Prerna Das



Document Type


Degree Name



Biomedical Informatics


Alzheimer’s disease (AD) is an irreversible neurodegenerative disorder. It is the sixth leading cause of death in the United States. Genome-wide association studies have uncovered nearly 40 common genetic variants (minor allele frequency (MAF) > 5%) which are associated with increased susceptibility to AD. However, the common variants found so far do not completely account for the genetic component of the disease. With the technological advancement of deep sequencing, the focus has shifted to exploring the role of rare (MAF < 0.5%) and private variants. In addition, it has been hypothesized that rare variants are generally functional and highly penetrant with large effect sizes. We investigated whether the aggregation of rare and private variants within a gene region based on linkage disequilibrium (LD) complemented the association between common variants in the gene region and the disease. The whole genome sequencing and phenotype data used in our study come from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). We looked at four AD associated genes with different LD structure - APOE, ABCA7, CD2AP, and CR1, and found a total of 3016 variants (common, low-frequency, rare and private) across the four genes. All four genes had varying percentages of rare (APOE-75.39%, ABCA7-47.77%, CD2AP-77.34%, CR1-70.34%) and private (APOE-54.45%, ABCA7-43.33%, CD2AP-42.74%, CR1-52.24%) variants. In order to aggregate the effects all types of variants present in these genes, we used the Sequence kernel association test (SKAT-O) to test the association between the overall burden of variants and the AD phenotype. We found that aggregating all the variants indeed complements the individual common variant – disease association and is an effective strategy to identify the genomic regions harboring potential rare causal variants.




School of Medicine



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