Protein Corona Sensor Array Nanosystem for Detection of Coronary Artery Disease

Author:

Lee Gha Young1,Li Andrew A.2,Moon Intae3,Katritsis Demos45,Pantos Yoannis4,Stingo Francesco6,Fabbrico Davide6,Molinaro Roberto7,Taraballi Francesca8,Tao Wei1,Corbo Claudia910ORCID

Affiliation:

1. Center for Nanomedicine Department of Anesthesiology Brigham and Women's Hospital Harvard Medical School Boston MA 02115 USA

2. Tepper School of Business Carnegie Mellon University Pittsburgh PA 15213 USA

3. Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA 4307 USA

4. Comprehensive Cardiology Care at Hygeia Hospital Athens 15123 Greece

5. Johns Hopkins Medicine Baltimore MD 21287 USA

6. Department of Statistics Computer Sciences and Applications University of Florence Florence 50121 Italy

7. Department of Cardiovascular Brigham and Women's Hospital Harvard Medical School Boston MA 02115 USA

8. Center for Musculoskeletal Regeneration Houston Methodist Academic Institute & Orthopedics and Sports Medicine Houston Methodist Hospital Houston TX 77030 USA

9. University of Milano‐Bicocca Department of Medicine and Surgery NANOMIB Center Monza 20900 Italy

10. IRCCS Istituto Ortopedico Galeazzi Milan 20161 Italy

Abstract

AbstractCoronary artery disease (CAD) is the most common type of heart disease and represents the leading cause of death in both men and women worldwide. Early detection of CAD is crucial for decreasing mortality, prolonging survival, and improving patient quality of life. Herein, a non‐invasive is described, nanoparticle‐based diagnostic technology which takes advantages of proteomic changes in the nano‐bio interface for CAD detection. Nanoparticles (NPs) exposed to biological fluids adsorb on their surface a layer of proteins, the “protein corona” (PC). Pathological changes that alter the plasma proteome can directly result in changes in the PC. By forming disease‐specific PCs on six NPs with varying physicochemical properties, a PC‐based sensor array is developed for detection of CAD using specific PC pattern recognition. While the PC of a single NP may not provide the required specificity, it is reasoned that multivariate PCs across NPs with different surface chemistries, can provide the desirable information to selectively discriminate the condition under investigation. The results suggest that such an approach can detect CAD with an accuracy of 92.84%, a sensitivity of 87.5%, and a specificity of 82.5%. These new findings demonstrate the potential of PC‐based sensor array detection systems for clinical use.

Publisher

Wiley

Subject

Biomaterials,Biotechnology,General Materials Science,General Chemistry

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