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Integrating Genetics and Socio-Environmental Factors to Predict Disease Progression

Award Number: R00HG013969
ORGANIZATION: NATIONAL HUMAN GENOME RESEARCH INSTITUTE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 07/01/2025
PERIOD OF PERFORMANCE END DATE: 06/30/2029

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Integrating Genetics and Socio-Environmental Factors to Predict Disease Progression - Project Summary/Abstract Common, complex diseases evolve over time through interactions between genetic liability and socio-environmental exposures, shaping disease onset and progression. While polygenic risk scores (PRS) derived from genome-wide association studies (GWAS) have shown promise for population risk stratification, most existing models are based on static case-control outcomes and do not explicitly model the timing of disease onset or progression. This limits their utility for understanding disease trajectories and informing clinical decision-making. Advancing precision medicine requires moving beyond static risk prediction toward longitudinal models that capture how genetic and environmental factors jointly influence disease progression. During the K99 phase, I developed genome-wide survival study (GWSS) frameworks to model time-to-event (TTE) phenotypes and constructed phenome-wide TTE outcomes in large-scale, multi-ancestry biobanks. I established analytical pipelines for constructing and evaluating PRS for longitudinal outcomes and demonstrated their reproducibility across multiple cohorts. I also developed and applied gene-based rare variant association methods for TTE phenotypes, demonstrating the feasibility of identifying gene-level contributions to disease onset, and initiated harmonization of socio-environmental data across biobanks through collaborative efforts. The R00 phase will build on this foundation to develop integrated models of disease progression that jointly incorporate common and rare genetic variation with socio-environmental factors. Specifically, this project will: (1) extend GWSS-derived PRS to model disease onset and progression across multiple genetic ancestry groups; (2) incorporate gene-level rare variant signals into polygenic prediction models to capture genetic effects across the allele-frequency spectrum; and (3) integrate socio-environmental factors with genetic predictors using scalable representations of exposure data to model context-dependent disease risk. These approaches will be evaluated across multiple large biobanks to assess predictive performance, generalizability, and clinical relevance. This work will advance precision medicine by enabling more accurate, interpretable, and generalizable prediction of disease progression. By integrating genetic and socio-environmental determinants of health within a unified framework, this project will provide new insights into how disease trajectories are shaped across populations and support the development of more targeted prevention and intervention strategies.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2026 ( Subtotal = $249,000 )
2026	2026	OHIO STATE UNIVERSITY, THE	1960 KENNY RD	COLUMBUS	OH	43210	FRANKLIN	USA	Human Genome Research	000	2	9/2/2026	EXTENSION WITH OR WITHOUT FUNDS	$249,000
														Subtotal = $249,000

Grand Total All Awards = $249,000

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Integrating Genetics and Socio-Environmental Factors to Predict Disease Progression

Award Number: R00HG013969

ORGANIZATION: NATIONAL HUMAN GENOME RESEARCH INSTITUTE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 07/01/2025

PERIOD OF PERFORMANCE END DATE: 06/30/2029

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