Abstract
Research Type:
Level 2 - Prospective comparative study, Meta-analysis of Level 2 studies or Level 1 studies with inconsistent results
Introduction/Purpose:
Ankle osteoarthritis (OA) is a rapidly progressing and understudied disease that affects nearly 600 million people worldwide. Most cases arise post-traumatically, often following ankle fractures. Despite its substantial impact, the mechanisms linking joint trauma to OA development remain poorly understood, limiting opportunities for early intervention. While OA research has historically focused on cartilage degeneration, growing evidence highlights the role of the synovium in driving disease progression. This study investigates the molecular pathways underlying post-traumatic ankle OA, with the goal of identifying early synovial changes that contribute to disease onset. Understanding these mechanisms is critical for developing targeted therapies to prevent or slow OA progression in high-risk individuals.
Methods:
Synovium samples were collected from patients undergoing ankle fracture repair (within 14 days of injury, n=10), ankle joint replacement for end-stage post-traumatic osteoarthritis (PTOA, post-fracture, n=9), and end-stage non-traumatic osteoarthritis (NTOA, n=16), using an active IRB-approved protocol supporting collection of these tissues. Additionally, synovium from patients with no or minimal OA signs (Outerbridge stage OB0 and OB1, n=8) undergoing routine ankle procedures served as controls. Bulk 150 bp, paired-end RNA sequencing (RNA-seq) was performed on all samples using the Illumina NovaSeq6000 platform. P-values were adjusted via the Benjamini-Hochberg method. Gene Ontology (GO) terms that describe the transcriptomic environment were derived from RNA-seq data. A machine learning model (ML) using logistic regression analyzed all gene counts to classify PTOA, NTOA, ankle fracture, and control synovium, quantifying prediction accuracy with AUC (0–1, where 1 indicates perfect classification).
Results:
RNA sequencing analysis of the post-fracture synovium revealed up-regulation of GO terms related to inflammation, extracellular matrix (ECM) organization, Wnt signaling, and cell contractility, compared to controls (Fig1A). Among the most upregulated genes were IL11 and WNT7B (Fig1B). Both genes were also highly expressed in PTOA synovium, with significantly greater fold increases compared to NTOA and controls (IL11: 193-fold; WNT7B: 106-fold; Fig1C-D). Furthermore, differential expression analysis identified 664 out of 37,806 genes distinguishing PTOA from NTOA (Fig1E). A logistic regression model using all synovial transcriptomic data sets correctly predicted synovial subtypes (NTOA, PTOA, post-fracture, and controls) based on transcriptomic signatures with high accuracy (AUC ~0.87, Fig1F).
Conclusion:
RNA sequencing and logistic regression analysis reveal distinct synovial signatures in post-fracture, PTOA, and NTOA synovium. Early post-fracture, pathways associated with Wnt signaling, IL11, ECM remodeling, and cell contractility are upregulated, mirroring changes in PTOA. IL11, a fibrosis driver, and WNT7B may contribute to disease progression, linking post-fracture synovial changes to PTOA onset. Additionally, differential expression patterns between PTOA and NTOA suggest distinct pathogenetic mechanisms underlying ankle PTOA. Our prediction model validated these molecular profiles, highlighting transcriptomic shifts in post-fracture and PTOA synovium. Further studies are needed to confirm these mechanisms and identify therapeutic targets for preventing or mitigating PTOA.
