Osteoarthritis: genetics and phenotypes in all their complexity

The genetic epidemiology of ostheoarthritis, using genome-wide association studies and other omics to elucidate teh pathology of this common joint disorder

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.</p

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.</p

Using multivariable Mendelian randomization to estimate the causal effect of bone mineral density on osteoarthritis risk, independent 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, OR(knee) = 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 (β(hip) = 1.10 [95% CI = 0.36, 1.84], p = 0.003, β(knee) = 4.16 [95% CI = 2.74, 5.57], p = 8 × 10(–9), β = 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

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-1β 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-1β release in PBMCs after stimulation. Co-localisation analysis showed that the GLIS3 locus was shared between LPS/BCP crystal-induced IL-1β 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.</p

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

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 sexspecific 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 (b=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

Genome-wide association and functional studies identify a role for matrix Gla protein in osteoarthritis of the hand

Objective Osteoarthritis (OA) is the most common form of arthritis and the leading cause of disability in the elderly. Of all the joints, genetic predisposition is strongest for OA of the hand; however, only few genetic risk loci for hand OA have been identified. Our aim was to identify novel genes associated with hand OA and examine the underlying mechanism. Methods We performed a genome-wide association study of a quantitative measure of hand OA in 12 784 individuals (discovery: 8743, replication: 4011). Genome-wide significant signals were followed up by analysing gene and allele-specific expression in a RNA sequencing dataset (n=96) of human articular cartilage. Results We found two significantly associated loci in the discovery set: at chr12 (p=3.5 × 10⁻¹⁰) near the matrix Gla protein (MGP) gene and at chr12 (p=6.1×10⁻⁹) near the CCDC91 gene. The DNA variant near the MGP gene was validated in three additional studies, which resulted in a highly significant association between the MGP variant and hand OA (rs4764133, Betameta=0.83, Pmeta=1.8*10⁻¹⁵). This variant is high linkage disequilibrium with a coding variant in MGP, a vitamin K-dependent inhibitor of cartilage calcification. Using RNA sequencing data from human primary cartilage tissue (n=96), we observed that the MGP RNA expression of the hand OA risk allele was significantly lowercompared with the MGP RNA expression of the reference allele (40.7%, p<5*10⁻¹⁶). Conclusions Our results indicate that the association between the MGP variant and increased risk for hand OA is caused by a lower expression of MGP, which may increase the burden of hand OA by decreased inhibition of cartilage calcification

Novel Genetic Variants for Cartilage Thickness and Hip Osteoarthritis

Osteoarthritis is one of the most frequent and disabling diseases of the elderly. Only few genetic variants have been identified for osteoarthritis, which is partly due to large phenotype heterogeneity. To reduce heterogeneity, we here examined cartilage thickness, one of the structural components of joint health. We conducted a genome-wide association study of minimal joint space width (mJSW), a proxy for cartilage thickness, in a discovery set of 13,013 participants from five different cohorts and replication in 8,227 individuals from seven independent cohorts. We identified five genome-wide significant (GWS, P≤5·0×10−8) SNPs annotated to four distinct loci. In addition, we found two additional loci that were significantly replicated, but results of combined meta-analysis fell just below the genome wide significance threshold. The four novel associated genetic loci were located in/near TGFA (rs2862851), PIK3R1 (rs10471753), SLBP/FGFR3 (rs2236995), and TREH/DDX6 (rs496547), while the other two (DOT1L and SUPT3H/RUNX2) were previously identified. A systematic prioritization for underlying causal genes was performed using diverse lines of evidence. Exome sequencing data (n = 2,050 individuals) indicated that there were no rare exonic variants that could explain the identified associations. In addition, TGFA, FGFR3 and PIK3R1 were differentially expressed in OA cartilage lesions versus non-lesioned cartilage in the same individuals. In conclusion, we identified four novel loci (TGFA, PIK3R1, FGFR3 and TREH) and confirmed two loci known to be associated with cartilage thickness.The identified associations were not caused by rare exonic variants. This is the first report linking TGFA to human OA, which may serve as a new target for future therapies