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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 β = 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.

ObjectiveMinimum joint space width (mJSW) from 2-dimensional images 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 use them to (ii) examine causal effects of mJSW on hip osteoarthritis (HOA) risk.MethodsGWAS meta-analysis of hip mJSW derived from plain X-rays (four cohorts) or DXA (one cohort) 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.Results50,745 individuals were included in the meta-analysis. 42 SNPs, which mapped to 39 loci (35 novel), were identified. Mendelian randomisation (MR) revealed little evidence of a causal effect of mJSW on HOA (βIVW-0.01 [95% CI -0.19, 0.17]). 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.ConclusionsGWAS and MR analyses suggested one group of mJSW loci reduces 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 mJSW and HOA risk via a growth-related mechanism.

Background/Aims Radiographic hip osteoarthritis (rHOA) is traditionally defined on hip x-rays, using subjective methods such as Kellgren-Lawrence scoring. Associations between subjective rHOA measures and symptoms are inconsistent. Applying digital tools to high-resolution dual-energy X-ray absorptiometry (DXA) scans, we aimed to develop a novel semi-automated classifier for rHOA and evaluate the face validity of the classifier based on relationships with hip pain, hospital diagnosed OA (HES OA), and risk of total hip replacement (THR). Methods Using hip DXAs in UK Biobank, osteophyte grades 0-3 were assigned based on manually measured osteophyte area. Minimum joint space width (mJSW) was automatically measured using outline points placed by a machine learning-based algorithm and then used to categorise individuals into joint space narrowing (JSN) grades 0-3. Osteophyte and JSN grades were combined, using a novel system giving greater to weight to osteophytes, to categorise individuals into rHOA grades 0-4. Logistic regression giving odds ratios (OR) was used to examine associations between rHOA grade and hip pain, and HES OA. Cox proportional hazard models giving hazard ratios (HR) were used to examine associations between rHOA grade and subsequent THR. Our adjusted model included age, sex, height and weight as covariates. Results 40,340 individuals were included in the study (mean age 63.7 [range 44-82], 19294/21046 male/female). 32758 (81.2%) had rHOA grade 0, 4565 (11.3%) grade 1, 2317 (5.7%) grade 2, 543 (1.3%) grade 3, 157 (0.4%) grade 4, with all features of rHOA being more common in males than females. rHOA grades ≥2 were associated with all three clinical outcomes in both unadjusted and adjusted models, a clear dose-response relationship was seen with each increase in grade showing a large rise in OR/HRs (Table 1). Grade 4 rHOA was strongly predictive of THR (HR 57.70 [95%CI 38.08-87.44]). Conclusion We successfully applied a novel semi-automated classifier to over 40,000 individuals from UKB. The validity of our classifier was supported by the strong and progressive relationships observed between rHOA and hip pain, and HES OA and risk of THR. We conclude that hip DXAs provide a promising means of defining rHOA, with potential screening applications in the clinic. Disclosure B.G. Faber: None. R. Ebsim: None. F.R. Saunders: None. M. Frysz: None. C. Lindner: None. J.S. Gregory: None. R.M. Aspden: None. N.C. Harvey: None. G. Davey Smith: None. T. Cootes: None. J.H. Tobias: None.

Objective Conventional scoring methods for radiographic hip OA (rHOA) are subjective and show inconsistent relationships with clinical outcomes. To provide a more objective rHOA scoring method, we aimed to develop a semi-automated classifier based on DXA images and confirm its relationships with clinical outcomes. Methods Hip DXAs in UK Biobank (UKB) were marked up for osteophyte area from which acetabular, superior and inferior femoral head osteophyte grades were derived. Joint space narrowing (JSN) grade was obtained automatically from minimum joint space width (mJSW) measures. Clinical outcomes related to rHOA comprised hip pain, hospital diagnosed OA (HES OA) and total hip replacement. Logistic regression and Cox proportional hazard modelling were used to examine associations between overall rHOA grade (0–4; derived from combining osteophyte and JSN grades) and the clinical outcomes. Results A toal of 40 340 individuals were included in the study (mean age 63.7), of whom 81.2% had no evidence of rHOA, while 18.8% had grade ≥1 rHOA. Grade ≥1 osteophytes at each location and JSN were associated with hip pain, HES OA and total hip replacement. Associations with all three clinical outcomes increased progressively according to rHOA grade, with grade 4 rHOA and total hip replacement showing the strongest association [57.70 (38.08–87.44)]. Conclusions Our novel semi-automated tool provides a useful means for classifying rHOA on hip DXAs, given its strong and progressive relationships with clinical outcomes. These findings suggest DXA scanning can be used to classify rHOA in large DXA-based cohort studies supporting further research, with the future potential for population-based screening.

Introduction: Alpha angle (AA) is a widely used imaging measure of hip shape that is commonly used to define cam morphology, a bulging of the lateral aspect of the femoral head. Cam morphology has shown strong associations with hip osteoarthritis (OA) making the AA a clinically relevant measure. In both clinical practice and research studies, AA tends to be measured manually which can be inconsistent and time-consuming. Objective: We aimed to (i) develop an automated method of deriving AA from anterior-posterior dual-energy x-ray absorptiometry (DXA) scans; and (ii) validate this method against manual measures of AA. Methods: 6,807 individuals with left hip DXAs were selected from UK Biobank. Outline points were manually placed around the femoral head on 1,930 images before training a Random Forest-based algorithm to place the points on a further 4,877 images. An automatic method for calculating AA was written in Python 3 utilising these outline points. An iterative approach was taken to developing and validating the method, testing the automated measures against independent batches of manually measured images in sequential experiments. Results: Over the course of six experimental stages the concordance correlation coefficient, when comparing the automatic AA to manual measures of AA, improved from 0.28 [95% confidence interval 0.13-0.43] for the initial version to 0.88 [0.84-0.92] for the final version. The inter-rater kappa statistic comparing automatic versus manual measures of cam morphology, defined as AA ³≥60°, improved from 0.43 [80% agreement] for the initial version to 0.86 [94% agreement] for the final version. Conclusions: We have developed and validated an automated measure of AA from DXA scans, showing high agreement with manually measuring AA. The proposed method is available to the wider research community from Zenodo.

© 2018 The Authors. Journal of Bone and Mineral Research Published by Wiley Periodicals, Inc. We aimed to report the first genomewide association study (GWAS) meta-analysis of dual-energy X-ray absorptiometry (DXA)-derived hip shape, which is thought to be related to the risk of both hip osteoarthritis and hip fracture. Ten hip shape modes (HSMs) were derived by statistical shape modeling using SHAPE software, from hip DXA scans in the Avon Longitudinal Study of Parents and Children (ALSPAC; adult females), TwinsUK (mixed sex), Framingham Osteoporosis Study (FOS; mixed), Osteoporotic Fractures in Men study (MrOS), and Study of Osteoporotic Fractures (SOF; females) (total N = 15,934). Associations were adjusted for age, sex, and ancestry. Five genomewide significant (p < 5 × 10−9, adjusted for 10 independent outcomes) single-nucleotide polymorphisms (SNPs) were associated with HSM1, and three SNPs with HSM2. One SNP, in high linkage disequilibrium with rs2158915 associated with HSM1, was associated with HSM5 at genomewide significance. In a look-up of previous GWASs, three of the identified SNPs were associated with hip osteoarthritis, one with hip fracture, and five with height. Seven SNPs were within 200 kb of genes involved in endochondral bone formation, namely SOX9, PTHrP, RUNX1, NKX3-2, FGFR4, DICER1, and HHIP. The SNP adjacent to DICER1 also showed osteoblast cis-regulatory activity of GSC, in which mutations have previously been reported to cause hip dysplasia. For three of the lead SNPs, SNPs in high LD (r2 > 0.5) were identified, which intersected with open chromatin sites as detected by ATAC-seq performed on embryonic mouse proximal femora. In conclusion, we identified eight SNPs independently associated with hip shape, most of which were associated with height and/or mapped close to endochondral bone formation genes, consistent with a contribution of processes involved in limb growth to hip shape and pathological sequelae. These findings raise the possibility that genetic studies of hip shape might help in understanding potential pathways involved in hip osteoarthritis and hip fracture. © 2018 The Authors. Journal of Bone and Mineral Research Published by Wiley Periodicals, Inc.

Purpose of review To review recent findings concerning the observational relationship between hip shape and hip osteoarthritis (HOA) and their shared genetic influences, and the potential for clinical application.Recent findings Recent observational studies have strengthened the evidence that specific shape deformities, such as cam and acetabular dysplasia, are related to HOA. Statistical shape modelling has emerged as a method to measure hip shape holistically, with the added advantage that this can be applied to dual X-ray absorptiometry scan images. This has led to several additional aspects of hip shape variation being identified, such as a wider femoral neck and larger lesser trochanter, in association with HOA. Furthermore, this method has formed the basis of genetic studies identifying novel genetic influences on hip shape, several of which are shared with known genetic risk factors for HOA.Summary Shared genetic influences of hip shape and HOA raise the possibility that hip shape plays a casual role in the development of HOA, justifying preventive approaches aiming to combat these adverse consequences.

Objective To examine relationships between known osteoarthritis (OA) susceptibility loci and hip shape in a population-based cohort of perimenopausal women in order to investigate whether hip shape contributes to OA development. Methods Hip shape was measured, using statistical shape modeling, on dual x-ray absorptiometry scans of the hip from mothers in the Avon Longitudinal Study of Parents and Children (ALSPAC). The proximal femur and superior acetabulum were outlined, and independent hip shape modes were generated. In a subregional model, points were restricted to the acetabulum and superior femoral head. Associations between 11 OA-related single-nucleotide polymorphisms, identified by literature search, and shape modes were analyzed in a multivariate canonical correlation analysis. Results A total of 3,111 women (mean age 48 years) had genetic and hip shape data. The KLHDC5/PTHLH rs10492367 OA risk allele was associated with a wider upper femur in the whole shape model (P = 1 × 10-5 ). The DOT1L rs12982744 OA risk allele was associated with reduced superior joint space in the subregional shape model (P = 2 × 10-3 ). The COL11A1 rs4907986 OA risk allele was associated with lateral displacement of the femoral head relative to the acetabulum in the subregional shape model (P = 5 × 10-4 ). Regional association plots identified an additional COL11A1 locus in moderate linkage disequilibrium with rs4907986, which was more strongly associated with hip shape (rs10047217; P = 3 × 10-6 ). Colocalization analysis indicated sharing of genetic signals for hip shape and hip OA for the KLHDC5/PTHLH and COL11A1 loci. Conclusion Hip OA susceptibility loci were associated with shape in this study, suggesting that these loci (and potentially yet-to-be-identified hip OA loci) could contribute to hip OA in later life via perturbing biologic pathways that mediate morphology development.