Liu Xiao-Lin, Ming Ya-Nan, Zhang Jing-Yi, Chen Xiao-Yu, Zeng Min-De, Mao Yi-Min
Division of Gastroenterology and Hepatology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Institute of Digestive Disease, Shanghai, China.
Exp Mol Med. 2017 Jan 13;49(1):e283. doi: 10.1038/emm.2016.123.
We sought to identify common key regulators and build a gene-metabolite network in different nonalcoholic fatty liver disease (NAFLD) phenotypes. We used a high-fat diet (HFD), a methionine-choline-deficient diet (MCDD) and streptozocin (STZ) to establish nonalcoholic fatty liver (NAFL), nonalcoholic steatohepatitis (NASH) and NAFL+type 2 diabetes mellitus (T2DM) in rat models, respectively. Transcriptomics and metabolomics analyses were performed in rat livers and serum. A functional network-based regulation model was constructed using Cytoscape with information derived from transcriptomics and metabolomics. The results revealed that 96 genes, 17 liver metabolites and 4 serum metabolites consistently changed in different NAFLD phenotypes (>2-fold, P<0.05). Gene-metabolite network analysis identified ccl2 and jun as hubs with the largest connections to other genes, which were mainly involved in tumor necrosis factor, P53, nuclear factor-kappa B, chemokine, peroxisome proliferator activated receptor and Toll-like receptor signaling pathways. The specifically regulated genes and metabolites in different NAFLD phenotypes constructed their own networks, which were mainly involved in the lipid and fatty acid metabolism in HFD models, the inflammatory and immune response in MCDD models, and the AMPK signaling pathway and response to insulin in HFD+STZ models. Our study identified networks showing the general and specific characteristics in different NAFLD phenotypes, complementing the genetic and metabolic features in NAFLD with hepatic and extra-hepatic manifestations.
我们试图识别不同非酒精性脂肪性肝病(NAFLD)表型中的共同关键调节因子,并构建基因-代谢物网络。我们分别使用高脂饮食(HFD)、蛋氨酸-胆碱缺乏饮食(MCDD)和链脲佐菌素(STZ)在大鼠模型中建立非酒精性脂肪肝(NAFL)、非酒精性脂肪性肝炎(NASH)和NAFL+2型糖尿病(T2DM)。对大鼠肝脏和血清进行转录组学和代谢组学分析。使用Cytoscape基于功能网络构建调节模型,该模型的信息来源于转录组学和代谢组学。结果显示,在不同的NAFLD表型中,96个基因、17种肝脏代谢物和4种血清代谢物持续发生变化(变化>2倍,P<0.05)。基因-代谢物网络分析确定ccl2和jun为与其他基因连接最多的枢纽基因,它们主要参与肿瘤坏死因子、P53、核因子-κB、趋化因子、过氧化物酶体增殖物激活受体和Toll样受体信号通路。不同NAFLD表型中特异性调节的基因和代谢物构建了各自的网络,这些网络在HFD模型中主要参与脂质和脂肪酸代谢,在MCDD模型中主要参与炎症和免疫反应,在HFD+STZ模型中主要参与AMPK信号通路和对胰岛素的反应。我们的研究确定了在不同NAFLD表型中具有一般和特异性特征的网络,以肝脏和肝外表现补充了NAFLD的遗传和代谢特征。