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The Genetics of Osteoarthritis

Zengini, Eleni (2019) The Genetics of Osteoarthritis. PhD thesis, University of Sheffield.

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Abstract

Introduction: Osteoarthritis (OA) is the most prevalent musculoskeletal disease and a leading cause of disability worldwide. It affects 40% of individuals over the age of 70. The health economic burden of OA is rising, commensurate with longevity and obesity rates, and there is currently no curative therapy. The genetic component of OA is ~50% and previous genetic studies have identified associated polymorphisms, traversing hip, knee and hand OA with limited overlap. The heritability explained by these loci is relatively low. Aims: The aim of the work conducted in this thesis was to unravel the genetic component of OA by conducting a series of GWAS followed by additional analyses and by examining established OA loci in so far non-studied populations. Methods: Initially a knee OA GWAS in a Greek population is described. Further, GWAS were performed using genotype data across 16.5 million variants from UK Biobank, followed by gene-based and gene-set analyses. OA was defined based on both self-reported status and through linkage to Hospital Episode Statistics data, and on joint-specificity of disease (knee and/or hip OA). In silico replication and meta-analysis of promising signals was carried out in further cases and controls. Finally, a hip and/or knee OA GWAS was conducted in an independent Greek ethnic group. Results: Confirmatory evidence for previously reported OA risk loci was found in the Greek population datasets, while three loci showed suggestive evidence for association. The UK Biobank analyses identified nine novel OA loci, located within TGFA, ANXA3, PLEC, MAP2K6, JPH3, ZNF345, near SLC30A10, between MPB3B and EQTN and near LTN1 respectively. Most of these signals are common at frequency and reside in or near genes reported to be associated with skeletal and OA relevant phenotypes by functional and animal model studies. Gene and gene based analyses identified genes and biological processes associated with OA. Conclusions: My findings contribute to a better understanding of OA pathophysiology taking the number of established OA loci to twenty nine and pointing to novel biological insights. Larger sample sizes are required to detect reported and novel OA risk loci at genome wide significance in the Greek population. Going forward, large-scale whole genome sequencing studies of well-phenotyped individuals across diverse populations will capture the full allele frequency and variation type spectrum, and afford us further insights into the causes of this debilitating disease.

Item Type: Thesis (PhD)
Academic Units: The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > Medicine (Sheffield)
Identification Number/EthosID: uk.bl.ethos.772916
Depositing User: Mrs Eleni Zengini
Date Deposited: 15 Apr 2019 08:41
Last Modified: 25 Sep 2019 20:07
URI: http://etheses.whiterose.ac.uk/id/eprint/23634

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