Genetic risk of osteoarthritis operates during human skeletogenesis.

Osteoarthritis (OA) is a polygenic disease of older people resulting in the breakdown of cartilage within articular joints. Although it is a leading cause of disability, there are no disease-modifying therapies. Evidence is emerging to support the origins of OA in skeletogenesis. Whereas methylation quantitative trait loci (mQTLs) co-localizing with OA genome-wide association study signals have been identified in aged human cartilage and used to identify effector genes and variants, such analyses have never been conducted during human development. Here, for the first time, we have investigated the developmental origins of OA genetic risk at seven well-characterized OA risk loci, comprising 39 OA-mQTL CpGs, in human fetal limb (FL) and cartilage (FC) tissues using a range of molecular genetic techniques. We identified significant OA-mQTLs at 14 and 29 CpGs in FL and FC tissues, respectively, and compared our results with aged cartilage samples (AC). Differential methylation was observed at 26 sites between FC and AC, with the majority becoming actively hypermethylated in old age. Notably, 6/9 OA effector genes showed allelic expression imbalances during fetal development. Finally, we conducted ATAC-sequencing in cartilage from the developing and aged hip and knee to identify accessible chromatin regions and found enrichment for transcription factor binding motifs including SOX9 and FOS/JUN. For the first time, we have demonstrated the activity of OA-mQTLs and expression imbalance of OA effector genes during human skeletogenesis. We show striking differences in the spatiotemporal function of these loci, contributing to our understanding of OA aetiology, with implications for the timing and strategy of pharmacological interventions.

Climate as a risk factor for armed conflict.

Research findings on the relationship between climate and conflict are diverse and contested. Here we assess the current understanding of the relationship between climate and conflict, based on the structured judgments of experts from diverse disciplines. These experts agree that climate has affected organized armed conflict within countries. However, other drivers, such as low socioeconomic development and low capabilities of the state, are judged to be substantially more influential, and the mechanisms of climate-conflict linkages remain a key uncertainty. Intensifying climate change is estimated to increase future risks of conflict.

The full blood count in screening asymptomatic infants for early-onset sepsis: A cross-sectional study.

AIM: The full blood count (FBC) is commonly measured as part of a partial septic work-up in asymptomatic infants at increased risk of early-onset neonatal sepsis (EOS). To determine the impact of FBC parameters on infants' subsequent management a retrospective cross-sectional study was performed. METHODS: Infants, born at ≥34 weeks gestation, asymptomatic at birth, undergoing a partial septic work-up and receiving prophylactic antibiotics due to increased risk of EOS in a single centre over a 2-year period, were included. The primary outcome measure was frequency of FBC result impacting on duration of antibiotic therapy. Secondary outcome measures included frequency of FBC parameters outside of the reference range and incidental diagnoses. RESULTS: In total, 16 726 live-born infants were delivered during the study period. A total of 802 (4.8%) were included. Thirteen infants (1.6%) received a prolonged course of antibiotics due to suspicion for EOS. Two of these infants had elevated white cell counts. All had normal neutrophil counts. In no case did the FBC result influence the decision to prolong the antibiotic course. CONCLUSION: In a cohort of 802 infants, asymptomatic at birth and at increased risk of EOS, the FBC result did not impact on the decision to prolong the course of antibiotics for suspicion of EOS.

Predicted and actual 2-year structural and pain progression in the IMI-APPROACH knee osteoarthritis cohort.

OBJECTIVES: The IMI-APPROACH knee osteoarthritis study used machine learning (ML) to predict structural and/or pain progression, expressed by a structural (S) and pain (P) predicted-progression score, to select patients from existing cohorts. This study evaluates the actual 2-year progression within the IMI-APPROACH, in relation to the predicted-progression scores. METHODS: Actual structural progression was measured using minimum joint space width (minJSW). Actual pain (progression) was evaluated using the Knee injury and Osteoarthritis Outcomes Score (KOOS) pain questionnaire. Progression was presented as actual change (Δ) after 2 years, and as progression over 2 years based on a per patient fitted regression line using 0, 0.5, 1 and 2-year values. Differences in predicted-progression scores between actual progressors and non-progressors were evaluated. Receiver operating characteristic (ROC) curves were constructed and corresponding area under the curve (AUC) reported. Using Youden's index, optimal cut-offs were chosen to enable evaluation of both predicted-progression scores to identify actual progressors. RESULTS: Actual structural progressors were initially assigned higher S predicted-progression scores compared with structural non-progressors. Likewise, actual pain progressors were assigned higher P predicted-progression scores compared with pain non-progressors. The AUC-ROC for the S predicted-progression score to identify actual structural progressors was poor (0.612 and 0.599 for Δ and regression minJSW, respectively). The AUC-ROC for the P predicted-progression score to identify actual pain progressors were good (0.817 and 0.830 for Δ and regression KOOS pain, respectively). CONCLUSION: The S and P predicted-progression scores as provided by the ML models developed and used for the selection of IMI-APPROACH patients were to some degree able to distinguish between actual progressors and non-progressors. TRIAL REGISTRATION: ClinicalTrials.gov, https://clinicaltrials.gov, NCT03883568.

Genome-wide association of phenotypes based on clustering patterns of hand osteoarthritis identify WNT9A as novel osteoarthritis gene.

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.

Identification of a novel, methylation-dependent, RUNX2 regulatory region associated with osteoarthritis risk.

Osteoarthritis (OA) is a common, multifactorial and polygenic skeletal disease that, in its severest form, requires joint replacement surgery to restore mobility and to relieve chronic pain. Using tissues from the articulating joints of 260 patients with OA and a range of in vitro experiments, including CRISPR-Cas9, we have characterized an intergenic regulatory element. Here, genotype at an OA risk locus correlates with differential DNA methylation, with altered gene expression of both a transcriptional regulator (RUNX2), and a chromatin remodelling protein (SUPT3H). RUNX2 is a strong candidate for OA susceptibility, with its encoded protein being essential for skeletogenesis and healthy joint function. The OA risk locus includes single nucleotide polymorphisms (SNPs) located within and flanking the differentially methylated region (DMR). The OA association SNP, rs10948172, demonstrates particularly strong correlation with methylation, and two intergenic SNPs falling within the DMR (rs62435998 and rs62435999) demonstrate genetic and epigenetic effects on the regulatory activity of this region. We therefore posit that the OA signal mediates its effect by modulating the methylation of the regulatory element, which then impacts on gene expression, with RUNX2 being the principal target. Our study highlights the interplay between DNA methylation, OA genetic risk and the downstream regulation of genes critical to normal joint function.

Methylation quantitative trait locus analysis of osteoarthritis links epigenetics with genetic risk.

Osteoarthritis (OA) is a common, painful and debilitating disease of articulating joints resulting from the age-associated loss of cartilage. Well-powered genetic studies have identified a number of DNA polymorphisms that are associated with OA susceptibility. Like most complex trait loci, these OA loci are thought to influence disease susceptibility through the regulation of gene expression, so-called expression quantitative loci, or eQTLs. One mechanism through which eQTLs act is epigenetic, by modulating DNA methylation. In such cases, there are quantitative differences in DNA methylation between the two alleles of the causal polymorphism, with the association signal referred to as a methylation quantitative trait locus, or meQTL. In this study, we aimed to investigate whether the OA susceptibility loci identified to date are functioning as meQTLs by integrating genotype data with whole genome methylation data of cartilage DNA. We investigated potential genotype-methylation correlations within a 1.0-1.5 Mb region surrounding each of 16 OA-associated single-nucleotide polymorphisms (SNPs) in 99 cartilage samples and identified four that function as meQTLs. Three of these replicated in an additional cohort of up to 62 OA patients. These observations suggest that OA susceptibility loci regulate the level of DNA methylation in cis and provide a mechanistic explanation as to how these loci impact upon OA susceptibility, further increasing our understanding of the role of genetics and epigenetics in this common disease.

The first international workshop on the epigenetics of osteoarthritis.

Osteoarthritis (OA) is a major clinical problem across the world, in part due to the lack of disease-modifying drugs resulting, to a significant degree, from our incomplete understanding of the underlying molecular mechanisms of the disease. Emerging evidence points to a role of epigenetics in the pathogenesis of OA, but research in this area is still in its early stages. In order to summarize current knowledge and to facilitate the potential coordination of future research activities, the first international workshop on the epigenetics of OA was held in Amsterdam in October 2015. Recent findings on DNA methylation and hydroxymethylation, histone modifications, noncoding RNAs, and other epigenetic mechanisms were presented and discussed. The workshop demonstrated the advantage of bringing together those working in this nascent field and highlights from the event are summarized in this report in the form of summaries from invited speakers and organizers.

Effects of temperature and precipitation variability on the risk of violence in sub-Saharan Africa, 1980-2012.

Ongoing debates in the academic community and in the public policy arena continue without clear resolution about the significance of global climate change for the risk of increased conflict. Sub-Saharan Africa is generally agreed to be the region most vulnerable to such climate impacts. Using a large database of conflict events and detailed climatological data covering the period 1980-2012, we apply a multilevel modeling technique that allows for a more nuanced understanding of a climate-conflict link than has been seen heretofore. In the aggregate, high temperature extremes are associated with more conflict; however, different types of conflict and different subregions do not show consistent relationship with temperature deviations. Precipitation deviations, both high and low, are generally not significant. The location and timing of violence are influenced less by climate anomalies (temperature or precipitation variations from normal) than by key political, economic, and geographic factors. We find important distinctions in the relationship between temperature extremes and conflict by using multiple methods of analysis and by exploiting our time-series cross-sectional dataset for disaggregated analyses.

The identification of trans-acting factors that regulate the expression of GDF5 via the osteoarthritis susceptibility SNP rs143383.

rs143383 is a C to T transition SNP located in the 5'untranslated region (5'UTR) of the growth differentiation factor 5 gene GDF5. The T allele of the SNP is associated with increased risk of osteoarthritis (OA) in Europeans and in Asians. This susceptibility is mediated by the T allele producing less GDF5 transcript relative to the C allele, a phenomenon known as differential allelic expression (DAE). The aim of this study was to identify trans-acting factors that bind to rs143383 and which regulate this GDF5 DAE. Protein binding to the gene was investigated by two experimental approaches: 1) competition and supershift electrophoretic mobility shift assays (EMSAs) and 2) an oligonucleotide pull down assay followed by quantitative mass spectrometry. Binding was then confirmed in vivo by chromatin immunoprecipitation (ChIP), and the functional effects of candidate proteins investigated by RNA interference (RNAi) and over expression. Using these approaches the trans-acting factors Sp1, Sp3, P15, and DEAF-1 were identified as interacting with the GDF5 5'UTR. Knockdown and over expression of the factors demonstrated that Sp1, Sp3, and DEAF-1 are repressors of GDF5 expression. Depletion of DEAF-1 modulated the DAE of GDF5 and this differential allelic effect was confirmed following over expression, with the rs143383 T allele being repressed to a significantly greater extent than the rs143383 C allele. In combination, Sp1 and DEAF-1 had the greatest repressive activity. In conclusion, we have identified four trans-acting factors that are binding to GDF5, three of which are modulating GDF5 expression via the OA susceptibility locus rs143383.

Genetic contribution to osteoarthritis development: current state of evidence.

PURPOSE OF REVIEW: Powerful association studies have identified a number of genetic signals that can be confidently judged as associated with osteoarthritis. Efforts have continued to discover new loci, whilst functional studies are being applied to assess which genes are the likely targets of the risk-conferring alleles. The study of epigenetics has highlighted an interaction between osteoarthritis genetics and DNA methylation. This review will summarize some of the recent key studies in osteoarthritis genetics, including functional and epigenetic analyses. RECENT FINDINGS: Several novel osteoarthritis susceptibility loci have been reported recently, including the regulatory genes NCOA3 and ALDH1A2. Functional analyses of these genes and of others reported previously support earlier suggestions that osteoarthritis susceptibility is principally mediated by modulations to gene expression. DNA methylation analyses provide additional insights into the osteoarthritis disease process, at both a genome-wide level and when investigating direct interactions with risk-conferring alleles. SUMMARY: Osteoarthritis genetic risk predominantly acts by modulating gene expression, an effect typically mediated via transcriptional regulation. Effects on various pathways have been detected, including cell differentiation and cartilage homeostasis. The continued identification of risk loci, their functional study, and the unification of genetic and epigenetic analyses will be key themes in the future.

Differential DNA methylation and expression of inflammatory and zinc transporter genes defines subgroups of osteoarthritic hip patients.

OBJECTIVES: We have previously shown that the cartilage DNA methylome delineates two clusters of osteoarthritic (OA) hip patients, characterised by differential methylation of inflammatory genes, while others have demonstrated a link between zinc homeostasis and inflammation in OA. We aimed to investigate these effects at the methylation and gene expression level. METHODS: We used our previously generated methylation data while quantitative PCR was used to measure gene expression using RNA from the hip cartilage of members of both clusters and from control individuals without hip OA. RESULTS: One of the OA clusters is characterised by the promoter hypomethylation and increased expression of inflammation-associated genes including IL1A and TNF. Furthermore, we show that the increase in expression of these genes is accompanied by increased expression of several zinc transporter genes. In addition, the zinc responsive transcription factor MTF1 is also upregulated, which is accompanied by an increase in the expression of its targets the metalloproteinases MMP13 and ADAMTS5. CONCLUSIONS: We have identified a subgroup of OA hip patients that are epigenetically and transcriptiomically characterised by a cartilage inflammatory phenotype with concurrent differential regulation of zinc regulators. The identification of subgroups enhances stratified phenotyping of OA patients and has important implications for future therapeutic applications.

Functional characterisation of the osteoarthritis susceptibility locus at chromosome 6q14.1 marked by the polymorphism rs9350591.

BACKGROUND: The arcOGEN genome-wide association study reported the rs9350591 C/T single nucleotide polymorphism (SNP) as marking a region on chromosome 6q14.1 that is associated with hip osteoarthritis (OA) in Europeans, with an odds ratio (OR) of 1.18 and a p-value of 2.42 × 10(-9). rs9350591 is an intergenic SNP surrounded by seven genes within 1 Mb. Six of the genes are expressed in cartilage. We sought to characterise this signal to assess whether the association of rs9350591 with OA is mediated by modulating gene expression. METHODS: Total RNA was extracted from hip or knee cartilage of 161 OA patients and from hip cartilage of 29 non-OA patients who had undergone hip replacements as a result of neck-of-femur (NOF) fractures. We used quantitative PCR (qPCR) to measure overall gene expression, and pyrosequencing to assess allelic expression of the genes. A mesenchymal stem cell (MSC) differentiation model was used to assess gene expression during chondrogenesis. RESULTS: We identified a significant decrease in the expression of SENP6 (p = 0.005) and MYO6 (p = 0.026) in OA hip cartilage relative to the non-OA hip control cartilage. However, we found no evidence for a correlation between gene expression and rs9350591 genotype for any of the six genes. In addition, we identified expression quantitative trait loci (eQTLs) operating on COL12A1, TMEM30A, SENP6 and MYO6, although these were not relevant to the OA associated signal. Finally, all genes were dynamically expressed during chondrogenesis. CONCLUSIONS: The regulation of gene expression at this locus is complex, highlighted by the down-regulation of SENP6 and MYO6 in OA hip cartilage and by eQTLs operating on four of the genes at the locus. However, modulation of gene expression in the end-stage OA cartilage that we have investigated is not the mechanism by which this association signal is operating. As implied by the dynamic patterns of gene expression throughout chondrogenesis, the association signal marked by rs9350591 could instead be exerting its effects during joint development.

Expression analysis of the osteoarthritis genetic susceptibility locus mapping to an intron of the MCF2L gene and marked by the polymorphism rs11842874.

BACKGROUND: Osteoarthritis (OA) is a painful, debilitating disease characterised by loss of articular cartilage with concurrent changes in other tissues of the synovial joint. Genetic association studies have shown that a number of common variants increase the risk of developing OA. Investigating their activity can uncover novel causal pathways and potentially highlight new treatment targets. One of the reported OA association signals is marked by the single nucleotide polymorphism (SNP) rs11842874 at chromosome 13q34. rs11842874 is positioned within a small linkage disequilibrium (LD) block within intron 4 of MCF2L, a gene encoding guanine-nucleotide exchange factor DBS. There are no non-synonymous SNPs that correlate with this association signal and we therefore set out to assess whether its effect on OA susceptibility is mediated by alteration of MCF2L expression. METHODS: Nucleic acid was extracted from cartilage, synovial membrane or infrapatellar fat pad tissues from OA patients. Expression of MCF2L was measured by quantitative PCR and RNA-sequencing whilst the presence of DBS was studied using immunohistochemistry. The functional effect of SNPs within the 13q34 locus was assessed using public databases and in vitro using luciferase reporter analysis. RESULTS: MCF2L gene and protein expression are detectable in joint tissues, with quantitative differences in the expression of the gene and in the transcript isoforms expressed between the tissues tested. There is an expression quantitative trait locus (eQTL) operating within synovial membrane tissue, with possession of the risk-conferring A allele of rs11842874 correlating with increased MCF2L expression. SNPs within the rs11842874 LD block reside within transcriptional regulatory elements and their direct analysis reveals that several show quantitative differences in regulatory activity at the allelic level. CONCLUSIONS: MCF2L is subject to a cis-acting eQTL in synovial membrane that correlates with the OA association signal. This signal contains several functional SNPs that could account for the susceptibility and which therefore merit further investigation. As far as we are aware, this is the first example of an OA susceptibility locus operating as an eQTL in synovial membrane tissue but not in cartilage.

Climate variability and conflict risk in East Africa, 1990-2009.

Recent studies concerning the possible relationship between climate trends and the risks of violent conflict have yielded contradictory results, partly because of choices of conflict measures and modeling design. In this study, we examine climate-conflict relationships using a geographically disaggregated approach. We consider the effects of climate change to be both local and national in character, and we use a conflict database that contains 16,359 individual geolocated violent events for East Africa from 1990 to 2009. Unlike previous studies that relied exclusively on political and economic controls, we analyze the many geographical factors that have been shown to be important in understanding the distribution and causes of violence while also considering yearly and country fixed effects. For our main climate indicators at gridded 1° resolution (~100 km), wetter deviations from the precipitation norms decrease the risk of violence, whereas drier and normal periods show no effects. The relationship between temperature and conflict shows that much warmer than normal temperatures raise the risk of violence, whereas average and cooler temperatures have no effect. These precipitation and temperature effects are statistically significant but have modest influence in terms of predictive power in a model with political, economic, and physical geographic predictors. Large variations in the climate-conflict relationships are evident between the nine countries of the study region and across time periods.

CpG methylation regulates allelic expression of GDF5 by modulating binding of SP1 and SP3 repressor proteins to the osteoarthritis susceptibility SNP rs143383.

GDF5 encodes an extracellular signalling molecule that is essential for normal skeletal development. The rs144383 C to T SNP located in the 5'UTR of this gene is functional and has a pleiotropic effect on the musculoskeletal system, being a risk factor for knee-osteoarthritis (OA), congenital hip dysplasia, lumbar disc degeneration and Achilles tendon pathology. rs143383 exerts a joint-wide effect on GDF5 expression, with expression of the OA-associated T allele being significantly reduced relative to the C allele, termed allelic expression imbalance. We have previously reported that the GDF5 locus is subject to DNA methylation and that allelic imbalance of rs143383 is mediated by SP1, SP3 and DEAF1 transcriptional repressors. In this study, we have assayed GDF5 methylation in normal and osteoarthritic cartilage, and investigated the effect of methylation on the allelic imbalance of rs143383. We observed demethylation of the GDF5 5'UTR in OA knee cartilage relative to both OA (p = 0.009) and non-OA (p = 0.001) hip cartilage, with the most significant demethylation observed at the highly conserved +37 CpG site located 4 bp upstream of rs143383. Methylation modulates the level and direction of allelic imbalance of rs143383, with methylation of the +37 CpG dinucleotide within the SP1/SP3 binding site having an allele-specific effect on SP1 and SP3 binding. Furthermore, methylation attenuated the repressive effects of SP1, SP3 and DEAF1 on GDF5 promoter activity. This data suggest that the differential methylation of the +37 CpG site between osteoarthritic hip and knee cartilage may be responsible for the knee-specific effect of rs143383 on OA susceptibility.

A variant in MCF2L is associated with osteoarthritis.

Osteoarthritis (OA) is a prevalent, heritable degenerative joint disease with a substantial public health impact. We used a 1000-Genomes-Project-based imputation in a genome-wide association scan for osteoarthritis (3177 OA cases and 4894 controls) to detect a previously unidentified risk locus. We discovered a small disease-associated set of variants on chromosome 13. Through large-scale replication, we establish a robust association with SNPs in MCF2L (rs11842874, combined odds ratio [95% confidence interval] 1.17 [1.11-1.23], p = 2.1 × 10(-8)) across a total of 19,041 OA cases and 24,504 controls of European descent. This risk locus represents the third established signal for OA overall. MCF2L regulates a nerve growth factor (NGF), and treatment with a humanized monoclonal antibody against NGF is associated with reduction in pain and improvement in function for knee OA patients.

Allelic expression analysis of the osteoarthritis susceptibility locus that maps to chromosome 3p21 reveals cis-acting eQTLs at GNL3 and SPCS1.

BACKGROUND: An osteoarthritis (OA) susceptibility locus has been mapped to chromosome 3p21, to a region of high linkage disequilibrium encompassing twelve genes. Six of these genes are expressed in joint tissues and we therefore assessed whether any of the six were subject to cis-acting regulatory polymorphisms active in these tissues and which could therefore account for the association signal. METHODS: We measured allelic expression using pyrosequencing assays that can distinguish mRNA output from each allele of a transcript single nucleotide polymorphism. We assessed RNA extracted from the cartilage and other joint tissues of OA patients who had undergone elective joint replacement surgery. A two-tailed Mann-Whitney exact test was used to test the significance of any allelic differences. RESULTS: GNL3 and SPCS1 demonstrated significant allelic expression imbalance (AEI) in OA cartilage (GNL3, mean AEI = 1.04, p = 0.0002; SPCS1, mean AEI = 1.07, p < 0.0001). Similar results were observed in other tissues. Expression of the OA-associated allele was lower than that of the non-associated allele for both genes. CONCLUSIONS: cis-acting regulatory polymorphisms acting on GNL3 and SPCS1 contribute to the OA association signal at chromosome 3p21, and these genes therefore merit further investigation.

Specific isoforms of the ubiquitin ligase gene WWP2 are targets of osteoarthritis genetic risk via a differentially methylated DNA sequence.

BACKGROUND: Transitioning from a genetic association signal to an effector gene and a targetable molecular mechanism requires the application of functional fine-mapping tools such as reporter assays and genome editing. In this report, we undertook such studies on the osteoarthritis (OA) risk that is marked by single nucleotide polymorphism (SNP) rs34195470 (A > G). The OA risk-conferring G allele of this SNP associates with increased DNA methylation (DNAm) at two CpG dinucleotides within WWP2. This gene encodes a ubiquitin ligase and is the host gene of microRNA-140 (miR-140). WWP2 and miR-140 are both regulators of TGFß signaling. METHODS: Nucleic acids were extracted from adult OA (arthroplasty) and foetal cartilage. Samples were genotyped and DNAm quantified by pyrosequencing at the two CpGs plus 14 flanking CpGs. CpGs were tested for transcriptional regulatory effects using a chondrocyte cell line and reporter gene assay. DNAm was altered using epigenetic editing, with the impact on gene expression determined using RT-qPCR. In silico analysis complemented laboratory experiments. RESULTS: rs34195470 genotype associates with differential methylation at 14 of the 16 CpGs in OA cartilage, forming a methylation quantitative trait locus (mQTL). The mQTL is less pronounced in foetal cartilage (5/16 CpGs). The reporter assay revealed that the CpGs reside within a transcriptional regulator. Epigenetic editing to increase their DNAm resulted in altered expression of the full-length and N-terminal transcript isoforms of WWP2. No changes in expression were observed for the C-terminal isoform of WWP2 or for miR-140. CONCLUSIONS: As far as we are aware, this is the first experimental demonstration of an OA association signal targeting specific transcript isoforms of a gene. The WWP2 isoforms encode proteins with varying substrate specificities for the components of the TGFß signaling pathway. Future analysis should focus on the substrates regulated by the two WWP2 isoforms that are the targets of this genetic risk.

Expression of the osteoarthritis-associated gene GDF5 is modulated epigenetically by DNA methylation.

GDF5 is involved in synovial joint development, maintenance and repair, and the rs143383 C/T single nucleotide polymorphism (SNP) located in the 5'UTR of GDF5 is associated, at the genome-wide significance level, with osteoarthritis susceptibility, and with other musculoskeletal phenotypes including height, congenital hip dysplasia and Achilles tendinopathy. There is a significant reduction in the expression of the disease-associated T allele relative to the C allele in synovial joint tissues, an effect influenced by a second SNP (rs143384, C/T) also within the 5'UTR. The differential allelic expression (DAE) imbalance of the C and T alleles of rs143383 varies intra- and inter-individually, suggesting that DAE may be modulated epigenetically. The C alleles of both SNPs form CpG dinucleotides that are potentially amenable to regulation by methylation. Here, we have examined whether DNA methylation regulates GDF5 expression and the allelic imbalance caused by rs143383. We observed methylation of the GDF5 promoter and 5'UTR in cell lines and joint tissues, with demethylation correlating with increased GDF5 expression. The CpG sites created by the C alleles at rs143383 and rs143384 were variably methylated, and treatment of a heterozygous cell line with a demethylating agent further increased the allelic expression imbalance between the C and T alleles. This demonstrates that the genetic effect of the rs143383 SNP on GDF5 expression is modulated epigenetically by DNA methylation. The variability in DAE of rs143383 is therefore partly accounted for by differences in DNA methylation that could influence the penetrance of this allele in susceptibility to common musculoskeletal diseases.