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Evaluating the frequency and impact of structural variation in amyotrophic lateral sclerosis (ALS)

Principal Investigator:
  • Allison A. Dilliott, McGill University
  • Seger-van Tol Family

Project Overview

Dr. Hubert van Tol Travel Fellowship

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease that lacks treatment options, and much remains to be understood regarding an individual’s genetic susceptibility to the disease. Recently, we were able to use large DNA sequencing datasets to determine that ALS cases carry an excess of small-scale rare variants, and further investigated the signal toi dentify a new ALS-associated gene, DNAJC7(Farhan et al., 2019). However, one major limitation of the study was that it did not consider larger variation, such as large deletions or duplications encompassing parts of or even entire genes, otherwise referred to as structural variants. These large variants within the genome are known to be important risk factors for other diseases, but there remains little known regarding how structural variants contribute to ALS. For my project, we are studying the DNA sequencing of4,828 ALS cases and 14,091 controls to identify structural variant signatures unique to ALS cases. Following the identification of structural variants in the ALS cases and controls, we are applying statistical models to detect signals of enrichment of genomic gains (duplications) and/or losses (deletions) in the ALS cases. In addition to taking an agnostic approach looking at all genes in the genome, I will investigate sets of genes known to contribute to molecular pathways associated with ALS. Further, I will use our understanding of which regions of the genome have had structural variants previously reported to be associated with other genomic disorders to guide the analyses.To validate our findings, our analyses are undergoing replication by collaborators using the same optimized approach on additional ALS cases and age-matched controls, with the goal of harmonizing our data and performing a meta-analysis from the two independent datasets. Our study is among the first to advance our knowledge of the frequency and impact of structural variation in neurodegeneration —specifically ALS —using a large, powerful sample size.