Determining the Influence of Clinicodemographic, Biologic and SDOH Factors in Racial and Ethnic Disparities in the Prognosis of Alcohol-Associated Liver Disease - Alcohol-associated liver disease (ALD) is a major public health problem and the most common cause of death from cirrhosis in the United States. Despite the high burden of disease, major gaps remain in understanding the natural history of ALD in contemporary U.S. populations. Most data on ALD progression come from European cohorts, while prognostic studies have largely focused on either the risk of developing ALD among drinkers or short-term prognosis in severe ALD. Few studies have comprehensively examined long-term outcomes and the clinical, metabolic, and biological factors that influence prognosis once ALD is established. Although genetic variation (e.g., PNPLA3) has been implicated in risk for developing ALD, less is known about how genetics influence disease progression and outcomes after diagnosis. Similarly, the contributions of patient-level clinical features such as metabolic syndrome, alcohol use patterns, and comorbidities to heterogeneity in ALD progression are incompletely defined. The central hypothesis of this proposal is that a combination of clinical, behavioral, and biological factors underlie the variability in natural history and outcomes among patients with ALD. To test this hypothesis, I will leverage a well-characterized U.S. cohort to pursue the following specific aims: 1) Define the role of clinical and behavioral factors in ALD severity and prognosis; 2) Examine the association of genetic factors with ALD progression. 3) Derive a multilevel risk stratification model to improve prognostication in ALD. This research will establish a comprehensive natural history framework for ALD in the U.S., identify predictors of progression, and support the development of risk stratification tools that can directly inform clinical care and clinical trial design. The PI is a clinical researcher and hepatologist at UT Southwestern with a long-term vision of improving care for patients with ALD through rigorous clinical and translational research. The proposed training plan is integrated with the research aims and builds on his existing expertise in clinical research, while providing advanced training in quantitative analysis, genetics, cohort building, survey methods, and machine learning for 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 researcher; Dr. Helen Hobbs, an international expert in genetics and liver disease; Dr. King, an expert in alcohol use disorder; Dr. Zhang, an expert in quantitative analyses; Dr. Kozlitina, an expert in genetic statistics; and Dr. Sandikçi, an expert in machine learning and risk prediction. The proposed studies have significant public health impact as they will fill critical gaps in our understanding of the natural history and prognosis of ALD. This award and training plan will provide the PI with the protected time, advanced skills, and mentorship necessary to develop into an independent investigator focused on improving outcomes for patients with ALD.
