Combined Utility of 25 Disease and Risk Factor Polygenic Risk Scores for Stratifying Risk of All-Cause Mortality

Am J Hum Genet. 2020 Sep 3;107(3):418-431. doi: 10.1016/j.ajhg.2020.07.002. Epub 2020 Aug 5.

Abstract

While genome-wide association studies have identified susceptibility variants for numerous traits, their combined utility for predicting broad measures of health, such as mortality, remains poorly understood. We used data from the UK Biobank to combine polygenic risk scores (PRS) for 13 diseases and 12 mortality risk factors into sex-specific composite PRS (cPRS). These cPRS were moderately associated with all-cause mortality in independent data within the UK Biobank: the estimated hazard ratios per standard deviation were 1.10 (95% confidence interval: 1.05, 1.16) and 1.15 (1.10, 1.19) for women and men, respectively. Differences in life expectancy between the top and bottom 5% of the cPRS were estimated to be 4.79 (1.76, 7.81) years and 6.75 (4.16, 9.35) years for women and men, respectively. These associations were substantially attenuated after adjusting for non-genetic mortality risk factors measured at study entry (i.e., middle age for most participants). The cPRS may be useful in counseling younger individuals at higher genetic risk of mortality on modification of non-genetic factors.

Keywords: all-cause mortality; cause-specific mortality; genetic risk stratification; genome-wide association studies; lifestyle modification; polygenic risk scores.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biological Specimen Banks
  • Female
  • Genetic Diseases, Inborn / genetics
  • Genetic Diseases, Inborn / mortality*
  • Genetic Diseases, Inborn / pathology
  • Genetic Predisposition to Disease*
  • Genome-Wide Association Study
  • Humans
  • Male
  • Middle Aged
  • Multifactorial Inheritance / genetics*
  • Phenotype
  • Polymorphism, Single Nucleotide / genetics
  • Proportional Hazards Models
  • Risk Assessment / statistics & numerical data*
  • Risk Factors
  • United Kingdom