Dissecting SOX9 dynamics reveals its differential regulation in osteoarthritis.

The transcription factor SOX9 is integral to tissue homeostasis and is implicated in skeletal malformation, campomelic dysplasia, and osteoarthritis (OA). Despite extensive research, the complete regulatory landscape of SOX9 transcriptional activity, interconnected with signaling pathways (TGFß, WNT, BMP, IHH, NFκB, and HIF), remains challenging to decipher. This study focuses on elucidating SOX9 signaling in OA pathology using Fluorescence Recovery After Photobleaching (FRAP) to assess SOX9 activity directly in live human primary chondrocytes (hPCs). Single cell FRAP data revealed two distinct subpopulations with differential SOX9 dynamics, showing varied distribution between healthy and OA hPCs. Moreover, inherently elevated SOX9-DNA binding was observed in healthy hPCs compared to preserved and OA counterparts. Anabolic factors (BMP7 and GREM1) and catabolic inhibitors (DKK1 and FRZb) were found to modulate SOX9 transcriptional activity in OA-hPCs. These findings provide valuable insights into the intricate regulation of SOX9 signaling in OA, suggesting potential therapeutic avenues for modulating SOX9 activity in diseased states.

Multi-trait analysis characterizes the genetics of thyroid function and identifies causal associations with clinical implications.

To date only a fraction of the genetic footprint of thyroid function has been clarified. We report a genome-wide association study meta-analysis of thyroid function in up to 271,040 individuals of European ancestry, including reference range thyrotropin (TSH), free thyroxine (FT4), free and total triiodothyronine (T3), proxies for metabolism (T3/FT4 ratio) as well as dichotomized high and low TSH levels. We revealed 259 independent significant associations for TSH (61% novel), 85 for FT4 (67% novel), and 62 novel signals for the T3 related traits. The loci explained 14.1%, 6.0%, 9.5% and 1.1% of the total variation in TSH, FT4, total T3 and free T3 concentrations, respectively. Genetic correlations indicate that TSH associated loci reflect the thyroid function determined by free T3, whereas the FT4 associations represent the thyroid hormone metabolism. Polygenic risk score and Mendelian randomization analyses showed the effects of genetically determined variation in thyroid function on various clinical outcomes, including cardiovascular risk factors and diseases, autoimmune diseases, and cancer. In conclusion, our results improve the understanding of thyroid hormone physiology and highlight the pleiotropic effects of thyroid function on various diseases.

Identified senescence endotypes in aged cartilage are reflected in the blood metabolome.

Heterogeneous accumulation of senescent cells expressing the senescence-associated secretory phenotype (SASP) affects tissue homeostasis which leads to diseases, such as osteoarthritis (OA). In this study, we set out to characterize heterogeneity of cellular senescence within aged articular cartilage and explored the presence of corresponding metabolic profiles in blood that could function as representative biomarkers. Hereto, we set out to perform cluster analyses, using a gene-set of 131 senescence genes (N = 57) in a previously established RNA sequencing dataset of aged articular cartilage and a generated metabolic dataset in overlapping blood samples. Using unsupervised hierarchical clustering and pathway analysis, we identified two robust cellular senescent endotypes. Endotype-1 was enriched for cell proliferating pathways, expressing forkhead box protein O4 (FOXO4), RB transcriptional corepressor like 2 (RBL2), and cyclin-dependent kinase inhibitor 1B (CDKN1B); the FOXO mediated cell cycle was identified as possible target for endotype-1 patients. Endotype-2 showed enriched inflammation-associated pathways, expressed by interleukin 6 (IL6), matrix metallopeptidase (MMP)1/3, and vascular endothelial growth factor (VEGF)C and SASP pathways were identified as possible targets for endotype-2 patients. Notably, plasma-based metabolic profiles in overlapping blood samples (N = 21) showed two corresponding metabolic clusters in blood. These non-invasive metabolic profiles could function as biomarkers for patient-tailored targeting of senescence in OA.

An epigenome-wide view of osteoarthritis in primary tissues.

Osteoarthritis is a complex degenerative joint disease. Here, we investigate matched genotype and methylation profiles of primary chondrocytes from macroscopically intact (low-grade) and degraded (high-grade) osteoarthritis cartilage and from synoviocytes collected from 98 osteoarthritis-affected individuals undergoing knee replacement surgery. We perform an epigenome-wide association study of knee cartilage degeneration and report robustly replicating methylation markers, which reveal an etiologic mechanism linked to the migration of epithelial cells. Using machine learning, we derive methylation models of cartilage degeneration, which we validate with 82% accuracy in independent data. We report a genome-wide methylation quantitative trait locus (mQTL) map of articular cartilage and synovium and identify 18 disease-grade-specific mQTLs in osteoarthritis cartilage. We resolve osteoarthritis GWAS loci through causal inference and colocalization analyses and decipher the epigenetic mechanisms that mediate the effect of genotype on disease risk. Together, our findings provide enhanced insights into epigenetic mechanisms underlying osteoarthritis in primary tissues.

Long non-coding RNA expression profiling of subchondral bone reveals AC005165.1 modifying FRZB expression during osteoarthritis.

OBJECTIVE: To gain insight in the expression profile of long non-coding RNAs (lncRNAs) in OA subchondral bone. METHODS: RNA sequencing data of macroscopically preserved and lesioned OA subchondral bone of patients that underwent joint replacement surgery due to OA (N = 22 pairs; 5 hips, 17 knees, Research osteoArthrits Articular Tissue (RAAK study) was run through an in-house pipeline to detect expression of lncRNAs. Differential expression analysis between preserved and lesioned bone was performed. Spearman correlations were calculated between differentially expressed lncRNAs and differentially expressed mRNAs identified previously in the same samples. Primary osteogenic cells were transfected with locked nucleic acid (LNA) GapmeRs targeting AC005165.1 lncRNA, to functionally investigate its potential mRNA targets. RESULTS: In total, 2816 lncRNAs were well-expressed in subchondral bone and we identified 233 lncRNAs exclusively expressed in knee and 307 lncRNAs exclusively in hip. Differential expression analysis, using all samples (N = 22 pairs; 5 hips, 17 knees), resulted in 21 differentially expressed lncRNAs [false discovery rate (FDR) < 0.05, fold change (FC) range 1.19-7.39], including long intergenic non-protein coding RNA (LINC) 1411 (LINC01411, FC = 7.39, FDR = 2.20 × 10-8), AC005165.1 (FC = 0.44, FDR = 2.37 × 10-6) and empty spiracles homeobox 2 opposite strand RNA (EMX2OS, FC = 0.41, FDR = 7.64 × 10-3). Among the differentially expressed lncRNAs, five were also differentially expressed in articular cartilage, including AC005165.1, showing similar direction of effect. Downregulation of AC005165.1 in primary osteogenic cells resulted in consistent downregulation of highly correlated frizzled related protein (FRZB). CONCLUSION: The current study identified a novel lncRNA, AC005165.1, being dysregulated in OA articular cartilage and subchondral bone. Downregulation of AC005165.1 caused a decreased expression of OA risk gene FRZB, an important member of the wnt pathway, suggesting that AC005165.1 could be an attractive potential therapeutic target with effects in articular cartilage and subchondral bone.

The role of TNFRSF11B in development of osteoarthritic cartilage.

OBJECTIVES: 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. METHODS: 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). RESULTS: 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. CONCLUSION: 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.

Circulating miRNAs as Potential Biomarkers for Celiac Disease Development.

Background & Aims: Celiac disease (CeD), an immune-mediated disease with enteropathy triggered by gluten, affects ~1% of the general European population. Currently, there are no biomarkers to predict CeD development. MicroRNAs (miRNAs) are short RNAs involved in post-transcriptional gene regulation, and certain disease- and stage-specific miRNA profiles have been found previously. We aimed to investigate whether circulating miRNAs can predict the development of CeD. Methods: Using next-generation miRNA-sequencing, we determined miRNAs in >200 serum samples from 53 participants of the PreventCD study, of whom 33 developed CeD during follow-up. Following study inclusion at 3 months of age, samples were drawn at predefined ages, diagnosis (first anti-transglutaminase antibody (TGA) positivity or diagnostic biopsy) and after the start of a gluten-free diet (GFD). This allowed identification of circulating miRNAs that are deregulated before TGA positivity. For validation of the biomarkers for CeD and GFD response, two additional cohorts were included in subsequent meta-analyses. Additionally, miRNAs were measured in duodenal biopsies in a case-control cohort. Results: 53 circulating miRNAs were increased (27) or decreased (26) in CeD versus controls. We assessed specific trends in these individual miRNAs in the PreventCD cohort by grouping the pre-diagnostic samples of the CeD patients (all had negative TGA) by how close to seroconversion (first sample positive TGA) the samples were taken. 8/53 miRNAs differed significantly between controls and samples taken <1 year before TGA positivity: miR-21-3p, miR-374a-5p, 144-3p, miR-500a-3p, miR-486-3p let-7d-3p, let-7e-5p and miR-3605-3p. 6/26 downregulated miRNAs reconstituted upon GFD, including miR-150-5p/-3p, whereas no upregulated miRNAs were downregulated upon GFD. 15/53 biomarker candidates also differed between CeD biopsies and controls, with a concordant direction, indicating that these circulating miRNAs might originate from the intestine. Conclusions: We identified 53 circulating miRNAs that are potential early biomarkers for CeD, of which several can be detected more than a year before TGA positivity and some start to normalize upon GFD.

Identification and characterization of two consistent osteoarthritis subtypes by transcriptome and clinical data integration.

OBJECTIVE: To identify OA subtypes based on cartilage transcriptomic data in cartilage tissue and characterize their underlying pathophysiological processes and/or clinically relevant characteristics. METHODS: 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. RESULTS: 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. CONCLUSION: 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.

RNA Sequencing Reveals Interacting Key Determinants of Osteoarthritis Acting in Subchondral Bone and Articular Cartilage: Identification of IL11 and CHADL as Attractive Treatment Targets.

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.

The miRNA-mRNA interactome of murine induced pluripotent stem cell-derived chondrocytes in response to inflammatory cytokines.

Osteoarthritis (OA) is a degenerative joint disease, and inflammation within an arthritic joint plays a critical role in disease progression. Pro-inflammatory cytokines, specifically IL-1 and TNF-α, induce aberrant expression of catabolic and degradative enzymes and inflammatory cytokines in OA and result in a challenging environment for cartilage repair and regeneration. MicroRNAs (miRNAS) are small noncoding RNAs and are important regulatory molecules that act by binding to target messenger RNAs (mRNAs) to reduce protein synthesis and have been implicated in many diseases, including OA. The goal of this study was to understand the mechanisms of miRNA regulation of the transcriptome of tissue-engineered cartilage in response to IL-1ß and TNF-α using an in vitro murine induced pluripotent stem cell (miPSC) model system. We performed miRNA and mRNA sequencing to determine the temporal and dynamic responses of genes to specific inflammatory cytokines as well as miRNAs that are differentially expressed (DE) in response to both cytokines or exclusively to IL-1ß or TNF-α. Through integration of mRNA and miRNA sequencing data, we created networks of miRNA-mRNA interactions which may be controlling the response to inflammatory cytokines. Within the networks, hub miRNAs, miR-29b-3p, miR-17-5p, and miR-20a-5p, were identified. As validation of these findings, we found that delivery of miR-17-5p and miR-20a-5p mimics significantly decreased degradative enzyme activity levels while also decreasing expression of inflammation-related genes in cytokine-treated cells. This study utilized an integrative approach to determine the miRNA interactome controlling the response to inflammatory cytokines and novel mediators of inflammation-driven degradation in tissue-engineered cartilage.