Autoantibodies as diagnostic biomarkers for the detection, subtyping, and progression of Multiple Sclerosis

Human serum samples from Multiple Sclerosis (MS) subjects and healthy control subjects were probed onto human protein microarrays in order to identify differentially expressed autoantibody biomarkers that could be used as diagnostic indicators. Other neurodegenerative and non-neurodegenerative diseases were also used to help measure the specificity of the selected biomarkers. In the study presented here, 51 mixed-MS serum samples and 31 control human serum samples were probed onto human protein microarrays in order to identify differentially expressed autoantibodies. Microarray data was analyzed using several statistical significance algorithms, and autoantibodies that demonstrated significant differences in group prevelance were selected as potential biomarkers of disease. Prediction classification analysis using Invitrogen's Prospector v5.2.1 and Random Forest tested the diagnostic efficacy of the identified biomarkers. Differentiation of MS samples from other neurodegenerative and non-neurodegenerative controls (early-stage Parkinson's disease and breast cancer) assessed the specificity of the selected biomarkers. Ccomparison of relapsing-remitting MS serum samples with secondary progressive MS serum samples assessed their utility for use in subtype staging and disease progression.