Diagnosis of Gulf War Illness Using Laser-Induced Spectra Acquired from Blood Samples. Issue 8 (August 2022)

• Record Type: Journal Article
• Authors: Gaudiuso, Rosalba; Chen, Sirui; Kokkotou, Efi; Conboy, Lisa; Jacobson, Eric; Hanlon, Eugene B.; Melikechi, Noureddine
• Is Part Of: Applied spectroscopy. Volume 76:Issue 8(2022)
• Page Start: 887
• Page End: 893
• Publication Date: 2022-08
• Subjects: Laser-induced breakdown spectroscopy -- Gulf War illness -- chemometrics -- spectral analysis -- classification algorithms -- blood plasma -- chronic low back pain -- chronic multisymptom illness -- diagnostic biomarker; Spectrum analysis -- Periodicals; 543.505
• DOI: 10.1177/00037028211042049
• Languages: English
• ISSNs: 0003-7028

Abstract

Gulf War illness (GWI) is a chronic illness with no known validated biomarkers that affects the lives of hundreds of thousands of people. As a result, there is an urgent need for the development of an untargeted and unbiased method to distinguish GWI patients from non-GWI patients. We report on the application of laser-induced breakdown spectroscopy (LIBS) to distinguish blood plasma samples from a group of subjects with GWI and from subjects with chronic low back pain as controls. We initially obtained LIBS data from blood plasma samples of four GWI patients and four non-GWI patients. We used an analytical method based on taking the difference between a mean LIBS spectrum obtained with those of GWI patients from the mean LIBS spectrum of those of the control group, to generate a "difference" spectrum for our classification model. This model was cross-validated using different numbers of differential LIBS emission peaks. A subset of 17 of the 82 atomic and ionic transitions that provided 70% of correct diagnosis was selected test in a blinded fashion using 10 additional samples and was found to yield 90% classification accuracy, 100% sensitivity, and 83.3% specificity. Of the 17 atomic and ionic transitions, eight could be assigned unambiguously to species of Na, K, and Fe. Graphical Abstract