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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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202
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Lin JS, Petrera A, Hauck SM, Müller CL, Peters A, Thorand B. Associations of Proteomics With Hypertension and Systolic Blood Pressure: KORA S4/F4/FF4 and KORA Age1/Age2 Cohort Studies. Hypertension 2024; 81:1156-1166. [PMID: 38445514 PMCID: PMC11025610 DOI: 10.1161/hypertensionaha.123.22614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Accepted: 02/19/2024] [Indexed: 03/07/2024]
Abstract
BACKGROUND Hypertension, a complex condition, is primarily defined based on blood pressure readings without involving its pathophysiological mechanisms. We aimed to identify biomarkers through a proteomic approach, thereby enhancing the future definition of hypertension with insights into its molecular mechanisms. METHODS The discovery analysis included 1560 participants, aged 55 to 74 years at baseline, from the KORA (Cooperative Health Research in the Region of Augsburg) S4/F4/FF4 cohort study, with 3332 observations over a median of 13.4 years of follow-up. Generalized estimating equations were used to estimate the associations of 233 plasma proteins with hypertension and systolic blood pressure (SBP). For validation, proteins significantly associated with hypertension or SBP in the discovery analysis were validated in the KORA Age1/Age2 cohort study (1024 participants, 1810 observations). A 2-sample Mendelian randomization analysis was conducted to infer causalities of validated proteins with SBP. RESULTS Discovery analysis identified 49 proteins associated with hypertension and 99 associated with SBP. Validation in the KORA Age1/Age2 study replicated 7 proteins associated with hypertension and 23 associated with SBP. Three proteins, NT-proBNP (N-terminal pro-B-type natriuretic peptide), KIM1 (kidney injury molecule 1), and OPG (osteoprotegerin), consistently showed positive associations with both outcomes. Five proteins demonstrated potential causal associations with SBP in Mendelian randomization analysis, including NT-proBNP and OPG. CONCLUSIONS We identified and validated 7 hypertension-associated and 23 SBP-associated proteins across 2 cohort studies. KIM1, NT-proBNP, and OPG demonstrated robust associations, and OPG was identified for the first time as associated with blood pressure. For NT-proBNP (protective) and OPG, causal associations with SBP were suggested.
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Affiliation(s)
- Jie-sheng Lin
- Institute of Epidemiology (J.-s.L., A. Peters, B.T.), Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Pettenkofer School of Public Health, Munich, Germany (J.-s.L., B.T.)
| | - Agnese Petrera
- Metabolomics and Proteomics Core (A. Petrera, S.M.H.), Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Stefanie M. Hauck
- Metabolomics and Proteomics Core (A. Petrera, S.M.H.), Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Christian L. Müller
- Institute of Computational Biology (C.L.M.), Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Department of Statistics (C.L.M.), Ludwig-Maximilians-Universität München, Munich, Germany
- Center for Computational Mathematics, Flatiron Institute, New York, NY (C.L.M.)
| | - Annette Peters
- Institute of Epidemiology (J.-s.L., A. Peters, B.T.), Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty (A. Peters), Ludwig-Maximilians-Universität München, Munich, Germany
- German Center for Diabetes Research, Partner München-Neuherberg, Germany (A. Peters, B.T.)
| | - Barbara Thorand
- Institute of Epidemiology (J.-s.L., A. Peters, B.T.), Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Pettenkofer School of Public Health, Munich, Germany (J.-s.L., B.T.)
- German Center for Diabetes Research, Partner München-Neuherberg, Germany (A. Peters, B.T.)
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203
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Landfors F, Henneman P, Chorell E, Nilsson SK, Kersten S. Drug-target Mendelian randomization analysis supports lowering plasma ANGPTL3, ANGPTL4, and APOC3 levels as strategies for reducing cardiovascular disease risk. EUROPEAN HEART JOURNAL OPEN 2024; 4:oeae035. [PMID: 38895109 PMCID: PMC11182694 DOI: 10.1093/ehjopen/oeae035] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 03/30/2024] [Accepted: 04/26/2024] [Indexed: 06/21/2024]
Abstract
Aims APOC3, ANGPTL3, and ANGPTL4 are circulating proteins that are actively pursued as pharmacological targets to treat dyslipidaemia and reduce the risk of atherosclerotic cardiovascular disease. Here, we used human genetic data to compare the predicted therapeutic and adverse effects of APOC3, ANGPTL3, and ANGPTL4 inactivation. Methods and results We conducted drug-target Mendelian randomization analyses using variants in proximity to the genes associated with circulating protein levels to compare APOC3, ANGPTL3, and ANGPTL4 as drug targets. We obtained exposure and outcome data from large-scale genome-wide association studies and used generalized least squares to correct for linkage disequilibrium-related correlation. We evaluated five primary cardiometabolic endpoints and screened for potential side effects across 694 disease-related endpoints, 43 clinical laboratory tests, and 11 internal organ MRI measurements. Genetically lowering circulating ANGPTL4 levels reduced the odds of coronary artery disease (CAD) [odds ratio, 0.57 per s.d. protein (95% CI 0.47-0.70)] and Type 2 diabetes (T2D) [odds ratio, 0.73 per s.d. protein (95% CI 0.57-0.94)]. Genetically lowering circulating APOC3 levels also reduced the odds of CAD [odds ratio, 0.90 per s.d. protein (95% CI 0.82-0.99)]. Genetically lowered ANGPTL3 levels via common variants were not associated with CAD. However, meta-analysis of protein-truncating variants revealed that ANGPTL3 inactivation protected against CAD (odds ratio, 0.71 per allele [95%CI, 0.58-0.85]). Analysis of lowered ANGPTL3, ANGPTL4, and APOC3 levels did not identify important safety concerns. Conclusion Human genetic evidence suggests that therapies aimed at reducing circulating levels of ANGPTL3, ANGPTL4, and APOC3 reduce the risk of CAD. ANGPTL4 lowering may also reduce the risk of T2D.
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Affiliation(s)
- Fredrik Landfors
- Department of Public Health and Clinical Medicine, Section of Medicine, Umeå University, B41, Norrlands universitetssjukhus, S-901 87 Umeå, Sweden
- Lipigon Pharmaceuticals AB, Tvistevägen 48C, S-907 36 Umeå, Sweden
| | - Peter Henneman
- Department of Human Genetics, Amsterdam University Medical Center, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
| | - Elin Chorell
- Department of Public Health and Clinical Medicine, Section of Medicine, Umeå University, B41, Norrlands universitetssjukhus, S-901 87 Umeå, Sweden
| | - Stefan K Nilsson
- Lipigon Pharmaceuticals AB, Tvistevägen 48C, S-907 36 Umeå, Sweden
- Department of Medical Biosciences, Umeå University, B41, Norrlands universitetssjukhus, S-901 87 Umeå, Sweden
| | - Sander Kersten
- Nutrition, Metabolism, and Genomics group, Division of Human Nutrition and Health, Wageningen University, 6708WE Wageningen, the Netherlands
- Division of Nutritional Sciences, Cornell University, Ithaca, NY 14853, USA
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204
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Abou-Karam R, Cheng F, Gady S, Fahed AC. The Role of Genetics in Advancing Cardiometabolic Drug Development. Curr Atheroscler Rep 2024; 26:153-162. [PMID: 38451435 DOI: 10.1007/s11883-024-01195-6] [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] [Accepted: 02/22/2024] [Indexed: 03/08/2024]
Abstract
PURPOSE OF REVIEW The objective of this review is to explore the role of genetics in cardiometabolic drug development. The declining costs of sequencing and the availability of large-scale genomic data have deepened our understanding of cardiometabolic diseases, revolutionizing drug discovery and development methodologies. We highlight four key areas in which genetics is empowering drug development for cardiometabolic disease: (1) identifying drug candidates, (2) anticipating drug target failures, (3) silencing and editing genes, and (4) enriching clinical trials. RECENT FINDINGS Identifying novel drug targets through genetic discovery studies and the use of genetic variants as indicators of potential drug efficacy and safety have become critical components of cardiometabolic drug discovery. We highlight the successes of genetically-informed therapeutic strategies, such as PCSK9 and ANGPTL3 inhibitors in lipid lowering and the emerging role of polygenic risk scores in improving the efficiency of clinical trials. Additionally, we explore the potential of gene silencing and editing technologies, such as antisense oligonucleotides and small interfering RNA, showcasing their promise in addressing diseases refractory to conventional treatments. In this review, we highlight four use cases that demonstrate the vital role of genetics in cardiometabolic drug development: (1) identifying drug candidates, (2) anticipating drug target failures, (3) silencing and editing genes, and (4) enriching clinical trials. Through these advances, genetics has paved the way to increased efficiency of drug development as well as the discovery of more personalized and effective treatments for cardiometabolic disease.
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Affiliation(s)
- Roukoz Abou-Karam
- Cardiovascular Research Center, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, 185 Cambridge Street|CPZN 3.128, Boston, MA, 02114, USA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Fangzhou Cheng
- Cardiovascular Research Center, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, 185 Cambridge Street|CPZN 3.128, Boston, MA, 02114, USA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Shoshana Gady
- Cardiovascular Research Center, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, 185 Cambridge Street|CPZN 3.128, Boston, MA, 02114, USA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Akl C Fahed
- Cardiovascular Research Center, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, 185 Cambridge Street|CPZN 3.128, Boston, MA, 02114, USA.
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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205
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Hezekiah C, Blakemore AI, Bailey DP, Pazoki R. Physical activity alters the effect of genetic determinants of adiposity on hypertension among individuals of European ancestry in the UKB. Scand J Med Sci Sports 2024; 34:e14636. [PMID: 38671551 PMCID: PMC11135603 DOI: 10.1111/sms.14636] [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: 01/25/2024] [Revised: 03/30/2024] [Accepted: 04/09/2024] [Indexed: 04/28/2024]
Abstract
Hypertension is a leading risk factor for cardiovascular disease and is modulated by genetic variants. This study aimed to assess the effect of obesity genetic liability and physical activity on hypertension among European and African ancestry individuals within the UK Biobank (UKB). Participants were 230 115 individuals of European ancestry and 3239 individuals of African ancestry from UKB. Genetic liability for obesity were estimated using previously published data including genetic variants and effect sizes for body mass index (BMI), waist-hip ratio (WHR) and waist circumference (WC) using Plink software. The outcome was defined as stage 2 hypertension (systolic blood pressure ≥ 140 mmHg, diastolic blood pressure ≥90 mmHg, or the use of anti-hypertensive medications). The association between obesity genetic liability and the outcome was assessed across categories of self-reported physical activity using logistic regression. Among European ancestry participants, there was up to a 1.2 greater odds of hypertension in individuals with high genetic liability and low physical activity compared to individuals with low genetic liability and high physical activity (p < 0.001). In individuals engaging in low levels of physical activity compared with moderate/high physical activity, the effect of BMI genetic liability on hypertension was greater (p interaction = 0.04). There was no evidence of an association between obesity genetic liability and hypertension in individuals of African ancestry in the whole sample or within separate physical activity groups (p > 0.05). This study suggests that higher physical activity levels are associated with lower odds of stage 2 hypertension among European ancestry individuals who carry high genetic liability for obesity. This cannot be inferred for individuals of African ancestry, possibly due to the low African ancestry sample size within the UKB.
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Affiliation(s)
- Chukwueloka Hezekiah
- Cardiovascular and Metabolic Research Group, Division of Biomedical Sciences, Department of Life Sciences, College of Health, Medicine and Life SciencesBrunel University LondonLondonUK
- Department of Mental Health, Faculty of Health, Science, Social Care and EducationKingston UniversitySurreyUK
| | - Alexandra I. Blakemore
- Department of Life Sciences, Centre for Cognitive Neuroscience, College of Health, Medicine and Life SciencesBrunel University LondonLondonUK
- Department of MetabolismDigestion and Reproduction, Imperial College LondonLondonUK
- School of MedicineUniversity of IrelandGalwayIreland
| | - Daniel P. Bailey
- Centre for Physical Activity in Health and Disease, College of Health, Medicine and Life SciencesBrunel University LondonUxbridgeUK
- Division of Sport, Health and Exercise Sciences, Department of Life SciencesBrunel University LondonUxbridgeUK
| | - Raha Pazoki
- Cardiovascular and Metabolic Research Group, Division of Biomedical Sciences, Department of Life Sciences, College of Health, Medicine and Life SciencesBrunel University LondonLondonUK
- Department of Epidemiology and Biostatistics, School of Public HealthImperial College LondonLondonUK
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206
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Mani A. Update in genetic and epigenetic causes of hypertension. Cell Mol Life Sci 2024; 81:201. [PMID: 38691164 PMCID: PMC11062952 DOI: 10.1007/s00018-024-05220-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Revised: 03/27/2024] [Accepted: 03/29/2024] [Indexed: 05/03/2024]
Abstract
Hypertension is a heritable disease that affects one-fourth of the population and accounts for about 50% of cardiovascular deaths. The genetic basis of hypertension is multifaceted, involving both monogenic and most commonly complex polygenic forms. With the advent of the human genome project, genome-wide association studies (GWAS) have identified a plethora of loci linked to hypertension by examining common genetic variations. It's notable, however, that the majority of these genetic variants do not affect the protein-coding sequences, posing a considerable obstacle in pinpointing the actual genes responsible for hypertension. Despite these challenges, precise mapping of GWAS-identified loci is emerging as a promising strategy to reveal novel genes and potential targets for the pharmacological management of blood pressure. This review provides insight into the monogenic and polygenic causes of hypertension. Special attention is given to PRDM6, among the earliest functionally characterized GWAS-identified genes. Moreover, this review delves into the roles of genes contributing to renal and vascular forms of hypertension, offering insights into their genetic and epigenetic mechanisms of action.
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Affiliation(s)
- Arya Mani
- Department of Internal Medicine, Yale University School of Medicine, Yale Cardiovascular Research Center, 300 George Street, New Haven, CT, 06511, USA.
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA.
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207
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Zhang J, Lu H, Cao M, Zhang J, Liu D, Meng X, Zheng D, Wu L, Liu X, Wang Y. Metabolic Traits and Risk of Ischemic Stroke in Japanese and European Populations: A Two-Sample Mendelian Randomization Study. Metabolites 2024; 14:255. [PMID: 38786732 PMCID: PMC11123267 DOI: 10.3390/metabo14050255] [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: 03/04/2024] [Revised: 04/11/2024] [Accepted: 04/22/2024] [Indexed: 05/25/2024] Open
Abstract
The role of metabolic traits in ischemic stroke (IS) has been explored through observational studies and a few Mendelian randomization (MR) studies employing limited methods in European populations. This study aimed to investigate the causal effects of metabolic traits on IS in both East Asian and European populations utilizing multiple MR methods based on genetic insights. Two-sample and multivariable MR were performed, and MR estimates were calculated as inverse-variance weighted (IVW), weighted median, and penalized weighted median. Pleiotropy was assessed by MR-Egger and Mendelian randomization pleiotropy residual sum and outlier tests. Systolic blood pressure (SBP) was associated with an increased risk of IS by IVW in both European (ORIVW: 1.032, 95% CI: 1.026-1.038, p < 0.001) and Japanese populations (ORIVW: 1.870, 95% CI: 1.122-3.116, p = 0.016), which was further confirmed by other methods. Unlike the European population, the evidence for the association of diastolic blood pressure (DBP) with IS in the Japanese population was not stable. No evidence supported an association between the other traits and IS (all Ps > 0.05) in both races. A positive association was found between SBP and IS in two races, while the results of DBP were only robust in Europeans.
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Affiliation(s)
- Jinxia Zhang
- School of Public Health, Capital Medical University, Beijing 100069, China; (J.Z.); (H.L.); (M.C.); (J.Z.); (X.M.); (D.Z.); (L.W.)
- Beijing Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing 100069, China
| | - Huimin Lu
- School of Public Health, Capital Medical University, Beijing 100069, China; (J.Z.); (H.L.); (M.C.); (J.Z.); (X.M.); (D.Z.); (L.W.)
- Beijing Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing 100069, China
| | - Mingyang Cao
- School of Public Health, Capital Medical University, Beijing 100069, China; (J.Z.); (H.L.); (M.C.); (J.Z.); (X.M.); (D.Z.); (L.W.)
- Beijing Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing 100069, China
| | - Jie Zhang
- School of Public Health, Capital Medical University, Beijing 100069, China; (J.Z.); (H.L.); (M.C.); (J.Z.); (X.M.); (D.Z.); (L.W.)
- Beijing Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing 100069, China
| | - Di Liu
- Centre for Biomedical Information Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Xiaoni Meng
- School of Public Health, Capital Medical University, Beijing 100069, China; (J.Z.); (H.L.); (M.C.); (J.Z.); (X.M.); (D.Z.); (L.W.)
- Beijing Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing 100069, China
| | - Deqiang Zheng
- School of Public Health, Capital Medical University, Beijing 100069, China; (J.Z.); (H.L.); (M.C.); (J.Z.); (X.M.); (D.Z.); (L.W.)
- Beijing Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing 100069, China
| | - Lijuan Wu
- School of Public Health, Capital Medical University, Beijing 100069, China; (J.Z.); (H.L.); (M.C.); (J.Z.); (X.M.); (D.Z.); (L.W.)
- Beijing Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing 100069, China
| | - Xiangdong Liu
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100069, China
| | - Youxin Wang
- School of Public Health, Capital Medical University, Beijing 100069, China; (J.Z.); (H.L.); (M.C.); (J.Z.); (X.M.); (D.Z.); (L.W.)
- Beijing Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing 100069, China
- School of Public Health, North China University of Science and Technology, Tangshan 063210, China
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208
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Beito MR, Ashraf S, Odogwu D, Harmancey R. Role of Ectopic Olfactory Receptors in the Regulation of the Cardiovascular-Kidney-Metabolic Axis. Life (Basel) 2024; 14:548. [PMID: 38792570 PMCID: PMC11122380 DOI: 10.3390/life14050548] [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: 04/02/2024] [Revised: 04/19/2024] [Accepted: 04/22/2024] [Indexed: 05/26/2024] Open
Abstract
Olfactory receptors (ORs) represent one of the largest yet least investigated families of G protein-coupled receptors in mammals. While initially believed to be functionally restricted to the detection and integration of odors at the olfactory epithelium, accumulating evidence points to a critical role for ectopically expressed ORs in the regulation of cellular homeostasis in extranasal tissues. This review aims to summarize the current state of knowledge on the expression and physiological functions of ectopic ORs in the cardiovascular system, kidneys, and primary metabolic organs and emphasizes how altered ectopic OR signaling in those tissues may impact cardiovascular-kidney-metabolic health.
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Affiliation(s)
| | | | | | - Romain Harmancey
- Division of Cardiology, Department of Internal Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA; (M.R.B.); (S.A.); (D.O.)
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209
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Øvretveit K, Ingeström EML, Spitieris M, Tragante V, Wade KH, Thomas LF, Wolford BN, Wisløff U, Gudbjartsson DF, Holm H, Stefansson K, Brumpton BM, Hveem K. Polygenic risk scores associate with blood pressure traits across the lifespan. Eur J Prev Cardiol 2024; 31:644-654. [PMID: 38007706 PMCID: PMC11025038 DOI: 10.1093/eurjpc/zwad365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 10/18/2023] [Accepted: 11/02/2023] [Indexed: 11/28/2023]
Abstract
AIMS Hypertension is a major modifiable cause of morbidity and mortality that affects over 1 billion people worldwide. Blood pressure (BP) traits have a strong genetic component that can be quantified with polygenic risk scores (PRSs). To date, the performance of BP PRSs has mainly been assessed in adults, and less is known about polygenic hypertension risk in childhood. METHODS AND RESULTS Multiple PRSs for systolic BP (SBP), diastolic BP (DBP), and pulse pressure were developed using either genome-wide significant weights, pruning and thresholding, or Bayesian regression. Among 87 total PRSs, the top performer for each trait was applied in independent cohorts of children and adult to assess genotype-phenotype associations and disease risk across the lifespan. Differences between those with low (1st decile), average (2nd-9th decile), and high (10th decile) PRS emerge in the first years of life and are maintained throughout adulthood. These diverging BP trajectories also seem to affect cardiovascular and renal disease risk, with increased risk observed among those in the top decile and reduced risk among those in the bottom decile of the polygenic risk distribution compared with the rest of the population. CONCLUSION Genetic risk factors are associated with BP traits across the lifespan, beginning in the first years of life. Given the importance of exposure time in disease pathogenesis and the early rise in BP levels among those genetically susceptible, PRSs may help identify high-risk individuals prior to hypertension onset, facilitate primordial prevention, and reduce the burden of this public health challenge.
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Affiliation(s)
- Karsten Øvretveit
- K.G. Jebsen Centre for Genetic Epidemiology, Faculty of Medicine and Health Sciences, Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Postboks 8905, N-7491 Trondheim, Norway
| | - Emma M L Ingeström
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Michail Spitieris
- K.G. Jebsen Centre for Genetic Epidemiology, Faculty of Medicine and Health Sciences, Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Postboks 8905, N-7491 Trondheim, Norway
- Department of Mathematical Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | | | - Kaitlin H Wade
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 1TH, UK
- Population Health Science, Bristol Medical School, Bristol BS8 1TH, UK
- Avon Longitudinal Study of Parents and Children, Bristol BS8 1TH, UK
| | - Laurent F Thomas
- K.G. Jebsen Centre for Genetic Epidemiology, Faculty of Medicine and Health Sciences, Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Postboks 8905, N-7491 Trondheim, Norway
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Brooke N Wolford
- K.G. Jebsen Centre for Genetic Epidemiology, Faculty of Medicine and Health Sciences, Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Postboks 8905, N-7491 Trondheim, Norway
| | - Ulrik Wisløff
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Daniel F Gudbjartsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Hilma Holm
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
| | - Kari Stefansson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Ben M Brumpton
- K.G. Jebsen Centre for Genetic Epidemiology, Faculty of Medicine and Health Sciences, Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Postboks 8905, N-7491 Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway
| | - Kristian Hveem
- K.G. Jebsen Centre for Genetic Epidemiology, Faculty of Medicine and Health Sciences, Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Postboks 8905, N-7491 Trondheim, Norway
- Department of Innovation and Research, St. Olavs Hospital, Trondheim, Norway
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210
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Churnosov M. Special Issue: "Genes and Human Diseases". Int J Mol Sci 2024; 25:4455. [PMID: 38674038 PMCID: PMC11050120 DOI: 10.3390/ijms25084455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2024] [Accepted: 04/17/2024] [Indexed: 04/28/2024] Open
Abstract
Studying mechanisms of development and the causes of various human diseases continues to be the focus of attention of various researchers [...].
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Affiliation(s)
- Mikhail Churnosov
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia
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211
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Türkmen D, Bowden J, Masoli JAH, Delgado J, Kuo CL, Melzer D, Pilling LC. Polygenic scores for cardiovascular risk factors improve estimation of clinical outcomes in CCB treatment compared to pharmacogenetic variants alone. THE PHARMACOGENOMICS JOURNAL 2024; 24:12. [PMID: 38632276 PMCID: PMC11023935 DOI: 10.1038/s41397-024-00333-2] [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: 11/16/2023] [Revised: 04/08/2024] [Accepted: 04/10/2024] [Indexed: 04/19/2024]
Abstract
Pharmacogenetic variants are associated with clinical outcomes during Calcium Channel Blocker (CCB) treatment, yet whether the effects are modified by genetically predicted clinical risk factors is unknown. We analyzed 32,000 UK Biobank participants treated with dihydropiridine CCBs (mean 5.9 years), including 23 pharmacogenetic variants, and calculated polygenic scores for systolic and diastolic blood pressures, body fat mass, and other patient characteristics. Outcomes included treatment discontinuation and heart failure. Pharmacogenetic variant rs10898815-A (NUMA1) increased discontinuation rates, highest in those with high polygenic scores for fat mass. The RYR3 variant rs877087 T-allele alone modestly increased heart failure risks versus non-carriers (HR:1.13, p = 0.02); in patients with high polygenic scores for fat mass, lean mass, and lipoprotein A, risks were substantially elevated (HR:1.55, p = 4 × 10-5). Incorporating polygenic scores for adiposity and lipoprotein A may improve risk estimates of key clinical outcomes in CCB treatment such as treatment discontinuation and heart failure, compared to pharmacogenetic variants alone.
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Affiliation(s)
- Deniz Türkmen
- Epidemiology & Public Health Group, Department of Clinical & Biomedical Science, Faculty of Health & Life Sciences, University of Exeter, Exeter, UK
| | - Jack Bowden
- Exeter Diabetes Group (ExCEED), Department of Clinical & Biomedical Science, Faculty of Health & Life Sciences, University of Exeter, Exeter, UK
- Department of Genetics, Novo Nordisk Research Centre Oxford, Innovation Building, Old Road Campus, Roosevelt Drive, Oxford, UK
| | - Jane A H Masoli
- Epidemiology & Public Health Group, Department of Clinical & Biomedical Science, Faculty of Health & Life Sciences, University of Exeter, Exeter, UK
- Department of Healthcare for Older People, Royal Devon University Healthcare NHS Foundation Trust, Barrack Road, Exeter, UK
| | - João Delgado
- Epidemiology & Public Health Group, Department of Clinical & Biomedical Science, Faculty of Health & Life Sciences, University of Exeter, Exeter, UK
| | - Chia-Ling Kuo
- UConn Center on Aging, University of Connecticut, Farmington, CT, USA
- Connecticut Convergence Institute for Translation in Regenerative Engineering, University of Connecticut, Storrs, CT, USA
| | - David Melzer
- Epidemiology & Public Health Group, Department of Clinical & Biomedical Science, Faculty of Health & Life Sciences, University of Exeter, Exeter, UK
| | - Luke C Pilling
- Epidemiology & Public Health Group, Department of Clinical & Biomedical Science, Faculty of Health & Life Sciences, University of Exeter, Exeter, UK.
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212
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Cao M, Cui B. Clinically relevant plasma proteome for adiposity depots: evidence from systematic mendelian randomization and colocalization analyses. Cardiovasc Diabetol 2024; 23:126. [PMID: 38614964 PMCID: PMC11016216 DOI: 10.1186/s12933-024-02222-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Accepted: 03/31/2024] [Indexed: 04/15/2024] Open
Abstract
BACKGROUND The accumulation of visceral and ectopic fat comprise a major cause of cardiometabolic diseases. However, novel drug targets for reducing unnecessary visceral and ectopic fat are still limited. Our study aims to provide a comprehensive investigation of the causal effects of the plasma proteome on visceral and ectopic fat using Mendelian randomization (MR) approach. METHODS We performed two-sample MR analyses based on five large genome-wide association study (GWAS) summary statistics of 2656 plasma proteins, to screen for causal associations of these proteins with traits of visceral and ectopic fat in over 30,000 participants of European ancestry, as well as to assess mediation effects by risk factors of outcomes. The colocalization analysis was conducted to examine whether the identified proteins and outcomes shared casual variants. RESULTS Genetically predicted levels of 14 circulating proteins were associated with visceral and ectopic fat (P < 4.99 × 10- 5, at a Bonferroni-corrected threshold). Colocalization analysis prioritized ten protein targets that showed effect on outcomes, including FST, SIRT2, DNAJB9, IL6R, CTSA, RGMB, PNLIPRP1, FLT4, PPY and IL6ST. MR analyses revealed seven risk factors for visceral and ectopic fat (P < 0.0024). Furthermore, the associations of CTSA, DNAJB9 and IGFBP1 with primary outcomes were mediated by HDL-C and SHBG. Sensitivity analyses showed little evidence of pleiotropy. CONCLUSIONS Our study identified candidate proteins showing putative causal effects as potential therapeutic targets for visceral and ectopic fat accumulation and outlined causal pathways for further prevention of downstream cardiometabolic diseases.
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Affiliation(s)
- Min Cao
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- 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 Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Bin Cui
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- 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 Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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213
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Sadler MC, Apostolov A, Cevallos C, Ribeiro DM, Altman RB, Kutalik Z. Leveraging large-scale biobank EHRs to enhance pharmacogenetics of cardiometabolic disease medications. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.06.24305415. [PMID: 38633781 PMCID: PMC11023668 DOI: 10.1101/2024.04.06.24305415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/19/2024]
Abstract
Electronic health records (EHRs) coupled with large-scale biobanks offer great promises to unravel the genetic underpinnings of treatment efficacy. However, medication-induced biomarker trajectories stemming from such records remain poorly studied. Here, we extract clinical and medication prescription data from EHRs and conduct GWAS and rare variant burden tests in the UK Biobank (discovery) and the All of Us program (replication) on ten cardiometabolic drug response outcomes including lipid response to statins, HbA1c response to metformin and blood pressure response to antihypertensives (N = 740-26,669). Our findings at genome-wide significance level recover previously reported pharmacogenetic signals and also include novel associations for lipid response to statins (N = 26,669) near LDLR and ZNF800. Importantly, these associations are treatment-specific and not associated with biomarker progression in medication-naive individuals. Furthermore, we demonstrate that individuals with higher genetically determined low-density and total cholesterol baseline levels experience increased absolute, albeit lower relative biomarker reduction following statin treatment. In summary, we systematically investigated the common and rare pharmacogenetic contribution to cardiometabolic drug response phenotypes in over 50,000 UK Biobank and All of Us participants with EHR and identified clinically relevant genetic predictors for improved personalized treatment strategies.
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Affiliation(s)
- Marie C. Sadler
- University Center for Primary Care and Public Health, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Alexander Apostolov
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Caterina Cevallos
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
| | - Diogo M. Ribeiro
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Russ B. Altman
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Zoltán Kutalik
- University Center for Primary Care and Public Health, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
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214
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Zeng L, Li Y, Hong C, Wang J, Zhu H, Li Q, Cui H, Ma P, Li R, He J, Zhu H, Liu L, Xiao L. Association between fatty liver index and controlled attenuation parameters as markers of metabolic dysfunction-associated fatty liver disease and bone mineral density: observational and two-sample Mendelian randomization studies. Osteoporos Int 2024; 35:679-689. [PMID: 38221591 DOI: 10.1007/s00198-023-06996-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 12/04/2023] [Indexed: 01/16/2024]
Abstract
Previously observational studies did not draw a clear conclusion on the association between fatty liver diseases and bone mineral density (BMD). Our large-scale studies revealed that MAFLD and hepatic steatosis had no causal effect on BMD, while some metabolic factors were correlated with BMD. The findings have important implications for the relationship between fatty liver diseases and BMD, and may help direct the clinical management of MAFLD patients who experience osteoporosis and osteopenia. PURPOSE Liver and bone are active endocrine organs with several metabolic functions. However, the link between metabolic dysfunction-associated fatty liver disease (MAFLD) and bone mineral density (BMD) is contradictory. METHODS Using the UK Biobank and National Health and Nutrition Examination Survey (NHANES) dataset, we investigated the association between MAFLD, steatosis, and BMD in the observational analysis. We performed genome-wide association analysis to identify single-nucleotide polymorphisms associated with MAFLD. Large-scale two-sample Mendelian randomization (TSMR) analyses examined the potential causal relationship between MAFLD, hepatic steatosis, or major comorbid metabolic factors, and BMD. RESULTS After adjusting for demographic factors and body mass index, logistic regression analysis demonstrated a significant association between MAFLD and reduced heel BMD. However, this association disappeared after adjusting for additional metabolic factors. MAFLD was not associated with total body, femur neck, and lumbar BMD in the NHANES dataset. Magnetic resonance imaging-measured steatosis did not show significant associations with reduced total body, femur neck, and lumbar BMD in multivariate analysis. TSMR analyses indicated that MAFLD and hepatic steatosis were not associated with BMD. Among all MAFLD-related comorbid factors, overweight and type 2 diabetes showed a causal relationship with increased BMD, while waist circumference and hyperlipidemia had the opposite effect. CONCLUSION No causal effect of MAFLD and hepatic steatosis on BMD was observed in this study, while some metabolic factors were correlated with BMD. This has important implications for understanding the relationship between fatty liver disease and BMD, which may help direct the clinical management of MAFLD patients with osteoporosis.
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Affiliation(s)
- Lin Zeng
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
- Big Data Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Yan Li
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Chang Hong
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Jiaren Wang
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Hongbo Zhu
- Department of Medical Oncology, the First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, 421001, Hunan Province, China
| | - Qimei Li
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Hao Cui
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Pengcheng Ma
- Big Data Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Ruining Li
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Jingzhe He
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Hong Zhu
- Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
| | - Li Liu
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
- Big Data Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
| | - Lushan Xiao
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
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215
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Wu O, Wu Y, Zhang X, Liu W, Zhang H, Khederzadeh S, Lu X, Zhu XW. Causal effect of interleukin (IL)-6 on blood pressure and hypertension: A mendelian randomization study. Immunogenetics 2024; 76:123-135. [PMID: 38427105 DOI: 10.1007/s00251-024-01332-0] [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: 10/12/2023] [Accepted: 01/11/2024] [Indexed: 03/02/2024]
Abstract
To examine whether circulating interleukin-6 (IL-6) levels (CirIL6) have a causal effect on blood pressure using Mendelian randomization (MR) methods. We used data from genome-wide association studies (GWAS) of European ancestry to obtain genetic instruments for circulating IL-6 levels and blood pressure measurements. We applied several robust MR methods to estimate the causal effects and to test for heterogeneity and pleiotropy. We found that circulating IL-6 had a significant positive causal effect on systolic blood pressure (SBP) and pulmonary arterial hypertension (PAH), but not on diastolic blood pressure (DBP) or hypertension. We found that as CirIL6 genetically increased, SBP increased using Inverse Variance Weighted (IVW) method (for ukb-b-20175, β = 0.082 with SE = 0.032, P = 0.011; for ukb-a-360, β = 0.075 with SE = 0.031, P = 0.014) and weighted median (WM) method (for ukb-b-20175, β = 0.061 with SE = 0.022, P = 0.006; for ukb-a-360, β = 0.065 with SE = 0.027, P = 0.014). Moreover, CirIL6 may be associated with an increased risk of PAH using WM method (odds ratio (OR) = 15.503, 95% CI, 1.025-234.525, P = 0.048), but not with IVW method. Our study provides novel evidence that circulating IL-6 has a causal role in the development of SBP and PAH, but not DBP or hypertension. These findings suggest that IL-6 may be a potential therapeutic target for preventing or treating cardiovascular diseases and metabolic disorders. However, more studies are needed to confirm the causal effects of IL-6 on blood pressure and to elucidate the underlying mechanisms and pathways.
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Affiliation(s)
- Ou Wu
- Shulan International Medical College, Zhejiang Shuren University, Hangzhou, Zhejiang, People's Republic of China.
- Zhejiang Chinese Medical University, Hangzhou, Zhejiang, People's Republic of China.
| | - Ya Wu
- Anhui Medical University, Hefei, Anhui, People's Republic of China
| | - Xingyu Zhang
- Thomas E. Starzl Transplantation Institute, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Wei Liu
- JFIntelligent Healthcare Technology Co., Ltd Building No.5-7, No.699 Tianxiang Avenue, Hi-Tech Zone, Nanchang, Jiangxi Province, People's Republic of China
| | - Hu Zhang
- Department of Thoracic Surgery, Sir Run Run Shaw Hospital Affiliated with Medical College of Zhejiang University, Hangzhou, Zhejiang, People's Republic of China
| | - Saber Khederzadeh
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, People's Republic of China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, People's Republic of China
| | - Xi Lu
- Hangzhou Vocational and Technical College, Hangzhou, Zhejiang, People's Republic of China.
| | - Xiao-Wei Zhu
- School of Medicine, Shaoxing University, Shaoxing, Zhejiang, People's Republic of China.
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216
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Chen SD, You J, Zhang W, Wu BS, Ge YJ, Xiang ST, Du J, Kuo K, Banaschewski T, Barker GJ, Bokde ALW, Desrivières S, Flor H, Grigis A, Garavan H, Gowland P, Heinz A, Brühl R, Martinot JL, Martinot MLP, Artiges E, Nees F, Orfanos DP, Lemaitre H, Paus T, Poustka L, Hohmann S, Millenet S, Baeuchl C, Smolka MN, Vaidya N, Walter H, Whelan R, Schumann G, Feng JF, Dong Q, Cheng W, Yu JT. The genetic architecture of the human hypothalamus and its involvement in neuropsychiatric behaviours and disorders. Nat Hum Behav 2024; 8:779-793. [PMID: 38182882 DOI: 10.1038/s41562-023-01792-6] [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: 02/06/2023] [Accepted: 11/20/2023] [Indexed: 01/07/2024]
Abstract
Despite its crucial role in the regulation of vital metabolic and neurological functions, the genetic architecture of the hypothalamus remains unknown. Here we conducted multivariate genome-wide association studies (GWAS) using hypothalamic imaging data from 32,956 individuals to uncover the genetic underpinnings of the hypothalamus and its involvement in neuropsychiatric traits. There were 23 significant loci associated with the whole hypothalamus and its subunits, with functional enrichment for genes involved in intracellular trafficking systems and metabolic processes of steroid-related compounds. The hypothalamus exhibited substantial genetic associations with limbic system structures and neuropsychiatric traits including chronotype, risky behaviour, cognition, satiety and sympathetic-parasympathetic activity. The strongest signal in the primary GWAS, the ADAMTS8 locus, was replicated in three independent datasets (N = 1,685-4,321) and was strengthened after meta-analysis. Exome-wide association analyses added evidence to the association for ADAMTS8, and Mendelian randomization showed lower ADAMTS8 expression with larger hypothalamic volumes. The current study advances our understanding of complex structure-function relationships of the hypothalamus and provides insights into the molecular mechanisms that underlie hypothalamic formation.
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Affiliation(s)
- Shi-Dong Chen
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
| | - Jia You
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Wei Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Bang-Sheng Wu
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
| | - Yi-Jun Ge
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
| | - Shi-Tong Xiang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Jing Du
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Kevin Kuo
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Gareth J Barker
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Sylvane Desrivières
- Institute of Psychiatry, Psychology & Neuroscience, Social, Genetic, Developmental Psychiatry Centre, King's College London, London, UK
| | - Herta Flor
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Department of Psychology, School of Social Sciences, University of Mannheim, Mannheim, Germany
| | - Antoine Grigis
- NeuroSpin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Hugh Garavan
- Departments of Psychiatry and Psychology, University of Vermont, Burlington, VT, USA
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy CCM, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Rüdiger Brühl
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U 1299 "Trajectoires développementales & psychiatrie", University Paris-Saclay, CNRS, Ecole Normale Supérieure Paris-Saclay, Centre Borelli, Gif-sur-Yvette, France
| | - Marie-Laure Paillère Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U 1299 "Trajectoires développementales & psychiatrie", University Paris-Saclay, CNRS, Ecole Normale Supérieure Paris-Saclay, Centre Borelli, Gif-sur-Yvette, France
- AP-HP, Sorbonne University, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Paris, France
| | - Eric Artiges
- Institut National de la Santé et de la Recherche Médicale, INSERM U 1299 "Trajectoires développementales & psychiatrie", University Paris-Saclay, CNRS, Ecole Normale Supérieure Paris-Saclay, Centre Borelli, Gif-sur-Yvette, France
- Psychiatry Department, EPS Barthélémy Durand, Etampes, France
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig Holstein, Kiel University, Kiel, Germany
| | | | - Herve Lemaitre
- NeuroSpin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
- Institut des Maladies Neurodégénératives, UMR 5293, CNRS, CEA, Université de Bordeaux, Bordeaux, France
| | - Tomáš Paus
- Departments of Psychiatry and Neuroscience, Faculty of Medicine and Centre Hosptalier Universitaire Sainte-Justine, University of Montreal, Montreal, Quebec, Canada
- Departments of Psychiatry and Psychology, University of Toronto, Toronto, Ontario, Canada
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, Göttingen, Germany
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry, Psychotherapy and Psychosomatics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Sabina Millenet
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Christian Baeuchl
- Department of Psychiatry and Psychotherapy, Technische Universität Dresden, Dresden, Germany
| | - Michael N Smolka
- Department of Psychiatry and Psychotherapy, Technische Universität Dresden, Dresden, Germany
| | - Nilakshi Vaidya
- Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Neuroscience, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy CCM, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Gunter Schumann
- Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Neuroscience, Charité Universitätsmedizin Berlin, Berlin, Germany
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, China
| | - Jian-Feng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China.
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China.
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
- Zhangjiang Fudan International Innovation Center, Shanghai, China.
| | - Qiang Dong
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China.
| | - Wei Cheng
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China.
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China.
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China.
- Shanghai Medical College and Zhongshan Hospital Immunotherapy Technology Transfer Center, Shanghai, China.
| | - Jin-Tai Yu
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China.
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217
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Tian G, Zhou R, Guo X, Li R. Causal effects of blood pressure and the risk of frailty: a bi-directional two-sample Mendelian randomization study. J Hum Hypertens 2024; 38:329-335. [PMID: 38361027 DOI: 10.1038/s41371-024-00901-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Revised: 02/02/2024] [Accepted: 02/05/2024] [Indexed: 02/17/2024]
Abstract
Observational studies have indicated that high blood pressure (BP) may be a risk factor to frailty. However, the causal association between BP and frailty remains not well determined. The purpose of this bi-directional two-sample Mendelian randomization (MR) study was to investigate the causal relationship between BP and frailty. Independent single nucleotide polymorphisms (SNPs) strongly (P < 5E-08) associated with systolic BP (SBP), diastolic BP (DBP), and pulse pressure (PP) were selected as instrumental variables. Two different published genome-wide association studies (GWAS) on BP from the CHARGE (n = 810,865) and ICBP (n = 757,601) consortia were included. Summary-level data on frailty index (FI) were obtained from the latest GWAS based on UK Biobank and Swedish TwinGene cohorts (n = 175,226). Inverse variance weighted (IVW) approach with other sensitivity analyses were used to calculate the causal estimate. Using the CHARGE dataset, genetic predisposition to increased SBP (β = 0.135, 95% CI = 0.093 to 0.176, P = 1.73E-10), DBP (β = 0.145, 95% CI = 0.104 to 0.186, P = 3.14E-12), and PP (β = 0.114, 95% CI = 0.070 to 0.157, p = 2.87E-07) contributed to a higher FI, which was validated in the ICBP dataset. There was no significant causal effect of FI on SBP, DBP, and PP. Similar results were obtained from different MR methods, indicating good stability. There was potential heterogeneity detected by Cochran's Q test, but no horizontal pleiotropy was observed in MR-Egger intercept test (P > 0.05). These findings evinced that higher BP and PP were causally associated with an increased risk of frailty, suggesting that controlling hypertension could reduce the risk of frailty.
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Affiliation(s)
- Ge Tian
- Xi'an Medical University, Xi'an, 710021, Shaanxi, China
- Department of Geriatric Neurology, Shaanxi Provincial People's Hospital, Xi'an, 710068, Shaanxi, China
| | - Rong Zhou
- Department of Geriatric Neurology, Shaanxi Provincial People's Hospital, Xi'an, 710068, Shaanxi, China
| | - Xingzhi Guo
- Department of Geriatric Neurology, Shaanxi Provincial People's Hospital, Xi'an, 710068, Shaanxi, China.
| | - Rui Li
- Xi'an Medical University, Xi'an, 710021, Shaanxi, China.
- Department of Geriatric Neurology, Shaanxi Provincial People's Hospital, Xi'an, 710068, Shaanxi, China.
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218
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Magavern EF, Kapil V, Saxena M, Gupta A, Caulfield MJ. Use of Genomics to Develop Novel Therapeutics and Personalize Hypertension Therapy. Arterioscler Thromb Vasc Biol 2024; 44:784-793. [PMID: 38385287 DOI: 10.1161/atvbaha.123.319220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/23/2024]
Abstract
Hypertension is a prevalent public health problem, contributing to >10 million deaths annually. Though multiple therapeutics exist, many patients suffer from treatment-resistant hypertension or try several medications before achieving blood pressure control. Genomic advances offer mechanistic understanding of blood pressure variability, therapeutic targets, therapeutic response, and promise a stratified approach to treatment of primary hypertension. Cyclic guanosine monophosphate augmentation, aldosterone synthase inhibitors, and angiotensinogen blockade with silencing RNA and antisense therapies are among the promising novel approaches. Pharmacogenomic studies have also been done to explore the genetic bases underpinning interindividual variability in response to existing therapeutics. A polygenic approach using risk scores is likely to be the next frontier in stratifying responses to existing therapeutics.
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Affiliation(s)
- Emma F Magavern
- Centre of Clinical Pharmacology and Precision Medicine, William Harvey Research Institute, Queen Mary University of London, Charterhouse Square, United Kingdom
| | - Vikas Kapil
- Centre of Clinical Pharmacology and Precision Medicine, William Harvey Research Institute, Queen Mary University of London, Charterhouse Square, United Kingdom
| | - Manish Saxena
- Centre of Clinical Pharmacology and Precision Medicine, William Harvey Research Institute, Queen Mary University of London, Charterhouse Square, United Kingdom
| | - Ajay Gupta
- Centre of Clinical Pharmacology and Precision Medicine, William Harvey Research Institute, Queen Mary University of London, Charterhouse Square, United Kingdom
| | - Mark J Caulfield
- Centre of Clinical Pharmacology and Precision Medicine, William Harvey Research Institute, Queen Mary University of London, Charterhouse Square, United Kingdom
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Reay WR, Clarke E, Eslick S, Riveros C, Holliday EG, McEvoy MA, Peel R, Hancock S, Scott RJ, Attia JR, Collins CE, Cairns MJ. Using Genetics to Inform Interventions Related to Sodium and Potassium in Hypertension. Circulation 2024; 149:1019-1032. [PMID: 38131187 PMCID: PMC10962430 DOI: 10.1161/circulationaha.123.065394] [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: 05/02/2023] [Accepted: 11/28/2023] [Indexed: 12/23/2023]
Abstract
BACKGROUND Hypertension is a key risk factor for major adverse cardiovascular events but remains difficult to treat in many individuals. Dietary interventions are an effective approach to lower blood pressure (BP) but are not equally effective across all individuals. BP is heritable, and genetics may be a useful tool to overcome treatment response heterogeneity. We investigated whether the genetics of BP could be used to identify individuals with hypertension who may receive a particular benefit from lowering sodium intake and boosting potassium levels. METHODS In this observational genetic study, we leveraged cross-sectional data from up to 296 475 genotyped individuals drawn from the UK Biobank cohort for whom BP and urinary electrolytes (sodium and potassium), biomarkers of sodium and potassium intake, were measured. Biologically directed genetic scores for BP were constructed specifically among pathways related to sodium and potassium biology (pharmagenic enrichment scores), as well as unannotated genome-wide scores (conventional polygenic scores). We then tested whether there was a gene-by-environment interaction between urinary electrolytes and these genetic scores on BP. RESULTS Genetic risk and urinary electrolytes both independently correlated with BP. However, urinary sodium was associated with a larger BP increase among individuals with higher genetic risk in sodium- and potassium-related pathways than in those with comparatively lower genetic risk. For example, each SD in urinary sodium was associated with a 1.47-mm Hg increase in systolic BP for those in the top 10% of the distribution of genetic risk in sodium and potassium transport pathways versus a 0.97-mm Hg systolic BP increase in the lowest 10% (P=1.95×10-3). This interaction with urinary sodium remained when considering estimated glomerular filtration rate and indexing sodium to urinary creatinine. There was no strong evidence of an interaction between urinary sodium and a standard genome-wide polygenic score of BP. CONCLUSIONS The data suggest that genetic risk in sodium and potassium pathways could be used in a precision medicine model to direct interventions more specifically in the management of hypertension. Intervention studies are warranted.
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Affiliation(s)
- William R. Reay
- Schools of Biomedical Sciences and Pharmacy (W.R.R., R.J.S., M.J.C.), The University of Newcastle, Callaghan, NSW, Australia
- Precision Medicine Research Program (W.R.R., M.J.C.), New Lambton, NSW, Australia
| | - Erin Clarke
- Health Sciences (E.C., S.E., C.E.C.), The University of Newcastle, Callaghan, NSW, Australia
- Food and Nutrition Research Program (E.C., C.E.C.), New Lambton, NSW, Australia
| | - Shaun Eslick
- Health Sciences (E.C., S.E., C.E.C.), The University of Newcastle, Callaghan, NSW, Australia
| | - Carlos Riveros
- Hunter Medical Research Institute (C.R., E.G.H., J.R.A.), New Lambton, NSW, Australia
| | - Elizabeth G. Holliday
- Medicine and Public Health (E.G.H., R.P., S.H., J.R.A.), The University of Newcastle, Callaghan, NSW, Australia
- Hunter Medical Research Institute (C.R., E.G.H., J.R.A.), New Lambton, NSW, Australia
| | - Mark A. McEvoy
- Rural Health School, La Trobe University, Bendigo, Victoria, Australia (M.A.M.)
| | - Roseanne Peel
- Medicine and Public Health (E.G.H., R.P., S.H., J.R.A.), The University of Newcastle, Callaghan, NSW, Australia
| | - Stephen Hancock
- Medicine and Public Health (E.G.H., R.P., S.H., J.R.A.), The University of Newcastle, Callaghan, NSW, Australia
| | - Rodney J. Scott
- Schools of Biomedical Sciences and Pharmacy (W.R.R., R.J.S., M.J.C.), The University of Newcastle, Callaghan, NSW, Australia
- Cancer Detection and Therapy Research Program (R.J.S.), New Lambton, NSW, Australia
| | - John R. Attia
- Medicine and Public Health (E.G.H., R.P., S.H., J.R.A.), The University of Newcastle, Callaghan, NSW, Australia
- Hunter Medical Research Institute (C.R., E.G.H., J.R.A.), New Lambton, NSW, Australia
| | - Clare E. Collins
- Health Sciences (E.C., S.E., C.E.C.), The University of Newcastle, Callaghan, NSW, Australia
- Food and Nutrition Research Program (E.C., C.E.C.), New Lambton, NSW, Australia
| | - Murray J. Cairns
- Schools of Biomedical Sciences and Pharmacy (W.R.R., R.J.S., M.J.C.), The University of Newcastle, Callaghan, NSW, Australia
- Precision Medicine Research Program (W.R.R., M.J.C.), New Lambton, NSW, Australia
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Mirzaei S, DeVon HA, Cantor RM, Cupido AJ, Pan C, Ha SM, Silva LF, Hilser JR, Hartiala J, Allayee H, Rey FE, Laakso M, Lusis AJ. Relationships and Mendelian Randomization of Gut Microbe-Derived Metabolites with Metabolic Syndrome Traits in the METSIM Cohort. Metabolites 2024; 14:174. [PMID: 38535334 PMCID: PMC10972019 DOI: 10.3390/metabo14030174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Revised: 03/13/2024] [Accepted: 03/15/2024] [Indexed: 07/17/2024] Open
Abstract
The role of gut microbe-derived metabolites in the development of metabolic syndrome (MetS) remains unclear. This study aimed to evaluate the associations of gut microbe-derived metabolites and MetS traits in the cross-sectional Metabolic Syndrome In Men (METSIM) study. The sample included 10,194 randomly related men (age 57.65 ± 7.12 years) from Eastern Finland. Levels of 35 metabolites were tested for associations with 13 MetS traits using lasso and stepwise regression. Significant associations were observed between multiple MetS traits and 32 metabolites, three of which exhibited particularly robust associations. N-acetyltryptophan was positively associated with Homeostatic Model Assessment for Insulin Resistant (HOMA-IR) (β = 0.02, p = 0.033), body mass index (BMI) (β = 0.025, p = 1.3 × 10-16), low-density lipoprotein cholesterol (LDL-C) (β = 0.034, p = 5.8 × 10-10), triglyceride (0.087, p = 1.3 × 10-16), systolic (β = 0.012, p = 2.5 × 10-6) and diastolic blood pressure (β = 0.011, p = 3.4 × 10-6). In addition, 3-(4-hydroxyphenyl) lactate yielded the strongest positive associations among all metabolites, for example, with HOMA-IR (β = 0.23, p = 4.4 × 10-33), and BMI (β = 0.097, p = 5.1 × 10-52). By comparison, 3-aminoisobutyrate was inversely associated with HOMA-IR (β = -0.19, p = 3.8 × 10-51) and triglycerides (β = -0.12, p = 5.9 × 10-36). Mendelian randomization analyses did not provide evidence that the observed associations with these three metabolites represented causal relationships. We identified significant associations between several gut microbiota-derived metabolites and MetS traits, consistent with the notion that gut microbes influence metabolic homeostasis, beyond traditional risk factors.
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Affiliation(s)
- Sahereh Mirzaei
- Department of Medicine, Division of Cardiology, David Geffen School of Medicine, University of California, Los Angeles, CA 90055, USA
- School of Nursing, University of California, Los Angeles, CA 90095, USA
| | - Holli A. DeVon
- School of Nursing, University of California, Los Angeles, CA 90095, USA
| | - Rita M. Cantor
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Arjen J. Cupido
- Department of Vascular Medicine, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam Cardiovascular Sciences, 1007 AZ Amsterdam, The Netherlands
| | - Calvin Pan
- Department of Medicine, Division of Cardiology, David Geffen School of Medicine, University of California, Los Angeles, CA 90055, USA
| | - Sung Min Ha
- Department of Integrative Biology and Physiology, University of California, Los Angeles, CA 90095, USA
| | - Lilian Fernandes Silva
- Department of Medicine, Division of Cardiology, David Geffen School of Medicine, University of California, Los Angeles, CA 90055, USA
- Department of Clinical Medicine, Internal Medicine, University of Eastern Finland, 70210 Kuopio, Finland
| | - James R. Hilser
- Department of Population & Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA
- Department of Biochemistry & Molecular Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Jaana Hartiala
- Department of Population & Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA
| | - Hooman Allayee
- Department of Population & Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA
- Department of Biochemistry & Molecular Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Federico E. Rey
- Department of Bacteriology, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Markku Laakso
- Department of Clinical Medicine, Internal Medicine, University of Eastern Finland, 70210 Kuopio, Finland
| | - Aldons J. Lusis
- Department of Medicine, Division of Cardiology, David Geffen School of Medicine, University of California, Los Angeles, CA 90055, USA
- Department of Human Genetics and Microbiology, Immunology & Molecular Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
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221
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Xu X, Khunsriraksakul C, Eales JM, Rubin S, Scannali D, Saluja S, Talavera D, Markus H, Wang L, Drzal M, Maan A, Lay AC, Prestes PR, Regan J, Diwadkar AR, Denniff M, Rempega G, Ryszawy J, Król R, Dormer JP, Szulinska M, Walczak M, Antczak A, Matías-García PR, Waldenberger M, Woolf AS, Keavney B, Zukowska-Szczechowska E, Wystrychowski W, Zywiec J, Bogdanski P, Danser AHJ, Samani NJ, Guzik TJ, Morris AP, Liu DJ, Charchar FJ, Tomaszewski M. Genetic imputation of kidney transcriptome, proteome and multi-omics illuminates new blood pressure and hypertension targets. Nat Commun 2024; 15:2359. [PMID: 38504097 PMCID: PMC10950894 DOI: 10.1038/s41467-024-46132-y] [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: 07/26/2023] [Accepted: 02/14/2024] [Indexed: 03/21/2024] Open
Abstract
Genetic mechanisms of blood pressure (BP) regulation remain poorly defined. Using kidney-specific epigenomic annotations and 3D genome information we generated and validated gene expression prediction models for the purpose of transcriptome-wide association studies in 700 human kidneys. We identified 889 kidney genes associated with BP of which 399 were prioritised as contributors to BP regulation. Imputation of kidney proteome and microRNAome uncovered 97 renal proteins and 11 miRNAs associated with BP. Integration with plasma proteomics and metabolomics illuminated circulating levels of myo-inositol, 4-guanidinobutanoate and angiotensinogen as downstream effectors of several kidney BP genes (SLC5A11, AGMAT, AGT, respectively). We showed that genetically determined reduction in renal expression may mimic the effects of rare loss-of-function variants on kidney mRNA/protein and lead to an increase in BP (e.g., ENPEP). We demonstrated a strong correlation (r = 0.81) in expression of protein-coding genes between cells harvested from urine and the kidney highlighting a diagnostic potential of urinary cell transcriptomics. We uncovered adenylyl cyclase activators as a repurposing opportunity for hypertension and illustrated examples of BP-elevating effects of anticancer drugs (e.g. tubulin polymerisation inhibitors). Collectively, our studies provide new biological insights into genetic regulation of BP with potential to drive clinical translation in hypertension.
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Affiliation(s)
- Xiaoguang Xu
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | | | - James M Eales
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Sebastien Rubin
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - David Scannali
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Sushant Saluja
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - David Talavera
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Havell Markus
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Lida Wang
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Maciej Drzal
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Akhlaq Maan
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Abigail C Lay
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Priscilla R Prestes
- Health Innovation and Transformation Centre, Federation University Australia, Ballarat, Australia
| | - Jeniece Regan
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Avantika R Diwadkar
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Matthew Denniff
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
| | - Grzegorz Rempega
- Department of Urology, Medical University of Silesia, Katowice, Poland
| | - Jakub Ryszawy
- Department of Urology, Medical University of Silesia, Katowice, Poland
| | - Robert Król
- Department of General, Vascular and Transplant Surgery, Faculty of Medical Sciences in Katowice, Medical University of Silesia, Katowice, Poland
| | - John P Dormer
- Department of Cellular Pathology, University Hospitals of Leicester, Leicester, UK
| | - Monika Szulinska
- Department of Obesity, Metabolic Disorders Treatment and Clinical Dietetics, Karol Marcinkowski University of Medical Sciences, Poznan, Poland
| | - Marta Walczak
- Department of Internal Diseases, Metabolic Disorders and Arterial Hypertension, Poznan University of Medical Sciences, Poznan, Poland
| | - Andrzej Antczak
- Department of Urology and Uro-oncology, Karol Marcinkowski University of Medical Sciences, Poznan, Poland
| | - Pamela R Matías-García
- Institute of Epidemiology, Helmholtz Center Munich, Neuherberg, Germany
- Research Unit Molecular Epidemiology, Helmholtz Center Munich, Neuherberg, Germany
- German Research Center for Cardiovascular Disease (DZHK), partner site Munich Heart Alliance, Munich, Germany
| | - Melanie Waldenberger
- Institute of Epidemiology, Helmholtz Center Munich, Neuherberg, Germany
- Research Unit Molecular Epidemiology, Helmholtz Center Munich, Neuherberg, Germany
- German Research Center for Cardiovascular Disease (DZHK), partner site Munich Heart Alliance, Munich, Germany
| | - Adrian S Woolf
- Division of Cell Matrix Biology and Regenerative Medicine, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- Royal Manchester Children's Hospital and Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust, Manchester, UK
| | - Bernard Keavney
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
- Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust Manchester, Manchester Royal Infirmary, Manchester, UK
| | | | - Wojciech Wystrychowski
- Department of General, Vascular and Transplant Surgery, Faculty of Medical Sciences in Katowice, Medical University of Silesia, Katowice, Poland
| | - Joanna Zywiec
- Department of Internal Medicine, Diabetology and Nephrology, Zabrze, Medical University of Silesia, Katowice, Poland
| | - Pawel Bogdanski
- Department of Obesity, Metabolic Disorders Treatment and Clinical Dietetics, Karol Marcinkowski University of Medical Sciences, Poznan, Poland
| | - A H Jan Danser
- Department of Internal Medicine, Division of Pharmacology and Vascular Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Tomasz J Guzik
- Department of Internal Medicine, Jagiellonian University Medical College, Kraków, Poland
- Centre for Cardiovascular Sciences, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
- Center for Medical Genomics OMICRON, Jagiellonian University Medical College, Kraków, Poland
| | - Andrew P Morris
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal & Dermatological Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Dajiang J Liu
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Fadi J Charchar
- Health Innovation and Transformation Centre, Federation University Australia, Ballarat, Australia
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- Department of Physiology, University of Melbourne, Melbourne, Australia
| | - Maciej Tomaszewski
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK.
- Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust Manchester, Manchester Royal Infirmary, Manchester, UK.
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222
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Thériault S, Li Z, Abner E, Luan J, Manikpurage HD, Houessou U, Zamani P, Briend M, Boudreau DK, Gaudreault N, Frenette L, Argaud D, Dahmene M, Dagenais F, Clavel MA, Pibarot P, Arsenault BJ, Boekholdt SM, Wareham NJ, Esko T, Mathieu P, Bossé Y. Integrative genomic analyses identify candidate causal genes for calcific aortic valve stenosis involving tissue-specific regulation. Nat Commun 2024; 15:2407. [PMID: 38494474 PMCID: PMC10944835 DOI: 10.1038/s41467-024-46639-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Accepted: 03/05/2024] [Indexed: 03/19/2024] Open
Abstract
There is currently no medical therapy to prevent calcific aortic valve stenosis (CAVS). Multi-omics approaches could lead to the identification of novel molecular targets. Here, we perform a genome-wide association study (GWAS) meta-analysis including 14,819 cases among 941,863 participants of European ancestry. We report 32 genomic loci, among which 20 are novel. RNA sequencing of 500 human aortic valves highlights an enrichment in expression regulation at these loci and prioritizes candidate causal genes. Homozygous genotype for a risk variant near TWIST1, a gene involved in endothelial-mesenchymal transition, has a profound impact on aortic valve transcriptomics. We identify five genes outside of GWAS loci by combining a transcriptome-wide association study, colocalization, and Mendelian randomization analyses. Using cross-phenotype and phenome-wide approaches, we highlight the role of circulating lipoproteins, blood pressure and inflammation in the disease process. Our findings pave the way for the development of novel therapies for CAVS.
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Affiliation(s)
- Sébastien Thériault
- Institut universitaire de cardiologie et de pneumologie de Québec-Université Laval, Quebec City, QC, Canada.
- Department of Molecular Biology, Medical Biochemistry and Pathology, Université Laval, Quebec City, QC, Canada.
| | - Zhonglin Li
- Institut universitaire de cardiologie et de pneumologie de Québec-Université Laval, Quebec City, QC, Canada
| | - Erik Abner
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Jian'an Luan
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
| | - Hasanga D Manikpurage
- Institut universitaire de cardiologie et de pneumologie de Québec-Université Laval, Quebec City, QC, Canada
| | - Ursula Houessou
- Institut universitaire de cardiologie et de pneumologie de Québec-Université Laval, Quebec City, QC, Canada
| | - Pardis Zamani
- Institut universitaire de cardiologie et de pneumologie de Québec-Université Laval, Quebec City, QC, Canada
| | - Mewen Briend
- Institut universitaire de cardiologie et de pneumologie de Québec-Université Laval, Quebec City, QC, Canada
| | - Dominique K Boudreau
- Institut universitaire de cardiologie et de pneumologie de Québec-Université Laval, Quebec City, QC, Canada
| | - Nathalie Gaudreault
- Institut universitaire de cardiologie et de pneumologie de Québec-Université Laval, Quebec City, QC, Canada
| | - Lily Frenette
- Institut universitaire de cardiologie et de pneumologie de Québec-Université Laval, Quebec City, QC, Canada
| | - Déborah Argaud
- Institut universitaire de cardiologie et de pneumologie de Québec-Université Laval, Quebec City, QC, Canada
| | - Manel Dahmene
- Institut universitaire de cardiologie et de pneumologie de Québec-Université Laval, Quebec City, QC, Canada
| | - François Dagenais
- Institut universitaire de cardiologie et de pneumologie de Québec-Université Laval, Quebec City, QC, Canada
- Department of Surgery, Université Laval, Quebec City, QC, Canada
| | - Marie-Annick Clavel
- Institut universitaire de cardiologie et de pneumologie de Québec-Université Laval, Quebec City, QC, Canada
- Department of Medicine, Université Laval, Quebec City, QC, Canada
| | - Philippe Pibarot
- Institut universitaire de cardiologie et de pneumologie de Québec-Université Laval, Quebec City, QC, Canada
- Department of Medicine, Université Laval, Quebec City, QC, Canada
| | - Benoit J Arsenault
- Institut universitaire de cardiologie et de pneumologie de Québec-Université Laval, Quebec City, QC, Canada
- Department of Medicine, Université Laval, Quebec City, QC, Canada
| | - S Matthijs Boekholdt
- Department of Cardiology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Nicholas J Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
| | - Tõnu Esko
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Patrick Mathieu
- Institut universitaire de cardiologie et de pneumologie de Québec-Université Laval, Quebec City, QC, Canada
- Department of Surgery, Université Laval, Quebec City, QC, Canada
| | - Yohan Bossé
- Institut universitaire de cardiologie et de pneumologie de Québec-Université Laval, Quebec City, QC, Canada
- Department of Molecular Medicine, Université Laval, Quebec City, QC, Canada
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Li Y, Xue F, Li B, Yang Y, Fan Z, Shu J, Yang X, Wang X, Lin J, Copana C, Zhao B. Analyzing bivariate cross-trait genetic architecture in GWAS summary statistics with the BIGA cloud computing platform. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.04.28.538585. [PMID: 38559152 PMCID: PMC10979906 DOI: 10.1101/2023.04.28.538585] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
As large-scale biobanks provide increasing access to deep phenotyping and genomic data, genome-wide association studies (GWAS) are rapidly uncovering the genetic architecture behind various complex traits and diseases. GWAS publications typically make their summary-level data (GWAS summary statistics) publicly available, enabling further exploration of genetic overlaps between phenotypes gathered from different studies and cohorts. However, systematically analyzing high-dimensional GWAS summary statistics for thousands of phenotypes can be both logistically challenging and computationally demanding. In this paper, we introduce BIGA (https://bigagwas.org/), a website that aims to offer unified data analysis pipelines and processed data resources for cross-trait genetic architecture analyses using GWAS summary statistics. We have developed a framework to implement statistical genetics tools on a cloud computing platform, combined with extensive curated GWAS data resources. Through BIGA, users can upload data, submit jobs, and share results, providing the research community with a convenient tool for consolidating GWAS data and generating new insights.
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Affiliation(s)
- Yujue Li
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA
| | - Fei Xue
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA
| | - Bingxuan Li
- Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA
| | - Yilin Yang
- Department of Computer and Information Science and Electrical and Systems Engineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Zirui Fan
- Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, PA 19104, 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
| | - Xiyao Wang
- Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA
| | - Jinjie Lin
- Yale School of Management, Yale University, New Haven, CT 06511, USA
| | - Carlos Copana
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA
| | - Bingxin Zhao
- Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Applied Mathematics and Computational Science Graduate Group, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for AI and Data Science for Integrated Diagnostics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Penn Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Population Aging Research Center, University of Pennsylvania, Philadelphia, PA 19104, USA
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
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224
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Zhang W, Zhang L, Xiao C, Wu X, Cui H, Yang C, Yan P, Tang M, Wang Y, Chen L, Liu Y, Zou Y, Zhang L, Yang C, Yao Y, Li J, Liu Z, Jiang X, Zhang B. Bidirectional relationship between type 2 diabetes mellitus and coronary artery disease: Prospective cohort study and genetic analyses. Chin Med J (Engl) 2024; 137:577-587. [PMID: 38062574 DOI: 10.1097/cm9.0000000000002894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Indexed: 03/13/2024] Open
Abstract
BACKGROUND While type 2 diabetes mellitus (T2DM) is considered a putative causal risk factor for coronary artery disease (CAD), the intrinsic link underlying T2DM and CAD is not fully understood. We aimed to highlight the importance of integrated care targeting both diseases by investigating the phenotypic and genetic relationships between T2DM and CAD. METHODS We evaluated phenotypic associations using data from the United Kingdom Biobank ( N = 472,050). We investigated genetic relationships by leveraging genomic data conducted in European ancestry for T2DM, with and without adjustment for body mass index (BMI) (T2DM: Ncase / Ncontrol = 74,124/824,006; T2DM adjusted for BMI [T2DM adj BMI]: Ncase / Ncontrol = 50,409/523,897) and for CAD ( Ncase / Ncontrol = 181,522/984,168). We performed additional analyses using genomic data conducted in multiancestry individuals for T2DM ( Ncase / Ncontrol = 180,834/1,159,055). RESULTS Observational analysis suggested a bidirectional relationship between T2DM and CAD (T2DM→CAD: hazard ratio [HR] = 2.12, 95% confidence interval [CI]: 2.01-2.24; CAD→T2DM: HR = 1.72, 95% CI: 1.63-1.81). A positive overall genetic correlation between T2DM and CAD was observed ( rg = 0.39, P = 1.43 × 10 -75 ), which was largely independent of BMI (T2DM adj BMI-CAD: rg = 0.31, P = 1.20 × 10 -36 ). This was corroborated by six local signals, among which 9p21.3 showed the strongest genetic correlation. Cross-trait meta-analysis replicated 101 previously reported loci and discovered six novel pleiotropic loci. Mendelian randomization analysis supported a bidirectional causal relationship (T2DM→CAD: odds ratio [OR] = 1.13, 95% CI: 1.11-1.16; CAD→T2DM: OR = 1.12, 95% CI: 1.07-1.18), which was confirmed in multiancestry individuals (T2DM→CAD: OR = 1.13, 95% CI: 1.10-1.16; CAD→T2DM: OR = 1.08, 95% CI: 1.04-1.13). This bidirectional relationship was significantly mediated by systolic blood pressure and intake of 3-hydroxy-3-methylglutaryl coenzyme A reductase inhibitors, with mediation proportions of 54.1% (95% CI: 24.9-83.4%) and 90.4% (95% CI: 29.3-151.5%), respectively. CONCLUSION Our observational and genetic analyses demonstrated an intrinsic bidirectional relationship between T2DM and CAD and clarified the biological mechanisms underlying this relationship.
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Affiliation(s)
- Wenqiang Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Li Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Chenghan Xiao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Xueyao Wu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Huijie Cui
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Chao Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Peijing Yan
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Mingshuang Tang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Yutong Wang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Lin Chen
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Yunjie Liu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Yanqiu Zou
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Ling Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Department of Iatrical Polymer Material and Artificial Apparatus, School of Polymer Science and Engineering, Sichuan University, Chengdu, Sichuan 610041, China
| | - Chunxia Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Yuqin Yao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Jiayuan Li
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Zhenmi Liu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Xia Jiang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm 17177, Sweden
| | - Ben Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
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Li J, Zhu J, Gray O, Sobreira DR, Wu D, Huang RT, Miao B, Sakabe NJ, Krause MD, Kaikkonen MU, Romanoski CE, Nobrega MA, Fang Y. Mechanosensitive super-enhancers regulate genes linked to atherosclerosis in endothelial cells. J Cell Biol 2024; 223:e202211125. [PMID: 38231044 PMCID: PMC10794123 DOI: 10.1083/jcb.202211125] [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: 12/07/2022] [Revised: 10/05/2023] [Accepted: 12/21/2023] [Indexed: 01/18/2024] Open
Abstract
Vascular homeostasis and pathophysiology are tightly regulated by mechanical forces generated by hemodynamics. Vascular disorders such as atherosclerotic diseases largely occur at curvatures and bifurcations where disturbed blood flow activates endothelial cells while unidirectional flow at the straight part of vessels promotes endothelial health. Integrated analysis of the endothelial transcriptome, the 3D epigenome, and human genetics systematically identified the SNP-enriched cistrome in vascular endothelium subjected to well-defined atherosclerosis-prone disturbed flow or atherosclerosis-protective unidirectional flow. Our results characterized the endothelial typical- and super-enhancers and underscored the critical regulatory role of flow-sensitive endothelial super-enhancers. CRISPR interference and activation validated the function of a previously unrecognized unidirectional flow-induced super-enhancer that upregulates antioxidant genes NQO1, CYB5B, and WWP2, and a disturbed flow-induced super-enhancer in endothelium which drives prothrombotic genes EDN1 and HIVEP in vascular endothelium. Our results employing multiomics identify the cis-regulatory architecture of the flow-sensitive endothelial epigenome related to atherosclerosis and highlight the regulatory role of super-enhancers in mechanotransduction mechanisms.
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Affiliation(s)
- Jin Li
- Committee on Molecular Metabolism and Nutrition, Biological Sciences Division, The University of Chicago, Chicago, IL, USA
- Department of Medicine, Biological Sciences Division, The University of Chicago, Chicago, IL, USA
| | - Jiayu Zhu
- Department of Medicine, Biological Sciences Division, The University of Chicago, Chicago, IL, USA
| | - Olivia Gray
- Department of Human Genetics, Biological Sciences Division, The University of Chicago, Chicago, IL, USA
| | - Débora R. Sobreira
- Department of Human Genetics, Biological Sciences Division, The University of Chicago, Chicago, IL, USA
| | - David Wu
- Committee on Molecular Metabolism and Nutrition, Biological Sciences Division, The University of Chicago, Chicago, IL, USA
- Department of Medicine, Biological Sciences Division, The University of Chicago, Chicago, IL, USA
| | - Ru-Ting Huang
- Department of Medicine, Biological Sciences Division, The University of Chicago, Chicago, IL, USA
| | - Bernadette Miao
- Department of Medicine, Biological Sciences Division, The University of Chicago, Chicago, IL, USA
| | - Noboru J. Sakabe
- Department of Human Genetics, Biological Sciences Division, The University of Chicago, Chicago, IL, USA
| | - Matthew D. Krause
- Department of Medicine, Biological Sciences Division, The University of Chicago, Chicago, IL, USA
| | - Minna U. Kaikkonen
- A.I.Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Casey E. Romanoski
- Department of Cellular and Molecular Medicine, University of Arizona, Tucson, AZ, USA
| | - Marcelo A. Nobrega
- Department of Human Genetics, Biological Sciences Division, The University of Chicago, Chicago, IL, USA
| | - Yun Fang
- Committee on Molecular Metabolism and Nutrition, Biological Sciences Division, The University of Chicago, Chicago, IL, USA
- Department of Medicine, Biological Sciences Division, The University of Chicago, Chicago, IL, USA
- Committee on Molecular Medicine, The University of Chicago, Chicago, IL, USA
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Acharya S, Liao S, Jung WJ, Kang YS, Moghaddam VA, Feitosa M, Wojczynski M, Lin S, Anema JA, Schwander K, Connell JO, Province M, Brent MR. Multi-omics Integration Identifies Genes Influencing Traits Associated with Cardiovascular Risks: The Long Life Family Study. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.03.04.24303657. [PMID: 38496585 PMCID: PMC10942516 DOI: 10.1101/2024.03.04.24303657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
The Long Life Family Study (LLFS) enrolled 4,953 participants in 539 pedigrees displaying exceptional longevity. To identify genetic mechanisms that affect cardiovascular risks in the LLFS population, we developed a multi-omics integration pipeline and applied it to 11 traits associated with cardiovascular risks. Using our pipeline, we aggregated gene-level statistics from rare-variant analysis, GWAS, and gene expression-trait association by Correlated Meta-Analysis (CMA). Across all traits, CMA identified 64 significant genes after Bonferroni correction (p ≤ 2.8×10-7), 29 of which replicated in the Framingham Heart Study (FHS) cohort. Notably, 20 of the 29 replicated genes do not have a previously known trait-associated variant in the GWAS Catalog within 50 kb. Thirteen modules in Protein-Protein Interaction (PPI) networks are significantly enriched in genes with low meta-analysis p-values for at least one trait, three of which are replicated in the FHS cohort. The functional annotation of genes in these modules showed a significant over-representation of trait-related biological processes including sterol transport, protein-lipid complex remodeling, and immune response regulation. Among major findings, our results suggest a role of triglyceride-associated and mast-cell functional genes FCER1A, MS4A2, GATA2, HDC, and HRH4 in atherosclerosis risks. Our findings also suggest that lower expression of ATG2A, a gene we found to be associated with BMI, may be both a cause and consequence of obesity. Finally, our results suggest that ENPP3 may play an intermediary role in triglyceride-induced inflammation. Our pipeline is freely available and implemented in the Nextflow workflow language, making it easily runnable on any compute platform (https://nf-co.re/omicsgenetraitassociation).
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Affiliation(s)
- Sandeep Acharya
- Division of Computational and Data Sciences, Washington University, St Louis, MO
| | - Shu Liao
- Department of Computer Science and Engineering, Washington University, St Louis, MO
| | - Wooseok J Jung
- Department of Computer Science and Engineering, Washington University, St Louis, MO
| | - Yu S Kang
- Department of Computer Science and Engineering, Washington University, St Louis, MO
| | - Vaha A Moghaddam
- Division of Statistical Genomics, Washington University School of Medicine, St Louis, MO
| | - Mary Feitosa
- Division of Statistical Genomics, Washington University School of Medicine, St Louis, MO
| | - Mary Wojczynski
- Division of Statistical Genomics, Washington University School of Medicine, St Louis, MO
| | - Shiow Lin
- Division of Statistical Genomics, Washington University School of Medicine, St Louis, MO
| | - Jason A Anema
- Division of Statistical Genomics, Washington University School of Medicine, St Louis, MO
| | - Karen Schwander
- Division of Statistical Genomics, Washington University School of Medicine, St Louis, MO
| | - Jeff O Connell
- Department of Medicine, University of Maryland, Baltimore, MD
| | - Mike Province
- Division of Statistical Genomics, Washington University School of Medicine, St Louis, MO
| | - Michael R Brent
- Department of Computer Science and Engineering, Washington University, St Louis, MO
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227
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Guirette M, Lan J, McKeown NM, Brown MR, Chen H, de Vries PS, Kim H, Rebholz CM, Morrison AC, Bartz TM, Fretts AM, Guo X, Lemaitre RN, Liu CT, Noordam R, de Mutsert R, Rosendaal FR, Wang CA, Beilin LJ, Mori TA, Oddy WH, Pennell CE, Chai JF, Whitton C, van Dam RM, Liu J, Tai ES, Sim X, Neuhouser ML, Kooperberg C, Tinker LF, Franceschini N, Huan T, Winkler TW, Bentley AR, Gauderman WJ, Heerkens L, Tanaka T, van Rooij J, Munroe PB, Warren HR, Voortman T, Chen H, Rao DC, Levy D, Ma J. Genome-Wide Interaction Analysis With DASH Diet Score Identified Novel Loci for Systolic Blood Pressure. Hypertension 2024; 81:552-560. [PMID: 38226488 PMCID: PMC10922535 DOI: 10.1161/hypertensionaha.123.22334] [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: 11/10/2023] [Accepted: 12/28/2023] [Indexed: 01/17/2024]
Abstract
BACKGROUND The Dietary Approaches to Stop Hypertension (DASH) diet score lowers blood pressure (BP). We examined interactions between genotype and the DASH diet score in relation to systolic BP. METHODS We analyzed up to 9 420 585 single nucleotide polymorphisms in up to 127 282 individuals of 6 population groups (91% of European population) from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (n=35 660) and UK Biobank (n=91 622) and performed European population-specific and cross-population meta-analyses. RESULTS We identified 3 loci in European-specific analyses and an additional 4 loci in cross-population analyses at Pinteraction<5e-8. We observed a consistent interaction between rs117878928 at 15q25.1 (minor allele frequency, 0.03) and the DASH diet score (Pinteraction=4e-8; P for heterogeneity, 0.35) in European population, where the interaction effect size was 0.42±0.09 mm Hg (Pinteraction=9.4e-7) and 0.20±0.06 mm Hg (Pinteraction=0.001) in Cohorts for Heart and Aging Research in Genomic Epidemiology and the UK Biobank, respectively. The 1 Mb region surrounding rs117878928 was enriched with cis-expression quantitative trait loci (eQTL) variants (P=4e-273) and cis-DNA methylation quantitative trait loci variants (P=1e-300). Although the closest gene for rs117878928 is MTHFS, the highest narrow sense heritability accounted by single nucleotide polymorphisms potentially interacting with the DASH diet score in this locus was for gene ST20 at 15q25.1. CONCLUSIONS We demonstrated gene-DASH diet score interaction effects on systolic BP in several loci. Studies with larger diverse populations are needed to validate our findings.
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Affiliation(s)
- Mélanie Guirette
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA (M.G., J.L., J.M.)
| | - Jessie Lan
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA (M.G., J.L., J.M.)
| | - Nicola M McKeown
- Programs of Nutrition, Department of Health Sciences, Sargent College of Health & Rehabilitation Sciences, Boston University, MA (N.M.M.)
| | - Michael R Brown
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston (M.R.B., H.C., P.S.d.V., A.C.M.)
| | - Han Chen
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston (M.R.B., H.C., P.S.d.V., A.C.M.)
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston (M.R.B., H.C., P.S.d.V., A.C.M.)
| | - Hyunju Kim
- Department of Epidemiology (H.K., A.M.F.), Cardiovascular Health Research Unit, University of Washington, Seattle, WA
| | - Casey M Rebholz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD (C.M.R.)
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston (M.R.B., H.C., P.S.d.V., A.C.M.)
| | - Traci M Bartz
- Departments of Biostatistics and Medicine (T.M.B.), Cardiovascular Health Research Unit, University of Washington, Seattle, WA
| | - Amanda M Fretts
- Department of Epidemiology (H.K., A.M.F.), Cardiovascular Health Research Unit, University of Washington, Seattle, WA
| | - Xiuqing Guo
- The Lundquist Institute at Harbor-University of California, Los Angeles, Torrance, CA (X.G.)
| | - Rozenn N Lemaitre
- Department of Medicine (R.N.L.), Cardiovascular Health Research Unit, University of Washington, Seattle, WA
| | - Ching-Ti Liu
- Biostatistics, Boston University School of Public Health, MA (C.-T.L.)
| | - Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and Geriatrics (R.N.), Leiden University Medical Center, the Netherlands
| | - Renée de Mutsert
- Department of Clinical Epidemiology (R.d.M., F.R.R.), Leiden University Medical Center, the Netherlands
| | - Frits R Rosendaal
- Department of Clinical Epidemiology (R.d.M., F.R.R.), Leiden University Medical Center, the Netherlands
| | - Carol A Wang
- School of Medicine and Public Health, University of Newcastle, NSW, Australia (C.A.W., C.E.P)
- Mothers' and Babies' Research Program, Hunter Medical Research Institute, NSW, Australia (C.A.W., C.E.P.)
| | - Lawrence J Beilin
- Medical School, Royal Perth Hospital Unit, University of Western Australia, Crawley (L.J.B., T.A.M.)
| | - Trevor A Mori
- Medical School, Royal Perth Hospital Unit, University of Western Australia, Crawley (L.J.B., T.A.M.)
| | - Wendy H Oddy
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia (W.H.O.)
| | - Craig E Pennell
- School of Medicine and Public Health, University of Newcastle, NSW, Australia (C.A.W., C.E.P)
- Mothers' and Babies' Research Program, Hunter Medical Research Institute, NSW, Australia (C.A.W., C.E.P.)
| | - Jin Fang Chai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System (J.F.C., C.W., R.M.v.D., E.S.T., X.S.)
| | - Clare Whitton
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System (J.F.C., C.W., R.M.v.D., E.S.T., X.S.)
- School of Population Health, Curtin University, Perth, Western Australia, Australia (C.W.)
| | - Rob M van Dam
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System (J.F.C., C.W., R.M.v.D., E.S.T., X.S.)
- Department of Exercise and Nutrition Sciences, Milken Institute School of Public Health, The George Washington University (R.M.v.D.)
| | - Jianjun Liu
- Genome Institute of Singapore, Agency for Science, Technology and Research (J.L.)
| | - E Shyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System (J.F.C., C.W., R.M.v.D., E.S.T., X.S.)
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore (E.S.T.)
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System (J.F.C., C.W., R.M.v.D., E.S.T., X.S.)
| | - Marian L Neuhouser
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA (M.L.N., C.K., L.F.T.)
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA (M.L.N., C.K., L.F.T.)
| | - Lesley F Tinker
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA (M.L.N., C.K., L.F.T.)
| | - Nora Franceschini
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill (N.F.)
| | - TianXiao Huan
- Framingham Heart Study and Population Sciences Branch, National Heart, Lung, and Blood Institute, MA (T.H., D.L.)
| | - Thomas W Winkler
- Department of Genetic Epidemiology, University of Regensburg, Germany (T.W.W.)
| | - Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD (A.R.B.)
| | - W James Gauderman
- Division of Biostatistics, Department of Population and Public Health Sciences, University of Southern California (W.J.G.)
| | - Luc Heerkens
- Division of Human Nutrition and Health, Wageningen University & Research, the Netherlands (L.H.)
| | - Toshiko Tanaka
- Longitudinal Studies Section, National Institute on Aging, Baltimore, MD (T.T.)
| | - Jeroen van Rooij
- Department of Internal Medicine (J.v.R.), Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Patricia B Munroe
- Centre of Clinical Pharmacology & Precision Medicine, William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, United Kingdom (P.B.M., H.R.W.)
| | - Helen R Warren
- Centre of Clinical Pharmacology & Precision Medicine, William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, United Kingdom (P.B.M., H.R.W.)
| | - Trudy Voortman
- Department of Epidemiology (T.V.), Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Honglei Chen
- Department of Epidemiology and Biostatistics College of Human Medicine, Michigan State University, East Lansing (H.C.)
| | - D C Rao
- Center for Biostatistics and Data Science, Institute for Informatics, Data Science, and Biostatistics, Washington University School of Medicine, St. Louis, MO (D.C.R.)
| | - Daniel Levy
- Framingham Heart Study and Population Sciences Branch, National Heart, Lung, and Blood Institute, MA (T.H., D.L.)
| | - Jiantao Ma
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA (M.G., J.L., J.M.)
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228
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Xu X, Wang SY, Wang R, Wu LY, Yan M, Sun ZL, Sun QH. Association of antihypertensive drugs with psoriasis: A trans-ancestry and drug-target Mendelian randomization study. Vascul Pharmacol 2024; 154:107284. [PMID: 38360195 DOI: 10.1016/j.vph.2024.107284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 02/02/2024] [Accepted: 02/11/2024] [Indexed: 02/17/2024]
Affiliation(s)
- Xiao Xu
- Department of Nursing, Nantong Health College of Jiangsu Province, Nantong, China.
| | - Shu-Yun Wang
- Academic Affair Office, Nantong Vocational University, Nantong, China; Department of Postgraduate, St. Paul University Philippines, Tuggegarau, Philippines.
| | - Rongyun Wang
- School of Nursing, Zhejiang Chinese Medical University, Hangzhou, China.
| | - Lin-Yun Wu
- College of Pharmacy, Zhejiang Chinese Medical University, Hangzhou, China.
| | - Min Yan
- Department of Epidemiology, School of Public Health, Changzhou University, Changzhou, China; Faculty of Health and Welfare, Satakunta University of Applied Sciences, Pori, Finland.
| | - Zhi-Ling Sun
- Department of Rheumatology, School of Nursing, Nanjing University of Chinese Medicine, Nanjing, China.
| | - Qiu-Hua Sun
- School of Nursing, Zhejiang Chinese Medical University, Hangzhou, China.
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Yang ML, Xu C, Gupte T, Hoffmann TJ, Iribarren C, Zhou X, Ganesh SK. Sex-specific genetic architecture of blood pressure. Nat Med 2024; 30:818-828. [PMID: 38459180 PMCID: PMC11797078 DOI: 10.1038/s41591-024-02858-2] [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: 01/17/2023] [Accepted: 02/05/2024] [Indexed: 03/10/2024]
Abstract
The genetic and genomic basis of sex differences in blood pressure (BP) traits remain unstudied at scale. Here, we conducted sex-stratified and combined-sex genome-wide association studies of BP traits using the UK Biobank resource, identifying 1,346 previously reported and 29 new BP trait-associated loci. Among associated loci, 412 were female-specific (Pfemale ≤ 5 × 10-8; Pmale > 5 × 10-8) and 142 were male-specific (Pmale ≤ 5 × 10-8; Pfemale > 5 × 10-8); these sex-specific loci were enriched for hormone-related transcription factors, in particular, estrogen receptor 1. Analyses of gene-by-sex interactions and sexually dimorphic effects identified four genomic regions, showing female-specific associations with diastolic BP or pulse pressure, including the chromosome 13q34-COL4A1/COL4A2 locus. Notably, female-specific pulse pressure-associated loci exhibited enriched acetylated histone H3 Lys27 modifications in arterial tissues and a female-specific association with fibromuscular dysplasia, a female-biased vascular disease; colocalization signals included Chr13q34: COL4A1/COL4A2, Chr9p21: CDKN2B-AS1 and Chr4q32.1: MAP9 regions. Sex-specific and sex-biased polygenic associations of BP traits were associated with multiple cardiovascular traits. These findings suggest potentially clinically significant and BP sex-specific pleiotropic effects on cardiovascular diseases.
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Affiliation(s)
- Min-Lee Yang
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Chang Xu
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Trisha Gupte
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Thomas J Hoffmann
- Department of Epidemiology & Biostatistics, and Institute for Human Genetics, School of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | | | - Xiang Zhou
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Santhi K Ganesh
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, MI, USA.
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA.
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
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230
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Hu M, Li B, Yang T, Yang Y, Yin C. Effect of Household Income on Cardiovascular Diseases, Cardiovascular Biomarkers, and Socioeconomic Factors. Clin Ther 2024; 46:239-245. [PMID: 38350757 DOI: 10.1016/j.clinthera.2024.01.005] [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: 06/09/2023] [Revised: 09/07/2023] [Accepted: 01/08/2024] [Indexed: 02/15/2024]
Abstract
PURPOSE To examine whether household income is causally related to cardiovascular diseases and investigate the potential reasons. METHODS Using 2-sample Mendelian randomization analyses, we obtained summary statistics from genome-wide association studies of household income and a range of cardiovascular diseases, biomarkers, and socioeconomic factors. FINDINGS Higher household income was causally associated with lower risks of coronary heart disease (odd ratio [OR] = 0.63; 95% CI: 0.49-0.79; P = 0.0001), myocardial infarction (OR = 0.64; 95% CI: 0.50-0.82; P = 0.0003), and hypertension (OR = 0.71; 95% CI: 0.58-0.88; P = 0.0015). With increasing household income, the cardiovascular biomarkers including triglycerides, C-reactive protein, body mass index, fasting glucose were decreased whereas telomere length and high-density lipoprotein cholesterol were increased. Besides, individuals with higher household income were less likely to smoke (β = -0.34; 95% CI: -0.47 to -0.21; P = 1.91×10-07), intake salt (β = -0.14; 95% CI: -0.21 to -0.07; P = 0.0001), or be exposed to air pollution (β = -0.10; 95% CI: -0.15 to -0.06; P = 8.81×10-06) or depression state (β = -0.03; 95% CI: -0.04 to -0.02; P = 5.16×10-07). They were more likely to take physical activity (β = 0.06; 95% CI: 0.02 to 010; P = 0.0016) and have long years of schooling (β = 0.70; 95% CI: 0.62 to 0.78; P = 5.32×10-67). IMPLICATIONS Higher household income is causally associated with better socioeconomic factors and improved cardiovascular biomarkers, which translates into a reduced prevalence of cardiovascular diseases. Policies to improve income equality may result in a reduced burden of cardiovascular diseases.
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Affiliation(s)
- Mengjin Hu
- Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Boyu Li
- Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Tao Yang
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Yuejin Yang
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Chunlin Yin
- Xuanwu Hospital, Capital Medical University, Beijing, China.
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231
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Zhai Y, Chen H, Che B, Liu Y, Peng Y, Chen J, Xu T, He J, Zhang Y, Zhong C. Efficacy of Immediate Antihypertensive Treatment in Patients With Acute Ischemic Stroke With Different Blood Pressure Genetic Variants. Hypertension 2024; 81:658-667. [PMID: 38174564 DOI: 10.1161/hypertensionaha.123.21851] [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: 07/27/2023] [Accepted: 12/12/2023] [Indexed: 01/05/2024]
Abstract
BACKGROUND It remains unclear whether blood pressure (BP) genetic variants could modify the efficacy of immediate antihypertensive treatment after acute ischemic stroke. We conducted a secondary analysis of the CATIS (China Antihypertensive Trial in Acute Ischemic Stroke) to investigate the effect of early antihypertensive treatment on clinical outcomes among patients with acute ischemic stroke according to 5 BP-associated genetic variants. METHODS The CATIS randomized 4071 patients with acute ischemic stroke with elevated systolic BP to receive antihypertensive treatment or discontinue all antihypertensive agents during hospitalization. Randomization was conducted centrally and was stratified by participating hospitals and use of antihypertensive medications. Five BP-associated single nucleotide polymorphisms (rs16849225, rs17030613, rs1173766, rs6825911, and rs35444 in FIGN-GRB14, ST7L-CAPZA1, NPR3, ENPEP, and near TBX3, respectively) were genotyped among 2590 patients. The primary outcome was a combination of death and major disability at 14 days or hospital discharge. A weighted BP genetic risk score was constructed by the 5 single nucleotide polymorphisms. RESULTS At 14 days or hospital discharge, the primary outcome was not significantly different between antihypertensive treatment and control groups based on genotype subgroups for all 5 single nucleotide polymorphisms (all P>0.05 for interaction). In addition, the BP genetic risk score did not modify the effect of antihypertensive treatment. The odds ratios (95% CIs) for the primary outcome were 0.95 (0.71-1.26), 1.08 (0.80-1.44), and 0.91 (0.69-1.22) in patients with low, intermediate, and high BP genetic risk score, respectively (P=0.88 for interaction). CONCLUSIONS Early antihypertensive treatment had a neutral effect on clinical outcomes among patients with acute ischemic stroke according to 5 BP-associated genetic variants. REGISTRATION URL: https://www.clinicaltrials.gov; Unique identifier: NCT01840072.
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Affiliation(s)
- Yujia Zhai
- Department of Epidemiology, School of Public Health, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, MOE Key Laboratory of Geriatric Diseases and Immunology, Suzhou Medical College of Soochow University, China (Y. Zhai, H.C., B.C., T.X., Y. Zhang, C.Z.)
| | - Hongyu Chen
- Department of Epidemiology, School of Public Health, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, MOE Key Laboratory of Geriatric Diseases and Immunology, Suzhou Medical College of Soochow University, China (Y. Zhai, H.C., B.C., T.X., Y. Zhang, C.Z.)
| | - Bizhong Che
- Department of Epidemiology, School of Public Health, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, MOE Key Laboratory of Geriatric Diseases and Immunology, Suzhou Medical College of Soochow University, China (Y. Zhai, H.C., B.C., T.X., Y. Zhang, C.Z.)
| | - Yang Liu
- Department of Cardiology, First Affiliated Hospital of Soochow University, Suzhou, China (Y.L.)
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (Y.L., J.C., J.H., C.Z.)
| | - Yanbo Peng
- Department of Neurology, Affiliated Hospital of North China University of Science and Technology, Hebei, China (Y.P.)
| | - Jing Chen
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (Y.L., J.C., J.H., C.Z.)
- Department of Medicine, Tulane University School of Medicine, New Orleans, LA (J.C., J.H.)
| | - Tan Xu
- Department of Epidemiology, School of Public Health, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, MOE Key Laboratory of Geriatric Diseases and Immunology, Suzhou Medical College of Soochow University, China (Y. Zhai, H.C., B.C., T.X., Y. Zhang, C.Z.)
| | - Jiang He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (Y.L., J.C., J.H., C.Z.)
- Department of Medicine, Tulane University School of Medicine, New Orleans, LA (J.C., J.H.)
| | - Yonghong Zhang
- Department of Epidemiology, School of Public Health, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, MOE Key Laboratory of Geriatric Diseases and Immunology, Suzhou Medical College of Soochow University, China (Y. Zhai, H.C., B.C., T.X., Y. Zhang, C.Z.)
| | - Chongke Zhong
- Department of Epidemiology, School of Public Health, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, MOE Key Laboratory of Geriatric Diseases and Immunology, Suzhou Medical College of Soochow University, China (Y. Zhai, H.C., B.C., T.X., Y. Zhang, C.Z.)
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (Y.L., J.C., J.H., C.Z.)
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Harrer P, Inderhees J, Zhao C, Schormair B, Tilch E, Gieger C, Peters A, Jöhren O, Fleming T, Nawroth PP, Berger K, Hermesdorf M, Winkelmann J, Schwaninger M, Oexle K. Phenotypic and genome-wide studies on dicarbonyls: major associations to glomerular filtration rate and gamma-glutamyltransferase activity. EBioMedicine 2024; 101:105007. [PMID: 38354534 PMCID: PMC10875252 DOI: 10.1016/j.ebiom.2024.105007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 01/26/2024] [Accepted: 01/29/2024] [Indexed: 02/16/2024] Open
Abstract
BACKGROUND The dicarbonyl compounds methylglyoxal (MG), glyoxal (GO) and 3-deoxyglucosone (3-DG) have been linked to various diseases. However, disease-independent phenotypic and genotypic association studies with phenome-wide and genome-wide reach, respectively, have not been provided. METHODS MG, GO and 3-DG were measured by LC-MS in 1304 serum samples of two populations (KORA, n = 482; BiDirect, n = 822) and assessed for associations with genome-wide SNPs (GWAS) and with phenome-wide traits. Redundancy analysis (RDA) was used to identify major independent trait associations. FINDINGS Mutual correlations of dicarbonyls were highly significant, being stronger between MG and GO (ρ = 0.6) than between 3-DG and MG or GO (ρ = 0.4). Significant phenotypic results included associations of all dicarbonyls with sex, waist-to-hip ratio, glomerular filtration rate (GFR), gamma-glutamyltransferase (GGT), and hypertension, of MG and GO with age and C-reactive protein, of GO and 3-DG with glucose and antidiabetics, of MG with contraceptives, of GO with ferritin, and of 3-DG with smoking. RDA revealed GFR, GGT and, in case of 3-DG, glucose as major contributors to dicarbonyl variance. GWAS did not identify genome-wide significant loci. SNPs previously associated with glyoxalase activity did not reach nominal significance. When multiple testing was restricted to the lead SNPs of GWASs on the traits selected by RDA, 3-DG was found to be associated (p = 2.3 × 10-5) with rs1741177, an eQTL of NF-κB inhibitor NFKBIA. INTERPRETATION This large-scale, population-based study has identified numerous associations, with GFR and GGT being of pivotal importance, providing unbiased perspectives on dicarbonyls beyond the current state. FUNDING Deutsche Forschungsgemeinschaft, Helmholtz Munich, German Centre for Cardiovascular Research (DZHK), German Federal Ministry of Research and Education (BMBF).
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Affiliation(s)
- Philip Harrer
- Institute of Neurogenomics, Helmholtz Munich, Neuherberg, Germany; Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany
| | - Julica Inderhees
- Institute for Experimental and Clinical Pharmacology and Toxicology, Center of Brain, Behavior and Metabolism, University of Lubeck, Lubeck, Germany; Bioanalytic Core Facility, Center for Brain, Behavior and Metabolism, University of Lübeck, Germany; German Centre for Cardiovascular Research (DZHK), Hamburg-Lübeck-Kiel, Germany
| | - Chen Zhao
- Institute of Neurogenomics, Helmholtz Munich, Neuherberg, Germany; Neurogenetic Systems Analysis Group, Institute of Neurogenomics, Helmholtz Munich, Neuherberg, Germany
| | - Barbara Schormair
- Institute of Neurogenomics, Helmholtz Munich, Neuherberg, Germany; Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany
| | - Erik Tilch
- Institute of Neurogenomics, Helmholtz Munich, Neuherberg, Germany; Neurogenetic Systems Analysis Group, Institute of Neurogenomics, Helmholtz Munich, Neuherberg, Germany
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Munich, Neuherberg, Germany; Institute of Epidemiology, Helmholtz Munich, Neuherberg, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Munich, Neuherberg, Germany; German Center for Diabetes Research (DZD), Neuherberg, Germany; Chair of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Olaf Jöhren
- Institute for Experimental and Clinical Pharmacology and Toxicology, Center of Brain, Behavior and Metabolism, University of Lubeck, Lubeck, Germany; Bioanalytic Core Facility, Center for Brain, Behavior and Metabolism, University of Lübeck, Germany
| | - Thomas Fleming
- Department of Internal Medicine, University of Heidelberg, Heidelberg, Germany
| | - Peter P Nawroth
- Department of Internal Medicine, University of Heidelberg, Heidelberg, Germany
| | - Klaus Berger
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - Marco Hermesdorf
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - Juliane Winkelmann
- Institute of Neurogenomics, Helmholtz Munich, Neuherberg, Germany; Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany; German Centre for Mental Health (DZPG), Munich-Augsburg, Germany
| | - Markus Schwaninger
- Institute for Experimental and Clinical Pharmacology and Toxicology, Center of Brain, Behavior and Metabolism, University of Lubeck, Lubeck, Germany; German Centre for Cardiovascular Research (DZHK), Hamburg-Lübeck-Kiel, Germany
| | - Konrad Oexle
- Institute of Neurogenomics, Helmholtz Munich, Neuherberg, Germany; Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany; Neurogenetic Systems Analysis Group, Institute of Neurogenomics, Helmholtz Munich, Neuherberg, Germany.
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Woo K, Lim JE, Lee EY. Influence of blood pressure polygenic risk scores and environmental factors on coronary artery disease in the Korean Genome and Epidemiology Study. J Hum Hypertens 2024; 38:221-227. [PMID: 37985823 DOI: 10.1038/s41371-023-00878-y] [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: 02/05/2023] [Revised: 10/19/2023] [Accepted: 11/02/2023] [Indexed: 11/22/2023]
Abstract
The present study aimed to investigate the association of blood pressure polygenic risk scores (BP PRSs) with coronary artery disease (CAD) in a Korean population and the interaction effects between PRSs and environmental factors on CAD. Data were derived from the Cardiovascular Disease Association Study (CAVAS; N = 5100) and the Health Examinee Study (HEXA; N = 58,623) within the Korean Genome and Epidemiology Study. PRSs for systolic and diastolic BP were calculated with the weighted allele sum of >200 single-nucleotide polymorphisms. Multivariable logistic regression models were used. BP PRSs were strongly associated with systolic BP (SBP), diastolic BP (DBP), and hypertension in both CAVAS and HEXA (p < 0.0001). PRSSBP was significantly associated with CAD in CAVAS, while PRSSBP and PRSDBP were significantly associated with CAD in HEXA. There was an interaction effect between the BP PRSs and environmental factors on CAD. The odds ratios (ORs) for CAD were 1.036 (95% confidence interval [CI], 1.016-1.055) for obesity, 1.028 (95% CI, 1.011-1.045) for abdominal obesity, 1.030 (95% CI, 1.009-1.050) for triglyceride, 1.024 (95% CI, 1.008-1.041) for high-density lipoprotein cholesterol, and 1.039 for smoking (95% CI, 1.003-1.077) in CAVAS. There was no significant interaction in HEXA, except between PRSDBP and triglyceride (OR, 1.012; 95% CI, 1.001-1.024). BP PRS was associated with an increased risk of hypertension and CAD. The interactions among PRSs and environmental risk factors increased the risk of CAD. Multi-component interventions to lower BP in the population via healthy behaviors are needed to prevent CAD regardless of genetic predisposition.
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Affiliation(s)
- Kyungsook Woo
- Institute of Health and Society, Hanyang University, Seoul, 04763, Republic of Korea
| | - Ji Eun Lim
- Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul, 02447, Republic of Korea
| | - Eun Young Lee
- Department of Nursing, Catholic Kkottongnae University, Cheongju, 28211, Republic of Korea.
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Teixeira SK, Pontes R, Zuleta LFG, Wang J, Xu D, Hildebrand S, Russell J, Zhan X, Choi M, Tang M, Li X, Ludwig S, Beutler B, Krieger JE. Genetic determinants of blood pressure and heart rate identified through ENU-induced mutagenesis with automated meiotic mapping. SCIENCE ADVANCES 2024; 10:eadj9797. [PMID: 38427739 PMCID: PMC10906923 DOI: 10.1126/sciadv.adj9797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 01/29/2024] [Indexed: 03/03/2024]
Abstract
We used N-ethyl-N-nitrosurea-induced germline mutagenesis combined with automated meiotic mapping to identify specific systolic blood pressure (SBP) and heart rate (HR) determinant loci. We analyzed 43,627 third-generation (G3) mice from 841 pedigrees to assess the effects of 45,378 variant alleles within 15,760 genes, in both heterozygous and homozygous states. We comprehensively tested 23% of all protein-encoding autosomal genes and found 87 SBP and 144 HR (with 7 affecting both) candidates exhibiting detectable hypomorphic characteristics. Unexpectedly, only 18 of the 87 SBP genes were previously known, while 26 of the 144 genes linked to HR were previously identified. Furthermore, we confirmed the influence of two genes on SBP regulation and three genes on HR control through reverse genetics. This underscores the importance of our research in uncovering genes associated with these critical cardiovascular risk factors and illustrate the effectiveness of germline mutagenesis for defining key determinants of polygenic phenotypes that must be studied in an intact organism.
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Affiliation(s)
- Samantha K. Teixeira
- Laboratório de Genética e Cardiologia Molecular, Instituto do Coração, Hospital das Clínicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
| | - Roberto Pontes
- Laboratório de Genética e Cardiologia Molecular, Instituto do Coração, Hospital das Clínicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
| | - Luiz Fernando G. Zuleta
- Laboratório de Genética e Cardiologia Molecular, Instituto do Coração, Hospital das Clínicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
| | - Jianhui Wang
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Darui Xu
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Sara Hildebrand
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Jamie Russell
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Xiaoming Zhan
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Mihwa Choi
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Miao Tang
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Xiaohong Li
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Sara Ludwig
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Bruce Beutler
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Jose E. Krieger
- Laboratório de Genética e Cardiologia Molecular, Instituto do Coração, Hospital das Clínicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
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Lee WH, Larsson SC, Wood A, Di Angelantonio E, Butterworth AS, Burgess S, Allara E. Genetically predicted plasma cortisol and common chronic diseases: A Mendelian randomization study. Clin Endocrinol (Oxf) 2024; 100:238-244. [PMID: 37667866 PMCID: PMC7615603 DOI: 10.1111/cen.14966] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 05/29/2023] [Accepted: 08/21/2023] [Indexed: 09/06/2023]
Abstract
OBJECTIVE Cushing's syndrome is characterized by hypercortisolaemia and is frequently accompanied by comorbidities such as type 2 diabetes, hypertension, osteoporosis, depression and schizophrenia. It is unclear whether moderate but lifelong hypercortisolaemia is causally associated with these diseases in the general population. We aimed to address this research gap using a Mendelian randomization approach. METHODS We used three cortisol-associated genetic variants in the SERPINA6/SERPINA1 region as genetic instruments in a two-sample, inverse-variance-weighted Mendelian randomization analysis. We obtained summary-level statistics for cortisol and disease outcomes from publicly available genetic consortia, and meta-analysed them as appropriate. We conducted a multivariable Mendelian randomization analysis to assess potential mediating effects. RESULTS A 1 standard deviation higher genetically predicted plasma cortisol was associated with greater odds of hypertension (odds ratio: 1.12; 95% confidence interval [CI]: 1.05-1.18) as well as higher systolic blood pressure (mean difference [MD]: 0.03 SD change; 95% CI: 0.01-0.05) and diastolic blood pressure (MD: 0.03 SD change; 95% CI: 0.01-0.04). There was no evidence of association with type 2 diabetes, osteoporosis, depression and schizophrenia. The association with hypertension was attenuated upon adjustment for waist circumference, suggesting potential mediation through central obesity. CONCLUSION There is strong evidence for a causal association between plasma cortisol and greater risk for hypertension, potentially mediated by obesity.
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Affiliation(s)
- Wei-Hsuan Lee
- British Heart Foundation Cardiovascular Epidemiology Uni, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Susanna C. Larsson
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Angela Wood
- British Heart Foundation Cardiovascular Epidemiology Uni, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Philip Dahdaleh National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, 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, Cambridge, UK
- Cambridge Centre of Artificial Intelligence in Medicine, Cambridge, UK
| | - Emanuele Di Angelantonio
- British Heart Foundation Cardiovascular Epidemiology Uni, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Philip Dahdaleh National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, 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, Cambridge, UK
- Health Data Science Research Centre, Human Technopole, Milan, Italy
| | - Adam S. Butterworth
- British Heart Foundation Cardiovascular Epidemiology Uni, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Philip Dahdaleh National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, 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, Cambridge, UK
| | - Stephen Burgess
- British Heart Foundation Cardiovascular Epidemiology Uni, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - Elias Allara
- British Heart Foundation Cardiovascular Epidemiology Uni, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Philip Dahdaleh National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK
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Yuan M, He J, Hu X, Yao L, Chen P, Wang Z, Liu P, Xiong Z, Jiang Y, Li L. Hypertension and NAFLD risk: Insights from the NHANES 2017-2018 and Mendelian randomization analyses. Chin Med J (Engl) 2024; 137:457-464. [PMID: 37455323 PMCID: PMC10876227 DOI: 10.1097/cm9.0000000000002753] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2023] [Indexed: 07/18/2023] Open
Abstract
BACKGROUND Hypertension and non-alcoholic fatty liver disease (NAFLD) share several pathophysiologic risk factors, and the exact relationship between the two remains unclear. Our study aims to provide evidence concerning the relationship between hypertension and NAFLD by analyzing data from the National Health and Nutrition Examination Survey (NHANES) 2017-2018 and Mendelian randomization (MR) analyses. METHODS Weighted multivariable-adjusted logistic regression was applied to assess the relationship between hypertension and NAFLD risk by using data from the NHANES 2017-2018. Subsequently, a two-sample MR study was performed using the genome-wide association study (GWAS) summary statistics to identify the causal association between hypertension, systolic blood pressure (SBP), diastolic blood pressure (DBP), and NAFLD. The primary inverse variance weighted (IVW) and other supplementary MR approaches were conducted to verify the causal association between hypertension and NAFLD. Sensitivity analyses were adopted to confirm the robustness of the results. RESULTS A total of 3144 participants were enrolled for our observational study in NHANES. Weighted multivariable-adjusted logistic regression analysis suggested that hypertension was positively related to NAFLD risk (odds ratio [OR] = 1.677; 95% confidence interval [CI], 1.159-2.423). SBP ≥130 mmHg and DBP ≥80 mmHg were also significantly positively correlated with NAFLD. Moreover, hypertension was independently connected with liver steatosis ( β = 7.836 [95% CI, 2.334-13.338]). The results of MR analysis also supported a causal association between hypertension (OR = 7.203 [95% CI, 2.297-22.587]) and NAFLD. Similar results were observed for the causal exploration between SBP (OR = 1.024 [95% CI, 1.003-1.046]), DBP (OR = 1.047 [95% CI, 1.005-1.090]), and NAFLD. The sensitive analysis further confirmed the robustness and reliability of these findings (all P >0.05). CONCLUSION Hypertension was associated with an increased risk of NAFLD.
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Affiliation(s)
- Mengqin Yuan
- Department of Infectious Diseases, Renmin Hospital of Wuhan University, Wuhan, Hubei 430000, China
| | - Jian He
- Department of Gastroenterology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510010, China
| | - Xue Hu
- Department of Infectious Diseases, Renmin Hospital of Wuhan University, Wuhan, Hubei 430000, China
| | - Lichao Yao
- Department of Infectious Diseases, Renmin Hospital of Wuhan University, Wuhan, Hubei 430000, China
| | - Ping Chen
- Department of Infectious Diseases, Renmin Hospital of Wuhan University, Wuhan, Hubei 430000, China
| | - Zheng Wang
- Department of Infectious Diseases, Renmin Hospital of Wuhan University, Wuhan, Hubei 430000, China
| | - Pingji Liu
- Department of Infectious Diseases, Renmin Hospital of Wuhan University, Wuhan, Hubei 430000, China
| | - Zhiyu Xiong
- Department of Infectious Diseases, Renmin Hospital of Wuhan University, Wuhan, Hubei 430000, China
| | - Yingan Jiang
- Department of Infectious Diseases, Renmin Hospital of Wuhan University, Wuhan, Hubei 430000, China
| | - Lanjuan Li
- Department of Infectious Diseases, Renmin Hospital of Wuhan University, Wuhan, Hubei 430000, China
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Centre for Infectious Diseases, Collaborative Innovation Centre for Diagnosis and Treatment of Infectious Diseases, Department of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang 310000, China
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Martin SS, Aday AW, Almarzooq ZI, Anderson CAM, Arora P, Avery CL, Baker-Smith CM, Barone Gibbs B, Beaton AZ, Boehme AK, Commodore-Mensah Y, Currie ME, Elkind MSV, Evenson KR, Generoso G, Heard DG, Hiremath S, Johansen MC, Kalani R, Kazi DS, Ko D, Liu J, Magnani JW, Michos ED, Mussolino ME, Navaneethan SD, Parikh NI, Perman SM, Poudel R, Rezk-Hanna M, Roth GA, Shah NS, St-Onge MP, Thacker EL, Tsao CW, Urbut SM, Van Spall HGC, Voeks JH, Wang NY, Wong ND, Wong SS, Yaffe K, Palaniappan LP, American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee. 2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association. Circulation 2024; 149:e347-e913. [PMID: 38264914 PMCID: PMC12146881 DOI: 10.1161/cir.0000000000001209] [Citation(s) in RCA: 845] [Impact Index Per Article: 845.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/25/2024]
Abstract
BACKGROUND The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains. RESULTS Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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238
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Xu Z, Rao X, Xing Y, Zhu Z, Yan L, Huang J, Zhang J, Zheng R. Connecting atrial fibrillation to digestive neoplasms: exploring mediation via ischemic stroke and heart failure in Mendelian randomization studies. Front Oncol 2024; 14:1301327. [PMID: 38444673 PMCID: PMC10912520 DOI: 10.3389/fonc.2024.1301327] [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: 09/24/2023] [Accepted: 01/22/2024] [Indexed: 03/07/2024] Open
Abstract
Background Notwithstanding the acknowledged interplay between atrial fibrillation (AF) and the emergence of digestive system neoplasms, the intricacies of this relationship remain ambiguous. By capitalizing univariable Mendelian Randomization (MR) complemented by a mediated MR tactic, our pursuit was to elucidate the causative roles of AF in precipitating digestive system malignancies and potential intermediary pathways. Method This research endeavor seeks to scrutinize the causal clinical implications of whether genetic predispositions to AF correlate with an increased risk of digestive system malignancies, employing MR analytical techniques. Utilizing a dataset amalgamated from six studies related to AF, encompassing over 1,000,000 subjects, we performed univariable MR assessments, employing the random-effects inverse-variance weighted (IVW) methodology as our principal analytical paradigm. Subsequently, a mediated MR framework was employed to probe the potential mediating influence of AF on the nexus between hypertension (HT), heart failure (HF), ischemic stroke (IS), coronary artery disease (CAD), and digestive system neoplasms. Result The univariable MR evaluation unveiled a notable causal nexus between the genetic inclination toward AF and the genetic susceptibility to colon, esophageal, and small intestine malignancies. The mediated MR scrutiny ascertained that the genetic inclination for AF amplifies the risk profile for colon cancer via IS pathways and partially explains the susceptibility to esophageal and small intestine tumors through the HF pathway. Conclusion Our investigative endeavor has highlighted a definitive causative association between genetic inclination to AF and specific digestive system neoplasms, spotlighting IS and HF as instrumental mediators. Such revelations furnish pivotal perspectives on the complex genetic interconnections between cardiovascular anomalies and certain digestive tract tumors, emphasizing prospective therapeutic and diagnostic worthy of pursuit.
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Affiliation(s)
- Zhijie Xu
- Beijing University of Chinese Medicine, Beijing, China
- Graduate School, Beijing University of Chinese Medicine, Beijing, China
| | - Xuezhi Rao
- Beijing University of Chinese Medicine, Beijing, China
- The Second School of Clinical Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Yaxuan Xing
- Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Zhiwei Zhu
- Beijing University of Chinese Medicine, Beijing, China
- Graduate School, Beijing University of Chinese Medicine, Beijing, China
| | - Longmei Yan
- Beijing University of Chinese Medicine, Beijing, China
| | - Jian Huang
- Department of Acupuncture and Moxibustion, Dongfang Hospital, Beijing University of Chinese Medicine, Beijing, China
| | - Jingchun Zhang
- Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Ruwen Zheng
- Department of Acupuncture and Moxibustion, Dongfang Hospital, Beijing University of Chinese Medicine, Beijing, China
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239
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Hu M, Yang T, Yang Y. Causal Associations of Education Level With Cardiovascular Diseases, Cardiovascular Biomarkers, and Socioeconomic Factors. Am J Cardiol 2024; 213:76-85. [PMID: 38199144 DOI: 10.1016/j.amjcard.2023.06.044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 05/12/2023] [Accepted: 06/11/2023] [Indexed: 01/12/2024]
Abstract
An inverse association of education level with cardiovascular diseases has been documented in observational studies, yet the causality and potential mechanisms remain to be determined. To systematically investigate the causal associations of education level with cardiovascular diseases, cardiovascular biomarkers, and socioeconomic factors, a 2-sample Mendelian randomization was performed. The results revealed that higher genetically determined education level was associated with lower risks of type 2 diabetes mellitus (odds ratio [OR] 0.54, 95% confidence interval [CI] 0.47 to 0.61, p = 3.04 × 10-23), peripheral artery disease (OR 0.62, 95% CI 0.51 to 0.76, p = 2.14 × 10-06), hypertension (OR 0.62, 95% CI 0.56 to 0.70, p = 4.22 × 10-16), coronary heart disease (OR 0.62, 95% CI 0.56 to 0.69, p = 3.50 × 10-19), myocardial infarction (OR 0.62, 95% CI 0.55 to 0.69, p = 2.58 × 10-16), ischemic stroke (OR 0.67, 95% CI 0.62 to 0.74, p = 6.00 × 10-19), deep vein thrombosis (OR 0.69, 95% CI 0.55 to 0.87, p = 0.0017), atrial fibrillation (OR 0.70, 95% CI 0.57 to 0.86, p = 0.0007), cardiac death (OR 0.71, 95% CI 0.60 to 0.86, p = 0.0003), heart failure (OR 0.72, 95% CI 0.65 to 0.79, p = 6.37 × 10-12), transient ischemic attack (OR 0.76, 95% CI 0.64 to 0.90, p = 0.0010), and venous thromboembolism (OR 0.79, 95% CI 0.67 to 0.92, p = 0.0028). Systolic blood pressure, diastolic blood pressure, C-reactive protein, body mass index, waist circumference, and triglycerides were decreased, whereas telomere length was increased. Subjects with higher education were less likely to smoke, intake salt, or be exposed to air pollution and depression state. They were more likely to take physical activity and possess more household income. In conclusion, higher education may causally decrease cardiovascular diseases through socioeconomic factors and cardiovascular biomarkers. Reducing education inequality is important in the management of cardiovascular diseases.
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Affiliation(s)
- Mengjin Hu
- Department of Cardiology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Tao Yang
- Department of Cardiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Yuejin Yang
- Department of Cardiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
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240
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Ardissino M, Morley AP, Slob EAW, Schuermans A, Rayes B, Raisi-Estabragh Z, de Marvao A, Burgess S, Rogne T, Honigberg MC, Ng FS. Birth weight influences cardiac structure, function, and disease risk: evidence of a causal association. Eur Heart J 2024; 45:443-454. [PMID: 37738114 PMCID: PMC10849320 DOI: 10.1093/eurheartj/ehad631] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 09/09/2023] [Accepted: 09/10/2023] [Indexed: 09/24/2023] Open
Abstract
BACKGROUND AND AIMS Low birth weight is a common pregnancy complication, which has been associated with higher risk of cardiometabolic disease in later life. Prior Mendelian randomization (MR) studies exploring this question do not distinguish the mechanistic contributions of variants that directly influence birth weight through the foetal genome (direct foetal effects), vs. variants influencing birth weight indirectly by causing an adverse intrauterine environment (indirect maternal effects). In this study, MR was used to assess whether birth weight, independent of intrauterine influences, is associated with cardiovascular disease risk and measures of adverse cardiac structure and function. METHODS Uncorrelated (r2 < .001), genome-wide significant (P < 5 × 10-8) single nucleotide polymorphisms were extracted from genome-wide association studies summary statistics for birth weight overall, and after isolating direct foetal effects only. Inverse-variance weighted MR was utilized for analyses on outcomes of atrial fibrillation, coronary artery disease, heart failure, ischaemic stroke, and 16 measures of cardiac structure and function. Multiple comparisons were accounted for by Benjamini-Hochberg correction. RESULTS Lower genetically-predicted birth weight, isolating direct foetal effects only, was associated with an increased risk of coronary artery disease (odds ratio 1.21, 95% confidence interval 1.06-1.37; P = .031), smaller chamber volumes, and lower stroke volume, but higher contractility. CONCLUSIONS The results of this study support a causal role of low birth weight in cardiovascular disease, even after accounting for the influence of the intrauterine environment. This suggests that individuals with a low birth weight may benefit from early targeted cardiovascular disease prevention strategies, independent of whether this was linked to an adverse intrauterine environment during gestation.
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Affiliation(s)
- Maddalena Ardissino
- National Heart and Lung Institute, Imperial College London, Hammersmith Campus, Du Cane Road, London W12 0NN, UK
- Department of Medicine, School of Clinical Medicine, University of Cambridge, UK
| | - Alec P Morley
- Department of Medicine, School of Clinical Medicine, University of Cambridge, UK
| | - Eric A W Slob
- Medical Research Council Biostatistics Unit, University of Cambridge, UK
- Department of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, the Netherlands
- Erasmus University Rotterdam Institute for Behavior and Biology, Erasmus University Rotterdam, the Netherlands
- Erasmus School of Social and Behavioural Sciences, Erasmus University Rotterdam, the Netherlands
| | - Art Schuermans
- Department of Cardiovascular Sciences, KU Leuven, Flanders, Leuven, Belgium
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Bilal Rayes
- National Heart and Lung Institute, Imperial College London, Hammersmith Campus, Du Cane Road, London W12 0NN, UK
| | - Zahra Raisi-Estabragh
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, UK
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health NHS Trust, UK
| | - Antonio de Marvao
- Department of Women and Children’s Health, King’s College London, UK
- British Heart Foundation Centre of Research Excellence, School of Cardiovascular Medicine and Sciences, King’s College London, UK
- Medical Research Council, London Institute of Medical Sciences, Imperial College London, UK
| | - Stephen Burgess
- Medical Research Council Biostatistics Unit, University of Cambridge, UK
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, UK
| | - Tormod Rogne
- Department of Chronic Disease Epidemiology, Yale School of Public Health, USA
| | - Michael C Honigberg
- Department of Cardiovascular Sciences, KU Leuven, Flanders, Leuven, Belgium
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Cardiology Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Fu Siong Ng
- National Heart and Lung Institute, Imperial College London, Hammersmith Campus, Du Cane Road, London W12 0NN, UK
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Hernáez Á, Lee Y, Page CM, Skåra KH, Håberg SE, Magnus P, Njølstad PR, Andreassen OA, Corfield EC, Havdahl A, Fraser A, Burgess S, Lawlor DA, Magnus MC. Impaired glucose tolerance and cardiovascular risk factors in relation to infertility: a Mendelian randomization analysis in the Norwegian Mother, Father, and Child Cohort Study. Hum Reprod 2024; 39:436-441. [PMID: 37949105 PMCID: PMC10833082 DOI: 10.1093/humrep/dead234] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2023] [Revised: 09/18/2023] [Indexed: 11/12/2023] Open
Abstract
STUDY QUESTION Are impaired glucose tolerance (as measured by fasting glucose, glycated hemoglobin, and fasting insulin) and cardiovascular disease risk (as measured by low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglycerides, systolic blood pressure, and diastolic blood pressure) causally related to infertility? SUMMARY ANSWER Genetic instruments suggest that higher fasting insulin may increase infertility in women. WHAT IS KNOWN ALREADY Observational evidence suggests a shared etiology between impaired glucose tolerance, cardiovascular risk, and fertility problems. STUDY DESIGN, SIZE, DURATION This study included two-sample Mendelian randomization (MR) analyses, in which we used genome-wide association summary data that were publicly available for the biomarkers of impaired glucose tolerance and cardiovascular disease, and sex-specific genome-wide association studies (GWASs) of infertility conducted in the Norwegian Mother, Father, and Child Cohort Study. PARTICIPANTS/MATERIALS, SETTING, METHODS There were 68 882 women (average age 30, involved in 81 682 pregnancies) and 47 474 of their male partners (average age 33, 55 744 pregnancies) who had available genotype data and who provided self-reported information on time-to-pregnancy and use of ARTs. Of couples, 12% were infertile (having tried to conceive for ≥12 months or used ARTs to conceive). We applied the inverse variance weighted method with random effects to pool data across variants and a series of sensitivity analyses to explore genetic instrument validity. (We checked the robustness of genetic instruments and the lack of unbalanced horizontal pleiotropy, and we used methods that are robust to population stratification.) Findings were corrected for multiple comparisons by the Bonferroni method (eight exposures: P-value < 0.00625). MAIN RESULTS AND THE ROLE OF CHANCE In women, increases in genetically determined fasting insulin levels were associated with greater odds of infertility (+1 log(pmol/l): odds ratio 1.60, 95% CI 1.17 to 2.18, P-value = 0.003). The results were robust in the sensitivity analyses exploring the validity of MR assumptions and the role of pleiotropy of other cardiometabolic risk factors. There was also evidence of higher glucose and glycated hemoglobin causing infertility in women, but the findings were imprecise and did not pass our P-value threshold for multiple testing. The results for lipids and blood pressure were close to the null, suggesting that these did not cause infertility. LIMITATIONS, REASONS FOR CAUTION We did not know if underlying causes of infertility were in the woman, man, or both. Our analyses only involved couples who had conceived. We did not have data on circulating levels of cardiometabolic risk factors, and we opted to conduct an MR analysis using GWAS summary statistics. No sex-specific genetic instruments on cardiometabolic risk factors were available. Our results may be affected by selection and misclassification bias. Finally, the characteristics of our study sample limit the generalizability of our results to populations of non-European ancestry. WIDER IMPLICATIONS OF THE FINDINGS Treatments for lower fasting insulin levels may reduce the risk of infertility in women. STUDY FUNDING/COMPETING INTEREST(S) The MoBa Cohort Study is supported by the Norwegian Ministry of Health and Care Services and the Norwegian Ministry of Education and Research. This work was supported by the European Research Council [grant numbers 947684, 101071773, 293574, 101021566], the Research Council of Norway [grant numbers 262700, 320656, 274611], the South-Eastern Norway Regional Health Authority [grant numbers 2020022, 2021045], and the British Heart Foundation [grant numbers CH/F/20/90003, AA/18/1/34219]. Open Access funding was provided by the Norwegian Institute of Public Health. The funders had no role in the study design; the collection, analysis, and interpretation of data; the writing of the report; or the decision to submit the article for publication. D.A.L. has received research support from National and International government and charitable bodies, Roche Diagnostics and Medtronic for research unrelated to the current work. O.A.A. has been a consultant to HealthLytix. The rest of the authors declare that no competing interests exist. TRIAL REGISTRATION NUMBER N/A.
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Affiliation(s)
- Álvaro Hernáez
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Blanquerna School of Health Sciences, Universitat Ramon Llull, Barcelona, Spain
| | - Yunsung Lee
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Christian M Page
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Division for Mental and Physical Health, Department of Physical Health and Ageing, Norwegian Institute of Public Health, Oslo, Norway
| | - Karoline H Skåra
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Community Medicine and Global Health, Institute of Health and Society, University of Oslo, Oslo, Norway
| | - Siri E Håberg
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Per Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Pål R Njølstad
- Department of Clinical Science, Mohn Center for Diabetes Precision Medicine, University of Bergen, Bergen, Norway
- Children and Youth Clinic, Haukeland University Hospital, Bergen, Norway
| | - Ole A Andreassen
- Division of Mental Health and Addiction, Norwegian Centre for Mental Disorders Research, NORMENT, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Elizabeth C Corfield
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- Nic Waals Institute, Lovisenberg Diakonale Hospital, Oslo, Norway
| | - Alexandra Havdahl
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- Nic Waals Institute, Lovisenberg Diakonale Hospital, Oslo, Norway
- PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Abigail Fraser
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Deborah A Lawlor
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre, Bristol, UK
| | - Maria C Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
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Chi X, Zhang N, Zhang L, Fan F, Jia J, Xu M, Li J. Effects of body mass index and blood pressure on atrioventricular block: Two-sample mendelian randomization. Heart Rhythm 2024; 21:174-183. [PMID: 37918507 DOI: 10.1016/j.hrthm.2023.10.024] [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: 08/29/2023] [Revised: 10/12/2023] [Accepted: 10/26/2023] [Indexed: 11/04/2023]
Abstract
BACKGROUND Observational studies have suggested associations between some atherogenic risk factors and atrioventricular (AV) block. OBJECTIVE The purpose of this study was to investigate the causal effects of several cardiometabolic exposures on AV block and evaluate the role of coronary artery disease (CAD) as a mediator on the causal pathway by mendelian randomization analysis. METHODS Two-sample bidirectional mendelian randomization was performed to assess the causal effects of cardiometabolic traits on AV block and examine causality inversely. The exposures of interest included body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), fasting glucose, fasting insulin, low-density lipoprotein, high-density lipoprotein, and triglyceride. Multivariable mendelian randomization was then conducted to disentangle the effect of each significant exposure. Mediation effect of CAD on the causal pathways were estimated by two-step, two-sample mendelian randomization. RESULTS Genetically predicted elevation of BMI (odds ratio [OR] 1.40; 95% confidence interval [CI] 1.10-1.78; P = .006), SBP (OR 1.02; 95% CI 1.00-1.03; P = .015), and DBP (OR 1.04; 95% CI 1.01-1.07; P = .005) were significantly associated with increased AV block risk. Effects of the other exposures were insignificant. There were no reverse causal effects. Multivariable mendelian randomization showed causal effects of increased BMI, SBP, and DBP on AV block after mutual adjustment. CAD mediated 14.20% (8.82%, 16.46%), 26.32% (25.00%, 26.47,%) and 12.20% (7.69%, 15.94%) of AV block risk from BMI, SBP and DBP, respectively. CONCLUSION Elevated BMI, SBP, and DBP exhibited causal effects on AV block. The impacts were partly mediated by CAD.
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Affiliation(s)
- Xiying Chi
- Department of Cardiology, Peking University First Hospital, Xicheng District, Beijing, China; Institute of Cardiovascular Disease, Peking University First Hospital, Xicheng District, Beijing, China
| | - Nan Zhang
- Department of Cardiology, Peking University First Hospital, Xicheng District, Beijing, China; Institute of Cardiovascular Disease, Peking University First Hospital, Xicheng District, Beijing, China
| | - Long Zhang
- Department of Cardiology, Peking University First Hospital, Xicheng District, Beijing, China; Institute of Cardiovascular Disease, Peking University First Hospital, Xicheng District, Beijing, China
| | - Fangfang Fan
- Department of Cardiology, Peking University First Hospital, Xicheng District, Beijing, China; Institute of Cardiovascular Disease, Peking University First Hospital, Xicheng District, Beijing, China
| | - Jia Jia
- Department of Cardiology, Peking University First Hospital, Xicheng District, Beijing, China; Institute of Cardiovascular Disease, Peking University First Hospital, Xicheng District, Beijing, China
| | - Ming Xu
- Department of Cardiology and Institute of Vascular Medicine, Peking University Third Hospital, Haidian District, Beijing, China
| | - Jianping Li
- Department of Cardiology, Peking University First Hospital, Xicheng District, Beijing, China; Institute of Cardiovascular Disease, Peking University First Hospital, Xicheng District, Beijing, China; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, China; NHC Key Laboratory of Cardiovascular Molecular Biology and Regulatory Peptides, Peking University, Beijing, China.
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Ye Z, Zeng Q, Ning L, Huang W, Su Q. Systolic blood pressure is associated with abnormal alterations in brain cortical structure: Evidence from a Mendelian randomization study. Eur J Intern Med 2024; 120:92-98. [PMID: 37852841 DOI: 10.1016/j.ejim.2023.10.018] [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: 08/13/2023] [Revised: 09/09/2023] [Accepted: 10/13/2023] [Indexed: 10/20/2023]
Abstract
BACKGROUND Hypertension has been recognized as a significant risk factor for cerebrovascular diseases and cognitive decline. However, the specific impact of hypertension, systolic/diastolic blood pressure, pulse pressure (PP) and mean arterial pressure (MAP) on brain cortical structure remains unclear. Mendelian randomization (MR) provides a robust approach to investigate the causal relationship between blood pressure components and brain cortical changes. METHODS In this MR study, data from large-scale genome-wide association studies for blood pressure components and neuroimaging were utilized to conduct our analyses. We leveraged genetic variants associated specifically with hypertension (122,620 cases and 332,683 controls), systolic (469,767 individuals), diastolic (490,469 individuals) blood pressure, PP (810,865 individuals) and MAP (over 1 million individuals) to evaluate their effects on brain cortex surficial area (51,665 individuals) and cortex thickness (51,665 individuals). RESULTS Our findings revealed a significant correlation between systolic blood pressure and abnormal reduction in brain cortex surficial area (β=-1330.69, 95% confident interval [CI]: -2655.35 to -6.02, p = 0.0489); however, no significant relationship was found between systolic blood pressure and brain cortex thickness (β=-0.0078, 95% CI: -0.0178 to 0.0022, p = 0.1287). Additionally, no significant associations were observed between hypertension (β=-200.05, p = 0.6884; β=-0.0051, p = 0.1179, respectively), diastolic blood pressure (β=-460.63, p = 0.5160; β=0.0047, p = 0.2448, respectively), PP (β=1041.84, p = 0.3725; β=-0.0112, p = 0.2212, respectively), MAP (β=-18.84, p = 0.8841; β=0.0002, p = 0.7654, respectively) and both brain cortex surficial area and brain cortex thickness. CONCLUSION Our MR study provides evidence supporting the hypothesis that systolic blood pressure, rather than diastolic blood pressure, PP or MAP, is associated with abnormal changes in brain cortical structure.
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Affiliation(s)
- Ziliang Ye
- Department of Cardiology, Jiangbin Hospital of Guangxi Zhuang Autonomous Region, No. 85 Hedi Road, Nanning, Guangxi 530021, China
| | - Qing Zeng
- Department of Cardiology, Jiangbin Hospital of Guangxi Zhuang Autonomous Region, No. 85 Hedi Road, Nanning, Guangxi 530021, China
| | - Limeng Ning
- Department of Cardiology, Jiangbin Hospital of Guangxi Zhuang Autonomous Region, No. 85 Hedi Road, Nanning, Guangxi 530021, China
| | - Wanzhong Huang
- Department of Cardiology, Jiangbin Hospital of Guangxi Zhuang Autonomous Region, No. 85 Hedi Road, Nanning, Guangxi 530021, China
| | - Qiang Su
- Department of Cardiology, Jiangbin Hospital of Guangxi Zhuang Autonomous Region, No. 85 Hedi Road, Nanning, Guangxi 530021, China.
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244
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Oliveri A, Rebernick RJ, Kuppa A, Pant A, Chen Y, Du X, Cushing KC, Bell HN, Raut C, Prabhu P, Chen VL, Halligan BD, Speliotes EK. Comprehensive genetic study of the insulin resistance marker TG:HDL-C in the UK Biobank. Nat Genet 2024; 56:212-221. [PMID: 38200128 PMCID: PMC10923176 DOI: 10.1038/s41588-023-01625-2] [Citation(s) in RCA: 35] [Impact Index Per Article: 35.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 11/28/2023] [Indexed: 01/12/2024]
Abstract
Insulin resistance (IR) is a well-established risk factor for metabolic disease. The ratio of triglycerides to high-density lipoprotein cholesterol (TG:HDL-C) is a surrogate marker of IR. We conducted a genome-wide association study of the TG:HDL-C ratio in 402,398 Europeans within the UK Biobank. We identified 369 independent SNPs, of which 114 had a false discovery rate-adjusted P value < 0.05 in other genome-wide studies of IR making them high-confidence IR-associated loci. Seventy-two of these 114 loci have not been previously associated with IR. These 114 loci cluster into five groups upon phenome-wide analysis and are enriched for candidate genes important in insulin signaling, adipocyte physiology and protein metabolism. We created a polygenic-risk score from the high-confidence IR-associated loci using 51,550 European individuals in the Michigan Genomics Initiative. We identified associations with diabetes, hyperglyceridemia, hypertension, nonalcoholic fatty liver disease and ischemic heart disease. Collectively, this study provides insight into the genes, pathways, tissues and subtypes critical in IR.
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Affiliation(s)
- Antonino Oliveri
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Ryan J Rebernick
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Annapurna Kuppa
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Asmita Pant
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Yanhua Chen
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Xiaomeng Du
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Kelly C Cushing
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Hannah N Bell
- Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, MI, USA
| | - Chinmay Raut
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Ponnandy Prabhu
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Vincent L Chen
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Brian D Halligan
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Elizabeth K Speliotes
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA.
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA.
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245
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Levi H, Elkon R, Shamir R. The predictive capacity of polygenic risk scores for disease risk is only moderately influenced by imputation panels tailored to the target population. Bioinformatics 2024; 40:btae036. [PMID: 38265251 PMCID: PMC10868313 DOI: 10.1093/bioinformatics/btae036] [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: 08/31/2023] [Revised: 12/20/2023] [Accepted: 01/20/2024] [Indexed: 01/25/2024] Open
Abstract
MOTIVATION Polygenic risk scores (PRSs) predict individuals' genetic risk of developing complex diseases. They summarize the effect of many variants discovered in genome-wide association studies (GWASs). However, to date, large GWASs exist primarily for the European population and the quality of PRS prediction declines when applied to other ethnicities. Genetic profiling of individuals in the discovery set (on which the GWAS was performed) and target set (on which the PRS is applied) is typically done by SNP arrays that genotype a fraction of common SNPs. Therefore, a key step in GWAS analysis and PRS calculation is imputing untyped SNPs using a panel of fully sequenced individuals. The imputation results depend on the ethnic composition of the imputation panel. Imputing genotypes with a panel of individuals of the same ethnicity as the genotyped individuals typically improves imputation accuracy. However, there has been no systematic investigation into the influence of the ethnic composition of imputation panels on the accuracy of PRS predictions when applied to ethnic groups that differ from the population used in the GWAS. RESULTS We estimated the effect of imputation of the target set on prediction accuracy of PRS when the discovery and the target sets come from different ethnic groups. We analyzed binary phenotypes on ethnically distinct sets from the UK Biobank and other resources. We generated ethnically homogenous panels, imputed the target sets, and generated PRSs. Then, we assessed the prediction accuracy obtained from each imputation panel. Our analysis indicates that using an imputation panel matched to the ethnicity of the target population yields only a marginal improvement and only under specific conditions. AVAILABILITY AND IMPLEMENTATION The source code used for executing the analyses is this paper is available at https://github.com/Shamir-Lab/PRS-imputation-panels.
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Affiliation(s)
- Hagai Levi
- The Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel
- Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel
| | - Ran Elkon
- Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv 69978, Israel
| | - Ron Shamir
- The Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel
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246
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Mersha TB. From Mendel to multi-omics: shifting paradigms. Eur J Hum Genet 2024; 32:139-142. [PMID: 37468578 PMCID: PMC10853174 DOI: 10.1038/s41431-023-01420-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2023] [Revised: 05/24/2023] [Accepted: 06/22/2023] [Indexed: 07/21/2023] Open
Affiliation(s)
- Tesfaye B Mersha
- Cincinnati Children's Hospital Medical Center, Department of Pediatrics, College of Medicine, University of Cincinnati, Cincinnati, OH, USA.
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247
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Kovacheva VP, Eberhard BW, Cohen RY, Maher M, Saxena R, Gray KJ. Preeclampsia Prediction Using Machine Learning and Polygenic Risk Scores From Clinical and Genetic Risk Factors in Early and Late Pregnancies. Hypertension 2024; 81:264-272. [PMID: 37901968 PMCID: PMC10842389 DOI: 10.1161/hypertensionaha.123.21053] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 10/12/2023] [Indexed: 10/31/2023]
Abstract
BACKGROUND Preeclampsia, a pregnancy-specific condition associated with new-onset hypertension after 20-weeks gestation, is a leading cause of maternal and neonatal morbidity and mortality. Predictive tools to understand which individuals are most at risk are needed. METHODS We identified a cohort of N=1125 pregnant individuals who delivered between May 2015 and May 2022 at Mass General Brigham Hospitals with available electronic health record data and linked genetic data. Using clinical electronic health record data and systolic blood pressure polygenic risk scores derived from a large genome-wide association study, we developed machine learning (XGBoost) and logistic regression models to predict preeclampsia risk. RESULTS Pregnant individuals with a systolic blood pressure polygenic risk score in the top quartile had higher blood pressures throughout pregnancy compared with patients within the lowest quartile systolic blood pressure polygenic risk score. In the first trimester, the most predictive model was XGBoost, with an area under the curve of 0.74. In late pregnancy, with data obtained up to the delivery admission, the best-performing model was XGBoost using clinical variables, which achieved an area under the curve of 0.91. Adding the systolic blood pressure polygenic risk score to the models did not improve the performance significantly based on De Long test comparing the area under the curve of models with and without the polygenic score. CONCLUSIONS Integrating clinical factors into predictive models can inform personalized preeclampsia risk and achieve higher predictive power than the current practice. In the future, personalized tools can be implemented to identify high-risk patients for preventative therapies and timely intervention to improve adverse maternal and neonatal outcomes.
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Affiliation(s)
- Vesela P Kovacheva
- Department of Anesthesiology, Perioperative and Pain Medicine (V.P.K., B.W.E., R.Y.C.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Braden W Eberhard
- Department of Anesthesiology, Perioperative and Pain Medicine (V.P.K., B.W.E., R.Y.C.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Raphael Y Cohen
- Department of Anesthesiology, Perioperative and Pain Medicine (V.P.K., B.W.E., R.Y.C.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
- PathAI, Boston, MA (R.Y.C.)
| | - Matthew Maher
- Department of Anesthesia, Critical Care and Pain Medicine, Center for Genomic Medicine, Massachusetts General Hospital, Boston (M.M., R.S., K.J.G.)
| | - Richa Saxena
- Department of Anesthesia, Critical Care and Pain Medicine, Center for Genomic Medicine, Massachusetts General Hospital, Boston (M.M., R.S., K.J.G.)
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston (R.S.)
| | - Kathryn J Gray
- Division of Maternal-Fetal Medicine (K.J.G.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA
- Department of Anesthesia, Critical Care and Pain Medicine, Center for Genomic Medicine, Massachusetts General Hospital, Boston (M.M., R.S., K.J.G.)
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248
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Xia M, Zhong Y, Peng Y, Qian C. Breakfast skipping and traits of cardiometabolic health: A mendelian randomization study. Clin Nutr ESPEN 2024; 59:328-333. [PMID: 38220394 DOI: 10.1016/j.clnesp.2023.12.149] [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: 07/19/2023] [Revised: 12/18/2023] [Accepted: 12/27/2023] [Indexed: 01/16/2024]
Abstract
BACKGROUND Breakfast skipping has been linked to poor cardiometabolic health in observational studies, but the causality remains unknown. Herein, we used Mendelian randomization (MR) approach to elucidate the potential causal effects of breakfast skipping on cardiometabolic traits. METHODS Genetic association estimates for breakfast skipping, cardiometabolic diseases, and cardiometabolic risk factors were extracted from the UK Biobank and several large genome-wide association studies. Two-sample MR analyses were performed primarily using the inverse variance weighted method, followed by sensitivity analysis to test the reliability of results. RESULTS MR results indicated no causal relationship between breakfast shipping with coronary heart disease (odds ratio [OR]: 1.079, 95 % confidence interval [CI]: 0.817-1.426; p = 0.591), stroke (OR: 0.877, 95 % CI: 0.680-1.131; p = 0.311), and type 2 diabetes mellitus (OR: 1.114, 95 % CI: 0.631-1.970; p = 0.709). However, genetically predicted breakfast skipping was significantly associated with increased body mass index (β: 0.250, standard error [SE]: 0.079; p = 0.001), waist-to-hip ratio (β: 0.177, SE: 0.076; p = 0.019), and low-density lipoprotein cholesterol (β: 0.260, SE: 0.115; p = 0.024). We found no evidence of association of genetic liability to breakfast skipping with blood pressure, glycemic traits, and other blood lipids. Sensitivity analysis supported the above results. CONCLUSION Our study suggested that breakfast skipping is causally linked to weight gain and higher serum low-density lipoprotein cholesterol, which may mediate the increased risk of cardiometabolic diseases reported in epidemiological studies.
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Affiliation(s)
- Meng Xia
- Department of Cardiology, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, Sichuan Province, China
| | - Yi Zhong
- Department of Cardiology, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, Sichuan Province, China
| | - Yongquan Peng
- Department of Cardiology, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, Sichuan Province, China
| | - Cheng Qian
- Department of Cardiology, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, Sichuan Province, China.
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249
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Sterenborg RBTM, Steinbrenner I, Li Y, Bujnis MN, Naito T, Marouli E, Galesloot TE, Babajide O, Andreasen L, Astrup A, Åsvold BO, Bandinelli S, Beekman M, Beilby JP, Bork-Jensen J, Boutin T, Brody JA, Brown SJ, Brumpton B, Campbell PJ, Cappola AR, Ceresini G, Chaker L, Chasman DI, Concas MP, Coutinho de Almeida R, Cross SM, Cucca F, Deary IJ, Kjaergaard AD, Echouffo Tcheugui JB, Ellervik C, Eriksson JG, Ferrucci L, Freudenberg J, Fuchsberger C, Gieger C, Giulianini F, Gögele M, Graham SE, Grarup N, Gunjača I, Hansen T, Harding BN, Harris SE, Haunsø S, Hayward C, Hui J, Ittermann T, Jukema JW, Kajantie E, Kanters JK, Kårhus LL, Kiemeney LALM, Kloppenburg M, Kühnel B, Lahti J, Langenberg C, Lapauw B, Leese G, Li S, Liewald DCM, Linneberg A, Lominchar JVT, Luan J, Martin NG, Matana A, Meima ME, Meitinger T, Meulenbelt I, Mitchell BD, Møllehave LT, Mora S, Naitza S, Nauck M, Netea-Maier RT, Noordam R, Nursyifa C, Okada Y, Onano S, Papadopoulou A, Palmer CNA, Pattaro C, Pedersen O, Peters A, Pietzner M, Polašek O, Pramstaller PP, Psaty BM, Punda A, Ray D, Redmond P, Richards JB, Ridker PM, Russ TC, Ryan KA, Olesen MS, Schultheiss UT, Selvin E, Siddiqui MK, et alSterenborg RBTM, Steinbrenner I, Li Y, Bujnis MN, Naito T, Marouli E, Galesloot TE, Babajide O, Andreasen L, Astrup A, Åsvold BO, Bandinelli S, Beekman M, Beilby JP, Bork-Jensen J, Boutin T, Brody JA, Brown SJ, Brumpton B, Campbell PJ, Cappola AR, Ceresini G, Chaker L, Chasman DI, Concas MP, Coutinho de Almeida R, Cross SM, Cucca F, Deary IJ, Kjaergaard AD, Echouffo Tcheugui JB, Ellervik C, Eriksson JG, Ferrucci L, Freudenberg J, Fuchsberger C, Gieger C, Giulianini F, Gögele M, Graham SE, Grarup N, Gunjača I, Hansen T, Harding BN, Harris SE, Haunsø S, Hayward C, Hui J, Ittermann T, Jukema JW, Kajantie E, Kanters JK, Kårhus LL, Kiemeney LALM, Kloppenburg M, Kühnel B, Lahti J, Langenberg C, Lapauw B, Leese G, Li S, Liewald DCM, Linneberg A, Lominchar JVT, Luan J, Martin NG, Matana A, Meima ME, Meitinger T, Meulenbelt I, Mitchell BD, Møllehave LT, Mora S, Naitza S, Nauck M, Netea-Maier RT, Noordam R, Nursyifa C, Okada Y, Onano S, Papadopoulou A, Palmer CNA, Pattaro C, Pedersen O, Peters A, Pietzner M, Polašek O, Pramstaller PP, Psaty BM, Punda A, Ray D, Redmond P, Richards JB, Ridker PM, Russ TC, Ryan KA, Olesen MS, Schultheiss UT, Selvin E, Siddiqui MK, Sidore C, Slagboom PE, Sørensen TIA, Soto-Pedre E, Spector TD, Spedicati B, Srinivasan S, Starr JM, Stott DJ, Tanaka T, Torlak V, Trompet S, Tuhkanen J, Uitterlinden AG, van den Akker EB, van den Eynde T, van der Klauw MM, van Heemst D, Verroken C, Visser WE, Vojinovic D, Völzke H, Waldenberger M, Walsh JP, Wareham NJ, Weiss S, Willer CJ, Wilson SG, Wolffenbuttel BHR, Wouters HJCM, Wright MJ, Yang Q, Zemunik T, Zhou W, Zhu G, Zöllner S, Smit JWA, Peeters RP, Köttgen A, Teumer A, Medici M. Multi-trait analysis characterizes the genetics of thyroid function and identifies causal associations with clinical implications. Nat Commun 2024; 15:888. [PMID: 38291025 PMCID: PMC10828500 DOI: 10.1038/s41467-024-44701-9] [Show More Authors] [Citation(s) in RCA: 26] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 12/29/2023] [Indexed: 02/01/2024] Open
Abstract
To date only a fraction of the genetic footprint of thyroid function has been clarified. We report a genome-wide association study meta-analysis of thyroid function in up to 271,040 individuals of European ancestry, including reference range thyrotropin (TSH), free thyroxine (FT4), free and total triiodothyronine (T3), proxies for metabolism (T3/FT4 ratio) as well as dichotomized high and low TSH levels. We revealed 259 independent significant associations for TSH (61% novel), 85 for FT4 (67% novel), and 62 novel signals for the T3 related traits. The loci explained 14.1%, 6.0%, 9.5% and 1.1% of the total variation in TSH, FT4, total T3 and free T3 concentrations, respectively. Genetic correlations indicate that TSH associated loci reflect the thyroid function determined by free T3, whereas the FT4 associations represent the thyroid hormone metabolism. Polygenic risk score and Mendelian randomization analyses showed the effects of genetically determined variation in thyroid function on various clinical outcomes, including cardiovascular risk factors and diseases, autoimmune diseases, and cancer. In conclusion, our results improve the understanding of thyroid hormone physiology and highlight the pleiotropic effects of thyroid function on various diseases.
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Affiliation(s)
- Rosalie B T M Sterenborg
- Department of Internal Medicine, Division of Endocrinology, Radboud University Medical Center, Nijmegen, The Netherlands
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Inga Steinbrenner
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Yong Li
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | | | - Tatsuhiko Naito
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Eirini Marouli
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
- Digital Environment Research Institute, Queen Mary University of London, London, UK
| | - Tessel E Galesloot
- Department for Health Evidence, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Oladapo Babajide
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Laura Andreasen
- Laboratory for Molecular Cardiology, Department of Cardiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
- Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Arne Astrup
- Department of Obesity and Nutritional Sciences, The Novo Nordisk Foundation, Hellerup, Denmark
| | - Bjørn Olav Åsvold
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Endocrinology, Clinic of Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | | | - Marian Beekman
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - John P Beilby
- School of Biomedical Sciences, The University of Western Australia, Perth, WA, 6009, Australia
| | - Jette Bork-Jensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Thibaud Boutin
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Suzanne J Brown
- Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, 6009, Australia
| | - Ben Brumpton
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Levanger, 7600, Norway
| | - Purdey J Campbell
- Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, 6009, Australia
| | - Anne R Cappola
- Division of Endocrinology, Diabetes, and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
| | - Graziano Ceresini
- Oncological Endocrinology, University of Parma, Parma, Italy
- Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
| | - Layal Chaker
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Centre, Rotterdam, The Netherlands
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, USA
- Harvard Medical School, Boston, USA
| | - Maria Pina Concas
- Institute for Maternal and Child Health - IRCCS "Burlo Garofolo", Trieste, Italy
| | - Rodrigo Coutinho de Almeida
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Simone M Cross
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Francesco Cucca
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, 09042, Monserrato (CA), Italy
- Università di Sassari, Dipartimento di Scienze Biomediche, V.le San Pietro, 07100, Sassari (SS), Italy
| | - Ian J Deary
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, EH8 9JZ, Edinburgh, United Kingdom
| | - Alisa Devedzic Kjaergaard
- Steno Diabetes Center Aarhus, Aarhus University Hospital, Palle Juul-Jensens Blvd. 11, Entrance A, 8200, Aarhus, Denmark
| | - Justin B Echouffo Tcheugui
- Division of Endocrinology, Diabetes, and Metabolism, Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA
| | - Christina Ellervik
- Harvard Medical School, Boston, USA
- Faculty of Medical Science, Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Department of Laboratory Medicine, Boston Children's Hospital, Boston, MA, USA
- Department of Clinical Biochemistry, Zealand University Hospital, Køge, Denmark
| | - Johan G Eriksson
- Department of General Practice and Primary health Care, University of Helsinki, Helsinki, Finland
- National University Singapore, Yong Loo Lin School of Medicine, Department of Obstetrics and Gynecology, Singapore, Singapore
| | - Luigi Ferrucci
- Longitudinal Study Section, National Institute on Aging, Baltimore, MD, USA
| | | | - Christian Fuchsberger
- Institute for Biomedicine (affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy
| | - Christian Gieger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Franco Giulianini
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, USA
| | - Martin Gögele
- Institute for Biomedicine (affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy
| | - Sarah E Graham
- Department of Internal Medicine, Cardiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ivana Gunjača
- Department of Medical Biology, University of Split, School of Medicine, Split, Croatia
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Barbara N Harding
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Barcelona Institute for Global Health, Barcelona, Spain
| | - Sarah E Harris
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, EH8 9JZ, Edinburgh, United Kingdom
| | - Stig Haunsø
- Laboratory for Molecular Cardiology, Department of Cardiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Jennie Hui
- Pathwest Laboratory Medicine WA, Nedlands, WA, 6009, Australia
- School of Population and Global Health, The University of Western Australia, Crawley, WA, 6009, Australia
| | - Till Ittermann
- Institute for Community Medicine, University Medicine Greifswald, 17475, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
- Netherlands Heart Institute, Utrecht, the Netherlands
| | - Eero Kajantie
- Finnish Institute for Health and Welfare, Population Health Unit, Helsinki and Oulu, Oulu, Finland
- Clinical Medicine Research Unit, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
| | - Jørgen K Kanters
- Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
- Center of Physiological Research, University of California San Francisco, San Francisco, USA
| | - Line L Kårhus
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark
| | - Lambertus A L M Kiemeney
- Department for Health Evidence, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Urology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Margreet Kloppenburg
- Departments of Rheumatology and Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Brigitte Kühnel
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Jari Lahti
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
- Computational Medicine, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - Bruno Lapauw
- Department of Endocrinology, Ghent University Hospital, C. Heymanslaan 10, 9000, Ghent, Belgium
| | | | - Shuo Li
- Department of Biostatistics, Boston University, Boston, MA, USA
| | - David C M Liewald
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, EH8 9JZ, Edinburgh, United Kingdom
| | - Allan Linneberg
- Center of Physiological Research, University of California San Francisco, San Francisco, USA
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jesus V T Lominchar
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jian'an Luan
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | | | - Antonela Matana
- Department of Medical Biology, University of Split, School of Medicine, Split, Croatia
| | - Marcel E Meima
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Thomas Meitinger
- Institute for Human Genetics, Technical University of Munich, Munich, Germany
| | - Ingrid Meulenbelt
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Braxton D Mitchell
- University of Maryland School of Medicine, Division of Endocrinology, Diabetes and Nutrition, Baltimore, USA
- Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore, MD, 21201, USA
| | - Line T Møllehave
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark
| | - Samia Mora
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, USA
- Harvard Medical School, Boston, USA
| | - Silvia Naitza
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, 09042, Monserrato (CA), Italy
| | - Matthias Nauck
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Romana T Netea-Maier
- Department of Internal Medicine, Division of Endocrinology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Casia Nursyifa
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
- Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan
- Premium Research Institute for Human Metaverse Medicine (WPI-PRIMe), Osaka University, Suita, Japan
| | - Stefano Onano
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, 09042, Monserrato (CA), Italy
| | - Areti Papadopoulou
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Colin N A Palmer
- Division of Population Health Genomics, School of Medicine, University of Dundee, DD19SY, Dundee, UK
| | - Cristian Pattaro
- Institute for Biomedicine (affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Center for Clinical Metabolic Research, Herlev-Gentofte University Hospital, Copenhagen, Denmark
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Maik Pietzner
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
- Computational Medicine, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - Ozren Polašek
- Department of Public Health, University of Split, School of Medicine, Split, Croatia
- Algebra University College, Zagreb, Croatia
| | - Peter P Pramstaller
- Institute for Biomedicine (affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Departments of Epidemiology and Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Ante Punda
- Department of Nuclear Medicine, University Hospital Split, Split, Croatia
| | - Debashree Ray
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA
| | - Paul Redmond
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, EH8 9JZ, Edinburgh, United Kingdom
| | - J Brent Richards
- Lady Davis Institute, Jewish General Hospital, Montreal, Quebec, H3T 1E2, Canada
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, USA
- Harvard Medical School, Boston, USA
| | - Tom C Russ
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, EH8 9JZ, Edinburgh, United Kingdom
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, United Kingdom
| | - Kathleen A Ryan
- University of Maryland School of Medicine, Division of Endocrinology, Diabetes and Nutrition, Baltimore, USA
| | - Morten Salling Olesen
- Laboratory for Molecular Cardiology, Department of Cardiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
- Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ulla T Schultheiss
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
- Department of Medicine IV - Nephrology and Primary Care, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Elizabeth Selvin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA
| | - Moneeza K Siddiqui
- Wolfson Institute of Population Health, Queen Mary University of London, London, UK
| | - Carlo Sidore
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, 09042, Monserrato (CA), Italy
| | - P Eline Slagboom
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Thorkild I A Sørensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Public Health, Section of Epidemiology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Enrique Soto-Pedre
- Division of Population Health Genomics, School of Medicine, University of Dundee, DD19SY, Dundee, UK
| | - Tim D Spector
- The Department of Twin Research & Genetic Epidemiology, King's College London, St Thomas' Campus, Lambeth Palace Road, London, SE1 7EH, UK
| | - Beatrice Spedicati
- Institute for Maternal and Child Health - IRCCS "Burlo Garofolo", Trieste, Italy
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy
| | - Sundararajan Srinivasan
- Division of Population Health Genomics, School of Medicine, University of Dundee, DD19SY, Dundee, UK
| | - John M Starr
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, United Kingdom
| | - David J Stott
- Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom
| | - Toshiko Tanaka
- Longitudinal Study Section, National Institute on Aging, Baltimore, MD, USA
| | - Vesela Torlak
- Department of Nuclear Medicine, University Hospital Split, Split, Croatia
| | - Stella Trompet
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Johanna Tuhkanen
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - André G Uitterlinden
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Erik B van den Akker
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
- Leiden Computational Biology Center, Leiden University Medical Center, Leiden, The Netherlands
- Department of Pattern Recognition and Bioinformatics, Delft University of Technology, Delft, The Netherlands
| | - Tibbert van den Eynde
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - Melanie M van der Klauw
- Department of Endocrinology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Diana van Heemst
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Charlotte Verroken
- Department of Endocrinology, Ghent University Hospital, C. Heymanslaan 10, 9000, Ghent, Belgium
| | - W Edward Visser
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Dina Vojinovic
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Centre, Rotterdam, The Netherlands
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, 17475, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
| | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - John P Walsh
- Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, 6009, Australia
- Medical School, The University of Western Australia, Crawley, WA, 6009, Australia
| | - Nicholas J Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | - Stefan Weiss
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Cristen J Willer
- Department of Internal Medicine, Cardiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Scott G Wilson
- School of Biomedical Sciences, The University of Western Australia, Perth, WA, 6009, Australia
- Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, 6009, Australia
- The Department of Twin Research & Genetic Epidemiology, King's College London, St Thomas' Campus, Lambeth Palace Road, London, SE1 7EH, UK
| | - Bruce H R Wolffenbuttel
- Department of Endocrinology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Hanneke J C M Wouters
- Department of Endocrinology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Margaret J Wright
- Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia
| | - Qiong Yang
- Department of Biostatistics, Boston University, Boston, MA, USA
| | - Tatijana Zemunik
- Department of Medical Biology, University of Split, School of Medicine, Split, Croatia
- Department of Nuclear Medicine, University Hospital Split, Split, Croatia
| | - Wei Zhou
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Gu Zhu
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Sebastian Zöllner
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Johannes W A Smit
- Department of Internal Medicine, Division of Endocrinology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Robin P Peeters
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA
- CIBSS - Centre for Integrative Biological Signalling Studies, Albert-Ludwigs-Universität Freiburg, Freiburg, Germany
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, 17475, Greifswald, Germany.
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany.
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany.
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Bialystok, Poland.
| | - Marco Medici
- Department of Internal Medicine, Division of Endocrinology, Radboud University Medical Center, Nijmegen, The Netherlands.
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands.
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250
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Bergstedt J, Pasman JA, Ma Z, Harder A, Yao S, Parker N, Treur JL, Smit DJA, Frei O, Shadrin A, Meijsen JJ, Shen Q, Hägg S, Tornvall P, Buil A, Werge T, Hjerling-Leffler J, Als TD, Børglum AD, Lewis CM, McIntosh AM, Valdimarsdóttir UA, Andreassen OA, Sullivan PF, Lu Y, Fang F. Distinct genomic signatures and modifiable risk factors underly the comorbidity between major depressive disorder and cardiovascular disease. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.09.01.23294931. [PMID: 37693619 PMCID: PMC10491387 DOI: 10.1101/2023.09.01.23294931] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Major depressive disorder (MDD) and cardiovascular disease (CVD) are often comorbid, resulting in excess morbidity and mortality. Using genomic data, this study elucidates biological mechanisms, key risk factors, and causal pathways underlying their comorbidity. We show that CVDs share a large proportion of their genetic risk factors with MDD. Multivariate genome-wide association analysis of the shared genetic liability between MDD and atherosclerotic CVD (ASCVD) revealed seven novel loci and distinct patterns of tissue and brain cell-type enrichments, suggesting a role for the thalamus. Part of the genetic overlap was explained by shared inflammatory, metabolic, and psychosocial/lifestyle risk factors. Finally, we found support for causal effects of genetic liability to MDD on CVD risk, but not from most CVDs to MDD, and demonstrated that the causal effects were partly explained by metabolic and psychosocial/lifestyle factors. The distinct signature of MDD-ASCVD comorbidity aligns with the idea of an immunometabolic sub-type of MDD more strongly associated with CVD than overall MDD. In summary, we identify plausible biological mechanisms underlying MDD-CVD comorbidity, as well as key modifiable risk factors for prevention of CVD in individuals with MDD.
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Affiliation(s)
- Jacob Bergstedt
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Joëlle A Pasman
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Ziyan Ma
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Arvid Harder
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Shuyang Yao
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department Medical Biochemistry and Biophysics, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Nadine Parker
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Jorien L Treur
- Genetic Epidemiology, Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Dirk J A Smit
- Genetic Epidemiology, Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Oleksandr Frei
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Alexey Shadrin
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Joeri J Meijsen
- Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
| | - Qing Shen
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Clinical Research Center for Mental Disorders, Shanghai Pudong New Area Mental Health Center, Tongji University School of Medicine, Shanghai, China
- Institute for Advanced Study, Tongji University, Shanghai, China
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Per Tornvall
- Department of Clinical Science and Education Södersjukhuset, Karolinska Institutet, Stockholm, Sweden
| | - Alfonso Buil
- Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
| | - Thomas Werge
- Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Copenhagen, Denmark
- Lundbeck Foundation GeoGenetics Centre, GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jens Hjerling-Leffler
- Department Medical Biochemistry and Biophysics, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Thomas D Als
- Department of Molecular Medicine (MOMA), Molecular Diagnostic Laboratory, Aarhus University Hospital, Aarhus, Denmark
| | - Anders D Børglum
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Cathryn M Lewis
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK
- Department of Medical and Molecular Genetics, King's College London, London, UK
| | - Andrew M McIntosh
- Centre for Clinical Brain Sciences, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
- Centre for Genomics and Experimental Medicine, University of Edinburgh, Edinburgh, UK
| | - Unnur A Valdimarsdóttir
- Centre of Public Health Sciences, Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Epidemiology, Harvard TH Chan School of Public Health, Harvard University, Boston, Massachusetts, USA
| | - Ole A Andreassen
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- K.G. Jebsen Centre for Neurodevelopmental disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Patrick F Sullivan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Departments of Genetics and Psychiatry, University of North Carolina at Chapel Hill, NC, USA
| | - Yi Lu
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Fang Fang
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
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