, Washington, DC, USA
| | - Ginger Metcalf
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - May E Montasser
- University of Maryland School of Medicine, Division of Endocrinology, Diabetes and Nutrition and Program for Personalized and Genomic Medicine, Baltimore, MD, USA
| | - Jee-Young Moon
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Donna Muzny
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Jeffrey R O'Connell
- University of Maryland School of Medicine, Division of Endocrinology, Diabetes and Nutrition and Program for Personalized and Genomic Medicine, Baltimore, MD, USA
| | - Nicholette D Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Juan M Peralta
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Adrienne M Stilp
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Michael Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Fei Fei Wang
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Daniel E Weeks
- Departments of Human Genetics and Biostatistics, University of Pittsburgh, Pittsburgh, Pittsburgh, PA, USA
| | - Lisa R Yanek
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - James G Wilson
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS, USA
| | - Goncalo Abecasis
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Donna K Arnett
- Deans office, School of Public Health, University of Kentucky, Lexington, KY, USA
| | - Lewis C Becker
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, 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
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Donald W Bowden
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Yi-Cheng Chang
- Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | - Yii-Der I 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
| | - Won Jung Choi
- Psomagen. Inc. (formerly Macrogen USA), Rockville, MD, USA
| | - Adolfo Correa
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, 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
| | - Mark J Daly
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Susan K Dutcher
- The McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
- Department of Genetics, Washington University in St. Louis, St. Louis, MO, USA
| | - Patrick T Ellinor
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Cardiac Arrhythmia Service and Cardiovascular Research Center Massachusetts General Hospital, Boston, MA, USA
| | - Myriam Fornage
- Institute of Molecular Medicine, the University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Barry I Freedman
- Department of Internal Medicine, Section on Nephrology, Wake Forest School of Medicine, Winston-, Salem, NC, USA
| | - Stacey Gabriel
- Genomics Platform, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | | | - Richard A Gibbs
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Jiang He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, and Tulane University Translational Science Institute, Tulane University, New Orleans, LA, USA
| | - Kristian Hveem
- Department of Public Health and General Practice, HUNT Research Centre, Norwegian University of Science and Technology, Levanger, Norway
- K. G. Jebsen Center for Genetic Epidemiology, Dept of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Gail P Jarvik
- Departments of Medicine (Medical Genetics) and Genome Sciences, University of Washington, Seattle, WA, 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 Research Center, Seattle, WA, USA
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Eimear Kenny
- The Charles Bronfman Institute for Personalized Medicine, Ichan School of Medicine at Mount Sinai, New York, NY, USA
| | - Ryan W Kim
- Psomagen. Inc. (formerly Macrogen USA), Rockville, MD, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Cathy C Laurie
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Seonwook Lee
- Psomagen. Inc. (formerly Macrogen USA), Rockville, MD, USA
| | - Don M Lloyd-Jones
- Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Ichan School of Medicine at Mount Sinai, New York, NY, USA
- The Mindich Child Health and Development Institute, Ichan School of Medicine at Mount Sinai, New York, NY, USA
| | - Steven A Lubitz
- Cardiac Arrhythmia Service and Cardiovascular Research Center Massachusetts General Hospital, Boston, MA, USA
| | - Rasika A Mathias
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | | | - Stephen T McGarvey
- Department of Epidemiology and International Health Institute, Brown University, Providence, RI, USA
| | - Braxton D Mitchell
- University of Maryland School of Medicine, Division of Endocrinology, Diabetes and Nutrition and Program for Personalized and Genomic Medicine, Baltimore, MD, USA
- Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore, MD, USA
| | - Deborah A Nickerson
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- University of Washington Center for Mendelian Genomics, Seattle, WA, USA
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Aarno Palotie
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Cheol Joo Park
- Psomagen. Inc. (formerly Macrogen USA), Rockville, MD, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
- Departments of Epidemiology and Health Services, University of Washington, Seattle, WA, USA
| | - D 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
| | - Alexander P Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Daekwan Seo
- Psomagen. Inc. (formerly Macrogen USA), Rockville, MD, USA
| | - Jeong-Sun Seo
- Psomagen. Inc. (formerly Macrogen USA), Rockville, MD, USA
| | - Albert V Smith
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
- The Icelandic Heart Association, Kopavogur, Iceland
| | - Russell P Tracy
- Departments of Pathology & Laboratory Medicine and Biochemistry, Larrner College of Medicine, University of Vermont, Colchester, VT, USA
| | - Ramachandran S Vasan
- Sections of Preventive Medicine and Epidemiology and Cardiology, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
- NHLBI Framingham Heart Study, Framingham, MA, USA
| | - Sekar Kathiresan
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Verve Therapeutics, Cambridge, MA, USA
| | - L Adrienne Cupples
- NHLBI Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 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
| | - 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
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Samuli Ripatti
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
- Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Cristen Willer
- Department of Internal Medicine: Cardiology, 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
| | - Gina M Peloso
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
| |
Collapse
|
44
|
Regulation of plasma triglyceride partitioning by adipose-derived ANGPTL4 in mice. Sci Rep 2021; 11:7873. [PMID: 33846453 PMCID: PMC8041937 DOI: 10.1038/s41598-021-87020-5] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Accepted: 03/22/2021] [Indexed: 11/29/2022] Open
Abstract
Elevated plasma triglyceride levels are associated with metabolic disease. Angiopoietin-like protein 4 (ANGPTL4) regulates plasma triglyceride levels by inhibiting lipoprotein lipase (LPL). Our aim was to investigate the role of adipocyte-specific deficiency of ANGPTL4 in mice during high fat diet feeding. Adipocyte-specific ANGPTL4 deficient mice were fed a high fat diet (60% kCal from fat) for either 12 weeks or 6 months. We performed plasma metabolic measurements, triglyceride clearance and uptake assays, LPL activity assays, and assessed glucose homeostasis. Mice lacking adipocyte ANGPTL4 recapitulated the triglyceride phenotypes of whole-body ANGPTL4 deficiency, including increased adipose LPL activity, lower plasma triglyceride levels, and increased uptake of triglycerides into adipose tissue. When fed a high fat diet (HFD), these mice continued to display enhanced adipose LPL activity and initially had improved glucose and insulin sensitivity. However, after 6 months on HFD, the improvements in glucose homeostasis were largely lost. Moreover, despite higher adipose LPL activity levels, mice lacking adipocyte ANGPTL4 no longer had increased triglyceride uptake into adipose compared to littermate controls after chronic high-fat feeding. These observations suggest that after chronic high-fat feeding LPL is no longer rate-limiting for triglyceride delivery to adipocytes. We conclude that while adipocyte-derived ANGPTL4 is an important regulator of plasma triglyceride levels and triglyceride partitioning under normal diet conditions, its role is diminished after chronic high-fat feeding.
Collapse
|
45
|
Trinder M, Brunham LR. Polygenic scores for dyslipidemia: the emerging genomic model of plasma lipoprotein trait inheritance. Curr Opin Lipidol 2021; 32:103-111. [PMID: 33395106 DOI: 10.1097/mol.0000000000000737] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
PURPOSE OF REVIEW Contemporary polygenic scores, which summarize the cumulative contribution of millions of common single-nucleotide variants to a phenotypic trait, can have effects comparable to monogenic mutations. This review focuses on the emerging use of 'genome-wide' polygenic scores for plasma lipoproteins to define the etiology of clinical dyslipidemia, modify the severity of monogenic disease, and inform therapeutic options. RECENT FINDINGS Polygenic scores for low-density lipoprotein cholesterol (LDL-C), triglycerides, and high-density lipoprotein cholesterol are associated with severe hypercholesterolemia, hypertriglyceridemia, or hypoalphalipoproteinemia, respectively. These polygenic scores for LDL-C or triglycerides associate with risk of incident coronary artery disease (CAD) independent of polygenic scores designed specifically for CAD and may identify individuals that benefit most from lipid-lowering medication. Additionally, the severity of hypercholesterolemia and CAD associated with familial hypercholesterolemia-a common monogenic disorder-is modified by these polygenic factors. The current focus of polygenic scores for dyslipidemia is to design predictive polygenic scores for diverse populations and determining how these polygenic scores could be implemented and standardized for use in the clinic. SUMMARY Polygenic scores have shown early promise for the management of dyslipidemias, but several challenges need to be addressed before widespread clinical implementation to ensure that potential benefits are robust and reproducible, equitable, and cost-effective.
Collapse
Affiliation(s)
- Mark Trinder
- Centre for Heart Lung Innovation, University of British Columbia
- Experimental Medicine Program, University of British Columbia
| | - Liam R Brunham
- Centre for Heart Lung Innovation, University of British Columbia
- Experimental Medicine Program, University of British Columbia
- Department of Medicine, University of British Columbia
- Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada
| |
Collapse
|
46
|
Song Y, Choi JE, Kwon YJ, Chang HJ, Kim JO, Park DH, Park JM, Kim SJ, Lee JW, Hong KW. Identification of susceptibility loci for cardiovascular disease in adults with hypertension, diabetes, and dyslipidemia. J Transl Med 2021; 19:85. [PMID: 33632238 PMCID: PMC7905883 DOI: 10.1186/s12967-021-02751-3] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2020] [Accepted: 02/11/2021] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Hypertension (HTN), diabetes mellitus (DM), and dyslipidemia (DL) are well-known risk factors of cardiovascular disease (CVD), but not all patients develop CVDs. Studies have been limited investigating genetic risk of CVDs specific to individuals with metabolic diseases. This study aimed to identify disease-specific and/or common genetic loci associated with CVD susceptibility in chronic metabolic disease patients. METHODS We conducted a genome-wide association study (GWAS) of a multiple case-control design with data from the City Cohort within Health EXAminees subcohort of the Korean Genome and Epidemiology Study (KoGES_HEXA). KoGES_HEXA is a population-based prospective cohort of 173,357 urban Korean adults that had health examinations at medical centers. 42,393 participants (16,309 HTN; 5,314 DM; 20,770 DL) were analyzed, and each metabolic disease group was divided into three CVD case-controls: coronary artery disease (CAD), ischemic stroke (IS), and cardio-cerebrovascular disease (CCD). GWASs were conducted for each case-control group with 7,975,321 imputed single nucleotide polymorphisms using the Phase 3 Asian panel from 1000 Genomes Project, by logistic regression and controlled for confounding variables. Genome-wide significant levels were implemented to identify important susceptibility loci. RESULTS Totaling 42,393 individuals, this study included 16,309 HTN (mean age [SD], 57.28 [7.45]; 816 CAD, 398 IS, and 1,185 CCD cases), 5,314 DM (57.79 [7.39]; 361 CAD, 153 IS, and 497 CCD cases), and 20,770 DL patients (55.34 [7.63]; 768 CAD, 295 IS, and 1,039 CCD cases). Six genome-wide significant CVD risk loci were identified, with relatively large effect sizes: 1 locus in HTN (HTN-CAD: 17q25.3/CBX8-CBX4 [OR, 2.607; P = 6.37 × 10-9]), 2 in DM (DM-IS: 4q32.3/MARCH1-LINC01207 [OR, 5.587; P = 1.34 × 10-8], and DM-CCD: 17q25.3/RPTOR [OR, 3.511; P = 1.99 × 10-8]), and 3 in DL (DL-CAD: 9q22.2/UNQ6494-LOC101927847 [OR, 2.282; P = 7.78 × 10-9], DL-IS: 3p22.1/ULK4 [OR, 2.162; P = 2.97 × 10-8], and DL-CCD: 2p22.2/CYP1B1-CYP1B1-AS1 [OR, 2.027; P = 4.24 × 10-8]). CONCLUSIONS This study identified 6 susceptibility loci and positional candidate genes for CVDs in HTN, DM, and DL patients using an unprecedented study design. 1 locus (17q25.3) was commonly associated with CAD. These associations warrant validation in additional studies for potential therapeutic applications.
Collapse
Affiliation(s)
- Youhyun Song
- Department of Family Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, 211, Eonju-ro, Gangnam-gu, Seoul, 06273, Korea
| | - Ja-Eun Choi
- Healthcare R&D Division, Theragen Bio Co., Ltd., Gwanggyo-ro 145, Suwon-si, Gyeonggi-do, 16229, Republic of Korea
| | - Yu-Jin Kwon
- Department of Family Medicine, Yongin Severance Hospital, Yonsei University College of Medicine, 363, Dongbaekjukjeon-daero, Giheung-gu, Yongin-si, 16995, Gyeonggi-do, Korea
| | - Hyuk-Jae Chang
- Division of Cardiology, Severance Cardiovascular Hospital, Yonsei University College of Medicine, 50-1, Yonsei-ro, Seodaemun-gu, Seoul, 03722, Korea
| | - Jung Oh Kim
- Healthcare R&D Division, Theragen Bio Co., Ltd., Gwanggyo-ro 145, Suwon-si, Gyeonggi-do, 16229, Republic of Korea
| | - Da-Hyun Park
- Healthcare R&D Division, Theragen Bio Co., Ltd., Gwanggyo-ro 145, Suwon-si, Gyeonggi-do, 16229, Republic of Korea
| | - Jae-Min Park
- Department of Family Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, 211, Eonju-ro, Gangnam-gu, Seoul, 06273, Korea
| | - Seong-Jin Kim
- Healthcare R&D Division, Theragen Bio Co., Ltd., Gwanggyo-ro 145, Suwon-si, Gyeonggi-do, 16229, Republic of Korea
| | - Ji Won Lee
- Department of Family Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, 211, Eonju-ro, Gangnam-gu, Seoul, 06273, Korea.
| | - Kyung-Won Hong
- Healthcare R&D Division, Theragen Bio Co., Ltd., Gwanggyo-ro 145, Suwon-si, Gyeonggi-do, 16229, Republic of Korea.
| |
Collapse
|
47
|
Thomas DG, Wei Y, Tall AR. Lipid and metabolic syndrome traits in coronary artery disease: a Mendelian randomization study. J Lipid Res 2021; 62:100044. [PMID: 32907989 PMCID: PMC7933489 DOI: 10.1194/jlr.p120001000] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Revised: 08/20/2020] [Indexed: 01/14/2023] Open
Abstract
Mendelian randomization (MR) of lipid traits in CAD has provided evidence for causal associations of LDL-C and TGs in CAD, but many lipid trait genetic variants have pleiotropic effects on other cardiovascular risk factors that may bias MR associations. The goal of this study was to evaluate pleiotropic effects of lipid trait genetic variants and to account for these effects in MR of lipid traits in CAD. We performed multivariable MR using inverse variance-weighted and MR-Egger methods in large (n ≥ 300,000) GWAS datasets. We found that 30% of lipid trait genetic variants have effects on metabolic syndrome traits, including BMI, T2D, and systolic blood pressure (SBP). Nonetheless, in multivariable MR analysis, LDL-C, HDL-C, TGs, BMI, T2D, and SBP are independently associated with CAD, and each of these associations is robust to adjustment for directional pleiotropy. MR at loci linked to direct effects on HDL-C and TGs suggests locus- and mechanism-specific causal effects of these factors on CAD.
Collapse
Affiliation(s)
- David G Thomas
- Department of Medicine, New York Presbyterian Hospital/Weill Cornell Medicine, New York, NY, USA
| | - Ying Wei
- Department of Biostatistics, Columbia University, New York, NY, USA
| | - Alan R Tall
- Division of Molecular Medicine, Department of Medicine, Columbia University, New York, NY, USA.
| |
Collapse
|
48
|
Farnier M, Zeller M, Masson D, Cottin Y. Triglycerides and risk of atherosclerotic cardiovascular disease: An update. Arch Cardiovasc Dis 2021; 114:132-139. [PMID: 33546998 DOI: 10.1016/j.acvd.2020.11.006] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Revised: 11/05/2020] [Accepted: 11/06/2020] [Indexed: 12/22/2022]
Abstract
Low-density lipoprotein cholesterol is a well-known causal factor for atherosclerotic cardiovascular disease, and is the primary target of lipid-lowering therapy. There is, however, still a substantial risk of atherosclerotic cardiovascular disease events despite intensive statin therapy, and data from clinical trials suggest that an elevated concentration of triglycerides is a marker of residual cardiovascular risk on low-density lipoprotein-lowering therapy. Serum triglycerides are a biomarker for triglyceride-rich lipoproteins, and several lines of evidence indicate that triglyceride-rich lipoproteins and their cholesterol-enriched remnant particles are associated with atherogenesis. Moreover, genetic data in humans strongly suggest that the remnants of triglyceride-rich lipoproteins are a causal cardiovascular risk factor. Although lifestyle changes remain the cornerstone of management of hypertriglyceridaemia, a recent trial with high doses of the omega-3 fatty acid icosapent ethyl showed a significant reduction in cardiovascular events that was not explained by the reduction in triglycerides alone. In patients with elevated triglycerides, several novel drugs are in development to reduce the residual risk on statin therapy linked to an excess of atherogenic triglyceride-rich lipoproteins. In this review, we provide an update on the biology, epidemiology and genetics of triglycerides, and the risk of atherosclerotic cardiovascular disease.
Collapse
Affiliation(s)
- Michel Farnier
- PEC2, EA 7460, University of Bourgogne Franche-Comté, 21000 Dijon, France; Cardiology Department, University Hospital Centre of Dijon Bourgogne, 21000 Dijon, France.
| | - Marianne Zeller
- PEC2, EA 7460, University of Bourgogne Franche-Comté, 21000 Dijon, France; Cardiology Department, University Hospital Centre of Dijon Bourgogne, 21000 Dijon, France
| | - David Masson
- Inserm, LNC UMR 1231, FCS Bourgogne Franche-Comté, LipSTIC LabEx, 21078 Dijon, France
| | - Yves Cottin
- PEC2, EA 7460, University of Bourgogne Franche-Comté, 21000 Dijon, France; Cardiology Department, University Hospital Centre of Dijon Bourgogne, 21000 Dijon, France
| |
Collapse
|
49
|
Ruhanen H, Haridas PAN, Jauhiainen M, Olkkonen VM. Angiopoietin-like protein 3, an emerging cardiometabolic therapy target with systemic and cell-autonomous functions. Biochim Biophys Acta Mol Cell Biol Lipids 2020; 1865:158791. [PMID: 32777482 DOI: 10.1016/j.bbalip.2020.158791] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 06/23/2020] [Accepted: 08/03/2020] [Indexed: 12/13/2022]
Abstract
Angiopoietin like protein 3 (ANGPTL3) is best known for its function as an inhibitor of lipoprotein and endothelial lipases. Due to the capacity of genetic or pharmacologic ANGPTL3 suppression to markedly reduce circulating lipoproteins, and the documented cardioprotection upon such suppression, ANGPTL3 has become an emerging therapy target for which both antibody and antisense oligonucleotide (ASO) therapeutics are being clinically tested. While the antibody is relatively selective for circulating ANGPTL3, the ASO also depletes the intra-hepatocellular protein, and there is emerging evidence for cell-autonomous functions of ANGPTL3 in the liver. These include regulation of hepatocyte glucose and fatty acid uptake, insulin sensitivity, LDL/VLDL remnant uptake, VLDL assembly/secretion, polyunsaturated fatty acid (PUFA) and PUFA-derived lipid mediator content, and gene expression. In this review we elaborate on (i) why ANGPTL3 is considered one of the most promising new cardiometabolic therapy targets, and (ii) the present evidences for its intra-hepatocellular or cell-autonomous functions.
Collapse
Affiliation(s)
- Hanna Ruhanen
- Minerva Foundation Institute for Medical Research, Helsinki, Finland; Molecular and Integrative Biosciences, University of Helsinki, Finland
| | | | - Matti Jauhiainen
- Minerva Foundation Institute for Medical Research, Helsinki, Finland
| | - Vesa M Olkkonen
- Minerva Foundation Institute for Medical Research, Helsinki, Finland; Department of Anatomy, Faculty of Medicine, University of Helsinki, Finland.
| |
Collapse
|
50
|
Stitziel NO, Kanter JE, Bornfeldt KE. Emerging Targets for Cardiovascular Disease Prevention in Diabetes. Trends Mol Med 2020; 26:744-757. [PMID: 32423639 PMCID: PMC7395866 DOI: 10.1016/j.molmed.2020.03.011] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Revised: 03/18/2020] [Accepted: 03/31/2020] [Indexed: 12/26/2022]
Abstract
Type 1 and type 2 diabetes mellitus (T1DM and T2DM) increase the risk of atherosclerotic cardiovascular disease (CVD), resulting in acute cardiovascular events, such as heart attack and stroke. Recent clinical trials point toward new treatment and prevention strategies for cardiovascular complications of T2DM. New antidiabetic agents show unexpected cardioprotective benefits. Moreover, genetic and reverse translational strategies have revealed potential novel targets for CVD prevention in diabetes, including inhibition of apolipoprotein C3 (APOC3). Modeling and pharmacology-based approaches to improve insulin action provide additional potential strategies to combat CVD. The development of new strategies for improved diabetes and lipid control fuels hope for future prevention of CVD associated with diabetes.
Collapse
Affiliation(s)
- Nathan O Stitziel
- Department of Internal Medicine, Cardiovascular Division, Washington University School of Medicine, St Louis, MO 63110, USA; Department of Genetics, Washington University School of Medicine, St Louis, MO 63110, USA; McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Jenny E Kanter
- Department of Medicine, Division of Metabolism, Endocrinology and Nutrition, University of Washington Medicine Diabetes Institute, University of Washington School of Medicine, Seattle, WA 98109, USA
| | - Karin E Bornfeldt
- Department of Medicine, Division of Metabolism, Endocrinology and Nutrition, University of Washington Medicine Diabetes Institute, University of Washington School of Medicine, Seattle, WA 98109, USA; Department of Pathology, University of Washington Medicine Diabetes Institute, University of Washington School of Medicine, Seattle, WA 98109, USA.
| |
Collapse
|