Objective: To identify key determinants of the interactive pathophysiologic processes in subchondral bone and cartilage in osteoarthritis (OA).Methods: We performed RNA sequencing on macroscopically preserved and lesional OA subchondral bone from patients in the Research Arthritis and Articular Cartilage study who underwent joint replacement surgery due to OA (n = 24 sample pairs: 6 hips and 18 knees). Unsupervised hierarchical clustering and differential expression analyses were conducted. Results were combined with data on previously identified differentially expressed genes in cartilage (partly overlapping samples) as well as data on recently identified OA risk genes.Results: We identified 1,569 genes that were significantly differentially expressed between lesional and preserved subchondral bone, including CNTNAP2 (fold change [FC] 2.4, false discovery rate [FDR] 3.36 × 10⁻⁵) and STMN2 (FC 9.6, FDR 2.36 × 10⁻³). Among these 1,569 genes, 305 were also differentially expressed, and with the same direction of effect, in cartilage, including the recently recognized OA susceptibility genes IL11 and CHADL. Upon differential expression analysis with stratification for joint site, we identified 509 genes that were exclusively differentially expressed in subchondral bone of the knee, including KLF11 and WNT4. These genes that were differentially expressed exclusively in the knee were enriched for involvement in epigenetic processes, characterized by, e.g., HIST1H3J and HIST1H3H.Conclusion: IL11 and CHADL were among the most consistently differentially expressed genes OA pathophysiology–related genes in both bone and cartilage. As these genes were recently also identified as robust OA risk genes, they classify as attractive therapeutic targets acting on 2 OA‐relevant tissues.

Background Despite recent advances in the understanding of the genetic architecture of osteoarthritis (OA), only two genetic loci have been identified for OA of the hand, in part explained by the complexity of the different hand joints and heterogeneity of OA pathology. Methods We used data from the Rotterdam Study (RSI, RSII and RSIII) to create three hand OA phenotypes based on clustering patterns of radiographic OA severity to increase power in our modest discovery genome-wide association studies in the RS (n=8700), and sought replication in an independent cohort, the Framingham Heart Study (n=1203). We used multiple approaches that leverage different levels of information and functional data to further investigate the underlying biological mechanisms and candidate genes for replicated loci. We also attempted to replicate known OA loci at other joint sites, including the hips and knees. Results We found two novel genome-wide significant loci for OA in the thumb joints. We identified WNT9A as a possible novel causal gene involved in OA pathogenesis. Furthermore, several previously identified genetic loci for OA seem to confer risk for OA across multiple joints: TGFa, RUNX2, COL27A1, ASTN2, IL11 and GDF5 loci. Conclusions We identified a robust novel genetic locus for hand OA on chromosome 1, of which WNT9A is the most likely causal gene. In addition, multiple genetic loci were identified to be associated with OA across multiple joints. Our study confirms the potential for novel insight into the genetic architecture of OA by using biologically meaningful stratified phenotypes.

Objectives In osteoarthritis, methylation of lysine 79 on histone H3 (H3K79me), a protective epigenetic mechanism, is reduced. Histone methylation levels are dynamically regulated by histone methyltransferases and demethylases. Here, we aimed to identify which histone demethylases regulate H3K79me in cartilage and investigate whether their targeting protects against osteoarthritis. Methods We determined histone demethylase expression in human non-osteoarthritis and osteoarthritis cartilage using qPCR. The role of histone demethylase families and subfamilies on H3K79me was interrogated by treatment of human C28/I2 chondrocytes with pharmacological inhibitors, followed by western blot and immunofluorescence. We performed C28/I2 micromasses to evaluate effects on glycosaminoglycans by Alcian blue staining. Changes in H3K79me after destabilisation of the medial meniscus (DMM) in mice were determined by immunohistochemistry. Daminozide, a KDM2/7 subfamily inhibitor, was intra-articularly injected in mice upon DMM. Histone demethylases targeted by daminozide were individually silenced in chondrocytes to dissect their role on H3K79me and osteoarthritis. Results We documented the expression signature of histone demethylases in human non-osteoarthritis and osteoarthritis articular cartilage. Inhibition of Jumonji-C demethylase family increased H3K79me in human chondrocytes. Blockade of KDM2/7 histone demethylases with daminozide increased H3K79me and glycosaminoglycans. In mouse articular cartilage, H3K79me decayed rapidly upon induction of joint injury. Early and sustained intra-articular treatment with daminozide enhanced H3K79me and exerted protective effects in mice upon DMM. Individual silencing of KDM7A/B demethylases in human chondrocytes demonstrated that KDM7A/B mediate protective effects of daminozide on H3K79me and osteoarthritis. Conclusion Targeting KDM7A/B histone demethylases could be an attractive strategy to protect joints against osteoarthritis.

Osteoarthritis is a prevalent joint disease and a major cause of disability worldwide with no curative therapy. Development of disease-modifying therapies requires a better understanding of the molecular mechanisms underpinning disease. A hallmark of osteoarthritis is cartilage degradation. To define molecular events characterizing osteoarthritis at the whole transcriptome level, we performed deep RNA sequencing in paired samples of low- and high-osteoarthritis grade knee cartilage derived from 124 patients undergoing total joint replacement. We detected differential expression between low- and high-osteoarthritis grade articular cartilage for 365 genes and identified a 38-gene signature in osteoarthritis cartilage by replicating our findings in an independent dataset. We also found differential expression for 25 novel long non-coding RNA genes (lncRNAs) and identified potential lncRNA interactions with RNA-binding proteins in osteoarthritis. We assessed alterations in the relative usage of individual gene transcripts and identified differential transcript usage for 82 genes, including ABI3BP, coding for an extracellular matrix protein, AKT1S1, a negative regulator of the mTOR pathway and TPRM4, coding for a transient receptor potential channel. We further assessed genome-wide differential splicing, for the first time in osteoarthritis, and detected differential splicing for 209 genes, which were enriched for extracellular matrix, proteoglycans and integrin surface interactions terms. In the largest study of its kind in osteoarthritis, we find that isoform and splicing changes, in addition to extensive differences in both coding and non-coding sequence expression, are associated with disease and demonstrate a novel layer of genomic complexity to osteoarthritis pathogenesis.

OA is a complex genetic disease with different risk factors contributing to its development. One of the genes, TNFRSF11B, previously identified with gain-of-function mutation in a family with early-onset OA with chondrocalcinosis, is among the highest upregulated genes in lesioned OA cartilage (RAAK-study). Here, we determined the role of TNFRSF11B overexpression in development of OA. Human primary articular chondrocytes (9 donors RAAK study) were transduced using lentiviral particles with or without TNFRSF11B. Cells were cultured for 1 week in a 3 D in-vitro chondrogenic model. TNFRSF11B overexpression was confirmed by RT-qPCR, immunohistochemistry and ELISA. Effects of TNFRSF11B overexpression on cartilage matrix deposition, matrix mineralization, and genes highly correlated to TNFRSF11B in RNA-sequencing dataset (r >0.75) were determined by RT-qPCR. Additionally, glycosaminoglycans and collagen deposition were visualized with Alcian blue staining and immunohistochemistry (COL1 and COL2). Overexpression of TNFRSF11B resulted in strong upregulation of MMP13, COL2A1 and COL1A1. Likewise, mineralization and osteoblast characteristic markers RUNX2, ASPN and OGN showed a consistent increase. Among 30 genes highly correlated to TNFRSF11B, expression of only eight changed significantly, with BMP6 showing the highest increase (9-fold) while expression of RANK and RANKL remained unchanged indicating previously unknown downstream pathways of TNFRSF11B in cartilage. Results of our 3D in vitro chondrogenesis model indicate that upregulation of TNFRSF11B in lesioned OA cartilage may act as a direct driving factor for chondrocyte to osteoblast transition observed in OA pathophysiology. This transition does not appear to act via the OPG/RANK/RANKL triad common in bone remodeling.

To identify OA subtypes based on cartilage transcriptomic data in cartilage tissue and characterize their underlying pathophysiological processes and/or clinically relevant characteristics. This study includes n = 66 primary OA patients (41 knees and 25 hips), who underwent a joint replacement surgery, from which macroscopically unaffected (preserved, n = 56) and lesioned (n = 45) OA articular cartilage were collected [Research Arthritis and Articular Cartilage (RAAK) study]. Unsupervised hierarchical clustering analysis on preserved cartilage transcriptome followed by clinical data integration was performed. Protein–protein interaction (PPI) followed by pathway enrichment analysis were done for genes significant differentially expressed between subgroups with interactions in the PPI network. Analysis of preserved samples (n = 56) resulted in two OA subtypes with n = 41 (cluster A) and n = 15 (cluster B) patients. The transcriptomic profile of cluster B cartilage, relative to cluster A (DE-AB genes) showed among others a pronounced upregulation of multiple genes involved in chemokine pathways. Nevertheless, upon investigating the OA pathophysiology in cluster B patients as reflected by differentially expressed genes between preserved and lesioned OA cartilage (DE-OA-B genes), the chemokine genes were significantly downregulated with OA pathophysiology. Upon integrating radiographic OA data, we showed that the OA phenotype among cluster B patients, relative to cluster A, may be characterized by higher joint space narrowing (JSN) scores and low osteophyte (OP) scores. Based on whole-transcriptome profiling, we identified two robust OA subtypes characterized by unique OA, pathophysiological processes in cartilage as well as a clinical phenotype. We advocate that further characterization, confirmation and clinical data integration is a prerequisite to allow for development of treatments towards personalized care with concurrently more effective treatment response.