Differential gene expression analysis reveals pathways important in early post-traumatic osteoarthritis in an equine model

Abstract

Background: Post-traumatic osteoarthritis (PTOA) is a common and significant problem in equine athletes. It is a disease of the entire joint, with the synovium thought to be a key player in disease onset and progression due to its role in inflammation. The development of effective tools for early diagnosis and treatment of PTOA remains an elusive goal. Altered gene expression represents the earliest discernable disease-related change, and can provide valuable information about disease pathogenesis and identify potential therapeutic targets. However, there is limited work examining global gene expression changes in early disease. In this study, we quantified gene expression changes in the synovium of osteoarthritis-affected joints using an equine metacarpophalangeal joint (MCPJ) chip model of early PTOA. Synovial samples were collected arthroscopically from the MCPJ of 11 adult horses before (preOA) and after (OA) surgical induction of osteoarthritis and from sham-operated joints. After sequencing synovial RNA, Salmon was used to quasi-map reads and quantify transcript abundances. Differential expression analysis with the limma-trend method used a fold-change cutoff of log2(1.1). Functional annotation was performed with PANTHER at FDR < 0.05. Pathway and network analyses were performed in Reactome and STRING, respectively.

Results: RNA was sequenced from 28 samples (6 preOA, 11 OA, 11 sham). "Sham" and "preOA" were not different and were grouped. Three hundred ninety-seven genes were upregulated and 365 downregulated in OA synovium compared to unaffected. Gene ontology (GO) terms related to extracellular matrix (ECM) organization, angiogenesis, and cell signaling were overrepresented. There were 17 enriched pathways, involved in ECM turnover, protein metabolism, and growth factor signaling. Network analysis revealed clusters of differentially expressed genes involved in ECM organization, endothelial regulation, and cellular metabolism.

Conclusions: Enriched pathways and overrepresented GO terms reflected a state of high metabolic activity and tissue turnover in OA-affected tissue, suggesting that the synovium may retain the capacity to support healing and homeostasis in early disease. Limitations of this study include small sample size and capture of one point post-injury. Differentially expressed genes within key pathways may represent potential diagnostic markers or therapeutic targets for PTOA. Mechanistic validation of these findings is an important next step.

Keywords: Animal model; Degenerative joint disease; Metacarpophalangeal joint; Osteochondral fragment; RNAseq; Synovium.

Fig. 1

Multi-dimensional scaling (MDS) plot showing clustering of samples based on normalized gene expression values (logCPM), with surrogate variables (SVA) removed. OA = osteoarthritis samples, red; Sham = sham samples, blue, preOA = samples prior to induction of osteoarthritis, green. Sham and preOA samples were combined for downstream analyses

Fig. 2

Heatmap of 762 DE genes in 17 non-affected (combined sham and preOA) and 11 OA samples. A complete list of DE genes can be found in Additional file 2

Fig. 3

Networks of enriched pathways for extracellular matrix organization and protein metabolism identified by Reactome among DE genes. A complete list genes within these pathways can be found in Additional file 5

Fig. 4

Clustering of DE genes using the MCL algorithm in STRING. Clusters with ten or more genes that were functionally annotated (Table 3) are circled and numbered. For clarity, DE genes that did not cluster with at least one other gene are not shown