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Considering strategies for SNP selection in genetic and polygenic risk scores

Authors :
Julien St.-Pierre
Xinyi Zhang
Tianyuan Lu
Lai Jiang
Xavier Loffree
Linbo Wang
Sahir Bhatnagar
Celia M. T. Greenwood
CANSSI team on Improving Robust High-Dimensional Causal Inference and Prediction Modelling
Source :
Frontiers in Genetics, Vol 13 (2022)
Publication Year :
2022
Publisher :
Frontiers Media S.A., 2022.

Abstract

Genetic risk scores (GRS) and polygenic risk scores (PRS) are weighted sums of, respectively, several or many genetic variant indicator variables. Although they are being increasingly proposed for clinical use, the best ways to construct them are still actively debated. In this commentary, we present several case studies illustrating practical challenges associated with building or attempting to improve score performance when there is expected to be heterogeneity of disease risk between cohorts or between subgroups of individuals. Specifically, we contrast performance associated with several ways of selecting single nucleotide polymorphisms (SNPs) for inclusion in these scores. By considering GRS and PRS as predictors that are measured with error, insights into their strengths and weaknesses may be obtained, and SNP selection approaches play an important role in defining such errors.

Details

Language :
English
ISSN :
16648021
Volume :
13
Database :
Directory of Open Access Journals
Journal :
Frontiers in Genetics
Publication Type :
Academic Journal
Accession number :
edsdoj.345a6abfddbc4b3a8e1fb671c79343e4
Document Type :
article
Full Text :
https://doi.org/10.3389/fgene.2022.900595