Network Medicine Approaches to Cachexia in COPD

摘要恶病质是慢性阻塞性肺疾病（COPD）、充血性心力衰竭（CHF）、癌症和艾滋病等许多复杂疾病的常见症状，其特征是体重和肌肉的迅速减少。无论原发疾病诊断如何，恶病质的存在与不良预后相关。同样重要的是，并不是每个被诊断患有复杂疾病（如慢性阻塞性肺病和慢性心力衰竭）的患者都会变成恶病质。这些信息促使我假设，在这些不同的复杂的慢性特征中，有共同的基因和途径影响恶病质。作为我长期职业规划的第一步，我计划开发复杂疾病中恶病质的网络医学方法研究项目，我计划主要研究COPD患者群体中的恶病质。COPD是美国第三大死亡原因，据估计，高达20%的COPD病例发展为恶病质，然而由于对恶病质定义的限制，这一数字可能被高估了。恶病质的发展是死亡率的一个强有力的预测指标。阐明慢性阻塞性肺病恶病质决定因素的公共卫生影响与我在Channing网络医学部门的培训相吻合，在那里我可以接触到几个特征明确的慢性阻塞性肺病人群（nh5300例慢性阻塞性肺病病例，纵向测量）。我们建议将多阶段GWAS应用于任何疾病的恶病质。慢性阻塞性肺病恶病质的研究将为其他慢性疾病的恶病质研究提供参考。网络医学应用系统生物学方法，例如整合来自基因型、基因表达水平和蛋白质-蛋白质相互作用的数据，试图了解系统中的扰动如何导致复杂疾病。这项研究有三个具体目的。(1)我们将在三个特征明确的COPD人群（ECLIPSE， TESRA和COPDGene）中研究COPD恶病质的遗传学，我们将研究COPDGene全外显子组测序（WES）变异与COPD患者恶病质的关系。我们将整合常见遗传变异与蛋白质-蛋白质相互作用的发现，以识别新的和/或已知的疾病模块。(2)我们将招募新的COPD病例人群，以证明使用双X线吸收仪（DXA）测量的无脂质量（FFM）与胸部计算机断层扫描（CT）扫描测量的胸肌面积（PMA）相关。此外，我们将测试基因表达特征与PMA和FFM之间的相关性。(3)我们将寻找与恶病质相关的基因表达特征，并生成一个差异共表达网络。这些发现将提高我们对慢性阻塞性肺病恶病质病因学和流行病学的理解。这将是长期计划的第一步，旨在探索包括慢性阻塞性肺病、慢性心力衰竭、癌症和艾滋病在内的复杂疾病的恶病质网络医学景观。

DESCRIPTION (provided by applicant): ABSTRACT Cachexia, featuring rapid loss of weight and muscle, is common to many complex diseases such as chronic obstructive pulmonary disease (COPD), congestive heart failure (CHF), cancer and AIDS. Regardless of the primary disease diagnosis, the presence of cachexia is associated with poor prognosis. Equally important is the observation that not every patient diagnosed with a complex disease such as COPD and CHF becomes cachectic. This information motivated me to hypothesize that there are common genes and pathways influencing cachexia in these different complex, chronic traits. For a first step in my long-term career plan to develop a research program on network medicine approaches to cachexia in complex disease, I plan to primarily study cachexia in COPD patient populations. COPD is the third leading cause of death in the United States and it has been estimated that as high as 20% of COPD cases develop cachexia, however this number may be overestimated due to limitations associated with defining cachexia. The development of cachexia is a strong predictor of mortality. The public health impact of elucidating determinants of COPD cachexia coincides with my training in the Channing Division of Network Medicine where I have access to several well- characterized COPD populations (NH5,300 COPD cases with longitudinal measures). We propose the first application of a multi-stage GWAS to cachexia in any disease. Research on cachexia in COPD will inform cachexia research for other chronic diseases. Network medicine applies systems biology approaches, such as integration of data from genotypes, gene expression levels and protein-protein interactions, to try to understand how perturbations in the system may lead to complex diseases. This study has three specific aims. (1) We will investigate the genetics of COPD cachexia in three well-characterized COPD populations (ECLIPSE, TESRA and COPDGene) and we will investigate the association of whole-exome sequencing (WES) variants with cachexia in COPD cases from COPDGene. We will integrate findings from common genetic variants with protein-protein interactions to identify novel and/or known disease modules. (2) We will recruit a new COPD case population in order to demonstrate that fat-free mass (FFM) measure using Dual X- ray Absorptiometry (DXA) correlates with pectoralis muscle area (PMA) measured from chest computed tomography (CT) scans. Further, we will test for correlation between gene expression signatures with PMA and FFM. (3) We will search for gene expression signatures that are associated with cachexia and generate a differential co-expression network. These findings will improve our understanding of the etiology and epidemiology of cachexia in COPD. This will be the first step in a long term plan to probe the cachexia network medicine landscape of complex diseases including COPD, CHF, cancer and AIDS.