Molecular Genetics of BAT Genes and SLE Risk

点击翻译按钮获取中文摘要

DESCRIPTION (provided by applicant): Systemic lupus erythematosus (SLE) is a prototypic, multisystem, autoimmune-mediated chronic inflammatory disease that primarily targets women of child-bearing age. It has a complex genetic basis and is caused by a complex interaction of environmental factors and multiple genetic susceptibility loci. There is compelling evidence for the involvement of the Major Histocompatibility Complex (MHC) locus on chromosome 6p21.3 in SLE ethiopathogenesis, as suggested initially by linkage and association studies and confirmed recently by genome-wide association studies (GWAS). Our follow-up work on the data from a recent GWAS indicates that BAT genes residing within MHC class III region are significantly and independently associated with SLE risk and lupus nephritis. Furthermore, there is extensive literature knowledge documenting the functional and clinical relevance of BAT genes, including their involvement in immune/inflammation responses, apoptosis, and SLE-related gene expression signature, and their association with rheumatoid arthritis and other immune/inflammatory diseases. Taking together, these observations provide a strong rationale to comprehensively examine the role of 4 BAT genes (BAT1, BAT2, BAT3, BAT4) in the ethiopathogenesis of SLE and related phenotypes. Clustering of functionally-related genes is the hallmark of the MHC locus and the GWAS data and/or published studies implicate that the BAT1-4 region harbors additional genes that are also relevant to SLE and related phenotypes. We will use a combination of resequencing, genotyping, and functional analysis techniques in conjunction with a variety of databases and bioinformatics tools in order to characterize the functional variants of the genes in the BAT1-4 region that influence the SLE risk. These genes will be resequenced in selected SLE cases and controls to catalogue both common and rare variation, followed by screening of common tag SNPs and rare variants in the entire discovery sample and replication of significant associations in two independent replication samples. A combination of bioinformatics tools, publicly available databases, and RNA experiments will be used to determine the functional relevance of significant variants. The data generated from this study is expected not only to increase our understanding about SLE-related disease mechanisms but also to shed light on other MHC-linked autoimmune diseases with overlapping pathology.