Molecular models of multiple sclerosis severity identify heterogeneity of pathogenic mechanisms

• Published in: Nature communications Vol. 13; no. 1; pp. 7670 - 16
• Main Authors: Kosa, Peter, Barbour, Christopher, Varosanec, Mihael, Wichman, Alison, Sandford, Mary, Greenwood, Mark, Bielekova, Bibiana
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 12.12.2022; Nature Publishing Group; Nature Portfolio
• Subjects: 38/79; 59/57; 631/154/53; 631/553/2695; 692/617/375/1666; Abnormalities; Aging; Aging (natural); Autoimmune diseases; Autopsies; Autopsy; Biomarkers; Biomarkers - cerebrospinal fluid; Central nervous system; Cerebrospinal fluid; Clinical trials; Drug development; Drug screening; Heterogeneity; Humanities and Social Sciences; Humans; Life span; Machine learning; Models, Molecular; Molecular modelling; multidisciplinary; Multiple sclerosis; Multiple Sclerosis - cerebrospinal fluid; Nervous System Diseases; Neurological diseases; Pharmacodynamics; Phenotypes; Science; Science (multidisciplinary)

While autopsy studies identify many abnormalities in the central nervous system (CNS) of subjects dying with neurological diseases, without their quantification in living subjects across the lifespan, pathogenic processes cannot be differentiated from epiphenomena. Using machine learning (ML), we se...