Il10 Low-Frequency Variants in Behcet's Disease Patients Publisher Pubmed



Matos M^{1, 2} ; Xavier JM^{1, 2} ; Abrantes P^{1, 2} ; Sousa I^{1, 2} ; Rei N^{1, 2} ; Davatchi F³ ; Shahram F³ ; Jesus G⁴ ; Barcelos F⁵ ; Vedes J⁶ ; Salgado M⁷ ; Abdollahi BS³ ; Nadji A³ ; Moraesfontes MF^{2, 8} Show All Authors Show Affiliations
Source: International Journal of Rheumatic Diseases Published:2017

Abstract

Aim: To explain the missing heritability after the genome-wide association studies era, sequencing studies allow the identification of low-frequency variants with a stronger effect on disease risk. Common variants in the interleukin 10 gene (IL10) have been consistently associated with Behcet's disease (BD) and the goal of this study is to investigate the role of low-frequency IL10 variants in BD susceptibility. Methods: To identify IL10 low-frequency variants, a discovery group of 50 Portuguese BD patients were Sanger-sequenced in a 7.7 kb genomic region encompassing the complete IL10 gene, 0.9 kb upstream and 2 kb downstream, and two conserved regions in the putative promoter. To assess if the novel variants are BD- and/or Portuguese-specific, they were assayed in an additional group of BD patients (26 Portuguese and 964 Iranian) and controls (104 Portuguese and 823 Iranian). Results: Rare IL10 coding variants were not detected in BD patients, but we identified 28 known single nucleotide polymorphisms with minor allele frequencies ranging from 0.010 to 0.390, and five novel non-coding variants in five heterozygous cases. ss836185595, located in the IL10 3′ untranslated region, was also detected in one Iranian control individual and therefore is not specific to BD. The remaining novel IL10 variants (ss836185596 and ss836185602 in intron 3, ss836185598 and ss836185604 in the putative promoter region) were not found in the replication dataset. Conclusion: This study highlights the importance of screening the whole gene and regulatory regions when searching for novel variants associated with complex diseases, and the need to develop bioinformatics tools to predict the functional impact of non-coding variants and statistical tests which incorporate these predictions. © 2014 Asia Pacific League of Associations for Rheumatology and Wiley Publishing Asia Pty Ltd