An alternative method of SNP inclusion to develop a generalized polygenic risk score analysis across Alzheimer's disease cohorts

Brookes, K.J. ORCID: 0000-0003-2427-2513, Guetta-Baranes, T., Thomas, A. and Morgan, K., 2023. An alternative method of SNP inclusion to develop a generalized polygenic risk score analysis across Alzheimer's disease cohorts. Frontiers in Dementia, 2: 1120206. ISSN 2813-3919

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Introduction: Polygenic risk scores (PRSs) have great clinical potential for detecting late-onset diseases such as Alzheimer's disease (AD), allowing the identification of those most at risk years before the symptoms present. Although many studies use various and complicated machine learning algorithms to determine the best discriminatory values for PRSs, few studies look at the commonality of the Single Nucleotide Polymorphisms (SNPs) utilized in these models.

Methods: This investigation focussed on identifying SNPs that tag blocks of linkage disequilibrium across the genome, allowing for a generalized PRS model across cohorts and genotyping panels. PRS modeling was conducted on five AD development cohorts, with the best discriminatory models exploring for a commonality of linkage disequilibrium clumps. Clumps that contributed to the discrimination of cases from controls that occurred in multiple cohorts were used to create a generalized model of PRS, which was then tested in the five development cohorts and three further AD cohorts.

Results: The model developed provided a discriminability accuracy average of over 70% in multiple AD cohorts and included variants of several well-known AD risk genes.

Discussion: A key element of devising a polygenic risk score that can be used in the clinical setting is one that has consistency in the SNPs that are used to calculate the score; this study demonstrates that using a model based on commonality of association findings rather than meta-analyses may prove useful.

Item Type: Journal article
Publication Title: Frontiers in Dementia
Creators: Brookes, K.J., Guetta-Baranes, T., Thomas, A. and Morgan, K.
Publisher: Frontiers Media SA
Date: 31 July 2023
Volume: 2
ISSN: 2813-3919
Rights: This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Divisions: Schools > School of Science and Technology
Record created by: Jonathan Gallacher
Date Added: 08 Aug 2023 09:20
Last Modified: 08 Aug 2023 09:20

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