Center for Lung Biology, Department of Medicine, University of Washington, Seattle, WA 98109, USA.
Sleep. 2013 Jan 1;36(1):23-30. doi: 10.5665/sleep.2294.
Obstructive sleep apnea (OSA) has been associated with metabolic dysregulation and systemic inflammation. This may be due to pathophysiologic effects of OSA on visceral adipose tissue. We sought to assess the transcriptional consequences of OSA on adipocytes by utilizing pathway-focused analyses.
Patients scheduled to undergo ventral hernia repair surgery were recruited to wear a portable home sleep monitor for 2 nights prior to surgery. Visceral fat biopsies were obtained intraoperatively. RNA was extracted and whole-genome expression profiling was performed. Gene Set Enrichment Analysis (GSEA) was used to identify curated gene sets that were differentially enriched in OSA subjects. Network analysis was applied to a select set of highly enriched pathways.
Ten patients with OSA and 8 control subjects were recruited. There were no differences in age, gender, or body mass index between the 2 groups, but the OSA subjects had a significantly higher respiratory disturbance index (19.2 vs. 0.6, P = 0.05) and worse hypoxemia (minimum oxygen saturation 79.7% vs. 87.8%, P < 0.001). GSEA identified a number of gene sets up-regulated in adipose tissue of OSA patients, including the pro-inflammatory NF-κB pathway and the proteolytic ubiquitin/proteasome module. A critical metabolic pathway, the peroxisome proliferator-activated receptor (PPAR), was down-regulated in subjects with OSA. Network analysis linked members of these modules together and identified regulatory hubs.
OSA is associated with alterations in visceral fat gene expression. Pathway-based network analysis highlighted perturbations in several key pathways whose coordinated interactions may contribute to the metabolic dysregulation observed in this complex disorder.
阻塞性睡眠呼吸暂停(OSA)与代谢失调和全身炎症有关。这可能是由于 OSA 对内脏脂肪组织的病理生理影响所致。我们试图通过利用针对途径的分析来评估 OSA 对脂肪细胞的转录后果。
招募计划接受腹疝修复手术的患者,在手术前的 2 个晚上佩戴便携式家庭睡眠监测仪。术中获取内脏脂肪活检。提取 RNA 并进行全基因组表达谱分析。基因集富集分析(GSEA)用于识别在 OSA 受试者中差异富集的已编辑基因集。网络分析应用于一组选择的高度富集途径。
招募了 10 名 OSA 患者和 8 名对照受试者。两组在年龄、性别或体重指数方面没有差异,但 OSA 患者的呼吸干扰指数明显更高(19.2 对 0.6,P = 0.05),低氧血症更严重(最低氧饱和度 79.7%对 87.8%,P <0.001)。GSEA 确定了 OSA 患者脂肪组织中上调的多个基因集,包括促炎 NF-κB 途径和蛋白水解泛素/蛋白酶体模块。一个关键的代谢途径,过氧化物酶体增殖物激活受体(PPAR),在 OSA 患者中下调。网络分析将这些模块的成员联系在一起,并确定了调节枢纽。
OSA 与内脏脂肪基因表达的改变有关。基于途径的网络分析突出了几个关键途径的干扰,其协调相互作用可能导致这种复杂疾病中观察到的代谢失调。