Document Type
Article
Department
Brain and Mind Institute
Abstract
INTRODUCTION Genome-wide association studies (GWAS) have identified 80+ genetic loci associated with Alzheimer's disease (AD), enabling the development of polygenic risk scores (PRS). However, the predictive accuracy of PRS in diverse populations remains low. Here, we evaluated the predictive accuracy of single-, multi-, and cross-ancestry AD-PRS models across multi-ancestral populations.
METHODS We used AD GWAS summary statistics from European, African, Admixed American, and East Asian populations to construct AD-PRS for each target population. Model performance was assessed by estimating odds ratios, R2, and area under the curve.
RESULTS The cross-ancestry Bayesian PRS model demonstrated the highest predictive performance in non-European populations. It was significantly associated with poorer cognitive function, lower Aβ42 cerebrospinal fluid levels, and the most severe category of Aβ and tau neuropathological burden.
DISCUSSION Inclusive genetic datasets and cross-ancestry PRS models are needed to enhance the transportability of AD-PRS across multi-ancestral populations.
Publication (Name of Journal)
Alzheimer's & dementia : the journal of the Alzheimer's Association
DOI
https://doi.org/10.1002/alz.71529
Recommended Citation
Okorie, M.,
Jonson, C.,
Oddi, A.,
Castruita, P.,
Fulton-Howard, B.,
Yaffe, K.,
Yokoyama, J.,
Momoh, C.,
Andrews, S.
(2026). Cross-ancestry polygenic risk scores enhance Alzheimer's disease risk prediction in multiethnic cohorts. Alzheimer's & dementia : the journal of the Alzheimer's Association, 22(8), 1-19.
Available at:
https://ecommons.aku.edu/bmi/517
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.