Evidence map›Paper›PMID 42523508›Full record

ArticlemedRxiv : the preprint server for health sciences2026

Multi-tissue analyses of allele-specific chromatin accessibility nominate likely functional variants for type 2 diabetes.

Narisu Narisu, Hannah X Li, Caleb J M Rathbun, Arushi Varshney, Amy J Swift, Tingfen Yan, Neelam Sinha, Kevin W Currin, Dongxiang Xue, Catherine C Robertson and 25 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing 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

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

35 authors.

Narisu NarisuCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA.ORCID 0000-0002-8483-1156
Hannah X LiCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Caleb J M RathbunCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Arushi VarshneyGilbert S. Omenn Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.ORCID 0000-0001-9177-9707
Amy J SwiftCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Tingfen YanCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Neelam SinhaCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA.ORCID 0000-0001-6496-224X
Kevin W CurrinDepartment of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA.
Dongxiang XueDepartment of Surgery, Center for Genomic Health, Weill Cornell Medicine, New York, NY 10065, USA.
Catherine C RobertsonCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA.
D Leland TaylorCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Henry J TaylorCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA.ORCID 0000-0003-2088-5240
Aimee BeckCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Brian N LeeCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA.ORCID 0000-0002-6090-4306
Li WangDepartment of Biology, Johns Hopkins University, Baltimore, MD 21218, USA.
K Alaine BroadawayDepartment of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA.
Emma P WilsonDepartment of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA.
Heather StringhamDepartment of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA.
Jouko SaramiesSouth Karelia Social and Health Care District, Wellbeing Services County of South Karelia, Finland.
Timo A LakkaInstitute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio, Finland.
Cassandra N SpracklenDepartment of Biostatistics and Epidemiology, University of Massachusetts Amherst, Amherst, MA 01003, USA.ORCID 0000-0003-3590-7182
Laura J ScottDepartment of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA.
Michael L StitzelThe Jackson Laboratory for Genomic Medicine, Farmington, CT, USA.
Jaakko TuomilehtoFinnish Institute for Health and Welfare, Helsinki, Finland.
Markku LaaksoInstitute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland.
Heikki A KoistinenFinnish Institute for Health and Welfare, Helsinki, Finland.
Michael BoehnkeDepartment of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA.
H Efsun ArdaLaboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.ORCID 0000-0002-5294-2521
Shuibing ChenDepartment of Surgery, Center for Genomic Health, Weill Cornell Medicine, New York, NY 10065, USA.
Leslie G BieseckerCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Lori L BonnycastleCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Michael R ErdosCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Karen L MohlkeDepartment of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA.
Stephen C J ParkerGilbert S. Omenn Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
Francis S CollinsCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA.

Funding

Genetic analysis of type II diabetes in Finnish populationZIAHG000024 · NHGRI · NATIONAL HUMAN GENOME RESEARCH INSTITUTE · PI ERDOS, MICHAEL · 2009 to 2025
$38.2M
Identifying Genes for Type 2 Diabetes: FUSIONU01DK062370 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BOEHNKE, MICHAEL L, SCOTT, LAURA J. · 2009 to 2021
$11.6M
Targeted Genetic Analysis of T2D and Quantitative TraitsR01DK072193 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI KAREN L. MOHLKE · 2005 to 2026
$11.3M
Identification of genomic regulatory elements in pancreas cellsZIABC011798 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI ARDA, HATICE · 2018 to 2025
$10.5M
Identifying Genes for Type 2 Diabetes:FUSIONR01DK062370 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BOEHNKE, MICHAEL L, SCOTT, LAURA J. · 2003 to 2025
$6.7M
Resources to interpret genetic signals and multi-tissue mechanisms for type 2 diabetes and related traitsRC2DK144819 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Melina C Claussnitzer, Anna Louise Gloyn · 2025 to 2026
$3.2M
Identifying Genes for Type 2 Diabetes: FUSIONR56DK062370 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BOEHNKE, MICHAEL L · 2008 to 2008
$500k
Intramural NIH HHS ZIA BC011798Intramural NIH HHS ZIA HG000024NIDDK NIH HHS R01 DK062370NIDDK NIH HHS R01 DK072193NIDDK NIH HHS R56 DK062370NIDDK NIH HHS RC2 DK144819NIDDK NIH HHS U01 DK062370
6 · The paper itself

Abstract

Genome-wide association studies (GWAS) have identified >1,200 signals associated with type 2 diabetes (T2D), yet identifying functional variants remains challenging because the majority of them lie in noncoding regions of the genome and are in areas of high linkage disequilibrium (LD). While chromatin accessibility QTL (caQTL) and expression QTL (eQTL) analyses are useful for nominating regulatory mechanisms underlying GWAS signals, limitations still exist in pinpointing functional variants within regions of high LD. A complementary approach that has been less frequently applied is to focus on the allele-specific effect on chromatin accessibility at heterozygous single-nucleotide polymorphisms (SNPs), hereafter referred to as "allelic imbalance". We analyzed the allelic imbalance of reads generated from an assay for transposase-accessible chromatin with sequencing (ATAC-seq) across genotyped samples from 490 donors in T2D-relevant tissues: skeletal muscle, liver, pancreatic islets, adipose tissue, and relevant cell types. We identified 119,949 allelically imbalanced SNPs (FDR<0.05) across the genome. The allelic imbalance was often most prominent in one tissue and showed an enrichment overlapping with tissue-specific transcription factor (TF) binding footprints. Focusing on the 8,581 SNPs in previously published 99% credible sets from 338 T2D GWAS signals, we identified 256 imbalanced SNPs across 123 (36.4% of) signals, each showing allelic imbalance in at least one tissue or cell type. Of these, 71 signals contained only a single imbalanced SNP, representing excellent candidate causative variants. As a proof-of-concept, we showed that 23 of the 256 imbalanced SNPs were supported by allelic assays from previous studies. Further, we experimentally validated two imbalanced SNPs as likely functional variants: rs34584161 among a seven-SNP T2D credible set at the

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PMID42523508
PMCPMC13405542

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