The genetic contribution to severe post-traumatic osteoarthritis

Objective: to compare the combined role of genetic variants loci associated with risk of knee or hip osteoarthritis (OA) in post-traumatic (PT) and non-traumatic (NT) cases of clinically severe OA leading to total joint replacement. Methods: A total of 1590 controls, 2168 total knee replacement (TKR) cases (33.2% PT) and 1567 total hip replacement (THR) cases (8.7% PT) from 2 UK cohorts were genotyped for 12 variants previously reported to be reproducibly associated with risk of knee or hip OA. A genetic risk score was generated and the association with PT and NT TKR and THR was assessed adjusting for covariates. Results: For THR, each additional genetic risk variant conferred lower risk among PT cases (OR=1.07, 95% CI 0.96 to 1.19; p=0.24) than NT cases (OR 1.11, 95% CI 1.06 to 1.17; p=1.55×10−5). In contrast, for TKR, each risk variant conferred slightly higher risk among PT cases (OR 1.12, 95% CI 1.07 to 1.19; p=1.82×10−5) than among NT cases (OR 1.08, 95% CI 1.03 to 1.1; p=0.00063). Conclusions: Based on the variants reported to date PT TKR cases have at least as high a genetic contribution as NT cases

Investigation of Association Between Hip Osteoarthritis Susceptibility Loci and Radiographic Proximal Femur Shape

Objective: To test whether previously reported hip morphology or osteoarthritis (OA) susceptibility loci are associated with proximal femur shape as represented by statistical shape model (SSM) modes and as univariate or multivariate quantitative traits. Methods: We used pelvic radiographs and genotype data from 929 subjects with unilateral hip OA who had been recruited previously for the Arthritis Research UK Osteoarthritis Genetics Consortium genome-wide association study. We built 3 SSMs capturing the shape variation of the OA-unaffected proximal femur in the entire mixed-sex cohort and for male/female-stratified cohorts. We selected 41 candidate single-nucleotide polymorphisms (SNPs) previously reported as being associated with hip morphology (for replication analysis) or OA (for discovery analysis) and for which genotype data were available. We performed 2 types of analysis for genotype–phenotype associations between these SNPs and the modes of the SSMs: 1) a univariate analysis using individual SSM modes and 2) a multivariate analysis using combinations of SSM modes. Results: The univariate analysis identified association between rs4836732 (within the ASTN2 gene) and mode 5 of the female SSM (P = 0.0016) and between rs6976 (within the GLT8D1 gene) and mode 7 of the mixed-sex SSM (P = 0.0003). The multivariate analysis identified association between rs5009270 (near the IFRD1 gene) and a combination of modes 3, 4, and 9 of the mixed-sex SSM (P = 0.0004). Evidence of associations remained significant following adjustment for multiple testing. All 3 SNPs had previously been associated with hip OA. Conclusion: These de novo findings suggest that rs4836732, rs6976, and rs5009270 may contribute to hip OA susceptibility by altering proximal femur shape

A novel variant in GLIS3 is associated with osteoarthritis

Objectives Osteoarthritis (OA) is a complex disease, but its genetic aetiology remains poorly characterised. To identify novel susceptibility loci for OA, we carried out a genome-wide association study (GWAS) in individuals from the largest UK-based OA collections to date. Methods We carried out a discovery GWAS in 5414 OA individuals with knee and/or hip total joint replacement (TJR) and 9939 population-based controls. We followed-up prioritised variants in OA subjects from the interim release of the UK Biobank resource (up to 12 658 cases and 50 898 controls) and our lead finding in operated OA subjects from the full release of UK Biobank (17 894 cases and 89 470 controls). We investigated its functional implications in methylation, gene expression and proteomics data in primary chondrocytes from 12 pairs of intact and degraded cartilage samples from patients undergoing TJR. Results We detect a genome-wide significant association at rs10116772 with TJR (P=3.7×10−8; for allele A: OR (95% CI) 0.97 (0.96 to 0.98)), an intronic variant in GLIS3, which is expressed in cartilage. Variants in strong correlation with rs10116772 have been associated with elevated plasma glucose levels and diabetes. Conclusions We identify a novel susceptibility locus for OA that has been previously implicated in diabetes and glycaemic traits

Development of a fully automatic shape model matching (FASMM) system to derive statistical shape models from radiographs: application to the accurate capture and global representation of proximal femur shape

SummaryObjectiveTo evaluate the accuracy and sensitivity of a fully automatic shape model matching (FASMM) system to derive statistical shape models (SSMs) of the proximal femur from non-standardised anteroposterior (AP) pelvic radiographs.DesignAP pelvic radiographs obtained with informed consent and appropriate ethical approval were available for 1105 subjects with unilateral hip osteoarthritis (OA) who had been recruited previously for The arcOGEN Study. The FASMM system was applied to capture the shape of the unaffected (i.e., without signs of radiographic OA) proximal femur from these radiographs. The accuracy and sensitivity of the FASMM system in calculating geometric measurements of the proximal femur and in shape representation were evaluated relative to validated manual methods.ResultsDe novo application of the FASMM system had a mean point-to-curve error of less than 0.9 mm in 99% of images (n = 266). Geometric measurements generated by the FASMM system were as accurate as those obtained manually. The analysis of the SSMs generated by the FASMM system for male and female subject groups identified more significant differences (in five of 17 SSM modes after Bonferroni adjustment) in their global proximal femur shape than those obtained from the analysis of conventional geometric measurements. Multivariate gender-classification accuracy was higher when using SSM mode values (76.3%) than when using conventional hip geometric measurements (71.8%).ConclusionsThe FASMM system rapidly and accurately generates a global SSM of the proximal femur from radiographs of varying quality and resolution. This system will facilitate complex morphometric analysis of global shape variation across large datasets. The FASMM system could be adapted to generate SSMs from the radiographs of other skeletal structures such as the hand, knee or pelvis

A Bayesian Approach to the Overlap Analysis of Epidemiologically Linked Traits.

Diseases often cooccur in individuals more often than expected by chance, and may be explained by shared underlying genetic etiology. A common approach to genetic overlap analyses is to use summary genome-wide association study data to identify single-nucleotide polymorphisms (SNPs) that are associated with multiple traits at a selected P-value threshold. However, P-values do not account for differences in power, whereas Bayes' factors (BFs) do, and may be approximated using summary statistics. We use simulation studies to compare the power of frequentist and Bayesian approaches with overlap analyses, and to decide on appropriate thresholds for comparison between the two methods. It is empirically illustrated that BFs have the advantage over P-values of a decreasing type I error rate as study size increases for single-disease associations. Consequently, the overlap analysis of traits from different-sized studies encounters issues in fair P-value threshold selection, whereas BFs are adjusted automatically. Extensive simulations show that Bayesian overlap analyses tend to have higher power than those that assess association strength with P-values, particularly in low-power scenarios. Calibration tables between BFs and P-values are provided for a range of sample sizes, as well as an approximation approach for sample sizes that are not in the calibration table. Although P-values are sometimes thought more intuitive, these tables assist in removing the opaqueness of Bayesian thresholds and may also be used in the selection of a BF threshold to meet a certain type I error rate. An application of our methods is used to identify variants associated with both obesity and osteoarthritis

Genome‐Wide DNA Methylation Study Identifies Significant Epigenomic Changes in Osteoarthritic Cartilage

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/108665/1/art38762.pd

Evaluation of the genetic overlap between osteoarthritis with body mass index and height using genome-wide association scan data.

OBJECTIVES: Obesity as measured by body mass index (BMI) is one of the major risk factors for osteoarthritis. In addition, genetic overlap has been reported between osteoarthritis and normal adult height variation. We investigated whether this relationship is due to a shared genetic aetiology on a genome-wide scale. METHODS: We compared genetic association summary statistics (effect size, p value) for BMI and height from the GIANT consortium genome-wide association study (GWAS) with genetic association summary statistics from the arcOGEN consortium osteoarthritis GWAS. Significance was evaluated by permutation. Replication of osteoarthritis association of the highlighted signals was investigated in an independent dataset. Phenotypic information of height and BMI was accounted for in a separate analysis using osteoarthritis-free controls. RESULTS: We found significant overlap between osteoarthritis and height (p=3.3×10(-5) for signals with p≤0.05) when the GIANT and arcOGEN GWAS were compared. For signals with p≤0.001 we found 17 shared signals between osteoarthritis and height and four between osteoarthritis and BMI. However, only one of the height or BMI signals that had shown evidence of association with osteoarthritis in the arcOGEN GWAS was also associated with osteoarthritis in the independent dataset: rs12149832, within the FTO gene (combined p=2.3×10(-5)). As expected, this signal was attenuated when we adjusted for BMI. CONCLUSIONS: We found a significant excess of shared signals between both osteoarthritis and height and osteoarthritis and BMI, suggestive of a common genetic aetiology. However, only one signal showed association with osteoarthritis when followed up in a new dataset

Identification of new therapeutic targets for osteoarthritis through genome-wide analyses of UK Biobank data

Osteoarthritis is the most common musculoskeletal disease and the leading cause of disability globally. Here, we performed a genome-wide association study for osteoarthritis (77,052 cases and 378,169 controls), analyzing four phenotypes: knee osteoarthritis, hip osteoarthritis, knee and/or hip osteoarthritis, and any osteoarthritis. We discovered 64 signals, 52 of them novel, more than doubling the number of established disease loci. Six signals fine-mapped to a single variant. We identified putative effector genes by integrating expression quantitative trait loci (eQTL) colocalization, fine-mapping, and human rare-disease, animal-model, and osteoarthritis tissue expression data. We found enrichment for genes underlying monogenic forms of bone development diseases, and for the collagen formation and extracellular matrix organization biological pathways. Ten of the likely effector genes, including TGFB1 (transforming growth factor beta 1), FGF18 (fibroblast growth factor 18), CTSK (cathepsin K), and IL11 (interleukin 11), have therapeutics approved or in clinical trials, with mechanisms of action supportive of evaluation for efficacy in osteoarthritis

Identification of new susceptibility loci for osteoarthritis (arcOGEN):a genome-wide association study

To access publisher's full text version of this article. Please click on the hyperlink in Additional Links field.Osteoarthritis is the most common form of arthritis worldwide and is a major cause of pain and disability in elderly people. The health economic burden of osteoarthritis is increasing commensurate with obesity prevalence and longevity. Osteoarthritis has a strong genetic component but the success of previous genetic studies has been restricted due to insufficient sample sizes and phenotype heterogeneity. We undertook a large genome-wide association study (GWAS) in 7410 unrelated and retrospectively and prospectively selected patients with severe osteoarthritis in the arcOGEN study, 80% of whom had undergone total joint replacement, and 11,009 unrelated controls from the UK. We replicated the most promising signals in an independent set of up to 7473 cases and 42,938 controls, from studies in Iceland, Estonia, the Netherlands, and the UK. All patients and controls were of European descent. We identified five genome-wide significant loci (binomial test p≤5·0×10(-8)) for association with osteoarthritis and three loci just below this threshold. The strongest association was on chromosome 3 with rs6976 (odds ratio 1·12 [95% CI 1·08-1·16]; p=7·24×10(-11)), which is in perfect linkage disequilibrium with rs11177. This SNP encodes a missense polymorphism within the nucleostemin-encoding gene GNL3. Levels of nucleostemin were raised in chondrocytes from patients with osteoarthritis in functional studies. Other significant loci were on chromosome 9 close to ASTN2, chromosome 6 between FILIP1 and SENP6, chromosome 12 close to KLHDC5 and PTHLH, and in another region of chromosome 12 close to CHST11. One of the signals close to genome-wide significance was within the FTO gene, which is involved in regulation of bodyweight-a strong risk factor for osteoarthritis. All risk variants were common in frequency and exerted small effects. Our findings provide insight into the genetics of arthritis and identify new pathways that might be amenable to future therapeutic intervention.Arthritis Research UK 1803

No evidence of an association between mitochondrial DNA variants and osteoarthritis in 7393 cases and 5122 controls.

OBJECTIVES: Osteoarthritis (OA) has a complex aetiology with a strong genetic component. Genome-wide association studies implicate several nuclear genes in the aetiology, but a major component of the heritability has yet to be defined at the molecular level. Initial studies implicate maternally inherited variants of mitochondrial DNA (mtDNA) in subgroups of patients with OA based on gender and specific joint involvement, but these findings have not been replicated. METHODS: The authors studied 138 maternally inherited mtDNA variants genotyped in a two cohort genetic association study across a total of 7393 OA cases from the arcOGEN consortium and 5122 controls genotyped in the Wellcome Trust Case Control consortium 2 study. RESULTS: Following data quality control we examined 48 mtDNA variants that were common in cohort 1 and cohort 2, and found no association with OA. None of the phenotypic subgroups previously associated with mtDNA haplogroups were associated in this study. CONCLUSIONS: We were not able to replicate previously published findings in the largest mtDNA association study to date. The evidence linking OA to mtDNA is not compelling at present