Evidence map›Paper›PMID 26366287›Full record

ArticleClinical & translational immunology2015

Expression profiling pre-diabetic mice to uncover drugs with clinical application to type 1 diabetes.

Dimeng Pang, Katharine M Irvine, Ahmed M Mehdi, Helen E Thomas, Mark Harris, Emma E Hamilton-Williams, Ranjeny Thomas

Open access · goldAbstract read
In one paragraph

Article in Clinical & translational immunology, 2015. 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
0.5field-weighted citation impact, top 25% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
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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

7 authors at 4 institutions in 1 country.

Dimeng PangDiamantina Institute, Translational Research Institute, University of Queensland , Woolloongabba, Queensland, Australia.
Katharine M IrvineDiamantina Institute, Translational Research Institute, University of Queensland , Woolloongabba, Queensland, Australia.
Ahmed M MehdiDiamantina Institute, Translational Research Institute, University of Queensland , Woolloongabba, Queensland, Australia.
Helen E ThomasSt Vincent's Institute , Fitzroy, Victoria, Australia.
Mark HarrisDepartment of Paediatric Endocrinology, Mater Health Services , South Brisbane, Queensland, Australia.
Emma E Hamilton-WilliamsDiamantina Institute, Translational Research Institute, University of Queensland , Woolloongabba, Queensland, Australia.
Ranjeny ThomasDiamantina Institute, Translational Research Institute, University of Queensland , Woolloongabba, Queensland, Australia.
Translational Research Institute · AUMater Health Services · AUSt Vincents Institute of Medical Research · AUUniversity of Queensland · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the NOD mouse model of type 1 diabetes (T1D), genetically identical mice in the same environment develop diabetes at different rates. Similar heterogeneity in the rate of progression to T1D exists in humans, but the underlying mechanisms are unclear. Here, we aimed to discover peripheral blood (PB) genes in NOD mice predicting insulitis severity and rate of progression to diabetes. We then wished to use these genes to mine existing databases to identify drugs effective in diabetes. In a longitudinal study, we analyzed gene expression in PB samples from NOD.CD45.2 mice at 10 weeks of age, then scored pancreatic insulitis at 14 weeks or determined age of diabetes onset. In a multilinear regression model, Tnf and Tgfb mRNA expression in PB predicted insulitis score (R (2)=0.56, P=0.01). Expression of these genes did not predict age of diabetes onset. However, by expression-profiling PB genes in 10-week-old NOD.CD45.2 mice, we found a signature of upregulated genes that predicted delayed or no diabetes. Major associated pathways included chromatin organization, cellular protein location and regulation of nitrogen compounds and RNA. In a clinical cohort, three of these genes were differentially expressed between first-degree relatives, T1D patients and controls. Bioinformatic analysis of differentially expressed genes in NOD.CD45.2 PB identified drugs that are predicted to delay or prevent diabetes. Of these drugs, 11 overlapped with drugs predicted to induce a human 'non-progressor' expression profile. These data demonstrate that disease heterogeneity in diabetes-prone mice can be exploited to mine novel clinical T1D biomarkers and drug targets.

Identifiers

PMID26366287
PMCPMC4558439
OpenAlexW2220108805

What OpenQuestion holds

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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.