Determining the Influence of Clinicodemographic, Biologic and SDOH Factors in Racial and Ethnic Disparities in the Prognosis of Alcohol-Associated Liver Disease

项目摘要/摘要 酒精相关性肝病(ALD)是一个主要的公共卫生问题，也是最常见的死亡原因 死于美国的肝硬变。ALD对种族/少数民族的影响不成比例，西班牙裔和美国人 与非西班牙裔白人患者相比，印度患者的发病率和死亡率更高。我们的 对这些差异的理解是有限的，因为大多数关于ALD自然历史的数据来自欧洲，而大多数 预后研究侧重于饮酒者发生酒精性肝病的风险或严重酒精性酒精性肝病的短期预后。 此外，很少有研究研究临床人口学(例如代谢综合征)和社会因素 在已确诊的ALD患者中，健康决定因素(SDOH)影响患者的预后。尽管这种关联 遗传学(例如，PNPLA3)与发生ALD的风险继续引起人们的兴趣，很少有研究进行检查 遗传学如何影响ALD的预后。我的中心假设是独特的临床人口学、生物学和 SDOH因素导致ALD的预后和自然病程在种族和民族之间存在差异， 包括导致拉美裔和人工授精患者ALD进展的危险因素。由改编的沃内克指导 概念模型，我将梳理临床人口学的直接和间接影响(例如，种族/民族)， 生物学(例如，遗传学)和SDOH(例如，护理障碍)因素通过以下方式预测ALD 在种族、民族和社会经济多样化的队列中的具体目标：1)定义 临床人口学和SDOH因素与ALD严重程度的种族和民族差异；2)检查 遗传因素与ALD严重程度的相关性；3)建立ALD的多水平危险分层模型 预言。这些数据将为减少ALD差异的最有效的干预措施提供信息。PI是一种 德克萨斯大学西南分校的临床研究员和肝病专家，着眼于改善对患者的护理 与ALD的合作，包括解决差距问题。拟议的培训计划与研究目标和 建立在他现有的临床研究知识的基础上，他将获得先进的新的高级技能 定量分析、健康差异、遗传学、队列建设、调查方法、风险中的机器学习 预测。他组建了一支才华横溢的跨学科导师团队，与 专长：Mack Mitchell博士，经验丰富的研究员和ALD内容专家；Amit Singal博士，世界- 著名的卫生服务和差异研究人员；海伦·霍布斯博士，国际遗传学和 肝病专家金博士，定量分析专家张博士，科兹利蒂纳博士， 遗传统计专家；桑迪克·西博士，风险预测中机器学习的专家统计学家。这个 这项建议中的研究将对公共卫生产生重大影响，因为它们将填补我们在理解上的空白 关于ALD在种族/少数民族中的预后。该奖励和培训计划将为PI提供 受保护的时间、培训和指导，以建立一个独立资助的专注于改进的研究事业 ALD结果。

PROJECT SUMMARY / ABSTRACT Alcohol-associated liver disease (ALD) is a major public health problem and the most common cause of death from cirrhosis in the US. ALD disproportionately impacts racial/ethnic minorities, with Hispanic and American Indian patients having increased morbidity and mortality compared with non-Hispanic White patients. Our understanding of these disparities is limited as most data on ALD natural history comes from Europe, while most prognostic studies focus on either risk of developing ALD among drinkers or short-term prognosis in severe ALD. Moreover, few studies have examined how clinicodemographic (e.g., metabolic syndrome) and social determinants of health (SDOH) factors impact patient prognosis in established ALD. Although the association of genetics (e.g., PNPLA3) with risk of developing ALD continues to garner interest, few studies have examined how genetics impact ALD prognosis. My central hypothesis is that unique clinicodemographic, biologic and SDOH factors drive differences in the prognosis and natural history of ALD among racial and ethnic groups, including risk factors leading to progression of ALD among Hispanics and AIs. Guided by an adapted Warnecke conceptual model, I will disentangle direct and indirect effects of clinicodemographic (e.g, Race/ethnicity), biologic (e.g., genetics), and SDOH (e.g. barriers to care) factors on ALD prognostication through the following specific aims in a racially, ethnically, and socioeconomically diverse cohort: 1) Define the role of clinicodemographic and SDOH factors with racial and ethnic differences in ALD severity; 2) Examine the association of genetic factors and ALD severity; 3) Derive a multilevel risk stratification model for ALD prognostication. These data will inform the most impactful interventions to reduce disparities in ALD. The PI is a clinical researcher and hepatologist at UT Southwestern, with a long-term vision of improving care for patients with ALD, including tackling disparities. The proposed training plan is integrated with the research aims and builds on his existing knowledge in clinical research whereby he will acquire new, advanced skills in advanced quantitative analysis, health disparities, genetics, cohort building, survey methods, machine learning in risk prediction. He has assembled an exceptionally talented interdisciplinary team of mentors with complementary expertise: Dr. Mack Mitchell, an experienced researcher and ALD content expert; Dr. Amit Singal, a world- renowned health services and disparities researcher; Dr. Helen Hobbs, an international expert in genetics and liver disease; Dr. King, an expert in AUD; Dr. Zhang, an expert statistician in quantitative analyses; Dr. Kozlitina, an expert in genetic statistics; and Dr. Sandikçi, an expert statistician in machine learning in risk prediction. The research studies in this proposal have significant public health impact as they will fill gaps in our understanding of the prognosis of ALD among racial/ethnic minorities. This award and training plan will provide the PI with the protected time, training, and mentorship, to build an independently-funded research career focused on improving ALD outcomes.