| Application: | 17712, Assesments of Joint Effect of Polygenic Disease-risk Scores and Modifiable Risk-factors on Major Chronic diseases and Mortality |
| Title: | Combined Utility of 25 Disease and Risk Factor Polygenic Risk Scores for Stratifying Risk of All-Cause Mortality |
| Size: | 45.5 MB |
| Archived: | 6 Apr 2021 |
| Stability: | Complete |
| Personal: | Contains individual-level data |
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Notes
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.Application 17712
Assesments of Joint Effect of Polygenic Disease-risk Scores and Modifiable Risk-factors on Major Chronic diseases and Mortality
The aim of the research is to use data from UK Biobank prospective cohort study to estimate joint risk of multiple common disease conditions, including cancer, type-2 diabetes, cardiovascular diseases, and overall mortality, associated with GWAS generated polygenic disease-risk scores and modifiable risk-factors such as smoking, BMI, alcohol and physical activity. The analysis will allow understanding of how the potential impact intervention on modifiable risk-factors, may or may not vary by individual's genetic risk-profiles. The proposed research will generate valuable information regarding whether genetic information could be useful for targeting certain primary prevention efforts for risk-factor intervention that cannot be applied to the general population for cost and other burdens. For subjects in the UK Biobank cohort, polygenic risk-score (PRS) for major chronic diseases will be constructed based on published literature on susceptibility SNPs and their disease odds-ratios. Data from UK Biobank will be then used to estimate absolute risk of different disease endpoints and mortality in population strata defined by polygenic risk scores and modifiable risk-factors. For evaluating combined endpoint like overall mortality or overall cancer incidence, the disease-specific PRSs will be combined to form a composite PRS. Further, to understand the potential causal effect of intervention of modifiable risk-factors, like BMI, a Mendelian Randomization approach will be used to estimate absolute risk-reduction parameters associated with BMI for the different outcomes within strata defined by the disease associated PRS variables. These `instrumental` variable derived absolute-risk reduction parameters will then be then compared with more direct epidemiological estimate of the same parameters for the assessment of consistency of results across two types of analyses. All subjects in the full cohort with or without genotype data
| Lead investigator: | Professor Nilanjan Chatterjee |
| Lead institution: | Johns Hopkins University |
1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 3285 | Combined Utility of 25 Disease and Risk Factor Polygenic Risk Scores for Stratifying Risk of All-Cause Mortality | Allison Meisner (+10) | 2020 | American Journal of Human Genetics |
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