Functional characterization of regulatory variants associated with maternal hyperglycemia

Duke University, Durham NC

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Abstract

Project Summary Maternal hyperglycemia and gestational diabetes mellitus (GDM) complicate 17% of pregnancies annually resulting in serious acute and lifelong perinatal outcomes for both mother and child. A genome-wide association study (GWAS) of 4,437 pregnant mothers established loci associated with gestational glycemic traits. Significant associations included those specific to pregnancy as well as several previously implicated with metabolic traits in non-gravid populations. The objective of this proposal is to quantify the effect of thousands of maternal hyperglycemia associated genetic variants on gene regulation. Our approach to meet this objective will use a population-scale high-throughput reporter assay to determine the effect of all variants in five maternal hyperglycemia GWA loci on gene regulation followed by targeted genome editing strategies and additional genomic assays. We have already completed targeted capture and sequencing of these regions for 835 mothers across four ancestries who exhibited metabolic phenotypes in the extreme deciles of their race group. My hypothesis is that both common and low frequency genetic variants in these regions contribute to maternal hyperglycemia and that the functional consequence of the causal variants will be altered gene expression. I will test that hypothesis in three specific aims. In Aim 1, I will use a high-throughput reporter approach developed by our lab to quantify the impact of putative enhancers and causal variants in maternal hyperglycemia loci on gene regulation. The advantage of assaying donor DNA directly is the ability to identify not only common, but also rare regulatory variants and relate them directly with phenotype. In Aim 2, I will map the long-range physical associations of enhancers to confirm their target genes. The outcome will be the first complete dissection of the three-dimensional cis-regulatory architecture of genomic loci implicated in a human metabolic disorder. In Aim 3, I will use CRISPR/Cas9-based genome and epigenome editing tools to functionally validate causal variants expected to perturb gene expression through altering enhancer activity. The expected outcomes are that I will identify the cis-regulatory framework driving maternal hyperglycemia and demonstrate a novel transferable GWAS screening methodology in a patient cohort. This will have immediate positive impacts on identifying mothers at risk for metabolic disease and new pathways for future studies.