Evidence map›Paper›PMID 20369014›Full record

ArticlePLoS computational biology2010

Metabolic network topology reveals transcriptional regulatory signatures of type 2 diabetes.

Aleksej Zelezniak, Tune H Pers, Simão Soares, Mary Elizabeth Patti, Kiran Raosaheb Patil

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.

0numbers the graph read from it
0cells of the map it votes in
49citing papers in PubMed
6.2field-weighted citation impact, top 3% 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

49 citing papers in PubMed, 89 citations in OpenAlex.

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  17. Metabolic shifts in residual breast cancer drive tumor recurrence.The Journal of clinical investigation · 2017
    Article
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  20. Statistical Mechanics of Allosteric Enzymes.The journal of physical chemistry. B · 2016
    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

5 authors at 3 institutions in 3 countries.

Aleksej ZelezniakDepartment of Systems Biology, Technical University of Denmark, Center for Microbial Biotechnology, Lyngby, Denmark.
Tune H Pers
Simão Soares
Mary Elizabeth Patti
Kiran Raosaheb Patil
Technical University of Denmark · DKInstitute for Biotechnology and Bioengineering · PTJoslin Diabetes Center · US

Funding

Diabetes Genome Anatomy Project (DGAP)R01DK060837 · NIDDK · JOSLIN DIABETES CENTER · PI KAHN, C RONALD · 2002 to 2006
$15.9M
Gene Expression in Prediabetes: Potential Role of PGC-1R01DK062948 · NIDDK · JOSLIN DIABETES CENTER · PI PATTI, MARY E · 2003 to 2006
$1.4M
NIDDK NIH HHS DK060837NIDDK NIH HHS DK062948NIDDK NIH HHS R01 DK060837NIDDK NIH HHS R01 DK062948
6 · The paper itself

Abstract

Type 2 diabetes mellitus (T2DM) is a disorder characterized by both insulin resistance and impaired insulin secretion. Recent transcriptomics studies related to T2DM have revealed changes in expression of a large number of metabolic genes in a variety of tissues. Identification of the molecular mechanisms underlying these transcriptional changes and their impact on the cellular metabolic phenotype is a challenging task due to the complexity of transcriptional regulation and the highly interconnected nature of the metabolic network. In this study we integrate skeletal muscle gene expression datasets with human metabolic network reconstructions to identify key metabolic regulatory features of T2DM. These features include reporter metabolites--metabolites with significant collective transcriptional response in the associated enzyme-coding genes, and transcription factors with significant enrichment of binding sites in the promoter regions of these genes. In addition to metabolites from TCA cycle, oxidative phosphorylation, and lipid metabolism (known to be associated with T2DM), we identified several reporter metabolites representing novel biomarker candidates. For example, the highly connected metabolites NAD+/NADH and ATP/ADP were also identified as reporter metabolites that are potentially contributing to the widespread gene expression changes observed in T2DM. An algorithm based on the analysis of the promoter regions of the genes associated with reporter metabolites revealed a transcription factor regulatory network connecting several parts of metabolism. The identified transcription factors include members of the CREB, NRF1 and PPAR family, among others, and represent regulatory targets for further experimental analysis. Overall, our results provide a holistic picture of key metabolic and regulatory nodes potentially involved in the pathogenesis of T2DM.

Indexed as

Gene Expression RegulationMetabolic Networks and PathwaysAlgorithmsCluster AnalysisDatabases, GeneticDiabetes Mellitus, Type 2Gene Expression ProfilingGene Regulatory NetworksHumansMaleMetabolomeModels, BiologicalMuscle, SkeletalOligonucleotide Array Sequence AnalysisRegulatory Elements, TranscriptionalTranscription, Genetic

Identifiers

PMID20369014
PMCPMC2848542
OpenAlexW2050153048

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.