Genetic and modifiable risk factors combine multiplicatively in common disease
Original Paper
0303 health sciences
Coronary Artery Disease
Polymorphism, Single Nucleotide
United Kingdom
ddc:
3. Good health
03 medical and health sciences
Risk Factors
Prevalence
Humans
Genetic Predisposition to Disease
Gene-Environment Interaction
Original Paper ; Coronary artery disease ; Genome-wide association studies ; Risk prediction ; Risk score ; Liability threshold ; Medical and Health Sciences
Alleles
Genome-Wide Association Study
DOI:
10.1007/s00392-022-02081-4
Publication Date:
2022-08-20T16:02:44Z
AUTHORS (15)
ABSTRACT
Abstract
Background
The joint contribution of genetic and environmental exposures to noncommunicable diseases is not well characterized.
Objectives
We modeled the cumulative effects of common risk alleles and their prevalence variations with classical risk factors.
Methods
We analyzed mathematically and statistically numbers and effect sizes of established risk alleles for coronary artery disease (CAD) and other conditions.
Results
In UK Biobank, risk alleles counts in the lowest (175.4) and highest decile (205.7) of the distribution differed by only 16.9%, which nevertheless increased CAD prevalence 3.4-fold (p < 0.01). Irrespective of the affected gene, a single risk allele multiplied the effects of all others carried by a person, resulting in a 2.9-fold stronger effect size in the top versus the bottom decile (p < 0.01) and an exponential increase in risk (R > 0.94). Classical risk factors shifted effect sizes to the steep upslope of the logarithmic function linking risk allele numbers with CAD prevalence. Similar phenomena were observed in the Estonian Biobank and for risk alleles affecting diabetes mellitus, breast and prostate cancer.
Conclusions
Alleles predisposing to common diseases can be carried safely in large numbers, but few additional ones lead to sharp risk increments. Here, we describe exponential functions by which risk alleles combine interchangeably but multiplicatively with each other and with modifiable risk factors to affect prevalence. Our data suggest that the biological systems underlying these diseases are modulated by hundreds of genes but become only fragile when a narrow window of total risk, irrespective of its genetic or environmental origins, has been passed.
Graphical Abstract
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