Cross-Tissue Transcriptome-Wide Association Study Prioritizes Candidate Genesand Compound-Associated Signatures for Osteoarthritis

INTRODUCTION: Osteoarthritis (OA) is a chronic degenerative joint disease with a high global prevalence. It is characterized by cartilage degradation, synovial inflammation, and persistent joint pain, which substantially impair quality of life. Current therapies mainly alleviate symptoms rather than prevent or reverse structural joint damage. Although numerous OA-associated loci have been identified, most reside in noncoding regions, and their downstream effector genes and regulatory mechanisms remain incompletely understood. Therefore, clarifying how these variants influence gene expression is essential for prioritizing candidate genes and improving the molecular interpretation of OA susceptibility loci. METHODS: Publicly available OA Genome-Wide Association Study (GWAS) summary statistics were integrated with Expression Quantitative Trait Locus (eQTL) data from the Genotype-Tissue Expression (GTEx) project. Cross-tissue and single-tissue transcriptome-wide association analyses were performed using UTMOST and FUSION, respectively. Candidate genes were then evaluated using COJO, MAGMA, Summary-databased Mendelian Randomization (SMR), Bayesian colocalization, and Mendelian Randomization (MR) analyses. GeneMANIA was used for network-based functional annotation, and Enrichr with the DSigDB library was used for compound-signature enrichment analysis. RESULTS: Cross-tissue TWAS identified 20 significant genes for knee OA and 12 for hip OA after FDR correction. Integration of UTMOST, FUSION, COJO, and MAGMA prioritized TACC3 and LTBP1 for knee OA and TMEM129 for hip OA. SMR, colocalization, and MR analyses provided additional but variable levels of statistical support across tissues. GeneMANIA indicated biologically relevant functional networks for LTBP1 and TACC3, whereas TMEM129 showed limited network enrichment. Enrichr/DSigDB analysis identified significant compound-signature enrichment terms overlapping the prioritized genes. DISCUSSION: These findings provide integrative statistical evidence linking OA-associated loci to gene regulation and prioritize TACC3, LTBP1, and TMEM129 as candidate genes associated with OA susceptibility. However, the strength of evidence differed across analytical frameworks, and the biological interpretation of tissue-specific signals remains to be validated in joint-relevant tissues and functional models. CONCLUSION: This study prioritized TACC3, LTBP1, and TMEM129 as candidate genes associated with OA susceptibility through integrated cross-tissue and single-tissue transcriptomic analyses. These findings improve the functional interpretation of OA GWAS loci and provide testable hypotheses for future validation in joint-relevant QTL datasets and experimental models.