# Identifying Cis-Regulatory Variants, Genes, and Regulatory Networks Underlying QT Interval Variation > **NIH NIH R01** · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · 2024 · $534,335 ## Abstract PROJECT SUMMARY/ABSTRACT Electrocardiographic QT interval, an index of ventricular repolarization, is a clinically relevant heritable quantitative trait associated with risk for cardiac arrhythmias and sudden cardiac death (SCD). Genetic studies in subjects with rare Mendelian long- and short-QT syndromes have identified rare, severe coding mutations in ~20 genes encoding voltage-gated ion channels, transporters and associated proteins that regulate cardiac action potential duration (APD) or excitation-contraction (EC) coupling. Prevalence of coding polymorphisms in these genes affecting population repolarization variability is extremely low. In contrast, genome-wide association studies (GWAS) of QT interval in the general population have identified common, noncoding variants at nearly three dozen loci, collectively explaining ~20% of the additive variance. Nearly half of these GWAS loci harbor genes known to regulate cardiac APD or EC coupling, thus serving as the likely causal genes. Nonetheless, the identities of the actual causal genes and molecular mechanisms underlying associations with the common and, largely noncoding variants at these loci, remain unknown. Moreover, a large fraction (~80%) of the additive variance remains unidentified. Leveraging information on known genes, in the proposed studies we will address these gaps in our knowledge based on the hypotheses that a) multiple common variants that impact the activities of several cis-regulatory elements (CREs) underlie a GWAS signal by collectively influencing the expression of a target gene, and b) genes underlying specific or similar diseases/traits are often functionally related, and that functionally related genes often belong to gene regulatory networks (GRNs), members of which are co-regulated. We aim to functionally characterize selected QT interval GWAS loci with a priori evidence for likely causal genes as well as extend gene discovery by assessing the impacts of perturbing the expression of known QT interval genes on their GRNs. Our specific aims are: (1) identification of functional CRE variants at selected QT interval GWAS loci by evaluating all trait-associated common variants overlapping cardiac open chromatin regions in high-throughput reporter assays in mouse cardiomyocyte HL1 cells; and to link CREs and their variants to putative target genes based on expression quantitative trait locus and chromatin contact analyses in human adult left ventricle tissue and induced pluripotent stem cells-derived cardiomyocytes (hiPSC-CMs); and (2) performing CRISPR activation/interference-based expression perturbations of selected QT interval genes in neonatal rat ventricular myocytes (NRVMs), and assessing transcriptome-wide effects to identify candidate co-regulated gene sets; evaluating the co-regulated gene sets for enrichment in sub-threshold GWAS loci; overlapping co-regulated genes with QT GWAS loci to identify likely causal genes; and assessing the impact of perturbing expres... ## Key facts - **NIH application ID:** 10816474 - **Project number:** 5R01HL158901-03 - **Recipient organization:** UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON - **Principal Investigator:** Ashish Kapoor - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $534,335 - **Award type:** 5 - **Project period:** 2022-05-01 → 2026-04-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10816474 ## Citation > US National Institutes of Health, RePORTER application 10816474, Identifying Cis-Regulatory Variants, Genes, and Regulatory Networks Underlying QT Interval Variation (5R01HL158901-03). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10816474. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*