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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.

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.

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.

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.