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Pattern Specification and Immune Response Transcriptional Signatures of Pericardial and Subcutaneous Adipose Tissue

Overview of attention for article published in PLOS ONE, October 2011
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Title
Pattern Specification and Immune Response Transcriptional Signatures of Pericardial and Subcutaneous Adipose Tissue
Published in
PLOS ONE, October 2011
DOI 10.1371/journal.pone.0026092
Pubmed ID
Authors

Frank H. Lau, Rahul C. Deo, Gregory Mowrer, Joshua Caplin, Tim Ahfeldt, Adam Kaplan, Leon Ptaszek, Jennifer D. Walker, Bruce R. Rosengard, Chad A. Cowan

Abstract

Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality in the United States. Recent studies suggest that pericardial adipose tissue (PCAT) secretes inflammatory factors that contribute to the development of CVD. To better characterize the role of PCAT in the pathogenesis of disease, we performed a large-scale unbiased analysis of the transcriptional differences between PCAT and subcutaneous adipose tissue, analysing 53 microarrays across 19 individuals. As it was unknown whether PCAT-secreted factors are produced by adipocytes or cells in the supporting stromal fraction, we also sought to identify differentially expressed genes in isolated pericardial adipocytes vs. isolated subcutaneous adipocytes. Using microarray analysis, we found that: 1) pericardial adipose tissue and isolated pericardial adipocytes both overexpress atherosclerosis-promoting chemokines and 2) pericardial and subcutaneous fat depots, as well as isolated pericardial adipocytes and subcutaneous adipocytes, express specific patterns of homeobox genes. In contrast, a core set of lipid processing genes showed no significant overlap with differentially expressed transcripts. These depot-specific homeobox signatures and transcriptional profiles strongly suggest different functional roles for the pericardial and subcutaneous adipose depots. Further characterization of these inter-depot differences should be a research priority.

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Geographical breakdown

Country Count As %
Unknown 29 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 31%
Professor > Associate Professor 3 10%
Professor 3 10%
Student > Master 3 10%
Student > Ph. D. Student 2 7%
Other 5 17%
Unknown 4 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 31%
Medicine and Dentistry 8 28%
Biochemistry, Genetics and Molecular Biology 3 10%
Economics, Econometrics and Finance 1 3%
Immunology and Microbiology 1 3%
Other 2 7%
Unknown 5 17%