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Lee GY, Li AA, Moon I, Katritsis D, Pantos Y, Stingo F, Fabbrico D, Molinaro R, Taraballi F, Tao W, Corbo C. Protein Corona Sensor Array Nanosystem for Detection of Coronary Artery Disease. Small 2024; 20:e2306168. [PMID: 37880910 DOI: 10.1002/smll.202306168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 09/26/2023] [Indexed: 10/27/2023]
Abstract
Coronary 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.
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Affiliation(s)
- Gha Young Lee
- Center for Nanomedicine, Department of Anesthesiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Andrew A Li
- Tepper School of Business, Carnegie Mellon University, Pittsburgh, PA, 15213, USA
| | - Intae Moon
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, 4307, USA
| | - Demos Katritsis
- Comprehensive Cardiology Care at Hygeia Hospital, Athens, 15123, Greece
- Johns Hopkins Medicine, Baltimore, MD, 21287, USA
| | - Yoannis Pantos
- Comprehensive Cardiology Care at Hygeia Hospital, Athens, 15123, Greece
| | - Francesco Stingo
- Department of Statistics, Computer Sciences and Applications, University of Florence, Florence, 50121, Italy
| | - Davide Fabbrico
- Department of Statistics, Computer Sciences and Applications, University of Florence, Florence, 50121, Italy
| | - Roberto Molinaro
- Department of Cardiovascular, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Francesca Taraballi
- Center for Musculoskeletal Regeneration, Houston Methodist Academic Institute & Orthopedics and Sports Medicine, Houston Methodist Hospital, Houston, TX, 77030, USA
| | - Wei Tao
- Center for Nanomedicine, Department of Anesthesiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Claudia Corbo
- University of Milano-Bicocca, Department of Medicine and Surgery, NANOMIB Center, Monza, 20900, Italy
- IRCCS Istituto Ortopedico Galeazzi, Milan, 20161, Italy
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