# Big data and small molecules for Alzheimer's disease

> **NIH NIH R01** · BOSTON UNIVERSITY MEDICAL CAMPUS · 2024 · $870,242

## Abstract

ABSTRACT
 Alzheimer’s disease (AD) is characterized by progressive loss of synapses and neurons along with
amyloid and Tau pathologies. Although amyloid-β (Aβ)-reducing immunotherapy received full approval by the
FDA for patients with mild cognitive impairment (MCI) or mild AD, developing future treatments against AD at all
stages is an urgent priority. One of our recent 12 publications described our cohorts of patients with MCI, mild,
moderate, or severe AD within the Department of Veterans Affairs (VA) Healthcare System. Using electronic
health records (EHRs), we reported a slower progression to AD among veterans on prescribed vasodilators,
including anti-hypertensive angiotensin converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers
(ARBs). We compared a spectrum of anti-hypertension, anti-diabetic or anti-hypercholesterolemia medications
and reported a reduced risk of AD onset among vasodilator users (e.g., Valsartan, Carvedilol, Losartan) and an
increased risk of AD onset among vasoconstrictor users (e.g., Propranolol). We also reported that ACEIs reduced
phosphorylated Tau (pTau) in mouse brains. We further reported that Fasudil, a specific vasodilator and a Rho-
associated coiled-coil kinase (ROCK) 1/2 inhibitor, decreased pTau in human neuro-spheroids. We therefore
propose to perform data mining of 25 million veterans’ 76 billion medical records from the VA Corporate Data
Warehouse and to test the clinical effectiveness of more potent vasodilators, such as a selective ROCK2 inhibitor
Belumosudil, in delaying AD onset among veterans. We will also test if Belumosudil suppresses
neurodegeneration in AD mouse models. Our access to VA EHR as well as our expertise in development and
multidisciplinary analysis of Familial AD mouse models place us in a unique position to test the hypothesis that
vasodilation alleviates cognitive impairment in AD patients as well as memory deficits and neurodegeneration in
AD mouse models. In this competing continuation application, we propose to evaluate the effects of more potent
vasodilators on cognitive impairment of AD patients and AD mouse models (Aim 1). We will perform big data
analysis of EHR to collect vasodilators that are associated with delayed onset of AD, compared to the benchmark
ARB drug Valsartan. We will also test whether vasodilators, such as Belumosudil, alleviate neurodegeneration
and memory impairment in AD mouse models. We will also explore molecular mechanisms of vasodilators using
single nucleus RNAseq and proteomic analyses of AD postmortem brains and mouse models (Aim 2). The
significant impact of the current study is that these small molecules derived from big data mining and validated
in AD mouse models may be fast-tracked to next generation safe therapies of AD.

## Key facts

- **NIH application ID:** 10992004
- **Project number:** 2R01AG063913-02
- **Recipient organization:** BOSTON UNIVERSITY MEDICAL CAMPUS
- **Principal Investigator:** Weiming Xia
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $870,242
- **Award type:** 2
- **Project period:** 2019-08-15 → 2029-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10992004

## Citation

> US National Institutes of Health, RePORTER application 10992004, Big data and small molecules for Alzheimer's disease (2R01AG063913-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10992004. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*