Evidence map›Paper›PMID 32356104›Full record

ArticleDiabetologia2020

E2f8 and Dlg2 genes have independent effects on impaired insulin secretion associated with hyperglycaemia.

Chieh-Hsin Yang, Salvatore P Mangiafico, Michaela Waibel, Thomas Loudovaris, Kim Loh, Helen E Thomas, Grant Morahan, Sofianos Andrikopoulos

Open access · bronzeAbstract read
PubMed Publisher
In one paragraph

Article in Diabetologia, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
4.1field-weighted citation impact, top 5% 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

13 citing papers in PubMed, 23 citations in OpenAlex.

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  8. Genetic Mapping of Behavioral Traits Using the Collaborative Cross Resource.International journal of molecular sciences · 2022
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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

8 authors at 5 institutions in 1 country.

Chieh-Hsin YangDepartment of Medicine (Austin Health), Austin Hospital, University of Melbourne, Level 7, Lance Townsend Building, Studley Road, Heidelberg, VIC, 3084, Australia. jyang@svi.edu.au.
Salvatore P MangiaficoDepartment of Medicine (Austin Health), Austin Hospital, University of Melbourne, Level 7, Lance Townsend Building, Studley Road, Heidelberg, VIC, 3084, Australia.
Michaela WaibelSt Vincent's Institute of Medical Research, 9 Princes Street, Fitzroy, VIC, 3065, Australia.
Thomas LoudovarisSt Vincent's Institute of Medical Research, 9 Princes Street, Fitzroy, VIC, 3065, Australia.
Kim LohSt Vincent's Institute of Medical Research, 9 Princes Street, Fitzroy, VIC, 3065, Australia.
Helen E ThomasSt Vincent's Institute of Medical Research, 9 Princes Street, Fitzroy, VIC, 3065, Australia.
Grant MorahanHarry Perkins Institute of Medical Research, Nedlands, WA, Australia.
Sofianos AndrikopoulosDepartment of Medicine (Austin Health), Austin Hospital, University of Melbourne, Level 7, Lance Townsend Building, Studley Road, Heidelberg, VIC, 3084, Australia. sof@unimelb.edu.au.
St Vincents Institute of Medical Research · AUAustin Health · AUAustin Hospital · AUHarry Perkins Institute of Medical Research · AUUniversity of Melbourne · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aims/hypothesisReduced insulin secretion results in hyperglycaemia and diabetes involving a complex aetiology that is yet to be fully elucidated. Genetic susceptibility is a key factor in beta cell dysfunction and hyperglycaemia but the responsible genes have not been defined. The Collaborative Cross (CC) is a recombinant inbred mouse panel with diverse genetic backgrounds allowing the identification of complex trait genes that are relevant to human diseases. The aim of this study was to identify and characterise genes associated with hyperglycaemia.

methodsUsing an unbiased genome-wide association study, we examined random blood glucose and insulin sensitivity in 53 genetically unique mouse strains from the CC population. The influences of hyperglycaemia susceptibility quantitative trait loci (QTLs) were investigated by examining glucose tolerance, insulin secretion, pancreatic histology and gene expression in the susceptible mice. Expression of candidate genes and their association with insulin secretion were examined in human islets. Mechanisms underlying reduced insulin secretion were studied in MIN6 cells using RNA interference.

resultsWide variations in blood glucose levels and the related metabolic traits (insulin sensitivity and body weight) were observed in the CC population. We showed that elevated blood glucose in the CC strains was not due to insulin resistance nor obesity but resulted from reduced insulin secretion. This insulin secretory defect was demonstrated to be independent of abnormalities in islet morphology, beta cell mass and pancreatic insulin content. Gene mapping identified the E2f8 (p = 2.19 × 10 CONCLUSIONS/

interpretationCollectively, these findings suggest that E2F transcription factor 8 (E2F8) and discs large homologue 2 (DLG2) regulate insulin secretion. The CC resource enables the identification of E2f8 and Dlg2 as novel genes associated with hyperglycaemia due to reduced insulin secretion in pancreatic beta cells. Taken together, our results provide better understanding of the molecular control of insulin secretion and further support the use of the CC resource to identify novel genes relevant to human diseases.

Indexed as

AnimalsBlood GlucoseCell LineFemaleGenome-Wide Association StudyGuanylate KinasesHyperglycemiaInsulinMaleMembrane ProteinsMiceRepressor ProteinsBlood GlucoseDlg2 protein, mouseE2F8 protein, mouseGuanylate KinasesInsulinMembrane ProteinsRepressor ProteinsCollaborative crossDiabetes susceptibilityDiscs large homologue 2E2F transcription factor 8Glucose-stimulated insulin secretionHyperglycaemia

Identifiers

PMID32356104
OpenAlexW3022738724

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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.