Assessment of Tandem Repeat Variation in Alzheimer’s Disease

Summary

The goal of this project is to identify novel tandem repeat variants that underlie Alzheimer’s Disease, enhancing our understanding about the genetic architecture of this disease.

Project Details

Aim1. Identification of rare and highly penetrant pathogenic expansions at short tandem repeat (TREs) in AD cases. Using novel algorithms, we will search for TREs that are either enriched, or occur uniquely, in AD cases compared to controls. Aim2. Identification of copy number variation at large TR as genetic risk factors for AD. Using WGS read depth, we will estimate the copy number of large TR in each sample, and use them to perform association analysis of copy number with AD status. Aim3. Experimental validation of size and sequence content of TR variants detected in Aims 1 and 2 

Despite Tandem Repeats (TR) representing a significant source of genetic variation and the underlying genetic cause of human diseases, primarily neurodegenerative diseases, they represent a largely unexplored aspect of the human genome and thus, an area of research with high probability of uncovering novel findings on AD pathogenesis. The availability of large genome sequencing datasets together with newly developed bioinformatics tools that are able to genotype TRs from whole genome sequencing data, now provide the opportunity to fill this gap and explore the link between TR variation and AD. The screening of the genomes of thousands of individuals, including 16,000 AD cases and 66,000 controls, will likely lead to the identification of novel TR variants that underlie AD, thus improving (i) our understanding of the genetic risk factors and pathways that lead to AD, (ii) diagnoses and genetic counseling in a fraction of AD cases, and (iii) providing a basis for future development of therapies. Furthermore, as a possible direct result of our study an accurate molecular diagnosis can be provided to some patients with unexplained AD, allowing a better health care for these patients.