Screening and validation for core genes in osteoarthritic cartilage based on weighted gene co-expression network...

Area of Science:

• Genomics
• Molecular Biology
• Immunology

Background:

• Osteoarthritis (OA) is a leading cause of disability, with increasing prevalence due to aging and obesity.
• Current diagnostic and therapeutic strategies for OA remain limited, highlighting the need for novel approaches.
• Understanding the molecular mechanisms underlying OA is crucial for developing effective interventions.

Purpose of the Study:

• To identify novel molecular targets for osteoarthritis (OA) through comprehensive gene expression analysis.
• To uncover potential biomarkers for early diagnosis and therapeutic intervention in OA.
• To investigate the genetic pathways and molecular players involved in OA pathogenesis.

Main Methods:

• Analysis of three OA cartilage tissue datasets from the Gene Expression Omnibus (GEO) database.
• Screening of differentially expressed genes and Weighted Gene Co-expression Network Analysis (WGCNA).
• Identification of hub genes using LASSO regression and ROC curve analysis, followed by experimental validation (PCR, Western Blot).

Main Results:

• 149 differentially expressed genes were identified, enriched in cytokine-cytokine receptor interaction and IL-17 signaling pathways.
• A significant co-expression module (blue) was associated with OA morbidity, yielding 13 overlapping genes.
• Three potential core genes (ATF3, FOSL2, GADD45B) were identified as significant signature genes.

Conclusions:

• ATF3, FOSL2, and GADD45B are identified as potential hub genes in osteoarthritis.
• These genes represent promising novel biomarkers and therapeutic targets for OA research.
• Further investigation into these genes may lead to advancements in OA diagnosis and treatment.