Preprint Article Version 3 Preserved in Portico This version is not peer-reviewed

Clinical Relevance of Genome-Wide Polygenic Score may Be Less than Claimed

Version 1 : Received: 8 October 2018 / Approved: 9 October 2018 / Online: 9 October 2018 (04:53:13 CEST)
Version 2 : Received: 9 October 2018 / Approved: 10 October 2018 / Online: 10 October 2018 (05:31:10 CEST)
Version 3 : Received: 5 December 2018 / Approved: 6 December 2018 / Online: 6 December 2018 (07:06:32 CET)

A peer-reviewed article of this Preprint also exists.

Curtis, D. Clinical Relevance of Genome‐wide Polygenic Score May Be Less than Claimed. Annals of Human Genetics 2019, 83, 274–277, doi:10.1111/ahg.12302. Curtis, D. Clinical Relevance of Genome‐wide Polygenic Score May Be Less than Claimed. Annals of Human Genetics 2019, 83, 274–277, doi:10.1111/ahg.12302.

Abstract

A recent study claimed that genome-wide polygenic scores (GPSs) for five common diseases could identify individuals with risk equivalent to monogenic mutations. Receiver operator curve analyses were reported to have areas under the curve (AUCs) ranging from 0.63 for inflammatory bowel disease up to 0.81 for coronary artery disease (CAD) but these models also included age and sex, themselves strong predictors of risk. The GPS for CAD identified 8% of the population at threefold increased risk, which it was claimed was comparable to the excess risk from monogenic mutations. In the present study attempts were made to model the distribution of the GPS for CAD to match the information provided. These models were based on the reported distribution of prevalence by centile of GPS and on the distribution of GPS in controls and cases and were fitted to the reported results using linear approximations to the distributions and using simulations of a liability-threshold model. It was impossible to produce a compatible model in which the GPS produced an AUC as high as 0.81 and the most plausible estimate was that the true AUC was only 0.65. The reported distributions of the GPS in cases and controls overlap so much that they are not compatible with an AUC of 0.7 or higher. The AUC of the GPS for these diseases is modest. Furthermore, the literature robustly demonstrates that true CAD risk associated with monogenic mutations is much higher than the threefold increase which is predicted by the GPS. Together, these findings cast doubt on the clinical utility of the GPS.

Supplementary and Associated Material

https://github.com/davenomiddlenamecurtis/modelGPS: Code to model GPS distributions

Keywords

genome-wide polygenic score; coronary artery disease; AUC

Subject

Biology and Life Sciences, Biochemistry and Molecular Biology

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