Evidence map›Paper›PMID 20020228›Full record

ArticleGenes & nutrition2010

Gene expression profiles of a mouse congenic strain carrying an obesity susceptibility QTL under obesigenic diets.

Hyoung Yon Kim, Taryn P Stewart, Brantley N Wyatt, Nalin Siriwardhana, Arnold M Saxton, Jung Han Kim

Open access · bronzeAbstract read
In one paragraph

Article in Genes & nutrition, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.6field-weighted citation impact, top 27% 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

0 citing papers in PubMed, 5 citations in OpenAlex.

No citing paper in PubMed yet.

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

6 authors at 2 institutions in 1 country.

Hyoung Yon Kim
Taryn P Stewart
Brantley N Wyatt
Nalin Siriwardhana
Arnold M Saxton
Jung Han Kim
University of Tennessee at Knoxville · USMarshall University · US

Funding

Genetics of diet-induced obesity in a new mouse modelR01DK077202 · NIDDK · UNIVERSITY OF TENNESSEE KNOXVILLE · PI KIM, JUNG HAN · 2008 to 2012
$1.4M
NIDDK NIH HHS R01 DK077202
6 · The paper itself

Abstract

Genetic factors are strongly involved in the development of obesity, likely through the interactions of susceptibility genes with obesigenic environments, such as high-fat, high-sucrose (HFS) diets. Previously, we have established a mouse congenic strain on C57BL/6 J background, carrying an obesity quantitative trait locus (QTL), tabw2, derived from obese diabetic TALLYHO/JngJ mice. The tabw2 congenic mice exhibit increased adiposity and hyperleptinemia, which becomes exacerbated upon feeding HFS diets. In this study, we conducted genome-wide gene expression profiling to evaluate differentially expressed genes between tabw2 and control mice fed HFS diets, which may lead to identification of candidate genes as well as insights into the mechanisms underlying obesity mediated by tabw2. Both tabw2 congenic mice and control mice were fed HFS diets for 10 weeks beginning at 4 weeks of age, and total RNA was isolated from liver and adipose tissue. Whole-genome microarray analysis was performed and verified by real-time quantitative RT-PCR. At False Discovery Rate adjusted P < 0.05, 1026 genes were up-regulated and 308 down-regulated in liver, whereas 393 were up-regulated and 187 down-regulated in adipose tissue in tabw2 congenic mice compared to controls. Within the tabw2 QTL interval, 70 genes exhibited differential expression in either liver or adipose tissue. A comprehensive pathway analysis revealed a number of biological pathways that may be perturbed in the diet-induced obesity mediated by tabw2.

Identifiers

PMID20020228
PMCPMC2935530
OpenAlexW2037067195

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.