Genotyping TOMM40′523 poly-T polymorphisms using whole-genome sequencing

Summary: The TOMM40′523 poly-T repeat polymorphism (rs10524523) has been associated with cognitive decline and Alzheimer's disease (AD) progression. Challenges in processing whole-genome sequencing (WGS) data traditionally require additional PCR and targeted sequencing assays to genotype these...

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Bibliographic Details
Main Authors: Ricardo A. Vialle, Lei Yu, Yan Li, Roberto T. Raittz, Jose M. Farfel, Philip L. De Jager, Julie A. Schneider, Lisa L. Barnes, Shinya Tasaki, David A. Bennett
Format: Article
Language:English
Published: Elsevier 2025-10-01
Series:HGG Advances
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Online Access:http://www.sciencedirect.com/science/article/pii/S2666247725000910
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Summary:Summary: The TOMM40′523 poly-T repeat polymorphism (rs10524523) has been associated with cognitive decline and Alzheimer's disease (AD) progression. Challenges in processing whole-genome sequencing (WGS) data traditionally require additional PCR and targeted sequencing assays to genotype these polymorphisms. We introduce a computational pipeline that integrates multiple short tandem repeat (STR) detection tools in an ensemble machine learning model using XGBoost. Using a sample of 1,202 participants from 4 cohort studies, we benchmarked our method against PCR-based measures. Our ensemble model outperformed individual STR tools, improving repeat length estimation accuracy (R2 = 0.92) and achieving an accuracy rate of 93.2% compared with PCR-derived genotypes. Additionally, we validated our WGS-derived genotypes by replicating previously reported associations between TOMM40′523 variants and cognitive decline. Our computational genotyping tool is a scalable and reliable alternative to PCR-based assays, enabling broader investigations of TOMM40 variation in studies with WGS data.
ISSN:2666-2477