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Updated: Oct 11, 2026

Tissue Collection and RNA Extraction from the Human Osteoarthritic Knee Joint
Published on: July 22, 2021
Genome-wide association studies of osteoarthritis: from genetic discovery to precision medicine
Yuezhou Wu1, Yang Hong2, Xukun Lyu3
1Department of Orthopedics, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200092, China; Suzhou Laboratory of Precision Health and Data Science, the Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215000, China; Biomedical Basic Research Center (BBRC) of Jiangsu Province, and Institute of Health Data Science, Soochow University, Suzhou, Jiangsu 215000, China.
Abstract:
Osteoarthritis (OA) affects more than 500 million people worldwide, yet disease-modifying therapies remain unavailable. Genome-wide association studies (GWAS) have transformed understanding of OA genetic susceptibility, progressing from early single-cohort analyses to multi-ancestry meta-analyses involving 2 million individuals and prioritizing hundreds of loci and 700 effector genes. This review summarizes the development of OA GWAS and examines how genetic discoveries are being translated into biological mechanisms and precision medicine. We discuss how integrating GWAS with fine-mapping, molecular quantitative trait loci (QTLs), chromatin interaction maps, single-cell and spatial omics, proteomics and metabolomics links non-coding signals to effector genes, regulatory programs and disease-relevant cell states. These genes converge on biological modules involving developmental patterning, extracellular matrix homeostasis, metabolism, immune-inflammatory signaling, circadian regulation and neuro-glial pathways, linking inherited susceptibility to joint structure, tissue homeostasis and symptoms. We further review translational applications, including Mendelian randomization, GWAS-informed drug target prioritization, polygenic risk scores for risk stratification and precision prevention, and AI-enabled multimodal models for phenotype refinement, subgrouping and trial enrichment. Finally, we highlight key challenges, including phenotype heterogeneity, ancestry imbalance, incomplete variant-to-function mapping and limited clinical validation. Addressing these challenges is essential for translating OA GWAS into globally relevant, mechanism-based and precision-oriented prevention and treatment.
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