Fig. 1: Overview of the study. | Nature Communications

Fig. 1: Overview of the study.

From: Proteomics reveal biomarkers for diagnosis, disease activity and long-term disability outcomes in multiple sclerosis

Fig. 1

a Prospective longitudinal study of two Swedish cohorts of persons with MS (pwMS) in the early stages and healthy controls (HC). b Proteomics profiling of cerebrospinal fluid (CSF) and plasma samples of all pwMS and HC at baseline. c Clinical examination of pwMS during a follow-up of up to 13 years. d Differential expression analysis, performed with a two-sided linear model t-test (Limma analysis), to find MS biomarker candidates. e Building machine learning models for identification of protein MS biomarkers for diagnosis (logistic regression model), prediction of short-term disease activity (logistic regression model), and prediction of long-term disability worsening (linear regression model).

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