Exploring Centrosome Amplification-Associated Biomarkers in Osteoarthritis Through Bioinformatics and Experimental Approaches

This work looks at using computers to find and confirm centrosome‑amplification‑related genes (CA‑RGs) that could serve as diagnostic markers for osteoarthritis (OA). Public transcriptome data are analyzed with three tools: differential gene‑expression profiling, weighted gene co‑expression network analysis (WGCNA), and Mendelian randomization (MR). These tools screen for strong genetic signals. The two top candidates, PLK2 and SUN2, are tested with receiver‑operating‑characteristic (ROC) curves to see how well they diagnose OA. A nomogram is built to predict the chance of disease, and gene‑set enrichment analysis (GSEA) reveals related lysosomal pathways and molecular mechanisms. Single‑cell RNA sequencing (scRNA‑seq) data are also examined to map immune‑cell infiltration and to show where the biomarkers

appear in different cell types inside the joint. The workflow gives clear steps for multi‑omic bioinformatics, helping researchers study how centrosome amplification contributes to joint degeneration. It can be used as a reference for computational biology projects that aim to discover biomarkers, move them toward clinical use, or find new therapeutic targets.

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