Evaluation of shared genetic aetiology between osteoarthritis and bone mineral density identifies SMAD3 as a novel osteoarthritis risk locus.

Osteoarthritis (OA) is a common complex disease with high public health burden and no curative therapy. High bone mineral density (BMD) is associated with an increased risk of developing OA, suggesting a shared underlying biology. Here, we performed the first systematic overlap analysis of OA and BMD on a genome wide scale. We used summary statistics from the GEFOS consortium for lumbar spine (n = 31,800) and femoral neck (n = 32,961) BMD, and from the arcOGEN consortium for three OA phenotypes (hip, ncases=3,498; knee, ncases=3,266; hip and/or knee, ncases=7,410; ncontrols=11,009). Performing LD score regression we found a significant genetic correlation between the combined OA phenotype (hip and/or knee) and lumbar spine BMD (rg=0.18, P = 2.23 × 10-2), which may be driven by the presence of spinal osteophytes. We identified 143 variants with evidence for cross-phenotype association which we took forward for replication in independent large-scale OA datasets, and subsequent meta-analysis with arcOGEN for a total sample size of up to 23,425 cases and 236,814 controls. We found robustly replicating evidence for association with OA at rs12901071 (OR 1.08 95% CI 1.05-1.11, Pmeta=3.12 × 10-10), an intronic variant in the SMAD3 gene, which is known to play a role in bone remodeling and cartilage maintenance. We were able to confirm expression of SMAD3 in intact and degraded cartilage of the knee and hip. Our findings provide the first systematic evaluation of pleiotropy between OA and BMD, highlight genes with biological relevance to both traits, and establish a robust new OA genetic risk locus at SMAD3.

Estimating an Individual's Probability of Revision Surgery After Knee Replacement: A Comparison of Modeling Approaches Using a National Data Set.

Tools that provide personalized risk prediction of outcomes after surgical procedures help patients make preference-based decisions among the available treatment options. However, it is unclear which modeling approach provides the most accurate risk estimation. We constructed and compared several parametric and nonparametric models for predicting prosthesis survivorship after knee replacement surgery for osteoarthritis. We used 430,455 patient-procedure episodes between April 2003 and September 2015 from the National Joint Registry for England, Wales, Northern Ireland, and the Isle of Man. The flexible parametric survival and random survival forest models most accurately captured the observed probability of remaining event-free. The concordance index for the flexible parametric model was the highest (0.705, 95% confidence interval (CI): 0.702, 0.707) for total knee replacement and was 0.639 (95% CI: 0.634, 0.643) for unicondylar knee replacement and 0.589 (95% CI: 0.586, 0.592) for patellofemoral replacement. The observed-to-predicted ratios for both the flexible parametric and the random survival forest approaches indicated that models tended to underestimate the risks for most risk groups. Our results show that the flexible parametric model has a better overall performance compared with other tested parametric methods and has better discrimination compared with the random survival forest approach.

Effect of denosumab on osteolytic lesion activity after total hip arthroplasty: a single-centre, randomised, double-blind, placebo-controlled, proof of concept trial.

BACKGROUND: Osteolysis causes recurrent pain and disability after total hip arthroplasty. We investigated the effect of the human monoclonal antibody denosumab on osteolytic lesion activity in patients undergoing revision total hip arthroplasty surgery to show the biological proof of concept for a non-surgical treatment for the disease. METHODS: We did a phase 2, randomised, double-blind, placebo-controlled, proof of concept superiority trial at Sheffield Teaching Hospitals, Sheffield, UK. Eligible patients aged 30 years or older and scheduled for revision surgery for symptomatic, radiographically confirmed osteolysis were randomly allocated (1:1) to subcutaneous denosumab (60 mg single-dose) or placebo by an independent pharmacist using a random number table. The primary outcome was the between-group difference in osteoclast number per mm of bone surface of biopsies taken from the osteolytic membrane-bone interface at surgery 8 weeks later, measured by quantitative histomorphometry in all patients who underwent revision surgery. Adverse events were analysed in all randomly assigned participants. This trial is registered with the EU Clinical Trials Register (EudraCT 2011-000541-20). FINDINGS: Between Dec 12, 2012, and June 24, 2018, 51 patients were assessed for eligibility, of whom 24 were randomly assigned to study treatment. Two patients had their revision surgery cancelled for unrelated reasons, leaving 22 patients (ten in the denosumab group) for analysis of the primary outcome. There were 83% fewer osteoclasts at the osteolysis membrane-bone interface in the denosumab versus the placebo group (median 0·05 per mm [IQR 0·11] vs 0·30 mm [0·40], p=0·011). No deaths or treatment-related serious adverse events occurred. Seven adverse events, including one severe adverse event, occurred in four (36%) of 11 patients in the denosumab group. In the placebo group ten adverse events, including three severe adverse events, occurred in five (38%) of 13 patients. INTERPRETATION: To our knowledge, this is the first clinical trial of an investigational drug for osteolysis that shows tissue-specific biological efficacy. These results justify the need for future trials that target earlier-stage disease to test for clinical efficacy in reducing the need for revision surgery. FUNDING: Amgen.

Homogeneity in prediction of survival probabilities for subcategories of hipprosthesis data: the Nordic Arthroplasty Register Association, 2000-2013.

Introduction: The four countries in the Nordic Arthroplasty Register Association (NARA) share geographic proximity, culture, and ethnicity. Pooling data from different sources in order to obtain higher precision and accuracy of survival-probability estimates is appealing. Nevertheless, survival probabilities of hip replacements vary between the countries. As such, risk prediction for individual patients within countries may be problematic if data are merged. In this study, our primary question was to address when data merging for estimating prosthesis survival in subcategories of patients is advantageous for survival prediction of individual patients, and at what sample sizes this may be advised. Methods: Patients undergoing total hip replacements for osteoarthritis between January 1, 2000 and December 31, 2013 in the four Nordic countries were studied. A total of 184,507 patients were stratified into 360 patient subcategories based on country, age-group, sex, fixation, head size, and articulation. For each patient category, we determined the sample size needed from a single country to obtain a more accurate and precise estimate of prosthesis-survival probability at 5 and 10 years compared to an estimate using data from all countries. The comparison was done using mean-square error. Results: We found large variations in the sample size needed, ranging from 40 to 2,060 hips, before an estimate from a single Nordic country was more accurate and precise than estimates based on the NARA data. Conclusion: Using pooled survival-probability estimates for individual risk prediction may be imprecise if there is heterogeneity in the pooled data sources. By applying mean-square error, we demonstrate that for small sample sizes, applying the larger NARA database may provide a more accurate and precise estimate; however, this effect is not consistent and varies with the characteristics of the subcategory.

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.

Regenerative medicine will make orthopaedic implants obsolete in our time Orthopaedic Research Society first annual meeting debate, San Diego, March 21st, 2017.

The mission of the Orthopaedic Research Society is to promote and advance musculoskeletal research worldwide. With this in mind, the Annual Meeting Program Committee sought to establish a debate as a key component of the meeting. Our purpose was to provoke discussion on topics that are core to our mission and to engage all constituencies within the society by examining questions of broad relevance. To this end, the topic "Regenerative medicine will make orthopaedic implants obsolete in our time" was selected as the title of the inaugural debate. The arguments for and against the motion are presented in this perspectives article. © 2018 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:2579-2585, 2018.

Genome-wide analyses using UK Biobank data provide insights into the genetic architecture of osteoarthritis.

Osteoarthritis is a common complex disease imposing a large public-health burden. Here, we performed a genome-wide association study for osteoarthritis, using data across 16.5 million variants from the UK Biobank resource. After performing replication and meta-analysis in up to 30,727 cases and 297,191 controls, we identified nine new osteoarthritis loci, in all of which the most likely causal variant was noncoding. For three loci, we detected association with biologically relevant radiographic endophenotypes, and in five signals we identified genes that were differentially expressed in degraded compared with intact articular cartilage from patients with osteoarthritis. We established causal effects on osteoarthritis for higher body mass index but not for triglyceride levels or genetic predisposition to type 2 diabetes.

Quantifying the characteristics of the acetabulum and proximal femur using a semi-automated hip morphology software programme (SHIPS).

BACKGROUND: Hip-joint shape is an important factor that affects an individual's risk of developing osteoarthritis (OA). However, validated tools to quantify these morphological characteristics on clinical plain radiographs are few. We developed a Matlab-based Semi-automated HIP Software programme (SHIPS) that measures 10 morphologic characteristics of the hip that are risk factors for OA using a plain digitised antero-posterior pelvic radiograph. In this study we validated the accuracy and repeatability of this freeware-tool. METHODS: Software accuracy was assessed using a test pelvic radiograph, and by repeated measurements of an AP-pelvic radiograph digitally recreated from pelvis computed-tomography images reformatted to create images rotated in 2-dimensions (2.5° increments, range -15° to +15°). Intra- and inter-observer repeatability was assessed using pelvic radiographs from 30 subjects analysed twice using the software by two readers, and expressed as coefficient of variation (CV). Clinical-repeatability was assessed by measuring sequential pelvic radiographs taken on the same day after re-positioning in 23 subjects. RESULTS: Software accuracy was within 0.1% for linear-ratios and 0.4° for angular-measurements. Changes in pelvic inclination and rotation of ±15° resulted in <14% change in linear-measurement ratios and <7° change in angular-measurements. The intra-observer CV was between 0.3 to 4.1%, and inter-observer CV 0.7 to 9.7% with the exception of horizontal-toit-externa (HTE, 14.6 and 24.2% respectively). Short-term clinical-repeatability varied from 0.4 to 6.1%, with the exception of HTE (37.4%). CONCLUSION: The software showed good accuracy and repeatability for measurement of most hip-joint morphologic risk factors for OA apart from HTE. This tool has particular value in studying large or retrospective datasets where cross-sectional imaging is not feasible or available.