Abstract
Purpose :
Gulf War Illness (GWI) is a chronic, multisystem disease diagnosed in Gulf War Era (GWE) veterans associated with manifestations of ocular disease including dry eye symptoms, photophobia and convergence insufficiency. Given the ability to image peripheral and central nerves within the eye and detect ocular surface inflammation, the eye may serve as a biomarker for GWI, assisting with diagnosis and the understanding of disease pathophysiology. In this study, we examine whether individuals presenting with GWI symptoms have differences in ocular imaging and inflammatory cytokine profiles compared to their GWE counterparts.
Methods :
This is a prospective case-control study of 94 individuals who served during the GWE. Individuals were split into 2 groups: those with GWI symptoms (cases, identified by Kansas criteria) and those without GWI symptoms (controls). Information on demographics, co-morbidities, and diagnoses of eye diseases were captured. In addition, all individuals underwent optical coherence tomography (OCT) imaging (retinal nerve fiber layer (NFL), ganglion cell layer-inner plexiform layer, and macular maps) and provided a blood sample. Blood was analyzed for inflammatory cytokines using a custom ELISA-based chemiluminescent assay. Statistical analyses were performed using SPSS 28.0. Predictors of GWI symptoms were analyzed using forward stepwise binary logistic regression and receiver operating characteristic (ROC) curves.
Results :
The mean patient age was 55±5, 90.3% self-identified as male, 55.9% as white, and 53.8% as Hispanic. After confirming non-collinearity between predictors, the binary logistic analysis model revealed that inferior temporal ganglion cell thickness (odds ratio; OR=0.66, 95% confidence interval; CI=0.49-0.88), superior temporal ganglion cell thickness (OR=1.34, 95% CI=1.03-1.75), temporal NFL thickness (OR=1.08, 95% CI=1.01-1.16), IL1 beta levels (OR=0.86, 95% CI=0.73-1.01), IL2 levels (OR=0.71, 95% CI=0.55-0.91), and IL17 levels (OR=1.03, 95% CI=1.01-1.04) all predicted GWI symptoms. ROC analysis demonstrated an area under the curve of 0.83 (95% CI=0.74-0.93, p<0.001) for this model. As determined by Youden’s index (top left point on the ROC curve), the best cut-of value for the prediction model was associated with a sensitivity of 90% and a specificity of 65%.
Conclusions :
These results elucidate differences in OCT and systemic inflammatory markers in individuals with versus without GWI symptoms.
This abstract was presented at the 2022 ARVO Annual Meeting, held in Denver, CO, May 1-4, 2022, and virtually.