Evidence map›Paper›PMID 28777829›Full record

ArticlePloS one2017

Identification of an early transcriptomic signature of insulin resistance and related diseases in lymphomonocytes of healthy subjects.

Alice Matone, Eleonora Derlindati, Luca Marchetti, Valentina Spigoni, Alessandra Dei Cas, Barbara Montanini, Diego Ardigò, Ivana Zavaroni, Corrado Priami, Riccardo C Bonadonna

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

6 citing papers in PubMed, 22 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 2 institutions in 1 country.

Alice MatoneThe Microsoft Research-University of Trento Centre for Computational and Systems Biology (COSBI), Rovereto, Italy.
Eleonora DerlindatiDepartment of Medicine and Surgery, University of Parma, Parma, Italy.
Luca MarchettiThe Microsoft Research-University of Trento Centre for Computational and Systems Biology (COSBI), Rovereto, Italy.ORCID http://orcid.org/0000-0001-9043-7705
Valentina SpigoniDepartment of Medicine and Surgery, University of Parma, Parma, Italy.
Alessandra Dei CasDepartment of Medicine and Surgery, University of Parma, Parma, Italy.
Barbara MontaniniDepartment of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parma, Italy.ORCID http://orcid.org/0000-0002-5419-7975
Diego ArdigòDepartment of Medicine and Surgery, University of Parma, Parma, Italy.
Ivana ZavaroniDepartment of Medicine and Surgery, University of Parma, Parma, Italy.
Corrado PriamiThe Microsoft Research-University of Trento Centre for Computational and Systems Biology (COSBI), Rovereto, Italy.ORCID http://orcid.org/0000-0002-3261-6235
Riccardo C BonadonnaDepartment of Medicine and Surgery, University of Parma, Parma, Italy.
University of Parma · ITUniversity of Trento · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Insulin resistance is considered to be a pathogenetic mechanism in several and diverse diseases (e.g. type 2 diabetes, atherosclerosis) often antedating them in apparently healthy subjects. The aim of this study is to investigate with a microarray based approach whether IR per se is characterized by a specific pattern of gene expression. For this purpose we analyzed the transcriptomic profile of peripheral blood mononuclear cells in two groups (10 subjects each) of healthy individuals, with extreme insulin resistance or sensitivity, matched for BMI, age and gender, selected within the MultiKnowledge Study cohort (n = 148). Data were analyzed with an ad-hoc rank-based classification method. 321 genes composed the gene set distinguishing the insulin resistant and sensitive groups, within which the "Adrenergic signaling in cardiomyocytes" KEGG pathway was significantly represented, suggesting a pattern of increased intracellular cAMP and Ca2+, and apoptosis in the IR group. The same pathway allowed to discriminate between insulin resistance and insulin sensitive subjects with BMI >25, supporting his role as a biomarker of IR. Moreover, ASCM pathway harbored biomarkers able to distinguish healthy and diseased subjects (from publicly available data sets) in IR-related diseases involving excitable cells: type 2 diabetes, chronic heart failure, and Alzheimer's disease. The altered gene expression profile of the ASCM pathway is an early molecular signature of IR and could provide a common molecular pathogenetic platform for IR-related disorders, possibly representing an important aid in the efforts aiming at preventing, early detecting and optimally treating IR-related diseases.

Indexed as

TranscriptomeAdultAlzheimer DiseaseBiomarkersBlood GlucoseCase-Control StudiesDiabetes Mellitus, Type 2FemaleHealthy VolunteersHeart FailureHumansInsulin ResistanceLeukocytes, MononuclearMaleBiomarkersBlood Glucose

Identifiers

PMID28777829
PMCPMC5544197
OpenAlexW2744138357

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.