Amyotrophic lateral sclerosis (ALS) is a devastating, incurable and rapidly fatal disorder of the motor neurons responsible for voluntary muscle movement. Genes responsible for the familial form of ALS have been identified, but the majority of ALS is sporadic and has a complex etiology with contributions of both genetic and environmental factors. The hypothesis that gene-environment (GxE) interaction may play a substantial role in ALS pathogenesis is supported by studies of high-risk clusters in the Western Pacific Islands. ALS is a disease of high priority for the Department of Veterans Affairs (VA) since an increased incidence of the disease has been reported in deployed compared to non-deployed Gulf War veterans. Recently, the VA has initiated a National Registry of veteran ALS patients, which is expected to recruit approximately 1,500 patients with blood samples over the next three years. Given this unique resource, the explosion of data from the Human Genome Project, and the development of new laboratory and statisticalgenetic analysis tools, the time is ripe for new approaches to dissecting the etiology of ALS, with an emphasis on uncovering complex GxE interactions.
The specific aims of the study proposed here are to (1) ascertain 3,000 veteran controls frequency-matched to the ALS Registry patients by age, sex, ethnicity and branch of military service; (2) collect environmental risk factor information from ALS patients and controls, building upon an instrument currently used in other ALS studies, which will be modified and expanded to include military-specific exposure assessment; (3) genotype nuclear DNA of ALS patients and controls for single-nucleotide polymorphisms (SNPs) in a number of putative candidate genes, using an efficient DNA pooling strategy combined with high-throughput individual genotyping; (4) genotype mitochondrial haplogroups of ALS patients and controls; and (5) perform statistical analysis of case-control and case-only data to identify main effects of genetic and non-genetic risk factors for ALS as well as GxE interaction. Both traditional regression-based well as novel computationally intensive methods will be employed. Genetic and environmental effects on disease progression will also be examined. Our study will not only be of great relevance for the veteran population, but is also likely to improve our understanding of ALS in the general population. ? ?
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