Evidence map›Paper›PMID 17330137›Full record

ArticleGenes and immunity2007

Transcriptional profiling of type 1 diabetes genes on chromosome 21 in a rat beta-cell line and human pancreatic islets.

R Bergholdt, A E Karlsen, P H Hagedorn, M Aalund, J H Nielsen, M Kruhøffer, T Orntoft, H Wang, C B Wollheim, J Nerup and 1 more

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Article in Genes and immunity, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.9field-weighted citation impact, top 24% 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

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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

4 citing papers in PubMed, 7 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

11 authors at 6 institutions in 2 countries.

R BergholdtSteno Diabetes Center, Gentofte, Denmark.
A E Karlsen
P H Hagedorn
M Aalund
J H Nielsen
M Kruhøffer
T Orntoft
H Wang
C B Wollheim
J Nerup
F Pociot
Aarhus University Hospital · DKLund University · SESteno Diabetes Center · DKNeuroSearch (Denmark) · DKTechnical University of Denmark · DKUniversity of Copenhagen · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We recently finemapped a type 1 diabetes (T1D)-linked region on chromosome 21, indicating that one or more T1D-linked genes exist in this region with 33 annotated genes. In the current study, we have taken a novel approach using transcriptional profiling in predicting and prioritizing the most likely candidate genes influencing beta-cell function in this region. Two array-based approaches were used, a rat insulinoma cell line (INS-1alphabeta) overexpressing pancreatic duodenum homeobox 1 (pdx-1) and treated with interleukin 1beta (IL-1beta) as well as human pancreatic islets stimulated with a mixture of cytokines. Several candidate genes with likely functional significance in T1D were identified. Genes showing differential expression in the two approaches were highly similar, supporting the role of these specific gene products in cytokine-induced beta-cell damage. These were genes involved in cytokine signaling, oxidative phosphorylation, defense responses and apoptosis. The analyses, furthermore, revealed several transcription factor binding sites shared by the differentially expressed genes and by genes demonstrating highly similar expression profiles with these genes. Comparable findings in the rat beta-cell line and human islets support the validity of the methods used and support this as a valuable approach for gene mapping and identification of genes with potential functional significance in T1D, within a region of linkage.

Indexed as

AdolescentAdultAnimalsCell Line, TumorChildChromosomes, Human, Pair 21Diabetes Mellitus, Type 1FemaleGene Expression ProfilingGenetic Predisposition to DiseaseHomeodomain ProteinsHumansInsulinomaInsulin-Secreting CellsInterleukin-1betaIn Vitro TechniquesHomeodomain ProteinsInterleukin-1betapancreatic and duodenal homeobox 1 proteinTrans-Activators

Identifiers

PMID17330137
OpenAlexW2009002991

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.