# Drug repositioning for Alzheimer's disease via genetics, electronic health records, and human iPSC models

> **NIH NIH R01** · VANDERBILT UNIVERSITY · 2021 · $838,304

## Abstract

Alzheimer's disease (AD) is a progressive neurodegenerative disease and the leading cause of 
dementia in the United States. Unfortunately, there is no cure for AD. Drug discovery for AD has 
suffered significant failures, many at late stage clinical trials, partly due to our poor 
understanding of AD pathology and the lack of disease-relevant and human-relevant discovery and 
development models. This calls for team efforts with diverse and complementary expertise to tackle 
the challenges together, by developing innovative approaches from multiple angles to achieve the 
goal of identifying AD drugs.

In this application, we propose three complementary  Specific Aims that together aim to identify 
FDA approved drugs with repurpose potential for AD, from distinct but complementary angles that act 
synergistically to boost the likelihood of success. AD is a highly heritable disease, with an 
estimated heritability of 70%, highlighting the critical role of genetics in understanding  the 
disease etiology. Recent genetic studies have identified over 30 loci, enabling us to dissect the 
genetic architecture of AD, including the biological processes and cell types involved in disease 
etiology. In particular, we aim to dissect the highly polygenic AD etiology into distinct 
pathophysiological components to guide drug repurposing,  which is only feasible in recent years 
thanks to large scale GWAS and massive genomics data available publicly (Aim 1). In parallel, we 
will mine millions of electronic health records (EHRs) to identify drugs that reduce AD risk and 
cognitive decline, by developing phenotyping algorithms from EHR for AD related phenotypes (Aim 2). 
In addition, we will develop a high­ throughput screening (HTS) gene expression profiling assay and 
use human induced pluripotent stem cell (iPSC) models to identify candidate compounds, and will 
further test the efficacy of the candidates in both patient-derived iPSC lines and AD mouse models 
(Aim 3). The three aims are complementary  and synergistic, in the sense that they independently  
tackle the same problem from drastically distinct angles, while findings from one can be served as 
validation for others. Altogether, leveraging distinct and complementary  expertise, we expect to 
yield bona fide repurposable drugs for AD with orthogonal support.

## Key facts

- **NIH application ID:** 10099798
- **Project number:** 1R01AG069900-01
- **Recipient organization:** VANDERBILT UNIVERSITY
- **Principal Investigator:** BINGSHAN LI
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $838,304
- **Award type:** 1
- **Project period:** 2021-04-15 → 2025-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10099798

## Citation

> US National Institutes of Health, RePORTER application 10099798, Drug repositioning for Alzheimer's disease via genetics, electronic health records, and human iPSC models (1R01AG069900-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10099798. Licensed CC0.

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