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| Funder | NATIONAL INSTITUTE ON AGING |
|---|---|
| Recipient Organization | University of North Carolina Chapel Hill |
| Country | United States |
| Start Date | Sep 15, 2024 |
| End Date | Jun 30, 2029 |
| Duration | 1,749 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | NIH (US) |
| Grant ID | 10973807 |
Project Summary Common genetic variants identified through genome-wide association studies have been reproducibly associated with risk for Alzheimer’s disease (AD), but the function of many risk variants are unknown and likely context-specific. At the same time, several environmental exposures have been implicated in AD and dementia,
including particulate matter air pollution (PM2.5), heavy metals (especially lead (Pb)), and infections. We posit that the genetic architecture of AD includes gene-environment interactions (GxE) between common, non-coding variants and environmental exposure. Here, we propose to identify these GxE using an in vitro model, "GxE in
a dish", using the inherent genetic diversity in a population of neural cells exposed to AD-relevant environmental exposures. We will test the context-specific function of common genetic variation in 100 induced pluripotent stem cell donors differentiated to cortical organoids. We will expose the organoids to PM2.5, Pb, infection mimics (LPS
+ IFNγ), or vehicle. We will collect scRNA-seq data from each exposed organoid, allowing inference of context- specific single cell expression quantitative trait loci (QTL). To find genetic variants associated with neural cell survival, we will additionally generate chimeric brain organoids composed of cells derived from multiple
independent donors. We will use the Census-seq approach to determine the proportion of each donor within the chimeric organoids in response to the exposures described above. We will then conduct a genetic association study to find common variants associated with differential survival response to these environmental exposures.
To complement our in vitro cell culture model, we will also identify GxE effects on brain structure in vivo using a large population scale database. We will then colocalize context-specific eQTLs, survival QTLs, and in vivo brain QTLs with each other and AD GWAS loci. In all, our results will reveal new mechanisms underlying AD GWAS
loci by exploring the context-specific nature of genetic variant function using both in vitro and in vivo systems.
University of North Carolina Chapel Hill
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