Arthritis Research & Therapy (Sep 2023)
Identification of candidate genes and chemicals associated with osteoarthritis by transcriptome-wide association study and chemical-gene interaction analysis
Abstract
Abstract Background Osteoarthritis (OA) is a common degenerative joint disease and causes chronic pain and disability to the elderly. Several risk factors are involved, such as aging, obesity, genetic susceptibility, and environmental factors. We conducted a transcriptome-wide association study (TWAS) and chemical-related gene set enrichment analysis (CGSEA) to investigate the susceptibility genes and environmental factors. Methods TWAS analysis was conducted to identify the susceptibility genes by integrating the summary-level genome-wide association study data of knee OA (KOA) and hip OA (HOA) with the precomputed expression weights from the Genotype-Tissue Expression Project (Version 8). The FUSION software was used for both single-tissue and cross-tissue TWAS, which were combined using an aggregate Cauchy association test. The biological function and pathways of the TWAS genes were explored using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) databases, and the human cartilage mRNA expression profiles were utilized to validate the TWAS genes. CGSEA analysis was performed to scan the OA-associated chemicals by integrating the TWAS results with the chemical-related gene sets. Results There were 44 and 93 unique TWAS genes identified in 7 and 11 chromosomes for KOA and HOA, respectively, fourteen and four of which showed significantly differential expression in the mRNA profiles, such as CRHR1, LTBP1, WWP2, LMX1B, and PTHLH. OA-related pathways were found in the KEGG and GO analysis, such as TGF-beta signaling pathway, MAPK signaling pathway, hyaluronan metabolic process, and chondrocyte differentiation. Forty-five OA-associated chemicals were identified, including quercetin, bisphenol A, and cadmium chloride. Conclusions Several candidate OA-associated genes and chemicals were identified through TWAS and CGSEA analysis, which expanded our understanding of the relationship between genes, chemicals, and their impact on OA.
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