Interaction of genetic susceptibility and traffic-related air pollution in cardiovascular disease

Abstract

This thesis aimed at investigating gene-environment interaction in cardiovascular disease (CVD). A study population of 618 coronary heart disease (CHD) cases (of which 192 first-time acute myocardial infarction (AMI) patients) and 3614 randomly selected population controls was genotyped for genetic variants in genes coding for nitric oxide synthase (NOS) and glutathione s-transferase (GST). Exposure to traffic-related air pollution was assessed using modeled mean annual concentrations of nitric dioxide (NO2) as a marker for long-term exposure. Among 58 single nucleotide polymorphisms (SNPs) in the NOS1, NOS2 and NOS3 genes investigated for risk of CHD and hypertension, several strong associations were found, some of which remained statistically significant after Bonferroni correction for multiple testing. The T-allele of NOS1 SNP rs3782218 was significantly associated with a protective effect for both CHD (odds ratio (OR) 0.6, 95% confidence interval (CI) 0.44-0.80) and hypertension (OR 0.8, 95% CI 0.68-0.97). A second study investigated SNPs in the genes GSTP1, GSTT1 and GSTCD for interaction with traffic-related air pollution on risk of AMI and hypertension. The risk of AMI from air pollution exposure seemed to vary by genotype strata (for example GSTP1 SNP rs596603 with OR 2.1, 95% CI 1.09-4.10 in the genotype TT+GT stratum; OR 1.4, 95% CI 0.73-2.68 in the genotype GG stratum, although the multiplicative interaction was not significant (p-value =0.27)). Finally, the methodology of estimating additive interaction between a dichotomous (e.g. genetic) variable and a continuous (e.g. air pollution) variable using output from a logistic regression model was investigated in detail. The measure of additive interaction in this setting was shown to be highly sensitive to variation in the parameters defining it, and a pragmatic proposal for controlling this variability when extending estimation of additive interaction to new settings was developed. The proposed method was applied to the GST genotype and air pollution exposure data to estimate the additive interaction of these exposures on risk of AMI, finding a sub-additive interaction effect for the GSTCD AG+GG genotype. To conclude, the results of this thesis indicate that NOS gene variants are associated with both CHD and hypertension, and that variants in the GST genes are of importance regarding the risk of hypertension and the risk of AMI due to air pollution exposure.