Empirical evaluation of analytic validity of polygenic scores

T Lin; J Zeng; SD Gordon; L Wallace; L Ziser; S Shah; O Pain; IM Nolte; H Snieder; C Wijmenga; JM Vonk; MA Swertz; S Sanna; EA Lopera Maya; JA Kuivenhoven; L Franke; P Deelen; R Aguirre-Gamboa; PA James; NG Martin; PM Visscher; E Lee; L Yengo; AK Henders; NR Wray

Journal article

Empirical evaluation of analytic validity of polygenic scores

T Lin, J Zeng, SD Gordon, L Wallace, L Ziser, S Shah, O Pain, IM Nolte, H Snieder, C Wijmenga, JM Vonk, MA Swertz, S Sanna, EA Lopera Maya, JA Kuivenhoven, L Franke, P Deelen, R Aguirre-Gamboa, PA James, NG Martin Show all

Genome Medicine | Published : 2026

DOI: 10.1186/s13073-026-01654-6

Open access

Abstract

Background: Polygenic scores (PGSs) are weighted sum scores of trait-associated alleles from up to millions of SNPs. As PGS research pivots to translation into health care settings a key issue for laboratories providing PGS is demonstration of analytical validity of PGS. Methods: We report data from 6 individuals who have been genotyped multiple times using the same and different technologies. These data were generated as part of standard experimental design for quality control purposes in two research settings over many studies and over many years. Using this opportunistic design of technical variability, we provide an empirical evaluation of technical reproducibility of PGS from 115 traits..

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