# Regulation of amyloid production by focused ultrasound

> **NIH NIH R21** · UNIVERSITY OF FLORIDA · 2022 · $515,220

## Abstract

PROJECT SUMMARY
Beta amyloid (Aβ) is a protein that aggregates to form plaques associated with Alzheimer disease (AD). Its
formation from amyloid precursor protein (APP) by hydrolytic enzymes beta and gamma secretases is regulated
by brain cholesterol and depends on clustering of the proteins. In this application we propose to use focus
ultrasound (FUS) to disrupt cholesterol’s clustering of APP and inflammatory regulators toll like receptor 4 (TLR4)
and tumor necrosis factor alpha (TNF𝛼) which are also contributors to AD. We hypothesize, in that FUS can
reverse the effects cholesterol in an AD brain.
To test our hypothesis, we propose two specific aims. First, we will analyze clustering of amyloid proteins APP
and gamma secretase with and without FUS using dSTORM super resolution imaging in a mouse model of AD.
In a second aim we will characterize the de-clustering of inflammatory proteins TLR4 and TNF𝛼 in response to
FUS also in an AD mouse model.
The premise of this work is that cholesterol regulates nanoscopic trafficking of proteins in the membrane and
FUS disrupts the trafficking. Completion of the studies establish a direct molecular mechanism for FUS
independent of opening the blood brain barrier and FUS protocols with the potential to prevent or stop AD
progression.

## Key facts

- **NIH application ID:** 10511752
- **Project number:** 1R21AG078845-01
- **Recipient organization:** UNIVERSITY OF FLORIDA
- **Principal Investigator:** Scott B Hansen
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $515,220
- **Award type:** 1
- **Project period:** 2022-09-01 → 2024-10-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10511752

## Citation

> US National Institutes of Health, RePORTER application 10511752, Regulation of amyloid production by focused ultrasound (1R21AG078845-01). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10511752. Licensed CC0.

---

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