Improving Diagnostics and Treatments for GWI Females by Accounting for the Effects of PTSD

Principal Investigator/Project Director

Travis Craddock

Colleges / Centers

College of Psychology

Funder

DOD - U.S. Army Medical Research Acquisition Activity

Start Date

9-30-2016

Abstract

Complex disorders like Gulf War Illness (GWI) often defy diagnosis on the basis of a single biomarker and may only be distinguishable by considering the coexpression of multiple markers measured in response to a challenge. We demonstrate the practical application of such an approach using an example where blood was collected from 26 GWI, 13 healthy control subjects, and 9 unhealthy controls with Chronic Fatigue at three points during a graded exercise challenge. A 3-way multivariate projection model based on 12 markers of endocrine and immune function was constructed using a training set of n = 10 GWI and n = 11 healthy controls. These groups were separated almost completely on the basis of two coexpression patterns. In a separate test set these same features allowed for discrimination of new GWI subjects (n = 16) from unhealthy (n = 9) and healthy control subjects with a sensitivity of 70% and a specificity of 90%. Key words: Cytokine profile, Coexpression patterns, Exercise response, Gulf War Illness, Regression model, Diagnostic classification, Partial least squares, Batch partial least squares

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