No abstract

A new version (version 2) of the genomic dose-response analysis software, BMDExpress, has been created. The software addresses the increasing use of transcriptomic dose-response data in toxicology, drug design, risk assessment and translational research. In this new version, we have implemented additional statistical filtering options (e.g. Williams' trend test), curve fitting models, Linux and Macintosh compatibility and support for additional transcriptomic platforms with up-to-date gene annotations. Furthermore, we have implemented extensive data visualizations, onthe-fly data filtering, and a batch-wise analysis workflow. We have also significantly re-engineered the code base to reflect contemporary software engineering practices and streamline future development. The first version of BMDExpress was developed in 2007 to meet an unmet demand for easy-touse transcriptomic dose-response analysis software. Since its original release, however, transcriptomic platforms, technologies, pathway annotations and quantitative methods for data analysis have undergone a large change necessitating a significant redevelopment of BMDExpress. To that end, as of 2016, the National Toxicology Program assumed stewardship of BMDExpress. The result is a modernized and updated BMDExpress 2 that addresses the needs of the growing toxicogenomics user community.

Objective This study describes associations of ozone and fine particulate matter with Parkinson’s disease observed among farmers in North Carolina and Iowa. Methods We used logistic regression to determine the associations of these pollutants with self-reported, doctor-diagnosed Parkinson’s disease. Daily predicted pollutant concentrations were used to derive surrogates of long-term exposure and link them to study participants’ geocoded addresses. Results We observed positive associations of Parkinson’s disease with ozone (OR=1.39; 95% CI: 0.98, 1.98) and fine particulate matter (OR=1.34; 95% CI: 0.93, 1.93) in North Carolina but not in Iowa. Conclusion The plausibility of an effect of ambient concentrations of these pollutants on Parkinson’s disease risk is supported by experimental data demonstrating damage to dopaminergic neurons at relevant concentrations. Additional studies are needed to address uncertainties related to confounding and to examine temporal aspects of the associations we observed.