Weight-Bearing Physical Activity, Lower-Limb Muscle Mass, and Risk of Knee Osteoarthritis.

Importance: It has been demonstrated that total physical activity is not associated with risk of osteoarthritis. However, the association of different types of physical activity with incident knee osteoarthritis remains unclear. Objective: To determine whether weight-bearing recreational physical activities are associated with increased risk of incident knee osteoarthritis. Design, Setting, and Participants: This prospective cohort study used data from the Rotterdam Study (1996 to 2009), including participants with knee x-ray measurements at baseline and follow-up examinations. Participants with knee osteoarthritis at baseline were excluded. Residents aged 45 years and older of the Ommoord district in the city of Rotterdam in The Netherlands were invited to join the Rotterdam Study (78% response rate). Analysis was conducted in June 2023. Exposure: Total, weight-bearing, and non-weight-bearing recreational physical activities collected by questionnaires at baseline. Main Outcomes and Measures: Incident radiographic knee osteoarthritis measured by knee x-ray was the primary outcome, and incident symptomatic knee osteoarthritis defined by x-ray and knee pain questionnaire was the secondary outcome. The association of different types of recreational physical activity with radiographic knee osteoarthritis was examined using logistic regression within generalized estimating equation framework after adjusting for potential confounders. A prespecified stratification analysis was planned on the basis of lower-limb muscle mass index (LMI) tertiles, measured by dual-energy x-ray absorptiometry. Results: A total of 5003 individuals (2804 women [56.0%]; mean [SD] age, 64.5 [7.9] years) were included. The knee osteoarthritis incident rate was 8.4% (793 of 9483 knees) for a mean (SD) follow-up time of 6.33 (2.46) years. Higher weight-bearing activity was associated with increased odds of incident knee osteoarthritis (odds ratio [OR], 1.22; 95% CI, 1.10-1.35; P < .001), but non-weight-bearing activity was not (OR, 1.04; 95% CI, 0.95-1.15; P = .37). In the analysis stratified by LMI tertiles, the association of weight-bearing activity with incident osteoarthritis was found only among 431 patients in the lowest LMI tertile (OR, 1.53; 95% CI, 1.15-2.04; P = .003), but not among patients in the middle or high LMI tertile. Conclusions and Relevance: The findings of this study suggest that weight-bearing activity is associated with incident knee osteoarthritis in people with low levels of lower-limb muscle mass, which might be a promising avenue for tailored advice for physical activity.

Cohort profile: Worldwide Collaboration on OsteoArthritis prediCtion for the Hip (World COACH) - an international consortium of prospective cohort studies with individual participant data on hip osteoarthritis.

PURPOSE: Hip osteoarthritis (OA) is a major cause of pain and disability worldwide. Lack of effective therapies may reflect poor knowledge on its aetiology and risk factors, and result in the management of end-stage hip OA with costly joint replacement. The Worldwide Collaboration on OsteoArthritis prediCtion for the Hip (World COACH) consortium was established to pool and harmonise individual participant data from prospective cohort studies. The consortium aims to better understand determinants and risk factors for the development and progression of hip OA, to optimise and automate methods for (imaging) analysis, and to develop a personalised prediction model for hip OA. PARTICIPANTS: World COACH aimed to include participants of prospective cohort studies with ≥200 participants, that have hip imaging data available from at least 2 time points at least 4 years apart. All individual participant data, including clinical data, imaging (data), biochemical markers, questionnaires and genetic data, were collected and pooled into a single, individual-level database. FINDINGS TO DATE: World COACH currently consists of 9 cohorts, with 38 021 participants aged 18-80 years at baseline. Overall, 71% of the participants were women and mean baseline age was 65.3±8.6 years. Over 34 000 participants had baseline pelvic radiographs available, and over 22 000 had an additional pelvic radiograph after 8-12 years of follow-up. Even longer radiographic follow-up (15-25 years) is available for over 6000 of these participants. FUTURE PLANS: The World COACH consortium offers unique opportunities for studies on the relationship between determinants/risk factors and the development or progression of hip OA, by using harmonised data on clinical findings, imaging, biomarkers, genetics and lifestyle. This provides a unique opportunity to develop a personalised hip OA risk prediction model and to optimise methods for imaging analysis of the hip.

Defining type 2 diabetes polygenic risk scores through colocalization and network-based clustering of metabolic trait genetic associations.

BACKGROUND: Type 2 diabetes (T2D) is a heterogeneous and polygenic disease. Previous studies have leveraged the highly polygenic and pleiotropic nature of T2D variants to partition the heterogeneity of T2D, in order to stratify patient risk and gain mechanistic insight. We expanded on these approaches by performing colocalization across GWAS traits while assessing the causality and directionality of genetic associations. METHODS: We applied colocalization between T2D and 20 related metabolic traits, across 243 loci, to obtain inferences of shared casual variants. Network-based unsupervised hierarchical clustering was performed on variant-trait associations. Partitioned polygenic risk scores (PRSs) were generated for each cluster using T2D summary statistics and validated in 21,742 individuals with T2D from 3 cohorts. Inferences of directionality and causality were obtained by applying Mendelian randomization Steiger's Z-test and further validated in a pediatric cohort without diabetes (aged 9-12 years old, n = 3866). RESULTS: We identified 146 T2D loci that colocalized with at least one metabolic trait locus. T2D variants within these loci were grouped into 5 clusters. The clusters corresponded to the following pathways: obesity, lipodystrophic insulin resistance, liver and lipid metabolism, hepatic glucose metabolism, and beta-cell dysfunction. We observed heterogeneity in associations between PRSs and metabolic measures across clusters. For instance, the lipodystrophic insulin resistance (Beta - 0.08 SD, 95% CI [- 0.10-0.07], p = 6.50 × 10-32) and beta-cell dysfunction (Beta - 0.10 SD, 95% CI [- 0.12, - 0.08], p = 1.46 × 10-47) PRSs were associated to lower BMI. Mendelian randomization Steiger analysis indicated that increased T2D risk in these pathways was causally associated to lower BMI. However, the obesity PRS was conversely associated with increased BMI (Beta 0.08 SD, 95% CI 0.06-0.10, p = 8.0 × 10-33). Analyses within a pediatric cohort supported this finding. Additionally, the lipodystrophic insulin resistance PRS was associated with a higher odds of chronic kidney disease (OR 1.29, 95% CI 1.02-1.62, p = 0.03). CONCLUSIONS: We successfully partitioned T2D genetic variants into phenotypic pathways using a colocalization first approach. Partitioned PRSs were associated to unique metabolic and clinical outcomes indicating successful partitioning of disease heterogeneity. Our work expands on previous approaches by providing stronger inferences of shared causal variants, causality, and directionality of GWAS variant-trait associations.

The identification of distinct protective and susceptibility mechanisms for hip osteoarthritis: findings from a genome-wide association study meta-analysis of minimum joint space width and Mendelian randomisation cluster analyses.

BACKGROUND: Hip minimum joint space width (mJSW) provides a proxy for cartilage thickness. This study aimed to conduct a genome-wide association study (GWAS) of mJSW to (i) identify new genetic determinants of mJSW and (ii) identify which mJSW loci convey hip osteoarthritis (HOA) risk and would therefore be of therapeutic interest. METHODS: GWAS meta-analysis of hip mJSW derived from plain X-rays and DXA was performed, stratified by sex and adjusted for age and ancestry principal components. Mendelian randomisation (MR) and cluster analyses were used to examine causal effect of mJSW on HOA. FINDINGS: 50,745 individuals were included in the meta-analysis. 42 SNPs, which mapped to 39 loci, were identified. Mendelian randomisation (MR) revealed little evidence of a causal effect of mJSW on HOA (ORIVW 0.98 [95% CI 0.82-1.18]). However, MR-Clust analysis suggested the null MR estimates reflected the net effect of two distinct causal mechanisms cancelling each other out, one of which was protective, whereas the other increased HOA susceptibility. For the latter mechanism, all loci were positively associated with height, suggesting mechanisms leading to greater height and mJSW increase the risk of HOA in later life. INTERPRETATIONS: One group of mJSW loci reduce HOA risk via increased mJSW, suggesting possible utility as targets for chondroprotective therapies. The second group of mJSW loci increased HOA risk, despite increasing mJSW, but were also positively related to height, suggesting they contribute to HOA risk via a growth-related mechanism. FUNDING: Primarily funded by the Medical Research Council and Wellcome Trust.

A functional genomics approach reveals suggestive quantitative trait loci associated with combined TLR4 and BCP crystal-induced inflammation and osteoarthritis.

OBJECTIVE: Basic calcium phosphate (BCP) crystals can activate the NLRP3 inflammasome and are potentially involved in the pathogenesis of osteoarthritis (OA). In order to elucidate relevant inflammatory mechanisms in OA, we used a functional genomics approach to assess genetic variation influencing BCP crystal-induced cytokine production. METHOD: Peripheral blood mononuclear cells (PBMCs) were isolated from healthy volunteers who were previously genotyped and stimulated with BCP crystals and/or lipopolysaccharide (LPS) after which cytokines release was assessed. Cytokine quantitative trait locus (cQTL) mapping was performed. For in vitro validation of the cQTL located in anoctamin 3 (ANO3), PBMCs were incubated with Tamoxifen and Benzbromarone prior to stimulation. Additionally, we performed co-localisation analysis of our top cQTLs with the most recent OA meta-analysis of genome-wide association studies (GWAS). RESULTS: We observed that BCP crystals and LPS synergistically induce IL-1ß in human PBMCs. cQTL analysis revealed several suggestive loci influencing cytokine release upon stimulation, among which are quantitative trait locus annotated to ANO3 and GLIS3. As functional validation, anoctamin inhibitors reduced IL-1ß release in PBMCs after stimulation. Co-localisation analysis showed that the GLIS3 locus was shared between LPS/BCP crystal-induced IL-1ß and genetic association with Knee OA. CONCLUSIONS: We identified and functionally validated a new locus, ANO3, associated with LPS/BCP crystal-induced inflammation in PBMCs. Moreover, the cQTL in the GLIS3 locus co-localises with the previously found locus associated with Knee OA, suggesting that this Knee OA locus might be explained through an inflammatory mechanism. These results form a basis for further exploration of inflammatory mechanisms in OA.

A Genome-Wide Association Study Meta-Analysis of Alpha Angle Suggests Cam-Type Morphology May Be a Specific Feature of Hip Osteoarthritis in Older Adults.

OBJECTIVE: To examine the genetic architecture of cam morphology using alpha angle (AA) as a proxy measure and conduct an AA genome-wide association study (GWAS) followed by Mendelian randomization (MR) to evaluate its causal relationship with hip osteoarthritis (OA). METHODS: Observational analyses examined associations between AA measurements derived from hip dual x-ray absorptiometry (DXA) scans from the UK Biobank study and radiographic hip OA outcomes and subsequent total hip replacement. Following these analyses, an AA GWAS meta-analysis was performed (N = 44,214) using AA measurements previously derived in the Rotterdam Study. Linkage disequilibrium score regression assessed the genetic correlation between AA and hip OA. Genetic associations considered significant (P < 5 × 10-8 ) were used as AA genetic instrument for 2-sample MR analysis. RESULTS: DXA-derived AA showed expected associations between AA and radiographic hip OA (adjusted odds ratio [OR] 1.63 [95% confidence interval (95% CI) 1.58, 1.67]) and between AA and total hip replacement (adjusted hazard ratio 1.45 [95% CI 1.33, 1.59]) in the UK Biobank study cohort. The heritability of AA was 10%, and AA had a moderate genetic correlation with hip OA (rg  = 0.26 [95% CI 0.10, 0.43]). Eight independent genetic signals were associated with AA. Two-sample MR provided weak evidence of causal effects of AA on hip OA risk (inverse variance weighted OR 1.84 [95% CI 1.14, 2.96], P = 0.01). In contrast, genetic predisposition for hip OA had stronger evidence of a causal effect on increased AA (inverse variance weighted ß = 0.09 [95% CI 0.04, 0.13], P = 4.58 × 10-5 ). CONCLUSION: Expected observational associations between AA and related clinical outcomes provided face validity for the DXA-derived AA measurements. Evidence of bidirectional associations between AA and hip OA, particularly for risk of hip OA on AA, suggests that hip shape modeling secondary to a genetic predisposition to hip OA contributes to the well-established relationship between hip OA and cam morphology in older adults.

Plasma proteomics identifies CRTAC1 as a biomarker for osteoarthritis severity and progression.

OBJECTIVES: The aim of this study was to identify biomarkers for radiographic OA severity and progression acting within the inflammation and metabolic pathways. METHODS: For 3517 Rotterdam Study participants, 184 plasma protein levels were measured using Olink inflammation and cardiometabolic panels. We studied associations with severity and progression of knee, hip and hand OA and a composite overall OA burden score by multivariable regression models, adjusting for age, sex, cell counts and BMI. RESULTS: We found 18 significantly associated proteins for overall OA burden, of which 5 stayed significant after multiple testing correction: circulating cartilage acidic protein 1 (CRTAC1), cartilage oligomeric matrix protein (COMP), thrombospondin 4, IL-18 receptor 1 (IL-18R1) and TNF ligand superfamily member 14. These proteins were also associated with progression of knee OA, with the exception of IL-18R1. The strongest association was found for the level of CRTAC1, with 1 s.d. increase in protein level resulting in an increase of 0.09 (95% CI 0.06, 0.12) in the overall OA Kellgren-Lawrence sum score (P = 2.9 × 10-8) in the model adjusted for age, sex, BMI and cell counts. This association was also present with the severity of OA in all three joints and progression of knee OA and was independent of BMI. We observed a stronger association for CRTAC1 with OA than for the well-known OA biomarker COMP. CONCLUSION: We identified several compelling biomarkers reflecting the overall OA burden and the increased risk for OA progression. CRTAC1 was the most compelling and robust biomarker for OA severity and progression. Such a biomarker may be used for disease monitoring.

Risk Assessment for Hip and Knee Osteoarthritis Using Polygenic Risk Scores.

OBJECTIVE: Polygenic risk scores (PRS) allow risk stratification using common single-nucleotide polymorphisms (SNPs), and clinical applications are currently explored for several diseases. This study was undertaken to assess the risk of hip and knee osteoarthritis (OA) using PRS. METHODS: We analyzed 12,732 individuals from a population-based cohort from the Rotterdam Study (n = 11,496), a clinical cohort (Cohort Hip and Cohort Knee [CHECK] study; n = 908), and a high-risk cohort of overweight women (Prevention of Knee OA in Overweight Females [PROOF] study; n = 328), for the association of the PRS with prevalence/incidence of radiographic OA, of clinical OA, and of total hip replacement (THR) or total knee replacement (TKR). The hip PRS and knee PRS contained 44 and 24 independent SNPs, respectively, and were derived from a recent genome-wide association study meta-analysis. Standardized PRS (with Z transformation) were used in all analyses. RESULTS: We found a stronger association of the PRS for clinically defined OA compared to radiographic OA phenotypes, and we observed the highest PRS risk stratification for TKR/THR. The odds ratio (OR) per SD was 1.3 for incident THR (95% confidence interval [95% CI] 1.1-1.5) and 1.6 (95% CI 1.3-1.9) for incident TKR in the Rotterdam Study. The knee PRS was associated with incident clinical knee OA in the CHECK study (OR 1.3 [95% CI 1.1-1.5]), but not for the PROOF study (OR 1.2 [95% CI 0.8-1.7]). The OR for OA increased gradually across the PRS distribution, up to 2.1 (95% CI 1.4-3.2) for individuals with the 10% highest PRS compared to the middle 50% of the PRS distribution. CONCLUSION: Our findings validated the association of PRS across OA definitions. Since OA is becoming frequent and primary prevention is not commonly applicable, PRS-based risk assessment could play a role in OA prevention. However, the utility of PRS is dependent on the setting. Further studies are needed to test the integration of genetic risk assessment in diverse health care settings.

WNT/beta-catenin signalling interrupts a senescence-induction cascade in human mesenchymal stem cells that restricts their expansion.

Senescence, the irreversible cell cycle arrest of damaged cells, is accompanied by a deleterious pro-inflammatory senescence-associated secretory phenotype (SASP). Senescence and the SASP are major factors in aging, cancer, and degenerative diseases, and interfere with the expansion of adult cells in vitro, yet little is known about how to counteract their induction and deleterious effects. Paracrine signals are increasingly recognized as important senescence triggers and understanding their regulation and mode of action may provide novel opportunities to reduce senescence-induced inflammation and improve cell-based therapies. Here, we show that the signalling protein WNT3A counteracts the induction of paracrine senescence in cultured human adult mesenchymal stem cells (MSCs). We find that entry into senescence in a small subpopulation of MSCs triggers a secretome that causes a feed-forward signalling cascade that with increasing speed induces healthy cells into senescence. WNT signals interrupt this cascade by repressing cytokines that mediate this induction of senescence. Inhibition of those mediators by interference with NF-κB or interleukin 6 signalling reduced paracrine senescence in absence of WNT3A and promoted the expansion of MSCs. Our work reveals how WNT signals can antagonize senescence and has relevance not only for expansion of adult cells but can also provide new insights into senescence-associated inflammatory and degenerative diseases.

Using multivariable Mendelian randomization to estimate the causal effect of bone mineral density on osteoarthritis risk, independently of body mass index.

OBJECTIVES: Observational analyses suggest that high bone mineral density (BMD) is a risk factor for osteoarthritis (OA); it is unclear whether this represents a causal effect or shared aetiology and whether these relationships are body mass index (BMI)-independent. We performed bidirectional Mendelian randomization (MR) to uncover the causal pathways between BMD, BMI and OA. METHODS: One-sample (1S)MR estimates were generated by two-stage least-squares regression. Unweighted allele scores instrumented each exposure. Two-sample (2S)MR estimates were generated using inverse-variance weighted random-effects meta-analysis. Multivariable MR (MVMR), including BMD and BMI instruments in the same model, determined the BMI-independent causal pathway from BMD to OA. Latent causal variable (LCV) analysis, using weight-adjusted femoral neck (FN)-BMD and hip/knee OA summary statistics, determined whether genetic correlation explained the causal effect of BMD on OA. RESULTS: 1SMR provided strong evidence for a causal effect of BMD estimated from heel ultrasound (eBMD) on hip and knee OA {odds ratio [OR]hip = 1.28 [95% confidence interval (CI) = 1.05, 1.57], p = 0.02, ORknee = 1.40 [95% CI = 1.20, 1.63], p = 3 × 10-5, OR per standard deviation [SD] increase}. 2SMR effect sizes were consistent in direction. Results suggested that the causal pathways between eBMD and OA were bidirectional (ßhip = 1.10 [95% CI = 0.36, 1.84], p = 0.003, ßknee = 4.16 [95% CI = 2.74, 5.57], p = 8 × 10-9, ß = SD increase per doubling in risk). MVMR identified a BMI-independent causal pathway between eBMD and hip/knee OA. LCV suggested that genetic correlation (i.e. shared genetic aetiology) did not fully explain the causal effects of BMD on hip/knee OA. CONCLUSIONS: These results provide evidence for a BMI-independent causal effect of eBMD on OA. Despite evidence of bidirectional effects, the effect of BMD on OA did not appear to be fully explained by shared genetic aetiology, suggesting a direct action of bone on joint deterioration.

Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations.

Osteoarthritis affects over 300 million people worldwide. Here, we conduct a genome-wide association study meta-analysis across 826,690 individuals (177,517 with osteoarthritis) and identify 100 independently associated risk variants across 11 osteoarthritis phenotypes, 52 of which have not been associated with the disease before. We report thumb and spine osteoarthritis risk variants and identify differences in genetic effects between weight-bearing and non-weight-bearing joints. We identify sex-specific and early age-at-onset osteoarthritis risk loci. We integrate functional genomics data from primary patient tissues (including articular cartilage, subchondral bone, and osteophytic cartilage) and identify high-confidence effector genes. We provide evidence for genetic correlation with phenotypes related to pain, the main disease symptom, and identify likely causal genes linked to neuronal processes. Our results provide insights into key molecular players in disease processes and highlight attractive drug targets to accelerate translation.

Vitamin K antagonist anticoagulant usage is associated with increased incidence and progression of osteoarthritis.

OBJECTIVES: Vitamin K is hypothesised to play a role in osteoarthritis (OA) pathogenesis through effects on vitamin K-dependent bone and cartilage proteins, and therefore may represent a modifiable risk factor. A genetic variant in a vitamin K-dependent protein that is an essential inhibitor for cartilage calcification, matrix Gla protein (MGP), was associated with an increased risk for OA. Vitamin K antagonist anticoagulants (VKAs), such as warfarin and acenocoumarol, act as anticoagulants through inhibition of vitamin K-dependent blood coagulation proteins. VKAs likely also affect the functioning of other vitamin K-dependent proteins such as MGP. METHODS: We investigated the effect of acenocoumarol usage on progression and incidence of radiographic OA in 3494 participants of the Rotterdam Study cohort. We also examined the effect of MGP and VKORC1 single nucleotide variants on this association. RESULTS: Acenocoumarol usage was associated with an increased risk of OA incidence and progression (OR=2.50, 95% CI=1.94-3.20), both for knee (OR=2.34, 95% CI=1.67-3.22) and hip OA (OR=2.74, 95% CI=1.82-4.11). Among acenocoumarol users, carriers of the high VKORC1(BB) expression haplotype together with the MGP OA risk allele (rs1800801-T) had an increased risk of OA incidence and progression (OR=4.18, 95% CI=2.69-6.50), while this relationship was not present in non-users of that group (OR=1.01, 95% CI=0.78-1.33). CONCLUSIONS: These findings support the importance of vitamin K and vitamin K-dependent proteins, as MGP, in the pathogenesis of OA. Additionally, these results may have direct implications for the clinical prevention of OA, supporting the consideration of direct oral anticoagulants in favour of VKAs.

Diversity, compositional and functional differences between gut microbiota of children and adults.

The gut microbiota has been shown to play diverse roles in human health and disease although the underlying mechanisms have not yet been fully elucidated. Large cohort studies can provide further understanding into inter-individual differences, with more precise characterization of the pathways by which the gut microbiota influences human physiology and disease processes. Here, we aimed to profile the stool microbiome of children and adults from two population-based cohort studies, comprising 2,111 children in the age-range of 9 to 12 years (the Generation R Study) and 1,427 adult individuals in the range of 46 to 88 years of age (the Rotterdam Study). For the two cohorts, 16S rRNA gene profile datasets derived from the Dutch population were generated. The comparison of the two cohorts showed that children had significantly lower gut microbiome diversity. Furthermore, we observed higher relative abundances of genus Bacteroides in children and higher relative abundances of genus Blautia in adults. Predicted functional metagenome analysis showed an overrepresentation of the glycan degradation pathways, riboflavin (vitamin B2), pyridoxine (vitamin B6) and folate (vitamin B9) biosynthesis pathways in children. In contrast, the gut microbiome of adults showed higher abundances of carbohydrate metabolism pathways, beta-lactam resistance, thiamine (vitamin B1) and pantothenic (vitamin B5) biosynthesis pathways. A predominance of catabolic pathways in children (valine, leucine and isoleucine degradation) as compared to biosynthetic pathways in adults (valine, leucine and isoleucine biosynthesis) suggests a functional microbiome switch to the latter in adult individuals. Overall, we identified compositional and functional differences in gut microbiome between children and adults in a population-based setting. These microbiome profiles can serve as reference for future studies on specific human disease susceptibility in childhood, adulthood and specific diseased populations.

Intestinal microbiome composition and its relation to joint pain and inflammation.

Macrophage-mediated inflammation is thought to have a causal role in osteoarthritis-related pain and severity, and has been suggested to be triggered by endotoxins produced by the gastrointestinal microbiome. Here we investigate the relationship between joint pain and the gastrointestinal microbiome composition, and osteoarthritis-related knee pain in the Rotterdam Study; a large population based cohort study. We show that abundance of Streptococcus species is associated with increased knee pain, which we validate by absolute quantification of Streptococcus species. In addition, we replicate these results in 867 Caucasian adults of the Lifelines-DEEP study. Finally we show evidence that this association is driven by local inflammation in the knee joint. Our results indicate the microbiome is a possible therapeutic target for osteoarthritis-related knee pain.

Publisher Correction: GWAS of bone size yields twelve loci that also affect height, BMD, osteoarthritis or fractures.

The original HTML version of this Article was updated shortly after publication to add links to the Peer Review file.In addition, affiliations 16 and 17 incorrectly read 'School of Medicine Sydney, University of Notre Dame Australia, Sydney, WA, 6160, Australia' and 'St Vincent's Clinical School, University of New South Wales Medicine, University of New South Wales, Sydney, NSW, 2052, Australia.' This has now been corrected in both the PDF and HTML versions of the Article.

GWAS of bone size yields twelve loci that also affect height, BMD, osteoarthritis or fractures.

Bone area is one measure of bone size that is easily derived from dual-energy X-ray absorptiometry (DXA) scans. In a GWA study of DXA bone area of the hip and lumbar spine (N ≥ 28,954), we find thirteen independent association signals at twelve loci that replicate in samples of European and East Asian descent (N = 13,608 - 21,277). Eight DXA area loci associate with osteoarthritis, including rs143384 in GDF5 and a missense variant in COL11A1 (rs3753841). The strongest DXA area association is with rs11614913[T] in the microRNA MIR196A2 gene that associates with lumbar spine area (P = 2.3 × 10-42, ß = -0.090) and confers risk of hip fracture (P = 1.0 × 10-8, OR = 1.11). We demonstrate that the risk allele is less efficient in repressing miR-196a-5p target genes. We also show that the DXA area measure contributes to the risk of hip fracture independent of bone density.

Role of Epigenomics in Bone and Cartilage Disease.

Phenotypic variation in skeletal traits and diseases is the product of genetic and environmental factors. Epigenetic mechanisms include information-containing factors, other than DNA sequence, that cause stable changes in gene expression and are maintained during cell divisions. They represent a link between environmental influences, genome features, and the resulting phenotype. The main epigenetic factors are DNA methylation, posttranslational changes of histones, and higher-order chromatin structure. Sometimes non-coding RNAs, such as microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), are also included in the broad term of epigenetic factors. There is rapidly expanding experimental evidence for a role of epigenetic factors in the differentiation of bone cells and the pathogenesis of skeletal disorders, such as osteoporosis and osteoarthritis. However, different from genetic factors, epigenetic signatures are cell- and tissue-specific and can change with time. Thus, elucidating their role has particular difficulties, especially in human studies. Nevertheless, epigenomewide association studies are beginning to disclose some disease-specific patterns that help to understand skeletal cell biology and may lead to development of new epigenetic-based biomarkers, as well as new drug targets useful for treating diffuse and localized disorders. Here we provide an overview and update of recent advances on the role of epigenomics in bone and cartilage diseases. © 2019 American Society for Bone and Mineral Research.

Genome-wide meta-analysis of 158,000 individuals of European ancestry identifies three loci associated with chronic back pain.

Back pain is the #1 cause of years lived with disability worldwide, yet surprisingly little is known regarding the biology underlying this symptom. We conducted a genome-wide association study (GWAS) meta-analysis of chronic back pain (CBP). Adults of European ancestry were included from 15 cohorts in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, and from the UK Biobank interim data release. CBP cases were defined as those reporting back pain present for ≥3-6 months; non-cases were included as comparisons ("controls"). Each cohort conducted genotyping using commercially available arrays followed by imputation. GWAS used logistic regression models with additive genetic effects, adjusting for age, sex, study-specific covariates, and population substructure. The threshold for genome-wide significance in the fixed-effect inverse-variance weighted meta-analysis was p<5×10(-8). Suggestive (p<5×10(-7)) and genome-wide significant (p<5×10(-8)) variants were carried forward for replication or further investigation in the remaining UK Biobank participants not included in the discovery sample. The discovery sample comprised 158,025 individuals, including 29,531 CBP cases. A genome-wide significant association was found for the intronic variant rs12310519 in SOX5 (OR 1.08, p = 7.2×10(-10)). This was subsequently replicated in 283,752 UK Biobank participants not included in the discovery sample, including 50,915 cases (OR 1.06, p = 5.3×10(-11)), and exceeded genome-wide significance in joint meta-analysis (OR 1.07, p = 4.5×10(-19)). We found suggestive associations at three other loci in the discovery sample, two of which exceeded genome-wide significance in joint meta-analysis: an intergenic variant, rs7833174, located between CCDC26 and GSDMC (OR 1.05, p = 4.4×10(-13)), and an intronic variant, rs4384683, in DCC (OR 0.97, p = 2.4×10(-10)). In this first reported meta-analysis of GWAS for CBP, we identified and replicated a genetic locus associated with CBP (SOX5). We also identified 2 other loci that reached genome-wide significance in a 2-stage joint meta-analysis (CCDC26/GSDMC and DCC).

Genome-wide association study identifies nine novel loci for 2D:4D finger ratio, a putative retrospective biomarker of testosterone exposure in utero.

The ratio of the length of the index finger to that of the ring finger (2D:4D) is sexually dimorphic and is commonly used as a non-invasive biomarker of prenatal androgen exposure. Most association studies of 2D:4D ratio with a diverse range of sex-specific traits have typically involved small sample sizes and have been difficult to replicate, raising questions around the utility and precise meaning of the measure. In the largest genome-wide association meta-analysis of 2D:4D ratio to date (N = 15 661, with replication N = 75 821), we identified 11 loci (9 novel) explaining 3.8% of the variance in mean 2D:4D ratio. We also found weak evidence for association (ß = 0.06; P = 0.02) between 2D:4D ratio and sensitivity to testosterone [length of the CAG microsatellite repeat in the androgen receptor (AR) gene] in females only. Furthermore, genetic variants associated with (adult) testosterone levels and/or sex hormone-binding globulin were not associated with 2D:4D ratio in our sample. Although we were unable to find strong evidence from our genetic study to support the hypothesis that 2D:4D ratio is a direct biomarker of prenatal exposure to androgens in healthy individuals, our findings do not explicitly exclude this possibility, and pathways involving testosterone may become apparent as the size of the discovery sample increases further. Our findings provide new insight into the underlying biology shaping 2D:4D variation in the general population.