Genetic and modifiable risk factors combine multiplicatively in common disease

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.

A population-based heritability estimate of bipolar disorder - In a Swedish twin sample

Twin- and family studies have shown variations in the heritability estimates of bipolar disorder (BPD). The current study uses an updated statistical methodology for heritability estimation in BPD by taking available time of follow-up into account while controlling for co-variates. We identified monozygotic and dizygotic same and different sex twins with BPD (n = 804) or unaffected from BPD (n = 91,604) from the Swedish Twin Register and the National Patient Register. We applied structural equational modeling with inversed probability weighting to estimate the heritability, taking into account censoring and truncation of data. Sex-limitation models were constructed to analyze qualitative or quantitative sex-differences in BPD. Heritability for BPD was 60.4% (95% Confidence Interval: 50.3-70.5) after age, sex, left-hand truncation and censoring of the data was taken into account. A larger proportion of females were affected from BPD (females 62.2%; males 37.8%, p < 0.001), but no sex-difference in BPD heritability was found, nor any sex-specific genetic effects. We demonstrated a robust 60% heritability for BPD with no evidence of sex-specific genetic effects on disease liability.