# Multi-omic functional assessment of novel AD variants using high-throughput and single-cell technologies

> **NIH NIH U01** · STANFORD UNIVERSITY · 2021 · $1,698,183

## Abstract

PROJECT SUMMARY / ABSTRACT
Through decades of research, genome-wide association studies (GWAS) have identified heritable coding and
noncoding single-nucleotide polymorphisms (SNPs) that lead to an increased risk of developing Alzheimer's
disease (AD). However, the vast majority of these SNPs remain largely under-characterized, and their
contribution to AD pathogenesis remains unclear, marking a critical roadblock to our understanding of AD
genetics and pathogenesis. While SNPs within the APOE and TREM2 genes have identified vital nodes in AD
biology, most AD-related SNPs reside within the noncoding genome, making their functional roles in the
disease less clear. Co-inheritance of nearby SNPs (linkage disequilibrium) and the cell type-specificity of
noncoding regulatory elements further complicate functional annotation of noncoding SNPs in AD. As part of
the Alzheimer's Disease Sequencing Project Functional Genomics Consortium (ADSP FGC), this project will
provide a robust and conclusive functional characterization of AD-related noncoding SNPs. To do this, we will
first create a comprehensive single-cell atlas of gene expression and chromatin accessibility across a cohort of
diverse clinico-pathologic states related to AD (Aim 1). Using these cell type-specific gene regulatory
landscapes, we will develop and implement innovative machine learning and statistical genomics methods to
predict functional noncoding, splicing, and coding SNPs (Aim 2). We will then validate these predictions using
massively parallel reporter assays (MPRAs) and large-scale, scarless, single-base CRISPR editing of iPSCs
followed by cell type-specific differentiations (Aim 3). Taken together (Aim 4), this project will pinpoint the
functional SNPs and target cell types for dozens of AD-related risk loci and provide an unprecedented picture
of the gene regulatory landscape of AD. This work will be performed as a joint collaboration between Stanford
University and the Gladstone Institutes at UCSF. Our team, with many long-standing collaborations, has
extensive experience in consortium science with long-term involvement in the Encyclopedia of DNA Elements,
The Cancer Genome Atlas, and The Genotype-Tissue Expression Project. The proposed project is thus well-
positioned to integrate into the highly collaborative ADSP Functional Genomics Consortium.

## Key facts

- **NIH application ID:** 10217784
- **Project number:** 1U01AG072573-01
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Anshul Kundaje
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $1,698,183
- **Award type:** 1
- **Project period:** 2021-07-01 → 2026-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10217784

## Citation

> US National Institutes of Health, RePORTER application 10217784, Multi-omic functional assessment of novel AD variants using high-throughput and single-cell technologies (1U01AG072573-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10217784. Licensed CC0.

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