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

> **NIH NIH K23** · UT SOUTHWESTERN MEDICAL CENTER · 2024 · $193,288

## Abstract

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 ...

## Key facts

- **NIH application ID:** 10930163
- **Project number:** 5K23AA031310-02
- **Recipient organization:** UT SOUTHWESTERN MEDICAL CENTER
- **Principal Investigator:** Thomas Gerard Cotter
- **Activity code:** K23 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $193,288
- **Award type:** 5
- **Project period:** 2023-09-20 → 2028-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10930163

## Citation

> US National Institutes of Health, RePORTER application 10930163, Determining the Influence of Clinicodemographic, Biologic and SDOH Factors in Racial and Ethnic Disparities in the Prognosis of Alcohol-Associated Liver Disease (5K23AA031310-02). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10930163. Licensed CC0.

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