1
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Elmore AR, Adhikari N, Hartley AE, Aparicio HJ, Posner DC, Hemani G, Tilling K, Gaunt TR, Wilson PW, Casas JP, Gaziano JM, Davey Smith G, Paternoster L, Cho K, Peloso GM. Protein Identification for Stroke Progression via Mendelian Randomization in Million Veteran Program and UK Biobank. Stroke 2024; 55:2045-2054. [PMID: 39038097 PMCID: PMC11259242 DOI: 10.1161/strokeaha.124.047103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Accepted: 06/07/2024] [Indexed: 07/24/2024]
Abstract
BACKGROUND Individuals who have experienced a stroke, or transient ischemic attack, face a heightened risk of future cardiovascular events. Identification of genetic and molecular risk factors for subsequent cardiovascular outcomes may identify effective therapeutic targets to improve prognosis after an incident stroke. METHODS We performed genome-wide association studies for subsequent major adverse cardiovascular events (MACE; ncases=51 929; ncontrols=39 980) and subsequent arterial ischemic stroke (AIS; ncases=45 120; ncontrols=46 789) after the first incident stroke within the Million Veteran Program and UK Biobank. We then used genetic variants associated with proteins (protein quantitative trait loci) to determine the effect of 1463 plasma protein abundances on subsequent MACE using Mendelian randomization. RESULTS Two variants were significantly associated with subsequent cardiovascular events: rs76472767 near gene RNF220 (odds ratio, 0.75 [95% CI, 0.64-0.85]; P=3.69×10-8) with subsequent AIS and rs13294166 near gene LINC01492 (odds ratio, 1.52 [95% CI, 1.37-1.67]; P=3.77×10-8) with subsequent MACE. Using Mendelian randomization, we identified 2 proteins with an effect on subsequent MACE after a stroke: CCL27 ([C-C motif chemokine 27], effect odds ratio, 0.77 [95% CI, 0.66-0.88]; adjusted P=0.05) and TNFRSF14 ([tumor necrosis factor receptor superfamily member 14], effect odds ratio, 1.42 [95% CI, 1.24-1.60]; adjusted P=0.006). These proteins are not associated with incident AIS and are implicated to have a role in inflammation. CONCLUSIONS We found evidence that 2 proteins with little effect on incident stroke appear to influence subsequent MACE after incident AIS. These associations suggest that inflammation is a contributing factor to subsequent MACE outcomes after incident AIS and highlights potential novel targets.
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Affiliation(s)
- Andrew R. Elmore
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol, United Kingdom (A.R.E., A.E.H., G.H., K.T., T.R.G., G.D.S., L.P.)
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, United Kingdom (A.R.E., A.E.H., G.H., K.T., T.R.G., G.D.S., L.P.)
| | - Nimish Adhikari
- Veteran’s Affairs Healthcare System, Boston, MA (N.A., D.C.P., J.P.C., J.M.G., K.C., G.M.P.)
- Department of Biostatistics, Boston University School of Public Health, MA (N.A., G.M.P.)
| | - April E. Hartley
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol, United Kingdom (A.R.E., A.E.H., G.H., K.T., T.R.G., G.D.S., L.P.)
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, United Kingdom (A.R.E., A.E.H., G.H., K.T., T.R.G., G.D.S., L.P.)
| | - Hugo Javier Aparicio
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, MA (H.J.A.)
- Boston Medical Center, MA (H.J.A.)
| | - Daniel C. Posner
- Veteran’s Affairs Healthcare System, Boston, MA (N.A., D.C.P., J.P.C., J.M.G., K.C., G.M.P.)
| | - Gibran Hemani
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol, United Kingdom (A.R.E., A.E.H., G.H., K.T., T.R.G., G.D.S., L.P.)
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, United Kingdom (A.R.E., A.E.H., G.H., K.T., T.R.G., G.D.S., L.P.)
| | - Kate Tilling
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol, United Kingdom (A.R.E., A.E.H., G.H., K.T., T.R.G., G.D.S., L.P.)
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, United Kingdom (A.R.E., A.E.H., G.H., K.T., T.R.G., G.D.S., L.P.)
| | - Tom R. Gaunt
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol, United Kingdom (A.R.E., A.E.H., G.H., K.T., T.R.G., G.D.S., L.P.)
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, United Kingdom (A.R.E., A.E.H., G.H., K.T., T.R.G., G.D.S., L.P.)
| | | | - Juan P. Casas
- Veteran’s Affairs Healthcare System, Boston, MA (N.A., D.C.P., J.P.C., J.M.G., K.C., G.M.P.)
- Division of Aging, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA (J.P.C., J.M.G., K.C.)
| | - John Michael Gaziano
- Veteran’s Affairs Healthcare System, Boston, MA (N.A., D.C.P., J.P.C., J.M.G., K.C., G.M.P.)
- Division of Aging, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA (J.P.C., J.M.G., K.C.)
| | - George Davey Smith
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol, United Kingdom (A.R.E., A.E.H., G.H., K.T., T.R.G., G.D.S., L.P.)
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, United Kingdom (A.R.E., A.E.H., G.H., K.T., T.R.G., G.D.S., L.P.)
| | - Lavinia Paternoster
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol, United Kingdom (A.R.E., A.E.H., G.H., K.T., T.R.G., G.D.S., L.P.)
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, United Kingdom (A.R.E., A.E.H., G.H., K.T., T.R.G., G.D.S., L.P.)
| | - Kelly Cho
- Veteran’s Affairs Healthcare System, Boston, MA (N.A., D.C.P., J.P.C., J.M.G., K.C., G.M.P.)
- Division of Aging, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA (J.P.C., J.M.G., K.C.)
| | - Gina M. Peloso
- Veteran’s Affairs Healthcare System, Boston, MA (N.A., D.C.P., J.P.C., J.M.G., K.C., G.M.P.)
- Department of Biostatistics, Boston University School of Public Health, MA (N.A., G.M.P.)
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2
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Verma A, Huffman JE, Rodriguez A, Conery M, Liu M, Ho YL, Kim Y, Heise DA, Guare L, Panickan VA, Garcon H, Linares F, Costa L, Goethert I, Tipton R, Honerlaw J, Davies L, Whitbourne S, Cohen J, Posner DC, Sangar R, Murray M, Wang X, Dochtermann DR, Devineni P, Shi Y, Nandi TN, Assimes TL, Brunette CA, Carroll RJ, Clifford R, Duvall S, Gelernter J, Hung A, Iyengar SK, Joseph J, Kember R, Kranzler H, Kripke CM, Levey D, Luoh SW, Merritt VC, Overstreet C, Deak JD, Grant SFA, Polimanti R, Roussos P, Shakt G, Sun YV, Tsao N, Venkatesh S, Voloudakis G, Justice A, Begoli E, Ramoni R, Tourassi G, Pyarajan S, Tsao P, O'Donnell CJ, Muralidhar S, Moser J, Casas JP, Bick AG, Zhou W, Cai T, Voight BF, Cho K, Gaziano JM, Madduri RK, Damrauer S, Liao KP. Diversity and scale: Genetic architecture of 2068 traits in the VA Million Veteran Program. Science 2024; 385:eadj1182. [PMID: 39024449 DOI: 10.1126/science.adj1182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 05/10/2024] [Indexed: 07/20/2024]
Abstract
One of the justifiable criticisms of human genetic studies is the underrepresentation of participants from diverse populations. Lack of inclusion must be addressed at-scale to identify causal disease factors and understand the genetic causes of health disparities. We present genome-wide associations for 2068 traits from 635,969 participants in the Department of Veterans Affairs Million Veteran Program, a longitudinal study of diverse United States Veterans. Systematic analysis revealed 13,672 genomic risk loci; 1608 were only significant after including non-European populations. Fine-mapping identified causal variants at 6318 signals across 613 traits. One-third (n = 2069) were identified in participants from non-European populations. This reveals a broadly similar genetic architecture across populations, highlights genetic insights gained from underrepresented groups, and presents an extensive atlas of genetic associations.
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Affiliation(s)
- Anurag Verma
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA 19104, USA
- Department of Medicine, Division of Translational Medicine and Human Genetics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
- Institute for Biomedical Informatics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Jennifer E Huffman
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA 02130, USA
- Palo Alto Veterans Institute for Research (PAVIR), Palo Alto Health Care System, Palo Alto, CA 94304, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Alex Rodriguez
- Data Science and Learning, Argonne National Laboratory, Lemont, IL 60439, USA
| | - Mitchell Conery
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Molei Liu
- Department of Biostatistics, Columbia University's Mailman School of Public Health, New York, NY 10032, USA
| | - Yuk-Lam Ho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA 02130, USA
| | - Youngdae Kim
- Mathematics and Computer Science Division, Argonne National Laboratory, Lemont, IL 60439, USA
| | - David A Heise
- National Security Sciences Directorate, Cyber Resilience and Intelligence Division, Oak Ridge National Laboratory, Dept of Energy, Oak Ridge, TN 37831, USA
| | - Lindsay Guare
- Department of Medicine, Division of Translational Medicine and Human Genetics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
| | | | - Helene Garcon
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA 02130, USA
| | - Franciel Linares
- R&D Systems Engineering, Information Technology Services Directorate, Oak Ridge National Laboratory, Dept of Energy, Oak Ridge, TN 37831, USA
| | - Lauren Costa
- MVP Boston Coordinating Center, VA Boston Healthcare System, Boston, MA 02111, USA
| | - Ian Goethert
- Data Management and Engineering, Information Technology Services Division, Oak Ridge National Laboratory, Dept of Energy, Oak Ridge, TN 37831, USA
| | - Ryan Tipton
- Knowledge Discovery Infrastructure, Information Technology Services Division, Oak Ridge National Laboratory, Dept of Energy, Oak Ridge, TN 37831, USA
| | - Jacqueline Honerlaw
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA 02130, USA
| | - Laura Davies
- Computing and Computational Sciences Dir PMO, PMO, Oak Ridge National Laboratory, Dept of Energy, Oak Ridge, TN 37831, USA
| | - Stacey Whitbourne
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- MVP Boston Coordinating Center, VA Boston Healthcare System, Boston, MA 02111, USA
- Department of Medicine, Division of Aging, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Jeremy Cohen
- National Security Sciences Directorate, Cyber Resilience and Intelligence Division, Oak Ridge National Laboratory, Dept of Energy, Oak Ridge, TN 37831, USA
| | - Daniel C Posner
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA 02130, USA
| | - Rahul Sangar
- MVP Boston Coordinating Center, VA Boston Healthcare System, Boston, MA 02111, USA
| | - Michael Murray
- MVP Boston Coordinating Center, VA Boston Healthcare System, Boston, MA 02111, USA
| | - Xuan Wang
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
- Department of Population Health Sciences, University of Utah, Salt Lake City, UT 84112, USA
| | - Daniel R Dochtermann
- VA Cooperative Studies Program, VA Boston Healthcare System, Boston, MA 02130, USA
| | - Poornima Devineni
- VA Cooperative Studies Program, VA Boston Healthcare System, Boston, MA 02130, USA
| | - Yunling Shi
- VA Cooperative Studies Program, VA Boston Healthcare System, Boston, MA 02130, USA
| | - Tarak Nath Nandi
- Data Science and Learning, Argonne National Laboratory, Lemont, IL 60439, USA
| | | | - Charles A Brunette
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- Research Service, VA Boston Healthcare System, Boston, MA 02130, USA
| | - Robert J Carroll
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37211, USA
| | - Royce Clifford
- Research Department, VA San Diego Healthcare System, San Diego, CA 92161, USA
- Department of Otolaryngology, UCSD San Diego, La Jolla, CA 92093, USA
| | - Scott Duvall
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT 84148, USA
- Internal Medicine, Epidemiology, University of Utah School of Medicine, Salt Lake City, UT 84132, USA
| | - Joel Gelernter
- Psychiatry, Human Genetics, Yale University, New Haven, CT, 06520, USA
- VA Connecticut Healthcare System West Haven, West Haven, CT, 06516, USA
| | - Adriana Hung
- Medicine, Nephrology & Hypertension, VA Tennessee Valley Healthcare System & Vanderbilt University, Nashville, TN 37232, USA
| | - Sudha K Iyengar
- Departments of Population and Quantitative Health Sciences, Genetics and Genome Sciences, and Ophthalmology and Visual Sciences and the Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Jacob Joseph
- Medicine, Cardiology Section, VA Providence Healthcare System, Providence, RI 02908, USA
- Department of Medicine, Brown University, Providence, RI, 02908, USA
| | - Rachel Kember
- Mental Illness Research, Education and Clinical Center, Corporal Michael Crescenz VA Medical Center, Philadelphia, PA 19104, USA
- Department of Psychiatry, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Henry Kranzler
- Mental Illness Research, Education and Clinical Center, Corporal Michael Crescenz VA Medical Center, Philadelphia, PA 19104, USA
- Department of Psychiatry, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Colleen M Kripke
- Department of Medicine, Division of Translational Medicine and Human Genetics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Daniel Levey
- Psychiatry, Human Genetics, Yale University, New Haven, CT, 06520, USA
- Medicine, VA Connecticut Healthcare System West Haven, West Haven, CT 06516, USA
| | - Shiuh-Wen Luoh
- VA Portland Health Care System, Portland, OR 97239, USA
- Division of Hematology and Medical Oncology, Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239, USA
| | - Victoria C Merritt
- Research Department, VA San Diego Healthcare System, San Diego, CA 92161, USA
| | - Cassie Overstreet
- Psychiatry, Human Genetics, Yale University, New Haven, CT, 06520, USA
| | - Joseph D Deak
- Psychiatry, Yale University, New Haven, CT 06520, USA
- Psychiatry, VA Connecticut Healthcare System West Haven, West Haven, CT 06516, USA
| | - Struan F A Grant
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Pediatrics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
- Divisions of Human Genetics and Endocrinology and Diabetes, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Genetics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
| | | | - Panos Roussos
- Psychiatry, Mental Illness Research, Education and Clinical Center, James J. Peters VA Medical Center; Icahn School of Medicine at Mount Sinai, Bronx, NY 10468, USA
| | - Gabrielle Shakt
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA 19104, USA
- Department of Surgery, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Yan V Sun
- Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA 30322, USA
| | - Noah Tsao
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA 19104, USA
- Department of Surgery, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Sanan Venkatesh
- Psychiatry, Mental Illness Research, Education and Clinical Center, James J. Peters VA Medical Center; Icahn School of Medicine at Mount Sinai, Bronx, NY 10468, USA
| | - Georgios Voloudakis
- Psychiatry, Mental Illness Research, Education and Clinical Center, James J. Peters VA Medical Center; Icahn School of Medicine at Mount Sinai, Bronx, NY 10468, USA
| | - Amy Justice
- Medicine, VA Connecticut Healthcare System West Haven, West Haven, CT 06516, USA
- Internal Medicine, General Medicine, Yale University, New Haven, CT 06520, USA
- Health Policy, Yale School of Public Health, New Haven, CT 06520, USA
| | - Edmon Begoli
- Oak Ridge National Laboratory, Dept of Energy, Oak Ridge, TN, 37831, USA
| | - Rachel Ramoni
- Office of Research and Development, Department of Veterans Affairs, Washington, DC, 20420, USA
| | - Georgia Tourassi
- National Center for Computational Sciences, Oak Ridge National Laboratory, Dept of Energy, Oak Ridge, TN, 37831, USA
| | - Saiju Pyarajan
- VA Cooperative Studies Program, VA Boston Healthcare System, Boston, MA 02130, USA
| | - Philip Tsao
- Medicine, Cardiology, VA Palo Alto Healthcare System, Palo Alto, CA 94304, USA
- Department of Medicine, Stanford University, Palo Alto, CA, 94304, USA
| | | | - Sumitra Muralidhar
- Office of Research and Development, Department of Veterans Affairs, Washington, DC, 20420, USA
| | - Jennifer Moser
- Office of Research and Development, Department of Veterans Affairs, Washington, DC, 20420, USA
| | - Juan P Casas
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA 02130, USA
| | - Alexander G Bick
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University, Nashville, TN, 37325, USA
| | - Wei Zhou
- Department of Medicine, Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research, Cambridge, MA 02142, USA
- Program in Medical and Population Genetics, Cambridge, MA 02142, USA
| | - Tianxi Cai
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
| | - Benjamin F Voight
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA 19104, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
- Department of Genetics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
- Institute of Translational Medicine and Therapeutics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Kelly Cho
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- MVP Boston Coordinating Center, VA Boston Healthcare System, Boston, MA 02111, USA
- Department of Medicine, Division of Aging, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - J Michael Gaziano
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- MVP Boston Coordinating Center, VA Boston Healthcare System, Boston, MA 02111, USA
- Department of Medicine, Division of Aging, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Ravi K Madduri
- Data Science and Learning, Argonne National Laboratory, Lemont, IL 60439, USA
| | - Scott Damrauer
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA 19104, USA
- Department of Genetics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
- Department of Surgery, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
- Cardiovascular Institute, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Katherine P Liao
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA 02130, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
- Medicine, Rheumatology, VA Boston Healthcare System, Boston, MA 02130, USA
- Department of Medicine, Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Boston, MA 02115, USA
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3
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Neale ZE, Fonda JR, Miller MW, Wolf EJ, Zhang R, Sherva R, Harrington KM, Merritt V, Panizzon MS, Hauger RL, Gaziano JM, Logue MW. Subjective cognitive concerns, APOE ε4, PTSD symptoms, and risk for dementia among older veterans. Alzheimers Res Ther 2024; 16:143. [PMID: 38951900 PMCID: PMC11218206 DOI: 10.1186/s13195-024-01512-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Accepted: 06/20/2024] [Indexed: 07/03/2024]
Abstract
BACKGROUND Posttraumatic stress disorder (PTSD) and traumatic brain injury (TBI) are associated with self-reported problems with cognition as well as risk for Alzheimer's disease and related dementias (ADRD). Overlapping symptom profiles observed in cognitive disorders, psychiatric disorders, and environmental exposures (e.g., head injury) can complicate the detection of early signs of ADRD. The interplay between PTSD, head injury, subjective (self-reported) cognitive concerns and genetic risk for ADRD is also not well understood, particularly in diverse ancestry groups. METHODS Using data from the U.S. Department of Veterans Affairs (VA) Million Veteran Program (MVP), we examined the relationship between dementia risk factors (APOE ε4, PTSD, TBI) and subjective cognitive concerns (SCC) measured in individuals of European (n = 140,921), African (n = 15,788), and Hispanic (n = 8,064) ancestry (EA, AA, and HA, respectively). We then used data from the VA electronic medical record to perform a retrospective survival analysis evaluating PTSD, TBI, APOE ε4, and SCC and their associations with risk of conversion to ADRD in Veterans aged 65 and older. RESULTS PTSD symptoms (B = 0.50-0.52, p < 1E-250) and probable TBI (B = 0.05-0.19, p = 1.51E-07 - 0.002) were positively associated with SCC across all three ancestry groups. APOE ε4 was associated with greater SCC in EA Veterans aged 65 and older (B = 0.037, p = 1.88E-12). Results of Cox models indicated that PTSD symptoms (hazard ratio [HR] = 1.13-1.21), APOE ε4 (HR = 1.73-2.05) and SCC (HR = 1.18-1.37) were positively associated with risk for ADRD across all three ancestry groups. In the EA group, probable TBI also contributed to increased risk of ADRD (HR = 1.18). CONCLUSIONS The findings underscore the value of SCC as an indicator of ADRD risk in Veterans 65 and older when considered in conjunction with other influential genetic, clinical, and demographic risk factors.
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Affiliation(s)
- Zoe E Neale
- National Center for PTSD, Behavioral Sciences Division, VA Boston Healthcare System, 150 South Huntington Ave (116B-2), Boston, MA, 02130, USA
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
- Institute for Genomics in Health (IGH), SUNY Downstate Health Sciences University, Brooklyn, NY, USA
| | - Jennifer R Fonda
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, 02130, USA
- Translational Research Center for TBI and Stress Disorders (TRACTS) and Geriatric Research, Educational and Clinical Center (GRECC), VA Boston Healthcare System, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Mark W Miller
- National Center for PTSD, Behavioral Sciences Division, VA Boston Healthcare System, 150 South Huntington Ave (116B-2), Boston, MA, 02130, USA
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, 02130, USA
| | - Erika J Wolf
- National Center for PTSD, Behavioral Sciences Division, VA Boston Healthcare System, 150 South Huntington Ave (116B-2), Boston, MA, 02130, USA
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, 02130, USA
| | - Rui Zhang
- National Center for PTSD, Behavioral Sciences Division, VA Boston Healthcare System, 150 South Huntington Ave (116B-2), Boston, MA, 02130, USA
| | - Richard Sherva
- Biomedical Genetics, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, 02130, USA
| | - Kelly M Harrington
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, 02130, USA
- Million Veteran Program (MVP) Coordinating Center, VA Boston Healthcare System, Boston, MA, USA
| | - Victoria Merritt
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California, La Jolla, San Diego, CA, USA
| | - Matthew S Panizzon
- Department of Psychiatry, University of California, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| | - Richard L Hauger
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| | - J Michael Gaziano
- Million Veteran Program (MVP) Coordinating Center, VA Boston Healthcare System, Boston, MA, USA
- Division of Aging, Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Mark W Logue
- National Center for PTSD, Behavioral Sciences Division, VA Boston Healthcare System, 150 South Huntington Ave (116B-2), Boston, MA, 02130, USA.
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, 02130, USA.
- Biomedical Genetics, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, 02130, USA.
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
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4
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Rodriguez A, Kim Y, Nandi TN, Keat K, Kumar R, Bhukar R, Conery M, Liu M, Hessington J, Maheshwari K, Schmidt D, Begoli E, Tourassi G, Muralidhar S, Natarajan P, Voight BF, Cho K, Gaziano JM, Damrauer SM, Liao KP, Zhou W, Huffman JE, Verma A, Madduri RK. Accelerating Genome- and Phenome-Wide Association Studies using GPUs - A case study using data from the Million Veteran Program. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.17.594583. [PMID: 38826407 PMCID: PMC11142062 DOI: 10.1101/2024.05.17.594583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
The expansion of biobanks has significantly propelled genomic discoveries yet the sheer scale of data within these repositories poses formidable computational hurdles, particularly in handling extensive matrix operations required by prevailing statistical frameworks. In this work, we introduce computational optimizations to the SAIGE (Scalable and Accurate Implementation of Generalized Mixed Model) algorithm, notably employing a GPU-based distributed computing approach to tackle these challenges. We applied these optimizations to conduct a large-scale genome-wide association study (GWAS) across 2,068 phenotypes derived from electronic health records of 635,969 diverse participants from the Veterans Affairs (VA) Million Veteran Program (MVP). Our strategies enabled scaling up the analysis to over 6,000 nodes on the Department of Energy (DOE) Oak Ridge Leadership Computing Facility (OLCF) Summit High-Performance Computer (HPC), resulting in a 20-fold acceleration compared to the baseline model. We also provide a Docker container with our optimizations that was successfully used on multiple cloud infrastructures on UK Biobank and All of Us datasets where we showed significant time and cost benefits over the baseline SAIGE model.
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Affiliation(s)
- Alex Rodriguez
- Data Science and Learning, Argonne National Laboratory, Lemont, IL, 60439, USA
| | - Youngdae Kim
- Mathematics and Computer Science Division, Argonne National Laboratory, Lemont, IL, 60439, USA
| | - Tarak Nath Nandi
- Data Science and Learning, Argonne National Laboratory, Lemont, IL, 60439, USA
| | - Karl Keat
- Institute for Biomedical Informatics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Rachit Kumar
- Institute for Biomedical Informatics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Rohan Bhukar
- Program in Medical and Population Genetics, Cambridge, MA, 02142, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Mitchell Conery
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Molei Liu
- Department of Biostatistics, Columbia University's Mailman School of Public Health, New York, NY, 10032, USA
| | - John Hessington
- Information systems, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | | | - Drew Schmidt
- Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Edmon Begoli
- Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Georgia Tourassi
- Computing and Computational Sciences Directorate, Oak Ridge National Laboratory, Oak Ridge, TN, 37830, USA
| | - Sumitra Muralidhar
- Office of Research and Development, Department of Veterans Affairs, Washington, DC, 20420, USA
| | - Pradeep Natarajan
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, 02114, USA
- Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Cardiology Division, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Benjamin F Voight
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, 19104, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Department of Genetics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Institute of Translational Medicine and Therapeutics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Kelly Cho
- MVP Boston Coordinating Center, VA Boston Healthcare System, Boston, MA, 02111, USA
- Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA
- Department of Medicine, Division of Aging, Brigham and Women's Hospital, Boston, MA, 02115, USA
| | - J Michael Gaziano
- MVP Boston Coordinating Center, VA Boston Healthcare System, Boston, MA, 02111, USA
- Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA
- Department of Medicine, Division of Aging, Brigham and Women's Hospital, Boston, MA, 02115, USA
| | - Scott M Damrauer
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, 19104, USA
- Department of Genetics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Department of Surgery, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Cardiovascular Institute, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Katherine P Liao
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, 02130, USA
- Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA
- Medicine, Rheumatology, VA Boston Healthcare System, Boston, MA, 02130, USA
- Department of Medicine, Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Boston, MA, 02115, USA
| | - Wei Zhou
- Program in Medical and Population Genetics, Cambridge, MA, 02142, USA
- Department of Medicine, Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, 02114, USA
- Stanley Center for Psychiatric Research, Cambridge, MA, 02142, USA
| | - Jennifer E Huffman
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, 02130, USA
- Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA
- Palo Alto Veterans Institute for Research (PAVIR), Palo Alto Health Care System, Palo Alto, CA, 94304, USA
| | - Anurag Verma
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, 19104, USA
- Institute for Biomedical Informatics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Department of Medicine, Division of Translational Medicine and Human Genetics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Ravi K Madduri
- Data Science and Learning, Argonne National Laboratory, Lemont, IL, 60439, USA
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Elmore A, Adhikari N, Hartley AE, Javier Aparicio H, Posner DC, Hemani G, Tilling K, Gaunt TR, Wilson P, Casas JP, Michael Gaziano J, Smith GD, Paternoster L, Cho K, Peloso GM. Protein identification for stroke progression via Mendelian Randomization in Million Veteran Program and UK Biobank. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.01.31.24302111. [PMID: 38352469 PMCID: PMC10863017 DOI: 10.1101/2024.01.31.24302111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/19/2024]
Abstract
Background Individuals who have experienced a stroke, or transient ischemic attack, face a heightened risk of future cardiovascular events. Identification of genetic and molecular risk factors for subsequent cardiovascular outcomes may identify effective therapeutic targets to improve prognosis after an incident stroke. Methods We performed genome-wide association studies (GWAS) for subsequent major adverse cardiovascular events (MACE) (Ncases=51,929, Ncntrl=39,980) and subsequent arterial ischemic stroke (AIS) Ncases=45,120, Ncntrl=46,789) after first incident stroke within the Million Veteran Program and UK Biobank. We then used genetic variants associated with proteins (pQTLs) to determine the effect of 1,463 plasma protein abundances on subsequent MACE using Mendelian randomization (MR). Results Two variants were significantly associated with subsequent cardiovascular events: rs76472767 (OR=0.75, 95% CI = 0.64-0.85, p= 3.69×10-08) with subsequent AIS and rs13294166 (OR=1.52, 95% CI = 1.37-1.67, p=3.77×10-08) with subsequent MACE. Using MR, we identified 2 proteins with an effect on subsequent MACE after a stroke: CCL27 (effect OR= 0.77, 95% CI = 0.66-0.88, adj. p=0.05), and TNFRSF14 (effect OR=1.42, 95% CI = 1.24-1.60, adj. p=0.006). These proteins are not associated with incident AIS and are implicated to have a role in inflammation. Conclusions We found evidence that two proteins with little effect on incident stroke appear to influence subsequent MACE after incident AIS. These associations suggest that inflammation is a contributing factor to subsequent MACE outcomes after incident AIS and highlights potential novel targets.
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Affiliation(s)
- Andrew Elmore
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol
| | - Nimish Adhikari
- Veteran’s Affairs Healthcare System, Boston, MA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - April E Hartley
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol
| | - Hugo Javier Aparicio
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA
- Boston Medical Center, Boston, MA
| | | | - Gibran Hemani
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol
| | - Kate Tilling
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol
| | - Tom R Gaunt
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol
| | | | - JP Casas
- Veteran’s Affairs Healthcare System, Boston, MA
- Division of Aging, Brigham and Women’s Hospital, Harvard Medical School
| | - John Michael Gaziano
- Veteran’s Affairs Healthcare System, Boston, MA
- Division of Aging, Brigham and Women’s Hospital, Harvard Medical School
| | - George Davey Smith
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol
| | - Lavinia Paternoster
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol
| | - Kelly Cho
- Veteran’s Affairs Healthcare System, Boston, MA
- Division of Aging, Brigham and Women’s Hospital, Harvard Medical School
| | - Gina M Peloso
- Veteran’s Affairs Healthcare System, Boston, MA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
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Harrington KM, Quaden R, Steele L, Helmer DA, Hauser ER, Ahmed ST, Aslan M, Radhakrishnan K, Honerlaw J, Nguyen XMT, Muralidhar S, Concato J, Cho K, Gaziano JM, Whitbourne SB. The Million Veteran Program 1990-1991 Gulf War Era Survey: An Evaluation of Veteran Response, Characteristics, and Representativeness of the Gulf War Era Veteran Population. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2024; 21:72. [PMID: 38248536 PMCID: PMC10815483 DOI: 10.3390/ijerph21010072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 12/22/2023] [Accepted: 12/22/2023] [Indexed: 01/23/2024]
Abstract
To address gaps in understanding the pathophysiology of Gulf War Illness (GWI), the VA Million Veteran Program (MVP) developed and implemented a survey to MVP enrollees who served in the U.S. military during the 1990-1991 Persian Gulf War (GW). Eligible Veterans were invited via mail to complete a survey assessing health conditions as well as GW-specific deployment characteristics and exposures. We evaluated the representativeness of this GW-era cohort relative to the broader population by comparing demographic, military, and health characteristics between respondents and non-respondents, as well as with all GW-era Veterans who have used Veterans Health Administration (VHA) services and the full population of U.S. GW-deployed Veterans. A total of 109,976 MVP GW-era Veterans were invited to participate and 45,270 (41%) returned a completed survey. Respondents were 84% male, 72% White, 8% Hispanic, with a mean age of 61.6 years (SD = 8.5). Respondents were more likely to be older, White, married, better educated, slightly healthier, and have higher socioeconomic status than non-respondents, but reported similar medical conditions and comparable health status. Although generally similar to all GW-era Veterans using VHA services and the full population of U.S. GW Veterans, respondents included higher proportions of women and military officers, and were slightly older. In conclusion, sample characteristics of the MVP GW-era cohort can be considered generally representative of the broader GW-era Veteran population. The sample represents the largest research cohort of GW-era Veterans established to date and provides a uniquely valuable resource for conducting in-depth studies to evaluate health conditions affecting 1990-1991 GW-era Veterans.
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Affiliation(s)
- Kelly M. Harrington
- Million Veteran Program (MVP) Coordinating Center, VA Boston Healthcare System, Boston, MA 02130, USA; (R.Q.); (J.H.); (X.-M.T.N.); (K.C.); (J.M.G.); (S.B.W.)
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
| | - Rachel Quaden
- Million Veteran Program (MVP) Coordinating Center, VA Boston Healthcare System, Boston, MA 02130, USA; (R.Q.); (J.H.); (X.-M.T.N.); (K.C.); (J.M.G.); (S.B.W.)
| | - Lea Steele
- Veterans Health Research Program, Yudofsky Division of Neuropsychiatry, Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX 77030, USA;
| | - Drew A. Helmer
- Center for Innovations in Quality, Effectiveness, and Safety (IQuESt), Michael E. DeBakey VA Medical Center, Houston, TX 77030, USA; (D.A.H.); (S.T.A.)
- Department of Medicine, Baylor College of Medicine, Houston, TX 77030, USA
| | - Elizabeth R. Hauser
- VA Cooperative Studies Program Epidemiology Center-Durham, Department of Veterans Affairs, Durham, NC 27705, USA;
- Department of Biostatistics and Bioinformatics, Duke Molecular Physiology Institute, Duke University, Durham, NC 27705, USA
| | - Sarah T. Ahmed
- Center for Innovations in Quality, Effectiveness, and Safety (IQuESt), Michael E. DeBakey VA Medical Center, Houston, TX 77030, USA; (D.A.H.); (S.T.A.)
- Department of Medicine, Baylor College of Medicine, Houston, TX 77030, USA
| | - Mihaela Aslan
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT 06516, USA; (M.A.)
- Department of Internal Medicine, Yale University School of Medicine, New Haven, CT 06511, USA;
| | - Krishnan Radhakrishnan
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT 06516, USA; (M.A.)
- National Mental Health and Substance Use Policy Laboratory, Substance Abuse and Mental Health Services Administration, Rockville, MD 20857, USA
| | - Jacqueline Honerlaw
- Million Veteran Program (MVP) Coordinating Center, VA Boston Healthcare System, Boston, MA 02130, USA; (R.Q.); (J.H.); (X.-M.T.N.); (K.C.); (J.M.G.); (S.B.W.)
| | - Xuan-Mai T. Nguyen
- Million Veteran Program (MVP) Coordinating Center, VA Boston Healthcare System, Boston, MA 02130, USA; (R.Q.); (J.H.); (X.-M.T.N.); (K.C.); (J.M.G.); (S.B.W.)
- Carle Illinois College of Medicine, University of Illinois, Champaign, IL 61820, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Sumitra Muralidhar
- Office of Research and Development, Veterans Health Administration, Washington, DC 20420, USA;
| | - John Concato
- Department of Internal Medicine, Yale University School of Medicine, New Haven, CT 06511, USA;
- Food and Drug Administration, Silver Spring, MD 20993, USA
| | - Kelly Cho
- Million Veteran Program (MVP) Coordinating Center, VA Boston Healthcare System, Boston, MA 02130, USA; (R.Q.); (J.H.); (X.-M.T.N.); (K.C.); (J.M.G.); (S.B.W.)
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- Division of Aging, Department of Medicine, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - J. Michael Gaziano
- Million Veteran Program (MVP) Coordinating Center, VA Boston Healthcare System, Boston, MA 02130, USA; (R.Q.); (J.H.); (X.-M.T.N.); (K.C.); (J.M.G.); (S.B.W.)
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- Division of Aging, Department of Medicine, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - Stacey B. Whitbourne
- Million Veteran Program (MVP) Coordinating Center, VA Boston Healthcare System, Boston, MA 02130, USA; (R.Q.); (J.H.); (X.-M.T.N.); (K.C.); (J.M.G.); (S.B.W.)
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- Division of Aging, Department of Medicine, Brigham and Women’s Hospital, Boston, MA 02115, USA
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7
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Nguyen XMT, Li Y, Wang DD, Whitbourne SB, Houghton SC, Hu FB, Willett WC, Sun YV, Djousse L, Gaziano JM, Cho K, Wilson PW. Impact of 8 lifestyle factors on mortality and life expectancy among United States veterans: The Million Veteran Program. Am J Clin Nutr 2024; 119:127-135. [PMID: 38065710 DOI: 10.1016/j.ajcnut.2023.10.032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 10/26/2023] [Accepted: 10/31/2023] [Indexed: 01/06/2024] Open
Abstract
BACKGROUND Lifestyle medicine has been proposed as a way to address the root causes of chronic disease and their associated health care costs. OBJECTIVE This study aimed to estimate mortality risk and longevity associated with individual lifestyle factors and comprehensive lifestyle therapy. METHODS Age- and sex-specific mortality rates were calculated on the basis of 719,147 veterans aged 40-99 y enrolled in the Veteran Affairs Million Veteran Program (2011-2019). Hazard ratios and estimated increase in life expectancy were examined among a subgroup of 276,132 veterans with complete data on 8 lifestyle factors at baseline. The 8 lifestyle factors included never smoking, physical activity, no excessive alcohol consumption, restorative sleep, nutrition, stress management, social connections, and no opioid use disorder. RESULTS On the basis of 1.12 million person-years of follow-up, 34,247 deaths were recorded. Among veterans who adopted 1, 2, 3, 4, 5, 6, 7, and 8 lifestyle factors, the adjusted hazard ratios for mortality were 0.74 (0.60-0.90), 0.60 (95% CI: 0.49, 0.73), 0.50 (95% CI: 0.41, 0.61), 0.43 (95% CI: 0.35, 0.52), 0.35 (95% CI: 0.29, 0.43), 0.27 (95% CI: 0.22, 0.33), 0.21 (95% CI: 0.17, 0.26), and 0.13 (95% CI: 0.10, 0.16), respectively, as compared with veterans with no adopted lifestyle factors. The estimated life expectancy at age 40 y was 23.0, 26.5, 28.8, 30.8, 32.7, 35.1, 38.3, 41.3, and 47.0 y among males and 27.0, 28.8, 33.1, 38.0, 39.2, 41.4, 43.8, 46.3, and 47.5 y for females who adopted 0, 1, 2, 3, 4, 5, 6, 7, and 8 lifestyle factors, respectively. The difference in life expectancy at age 40 y was 24.0 y for male veterans and 20.5 y for female veterans when comparing adoption of 8-9 lifestyle factors. CONCLUSIONS A combination of 8 lifestyle factors is associated with a significantly lower risk of premature mortality and an estimated prolonged life expectancy.
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Affiliation(s)
- Xuan-Mai T Nguyen
- Million Veteran Program Boston Coordinating Center, VA Boston Healthcare System, Boston, MA 02111, United States; Carle Illinois College of Medicine, University of Illinois Urbana Champaign, Champaign, IL, United States
| | - Yanping Li
- Million Veteran Program Boston Coordinating Center, VA Boston Healthcare System, Boston, MA 02111, United States; Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA, United States.
| | - Dong D Wang
- Million Veteran Program Boston Coordinating Center, VA Boston Healthcare System, Boston, MA 02111, United States; Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA, United States; The Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States
| | - Stacey B Whitbourne
- Million Veteran Program Boston Coordinating Center, VA Boston Healthcare System, Boston, MA 02111, United States; Division of Aging, Brigham and Women's Hospital, Boston, MA, United States; Department of Medicine, Harvard Medical School, Boston, MA, United States
| | - Serena C Houghton
- Million Veteran Program Boston Coordinating Center, VA Boston Healthcare System, Boston, MA 02111, United States
| | - Frank B Hu
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA, United States; The Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States; Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, United States
| | - Walter C Willett
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA, United States; Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, United States
| | - Yan V Sun
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, United States; Department of Medicine, Atlanta VA Health Care System, Decatur, GA 30033, United States
| | - Luc Djousse
- Million Veteran Program Boston Coordinating Center, VA Boston Healthcare System, Boston, MA 02111, United States; Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA, United States; Division of Aging, Brigham and Women's Hospital, Boston, MA, United States; Department of Medicine, Harvard Medical School, Boston, MA, United States
| | - John Michael Gaziano
- Million Veteran Program Boston Coordinating Center, VA Boston Healthcare System, Boston, MA 02111, United States; Division of Aging, Brigham and Women's Hospital, Boston, MA, United States; Department of Medicine, Harvard Medical School, Boston, MA, United States
| | - Kelly Cho
- Million Veteran Program Boston Coordinating Center, VA Boston Healthcare System, Boston, MA 02111, United States; Division of Aging, Brigham and Women's Hospital, Boston, MA, United States; Department of Medicine, Harvard Medical School, Boston, MA, United States
| | - Peter Wf Wilson
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, United States; Department of Medicine, Atlanta VA Health Care System, Decatur, GA 30033, United States; Cardiology Division, Emory Clinical Cardiovascular Research Institute, Atlanta, GA 30033, United States
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8
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Felsky D, Cannitelli A, Pipitone J. Whole Person Modeling: a transdisciplinary approach to mental health research. DISCOVER MENTAL HEALTH 2023; 3:16. [PMID: 37638348 PMCID: PMC10449734 DOI: 10.1007/s44192-023-00041-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Accepted: 08/10/2023] [Indexed: 08/29/2023]
Abstract
The growing global burden of mental illness has prompted calls for innovative research strategies. Theoretical models of mental health include complex contributions of biological, psychosocial, experiential, and other environmental influences. Accordingly, neuropsychiatric research has self-organized into largely isolated disciplines working to decode each individual contribution. However, research directly modeling objective biological measurements in combination with cognitive, psychological, demographic, or other environmental measurements is only now beginning to proliferate. This review aims to (1) to describe the landscape of modern mental health research and current movement towards integrative study, (2) to provide a concrete framework for quantitative integrative research, which we call Whole Person Modeling, (3) to explore existing and emerging techniques and methods used in Whole Person Modeling, and (4) to discuss our observations about the scarcity, potential value, and untested aspects of highly transdisciplinary research in general. Whole Person Modeling studies have the potential to provide a better understanding of multilevel phenomena, deliver more accurate diagnostic and prognostic tests to aid in clinical decision making, and test long standing theoretical models of mental illness. Some current barriers to progress include challenges with interdisciplinary communication and collaboration, systemic cultural barriers to transdisciplinary career paths, technical challenges in model specification, bias, and data harmonization, and gaps in transdisciplinary educational programs. We hope to ease anxiety in the field surrounding the often mysterious and intimidating world of transdisciplinary, data-driven mental health research and provide a useful orientation for students or highly specialized researchers who are new to this area.
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Affiliation(s)
- Daniel Felsky
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, 250 College Street, Toronto, ON M5T 1R8 Canada
- Department of Psychiatry, Faculty of Medicine, University of Toronto, Toronto, ON Canada
- Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON Canada
- Rotman Research Institute, Baycrest Hospital, Toronto, ON Canada
- Faculty of Medicine, McMaster University, Hamilton, ON Canada
| | - Alyssa Cannitelli
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, 250 College Street, Toronto, ON M5T 1R8 Canada
- Faculty of Medicine, McMaster University, Hamilton, ON Canada
| | - Jon Pipitone
- Department of Psychiatry, Queen’s University, Kingston, ON Canada
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9
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Verma A, Huffman JE, Rodriguez A, Conery M, Liu M, Ho YL, Kim Y, Heise DA, Guare L, Panickan VA, Garcon H, Linares F, Costa L, Goethert I, Tipton R, Honerlaw J, Davies L, Whitbourne S, Cohen J, Posner DC, Sangar R, Murray M, Wang X, Dochtermann DR, Devineni P, Shi Y, Nandi TN, Assimes TL, Brunette CA, Carroll RJ, Clifford R, Duvall S, Gelernter J, Hung A, Iyengar SK, Joseph J, Kember R, Kranzler H, Levey D, Luoh SW, Merritt VC, Overstreet C, Deak JD, Grant SFA, Polimanti R, Roussos P, Sun YV, Venkatesh S, Voloudakis G, Justice A, Begoli E, Ramoni R, Tourassi G, Pyarajan S, Tsao PS, O’Donnell CJ, Muralidhar S, Moser J, Casas JP, Bick AG, Zhou W, Cai T, Voight BF, Cho K, Gaziano MJ, Madduri RK, Damrauer SM, Liao KP. Diversity and Scale: Genetic Architecture of 2,068 Traits in the VA Million Veteran Program. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.28.23291975. [PMID: 37425708 PMCID: PMC10327290 DOI: 10.1101/2023.06.28.23291975] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Genome-wide association studies (GWAS) have underrepresented individuals from non-European populations, impeding progress in characterizing the genetic architecture and consequences of health and disease traits. To address this, we present a population-stratified phenome-wide GWAS followed by a multi-population meta-analysis for 2,068 traits derived from electronic health records of 635,969 participants in the Million Veteran Program (MVP), a longitudinal cohort study of diverse U.S. Veterans genetically similar to the respective African (121,177), Admixed American (59,048), East Asian (6,702), and European (449,042) superpopulations defined by the 1000 Genomes Project. We identified 38,270 independent variants associating with one or more traits at experiment-wide P < 4.6 × 10 - 11 significance; fine-mapping 6,318 signals identified from 613 traits to single-variant resolution. Among these, a third (2,069) of the associations were found only among participants genetically similar to non-European reference populations, demonstrating the importance of expanding diversity in genetic studies. Our work provides a comprehensive atlas of phenome-wide genetic associations for future studies dissecting the architecture of complex traits in diverse populations.
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Affiliation(s)
- Anurag Verma
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, 19104, USA
- Department of Medicine, Division of Translational Medicine and Human Genetics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Institute for Biomedical Informatics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Jennifer E Huffman
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, 02130, USA
- Palo Alto Veterans Institute for Research (PAVIR), Palo Alto Health Care System, Palo Alto, CA, 94304, USA
- Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA
| | - Alex Rodriguez
- Data Science and Learning, Argonne National Laboratory, Lemont, IL, 60439, USA
| | - Mitchell Conery
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Molei Liu
- Department of Biostatistics, Columbia University’s Mailman School of Public Health, New York, NY, 10032, USA
| | - Yuk-Lam Ho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, 02130, USA
| | - Youngdae Kim
- Mathematics and Computer Science Division, Argonne National Laboratory, Lemont, IL, 60439, USA
| | - David A Heise
- National Security Sciences Directorate, Cyber Resilience and Intelligence Division, Oak Ridge National Laboratory, Dept of Energy, Oak Ridge, TN, 37831, USA
| | - Lindsay Guare
- Department of Medicine, Division of Translational Medicine and Human Genetics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | | | - Helene Garcon
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, 02130, USA
| | - Franciel Linares
- R&D Systems Engineering, Information Technology Services Directorate, Oak Ridge National Laboratory, Dept of Energy, Oak Ridge, TN, 37831, USA
| | - Lauren Costa
- MVP Boston Coordinating Center, VA Boston Healthcare System, Boston, MA, 02111, USA
| | - Ian Goethert
- Data Management and Engineering, Information Technology Services Division, Oak Ridge National Laboratory, Dept of Energy, Oak Ridge, TN, 37831, USA
| | - Ryan Tipton
- Knowledge Discovery Infrastructure, Information Technology Services Division, Oak Ridge National Laboratory, Dept of Energy, Oak Ridge, TN, 37831, USA
| | - Jacqueline Honerlaw
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, 02130, USA
| | - Laura Davies
- Computing and Computational Sciences Dir PMO, PMO, Oak Ridge National Laboratory, Dept of Energy, Oak Ridge, TN, 37831, USA
| | - Stacey Whitbourne
- Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA
- MVP Boston Coordinating Center, VA Boston Healthcare System, Boston, MA, 02111, USA
- Department of Medicine, Division of Aging, Brigham and Women’s Hospital, Boston, MA, 02115, USA
| | - Jeremy Cohen
- National Security Sciences Directorate, Cyber Resilience and Intelligence Division, Oak Ridge National Laboratory, Dept of Energy, Oak Ridge, TN, 37831, USA
| | - Daniel C Posner
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, 02130, USA
| | - Rahul Sangar
- MVP Boston Coordinating Center, VA Boston Healthcare System, Boston, MA, 02111, USA
| | - Michael Murray
- MVP Boston Coordinating Center, VA Boston Healthcare System, Boston, MA, 02111, USA
| | - Xuan Wang
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA
| | - Daniel R Dochtermann
- VA Cooperative Studies Program, VA Boston Healthcare System, Boston, MA, 02130, USA
| | - Poornima Devineni
- VA Cooperative Studies Program, VA Boston Healthcare System, Boston, MA, 02130, USA
| | - Yunling Shi
- VA Cooperative Studies Program, VA Boston Healthcare System, Boston, MA, 02130, USA
| | - Tarak Nath Nandi
- Data Science and Learning, Argonne National Laboratory, Lemont, IL, 60439, USA
| | | | - Charles A Brunette
- Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA
- Research Service, VA Boston Healthcare System, Boston, MA, 02130, USA
| | - Robert J Carroll
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, 37211, USA
| | - Royce Clifford
- Research Department, VA San Diego Healthcare System, San Diego, CA, 92161, USA
- Surgery, Otolaryngology, UCSD San Diego, La Jolla, California, 92093, USA
| | - Scott Duvall
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, 84148, USA
- Internal Medicine, Epidemiology, University of Utah School of Medicine, Salt Lake City, UT, 84132, USA
| | - Joel Gelernter
- Psychiatry, Human Genetics, Yale University, New Haven, CT, 06520, USA
- VA Connecticut Healthcare System West Haven, West Haven, CT, 06516, USA
| | - Adriana Hung
- Medicine, Nephrology & Hypertension, VA Tennessee Valley Healthcare System & Vanderbilt University, Nashville, TN, 37232, USA
| | - Sudha K Iyengar
- Population and Quantitative Health Sciences, Case Western Reserve University, School of Medicine, Cleveland, OH, 44106, USA
| | - Jacob Joseph
- Medicine, Cardiology Section, VA Providence Healthcare System, Providence, RI, 02908, USA
- Department of Medicine, Brown University, Providence, RI, 02908, USA
| | - Rachel Kember
- Mental Illness Research, Education and Clinical Center, Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, 19104, USA
- Department of Psychiatry, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Henry Kranzler
- Mental Illness Research, Education and Clinical Center, Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, 19104, USA
- Department of Psychiatry, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Daniel Levey
- Psychiatry, Human Genetics, Yale University, New Haven, CT, 06520, USA
- Medicine, VA Connecticut Healthcare System West Haven, West Haven, CT, 06516, USA
| | - Shiuh-Wen Luoh
- VA Portland Health Care System, Portland, OR, 97239, USA
- Division of Hematology and Medical Oncology, Knight Cancer Institute, Oregon Health and Science University, Portland, OR, 97239, USA
| | - Victoria C Merritt
- Research Department, VA San Diego Healthcare System, San Diego, CA, 92161, USA
| | - Cassie Overstreet
- Psychiatry, Human Genetics, Yale University, New Haven, CT, 06520, USA
| | - Joseph D Deak
- Psychiatry, Yale University, New Haven, CT, 06520, USA
- Psychiatry, VA Connecticut Healthcare System West Haven, West Haven, CT, 06516, USA
| | - Struan F A Grant
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Department of Pediatrics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Divisions of Human Genetics and Endocrinology and Diabetes, Children’s Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Department of Genetics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | | | - Panos Roussos
- Psychiatry, Mental Illness Research, Education and Clinical Center, James J. Peters VA Medical Center; Icahn School of Medicine at Mount Sinai, Bronx, NY, 10468, USA
| | - Yan V Sun
- Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, 30322, USA
| | - Sanan Venkatesh
- Psychiatry, Mental Illness Research, Education and Clinical Center, James J. Peters VA Medical Center; Icahn School of Medicine at Mount Sinai, Bronx, NY, 10468, USA
| | - Georgios Voloudakis
- Psychiatry, Mental Illness Research, Education and Clinical Center, James J. Peters VA Medical Center; Icahn School of Medicine at Mount Sinai, Bronx, NY, 10468, USA
| | - Amy Justice
- Medicine, VA Connecticut Healthcare System West Haven, West Haven, CT, 06516, USA
- Internal Medicine, General Medicine, Yale University, New Haven, CT, 06520, USA
- Health Policy, Yale School of Public Health, New Haven, CT, 06520, USA
| | - Edmon Begoli
- Oak Ridge National Laboratory, Dept of Energy, Oak Ridge, TN, 37831, USA
| | - Rachel Ramoni
- Office of Research and Development, Department of Veterans Affairs, Washington, DC, 20420, USA
| | - Georgia Tourassi
- National Center for Computational Sciences, Oak Ridge National Laboratory, Dept of Energy, Oak Ridge, TN, 37831, USA
| | - Saiju Pyarajan
- VA Cooperative Studies Program, VA Boston Healthcare System, Boston, MA, 02130, USA
| | - Philip S Tsao
- Medicine, Cardiology, VA Palo Alto Healthcare System, Palo Alto, CA, 94304, USA
- Department of Medicine, Stanford University, Palo Alto, CA, 94304, USA
| | | | - Sumitra Muralidhar
- Office of Research and Development, Department of Veterans Affairs, Washington, DC, 20420, USA
| | - Jennifer Moser
- Office of Research and Development, Department of Veterans Affairs, Washington, DC, 20420, USA
| | - Juan P Casas
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, 02130, USA
| | - Alexander G Bick
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University, Nashville, TN, 37325, USA
| | - Wei Zhou
- Department of Medicine, Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, 02114, USA
- Stanley Center for Psychiatric Research, Cambridge, MA, 02142, USA
- Program in Medical and Population Genetics, Cambridge, MA, 02142, USA
| | - Tianxi Cai
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA
| | - Benjamin F Voight
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, 19104, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Department of Genetics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Institute of Translational Medicine and Therapeutics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Kelly Cho
- Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA
- MVP Boston Coordinating Center, VA Boston Healthcare System, Boston, MA, 02111, USA
- Department of Medicine, Division of Aging, Brigham and Women’s Hospital, Boston, MA, 02115, USA
| | - Michael J Gaziano
- Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA
- MVP Boston Coordinating Center, VA Boston Healthcare System, Boston, MA, 02111, USA
- Department of Medicine, Division of Aging, Brigham and Women’s Hospital, Boston, MA, 02115, USA
| | - Ravi K Madduri
- Data Science and Learning, Argonne National Laboratory, Lemont, IL, 60439, USA
| | - Scott M Damrauer
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, 19104, USA
- Department of Genetics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Department of Surgery, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Cardiovascular Institute, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Katherine P Liao
- Medicine, Rheumatology, VA Boston Healthcare System, Boston, MA, 02130, USA
- Department of Medicine, Division of Rheumatology, Inflammation, and Immunity, Brigham and Women’s Hospital, Boston, MA, 02115, USA
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10
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Deak JD, Levey DF, Wendt FR, Zhou H, Galimberti M, Kranzler HR, Gaziano JM, Stein MB, Polimanti R, Gelernter J. Genome-Wide Investigation of Maximum Habitual Alcohol Intake in US Veterans in Relation to Alcohol Consumption Traits and Alcohol Use Disorder. JAMA Netw Open 2022; 5:e2238880. [PMID: 36301540 PMCID: PMC9614582 DOI: 10.1001/jamanetworkopen.2022.38880] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 08/30/2022] [Indexed: 11/14/2022] Open
Abstract
Importance Alcohol genome-wide association studies (GWASs) have generally focused on alcohol consumption and alcohol use disorder (AUD); few have examined habitual drinking behaviors like maximum habitual alcohol intake (MaxAlc). Objectives To identify genetic loci associated with MaxAlc and to elucidate the genetic architecture across alcohol traits. Design, Setting, and Participants This MaxAlc genetic association study was performed among Million Veteran Program participants enrolled from January 10, 2011, to September 30, 2020. Ancestry-specific GWASs were conducted in participants with European (n = 218 623) and African (n = 29 132) ancestry, then meta-analyzed (N = 247 755). Linkage-disequilibrium score regression was used to estimate single nucleotide variant (SNV)-heritability and genetic correlations (rg) with other alcohol and psychiatric traits. Genomic structural equation modeling (gSEM) was used to evaluate genetic associations between MaxAlc and other alcohol traits. Mendelian randomization was used to examine potential causal relationships between MaxAlc and liver enzyme levels. MTAG (multitrait analysis of GWAS) was used to analyze MaxAlc and problematic alcohol use (PAU) jointly. Exposures Genetic associations. Main Outcomes and Measures MaxAlc was defined from the following survey item: "in a typical month, what is/was the largest number of drinks of alcohol you may have had in one day?" with ordinal responses from 0 to 15 or more drinks. Results GWASs were conducted on sample sizes of as many as 247 455 US veterans. Participants were 92.68% male and had mean (SD) age of 65.92 (11.70) years. The MaxAlc GWAS resulted in 15 genome-wide significant loci. Top associations in European-ancestry and African-ancestry participants were with known functional variants in the ADH1B gene, namely rs1229984 (P = 3.12 × 10-101) and rs2066702 (P = 6.30 × 10-17), respectively. Novel associations were also found. SNV-heritability was 6.65% (SE, 0.41) in European-ancestry participants and 3.42% (SE, 1.46) in African-ancestry participants. MaxAlc was positively correlated with PAU (rg = 0.79; P = 3.95 × 10-149) and AUD (rg = 0.76; P = 1.26 × 10-127) and had negative rg with the UK Biobank "alcohol usually taken with meals" (rg = -0.53; P = 1.40 × 10-50). For psychiatric traits, MaxAlc had the strongest genetic correlation with suicide attempt (rg = 0.40; P = 3.02 × 10-21). gSEM supported a 2-factor model with MaxAlc loading on a factor with PAU and AUD and other alcohol consumption measures loading on a separate factor. Mendelian randomization supported an association between MaxAlc and the liver enzyme gamma-glutamyltransferase (β = 0.012; P = 2.66 × 10-10). MaxAlc MTAG resulted in 31 genome-wide significant loci. Conclusions and Relevance The findings suggest that MaxAlc closely aligns genetically with PAU traits. This study improves understanding of the mechanisms associated with normative alcohol consumption vs problematic habitual use and AUD as well as how MaxAlc relates to psychiatric and medical conditions genetically and biologically.
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Affiliation(s)
- Joseph D. Deak
- Yale School of Medicine, New Haven, Connecticut
- VA Connecticut Healthcare Center, West Haven, Connecticut
| | - Daniel F. Levey
- Yale School of Medicine, New Haven, Connecticut
- VA Connecticut Healthcare Center, West Haven, Connecticut
| | - Frank R. Wendt
- Yale School of Medicine, New Haven, Connecticut
- VA Connecticut Healthcare Center, West Haven, Connecticut
| | - Hang Zhou
- Yale School of Medicine, New Haven, Connecticut
- VA Connecticut Healthcare Center, West Haven, Connecticut
| | - Marco Galimberti
- Yale School of Medicine, New Haven, Connecticut
- VA Connecticut Healthcare Center, West Haven, Connecticut
| | - Henry R. Kranzler
- University of Pennsylvania Perelman School of Medicine, Philadelphia
- Crescenz VA Medical Center, Philadelphia, Pennsylvania
| | - J. Michael Gaziano
- Massachusetts Veterans Epidemiology and Research Information Center (MAVERIC), Boston Veterans Affairs Healthcare System, Boston
- Department of Medicine, Divisions of Aging and Preventative Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Murray B. Stein
- University of California, San Diego, La Jolla
- VA San Diego Healthcare System, San Diego, California
| | - Renato Polimanti
- Yale School of Medicine, New Haven, Connecticut
- VA Connecticut Healthcare Center, West Haven, Connecticut
| | - Joel Gelernter
- Yale School of Medicine, New Haven, Connecticut
- VA Connecticut Healthcare Center, West Haven, Connecticut
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