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Xiang R, Liu Y, Ben-Eghan C, Ritchie S, Lambert SA, Xu Y, Takeuchi F, Inouye M. Genome-wide analyses of variance in blood cell phenotypes provide new insights into complex trait biology and prediction. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.15.24305830. [PMID: 38699308 PMCID: PMC11065006 DOI: 10.1101/2024.04.15.24305830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Abstract
Blood cell phenotypes are routinely tested in healthcare to inform clinical decisions. Genetic variants influencing mean blood cell phenotypes have been used to understand disease aetiology and improve prediction; however, additional information may be captured by genetic effects on observed variance. Here, we mapped variance quantitative trait loci (vQTL), i.e. genetic loci associated with trait variance, for 29 blood cell phenotypes from the UK Biobank (N~408,111). We discovered 176 independent blood cell vQTLs, of which 147 were not found by additive QTL mapping. vQTLs displayed on average 1.8-fold stronger negative selection than additive QTL, highlighting that selection acts to reduce extreme blood cell phenotypes. Variance polygenic scores (vPGSs) were constructed to stratify individuals in the INTERVAL cohort (N~40,466), where genetically less variable individuals (low vPGS) had increased conventional PGS accuracy (by ~19%) than genetically more variable individuals. Genetic prediction of blood cell traits improved by ~10% on average combining PGS with vPGS. Using Mendelian randomisation and vPGS association analyses, we found that alcohol consumption significantly increased blood cell trait variances highlighting the utility of blood cell vQTLs and vPGSs to provide novel insight into phenotype aetiology as well as improve prediction.
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Affiliation(s)
- Ruidong Xiang
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, Victoria 3083, Australia
- Baker Department of Cardiovascular Research, Translation and Implementation, La Trobe University, Melbourne, VIC, 3086, Australia
- Baker Department of Cardiometabolic Health, The University of Melbourne, VIC, 3010, Australia
| | - Yang Liu
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- 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
| | - Chief Ben-Eghan
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- 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
| | - Scott Ritchie
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- 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
| | - Samuel A. Lambert
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- 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
| | - Yu Xu
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- 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
| | - Fumihiko Takeuchi
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Michael Inouye
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- 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
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2
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Herrera-Rivero M, Gutiérrez-Fragoso K, Kurtz J, Baune BT. Immunogenetics of lithium response and psychiatric phenotypes in patients with bipolar disorder. Transl Psychiatry 2024; 14:174. [PMID: 38570518 PMCID: PMC10991481 DOI: 10.1038/s41398-024-02865-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 03/05/2024] [Accepted: 03/08/2024] [Indexed: 04/05/2024] Open
Abstract
The link between bipolar disorder (BP) and immune dysfunction remains controversial. While epidemiological studies have long suggested an association, recent research has found only limited evidence of such a relationship. To clarify this, we performed an exploratory study of the contributions of immune-relevant genetic factors to the response to lithium (Li) treatment and the clinical presentation of BP. First, we assessed the association of a large collection of immune-related genes (4925) with Li response, defined by the Retrospective Assessment of the Lithium Response Phenotype Scale (Alda scale), and clinical characteristics in patients with BP from the International Consortium on Lithium Genetics (ConLi+Gen, N = 2374). Second, we calculated here previously published polygenic scores (PGSs) for immune-related traits and evaluated their associations with Li response and clinical features. Overall, we observed relatively weak associations (p < 1 × 10-4) with BP phenotypes within immune-related genes. Network and functional enrichment analyses of the top findings from the association analyses of Li response variables showed an overrepresentation of pathways participating in cell adhesion and intercellular communication. These appeared to converge on the well-known Li-induced inhibition of GSK-3β. Association analyses of age-at-onset, number of mood episodes, and presence of psychosis, substance abuse and/or suicidal ideation suggested modest contributions of genes such as RTN4, XKR4, NRXN1, NRG1/3 and GRK5 to disease characteristics. PGS analyses returned weak associations (p < 0.05) between inflammation markers and the studied BP phenotypes. Our results suggest a modest relationship between immunity and clinical features in BP. More research is needed to assess the potential therapeutic relevance.
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Affiliation(s)
- Marisol Herrera-Rivero
- Department of Psychiatry and Psychotherapy, University of Münster, Münster, Germany
- Department of Genetic Epidemiology, Institute of Human Genetics, University of Münster, Münster, Germany
- Joint Institute for Individualisation in a Changing Environment (JICE), University of Münster and Bielefeld University, Münster, Germany
| | - Karina Gutiérrez-Fragoso
- Division of Engineering in Computational Systems, Higher Technological Institute of the East of the State of Hidalgo, Hidalgo, Mexico
| | - Joachim Kurtz
- Joint Institute for Individualisation in a Changing Environment (JICE), University of Münster and Bielefeld University, Münster, Germany
- Institute for Evolution and Biodiversity, University of Münster, Münster, Germany
| | - Bernhard T Baune
- Department of Psychiatry and Psychotherapy, University of Münster, Münster, Germany.
- Joint Institute for Individualisation in a Changing Environment (JICE), University of Münster and Bielefeld University, Münster, Germany.
- Department of Psychiatry, Melbourne Medical School, University of Melbourne, Melbourne, Australia.
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Australia.
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3
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Aw AJ, McRae J, Rahmani E, Song YS. Highly parameterized polygenic scores tend to overfit to population stratification via random effects. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.27.577589. [PMID: 38352303 PMCID: PMC10862757 DOI: 10.1101/2024.01.27.577589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/22/2024]
Abstract
Polygenic scores (PGSs), increasingly used in clinical settings, frequently include many genetic variants, with performance typically peaking at thousands of variants. Such highly parameterized PGSs often include variants that do not pass a genome-wide significance threshold. We propose a mathematical perspective that renders the effects of many of these non-significant variants random rather than causal, with the randomness capturing population structure. We devise methods to assess variant effect randomness and population stratification bias. Applying these methods to 141 traits from the UK Biobank, we find that, for many PGSs, the effects of non-significant variants are considerably random, with the extent of randomness associated with the degree of overfitting to population structure of the discovery cohort. Our findings explain why highly parameterized PGSs simultaneously have superior cohort-specific performance and limited generalizability, suggesting the critical need for variant randomness tests in PGS evaluation. Supporting code and a dashboard are available at https://github.com/songlab-cal/StratPGS.
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Affiliation(s)
- Alan J. Aw
- Department of Statistics, University of California, Berkeley
- Center for Computational Biology, University of California, Berkeley
- Artificial Intelligence Laboratory, Illumina Inc
| | - Jeremy McRae
- Artificial Intelligence Laboratory, Illumina Inc
| | - Elior Rahmani
- Department of Computational Medicine, University of California, Los Angeles
| | - Yun S. Song
- Department of Statistics, University of California, Berkeley
- Center for Computational Biology, University of California, Berkeley
- Computer Science Division, University of California, Berkeley
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4
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Herrera-Rivero M, Gutiérrez-Fragoso K, Thalamuthu A, Amare AT, Adli M, Akiyama K, Akula N, Ardau R, Arias B, Aubry JM, Backlund L, Bellivier F, Benabarre A, Bengesser S, Abesh B, Biernacka J, Birner A, Cearns M, Cervantes P, Chen HC, Chillotti C, Cichon S, Clark S, Colom F, Cruceanu C, Czerski P, Dalkner N, Degenhardt F, Del Zompo M, DePaulo JR, Etain B, Falkai P, Ferensztajn-Rochowiak E, Forstner AJ, Frank J, Frisen L, Frye M, Fullerton J, Gallo C, Gard S, Garnham J, Goes F, Grigoroiu-Serbanescu M, Grof P, Hashimoto R, Hasler R, Hauser J, Heilbronner U, Herms S, Hoffmann P, Hou L, Hsu Y, Jamain S, Jiménez E, Kahn JP, Kassem L, Kato T, Kelsoe J, Kittel-Schneider S, Kuo PH, Kurtz J, Kusumi I, König B, Laje G, Landén M, Lavebratt C, Leboyer M, Leckband S, Maj M, Manchia M, Marie-Claire C, Martinsson L, McCarthy M, McElroy SL, Millischer V, Mitjans M, Mondimore F, Monteleone P, Nievergelt C, Novak T, Nöthen M, Odonovan C, Ozaki N, Papiol S, Pfennig A, Pisanu C, Potash J, Reif A, Reininghaus E, Richard-Lepouriel H, Roberts G, Rouleau G, Rybakowski JK, Schalling M, Schofield P, Schubert KO, Schulte E, Schweizer B, Severino G, Shekhtman T, Shilling P, Shimoda K, Simhandl C, Slaney C, Squassina A, Stamm T, Stopkova P, Streit F, Ayele F, Tortorella A, Turecki G, Veeh J, Vieta E, Viswanath B, Witt S, Zandi P, Alda M, Bauer M, McMahon F, Mitchell P, Rietschel M, Schulze T, Baune B. Immunogenetics of lithium response and psychiatric phenotypes in patients with bipolar disorder. RESEARCH SQUARE 2023:rs.3.rs-3068352. [PMID: 37461719 PMCID: PMC10350128 DOI: 10.21203/rs.3.rs-3068352/v1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/25/2023]
Abstract
The link between bipolar disorder (BP) and immune dysfunction remains controversial. While epidemiological studies have long suggested an association, recent research has found only limited evidence of such a relationship. To clarify this, we investigated the contributions of immune-relevant genetic factors to the response to lithium (Li) treatment and the clinical presentation of BP. First, we assessed the association of a large collection of immune-related genes (4,925) with Li response, defined by the Retrospective Assessment of the Lithium Response Phenotype Scale (Alda scale), and clinical characteristics in patients with BP from the International Consortium on Lithium Genetics (ConLi+Gen, N = 2,374). Second, we calculated here previously published polygenic scores (PGSs) for immune-related traits and evaluated their associations with Li response and clinical features. We found several genes associated with Li response at p < 1×10- 4 values, including HAS3, CNTNAP5 and NFIB. Network and functional enrichment analyses uncovered an overrepresentation of pathways involved in cell adhesion and intercellular communication, which appear to converge on the well-known Li-induced inhibition of GSK-3β. We also found various genes associated with BP's age-at-onset, number of mood episodes, and presence of psychosis, substance abuse and/or suicidal ideation at the exploratory threshold. These included RTN4, XKR4, NRXN1, NRG1/3 and GRK5. Additionally, PGS analyses suggested serum FAS, ECP, TRANCE and cytokine ligands, amongst others, might represent potential circulating biomarkers of Li response and clinical presentation. Taken together, our results support the notion of a relatively weak association between immunity and clinically relevant features of BP at the genetic level.
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Affiliation(s)
| | | | | | | | | | - Kazufumi Akiyama
- Department of Biological Psychiatry and Neuroscience, Dokkyo Medical University
| | - Nirmala Akula
- National Institutes of Health, US Dept of Health & Human Services
| | | | - Bárbara Arias
- Facultat de Biologia and Institut de Biomedicina (IBUB), Universitat de Barcelona, CIBERSAM
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Urs Heilbronner
- Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich
| | | | | | - Liping Hou
- National Institute of Mental Health Intramural Research Program, National Institutes of Health
| | | | | | | | | | | | - Tadafumi Kato
- Laboratory for Molecular Dynamics of Mental Disorders, RIKEN Brain Science Institute, Wako, Saitama 351-0198, Japan
| | | | | | - Po-Hsiu Kuo
- College of Public Health, National Taiwan University, Taipei, Taiwan
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Marina Mitjans
- Max Planck Institute of Experimental Medicine, Göttingen, Germany
| | | | | | | | - Tomas Novak
- National Institute of Mental Health, Klecany
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Thomas Stamm
- Charité - Universitätsmedizin Berlin, Campus Charité Mitte
| | | | | | | | | | - Gustavo Turecki
- Douglas Institute, Department of Psychiatry, McGill University
| | | | | | - Biju Viswanath
- National Institute of Mental Health and Neuro Sciences, Bengaluru, Karnataka, India
| | | | | | | | | | - Francis McMahon
- National Institute of Mental Health Intramural Research Program; National Institutes of Health
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5
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Nandhini K, Tamilpavai G. An Optimal Stacked ResNet-BiLSTM-Based Accurate Detection and Classification of Genetic Disorders. Neural Process Lett 2023:1-22. [PMID: 37359129 PMCID: PMC10196306 DOI: 10.1007/s11063-023-11195-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/13/2023] [Indexed: 06/28/2023]
Abstract
Gene is located inside the nuclease and the genetic data is contained in deoxyribonucleic acid (DNA). A person's gene count ranges from 20,000 to 30,000. Even a minor alteration to the DNA sequence can be harmful if it affects the cell's fundamental functions. As a result, the gene begins to act abnormally. The sorts of genetic abnormalities brought on by mutation include chromosomal disorders, complex disorders, and single-gene disorders. Therefore, a detailed diagnosis method is required. Thus, we proposed an Elephant Herd Optimization-Whale Optimization Algorithm (EHO-WOA) optimized Stacked ResNet-Bidirectional Long Term Short Memory (ResNet-BiLSTM) model for detecting genetic disorders. Here, a hybrid EHO-WOA algorithm is presented to assess the Stacked ResNet-BiLSTM architecture's fitness. The ResNet-BiLSTM design uses the genotype and gene expression phenotype as input data. Furthermore, the proposed method identifies rare genetic disorders such as Angelman Syndrome, Rett Syndrome, and Prader-Willi Syndrome. It demonstrates the effectiveness of the developed model with greater accuracy, recall, specificity, precision, and f1-score. Thus, a wide range of DNA deficiencies including Prader-Willi syndrome, Marfan syndrome, Early Onset Morbid Obesity, Rett syndrome, and Angelman syndrome are predicted accurately.
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Affiliation(s)
- K. Nandhini
- Department of Computer Science and Engineering, Anna University, Chennai, India
| | - G. Tamilpavai
- Department of Computer Science and Engineering, Government College of Engineering, Tirunelveli, India
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6
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Xu Y, Ritchie SC, Liang Y, Timmers PRHJ, Pietzner M, Lannelongue L, Lambert SA, Tahir UA, May-Wilson S, Foguet C, Johansson Å, Surendran P, Nath AP, Persyn E, Peters JE, Oliver-Williams C, Deng S, Prins B, Luan J, Bomba L, Soranzo N, Di Angelantonio E, Pirastu N, Tai ES, van Dam RM, Parkinson H, Davenport EE, Paul DS, Yau C, Gerszten RE, Mälarstig A, Danesh J, Sim X, Langenberg C, Wilson JF, Butterworth AS, Inouye M. An atlas of genetic scores to predict multi-omic traits. Nature 2023; 616:123-131. [PMID: 36991119 PMCID: PMC10323211 DOI: 10.1038/s41586-023-05844-9] [Citation(s) in RCA: 28] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 02/15/2023] [Indexed: 03/30/2023]
Abstract
The use of omic modalities to dissect the molecular underpinnings of common diseases and traits is becoming increasingly common. But multi-omic traits can be genetically predicted, which enables highly cost-effective and powerful analyses for studies that do not have multi-omics1. Here we examine a large cohort (the INTERVAL study2; n = 50,000 participants) with extensive multi-omic data for plasma proteomics (SomaScan, n = 3,175; Olink, n = 4,822), plasma metabolomics (Metabolon HD4, n = 8,153), serum metabolomics (Nightingale, n = 37,359) and whole-blood Illumina RNA sequencing (n = 4,136), and use machine learning to train genetic scores for 17,227 molecular traits, including 10,521 that reach Bonferroni-adjusted significance. We evaluate the performance of genetic scores through external validation across cohorts of individuals of European, Asian and African American ancestries. In addition, we show the utility of these multi-omic genetic scores by quantifying the genetic control of biological pathways and by generating a synthetic multi-omic dataset of the UK Biobank3 to identify disease associations using a phenome-wide scan. We highlight a series of biological insights with regard to genetic mechanisms in metabolism and canonical pathway associations with disease; for example, JAK-STAT signalling and coronary atherosclerosis. Finally, we develop a portal ( https://www.omicspred.org/ ) to facilitate public access to all genetic scores and validation results, as well as to serve as a platform for future extensions and enhancements of multi-omic genetic scores.
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Affiliation(s)
- Yu Xu
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK.
| | - Scott C Ritchie
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Yujian Liang
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Paul R H J Timmers
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Maik Pietzner
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
- Computational Medicine, Berlin Institute of Health (BIH) at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - Loïc Lannelongue
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
| | - Samuel A Lambert
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK
| | - Usman A Tahir
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Sebastian May-Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Carles Foguet
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
| | - Åsa Johansson
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Praveen Surendran
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Artika P Nath
- 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
| | - Elodie Persyn
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
| | - James E Peters
- Department of Immunology and Inflammation, Faculty of Medicine, Imperial College London, London, UK
| | - Clare Oliver-Williams
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Shuliang Deng
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Bram Prins
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Jian'an Luan
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Lorenzo Bomba
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
- BioMarin Pharmaceutical, Novato, CA, USA
| | - Nicole Soranzo
- British Heart Foundation Centre of Research Excellence, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
- Department of Haematology, University of Cambridge, Cambridge, UK
- NIHR Blood and Transplant Research Unit in Donor Health and Behaviour, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Genomics Research Centre, Human Technopole, Milan, Italy
| | - Emanuele Di Angelantonio
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- NIHR Blood and Transplant Research Unit in Donor Health and Behaviour, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Health Data Science Research Centre, Human Technopole, Milan, Italy
| | - Nicola Pirastu
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
- Genomics Research Centre, Human Technopole, Milan, Italy
| | - E Shyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Department of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Rob M van Dam
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Departments of Exercise and Nutrition Sciences and Epidemiology, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA
| | - Helen Parkinson
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK
| | | | - Dirk S Paul
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Christopher Yau
- Nuffield Department of Women's and Reproductive Health, University of Oxford, Oxford, UK
- Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- Health Data Research UK, London, UK
| | - Robert E Gerszten
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Broad Institute of Harvard University and Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Anders Mälarstig
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Pfizer Worldwide Research, Development and Medical, Stockholm, Sweden
| | - John Danesh
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
- NIHR Blood and Transplant Research Unit in Donor Health and Behaviour, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
- Computational Medicine, Berlin Institute of Health (BIH) at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - 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
| | - Adam S Butterworth
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- NIHR Blood and Transplant Research Unit in Donor Health and Behaviour, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Michael Inouye
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK.
- British Heart Foundation Centre of Research Excellence, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK.
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.
- The Alan Turing Institute, London, UK.
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7
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Aragam KG, Jiang T, Goel A, Kanoni S, Wolford BN, Atri DS, Weeks EM, Wang M, Hindy G, Zhou W, Grace C, Roselli C, Marston NA, Kamanu FK, Surakka I, Venegas LM, Sherliker P, Koyama S, Ishigaki K, Åsvold BO, Brown MR, Brumpton B, de Vries PS, Giannakopoulou O, Giardoglou P, Gudbjartsson DF, Güldener U, Haider SMI, Helgadottir A, Ibrahim M, Kastrati A, Kessler T, Kyriakou T, Konopka T, Li L, Ma L, Meitinger T, Mucha S, Munz M, Murgia F, Nielsen JB, Nöthen MM, Pang S, Reinberger T, Schnitzler G, Smedley D, Thorleifsson G, von Scheidt M, Ulirsch JC, Arnar DO, Burtt NP, Costanzo MC, Flannick J, Ito K, Jang DK, Kamatani Y, Khera AV, Komuro I, Kullo IJ, Lotta LA, Nelson CP, Roberts R, Thorgeirsson G, Thorsteinsdottir U, Webb TR, Baras A, Björkegren JLM, Boerwinkle E, Dedoussis G, Holm H, Hveem K, Melander O, Morrison AC, Orho-Melander M, Rallidis LS, Ruusalepp A, Sabatine MS, Stefansson K, Zalloua P, Ellinor PT, Farrall M, Danesh J, Ruff CT, Finucane HK, Hopewell JC, Clarke R, Gupta RM, Erdmann J, Samani NJ, Schunkert H, Watkins H, Willer CJ, Deloukas P, Kathiresan S, Butterworth AS. Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participants. Nat Genet 2022; 54:1803-1815. [PMID: 36474045 PMCID: PMC9729111 DOI: 10.1038/s41588-022-01233-6] [Citation(s) in RCA: 167] [Impact Index Per Article: 83.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Accepted: 10/17/2022] [Indexed: 12/12/2022]
Abstract
The discovery of genetic loci associated with complex diseases has outpaced the elucidation of mechanisms of disease pathogenesis. Here we conducted a genome-wide association study (GWAS) for coronary artery disease (CAD) comprising 181,522 cases among 1,165,690 participants of predominantly European ancestry. We detected 241 associations, including 30 new loci. Cross-ancestry meta-analysis with a Japanese GWAS yielded 38 additional new loci. We prioritized likely causal variants using functionally informed fine-mapping, yielding 42 associations with less than five variants in the 95% credible set. Similarity-based clustering suggested roles for early developmental processes, cell cycle signaling and vascular cell migration and proliferation in the pathogenesis of CAD. We prioritized 220 candidate causal genes, combining eight complementary approaches, including 123 supported by three or more approaches. Using CRISPR-Cas9, we experimentally validated the effect of an enhancer in MYO9B, which appears to mediate CAD risk by regulating vascular cell motility. Our analysis identifies and systematically characterizes >250 risk loci for CAD to inform experimental interrogation of putative causal mechanisms for CAD.
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Grants
- MR/L003120/1 Medical Research Council
- BRC-1215-20014 Department of Health
- R01 HL125863 NHLBI NIH HHS
- UL1 RR025005 NCRR NIH HHS
- R01 HL059367 NHLBI NIH HHS
- U01 HG004402 NHGRI NIH HHS
- RG/14/5/30893 British Heart Foundation
- SP/13/2/30111 British Heart Foundation
- SP/16/4/32697 British Heart Foundation
- HHSN268201700001I NHLBI NIH HHS
- FS/14/55/30806 British Heart Foundation
- R01 HL087641 NHLBI NIH HHS
- MC_PC_17228 Medical Research Council
- MR/S502443/1 Medical Research Council
- R01 HL109946 NHLBI NIH HHS
- UM1 DK105554 NIDDK NIH HHS
- KL2 TR002542 NCATS NIH HHS
- 203141/Z/16/Z Wellcome Trust
- Department of Health
- FS/14/66/3129 British Heart Foundation
- R01 HL086694 NHLBI NIH HHS
- R35 HL135824 NHLBI NIH HHS
- RG/18/13/33946 British Heart Foundation
- T32 HG000040 NHGRI NIH HHS
- R01 HL146860 NHLBI NIH HHS
- HHSN268201700002C NHLBI NIH HHS
- SP/19/2/34462 British Heart Foundation
- HHSN268201700004I NHLBI NIH HHS
- RE/13/1/30181 British Heart Foundation
- K08 HL153950 NHLBI NIH HHS
- HHSN268201700005C NHLBI NIH HHS
- HHSN268201700001C NHLBI NIH HHS
- HHSN268201700003C NHLBI NIH HHS
- HHSN268201700004C NHLBI NIH HHS
- Wellcome Trust
- HHSN268201700002I NHLBI NIH HHS
- HHSN268201700005I NHLBI NIH HHS
- K08 HL153937 NHLBI NIH HHS
- HHSN268201700003I NHLBI NIH HHS
- RG/13/13/30194 British Heart Foundation
- T32 HL007604 NHLBI NIH HHS
- SP/09/002 British Heart Foundation
- G0800270 Medical Research Council
- K08 HG010155 NHGRI NIH HHS
- MC_QA137853 Medical Research Council
- K.G.A. has received support from the American Heart Association Institute for Precision Cardiovascular Medicine (17IFUNP3384001), a KL2/Catalyst Medical Research Investigator Training (CMeRIT) award from the Harvard Catalyst (KL2 TR002542), and the NIH (1K08HL153937).
- B.N.W is supported by the National Science Foundation Graduate Research Program (DGE 1256260).
- I.S. is supported by a Precision Health Scholars Award from the University of Michigan Medical School.
- I.K., S.Ko., and K.It. are funded by the Japan Agency for Medical Research and Development, AMED, under Grant Numbers JP16ek0109070h0003, JP18kk0205008h0003, JP18kk0205001s0703, JP20km0405209, and JP20ek0109487. The BioBank Japan is supported by AMED under Grant Number JP20km0605001.
- J.L.M.B. acknowledges research support from NIH R01HL125863, American Heart Association (A14SFRN20840000), the Swedish Research Council (2018-02529) and Heart Lung Foundation (20170265) and the Foundation Leducq (PlaqueOmics: Novel Roles of Smooth Muscle and Other Matrix Producing Cells in Atherosclerotic Plaque Stability and Rupture, 18CVD02.
- P.S.dV was supported by American Heart Association grant number 18CDA34110116 and National Heart, Lung, and Blood Institute grant R01HL146860. The Atherosclerosis Risk in Communities study has been funded in whole or in part with Federal funds from the National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services (contract numbers HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700004I and HHSN268201700005I), R01HL087641, R01HL059367 and R01HL086694; National Human Genome Research Institute contract U01HG004402; and National Institutes of Health contract HHSN268200625226C. The authors thank the staff and participants of the ARIC study for their important contributions. Infrastructure was partly supported by Grant Number UL1RR025005, a component of the National Institutes of Health and NIH Roadmap for Medical Research.
- O.G. has received funding from the British Heart Foundation (BHF) (FS/14/66/3129).
- T.K. is supported by the Corona-Foundation (Junior Research Group Translational Cardiovascular Genomics) and the German Research Foundation (DFG) as part of the Sonderforschungsbereich SFB 1123 (B02).
- D.S.A. has received support from a training grant from the NIH (T32HL007604).
- N.P.B., M.C.C., J.F., and D.-K.J. have been funded by the National Institute of Diabetes and Digestive and Kidney Diseases (2UM1DK105554).
- A.V.K. has been funded by 1K08HG010155 from the National Human Genome Research Institute.
- C.P.N. and T.R.W received funding from the British Heart Foundation (SP/16/4/32697).
- The Trøndelag Health Study (The HUNT Study) is a collaboration between HUNT Research Centre (Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology), Trøndelag County Council, Central Norway Regional Health Authority, and the Norwegian Institute of Public Health. The K.G. Jebsen Center for Genetic Epidemiology is financed by Stiftelsen Kristian Gerhard Jebsen; Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology; and Central Norway Regional Health Authority. Whole genome sequencing for the HUNT study was funded by HL109946.
- O.M. was funded by the Swedish Heart- and Lung Foundation, the Swedish Research Council, the European Research Council ERC-AdG-2019-885003 and Lund University Infrastructure grant ”Malmö population-based cohorts” (STYR 2019/2046).
- This work was supported by the European Commission (HEALTH-F2–2013-601456) and the TriPartite Immunometabolism Consortium [TrIC]- NovoNordisk Foundation (NNF15CC0018486), VIAgenomics (SP/19/2/344612), the British Heart Foundation, a Wellcome Trust core award (M.F., H.W., 203141/Z/16/Z) and support from the NIHR Oxford Biomedical Research Centre. M.F. and H.W. are members of the Oxford BHF Centre of Research Excellence (RE/13/1/30181). The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health.
- J.D. is a British Heart Foundation Professor, European Research Council Senior Investigator, and National Institute for Health Research (NIHR) Senior Investigator.
- J.C.H. acknowledges personal funding from the British Heart Foundation (FS/14/55/30806) and is a member of the Oxford BHF Centre of Research Excellence (RE/13/1/30181).
- R.C. has received funding from the British Heart Foundation and British Heart Foundation Centre of Research Excellence.
- This research was supported by BHF (SP/13/2/30111) and conducted using the UK Biobank Resource (application number 9922).
- The GerMIFs gratefully acknowledge the support of the Bavarian State Ministry of Health and Care, furthermore founded this work within its framework of DigiMed Bayern (grant No: DMB-1805-0001), the German Federal Ministry of Education and Research (BMBF) within the framework of ERA-NET on Cardiovascular Disease (Druggable-MI-genes: 01KL1802), within the scheme of target validation (BlockCAD: 16GW0198K), within the framework of the e:Med research and funding concept (AbCD-Net: 01ZX1706C), the British Heart Foundation (BHF)/German Centre of Cardiovascular Research (DZHK)-collaboration (VIAgenomics) and the German Research Foundation (DFG) as part of the Sonderforschungsbereich SFB 1123 (B02) and the Sonderforschungsbereich SFB TRR 267 (B05).
- C.J.W. is funded by NIH grant R35-HL135824.
- This work was supported by the British Heart Foundation (BHF) grant RG/14/5/30893 (P.D.) and forms part of the research themes contributing to the translational research portfolios of the Barts Biomedical Research Centre funded by the UK National Institute for Health Research (NIHR).
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Affiliation(s)
- Krishna G Aragam
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA.
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Tao Jiang
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Anuj Goel
- Radcliffe Department of Medicine, Division of Cardiovascular Medicine, University of Oxford, Oxford, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Stavroula Kanoni
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Brooke N Wolford
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Deepak S Atri
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Divisions of Cardiovascular Medicine and Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Elle M Weeks
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Minxian Wang
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - George Hindy
- Department of Population Medicine, Qatar University College of Medicine, Doha, Qatar
| | - Wei Zhou
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Christopher Grace
- Radcliffe Department of Medicine, Division of Cardiovascular Medicine, University of Oxford, Oxford, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Carolina Roselli
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Nicholas A Marston
- TIMI Study Group, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Frederick K Kamanu
- TIMI Study Group, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ida Surakka
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, USA
| | - Loreto Muñoz Venegas
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany
- German Research Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Lübeck/Kiel, Lübeck, Germany
| | - Paul Sherliker
- Medical Research Council Population Health Research Unit, CTSU-Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Satoshi Koyama
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Tsurumi-ku, Yokohama, Japan
| | - Kazuyoshi Ishigaki
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Tsurumi-ku, Yokohama, Japan
| | - Bjørn O Åsvold
- Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, NTNU, Trondheim, Norway
- HUNT Research Centre, Norwegian University of Science and Technology, Levanger, Norway
- Department of Endocrinology, Clinic of Medicine, St. Olavs Hospital, Trondheim, Norway
| | - Michael R Brown
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Ben Brumpton
- Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, NTNU, Trondheim, Norway
- HUNT Research Centre, Norwegian University of Science and Technology, Levanger, Norway
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Olga Giannakopoulou
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Panagiota Giardoglou
- Department of Nutrition-Dietetics, School of Health Science and Education, Harokopio University, Athens, Greece
| | - Daniel F Gudbjartsson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Ulrich Güldener
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany
| | - Syed M Ijlal Haider
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany
- German Research Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Lübeck/Kiel, Lübeck, Germany
| | | | - Maysson Ibrahim
- CTSU-Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Adnan Kastrati
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany
- German Research Center for Cardiovascular Research (DZHK e.V.), Partner Site Munich Heart Alliance, Munich, Germany
| | - Thorsten Kessler
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany
- German Research Center for Cardiovascular Research (DZHK e.V.), Partner Site Munich Heart Alliance, Munich, Germany
| | | | - Tomasz Konopka
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Ling Li
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany
| | - Lijiang Ma
- Department of Genetics and Genomic Science, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Zena and Michael A. Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Thomas Meitinger
- German Research Center for Cardiovascular Research (DZHK e.V.), Partner Site Munich Heart Alliance, Munich, Germany
- Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Klinikum Rechts der Isar, Institute of Human Genetics, Technical University of Munich, Munich, Germany
| | - Sören Mucha
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany
- German Research Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Lübeck/Kiel, Lübeck, Germany
| | - Matthias Munz
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany
- German Research Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Lübeck/Kiel, Lübeck, Germany
| | - Federico Murgia
- CTSU-Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Jonas B Nielsen
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, USA
- Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, NTNU, Trondheim, Norway
| | - Markus M Nöthen
- School of Medicine and University Hospital Bonn, Institute of Human Genetics, University of Bonn, Bonn, Germany
| | - Shichao Pang
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany
| | - Tobias Reinberger
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany
- German Research Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Lübeck/Kiel, Lübeck, Germany
| | - Gavin Schnitzler
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Damian Smedley
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | | | - Moritz von Scheidt
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany
- German Research Center for Cardiovascular Research (DZHK e.V.), Partner Site Munich Heart Alliance, Munich, Germany
| | - Jacob C Ulirsch
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, MA, USA
| | - David O Arnar
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- Department of Internal Medicine, Division of Cardiology, Landspitali-National University Hospital of Iceland, Hringbraut, Reykjavik, Iceland
| | - Noël P Burtt
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Maria C Costanzo
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jason Flannick
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA
| | - Kaoru Ito
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Tsurumi-ku, Yokohama, Japan
| | - Dong-Keun Jang
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Yoichiro Kamatani
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Amit V Khera
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Issei Komuro
- Department of Cardiovascular Medicine, The University of Tokyo, Tokyo, Japan
| | - Iftikhar J Kullo
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Luca A Lotta
- Regeneron Genetics Center, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Christopher P Nelson
- Department of Cardiovascular Sciences and NIHR Leicester Biomedical Research Centre, University of Leicester, Glenfield Hospital, Leicester, UK
| | - Robert Roberts
- Cardiovascular Genomics and Genetics, University of Arizona College of Medicin, Phoenix, AZ, USA
| | - Gudmundur Thorgeirsson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- Department of Internal Medicine, Division of Cardiology, Landspitali-National University Hospital of Iceland, Hringbraut, Reykjavik, Iceland
| | - Unnur Thorsteinsdottir
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Thomas R Webb
- Department of Cardiovascular Sciences and NIHR Leicester Biomedical Research Centre, University of Leicester, Glenfield Hospital, Leicester, UK
| | - Aris Baras
- Regeneron Genetics Center, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Johan L M Björkegren
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Integrated Cardio Metabolic Centre, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden
- Clinical Gene Networks AB, Stockholm, Sweden
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - George Dedoussis
- Department of Nutrition-Dietetics, School of Health Science and Education, Harokopio University, Athens, Greece
| | - Hilma Holm
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
| | - Kristian Hveem
- Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, NTNU, Trondheim, Norway
- HUNT Research Centre, Norwegian University of Science and Technology, Levanger, Norway
| | - Olle Melander
- Department of Clinical Sciences in Malmö, Lund University, Malmö, Sweden
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | | | - Loukianos S Rallidis
- Second Department of Cardiology, Medical School, National and Kapodistrian University of Athens, University General Hospital Attikon, Athens, Greece
| | - Arno Ruusalepp
- Department of Cardiac Surgery, Tartu University Hospital and Institute of Clinical Medicine, Tartu University, Tartu, Estonia
| | - Marc S Sabatine
- TIMI Study Group, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Kari Stefansson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Pierre Zalloua
- Harvard T.H.Chan School of Public Health, Boston, MA, USA
- College of Medicine and Health Sciences, Khalifa University, Abu Dhabi, UAE
| | - Patrick T Ellinor
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Martin Farrall
- Radcliffe Department of Medicine, Division of Cardiovascular Medicine, University of Oxford, Oxford, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - John Danesh
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- National Institute for Health and Care Research Cambridge Biomedical Research Centre, Cambridge University Hospitals, Cambridge, UK
- The National Institute for Health and Care Research Blood and Transplant Unit (NIHR BTRU) in Donor Health and Genomics, University of Cambridge, Cambridge, UK
- Human Genetics, Wellcome Sanger Institute, Saffron Walden, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, Division of Cardiovascular Medicine, Addenbrooke's Hospital, Cambridge, UK
| | - Christian T Ruff
- TIMI Study Group, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Hilary K Finucane
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jemma C Hopewell
- CTSU-Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Robert Clarke
- CTSU-Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Rajat M Gupta
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Divisions of Cardiovascular Medicine and Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jeanette Erdmann
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany
- German Research Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Lübeck/Kiel, Lübeck, Germany
| | - Nilesh J Samani
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Heribert Schunkert
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany
- German Research Center for Cardiovascular Research (DZHK e.V.), Partner Site Munich Heart Alliance, Munich, Germany
| | - Hugh Watkins
- Radcliffe Department of Medicine, Division of Cardiovascular Medicine, University of Oxford, Oxford, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Cristen J Willer
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Panos Deloukas
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Princess Al-Jawhara Al-Brahim Centre of Excellence in Research of Hereditary Disorders (PACER-HD), King Abdulaziz University, Jeddah, Saudi Arabia
| | | | - Adam S Butterworth
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
- National Institute for Health and Care Research Cambridge Biomedical Research Centre, Cambridge University Hospitals, Cambridge, UK.
- The National Institute for Health and Care Research Blood and Transplant Unit (NIHR BTRU) in Donor Health and Genomics, University of Cambridge, Cambridge, UK.
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK.
- British Heart Foundation Centre of Research Excellence, Division of Cardiovascular Medicine, Addenbrooke's Hospital, Cambridge, UK.
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Zhang C, Ye Y, Zhao H. Comparison of Methods Utilizing Sex-Specific PRSs Derived From GWAS Summary Statistics. Front Genet 2022; 13:892950. [PMID: 35873490 PMCID: PMC9304553 DOI: 10.3389/fgene.2022.892950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Accepted: 05/23/2022] [Indexed: 11/13/2022] Open
Abstract
The polygenic risk score (PRS) is calculated as the weighted sum of an individual's genotypes and their estimated effect sizes, which is often used to estimate an individual's genetic susceptibility to complex traits and disorders. It is well known that some complex human traits or disorders have sex differences in trait distributions, disease onset, progression, and treatment response, although the underlying mechanisms causing these sex differences remain largely unknown. PRSs for these traits are often based on Genome-Wide Association Studies (GWAS) data with both male and female samples included, ignoring sex differences. In this study, we present a benchmark study using both simulations with various combinations of genetic correlation and sample size ratios between sexes and real data to investigate whether combining sex-specific PRSs can outperform sex-agnostic PRSs on traits showing sex differences. We consider two types of PRS models in our study: single-population PRS models (PRScs, LDpred2) and multiple-population PRS models (PRScsx). For each trait or disorder, the candidate PRSs were calculated based on sex-specific GWAS data and sex-agnostic GWAS data. The simulation results show that applying LDpred2 or PRScsx to sex-specific GWAS data and then combining sex-specific PRSs leads to the highest prediction accuracy when the genetic correlation between sexes is low and the sample sizes for both sexes are balanced and large. Otherwise, the PRS generated by applying LDpred2 or PRScs to sex-agnostic GWAS data is more appropriate. If the sample sizes between sexes are not too small and very unbalanced, combining LDpred2-based sex-specific PRSs to predict on the sex with a larger sample size and combining PRScsx-based sex-specific PRSs to predict on the sex with a smaller size are the preferred strategies. For real data, we considered 19 traits from Genetic Investigation of ANthropometric Traits (GIANT) consortium studies and UK Biobank with both sex-specific GWAS data and sex-agnostic GWAS data. We found that for waist-to-hip ratio (WHR) related traits, accounting for sex differences and incorporating information from the opposite sex could help improve PRS prediction accuracy. Taken together, our findings in this study provide guidance on how to calculate the best PRS for sex-differentiated traits or disorders, especially as the sample size of GWASs grows in the future.
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Affiliation(s)
- Chi Zhang
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, United States
| | - Yixuan Ye
- Program of Computational Biology and Bioinformatics, Yale University, New Haven, CT, United States
| | - Hongyu Zhao
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, United States
- Program of Computational Biology and Bioinformatics, Yale University, New Haven, CT, United States
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Polygenic score development in the era of large-scale biobanks. CELL GENOMICS 2022; 2:100088. [PMID: 36777037 PMCID: PMC9903709 DOI: 10.1016/j.xgen.2021.100088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
In this issue of Cell Genomics, Xu et al. report a comprehensive analysis of the genetics of 26 blood cell traits, leveraging data from two large biobanks to construct and make available machine-learning optimized polygenic scores (PGSs). In addition to delivering insights into the biology and clinical associations of these traits, the authors evaluate and provide recommendations on methods for PGS construction.
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