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Polygenic Risk Scores for Incident Dementia in the Multi-Ethnic Study of Atherosclerosis.

Polygenic Risk Scores for Incident Dementia in the Multi-Ethnic Study of Atherosclerosis.

期刊: Genetic epidemiology 日期: 2026-07-01 PMID: 42334086 DOI: 10.1002/gepi.70046 浏览: 40
作者: Xue D, Blue EE, Sofer T, Hughes TM, Rotter JI, Post WS, Fohner AE
D, X., EE, B., T, S., TM, H., JI, R., WS, P., & AE, F. (2026). Polygenic Risk Scores for Incident Dementia in the Multi-Ethnic Study of Atherosclerosis.. Genetic epidemiology. https://doi.org/10.1002/gepi.70046
D X, EE B, T S, TM H, JI R, WS P, et al. Polygenic Risk Scores for Incident Dementia in the Multi-Ethnic Study of Atherosclerosis.. Genetic epidemiology. 2026; doi: 10.1002/gepi.70046
D X, EE B, T S, et al. Polygenic Risk Scores for Incident Dementia in the Multi-Ethnic Study of Atherosclerosis.[J]. Genetic epidemiology. 2026. DOI: 10.1002/gepi.70046.
@article{d2026,
  author = {Xue D and Blue EE and Sofer T and Hughes TM and Rotter JI and Post WS and Fohner AE},
  title = {Polygenic Risk Scores for Incident Dementia in the Multi-Ethnic Study of Atherosclerosis.},
  journal = {Genetic epidemiology},
  year = {2026},
  doi = {10.1002/gepi.70046},
  note = {PMID: 42334086},
}
TY  - JOUR
AU  - Xue D
AU  - Blue EE
AU  - Sofer T
AU  - Hughes TM
AU  - Rotter JI
AU  - Post WS
AU  - Fohner AE
TI  - Polygenic Risk Scores for Incident Dementia in the Multi-Ethnic Study of Atherosclerosis.
T2  - Genetic epidemiology
PY  - 2026
DO  - 10.1002/gepi.70046
AN  - PMID:42334086
ER  - 

摘要

Over 75 Alzheimer's disease (AD) and dementia-associated variants have been identified through genome-wide association studies, but the utility of polygenic risk scores (PRS) for predicting AD and dementia in diverse and admixed populations remains unclear. We compared how PRS approaches differing in p-value thresholds, variant weights, and source ancestry perform in predicting dementia in 6338 African American, Chinese, Hispanic, and White individuals from the Multi-Ethnic Study of Atherosclerosis. We tested clumping and thresholding (C+T) methods with varying parameters against Bayesian approaches (PRS-CS, PRS-CSx). We compared the ability of each method to predict incident dementia in all participants and in groups stratified by self-reported race/ethnicity. We additionally analyzed performance across groups stratified by estimated proportion of non-Finnish European (NFE)-like ancestry. Including more variants does not improve performance. We found comparable associations between dementia and PRS when comparing a C+T method with only 15 SNPs and PRS derived from Bayesian models that include > 800,000 SNPs (HR5e-08 = 1.18, 95% CI: 1.08-1.28; HRCSx = 1.17, 95% CI: 1.07-1.27). The p < 5e-08 C+T method was more strongly associated with incident dementia in populations genetically dissimilar from the source data (HRlowNFE_5e-08 = 1.27, 95% CI: 1.08-1.50; HRlowNFE_CSx = 1.12, 95% CI: 0.94-1.33). More selective PRS models using genome-wide significant SNPs may be preferable for dementia prediction in diverse populations.

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