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Piga NN, Boua PR, Soremekun C, Shrine N, Coley K, Brandenburg JT, Tobin MD, Ramsay M, Fatumo S, Choudhury A, Batini C. Genetic insights into smoking behaviours in 10,558 men of African ancestry from continental Africa and the UK. Sci Rep 2022; 12:18828. [PMID: 36335192 PMCID: PMC9637114 DOI: 10.1038/s41598-022-22218-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Accepted: 10/11/2022] [Indexed: 11/08/2022] Open
Abstract
Smoking is a leading risk factor for many of the top ten causes of death worldwide. Of the 1.3 billion smokers globally, 80% live in low- and middle-income countries, where the number of deaths due to tobacco use is expected to double in the next decade according to the World Health Organization. Genetic studies have helped to identify biological pathways for smoking behaviours, but have mostly focussed on individuals of European ancestry or living in either North America or Europe. We performed a genome-wide association study of two smoking behaviour traits in 10,558 men of African ancestry living in five African countries and the UK. Eight independent variants were associated with either smoking initiation or cessation at P-value < 5 × 10-6, four being monomorphic or rare in European populations. Gene prioritisation strategy highlighted five genes, including SEMA6D, previously described as associated with several smoking behaviour traits. These results confirm the importance of analysing underrepresented populations in genetic epidemiology, and the urgent need for larger genomic studies to boost discovery power to better understand smoking behaviours, as well as many other traits.
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Affiliation(s)
- Noemi-Nicole Piga
- Genetic Epidemiology Group, Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Palwende Romuald Boua
- Clinical Research Unit of Nanoro, Institut de Recherche en Sciences de La Santé, Nanoro, Burkina Faso
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Division of Human Genetics, National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Chisom Soremekun
- Department of Immunology and Molecular Biology, College of Health Science, Makerere University, Kampala, Uganda
- H3Africa Bioinformatics Network (H3ABioNet) Node, Center for Genomics Research and Innovation (CGRI), National Biotechnology Development Agency CGRI/NABDA, Abuja, Nigeria
- The African Computational Genomics (TACG) Research Group, MRC/UVRI LSHTM Uganda Research Unit, Entebbe, Uganda
| | - Nick Shrine
- Genetic Epidemiology Group, Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Kayesha Coley
- Genetic Epidemiology Group, Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Jean-Tristan Brandenburg
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Martin D Tobin
- Genetic Epidemiology Group, Department of Population Health Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Michèle Ramsay
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Division of Human Genetics, National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Segun Fatumo
- H3Africa Bioinformatics Network (H3ABioNet) Node, Center for Genomics Research and Innovation (CGRI), National Biotechnology Development Agency CGRI/NABDA, Abuja, Nigeria
- The African Computational Genomics (TACG) Research Group, MRC/UVRI LSHTM Uganda Research Unit, Entebbe, Uganda
- Department of Non-Communicable Disease Epidemiology (NCDE), London School of Hygiene and Tropical Medicine, London, UK
| | - Ananyo Choudhury
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Chiara Batini
- Genetic Epidemiology Group, Department of Population Health Sciences, University of Leicester, Leicester, UK.
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152
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Mishra A, Malik R, Hachiya T, Jürgenson T, Namba S, Posner DC, Kamanu FK, Koido M, Le Grand Q, Shi M, He Y, Georgakis MK, Caro I, Krebs K, Liaw YC, Vaura FC, Lin K, Winsvold BS, Srinivasasainagendra V, Parodi L, Bae HJ, Chauhan G, Chong MR, Tomppo L, Akinyemi R, Roshchupkin GV, Habib N, Jee YH, Thomassen JQ, Abedi V, Cárcel-Márquez J, Nygaard M, Leonard HL, Yang C, Yonova-Doing E, Knol MJ, Lewis AJ, Judy RL, Ago T, Amouyel P, Armstrong ND, Bakker MK, Bartz TM, Bennett DA, Bis JC, Bordes C, Børte S, Cain A, Ridker PM, Cho K, Chen Z, Cruchaga C, Cole JW, de Jager PL, de Cid R, Endres M, Ferreira LE, Geerlings MI, Gasca NC, Gudnason V, Hata J, He J, Heath AK, Ho YL, Havulinna AS, Hopewell JC, Hyacinth HI, Inouye M, Jacob MA, Jeon CE, Jern C, Kamouchi M, Keene KL, Kitazono T, Kittner SJ, Konuma T, Kumar A, Lacaze P, Launer LJ, Lee KJ, Lepik K, Li J, Li L, Manichaikul A, Markus HS, Marston NA, Meitinger T, Mitchell BD, Montellano FA, Morisaki T, Mosley TH, Nalls MA, Nordestgaard BG, O'Donnell MJ, Okada Y, Onland-Moret NC, Ovbiagele B, Peters A, Psaty BM, Rich SS, et alMishra A, Malik R, Hachiya T, Jürgenson T, Namba S, Posner DC, Kamanu FK, Koido M, Le Grand Q, Shi M, He Y, Georgakis MK, Caro I, Krebs K, Liaw YC, Vaura FC, Lin K, Winsvold BS, Srinivasasainagendra V, Parodi L, Bae HJ, Chauhan G, Chong MR, Tomppo L, Akinyemi R, Roshchupkin GV, Habib N, Jee YH, Thomassen JQ, Abedi V, Cárcel-Márquez J, Nygaard M, Leonard HL, Yang C, Yonova-Doing E, Knol MJ, Lewis AJ, Judy RL, Ago T, Amouyel P, Armstrong ND, Bakker MK, Bartz TM, Bennett DA, Bis JC, Bordes C, Børte S, Cain A, Ridker PM, Cho K, Chen Z, Cruchaga C, Cole JW, de Jager PL, de Cid R, Endres M, Ferreira LE, Geerlings MI, Gasca NC, Gudnason V, Hata J, He J, Heath AK, Ho YL, Havulinna AS, Hopewell JC, Hyacinth HI, Inouye M, Jacob MA, Jeon CE, Jern C, Kamouchi M, Keene KL, Kitazono T, Kittner SJ, Konuma T, Kumar A, Lacaze P, Launer LJ, Lee KJ, Lepik K, Li J, Li L, Manichaikul A, Markus HS, Marston NA, Meitinger T, Mitchell BD, Montellano FA, Morisaki T, Mosley TH, Nalls MA, Nordestgaard BG, O'Donnell MJ, Okada Y, Onland-Moret NC, Ovbiagele B, Peters A, Psaty BM, Rich SS, Rosand J, Sabatine MS, Sacco RL, Saleheen D, Sandset EC, Salomaa V, Sargurupremraj M, Sasaki M, Satizabal CL, Schmidt CO, Shimizu A, Smith NL, Sloane KL, Sutoh Y, Sun YV, Tanno K, Tiedt S, Tatlisumak T, Torres-Aguila NP, Tiwari HK, Trégouët DA, Trompet S, Tuladhar AM, Tybjærg-Hansen A, van Vugt M, Vibo R, Verma SS, Wiggins KL, Wennberg P, Woo D, Wilson PWF, Xu H, Yang Q, Yoon K, Millwood IY, Gieger C, Ninomiya T, Grabe HJ, Jukema JW, Rissanen IL, Strbian D, Kim YJ, Chen PH, Mayerhofer E, Howson JMM, Irvin MR, Adams H, Wassertheil-Smoller S, Christensen K, Ikram MA, Rundek T, Worrall BB, Lathrop GM, Riaz M, Simonsick EM, Kõrv J, França PHC, Zand R, Prasad K, Frikke-Schmidt R, de Leeuw FE, Liman T, Haeusler KG, Ruigrok YM, Heuschmann PU, Longstreth WT, Jung KJ, Bastarache L, Paré G, Damrauer SM, Chasman DI, Rotter JI, Anderson CD, Zwart JA, Niiranen TJ, Fornage M, Liaw YP, Seshadri S, Fernández-Cadenas I, Walters RG, Ruff CT, Owolabi MO, Huffman JE, Milani L, Kamatani Y, Dichgans M, Debette S. Stroke genetics informs drug discovery and risk prediction across ancestries. Nature 2022; 611:115-123. [PMID: 36180795 PMCID: PMC9524349 DOI: 10.1038/s41586-022-05165-3] [Show More Authors] [Citation(s) in RCA: 248] [Impact Index Per Article: 82.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 07/29/2022] [Indexed: 01/29/2023]
Abstract
Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.
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Affiliation(s)
- Aniket Mishra
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France
| | - Rainer Malik
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Tsuyoshi Hachiya
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate, Japan
| | - Tuuli Jürgenson
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
- Institute of Mathematics and Statistics, University of Tartu, Tartu, Estonia
| | - Shinichi Namba
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Daniel C Posner
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Frederick K Kamanu
- TIMI Study Group, Boston, MA, USA
- Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Masaru Koido
- Division of Molecular Pathology, Institute of Medical Sciences, The University of Tokyo, Tokyo, Japan
- Laboratory of Complex Trait Genomics, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Quentin Le Grand
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France
| | - Mingyang Shi
- Laboratory of Complex Trait Genomics, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Yunye He
- Laboratory of Complex Trait Genomics, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Marios K Georgakis
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ilana Caro
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France
| | - Kristi Krebs
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Yi-Ching Liaw
- Laboratory of Clinical Genome Sequencing, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, Taichung, Taiwan
| | - Felix C Vaura
- Department of Internal Medicine, University of Turku, Turku, Finland
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Turku, Finland
| | - Kuang Lin
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Bendik Slagsvold Winsvold
- Department of Research and Innovation, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Vinodh Srinivasasainagendra
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Livia Parodi
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Hee-Joon Bae
- Department of Neurology and Cerebrovascular Disease Center, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Republic of Korea
| | | | - Michael R Chong
- Thrombosis and Atherosclerosis Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, Ontario, Canada
- Department of Pathology and Molecular Medicine, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Liisa Tomppo
- Department of Neurology, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Rufus Akinyemi
- Center for Genomic and Precision Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
- Neuroscience and Ageing Research Unit Institute for Advanced Medical Research and Training, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Gennady V Roshchupkin
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Naomi Habib
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Yon Ho Jee
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Jesper Qvist Thomassen
- Department of Clinical Biochemistry, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark
| | - Vida Abedi
- Department of Molecular and Functional Genomics, Weis Center for Research, Geisinger Health System, Danville, VA, USA
- Department of Public Health Sciences, College of Medicine, The Pennsylvania State University, State College, PA, USA
| | - Jara Cárcel-Márquez
- Stroke Pharmacogenomics and Genetics Laboratory, Biomedical Research Institute Sant Pau (IIB Sant Pau), Barcelona, Spain
- Departament de Medicina, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Marianne Nygaard
- The Danish Twin Registry, Department of Public Health, University of Southern Denmark, Odense, Denmark
- Department of Clinical Genetics, Odense University Hospital, Odense, Denmark
| | - Hampton L Leonard
- Center for Alzheimer's and Related Dementias, National Institutes of Health, Bethesda, MD, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Data Tecnica International, Glen Echo, MD, USA
| | - Chaojie Yang
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, USA
| | - Ekaterina Yonova-Doing
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Department of Genetics, Novo Nordisk Research Centre Oxford, Oxford, UK
| | - Maria J Knol
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Adam J Lewis
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Renae L Judy
- Department of Surgery, University of Pennsylvania, Philadelphia, PA, USA
| | - Tetsuro Ago
- Department of Medicine and Clinical Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Philippe Amouyel
- University of Lille, INSERM U1167, RID-AGE, LabEx DISTALZ, Risk Factors and Molecular Determinants of Aging-Related Diseases, Lille, France
- CHU Lille, Public Health Department, Lille, France
- Institut Pasteur de Lille, Lille, France
| | - Nicole D Armstrong
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Mark K Bakker
- UMC Utrecht Brain Center, Department of Neurology and Neurosurgery, University Medical Center Utrecht, University Utrecht, Utrecht, The Netherlands
| | - Traci M Bartz
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Constance Bordes
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France
| | - Sigrid Børte
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
- Research and Communication Unit for Musculoskeletal Health (FORMI), Department of Research and Innovation, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
| | - Anael Cain
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Zhengming Chen
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, University of Oxford, Oxford, UK
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, Saint Louis, MO, USA
| | - John W Cole
- VA Maryland Health Care System, Baltimore, MD, USA
- Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Phil L de Jager
- Program in Medical and Population Genetics, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
- Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, New York, NY, USA
| | - Rafael de Cid
- GenomesForLife-GCAT Lab Group, Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain
| | - Matthias Endres
- Klinik und Hochschulambulanz für Neurologie, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Center for Stroke Research Berlin, Berlin, Germany
- German Center for Neurodegenerative Diseases (DZNE), partner site Berlin, Berlin, Germany
- German Centre for Cardiovascular Research (DZHK), partner site Berlin, Berlin, Germany
| | - Leslie E Ferreira
- Post-Graduation Program on Health and Environment, Department of Medicine and Joinville Stroke Biobank, University of the Region of Joinville, Santa Catarina, Brazil
| | - Mirjam I Geerlings
- Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Natalie C Gasca
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Jun Hata
- Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Jing He
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Alicia K Heath
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Yuk-Lam Ho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Aki S Havulinna
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
- Institute for Molecular Medicine Finland, FIMM-HiLIFE, Helsinki, Finland
| | - Jemma C Hopewell
- Clinical Trial Service and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Hyacinth I Hyacinth
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Michael Inouye
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
| | - Mina A Jacob
- Department of Neurology, Donders Center for Medical Neuroscience, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Christina E Jeon
- Los Angeles County Department of Public Health, Los Angeles, CA, USA
| | - Christina Jern
- Institute of Biomedicine, Department of Laboratory Medicine, the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Clinical Genetics and Genomics, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Masahiro Kamouchi
- Department of Health Care Administration and Management, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Keith L Keene
- Department of Biology, Brody School of Medicine Center for Health Disparities, East Carolina University, Greenville, NC, USA
| | - Takanari Kitazono
- Department of Medicine and Clinical Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Steven J Kittner
- Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, USA
- Department of Neurology and Geriatric Research and Education Clinical Center, VA Maryland Health Care System, Baltimore, MD, USA
| | - Takahiro Konuma
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Amit Kumar
- Rajendra Institute of Medical Sciences, Ranchi, India
| | - Paul Lacaze
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Lenore J Launer
- Intramural Research Program, National Institute on Aging, NIH, Baltimore, MD, USA
| | - Keon-Joo Lee
- Department of Neurology, Korea University Guro Hospital, Seoul, Republic of Korea
| | - Kaido Lepik
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- University Center for Primary Care and Public Health, Lausanne, Switzerland
| | - Jiang Li
- Department of Molecular and Functional Genomics, Weis Center for Research, Geisinger Health System, Danville, VA, USA
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Ani Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Hugh S Markus
- Stroke Research Group, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Nicholas A Marston
- TIMI Study Group, Boston, MA, USA
- Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Thomas Meitinger
- Institute of Human Genetics, Technical University of Munich, Munich, Germany
- Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Braxton D Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore, MD, USA
| | - Felipe A Montellano
- Institute of Clinical Epidemiology and Biometry, University of Würzburg, Würzburg, Germany
- Department of Neurology, University Hospital Würzburg, Würzburg, Germany
| | - Takayuki Morisaki
- Division of Molecular Pathology, Institute of Medical Sciences, The University of Tokyo, Tokyo, Japan
| | - Thomas H Mosley
- The MIND Center, University of Mississippi Medical Center, Jackson, MS, USA
| | - Mike A Nalls
- Center for Alzheimer's and Related Dementias, National Institutes of Health, Bethesda, MD, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Data Tecnica International, Glen Echo, MD, USA
| | - Børge G Nordestgaard
- Department of Clinical Biochemistry, Copenhagen University Hospital-Herlev and Gentofte, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Martin J O'Donnell
- College of Medicine Nursing and Health Science, NUI Galway, Galway, Ireland
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Department of Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Japan
- Center for Infectious Disease Education and Research (CiDER), Osaka University, Suita, Japan
| | - N Charlotte Onland-Moret
- Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Bruce Ovbiagele
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München,, German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig Maximilian University Munich, Munich, Germany
- German Centre for Cardiovascular Research (DZHK), partner site Munich, Munich, Germany
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Jonathan Rosand
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
- McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, USA
| | - Marc S Sabatine
- TIMI Study Group, Boston, MA, USA
- Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ralph L Sacco
- Department of Neurology, University of Miami Miller School of Medicine, Miami, FL, USA
- Evelyn F. McKnight Brain Institute, Gainesville, FL, USA
| | - Danish Saleheen
- Division of Cardiology, Department of Medicine, Columbia University, New York, NY, USA
| | - Else Charlotte Sandset
- Stroke Unit, Department of Neurology, Oslo University Hospital, Oslo, Norway
- Research and Development, The Norwegian Air Ambulance Foundation, Oslo, Norway
| | - Veikko Salomaa
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Muralidharan Sargurupremraj
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Makoto Sasaki
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate, Japan
| | - Claudia L Satizabal
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Carsten O Schmidt
- University Medicine Greifswald, Institute for Community Medicine, SHIP/KEF, Greifswald, Germany
| | - Atsushi Shimizu
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate, Japan
| | - Nicholas L Smith
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, WA, USA
- Department of Veterans Affairs Office of Research and Development, Seattle Epidemiologic Research and Information Center, Seattle, WA, USA
| | - Kelly L Sloane
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Yoichi Sutoh
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate, Japan
| | - Yan V Sun
- Atlanta VA Health Care System, Decatur, GA, USA
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
| | - Kozo Tanno
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate, Japan
| | - Steffen Tiedt
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Turgut Tatlisumak
- Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska Unviersity Hospital, Gothenburg, Sweden
| | - Nuria P Torres-Aguila
- Stroke Pharmacogenomics and Genetics Laboratory, Biomedical Research Institute Sant Pau (IIB Sant Pau), Barcelona, Spain
| | - Hemant K Tiwari
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - David-Alexandre Trégouët
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France
| | - Stella Trompet
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands
- Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Anil Man Tuladhar
- Department of Neurology, Donders Center for Medical Neuroscience, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Anne Tybjærg-Hansen
- Department of Clinical Biochemistry, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Marion van Vugt
- Division Heart & Lungs, Department of Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Riina Vibo
- Department of Neurology and Neurosurgery, University of Tartu, Tartu, Estonia
| | - Shefali S Verma
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Kerri L Wiggins
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Patrik Wennberg
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Daniel Woo
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Peter W F Wilson
- Atlanta VA Health Care System, Decatur, GA, USA
- Department of Medicine, Division of Cardiovascular Disease, Emory University School of Medicine, Atlanta, GA, USA
| | - Huichun Xu
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Qiong Yang
- Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Kyungheon Yoon
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju, Republic of Korea
| | - Iona Y Millwood
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, University of Oxford, Oxford, UK
| | - Christian Gieger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Toshiharu Ninomiya
- Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), site Rostock/Greifswald, Rostock, Germany
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands
- Netherlands Heart Institute, Utrecht, The Netherlands
- Einthoven Laboratory for Experimental Vascular Medicine, LUMC, Leiden, The Netherlands
| | - Ina L Rissanen
- Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Daniel Strbian
- Department of Neurology, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Young Jin Kim
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju, Republic of Korea
| | - Pei-Hsin Chen
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, Taichung, Taiwan
| | - Ernst Mayerhofer
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Joanna M M Howson
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Department of Genetics, Novo Nordisk Research Centre Oxford, Oxford, UK
| | - Marguerite R Irvin
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Hieab Adams
- Department of Clinical Genetics, Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
- Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Sylvia Wassertheil-Smoller
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, New York, NY, USA
| | - Kaare Christensen
- The Danish Twin Registry, Department of Public Health, University of Southern Denmark, Odense, Denmark
- Department of Clinical Genetics, Odense University Hospital, Odense, Denmark
- Department of Clinical Biochemistry and Pharmacology, Odense University Hospital, Odense, Denmark
| | - Mohammad A Ikram
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Tatjana Rundek
- Department of Neurology, University of Miami Miller School of Medicine, Miami, FL, USA
- Evelyn F. McKnight Brain Institute, Gainesville, FL, USA
| | - Bradford B Worrall
- Department of Neurology, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Science, University of Virginia, Charlottesville, VA, USA
| | | | - Moeen Riaz
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Eleanor M Simonsick
- Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, USA
| | - Janika Kõrv
- Department of Neurology and Neurosurgery, University of Tartu, Tartu, Estonia
| | - Paulo H C França
- Post-Graduation Program on Health and Environment, Department of Medicine and Joinville Stroke Biobank, University of the Region of Joinville, Santa Catarina, Brazil
| | - Ramin Zand
- Geisinger Neuroscience Institute, Geisinger Health System, Danville, PA, USA
- Department of Neurology, College of Medicine, The Pennsylvania State University, State College, PA, USA
| | | | - Ruth Frikke-Schmidt
- Department of Clinical Biochemistry, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Frank-Erik de Leeuw
- Department of Neurology, Donders Center for Medical Neuroscience, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Thomas Liman
- Center for Stroke Research Berlin, Berlin, Germany
- Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Klinik für Neurologie, Carl von Ossietzky University of Oldenburg, Oldenburg, Germany
| | | | - Ynte M Ruigrok
- UMC Utrecht Brain Center, Department of Neurology and Neurosurgery, University Medical Center Utrecht, University Utrecht, Utrecht, The Netherlands
| | - Peter Ulrich Heuschmann
- Institute of Clinical Epidemiology and Biometry, University of Würzburg, Würzburg, Germany
- Comprehensive Heart Failure Center, University Hospital Würzburg, Würzburg, Germany
- Clinical Trial Center, University Hospital Würzburg, Würzburg, Germany
| | - W T Longstreth
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Department of Neurology, University of Washington, Seattle, WA, USA
| | - Keum Ji Jung
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Institute for Health Promotion, Graduate School of Public Health, Yonsei University, Seoul, Republic of Korea
| | - Lisa Bastarache
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Guillaume Paré
- Thrombosis and Atherosclerosis Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, Ontario, Canada
- Department of Pathology and Molecular Medicine, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, Ontario, Canada
| | - Scott M Damrauer
- Department of Surgery and Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, USA
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Christopher D Anderson
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
- McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - John-Anker Zwart
- Department of Research and Innovation, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Teemu J Niiranen
- Department of Internal Medicine, University of Turku, Turku, Finland
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Turku, Finland
- Division of Medicine, Turku University Hospital, Turku, Finland
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Yung-Po Liaw
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, Taichung, Taiwan
- Department of Medical Imaging, Chung Shan Medical University Hospital, Taichung, Taiwan
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
- Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Israel Fernández-Cadenas
- Stroke Pharmacogenomics and Genetics Laboratory, Biomedical Research Institute Sant Pau (IIB Sant Pau), Barcelona, Spain
| | - Robin G Walters
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, University of Oxford, Oxford, UK
| | - Christian T Ruff
- TIMI Study Group, Boston, MA, USA
- Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Mayowa O Owolabi
- Center for Genomic and Precision Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
- Department of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Jennifer E Huffman
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Lili Milani
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Yoichiro Kamatani
- Laboratory of Complex Trait Genomics, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Martin Dichgans
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany.
- Munich Cluster for Systems Neurology, Munich, Germany.
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.
| | - Stephanie Debette
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France.
- Department of Neurology, Institute for Neurodegenerative Diseases, CHU de Bordeaux, Bordeaux, France.
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153
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Huang X, Li L, Zhou S, Kong D, Luo J, Lu L, Xu HM, Wang X. Multi-omics analysis reveals expression complexity and functional diversity of mouse kinome. Proteomics 2022; 22:e2200120. [PMID: 35856475 DOI: 10.1002/pmic.202200120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 07/01/2022] [Accepted: 07/15/2022] [Indexed: 12/29/2022]
Abstract
Protein kinases are a crucial component of signaling pathways involved in a wide range of cellular responses, including growth, proliferation, differentiation, and migration. Systematic investigation of protein kinases is critical to better understand phosphorylation-mediated signaling pathways and may provide insights into the development of potential therapeutic drug targets. Here we perform a systems-level analysis of the mouse kinome by analyzing multi-omics data. We used bulk and single-cell transcriptomic data from the C57BL/6J mouse strain to define tissue- and cell-type-specific expression of protein kinases, followed by investigating variations in sequence and expression between C57BL/6J and DBA/2J strains. We then profiled a deep brain phosphoproteome from C57BL/6J and DBA/2J strains as well as their reciprocal hybrids to infer the activity of the mouse kinome. Finally, we performed phenome-wide association analysis using the BXD recombinant inbred (RI) mice (a cross between C57BL/6J and DBA/2J strains) to identify any associations between variants in protein kinases and phenotypes. Collectively, our study provides a comprehensive analysis of the mouse kinome by investigating genetic sequence variation, tissue-specific expression patterns, and associations with downstream phenotypes.
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Affiliation(s)
- Xin Huang
- Institute of Crop Science and Institute of Bioinformatics, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China
| | - Ling Li
- Department of Biology, University of North Dakota, Grand Forks, North Dakota, USA
| | - Suiping Zhou
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Dehui Kong
- Department of Biology, University of North Dakota, Grand Forks, North Dakota, USA
| | - Jie Luo
- Central Laboratory of Zhejiang Academy of Agricultural Sciences, Zhejiang Academy of Agricultural Sciences, Hangzhou, China
| | - Lu Lu
- Department of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Hai-Ming Xu
- Institute of Crop Science and Institute of Bioinformatics, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China
| | - Xusheng Wang
- Department of Biology, University of North Dakota, Grand Forks, North Dakota, USA
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154
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Namjou B, Lape M, Malolepsza E, DeVore SB, Weirauch MT, Dikilitas O, Jarvik GP, Kiryluk K, Kullo IJ, Liu C, Luo Y, Satterfield BA, Smoller JW, Walunas TL, Connolly J, Sleiman P, Mersha TB, Mentch FD, Hakonarson H, Prows CA, Biagini JM, Khurana Hershey GK, Martin LJ, Kottyan L, The eMERGE Network. Multiancestral polygenic risk score for pediatric asthma. J Allergy Clin Immunol 2022; 150:1086-1096. [PMID: 35595084 PMCID: PMC9643615 DOI: 10.1016/j.jaci.2022.03.035] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 03/07/2022] [Accepted: 03/29/2022] [Indexed: 10/18/2022]
Abstract
BACKGROUND Asthma is the most common chronic condition in children and the third leading cause of hospitalization in pediatrics. The genome-wide association study catalog reports 140 studies with genome-wide significance. A polygenic risk score (PRS) with predictive value across ancestries has not been evaluated for this important trait. OBJECTIVES This study aimed to train and validate a PRS relying on genetic determinants for asthma to provide predictions for disease occurrence in pediatric cohorts of diverse ancestries. METHODS This study applied a Bayesian regression framework method using the Trans-National Asthma Genetic Consortium genome-wide association study summary statistics to derive a multiancestral PRS score, used one Electronic Medical Records and Genomics (eMERGE) cohort as a training set, used a second independent eMERGE cohort to validate the score, and used the UK Biobank data to replicate the findings. A phenome-wide association study was performed using the PRS to identify shared genetic etiology with other phenotypes. RESULTS The multiancestral asthma PRS was associated with asthma in the 2 pediatric validation datasets. Overall, the multiancestral asthma PRS has an area under the curve (AUC) of 0.70 (95% CI, 0.69-0.72) in the pediatric validation 1 and AUC of 0.66 (0.65-0.66) in the pediatric validation 2 datasets. We found significant discrimination across pediatric subcohorts of European (AUC, 95% CI, 0.60 and 0.66), African (AUC, 95% CI, 0.61 and 0.66), admixed American (AUC, 0.64 and 0.70), Southeast Asian (AUC, 0.65), and East Asian (AUC, 0.73) ancestry. Pediatric participants with the top 5% PRS had 2.80 to 5.82 increased odds of asthma compared to the bottom 5% across the training, validation 1, and validation 2 cohorts when adjusted for ancestry. Phenome-wide association study analysis confirmed the strong association of the identified PRS with asthma (odds ratio, 2.71, PFDR = 3.71 × 10-65) and related phenotypes. CONCLUSIONS A multiancestral PRS for asthma based on Bayesian posterior genomic effect sizes identifies increased odds of pediatric asthma.
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Affiliation(s)
- Bahram Namjou
- Center for Autoimmune Genomics and Etiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio 45229
- Department of Pediatrics, University of Cincinnati, College of Medicine, Cincinnati, Ohio 45229
| | - Michael Lape
- Center for Autoimmune Genomics and Etiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio 45229
- Department of Pediatrics, University of Cincinnati, College of Medicine, Cincinnati, Ohio 45229
- Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio 45229
| | - Edyta Malolepsza
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts 02142
| | - Stanley B. DeVore
- Department of Pediatrics, University of Cincinnati, College of Medicine, Cincinnati, Ohio 45229
- Division of Asthma Research, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio 45229
| | - Matthew T. Weirauch
- Center for Autoimmune Genomics and Etiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio 45229
- Department of Pediatrics, University of Cincinnati, College of Medicine, Cincinnati, Ohio 45229
- Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio 45229
- Division of Developmental Biology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio 45229
| | - Ozan Dikilitas
- Department of Internal Medicine, Mayo Clinic, Rochester, Minnesota 55905
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota 55905
| | - Gail P. Jarvik
- Departments of Medicine (Division of Medical Genetics) and Genome Sciences, University of Washington Medical Center, Seattle, Washington 98195
| | - Krzysztof Kiryluk
- Department of Medicine, Division of Nephrology, College of Physicians and Surgeons, Columbia University, New York, New York 10032
| | - Iftikhar J. Kullo
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota 55905
| | - Cong Liu
- Department of Biomedical Informatics, Columbia University, New York, New York 10032
| | - Yuan Luo
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois 60611
| | | | - Jordan W. Smoller
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts 02115
| | - Theresa L. Walunas
- Division of General Internal Medicine and Geriatrics, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois 60611
| | - John Connolly
- Center for Applied Genomics, Children’s Hospital of Philadelphia, Department of Pediatrics, Philadelphia, Pennsylvania 19104
| | - Patrick Sleiman
- Center for Applied Genomics, Children’s Hospital of Philadelphia, Department of Pediatrics, Philadelphia, Pennsylvania 19104
- Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Tesfaye B. Mersha
- Department of Pediatrics, University of Cincinnati, College of Medicine, Cincinnati, Ohio 45229
- Division of Asthma Research, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio 45229
| | - Frank D Mentch
- Center for Applied Genomics, Children’s Hospital of Philadelphia, Department of Pediatrics, Philadelphia, Pennsylvania 19104
| | - Hakon Hakonarson
- Center for Applied Genomics, Children’s Hospital of Philadelphia, Department of Pediatrics, Philadelphia, Pennsylvania 19104
- Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Cynthia A. Prows
- Department of Pediatrics, University of Cincinnati, College of Medicine, Cincinnati, Ohio 45229
- Division of Human Genetics, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio 45229
- Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio 45229
| | - Jocelyn M. Biagini
- Department of Pediatrics, University of Cincinnati, College of Medicine, Cincinnati, Ohio 45229
- Division of Asthma Research, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio 45229
| | - Gurjit K. Khurana Hershey
- Department of Pediatrics, University of Cincinnati, College of Medicine, Cincinnati, Ohio 45229
- Division of Asthma Research, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio 45229
- Division of Allergy & Immunology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio 45229
| | - Lisa J. Martin
- Department of Pediatrics, University of Cincinnati, College of Medicine, Cincinnati, Ohio 45229
- Division of Human Genetics, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio 45229
| | - Leah Kottyan
- Center for Autoimmune Genomics and Etiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio 45229
- Department of Pediatrics, University of Cincinnati, College of Medicine, Cincinnati, Ohio 45229
- Division of Allergy & Immunology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio 45229
| | - The eMERGE Network
- National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland 20892
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155
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Fromme M, Schneider CV, Schlapbach C, Cazzaniga S, Trautwein C, Rader DJ, Borradori L, Strnad P. Comorbidities in lichen planus by phenome-wide association study in two biobank population cohorts. Br J Dermatol 2022; 187:722-729. [PMID: 35819183 DOI: 10.1111/bjd.21762] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Revised: 06/05/2022] [Accepted: 07/09/2022] [Indexed: 12/30/2022]
Abstract
BACKGROUND Lichen planus (LP) is a relatively frequent mucocutaneous inflammatory disease affecting the skin, skin appendages and mucosae, including oral mucosae, and less frequently the anogenital area, conjunctivae, oesophagus or larynx. OBJECTIVES To estimate the association of LP, with emphasis on dermatological and gastrointestinal conditions, in two large independent population cohorts. MATERIALS AND METHODS We performed a phenome-wide association study (PheWAS) and examined conditions associated with LP in two unrelated cohorts, i.e. the multicentre, community-based UK Biobank (UKB: 501 381 controls; 1130 LP subjects) and the healthcare-associated Penn Medicine BioBank (PMBB; 42 702 controls; 764 LP subjects). The data were analysed in 2021. The 'PheWAS' R package was used to perform the PheWAS analyses and Bonferroni correction was used to adjust for multiple testing. Odds ratios (ORs) were adjusted for age, sex and body mass index. RESULTS In the UKB, PheWAS revealed 133 phenome codes (PheCodes) significantly associated with LP and most of them were confirmed in PMBB. Dermatological and digestive PheCodes were the most abundant: 29 and 34 of these disorders, respectively, were significantly overrepresented in LP individuals from both cohorts. The 29 dermatological and 12 oral disorders were often highly enriched, whereas hepatic, gastric, oesophageal and intestinal PheCodes displayed ORs in the range of 1·6-4·5. Several autoimmune disorders also exhibited OR > 5 in both cohorts. CONCLUSIONS PheWAS in two large unrelated cohorts identified previously unknown comorbidities and may support clinical counselling of patients with LP. What is already known about this topic? Lichen planus (LP) is known to affect the skin, skin appendages and mucosae, including oral mucosae, and less frequently the anogenital area, conjunctivae, oesophagus or larynx. What does this study add? Our data provide the most comprehensive collection of associated dermatological, digestive and autoimmune disorders to date. Our findings are expected to be useful for the evaluation and management of patients with LP.
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Affiliation(s)
- Malin Fromme
- Medical Clinic III, Gastroenterology, Metabolic Diseases and Intensive Care, University Hospital RWTH Aachen, Aachen, Germany
| | - Carolin V Schneider
- Medical Clinic III, Gastroenterology, Metabolic Diseases and Intensive Care, University Hospital RWTH Aachen, Aachen, Germany.,The Institute for Translational Medicine and Therapeutics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Christoph Schlapbach
- Department of Dermatology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Simone Cazzaniga
- Department of Dermatology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.,Centro Studi GISED, Bergamo, Italy
| | - Christian Trautwein
- Medical Clinic III, Gastroenterology, Metabolic Diseases and Intensive Care, University Hospital RWTH Aachen, Aachen, Germany
| | - Dan J Rader
- The Institute for Translational Medicine and Therapeutics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Luca Borradori
- Department of Dermatology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Pavel Strnad
- Medical Clinic III, Gastroenterology, Metabolic Diseases and Intensive Care, University Hospital RWTH Aachen, Aachen, Germany
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156
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Privé F, Arbel J, Aschard H, Vilhjálmsson BJ. Identifying and correcting for misspecifications in GWAS summary statistics and polygenic scores. HGG ADVANCES 2022; 3:100136. [PMID: 36105883 PMCID: PMC9465343 DOI: 10.1016/j.xhgg.2022.100136] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 08/11/2022] [Indexed: 11/18/2022] Open
Abstract
Publicly available genome-wide association studies (GWAS) summary statistics exhibit uneven quality, which can impact the validity of follow-up analyses. First, we present an overview of possible misspecifications that come with GWAS summary statistics. Then, in both simulations and real-data analyses, we show that additional information such as imputation INFO scores, allele frequencies, and per-variant sample sizes in GWAS summary statistics can be used to detect possible issues and correct for misspecifications in the GWAS summary statistics. One important motivation for us is to improve the predictive performance of polygenic scores built from these summary statistics. Unfortunately, owing to the lack of reporting standards for GWAS summary statistics, this additional information is not systematically reported. We also show that using well-matched linkage disequilibrium (LD) references can improve model fit and translate into more accurate prediction. Finally, we discuss how to make polygenic score methods such as lassosum and LDpred2 more robust to these misspecifications to improve their predictive power.
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Affiliation(s)
- Florian Privé
- National Centre for Register-Based Research, Aarhus University, 8210 Aarhus, Denmark
| | - Julyan Arbel
- Université Grenoble Alpes, Inria, CNRS, Grenoble INP, LJK, 38000 Grenoble, France
| | - Hugues Aschard
- Department of Computational Biology, Institut Pasteur, Université Paris Cité, 75015 Paris, France
- Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Bjarni J. Vilhjálmsson
- National Centre for Register-Based Research, Aarhus University, 8210 Aarhus, Denmark
- Bioinformatics Research Centre, Aarhus University, 8000 Aarhus, Denmark
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157
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Bezamat M, Rothenberger S, Vieira AR. Genetic contribution to cancer risk in patients with tooth loss: a genetic association study. Sci Rep 2022; 12:16098. [PMID: 36167768 PMCID: PMC9515225 DOI: 10.1038/s41598-022-20556-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Accepted: 09/14/2022] [Indexed: 11/09/2022] Open
Abstract
Early-stage cancer diagnosis is critical for higher survival rates. Because early cancers can be difficult to detect, our focus is on the identification of cancer risk markers such as pleiotropic genes involved in the etiology of both craniofacial conditions and cancers. In this study we aimed to test if our previously detected association between ERN1 rs196929 marker and oral health outcomes would be detected in individuals diagnosed with cancer as well as in a subpopulation of individuals who also had one or more teeth missing due to dental caries, periodontal disease, or periapical lesions. We genotyped a total of 1,671 subjects and selected a subset of 1,421 subjects for stratified analysis of cancer types; three hundred and twelve self-reported a diagnosis of various cancer types and 1,109 reported never receiving a diagnosis of cancer. Our results showed a statistically significant association between the rs196929 in ERN1, and cancer overall in both the additive and dominant models (OR = 1.37, 95% C.I. 1.06-1.79, p = 0.014). When we stratified the analysis for each cancer type, our results show that the rs196929 ERN1 variant is associated with skin cancer (OR = 2.07, 95% C.I. 1.27-3.37, p = 0.003) and breast cancer (OR = 1.83, 95% C.I. 1.13-2.99, p = 0.013) in the subset of patients that had tooth loss. An additional nominal association between the rs196929 in ERN1 and male's reproductive system cancers (OR = 1.96, 95% C.I. 1.07-3.59, p = 0.028) was identified. We hope that our study helps guide future genetic studies on these cancers and this specific genetic variant as well as drive attention to the potential for oral health outcomes to serve as indicators for cancer risk. The early identification of genetic markers and/or oral conditions that indicate increased cancer risk could positively impact cancer outcomes and survival rates with timely implementation of preventive and diagnostic measures. In conclusion, our results suggest that the genetic variant in ERN1 (rs196929) is associated with increased risk of skin and breast cancers.
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Affiliation(s)
- Mariana Bezamat
- Department of Oral and Craniofacial Sciences, School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
| | - Scott Rothenberger
- Division of General Internal Medicine, Center for Research on Health Care Data Center, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Alexandre R Vieira
- Department of Oral and Craniofacial Sciences, School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA, USA
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158
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Jiang L, Kerchberger VE, Shaffer C, Dickson AL, Ormseth MJ, Daniel LL, Leon BGC, Cox NJ, Chung CP, Wei WQ, Stein CM, Feng Q. Genome-wide association analyses of common infections in a large practice-based biobank. BMC Genomics 2022; 23:672. [PMID: 36167494 PMCID: PMC9512962 DOI: 10.1186/s12864-022-08888-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 08/26/2022] [Indexed: 12/15/2022] Open
Abstract
INTRODUCTION Infectious diseases are common causes of morbidity and mortality worldwide. Susceptibility to infection is highly heritable; however, little has been done to identify the genetic determinants underlying common infectious diseases. One GWAS was performed using 23andMe information about self-reported infections; we set out to confirm previous loci and identify new ones using medically diagnosed infections. METHODS We used the electronic health record (EHR)-based biobank at Vanderbilt and diagnosis codes to identify cases of 12 infectious diseases in white patients: urinary tract infection, pneumonia, chronic sinus infections, otitis media, candidiasis, streptococcal pharyngitis, herpes zoster, herpes labialis, hepatitis B, infectious mononucleosis, tuberculosis (TB) or a positive TB test, and hepatitis C. We selected controls from patients with no diagnosis code for the candidate disease and matched by year of birth, sex, and calendar year at first and last EHR visits. We conducted GWAS using SAIGE and transcriptome-wide analysis (TWAS) using S-PrediXcan. We also conducted phenome-wide association study to understand associations between identified genetic variants and clinical phenotypes. RESULTS We replicated three 23andMe loci (p ≤ 0.05): herpes zoster and rs7047299-A (p = 2.6 × 10-3) and rs2808290-C (p = 9.6 × 10-3;); otitis media and rs114947103-C (p = 0.04). We also identified 2 novel regions (p ≤ 5 × 10-8): rs113235453-G for otitis media (p = 3.04 × 10-8), and rs10422015-T for candidiasis (p = 3.11 × 10-8). In TWAS, four gene-disease associations were significant: SLC30A9 for otitis media (p = 8.06 × 10-7); LRP3 and WDR88 for candidiasis (p = 3.91 × 10-7 and p = 1.95 × 10-6); and AAMDC for hepatitis B (p = 1.51 × 10-6). CONCLUSION We conducted GWAS and TWAS for 12 infectious diseases and identified novel genetic contributors to the susceptibility of infectious diseases.
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Affiliation(s)
- Lan Jiang
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - V Eric Kerchberger
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Christian Shaffer
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Alyson L Dickson
- Division of Rheumatology and Immunology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Michelle J Ormseth
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.,Division of Rheumatology and Immunology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.,Division of Research and Development, Tennessee Valley Healthcare System, U.S. Department of Veterans Affairs, Nashville, TN, USA
| | - Laura L Daniel
- Division of Rheumatology and Immunology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Barbara G Carranza Leon
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Nancy J Cox
- Department of Medicine, Vanderbilt Genetic Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Cecilia P Chung
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.,Division of Rheumatology and Immunology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.,Department of Medicine, Vanderbilt Genetic Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Wei-Qi Wei
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - C Michael Stein
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.,Department of Pharmacology, Vanderbilt University, Nashville, TN, USA
| | - QiPing Feng
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA. .,Department of Medicine, Vanderbilt Genetic Institute, Vanderbilt University Medical Center, Nashville, TN, USA.
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159
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Johnson R, Ding Y, Venkateswaran V, Bhattacharya A, Boulier K, Chiu A, Knyazev S, Schwarz T, Freund M, Zhan L, Burch KS, Caggiano C, Hill B, Rakocz N, Balliu B, Denny CT, Sul JH, Zaitlen N, Arboleda VA, Halperin E, Sankararaman S, Butte MJ, Lajonchere C, Geschwind DH, Pasaniuc B. Leveraging genomic diversity for discovery in an electronic health record linked biobank: the UCLA ATLAS Community Health Initiative. Genome Med 2022; 14:104. [PMID: 36085083 PMCID: PMC9461263 DOI: 10.1186/s13073-022-01106-x] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 08/03/2022] [Indexed: 01/13/2023] Open
Abstract
BACKGROUND Large medical centers in urban areas, like Los Angeles, care for a diverse patient population and offer the potential to study the interplay between genetic ancestry and social determinants of health. Here, we explore the implications of genetic ancestry within the University of California, Los Angeles (UCLA) ATLAS Community Health Initiative-an ancestrally diverse biobank of genomic data linked with de-identified electronic health records (EHRs) of UCLA Health patients (N=36,736). METHODS We quantify the extensive continental and subcontinental genetic diversity within the ATLAS data through principal component analysis, identity-by-descent, and genetic admixture. We assess the relationship between genetically inferred ancestry (GIA) and >1500 EHR-derived phenotypes (phecodes). Finally, we demonstrate the utility of genetic data linked with EHR to perform ancestry-specific and multi-ancestry genome and phenome-wide scans across a broad set of disease phenotypes. RESULTS We identify 5 continental-scale GIA clusters including European American (EA), African American (AA), Hispanic Latino American (HL), South Asian American (SAA) and East Asian American (EAA) individuals and 7 subcontinental GIA clusters within the EAA GIA corresponding to Chinese American, Vietnamese American, and Japanese American individuals. Although we broadly find that self-identified race/ethnicity (SIRE) is highly correlated with GIA, we still observe marked differences between the two, emphasizing that the populations defined by these two criteria are not analogous. We find a total of 259 significant associations between continental GIA and phecodes even after accounting for individuals' SIRE, demonstrating that for some phenotypes, GIA provides information not already captured by SIRE. GWAS identifies significant associations for liver disease in the 22q13.31 locus across the HL and EAA GIA groups (HL p-value=2.32×10-16, EAA p-value=6.73×10-11). A subsequent PheWAS at the top SNP reveals significant associations with neurologic and neoplastic phenotypes specifically within the HL GIA group. CONCLUSIONS Overall, our results explore the interplay between SIRE and GIA within a disease context and underscore the utility of studying the genomes of diverse individuals through biobank-scale genotyping linked with EHR-based phenotyping.
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Affiliation(s)
- Ruth Johnson
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
| | - Yi Ding
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Vidhya Venkateswaran
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Oral Biology, School of Dentistry, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Arjun Bhattacharya
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Institute for Quantitative and Computational Biosciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Kristin Boulier
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Medicine, Division of Cardiology, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Alec Chiu
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Sergey Knyazev
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Institute for Quantitative and Computational Biosciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Tommer Schwarz
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Malika Freund
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Genetics, Stanford School of Medicine, Stanford, CA, 94305, USA
| | - Lingyu Zhan
- Molecular Biology Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Kathryn S Burch
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Christa Caggiano
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Brian Hill
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Nadav Rakocz
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Brunilda Balliu
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Christopher T Denny
- Division of Hematology/Oncology, Department of Pediatrics, Gwynne Hazen Cherry Memorial Laboratories, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Jae Hoon Sul
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Noah Zaitlen
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Valerie A Arboleda
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Eran Halperin
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Sriram Sankararaman
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Manish J Butte
- Department of Pediatrics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Clara Lajonchere
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Institute of Precision Health, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Daniel H Geschwind
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Institute of Precision Health, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Bogdan Pasaniuc
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Institute of Precision Health, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
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160
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Wang Z, Emmerich A, Pillon NJ, Moore T, Hemerich D, Cornelis MC, Mazzaferro E, Broos S, Ahluwalia TS, Bartz TM, Bentley AR, Bielak LF, Chong M, Chu AY, Berry D, Dorajoo R, Dueker ND, Kasbohm E, Feenstra B, Feitosa MF, Gieger C, Graff M, Hall LM, Haller T, Hartwig FP, Hillis DA, Huikari V, Heard-Costa N, Holzapfel C, Jackson AU, Johansson Å, Jørgensen AM, Kaakinen MA, Karlsson R, Kerr KF, Kim B, Koolhaas CM, Kutalik Z, Lagou V, Lind PA, Lorentzon M, Lyytikäinen LP, Mangino M, Metzendorf C, Monroe KR, Pacolet A, Pérusse L, Pool R, Richmond RC, Rivera NV, Robiou-du-Pont S, Schraut KE, Schulz CA, Stringham HM, Tanaka T, Teumer A, Turman C, van der Most PJ, Vanmunster M, van Rooij FJA, van Vliet-Ostaptchouk JV, Zhang X, Zhao JH, Zhao W, Balkhiyarova Z, Balslev-Harder MN, Baumeister SE, Beilby J, Blangero J, Boomsma DI, Brage S, Braund PS, Brody JA, Bruinenberg M, Ekelund U, Liu CT, Cole JW, Collins FS, Cupples LA, Esko T, Enroth S, Faul JD, Fernandez-Rhodes L, Fohner AE, Franco OH, Galesloot TE, Gordon SD, Grarup N, Hartman CA, Heiss G, Hui J, Illig T, Jago R, James A, Joshi PK, Jung T, Kähönen M, Kilpeläinen TO, Koh WP, Kolcic I, et alWang Z, Emmerich A, Pillon NJ, Moore T, Hemerich D, Cornelis MC, Mazzaferro E, Broos S, Ahluwalia TS, Bartz TM, Bentley AR, Bielak LF, Chong M, Chu AY, Berry D, Dorajoo R, Dueker ND, Kasbohm E, Feenstra B, Feitosa MF, Gieger C, Graff M, Hall LM, Haller T, Hartwig FP, Hillis DA, Huikari V, Heard-Costa N, Holzapfel C, Jackson AU, Johansson Å, Jørgensen AM, Kaakinen MA, Karlsson R, Kerr KF, Kim B, Koolhaas CM, Kutalik Z, Lagou V, Lind PA, Lorentzon M, Lyytikäinen LP, Mangino M, Metzendorf C, Monroe KR, Pacolet A, Pérusse L, Pool R, Richmond RC, Rivera NV, Robiou-du-Pont S, Schraut KE, Schulz CA, Stringham HM, Tanaka T, Teumer A, Turman C, van der Most PJ, Vanmunster M, van Rooij FJA, van Vliet-Ostaptchouk JV, Zhang X, Zhao JH, Zhao W, Balkhiyarova Z, Balslev-Harder MN, Baumeister SE, Beilby J, Blangero J, Boomsma DI, Brage S, Braund PS, Brody JA, Bruinenberg M, Ekelund U, Liu CT, Cole JW, Collins FS, Cupples LA, Esko T, Enroth S, Faul JD, Fernandez-Rhodes L, Fohner AE, Franco OH, Galesloot TE, Gordon SD, Grarup N, Hartman CA, Heiss G, Hui J, Illig T, Jago R, James A, Joshi PK, Jung T, Kähönen M, Kilpeläinen TO, Koh WP, Kolcic I, Kraft PP, Kuusisto J, Launer LJ, Li A, Linneberg A, Luan J, Vidal PM, Medland SE, Milaneschi Y, Moscati A, Musk B, Nelson CP, Nolte IM, Pedersen NL, Peters A, Peyser PA, Power C, Raitakari OT, Reedik M, Reiner AP, Ridker PM, Rudan I, Ryan K, Sarzynski MA, Scott LJ, Scott RA, Sidney S, Siggeirsdottir K, Smith AV, Smith JA, Sonestedt E, Strøm M, Tai ES, Teo KK, Thorand B, Tönjes A, Tremblay A, Uitterlinden AG, Vangipurapu J, van Schoor N, Völker U, Willemsen G, Williams K, Wong Q, Xu H, Young KL, Yuan JM, Zillikens MC, Zonderman AB, Ameur A, Bandinelli S, Bis JC, Boehnke M, Bouchard C, Chasman DI, Smith GD, de Geus EJC, Deldicque L, Dörr M, Evans MK, Ferrucci L, Fornage M, Fox C, Garland T, Gudnason V, Gyllensten U, Hansen T, Hayward C, Horta BL, Hyppönen E, Jarvelin MR, Johnson WC, Kardia SLR, Kiemeney LA, Laakso M, Langenberg C, Lehtimäki T, Marchand LL, Magnusson PKE, Martin NG, Melbye M, Metspalu A, Meyre D, North KE, Ohlsson C, Oldehinkel AJ, Orho-Melander M, Pare G, Park T, Pedersen O, Penninx BWJH, Pers TH, Polasek O, Prokopenko I, Rotimi CN, Samani NJ, Sim X, Snieder H, Sørensen TIA, Spector TD, Timpson NJ, van Dam RM, van der Velde N, van Duijn CM, Vollenweider P, Völzke H, Voortman T, Waeber G, Wareham NJ, Weir DR, Wichmann HE, Wilson JF, Hevener AL, Krook A, Zierath JR, Thomis MAI, Loos RJF, Hoed MD. Genome-wide association analyses of physical activity and sedentary behavior provide insights into underlying mechanisms and roles in disease prevention. Nat Genet 2022; 54:1332-1344. [PMID: 36071172 PMCID: PMC9470530 DOI: 10.1038/s41588-022-01165-1] [Show More Authors] [Citation(s) in RCA: 111] [Impact Index Per Article: 37.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 07/18/2022] [Indexed: 02/02/2023]
Abstract
Although physical activity and sedentary behavior are moderately heritable, little is known about the mechanisms that influence these traits. Combining data for up to 703,901 individuals from 51 studies in a multi-ancestry meta-analysis of genome-wide association studies yields 99 loci that associate with self-reported moderate-to-vigorous intensity physical activity during leisure time (MVPA), leisure screen time (LST) and/or sedentary behavior at work. Loci associated with LST are enriched for genes whose expression in skeletal muscle is altered by resistance training. A missense variant in ACTN3 makes the alpha-actinin-3 filaments more flexible, resulting in lower maximal force in isolated type IIA muscle fibers, and possibly protection from exercise-induced muscle damage. Finally, Mendelian randomization analyses show that beneficial effects of lower LST and higher MVPA on several risk factors and diseases are mediated or confounded by body mass index (BMI). Our results provide insights into physical activity mechanisms and its role in disease prevention.
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Affiliation(s)
- Zhe Wang
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Andrew Emmerich
- Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
| | - Nicolas J Pillon
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Tim Moore
- Division of Cardiology, Department of Medicine, University of California, Los Angeles, CA, USA
| | - Daiane Hemerich
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Marilyn C Cornelis
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Eugenia Mazzaferro
- The Beijer Laboratory and Department of Immunology, Genetics and Pathology, Uppsala University and SciLifeLab, Uppsala, Sweden
| | - Siacia Broos
- Faculty of Movement and Rehabilitation Sciences, Department of Movement Sciences - Exercise Physiology Research Group, KU Leuven, Leuven, Belgium
- Faculty of Movement and Rehabilitation Sciences, Department of Movement Sciences - Physical Activity, Sports & Health Research Group, KU Leuven, Leuven, Belgium
| | - Tarunveer S Ahluwalia
- Steno Diabetes Center Copenhagen, Herlev, Denmark
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- The Bioinformatics Center, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Traci M Bartz
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Lawrence F Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Mike Chong
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Audrey Y Chu
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
- GlaxoSmithKline, Cambridge, MA, USA
| | - Diane Berry
- Division of Population, Policy and Practice, Great Ormond Street Hospital Institute for Child Health, University College London, London, UK
| | - Rajkumar Dorajoo
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
- Health Services and Systems Research, Duke-NUS Medical School, Singapore, Singapore
| | - Nicole D Dueker
- John P. Hussman Institute for Human Genomics, University of Miami, Miami, FL, USA
- Department of Epidemiology & Public Health, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Elisa Kasbohm
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- Institute of Mathematics and Computer Science, University of Greifswald, Greifswald, Germany
| | - Bjarke Feenstra
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Mary F Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München -Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Munich, Germany
| | - Mariaelisa Graff
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Leanne M Hall
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Toomas Haller
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Fernando P Hartwig
- Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil
- MRC Integrative Epidemiology Unit, NIHR Bristol Biomedical Research Center, University of Bristol, Bristol, UK
| | - David A Hillis
- Genetics, Genomics, and Bioinformatics Graduate Program, University of California, Riverside, CA, USA
| | - Ville Huikari
- Institute of Health Sciences, University of Oulu, Oulu, Finland
| | - Nancy Heard-Costa
- Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Christina Holzapfel
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München -Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Munich, Germany
- Institute for Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
| | - Anne U Jackson
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Åsa Johansson
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Anja Moltke Jørgensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Marika A Kaakinen
- Section of Statistical Multi-omics, Department of Clinical and Experimental Medicine, University of Surrey, Guildford, UK
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Robert Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Kathleen F Kerr
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Boram Kim
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, South Korea
| | - Chantal M Koolhaas
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Zoltan Kutalik
- University Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | | | - Penelope A Lind
- Mental Health and Neuroscience Research Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- School of Biomedical Science, Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia
| | - Mattias Lorentzon
- Geriatric Medicine, Institute of Medicine, University of Gothenburg and Sahlgrenska University Hospital Mölndal, Gothenburg, Sweden
- Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, Victoria, Australia
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Finnish Cardiovascular Research Center - Tampere, Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK
- NIHR Biomedical Research Centre at Guy's and St Thomas' Foundation Trust, London, UK
| | - Christoph Metzendorf
- The Beijer Laboratory and Department of Immunology, Genetics and Pathology, Uppsala University and SciLifeLab, Uppsala, Sweden
| | - Kristine R Monroe
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Alexander Pacolet
- Faculty of Movement and Rehabilitation Sciences, Department of Movement Sciences - Exercise Physiology Research Group, KU Leuven, Leuven, Belgium
| | - Louis Pérusse
- Department of Kinesiology, Université Laval, Quebec, Quebec, Canada
- Centre Nutrition Santé et Société (NUTRISS), Institute of Nutrition and Functional Foods (INAF), Université Laval, Quebec, Quebec, Canada
| | - Rene Pool
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam UMC, Amsterdam, the Netherlands
| | - Rebecca C Richmond
- MRC Integrative Epidemiology Unit and Avon Longitudinal Study of Parents and Children, University of Bristol Medical School, Population Health Sciences and Avon Longitudinal Study of Parents and Children, University of Bristol, Bristol, UK
| | - Natalia V Rivera
- Respiratory Division, Department of Medicine, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
- Rheumatology Division, Department of Medicine, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
- Center of Molecular Medicine (CMM), Karolinska Institutet, Stockholm, Sweden
| | - Sebastien Robiou-du-Pont
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
| | - Katharina E Schraut
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Christina-Alexandra Schulz
- Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
- Department of Nutrition and Food Sciences, Nutritional Epidemiology, University of Bonn, Bonn, Germany
| | - Heather M Stringham
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Toshiko Tanaka
- Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, USA
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- German Centre for Cardiovascular Research (DZHK), partner site Greifswald, Greifswald, Germany
| | - Constance Turman
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Peter J van der Most
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Mathias Vanmunster
- Faculty of Movement and Rehabilitation Sciences, Department of Movement Sciences - Exercise Physiology Research Group, KU Leuven, Leuven, Belgium
| | - Frank J A van Rooij
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Jana V van Vliet-Ostaptchouk
- Department of Endocrinology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Xiaoshuai Zhang
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
- School of Public Health, Department of Biostatistics, Shandong University, Jinan, China
| | - Jing-Hua Zhao
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Zhanna Balkhiyarova
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- Department of Clinical and Experimental Medicine, University of Surrey, Guilford, UK
- People-Centred Artificial Intelligence Institute, University of Surrey, Guilford, UK
| | - Marie N Balslev-Harder
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Sebastian E Baumeister
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- University of Münster, Münster, Germany
| | - John Beilby
- Diagnostic Genomics, PathWest Laboratory Medicine WA, Perth, Western Australia, Australia
| | - John Blangero
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam UMC, Amsterdam, the Netherlands
| | - Soren Brage
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Peter S Braund
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | | | - Ulf Ekelund
- Department of Sports Medicine, Norwegian School of Sport Sciences, Oslo, Norway
- Department of Chronic Diseases, Norwegian Institute of Public Health, Oslo, Norway
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - John W Cole
- Vascular Neurology, Department of Neurology, University of Maryland School of Medicine and the Baltimore VAMC, Baltimore, MD, USA
| | - Francis S Collins
- Center for Precision Health Research, National Human Genome Research Institute, NIH, Bethesda, MD, USA
| | - L Adrienne Cupples
- Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Tõnu Esko
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Stefan Enroth
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Jessica D Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Lindsay Fernandez-Rhodes
- Department of Biobehavioral Health, College of Health and Human Development, Pennsylvania State University, University Park, PA, USA
| | - Alison E Fohner
- Department of Epidemiology, Institute of Public Health Genetics, Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA
| | - Oscar H Franco
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland
| | - Tessel E Galesloot
- Radboud Institute for Health Sciences, Department for Health Evidence, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Scott D Gordon
- Mental Health and Neuroscience Research Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Catharina A Hartman
- Interdisciplinary Center Psychopathology and Emotion Regulation, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Gerardo Heiss
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Jennie Hui
- Diagnostic Genomics, PathWest Laboratory Medicine WA, Perth, Western Australia, Australia
- School of Population and Global Health, The University of Western Australia, Perth, Western Australia, Australia
- Busselton Population Medical Research Institute, Busselton, Western Australia, Australia
| | - Thomas Illig
- Hannover Unified Biobank, Hannover Medical School, Hannover, Germany
- Department of Human Genetics, Hannover Medical School, Hannover, Germany
| | - Russell Jago
- Centre for Exercise Nutrition & Health Sciences, School for Policy Studies, University of Bristol, Bristol, UK
| | - Alan James
- Department of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital, Western Australia, Perth, Australia
| | - Peter K Joshi
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
- Humanity Inc, Boston, MA, USA
| | - Taeyeong Jung
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, South Korea
| | - Mika Kähönen
- Finnish Cardiovascular Research Center - Tampere, Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland
| | - Tuomas O Kilpeläinen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Woon-Puay Koh
- Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Singapore Institute for Clinical Sciences, Agency for Science, Technology, and Research, Singapore, Singapore
| | - Ivana Kolcic
- Department of Public Health, University of Split School of Medicine, Split, Croatia
| | - Peter P Kraft
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Johanna Kuusisto
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, National Institutes of Health, Baltimore, MD, USA
| | - Aihua Li
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
| | - Allan Linneberg
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jian'an Luan
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Pedro Marques Vidal
- Division of Internal Medicine, Department of Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Sarah E Medland
- Mental Health and Neuroscience Research Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- School of Psychology and Faculty of Medicine, University of Queensland, St Lucia, Queensland, Australia
| | - Yuri Milaneschi
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit, Amsterdam, the Netherlands
| | - Arden Moscati
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bill Musk
- Busselton Population Medical Research Institute, Busselton, Western Australia, Australia
| | - Christopher P Nelson
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Ilja M Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München -Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Munich, Germany
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Christine Power
- Division of Population, Policy and Practice, Great Ormond Street Hospital Institute for Child Health, University College London, London, UK
| | - Olli T Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Mägi Reedik
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Alex P Reiner
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Igor Rudan
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Kathy Ryan
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Mark A Sarzynski
- Department of Exercise Science, University of South Carolina, Columbia, SC, USA
| | - Laura J Scott
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Robert A Scott
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Stephen Sidney
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | | | - Albert V Smith
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
- Icelandic Heart Association, Kópavogur, Iceland
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Emily Sonestedt
- Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
| | - Marin Strøm
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
- Faculty of Health Sciences, University of the Faroe Islands, Tórshavn, Faroe Islands
| | - E Shyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Koon K Teo
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum München -Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Munich, Germany
| | - Anke Tönjes
- Department of Medicine, University of Leipzig, Leipzig, Germany
| | - Angelo Tremblay
- Department of Kinesiology, Université Laval, Quebec, Quebec, Canada
- Centre Nutrition Santé et Société (NUTRISS), Institute of Nutrition and Functional Foods (INAF), Université Laval, Quebec, Quebec, Canada
| | - Andre G Uitterlinden
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Jagadish Vangipurapu
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Natasja van Schoor
- Department of Epidemiology and Biostatistics, Amsterdam Public Health Research Institute, VU University Medical Center, Amsterdam, the Netherlands
| | - Uwe Völker
- German Centre for Cardiovascular Research (DZHK), partner site Greifswald, Greifswald, Germany
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam UMC, Amsterdam, the Netherlands
| | - Kayleen Williams
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Quenna Wong
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Huichun Xu
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Kristin L Young
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Jian Min Yuan
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - M Carola Zillikens
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Alan B Zonderman
- Laboratory of Epidemiology and Population Science, National Instiute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Adam Ameur
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | | | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Claude Bouchard
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, USA
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, NIHR Bristol Biomedical Research Center, University of Bristol, Bristol, UK
- Population Health Science, Bristol Medical School, NIHR Bristol Biomedical Research Center, University of Bristol, Bristol, UK
| | - Eco J C de Geus
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam UMC, Amsterdam, the Netherlands
| | - Louise Deldicque
- Faculty of Movement and Rehabilitation Sciences, Institute of Neuroscience, UC Louvain, Louvain-la-Neuve, Belgium
| | - Marcus Dörr
- German Centre for Cardiovascular Research (DZHK), partner site Greifswald, Greifswald, Germany
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | - Michele K Evans
- Laboratory of Epidemiology and Population Science, National Instiute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Luigi Ferrucci
- Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, USA
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Caroline Fox
- Genetics and Pharmacogenomics (GpGx), Merck Research Labs, Boston, MA, USA
| | - Theodore Garland
- Department of Evolution, Ecology, and Organismal Biology, University of California, Riverside, Riverside, CA, USA
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kópavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Ulf Gyllensten
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Bernardo L Horta
- Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil
| | - Elina Hyppönen
- Australian Centre for Precision Health, Unit of Clinical and Health Sciences, University of South Australia, Adelaide, South Australia, Australia
- South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia
- Population, Policy and Practice, Great Ormond Street Hospital Institute for Child Health, University College London, London, UK
| | - Marjo-Riitta Jarvelin
- Institute of Health Sciences, University of Oulu, Oulu, Finland
- Department of Epidemiology and Biostatistics and HPA-MRC Center, School of Public Health, Imperial College London, London, UK
| | - W Craig Johnson
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Lambertus A Kiemeney
- Radboud Institute for Health Sciences, Department for Health Evidence, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
- Computational Medicine, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Finnish Cardiovascular Research Center - Tampere, Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Loic Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Nicholas G Martin
- Mental Health and Neuroscience Research Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Mads Melbye
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- K.G.Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Center for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Andres Metspalu
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - David Meyre
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
| | - Kari E North
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Claes Ohlsson
- Centre for Bone and Arthritis Research, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Drug Treatment, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Albertine J Oldehinkel
- Interdisciplinary Center Psychopathology and Emotion Regulation, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | | | - Guillaume Pare
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Taesung Park
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, South Korea
- Department of Statistics, Seoul National University, Seoul, South Korea
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Brenda W J H Penninx
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit, Amsterdam, the Netherlands
| | - Tune H Pers
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ozren Polasek
- University of Split School of Medicine, Split, Croatia
| | - Inga Prokopenko
- Department of Clinical and Experimental Medicine, University of Surrey, Guilford, UK
- People-Centred Artificial Intelligence Institute, University of Surrey, Guilford, UK
- UMR 8199 - EGID, Institut Pasteur de Lille, CNRS, University of Lille, Lille, France
| | - Charles N Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, 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
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit, University of Bristol Medical School, University of Bristol, Bristol, UK
| | - Rob M van Dam
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
- Department of Exercise and Nutrition Sciences, Milken Institute School of Public Health, George Washington University, Washington, DC, USA
| | - Nathalie van der Velde
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands
- Section of Geriatrics, Department of Internal Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
- Amsterdam Public Health, Aging and Later Life, Amsterdam, the Netherlands
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Peter Vollenweider
- Division of Internal Medicine, Department of Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- German Centre for Cardiovascular Research (DZHK), partner site Greifswald, Greifswald, Germany
| | - Trudy Voortman
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Gérard Waeber
- Division of Internal Medicine, Department of Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | | | - David R Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Heinz-Erich Wichmann
- Institute of Epidemiology, Helmholtz Zentrum München -Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Munich, Germany
| | - James F Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Andrea L Hevener
- Division of Endocrinology, Department of Medicine, University of California, Los Angeles, CA, USA
| | - Anna Krook
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Juleen R Zierath
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Martine A I Thomis
- Faculty of Movement and Rehabilitation Sciences, Department of Movement Sciences - Physical Activity, Sports & Health Research Group, KU Leuven, Leuven, Belgium
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, 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
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Marcel den Hoed
- The Beijer Laboratory and Department of Immunology, Genetics and Pathology, Uppsala University and SciLifeLab, Uppsala, Sweden.
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Kleinjans M, Schneider CV, Bruns T, Strnad P. Phenome of coeliac disease vs. inflammatory bowel disease. Sci Rep 2022; 12:14572. [PMID: 36028550 PMCID: PMC9418215 DOI: 10.1038/s41598-022-18593-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 08/16/2022] [Indexed: 11/09/2022] Open
Abstract
Coeliac disease (CeD) is characterized by gliadin-induced intestinal inflammation appearing in genetically susceptible individuals, such as HLA-DQ2.5 carriers. CeD, as well as other chronic intestinal disorders, such as Crohn's disease (CD) and ulcerative colitis, has been associated with increased morbidity and mortality, but the causes are unknown. We systematically analysed CeD-associated diagnoses and compared them to conditions enriched in subjects with CD/UC as well as in HLA-DQ2.5 carriers without CeD. We compared the overall and cause-specific mortality and morbidity of 3,001 patients with CeD, 2,020 with CD, 4,399 with UC and 492,200 controls in the community-based UK Biobank. Disease-specific phenotypes were assessed with the multivariable Phenome Wide Association Study (PheWAS) method. Associations were adjusted for age, sex and body mass index. All disease groups displayed higher overall mortality than controls (CD: aHR = 1.91[1.70-2.17]; UC: aHR = 1.32 [1.20-1.46]; CeD: aHR = 1.38 [1.22-1.55]). Cardiovascular and cancer-related deaths were responsible for the majority of fatalities. PheWAS analysis revealed 166 Phecodes overrepresented in all three disorders, whereas only ~ 20% of enriched Phecodes were disease specific. Seven of the 58 identified CeD-specific Phecodes were enriched in individuals homozygous for HLA-DQ2.5 without diagnosed CeD. Four out of these seven Phecodes and eight out of 19 HLA-DQ2.5 specific Phecodes were more common in homozygous HLA-DQ2.5 subjects with vs. without CeD, highlighting the interplay between genetics and diagnosis-related factors. Our study illustrates that the morbidity and mortality in CeD share similarities with CD/UC, while the CeD-restricted conditions might be driven by both inherited and acquired factors.
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Affiliation(s)
- Moritz Kleinjans
- Medical Clinic III, Gastroenterology, Metabolic Diseases and Intensive Care, University Hospital RWTH Aachen, Pauwelsstr. 30, 52074, Aachen, Germany
| | - Carolin V Schneider
- Medical Clinic III, Gastroenterology, Metabolic Diseases and Intensive Care, University Hospital RWTH Aachen, Pauwelsstr. 30, 52074, Aachen, Germany
- The Institute for Translational Medicine and Therapeutics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Tony Bruns
- Medical Clinic III, Gastroenterology, Metabolic Diseases and Intensive Care, University Hospital RWTH Aachen, Pauwelsstr. 30, 52074, Aachen, Germany
| | - Pavel Strnad
- Medical Clinic III, Gastroenterology, Metabolic Diseases and Intensive Care, University Hospital RWTH Aachen, Pauwelsstr. 30, 52074, Aachen, Germany.
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Ramirez AH, Sulieman L, Schlueter DJ, Halvorson A, Qian J, Ratsimbazafy F, Loperena R, Mayo K, Basford M, Deflaux N, Muthuraman KN, Natarajan K, Kho A, Xu H, Wilkins C, Anton-Culver H, Boerwinkle E, Cicek M, Clark CR, Cohn E, Ohno-Machado L, Schully SD, Ahmedani BK, Argos M, Cronin RM, O’Donnell C, Fouad M, Goldstein DB, Greenland P, Hebbring SJ, Karlson EW, Khatri P, Korf B, Smoller JW, Sodeke S, Wilbanks J, Hentges J, Mockrin S, Lunt C, Devaney SA, Gebo K, Denny JC, Carroll RJ, Glazer D, Harris PA, Hripcsak G, Philippakis A, Roden DM, Ahmedani B, Cole Johnson CD, Ahsan H, Antoine-LaVigne D, Singleton G, Anton-Culver H, Topol E, Baca-Motes K, Steinhubl S, Wade J, Begale M, Jain P, Sutherland S, Lewis B, Korf B, Behringer M, Gharavi AG, Goldstein DB, Hripcsak G, Bier L, Boerwinkle E, Brilliant MH, Murali N, Hebbring SJ, Farrar-Edwards D, Burnside E, Drezner MK, Taylor A, Channamsetty V, Montalvo W, Sharma Y, Chinea C, Jenks N, Cicek M, Thibodeau S, Holmes BW, Schlueter E, Collier E, Winkler J, Corcoran J, D’Addezio N, Daviglus M, Winn R, Wilkins C, Roden D, Denny J, Doheny K, Nickerson D, Eichler E, Jarvik G, Funk G, Philippakis A, et alRamirez AH, Sulieman L, Schlueter DJ, Halvorson A, Qian J, Ratsimbazafy F, Loperena R, Mayo K, Basford M, Deflaux N, Muthuraman KN, Natarajan K, Kho A, Xu H, Wilkins C, Anton-Culver H, Boerwinkle E, Cicek M, Clark CR, Cohn E, Ohno-Machado L, Schully SD, Ahmedani BK, Argos M, Cronin RM, O’Donnell C, Fouad M, Goldstein DB, Greenland P, Hebbring SJ, Karlson EW, Khatri P, Korf B, Smoller JW, Sodeke S, Wilbanks J, Hentges J, Mockrin S, Lunt C, Devaney SA, Gebo K, Denny JC, Carroll RJ, Glazer D, Harris PA, Hripcsak G, Philippakis A, Roden DM, Ahmedani B, Cole Johnson CD, Ahsan H, Antoine-LaVigne D, Singleton G, Anton-Culver H, Topol E, Baca-Motes K, Steinhubl S, Wade J, Begale M, Jain P, Sutherland S, Lewis B, Korf B, Behringer M, Gharavi AG, Goldstein DB, Hripcsak G, Bier L, Boerwinkle E, Brilliant MH, Murali N, Hebbring SJ, Farrar-Edwards D, Burnside E, Drezner MK, Taylor A, Channamsetty V, Montalvo W, Sharma Y, Chinea C, Jenks N, Cicek M, Thibodeau S, Holmes BW, Schlueter E, Collier E, Winkler J, Corcoran J, D’Addezio N, Daviglus M, Winn R, Wilkins C, Roden D, Denny J, Doheny K, Nickerson D, Eichler E, Jarvik G, Funk G, Philippakis A, Rehm H, Lennon N, Kathiresan S, Gabriel S, Gibbs R, Gil Rico EM, Glazer D, Grand J, Greenland P, Harris P, Shenkman E, Hogan WR, Igho-Pemu P, Pollan C, Jorge M, Okun S, Karlson EW, Smoller J, Murphy SN, Ross ME, Kaushal R, Winford E, Wallace F, Khatri P, Kheterpal V, Ojo A, Moreno FA, Kron I, Peterson R, Menon U, Lattimore PW, Leviner N, Obedin-Maliver J, Lunn M, Malik-Gagnon L, Mangravite L, Marallo A, Marroquin O, Visweswaran S, Reis S, Marshall G, McGovern P, Mignucci D, Moore J, Munoz F, Talavera G, O'Connor GT, O'Donnell C, Ohno-Machado L, Orr G, Randal F, Theodorou AA, Reiman E, Roxas-Murray M, Stark L, Tepp R, Zhou A, Topper S, Trousdale R, Tsao P, Weidman L, Weiss ST, Wellis D, Whittle J, Wilson A, Zuchner S, Zwick ME. The All of Us Research Program: Data quality, utility, and diversity. PATTERNS (NEW YORK, N.Y.) 2022; 3:100570. [PMID: 36033590 PMCID: PMC9403360 DOI: 10.1016/j.patter.2022.100570] [Show More Authors] [Citation(s) in RCA: 132] [Impact Index Per Article: 44.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 03/30/2022] [Accepted: 07/14/2022] [Indexed: 11/05/2022]
Abstract
The All of Us Research Program seeks to engage at least one million diverse participants to advance precision medicine and improve human health. We describe here the cloud-based Researcher Workbench that uses a data passport model to democratize access to analytical tools and participant information including survey, physical measurement, and electronic health record (EHR) data. We also present validation study findings for several common complex diseases to demonstrate use of this novel platform in 315,000 participants, 78% of whom are from groups historically underrepresented in biomedical research, including 49% self-reporting non-White races. Replication findings include medication usage pattern differences by race in depression and type 2 diabetes, validation of known cancer associations with smoking, and calculation of cardiovascular risk scores by reported race effects. The cloud-based Researcher Workbench represents an important advance in enabling secure access for a broad range of researchers to this large resource and analytical tools.
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163
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Xu J, Johnson JS, Signer R, Birgegård A, Jordan J, Kennedy MA, Landén M, Maguire SL, Martin NG, Mortensen PB, Petersen LV, Thornton LM, Bulik CM, Huckins LM. Exploring the clinical and genetic associations of adult weight trajectories using electronic health records in a racially diverse biobank: a phenome-wide and polygenic risk study. Lancet Digit Health 2022; 4:e604-e614. [PMID: 35780037 PMCID: PMC9612590 DOI: 10.1016/s2589-7500(22)00099-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 04/19/2022] [Accepted: 05/06/2022] [Indexed: 11/10/2022]
Abstract
BACKGROUND Weight trajectories might reflect individual health status. In this study, we aimed to examine the clinical and genetic associations of adult weight trajectories using electronic health records (EHRs) in the BioMe Biobank. METHODS We constructed four weight trajectories based on a-priori definitions of weight changes (5% or 10%) using annual weight in EHRs (stable weight, weight gain, weight loss, and weight cycle); the final weight dataset included 21 487 participants with 162 783 annual weight measures. To confirm accurate assignment of weight trajectories, we manually reviewed weight trajectory plots for 100 random individuals. We then did a hypothesis-free phenome-wide association study (PheWAS) to identify diseases associated with each weight trajectory. Next, we estimated the single-nucleotide polymorphism-based heritability (hSNP2) of weight trajectories using GCTA-GREML, and we did a hypothesis-driven analysis of anorexia nervosa and depression polygenic risk scores (PRS) on these weight trajectories, given both diseases are associated with weight changes. We extended our analyses to the UK Biobank to replicate findings from a patient population to a generally healthy population. FINDINGS We found high concordance between manually assigned weight trajectories and those assigned by the algorithm (accuracy ≥98%). Stable weight was consistently associated with lower disease risks among those passing Bonferroni-corrected p value in our PheWAS (p≤4·4 × 10-5). Additionally, we identified an association between depression and weight cycle (odds ratio [OR] 1·42, 95% CI 1·31-1·55, p≤7·7 × 10-16). The adult weight trajectories were heritable (using 5% weight change as the cutoff: hSNP2 of 2·1%, 95% CI 0·9-3·3, for stable weight; 4·1%, 1·4-6·8, for weight gain; 5·5%, 2·8-8·2, for weight loss; and 4·7%, 2·3-7·1%, for weight cycle). Anorexia nervosa PRS was positively associated with weight loss trajectory among individuals without eating disorder diagnoses (OR1SD 1·16, 95% CI 1·07-1·26, per 1 SD higher PRS, p=0·011), and the association was not attenuated by obesity PRS. No association was found between depression PRS and weight trajectories after permutation tests. All main findings were replicated in the UK Biobank (p<0·05). INTERPRETATION Our findings suggest the importance of considering weight from a longitudinal aspect for its association with health and highlight a crucial role of weight management during disease development and progression. FUNDING Klarman Family Foundation, US National Institute of Mental Health (NIMH).
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Affiliation(s)
- Jiayi Xu
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jessica S Johnson
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Rebecca Signer
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Andreas Birgegård
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Jennifer Jordan
- Department of Psychological Medicine, University of Otago, Christchurch, New Zealand; Canterbury District Health Board, Christchurch, New Zealand
| | - Martin A Kennedy
- Department of Pathology and Biomedical Science, University of Otago, Christchurch, New Zealand
| | - Mikael Landén
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
| | - Sarah L Maguire
- InsideOut Institute, Charles Perkins Centre, The University of Sydney, Camperdown, Sydney, NSW, Australia
| | - Nicholas G Martin
- Genetics & Computational Biology Department, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Preben Bo Mortensen
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark; National Centre for Register-Based Research, Aarhus BSS, and Centre for Integrated Register-based Research, Aarhus University, Aarhus, Denmark
| | - Liselotte V Petersen
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark; National Centre for Register-Based Research, Aarhus BSS, and Centre for Integrated Register-based Research, Aarhus University, Aarhus, Denmark
| | - Laura M Thornton
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Cynthia M Bulik
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Laura M Huckins
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Mental Illness Research, Education and Clinical Centers, James J Peters Department of Veterans Affairs Medical Center, Bronx, NY, USA.
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164
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Liu H, Doke T, Guo D, Sheng X, Ma Z, Park J, Vy HMT, Nadkarni GN, Abedini A, Miao Z, Palmer M, Voight BF, Li H, Brown CD, Ritchie MD, Shu Y, Susztak K. Epigenomic and transcriptomic analyses define core cell types, genes and targetable mechanisms for kidney disease. Nat Genet 2022; 54:950-962. [PMID: 35710981 PMCID: PMC11626562 DOI: 10.1038/s41588-022-01097-w] [Citation(s) in RCA: 102] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 05/09/2022] [Indexed: 12/29/2022]
Abstract
More than 800 million people suffer from kidney disease, yet the mechanism of kidney dysfunction is poorly understood. In the present study, we define the genetic association with kidney function in 1.5 million individuals and identify 878 (126 new) loci. We map the genotype effect on the methylome in 443 kidneys, transcriptome in 686 samples and single-cell open chromatin in 57,229 kidney cells. Heritability analysis reveals that methylation variation explains a larger fraction of heritability than gene expression. We present a multi-stage prioritization strategy and prioritize target genes for 87% of kidney function loci. We highlight key roles of proximal tubules and metabolism in kidney function regulation. Furthermore, the causal role of SLC47A1 in kidney disease is defined in mice with genetic loss of Slc47a1 and in human individuals carrying loss-of-function variants. Our findings emphasize the key role of bulk and single-cell epigenomic information in translating genome-wide association studies into identifying causal genes, cellular origins and mechanisms of complex traits.
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Affiliation(s)
- Hongbo Liu
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Tomohito Doke
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Dong Guo
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland, Baltimore, Baltimore, MD, USA
| | - Xin Sheng
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Ziyuan Ma
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Joseph Park
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
- Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ha My T Vy
- Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Girish N Nadkarni
- Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Hasso Plattner Institute of Digital Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Mount Sinai Clinical Intelligence Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Amin Abedini
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Zhen Miao
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Matthew Palmer
- Pathology and Laboratory Medicine, Hospital of the University of Pennsylvania, Philadelphia, USA
| | - Benjamin F Voight
- Institute of Diabetes Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA, USA
| | - Hongzhe Li
- Department of Biostatistics, Epidemiology, and Informatics, and Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Marylyn D Ritchie
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
- Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Yan Shu
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland, Baltimore, Baltimore, MD, USA
| | - Katalin Susztak
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA.
- Institute of Diabetes Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA.
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Markowitz RHG, LaBella AL, Shi M, Rokas A, Capra JA, Ferguson JF, Mosley JD, Bordenstein SR. Microbiome-associated human genetic variants impact phenome-wide disease risk. Proc Natl Acad Sci U S A 2022; 119:e2200551119. [PMID: 35749358 PMCID: PMC9245617 DOI: 10.1073/pnas.2200551119] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Accepted: 04/29/2022] [Indexed: 12/26/2022] Open
Abstract
Human genetic variation associates with the composition of the gut microbiome, yet its influence on clinical traits remains largely unknown. We analyzed the consequences of nearly a thousand gut microbiome-associated variants (MAVs) on phenotypes reported in electronic health records from tens of thousands of individuals. We discovered and replicated associations of MAVs with neurological, metabolic, digestive, and circulatory diseases. Five significant MAVs in these categories correlate with the relative abundance of microbes down to the strain level. We also demonstrate that these relationships are independently observed and concordant with microbe by disease associations reported in case-control studies. Moreover, a selective sweep and population differentiation impacted some disease-linked MAVs. Combined, these findings establish triad relationships among the human genome, microbiome, and disease. Consequently, human genetic influences may offer opportunities for precision diagnostics of microbiome-associated diseases but also highlight the relevance of genetic background for microbiome modulation and therapeutics.
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Affiliation(s)
- Robert H. George Markowitz
- Vanderbilt Microbiome Innovation Center, Vanderbilt University, Nashville, TN 37232
- Department of Biological Sciences, Vanderbilt University, Nashville, TN 37232
| | | | - Mingjian Shi
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232
| | - Antonis Rokas
- Department of Biological Sciences, Vanderbilt University, Nashville, TN 37232
| | - John A. Capra
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA 94143
- Bakar Computational Health Sciences Institute, University of California, San Francisco, CA 94143
| | - Jane F. Ferguson
- Vanderbilt Microbiome Innovation Center, Vanderbilt University, Nashville, TN 37232
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232
| | - Jonathan D. Mosley
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232
| | - Seth R. Bordenstein
- Vanderbilt Microbiome Innovation Center, Vanderbilt University, Nashville, TN 37232
- Department of Biological Sciences, Vanderbilt University, Nashville, TN 37232
- Vanderbilt Institute for Infection, Immunology and Inflammation, Vanderbilt University Medical Center, Nashville, TN 37232
- Department of Pathology, Microbiology, and Immunology, School of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232
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Shi M, Wang C, Mei H, Temprosa M, Florez JC, Tripputi M, Merino J, Lipworth L, Shu X, Gerszten RE, Wang TJ, Beckman JA, Gamboa JL, Mosley JD, Ferguson JF, Diabetes Prevention Program Research Group. Genetic Architecture of Plasma Alpha-Aminoadipic Acid Reveals a Relationship With High-Density Lipoprotein Cholesterol. J Am Heart Assoc 2022; 11:e024388. [PMID: 35621206 PMCID: PMC9238724 DOI: 10.1161/jaha.121.024388] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Accepted: 04/13/2022] [Indexed: 11/16/2022]
Abstract
Background Elevated plasma levels of alpha-aminoadipic acid (2-AAA) have been associated with the development of type 2 diabetes and atherosclerosis. However, the nature of the association remains unknown. Methods and Results We identified genetic determinants of plasma 2-AAA through meta-analysis of genome-wide association study data in 5456 individuals of European, African, and Asian ancestry from the Framingham Heart Study, Diabetes Prevention Program, Jackson Heart Study, and Shanghai Women's and Men's Health Studies. No single nucleotide polymorphisms reached genome-wide significance across all samples. However, the top associations from the meta-analysis included single-nucleotide polymorphisms in the known 2-AAA pathway gene DHTKD1, and single-nucleotide polymorphisms in genes involved in mitochondrial respiration (NDUFS4) and macrophage function (MSR1). We used a Mendelian randomization instrumental variable approach to evaluate relationships between 2-AAA and cardiometabolic phenotypes in large disease genome-wide association studies. Mendelian randomization identified a suggestive inverse association between increased 2-AAA and lower high-density lipoprotein cholesterol (P=0.005). We further characterized the genetically predicted relationship through measurement of plasma 2-AAA and high-density lipoprotein cholesterol in 2 separate samples of individuals with and without cardiometabolic disease (N=98), and confirmed a significant negative correlation between 2-AAA and high-density lipoprotein (rs=-0.53, P<0.0001). Conclusions 2-AAA levels in plasma may be regulated, in part, by common variants in genes involved in mitochondrial and macrophage function. Elevated plasma 2-AAA associates with reduced levels of high-density lipoprotein cholesterol. Further mechanistic studies are required to probe this as a possible mechanism linking 2-AAA to future cardiometabolic risk.
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Affiliation(s)
- Mingjian Shi
- Department of Biomedical InformaticsVanderbilt University Medical CenterNashvilleTN
| | - Chuan Wang
- Division of Cardiovascular MedicineDepartment of MedicineVanderbilt University Medical CenterNashvilleTN
| | - Hao Mei
- Department of Data ScienceSchool of Population HealthUniversity of Mississippi Medical CenterJacksonMS
| | - Marinella Temprosa
- Department of Biostatistics and BioinformaticsMilken Institute School of Public HealthGeorge Washington UniversityRockvilleMD
| | - Jose C. Florez
- Center for Genomic Medicine and Diabetes UnitMassachusetts General HospitalBostonMA
- Programs in Metabolism and Medical & Population GeneticsBroad InstituteCambridgeMA
- Department of MedicineHarvard Medical SchoolBostonMA
| | - Mark Tripputi
- Department of Biostatistics and BioinformaticsMilken Institute School of Public HealthGeorge Washington UniversityRockvilleMD
| | - Jordi Merino
- Center for Genomic Medicine and Diabetes UnitMassachusetts General HospitalBostonMA
- Programs in Metabolism and Medical & Population GeneticsBroad InstituteCambridgeMA
- Department of MedicineHarvard Medical SchoolBostonMA
| | - Loren Lipworth
- Division of EpidemiologyDepartment of MedicineVanderbilt University Medical CenterNashvilleTN
| | - Xiao‐Ou Shu
- Division of EpidemiologyDepartment of MedicineVanderbilt University Medical CenterNashvilleTN
| | - Robert E. Gerszten
- Division of Cardiovascular MedicineBeth Israel Deaconess Medical CenterBostonMA
- Broad Institute of Harvard and MITCambridgeMA
| | - Thomas J. Wang
- Department of MedicineUT Southwestern Medical CenterDallasTX
| | - Joshua A. Beckman
- Division of Cardiovascular MedicineDepartment of MedicineVanderbilt University Medical CenterNashvilleTN
| | - Jorge L. Gamboa
- Division of Clinical PharmacologyDepartment of MedicineVanderbilt University Medical CenterNashvilleTN
| | - Jonathan D. Mosley
- Department of Biomedical InformaticsVanderbilt University Medical CenterNashvilleTN
- Division of Clinical PharmacologyDepartment of MedicineVanderbilt University Medical CenterNashvilleTN
| | - Jane F. Ferguson
- Division of Cardiovascular MedicineDepartment of MedicineVanderbilt University Medical CenterNashvilleTN
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Chang T, Yen T, Wei C, Hsiao T, Chen I. Impacts of ADH1B rs1229984 and ALDH2 rs671 polymorphisms on risks of alcohol-related disorder and cancer. Cancer Med 2022; 12:747-759. [PMID: 35670037 PMCID: PMC9844601 DOI: 10.1002/cam4.4920] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 05/18/2022] [Accepted: 05/24/2022] [Indexed: 01/25/2023] Open
Abstract
BACKGROUND ADH1B rs1229984 and ALDH2 rs671 are the specifically prevalent functional variants in the East Asians. These variants, which result in a dramatic change in enzyme activity, are highly associated with alcohol-related disorders and cancer. Previous studies focusing on the additive and synergic effects of the variants are few and inconsistent. The aim of the research was to evaluate the associations of ADH1B rs1229984 and ALDH2 rs671 with the risks of alcohol-related disorder and cancer. METHODS This cohort study enrolled 42,665 participants from the Taiwan Precision Medicine Initiative database, including 19,522 and 20,534, ADH1B and ALDH2 carriers, respectively. The associations between the two variants and cancer risk were analyzed by univariable and multivariable logistic regression. RESULTS Compared with the noncarriers, the ADH1B rs1229984 variant had a stronger effect on alcohol-related disorders and was related to an increased risk of alcohol-related cancers. The CC genotype of ADH1B rs1229984 was significantly associated with cancer of the larynx, pharynx, and nasal cavities [odds ratio (OR) = 1.56, p = 0.0009], cancer of the pancreas (OR = 1.66, p = 0.018), and cancer of the esophagus (OR = 4.10, p < 0.001). Participants who carried the rs1229984 TC/CC and rs671 GG genotypes were at higher risk of esophageal cancer (OR = 3.02, p < 0.001). The risk of esophageal cancer was increased by 381% (OR = 4.81, p < 0.001) in those carrying the rs1229984 TC/CC and rs671 GA/AA genotypes. CONCLUSION rs1229984 and rs671 are common and functionally important genetic variants in the Taiwanese population. Our findings provide strong evidence of additive and synergic risks of ADH1B and ALDH2 variants for alcohol-related disorders and cancer. The results suggested that are reduction in alcohol consumption should be advised as a preventive measure for high-risk patients carrying ADH1B rs1229984 C or the ALDH2 rs671 A allele.
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Affiliation(s)
- Ting‐Gang Chang
- Department of PsychiatryTaichung Veterans General HospitalTaichungTaiwan,School of PsychologyChung Shan Medical UniversityTaichungTaiwan
| | - Ting‐Ting Yen
- Department of OtorhinolaryngologyTaichung Veterans General HospitalTaichungTaiwan,School of MedicineNational Yang Ming Chiao Tung UniversityTaipeiTaiwan
| | - Chia‐Yi Wei
- Department of Medical ResearchTaichung Veterans General HospitalTaichungTaiwan
| | - Tzu‐Hung Hsiao
- Department of Medical ResearchTaichung Veterans General HospitalTaichungTaiwan,Department of Public Health, College of MedicineFu Jen Catholic UniversityNew Taipei CityTaiwan,Institute of Genomics and BioinformaticsNational Chung Hsing UniversityTaichungTaiwan
| | - I‐Chieh Chen
- Department of Medical ResearchTaichung Veterans General HospitalTaichungTaiwan
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168
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Cadby G, Giles C, Melton PE, Huynh K, Mellett NA, Duong T, Nguyen A, Cinel M, Smith A, Olshansky G, Wang T, Brozynska M, Inouye M, McCarthy NS, Ariff A, Hung J, Hui J, Beilby J, Dubé MP, Watts GF, Shah S, Wray NR, Lim WLF, Chatterjee P, Martins I, Laws SM, Porter T, Vacher M, Bush AI, Rowe CC, Villemagne VL, Ames D, Masters CL, Taddei K, Arnold M, Kastenmüller G, Nho K, Saykin AJ, Han X, Kaddurah-Daouk R, Martins RN, Blangero J, Meikle PJ, Moses EK. Comprehensive genetic analysis of the human lipidome identifies loci associated with lipid homeostasis with links to coronary artery disease. Nat Commun 2022; 13:3124. [PMID: 35668104 PMCID: PMC9170690 DOI: 10.1038/s41467-022-30875-7] [Citation(s) in RCA: 51] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 05/17/2022] [Indexed: 12/26/2022] Open
Abstract
We integrated lipidomics and genomics to unravel the genetic architecture of lipid metabolism and identify genetic variants associated with lipid species putatively in the mechanistic pathway for coronary artery disease (CAD). We quantified 596 lipid species in serum from 4,492 individuals from the Busselton Health Study. The discovery GWAS identified 3,361 independent lipid-loci associations, involving 667 genomic regions (479 previously unreported), with validation in two independent cohorts. A meta-analysis revealed an additional 70 independent genomic regions associated with lipid species. We identified 134 lipid endophenotypes for CAD associated with 186 genomic loci. Associations between independent lipid-loci with coronary atherosclerosis were assessed in ∼456,000 individuals from the UK Biobank. Of the 53 lipid-loci that showed evidence of association (P < 1 × 10-3), 43 loci were associated with at least one lipid endophenotype. These findings illustrate the value of integrative biology to investigate the aetiology of atherosclerosis and CAD, with implications for other complex diseases.
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Affiliation(s)
- Gemma Cadby
- School of Population and Global Health, University of Western Australia, Crawley, WA, Australia
| | - Corey Giles
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
- Baker Department of Cardiometabolic Health, University of Melbourne, Melbourne, VIC, Australia
| | - Phillip E Melton
- School of Population and Global Health, University of Western Australia, Crawley, WA, Australia
- Menzies Research Institute, University of Tasmania, Hobart, TAS, Australia
| | - Kevin Huynh
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
- Baker Department of Cardiometabolic Health, University of Melbourne, Melbourne, VIC, Australia
| | | | - Thy Duong
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
| | - Anh Nguyen
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
| | - Michelle Cinel
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
| | - Alex Smith
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
| | - Gavriel Olshansky
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
- Baker Department of Cardiometabolic Health, University of Melbourne, Melbourne, VIC, Australia
| | - Tingting Wang
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
- Baker Department of Cardiometabolic Health, University of Melbourne, Melbourne, VIC, Australia
| | - Marta Brozynska
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
| | - Mike Inouye
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
| | - Nina S McCarthy
- School of Biomedical Sciences, University of Western Australia, Crawley, WA, Australia
| | - Amir Ariff
- School of Women's and Children's Health, University of New South Wales, Sydney, NSW, Australia
| | - Joseph Hung
- School of Medicine, The University of Western Australia, Crawley, WA, Australia
- Department of Cardiovascular Medicine, Sir Charles Gairdner Hospital, Perth, WA, Australia
- Busselton Population Medical Research Institute Inc., Perth, WA, Australia
| | - Jennie Hui
- Busselton Population Medical Research Institute Inc., Perth, WA, Australia
- PathWest Laboratory Medicine WA, Perth, WA, Australia
| | - John Beilby
- Busselton Population Medical Research Institute Inc., Perth, WA, Australia
- PathWest Laboratory Medicine WA, Perth, WA, Australia
| | - Marie-Pierre Dubé
- Université de Montréal Beaulieu-Saucier Pharmacogenomics Centre, Montreal Heart Institute, Montreal, QC, Canada
| | - Gerald F Watts
- School of Medicine, The University of Western Australia, Crawley, WA, Australia
- Lipid Disorders Clinic, Department of Cardiology, Royal Perth Hospital, Perth, WA, Australia
| | - Sonia Shah
- Institute for Molecular Biosciences, University of Queensland, Brisbane, QLD, Australia
| | - Naomi R Wray
- Institute for Molecular Biosciences, University of Queensland, Brisbane, QLD, Australia
- Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia
| | - Wei Ling Florence Lim
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- Cooperative research Centre (CRC) for Mental Health, Joondalup, WA, Australia
| | - Pratishtha Chatterjee
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- Department of Biomedical Sciences, Macquarie University, North Ryde, NSW, Australia
- KaRa Institute of Neurological Disease, Sydney, Macquarie Park, NSW, Australia
| | - Ian Martins
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - Simon M Laws
- Centre for Precision Health, Edith Cowan University, Joondalup, WA, Australia
- Collaborative Genomics Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- Curtin Health Innovation Research Institute, Curtin University, Perth, WA, Australia
| | - Tenielle Porter
- Centre for Precision Health, Edith Cowan University, Joondalup, WA, Australia
- Collaborative Genomics Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- Curtin Health Innovation Research Institute, Curtin University, Perth, WA, Australia
| | - Michael Vacher
- Centre for Precision Health, Edith Cowan University, Joondalup, WA, Australia
- Collaborative Genomics Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- The Australian e-Health Research Centre, Health and Biosecurity, CSIRO, Floreat, WA, Australia
| | - Ashley I Bush
- The Florey Department of Neuroscience and Mental Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Christopher C Rowe
- The Florey Department of Neuroscience and Mental Health, The University of Melbourne, Melbourne, VIC, Australia
- Department of Molecular Imaging and Therapy, Austin Health, Heidelberg, VIC, Australia
| | - Victor L Villemagne
- Department of Molecular Imaging and Therapy, Austin Health, Heidelberg, VIC, Australia
- Department of Medicine, Austin Health, The University of Melbourne, Heidelberg, VIC, Australia
| | - David Ames
- National Ageing Research Institute, Parkville, VIC, Australia
- University of Melbourne Academic Unit for Psychiatry of Old Age, St George's Hospital, Kew, VIC, Australia
| | - Colin L Masters
- The Florey Department of Neuroscience and Mental Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Kevin Taddei
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - Matthias Arnold
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Gabi Kastenmüller
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Kwangsik Nho
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Andrew J Saykin
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Xianlin Han
- Barshop Institute for Longevity and Aging Studies, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Rima Kaddurah-Daouk
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
- Duke Institute of Brain Sciences, Duke University, Durham, NC, USA
- Department of Medicine, Duke University, Durham, NC, USA
| | - Ralph N Martins
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- Cooperative research Centre (CRC) for Mental Health, Joondalup, WA, Australia
- Department of Biomedical Sciences, Macquarie University, North Ryde, NSW, Australia
- KaRa Institute of Neurological Disease, Sydney, Macquarie Park, NSW, Australia
| | - John Blangero
- South Texas Diabetes and Obesity Institute, The University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - Peter J Meikle
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia.
- Baker Department of Cardiometabolic Health, University of Melbourne, Melbourne, VIC, Australia.
- Monash University, Melbourne, VIC, Australia.
| | - Eric K Moses
- Menzies Research Institute, University of Tasmania, Hobart, TAS, Australia.
- School of Biomedical Sciences, University of Western Australia, Crawley, WA, Australia.
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169
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Sorokin EP, Basty N, Whitcher B, Liu Y, Bell JD, Cohen RL, Cule M, Thomas EL. Analysis of MRI-derived spleen iron in the UK Biobank identifies genetic variation linked to iron homeostasis and hemolysis. Am J Hum Genet 2022; 109:1092-1104. [PMID: 35568031 PMCID: PMC9247824 DOI: 10.1016/j.ajhg.2022.04.013] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Accepted: 04/19/2022] [Indexed: 11/25/2022] Open
Abstract
The spleen plays a key role in iron homeostasis. It is the largest filter of the blood and performs iron reuptake from old or damaged erythrocytes. Despite this role, spleen iron concentration has not been measured in a large, population-based cohort. In this study, we quantify spleen iron in 41,764 participants of the UK Biobank by using magnetic resonance imaging and provide a reference range for spleen iron in an unselected population. Through genome-wide association study, we identify associations between spleen iron and regulatory variation at two hereditary spherocytosis genes, ANK1 and SPTA1. Spherocytosis-causing coding mutations in these genes are associated with lower reticulocyte volume and increased reticulocyte percentage, while these common alleles are associated with increased expression of ANK1 and SPTA1 in blood and with larger reticulocyte volume and reduced reticulocyte percentage. As genetic modifiers, these common alleles may explain mild spherocytosis phenotypes that have been observed clinically. Our genetic study also identifies a signal that co-localizes with a splicing quantitative trait locus for MS4A7, and we show this gene is abundantly expressed in the spleen and in macrophages. The combination of deep learning and efficient image processing enables non-invasive measurement of spleen iron and, in turn, characterization of genetic factors related to the lytic phase of the erythrocyte life cycle and iron reuptake in the spleen.
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Affiliation(s)
| | - Nicolas Basty
- Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK
| | - Brandon Whitcher
- Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK
| | - Yi Liu
- Calico Life Sciences LLC, South San Francisco, CA, USA
| | - Jimmy D Bell
- Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK
| | | | | | - E Louise Thomas
- Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK.
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170
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Raghavan S, Huang J, Tcheandjieu C, Huffman JE, Litkowski E, Liu C, Ho YLA, Hunter-Zinck H, Zhao H, Marouli E, North KE, the VA Million Veteran Program, Lange E, Lange LA, Voight BF, Gaziano JM, Pyarajan S, Hauser ER, Tsao PS, Wilson PWF, Chang KM, Cho K, O’Donnell CJ, Sun YV, Assimes TL. A multi-population phenome-wide association study of genetically-predicted height in the Million Veteran Program. PLoS Genet 2022; 18:e1010193. [PMID: 35653334 PMCID: PMC9162317 DOI: 10.1371/journal.pgen.1010193] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 04/05/2022] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND Height has been associated with many clinical traits but whether such associations are causal versus secondary to confounding remains unclear in many cases. To systematically examine this question, we performed a Mendelian Randomization-Phenome-wide association study (MR-PheWAS) using clinical and genetic data from a national healthcare system biobank. METHODS AND FINDINGS Analyses were performed using data from the US Veterans Affairs (VA) Million Veteran Program in non-Hispanic White (EA, n = 222,300) and non-Hispanic Black (AA, n = 58,151) adults in the US. We estimated height genetic risk based on 3290 height-associated variants from a recent European-ancestry genome-wide meta-analysis. We compared associations of measured and genetically-predicted height with phenome-wide traits derived from the VA electronic health record, adjusting for age, sex, and genetic principal components. We found 345 clinical traits associated with measured height in EA and an additional 17 in AA. Of these, 127 were associated with genetically-predicted height at phenome-wide significance in EA and 2 in AA. These associations were largely independent from body mass index. We confirmed several previously described MR associations between height and cardiovascular disease traits such as hypertension, hyperlipidemia, coronary heart disease (CHD), and atrial fibrillation, and further uncovered MR associations with venous circulatory disorders and peripheral neuropathy in the presence and absence of diabetes. As a number of traits associated with genetically-predicted height frequently co-occur with CHD, we evaluated effect modification by CHD status of genetically-predicted height associations with risk factors for and complications of CHD. We found modification of effects of MR associations by CHD status for atrial fibrillation/flutter but not for hypertension, hyperlipidemia, or venous circulatory disorders. CONCLUSIONS We conclude that height may be an unrecognized but biologically plausible risk factor for several common conditions in adults. However, more studies are needed to reliably exclude horizontal pleiotropy as a driving force behind at least some of the MR associations observed in this study.
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Affiliation(s)
- Sridharan Raghavan
- Medicine Service, Veterans Affairs Eastern Colorado Health Care System, Aurora, Colorado, United States of America
- Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States of America
| | - Jie Huang
- School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen, Guangdong, China
| | - Catherine Tcheandjieu
- Veterans Affairs Palo Alto Health Care System, Palo Alto, California, United States of America
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, California, United States of America
| | - Jennifer E. Huffman
- Veterans Affairs Boston Healthcare System, Boston, Massachusetts, United States of America
| | - Elizabeth Litkowski
- Medicine Service, Veterans Affairs Eastern Colorado Health Care System, Aurora, Colorado, United States of America
| | - Chang Liu
- Atlanta Veterans Affairs Medical Center, Atlanta, Georgia, United States of America
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, Georgia, United States of America
| | - Yuk-Lam A. Ho
- Veterans Affairs Boston Healthcare System, Boston, Massachusetts, United States of America
| | - Haley Hunter-Zinck
- Veterans Affairs Boston Healthcare System, Boston, Massachusetts, United States of America
| | - Hongyu Zhao
- Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut, United States of America
- Department of Biostatistics, Yale University School of Public Health, New Haven, Connecticut, United States of America
| | - Eirini Marouli
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Kari E. North
- Department of Epidemiology, Gillings School of Public Health, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | | | - Ethan Lange
- Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States of America
| | - Leslie A. Lange
- Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States of America
| | - Benjamin F. Voight
- Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania, United States of America
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States of America
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States of America
- Institute of Translational Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States of America
| | - J. Michael Gaziano
- Veterans Affairs Boston Healthcare System, Boston, Massachusetts, United States of America
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Saiju Pyarajan
- Veterans Affairs Boston Healthcare System, Boston, Massachusetts, United States of America
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Elizabeth R. Hauser
- Cooperative Studies Program Epidemiology Center- Durham, Durham Veterans Affairs Health Care System, Durham, North Carolina, United States of America
- Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, North Carolina, United States of America
| | - Philip S. Tsao
- Veterans Affairs Palo Alto Health Care System, Palo Alto, California, United States of America
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, California, United States of America
| | - Peter W. F. Wilson
- Atlanta Veterans Affairs Medical Center, Atlanta, Georgia, United States of America
- Division of Cardiology, Emory University School of Medicine, Atlanta, Georgia, United States of America
| | - Kyong-Mi Chang
- Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania, United States of America
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States of America
| | - Kelly Cho
- Veterans Affairs Boston Healthcare System, Boston, Massachusetts, United States of America
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Christopher J. O’Donnell
- Veterans Affairs Boston Healthcare System, Boston, Massachusetts, United States of America
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Yan V. Sun
- Atlanta Veterans Affairs Medical Center, Atlanta, Georgia, United States of America
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, Georgia, United States of America
| | - Themistocles L. Assimes
- Veterans Affairs Palo Alto Health Care System, Palo Alto, California, United States of America
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, California, United States of America
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Huang RDL, Nguyen XMT, Peloso GM, Trinder M, Posner DC, Aragam KG, Ho YL, Lynch JA, Damrauer SM, Chang KM, Tsao PS, Natarajan P, Assimes T, Gaziano JM, Djousse L, Cho K, Wilson PWF, Huffman JE, O’Donnell CJ, on behalf of the Veterans Affairs’ Million Veteran Program. Genome-wide and phenome-wide analysis of ideal cardiovascular health in the VA Million Veteran Program. PLoS One 2022; 17:e0267900. [PMID: 35613103 PMCID: PMC9132265 DOI: 10.1371/journal.pone.0267900] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2021] [Accepted: 04/18/2022] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Genetic studies may help identify causal pathways; therefore, we sought to identify genetic determinants of ideal CVH and their association with CVD outcomes in the multi-population Veteran Administration Million Veteran Program. METHODS An ideal health score (IHS) was calculated from 3 clinical factors (blood pressure, total cholesterol, and blood glucose levels) and 3 behavioral factors (smoking status, physical activity, and BMI), ascertained at baseline. Multi-population genome-wide association study (GWAS) was performed on IHS and binary ideal health using linear and logistic regression, respectively. Using the genome-wide significant SNPs from the IHS GWAS, we created a weighted IHS polygenic risk score (PRSIHS) which was used (i) to conduct a phenome-wide association study (PheWAS) of associations between PRSIHS and ICD-9 phenotypes and (ii) to further test for associations with mortality and selected CVD outcomes using logistic and Cox regression and, as an instrumental variable, in Mendelian Randomization. RESULTS The discovery and replication cohorts consisted of 142,404 (119,129 European American (EUR); 16,495 African American (AFR)), and 45,766 (37,646 EUR; 5,366 AFR) participants, respectively. The mean age was 65.8 years (SD = 11.2) and 92.7% were male. Overall, 4.2% exhibited ideal CVH based on the clinical and behavioral factors. In the multi-population meta-analysis, variants at 17 loci were associated with IHS and each had known GWAS associations with multiple components of the IHS. PheWAS analysis in 456,026 participants showed that increased PRSIHS was associated with a lower odds ratio for many CVD outcomes and risk factors. Both IHS and PRSIHS measures of ideal CVH were associated with significantly less CVD outcomes and CVD mortality. CONCLUSION A set of high interest genetic variants contribute to the presence of ideal CVH in a multi-ethnic cohort of US Veterans. Genetically influenced ideal CVH is associated with lower odds of CVD outcomes and mortality.
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Affiliation(s)
- Rose D. L. Huang
- Center for Population Genomics, Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America
| | - Xuan-Mai T. Nguyen
- MAVERIC, VA Boston Healthcare System, Boston, Massachusetts, United States of America
- Carle Illinois College of Medicine, University of Illinois at Urbana-Champaign, Champaign, Illinois, United States of America
| | - Gina M. Peloso
- Center for Population Genomics, Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
| | - Mark Trinder
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, Canada
- Program in Medical and Population Genetics and the Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Daniel C. Posner
- MAVERIC, VA Boston Healthcare System, Boston, Massachusetts, United States of America
| | - Krishna G. Aragam
- Program in Medical and Population Genetics and the Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
- Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Yuk-Lam Ho
- MAVERIC, VA Boston Healthcare System, Boston, Massachusetts, United States of America
| | - Julie A. Lynch
- VA Informatics & Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, Utah, United States of America
- College of Nursing & Health Sciences, University of Massachusetts Boston, Boston, Massachusetts, United States of America
| | - Scott M. Damrauer
- Corporal Michael Crescenz VA Medical Center, Philadelphia, Pennsylvania, United States of America
- Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Kyong-Mi Chang
- Corporal Michael Crescenz VA Medical Center, Philadelphia, Pennsylvania, United States of America
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Philip S. Tsao
- VA Palo Alto Health Care System, Palo Alto, California, United States of America
- Department of Medicine, Stanford University School of Medicine, Stanford, California, United States of America
| | - Pradeep Natarajan
- Program in Medical and Population Genetics and the Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
- Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Themistocles Assimes
- VA Palo Alto Health Care System, Palo Alto, California, United States of America
- Department of Medicine, Stanford University School of Medicine, Stanford, California, United States of America
| | - J. Michael Gaziano
- MAVERIC, VA Boston Healthcare System, Boston, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
- Division of Aging, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
| | - Luc Djousse
- MAVERIC, VA Boston Healthcare System, Boston, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
- Division of Aging, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
| | - Kelly Cho
- MAVERIC, VA Boston Healthcare System, Boston, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
- Division of Aging, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
| | - Peter W. F. Wilson
- Atlanta VA Medical Center, Decatur, Georgia, United States of America
- Emory University School of Medicine, Atlanta, Georgia, United States of America
| | - Jennifer E. Huffman
- Center for Population Genomics, Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America
| | - Christopher J. O’Donnell
- Center for Population Genomics, Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
- Heart & Vascular Center, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
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Feng YCA, Stanaway IB, Connolly JJ, Denny JC, Luo Y, Weng C, Wei WQ, Weiss ST, Karlson EW, Smoller JW. Psychiatric manifestations of rare variation in medically actionable genes: a PheWAS approach. BMC Genomics 2022; 23:385. [PMID: 35590255 PMCID: PMC9121574 DOI: 10.1186/s12864-022-08600-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Accepted: 04/22/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND As genomic sequencing moves closer to clinical implementation, there has been an increasing acceptance of returning incidental findings to research participants and patients for mutations in highly penetrant, medically actionable genes. A curated list of genes has been recommended by the American College of Medical Genetics and Genomics (ACMG) for return of incidental findings. However, the pleiotropic effects of these genes are not fully known. Such effects could complicate genetic counseling when returning incidental findings. In particular, there has been no systematic evaluation of psychiatric manifestations associated with rare variation in these genes. RESULTS Here, we leveraged a targeted sequence panel and real-world electronic health records from the eMERGE network to assess the burden of rare variation in the ACMG-56 genes and two psychiatric-associated genes (CACNA1C and TCF4) across common mental health conditions in 15,181 individuals of European descent. As a positive control, we showed that this approach replicated the established association between rare mutations in LDLR and hypercholesterolemia with no visible inflation from population stratification. However, we did not identify any genes significantly enriched with rare deleterious variants that confer risk for common psychiatric disorders after correction for multiple testing. Suggestive associations were observed between depression and rare coding variation in PTEN (P = 1.5 × 10-4), LDLR (P = 3.6 × 10-4), and CACNA1S (P = 5.8 × 10-4). We also observed nominal associations between rare variants in KCNQ1 and substance use disorders (P = 2.4 × 10-4), and APOB and tobacco use disorder (P = 1.1 × 10-3). CONCLUSIONS Our results do not support an association between psychiatric disorders and incidental findings in medically actionable gene mutations, but power was limited with the available sample sizes. Given the phenotypic and genetic complexity of psychiatric phenotypes, future work will require a much larger sequencing dataset to determine whether incidental findings in these genes have implications for risk of psychopathology.
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Affiliation(s)
- Yen-Chen A Feng
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA, USA.
- Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan.
- Master of Public Health Program, National Taiwan University, Taipei, Taiwan.
| | - Ian B Stanaway
- Division of Nephrology, School of Medicine, Kidney Research Institute, University of Washington, Seattle, WA, USA
| | - John J Connolly
- Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Joshua C Denny
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- All of Us Research Program, National Institutes of Health, Besthesda, MD, USA
| | - Yuan Luo
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Chunhua Weng
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Wei-Qi Wei
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Scott T Weiss
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Elizabeth W Karlson
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women's Hospital, Boston, MA, USA
| | - Jordan W Smoller
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA, USA.
- Center for Precision Psychiatry, Massachusetts General Hospital, Boston, MA, USA.
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173
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Gagliano Taliun SA, Sulem P, Sveinbjornsson G, Gudbjartsson DF, Stefansson K, Paterson AD, Barua M. GWAS of Hematuria. Clin J Am Soc Nephrol 2022; 17:672-683. [PMID: 35474271 PMCID: PMC9269584 DOI: 10.2215/cjn.13711021] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Accepted: 03/21/2022] [Indexed: 01/25/2023]
Abstract
BACKGROUND AND OBJECTIVES Glomerular hematuria has varied causes but can have a genetic basis, including Alport syndrome and IgA nephropathy. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS We used summary statistics to identify genetic variants associated with hematuria in White British UK Biobank participants. Individuals with glomerular hematuria were enriched by excluding participants with genitourinary conditions. A strongly associated locus on chromosome 2 (COL4A4-COL4A3) was identified. The region was reimputed using the Trans-Omics for Precision Medicine Program followed by sequential rounds of regional conditional analysis, conditioning on previous genetic signals. Similarly, we applied conditional analysis to identify independent variants in the MHC region on chromosome 6 using imputed HLA haplotypes. RESULTS In total, 16,866 hematuria cases and 391,420 controls were included. Cases had higher urinary albumin-creatinine compared with controls (women: 13.01 mg/g [8.05-21.33] versus 12.12 mg/g [7.61-19.29]; P<0.001; men: 8.85 mg/g [5.66-16.19] versus 7.52 mg/g [5.04-12.39]; P<0.001) and lower eGFR (women: 88±14 versus 90±13 ml/min per 1.72 m2; P<0.001; men: 87±15 versus 90±13 ml/min per 1.72 m2; P<0.001), supporting enrichment of glomerular hematuria. Variants at six loci (PDPN, COL4A4-COL4A3, HLA-B, SORL1, PLLP, and TGFB1) met genome-wide significance (P<5E-8). At chromosome 2, COL4A4 p.Ser969X (rs35138315; minor allele frequency=0.00035; P<7.95E-35; odds ratio, 87.3; 95% confidence interval, 47.9 to 159.0) had the most significant association, and two variants in the locus remained associated with hematuria after conditioning for this variant: COL4A3 p.Gly695Arg (rs200287952; minor allele frequency=0.00021; P<2.16E-7; odds ratio, 45.5; 95% confidence interval, 11.8 to 168.0) and a common COL4A4 intron 25 variant (not previously reported; rs58261427; minor allele frequency=0.214; P<2.00E-9; odds ratio, 1.09; 95% confidence interval, 1.06 to 1.12). Of the HLA haplotypes, HLA-B (*0801; minor allele frequency=0.14; P<4.41E-24; odds ratio, 0.84; 95% confidence interval, 0.82 to 0.88) displayed the most statistically significant association. For remaining loci, we identified three novel associations, which were replicated in the deCODE dataset for dipstick hematuria (nearest genes: PDPN, SORL1, and PLLP). CONCLUSIONS Our study identifies six loci associated with hematuria, including independent variants in COL4A4-COL4A3 and HLA-B. Additionally, three novel loci are reported, including an association with an intronic variant in PDPN expressed in the podocyte. PODCAST This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2022_04_26_CJN13711021.mp3.
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Affiliation(s)
- Sarah A. Gagliano Taliun
- Department of Medicine, Université de Montréal, Montreal, Quebec, Canada,Department of Neurosciences, Université de Montréal, Montreal, Quebec, Canada,Research Centre, Montréal Heart Institute, Montreal, Quebec, Canada
| | | | | | | | - Kari Stefansson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland,Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Andrew D. Paterson
- Division of Epidemiology, Dalla Lana School of Public Health, Toronto, Ontario, Canada,Division of Biostatistics, Dalla Lana School of Public Health, Toronto, Ontario, Canada,Genetics and Genome Biology, Research Institute at The Hospital for Sick Children, Toronto, Ontario, Canada,Institute of Medical Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Moumita Barua
- Institute of Medical Sciences, University of Toronto, Toronto, Ontario, Canada,Division of Nephrology, University Health Network, Toronto, Ontario, Canada,Department of Medicine, University of Toronto, Toronto, Ontario, Canada,Toronto General Hospital Research Institute, Toronto, Ontario, Canada
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174
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Said S, Pazoki R, Karhunen V, Võsa U, Ligthart S, Bodinier B, Koskeridis F, Welsh P, Alizadeh BZ, Chasman DI, Sattar N, Chadeau-Hyam M, Evangelou E, Jarvelin MR, Elliott P, Tzoulaki I, Dehghan A. Genetic analysis of over half a million people characterises C-reactive protein loci. Nat Commun 2022; 13:2198. [PMID: 35459240 PMCID: PMC9033829 DOI: 10.1038/s41467-022-29650-5] [Citation(s) in RCA: 95] [Impact Index Per Article: 31.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Accepted: 03/25/2022] [Indexed: 01/08/2023] Open
Abstract
Chronic low-grade inflammation is linked to a multitude of chronic diseases. We report the largest genome-wide association study (GWAS) on C-reactive protein (CRP), a marker of systemic inflammation, in UK Biobank participants (N = 427,367, European descent) and the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium (total N = 575,531 European descent). We identify 266 independent loci, of which 211 are not previously reported. Gene-set analysis highlighted 42 gene sets associated with CRP levels (p ≤ 3.2 ×10-6) and tissue expression analysis indicated a strong association of CRP related genes with liver and whole blood gene expression. Phenome-wide association study identified 27 clinical outcomes associated with genetically determined CRP and subsequent Mendelian randomisation analyses supported a causal association with schizophrenia, chronic airway obstruction and prostate cancer. Our findings identified genetic loci and functional properties of chronic low-grade inflammation and provided evidence for causal associations with a range of diseases.
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Affiliation(s)
- Saredo Said
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Raha Pazoki
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Cardiovascular and Metabolic Research Group, Department of Life Sciences, Brunel University London, London, UK
- The Centre for Inflammation Research and Translational Medicine (CIRTM), Brunel University London, London, UK
- Centre for Health and Well-being Across the Life Course, Brunel University London, London, UK
| | - Ville Karhunen
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Centre for Life Course Health Research, University of Oulu, Oulu, Finland
- Research Unit of Mathematical Sciences, University of Oulu, Oulu, Finland
| | - Urmo Võsa
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Symen Ligthart
- Department of Intensive Care, University Hospital Antwerp, Antwerp, Belgium
| | - Barbara Bodinier
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Fotios Koskeridis
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece
| | - Paul Welsh
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, G12 8TA, UK
| | - Behrooz Z Alizadeh
- Department of Epidemiology, University of Groningen and University Medical Centre Groningen, Groningen, the Netherlands
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham & Women's Hospital, Boston, MA, 02115, USA
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Naveed Sattar
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, G12 8TA, UK
| | - Marc Chadeau-Hyam
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, W2 1PG, UK
| | - Evangelos Evangelou
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece
| | - Marjo-Riitta Jarvelin
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Centre for Life Course Health Research, University of Oulu, Oulu, Finland
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, W2 1PG, UK
- UK Dementia Research Institute at Imperial College London, Burlington Danes Building, Hammersmith Hospital, DuCane Road, London, W12 0NN, UK
- National Institute for Health Research Imperial Biomedical Research Centre, Imperial College London, London, W2 1PG, UK
| | - Ioanna Tzoulaki
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, W2 1PG, UK
- UK Dementia Research Institute at Imperial College London, Burlington Danes Building, Hammersmith Hospital, DuCane Road, London, W12 0NN, UK
| | - Abbas Dehghan
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, W2 1PG, UK.
- UK Dementia Research Institute at Imperial College London, Burlington Danes Building, Hammersmith Hospital, DuCane Road, London, W12 0NN, UK.
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175
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Lu C, Jin D, Palmer N, Fox K, Kohane IS, Smoller JW, Yu KH. Large-scale real-world data analysis identifies comorbidity patterns in schizophrenia. Transl Psychiatry 2022; 12:154. [PMID: 35410453 PMCID: PMC9001711 DOI: 10.1038/s41398-022-01916-y] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/27/2021] [Revised: 03/22/2022] [Accepted: 03/23/2022] [Indexed: 11/23/2022] Open
Abstract
Schizophrenia affects >3.2 million people in the USA. However, its comorbidity patterns have not been systematically characterized in real-world populations. To address this gap, we conducted an observational study using a cohort of 86 million patients in a nationwide health insurance dataset. We identified participants with schizophrenia and those without schizophrenia matched by age, sex, and the first three digits of zip code. For each phenotype encoded in phecodes, we compared their prevalence in schizophrenia patients and the matched non-schizophrenic participants, and we performed subgroup analyses stratified by age and sex. Results show that anxiety, posttraumatic stress disorder, and substance abuse commonly occur in adolescents and young adults prior to schizophrenia diagnoses. Patients aged 60 and above are at higher risks of developing delirium, alcoholism, dementia, pelvic fracture, and osteomyelitis than their matched controls. Type 2 diabetes, sleep apnea, and eating disorders were more prevalent in women prior to schizophrenia diagnosis, whereas acute renal failure, rhabdomyolysis, and developmental delays were found at higher rates in men. Anxiety and obesity are more commonly seen in patients with schizoaffective disorders compared to patients with other types of schizophrenia. Leveraging a large-scale insurance claims dataset, this study identified less-known comorbidity patterns of schizophrenia and confirmed known ones. These comorbidity profiles can guide clinicians and researchers to take heed of early signs of co-occurring diseases.
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Affiliation(s)
- Chenyue Lu
- grid.38142.3c000000041936754XDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA USA
| | - Di Jin
- grid.116068.80000 0001 2341 2786Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA USA
| | - Nathan Palmer
- grid.38142.3c000000041936754XDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA USA
| | - Kathe Fox
- grid.38142.3c000000041936754XDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA USA
| | - Isaac S. Kohane
- grid.38142.3c000000041936754XDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA USA
| | - Jordan W. Smoller
- grid.32224.350000 0004 0386 9924Department of Psychiatry, Massachusetts General Hospital, Boston, MA USA ,grid.38142.3c000000041936754XDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA USA
| | - Kun-Hsing Yu
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
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176
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Kerley CI, Chaganti S, Nguyen TQ, Bermudez C, Cutting LE, Beason-Held LL, Lasko T, Landman BA. pyPheWAS: A Phenome-Disease Association Tool for Electronic Medical Record Analysis. Neuroinformatics 2022; 20:483-505. [PMID: 34981404 PMCID: PMC9250547 DOI: 10.1007/s12021-021-09553-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/29/2021] [Indexed: 11/29/2022]
Abstract
Along with the increasing availability of electronic medical record (EMR) data, phenome-wide association studies (PheWAS) and phenome-disease association studies (PheDAS) have become a prominent, first-line method of analysis for uncovering the secrets of EMR. Despite this recent growth, there is a lack of approachable software tools for conducting these analyses on large-scale EMR cohorts. In this article, we introduce pyPheWAS, an open-source python package for conducting PheDAS and related analyses. This toolkit includes 1) data preparation, such as cohort censoring and age-matching; 2) traditional PheDAS analysis of ICD-9 and ICD-10 billing codes; 3) PheDAS analysis applied to a novel EMR phenotype mapping: current procedural terminology (CPT) codes; and 4) novelty analysis of significant disease-phenotype associations found through PheDAS. The pyPheWAS toolkit is approachable and comprehensive, encapsulating data prep through result visualization all within a simple command-line interface. The toolkit is designed for the ever-growing scale of available EMR data, with the ability to analyze cohorts of 100,000 + patients in less than 2 h. Through a case study of Down Syndrome and other intellectual developmental disabilities, we demonstrate the ability of pyPheWAS to discover both known and potentially novel disease-phenotype associations across different experiment designs and disease groups. The software and user documentation are available in open source at https://github.com/MASILab/pyPheWAS .
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Affiliation(s)
- Cailey I Kerley
- Department of Electrical Engineering, Vanderbilt University, Nashville, TN, USA.
| | - Shikha Chaganti
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Tin Q Nguyen
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
- Department of Special Education, Peabody College of Education and Human Development, Nashville, TN, USA
| | - Camilo Bermudez
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Laurie E Cutting
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
- Department of Special Education, Peabody College of Education and Human Development, Nashville, TN, USA
- Vanderbilt Kennedy Center, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA
| | - Lori L Beason-Held
- Laboratory of Behavioral Neuroscience, National Institute On Aging, NIH, Baltimore, MD, USA
| | - Thomas Lasko
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Bennett A Landman
- Department of Electrical Engineering, Vanderbilt University, Nashville, TN, USA
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Kennedy Center, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
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177
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Verma A, Tsao NL, Thomann LO, Ho YL, Iyengar SK, Luoh SW, Carr R, Crawford DC, Efird JT, Huffman JE, Hung A, Ivey KL, Levin MG, Lynch J, Natarajan P, Pyarajan S, Bick AG, Costa L, Genovese G, Hauger R, Madduri R, Pathak GA, Polimanti R, Voight B, Vujkovic M, Zekavat SM, Zhao H, Ritchie MD, VA Million Veteran Program COVID-19 Science Initiative, Chang KM, Cho K, Casas JP, Tsao PS, Gaziano JM, O’Donnell C, Damrauer SM, Liao KP. A Phenome-Wide Association Study of genes associated with COVID-19 severity reveals shared genetics with complex diseases in the Million Veteran Program. PLoS Genet 2022; 18:e1010113. [PMID: 35482673 PMCID: PMC9049369 DOI: 10.1371/journal.pgen.1010113] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Accepted: 02/20/2022] [Indexed: 12/14/2022] Open
Abstract
The study aims to determine the shared genetic architecture between COVID-19 severity with existing medical conditions using electronic health record (EHR) data. We conducted a Phenome-Wide Association Study (PheWAS) of genetic variants associated with critical illness (n = 35) or hospitalization (n = 42) due to severe COVID-19 using genome-wide association summary data from the Host Genetics Initiative. PheWAS analysis was performed using genotype-phenotype data from the Veterans Affairs Million Veteran Program (MVP). Phenotypes were defined by International Classification of Diseases (ICD) codes mapped to clinically relevant groups using published PheWAS methods. Among 658,582 Veterans, variants associated with severe COVID-19 were tested for association across 1,559 phenotypes. Variants at the ABO locus (rs495828, rs505922) associated with the largest number of phenotypes (nrs495828 = 53 and nrs505922 = 59); strongest association with venous embolism, odds ratio (ORrs495828 1.33 (p = 1.32 x 10-199), and thrombosis ORrs505922 1.33, p = 2.2 x10-265. Among 67 respiratory conditions tested, 11 had significant associations including MUC5B locus (rs35705950) with increased risk of idiopathic fibrosing alveolitis OR 2.83, p = 4.12 × 10-191; CRHR1 (rs61667602) associated with reduced risk of pulmonary fibrosis, OR 0.84, p = 2.26× 10-12. The TYK2 locus (rs11085727) associated with reduced risk for autoimmune conditions, e.g., psoriasis OR 0.88, p = 6.48 x10-23, lupus OR 0.84, p = 3.97 x 10-06. PheWAS stratified by ancestry demonstrated differences in genotype-phenotype associations. LMNA (rs581342) associated with neutropenia OR 1.29 p = 4.1 x 10-13 among Veterans of African and Hispanic ancestry but not European. Overall, we observed a shared genetic architecture between COVID-19 severity and conditions related to underlying risk factors for severe and poor COVID-19 outcomes. Differing associations between genotype-phenotype across ancestries may inform heterogenous outcomes observed with COVID-19. Divergent associations between risk for severe COVID-19 with autoimmune inflammatory conditions both respiratory and non-respiratory highlights the shared pathways and fine balance of immune host response and autoimmunity and caution required when considering treatment targets.
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Affiliation(s)
- Anurag Verma
- Corporal Michael Crescenz VA Medical Center, Philadelphia, Pennsylvania, United States of America
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Noah L. Tsao
- Corporal Michael Crescenz VA Medical Center, Philadelphia, Pennsylvania, United States of America
- Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Lauren O. Thomann
- VA Boston Healthcare System, Boston, Massachusetts, United States of America
| | - Yuk-Lam Ho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America
| | - Sudha K. Iyengar
- Louis Stokes Cleveland VA Medical Center, Cleveland, Ohio, United States of America
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Shiuh-Wen Luoh
- VA Portland Health Care System, Portland, Oregon, United States of America
- Division of Hematology and Medical Oncology, Knight Cancer Institute, Oregon Health and Science University, Portland, Oregon, United States of America
| | - Rotonya Carr
- Corporal Michael Crescenz VA Medical Center, Philadelphia, Pennsylvania, United States of America
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- University of Washington, Division of Gastroenterology, Seattle, Washington, United States of America
| | - Dana C. Crawford
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, United States of America
- Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, Ohio, United States of America
- Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Jimmy T. Efird
- Cooperative Studies Program Epidemiology Center, Health Services Research and Development, DVAHCS (Duke University Affiliate), Durham, North Carolina, United States of America
| | - Jennifer E. Huffman
- VA Boston Healthcare System, Boston, Massachusetts, United States of America
| | - Adriana Hung
- Tennessee Valley Healthcare System (Nashville VA) & Vanderbilt University, Nashville, Tennessee, United States of America
| | - Kerry L. Ivey
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America
- South Australian Health and Medical Research Institute, Infection and Immunity Theme, Adelaide, South Australia, Australia
- Harvard T.H. Chan School of Public Health, Department of Nutrition, Cambridge, Massachusetts, United States of America
| | - Michael G. Levin
- Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Julie Lynch
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, Utah, United States of America
| | - Pradeep Natarajan
- VA Boston Healthcare System, Boston, Massachusetts, United States of America
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Program in Medical and Population Genetics and the Cardiovascular Disease Initiative, Broad Institute of Harvard & MIT, Cambridge, Massachusetts, United States of America
| | - Saiju Pyarajan
- VA Boston Healthcare System, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
| | - Alexander G. Bick
- VA Boston Healthcare System, Boston, Massachusetts, United States of America
- Department of Medicine, Vanderbilt University, Nashville, Tennessee, United States of America
| | - Lauren Costa
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America
| | - Giulio Genovese
- Program in Medical and Population Genetics and the Cardiovascular Disease Initiative, Broad Institute of Harvard & MIT, Cambridge, Massachusetts, United States of America
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Richard Hauger
- Department of Psychiatry, University of California, San Diego, La Jolla, California; Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, California, United States of America
| | - Ravi Madduri
- University of Chicago Consortium for Advanced Science and Engineering, The University of Chicago, Chicago, Illinois, United States of America
- Data Science and Learning Division, Argonne National Laboratory, Lemont, Illinois, United States of America
| | - Gita A. Pathak
- VA Connecticut Healthcare System, West Haven, Connecticut, United States of America
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut, United States of America
| | - Renato Polimanti
- VA Connecticut Healthcare System, West Haven, Connecticut, United States of America
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut, United States of America
| | - Benjamin Voight
- Corporal Michael Crescenz VA Medical Center, Philadelphia, Pennsylvania, United States of America
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Marijana Vujkovic
- Corporal Michael Crescenz VA Medical Center, Philadelphia, Pennsylvania, United States of America
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Seyedeh Maryam Zekavat
- VA Boston Healthcare System, Boston, Massachusetts, United States of America
- Broad Institute of MIT & Harvard, Cambridge, Massachusetts, United States of America
- Yale School of Medicine New Haven, New Haven, Connecticut, United States of America
| | - Hongyu Zhao
- VA Connecticut Healthcare System, West Haven, Connecticut, United States of America
- Yale School of Medicine New Haven, New Haven, Connecticut, United States of America
- Computational Biology and Bioinformatics Program, Yale University, New Haven, Connecticut, United States of America
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, United States of America
| | - Marylyn D. Ritchie
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | | | - Kyong-Mi Chang
- Corporal Michael Crescenz VA Medical Center, Philadelphia, Pennsylvania, United States of America
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America
| | - Juan P. Casas
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America
- Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
| | - Philip S. Tsao
- VA Palo Alto Health Care System, Palo Alto, California, United States of America
- Department of Medicine (Cardiovascular Medicine), Stanford University School of Medicine, Stanford, California, United States of America
| | - J. Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America
- Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
| | - Christopher O’Donnell
- VA Boston Healthcare System, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
- Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
| | - Scott M. Damrauer
- Corporal Michael Crescenz VA Medical Center, Philadelphia, Pennsylvania, United States of America
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Katherine P. Liao
- VA Boston Healthcare System, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
- Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
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178
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Fu M, Chang TS. Phenome-Wide Association Study of Polygenic Risk Score for Alzheimer's Disease in Electronic Health Records. Front Aging Neurosci 2022; 14:800375. [PMID: 35370621 PMCID: PMC8965623 DOI: 10.3389/fnagi.2022.800375] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2021] [Accepted: 02/04/2022] [Indexed: 11/13/2022] Open
Abstract
Alzheimer's disease (AD) is the most common form of dementia and a growing public health burden in the United States. Significant progress has been made in identifying genetic risk for AD, but limited studies have investigated how AD genetic risk may be associated with other disease conditions in an unbiased fashion. In this study, we conducted a phenome-wide association study (PheWAS) by genetic ancestry groups within a large academic health system using the polygenic risk score (PRS) for AD. PRS was calculated using LDpred2 with genome-wide association study (GWAS) summary statistics. Phenotypes were extracted from electronic health record (EHR) diagnosis codes and mapped to more clinically meaningful phecodes. Logistic regression with Firth's bias correction was used for PRS phenotype analyses. Mendelian randomization was used to examine causality in significant PheWAS associations. Our results showed a strong association between AD PRS and AD phenotype in European ancestry (OR = 1.26, 95% CI: 1.13, 1.40). Among a total of 1,515 PheWAS tests within the European sample, we observed strong associations of AD PRS with AD and related phenotypes, which include mild cognitive impairment (MCI), memory loss, and dementias. We observed a phenome-wide significant association between AD PRS and gouty arthropathy (OR = 0.90, adjusted p = 0.05). Further causal inference tests with Mendelian randomization showed that gout was not causally associated with AD. We concluded that genetic predisposition of AD was negatively associated with gout, but gout was not a causal risk factor for AD. Our study evaluated AD PRS in a real-world EHR setting and provided evidence that AD PRS may help to identify individuals who are genetically at risk of AD and other related phenotypes. We identified non-neurodegenerative diseases associated with AD PRS, which is essential to understand the genetic architecture of AD and potential side effects of drugs targeting genetic risk factors of AD. Together, these findings expand our understanding of AD genetic and clinical risk factors, which provide a framework for continued research in aging with the growing number of real-world EHR linked with genetic data.
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Affiliation(s)
- Mingzhou Fu
- Movement Disorders Program, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
- Medical Informatics Home Area, Department of Bioinformatics, University of California, Los Angeles, Los Angeles, CA, United States
| | - Timothy S. Chang
- Movement Disorders Program, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
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179
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Schneider CV, Schneider KM, Teumer A, Rudolph KL, Hartmann D, Rader DJ, Strnad P. Association of Telomere Length With Risk of Disease and Mortality. JAMA Intern Med 2022; 182:291-300. [PMID: 35040871 PMCID: PMC8767489 DOI: 10.1001/jamainternmed.2021.7804] [Citation(s) in RCA: 106] [Impact Index Per Article: 35.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
IMPORTANCE Telomeres protect DNA from damage. Because they shorten with each mitotic cycle, leukocyte telomere length (LTL) serves as a mitotic clock. Reduced LTL has been associated with multiple human disorders. OBJECTIVE To determine the association between LTL and overall as well as disease-specific mortality and morbidity. DESIGN, SETTING, AND PARTICIPANTS This multicenter, community-based cohort study conducted from March 2006 to December 2010 included longitudinal follow-up (mean [SD], 12 [2] years) for 472 432 English participants from the United Kingdom Biobank (UK Biobank) and analyzed morbidity and mortality. The data were analyzed in 2021. MAIN OUTCOMES AND MEASURES Hazard ratios (HRs) and odds ratios for mortality and morbidity associated with a standard deviation change in LTL, adjusted for age, sex, body mass index (calculated as weight in kilograms divided by height in meters squared), and ethnicity. RESULTS This study included a total of 472 432 English participants, of whom 54% were women (mean age, 57 years). Reduced LTL was associated with increased overall (HR, 1.08; 95% CI, 1.07-1.09), cardiovascular (HR, 1.09; 95% CI, 1.06-1.12), respiratory (HR, 1.40; 95% CI, 1.34-1.45), digestive (HR, 1.26; 95% CI, 1.19-1.33), musculoskeletal (HR, 1.51; 95% CI, 1.35-1.92), and COVID-19 (HR, 1.15; 95% CI, 1.07-1.23) mortality, but not cancer-related mortality. A total of 214 disorders were significantly overrepresented and 37 underrepresented in participants with shorter LTL. Respiratory (11%), digestive/liver-related (14%), circulatory (18%), and musculoskeletal conditions (6%), together with infections (5%), accounted for most positive associations, whereas (benign) neoplasms and endocrinologic/metabolic disorders were the most underrepresented entities. Malignant tumors, esophageal cancer, and lymphoid and myeloid leukemia were significantly more common in participants with shorter LTL, whereas brain cancer and melanoma were less prevalent. While smoking and alcohol consumption were associated with shorter LTL, additional adjustment for both factors, as well as cognitive function/major comorbid conditions, did not significantly alter the results. CONCLUSIONS AND RELEVANCE This cohort study found that shorter LTL was associated with a small risk increase of overall mortality, but a higher risk of mortality was associated with specific organs and diseases.
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Affiliation(s)
- Carolin V Schneider
- The Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Kai Markus Schneider
- Perelman School of Medicine, Department of Microbiology, University of Pennsylvania, Philadelphia
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany.,German Centre for Cardiovascular Research (DZHK), partner site Greifswald, Greifswald, Germany.,Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Bialystok, Poland
| | | | - Daniel Hartmann
- Department of Surgery, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Daniel J Rader
- The Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Pavel Strnad
- Medical Clinic III, Gastroenterology, Metabolic diseases and Intensive Care, University Hospital RWTH Aachen, Aachen, Germany
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180
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Yengo-Kahn AM, Hibshman N, Bonfield CM, Torstenson ES, Gifford KA, Belikau D, Davis LK, Zuckerman SL, Dennis JK. Association of Preinjury Medical Diagnoses With Pediatric Persistent Postconcussion Symptoms in Electronic Health Records. J Head Trauma Rehabil 2022; 37:E80-E89. [PMID: 33935230 DOI: 10.1097/htr.0000000000000686] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
OBJECTIVE To identify risk factors and generate hypotheses for pediatric persistent postconcussion symptoms (PPCS). SETTING A regional healthcare system in the Southeastern United States. PARTICIPANTS An electronic health record-based algorithm was developed and validated to identify PPCS cases and controls from an institutional database of more than 2.8 million patients. PPCS cases (n = 274) were patients aged 5 to 18 years with PPCS-related diagnostic codes or with PPCS key words identified by natural language processing of clinical notes. Age, sex, and year of index event-matched controls (n = 1096) were patients with mild traumatic brain injury codes only. Patients with moderate or severe traumatic brain injury were excluded. All patients used our healthcare system at least 3 times 180 days before their injury. DESIGN Case-control study. MAIN MEASURES The outcome was algorithmic classification of PPCS. Exposures were all preinjury medical diagnoses assigned at least 180 days before the injury. RESULTS Cases and controls both had a mean of more than 9 years of healthcare system use preinjury. Of 221 preinjury medical diagnoses, headache disorder was associated with PPCS after accounting for multiple testing (odds ratio [OR] = 2.9; 95% confidence interval [CI]: 1.6-5.0; P = 2.1e-4). Six diagnoses were associated with PPCS at a suggestive threshold for statistical significance (false discovery rate P < .10): gastritis/duodenitis (OR = 2.8; 95% CI: 1.6-5.1; P = 5.0e-4), sleep disorders (OR = 2.3; 95% CI: 1.4-3.7; P = 7.4e-4), abdominal pain (OR = 1.6; 95% CI: 1.2-2.2; P = 9.2e-4), chronic sinusitis (OR = 2.8; 95% CI: 1.5-5.2; P = 1.3e-3), congenital anomalies of the skin (OR = 2.9; 95% CI: 1.5-5.5; P = 1.9e-3), and chronic pharyngitis/nasopharyngitis (OR = 2.4; 95% CI: 1.4-4.3; P = 2.5e-3). CONCLUSIONS These results support the strong association of preinjury headache disorders with PPCS. An association of PPCS with prior gastritis/duodenitis, sinusitis, and pharyngitis/nasopharyngitis suggests a role for chronic inflammation in PPCS pathophysiology and risk, although results could equally be attributable to a higher likelihood of somatization among PPCS cases. Identified risk factors should be investigated further and potentially considered during the management of pediatric mild traumatic brain injury cases.
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Affiliation(s)
- Aaron M Yengo-Kahn
- Department of Neurological Surgery (Drs Yengo-Kahn, Bonfield, and Zuckerman), Vanderbilt Sport Concussion Center (Drs Yengo-Kahn, Bonfield, Gifford, Zuckerman, and Dennis and Ms Hibshman), Division of Epidemiology, Department of Medicine (Mr Torstenson), Vanderbilt Epidemiology Center, Institute for Medicine and Public Health (Mr Torstenson), Vanderbilt Genetics Institute (Mr Torstenson and Drs Davis and Dennis), Department of Neurology (Dr Gifford), and Division of Genetic Medicine, Department of Medicine (Drs Davis and Dennis), Vanderbilt University Medical Center, Nashville, Tennessee; Vanderbilt University School of Medicine, Nashville, Tennessee (Ms Hibshman); British Columbia Children's Hospital Research Institute, Vancouver, British Columbia, Canada (Ms Belikau and Dr Dennis); and Department of Medical Genetics, The University of British Columbia, Vancouver, British Columbia, Canada (Dr Dennis)
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181
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Zanussi JT, Zhao J, Dorn CA, Liu G, Feng Q, Wei W, Mosley JD, Stein CM, Kawai VK. Identifying Potential Therapeutic Applications and Diagnostic Harms of Increased Bilirubin Concentrations: A Clinical and Genetic Approach. Clin Pharmacol Ther 2022; 111:435-443. [PMID: 34625956 PMCID: PMC8748314 DOI: 10.1002/cpt.2441] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Accepted: 09/16/2021] [Indexed: 02/03/2023]
Abstract
Bilirubin has antioxidant and anti-inflammatory properties in vitro and in animal studies and protects against inflammatory, cardiovascular, and other diseases in observational studies; therefore, bilirubin has potential as a therapeutic agent. However, observational studies could be confounded by many factors. We used a genetic (n = 61,281) and clinical (n = 234,670) approach to define the association between bilirubin and 19 conditions with a putative protective signal in observational studies. We also tested if individuals with genetically higher bilirubin levels underwent more diagnostic tests. We used a common variant in UGT1A1 (rs6742078) associated with an 26% increase in bilirubin levels in the genetic studies. Carriers of the variant had higher bilirubin levels (P = 2.2 × 10-16 ) but there was no significant association with any of the 19 conditions. In a phenome-wide association study (pheWAS) to seek undiscovered genetic associations, the only significant finding was increased risk of "jaundice-not of newborn." Carriers of the variant allele were more likely to undergo an abdominal ultrasound (odds ratio = 1.04, [1.00-1.08], P = 0.03). In contrast, clinically measured bilirubin levels were significantly associated with 15 of the 19 conditions (P < 0.003) and with 431 clinical diagnoses in the pheWAS (P < 1 × 10-5 adjusted for sex, age, and follow-up). With additional adjustment for smoking and body mass index, 7 of 19 conditions and 260 pheWAS diagnoses remained significantly associated with bilirubin levels. In conclusion, bilirubin does not protect against inflammatory or other diseases using a genetic approach; the many putative beneficial associations reported clinically are likely due to confounding.
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Affiliation(s)
- Jacy T. Zanussi
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Juan Zhao
- Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Chad A. Dorn
- Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Ge Liu
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - QiPing Feng
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - WeiQi Wei
- Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Jonathan D. Mosley
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - C. Michael Stein
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Vivian K. Kawai
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
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182
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Yuan S, Yu L, Gou W, Wang L, Sun J, Li D, Lu Y, Cai X, Yu H, Yuan C, Zheng JS, Larsson SC, Theodoratou E, Li X. Health effects of high serum calcium levels: Updated phenome-wide Mendelian randomisation investigation and review of Mendelian randomisation studies. EBioMedicine 2022; 76:103865. [PMID: 35134646 PMCID: PMC8844774 DOI: 10.1016/j.ebiom.2022.103865] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Revised: 01/18/2022] [Accepted: 01/19/2022] [Indexed: 02/08/2023] Open
Abstract
Background Calcium plays a role in a wide range of biological functions. Here we conducted a phenome-wide Mendelian randomisation (MR-PheWAS) analysis and a systematic review for MR studies to comprehensively investigate the health effects of serum calcium. Methods One-hundred and thirty genetic variants strongly associated with serum calcium levels were used as instrumental variables. A phenome-wide association analysis (PheWAS) was conducted to examine the associations of genetically predicted serum calcium with 1473 distinct phenotypes in the UK Biobank including 339,197 individuals. Observed associations in PheWAS were further tested for replication in two-sample MR replication analysis. A systematic review for MR studies on serum calcium was performed to synthesize the published evidence and compare with the current MR-PheWAS findings. Findings Higher genetically predicted calcium levels were associated with decreased risk of 5 diseases in dermatologic and musculoskeletal systems and increased risk of 17 diseases in circulatory, digestive, endocrine, genitourinary and immune systems. Eight associations were replicated in two-sample MR analysis. These included decreased risk of osteoarthritis and increased risk of coronary artery disease, myocardial infarction, coronary atherosclerosis, hyperparathyroidism, disorder of parathyroid gland, gout, and calculus of kidney and ureter with increased serum calcium. Systematic review of 25 MR studies provided supporting evidence on five out of the eight disease outcomes, while the increased risk of gout, hyperparathyroidism and disorder of parathyroid gland were novel findings. Interpretation This study found wide-ranged health effects of high serum calcium, which suggests that the benefits and adversities of strategies promoting calcium intake should be assessed. Funding ET is supported by a CRUK Career Development Fellowship (C31250/A22804). XL is supported by the Natural Science Fund for Distinguished Young Scholars of Zhejiang Province. SCL acknowledges research funding from the Swedish Heart Lung Foundation (Hjärt-Lungfonden, 20210351), the Swedish Research Council (Vetenskapsrådet, 2019-00977), and the Swedish Cancer Society (Cancerfonden).
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Affiliation(s)
- Shuai Yuan
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
| | - Lili Yu
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Wanglong Gou
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
| | - Lijuan Wang
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jing Sun
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Doudou Li
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Ying Lu
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaxia Cai
- Department of Nutrition and Food Hygiene, Beijing Key Laboratory of Environmental Toxicology, School of Public Health, Capital Medical University, Beijing, China
| | - Huanling Yu
- Department of Nutrition and Food Hygiene, Beijing Key Laboratory of Environmental Toxicology, School of Public Health, Capital Medical University, Beijing, China
| | - Changzheng Yuan
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, USA
| | - Ju-Sheng Zheng
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
| | - 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
| | - Evropi Theodoratou
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK; Cancer Research UK Edinburgh Centre, Medical Research Council Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Xue Li
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK.
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183
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Taub MA, Conomos MP, Keener R, Iyer KR, Weinstock JS, Yanek LR, Lane J, Miller-Fleming TW, Brody JA, Raffield LM, McHugh CP, Jain D, Gogarten SM, Laurie CA, Keramati A, Arvanitis M, Smith AV, Heavner B, Barwick L, Becker LC, Bis JC, Blangero J, Bleecker ER, Burchard EG, Celedón JC, Chang YPC, Custer B, Darbar D, de las Fuentes L, DeMeo DL, Freedman BI, Garrett ME, Gladwin MT, Heckbert SR, Hidalgo BA, Irvin MR, Islam T, Johnson WC, Kaab S, Launer L, Lee J, Liu S, Moscati A, North KE, Peyser PA, Rafaels N, Seidman C, Weeks DE, Wen F, Wheeler MM, Williams LK, Yang IV, Zhao W, Aslibekyan S, Auer PL, Bowden DW, Cade BE, Chen Z, Cho MH, Cupples LA, Curran JE, Daya M, Deka R, Eng C, Fingerlin TE, Guo X, Hou L, Hwang SJ, Johnsen JM, Kenny EE, Levin AM, Liu C, Minster RL, Naseri T, Nouraie M, Reupena MS, Sabino EC, Smith JA, Smith NL, Lasky-Su J, Taylor JG, Telen MJ, Tiwari HK, Tracy RP, White MJ, Zhang Y, Wiggins KL, Weiss ST, Vasan RS, Taylor KD, Sinner MF, Silverman EK, Shoemaker MB, Sheu WHH, Sciurba F, Schwartz DA, Rotter JI, Roden D, Redline S, Raby BA, et alTaub MA, Conomos MP, Keener R, Iyer KR, Weinstock JS, Yanek LR, Lane J, Miller-Fleming TW, Brody JA, Raffield LM, McHugh CP, Jain D, Gogarten SM, Laurie CA, Keramati A, Arvanitis M, Smith AV, Heavner B, Barwick L, Becker LC, Bis JC, Blangero J, Bleecker ER, Burchard EG, Celedón JC, Chang YPC, Custer B, Darbar D, de las Fuentes L, DeMeo DL, Freedman BI, Garrett ME, Gladwin MT, Heckbert SR, Hidalgo BA, Irvin MR, Islam T, Johnson WC, Kaab S, Launer L, Lee J, Liu S, Moscati A, North KE, Peyser PA, Rafaels N, Seidman C, Weeks DE, Wen F, Wheeler MM, Williams LK, Yang IV, Zhao W, Aslibekyan S, Auer PL, Bowden DW, Cade BE, Chen Z, Cho MH, Cupples LA, Curran JE, Daya M, Deka R, Eng C, Fingerlin TE, Guo X, Hou L, Hwang SJ, Johnsen JM, Kenny EE, Levin AM, Liu C, Minster RL, Naseri T, Nouraie M, Reupena MS, Sabino EC, Smith JA, Smith NL, Lasky-Su J, Taylor JG, Telen MJ, Tiwari HK, Tracy RP, White MJ, Zhang Y, Wiggins KL, Weiss ST, Vasan RS, Taylor KD, Sinner MF, Silverman EK, Shoemaker MB, Sheu WHH, Sciurba F, Schwartz DA, Rotter JI, Roden D, Redline S, Raby BA, Psaty BM, Peralta JM, Palmer ND, Nekhai S, Montgomery CG, Mitchell BD, Meyers DA, McGarvey ST, Fernando D. Martinez on behalf of the NHLBI CARE Network, Mak AC, Loos RJ, Kumar R, Kooperberg C, Konkle BA, Kelly S, Kardia SL, Kaplan R, He J, Gui H, Gilliland FD, Gelb BD, Fornage M, Ellinor PT, de Andrade M, Correa A, Chen YDI, Boerwinkle E, Barnes KC, Ashley-Koch AE, Arnett DK, Albert C, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Hematology and Hemostasis Working Group, TOPMed Structural Variation Working Group, Laurie CC, Abecasis G, Nickerson DA, Wilson JG, Rich SS, Levy D, Ruczinski I, Aviv A, Blackwell TW, Thornton T, O’Connell J, Cox NJ, Perry JA, Armanios M, Battle A, Pankratz N, Reiner AP, Mathias RA. Genetic determinants of telomere length from 109,122 ancestrally diverse whole-genome sequences in TOPMed. CELL GENOMICS 2022; 2:S2666-979X(21)00105-1. [PMID: 35530816 PMCID: PMC9075703 DOI: 10.1016/j.xgen.2021.100084] [Show More Authors] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Revised: 09/03/2021] [Accepted: 12/10/2021] [Indexed: 01/16/2023]
Abstract
Genetic studies on telomere length are important for understanding age-related diseases. Prior GWAS for leukocyte TL have been limited to European and Asian populations. Here, we report the first sequencing-based association study for TL across ancestrally-diverse individuals (European, African, Asian and Hispanic/Latino) from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. We used whole genome sequencing (WGS) of whole blood for variant genotype calling and the bioinformatic estimation of telomere length in n=109,122 individuals. We identified 59 sentinel variants (p-value <5×10-9) in 36 loci associated with telomere length, including 20 newly associated loci (13 were replicated in external datasets). There was little evidence of effect size heterogeneity across populations. Fine-mapping at OBFC1 indicated the independent signals colocalized with cell-type specific eQTLs for OBFC1 (STN1). Using a multi-variant gene-based approach, we identified two genes newly implicated in telomere length, DCLRE1B (SNM1B) and PARN. In PheWAS, we demonstrated our TL polygenic trait scores (PTS) were associated with increased risk of cancer-related phenotypes.
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Affiliation(s)
- Margaret A. Taub
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Matthew P. Conomos
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA
| | - Rebecca Keener
- Department of Biomedical Engineering, Johns Hopkins Whiting School of Engineering, Baltimore, MD, USA
| | - Kruthika R. Iyer
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Joshua S. Weinstock
- 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
| | - Lisa R. Yanek
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - John Lane
- Department of Laboratory Medicine & Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Tyne W. Miller-Fleming
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jennifer A. Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Laura M. Raffield
- Department of Genetics, University of North Carolina, Chapel Hill, Chapel Hill, NC, USA
| | - Caitlin P. McHugh
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA
| | - Deepti Jain
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA
| | - Stephanie M. Gogarten
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA
| | - Cecelia A. Laurie
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA
| | - Ali Keramati
- Department of Cardiology, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Marios Arvanitis
- Department of Medicine, Division of Cardiology, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Albert V. Smith
- 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
| | - Benjamin Heavner
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA
| | - Lucas Barwick
- LTRC Data Coordinating Center, The Emmes Company, LLC, Rockville, MD, USA
| | - Lewis C. Becker
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Joshua C. Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Eugene R. Bleecker
- Department of Medicine, Division of Genetics, Genomics, and Precision Medicine, University of Arizona, Tucson, AZ, USA
- Division of Pharmacogenomics, University of Arizona, Tucson, AZ, USA
| | - Esteban G. Burchard
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA
| | - Juan C. Celedón
- Division of Pediatric Pulmonary Medicine, UPMC Children’s Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, PA, USA
| | - Yen Pei C. Chang
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Brian Custer
- Vitalant Research Institute, San Francisco, CA, USA
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Dawood Darbar
- Division of Cardiology, University of Illinois at Chicago, Chicago, IL, USA
| | - Lisa de las Fuentes
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Dawn L. DeMeo
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Barry I. Freedman
- Department of Internal Medicine, Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Melanie E. Garrett
- Department of Medicine and Duke Comprehensive Sickle Cell Center, Duke University Medical Center, Durham, NC, USA
- Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC, USA
| | - Mark T. Gladwin
- Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Susan R. Heckbert
- Cardiovascular Health Research Unit and Department of Epidemiology, University of Washington, Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Bertha A. Hidalgo
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Marguerite R. Irvin
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Talat Islam
- Division of Environmental Health, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
| | - W. Craig Johnson
- Department of Biostatistics, Collaborative Health Studies Coordinating Center, University of Washington, Seattle, WA, USA
| | - Stefan Kaab
- Department of Medicine I, University Hospital Munich, Ludwig-Maximilian’s University, Munich, Germany
- German Centre for Cardiovascular Research (DZHK), partner site Munich Heart Alliance, Munich, Germany
| | - Lenore Launer
- Laboratory of Epidemiology and Population Science, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Jiwon Lee
- Department of Medicine, Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
| | - Simin Liu
- Department of Epidemiology and Brown Center for Global Cardiometabolic Health, Brown University, Providence, RI, USA
| | - Arden Moscati
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kari E. North
- Department of Epidemiology, University of North Carolina, Chapel Hill, Chapel Hill, NC, USA
| | - Patricia A. Peyser
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Nicholas Rafaels
- Department of Medicine, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO, USA
| | | | - Daniel E. Weeks
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Fayun Wen
- Center for Sickle Cell Disease and Department of Medicine, College of Medicine, Howard University, Washington, DC 20059, USA
| | - Marsha M. Wheeler
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - L. Keoki Williams
- Center for Individualized and Genomic Medicine Research (CIGMA), Department of Internal Medicine, Henry Ford Health System, Detroit, MI, USA
| | - Ivana V. Yang
- Department of Medicine, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO, USA
| | - Wei Zhao
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Stella Aslibekyan
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Paul L. Auer
- Zilber School of Public Health, University of Wisconsin, Milwaukee, Milwaukee, WI, USA
| | - Donald W. Bowden
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Brian E. Cade
- Harvard Medical School, Boston, MA, USA
- Division of Sleep Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Zhanghua Chen
- Division of Environmental Health, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
| | - Michael H. Cho
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - L. Adrienne Cupples
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- The National Heart, Lung, and Blood Institute, Boston University’s Framingham Heart Study, Framingham, MA, USA
| | - Joanne E. Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Michelle Daya
- Department of Medicine, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO, USA
| | - Ranjan Deka
- Department of Environmental and Public Health Sciences, University of Cincinnati, Cincinnati, OH, USA
| | - Celeste Eng
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Tasha E. Fingerlin
- Center for Genes, Environment, and Health, National Jewish Health, Denver, CO, USA
- Department of Biostatistics and Informatics, University of Colorado, Denver, Aurora, CO, 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
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - Shih-Jen Hwang
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jill M. Johnsen
- Bloodworks Northwest Research Institute, Seattle, WA, USA
- University of Washington, Department of Medicine, Seattle, WA, USA
| | - Eimear E. Kenny
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Albert M. Levin
- Department of Public Health Sciences, Henry Ford Health System, Detroit, MI, USA
| | - Chunyu Liu
- The National Heart, Lung, and Blood Institute, Boston University’s Framingham Heart Study, Framingham, MA, USA
- The Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, MD, USA
| | - Ryan L. Minster
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Take Naseri
- Ministry of Health, Government of Samoa, Apia, Samoa
- Department of Epidemiology & International Health Institute, School of Public Health, Brown University, Providence, RI, USA
| | - Mehdi Nouraie
- Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | | | - Ester C. Sabino
- Instituto de Medicina Tropical da Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Jennifer A. Smith
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Nicholas L. Smith
- Cardiovascular Health Research Unit and Department of Epidemiology, University of Washington, Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Jessica Lasky-Su
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - James G. Taylor
- Center for Sickle Cell Disease and Department of Medicine, College of Medicine, Howard University, Washington, DC 20059, USA
| | - Marilyn J. Telen
- Department of Medicine and Duke Comprehensive Sickle Cell Center, Duke University Medical Center, Durham, NC, USA
- Duke Comprehensive Sickle Cell Center, Duke University Medical Center, Durham, NC, USA
| | - Hemant K. Tiwari
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Russell P. Tracy
- Departments of Pathology & Laboratory Medicine and Biochemistry, Larrner College of Medicine, University of Vermont, Colchester, VT, USA
| | - Marquitta J. White
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Yingze Zhang
- Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Kerri L. Wiggins
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Scott T. Weiss
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Ramachandran S. Vasan
- The National Heart, Lung, and Blood Institute, Boston University’s Framingham Heart Study, Framingham, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
| | - Kent D. Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Moritz F. Sinner
- Department of Medicine I, University Hospital Munich, Ludwig-Maximilian’s University, Munich, Germany
- German Centre for Cardiovascular Research (DZHK), partner site Munich Heart Alliance, Munich, Germany
| | - Edwin K. Silverman
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - M. Benjamin Shoemaker
- Departments of Medicine, Pharmacology, and Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Wayne H.-H. Sheu
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Frank Sciurba
- Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - David A. Schwartz
- Department of Medicine, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO, USA
| | - Jerome I. Rotter
- Institute for Translational Genomics and Population Sciences, Departments of Pediatrics and Medicine, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Daniel Roden
- Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Susan Redline
- Division of Sleep Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Benjamin A. Raby
- Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Pulmonary Medicine, Boston Children’s Hospital, Boston, MA, USA
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services, University of Washington, Seattle, WA, USA
| | - Juan M. Peralta
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Nicholette D. Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Sergei Nekhai
- Center for Sickle Cell Disease and Department of Medicine, College of Medicine, Howard University, Washington, DC 20059, USA
| | - Courtney G. Montgomery
- Genes and Human Disease Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA
| | - Braxton D. Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore, MD, USA
| | - Deborah A. Meyers
- Department of Medicine, Division of Genetics, Genomics, and Precision Medicine, University of Arizona, Tucson, AZ, USA
- Division of Pharmacogenomics, University of Arizona, Tucson, AZ, USA
| | - Stephen T. McGarvey
- Department of Epidemiology & International Health Institute, School of Public Health, Brown University, Providence, RI, USA
| | | | - Angel C.Y. Mak
- Department of Medicine, University of California, San Francisco, San Francisco, CA, 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
| | - Rajesh Kumar
- Division of Allergy and Clinical Immunology, The Ann and Robert H. Lurie Children’s Hospital of Chicago, and Department of Pediatrics, Northwestern University, Chicago, IL, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Barbara A. Konkle
- Bloodworks Northwest Research Institute, Seattle, WA, USA
- University of Washington, Department of Medicine, Seattle, WA, USA
| | - Shannon Kelly
- Vitalant Research Institute, San Francisco, CA, USA
- UCSF Benioff Children’s Hospital, Oakland, CA, USA
| | - Sharon L.R. Kardia
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Robert Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Jiang He
- Department of Medicine, Tulane University School of Medicine, New Orleans, LA, USA
| | - Hongsheng Gui
- Center for Individualized and Genomic Medicine Research (CIGMA), Department of Internal Medicine, Henry Ford Health System, Detroit, MI, USA
| | - Frank D. Gilliland
- Division of Environmental Health, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
| | - Bruce D. Gelb
- Mindich Child Health and Development Institute, Departments of Pediatrics and Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Patrick T. Ellinor
- Cardiology Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Mariza de Andrade
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, USA
| | - Adolfo Correa
- Jackson Heart Study and Departments of Medicine and Population Health Science, Jackson, MS, USA
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Kathleen C. Barnes
- Department of Medicine, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO, USA
| | - Allison E. Ashley-Koch
- Department of Medicine and Duke Comprehensive Sickle Cell Center, Duke University Medical Center, Durham, NC, USA
- Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC, USA
| | - Donna K. Arnett
- College of Public Health, University of Kentucky, Lexington, KY, USA
| | - Christine Albert
- Harvard Medical School, Boston, MA, USA
- Division of Cardiovascular Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | | | | | | | - Cathy C. Laurie
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA
| | - Goncalo Abecasis
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | | | - James G. Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MI, USA
| | - Stephen S. Rich
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - Daniel Levy
- The National Heart, Lung, and Blood Institute, Boston University’s Framingham Heart Study, Framingham, MA, USA
- The Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, MD, USA
| | - Ingo Ruczinski
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Abraham Aviv
- Center of Human Development and Aging, Rutgers New Jersey Medical School, Newark, NJ, USA
| | - Thomas W. Blackwell
- 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
| | - Timothy Thornton
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Jeff O’Connell
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Nancy J. Cox
- Vanderbilt Genetics Institute and Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - James A. Perry
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Mary Armanios
- Department of Oncology, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Alexis Battle
- Department of Biomedical Engineering, Johns Hopkins Whiting School of Engineering, Baltimore, MD, USA
- Departments of Computer Science and Genetic Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Nathan Pankratz
- Department of Laboratory Medicine & Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Alexander P. Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Rasika A. Mathias
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
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184
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Associations between genetic loci, environment factors and mental disorders: a genome-wide survival analysis using the UK Biobank data. Transl Psychiatry 2022; 12:17. [PMID: 35017462 PMCID: PMC8752606 DOI: 10.1038/s41398-022-01782-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 12/10/2021] [Accepted: 12/22/2021] [Indexed: 11/08/2022] Open
Abstract
It is well-accepted that both environment and genetic factors contribute to the development of mental disorders (MD). However, few genetic studies used time-to-event data analysis to identify the susceptibility genetic variants associated with MD and explore the role of environment factors in these associations. In order to detect novel genetic loci associated with MD based on the time-to-event data and identify the role of environmental factors in them, this study recruited 376,806 participants from the UK Biobank cohort. The MD outcomes (including overall MD status, anxiety, depression and substance use disorders (SUD)) were defined based on in-patient hospital, self-reported and death registry data collected in the UK Biobank. SPACOX approach was used to identify the susceptibility loci for MD using the time-to-event data of the UK Biobank cohort. And then we estimated the associations between identified candidate loci, fourteen environment factors and MD through a phenome-wide association study and mediation analysis. SPACOX identified multiple candidate loci for overall MD status, depression and SUD, such as rs139813674 (P value = 8.39 × 10-9, ZNF684) for overall MD status, rs7231178 (DCC, P value = 2.11 × 10-9) for depression, and rs10228494 (FOXP2, P value = 6.58 × 10-10) for SUD. Multiple environment factors could influence the associations between identified loci and MD, such as confide in others and felt hated. Our study identified novel candidate loci for MD, highlighting the strength of time-to-event data based genetic association studies. We also observed that multiple environment factors could influence the association between susceptibility loci and MD.
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185
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Privé F, Aschard H, Carmi S, Folkersen L, Hoggart C, O'Reilly PF, Vilhjálmsson BJ. Portability of 245 polygenic scores when derived from the UK Biobank and applied to 9 ancestry groups from the same cohort. Am J Hum Genet 2022; 109:12-23. [PMID: 34995502 PMCID: PMC8764121 DOI: 10.1016/j.ajhg.2021.11.008] [Citation(s) in RCA: 166] [Impact Index Per Article: 55.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Accepted: 11/04/2021] [Indexed: 12/25/2022] Open
Abstract
The low portability of polygenic scores (PGSs) across global populations is a major concern that must be addressed before PGSs can be used for everyone in the clinic. Indeed, prediction accuracy has been shown to decay as a function of the genetic distance between the training and test cohorts. However, such cohorts differ not only in their genetic distance but also in their geographical distance and their data collection and assaying, conflating multiple factors. In this study, we examine the extent to which PGSs are transferable between ancestries by deriving polygenic scores for 245 curated traits from the UK Biobank data and applying them in nine ancestry groups from the same cohort. By restricting both training and testing to the UK Biobank data, we reduce the risk of environmental and genotyping confounding from using different cohorts. We define the nine ancestry groups at a sub-continental level, based on a simple, robust, and effective method that we introduce here. We then apply two different predictive methods to derive polygenic scores for all 245 phenotypes and show a systematic and dramatic reduction in portability of PGSs trained using Northwestern European individuals and applied to nine ancestry groups. These analyses demonstrate that prediction already drops off within European ancestries and reduces globally in proportion to genetic distance. Altogether, our study provides unique and robust insights into the PGS portability problem.
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Affiliation(s)
- Florian Privé
- National Centre for Register-Based Research, Aarhus University, Aarhus 8210, Denmark.
| | - Hugues Aschard
- Department of Computational Biology, Institut Pasteur, Paris 75015, France; Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Shai Carmi
- Braun School of Public Health and Community Medicine, The Hebrew University of Jerusalem, Jerusalem 9112102, Israel
| | | | - Clive Hoggart
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Paul F O'Reilly
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Bjarni J Vilhjálmsson
- National Centre for Register-Based Research, Aarhus University, Aarhus 8210, Denmark; Bioinformatics Research Centre, Aarhus University, Aarhus 8000, Denmark
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186
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Maturation and application of phenome-wide association studies. Trends Genet 2022; 38:353-363. [PMID: 34991903 DOI: 10.1016/j.tig.2021.12.002] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2021] [Revised: 11/12/2021] [Accepted: 12/02/2021] [Indexed: 12/12/2022]
Abstract
In the past 10 years since its introduction, phenome-wide association studies (PheWAS) have uncovered novel genotype-phenotype relationships. Along the way, PheWAS have evolved in many aspects as a study design with the expanded availability of large data repositories with genome-wide data linked to detailed phenotypic data. Advancement in methods, including algorithms, software, and publicly available integrated resources, makes it feasible to more fully realize the potential of PheWAS, overcoming the previous computational and analytical limitations. We review here the most recent improvements and notable applications of PheWAS since the second half of the decade from its inception. We also note the challenges that remain embedded along the entire PheWAS analytical pipeline that necessitate further development of tools and resources to further advance the understanding of the complex genetic architecture underlying human diseases and traits.
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187
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Schlauch KA, Read RW, Koning SM, Neveux I, Grzymski JJ. Using phenome-wide association studies and the SF-12 quality of life metric to identify profound consequences of adverse childhood experiences on adult mental and physical health in a Northern Nevadan population. Front Psychiatry 2022; 13:984366. [PMID: 36276335 PMCID: PMC9583677 DOI: 10.3389/fpsyt.2022.984366] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 09/15/2022] [Indexed: 11/13/2022] Open
Abstract
In this research, we examine and identify the implications of Adverse Childhood Experiences (ACEs) on a range of health outcomes, with particular focus on a number of mental health disorders. Many previous studies observed that traumatic childhood events are linked to long-term adult diseases using the standard Adverse Childhood Experience Questionnaire. The study cohort was derived from the Healthy Nevada Project, a volunteer-based population health study in which each adult participant is invited to take a retrospective questionnaire that includes the Adverse Childhood Experience Questionnaire, the 12-item Short Form Survey measuring quality of life, and self-reported incidence of nine mental disorders. Using participant's cross-referenced electronic health records, a phenome-wide association analysis of 1,703 phenotypes and the incidence of ACEs examined links between traumatic events in childhood and adult disease. These analyses showed that many mental disorders were significantly associated with ACEs in a dose-response manner. Similarly, a dose response between ACEs and obesity, chronic pain, migraine, and other physical phenotypes was identified. An examination of the prevalence of self-reported mental disorders and incidence of ACEs showed a positive relationship. Furthermore, participants with less adverse childhood events experienced a higher quality of life, both physically and mentally. The whole-phenotype approach confirms that ACEs are linked with many negative adult physical and mental health outcomes. With the nationwide prevalence of ACEs as high as 67%, these findings suggest a need for new public health resources: ACE-specific interventions and early childhood screenings.
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Affiliation(s)
- Karen A Schlauch
- Center for Genomic Medicine, Desert Research Institute, Reno, NV, United States
| | - Robert W Read
- Center for Genomic Medicine, Desert Research Institute, Reno, NV, United States
| | | | - Iva Neveux
- Center for Genomic Medicine, Desert Research Institute, Reno, NV, United States
| | - Joseph J Grzymski
- Center for Genomic Medicine, Desert Research Institute, Reno, NV, United States.,Renown Health, Reno, NV, United States
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188
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Shuey MM, Xiang RR, Moss ME, Carvajal BV, Wang Y, Camarda N, Fabbri D, Rahman P, Ramsey J, Stepanian A, Sebastiani P, Wells QS, Beckman JA, Jaffe IZ. Systems Approach to Integrating Preclinical Apolipoprotein E-Knockout Investigations Reveals Novel Etiologic Pathways and Master Atherosclerosis Network in Humans. Arterioscler Thromb Vasc Biol 2022; 42:35-48. [PMID: 34758633 PMCID: PMC8887835 DOI: 10.1161/atvbaha.121.317071] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
OBJECTIVE Animal models of atherosclerosis are used extensively to interrogate molecular mechanisms in serial fashion. We tested whether a novel systems biology approach to integration of preclinical data identifies novel pathways and regulators in human disease. Approach and Results: Of 716 articles published in ATVB from 1995 to 2019 using the apolipoprotein E knockout mouse to study atherosclerosis, data were extracted from 360 unique studies in which a gene was experimentally perturbed to impact plaque size or composition and analyzed using Ingenuity Pathway Analysis software. TREM1 (triggering receptor expressed on myeloid cells) signaling and LXR/RXR (liver X receptor/retinoid X receptor) activation were identified as the top atherosclerosis-associated pathways in mice (both P<1.93×10-4, TREM1 implicated early and LXR/RXR in late atherogenesis). The top upstream regulatory network in mice (sc-58125, a COX2 inhibitor) linked 64.0% of the genes into a single network. The pathways and networks identified in mice were interrogated by testing for associations between the genetically predicted gene expression of each mouse pathway-identified human homolog with clinical atherosclerosis in a cohort of 88 660 human subjects. Homologous human pathways and networks were significantly enriched for gene-atherosclerosis associations (empirical P<0.01 for TREM1 and LXR/RXR pathways and COX2 network). This included 12(60.0%) TREM1 pathway genes, 15(53.6%) LXR/RXR pathway genes, and 67(49.3%) COX2 network genes. Mouse analyses predicted, and human study validated, the strong association of COX2 expression (PTGS2) with increased likelihood of atherosclerosis (odds ratio, 1.68 per SD of genetically predicted gene expression; P=1.07×10-6). CONCLUSIONS PRESCIANT (Preclinical Science Integration and Translation) leverages published preclinical investigations to identify high-confidence pathways, networks, and regulators of human disease.
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Affiliation(s)
| | | | - M. Elizabeth Moss
- Department of Medicine (M.M.S., J.R., Q.S.W., J.A.B.) and Department of Biomedical Informatics (D.F., P.R.), Vanderbilt University Medical Center, Nashville, TN. Molecular Cardiology Research Institute (R.R.X., M.E.M., B.V.C., Y.W., N.C., A.S., I.Z.J.) and Institute for Clinical Research and Health Policy Studies (P.S.), Tufts Medical Center, Boston, MA
| | - Brigett V. Carvajal
- Department of Medicine (M.M.S., J.R., Q.S.W., J.A.B.) and Department of Biomedical Informatics (D.F., P.R.), Vanderbilt University Medical Center, Nashville, TN. Molecular Cardiology Research Institute (R.R.X., M.E.M., B.V.C., Y.W., N.C., A.S., I.Z.J.) and Institute for Clinical Research and Health Policy Studies (P.S.), Tufts Medical Center, Boston, MA
| | - Yihua Wang
- Department of Medicine (M.M.S., J.R., Q.S.W., J.A.B.) and Department of Biomedical Informatics (D.F., P.R.), Vanderbilt University Medical Center, Nashville, TN. Molecular Cardiology Research Institute (R.R.X., M.E.M., B.V.C., Y.W., N.C., A.S., I.Z.J.) and Institute for Clinical Research and Health Policy Studies (P.S.), Tufts Medical Center, Boston, MA
| | - Nicholas Camarda
- Department of Medicine (M.M.S., J.R., Q.S.W., J.A.B.) and Department of Biomedical Informatics (D.F., P.R.), Vanderbilt University Medical Center, Nashville, TN. Molecular Cardiology Research Institute (R.R.X., M.E.M., B.V.C., Y.W., N.C., A.S., I.Z.J.) and Institute for Clinical Research and Health Policy Studies (P.S.), Tufts Medical Center, Boston, MA
| | - Daniel Fabbri
- Department of Medicine (M.M.S., J.R., Q.S.W., J.A.B.) and Department of Biomedical Informatics (D.F., P.R.), Vanderbilt University Medical Center, Nashville, TN. Molecular Cardiology Research Institute (R.R.X., M.E.M., B.V.C., Y.W., N.C., A.S., I.Z.J.) and Institute for Clinical Research and Health Policy Studies (P.S.), Tufts Medical Center, Boston, MA
| | - Protiva Rahman
- Department of Medicine (M.M.S., J.R., Q.S.W., J.A.B.) and Department of Biomedical Informatics (D.F., P.R.), Vanderbilt University Medical Center, Nashville, TN. Molecular Cardiology Research Institute (R.R.X., M.E.M., B.V.C., Y.W., N.C., A.S., I.Z.J.) and Institute for Clinical Research and Health Policy Studies (P.S.), Tufts Medical Center, Boston, MA
| | - Jacob Ramsey
- Department of Medicine (M.M.S., J.R., Q.S.W., J.A.B.) and Department of Biomedical Informatics (D.F., P.R.), Vanderbilt University Medical Center, Nashville, TN. Molecular Cardiology Research Institute (R.R.X., M.E.M., B.V.C., Y.W., N.C., A.S., I.Z.J.) and Institute for Clinical Research and Health Policy Studies (P.S.), Tufts Medical Center, Boston, MA
| | - Alec Stepanian
- Department of Medicine (M.M.S., J.R., Q.S.W., J.A.B.) and Department of Biomedical Informatics (D.F., P.R.), Vanderbilt University Medical Center, Nashville, TN. Molecular Cardiology Research Institute (R.R.X., M.E.M., B.V.C., Y.W., N.C., A.S., I.Z.J.) and Institute for Clinical Research and Health Policy Studies (P.S.), Tufts Medical Center, Boston, MA
| | - Paola Sebastiani
- Department of Medicine (M.M.S., J.R., Q.S.W., J.A.B.) and Department of Biomedical Informatics (D.F., P.R.), Vanderbilt University Medical Center, Nashville, TN. Molecular Cardiology Research Institute (R.R.X., M.E.M., B.V.C., Y.W., N.C., A.S., I.Z.J.) and Institute for Clinical Research and Health Policy Studies (P.S.), Tufts Medical Center, Boston, MA
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189
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Mallard TT, Savage JE, Johnson EC, Huang Y, Edwards AC, Hottenga JJ, Grotzinger AD, Gustavson DE, Jennings MV, Anokhin A, Dick DM, Edenberg HJ, Kramer JR, Lai D, Meyers JL, Pandey AK, Paige Harden K, Nivard MG, de Geus EJC, Boomsma DI, Agrawal A, Davis LK, Clarke TK, Palmer AA, Sanchez-Roige S. Item-Level Genome-Wide Association Study of the Alcohol Use Disorders Identification Test in Three Population-Based Cohorts. Am J Psychiatry 2022; 179:58-70. [PMID: 33985350 PMCID: PMC9272895 DOI: 10.1176/appi.ajp.2020.20091390] [Citation(s) in RCA: 69] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
OBJECTIVE Genome-wide association studies (GWASs) of the Alcohol Use Disorders Identification Test (AUDIT), a 10-item screen for alcohol use disorder (AUD), have elucidated novel loci for alcohol consumption and misuse. However, these studies also revealed that GWASs can be influenced by numerous biases (e.g., measurement error, selection bias), which may have led to inconsistent genetic correlations between alcohol involvement and AUD, as well as paradoxically negative genetic correlations between alcohol involvement and psychiatric disorders and/or medical conditions. The authors used genomic structural equation modeling to elucidate the genetics of alcohol consumption and problematic consequences of alcohol use as measured by AUDIT. METHODS To explore these unexpected differences in genetic correlations, the authors conducted the first item-level and the largest GWAS of AUDIT items (N=160,824) and applied a multivariate framework to mitigate previous biases. RESULTS The authors identified novel patterns of similarity (and dissimilarity) among the AUDIT items and found evidence of a correlated two-factor structure at the genetic level ("consumption" and "problems," rg=0.80). Moreover, by applying empirically derived weights to each of the AUDIT items, the authors constructed an aggregate measure of alcohol consumption that was strongly associated with alcohol dependence (rg=0.67), moderately associated with several other psychiatric disorders, and no longer positively associated with health and positive socioeconomic outcomes. Lastly, by conducting polygenic analyses in three independent cohorts that differed in their ascertainment and prevalence of AUD, the authors identified novel genetic associations between alcohol consumption, alcohol misuse, and health. CONCLUSIONS This work further emphasizes the value of AUDIT for both clinical and genetic studies of AUD and the importance of using multivariate methods to study genetic associations that are more closely related to AUD.
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Affiliation(s)
- Travis T Mallard
- Department of Psychology, University of Texas at Austin, Austin, TX, 78712
| | - Jeanne E Savage
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Netherlands, 1081HV
| | - Emma C Johnson
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO 63110
| | - Yuye Huang
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093
| | - Alexis C Edwards
- Virginia Institute for Psychiatric and Behavioral Genetics, Richmond, VA 23298
| | - Jouke J Hottenga
- Dept of Biological Psychology & EMGO+ Institute for Health and Care Research, Vrije Universiteit Amsterdam, Amsterdam, NL
| | | | - Daniel E Gustavson
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN 37232
| | - Mariela V Jennings
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093
| | - Andrey Anokhin
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO 63110
| | - Danielle M Dick
- Department of Psychology, Virginia Commonwealth University, Richmond, VA 23220
| | - Howard J Edenberg
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN 46202
| | - John R Kramer
- Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa City, IA 52242
| | - Dongbing Lai
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 4622
| | - Jacquelyn L Meyers
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY 11203
| | - Ashwini K Pandey
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY 11203
| | | | - Michel G Nivard
- Dept of Biological Psychology & EMGO+ Institute for Health and Care Research, Vrije Universiteit Amsterdam, Amsterdam, NL
| | - Eco JC de Geus
- Dept of Biological Psychology & EMGO+ Institute for Health and Care Research, Vrije Universiteit Amsterdam, Amsterdam, NL
| | - Dorret I Boomsma
- Dept of Biological Psychology & EMGO+ Institute for Health and Care Research, Vrije Universiteit Amsterdam, Amsterdam, NL
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO 63110
| | - Lea K Davis
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN 37232
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Toni-Kim Clarke
- Division of Psychiatry, University of Edinburgh, Scotland, UK, EH8 9YL
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA 92093
| | - Sandra Sanchez-Roige
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN 37232
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190
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van Duijvenboden S, Ramírez J, Young WJ, Orini M, Mifsud B, Tinker A, Lambiase PD, Munroe PB. Genomic and pleiotropic analyses of resting QT interval identifies novel loci and overlap with atrial electrical disorders. Hum Mol Genet 2021; 30:2513-2523. [PMID: 34274964 PMCID: PMC8643508 DOI: 10.1093/hmg/ddab197] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 05/26/2021] [Accepted: 06/17/2021] [Indexed: 11/13/2022] Open
Abstract
The resting QT interval, an electrocardiographic (ECG) measure of ventricular myocardial repolarization, is a heritable risk marker of cardiovascular mortality, but the mechanisms remain incompletely understood. Previously reported candidate genes have provided insights into the regulatory mechanisms of the QT interval. However, there are still important knowledge gaps. We aimed to gain new insights by (i) providing new candidate genes, (ii) identifying pleiotropic associations with other cardiovascular traits, and (iii) scanning for sexually dimorphic genetic effects. We conducted a genome-wide association analysis for resting QT interval with ~9.8 million variants in 52 107 individuals of European ancestry without known cardiovascular disease from the UK Biobank. We identified 40 loci, 13 of which were novel, including 2 potential sex-specific loci, explaining ~11% of the trait variance. Candidate genes at novel loci were involved in myocardial structure and arrhythmogenic cardiomyopathy. Investigation of pleiotropic effects of QT interval variants using phenome-wide association analyses in 302 000 unrelated individuals from the UK Biobank and pairwise genome-wide comparisons with other ECG and cardiac imaging traits revealed genetic overlap with atrial electrical pathology. These findings provide novel insights into how abnormal myocardial repolarization and increased cardiovascular mortality may be linked.
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Affiliation(s)
- Stefan van Duijvenboden
- Institute of Cardiovascular Science, University College London, London WC1E 6BT, UK
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK
| | - Julia Ramírez
- Institute of Cardiovascular Science, University College London, London WC1E 6BT, UK
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK
| | - William J Young
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK
- Barts Heart Centre, St Bartholomew’s Hospital, London EC1A 7BE, UK
| | - Michele Orini
- Institute of Cardiovascular Science, University College London, London WC1E 6BT, UK
| | - Borbala Mifsud
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK
- College of Health and Life Sciences, Hamad Bin Khalifa University, Doha PO 34110, Qatar
| | - Andrew Tinker
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK
- NIHR Barts Cardiovascular Biomedical Research Unit, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK
| | - Pier D Lambiase
- Institute of Cardiovascular Science, University College London, London WC1E 6BT, UK
- Barts Heart Centre, St Bartholomew’s Hospital, London EC1A 7BE, UK
| | - Patricia B Munroe
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK
- NIHR Barts Cardiovascular Biomedical Research Unit, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK
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191
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Zou XL, Wang S, Wang LY, Xiao LX, Yao TX, Zeng Y, Zhang L. Childhood Obesity and Risk of Stroke: A Mendelian Randomisation Analysis. Front Genet 2021; 12:727475. [PMID: 34868204 PMCID: PMC8638161 DOI: 10.3389/fgene.2021.727475] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Accepted: 10/05/2021] [Indexed: 12/03/2022] Open
Abstract
Background: The causal relationship between childhood obesity and stroke remains unclear. Our objective was to elucidate the causal relationship between childhood obesity and the risk of stroke and its subtypes by performing Mendelian randomisation (MR) analyses. Methods: Genetic instruments for childhood obesity were obtained from a genome-wide association study (GWAS) of 13,848 European participants. Summary level data for stroke, intracerebral haemorrhage, ischaemic stroke (IS), and its subtypes were evaluated using the MEGASTROKE GWAS dataset, which included 446,696 European adults. Inverse-variance weighting, weighted-median analysis, MR-Egger regression, MR Pleiotropy RESidual Sum and Outlier test (MR-PRESSO), and MR-Robust Adjusted Profile Score were applied in this MR analysis. The leave-one-out sensitivity test, MR-PRESSO Global test, and Cochran's Q test were conducted to confirm the accuracy and robustness of our results. Results: Genetic evaluations revealed that childhood obesity was associated with a higher risk of stroke (OR = 1.04, 95%CI: 1.01-1.07, p = 0.005) and IS (OR = 1.05, 95%CI: 1.02-1.08, p = 0.003), but not with intracerebral haemorrhage (ICH, OR = 0.93, 95%CI: 0.80-1.09, p = 0.39). In the subtype analysis, childhood obesity was also associated with large artery stroke (LAS, OR = 1.12, 95%CI: 1.02-1.22, p = 0.016) but not with cardioembolic stroke (OR = 1.06, 95%CI: 0.96-1.18, p = 0.21) and small vessel stroke (OR = 1.06, 95%CI: 0.98-1.15, p = 0.17). These results were stable in the sensitivity analysis and remained significant after Bonferroni correction. Conclusion: Our study provides evidence that childhood obesity is associated with a higher risk of stroke, IS, and LAS. The prevention of stroke, especially IS and LAS, should be promoted in populations with childhood obesity.
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Affiliation(s)
- Xue-Lun Zou
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Sai Wang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Lei-Yun Wang
- Department of Clinical Pharmacology, Hunan Key Laboratory of Pharmacogenetics, Xiangya Hospital, Institute of Clinical Pharmacology, Central South University, Changsha, China
| | - Lin-Xiao Xiao
- Department of Spine Surgery and Orthopaedics, Xiangya Hospital, Central South University, Changsha, China
| | - Tian-Xing Yao
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Yi Zeng
- Department of Geriatrics, Second Xiangya Hospital, Central South University, Changsha, China
| | - Le Zhang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
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192
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Nagar SD, Conley AB, Sharma S, Rishishwar L, Jordan IK, Mariño-Ramírez L. Comparing Genetic and Socioenvironmental Contributions to Ethnic Differences in C-Reactive Protein. Front Genet 2021; 12:738485. [PMID: 34733313 PMCID: PMC8558394 DOI: 10.3389/fgene.2021.738485] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Accepted: 10/05/2021] [Indexed: 02/03/2023] Open
Abstract
C-reactive protein (CRP) is a routinely measured blood biomarker for inflammation. Elevated levels of circulating CRP are associated with response to infection, risk for a number of complex common diseases, and psychosocial stress. The objective of this study was to compare the contributions of genetic ancestry, socioenvironmental factors, and inflammation-related health conditions to ethnic differences in C-reactive protein levels. We used multivariable regression to compare CRP blood serum levels between Black and White ethnic groups from the United Kingdom Biobank (UKBB) prospective cohort study. CRP serum levels are significantly associated with ethnicity in an age and sex adjusted model. Study participants who identify as Black have higher average CRP than those who identify as White, CRP increases with age, and females have higher average CRP than males. Ethnicity and sex show a significant interaction effect on CRP. Black females have higher average CRP levels than White females, whereas White males have higher average CRP than Black males. Significant associations between CRP, ethnicity, and genetic ancestry are almost completely attenuated in a fully adjusted model that includes socioenvironmental factors and inflammation-related health conditions. BMI, smoking, and socioeconomic deprivation all have high relative effects on CRP. These results indicate that socioenvironmental factors contribute more to CRP ethnic differences than genetics. Differences in CRP are associated with ethnic disparities for a number of chronic diseases, including type 2 diabetes, essential hypertension, sarcoidosis, and lupus erythematosus. Our results indicate that ethnic differences in CRP are linked to both socioenvironmental factors and numerous ethnic health disparities.
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Affiliation(s)
- Shashwat Deepali Nagar
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, United States
| | - Andrew B Conley
- IHRC-Georgia Tech Applied Bioinformatics Laboratory, Atlanta, GA, United States.,National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, United States
| | - Shivam Sharma
- National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, United States
| | - Lavanya Rishishwar
- IHRC-Georgia Tech Applied Bioinformatics Laboratory, Atlanta, GA, United States.,National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, United States
| | - I King Jordan
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, United States.,IHRC-Georgia Tech Applied Bioinformatics Laboratory, Atlanta, GA, United States.,PanAmerican Bioinformatics Institute, Cali, Colombia
| | - Leonardo Mariño-Ramírez
- National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, United States.,PanAmerican Bioinformatics Institute, Cali, Colombia
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193
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Vysotskiy M, Zhong X, Miller-Fleming TW, Zhou D, Cox NJ, Weiss LA. Integration of genetic, transcriptomic, and clinical data provides insight into 16p11.2 and 22q11.2 CNV genes. Genome Med 2021; 13:172. [PMID: 34715901 PMCID: PMC8557010 DOI: 10.1186/s13073-021-00972-1] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Accepted: 09/16/2021] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND Deletions and duplications of the multigenic 16p11.2 and 22q11.2 copy number variant (CNV) regions are associated with brain-related disorders including schizophrenia, intellectual disability, obesity, bipolar disorder, and autism spectrum disorder (ASD). The contribution of individual CNV genes to each of these identified phenotypes is unknown, as well as the contribution of these CNV genes to other potentially subtler health implications for carriers. Hypothesizing that DNA copy number exerts most effects via impacts on RNA expression, we attempted a novel in silico fine-mapping approach in non-CNV carriers using both GWAS and biobank data. METHODS We first asked whether gene expression level in any individual gene in the CNV region alters risk for a known CNV-associated behavioral phenotype(s). Using transcriptomic imputation, we performed association testing for CNV genes within large genotyped cohorts for schizophrenia, IQ, BMI, bipolar disorder, and ASD. Second, we used a biobank containing electronic health data to compare the medical phenome of CNV carriers to controls within 700,000 individuals in order to investigate the full spectrum of health effects of the CNVs. Third, we used genotypes for over 48,000 individuals within the biobank to perform phenome-wide association studies between imputed expressions of individual 16p11.2 and 22q11.2 genes and over 1500 health traits. RESULTS Using large genotyped cohorts, we found individual genes within 16p11.2 associated with schizophrenia (TMEM219, INO80E, YPEL3), BMI (TMEM219, SPN, TAOK2, INO80E), and IQ (SPN), using conditional analysis to identify upregulation of INO80E as the driver of schizophrenia, and downregulation of SPN and INO80E as increasing BMI. We identified both novel and previously observed over-represented traits within the electronic health records of 16p11.2 and 22q11.2 CNV carriers. In the phenome-wide association study, we found seventeen significant gene-trait pairs, including psychosis (NPIPB11, SLX1B) and mood disorders (SCARF2), and overall enrichment of mental traits. CONCLUSIONS Our results demonstrate how integration of genetic and clinical data aids in understanding CNV gene function and implicates pleiotropy and multigenicity in CNV biology.
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Affiliation(s)
- Mikhail Vysotskiy
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, 513 Parnassus Ave., Health Sciences East 9th floor HSE901E, San Francisco, CA, 94143, USA
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, 94143, USA
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, 94143, USA
- Pharmaceutical Sciences and Pharmacogenomics Graduate Program, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Xue Zhong
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
- Vanderbilt Genetics Institute, Nashville, TN, 37232, USA
| | - Tyne W Miller-Fleming
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
- Vanderbilt Genetics Institute, Nashville, TN, 37232, USA
| | - Dan Zhou
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
- Vanderbilt Genetics Institute, Nashville, TN, 37232, USA
| | - Nancy J Cox
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
- Vanderbilt Genetics Institute, Nashville, TN, 37232, USA
| | - Lauren A Weiss
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, 513 Parnassus Ave., Health Sciences East 9th floor HSE901E, San Francisco, CA, 94143, USA.
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, 94143, USA.
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, 94143, USA.
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194
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Verma A, Tsao N, Thomann L, Ho YL, Iyengar S, Luoh SW, Carr R, Crawford D, Efird JT, Huffman J, Hung A, Ivey K, Levin M, Lynch J, Natarajan P, Pyarajan S, Bick A, Costa L, Genovese G, Hauger R, Madduri R, Pathak G, Polimanti R, Voight B, Vujkovic M, Zekavat M, Zhao H, Ritchie MD, Chang KM, Cho K, Casas JP, Tsao PS, Gaziano JM, O'Donnell C, Damrauer S, Liao K. A Phenome-Wide Association Study of genes associated with COVID-19 severity reveals shared genetics with complex diseases in the Million Veteran Program. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2021. [PMID: 34642702 PMCID: PMC8509103 DOI: 10.1101/2021.05.18.21257396] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
The study aims to determine the shared genetic architecture between COVID-19 severity with existing medical conditions using electronic health record (EHR) data. We conducted a Phenome-Wide Association Study (PheWAS) of genetic variants associated with critical illness (n=35) or hospitalization (n=42) due to severe COVID-19 using genome-wide association summary from the Host Genetics Initiative. PheWAS analysis was performed using genotype-phenotype data from the Veterans Affairs Million Veteran Program (MVP). Phenotypes were defined by International Classification of Diseases (ICD) codes mapped to clinically relevant groups using published PheWAS methods. Among 658,582 Veterans, variants associated with severe COVID-19 were tested for association across 1,559 phenotypes. Variants at the ABO locus (rs495828, rs505922) associated with the largest number of phenotypes (nrs495828=53 and nrs505922=59); strongest association with venous embolism, odds ratio (ORrs495828 1.33 (p=1.32 × 10-199), and thrombosis ORrs505922 1.33, p=2.2 × 10-265. Among 67 respiratory conditions tested, 11 had significant associations including MUC5B locus (rs35705950) with increased risk of idiopathic fibrosing alveolitis OR 2.83, p=4.12 × 10-191; CRHR1 (rs61667602) associated with reduced risk of pulmonary fibrosis, OR 0.84, p=2.26 × 10-12. The TYK2 locus (rs11085727) associated with reduced risk for autoimmune conditions, e.g., psoriasis OR 0.88, p=6.48 × 10-23, lupus OR 0.84, p=3.97 × 10-06. PheWAS stratified by genetic ancestry demonstrated differences in genotype-phenotype associations across ancestry. LMNA (rs581342) associated with neutropenia OR 1.29 p=4.1 × 10-13 among Veterans of African ancestry but not European. Overall, we observed a shared genetic architecture between COVID-19 severity and conditions related to underlying risk factors for severe and poor COVID-19 outcomes. Differing associations between genotype-phenotype across ancestries may inform heterogenous outcomes observed with COVID-19. Divergent associations between risk for severe COVID-19 with autoimmune inflammatory conditions both respiratory and non-respiratory highlights the shared pathways and fine balance of immune host response and autoimmunity and caution required when considering treatment targets.
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Affiliation(s)
- Anurag Verma
- Corporal Michael Crescenz VA Medical Center, Philadelphia, Philadelphia, USA.,Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Noah Tsao
- Corporal Michael Crescenz VA Medical Center, Philadelphia, Philadelphia, USA.,Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | | | - Yuk-Lam Ho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Sudha Iyengar
- Louis Stokes Cleveland VA Medical Center, Cleveland, OH, USA.,Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, USA
| | - Shiuh-Wen Luoh
- VA Portland Health Care System, Portland OR, USA.,Division of Hematology and Medical Oncology, Knight Cancer Institute, Oregon Health and Science University, Portland, Oregon, USA
| | - Rotonya Carr
- Corporal Michael Crescenz VA Medical Center, Philadelphia, Philadelphia, USA.,Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,University of Washington, Division of Gastroenterology Seattle, WA USA
| | - Dana Crawford
- Cleveland Institute for Computational Biology, Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, USA.,Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, USA.,Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, Ohio, USA
| | - Jimmy T Efird
- Cardiovascular Medicine Division, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | | | - Adriana Hung
- Division of Hematology and Medical Oncology, Knight Cancer Institute, Oregon Health and Science University, Portland, Oregon, USA.,Cooperative Studies Program Epidemiology Center, Health Services Research and Development, DVAHCS (Duke University Affiliate), Durham, North Carolina, USA
| | - Kerry Ivey
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Tennessee Valley Healthcare System (Nashville VA) & Vanderbilt University, Nashville, Tennessee, USA.,Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, USA
| | - Michael Levin
- VA Portland Health Care System, Portland OR, USA.,Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Division of Hematology and Medical Oncology, Knight Cancer Institute, Oregon Health and Science University, Portland, Oregon, USA
| | - Julie Lynch
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, Utah, USA
| | - Pradeep Natarajan
- VA Boston Healthcare System, Boston, Massachusetts, USA.,Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.,Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA.,Program in Medical and Population Genetics and the Cardiovascular Disease Initiative, Broad Institute of Harvard & MIT, Cambridge, Massachusetts, USA
| | - Saiju Pyarajan
- VA Boston Healthcare System, Boston, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
| | - Alexander Bick
- VA Boston Healthcare System, Boston, Massachusetts, USA.,Vanderbilt University, Nashville, Tennessee, USA
| | - Lauren Costa
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Giulio Genovese
- Program in Medical and Population Genetics and the Cardiovascular Disease Initiative, Broad Institute of Harvard & MIT, Cambridge, Massachusetts, USA.,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Richard Hauger
- Department of Psychiatry, University of California, San Diego, La Jolla, CA; Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
| | - Ravi Madduri
- University of Chicago Consortium for Advanced Science and Engineering, The University of Chicago, Chicago, Illinois, USA.,Data Science and Learning Division, Argonne National Laboratory, Lemont, Illinois
| | - Gita Pathak
- VA Connecticut Healthcare System, West Haven, CT, USA.,Department of Psychiatry, Yale School of Medicine, Connecticut, USA
| | - Renato Polimanti
- VA Connecticut Healthcare System, West Haven, CT, USA.,Department of Psychiatry, Yale School of Medicine, Connecticut, USA
| | - Benjamin Voight
- Corporal Michael Crescenz VA Medical Center, Philadelphia, Philadelphia, USA.,Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Marijana Vujkovic
- Corporal Michael Crescenz VA Medical Center, Philadelphia, Philadelphia, USA.,Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Maryam Zekavat
- VA Boston Healthcare System, Boston, Massachusetts, USA.,Broad Institute of MIT & Harvard, Cambridge, MA, USA.,Yale School of Medicine New Haven, CT, USA
| | - Hongyu Zhao
- VA Connecticut Healthcare System, West Haven, CT, USA.,Yale School of Medicine New Haven, CT, USA.,Computational Biology and Bioinformatics Program, Yale University, New Haven, CT, USA
| | | | | | - Kyong-Mi Chang
- Corporal Michael Crescenz VA Medical Center, Philadelphia, Philadelphia, USA.,Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Juan P Casas
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA.,Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Philip S Tsao
- VA Palo Alto Health Care System, Palo Alto, California, USA.,Department of Medicine (Cardiovascular Medicine), Stanford University School of Medicine, Stanford, CA, USA
| | - J Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA.,Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Christopher O'Donnell
- VA Boston Healthcare System, Boston, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA.,Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Scott Damrauer
- Corporal Michael Crescenz VA Medical Center, Philadelphia, Philadelphia, USA.,Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Katherine Liao
- VA Boston Healthcare System, Boston, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA.,Brigham and Women's Hospital, Boston, Massachusetts, USA
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195
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Kelchtermans J, Chang X, March ME, Mentch F, Sleiman PMA, Hakonarson H. HIF-1α Pulmonary Phenotype Wide Association Study Unveils a Link to Inflammatory Airway Conditions. Front Genet 2021; 12:756645. [PMID: 34621299 PMCID: PMC8490729 DOI: 10.3389/fgene.2021.756645] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Accepted: 09/08/2021] [Indexed: 11/21/2022] Open
Abstract
Despite experimental data linking HIF-1α dysfunction to inflammatory airway conditions, the effect of single nucleotide polymorphisms within the HIF1A gene on these conditions remains poorly understood. In the current study, we complete a phenotype wide association study to assess the link between SNPs with known disease associations and respiratory phenotypes. We report two SNPs of the HIF1A gene, the intronic rs79865957 and the missense rs41508050. In these positions the A and the T allele are significantly associated with allergic rhinitis and acute bronchitis and bronchiolitis, respectively. These findings further support the role of HIF-1α in inflammatory pulmonary conditions and may serve as a basis to refine our understanding of other HIF-1α associated phenotypes.
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Affiliation(s)
- Jelte Kelchtermans
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.,The Center of Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Xiao Chang
- The Center of Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Michael E March
- The Center of Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Frank Mentch
- The Center of Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Patrick M A Sleiman
- The Center of Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Hakon Hakonarson
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.,The Center of Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, United States
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196
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Park J, Packard EA, Levin MG, Judy RL, Damrauer SM, Day SM, Ritchie MD, Rader DJ. A genome-first approach to rare variants in hypertrophic cardiomyopathy genes MYBPC3 and MYH7 in a medical biobank. Hum Mol Genet 2021; 31:827-837. [PMID: 34542152 DOI: 10.1093/hmg/ddab249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Revised: 07/24/2021] [Accepted: 08/19/2021] [Indexed: 11/14/2022] Open
Abstract
'Genome-first' approaches to analyzing rare variants can reveal new insights into human biology and disease. Because pathogenic variants are often rare, new discovery requires aggregating rare coding variants into 'gene burdens' for sufficient power. However, a major challenge is deciding which variants to include in gene burden tests. Pathogenic variants in MYBPC3 and MYH7 are well-known causes of hypertrophic cardiomyopathy (HCM), and focusing on these 'positive control' genes in a genome-first approach could help inform variant selection methods and gene burdening strategies for other genes and diseases. Integrating exome sequences with electronic health records among 41 759 participants in the Penn Medicine BioBank, we evaluated the performance of aggregating predicted loss-of-function (pLOF) and/or predicted deleterious missense (pDM) variants in MYBPC3 and MYH7 for gene burden phenome-wide association studies (PheWAS). The approach to grouping rare variants for these two genes produced very different results: pLOFs but not pDM variants in MYBPC3 were strongly associated with HCM, whereas the opposite was true for MYH7. Detailed review of clinical charts revealed that only 38.5% of patients with HCM diagnoses carrying an HCM-associated variant in MYBPC3 or MYH7 had a clinical genetic test result. Additionally, 26.7% of MYBPC3 pLOF carriers without HCM diagnoses had clear evidence of left atrial enlargement and/or septal/LV hypertrophy on echocardiography. Our study shows the importance of evaluating both pLOF and pDM variants for gene burden testing in future studies to uncover novel gene-disease relationships and identify new pathogenic loss-of-function variants across the human genome through genome-first analyses of healthcare-based populations.
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Affiliation(s)
- Joseph Park
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.,Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.,Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Elizabeth A Packard
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Michael G Levin
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Renae L Judy
- Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | | | - Scott M Damrauer
- Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Sharlene M Day
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Marylyn D Ritchie
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.,Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Daniel J Rader
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.,Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.,Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
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197
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Grassmann F, Yang H, Eriksson M, Azam S, Hall P, Czene K. Mammographic features are associated with cardiometabolic disease risk and mortality. Eur Heart J 2021; 42:3361-3370. [PMID: 34338750 PMCID: PMC8423470 DOI: 10.1093/eurheartj/ehab502] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Revised: 04/01/2021] [Accepted: 07/15/2021] [Indexed: 01/03/2023] Open
Abstract
AIMS In recent years, microcalcifications identified in routine mammograms were found to be associated with cardiometabolic disease in women. Here, we aimed to systematically evaluate the association of microcalcifications and other mammographic features with cardiometabolic disease risk and mortality in a large screening cohort and to understand a potential genetic contribution. METHODS AND RESULTS This study included 57 867 women from a prospective mammographic screening cohort in Sweden (KARMA) and 49 583 sisters. Cardiometabolic disease diagnoses and mortality and medication were extracted by linkage to Swedish population registries with virtually no missing data. In the cardiometabolic phenome-wide association study, we found that a higher number of microcalcifications were associated with increased risk for multiple cardiometabolic diseases, particularly in women with pre-existing cardiometabolic diseases. In contrast, dense breasts were associated with a lower incidence of cardiometabolic diseases. Importantly, we observed similar associations in sisters of KARMA women, indicating a potential genetic overlap between mammographic features and cardiometabolic traits. Finally, we observed that the presence of microcalcifications was associated with increased cardiometabolic mortality in women with pre-existing cardiometabolic diseases (hazard ratio and 95% confidence interval: 1.79 [1.24-2.58], P = 0.002) while we did not find such effects in women without cardiometabolic diseases. CONCLUSIONS We found that mammographic features are associated with cardiometabolic risk and mortality. Our results strengthen the notion that a combination of mammographic features and other breast cancer risk factors could be a novel and affordable tool to assess cardiometabolic health in women attending mammographic screening.
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Affiliation(s)
- Felix Grassmann
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels väg 12A, Stockholm 171 65, Sweden
- Institute of Medical Sciences, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, UK
| | - Haomin Yang
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels väg 12A, Stockholm 171 65, Sweden
- Department of Epidemiology and Health Statistics, The School of Public Health, Fujian Medical University, Xuefu North Road 1, University Town, Fuzhou 350122, China
| | - Mikael Eriksson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels väg 12A, Stockholm 171 65, Sweden
| | - Shadi Azam
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels väg 12A, Stockholm 171 65, Sweden
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels väg 12A, Stockholm 171 65, Sweden
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels väg 12A, Stockholm 171 65, Sweden
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198
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Papadopoulou A, Musa H, Sivaganesan M, McCoy D, Deloukas P, Marouli E. COVID-19 susceptibility variants associate with blood clots, thrombophlebitis and circulatory diseases. PLoS One 2021; 16:e0256988. [PMID: 34478452 PMCID: PMC8415605 DOI: 10.1371/journal.pone.0256988] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Accepted: 08/19/2021] [Indexed: 12/16/2022] Open
Abstract
Epidemiological studies suggest that individuals with comorbid conditions including diabetes, chronic lung, inflammatory and vascular disease, are at higher risk of adverse COVID-19 outcomes. Genome-wide association studies have identified several loci associated with increased susceptibility and severity for COVID-19. However, it is not clear whether these associations are genetically determined or not. We used a Phenome-Wide Association (PheWAS) approach to investigate the role of genetically determined COVID-19 susceptibility on disease related outcomes. PheWAS analyses were performed in order to identify traits and diseases related to COVID-19 susceptibility and severity, evaluated through a predictive COVID-19 risk score. We utilised phenotypic data in up to 400,000 individuals from the UK Biobank, including Hospital Episode Statistics and General Practice data. We identified a spectrum of associations between both genetically determined COVID-19 susceptibility and severity with a number of traits. COVID-19 risk was associated with increased risk for phlebitis and thrombophlebitis (OR = 1.11, p = 5.36e-08). We also identified significant signals between COVID-19 susceptibility with blood clots in the leg (OR = 1.1, p = 1.66e-16) and with increased risk for blood clots in the lung (OR = 1.12, p = 1.45 e-10). Our study identifies significant association of genetically determined COVID-19 with increased blood clot events in leg and lungs. The reported associations between both COVID-19 susceptibility and severity and other diseases adds to the identification and stratification of individuals at increased risk, adverse outcomes and long-term effects.
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Affiliation(s)
- Areti Papadopoulou
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
- Centre for Genomic Health, Life Sciences, Queen Mary University of London, London, United Kingdom
| | - Hanan Musa
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Mathura Sivaganesan
- Barts and the London School of Medicine, Queen Mary University of London, London, United Kingdom
| | - David McCoy
- Population Health Sciences, Queen Mary University of London, London, United Kingdom
| | - Panos Deloukas
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
- Centre for Genomic Health, Life Sciences, Queen Mary University of London, London, United Kingdom
| | - Eirini Marouli
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
- Centre for Genomic Health, Life Sciences, Queen Mary University of London, London, United Kingdom
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199
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Bagheri M, Wang C, Shi M, Manouchehri A, Murray KT, Murphy MB, Shaffer CM, Singh K, Davis LK, Jarvik GP, Stanaway IB, Hebbring S, Reilly MP, Gerszten RE, Wang TJ, Mosley JD, Ferguson JF. The genetic architecture of plasma kynurenine includes cardiometabolic disease mechanisms associated with the SH2B3 gene. Sci Rep 2021; 11:15652. [PMID: 34341450 PMCID: PMC8329184 DOI: 10.1038/s41598-021-95154-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Accepted: 07/21/2021] [Indexed: 01/11/2023] Open
Abstract
Inflammation increases the risk of cardiometabolic disease. Delineating specific inflammatory pathways and biomarkers of their activity could identify the mechanistic underpinnings of the increased risk. Plasma levels of kynurenine, a metabolite involved in inflammation, associates with cardiometabolic disease risk. We used genetic approaches to identify inflammatory mechanisms associated with kynurenine variability and their relationship to cardiometabolic disease. We identified single-nucleotide polymorphisms (SNPs) previously associated with plasma kynurenine, including a missense-variant (rs3184504) in the inflammatory gene SH2B3/LNK. We examined the association between rs3184504 and plasma kynurenine in independent human samples, and measured kynurenine levels in SH2B3-knock-out mice and during human LPS-evoked endotoxemia. We conducted phenome scanning to identify clinical phenotypes associated with each kynurenine-related SNP and with a kynurenine polygenic score using the UK-Biobank (n = 456,422), BioVU (n = 62,303), and Electronic Medical Records and Genetics (n = 32,324) databases. The SH2B3 missense variant associated with plasma kynurenine levels and SH2B3-/- mice had significant tissue-specific differences in kynurenine levels.LPS, an acute inflammatory stimulus, increased plasma kynurenine in humans. Mendelian randomization showed increased waist-circumference, a marker of central obesity, associated with increased kynurenine, and increased kynurenine associated with C-reactive protein (CRP). We found 30 diagnoses associated (FDR q < 0.05) with the SH2B3 variant, but not with SNPs mapping to genes known to regulate tryptophan-kynurenine metabolism. Plasma kynurenine may be a biomarker of acute and chronic inflammation involving the SH2B3 pathways. Its regulation lies upstream of CRP, suggesting that kynurenine may be a biomarker of one inflammatory mechanism contributing to increased cardiometabolic disease risk.
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Affiliation(s)
- Minoo Bagheri
- Division of Cardiovascular Medicine, Department of Medicine, Vanderbilt University Medical Center, 2220 Pierce Ave, PRB 354B, Nashville, TN, 37232, USA
| | - Chuan Wang
- Division of Cardiovascular Medicine, Department of Medicine, Vanderbilt University Medical Center, 2220 Pierce Ave, PRB 354B, Nashville, TN, 37232, USA
| | - Mingjian Shi
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Ali Manouchehri
- Division of Cardiovascular Medicine, Department of Medicine, Vanderbilt University Medical Center, 2220 Pierce Ave, PRB 354B, Nashville, TN, 37232, USA
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Katherine T Murray
- Division of Cardiovascular Medicine, Department of Medicine, Vanderbilt University Medical Center, 2220 Pierce Ave, PRB 354B, Nashville, TN, 37232, USA
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Matthew B Murphy
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Christian M Shaffer
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Kritika Singh
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lea K Davis
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Gail P Jarvik
- Departments of Medicine (Medical Genetics) and Genome Sciences, University of Washington, Seattle, WA, USA
| | - Ian B Stanaway
- Division of Nephrology, School of Medicine, Harborview Medical Center Kidney Research Institute, University of Washington, Seattle, WA, USA
| | - Scott Hebbring
- Center for Precision Medicine Research, Marshfield Clinic Research Institute, Marshfield, WI, USA
| | - Muredach P Reilly
- Irving Institute for Clinical and Translational Research and Division of Cardiology, Columbia University Medical Center, New York, NY, USA
| | - Robert E Gerszten
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Thomas J Wang
- Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, USA
| | - Jonathan D Mosley
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jane F Ferguson
- Division of Cardiovascular Medicine, Department of Medicine, Vanderbilt University Medical Center, 2220 Pierce Ave, PRB 354B, Nashville, TN, 37232, USA.
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200
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Satterfield BA, Dikilitas O, Safarova MS, Clarke SL, Tcheandjieu C, Zhu X, Bastarache L, Larson EB, Justice AE, Shang N, Rosenthal EA, Shah AS, Namjou-Khales B, Urbina EM, Wei WQ, Feng Q, Jarvik GP, Hebbring SJ, de Andrade M, Manolio TA, Assimes TL, Kullo IJ. Associations of Genetically Predicted Lp(a) (Lipoprotein [a]) Levels With Cardiovascular Traits in Individuals of European and African Ancestry. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2021; 14:e003354. [PMID: 34282949 PMCID: PMC8634549 DOI: 10.1161/circgen.120.003354] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
BACKGROUND Lp(a) (lipoprotein [a]) levels are higher in individuals of African ancestry (AA) than in individuals of European ancestry (EA). We examined associations of genetically predicted Lp(a) levels with (1) atherosclerotic cardiovascular disease subtypes: coronary heart disease, cerebrovascular disease, peripheral artery disease, and abdominal aortic aneurysm and (2) nonatherosclerotic cardiovascular disease phenotypes, stratified by ancestry. METHODS We performed (1) Mendelian randomization analyses for previously reported cardiovascular associations and (2) Mendelian randomization-phenome-wide association analyses for novel associations. Analyses were stratified by ancestry in electronic Medical Records and Genomics, United Kingdom Biobank, and Million Veteran Program cohorts separately and in a combined cohort of 804 507 EA and 103 580 AA participants. RESULTS In Mendelian randomization analyses using the combined cohort, a 1-SD genetic increase in Lp(a) level was associated with atherosclerotic cardiovascular disease subtypes in EA-odds ratio and 95% CI for coronary heart disease 1.28 (1.16-1.41); cerebrovascular disease 1.14 (1.07-1.21); peripheral artery disease 1.22 (1.11-1.34); abdominal aortic aneurysm 1.28 (1.17-1.40); in AA, the effect estimate was lower than in EA and nonsignificant for coronary heart disease 1.11 (0.99-1.24) and cerebrovascular disease 1.06 (0.99-1.14) but similar for peripheral artery disease 1.16 (1.01-1.33) and abdominal aortic aneurysm 1.34 (1.11-1.62). In EA, a 1-SD genetic increase in Lp(a) level was associated with aortic valve disorders 1.34 (1.10-1.62), mitral valve disorders 1.18 (1.09-1.27), congestive heart failure 1.12 (1.05-1.19), and chronic kidney disease 1.07 (1.01-1.14). In AA, no significant associations were noted for aortic valve disorders 1.08 (0.94-1.25), mitral valve disorders 1.02 (0.89-1.16), congestive heart failure 1.02 (0.95-1.10), or chronic kidney disease 1.05 (0.99-1.12). Mendelian randomization-phenome-wide association analyses identified novel associations in EA with arterial thromboembolic disease, nonaortic aneurysmal disease, atrial fibrillation, cardiac conduction disorders, and hypertension. CONCLUSIONS Many cardiovascular associations of genetically increased Lp(a) that were significant in EA were not significant in AA. Lp(a) was associated with atherosclerotic cardiovascular disease in four major arterial beds in EA but only with peripheral artery disease and abdominal aortic aneurysm in AA. Additionally, novel cardiovascular associations were detected in EA.
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Affiliation(s)
| | - Ozan Dikilitas
- Dept of Cardiovascular Medicine, Mayo Clinic, Rochester, MN
| | | | - Shoa L. Clarke
- VA Palo Alto Health Care System, Palo Alto
- Division of Cardiovascular Medicine, Dept of Medicine, Stanford Univ School of Medicine, Stanford, CA
| | - Catherine Tcheandjieu
- VA Palo Alto Health Care System, Palo Alto
- Division of Cardiovascular Medicine, Dept of Medicine, Stanford Univ School of Medicine, Stanford, CA
- Dept of Pediatric Cardiology, Stanford Univ School of Medicine, Stanford, CA
| | - Xiang Zhu
- VA Palo Alto Health Care System, Palo Alto
- Dept of Statistics, The Pennsylvania State Univ, University Park, PA
- Huck Institutes of the Life Sciences, The Pennsylvania State Univ, University Park, PA
- Dept of Statistics, Stanford Univ, Stanford, CA
| | - Lisa Bastarache
- Dept of Biomedical Informatics, Vanderbilt Univ, Nashville, TN
| | - Eric B. Larson
- Kaiser Permanente Washington Health Research Institutes, Seattle, WA
| | | | - Ning Shang
- Dept of Biomedical Informatics, Columbia Univ, New York, NY
| | | | - Amy Sanghavi Shah
- Division of Endocrinology, Cincinnati Children’s Hospital Medical Center & Univ of Cincinnati
| | - Bahram Namjou-Khales
- Center for Autoimmune Genomics and Etiology, Cincinnati Children’s Hospital Medical Center & Dept of Pediatrics, Univ of Cincinnati, College of Medicine, Cincinnati, OH
| | - Elaine M. Urbina
- Division of Endocrinology, Heart Institute, Cincinnati Children’s Hospital Medical Center & Univ of Cincinnati
| | - Wei-Qi Wei
- Dept of Biomedical Informatics, Vanderbilt Univ, Nashville, TN
| | - QiPing Feng
- Division of Clinical Pharmacology, Dept of Medicine, Vanderbilt Univ Medical Center, Nashville, TN
| | - Gail P. Jarvik
- Division of Medical Genetics, Dept of Medicine, Univ of Washington, Seattle, WA
| | - Scott J. Hebbring
- Center for Precision Medicine, Marshfield Clinic Research Institute, WI
| | - Mariza de Andrade
- Dept of Cardiovascular Medicine, Dept of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Teri A. Manolio
- Division of Genomic Medicine, National Human Genome Research Institute, Bethesda, MD
| | | | - Iftikhar J. Kullo
- Dept of Cardiovascular Medicine, Mayo Clinic, Rochester, MN
- Dept of Cardiovascular Medicine, Gonda Vascular Center, Mayo Clinic, Rochester, MN
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