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

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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.