Evidence map›Paper›PMID 25047837›Full record

ArticleMolecular and cellular biology2014

ISL1 regulates peroxisome proliferator-activated receptor γ activation and early adipogenesis via bone morphogenetic protein 4-dependent and -independent mechanisms.

Xiuquan Ma, Pengyi Yang, Warren H Kaplan, Bon Hyang Lee, Lindsay E Wu, Jean Yee-Hwa Yang, Mayu Yasunaga, Kenzo Sato, Donald J Chisholm, David E James

Open access · bronzeAbstract read
In one paragraph

Article in Molecular and cellular biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.7field-weighted citation impact, top 29% 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, 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

10 authors at 3 institutions in 2 countries.

Xiuquan MaDiabetes and Obesity Research Program, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia.
Pengyi YangDiabetes and Obesity Research Program, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia School of Mathematics and Statistics, The University of Sydney, Sydney, New South Wales, Australia School of Information Technologies, The University of Sydney, Sydney, New South Wales, Australia.
Warren H KaplanPeter Wills Bioinformatics Center, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia.
Bon Hyang LeeDiabetes and Obesity Research Program, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia.
Lindsay E WuDiabetes and Obesity Research Program, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia School of Medical Sciences, University of New South Wales, Sydney, New South Wales, Australia.
Jean Yee-Hwa YangSchool of Mathematics and Statistics, The University of Sydney, Sydney, New South Wales, Australia.
Mayu YasunagaDivision of Molecular Biology, School of Life Sciences, Tottori University Faculty of Medicine, Yonago, Japan.
Kenzo SatoDivision of Molecular Biology, School of Life Sciences, Tottori University Faculty of Medicine, Yonago, Japan.
Donald J ChisholmDiabetes and Obesity Research Program, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia.
David E JamesDiabetes and Obesity Research Program, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia Charles Perkins Centre Research and Education Hub, The University of Sydney, Sydney, New South Wales, Australia david.james@sydney.edu.au.
Garvan Institute of Medical Research · AUUniversity of Sydney · AUTottori University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While adipogenesis is controlled by a cascade of transcription factors, the global gene expression profiles in the early phase of adipogenesis are not well defined. Using microarray analysis of gene expression in 3T3-L1 cells, we have identified evidence for the activity of 2,568 genes during the early phase of adipocyte differentiation. One of these, the ISL1 gene, was of interest since its expression was markedly upregulated 1 h after initiation of differentiation, with a subsequent rapid decline. Overexpression of ISL1 at early times during adipocyte differentiation but not at later times was found to profoundly inhibit differentiation. This was accompanied by moderate downregulation of peroxisome proliferator-activated receptor γ (PPARγ) levels, substantial downregulation of PPARγ downstream genes, and downregulation of bone morphogenetic protein 4 (BMP4) levels in preadipocytes. Readdition of BMP4 overcame the inhibitory effect of ISL1 on the expression of PPARγ but not aP2, a gene downstream of PPARγ, and BMP4 also partially rescued ISL1 inhibition of adipogenesis, an effect which is additive with rosiglitazone. These results suggest that ISL1 is intimately involved in early regulation of adipogenesis, modulating PPARγ expression and activity via BMP4-dependent and -independent mechanisms. Our time course gene expression survey sets the stage for further studies to explore other early and immediate regulators.

Indexed as

Adipogenesis3T3-L1 CellsAnimalsBase SequenceBone Morphogenetic Protein 4Fatty Acid-Binding ProteinsGene Expression RegulationLIM-Homeodomain ProteinsMiceMolecular Sequence DataOligonucleotide Array Sequence AnalysisPPAR gammaRosiglitazoneThiazolidinedionesTranscription FactorsBmp4 protein, mouseBone Morphogenetic Protein 4Fabp4 protein, mouseFatty Acid-Binding Proteinsinsulin gene enhancer binding protein Isl-1LIM-Homeodomain ProteinsPPAR gammaRosiglitazoneThiazolidinedionesTranscription Factors

Identifiers

PMID25047837
PMCPMC4187726
OpenAlexW2114127363

What OpenQuestion holds

Textmetadata
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.