Evidence map›Paper›PMID 25469308›Full record

ArticleBMJ open diabetes research & care2014

Two novel type 2 diabetes loci revealed through integration of TCF7L2 DNA occupancy and SNP association data.

Matthew E Johnson, Jianhua Zhao, Jonathan Schug, Sandra Deliard, Qianghua Xia, Vanessa C Guy, Jesus Sainz, Klaus H Kaestner, Andrew D Wells, Struan F A Grant

Open access · goldAbstract read
In one paragraph

Article in BMJ open diabetes research & care, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
1.6field-weighted citation impact, top 17% of its field
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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.

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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

10 authors at 3 institutions in 2 countries.

Matthew E JohnsonDivision of Human Genetics , The Children's Hospital of Philadelphia , Philadelphia, Pennsylvania , USA.
Jianhua ZhaoDivision of Human Genetics , The Children's Hospital of Philadelphia , Philadelphia, Pennsylvania , USA.
Jonathan SchugDepartment of Genetics and Institute of Diabetes, Obesity and Metabolism , Perelman School of Medicine, University of Pennsylvania , Philadelphia, Pennsylvania , USA.
Sandra DeliardDivision of Human Genetics , The Children's Hospital of Philadelphia , Philadelphia, Pennsylvania , USA.
Qianghua XiaDivision of Human Genetics , The Children's Hospital of Philadelphia , Philadelphia, Pennsylvania , USA.
Vanessa C GuyDivision of Human Genetics , The Children's Hospital of Philadelphia , Philadelphia, Pennsylvania , USA.
Jesus SainzInstitute of Biomedicine and Biotechnology of Cantabria (IBBTEC), Spanish National Research Council (CSIC) , Santander , Spain.
Klaus H KaestnerDepartment of Genetics and Institute of Diabetes, Obesity and Metabolism , Perelman School of Medicine, University of Pennsylvania , Philadelphia, Pennsylvania , USA.
Andrew D WellsPathology and Laboratory Medicine , Children's Hospital of Philadelphia , Philadelphia, Pennsylvania , USA.
Struan F A GrantDivision of Human Genetics , The Children's Hospital of Philadelphia , Philadelphia, Pennsylvania , USA ; Department of Genetics and Institute of Diabetes, Obesity and Metabolism , Perelman School of Medicine, University of Pennsylvania , Philadelphia, Pennsylvania , USA ; Department of Pediatrics , Perelman School of Medicine, University of Pennsylvania , Philadelphia, Pennsylvania , USA.ORCID 0000-0003-2025-5302
Children's Hospital of Philadelphia · USUniversity of Pennsylvania · USConsejo Superior de Investigaciones Científicas · ES

Funding

VIRAL VECTOR COREP30DK019525 · NIDDK · UNIVERSITY OF PENNSYLVANIA · PI MITCHELL A. LAZAR · 1986 to 2026
$48.3M
NIDDK NIH HHS P30 DK019525
6 · The paper itself

Abstract

backgroundThe transcription factor 7-like 2 (TCF7L2) locus is strongly implicated in the pathogenesis of type 2 diabetes (T2D). We previously mapped the genomic regions bound by TCF7L2 using ChIP (chromatin immunoprecipitation)-seq in the colorectal carcinoma cell line, HCT116, revealing an unexpected highly significant over-representation of genome-wide association studies (GWAS) loci associated primarily with endocrine (in particular T2D) and cardiovascular traits.

methodsIn order to further explore if this observed phenomenon occurs in other cell lines, we carried out ChIP-seq in HepG2 cells and leveraged ENCODE data for five additional cell lines. Given that only a minority of the predicted genetic component to most complex traits has been identified to date, plus our GWAS-related observations with respect to TCF7L2 occupancy, we investigated if restricting association analyses to the genes yielded from this approach, in order to reduce the constraints of multiple testing, could reveal novel T2D loci.

resultsWe found strong evidence for the continued enrichment of endocrine and cardiovascular GWAS categories, with additional support for cancer. When investigating all the known GWAS loci bound by TCF7L2 in the shortest gene list, derived from HCT116, the coronary artery disease-associated variant, rs46522 at the UBE2Z-GIP-ATP5G1-SNF8 locus, yielded significant association with T2D within DIAGRAM. Furthermore, when we analyzed tag-SNPs (single nucleotide polymorphisms) in genes not previously implicated by GWAS but bound by TCF7L2 within 5 kb, we observed a significant association of rs4780476 within CPPED1 in DIAGRAM.

conclusionsChIP-seq data generated with this GWAS-implicated transcription factor provided a biologically plausible method to limit multiple testing in the assessment of genome-wide genotyping data to uncover two novel T2D-associated loci.

Indexed as

GeneGenetic AssociationTranscription FactorType 2

Identifiers

PMID25469308
PMCPMC4250976
OpenAlexW2125917665

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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.