Cholesterol-lowering drugs reduce APP processing to Aβ by inducing APP dimerization

Vanessa F. Langness, Rik Van der Kant, Utpal Das, Louie Wang, Rodrigo Dos Santos Chaves, Lawrence S.B. Goldstein*

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Amyloid beta (Aβ) is a major component of amyloid plaques, which are a key pathological hallmark found in the brains of Alzheimer's disease (AD) patients. We show that statins are effective at reducing Aβ in human neurons from nondemented control subjects, as well as subjects with familial AD and sporadic AD. Aβ is derived from amyloid precursor protein (APP) through sequential proteolytic cleavage by BACE1 and γ-secretase. While previous studies have shown that cholesterol metabolism regulates APP processing to Aβ, the mechanism is not well understood. We used iPSC-derived neurons and bimolecular fluorescence complementation assays in transfected cells to elucidate how altering cholesterol metabolism influences APP processing. Altering cholesterol metabolism using statins decreased the generation of sAPPβ and increased levels of full-length APP (flAPP), indicative of reduced processing of APP by BACE1. We further show that statins decrease flAPP interaction with BACE1 and enhance APP dimerization. Additionally, statin-induced changes in APP dimerization and APP-BACE1 are dependent on cholesterol binding to APP. Our data indicate that statins reduce Aβ production by decreasing BACE1 interaction with flAPP and suggest that this process may be regulated through competition between APP dimerization and APP cholesterol binding.

Original languageEnglish
Pages (from-to)247-259
Number of pages13
JournalMolecular Biology of the Cell
Volume32
Issue number3
Early online date28 Jan 2021
DOIs
Publication statusPublished - 1 Feb 2021

Bibliographical note

Funding Information:
We thank Cody Fine and Jesus Olvera at the Sanford Consortium Stem Cell Core for helpful advice on flow cytometry data analysis. R.v.d.K. was supported by an Alzheimer Netherlands Fellowship (WE.15-2013-01) and an ERC Marie Curie International Outgoing fellowship (622444; APPtoTau). V.F.L. was supported by a National Institutes of Health T32 training grant (5T32AG000216-24). R.S.C. was supported by U.S. Department of Defense (DoD) Peer Reviewed Alzheimer’s Research Program (PRARP) grants (W81XWH-19-1-0315 and W81XWH-15-1-0561). U.D. and L.S.G. were supported by a National Institutes of Health grant (1R56AG054013). This work is supported by National Institute on Aging (1RF1AG048083-01) and California Institute for Regenerative Medicine (RB5-07011) grants to L.S.B.G.

Publisher Copyright:
© 2021 American Society for Cell Biology. All rights reserved.

Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.

Funding

We thank Cody Fine and Jesus Olvera at the Sanford Consortium Stem Cell Core for helpful advice on flow cytometry data analysis. R.v.d.K. was supported by an Alzheimer Netherlands Fellowship (WE.15-2013-01) and an ERC Marie Curie International Outgoing fellowship (622444; APPtoTau). V.F.L. was supported by a National Institutes of Health T32 training grant (5T32AG000216-24). R.S.C. was supported by U.S. Department of Defense (DoD) Peer Reviewed Alzheimer’s Research Program (PRARP) grants (W81XWH-19-1-0315 and W81XWH-15-1-0561). U.D. and L.S.G. were supported by a National Institutes of Health grant (1R56AG054013). This work is supported by National Institute on Aging (1RF1AG048083-01) and California Institute for Regenerative Medicine (RB5-07011) grants to L.S.B.G.

FundersFunder number
National Institute on AgingT32AG000216

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