Biomarker Based Validation of GIS-Modeled Ambient Pesticide Exposures

Abstract

Biomarker Based Validation of GIS-Modeled Ambient Pesticide ExposuresAbstract Number:2784 Beate Ritz*, Jeff Bronstein, Kim Paul, and Myles Cockburn Beate Ritz* University of California Los Angeles Search for more papers by this author , Jeff Bronstein University of California Los Angeles Search for more papers by this author , Kim Paul University of California Los Angeles Search for more papers by this author , and Myles Cockburn University of Southern California Search for more papers by this author AbstractAssessment of pesticide exposure in humans continues to present a challenge, with exposure misclassification a major problem in environmental and occupational studies. Using the California mandated pesticide use report (CA-PUR) record system combined with a sophisticated geographic information system (GIS) model, we estimate ambient pesticide exposure and use the model-derived exposure estimates to predict measured platelet mitochondrial function. In 23 incident Parkinson’s disease patients along with 23 age, sex, and race matched population controls, we assessed platelet mitochondrial function by measuring activities of electron transport chain complexes. We estimated ambient pesticide exposure, due to commercial application, during the years prior to blood draw, using our GIS based computer model, which integrates geocoded work place and residential histories for each participant, CA-PUR data, and land use maps. We then classified participants’ exposure to different pesticide groups including mitochondrial complex I inhibiting pesticides. We used linear regression to assess whether our estimated pesticide exposure predicted mitochondrial function. Exposure to mitochondrial complex I inhibitors during the five years prior to blood draw was associated with a lower mitochondrial complex I activity (ß=-0.024, SE=0.01, p=0.04), with results very similar for exposure during the year and two years prior, as expected due to high correlation (?=0.71-1.00, p<.0001). This study demonstrates that our GIS-based assessment of ambient exposure to mitochondrial complex I inhibiting pesticides did in fact predict lower mitochondrial function, validating the GIS based exposure assessment methods we used.