Machine learning analysis using RNA-seq to distinguish neuromyelitis optica from multiple sclerosis and identify therapeutic candidates

This study aims to identify RNA biomarkers distinguishing neuromyelitis optica (NMO) from relapsing-remitting multiple sclerosis (RRMS) and explore potential therapeutic applications leveraging machine learning (ML). An ensemble approach was developed using differential gene expression analysis and competitive ML methodologies, interrogating total RNA sequencing datasets from peripheral whole blood of treatment-na ïve RRMS and NMO patients and healthy individuals. Pathway analysis of candidate biomarkers informed the biological context of disease, transcription factor activity, and small-molecule therapeutic potential.
Source: Journal of Molecular Diagnostics - Category: Pathology Authors: Tags: Regular Article Source Type: research