Identification of aging-related genes in diagnosing osteoarthritis via integrating bioinformatics analysis and machine learning.

ABSTRACT:

Background

Osteoarthritis (OA) is one of the main causes of pain and disability in the world, it may be caused by many factors. Aging plays a significant role in the onset and progression of OA. However, the mechanisms underlying it remain unknown. Our research aimed to uncover the role of aging-related genes in the progression of OA.

Methods

In Human OA datasets and aging-related genes were obtained from the GEO database and the HAGR website, respectively. Bioinformatics methods including Gene Ontology (GO), Kyoto Encyclopedia of Genes Genomes (KEGG) pathway enrichment, and Protein-protein interaction (PPI) network analysis were used to analyze differentially expressed aging-related genes (DEARGs) in the normal control group and the OA group. And then weighted gene coexpres

SUBMITTER: Huang J 

PROVIDER: S-EPMC10817387 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature