Issue 17, 2020

Effective atherosclerotic plaque inflammation inhibition with targeted drug delivery by hyaluronan conjugated atorvastatin nanoparticles

Abstract

Atherosclerosis is associated with inflammation in the arteries, which is a major cause of heart attacks and strokes. Reducing the extent of local inflammation at atherosclerotic plaques can be an attractive strategy to combat atherosclerosis. While statins can exhibit direct anti-inflammatory activities, the high dose required for such a therapy renders it unrealistic due to their low systemic bioavailabilities and potential side effects. To overcome this, a new hyaluronan (HA)–atorvastatin (ATV) conjugate was designed with the hydrophobic statin ATV forming the core of the nanoparticle (HA-ATV-NP). The HA on the NPs can selectively bind with CD44, a cell surface receptor overexpressed on cells residing in atherosclerotic plaques and known to play important roles in plaque development. HA-ATV-NPs exhibited significantly higher anti-inflammatory effects on macrophages compared to ATV alone in vitro. Furthermore, when administered in an apolipoprotein E (ApoE)-knockout mouse model of atherosclerosis following a 1-week treatment regimen, HA-ATV-NPs markedly decreased inflammation in advanced atherosclerotic plaques, which were monitored through contrast agent aided magnetic resonance imaging. These results suggest CD44 targeting with HA-ATV-NPs is an attractive strategy to reduce harmful inflammation in atherosclerotic plaques.

Graphical abstract: Effective atherosclerotic plaque inflammation inhibition with targeted drug delivery by hyaluronan conjugated atorvastatin nanoparticles

Supplementary files

Article information

Article type
Paper
Submitted
11 Jan 2020
Accepted
03 Apr 2020
First published
13 Apr 2020

Nanoscale, 2020,12, 9541-9556

Effective atherosclerotic plaque inflammation inhibition with targeted drug delivery by hyaluronan conjugated atorvastatin nanoparticles

S. Hossaini Nasr, Z. Rashidijahanabad, S. Ramadan, N. Kauffman, N. Parameswaran, K. R. Zinn, C. Qian, R. Arora, D. Agnew and X. Huang, Nanoscale, 2020, 12, 9541 DOI: 10.1039/D0NR00308E

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