Abstract

Advances in genomic medicine have enabled the emergence of precision public health, with polygenic risk scores 
(PRS) offering novel tools for population-level risk stratification and intervention. Alzheimer’s disease (AD), the 
most prevalent neurodegenerative disorder globally, exhibits a polygenic architecture that can be quantified 
through PRS derived from genome-wide association studies (GWAS). PRS for AD facilitates the prediction of 
disease onset, cognitive decline, and identification of high-risk individuals, potentially informing early detection, 
prevention strategies, and resource allocation in public health. However, challenges persist, including limited 
validation across diverse populations, potential exacerbation of health inequities, data infrastructure and privacy 
concerns, integration into existing public health frameworks, and workforce capacity for implementation. Evidence 
highlights the need for population-specific PRS development, robust longitudinal studies, and equitable 
governance frameworks to maximize public health benefit while mitigating ethical, social, and economic risks. 
Strategic application of PRS in AD may enhance preventive interventions, optimize resource allocation, and 
support informed policymaking in precision public health.