# Towards a better understanding of genetic architecture of Alzheimer's disease with human iPSC models

> **NIH NIH R01** · EMORY UNIVERSITY · 2020 · $787,568

## Abstract

PROJECT SUMMARY
Alzheimer's disease (AD) is a progressive neurodegenerative disease and the leading cause of dementia with
high heritability (~70%). It is increasingly clear that AD is highly polygenic, and for most of AD cases it is the
polygenicity of the risk variants across the genome that predisposes the disease risk. In contrast to the rapid
identification of risk loci associated with AD by recent genome-wide association studies (GWAS), identifying the
potential causal variants/genes at the reported risk loci and decoding these variants/genes into molecular and
cellular pathology have lagged far behind. Since disease variants, mostly locating in noncoding regions of the
human genome, have been shown to affect cellular function through multi-level regulations such as DNA
accessibility and histone modifications, DNA methylation and RNA expression in a cell type-specific manner,
comprehensive and unbiased investigating the cell type-specific influence of generic risk variants on AD risk at
multiple levels, including epigenomic, transcriptomic, and cellular levels, in an isogenic background is crucial to
understand the genetic basis of AD pathogenesis. In the current application, by combining human induced
pluripotent stem cells (hiPSCs) with gene editing and comprehensive multi-omics and cellular analyses, we will
dissect the AD genetic risk variants into cell type-specific molecular and cellular pathology. Given the polygenic
nature of AD, and the heterogeneity of AD risk genes on the cellular level, we hypothesize that multiple genetic
risk variants act synergistically among different compartments (e.g. cell types) to contribute to pathogenesis of
AD. First, we will identify AD risk variants and genes with comprehensive analyses of AD genetic architecture
using machine learning approaches including DVAR, eVAR and iRIGS (Aim 1). Second, we will delineate the
cell type-specific epigenetic and transcriptomic signatures associated with AD candidate risk variants using
human iPSC-derived neurons/microglia/astrocytes (Aim 2). Last, we will determine the functional impact of AD
candidate risk variants on AD-like cellular pathology in neurons, microglia, astrocytes, and their co-cultures (Aim
3). Our proposal may advance our understanding of the complex genetic architecture of AD, leading to a better
understanding of AD pathogenesis and facilitating the development of novel therapeutic strategies.

## Key facts

- **NIH application ID:** 10052141
- **Project number:** 1R01AG065611-01A1
- **Recipient organization:** EMORY UNIVERSITY
- **Principal Investigator:** BINGSHAN LI
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $787,568
- **Award type:** 1
- **Project period:** 2020-08-15 → 2025-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10052141

## Citation

> US National Institutes of Health, RePORTER application 10052141, Towards a better understanding of genetic architecture of Alzheimer's disease with human iPSC models (1R01AG065611-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10052141. Licensed CC0.

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