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. 2023 Dec;19(12):5690-5699.
doi: 10.1002/alz.13319. Epub 2023 Jul 6.

A simulative deep learning model of SNP interactions on chromosome 19 for predicting Alzheimer's disease risk and rates of disease progression

Jinhyeong Bae  1 , Paige E Logan  1 , Dominic J Acri  2 , Apoorva Bharthur  1 , Kwangsik Nho  3 , Andrew J Saykin  3 , Shannon L Risacher  3 , Kelly Nudelman  2 , Angelina J Polsinelli  1 , Valentin Pentchev  4 , Jungsu Kim  2 , Dustin B Hammers  1 , Liana G Apostolova  1   2   3 ; Alzheimer's Disease Neuroimaging Initiative
Affiliations

A simulative deep learning model of SNP interactions on chromosome 19 for predicting Alzheimer's disease risk and rates of disease progression

Jinhyeong Bae et al. Alzheimers Dement. 2023 Dec.

Abstract

Background: Identifying genetic patterns that contribute to Alzheimer's disease (AD) is important not only for pre-symptomatic risk assessment but also for building personalized therapeutic strategies.

Methods: We implemented a novel simulative deep learning model to chromosome 19 genetic data from the Alzheimer's Disease Neuroimaging Initiative and the Imaging and Genetic Biomarkers of Alzheimer's Disease datasets. The model quantified the contribution of each single nucleotide polymorphism (SNP) and their epistatic impact on the likelihood of AD using the occlusion method. The top 35 AD-risk SNPs in chromosome 19 were identified, and their ability to predict the rate of AD progression was analyzed.

Results: Rs561311966 (APOC1) and rs2229918 (ERCC1/CD3EAP) were recognized as the most powerful factors influencing AD risk. The top 35 chromosome 19 AD-risk SNPs were significant predictors of AD progression.

Discussion: The model successfully estimated the contribution of AD-risk SNPs that account for AD progression at the individual level. This can help in building preventive precision medicine.

Keywords: Alzheimer's disease; deep learning; genetics.

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Conflict of interest statement

Conflicts of Interest

We have no conflicts of interest to disclose. Please refer ICMJE forms for detailed information.

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