Discovering a critical transition state from nonalcoholic hepatosteatosis to nonalcoholic steatohepatitis by lipidomics and dynamical network biomarkers
Discovering a critical transition state from nonalcoholic hepatosteatosis to nonalcoholic steatohepatitis by lipidomics and dynamical network biomarkers
复制标题
通过脂质组学和动态网络生物标志物发现从非酒精性肝脂肪变性到非酒精性脂肪性肝炎的关键过渡状态。
DOI：
10.1093/jmcb/mjw016
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发表时间：
2016
影响因子：
5.5
通讯作者：
Yin Huiyong
中科院分区：
文献类型：
--
作者：
Sa Rina;Zhang Wanwei;Ge Jing;Wei Xinben;Zhou Yunhua;L;zberg David R.;Wang Zhenzhen;Han Xianlin;Chen Luonan;Yin Huiyong
非酒精性脂肪肝（NAFLD）是2型糖尿病和代谢综合征的主要危险因素。然而，准确区分非酒精性脂肪性肝炎（NASH）和脂肪肝仍然是一个临床挑战。我们使用脂质组学和称为动态网络生物标志物（DNB）的数学模型，在高脂肪诱导的NAFLD小鼠模型中确定了从脂肪肝向NASH进展期间的关键过渡阶段（称为NASH前）。与传统的基于分子表达丰度的生物标志物方法不同，DNB模型在网络水平上利用不同代谢物的集体波动和相关性。我们发现，从脂肪变性转变为NASH后，血液和肝脏脂质种类之间的相关性急剧下降，这可能是目前难以根据血脂区分NASH和脂肪变性的原因。此外，血液循环中的大多数DNB成员，特别是三酰甘油（TAG），也在疾病进展期间在肝脏中被鉴定，这表明DNB在基于血脂诊断NASH中的潜在临床应用。我们进一步确定了负责这种转变的代谢途径。我们的研究表明，从脂肪变性到NASH的转变并不顺利，NASH前体的存在可能是目前诊断NASH的临床局限性的部分原因。如果在人类中得到验证，我们的研究将开辟一条新的途径，以可靠地诊断NASH前期并实现NAFLD的早期干预。
Nonalcoholic fatty liver disease (NAFLD) is a major risk factor for type 2 diabetes and metabolic syndrome. However, accurately differentiating nonalcoholic steatohepatitis (NASH) from hepatosteatosis remains a clinical challenge. We identified a critical transition stage (termed pre-NASH) during the progression from hepatosteatosis to NASH in a mouse model of high fat-induced NAFLD, using lipidomics and a mathematical model termed dynamic network biomarkers (DNB). Different from the conventional biomarker approach based on the abundance of molecular expressions, the DNB model exploits collective fluctuations and correlations of different metabolites at a network level. We found that the correlations between the blood and liver lipid species drastically decreased after the transition from steatosis to NASH, which may account for the current difficulty in differentiating NASH from steatosis based on blood lipids. Furthermore, most DNB members in the blood circulation, especially for triacylglycerol (TAG), are also identified in the liver during the disease progression, suggesting a potential clinical application of DNB to diagnose NASH based on blood lipids. We further identified metabolic pathways responsible for this transition. Our study suggests that the transition from steatosis to NASH is not smooth and the existence of pre-NASH may be partially responsible for the current clinical limitations to diagnose NASH. If validated in humans, our study will open a new avenue to reliably diagnose pre-NASH and achieve early intervention of NAFLD.