Background/Purpose: Knee Osteoarthritis (OA) is a painful, disabling condition and molecular mechanisms underlying this disease are poorly understood. In recent years, OA is increasingly viewed as a disease with differing phenotypes which may contribute to its pathogenesis. Characterizing these phenotypes could play an integral role in the development of appropriate therapies. The synovium is a key driver of pathological changes in OA and to date there are few studies examining total RNA sequencing in synovial tissue.  This study uses total RNA sequencing to profile the synovium of patients with advanced radiographic knee OA, and elucidates whether these patients have differing endogenous molecular phenotypes.

Methods: Total RNA sequencing was performed on synovium samples from 50 end-stage knee OA patients (KL 3/4).  After filtering, 19,857 genes were expressed in synovium. Genes with a mean, and variance greater than 30 across samples were kept for further downstream analysis (4267). To objectively identify number of distinct clusters within the patient cohort, mean silhouette width was plotted, and peaked at 3; indicating this was the optimal cluster number. Genes differentially expressed between clusters were used for pathway analysis. Identified pathways with a q-value less than 0.01 and a gene-ratio higher than 0.05 were retained and annotated to pathways. Interactions among genes were collected using Integrated Integrations Database (University of Toronto), and networks were constructed. Pearson correlation was calculated in each cluster for long-noncoding (lnc) and circular (circ) RNA from differentially expressed genes between clusters. Only correlations with absolute rho greater than 0.95 (lncRNA) or 0.85 (circRNA) were retained and used to construct Protein-Protein Interaction networks.

Results: Unbiased gene clustering indicated 3 clusters of patients distinguished by endogenous molecular differences. These groups do not demonstrate significant differences in measured clinical or anthropometric characteristics including sex, BMI, blood pressure, cholesterol, synovial inflammation, and patient reported pain. The clusters share signaling pathways such as  EGFR1, innate and adaptive immune system. Differentially regulated pathways include: signaling by receptor tyrosine kinase, cytokine signaling, and TCR (cluster 2 vs 1) as well as neutrophil degranulation, skeletal muscle, EMT regulation, apoptosis, membrane trafficking, vesicle mediated transport, toll-like receptor signaling and hemostasis (cluster 3 vs 2). We have identified several lnc and circRNA that interact with genes in each distinct pathway and have defined their associated clusters and their positive or negative gene interactions.

Conclusion: Overall, we have observed that endogenous molecular signatures derived from synovium of end-stage OA patients cluster into 3 groups. Pronounced differences in gene expression between clusters indicate both shared and distinct actively transcribed pathways. Identified lnc and circRNA contribute to unique molecular mechanisms differentially expressed between clusters. These differences in endogenous molecular mechanisms may play a role in heterogenous disease development.

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ACR Meeting Abstracts - https://acrabstracts.org/abstract/molecular-phenotyping-of-late-stage-knee-osteoarthritis-synovium-through-total-rna-sequencing/