Epigenome-Guided Causal Variant Discovery and Mechanisms

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PROJECT SUMMARY Systemic lupus erythematosus (SLE) is a prototypic autoimmune disease characterized by dysregulated interferon responses and loss of self-tolerance to cellular antigens, which result in inflammatory processes that ultimately lead to systemic end-organ damage. Despite decades of research, the underlying mechanisms driving the pathogenesis of SLE remain incompletely understood. Genome-wide association studies (GWAS) have identified over 100 SLE risk haplotypes carrying hundreds of SNPs with unknown functional importance in disease onset and progression. Distinguishing causal from non-causal SNPs, and thus translating genetic knowledge into actionable clinical knowledge has been a laborious, inefficient, and resource-intensive task. Our laboratory has developed a new approach to expedite the causal variant discovery process where we use the epigenome to identify likely causal variants on risk haplotypes. We do this by identifying epigenetic footprints of allelic imbalance at SNPs (“hQTLs”) in poised and active enhancers measured by ChIP- sequencing. Our approach is able to identify causal variants in the context of linkage disequilibrium and provides a priori evidence that the putative causal variant is functional by identifying allelic imbalance in the magnitude of histone marks. We also use 3D chromatin topology data to construct a molecular wiring diagram of interacting enhancers and promoters that contain hQTLs. Since these data leverage the epigenome distinct profiles in specific cells and cell states provide important contextual information about what cellular processes the epiQTL is most important in regulating. This resubmission of R01 AR073606 aims to 1) use an epigenome-guided approach to identify resting and stimulus-dependent hQTLs from primary B cells; 2) validate and confirm the allele-specific transcriptional regulation attributed to hQTLs using an orthogonal massively parallel reporter assay; and 3) determine how hQTLs modify gene expression and 3D chromatin organization of genes contained within regulatory networks of hQTLs using multiplex quantitative PCR and chromatin conformation capture (3C). We believe this project positions us at the leading edge of causal variant identification and risk haplotype functional characterization and will contribute to a better understanding of the connection between genotype and phenotype for human SLE and related autoimmune diseases.