A Novel Multimodal Approach to Characterize NAFLD Severity and Prognosis

项目总结 非酒精性脂肪性肝病(NAFLD)是导致肝硬变的一种越来越常见的原因，并有可能成为 美国肝移植的主要适应症。(1，2)非酒精性脂肪肝表现为一系列疾病 从孤立性脂肪变性到非酒精性脂肪性肝炎，这些脂肪变性预示着发病率很低 (NASH)，以炎症和细胞死亡为特征，有很大的进展为肝硬变的风险 和肝脏相关的死亡率。(3)不幸的是，肝脏活检仍然是准确区分 孤立的脂肪变性和NASH；然而，该过程是侵入性的，仍然不适用于扩大到 据估计，美国受影响的成年人人数为6000万。试图使用个人或小型 用于表征NAFLD风险的生物标志物组合在很大程度上并不成功，留下了巨大的 需要进行非侵入性风险分层。我的中心假设是可以确定NAFLD的不同亚型 使用先进的分析技术将多种非侵入性生物标志物、遗传和临床因素结合起来 用于高维数据。通过我与NIH资助的多中心NASH临床研究中心的合作 网络(Nash CRN)I研究了28个可能的血浆生物标记物与NAFLD组织学之间的关系 并发现少量的生物标记物在区分临床上有意义的疾病阶段方面是有限的。 组织学严重度。然而，通过应用一种新的统计技术，潜在类别分析(LCA)，我们生成了 初步数据确定与组织学密切相关的NAFLD患者亚组 严肃性。这一应用的研究目标是(1)结合临床和饮食因素、遗传标记和 一组扩展的血浆生物标记物，用于使用LCA精炼NAFLD的不同表型，(2)验证 LCA定义的表型与组织学严重程度之间的关系 已证实的NAFLD，(3)建立在现有纵向队列的基础上，并测试这些表型预测的能力 纤维化和炎症的进展。我的长期目标是将多式联运、非侵入式 NAFLD的生物标志物与先进的分析技术相结合，以实现个性化的管理和治疗 非酒精性脂肪肝患者。为了实现这一目标，我组建了一支出色的指导团队 包括我的主要导师罗希特·伦巴博士，他是国际知名的NAFLD专家和 加州大学圣迭戈分校NAFLD研究中心主任。此外，儿科科长阿里尔·费尔德斯坦博士 胃肠病学，以及将NAFLD病理生理学转化为生物标记物开发的专家将提供服务 作为共同导师。加州大学圣地亚哥分校临床和翻译研究中心生物统计学主任徐莉莉教授 将担任我的生物统计学导师。我们一起形成了一个四重职业发展计划，以获得 擅长(1)队列开发、生物库和先进的NAFLD表型，(2)统计分析 遗传和高维数据，(3)NAFLD病理生物学和生物标记物开发，以及(4)研究 在NAFLD的非侵入性评估中传播和发展国家认可。

PROJECT SUMMARY Nonalcoholic fatty liver disease (NAFLD) is an increasingly common cause of cirrhosis and on pace to be the leading indication for liver transplantation in the United States.(1, 2) NAFLD presents as a spectrum of disease ranging from isolated steatosis, which portends little risk of significant morbidity, to nonalcoholic steatohepatitis (NASH), which is characterized by inflammation and cell death and has substantial risk of progression to cirrhosis and liver-related mortality.(3) Unfortunately, liver biopsy remains the only way to accurately discriminate between isolated steatosis and NASH; however the procedure is invasive and remains impractical to scale to the estimated affected population of 60 million adults in the United States. Attempts to use individual or small combinations of biomarkers to characterize risk in NAFLD have been largely unsuccessful leaving a tremendous need for non-invasive risk stratification. My central hypothesis is that distinct subtypes of NAFLD can be identified by combining multiple non-invasive biomarkers, genetic and clinical factors using advanced analytic techniques for high dimensional data. Through my collaboration with the NIH-funded, multicenter NASH Clinical Research Network (NASH CRN) I explored the association between 28 putative plasma biomarkers and NAFLD histology and found that small sets of biomarkers were limited in discriminating between clinically significant stages of histologic severity. However, by applying a novel statistical technique, latent class analysis (LCA), we generated preliminary data identifying distinct subgroups of patients with NAFLD that are strongly associated with histologic severity. The research goal of this application is to (1) combine clinical and dietary factors, genetic markers and an expanded set of plasma biomarkers to refine distinct phenotypes of NAFLD using LCA, (2) validate the association between LCA defined phenotypes and histologic severity in an independent cohort with biopsy proven NAFLD, (3) build on an existing longitudinal cohort and test the ability of these phenotypes to predict progression of fibrosis and inflammation. My long-term goal is to combine expertise in multimodal, non-invasive biomarkers of NAFLD with advanced analytic techniques to personalize the management and treatment of patients with NAFLD. In order to accomplish this goal, I have assembled an exceptional mentorship team including my primary mentor, Dr. Rohit Loomba, who is an internationally renowned expert in NAFLD and Director of the UCSD NAFLD Research Center. In addition, Dr. Ariel Feldstein, Chief of the Division of Pediatric Gastroenterology, and an expert in translating NAFLD pathophysiology into biomarker development will serve as a co-mentor. Professor Lily Xu, biostatistical director of the UCSD Clinical and Translational Research Institute, will serve as my biostatistical mentor. Together, we formed a four-fold career development plan to gain expertise in (1) cohort development, biobanking and advanced NAFLD phenotyping, (2) statistical analysis of genetic and high dimensional data, (3) NAFLD pathobiology and biomarker development, and (4) research dissemination and the development of national recognition in the non-invasive assessment of NAFLD.