Considering strategies for SNP selection in genetic and polygenic risk scores - St.-Pierre, Julien; Zhang, Xinyi; Lu, Tianyuan; Jiang, Lai; Loffree, Xavier; Wang, Linbo; Bhatnagar, Sahir; Greenwood, Celia M. T.; , CANSSI team on Improving Robust High-Dimensional Causal Inference and Prediction Modelling (Frontiers in Genetics, 2022)
Polygenic risk scores (PRS) are being increasingly discussed for clinical use, yet the best way to construct them is still actively debated. In this commentary, we present several case studies of the practical challenges associated with building PRS. We discuss ways of selecting single nucleotide polymorphisms (SNPs) for inclusion, and the potential for biased coefficients associated with these SNPs. By considering PRS from the point of view of a predictor that is measured with error, insight into its strengths and weaknesses may be obtained.