229 research outputs found

    Agricultural Exposures and Stroke Mortality in the Agricultural Health Study

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    Exposures associated with common agricultural activities may increase risk of stroke. The authors evaluated associations between self-reported agricultural activities including pesticide use and handling of crops and stroke mortality among 51,603 male pesticide applicators enrolled in the Agricultural Health Study (AHS). Vital status was obtained through 2008. Stroke mortality was defined by underlying or contributing cause of death (ICD-9 430–438, ICD-10 I60-I69). Information regarding lifetime pesticide use, working with crops or animals, engagement in other agricultural activities, and potential confounders was self-reported at enrollment. Cox proportional hazards models, with age as the time scale, were used to estimate hazard ratios (HR) and 95% confidence intervals (CI) adjusted for state of residence, smoking status, and alcohol consumption. Median follow-up time was 13 years, during which 308 stroke deaths occurred. No measure of overall or specific pesticide use was positively associated with mortality due to stroke. Stroke mortality was inversely associated with handling hay, grain, or silage at least once each year as reported at enrollment (HR: 0.75; 95% CI: 0.58, 0.98). There was no evidence of an association between pesticide use and stroke mortality. The inverse association between handling of hays and grains and stroke mortality may be due to (1) those engaging in such activities being healthier than those who did not or (2) exposure to some biological agent present in hays and grains. Further investigation of incident stroke, rather than stroke mortality, as well as stroke subtypes are needed to determine the full role of agricultural exposures and stroke

    Interaction between Genetic Risk Scores for Reduced Pulmonary Function and Smoking, Asthma and Endotoxin

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    Rationale Genome-wide association studies (GWASs) have identified numerous loci associated with lower pulmonary function. Pulmonary function is strongly related to smoking and has also been associated with asthma and dust endotoxin. At the individual SNP level, genome-wide analyses of pulmonary function have not identified appreciable evidence for gene by environment interactions. Genetic Risk Scores (GRSs) may enhance power to identify gene–environment interactions, but studies are few. Methods We analysed 2844 individuals of European ancestry with 1000 Genomes imputed GWAS data from a case–control study of adult asthma nested within a US agricultural cohort. Pulmonary function traits were FEV1, FVC and FEV1/FVC. Using data from a recent large meta-analysis of GWAS, we constructed a weighted GRS for each trait by combining the top (p value\u3c5×10−9) genetic variants, after clumping based on distance (±250 kb) and linkage disequilibrium (r2=0.5). We used linear regression, adjusting for relevant covariates, to estimate associations of each trait with its GRS and to assess interactions. Results Each trait was highly significantly associated with its GRS (all three p values\u3c8.9×10−8). The inverse association of the GRS with FEV1/FVC was stronger for current smokers (pinteraction=0.017) or former smokers (pinteraction=0.064) when compared with never smokers and among asthmatics compared with non-asthmatics (pinteraction=0.053). No significant interactions were observed between any GRS and house dust endotoxin. Conclusions Evaluation of interactions using GRSs supports a greater impact of increased genetic susceptibility on reduced pulmonary function in the presence of smoking or asthma

    Respiratory disease in United States farmers

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    Farmers may be at increased risk for adverse respiratory outcomes compared with the general population due to their regular exposures to dusts, animals and chemicals. However, early life farm exposures to microbial agents may result in reduced risk. Understanding respiratory disease risk among farmers and identifying differences between farmers and other populations may lead to better understanding of the contribution of environmental exposures to respiratory disease risk in the general population

    Possible pro-carcinogenic association of endotoxin on lung cancer among Shanghai women textile workers

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    Background: Endotoxin (lipopolysaccharide) is a widespread contaminant in many environmental settings. Since the 1970s, there has been generally consistent evidence indicating reduced risks for lung cancer associated with occupational endotoxin exposure. Methods: We updated a case–cohort study nested within a cohort of 267 400 female textile workers in Shanghai, China. We compared exposure histories of 1456 incident lung cancers cases diagnosed during 1989–2006 with those of a reference subcohort of 3022 workers who were free of lung cancer at the end of follow-up. We applied Cox proportional hazards modelling to estimate exposure–response trends, adjusted for age and smoking, for cumulative exposures lagged by 0, 10, and 20 years, and separately for time windows of ⩽15 and \u3e15 years since first exposure. Results: We observed no associations between cumulative exposure and lung cancer, irrespective of lag interval. In contrast, analyses by exposure time windows revealed modestly elevated, but not statistically significant relative risks (∼1.27) at the highest three exposure quintiles for exposures that occurred \u3e15 years since first exposure. Conclusions: The findings do not support a protective effect of endotoxin, but are suggestive of possible lung cancer promotion with increasing time since first exposure

    Evaluation of European-based polygenic risk score for breast cancer in Ashkenazi Jewish women in Israel

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    To date, most BC GWASs have been performed Background Polygenic risk score (PRS), calculated in individuals of European (EUR) ancestry, and based on genome-wide association studies (GWASs), the generalisation of EUR-based PRS to other can improve breast cancer (BC) risk assessment. populations is a major challenge. In this study, we examined the performance of EUR-based BC PRS models in Ashkenazi Jewish (AJ) women. Methods We generated PRSs based on data on EUR women from the Breast Cancer Association Consortium (BCAC). We tested the performance of the PRSs in a cohort of 2161 AJ women from Israel (1437 cases and 724 controls) from BCAC (BCAC cohort from Israel (BCAC-IL)). In addition, we tested the performance of these EUR-based BC PRSs, as well as the established 313-SNP EUR BC PRS, in an independent cohort of 181 AJ women from Hadassah Medical Center (HMC) in Israel. Results In the BCAC-IL cohort, the highest OR per 1 SD was 1.56 (±0.09). The OR for AJ women at the top 10% of the PRS distribution compared with the middle quintile was 2.10 (±0.24). In the HMC cohort, the OR per 1 SD of the EUR-based PRS that performed best in the BCAC-IL cohort was 1.58±0.27. The OR per 1 SD of the commonly used 313-SNP BC PRS was 1.64 (±0.28). Conclusions Extant EUR GWAS data can be used for generating PRSs that identify AJ women with markedly elevated risk of BC and therefore hold promise for improving BC risk assessment in AJ women.</p

    Genome-wide association study identifies multiple risk loci for renal cell carcinoma

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    Previous genome-wide association studies (GWAS) have identified six risk loci for renal cell carcinoma (RCC). We conducted a meta-analysis of two new scans of 5,198 cases and 7,331 controls together with four existing scans, totalling 10,784 cases and 20,406 controls of European ancestry. Twenty-four loci were tested in an additional 3,182 cases and 6,301 controls. We confirm the six known RCC risk loci and identify seven new loci at 1p32.3 (rs4381241, P=3.1 × 10−10), 3p22.1 (rs67311347, P=2.5 × 10−8), 3q26.2 (rs10936602, P=8.8 × 10−9), 8p21.3 (rs2241261, P=5.8 × 10−9), 10q24.33-q25.1 (rs11813268, P=3.9 × 10−8), 11q22.3 (rs74911261, P=2.1 × 10−10) and 14q24.2 (rs4903064, P=2.2 × 10−24). Expression quantitative trait analyses suggest plausible candidate genes at these regions that may contribute to RCC susceptibility

    Fast and efficient QTL mapper for thousands of molecular phenotypes

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    In order to discover quantitative trait loci, multi-dimensional genomic datasets combining DNA-seq and ChiP-/RNA-seq require methods that rapidly correlate tens of thousands of molecular phenotypes with millions of genetic variants while appropriately controlling for multiple testing
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