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.

Development and validation of a machine learning-supported strategy of patient selection for osteoarthritis clinical trials: the IMI-APPROACH study.

Objectives: To efficiently assess the disease-modifying potential of new osteoarthritis treatments, clinical trials need progression-enriched patient populations. To assess whether the application of machine learning results in patient selection enrichment, we developed a machine learning recruitment strategy targeting progressive patients and validated it in the IMI-APPROACH knee osteoarthritis prospective study. Design: We designed a two-stage recruitment process supported by machine learning models trained to rank candidates by the likelihood of progression. First stage models used data from pre-existing cohorts to select patients for a screening visit. The second stage model used screening data to inform the final inclusion. The effectiveness of this process was evaluated using the actual 24-month progression. Results: From 3500 candidate patients, 433 with knee osteoarthritis were screened, 297 were enrolled, and 247 completed the 2-year follow-up visit. We observed progression related to pain (P, 30%), structure (S, 13%), and combined pain and structure (P â€‹+ â€‹S, 5%), and a proportion of non-progressors (N, 52%) ∼15% lower vs an unenriched population. Our model predicted these outcomes with AUC of 0.86 [95% CI, 0.81-0.90] for pain-related progression and AUC of 0.61 [95% CI, 0.52-0.70] for structure-related progression. Progressors were ranked higher than non-progressors for P â€‹+ â€‹S (median rank 65 vs 143, AUC = 0.75), P (median rank 77 vs 143, AUC = 0.71), and S patients (median rank 107 vs 143, AUC = 0.57). Conclusions: The machine learning-supported recruitment resulted in enriched selection of progressive patients. Further research is needed to improve structural progression prediction and assess this strategy in an interventional trial.

Osteoarthritis genetic risk acting on the galactosyltransferase gene COLGALT2 has opposing functional effects in articulating joint tissues.

BACKGROUND: Investigation of cartilage and chondrocytes has revealed that the osteoarthritis risk marked by the independent DNA variants rs11583641 and rs1046934 mediate  their effects by decreasing the methylation status of CpG dinucleotides in enhancers and increasing the expression of shared target gene COLGALT2. We set out to investigate if these functional effects operate in a non-cartilaginous joint tissue. METHODS: Nucleic acids were extracted from the synovium of osteoarthritis patients. Samples were genotyped, and DNA methylation was quantified by pyrosequencing at CpGs within the COLGALT2 enhancers. CpGs were tested for enhancer effects using a synovial cell line and a reporter gene assay. DNA methylation was altered using epigenetic editing, with the impact on gene expression determined using quantitative polymerase chain reaction. In silico analysis complemented laboratory experiments. RESULTS: The rs1046934 genotype did not associate with DNA methylation or COLGALT2 expression in the synovium, whereas the rs11583641 genotype did. Surprisingly, the effects for rs11583641 were opposite to those previously observed in cartilage. Epigenetic editing in synovial cells revealed that enhancer methylation is causally linked to COLGALT2 expression. CONCLUSIONS: This is the first direct demonstration for osteoarthritis genetic risk of a functional link between DNA methylation and gene expression operating in opposite directions between articular joint tissues. It highlights pleiotropy in the action of osteoarthritis risk and provides a cautionary note in the application of future genetically based osteoarthritis therapies: an intervention that decreases the detrimental effect of a risk allele in one joint tissue may inadvertently increase its detrimental effect in another joint tissue.

Mediation of the Same Epigenetic and Transcriptional Effect by Independent Osteoarthritis Risk-Conferring Alleles on a Shared Target Gene, COLGALT2.

OBJECTIVE: Over 100 DNA variants have been associated with osteoarthritis (OA), including rs1046934, located within a linkage disequilibrium block encompassing part of COLGALT2 and TSEN15. The present study was undertaken to determine the target gene(s) and the mechanism of action of the OA locus using human fetal cartilage, cartilage from OA and femoral neck fracture arthroplasty patients, and a chondrocyte cell model. METHODS: Genotyping and methylation array data of DNA from human OA cartilage samples (n = 87) were used to determine whether the rs1046934 genotype is associated with differential DNA methylation at proximal CpGs. Results were replicated in DNA from human arthroplasty (n = 132) and fetal (n = 77) cartilage samples using pyrosequencing. Allelic expression imbalance (AEI) measured the effects of genotype on COLGALT2 and TSEN15 expression. Reporter gene assays and epigenetic editing determined the functional role of regions harboring differentially methylated CpGs. In silico analyses complemented these experiments. RESULTS: Three differentially methylated CpGs residing within regulatory regions were detected in the human OA cartilage array data, and 2 of these were replicated in human arthroplasty and fetal cartilage. AEI was detected for COLGALT2 and TSEN15, with associations between expression and methylation for COLGALT2. Reporter gene assays confirmed that the CpGs are in chondrocyte enhancers, with epigenetic editing results directly linking methylation with COLGALT2 expression. CONCLUSION: COLGALT2 is a target of this OA locus. We previously characterized another OA locus, marked by rs11583641, that independently targets COLGALT2. The genotype of rs1046934, like rs11583641, mediates its effect by modulating expression of COLGALT2 via methylation changes to CpGs located in enhancers. Although the single-nucleotide polymorphisms, CpGs, and enhancers are distinct between the 2 independent OA risk loci, their effect on COLGALT2 is the same. COLGALT2 is the target of independent OA risk loci sharing a common mechanism of action.

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.

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.

Research priorities to reduce the impact of musculoskeletal disorders: a priority setting exercise with the child health and nutrition research initiative method.

Involving research users in setting priorities for research is essential to ensure the outcomes are patient-centred and maximise its value and impact. The Musculoskeletal Disorders Research Advisory Group Versus Arthritis led a research priority setting exercise across musculoskeletal disorders. The Child Health and Nutrition Research Initiative (CHNRI) method of setting research priorities with a range of stakeholders was used, involving four stages and two surveys, to: (1) gather research uncertainties, (2) consolidate these, (3) score uncertainties against importance and impact, and (4) analyse scoring for prioritisation. 213 people responded to the first survey and 285 people to the second, representing clinicians, researchers, and people with musculoskeletal disorders. Key priorities included developing and testing new treatments, better treatment targeting, early diagnosis, prevention, and better understanding and management of pain, with an emphasis on understanding underpinning mechanisms. We present a call to action to researchers and funders to target these priorities.

Identification of TMEM129, encoding a ubiquitin-protein ligase, as an effector gene of osteoarthritis genetic risk.

BACKGROUND: Osteoarthritis is highly heritable and genome-wide studies have identified single nucleotide polymorphisms (SNPs) associated with the disease. One such locus is marked by SNP rs11732213 (T > C). Genotype at rs11732213 correlates with the methylation levels of nearby CpG dinucleotides (CpGs), forming a methylation quantitative trait locus (mQTL). This study investigated the regulatory activity of the CpGs to identify a target gene of the locus. METHODS: Nucleic acids were extracted from the articular cartilage of osteoarthritis patients. Samples were genotyped, and DNA methylation was quantified by pyrosequencing at 14 CpGs within a 259-bp interval. CpGs were tested for enhancer effects in immortalised chondrocytes using a reporter gene assay. DNA methylation at the locus was altered using targeted epigenome editing, with the impact on gene expression determined using quantitative polymerase chain reaction. RESULTS: rs11732213 genotype correlated with DNA methylation at nine CpGs, which formed a differentially methylated region (DMR), with the osteoarthritis risk allele T corresponding to reduced levels of methylation. The DMR acted as an enhancer and demethylation of the CpGs altered expression of TMEM129. Allelic imbalance in TMEM129 expression was identified in cartilage, with under-expression of the risk allele. CONCLUSIONS: TMEM129 is a target of osteoarthritis genetic risk at this locus. Genotype at rs11732213 impacts DNA methylation at the enhancer, which, in turn, modulates TMEM129 expression. TMEM129 encodes an enzyme involved in protein degradation within the endoplasmic reticulum, a process previously implicated in osteoarthritis. TMEM129 is a compelling osteoarthritis susceptibility target.

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.

Translating osteoarthritis genetics research: challenging times ahead.

The ultimate goal of molecular genetic studies of human diseases is to translate the discoveries for patient benefit. For diseases that lack licensed disease-modifying therapeutics, such as osteoarthritis (OA), the need is acute. OA is polygenic and affects older individuals, with a recent genome-wide study of over 800 000 individuals adding 52 novel association signals to those already reported on for this common arthritis. Many of the predicted effector genes of these signals encode proteins that are targets of drugs for other indications, highlighting repurposing opportunities. Here, the potential for OA genetic data to translate is discussed, including whether the developmental origin of OA will limit the application of genetic risk data for disease-modification purposes.

Neuropathic pain in the IMI-APPROACH knee osteoarthritis cohort: prevalence and phenotyping.

OBJECTIVES: Osteoarthritis (OA) patients with a neuropathic pain (NP) component may represent a specific phenotype. This study compares joint damage, pain and functional disability between knee OA patients with a likely NP component, and those without a likely NP component. METHODS: Baseline data from the Innovative Medicines Initiative Applied Public-Private Research enabling OsteoArthritis Clinical Headway knee OA cohort study were used. Patients with a painDETECT score ≥19 (with likely NP component, n=24) were matched on a 1:2 ratio to patients with a painDETECT score ≤12 (without likely NP component), and similar knee and general pain (Knee Injury and Osteoarthritis Outcome Score pain and Short Form 36 pain). Pain, physical function and radiographic joint damage of multiple joints were determined and compared between OA patients with and without a likely NP component. RESULTS: OA patients with painDETECT scores ≥19 had statistically significant less radiographic joint damage (p≤0.04 for Knee Images Digital Analysis parameters and Kellgren and Lawrence grade), but an impaired physical function (p<0.003 for all tests) compared with patients with a painDETECT score ≤12. In addition, more severe pain was found in joints other than the index knee (p≤0.001 for hips and hands), while joint damage throughout the body was not different. CONCLUSIONS: OA patients with a likely NP component, as determined with the painDETECT questionnaire, may represent a specific OA phenotype, where local and overall joint damage is not the main cause of pain and disability. Patients with this NP component will likely not benefit from general pain medication and/or disease-modifying OA drug (DMOAD) therapy. Reserved inclusion of these patients in DMOAD trials is advised in the quest for successful OA treatments.Trial registration numberThe study is registered under clinicaltrials.gov nr: NCT03883568.

Haematological parameters and coagulation in umbilical cord blood following COVID-19 infection in pregnancy.

OBJECTIVE: The aim of this study was to evaluate infants, born to women with SARS-CoV-2 detected during pregnancy, for evidence of haematological abnormalities or hypercoagulability in umbilical cord blood. STUDY DESIGN: This was a prospective observational case-control study of infants born to women who had SARS-CoV-2 RNA detected by PCR at any time during their pregnancy (n = 15). The study was carried out in a Tertiary University Maternity Hospital (8,500 deliveries/year) in Ireland. This study was approved by the Hospital Research Ethics Committee and written consent was obtained. Umbilical cord blood samples were collected at delivery, full blood count and Calibrated Automated Thrombography were performed. Demographics and clinical outcomes were recorded. Healthy term infants, previously recruited as controls to a larger study prior to the outbreak of COVID-19, were the historical control population (n = 10). RESULTS: Infants born to women with SARS-CoV-2 had similar growth parameters (birth weight 3600 g v 3680 g, p = 0.83) and clinical outcomes to healthy controls, such as need for resuscitation at birth (2 (13.3%) v 1 (10%), p = 1.0) and NICU admission (1 (6.7%) v 2 (20%), p = 0.54). Haematological parameters (Haemoglobin, platelet, white cell and lymphocyte counts) in the COVID-19 group were all within normal neonatal reference ranges. Calibrated Automated Thrombography revealed no differences in any thrombin generation parameters (lag time (p = 0.92), endogenous thrombin potential (p = 0.24), peak thrombin (p = 0.44), time to peak thrombin (p = 0.94)) between the two groups. CONCLUSION: In this prospective study including eligible cases in a very large population of approximately 1500 women, there was no evidence of derangement of the haematological parameters or hypercoagulability in umbilical cord blood due to COVID-19. Further research is required to investigate the pathological placental changes, particularly COVID-19 placentitis and the impact of different strains of SARS-CoV-2 (particularly the B.1.1.7 and the emerging Delta variant) and the severity and timing of infection on the developing fetus.

Genetic and Epigenetic Fine-Tuning of TGFB1 Expression Within the Human Osteoarthritic Joint.

OBJECTIVE: Osteoarthritis (OA) is an age-related disease characterized by articular cartilage degeneration. It is largely heritable, and genetic screening has identified single-nucleotide polymorphisms (SNPs) marking genomic risk loci. One such locus is marked by the G>A SNP rs75621460, downstream of TGFB1. This gene encodes transforming growth factor ß1, the correct expression of which is essential for cartilage maintenance. This study investigated the regulatory activity of rs75621460 to characterize its impact on TGFB1 expression in disease-relevant patient samples (n = 319) and in Tc28a2 immortalized chondrocytes. METHODS: Articular cartilage samples from human patients were genotyped, and DNA methylation levels were quantified using pyrosequencing. Gene reporter and electrophoretic mobility shift assays were used to determine differential nuclear protein binding to the region. The functional impact of DNA methylation on TGFB1 expression was tested using targeted epigenome editing. RESULTS: The analyses showed that SNP rs75621460 was located within a TGFB1 enhancer region, and the OA risk allele A altered transcription factor binding, with decreased enhancer activity. Protein complexes binding to A (but not G) induced DNA methylation at flanking CG dinucleotides. Strong correlations between patient DNA methylation levels and TGFB1 expression were observed, with directly opposing effects in the cartilage and the synovium at this locus. This demonstrated biologic pleiotropy in the impact of the SNP within different tissues of the articulating joint. CONCLUSION: The OA risk SNP rs75621460 impacts TGFB1 expression by modulating the function of a gene enhancer. We propose a mechanism by which the SNP impacts enhancer function, providing novel biologic insight into one mechanism of OA genetic risk, which may facilitate the development of future pharmacologic therapies.

Genetic and Epigenetic Interplay Within a COLGALT2 Enhancer Associated With Osteoarthritis.

OBJECTIVE: The osteoarthritis (OA)-associated single-nucleotide polymorphism (SNP) rs11583641 is located in COLGALT2, encoding a posttranslational modifier of collagen. In cartilage, the SNP genotype correlates with DNA methylation in a putative enhancer. This study was undertaken to characterize the mechanistic relationship between rs11583641, the putative enhancer, and COLGALT2 expression using cartilage samples from human patients and a chondrocyte cell model. METHODS: Nucleic acids were extracted from articular cartilage samples obtained from patients with OA (n = 137). Samples were genotyped, and DNA methylation was quantified at 12 CpGs using pyrosequencing. The putative enhancer was deleted in Tc28a2 chondrocytes using clustered regularly interspaced short palindromic repeat/Cas9, and the impact on nearby gene expression was determined using real-time quantitative polymerase chain reaction. Targeted modulation of the epigenome using catalytically dead Cas9 (dCas9) constructs fused to DNA methyltransferase 3a or ten-eleven translocase 1 allowed for the investigation of a causal relationship between DNA methylation and enhancer activity. RESULTS: The genotype at rs11583641 correlated with DNA methylation at 3 CpGs, and the presence of the OA risk allele, C, corresponded to reduced levels of methylation. Deletion of the enhancer resulted in a 2.7-fold reduction in COLGALT2 expression. Targeted methylation and demethylation of the CpGs had antagonistic effects on COLGALT2 expression. An allelic imbalance in the expression of COLGALT2 was identified in the cartilage from patients with OA, with relative overexpression of the OA risk allele. Allelic expression ratios correlated with DNA methylation at 4 CpGs. CONCLUSION: COLGALT2 is a target of OA genetic risk at this locus. The genotype at rs11583641 impacts DNA methylation in a gene enhancer, which, in turn, modulates COLGALT2 expression. COLGALT2 encodes an enzyme that initiates posttranslational glycosylation of collagens and is therefore a compelling OA susceptibility target.

Osteoarthritis Research Society International (OARSI): Past, present and future.

We provide a detailed account of the origin and establishment of the Osteoarthritis Research Society International (OARSI) and celebrate its history from inception to the current day. We discuss the mission, vision and strategic objectives of OARSI and how these have developed and evolved over the last 3 decades. We celebrate the achievements of the society as we approach its 30th birthday, honor the entire presidential line and respectfully pay tribute to the past presidents who are no longer with us. We reflect on the strong foundations of our society, OARSI's efforts to disseminate understanding of the health, disability and economic burdens of osteoarthritis (OA) to policymakers, and the exciting initiatives to make the society inclusive and international. We thank our corporate and industrial sponsors, who have supported us over many years, without whom our annual congresses would not have been possible. We celebrate our longstanding strategic partnership with our publisher, Elsevier, and the successful launch of our new journal Osteoarthritis and Cartilage Open, the most significant new development in our dissemination toolbox. For the first time in the history of the organization, our annual congress was cancelled in April 2020 and the 2021 meeting will be virtual. Despite the numerous challenges posed by the ongoing COVID-19 pandemic and the need to adapt quickly to a rapidly changing landscape, we must remain optimistic about the future. We will take advantage of new exciting opportunities to advance our mission and vision to enhance the quality of life of persons with OA.

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.

Multi-Tissue Epigenetic and Gene Expression Analysis Combined With Epigenome Modulation Identifies RWDD2B as a Target of Osteoarthritis Susceptibility.

OBJECTIVE: Osteoarthritis (OA) is polygenic, with more than 90 risk loci currently mapped, including at the single-nucleotide polymorphism rs6516886. Previous analysis of OA cartilage DNA identified 6 CpG dinucleotides whose methylation levels correlated with the rs6516886 genotype, forming methylation quantitative trait loci (mQTLs). We undertook this study to investigate these mQTLs and to map expression quantitative trait loci (eQTLs) across joint tissues in order to prioritize a particular gene as a target of the rs6516886 association effect. METHODS: Nucleic acids were extracted from the cartilage, fat pad, synovium, and peripheral blood from OA patients. Methylation of CpGs and allelic expression imbalance of potential target genes were assessed by pyrosequencing. A chondrocyte cell line expressing deactivated Cas9 (dCas9)-TET1 was used to directly alter CpG methylation levels, with effects on gene expression quantified by polymerase chain reaction. RESULTS: Multiple mQTLs were detected, with effects strongest in joint tissues and with methylation at CpG cg20220242 correlating most significantly with the rs6516886 genotype. CpG cg20220242 is located upstream of RWDD2B. Significant rs6516886 eQTLs were observed for this gene, with the OA risk-conferring allele of rs6516886 correlating with reduced expression CpG methylation also correlated with allelic expression of RWDD2B, forming methylation-expression QTLs (meQTLs). Deactivated Cas9-TET1 reduction in the methylation of cg20220242 increased expression of RWDD2B. CONCLUSION: The rs6516886 association signal is a multi-tissue meQTL involving cg20220242 and acting on RWDD2B. Modulating CpG methylation reverses the impact of the risk allele. RWDD2B codes for a protein about which little is currently known. Its further analysis as a target of OA genetic risk will provide novel insight into this complex disease.

Predicting bacteraemia in maternity patients using full blood count parameters: A supervised machine learning algorithm approach.

INTRODUCTION: Bacteraemia in pregnancy and the post-partum period can lead to maternal and newborn morbidly. The purpose of this study was to use machine learning tools to identify if bacteraemia in pregnant or post-partum women could be predicted by full blood count (FBC) parameters other than the white cell count. METHODS: The study was performed on 129 women with a positive blood culture (BC) for a clinically significant organism, who had a FBC taken at the same time. They were matched with controls who had a negative BC taken at the same time as a FBC. The data were split in to a training (70%) and test (30%) data set. Machine learning techniques such as recursive partitioning and classification and regression trees were used. RESULTS: A neutrophil/lymphocyte ratio (NLR) of >20 was found to be the most clinically relevant and interpretable construct of the FBC result to predict bacteraemia. The diagnostic accuracy of NLR >20 to predict bacteraemia was then examined. Thirty-six of the 129 bacteraemia patients had a NLR >20, while only 223 of the 3830 controls had a NLR >20. This gave a sensitivity of 27.9% (95% CI 20.3-36.4), specificity of 94.1% (93.3-94.8), positive predictive value of 13.9% (10.6-17.9) and a negative predictive value (NPV) of 97.4% (97.2-97.7) when the prevalence of bacteraemia was 3%. CONCLUSION: The NLR should be considered for use in routine clinical practice when assessing the FBC result in patients with suspected bacteraemia during pregnancy or in the post-partum period.

Directions for Research on Climate and Conflict.

The potential links between climate and conflict are well studied, yet disagreement about the specific mechanisms and their significance for societies persists. Here, we build on assessment of the relationship between climate and organized armed conflict to define crosscutting priorities for future directions of research. They include (1) deepening insight into climate-conflict linkages and conditions under which they manifest, (2) ambitiously integrating research designs, (3) systematically exploring future risks and response options, responsive to ongoing decision-making, and (4) evaluating the effectiveness of interventions to manage climate-conflict links. The implications of this expanding scientific domain unfold in real time.