A Genome-Wide Association Study and Rare Variant Analysis for Dupuytren Disease in a North American Population.

Abstract

Although European genome-wide association studies (GWAS) have aided in defining genetic associations in Dupuytren disease (DD), North American populations have been infrequently analyzed. Additionally, there are a paucity of rare variant analyses (RVA) for DD, which can help define both trait variability and risk for low-frequency variants. Our purpose was to perform a GWAS and RVA for DD using a North American database. The study cohort (cases and controls) consisted of patients from our institutional MyCode Community Health Initiative, an unselected clinical cohort. A GWAS was performed controlling for age, sex and body mass index. For the RVA, sequence kernel association test analysis was performed on the most significant genes from the GWAS. Sequence kernel association test is a regression method to test associations between common and rare genetic variants in a defined region and a specific trait while adjusting for covariates. A total of 1,123 DD cases and 130,822 controls were included. DD cases were significantly older, more likely to be male, and had higher body mass indices. The GWAS yielded variants in two genes with a statistically significant difference between cases and controls: WNT7B and EPDR1. WNT7B variants rs9330811 (odds ratio, 1.96; 95% confidence interval, 1.73-2.23) and rs10448585 (odds ratio, 1.68; 95% confidence interval, 1.44-1.96) were the top hits. Variant rs2122625 in EPDR1 also reached genome-wide significance. The RVA indicated that WNT7B, DUXA, LOXL1, CSMD2, and TACC2 were significantly associated with a diagnosis of DD. In our North American population, GWAS yielded variants in two genes that were significantly associated with DD (WNT7B and EPDR), which likely contribute to abnormal proliferation of fibroblasts. Five rare variants (WNT7B, DUXA, LOXL1, CSMD2, and TACC2) were also significantly associated with DD. As disease-modifying treatments are explored, these data add to a growing body of literature defining genetic variants in DD.