Evidence map›Paper›PMID 40421528›Full record

ArticleCirculation. Genomic and precision medicine2025

Identification and Functional Assessment of Candidate Causal

Supraja Kadagandla, Lavanya Gunamalai, Dongwon Lee, Ashish Kapoor

Abstract read
In one paragraph

Article in Circulation. Genomic and precision medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Supraja KadagandlaInstitute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston (S.K., L.G., A.K.).ORCID 0009-0009-3964-2047
Lavanya GunamalaiInstitute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston (S.K., L.G., A.K.).ORCID 0000-0002-6348-3359
Dongwon LeeDivision of Nephrology, Department of Pediatrics, Boston Children's Hospital and Harvard Medical School, MA (D.L.).ORCID 0000-0002-1568-2249
Ashish KapoorInstitute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston (S.K., L.G., A.K.).ORCID 0000-0003-3977-6140

Funding

Identifying Cis-Regulatory Variants, Genes, and Regulatory Networks Underlying QT Interval VariationR01HL158901 · NHLBI · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI KAPOOR, ASHISH · 2022 to 2025
$2.1M
NHLBI NIH HHS R01 HL158901
6 · The paper itself

Abstract

backgroundIdentifying causal variants among tens or hundreds of associated variants at each locus in genome-wide association studies is challenging. As the vast majority of genome-wide association studies variants are noncoding, sequence variation at

methodsCommon variants in high linkage disequilibrium with genome-wide significant variants were identified using variant call format tools. Genome-wide maps of cardiac putative CREs were generated by MACS2-based peak calling in human cardiac left ventricular DNase I sequencing and Assay for Transposase-Accessible Chromatin using sequencing data sets (

resultsAt a dozen genome-wide association studies loci, selected for higher effect sizes and better understanding of the likely causal genes, we identified all genome-wide significant variants (

conclusionsThese efforts have generated a comprehensive set of candidate causal variants expected to be enriched for

Indexed as

ElectrocardiographyGenome-Wide Association StudyRegulatory Sequences, Nucleic AcidAnimalsCell LineEnhancer Elements, GeneticHumansLinkage DisequilibriumMiceMyocytes, CardiacPolymorphism, Single NucleotideQuantitative Trait Locichromatinenhancer elements, geneticgene expression regulationgenetic variationgenome-wide association studylinkage disequilibriumquantitative trait loci

Identifiers

PMID40421528
PMCPMC12173768

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.