1
|
Khan A, Kiryluk K. Polygenic scores and their applications in kidney disease. Nat Rev Nephrol 2024:10.1038/s41581-024-00886-2. [PMID: 39271761 DOI: 10.1038/s41581-024-00886-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/06/2024] [Indexed: 09/15/2024]
Abstract
Genome-wide association studies (GWAS) have uncovered thousands of risk variants that individually have small effects on the risk of human diseases, including chronic kidney disease, type 2 diabetes, heart diseases and inflammatory disorders, but cumulatively explain a substantial fraction of disease risk, underscoring the complexity and pervasive polygenicity of common disorders. This complexity poses unique challenges to the clinical translation of GWAS findings. Polygenic scores combine small effects of individual GWAS risk variants across the genome to improve personalized risk prediction. Several polygenic scores have now been developed that exhibit sufficiently large effects to be considered clinically actionable. However, their clinical use is limited by their partial transferability across ancestries and a lack of validated models that combine polygenic, monogenic, family history and clinical risk factors. Moreover, prospective studies are still needed to demonstrate the clinical utility and cost-effectiveness of polygenic scores in clinical practice. Here, we discuss evolving methods for developing polygenic scores, best practices for validating and reporting their performance, and the study designs that will empower their clinical implementation. We specifically focus on the polygenic scores relevant to nephrology and other chronic, complex diseases and review their key limitations, necessary refinements and potential clinical applications.
Collapse
Affiliation(s)
- Atlas Khan
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Krzysztof Kiryluk
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA.
| |
Collapse
|
2
|
Stankovic S, Shekari S, Huang QQ, Gardner EJ, Ivarsdottir EV, Owens NDL, Mavaddat N, Azad A, Hawkes G, Kentistou KA, Beaumont RN, Day FR, Zhao Y, Jonsson H, Rafnar T, Tragante V, Sveinbjornsson G, Oddsson A, Styrkarsdottir U, Gudmundsson J, Stacey SN, Gudbjartsson DF, Kennedy K, Wood AR, Weedon MN, Ong KK, Wright CF, Hoffmann ER, Sulem P, Hurles ME, Ruth KS, Martin HC, Stefansson K, Perry JRB, Murray A. Genetic links between ovarian ageing, cancer risk and de novo mutation rates. Nature 2024:10.1038/s41586-024-07931-x. [PMID: 39261734 DOI: 10.1038/s41586-024-07931-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Accepted: 08/08/2024] [Indexed: 09/13/2024]
Abstract
Human genetic studies of common variants have provided substantial insight into the biological mechanisms that govern ovarian ageing1. Here we report analyses of rare protein-coding variants in 106,973 women from the UK Biobank study, implicating genes with effects around five times larger than previously found for common variants (ETAA1, ZNF518A, PNPLA8, PALB2 and SAMHD1). The SAMHD1 association reinforces the link between ovarian ageing and cancer susceptibility1, with damaging germline variants being associated with extended reproductive lifespan and increased all-cause cancer risk in both men and women. Protein-truncating variants in ZNF518A are associated with shorter reproductive lifespan-that is, earlier age at menopause (by 5.61 years) and later age at menarche (by 0.56 years). Finally, using 8,089 sequenced trios from the 100,000 Genomes Project (100kGP), we observe that common genetic variants associated with earlier ovarian ageing associate with an increased rate of maternally derived de novo mutations. Although we were unable to replicate the finding in independent samples from the deCODE study, it is consistent with the expected role of DNA damage response genes in maintaining the genetic integrity of germ cells. This study provides evidence of genetic links between age of menopause and cancer risk.
Collapse
Affiliation(s)
- Stasa Stankovic
- MRC Epidemiology Unit, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Saleh Shekari
- University of Exeter Medical School, University of Exeter, Exeter, UK
- School of Public Health, Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia
| | - Qin Qin Huang
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | - Eugene J Gardner
- MRC Epidemiology Unit, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | | | - Nick D L Owens
- University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Nasim Mavaddat
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Ajuna Azad
- DNRF Center for Chromosome Stability, Department of Cellular and Molecular Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Gareth Hawkes
- University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Katherine A Kentistou
- MRC Epidemiology Unit, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Robin N Beaumont
- University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Felix R Day
- MRC Epidemiology Unit, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Yajie Zhao
- MRC Epidemiology Unit, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | | | | | | | | | | | | | | | | | | | - Kitale Kennedy
- University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Andrew R Wood
- University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Michael N Weedon
- University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Ken K Ong
- MRC Epidemiology Unit, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Department of Paediatrics, University of Cambridge, Cambridge, UK
| | - Caroline F Wright
- University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Eva R Hoffmann
- DNRF Center for Chromosome Stability, Department of Cellular and Molecular Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | - Matthew E Hurles
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | - Katherine S Ruth
- University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Hilary C Martin
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | | | - John R B Perry
- MRC Epidemiology Unit, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK.
- Metabolic Research Laboratory, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK.
| | - Anna Murray
- University of Exeter Medical School, University of Exeter, Exeter, UK.
| |
Collapse
|
3
|
Kontou PI, Bagos PG. The goldmine of GWAS summary statistics: a systematic review of methods and tools. BioData Min 2024; 17:31. [PMID: 39238044 PMCID: PMC11375927 DOI: 10.1186/s13040-024-00385-x] [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: 02/09/2024] [Accepted: 08/27/2024] [Indexed: 09/07/2024] Open
Abstract
Genome-wide association studies (GWAS) have revolutionized our understanding of the genetic architecture of complex traits and diseases. GWAS summary statistics have become essential tools for various genetic analyses, including meta-analysis, fine-mapping, and risk prediction. However, the increasing number of GWAS summary statistics and the diversity of software tools available for their analysis can make it challenging for researchers to select the most appropriate tools for their specific needs. This systematic review aims to provide a comprehensive overview of the currently available software tools and databases for GWAS summary statistics analysis. We conducted a comprehensive literature search to identify relevant software tools and databases. We categorized the tools and databases by their functionality, including data management, quality control, single-trait analysis, and multiple-trait analysis. We also compared the tools and databases based on their features, limitations, and user-friendliness. Our review identified a total of 305 functioning software tools and databases dedicated to GWAS summary statistics, each with unique strengths and limitations. We provide descriptions of the key features of each tool and database, including their input/output formats, data types, and computational requirements. We also discuss the overall usability and applicability of each tool for different research scenarios. This comprehensive review will serve as a valuable resource for researchers who are interested in using GWAS summary statistics to investigate the genetic basis of complex traits and diseases. By providing a detailed overview of the available tools and databases, we aim to facilitate informed tool selection and maximize the effectiveness of GWAS summary statistics analysis.
Collapse
Affiliation(s)
| | - Pantelis G Bagos
- Department of Computer Science and Biomedical Informatics, University of Thessaly, 35131, Lamia, Greece.
| |
Collapse
|
4
|
Visconti A, Rossi N, Bondt A, Ederveen AH, Thareja G, Koeleman CAM, Stephan N, Halama A, Lomax-Browne HJ, Pickering MC, Zhou XJ, Wuhrer M, Suhre K, Falchi M. The genetics and epidemiology of N- and O-immunoglobulin A glycomics. Genome Med 2024; 16:96. [PMID: 39123268 PMCID: PMC11312925 DOI: 10.1186/s13073-024-01369-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2024] [Accepted: 07/26/2024] [Indexed: 08/12/2024] Open
Abstract
BACKGROUND Immunoglobulin (Ig) glycosylation modulates the immune response and plays a critical role in ageing and diseases. Studies have mainly focused on IgG glycosylation, and little is known about the genetics and epidemiology of IgA glycosylation. METHODS We generated, using a novel liquid chromatography-mass spectrometry method, the first large-scale IgA glycomics dataset in serum from 2423 twins, encompassing 71 N- and O-glycan species. RESULTS We showed that, despite the lack of a direct genetic template, glycosylation is highly heritable, and that glycopeptide structures are sex-specific, and undergo substantial changes with ageing. We observe extensive correlations between the IgA and IgG glycomes, and, exploiting the twin design, show that they are predominantly influenced by shared genetic factors. A genome-wide association study identified eight loci associated with both the IgA and IgG glycomes (ST6GAL1, ELL2, B4GALT1, ABCF2, TMEM121, SLC38A10, SMARCB1, and MGAT3) and two novel loci specifically modulating IgA O-glycosylation (C1GALT1 and ST3GAL1). Validation of our findings in an independent cohort of 320 individuals from Qatar showed that the underlying genetic architecture is conserved across ancestries. CONCLUSIONS Our study delineates the genetic landscape of IgA glycosylation and provides novel potential functional links with the aetiology of complex immune diseases, including genetic factors involved in IgA nephropathy risk.
Collapse
Affiliation(s)
- Alessia Visconti
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
- Center for Biostatistics, Epidemiology and Public Health, Department of Clinical and Biological Sciences, University of Turin, Turin, Italy
| | - Niccolò Rossi
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Albert Bondt
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands
| | - Agnes Hipgrave Ederveen
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands
| | - Gaurav Thareja
- Department of Biophysics and Physiology, Weill Cornell Medicine-Qatar, Doha, Qatar
| | - Carolien A M Koeleman
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands
| | - Nisha Stephan
- Department of Biophysics and Physiology, Weill Cornell Medicine-Qatar, Doha, Qatar
| | - Anna Halama
- Department of Biophysics and Physiology, Weill Cornell Medicine-Qatar, Doha, Qatar
| | - Hannah J Lomax-Browne
- Centre for Inflammatory Disease, Department of Immunology and Inflammation, Imperial College London, London, UK
| | - Matthew C Pickering
- Centre for Inflammatory Disease, Department of Immunology and Inflammation, Imperial College London, London, UK
| | - Xu-Jie Zhou
- Renal Division, Peking University First Hospital, Beijing, China
- Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Ministry of Education, Peking University, Beijing, China
| | - Manfred Wuhrer
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands
| | - Karsten Suhre
- Department of Biophysics and Physiology, Weill Cornell Medicine-Qatar, Doha, Qatar
| | - Mario Falchi
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
| |
Collapse
|
5
|
Robertson CC, Elgamal RM, Henry-Kanarek BA, Arvan P, Chen S, Dhawan S, Eizirik DL, Kaddis JS, Vahedi G, Parker SCJ, Gaulton KJ, Soleimanpour SA. Untangling the genetics of beta cell dysfunction and death in type 1 diabetes. Mol Metab 2024; 86:101973. [PMID: 38914291 PMCID: PMC11283044 DOI: 10.1016/j.molmet.2024.101973] [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: 03/14/2024] [Revised: 06/18/2024] [Accepted: 06/19/2024] [Indexed: 06/26/2024] Open
Abstract
BACKGROUND Type 1 diabetes (T1D) is a complex multi-system disease which arises from both environmental and genetic factors, resulting in the destruction of insulin-producing pancreatic beta cells. Over the past two decades, human genetic studies have provided new insight into the etiology of T1D, including an appreciation for the role of beta cells in their own demise. SCOPE OF REVIEW Here, we outline models supported by human genetic data for the role of beta cell dysfunction and death in T1D. We highlight the importance of strong evidence linking T1D genetic associations to bona fide candidate genes for mechanistic and therapeutic consideration. To guide rigorous interpretation of genetic associations, we describe molecular profiling approaches, genomic resources, and disease models that may be used to construct variant-to-gene links and to investigate candidate genes and their role in T1D. MAJOR CONCLUSIONS We profile advances in understanding the genetic causes of beta cell dysfunction and death at individual T1D risk loci. We discuss how genetic risk prediction models can be used to address disease heterogeneity. Further, we present areas where investment will be critical for the future use of genetics to address open questions in the development of new treatment and prevention strategies for T1D.
Collapse
Affiliation(s)
- Catherine C Robertson
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA; Center for Precision Health Research, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Ruth M Elgamal
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Belle A Henry-Kanarek
- Department of Internal Medicine and Division of Metabolism, Endocrinology, and Diabetes, University of Michigan, Ann Arbor, MI, USA
| | - Peter Arvan
- Department of Internal Medicine and Division of Metabolism, Endocrinology, and Diabetes, University of Michigan, Ann Arbor, MI, USA
| | - Shuibing Chen
- Department of Surgery, Weill Cornell Medicine, New York, NY, USA; Center for Genomic Health, Weill Cornell Medicine, New York, NY, USA
| | - Sangeeta Dhawan
- Department of Translational Research and Cellular Therapeutics, Arthur Riggs Diabetes and Metabolism Research Institute, City of Hope, Duarte, CA, USA
| | - Decio L Eizirik
- ULB Center for Diabetes Research, Université Libre de Bruxelles, Brussels, Belgium
| | - John S Kaddis
- Department of Diabetes and Cancer Discovery Science, Arthur Riggs Diabetes and Metabolism Research Institute, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Golnaz Vahedi
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Stephen C J Parker
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA; Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA; Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
| | - Kyle J Gaulton
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA.
| | - Scott A Soleimanpour
- Department of Internal Medicine and Division of Metabolism, Endocrinology, and Diabetes, University of Michigan, Ann Arbor, MI, USA.
| |
Collapse
|
6
|
Castaldi PJ, Sauler M. Molecular Characterization of the Distal Lung: Novel Insights from Chronic Obstructive Pulmonary Disease Omics. Am J Respir Crit Care Med 2024; 210:147-154. [PMID: 38701385 PMCID: PMC11273319 DOI: 10.1164/rccm.202310-1972pp] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 05/02/2024] [Indexed: 05/05/2024] Open
Affiliation(s)
- Peter J. Castaldi
- Channing Division of Network Medicine and
- Division of General Internal Medicine and Primary Care, Brigham and Women’s Hospital, Boston, Massachusetts; and
| | - Maor Sauler
- Division of Pulmonary, Critical Care, and Sleep Medicine, School of Medicine, Yale University, New Haven, Connecticut
| |
Collapse
|
7
|
He J, Perera D, Wen W, Ping J, Li Q, Lyu L, Chen Z, Shu X, Long J, Cai Q, Shu XO, Zheng W, Long Q, Guo X. Enhancing Disease Risk Gene Discovery by Integrating Transcription Factor-Linked Trans-located Variants into Transcriptome-Wide Association Analyses. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.10.10.23295443. [PMID: 37873299 PMCID: PMC10593059 DOI: 10.1101/2023.10.10.23295443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Transcriptome-wide association studies (TWAS) have been successful in identifying disease susceptibility genes by integrating cis-variants predicted gene expression with genome-wide association studies (GWAS) data. However, trans-located variants for predicting gene expression remain largely unexplored. Here, we introduce transTF-TWAS, which incorporates transcription factor (TF)-linked trans-located variants to enhance model building. Using data from the Genotype-Tissue Expression project, we predict gene expression and alternative splicing and applied these models to large GWAS datasets for breast, prostate, and lung cancers. We demonstrate that transTF-TWAS outperforms other existing TWAS approaches in both constructing gene prediction models and identifying disease-associated genes, as evidenced by simulations and real data analysis. Our transTF-TWAS approach significantly contributes to the discovery of disease risk genes. Findings from this study have shed new light on several genetically driven key regulators and their associated regulatory networks underlying disease susceptibility.
Collapse
|
8
|
Ramírez J, van Duijvenboden S, Young WJ, Chen Y, Usman T, Orini M, Lambiase PD, Tinker A, Bell CG, Morris AP, Munroe PB. Fine mapping of candidate effector genes for heart rate. Hum Genet 2024:10.1007/s00439-024-02684-z. [PMID: 38969939 DOI: 10.1007/s00439-024-02684-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Accepted: 06/19/2024] [Indexed: 07/07/2024]
Abstract
An elevated resting heart rate (RHR) is associated with increased cardiovascular mortality. Genome-wide association studies (GWAS) have identified > 350 loci. Uniquely, in this study we applied genetic fine-mapping leveraging tissue specific chromatin segmentation and colocalization analyses to identify causal variants and candidate effector genes for RHR. We used RHR GWAS summary statistics from 388,237 individuals of European ancestry from UK Biobank and performed fine mapping using publicly available genomic annotation datasets. High-confidence causal variants (accounting for > 75% posterior probability) were identified, and we collated candidate effector genes using a multi-omics approach that combined evidence from colocalisation with molecular quantitative trait loci (QTLs), and long-range chromatin interaction analyses. Finally, we performed druggability analyses to investigate drug repurposing opportunities. The fine mapping pipeline indicated 442 distinct RHR signals. For 90 signals, a single variant was identified as a high-confidence causal variant, of which 22 were annotated as missense. In trait-relevant tissues, 39 signals colocalised with cis-expression QTLs (eQTLs), 3 with cis-protein QTLs (pQTLs), and 75 had promoter interactions via Hi-C. In total, 262 candidate genes were highlighted (79% had promoter interactions, 15% had a colocalised eQTL, 8% had a missense variant and 1% had a colocalised pQTL), and, for the first time, enrichment in nervous system pathways. Druggability analyses highlighted ACHE, CALCRL, MYT1 and TDP1 as potential targets. Our genetic fine-mapping pipeline prioritised 262 candidate genes for RHR that warrant further investigation in functional studies, and we provide potential therapeutic targets to reduce RHR and cardiovascular mortality.
Collapse
Affiliation(s)
- Julia Ramírez
- Aragon Institute of Engineering Research, University of Zaragoza, Zaragoza, Spain.
- Centro de Investigación Biomédica en Red - Bioingeniería, Biomateriales y Nanomedicina, Zaragoza, Spain.
- William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK.
| | - Stefan van Duijvenboden
- William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK.
- Nuffield Department of Population Health, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF, UK.
- Institute of Cardiovascular Science, University College London, London, UK.
| | - William J Young
- William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
- Barts Heart Centre, St Bartholomew's Hospital, London, EC1A 7BE, UK
| | - Yutang Chen
- William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
- Department of Environmental Systems Science, ETH Zurich, Zurich, Switzerland
| | | | - Michele Orini
- Institute of Cardiovascular Science, University College London, London, UK
| | - Pier D Lambiase
- Institute of Cardiovascular Science, University College London, London, UK
- Barts Heart Centre, St Bartholomew's Hospital, London, EC1A 7BE, UK
| | - Andrew Tinker
- William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
- Barts Cardiovascular Biomedical Research Centre, National Institute of Health and Care Research, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Christopher G Bell
- William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Andrew P Morris
- Centre for Musculoskeletal Research, The University of Manchester, Manchester, UK
- National Institute of Health and Care Research, Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | - Patricia B Munroe
- William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK.
- Khalifa University, Abu Dhabi, United Arab Emirates.
- Barts Cardiovascular Biomedical Research Centre, National Institute of Health and Care Research, Queen Mary University of London, London, EC1M 6BQ, UK.
| |
Collapse
|
9
|
Monistrol-Mula A, Diaz-Torres S, Felez-Nobrega M, Haro JM, Medland SE, Mitchell BL. Genetic analyses point to alterations in immune-related pathways underpinning the association between psychiatric disorders and COVID-19. Mol Psychiatry 2024:10.1038/s41380-024-02643-0. [PMID: 38956374 DOI: 10.1038/s41380-024-02643-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 06/17/2024] [Accepted: 06/21/2024] [Indexed: 07/04/2024]
Abstract
Current literature suggests that people with psychiatric disorders have a higher risk of COVID-19 infection and a worse prognosis of the disease. We aimed to study the genetic contribution to these associations across seven psychiatric disorders as well as a general psychopathology factor (P-factor) and determine whether these are unique or shared across psychiatric disorders using statistical genetic techniques. Using the largest available genome-wide association studies (GWAS), we found a significant genetic overlap between depression, ADHD, PTSD, and the P-factor with both COVID-19 infection and hospitalization, and between anxiety and COVID-19 hospitalization. We used pairwise GWAS to examine this overlap on a fine-grained scale and identified specific regions of the genome shared between several psychiatric disorders, the P-factor, and COVID-19. Gene-based analysis in these genomic regions suggested possible links with immune-related pathways such as thyroid homeostasis, inflammation, and stress response. Finally, we show preliminary evidence for causal associations between depression, ADHD, PTSD, and the P-factor, and higher COVID-19 infection and hospitalization using Mendelian Randomization and Latent Causal Variable methods. Our results support the hypothesis that the relationship between psychiatric disorders and COVID-19 risk is likely due to shared alterations in immune-related pathways and is not a result of environmental factors alone, shedding light on potentially viable therapeutic targets.
Collapse
Affiliation(s)
- Anna Monistrol-Mula
- Group of Epidemiology of Psychiatric disorders and Ageing, Sant Joan de Déu Research Institute, Sant Boi de Llobregat, Barcelona, Spain.
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain.
- Department of Medicine, University of Barcelona, Barcelona, Spain.
- Mental Health and Neuroscience program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
| | - Santiago Diaz-Torres
- Mental Health and Neuroscience program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Mireia Felez-Nobrega
- Group of Epidemiology of Psychiatric disorders and Ageing, Sant Joan de Déu Research Institute, Sant Boi de Llobregat, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Josep Maria Haro
- Group of Epidemiology of Psychiatric disorders and Ageing, Sant Joan de Déu Research Institute, Sant Boi de Llobregat, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
- Department of Medicine, University of Barcelona, Barcelona, Spain
| | - Sarah E Medland
- Mental Health and Neuroscience program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Psychology, The University of Queensland, Brisbane, QLD, Australia
- School of Psychology and Counselling, Queensland University of Technology, Brisbane, QLD, Australia
| | - Brittany L Mitchell
- Mental Health and Neuroscience program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, University of Queensland, Brisbane, QLD, Australia
| |
Collapse
|
10
|
Kentistou KA, Kaisinger LR, Stankovic S, Vaudel M, Mendes de Oliveira E, Messina A, Walters RG, Liu X, Busch AS, Helgason H, Thompson DJ, Santoni F, Petricek KM, Zouaghi Y, Huang-Doran I, Gudbjartsson DF, Bratland E, Lin K, Gardner EJ, Zhao Y, Jia RY, Terao C, Riggan MJ, Bolla MK, Yazdanpanah M, Yazdanpanah N, Bradfield JP, Broer L, Campbell A, Chasman DI, Cousminer DL, Franceschini N, Franke LH, Girotto G, He C, Järvelin MR, Joshi PK, Kamatani Y, Karlsson R, Luan J, Lunetta KL, Mägi R, Mangino M, Medland SE, Meisinger C, Noordam R, Nutile T, Concas MP, Polašek O, Porcu E, Ring SM, Sala C, Smith AV, Tanaka T, van der Most PJ, Vitart V, Wang CA, Willemsen G, Zygmunt M, Ahearn TU, Andrulis IL, Anton-Culver H, Antoniou AC, Auer PL, Barnes CLK, Beckmann MW, Berrington de Gonzalez A, Bogdanova NV, Bojesen SE, Brenner H, Buring JE, Canzian F, Chang-Claude J, Couch FJ, Cox A, Crisponi L, Czene K, Daly MB, Demerath EW, Dennis J, Devilee P, De Vivo I, Dörk T, Dunning AM, Dwek M, Eriksson JG, Fasching PA, Fernandez-Rhodes L, Ferreli L, Fletcher O, Gago-Dominguez M, García-Closas M, García-Sáenz JA, González-Neira A, Grallert H, Guénel P, Haiman CA, Hall P, Hamann U, Hakonarson H, Hart RJ, Hickey M, Hooning MJ, Hoppe R, Hopper JL, Hottenga JJ, Hu FB, Huebner H, Hunter DJ, Jernström H, John EM, Karasik D, Khusnutdinova EK, Kristensen VN, Lacey JV, Lambrechts D, Launer LJ, Lind PA, Lindblom A, Magnusson PKE, Mannermaa A, McCarthy MI, Meitinger T, Menni C, Michailidou K, Millwood IY, Milne RL, Montgomery GW, Nevanlinna H, Nolte IM, Nyholt DR, Obi N, O'Brien KM, Offit K, Oldehinkel AJ, Ostrowski SR, Palotie A, Pedersen OB, Peters A, Pianigiani G, Plaseska-Karanfilska D, Pouta A, Pozarickij A, Radice P, Rennert G, Rosendaal FR, Ruggiero D, Saloustros E, Sandler DP, Schipf S, Schmidt CO, Schmidt MK, Small K, Spedicati B, Stampfer M, Stone J, Tamimi RM, Teras LR, Tikkanen E, Turman C, Vachon CM, Wang Q, Winqvist R, Wolk A, Zemel BS, Zheng W, van Dijk KW, Alizadeh BZ, Bandinelli S, Boerwinkle E, Boomsma DI, Ciullo M, Chenevix-Trench G, Cucca F, Esko T, Gieger C, Grant SFA, Gudnason V, Hayward C, Kolčić I, Kraft P, Lawlor DA, Martin NG, Nøhr EA, Pedersen NL, Pennell CE, Ridker PM, Robino A, Snieder H, Sovio U, Spector TD, Stöckl D, Sudlow C, Timpson NJ, Toniolo D, Uitterlinden A, Ulivi S, Völzke H, Wareham NJ, Widen E, Wilson JF, Pharoah PDP, Li L, Easton DF, Njølstad PR, Sulem P, Murabito JM, Murray A, Manousaki D, Juul A, Erikstrup C, Stefansson K, Horikoshi M, Chen Z, Farooqi IS, Pitteloud N, Johansson S, Day FR, Perry JRB, Ong KK. Understanding the genetic complexity of puberty timing across the allele frequency spectrum. Nat Genet 2024; 56:1397-1411. [PMID: 38951643 PMCID: PMC11250262 DOI: 10.1038/s41588-024-01798-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 05/13/2024] [Indexed: 07/03/2024]
Abstract
Pubertal timing varies considerably and is associated with later health outcomes. We performed multi-ancestry genetic analyses on ~800,000 women, identifying 1,080 signals for age at menarche. Collectively, these explained 11% of trait variance in an independent sample. Women at the top and bottom 1% of polygenic risk exhibited ~11 and ~14-fold higher risks of delayed and precocious puberty, respectively. We identified several genes harboring rare loss-of-function variants in ~200,000 women, including variants in ZNF483, which abolished the impact of polygenic risk. Variant-to-gene mapping approaches and mouse gonadotropin-releasing hormone neuron RNA sequencing implicated 665 genes, including an uncharacterized G-protein-coupled receptor, GPR83, which amplified the signaling of MC3R, a key nutritional sensor. Shared signals with menopause timing at genes involved in DNA damage response suggest that the ovarian reserve might signal centrally to trigger puberty. We also highlight body size-dependent and independent mechanisms that potentially link reproductive timing to later life disease.
Collapse
Affiliation(s)
- Katherine A Kentistou
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
| | - Lena R Kaisinger
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
| | - Stasa Stankovic
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
| | - Marc Vaudel
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Genetics and Bioinformatics, Health Data and Digitalization, Norwegian Institute of Public Health, Oslo, Norway
| | - Edson Mendes de Oliveira
- University of Cambridge Metabolic Research Laboratories and NIHR Cambridge Biomedical Research Centre, Wellcome-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK
| | - Andrea Messina
- Division of Endocrinology, Diabetology, and Metabolism, Lausanne University Hospital, Lausanne, Switzerland
- Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Robin G Walters
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Xiaoxi Liu
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Alexander S Busch
- Department of General Pediatrics, University of Münster, Münster, Germany
- Department of Growth and Reproduction, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark
| | - Hannes Helgason
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Deborah J Thompson
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Federico Santoni
- Division of Endocrinology, Diabetology, and Metabolism, Lausanne University Hospital, Lausanne, Switzerland
- Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Konstantin M Petricek
- Charité Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Pharmacology, Berlin, Germany
| | - Yassine Zouaghi
- Division of Endocrinology, Diabetology, and Metabolism, Lausanne University Hospital, Lausanne, Switzerland
- Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Isabel Huang-Doran
- University of Cambridge Metabolic Research Laboratories and NIHR Cambridge Biomedical Research Centre, Wellcome-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK
| | - Daniel F Gudbjartsson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Eirik Bratland
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - Kuang Lin
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Eugene J Gardner
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
| | - Yajie Zhao
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
| | - Raina Y Jia
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
- Department of Applied Genetics, The School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
| | - Marjorie J Riggan
- Department of Gynecology, Duke University Medical Center, Durham, NC, USA
| | - Manjeet K Bolla
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Mojgan Yazdanpanah
- Research Center of the Sainte-Justine University Hospital, University of Montreal, Montreal, Quebec, Canada
| | - Nahid Yazdanpanah
- Research Center of the Sainte-Justine University Hospital, University of Montreal, Montreal, Quebec, Canada
| | - Jonathan P Bradfield
- Quantinuum Research, Wayne, PA, USA
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Linda Broer
- Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Diana L Cousminer
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Lude H Franke
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Giorgia Girotto
- Institute for Maternal and Child Health-IRCCS 'Burlo Garofolo', Trieste, Italy
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy
| | - Chunyan He
- Department of Internal Medicine, Division of Medical Oncology, University of Kentucky College of Medicine, Lexington, KY, USA
- Cancer Prevention and Control Research Program, Markey Cancer Center, University of Kentucky, Lexington, KY, USA
| | - Marjo-Riitta Järvelin
- Department of Epidemiology and Biostatistics, MRC Health Protection Agency (HPA) Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Institute of Health Sciences, University of Oulu, Oulu, Finland
- Biocenter Oulu, University of Oulu, Oulu, Finland
- Unit of Primary Care, Oulu University Hospital, Oulu, Finland
- Department of Children and Young People and Families, National Institute for Health and Welfare, Oulu, Finland
| | - Peter K Joshi
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland
| | - Yoichiro Kamatani
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Robert Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Jian'an Luan
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
| | - Kathryn L Lunetta
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- NHLBI's and Boston University's Framingham Heart Study, Framingham, MA, USA
| | - Reedik Mägi
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
- NIHR Biomedical Research Centre at Guy's and St. Thomas' Foundation Trust, London, UK
| | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- School of Psychology, University of Queensland, Brisbane, Queensland, Australia
- Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia
| | - Christa Meisinger
- Epidemiology, Medical Faculty, University of Augsburg, University Hospital of Augsburg, Augsburg, Germany
| | - Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands
| | - Teresa Nutile
- Institute of Genetics and Biophysics 'A. Buzzati-Traverso', CNR, Naples, Italy
| | - Maria Pina Concas
- Institute for Maternal and Child Health-IRCCS 'Burlo Garofolo', Trieste, Italy
| | - Ozren Polašek
- University of Split School of Medicine, Split, Croatia
- Algebra University College, Zagreb, Croatia
| | - Eleonora Porcu
- Institute of Genetics and Biomedical Research, National Research Council, Sardinia, Italy
- Department of Biomedical Sciences, University of Sassari, Sassari, Italy
| | - Susan M Ring
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | - Cinzia Sala
- Division of Genetics and Cell Biology, San Raffele Hospital, Milano, Italy
| | - Albert V Smith
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Toshiko Tanaka
- National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Peter J van der Most
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Veronique Vitart
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Carol A Wang
- School of Medicine and Public Health, University of Newcastle, Newcastle, New South Wales, Australia
- Hunter Medical Research Institute, Newcastle, New South Wales, Australia
| | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit Amsterdam; Amsterdam Public Health (APH) Research Institute, Amsterdam, The Netherlands
| | - Marek Zygmunt
- Clinic of Gynaecology and Obstetrics, University Medicine Greifswald, Greifswald, Germany
| | - Thomas U Ahearn
- Division of Cancer Epidemiology and Genetics National Cancer Institute, National Institutes of Health, Department of Health and Human Services Bethesda, Bethesda, MD, USA
| | - Irene L Andrulis
- Fred A. Litwin Center for Cancer Genetics, Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Hoda Anton-Culver
- Department of Medicine, Genetic Epidemiology Research Institute, University of California Irvine, Irvine, CA, USA
| | - Antonis C Antoniou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Paul L Auer
- Division of Biostatistics, Institute for Health and Equity and Cancer Center, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Catriona L K Barnes
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland
| | - Matthias W Beckmann
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, Friedrich-Alexander University Erlangen-Nuremberg, University Hospital Erlangen, Erlangen, Germany
| | | | - Natalia V Bogdanova
- Department of Radiation Oncology, Hannover Medical School, Hannover, Germany
- Gynaecology Research Unit, Hannover Medical School, Hannover, Germany
- N.N. Alexandrov Research Institute of Oncology and Medical Radiology, Minsk, Belarus
| | - Stig E Bojesen
- Copenhagen General Population Study, Herlev and Gentofte Hospital Copenhagen University Hospital, Herlev, Denmark
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital Copenhagen University Hospital, Herlev, Denmark
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Julie E Buring
- Division of Preventive Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Federico Canzian
- Genomic Epidemiology Group, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Jenny Chang-Claude
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Cancer Epidemiology Group, University Cancer Center Hamburg (UCCH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Fergus J Couch
- Department of Laboratory Medicine and Pathology, Mayo Clinic Rochester, Rochester, MN, USA
| | - Angela Cox
- Sheffield Institute for Nucleic Acids (SInFoNiA), Department of Oncology and Metabolism, University of Sheffield, Sheffield, UK
| | - Laura Crisponi
- Institute of Genetics and Biomedical Research, National Research Council, Sardinia, Italy
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Mary B Daly
- Department of Clinical Genetics, Fox Chase Cancer Center, Philadelphia, PA, USA
| | - Ellen W Demerath
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Peter Devilee
- Department of Pathology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Immaculata De Vivo
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Thilo Dörk
- Gynaecology Research Unit, Hannover Medical School, Hannover, Germany
| | - Alison M Dunning
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Miriam Dwek
- School of Life Sciences, University of Westminster, London, UK
| | - Johan G Eriksson
- Department of General Practice and Primary Healthcare, University of Helsinki, Helsinki University Hospital, Helsinki, Finland
- Yong Loo Lin School of Medicine, Department of Obstetrics and Gynecology and Human Potential Translational Research Programme, National University Singapore, Singapore City, Singapore
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore City, Singapore
| | - Peter A Fasching
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, Friedrich-Alexander University Erlangen-Nuremberg, University Hospital Erlangen, Erlangen, Germany
| | | | - Liana Ferreli
- Institute of Genetics and Biomedical Research, National Research Council, Sardinia, Italy
| | - Olivia Fletcher
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK
| | - Manuela Gago-Dominguez
- Genomic Medicine Group, International Cancer Genetics and Epidemiology Group Fundación Pública Galega de Medicina Xenómica, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Complejo Hospitalario Universitario de Santiago, SERGAS Santiago de Compostela, Coruña, Spain
| | - Montserrat García-Closas
- Division of Cancer Epidemiology and Genetics National Cancer Institute, National Institutes of Health, Department of Health and Human Services Bethesda, Bethesda, MD, USA
| | - José A García-Sáenz
- Medical Oncology Department, Hospital Clínico San Carlos Instituto de Investigación Sanitaria San Carlos (IdISSC), Centro Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain
| | - Anna González-Neira
- Human Genotyping Unit-CeGen, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Harald Grallert
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Pascal Guénel
- Team 'Exposome and Heredity', CESP, Gustave Roussy INSERM, University Paris-Saclay, UVSQ, Orsay, France
| | - Christopher A Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Oncology, Södersjukhuset, Stockholm, Sweden
| | - Ute Hamann
- Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Hakon Hakonarson
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Division of Pulmonary Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Roger J Hart
- Division of Obstetrics and Gynaecology, University of Western Australia, Crawley, Western Australia, Australia
| | - Martha Hickey
- Department of Obstetrics and Gynaecology, University of Melbourne and The Royal Women's Hospital, Parkville, Victoria, Australia
| | - Maartje J Hooning
- Department of Medical Oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Reiner Hoppe
- Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany
- University of Tübingen, Tübingen, Germany
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam; Amsterdam Public Health (APH) Research Institute, Amsterdam, The Netherlands
| | - Frank B Hu
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health School of Public Health, Boston, MA, USA
| | - Hanna Huebner
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, Friedrich-Alexander University Erlangen-Nuremberg, University Hospital Erlangen, Erlangen, Germany
| | - David J Hunter
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Helena Jernström
- Oncology, Department of Clinical Sciences in Lund, Lund University, Lund, Sweden
| | - Esther M John
- Department of Epidemiology and Population Health, Stanford University School of Medicine Stanford, Stanford, CA, USA
- Department of Medicine, Division of Oncology Stanford Cancer Institute, Stanford University School of Medicine Stanford, Stanford, CA, USA
| | - David Karasik
- Hebrew SeniorLife Institute for Aging Research, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Elza K Khusnutdinova
- Institute of Biochemistry and Genetics of the Ufa Federal Research Centre of the Russian Academy of Sciences, Ufa, Russia
- Department of Genetics and Fundamental Medicine, Bashkir State University, Ufa, Russia
| | - Vessela N Kristensen
- Department of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - James V Lacey
- Department of Computational and Quantitative Medicine, City of Hope, Duarte, CA, USA
- City of Hope Comprehensive Cancer Center, City of Hope, Duarte, CA, USA
| | - Diether Lambrechts
- Laboratory for Translational Genetics, Department of Human Genetics, KU Leuven, Leuven, Belgium
- VIB Center for Cancer Biology, VIB, Leuven, Belgium
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Penelope A Lind
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia
- School of Biomedical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Annika Lindblom
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Arto Mannermaa
- Translational Cancer Research Area, University of Eastern Finland, Kuopio, Finland
- Institute of Clinical Medicine, Pathology and Forensic Medicine, University of Eastern Finland, Kuopio, Finland
| | - Mark I McCarthy
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford, UK
- NIHR Oxford Biomedical Research Centre, Churchill Hospital, Oxford, UK
| | - Thomas Meitinger
- Institute of Human Genetics, Klinikum rechts der Isar, Technical University of Munich, School of Medicine, Munich, Germany
| | - Cristina Menni
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Kyriaki Michailidou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Biostatistics Unit, The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus
| | - Iona Y Millwood
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Roger L Milne
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Grant W Montgomery
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Heli Nevanlinna
- Department of Obstetrics and Gynecology, Helsinki University Hospital, University of Helsinki, Helsinki, Finland
| | - Ilja M Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Dale R Nyholt
- School of Biomedical Sciences, Faculty of Health, Centre for Genomics and Personalised Health, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Nadia Obi
- Institute for Occupational Medicine and Maritime Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Institute of Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Katie M O'Brien
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH Research Triangle Park, Durham, NC, USA
| | - Kenneth Offit
- Clinical Genetics Research Lab, Department of Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center, New York City, NY, USA
- Clinical Genetics Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York City, NY, USA
| | - Albertine J Oldehinkel
- Interdisciplinary Center Psychopathology and Emotion Regulation, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Sisse R Ostrowski
- Department of Clinical Immunology, Rigshospitalet-University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Aarno Palotie
- Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK
- Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Ole B Pedersen
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Immunology, Zealand University Hospital, Køge, Denmark
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology-IBE, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Giulia Pianigiani
- Institute for Maternal and Child Health-IRCCS 'Burlo Garofolo', Trieste, Italy
| | - Dijana Plaseska-Karanfilska
- Research Centre for Genetic Engineering and Biotechnology 'Georgi D. Efremov', MASA, Skopje, Republic of North Macedonia
| | - Anneli Pouta
- National Institute for Health and Welfare, Helsinki, Finland
| | - Alfred Pozarickij
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Paolo Radice
- Unit of Preventive Medicine: Molecular Bases of Genetic Risk, Department of Experimental Oncology, Fondazione IRCCS, Istituto Nazionale dei Tumori (INT), Milan, Italy
| | - Gad Rennert
- Faculty of Medicine, Clalit National Cancer Control Center, Carmel Medical Center and Technion, Haifa, Israel
| | - Frits R Rosendaal
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Daniela Ruggiero
- Institute of Genetics and Biophysics 'A. Buzzati-Traverso', CNR, Naples, Italy
- IRCCS Neuromed, Isernia, Italy
| | - Emmanouil Saloustros
- Division of Oncology, Faculty of Medicine, School of Health Sciences, University of Thessaly, Larissa, Greece
| | - Dale P Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH Research Triangle Park, Durham, NC, USA
| | - Sabine Schipf
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Carsten O Schmidt
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Marjanka K Schmidt
- Division of Molecular Pathology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
- Division of Psychosocial Research and Epidemiology, The Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
| | - Kerrin Small
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Beatrice Spedicati
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy
| | - Meir Stampfer
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Jennifer Stone
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
- Genetic Epidemiology Group, School of Population and Global Health, University of Western Australia Perth, Perth, Western Australia, Australia
| | - Rulla M Tamimi
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Population Health Sciences, Weill Cornell Medicine, New York City, NY, USA
| | - Lauren R Teras
- Department of Population Science, American Cancer Society, Atlanta, GA, USA
| | - Emmi Tikkanen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Public Health Genomics Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
| | - Constance Turman
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Celine M Vachon
- Department of Quantitative Health Sciences, Division of Epidemiology, Mayo Clinic Rochester, Rochester, MN, USA
| | - Qin Wang
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Robert Winqvist
- Laboratory of Cancer Genetics and Tumor Biology, Translational Medicine Research Unit, Biocenter Oulu, University of Oulu, Oulu, Finland
- Laboratory of Cancer Genetics and Tumor Biology, Northern Finland Laboratory Centre, Oulu, Finland
| | - Alicja Wolk
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Babette S Zemel
- Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Division of Gastroenterology, Hepatology and Nutrition, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Ko W van Dijk
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
- Department of Internal Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, The Netherlands
| | - Behrooz Z Alizadeh
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | | | - Eric Boerwinkle
- Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam; Amsterdam Public Health (APH) Research Institute, Amsterdam, The Netherlands
- Amsterdam Reproduction and Development Research Institute, Amsterdam, The Netherlands
| | - Marina Ciullo
- Institute of Genetics and Biophysics 'A. Buzzati-Traverso', CNR, Naples, Italy
- IRCCS Neuromed, Isernia, Italy
| | | | - Francesco Cucca
- Institute of Genetics and Biomedical Research, National Research Council, Sardinia, Italy
- Department of Biomedical Sciences, University of Sassari, Sassari, Italy
| | - Tõnu Esko
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Struan F A Grant
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Division of Endocrinology and Diabetes, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Ivana Kolčić
- University of Split School of Medicine, Split, Croatia
- Algebra University College, Zagreb, Croatia
| | - Peter Kraft
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | - Nicholas G Martin
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Ellen A Nøhr
- Institute of Clinical Research, University of Southern Denmark, Department of Obstetrics and Gynecology, Odense University Hospital, Odense, Denmark
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Craig E Pennell
- School of Medicine and Public Health, University of Newcastle, Newcastle, New South Wales, Australia
- Hunter Medical Research Institute, Newcastle, New South Wales, Australia
- Department of Maternity and Gynaecology, John Hunter Hospital, Newcastle, New South Wales, Australia
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Antonietta Robino
- Institute for Maternal and Child Health-IRCCS 'Burlo Garofolo', Trieste, Italy
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Ulla Sovio
- Department of Epidemiology and Biostatistics, MRC Health Protection Agency (HPA) Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Department of Obstetrics and Gynaecology, University of Cambridge, Cambridge, UK
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Doris Stöckl
- Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- State Institute of Health, Bavarian Health and Food Safety Authority (LGL), Oberschleissheim, Germany
| | - Cathie Sudlow
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
- Centre for Medical Informatics, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Nic J Timpson
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | - Daniela Toniolo
- Division of Genetics and Cell Biology, San Raffele Hospital, Milano, Italy
| | - André Uitterlinden
- Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - Sheila Ulivi
- Institute for Maternal and Child Health-IRCCS 'Burlo Garofolo', Trieste, Italy
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Nicholas J Wareham
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
| | - Elisabeth Widen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - James F Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland
| | - Paul D P Pharoah
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing, China
| | - Douglas F Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Pål R Njølstad
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
- Children and Adolescent Clinic, Haukeland University Hospital, Bergen, Norway
| | | | - Joanne M Murabito
- NHLBI's and Boston University's Framingham Heart Study, Framingham, MA, USA
- Boston University Chobanian and Avedisian School of Medicine, Department of Medicine, Section of General Internal Medicine, Boston, MA, USA
| | - Anna Murray
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, RILD Level 3, Royal Devon and Exeter Hospital, Exeter, UK
| | - Despoina Manousaki
- Centre Hospitalier Universitaire (CHU) Sainte-Justine Research Center, University of Montreal, Montreal, Quebec, Canada
- Department of Pediatrics, University of Montreal, Montreal, Quebec, Canada
- Department of Biochemistry and Molecular Medicine, University of Montreal, Montreal, Quebec, Canada
| | - Anders Juul
- Department of Growth and Reproduction, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark
- International Center for Research and Research Training in Endocrine Disruption of Male Reproduction and Child Health (EDMaRC), Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Christian Erikstrup
- Department of Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Kari Stefansson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Momoko Horikoshi
- Laboratory for Genomics of Diabetes and Metabolism, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Zhengming Chen
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - I Sadaf Farooqi
- University of Cambridge Metabolic Research Laboratories and NIHR Cambridge Biomedical Research Centre, Wellcome-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK
| | - Nelly Pitteloud
- Division of Endocrinology, Diabetology, and Metabolism, Lausanne University Hospital, Lausanne, Switzerland
- Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Stefan Johansson
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - Felix R Day
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
| | - John R B Perry
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK.
- Metabolic Research Laboratory, Wellcome-MRC Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK.
| | - Ken K Ong
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
- Department of Paediatrics, University of Cambridge, Cambridge, UK
| |
Collapse
|
11
|
Murphy WJ, Harris AJ. Toward telomere-to-telomere cat genomes for precision medicine and conservation biology. Genome Res 2024; 34:655-664. [PMID: 38849156 PMCID: PMC11216403 DOI: 10.1101/gr.278546.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2024]
Abstract
Genomic data from species of the cat family Felidae promise to stimulate veterinary and human medical advances, and clarify the coherence of genome organization. We describe how interspecies hybrids have been instrumental in the genetic analysis of cats, from the first genetic maps to propelling cat genomes toward the T2T standard set by the human genome project. Genotype-to-phenotype mapping in cat models has revealed dozens of health-related genetic variants, the molecular basis for mammalian pigmentation and patterning, and species-specific adaptations. Improved genomic surveillance of natural and captive populations across the cat family tree will increase our understanding of the genetic architecture of traits, population dynamics, and guide a future of genome-enabled biodiversity conservation.
Collapse
Affiliation(s)
- William J Murphy
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, Texas 77843-4458, USA;
- Department of Biology, Texas A&M University, College Station, Texas 77843-4458, USA
- Interdisciplinary Program in Genetics and Genomics, Texas A&M University, College Station, Texas 77843-4458, USA
| | - Andrew J Harris
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, Texas 77843-4458, USA
- Interdisciplinary Program in Genetics and Genomics, Texas A&M University, College Station, Texas 77843-4458, USA
| |
Collapse
|
12
|
Shen S, Sobczyk MK, Paternoster L, Brown SJ. From GWASs toward Mechanistic Understanding with Case Studies in Dermatogenetics. J Invest Dermatol 2024; 144:1189-1199.e8. [PMID: 38782533 DOI: 10.1016/j.jid.2024.03.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Revised: 02/13/2024] [Accepted: 03/06/2024] [Indexed: 05/25/2024]
Abstract
Many human skin diseases result from the complex interplay of genetic and environmental mechanisms that are largely unknown. GWASs have yielded insight into the genetic aspect of complex disease by highlighting regions of the genome or specific genetic variants associated with disease. Leveraging this information to identify causal genes and cell types will provide insight into fundamental biology, inform diagnostics, and aid drug discovery. However, the etiological mechanisms from genetic variant to disease are still unestablished in most cases. There now exists an unprecedented wealth of data and computational methods for variant interpretation in a functional context. It can be challenging to decide where to start owing to a lack of consensus on the best way to identify causal genetic mechanisms. This article highlights 3 key aspects of genetic variant interpretation: prioritizing causal genes, cell types, and pathways. We provide a practical overview of the main methods and datasets, giving examples from recent atopic dermatitis studies to provide a blueprint for variant interpretation. A collection of resources, including brief description and links to the packages and web tools, is provided for researchers looking to start in silico follow-up genetic analysis of associated genetic variants.
Collapse
Affiliation(s)
- Silvia Shen
- Centre for Genomic & Experimental Medicine, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, United Kingdom; Institute for Evolution and Ecology, School of Biological Sciences, The University of Edinburgh, Edinburgh, United Kingdom.
| | - Maria K Sobczyk
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Lavinia Paternoster
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Sara J Brown
- Centre for Genomic & Experimental Medicine, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, United Kingdom; Department of Dermatology, NHS Lothian, Edinburgh, United Kingdom
| |
Collapse
|
13
|
Zhang H, Chen Y, Xu P, Liu D, Wu N, Wang L, Mo X. Unveiling blood pressure-associated genes in aortic cells through integrative analysis of GWAS and RNA modification-associated variants. Chronic Dis Transl Med 2024; 10:118-129. [PMID: 38872756 PMCID: PMC11166679 DOI: 10.1002/cdt3.124] [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: 01/25/2024] [Revised: 04/02/2024] [Accepted: 04/10/2024] [Indexed: 06/15/2024] Open
Abstract
Background Genome-wide association studies (GWAS) have identified more than a thousand loci for blood pressure (BP). Functional genes in these loci are cell-type specific. The aim of this study was to elucidate potentially functional genes associated with BP in the aorta through the utilization of RNA modification-associated single-nucleotide polymorphisms (RNAm-SNPs). Methods Utilizing large-scale genetic data of 757,601 individuals from the UK Biobank and International Consortium of Blood Pressure consortium, we identified associations between RNAm-SNPs and BP. The association between RNAm-SNPs, gene expression, and BP were examined. Results A total of 355 RNAm-SNPs related to m6A, m1A, m5C, m7G, and A-to-I modification were associated with BP. The related genes were enriched in the pancreatic secretion pathway and renin secretion pathway. The BP GWAS signals were significantly enriched with m6A-SNPs, highlighting the potential functional relevance of m6A in physiological processes influencing BP. Notably, m6A-SNPs in CYP11B1, PDE3B, HDAC7, ACE, SLC4A7, PDE1A, FRK, MTHFR, NPPA, CACNA1D, and HDAC9 were identified. Differential methylation and differential expression of the BP genes in FTO-overexpression and METTL14-knockdown vascular smooth muscle cells were detected. RNAm-SNPs were associated with ascending and descending aorta diameter and the genes showed differential methylation between aortic dissection (AD) cases and controls. In scRNA-seq study, we identified ARID5A, HLA-DPB1, HLA-DRA, IRF1, LINC01091, MCL1, MLF1, MLXIPL, NAA16, NADK, RERG, SRM, and USP53 as differential expression genes for AD in aortic cells. Conclusion The present study identified RNAm-SNPs in BP loci and elucidated the associations between the RNAm-SNPs, gene expression, and BP. The identified BP-associated genes in aortic cells were associated with AD.
Collapse
Affiliation(s)
- Huan Zhang
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Department of Epidemiology, School of Public HealthMedical College of Soochow UniversitySuzhouJiangsuChina
| | - Yuxi Chen
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Department of Epidemiology, School of Public HealthMedical College of Soochow UniversitySuzhouJiangsuChina
| | - Peng Xu
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Department of Epidemiology, School of Public HealthMedical College of Soochow UniversitySuzhouJiangsuChina
| | - Dan Liu
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular DiseasesChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Naqiong Wu
- Cardiometabolic Center, Fuwai Hospital, National Center for Cardiovascular DiseasesChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Laiyuan Wang
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular DiseasesChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Xingbo Mo
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Department of Epidemiology, School of Public HealthMedical College of Soochow UniversitySuzhouJiangsuChina
- MOE Key Laboratory of Geriatric Diseases and Immunology, School of Public Health, Center for Genetic Epidemiology and GenomicsMedical College of Soochow UniversitySuzhouJiangsuChina
| |
Collapse
|
14
|
Choi J, Lee SM, Norwitz ER, Kim JH, Jung YM, Park CW, Jun JK, Lee D, Jin Y, Kim S, Cha B, Park JS, Kim JI. Placental expression quantitative trait loci in an East Asian population. HGG ADVANCES 2024; 5:100276. [PMID: 38310352 PMCID: PMC10883826 DOI: 10.1016/j.xhgg.2024.100276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 01/29/2024] [Accepted: 01/29/2024] [Indexed: 02/05/2024] Open
Abstract
Expression quantitative trait loci (eQTL) analysis measures the contribution of genetic variation in gene expression on complex traits. Although this methodology has been used to examine gene regulation in numerous human tissues, eQTL research in solid tissues is relatively lacking. We conducted eQTL analysis on placentas collected from an East Asian population in an effort to identify gene regulatory mechanisms in this tissue. Placentas (n = 102) were collected at the time of cesarean delivery. mRNA was extracted, sequenced with NGS, and compared with matched maternal and fetal DNA arrays performed using maternal and neonatal cord blood. Linear regression modeling was performed using tensorQTL. Fine-mapping along with epigenomic annotation was used to select putative functional variants. We identified 2,703 coding genes that contained at least one eQTL with statistical significance (false discovery rate <0.05). After fine-mapping, we found 108 previously unreported eQTL variants with posterior inclusion probability >0.1. Of these, 19% were located in genomic regions with evidence from public placental epigenome suggesting that they may be functionally relevant. For example, variant rs28379289 located in the placenta-specific regulatory region changes the binding affinity of transcription factor leading to higher expression of LGALS3, which is known to affect placental function. This study expands the knowledge base of regulatory elements within the human placenta and identifies 108 previously unreported placenta eQTL signals, which are listed in our publicly available GMI eQTL database. Further studies are needed to identify and characterize genetic regulatory mechanisms that affect placental function in normal pregnancy and placenta-related diseases.
Collapse
Affiliation(s)
- Jaeyong Choi
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea; Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, Korea
| | - Seung Mi Lee
- Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul, Korea
| | | | - Ji Hoi Kim
- Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul, Korea
| | - Young Mi Jung
- Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul, Korea
| | - Chan-Wook Park
- Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul, Korea
| | - Jong Kwan Jun
- Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul, Korea
| | - Dakyung Lee
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea; Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, Korea
| | - Yongjoon Jin
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea; Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, Korea
| | - Sookyung Kim
- Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, Korea
| | - Bukyoung Cha
- Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, Korea
| | - Joong Shin Park
- Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul, Korea.
| | - Jong-Il Kim
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea; Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, Korea.
| |
Collapse
|
15
|
Xiong Z, Thach TQ, Zhang YD, Sham PC. Improved estimation of functional enrichment in SNP heritability using feasible generalized least squares. HGG ADVANCES 2024; 5:100272. [PMID: 38327050 PMCID: PMC10901842 DOI: 10.1016/j.xhgg.2024.100272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 01/23/2024] [Accepted: 01/23/2024] [Indexed: 02/09/2024] Open
Abstract
Functional enrichment results typically implicate tissue or cell-type-specific biological pathways in disease pathogenesis and as therapeutic targets. We propose generalized linkage disequilibrium score regression (g-LDSC) that requires only genome-wide association studies (GWASs) summary-level data to estimate functional enrichment. The method adopts the same assumptions and regression model formulation as stratified linkage disequilibrium score regression (s-LDSC). Although s-LDSC only partially uses LD information, our method uses the whole LD matrix, which accounts for possible correlated error structure via a feasible generalized least-squares estimation. We demonstrate through simulation studies under various scenarios that g-LDSC provides more precise estimates of functional enrichment than s-LDSC, regardless of model misspecification. In an application to GWAS summary statistics of 15 traits from the UK Biobank, estimates of functional enrichment using g-LDSC were lower and more realistic than those obtained from s-LDSC. In addition, g-LDSC detected more significantly enriched functional annotations among 24 functional annotations for the 15 traits than s-LDSC (118 vs. 51).
Collapse
Affiliation(s)
- Zewei Xiong
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Thuan-Quoc Thach
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Yan Dora Zhang
- Department of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong SAR, China; Centre for PanorOmic Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
| | - Pak Chung Sham
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China; Centre for PanorOmic Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China; State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong SAR, China.
| |
Collapse
|
16
|
Everman ER, Macdonald SJ. Gene expression variation underlying tissue-specific responses to copper stress in Drosophila melanogaster. G3 (BETHESDA, MD.) 2024; 14:jkae015. [PMID: 38262701 PMCID: PMC11021028 DOI: 10.1093/g3journal/jkae015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 01/04/2024] [Accepted: 01/08/2024] [Indexed: 01/25/2024]
Abstract
Copper is one of a handful of biologically necessary heavy metals that is also a common environmental pollutant. Under normal conditions, copper ions are required for many key physiological processes. However, in excess, copper results in cell and tissue damage ranging in severity from temporary injury to permanent neurological damage. Because of its biological relevance, and because many conserved copper-responsive genes respond to nonessential heavy metal pollutants, copper resistance in Drosophila melanogaster is a useful model system with which to investigate the genetic control of the heavy metal stress response. Because heavy metal toxicity has the potential to differently impact specific tissues, we genetically characterized the control of the gene expression response to copper stress in a tissue-specific manner in this study. We assessed the copper stress response in head and gut tissue of 96 inbred strains from the Drosophila Synthetic Population Resource using a combination of differential expression analysis and expression quantitative trait locus mapping. Differential expression analysis revealed clear patterns of tissue-specific expression. Tissue and treatment specific responses to copper stress were also detected using expression quantitative trait locus mapping. Expression quantitative trait locus associated with MtnA, Mdr49, Mdr50, and Sod3 exhibited both genotype-by-tissue and genotype-by-treatment effects on gene expression under copper stress, illuminating tissue- and treatment-specific patterns of gene expression control. Together, our data build a nuanced description of the roles and interactions between allelic and expression variation in copper-responsive genes, provide valuable insight into the genomic architecture of susceptibility to metal toxicity, and highlight candidate genes for future functional characterization.
Collapse
Affiliation(s)
- Elizabeth R Everman
- School of Biological Sciences, The University of Oklahoma, 730 Van Vleet Oval, Norman, OK 73019, USA
| | - Stuart J Macdonald
- Molecular Biosciences, University of Kansas, 1200 Sunnyside Ave, Lawrence, KS 66045, USA
| |
Collapse
|
17
|
McEwan AR, Hing B, Erickson JC, Hutchings G, Urama C, Norton-Hughes E, D'Ippolito M, Berry S, Delibegovic M, Grassmann F, MacKenzie A. An ancient polymorphic regulatory region within the BDNF gene associated with obesity modulates anxiety-like behaviour in mice and humans. Mol Psychiatry 2024; 29:660-670. [PMID: 38228888 PMCID: PMC11153140 DOI: 10.1038/s41380-023-02359-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 11/10/2023] [Accepted: 12/01/2023] [Indexed: 01/18/2024]
Abstract
Obesity and anxiety are morbidities notable for their increased impact on society during the recent COVID-19 pandemic. Understanding the mechanisms governing susceptibility to these conditions will increase our quality of life and resilience to future pandemics. In the current study, we explored the function of a highly conserved regulatory region (BE5.1) within the BDNF gene that harbours a polymorphism strongly associated with obesity (rs10767664; p = 4.69 × 10-26). Analysis in primary cells suggested that the major T-allele of BE5.1 was an enhancer, whereas the obesity-associated A-allele was not. However, CRISPR/CAS9 deletion of BE5.1 from the mouse genome (BE5.1KO) produced no significant effect on the expression of BDNF transcripts in the hypothalamus, no change in weight gain after 28 days and only a marginally significant increase in food intake. Nevertheless, transcripts were significantly increased in the amygdala of female mice and elevated zero maze and marble-burying tests demonstrated a significant increase in anxiety-like behaviour that could be reversed by diazepam. Consistent with these observations, human GWAS cohort analysis demonstrated a significant association between rs10767664 and anxiousness in human populations. Intriguingly, interrogation of the human GTEx eQTL database demonstrated no effect on BDNF mRNA levels associated with rs10767664 but a highly significant effect on BDNF-antisense (BDNF-AS) gene expression and splicing. The subsequent observation that deletion of BE5.1 also significantly reduced BDNF-AS expression in mice suggests a novel mechanism in the regulation of BDNF expression common to mice and humans, which contributes to the modulation of mood and anxiety in both species.
Collapse
Affiliation(s)
- Andrew R McEwan
- School of Medicine, Medical Sciences and Nutrition, Institute of Medical Sciences, University of Aberdeen, Foresterhill, Aberdeen, AB24 2ZD, UK
| | - Benjamin Hing
- Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa City, IA, USA
| | - Johanna C Erickson
- School of Medicine, Medical Sciences and Nutrition, Institute of Medical Sciences, University of Aberdeen, Foresterhill, Aberdeen, AB24 2ZD, UK
| | - Greg Hutchings
- School of Medicine, Medical Sciences and Nutrition, Institute of Medical Sciences, University of Aberdeen, Foresterhill, Aberdeen, AB24 2ZD, UK
| | - Charity Urama
- School of Medicine, Medical Sciences and Nutrition, Institute of Medical Sciences, University of Aberdeen, Foresterhill, Aberdeen, AB24 2ZD, UK
| | - Emily Norton-Hughes
- School of Medicine, Medical Sciences and Nutrition, Institute of Medical Sciences, University of Aberdeen, Foresterhill, Aberdeen, AB24 2ZD, UK
| | - Mariam D'Ippolito
- School of Medicine, Medical Sciences and Nutrition, Institute of Medical Sciences, University of Aberdeen, Foresterhill, Aberdeen, AB24 2ZD, UK
| | - Susan Berry
- School of Medicine, Medical Sciences and Nutrition, Institute of Medical Sciences, University of Aberdeen, Foresterhill, Aberdeen, AB24 2ZD, UK
| | - Mirela Delibegovic
- School of Medicine, Medical Sciences and Nutrition, Institute of Medical Sciences, University of Aberdeen, Foresterhill, Aberdeen, AB24 2ZD, UK
| | - Felix Grassmann
- Institute for Clinical Research and Systems Medicine, Health and Medical University, Potsdam, Germany
| | - Alasdair MacKenzie
- School of Medicine, Medical Sciences and Nutrition, Institute of Medical Sciences, University of Aberdeen, Foresterhill, Aberdeen, AB24 2ZD, UK.
| |
Collapse
|
18
|
Chen H, Wang Z, Gong L, Wang Q, Chen W, Wang J, Ma X, Ding R, Li X, Zou X, Plass M, Lian C, Ni T, Wei GH, Li W, Deng L, Li L. A distinct class of pan-cancer susceptibility genes revealed by an alternative polyadenylation transcriptome-wide association study. Nat Commun 2024; 15:1729. [PMID: 38409266 PMCID: PMC10897204 DOI: 10.1038/s41467-024-46064-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Accepted: 02/12/2024] [Indexed: 02/28/2024] Open
Abstract
Alternative polyadenylation plays an important role in cancer initiation and progression; however, current transcriptome-wide association studies mostly ignore alternative polyadenylation when identifying putative cancer susceptibility genes. Here, we perform a pan-cancer 3' untranslated region alternative polyadenylation transcriptome-wide association analysis by integrating 55 well-powered (n > 50,000) genome-wide association studies datasets across 22 major cancer types with alternative polyadenylation quantification from 23,955 RNA sequencing samples across 7,574 individuals. We find that genetic variants associated with alternative polyadenylation are co-localized with 28.57% of cancer loci and contribute a significant portion of cancer heritability. We further identify 642 significant cancer susceptibility genes predicted to modulate cancer risk via alternative polyadenylation, 62.46% of which have been overlooked by traditional expression- and splicing- studies. As proof of principle validation, we show that alternative alleles facilitate 3' untranslated region lengthening of CRLS1 gene leading to increased protein abundance and promoted proliferation of breast cancer cells. Together, our study highlights the significant role of alternative polyadenylation in discovering new cancer susceptibility genes and provides a strong foundational framework for enhancing our understanding of the etiology underlying human cancers.
Collapse
Affiliation(s)
- Hui Chen
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, 518055, China
| | - Zeyang Wang
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, 518055, China
| | - Lihai Gong
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, 518055, China
| | - Qixuan Wang
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, 518055, China
| | - Wenyan Chen
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, 518055, China
| | - Jia Wang
- Institute of Molecular Physiology, Shenzhen Bay Laboratory, Shenzhen, 518055, China
| | - Xuelian Ma
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, 518055, China
| | - Ruofan Ding
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, 518055, China
| | - Xing Li
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, 518055, China
| | - Xudong Zou
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, 518055, China
| | - Mireya Plass
- Gene Regulation of Cell Identity Group, Regenerative Medicine Program, Bellvitge Institute for Biomedical Research (IDIBELL), L'Hospitalet de Llobregat, Barcelona, 08908, Spain
- Program for Advancing Clinical Translation of Regenerative Medicine of Catalonia, P-CMR[C], L'Hospitalet de Llobregat, Barcelona, 08908, Spain
- Center for Networked Biomedical Research on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, 28029, Spain
| | - Cheng Lian
- Department of Biochemistry and Molecular Biology of School of Basic Medical Sciences, Shanghai Medical College of Fudan University, Shanghai, 200032, China
| | - Ting Ni
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center of Genetics and Development, Human Phenome Institute, School of Life Sciences and Huashan Hospital, Fudan University, Shanghai, 200438, China
| | - Gong-Hong Wei
- Department of Biochemistry and Molecular Biology of School of Basic Medical Sciences, Shanghai Medical College of Fudan University, Shanghai, 200032, China
- Disease Networks Research Unit, Faculty of Biochemistry and Molecular Medicine & Biocenter Oulu, University of Oulu, Oulu, 90410, Finland
| | - Wei Li
- Division of Computational Biomedicine, Department of Biological Chemistry, School of Medicine, The University of California, Irvine, CA, 92697, USA.
| | - Lin Deng
- Institute of Molecular Physiology, Shenzhen Bay Laboratory, Shenzhen, 518055, China.
| | - Lei Li
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, 518055, China.
| |
Collapse
|
19
|
Gao Y, Zhou Q, Luo J, Xia C, Zhang Y, Yue Z. Crop-GPA: an integrated platform of crop gene-phenotype associations. NPJ Syst Biol Appl 2024; 10:15. [PMID: 38346982 PMCID: PMC10861494 DOI: 10.1038/s41540-024-00343-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 01/22/2024] [Indexed: 02/15/2024] Open
Abstract
With the increasing availability of large-scale biology data in crop plants, there is an urgent demand for a versatile platform that fully mines and utilizes the data for modern molecular breeding. We present Crop-GPA ( https://crop-gpa.aielab.net ), a comprehensive and functional open-source platform for crop gene-phenotype association data. The current Crop-GPA provides well-curated information on genes, phenotypes, and their associations (GPAs) to researchers through an intuitive interface, dynamic graphical visualizations, and efficient online tools. Two computational tools, GPA-BERT and GPA-GCN, are specifically developed and integrated into Crop-GPA, facilitating the automatic extraction of gene-phenotype associations from bio-crop literature and predicting unknown relations based on known associations. Through usage examples, we demonstrate how our platform enables the exploration of complex correlations between genes and phenotypes in crop plants. In summary, Crop-GPA serves as a valuable multi-functional resource, empowering the crop research community to gain deeper insights into the biological mechanisms of interest.
Collapse
Affiliation(s)
- Yujia Gao
- School of Information and Artificial Intelligence, Anhui Beidou Precision Agriculture Information Engineering Research Center, Anhui Agricultural University, Hefei, Anhui, 230036, China
| | - Qian Zhou
- School of Information and Artificial Intelligence, Anhui Beidou Precision Agriculture Information Engineering Research Center, Anhui Agricultural University, Hefei, Anhui, 230036, China
| | - Jiaxin Luo
- School of Information and Artificial Intelligence, Anhui Beidou Precision Agriculture Information Engineering Research Center, Anhui Agricultural University, Hefei, Anhui, 230036, China
| | - Chuan Xia
- School of Information and Artificial Intelligence, Anhui Beidou Precision Agriculture Information Engineering Research Center, Anhui Agricultural University, Hefei, Anhui, 230036, China
| | - Youhua Zhang
- School of Information and Artificial Intelligence, Anhui Beidou Precision Agriculture Information Engineering Research Center, Anhui Agricultural University, Hefei, Anhui, 230036, China.
| | - Zhenyu Yue
- School of Information and Artificial Intelligence, Anhui Beidou Precision Agriculture Information Engineering Research Center, Anhui Agricultural University, Hefei, Anhui, 230036, China.
| |
Collapse
|
20
|
Boye C, Kalita CA, Findley AS, Alazizi A, Wei J, Wen X, Pique-Regi R, Luca F. Characterization of caffeine response regulatory variants in vascular endothelial cells. eLife 2024; 13:e85235. [PMID: 38334359 PMCID: PMC10901511 DOI: 10.7554/elife.85235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 02/08/2024] [Indexed: 02/10/2024] Open
Abstract
Genetic variants in gene regulatory sequences can modify gene expression and mediate the molecular response to environmental stimuli. In addition, genotype-environment interactions (GxE) contribute to complex traits such as cardiovascular disease. Caffeine is the most widely consumed stimulant and is known to produce a vascular response. To investigate GxE for caffeine, we treated vascular endothelial cells with caffeine and used a massively parallel reporter assay to measure allelic effects on gene regulation for over 43,000 genetic variants. We identified 665 variants with allelic effects on gene regulation and 6 variants that regulate the gene expression response to caffeine (GxE, false discovery rate [FDR] < 5%). When overlapping our GxE results with expression quantitative trait loci colocalized with coronary artery disease and hypertension, we dissected their regulatory mechanisms and showed a modulatory role for caffeine. Our results demonstrate that massively parallel reporter assay is a powerful approach to identify and molecularly characterize GxE in the specific context of caffeine consumption.
Collapse
Affiliation(s)
- Carly Boye
- Center for Molecular Medicine and Genetics, Wayne State UniversityDetroitUnited States
| | - Cynthia A Kalita
- Center for Molecular Medicine and Genetics, Wayne State UniversityDetroitUnited States
| | - Anthony S Findley
- Center for Molecular Medicine and Genetics, Wayne State UniversityDetroitUnited States
| | - Adnan Alazizi
- Center for Molecular Medicine and Genetics, Wayne State UniversityDetroitUnited States
| | - Julong Wei
- Center for Molecular Medicine and Genetics, Wayne State UniversityDetroitUnited States
| | - Xiaoquan Wen
- Department of Biostatistics, University of MichiganAnn ArborUnited States
| | - Roger Pique-Regi
- Center for Molecular Medicine and Genetics, Wayne State UniversityDetroitUnited States
- Department of Obstetrics and Gynecology, Wayne State UniversityDetroitUnited States
| | - Francesca Luca
- Center for Molecular Medicine and Genetics, Wayne State UniversityDetroitUnited States
- Department of Obstetrics and Gynecology, Wayne State UniversityDetroitUnited States
- Department of Biology, University of Rome Tor VergataRomeItaly
| |
Collapse
|
21
|
Baranger DAA, Hatoum AS, Polimanti R, Gelernter J, Edenberg HJ, Bogdan R, Agrawal A. Multi-omics cannot replace sample size in genome-wide association studies. GENES, BRAIN, AND BEHAVIOR 2023; 22:e12846. [PMID: 36977197 PMCID: PMC10733567 DOI: 10.1111/gbb.12846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 02/20/2023] [Accepted: 03/13/2023] [Indexed: 03/30/2023]
Abstract
The integration of multi-omics information (e.g., epigenetics and transcriptomics) can be useful for interpreting findings from genome-wide association studies (GWAS). It has been suggested that multi-omics could circumvent or greatly reduce the need to increase GWAS sample sizes for novel variant discovery. We tested whether incorporating multi-omics information in earlier and smaller-sized GWAS boosts true-positive discovery of genes that were later revealed by larger GWAS of the same/similar traits. We applied 10 different analytic approaches to integrating multi-omics data from 12 sources (e.g., Genotype-Tissue Expression project) to test whether earlier and smaller GWAS of 4 brain-related traits (alcohol use disorder/problematic alcohol use, major depression/depression, schizophrenia, and intracranial volume/brain volume) could detect genes that were revealed by a later and larger GWAS. Multi-omics data did not reliably identify novel genes in earlier less-powered GWAS (PPV <0.2; 80% false-positive associations). Machine learning predictions marginally increased the number of identified novel genes, correctly identifying 1-8 additional genes, but only for well-powered early GWAS of highly heritable traits (i.e., intracranial volume and schizophrenia). Although multi-omics, particularly positional mapping (i.e., fastBAT, MAGMA, and H-MAGMA), can help to prioritize genes within genome-wide significant loci (PPVs = 0.5-1.0) and translate them into information about disease biology, it does not reliably increase novel gene discovery in brain-related GWAS. To increase power for discovery of novel genes and loci, increasing sample size is required.
Collapse
Affiliation(s)
- David A. A. Baranger
- Department of Psychological & Brain SciencesWashington University in St. Louis Medical SchoolSaint LouisMissouriUSA
| | - Alexander S. Hatoum
- Department of PsychiatryWashington University School of MedicineSaint LouisMissouriUSA
| | - Renato Polimanti
- Department of Psychiatry, Division of Human GeneticsYale School of MedicineNew HavenConnecticutUSA
- PsychiatryVeterans Affairs Connecticut Healthcare SystemWest HavenConnecticutUSA
| | - Joel Gelernter
- Department of Psychiatry, Division of Human GeneticsYale School of MedicineNew HavenConnecticutUSA
- PsychiatryVeterans Affairs Connecticut Healthcare SystemWest HavenConnecticutUSA
- Department of GeneticsYale School of MedicineNew HavenConnecticutUSA
- Department of NeuroscienceYale School of MedicineNew HavenConnecticutUSA
| | - Howard J. Edenberg
- Department of Biochemistry and Molecular BiologyIndiana University School of MedicineIndianapolisIndianaUSA
- Department of Medical and Molecular GeneticsIndiana University School of MedicineIndianapolisIndianaUSA
| | - Ryan Bogdan
- Department of Psychological & Brain SciencesWashington University in St. Louis Medical SchoolSaint LouisMissouriUSA
| | - Arpana Agrawal
- Department of PsychiatryWashington University School of MedicineSaint LouisMissouriUSA
| |
Collapse
|
22
|
Moore A, Marks JA, Quach BC, Guo Y, Bierut LJ, Gaddis NC, Hancock DB, Page GP, Johnson EO. Evaluating 17 methods incorporating biological function with GWAS summary statistics to accelerate discovery demonstrates a tradeoff between high sensitivity and high positive predictive value. Commun Biol 2023; 6:1199. [PMID: 38001305 PMCID: PMC10673847 DOI: 10.1038/s42003-023-05413-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 10/03/2023] [Indexed: 11/26/2023] Open
Abstract
Where sufficiently large genome-wide association study (GWAS) samples are not currently available or feasible, methods that leverage increasing knowledge of the biological function of variants may illuminate discoveries without increasing sample size. We comprehensively evaluated 17 functional weighting methods for identifying novel associations. We assessed the performance of these methods using published results from multiple GWAS waves across each of five complex traits. Although no method achieved both high sensitivity and positive predictive value (PPV) for any trait, a subset of methods utilizing pleiotropy and expression quantitative trait loci nominated variants with high PPV (>75%) for multiple traits. Application of functionally weighting methods to enhance GWAS power for locus discovery is unlikely to circumvent the need for larger sample sizes in truly underpowered GWAS, but these results suggest that applying functional weighting to GWAS can accurately nominate additional novel loci from available samples for follow-up studies.
Collapse
Affiliation(s)
- Amy Moore
- Genomics and Translational Research Center, RTI International, Research Triangle Park, NC, 27709, USA.
| | - Jesse A Marks
- Genomics and Translational Research Center, RTI International, Research Triangle Park, NC, 27709, USA
| | - Bryan C Quach
- Genomics and Translational Research Center, RTI International, Research Triangle Park, NC, 27709, USA
| | - Yuelong Guo
- GeneCentric Therapeutics, Inc., Cary, NC, USA
| | - Laura J Bierut
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Nathan C Gaddis
- Genomics and Translational Research Center, RTI International, Research Triangle Park, NC, 27709, USA
| | - Dana B Hancock
- Genomics and Translational Research Center, RTI International, Research Triangle Park, NC, 27709, USA
| | - Grier P Page
- Genomics and Translational Research Center, RTI International, Research Triangle Park, NC, 27709, USA
- Fellow Program, RTI International, Research Triangle Park, NC, 27709, USA
| | - Eric O Johnson
- Genomics and Translational Research Center, RTI International, Research Triangle Park, NC, 27709, USA.
- Fellow Program, RTI International, Research Triangle Park, NC, 27709, USA.
| |
Collapse
|
23
|
Mazidi M, Wright N, Yao P, Kartsonaki C, Millwood IY, Fry H, Said S, Pozarickij A, Pei P, Chen Y, Avery D, Du H, Schmidt DV, Yang L, Lv J, Yu C, Chen J, Hill M, Holmes MV, Howson JMM, Peto R, Collins R, Bennett DA, Walters RG, Li L, Clarke R, Chen Z. Plasma Proteomics to Identify Drug Targets for Ischemic Heart Disease. J Am Coll Cardiol 2023; 82:1906-1920. [PMID: 37940228 PMCID: PMC10641761 DOI: 10.1016/j.jacc.2023.09.804] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 08/11/2023] [Accepted: 09/05/2023] [Indexed: 11/10/2023]
Abstract
BACKGROUND Integrated analyses of plasma proteomic and genetic markers in prospective studies can clarify the causal relevance of proteins and discover novel targets for ischemic heart disease (IHD) and other diseases. OBJECTIVES The purpose of this study was to examine associations of proteomics and genetics data with IHD in population studies to discover novel preventive treatments. METHODS We conducted a nested case-cohort study in the China Kadoorie Biobank (CKB) involving 1,971 incident IHD cases and 2,001 subcohort participants who were genotyped and free of prior cardiovascular disease. We measured 1,463 proteins in the stored baseline samples using the OLINK EXPLORE panel. Cox regression yielded adjusted HRs for IHD associated with individual proteins after accounting for multiple testing. Moreover, cis-protein quantitative loci (pQTLs) identified for proteins in genome-wide association studies of CKB and of UK Biobank were used as instrumental variables in separate 2-sample Mendelian randomization (MR) studies involving global CARDIOGRAM+C4D consortium (210,842 IHD cases and 1,378,170 controls). RESULTS Overall 361 proteins were significantly associated at false discovery rate <0.05 with risk of IHD (349 positively, 12 inversely) in CKB, including N-terminal prohormone of brain natriuretic peptide and proprotein convertase subtilisin/kexin type 9. Of these 361 proteins, 212 had cis-pQTLs in CKB, and MR analyses of 198 variants in CARDIOGRAM+C4D identified 13 proteins that showed potentially causal associations with IHD. Independent MR analyses of 307 cis-pQTLs identified in Europeans replicated associations for 4 proteins (FURIN, proteinase-activated receptor-1, Asialoglycoprotein receptor-1, and matrix metalloproteinase-3). Further downstream analyses showed that FURIN, which is highly expressed in endothelial cells, is a potential novel target and matrix metalloproteinase-3 a potential repurposing target for IHD. CONCLUSIONS Integrated analyses of proteomic and genetic data in Chinese and European adults provided causal support for FURIN and multiple other proteins as potential novel drug targets for treatment of IHD.
Collapse
Affiliation(s)
- Mohsen Mazidi
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Neil Wright
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Pang Yao
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Christiana Kartsonaki
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Iona Y Millwood
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Hannah Fry
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Saredo Said
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Alfred Pozarickij
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Yiping Chen
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Daniel Avery
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Huaidong Du
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Dan Valle Schmidt
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Ling Yang
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Jun Lv
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China; Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China; Key Laboratory of Epidemiology of Major (Peking University), Ministry of Education, Beijing, China
| | - Canqing Yu
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China; Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China; Key Laboratory of Epidemiology of Major (Peking University), Ministry of Education, Beijing, China
| | - Junshi Chen
- China National Center for Food Risk Assessment, Beijing, China
| | - Michael Hill
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Michael V Holmes
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | | | - Richard Peto
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Rory Collins
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Derrick A Bennett
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Robin G Walters
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Liming Li
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China; Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China; Key Laboratory of Epidemiology of Major (Peking University), Ministry of Education, Beijing, China
| | - Robert Clarke
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.
| | - Zhengming Chen
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.
| |
Collapse
|
24
|
Zhang K, Yang Q, Du M, Zhang Z, Wang W, Zhang G, Li A, Li L. Genome-wide mapping of regulatory variants for temperature- and salinity-adaptive genes reveals genetic basis of genotype-by-environment interaction in Crassostrea ariakensis. ENVIRONMENTAL RESEARCH 2023; 236:116614. [PMID: 37442261 DOI: 10.1016/j.envres.2023.116614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 06/14/2023] [Accepted: 07/09/2023] [Indexed: 07/15/2023]
Abstract
Regulatory variants in gene expression serve as bridges linking genetic variation and phenotypic plasticity. Environmental conditions typically influence the effects of regulatory variants on phenotypic plasticity; however, such genotype-by-environment interactions (G × E) are poorly understood. This study aimed to investigate the genetic basis of G × E in estuarine oyster (Crassostrea ariakensis), which is an important model animal for studying environmental adaption owing to its high plasticity and large intraspecific divergence. Genome-wide mapping of expression quantitative trait loci (eQTLs) for 23 environmental adaptive genes was performed for 256 estuarine oysters. We identified 1194 eQTL single nucleotide polymorphisms (eSNPs), including 433 cis-eSNPs in four genes and 722 trans-eSNPs in eight genes. The expression variation explanation of cis-eSNPs (9.95%) was significantly higher than that of trans-eSNPs (9.15%). We specifically showed cis- and trans-eSNPs with high linkage disequilibrium (LD) for Traf7, Slc6a5, Ggt, and Dap3. For example, we identified a cis-regulatory LD block containing 68 cis-eSNP and a trans-regulatory LD block, including 20 trans-eSNPs in Traf7. A high proportion (85%) of 40 vital eSNPs exhibited significant G × E effects. We identified crossing and nonparallel interactions of G × E, with the tag cis-eSNPs of Baat and Slc6a5 as representatives. Our results indicated that cis-eQTLs are highly conserved. This study provides insights into the understanding of adaptive evolutionary mechanisms and phenotypic response prediction to variable environments, as well as the genetic improvement for superior adaptive traits for genetic resource conservation and aquaculture.
Collapse
Affiliation(s)
- Kexin Zhang
- CAS and Shandong Province Key Laboratory of Experimental Marine Biology, Center for Ocean Mega-Science, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China; Laboratory for Marine Biology and Biotechnology, Pilot National Laboratory for Marine Science and Technology, Qingdao 266237, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Qi Yang
- CAS and Shandong Province Key Laboratory of Experimental Marine Biology, Center for Ocean Mega-Science, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
| | - Mingyang Du
- CAS and Shandong Province Key Laboratory of Experimental Marine Biology, Center for Ocean Mega-Science, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China; Laboratory for Marine Biology and Biotechnology, Pilot National Laboratory for Marine Science and Technology, Qingdao 266237, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Ziyan Zhang
- CAS and Shandong Province Key Laboratory of Experimental Marine Biology, Center for Ocean Mega-Science, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China; Laboratory for Marine Biology and Biotechnology, Pilot National Laboratory for Marine Science and Technology, Qingdao 266237, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wei Wang
- CAS and Shandong Province Key Laboratory of Experimental Marine Biology, Center for Ocean Mega-Science, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China; Key Laboratory of Breeding Biotechnology and Sustainable Aquaculture, Chinese Academy of Sciences, Wuhan 430072, China; National and Local Joint Engineering Laboratory of Ecological Mariculture, Qingdao 266071, China
| | - Guofan Zhang
- CAS and Shandong Province Key Laboratory of Experimental Marine Biology, Center for Ocean Mega-Science, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China; Laboratory for Marine Biology and Biotechnology, Pilot National Laboratory for Marine Science and Technology, Qingdao 266237, China; National and Local Joint Engineering Laboratory of Ecological Mariculture, Qingdao 266071, China
| | - Ao Li
- CAS and Shandong Province Key Laboratory of Experimental Marine Biology, Center for Ocean Mega-Science, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China; Key Laboratory of Breeding Biotechnology and Sustainable Aquaculture, Chinese Academy of Sciences, Wuhan 430072, China; National and Local Joint Engineering Laboratory of Ecological Mariculture, Qingdao 266071, China.
| | - Li Li
- CAS and Shandong Province Key Laboratory of Experimental Marine Biology, Center for Ocean Mega-Science, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China; Key Laboratory of Breeding Biotechnology and Sustainable Aquaculture, Chinese Academy of Sciences, Wuhan 430072, China; University of Chinese Academy of Sciences, Beijing 100049, China; National and Local Joint Engineering Laboratory of Ecological Mariculture, Qingdao 266071, China; Shandong Technology Innovation Center of Oyster Seed Industry, Qingdao 266000, China.
| |
Collapse
|
25
|
Zhang W, Zhang L, Zhu J, Xiao C, Cui H, Yang C, Yan P, Tang M, Wang Y, Chen L, Liu Y, Zou Y, Wu X, Zhang L, Yang C, Yao Y, Li J, Liu Z, Jiang X, Zhang B. Additional Evidence for the Relationship Between Type 2 Diabetes and Stroke Through Observational and Genetic Analyses. Diabetes 2023; 72:1671-1681. [PMID: 37552871 DOI: 10.2337/db22-0954] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 08/01/2023] [Indexed: 08/10/2023]
Abstract
While type 2 diabetes mellitus (T2DM) is commonly considered a putative causal risk factor for stroke, the effect of stroke on T2DM remains unclear. The intrinsic link underlying T2DM and stroke has not been thoroughly examined. We aimed to evaluate the phenotypic and genetic relationships underlying T2DM and stroke. We evaluated phenotypic associations using data from the UK Biobank (N = 472,050). We then investigated genetic relationships by leveraging genomic data in European ancestry for T2DM, with and without adjusting (adj) for BMI (T2DM: n = 74,124 case subjects/824,006 control subjects; T2DMadjBMI: n = 50,409 case subjects/523,897 control subjects), and for stroke (n = 73,652 case subjects/1,234,808 control subjects). We performed additional analyses using genomic data in East Asian ancestry for T2DM (n = 77,418 case subjects/356,122 control subjects) and for stroke (n = 27,413 case subjects/237,242 control subjects). Observational analyses suggested a significantly increased hazard of stroke among individuals with T2DM (hazard ratio 2.28 [95% CI 1.97-2.64]), but a slightly increased hazard of T2DM among individuals with stroke (1.22 [1.03-1.45]) which attenuated to 1.14 (0.96-1.36) in sensitivity analysis. A positive global T2DM-stroke genetic correlation was observed (rg = 0.35; P = 1.46 × 10-27), largely independent of BMI (T2DMadjBMI-stroke: rg = 0.27; P = 3.59 × 10-13). This was further corroborated by 38 shared independent loci and 161 shared expression-trait associations. Mendelian randomization analyses suggested a putative causal effect of T2DM on stroke in Europeans (odds ratio 1.07 [95% CI 1.06-1.09]), which remained significant in East Asians (1.03 [1.01-1.06]). Conversely, despite a putative causal effect of stroke on T2DM also observed in Europeans (1.21 [1.07-1.37]), it attenuated to 1.04 (0.91-1.19) in East Asians. Our study provides additional evidence to underscore the significant relationship between T2DM and stroke. ARTICLE HIGHLIGHTS
Collapse
Affiliation(s)
- Wenqiang Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
| | - Li Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
| | - Jingwei Zhu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
| | - Chenghan Xiao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Huijie Cui
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
| | - Chao Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
| | - Peijing Yan
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
| | - Mingshuang Tang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
| | - Yutong Wang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
| | - Lin Chen
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
| | - Yunjie Liu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
| | - Yanqiu Zou
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
| | - Xueyao Wu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
| | - Ling Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
- Department of Iatrical Polymer Material and Artificial Apparatus, School of Polymer Science and Engineering, Sichuan University, Chengdu, China
| | - Chunxia Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
| | - Yuqin Yao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Jiayuan Li
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
| | - Zhenmi Liu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xia Jiang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Ben Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C.C. Chen Institute of Health, West China School of Public Health, and West China Fourth Hospital, Sichuan University, Chengdu
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| |
Collapse
|
26
|
Urbut SM, Koyama S, Hornsby W, Bhukar R, Kheterpal S, Truong B, Selvaraj MS, Neale B, O’Donnell CJ, Peloso GM, Natarajan P. Bayesian multivariate genetic analysis improves translational insights. iScience 2023; 26:107854. [PMID: 37766997 PMCID: PMC10520309 DOI: 10.1016/j.isci.2023.107854] [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: 01/10/2023] [Revised: 05/15/2023] [Accepted: 09/05/2023] [Indexed: 09/29/2023] Open
Abstract
While lipid traits are known essential mediators of cardiovascular disease, few approaches have taken advantage of their shared genetic effects. We apply a Bayesian multivariate size estimator, mash, to GWAS of four lipid traits in the Million Veterans Program (MVP) and provide posterior mean and local false sign rates for all effects. These estimates borrow information across traits to improve effect size accuracy. We show that controlling local false sign rates accurately and powerfully identifies replicable genetic associations and that multivariate control furthers the ability to explain complex diseases. Our application yields high concordance between independent datasets, more accurately prioritizes causal genes, and significantly improves polygenic prediction beyond state-of-the-art methods by up to 59% for lipid traits. The use of Bayesian multivariate genetic shrinkage has yet to be applied to human quantitative trait GWAS results, and we present a staged approach to prediction on a polygenic scale.
Collapse
Affiliation(s)
- Sarah M. Urbut
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA 02114, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA
| | - Satoshi Koyama
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA 02114, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA
- Department of Medicine Harvard Medical School, Boston, MA 02115, USA
| | - Whitney Hornsby
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA 02114, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA
- Department of Medicine Harvard Medical School, Boston, MA 02115, USA
| | - Rohan Bhukar
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA 02114, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA
- Department of Medicine Harvard Medical School, Boston, MA 02115, USA
| | - Sumeet Kheterpal
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA 02114, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA
| | - Buu Truong
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA 02114, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA
- Department of Medicine Harvard Medical School, Boston, MA 02115, USA
| | - Margaret S. Selvaraj
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA 02114, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA
- Department of Medicine Harvard Medical School, Boston, MA 02115, USA
| | - Benjamin Neale
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA
- Department of Medicine Harvard Medical School, Boston, MA 02115, USA
- Analytic Translational and Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Christopher J. O’Donnell
- Department of Medicine Harvard Medical School, Boston, MA 02115, USA
- VA Boston Department of Veterans Affairs, Boston, MA 02130, USA
| | - Gina M. Peloso
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02218, USA
| | - Pradeep Natarajan
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA 02114, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA
- Department of Medicine Harvard Medical School, Boston, MA 02115, USA
| |
Collapse
|
27
|
Zhao Z, D’Oliveira Albanus R, Taylor H, Tang X, Han Y, Orchard P, Varshney A, Zhang T, Manickam N, Erdos M, Narisu N, Taylor L, Saavedra X, Zhong A, Li B, Zhou T, Naji A, Liu C, Collins F, Parker SCJ, Chen S. An integrative single-cell multi-omics profiling of human pancreatic islets identifies T1D associated genes and regulatory signals. RESEARCH SQUARE 2023:rs.3.rs-3343318. [PMID: 37886586 PMCID: PMC10602166 DOI: 10.21203/rs.3.rs-3343318/v1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
Genome wide association studies (GWAS) have identified over 100 signals associated with type 1 diabetes (T1D). However, translating any given T1D GWAS signal into mechanistic insights, including putative causal variants and the context (cell type and cell state) in which they function, has been limited. Here, we present a comprehensive multi-omic integrative analysis of single-cell/nucleus resolution profiles of gene expression and chromatin accessibility in healthy and autoantibody+ (AAB+) human islets, as well as islets under multiple T1D stimulatory conditions. We broadly nominate effector cell types for all T1D GWAS signals. We further nominated higher-resolution contexts, including effector cell types, regulatory elements, and genes for three independent T1D risk variants acting through islet cells within the pancreas at the DLK1/MEG3, RASGRP1, and TOX loci. Subsequently, we created isogenic gene knockouts DLK1-/-, RASGRP1-/-, and TOX-/-, and the corresponding regulatory region knockout, RASGRP1Δ, and DLK1Δ hESCs. Loss of RASGRP1 or DLK1, as well as knockout of the regulatory region of RASGRP1 or DLK1, increased β cell apoptosis. Additionally, pancreatic β cells derived from isogenic hESCs carrying the risk allele of rs3783355A/A exhibited increased β cell death. Finally, RNA-seq and ATAC-seq identified five genes upregulated in both RASGRP1-/- and DLK1-/- β-like cells, four of which are associated with T1D. Together, this work reports an integrative approach for combining single cell multi-omics, GWAS, and isogenic hESC-derived β-like cells to prioritize the T1D associated signals and their underlying context-specific cell types, genes, SNPs, and regulatory elements, to illuminate biological functions and molecular mechanisms.
Collapse
Affiliation(s)
- Zeping Zhao
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
- Center for Genomic Health, Weill Cornell Medicine, 1300 York Ave, New York, NY 15 10065, USA
| | | | - Henry Taylor
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Xuming Tang
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
- Center for Genomic Health, Weill Cornell Medicine, 1300 York Ave, New York, NY 15 10065, USA
| | - Yuling Han
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
- Center for Genomic Health, Weill Cornell Medicine, 1300 York Ave, New York, NY 15 10065, USA
| | - Peter Orchard
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Arushi Varshney
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Tuo Zhang
- Stem Cell Research Facility, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA
| | - Nandini Manickam
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Mike Erdos
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Narisu Narisu
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Leland Taylor
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Xiaxia Saavedra
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
| | - Aaron Zhong
- Genomic Resource Core Facility, Weill Cornell Medical College, NY 10065, USA
| | - Bo Li
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
| | - Ting Zhou
- Genomic Resource Core Facility, Weill Cornell Medical College, NY 10065, USA
| | - Ali Naji
- Department of Surgery, University of Pennsylvania School of Medicine, Philadelphia, PA19104, USA
| | - Chengyang Liu
- Department of Surgery, University of Pennsylvania School of Medicine, Philadelphia, PA19104, USA
| | - Francis Collins
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Stephen CJ Parker
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Shuibing Chen
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
- Center for Genomic Health, Weill Cornell Medicine, 1300 York Ave, New York, NY 15 10065, USA
| |
Collapse
|
28
|
Shi W, Ye J, Shi Z, Pan C, Zhang Q, Lin Y, Liang D, Liu Y, Lin X, Zheng Y. Single-cell chromatin accessibility and transcriptomic characterization of Behcet's disease. Commun Biol 2023; 6:1048. [PMID: 37848613 PMCID: PMC10582193 DOI: 10.1038/s42003-023-05420-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 10/04/2023] [Indexed: 10/19/2023] Open
Abstract
Behect's disease is a chronic vasculitis characterized by complex multi-organ immune aberrations. However, a comprehensive understanding of the gene-regulatory profile of peripheral autoimmunity and the diverse immune responses across distinct cell types in Behcet's disease (BD) is still lacking. Here, we present a multi-omic single-cell study of 424,817 cells in BD patients and non-BD individuals. This study maps chromatin accessibility and gene expression in the same biological samples, unraveling vast cellular heterogeneity. We identify widespread cell-type-specific, disease-associated active and pro-inflammatory immunity in both transcript and epigenomic aspects. Notably, integrative multi-omic analysis reveals putative TF regulators that might contribute to chromatin accessibility and gene expression in BD. Moreover, we predicted gene-regulatory networks within nominated TF activators, including AP-1, NF-kB, and ETS transcript factor families, which may regulate cellular interaction and govern inflammation. Our study illustrates the epigenetic and transcriptional landscape in BD peripheral blood and expands understanding of potential epigenomic immunopathology in this disease.
Collapse
Affiliation(s)
- Wen Shi
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, 510060, Guangzhou, China
- Research Unit of Ocular Development and Regeneration, Chinese Academy of Medical Sciences, 100085, Beijing, China
| | - Jinguo Ye
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, 510060, Guangzhou, China
| | - Zhuoxing Shi
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, 510060, Guangzhou, China
| | - Caineng Pan
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, 510060, Guangzhou, China
| | - Qikai Zhang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, 510060, Guangzhou, China
| | - Yuheng Lin
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, 510060, Guangzhou, China
| | - Dan Liang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, 510060, Guangzhou, China.
| | - Yizhi Liu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, 510060, Guangzhou, China.
- Research Unit of Ocular Development and Regeneration, Chinese Academy of Medical Sciences, 100085, Beijing, China.
| | - Xianchai Lin
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, 510060, Guangzhou, China.
- Research Unit of Ocular Development and Regeneration, Chinese Academy of Medical Sciences, 100085, Beijing, China.
| | - Yingfeng Zheng
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, 510060, Guangzhou, China.
- Research Unit of Ocular Development and Regeneration, Chinese Academy of Medical Sciences, 100085, Beijing, China.
| |
Collapse
|
29
|
Hu M, Kim I, Morán I, Peng W, Sun O, Bonnefond A, Khamis A, Bonas-Guarch S, Froguel P, Rutter GA. Multiple genetic variants at the SLC30A8 locus affect local super-enhancer activity and influence pancreatic β-cell survival and function. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.13.548906. [PMID: 37502937 PMCID: PMC10369998 DOI: 10.1101/2023.07.13.548906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Variants at the SLC30A8 locus are associated with type 2 diabetes (T2D) risk. The lead variant, rs13266634, encodes an amino acid change, Arg325Trp (R325W), at the C-terminus of the secretory granule-enriched zinc transporter, ZnT8. Although this protein-coding variant was previously thought to be the sole driver of T2D risk at this locus, recent studies have provided evidence for lowered expression of SLC30A8 mRNA in protective allele carriers. In the present study, combined allele-specific expression (cASE) analysis in human islets revealed multiple variants that influence SLC30A8 expression. Epigenomic mapping identified an islet-selective enhancer cluster at the SLC30A8 locus, hosting multiple T2D risk and cASE associations, which is spatially associated with the SLC30A8 promoter and additional neighbouring genes. Deletions of variant-bearing enhancer regions using CRISPR-Cas9 in human-derived EndoC-βH3 cells lowered the expression of SLC30A8 and several neighbouring genes, and improved insulin secretion. Whilst down-regulation of SLC30A8 had no effect on beta cell survival, loss of UTP23, RAD21 or MED30 markedly reduced cell viability. Although eQTL or cASE analyses in human islets did not support the association between these additional genes and diabetes risk, the transcriptional regulator JQ1 lowered the expression of multiple genes at the SLC30A8 locus and enhanced stimulated insulin secretion.
Collapse
Affiliation(s)
- Ming Hu
- Section of Cell Biology and Functional Genomics, Division of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Du Cane Road, London W12 0NN, UK
| | - Innah Kim
- Section of Cell Biology and Functional Genomics, Division of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Du Cane Road, London W12 0NN, UK
| | - Ignasi Morán
- Life Sciences Department, Barcelona Supercomputing Center (BSC-CNS), 08034 Barcelona, Spain
| | - Weicong Peng
- Section of Cell Biology and Functional Genomics, Division of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Du Cane Road, London W12 0NN, UK
| | - Orien Sun
- Section of Cell Biology and Functional Genomics, Division of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Du Cane Road, London W12 0NN, UK
| | - Amélie Bonnefond
- Department of Metabolism, Digestion, and Reproduction, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London W12 0NN, UK
- Inserm U1283, CNRS UMR 8199, EGID, Institut Pasteur de Lille, F-59000, France
- University of Lille, Lille University Hospital, Lille, F-59000, France.France
| | - Amna Khamis
- Department of Metabolism, Digestion, and Reproduction, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London W12 0NN, UK
- Inserm U1283, CNRS UMR 8199, EGID, Institut Pasteur de Lille, F-59000, France
- University of Lille, Lille University Hospital, Lille, F-59000, France.France
| | - Silvia Bonas-Guarch
- Department of Metabolism, Digestion, and Reproduction, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London W12 0NN, UK
- Center for Genomic Regulation (CRG), C/ Dr. Aiguader, 88, PRBB Building, 08003 Barcelona, Spain
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Spain
| | - Philippe Froguel
- Department of Metabolism, Digestion, and Reproduction, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London W12 0NN, UK
- Inserm U1283, CNRS UMR 8199, EGID, Institut Pasteur de Lille, F-59000, France
- University of Lille, Lille University Hospital, Lille, F-59000, France.France
| | - Guy A. Rutter
- Section of Cell Biology and Functional Genomics, Division of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Du Cane Road, London W12 0NN, UK
- Centre de Recherche du CHUM, Faculté de Médicine, Université de Montréal, Montréal, QC, Canada
- Lee Kong Chian Imperial Medical School, Nanyang Technological University, Singapore
| |
Collapse
|
30
|
van Duijvenboden S, Ramírez J, Young WJ, Olczak KJ, Ahmed F, Alhammadi MJAY, Bell CG, Morris AP, Munroe PB. Integration of genetic fine-mapping and multi-omics data reveals candidate effector genes for hypertension. Am J Hum Genet 2023; 110:1718-1734. [PMID: 37683633 PMCID: PMC10577090 DOI: 10.1016/j.ajhg.2023.08.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 08/11/2023] [Accepted: 08/11/2023] [Indexed: 09/10/2023] Open
Abstract
Genome-wide association studies of blood pressure (BP) have identified >1,000 loci, but the effector genes and biological pathways at these loci are mostly unknown. Using published association summary statistics, we conducted annotation-informed fine-mapping incorporating tissue-specific chromatin segmentation and colocalization to identify causal variants and candidate effector genes for systolic BP, diastolic BP, and pulse pressure. We observed 532 distinct signals associated with ≥2 BP traits and 84 with all three. For >20% of signals, a single variant accounted for >75% posterior probability, 65 were missense variants in known (SLC39A8, ADRB2, and DBH) and previously unreported BP candidate genes (NRIP1 and MMP14). In disease-relevant tissues, we colocalized >80 and >400 distinct signals for each BP trait with cis-eQTLs and regulatory regions from promoter capture Hi-C, respectively. Integrating mouse, human disorder, gene expression and tissue abundance data, and literature review, we provide consolidated evidence for 436 BP candidate genes for future functional validation and discover several potential drug targets.
Collapse
Affiliation(s)
- Stefan van Duijvenboden
- William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, EC1M 6BQ London, UK; Institute of Cardiovascular Science, University College London, London, UK; Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Julia Ramírez
- William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, EC1M 6BQ London, UK; Aragon Institute of Engineering Research, University of Zaragoza, Zaragoza, Spain; Centro de Investigación Biomédica en Red - Bioingeniería, Biomateriales y Nanomedicina, Zaragoza, Spain
| | - William J Young
- William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, EC1M 6BQ London, UK; Barts Heart Centre, St Bartholomew's Hospital, EC1A 7BE London, UK
| | - Kaya J Olczak
- William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, EC1M 6BQ London, UK
| | - Farah Ahmed
- William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, EC1M 6BQ London, UK
| | | | - Christopher G Bell
- William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, EC1M 6BQ London, UK
| | - Andrew P Morris
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, The University of Manchester, Manchester, UK; National Institute of Health and Care Research, Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK.
| | - Patricia B Munroe
- William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, EC1M 6BQ London, UK; National Institute of Health and Care Research, Barts Cardiovascular Biomedical Research Centre, Queen Mary University of London, EC1M 6BQ London, UK.
| |
Collapse
|
31
|
Hou L, Xiong X, Park Y, Boix C, James B, Sun N, He L, Patel A, Zhang Z, Molinie B, Van Wittenberghe N, Steelman S, Nusbaum C, Aguet F, Ardlie KG, Kellis M. Multitissue H3K27ac profiling of GTEx samples links epigenomic variation to disease. Nat Genet 2023; 55:1665-1676. [PMID: 37770633 PMCID: PMC10562256 DOI: 10.1038/s41588-023-01509-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2022] [Accepted: 08/22/2023] [Indexed: 09/30/2023]
Abstract
Genetic variants associated with complex traits are primarily noncoding, and their effects on gene-regulatory activity remain largely uncharacterized. To address this, we profile epigenomic variation of histone mark H3K27ac across 387 brain, heart, muscle and lung samples from Genotype-Tissue Expression (GTEx). We annotate 282 k active regulatory elements (AREs) with tissue-specific activity patterns. We identify 2,436 sex-biased AREs and 5,397 genetically influenced AREs associated with 130 k genetic variants (haQTLs) across tissues. We integrate genetic and epigenomic variation to provide mechanistic insights for disease-associated loci from 55 genome-wide association studies (GWAS), by revealing candidate tissues of action, driver SNPs and impacted AREs. Lastly, we build ARE-gene linking scores based on genetics (gLink scores) and demonstrate their unique ability to prioritize SNP-ARE-gene circuits. Overall, our epigenomic datasets, computational integration and mechanistic predictions provide valuable resources and important insights for understanding the molecular basis of human diseases/traits such as schizophrenia.
Collapse
Affiliation(s)
- Lei Hou
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, MA, USA
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Xushen Xiong
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, MA, USA
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Liangzhu Laboratory, Zhejiang University, Hangzhou, China
| | - Yongjin Park
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, MA, USA
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Carles Boix
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, MA, USA
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Benjamin James
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, MA, USA
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Na Sun
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, MA, USA
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Liang He
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, MA, USA
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Aman Patel
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, MA, USA
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Zhizhuo Zhang
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, MA, USA
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Benoit Molinie
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | | | - Scott Steelman
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Chad Nusbaum
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - François Aguet
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | | | - Manolis Kellis
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, MA, USA.
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA.
| |
Collapse
|
32
|
Yang X, Wen J, Yang H, Jones IR, Zhu X, Liu W, Li B, Clelland CD, Luo W, Wong MY, Ren X, Cui X, Song M, Liu H, Chen C, Eng N, Ravichandran M, Sun Y, Lee D, Van Buren E, Jiang MZ, Chan CSY, Ye CJ, Perera RM, Gan L, Li Y, Shen Y. Functional characterization of Alzheimer's disease genetic variants in microglia. Nat Genet 2023; 55:1735-1744. [PMID: 37735198 PMCID: PMC10939305 DOI: 10.1038/s41588-023-01506-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 08/20/2023] [Indexed: 09/23/2023]
Abstract
Candidate cis-regulatory elements (cCREs) in microglia demonstrate the most substantial enrichment for Alzheimer's disease (AD) heritability compared to other brain cell types. However, whether and how these genome-wide association studies (GWAS) variants contribute to AD remain elusive. Here we prioritize 308 previously unreported AD risk variants at 181 cCREs by integrating genetic information with microglia-specific 3D epigenome annotation. We further establish the link between functional variants and target genes by single-cell CRISPRi screening in microglia. In addition, we show that AD variants exhibit allelic imbalance on target gene expression. In particular, rs7922621 is the effective variant in controlling TSPAN14 expression among other nominated variants in the same cCRE and exerts multiple physiological effects including reduced cell surface ADAM10 and altered soluble TREM2 (sTREM2) shedding. Our work represents a systematic approach to prioritize and characterize AD-associated variants and provides a roadmap for advancing genetic association to experimentally validated cell-type-specific phenotypes and mechanisms.
Collapse
Affiliation(s)
- Xiaoyu Yang
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Jia Wen
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Han Yang
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Ian R Jones
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
- Pharmaceutical Sciences and Pharmacogenomics Graduate Program, University of California, San Francisco, San Francisco, CA, USA
| | - Xiaodong Zhu
- Helen and Robert Appel Alzheimer's Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York City, NY, USA
| | - Weifang Liu
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC, USA
| | - Bingkun Li
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Claire D Clelland
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Wenjie Luo
- Helen and Robert Appel Alzheimer's Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York City, NY, USA
| | - Man Ying Wong
- Helen and Robert Appel Alzheimer's Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York City, NY, USA
| | - Xingjie Ren
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Xiekui Cui
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Michael Song
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
- Pharmaceutical Sciences and Pharmacogenomics Graduate Program, University of California, San Francisco, San Francisco, CA, USA
| | - Hongjiang Liu
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Cady Chen
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Nicolas Eng
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | | | - Yang Sun
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
- Division of Rheumatology, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - David Lee
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
- Division of Rheumatology, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Eric Van Buren
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Min-Zhi Jiang
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Candace S Y Chan
- Tetrad Graduate Program, University of California, San Francisco, San Francisco, CA, USA
| | - Chun Jimmie Ye
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
- Division of Rheumatology, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- Rosalind Russell/Ephraim P. Engleman Rheumatology Research Center, University of California, San Francisco, San Francisco, CA, USA
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
- Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Rushika M Perera
- Department of Anatomy, University of California, San Francisco, San Francisco, CA, USA
- Department of Pathology, University of California, San Francisco, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
| | - Li Gan
- Helen and Robert Appel Alzheimer's Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York City, NY, USA
| | - Yun Li
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA.
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC, USA.
- Department of Computer Science, University of North Carolina, Chapel Hill, NC, USA.
| | - Yin Shen
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA.
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA.
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.
| |
Collapse
|
33
|
Ahangari M, Gentry AE, Hassan MF, Nguyen TH, Kendler KS, Bacanu SA, Peterson RE, Riley BP, Webb BT. Improving the discovery of rare variants associated with alcohol problems by leveraging machine learning phenotype prediction and functional information. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.11.557163. [PMID: 37745400 PMCID: PMC10515858 DOI: 10.1101/2023.09.11.557163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Alcohol use disorder (AUD) is moderately heritable with significant social and economic impact. Genome-wide association studies (GWAS) have identified common variants associated with AUD, however, rare variant investigations have yet to achieve well-powered sample sizes. In this study, we conducted an interval-based exome-wide analysis of the Alcohol Use Disorder Identification Test Problems subscale (AUDIT-P) using both machine learning (ML) predicted risk and empirical functional weights. This research has been conducted using the UK Biobank Resource (application number 30782.) Filtering the 200k exome release to unrelated individuals of European ancestry resulted in a sample of 147,386 individuals with 51,357 observed and 96,029 unmeasured but predicted AUDIT-P for exome analysis. Sequence Kernel Association Test (SKAT/SKAT-O) was used for rare variant (Minor Allele Frequency (MAF) < 0.01) interval analyses using default and empirical weights. Empirical weights were constructed using annotations found significant by stratified LD Score Regression analysis of predicted AUDIT-P GWAS, providing prior functional weights specific to AUDIT-P. Using only samples with observed AUDIT-P yielded no significantly associated intervals. In contrast, ADH1C and THRA gene intervals were significant (False discovery rate (FDR) <0.05) using default and empirical weights in the predicted AUDIT-P sample, with the most significant association found using predicted AUDIT-P and empirical weights in the ADH1C gene (SKAT-O P Default = 1.06 x 10 -9 and P Empirical weight = 6.25 x 10 -11 ). These findings provide evidence for rare variant association of the ADH1C gene with the AUDIT-P and highlight the successful leveraging of ML to increase effective sample size and prior empirical functional weights based on common variant GWAS data to refine and increase the statistical significance in underpowered phenotypes.
Collapse
|
34
|
Quaye LNK, Dalzell CE, Deloukas P, Smith AJP. The Genetics of Coronary Artery Disease: A Vascular Perspective. Cells 2023; 12:2232. [PMID: 37759455 PMCID: PMC10527262 DOI: 10.3390/cells12182232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 08/31/2023] [Accepted: 09/01/2023] [Indexed: 09/29/2023] Open
Abstract
Genome-wide association studies (GWAS) have identified a large number of genetic loci for coronary artery disease (CAD), with many located close to genes associated with traditional CAD risk pathways, such as lipid metabolism and inflammation. It is becoming evident with recent CAD GWAS meta-analyses that vascular pathways are also highly enriched and present an opportunity for novel therapeutics. This review examines GWAS-enriched vascular gene loci, the pathways involved and their potential role in CAD pathogenesis. The functionality of variants is explored from expression quantitative trait loci, massively parallel reporter assays and CRISPR-based gene-editing tools. We discuss how this research may lead to novel therapeutic tools to treat cardiovascular disorders.
Collapse
Affiliation(s)
| | | | - Panos Deloukas
- William Harvey Research Institute, Faculty of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK; (L.N.K.Q.); (C.E.D.); (A.J.P.S.)
| | | |
Collapse
|
35
|
Amariuta T, Siewert-Rocks K, Price AL. Modeling tissue co-regulation estimates tissue-specific contributions to disease. Nat Genet 2023; 55:1503-1511. [PMID: 37580597 PMCID: PMC10904330 DOI: 10.1038/s41588-023-01474-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 07/13/2023] [Indexed: 08/16/2023]
Abstract
Integrative analyses of genome-wide association studies and gene expression data have implicated many disease-critical tissues. However, co-regulation of genetic effects on gene expression across tissues impedes distinguishing biologically causal tissues from tagging tissues. In the present study, we introduce tissue co-regulation score regression (TCSC), which disentangles causal tissues from tagging tissues by regressing gene-disease association statistics (from transcriptome-wide association studies) on tissue co-regulation scores, reflecting correlations of predicted gene expression across genes and tissues. We applied TCSC to 78 diseases/traits (average n = 302,000) and gene expression prediction models for 48 GTEx tissues. TCSC identified 21 causal tissue-trait pairs at a 5% false discovery rate (FDR), including well-established findings, biologically plausible new findings (for example, aorta artery and glaucoma) and increased specificity of known tissue-trait associations (for example, subcutaneous adipose, but not visceral adipose, and high-density lipoprotein). TCSC also identified 17 causal tissue-trait covariance pairs at 5% FDR. In conclusion, TCSC is a precise method for distinguishing causal tissues from tagging tissues.
Collapse
Affiliation(s)
- Tiffany Amariuta
- Halıcıoğlu Data Science Institute, University of California San Diego, La Jolla, CA, USA.
- Department of Medicine, University of California San Diego, La Jolla, CA, USA.
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Katherine Siewert-Rocks
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Alkes L Price
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| |
Collapse
|
36
|
Selewa A, Luo K, Wasney M, Smith L, Sun X, Tang C, Eckart H, Moskowitz IP, Basu A, He X, Pott S. Single-cell genomics improves the discovery of risk variants and genes of atrial fibrillation. Nat Commun 2023; 14:4999. [PMID: 37591828 PMCID: PMC10435551 DOI: 10.1038/s41467-023-40505-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 08/01/2023] [Indexed: 08/19/2023] Open
Abstract
Genome-wide association studies (GWAS) have linked hundreds of loci to cardiac diseases. However, in most loci the causal variants and their target genes remain unknown. We developed a combined experimental and analytical approach that integrates single cell epigenomics with GWAS to prioritize risk variants and genes. We profiled accessible chromatin in single cells obtained from human hearts and leveraged the data to study genetics of Atrial Fibrillation (AF), the most common cardiac arrhythmia. Enrichment analysis of AF risk variants using cell-type-resolved open chromatin regions (OCRs) implicated cardiomyocytes as the main mediator of AF risk. We then performed statistical fine-mapping, leveraging the information in OCRs, and identified putative causal variants in 122 AF-associated loci. Taking advantage of the fine-mapping results, our novel statistical procedure for gene discovery prioritized 46 high-confidence risk genes, highlighting transcription factors and signal transduction pathways important for heart development. In summary, our analysis provides a comprehensive map of AF risk variants and genes, and a general framework to integrate single-cell genomics with genetic studies of complex traits.
Collapse
Affiliation(s)
- Alan Selewa
- Biophysical Sciences Graduate Program, The University of Chicago, Chicago, IL, 60637, USA
| | - Kaixuan Luo
- Department of Human Genetics, The University of Chicago, Chicago, IL, 60637, USA
| | - Michael Wasney
- Department of Medicine, Section of Genetic Medicine, The University of Chicago, Chicago, IL, 60637, USA
| | - Linsin Smith
- Committee on Genetics, Genomics and Systems Biology, The University of Chicago, Chicago, IL, 60637, USA
| | - Xiaotong Sun
- Department of Human Genetics, The University of Chicago, Chicago, IL, 60637, USA
| | - Chenwei Tang
- The College, The University of Chicago, Chicago, IL, 60637, USA
| | - Heather Eckart
- Department of Medicine, Section of Genetic Medicine, The University of Chicago, Chicago, IL, 60637, USA
| | - Ivan P Moskowitz
- Department of Human Genetics, The University of Chicago, Chicago, IL, 60637, USA
- Department of Pediatrics, The University of Chicago, Chicago, IL, 60637, USA
| | - Anindita Basu
- Department of Medicine, Section of Genetic Medicine, The University of Chicago, Chicago, IL, 60637, USA.
| | - Xin He
- Department of Human Genetics, The University of Chicago, Chicago, IL, 60637, USA.
| | - Sebastian Pott
- Department of Medicine, Section of Genetic Medicine, The University of Chicago, Chicago, IL, 60637, USA.
| |
Collapse
|
37
|
Choi J, Kim S, Kim J, Son HY, Yoo SK, Kim CU, Park YJ, Moon S, Cha B, Jeon MC, Park K, Yun JM, Cho B, Kim N, Kim C, Kwon NJ, Park YJ, Matsuda F, Momozawa Y, Kubo M, Kim HJ, Park JH, Seo JS, Kim JI, Im SW. A whole-genome reference panel of 14,393 individuals for East Asian populations accelerates discovery of rare functional variants. SCIENCE ADVANCES 2023; 9:eadg6319. [PMID: 37556544 PMCID: PMC10411914 DOI: 10.1126/sciadv.adg6319] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 07/06/2023] [Indexed: 08/11/2023]
Abstract
Underrepresentation of non-European (EUR) populations hinders growth of global precision medicine. Resources such as imputation reference panels that match the study population are necessary to find low-frequency variants with substantial effects. We created a reference panel consisting of 14,393 whole-genome sequences including more than 11,000 Asian individuals. Genome-wide association studies were conducted using the reference panel and a population-specific genotype array of 72,298 subjects for eight phenotypes. This panel yields improved imputation accuracy of rare and low-frequency variants within East Asian populations compared with the largest reference panel. Thirty-nine previously unidentified associations were found, and more than half of the variants were East Asian specific. We discovered genes with rare protein-altering variants, including LTBP1 for height and GPR75 for body mass index, as well as putative regulatory mechanisms for rare noncoding variants with cell type-specific effects. We suggest that this dataset will add to the potential value of Asian precision medicine.
Collapse
Affiliation(s)
- Jaeyong Choi
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea
| | | | - Juhyun Kim
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Ho-Young Son
- Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, Republic of Korea
| | - Seong-Keun Yoo
- The Marc and Jennifer Lipschultz Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Young Jun Park
- Department of Translational Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Sungji Moon
- Interdisciplinary Program in Cancer Biology, Seoul National University College of Medicine, Seoul, Republic of Korea
- Cancer Research Institute, Seoul National University, Seoul, Republic of Korea
| | - Bukyoung Cha
- Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, Republic of Korea
| | - Min Chul Jeon
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Kyunghyuk Park
- Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, Republic of Korea
| | - Jae Moon Yun
- Department of Family Medicine, Seoul National University Hospital, Seoul, Republic of Korea
| | - Belong Cho
- Department of Family Medicine, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Family Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | | | | | | | - Young Joo Park
- Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, Republic of Korea
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Republic of Korea
| | - Fumihiko Matsuda
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | | | - Michiaki Kubo
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | | | - Hyun-Jin Kim
- National Cancer Control Institute, National Cancer Center, Goyang, Republic of Korea
| | - Jin-Ho Park
- Department of Family Medicine, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Family Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jeong-Sun Seo
- Macrogen Inc., Seoul, Republic of Korea
- Asian Genome Center, Seoul National University Bundang Hospital, Gyeonggi, Republic of Korea
| | - Jong-Il Kim
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea
- Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, Republic of Korea
- Cancer Research Institute, Seoul National University, Seoul, Republic of Korea
- Department of Biochemistry and Molecular Biology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Sun-Wha Im
- Department of Biochemistry and Molecular Biology, Kangwon National University School of Medicine, Gangwon, Republic of Korea
| |
Collapse
|
38
|
Gaulton KJ, Preissl S, Ren B. Interpreting non-coding disease-associated human variants using single-cell epigenomics. Nat Rev Genet 2023; 24:516-534. [PMID: 37161089 PMCID: PMC10629587 DOI: 10.1038/s41576-023-00598-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/27/2023] [Indexed: 05/11/2023]
Abstract
Genome-wide association studies (GWAS) have linked hundreds of thousands of sequence variants in the human genome to common traits and diseases. However, translating this knowledge into a mechanistic understanding of disease-relevant biology remains challenging, largely because such variants are predominantly in non-protein-coding sequences that still lack functional annotation at cell-type resolution. Recent advances in single-cell epigenomics assays have enabled the generation of cell type-, subtype- and state-resolved maps of the epigenome in heterogeneous human tissues. These maps have facilitated cell type-specific annotation of candidate cis-regulatory elements and their gene targets in the human genome, enhancing our ability to interpret the genetic basis of common traits and diseases.
Collapse
Affiliation(s)
- Kyle J Gaulton
- Department of Paediatrics, Paediatric Diabetes Research Center, University of California San Diego School of Medicine, La Jolla, CA, USA.
| | - Sebastian Preissl
- Center for Epigenomics, University of California San Diego School of Medicine, La Jolla, CA, USA.
- Institute of Experimental and Clinical Pharmacology and Toxicology, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
| | - Bing Ren
- Center for Epigenomics, University of California San Diego School of Medicine, La Jolla, CA, USA.
- Department of Cellular and Molecular Medicine, University of California San Diego School of Medicine, La Jolla, CA, USA.
- Ludwig Institute for Cancer Research, La Jolla, CA, USA.
| |
Collapse
|
39
|
Fan K, Pfister E, Weng Z. Toward a comprehensive catalog of regulatory elements. Hum Genet 2023; 142:1091-1111. [PMID: 36935423 DOI: 10.1007/s00439-023-02519-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Accepted: 01/03/2023] [Indexed: 03/21/2023]
Abstract
Regulatory elements are the genomic regions that interact with transcription factors to control cell-type-specific gene expression in different cellular environments. A precise and complete catalog of functional elements encoded by the human genome is key to understanding mammalian gene regulation. Here, we review the current state of regulatory element annotation. We first provide an overview of assays for characterizing functional elements, including genome, epigenome, transcriptome, three-dimensional chromatin interaction, and functional validation assays. We then discuss computational methods for defining regulatory elements, including peak-calling and other statistical modeling methods. Finally, we introduce several high-quality lists of regulatory element annotations and suggest potential future directions.
Collapse
Affiliation(s)
- Kaili Fan
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, 368 Plantation Street, ASC5-1069, Worcester, MA, 01605, USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138, USA
| | - Edith Pfister
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, 368 Plantation Street, ASC5-1069, Worcester, MA, 01605, USA
| | - Zhiping Weng
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, 368 Plantation Street, ASC5-1069, Worcester, MA, 01605, USA.
| |
Collapse
|
40
|
Everman ER, Macdonald SJ. Gene expression variation underlying tissue-specific responses to copper stress in Drosophila melanogaster. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.12.548746. [PMID: 37503205 PMCID: PMC10370140 DOI: 10.1101/2023.07.12.548746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Copper is one of a handful of biologically necessary heavy metals that is also a common environmental pollutant. Under normal conditions, copper ions are required for many key physiological processes. However, in excess, copper quickly results in cell and tissue damage that can range in severity from temporary injury to permanent neurological damage. Because of its biological relevance, and because many conserved copper-responsive genes also respond to other non-essential heavy metal pollutants, copper resistance in Drosophila melanogaster is a useful model system with which to investigate the genetic control of the response to heavy metal stress. Because heavy metal toxicity has the potential to differently impact specific tissues, we genetically characterized the control of the gene expression response to copper stress in a tissue-specific manner in this study. We assessed the copper stress response in head and gut tissue of 96 inbred strains from the Drosophila Synthetic Population Resource (DSPR) using a combination of differential expression analysis and expression quantitative trait locus (eQTL) mapping. Differential expression analysis revealed clear patterns of tissue-specific expression, primarily driven by a more pronounced gene expression response in gut tissue. eQTL mapping of gene expression under control and copper conditions as well as for the change in gene expression following copper exposure (copper response eQTL) revealed hundreds of genes with tissue-specific local cis-eQTL and many distant trans-eQTL. eQTL associated with MtnA, Mdr49, Mdr50, and Sod3 exhibited genotype by environment effects on gene expression under copper stress, illuminating several tissue- and treatment-specific patterns of gene expression control. Together, our data build a nuanced description of the roles and interactions between allelic and expression variation in copper-responsive genes, provide valuable insight into the genomic architecture of susceptibility to metal toxicity, and highlight many candidate genes for future functional characterization.
Collapse
Affiliation(s)
- Elizabeth R Everman
- 1200 Sunnyside Ave, University of Kansas, Molecular Biosciences, Lawrence, KS 66045, USA
- 730 Van Vleet Oval, University of Oklahoma, Biology, Norman, OK 73019, USA
| | - Stuart J Macdonald
- 1200 Sunnyside Ave, University of Kansas, Molecular Biosciences, Lawrence, KS 66045, USA
- 1200 Sunnyside Ave, University of Kansas, Center for Computational Biology, Lawrence, KS 66045, USA
| |
Collapse
|
41
|
Deng Q, Gupta A, Jeon H, Nam JH, Yilmaz AS, Chang W, Pietrzak M, Li L, Kim HJ, Chung D. graph-GPA 2.0: improving multi-disease genetic analysis with integration of functional annotation data. Front Genet 2023; 14:1079198. [PMID: 37501720 PMCID: PMC10370274 DOI: 10.3389/fgene.2023.1079198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 06/21/2023] [Indexed: 07/29/2023] Open
Abstract
Genome-wide association studies (GWAS) have successfully identified a large number of genetic variants associated with traits and diseases. However, it still remains challenging to fully understand the functional mechanisms underlying many associated variants. This is especially the case when we are interested in variants shared across multiple phenotypes. To address this challenge, we propose graph-GPA 2.0 (GGPA 2.0), a statistical framework to integrate GWAS datasets for multiple phenotypes and incorporate functional annotations within a unified framework. Our simulation studies showed that incorporating functional annotation data using GGPA 2.0 not only improves the detection of disease-associated variants, but also provides a more accurate estimation of relationships among diseases. Next, we analyzed five autoimmune diseases and five psychiatric disorders with the functional annotations derived from GenoSkyline and GenoSkyline-Plus, along with the prior disease graph generated by biomedical literature mining. For autoimmune diseases, GGPA 2.0 identified enrichment for blood-related epigenetic marks, especially B cells and regulatory T cells, across multiple diseases. Psychiatric disorders were enriched for brain-related epigenetic marks, especially the prefrontal cortex and the inferior temporal lobe for bipolar disorder and schizophrenia, respectively. In addition, the pleiotropy between bipolar disorder and schizophrenia was also detected. Finally, we found that GGPA 2.0 is robust to the use of irrelevant and/or incorrect functional annotations. These results demonstrate that GGPA 2.0 can be a powerful tool to identify genetic variants associated with each phenotype or those shared across multiple phenotypes, while also promoting an understanding of functional mechanisms underlying the associated variants.
Collapse
Affiliation(s)
- Qiaolan Deng
- The Interdisciplinary PhD Program in Biostatistics, The Ohio State University, Columbus, OH, United States
| | - Arkobrato Gupta
- The Interdisciplinary PhD Program in Biostatistics, The Ohio State University, Columbus, OH, United States
| | - Hyeongseon Jeon
- Department of Biomedical Informatics, The Ohio State University, Columbus, OH, United States
- Pelotonia Institute for Immuno-Oncology, The James Comprehensive Cancer Center, The Ohio State University, Columbus, OH, United States
| | - Jin Hyun Nam
- Division of Big Data Science, Korea University Sejong Campus, Sejong, Republic of Korea
| | - Ayse Selen Yilmaz
- Department of Biomedical Informatics, The Ohio State University, Columbus, OH, United States
| | - Won Chang
- Division of Statistics and Data Science, University of Cincinnati, Cincinnati, OH, United States
| | - Maciej Pietrzak
- Department of Biomedical Informatics, The Ohio State University, Columbus, OH, United States
| | - Lang Li
- Department of Biomedical Informatics, The Ohio State University, Columbus, OH, United States
| | - Hang J. Kim
- Division of Statistics and Data Science, University of Cincinnati, Cincinnati, OH, United States
| | - Dongjun Chung
- Department of Biomedical Informatics, The Ohio State University, Columbus, OH, United States
- Pelotonia Institute for Immuno-Oncology, The James Comprehensive Cancer Center, The Ohio State University, Columbus, OH, United States
| |
Collapse
|
42
|
Kentistou KA, Kaisinger LR, Stankovic S, Vaudel M, de Oliveira EM, Messina A, Walters RG, Liu X, Busch AS, Helgason H, Thompson DJ, Santon F, Petricek KM, Zouaghi Y, Huang-Doran I, Gudbjartsson DF, Bratland E, Lin K, Gardner EJ, Zhao Y, Jia R, Terao C, Riggan M, Bolla MK, Yazdanpanah M, Yazdanpanah N, Bradfield JP, Broer L, Campbell A, Chasman DI, Cousminer DL, Franceschini N, Franke LH, Girotto G, He C, Järvelin MR, Joshi PK, Kamatani Y, Karlsson R, Luan J, Lunetta KL, Mägi R, Mangino M, Medland SE, Meisinger C, Noordam R, Nutile T, Concas MP, Polašek O, Porcu E, Ring SM, Sala C, Smith AV, Tanaka T, van der Most PJ, Vitart V, Wang CA, Willemsen G, Zygmunt M, Ahearn TU, Andrulis IL, Anton-Culver H, Antoniou AC, Auer PL, Barnes CLK, Beckmann MW, Berrington A, Bogdanova NV, Bojesen SE, Brenner H, Buring JE, Canzian F, Chang-Claude J, Couch FJ, Cox A, Crisponi L, Czene K, Daly MB, Demerath EW, Dennis J, Devilee P, Vivo ID, Dörk T, Dunning AM, Dwek M, Eriksson JG, Fasching PA, Fernandez-Rhodes L, Ferreli L, Fletcher O, Gago-Dominguez M, García-Closas M, García-Sáenz JA, González-Neira A, Grallert H, Guénel P, Haiman CA, Hall P, Hamann U, Hakonarson H, Hart RJ, Hickey M, Hooning MJ, Hoppe R, Hopper JL, Hottenga JJ, Hu FB, Hübner H, Hunter DJ, Jernström H, John EM, Karasik D, Khusnutdinova EK, Kristensen VN, Lacey JV, Lambrechts D, Launer LJ, Lind PA, Lindblom A, Magnusson PKE, Mannermaa A, McCarthy MI, Meitinger T, Menni C, Michailidou K, Millwood IY, Milne RL, Montgomery GW, Nevanlinna H, Nolte IM, Nyholt DR, Obi N, O’Brien KM, Offit K, Oldehinkel AJ, Ostrowski SR, Palotie A, Pedersen OB, Peters A, Pianigiani G, Plaseska-Karanfilska D, Pouta A, Pozarickij A, Radice P, Rennert G, Rosendaal FR, Ruggiero D, Saloustros E, Sandler DP, Schipf S, Schmidt CO, Schmidt MK, Small K, Spedicati B, Stampfer M, Stone J, Tamimi RM, Teras LR, Tikkanen E, Turman C, Vachon CM, Wang Q, Winqvist R, Wolk A, Zemel BS, Zheng W, van Dijk KW, Alizadeh BZ, Bandinelli S, Boerwinkle E, Boomsma DI, Ciullo M, Chenevix-Trench G, Cucca F, Esko T, Gieger C, Grant SFA, Gudnason V, Hayward C, Kolčić I, Kraft P, Lawlor DA, Martin NG, Nøhr EA, Pedersen NL, Pennell CE, Ridker PM, Robino A, Snieder H, Sovio U, Spector TD, Stöckl D, Sudlow C, Timpson NJ, Toniolo D, Uitterlinden A, Ulivi S, Völzke H, Wareham NJ, Widen E, Wilson JF, Pharoah PDP, Li L, Easton DF, Njølstad P, Sulem P, Murabito JM, Murray A, Manousaki D, Juul A, Erikstrup C, Stefansson K, Horikoshi M, Chen Z, Farooqi IS, Pitteloud N, Johansson S, Day FR, Perry JRB, Ong KK. Understanding the genetic complexity of puberty timing across the allele frequency spectrum. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.14.23291322. [PMID: 37503126 PMCID: PMC10371120 DOI: 10.1101/2023.06.14.23291322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Pubertal timing varies considerably and has been associated with a range of health outcomes in later life. To elucidate the underlying biological mechanisms, we performed multi-ancestry genetic analyses in ~800,000 women, identifying 1,080 independent signals associated with age at menarche. Collectively these loci explained 11% of the trait variance in an independent sample, with women at the top and bottom 1% of polygenic risk exhibiting a ~11 and ~14-fold higher risk of delayed and precocious pubertal development, respectively. These common variant analyses were supported by exome sequence analysis of ~220,000 women, identifying several genes, including rare loss of function variants in ZNF483 which abolished the impact of polygenic risk. Next, we implicated 660 genes in pubertal development using a combination of in silico variant-to-gene mapping approaches and integration with dynamic gene expression data from mouse embryonic GnRH neurons. This included an uncharacterized G-protein coupled receptor GPR83, which we demonstrate amplifies signaling of MC3R, a key sensor of nutritional status. Finally, we identified several genes, including ovary-expressed genes involved in DNA damage response that co-localize with signals associated with menopause timing, leading us to hypothesize that the ovarian reserve might signal centrally to trigger puberty. Collectively these findings extend our understanding of the biological complexity of puberty timing and highlight body size dependent and independent mechanisms that potentially link reproductive timing to later life disease.
Collapse
Affiliation(s)
- Katherine A Kentistou
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK
| | - Lena R Kaisinger
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK
| | - Stasa Stankovic
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK
| | - Marc Vaudel
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, NO-5020, Bergen, Norway
- Department of Genetics and Bioinformatics, Health Data and Digitalization, Norwegian Institute of Public Health, NO-0213, Oslo, Norway
| | - Edson M de Oliveira
- University of Cambridge Metabolic Research Laboratories and NIHR Cambridge Biomedical Research Centre, Wellcome-MRC Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK
| | - Andrea Messina
- Division of Endocrinology, Diabetology, and Metabolism, Lausanne University Hospital, 1011 Lausanne, Switzerland
| | - Robin G Walters
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- MRC Population Health Research Unit, University of Oxford, Oxford OX3 7LF, UK
| | - Xiaoxi Liu
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Alexander S Busch
- Department of General Pediatrics, University of Münster, Münster, Germany
- Deptartment of Growth and Reproduction, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Hannes Helgason
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Deborah J Thompson
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
| | - Federico Santon
- Division of Endocrinology, Diabetology, and Metabolism, Lausanne University Hospital, 1011 Lausanne, Switzerland
| | - Konstantin M Petricek
- Charité Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Pharmacology, Berlin, Germany
| | - Yassine Zouaghi
- Division of Endocrinology, Diabetology, and Metabolism, Lausanne University Hospital, 1011 Lausanne, Switzerland
| | - Isabel Huang-Doran
- University of Cambridge Metabolic Research Laboratories and NIHR Cambridge Biomedical Research Centre, Wellcome-MRC Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK
| | - Daniel F Gudbjartsson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Eirik Bratland
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, NO-5020, Bergen, Norway
- Department of Medical Genetics, Haukeland University Hospital, NO-5021, Bergen, Norway
| | - Kuang Lin
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Eugene J Gardner
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK
| | - Yajie Zhao
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK
| | - Raina Jia
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
- The Department of Applied Genetics, The School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
| | - Margie Riggan
- Department of Gynecology, Duke University Medical Center, Durham, North Carolina, USA
| | - Manjeet K Bolla
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
| | - Mojgan Yazdanpanah
- Research Center of the Sainte-Justine University Hospital, University of Montreal, Montreal, Quebec, Canada
| | - Nahid Yazdanpanah
- Research Center of the Sainte-Justine University Hospital, University of Montreal, Montreal, Quebec, Canada
| | - Jonath P Bradfield
- Quantinuum Research, Wayne, PA, USA
- Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Linda Broer
- Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics & Cancer, University of Edinburgh, Edinburgh, UK
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02215, USA
| | - Diana L Cousminer
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Lude H Franke
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Giorgia Girotto
- Institute for Maternal and Child Health – IRCCS ‘‘Burlo Garofolo”, Trieste, Italy
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy
| | - Chunyan He
- Department of Epidemiology and Biostatistics, Department of Big Data in Health Science, School of Public Health, Zhejiang University School of Medicine, Hangzhou 310058, China
- Departments of Medical Oncology and Hematology, Sir Runrun Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou 310016, China
| | - Marjo-Riitta Järvelin
- Department of Epidemiology and Biostatistics, MRC Health Protection Agency (HPA) Centre for Environment and Health, School of Public Health, Imperial College London, UK
- Institute of Health Sciences, P.O.Box 5000, FI-90014 University of Oulu, Finland
- Biocenter Oulu, P.O.Box 5000, Aapistie 5A, FI-90014 University of Oulu, Finland
- Unit of Primary Care, Oulu University Hospital, Kajaanintie 50, P.O.Box 20, FI-90220 Oulu, 90029 OYS, Finland
- Department of Children and Young People and Families, National Institute for Health and Welfare, Aapistie 1, Box 310, FI-90101 Oulu, Finland
| | - Peter K Joshi
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh EH8 9AG, Scotland
| | - Yoichiro Kamatani
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Robert Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Jian’an Luan
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK
| | - Kathryn L Lunetta
- Boston University School of Public Health, Department of Biostatistics. Boston, Massachusetts 02118, USA
- NHLBI’s and Boston University’s Framingham Heart Study, Framingham, Massachusetts 01702-5827, USA
| | - Reedik Mägi
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, King’s College London, London, UK
- NIHR Biomedical Research Centre at Guy’s and St. Thomas’ Foundation Trust, London, UK
| | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- School of Psychology, University of Queensland, Brisbane, Queensland, Australia
- Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia
| | - Christa Meisinger
- Epidemiology, Medical Faculty, University of Augsburg, University Hospital of Augsburg, Augsburg, Germany
| | - Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands
| | - Teresa Nutile
- Institute of Genetics and Biophysics “A. Buzzati-Traverso”, CNR, Naples, Italy
| | - Maria Pina Concas
- Institute for Maternal and Child Health – IRCCS ‘‘Burlo Garofolo”, Trieste, Italy
| | - Ozren Polašek
- University of Split School of Medicine, Split, Croatia
- Algebra University College, Zagreb, Croatia
| | - Eleonora Porcu
- Institute of Genetics and Biomedical Research, National Research Council, Cagliari, Sardinia 09042, Italy
- University of Sassari, Department of Biomedical Sciences, Sassari, Sassari 07100, Italy
| | - Susan M Ring
- MRC Integrative Epidemiology Unit at the University of Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, UK
| | - Cinzia Sala
- Division of Genetics and Cell Biology, San Raffele Hospital, Milano, Italy
| | - Albert V Smith
- Icelandic Heart Association, 201 Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland
| | - Toshiko Tanaka
- National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Peter J van der Most
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, The Netherlands
| | - Veronique Vitart
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Carol A Wang
- School of Medicine and Public Health, University of Newcastle, Newcastle, New South Wales 2308, Australia
- Hunter Medical Research Institute, Newcastle, New South Wales 2305, Australia
| | - Gonneke Willemsen
- Dept of Biological Psychology, Vrije Universiteit, Amsterdam; Amsterdam Public Health (APH) research institute, The Netherlands
| | - Marek Zygmunt
- Clinic of Gynaecology and Obstetrics, University Medicine Greifswald, Germany
| | - Thomas U Ahearn
- Division of Cancer Epidemiology and Genetics National Cancer Institute, National Institutes of Health, Department of Health and Human Services Bethesda, MD, USA
| | - Irene L Andrulis
- Fred A. Litwin Center for Cancer Genetics Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital Toronto, Ontario, Canada
- Department of Molecular Genetics University of Toronto Toronto, Ontario, Canada
| | - Hoda Anton-Culver
- Department of Medicine, Genetic Epidemiology Research Institute University of California Irvine Irvine, CA, USA
| | - Antonis C Antoniou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
| | - Paul L Auer
- Division of Biostatistics, Institute for Health and Equity, and Cancer Center Medical College of Wisconsin Milwaukee, WI, USA
| | - Catriona LK Barnes
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh EH8 9AG, Scotland
| | - Matthias W Beckmann
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, Friedrich-Alexander University Erlangen-Nuremberg, University Hospital Erlangen, Erlangen, Germany
| | - Amy Berrington
- Division of Genetics and Epidemiology The Institute of Cancer Research, London, UK
| | - Natalia V Bogdanova
- Department of Radiation Oncology, Hannover Medical School, Hannover, Germany
- Gynaecology Research Unit, Hannover Medical School, Hannover, Germany
- N.N. Alexandrov Research Institute of Oncology and Medical Radiology, Minsk, Belarus
| | - Stig E Bojesen
- Copenhagen General Population Study, Herlev and Gentofte Hospital Copenhagen University Hospital, Herlev, Denmark
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital Copenhagen University Hospital, Herlev, Denmark
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research German Cancer Research Center (DKFZ), Heidelberg, Germany
- Division of Preventive Oncology German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany
- German Cancer Consortium (DKTK) German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Julie E Buring
- Division of Preventive Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02215, USA
| | - Federico Canzian
- Genomic Epidemiology Group German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Jenny Chang-Claude
- Division of Cancer Epidemiology German Cancer Research Center (DKFZ), Heidelberg, Germany
- Cancer Epidemiology Group, University Cancer Center Hamburg (UCCH) University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Fergus J Couch
- Department of Laboratory Medicine and Pathology Mayo Clinic Rochester, MN, USA
| | - Angela Cox
- Sheffield Institute for Nucleic Acids (SInFoNiA), Department of Oncology and Metabolism, University of Sheffield, Sheffield, UK
| | - Laura Crisponi
- Institute of Genetics and Biomedical Research, National Research Council, Cagliari, Sardinia 09042, Italy
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Mary B Daly
- Department of Clinical Genetics Fox Chase Cancer Center Philadelphia, PA, USA
| | - Ellen W Demerath
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, USA
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
| | - Peter Devilee
- Department of Pathology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Immaculata De Vivo
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Thilo Dörk
- Gynaecology Research Unit, Hannover Medical School, Hannover, Germany
| | - Alison M Dunning
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge CB1 8RN, UK
| | - Miriam Dwek
- School of Life Sciences, University of Westminster, London, UK
| | - Johan G Eriksson
- Department of General Practice and Primary Healthcare, University of Helsinki, Helsinki University Hospital, Helsinki, Finland
| | - Peter A Fasching
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, Friedrich-Alexander University Erlangen-Nuremberg, University Hospital Erlangen, Erlangen, Germany
| | | | - Liana Ferreli
- Institute of Genetics and Biomedical Research, National Research Council, Cagliari, Sardinia 09042, Italy
| | - Olivia Fletcher
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK
| | - Manuela Gago-Dominguez
- Genomic Medicine Group, International Cancer Genetics and Epidemiology Group Fundación Pública Galega de Medicina Xenómica, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Complejo Hospitalario Universitario de Santiago, SERGAS Santiago de Compostela, Spain
| | - Montserrat García-Closas
- Division of Cancer Epidemiology and Genetics National Cancer Institute, National Institutes of Health, Department of Health and Human Services Bethesda, MD, USA
| | - José A García-Sáenz
- Medical Oncology Department, Hospital Clínico San Carlos Instituto de Investigación Sanitaria San Carlos (IdISSC), Centro Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain
| | - Anna González-Neira
- Human Genotyping Unit-CeGen, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Harald Grallert
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München–German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München–German Research Center for Environmental Health, Neuherberg, Germany
| | - Pascal Guénel
- Team “Exposome and Heredity”, CESP, Gustave Roussy INSERM, University Paris-Saclay, UVSQ Villejuif, France
| | - Christopher A Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Oncology, Södersjukhuset, Stockholm, Sweden
| | - Ute Hamann
- Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Hakon Hakonarson
- Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Division of Pulmonary Medicine, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Roger J Hart
- Division of Obstetrics and Gynaecology, University of Western Australia, Western Australia, Australia
| | - Martha Hickey
- Department of Obstetrics and Gynaecology at the University of Melbourne and The Royal Women’s Hospital, Victoria, Australia
| | - Maartje J Hooning
- Department of Medical Oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Reiner Hoppe
- Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany
- University of Tübingen, Tübingen, Germany
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne Melbourne, Victoria, Australia
| | - Jouke-Jan Hottenga
- Dept of Biological Psychology, Vrije Universiteit, Amsterdam; Amsterdam Public Health (APH) research institute, The Netherlands
| | - Frank B Hu
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health School of Public Health, Boston, Massachusetts 02115, USA
| | - Hanna Hübner
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, Friedrich-Alexander University Erlangen-Nuremberg, University Hospital Erlangen, Erlangen, Germany
| | - David J Hunter
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, USA
| | - ABCTB Investigators
- Australian Breast Cancer Tissue Bank, Westmead Institute for Medical Research, University of Sydney, Sydney, New South Wales, Australia
| | - Helena Jernström
- Oncology, Department of Clinical Sciences in Lund, Lund University, Lund, Sweden
| | - Esther M John
- Department of Epidemiology and Population Health, Stanford University School of Medicine Stanford, CA, USA
- Department of Medicine, Division of Oncology Stanford Cancer Institute, Stanford University School of Medicine Stanford, CA, USA
| | - David Karasik
- Hebrew SeniorLife Institute for Aging Research, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Elza K Khusnutdinova
- Institute of Biochemistry and Genetics of the Ufa Federal Research Centre of the Russian Academy of Sciences, Ufa, Russia
- Department of Genetics and Fundamental Medicine, Bashkir State University, Ufa, Russia
| | - Vessela N Kristensen
- Department of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - James V Lacey
- Department of Computational and Quantitative Medicine, City of Hope Duarte, CA, USA
- City of Hope Comprehensive Cancer Center, City of Hope Duarte, CA, USA
| | - Diether Lambrechts
- Laboratory for Translational Genetics, Department of Human Genetics, KU Leuven, Leuven, Belgium
- VIB Center for Cancer Biology, VIB, Leuven, Belgium
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Intramural Research Program, National Institutes of Health, Bethesda, Maryland, 20892, USA
| | - Penelope A Lind
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia
- School of Biomedical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Annika Lindblom
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Patrik KE Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Arto Mannermaa
- Translational Cancer Research Area, University of Eastern Finland, Kuopio, Finland
- Institute of Clinical Medicine, Pathology and Forensic Medicine, University of Eastern Finland, Kuopio, Finland
| | - Mark I McCarthy
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology, & Metabolism, University of Oxford, Churchill Hospital, Oxford OX3 7LJ, UK
- NIHR Oxford Biomedical Research Centre, Churchill Hospital, OX3 7LE Oxford, UK
| | - Thomas Meitinger
- Institute of Human Genetics, Klinikum rechts der Isar, Technical University of Munich, School of Medicine, Munich, Germany
| | - Cristina Menni
- Department of Twin Research and Genetic Epidemiology, King’s College London, London, UK
| | - Kyriaki Michailidou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
- Biostatistics Unit, The Cyprus Institute of Neurology & Genetics, Nicosia, Cyprus
| | - Iona Y Millwood
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- MRC Population Health Research Unit, University of Oxford, Oxford OX3 7LF, UK
| | - Roger L Milne
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne Melbourne, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Grant W Montgomery
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Heli Nevanlinna
- Department of Obstetrics and Gynecology, Helsinki University Hospital, University of Helsinki, Helsinki, Finland
| | - Ilja M Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Dale R Nyholt
- School of Biomedical Sciences, Faculty of Health, Centre for Genomics and Personalised Health, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Nadia Obi
- Institute for Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Katie M O’Brien
- Epidemiology Branch National Institute of Environmental Health Sciences, NIH Research Triangle Park, NC, USA
| | - Kenneth Offit
- Clinical Genetics Research Lab, Department of Cancer Biology and Genetics Memorial Sloan Kettering Cancer Center New York, NY, USA
- Clinical Genetics Service, Department of Medicine Memorial Sloan Kettering Cancer Center New York, NY, USA
| | - Albertine J Oldehinkel
- Interdisciplinary Center Psychopathology and Emotion Regulation, University Medical Center Groningen, University of Groningen, The Netherlands
| | - Sisse R Ostrowski
- Department of Clinical Immunology, Rigshospitalet - University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of health and medical sciences, University of Copenhagen, Denmark
| | - Aarno Palotie
- Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK
- Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Ole B Pedersen
- Department of Clinical Medicine, Faculty of health and medical sciences, University of Copenhagen, Denmark
- Department of Clinical Immunology, Zealand University Hospital, Køge, Denmark
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München–German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology - IBE, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Giulia Pianigiani
- Institute for Maternal and Child Health – IRCCS ‘‘Burlo Garofolo”, Trieste, Italy
| | - Dijana Plaseska-Karanfilska
- Research Centre for Genetic Engineering and Biotechnology “Georgi D. Efremov” MASA Skopje Republic of North Macedonia
| | - Anneli Pouta
- National Institute for Health and Welfare, Finland
| | - Alfred Pozarickij
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Paolo Radice
- Unit of Molecular Bases of Genetic Risk and Genetic Testing, Department of Research Fondazione IRCCS, Istituto Nazionale dei Tumori (INT), Milan, Italy
| | - Gad Rennert
- Clalit National Cancer Control Center, Carmel Medical Center and Technion, Faculty of Medicine, Haifa, Israel
| | - Frits R Rosendaal
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Daniela Ruggiero
- Institute of Genetics and Biophysics “A. Buzzati-Traverso”, CNR, Naples, Italy
- IRCCS Neuromed, Pozzilli, Isernia, Italy
| | | | - Dale P Sandler
- Epidemiology Branch National Institute of Environmental Health Sciences, NIH Research Triangle Park, NC, USA
| | - Sabine Schipf
- Institute for Community Medicine, University Medicine Greifswald, Germany
| | - Carsten O Schmidt
- Institute for Community Medicine, University Medicine Greifswald, Germany
| | - Marjanka K Schmidt
- Division of Molecular Pathology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
- Division of Psychosocial Research and Epidemiology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek hospital, Amsterdam, The Netherlands
| | - Kerrin Small
- Department of Twin Research and Genetic Epidemiology, King’s College London, London, UK
| | - Beatrice Spedicati
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy
| | - Meir Stampfer
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Jennifer Stone
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne Melbourne, Victoria, Australia
- Genetic Epidemiology Group, School of Population and Global Health, University of Western Australia Perth, Western Australia, Australia
| | - Rulla M Tamimi
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, USA
- Department of Population Health Sciences Weill Cornell Medicine New York, NY, USA
| | - Lauren R Teras
- Department of Population Science American Cancer Society Atlanta, GA, USA
| | - Emmi Tikkanen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Public Health Genomics Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
| | - Constance Turman
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, USA
- Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Celine M Vachon
- Department of Quantitative Health Sciences, Division of Epidemiology Mayo Clinic Rochester, MN, USA
| | - Qin Wang
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
| | - Robert Winqvist
- Laboratory of Cancer Genetics and Tumor Biology, Translational Medicine Research Unit, Biocenter Oulu, University of Oulu, Oulu, Finland
- Laboratory of Cancer Genetics and Tumor Biology, Northern Finland Laboratory Centre Oulu, Oulu, Finland
| | - Alicja Wolk
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Babette S Zemel
- Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Division of Gastroenterology, Hepatology and Nutrition, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center Vanderbilt University School of Medicine Nashville, TN, USA
| | - Ko W van Dijk
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
- Department of Internal Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, The Netherlands
| | - Behrooz Z Alizadeh
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | | | - Eric Boerwinkle
- Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Dorret I Boomsma
- Dept of Biological Psychology, Vrije Universiteit, Amsterdam; Amsterdam Public Health (APH) research institute, The Netherlands
- Amsterdam Reproduction & Development research institute, Amsterdam, The Netherlands
| | - Marina Ciullo
- Institute of Genetics and Biophysics “A. Buzzati-Traverso”, CNR, Naples, Italy
- IRCCS Neuromed, Pozzilli, Isernia, Italy
| | | | - Francesco Cucca
- Institute of Genetics and Biomedical Research, National Research Council, Cagliari, Sardinia 09042, Italy
- University of Sassari, Department of Biomedical Sciences, Sassari, Sassari 07100, Italy
| | - Tõnu Esko
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München–German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München–German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Struan FA Grant
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Division of Endocrinology and Diabetes, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Vilmundur Gudnason
- Icelandic Heart Association, 201 Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Ivana Kolčić
- University of Split School of Medicine, Split, Croatia
- Algebra University College, Zagreb, Croatia
| | - Peter Kraft
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, USA
- Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit at the University of Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, UK
| | - Nicholas G Martin
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Ellen A Nøhr
- Institute of Clinical Research, University of Southern Denmark, Department of Obstetrics & Gynecology, Odense University Hospital, Denmark
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Craig E Pennell
- School of Medicine and Public Health, University of Newcastle, Newcastle, New South Wales 2308, Australia
- Hunter Medical Research Institute, Newcastle, New South Wales 2305, Australia
- Department of Maternity and Gynaecology, John Hunter Hospital, Newcastle, New South Wales 2305, Australia
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02215, USA
| | - Antonietta Robino
- Institute for Maternal and Child Health – IRCCS ‘‘Burlo Garofolo”, Trieste, Italy
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Ulla Sovio
- Department of Epidemiology and Biostatistics, MRC Health Protection Agency (HPA) Centre for Environment and Health, School of Public Health, Imperial College London, UK
- Department of Obstetrics and Gynaecology, University of Cambridge, Cambridge, UK
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, King’s College London, London, UK
| | - Doris Stöckl
- Gesundheitsamt Fürstenfeldbruck, Regierung von Oberbayern, Fürstenfeldbruck, Germany
| | - Cathie Sudlow
- Centre for Genomic and Experimental Medicine, Institute of Genetics & Cancer, University of Edinburgh, Edinburgh, UK
- Centre for Medical Informatics, Usher Institute, University of Edinburgh
| | - Nic J Timpson
- MRC Integrative Epidemiology Unit at the University of Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, UK
| | - Daniela Toniolo
- Division of Genetics and Cell Biology, San Raffele Hospital, Milano, Italy
| | - André Uitterlinden
- Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - Sheila Ulivi
- Institute for Maternal and Child Health – IRCCS ‘‘Burlo Garofolo”, Trieste, Italy
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Germany
| | - Nicholas J Wareham
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK
| | - Elisabeth Widen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - James F Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh EH8 9AG, Scotland
| | | | | | | | | | | | | | - Paul DP Pharoah
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge CB1 8RN, UK
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing, China
| | - Douglas F Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge CB1 8RN, UK
| | - Pål Njølstad
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, NO-5020, Bergen, Norway
- Department of Pediatrics and Adolescents, Haukeland University Hospital, NO-5021, Bergen, Norway
| | | | - Joanne M Murabito
- NHLBI’s and Boston University’s Framingham Heart Study, Framingham, Massachusetts 01702-5827, USA
- Boston University Chobanian & Avedisian School of Medicine, Department of Medicine, Section of General Internal Medicine, Boston, MA 02118, USA
| | - Anna Murray
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, RILD Level 3, Royal Devon & Exeter Hospital, Barrack Road, Exeter, EX2 5DW, UK
| | - Despoina Manousaki
- Research Center of the Sainte-Justine University Hospital, University of Montreal, Montreal, Quebec, Canada
- Department of Pediatrics, University of Montreal, Montreal, Canada
- Department of Biochemistry and Molecular Medicine, University of Montreal, Montreal, Canada
| | - Anders Juul
- Department of Growth and Reproduction, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
- International Center for Research and Research Training in Endocrine Disruption of Male Reproduction and Child Health (EDMaRC), Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Christian Erikstrup
- Department of Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Kari Stefansson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland
| | - Momoko Horikoshi
- Laboratory for Genomics of Diabetes and Metabolism, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Zhengming Chen
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- MRC Population Health Research Unit, University of Oxford, Oxford OX3 7LF, UK
| | - I Sadaf Farooqi
- University of Cambridge Metabolic Research Laboratories and NIHR Cambridge Biomedical Research Centre, Wellcome-MRC Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK
| | - Nelly Pitteloud
- Division of Endocrinology, Diabetology, and Metabolism, Lausanne University Hospital, 1011 Lausanne, Switzerland
- Faculty of Biology and Medicine, University of Lausanne, Lausanne 1005, Switzerland
| | - Stefan Johansson
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, NO-5020, Bergen, Norway
- Department of Medical Genetics, Haukeland University Hospital, NO-5021, Bergen, Norway
| | - Felix R Day
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK
| | - John RB Perry
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK
- Metabolic Research Laboratory, Wellcome-MRC Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge CB2 0QQ, UK
| | - Ken K Ong
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK
- Department of Paediatrics, University of Cambridge, Cambridge CB2 0QQ, UK
| |
Collapse
|
43
|
Aberra YT, Ma L, Björkegren JLM, Civelek M. Predicting mechanisms of action at genetic loci associated with discordant effects on type 2 diabetes and abdominal fat accumulation. eLife 2023; 12:e79834. [PMID: 37326626 PMCID: PMC10275637 DOI: 10.7554/elife.79834] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 05/31/2023] [Indexed: 06/17/2023] Open
Abstract
Obesity is a major risk factor for cardiovascular disease, stroke, and type 2 diabetes (T2D). Excessive accumulation of fat in the abdomen further increases T2D risk. Abdominal obesity is measured by calculating the ratio of waist-to-hip circumference adjusted for the body-mass index (WHRadjBMI), a trait with a significant genetic inheritance. Genetic loci associated with WHRadjBMI identified in genome-wide association studies are predicted to act through adipose tissues, but many of the exact molecular mechanisms underlying fat distribution and its consequences for T2D risk are poorly understood. Further, mechanisms that uncouple the genetic inheritance of abdominal obesity from T2D risk have not yet been described. Here we utilize multi-omic data to predict mechanisms of action at loci associated with discordant effects on abdominal obesity and T2D risk. We find six genetic signals in five loci associated with protection from T2D but also with increased abdominal obesity. We predict the tissues of action at these discordant loci and the likely effector Genes (eGenes) at three discordant loci, from which we predict significant involvement of adipose biology. We then evaluate the relationship between adipose gene expression of eGenes with adipogenesis, obesity, and diabetic physiological phenotypes. By integrating these analyses with prior literature, we propose models that resolve the discordant associations at two of the five loci. While experimental validation is required to validate predictions, these hypotheses provide potential mechanisms underlying T2D risk stratification within abdominal obesity.
Collapse
Affiliation(s)
- Yonathan Tamrat Aberra
- Department of Biomedical Engineering, University of VirginiaCharlottesvilleUnited States
- Center for Public Health Genomics, University of VirginiaCharlottesvilleUnited States
| | - Lijiang Ma
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount SinaiNew YorkUnited States
| | - Johan LM Björkegren
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount SinaiNew YorkUnited States
- Department of Medicine, Karolinska Institutet, HuddingeStockholmSweden
| | - Mete Civelek
- Department of Biomedical Engineering, University of VirginiaCharlottesvilleUnited States
- Center for Public Health Genomics, University of VirginiaCharlottesvilleUnited States
| |
Collapse
|
44
|
Qiao J, Wu Y, Zhang S, Xu Y, Zhang J, Zeng P, Wang T. Evaluating significance of European-associated index SNPs in the East Asian population for 31 complex phenotypes. BMC Genomics 2023; 24:324. [PMID: 37312035 DOI: 10.1186/s12864-023-09425-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Accepted: 06/01/2023] [Indexed: 06/15/2023] Open
Abstract
BACKGROUND Genome-wide association studies (GWASs) have identified many single-nucleotide polymorphisms (SNPs) associated with complex phenotypes in the European (EUR) population; however, the extent to which EUR-associated SNPs can be generalized to other populations such as East Asian (EAS) is not clear. RESULTS By leveraging summary statistics of 31 phenotypes in the EUR and EAS populations, we first evaluated the difference in heritability between the two populations and calculated the trans-ethnic genetic correlation. We observed the heritability estimates of some phenotypes varied substantially across populations and 53.3% of trans-ethnic genetic correlations were significantly smaller than one. Next, we examined whether EUR-associated SNPs of these phenotypes could be identified in EAS using the trans-ethnic false discovery rate method while accounting for winner's curse for SNP effect in EUR and difference of sample sizes in EAS. We found on average 54.5% of EUR-associated SNPs were also significant in EAS. Furthermore, we discovered non-significant SNPs had higher effect heterogeneity, and significant SNPs showed more consistent linkage disequilibrium and allele frequency patterns between the two populations. We also demonstrated non-significant SNPs were more likely to undergo natural selection. CONCLUSIONS Our study revealed the extent to which EUR-associated SNPs could be significant in the EAS population and offered deep insights into the similarity and diversity of genetic architectures underlying phenotypes in distinct ancestral groups.
Collapse
Affiliation(s)
- Jiahao Qiao
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Yuxuan Wu
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Shuo Zhang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Yue Xu
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Jinhui Zhang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Ping Zeng
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
- Center for Medical Statistics and Data Analysis, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
- Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
- Key Laboratory of Environment and Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
- Engineering Research Innovation Center of Biological Data Mining and Healthcare Transformation, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
| | - Ting Wang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
| |
Collapse
|
45
|
López Rodríguez M, Arasu UT, Kaikkonen MU. Exploring the genetic basis of coronary artery disease using functional genomics. Atherosclerosis 2023; 374:87-98. [PMID: 36801133 DOI: 10.1016/j.atherosclerosis.2023.01.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 01/20/2023] [Accepted: 01/24/2023] [Indexed: 02/05/2023]
Abstract
Genome-wide Association Studies (GWAS) have identified more than 300 loci associated with coronary artery disease (CAD), defining the genetic risk map of the disease. However, the translation of the association signals into biological-pathophysiological mechanisms constitute a major challenge. Through a group of examples of studies focused on CAD, we discuss the rationale, basic principles and outcomes of the main methodologies implemented to prioritize and characterize causal variants and their target genes. Additionally, we highlight the strategies as well as the current methods that integrate association and functional genomics data to dissect the cellular specificity underlying the complexity of disease mechanisms. Despite the limitations of existing approaches, the increasing knowledge generated through functional studies helps interpret GWAS maps and opens novel avenues for the clinical usability of association data.
Collapse
Affiliation(s)
- Maykel López Rodríguez
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, 70211, Finland; Department of Pathology and Laboratory Medicine, University of California, UCLA, Los Angeles, USA.
| | - Uma Thanigai Arasu
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, 70211, Finland
| | - Minna U Kaikkonen
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, 70211, Finland.
| |
Collapse
|
46
|
Huynh K, Smith BR, Macdonald SJ, Long AD. Genetic variation in chromatin state across multiple tissues in Drosophila melanogaster. PLoS Genet 2023; 19:e1010439. [PMID: 37146087 PMCID: PMC10191298 DOI: 10.1371/journal.pgen.1010439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 05/17/2023] [Accepted: 04/20/2023] [Indexed: 05/07/2023] Open
Abstract
We use ATAC-seq to examine chromatin accessibility for four different tissues in Drosophila melanogaster: adult female brain, ovaries, and both wing and eye-antennal imaginal discs from males. Each tissue is assayed in eight different inbred strain genetic backgrounds, seven associated with a reference quality genome assembly. We develop a method for the quantile normalization of ATAC-seq fragments and test for differences in coverage among genotypes, tissues, and their interaction at 44099 peaks throughout the euchromatic genome. For the strains with reference quality genome assemblies, we correct ATAC-seq profiles for read mis-mapping due to nearby polymorphic structural variants (SVs). Comparing coverage among genotypes without accounting for SVs results in a highly elevated rate (55%) of identifying false positive differences in chromatin state between genotypes. After SV correction, we identify 1050, 30383, and 4508 regions whose peak heights are polymorphic among genotypes, among tissues, or exhibit genotype-by-tissue interactions, respectively. Finally, we identify 3988 candidate causative variants that explain at least 80% of the variance in chromatin state at nearby ATAC-seq peaks.
Collapse
Affiliation(s)
- Khoi Huynh
- Department of Ecology and Evolutionary Biology, University of California, Irvine, California, United States of America
| | - Brittny R. Smith
- Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas, United States of America
| | - Stuart J. Macdonald
- Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas, United States of America
- Center for Computational Biology, University of Kansas, Lawrence, Kansas, United States of America
| | - Anthony D. Long
- Department of Ecology and Evolutionary Biology, University of California, Irvine, California, United States of America
| |
Collapse
|
47
|
Cai J, Zhan J, Arking DE, Bader JS. Priors, population sizes, and power in genome-wide hypothesis tests. BMC Bioinformatics 2023; 24:170. [PMID: 37101120 PMCID: PMC10134629 DOI: 10.1186/s12859-023-05261-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Accepted: 03/27/2023] [Indexed: 04/28/2023] Open
Abstract
BACKGROUND Genome-wide tests, including genome-wide association studies (GWAS) of germ-line genetic variants, driver tests of cancer somatic mutations, and transcriptome-wide association tests of RNAseq data, carry a high multiple testing burden. This burden can be overcome by enrolling larger cohorts or alleviated by using prior biological knowledge to favor some hypotheses over others. Here we compare these two methods in terms of their abilities to boost the power of hypothesis testing. RESULTS We provide a quantitative estimate for progress in cohort sizes and present a theoretical analysis of the power of oracular hard priors: priors that select a subset of hypotheses for testing, with an oracular guarantee that all true positives are within the tested subset. This theory demonstrates that for GWAS, strong priors that limit testing to 100-1000 genes provide less power than typical annual 20-40% increases in cohort sizes. Furthermore, non-oracular priors that exclude even a small fraction of true positives from the tested set can perform worse than not using a prior at all. CONCLUSION Our results provide a theoretical explanation for the continued dominance of simple, unbiased univariate hypothesis tests for GWAS: if a statistical question can be answered by larger cohort sizes, it should be answered by larger cohort sizes rather than by more complicated biased methods involving priors. We suggest that priors are better suited for non-statistical aspects of biology, such as pathway structure and causality, that are not yet easily captured by standard hypothesis tests.
Collapse
Affiliation(s)
- Jitong Cai
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Jianan Zhan
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Dan E Arking
- Department of Genetic Medicine, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Joel S Bader
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.
- Department of Genetic Medicine, Johns Hopkins University, Baltimore, MD, 21218, USA.
| |
Collapse
|
48
|
McManus JN, Lovelett RJ, Lowengrub D, Christensen S. A unifying statistical framework to discover disease genes from GWASs. CELL GENOMICS 2023; 3:100264. [PMID: 36950381 PMCID: PMC10025450 DOI: 10.1016/j.xgen.2023.100264] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 09/07/2022] [Accepted: 01/19/2023] [Indexed: 03/10/2023]
Abstract
Genome-wide association studies (GWASs) identify genomic loci associated with complex traits, but it remains a challenge to identify the genes affected by causal genetic variants in these loci. Attempts to solve this challenge are frustrated by a number of compounding problems. Here, we show how to combine solutions to these problems into a unified mathematical framework. From this synthesis, it becomes possible to compute the probability that each gene in the genome is affected by a causal variant, given a particular trait, without making assumptions about the relevant cell types or tissues. We validate each component of the framework individually and in combination. When applied to large GWASs of human disease, the resulting paradigm can rediscover the majority of well-known disease genes. Moreover, it establishes human genetics support for many genes previously implicated only by clinical or preclinical evidence, and it uncovers a plethora of novel disease genes with compelling biological rationale.
Collapse
|
49
|
Shrine N, Izquierdo AG, Chen J, Packer R, Hall RJ, Guyatt AL, Batini C, Thompson RJ, Pavuluri C, Malik V, Hobbs BD, Moll M, Kim W, Tal-Singer R, Bakke P, Fawcett KA, John C, Coley K, Piga NN, Pozarickij A, Lin K, Millwood IY, Chen Z, Li L, Wijnant SRA, Lahousse L, Brusselle G, Uitterlinden AG, Manichaikul A, Oelsner EC, Rich SS, Barr RG, Kerr SM, Vitart V, Brown MR, Wielscher M, Imboden M, Jeong A, Bartz TM, Gharib SA, Flexeder C, Karrasch S, Gieger C, Peters A, Stubbe B, Hu X, Ortega VE, Meyers DA, Bleecker ER, Gabriel SB, Gupta N, Smith AV, Luan J, Zhao JH, Hansen AF, Langhammer A, Willer C, Bhatta L, Porteous D, Smith BH, Campbell A, Sofer T, Lee J, Daviglus ML, Yu B, Lim E, Xu H, O'Connor GT, Thareja G, Albagha OME, Suhre K, Granell R, Faquih TO, Hiemstra PS, Slats AM, Mullin BH, Hui J, James A, Beilby J, Patasova K, Hysi P, Koskela JT, Wyss AB, Jin J, Sikdar S, Lee M, May-Wilson S, Pirastu N, Kentistou KA, Joshi PK, Timmers PRHJ, Williams AT, Free RC, Wang X, Morrison JL, Gilliland FD, Chen Z, Wang CA, Foong RE, Harris SE, Taylor A, Redmond P, Cook JP, Mahajan A, Lind L, Palviainen T, Lehtimäki T, Raitakari OT, Kaprio J, Rantanen T, Pietiläinen KH, Cox SR, Pennell CE, Hall GL, Gauderman WJ, Brightling C, Wilson JF, Vasankari T, Laitinen T, Salomaa V, Mook-Kanamori DO, Timpson NJ, Zeggini E, Dupuis J, Hayward C, Brumpton B, Langenberg C, Weiss S, Homuth G, Schmidt CO, Probst-Hensch N, Jarvelin MR, Morrison AC, Polasek O, Rudan I, Lee JH, Sayers I, Rawlins EL, Dudbridge F, Silverman EK, Strachan DP, Walters RG, Morris AP, London SJ, Cho MH, Wain LV, Hall IP, Tobin MD. Multi-ancestry genome-wide association analyses improve resolution of genes and pathways influencing lung function and chronic obstructive pulmonary disease risk. Nat Genet 2023; 55:410-422. [PMID: 36914875 PMCID: PMC10011137 DOI: 10.1038/s41588-023-01314-0] [Citation(s) in RCA: 37] [Impact Index Per Article: 37.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 01/25/2023] [Indexed: 03/16/2023]
Abstract
Lung-function impairment underlies chronic obstructive pulmonary disease (COPD) and predicts mortality. In the largest multi-ancestry genome-wide association meta-analysis of lung function to date, comprising 580,869 participants, we identified 1,020 independent association signals implicating 559 genes supported by ≥2 criteria from a systematic variant-to-gene mapping framework. These genes were enriched in 29 pathways. Individual variants showed heterogeneity across ancestries, age and smoking groups, and collectively as a genetic risk score showed strong association with COPD across ancestry groups. We undertook phenome-wide association studies for selected associated variants as well as trait and pathway-specific genetic risk scores to infer possible consequences of intervening in pathways underlying lung function. We highlight new putative causal variants, genes, proteins and pathways, including those targeted by existing drugs. These findings bring us closer to understanding the mechanisms underlying lung function and COPD, and should inform functional genomics experiments and potentially future COPD therapies.
Collapse
Affiliation(s)
- Nick Shrine
- Department of Population Health Sciences, University of Leicester, Leicester, UK.
| | - Abril G Izquierdo
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Jing Chen
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Richard Packer
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Robert J Hall
- Division of Respiratory Medicine and NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Anna L Guyatt
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Chiara Batini
- Department of Population Health Sciences, University of Leicester, Leicester, UK
- Leicester National Institute for Health and Care Research, Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Rebecca J Thompson
- Division of Respiratory Medicine and NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Chandan Pavuluri
- Channing Division of Network Medicine, Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Vidhi Malik
- Channing Division of Network Medicine, Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Brian D Hobbs
- Channing Division of Network Medicine, Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Matthew Moll
- Channing Division of Network Medicine, Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Wonji Kim
- Channing Division of Network Medicine, Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | | | - Per Bakke
- Department of Clinical Science, Unversity of Bergen, Bergen, Norway
| | - Katherine A Fawcett
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Catherine John
- Department of Population Health Sciences, University of Leicester, Leicester, UK
- Leicester National Institute for Health and Care Research, Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Kayesha Coley
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Noemi Nicole Piga
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Alfred Pozarickij
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Kuang Lin
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Iona Y Millwood
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, University of Oxford, Oxford, UK
| | - Zhengming Chen
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, University of Oxford, Oxford, UK
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Sara R A Wijnant
- Department of Respiratory Diseases, Ghent Universital Hospital, Ghent, Belgium
- Department of Bioanalysis, Faculty of Pharmaceutical Sciences, Ghent University, Ghent, Belgium
- Department of Epidemiology, Eramus Medical Center, Rotterdam, The Netherlands
| | - Lies Lahousse
- Department of Bioanalysis, Faculty of Pharmaceutical Sciences, Ghent University, Ghent, Belgium
- Department of Epidemiology, Eramus Medical Center, Rotterdam, The Netherlands
| | - Guy Brusselle
- Department of Respiratory Diseases, Ghent Universital Hospital, Ghent, Belgium
- Department of Epidemiology, Eramus Medical Center, Rotterdam, The Netherlands
| | - Andre G Uitterlinden
- Department of Internal Medicine, Eramus Medical Center, Rotterdam, The Netherlands
| | - Ani Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Elizabeth C Oelsner
- Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - R Graham Barr
- Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Shona M Kerr
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Veronique Vitart
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - 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
| | - Matthias Wielscher
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Medea Imboden
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- Department of Public Health, University of Basel, Basel, Switzerland
| | - Ayoung Jeong
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- Department of Public Health, University of Basel, Basel, Switzerland
| | - Traci M Bartz
- Cardiovascular Health Research Unit, Departments of Medicine and Biostatistics, University of Washington, Seattle, WA, USA
| | - Sina A Gharib
- Computational Medicine Core, Center for Lung Biology, Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Claudia Flexeder
- Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, Munich, Germany
- Comprehensive Pneumology Center Munich (CPC-M), German Center for Lung Research (DZL), Munich, Germany
- Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Stefan Karrasch
- Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, Munich, Germany
- Comprehensive Pneumology Center Munich (CPC-M), German Center for Lung Research (DZL), Munich, Germany
- Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Christian Gieger
- Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig Maximilian University, Munich, Germany
| | - Beate Stubbe
- Department of Internal Medicine B-Cardiology, Intensive Care, Pulmonary Medicine and Infectious Diseases, University Medicine Greifswald, Greifswald, Germany
| | - Xiaowei Hu
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Victor E Ortega
- Division of Respiratory Medicine, Department of Internal Medicine, Center for Individualized Medicine, Mayo Clinic, Scottsdale, AZ, USA
| | | | | | | | - Namrata Gupta
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Albert Vernon 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
| | - Jian'an Luan
- MRC Epidemiology Unit, Institute of Metabolic Science, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Jing-Hua Zhao
- Department of Public and Primary Care, Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
| | - Ailin F Hansen
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU Norwegian University of Science and Technology, Trondheim, Norway
| | - Arnulf Langhammer
- HUNT Research Centre, Department of Public Health and Nursing, NTNU Norwegian University of Science and Technology, Levanger, Norway
- Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger, Norway
| | - Cristen Willer
- Division of Cardiology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Laxmi Bhatta
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU Norwegian University of Science and Technology, Trondheim, Norway
| | - David Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Blair H Smith
- Division of Population Health and Genomics, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Tamar Sofer
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jiwon Lee
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
| | - Martha L Daviglus
- Institute for Minority Health Research, University of Illinois at Chicago, Chicago, IL, USA
| | - Bing Yu
- 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
| | - Elise Lim
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA
| | - Hanfei Xu
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA
| | - George T O'Connor
- Pulmonary Center, School of Medicine, Boston University, Boston, MA, USA
| | - Gaurav Thareja
- Bioinformatics Core, Weill Cornell Medicine-Qatar, Education City, Doha, Qatar
| | - Omar M E Albagha
- College of Health and Life Sciences, Hamad Bin Khalifa University, Doha, Qatar
- Center for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Karsten Suhre
- Bioinformatics Core, Weill Cornell Medicine-Qatar, Education City, Doha, Qatar
- Department of Biophysics and Physiology, Weill Cornell Medicine, New York, NY, USA
| | - Raquel Granell
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Tariq O Faquih
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Pieter S Hiemstra
- Department of Pulmonology, Leiden University Medical Center, Leiden, The Netherlands
| | - Annelies M Slats
- Department of Pulmonology, Leiden University Medical Center, Leiden, The Netherlands
| | - Benjamin H Mullin
- Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
- School of Biomedical Sciences, University of Western Australia, Crawley, Western Australia, Australia
| | - Jennie Hui
- Busselton Population Medical Research Institute, QEII Medical Centre, Nedlands, Western Australia, Australia
- School of Population and Global Health, University of Western Australia, Crawley, Western Australia, Australia
- PathWest Laboratory Medicine of WA, Nedlands, Western Australia, Australia
| | - Alan James
- Busselton Population Medical Research Institute, QEII Medical Centre, Nedlands, Western Australia, Australia
| | - John Beilby
- School of Biomedical Sciences, University of Western Australia, Crawley, Western Australia, Australia
- Busselton Population Medical Research Institute, QEII Medical Centre, Nedlands, Western Australia, Australia
| | - Karina Patasova
- Department of Twin Research and Genetic Epidemiology, King's College London School of Medicine, London, UK
- Division of Respiratory Medicine, Department of Medicine Solna, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
| | - Pirro Hysi
- Department of Twin Research and Genetic Epidemiology, King's College London School of Medicine, London, UK
- UCL Institute of Ophthalmology, University College London, London, UK
| | - Jukka T Koskela
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Annah B Wyss
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | | | - Sinjini Sikdar
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
- Department of Mathematics and Statistics, Old Dominion University, Norfolk, VA, USA
| | - Mikyeong Lee
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | - Sebastian May-Wilson
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Nicola Pirastu
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Katherine A Kentistou
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
- Centre for Cardiovascular Sciences, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Peter K Joshi
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Paul R H J Timmers
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Alexander T Williams
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Robert C Free
- Leicester National Institute for Health and Care Research, Biomedical Research Centre, Glenfield Hospital, Leicester, UK
- Department of Respiratory Sciences, University of Leicester, Leicester, UK
| | - Xueyang Wang
- Leicester National Institute for Health and Care Research, Biomedical Research Centre, Glenfield Hospital, Leicester, UK
- Department of Respiratory Sciences, University of Leicester, Leicester, UK
| | - John L Morrison
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Frank D Gilliland
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Zhanghua Chen
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Carol A Wang
- School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, New South Wales, Australia
- Hunter Medical Research Institute, Newcastle, New South Wales, Australia
| | - Rachel E Foong
- Wal-yan Respiratory Research Centre, Telethon Kids Institute, Perth, Western Australia, Australia
- School of Allied Health, Faculty of Health Sciences, Curtin University, Perth, Western Australia, Australia
| | - Sarah E Harris
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Adele Taylor
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Paul Redmond
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - James P Cook
- Department of Health Data Science, University of Liverpool, Liverpool, UK
| | - Anubha Mahajan
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Genentech, South San Francisco, CA, USA
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Teemu Palviainen
- Institute for Molecular Medicine Finland-FIMM, University of Helsinki, Helsinki, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Olli T Raitakari
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland-FIMM, University of Helsinki, Helsinki, Finland
| | - Taina Rantanen
- Faculty of Sport and Health Sciences, University of Jyvaskyla, Jyvaskyla, Finland
| | - Kirsi H Pietiläinen
- Obesity Research Unit, Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Obesity and Abdominal Centers, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Simon R Cox
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Craig E Pennell
- School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, New South Wales, Australia
- Hunter Medical Research Institute, Newcastle, New South Wales, Australia
- Department of Maternity and Gynaecology, John Hunter Hospital, Newcastle, New South Wales, Australia
| | - Graham L Hall
- Wal-yan Respiratory Research Centre, Telethon Kids Institute, Perth, Western Australia, Australia
- School of Allied Health, Faculty of Health Sciences, Curtin University, Perth, Western Australia, Australia
| | - W James Gauderman
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Chris Brightling
- Leicester National Institute for Health and Care Research, Biomedical Research Centre, Glenfield Hospital, Leicester, UK
- Department of Infection, Inflammation and Immunity, Institute for Lung Health, University of Leicester, Leicester, UK
| | - James F Wilson
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Tuula Vasankari
- FILHA-Finnish Lung Health Association, Helsinki, Finland
- Department of Respiratory Diseases and Allergology, University of Turku, Turku, Finland
| | - Tarja Laitinen
- Administration Center, Tampere University Hospital and University of Tampere, Tampere, Finland
| | - Veikko Salomaa
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Dennis O Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, The Netherlands
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- ALSPAC, Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Eleftheria Zeggini
- Wellcome Sanger Institute, Cambridge, UK
- Institute of Translational Genomics, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- Technical University of Munich (TUM) and Klinikum Rechts der Isar, TUM School of Medicine, Munich, Germany
| | - Josée Dupuis
- Department of Epidemiology, Biostatistics, and Occupational Health, School of Population and Global Health, McGill University, Montreal, Quebec, Canada
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Ben Brumpton
- HUNT Research Centre, Department of Public Health and Nursing, NTNU Norwegian University of Science and Technology, Levanger, Norway
- Clinic of Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
- Computational Medicine, Berlin Institute of Health at Charité, Universitätsmedizin Berlin, Berlin, Germany
| | - Stefan Weiss
- Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Carsten Oliver Schmidt
- Institute for Community Medicine, SHIP-Clinical Epidemiological Research, University Medicine Greifswald, Greifswald, Germany
| | - Nicole Probst-Hensch
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- Department of Public Health, University of Basel, Basel, Switzerland
| | - Marjo-Riitta Jarvelin
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Biocenter Oulu, University of Oulu, Oulu, Finland
- Unit of Primary Health Care, Oulu University Hospital, OYS, Oulu, Finland
| | - 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
| | - Ozren Polasek
- School of Medicine, University of Split, Split, Croatia
| | - Igor Rudan
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Joo-Hyeon Lee
- Jeffrey Cheah Biomedical Centre, Wellcome-MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK
| | - Ian Sayers
- Division of Respiratory Medicine and NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Emma L Rawlins
- Wellcome Trust-CRUK Gurdon Institute and Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK
| | - Frank Dudbridge
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Edwin K Silverman
- Channing Division of Network Medicine, Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - David P Strachan
- Population Health Research Institute, St George's University of London, London, UK
| | - Robin G Walters
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, University of Oxford, Oxford, UK
| | - Andrew P Morris
- Centre for Genetics and Genomics Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, Centre for Musculoskeletal Research, The University of Manchester, Manchester, UK
| | - Stephanie J London
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | - Michael H Cho
- Channing Division of Network Medicine, Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Louise V Wain
- Department of Population Health Sciences, University of Leicester, Leicester, UK
- Leicester National Institute for Health and Care Research, Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Ian P Hall
- Division of Respiratory Medicine and NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Martin D Tobin
- Department of Population Health Sciences, University of Leicester, Leicester, UK.
- Leicester National Institute for Health and Care Research, Biomedical Research Centre, Glenfield Hospital, Leicester, UK.
| |
Collapse
|
50
|
Li Q, Perera D, Cao C, He J, Bian J, Chen X, Azeem F, Howe A, Au B, Wu J, Yan J, Long Q. Interaction-integrated linear mixed model reveals 3D-genetic basis underlying Autism. Genomics 2023; 115:110575. [PMID: 36758877 DOI: 10.1016/j.ygeno.2023.110575] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 01/16/2023] [Accepted: 02/03/2023] [Indexed: 02/10/2023]
Abstract
Genetic interactions play critical roles in genotype-phenotype associations. We developed a novel interaction-integrated linear mixed model (ILMM) that integrates a priori knowledge into linear mixed models. ILMM enables statistical integration of genetic interactions upfront and overcomes the problems of searching for combinations. To demonstrate its utility, with 3D genomic interactions (assessed by Hi-C experiments) as a priori, we applied ILMM to whole-genome sequencing data for Autism Spectrum Disorders (ASD) and brain transcriptome data, revealing the 3D-genetic basis of ASD and 3D-expression quantitative loci (3D-eQTLs) for brain tissues. Notably, we reported a potential mechanism involving distal regulation between FOXP2 and DNMT3A, conferring the risk of ASD.
Collapse
Affiliation(s)
- Qing Li
- Department of Biochemistry and Molecular Biology, University of Calgary, Alberta T2N 1N4, Canada
| | - Deshan Perera
- Department of Biochemistry and Molecular Biology, University of Calgary, Alberta T2N 1N4, Canada
| | - Chen Cao
- Department of Biochemistry and Molecular Biology, University of Calgary, Alberta T2N 1N4, Canada
| | - Jingni He
- Department of Biochemistry and Molecular Biology, University of Calgary, Alberta T2N 1N4, Canada
| | - Jiayi Bian
- Department of Mathematics and Statistics, University of Calgary, Alberta T2N 1N4, Canada
| | - Xingyu Chen
- Department of Biochemistry and Molecular Biology, University of Calgary, Alberta T2N 1N4, Canada
| | - Feeha Azeem
- Department of Biochemistry and Molecular Biology, University of Calgary, Alberta T2N 1N4, Canada
| | - Aaron Howe
- Heritage Youth Researcher Summer Program, University of Calgary, Alberta T2N 1N4, Canada
| | - Billie Au
- Department of Medical Genetics, University of Calgary, Alberta T2N 1N4, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Alberta T2N 1N4, Canada
| | - Jingjing Wu
- Department of Mathematics and Statistics, University of Calgary, Alberta T2N 1N4, Canada
| | - Jun Yan
- Department of Physiology and Pharmacology, University of Calgary, Alberta T2N 1N4, Canada; Hotchkiss Brain Institute, University of Calgary, Alberta T2N 1N4, Canada.
| | - Quan Long
- Department of Biochemistry and Molecular Biology, University of Calgary, Alberta T2N 1N4, Canada; Department of Medical Genetics, University of Calgary, Alberta T2N 1N4, Canada; Department of Mathematics and Statistics, University of Calgary, Alberta T2N 1N4, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Alberta T2N 1N4, Canada; Hotchkiss Brain Institute, University of Calgary, Alberta T2N 1N4, Canada.
| |
Collapse
|