Work

Genetic risk in Alzheimer’s disease

Year: 2026

Type: article

Abstract: Alzheimer's disease (AD) has a strong genetic predisposition. Genome-wide association studies have identified multiple risk loci, yet many non-coding variants remain uncharacterized. Machine learning-based polygenic risk scores (PRS) enhance prediction by modeling genetic epistasis and sex-specific risks. This review summarizes AD genetic risk factors, PRS methodologies, and ML-based AD risk prediction. It also highlights challenges such as population bias, functional validation, and integrating multi-omics for precision medicine.

Source: npj Systems Biology and Applications

DOI: 10.1038/s41540-026-00665-8

Authors: Yining Pan, Hwayoung Cho, Qian Lou, Wei Zhang, Breton Asken, Qianqian Song

Institutions: University of Florida Health, University of Florida, University of Central Florida

Language: English

Topic: Alzheimer's disease research and treatments

Subfield: Physiology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,490