Evidence map›Paper›PMID 30647452›Full record

ArticleInternational journal of obesity (2005)2020

Deletion of translin (Tsn) induces robust adiposity and hepatic steatosis without impairing glucose tolerance.

Aparna P Shah, Miranda D Johnson, Xiuping Fu, Gretha J Boersma, Madhura Shah, Michael J Wolfgang, Kellie L Tamashiro, Jay M Baraban

Abstract read
In one paragraph

Article in International journal of obesity (2005), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.2field-weighted citation impact, top 22% 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

7 citing papers in PubMed, 11 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

8 authors at 3 institutions in 2 countries.

Aparna P Shah *Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
Miranda D Johnson *Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
Xiuping Fu *Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
Gretha J BoersmaDepartment of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
Madhura ShahSolomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
Michael J WolfgangDepartment of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
Kellie L TamashiroDepartment of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
Jay M BarabanSolomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA. jay.baraban@gmail.com.
Johns Hopkins University · USJohns Hopkins Medicine · USGGZ Drenthe · NL

Funding

UNDERSTANDING NO SIGNALING RESULTING IN NEUROPROTECTION.P50DA000266 · NIDA · JOHNS HOPKINS UNIVERSITY · PI WORLEY, PAUL F · 1985 to 2017
$45.2M
Murine Mutagenesis CoreP30NS050274 · NINDS · JOHNS HOPKINS UNIVERSITY · PI KOLODKIN, ALEX L · 2005 to 2020
$10.9M
Thorase Regulation of the Actions of CocaineP50DA044123 · NIDA · JOHNS HOPKINS UNIVERSITY · PI DAWSON, VALINA L., JANAK, PATRICIA H. · 2018 to 2022
$9.0M
NIDA NIH HHS P50 DA000266NIDA NIH HHS P50 DA044123NINDS NIH HHS P30 NS050274
6 · The paper itself

Abstract

objectiveTranslin knockout (KO) mice display robust adiposity. Recent studies indicate that translin and its partner protein, trax, regulate the microRNA and ATM kinase signaling pathways, both of which have been implicated in regulating metabolism. In the course of characterizing the metabolic profile of these mice, we found that they display normal glucose tolerance despite their elevated adiposity. Accordingly, we investigated why translin KO mice display this paradoxical phenotype.

methodsTo help distinguish between the metabolic effects of increased adiposity and those of translin deletion per se, we compared three groups: (1) wild-type (WT), (2) translin KO mice on a standard chow diet, and (3) adiposity-matched WT mice that were placed on a high-fat diet until they matched translin KO adiposity levels. All groups were scanned to determine their body composition and tested to evaluate their glucose and insulin tolerance. Plasma, hepatic, and adipose tissue samples were collected and used for histological and molecular analyses.

resultsTranslin KO mice show normal glucose tolerance whereas adiposity-matched WT mice, placed on a high-fat diet, do not. In addition, translin KO mice display prominent hepatic steatosis that is more severe than that of adiposity-matched WT mice. Unlike adiposity-matched WT mice, translin KO mice display three key features that have been shown to reduce susceptibility to insulin resistance: increased accumulation of subcutaneous fat, increased levels of circulating adiponectin, and decreased Tnfα expression in hepatic and adipose tissue.

conclusionsThe ability of translin KO mice to retain normal glucose tolerance in the face of marked adipose tissue expansion may be due to the three protective factors noted above. Further studies aimed at defining the molecular bases for this combination of protective phenotypes may yield new approaches to limit the adverse metabolic consequences of obesity.

Indexed as

Blood GlucoseDNA-Binding ProteinsRNA-Binding ProteinsAdiposityAnimalsBody CompositionDiet, High-FatFatty LiverGlucose Tolerance TestInsulin ResistanceMiceMice, KnockoutBlood GlucoseDNA-Binding ProteinsRNA-Binding ProteinsTsn protein, mouse

Identifiers

PMID30647452
PMCPMC6629527
OpenAlexW2908646567

What OpenQuestion holds

Textmetadata
LicenceTDM
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 OpenQuestion graph.