Prediction and analysis of osteoarthritis hub genes with bioinformatics.

ABSTRACT:

Background

Osteoarthritis (OA) is the most common type of arthritis. OA can cause joint pain, stiffness, and loss of function. The pathogenesis of OA is not completely clear. Moreover, there is no effective treatment, and clinical management is limited to symptomatic relief or joint surgery. This study utilized bioinformatics to analyze normal and OA articular cartilage samples to find biomarkers and therapeutic targets for OA.

Methods

The GSE169077 gene chip dataset was downloaded from the public gene chip data platform of the National Biotechnology Information Center. The dataset included 6 samples of OA tissues and 5 samples of healthy cartilage tissues. Differentially expressed genes (DEGs) were screened using the R language "limma" function package under the threshold o

SUBMITTER: Zhong J 

PROVIDER: S-EPMC9929772 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature