Lung Health Study in the Agricultural Health Study

National Institute Of Environmental Health Sciences

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Abstract

To investigate the relationship between farming exposures and asthma, we have developed a case-cohort study within a large cohort of farmers -- the Agricultural Health Study. This study follows up findings regarding the association between correlates of exposure to pathogen associated molecular patterns (such as endotoxin) and various questionnaire-based asthma and atopy phenotypes. It is also designed to follow-up findings based on questionnaire data of positive associations between pesticide exposures, especially organophospates, and questionnaire-based asthma phenotypes. To confirm and better understand these associations, objective measures of asthma and atopy phenotype are needed along with more detailed and objective exposure assessment. This study builds upon the Agricultural Health Study, a large cohort of farmers and their spouses in Iowa and North Carolina. We identified presumptive cases of asthma and non cases from the third phase of cohort follow-up and made home visits on eligible subjects. The Lung Health Study was launched on Feb 4, 2009. Field work ended September 30, 2013 and telephone interviews ended on November 15, 2013. We completed home visits with 3,255 people and 3,200 (98%) completed telephone interviews following their home visit. In the past fiscal year we completed data cleaning and created code books and analysis dataset for all questionnaire, pulmonary function, exhaled NO, and anthropometry data. Analyses of dust measurements for endotoxin and glucans have been completed. Analyses of atopy by specific IgE have been completed. In June 2015 we received measurement of dust microbiome for a random sample of approximately 1,000 subjects. We also received genome wide genotyping data (Affymetrix Axiom Biobank chip) on approximately 3,000 subjects and completed imputation to 1000 Genomes. We are in the process of analyzing these various types of data. We are also participating in consortium analyses using our GWAS and exome chip data.