Evidence map›Paper›PMID 23762820›Full record

ArticleInternational journal of genomics2013

Variants of insulin-signaling inhibitor genes in type 2 diabetes and related metabolic abnormalities.

Carlo de Lorenzo, Annalisa Greco, Teresa Vanessa Fiorentino, Gaia Chiara Mannino, Marta Letizia Hribal

Open access · goldAbstract read
In one paragraph

Article in International journal of genomics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
1.0field-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

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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Frontiers in endocrinology · 2021
    Pooled it
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  5. Review
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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

5 authors at 1 institution in 1 country.

Carlo de LorenzoDepartment of Medical and Surgical Sciences, University of Catanzaro "Magna Graecia", 88100 Catanzaro, Italy.
Annalisa Greco
Teresa Vanessa Fiorentino
Gaia Chiara Mannino
Marta Letizia Hribal
Magna Graecia University · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Insulin resistance has a central role in the pathogenesis of several metabolic diseases, including type 2 diabetes, obesity, glucose intolerance, metabolic syndrome, atherosclerosis, and cardiovascular diseases. Insulin resistance and related traits are likely to be caused by abnormalities in the genes encoding for proteins involved in the composite network of insulin-signaling; in this review we have focused our attention on genetic variants of insulin-signaling inhibitor molecules. These proteins interfere with different steps in insulin-signaling: ENPP1/PC-1 and the phosphatases PTP1B and PTPRF/LAR inhibit the insulin receptor activation; INPPL1/SHIP-2 hydrolyzes PI3-kinase products, hampering the phosphoinositide-mediated downstream signaling; and TRIB3 binds the serine-threonine kinase Akt, reducing its phosphorylation levels. While several variants have been described over the years for all these genes, solid evidence of an association with type 2 diabetes and related diseases seems to exist only for rs1044498 of the ENPP1 gene and for rs2295490 of the TRIB3 gene. However, overall the data recapitulated in this Review article may supply useful elements to interpret the results of novel, more technically advanced genetic studies; indeed it is becoming increasingly evident that genetic information on metabolic diseases should be interpreted taking into account the complex biological pathways underlying their pathogenesis.

Identifiers

PMID23762820
PMCPMC3674720
OpenAlexW1978569113

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.