Osteoarthritis phenotypes: advancing precision medicine through clinical, structural, and molecular stratification.

PURPOSE: Osteoarthritis (OA) is now understood as a heterogeneous syndrome driven by diverse biological, biomechanical, metabolic, genetic, and molecular mechanisms. This variability explains differences in disease progression and treatment response, challenging the traditional "one-size-fits-all" approach. This review highlights OA phenotyping as a key step toward precision medicine, focusing on clinical, structural, and molecular classifications that inform individualized care.

METHODS

A narrative review was conducted using a non-systematic search of major databases and Osteoarthritis Research Society International sources (2010-2026). Evidence was thematically synthesized across clinical, imaging, and molecular domains to characterize OA phenotypes and their potential relevance to precision medicine.

RESULTS

Multiple OA phenotypes were identified: inflammatory, metabolic, biomechanical, cartilage-subchondral, pain-sensitization, and aging/senescence. These exhibit distinct clinical features, risk factors, and therapeutic responses. Imaging-based phenotypes (e.g., inflammatory, meniscus-cartilage, subchondral bone, atrophic, hypertrophic) and molecular endotypes (low turnover, structural damage, systemic inflammation) further refine stratification. Pain-structure discordance is notable in sensitization phenotypes and may predict poorer surgical outcomes. Joint-specific variations and emerging genomic and epigenetic insights underscore disease complexity. Advances in imaging, biomarkers, and machine learning may enable earlier detection and patient clustering, though clinical application remains limited.

CONCLUSION

Phenotype- and endotype-based classification represents a critical advancement toward precision OA management. Tailored interventions based on stratification hold promise for improving outcomes; however, clinical translation remains limited by overlapping phenotypes, lack of validated biomarkers, and inconsistent results from phenotype-driven trials. Wider clinical adoption requires standardized definitions, validation across joints, and integration of multimodal diagnostic tools into routine practice.