PROJECT SUMMARY
Alzheimer disease (AD) is the leading cause of dementia in the elderly in the United States and occurs in all
ethnic and racial groups. Although >20 susceptibility loci have been associated with AD, much of the genetic
influence on AD remains unknown. This is particularly true for diverse ethnic populations such as Hispanics (HI)
and African Americans (AA) that are underrepresented in most genetic studies compared to non-Hispanic Whites
(NHW). Though emerging studies have begun to unravel some of the ancestry associated genetic risk of AD,
understanding the role of DNA variation is only one critical step in understanding the complex underlying biology
variants do not always provide direct information on the genes and mechanisms influenced.
To expand the context of ongoing large-scale genomic genotyping and whole genome sequencing efforts to
individuals of diverse ancestries, here we propose a transcriptomic, epigenomic, and genomic association study
of NHW, AA, and HI from Puerto Rico (PR) and Peru (PER) addressing diverse admixed populations. Completion
of this project will provide powerful functional genomic resources that could be applied to large existing and
emerging AD datasets to better understand the biological impact of genetic variation on AD risk. Specifically, we
will 1) generate whole-blood RNAseq, single-cell RNAseq, and DNA methylation datasets on existing collections
of NHW, AA, PR, and PER AD cases and elderly cognitively normal controls; 2) identify transcriptomic and
methylation differences including gene expression, alternative splicing, allele specific expression, and site and
regional methylation differences between NHW, AA, and HI cases and controls that may drive disease risk
differences between the ancestries; 3) combine these data with available DNA genotyping/whole genome
sequencing data to identify population and disease-specific expression/methylation QTLs; 4) generate the first
multiethnic imputation panel of expression/methylation QTL effects for estimating gene expression traits in
diverse (NWH, AA, HI) AD datasets; and 5) apply these panels to a broader set of thousands of multi-ethnic
genotyped samples.
The multi-omics approach outlined here will provide much needed functional context to the ongoing DNA
variant discovery efforts in these populations while addressing the important problem of disparities in AD
research. These studies will broaden the spectrum of AD risk to gene expression and methylation and expand
existing genomic efforts to a broader AD community.
