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Localizing functional variants in SLE susceptibility genes

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Systemic lupus erythematosus (SLE or lupus) is a complex autoimmune disease characterized by a broad spectrum of clinical manifestations that arise from pathogenic autoantibody production. SLE disproportionately affects women and certain ethnic groups. Asians, African-Americans, and Hispanics show 3-5 fold higher prevalence and more severe clinical manifestations of SLE compared to European-Americans. Genetic factors strongly influence lupus development and progression, and genome-wide association studies (GWAS) have identified over 40 genetic associations for SLE susceptibility, mostly from the individuals with European ancestry. In order to understand the biological mechanisms that lead to disease sub-phenotypes in SLE, it is crucial to delineate the functional variants responsible for GWAS association signals. However, precisely delineating functional variants has been a major challenge, since associated variants from GWAS are often ''tags'' for haplotypes on which the actual functional variants reside. Our research team has acquired the experience, expertise, resources and infrastructure necessary to move beyond GWAS to accelerate discovery and characterization of the causal variants underlying these signals. We have successfully identified causal variants and their functional consequences in the ITGAM gene. We propose studying four SLE-susceptibility genes, IFIH1, ETS1, IKZF1, and PRDM1, that have been implicated in susceptibility to multiple autoimmune diseases, suggesting their broader roles in autoimmunity. Our primary goals are to define functional variants in these genes and explain their causal relationships with SLE and its clinical sub-phenotypes. In Aim 1 we will integrate our genotype and sequencing data from multi-ethnic cohorts with 1000 Genomes, while leveraging genetic differences between populations. These analyses will identify the most likely functional variants from our candidate genes, and elucidate genetic and clinical heterogeneity with SLE clinical sub-phenotypes. In Aim 2 we will predict and validate functional effects for candidate variants. We will first identify functional elements from ENCODE data, including protein coding sequence, transcriptional regulatory regions, attendant chromatin states, epigenetic marks, and eQTL signals. Bioinformatics and molecular modeling will guide follow-up experiments in primary and cultured cells to validate the functional effects of candidate variants on gene expression and protein function. Most of the data and samples for conducting this proposal are already available to us. With our integrated research strategy, cumulative expertise, strong track record, available biomaterials, resources and infrastructure, we have strong potential to successfully complete this project. We expect that this project will identify SLE-associated functional variants and define their effects on relevant biological pathways in order to elucidate the pathogenic mechanisms of lupus. Ultimately, this project could provide a basis for future therapeutic interventions for SLE and other autoimmune diseases influenced by these genes.
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