Spatiotemporal Dynamics of Lake Water Quality and ALS Spatial Clusters

点击翻译按钮获取中文摘要

There is broad scientific consensus that some diseases are influenced by the environment. Recent work has suggested that harmful algae in lakes are linked to some illnesses and diseases. This project will study relationships among lake water quality, harmful algae, and Amyotrophic lateral sclerosis (ALS), also known as Lou Gehrig's disease. An interdisciplinary team of geographers, neurologists, epidemiologists, and statisticians will collaborate to assess how and under what conditions algal levels and water quality impact ALS incidence, a very poorly understood disease. This work will contribute to research on disease ecology as well as inform a wide audience concerned with health outcomes including public health and environmental agencies, medical centers, those potentially exposed to the risk factors, and property owners.Amyotrophic lateral sclerosis (ALS) is a progressive, fatal disease with an average life expectancy of two to five years from time of diagnosis. Approximately 90% of ALS cases have no known genetic cause and are commonly known as sporadic ALS (sALS). Despite many recent discoveries about the genetics of ALS, the etiology or causal origins of sALS remain largely unknown. It is most likely that sALS results from a combination of underlying genetic susceptibility coupled with environmental exposure to one or more toxins. Recent work has shown linkages between lake water quality and high ALS incidence, with the [algal] cyanotoxin beta methyl-amino-alanine (BMAA) as a potential trigger. The overarching goal of this study is to characterize the relationship between sALS incidence and lake water quality parameters that favor cyanobacteria growth. Multi-scale satellite remote sensing imagery will be used to map lake water quality attributes including cyanobacteria, phycocyanin, chlorophyll-a, and total nitrogen in freshwater lakes in northern New England. An ALS database with completed questionnaire surveys, including information on residential history and related risk factors, will be integrated into a spatial analysis framework that will be generalizable to other similar freshwater / residential systems. Eco-epidemiological modeling will be conducted to test the relationships among lake conditions, risk factors, and sALS. This work will develop tools for assessing stressor response relationships improve understanding of sALS. The results will assist in identifying potential causal factors as well as and means by which they may be remotely monitored, thereby contributing to the quantification of the role of freshwater aquatic ecosystems in human health risk.