Genetic risk in Alzheimer's disease
Yining Pan1, Hwayoung Cho2, Qian Lou3
1Department of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, FL, USA.
None:
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.
Related Concept Videos
Alzheimer's Disease: Overview
The clinical diagnosis of AD hinges on the presence of memory and other cognitive impairments. Biomarkers, such as changes in Aβ and tau...
Alzheimer's Disease: Treatment
Pharmacogenomics: Identification of New Drug Targets
Human Genetics
The complex relationship between genetics and psychology is observable through common biological components such...
Alzheimer Disease l: Introduction
Alzheimer Disease ll: Pathophysiology
