Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe

Gender Differences in Demographic and Health Characteristics of the Million Veteran Program Cohort

The Department of Veterans Affairs Million Veteran Program (MVP) is the largest ongoing cohort program of its kind, with 654,903 enrollees as of June 2018. The objectives of this study were to examine gender differences in the MVP cohort with respect to response and enrollment rates; demographic, health, and health care characteristics; and prevalence of self-reported health conditions. The MVP Baseline Survey was completed by 415,694 veterans (8% women), providing self-report measures of demographic characteristics, health status, and medical history. Relative to men, women demonstrated a higher positive responder rate (23.0% vs. 16.0%), slightly higher enrollment rate (13.5% vs. 12.9%), and, among enrollees, a lower survey completion rate (59.7% vs. 63.8%). Women were younger, more racially diverse, had higher educational attainment, and were less likely to be married or cohabitating with a partner than men. Women were more likely to report good to excellent health status but poorer physical fitness, and less likely to report lifetime smoking and drinking than men. Compared with men, women veterans showed an increased prevalence of musculoskeletal conditions, thyroid problems, gastrointestinal conditions, migraine headaches, and mental health disorders, as well as a decreased prevalence of gout, cardiovascular diseases, high cholesterol, diabetes, and hearing problems. These results revealed some substantial gender differences in the research participation rates, demographic profile, health characteristics, and prevalence of health conditions for veterans in the MVP cohort. Findings highlight the need for tailoring recruitment efforts to ensure representation of the increasing women veteran population receiving care through the Veterans Health Administration

Genomics of Gulf War Illness in U.S. Veterans Who Served during the 1990–1991 Persian Gulf War: Methods and Rationale for Veterans Affairs Cooperative Study #2006

Background: Approximately 697,000 members of the U.S. Armed Forces were deployed to the Persian Gulf in support of the 1990–1991 Persian Gulf War (GW). Subsequently, many deployed and some non-deployed veterans developed a chronic multi-symptom illness, now named Gulf War Illness (GWI). This manuscript outlines the methods and rationale for studying the genomics of GWI within the Million Veteran Program (MVP), a VA-based national research program that has linked medical records, surveys, and genomic data, enabling genome-wide association studies (GWASs). Methods: MVP participants who served in the military during the GW era were contacted by mail and invited to participate in the GWI study. A structured health questionnaire, based on a previously tested instrument, was also included in the mailing. Data on deployment locations and exposures, symptoms associated with GWI, clinical diagnoses, personal habits, and health care utilization were collected. Self-reported data will be augmented with chart reviews and structured international classification of disease codes, to classify participants by GWI case status. We will develop a phenotyping algorithm, based on two commonly used case definitions, to determine GWI status, and then conduct a nested case-control GWAS. Genetic variants associated with GWI will be investigated, and gene–gene and gene–environment interactions studied. The genetic overlap of GWI with, and causative mechanisms linking this illness to, other health conditions and the effects of genomic regulatory mechanisms on GWI risk will also be explored. Conclusions: The proposed initial GWAS described in this report will investigate the genomic underpinnings of GWI with a large sample size and state-of-the-art genomic analyses and phenotyping. The data generated will provide a rich and expansive foundation on which to build additional analyses

Million Veteran Program's response to COVID-19: Survey development and preliminary findings.

BackgroundIn response to the novel Coronavirus Disease 2019 (COVID-19) pandemic, the Department of Veterans Affairs (VA) Million Veteran Program (MVP) organized efforts to better understand the impact of COVID-19 on Veterans by developing and deploying a self-reported survey.MethodsThe MVP COVID-19 Survey was developed to collect COVID-19 specific elements including symptoms, diagnosis, hospitalization, behavioral and psychosocial factors and to augment existing MVP data with longitudinal collection of key domains in physical and mental health. Due to the rapidly evolving nature of the pandemic, a multipronged strategy was implemented to widely disseminate the COVID-19 Survey and capture data using both the online platform and mailings.ResultsWe limited the findings of this paper to the initial phase of survey dissemination which began in May 2020. A total of 729,625 eligible MVP Veterans were invited to complete version 1 of the COVID-19 Survey. As of October 31, 2020, 58,159 surveys have been returned. The mean and standard deviation (SD) age of responders was 71 (11) years, 8.6% were female, 8.2% were Black, 5.6% were Hispanic, and 446 (0.8%) self-reported a COVID-19 diagnosis. Over 90% of responders reported wearing masks, practicing social distancing, and frequent hand washing.ConclusionThe MVP COVID-19 Survey provides a systematic collection of data regarding COVID-19 behaviors among Veterans and represents one of the first large-scale, national surveillance efforts of COVID-19 in the Veteran population. Continued work will examine the overall response to the survey with comparison to available VA health record data

Phenome-wide association of 1809 phenotypes and COVID-19 disease progression in the Veterans Health Administration Million Veteran Program.

BackgroundThe risk factors associated with the stages of Coronavirus Disease-2019 (COVID-19) disease progression are not well known. We aim to identify risk factors specific to each state of COVID-19 progression from SARS-CoV-2 infection through death.Methods and resultsWe included 648,202 participants from the Veteran Affairs Million Veteran Program (2011-). We identified characteristics and 1,809 ICD code-based phenotypes from the electronic health record. We used logistic regression to examine the association of age, sex, body mass index (BMI), race, and prevalent phenotypes to the stages of COVID-19 disease progression: infection, hospitalization, intensive care unit (ICU) admission, and 30-day mortality (separate models for each). Models were adjusted for age, sex, race, ethnicity, number of visit months and ICD codes, state infection rate and controlled for multiple testing using false discovery rate (≤0.1). As of August 10, 2020, 5,929 individuals were SARS-CoV-2 positive and among those, 1,463 (25%) were hospitalized, 579 (10%) were in ICU, and 398 (7%) died. We observed a lower risk in women vs. men for ICU and mortality (Odds Ratio (95% CI): 0.48 (0.30-0.76) and 0.59 (0.31-1.15), respectively) and a higher risk in Black vs. Other race patients for hospitalization and ICU (OR (95%CI): 1.53 (1.32-1.77) and 1.63 (1.32-2.02), respectively). We observed an increased risk of all COVID-19 disease states with older age and BMI ≥35 vs. 20-24 kg/m2. Renal failure, respiratory failure, morbid obesity, acid-base balance disorder, white blood cell diseases, hydronephrosis and bacterial infections were associated with an increased risk of ICU admissions; sepsis, chronic skin ulcers, acid-base balance disorder and acidosis were associated with mortality.ConclusionsOlder age, higher BMI, males and patients with a history of respiratory, kidney, bacterial or metabolic comorbidities experienced greater COVID-19 severity. Future studies to investigate the underlying mechanisms associated with these phenotype clusters and COVID-19 are warranted

Gender Differences in Demographic and Health Characteristics of the Million Veteran Program Cohort

Background: The Department of Veterans Affairs Million Veteran Program (MVP) is the largest ongoing cohort program of its kind, with 654,903 enrollees as of June 2018. The objectives of this study were to examine gender differences in the MVP cohort with respect to response and enrollment rates; demographic, health, and health care characteristics; and prevalence of self-reported health conditions. Methods: The MVP Baseline Survey was completed by 415,694 veterans (8% women), providing self-report measures of demographic characteristics, health status, and medical history. Results: Relative to men, women demonstrated a higher positive responder rate (23.0% vs. 16.0%), slightly higher enrollment rate (13.5% vs. 12.9%), and, among enrollees, a lower survey completion rate (59.7% vs. 63.8%). Women were younger, more racially diverse, had higher educational attainment, and were less likely to be married or cohabitating with a partner than men. Women were more likely to report good to excellent health status but poorer physical fitness, and less likely to report lifetime smoking and drinking than men. Compared with men, women veterans showed an increased prevalence of musculoskeletal conditions, thyroid problems, gastrointestinal conditions, migraine headaches, and mental health disorders, as well as a decreased prevalence of gout, cardiovascular diseases, high cholesterol, diabetes, and hearing problems. Conclusions: These results revealed some substantial gender differences in the research participation rates, demographic profile, health characteristics, and prevalence of health conditions for veterans in the MVP cohort. Findings highlight the need for tailoring recruitment efforts to ensure representation of the increasing women veteran population receiving care through the Veterans Health Administration

Harmonizing Genetic Ancestry and Self-identified Race/Ethnicity in Genome-wide Association Studies

Large-scale multi-ethnic cohorts offer unprecedented opportunities to elucidate the genetic factors influencing complex traits related to health and disease among minority populations. At the same time, the genetic diversity in these cohorts presents new challenges for analysis and interpretation. We consider the utility of race and/or ethnicity categories in genome-wide association studies (GWASs) of multi-ethnic cohorts. We demonstrate that race/ethnicity information enhances the ability to understand population-specific genetic architecture. To address the practical issue that self-identified racial/ethnic information may be incomplete, we propose a machine learning algorithm that produces a surrogate variable, termed HARE. We use height as a model trait to demonstrate the utility of HARE and ethnicity-specific GWASs

Gender Differences in Demographic and Health Characteristics of the Million Veteran Program Cohort

BackgroundThe Department of Veterans Affairs Million Veteran Program (MVP) is the largest ongoing cohort program of its kind, with 654,903 enrollees as of June 2018. The objectives of this study were to examine gender differences in the MVP cohort with respect to response and enrollment rates; demographic, health, and health care characteristics; and prevalence of self-reported health conditions.MethodsThe MVP Baseline Survey was completed by 415,694 veterans (8% women), providing self-report measures of demographic characteristics, health status, and medical history.ResultsRelative to men, women demonstrated a higher positive responder rate (23.0% vs. 16.0%), slightly higher enrollment rate (13.5% vs. 12.9%), and, among enrollees, a lower survey completion rate (59.7% vs. 63.8%). Women were younger, more racially diverse, had higher educational attainment, and were less likely to be married or cohabitating with a partner than men. Women were more likely to report good to excellent health status but poorer physical fitness, and less likely to report lifetime smoking and drinking than men. Compared with men, women veterans showed an increased prevalence of musculoskeletal conditions, thyroid problems, gastrointestinal conditions, migraine headaches, and mental health disorders, as well as a decreased prevalence of gout, cardiovascular diseases, high cholesterol, diabetes, and hearing problems.ConclusionsThese results revealed some substantial gender differences in the research participation rates, demographic profile, health characteristics, and prevalence of health conditions for veterans in the MVP cohort. Findings highlight the need for tailoring recruitment efforts to ensure representation of the increasing women veteran population receiving care through the Veterans Health Administration