Machine learning identifies ferroptosis-related genes as potential diagnostic biomarkers for osteoarthritis.

ABSTRACT:

Background

Osteoarthritis (OA) is one of the most common forms of degenerative arthritis and a major cause of pain and disability. Ferroptosis, a novel mode of cell death, has been verified to participate in the development of OA, but its mechanism is still unclear. This paper analyzed the ferroptosis-related genes (FRGs) in OA and explored their potential clinical value.

Methods

We downloaded data through the GEO database and screened for DEGs. Subsequently, FRGs were obtained using two machine learning methods, LASSO regression and SVM-RFE. The accuracy of the FRGs as disease diagnosis was identified using ROC curves and externally validated. The CIBERSORT analyzed the immune microenvironment rug regulatory network constructed through the DGIdb. The competitive endogenous

SUBMITTER: Qiu Y 

PROVIDER: S-EPMC10292652 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature