Large uncertainty in individual polygenic risk score estimation impacts PRS-based risk stratification

Yi Ding; Kangcheng Hou; Kathryn S Burch; Sandra Lapinska; Florian Privé; Bjarni Vilhjálmsson; Sriram Sankararaman; Bogdan Pasaniuc

doi:10.1038/s41588-021-00961-5

Large uncertainty in individual polygenic risk score estimation impacts PRS-based risk stratification

Nat Genet. 2022 Jan;54(1):30-39. doi: 10.1038/s41588-021-00961-5. Epub 2021 Dec 20.

Authors

Yi Ding^#¹, Kangcheng Hou^#², Kathryn S Burch³, Sandra Lapinska³, Florian Privé⁴, Bjarni Vilhjálmsson⁴, Sriram Sankararaman^{3

5

6

7}, Bogdan Pasaniuc^{8

9

10

11}

Affiliations

¹ Bioinformatics Interdepartmental Program, University of California, Los Angeles (UCLA), Los Angeles, CA, USA. yiding920@ucla.edu.
² Bioinformatics Interdepartmental Program, University of California, Los Angeles (UCLA), Los Angeles, CA, USA. houkc@ucla.edu.
³ Bioinformatics Interdepartmental Program, University of California, Los Angeles (UCLA), Los Angeles, CA, USA.
⁴ Department of Economics and Business Economics, National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark.
⁵ Department of Computer Science, UCLA, Los Angeles, CA, USA.
⁶ Department of Computational Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
⁷ Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
⁸ Bioinformatics Interdepartmental Program, University of California, Los Angeles (UCLA), Los Angeles, CA, USA. pasaniuc@ucla.edu.
⁹ Department of Computational Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA. pasaniuc@ucla.edu.
¹⁰ Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA. pasaniuc@ucla.edu.
¹¹ Department of Pathology and Laboratory Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA. pasaniuc@ucla.edu.

^# Contributed equally.

Abstract

Although the cohort-level accuracy of polygenic risk scores (PRSs)-estimates of genetic value at the individual level-has been widely assessed, uncertainty in PRSs remains underexplored. In the present study, we show that Bayesian PRS methods can estimate the variance of an individual's PRS and can yield well-calibrated credible intervals via posterior sampling. For 13 real traits in the UK Biobank (n = 291,273 unrelated 'white British'), we observe large variances in individual PRS estimates which impact interpretation of PRS-based stratification; averaging across traits, only 0.8% (s.d. = 1.6%) of individuals with PRS point estimates in the top decile have corresponding 95% credible intervals fully contained in the top decile. We provide an analytical estimator for the expectation of individual PRS variance as a function of SNP heritability, number of causal SNPs and sample size. Our results showcase the importance of incorporating uncertainty in individual PRS estimates into subsequent analyses.

Publication types

Research Support, N.I.H., Extramural

MeSH terms

Genetic Association Studies
Genetic Predisposition to Disease*
Genome-Wide Association Study
Humans
Models, Genetic
Models, Statistical
Multifactorial Inheritance*
Risk Assessment*
Uncertainty*

Abstract

Publication types

MeSH terms

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