Association studies of systemic lupus erythematosus (SLE) : from novel susceptibility loci to gene-gene interaction

Abstract

Systemic lupus erythematosus (SLE) is characterized as an autoimmune disorder with unclear etiology.

To identify the genetic effect of SLE, a genome wide association study (GWAS) and its further replication were conducted on SLE patients in Asian populations and ethnically matched controls. Before this study, most of the confirmed association loci were identified by GWAS studies in European populations. Apart from the established associations, we identified a SLE susceptible single nucleotide polymorphisms (SNP) located in ETS1 (rs1128334, P=2.3E-11, OR=1.29) in four different cohorts. This locus is probably an Asian-specific susceptibility locus since no Caucasian study has reported further validation in the last years. A new susceptibility variant in UHRF1BP1 (rs13205210, P=4.4E-09, OR=1.49) independent from the previously confirmed SNPs in Caucasian study was also confirmed to be associated with SLE in the Hong Kong Chinese population.

Meta-analysis was performed by introducing another Chinese Han GWAS data set from Anhui province, China. Three loci, TET3-DGUOK, CD80, DRAM1, were confirmed to be associated with SLE. Two loci with suggestive signals in Hong Kong GWAS and further replication were also confirmed by the meta-analysis: PTTG1-MiRNA146a, YDJC.

In order to identify the genetic effect for females who have predominant chance to suffer from SLE, X chromosome specific meta-analysis based on the Hong Kong and Anhui GWAS data and further replication study were performed by considering the difference between females and males. A signal in PRPS2, and three independent signals in the Xq28 were confirmed with the replication in three different cohorts by considering both females and males.

Gene-gene interactions were also investigated genome-widely in a hypothesis free manner based on the meta-analysis results. The further validation processes were preceeded based on each independent GWAS data set. Four pairswise interacting loci were found and cross validated by three methods including logistic regression and Multifactor Dimensionality Reduction (MDR) and information gain theory based on the Anhui GWAS data set. Further studies are still needed to better explain the real features of genetic epistasis and the potential biological roles.

By incorporating two GWAS from the same population, the population difference is efficiently avoided. Together with the putative gene-gene interactions, this study presents a comprehensive analysis based on the GWAS data conducted on SLE. It may shed new light on the disease mechanisms of SLE.