Characterizing mitochondrial features in osteoarthritis through integrative multi-omics and machine learning analysis.

ABSTRACT:

Purpose

Osteoarthritis (OA) stands as the most prevalent joint disorder. Mitochondrial dysfunction has been linked to the pathogenesis of OA. The main goal of this study is to uncover the pivotal role of mitochondria in the mechanisms driving OA development.

Materials and methods

We acquired seven bulk RNA-seq datasets from the Gene Expression Omnibus (GEO) database and examined the expression levels of differentially expressed genes related to mitochondria in OA. We utilized single-sample gene set enrichment analysis (ssGSEA), gene set enrichment analysis (GSEA), and weighted gene co-expression network analysis (WGCNA) analyses to explore the functional mechanisms associated with these genes. Seven machine learning algorithms were utilized to identify hub mitochondria-relat

SUBMITTER: Wu Y 

PROVIDER: S-EPMC11254675 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature