Ambient Air Pollutants and Traffic Factors Were Associated with Blood and Urine Biomarkers and Asthma Risk.

The UK Biobank (UKBB) is a large population-based cohort that provides a unique opportunity to study the association between environmental exposure and biomarkers and to identify biomarkers as potential instruments for assessing exposure dose, health damage, and disease risks. On 462 063 participants of European ancestry, we characterized the relationship of 38 disease-relevant biomarkers, asthma diagnosis, ambient pollution, traffic factors, and genetic background. The air pollutant exposure on the UKBB cohort was fairly low (e.g., mean PM2.5 concentration at 10.0 µg/m3). Nevertheless, 30 biomarkers were in association with at least one environmental factor; e.g., C-reactive protein levels were positively associated with NO (padj = 2.99 × 10-4), NO2 (padj = 4.15 × 10-4), and PM2.5 (padj = 1.92 × 10-6) even after multiple testing adjustment. Asthma diagnosis was associated with four pollutants (NO, NO2, PM2.5, and PM10). The largest effect size was observed in PM2.5, where a 5 µg/m3 increment of exposure was associated with a 1.52 increase in asthma diagnosis (p = 4.41 × 10-13). Further, environmental exposure and genetic predisposition influenced biomarker levels and asthma diagnosis in an additive model. The exposure-biomarker associations identified in this study could serve as potential indicators for environmental exposure induced health damages. Our results also shed light on possible mechanisms whereby environmental exposure influences disease-causing biomarkers and in turn increases disease risk.

Radiogenomics Consortium Genome-Wide Association Study Meta-Analysis of Late Toxicity After Prostate Cancer Radiotherapy.

BACKGROUND: A total of 10%-20% of patients develop long-term toxicity following radiotherapy for prostate cancer. Identification of common genetic variants associated with susceptibility to radiotoxicity might improve risk prediction and inform functional mechanistic studies. METHODS: We conducted an individual patient data meta-analysis of six genome-wide association studies (n = 3871) in men of European ancestry who underwent radiotherapy for prostate cancer. Radiotoxicities (increased urinary frequency, decreased urinary stream, hematuria, rectal bleeding) were graded prospectively. We used grouped relative risk models to test associations with approximately 6 million genotyped or imputed variants (time to first grade 2 or higher toxicity event). Variants with two-sided Pmeta less than 5 × 10-8 were considered statistically significant. Bayesian false discovery probability provided an additional measure of confidence. Statistically significant variants were evaluated in three Japanese cohorts (n = 962). All statistical tests were two-sided. RESULTS: Meta-analysis of the European ancestry cohorts identified three genomic signals: single nucleotide polymorphism rs17055178 with rectal bleeding (Pmeta = 6.2 × 10-10), rs10969913 with decreased urinary stream (Pmeta = 2.9 × 10-10), and rs11122573 with hematuria (Pmeta = 1.8 × 10-8). Fine-scale mapping of these three regions was used to identify another independent signal (rs147121532) associated with hematuria (Pconditional = 4.7 × 10-6). Credible causal variants at these four signals lie in gene-regulatory regions, some modulating expression of nearby genes. Previously identified variants showed consistent associations (rs17599026 with increased urinary frequency, rs7720298 with decreased urinary stream, rs1801516 with overall toxicity) in new cohorts. rs10969913 and rs17599026 had similar effects in the photon-treated Japanese cohorts. CONCLUSIONS: This study increases the understanding of the architecture of common genetic variants affecting radiotoxicity, points to novel radio-pathogenic mechanisms, and develops risk models for testing in clinical studies. Further multinational radiogenomics studies in larger cohorts are worthwhile.