ObjectiveTo uncover the microRNA (miRNA) interactome of the osteoarthritis (OA) pathophysiological process in the cartilage.MethodsWe performed RNA sequencing in 130 samples (n=35 and n=30 pairs for messenger RNA (mRNA) and miRNA, respectively) on macroscopically preserved and lesioned OA cartilage from the same patient and performed differential expression (DE) analysis of miRNA and mRNAs. To build an OA-specific miRNA interactome, a prioritisation scheme was applied based on inverse Pearson’s correlations and inverse DE of miRNAs and mRNAs. Subsequently, these were filtered by those present in predicted (TargetScan/microT-CDS) and/or experimentally validated (miRTarBase/TarBase) public databases. Pathway enrichment analysis was applied to elucidate OA-related pathways likely mediated by miRNA regulatory mechanisms.ResultsWe found 142 miRNAs and 2387 mRNAs to be differentially expressed between lesioned and preserved OA articular cartilage. After applying prioritisation towards likely miRNA-mRNA targets, a regulatory network of 62 miRNAs targeting 238 mRNAs was created. Subsequent pathway enrichment analysis of these mRNAs (or genes) elucidated that genes within the ‘nervous system development’ are likely mediated by miRNA regulatory mechanisms (familywise error=8.4×10−5). Herein NTF3 encodes neurotrophin-3, which controls survival and differentiation of neurons and which is closely related to the nerve growth factor.ConclusionsBy an integrated approach of miRNA and mRNA sequencing data of OA cartilage, an OA miRNA interactome and related pathways were elucidated. Our functional data demonstrated interacting levels at which miRNA affects expression of genes in the cartilage and exemplified the complexity of functionally validating a network of genes that may be targeted by multiple miRNAs.

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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.

Objective To identify robustly differentially expressed long noncoding RNAs (lncRNAs) with osteoarthritis (OA) pathophysiology in cartilage and to explore potential target messenger RNA (mRNA) by establishing coexpression networks, followed by functional validation. Methods RNA sequencing was performed on macroscopically lesioned and preserved OA cartilage from patients who underwent joint replacement surgery due to OA (n = 98). Differential expression analysis was performed on lncRNAs that were annotated in GENCODE and Ensembl databases. To identify potential interactions, correlations were calculated between the identified differentially expressed lncRNAs and the previously reported differentially expressed protein‐coding genes in the same samples. Modulation of chondrocyte lncRNA expression was achieved using locked nucleic acid GapmeRs. Results By applying our in‐house pipeline, we identified 5,053 lncRNAs that were robustly expressed, of which 191 were significantly differentially expressed (according to false discovery rate) between lesioned and preserved OA cartilage. Upon integrating mRNA sequencing data, we showed that intergenic and antisense differentially expressed lncRNAs demonstrate high, positive correlations with their respective flanking sense genes. To functionally validate this observation, we selected P3H2‐AS1, which was down‐regulated in primary chondrocytes, resulting in the down‐regulation of P3H2 gene expression levels. As such, we can confirm that P3H2‐AS1 regulates its sense gene P3H2. Conclusion By applying an improved detection strategy, robustly differentially expressed lncRNAs in OA cartilage were detected. Integration of these lncRNAs with differential mRNA expression levels in the same samples provided insight into their regulatory networks. Our data indicates that intergenic and antisense lncRNAs play an important role in regulating the pathophysiology of OA.

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Introduction Likely due to ignored heterogeneity in disease pathophysiology, osteoarthritis (OA) has become the most common disabling joint disease, without effective disease-modifying treatment causing a large social and economic burden. In this study we set out to explore responses of aged human osteochondral explants upon different OA-related perturbing triggers (inflammation, hypertrophy and mechanical stress) for future tailored biomimetic human models. Methods Human osteochondral explants were treated with IL-1β (10 ng/ml) or triiodothyronine (T3; 10 nM) or received 65% strains of mechanical stress (65% MS). Changes in chondrocyte signalling were determined by expression levels of nine genes involved in catabolism, anabolism and hypertrophy. Breakdown of cartilage was measured by sulphated glycosaminoglycans (sGAGs) release, scoring histological changes (Mankin score) and mechanical properties of cartilage. Results All three perturbations (IL-1β, T3 and 65% MS) resulted in upregulation of the catabolic genes MMP13 and EPAS1 . IL-1β abolished COL2A1 and ACAN gene expression and increased cartilage degeneration, reflected by increased Mankin scores and sGAGs released. Treatment with T3 resulted in a high and significant upregulation of the hypertrophic markers COL1A1 , COL10A1 and ALPL . However, 65% MS increased sGAG release and detrimentally altered mechanical properties of cartilage. Conclusion We present consistent and specific output on three different triggers of OA. Perturbation with the pro-inflammatory IL-1β mainly induced catabolic chondrocyte signalling and cartilage breakdown, while T3 initiated expression of hypertrophic and mineralization markers. Mechanical stress at a strain of 65% induced catabolic chondrocyte signalling and changed cartilage matrix integrity. The major strength of our ex vivo models was that they considered aged, preserved, human cartilage of a heterogeneous OA patient population. As a result, the explants may reflect a reliable biomimetic model prone to OA onset allowing for development of different treatment modalities. Supplementary Information The online version contains supplementary material available at 10.1007/s40744-021-00287-y.

Objective: The aim of this study was to identify key determinants of the interactive osteoarthritis (OA) pathophysiological processes of subchondral bone and cartilage. Methods:We performed RNA sequencing on macroscopically preserved and lesioned OA subchondral bone of patients that underwent joint replacement surgery due to OA (N=24 pairs; 6 hips, 18 knees, RAAK-study). Unsupervised hierarchical clustering and differential expression analyses were performed. Results were combined with previously identified, differentially expressed genes in cartilage (partly overlapping samples) as well as with recently identified OA risk genes . Results:We identified 1569 genes significantly differentially expressed between lesioned and preserved subchondral bone, including CNTNAP2 (FC=2.4, FDR=3.36x10 -5 ) and STMN2 (FC=9.6, FDR=3.36x10 -3 ). Among the identified genes, 305 were also differentially expressed and with same direction of effects in cartilage, including IL11 and CHADL, recently acknowledged OA susceptibility genes. Upon differential expression analysis stratifying for joint site, we identified 509 genes exclusively differentially expressed in subchondral bone of the knee, such as KLF11 and WNT4. These exclusive knee genes were enriched for involvement in epigenetic processes, characterized by for instance HIST1H3J and HIST1H3H. Conclusion:To our knowledge, we are the first to report on differential gene expression patterns of paired OA subchondral bone tissue using RNA sequencing. Among the most consistently differentially expressed genes with OA pathophysiology in both bone and cartilage were IL11 and CHADL. As these genes were recently also identified as robust OA risk genes they classify as attractive druggable targets acting on two OA disease relevant tissues.

Fibronectin binding to collagen type II is crucial for articular chondrocytes to stay in a healthy steady state.