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 co-expression 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 co-expression 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%.
Keywords: Batch PLS; Co-expression patterns; Cytokine profile; Diagnostic classification; Exercise response; Gulf War illness; Partial least squares; Regression model.