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 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%.
| Original language | English |
|---|---|
| Title of host publication | Methods in Molecular Biology |
| Publisher | Humana Press Inc. |
| Pages | 101-120 |
| Number of pages | 20 |
| DOIs | |
| State | Published - 2018 |
Publication series
| Name | Methods in Molecular Biology |
|---|---|
| Volume | 1781 |
| ISSN (Print) | 1064-3745 |
Bibliographical note
Publisher Copyright:© 2018, Springer Science+Business Media, LLC, part of Springer Nature.
ASJC Scopus Subject Areas
- Molecular Biology
- Genetics
Keywords
- Batch PLS
- Co-expression patterns
- Cytokine profile
- Diagnostic classification
- Exercise response
- Gulf War illness
- Partial least squares
- Regression model