Modeling the longitudinal changes of ancestry diversity in the Million Veteran Program.

BACKGROUND: The Million Veteran Program (MVP) participants represent 100 years of US history, including significant social and demographic changes over time. Our study assessed two aspects of the MVP: (i) longitudinal changes in population diversity and (ii) how these changes can be accounted for in genome-wide association studies (GWAS). To investigate these aspects, we divided MVP participants into five birth cohorts (N-range = 123,888 [born from 1943 to 1947] to 136,699 [born from 1948 to 1953]). RESULTS: Ancestry groups were defined by (i) HARE (harmonized ancestry and race/ethnicity) and (ii) a random-forest clustering approach using the 1000 Genomes Project and the Human Genome Diversity Project (1kGP + HGDP) reference panels (77 world populations representing six continental groups). In these groups, we performed GWASs of height, a trait potentially affected by population stratification. Birth cohorts demonstrate important trends in ancestry diversity over time. More recent HARE-assigned Europeans, Africans, and Hispanics had lower European ancestry proportions than older birth cohorts (0.010 < Cohen's d < 0.259, p < 7.80 × 10-4). Conversely, HARE-assigned East Asians showed an increase in European ancestry proportion over time. In GWAS of height using HARE assignments, genomic inflation due to population stratification was prevalent across all birth cohorts (linkage disequilibrium score regression intercept = 1.08 ± 0.042). The 1kGP + HGDP-based ancestry assignment significantly reduced the population stratification (mean intercept reduction = 0.045 ± 0.007, p < 0.05) confounding in the GWAS statistics. CONCLUSIONS: This study provides a characterization of ancestry diversity of the MVP cohort over time and compares two strategies to infer genetically defined ancestry groups by assessing differences in controlling population stratification in genome-wide association studies.

Health-Related Quality of Life by Gulf War Illness Case Status.

This study examines how health-related quality of life (HRQOL) and related indices vary by Gulf War illness (GWI) case status. The study population included veterans from the Gulf War Era Cohort and Biorepository (n = 1116). Outcomes were physical and mental health from the Veterans RAND 12 and depression, post-traumatic stress (PTSD), sleep disturbance, and pain. Kansas (KS) and Centers for Disease Control and Prevention (CDC) GWI definitions were used. Kansas GWI derived subtypes included GWI (met symptom criteria; no exclusionary conditions (KS GWI: Sym+/Dx−)) and those without GWI: KS noncase (1): Sym+/Dx+, KS noncase (2): Sym−/Dx+, and noncase (3): Sym−/Dx−. CDC-derived subtypes included CDC GWI severe, CDC GWI mild-to-moderate and CDC noncases. Case status and outcomes were examined using multivariable regression adjusted for sociodemographic and military-related characteristics. Logistic regression analysis was used to examine associations between GWI case status and binary measures for depression, PTSD, and severe pain. The KS GWI: Sym+/Dx− and KS noncase (1): Sym+/Dx+ groups had worse mental and physical HRQOL outcomes than veterans in the KS noncase (2): Sym−/Dx+ and KS noncase (3): Sym−/Dx− groups (ps < 0.001). Individuals who met the CDC GWI severe criteria had worse mental and physical HRQOL outcomes than those meeting the CDC GWI mild-to-moderate or CDC noncases (ps < 0.001). For other outcomes, results followed a similar pattern. Relative to the less symptomatic comparison subtypes, veterans who met the Kansas symptom criteria, regardless of exclusionary conditions, and those who met the CDC GWI severe criteria experienced lower HRQOL and higher rates of depression, PTSD, and severe pain.

Association of Gulf War Illness-Related Symptoms with Military Exposures among 1990-1991 Gulf War Veterans Evaluated at the War-Related Illness and Injury Study Center (WRIISC).

Veterans with difficult-to-diagnose conditions who receive care in the Department of Veterans Affairs (VA) healthcare system can be referred for evaluation at one of three specialty VA War-Related Illness and Injury Study Centers (WRIISC). Veterans of the 1990−1991 Gulf War have long experienced excess rates of chronic symptoms associated with the condition known as Gulf War Illness (GWI), with hundreds evaluated at the WRIISC. Here we provide the first report from a cohort of 608 Gulf War Veterans seen at the WRIISC who completed questionnaires on chronic symptoms (>6 months) consistent with GWI as well as prominent exposures during Gulf War deployment. These included veterans' reports of hearing chemical alarms/donning Military-Ordered Protective Posture Level 4 (MOPP4) gear, pesticide use, and use of pyridostigmine bromide (PB) pills as prophylaxis against the effects of nerve agents. Overall, veterans in the cohort were highly symptomatic and reported a high degree of exposures. In multivariable models, these exposures were significantly associated with moderate-to-severe chronic symptoms in neurocognitive/mood, fatigue/sleep, and pain domains. Specifically, exposure to pesticides was associated with problems with concentration and memory, problems sleeping, unrefreshing sleep, and joint pain. Use of MOPP4 was associated with light sensitivity and unrefreshing sleep and use of PB was associated with depression. We also evaluated the association of exposures with symptom summary scores based on veterans' severity of symptoms in four domains and overall. In multivariable modeling, the pain symptom severity score was significantly associated with pesticide use (Odds ratio (OR): 4.13, 95% confidence intervals (CI): 1.78−9.57) and taking PB pills (OR: 2.28, 95% CI: 1.02−5.09), and overall symptom severity was significantly associated with use of PB pills (OR: 2.41, 95% CI: 1.01−5.75). Conclusion: Decades after deployment, Gulf War veterans referred to a VA tertiary evaluation center report a high burden of chronic symptoms, many of which were associated with reported neurotoxicant exposures during the war.

Association of Gulf War Illness with Characteristics in Deployed vs. Non-Deployed Gulf War Era Veterans in the Cooperative Studies Program 2006/Million Veteran Program 029 Cohort: A Cross-Sectional Analysis.

Gulf War Illness (GWI), a chronic multisymptom illness with a complex and uncertain etiology and pathophysiology, is highly prevalent among veterans deployed to the 1990-1991 GW. We examined how GWI phenotypes varied by demographic and military characteristics among GW-era veterans. Data were from the VA's Cooperative Studies Program 2006/Million Veteran Program (MVP) 029 cohort, Genomics of GWI. From June 2018 to March 2019, 109,976 MVP enrollees (out of a total of over 676,000) were contacted to participate in the 1990-1991 GW-era Survey. Of 109,976 eligible participants, 45,169 (41.1%) responded to the 2018-2019 survey, 35,902 respondents met study inclusion criteria, 13,107 deployed to the GW theater. GWI phenotypes were derived from Kansas (KS) and Centers for Disease Control and Prevention (CDC) GWI definitions: (a) KS Symptoms (KS Sym+), (b) KS GWI (met symptom criteria and without exclusionary health conditions) [KS GWI: Sym+/Dx-], (c) CDC GWI and (d) CDC GWI Severe. The prevalence of each phenotype was 67.1% KS Sym+, 21.5% KS Sym+/Dx-, 81.1% CDC GWI, and 18.6% CDC GWI severe. These findings affirm the persistent presence of GWI among GW veterans providing a foundation for further exploration of biological and environmental underpinnings of this condition.

Gene-Toxicant Interactions in Gulf War Illness: Differential Effects of the PON1 Genotype.

About 25-35% of United States veterans who fought in the 1990-1991 Gulf War report several moderate or severe chronic systemic symptoms, defined as Gulf War illness (GWI). Thirty years later, there is little consensus on the causes or biological underpinnings of GWI. The Gulf War Era Cohort and Biorepository (GWECB) was designed to investigate genetic and environmental associations with GWI and consists of 1343 veterans. We investigate candidate gene-toxicant interactions that may be associated with GWI based on prior associations found in human and animal model studies, focusing on SNPs in or near ACHE, BCHE, and PON1 genes to replicate results from prior studies. SOD1 was also considered as a candidate gene. CDC Severe GWI, the primary outcome, was observed in 26% of the 810 deployed veterans included in this study. The interaction between the candidate SNP rs662 and pyridostigmine bromide (PB) pills was found to be associated with CDC Severe GWI. Interactions between PB pill exposure and rs3917545, rs3917550, and rs2299255, all in high linkage disequilibrium in PON1, were also associated with respiratory symptoms. These SNPs could point toward biological pathways through which GWI may develop, which could lead to biomarkers to detect GWI or to better treatment options for veterans with GWI.

Research tool for classifying Gulf War illness using survey responses: Lessons for writing replicable algorithms for symptom-based conditions.

AIMS: Gulf War illness (GWI), a chronic symptom-based disorder, affects up to 30% of Veterans who served in the 1990-1991 Gulf War1. Because no diagnostic test or code for GWI exists, researchers typically determine case status using self-reported symptoms and conditions according to Kansas2 and CDC3 criteria. No validated algorithm has been published and case definitions have varied slightly by study. This paper aims to standardize the application of the original CDC and Kansas case definitions by defining a framework for writing reliable code for complex case definitions, implementing this framework on a sample of 1343 Gulf War Veterans (GWVs), and validating the framework by applying the code to a sample of 41,077 GWVs. MAIN METHODS: Methods were drawn from software engineering: write pseudocode, write test cases, and write code; then test code. Code was examined for accuracy, flexibility, replicability, and reusability. KEY FINDINGS: The pseudocode promoted understanding of the planned algorithm, encouraging discussion and leading to agreement on the case definition algorithms among all team members. The completed SAS code was written for and tested in the Gulf War Era Cohort and Biorepository (GWECB)4. This code was adapted and tested in the Million Veteran Program (MVP)5. The code was documented for reproducibility and reusability. SIGNIFICANCE: Ease of reuse suggests that this method could be used to standardize the application of other case definitions, reducing time and resources spent by each study team. Documentation, code, and test cases are available through the Department of Veterans Affairs (VA) Phenomics catalog6.

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.

Gulf War illness in the Gulf War Era Cohort and Biorepository: The Kansas and Centers for Disease Control definitions.

AIMS: This study characterizes Gulf War Illness (GWI) among U.S. veterans who participated in the Gulf War Era Cohort and Biorepository (GWECB). MAIN METHODS: Mailed questionnaires were collected between 2014 and 2016. Self-reported GWI symptoms, symptom domain criteria, exclusionary diagnoses, and case status were examined based on the originally published Kansas and Centers for Disease Control (CDC) definitions in the GWECB cohort (n = 849 deployed to Gulf and n = 267 non-deployed). Associations among GWI and deployment status, demographic, and military service characteristics were examined using logistic regression. KEY FINDINGS: Among deployed veterans in our sample, 39.9% met the Kansas criteria and 84.2% met the CDC criteria for GWI. Relative to non-deployed veterans, deployed veterans had a higher odds of meeting four GWI case status-related measures including the Kansas symptom criteria (aOR = 2.05, 95% CI = 1.50, 2.80), Kansas GWI case status (aOR = 1.42, 95% CI = 1.05, 1.93), the CDC GWI case status (aOR = 1.57, 95% CI = 1.07, 2.29) and the CDC severe criteria (aOR = 2.67, 95% CI = 1.79, 3.99). Forty percent met the Kansas exclusionary criteria, with no difference by deployment status. Some symptoms were nearly universally endorsed. SIGNIFICANCE: This analysis provides evidence of a sustained, multisymptom illness in veterans who deployed to the Persian Gulf War compared to non-deployed Gulf War era veterans nearly 25 years later. Differences in symptoms attributed to GWI by deployment status have diminished since initial reports, suggesting the need to update GWI definitions to account for aging-related conditions and symptoms. This study provides a foundation for future efforts to establish a single GWI case definition and analyses that employ the biorepository.

Correction to: blood handling and leukocyte isolation methods impact the global transcriptome of immune cells.

It has been highlighted that the original article [1] contained a typesetting mistake in the middle name of Arthur F. Steinschneider.

Blood handling and leukocyte isolation methods impact the global transcriptome of immune cells.

BACKGROUND: Transcriptional profiling with ultra-low input methods can yield valuable insights into disease, particularly when applied to the study of immune cells using RNA-sequencing. The advent of these methods has allowed for their use in profiling cells collected in clinical trials and other studies that involve the coordination of human-derived material. To date, few studies have sought to quantify what effects that collection and handling of this material can have on resulting data. RESULTS: We characterized the global effects of blood handling, methods for leukocyte isolation, and preservation media on low numbers of immune cells isolated from blood. We found overall that storage/shipping temperature of blood prior to leukocyte isolation and sorting led to global changes in both CD8+ T cells and monocytes, including alterations in immune-related gene sets. We found that the use of a leukocyte filtration system minimized these alterations and we applied this method to generate high-quality transcriptional data from sorted immune cells isolated from the blood of intracerebral hemorrhage patients and matched healthy controls. CONCLUSIONS: Our data underscore the necessity of processing samples with comparably defined protocols prior to transcriptional profiling and demonstrate that a filtration method can be applied to quickly isolate immune cells of interest while minimizing transcriptional bias.