Evaluation of Biomarkers and Immune Microenvironment of Osteoarthritis: Evidence From Omics Data and Machine Learning.

ABSTRACT: Objectives: This study aimed to identify novel biomarkers for osteoarthritis (OA) and explore potential pathological immune cell infiltration. Methods: We identified differentially expressed genes (DEGs) between OA and normal synovial tissues using the limma package in R, and performed enrichment analyses to understand the functions and enriched pathways of DEGs. Weighted gene co-expression network analysis (WGCNA) and distinct machine-learning algorithms were then used to identify hub modules and candidate biomarkers. We assessed the diagnostic value of the candidate biomarkers using receiver operating characteristic (ROC) analysis. We then used the CIBERSORT algorithm to analyze immune cell infiltration patterns, and the Wilcoxon test to screen out hub immune cells t

SUBMITTER: Liu Z 

PROVIDER: S-EPMC9149375 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature