Evaluating polygenic architecture of Alzheimer’s disease using next gen sequencing data

Research objective: To examine the polygenic architecture of AD using genetic variants identified in the ADSP data set. We plan to evaluate genetic variation originating from genes, pathways and other functional units for association with AD.
Study design: Using whole genome and whole exome sequence, we will perform subject and variant QC using in house pipelines. We will then search for small sets of functionally related variants that show significant, replicable association with AD.
Analysis plan: Our analysis plan will include in depth quality control of samples/subjects for the following metrics: sequencing coverage, sample call rate, missing chromosomes, sample contamination, sex check, relatedness, population substructure and a check of APOE genotypes. This will be followed by variant quality control and subsequent single variant association analysis adjusting for variation arising from population substructure, sequencing centers, sex, and APOE genotype. Using approaches suitable for analyzing sets of genes and/or variants (e.g. polygenic score analysis, SKAT-O), we will explore the polygenic architecture of AD of all available datasets by searching for sets of functionally related genes and/or variants which show significant, replicable association with AD.

To identify novel AD genes which can be studied to develop new therapeutic approaches to AD, we will extend conventional analysis of single genetic variants by using methods capable of jointly analyzing all of the genetic variation in individual genes and functionally related sets of genes. These methods should enable us to identify novel, functionally related sets of genes which alter risk of AD.