Meta-analysis Integrated With Multi-omics Data Analysis to Elucidate Pathogenic Mechanisms of Age-Related Knee Osteoarthritis in Mice

Abstract

Increased mechanistic insight into the pathogenesis of knee osteoarthritis (KOA) is needed to develop efficacious disease-modifying treatments. Though age-related pathogenic mechanisms are most relevant to the majority of clinically presenting KOA, the bulk of our mechanistic understanding of KOA has been derived using surgically induced posttraumatic OA (PTOA) models. Here, we took an integrated approach of meta-analysis and multi-omics data analysis to elucidate pathogenic mechanisms of age-related KOA in mice. Protein-level data were integrated with transcriptomic profiling to reveal inflammation, autophagy, and cellular senescence as primary hallmarks of age-related KOA. Importantly, the molecular profiles of cartilage aging were unique from those observed following PTOA, with less than 3% overlap between the 2 models. At the nexus of the 3 aging hallmarks, advanced glycation end product (AGE)/receptor for AGE (RAGE) emerged as the most statistically robust pathway associated with age-related KOA. This pathway was further supported by analysis of mass spectrometry data. Notably, the change in AGE-RAGE signaling over time was exclusively observed in male mice, suggesting sexual dimorphism in the pathogenesis of age-induced KOA in murine models. Collectively, these findings implicate dysregulation of AGE-RAGE signaling as a sex-dependent driver of age-related KOA.

Keywords: AGE; Aging; Articular cartilage; Bioinformatics; Meta-analysis; RAGE signaling pathway.