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Purdue MP, Dutta D, Machiela MJ, Gorman BR, Winter T, Okuhara D, Cleland S, Ferreiro-Iglesias A, Scheet P, Liu A, Wu C, Antwi SO, Larkin J, Zequi SC, Sun M, Hikino K, Hajiran A, Lawson KA, Cárcano F, Blanchet O, Shuch B, Nepple KG, Margue G, Sundi D, Diver WR, Folgueira MAAK, van Bokhoven A, Neffa F, Brown KM, Hofmann JN, Rhee J, Yeager M, Cole NR, Hicks BD, Manning MR, Hutchinson AA, Rothman N, Huang WY, Linehan WM, Lori A, Ferragu M, Zidane-Marinnes M, Serrano SV, Magnabosco WJ, Vilas A, Decia R, Carusso F, Graham LS, Anderson K, Bilen MA, Arciero C, Pellegrin I, Ricard S, Scelo G, Banks RE, Vasudev NS, Soomro N, Stewart GD, Adeyoju A, Bromage S, Hrouda D, Gibbons N, Patel P, Sullivan M, Protheroe A, Nugent FI, Fournier MJ, Zhang X, Martin LJ, Komisarenko M, Eisen T, Cunningham SA, Connolly DC, Uzzo RG, Zaridze D, Mukeria A, Holcatova I, Hornakova A, Foretova L, Janout V, Mates D, Jinga V, Rascu S, Mijuskovic M, Savic S, Milosavljevic S, Gaborieau V, Abedi-Ardekani B, McKay J, Johansson M, Phouthavongsy L, Hayman L, Li J, Lungu I, Bezerra SM, Souza AG, Sares CTG, Reis RB, Gallucci FP, Cordeiro MD, Pomerantz M, Lee GSM, Freedman ML, Jeong A, Greenberg SE, Sanchez A, Thompson RH, Sharma V, Thiel DD, Ball CT, Abreu D, Lam ET, Nahas WC, Master VA, Patel AV, Bernhard JC, Freedman ND, Bigot P, Reis RM, Colli LM, Finelli A, Manley BJ, Terao C, Choueiri TK, Carraro DM, Houlston R, Eckel-Passow JE, Abbosh PH, Ganna A, Brennan P, Gu J, Chanock SJ. Multi-ancestry genome-wide association study of kidney cancer identifies 63 susceptibility regions. Nat Genet 2024; 56:809-818. [PMID: 38671320 DOI: 10.1038/s41588-024-01725-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 03/13/2024] [Indexed: 04/28/2024]
Abstract
Here, in a multi-ancestry genome-wide association study meta-analysis of kidney cancer (29,020 cases and 835,670 controls), we identified 63 susceptibility regions (50 novel) containing 108 independent risk loci. In analyses stratified by subtype, 52 regions (78 loci) were associated with clear cell renal cell carcinoma (RCC) and 6 regions (7 loci) with papillary RCC. Notably, we report a variant common in African ancestry individuals ( rs7629500 ) in the 3' untranslated region of VHL, nearly tripling clear cell RCC risk (odds ratio 2.72, 95% confidence interval 2.23-3.30). In cis-expression quantitative trait locus analyses, 48 variants from 34 regions point toward 83 candidate genes. Enrichment of hypoxia-inducible factor-binding sites underscores the importance of hypoxia-related mechanisms in kidney cancer. Our results advance understanding of the genetic architecture of kidney cancer, provide clues for functional investigation and enable generation of a validated polygenic risk score with an estimated area under the curve of 0.65 (0.74 including risk factors) among European ancestry individuals.
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Affiliation(s)
- Mark P Purdue
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA.
| | - Diptavo Dutta
- Integrative Tumor Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Mitchell J Machiela
- Integrative Tumor Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | | | - Timothy Winter
- Laboratory of Genetic Susceptibility, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | | | | | | | - Paul Scheet
- Department of Epidemiology, Division of Cancer Prevention and Population Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Aoxing Liu
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Chao Wu
- Biosample Repository, Fox Chase Cancer Center-Temple Health, Philadelphia, PA, USA
| | - Samuel O Antwi
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL, USA
| | - James Larkin
- Department of Medical Oncology, Royal Marsden NHS Foundation Trust, London, UK
| | - Stênio C Zequi
- Department of Urology, A.C. Camargo Cancer Center, São Paulo, Brazil
- National Institute for Science and Technology in Oncogenomics and Therapeutic Innovation INCIT-INOTE, São Paulo, Brazil
- Latin American Renal Cancer Group, São Paulo, Brazil
- Department of Surgery, Division of Urology, São Paulo Federal University, São Paulo, Brazil
| | - Maxine Sun
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Keiko Hikino
- Laboratory for Pharmacogenomics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Ali Hajiran
- Department of Urology, Division of Urologic Oncology, West Virginia University Cancer Institute, Morgantown, WV, USA
| | - Keith A Lawson
- Department of Surgical Oncology, Division of Urology, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Flavio Cárcano
- Department of Medical Oncology, Barretos Cancer Hospital, Barretos, Brazil
| | | | - Brian Shuch
- Department of Urology, UCLA Jonsson Comprehensive Cancer Center, Los Angeles, CA, USA
| | - Kenneth G Nepple
- Department of Urology, Holden Comprehensive Cancer Center, University of Iowa, Iowa City, IA, USA
| | - Gaëlle Margue
- Department of Urology, CHU Bordeaux, Bordeaux, France
| | - Debasish Sundi
- Department of Urology, The Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - W Ryan Diver
- Department of Population Science, American Cancer Society, Atlanta, GA, USA
| | - Maria A A K Folgueira
- Departments of Radiology and Oncology, Comprehensive Center for Precision Oncology-C2PO, Centro de Investigação Translacional em Oncologia, Instituto do Cancer do Estado de São Paulo, Hospital das Clinicas, Faculdade de Medicina Universidade de São Paulo, São Paulo, Brazil
| | - Adrie van Bokhoven
- Department of Pathology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | | | - Kevin M Brown
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Jonathan N Hofmann
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Jongeun Rhee
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Meredith Yeager
- Cancer Genomics Research Laboratory, Frederick National Laboratory, Rockville, MD, USA
| | - Nathan R Cole
- Cancer Genomics Research Laboratory, Frederick National Laboratory, Rockville, MD, USA
| | - Belynda D Hicks
- Cancer Genomics Research Laboratory, Frederick National Laboratory, Rockville, MD, USA
| | - Michelle R Manning
- Cancer Genomics Research Laboratory, Frederick National Laboratory, Rockville, MD, USA
| | - Amy A Hutchinson
- Cancer Genomics Research Laboratory, Frederick National Laboratory, Rockville, MD, USA
| | - Nathaniel Rothman
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Wen-Yi Huang
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - W Marston Linehan
- Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
| | - Adriana Lori
- Department of Population Science, American Cancer Society, Atlanta, GA, USA
| | | | | | - Sérgio V Serrano
- Department of Medical Oncology, Barretos Cancer Hospital, Barretos, Brazil
| | | | - Ana Vilas
- Department of Pathology, Hospital Pasteur, Montevideo, Uruguay
| | - Ricardo Decia
- Department of Urology, Hospital Pasteur, Montevideo, Uruguay
| | | | - Laura S Graham
- Department of Medicine, Division of Medical Oncology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Kyra Anderson
- Oncology Clinical Research Support Team, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Mehmet A Bilen
- Department of Hematology and Medical Oncology, Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA, USA
| | - Cletus Arciero
- Department of Surgery, Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA, USA
| | | | - Solène Ricard
- Department of Urology, CHU Bordeaux, Bordeaux, France
| | - Ghislaine Scelo
- Observational and Pragmatic Research Institute Pte Ltd, Singapore, Singapore
| | - Rosamonde E Banks
- Leeds Institute of Medical Research at St James's, University of Leeds, Leeds, UK
| | - Naveen S Vasudev
- Department of Oncology, Leeds Institute of Medical Research at St James's, University of Leeds, Leeds, UK
| | - Naeem Soomro
- Department of Urology, Newcastle Hospitals NHS Foundation Trust, Newcastle, UK
| | - Grant D Stewart
- Department of Urology, Western General Hospital, NHS Lothian, Edinburgh, UK
- Department of Surgery, University of Cambridge, Cambridge, UK
| | - Adebanji Adeyoju
- Department of Urology, Stockport NHS Foundation Trust, Stockport, UK
| | - Stephen Bromage
- Department of Urology, Stockport NHS Foundation Trust, Stockport, UK
| | - David Hrouda
- Department of Urology, Imperial College Healthcare NHS Trust, London, UK
| | - Norma Gibbons
- Department of Urology, Imperial College Healthcare NHS Trust, London, UK
| | - Poulam Patel
- Division of Oncology, University of Nottingham, Nottingham, UK
| | - Mark Sullivan
- Department of Urology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Andrew Protheroe
- Department of Oncology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Francesca I Nugent
- Department of Urology, Holden Comprehensive Cancer Center, University of Iowa, Iowa City, IA, USA
| | | | - Xiaoyu Zhang
- Department of Surgical Oncology, Division of Urology, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Lisa J Martin
- Department of Surgical Oncology, Division of Urology, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Maria Komisarenko
- Department of Surgical Oncology, Division of Urology, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Timothy Eisen
- Department of Oncology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Sonia A Cunningham
- Department of Epidemiology, Division of Cancer Prevention and Population Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Denise C Connolly
- Cancer Signaling and Microenvironment, Biosample Repository Facility, Fox Chase Cancer Center-Temple Health, Philadelphia, PA, USA
| | - Robert G Uzzo
- Department of Urology, Fox Chase Cancer Center-Temple Health, Philadelphia, PA, USA
| | - David Zaridze
- Department of Clinical Epidemiology, N.N. Blokhin National Medical Research Centre of Oncology, Moscow, Russia
| | - Anush Mukeria
- Department of Clinical Epidemiology, N.N. Blokhin National Medical Research Centre of Oncology, Moscow, Russia
| | - Ivana Holcatova
- Institute of Public Health and Preventive Medicine, Second Faculty of Medicine, Charles University, Prague, Czech Republic
- Department of Oncology, Second Faculty of Medicine and University Hospital Motol, Charles University, Prague, Czech Republic
| | - Anna Hornakova
- Institute of Hygiene and Epidemiology, First Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Lenka Foretova
- Department of Cancer Epidemiology and Genetics, Masaryk Memorial Cancer Institute, Brno, Czech Republic
| | - Vladimir Janout
- Faculty of Health Sciences, Palacky University, Olomouc, Czech Republic
| | - Dana Mates
- Department of Occupational Health and Toxicology, National Center for Environmental Risk Monitoring, National Institute of Public Health, Bucharest, Romania
| | - Viorel Jinga
- Urology Department, Academy of Romanian Scientists, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
| | - Stefan Rascu
- Urology Department, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
| | - Mirjana Mijuskovic
- Clinic of Nephrology, Faculty of Medicine, Military Medical Academy, Belgrade, Serbia
| | - Slavisa Savic
- Department of Urology, Clinical Hospital Center Dr Dragisa Misovic Dedinje, Belgrade, Serbia
| | - Sasa Milosavljevic
- International Organisation for Cancer Prevention and Research, Belgrade, Serbia
| | - Valérie Gaborieau
- Genomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France
| | | | - James McKay
- Genomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France
| | - Mattias Johansson
- Genomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France
| | - Larry Phouthavongsy
- Ontario Tumour Bank, Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Lindsay Hayman
- Diagnostic Development Program, Tissue Portal, Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Jason Li
- Diagnostic Development Program, Tissue Portal, Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Ilinca Lungu
- Ontario Tumour Bank, Ontario Institute for Cancer Research, Toronto, Ontario, Canada
- Diagnostic Development Program, Tissue Portal, Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | | | - Aline G Souza
- Departments of Medical Imaging, Hematology and Oncology, Division of Medical Oncology, Ribeirao Preto Medical School, University of São Paulo, Ribeirao Preto, Brazil
| | - Claudia T G Sares
- Departments of Surgery and Anatomy, Division of Urology, Ribeirao Preto Medical School, University of São Paulo, Ribeirao Preto, Brazil
| | - Rodolfo B Reis
- Departments of Surgery and Anatomy, Division of Urology, Ribeirao Preto Medical School, University of São Paulo, Ribeirao Preto, Brazil
| | - Fabio P Gallucci
- Surgery Department, Urology Division, Instituto do Cancer do Estado de São Paulo, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
| | - Mauricio D Cordeiro
- Surgery Department, Urology Division, Instituto do Cancer do Estado de São Paulo, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
| | | | - Gwo-Shu M Lee
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Matthew L Freedman
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Dana-Farber Cancer Institute, Boston, MA, USA
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of MIT and Harvard, Boston, MA, USA
| | - Anhyo Jeong
- Department of Urology, UCLA Jonsson Comprehensive Cancer Center, Los Angeles, CA, USA
| | - Samantha E Greenberg
- Department of Population Sciences, Genetic Counseling Shared Resource, Huntsman Cancer Institute, Salt Lake City, UT, USA
| | - Alejandro Sanchez
- Department of Surgery, Division of Urology, Huntsman Cancer Institute and University of Utah, Salt Lake City, UT, USA
| | | | - Vidit Sharma
- Department of Urology, Mayo Clinic, Rochester, MN, USA
| | - David D Thiel
- Department of Urology, Mayo Clinic, Jacksonville, FL, USA
| | - Colleen T Ball
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL, USA
| | - Diego Abreu
- Department of Urology, Hospital Pasteur, Montevideo, Uruguay
| | - Elaine T Lam
- Department of Medicine, Division of Medical Oncology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - William C Nahas
- Surgery Department, Urology Division, Instituto do Cancer do Estado de São Paulo, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
| | - Viraj A Master
- Department of Urology, Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA, USA
| | - Alpa V Patel
- Department of Population Science, American Cancer Society, Atlanta, GA, USA
| | | | - Neal D Freedman
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Pierre Bigot
- Department of Urology, CHU Angers, Angers, France
| | - Rui M Reis
- Molecular Oncology Research Center, Barretos Cancer Hospital, Barretos, Brazil
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal
| | - Leandro M Colli
- Departament of Medical Image, Hematology and Oncology, Division of Medical Oncology, Ribeirao Preto Medical School, University of São Paulo, Ribeirao Preto, Brazil
| | - Antonio Finelli
- Department of Surgical Oncology, Division of Urology, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Brandon J Manley
- Genitourinary Oncology Program, Moffitt Cancer Center, Tampa, FL, USA
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Toni K Choueiri
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Dirce M Carraro
- Clinical and Functional Genomics Group, CIPE (International Research Center), A.C. Camargo Cancer Center, São Paulo, Brazil
| | - Richard Houlston
- Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, UK
| | | | - Philip H Abbosh
- Department of Nuclear Dynamics and Cancer, Fox Chase Cancer Center-Temple Health, Philadelphia, PA, USA
| | - Andrea Ganna
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Paul Brennan
- Genomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France
| | - Jian Gu
- Department of Epidemiology, Division of Cancer Prevention and Population Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Stephen J Chanock
- Laboratory of Genetic Susceptibility, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA.
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Gorman BR, Francis M, Nealon CL, Halladay CW, Duro N, Markianos K, Genovese G, Hysi PG, Choquet H, Afshari NA, Li YJ, Gaziano JM, Hung AM, Wu WC, Greenberg PB, Pyarajan S, Lass JH, Peachey NS, Iyengar SK. A multi-ancestry GWAS of Fuchs corneal dystrophy highlights the contributions of laminins, collagen, and endothelial cell regulation. Commun Biol 2024; 7:418. [PMID: 38582945 PMCID: PMC10998918 DOI: 10.1038/s42003-024-06046-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 03/13/2024] [Indexed: 04/08/2024] Open
Abstract
Fuchs endothelial corneal dystrophy (FECD) is a leading indication for corneal transplantation, but its molecular etiology remains poorly understood. We performed genome-wide association studies (GWAS) of FECD in the Million Veteran Program followed by multi-ancestry meta-analysis with the previous largest FECD GWAS, for a total of 3970 cases and 333,794 controls. We confirm the previous four loci, and identify eight novel loci: SSBP3, THSD7A, LAMB1, PIDD1, RORA, HS3ST3B1, LAMA5, and COL18A1. We further confirm the TCF4 locus in GWAS for admixed African and Hispanic/Latino ancestries and show an enrichment of European-ancestry haplotypes at TCF4 in FECD cases. Among the novel associations are low frequency missense variants in laminin genes LAMA5 and LAMB1 which, together with previously reported LAMC1, form laminin-511 (LM511). AlphaFold 2 protein modeling, validated through homology, suggests that mutations at LAMA5 and LAMB1 may destabilize LM511 by altering inter-domain interactions or extracellular matrix binding. Finally, phenome-wide association scans and colocalization analyses suggest that the TCF4 CTG18.1 trinucleotide repeat expansion leads to dysregulation of ion transport in the corneal endothelium and has pleiotropic effects on renal function.
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Affiliation(s)
- Bryan R Gorman
- Center for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Boston, MA, USA
- Booz Allen Hamilton, McLean, VA, USA
| | - Michael Francis
- Center for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Boston, MA, USA
- Booz Allen Hamilton, McLean, VA, USA
| | - Cari L Nealon
- Eye Clinic, VA Northeast Ohio Healthcare System, Cleveland, OH, USA
| | - Christopher W Halladay
- Center of Innovation in Long Term Services and Supports, Providence VA Medical Center, Providence, RI, USA
| | - Nalvi Duro
- Center for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Boston, MA, USA
- Booz Allen Hamilton, McLean, VA, USA
| | - Kyriacos Markianos
- Center for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Boston, MA, USA
| | - Giulio Genovese
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanley Center, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Pirro G Hysi
- Department of Ophthalmology, King's College London, London, UK
- Department of Twins Research and Genetic Epidemiology, King's College London, London, UK
- UCL Great Ormond Street Hospital Institute of Child Health, King's College London, London, UK
| | - Hélène Choquet
- Division of Research, Kaiser Permanente Northern California (KPNC), Oakland, CA, USA
| | - Natalie A Afshari
- Shiley Eye Institute, Viterbi Family Department of Ophthalmology, University of California, San Diego, La Jolla, CA, USA
| | - Yi-Ju Li
- Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, USA
| | - J Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
- Division of Aging, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Adriana M Hung
- Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Center for Kidney Disease, Vanderbilt University Medical Center, Nashville, TN, USA
- VA Tennessee Valley Healthcare System, Nashville, TN, USA
| | - Wen-Chih Wu
- Cardiology Section, Medical Service, Providence VA Medical Center, Providence, RI, USA
| | - Paul B Greenberg
- Ophthalmology Section, Providence VA Medical Center, Providence, RI, USA
- Division of Ophthalmology, Alpert Medical School, Brown University, Providence, RI, USA
| | - Saiju Pyarajan
- Center for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Boston, MA, USA
| | - Jonathan H Lass
- Department of Ophthalmology and Visual Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Neal S Peachey
- Research Service, VA Northeast Ohio Healthcare System, Cleveland, OH, USA.
- Cole Eye Institute, Cleveland Clinic Foundation, Cleveland, OH, USA.
- Department of Ophthalmology, Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH, USA.
| | - Sudha K Iyengar
- Research Service, VA Northeast Ohio Healthcare System, Cleveland, OH, USA.
- Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA.
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA.
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3
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Bigdeli TB, Barr PB, Rajeevan N, Graham DP, Li Y, Meyers JL, Gorman BR, Peterson RE, Sayward F, Radhakrishnan K, Natarajan S, Nielsen DA, Wilkinson AV, Malhotra AK, Zhao H, Brophy M, Shi Y, O'Leary TJ, Gleason T, Przygodzki R, Pyarajan S, Muralidhar S, Gaziano JM, Huang GD, Concato J, Siever LJ, DeLisi LE, Kimbrel NA, Beckham JC, Swann AC, Kosten TR, Fanous AH, Aslan M, Harvey PD. Correlates of suicidal behaviors and genetic risk among United States veterans with schizophrenia or bipolar I disorder. Mol Psychiatry 2024:10.1038/s41380-024-02472-1. [PMID: 38491344 DOI: 10.1038/s41380-024-02472-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 01/22/2024] [Accepted: 01/31/2024] [Indexed: 03/18/2024]
Abstract
Persons diagnosed with schizophrenia (SCZ) or bipolar I disorder (BPI) are at high risk for self-injurious behavior, suicidal ideation, and suicidal behaviors (SB). Characterizing associations between diagnosed health problems, prior pharmacological treatments, and polygenic scores (PGS) has potential to inform risk stratification. We examined self-reported SB and ideation using the Columbia Suicide Severity Rating Scale (C-SSRS) among 3,942 SCZ and 5,414 BPI patients receiving care within the Veterans Health Administration (VHA). These cross-sectional data were integrated with electronic health records (EHRs), and compared across lifetime diagnoses, treatment histories, follow-up screenings, and mortality data. PGS were constructed using available genomic data for related traits. Genome-wide association studies were performed to identify and prioritize specific loci. Only 20% of the veterans who reported SB had a corroborating ICD-9/10 EHR code. Among those without prior SB, more than 20% reported new-onset SB at follow-up. SB were associated with a range of additional clinical diagnoses, and with treatment with specific classes of psychotropic medications (e.g., antidepressants, antipsychotics, etc.). PGS for externalizing behaviors, smoking initiation, suicide attempt, and major depressive disorder were associated with SB. The GWAS for SB yielded no significant loci. Among individuals with a diagnosed mental illness, self-reported SB were strongly associated with clinical variables across several EHR domains. Analyses point to sequelae of substance-related and psychiatric comorbidities as strong correlates of prior and subsequent SB. Nonetheless, past SB was frequently not documented in health records, underscoring the value of regular screening with direct, in-person assessments, especially among high-risk individuals.
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Affiliation(s)
- Tim B Bigdeli
- VA New York Harbor Healthcare System, Brooklyn, NY, US.
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, US.
- Institute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, NY, US.
- Department of Epidemiology and Biostatistics, School of Public Health, SUNY Downstate Health Sciences University, Brooklyn, NY, US.
| | - Peter B Barr
- VA New York Harbor Healthcare System, Brooklyn, NY, US
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, US
- Institute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, NY, US
- Department of Epidemiology and Biostatistics, School of Public Health, SUNY Downstate Health Sciences University, Brooklyn, NY, US
| | - Nallakkandi Rajeevan
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT, USA
- Yale University School of Medicine, New Haven, CT, USA
| | - David P Graham
- Michael E. DeBakey VA Medical Center, Houston, TX, USA
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Yuli Li
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT, USA
- Yale University School of Medicine, New Haven, CT, USA
| | - Jacquelyn L Meyers
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, US
- Institute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, NY, US
- Department of Epidemiology and Biostatistics, School of Public Health, SUNY Downstate Health Sciences University, Brooklyn, NY, US
| | - Bryan R Gorman
- Massachusetts Area Veterans Epidemiology, Research and Information Center (MAVERIC), Jamaica Plain, MA, USA
| | - Roseann E Peterson
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, US
- Institute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, NY, US
- Department of Epidemiology and Biostatistics, School of Public Health, SUNY Downstate Health Sciences University, Brooklyn, NY, US
| | - Frederick Sayward
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT, USA
- Yale University School of Medicine, New Haven, CT, USA
| | - Krishnan Radhakrishnan
- National Mental Health and Substance Use Policy Laboratory, Substance Abuse and Mental Health Services Administration, Rockville, MD, USA
| | | | - David A Nielsen
- Michael E. DeBakey VA Medical Center, Houston, TX, USA
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Anna V Wilkinson
- Michael E. DeBakey VA Medical Center, Houston, TX, USA
- Department of Epidemiology, Human Genetics and Environmental Science, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Anil K Malhotra
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA
- Division of Psychiatry Research, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, USA
- Department of Psychiatry, Hofstra Northwell School of Medicine, Hempstead, NY, USA
| | - Hongyu Zhao
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT, USA
- Yale University School of Medicine, New Haven, CT, USA
| | - Mary Brophy
- Massachusetts Area Veterans Epidemiology, Research and Information Center (MAVERIC), Jamaica Plain, MA, USA
- Boston University School of Medicine, Boston, MA, USA
| | - Yunling Shi
- Massachusetts Area Veterans Epidemiology, Research and Information Center (MAVERIC), Jamaica Plain, MA, USA
| | - Timothy J O'Leary
- Office of Research and Development, Veterans Health Administration, Washington, DC, USA
| | - Theresa Gleason
- Office of Research and Development, Veterans Health Administration, Washington, DC, USA
| | - Ronald Przygodzki
- Office of Research and Development, Veterans Health Administration, Washington, DC, USA
| | - Saiju Pyarajan
- Massachusetts Area Veterans Epidemiology, Research and Information Center (MAVERIC), Jamaica Plain, MA, USA
| | | | - J Michael Gaziano
- Massachusetts Area Veterans Epidemiology, Research and Information Center (MAVERIC), Jamaica Plain, MA, USA
- Harvard University, Boston, MA, USA
| | - Grant D Huang
- Office of Research and Development, Veterans Health Administration, Washington, DC, USA
| | - John Concato
- Yale University School of Medicine, New Haven, CT, USA
- Office of Research and Development, Veterans Health Administration, Washington, DC, USA
- Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Larry J Siever
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA
| | - Lynn E DeLisi
- Department of Psychiatry, Cambridge Health Alliance, Cambridge, MA, USA
| | - Nathan A Kimbrel
- Durham VA Health Care System, Durham, NC, USA
- VA Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham, NC, USA
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Jean C Beckham
- Durham VA Health Care System, Durham, NC, USA
- VA Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham, NC, USA
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Alan C Swann
- Michael E. DeBakey VA Medical Center, Houston, TX, USA
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Thomas R Kosten
- Michael E. DeBakey VA Medical Center, Houston, TX, USA
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Ayman H Fanous
- VA New York Harbor Healthcare System, Brooklyn, NY, US
- Department of Psychiatry, University of Arizona College of Medicine Phoenix, Phoenix, AZ, USA
| | - Mihaela Aslan
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT, USA
- Yale University School of Medicine, New Haven, CT, USA
| | - Philip D Harvey
- Bruce W. Carter Miami Veterans Affairs (VA) Medical Center, Miami, FL, USA
- University of Miami School of Medicine, Miami, FL, USA
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Davis SM, Teerlink C, Lynch JA, Gorman BR, Pagadala M, Liu A, Panizzon MS, Merritt VC, Genovese G, Ross JL, Hauger RL. Prevalence, Morbidity, and Mortality of Men With Sex Chromosome Aneuploidy in the Million Veteran Program Cohort. JAMA Netw Open 2024; 7:e244113. [PMID: 38551561 PMCID: PMC10980972 DOI: 10.1001/jamanetworkopen.2024.4113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Accepted: 01/15/2024] [Indexed: 04/01/2024] Open
Abstract
Importance The reported phenotypes of men with 47,XXY and 47,XYY syndromes include tall stature, multisystem comorbidities, and poor health-related quality of life (HRQOL). However, knowledge about these sex chromosome aneuploidy (SCA) conditions has been derived from studies in the less than 15% of patients who are clinically diagnosed and also lack diversity in age and genetic ancestry. Objectives To determine the prevalence of clinically diagnosed and undiagnosed X or Y chromosome aneuploidy among men enrolled in the Million Veteran Program (MVP); to describe military service metrics of men with SCAs; and to compare morbidity and mortality outcomes between men with SCA with and without a clinical diagnosis vs matched controls. Design, Setting, and Participants This cross-sectional study used a case-control recruitment design to select biological males enrolled in the MVP biobank in the US Veterans Administration health care system from 2011 to 2022. Cases were participants with 47,XXY syndrome or 47,XYY syndrome, matched 1:5 with controls based on sex, age, and genetic ancestry. Data were analyzed from January 2022 to December 2023. Exposure Genomic identification of an additional X or Y chromosome. Main Outcomes and Measures Outcomes of interest included prevalence of men with SCAs from genomic analysis; clinical SCA diagnosis; Charlson Comorbidity Index; rates of outpatient, inpatient, and emergency encounters per year; self-reported health outcomes; and standardized mortality ratio. Results Of 595 612 genotyped males in the MVP, 862 had an additional X chromosome (47,XXY) and 747 had an extra Y chromosome (47,XYY), with the highest prevalence among men with East Asian (47,XXY: 10 of 7313 participants; 47,XYY: 14 of 7313 participants) and European (47,XXY: 725 of 427 143 participants; 47,XYY: 625 of 427 143 participants) ancestry. Mean (SD) age at assessment was 61 (12) years, at which point 636 veterans (74.X%) with 47,XXY and 745 veterans (99%) with 47,XYY remained undiagnosed. Individuals with 47,XXY and 47,XYY had similar military service history, all-cause standardized mortality ratio, and age of death compared with matched controls. Individuals with SCA, compared with controls, had higher Charlson Comorbidity Index scores (47,XXY: mean [SD], 4.30 [2.72] vs controls: mean [SD], 3.90 [2.47]; 47,XYY: mean [SD], 4.45 [2.90] vs controls: mean [SD], 3.82 [2.50]) and health care utilization (eg, median [IQR] outpatient encounters per year: 47,XXY, 22.6 [11.8-37.8] vs controls, 16.8 [9.4-28]; 47,XYY: 21.4 [12.4-33.8] vs controls: 17.0 [9.4-28.2]), while several measures of HRQOL were lower (eg, mean [SD] self-reported physical function: 47,XXY: 34.2 [12] vs control mean [SD] 37.8 [12.8]; 47,XYY: 36.3 [11.6] vs control 37.9 [12.8]). Men with a clinical diagnosis of 47,XXY, compared with individuals without a clinical diagnosis, had higher health care utilization (eg, median [IQR] encounters per year: 26.6 [14.9-43.2] vs 22.2 [11.3-36.0]) but lower Charlson Comorbidity Index scores (mean [SD]: 3.7 [2.7] vs 4.5 [4.1]). Conclusion and Relevance In this case-control study of men with 47,XXY and 47,XYY syndromes, prevalence of SCA was comparable with estimates in the general population. While these men had successfully served in the military, they had higher morbidity and reported poorer HRQOL with aging. Longer longitudinal follow-up of this sample will be informative for clinical and patient-reported outcomes, the role of ancestry, and mortality statistics.
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Affiliation(s)
- Shanlee M Davis
- Department of Pediatrics, University of Colorado School of Medicine, Aurora
- eXtraOrdinarY Kids Clinic, Children's Hospital Colorado, Aurora
| | - Craig Teerlink
- VA Informatics and Computing Infrastructure, VA Salt Lake City Healthcare System, Salt Lake City, Utah
- Department of Internal Medicine, University of Utah Health, Salt Lake City
| | - Julie A Lynch
- VA Informatics and Computing Infrastructure, VA Salt Lake City Healthcare System, Salt Lake City, Utah
- Department of Internal Medicine, University of Utah Health, Salt Lake City
- College of Nursing and Health Sciences, University of Massachusetts, Lowell
| | | | - Meghana Pagadala
- Medical Scientist Training Program, University of California San Diego, La Jolla
- Biomedical Science Program, University of California San Diego, La Jolla
| | - Aoxing Liu
- University of Helsinki Institute for Molecular Medicine, Helsinki, Finland
| | - Matthew S Panizzon
- Center for Behavioral Genetics of Aging, School of Medicine, University of California San Diego, La Jolla
| | - Victoria C Merritt
- Department of Psychiatry, University of California San Diego, La Jolla
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, California
| | - Giulio Genovese
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Boston, Massachusetts
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Department of Genetics, Harvard Medical School, Boston, Massachusetts
| | - Judith L Ross
- Nemours Children's Hospital Delaware, Wilmington
- Department of Pediatrics, School of Medicine, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Richard L Hauger
- Center for Behavioral Genetics of Aging, School of Medicine, University of California San Diego, La Jolla
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, California
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Genovese G, Rockweiler NB, Gorman BR, Bigdeli TB, Pato MT, Pato CN, Ichihara K, McCarroll SA. BCFtools/liftover: an accurate and comprehensive tool to convert genetic variants across genome assemblies. Bioinformatics 2024; 40:btae038. [PMID: 38261650 PMCID: PMC10832354 DOI: 10.1093/bioinformatics/btae038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 12/07/2023] [Accepted: 01/18/2024] [Indexed: 01/25/2024] Open
Abstract
MOTIVATION Many genetics studies report results tied to genomic coordinates of a legacy genome assembly. However, as assemblies are updated and improved, researchers are faced with either realigning raw sequence data using the updated coordinate system or converting legacy datasets to the updated coordinate system to be able to combine results with newer datasets. Currently available tools to perform the conversion of genetic variants have numerous shortcomings, including poor support for indels and multi-allelic variants, that lead to a higher rate of variants being dropped or incorrectly converted. As a result, many researchers continue to work with and publish using legacy genomic coordinates. RESULTS Here we present BCFtools/liftover, a tool to convert genomic coordinates across genome assemblies for variants encoded in the variant call format with improved support for indels represented by different reference alleles across genome assemblies and full support for multi-allelic variants. It further supports variant annotation fields updates whenever the reference allele changes across genome assemblies. The tool has the lowest rate of variants being dropped with an order of magnitude less indels dropped or incorrectly converted and is an order of magnitude faster than other tools typically used for the same task. It is particularly suited for converting variant callsets from large cohorts to novel telomere-to-telomere assemblies as well as summary statistics from genome-wide association studies tied to legacy genome assemblies. AVAILABILITY AND IMPLEMENTATION The tool is written in C and freely available under the MIT open source license as a BCFtools plugin available at http://github.com/freeseek/score.
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Affiliation(s)
- Giulio Genovese
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, United States
- Stanley Center, Broad Institute of MIT and Harvard, Cambridge, MA 02142, United States
- Department of Genetics, Harvard Medical School, Boston, MA 02115, United States
| | - Nicole B Rockweiler
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, United States
- Stanley Center, Broad Institute of MIT and Harvard, Cambridge, MA 02142, United States
- Department of Genetics, Harvard Medical School, Boston, MA 02115, United States
| | - Bryan R Gorman
- Center for Data and Computational Sciences, VA Boston HealthCare System, Boston, MA 02130, United States
- Booz Allen Hamilton Inc, McLean, VA 22102, United States
| | - Tim B Bigdeli
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, United States
- Institute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, United States
- Cooperative Studies Program, VA New York Harbor Healthcare System, Brooklyn, NY 11209, United States
| | - Michelle T Pato
- Department of Psychiatry, Robert Wood Johnson Medical School, New Brunswick, NJ 08901, United States
| | - Carlos N Pato
- Department of Psychiatry, Robert Wood Johnson Medical School, New Brunswick, NJ 08901, United States
| | - Kiku Ichihara
- Stanley Center, Broad Institute of MIT and Harvard, Cambridge, MA 02142, United States
- Department of Genetics, Harvard Medical School, Boston, MA 02115, United States
| | - Steven A McCarroll
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, United States
- Stanley Center, Broad Institute of MIT and Harvard, Cambridge, MA 02142, United States
- Department of Genetics, Harvard Medical School, Boston, MA 02115, United States
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Nealon CL, Halladay CW, Gorman BR, Simpson P, Roncone DP, Canania RL, Anthony SA, Rogers LRS, Leber JN, Dougherty JM, Bailey JNC, Crawford DC, Sullivan JM, Galor A, Wu WC, Greenberg PB, Lass JH, Iyengar SK, Peachey NS. Association Between Fuchs Endothelial Corneal Dystrophy, Diabetes Mellitus, and Multimorbidity. Cornea 2023; 42:1140-1149. [PMID: 37170406 PMCID: PMC10523841 DOI: 10.1097/ico.0000000000003311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 04/11/2023] [Indexed: 05/13/2023]
Abstract
PURPOSE The aim of this study was to assess risk for demographic variables and other health conditions that are associated with Fuchs endothelial corneal dystrophy (FECD). METHODS We developed a FECD case-control algorithm based on structured electronic health record data and confirmed accuracy by individual review of charts at 3 Veterans Affairs (VA) Medical Centers. This algorithm was applied to the Department of VA Million Veteran Program cohort from whom sex, genetic ancestry, comorbidities, diagnostic phecodes, and laboratory values were extracted. Single-variable and multiple variable logistic regression models were used to determine the association of these risk factors with FECD diagnosis. RESULTS Being a FECD case was associated with female sex, European genetic ancestry, and a greater number of comorbidities. Of 1417 diagnostic phecodes evaluated, 213 had a significant association with FECD, falling in both ocular and nonocular conditions, including diabetes mellitus (DM). Five of 69 laboratory values were associated with FECD, with the direction of change for 4 being consistent with DM. Insulin dependency and type 1 DM raised risk to a greater degree than type 2 DM, like other microvascular diabetic complications. CONCLUSIONS Female sex, European ancestry, and multimorbidity increased FECD risk. Endocrine/metabolic clinic encounter codes and altered patterns of laboratory values support DM increasing FECD risk. Our results evoke a threshold model in which the FECD phenotype is intensified by DM and potentially other health conditions that alter corneal physiology. Further studies to better understand the relationship between FECD and DM are indicated and may help identify opportunities for slowing FECD progression.
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Affiliation(s)
- Cari L. Nealon
- Eye Clinic, VA Northeast Ohio Healthcare System, Cleveland, Ohio, USA
| | - Christopher W. Halladay
- Center of Innovation in Long Term Services and Supports, Providence VA Medical Center, Providence, Rhode Island, USA
| | - Bryan R. Gorman
- VA Cooperative Studies Program, VA Boston Healthcare System, Boston, Massachusetts
- Booz Allen Hamilton, McLean, Virginia, USA
| | - Piana Simpson
- Eye Clinic, VA Northeast Ohio Healthcare System, Cleveland, Ohio, USA
| | - David P. Roncone
- Eye Clinic, VA Northeast Ohio Healthcare System, Cleveland, Ohio, USA
| | | | - Scott A. Anthony
- Eye Clinic, VA Northeast Ohio Healthcare System, Cleveland, Ohio, USA
| | | | - Jenna N. Leber
- Ophthalmology Section, VA Western NY Health Care System, Buffalo, New York, USA
| | | | - Jessica N. Cooke Bailey
- Cleveland Institute for Computational Biology, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
- Department of Population & Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
- Research Service, VA Northeast Ohio Healthcare System, Cleveland, Ohio, USA
| | - Dana C. Crawford
- Cleveland Institute for Computational Biology, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
- Department of Population & Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
- Research Service, VA Northeast Ohio Healthcare System, Cleveland, Ohio, USA
| | - Jack M. Sullivan
- Ophthalmology Section, VA Western NY Health Care System, Buffalo, New York, USA
- Research Service, VA Western NY Health Care System, Buffalo, New York, USA
- Department of Ophthalmology (Ross Eye Institute), University at Buffalo-SUNY, Buffalo, New York, USA
| | - Anat Galor
- Miami Veterans Affairs Medical Center, Miami, Florida, USA
- Bascom Palmer Eye Institute, University of Miami, Miami, Florida, USA
| | - Wen-Chih Wu
- Cardiology Section, Medical Service, Providence VA Medical Center, Providence, Rhode Island, USA
| | - Paul B. Greenberg
- Ophthalmology Section, Providence VA Medical Center, Providence, Rhode Island, USA
- Division of Ophthalmology, Alpert Medical School, Brown University, Providence, Rhode Island, USA
| | | | - Jonathan H. Lass
- Department of Ophthalmology & Visual Sciences, Case Western Reserve University, Cleveland, Ohio, USA
- University Hospitals Eye Institute, Cleveland, Ohio, USA
| | - Sudha K. Iyengar
- Cleveland Institute for Computational Biology, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
- Department of Population & Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
- Research Service, VA Northeast Ohio Healthcare System, Cleveland, Ohio, USA
| | - Neal S. Peachey
- Research Service, VA Northeast Ohio Healthcare System, Cleveland, Ohio, USA
- Cole Eye Institute, Cleveland Clinic Foundation, Cleveland, Ohio, USA
- Department of Ophthalmology, Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, Ohio, USA
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7
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Cullina S, Wojcik GL, Shemirani R, Klarin D, Gorman BR, Sorokin EP, Gignoux CR, Belbin GM, Pyarajan S, Asgari S, Tsao PS, Damrauer SM, Abul-Husn NS, Kenny EE. Admixture mapping of peripheral artery disease in a Dominican population reveals a putative risk locus on 2q35. Front Genet 2023; 14:1181167. [PMID: 37600667 PMCID: PMC10432698 DOI: 10.3389/fgene.2023.1181167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 07/10/2023] [Indexed: 08/22/2023] Open
Abstract
Peripheral artery disease (PAD) is a form of atherosclerotic cardiovascular disease, affecting ∼8 million Americans, and is known to have racial and ethnic disparities. PAD has been reported to have a significantly higher prevalence in African Americans (AAs) compared to non-Hispanic European Americans (EAs). Hispanic/Latinos (HLs) have been reported to have lower or similar rates of PAD compared to EAs, despite having a paradoxically high burden of PAD risk factors; however, recent work suggests prevalence may differ between sub-groups. Here, we examined a large cohort of diverse adults in the BioMe biobank in New York City. We observed the prevalence of PAD at 1.7% in EAs vs. 8.5% and 9.4% in AAs and HLs, respectively, and among HL sub-groups, the prevalence was found at 11.4% and 11.5% in Puerto Rican and Dominican populations, respectively. Follow-up analysis that adjusted for common risk factors demonstrated that Dominicans had the highest increased risk for PAD relative to EAs [OR = 3.15 (95% CI 2.33-4.25), p < 6.44 × 10-14]. To investigate whether genetic factors may explain this increased risk, we performed admixture mapping by testing the association between local ancestry and PAD in Dominican BioMe participants (N = 1,813) separately from European, African, and Native American (NAT) continental ancestry tracts. The top association with PAD was an NAT ancestry tract at chromosome 2q35 [OR = 1.96 (SE = 0.16), p < 2.75 × 10-05) with 22.6% vs. 12.9% PAD prevalence in heterozygous NAT tract carriers versus non-carriers, respectively. Fine-mapping at this locus implicated tag SNP rs78529201 located within a long intergenic non-coding RNA (lincRNA) LINC00607, a gene expression regulator of key genes related to thrombosis and extracellular remodeling of endothelial cells, suggesting a putative link of the 2q35 locus to PAD etiology. Efforts to reproduce the signal in other Hispanic cohorts were unsuccessful. In summary, we showed how leveraging health system data helped understand nuances of PAD risk across HL sub-groups and admixture mapping approaches elucidated a putative risk locus in a Dominican population.
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Affiliation(s)
- Sinead Cullina
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Genevieve L. Wojcik
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Ruhollah Shemirani
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Derek Klarin
- VA Palo Alto Healthcare System, Palo Alto, CA, United States
- Division of Vascular Surgery, Stanford University School of Medicine, Palo Alto, CA, United States
| | - Bryan R. Gorman
- Center for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Boston, MA, United States
- Booz Allen Hamilton, McLean, VA, United States
| | - Elena P. Sorokin
- Department of Genetics, Stanford University, Stanford, CA, United States
| | - Christopher R. Gignoux
- Human Medical Genetics and Genomics Program, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
- Colorado Center for Personalized Medicine, Aurora, CO, United States
| | - Gillian M. Belbin
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Division of General Internal Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Saiju Pyarajan
- Center for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Boston, MA, United States
- Department of Medicine, Brigham Women’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Samira Asgari
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Philip S. Tsao
- VA Palo Alto Healthcare System, Palo Alto, CA, United States
| | - Scott M. Damrauer
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, United States
- Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Noura S. Abul-Husn
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Division of Genomic Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Eimear E. Kenny
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Division of General Internal Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Division of Genomic Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States
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Davis SM, Teerlink C, Lynch JA, Gorman BR, Pagadala M, Liu A, Panizzon MS, Merritt VC, Genovese G, Pyarajan S, Ross JL, Hauger RL. Prevalence, Morbidity, and Mortality of 1,609 Men with Sex Chromosome Aneuploidy: Results from the Diverse Million Veteran Program Cohort. medRxiv 2023:2023.07.15.23292710. [PMID: 37502926 PMCID: PMC10371178 DOI: 10.1101/2023.07.15.23292710] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Importance The reported phenotypes of men with 47,XXY and 47,XYY syndromes include tall stature, multisystem comorbidities, and poor health-related quality of life (HRQoL). However, knowledge about these sex chromosome aneuploidy (SCA) conditions has been derived from studies in the <15% of patients who are clinically diagnosed and also lack diversity in age and genetic ancestry. Objectives Determine the prevalence of clinically diagnosed and undiagnosed X or Y chromosome aneuploidy among men enrolled in the Million Veteran Program (MVP); describe military service metrics of men with SCAs; compare morbidity and mortality outcomes between men with SCA with and without a clinical diagnosis to matched controls. Design Cross-sectional, case-control. Setting United States Veterans Administration Healthcare System. Participants Biologic males enrolled in the MVP biobank with genomic identification of an additional X or Y chromosome (cases); controls matched 1:5 on sex, age, and genetic ancestry. Main Outcomes and Measures Prevalence of men with SCAs from genomic analysis; clinical SCA diagnosis; Charlson Comorbidity Index (CCI); rates of outpatient, inpatient, and emergency encounters per year; self-reported health outcomes; standardized mortality ratio (SMR). Results An additional X or Y chromosome was present in 145 and 125 per 100,000 males in the MVP, respectively, with the highest prevalence among men with European and East Asian ancestry. At a mean age of 61±12 years, 74% of male veterans with 47,XXY and >99% with 47,XYY remained undiagnosed. Individuals with 47,XXY (n=862) and 47,XYY (n=747) had similar military service history, all-cause SMR, and age of death compared to matched controls. CCI and healthcare utilization were higher among individuals with SCA, while several measures of HRQoL were lower. Men with a clinical diagnosis of 47,XXY had higher healthcare utilization but lower comorbidity score compared to those undiagnosed. Conclusion and Relevance One in 370 males in the MVP cohort have SCA, a prevalence comparable to estimates in the general population. While these men have successfully served in the military, they have higher morbidity and report poorer HRQoL with aging. Longer longitudinal follow-up of this sample will be informative for clinical and patient-reported outcomes, the role of ancestry, and mortality statistics. KEY POINTS Comparable to the general population, approximately 1 in 370 male veterans have a sex chromosome aneuploidy, but most are undiagnosed.Men with X or Y chromosome aneuploidy successfully complete US miliary duty with similar service history compared to their 46,XY peers.Medical comorbidities and healthcare utilization metrics are higher in male veterans with 47,XXY and 47,XYY during aging, however life expectancy is similar to matched controls.
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9
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Talwar JV, Laub D, Pagadala MS, Castro A, Lewis M, Luebeck GE, Gorman BR, Pan C, Dong FN, Markianos K, Teerlink CC, Lynch J, Hauger R, Pyarajan S, Tsao PS, Morris GP, Salem RM, Thompson WK, Curtius K, Zanetti M, Carter H. Autoimmune alleles at the major histocompatibility locus modify melanoma susceptibility. Am J Hum Genet 2023; 110:1138-1161. [PMID: 37339630 PMCID: PMC10357503 DOI: 10.1016/j.ajhg.2023.05.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 05/20/2023] [Accepted: 05/22/2023] [Indexed: 06/22/2023] Open
Abstract
Autoimmunity and cancer represent two different aspects of immune dysfunction. Autoimmunity is characterized by breakdowns in immune self-tolerance, while impaired immune surveillance can allow for tumorigenesis. The class I major histocompatibility complex (MHC-I), which displays derivatives of the cellular peptidome for immune surveillance by CD8+ T cells, serves as a common genetic link between these conditions. As melanoma-specific CD8+ T cells have been shown to target melanocyte-specific peptide antigens more often than melanoma-specific antigens, we investigated whether vitiligo- and psoriasis-predisposing MHC-I alleles conferred a melanoma-protective effect. In individuals with cutaneous melanoma from both The Cancer Genome Atlas (n = 451) and an independent validation set (n = 586), MHC-I autoimmune-allele carrier status was significantly associated with a later age of melanoma diagnosis. Furthermore, MHC-I autoimmune-allele carriers were significantly associated with decreased risk of developing melanoma in the Million Veteran Program (OR = 0.962, p = 0.024). Existing melanoma polygenic risk scores (PRSs) did not predict autoimmune-allele carrier status, suggesting these alleles provide orthogonal risk-relevant information. Mechanisms of autoimmune protection were neither associated with improved melanoma-driver mutation association nor improved gene-level conserved antigen presentation relative to common alleles. However, autoimmune alleles showed higher affinity relative to common alleles for particular windows of melanocyte-conserved antigens and loss of heterozygosity of autoimmune alleles caused the greatest reduction in presentation for several conserved antigens across individuals with loss of HLA alleles. Overall, this study presents evidence that MHC-I autoimmune-risk alleles modulate melanoma risk unaccounted for by current PRSs.
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Affiliation(s)
- James V Talwar
- Department of Medicine, Division of Medical Genetics, University of California San Diego, La Jolla, CA 92093, USA; Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA 92093, USA
| | - David Laub
- Department of Medicine, Division of Medical Genetics, University of California San Diego, La Jolla, CA 92093, USA; Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA 92093, USA
| | - Meghana S Pagadala
- Biomedical Science Program, University of California San Diego, La Jolla, CA 92093, USA
| | - Andrea Castro
- Department of Medicine, Division of Medical Genetics, University of California San Diego, La Jolla, CA 92093, USA; Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA 92093, USA
| | - McKenna Lewis
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Georg E Luebeck
- Public Health Sciences Division, Herbold Computational Biology Program, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Bryan R Gorman
- Center for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Boston, MA 02130, USA; Booz Allen Hamilton, Inc., McLean, VA 22102, USA
| | - Cuiping Pan
- Palo Alto Epidemiology Research and Information Center for Genomics, VA Palo Alto, CA, USA
| | - Frederick N Dong
- Center for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Boston, MA 02130, USA; Booz Allen Hamilton, Inc., McLean, VA 22102, USA
| | - Kyriacos Markianos
- Center for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Boston, MA 02130, USA; Division of Genetics and Genomics, Department of Pediatrics, Boston Children's Hospital, Boston, MA 02115, USA; Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of Harvard and MIT, Cambridge, MA 02115, USA
| | - Craig C Teerlink
- Department of Veterans Affairs Informatics and Computing Infrastructure (VINCI), VA Salt Lake City Healthcare System, Salt Lake City, UT, USA; Department of Internal Medicine, Division of Epidemiology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Julie Lynch
- Department of Veterans Affairs Informatics and Computing Infrastructure (VINCI), VA Salt Lake City Healthcare System, Salt Lake City, UT, USA; Department of Internal Medicine, Division of Epidemiology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Richard Hauger
- VA San Diego Healthcare System, La Jolla, CA, USA; Center for Behavioral Genetics of Aging, University of California San Diego, La Jolla, CA, USA; Center of Excellence for Stress and Mental Health (CESAMH), VA San Diego Healthcare System, San Diego, CA, USA
| | - Saiju Pyarajan
- Center for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Boston, MA 02130, USA; Department of Medicine, Brigham Women's Hospital, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Philip S Tsao
- Palo Alto Epidemiology Research and Information Center for Genomics, VA Palo Alto, CA, USA; Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Gerald P Morris
- Department of Pathology, University of California San Diego, La Jolla, CA 92093, USA
| | - Rany M Salem
- Division of Epidemiology, Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA 92093, USA
| | - Wesley K Thompson
- Center for Population Neuroscience and Genetics, Laureate Institute for Brain Research, Tulsa, OK 74136, USA
| | - Kit Curtius
- Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA 92093, USA; Moores Cancer Center, University of California San Diego, La Jolla, CA 92093, USA; Division of Biomedical Informatics, Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Maurizio Zanetti
- Moores Cancer Center, University of California San Diego, La Jolla, CA 92093, USA; The Laboratory of Immunology, University of California San Diego, La Jolla, CA 92093, USA; Department of Medicine, Division of Hematology and Oncology, University of California San Diego, La Jolla, CA 92093, USA
| | - Hannah Carter
- Department of Medicine, Division of Medical Genetics, University of California San Diego, La Jolla, CA 92093, USA; Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA 92093, USA; Moores Cancer Center, University of California San Diego, La Jolla, CA 92093, USA.
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10
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Cullina S, Wojcik GL, Shemirani R, Klarin D, Gorman BR, Sorokin EP, Gignoux CR, Belbin GM, Pyarajan S, Asgari S, Tsao PS, Damrauer SM, Abul-Husn NS, Kenny EE. Admixture Mapping of Peripheral Artery Disease in a Dominican Population Reveals a Novel Risk Locus on 2q35. medRxiv 2023:2023.03.27.23287788. [PMID: 37034679 PMCID: PMC10081406 DOI: 10.1101/2023.03.27.23287788] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/29/2023]
Abstract
Peripheral artery disease (PAD) is a form of atherosclerotic cardiovascular disease, affecting ∼8 million Americans, and is known to have racial and ethnic disparities. PAD has been reported to have significantly higher prevalence in African Americans (AAs) compared to non-Hispanic European Americans (EAs). Hispanic/Latinos (HLs) have been reported to have lower or similar rates of PAD compared to EAs, despite having a paradoxically high burden of PAD risk factors, however recent work suggests prevalence may differ between sub-groups. Here we examined a large cohort of diverse adults in the Bio Me biobank in New York City (NYC). We observed the prevalence of PAD at 1.7% in EAs vs 8.5% and 9.4% in AAs and HLs, respectively; and among HL sub-groups, at 11.4% and 11.5% in Puerto Rican and Dominican populations, respectively. Follow-up analysis that adjusted for common risk factors demonstrated that Dominicans had the highest increased risk for PAD relative to EAs (OR=3.15 (95% CI 2.33-4.25), P <6.44×10 -14 ). To investigate whether genetic factors may explain this increased risk, we performed admixture mapping by testing the association between local ancestry (LA) and PAD in Dominican Bio Me participants (N=1,940) separately for European (EUR), African (AFR) and Native American (NAT) continental ancestry tracts. We identified a NAT ancestry tract at chromosome 2q35 that was significantly associated with PAD (OR=2.05 (95% CI 1.51-2.78), P <4.06×10 -6 ) with 22.5% vs 12.5% PAD prevalence in heterozygous NAT tract carriers versus non-carriers, respectively. Fine-mapping at this locus implicated tag SNP rs78529201 located within a long intergenic non-coding RNA (lincRNA) LINC00607 , a gene expression regulator of key genes related to thrombosis and extracellular remodeling of endothelial cells, suggesting a putative link of the 2q35 locus to PAD etiology. In summary, we showed how leveraging health systems data helped understand nuances of PAD risk across HL sub-groups and admixture mapping approaches elucidated a novel risk locus in a Dominican population.
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11
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Bigdeli TB, Barr PB, Rajeevan N, Graham DP, Li Y, Meyers JL, Gorman BR, Peterson RE, Sayward F, Radhakrishnan K, Natarajan S, Nielsen DA, Wilkinson AV, Malhotra AK, Zhao H, Brophy M, Shi Y, O’Leary TJ, Gleason T, Przygodzki R, Pyarajan S, Muralidhar S, Gaziano JM, Huang GD, Concato J, Siever LJ, DeLisi LE, Kimbrel NA, Beckham JC, Swann AC, Kosten TR, Fanous AH, Aslan M, Harvey PD. Correlates of suicidal behaviors and genetic risk among United States veterans with schizophrenia or bipolar I disorder. medRxiv 2023:2023.03.06.23286866. [PMID: 36945597 PMCID: PMC10029042 DOI: 10.1101/2023.03.06.23286866] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2023]
Abstract
Objective Persons diagnosed with schizophrenia (SCZ) or bipolar I disorder (BPI) are at high risk for self-injurious behavior, suicidal ideation, and suicidal behaviors (SB). Characterizing associations between diagnosed mental and physical health problems, prior pharmacological treatments, and aggregate genetic factors has potential to inform risk stratification and mitigation strategies. Methods In this study of 3,942 SCZ and 5,414 BPI patients receiving VA care, self-reported SB and ideation were assessed using the Columbia Suicide Severity Rating Scale (C-SSRS). These cross-sectional data were integrated with electronic health records (EHR), and compared by lifetime diagnoses, treatment histories, follow-up screenings, and mortality data. Polygenic scores (PGS) for traits related to psychiatric disorders, substance use, and cognition were constructed using available genomic data, and exploratory genome-wide association studies were performed to identify and prioritize specific loci. Results Only 20% of veterans who self-reported SB had a corroborating ICD-9/10 code in their EHR; and among those who denied prior behaviors, more than 20% reported new-onset SB at follow-up. SB were associated with a range of psychiatric and non-psychiatric diagnoses, and with treatment with specific classes of psychotropic medications (e.g., antidepressants, antipsychotics, etc.). PGS for externalizing behaviors, smoking, suicide attempt, and major depressive disorder were also associated with attempt and ideation. Conclusions Among individuals with a diagnosed mental illness, a GWAS for SB did not yield any significant loci. Self-reported SB were strongly associated with clinical variables across several EHR domains. Overall, clinical and polygenic analyses point to sequelae of substance-use related behaviors and other psychiatric comorbidities as strong correlates of prior and subsequent SB. Nonetheless, past SB was frequently not documented in clinical settings, underscoring the value of regular screening based on direct, in-person assessments, especially among high-risk individuals.
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Affiliation(s)
- Tim B. Bigdeli
- VA New York Harbor Healthcare System, Brooklyn, NY
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY
| | - Peter B. Barr
- VA New York Harbor Healthcare System, Brooklyn, NY
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY
| | - Nallakkandi Rajeevan
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - David P. Graham
- Michael E. DeBakey VA Medical Center, Houston, TX
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX
| | - Yuli Li
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - Jacquelyn L. Meyers
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY
| | - Bryan R. Gorman
- Massachusetts Area Veterans Epidemiology, Research and Information Center (MAVERIC), Jamaica Plain, MA
| | - Roseann E. Peterson
- VA New York Harbor Healthcare System, Brooklyn, NY
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA
| | - Frederick Sayward
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - Krishnan Radhakrishnan
- National Mental Health and Substance Use Policy Laboratory, Substance Abuse and Mental Health Services Administration, Rockville, MD
| | | | - David A. Nielsen
- Michael E. DeBakey VA Medical Center, Houston, TX
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX
| | - Anna V. Wilkinson
- Michael E. DeBakey VA Medical Center, Houston, TX
- National Mental Health and Substance Use Policy Laboratory, Substance Abuse and Mental Health Services Administration, Rockville, MD
| | - Anil K. Malhotra
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY
- Division of Psychiatry Research, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY
- Department of Psychiatry, Hofstra Northwell School of Medicine, Hempstead, NY
| | - Hongyu Zhao
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - Mary Brophy
- Massachusetts Area Veterans Epidemiology, Research and Information Center (MAVERIC), Jamaica Plain, MA
- Boston University School of Medicine, Boston, MA
| | - Yunling Shi
- Massachusetts Area Veterans Epidemiology, Research and Information Center (MAVERIC), Jamaica Plain, MA
| | - Timothy J. O’Leary
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - Theresa Gleason
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - Ronald Przygodzki
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - Saiju Pyarajan
- Massachusetts Area Veterans Epidemiology, Research and Information Center (MAVERIC), Jamaica Plain, MA
| | - Sumitra Muralidhar
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - J. Michael Gaziano
- Massachusetts Area Veterans Epidemiology, Research and Information Center (MAVERIC), Jamaica Plain, MA
- Harvard University, Boston, MA
| | | | | | - Grant D. Huang
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - John Concato
- Yale University School of Medicine, New Haven, CT
- Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD
| | - Larry J. Siever
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, NY
- James J. Peters Veterans Affairs Medical Center, Bronx, NY
| | - Lynn E. DeLisi
- Department of Psychiatry, Cambridge Health Alliance, Cambridge, MA
| | - Nathan A. Kimbrel
- Durham VA Health Care System, Durham, NC
- VA Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham, NC
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC
| | - Jean C. Beckham
- Durham VA Health Care System, Durham, NC
- VA Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham, NC
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC
| | - Alan C. Swann
- Michael E. DeBakey VA Medical Center, Houston, TX
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX
| | - Thomas R. Kosten
- Michael E. DeBakey VA Medical Center, Houston, TX
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX
- Departments of Neuroscience, Pharmacology, and Immunology and Rheumatology, Baylor College of Medicine, Houston, TX
| | - Ayman H. Fanous
- VA New York Harbor Healthcare System, Brooklyn, NY
- Department of Psychiatry, University of Arizona College of Medicine Phoenix, Phoenix, AZ
| | - Mihaela Aslan
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - Philip D. Harvey
- Bruce W. Carter Miami Veterans Affairs (VA) Medical Center, Miami, FL
- University of Miami School of Medicine, Miami, FL
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12
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Verma A, Minnier J, Wan ES, Huffman JE, Gao L, Joseph J, Ho YL, Wu WC, Cho K, Gorman BR, Rajeevan N, Pyarajan S, Garcon H, Meigs JB, Sun YV, Reaven PD, McGeary JE, Suzuki A, Gelernter J, Lynch JA, Petersen JM, Zekavat SM, Natarajan P, Dalal S, Jhala DN, Arjomandi M, Gatsby E, Lynch KE, Bonomo RA, Freiberg M, Pathak GA, Zhou JJ, Donskey CJ, Madduri RK, Wells QS, Huang RDL, Polimanti R, Chang KM, Liao KP, Tsao PS, Wilson PWF, Hung AM, O’Donnell CJ, Gaziano JM, Hauger RL, Iyengar SK, Luoh SW. A MUC5B Gene Polymorphism, rs35705950-T, Confers Protective Effects Against COVID-19 Hospitalization but Not Severe Disease or Mortality. Am J Respir Crit Care Med 2022; 206:1220-1229. [PMID: 35771531 PMCID: PMC9746845 DOI: 10.1164/rccm.202109-2166oc] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Abstract
Rationale: A common MUC5B gene polymorphism, rs35705950-T, is associated with idiopathic pulmonary fibrosis (IPF), but its role in severe acute respiratory syndrome coronavirus 2 infection and disease severity is unclear. Objectives: To assess whether rs35705950-T confers differential risk for clinical outcomes associated with coronavirus disease (COVID-19) infection among participants in the Million Veteran Program (MVP). Methods: The MUC5B rs35705950-T allele was directly genotyped among MVP participants; clinical events and comorbidities were extracted from the electronic health records. Associations between the incidence or severity of COVID-19 and rs35705950-T were analyzed within each ancestry group in the MVP followed by transancestry meta-analysis. Replication and joint meta-analysis were conducted using summary statistics from the COVID-19 Host Genetics Initiative (HGI). Sensitivity analyses with adjustment for additional covariates (body mass index, Charlson comorbidity index, smoking, asbestosis, rheumatoid arthritis with interstitial lung disease, and IPF) and associations with post-COVID-19 pneumonia were performed in MVP subjects. Measurements and Main Results: The rs35705950-T allele was associated with fewer COVID-19 hospitalizations in transancestry meta-analyses within the MVP (Ncases = 4,325; Ncontrols = 507,640; OR = 0.89 [0.82-0.97]; P = 6.86 × 10-3) and joint meta-analyses with the HGI (Ncases = 13,320; Ncontrols = 1,508,841; OR, 0.90 [0.86-0.95]; P = 8.99 × 10-5). The rs35705950-T allele was not associated with reduced COVID-19 positivity in transancestry meta-analysis within the MVP (Ncases = 19,168/Ncontrols = 492,854; OR, 0.98 [0.95-1.01]; P = 0.06) but was nominally significant (P < 0.05) in the joint meta-analysis with the HGI (Ncases = 44,820; Ncontrols = 1,775,827; OR, 0.97 [0.95-1.00]; P = 0.03). Associations were not observed with severe outcomes or mortality. Among individuals of European ancestry in the MVP, rs35705950-T was associated with fewer post-COVID-19 pneumonia events (OR, 0.82 [0.72-0.93]; P = 0.001). Conclusions: The MUC5B variant rs35705950-T may confer protection in COVID-19 hospitalizations.
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Affiliation(s)
- Anurag Verma
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania;,Department of Medicine, Perelman School of Medicine, and
| | - Jessica Minnier
- OHSU-PSU School of Public Health and,Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon;,VA Portland Health Care System, Portland, Oregon
| | - Emily S. Wan
- Department of Medicine, Pulmonary, Critical Care, Sleep, and Allergy Section,,Channing Division of Network Medicine and
| | | | - Lina Gao
- Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon;,VA Portland Health Care System, Portland, Oregon
| | - Jacob Joseph
- Department of Medicine,,Medicine, Cardiovascular, Brigham & Women’s Hospital, Boston, Massachusetts
| | | | - Wen-Chih Wu
- Department of Medicine, Cardiology, Providence VA Healthcare System, Providence, Rhode Island;,Alpert Medical School & School of Public Health, Brown University, Providence, Rhode Island
| | - Kelly Cho
- MAVERIC,,Medicine, Aging, Brigham & Women’s Hospital and
| | | | - Nallakkandi Rajeevan
- Yale Center for Medical Informatics,,Clinical Epidemiology Research Center (CERC)
| | - Saiju Pyarajan
- MAVERIC,,Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | | | | | - Yan V. Sun
- Epidemiology, School of Public Health and,Atlanta VA Healthcare System, Decatur, Georgia
| | - Peter D. Reaven
- Department of Medicine, Phoenix VA Healthcare System, Phoenix, Arizona;,College of Medicine, University of Arizona, Phoenix, Arizona
| | - John E. McGeary
- Department of Psychiatry and Human Behavior, Providence VA Medical Center, Providence, Rhode Island;,Department of Psychiatry and Human Behavior, Brown University Medical School, Providence, Rhode Island
| | - Ayako Suzuki
- Department of Medicine, Gastroenterology, Durham VA Medical Center, Durham, North Carolina;,Department of Medicine, Gastroenterology, Duke University, Durham, North Carolina
| | - Joel Gelernter
- Division of Human Genetics, Department of Psychiatry, and,VA Connecticut Healthcare System, West Haven, Connecticut
| | - Julie A. Lynch
- VA Informatics & Computing Infrastructure (VINCI), VA Salt Lake City Healthcare System, Salt Lake City, Utah;,Department of Medicine and
| | - Jeffrey M. Petersen
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania;,Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Seyedeh Maryam Zekavat
- Computational Biology & Bioinformatics, Yale University School of Medicine, New Haven, Connecticut;,Program in Medical and Population Genetics, Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, Massachusetts
| | - Pradeep Natarajan
- Department of Medicine, Harvard Medical School, Boston, Massachusetts;,Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts;,Program in Medical and Population Genetics, Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, Massachusetts
| | - Sharvari Dalal
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania;,Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Darshana N. Jhala
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania;,Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Mehrdad Arjomandi
- Medicine, Pulmonary and Critical Care, San Francisco VA Healthcare System, University of California, San Francisco, San Francisco, California
| | - Elise Gatsby
- VA Informatics & Computing Infrastructure (VINCI), VA Salt Lake City Healthcare System, Salt Lake City, Utah
| | - Kristine E. Lynch
- VA Informatics & Computing Infrastructure (VINCI), VA Salt Lake City Healthcare System, Salt Lake City, Utah;,Internal Medicine, Epidemiology, University of Utah School of Medicine, Salt Lake City, Utah
| | | | | | - Gita A. Pathak
- Division of Human Genetics, Department of Psychiatry, and,VA Connecticut Healthcare System, West Haven, Connecticut
| | - Jin J. Zhou
- Department of Medicine, University of California, Los Angeles, Los Angeles, California;,Epidemiology and Biostatistics, University of Arizona, Tucson, Arizona
| | | | - Ravi K. Madduri
- Data Science and Learning, Argonne National Laboratory, Lemont, Illinois
| | - Quinn S. Wells
- Department of Medicine,,Department of Biomedical Informatics, and,Department of Pharmacology, Vanderbilt University Medical Center, Nashville, Tennessee
| | | | - Renato Polimanti
- Division of Human Genetics, Department of Psychiatry, and,VA Connecticut Healthcare System, West Haven, Connecticut
| | - Kyong-Mi Chang
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania
| | | | - Philip S. Tsao
- Precision Medicine, VA Palo Alto Health Care System, Palo Alto, California
| | - Peter W. F. Wilson
- Emory University, Atlanta, Georgia;,Atlanta VA Healthcare System, Decatur, Georgia
| | - Adriana M. Hung
- Department of Veteran’s Affairs, Tennessee Valley Healthcare System, Vanderbilt University Medical Center, Division of Nephrology & Hypertension, Nashville, Tennessee
| | | | | | - Richard L. Hauger
- Center of Excellence for Stress & Mental Health, VA San Diego Healthcare System, San Diego, California; and,Center for Behavioral Genetics of Aging, University of California, San Diego, La Jolla, California
| | - Sudha K. Iyengar
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio;,Louis Stokes Cleveland VA Medical Center, Cleveland, Ohio
| | - Shiuh-Wen Luoh
- Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon;,VA Portland Health Care System, Portland, Oregon
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13
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Bigdeli TB, Voloudakis G, Barr PB, Gorman BR, Genovese G, Peterson RE, Burstein DE, Velicu VI, Li Y, Gupta R, Mattheisen M, Tomasi S, Rajeevan N, Sayward F, Radhakrishnan K, Natarajan S, Malhotra AK, Shi Y, Zhao H, Kosten TR, Concato J, O’Leary TJ, Przygodzki R, Gleason T, Pyarajan S, Brophy M, Huang GD, Muralidhar S, Gaziano JM, Aslan M, Fanous AH, Harvey PD, Roussos P. Penetrance and Pleiotropy of Polygenic Risk Scores for Schizophrenia, Bipolar Disorder, and Depression Among Adults in the US Veterans Affairs Health Care System. JAMA Psychiatry 2022; 79:2796413. [PMID: 36103194 PMCID: PMC9475441 DOI: 10.1001/jamapsychiatry.2022.2742] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Accepted: 07/20/2022] [Indexed: 12/21/2022]
Abstract
Importance Serious mental illnesses, including schizophrenia, bipolar disorder, and depression, are heritable, highly multifactorial disorders and major causes of disability worldwide. Objective To benchmark the penetrance of current neuropsychiatric polygenic risk scores (PRSs) in the Veterans Health Administration health care system and to explore associations between PRS and broad categories of human disease via phenome-wide association studies. Design, Setting, and Participants Extensive Veterans Health Administration's electronic health records were assessed from October 1999 to January 2021, and an embedded cohort of 9378 individuals with confirmed diagnoses of schizophrenia or bipolar 1 disorder were found. The performance of schizophrenia, bipolar disorder, and major depression PRSs were compared in participants of African or European ancestry in the Million Veteran Program (approximately 400 000 individuals), and associations between PRSs and 1650 disease categories based on ICD-9/10 billing codes were explored. Last, genomic structural equation modeling was applied to derive novel PRSs indexing common and disorder-specific genetic factors. Analysis took place from January 2021 to January 2022. Main Outcomes and Measures Diagnoses based on in-person structured clinical interviews were compared with ICD-9/10 billing codes. PRSs were constructed using summary statistics from genome-wide association studies of schizophrenia, bipolar disorder, and major depression. Results Of 707 299 enrolled study participants, 459 667 were genotyped at the time of writing; 84 806 were of broadly African ancestry (mean [SD] age, 58 [12.1] years) and 314 909 were of broadly European ancestry (mean [SD] age, 66.4 [13.5] years). Among 9378 individuals with confirmed diagnoses of schizophrenia or bipolar 1 disorder, 8962 (95.6%) were correctly identified using ICD-9/10 codes (2 or more). Among those of European ancestry, PRSs were robustly associated with having received a diagnosis of schizophrenia (odds ratio [OR], 1.81 [95% CI, 1.76-1.87]; P < 10-257) or bipolar disorder (OR, 1.42 [95% CI, 1.39-1.44]; P < 10-295). Corresponding effect sizes in participants of African ancestry were considerably smaller for schizophrenia (OR, 1.35 [95% CI, 1.29-1.42]; P < 10-38) and bipolar disorder (OR, 1.16 [95% CI, 1.11-1.12]; P < 10-10). Neuropsychiatric PRSs were associated with increased risk for a range of psychiatric and physical health problems. Conclusions and Relevance Using diagnoses confirmed by in-person structured clinical interviews and current neuropsychiatric PRSs, the validity of an electronic health records-based phenotyping approach in US veterans was demonstrated, highlighting the potential of PRSs for disentangling biological and mediated pleiotropy.
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Affiliation(s)
- Tim B. Bigdeli
- VA New York Harbor Healthcare System, Brooklyn
- Institute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, New York
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, New York
| | - Georgios Voloudakis
- James J. Peters Veterans Affairs Medical Center, Bronx, New York
- Departments of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York
- Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Peter B. Barr
- VA New York Harbor Healthcare System, Brooklyn
- Institute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, New York
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, New York
| | - Bryan R. Gorman
- Massachusetts Area Veterans Epidemiology, Research, and Information Center (MAVERIC), Jamaica Plain
| | - Giulio Genovese
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Roseann E. Peterson
- VA New York Harbor Healthcare System, Brooklyn
- Institute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, New York
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, New York
- Department of Psychiatry, Virginia Commonwealth University, Richmond
| | - David E. Burstein
- James J. Peters Veterans Affairs Medical Center, Bronx, New York
- Departments of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York
- Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Vlad I. Velicu
- James J. Peters Veterans Affairs Medical Center, Bronx, New York
- Departments of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York
- Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Yuli Li
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut
- Yale University School of Medicine, New Haven, Connecticut
| | - Rishab Gupta
- Department of Psychiatry, Brigham & Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Manuel Mattheisen
- Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada
- Department of Community Health, Dalhousie University, Halifax, Nova Scotia, Canada
- Department of Epidemiology, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Simone Tomasi
- James J. Peters Veterans Affairs Medical Center, Bronx, New York
- Departments of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York
- Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Nallakkandi Rajeevan
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut
- Yale University School of Medicine, New Haven, Connecticut
| | - Frederick Sayward
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut
- Yale University School of Medicine, New Haven, Connecticut
| | - Krishnan Radhakrishnan
- National Mental Health and Substance Use Policy Laboratory, Substance Abuse and Mental Health Services Administration, Rockville, Maryland
| | | | - Anil K. Malhotra
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, New York
- Division of Psychiatry Research, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, New York
- Department of Psychiatry, Hofstra Northwell School of Medicine, Hempstead, New York
| | - Yunling Shi
- Massachusetts Area Veterans Epidemiology, Research, and Information Center (MAVERIC), Jamaica Plain
| | - Hongyu Zhao
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut
- Yale University School of Medicine, New Haven, Connecticut
| | - Thomas R. Kosten
- Michael E. DeBakey VA Medical Center, Houston, Texas
- Department of Psychiatry, Neuroscience, Pharmacology, and Immunology and Rheumatology, Baylor College of Medicine, Houston, Texas
| | - John Concato
- Yale University School of Medicine, New Haven, Connecticut
- Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland
| | - Timothy J. O’Leary
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - Ronald Przygodzki
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - Theresa Gleason
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - Saiju Pyarajan
- Massachusetts Area Veterans Epidemiology, Research, and Information Center (MAVERIC), Jamaica Plain
| | - Mary Brophy
- Massachusetts Area Veterans Epidemiology, Research, and Information Center (MAVERIC), Jamaica Plain
- Boston University School of Medicine, Boston, Massachusetts
| | - Grant D. Huang
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - Sumitra Muralidhar
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - J. Michael Gaziano
- Massachusetts Area Veterans Epidemiology, Research, and Information Center (MAVERIC), Jamaica Plain
- Harvard Medical School, Boston, Massachusetts
| | - Mihaela Aslan
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut
- Yale University School of Medicine, New Haven, Connecticut
| | - Ayman H. Fanous
- Department of Psychiatry, University of Arizona College of Medicine-Phoenix, Phoenix
- Carl T. Hayden Veterans Affairs Medical Center, Phoenix, Arizona
| | - Philip D. Harvey
- Bruce W. Carter Miami Veterans Affairs (VA) Medical Center, Miami, Florida
- University of Miami Miller School of Medicine, Miami, Florida
| | - Panos Roussos
- James J. Peters Veterans Affairs Medical Center, Bronx, New York
- Departments of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York
- Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York
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14
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Tcheandjieu C, Zhu X, Hilliard AT, Clarke SL, Napolioni V, Ma S, Lee KM, Fang H, Chen F, Lu Y, Tsao NL, Raghavan S, Koyama S, Gorman BR, Vujkovic M, Klarin D, Levin MG, Sinnott-Armstrong N, Wojcik GL, Plomondon ME, Maddox TM, Waldo SW, Bick AG, Pyarajan S, Huang J, Song R, Ho YL, Buyske S, Kooperberg C, Haessler J, Loos RJF, Do R, Verbanck M, Chaudhary K, North KE, Avery CL, Graff M, Haiman CA, Le Marchand L, Wilkens LR, Bis JC, Leonard H, Shen B, Lange LA, Giri A, Dikilitas O, Kullo IJ, Stanaway IB, Jarvik GP, Gordon AS, Hebbring S, Namjou B, Kaufman KM, Ito K, Ishigaki K, Kamatani Y, Verma SS, Ritchie MD, Kember RL, Baras A, Lotta LA, Kathiresan S, Hauser ER, Miller DR, Lee JS, Saleheen D, Reaven PD, Cho K, Gaziano JM, Natarajan P, Huffman JE, Voight BF, Rader DJ, Chang KM, Lynch JA, Damrauer SM, Wilson PWF, Tang H, Sun YV, Tsao PS, O'Donnell CJ, Assimes TL. Large-scale genome-wide association study of coronary artery disease in genetically diverse populations. Nat Med 2022; 28:1679-1692. [PMID: 35915156 PMCID: PMC9419655 DOI: 10.1038/s41591-022-01891-3] [Citation(s) in RCA: 87] [Impact Index Per Article: 43.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Accepted: 06/08/2022] [Indexed: 02/03/2023]
Abstract
We report a genome-wide association study (GWAS) of coronary artery disease (CAD) incorporating nearly a quarter of a million cases, in which existing studies are integrated with data from cohorts of white, Black and Hispanic individuals from the Million Veteran Program. We document near equivalent heritability of CAD across multiple ancestral groups, identify 95 novel loci, including nine on the X chromosome, detect eight loci of genome-wide significance in Black and Hispanic individuals, and demonstrate that two common haplotypes at the 9p21 locus are responsible for risk stratification in all populations except those of African origin, in which these haplotypes are virtually absent. Moreover, in the largest GWAS for angiographically derived coronary atherosclerosis performed to date, we find 15 loci of genome-wide significance that robustly overlap with established loci for clinical CAD. Phenome-wide association analyses of novel loci and polygenic risk scores (PRSs) augment signals related to insulin resistance, extend pleiotropic associations of these loci to include smoking and family history, and precisely document the markedly reduced transferability of existing PRSs to Black individuals. Downstream integrative analyses reinforce the critical roles of vascular endothelial, fibroblast, and smooth muscle cells in CAD susceptibility, but also point to a shared biology between atherosclerosis and oncogenesis. This study highlights the value of diverse populations in further characterizing the genetic architecture of CAD.
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Affiliation(s)
- Catherine Tcheandjieu
- VA Palo Alto Health Care System, Palo Alto, CA, USA.
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA.
- Gladstone Institute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA, USA.
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA.
| | - Xiang Zhu
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Statistics, Stanford University, Stanford, CA, USA
- Department of Statistics, The Pennsylvania State University, University Park, PA, USA
- Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA, USA
| | | | - Shoa L Clarke
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Valerio Napolioni
- School of Biosciences and Veterinary Medicine, University of Camerino, Camerino, Italy
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Shining Ma
- Department of Statistics, Stanford University, Stanford, CA, USA
| | - Kyung Min Lee
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
| | - Huaying Fang
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Fei Chen
- Department of Preventive Medicine, Center for Genetic Epidemiology, University of Southern California, Los Angeles, CA, USA
| | - Yingchang Lu
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Noah L Tsao
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Sridharan Raghavan
- Medicine Service, VA Eastern Colorado Health Care System, Aurora, CO, USA
- Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Satoshi Koyama
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Bryan R Gorman
- VA Boston Healthcare System, Boston, MA, USA
- Booz Allen Hamilton, McLean, VA, USA
| | - Marijana Vujkovic
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Derek Klarin
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- VA Boston Healthcare System, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Vascular Surgery and Endovascular Therapy, University of Florida School of Medicine, Gainesville, FL, USA
- Stanford University School of Medicine, Stanford, CA, USA
| | - Michael G Levin
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Nasa Sinnott-Armstrong
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Genevieve L Wojcik
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Mary E Plomondon
- Department of Medicine, Rocky Mountain Regional VA Medical Center, Aurora, CO, USA
- CART Program, VHA Office of Quality and Patient Safety, Washington, DC, USA
| | - Thomas M Maddox
- Healthcare Innovation Lab, JC HealthCare/Washington University School of Medicine, St Louis, MO, USA
- Division of Cardiology, Washington University School of Medicine, St Louis, MO, USA
| | - Stephen W Waldo
- Department of Medicine, Rocky Mountain Regional VA Medical Center, Aurora, CO, USA
- CART Program, VHA Office of Quality and Patient Safety, Washington, DC, USA
- Division of Cardiology, University of Colorado School of Medicine, Aurora, CO, USA
| | - Alexander G Bick
- Department of Biomedical Informatics, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Saiju Pyarajan
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jie Huang
- VA Boston Healthcare System, Boston, MA, USA
- Department of Global Health, Peking University School of Public Health, Beijing, China
- School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen, China
| | | | - Yuk-Lam Ho
- VA Boston Healthcare System, Boston, MA, USA
| | - Steven Buyske
- Department of Statistics, Rutgers University, Piscataway, NJ, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Jeffrey Haessler
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Ruth J F Loos
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ron Do
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Marie Verbanck
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- EA 7537 BioSTM, Université de Paris, Paris, France
| | - Kumardeep Chaudhary
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Christy L Avery
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Mariaelisa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Christopher A Haiman
- Department of Preventive Medicine, Center for Genetic Epidemiology, University of Southern California, Los Angeles, CA, USA
| | - Loïc Le Marchand
- Cancer Epidemiology Program, University of Hawaii Cancer Center, University of Hawaii, Honolulu, HI, USA
| | - Lynne R Wilkens
- Cancer Epidemiology Program, University of Hawaii Cancer Center, University of Hawaii, Honolulu, HI, USA
| | - Joshua C Bis
- Department of Medicine, Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA
| | - Hampton Leonard
- Molecular Genetics Section, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
- Data Tecnica Int'l, LLC, Glen Echo, MD, USA
| | - Botong Shen
- Health Disparities Research Section, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Leslie A Lange
- Department of Medicine, Division of Biomedical Informatics and Personalized Medicine, Aurora, CO, USA
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, Aurora, CO, USA
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Ayush Giri
- Department of Medicine, Division of Epidemiology, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Obstetrics and Gynecology, Division of Quantitative Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Ozan Dikilitas
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Iftikhar J Kullo
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Ian B Stanaway
- Department of Medicine, Division of Nephrology, University of Washington, Seattle, WA, USA
| | - Gail P Jarvik
- Department of Medicine, Medical Genetics, University of Washington School of Medicine, Seattle, WA, USA
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Adam S Gordon
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Scott Hebbring
- Center for Precision Medicine Research, Marshfield Clinic Research Institute, Marshfield, WI, USA
| | - Bahram Namjou
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Kenneth M Kaufman
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Kaoru Ito
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Kazuyoshi Ishigaki
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Yoichiro Kamatani
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences - The University of Tokyo, Tokyo, Japan
| | - Shefali S Verma
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Institute for Biomedical Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Marylyn D Ritchie
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Institute for Biomedical Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Rachel L Kember
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Aris Baras
- Regeneron Genetics Center, Tarrytown, NY, USA
| | | | - Sekar Kathiresan
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Cardiology Division, Massachusetts General Hospital, Boston, MA, USA
- Verve Therapeutics, Cambridge, MA, USA
| | - Elizabeth R Hauser
- Cooperative Studies Program Epidemiology Center-Durham, Durham VA Health Care System, Durham, NC, USA
- Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC, USA
| | - Donald R Miller
- Center for Healthcare Organization and Implementation Research, Bedford VA Healthcare System, Bedford, MA, USA
- Center for Population Health, Department of Biomedical and Nutritional Sciences, University of Massachusetts, Lowell, MA, USA
| | - Jennifer S Lee
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Danish Saleheen
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Division of Cardiology, Columbia University, New York, NY, USA
| | - Peter D Reaven
- Phoenix VA Health Care System, Phoenix, AZ, USA
- College of Medicine, University of Arizona, Phoenix, AZ, USA
| | - Kelly Cho
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - J Michael Gaziano
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Pradeep Natarajan
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Cardiology Division, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | | | - Benjamin F Voight
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Institute of Translational Medicine and Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Daniel J Rader
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Kyong-Mi Chang
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Julie A Lynch
- VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- College of Nursing and Health Sciences, University of Massachusetts, Boston, MA, USA
| | - Scott M Damrauer
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Peter W F Wilson
- Atlanta VA Medical Center, Atlanta, GA, USA
- Division of Cardiology, Emory University School of Medicine, Atlanta, GA, USA
| | - Hua Tang
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Yan V Sun
- Atlanta VA Health Care System, Atlanta, GA, USA
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
| | - Philip S Tsao
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Christopher J O'Donnell
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Themistocles L Assimes
- VA Palo Alto Health Care System, Palo Alto, CA, USA.
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA.
- Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA.
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA.
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15
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Verma A, Huffman JE, Gao L, Minnier J, Wu WC, Cho K, Ho YL, Gorman BR, Pyarajan S, Rajeevan N, Garcon H, Joseph J, McGeary JE, Suzuki A, Reaven PD, Wan ES, Lynch JA, Petersen JM, Meigs JB, Freiberg MS, Gatsby E, Lynch KE, Zekavat SM, Natarajan P, Dalal S, Jhala DN, Arjomandi M, Bonomo RA, Thompson TK, Pathak GA, Zhou JJ, Donskey CJ, Madduri RK, Wells QS, Gelernter J, Huang RDL, Polimanti R, Chang KM, Liao KP, Tsao PS, Sun YV, Wilson PWF, O’Donnell CJ, Hung AM, Gaziano JM, Hauger RL, Iyengar SK, Luoh SW. Association of Kidney Comorbidities and Acute Kidney Failure With Unfavorable Outcomes After COVID-19 in Individuals With the Sickle Cell Trait. JAMA Intern Med 2022; 182:796-804. [PMID: 35759254 PMCID: PMC9237798 DOI: 10.1001/jamainternmed.2022.2141] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Importance Sickle cell trait (SCT), defined as the presence of 1 hemoglobin beta sickle allele (rs334-T) and 1 normal beta allele, is prevalent in millions of people in the US, particularly in individuals of African and Hispanic ancestry. However, the association of SCT with COVID-19 is unclear. Objective To assess the association of SCT with the prepandemic health conditions in participants of the Million Veteran Program (MVP) and to assess the severity and sequelae of COVID-19. Design, Setting, and Participants COVID-19 clinical data include 2729 persons with SCT, of whom 353 had COVID-19, and 129 848 SCT-negative individuals, of whom 13 488 had COVID-19. Associations between SCT and COVID-19 outcomes were examined using firth regression. Analyses were performed by ancestry and adjusted for sex, age, age squared, and ancestral principal components to account for population stratification. Data for the study were collected between March 2020 and February 2021. Exposures The hemoglobin beta S (HbS) allele (rs334-T). Main Outcomes and Measures This study evaluated 4 COVID-19 outcomes derived from the World Health Organization severity scale and phenotypes derived from International Classification of Diseases codes in the electronic health records. Results Of the 132 577 MVP participants with COVID-19 data, mean (SD) age at the index date was 64.8 (13.1) years. Sickle cell trait was present in 7.8% of individuals of African ancestry and associated with a history of chronic kidney disease, diabetic kidney disease, hypertensive kidney disease, pulmonary embolism, and cerebrovascular disease. Among the 4 clinical outcomes of COVID-19, SCT was associated with an increased COVID-19 mortality in individuals of African ancestry (n = 3749; odds ratio, 1.77; 95% CI, 1.13 to 2.77; P = .01). In the 60 days following COVID-19, SCT was associated with an increased incidence of acute kidney failure. A counterfactual mediation framework estimated that on average, 20.7% (95% CI, -3.8% to 56.0%) of the total effect of SCT on COVID-19 fatalities was due to acute kidney failure. Conclusions and Relevance In this genetic association study, SCT was associated with preexisting kidney comorbidities, increased COVID-19 mortality, and kidney morbidity.
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Affiliation(s)
- Anurag Verma
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania
- Perelman School of Medicine, Department of Medicine, University of Pennsylvania, Philadelphia
| | | | - Lina Gao
- Knight Cancer Institute, Biostatistics Shared Resource, Oregon Health & Science University, Portland
- VA Portland Health Care System, Portland, Oregon
| | - Jessica Minnier
- VA Portland Health Care System, Portland, Oregon
- OHSU-PSU School of Public Health, Oregon Health & Science University, Portland
- Knight Cancer Institute, Biostatistics Shared Resource, Oregon Health & Science University, Portland
| | - Wen-Chih Wu
- Department of Medicine, Cardiology, Providence VA Healthcare System, Providence, Rhode Island
- Alpert Medical School & School of Public Health, Brown University, Providence, Rhode Island
| | - Kelly Cho
- MAVERIC, VA Boston Healthcare System, Boston, Massachusetts
- Medicine, Aging, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Yuk-Lam Ho
- MAVERIC, VA Boston Healthcare System, Boston, Massachusetts
| | | | - Saiju Pyarajan
- VA Boston Healthcare System, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Nallakkandi Rajeevan
- Yale Center for Medical Informatics, Yale School of Medicine, New Haven, Connecticut
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven
| | - Helene Garcon
- MAVERIC, VA Boston Healthcare System, Boston, Massachusetts
| | - Jacob Joseph
- Department of Medicine, VA Boston Healthcare System, Boston, Massachusetts
- Brigham & Women’s Hospital, Boston, Massachusetts
| | - John E. McGeary
- Department of Psychiatry and Human Behavior, Providence VA Medical Center, Providence, Rhode Island
- Brown University Medical School, Providence, Rhode Island
| | - Ayako Suzuki
- Department of Medicine, Gastroenterology, Durham VA Medical Center, Durham, North Carolina
- Department of Medicine, Gastroenterology, Duke University, Durham, North Carolina
| | - Peter D. Reaven
- Department of Medicine, Phoenix VA Healthcare System, Phoenix, Arizona
- University of Arizona, Phoenix
| | - Emily S. Wan
- Department of Medicine, Pulmonary, Critical Care, Sleep, and Allergy Section, VA Boston Healthcare System, Boston, Massachusetts
- Channing Division of Network Medicine, Brigham & Women’s Hospital, Boston, Massachusetts
| | - Julie A. Lynch
- VA Informatics & Computing Infrastructure, VA Salt Lake City Utah & University of Utah, School of Medicine, Salt Lake City
| | - Jeffrey M. Petersen
- Pathology and Laboratory Medicine, Corporal Michael Crescenz VA Medical Center, Philadelphia, Pennsylvania
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - James B. Meigs
- Medicine, General Internal Medicine, Massachusetts General Hospital, Boston
| | | | - Elise Gatsby
- VA Informatics and Computing Infrastructure (VINCI), VA Salt Lake City Healthcare System, Salt Lake City, Utah
| | - Kristine E. Lynch
- VA Informatics and Computing Infrastructure (VINCI), VA Salt Lake City Healthcare System, Salt Lake City, Utah
- Internal Medicine, Epidemiology, University of Utah School of Medicine, Salt Lake City
| | - Seyedeh Maryam Zekavat
- Computational Biology & Bioinformatics, Yale School of Medicine, New Haven, Connecticut
- Program in Medical and Population Genetics, Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, Massachusetts
| | - Pradeep Natarajan
- Program in Medical and Population Genetics, Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, Massachusetts
- Cardiovascular Research Center, Massachusetts General Hospital, Boston
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Clinical Data Science Research Group, ORD, Portland VA Medical Center, Portland, Oregon
| | - Sharvari Dalal
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Pathology and Laboratory Medicine, Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania
| | - Darshana N. Jhala
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Pathology and Laboratory Medicine, Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania
| | - Mehrdad Arjomandi
- Medicine, Pulmonary and Critical Care, San Francisco VA Healthcare System, San Francisco, California
- University of California San Francisco
| | - Robert A. Bonomo
- Cleveland VA Medical Center, Cleveland, Ohio
- Medicine, Case Western Reserve University School of Medicine, Cleveland, Ohio
| | | | - Gita A. Pathak
- Department of Psychiatry, Division of Human Genetics, Yale School of Medicine, New Haven, Connecticut
- VA Connecticut Healthcare System, West Haven
| | - Jin J. Zhou
- Medicine, University of California, Los Angeles
- Epidemiology and Biostatistics, University of Arizona, Phoenix
| | - Curtis J. Donskey
- Infectious Disease Section, Louis Stokes Cleveland VA, Cleveland, Ohio
- Case Western Reserve University, Cleveland, Ohio
| | - Ravi K. Madduri
- Data Science and Learning, Argonne National Laboratory, Lemont, Illinois
| | - Quinn S. Wells
- Departments of Medicine, Biomedical Informatics, and Pharmacology, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Joel Gelernter
- VA Connecticut Healthcare System, West Haven
- Psychiatry, Human Genetics, Yale University School of Medicine, West Haven, Connecticut
| | | | - Renato Polimanti
- Departments of Medicine, Biomedical Informatics, and Pharmacology, Vanderbilt University Medical Center, Nashville, Tennessee
- Psychiatry, Human Genetics, Yale University School of Medicine, West Haven, Connecticut
| | - Kyong-Mi Chang
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Katherine P. Liao
- Medicine, Rheumatology, VA Boston Healthcare System, Boston, Massachusetts
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women’s Hospital, Boston, Massachusetts
- Department of Medicine & Biomedical Informatics, Harvard Medical School, Boston, Massachusetts
| | - Philip S. Tsao
- Precision Medicine, VA Palo Alto Health Care System, Palo Alto, California
| | - Yan V. Sun
- Epidemiology, Emory University School of Public Health, Atlanta, Georgia
- Atlanta VA Health Care System, Decatur, Georgia
| | - Peter W. F. Wilson
- Atlanta VA Health Care System, Decatur, Georgia
- Emory University School of Medicine, Atlanta, Georgia
| | | | - Adriana M. Hung
- Vanderbilt University Medical Center, Nashville, Tennessee
- Nashville VA Medical Center, Nashville, Tennessee
| | - J. Michael Gaziano
- VA Boston Health Care System, Boston, Massachusetts
- Medicine, Harvard Medical School, Boston, Massachusetts
| | - Richard L. Hauger
- Center of Excellence for Stress & Mental Health, VA San Diego Healthcare System, San Diego, California
- Center for Behavioral Genetics of Aging, University of California, San Diego, La Jolla
| | - Sudha K. Iyengar
- Departments of Population and Quantitative Health Sciences, Ophthalmology and Visual Sciences and Genetics and Genome Sciences, Case Western Reserve University, Cleveland, Ohio
- Louis Stokes Cleveland VA Medical Center, Cleveland, Ohio
| | - Shiuh-Wen Luoh
- VA Portland Health Care System, Portland, Oregon
- Division of Hematology and Medical Oncology, Knight Cancer Institute, Oregon Health and Science University, Portland
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16
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Tuteja S, Yu Z, Wilson O, Chen H, Wendt F, Chung CP, Shah SC, Hunt CM, Suzuki A, Chanfreau C, Gorman BR, Joseph J, Luoh S, Napolioni V, Robinson‐Cohen C, Tao R, Zhou J, Chang K, Hung AM. Pharmacogenetic variants and risk of remdesivir-associated liver enzyme elevations in Million Veteran Program participants hospitalized with COVID-19. Clin Transl Sci 2022; 15:1880-1886. [PMID: 35684976 PMCID: PMC9347806 DOI: 10.1111/cts.13313] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 05/04/2022] [Accepted: 05/06/2022] [Indexed: 01/17/2023] Open
Abstract
Remdesivir is the first US Food and Drug Administration (FDA)-approved drug for the treatment of coronavirus disease 2019 (COVID-19). We conducted a retrospective pharmacogenetic study to examine remdesivir-associated liver enzyme elevation among Million Veteran Program participants hospitalized with COVID-19 between March 15, 2020, and June 30, 2021. Pharmacogene phenotypes were assigned using Stargazer. Linear regression was performed on peak log-transformed enzyme values, stratified by population, adjusted for age, sex, baseline liver enzymes, comorbidities, and 10 population-specific principal components. Patients on remdesivir had higher peak alanine aminotransferase (ALT) values following treatment initiation compared with patients not receiving remdesivir. Remdesivir administration was associated with a 33% and 24% higher peak ALT in non-Hispanic White (NHW) and non-Hispanic Black (NHB) participants (p < 0.001), respectively. In a multivariable model, NHW CYP2C19 intermediate/poor metabolizers had a 9% increased peak ALT compared with NHW normal/rapid/ultrarapid metabolizers (p = 0.015); this association was not observed in NHB participants. In summary, remdesivir-associated ALT elevations appear to be multifactorial, and further studies are needed.
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Affiliation(s)
- Sony Tuteja
- Corporal Michael J. Crescenz VA Medical Center and University of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Zhihong Yu
- Tennessee Valley Healthcare System Nashville VA and Vanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Otis Wilson
- Tennessee Valley Healthcare System Nashville VA and Vanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Hua‐Chang Chen
- Tennessee Valley Healthcare System Nashville VA and Vanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Frank Wendt
- VA CT Healthcare System and Yale School of Medicine Department of PsychiatryNew HavenConnecticutUSA
| | - Cecilia P. Chung
- Tennessee Valley Healthcare System Nashville VA and Vanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Shailja C. Shah
- VA San Diego Healthcare System and Division of GastroenterologyUniversity of California San DiegoSan DiegoCaliforniaUSA
| | - Christine M. Hunt
- Durham VA Healthcare System and Duke University School of MedicineDurhamNorth CarolinaUSA
| | - Ayako Suzuki
- Durham VA Healthcare System and Duke University School of MedicineDurhamNorth CarolinaUSA
| | - Catherine Chanfreau
- VA Informatics and Computing Infrastructure (VINCI)VA Salt Lake City Health Care SystemSalt Lake CityUtahUSA
| | | | - Jacob Joseph
- Cardiology Section, VA Boston Healthcare System and Cardiovascular DivisionBrigham & Women's HospitalBostonMassachusettsUSA
| | | | - Valerio Napolioni
- School of Biosciences and Veterinary MedicineUniversity of CamerinoCamerinoItaly,Department of Neurology and Neurological SciencesStanford University School of MedicineStanfordCaliforniaUSA
| | - Cassianne Robinson‐Cohen
- Division of Nephrology and Hypertension, Department of MedicineVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Ran Tao
- Department of BiostatisticsVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Jin Zhou
- Department of Epidemiology and BiostatisticsUniversity of ArizonaTucsonArizonaUSA
| | - Kyong‐Mi Chang
- Corporal Michael J. Crescenz VA Medical Center and University of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Adriana M. Hung
- Tennessee Valley Healthcare System Nashville VA and Vanderbilt University Medical CenterNashvilleTennesseeUSA
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17
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Gaziano L, Giambartolomei C, Pereira AC, Gaulton A, Posner DC, Swanson SA, Ho YL, Iyengar SK, Kosik NM, Vujkovic M, Gagnon DR, Bento AP, Barrio-Hernandez I, Rönnblom L, Hagberg N, Lundtoft C, Langenberg C, Pietzner M, Valentine D, Gustincich S, Tartaglia GG, Allara E, Surendran P, Burgess S, Zhao JH, Peters JE, Prins BP, Angelantonio ED, Devineni P, Shi Y, Lynch KE, DuVall SL, Garcon H, Thomann LO, Zhou JJ, Gorman BR, Huffman JE, O'Donnell CJ, Tsao PS, Beckham JC, Pyarajan S, Muralidhar S, Huang GD, Ramoni R, Beltrao P, Danesh J, Hung AM, Chang KM, Sun YV, Joseph J, Leach AR, Edwards TL, Cho K, Gaziano JM, Butterworth AS, Casas JP. Actionable druggable genome-wide Mendelian randomization identifies repurposing opportunities for COVID-19. Nat Med 2021; 27:668-676. [PMID: 33837377 PMCID: PMC7612986 DOI: 10.1038/s41591-021-01310-z] [Citation(s) in RCA: 86] [Impact Index Per Article: 28.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Accepted: 03/05/2021] [Indexed: 12/31/2022]
Abstract
Drug repurposing provides a rapid approach to meet the urgent need for therapeutics to address COVID-19. To identify therapeutic targets relevant to COVID-19, we conducted Mendelian randomization analyses, deriving genetic instruments based on transcriptomic and proteomic data for 1,263 actionable proteins that are targeted by approved drugs or in clinical phase of drug development. Using summary statistics from the Host Genetics Initiative and the Million Veteran Program, we studied 7,554 patients hospitalized with COVID-19 and >1 million controls. We found significant Mendelian randomization results for three proteins (ACE2, P = 1.6 × 10-6; IFNAR2, P = 9.8 × 10-11 and IL-10RB, P = 2.3 × 10-14) using cis-expression quantitative trait loci genetic instruments that also had strong evidence for colocalization with COVID-19 hospitalization. To disentangle the shared expression quantitative trait loci signal for IL10RB and IFNAR2, we conducted phenome-wide association scans and pathway enrichment analysis, which suggested that IFNAR2 is more likely to play a role in COVID-19 hospitalization. Our findings prioritize trials of drugs targeting IFNAR2 and ACE2 for early management of COVID-19.
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Affiliation(s)
- Liam Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Claudia Giambartolomei
- Central RNA Lab, Istituto Italiano di Tecnologia, Genoa, Italy
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Alexandre C Pereira
- Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of São Paulo, São Paulo, Brazil
- Genetics Department, Harvard Medical School, Harvard University, Boston, MA, USA
| | - Anna Gaulton
- Chemical Biology, European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Daniel C Posner
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Sonja A Swanson
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Yuk-Lam Ho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Sudha K Iyengar
- Louis Stokes Cleveland VA Medical Center, Cleveland, OH, USA
- Department of Population and Quantitative Health Sciences, Case Western Reserve University and Louis Stoke, Cleveland VA, Cleveland, OH, USA
| | - Nicole M Kosik
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Marijana Vujkovic
- The Corporal Michael J. Crescenz VA Medical Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - David R Gagnon
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
- Biostatistics, School of Public Health, Boston University, Boston, MA, USA
| | - A Patrícia Bento
- Chemical Biology, European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | | | - Lars Rönnblom
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Niklas Hagberg
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | | | - Claudia Langenberg
- Berlin Institute of Health, Charité University Medicine Berlin, Berlin, Germany
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Maik Pietzner
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Dennis Valentine
- Institute of Health Informatics, University College London, London, UK
- Health Data Research, University College London, London, UK
| | | | | | - Elias Allara
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Praveen Surendran
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Stephen Burgess
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - Jing Hua Zhao
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - James E Peters
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- Centre for Inflammatory Disease, Dept of Immunology and Inflammation, Imperial College, London, UK
| | - Bram P Prins
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
| | - Emanuele Di Angelantonio
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK
- National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, UK
| | - Poornima Devineni
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Yunling Shi
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Kristine E Lynch
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Internal Medicine, Epidemiology, University of Utah, Salt Lake City, UT, USA
| | - Scott L DuVall
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Internal Medicine, Epidemiology, University of Utah, Salt Lake City, UT, USA
| | - Helene Garcon
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Lauren O Thomann
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Jin J Zhou
- Department of Epidemiology and Biostatistics, University of Arizona, Tucson, AZ, USA
- Phoenix VA Health Care System, Phoenix, AZ, USA
| | - Bryan R Gorman
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Jennifer E Huffman
- Center for Population Genomics, Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Christopher J O'Donnell
- Cardiology, VA Boston Healthcare System, Boston, MA, USA
- Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Philip S Tsao
- Epidemiology Research and Information Center (ERIC), VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Medicine, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Jean C Beckham
- MIRECC, Durham VA Medical Center, Durham, NC, USA
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Saiju Pyarajan
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Sumitra Muralidhar
- Office of Research and Development, Department of Veterans Affairs, Washington, DC, USA
| | - Grant D Huang
- Office of Research and Development, Department of Veterans Affairs, Washington, DC, USA
| | - Rachel Ramoni
- Office of Research and Development, Department of Veterans Affairs, Washington, DC, USA
| | - Pedro Beltrao
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - John Danesh
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK
- National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, UK
| | - Adriana M Hung
- VA Tennessee Valley Healthcare System, Nashville, TN, USA
- Nephrology & Hypertension, Vanderbilt University, Nashville, TN, USA
| | - Kyong-Mi Chang
- Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
- The Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
| | - Yan V Sun
- Atlanta VA Health Care System, Decatur, GA, USA
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
| | - Jacob Joseph
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
- Medicine, Cardiovascular, VA Boston Healthcare System and Brigham & Women's Hospital, Boston, MA, USA
| | - Andrew R Leach
- Chemical Biology, European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Todd L Edwards
- Department of Veterans Affairs, Tennessee Valley Healthcare System, Vanderbilt University, Nashville, TN, USA
- Medicine, Epidemiology, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
- Division of Aging, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - J Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
- Division of Aging, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Adam S Butterworth
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK.
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK.
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK.
- National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, UK.
| | - Juan P Casas
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA.
- Division of Aging, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
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18
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Gorman BR, Lu J, Baccei A, Lowry NC, Purvis JE, Mangoubi RS, Lerou PH. Multi-scale imaging and informatics pipeline for in situ pluripotent stem cell analysis. PLoS One 2014; 9:e116037. [PMID: 25551762 PMCID: PMC4281228 DOI: 10.1371/journal.pone.0116037] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2014] [Accepted: 12/01/2014] [Indexed: 01/01/2023] Open
Abstract
Human pluripotent stem (hPS) cells are a potential source of cells for medical therapy and an ideal system to study fate decisions in early development. However, hPS cells cultured in vitro exhibit a high degree of heterogeneity, presenting an obstacle to clinical translation. hPS cells grow in spatially patterned colony structures, necessitating quantitative single-cell image analysis. We offer a tool for analyzing the spatial population context of hPS cells that integrates automated fluorescent microscopy with an analysis pipeline. It enables high-throughput detection of colonies at low resolution, with single-cellular and sub-cellular analysis at high resolutions, generating seamless in situ maps of single-cellular data organized by colony. We demonstrate the tool's utility by analyzing inter- and intra-colony heterogeneity of hPS cell cycle regulation and pluripotency marker expression. We measured the heterogeneity within individual colonies by analyzing cell cycle as a function of distance. Cells loosely associated with the outside of the colony are more likely to be in G1, reflecting a less pluripotent state, while cells within the first pluripotent layer are more likely to be in G2, possibly reflecting a G2/M block. Our multi-scale analysis tool groups colony regions into density classes, and cells belonging to those classes have distinct distributions of pluripotency markers and respond differently to DNA damage induction. Lastly, we demonstrate that our pipeline can robustly handle high-content, high-resolution single molecular mRNA FISH data by using novel image processing techniques. Overall, the imaging informatics pipeline presented offers a novel approach to the analysis of hPS cells that includes not only single cell features but also colony wide, and more generally, multi-scale spatial configuration.
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Affiliation(s)
- Bryan R. Gorman
- Department Of Pediatric Newborn Medicine and Department of Medicine, Division of Genetics, Brigham and Women's Hospital; Harvard Medical School; Harvard Stem Cell Institute, Boston, Massachusetts, United States of America
- Harvard-MIT Division Of Health Sciences and Technology, Massachusetts Institute Of Technology, Cambridge, Massachusetts, United States of America
- Charles Stark Draper Laboratory, Cambridge, Massachusetts, United States of America
| | - Junjie Lu
- Department Of Pediatric Newborn Medicine and Department of Medicine, Division of Genetics, Brigham and Women's Hospital; Harvard Medical School; Harvard Stem Cell Institute, Boston, Massachusetts, United States of America
| | - Anna Baccei
- Department Of Pediatric Newborn Medicine and Department of Medicine, Division of Genetics, Brigham and Women's Hospital; Harvard Medical School; Harvard Stem Cell Institute, Boston, Massachusetts, United States of America
| | - Nathan C. Lowry
- Charles Stark Draper Laboratory, Cambridge, Massachusetts, United States of America
| | - Jeremy E. Purvis
- Department Of Genetics, University of North Carolina School of Medicine, Chapel Hill, North Carolina, United States of America
| | - Rami S. Mangoubi
- Charles Stark Draper Laboratory, Cambridge, Massachusetts, United States of America
| | - Paul H. Lerou
- Department Of Pediatric Newborn Medicine and Department of Medicine, Division of Genetics, Brigham and Women's Hospital; Harvard Medical School; Harvard Stem Cell Institute, Boston, Massachusetts, United States of America
- * E-mail:
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