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Chen Z, Yang Y, Peng C, Zhou Z, Wang F, Miao C, Li X, Wang M, Feng S, Chen T, Chen R, Liang Z. Mendelian randomisation studies for causal inference in chronic obstructive pulmonary disease: A narrative review. Pulmonology 2025; 31:2470556. [PMID: 39996617 DOI: 10.1080/25310429.2025.2470556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2024] [Accepted: 02/14/2025] [Indexed: 02/26/2025] Open
Abstract
BACKGROUND AND OBJECTIVE Most non-randomised controlled trials are unable to establish clear causal relationships in chronic obstructive pulmonary disease (COPD) due to the presence of confounding factors. This review summarises the evidence that the Mendelian randomisation method can be a powerful tool for performing causal inferences in COPD. METHODS A non-systematic search of English-language scientific literature was performed on PubMed using the following keywords: 'Mendelian randomisation', 'COPD', 'lung function', and 'GWAS'. No date restrictions were applied. The types of articles selected included randomised controlled trials, cohort studies, observational studies, and reviews. RESULTS Mendelian randomisation is becoming an increasingly popular method for identifying the risk factors of COPD. Recent Mendelian randomisation studies have revealed some risk factors for COPD, such as club cell secretory protein-16, impaired kidney function, air pollutants, asthma, and depression. In addition, Mendelian randomisation results suggest that genetically predicted factors such as PM2.5, inflammatory cytokines, growth differentiation factor 15, docosahexaenoic acid, and testosterone may have causal relationships with lung function. CONCLUSION Mendelian randomisation is a robust method for performing causal inferences in COPD research as it reduces the impact of confounding factors.
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Affiliation(s)
- Zizheng Chen
- Guangzhou Institute of Respiratory Health, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Clinical Medicine, Guangzhou Medical University, Guangzhou, China
| | - Yuqiong Yang
- Guangzhou Institute of Respiratory Health, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Chusheng Peng
- Department of Clinical Medicine, Guangzhou Medical University, Guangzhou, China
| | - Zifei Zhou
- Guangzhou Institute of Respiratory Health, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Clinical Medicine, Guangzhou Medical University, Guangzhou, China
| | - Fengyan Wang
- Guangzhou Institute of Respiratory Health, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Clinical Medicine, Guangzhou Medical University, Guangzhou, China
| | - Chengyu Miao
- Guangzhou Institute of Respiratory Health, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Clinical Medicine, Guangzhou Medical University, Guangzhou, China
| | - Xueping Li
- Guangzhou Institute of Respiratory Health, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Clinical Medicine, Guangzhou Medical University, Guangzhou, China
| | - Mingdie Wang
- Guangzhou Institute of Respiratory Health, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Clinical Medicine, Guangzhou Medical University, Guangzhou, China
| | - Shengchuan Feng
- Department of Clinical Medicine, Guangzhou Medical University, Guangzhou, China
| | - Tingnan Chen
- Department of Clinical Medicine, Guangzhou Medical University, Guangzhou, China
| | - Rongchang Chen
- Guangzhou Institute of Respiratory Health, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Respiratory and Critical Care Medicine, Hetao Institute of Guangzhou National Laboratory, Shenzhen, Guangdong, China
| | - Zhenyu Liang
- Guangzhou Institute of Respiratory Health, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Clinical Medicine, Guangzhou Medical University, Guangzhou, China
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Sun Z, Zheng Y. Metabolic diseases in the East Asian populations. Nat Rev Gastroenterol Hepatol 2025:10.1038/s41575-025-01058-8. [PMID: 40200111 DOI: 10.1038/s41575-025-01058-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/05/2025] [Indexed: 04/10/2025]
Abstract
East Asian populations, which account for approximately 20% of the global population, have become central to the worldwide rise of metabolic diseases over the past few decades. The prevalence of metabolic disorders, including type 2 diabetes mellitus, hypertension and metabolic dysfunction-associated steatotic liver disease, has escalated sharply, contributing to a substantial burden of complications such as cardiovascular disease, chronic kidney disease, cancer and increased mortality. This concerning trend is primarily driven by a combination of genetic predisposition, unique fat distribution patterns and rapidly changing lifestyle factors, including urbanization and the adoption of Westernized dietary habits. Current advances in genomics, proteomics, metabolomics and microbiome research have provided new insights into the biological mechanisms that might contribute to the heightened susceptibility of East Asian populations to metabolic diseases. This Review synthesizes epidemiological data, risk factors and biomarkers to provide an overview of how metabolic diseases are reshaping public health in East Asia and offers insights into biological and societal drivers to guide effective, region-specific strategies.
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Affiliation(s)
- Zhonghan Sun
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yan Zheng
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhongshan Hospital, Fudan University, Shanghai, China.
- Department of Nutrition and Food Hygiene, School of Public Health, Institute of Nutrition, Fudan University, Shanghai, China.
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Lee S, Miller CL, Bentley AR, Brown MR, Nagarajan P, Noordam R, Morrison J, Schwander K, Westerman K, Kho M, Kraja AT, de Vries PS, Ammous F, Aschard H, Bartz TM, Do A, Dupont CT, Feitosa MF, Gudmundsdottir V, Guo X, Harris SE, Hikino K, Huang Z, Lefevre C, Lyytikäinen LP, Milaneschi Y, Nardone GG, Santin A, Schmidt H, Shen B, Sofer T, Sun Q, Tan YA, Tang J, Thériault S, van der Most PJ, Ware EB, Weiss S, Ya Xing W, Yu C, Zhao W, Ansari MAY, Anugu P, Attia JR, Bazzano LA, Bis JC, Breyer M, Cade B, Chen G, Collins S, Corley J, Davies G, Dörr M, Du J, Edwards TL, Faquih T, Faul JD, Fohner AE, Fretts AM, Gangireddy S, Gepner A, Graff M, Hofer E, Homuth G, Hood MM, Jie X, Kähönen M, Kardia SL, Karvonen-Gutierrez CA, Launer LJ, Levy D, Maheshwari M, Martin LW, Matsuda K, McNeil JJ, Nolte IM, Okochi T, Raffield LM, Raitakari OT, Risch L, Risch M, Roux AD, Ruiz-Narvaez EA, Russ TC, Saito T, Schreiner PJ, Scott RJ, Shikany J, Smith JA, Snieder H, Spedicati B, Tai ES, Taylor AM, Taylor KD, Tesolin P, van Dam RM, Wang R, Wenbin W, Xie T, Yao J, et alLee S, Miller CL, Bentley AR, Brown MR, Nagarajan P, Noordam R, Morrison J, Schwander K, Westerman K, Kho M, Kraja AT, de Vries PS, Ammous F, Aschard H, Bartz TM, Do A, Dupont CT, Feitosa MF, Gudmundsdottir V, Guo X, Harris SE, Hikino K, Huang Z, Lefevre C, Lyytikäinen LP, Milaneschi Y, Nardone GG, Santin A, Schmidt H, Shen B, Sofer T, Sun Q, Tan YA, Tang J, Thériault S, van der Most PJ, Ware EB, Weiss S, Ya Xing W, Yu C, Zhao W, Ansari MAY, Anugu P, Attia JR, Bazzano LA, Bis JC, Breyer M, Cade B, Chen G, Collins S, Corley J, Davies G, Dörr M, Du J, Edwards TL, Faquih T, Faul JD, Fohner AE, Fretts AM, Gangireddy S, Gepner A, Graff M, Hofer E, Homuth G, Hood MM, Jie X, Kähönen M, Kardia SL, Karvonen-Gutierrez CA, Launer LJ, Levy D, Maheshwari M, Martin LW, Matsuda K, McNeil JJ, Nolte IM, Okochi T, Raffield LM, Raitakari OT, Risch L, Risch M, Roux AD, Ruiz-Narvaez EA, Russ TC, Saito T, Schreiner PJ, Scott RJ, Shikany J, Smith JA, Snieder H, Spedicati B, Tai ES, Taylor AM, Taylor KD, Tesolin P, van Dam RM, Wang R, Wenbin W, Xie T, Yao J, Young KL, Zhang R, Zonderman AB, Concas MP, Conen D, Cox SR, Evans MK, Fox ER, de Las Fuentes L, Giri A, Girotto G, Grabe HJ, Gu C, Gudnason V, Harlow SD, Holliday E, Jost JB, Lacaze P, Lee S, Lehtimäki T, Li C, Liu CT, Morrison AC, North KE, Penninx BW, Peyser PA, Province MM, Psaty BM, Redline S, Rosendaal FR, Rotimi CN, Rotter JI, Schmidt R, Sim X, Terao C, Weir DR, Zhu X, Franceschini N, O'Connell JR, Jaquish CE, Wang H, Manning A, Munroe PB, Rao DC, Chen H, Gauderman WJ, Bierut L, Winkler TW, Fornage M. A Large-Scale Genome-wide Association Study of Blood Pressure Accounting for Gene-Depressive Symptomatology Interactions in 564,680 Individuals from Diverse Populations. RESEARCH SQUARE 2025:rs.3.rs-6025759. [PMID: 40034430 PMCID: PMC11875294 DOI: 10.21203/rs.3.rs-6025759/v1] [Show More Authors] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/05/2025]
Abstract
Background Gene-environment interactions may enhance our understanding of hypertension. Our previous study highlighted the importance of considering psychosocial factors in gene discovery for blood pressure (BP) but was limited in statistical power and population diversity. To address these challenges, we conducted a multi-population genome-wide association study (GWAS) of BP accounting for gene-depressive symptomatology (DEPR) interactions in a larger and more diverse sample. Results Our study included 564,680 adults aged 18 years or older from 67 cohorts and 4 population backgrounds (African (5%), Asian (7%), European (85%), and Hispanic (3%)). We discovered seven novel gene-DEPR interaction loci for BP traits. These loci mapped to genes implicated in neurogenesis (TGFA, CASP3), lipid metabolism (ACSL1), neuronal apoptosis (CASP3), and synaptic activity (CNTN6, DBI). We also identified evidence for gene-DEPR interaction at nine known BP loci, further suggesting links between mood disturbance and BP regulation. Of the 16 identified loci, 11 loci were derived from African, Asian, or Hispanic populations. Post-GWAS analyses prioritized 36 genes, including genes involved in synaptic functions (DOCK4, MAGI2) and neuronal signaling (CCK, UGDH, SLC01A2). Integrative druggability analyses identified 11 druggable candidate gene targets, including genes implicated in pathways linked to mood disorders as well as gene products targeted by known antihypertensive drugs. Conclusions Our findings emphasize the importance of considering gene-DEPR interactions on BP, particularly in non-European populations. Our prioritized genes and druggable targets highlight biological pathways connecting mood disorders and hypertension and suggest opportunities for BP drug repurposing and risk factor prevention, especially in individuals with DEPR.
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Affiliation(s)
- Songmi Lee
- Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, McGovern Medical School, Houston, TX
| | - Clint L Miller
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA
| | - Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD
| | - Michael R Brown
- Human Genetics Center, Department of Epidemiology, The University of Texas Health Science Center at Houston School of Public Health, Houston, TX
| | - Pavithra Nagarajan
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA
| | - Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden
| | - John Morrison
- Division of Biostatistics, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA
| | - Karen Schwander
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO
| | - Kenneth Westerman
- Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital, Boston, MA
| | - Minjung Kho
- Graduate School of Data Science, Seoul National University, Seoul
| | - Aldi T Kraja
- University of Mississippi Medical Center, Jackson, MS
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, The University of Texas Health Science Center at Houston School of Public Health, Houston, TX
| | - Farah Ammous
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI
| | - Hughes Aschard
- Department of Computational Biology, F-75015 Paris, France Institut Pasteur, Université Paris Cité, Paris
| | - Traci M Bartz
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA
| | - Anh Do
- Center for Biostatistics and Data Science, Institute for Informatics, Data Science, and Biostatistics, Washington University in St. Louis, School of Medicine, St. Louis, MO
| | - Charles T Dupont
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN
| | - Mary F Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO
| | | | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Sarah E Harris
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, Edinburgh
| | - Keiko Hikino
- Laboratory for Pharmacogenomics, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa
| | - Zhijie Huang
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA
| | - Christophe Lefevre
- Department of Data Sciences, Hunter Medical Research Institute, New Lambton Heights, NSW
| | - Leo-Pekka Lyytikäinen
- Finnish Cardiovascular Research Center - Tampere, Department of Clinical Chemistry, Fimlab Laboratories and Faculty of Medicine and Health Technology, Tampere University, Tampere
| | - Yuri Milaneschi
- Department of Psychiatry, Amsterdam UMC/Vrije universiteit, Amsterdam
| | | | - Aurora Santin
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste
| | - Helena Schmidt
- Department of Molecular Biology and Biochemistry, Medical University Graz, Graz, Styria
| | - Botong Shen
- Laboratory of Epidemiology and Population Sciences, Health Disparities Research Section, National Institute on Aging, National Institutes of Health, Baltimore, MD
| | - Tamar Sofer
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA
| | - Quan Sun
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Ye An Tan
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
| | - Jingxian Tang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Sébastien Thériault
- Institut universitaire de cardiologie et de pneumologie de Québec-Université Laval, Department of Molecular Biology, Medical Biochemistry and Pathology, Université Laval, Quebec City, QC
| | - Peter J van der Most
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen
| | - Erin B Ware
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI
| | - Stefan Weiss
- Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald
| | - Wang Ya Xing
- Beijing Institute of Ophthalmology, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology and Visual Sciences Key Laboratory, Beijing, Beijing
| | - Chenglong Yu
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC
| | - Wei Zhao
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI
| | - Md Abu Yusuf Ansari
- Department of Data Science, University of Mississippi Medical Center, Jackson, MS
| | - Pramod Anugu
- Jackson Heart Study, University of Mississippi Medical Center, Jackson, MS
| | - John R Attia
- School of Medicine and Public Health, College of Health Medicine and Wellbeing, University of Newcastle, New Lambton Heights, NSW
| | - Lydia A Bazzano
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA
| | - Max Breyer
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Brian Cade
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA
| | - Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD
| | - Stacey Collins
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI
| | - Janie Corley
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, Edinburgh
| | - Gail Davies
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, Edinburgh
| | - Marcus Dörr
- German Center for Cardiovascular Research (DZHK), partner site Greifswald, Greifswald
| | - Jiawen Du
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Todd L Edwards
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Tariq Faquih
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA
| | - Jessica D Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI
| | - Alison E Fohner
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA
| | - Amanda M Fretts
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA
| | - Srushti Gangireddy
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN
| | - Adam Gepner
- Cardiovascular Medicine, Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
| | - MariaElisa Graff
- Cardiovascular Disease (CVD) Genetic Epidemiology Laboratory, Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Edith Hofer
- Department of Neurology, Medical University Graz, Graz, Styria
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald
| | - Michelle M Hood
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI
| | - Xu Jie
- Beijing Institute of Ophthalmology, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology and Visual Sciences Key Laboratory, Beijing, Beijing
| | - Mika Kähönen
- Finnish Cardiovascular Research Center - Tampere, Department of Clinical Physiology, Tampere University Hospital and Faculty of Medicine and Health Technology, Tampere University, Tampere
| | - Sharon Lr Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI
| | | | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, National Institutes of Health, Baltimore, MD
| | - Daniel Levy
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | | | - Lisa W Martin
- Department of Cardiology, George Washington University, Washington, DC
| | - Koichi Matsuda
- Institute of Medical Science, The University of Tokyo, Minato-ku, Tokyo
| | - John J McNeil
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC
| | - Ilja M Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen
| | - Tomo Okochi
- Department of Psychiatry, Fujita Health University School of Medicine, Toyoake, Aichi
| | - Laura M Raffield
- Department of Genetics, University of North Carolina, Chapel Hill, NC
| | - Olli T Raitakari
- Centre for Population Health Research, Department of Clinical Physiology and Nuclear Medicine, InFLAMES Research Flagship, Turku University Hospital and University of Turku, Turku
| | - Lorenz Risch
- Faculty of Medical Sciences , Institute for Laboratory Medicine, Private University in the Principality of Liechtenstein, Vaduz
| | - Martin Risch
- Central Laboratory, Cantonal Hospital Graubünden, Chur
| | - Ana Diez Roux
- Urban Health Collaborative, Department of Epidemiology and Biostatistics, Drexel University, Philadelphia, PA
| | | | - Tom C Russ
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, Edinburgh
| | - Takeo Saito
- Department of Psychiatry, Fujita Health University School of Medicine, Toyoake, Aichi
| | - Pamela J Schreiner
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN
| | - Rodney J Scott
- School of Medicine and Public Health, College of Health Medicine and Wellbeing, University of Newcastle, New Lambton Heights, NSW
| | - James Shikany
- Division of General Internal Medicine and Population Science, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL
| | - Jennifer A Smith
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen
| | - Beatrice Spedicati
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste
| | - E Shyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
| | - Adele M Taylor
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, Edinburgh
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Paola Tesolin
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste
| | - Rob M van Dam
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
| | - Rujia Wang
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen
| | - Wei Wenbin
- Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, Beijing
| | - Tian Xie
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen
| | - Jie Yao
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Kristin L Young
- Cardiovascular Disease (CVD) Genetic Epidemiology Laboratory, Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Ruiyuan Zhang
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA
| | - Alan B Zonderman
- Laboratory of Epidemiology and Population Sciences, Health Disparities Research Section, National Institute on Aging, National Institutes of Health, Baltimore, MD
| | - Maria Pina Concas
- Institute for Maternal and Child Health - IRCCS "Burlo Garofolo", Trieste
| | - David Conen
- Population Health Research Institute, Department of Medicine, McMaster University, Hamilton, ON
| | - Simon R Cox
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, Edinburgh
| | - Michele K Evans
- Laboratory of Epidemiology and Population Sciences, Health Disparities Research Section, National Institute on Aging, National Institutes of Health, Baltimore, MD
| | - Ervin R Fox
- Jackson Heart Study, University of Mississippi Medical Center, Jackson, MS
| | - Lisa de Las Fuentes
- Center for Biostatistics and Data Science, Institute for Informatics, Data Science, and Biostatistics, Washington University in St. Louis, School of Medicine, St. Louis, MO
| | - Ayush Giri
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Giorgia Girotto
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Mecklenburg-Western Pomerania
| | - Charles Gu
- Center for Biostatistics and Data Science, Institute for Informatics, Data Science, and Biostatistics, Washington University in St. Louis, School of Medicine, St. Louis, MO
| | | | - Sioban D Harlow
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI
| | - Elizabeth Holliday
- School of Medicine and Public Health, College of Health Medicine and Wellbeing, University of Newcastle, New Lambton Heights, NSW
| | - Jonas B Jost
- Rothschild Foundation Hospital, Institut Français de Myopie, Paris
| | - Paul Lacaze
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC
| | - Seunggeun Lee
- Graduate School of Data Science, Seoul National University, Seoul
| | - Terho Lehtimäki
- Finnish Cardiovascular Research Center - Tampere, Department of Clinical Chemistry, Fimlab Laboratories and Faculty of Medicine and Health Technology, Tampere University, Tampere
| | - Changwei Li
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, The University of Texas Health Science Center at Houston School of Public Health, Houston, TX
| | - Kari E North
- Cardiovascular Disease (CVD) Genetic Epidemiology Laboratory, Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | | | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI
| | - Michael M Province
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA
| | - Frits R Rosendaal
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden
| | - Charles N Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD
| | - 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
| | | | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
| | - Chikashi Terao
- The Clinical Research Center at Shizuoka General Hospital, Shizuoka
| | - David R Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI
| | - Xiaofeng Zhu
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Jeffrey R O'Connell
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD
| | - Cashell E Jaquish
- Division of Cardiovascular Science, Epidemiology Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - Heming Wang
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA
| | - Alisa Manning
- Metabolism Program, Broad Institute of MIT and Harvard, Cambridge, MA
| | - Patricia B Munroe
- Clinical Pharmacology and Precision Medicine, Queen Mary University of London, London
| | - Dabeeru C Rao
- Center for Biostatistics and Data Science, Institute for Informatics, Data Science, and Biostatistics, Washington University in St. Louis, School of Medicine, St. Louis, MO
| | - Han Chen
- Human Genetics Center, Department of Epidemiology, The University of Texas Health Science Center at Houston School of Public Health, Houston, TX
| | - W James Gauderman
- Division of Biostatistics, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA
| | - Laura Bierut
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO
| | - Thomas W Winkler
- Department of Genetic Epidemiology, University of Regensburg, Regensburg
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, McGovern Medical School, Houston, TX
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Sutoh Y, Hachiya T, Otsuka-Yamasaki Y, Komaki S, Minabe S, Ohmomo H, Sasaki M, Shimizu A. Healthy lifestyle practice correlates with decreased obesity prevalence in individuals with high polygenic risk: TMM CommCohort study. J Hum Genet 2025; 70:9-15. [PMID: 39174808 DOI: 10.1038/s10038-024-01280-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Revised: 06/24/2024] [Accepted: 07/24/2024] [Indexed: 08/24/2024]
Abstract
Obesity and overweight, fundamental components of the metabolic syndrome, predispose individuals to lifestyle-related diseases. The extent to which adopting healthy lifestyles can reduce obesity risk, even in those with a high genetic risk, remains uncertain. Our aim was to assess the extent to which lifestyle modifications can improve outcomes in individuals with a high polygenic score (PGS) for obesity. We quantified the genetic risk of obesity using PGSs. Four datasets from the Tohoku Medical Megabank Community-Based Cohort (TMM CommCohort) were employed in the study. One dataset (n = 9958) was used to select the best model for calculating PGS. The remaining datasets (total n = 69,341) were used in a meta-analysis to validate the model and to evaluate associated risks. The odds ratio (OR) for obesity risk in the intermediate (11th-90th percentiles in the dataset) and high PGS categories (91st-100th) was 2.27 [95% confidence intervals: 2.12-2.44] and 4.83 [4.45-5.25], respectively, compared to that in the low PGS category (1st-10th). Trend analysis showed that an increase in leisure-time physical activity was significantly associated with reduced obesity risk across all genetic risk categories, representing an OR of 0.9 [0.87-0.94] even among individuals in the high PGS category. Similarly, sodium intake displayed a positive association with obesity across all genetic risk categories, yielding an OR of 1.24 [1.17-1.31] in the high PGS category. The risk of obesity was linked to the adoption of healthy lifestyles, even in individuals with high PGS. Our results may provide perspectives for integrating PGSs into preventive medicine.
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Affiliation(s)
- Yoichi Sutoh
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Yahaba, Japan
- Division of Biomedical Information Analysis, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan
| | - Tsuyoshi Hachiya
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Yahaba, Japan
- Division of Biomedical Information Analysis, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan
| | - Yayoi Otsuka-Yamasaki
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Yahaba, Japan
- Division of Biomedical Information Analysis, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan
| | - Shohei Komaki
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Yahaba, Japan
- Division of Biomedical Information Analysis, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan
| | - Shiori Minabe
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Yahaba, Japan
- Division of Biomedical Information Analysis, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan
| | - Hideki Ohmomo
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Yahaba, Japan
- Division of Biomedical Information Analysis, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan
| | - Makoto Sasaki
- Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Yahaba, Japan
- Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan
| | - Atsushi Shimizu
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Yahaba, Japan.
- Division of Biomedical Information Analysis, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan.
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5
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Shine BK, Choi JE, Park YJ, Hong KW. The Genetic Variants Influencing Hypertension Prevalence Based on the Risk of Insulin Resistance as Assessed Using the Metabolic Score for Insulin Resistance (METS-IR). Int J Mol Sci 2024; 25:12690. [PMID: 39684400 DOI: 10.3390/ijms252312690] [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: 10/21/2024] [Revised: 11/24/2024] [Accepted: 11/25/2024] [Indexed: 12/18/2024] Open
Abstract
Insulin resistance is a major indicator of cardiovascular diseases, including hypertension. The Metabolic Score for Insulin Resistance (METS-IR) offers a simplified and cost-effective way to evaluate insulin resistance. This study aimed to identify genetic variants associated with the prevalence of hypertension stratified by METS-IR score levels. Data from the Korean Genome and Epidemiology Study (KoGES) were analyzed. The METS-IR was calculated using the following formula: ln [(2 × fasting blood glucose (FBG) + triglycerides (TG)) × body mass index (BMI)]/ ln [high-density lipoprotein cholesterol (HDL-C)]. The participants were divided into tertiles 1 (T1) and 3 (T3) based on their METS-IR scores. Genome-wide association studies (GWAS) were performed for hypertensive cases and non-hypertensive controls within these tertile groups using logistic regression adjusted for age, sex, and lifestyle factors. Among the METS-IR tertile groups, 3517 of the 19,774 participants (17.8%) at T1 had hypertension, whereas 8653 of the 20,374 participants (42.5%) at T3 had hypertension. A total of 113 single-nucleotide polymorphisms (SNPs) reached the GWAS significance threshold (p < 5 × 10-8) in at least one tertile group, mapping to six distinct genetic loci. Notably, four loci, rs11899121 (chr2p24), rs7556898 (chr2q24.3), rs17249754 (ATP2B1), and rs1980854 (chr20p12.2), were significantly associated with hypertension in the high-METS-score group (T3). rs10857147 (FGF5) was significant in both the T1 and T3 groups, whereas rs671 (ALDH2) was significant only in the T1 group. The GWASs identified six genetic loci significantly associated with hypertension, with distinct patterns across METS-IR tertiles, highlighting the role of metabolic context in genetic susceptibility. These findings underscore critical genetic factors influencing hypertension prevalence and provide insights into the metabolic-genetic interplay underlying this condition.
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Affiliation(s)
- Bo-Kyung Shine
- Department of Family Medicine, Medical Center, Dong-A University, Busan 49201, Republic of Korea
| | - Ja-Eun Choi
- Institute of Advanced Technology, Theragen Health Co., Ltd., Seongnam 13493, Republic of Korea
| | - Young-Jin Park
- Department of Family Medicine, Medical Center, Dong-A University, Busan 49201, Republic of Korea
| | - Kyung-Won Hong
- Institute of Advanced Technology, Theragen Health Co., Ltd., Seongnam 13493, Republic of Korea
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6
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Liu Q, Cui Z, Deng C, Yang C, Shi T. A real-world pharmacovigilance analysis of adverse events associated with irbesartan using the FAERS and JADER databases. Front Pharmacol 2024; 15:1485190. [PMID: 39635439 PMCID: PMC11614654 DOI: 10.3389/fphar.2024.1485190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2024] [Accepted: 10/28/2024] [Indexed: 12/07/2024] Open
Abstract
Objective Hypertension is a leading global risk factor for disability and death. Irbesartan, a potent angiotensin II receptor blocker, requires continuous safety monitoring. We conducted a disproportionality analysis of irbesartan-related adverse drug events (ADEs) using the FDA's FAERS and Japan's JADER databases. Methods We extracted irbesartan-related ADE reports from FAERS (Q1 2004 to Q1 2024) and JADER (Q2 2008 to Q4 2023). We used Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Empirical Bayesian Geometric Mean (EBGM) for signal detection. Sensitivity analyses were conducted to exclude comorbid medications, and subgroup analyses by age and gender were performed to explore ADE occurrence in specific populations. Th time to onset (TTO) of ADEs was assessed using Weibull distribution test and Kaplan-Meier curves. Results A total of 5,816 (FAERS) and 366 (JADER) reports were analyzed, with irbesartan-related preferred terms (PTs) involving 27 System Organ Classes (SOCs) in FAERS and 22 in JADER. Three SOCs met detection thresholds in both databases: "metabolism and nutrition disorders," "cardiac disorders," and "renal and urinary disorders." We identified 219 positive signals in FAERS and 20 in JADER, including known signals like hyperkalemia, hypotension, and acute kidney injury. Notably, newly identified signals such as acute pancreatitis (n = 50, ROR: 7.76 [5.88-10.25]) and rhabdomyolysis (n = 50, ROR: 7.76 [5.88-10.25]) in FAERS and respiratory failure (n = 7, ROR: 6.76 [3.20-14.26]) in JADER could have significant clinical implications, as they may lead to severe outcomes if not recognized and managed promptly. Subgroup analyses revealed both similarities and differences in signal detection across gender and age groups. Sensitivity analyses, excluding concomitant medications, confirmed the persistence of key positive signals, including hyperkalemia, angioedema, acute pancreatitis, and agranulocytosis. ADEs mainly occurred within 1 month (34.14%) and after 1 year (32.32%) after dosing, with a median onset of 107 days. Conclusion This study provides valuable real-world evidence on the safety profile of irbesartan. The identification of new safety signals underscores the necessity of updating drug labels, particularly for assessing and managing high-risk patients. Additionally, the TTO analysis emphasizes the importance of sustained vigilance for adverse events over time. In conclusion, our findings contribute to a more comprehensive understanding of irbesartan's safety, aiding healthcare professionals in optimizing its use in clinical practice.
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Affiliation(s)
- Qian Liu
- Department of Cardiovascular Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Zhiwei Cui
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Chao Deng
- Department of Cardiovascular Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Chao Yang
- Department of Cardiovascular Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Tao Shi
- Department of Cardiovascular Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
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7
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Ardissino M, Truong B, Slob EAW, Schuermans A, Yoshiji S, Morley AP, Burgess S, Ng FS, de Marvao A, Natarajan P, Nicolaides K, Gaziano L, Butterworth A, Honigberg MC. Proteome- and Transcriptome-Wide Genetic Analysis Identifies Biological Pathways and Candidate Drug Targets for Preeclampsia. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2024; 17:e004755. [PMID: 39119725 PMCID: PMC7616531 DOI: 10.1161/circgen.124.004755] [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: 04/05/2024] [Accepted: 07/25/2024] [Indexed: 08/10/2024]
Abstract
BACKGROUND Preeclampsia is a leading cause of maternal and perinatal morbidity and mortality. However, the current understanding of its underlying biological pathways remains limited. METHODS In this study, we performed a cross-platform proteome- and transcriptome-wide genetic analysis aimed at evaluating the causal relevance of >2000 circulating proteins with preeclampsia, supported by data on the expression of over 15 000 genes across 36 tissues leveraging large-scale preeclampsia genetic association data from women of European ancestry. RESULTS We demonstrate genetic associations of 18 circulating proteins with preeclampsia (SULT1A1 [sulfotransferase 1A1], SH2B3 [SH2B adapter protein 3], SERPINE2 [serpin family E member 2], RGS18 [regulator of G-protein signaling 18], PZP [pregnancy zone protein], NOTUM [notum, palmitoleoyl-protein carboxylesterase], METAP1 [methionyl aminopeptidase 1], MANEA [mannosidase endo-alpha], jun-D [JunD proto-oncogene], GDF15 [growth differentiation factor 15], FGL1 [fibrinogen like 1], FGF5 [fibroblast growth factor 5], FES [FES proto-oncogene], APOBR [apolipoprotein B receptor], ANP [natriuretic peptide A], ALDH-E2 [aldehyde dehydrogenase 2 family member], ADAMTS13 [ADAM metallopeptidase with thrombospondin type 1 motif 13], and 3MG [N-methylpurine DNA glycosylase]), among which 11 were either directly or indirectly supported by gene expression data, 9 were supported by Bayesian colocalization analyses, and 5 (SERPINE2, PZP, FGF5, FES, and ANP) were supported by all lines of evidence examined. Protein interaction mapping identified potential shared biological pathways through natriuretic peptide signaling, blood pressure regulation, immune tolerance, and thrombin activity regulation. CONCLUSIONS This investigation identified multiple targetable proteins linked to cardiovascular, inflammatory, and coagulation pathways, with SERPINE2, PZP, FGF5, FES, and ANP identified as pivotal proteins with likely causal roles in the development of preeclampsia. The identification of these potential targets may guide the development of targeted therapies for preeclampsia.
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Affiliation(s)
- Maddalena Ardissino
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care (M.A., L.G., A.B.), University of Cambridge, United Kingdom
- Victor Phillip Dahdaleh Heart and Lung Research Institute (M.A, A.B.), University of Cambridge, United Kingdom
- National Heart and Lung Institute (M.A, F.S.N.), Imperial College London, United Kingdom
- Medical Research Council, London Institute of Medical Sciences (M.A.), Imperial College London, United Kingdom
| | - Buu Truong
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative (B.T., A.S., P.N., M.C.H.)
- Center for Genomic Medicine and Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston (B.T., A.S., P.N., M.C.H.)
| | - Eric A W Slob
- MRC Biostatistics Unit (E.A.W.S., S.B.), University of Cambridge, United Kingdom
- Department of Applied Economics, Erasmus School of Economics (E.A.W.S.), Erasmus University Rotterdam, the Netherlands
- Erasmus University Rotterdam Institute for Behavior and Biology (E.A.W.S.), Erasmus University Rotterdam, the Netherlands
- Department of Psychology, Education and Child Studies (E.A.W.S.), Erasmus University Rotterdam, the Netherlands
| | - Art Schuermans
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative (B.T., A.S., P.N., M.C.H.)
- Center for Genomic Medicine and Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston (B.T., A.S., P.N., M.C.H.)
- Faculty of Medicine, KU Leuven, Belgium (A.S.)
| | - Satoshi Yoshiji
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA (S.Y.)
| | - Alec P Morley
- Department of Medicine, School of Clinical Medicine (A.P.M.), University of Cambridge, United Kingdom
- Gonville and Caius College (A.P.M.), University of Cambridge, United Kingdom
| | - Stephen Burgess
- MRC Biostatistics Unit (E.A.W.S., S.B.), University of Cambridge, United Kingdom
| | - Fu Siong Ng
- National Heart and Lung Institute (M.A, F.S.N.), Imperial College London, United Kingdom
| | - Antonio de Marvao
- Department of Women and Children's Health (A.d.M., K.N.)
- British Heart Foundation Center of Research Excellence, School of Cardiovascular Medicine and Sciences (A.d.M.), King's College Hospital, London, United Kingdom
- Fetal Medicine Research Institute (A.d.M., K.N.), King's College Hospital, London, United Kingdom
| | - Pradeep Natarajan
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative (B.T., A.S., P.N., M.C.H.)
- Center for Genomic Medicine and Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston (B.T., A.S., P.N., M.C.H.)
| | - Kypros Nicolaides
- Department of Women and Children's Health (A.d.M., K.N.)
- Fetal Medicine Research Institute (A.d.M., K.N.), King's College Hospital, London, United Kingdom
| | - Liam Gaziano
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care (M.A., L.G., A.B.), University of Cambridge, United Kingdom
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System (L.G.), Harvard Medical School, Boston
| | - Adam Butterworth
- Victor Phillip Dahdaleh Heart and Lung Research Institute (M.A, A.B.), University of Cambridge, United Kingdom
- British Heart Foundation Center of Research Excellence (A.B.), University of Cambridge, United Kingdom
- Health Data Research UK Cambridge, Wellcome Genome Campus (A.B.), University of Cambridge, United Kingdom
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics (A.B.), University of Cambridge, United Kingdom
| | - Michael C Honigberg
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative (B.T., A.S., P.N., M.C.H.)
- Department of Medicine (M.C.H.), Harvard Medical School, Boston
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8
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Shi S, Rubinacci S, Hu S, Moutsianas L, Stuckey A, Need AC, Palamara PF, Caulfield M, Marchini J, Myers S. A Genomics England haplotype reference panel and imputation of UK Biobank. Nat Genet 2024; 56:1800-1803. [PMID: 39134668 PMCID: PMC11387190 DOI: 10.1038/s41588-024-01868-7] [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: 11/21/2023] [Accepted: 07/11/2024] [Indexed: 09/12/2024]
Abstract
We built a reference panel with 342 million autosomal variants using 78,195 individuals from the Genomics England (GEL) dataset, achieving a phasing switch error rate of 0.18% for European samples and imputation quality of r2 = 0.75 for variants with minor allele frequencies as low as 2 × 10-4 in white British samples. The GEL-imputed UK Biobank genome-wide association analysis identified 70% of associations found by direct exome sequencing (P < 2.18 × 10-11), while extending testing of rare variants to the entire genome. Coding variants dominated the rare-variant genome-wide association results, implying less disruptive effects of rare non-coding variants.
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Affiliation(s)
- Sinan Shi
- Department of Statistics, University of Oxford, Oxford, UK.
| | | | - Sile Hu
- Novo Nordisk Research Centre, Oxford, UK
| | - Loukas Moutsianas
- Genomics England, London, UK
- Queen Mary University of London, London, UK
| | | | | | | | - Mark Caulfield
- Genomics England, London, UK
- Queen Mary University of London, London, UK
| | | | - Simon Myers
- Department of Statistics, University of Oxford, Oxford, UK.
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9
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Gupta MK, Gouda G, Vadde R. Relation Between Obesity and Type 2 Diabetes: Evolutionary Insights, Perspectives and Controversies. Curr Obes Rep 2024; 13:475-495. [PMID: 38850502 DOI: 10.1007/s13679-024-00572-1] [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] [Accepted: 05/13/2024] [Indexed: 06/10/2024]
Abstract
PURPOSE OF REVIEW Since the mid-twentieth century, obesity and its related comorbidities, notably insulin resistance (IR) and type 2 diabetes (T2D), have surged. Nevertheless, their underlying mechanisms remain elusive. Evolutionary medicine (EM) sheds light on these issues by examining how evolutionary processes shape traits and diseases, offering insights for medical practice. This review summarizes the pathogenesis and genetics of obesity-related IR and T2D. Subsequently, delving into their evolutionary connections. Addressing limitations and proposing future research directions aims to enhance our understanding of these conditions, paving the way for improved treatments and prevention strategies. RECENT FINDINGS Several evolutionary hypotheses have been proposed to unmask the origin of obesity-related IR and T2D, e.g., the "thrifty genotype" hypothesis suggests that certain "thrifty genes" that helped hunter-gatherer populations efficiently store energy as fat during feast-famine cycles are now maladaptive in our modern obesogenic environment. The "drifty genotype" theory suggests that if thrifty genes were advantageous, they would have spread widely, but proposes genetic drift instead. The "behavioral switch" and "carnivore connection" hypotheses propose insulin resistance as an adaptation for a brain-dependent, low-carbohydrate lifestyle. The thrifty phenotype theory suggests various metabolic outcomes shaped by genes and environment during development. However, the majority of these hypotheses lack experimental validation. Understanding why ancestral advantages now predispose us to diseases may aid in drug development and prevention of disease. EM helps us to understand the evolutionary relation between obesity-related IR and T2D. But still gaps and contradictions persist. Further interdisciplinary research is required to elucidate complete mechanisms.
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Affiliation(s)
- Manoj Kumar Gupta
- Department of Biotechnology & Bioinformatics, Yogi Vemana University, Kadapa, 516005, Andhra Pradesh, India.
| | - Gayatri Gouda
- ICAR-National Rice Research Institute, Cuttack, 753 006, Odisha, India
| | - Ramakrishna Vadde
- Department of Biotechnology & Bioinformatics, Yogi Vemana University, Kadapa, 516005, Andhra Pradesh, India
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10
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Kumar N, Yang ML, Sun P, Hunker KL, Li J, Jia J, Fan F, Wang J, Ning X, Gao W, Xu M, Zhang J, Chang L, Chen YE, Huo Y, Zhang Y, Ganesh SK. Genetic variation in CCDC93 is associated with elevated central systolic blood pressure, impaired arterial relaxation, and mitochondrial dysfunction. PLoS Genet 2024; 20:e1011151. [PMID: 39250516 PMCID: PMC11421807 DOI: 10.1371/journal.pgen.1011151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 09/24/2024] [Accepted: 01/23/2024] [Indexed: 09/11/2024] Open
Abstract
Genetic studies of blood pressure (BP) traits to date have been performed on conventional measures by brachial cuff sphygmomanometer for systolic BP (SBP) and diastolic BP, integrating several physiologic occurrences. Genetic associations with central SBP (cSBP) have not been well-studied. Genetic discovery studies of BP have been most often performed in European-ancestry samples. Here, we investigated genetic associations with cSBP in a Chinese population and functionally validated the impact of a novel associated coiled-coil domain containing 93 (CCDC93) gene on BP regulation. An exome-wide association study (EWAS) was performed using a mixed linear model of non-invasive cSBP and peripheral BP traits in a Han Chinese population (N = 5,954) from Beijing, China genotyped with a customized Illumina ExomeChip array. We identified four SNP-trait associations with three SNPs, including two novel associations (rs2165468-SBP and rs33975708-cSBP). rs33975708 is a coding variant in the CCDC93 gene, c.535C>T, p.Arg179Cys (MAF = 0.15%), and was associated with increased cSBP (β = 29.3 mmHg, P = 1.23x10-7). CRISPR/Cas9 genome editing was used to model the effect of Ccdc93 loss in mice. Homozygous Ccdc93 deletion was lethal prior to day 10.5 of embryonic development. Ccdc93+/- heterozygous mice were viable and morphologically normal, with 1.3-fold lower aortic Ccdc93 protein expression (P = 0.0041) and elevated SBP as compared to littermate Ccdc93+/+ controls (110±8 mmHg vs 125±10 mmHg, P = 0.016). Wire myography of Ccdc93+/- aortae showed impaired acetylcholine-induced relaxation and enhanced phenylephrine-induced contraction. RNA-Seq transcriptome analysis of Ccdc93+/- mouse thoracic aortae identified significantly enriched pathways altered in fatty acid metabolism and mitochondrial metabolism. Plasma free fatty acid levels were elevated in Ccdc93+/- mice (96±7mM vs 124±13mM, P = 0.0031) and aortic mitochondrial dysfunction was observed through aberrant Parkin and Nix protein expression. Together, our genetic and functional studies support a novel role of CCDC93 in the regulation of BP through its effects on vascular mitochondrial function and endothelial function.
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Affiliation(s)
- Nitin Kumar
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
- Department of Human Genetics, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
| | - Min-Lee Yang
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
- Department of Human Genetics, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
| | - Pengfei Sun
- Department of Cardiology, Peking University First hospital, Beijing, China
- Department of Cardiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Kristina L. Hunker
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
- Department of Human Genetics, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
| | - Jianping Li
- Department of Cardiology, Peking University First hospital, Beijing, China
| | - Jia Jia
- Department of Cardiology, Peking University First hospital, Beijing, China
| | - Fangfang Fan
- Department of Cardiology, Peking University First hospital, Beijing, China
| | - Jinghua Wang
- Laboratory of Epidemiology, Tianjin Neurological Institute, Tianjin, China
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China
| | - Xianjia Ning
- Laboratory of Epidemiology, Tianjin Neurological Institute, Tianjin, China
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China
| | - Wei Gao
- Department of Cardiology, Peking University Third hospital, Beijing, China
| | - Ming Xu
- Department of Cardiology, Peking University Third hospital, Beijing, China
| | - Jifeng Zhang
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
| | - Lin Chang
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
| | - Y. Eugene Chen
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
| | - Yong Huo
- Department of Cardiology, Peking University First hospital, Beijing, China
| | - Yan Zhang
- Department of Cardiology, Peking University First hospital, Beijing, China
- Institute of Cardiovascular Disease, Peking University First Hospital, Beijing, China
- Hypertension Precision Diagnosis and Treatment Research Center, Peking University First Hospital, Beijing, China
| | - Santhi K. Ganesh
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
- Department of Human Genetics, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
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11
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Fry H, Mazidi M, Kartsonaki C, Clarke R, Walters RG, Chen Z, Millwood IY. The Role of Furin and Its Therapeutic Potential in Cardiovascular Disease Risk. Int J Mol Sci 2024; 25:9237. [PMID: 39273186 PMCID: PMC11394739 DOI: 10.3390/ijms25179237] [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: 07/12/2024] [Revised: 08/07/2024] [Accepted: 08/08/2024] [Indexed: 09/15/2024] Open
Abstract
Furin is an important proteolytic enzyme, converting several proteins from inactive precursors to their active forms. Recently, proteo-genomic analyses in European and East Asian populations suggested a causal association of furin with ischaemic heart disease, and there is growing interest in its role in cardiovascular disease (CVD) aetiology. In this narrative review, we present a critical appraisal of evidence from population studies to assess furin's role in CVD risk and potential as a drug target for CVD. Whilst most observational studies report positive associations between furin expression and CVD risk, some studies report opposing effects, which may reflect the complex biological roles of furin and its substrates. Genetic variation in FURIN is also associated with CVD and its risk factors. We found no evidence of current clinical development of furin as a drug target for CVD, although several phase 1 and 2 clinical trials of furin inhibitors as a type of cancer immunotherapy have been completed. The growing field of proteo-genomics in large-scale population studies may inform the future development of furin and other potential drug targets to improve the treatment and prevention of CVD.
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Affiliation(s)
| | | | | | | | | | | | - Iona Y. Millwood
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK; (H.F.); (M.M.); (C.K.); (R.C.); (R.G.W.); (Z.C.)
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Li X, Guo Y, Liang H, Wang J, Qi L. Genome-wide association analysis of hypertension and epigenetic aging reveals shared genetic architecture and identifies novel risk loci. Sci Rep 2024; 14:17792. [PMID: 39090212 PMCID: PMC11294447 DOI: 10.1038/s41598-024-68751-7] [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: 01/14/2024] [Accepted: 07/26/2024] [Indexed: 08/04/2024] Open
Abstract
Hypertension is a disease associated with epigenetic aging. However, the pathogenic mechanism underlying this relationship remains unclear. We aimed to characterize the shared genetic architecture of hypertension and epigenetic aging, and identify novel risk loci. Leveraging genome-wide association studies (GWAS) summary statistics of hypertension (129,909 cases and 354,689 controls) and four epigenetic clocks (N = 34,710), we investigated genetic architectures and genetic overlap using bivariate casual mixture model and conditional/conjunctional false discovery rate methods. Functional gene-sets pathway analyses were performed by functional mapping and gene annotation (FUMA) protocol. Hypertension was polygenic with 2.8 K trait-influencing genetic variants. We observed cross-trait genetic enrichment and genetic overlap between hypertension and all four measures of epigenetic aging. Further, we identified 32 distinct genomic loci jointly associated with hypertension and epigenetic aging. Notably, rs1849209 was shared between hypertension and three epigenetic clocks (HannumAge, IEAA, and PhenoAge). The shared loci exhibited a combination of concordant and discordant allelic effects. Functional gene-set analyses revealed significant enrichment in biological pathways related to sensory perception of smell and nervous system processes. We observed genetic overlaps with mixed effect directions between hypertension and all four epigenetic aging measures, and identified 32 shared distinct loci with mixed effect directions, 25 of which were novel for hypertension. Shared genes enriched in biological pathways related to olfaction.
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Affiliation(s)
- Xin Li
- The Sino-Russian Medical Research Center of Jinan University, The Institute of Chronic Disease of Jinan University, The First Affiliated Hospital of Jinan University, Guangzhou, 511436, China
| | - Yu Guo
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin, 150086, China
| | - Haihai Liang
- The Sino-Russian Medical Research Center of Jinan University, The Institute of Chronic Disease of Jinan University, The First Affiliated Hospital of Jinan University, Guangzhou, 511436, China.
- Department of Pharmacology (State-Province Key Laboratories of Biomedicine-Pharmaceutics of China, Key Laboratory of Cardiovascular Research, Ministry of Education), College of Pharmacy, Harbin Medical University, Harbin, 150086, China.
| | - Jinghao Wang
- Department of Pharmacy, the First Affiliated Hospital, Jinan University, Guangzhou, 510630, Guangdong, China.
- The Guangzhou Key Laboratory of Basic and Translational Research on Chronic Diseases, Jinan University, Guangzhou, 510630, Guangdong, China.
| | - Lishuang Qi
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China.
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Pozarickij A, Gan W, Lin K, Clarke R, Fairhurst-Hunter Z, Koido M, Kanai M, Okada Y, Kamatani Y, Bennett D, Du H, Chen Y, Yang L, Avery D, Guo Y, Yu M, Yu C, Schmidt Valle D, Lv J, Chen J, Peto R, Collins R, Li L, Chen Z, Millwood IY, Walters RG. Causal relevance of different blood pressure traits on risk of cardiovascular diseases: GWAS and Mendelian randomisation in 100,000 Chinese adults. Nat Commun 2024; 15:6265. [PMID: 39048560 PMCID: PMC11269703 DOI: 10.1038/s41467-024-50297-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: 01/27/2023] [Accepted: 07/04/2024] [Indexed: 07/27/2024] Open
Abstract
Elevated blood pressure (BP) is major risk factor for cardiovascular diseases (CVD). Genome-wide association studies (GWAS) conducted predominantly in populations of European ancestry have identified >2,000 BP-associated loci, but other ancestries have been less well-studied. We conducted GWAS of systolic, diastolic, pulse, and mean arterial BP in 100,453 Chinese adults. We identified 128 non-overlapping loci associated with one or more BP traits, including 74 newly-reported associations. Despite strong genetic correlations between populations, we identified appreciably higher heritability and larger variant effect sizes in Chinese compared with European or Japanese ancestry populations. Using instruments derived from these GWAS, multivariable Mendelian randomisation demonstrated that BP traits contribute differently to the causal associations of BP with CVD. In particular, only pulse pressure was independently causally associated with carotid plaque. These findings reinforce the need for studies in diverse populations to understand the genetic determinants of BP traits and their roles in disease risk.
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Affiliation(s)
- Alfred Pozarickij
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Wei Gan
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Human Genetics Centre of Excellence, Novo Nordisk Research Centre Oxford, Innovation Building, Old Road Campus, Oxford, UK
| | - Kuang Lin
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Robert Clarke
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Zammy Fairhurst-Hunter
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Masaru Koido
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Masahiro Kanai
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, 02114, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, 565-0871, Japan
- Department of Genome Informatics, Graduate School of Medicine, University of Tokyo, Tokyo, 113-0033, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, 230- 0045, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, 565-0871, Japan
| | - Yoichiro Kamatani
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Derrick Bennett
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Huaidong Du
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Yiping Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Ling Yang
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Daniel Avery
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Yu Guo
- National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences, 100037, Beijing, China
| | - Min Yu
- Zhejiang CDC, Zhejiang, China
| | - Canqing Yu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Xueyuan Road, Haidian District, 100191, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, 100191, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, 100191, Beijing, China
| | - Dan Schmidt Valle
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Jun Lv
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Xueyuan Road, Haidian District, 100191, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, 100191, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, 100191, Beijing, China
| | - Junshi Chen
- China National Center For Food Safety Risk Assessment, Beijing, China
| | - Richard Peto
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Rory Collins
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Liming Li
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Xueyuan Road, Haidian District, 100191, Beijing, China.
- Peking University Center for Public Health and Epidemic Preparedness and Response, 100191, Beijing, China.
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, 100191, Beijing, China.
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Iona Y Millwood
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Robin G Walters
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
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Huang D, Shang W, Xu M, Wan Q, Zhang J, Tang X, Shen Y, Wang Y, Yu Y. Genome-Wide Methylation Analysis Reveals a KCNK3-Prominent Causal Cascade on Hypertension. Circ Res 2024; 135:e76-e93. [PMID: 38841840 DOI: 10.1161/circresaha.124.324455] [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: 02/16/2024] [Accepted: 05/22/2024] [Indexed: 06/07/2024]
Abstract
BACKGROUND Despite advances in understanding hypertension's genetic structure, how noncoding genetic variants influence it remains unclear. Studying their interaction with DNA methylation is crucial to deciphering this complex disease's genetic mechanisms. METHODS We investigated the genetic and epigenetic interplay in hypertension using whole-genome bisulfite sequencing. Methylation profiling in 918 males revealed allele-specific methylation and methylation quantitative trait loci. We engineered rs1275988T/C mutant mice using CRISPR (clustered regularly interspaced short palindromic repeats)/Cas9 (CRISPR-associated protein 9), bred them for homozygosity, and subjected them to a high-salt diet. Telemetry captured their cardiovascular metrics. Protein-DNA interactions were elucidated using DNA pull-downs, mass spectrometry, and Western blots. A wire myograph assessed vascular function, and analysis of the Kcnk3 gene methylation highlighted the mutation's role in hypertension. RESULTS We discovered that DNA methylation-associated genetic effects, especially in non-cytosine-phosphate-guanine (non-CpG) island and noncoding distal regulatory regions, significantly contribute to hypertension predisposition. We identified distinct methylation quantitative trait locus patterns in the hypertensive population and observed that the onset of hypertension is influenced by the transmission of genetic effects through the demethylation process. By evidence-driven prioritization and in vivo experiments, we unearthed rs1275988 in a cell type-specific enhancer as a notable hypertension causal variant, intensifying hypertension through the modulation of local DNA methylation and consequential alterations in Kcnk3 gene expression and vascular remodeling. When exposed to a high-salt diet, mice with the rs1275988C/C genotype exhibited exacerbated hypertension and significant vascular remodeling, underscored by increased aortic wall thickness. The C allele of rs1275988 was associated with elevated DNA methylation levels, driving down the expression of the Kcnk3 gene by attenuating Nr2f2 (nuclear receptor subfamily 2 group F member 2) binding at the enhancer locus. CONCLUSIONS Our research reveals new insights into the complex interplay between genetic variations and DNA methylation in hypertension. We underscore hypomethylation's potential in hypertension onset and identify rs1275988 as a causal variant in vascular remodeling. This work advances our understanding of hypertension's molecular mechanisms and encourages personalized health care strategies.
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Affiliation(s)
- Dandan Huang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammatory Biology, Center for Cardiovascular Diseases, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, State Key Laboratory of Experimental Hematology, School of Basic Medical Sciences, Tianjin Medical University, China (D.H., W.S., M.X., Y.S., Y.Y.)
- School of Food Science and Technology, Jiangnan University, Wuxi, China (D.H.)
| | - Wenlong Shang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammatory Biology, Center for Cardiovascular Diseases, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, State Key Laboratory of Experimental Hematology, School of Basic Medical Sciences, Tianjin Medical University, China (D.H., W.S., M.X., Y.S., Y.Y.)
| | - Mengtong Xu
- Department of Pharmacology, Tianjin Key Laboratory of Inflammatory Biology, Center for Cardiovascular Diseases, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, State Key Laboratory of Experimental Hematology, School of Basic Medical Sciences, Tianjin Medical University, China (D.H., W.S., M.X., Y.S., Y.Y.)
| | - Qiangyou Wan
- Academy of Integrative Medicine, Shanghai University of Traditional Chinese Medicine (Q.W.)
| | - Jin Zhang
- Department of Cardiovascular Medicine, Research Center for Hypertension Management and Prevention in Community, State Key Laboratory of Medical Genomics, Shanghai Key Laboratory of Hypertension, Shanghai Institute of Hypertension, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China (J.Z., X.T., Y.W.)
| | - Xiaofeng Tang
- Department of Cardiovascular Medicine, Research Center for Hypertension Management and Prevention in Community, State Key Laboratory of Medical Genomics, Shanghai Key Laboratory of Hypertension, Shanghai Institute of Hypertension, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China (J.Z., X.T., Y.W.)
| | - Yujun Shen
- Department of Pharmacology, Tianjin Key Laboratory of Inflammatory Biology, Center for Cardiovascular Diseases, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, State Key Laboratory of Experimental Hematology, School of Basic Medical Sciences, Tianjin Medical University, China (D.H., W.S., M.X., Y.S., Y.Y.)
| | - Yan Wang
- Department of Cardiovascular Medicine, Research Center for Hypertension Management and Prevention in Community, State Key Laboratory of Medical Genomics, Shanghai Key Laboratory of Hypertension, Shanghai Institute of Hypertension, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China (J.Z., X.T., Y.W.)
| | - Ying Yu
- Department of Pharmacology, Tianjin Key Laboratory of Inflammatory Biology, Center for Cardiovascular Diseases, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, State Key Laboratory of Experimental Hematology, School of Basic Medical Sciences, Tianjin Medical University, China (D.H., W.S., M.X., Y.S., Y.Y.)
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15
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Lorincz-Comi N, Yang Y, Li G, Zhu X. MRBEE: A bias-corrected multivariable Mendelian randomization method. HGG ADVANCES 2024; 5:100290. [PMID: 38582968 PMCID: PMC11053334 DOI: 10.1016/j.xhgg.2024.100290] [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: 11/17/2023] [Revised: 04/01/2024] [Accepted: 04/01/2024] [Indexed: 04/08/2024] Open
Abstract
Mendelian randomization (MR) is an instrumental variable approach used to infer causal relationships between exposures and outcomes, which is becoming increasingly popular because of its ability to handle summary statistics from genome-wide association studies. However, existing MR approaches often suffer the bias from weak instrumental variables, horizontal pleiotropy and sample overlap. We introduce MRBEE (MR using bias-corrected estimating equation), a multivariable MR method capable of simultaneously removing weak instrument and sample overlap bias and identifying horizontal pleiotropy. Our extensive simulations and real data analyses reveal that MRBEE provides nearly unbiased estimates of causal effects, well-controlled type I error rates and higher power than comparably robust methods and is computationally efficient. Our real data analyses result in consistent causal effect estimates and offer valuable guidance for conducting multivariable MR studies, elucidating the roles of pleiotropy, and identifying total 42 horizontal pleiotropic loci missed previously that are associated with myopia, schizophrenia, and coronary artery disease.
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Affiliation(s)
- Noah Lorincz-Comi
- Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Yihe Yang
- Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Gen Li
- Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Xiaofeng Zhu
- Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA.
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16
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Fujita K, Yoshida S, Ishizaki R, Yamamoto E, Takahashi N, Iwamae A. Estimation of the relationship between the thermal environment of a house in winter and its occupants' health. ENVIRONMENTAL RESEARCH 2024; 253:119147. [PMID: 38754611 DOI: 10.1016/j.envres.2024.119147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 05/06/2024] [Accepted: 05/13/2024] [Indexed: 05/18/2024]
Abstract
This study aims to quantify the relationship between the arbitrary thermal environment of houses in winter and their occupants' health through a comprehensive questionnaire survey, involving approximately 24,000 individuals who moved into insulated dwellings in Japan. A relationship between the degree of the thermal insulation of these houses and corresponding rates of improvement in the following 10 diseases were formulated: heart disease, cerebrovascular disease, hypertension, diabetes mellitus, asthma, dermatitis and eczema, pneumonia, inflammatory polyarthropathies, allergic rhinitis, and conjunctivitis. Following the statistical analysis of these outcomes, significant differences in improvement rates were identified among the levels of the thermal insulation of houses for the following five diseases: cerebrovascular diseases, asthma, dermatitis and eczema, allergic rhinitis, and conjunctivitis. In addition, the thermal environments of houses corresponding to each thermal insulation level were estimated by numerical simulations. Using these results, we organized the relationships between the thermal environment conditions of houses and observed prevalence rate for the following four diseases for which the improvement rates increased with increasing insulation levels and significant differences were identified: asthma, dermatitis and eczema, allergic rhinitis, and conjunctivitis. Consequently, we formulated equations to predict the prevalence rates of these diseases using the "mean operative temperature of rooms occupied by each family member from January 1 to February 28."
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Affiliation(s)
- Koji Fujita
- Faculty of Biology-Oriented Science and Technology, Kindai University, 930 Nishimitani, Kinokawa, Wakayama, 649-6493, Japan.
| | - Satoshi Yoshida
- LIXIL Corporation, 24F Osaki Garden Tower, 1-1-1, Nishi-shinagawa, Shinagawa-ku, Tokyo, 141-0033, Japan
| | - Risa Ishizaki
- LIXIL Corporation, 24F Osaki Garden Tower, 1-1-1, Nishi-shinagawa, Shinagawa-ku, Tokyo, 141-0033, Japan
| | - Eiji Yamamoto
- LIXIL Corporation, 24F Osaki Garden Tower, 1-1-1, Nishi-shinagawa, Shinagawa-ku, Tokyo, 141-0033, Japan
| | - Naoko Takahashi
- LIXIL Corporation, 24F Osaki Garden Tower, 1-1-1, Nishi-shinagawa, Shinagawa-ku, Tokyo, 141-0033, Japan
| | - Atsushi Iwamae
- Faculty of Architecture, Kindai University, 3-4-1 Kowakae, Higashiosaka, Osaka, 577-8502, Japan
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17
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He Y, Wang Z, Zhang H, Lai X, Liu M, Yang L, Zheng Y, He M, Kong W, Zhang X. Polygenic Risk Score Modifies the Association of HbA1c With Hearing Loss in Middle-Aged and Older Chinese Individuals: The Dongfeng-Tongji Cohort. Diabetes Care 2024; 47:1186-1193. [PMID: 38728232 PMCID: PMC11208759 DOI: 10.2337/dc23-2341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 04/14/2024] [Indexed: 05/12/2024]
Abstract
OBJECTIVE Evidence regarding the modifying effect of the polygenic risk score (PRS) on the associations between glycemic traits and hearing loss (HL) was lacking. We aimed to examine whether these associations can be influenced by genetic susceptibility. RESEARCH DESIGN AND METHODS This cross-sectional study included 13,275 participants aged 64.9 years from the Dongfeng-Tongji cohort. HL was defined according to a pure tone average >25 dB in the better ear and further classified by severity. Prediabetes and type 2 diabetes (T2D) were defined based on the 2013 criteria from the American Diabetes Association. A PRS was derived from 37 single nucleotide polymorphisms associated with HL. Multivariable logistic regression models were fitted to estimate the associations of PRS and glycemic traits with HL and its severity. RESULTS Elevated fasting plasma glucose (FPG), glycosylated hemoglobin (HbA1c), and T2D were positively associated with higher HL risks and its severity, with odds ratios (ORs) ranging from 1.04 (95% CI 1.00, 1.08) to 1.25 (95% CI 1.06, 1.46). We also found significant interaction between HbA1c and PRS on risks of overall HL and its severity (P for multiplicative interaction <0.05), and the effects of HbA1c on HL risks were significant only in the group with high PRS. Additionally, compared with normoglycemia in the group with low PRS, T2D was associated with an OR of up to 2.00 and 2.40 for overall HL and moderate to severe HL, respectively, in the group with high PRS (P for additive interaction <0.05). CONCLUSIONS PRS modifies the association of HbA1c with HL prevalence among middle-aged and older Chinese individuals.
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Affiliation(s)
- Yaling He
- Department of Occupational and Environmental Health, Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Zhichao Wang
- Department of Otorhinolaryngology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Haiqing Zhang
- Department of Occupational and Environmental Health, Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xuefeng Lai
- Department of Occupational and Environmental Health, Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Miao Liu
- Department of Occupational and Environmental Health, Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Liangle Yang
- Department of Occupational and Environmental Health, Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yiquan Zheng
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Meian He
- Department of Occupational and Environmental Health, Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Weijia Kong
- Department of Otorhinolaryngology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xiaomin Zhang
- Department of Occupational and Environmental Health, Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
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18
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Li X, Zhou Z, Ma Y, Ding K, Xiao H, Chen D, Liu N. Shared Genetic Architectures between Coronary Artery Disease and Type 2 Diabetes Mellitus in East Asian and European Populations. Biomedicines 2024; 12:1243. [PMID: 38927450 PMCID: PMC11201280 DOI: 10.3390/biomedicines12061243] [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: 03/25/2024] [Revised: 05/23/2024] [Accepted: 05/29/2024] [Indexed: 06/28/2024] Open
Abstract
Coronary artery disease (CAD) is a common comorbidity of type 2 diabetes mellitus (T2DM). However, the pathophysiology connecting these two phenotypes remains to be further understood. Combined analysis in multi-ethnic populations can help contribute to deepening our understanding of biological mechanisms caused by shared genetic loci. We applied genetic correlation analysis and then performed conditional and joint association analyses in Chinese, Japanese, and European populations to identify the genetic variants jointly associated with CAD and T2DM. Next, the associations between genes and the two traits were also explored. Finally, fine-mapping and functional enrichment analysis were employed to identify the potential causal variants and pathways. Genetic correlation results indicated significant genetic overlap between CAD and T2DM in the three populations. Over 10,000 shared signals were identified, and 587 were shared by East Asian and European populations. Fifty-six novel shared genes were found to have significant effects on both CAD and T2DM. Most loci were fine-mapped to plausible causal variant sets. Several similarities and differences of the involved genes in GO terms and KEGG pathways were revealed across East Asian and European populations. These findings highlight the importance of immunoregulation, neuroregulation, heart development, and the regulation of glucose metabolism in shared etiological mechanisms between CAD and T2DM.
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Affiliation(s)
- Xiaoyi Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; (X.L.); (Z.Z.); (Y.M.); (K.D.); (H.X.)
| | - Zechen Zhou
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; (X.L.); (Z.Z.); (Y.M.); (K.D.); (H.X.)
| | - Yujia Ma
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; (X.L.); (Z.Z.); (Y.M.); (K.D.); (H.X.)
| | - Kexin Ding
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; (X.L.); (Z.Z.); (Y.M.); (K.D.); (H.X.)
| | - Han Xiao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; (X.L.); (Z.Z.); (Y.M.); (K.D.); (H.X.)
| | - Dafang Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; (X.L.); (Z.Z.); (Y.M.); (K.D.); (H.X.)
| | - Na Liu
- Department of Neurology, Peking University Third Hospital, Beijing 100191, China
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19
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Chen S, Zhang M, Zhang W, Shao X, Yang X, Yang Z, Nan K. The Causal Association Between Blood Lead and Sleep Disorders: Evidence from National Health and Nutrition Examination Survey and Mendelian Randomization Analysis. J Epidemiol Glob Health 2024; 14:462-469. [PMID: 38372894 PMCID: PMC11176123 DOI: 10.1007/s44197-024-00199-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 01/22/2024] [Indexed: 02/20/2024] Open
Abstract
BACKGROUND Poor sleep quality is a global public health concern. This study aimed to identify the risk factors for sleep disorders and clarify their causal effects. METHODS Data were obtained from the National Health and Nutrition Examination Survey (NHANES) and Mendelian randomization (MR)-Base databases. Baseline characteristics of individuals with and without sleep disorders were compared. A multivariate logistic regression analysis was performed to calculate the effects of each variable on sleep disorders. Causal effects of blood lead levels and hypertension on sleep disorders were assessed using MR analysis. RESULTS In total, 3660 individuals were enrolled in the study. The prevalence of self-reported sleep disorders was 26.21%. Serum lead level, serum mercury level, serum retinol level, prevalence of hypertension, and daily vigorous work duration were significantly higher for those in the sleep disorders group than the control group. After adjusting for various covariates, the effects of serum lead and hypertension on sleep disorders were stable from logistic regression models 1-4. MR analysis showed that blood lead levels were causally related to the risk of sleep disorders (odds ratio (OR) = 1.09, 95% confidence interval (CI) 1.01-1.17, P = 0.030). There was no causal link between elevated blood pressure and sleep disorders (OR = 0.99, 95% CI 0.94-1.04, P = 0.757). Goodness-of-fit tests and sensitivity analyses were used to verify the reliability of the results. CONCLUSIONS Blood lead is positively and causally associated with an increased risk of sleep disorders. These findings provide a novel perspective regarding sleep protection. Taking effective measures to reduce lead exposure may significantly improve sleep health.
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Affiliation(s)
- Shengnan Chen
- Department of Joint Surgery, HongHui Hospital, Xi'an Jiaotong University, Xi'an, 710054, Shaanxi, China
- Medical Department, Xi'an Jiaotong University, Xi'an, 710048, Shaanxi, China
| | - Ming Zhang
- Department of General Practice, Honghui Hospital, Xi'an Jiaotong University, Xi'an, 710054, Shaanxi, China
| | - Weisong Zhang
- Department of Joint Surgery, HongHui Hospital, Xi'an Jiaotong University, Xi'an, 710054, Shaanxi, China
| | - Xiaolong Shao
- Department of Joint Surgery, HongHui Hospital, Xi'an Jiaotong University, Xi'an, 710054, Shaanxi, China
| | - Xiaobin Yang
- Hongdong County Hospital of Traditional Chinese Medicine, Hongdong, 041600, Shaanxi, China
| | - Zhi Yang
- Department of Joint Surgery, HongHui Hospital, Xi'an Jiaotong University, Xi'an, 710054, Shaanxi, China.
| | - Kai Nan
- Department of Joint Surgery, HongHui Hospital, Xi'an Jiaotong University, Xi'an, 710054, Shaanxi, China.
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Keaton JM, Kamali Z, Xie T, Vaez A, Williams A, Goleva SB, Ani A, Evangelou E, Hellwege JN, Yengo L, Young WJ, Traylor M, Giri A, Zheng Z, Zeng J, Chasman DI, Morris AP, Caulfield MJ, Hwang SJ, Kooner JS, Conen D, Attia JR, Morrison AC, Loos RJF, Kristiansson K, Schmidt R, Hicks AA, Pramstaller PP, Nelson CP, Samani NJ, Risch L, Gyllensten U, Melander O, Riese H, Wilson JF, Campbell H, Rich SS, Psaty BM, Lu Y, Rotter JI, Guo X, Rice KM, Vollenweider P, Sundström J, Langenberg C, Tobin MD, Giedraitis V, Luan J, Tuomilehto J, Kutalik Z, Ripatti S, Salomaa V, Girotto G, Trompet S, Jukema JW, van der Harst P, Ridker PM, Giulianini F, Vitart V, Goel A, Watkins H, Harris SE, Deary IJ, van der Most PJ, Oldehinkel AJ, Keavney BD, Hayward C, Campbell A, Boehnke M, Scott LJ, Boutin T, Mamasoula C, Järvelin MR, Peters A, Gieger C, Lakatta EG, Cucca F, Hui J, Knekt P, Enroth S, De Borst MH, Polašek O, Concas MP, Catamo E, Cocca M, Li-Gao R, Hofer E, Schmidt H, Spedicati B, Waldenberger M, Strachan DP, Laan M, Teumer A, Dörr M, Gudnason V, Cook JP, Ruggiero D, Kolcic I, Boerwinkle E, Traglia M, et alKeaton JM, Kamali Z, Xie T, Vaez A, Williams A, Goleva SB, Ani A, Evangelou E, Hellwege JN, Yengo L, Young WJ, Traylor M, Giri A, Zheng Z, Zeng J, Chasman DI, Morris AP, Caulfield MJ, Hwang SJ, Kooner JS, Conen D, Attia JR, Morrison AC, Loos RJF, Kristiansson K, Schmidt R, Hicks AA, Pramstaller PP, Nelson CP, Samani NJ, Risch L, Gyllensten U, Melander O, Riese H, Wilson JF, Campbell H, Rich SS, Psaty BM, Lu Y, Rotter JI, Guo X, Rice KM, Vollenweider P, Sundström J, Langenberg C, Tobin MD, Giedraitis V, Luan J, Tuomilehto J, Kutalik Z, Ripatti S, Salomaa V, Girotto G, Trompet S, Jukema JW, van der Harst P, Ridker PM, Giulianini F, Vitart V, Goel A, Watkins H, Harris SE, Deary IJ, van der Most PJ, Oldehinkel AJ, Keavney BD, Hayward C, Campbell A, Boehnke M, Scott LJ, Boutin T, Mamasoula C, Järvelin MR, Peters A, Gieger C, Lakatta EG, Cucca F, Hui J, Knekt P, Enroth S, De Borst MH, Polašek O, Concas MP, Catamo E, Cocca M, Li-Gao R, Hofer E, Schmidt H, Spedicati B, Waldenberger M, Strachan DP, Laan M, Teumer A, Dörr M, Gudnason V, Cook JP, Ruggiero D, Kolcic I, Boerwinkle E, Traglia M, Lehtimäki T, Raitakari OT, Johnson AD, Newton-Cheh C, Brown MJ, Dominiczak AF, Sever PJ, Poulter N, Chambers JC, Elosua R, Siscovick D, Esko T, Metspalu A, Strawbridge RJ, Laakso M, Hamsten A, Hottenga JJ, de Geus E, Morris AD, Palmer CNA, Nolte IM, Milaneschi Y, Marten J, Wright A, Zeggini E, Howson JMM, O'Donnell CJ, Spector T, Nalls MA, Simonsick EM, Liu Y, van Duijn CM, Butterworth AS, Danesh JN, Menni C, Wareham NJ, Khaw KT, Sun YV, Wilson PWF, Cho K, Visscher PM, Denny JC, Levy D, Edwards TL, Munroe PB, Snieder H, Warren HR. Genome-wide analysis in over 1 million individuals of European ancestry yields improved polygenic risk scores for blood pressure traits. Nat Genet 2024; 56:778-791. [PMID: 38689001 PMCID: PMC11096100 DOI: 10.1038/s41588-024-01714-w] [Show More Authors] [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: 03/01/2022] [Accepted: 03/11/2024] [Indexed: 05/02/2024]
Abstract
Hypertension affects more than one billion people worldwide. Here we identify 113 novel loci, reporting a total of 2,103 independent genetic signals (P < 5 × 10-8) from the largest single-stage blood pressure (BP) genome-wide association study to date (n = 1,028,980 European individuals). These associations explain more than 60% of single nucleotide polymorphism-based BP heritability. Comparing top versus bottom deciles of polygenic risk scores (PRSs) reveals clinically meaningful differences in BP (16.9 mmHg systolic BP, 95% CI, 15.5-18.2 mmHg, P = 2.22 × 10-126) and more than a sevenfold higher odds of hypertension risk (odds ratio, 7.33; 95% CI, 5.54-9.70; P = 4.13 × 10-44) in an independent dataset. Adding PRS into hypertension-prediction models increased the area under the receiver operating characteristic curve (AUROC) from 0.791 (95% CI, 0.781-0.801) to 0.826 (95% CI, 0.817-0.836, ∆AUROC, 0.035, P = 1.98 × 10-34). We compare the 2,103 loci results in non-European ancestries and show significant PRS associations in a large African-American sample. Secondary analyses implicate 500 genes previously unreported for BP. Our study highlights the role of increasingly large genomic studies for precision health research.
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Affiliation(s)
- Jacob M Keaton
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Zoha Kamali
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
- Department of Bioinformatics, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Tian Xie
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Ahmad Vaez
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
- Department of Bioinformatics, Isfahan University of Medical Sciences, Isfahan, Iran.
| | - Ariel Williams
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Slavina B Goleva
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Alireza Ani
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
- Department of Bioinformatics, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Evangelos Evangelou
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece
- Department of Biomedical Research, Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology-Hellas, Ioannina, Greece
| | - Jacklyn N Hellwege
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville, TN, USA
| | - Loic Yengo
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - William J Young
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, UK
| | - Matthew Traylor
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Department of Genetics, Novo Nordisk Research Centre Oxford, Oxford, UK
| | - Ayush Giri
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Division of Quantitative Sciences, Department of Obstetrics and Gynecology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Zhili Zheng
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
- Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Jian Zeng
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Daniel I Chasman
- Division of Preventive Medicine Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Andrew P Morris
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, The University of Manchester, Manchester, UK
| | - Mark J Caulfield
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Shih-Jen Hwang
- Population Sciences Branch, NHLBI Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University, Boston, MA, USA
| | - Jaspal S Kooner
- National Heart and Lung Institute, Imperial College London, London, UK
| | - David Conen
- Population Health Research Institute, McMaster University, Hamilton, Ontario, Canada
| | - John R Attia
- Faculty of Health and Medicine, University of Newcastle, New Lambton Heights, Newcastle, New South Wales, Australia
| | - 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
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Kati Kristiansson
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | | | - Andrew A Hicks
- Institute for Biomedicine, Eurac Research, Bolzano, Italy
- University of Lübeck, Lübeck, Germany
| | - Peter P Pramstaller
- Institute for Biomedicine, Eurac Research, Bolzano, Italy
- University of Lübeck, Lübeck, Germany
| | - Christopher P Nelson
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
| | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
| | - Lorenz Risch
- Faculty of Medical Sciences, Private University of the Principality of Liechtenstein, Triesen, Liechtenstein
- Department of Laboratory Medicine, Dr. Risch Anstalt, Vaduz, Liechtenstein
| | - Ulf Gyllensten
- Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Olle Melander
- Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
- Department of Internal Medicine, Skåne University Hospital, Malmö, Sweden
| | - Harriette Riese
- Interdisciplinary Center Psychopathology and Emotional Regulation (ICPE), Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - James F Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, Scotland
| | - Harry Campbell
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Yingchang Lu
- Vanderbilt Genetic Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, 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
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Kenneth M Rice
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Peter Vollenweider
- Department of Medicine, Internal Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Johan Sundström
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
- The George Institute for Global Health, University of New South Wales, Sydney, New South Wales, Australia
| | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
- Computational Medicine, Berlin Institute of Health (BIH) at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - Martin D Tobin
- Department of Health Sciences, University of Leicester, Leicester, UK
- Leicester NIHR Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Vilmantas Giedraitis
- Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden
| | - Jian'an Luan
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Jaakko Tuomilehto
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Zoltan Kutalik
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Veikko Salomaa
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Giorgia Girotto
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy
- Institute for Maternal and Child Health - IRCCS, Burlo Garofolo, Trieste, Italy
| | - Stella Trompet
- Department Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
- Department of Cardiology, 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
| | - Pim van der Harst
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, Utrecht, the Netherlands
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Paul M Ridker
- Division of Preventive Medicine Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Franco Giulianini
- Division of Preventive Medicine Brigham and Women's Hospital, Boston, MA, USA
| | - Veronique Vitart
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, Scotland
| | - Anuj Goel
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Hugh Watkins
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Sarah E Harris
- Lothian Birth Cohorts Group, Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Ian J Deary
- Lothian Birth Cohorts Group, Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Peter J van der Most
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Albertine J Oldehinkel
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Bernard D Keavney
- Division of Cardiovascular Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
- Manchester Heart Institute, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, Scotland
- Centre for Genomic and Experimental Medicine, IGC, University of Edinburgh, Edinburgh, UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, IGC, University of Edinburgh, Edinburgh, UK
- Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Michael Boehnke
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Laura J Scott
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Thibaud Boutin
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, Scotland
| | | | - Marjo-Riitta Järvelin
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Unit of Primary Health Care, Oulu University Hospital, OYS, Oulu, Finland
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Lehrstuhl für Epidemiologie, Institut für Medizinische Informationsverarbeitung, Biometrie und Epidemiologie (IBE), Ludwig-Maximilians-Universität München, Neuherberg, Germany
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Edward G Lakatta
- Laboratory of Cardiovascular Science, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Francesco Cucca
- Institute of Genetic and Biomedical Research, National Research Council (CNR), Monserrato, Italy
| | - Jennie Hui
- Busselton Population Medical Research Institute, Perth, Western Australia, Australia
- School of Population and Global Health, The University of Western Australia, Nedlands, Western Australia, Australia
| | - Paul Knekt
- Population Health Unit, Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Stefan Enroth
- Department of Immunology, Genetics, and Pathology, Biomedical Center, Science for Life Laboratory (SciLifeLab) Uppsala, Uppsala University, Uppsala, Sweden
| | - Martin H De Borst
- Department of Medicine, Division of Nephrology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Ozren Polašek
- University of Split School of Medicine, Split, Croatia
- Algebra University College, Zagreb, Croatia
| | - Maria Pina Concas
- Institute for Maternal and Child Health - IRCCS, Burlo Garofolo, Trieste, Italy
| | - Eulalia Catamo
- Institute for Maternal and Child Health - IRCCS, Burlo Garofolo, Trieste, Italy
| | - Massimiliano Cocca
- Institute for Maternal and Child Health - IRCCS, Burlo Garofolo, Trieste, Italy
| | - Ruifang Li-Gao
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Edith Hofer
- Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Graz, Austria
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria
| | - Helena Schmidt
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Medical University of Graz, Graz, Austria
| | - Beatrice Spedicati
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - David P Strachan
- Population Health Sciences Institute St George's, University of London, London, UK
| | - Maris Laan
- Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
| | - Marcus Dörr
- DZHK (German Center for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Kopavogur, Iceland
| | - James P Cook
- Department of Health Data Science, University of Liverpool, Liverpool, UK
| | - Daniela Ruggiero
- IRCCS Neuromed, Pozzilli, Italy
- Institute of Genetics and Biophysics - 'A. Buzzati-Traverso', National Research Council of Italy, Naples, Italy
| | - Ivana Kolcic
- Algebra University College, Zagreb, Croatia
- Department of Public Health, University of Split School of Medicine, Split, Croatia
| | - 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
| | - Michela Traglia
- Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milan, Italy
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Olli T Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Andrew D Johnson
- Population Sciences Branch, NHLBI Framingham Heart Study, Framingham, MA, USA
- The Framingham Heart Study, Framingham, MA, USA
| | - Christopher Newton-Cheh
- Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Morris J Brown
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Anna F Dominiczak
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Peter J Sever
- International Centre for Circulatory Health, Imperial College London, London, UK
| | - Neil Poulter
- School of Public Health, Imperial College London, London, UK
| | - John C Chambers
- Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Singapore
| | - Roberto Elosua
- Hospital del Mar Research Institute (IMIM), Barcelona, Spain
- CIBER Enfermedades Cardiovasculares (CIBERCV), Barcelona, Spain
- Faculty of Medicine, University of Vic-Central University of Catalonia (UVic-UCC), Vic, Spain
| | | | - Tõnu Esko
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | | | - Rona J Strawbridge
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
- Health Data Research UK, Glasgow, UK
- Division of Cardiovascular Medicine, Department of Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
- Kuopio University Hospital, Kuopio, Finland
| | - Anders Hamsten
- Division of Cardiovascular Medicine, Department of Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Faculty of Behavioural and Movement Sciences, Vrije Universiteit, Amsterdam, the Netherlands
| | - Eco de Geus
- Department of Biological Psychology, Faculty of Behavioural and Movement Sciences, Vrije Universiteit, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam University Medical Centre, Amsterdam, the Netherlands
| | - Andrew D Morris
- Data Science, University of Edinburgh, Edinburgh, UK
- Health Data Research UK, London, UK
| | - Colin N A Palmer
- Population Health and Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - Ilja M Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Yuri Milaneschi
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Jonathan Marten
- Centre for Genomic and Experimental Medicine, IGC, University of Edinburgh, Edinburgh, UK
| | - Alan Wright
- Centre for Genomic and Experimental Medicine, IGC, University of Edinburgh, Edinburgh, UK
| | - Eleftheria Zeggini
- Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Technical University of Munich (TUM) and Klinikum Rechts der Isar, TUM School of Medicine, Munich, Germany
| | - Joanna M M Howson
- Department of Genetics, Novo Nordisk Research Centre Oxford, Oxford, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Christopher J O'Donnell
- VA Boston Healthcare System, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Tim Spector
- Department of Twin Research, King's College London, London, UK
| | - Mike A Nalls
- Center for Alzheimer's and Related Dementias, NIA/NINDS, NIH, Bethesda, MD, USA
- Laboratory of Neurogenetics, NIA, NIH, Bethesda, MD, USA
- DataTecnica LLC, Washington, DC, USA
| | - Eleanor M Simonsick
- Intramural Research Program, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Yongmei Liu
- Division of Cardiology, Duke University School of Medicine, Durham, NC, USA
| | - Cornelia M van Duijn
- Nuffield Department of Population Health, Big Data Institute, University of Oxford, Oxford, UK
| | - Adam S Butterworth
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- National Institute for Health and Care Research Blood and Transplant Research Unit in Donor Health and Behaviour, University of Cambridge, Cambridge, UK
| | - John N Danesh
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- National Institute for Health and Care Research Blood and Transplant Research Unit in Donor Health and Behaviour, University of Cambridge, Cambridge, UK
- Department of Human Genetics, The Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Cristina Menni
- Department of Twin Research and Genetic Epidemiology, London, UK
| | | | - Kay-Tee Khaw
- Department of Public Health and Primary Care, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Yan V Sun
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, Georgia, USA
- VA Atlanta Healthcare System, Decatur, GA, USA
| | - Peter W F Wilson
- Emory Clinical Cardiovascular Research Institute, Atlanta, GA, USA
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Kelly Cho
- Division of Aging, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Cardiovascular Health Research Unit, Departments of Medicine and Epidemiology, University of Washington, Seattle, WA, USA
| | - Peter M Visscher
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Joshua C Denny
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Daniel Levy
- Population Sciences Branch, NHLBI Framingham Heart Study, Framingham, MA, USA
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Todd L Edwards
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
| | - Patricia B Munroe
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Helen R Warren
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
- NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
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21
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Momin MM, Zhou X, Hyppönen E, Benyamin B, Lee SH. Cross-ancestry genetic architecture and prediction for cholesterol traits. Hum Genet 2024; 143:635-648. [PMID: 38536467 DOI: 10.1007/s00439-024-02660-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 02/13/2024] [Indexed: 05/18/2024]
Abstract
While cholesterol is essential, a high level of cholesterol is associated with the risk of cardiovascular diseases. Genome-wide association studies (GWASs) have proven successful in identifying genetic variants that are linked to cholesterol levels, predominantly in white European populations. However, the extent to which genetic effects on cholesterol vary across different ancestries remains largely unexplored. Here, we estimate cross-ancestry genetic correlation to address questions on how genetic effects are shared across ancestries. We find significant genetic heterogeneity between ancestries for cholesterol traits. Furthermore, we demonstrate that single nucleotide polymorphisms (SNPs) with concordant effects across ancestries for cholesterol are more frequently found in regulatory regions compared to other genomic regions. Indeed, the positive genetic covariance between ancestries is mostly driven by the effects of the concordant SNPs, whereas the genetic heterogeneity is attributed to the discordant SNPs. We also show that the predictive ability of the concordant SNPs is significantly higher than the discordant SNPs in the cross-ancestry polygenic prediction. The list of concordant SNPs for cholesterol is available in GWAS Catalog. These findings have relevance for the understanding of shared genetic architecture across ancestries, contributing to the development of clinical strategies for polygenic prediction of cholesterol in cross-ancestral settings.
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Affiliation(s)
- Md Moksedul Momin
- Australian Centre for Precision Health, University of South Australia, Adelaide, SA, 5000, Australia.
- UniSA Allied Health and Human Performance, University of South Australia, Adelaide, SA, 5000, Australia.
- Department of Genetics and Animal Breeding, Faculty of Veterinary Medicine, Chattogram Veterinary and Animal Sciences University (CVASU), Khulshi, Chattogram, 4225, Bangladesh.
- South Australian Health and Medical Research Institute (SAHMRI), University of South Australia, Adelaide, SA, 5000, Australia.
| | - Xuan Zhou
- Australian Centre for Precision Health, University of South Australia, Adelaide, SA, 5000, Australia
- UniSA Allied Health and Human Performance, University of South Australia, Adelaide, SA, 5000, Australia
- South Australian Health and Medical Research Institute (SAHMRI), University of South Australia, Adelaide, SA, 5000, Australia
| | - Elina Hyppönen
- Australian Centre for Precision Health, University of South Australia, Adelaide, SA, 5000, Australia
- South Australian Health and Medical Research Institute (SAHMRI), University of South Australia, Adelaide, SA, 5000, Australia
- UniSA Clinical and Health Sciences, University of South Australia, Adelaide, SA, Australia
| | - Beben Benyamin
- Australian Centre for Precision Health, University of South Australia, Adelaide, SA, 5000, Australia
- UniSA Allied Health and Human Performance, University of South Australia, Adelaide, SA, 5000, Australia
- South Australian Health and Medical Research Institute (SAHMRI), University of South Australia, Adelaide, SA, 5000, Australia
| | - S Hong Lee
- Australian Centre for Precision Health, University of South Australia, Adelaide, SA, 5000, Australia.
- UniSA Allied Health and Human Performance, University of South Australia, Adelaide, SA, 5000, Australia.
- South Australian Health and Medical Research Institute (SAHMRI), University of South Australia, Adelaide, SA, 5000, Australia.
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22
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Yousof TR, Mejia-Benitez A, Morrison KM, Austin RC. Reduced plasma GDF10 levels are positively associated with cholesterol impairment and childhood obesity. Sci Rep 2024; 14:1805. [PMID: 38245533 PMCID: PMC10799949 DOI: 10.1038/s41598-024-51635-1] [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: 11/29/2023] [Accepted: 01/08/2024] [Indexed: 01/22/2024] Open
Abstract
Childhood obesity is a global health concern affecting over 150 million children worldwide, with projections of a rise to 206 million by 2025. Understanding the mechanisms underlying this epidemic is crucial for developing effective interventions. In this study, we investigated circulating levels of Growth Differentiation Factor 10 (GDF10), a novel regulator of adipogenesis. Previous studies report diminished circulating GDF10 levels contribute to obesity and hepatic steatosis in mice. To further understand the role of plasma GDF10 in childhood obesity, a prospective case-control study was conducted. Using an enzyme-linked immunosorbent assay, plasma GDF10 levels were measured in children aged 5-17 years of age with normal (n = 36) and increased (n = 56) body mass index (BMI). Subsequently, plasma GDF10 levels were compared to various cardio-metabolic parameters. Children with increased BMI exhibit significantly lower levels of plasma GDF10 compared to children with normal BMI (p < 0.05). This study not only supports previous mouse data but is the first to report that lower levels of GDF10 is associated with childhood obesity, providing an important human connection for the relevance of GDF10 in obesity. Furthermore, this study revealed a significant correlation between low plasma GDF10 levels and elevated LDL-cholesterol and total cholesterol levels dependent on BMI (95% CI, p < 0.05). This study supports the hypothesis that children with obesity display lower plasma levels of GDF10, which correlates with elevated cholesterol levels. These insights shed light on potential mechanisms contributing to childhood obesity and may lead to future therapeutic interventions targeting GDF10 to mitigate adverse effects of adipogenesis in cardiometabolic health.
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Affiliation(s)
- Tamana R Yousof
- Division of Nephrology, Department of Medicine, McMaster University and The Research Institute of St. Joe's Hamilton, Hamilton, ON, Canada
| | - Aurora Mejia-Benitez
- Division of Nephrology, Department of Medicine, McMaster University and The Research Institute of St. Joe's Hamilton, Hamilton, ON, Canada
| | - Katherine M Morrison
- Department of Pediatrics, Centre for Metabolism, Obesity and Diabetes Research, McMaster University, Hamilton, Canada
| | - Richard C Austin
- Division of Nephrology, Department of Medicine, McMaster University and The Research Institute of St. Joe's Hamilton, Hamilton, ON, Canada.
- Department of Pediatrics, Centre for Metabolism, Obesity and Diabetes Research, McMaster University, Hamilton, Canada.
- Division of Nephrology, Department of Medicine, McMaster University and The Research Institute of St. Joe's Hamilton, 50 Charlton Ave. E., Rm. T-3313, Hamilton, ON, L8N 4A6, Canada.
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23
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Chung RH, Chuang SY, Zhuang YS, Jhang YS, Huang TH, Li GH, Chang IS, Hsiung CA, Chiou HY. Evaluating polygenic risk scores for predicting cardiometabolic traits and disease risks in the Taiwan Biobank. HGG ADVANCES 2024; 5:100260. [PMID: 38053338 PMCID: PMC10777116 DOI: 10.1016/j.xhgg.2023.100260] [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: 08/07/2023] [Revised: 12/01/2023] [Accepted: 12/01/2023] [Indexed: 12/07/2023] Open
Abstract
Type 2 diabetes (T2D) and hypertension are common comorbidities and, along with hyperlipidemia, serve as risk factors for cardiovascular diseases. This study aimed to evaluate the predictive value of polygenic risk scores (PRSs) on cardiometabolic traits related to T2D, hypertension, and hyperlipidemia and the incidence of these three diseases in Taiwan Biobank samples. Using publicly available, large-scale genome-wide association studies summary statistics, we constructed cross-ethnic PRSs for T2D, hypertension, body mass index, and nine quantitative traits typically used to define the three diseases. A composite PRS (cPRS) for each of the nine traits was constructed by aggregating the significant PRSs of its genetically correlated traits. The associations of each of the nine traits at baseline as well as the change of trait values during a 3- to 6-year follow-up period with its cPRS were evaluated. The predictive performances of cPRSs in predicting future incidences of T2D, hypertension, and hyperlipidemia were assessed. The cPRSs had significant associations with baseline and changes of trait values in 3-6 years and explained a higher proportion of variance for all traits than individual PRSs. Furthermore, models incorporating disease-related cPRSs, along with clinical features and relevant trait measurements achieved area under the curve values of 87.8%, 83.7%, and 75.9% for predicting future T2D, hypertension, and hyperlipidemia in 3-6 years, respectively.
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Affiliation(s)
- Ren-Hua Chung
- Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan.
| | - Shao-Yuan Chuang
- Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan
| | - Yong-Sheng Zhuang
- Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan
| | - Yi-Syuan Jhang
- Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan
| | - Tsung-Hsien Huang
- Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan
| | - Guo-Hung Li
- Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan
| | - I-Shou Chang
- National Institute of Cancer Research, National Health Research Institutes, Zhunan, Taiwan
| | - Chao A Hsiung
- Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan
| | - Hung-Yi Chiou
- Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan; School of Public Health, College of Public Health, Taipei Medical University, Taipei, Taiwan
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24
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Ahles A, Engelhardt S. Genetic Variants of Adrenoceptors. Handb Exp Pharmacol 2024; 285:27-54. [PMID: 37578621 DOI: 10.1007/164_2023_676] [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] [Indexed: 08/15/2023]
Abstract
Adrenoceptors are class A G-protein-coupled receptors grouped into three families (α1-, α2-, and β-adrenoceptors), each one including three members. All nine corresponding adrenoceptor genes display genetic variation in their coding and adjacent non-coding genomic region. Coding variants, i.e., nucleotide exchanges within the transcribed and translated receptor sequence, may result in a difference in amino acid sequence thus altering receptor function and signaling. Such variants have been intensely studied in vitro in overexpression systems and addressed in candidate-gene studies for distinct clinical parameters. In recent years, large cohorts were analyzed in genome-wide association studies (GWAS), where variants are detected as significant in context with specific traits. These studies identified two of the in-depth characterized 18 coding variants in adrenoceptors as repeatedly statistically significant genetic risk factors - p.Arg389Gly in the β1- and p.Thr164Ile in the β2-adrenoceptor, along with 56 variants in the non-coding regions adjacent to the adrenoceptor gene loci, the functional role of which is largely unknown at present. This chapter summarizes current knowledge on the two coding variants in adrenoceptors that have been consistently validated in GWAS and provides a prospective overview on the numerous non-coding variants more recently attributed to adrenoceptor gene loci.
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Affiliation(s)
- Andrea Ahles
- Institute of Pharmacology and Toxicology, Technical University of Munich (TUM), Munich, Germany
| | - Stefan Engelhardt
- Institute of Pharmacology and Toxicology, Technical University of Munich (TUM), Munich, Germany.
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, Munich, Germany.
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25
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Ciofani JL, Han D, Allahwala UK, Woolf B, Gill D, Bhindi R. Lipids, Blood Pressure, and Diabetes Mellitus on Risk of Cardiovascular Diseases in East Asians: A Mendelian Randomization Study. Am J Cardiol 2023; 205:329-337. [PMID: 37633070 PMCID: PMC7615095 DOI: 10.1016/j.amjcard.2023.08.007] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 07/29/2023] [Accepted: 08/03/2023] [Indexed: 08/28/2023]
Abstract
Elevated blood pressure, dyslipidemia, and impaired glycemic control are well-established cardiovascular risk factors in Europeans, but there are comparatively few studies focused on East Asian populations. This study evaluated the potential causal relations between traditional cardiovascular risk factors and disease risk in East Asians through a 2-sample Mendelian randomization approach. We collected summary statistics for blood pressure parameters, lipid subsets, and type 2 diabetes mellitus liability from large genome-wide association study meta-analyses conducted in East Asians and Europeans. These were paired with summary statistics for ischemic heart disease (IHD), ischemic stroke (IS), peripheral vascular disease, heart failure (HF) and atrial fibrillation (AF). We performed univariable Mendelian randomization analyses for each exposure-outcome pair, followed by multivariable analyses for the available lipid subsets. The genetically predicted risk factors associated with IHD and AF were similar between East Asians and Europeans. However, in East Asians only genetically predicted elevated blood pressure was significantly associated with IS (odds ratio 1.05, 95% confidence interval 1.04 to 1.06, p <0.0001) and HF (odds ratio 1.05, 95% confidence interval 1.04 to 1.06, p <0.0001), whereas nearly all genetically predicted risk factors were significantly associated with IS and HF in Europeans. In conclusion, this study provides supportive evidence for similar causal relations between traditional cardiovascular risk factors and IHD and AF in both East Asian and European ancestry populations. However, the identified risk factors for IS and HF differed between East Asians and Europeans, potentially highlighting distinct disease etiologies between these populations.
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Affiliation(s)
- Jonathan L Ciofani
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom; Department of Cardiology, Royal North Shore Hospital, Sydney, New South Wales, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.
| | - Daniel Han
- Medical Research Council Laboratory of Molecular Biology, Cambridge, United Kingdom; Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, United Kingdom; School of Mathematics and Statistics, University of New South Wales, Sydney, New South Wales, Australia
| | - Usaid K Allahwala
- Department of Cardiology, Royal North Shore Hospital, Sydney, New South Wales, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Benjamin Woolf
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom; School of Psychological Science, University of Bristol, Bristol, United Kingdom; Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom; Chief Scientific Advisor Office, Novo Nordisk, Copenhagen, Denmark
| | - Ravinay Bhindi
- Department of Cardiology, Royal North Shore Hospital, Sydney, New South Wales, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
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26
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Kononov SI, Azarova YE, Klyosova EY, Bykanova MA, Solodilova MA, Polonikov AV. The Protective Effect of Polymorphisms rs2681472 and rs17249754 of the ATP2B1 Gene Against Coronary Artery Disease and Hypertension is Abolished by Tobacco Smoking. KARDIOLOGIIA 2023; 63:45-50. [PMID: 37815139 DOI: 10.18087/cardio.2023.9.n2252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 09/16/2022] [Indexed: 10/11/2023]
Abstract
Aim To study the relationship of single nucleotide polymorphisms rs2681472 and rs17249754 in the ATP2B1 gene with risk of ischemic heart disease (IHD) and arterial hypertension (AH) among residents of Central Russia and to evaluate the trigger role of smoking as a risk factor for development of IHD and AH in carriers of ATP2B1 gene polymorphic variants.Material and methods The study included DNA samples from 1960 residents of Central Russia of Slavic origin. Among them, there were 1261 patients with cardiovascular diseases and 699 healthy persons. The vast majority of patients had both IHD and AH. Genotyping was performed using the iPLEX technique on a MassARRAY-4 genomic mass-spectrometer. The relationship of ATP2B1 alleles, genotypes, and haplotypes with the risk of diseases was calculated by logistic regression analysis with adjustments for sex and age.Results Carriage of AG and GG (rs2681472) genotypes and GA (rs17249754) genotype was associated with a reduced risk of both IHD (p=0.0057 and p=0.022 for rs2681472 and rs17249754, respectively) and AH (p=0.016 and p=0.036, respectively). Rare rs2681472G-rs17249754G and rs2681472A-rs17249754A haplotypes were associated with a reduced risk of IHD (odds ratio, OR, 0.22; 95 % CI: 0.11-0.46, p=0.0001) and AH (OR, 0.22; 95 % CI: 0.10-0.47, p=0.0001). Analysis of the groups stratified by the smoking status showed that in smokers, the studied polymorphic variants did not have a protective action with respect of either IHD or AH. However, in non-smokers, the genotypes AG and GG rs2681472 (OR, 0.62; 95 % CI: 0.47-0.80, p=0.0004) and GA rs17249754 (OR, 0.61; 95 % CI: 0.47-0.81, p=0.0004) were associated with a reduced risk of IHD and AH (OR, 0.63; 95 % CI: 0.48-0.83, p=0.0004 for rs2681472; OR, 0.63; 95 % CI: 0.48-0.83, p=0.001 for rs17249754), as well as the carriage of the minor alleles rs2681472‑G and rs17249754‑A.Conclusion It was shown for the first time that the polymorphic variants rs17249754 and rs2681472 of the ATP2B1 gene are associated with a reduced risk for IHD and AH only in non-smokers.
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27
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Walters RG, Millwood IY, Lin K, Schmidt Valle D, McDonnell P, Hacker A, Avery D, Edris A, Fry H, Cai N, Kretzschmar WW, Ansari MA, Lyons PA, Collins R, Donnelly P, Hill M, Peto R, Shen H, Jin X, Nie C, Xu X, Guo Y, Yu C, Lv J, Clarke RJ, Li L, Chen Z, China Kadoorie Biobank Collaborative Group. Genotyping and population characteristics of the China Kadoorie Biobank. CELL GENOMICS 2023; 3:100361. [PMID: 37601966 PMCID: PMC10435379 DOI: 10.1016/j.xgen.2023.100361] [Citation(s) in RCA: 46] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 02/09/2023] [Accepted: 06/24/2023] [Indexed: 08/22/2023]
Abstract
The China Kadoorie Biobank (CKB) is a population-based prospective cohort of >512,000 adults recruited from 2004 to 2008 from 10 geographically diverse regions across China. Detailed data from questionnaires and physical measurements were collected at baseline, with additional measurements at three resurveys involving ∼5% of surviving participants. Analyses of genome-wide genotyping, for >100,000 participants using custom-designed Axiom arrays, reveal extensive relatedness, recent consanguinity, and signatures reflecting large-scale population movements from recent Chinese history. Systematic genome-wide association studies of incident disease, captured through electronic linkage to death and disease registries and to the national health insurance system, replicate established disease loci and identify 14 novel disease associations. Together with studies of candidate drug targets and disease risk factors and contributions to international genetics consortia, these demonstrate the breadth, depth, and quality of the CKB data. Ongoing high-throughput omics assays of collected biosamples and planned whole-genome sequencing will further enhance the scientific value of this biobank.
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Affiliation(s)
- Robin G. Walters
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- MRC Population Health Research Unit, University of Oxford, Oxford OX3 7LF, UK
| | - Iona Y. Millwood
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- MRC Population Health Research Unit, University of Oxford, Oxford OX3 7LF, UK
| | - Kuang Lin
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Dan Schmidt Valle
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Pandora McDonnell
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Alex Hacker
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Daniel Avery
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Ahmed Edris
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Hannah Fry
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Na Cai
- Wellcome Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | | | - M. Azim Ansari
- Nuffield Department of Medicine, Oxford University, Oxford OX1 3SY, UK
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford OX3 9DU, UK
| | - Paul A. Lyons
- Cambridge Institute for Therapeutic Immunology and Infectious Disease, University of Cambridge, Cambridge CB2 0AW, UK
- Department of Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Rory Collins
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Peter Donnelly
- Wellcome Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Michael Hill
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- MRC Population Health Research Unit, University of Oxford, Oxford OX3 7LF, UK
| | - Richard Peto
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Hongbing Shen
- Department of Epidemiology, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing 211116, China
| | - Xin Jin
- BGI-Shenzhen, Shenzhen 518083, China
| | - Chao Nie
- BGI-Shenzhen, Shenzhen 518083, China
| | - Xun Xu
- BGI-Shenzhen, Shenzhen 518083, China
| | - Yu Guo
- Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing 100037, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
- Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing 100191, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
- Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing 100191, China
| | - Robert J. Clarke
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
- Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing 100191, China
| | - Zhengming Chen
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- MRC Population Health Research Unit, University of Oxford, Oxford OX3 7LF, UK
| | - China Kadoorie Biobank Collaborative Group
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- MRC Population Health Research Unit, University of Oxford, Oxford OX3 7LF, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
- Nuffield Department of Medicine, Oxford University, Oxford OX1 3SY, UK
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford OX3 9DU, UK
- Cambridge Institute for Therapeutic Immunology and Infectious Disease, University of Cambridge, Cambridge CB2 0AW, UK
- Department of Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
- Department of Epidemiology, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing 211116, China
- BGI-Shenzhen, Shenzhen 518083, China
- Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing 100037, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
- Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing 100191, China
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28
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Oliveros W, Delfosse K, Lato DF, Kiriakopulos K, Mokhtaridoost M, Said A, McMurray BJ, Browning JW, Mattioli K, Meng G, Ellis J, Mital S, Melé M, Maass PG. Systematic characterization of regulatory variants of blood pressure genes. CELL GENOMICS 2023; 3:100330. [PMID: 37492106 PMCID: PMC10363820 DOI: 10.1016/j.xgen.2023.100330] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 03/29/2023] [Accepted: 04/28/2023] [Indexed: 07/27/2023]
Abstract
High blood pressure (BP) is the major risk factor for cardiovascular disease. Genome-wide association studies have identified genetic variants for BP, but functional insights into causality and related molecular mechanisms lag behind. We functionally characterize 4,608 genetic variants in linkage with 135 BP loci in vascular smooth muscle cells and cardiomyocytes by massively parallel reporter assays. High densities of regulatory variants at BP loci (i.e., ULK4, MAP4, CFDP1, PDE5A) indicate that multiple variants drive genetic association. Regulatory variants are enriched in repeats, alter cardiovascular-related transcription factor motifs, and spatially converge with genes controlling specific cardiovascular pathways. Using heuristic scoring, we define likely causal variants, and CRISPR prime editing finally determines causal variants for KCNK9, SFXN2, and PCGF6, which are candidates for developing high BP. Our systems-level approach provides a catalog of functionally relevant variants and their genomic architecture in two trait-relevant cell lines for a better understanding of BP gene regulation.
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Affiliation(s)
- Winona Oliveros
- Life Sciences Department, Barcelona Supercomputing Center, 08034 Barcelona, Catalonia, Spain
| | - Kate Delfosse
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Daniella F. Lato
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Katerina Kiriakopulos
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Milad Mokhtaridoost
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Abdelrahman Said
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Brandon J. McMurray
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Jared W.L. Browning
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Kaia Mattioli
- Division of Genetics, Department of Medicine, Brigham & Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Guoliang Meng
- Developmental and Stem Cell Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - James Ellis
- Developmental and Stem Cell Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Seema Mital
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
- Ted Rogers Centre for Heart Research, Toronto, ON M5G 1X8, Canada
- Department of Pediatrics, The Hospital for Sick Children, University of Toronto, Toronto, ON M5G 0A4, Canada
| | - Marta Melé
- Life Sciences Department, Barcelona Supercomputing Center, 08034 Barcelona, Catalonia, Spain
| | - Philipp G. Maass
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
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29
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Zhao B, Li T, Fan Z, Yang Y, Shu J, Yang X, Wang X, Luo T, Tang J, Xiong D, Wu Z, Li B, Chen J, Shan Y, Tomlinson C, Zhu Z, Li Y, Stein JL, Zhu H. Heart-brain connections: Phenotypic and genetic insights from magnetic resonance images. Science 2023; 380:abn6598. [PMID: 37262162 PMCID: PMC11987082 DOI: 10.1126/science.abn6598] [Citation(s) in RCA: 84] [Impact Index Per Article: 42.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 04/11/2023] [Indexed: 06/03/2023]
Abstract
Cardiovascular health interacts with cognitive and mental health in complex ways, yet little is known about the phenotypic and genetic links of heart-brain systems. We quantified heart-brain connections using multiorgan magnetic resonance imaging (MRI) data from more than 40,000 subjects. Heart MRI traits displayed numerous association patterns with brain gray matter morphometry, white matter microstructure, and functional networks. We identified 80 associated genomic loci (P < 6.09 × 10-10) for heart MRI traits, which shared genetic influences with cardiovascular and brain diseases. Genetic correlations were observed between heart MRI traits and brain-related traits and disorders. Mendelian randomization suggests that heart conditions may causally contribute to brain disorders. Our results advance a multiorgan perspective on human health by revealing heart-brain connections and shared genetic influences.
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Affiliation(s)
- Bingxin Zhao
- Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA
| | - Tengfei Li
- Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Zirui Fan
- Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA
| | - Yue Yang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Juan Shu
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA
| | - Xiaochen Yang
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA
| | - Xifeng Wang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Tianyou Luo
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jiarui Tang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Di Xiong
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Zhenyi Wu
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA
| | - Bingxuan Li
- Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA
| | - Jie Chen
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Yue Shan
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Chalmer Tomlinson
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Ziliang Zhu
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jason L. Stein
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Hongtu Zhu
- Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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30
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Ivanova T, Churnosova M, Abramova M, Ponomarenko I, Reshetnikov E, Aristova I, Sorokina I, Churnosov M. Risk Effects of rs1799945 Polymorphism of the HFE Gene and Intergenic Interactions of GWAS-Significant Loci for Arterial Hypertension in the Caucasian Population of Central Russia. Int J Mol Sci 2023; 24:ijms24098309. [PMID: 37176017 PMCID: PMC10179076 DOI: 10.3390/ijms24098309] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2023] [Revised: 04/24/2023] [Accepted: 04/25/2023] [Indexed: 05/15/2023] Open
Abstract
The aim of this case-control replicative study was to investigate the link between GWAS-impact for arterial hypertension (AH) and/or blood pressure (BP) gene polymorphisms and AH risk in Russian subjects (Caucasian population of Central Russia). AH (n = 939) and control (n = 466) cohorts were examined for ten GWAS AH/BP risk loci. The genotypes/alleles of these SNP and their combinations (SNP-SNP interactions) were tested for their association with the AH development using a logistic regression statistical procedure. The genotype GG of the SNP rs1799945 (C/G) HFE was strongly linked with an increased AH risk (ORrecGG = 2.53; 95%CIrecGG1.03-6.23; ppermGG = 0.045). The seven SNPs such as rs1173771 (G/A) AC026703.1, rs1799945 (C/G) HFE, rs805303 (G/A) BAG6, rs932764 (A/G) PLCE1, rs4387287 (C/A) OBFC1, rs7302981 (G/A) CERS5, rs167479 (T/G) RGL3, out of ten regarded loci, were related with AH within eight SNP-SNP interaction models (<0.001 ≤ pperm-interaction ≤ 0.047). Three polymorphisms such as rs8068318 (T/C) TBX2, rs633185 (C/G) ARHGAP42, and rs2681472 (A/G) ATP2B1 were not linked with AH. The pairwise rs805303 (G/A) BAG6-rs7302981 (G/A) CERS5 combination was a priority in determining the susceptibility to AH (included in six out of eight SNP-SNP interaction models [75%] and described 0.82% AH entropy). AH-associated variants are conjecturally functional for 101 genes involved in processes related to the immune system (major histocompatibility complex protein, processing/presentation of antigens, immune system process regulation, etc.). In conclusion, the rs1799945 polymorphism of the HFE gene and intergenic interactions of BAG6, CERS5, AC026703.1, HFE, PLCE1, OBFC1, RGL3 have been linked with AH risky in the Caucasian population of Central Russia.
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Affiliation(s)
- Tatiana Ivanova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Maria Churnosova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Maria Abramova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Irina Ponomarenko
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Evgeny Reshetnikov
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Inna Aristova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Inna Sorokina
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Mikhail Churnosov
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
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31
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Zucker R, Kovalerchik M, Linial M. Gene-based association study reveals a distinct female genetic signal in primary hypertension. Hum Genet 2023:10.1007/s00439-023-02567-9. [PMID: 37133573 DOI: 10.1007/s00439-023-02567-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 04/25/2023] [Indexed: 05/04/2023]
Abstract
Hypertension is a polygenic disease that affects over 1.2 billion adults aged 30-79 worldwide. It is a major risk factor for renal, cerebrovascular, and cardiovascular diseases. The heritability of hypertension is estimated to be high; nevertheless, our understanding of its underlying mechanisms remains scarce and incomplete. This study covered the entries from European ancestry from the UK-Biobank (UKB), with 74,090 cases diagnosed with essential (primary) hypertension and 200,734 controls. We compared the findings from large-scale genome-wide association studies (GWAS) to the gene-based method of proteome-wide association studies (PWAS). We focused on 70 statistically significant associated genes, most of which failed to reach significance in variant-based GWAS. A total of 30% of the PWAS-associated genes were validated against independent cohorts, including the Finnish Biobank. Furthermore, gene-based analyses that were performed on both sexes revealed sex-dependent genetics with a stronger genetic component associated with females. Analysis of systolic and diastolic blood pressure measurements confirms a strong genetic effect associated with females. We demonstrated that gene-based approaches provide insight into the underlying biology of hypertension. Specifically, the expression profiles of the identified genes exposed the enrichment of endothelial cells from multiple organs. Furthermore, females' top-ranked significant genes are involved in cellular immunity. We conclude that studying hypertension and blood pressure via gene-based association methods improves interpretability and exposes sex-dependent genetic effects, which enhances clinical utility.
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Affiliation(s)
- Roei Zucker
- The Rachel and Selim Benin School of Computer Science and Engineering, The Hebrew University of Jerusalem, 91904, Jerusalem, Israel
| | - Michael Kovalerchik
- The Rachel and Selim Benin School of Computer Science and Engineering, The Hebrew University of Jerusalem, 91904, Jerusalem, Israel
| | - Michal Linial
- Department of Biological Chemistry, Institute of Life Sciences, The Hebrew University of Jerusalem, 91904, Jerusalem, Israel.
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32
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Ivanova T, Churnosova M, Abramova M, Plotnikov D, Ponomarenko I, Reshetnikov E, Aristova I, Sorokina I, Churnosov M. Sex-Specific Features of the Correlation between GWAS-Noticeable Polymorphisms and Hypertension in Europeans of Russia. Int J Mol Sci 2023; 24:ijms24097799. [PMID: 37175507 PMCID: PMC10178435 DOI: 10.3390/ijms24097799] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2023] [Revised: 04/13/2023] [Accepted: 04/20/2023] [Indexed: 05/15/2023] Open
Abstract
The aim of the study was directed at studying the sex-specific features of the correlation between genome-wide association studies (GWAS)-noticeable polymorphisms and hypertension (HTN). In two groups of European subjects of Russia (n = 1405 in total), such as men (n = 821 in total: n = 564 HTN, n = 257 control) and women (n = 584 in total: n = 375 HTN, n = 209 control), the distribution of ten specially selected polymorphisms (they have confirmed associations of GWAS level with blood pressure (BP) parameters and/or HTN in Europeans) has been considered. The list of studied loci was as follows: (PLCE1) rs932764 A > G, (AC026703.1) rs1173771 G > A, (CERS5) rs7302981 G > A, (HFE) rs1799945 C > G, (OBFC1) rs4387287 C > A, (BAG6) rs805303 G > A, (RGL3) rs167479 T > G, (ARHGAP42) rs633185 C > G, (TBX2) rs8068318 T > C, and (ATP2B1) rs2681472 A > G. The contribution of individual loci and their inter-locus interactions to the HTN susceptibility with bioinformatic interpretation of associative links was evaluated separately in men's and women's cohorts. The men-women differences in involvement in the disease of the BP/HTN-associated GWAS SNPs were detected. Among women, the HTN risk has been associated with HFE rs1799945 C > G (genotype GG was risky; ORGG = 11.15 ppermGG = 0.014) and inter-locus interactions of all 10 examined SNPs as part of 26 intergenic interactions models. In men, the polymorphism BAG6 rs805303 G > A (genotype AA was protective; ORAA = 0.30 ppermAA = 0.0008) and inter-SNPs interactions of eight loci in only seven models have been founded as HTN-correlated. HTN-linked loci and strongly linked SNPs were characterized by pronounced polyvector functionality in both men and women, but at the same time, signaling pathways of HTN-linked genes/SNPs in women and men were similar and were represented mainly by immune mechanisms. As a result, the present study has demonstrated a more pronounced contribution of BP/HTN-associated GWAS SNPs to the HTN susceptibility (due to weightier intergenic interactions) in European women than in men.
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Affiliation(s)
- Tatiana Ivanova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Maria Churnosova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Maria Abramova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Denis Plotnikov
- Genetic Epidemiology Lab, Kazan State Medical University, 420012 Kazan, Russia
| | - Irina Ponomarenko
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Evgeny Reshetnikov
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Inna Aristova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Inna Sorokina
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Mikhail Churnosov
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
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33
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Adua E. Decoding the mechanism of hypertension through multiomics profiling. J Hum Hypertens 2023; 37:253-264. [PMID: 36329155 PMCID: PMC10063442 DOI: 10.1038/s41371-022-00769-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 08/24/2022] [Accepted: 10/17/2022] [Indexed: 11/06/2022]
Abstract
Hypertension, characterised by a constant high blood pressure, is the primary risk factor for multiple cardiovascular events and a major cause of death in adults. Excitingly, innovations in high-throughput technologies have enabled the global exploration of the whole genome (genomics), revealing dysregulated genes that are linked to hypertension. Moreover, post-genomic biomarkers, from the emerging fields of transcriptomics, proteomics, glycomics and lipidomics, have provided new insights into the molecular underpinnings of hypertension. In this paper, we review the pathophysiology of hypertension, and highlight the multi-omics approaches for hypertension prediction and diagnosis.
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Affiliation(s)
- Eric Adua
- School of Clinical Medicine, Medicine & Health, Rural Clinical Campus, University of New South Wales, Wagga Wagga, NSW, Australia.
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia.
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34
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Earley EJ, Kelly S, Fang F, Alencar CS, Rodrigues DDOW, Soares Cruz DT, Flanagan JM, Ware RE, Zhang X, Gordeuk V, Gladwin M, Zhang Y, Nouraie M, Nekhai S, Sabino E, Custer B, Dinardo C, Page GP. Genome-wide association study of early ischaemic stroke risk in Brazilian individuals with sickle cell disease implicates ADAMTS2 and CDK18 and uncovers novel loci. Br J Haematol 2023; 201:343-352. [PMID: 36602125 PMCID: PMC10155195 DOI: 10.1111/bjh.18637] [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: 09/12/2022] [Accepted: 12/21/2022] [Indexed: 01/06/2023]
Abstract
Ischaemic stroke is a common complication of sickle cell disease (SCD) and without intervention can affect 11% of children with SCD before the age of 20. Within the Trans-Omics for Precision Medicine (TOPMed), a genome-wide association study (GWAS) of ischaemic stroke was performed on 1333 individuals with SCD from Brazil (178 cases, 1155 controls). Via a novel Cox proportional-hazards analysis, we searched for variants associated with ischaemic stroke occurring at younger ages. Variants at genome-wide significance (p < 5 × 10-8 ) include two near genes previously linked to non-SCD early-onset stroke (<65 years): ADAMTS2 (rs147625068, p = 3.70 × 10-9 ) and CDK18 (rs12144136, p = 2.38 × 10-9 ). Meta-analysis, which included the independent SCD cohorts Walk-PHaSST and PUSH, exhibited consistent association for variants rs1209987 near gene TBC1D32 (p = 3.36 × 10-10 ), rs188599171 near CUX1 (p = 5.89 × 10-11 ), rs77900855 near BTG1 (p = 4.66 × 10-8 ), and rs141674494 near VPS13C (1.68 × 10-9 ). Findings from this study support a multivariant model of early ischaemic stroke risk and possibly a shared genetic architecture between SCD individuals and non-SCD individuals younger than 65 years.
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Affiliation(s)
- Eric Jay Earley
- GenOmics, Bioinformatics, and Translational Research Center, RTI International, Research Triangle Park, Durham, NC, USA
| | - Shannon Kelly
- Benioff Children’s Hospital, University of San Francisco, California, USA
- Vitalant Research Institute, San Francisco, California, USA
| | - Fang Fang
- GenOmics, Bioinformatics, and Translational Research Center, RTI International, Research Triangle Park, Durham, NC, USA
| | | | | | - Dahra Teles Soares Cruz
- Department of Hematology, Fundação de Hematologia e Hemoterapia de Pernambuco, HEMOPE, Pernambuco, Brazil
| | - Jonathan M. Flanagan
- Division of Hematology and Oncology, Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
| | - Russell E. Ware
- Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio, USA
| | - Xu Zhang
- Department of Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Victor Gordeuk
- Department of Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Mark Gladwin
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Yingze Zhang
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Mehdi Nouraie
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Sergei Nekhai
- Center for Sickle Cell Disease, Department of Medicine, Howard University, Washington DC, USA
| | - Ester Sabino
- Instituto de Medicina Tropical, University of São Paulo, Brazil
| | - Brian Custer
- Vitalant Research Institute, San Francisco, California, USA
- Department of Laboratory Medicine, University of California, San Francisco, USA
| | - Carla Dinardo
- Instituto de Medicina Tropical, University of São Paulo, Brazil
| | - Grier P. Page
- GenOmics, Bioinformatics, and Translational Research Center, RTI International, Research Triangle Park, Durham, NC, USA
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35
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Yang Y, Knol MJ, Wang R, Mishra A, Liu D, Luciano M, Teumer A, Armstrong N, Bis JC, Jhun MA, Li S, Adams HHH, Aziz NA, Bastin ME, Bourgey M, Brody JA, Frenzel S, Gottesman RF, Hosten N, Hou L, Kardia SLR, Lohner V, Marquis P, Maniega SM, Satizabal CL, Sorond FA, Valdés Hernández MC, van Duijn CM, Vernooij MW, Wittfeld K, Yang Q, Zhao W, Boerwinkle E, Levy D, Deary IJ, Jiang J, Mather KA, Mosley TH, Psaty BM, Sachdev PS, Smith JA, Sotoodehnia N, DeCarli CS, Breteler MMB, Ikram MA, Grabe HJ, Wardlaw J, Longstreth WT, Launer LJ, Seshadri S, Debette S, Fornage M. Epigenetic and integrative cross-omics analyses of cerebral white matter hyperintensities on MRI. Brain 2023; 146:492-506. [PMID: 35943854 PMCID: PMC9924914 DOI: 10.1093/brain/awac290] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Revised: 06/23/2022] [Accepted: 07/08/2022] [Indexed: 11/13/2022] Open
Abstract
Cerebral white matter hyperintensities on MRI are markers of cerebral small vessel disease, a major risk factor for dementia and stroke. Despite the successful identification of multiple genetic variants associated with this highly heritable condition, its genetic architecture remains incompletely understood. More specifically, the role of DNA methylation has received little attention. We investigated the association between white matter hyperintensity burden and DNA methylation in blood at ∼450 000 cytosine-phosphate-guanine (CpG) sites in 9732 middle-aged to older adults from 14 community-based studies. Single CpG and region-based association analyses were carried out. Functional annotation and integrative cross-omics analyses were performed to identify novel genes underlying the relationship between DNA methylation and white matter hyperintensities. We identified 12 single CpG and 46 region-based DNA methylation associations with white matter hyperintensity burden. Our top discovery single CpG, cg24202936 (P = 7.6 × 10-8), was associated with F2 expression in blood (P = 6.4 × 10-5) and co-localized with FOLH1 expression in brain (posterior probability = 0.75). Our top differentially methylated regions were in PRMT1 and in CCDC144NL-AS1, which were also represented in single CpG associations (cg17417856 and cg06809326, respectively). Through Mendelian randomization analyses cg06809326 was putatively associated with white matter hyperintensity burden (P = 0.03) and expression of CCDC144NL-AS1 possibly mediated this association. Differentially methylated region analysis, joint epigenetic association analysis and multi-omics co-localization analysis consistently identified a role of DNA methylation near SH3PXD2A, a locus previously identified in genome-wide association studies of white matter hyperintensities. Gene set enrichment analyses revealed functions of the identified DNA methylation loci in the blood-brain barrier and in the immune response. Integrative cross-omics analysis identified 19 key regulatory genes in two networks related to extracellular matrix organization, and lipid and lipoprotein metabolism. A drug-repositioning analysis indicated antihyperlipidaemic agents, more specifically peroxisome proliferator-activated receptor-alpha, as possible target drugs for white matter hyperintensities. Our epigenome-wide association study and integrative cross-omics analyses implicate novel genes influencing white matter hyperintensity burden, which converged on pathways related to the immune response and to a compromised blood-brain barrier possibly due to disrupted cell-cell and cell-extracellular matrix interactions. The results also suggest that antihyperlipidaemic therapy may contribute to lowering risk for white matter hyperintensities possibly through protection against blood-brain barrier disruption.
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Affiliation(s)
- Yunju Yang
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science at Houston, Houston, TX 77030, USA
| | - Maria J Knol
- Department of Epidemiology, Erasmus MC University Medical Center, 3015 GD, Rotterdam, The Netherlands
| | - Ruiqi Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Aniket Mishra
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, Team VINTAGE, UMR 1219, F-33000 Bordeaux, France
| | - Dan Liu
- Population Health Sciences, German Centre for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
| | - Michelle Luciano
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald 17475, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald 17475, Germany
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Bialystok, 15-269, Poland
| | - Nicola Armstrong
- Mathematics and Statistics, Curtin University, 6845 Perth, Australia
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 02115, USA
| | - Min A Jhun
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48104, USA
| | - Shuo Li
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Hieab H H Adams
- Department of Epidemiology, Erasmus MC University Medical Center, 3015 GD, Rotterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center, 3015 GD, Rotterdam, The Netherlands
| | - Nasir Ahmad Aziz
- Population Health Sciences, German Centre for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
- Department of Neurology, Faculty of Medicine, University of Bonn, 53127 Bonn, Germany
| | - Mark E Bastin
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, EH8 9AB, UK
| | - Mathieu Bourgey
- Canadian Centre for Computational Genomics, McGill University, Montréal, Quebec, Canada H3A 0G1
- Department for Human Genetics, McGill University Genome Centre, McGill University, Montréal, Quebec, Canada H3A 0G1
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 02115, USA
| | - Stefan Frenzel
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald 17475, Germany
| | - Rebecca F Gottesman
- Stroke Branch, National Institutes of Neurological Disorders and Stroke, Bethesda, MD 20814, USA
| | - Norbert Hosten
- Department of Radiology and Neuroradiology, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48104, USA
| | - Valerie Lohner
- Population Health Sciences, German Centre for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
| | - Pascale Marquis
- Canadian Centre for Computational Genomics, McGill University, Montréal, Quebec, Canada H3A 0G1
- Department for Human Genetics, McGill University Genome Centre, McGill University, Montréal, Quebec, Canada H3A 0G1
| | - Susana Muñoz Maniega
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, EH8 9AB, UK
| | - Claudia L Satizabal
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases and Department of Population Health Sciences, UT Health San Antonio, San Antonio, TX 78229, USA
- The Framingham Heart Study, Framingham, MA 01701, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA 02115, USA
| | - Farzaneh A Sorond
- Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Maria C Valdés Hernández
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, EH8 9AB, UK
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus MC University Medical Center, 3015 GD, Rotterdam, The Netherlands
- Nuffield Department of Population Health, Oxford University, Oxford, OX3 7LF, UK
| | - Meike W Vernooij
- Department of Epidemiology, Erasmus MC University Medical Center, 3015 GD, Rotterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center, 3015 GD, Rotterdam, The Netherlands
| | - Katharina Wittfeld
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald 17475, Germany
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, 17475 Rostock, Germany
| | - Qiong Yang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
- The Framingham Heart Study, Framingham, MA 01701, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48104, USA
| | - Eric Boerwinkle
- Human Genetics Center, School of Public Health, University of Texas Health Science at Houston, Houston, TX 77030, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Daniel Levy
- The Framingham Heart Study, Framingham, MA 01701, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20814, USA
| | - Ian J Deary
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Jiyang Jiang
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW 2052, Australia
| | - Karen A Mather
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW 2052, Australia
- Neuroscience Research Australia, Sydney, NSW 2031, Australia
| | - Thomas H Mosley
- The Memory Impairment Neurodegenerative Dementia (MIND) Research Center, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 02115, USA
- Department of Epidemiology, University of Washington, Seattle, WA 98104, USA
| | - Perminder S Sachdev
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW 2052, Australia
- Neuropsychiatric Institute, The Prince of Wales Hospital, University of New South Wales, Randwick, NSW 2031, Australia
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48104, USA
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 02115, USA
| | - Charles S DeCarli
- Department of Neurology and Center for Neuroscience, University of California at Davis, Sacramento, CA 95816, USA
| | - Monique M B Breteler
- Population Health Sciences, German Centre for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
- Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, 53127 Bonn, Germany
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, 3015 GD, Rotterdam, The Netherlands
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald 17475, Germany
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, 17475 Rostock, Germany
| | - Joanna Wardlaw
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, EH8 9AB, UK
| | - W T Longstreth
- Department of Epidemiology, University of Washington, Seattle, WA 98104, USA
- Department of Neurology, University of Washington, Seattle, WA 98104, USA
| | - Lenore J Launer
- Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases and Department of Population Health Sciences, UT Health San Antonio, San Antonio, TX 78229, USA
- The Framingham Heart Study, Framingham, MA 01701, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA 02115, USA
| | - Stephanie Debette
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, Team VINTAGE, UMR 1219, F-33000 Bordeaux, France
- Department of Neurology, Boston University School of Medicine, Boston, MA 02115, USA
- CHU de Bordeaux, Department of Neurology, F-33000 Bordeaux, France
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science at Houston, Houston, TX 77030, USA
- Human Genetics Center, School of Public Health, University of Texas Health Science at Houston, Houston, TX 77030, USA
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Suri P, Heagerty PJ, Korpak A, Jensen MP, Gold LS, Chan KCG, Timmons A, Friedly J, Jarvik JG, Baraff A. Improving Power and Accuracy in Randomized Controlled Trials of Pain Treatments by Accounting for Concurrent Analgesic Use. THE JOURNAL OF PAIN 2023; 24:332-344. [PMID: 36220482 PMCID: PMC9898095 DOI: 10.1016/j.jpain.2022.09.017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 09/17/2022] [Accepted: 09/19/2022] [Indexed: 11/08/2022]
Abstract
The 0 to 10 numeric rating scale of pain intensity is a standard outcome in randomized controlled trials (RCTs) of pain treatments. For individuals taking analgesics, there may be a disparity between "observed" pain intensity (pain intensity with concurrent analgesic use) and pain intensity without concurrent analgesic use (what the numeric rating scale would be had analgesics not been taken). Using a contemporary causal inference framework, we compare analytic methods that can potentially account for concurrent analgesic use, first in statistical simulations, and second in analyses of real (non-simulated) data from an RCT of lumbar epidural steroid injections. The default analytic method was ignoring analgesic use, which is the most common approach in pain RCTs. Compared to ignoring analgesic use and other analytic methods, simulations showed that a quantitative pain and analgesia composite outcome based on adding 1.5 points to pain intensity for those who were taking an analgesic (the QPAC1.5) optimized power and minimized bias. Analyses of real RCT data supported the results of the simulations, showing greater power with analysis of the QPAC1.5 as compared to ignoring analgesic use and most other methods examined. We propose alternative methods that should be considered in the analysis of pain RCTs. PERSPECTIVE: This article presents the conceptual framework behind a new quantitative pain and analgesia composite outcome, the QPAC1.5, and the results of statistical simulations and analyses of trial data supporting improvements in power and bias using the QPAC1.5. Methods of this type should be considered in the analysis of pain RCTs.
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Affiliation(s)
- Pradeep Suri
- Seattle Epidemiologic Research and Information Center, VA Puget Sound Health Care System, Seattle, Washington; Division of Rehabilitation Care Services, VA Puget Sound Health Care System, Seattle, Washington; Clinical Learning, Evidence, and Research Center, University of Washington, Seattle, Washington; Department of Rehabilitation Medicine, University of Washington, Seattle, Washington.
| | - Patrick J Heagerty
- Department of Biostatistics, University of Washington, Seattle, Washington
| | - Anna Korpak
- Seattle Epidemiologic Research and Information Center, VA Puget Sound Health Care System, Seattle, Washington
| | - Mark P Jensen
- Department of Rehabilitation Medicine, University of Washington, Seattle, Washington
| | - Laura S Gold
- Clinical Learning, Evidence, and Research Center, University of Washington, Seattle, Washington; Departments of Radiology and Neurological Surgery, University of Washington, Seattle, Washington
| | - Kwun C G Chan
- Department of Biostatistics, University of Washington, Seattle, Washington
| | - Andrew Timmons
- Seattle Epidemiologic Research and Information Center, VA Puget Sound Health Care System, Seattle, Washington
| | - Janna Friedly
- Clinical Learning, Evidence, and Research Center, University of Washington, Seattle, Washington; Department of Rehabilitation Medicine, University of Washington, Seattle, Washington
| | - Jeffrey G Jarvik
- Clinical Learning, Evidence, and Research Center, University of Washington, Seattle, Washington; Departments of Radiology and Neurological Surgery, University of Washington, Seattle, Washington
| | - Aaron Baraff
- Seattle Epidemiologic Research and Information Center, VA Puget Sound Health Care System, Seattle, Washington; Department of Statistics, University of Washington, Seattle, Washington
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Soremekun O, Dib MJ, Rajasundaram S, Fatumo S, Gill D. Genetic heterogeneity in cardiovascular disease across ancestries: Insights for mechanisms and therapeutic intervention. CAMBRIDGE PRISMS. PRECISION MEDICINE 2023; 1:e8. [PMID: 38550935 PMCID: PMC10953756 DOI: 10.1017/pcm.2022.13] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 12/09/2022] [Accepted: 12/15/2022] [Indexed: 11/03/2024]
Abstract
Cardiovascular diseases (CVDs) are complex in their aetiology, arising due to a combination of genetics, lifestyle and environmental factors. By nature of this complexity, different CVDs vary in their molecular mechanisms, clinical presentation and progression. Although extensive efforts are being made to develop novel therapeutics for CVDs, genetic heterogeneity is often overlooked in the development process. By considering molecular mechanisms at an individual and ancestral level, a richer understanding of the influence of environmental and lifestyle factors can be gained and more refined therapeutic interventions can be developed. It is therefore expedient to understand the molecular and clinical heterogeneity in CVDs that exists across different populations. In this review, we highlight how the mechanisms underlying CVDs vary across diverse population ancestry groups due to genetic heterogeneity. We then discuss how such genetic heterogeneity is being leveraged to inform therapeutic interventions and personalised medicine, highlighting examples across the CVD spectrum. Finally, we present an overview of how polygenic risk scores and Mendelian randomisation can foster more robust insight into disease mechanisms and therapeutic intervention in diverse populations. Fulfilment of the vision of precision medicine requires more exhaustive leveraging of the genetic variability across diverse ancestry populations to improve our understanding of disease onset, progression and response to therapeutic intervention.
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Affiliation(s)
- Opeyemi Soremekun
- The African Computational Genomics (TACG) Research Group, Medical Research Council/Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine, Uganda Research Unit, Entebbe, Uganda
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Molecular Bio-Computation and Drug Design Laboratory, School of Health Sciences, University of KwaZulu-Natal, Westville Campus, Durban, South Africa
| | - Marie-Joe Dib
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- British Heart Foundation Centre of Excellence, Imperial College London, London, UK
| | - Skanda Rajasundaram
- Centre for Evidence-Based Medicine, University of Oxford, Oxford, UK
- Faculty of Medicine, Imperial College London, London, UK
| | - Segun Fatumo
- The African Computational Genomics (TACG) Research Group, Medical Research Council/Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine, Uganda Research Unit, Entebbe, Uganda
- Department of Non-Communicable Disease Epidemiology (NCDE), London School of Hygiene and Tropical Medicine, London, UK
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- British Heart Foundation Centre of Excellence, Imperial College London, London, UK
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Bakker MK, van Straten T, Chong M, Paré G, Gill D, Ruigrok YM. Anti-Epileptic Drug Target Perturbation and Intracranial Aneurysm Risk: Mendelian Randomization and Colocalization Study. Stroke 2023; 54:208-216. [PMID: 36300369 PMCID: PMC9794136 DOI: 10.1161/strokeaha.122.040598] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
BACKGROUND In a genome-wide association study of intracranial aneurysms (IA), enrichment was found between genes associated with IA and genes encoding targets of effective anti-epileptic drugs. Our aim was to assess if this pleiotropy is driven by shared disease mechanisms that could potentially highlight a treatment strategy for IA. METHODS Using 2-sample inverse-variance weighted Mendelian randomization and genetic colocalization analyses we assessed: (1) if epilepsy liability in general affects IA risk, and (2) whether changes in gene- and protein-expression levels of anti-epileptic drug targets in blood and arterial tissue may causally affect IA risk. RESULTS We found no overall effect of epilepsy liability on IA. Expression of 21 genes and 13 proteins corresponding to anti-epileptic drug targets supported a causal effect (P<0.05) on IA risk. Of those genes and proteins, genetic variants affecting CNNM2 levels showed strong evidence for colocalization with IA risk (posterior probability>70%). Higher CNNM2 levels in arterial tissue were associated with increased IA risk (odds ratio, 3.02; [95% CI, 2.32-3.94]; P=3.39×10-16). CNNM2 expression was best proxied by rs11191580. The magnitude of the effect of this variant was greater than would be expected if systemic blood pressure was the sole IA-causing mechanism in this locus. CONCLUSIONS CNNM2 is a driver of the pleiotropy between IA and anti-epileptic drug targets. Administration of the anti-epileptic drugs phenytoin, valproic acid, or carbamazepine may be expected to decrease CNNM2 levels and therefore subsequently decrease IA risk. CNNM2 is therefore an important target to investigate further for its role in the pathogenesis of IA.
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Affiliation(s)
- Mark K. Bakker
- Department of Neurology and Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University, the Netherlands (M.K.B., T.v.S., Y.M.R.)
| | - Tijmen van Straten
- Department of Neurology and Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University, the Netherlands (M.K.B., T.v.S., Y.M.R.)
| | - Michael Chong
- Population Health Research Institute; Thrombosis and Atherosclerosis Research Institute; Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario (M.C., G.P.)
| | - Guillaume Paré
- Population Health Research Institute; Thrombosis and Atherosclerosis Research Institute; Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario (M.C., G.P.)
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, United Kingdom (D.G.)
| | - Ynte M. Ruigrok
- Department of Neurology and Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University, the Netherlands (M.K.B., T.v.S., Y.M.R.)
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Abramova M, Churnosova M, Efremova O, Aristova I, Reshetnikov E, Polonikov A, Churnosov M, Ponomarenko I. Effects of Pre-Pregnancy Overweight/Obesity on the Pattern of Association of Hypertension Susceptibility Genes with Preeclampsia. Life (Basel) 2022; 12:2018. [PMID: 36556383 PMCID: PMC9784908 DOI: 10.3390/life12122018] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Revised: 11/21/2022] [Accepted: 12/01/2022] [Indexed: 12/12/2022] Open
Abstract
The aim of this study was to explore the effects of pre-pregnancy overweight/obesity on the pattern of association of hypertension susceptibility genes with preeclampsia (PE). Ten single-nucleotide polymorphisms (SNPs) of the 10 genome-wide association studies (GWAS)-significant hypertension/blood pressure (BP) candidate genes were genotyped in 950 pregnant women divided into two cohorts according to their pre-pregnancy body mass index (preBMI): preBMI ≥ 25 (162 with PE and 159 control) and preBMI < 25 (290 with PE and 339 control). The PLINK software package was utilized to study the association (analyzed four genetic models using logistic regression). The functionality of PE-correlated loci was analyzed by performing an in silico database analysis. Two SNP hypertension/BP genes, rs805303 BAG6 (OR: 0.36−0.66) and rs167479 RGL3 (OR: 1.86), in subjects with preBMI ≥ 25 were associated with PE. No association between the studied SNPs and PE in the preBMI < 25 group was determined. Further analysis showed that two PE-associated SNPs are functional (have weighty eQTL, sQTL, regulatory, and missense values) and could be potentially implicated in PE development. In conclusion, this study was the first to discover the modifying influence of overweight/obesity on the pattern of association of GWAS-significant hypertension/BP susceptibility genes with PE: these genes are linked with PE in preBMI ≥ 25 pregnant women and are not PE-involved in the preBMI < 25 group.
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Affiliation(s)
- Maria Abramova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Maria Churnosova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Olesya Efremova
- Department of Medical Genetics, Kharkiv National Medical University, 61022 Kharkov, Ukraine
- Grishchenko Clinic of Reproductive Medicine, 61052 Kharkov, Ukraine
| | - Inna Aristova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Evgeny Reshetnikov
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Alexey Polonikov
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
- Department of Biology, Medical Genetics and Ecology and Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 305041 Kursk, Russia
| | - Mikhail Churnosov
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
| | - Irina Ponomarenko
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
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40
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Abramova MY, Ponomarenko IV, Churnosov MI. The Polymorphic Locus rs167479 of the RGL3 Gene Is Associated with the Risk of Severe Preeclampsia. RUSS J GENET+ 2022. [DOI: 10.1134/s102279542212002x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
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Nakaya N, Nakaya K, Tsuchiya N, Sone T, Kogure M, Hatanaka R, kanno I, Metoki H, Obara T, Ishikuro M, Hozawa A, Kuriyama S. Similarities in cardiometabolic risk factors among random male-female pairs: a large observational study in Japan. BMC Public Health 2022; 22:1978. [PMID: 36307801 PMCID: PMC9617423 DOI: 10.1186/s12889-022-14348-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Revised: 09/26/2022] [Accepted: 10/13/2022] [Indexed: 11/21/2022] Open
Abstract
Background: Previous observational studies have shown similarities in cardiometabolic risk factors between spouses. It is still possible that this result reflects the age similarity of spouses rather than environmental factors of spouses (e.g. cohabitation effect). To clarify the importance of mate cardiometabolic risk factors for similarity of environmental factors, it is necessary to examine whether they are observed in random male-female pairs while maintaining the age of the spousal pairs. This study aimed to determine whether the similarities found between spousal pairs for cardiometabolic risks were also observed between random male-female pairs. Methods: This cross-sectional study included 5,391 spouse pairs from Japan; data were obtained from a large biobank study. For pairings, women of the same age were randomly shuffled to create new male-female pairs of the same age as that of the original spouse pairs. Similarities in cardiometabolic risk factors between the random male-female pairs were analysed using Pearson’s correlation or age-adjusted logistic regression analyses. Results: The mean ages of the men and women were 63.2 and 60.4 years, respectively. Almost all cardiometabolic risk factors similarities were not noted in cardiometabolic risk factors, including the continuous risk factors (anthropometric traits, blood pressure, glycated haemoglobin level, and lipid traits); lifestyle habits (smoking, drinking, and physical activity); or diseases (hypertension, type 2 diabetes mellitus, and metabolic syndrome) between the random male-female pairs. The age-adjusted correlation coefficients ranged from − 0.007 for body mass index to 0.071 for total cholesterol. The age-adjusted odds ratio (95% confidence interval) for current drinkers was 0.94 (0.81 − 1.09); hypertension, 1.07 (0.93 − 1.23); and type 2 diabetes mellitus, 1.08 (0.77 − 1.50). Conclusion: In this study, few similarities in cardiometabolic risk factors were noted among the random male-female pairs. As spouse pairs may share environmental factors, intervention strategies targeting lifestyle habits and preventing lifestyle-related diseases may be effective.
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Sethi A, Taylor DL, Ruby JG, Venkataraman J, Sorokin E, Cule M, Melamud E. Calcification of the abdominal aorta is an under-appreciated cardiovascular disease risk factor in the general population. Front Cardiovasc Med 2022; 9:1003246. [PMID: 36277789 PMCID: PMC9582957 DOI: 10.3389/fcvm.2022.1003246] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 09/13/2022] [Indexed: 12/05/2022] Open
Abstract
Calcification of large arteries is a high-risk factor in the development of cardiovascular diseases, however, due to the lack of routine monitoring, the pathology remains severely under-diagnosed and prevalence in the general population is not known. We have developed a set of machine learning methods to quantitate levels of abdominal aortic calcification (AAC) in the UK Biobank imaging cohort and carried out the largest to-date analysis of genetic, biochemical, and epidemiological risk factors associated with the pathology. In a genetic association study, we identified three novel loci associated with AAC (FGF9, NAV9, and APOE), and replicated a previously reported association at the TWIST1/HDAC9 locus. We find that AAC is a highly prevalent pathology, with ~ 1 in 10 adults above the age of 40 showing significant levels of hydroxyapatite build-up (Kauppila score > 3). Presentation of AAC was strongly predictive of future cardiovascular events including stenosis of precerebral arteries (HR~1.5), myocardial infarction (HR~1.3), ischemic heart disease (HR~1.3), as well as other diseases such as chronic obstructive pulmonary disease (HR~1.3). Significantly, we find that the risk for myocardial infarction from elevated AAC (HR ~1.4) was comparable to the risk of hypercholesterolemia (HR~1.4), yet most people who develop AAC are not hypercholesterolemic. Furthermore, the overwhelming majority (98%) of individuals who develop pathology do so in the absence of known pre-existing risk conditions such as chronic kidney disease and diabetes (0.6% and 2.7% respectively). Our findings indicate that despite the high cardiovascular risk, calcification of large arteries remains a largely under-diagnosed lethal condition, and there is a clear need for increased awareness and monitoring of the pathology in the general population.
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Affiliation(s)
| | | | | | | | | | - Madeleine Cule
- Calico Life Sciences LLC, South San Francisco, CA, United States
| | - Eugene Melamud
- Calico Life Sciences LLC, South San Francisco, CA, United States
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Mildly elevated diastolic blood pressure increases subsequent risk of breast cancer in postmenopausal women in the Health Examinees-Gem study. Sci Rep 2022; 12:15995. [PMID: 36163474 PMCID: PMC9512811 DOI: 10.1038/s41598-022-19705-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 09/02/2022] [Indexed: 12/24/2022] Open
Abstract
Epidemiological evidence suggests that hypertension is associated with breast cancer risk. However, previous studies disregard blood pressure components in the healthy population. We aimed to examine the relationship between systolic and diastolic blood pressure and breast cancer risk in a Korean population-based prospective cohort. A total of 73,031 women from the Health Examinees Gem Study were followed from baseline (2004 to 2013) through 2018. Systolic and diastolic blood pressure were measured by trainee physicians at baseline recruitment and then categorized based on the international guidelines for clinical hypertension. Associations between systolic and diastolic blood pressure with overall breast cancer and stratified by premenopausal and postmenopausal status were evaluated using adjusted multivariable Cox proportional hazard regression. A total of 858 breast cancer cases were recorded for a median follow-up period of 9 years. Compared with the normal DBP category (< 85 mmHg), the normal-high category was positively associated with breast cancer risk in postmenopausal women (85–89 mmHg, HR 1.73 95% CI 1.28–2.33), but not in premenopausal women (85–89 mmHg, HR 0.87 95% CI 0.56–1.35). Similar results were found when all cases of self-reported hypertension were excluded. Results for SBP did not show a significant association with breast cancer risk. The association between DBP and breast cancer suggests DBP could be an important factor in cancer prevention, especially for women after menopause. Our study provides a first detailed approach to understanding the importance of diastolic blood pressure for breast cancer prevention and warrants further investigation.
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Le Floch E, Cosentino T, Larsen CK, Beuschlein F, Reincke M, Amar L, Rossi GP, De Sousa K, Baron S, Chantalat S, Saintpierre B, Lenzini L, Frouin A, Giscos-Douriez I, Ferey M, Abdellatif AB, Meatchi T, Empana JP, Jouven X, Gieger C, Waldenberger M, Peters A, Cusi D, Salvi E, Meneton P, Touvier M, Deschasaux M, Druesne-Pecollo N, Boulkroun S, Fernandes-Rosa FL, Deleuze JF, Jeunemaitre X, Zennaro MC. Identification of risk loci for primary aldosteronism in genome-wide association studies. Nat Commun 2022; 13:5198. [PMID: 36057693 PMCID: PMC9440917 DOI: 10.1038/s41467-022-32896-8] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Accepted: 08/23/2022] [Indexed: 11/23/2022] Open
Abstract
Primary aldosteronism affects up to 10% of hypertensive patients and is responsible for treatment resistance and increased cardiovascular risk. Here we perform a genome-wide association study in a discovery cohort of 562 cases and 950 controls and identify three main loci on chromosomes 1, 13 and X; associations on chromosome 1 and 13 are replicated in a second cohort and confirmed by a meta-analysis involving 1162 cases and 3296 controls. The association on chromosome 13 is specific to men and stronger in bilateral adrenal hyperplasia than aldosterone producing adenoma. Candidate genes located within the two loci, CASZ1 and RXFP2, are expressed in human and mouse adrenals in different cell clusters. Their overexpression in adrenocortical cells suppresses mineralocorticoid output under basal and stimulated conditions, without affecting cortisol biosynthesis. Our study identifies the first risk loci for primary aldosteronism and highlights new mechanisms for the development of aldosterone excess.
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Affiliation(s)
- Edith Le Floch
- Centre National de Recherche en Génomique Humaine, Institut de biologie François Jacob, CEA, Université Paris-Saclay, Evry, France
| | | | - Casper K Larsen
- Université Paris Cité, Inserm, PARCC, F-75015, Paris, France
| | - Felix Beuschlein
- Medizinische Klinik und Poliklinik IV, Ludwig-Maximilians-University, 80336, Munich, Germany
- Klinik für Endokrinologie, Diabetologie und Klinische Ernährung, Universitätsspital Zürich (USZ) und Universität Zürich (UZH), Zürich, Switzerland
| | - Martin Reincke
- Medizinische Klinik und Poliklinik IV, Ludwig-Maximilians-University, 80336, Munich, Germany
| | - Laurence Amar
- Université Paris Cité, Inserm, PARCC, F-75015, Paris, France
- Assistance Publique-Hôpitaux de Paris, Hôpital Européen Georges Pompidou, Unité Hypertension artérielle, Paris, France
| | - Gian-Paolo Rossi
- DMCS 'G. Patrassi' University of Padova Medical School, University Hospital, 35126, Padova, Italy
| | - Kelly De Sousa
- Université Paris Cité, Inserm, PARCC, F-75015, Paris, France
| | - Stéphanie Baron
- Université Paris Cité, F-75006, Paris, France
- Assistance Publique-Hôpitaux de Paris, Hôpital Européen Georges Pompidou, Service de Physiologie, Paris, France
| | - Sophie Chantalat
- Centre National de Recherche en Génomique Humaine, Institut de biologie François Jacob, CEA, Université Paris-Saclay, Evry, France
| | - Benjamin Saintpierre
- Université Paris Cité, Institut Cochin, Genom'IC platform, INSERM, CNRS, 75014, Paris, France
| | - Livia Lenzini
- DMCS 'G. Patrassi' University of Padova Medical School, University Hospital, 35126, Padova, Italy
| | - Arthur Frouin
- Centre National de Recherche en Génomique Humaine, Institut de biologie François Jacob, CEA, Université Paris-Saclay, Evry, France
| | | | - Matthis Ferey
- Université Paris Cité, Inserm, PARCC, F-75015, Paris, France
| | | | - Tchao Meatchi
- Université Paris Cité, Inserm, PARCC, F-75015, Paris, France
- Assistance Publique-Hôpitaux de Paris, Hôpital Européen Georges Pompidou, Service d'Anatomie Pathologique, Paris, France
| | | | - Xavier Jouven
- Université Paris Cité, Inserm, PARCC, F-75015, Paris, France
- Assistance Publique-Hôpitaux de Paris, Hôpital Européen Georges Pompidou, Service de Cardiologie, Paris, France
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Research Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- German Research Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Daniele Cusi
- Institute of Biomedical Technologies National Research Council of Italy, Milan, Italy
- Bio4Dreams-Business Nursery for Life Sciences, Milan, Italy
| | - Erika Salvi
- Neuroalgology Unit, Fondazione IRCCS Istituto Neurologico 'Carlo Besta', Milan, Italy
| | - Pierre Meneton
- UMR_1142, INSERM, Sorbonne Université, Université Paris 13, Paris, France
| | - Mathilde Touvier
- Sorbonne Paris Nord University, INSERM U1153, INRAe U1125, CNAM, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - Université Paris Cité (CRESS), 93017, Bobigny, France
| | - Mélanie Deschasaux
- Sorbonne Paris Nord University, INSERM U1153, INRAe U1125, CNAM, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - Université Paris Cité (CRESS), 93017, Bobigny, France
| | - Nathalie Druesne-Pecollo
- Sorbonne Paris Nord University, INSERM U1153, INRAe U1125, CNAM, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - Université Paris Cité (CRESS), 93017, Bobigny, France
| | | | | | - Jean-François Deleuze
- Centre National de Recherche en Génomique Humaine, Institut de biologie François Jacob, CEA, Université Paris-Saclay, Evry, France
| | - Xavier Jeunemaitre
- Université Paris Cité, Inserm, PARCC, F-75015, Paris, France
- Assistance Publique-Hôpitaux de Paris, Hôpital Européen Georges Pompidou, Service de Génétique, Paris, France
| | - Maria-Christina Zennaro
- Université Paris Cité, Inserm, PARCC, F-75015, Paris, France.
- Assistance Publique-Hôpitaux de Paris, Hôpital Européen Georges Pompidou, Service de Génétique, Paris, France.
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45
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Ju D, Hui D, Hammond DA, Wonkam A, Tishkoff SA. Importance of Including Non-European Populations in Large Human Genetic Studies to Enhance Precision Medicine. Annu Rev Biomed Data Sci 2022; 5:321-339. [PMID: 35576557 PMCID: PMC9904154 DOI: 10.1146/annurev-biodatasci-122220-112550] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
One goal of genomic medicine is to uncover an individual's genetic risk for disease, which generally requires data connecting genotype to phenotype, as done in genome-wide association studies (GWAS). While there may be clinical promise to employing prediction tools such as polygenic risk scores (PRS), it currently stands that individuals of non-European ancestry may not reap the benefits of genomic medicine because of underrepresentation in large-scale genetics studies. Here, we discuss why this inequity poses a problem for genomic medicine and the reasons for the low transferability of PRS across populations. We also survey the ancestry representation of published GWAS and investigate how estimates of ancestry diversity in GWASparticipants might be biased. We highlight the importance of expanding genetic research in Africa, one of the most underrepresented regions in human genomics research, and discuss issues of ethics, resources, and technology for equitable advancement of genomic medicine.
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Affiliation(s)
- Dan Ju
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA;
| | - Daniel Hui
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA;
- Graduate Program in Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Dorothy A Hammond
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA;
- Penn Center for Global Genomics & Health Equity, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Ambroise Wonkam
- Division of Human Genetics, Department of Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
- Department of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA;
| | - Sarah A Tishkoff
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA;
- Department of Biology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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46
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Kelly TN, Sun X, He KY, Brown MR, Taliun SAG, Hellwege JN, Irvin MR, Mi X, Brody JA, Franceschini N, Guo X, Hwang SJ, de Vries PS, Gao Y, Moscati A, Nadkarni GN, Yanek LR, Elfassy T, Smith JA, Chung RH, Beitelshees AL, Patki A, Aslibekyan S, Blobner BM, Peralta JM, Assimes TL, Palmas WR, Liu C, Bress AP, Huang Z, Becker LC, Hwa CM, O'Connell JR, Carlson JC, Warren HR, Das S, Giri A, Martin LW, Craig Johnson W, Fox ER, Bottinger EP, Razavi AC, Vaidya D, Chuang LM, Chang YPC, Naseri T, Jain D, Kang HM, Hung AM, Srinivasasainagendra V, Snively BM, Gu D, Montasser ME, Reupena MS, Heavner BD, LeFaive J, Hixson JE, Rice KM, Wang FF, Nielsen JB, Huang J, Khan AT, Zhou W, Nierenberg JL, Laurie CC, Armstrong ND, Shi M, Pan Y, Stilp AM, Emery L, Wong Q, Hawley NL, Minster RL, Curran JE, Munroe PB, Weeks DE, North KE, Tracy RP, Kenny EE, Shimbo D, Chakravarti A, Rich SS, Reiner AP, Blangero J, Redline S, Mitchell BD, Rao DC, Ida Chen YD, Kardia SLR, Kaplan RC, Mathias RA, He J, Psaty BM, Fornage M, Loos RJF, Correa A, Boerwinkle E, Rotter JI, Kooperberg C, Edwards TL, et alKelly TN, Sun X, He KY, Brown MR, Taliun SAG, Hellwege JN, Irvin MR, Mi X, Brody JA, Franceschini N, Guo X, Hwang SJ, de Vries PS, Gao Y, Moscati A, Nadkarni GN, Yanek LR, Elfassy T, Smith JA, Chung RH, Beitelshees AL, Patki A, Aslibekyan S, Blobner BM, Peralta JM, Assimes TL, Palmas WR, Liu C, Bress AP, Huang Z, Becker LC, Hwa CM, O'Connell JR, Carlson JC, Warren HR, Das S, Giri A, Martin LW, Craig Johnson W, Fox ER, Bottinger EP, Razavi AC, Vaidya D, Chuang LM, Chang YPC, Naseri T, Jain D, Kang HM, Hung AM, Srinivasasainagendra V, Snively BM, Gu D, Montasser ME, Reupena MS, Heavner BD, LeFaive J, Hixson JE, Rice KM, Wang FF, Nielsen JB, Huang J, Khan AT, Zhou W, Nierenberg JL, Laurie CC, Armstrong ND, Shi M, Pan Y, Stilp AM, Emery L, Wong Q, Hawley NL, Minster RL, Curran JE, Munroe PB, Weeks DE, North KE, Tracy RP, Kenny EE, Shimbo D, Chakravarti A, Rich SS, Reiner AP, Blangero J, Redline S, Mitchell BD, Rao DC, Ida Chen YD, Kardia SLR, Kaplan RC, Mathias RA, He J, Psaty BM, Fornage M, Loos RJF, Correa A, Boerwinkle E, Rotter JI, Kooperberg C, Edwards TL, Abecasis GR, Zhu X, Levy D, Arnett DK, Morrison AC. Insights From a Large-Scale Whole-Genome Sequencing Study of Systolic Blood Pressure, Diastolic Blood Pressure, and Hypertension. Hypertension 2022; 79:1656-1667. [PMID: 35652341 PMCID: PMC9593435 DOI: 10.1161/hypertensionaha.122.19324] [Show More Authors] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 05/12/2022] [Indexed: 12/30/2022]
Abstract
BACKGROUND The availability of whole-genome sequencing data in large studies has enabled the assessment of coding and noncoding variants across the allele frequency spectrum for their associations with blood pressure. METHODS We conducted a multiancestry whole-genome sequencing analysis of blood pressure among 51 456 Trans-Omics for Precision Medicine and Centers for Common Disease Genomics program participants (stage-1). Stage-2 analyses leveraged array data from UK Biobank (N=383 145), Million Veteran Program (N=318 891), and Reasons for Geographic and Racial Differences in Stroke (N=10 643) participants, along with whole-exome sequencing data from UK Biobank (N=199 631) participants. RESULTS Two blood pressure signals achieved genome-wide significance in meta-analyses of stage-1 and stage-2 single variant findings (P<5×10-8). Among them, a rare intergenic variant at novel locus, LOC100506274, was associated with lower systolic blood pressure in stage-1 (beta [SE]=-32.6 [6.0]; P=4.99×10-8) but not stage-2 analysis (P=0.11). Furthermore, a novel common variant at the known INSR locus was suggestively associated with diastolic blood pressure in stage-1 (beta [SE]=-0.36 [0.07]; P=4.18×10-7) and attained genome-wide significance in stage-2 (beta [SE]=-0.29 [0.03]; P=7.28×10-23). Nineteen additional signals suggestively associated with blood pressure in meta-analysis of single and aggregate rare variant findings (P<1×10-6 and P<1×10-4, respectively). DISCUSSION We report one promising but unconfirmed rare variant for blood pressure and, more importantly, contribute insights for future blood pressure sequencing studies. Our findings suggest promise of aggregate analyses to complement single variant analysis strategies and the need for larger, diverse samples, and family studies to enable robust rare variant identification.
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Affiliation(s)
- Tanika N Kelly
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
- Translational Sciences Institute (T.N.K., J.H.), Tulane University, New Orleans, LA
| | - Xiao Sun
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Karen Y He
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH (K.Y.H., X.Z.)
| | - Michael R Brown
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health (M.R.B., P.D.d.V., J.E.H., E.B., A.C.M.), The University of Texas Health Science Center at Houston' Houston' TX
| | - Sarah A Gagliano Taliun
- Department of Biostatistics (S.A.G.T., S.D., H.M.K., J.L., G.R.A.), University of Michigan, Ann Arbor' MI
| | - Jacklyn N Hellwege
- Division of Genetic Medicine, Department of Medicine (J.N.H.), Vanderbilt University Medical Center, Nashville, TN
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville' TN (J.N.H., A.G., A.M.H., T.L.E.)
| | - Marguerite R Irvin
- Department of Epidemiology (M.R.I., S.A., N.D.A.), University of Alabama at Birmingham' AL
| | - Xuenan Mi
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine (J.A.B., K.E.N.), University of Washington, Seattle' WA
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina, Chapel Hill (N.F.)
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance' CA (X.G., Y.-D.I.C., J.I.R., D.L.)
| | - Shih-Jen Hwang
- National Heart, Lung and Blood Institute, Population Sciences Branch, National Institutes of Health, Framingham, MA (S.-J.H.)
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health (M.R.B., P.D.d.V., J.E.H., E.B., A.C.M.), The University of Texas Health Science Center at Houston' Houston' TX
| | - Yan Gao
- Department of Physiology and Biophysics (Y.G., E.E.K., R.J.F.L.), University of Mississippi Medical Center, Jackson' MS
| | - Arden Moscati
- The Charles Bronfman Institute for Personalized Medicine (A.M., G.N.N.), The Icahn School of Medicine at Mount Sinai, New York, NY
| | - Girish N Nadkarni
- The Charles Bronfman Institute for Personalized Medicine (A.M., G.N.N.), The Icahn School of Medicine at Mount Sinai, New York, NY
- Department of Medicine (G.N.N.), The Icahn School of Medicine at Mount Sinai, New York, NY
| | - Lisa R Yanek
- Division of General Internal Medicine, Department of Medicine (L.R.Y., D.V.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Tali Elfassy
- Division of Epidemiology, Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami' FL (T.E.)
| | - Jennifer A Smith
- Department of Epidemiology (J.A.S., S.L.R.K.), University of Michigan, Ann Arbor' MI
| | - Ren-Hua Chung
- Institute of Population Sciences, National Health Research Institutes, Taiwan (R.-H.C.)
| | - Amber L Beitelshees
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore' MD (A.L.B., J.R.O., Y.-P.C.C., M.E.M., B.D.M.)
| | - Amit Patki
- Department of Biostatistics (A.P., V.S.), University of Alabama at Birmingham' AL
| | - Stella Aslibekyan
- Department of Epidemiology (M.R.I., S.A., N.D.A.), University of Alabama at Birmingham' AL
| | - Brandon M Blobner
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services (B.M.P.), University of Washington, Seattle' WA
- Department of Human Genetics (B.M.B., R.L.M., D.E.W.), University of Pittsburgh, PA
| | - Juan M Peralta
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville' TX (J.M.P., J.E.C., J.B.)
| | - Themistocles L Assimes
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford' CA (T.L.A.)
- Division of Cardiology Medicine, Palo Alto VA HealthCare System, Palo Alto' CA (T.L.A.)
| | - Walter R Palmas
- Division of General Medicine, Department of Medicine, Columbia University, New York, NY (W.R.P.)
| | - Chunyu Liu
- Department of Biostatistics, Boston University, Boston' MA (C.L.)
| | - Adam P Bress
- Division of Health System Innovation and Research, Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City' UT (A.P.B.)
| | - Zhijie Huang
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Lewis C Becker
- Division of Cardiology, Department of Medicine (L.C.B.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Chii-Min Hwa
- Taichung Veterans General Hospital, Taichung, Taiwan (C.-M.H.)
| | - Jeffrey R O'Connell
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore' MD (A.L.B., J.R.O., Y.-P.C.C., M.E.M., B.D.M.)
| | - Jenna C Carlson
- Department of Biostatistics, Graduate School of Public Health (J.C.C.), University of Pittsburgh, PA
| | - Helen R Warren
- Department of Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry (H.R.W., P.B.M.), Queen Mary University of London, United Kingdom
- National Institute for Health Research Barts Cardiovascular Biomedical Research Centre (H.R.W., P.B.M.), Queen Mary University of London, United Kingdom
| | - Sayantan Das
- Department of Biostatistics (S.A.G.T., S.D., H.M.K., J.L., G.R.A.), University of Michigan, Ann Arbor' MI
| | - Ayush Giri
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville' TN (J.N.H., A.G., A.M.H., T.L.E.)
- Division of Quantitative Sciences, Department of Obstetrics and Gynecology, Vanderbilt University, Nashville, TN (A.G.)
| | - Lisa W Martin
- Division of Cardiology, Department of Medicine, George Washington University, Washington, DC (L.W.M.)
| | - W Craig Johnson
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Ervin R Fox
- Division of Cardiology, Department of Medicine (E.R.F.), University of Mississippi Medical Center, Jackson' MS
| | - Erwin P Bottinger
- Hasso Plattner Institute for Digital Health at Mount Sinai (E.P.B.), The Icahn School of Medicine at Mount Sinai, New York, NY
| | - Alexander C Razavi
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Dhananjay Vaidya
- Division of General Internal Medicine, Department of Medicine (L.R.Y., D.V.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Lee-Ming Chuang
- Department of Internal Medicine, National Taiwan University Hospital, Taipei' Taiwan (L.-M.C.)
| | - Yen-Pei C Chang
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore' MD (A.L.B., J.R.O., Y.-P.C.C., M.E.M., B.D.M.)
| | - Take Naseri
- Ministry of Health, Government of Samoa, Apia' Samoa (T.N.)
| | - Deepti Jain
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Hyun Min Kang
- Department of Biostatistics (S.A.G.T., S.D., H.M.K., J.L., G.R.A.), University of Michigan, Ann Arbor' MI
| | - Adriana M Hung
- Division of Nephrology and Hypertension, Department of Medicine (A.M.H.), Vanderbilt University Medical Center, Nashville, TN
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville' TN (J.N.H., A.G., A.M.H., T.L.E.)
| | | | - Beverly M Snively
- Division of Public Health Sciences, Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC (B.M.S.)
| | - Dongfeng Gu
- Department of Epidemiology and Key Laboratory of Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (D.G., J.H.)
| | - May E Montasser
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore' MD (A.L.B., J.R.O., Y.-P.C.C., M.E.M., B.D.M.)
| | | | - Benjamin D Heavner
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Jonathon LeFaive
- Department of Biostatistics (S.A.G.T., S.D., H.M.K., J.L., G.R.A.), University of Michigan, Ann Arbor' MI
| | - James E Hixson
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health (M.R.B., P.D.d.V., J.E.H., E.B., A.C.M.), The University of Texas Health Science Center at Houston' Houston' TX
| | - Kenneth M Rice
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Fei Fei Wang
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Jonas B Nielsen
- Department of Internal Medicine: Cardiology (J.B.N.), University of Michigan, Ann Arbor' MI
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark (J.B.N.)
| | - Jianfeng Huang
- Translational Sciences Institute (T.N.K., J.H.), Tulane University, New Orleans, LA
- Department of Epidemiology and Key Laboratory of Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (D.G., J.H.)
| | - Alyna T Khan
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Wei Zhou
- Department of Computational Medicine and Bioinformatics (W.Z.), University of Michigan, Ann Arbor' MI
| | - Jovia L Nierenberg
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Cathy C Laurie
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Nicole D Armstrong
- Department of Epidemiology (M.R.I., S.A., N.D.A.), University of Alabama at Birmingham' AL
| | - Mengyao Shi
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Yang Pan
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Adrienne M Stilp
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Leslie Emery
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Quenna Wong
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Nicola L Hawley
- Department of Chronic Disease Epidemiology, Yale University, New Haven, CT (N.L.H.)
| | - Ryan L Minster
- Department of Human Genetics (B.M.B., R.L.M., D.E.W.), University of Pittsburgh, PA
| | - Joanne E Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville' TX (J.M.P., J.E.C., J.B.)
| | - Patricia B Munroe
- Department of Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry (H.R.W., P.B.M.), Queen Mary University of London, United Kingdom
- National Institute for Health Research Barts Cardiovascular Biomedical Research Centre (H.R.W., P.B.M.), Queen Mary University of London, United Kingdom
| | - Daniel E Weeks
- Department of Human Genetics (B.M.B., R.L.M., D.E.W.), University of Pittsburgh, PA
- Department of Biostatistics (D.E.W.), University of Pittsburgh, PA
| | - Kari E North
- Cardiovascular Health Research Unit, Department of Medicine (J.A.B., K.E.N.), University of Washington, Seattle' WA
| | - Russell P Tracy
- Department of Pathology & Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington' VT (R.P.T.)
| | - Eimear E Kenny
- Department of Physiology and Biophysics (Y.G., E.E.K., R.J.F.L.), University of Mississippi Medical Center, Jackson' MS
- Department of Genetics and Genomics (E.E.K.), The Icahn School of Medicine at Mount Sinai, New York, NY
| | - Daichi Shimbo
- Division of Cardiology, Department of Medicine, Columbia University Medical Center, New York, NY (D.S.)
| | - Aravinda Chakravarti
- Department of Medicine (A.C.), University of Mississippi Medical Center, Jackson' MS
| | - Stephen S Rich
- Center for Public Health, University of Virginia, Charlottesville' VA (S.S.R.)
| | - Alex P Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA (A.P.R., C.K.)
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville' TX (J.M.P., J.E.C., J.B.)
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA (S.R.)
| | - Braxton D Mitchell
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore' MD (A.L.B., J.R.O., Y.-P.C.C., M.E.M., B.D.M.)
- Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore' MD (B.D.M.)
| | - Dabeeru C Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO (D.C.R.)
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance' CA (X.G., Y.-D.I.C., J.I.R., D.L.)
| | - Sharon L R Kardia
- Department of Epidemiology (J.A.S., S.L.R.K.), University of Michigan, Ann Arbor' MI
| | - Robert C Kaplan
- Division of Social Medicine, Albert Einstein College of Medicine, Bronx, NY (R.C.K.)
| | - Rasika A Mathias
- Division of Allergy & Clinical Immunology, Department of Medicine (R.A.M.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Jiang He
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Bruce M Psaty
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
- Kaiser Permanente Washington Health Research Institute, Seattle' WA (B.M.P.)
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine (M.F.), The University of Texas Health Science Center at Houston' Houston' TX
- Human Genetics Center (M.F.), The University of Texas Health Science Center at Houston' Houston' TX
| | - Ruth J F Loos
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance' CA (X.G., Y.-D.I.C., J.I.R., D.L.)
- The Mindich Child Health and Development Institute (R.J.F.L.), The Icahn School of Medicine at Mount Sinai, New York, NY
| | - Adolfo Correa
- Center for Human Genetics and Genomics, New York University Grossman School of Medicine, New York, NY (A.C.)
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health (M.R.B., P.D.d.V., J.E.H., E.B., A.C.M.), The University of Texas Health Science Center at Houston' Houston' TX
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX (E.B.)
| | - 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 (X.G., Y.-D.I.C., J.I.R., D.L.)
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA (A.P.R., C.K.)
| | - Todd L Edwards
- Division of Epidemiology, Department of Medicine (T.L.E.), Vanderbilt University Medical Center, Nashville, TN
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville' TN (J.N.H., A.G., A.M.H., T.L.E.)
| | - Gonçalo R Abecasis
- Department of Biostatistics (S.A.G.T., S.D., H.M.K., J.L., G.R.A.), University of Michigan, Ann Arbor' MI
| | - Xiaofeng Zhu
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH (K.Y.H., X.Z.)
| | - Daniel Levy
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance' CA (X.G., Y.-D.I.C., J.I.R., D.L.)
| | - Donna K Arnett
- College of Public Health, University of Kentucky, Lexington, KY (D.K.A.)
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health (M.R.B., P.D.d.V., J.E.H., E.B., A.C.M.), The University of Texas Health Science Center at Houston' Houston' TX
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47
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Yun H, Sun L, Wu Q, Luo Y, Qi Q, Li H, Gu W, Wang J, Ning G, Zeng R, Zong G, Lin X. Lipidomic Signatures of Dairy Consumption and Associated Changes in Blood Pressure and Other Cardiovascular Risk Factors Among Chinese Adults. Hypertension 2022; 79:1617-1628. [PMID: 35469422 DOI: 10.1161/hypertensionaha.122.18981] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Omics data may provide a unique opportunity to discover dairy-related biomarkers and their linked cardiovascular health. METHODS Dairy-related lipidomic signatures were discovered in baseline data from a Chinese cohort study (n=2140) and replicated in another Chinese study (n=212). Dairy intake was estimated by a validated food-frequency questionnaire. Lipidomics was profiled by high-coverage liquid chromatography-tandem mass spectrometry. Associations of dairy-related lipids with 6-year changes in cardiovascular risk factors were examined in the discovery cohort, and their causalities were analyzed by 2-sample Mendelian randomization using available genome-wide summary data. RESULTS Of 350 lipid metabolites, 4 sphingomyelins, namely sphingomyelin (OH) C32:2, sphingomyelin C32:1, sphingomyelin (2OH) C30:2, and sphingomyelin (OH) C38:2, were identified and replicated to be positively associated with total dairy consumption (β=0.130 to 0.148; P<1.43×10-4), but not or weakly with nondairy food items. The score of 4 sphingomyelins showed inverse associations with 6-year changes in systolic (-2.68 [95% CI, -4.92 to -0.43]; P=0.019), diastolic blood pressures (-1.86 [95% CI, -3.12 to -0.61]; P=0.004), and fasting glucose (-0.25 [95% CI, -0.41 to -0.08]; P=0.003). Mendelian randomization analyses further revealed that genetically inferred sphingomyelin (OH) C32:2 was inversely associated with systolic (-0.57 [95% CI, -0.85 to -0.28]; P=9.16×10-5) and diastolic blood pressures (-0.39 [95% CI, -0.59 to -0.20]; P=7.09×10-5). CONCLUSIONS The beneficial effects of dairy products on cardiovascular health might be mediated through specific sphingomyelins among Chinese with overall low dairy consumption.
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Affiliation(s)
- Huan Yun
- Shanghai Institute of Nutrition and Health (H.Y., L.S., Y.L., H.L., G.Z., X.L.), University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Liang Sun
- Shanghai Institute of Nutrition and Health (H.Y., L.S., Y.L., H.L., G.Z., X.L.), University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Qingqing Wu
- CAS Key Laboratory of Systems Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, China (Q.W., R.Z.)
| | - Yaogan Luo
- Shanghai Institute of Nutrition and Health (H.Y., L.S., Y.L., H.L., G.Z., X.L.), University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Qibin Qi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY (Q.Q.)
| | - Huaixing Li
- Shanghai Institute of Nutrition and Health (H.Y., L.S., Y.L., H.L., G.Z., X.L.), University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Weiqiong Gu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China (W.G., J.W., G.N.).,Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China (W.G., J.W., G.N.)
| | - Jiqiu Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China (W.G., J.W., G.N.).,Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China (W.G., J.W., G.N.)
| | - Guang Ning
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China (W.G., J.W., G.N.).,Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China (W.G., J.W., G.N.)
| | - Rong Zeng
- Key Laboratory of Systems Biology, Hangzhou Institute for Advanced Study (R.Z., X.L.), University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.,Key Laboratory of Systems Health Science of Zhejiang Province, Hangzhou Institute for Advanced Study (R.Z., X.L.), University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.,CAS Key Laboratory of Systems Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, China (Q.W., R.Z.)
| | - Geng Zong
- Shanghai Institute of Nutrition and Health (H.Y., L.S., Y.L., H.L., G.Z., X.L.), University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Xu Lin
- Shanghai Institute of Nutrition and Health (H.Y., L.S., Y.L., H.L., G.Z., X.L.), University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.,Key Laboratory of Systems Biology, Hangzhou Institute for Advanced Study (R.Z., X.L.), University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.,Key Laboratory of Systems Health Science of Zhejiang Province, Hangzhou Institute for Advanced Study (R.Z., X.L.), University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
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48
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Khor BH, Komnenov D, Rossi NF. Impact of Dietary Fructose and High Salt Diet: Are Preclinical Studies Relevant to Asian Societies? Nutrients 2022; 14:2515. [PMID: 35745245 PMCID: PMC9227020 DOI: 10.3390/nu14122515] [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] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 06/08/2022] [Accepted: 06/11/2022] [Indexed: 02/01/2023] Open
Abstract
Fructose consumption, especially in food additives and sugar-sweetened beverages, has gained increasing attention due to its potential association with obesity and metabolic syndrome. The relationship between fructose and a high-salt diet, leading to hypertension and other deleterious cardiovascular parameters, has also become more evident, especially in preclinical studies. However, these studies have been modeled primarily on Western diets. The purpose of this review is to evaluate the dietary habits of individuals from China, Japan, and Korea, in light of the existing preclinical studies, to assess the potential relevance of existing data to East Asian societies. This review is not intended to be exhaustive, but rather to highlight the similarities and differences that should be considered in future preclinical, clinical, and epidemiologic studies regarding the impact of dietary fructose and salt on blood pressure and cardiovascular health worldwide.
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Affiliation(s)
- Ban Hock Khor
- Faculty of Food Science and Nutrition, Universiti Malaysia Sabah, Kota Kinabalu 88400, Malaysia;
| | - Dragana Komnenov
- Department of Internal Medicine, Wayne State University, Detroit, MI 48201, USA;
| | - Noreen F. Rossi
- Department of Internal Medicine, Wayne State University, Detroit, MI 48201, USA;
- Department of Physiology, Wayne State University, Detroit, MI 48201, USA
- Division of Research, John D. Dingell VA Medical Center, Detroit, MI 38201, USA
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49
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Zhang X, Lucas AM, Veturi Y, Drivas TG, Bone WP, Verma A, Chung WK, Crosslin D, Denny JC, Hebbring S, Jarvik GP, Kullo I, Larson EB, Rasmussen-Torvik LJ, Schaid DJ, Smoller JW, Stanaway IB, Wei WQ, Weng C, Ritchie MD. Large-scale genomic analyses reveal insights into pleiotropy across circulatory system diseases and nervous system disorders. Nat Commun 2022; 13:3428. [PMID: 35701404 PMCID: PMC9198016 DOI: 10.1038/s41467-022-30678-w] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Accepted: 05/10/2022] [Indexed: 01/18/2023] Open
Abstract
Clinical and epidemiological studies have shown that circulatory system diseases and nervous system disorders often co-occur in patients. However, genetic susceptibility factors shared between these disease categories remain largely unknown. Here, we characterized pleiotropy across 107 circulatory system and 40 nervous system traits using an ensemble of methods in the eMERGE Network and UK Biobank. Using a formal test of pleiotropy, five genomic loci demonstrated statistically significant evidence of pleiotropy. We observed region-specific patterns of direction of genetic effects for the two disease categories, suggesting potential antagonistic and synergistic pleiotropy. Our findings provide insights into the relationship between circulatory system diseases and nervous system disorders which can provide context for future prevention and treatment strategies.
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Affiliation(s)
- Xinyuan Zhang
- Department of Genetics and Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Genomics and Computational Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Anastasia M Lucas
- Department of Genetics and Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Yogasudha Veturi
- Department of Genetics and Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Theodore G Drivas
- Department of Genetics and Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - William P Bone
- Department of Genetics and Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Genomics and Computational Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Anurag Verma
- Department of Genetics and Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Wendy K Chung
- Department of Pediatrics and Medicine, Columbia University, New York, NY, 10032, USA
| | - David Crosslin
- Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, 98109, USA
| | - Joshua C Denny
- Department of Medicine, Vanderbilt University, Nashville, TN, 37235, USA
- Department of Biomedical Informatics, Vanderbilt University, Nashville, TN, 37230, USA
| | - Scott Hebbring
- Center for Human Genetics, Marshfield Clinic, Marshfield, WI, 54449, USA
| | - Gail P Jarvik
- Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, 98109, USA
| | - Iftikhar Kullo
- Division of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, 55905, USA
| | - Eric B Larson
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, 98101, USA
| | - Laura J Rasmussen-Torvik
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
| | - Daniel J Schaid
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, 55905, USA
| | - Jordan W Smoller
- Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Ian B Stanaway
- Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, 98109, USA
| | - Wei-Qi Wei
- Department of Biomedical Informatics, Vanderbilt University, Nashville, TN, 37230, USA
| | - Chunhua Weng
- Department of Biomedical Informatics, Columbia University, New York, NY, 10032, USA
| | - Marylyn D Ritchie
- Department of Genetics and Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
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50
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Dettwyler SA, Thull DL, McAuliffe PF, Steiman JG, Johnson RR, Diego EJ, Mai PL. Timely cancer genetic counseling and testing for young women with breast cancer: impact on surgical decision-making for contralateral risk-reducing mastectomy. Breast Cancer Res Treat 2022; 194:393-401. [PMID: 35596825 DOI: 10.1007/s10549-022-06619-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 04/25/2022] [Indexed: 01/02/2023]
Abstract
PURPOSE Genetic testing (GT) can identify individuals with pathogenic/likely pathogenic variants (PV/LPVs) in breast cancer (BC) predisposition genes, who may consider contralateral risk-reducing mastectomy (CRRM). We report on CRRM rates in young women newly diagnosed with BC who received GT through a multidisciplinary clinic. METHODS Clinical data were reviewed for patients seen between November 2014 and June 2019. Patients with non-metastatic, unilateral BC diagnosed at age ≤ 45 and completed GT prior to surgery were included. Associations between surgical intervention and age, BC stage, family history, and GT results were evaluated. RESULTS Of the 194 patients, 30 (15.5%) had a PV/LPV in a BC predisposition gene (ATM, BRCA1, BRCA2, CHEK2, NBN, NF1), with 66.7% in BRCA1 or BRCA2. Of 164 (84.5%) uninformative results, 132 (68%) were negative and 32 (16.5%) were variants of uncertain significance (VUS). Overall, 67 (34.5%) had CRRM, including 25/30 (83.3%) PV/LPV carriers and 42/164 (25.6%) non-carriers. A positive test result (p < 0.01) and significant family history were associated with CRRM (p = 0.02). For the 164 with uninformative results, multivariate analysis showed that CRRM was not associated with age (p = 0.23), a VUS, (p = 0.08), family history (p = 0.10), or BC stage (p = 0.11). CONCLUSION In this cohort of young women with BC, the identification of a PV/LPV in a BC predisposition gene and a significant family history were associated with the decision to pursue CRRM. Thus, incorporation of genetic services in the initial evaluation of young patients with a new BC could contribute to the surgical decision-making process.
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Affiliation(s)
- Shenin A Dettwyler
- UPMC Magee-Womens Hospital (Cancer Genetics Program), Pittsburgh, PA, USA. .,Currently at NYU Langone Health (The Pancreatic Cancer Center), New York, NY, USA.
| | - Darcy L Thull
- UPMC Magee-Womens Hospital (Cancer Genetics Program), Pittsburgh, PA, USA
| | | | - Jennifer G Steiman
- UPMC Magee-Womens Hospital (Magee-Womens Surgical Associates), Pittsburgh, PA, USA
| | - Ronald R Johnson
- UPMC Magee-Womens Hospital (Magee-Womens Surgical Associates), Pittsburgh, PA, USA
| | - Emilia J Diego
- UPMC Magee-Womens Hospital (Magee-Womens Surgical Associates), Pittsburgh, PA, USA
| | - Phuong L Mai
- University of Pittsburgh School of Medicine (Center for Clinical Genetics and Genomics), Pittsburgh, PA, USA
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