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Panoutsopoulou, Kalliope; Thiagarajah, Shankar; Zengini, Eleni; Day-Williams, Aaron G; Ramos, Yolande Fm; Meessen, Jennifer Mta; Huetink, Kasper; Nelissen, Rob Ghh; Southam, Lorraine; Rayner, N William; Doherty, Michael; Meulenbelt, Ingrid; Zeggini, Eleftheria; Wilkinson, J Mark
Annals of the rheumatic diseases, 07/2017, Letnik: 76, Številka: 7Journal Article
Osteoarthritis (OA) has a strong genetic component but the success of previous genome-wide association studies (GWAS) has been restricted due to insufficient sample sizes and phenotype heterogeneity. Our aim was to examine the effect of clinically relevant endophenotyping according to site of maximal joint space narrowing (maxJSN) and bone remodelling response on GWAS signal detection in hip OA. A stratified GWAS meta-analysis was conducted in 2118 radiographically defined hip OA cases and 6500 population-based controls. Signals were followed up by analysing differential expression of proximal genes for bone remodelling endophenotypes in 33 pairs of macroscopically intact and OA-affected cartilage. We report suggestive evidence (p<5×10 ) of association at 6 variants with OA endophenotypes that would have been missed by using presence of hip OA as the disease end point. For example, in the analysis of hip OA cases with superior maxJSN versus cases with non-superior maxJSN we detected association with a variant in the gene (rs754106, p=1.49×10 , OR (95% CIs) 0.70 (0.61 to 0.80)). In the comparison of hypertrophic with non-hypertrophic OA the most significant variant was located between and (rs6766414, p=3.13×10 , OR (95% CIs) 1.45 (1.24 to 1.69)). Both of these associations were fully attenuated in non-stratified analyses of all hip OA cases versus population controls (p>0.05). was significantly upregulated in OA-affected versus intact cartilage, particularly in the analysis of hypertrophic and normotrophic compared with atrophic bone remodelling pattern (p=4.2×10 ). Our findings demonstrate that stratification of OA cases into more homogeneous endophenotypes can identify genes of potential functional importance otherwise obscured by disease heterogeneity.
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