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Background <p>The use of polygenic risk scores (PRS) for predicting disease risk in Japanese populations, particularly for dementia and related phenotypes, remains markedly unexplored. The aim of this study was to bridge this gap by developing a novel PRS model designed to predict amyloid-β (Aβ) deposition utilizing positron emission tomography (PET) imaging data from a Japanese cohort.</p> Methods <p>Using the polygenic risk score-continuous shrinkage (PRS-CS) algorithm, we calculated PRS based on significant single nucleotide polymorphisms (SNPs) associated with Alzheimer’s disease (AD) in this population. We applied a PRS calculation approach informed by Japanese genome-wide association studies (GWAS) summary statistics into a Japanese dementia cohort from Keio University.</p> Results <p>Our findings revealed that a <i>p</i>-value threshold of pT &lt; 0.1 optimally enhanced the predictive capability of the Japanese Aβ PET positivity risk model. Moreover, we demonstrated that distinguishing between the counts of APOE2 and APOE4 alleles in our calculations significantly elevated model performance, achieving an area under the curve (AUC) of 0.759. Remarkably, this predictive accuracy remained robust even when the pT was adjusted to be &lt; 1.0 × 10<sup>− 5</sup>, maintaining an AUC of 0.735. This study validated the efficacy of the model in identifying individuals with a increased risk of amyloid pathology.</p> Conclusions <p>These findings highlight the potential of PRS as a noninvasive tool for early detection and risk stratification of AD, which could lead to enhanced clinical applications and interventions.</p>

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Development of a Japanese polygenic risk score model for amyloid-β PET imaging in Alzheimer’s disease

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  • 发表日期：

    2025年5月22日

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  • Misato Kaishima,
  • Junichi Ito,
  • Kentaro Takahashi,
  • Kenji Tai,
  • Junro Kuromitsu,
  • Shogyoku Bun,
  • Daisuke Ito

摘要

Background

The use of polygenic risk scores (PRS) for predicting disease risk in Japanese populations, particularly for dementia and related phenotypes, remains markedly unexplored. The aim of this study was to bridge this gap by developing a novel PRS model designed to predict amyloid-β (Aβ) deposition utilizing positron emission tomography (PET) imaging data from a Japanese cohort.

Methods

Using the polygenic risk score-continuous shrinkage (PRS-CS) algorithm, we calculated PRS based on significant single nucleotide polymorphisms (SNPs) associated with Alzheimer’s disease (AD) in this population. We applied a PRS calculation approach informed by Japanese genome-wide association studies (GWAS) summary statistics into a Japanese dementia cohort from Keio University.

Results

Our findings revealed that a p-value threshold of pT < 0.1 optimally enhanced the predictive capability of the Japanese Aβ PET positivity risk model. Moreover, we demonstrated that distinguishing between the counts of APOE2 and APOE4 alleles in our calculations significantly elevated model performance, achieving an area under the curve (AUC) of 0.759. Remarkably, this predictive accuracy remained robust even when the pT was adjusted to be < 1.0 × 10− 5, maintaining an AUC of 0.735. This study validated the efficacy of the model in identifying individuals with a increased risk of amyloid pathology.

Conclusions

These findings highlight the potential of PRS as a noninvasive tool for early detection and risk stratification of AD, which could lead to enhanced clinical applications and interventions.