ArticleAlzheimer's research & therapy2025
Benchmarking Alzheimer's disease prediction: personalised risk assessment using polygenic risk scores across various methodologies and genome-wide studies.
Article in Alzheimer's research & therapy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- A multiancestry polygenic risk score for Alzheimer's disease is associated with cognitive decline and neuropathological hallmarks in diverse populations.Nature genetics · 2026Article
- Artificial Intelligence and Genomic Data Analysis: New Frontiers in Precision Medicine.International journal of molecular sciences · 2026Review
- Polygenic risk scores in neurological disorders: restless legs syndrome as a translational model.Medizinische Genetik : Mitteilungsblatt des Berufsverbandes Medizinische Genetik e.V · 2026Article
- Polygenic Risk Scores for Incident Dementia in the Multi-Ethnic Study of Atherosclerosis.Genetic epidemiology · 2026Article
- Downward bias in the association between APOE and Alzheimer's disease using prevalent and by-proxy disease sampling in the All of Us research program.BMC medical genomics · 2026Article
- Integrative machine learning approach to risk prediction for dementia and Alzheimer's disease.GeroScience · 2026Article
- Genetic risk in Alzheimer's disease.NPJ systems biology and applications · 2026Review
- Prediction of Episodic Memory With Multiomics Scores.Biological psychiatry global open science · 2026Article
- Toward personalized medicine in AD/ADRD through genetic-exposome dementia risk assessments.NPJ dementia · 2026Review
- A multi-ancestry polygenic risk score for Alzheimer disease is associated with cognitive decline, hippocampal atrophy and neuropathological hallmarks in diverse populations.medRxiv : the preprint server for health sciences · 2025Article
- Mitochondrial and ER stress crosstalk in TBI: mechanistic insights and therapeutic opportunities.Frontiers in cellular neuroscience · 2025Review
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11 authors.
Funding
Abstract
backgroundThe success of selecting high risk or early-stage Alzheimer's disease individuals for the delivery of clinical trials depends on the design and the appropriate recruitment of participants. Polygenic risk scores (PRS) show potential for identifying individuals at risk for Alzheimer's disease (AD). Our study comprehensively examines AD PRS utility using various methods and models.
methodsWe compared the PRS prediction accuracy in ADNI (N = 568) and BioFINDER (N = 766) cohorts using five disease risk modelling approaches, three PRS derivation methods, two AD genome-wide association study (GWAS) statistics and two sets of SNPs: the whole genome and microglia-selective regions only.
resultsThe best prediction accuracy was achieved when modelling genetic risk by using two predictors: APOE and remaining PRS (AUC = 0.72-0.76). Microglial PRS showed comparable accuracy to the whole genome (AUC = 0.71-0.74). The individuals' risk scores differed substantially, with the largest discrepancies (up to 70%) attributable to the GWAS statistics used.
conclusionsOur work benchmarks the best PRS derivation and modelling strategies for AD genetic prediction.
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