ALS is a devastating and fatal neurodegenerative disease for which there is no cure or effective treatment. The causes of ALS likely involve interaction of environmental and genetic susceptibility factors. Exposure to the damaging environmental stressors likely occurs at particularly susceptible time-periods, and for a prolonged period. We will investigate the poques during which environmental exposures carry the greatest risk for later development of ALS. We will use questionnaire data, residential history, and DNA samples from our on-going epidemiologic studies in Northern New England and Ohio, the existing environmental and genetic variant data from the National ALS Registry for ALS patients nationwide, and both clinic- and random population-based controls. We will use geospatial algorithms to estimate residential exposures in years extending backwards for ~30 years derived from our databases of time-linked contents of sources of environmental toxins (cyanobacteria) and toxicants (landfills, municipal incinerators, Superfund and Brownfield sites, pesticide applications). We also propose to identify genetic risk factors for ALS that manifest effects specifically in the presence of an environmental stressor. We will use the existing Illumina NeuroChip data covering 500,000 genetic variants implicated in neurodegenerative illness on the National ALS Biorepository participants, and propose to assay our epidemiologic study DNA samples on the same panel to construct a large, pooled genotype dataset. Genetic imputation will allow genome-wide coverage for identification of novel variants. We will employ the machine- learning methods to identify gene x environment interactions, the genetic variants that synergize with environmental stressors to increase disease risk. This project has the potential to identify the environmental and genetic risk factors in periods of temporal susceptibility that will lead to disease prevention through exposure mitigation, early-identification, and development of interventions to block disease progression.
/RELEVANCE TO PUBLIC HEALTH The prevention and cure of ALS require identification of susceptibility genes and the most important environmental risk factors, their most sensitive period of exposure, and the implementation of steps to mitigate these exposures. We propose to use residential history to estimate exposures to waterbody cyanobacteria, pesticides, and polluted sites in ALS patients compared to healthy controls using time-linked databases. We expect these studies to reveal genetic variants that raise ALS susceptibility, and determine the periods of life that carry the greatest risk for developing ALS from exposures to environmental stressors.
