101
|
Leppilahti JM, Knuutila J, Pesonen P, Vuollo V, Männikkö M, Karjalainen MK, Suominen AL, Sipilä K. Genome-Wide Association Study of Temporomandibular Disorder-Related Pain in Finnish Populations. J Oral Rehabil 2025; 52:151-159. [PMID: 39482899 PMCID: PMC11740273 DOI: 10.1111/joor.13883] [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: 08/09/2023] [Revised: 09/27/2024] [Accepted: 10/01/2024] [Indexed: 11/03/2024]
Abstract
BACKGROUND Temporomandibular disorders (TMD) are multifactorial musculoskeletal pain and dysfunctions in temporomandibular joints (TMJs) and masticatory muscles. Genetic factors play a role in TMD-related pain, but only a few genome-wide association studies (GWAS) have been conducted. OBJECTIVE The aim of this GWAS was to explore genetic factors associated with painful TMD in Finnish populations. METHODS Data from two epidemiological surveys, the Northern Finland Birth Cohort 1966 (NFBC1966) and the Health 2000 Survey in Finland, including altogether 468 cases and 6833 controls, were used. Case definition was based on pain on palpation of masticatory muscles and/or TMJs. GWASs of the whole data and stratified by sex were conducted from both cohorts using additive models, followed by meta-analysis of the two cohorts. Replications of the previously reported TMD risk loci (rs73460075, DMD; rs4794106, SGCA; rs73271865, SP4; rs60249166, RXP2; rs1531554, BAHCCI; rs5862730, OTUD4/SMAD1; rs10092633, SFRP1; rs34612513, SOX14/CLDN18; rs878962, TSPAN9) were also investigated. RESULTS Four genome-wide significant loci were found in sex-stratified analysis of NFBC1966, including associations at three loci in males (rs1023114, PRIM2, p = 5 × 10-9; rs4244867, ALG10, p = 3 × 10-8; rs79841648, ADCYAP1, p = 4 × 10-9) and one locus in females (rs148476652, DNER, p = 4 × 10-9). However, the results could not be replicated in the Health 2000 Survey or in the meta-analysis of these two cohorts. The previous TMD GWAS associations did not replicate in our data either. CONCLUSION Several TMD pain-associated variants were found in sex-stratified analysis of NFBC1966, suggesting the role of neuroendocrine stress responses and central nervous system. These findings need to be confirmed in future studies.
Collapse
Affiliation(s)
- J. M. Leppilahti
- Research Unit of Population Health, Faculty of MedicineUniversity of OuluOuluFinland
| | - J. Knuutila
- Research Unit of Population Health, Faculty of MedicineUniversity of OuluOuluFinland
| | - P. Pesonen
- Northern Finland Birth Cohorts, Arctic Biobank, Infrastructure for Population Studies, Faculty of MedicineUniversity of OuluOuluFinland
| | - V. Vuollo
- Research Unit of Population Health, Faculty of MedicineUniversity of OuluOuluFinland
| | - M. Männikkö
- Northern Finland Birth Cohorts, Arctic Biobank, Infrastructure for Population Studies, Faculty of MedicineUniversity of OuluOuluFinland
| | - M. K. Karjalainen
- Research Unit of Population Health, Faculty of MedicineUniversity of OuluOuluFinland
- Northern Finland Birth Cohorts, Arctic Biobank, Infrastructure for Population Studies, Faculty of MedicineUniversity of OuluOuluFinland
| | - A. L. Suominen
- Institute of Dentistry, University of Eastern FinlandKuopioFinland
- Oral and Maxillofacial Teaching ClinicKuopio University HospitalKuopioFinland
- Department of Public Health and WelfareNational Institute for Health and Welfare (THL)HelsinkiFinland
| | - K. Sipilä
- Research Unit of Population Health, Faculty of MedicineUniversity of OuluOuluFinland
- Medical Research Center OuluOulu University Hospital and University of OuluOuluFinland
| |
Collapse
|
102
|
Roshandel D, Spiliopoulou A, McGurnaghan SJ, Iakovliev A, Lipschutz D, Hayward C, Bull SB, Klein BE, Lee KE, Kinney GL, Rewers M, Costacou T, Miller RG, McKeigue PM, Paterson AD, Colhoun HM. Genetics of C-Peptide and Age at Diagnosis in Type 1 Diabetes. Diabetes 2025; 74:223-233. [PMID: 39556808 PMCID: PMC11755686 DOI: 10.2337/db24-0340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/19/2024] [Accepted: 11/13/2024] [Indexed: 11/20/2024]
Abstract
ARTICLE HIGHLIGHTS Identified genetic loci for C-peptide and type 1 diabetes (T1D) age at diagnosis (AAD) explain only a small proportion of their variation. We aimed to identify additional genetic loci associated with C-peptide and AAD. Some HLA allele/haplotypes associated with T1D also contributed to variability of C-peptide and AAD, whereas outside the HLA region, T1D loci were mostly not associated with C-peptide or AAD. Genetic variation within CTSH can affect AAD. There is still residual heritability of C-peptide and AAD outside of HLA that could benefit from larger meta-genome-wide association studies.
Collapse
Affiliation(s)
- Delnaz Roshandel
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, Canada
| | - Athina Spiliopoulou
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, U.K
- Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, U.K
| | | | - Andrii Iakovliev
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, U.K
| | - Debby Lipschutz
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, U.K
| | - Caroline Hayward
- Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, U.K
| | - Shelley B. Bull
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Barbara E.K. Klein
- School of Medicine and Public Health, Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, WI
| | - Kristine E. Lee
- School of Medicine and Public Health, Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, WI
| | - Gregory L. Kinney
- Department of Epidemiology, Colorado School of Public Health, University of Colorado, Aurora, CO
| | - Marian Rewers
- Barbara Davis Center for Diabetes, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Tina Costacou
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA
| | - Rachel G. Miller
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA
| | - Paul M. McKeigue
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, U.K
| | - Andrew D. Paterson
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Helen M. Colhoun
- Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, U.K
| |
Collapse
|
103
|
Spychala KM, Yeung EW, Miller AP, Slutske WS, Action Consortium, Wilhelmsen KC, Gizer IR. Genetic risk for trait aggression and alcohol use predict unique facets of alcohol-related aggression. PSYCHOLOGY OF ADDICTIVE BEHAVIORS 2025; 39:63-75. [PMID: 38842867 PMCID: PMC11621227 DOI: 10.1037/adb0001015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/07/2024]
Abstract
OBJECTIVE A propensity for aggression or alcohol use may be associated with alcohol-related aggression. Previous research has shown genetic overlap between alcohol use and aggression but has not looked at how alcohol-related aggression may be uniquely influenced by genetic risk for aggression or alcohol use. The present study examined the associations of genetic risk for trait aggression, alcohol use, and alcohol use disorder (AUD) with alcohol-related aggression using a polygenic risk score (PRS) approach. METHOD Using genome-wide association study summary statistics, PRSs were created for trait aggression, alcohol consumption, and AUD. These PRSs were used to predict the phenotype of alcohol-related aggression among drinkers in two independent samples: the University of California at San Francisco (UCSF) Family Alcoholism Study (n = 1,162) and the National Longitudinal Study of Adolescent to Adult Health (Add Health; n = 4,291). RESULTS There were significant associations between the AUD PRS and lifetime alcohol-related aggression in the UCSF study sample. Additionally, the trait aggression PRS was associated with three or more experiences of hitting anyone else and getting into physical fights while under the influence of alcohol, along with a composite score of three or more experiences of alcohol-related aggression, in the UCSF study sample. No significant associations were observed in the Add Health sample. Limited sex-specific genetic effects were observed. CONCLUSIONS These results provide preliminary evidence that genetic influences underlying alcohol use and aggression are uniquely associated with alcohol-related aggression and suggest that these associations may differ by type and frequency of alcohol-related aggression incidents. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
Collapse
Affiliation(s)
| | - Ellen W Yeung
- Department of Psychological Sciences, University of Missouri
| | - Alex P Miller
- Department of Psychological Sciences, University of Missouri
| | - Wendy S Slutske
- Department of Family Medicine and Community Health, Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health
| | | | | | - Ian R Gizer
- Department of Psychological Sciences, University of Missouri
| |
Collapse
|
104
|
Hoffmann TJ, Graff RE, Madduri RK, Rodriguez AA, Cario CL, Feng K, Jiang Y, Wang A, Klein RJ, Pierce BL, Eggener S, Tong L, Blot W, Long J, Goss LB, Darst BF, Rebbeck T, Lachance J, Andrews C, Adebiyi AO, Adusei B, Aisuodionoe-Shadrach OI, Fernandez PW, Jalloh M, Janivara R, Chen WC, Mensah JE, Agalliu I, Berndt SI, Shelley JP, Schaffer K, Machiela MJ, Freedman ND, Huang WY, Li SA, Goodman PJ, Till C, Thompson I, Lilja H, Ranatunga DK, Presti J, Van Den Eeden SK, Chanock SJ, Mosley JD, Conti DV, Haiman CA, Justice AC, Kachuri L, Witte JS. Genome-wide association study of prostate-specific antigen levels in 392,522 men identifies new loci and improves prediction across ancestry groups. Nat Genet 2025; 57:334-344. [PMID: 39930085 PMCID: PMC11821537 DOI: 10.1038/s41588-024-02068-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Accepted: 12/20/2024] [Indexed: 02/14/2025]
Abstract
We conducted a multiancestry genome-wide association study of prostate-specific antigen (PSA) levels in 296,754 men (211,342 European ancestry, 58,236 African ancestry, 23,546 Hispanic/Latino and 3,630 Asian ancestry; 96.5% of participants were from the Million Veteran Program). We identified 318 independent genome-wide significant (P ≤ 5 × 10-8) variants, 184 of which were novel. Most demonstrated evidence of replication in an independent cohort (n = 95,768). Meta-analyzing discovery and replication (n = 392,522) identified 447 variants, of which a further 111 were novel. Out-of-sample variance in PSA explained by our genome-wide polygenic risk scores ranged from 11.6% to 16.6% for European ancestry, 5.5% to 9.5% for African ancestry, 13.5% to 18.2% for Hispanic/Latino and 8.6% to 15.3% for Asian ancestry and decreased with increasing age. Midlife genetically adjusted PSA levels were more strongly associated with overall and aggressive prostate cancer than unadjusted PSA levels. Our study highlights how including proportionally more participants from underrepresented populations improves genetic prediction of PSA levels, offering potential to personalize prostate cancer screening.
Collapse
Affiliation(s)
- Thomas J Hoffmann
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - Rebecca E Graff
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - Ravi K Madduri
- Data Science and Learning Division, Argonne National Laboratory, Argonne, IL, USA
| | - Alex A Rodriguez
- Data Science and Learning Division, Argonne National Laboratory, Argonne, IL, USA
| | - Clinton L Cario
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA
| | - Karen Feng
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Yu Jiang
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA
| | - Anqi Wang
- Center for Genetic Epidemiology, Department of Population and Preventive Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Robert J Klein
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Brandon L Pierce
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
- Comprehensive Cancer Center, University of Chicago, Chicago, IL, USA
| | - Scott Eggener
- Comprehensive Cancer Center, University of Chicago, Chicago, IL, USA
- Department of Urology, University of Chicago, Chicago, IL, USA
- Department of Surgery, University of Chicago, Chicago, IL, USA
| | - Lin Tong
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
| | - William Blot
- Division of Epidemiology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jirong Long
- Division of Epidemiology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Louisa B Goss
- Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Burcu F Darst
- Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Timothy Rebbeck
- Dana Farber Cancer Institute, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Joseph Lachance
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - Caroline Andrews
- Dana Farber Cancer Institute, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Akindele O Adebiyi
- Department of Community Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | | | - Oseremen I Aisuodionoe-Shadrach
- College of Health Sciences, University of Abuja, Abuja, Nigeria
- Cancer Science Centre Abuja, Abuja, Nigeria
- University of Abuja Teaching Hospital, Abuja, Nigeria
| | - Pedro W Fernandez
- Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Mohamed Jalloh
- Hospital General Idrissa Pouye, Dakar, Senegal
- Ecole Doctorale, Universite Iba Der Thiam de Thies, Thies, Senegal
| | - Rohini Janivara
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - Wenlong C Chen
- Strengthening Oncology Services Research Unit, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- National Cancer Registry, National Health Laboratory Service, Johannesburg, South Africa
| | - James E Mensah
- Korle-Bu Teaching Hospital and University of Ghana Medical School, Accra, Ghana
| | - Ilir Agalliu
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, New York, NY, USA
- Department of Urology, Albert Einstein College of Medicine, New York, NY, USA
| | - Sonja I Berndt
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - John P Shelley
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Kerry Schaffer
- Division of Hematology and Oncology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Mitchell J Machiela
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Neal D Freedman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Wen-Yi Huang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Shengchao A Li
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Phyllis J Goodman
- SWOG Statistics and Data Management Center, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Cathee Till
- SWOG Statistics and Data Management Center, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Ian Thompson
- CHRISTUS Santa Rosa Medical Center Hospital, San Antonio, TX, USA
| | - Hans Lilja
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Translational Medicine, Lund University, Malmö, Sweden
- Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | | | - Joseph Presti
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | | | - Stephen J Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Jonathan D Mosley
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Internal Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - David V Conti
- Center for Genetic Epidemiology, Department of Population and Preventive Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Christopher A Haiman
- Center for Genetic Epidemiology, Department of Population and Preventive Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Amy C Justice
- Veterans Administration Connecticut Healthcare System, West Haven, CT, USA
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
- Yale University School of Public Health, Yale School of Medicine, New Haven, CT, USA
| | - Linda Kachuri
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA.
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA.
| | - John S Witte
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA.
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA.
- Department of Genetics, Stanford University, Stanford, CA, USA.
| |
Collapse
|
105
|
Willett JDS, Waqas M, Choi Y, Ngai T, Mullin K, Tanzi RE, Prokopenko D. Identification of 16 novel Alzheimer's disease loci using multi-ancestry meta-analyses. Alzheimers Dement 2025; 21:e14592. [PMID: 39998322 PMCID: PMC11852348 DOI: 10.1002/alz.14592] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2024] [Revised: 01/10/2025] [Accepted: 01/12/2025] [Indexed: 02/26/2025]
Abstract
INTRODUCTION Alzheimer's disease (AD) is the most prevalent form of dementia. While many AD-associated genetic determinants have been identified, few studies have analyzed individuals of non-European ancestry. METHODS We conducted a multi-ancestry genome-wide association study (GWAS) of clinically diagnosed AD and AD-by-proxy using whole genome sequencing data from the National Institute on Aging Genetics of Alzheimer's Disease Data Storage Site (NIAGADS), National Institute of Mental Health, UK Biobank (UKB), and All of Us (AoU) consisting of 49,149 cases (12,074 clinically diagnosed and 37,075 AD-by-proxy) and 383,225 controls. Nearly half of NIAGADS and AoU participants were of non-European ancestry. RESULTS For clinically diagnosed AD, we identified 14 new loci-five common (FBN2/SCL27A6, AC090115.1, DYM, KCNG1/AL121785.1, TIAM1) and nine rare (VWA5B1, RNU6-755P/LMX1A, MOB1A, MORC1-AS1, LINC00989, PDE4D, RNU2-49P/CDO1, NEO1, and SLC35G3/AC022916.1). Meta-analysis of UKB and AoU AD-by-proxy cases yielded two new rare loci (RPL23/LASP1 and CEBPA/AC008738.6), also nominally significant in NIAGADS. DISCUSSION In summary, we provide evidence for 16 novel AD loci and advocate for more studies using whole genome sequencing-based GWAS of diverse cohorts. HIGHLIGHTS We used whole-genome sequencing data from large and diverse cohorts. We found novel genome-wide association study findings based on whole-genome data. We performed a multiancestry meta-analysis and incorporated results from underrepresented groups.
Collapse
Affiliation(s)
- Julian Daniel Sunday Willett
- Genetics and Aging Research Unit and the McCance Center for Brain HealthDepartment of NeurologyMassachusetts General HospitalBostonMassachusettsUSA
| | - Mohammad Waqas
- Genetics and Aging Research Unit and the McCance Center for Brain HealthDepartment of NeurologyMassachusetts General HospitalBostonMassachusettsUSA
| | - Younjung Choi
- Genetics and Aging Research Unit and the McCance Center for Brain HealthDepartment of NeurologyMassachusetts General HospitalBostonMassachusettsUSA
| | - Tiffany Ngai
- Genetics and Aging Research Unit and the McCance Center for Brain HealthDepartment of NeurologyMassachusetts General HospitalBostonMassachusettsUSA
- Department of Systems Design EngineeringUniversity of WaterlooWaterlooOntarioCanada
| | - Kristina Mullin
- Genetics and Aging Research Unit and the McCance Center for Brain HealthDepartment of NeurologyMassachusetts General HospitalBostonMassachusettsUSA
| | - Rudolph E. Tanzi
- Genetics and Aging Research Unit and the McCance Center for Brain HealthDepartment of NeurologyMassachusetts General HospitalBostonMassachusettsUSA
| | - Dmitry Prokopenko
- Genetics and Aging Research Unit and the McCance Center for Brain HealthDepartment of NeurologyMassachusetts General HospitalBostonMassachusettsUSA
| |
Collapse
|
106
|
Trenkwalder T, Maj C, Al-Kassou B, Debiec R, Doppler SA, Musameh MD, Nelson CP, Dasmeh P, Grover S, Knoll K, Naamanka J, Mordi IR, Braund PS, Dreßen M, Lahm H, Wirth F, Baldus S, Kelm M, von Scheidt M, Krefting J, Ellinghaus D, Small AM, Peloso GM, Natarajan P, Thanassoulis G, Engert JC, Dufresne L, Franke A, Görg S, Laudes M, Nowak-Göttl U, Vaht M, Metspalu A, Stoll M, Berger K, Pellegrini C, Kastrati A, Hengstenberg C, Lang CC, Kessler T, Hovatta I, Nickenig G, Nöthen MM, Krane M, Schunkert H, Samani NJ, Schumacher J. Distinct Genetic Risk Profile in Aortic Stenosis Compared With Coronary Artery Disease. JAMA Cardiol 2025; 10:145-154. [PMID: 39504041 PMCID: PMC11541746 DOI: 10.1001/jamacardio.2024.3738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 08/11/2024] [Indexed: 11/09/2024]
Abstract
Importance Aortic stenosis (AS) and coronary artery disease (CAD) frequently coexist. However, it is unknown which genetic and cardiovascular risk factors might be AS-specific and which could be shared between AS and CAD. Objective To identify genetic risk loci and cardiovascular risk factors with AS-specific associations. Design, Setting, and Participants This was a genomewide association study (GWAS) of AS adjusted for CAD with participants from the European Consortium for the Genetics of Aortic Stenosis (EGAS) (recruited 2000-2020), UK Biobank (recruited 2006-2010), Estonian Biobank (recruited 1997-2019), and FinnGen (recruited 1964-2019). EGAS participants were collected from 7 sites across Europe. All participants were of European ancestry, and information on comorbid CAD was available for all participants. Follow-up analyses with GWAS data on cardiovascular traits and tissue transcriptome data were also performed. Data were analyzed from October 2022 to July 2023. Exposures Genetic variants. Main Outcomes and Measures Cardiovascular traits associated with AS adjusted for CAD. Replication was performed in 2 independent AS GWAS cohorts. Results A total of 18 792 participants with AS and 434 249 control participants were included in this GWAS adjusted for CAD. The analysis found 17 AS risk loci, including 5 loci with novel and independently replicated associations (RNF114A, AFAP1, PDGFRA, ADAMTS7, HAO1). Of all 17 associated loci, 11 were associated with risk specifically for AS and were not associated with CAD (ALPL, PALMD, PRRX1, RNF144A, MECOM, AFAP1, PDGFRA, IL6, TPCN2, NLRP6, HAO1). Concordantly, this study revealed only a moderate genetic correlation of 0.15 (SE, 0.05) between AS and CAD (P = 1.60 × 10-3). Mendelian randomization revealed that serum phosphate was an AS-specific risk factor that was absent in CAD (AS: odds ratio [OR], 1.20; 95% CI, 1.11-1.31; P = 1.27 × 10-5; CAD: OR, 0.97; 95% CI 0.94-1.00; P = .04). Mendelian randomization also found that blood pressure, body mass index, and cholesterol metabolism had substantially lesser associations with AS compared with CAD. Pathway and transcriptome enrichment analyses revealed biological processes and tissues relevant for AS development. Conclusions and Relevance This GWAS adjusted for CAD found a distinct genetic risk profile for AS at the single-marker and polygenic level. These findings provide new targets for future AS research.
Collapse
Affiliation(s)
- Teresa Trenkwalder
- Technical University of Munich, School of Medicine and Health, Department of Cardiovascular Diseases, German Heart Centre Munich, TUM University Hospital, Munich, Germany
- German Center for Cardiovascular Research, Partner Site Munich Heart Alliance, Munich, Germany
| | - Carlo Maj
- Institute of Human Genetics, Philipps University of Marburg, Marburg, Germany
| | - Baravan Al-Kassou
- Department of Medicine II, Heart Center Bonn, University of Bonn and University Hospital Bonn, Bonn, Germany
| | - Radoslaw Debiec
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom
- National Institute for Health and Care Research Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom
| | - Stefanie A. Doppler
- Department of Cardiovascular Surgery, German Heart Center Munich, School of Medicine and Health, TUM University Hospital, Technical University of Munich, Munich, Germany
- Institute Insure, German Heart Center Munich, School of Medicine and Health, TUM University Hospital, Technical University of Munich, Munich, Germany
| | - Muntaser D. Musameh
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom
- National Institute for Health and Care Research Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom
| | - Christopher P. Nelson
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom
- National Institute for Health and Care Research Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom
| | - Pouria Dasmeh
- Institute of Human Genetics, Philipps University of Marburg, Marburg, Germany
| | - Sandeep Grover
- Institute of Human Genetics, Philipps University of Marburg, Marburg, Germany
| | - Katharina Knoll
- Technical University of Munich, School of Medicine and Health, Department of Cardiovascular Diseases, German Heart Centre Munich, TUM University Hospital, Munich, Germany
- German Center for Cardiovascular Research, Partner Site Munich Heart Alliance, Munich, Germany
| | - Joonas Naamanka
- SleepWell Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Ify R. Mordi
- Division of Molecular and Clinical Medicine, University of Dundee, Ninewells Hospital and Medical School, Dundee, United Kingdom
| | - Peter S. Braund
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom
- National Institute for Health and Care Research Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom
| | - Martina Dreßen
- Department of Cardiovascular Surgery, German Heart Center Munich, School of Medicine and Health, TUM University Hospital, Technical University of Munich, Munich, Germany
- Institute Insure, German Heart Center Munich, School of Medicine and Health, TUM University Hospital, Technical University of Munich, Munich, Germany
| | - Harald Lahm
- Department of Cardiovascular Surgery, German Heart Center Munich, School of Medicine and Health, TUM University Hospital, Technical University of Munich, Munich, Germany
- Institute Insure, German Heart Center Munich, School of Medicine and Health, TUM University Hospital, Technical University of Munich, Munich, Germany
| | - Felix Wirth
- Department of Cardiovascular Surgery, German Heart Center Munich, School of Medicine and Health, TUM University Hospital, Technical University of Munich, Munich, Germany
- Institute Insure, German Heart Center Munich, School of Medicine and Health, TUM University Hospital, Technical University of Munich, Munich, Germany
| | - Stephan Baldus
- Department of Cardiology, Faculty of Medicine, Heart Center, University of Cologne, Cologne, Germany
| | - Malte Kelm
- Department of Cardiology, Pulmonology and Vascular Medicine, Medical Faculty of the Heinrich Heine University, Düsseldorf, Germany
| | - Moritz von Scheidt
- Technical University of Munich, School of Medicine and Health, Department of Cardiovascular Diseases, German Heart Centre Munich, TUM University Hospital, Munich, Germany
- German Center for Cardiovascular Research, Partner Site Munich Heart Alliance, Munich, Germany
| | - Johannes Krefting
- Technical University of Munich, School of Medicine and Health, Department of Cardiovascular Diseases, German Heart Centre Munich, TUM University Hospital, Munich, Germany
- German Center for Cardiovascular Research, Partner Site Munich Heart Alliance, Munich, Germany
| | - David Ellinghaus
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Aeron M. Small
- Division of Cardiovascular Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
- Center for Genomic Medicine and Cardiovascular Research Center, Massachusetts General Hospital, Boston
- Program in Medical and Population Genetics and the Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, Massachusetts
| | - Gina M. Peloso
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - Pradeep Natarajan
- Center for Genomic Medicine and Cardiovascular Research Center, Massachusetts General Hospital, Boston
- Program in Medical and Population Genetics and the Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - George Thanassoulis
- Division of Experimental Medicine, McGill University, Montreal, Canada
- Preventive and Genomic Cardiology, McGill University Health Centre and Research Institute, Montreal, Canada
| | - James C. Engert
- Division of Experimental Medicine, McGill University, Montreal, Canada
- Preventive and Genomic Cardiology, McGill University Health Centre and Research Institute, Montreal, Canada
| | - Line Dufresne
- Preventive and Genomic Cardiology, McGill University Health Centre and Research Institute, Montreal, Canada
| | - Andre Franke
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Siegfried Görg
- Institute of Transfusion Medicine, University Hospital of Schleswig-Holstein, Kiel, Germany
| | - Matthias Laudes
- Institute for Diabetes and Clinical Metabolic Research, University Medical Center Schleswig-Holstein, Kiel, Germany
| | - Ulrike Nowak-Göttl
- Thrombosis and Hemostasis Unit, Institute of Clinical Chemistry, University Hospital Kiel, Kiel, Germany
| | - Mariliis Vaht
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Andres Metspalu
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Monika Stoll
- Institute of Human Genetics, Division of Genetic Epidemiology, University of Muenster, Muenster, Germany
| | - Klaus Berger
- Institute of Epidemiology and Social Medicine, University of Münster, Munster, Germany
| | - Costanza Pellegrini
- Technical University of Munich, School of Medicine and Health, Department of Cardiovascular Diseases, German Heart Centre Munich, TUM University Hospital, Munich, Germany
- German Center for Cardiovascular Research, Partner Site Munich Heart Alliance, Munich, Germany
| | - Adnan Kastrati
- Technical University of Munich, School of Medicine and Health, Department of Cardiovascular Diseases, German Heart Centre Munich, TUM University Hospital, Munich, Germany
- German Center for Cardiovascular Research, Partner Site Munich Heart Alliance, Munich, Germany
| | - Christian Hengstenberg
- Department of Internal Medicine II, Division of Cardiology, Medical University of Vienna, Vienna, Austria
| | - Chim C. Lang
- Division of Molecular and Clinical Medicine, University of Dundee, Ninewells Hospital and Medical School, Dundee, United Kingdom
| | - Thorsten Kessler
- Technical University of Munich, School of Medicine and Health, Department of Cardiovascular Diseases, German Heart Centre Munich, TUM University Hospital, Munich, Germany
- German Center for Cardiovascular Research, Partner Site Munich Heart Alliance, Munich, Germany
| | - Iiris Hovatta
- SleepWell Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Georg Nickenig
- Department of Medicine II, Heart Center Bonn, University of Bonn and University Hospital Bonn, Bonn, Germany
| | - Markus M. Nöthen
- Institute of Human Genetics, University of Bonn, School of Medicine and University Hospital Bonn, Bonn, Germany
| | - Markus Krane
- German Center for Cardiovascular Research, Partner Site Munich Heart Alliance, Munich, Germany
- Department of Cardiovascular Surgery, German Heart Center Munich, School of Medicine and Health, TUM University Hospital, Technical University of Munich, Munich, Germany
- Institute Insure, German Heart Center Munich, School of Medicine and Health, TUM University Hospital, Technical University of Munich, Munich, Germany
- Yale School of Medicine, Division of Cardiac Surgery, Department of Surgery, New Haven, Connecticut
| | - Heribert Schunkert
- Technical University of Munich, School of Medicine and Health, Department of Cardiovascular Diseases, German Heart Centre Munich, TUM University Hospital, Munich, Germany
- German Center for Cardiovascular Research, Partner Site Munich Heart Alliance, Munich, Germany
| | - Nilesh J. Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom
- National Institute for Health and Care Research Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom
| | - Johannes Schumacher
- Institute of Human Genetics, Philipps University of Marburg, Marburg, Germany
- Institute of Human Genetics, University of Bonn, School of Medicine and University Hospital Bonn, Bonn, Germany
| |
Collapse
|
107
|
Wilson AC, Rocco A, Chiles J, Srinivasasainagendra V, Labaki W, Meyers D, Hidalgo B, Irvin MR, Bhatt SP, Tiwari H, McDonald ML. Novel risk loci encompassing genes influencing STAT3, GPCR, and oxidative stress signaling are associated with co-morbid GERD and COPD. PLoS Genet 2025; 21:e1011531. [PMID: 39919125 PMCID: PMC11805425 DOI: 10.1371/journal.pgen.1011531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Accepted: 12/05/2024] [Indexed: 02/09/2025] Open
Abstract
Chronic obstructive pulmonary disease (COPD) is a leading cause of death globally. Gastroesophageal reflux disease (GERD) is a common comorbidity in COPD associated with worse pulmonary symptoms, reduced quality of life, and increased exacerbations and hospitalizations. GERD treatment in COPD is associated with a lower risk of exacerbations and mortality; however, it is not clear whether these findings can be attributed to aging populations where both diseases are likely to co-occur or reflect shared etiology. To test for the influence of common etiology in both diseases, we aimed to identify shared genetic etiology between GERD and COPD. We performed the first whole-genome sequence association analysis of comorbid GERD and COPD in 12,438 multi-ancestry participants. The co-heritability of GERD and COPD was 39.7% (h2 = 0.397, SE = 0.074) and we identified several ancestry-independent loci associated with co-morbid GERD and COPD (within LINC02493 and FRYL) known to be involved in oxidative stress and G protein-coupled receptor (GPCR) signaling mechanisms. We found several loci associated with co-morbid GERD and COPD previously associated with GERD or COPD individually, including HCG17, which plays a role in oxidative stress mechanisms. Gene set enrichment identified GPCR signaling pathways in co-morbid GERD and COPD loci. Rare variants in ZFP42, encoding key regulators of the IL6/STAT3 pathway, have been previously implicated with GI disorders and were associated with co-morbid GERD and COPD. We identified common genetic etiology for GERD in COPD which begins to provide a mechanistic foundation for the potential therapeutic utility of STAT3, oxidation, and GPCR signaling pathway modulators in both GERD and COPD.
Collapse
Affiliation(s)
- Ava C. Wilson
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, United States of America
| | - Alison Rocco
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Joe Chiles
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Vinodh Srinivasasainagendra
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Wassim Labaki
- Division of Pulmonary and Critical Care Medicine, Michigan Medicine, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Deborah Meyers
- Division of Genetics, Genomics, and Precision Medicine, University of Arizona, Tucson, Arizona, United States of America
| | - Bertha Hidalgo
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Marguerite R. Irvin
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Surya P. Bhatt
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Hemant Tiwari
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Merry-Lynn McDonald
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
- Department of Genetics, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| |
Collapse
|
108
|
McGrail C, Chiou J, Elgamal R, Luckett AM, Oram RA, Benaglio P, Gaulton KJ. Genetic Discovery and Risk Prediction for Type 1 Diabetes in Individuals Without High-Risk HLA-DR3/DR4 Haplotypes. Diabetes Care 2025; 48:202-211. [PMID: 39626097 PMCID: PMC11770152 DOI: 10.2337/dc24-1251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2024] [Accepted: 10/27/2024] [Indexed: 12/11/2024]
Abstract
OBJECTIVE More than 10% of patients with type 1 diabetes (T1D) do not have high-risk HLA-DR3 or -DR4 haplotypes with distinct clinical features, such as later onset and reduced insulin dependence. We aimed to identify genetic drivers of T1D in the absence of DR3/DR4 and improve prediction of T1D risk in these individuals. RESEARCH DESIGN AND METHODS We performed T1D association and fine-mapping analyses in 12,316 non-DR3/DR4 samples. Next, we performed heterogeneity tests to examine differences in T1D risk variants in individuals without versus those with DR3/DR4 haplotypes. We further assessed genome-wide differences in gene regulatory element and biological pathway enrichments between the non-DR3/DR4 and DR3/DR4 cohorts. Finally, we developed a genetic risk score (GRS) to predict T1D in individuals without DR3/DR4 and compared with an existing T1D GRS. RESULTS A total of 18 T1D risk variants in non-DR3/DR4 samples were identified. Risk variants at the MHC and multiple other loci genome wide had heterogeneity in effects on T1D dependent on DR3/DR4 status, and non-DR3/DR4 T1D had evidence for a greater polygenic burden. T1D-associated variants in non-DR3/DR4 were more enriched for regulatory elements and pathways involved in antigen presentation, innate immunity, and β-cells and depleted in T cells compared with DR3/DR4. A non-DR3/DR4 GRS outperformed an existing risk score GRS2 in discriminating non-DR3/DR4 T1D from no diabetes (area under the curve 0.867; P = 7.48 × 10-32) and type 2 diabetes (0.907; P = 4.94 × 10-44). CONCLUSIONS In total, we identified heterogeneity in T1D genetic risk dependent on high-risk HLA-DR3/DR4 haplotype, which uncovers disease mechanisms and enables more accurate prediction of T1D across the HLA background.
Collapse
Affiliation(s)
- Carolyn McGrail
- Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, CA
| | - Joshua Chiou
- Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, CA
| | - Ruth Elgamal
- Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, CA
| | - Amber M. Luckett
- University of Exeter College of Medicine and Health, Exeter, U.K
| | - Richard A. Oram
- University of Exeter College of Medicine and Health, Exeter, U.K
- Royal Devon University Healthcare NHS Foundation Trust, Exeter, U.K
| | - Paola Benaglio
- Department of Pediatrics, University of California, San Diego, La Jolla, CA
| | - Kyle J. Gaulton
- Department of Pediatrics, University of California, San Diego, La Jolla, CA
| |
Collapse
|
109
|
Faber BG, Frysz M, Zheng J, Lin H, Flynn KA, Ebsim R, Saunders FR, Beynon R, Gregory JS, Aspden RM, Harvey NC, Lindner C, Cootes T, Evans DM, Davey Smith G, Gao X, Wang S, Kemp JP, Tobias JH. The genetic architecture of hip shape and its role in the development of hip osteoarthritis and fracture. Hum Mol Genet 2025; 34:207-217. [PMID: 39574169 PMCID: PMC11792254 DOI: 10.1093/hmg/ddae169] [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: 09/19/2024] [Revised: 11/07/2024] [Accepted: 11/12/2024] [Indexed: 01/23/2025] Open
Abstract
OBJECTIVES Hip shape is thought to be an important causal risk factor for hip osteoarthritis and fracture. We aimed to identify genetic determinants of hip shape and use these to assess causal relationships with hip osteoarthritis. METHODS Statistical hip shape modelling was used to derive 10 hip shape modes (HSMs) from DXA images in UK Biobank and Shanghai Changfeng cohorts (ntotal = 43 485). Genome-wide association study meta-analyses were conducted for each HSM. Two-sample Mendelian randomisation (MR) was used to estimate causal effects between HSM and hip osteoarthritis using hip fracture as a positive control. RESULTS Analysis of the first 10 HSMs identified 203 independent association signals (P < 5 × 10-9). Hip shape SNPs were also associated (P < 2.5 × 10-4) with hip osteoarthritis (n = 26) and hip fracture (n = 4). Fine mapping implicated SMAD3 and PLEC as candidate genes that may be involved in the development of hip shape and hip osteoarthritis. MR analyses suggested there was no causal effect between any HSM and hip osteoarthritis, however there was evidence that HSM2 (more obtuse neck-shaft angle) and HSM4 (wider femoral neck) have a causal effect on hip fracture (ORIVW method 1.27 [95% CI 1.12-1.44], P = 1.79 × 10-4 and ORIVW 0.74 [0.65-0.84], P = 7.60 × 10-6 respectively). CONCLUSIONS We report the largest hip shape GWAS meta-analysis that identifies hundreds of novel loci, some of which are also associated with hip osteoarthritis and hip fracture. MR analyses suggest hip shape may not cause hip osteoarthritis but is implicated in hip fractures. Consequently, interventions targeting hip shape in older adults to prevent hip osteoarthritis may prove ineffective.
Collapse
Affiliation(s)
- Benjamin G Faber
- Musculoskeletal Research Unit, Learning and Research Building, University of Bristol, Southmead Hospital, Bristol BS10 5NB, United Kingdom
- Medical Research Council Integrative Epidemiology Unit, Oakfield House, University of Bristol, Bristol BS8 2BN, United Kingdom
| | - Monika Frysz
- Musculoskeletal Research Unit, Learning and Research Building, University of Bristol, Southmead Hospital, Bristol BS10 5NB, United Kingdom
- Medical Research Council Integrative Epidemiology Unit, Oakfield House, University of Bristol, Bristol BS8 2BN, United Kingdom
| | - Jaiyi Zheng
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, China
| | - Huandong Lin
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, 111 Yixueyuan Road, Xuhui District, Shanghai 200031, China
- Fudan Institute for Metabolic Diseases, Fudan University, Shanghai 200032, China
| | - Kaitlyn A Flynn
- Mater Research Institute, The University of Queensland, 37 Kent Street, Woolloongabba, Brisbane QLD 4102, Australia
| | - Raja Ebsim
- Division of Informatics, Imaging and Data Sciences, The University of Manchester, Oxford Road, Manchester M13 9PL, United Kingdom
| | - Fiona R Saunders
- Centre for Arthritis and Musculoskeletal Health, University of Aberdeen, Kings College, Aberdeen AB24 3FX, United Kingdom
| | - Rhona Beynon
- Musculoskeletal Research Unit, Learning and Research Building, University of Bristol, Southmead Hospital, Bristol BS10 5NB, United Kingdom
| | - Jennifer S Gregory
- Centre for Arthritis and Musculoskeletal Health, University of Aberdeen, Kings College, Aberdeen AB24 3FX, United Kingdom
| | - Richard M Aspden
- Centre for Arthritis and Musculoskeletal Health, University of Aberdeen, Kings College, Aberdeen AB24 3FX, United Kingdom
| | - Nicholas C Harvey
- Medical Research Council Lifecourse Epidemiology Centre, University of Southampton,Tremona Road, Southampton SO16 6YD, United Kingdom
- NIHR Southampton Biomedical Research Centre, University of Southampton, Tremona Road, Southampton SO16 6YD, United Kingdom
- University Hospital Southampton NHS Foundation Trust, Southampton General Hospital, Tremona Road, Southampton SO16 6YD, United Kingdom
| | - Claudia Lindner
- Division of Informatics, Imaging and Data Sciences, The University of Manchester, Oxford Road, Manchester M13 9PL, United Kingdom
| | - Timothy Cootes
- Division of Informatics, Imaging and Data Sciences, The University of Manchester, Oxford Road, Manchester M13 9PL, United Kingdom
| | - David M Evans
- Institute for Molecular Bioscience, The University of Queensland, 306 Carmody Road, Brisbane St Lucia QLD 4067, Australia
- The University of Queensland Diamantina Institute, The University of Queensland, Brisbane St Lucia, QLD 4072, Australia
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit, Oakfield House, University of Bristol, Bristol BS8 2BN, United Kingdom
| | - Xin Gao
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, 111 Yixueyuan Road, Xuhui District, Shanghai 200031, China
- Fudan Institute for Metabolic Diseases, Fudan University, Shanghai 200032, China
| | - Sijia Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, China
| | - John P Kemp
- Medical Research Council Integrative Epidemiology Unit, Oakfield House, University of Bristol, Bristol BS8 2BN, United Kingdom
- Mater Research Institute, The University of Queensland, 37 Kent Street, Woolloongabba, Brisbane QLD 4102, Australia
- Frazer Institute, The University of Queensland, 37 Kent Street, Woolloongabba, Brisbane QLD 4102, Australia
| | - Jonathan H Tobias
- Musculoskeletal Research Unit, Learning and Research Building, University of Bristol, Southmead Hospital, Bristol BS10 5NB, United Kingdom
- Medical Research Council Integrative Epidemiology Unit, Oakfield House, University of Bristol, Bristol BS8 2BN, United Kingdom
| |
Collapse
|
110
|
Geng J, Ruan X, Wu X, Chen X, Fu T, Gill D, Burgess S, Chen J, Ludvigsson JF, Larsson SC, Li X, Du Z, Yuan S. Network Mendelian randomisation analysis deciphers protein pathways linking type 2 diabetes and gastrointestinal disease. Diabetes Obes Metab 2025; 27:866-875. [PMID: 39592890 PMCID: PMC7617254 DOI: 10.1111/dom.16087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2024] [Revised: 11/09/2024] [Accepted: 11/09/2024] [Indexed: 11/28/2024]
Abstract
AIMS The molecular mechanisms underlying the association between type 2 diabetes (T2D) and gastrointestinal (GI) disease are unclear. To identify protein pathways, we conducted a two-stage network Mendelian randomisation (MR) study. MATERIALS AND METHODS Genetic instruments for T2D were obtained from a large-scale summary-level genome-wide meta-analysis. Genetic associations with blood protein levels were obtained from three genome-wide association studies on plasma proteins (i.e. the deCODE study as the discovery and the UKB-PPP and Fenland studies as the replication). Summary-level data on 10 GI diseases were derived from genome-wide meta-analysis of the UK Biobank and FinnGen. MR and colocalisation analyses were performed. Pathways were constructed according to the directionality of total and indirect effects, and corresponding proportional mediation was estimated. Druggability assessments were conducted across four databases to prioritise protein mediators. RESULTS Genetic liability to T2D was associated with 69 proteins in the discovery protein dataset after multiple testing corrections. All associations were replicated at the nominal significance level. Among T2D-associated proteins, genetically predicted levels of nine proteins were associated with at least one of the GI diseases. Genetically predicted levels of SULT2A1 (odds ratio = 1.98, 95% CI 1.80-2.18), and ADH1B (odds ratio = 2.05, 95% CI 1.43-2.94) were associated with cholelithiasis and cirrhosis respectively. SULT2A1 and cholelithiasis (PH4 = 0.996) and ADH1B and cirrhosis (PH4 = 0.931) have strong colocalisation support, accounting for the mediation proportion of 72.8% (95% CI 45.7-99.9) and 42.9% (95% CI 15.5-70.4) respectively. CONCLUSIONS The study identified some proteins mediating T2D-GI disease associations, which provided biological insights into the underlying pathways.
Collapse
Affiliation(s)
- Jiawei Geng
- Zhejiang Key Laboratory of Blood-Stasis-Toxin Syndrome, Zhejiang Chinese Medical University, Hangzhou, 310053, China
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xixian Ruan
- Department of Gastroenterology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Xing Wu
- Department of Gastroenterology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Xuejie Chen
- Department of Gastroenterology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Tian Fu
- Department of Gastroenterology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, LondonSW7 2BX, UK
| | - Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Jie Chen
- Zhejiang Key Laboratory of Blood-Stasis-Toxin Syndrome, Zhejiang Chinese Medical University, Hangzhou, 310053, China
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Department of Gastroenterology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Jonas F. Ludvigsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Pediatrics, Orebro University Hospital, Orebro, Sweden
- Department of Medicine, Celiac Disease Center at Columbia University Medical Center, New York, New York, USA
| | - Susanna C. Larsson
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, 10Uppsala, Sweden
| | - Xue Li
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Zhongyan Du
- Zhejiang Key Laboratory of Blood-Stasis-Toxin Syndrome, Zhejiang Chinese Medical University, Hangzhou, 310053, China
- Zhejiang Engineering Research Center for "Preventive Treatment" Smart Health of Traditional Chinese Medicine, Zhejiang Chinese Medical University, Hangzhou, 310053, China
- School of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Shuai Yuan
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of surgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| |
Collapse
|
111
|
Magavern EF, Deshmukh H, Asselin G, Theusch E, Trompet S, Li X, Noordam R, Chen YDI, Seeman TE, Taylor KD, Post WS, Tardif JC, Paul DS, Benjamin EJ, Heard-Costa NL, Vasan RS, Rotter JI, Krauss RM, Jukema JW, Ridker PM, Munroe PB, Caulfield MJ, Chasman DI, Dubé MP, Hitman GA, Warren HR. GWAS of CRP response to statins further supports the role of APOE in statin response: A GIST consortium study. Pharmacol Res 2025; 212:107575. [PMID: 39798939 DOI: 10.1016/j.phrs.2024.107575] [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: 10/15/2024] [Revised: 12/30/2024] [Accepted: 12/31/2024] [Indexed: 01/15/2025]
Abstract
Statins are first-line treatments in the primary and secondary prevention of cardiovascular disease. Clinical studies show statins act independently of lipid-lowering mechanisms to decrease C-reactive protein (CRP), an inflammation marker. We aim to elucidate genetic loci associated with CRP statin response. CRP statin response is the change in log-CRP between off-treatment and on-treatment measurements. Cohort-level Genome-Wide Association Studies (GWAS) of CRP response were performed using 1000 Genomes imputed data, testing ∼10 million common genetic variants. GWAS meta-analysis combined results from seven cohorts and clinical trials totalling 14,070 statin-treated individuals of European ancestry within the GIST consortium. Secondary analyses included statin-by-placebo interaction analyses, and lookups in African ancestry cohorts. Our GWAS identified two genome-wide significant (P < 5e-8) loci: APOE and HNF1A for CRP statin response corrected for baseline CRP. The missense lead variant rs429358 at APOE, contributing to the APOE-E4 haplotype, is a risk locus for dyslipidaemia, Alzheimer's and coronary artery disease (CAD). The HNF1A locus is associated with diabetes, cholesterol levels, and CAD. Both loci are also associated with baseline CRP levels, and neither locus achieved a significant (P < 0.05) result from the statin v. placebo interaction meta-analysis using randomized clinical trial data. However, the interaction result (P-int=0.09) for APOE was suggestive and possibly underpowered. The APOE-E4 signal may therefore be associated with both CRP and LDL-cholesterol statin response. Combined with suggestions in the literature that APOE also leads to differential statin benefit in Alzheimer's, the APOE locus warrants further investigation for potential genetic effects on healthcare with statin treatment.
Collapse
Affiliation(s)
- Emma F Magavern
- Centre of Clinical Pharmacology & Precision Medicine, William Harvey Research Institute, Queen Mary University of London, London, UK; NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, UK
| | | | - Geraldine Asselin
- Faculty of Medicine, Université de Montréal, and the Montreal Heart Institute, Montreal, Canada
| | - Elizabeth Theusch
- Department of Pediatrics, University of California San Francisco, Oakland, CA, United States
| | - Stella Trompet
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands; Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Xiaohui Li
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics and The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Y-D Ida Chen
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics and The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Teresa E Seeman
- Division of Geriatrics, Dept of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics and The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Wendy S Post
- Division of Cardiology, Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Jean-Claude Tardif
- Faculty of Medicine, Université de Montréal, and the Montreal Heart Institute, Montreal, Canada
| | - Dirk S Paul
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK; Precision Medicine and Biosamples, Oncology R&D, AstraZeneca, Cambridge, UK
| | - Emelia J Benjamin
- Boston University Chobanian & Avedisian School of Medicine and School of Public Health, NHLBI and Boston University's Framingham Heart Study, Framingham, MA, United States
| | - Nancy L Heard-Costa
- Boston University Chobanian & Avedisian School of Medicine and School of Public Health, NHLBI and Boston University's Framingham Heart Study, Framingham, MA, United States
| | - Ramachandran S Vasan
- Boston University Chobanian & Avedisian School of Medicine and School of Public Health, NHLBI and Boston University's Framingham Heart Study, Framingham, MA, United States
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics and The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Ronald M Krauss
- Department of Pediatrics, University of California San Francisco, Oakland, CA, United States
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, United States
| | - Patricia B Munroe
- Centre of Clinical Pharmacology & Precision Medicine, William Harvey Research Institute, Queen Mary University of London, London, UK; NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, UK
| | - Mark J Caulfield
- Centre of Clinical Pharmacology & Precision Medicine, William Harvey Research Institute, Queen Mary University of London, London, UK; NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, UK
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, United States
| | - Marie-Pierre Dubé
- Faculty of Medicine, Université de Montréal, and the Montreal Heart Institute, Montreal, Canada
| | - Graham A Hitman
- Centre of Genomic Medicine and Child Health, Blizard Institute, Queen Mary University of London, London, UK
| | - Helen R Warren
- Centre of Clinical Pharmacology & Precision Medicine, William Harvey Research Institute, Queen Mary University of London, London, UK; NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, UK.
| |
Collapse
|
112
|
Greene CA, Hampton G, Jaworski J, Shuey MM, Khan A, Luo Y, Jarvik GP, Namjou-Khales B, Edwards TL, Velez Edwards DR, Hellwege JN. Multi-ancestry meta-analysis of keloids uncovers novel susceptibility loci in diverse populations. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2025:2025.01.28.25321288. [PMID: 39974034 PMCID: PMC11838924 DOI: 10.1101/2025.01.28.25321288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/21/2025]
Abstract
Keloids are raised scars that grow beyond original wound boundaries, resulting in pain and disfigurement. Reasons for keloid development are not well-understood, and current treatment options are limited. Keloids are more likely to occur in darker-skinned individuals of African and Asian descent than in Europeans. We performed a genome-wide association study (GWAS) examining keloid risk across and within continental ancestry groups, incorporating 7,837 cases and 1,593,009 controls. We detected 21 novel independent loci in the multi-ancestry analysis, including several previously associated with fibroproliferative disorders. Heritability estimates were 6%, 21%, and 34% for the European, East Asian, and African ancestry analyses, respectively. Genetically predicted gene expression and colocalization analyses identified 27 gene-tissue pairs, including nine in skin and fibroblasts. Pathway analysis implicated integrin signaling and upstream regulators involved in cancer, fibrosis, and sex hormone signaling. This investigation nearly quintuples the number of keloid-associated risk loci, illuminating biological processes in keloid pathology.
Collapse
|
113
|
Zhang M, Su W, Deng J, Zhai B, Zhu G, Gao R, Zeng Q, Qiu J, Bian Z, Xiao H, Luan G, Wang R. Multi-ancestry genome-wide meta-analysis with 472,819 individuals identifies 32 novel risk loci for psoriasis. J Transl Med 2025; 23:133. [PMID: 39885523 PMCID: PMC11783861 DOI: 10.1186/s12967-024-06015-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2024] [Accepted: 12/20/2024] [Indexed: 02/01/2025] Open
Abstract
BACKGROUND Psoriasis is a common chronic, recurrent, immune-mediated disease involved in the skin or joints or both. However, deeper insight into the genetic susceptibility of psoriasis is still unclear. METHODS Here we performed the largest multi-ancestry meta-analysis of genome-wide association study including 28,869 psoriasis cases and 443,950 healthy controls. RESULTS We identified 74 genome-wide significant loci for psoriasis. Of 74 loci, 32 were novel psoriasis risk loci. Across 74 loci, 801 likely causal genes are indicated and 164 causal genes are prioritized. SNP-based heritability analyses demonstrated that common variants explain 15% of genetic risk for psoriasis. Gene-set analyses and the genetic correlation revealed that psoriasis-related genes have the positive correlations with autoimmune diseases such as ulcerative colitis, inflammatory bowel diseases, and Crohn's disease. Gene-drug interaction analysis suggested that psoriasis-associated genes overlapped with targets of current medications for psoriasis. Finally, we used the multi-ancestry meta-analysis to explore drug repurposing and the potential targets for psoriasis. CONCLUSIONS We identified 74 genome-wide significant loci for psoriasis. Based on 74 loci, we provided new biological insights to the etiology of psoriasis. Of clinical interest, we gave some hints for 76 potential targets and drug repurposing for psoriasis.
Collapse
Affiliation(s)
- Min Zhang
- Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, China
- Laboratory for Clinical Medicine, Capital Medical University, Beijing, China
| | - Wenting Su
- Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, China
- Laboratory for Clinical Medicine, Capital Medical University, Beijing, China
| | - Jiahui Deng
- Department of Neurosurgery, SanBo Brain Hospital, Capital Medical University, Beijing, China
- Laboratory for Clinical Medicine, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Epilepsy, Department of Brain Institute, Center of Epilepsy, Beijing Institute for Brain Disorders, SanBo Brain Hospital, Capital Medical University, Beijing, China
| | - Bin Zhai
- Department of Hematology, The Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Gaizhi Zhu
- Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, China
- Laboratory for Clinical Medicine, Capital Medical University, Beijing, China
| | - Ran Gao
- Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, China
- Laboratory for Clinical Medicine, Capital Medical University, Beijing, China
| | - Qi Zeng
- Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, China
- Laboratory for Clinical Medicine, Capital Medical University, Beijing, China
| | - Jinming Qiu
- Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, China
- Laboratory for Clinical Medicine, Capital Medical University, Beijing, China
| | - Ziqing Bian
- Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, China
- Laboratory for Clinical Medicine, Capital Medical University, Beijing, China
| | - He Xiao
- State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, Beijing, China
| | - Guoming Luan
- Department of Neurosurgery, SanBo Brain Hospital, Capital Medical University, Beijing, China.
- Laboratory for Clinical Medicine, Capital Medical University, Beijing, China.
- Beijing Key Laboratory of Epilepsy, Department of Brain Institute, Center of Epilepsy, Beijing Institute for Brain Disorders, SanBo Brain Hospital, Capital Medical University, Beijing, China.
| | - Renxi Wang
- Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, China.
- Laboratory for Clinical Medicine, Capital Medical University, Beijing, China.
| |
Collapse
|
114
|
Lee MA, Burley KL, Hazelwood EL, Moore S, Lewis SJ, Goudswaard LJ. Exploring the role of circulating proteins in multiple myeloma risk: a Mendelian randomization study. Sci Rep 2025; 15:3752. [PMID: 39885253 PMCID: PMC11782597 DOI: 10.1038/s41598-025-86222-5] [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: 07/25/2024] [Accepted: 01/09/2025] [Indexed: 02/01/2025] Open
Abstract
Multiple myeloma (MM) is an incurable blood cancer with unclear aetiology. Proteomics is a valuable tool in exploring mechanisms of disease. We investigated the causal relationship between circulating proteins and MM risk, using two of the largest cohorts with proteomics data to-date. We performed bidirectional two-sample Mendelian randomization (MR; forward MR = causal effect estimation of proteins and MM risk; reverse MR = causal effect estimation of MM risk and proteins). Summary statistics for plasma proteins were obtained from genome-wide association studies performed using SomaLogic (N = 35,559; deCODE) and Olink (N = 34,557; UK Biobank; UKB) proteomic platforms and for MM risk from a meta-analysis of UKB and FinnGen (case = 1649; control = 727,247) or FinnGen only (case = 1085; control = 271,463). Cis-SNPs associated with protein levels were used to instrument circulating proteins. We evaluated proteins for the consistency of directions of effect across MR analyses (with 95% confidence intervals not overlapping the null) and corroborating evidence from genetic colocalization. In the forward MR, 994 (SomaLogic) and 1570 (Olink) proteins were instrumentable. 440 proteins were analysed in both deCODE and UKB; 302 (69%) of these showed consistent directions of effect in the forward MR. Seven proteins had 95% confidence intervals (CIs) that did not overlap the null in both forward MR analyses and did not have evidence for an effect in the reverse direction: higher levels of dermatopontin (DPT), beta-crystallin B1 (CRYBB1), interleukin-18-binding protein (IL18BP) and vascular endothelial growth factor receptor 2 (KDR) and lower levels of odorant-binding protein 2b (OBP2B), glutamate-cysteine ligase regulatory subunit (GCLM) and gamma-crystallin D (CRYGD) were implicated in increasing MM risk. Evidence from genetic colocalization did not meet our threshold for a shared causal signal between any of these proteins and MM risk (h4 < 0.8). Our results highlight seven circulating proteins which may be involved in MM risk. Although evidence from genetic colocalization suggests these associations may not be robust to the effects of horizontal pleiotropy, these proteins may be useful markers of MM risk. Future work should explore the utility of these proteins in disease prediction or prevention using proteomic data from patients with MM or precursor conditions.
Collapse
Affiliation(s)
- Matthew A Lee
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organisation, Lyon, France
- Population Health Sciences, University of Bristol, Bristol, UK
| | - Kate L Burley
- School of Cellular and Molecular Medicine, University of Bristol, Bristol, UK
| | - Emma L Hazelwood
- Population Health Sciences, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Sally Moore
- University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK
| | - Sarah J Lewis
- Population Health Sciences, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Lucy J Goudswaard
- Population Health Sciences, University of Bristol, Bristol, UK.
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
| |
Collapse
|
115
|
Morales-Berstein F, Khouja J, Gormley M, Ebrahimi E, Virani S, McKay J, Brennan P, Richardson TG, Relton CL, Smith GD, Borges MC, Dudding T, Richmond RC. Reassessing the link between adiposity and head and neck cancer: a Mendelian randomization study. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2025:2024.11.21.24317707. [PMID: 39974030 PMCID: PMC11838947 DOI: 10.1101/2024.11.21.24317707] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/21/2025]
Abstract
Background Adiposity has been associated with an increased risk of head and neck cancer (HNC). Although body mass index (BMI) has been inversely associated with HNC risk among smokers, this is likely due to confounding. Previous Mendelian randomization (MR) studies could not fully discount causality between adiposity and HNC due to limited statistical power. Hence, we aimed to revisit this using the largest genome-wide association study (GWAS) of HNC available, which has more granular data on HNC subsites. Methods We assessed the genetically predicted effects of BMI (N=806,834), waist-to-hip ratio (WHR; N=697,734) and waist circumference (N=462,166) on the risk of HNC (N=12,264 cases and 19,259 controls) and its subsites (oral, laryngeal, hypopharyngeal and oropharyngeal cancers) using a two-sample MR framework. We used the inverse variance weighted (IVW) MR approach and multiple sensitivity analyses including the weighted median, weighted mode, MR-Egger, MR-PRESSO, and CAUSE approaches. We also used multivariable MR (MVMR) to explore the direct effects of the adiposity measures on HNC, while accounting for smoking behaviour, a well-known HNC risk factor. Results In univariable MR, higher genetically predicted BMI increased the risk of overall HNC (IVW OR=1.17 per 1 standard deviation [1-SD] higher BMI, 95% CI 1.02-1.34, p=0.03), with no heterogeneity across subsites (Q p=0.78). However, the effect was not consistent in sensitivity analyses. The IVW effect was attenuated when smoking was included in the MVMR model (OR accounting for comprehensive smoking index=0.96 per 1-SD higher BMI, 95% CI 0.80-1.15, p=0.64) and CAUSE indicated the IVW results could be biased by correlated pleiotropy. Furthermore, we did not find a link between genetically predicted WHR (IVW OR=1.05 per 1-SD higher WHR, 95% CI 0.89-1.24, p=0.53) or waist circumference and HNC risk (IVW OR=1.01 per 1-SD higher waist circumference, 95% CI 0.85-1.21, p=0.87). Conclusions Our findings suggest that adiposity does not play a role in HNC risk.
Collapse
Affiliation(s)
- Fernanda Morales-Berstein
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Jasmine Khouja
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Mark Gormley
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
- University of Bristol Dental School, 1 Trinity Walk, Avon Street, Bristol, United Kingdom
| | - Elmira Ebrahimi
- Genomic Epidemiology Branch, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Shama Virani
- Genomic Epidemiology Branch, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - James McKay
- Genomic Epidemiology Branch, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Paul Brennan
- Genomic Epidemiology Branch, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Tom G Richardson
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Caroline L Relton
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
- London School of Hygiene & Tropical Medicine, Keppel Street, London WC1E 7HT, United Kingdom
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - M Carolina Borges
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Tom Dudding
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
- University of Bristol Dental School, 1 Trinity Walk, Avon Street, Bristol, United Kingdom
| | - Rebecca C Richmond
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| |
Collapse
|
116
|
Wang L, Kranzler HR, Gelernter J, Zhou H. Investigating the Contribution of Coding Variants in Alcohol Use Disorder Using Whole-Exome Sequencing Across Ancestries. Biol Psychiatry 2025:S0006-3223(25)00062-9. [PMID: 39892688 DOI: 10.1016/j.biopsych.2025.01.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/06/2024] [Revised: 12/16/2024] [Accepted: 01/26/2025] [Indexed: 02/04/2025]
Abstract
BACKGROUND Alcohol use disorder (AUD) is a leading cause of death and disability worldwide. There has been substantial progress in identifying genetic variants that underlie AUD. However, whole-exome sequencing studies of AUD have been hampered by the lack of available samples. METHODS We analyzed whole-exome sequencing data of 4530 samples from the Yale-Penn cohort and 469,835 samples from the UK Biobank, which represent an unprecedented resource for exploring the contribution of coding variants in AUD. After quality control, 1750 African-ancestry (1142 cases) and 2039 European-ancestry (1420 cases) samples from the Yale-Penn and 6142 African-ancestry (130 cases), 415,617 European-ancestry (12,861 cases), and 4607 South Asian (130 cases) samples from the UK Biobank cohorts were included in the analyses. RESULTS We confirmed the well-known functional variant rs1229984 in ADH1B (p = 4.88 × 10-31) and several other variants in ADH1C. Gene-based collapsing tests that considered the high allelic heterogeneity revealed the previously unreported genes CNST (p = 1.19 × 10-6), attributable to rare variants with allele frequency < 0.001, and IFIT5 (p = 3.74 × 10-6), driven by the burden of both common and rare loss-of-function and missense variants. CONCLUSIONS This study extends our understanding of the genetic architecture of AUD by providing insights into the contribution of rare coding variants, separately and convergently with common variants in AUD.
Collapse
Affiliation(s)
- Lu Wang
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut; Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut
| | - Henry R Kranzler
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania; Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania
| | - Joel Gelernter
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut; Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut; Department of Genetics, Yale School of Medicine, New Haven, Connecticut; Department of Neuroscience, Yale School of Medicine, New Haven, Connecticut.
| | - Hang Zhou
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut; Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut; Department of Biomedical Informatics and Data Science, Yale School of Medicine, New Haven, Connecticut; Center for Brain and Mind Health, Yale School of Medicine, New Haven, Connecticut.
| |
Collapse
|
117
|
Aliev F, De Sa Nogueira D, Aston-Jones G, Dick DM. Genetic associations between orexin genes and phenotypes related to behavioral regulation in humans, including substance use. Mol Psychiatry 2025:10.1038/s41380-025-02895-4. [PMID: 39880903 DOI: 10.1038/s41380-025-02895-4] [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: 02/22/2024] [Revised: 08/23/2024] [Accepted: 01/14/2025] [Indexed: 01/31/2025]
Abstract
The hypothalamic neuropeptide system of orexin (hypocretin) neurons provides projections throughout the neuraxis and has been linked to sleep regulation, feeding and motivation for salient rewards including drugs of abuse. However, relatively little has been done to examine genes associated with orexin signaling and specific behavioral phenotypes in humans. Here, we tested for association of twenty-seven genes involved in orexin signaling with behavioral phenotypes in humans. We tested the full gene set, functional subsets, and individual genes involved in orexin signaling. Our primary phenotype of interest was Externalizing, a composite factor comprised of behaviors and disorders associated with reward-seeking, motivation, and behavioral regulation. We also tested for association with additional phenotypes that have been related to orexin regulation in model organism studies, including alcohol consumption, problematic alcohol use, daytime sleepiness, insomnia, cigarettes per day, smoking initiation, and body mass index. The composite set of 27 genes corresponding to orexin function was highly associated with Externalizing, as well as with alcohol consumption, insomnia, cigarettes per day, smoking initiation and BMI. In addition, all gene subsets (except the OXR2/HCRTR2 subset) were associated with Externalizing. BMI was significantly associated with all gene subsets. The "validated factors for PPOX/HCRT" and "PPOX/HCRT upregulation" gene subsets also were associated with alcohol consumption. Individually, 8 genes showed a strong association with Externalizing, 12 with BMI, 7 with smoking initiation, 3 with alcohol consumption, and 2 with problematic alcohol use, after correction for multiple testing. This study indicates that orexin genes are associated with multiple behaviors and disorders related to self-regulation in humans. This is consistent with prior work in animals that implicated orexin signaling in motivational activation induced by salient stimuli, and supports the hypothesis that orexin signaling is an important potential therapeutic target for numerous behavioral disorders.
Collapse
Affiliation(s)
- Fazil Aliev
- Department of Psychiatry, Rutgers Robert Wood Johnson Medical School, Piscataway, NJ, 08854, USA
- Rutgers Addiction Research Center, Brain Health Institute, Rutgers University and Rutgers Health, Piscataway, NJ, 08854, USA
| | - David De Sa Nogueira
- Department of Psychiatry, Rutgers Robert Wood Johnson Medical School, Piscataway, NJ, 08854, USA
- Rutgers Addiction Research Center, Brain Health Institute, Rutgers University and Rutgers Health, Piscataway, NJ, 08854, USA
| | - Gary Aston-Jones
- Department of Psychiatry, Rutgers Robert Wood Johnson Medical School, Piscataway, NJ, 08854, USA
- Rutgers Addiction Research Center, Brain Health Institute, Rutgers University and Rutgers Health, Piscataway, NJ, 08854, USA
| | - Danielle M Dick
- Department of Psychiatry, Rutgers Robert Wood Johnson Medical School, Piscataway, NJ, 08854, USA.
- Rutgers Addiction Research Center, Brain Health Institute, Rutgers University and Rutgers Health, Piscataway, NJ, 08854, USA.
| |
Collapse
|
118
|
Kweon H, Burik CAP, Ning Y, Ahlskog R, Xia C, Abner E, Bao Y, Bhatta L, Faquih TO, de Feijter M, Fisher P, Gelemanović A, Giannelis A, Hottenga JJ, Khalili B, Lee Y, Li-Gao R, Masso J, Myhre R, Palviainen T, Rietveld CA, Teumer A, Verweij RM, Willoughby EA, Agerbo E, Bergmann S, Boomsma DI, Børglum AD, Brumpton BM, Davies NM, Esko T, Gordon SD, Homuth G, Ikram MA, Johannesson M, Kaprio J, Kidd MP, Kutalik Z, Kwong ASF, Lee JJ, Luik AI, Magnus P, Marques-Vidal P, Martin NG, Mook-Kanamori DO, Mortensen PB, Oskarsson S, Pedersen EM, Polašek O, Rosendaal FR, Smart MC, Snieder H, van der Most PJ, Vollenweider P, Völzke H, Willemsen G, Beauchamp JP, DiPrete TA, Linnér RK, Lu Q, Morris TT, Okbay A, Harden KP, Abdellaoui A, Hill WD, de Vlaming R, Benjamin DJ, Koellinger PD. Associations between common genetic variants and income provide insights about the socio-economic health gradient. Nat Hum Behav 2025:10.1038/s41562-024-02080-7. [PMID: 39875632 DOI: 10.1038/s41562-024-02080-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Accepted: 10/23/2024] [Indexed: 01/30/2025]
Abstract
We conducted a genome-wide association study on income among individuals of European descent (N = 668,288) to investigate the relationship between socio-economic status and health disparities. We identified 162 genomic loci associated with a common genetic factor underlying various income measures, all with small effect sizes (the Income Factor). Our polygenic index captures 1-5% of income variance, with only one fourth due to direct genetic effects. A phenome-wide association study using this index showed reduced risks for diseases including hypertension, obesity, type 2 diabetes, depression, asthma and back pain. The Income Factor had a substantial genetic correlation (0.92, s.e. = 0.006) with educational attainment. Accounting for the genetic overlap of educational attainment with income revealed that the remaining genetic signal was linked to better mental health but reduced physical health and increased risky behaviours such as drinking and smoking. These findings highlight the complex genetic influences on income and health.
Collapse
Affiliation(s)
- Hyeokmoon Kweon
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Casper A P Burik
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Yuchen Ning
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Rafael Ahlskog
- Department of Government, Uppsala University, Uppsala, Sweden
| | - Charley Xia
- Department of Psychology, School of Philosophy, Psychology and Language Sciences, University of Edinburgh, Edinburgh, UK
| | - Erik Abner
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Yanchun Bao
- School of Mathematics, Statistics and Actuarial Sciences, University of Essex, Essex, UK
| | - Laxmi Bhatta
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | - Tariq O Faquih
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Maud de Feijter
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - Paul Fisher
- Institute for Social and Economic Research, University of Essex, Essex, UK
| | - Andrea Gelemanović
- Department of Public Health, University of Split School of Medicine, Split, Croatia
| | | | - Jouke-Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Bita Khalili
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Yunsung Lee
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Ruifang Li-Gao
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Jaan Masso
- School of Economics and Business Administration, University of Tartu, Tartu, Estonia
| | - Ronny Myhre
- Department of Genetics and Bioinformatics, Norwegian Institute of Public Health, Oslo, Norway
| | - Teemu Palviainen
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Cornelius A Rietveld
- Department of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, the Netherlands
- Rotterdam Institute for Behavior and Biology, Erasmus University Rotterdam, Rotterdam, the Netherlands
| | - Alexander Teumer
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Renske M Verweij
- Department of Public Administration and Sociology, Erasmus University Rotterdam, Rotterdam, the Netherlands
| | - Emily A Willoughby
- Department of Psychology, University of Minnesota Twin Cities, Minneapolis, USA
| | - Esben Agerbo
- iPSYCH-the Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus University, Aarhus, Denmark
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark
- School of Business and Social Sciences, Aarhus University, Aarhus, Denmark
| | - Sven Bergmann
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Public Health, Amsterdam UMC, Amsterdam, the Netherlands
- Amsterdam Reproduction & Development, Amsterdam UMC, Amsterdam, the Netherlands
- Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Anders D Børglum
- iPSYCH-the Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus University, Aarhus, Denmark
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- Center for Genome Analysis and Personalized Medicine, Aarhus, Denmark
| | - Ben M Brumpton
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway
- Clinic of Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Neil Martin Davies
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
- Division of Psychiatry and Department of Statistical Sciences, University College London, London, UK
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Tõnu Esko
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Scott D Gordon
- Genetic Epidemiology Lab, Queensland Institute of Medical Research, Brisbane, Queensland, Australia
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - Magnus Johannesson
- Department of Economics, Stockholm School of Economics, Stockholm, Sweden
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Michael P Kidd
- Economics, RMIT University, Melbourne, Victoria, Australia
- International School of Technology and Management, Feng Chia University, Taichung, Taiwan
| | - Zoltán Kutalik
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- University Center for Primary Care and Public Health, Unisante, Lausanne, Switzerland
| | - Alex S F Kwong
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - James J Lee
- Department of Psychology, University of Minnesota Twin Cities, Minneapolis, USA
| | - Annemarie I Luik
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
- Trimbos Institute-Netherlands Institute for Mental Health and Addiction, Utrecht, the Netherlands
| | - Per Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Pedro Marques-Vidal
- Department of Medicine, Internal Medicine, Lausanne University Hospital (CHUV), Lausanne, Switzerland
- Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Nicholas G Martin
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Dennis O Mook-Kanamori
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, the Netherlands
| | - Preben Bo Mortensen
- iPSYCH-the Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus University, Aarhus, Denmark
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark
- School of Business and Social Sciences, Aarhus University, Aarhus, Denmark
| | - Sven Oskarsson
- Department of Government, Uppsala University, Uppsala, Sweden
| | - Emil M Pedersen
- iPSYCH-the Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus University, Aarhus, Denmark
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark
- School of Business and Social Sciences, Aarhus University, Aarhus, Denmark
| | - Ozren Polašek
- Department of Public Health, University of Split School of Medicine, Split, Croatia
- Algebra University, Zagreb, Croatia
| | - Frits R Rosendaal
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Melissa C Smart
- Institute for Social and Economic Research, University of Essex, Essex, UK
| | - Harold Snieder
- Department of Epidemiology, University of Groningen and University Medical Center Groningen, Groningen, the Netherlands
| | - Peter J van der Most
- Department of Epidemiology, University of Groningen and University Medical Center Groningen, Groningen, the Netherlands
| | - Peter Vollenweider
- Trimbos Institute-Netherlands Institute for Mental Health and Addiction, Utrecht, the Netherlands
- Department of Medicine, Internal Medicine, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Faculty of Health, Sports and Wellbeing, Inholland University of Applied Sciences, Haarlem, the Netherlands
| | - Jonathan P Beauchamp
- Interdisciplinary Center for Economic Science and Department of Economics, George Mason University, Fairfax, VA, USA
| | | | - Richard Karlsson Linnér
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Department of Economics, Leiden Law School, Universiteit Leiden, Leiden, the Netherlands
| | - Qiongshi Lu
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, USA
| | - Tim T Morris
- Centre for Longitudinal Studies, Social Research Institute, University College London, London, UK
| | - Aysu Okbay
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - K Paige Harden
- Department of Psychology and Population Reseach Center, University of Texas at Austin, Austin, TX, USA
| | - Abdel Abdellaoui
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.
| | - W David Hill
- Department of Psychology, School of Philosophy, Psychology and Language Sciences, University of Edinburgh, Edinburgh, UK.
- Lothian Birth Cohort Studies, University of Edinburgh, Edinburgh, UK.
| | - Ronald de Vlaming
- Department of Econometrics and Data Science, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Daniel J Benjamin
- Anderson School of Management, University of California, Los Angeles, Los Angeles, CA, USA
- Human Genetics Department, UCLA David Geffen School of Medicine, Los Angeles, CA, USA
- National Bureau of Economic Research, Cambridge, MA, USA
| | - Philipp D Koellinger
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
- DeSci Foundation, Geneva, Switzerland.
| |
Collapse
|
119
|
Nair JM, Bandesh K, Giri AK, Chakraborty S, Marwaha RK, Basu A, Tandon N, Bharadwaj D. Genetic insights into CRP levels in Indian adolescents: confirming adult genetic associations. Mol Genet Genomics 2025; 300:17. [PMID: 39843866 DOI: 10.1007/s00438-024-02213-7] [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: 09/17/2024] [Accepted: 12/11/2024] [Indexed: 01/30/2025]
Abstract
CRP is a biomarker of acute inflammation linked to metabolic complications. Given the rising prevalence of these conditions in India, we investigated the genetic basis of CRP levels in Indian adolescents, an underrepresented group in genetic studies, to identify early markers of metabolic risk. We performed a two-phased genome-wide association study (GWAS; N = 5052) and an independent Exome-wide association study (ExWAS; N = 4547), to identify both common and rare genetic variants associated with CRP levels. The study identified intergenic variants near CRP and CRPP1 genes, and APOC1 gene as the key regulators of CRP levels establishing the universality of these associations. The GWAS identified the variant rs4247360 (PITPNC1) to be associated at a suggestive significance. The ExWAS single variant association identified novel associations in genes FGL1 (rs35431851), C19orf45 (rs608144, rs475923, rs484870), TRAPPC12 (rs11686212) and KIAA0087 (rs17153822). The SKATO analysis of the rare variants highlighted the role of loss of function and missense variants in genes EPS15, CCDC15, ZNF286A, ELF1, B3GNT8, ZNF850, MAP2, and PSG2. The GWAS and ExWAS in the present study validated the association of 56 variants previously reported for CRP levels. The meta-analysis with the CRP GWAS earlier reported in Indian adults revealed the shared genetic architecture of CRP levels across age groups. The gene-set enrichment analysis highlighted the role of CRP-associated genes in inflammatory and cardiometabolic pathways. The study enhances understanding of genetic predispositions to inflammation and metabolic disorders confirming known associations, identifying novel loci, and validating shared genetic architecture across age-groups, guiding targeted prevention for at-risk youth.
Collapse
Affiliation(s)
- Janaki M Nair
- Systems Genomics Laboratory, School of Biotechnology, Jawaharlal Nehru University, New Delhi, 110067, India
| | - Khushdeep Bandesh
- CSIR-Institute of Genomics and Integrative Biology, Delhi, 110025, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Anil K Giri
- CSIR-Institute of Genomics and Integrative Biology, Delhi, 110025, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Shraddha Chakraborty
- CSIR-Institute of Genomics and Integrative Biology, Delhi, 110025, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Raman K Marwaha
- International Life Sciences Institute (ILSI), New Delhi, India
| | - Analabha Basu
- National Institute of Biomedical Genomics, Kalyani, West Bengal, 741251, India
| | - Nikhil Tandon
- Department of Endocrinology and Metabolism, All India Institute of Medical Sciences, New Delhi, 110029, India.
| | - Dwaipayan Bharadwaj
- Systems Genomics Laboratory, School of Biotechnology, Jawaharlal Nehru University, New Delhi, 110067, India.
| |
Collapse
|
120
|
Kuang A, Hivert MF, Hayes MG, Lowe WL, Scholtens DM. Multi-ancestry genome-wide association analyses: a comparison of meta- and mega-analyses in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study. BMC Genomics 2025; 26:65. [PMID: 39849370 PMCID: PMC11755808 DOI: 10.1186/s12864-025-11229-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2024] [Accepted: 01/08/2025] [Indexed: 01/25/2025] Open
Abstract
BACKGROUND There is increasing need for effective incorporation of high-dimensional genetics data from individuals with varied ancestry in genome-wide association (GWAS) analyses. Classically, multi-ancestry GWAS analyses are performed using statistical meta-analysis to combine results conducted within homogeneous ancestry groups. The emergence of cosmopolitan reference panels makes collective preprocessing of GWAS data possible, but impact on downstream GWAS results in a mega-analysis framework merits investigation. We utilized GWAS data from the multi-national Hyperglycemia and Adverse Pregnancy Outcome Study to investigate differences in GWAS findings using a homogeneous ancestry meta-analysis versus a heterogeneous ancestry mega-analysis pipeline. Maternal fasting and 1-hr glucose and metabolomics measured during a 2-hr 75-gram oral glucose tolerance test during early third trimester pregnancy were evaluated as phenotypes. RESULTS For the homogeneous ancestry meta-analysis pipeline, variant data were prepared by identifying sets of individuals with similar ancestry and imputing to ancestry-specific reference panels. GWAS was conducted within each ancestry group and results were combined using random-effects meta-analysis. For the heterogeneous ancestry mega-analysis pipeline, data for all individuals were collectively imputed to the Trans-Omics for Precision Medicine (TOPMed) cosmopolitan reference panel, and GWAS was conducted using a unified mega-analysis. The meta-analysis pipeline identified genome-wide significant associations for 15 variants in a region close to GCK on chromosome 7 with maternal fasting glucose and no significant findings for 1-hr glucose. Associations in this same region were identified using the mega-analysis pipeline, along with a well-documented association at MTNR1B on chromosome 11 with both fasting and 1-hr maternal glucose. For metabolomics analyses, the number of significant findings in the heterogeneous ancestry mega-analysis far exceeded those from the homogeneous ancestry meta-analysis and confirmed many previously documented associations, but genomic inflation factors were much more variable. CONCLUSIONS For multi-ancestry GWAS, heterogeneous ancestry mega-analysis generates a rich set of variants for analysis using a cosmopolitan reference panel and results in vastly more significant, biologically credible and previously documented associations than a homogeneous ancestry meta-analysis approach. Genomic inflation factors do indicate that findings from the mega-analysis pipeline may merit cautious interpretation and further follow-up.
Collapse
Affiliation(s)
- Alan Kuang
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Marie-France Hivert
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada
- Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, QC, Canada
| | - M Geoffrey Hayes
- Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - William L Lowe
- Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Denise M Scholtens
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
| |
Collapse
|
121
|
Lu T, Zhang W, Robinson-Cohen C, Engelman CD, Lu Q, de Boer IH, Sun L, Paterson AD. Characterization of gene-environment interactions for vitamin D through variance quantitative trait loci: a UK Biobank-based genetic epidemiology study. Am J Clin Nutr 2025:S0002-9165(25)00021-8. [PMID: 39855341 DOI: 10.1016/j.ajcnut.2025.01.021] [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: 09/05/2024] [Revised: 12/23/2024] [Accepted: 01/21/2025] [Indexed: 01/27/2025] Open
Abstract
BACKGROUND Understanding gene-environment interactions associated with vitamin D status may refine nutrition and public health strategies for vitamin D deficiency. Recent methodological advances have enabled the identification of variance quantitative trait loci (vQTLs) where gene-environment interactions are enriched. OBJECTIVES The study aims to identify vQTLs for serum 25-hydroxy vitamin D (25OHD) concentrations and characterize potential gene-environment interactions of vQTLs. METHODS We conducted vQTL discovery for 25OHD using a newly developed quantile integral linear model in the UK Biobank individuals of European (N = 313,514), African (N = 7800), East Asian (N = 2146), and South Asian (N = 8771) ancestries, respectively. We tested for interactions between the identified vQTL lead variants and 18 environmental, biological, or lifestyle factors, followed by multiple sensitivity analyses. RESULTS We identified 19 independent vQTL lead variants (P < 5 × 10-8) in the European ancestry population. No vQTLs were identified in the non-European ancestry populations, likely because of limited sample sizes. A total of 32 interactions were detected with a false discovery rate <0.05. Although known gene-season of measurement interactions were confirmed, additional interactions were identified involving modifiable risk factors, including time spent outdoors and body mass index. The magnitudes of these interactions were consistent within each locus upon adjusting for the season of measurement and other covariates. We also identified a gene-sex interaction at a vQTL that implicates DHCR7. Integrating transcript- and protein-level evidence, we found that the sex-differentiated genetic associations may act through sex-biased expression of DHCR7 isoforms in skin tissues because of alternative splicing. CONCLUSIONS Through the lens of vQTLs, we identified additional gene-environment interactions affecting vitamin D status in addition to the season of measurement. These findings may provide new insights into the etiology of vitamin D deficiency and encourage personalized prevention and management of associated diseases for at-risk individuals.
Collapse
Affiliation(s)
- Tianyuan Lu
- Department of Population Health Sciences, University of Wisconsin-Madison, Madison, WI, United States; Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, United States; Department of Statistical Sciences, University of Toronto, Toronto, ON, Canada.
| | | | - Cassianne Robinson-Cohen
- Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Corinne D Engelman
- Department of Population Health Sciences, University of Wisconsin-Madison, Madison, WI, United States
| | - Qiongshi Lu
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, United States; Department of Statistics, University of Wisconsin-Madison, Madison, WI, United States; Center for Demography of Health and Aging, University of Wisconsin-Madison, Madison, WI, United States
| | - Ian H de Boer
- Division of Nephrology, Department of Medicine, University of Washington, Seattle, WA, United States; Kidney Research Institute, University of Washington, Seattle, WA, United States
| | - Lei Sun
- Department of Statistical Sciences, University of Toronto, Toronto, ON, Canada; Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Andrew D Paterson
- Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada; Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada; Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada
| |
Collapse
|
122
|
Marques IF, Domènech-Panicello C, Geurtsen ML, Hoang TT, Richmond R, Polinski K, Sirignano L, Page CM, Binter AC, Everson T, Burt A, Deuschle M, Gilles M, Streit F, Mumford SL, Magnus P, Reiss IKM, Vermeulen MJ, Witt SH, Chaves I, Yeung E, London SJ, Guxens M, Felix JF. Associations of maternal night shift work during pregnancy with DNA methylation in offspring: a meta-analysis in the PACE consortium. Clin Epigenetics 2025; 17:12. [PMID: 39844285 PMCID: PMC11756212 DOI: 10.1186/s13148-024-01810-y] [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: 09/19/2024] [Accepted: 12/27/2024] [Indexed: 01/24/2025] Open
Abstract
BACKGROUND Night shift work during pregnancy has been associated with differential DNA methylation in placental tissue, but no studies have explored this association in cord blood. We aimed to examine associations of maternal night shift work with cord blood DNA methylation. METHODS A total of 4487 mother-newborn pairs from 7 studies were included. Maternal night shift work during pregnancy was ascertained via questionnaires and harmonized into "any" versus "no". DNA methylation was measured in cord blood using the Illumina Infinium Methylation arrays. Robust linear regression models adjusted for relevant confounders were run in the individual cohorts, and results were meta-analyzed. RESULTS Maternal night shift work during pregnancy ranged from 3.4% to 26.3%. Three CpGs were differentially methylated in relation to maternal night shift work during pregnancy at a false discovery rate adjusted P < 0.05: cg10945885 (estimate (β) 0.38%, standard error (SE) 0.07), cg00773359 (β 0.25%, SE 0.05), and cg21836426 (β - 0.29%, SE 0.05). Associations of the identified CpGs were found in previous literature for gestational age and childhood and adolescent BMI. In a mouse model of prenatal jet lag exposure, information on offspring DNA methylation of ten homologous genes annotated to the 16 CpGs with P < 1 × 10-5 in our analysis was available, of which eight were associated (enrichment P: 1.62 × 10-11). CONCLUSION Maternal night shift work during pregnancy was associated with newborn DNA methylation at 3 CpGs. Top findings overlapped with those in a mouse model of gestational jet lag. This work strengthens evidence that DNA methylation could be a marker or mediator of impacts of circadian rhythm disturbances.
Collapse
Affiliation(s)
- Irene F Marques
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Carola Domènech-Panicello
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
| | - Madelon L Geurtsen
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Thanh T Hoang
- Division of Intramural Research, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
- Department of Pediatrics, Division of Hematology-Oncology, Baylor College of Medicine, Houston, TX, USA
- Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, USA
- Cancer and Hematology Center, Texas Children's Hospital, Houston, TX, USA
| | - Rebecca Richmond
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Oxford Health Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Kristen Polinski
- Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD, USA
| | - Lea Sirignano
- Department of Genetic Epidemiology in Psychiatry, Medical Faculty Mannheim, Central Institute of Mental Health, Heidelberg University, Mannheim, Germany
| | - Christian M Page
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Physical Health and Aging, Division for Physical and Mental Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Anne-Claire Binter
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
| | - Todd Everson
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Amber Burt
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Michael Deuschle
- Department of Psychiatry and Psychotherapy, Medical Faculty Mannheim, Central Institute of Mental Health, Heidelberg University, Mannheim, Germany
| | - Maria Gilles
- Department of Psychiatry and Psychotherapy, Medical Faculty Mannheim, Central Institute of Mental Health, Heidelberg University, Mannheim, Germany
| | - Fabian Streit
- Department of Genetic Epidemiology in Psychiatry, Medical Faculty Mannheim, Central Institute of Mental Health, Heidelberg University, Mannheim, Germany
- Department of Psychiatry and Psychotherapy, Medical Faculty Mannheim, Central Institute of Mental Health, Heidelberg University, Mannheim, Germany
- Medical Faculty Mannheim, Hector Institute for Artificial Intelligence in Psychiatry, Central Institute of Mental Health, Heidelberg University, Mannheim, Germany
| | - Sunni L Mumford
- Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD, USA
- Department of Biostatistics, Epidemiology and Informatics and Department of Obstetrics and Gynecology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Per Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Irwin K M Reiss
- Department of Neonatal and Pediatric Intensive Care, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Marijn J Vermeulen
- Department of Neonatal and Pediatric Intensive Care, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Stephanie H Witt
- Department of Genetic Epidemiology in Psychiatry, Medical Faculty Mannheim, Central Institute of Mental Health, Heidelberg University, Mannheim, Germany
| | - Inês Chaves
- Department of Molecular Genetics, Erasmus MC Cancer Institute, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Edwina Yeung
- Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD, USA
| | - Stephanie J London
- Division of Intramural Research, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Mònica Guxens
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- ICREA, Barcelona, Spain
| | - Janine F Felix
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.
| |
Collapse
|
123
|
Fragoso-Bargas N, Mcbride NS, Lee-Ødegård S, Lawlor DA, Yousefi PD, Moen GH, Opsahl JO, Jenum AK, Franks PW, Prasad RB, Qvigstad E, Birkeland KI, Richardsen KR, Sommer C. Epigenome-wide association study of objectively measured physical activity in peripheral blood leukocytes. BMC Genomics 2025; 26:62. [PMID: 39844050 PMCID: PMC11755845 DOI: 10.1186/s12864-025-11262-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2024] [Accepted: 01/17/2025] [Indexed: 01/24/2025] Open
Abstract
BACKGROUND Few studies have explored the association between DNA methylation and physical activity. The aim of this study was to evaluate the association of objectively measured hours of sedentary behavior (SB) and moderate physical activity (MPA) with DNA methylation. We further aimed to explore the association between SB or MPA related CpG sites and cardiometabolic traits, gene expression, and genetic variation. RESULTS For discovery, we performed cross sectional analyses in pregnant women from the Epigenetics in pregnancy (EPIPREG) sample with both DNA methylation (Illumina MethylationEPIC BeadChip) and objectively measured physical activity data (SenseWear™ Pro 3 armband) (European = 244, South Asian = 109). For EWAS of SB and MPA, two main models were designed: model (1) a linear mixed model adjusted for age, smoking, blood cell composition, including ancestry as random intercept, and model (2) which was additionally adjusted for the total number of steps per day. In model 1, we did not identify any CpG sites associated with neither SB nor MPA. In model 2, SB was positively associated (false discovery rate, FDR < 0.05) with two CpG sites within the VSX1 gene. Both CpG sites were positively associated with BMI and were associated with several genetic variants in cis. MPA was associated with 122 significant CpG sites at FDR < 0.05 (model 2). We further analyzed the ten most statistically significant MPA related CpG sites and found that they presented opposite associations with sedentary behavior and BMI. We were not able to replicate the SB and MPA-related CpG sites in the Avon Longitudinal Study of Parents and Children (ALSPAC). ALSPAC had available objectively measured physical activity data from Actigraph (without steps/day available) and leucocyte DNA methylation data collected during adolescence (n = 408, European). CONCLUSION This study suggests associations of objectively measured SB and MPA with maternal DNA methylation in peripheral blood leukocytes, that needs to be confirmed in larger samples of similar study design.
Collapse
Affiliation(s)
- Nicolas Fragoso-Bargas
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, 5023, Norway.
- Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway.
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway.
| | - Nancy S Mcbride
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre, University of Bristol, Bristol, UK
| | - Sindre Lee-Ødegård
- Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre, University of Bristol, Bristol, UK
| | - Paul D Yousefi
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre, University of Bristol, Bristol, UK
- Institute of Molecular Biosciences, The University of Queensland, Brisbane, Australia
| | - Gunn-Helen Moen
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
- Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- The Frazer Institute, The University of Queensland, Woolloongabba, Australia
- Department of General Practice, Institute of Health and Society, Faculty of Medicine, General Practice Research Unit (AFE), University of Oslo, Oslo, Norway
| | - Julia O Opsahl
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Anne Karen Jenum
- Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Malmö, Sweden
| | - Paul W Franks
- Institute for Molecular Medicine Finland FIMM, Helsinki University, Helsinki, Finland
| | - Rashmi B Prasad
- Institute for Molecular Medicine Finland FIMM, Helsinki University, Helsinki, Finland
- Faculty of Health Sciences, Department of Rehabilitation Science and Health Technology, Oslo Metropolitan University, Oslo, Norway
| | - Elisabeth Qvigstad
- Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Kåre I Birkeland
- Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Kåre R Richardsen
- Faculty of Health Sciences, Department of Rehabilitation Science and Health Technology, Oslo Metropolitan University, Oslo, Norway
| | - Christine Sommer
- Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway
| |
Collapse
|
124
|
Willett JDS, Mullin K, Tanzi RE, Prokopenko D. Matching Heterogeneous Cohorts by Projected Principal Components Reveals Two Novel Alzheimer's Disease-Associated Genes in the Hispanic Population. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2025:2025.01.18.25320774. [PMID: 39867396 PMCID: PMC11759617 DOI: 10.1101/2025.01.18.25320774] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/28/2025]
Abstract
Alzheimer's disease (AD) is the most common form of dementia in elderly, affecting 6.9 million individuals in the United States. Some studies have suggested the prevalence of AD is greater in individuals who self-identify as Hispanic. Focused results are relevant for personalized and equitable clinical interventions. Ethnicity as a stratifying tool in genetic studies is often accompanied by genomic inflation due to heterogeneity. In this study, we report GWAS and meta-analyses conducted among NIAGADS subjects who self-identified as Hispanic and All of Us (AoU) sub-cohorts matched to that cohort, using projected genetically-derived principal components, with and without age and sex. In Hispanic NIAGADS subjects, we identified a common variant in PIEZO2 that was protective for AD with a p-value just beyond genome-wide significance (p = 5.4 * 10-8). Meta-analyses with genetically-matched AoU participants yielded three (two novel) genome-wide significant AD-associated loci based on rare lead variants: rs374043832 (RGS6/PSEN1), rs192423465 (ASPSCR1), and rs935208076 (GDAP2), which were also nominally significant in AoU sub-cohorts. We also show how genomic inflation can be mitigated in heterogeneous populations while increasing sample size and result generalizability.
Collapse
Affiliation(s)
- Julian Daniel Sunday Willett
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA
| | - Kristina Mullin
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA
| | - Rudolph E. Tanzi
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA
| | - Dmitry Prokopenko
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA
| |
Collapse
|
125
|
Dong ZY, He MJ, Yu YK, Wang F, Zhao PY, Ran DL, Fu DS, He Q, Yang RP, Zhang JA. Integrative genetics and multiomics analysis reveal mechanisms and therapeutic targets in vitiligo highlighting JAK STAT pathway regulation of CTSS. Sci Rep 2025; 15:2245. [PMID: 39824912 PMCID: PMC11742684 DOI: 10.1038/s41598-025-86134-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2024] [Accepted: 01/08/2025] [Indexed: 01/30/2025] Open
Abstract
Vitiligo is a complex autoimmune disease characterized by the loss of melanocytes, leading to skin depigmentation. Despite advances in understanding its genetic and molecular basis, the precise mechanisms driving vitiligo remain elusive. Integrating multiple layers of omics data can provide a comprehensive view of disease pathogenesis and identify potential therapeutic targets. The study aims to delineate the genetic and molecular mechanisms of vitiligo pathogenesis using an integrative multiomics strategy. We focus on exploring the regulatory influence of the JAK/STAT pathway on Cathepsin S, a potential therapeutic target in vitiligo. Our GWAS-meta analysis pinpointed five druggable genes: ERBB3, RHOH, CDK10, MC1R, and NDUFAF3, and underwent drug target exploration and molecular docking. SMR analysis linked CTSS, CTSH, STX8, KIR2DL3, and GRHPR to vitiligo through pQTL and eQTL associations. Microarray and single-cell RNA-seq data showed differential expression of CTSS and STAT1/3 in vitiligo patients' blood and skin lesions. Our study offers novel perspectives on vitiligo's genetic and molecular basis, highlighting the JAK/STAT pathway's role in regulating CTSS for antigen processing in melanocytes. Further research is needed to confirm these results and assess the therapeutic potential of CTSS and related genes.
Collapse
Affiliation(s)
- Zi-Yue Dong
- Department of Dermatology, Zhengzhou People's Hospital, Zhengzhou, Henan, China
- Department of Dermatology, First Affiliated Hospital of Zhengzhou University, No.1 Longhu Outer Ring Road, Jinshui District, Zhengzhou, 450052, Henan, China
| | - Ming-Jie He
- Department of Dermatology, First Affiliated Hospital of Zhengzhou University, No.1 Longhu Outer Ring Road, Jinshui District, Zhengzhou, 450052, Henan, China
| | - Yong-Kai Yu
- Department of Dermatology, Jiangsu Province Hospital and Nanjing Medical University First Affiliated Hospital, Nanjing, Jiangsu, China
| | - Fang Wang
- Department of Dermatology, First Affiliated Hospital of Zhengzhou University, No.1 Longhu Outer Ring Road, Jinshui District, Zhengzhou, 450052, Henan, China
| | - Peng-Yuan Zhao
- Department of Dermatology, First Affiliated Hospital of Zhengzhou University, No.1 Longhu Outer Ring Road, Jinshui District, Zhengzhou, 450052, Henan, China
| | - De-Long Ran
- Department of Dermatology, First Affiliated Hospital of Zhengzhou University, No.1 Longhu Outer Ring Road, Jinshui District, Zhengzhou, 450052, Henan, China
| | - De-Shuang Fu
- Department of Dermatology, First Affiliated Hospital of Zhengzhou University, No.1 Longhu Outer Ring Road, Jinshui District, Zhengzhou, 450052, Henan, China
| | - Qing He
- Department of Dermatology, First Affiliated Hospital of Zhengzhou University, No.1 Longhu Outer Ring Road, Jinshui District, Zhengzhou, 450052, Henan, China
| | - Run-Ping Yang
- Department of Dermatology, The Sixth Medical Center of Chinese, PLA General Hospital, 6 Fucheng Road, Haidian District, Beijing, 100048, China.
| | - Jiang-An Zhang
- Department of Dermatology, First Affiliated Hospital of Zhengzhou University, No.1 Longhu Outer Ring Road, Jinshui District, Zhengzhou, 450052, Henan, China.
| |
Collapse
|
126
|
Gálvez‐Montosa F, Peduzzi G, Sanchez‐Maldonado JM, ter Horst R, Cabrera‐Serrano AJ, Gentiluomo M, Macauda A, Luque N, Ünal P, García‐Verdejo FJ, Li Y, López López JA, Stein A, Bueno‐de‐Mesquita HB, Arcidiacono PG, Zanette DL, Kahlert C, Perri F, Soucek P, Talar‐Wojnarowska R, Theodoropoulos GE, Izbicki JR, Tamás H, Van Laarhoven H, Nappo G, Petrone MC, Lovecek M, Vermeulen RCH, Adamonis K, Reyes‐Zurita FJ, Holleczek B, Sumskiene J, Mohelníková‐Duchoňová B, Lawlor RT, Pezzilli R, Aoki MN, Pasquali C, Petrenkiene V, Basso D, Bunduc S, Comandatore A, Brenner H, Ermini S, Vanella G, Goetz MR, Archibugi L, Lucchesi M, Uzunoglu FG, Busch O, Milanetto AC, Puzzono M, Kupcinskas J, Morelli L, Sperti C, Carrara S, Capurso G, van Eijck CHJ, Oliverius M, Roth S, Tavano F, Kaaks R, Szentesi A, Vodickova L, Luchini C, Schöttker B, Landi S, Dohan O, Tacelli M, Greenhalf W, Gazouli M, Neoptolemos JP, Cavestro GM, Boggi U, Latiano A, Hegyi P, Ginocchi L, Netea MG, Sánchez‐Rovira P, Canzian F, Campa D, Sainz J. Polymorphisms within autophagy-related genes as susceptibility biomarkers for pancreatic cancer: A meta-analysis of three large European cohorts and functional characterization. Int J Cancer 2025; 156:339-352. [PMID: 39319538 PMCID: PMC11578083 DOI: 10.1002/ijc.35196] [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: 04/04/2024] [Revised: 07/17/2024] [Accepted: 08/26/2024] [Indexed: 09/26/2024]
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers with patients having unresectable or metastatic disease at diagnosis, with poor prognosis and very short survival. Given that genetic variation within autophagy-related genes influences autophagic flux and susceptibility to solid cancers, we decided to investigate whether 55,583 single nucleotide polymorphisms (SNPs) within 234 autophagy-related genes could influence the risk of developing PDAC in three large independent cohorts of European ancestry including 12,754 PDAC cases and 324,926 controls. The meta-analysis of these populations identified, for the first time, the association of the BIDrs9604789 variant with an increased risk of developing the disease (ORMeta = 1.31, p = 9.67 × 10-6). We also confirmed the association of TP63rs1515496 and TP63rs35389543 variants with PDAC risk (OR = 0.89, p = 6.27 × 10-8 and OR = 1.16, p = 2.74 × 10-5). Although it is known that BID induces autophagy and TP63 promotes cell growth, cell motility and invasion, we also found that carriers of the TP63rs1515496G allele had increased numbers of FOXP3+ Helios+ T regulatory cells and CD45RA+ T regulatory cells (p = 7.67 × 10-4 and p = 1.56 × 10-3), but also decreased levels of CD4+ T regulatory cells (p = 7.86 × 10-4). These results were in agreement with research suggesting that the TP63rs1515496 variant alters binding sites for FOXA1 and CTCF, which are transcription factors involved in modulating specific subsets of regulatory T cells. In conclusion, this study identifies BID as new susceptibility locus for PDAC and confirms previous studies suggesting that the TP63 gene is involved in the development of PDAC. This study also suggests new pathogenic mechanisms of the TP63 locus in PDAC.
Collapse
Affiliation(s)
| | | | - José Manuel Sanchez‐Maldonado
- Department of Biochemistry and Molecular Biology IUniversity of GranadaGranadaSpain
- Genomic Oncology Area, GENYO, Centre for Genomics and Oncological Research: Pfizer/University of Granada/Andalusian Regional Government, PTSGranadaSpain
- Instituto de Investigación Biosanataria Ibs.GranadaGranadaSpain
- Genomic Epidemiology GroupGerman Cancer Research Center (DKFZ)HeidelbergGermany
| | - Rob ter Horst
- Department of Internal Medicine and Radboud Center for Infectious DiseasesRadboud University Medical CenterNijmegenThe Netherlands
- CeMM Research Center for Molecular Medicine of the Austrian Academy of SciencesViennaAustria
| | - Antonio J. Cabrera‐Serrano
- Genomic Oncology Area, GENYO, Centre for Genomics and Oncological Research: Pfizer/University of Granada/Andalusian Regional Government, PTSGranadaSpain
- Instituto de Investigación Biosanataria Ibs.GranadaGranadaSpain
| | | | - Angelica Macauda
- Genomic Epidemiology GroupGerman Cancer Research Center (DKFZ)HeidelbergGermany
| | - Natalia Luque
- Department of Medical OncologyComplejo Hospitalario de JaénJaénSpain
| | - Pelin Ünal
- Genomic Epidemiology GroupGerman Cancer Research Center (DKFZ)HeidelbergGermany
| | | | - Yang Li
- Department of Internal Medicine and Radboud Center for Infectious DiseasesRadboud University Medical CenterNijmegenThe Netherlands
- CeMM Research Center for Molecular Medicine of the Austrian Academy of SciencesViennaAustria
| | | | - Angelika Stein
- Genomic Epidemiology GroupGerman Cancer Research Center (DKFZ)HeidelbergGermany
| | | | - Paolo Giorgio Arcidiacono
- Pancreatico/Biliary Endoscopy & Endosonography Division, Pancreas Translational & Clinical Research CenterSan Raffaele Scientific InstituteMilanItaly
| | - Dalila Luciola Zanette
- Laboratory for Applied Science and Technology in HealthCarlos Chagas Institute, Oswaldo Cruz Foundation (Fiocruz)CuritibaBrazil
| | - Christoph Kahlert
- Department of General SurgeryUniversity of HeidelbergHeidelbergBaden‐WürttembergGermany
| | - Francesco Perri
- Division of Gastroenterology and Research LaboratoryFondazione IRCCS “Casa Sollievo della Sofferenza” HospitalFoggiaItaly
| | - Pavel Soucek
- Biomedical Center, Faculty of Medicine in PilsenCharles UniversityPilsenCzech Republic
| | | | - George E. Theodoropoulos
- Colorectal Unit, First Department of Propaedeutic SurgeryMedical School of National and Kapodistrian University of Athens, Hippocration General HospitalAthensGreece
| | - Jakob R. Izbicki
- Department of General, Visceral and Thoracic SurgeryUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Hussein Tamás
- Center for Translational MedicineSemmelweis UniversityBudapestHungary
- Division of Pancreatic Diseases, Heart and Vascular CenterSemmelweis UniversityBudapestHungary
| | - Hanneke Van Laarhoven
- Department of Medical OncologyAmsterdam UMC location University of AmsterdamAmsterdamThe Netherlands
- Cancer Center AmsterdamImaging and BiomarkersAmsterdamThe Netherlands
| | - Gennaro Nappo
- Pancreatic UnitIRCCS Humanitas Research HospitalMilanItaly
- Department of Biomedical SciencesHumanitas UniversityMilanItaly
| | - Maria Chiara Petrone
- Pancreatico/Biliary Endoscopy & Endosonography Division, Pancreas Translational & Clinical Research CenterSan Raffaele Scientific InstituteMilanItaly
| | - Martin Lovecek
- Department of Surgery IUniversity Hospital OlomoucOlomoucCzech Republic
| | | | - Kestutis Adamonis
- Gastroenterology Department and Institute for Digestive ResearchLithuanian University of Health SciencesKaunasLithuania
| | | | - Bernd Holleczek
- Saarland Cancer RegistrySaarbrückenGermany
- Division of Clinical Epidemiology and Aging ResearchGerman Cancer Research Center (DKFZ)HeidelbergGermany
| | - Jolanta Sumskiene
- Gastroenterology Department and Institute for Digestive ResearchLithuanian University of Health SciencesKaunasLithuania
| | | | - Rita T. Lawlor
- ARC‐Net Centre for Applied Research on Cancer University of VeronaVeronaItaly
- Department of Diagnostics and Public Health, Section of PathologyUniversity of VeronaVeronaItaly
| | | | - Mateus Nobrega Aoki
- Laboratory for Applied Science and Technology in HealthCarlos Chagas Institute, Oswaldo Cruz Foundation (Fiocruz)CuritibaBrazil
| | | | - Vitalija Petrenkiene
- Gastroenterology Department and Institute for Digestive ResearchLithuanian University of Health SciencesKaunasLithuania
| | - Daniela Basso
- Department of DIMEDLaboratory Medicine, University of PadovaPadovaItaly
| | - Stefania Bunduc
- Center for Translational MedicineSemmelweis UniversityBudapestHungary
- Division of Pancreatic Diseases, Heart and Vascular CenterSemmelweis UniversityBudapestHungary
- Carol Davila University of Medicine and PharmacyBucharestRomania
- Digestive Diseases and Liver Transplantation CenterFundeni Clinical InstituteBucharestRomania
| | - Annalisa Comandatore
- General Surgery Unit, Department of Translational Research and New Technologies in MedicineUniversity of PisaPisaItaly
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging ResearchGerman Cancer Research Center (DKFZ)HeidelbergGermany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ)HeidelbergGermany
| | | | - Giuseppe Vanella
- Digestive and Liver Disease UnitS Andrea HospitalRomeItaly
- Pancreas Translational and Clinical Research CenterPancreato‐Biliary Endoscopy and Endoscopic Ultrasound, San Raffaele Scientific Institute IRCCSMilanItaly
| | - Mara R. Goetz
- Department of General, Visceral and Thoracic SurgeryUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Livia Archibugi
- Digestive and Liver Disease UnitS Andrea HospitalRomeItaly
- Pancreas Translational and Clinical Research CenterPancreato‐Biliary Endoscopy and Endoscopic Ultrasound, San Raffaele Scientific Institute IRCCSMilanItaly
| | | | - Faik Guntac Uzunoglu
- Department of General, Visceral and Thoracic SurgeryUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Olivier Busch
- Cancer Center AmsterdamImaging and BiomarkersAmsterdamThe Netherlands
- Department of Medical OncologyAmsterdam UMC Location University of AmsterdamAmsterdamThe Netherlands
| | | | - Marta Puzzono
- Gastroenterology and Gastrointestinal Endoscopy UnitVita‐Salute San Raffaele University, IRCCS San Raffaele Scientific InstituteMilanItaly
| | - Juozas Kupcinskas
- Gastroenterology Department and Institute for Digestive ResearchLithuanian University of Health SciencesKaunasLithuania
| | - Luca Morelli
- General Surgery Unit, Department of Translational Research and New Technologies in MedicineUniversity of PisaPisaItaly
| | | | - Silvia Carrara
- Department of GastroenterologyIRCCS Humanitas Research Hospital – Endoscopic UnitMilanItaly
| | - Gabriele Capurso
- Digestive and Liver Disease UnitS Andrea HospitalRomeItaly
- Pancreas Translational and Clinical Research CenterPancreato‐Biliary Endoscopy and Endoscopic Ultrasound, San Raffaele Scientific Institute IRCCSMilanItaly
| | | | - Martin Oliverius
- Department of Surgery, University Hospital Kralovske Vinohrady, Third Faculty of MedicineCharles UniversityPragueCzech Republic
| | - Susanne Roth
- Department of General SurgeryUniversity of HeidelbergHeidelbergBaden‐WürttembergGermany
| | - Francesca Tavano
- Division of Gastroenterology and Research LaboratoryFondazione IRCCS “Casa Sollievo della Sofferenza” HospitalFoggiaItaly
| | - Rudolf Kaaks
- Division of Cancer EpidemiologyGerman Cancer Research Center (DKFZ)HeidelbergGermany
| | - Andrea Szentesi
- Institute for Translational Medicine, Medical SchoolUniversity of PécsPécsHungary
| | - Ludmila Vodickova
- Department of Molecular Biology of Cancer, Institute of Experimental MedicineCzech Academy of SciencesPragueCzech Republic
- Institute of Biology and Medical Genetics, First Faculty of MedicineCharles UniversityPragueCzech Republic
- Faculty of Medicine and Biomedical Center in PilsenCharles UniversityPilsenCzech Republic
| | - Claudio Luchini
- ARC‐Net Centre for Applied Research on Cancer University of VeronaVeronaItaly
- Department of Engineering for Innovation in MedicineUniversity of VeronaVeronaItaly
| | - Ben Schöttker
- Division of Clinical Epidemiology and Aging ResearchGerman Cancer Research Center (DKFZ)HeidelbergGermany
| | | | - Orsolya Dohan
- Division of Pancreatic Diseases, Heart and Vascular CenterSemmelweis UniversityBudapestHungary
| | - Matteo Tacelli
- Pancreatico/Biliary Endoscopy & Endosonography Division, Pancreas Translational & Clinical Research CenterSan Raffaele Scientific InstituteMilanItaly
| | - William Greenhalf
- Institute for Health Research Liverpool Pancreas Biomedical Research UnitUniversity of LiverpoolLiverpoolUK
| | - Maria Gazouli
- Department of Basic Medical Science, Laboratory of Biology, Medical SchoolNational and Kapodistrian University of AthensAthensGreece
| | - John P. Neoptolemos
- Department of General SurgeryUniversity of HeidelbergHeidelbergBaden‐WürttembergGermany
| | - Giulia Martina Cavestro
- Gastroenterology and Gastrointestinal Endoscopy UnitVita‐Salute San Raffaele University, IRCCS San Raffaele Scientific InstituteMilanItaly
| | - Ugo Boggi
- Division of General and Transplant SurgeryPisa University HospitalPisaItaly
| | - Anna Latiano
- Division of Gastroenterology and Research LaboratoryFondazione IRCCS “Casa Sollievo della Sofferenza” HospitalFoggiaItaly
| | - Péter Hegyi
- Center for Translational MedicineSemmelweis UniversityBudapestHungary
- Division of Pancreatic Diseases, Heart and Vascular CenterSemmelweis UniversityBudapestHungary
- Institute for Translational Medicine, Medical SchoolUniversity of PécsPécsHungary
- János Szentágothai Research CenterUniversity of PécsPécsHungary
| | - Laura Ginocchi
- Oncologia Massa CarraraAzienda USL Toscana Nord OvestCarraraItaly
| | - Mihai G. Netea
- Centre for Individualised Infection Medicine (CiiM) & TWINCOREjoint Ventures Between the Helmholtz‐Centre for Infection Research (HZI) and the Hannover Medical School (MHH)HannoverGermany
- Department for Immunology & Metabolism, Life and Medical Sciences Institute (LIMES)University of BonnBonnGermany
| | | | - Federico Canzian
- Genomic Epidemiology GroupGerman Cancer Research Center (DKFZ)HeidelbergGermany
| | | | - Juan Sainz
- Department of Biochemistry and Molecular Biology IUniversity of GranadaGranadaSpain
- Genomic Oncology Area, GENYO, Centre for Genomics and Oncological Research: Pfizer/University of Granada/Andalusian Regional Government, PTSGranadaSpain
- Instituto de Investigación Biosanataria Ibs.GranadaGranadaSpain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP)BarcelonaSpain
| |
Collapse
|
127
|
Langie J, Chan TF, Yang W, Kang AY, Morimoto L, Stram DO, Mancuso N, Ma X, Metayer C, Lupo PJ, Rabin KR, Scheurer ME, Wiemels JL, Yang JJ, de Smith AJ, Chiang CWK. The impact of Indigenous American-like ancestry on risk of acute lymphoblastic leukemia in Hispanic/Latino children. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2025:2025.01.14.25320563. [PMID: 39867407 PMCID: PMC11759616 DOI: 10.1101/2025.01.14.25320563] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 01/28/2025]
Abstract
Acute lymphoblastic leukemia (ALL) is the most common childhood cancer, with Hispanic/Latino children having a higher incidence of ALL than other racial/ethnic groups. Genetic variants, particularly ones found enriched in Indigenous American (IA)-like ancestry and inherited by Hispanics/Latinos, may contribute to this disparity. In this study, we characterized the impact of IA-like ancestry on overall ALL risk and the frequency and effect size of known risk alleles in a large cohort of self-reported Hispanic/Latino individuals. We also performed genome-wide admixture mapping analysis to identify potentially novel ALL risk loci. We found that global IA ancestry was positively associated with ALL risk, but the association was not significant after adjusting for socio-economic indicators. In a series of local ancestry analyses, we uncovered that at known ALL risk loci, increasing copies of the IA-like haplotype were positively and significantly associated with ALL case-control status. Further, the IA-like haplotype had ~1.33 times the odds of harboring the risk allele compared to non-IA-like haplotypes. We found no evidence of interaction between genotype and ancestry (local or global) in relation to ALL risk. Admixture mapping identified association signals on chromosomes 2 (2q21.2), 7 (7p12.2), 10 (10q21.2), and 15 (15q22.31); however, only the variants at 7p12.2 and 10q21.2 replicated in additional cohorts. Taken together, our results suggest that increased risk of ALL in Hispanic/Latino children may be conferred by higher frequency of risk alleles within IA-like ancestry, which can be leveraged as targets of new precision health strategies and therapeutics.
Collapse
Affiliation(s)
- Jalen Langie
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California Keck School of Medicine, Los Angeles, CA, USA
- USC Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA
| | - Tsz Fung Chan
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California Keck School of Medicine, Los Angeles, CA, USA
- USC Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA
| | - Wenjian Yang
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Alice Y Kang
- School of Public Health, University of California Berkeley, Berkeley, CA, USA
| | - Libby Morimoto
- School of Public Health, University of California Berkeley, Berkeley, CA, USA
| | - Daniel O Stram
- Department of Population and Public Health Sciences, University of Southern California Keck School of Medicine, Los Angeles, CA, USA
| | - Nicholas Mancuso
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California Keck School of Medicine, Los Angeles, CA, USA
- USC Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA
| | - Xiaomei Ma
- Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, CT, USA
| | - Catherine Metayer
- School of Public Health, University of California Berkeley, Berkeley, CA, USA
| | - Philip J Lupo
- Division of Hematology-Oncology, Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
- Texas Children's Cancer and Hematology Centers, Texas Children's Hospital, Houston, TX, USA
| | - Karen R Rabin
- Division of Hematology-Oncology, Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
- Texas Children's Cancer and Hematology Centers, Texas Children's Hospital, Houston, TX, USA
| | - Michael E Scheurer
- Division of Hematology-Oncology, Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
- Texas Children's Cancer and Hematology Centers, Texas Children's Hospital, Houston, TX, USA
| | - Joseph L Wiemels
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California Keck School of Medicine, Los Angeles, CA, USA
- USC Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA
| | - Jun J Yang
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Adam J de Smith
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California Keck School of Medicine, Los Angeles, CA, USA
- USC Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA
- Co-senior authors
| | - Charleston W K Chiang
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California Keck School of Medicine, Los Angeles, CA, USA
- USC Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
- Co-senior authors
| |
Collapse
|
128
|
Kim H, Do H, Son CN, Jang JW, Choi SS, Moon KW. Effects of Genetic Risk and Lifestyle Habits on Gout: A Korean Cohort Study. J Korean Med Sci 2025; 40:e1. [PMID: 39807002 PMCID: PMC11729237 DOI: 10.3346/jkms.2025.40.e1] [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: 07/09/2024] [Accepted: 09/19/2024] [Indexed: 01/16/2025] Open
Abstract
BACKGROUND Gout is a type of inflammatory arthritis caused by monosodium urate crystal deposits, and the prevalence of this condition has been increasing. This study aimed to determine the combined effects of genetic risk factors and lifestyle habits on gout, using data from a Korean cohort study. Identifying high-risk individuals in advance can help prevent gout and its associated disorders. METHODS We analyzed data from the Korean Genome and Epidemiology Study-Urban Health Examinees cohort (KoGES-HEXA). Genetic information of the participants was collected at baseline, and gout cases were identified based on patient statements. The polygenic risk score (PRS) was calculated using nine independent genome-wide association study datasets, and lifestyle factors and metabolic syndrome status were measured for each participant using the KoGES. Logistic regression models were used to estimate the odds ratios (ORs) for gout in relation to genetic risk, lifestyle habits, and metabolic health status, after adjusting for age and sex. RESULTS Among 44,605 participants, 617 were diagnosed with gout. Gout was associated with older age, higher body mass index, and higher prevalence of hypertension, diabetes, and hypertriglyceridemia. High PRS, unfavorable lifestyle habits, and poor metabolic profiles were significantly associated with an increased risk of gout. Compared with that in the low-genetic-risk and healthy lifestyle group or ideal metabolic profile group, the risk of gout was increased in the high-genetic-risk plus unfavorable lifestyle (OR, 3.64; 95% confidence interval [CI], 2.32-6.03) or poor metabolic profile (OR, 7.78; 95% CI, 4.61-13.40) group. Conversely, adherence to favorable lifestyle habits significantly reduced gout risk, especially in high-genetic-risk groups. CONCLUSION Genetic predisposition and unhealthy lifestyle habits significantly increase the risk of gout. Promoting healthy lifestyle habits is crucial to prevent the development of gout, particularly in individuals with high genetic susceptibility.
Collapse
Affiliation(s)
- Hyunjung Kim
- Division of Biomedical Convergence, College of Biomedical Science, Institute of Bioscience & Biotechnology, Kangwon National University, Chuncheon, Korea
| | - Hyunsue Do
- Division of Rheumatology, Department of Internal Medicine, Kangwon National University School of Medicine, Chuncheon, Korea
| | - Chang-Nam Son
- Eulji Rheumatology Research Institute, Eulji University School of Medicine, Uijeongbu, Korea
| | - Jae-Won Jang
- Department of Neurology, Kangwon National University School of Medicine, Chuncheon, Korea
- Department of Medical Bigdata Convergence, Kangwon National University, Chuncheon, Korea
| | - Sun Shim Choi
- Division of Biomedical Convergence, College of Biomedical Science, Institute of Bioscience & Biotechnology, Kangwon National University, Chuncheon, Korea.
| | - Ki Won Moon
- Division of Rheumatology, Department of Internal Medicine, Kangwon National University School of Medicine, Chuncheon, Korea
- Department of Medical Bigdata Convergence, Kangwon National University, Chuncheon, Korea.
| |
Collapse
|
129
|
Konieczny MJ, Omarov M, Zhang L, Malik R, Richardson TG, Baumeister SE, Bernhagen J, Dichgans M, Georgakis MK. The genomic architecture of circulating cytokine levels points to drug targets for immune-related diseases. Commun Biol 2025; 8:34. [PMID: 39794498 PMCID: PMC11724035 DOI: 10.1038/s42003-025-07453-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: 06/04/2024] [Accepted: 01/02/2025] [Indexed: 01/13/2025] Open
Abstract
Circulating cytokines orchestrate immune reactions and are promising drug targets for immune-mediated and inflammatory diseases. Exploring the genetic architecture of circulating cytokine levels could yield key insights into causal mediators of human disease. Here, we performed genome-wide association studies (GWAS) for 40 circulating cytokines in meta-analyses of 74,783 individuals. We detected 359 significant associations between cytokine levels and variants in 169 independent loci, including 150 trans- and 19 cis-acting loci. Integration with transcriptomic data point to key regulatory mechanisms, such as the buffering function of the Atypical Chemokine Receptor 1 (ACKR1) acting as scavenger for multiple chemokines and the role of tumor necrosis factor receptor-associated factor 1 (TRAFD1) in modulating the cytokine storm triggered by TNF signaling. Applying Mendelian randomization (MR), we detected a network of complex cytokine interconnections with TNF-b, VEGF, and IL-1ra exhibiting pleiotropic downstream effects on multiple cytokines. Drug target cis-MR using 2 independent proteomics datasets paired with colocalization revealed G-CSF/CSF-3 and CXCL9/MIG as potential causal mediators of asthma and Crohn's disease, respectively, but also a potentially protective role of TNF-b in multiple sclerosis. Our results provide an overview of the genetic architecture of circulating cytokines and could guide the development of targeted immunotherapies.
Collapse
Affiliation(s)
- Marek J Konieczny
- Institute for Stroke and Dementia Research (ISD), LMU University Hospital, LMU Munich, Munich, Germany
| | - Murad Omarov
- Institute for Stroke and Dementia Research (ISD), LMU University Hospital, LMU Munich, Munich, Germany
| | - Lanyue Zhang
- Institute for Stroke and Dementia Research (ISD), LMU University Hospital, LMU Munich, Munich, Germany
| | - Rainer Malik
- Institute for Stroke and Dementia Research (ISD), LMU University Hospital, LMU Munich, Munich, Germany
| | - Tom G Richardson
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | | | - Jürgen Bernhagen
- Institute for Stroke and Dementia Research (ISD), LMU University Hospital, LMU Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
- German Centre for Cardiovascular Research (DZHKMunich), Munich, Germany
| | - Martin Dichgans
- Institute for Stroke and Dementia Research (ISD), LMU University Hospital, LMU Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
- German Centre for Cardiovascular Research (DZHKMunich), Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Marios K Georgakis
- Institute for Stroke and Dementia Research (ISD), LMU University Hospital, LMU Munich, Munich, Germany.
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| |
Collapse
|
130
|
Euesden J, Ali M, Robins C, Surendran P, Gormley P, Pulford D, Cruchaga C. Patient stratification by genetic risk in Alzheimer's disease is only effective in the presence of phenotypic heterogeneity. PLoS One 2025; 20:e0310977. [PMID: 39787209 PMCID: PMC11717250 DOI: 10.1371/journal.pone.0310977] [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: 01/03/2024] [Accepted: 09/10/2024] [Indexed: 01/12/2025] Open
Abstract
Case-only designs in longitudinal cohorts are a valuable resource for identifying disease-relevant genes, pathways, and novel targets influencing disease progression. This is particularly relevant in Alzheimer's disease (AD), where longitudinal cohorts measure disease "progression," defined by rate of cognitive decline. Few of the identified drug targets for AD have been clinically tractable, and phenotypic heterogeneity is an obstacle to both clinical research and basic science. In four cohorts (n = 7241), we performed genome-wide association studies (GWAS) and Mendelian randomization (MR) to discover novel targets associated with progression and assess causal relationships. We tested opportunities for patient stratification by deriving polygenic risk scores (PRS) for AD risk and severity and tested the value of these scores in predicting progression. Genome-wide association studies identified no loci associated with progression at genome-wide significance (α = 5×10-8); MR analyses provided no significant evidence of an association between cognitive decline in AD patients and protein levels in brain, cerebrospinal fluid (CSF), and plasma. Polygenic risk scores for AD risk did not reliably stratify fast from slow progressors; however, a deeper investigation found that APOE ε4 status predicts amyloid-β and tau positive versus negative patients (odds ratio for an additional APOE ε4 allele = 5.78 [95% confidence interval: 3.76-8.89], P<0.001) when restricting to a subset of patients with available CSF biomarker data. These results provided no evidence for large-effect, common-variant loci involved in the rate of memory decline, suggesting that patient stratification based on common genetic risk factors for progression may have limited utility. Where clinically relevant biomarkers suggest diagnostic heterogeneity, there is evidence that a priori identified genetic risk factors may have value in patient stratification. Mendelian randomization was less tractable due to the lack of large-effect loci, and future analyses with increased samples sizes are needed to replicate and validate our results.
Collapse
Affiliation(s)
- Jack Euesden
- Biostatistics, GSK Pharma R&D, Stevenage, Hertfordshire, United Kingdom
| | - Muhammad Ali
- Washington University School of Medicine, NeuroGenomics and Informatics Center, St. Louis, MO, United States of America
| | - Chloe Robins
- Genomic Sciences, GSK Pharma R&D, Collegeville, PA, United States of America
| | - Praveen Surendran
- Genomic Sciences, GSK Pharma R&D, Stevenage, Hertfordshire, United Kingdom
| | - Padhraig Gormley
- Genomic Sciences, GSK Pharma R&D, Cambridge, MA, United States of America
| | | | - David Pulford
- Genomic Sciences, GSK Pharma R&D, Stevenage, Hertfordshire, United Kingdom
| | - Carlos Cruchaga
- Washington University School of Medicine, NeuroGenomics and Informatics Center, St. Louis, MO, United States of America
| |
Collapse
|
131
|
Mack JA, Burkholder A, Akhtari FS, House JS, Sovio U, Smith GCS, Schmitt CP, Fargo DC, Hall JE, Motsinger-Reif AA. A multi-ancestry genome-wide association study identifies novel candidate loci in the RARB gene associated with hypertensive disorders of pregnancy. HGG ADVANCES 2025; 6:100385. [PMID: 39580622 PMCID: PMC11667702 DOI: 10.1016/j.xhgg.2024.100385] [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: 05/30/2024] [Revised: 11/19/2024] [Accepted: 11/19/2024] [Indexed: 11/26/2024] Open
Abstract
Genetic factors related to pregnancy-related traits are understudied, especially in ancestrally diverse cohorts. To assess maternal contributions to hypertensive disorders of pregnancy (HDP), we performed a multi-ancestry genome-wide association study (GWAS) of HDP in data from the North Carolina-based Personalized Environment and Genes Study (PEGS) cohort with validation in the UK Biobank (UKBB). The GWAS revealed two maternal loci associated with HDP at the genome-wide significance level. The lead independent variants were rs114954125 on chromosome 2 (near LRP1B; odds ratio [OR] [95% confidence interval {CI}]): 2.96 [2.02-4.34]; p = 2.82 × 10-8) and rs61176331 on chromosome 3 (on RARB; OR (95% CI): 3.08 (2.12-4.48); p = 3.52 × 10-9). We validated the associations near RARB with a meta-analysis of PEGS and the UKBB. We also identified cis-expression quantitative trait loci in the candidate region associated with decreased RARB expression in macrophage cells exposed to Salmonella. Chromatin mapping in FUMA identified a significant interaction within chromosome 3's enhancer and open chromatin regions, with strong effects observed for RARB and H3P10 gene regulation in mesendoderm cells, mesenchymal stem cells, and trophoblast-like stem cells. We applied existing polygenic scores (PGS) for preeclampsia and gestational hypertension and found that the scores were significantly associated with HDP in PEGS. The findings demonstrate the power of multi-ancestry studies for genetic discovery and highlight the relationship between immune response, regulation, and HDP and the utility of PGS for risk prediction. (PEGS is registered at ClinicalTrials.gov: NCT00341237.).
Collapse
Affiliation(s)
- Jasmine A Mack
- National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, USA; University of Cambridge, Department of Obstetrics and Gynaecology, Cambridge CB2 0SW, UK
| | - Adam Burkholder
- National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, USA
| | - Farida S Akhtari
- National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, USA
| | - John S House
- National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, USA
| | - Ulla Sovio
- University of Cambridge, Department of Obstetrics and Gynaecology, Cambridge CB2 0SW, UK
| | - Gordon C S Smith
- University of Cambridge, Department of Obstetrics and Gynaecology, Cambridge CB2 0SW, UK
| | - Charles P Schmitt
- National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, USA
| | - David C Fargo
- National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, USA
| | - Janet E Hall
- National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, USA
| | | |
Collapse
|
132
|
Rodriguez A, Yang C, Gan W, Karlinsey K, Zhou B, Rich SS, Taylor KD, Guo X, Rotter JI, Johnson WC, Cornell E, Tracy RP, Durda JP, Gerszten RE, Clish CB, Blackwell T, Papanicolaou GJ, Lin H, Raffield LM, Vargas JD, Vasan R, Manichaikul A. Soluble Immune Checkpoint Protein and Lipid Network Associations with All-Cause Mortality Risk: Trans-Omics for Precision Medicine (TOPMed) Program. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2025:2025.01.08.25320225. [PMID: 39830278 PMCID: PMC11741490 DOI: 10.1101/2025.01.08.25320225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/22/2025]
Abstract
Adverse cardiovascular events are emerging with the use of immune checkpoint therapies in oncology. Using datasets in the Trans-Omics for Precision Medicine program (Multi-Ethnic Study of Atherosclerosis, Jackson Heart Study [JHS], and Framingham Heart Study), we examined the association of immune checkpoint plasma proteins with each other, their associated protein network with high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C), and the association of HDL-C- and LDL-C-associated protein networks with all-cause mortality risk. Plasma levels of LAG3 and HAVCR2 showed statistically significant associations with mortality risk. Colocalization analysis using genome wide-association studies of HDL-C or LDL-C and protein quantitative trait loci from JHS and the Atherosclerosis Risk in Communities identified TFF3 rs60467699 and CD36 rs3211938 variants as significantly colocalized with HDL-C; in contrast, none colocalized with LDL-C. The measurement of plasma LAG3, HAVCR2, and associated proteins plus targeted genotyping may identify patients at increased mortality risk.
Collapse
|
133
|
Downie CG, Highland HM, Alotaibi M, Welch BM, Howard AG, Cheng S, Miller N, Jain M, Kaplan RC, Lilly AG, Long T, Sofer T, Thyagarajan B, Yu B, North KE, Avery CL. Genome-wide association study reveals shared and distinct genetic architecture of fatty acids and oxylipins in the Hispanic Community Health Study/Study of Latinos. HGG ADVANCES 2025; 6:100390. [PMID: 39644095 PMCID: PMC11751521 DOI: 10.1016/j.xhgg.2024.100390] [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: 06/10/2024] [Revised: 12/02/2024] [Accepted: 12/02/2024] [Indexed: 12/09/2024] Open
Abstract
Bioactive fatty acid-derived oxylipin molecules play key roles mediating inflammation and oxidative stress. Circulating levels of fatty acids and oxylipins are influenced by environmental and genetic factors; characterizing the genetic architecture of bioactive lipids could yield new insights into underlying biology. We performed a genome-wide association study (GWAS) of 81 fatty acids and oxylipins in 11,584 Hispanic Community Health Study/Study of Latinos (HCHS/SOL) participants with genetic and lipidomic data measured at study baseline (58.6% female, mean age = 46.1 years (standard deviation 13.8)). Additionally, given the effects of central obesity on inflammation, we examined interactions with waist circumference using two-degree-of-freedom joint tests. Thirty-three of the 81 oxylipins and fatty acids were significantly heritable (heritability range: 0-32.7%). Forty (49.4%) oxylipins and fatty acids had at least one genome-wide significant (p < 6.94E-11) variant resulting in 19 independent genetic loci. Six loci (lead variant minor allele frequency [MAF] range: 0.08-0.50), including desaturase-encoding FADS and OATP1B1 transporter protein-encoding SLCO1B1, exhibited associations with two or more fatty acids and oxylipins. At several of these loci, there was evidence of colocalization of the top variant across fatty acids and oxylipins. The remaining loci were only associated with one oxylipin or fatty acid and included several CYP loci. We also identified an additional rare variant (MAF = 0.002) near CARS2 in two-degree-of-freedom tests. Our analyses revealed shared and distinct genetic architecture underlying fatty acids and oxylipins, providing insights into genetic factors and motivating work to characterize these compounds and elucidate their roles in disease.
Collapse
Affiliation(s)
- Carolina G Downie
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
| | - Heather M Highland
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Mona Alotaibi
- Division of Pulmonary, Critical Care and Sleep Medicine, University of California, San Diego, San Diego, CA, USA
| | - Barrett M Welch
- School of Public Health, University of Nevada, Reno, Reno, NV, USA
| | - Annie Green Howard
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Susan Cheng
- Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | | | - Mohit Jain
- Sapient Bioanalytics, San Diego, CA, USA; Departments of Medicine and Pharmacology, University of California, San Diego, San Diego, CA, USA
| | - Robert C Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA; Public Health Sciences Division, Fred Hutchison Cancer Center, Seattle, WA, USA
| | - Adam G Lilly
- Department of Sociology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Tao Long
- Sapient Bioanalytics, San Diego, CA, USA
| | - Tamar Sofer
- CardioVascular Institute (CVI), Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Bharat Thyagarajan
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical Center, Minneapolis, MN, USA
| | - Bing Yu
- Department of Epidemiology, Human Genetics, and Environmental Sciences, The University of Texas Health Science Center at Houston, School of Public Health, Houston, TX, USA
| | - Kari E North
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Christy L Avery
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| |
Collapse
|
134
|
Jee YH, Wang Y, Jung KJ, Lee JY, Kimm H, Duan R, Price AL, Martin AR, Kraft P. Genome-wide association studies in a large Korean cohort identify novel quantitative trait loci for 36 traits and illuminate their genetic architectures. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2025:2024.05.17.24307550. [PMID: 38798434 PMCID: PMC11118625 DOI: 10.1101/2024.05.17.24307550] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Genome-wide association studies (GWAS) have been predominantly conducted in populations of European ancestry, limiting opportunities for biological discovery in diverse populations. We report GWAS findings from 153,950 individuals across 36 quantitative traits in the Korean Cancer Prevention Study-II (KCPS2) Biobank. We discovered 301 novel genetic loci in KCPS2, including an association between thyroid-stimulating hormone and CD36. Meta-analysis with the Korean Genome and Epidemiology Study, Biobank Japan, Taiwan Biobank, and UK Biobank identified 4,588 loci that were not significant in any contributing GWAS. We describe differences in genetic architectures across these East Asian and European samples. We also highlight East Asian specific associations, including a known pleiotropic missense variant in ALDH2, which fine-mapping identified as a likely causal variant for a diverse set of traits. Our findings provide insights into the genetic architecture of complex traits in East Asian populations and highlight how broadening the population diversity of GWAS samples can aid discovery.
Collapse
Affiliation(s)
- Yon Ho Jee
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Ying Wang
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Keum Ji Jung
- Institute for Health Promotion, Department of Epidemiology and Health Promotion, Graduate School of Public Health, Yonsei University, Seoul, Korea
| | - Ji-Young Lee
- Institute for Health Promotion, Department of Epidemiology and Health Promotion, Graduate School of Public Health, Yonsei University, Seoul, Korea
| | - Heejin Kimm
- Institute for Health Promotion, Department of Epidemiology and Health Promotion, Graduate School of Public Health, Yonsei University, Seoul, Korea
| | - Rui Duan
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Alkes L. Price
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Alicia R. Martin
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Peter Kraft
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Transdivisional Research Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, MD, USA
| |
Collapse
|
135
|
Biswas S, Hilser JR, Woodward NC, Wang Z, Gukasyan J, Nemet I, Schwartzman WS, Huang P, Han Y, Fouladian Z, Charugundla S, Spencer NJ, Pan C, Tang WHW, Lusis AJ, Hazen SL, Hartiala JA, Allayee H. Exploring the Role of Glycine Metabolism in Coronary Artery Disease: Insights from Human Genetics and Mouse Models. Nutrients 2025; 17:198. [PMID: 39796632 PMCID: PMC11723402 DOI: 10.3390/nu17010198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2024] [Revised: 12/19/2024] [Accepted: 12/31/2024] [Indexed: 01/13/2025] Open
Abstract
Background: Circulating glycine levels have been associated with reduced risk of coronary artery disease (CAD) in humans but these associations have not been observed in all studies. We evaluated whether the relationship between glycine levels and atherosclerosis was causal using genetic analyses in humans and feeding studies in mice. Methods: Serum glycine levels were evaluated for association with risk of CAD in the UK Biobank. Genetic determinants of glycine levels were identified through a genome-wide association study (GWAS) and used to evaluate the causal relationship between glycine and risk of CAD by Mendelian randomization (MR). A dietary supplementation study was carried out with atherosclerosis-prone apolipoprotein E deficient (ApoE-/-) mice to determine the effects of increased circulating glycine levels on cardiometabolic traits and aortic lesion formation. Results: Among 105,718 UK Biobank subjects, elevated serum glycine levels were associated with significantly reduced risk of prevalent CAD (Quintile 5 vs. Quintile 1 OR = 0.76, 95% CI 0.67-0.87; p < 0.0001) and incident CAD (Quintile 5 vs. Quintile 1 HR = 0.70, 95% CI 0.65-0.77; p < 0.0001) after adjustment for age, sex, ethnicity, anti-hypertensive and lipid-lowering medications, blood pressure, kidney function, and diabetes. A GWAS meta-analysis with 230,947 subjects identified 61 loci for glycine levels, of which 26 were novel. MR analyses provided modest evidence that genetically elevated glycine levels were causally associated with reduced systolic blood pressure and risk of type 2 diabetes, but did not provide significant evidence for an association with decreased risk of CAD. Glycine supplementation in mice had no effects on cardiometabolic traits or atherosclerotic lesion development. Conclusions: While expanding the genetic architecture of glycine metabolism, MR analyses and in vivo feeding studies did not provide evidence that the clinical association of this amino acid with atherosclerosis represents a causal relationship.
Collapse
Affiliation(s)
- Subarna Biswas
- Department of Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - James R. Hilser
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
- Department of Biochemistry and Molecular Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Nicholas C. Woodward
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
- Department of Biochemistry and Molecular Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Zeneng Wang
- Department of Cardiovascular and Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
- Center for Microbiome and Human Health, Cleveland Clinic, Cleveland, OH 44195, USA
- Department of Cardiovascular Medicine, Heart, Vascular and Thoracic Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Janet Gukasyan
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
- Department of Biochemistry and Molecular Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Ina Nemet
- Department of Cardiovascular and Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
- Center for Microbiome and Human Health, Cleveland Clinic, Cleveland, OH 44195, USA
| | - William S. Schwartzman
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
- Department of Biochemistry and Molecular Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Pin Huang
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
- Department of Biochemistry and Molecular Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Yi Han
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
- Department of Biochemistry and Molecular Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Zachary Fouladian
- Department of Medicine, David Geffen School of Medicine of UCLA, Los Angeles, CA 90095, USA
| | - Sarada Charugundla
- Department of Medicine, David Geffen School of Medicine of UCLA, Los Angeles, CA 90095, USA
| | - Neal J. Spencer
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
- Department of Biochemistry and Molecular Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Calvin Pan
- Department of Human Genetics, David Geffen School of Medicine of UCLA, Los Angeles, CA 90095, USA
| | - W. H. Wilson Tang
- Department of Cardiovascular and Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
- Center for Microbiome and Human Health, Cleveland Clinic, Cleveland, OH 44195, USA
- Department of Cardiovascular Medicine, Heart, Vascular and Thoracic Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Aldons J. Lusis
- Department of Medicine, David Geffen School of Medicine of UCLA, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine of UCLA, Los Angeles, CA 90095, USA
- Department of Microbiology, Immunology, and Molecular Genetics, David Geffen School of Medicine of UCLA, Los Angeles, CA 90095, USA
| | - Stanley L. Hazen
- Department of Cardiovascular and Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
- Center for Microbiome and Human Health, Cleveland Clinic, Cleveland, OH 44195, USA
- Department of Cardiovascular Medicine, Heart, Vascular and Thoracic Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Jaana A. Hartiala
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Hooman Allayee
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
- Department of Biochemistry and Molecular Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| |
Collapse
|
136
|
Kang J, Ahn K, Oh J, Lee T, Hwang S, Uh Y, Choi SJ. Identification of Endometriosis Pathophysiologic-Related Genes Based on Meta-Analysis and Bayesian Approach. Int J Mol Sci 2025; 26:424. [PMID: 39796277 PMCID: PMC11720405 DOI: 10.3390/ijms26010424] [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: 11/27/2024] [Revised: 12/31/2024] [Accepted: 01/03/2025] [Indexed: 01/13/2025] Open
Abstract
Endometriosis is a complex disease with diverse etiologies, including hormonal, immunological, and environmental factors; however, its exact pathogenesis remains unknown. While surgical approaches are the diagnostic and therapeutic gold standard, identifying endometriosis-associated genes is a crucial first step. Five endometriosis-related gene expression studies were selected from the available datasets. Approximately, 14,167 genes common to these 5 datasets were analyzed for differential expression. Meta-analyses utilized fold-change values and standard errors obtained from each analysis, with the binomial and continuous datasets contributing to endometriosis presence and endometriosis severity meta-analysis, respectively. Approximately 160 genes showed significant results in both meta-analyses. For Bayesian analysis, endometriosis-related single nucleotide polymorphisms (SNPs), the human transcription factor catalog, uterine SNP-related gene expression, disease-gene databases, and interactome databases were utilized. Twenty-four genes, present in at least three or more databases, were identified. Network analysis based on Pearson's correlation coefficients revealed the HLA-DQB1 gene with both a high score in the Bayesian analysis and a central position in the network. Although ZNF24 had a lower score, it occupied a central position in the network, followed by other ZNF family members. Bayesian analysis identified genes with high confidence that could support discovering key diagnostic biomarkers and therapeutic targets for endometriosis.
Collapse
Affiliation(s)
- Jieun Kang
- Department of Obstetrics and Gynecology, Yonsei University Wonju College of Medicine, 20, Ilsan-ro, Wonju-si 26426, Republic of Korea;
| | - Kwangjin Ahn
- Department of Laboratory Medicine, Yonsei University Wonju College of Medicine, 20, Ilsan-ro, Wonju-si 26426, Republic of Korea;
| | - Jiyeon Oh
- Department of Global Medical Science, Yonsei University Wonju College of Medicine, 20, Ilsan-ro, Wonju-si 26426, Republic of Korea;
| | - Taesic Lee
- Department of Family Medicine, Yonsei University Wonju College of Medicine, 20, Ilsan-ro, Wonju-si 26426, Republic of Korea;
| | - Sangwon Hwang
- Department of Precision Medicine, Yonsei University Wonju College of Medicine, 20, Ilsan-ro, Wonju-si 26426, Republic of Korea;
| | - Young Uh
- Department of Laboratory Medicine, Yonsei University Wonju College of Medicine, 20, Ilsan-ro, Wonju-si 26426, Republic of Korea;
| | - Seong Jin Choi
- Department of Obstetrics and Gynecology, Yonsei University Wonju College of Medicine, 20, Ilsan-ro, Wonju-si 26426, Republic of Korea;
| |
Collapse
|
137
|
De Jager P, Zeng L, Khan A, Lama T, Chitnis T, Weiner H, Wang G, Fujita M, Zipp F, Taga M, Kiryluk K. GWAS highlights the neuronal contribution to multiple sclerosis susceptibility. RESEARCH SQUARE 2025:rs.3.rs-5644532. [PMID: 39866869 PMCID: PMC11760239 DOI: 10.21203/rs.3.rs-5644532/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/28/2025]
Abstract
Multiple Sclerosis (MS) is a chronic inflammatory and neurodegenerative disease affecting the brain and spinal cord. Genetic studies have identified many risk loci, that were thought to primarily impact immune cells and microglia. Here, we performed a multi-ancestry genome-wide association study with 20,831 MS and 729,220 control participants, identifying 236 susceptibility variants outside the Major Histocompatibility Complex, including four novel loci. We derived a polygenic score for MS and, optimized for European ancestry, it is informative for African-American and Latino participants. Integrating single-cell data from blood and brain tissue, we identified 76 genes affected by MS risk variants. Notably, while T cells showed the strongest enrichment, inhibitory neurons emerged as a key cell type. The expression of IL7 and STAT3 are affected only in inhibitory neurons, highlighting the importance of neuronal and glial dysfunction in MS susceptibility.
Collapse
Affiliation(s)
| | - Lu Zeng
- Columbia University Irving Medical Center
| | | | | | | | | | | | | | - Frauke Zipp
- University Medical Center of the Johannes Gutenberg University Mainz
| | - Mariko Taga
- Center for Translational & Computational Neuroimmunology
| | | |
Collapse
|
138
|
da Silva MRG, Veroneze R, Marques DBD, da Silva DA, Machado II, Brito LF, Lopes PS. A meta-analysis of genome-wide association studies to identify candidate genes associated with feed efficiency traits in pigs. J Anim Sci 2025; 103:skaf010. [PMID: 39847436 PMCID: PMC11833465 DOI: 10.1093/jas/skaf010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2024] [Accepted: 01/21/2025] [Indexed: 01/24/2025] Open
Abstract
Pig production is an agricultural sector of great economic and social relevance to Brazil and global markets. Feed efficiency traits directly influence the sustainability of pig production due to the economic impact of feed costs on the production system and the environmental footprint of the industry. Therefore, breeding for improved feed efficiency has been a target of worldwide pig breeding programs. Genome-wide association studies (GWAS) enable the assessment of the genetic background of complex traits, which contributes to a better understanding of the biological mechanisms regulating their phenotypic expression. In this context, the primary objective of this study was to identify and validate genomic regions and candidate genes associated with feed conversion ratio (FCR) and residual feed intake (RFI) in pigs based on a comprehensive systematic review and meta-analysis of GWAS. The METAL software was used to implement the meta-analysis and the Bonferroni multiple testing correction considering a significance threshold 0.05. The significant single nucleotide polymorphisms (SNPs) in the meta-analysis were used to identify candidate genes, followed by a functional genomic enrichment analysis. The systematic review identified 13 studies, of which 7 evaluated FCR, 3 evaluated RFI, and 3 studies investigated both traits, with 160 and 96 SNPs identified for FCR and RFI, respectively. After the meta-analysis, 145 markers were significantly associated with FCR and 90 with RFI. The gene annotation process resulted in 105 and 114 genes for FCR and RFI, respectively. The enrichment analysis for FCR resulted in 16 significant gene ontology (GO) terms, while 6 terms were identified for RFI. The main GO terms were actin cytoskeleton (GO_BP:0030036), membrane (GO_CC:0016020), integral components of the peroxisomal membrane (GO_CC:0005779), and carbohydrate-binding (GO_MF:0030246). The main candidate genes identified were MED18, PHACTR4, ABCC2, TRHDE, FRS2, FAR2 and FIS1 for FCR, and ADGRL2, ASGR1, ASGR2, and MAN2B1 for RFI. These findings contribute to a better understanding of the genetic mechanisms associated with feed efficiency traits in pigs, providing a foundation for future improvements in pig breeding programs.
Collapse
Affiliation(s)
- Maria Rita Gonçalves da Silva
- Department of Animal Science, Federal University of Viçosa, Viçosa, MG, Brazil
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA
| | - Renata Veroneze
- Department of Animal Science, Federal University of Viçosa, Viçosa, MG, Brazil
| | - Daniele B D Marques
- Department of Animal Science, Federal University of Viçosa, Viçosa, MG, Brazil
| | - Delvan A da Silva
- Department of Animal Science, Federal University of Viçosa, Viçosa, MG, Brazil
| | - Inaê I Machado
- Department of Animal Science, Federal University of Viçosa, Viçosa, MG, Brazil
| | - Luiz F Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA
| | - Paulo S Lopes
- Department of Animal Science, Federal University of Viçosa, Viçosa, MG, Brazil
| |
Collapse
|
139
|
Jin Y, Topaloudi A, Shekhar S, Chen G, Scott AN, Colon BD, Drineas P, Rochet C, Paschou P. Neuropathology-based approach reveals novel Alzheimer's Disease genes and highlights female-specific pathways and causal links to disrupted lipid metabolism: insights into a vicious cycle. Acta Neuropathol Commun 2025; 13:1. [PMID: 39755674 DOI: 10.1186/s40478-024-01909-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2024] [Accepted: 12/05/2024] [Indexed: 01/06/2025] Open
Abstract
Dementia refers to an umbrella phenotype of many different underlying pathologies with Alzheimer's disease (AD) being the most common type. Neuropathological examination remains the gold standard for accurate AD diagnosis, however, most that we know about AD genetics is based on Genome-Wide Association Studies (GWAS) of clinically defined AD. Such studies have identified multiple AD susceptibility variants with a significant portion of the heritability unexplained and highlighting the phenotypic and genetic heterogeneity of the clinically defined entity. Furthermore, despite women's increased susceptibility to dementia, there is a lack of sex-specific genetic studies and understanding of sex-specific background for the disorder. Here, we aim to tackle the heterogeneity of AD by specifically concentrating on neuropathological features and pursuing sex-specific analysis. We bring together 14 different genomic and neuropathology datasets (6960 individuals) and we integrate our GWAS findings with transcriptomic and phenotypic data aiming to also identify biomarkers for AD progression. We uncover novel genetic associations to AD neuropathology, including BIN1 and OPCML. Our sex-specific analysis points to a role for BIN1 specifically in women as well as novel AD loci including QRFPR and SGCZ. Post-GWAS analyses illuminate the functional and biological mechanisms underlying AD and reveal sex-specific differences. Finally, through PheWAS and Mendelian Randomization analysis, we identify causal links with AD neuropathology pointing to disrupted lipid metabolism, as well as impaired peripheral immune response and liver dysfunction as part of a vicious cycle that fuels neurodegeneration.
Collapse
Affiliation(s)
- Yin Jin
- Department of Biological Sciences, Purdue University, 915 Mitch Daniels Blvd, West Lafayette, IN, USA
| | - Apostolia Topaloudi
- Department of Biological Sciences, Purdue University, 915 Mitch Daniels Blvd, West Lafayette, IN, USA
| | - Sudhanshu Shekhar
- Department of Biological Sciences, Purdue University, 915 Mitch Daniels Blvd, West Lafayette, IN, USA
| | - Guangxin Chen
- Department of Biological Sciences, Purdue University, 915 Mitch Daniels Blvd, West Lafayette, IN, USA
| | - Alicia Nicole Scott
- Medicinal Chemistry and Molecular Pharmacology, Purdue University, West Lafayette, IN, USA
| | - Bryce David Colon
- Medicinal Chemistry and Molecular Pharmacology, Purdue University, West Lafayette, IN, USA
| | - Petros Drineas
- Computer Science, Purdue University, West Lafayette, IN, USA
| | - Chris Rochet
- Medicinal Chemistry and Molecular Pharmacology, Purdue University, West Lafayette, IN, USA
| | - Peristera Paschou
- Department of Biological Sciences, Purdue University, 915 Mitch Daniels Blvd, West Lafayette, IN, USA.
| |
Collapse
|
140
|
Oh K, Yuk M, Yang S, Youn J, Dong Q, Wang Z, Song N. A genome-wide association study of high-sensitivity C-reactive protein in a large Korean population highlights its genetic relationship with cholesterol metabolism. Sci Rep 2025; 15:189. [PMID: 39747571 PMCID: PMC11696572 DOI: 10.1038/s41598-024-84466-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2024] [Accepted: 12/24/2024] [Indexed: 01/04/2025] Open
Abstract
High-sensitivity C-reactive protein (hsCRP) is a representative biomarker of systemic inflammation and is associated with numerous chronic diseases. To explore the biological pathways and functions underlying chronic inflammation, we conducted a genome-wide association study (GWAS) and several post-GWAS analyses of the hsCRP levels. This study was performed on data from 71,019 Koreans and is one of the largest East Asian studies. Overall, 69 independent single nucleotide polymorphisms (SNPs) were identified, including 13 novel variants. The implicated genes and pathways are primarily involved in cholesterol metabolism and the immune response. A phenome-wide association study was performed based on a polygenic risk score (PRS) constructed using 69 hsCRP-associated SNPs. Notably, the alleles associated with higher hsCRP levels appeared to be associated with lower low-density lipoprotein cholesterol levels (P = 1.69 × 10-33, β = -1.47) and higher γ -glutamyl transpeptidase (P = 8.30 × 10-8, β = 0.84). It suggests that increase in genetically determined hsCRP may contribute to a decrease in cholesterol level and a strong oxidative environment in the blood vessel. Thus, individuals with higher hsCRP-PRS may have a greater risk of cardiovascular diseases. Our findings suggest the genetic association between cholesterol and hsCRP, as well as the clinical importance of hsCRP-PRS for predicting the potential risk of cardiovascular diseases.
Collapse
Affiliation(s)
- Kwangyeon Oh
- Department of Pharmacy, College of Pharmacy, Chungbuk National University, 194-21, Osongsaengmyeong-1 ro, Heungdeok-gu, Cheongju, 28160, Chungcheongbuk-do, Korea
| | - Minju Yuk
- Department of Pharmacy, College of Pharmacy, Chungbuk National University, 194-21, Osongsaengmyeong-1 ro, Heungdeok-gu, Cheongju, 28160, Chungcheongbuk-do, Korea
| | - Soyoun Yang
- Department of Pharmacy, College of Pharmacy, Chungbuk National University, 194-21, Osongsaengmyeong-1 ro, Heungdeok-gu, Cheongju, 28160, Chungcheongbuk-do, Korea
| | - Jiyeong Youn
- Department of Pharmacy, College of Pharmacy, Chungbuk National University, 194-21, Osongsaengmyeong-1 ro, Heungdeok-gu, Cheongju, 28160, Chungcheongbuk-do, Korea
| | - Qian Dong
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, 38105, 262 Danny Thomas Place, Memphis, Tennessee, USA
| | - Zhaoming Wang
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, 38105, 262 Danny Thomas Place, Memphis, Tennessee, USA
| | - Nan Song
- Department of Pharmacy, College of Pharmacy, Chungbuk National University, 194-21, Osongsaengmyeong-1 ro, Heungdeok-gu, Cheongju, 28160, Chungcheongbuk-do, Korea.
| |
Collapse
|
141
|
Cao S, Zeng Y, Pang K, Chen M, Guo R, Wu N, Fang C, Deng H, Zhang X, Xie X, Ouyang W, Yang H. Unraveling the causal impact of smoking and its DNA methylation signatures on cardiovascular disease: Mendelian randomization and colocalization analysis. Clin Epigenetics 2025; 17:1. [PMID: 39748436 PMCID: PMC11694376 DOI: 10.1186/s13148-024-01808-6] [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: 09/09/2024] [Accepted: 12/23/2024] [Indexed: 01/04/2025] Open
Abstract
BACKGROUND To explore the mechanisms linking smoking to cardiovascular diseases (CVDs) from an epigenetic perspective. METHODS Mendelian Randomization (MR) analysis was performed to assess the causal effects of smoking behavior and DNA methylation levels at smoking-related CpG sites on nine CVDs, including aortic aneurysm, atrial fibrillation, coronary atherosclerosis, coronary heart disease, heart failure, intracerebral hemorrhage, ischemic stroke, myocardial infarction, subarachnoid hemorrhage. Colocalization analysis was used to further identify key smoking-related CpG sites from the MR causal estimates. Reactome enrichment analysis was used to elucidate the potential mechanisms. RESULTS MR analysis indicates that smoking behaviors are significantly associated with an increased risk of nine CVDs (OR > 1, P < 0.05). Through MR and colocalization analysis, five key smoking-related CpG sites were ultimately determined. DNA methylation alteration at cg25313468 (located in the TSS1500 region of REST) is simultaneously associated with the risk of atrial fibrillation, coronary atherosclerosis, coronary heart disease, and myocardial infarction. Additionally, cg21647257 (located in the TSS200 region of CLIP3) is associated with the risk of atrial fibrillation; cg06197751 (located in SGEF gene body) and cg07520810 (located in ARID5B gene body) are associated with the risk of coronary atherosclerosis; cg16822035 (located in MCF2L gene body) is associated with the risk of myocardial infarction. Enrichment analysis suggests that phosphatase and tensin homologue (PTEN) may be involved in the downstream mechanisms of cg25313468 (REST). CONCLUSION This study uncovers the relationship between smoking, DNA methylation, and CVDs, providing new insights into the pathogenic effect of smoking on CVDs from an epigenetic perspective.
Collapse
Affiliation(s)
- Si Cao
- Department of Anesthesiology, Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China
| | - Youjie Zeng
- Department of Anesthesiology, Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China
| | - Ke Pang
- Department of Anesthesiology, Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China
| | - Minghua Chen
- Department of Anesthesiology, Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China
| | - Ren Guo
- Department of Pharmacy, Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China
| | - Nayiyuan Wu
- The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University/Hunan Cancer Hospital, Changsha, Hunan, China
| | - Chao Fang
- The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University/Hunan Cancer Hospital, Changsha, Hunan, China
| | - Huiyin Deng
- Department of Anesthesiology, Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China
| | - Xiaoyi Zhang
- Department of Medicine, Jacobi Medical Center, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - Xiaohui Xie
- Department of Medicine, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Wen Ouyang
- Department of Anesthesiology, Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China
| | - Heng Yang
- Department of Neurology, Third Xiangya Hospital, Central South University, 138 Tongzipo Road, Yuelu District, Changsha, 410013, Hunan, China.
| |
Collapse
|
142
|
Valo E, Richmond A, Mutter S, Dahlström EH, Campbell A, Porteous DJ, Wilson JF, Groop PH, Hayward C, Sandholm N. Genome-wide characterization of 54 urinary metabolites reveals molecular impact of kidney function. Nat Commun 2025; 16:325. [PMID: 39746953 PMCID: PMC11696681 DOI: 10.1038/s41467-024-55182-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Accepted: 11/27/2024] [Indexed: 01/04/2025] Open
Abstract
Dissecting the genetic mechanisms underlying urinary metabolite concentrations can provide molecular insights into kidney function and open possibilities for causal assessment of urinary metabolites with risk factors and disease outcomes. Proton nuclear magnetic resonance metabolomics provides a high-throughput means for urinary metabolite profiling, as widely applied for blood biomarker studies. Here we report a genome-wide association study meta-analysed for 3 European cohorts comprising 8,011 individuals, covering both people with type 1 diabetes and general population settings. We identify 54 associations (p < 9.3 × 10-10) for 19 of 54 studied metabolite concentrations. Out of these, 33 were not reported previously for relevant urinary or blood metabolite traits. Subsequent two-sample Mendelian randomization analysis suggests that estimated glomerular filtration rate causally affects 13 urinary metabolite concentrations whereas urinary ethanolamine, an initial precursor for phosphatidylcholine and phosphatidylethanolamine, was associated with higher eGFR lending support for a potential protective role. Our study provides a catalogue of genetic associations for 53 metabolites, enabling further investigation on how urinary metabolites are linked to human health.
Collapse
Grants
- Wellcome Trust
- MC_UU_00007/10 Medical Research Council
- Folkhälsan Research Foundation, Wilhelm and Else Stockmann Foundation, Liv och Hälsa Society, Helsinki University Hospital Research Funds (EVO TYH2018207), Academy of Finland (299200, and 316664), Novo Nordisk Foundation (NNF OC0013659, NNF23OC0082732), Sigrid Jusélius Foundation, and Finnish Diabetes Research Foundation. Genotyping of the FinnDiane GWAS data was funded by the Juvenile Diabetes Research Foundation (JDRF) within the Diabetic Nephropathy Collaborative Research Initiative (DNCRI; Grant 17-2013-7), with GWAS quality control and imputation performed at University of Virginia. Generation Scotland received core support from the Chief Scientist Office of the Scottish Government Health Directorates [CZD/16/6] and the Scottish Funding Council [HR03006] and is currently supported by the Wellcome Trust [216767/Z/19/Z]. Genotyping of the GS:SFHS samples was carried out by the Genetics Core Laboratory at the Edinburgh Clinical Research Facility, University of Edinburgh, Scotland and was funded by the Medical Research Council UK and the Wellcome Trust (Wellcome Trust Strategic Award “STratifying Resilience and Depression Longitudinally” (STRADL) Reference 104036/Z/14/Z). CH was supported by the MRC Human Genetics Unit quinquennial programme grant “QTL in Health and Disease” (MC_UU_00007/10.) The Viking Health Study – Shetland (VIKING) was supported by the MRC Human Genetics Unit quinquennial programme grant “QTL in Health and Disease” (MC_UU_00007/10).
Collapse
Affiliation(s)
- Erkka Valo
- Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Anne Richmond
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, UK
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Stefan Mutter
- Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Emma H Dahlström
- Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - James F Wilson
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, UK
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, UK
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Per-Henrik Groop
- Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Diabetes, Central Clinical School, Monash University, Melbourne, VIC, Australia
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
| | - Caroline Hayward
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, UK.
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, UK.
| | - Niina Sandholm
- Folkhälsan Research Center, Helsinki, Finland.
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
| |
Collapse
|
143
|
Ji A, Sui Y, Xue X, Ji X, Shi W, Shi Y, Terkeltaub R, Dalbeth N, Takei R, Yan F, Sun M, Li M, Lu J, Cui L, Liu Z, Wang C, Li X, Han L, Fang Z, Sun W, Liang Y, He Y, Zheng G, Wang X, Wang J, Zhang H, Pang L, Qi H, Li Y, Cheng Z, Li Z, Xiao J, Zeng C, Merriman TR, Qu H, Fang X, Li C. Novel Genetic Loci in Early-Onset Gout Derived From Whole-Genome Sequencing of an Adolescent Gout Cohort. Arthritis Rheumatol 2025; 77:107-115. [PMID: 39118347 DOI: 10.1002/art.42969] [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: 06/20/2024] [Revised: 08/01/2024] [Accepted: 08/05/2024] [Indexed: 08/10/2024]
Abstract
OBJECTIVE Mechanisms underlying the adolescent-onset and early-onset gout are unclear. This study aimed to discover variants associated with early-onset gout. METHODS We conducted whole-genome sequencing in a discovery adolescent-onset gout cohort of 905 individuals (gout onset 12 to 19 years) to discover common and low-frequency single-nucleotide variants (SNVs) associated with gout. Candidate common SNVs were genotyped in an early-onset gout cohort of 2,834 individuals (gout onset ≤30 years old), and meta-analysis was performed with the discovery and replication cohorts to identify loci associated with early-onset gout. Transcriptome and epigenomic analyses, quantitative real-time polymerase chain reaction and RNA sequencing in human peripheral blood leukocytes, and knock-down experiments in human THP-1 macrophage cells investigated the regulation and function of candidate gene RCOR1. RESULTS In addition to ABCG2, a urate transporter previously linked to pediatric-onset and early-onset gout, we identified two novel loci (Pmeta < 5.0 × 10-8): rs12887440 (RCOR1) and rs35213808 (FSTL5-MIR4454). Additionally, we found associations at ABCG2 and SLC22A12 that were driven by low-frequency SNVs. SNVs in RCOR1 were linked to elevated blood leukocyte messenger RNA levels. THP-1 macrophage culture studies revealed the potential of decreased RCOR1 to suppress gouty inflammation. CONCLUSION This is the first comprehensive genetic characterization of adolescent-onset gout. The identified risk loci of early-onset gout mediate inflammatory responsiveness to crystals that could mediate gouty arthritis. This study will contribute to risk prediction and therapeutic interventions to prevent adolescent-onset gout.
Collapse
Affiliation(s)
- Aichang Ji
- Affiliated Hospital of Qingdao University, Qingdao, China
| | - Yang Sui
- China National Center for Bioinformation, Beijing Institute of Genomics, Chinese Academy of Sciences, and University of Chinese Academy of Sciences, Beijing, China
| | - Xiaomei Xue
- Affiliated Hospital of Qingdao University, Qingdao, China
| | - Xiapeng Ji
- Affiliated Hospital of Qingdao University, Qingdao, China
| | - Wenrui Shi
- China National Center for Bioinformation, Beijing Institute of Genomics, Chinese Academy of Sciences, and University of Chinese Academy of Sciences, Beijing, China
| | - Yongyong Shi
- Affiliated Hospital of Qingdao University and Biomedical Sciences Institute of Qingdao University (Qingdao Branch of SJTU Bio-X Institutes), Qingdao University, Qingdao, China, and Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai, China
| | | | | | - Riku Takei
- Asia Pacific Gout Consortium and University of Alabama at Birmingham
| | - Fei Yan
- Affiliated Hospital of Qingdao University, Qingdao, China
| | - Mingshu Sun
- Shandong Provincial Clinical Research Center for Immune Diseases and Gout & Shandong Provincial Key Laboratory of Metabolic Diseases, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Maichao Li
- Affiliated Hospital of Qingdao University, Qingdao, China
| | - Jie Lu
- Affiliated Hospital of Qingdao University, Qingdao, China
| | - Lingling Cui
- Affiliated Hospital of Qingdao University, Qingdao, China
| | - Zhen Liu
- Affiliated Hospital of Qingdao University, Qingdao, China
| | - Can Wang
- Affiliated Hospital of Qingdao University, Qingdao, China
| | - Xinde Li
- Affiliated Hospital of Qingdao University, Qingdao, China
| | - Lin Han
- Affiliated Hospital of Qingdao University, Qingdao, China
| | - Zhanjie Fang
- China National Center for Bioinformation, Beijing Institute of Genomics, Chinese Academy of Sciences, and University of Chinese Academy of Sciences, Beijing, China
| | - Wenyan Sun
- Affiliated Hospital of Qingdao University, Qingdao, China
| | - Yue Liang
- China National Center for Bioinformation, Beijing Institute of Genomics, Chinese Academy of Sciences, and University of Chinese Academy of Sciences, Beijing, China
| | - Yuwei He
- Affiliated Hospital of Qingdao University, Qingdao, China
| | - Guangmin Zheng
- China National Center for Bioinformation, Beijing Institute of Genomics, Chinese Academy of Sciences, and University of Chinese Academy of Sciences, Beijing, China
| | - Xuefeng Wang
- Affiliated Hospital of Qingdao University, Qingdao, China
| | - Jiayi Wang
- Development Center for Medical Science & Technology, National Health Commission of the People's Republic of China, Beijing, China
| | - Hui Zhang
- Institute of Metabolic Diseases, Qingdao University, Qingdao, China
| | - Lei Pang
- Affiliated Hospital of Qingdao University, Qingdao, China
| | - Han Qi
- Affiliated Hospital of Qingdao University, Qingdao, China
| | - Yushuang Li
- Affiliated Hospital of Qingdao University, Qingdao, China
| | - Zan Cheng
- Affiliated Hospital of Qingdao University, Qingdao, China
| | - Zhiqiang Li
- The Biomedical Sciences Institute and The Affiliated Hospital of Qingdao University, Qingdao University, Qingdao, Shandong, China
| | - Jingfa Xiao
- China National Center for Bioinformation, Beijing Institute of Genomics, Chinese Academy of Sciences, and University of Chinese Academy of Sciences, Beijing, China
| | - Changqing Zeng
- China National Center for Bioinformation, Beijing Institute of Genomics, Chinese Academy of Sciences, and University of Chinese Academy of Sciences, Beijing, China
| | - Tony R Merriman
- Asia Pacific Gout Consortium, University of Alabama at Birmingham, Institute of Metabolic Diseases, Qingdao University, Qingdao, China, and University of Otago, Dunedin, New Zealand
| | - Hongzhu Qu
- China National Center for Bioinformation, Beijing Institute of Genomics, Chinese Academy of Sciences, University of Chinese Academy of Sciences, and Beijing Key Laboratory of Genome and Precision Medicine Technologies, Beijing, China
| | - Xiangdong Fang
- China National Center for Bioinformation, Beijing Institute of Genomics, Chinese Academy of Sciences, University of Chinese Academy of Sciences, and Beijing Key Laboratory of Genome and Precision Medicine Technologies, Beijing, China
| | - Changgui Li
- The Affiliated Hospital of Qingdao University, Qingdao, China, Asia Pacific Gout Consortium, and Institute of Metabolic Diseases, Qingdao University, Qingdao, China
| |
Collapse
|
144
|
De Walsche A, Vergne A, Rincent R, Roux F, Nicolas S, Welcker C, Mezmouk S, Charcosset A, Mary-Huard T. metaGE: Investigating genotype x environment interactions through GWAS meta-analysis. PLoS Genet 2025; 21:e1011553. [PMID: 39792927 PMCID: PMC11756807 DOI: 10.1371/journal.pgen.1011553] [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: 08/07/2024] [Revised: 01/23/2025] [Accepted: 12/23/2024] [Indexed: 01/12/2025] Open
Abstract
Elucidating the genetic components of plant genotype-by-environment interactions is of key importance in the context of increasing climatic instability, diversification of agricultural practices and pest pressure due to phytosanitary treatment limitations. The genotypic response to environmental stresses can be investigated through multi-environment trials (METs). However, genome-wide association studies (GWAS) of MET data are significantly more complex than that of single environments. In this context, we introduce metaGE, a flexible and computationally efficient meta-analysis approach for jointly analyzing single-environment GWAS of any MET experiment. The metaGE procedure accounts for the heterogeneity of quantitative trait loci (QTL) effects across the environmental conditions and allows the detection of QTL whose allelic effect variations are strongly correlated to environmental cofactors. We evaluated the performance of the proposed methodology and compared it to two competing procedures through simulations. We also applied metaGE to two emblematic examples: the detection of flowering QTLs whose effects are modulated by competition in Arabidopsis and the detection of yield QTLs impacted by drought stresses in maize. The procedure identified known and new QTLs, providing valuable insights into the genetic architecture of complex traits and QTL effects dependent on environmental stress conditions. The whole statistical approach is available as an R package.
Collapse
Affiliation(s)
- Annaïg De Walsche
- Génétique Quantitative et Evolution - Le Moulon, INRAE, CNRS, AgroParisTech, Université Paris-Saclay, Gif-sur-Yvette, France
- MIA Paris-Saclay, INRAE, AgroParisTech, Université Paris-Saclay, Palaiseau, France
| | | | - Renaud Rincent
- Génétique Quantitative et Evolution - Le Moulon, INRAE, CNRS, AgroParisTech, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Fabrice Roux
- LIPME, INRAE, CNRS, Université de Toulouse, Castanet-Tolosan, France
| | - Stéphane Nicolas
- Génétique Quantitative et Evolution - Le Moulon, INRAE, CNRS, AgroParisTech, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Claude Welcker
- LEPSE, Université de Montpellier, INRAE, Institut Agro, Montpellier, France
| | | | - Alain Charcosset
- Génétique Quantitative et Evolution - Le Moulon, INRAE, CNRS, AgroParisTech, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Tristan Mary-Huard
- Génétique Quantitative et Evolution - Le Moulon, INRAE, CNRS, AgroParisTech, Université Paris-Saclay, Gif-sur-Yvette, France
- MIA Paris-Saclay, INRAE, AgroParisTech, Université Paris-Saclay, Palaiseau, France
| |
Collapse
|
145
|
Fu Q, Dai H, Shen S, He Y, Zheng S, Jiang H, Gu P, Sun M, Zhu X, Xu K, Yang T. Interactions of genes with alcohol consumption affect insulin sensitivity and beta cell function. Diabetologia 2025; 68:116-127. [PMID: 39425782 DOI: 10.1007/s00125-024-06291-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/12/2024] [Accepted: 08/12/2024] [Indexed: 10/21/2024]
Abstract
AIMS/HYPOTHESIS Alcohol consumption has complex effects on diabetes and metabolic disease, but there is widespread heterogeneity within populations and the specific reasons are unclear. Genetic factors may play a role and warrant exploration. The aim of this study was to elucidate genetic variants modulating the impact of alcohol consumption on insulin sensitivity and pancreatic beta cell function within populations presenting normal glucose tolerance (NGT). METHODS We recruited 4194 volunteers in Nanjing, 854 in Jurong and an additional 5833 in Nanjing for Discovery cohorts 1 and 2 and a Validation cohort, respectively. We performed an OGTT on all participants, establishing a stringent NGT group, and then assessed insulin sensitivity and beta cell function. Alcohol consumption was categorised as abstinent, light-to-moderate (<210 g per week) or heavy (≥210 g per week). After excluding ineligible individuals, an exploratory genome-wide association study identified potential variants interacting with alcohol consumption in 1862 NGT individuals. These findings were validated in an additional cohort of 2169 NGT individuals. Cox proportional hazard regression was further employed to evaluate the effect of the interaction between the potential variants and alcohol consumption on the risk of type 2 diabetes within the UK Biobank cohort. RESULTS A significant correlation was observed between drinking levels and insulin sensitivity, accompanied by a consequent inverse relationship with insulin resistance and beta cell insulin secretion after adjusting for confounding factors in NGT individuals. However, no significant associations were noted in the disposition indexes. The interaction of variant rs56221195 with alcohol intake exhibited a pronounced effect on the liver insulin resistance index (LIRI) in the discovery set, corroborated in the validation set (combined p=1.32 × 10-11). Alcohol consumption did not significantly affect LIRI in rs56221195 wild-type (TT) carriers, but a strong negative association emerged in heterozygous (TA) and homozygous (AA) individuals. The rs56221195 variant also significantly interacts with alcohol consumption, influencing the total insulin secretion index INSR120 (the ratio of the AUC of insulin to glucose from 0 to 120 min) (p=2.06 × 10-9) but not disposition index. In the UK Biobank, we found a significant interaction between rs56221195 and alcohol consumption, which was linked to the risk of type 2 diabetes (HR 0.897, p=0.008). CONCLUSIONS/INTERPRETATION Our findings reveal the effects of the interaction of alcohol and rs56221195 on hepatic insulin sensitivity in NGT individuals. It is imperative to weigh potential benefits and detriments thoughtfully when considering alcohol consumption across diverse genetic backgrounds.
Collapse
Affiliation(s)
- Qi Fu
- Department of Endocrinology and Metabolism, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Hao Dai
- Department of Endocrinology and Metabolism, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Sipeng Shen
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Yunqiang He
- Department of Endocrinology and Metabolism, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Shuai Zheng
- Department of Endocrinology and Metabolism, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Hemin Jiang
- Department of Endocrinology and Metabolism, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Pan Gu
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Min Sun
- Department of Endocrinology and Metabolism, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Xiaowei Zhu
- Department of Endocrinology and Metabolism, the Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, China.
- Department of Endocrinology and Metabolism, Wuxi People's Hospital, Wuxi, China.
- Department of Endocrinology and Metabolism, Wuxi Medical Center, Nanjing Medical University, Wuxi, China.
| | - Kuanfeng Xu
- Department of Endocrinology and Metabolism, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
| | - Tao Yang
- Department of Endocrinology and Metabolism, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
- Department of Endocrinology and Metabolism, the Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, China.
- Department of Endocrinology and Metabolism, Wuxi People's Hospital, Wuxi, China.
- Department of Endocrinology and Metabolism, Wuxi Medical Center, Nanjing Medical University, Wuxi, China.
| |
Collapse
|
146
|
Zhou X, Cao H, Jiang Y, Chen Y, Zhong H, Fu WY, Lo RMN, Wong BWY, Cheng EYL, Mok KY, Kwok TCY, Mok VCT, Ip FCF, Miyashita A, Hara N, Ikeuchi T, Hardy J, Chen Y, Fu AKY, Ip NY. Transethnic analysis identifies SORL1 variants and haplotypes protective against Alzheimer's disease. Alzheimers Dement 2025; 21:e14214. [PMID: 39655505 PMCID: PMC11772736 DOI: 10.1002/alz.14214] [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: 04/28/2024] [Revised: 07/25/2024] [Accepted: 07/29/2024] [Indexed: 01/03/2025]
Abstract
INTRODUCTION The SORL1 locus exhibits protective effects against Alzheimer's disease (AD) across ancestries, yet systematic studies in diverse populations are sparse. METHODS Logistic regression identified AD-associated SORL1 haplotypes in East Asian (N = 5249) and European (N = 8588) populations. Association analysis between SORL1 haplotypes and AD-associated traits or plasma biomarkers was conducted. The effects of non-synonymous mutations were assessed in cell-based systems. RESULTS Protective SORL1 variants/haplotypes were identified in the East Asian and European populations. Haplotype Hap_A showed a strong protective effect against AD in East Asians, linked to less severe AD phenotypes, higher SORL1 transcript levels, and plasma proteomic changes. A missense variant within Hap_A, rs2282647-C allele, was linked to a lower risk of AD and decreased expression of a truncated SORL1 protein isoform. DISCUSSION Our transethnic analysis revealed key SORL1 haplotypes that exert protective effects against AD, suggesting mechanisms of the protective role of SORL1 in AD. HIGHLIGHTS We examined the AD-protective mechanisms of SORL1 in the general population across diverse ancestral backgrounds by jointly analyzing data from three East Asian cohorts (ie, mainland China, Hong Kong, and Japan) and a European cohort. Comparative analysis unveiled key ethnic-specific SORL1 genetic variants and haplotypes. Among these, the SORL1 minor haplotype, Hap_A, emerged as the primary AD-protective factor in East Asians. Hap_A exerts significant AD-protective effects in both APOE ε4 carriers and non-carriers. SORL1 haplotype Hap_A is associated with cognitive function, brain volume, and the activity of specific neuronal and immune-related pathways closely connected to AD risk. Protective variants within Hap_A are linked to increased SORL1 expression in human tissues. We identified an isoform-specific missense variant in Hap_A that modifies the function and levels of a truncated SORL1 protein isoform that is poorly investigated.
Collapse
Affiliation(s)
- Xiaopu Zhou
- Division of Life Science, State Key Laboratory of Molecular Neuroscience, Molecular Neuroscience CenterThe Hong Kong University of Science and TechnologyHong KongChina
- Hong Kong Center for Neurodegenerative DiseasesHong KongChina
- Guangdong Provincial Key Laboratory of Brain Science, Disease and Drug DevelopmentHKUST Shenzhen Research InstituteShenzhenGuangdongChina
| | - Han Cao
- Division of Life Science, State Key Laboratory of Molecular Neuroscience, Molecular Neuroscience CenterThe Hong Kong University of Science and TechnologyHong KongChina
| | - Yuanbing Jiang
- Division of Life Science, State Key Laboratory of Molecular Neuroscience, Molecular Neuroscience CenterThe Hong Kong University of Science and TechnologyHong KongChina
- Hong Kong Center for Neurodegenerative DiseasesHong KongChina
| | - Yuewen Chen
- Division of Life Science, State Key Laboratory of Molecular Neuroscience, Molecular Neuroscience CenterThe Hong Kong University of Science and TechnologyHong KongChina
- Guangdong Provincial Key Laboratory of Brain Science, Disease and Drug DevelopmentHKUST Shenzhen Research InstituteShenzhenGuangdongChina
- SIAT–HKUST Joint Laboratory for Brain ScienceShenzhenGuangdongChina
- The Brain Cognition and Brain Disease Institute, Shenzhen Institutes of Advanced Technology, Chinese Academy of SciencesShenzhen–Hong Kong Institute of Brain Science – Shenzhen Fundamental Research InstitutionsShenzhenGuangdongChina
| | - Huan Zhong
- Division of Life Science, State Key Laboratory of Molecular Neuroscience, Molecular Neuroscience CenterThe Hong Kong University of Science and TechnologyHong KongChina
- Hong Kong Center for Neurodegenerative DiseasesHong KongChina
| | - Wing Yu Fu
- Division of Life Science, State Key Laboratory of Molecular Neuroscience, Molecular Neuroscience CenterThe Hong Kong University of Science and TechnologyHong KongChina
| | - Ronnie Ming Nok Lo
- Division of Life Science, State Key Laboratory of Molecular Neuroscience, Molecular Neuroscience CenterThe Hong Kong University of Science and TechnologyHong KongChina
- Hong Kong Center for Neurodegenerative DiseasesHong KongChina
| | - Bonnie Wing Yan Wong
- Division of Life Science, State Key Laboratory of Molecular Neuroscience, Molecular Neuroscience CenterThe Hong Kong University of Science and TechnologyHong KongChina
- Hong Kong Center for Neurodegenerative DiseasesHong KongChina
| | - Elaine Yee Ling Cheng
- Division of Life Science, State Key Laboratory of Molecular Neuroscience, Molecular Neuroscience CenterThe Hong Kong University of Science and TechnologyHong KongChina
- Hong Kong Center for Neurodegenerative DiseasesHong KongChina
| | - Kin Ying Mok
- Division of Life Science, State Key Laboratory of Molecular Neuroscience, Molecular Neuroscience CenterThe Hong Kong University of Science and TechnologyHong KongChina
- Guangdong Provincial Key Laboratory of Brain Science, Disease and Drug DevelopmentHKUST Shenzhen Research InstituteShenzhenGuangdongChina
- Department of Molecular NeuroscienceUCL Institute of NeurologyLondonUK
| | - Timothy C. Y. Kwok
- Therese Pei Fong Chow Research Centre for Prevention of Dementia, Division of Geriatrics, Department of Medicine and TherapeuticsThe Chinese University of Hong KongHong KongChina
| | - Vincent C. T. Mok
- Gerald Choa Neuroscience Centre, Lui Che Woo Institute of Innovative Medicine, Therese Pei Fong Chow Research Centre for Prevention of Dementia, Division of Neurology, Department of Medicine and TherapeuticsThe Chinese University of Hong KongHong KongChina
| | - Fanny C. F. Ip
- Division of Life Science, State Key Laboratory of Molecular Neuroscience, Molecular Neuroscience CenterThe Hong Kong University of Science and TechnologyHong KongChina
- Hong Kong Center for Neurodegenerative DiseasesHong KongChina
- Guangdong Provincial Key Laboratory of Brain Science, Disease and Drug DevelopmentHKUST Shenzhen Research InstituteShenzhenGuangdongChina
| | | | - Akinori Miyashita
- Department of Molecular Genetics, Brain Research InstituteNiigata UniversityNiigataJapan
| | - Norikazu Hara
- Department of Molecular Genetics, Brain Research InstituteNiigata UniversityNiigataJapan
| | - Takeshi Ikeuchi
- Department of Molecular Genetics, Brain Research InstituteNiigata UniversityNiigataJapan
| | - John Hardy
- Hong Kong Center for Neurodegenerative DiseasesHong KongChina
- Department of Molecular NeuroscienceUCL Institute of NeurologyLondonUK
- Institute for Advanced StudyThe Hong Kong University of Science and TechnologyHong KongChina
| | - Yu Chen
- Division of Life Science, State Key Laboratory of Molecular Neuroscience, Molecular Neuroscience CenterThe Hong Kong University of Science and TechnologyHong KongChina
- Guangdong Provincial Key Laboratory of Brain Science, Disease and Drug DevelopmentHKUST Shenzhen Research InstituteShenzhenGuangdongChina
- SIAT–HKUST Joint Laboratory for Brain ScienceShenzhenGuangdongChina
- The Brain Cognition and Brain Disease Institute, Shenzhen Institutes of Advanced Technology, Chinese Academy of SciencesShenzhen–Hong Kong Institute of Brain Science – Shenzhen Fundamental Research InstitutionsShenzhenGuangdongChina
| | - Amy K. Y. Fu
- Division of Life Science, State Key Laboratory of Molecular Neuroscience, Molecular Neuroscience CenterThe Hong Kong University of Science and TechnologyHong KongChina
- Hong Kong Center for Neurodegenerative DiseasesHong KongChina
- Guangdong Provincial Key Laboratory of Brain Science, Disease and Drug DevelopmentHKUST Shenzhen Research InstituteShenzhenGuangdongChina
- SIAT–HKUST Joint Laboratory for Brain ScienceShenzhenGuangdongChina
| | - Nancy Y. Ip
- Division of Life Science, State Key Laboratory of Molecular Neuroscience, Molecular Neuroscience CenterThe Hong Kong University of Science and TechnologyHong KongChina
- Hong Kong Center for Neurodegenerative DiseasesHong KongChina
- Guangdong Provincial Key Laboratory of Brain Science, Disease and Drug DevelopmentHKUST Shenzhen Research InstituteShenzhenGuangdongChina
- SIAT–HKUST Joint Laboratory for Brain ScienceShenzhenGuangdongChina
| |
Collapse
|
147
|
Brotman SM, El-Sayed Moustafa JS, Guan L, Broadaway KA, Wang D, Jackson AU, Welch R, Currin KW, Tomlinson M, Vadlamudi S, Stringham HM, Roberts AL, Lakka TA, Oravilahti A, Fernandes Silva L, Narisu N, Erdos MR, Yan T, Bonnycastle LL, Raulerson CK, Raza Y, Yan X, Parker SCJ, Kuusisto J, Pajukanta P, Tuomilehto J, Collins FS, Boehnke M, Love MI, Koistinen HA, Laakso M, Mohlke KL, Small KS, Scott LJ. Adipose tissue eQTL meta-analysis highlights the contribution of allelic heterogeneity to gene expression regulation and cardiometabolic traits. Nat Genet 2025; 57:180-192. [PMID: 39747594 DOI: 10.1038/s41588-024-01982-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Accepted: 10/11/2024] [Indexed: 01/04/2025]
Abstract
Complete characterization of the genetic effects on gene expression is needed to elucidate tissue biology and the etiology of complex traits. In the present study, we analyzed 2,344 subcutaneous adipose tissue samples and identified 34,774 conditionally distinct expression quantitative trait locus (eQTL) signals at 18,476 genes. Over half of eQTL genes exhibited at least two eQTL signals. Compared with primary eQTL signals, nonprimary eQTL signals had lower effect sizes, lower minor allele frequencies and less promoter enrichment; they corresponded to genes with higher heritability and higher tolerance for loss of function. Colocalization of eQTLs with genome-wide association study (GWAS) signals for 28 cardiometabolic traits identified 1,835 genes. Inclusion of nonprimary eQTL signals increased discovery of colocalized GWAS-eQTL signals by 46%. Furthermore, 21 genes with ≥2 colocalized GWAS-eQTL signals showed a mediating gene dosage effect on the GWAS trait. Thus, expanded eQTL identification reveals more mechanisms underlying complex traits and improves understanding of the complexity of gene expression regulation.
Collapse
Affiliation(s)
- Sarah M Brotman
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | | | - Li Guan
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - K Alaine Broadaway
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Dongmeng Wang
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Anne U Jackson
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Ryan Welch
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Kevin W Currin
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Max Tomlinson
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
- Department of Medical and Molecular Genetics, King's College London, London, UK
| | | | - Heather M Stringham
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Amy L Roberts
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Timo A Lakka
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
- Foundation for Research in Health Exercise and Nutrition, Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Anniina Oravilahti
- Institute of Clinical Medicine, Kuopio University Hospital, University of Eastern Finland, Kuopio, Finland
| | - Lilian Fernandes Silva
- Institute of Clinical Medicine, Kuopio University Hospital, University of Eastern Finland, Kuopio, Finland
| | - Narisu Narisu
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Michael R Erdos
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Tingfen Yan
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Lori L Bonnycastle
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | | | - Yasrab Raza
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Xinyu Yan
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Stephen C J Parker
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Johanna Kuusisto
- Department of Medicine and Clinical Research, Kuopio University Hospital, Kuopio, Finland
| | - Päivi Pajukanta
- Department of Human Genetics and Institute for Precision Health, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Jaakko Tuomilehto
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Francis S Collins
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Michael I Love
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC, USA
| | - Heikki A Koistinen
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
- University of Helsinki and Department of Medicine, Helsinki University Hospital, Helsinki, Finland
- Minerva Foundation Institute for Medical Research, Helsinki, Finland
| | - Markku Laakso
- Institute of Clinical Medicine, Kuopio University Hospital, University of Eastern Finland, Kuopio, Finland
- Department of Medicine and Clinical Research, Kuopio University Hospital, Kuopio, Finland
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA.
| | - Kerrin S Small
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
| | - Laura J Scott
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA.
| |
Collapse
|
148
|
Cosin-Tomas M, Hoang T, Qi C, Monasso GS, Langdon R, Kebede Merid S, Calas L, de Prado-Bert P, Richmond R, Jaddoe VV, Duijts L, Wright J, Annesi-Maesano I, Grazuleviciene R, Karachaliou M, Koppelman GH, Melén E, Gruzieva O, Vrijheid M, Yousefi P, Felix JF, London SJ, Bustamante M. Association of exposure to second-hand smoke during childhood with blood DNA methylation. ENVIRONMENT INTERNATIONAL 2025; 195:109204. [PMID: 39693780 DOI: 10.1016/j.envint.2024.109204] [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: 08/30/2024] [Revised: 11/11/2024] [Accepted: 12/09/2024] [Indexed: 12/20/2024]
Abstract
INTRODUCTION By recent estimates, 40% of children worldwide are exposed to second-hand smoke (SHS), which has been associated with adverse health outcomes. While numerous studies have linked maternal smoking during pregnancy (MSDP) to widespread differences in child blood DNA methylation (DNAm), research specifically examining postnatal SHS exposure remains sparse. To address this gap, we conducted epigenome-wide meta-analyses to identify associations of postnatal SHS and child blood DNAm. METHODS Six cohorts from the Pregnancy And Childhood Epigenetics (PACE) Consortium (total N = 2,695), with SHS data and child blood DNAm (aged 7-9 years) measured with the Illumina 450K array were included in the meta-analysis. Linear regression models adjusted for covariates were fitted to examine the association between the number of household smokers in postnatal life (0, 1, 2+) and child blood DNAm. Sensitivity models without adjusting for MSDP and restricted to mothers who did not smoke during pregnancy were evaluated. RESULTS Our analysis revealed significant associations (False Discovery Rate < 0.05) between household postnatal SHS exposure and DNAm at 11 CpGs in exposed children. Nine CpGs were mapped to genes (MYO1G, FAM184B, CTDSPL2, LTBP3, PDE10A, and FIBCD1), while 2 CpGs were located in open sea regions. Notably, all except 2 CpGs (mapped to FIBCD1 and CTDSPL2) have previously been linked to either personal smoking habits or in utero exposure to smoking. The models restricted to non-smoking mothers provided similar results. Importantly, several of these CpGs and their associated genes are implicated in conditions exacerbated by or directly linked to SHS. CONCLUSIONS Our findings highlight the potential biological effects of SHS on blood DNAm. These findings support further research on epigenetic factors mediating deleterious effects of SHS on child health and call for public health policies aimed at reducing exposure, particularly in environments where children are present.
Collapse
Affiliation(s)
- Marta Cosin-Tomas
- ISGlobal, Barcelona, Catalonia, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Catalonia, Spain; Centro de investigación biomédica en red en epidemiología y salud pública (CIBERESP), Madrid, Spain.
| | - Thanh Hoang
- Division of Intramural Research, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA; Department of Pediatrics, Division of Hematology-Oncology, Baylor College of Medicine, Houston, TX, USA; Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, USA; Cancer and Hematology Center, Texas Children's Hospital, Houston, TX, USA
| | - Cancan Qi
- Groningen Research Institute for Asthma and COPD, Groningen, the Netherlands; Department of Pediatric Pulmonology and Pediatric Allergology, Beatrix Children's Hospital, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands; Microbiome Medicine Center, Department of Laboratory Medicine, ZhuJiang Hospital, Southern Medical University, Guangzhou, China
| | - Giulietta S Monasso
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Ryan Langdon
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK; Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | - Simon Kebede Merid
- Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden
| | - Lucinda Calas
- Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Center for Research in Epidemiology and StatisticS (CRESS), F-75004, Paris, France
| | - Paula de Prado-Bert
- ISGlobal, Barcelona, Catalonia, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Catalonia, Spain; Centro de investigación biomédica en red en epidemiología y salud pública (CIBERESP), Madrid, Spain
| | - Rebecca Richmond
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK; Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | - Vincent Vw Jaddoe
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Liesbeth Duijts
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of Neonatal and Pediatric Intensive Care, division of Neonatology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - John Wright
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
| | - Isabella Annesi-Maesano
- Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Center for Research in Epidemiology and StatisticS (CRESS), F-75004, Paris, France
| | | | - Marianna Karachaliou
- ISGlobal, Barcelona, Catalonia, Spain; Clinic of preventive and Social Medicine, Medical School, University of Crete, Iraklio, Greece
| | - Gerard H Koppelman
- Groningen Research Institute for Asthma and COPD, Groningen, the Netherlands; Department of Pediatric Pulmonology and Pediatric Allergology, Beatrix Children's Hospital, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Erik Melén
- Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden; Sachs' Children's Hospital, Stockholm, Sweden
| | - Olena Gruzieva
- Centre for Occupational and Environmental Medicine, Region Stockholm, Stockholm, Sweden; Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Martine Vrijheid
- ISGlobal, Barcelona, Catalonia, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Catalonia, Spain; Centro de investigación biomédica en red en epidemiología y salud pública (CIBERESP), Madrid, Spain
| | - Paul Yousefi
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK; Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK; NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol, Bristol, UK
| | - Janine F Felix
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.
| | - Stephanie J London
- Division of Intramural Research, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Mariona Bustamante
- ISGlobal, Barcelona, Catalonia, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Catalonia, Spain; Centro de investigación biomédica en red en epidemiología y salud pública (CIBERESP), Madrid, Spain
| |
Collapse
|
149
|
Jia G, Chen Z, Ping J, Cai Q, Tao R, Li C, Bauer JA, Xie Y, Ambs S, Barnard ME, Chen Y, Choi JY, Gao YT, Garcia-Closas M, Gu J, Hu JJ, Iwasaki M, John EM, Kweon SS, Li CI, Matsuda K, Matsuo K, Nathanson KL, Nemesure B, Olopade OI, Pal T, Park SK, Park B, Press MF, Sanderson M, Sandler DP, Shen CY, Troester MA, Yao S, Zheng Y, Ahearn T, Brewster AM, Falusi A, Hennis AJM, Ito H, Kubo M, Lee ES, Makumbi T, Ndom P, Noh DY, O'Brien KM, Ojengbede O, Olshan AF, Park MH, Reid S, Yamaji T, Zirpoli G, Butler EN, Huang M, Low SK, Obafunwa J, Weinberg CR, Zhang H, Zhao H, Cote ML, Ambrosone CB, Huo D, Li B, Kang D, Palmer JR, Shu XO, Haiman CA, Guo X, Long J, Zheng W. Refining breast cancer genetic risk and biology through multi-ancestry fine-mapping analyses of 192 risk regions. Nat Genet 2025; 57:80-87. [PMID: 39753771 DOI: 10.1038/s41588-024-02031-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Accepted: 11/11/2024] [Indexed: 01/16/2025]
Abstract
Genome-wide association studies have identified approximately 200 genetic risk loci for breast cancer, but the causal variants and target genes are mostly unknown. We sought to fine-map all known breast cancer risk loci using genome-wide association study data from 172,737 female breast cancer cases and 242,009 controls of African, Asian and European ancestry. We identified 332 independent association signals for breast cancer risk, including 131 signals not reported previously, and for 50 of them, we narrowed the credible causal variants down to a single variant. Analyses integrating functional genomics data identified 195 putative susceptibility genes, enriched in PI3K/AKT, TNF/NF-κB, p53 and Wnt/β-catenin pathways. Single-cell RNA sequencing or in vitro experiment data provided additional functional evidence for 105 genes. Our study uncovered large numbers of association signals and candidate susceptibility genes for breast cancer, uncovered breast cancer genetics and biology, and supported the value of including multi-ancestry data in fine-mapping analyses.
Collapse
Affiliation(s)
- Guochong Jia
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Zhishan Chen
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jie Ping
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Qiuyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Ran Tao
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Chao Li
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Joshua A Bauer
- Department of Biochemistry, Vanderbilt Institute of Chemical Biology, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Yuhan Xie
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
| | - Stefan Ambs
- Laboratory of Human Carcinogenesis, Center of Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | | | - Yu Chen
- Division of Epidemiology, Department of Population Health, NYU Grossman School of Medicine, New York, NY, USA
| | - Ji-Yeob Choi
- Department of Biomedical Sciences, Seoul National University Graduate School, Seoul, South Korea
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, South Korea
| | - Yu-Tang Gao
- State Key Laboratory of Oncogene and Related Genes and Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | | | - Jian Gu
- Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jennifer J Hu
- Department of Public Health Sciences, University of Miami School of Medicine, Miami, FL, USA
| | - Motoki Iwasaki
- Division of Epidemiology, National Cancer Center Institute for Cancer Control, Tokyo, Japan
| | - Esther M John
- Department of Epidemiology and Population Health and Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Sun-Seog Kweon
- Department of Preventive Medicine, Chonnam National University Medical School, Hwasun, South Korea
- Jeonnam Regional Cancer Center, Chonnam National University Hwasun Hospital, Hwasun, South Korea
| | - Christopher I Li
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Koichi Matsuda
- Laboratory of Clinical Genome Sequencing, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Keitaro Matsuo
- Division of Cancer Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya, Japan
- Division of Cancer Epidemiology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Katherine L Nathanson
- Division of Hematology/Oncology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Basser Center for BRCA, Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Barbara Nemesure
- Department of Family, Population and Preventive Medicine, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY, USA
| | - Olufunmilayo I Olopade
- Center for Clinical Cancer Genetics and Global Health, Department of Medicine, The University of Chicago, Chicago, IL, USA
| | - Tuya Pal
- Division of Genetic Medicine, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Sue K Park
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, South Korea
- Integrated Major in Innovative Medical Science, Seoul National University College of Medicine, Seoul, South Korea
- Cancer Research Institute, Seoul National University, Seoul, South Korea
| | - Boyoung Park
- Department of Preventive Medicine, Hanyang University College of Medicine, Seoul, South Korea
| | - Michael F Press
- Department of Pathology, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA
| | - Maureen Sanderson
- Department of Family and Community Medicine, Meharry Medical College, Nashville, TN, USA
| | - Dale P Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Chen-Yang Shen
- College of Public Health, China Medical University, Taichong, Taiwan
- Taiwan Biobank, Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Melissa A Troester
- Department of Epidemiology and Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Song Yao
- Department of Cancer Prevention and Control, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | - Ying Zheng
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Thomas Ahearn
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Abenaa M Brewster
- Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Adeyinka Falusi
- Genetic and Bioethics Research Unit, Institute for Advanced Medical Research and Training, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Anselm J M Hennis
- Department of Family, Population and Preventive Medicine, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY, USA
- George Alleyne Chronic Disease Research Centre, University of the West Indies, Bridgetown, Barbados
| | - Hidemi Ito
- Division of Cancer Information and Control, Aichi Cancer Center Research Institute, Nagoya, Japan
- Department of Descriptive Cancer Epidemiology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Michiaki Kubo
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Eun-Sook Lee
- National Cancer Center Graduate School of Cancer Science and Policy, Goyang, South Korea
- Hospital, National Cancer Center, Goyang, South Korea
| | | | - Paul Ndom
- Yaounde General Hospital, Yaounde, Cameroon
| | - Dong-Young Noh
- College of Medicine, Cancer Research Institute, Seoul National University, Seoul, South Korea
- Department of Surgery, Seoul National University Hospital, Seoul, South Korea
| | - Katie M O'Brien
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Oladosu Ojengbede
- Center for Population and Reproductive Health, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Andrew F Olshan
- Department of Epidemiology and Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Min-Ho Park
- Department of Surgery, Chonnam National University Medical School, Gwangju, South Korea
| | - Sonya Reid
- Division of Hematology and Oncology, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Taiki Yamaji
- Division of Epidemiology, National Cancer Center Institute for Cancer Control, Tokyo, Japan
| | - Gary Zirpoli
- Slone Epidemiology Center, Boston University, Boston, MA, USA
| | - Ebonee N Butler
- Department of Epidemiology and Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Maosheng Huang
- Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Siew-Kee Low
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - John Obafunwa
- Department of Pathology and Forensic Medicine, Lagos State University Teaching Hospital, Lagos, Nigeria
| | - Clarice R Weinberg
- Biostatistics and Computational Biology Branch, National Institutes of Environmental Health Sciences, Research Triangle Park, NC, USA
| | - Haoyu Zhang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Hongyu Zhao
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
| | - Michelle L Cote
- Fairbanks School of Public Health, Indiana University, Indianapolis, IN, USA
- Simon Comprehensive Cancer Center, Indianapolis, IN, USA
| | - Christine B Ambrosone
- Department of Cancer Prevention and Control, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | - Dezheng Huo
- Department of Public Health Sciences, The University of Chicago, Chicago, IL, USA
| | - Bingshan Li
- Department of Molecular Physiology & Biophysics, Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA
| | - Daehee Kang
- Department of Biomedical Sciences, Seoul National University Graduate School, Seoul, South Korea
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, South Korea
| | - Julie R Palmer
- Slone Epidemiology Center, Boston University, Boston, MA, USA
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Christopher A Haiman
- Department of Preventive Medicine, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Xingyi Guo
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jirong Long
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA.
| |
Collapse
|
150
|
Guo X, Feng Y, Ji X, Jia N, Maimaiti A, Lai J, Wang Z, Yang S, Hu S. Shared genetic architecture and bidirectional clinical risks within the psycho-metabolic nexus. EBioMedicine 2025; 111:105530. [PMID: 39731856 PMCID: PMC11743124 DOI: 10.1016/j.ebiom.2024.105530] [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: 09/05/2024] [Revised: 12/12/2024] [Accepted: 12/12/2024] [Indexed: 12/30/2024] Open
Abstract
BACKGROUND Increasing evidence suggests a complex interplay between psychiatric disorders and metabolic dysregulations. However, most research has been limited to specific disorder pairs, leaving a significant gap in our understanding of the broader psycho-metabolic nexus. METHODS This study leveraged large-scale cohort data and genome-wide association study (GWAS) summary statistics, covering 8 common psychiatric disorders and 43 metabolic traits. We introduced a comprehensive analytical strategy to identify shared genetic bases sequentially, from key genetic correlation regions to local pleiotropy and pleiotropic genes. Finally, we developed polygenic risk score (PRS) models to translate these findings into clinical applications. FINDINGS We identified significant bidirectional clinical risks between psychiatric disorders and metabolic dysregulations among 310,848 participants from the UK Biobank. Genetic correlation analysis confirmed 104 robust trait pairs, revealing 1088 key genomic regions, including critical hotspots such as chr3: 47588462-50387742. Cross-trait meta-analysis uncovered 388 pleiotropic single nucleotide variants (SNVs) and 126 shared causal variants. Among variants, 45 novel SNVs were associated with psychiatric disorders and 75 novel SNVs were associated with metabolic traits, shedding light on new targets to unravel the mechanism of comorbidity. Notably, RBM6, a gene involved in alternative splicing and cellular stress response regulation, emerged as a key pleiotropic gene. When psychiatric and metabolic genetic information were integrated, PRS models demonstrated enhanced predictive power. INTERPRETATION The study highlights the intertwined genetic and clinical relationships between psychiatric disorders and metabolic dysregulations, emphasising the need for integrated approaches in diagnosis and treatment. FUNDING The National Key Research and Development Program of China (2023YFC2506200, SHH). The National Natural Science Foundation of China (82273741, SY).
Collapse
Affiliation(s)
- Xiaonan Guo
- Department of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Yu Feng
- Department of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China; Department of Psychiatry, Melbourne Neuropsychiatry Centre, The University of Melbourne, Carlton South, VIC, Australia
| | - Xiaolong Ji
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Ningning Jia
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, Jilin, China
| | - Aierpati Maimaiti
- Department of Neurosurgery, Xinjiang Medical University Affiliated First Hospital, Urumqi, Xinjiang, China
| | - Jianbo Lai
- Department of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Zheng Wang
- Department of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
| | - Sheng Yang
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China.
| | - Shaohua Hu
- Department of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China; Nanhu Brain-Computer Interface Institute, Hangzhou, Zhejiang, China; Zhejiang Key Laboratory of Precision Psychiatry, Hangzhou, 310003, China; Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 311121, China; Brain Research Institute of Zhejiang University, Hangzhou, 310058, China; MOE Frontier Science Center for Brain Science and Brain-Machine Integration, Zhejiang University School of Medicine, Hangzhou, 310058, China; Department of Psychology and Behavioral Sciences, Graduate School, Zhejiang University, Hangzhou, 310058, China.
| |
Collapse
|