Abstract
Obstructive sleep apnea (OSA) is a prevalent disorder characterized by intermittent hypoxia (IH) during sleep. OSA is strongly associated with obesity and dysregulation of metabolism-yet the molecular pathways linking the effects of IH on adipocyte biology remain unknown. We hypothesized that exposure to IH would activate distinct, time-dependent transcriptional programs in visceral adipose tissue of mice. We exposed 36 mice to IH or normoxia for up to 13 days. We transcriptionally profiled visceral fat tissue harvested from the animals and performed functional enrichment and network analysis on differentially expressed genes. We identified over 3,000 genes with significant expression patterns during the time course of IH exposure. The most enriched pathways mapped to metabolic processes, mitochondrion, and oxidative stress responses. We confirmed the pathophysiological relevance of these findings by demonstrating that mice exposed to chronic IH developed dyslipidemia and underwent significant lipid and protein oxidation within their visceral adipose depots. We applied gene-gene interaction network analysis to identify critical controllers of IHinduced transcriptional programs in adipocytes-these network hubs represent putative targets to modulate the effects of chronic IH on adipose tissue. Our approach to integrate computational methods with gene expression profiling of visceral fat tissue during IH exposure shows promise in helping unravel the mechanistic links between OSA and adipocyte biology.
Original language | English (US) |
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Pages (from-to) | 435-445 |
Number of pages | 11 |
Journal | Journal of Molecular Medicine |
Volume | 90 |
Issue number | 4 |
DOIs | |
State | Published - Apr 2012 |
Funding
Acknowledgments This work was supported in part by the National Institutes of Health HL065270 and HL086662 (DG) and American Sleep Medicine Foundation Junior Faculty Research Award (SAG).
Keywords
- Adipocyte
- Metabolism
- Microarray
- Network analysis
- Oxidative stress
- Sleep apnea
ASJC Scopus subject areas
- Drug Discovery
- Genetics(clinical)
- Molecular Medicine