# Targeted Genetic Analysis of T2D and Quantitative Traits

> **NIH NIH R01** · UNIV OF NORTH CAROLINA CHAPEL HILL · 2022 · $617,198

## Abstract

PROJECT SUMMARY
Type 2 diabetes (T2D) is a major cause of morbidity and mortality in the USA and worldwide. Identification of
genes increasing susceptibility to T2D would substantially improve public health by providing biological and
clinical data about development and treatment of T2D and by advising lifestyle changes in at-risk individuals.
Our overall goal is to identify the functional variants, target genes, and mechanisms responsible for T2D and
diabetes-related quantitative trait (QT) association signals. Previously, we have identified hundreds of novel loci
for T2D and QTs by leading and contributing to genome-wide association study (GWAS) analyses and meta-
analyses. To examine loci, we identified candidate genes and developed and applied methods to predict
regulatory variants. We used experimental manipulation, including regulatory variant assays and genome editing,
to identify mechanisms by which variant alleles bind transcriptional regulators and increase or decrease
expression of specific target genes and alter traits such as insulin secretion. In this proposal, we seek to extend
these successes to additional T2D and QT loci. We will study the two key and complementary aspects of T2D
pathogenesis, insulin resistance and insulin secretion, by focusing on association signals that (1) affect gene
regulation in the liver, or (2) act through insulin processing in pancreatic islets. Specifically, we will map liver
transcriptional regulatory elements using chromatin accessibility data in hundreds of samples, identify chromatin
accessibility quantitative trait loci (caQTL), perform multi-omic integration to identify variants and genes that
affect T2D risk and QT variability, and assess the function of variants and genes using high throughput
transcriptional reporter assays, genome editing, and assays of liver gene function. We will identify genetic
variants and target genes that alter insulin processing and secretion by integration of known and new proinsulin
GWAS loci with pancreatic islet multi-omic data, characterize mechanistic pathways, and assess the function of
candidate variants and genes using regulatory assays, genome editing, and assays of insulin and proinsulin
secretion. To accelerate advances in T2D genetics including cross-tissue analyses, we will share data via T2D
web portals. Successful completion of this work will translate T2D association signals into biological insights and
potential therapeutic targets. We will identify risk variants, the mechanisms by which they affect gene function,
and their pathological effects on disease processes, guiding studies that evaluate novel therapies and intervene
in at-risk individuals to prevent disease.

## Key facts

- **NIH application ID:** 10435580
- **Project number:** 5R01DK072193-16
- **Recipient organization:** UNIV OF NORTH CAROLINA CHAPEL HILL
- **Principal Investigator:** KAREN L. MOHLKE
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $617,198
- **Award type:** 5
- **Project period:** 2005-09-01 → 2025-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10435580

## Citation

> US National Institutes of Health, RePORTER application 10435580, Targeted Genetic Analysis of T2D and Quantitative Traits (5R01DK072193-16). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10435580. Licensed CC0.

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