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BMJ Publishing Group, Annals of the Rheumatic Diseases, 6(72), p. 935-941, 2012

DOI: 10.1136/annrheumdis-2012-202081

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Evaluation of the genetic overlap between osteoarthritis with body mass index and height using genome-wide association scan data

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

ObjectivesObesity as measured by body mass index (BMI) is one of the major risk factors for osteoarthritis. In addition, genetic overlap has been reported between osteoarthritis and normal adult height variation. We investigated whether this relationship is due to a shared genetic aetiology on a genome-wide scale.MethodsWe compared genetic association summary statistics (effect size, p value) for BMI and height from the GIANT consortium genome-wide association study (GWAS) with genetic association summary statistics from the arcOGEN consortium osteoarthritis GWAS. Significance was evaluated by permutation. Replication of osteoarthritis association of the highlighted signals was investigated in an independent dataset. Phenotypic information of height and BMI was accounted for in a separate analysis using osteoarthritis-free controls.ResultsWe found significant overlap between osteoarthritis and height (p=3.3×10−5for signals with p≤0.05) when the GIANT and arcOGEN GWAS were compared. For signals with p≤0.001 we found 17 shared signals between osteoarthritis and height and four between osteoarthritis and BMI. However, only one of the height or BMI signals that had shown evidence of association with osteoarthritis in the arcOGEN GWAS was also associated with osteoarthritis in the independent dataset: rs12149832, within theFTOgene (combined p=2.3×10−5). As expected, this signal was attenuated when we adjusted for BMI.ConclusionsWe found a significant excess of shared signals between both osteoarthritis and height and osteoarthritis and BMI, suggestive of a common genetic aetiology. However, only one signal showed association with osteoarthritis when followed up in a new dataset.