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Time-dependent network analysis reveals molecular targets underlying the development of diet-induced obesity and non-alcoholic steatohepatitis

机译:时间依赖性网络分析揭示了饮食诱导的肥胖和非酒精性脂肪性肝炎发展的潜在分子靶标

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Prolonged high-fat diet leads to the development of obesity and multiple comorbidities including non-alcoholic steatohepatitis (NASH), but the underlying molecular basis is not fully understood. We combine molecular networks and time course gene expression profiles to reveal the dynamic changes in molecular networks underlying diet-induced obesity and NASH. We also identify hub genes associated with the development of NASH. Core diet-induced obesity networks were constructed using Ingenuity pathway analysis (IPA) based on 332 high-fat diet responsive genes identified in liver by time course microarray analysis (8 time points over 24?weeks) of high-fat diet-fed mice compared to normal diet-fed mice. IPA identified five core diet-induced obesity networks with time-dependent gene expression changes in liver. These networks were associated with cell-to-cell signaling and interaction (Network 1), lipid metabolism (Network 2), hepatic system disease (Network 3 and 5), and inflammatory response (Network 4). When we merged these core diet-induced obesity networks, Tlr2, Cd14, and Ccnd1 emerged as hub genes associated with both liver steatosis and inflammation and were altered in a time-dependent manner. Further, protein–protein interaction network analysis revealed Tlr2, Cd14, and Ccnd1 were interrelated through the ErbB/insulin signaling pathway. Dynamic changes occur in molecular networks underlying diet-induced obesity. Tlr2, Cd14, and Ccnd1 appear to be hub genes integrating molecular interactions associated with the development of NASH. Therapeutics targeting hub genes and core diet-induced obesity networks may help ameliorate diet-induced obesity and NASH.
机译:长期的高脂饮食会导致肥胖和包括非酒精性脂肪性肝炎(NASH)在内的多种合并症的发生,但其潜在的分子基础尚不完全清楚。我们结合分子网络和时程基因表达谱,揭示饮食诱导的肥胖和NASH背后的分子网络的动态变化。我们还确定了与NASH的发展相关的枢纽基因。使用Ingenuity途径分析(IPA),通过对高脂饮食喂养小鼠进行时程微阵列分析(24个星期内的8个时间点),在肝脏中鉴定出的332种高脂饮食响应基因,使用Ingenuity途径分析(IPA)构建了核心饮食诱导的肥胖网络。正常饮食喂养的小鼠。 IPA鉴定了五个核心饮食诱导的肥胖网络,这些网络在肝脏中具有随时间变化的基因表达变化。这些网络与细胞间信号和相互作用(网络1),脂质代谢(网络2),肝系统疾病(网络3和5)以及炎症反应(网络4)相关。当我们合并这些核心饮食诱导的肥胖网络时,Tlr2,Cd14和Ccnd1作为与肝脂肪变性和炎症相关的枢纽基因出现,并以时间依赖性方式发生改变。此外,蛋白质-蛋白质相互作用网络分析表明,Tlr2,Cd14和Ccnd1通过ErbB /胰岛素信号传导途径相互关联。饮食引起的肥胖症的分子网络发生动态变化。 Tlr2,Cd14和Ccnd1似乎是整合与NASH发育相关的分子相互作用的中枢基因。针对中心基因和核心饮食诱导的肥胖网络的治疗药物可能有助于改善饮食诱导的肥胖和NASH。

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