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The Genetic Epidemiology of Developmental Dysplasia of the Hip: A Genome-Wide Association Study Harnessing National Clinical Audit Data

By Konstantinos Hatzikotoulas, Andreas Roposch, Karan M. Shah, Matthew J Clark, Selina Bratherton, Vasanti Limbani, Julia Steinberg, Eleni Zengini, Kaltuun Warsame, Madhushika Ratnayake, Maria Tselepi, Jeremy Schwartzentruber, John Loughlin, Deborah M Eastwood, Eleftheria Zeggini, J Mark Wilkinson

Posted 24 Jun 2017
bioRxiv DOI: 10.1101/154013

Background: Developmental dysplasia of the hip (DDH) is a common, heritable condition characterised by abnormal formation of the hip joint, but has a poorly understood genetic architecture due to small sample sizes. We apply a novel case-ascertainment approach using national clinical audit (NCA) data to conduct the largest DDH genome-wide association study (GWAS) to date, and replicate our findings in independent cohorts. Methods: We used the English National Joint Registry (NJR) dataset to collect DNA and conducted a GWAS in 770 DDH cases and 3364 controls. We tested the variant most strongly associated with DDH in independent replication cohorts comprising 1129 patients and 4652 controls. Results: The heritable component of DDH attributable to common variants was 55% and distributed similarly across autosomal and the X-chromosomes. Variation within the GDF5 gene promoter was strongly and reproducibly associated with DDH (rs143384, OR 1.44 [95% CI 1.34-1.56], p=3.55x1022). Two further replicating loci showed suggestive association with DDH near NFIB (rs4740554, OR 1.30 [95% CI 1.16-1.45], p=4.44x10-6) and LOXL4 (rs4919218, 1.19 [1.10-1.28] p=4.38x10-6). Through gene-based enrichment we identify GDF5, UQCC1, MMP24, RETSAT and PDRG1 association with DDH (p<1.2x10-7). Using the UK Biobank and arcOGEN cohorts to generate polygenic risk scores we find that risk alleles for hip osteoarthritis explain <0.5% of the variance in DDH susceptibility. Conclusion: Using the NJR as a proof-of-principle, we describe the genetic architecture of DDH and identify several candidate intervention loci and demonstrate a scalable recruitment strategy for genetic studies that is transferrable to other complex diseases.

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