Evidence map›Paper›PMID 40961947›Full record

ArticleCell genomics2025

Identification of novel type 1 and type 2 diabetes genes by co-localization of human islet eQTL and GWAS variants with colocRedRibbon.

Anthony Piron, Florian Szymczak, Lise Folon, Daniel J M Crouch, Theodora Papadopoulou, Maria Lytrivi, Yue Tong, Maria Inês Alvelos, Maikel L Colli, Xiaoyan Yi and 10 more

Abstract read
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In one paragraph

Article in Cell genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. The diabetes-associated KDiabetologia · 2026
    Article
  6. Article
4 · The record

Corrections and comments

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

20 authors.

Anthony PironULB Center for Diabetes Research, Medical Faculty, Université Libre de Bruxelles, 1070 Brussels, Belgium; Pharmacognosy, Bioanalysis and Drug Discovery, Pharmacy Faculty, Université Libre de Bruxelles, 1050 Brussels, Belgium; Interuniversity Institute of Bioinformatics in Brussels (IB2), 1050 Brussels, Belgium; JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7BN, UK. Electronic address: anthony.piron@ulb.be.
Florian SzymczakULB Center for Diabetes Research, Medical Faculty, Université Libre de Bruxelles, 1070 Brussels, Belgium; Interuniversity Institute of Bioinformatics in Brussels (IB2), 1050 Brussels, Belgium.
Lise FolonULB Center for Diabetes Research, Medical Faculty, Université Libre de Bruxelles, 1070 Brussels, Belgium.
Daniel J M CrouchJDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7BN, UK.
Theodora PapadopoulouULB Center for Diabetes Research, Medical Faculty, Université Libre de Bruxelles, 1070 Brussels, Belgium.
Maria LytriviULB Center for Diabetes Research, Medical Faculty, Université Libre de Bruxelles, 1070 Brussels, Belgium.
Yue TongULB Center for Diabetes Research, Medical Faculty, Université Libre de Bruxelles, 1070 Brussels, Belgium.
Maria Inês AlvelosULB Center for Diabetes Research, Medical Faculty, Université Libre de Bruxelles, 1070 Brussels, Belgium.
Maikel L ColliULB Center for Diabetes Research, Medical Faculty, Université Libre de Bruxelles, 1070 Brussels, Belgium.
Xiaoyan YiULB Center for Diabetes Research, Medical Faculty, Université Libre de Bruxelles, 1070 Brussels, Belgium.
Marcin L PekalskiJDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7BN, UK; Military Institute of Medicine, National Research Institute Warsaw, Warsaw, Poland.
Konstantinos HatzikotoulasInstitute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany.
Alicia Huerta-ChagoyaDiabetes Unit, Massachusetts General Hospital, Boston, MA 02144, USA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA.
Henry J TaylorCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892-2152, USA; British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB2 0BB, UK; Heart and Lung Research Institute, University of Cambridge, Cambridge CB2 0BB, UK.
Type 2 Diabetes Global Genomics Initiative
Matthieu DefranceInteruniversity Institute of Bioinformatics in Brussels (IB2), 1050 Brussels, Belgium.
John A ToddJDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7BN, UK.
Décio L EizirikULB Center for Diabetes Research, Medical Faculty, Université Libre de Bruxelles, 1070 Brussels, Belgium.
Josep M MercaderDiabetes Unit, Massachusetts General Hospital, Boston, MA 02144, USA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA; Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Miriam CnopULB Center for Diabetes Research, Medical Faculty, Université Libre de Bruxelles, 1070 Brussels, Belgium; Division of Endocrinology, Erasmus Hospital, Université Libre de Bruxelles, 1070 Brussels, Belgium; WEL Research Institute, 1300 Wavre, Belgium. Electronic address: miriam.cnop@ulb.be.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over 1,000 genetic variants have been associated with diabetes by genome-wide association studies (GWASs), but for most, their functional impact is unknown; only 7% alter gene expression in pancreatic islets in expression quantitative trait locus (eQTL) studies. To fill this gap, we developed a co-localization pipeline, colocRedRibbon, that prefilters eQTLs by the direction of effect on gene expression and shortlists overlapping eQTL and GWAS variants prior to co-localization. Applying colocRedRibbon to recent diabetes and glycemic trait GWASs, we identified 292 co-localizing gene regions, including 24 co-localizations for type 1 diabetes and 268 for type 2 diabetes and glycemic traits, representing a 4-fold increase. A low-frequency type 2 diabetes protective variant increases islet MYO5C expression, and a type 1 diabetes protective variant increases FUT2 expression. These novel co-localizations advance the understanding of diabetes genetics and its impact on human islet biology. colocRedRibbon has broad applicability to co-localize GWASs and various QTLs.

Indexed as

Diabetes Mellitus, Type 1Diabetes Mellitus, Type 2Genome-Wide Association StudyIslets of LangerhansQuantitative Trait LociGenetic Predisposition to DiseaseHumansPolymorphism, Single Nucleotideco-localizationcolocRedRibbondiabeteseQTLgeneticsglycemic traitsGWASinsulinmeQTLmulti-ancestrypancreatic isletspQTLβ cells

Identifiers

PMID40961947
PMCPMC12648100

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Registered trials

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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.