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Network Modeling of Inflammatory Dynamics Induced by Biomass Smoke Leading to Chronic Obstructive Pulmonary Disease
Hai-shan Yu,Zhi-chao Pan,Jie-lou Liao*
Author NameAffiliationE-mail
Hai-shan Yu Department of Chemical Physics, University of Science and Technology of China, Hefei 230026, China  
Zhi-chao Pan Department of Chemical Physics, University of Science and Technology of China, Hefei 230026, China  
Jie-lou Liao* Department of Chemical Physics, University of Science and Technology of China, Hefei 230026, China liaojl@ustc.edu.cn 
Abstract:
Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory disorder characterized by airflow obstruction and progressive damage of lung tissues. As currently more than 3 billion people use biomass fuel for cooking and heating worldwide, exposure to biomass smoke (BS) is recognized as a significant risk factor for COPD. Recent clinical data have shown that BS-COPD patients have a Th2-type inflammatory profile significantly different from that in COPD induced by cigarette smoke. As COPD is essentially proinflammatory, however, the mechanism underlying this Th2-type anti-inflammatory profile remains elusive. In this work, a network model is applied to study BS-induced inflammatory dynamics. The network model involves several positive feedback loops, activations of which are responsible for different mechanisms by which clinical phenotypes of COPD are produced. Our modeling study in this work has identified a subset of BS-COPD patients with a mixed M1-and Th2-type inflammatory profile. The model's prediction is in good agreement with clinical experiments and our in silico knockout simulations have demonstrated several important network components that play an important role in the disease. Our modeling study provides novel insight into BS-COPD progression, offering a rationale for targeted therapy and personalized medicine for treatment of the disease in future.
Key words:  Network model  Inflammatory dynamics  Positive feedback loops  Biomass smoke  Chronic obstructive pulmonary disease
FundProject:This work was supported by the National Natural Science Foundation of China (No.21273209).
网络建模研究生物质烟雾引起的导致慢性阻塞性肺病的炎症反应动力学
余海山,潘志超,廖结楼*
摘要:
慢性阻塞性肺病(COPD)是一种由慢性炎症引起的气道阻塞和渐进性的肺组织损伤.目前在全球范围内大概有30亿人使用生物质燃料进行烹饪和加热取暖,生物质烟雾被认为是慢性阻塞性肺病一个重要的危险因素.最近的临床数据表明,与吸烟引起的慢性阻塞性肺病不同,生物质烟雾引起的慢性阻塞性肺病(BS-COPD)病人有Th2类型的抗炎反应特征.然而,由于促炎反应是慢性阻塞性肺病的一个基本特征,人们对生物质烟雾引起的慢性阻塞性肺病的Th2类型的抗炎特征形成机理还不是很清楚.本文应用多尺度网络模型计算研究了生物质烟雾引起的炎症反应动力学.本文的网络模型涉及几个不同的正反馈通路,激活这些正反馈通路分别对应不同的慢性阻塞性肺病临床表现的形成机制.建模研究确定在一部分BS-COPD病人具有混合的M1(促炎)和Th2炎症反应特征.本文的计算结果与临床试验吻合得很好,而且计算敲除模拟显示几种重要的网络组成部分对COPD疾病形成起着重要作用.研究对BS-COPD的形成机制提供了新的见解,为未来利用标靶和个性化治疗慢性阻塞性肺病提供了可能的理论基础.
关键词:  网络模型  炎症反应动力学  正反馈循环  生物质烟雾  慢性阻塞性肺病
DOI:10.1063/1674-0068/31/cjcp1801001
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