Krishnan Radhakrishnan1,2, Mihaela Aslan1,3, Kelly M Harrington4,5, Robert H Pietrzak1,6, Grant Huang7, Sumitra Muralidhar7, Kelly Cho4, Rachel Quaden4, David Gagnon4,8, Saiju Pyarajan4, Ning Sun1,3, Hongyu Zhao1,3, Michael Gaziano4,9, John Concato1,3, Murray B Stein10,11, Joel Gelernter3,12. 1. Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut, USA. 2. College of Medicine, University of Kentucky, Lexington, Kentucky, USA. 3. School of Medicine, Yale University, New Haven, Connecticut, USA. 4. Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA. 5. School of Medicine, Boston University, Boston, Massachusetts, USA. 6. U.S. Department of Veterans Affairs National Center for Posttraumatic Stress Disorder, Clinical Neurosciences Division, VA Connecticut Healthcare System, West Haven, Connecticut, USA. 7. Office of Research and Development, Veterans Health Administration, Washington, DC, USA. 8. School of Public Health, Boston University, Boston, Massachusetts, USA. 9. Harvard Medical School, Harvard University, Boston, Massachusetts, USA. 10. VA San Diego Healthcare System, San Diego, California, USA. 11. School of Medicine, University of California, San Diego, La Jolla, California, USA. 12. Psychiatry Service, VA Connecticut Healthcare System, West Haven, Connecticut, USA.
Abstract
OBJECTIVES: Heritability in the risk for developing posttraumatic stress disorder (PTSD) has been established, but most genome-wide association studies (GWASs) of PTSD involve relatively small sample sizes and limited identification of associated genetic loci. This report describes the methodology of a Veterans Affairs (VA) Cooperative Studies Program GWAS of PTSD among combat-exposed U.S. veterans. METHODS: Probable cases (with PTSD) and probable controls (without PTSD) were identified from among veterans enrolled in the VA Million Veteran Program (MVP) with an algorithm developed using questionnaire responses and electronic health record information. This algorithm, based on a statistical model, relied on medical chart reviews as a reference standard and was refined using telephone interviews. Subsequently, to evaluate the impact of probabilistic phenotyping on statistical power, the threshold probability for case-control selection was varied in simulations. RESULTS: As of September 2018, >695,000 veterans have enrolled in MVP. For current analyses, genotyping data were available for >353,000 participants, including >83,000 combat-exposed veterans. A threshold probability of 0.7 for case and control designation yielded an interim >16,000 cases and >33,000 controls. CONCLUSIONS: A formal methodological approach was used to identify cases and controls for subsequent GWAS analyses to identify genetic risk loci for PTSD.
OBJECTIVES: Heritability in the risk for developing posttraumatic stress disorder (PTSD) has been established, but most genome-wide association studies (GWASs) of PTSD involve relatively small sample sizes and limited identification of associated genetic loci. This report describes the methodology of a Veterans Affairs (VA) Cooperative Studies Program GWAS of PTSD among combat-exposed U.S. veterans. METHODS: Probable cases (with PTSD) and probable controls (without PTSD) were identified from among veterans enrolled in the VA Million Veteran Program (MVP) with an algorithm developed using questionnaire responses and electronic health record information. This algorithm, based on a statistical model, relied on medical chart reviews as a reference standard and was refined using telephone interviews. Subsequently, to evaluate the impact of probabilistic phenotyping on statistical power, the threshold probability for case-control selection was varied in simulations. RESULTS: As of September 2018, >695,000 veterans have enrolled in MVP. For current analyses, genotyping data were available for >353,000 participants, including >83,000 combat-exposed veterans. A threshold probability of 0.7 for case and control designation yielded an interim >16,000 cases and >33,000 controls. CONCLUSIONS: A formal methodological approach was used to identify cases and controls for subsequent GWAS analyses to identify genetic risk loci for PTSD.
Authors: Margaret A Gates; Darren W Holowka; Jennifer J Vasterling; Terence M Keane; Brian P Marx; Raymond C Rosen Journal: Psychol Serv Date: 2012-03-05
Authors: Lynn M Almli; Jennifer S Stevens; Alicia K Smith; Varun Kilaru; Qian Meng; Janine Flory; Duna Abu-Amara; Rasha Hammamieh; Ruoting Yang; Kristina B Mercer; Elizabeth B Binder; Bekh Bradley; Steven Hamilton; Marti Jett; Rachel Yehuda; Charles R Marmar; Kerry J Ressler Journal: Am J Med Genet B Neuropsychiatr Genet Date: 2015-05-18 Impact factor: 3.568
Authors: Jessica J Fulton; Patrick S Calhoun; H Ryan Wagner; Amie R Schry; Lauren P Hair; Nicole Feeling; Eric Elbogen; Jean C Beckham Journal: J Anxiety Disord Date: 2015-02-19
Authors: Darren W Holowka; Brian P Marx; Margaret A Gates; Heather J Litman; Gayatri Ranganathan; Raymond C Rosen; Terence M Keane Journal: J Consult Clin Psychol Date: 2014-04-14
Authors: Krishnan Radhakrishnan; Mihaela Aslan; Kelly M Harrington; Robert H Pietrzak; Grant Huang; Sumitra Muralidhar; Kelly Cho; Rachel Quaden; David Gagnon; Saiju Pyarajan; Ning Sun; Hongyu Zhao; Michael Gaziano; John Concato; Murray B Stein; Joel Gelernter Journal: Int J Methods Psychiatr Res Date: 2019-02-14 Impact factor: 4.035
Authors: Murray B Stein; Joel Gelernter; Daniel F Levey; Zhongshan Cheng; Frank R Wendt; Kelly Harrington; Gita A Pathak; Kelly Cho; Rachel Quaden; Krishnan Radhakrishnan; Matthew J Girgenti; Yuk-Lam Anne Ho; Daniel Posner; Mihaela Aslan; Ronald S Duman; Hongyu Zhao; Renato Polimanti; John Concato Journal: Nat Genet Date: 2021-01-28 Impact factor: 38.330