Long-term exposure to road traffic noise, ambient air pollution, and cardiovascular risk factors in the HUNT and lifelines cohorts

Aims: Blood biochemistry may provide information on associations between road traffic noise, air pollution, and cardiovascular disease risk. We evaluated this in two large European cohorts (HUNT3, Lifelines). Methods and results: Road traffic noise exposure was modelled for 2009 using a simplified version of the Common Noise Assessment Methods in Europe (CNOSSOS-EU). Annual ambient air pollution (PM10, NO2) at residence was estimated for 2007 using a Land Use Regression model. The statistical platform DataSHIELD was used to pool data from 144 082 participants aged ≥20 years to enable individual-level analysis. Generalized linear models were fitted to assess cross-sectional associations between pollutants and high-sensitivity C-reactive protein (hsCRP), blood lipids and for (Lifelines only) fasting blood glucose, for samples taken during recruitment in 2006-2013. Pooling both cohorts, an inter-quartile range (IQR) higher day-time noise (5.1 dB(A)) was associated with 1.1% [95% confidence interval (95% CI: 0.02-2.2%)] higher hsCRP, 0.7% (95% CI: 0.3-1.1%) higher triglycerides, and 0.5% (95% CI: 0.3-0.7%) higher high-density lipoprotein (HDL); only the association with HDL was robust to adjustment for air pollution. An IQR higher PM10 (2.0 µg/m3) or NO2 (7.4 µg/m3) was associated with higher triglycerides (1.9%, 95% CI: 1.5-2.4% and 2.2%, 95% CI: 1.6-2.7%), independent of adjustment for noise. Additionally for NO2, a significant association with hsCRP (1.9%, 95% CI: 0.5-3.3%) was seen. In Lifelines, an IQR higher noise (4.2 dB(A)) and PM10 (2.4 µg/m3) was associated with 0.2% (95% CI: 0.1-0.3%) and 0.6% (95% CI: 0.4-0.7%) higher fasting glucose respectively, with both remaining robust to adjustment for air/noise pollution. Conclusion: Long-term exposures to road traffic noise and ambient air pollution were associated with blood biochemistry, providing a possible link between road traffic noise/air pollution and cardio-metabolic disease risk

Effects of the coronary artery disease associated LPA and 9p21 loci on risk of aortic valve stenosis

BACKGROUND: Aortic valve stenosis (AVS) and coronary artery disease (CAD) have a significant genetic contribution and commonly co-exist. To compare and contrast genetic determinants of the two diseases, we investigated associations of the LPA and 9p21 loci, i.e. the two strongest CAD risk loci, with risk of AVS. METHODS: We genotyped the CAD-associated variants at the LPA (rs10455872) and 9p21 loci (rs1333049) in the GeneCAST (Genetics of Calcific Aortic STenosis) Consortium and conducted a meta-analysis for their association with AVS. Cases and controls were stratified by CAD status. External validation of findings was undertaken in five cohorts including 7880 cases and 851,152 controls. RESULTS: In the meta-analysis including 4651 cases and 8231 controls the CAD-associated allele at the LPA locus was associated with increased risk of AVS (OR 1.37; 95%CI 1.24-1.52, p = 6.9 × 10-10) with a larger effect size in those without CAD (OR 1.53; 95%CI 1.31-1.79) compared to those with CAD (OR 1.27; 95%CI 1.12-1.45). The CAD-associated allele at 9p21 was associated with a trend towards lower risk of AVS (OR 0.93; 95%CI 0.88-0.99, p = 0.014). External validation confirmed the association of the LPA risk allele with risk of AVS (OR 1.37; 95%CI 1.27-1.47), again with a higher effect size in those without CAD. The small protective effect of the 9p21 CAD risk allele could not be replicated (OR 0.98; 95%CI 0.95-1.02). CONCLUSIONS: Our study confirms the association of the LPA locus with risk of AVS, with a higher effect in those without concomitant CAD. Overall, 9p21 was not associated with AVS

Genetic diversity fuels gene discovery for tobacco and alcohol use

Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury1–4. These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries5. Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction