Genomic and Multi-Omic Analysis of Alzheimer's Disease in Diverse Populations

We are requesting data from the NIAGDS portal for utilization in our project concerning genomic and multiomic analysis of Alzheimer's disease in diverse populations. This is relevant to funded NIA grant R01AG075884 as well as pending NIA applications. We will use deidentified data from NIAGDS, as well as from other data sources including the TOPMed consortium and newly generated data from cohorts such as Jackson Heart Study, to identify putative risk factors and biological mechanisms for identified genetic loci for Alzheimer's disease risk. We will utilize statistical and genetic analysis methods (including polygenic risk score construction, colocalization using GWAS summary statistics, and association analysis for gene transcripts, proteins, and metabolites) to identify putative risk factors for Alzheimer's disease.

Black Americans face a disproportionately high risk of developing cognitive impairment and Alzheimer’s disease and related dementias (ADRD), compared to non-Hispanic White adults, but the biological mediators underlying this elevated risk are not well understood. Additionally, most efforts to identify risk biomarkers have not included diverse populations, making results less relevant to all Americans. High throughput multi-omics data from blood samples in diverse participants, including through newly funded grants and existing funded data from NIA, may allow us to identify predictors of ADRD and incident cognitive impairment risk across diverse US populations, including in Black adults underrepresented in ADRD research. Integration of genetic data may allow us to further clarify the genes, proteins, and metabolites through which Alzheimer’s disease genetic risk variants function, as well as improve risk prediction in populations with substantial non-European ancestry.