Genome-wide Association Clustering Meta-analysis in European and Chinese Datasets for Systemic Lupus Erythematosus identifies new genes

Abstract

AbstractGenome-wide association studies (GWAS) face multiple challenges in order to identify reliable susceptibility genes for complex disorders, such as Systemic lupus erythematosus (SLE). These include high false positivity due to number of SNPs genotyped, false negativity due to statistical corrections and the proportional signals problem. Association clustering methods, by reducing the testing burden, have increased power than single variant analysis. Here, OASIS, a locus-based test, and its novel statistic, the OASIS locus index (OLI), is applied to European (EU) and Chinese (Chi) SLE GWAS to identify common significant non-HLA, autosomal genes. Six SLE dbGAP GWAS datasets, 4 EU and 2 Chi involving 19,710 SLE cases and 30,876 controls were analyzed. OLI is defined as the product of maximum −logP at a locus with the ratio of actual to predicted number of significant SNPs and compared against the standard P-value using Box plots and Wilcoxon Signed Rank Test. OLI outperformed the standard P-value statistic in detecting true associations (Wilcoxon Signed Test Z= - 4.11, P<1×10−4). Top non-HLA significant loci, common in both ethnicities were 2q32.2 (STAT4, rs4274624, P=9.7×10−66), 1q25.3 (SMG7, rs41272536, P=3.5×10−52), 7q32.1 (IRF5, rs35000415, P=1.9×10−45), 8p23.1 (BLK, rs2736345, P=1.5×10−25) and 6q23.3 (TNFAIP3, rs5029937, P=4.4×10−24). Overall, OASIS identified 19 highly significant and 16 modestly significant (P>10−8) non-HLA SLE associated genes common to EU and Chi ethnicities. Interaction of these 35 genes elucidated important SLE pathways viz NOD, TLR, JAK-STAT and RIG-1. OASIS aims to advance GWAS by rapid and cost-effective identification of genes of modest significance for complex disorders.Key MessagesGWAS are challenged by risk genes of modest effect.OASIS, a clustering algorithm, can help identify genes of modest significance for complex disorders such SLE, rapidly and cost-effectively using publicly available GWAS datasets.This meta-analysis identified 35 genes common to both European and Chinese populations.Interaction of these genes identify major SLE pathways to be NOD, TLR, JAK-STAT and RIG-1.