Three-Biomarker Joint Strategy for Early and Accurate Diagnosis of Acute Myocardial Infarction via a Multiplex Electrochemiluminescence Immunoarray Coupled with Robust Machine Learning
Acute myocardial infarction (AMI) represents a leading cause of death globally. Key to AMI recovery is timely diagnosis and initiation of treatment, ideally within 3 h of symptom onset. Cardiac troponin T (cTnT) is the gold standard yet a low cTnT result cannot rule out AMI at early times. Here, we...
| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
American Chemical Society
2023-04-01
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| Series: | Chemical & Biomedical Imaging |
| Online Access: | https://doi.org/10.1021/cbmi.3c00035 |
| _version_ | 1797739821810057216 |
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| author | Mingquan Guo Dexin Du Jue Wang Yao Ma Di Yang Mohammad A. Haghighatbin Jiangnan Shu Wei Nie Ruoxian Zhang Zhiping Bian Liansheng Wang Zachary J. Smith Hua Cui |
| author_facet | Mingquan Guo Dexin Du Jue Wang Yao Ma Di Yang Mohammad A. Haghighatbin Jiangnan Shu Wei Nie Ruoxian Zhang Zhiping Bian Liansheng Wang Zachary J. Smith Hua Cui |
| author_sort | Mingquan Guo |
| collection | DOAJ |
| description | Acute myocardial infarction (AMI) represents a leading cause of death globally. Key to AMI recovery is timely diagnosis and initiation of treatment, ideally within 3 h of symptom onset. Cardiac troponin T (cTnT) is the gold standard yet a low cTnT result cannot rule out AMI at early times. Here, we develop a three-biomarker joint strategy for early and accurate diagnosis of AMI via an electrochemiluminescence (ECL) immunoarray coupled with robust machine learning. The ECL immunoarray is based on an array microchip with a single-electrode and chemiluminescent immuno-Gold (ciGold) nanoassemblies. The ciGold immunoarray was obtained by successively assembling nanocomposites of Cu2+/cysteine complexes and N-(aminobutyl)-N-(ethylisoluminol) bifunctionalized gold nanoparticles combined with chitosan and antibody conjugated gold nanoparticles on the surface of a microchip. Three biomarkers, including cardiac troponin I, heart type fatty acid binding protein, and copeptin, were simultaneously detected in 260 serum samples from patients presenting with chest pain by an innovative multiplexed ECL immunoarray, and classified via the three-biomarker joint assessment model using support vector machines. The model achieved perfect discrimination (100% sensitivity and specificity) for AMI vs non-AMI patients, substantially higher than cTnT alone. Within 12 h of symptom onset, high-sensitivity cardiac troponin T (hs-cTnT) misclassified >20% of patients, while the joint biomarker assessment model retained perfect accuracy. As the time between symptom onset and testing became shorter, the degree to which the joint assessment model outperformed hs-cTnT increased. The proposed three-biomarker joint strategy is obviously superior to hs-cTnT for early and accurate diagnosis of AMI, hopefully reducing AMI mortality and saving limited medical resources. |
| first_indexed | 2024-03-12T14:03:42Z |
| format | Article |
| id | doaj.art-5dddd8fb350e46488e139ba3a47dc5c6 |
| institution | Directory Open Access Journal |
| issn | 2832-3637 |
| language | English |
| last_indexed | 2024-03-12T14:03:42Z |
| publishDate | 2023-04-01 |
| publisher | American Chemical Society |
| record_format | Article |
| series | Chemical & Biomedical Imaging |
| spelling | doaj.art-5dddd8fb350e46488e139ba3a47dc5c62023-08-21T17:58:16ZengAmerican Chemical SocietyChemical & Biomedical Imaging2832-36372023-04-011217918510.1021/cbmi.3c00035Three-Biomarker Joint Strategy for Early and Accurate Diagnosis of Acute Myocardial Infarction via a Multiplex Electrochemiluminescence Immunoarray Coupled with Robust Machine LearningMingquan Guo0Dexin Du1Jue Wang2Yao Ma3Di Yang4Mohammad A. Haghighatbin5Jiangnan Shu6Wei Nie7Ruoxian Zhang8Zhiping Bian9Liansheng Wang10Zachary J. Smith11Hua Cui12Key Laboratory of Precision and Intelligent Chemistry, iChEM (Collaborative Innovation Center of Chemistry for Energy Materials), Department of Chemistry, University of Science and Technology of China, Hefei, Anhui, P. R. ChinaKey Laboratory of Precision and Intelligent Chemistry, iChEM (Collaborative Innovation Center of Chemistry for Energy Materials), Department of Chemistry, University of Science and Technology of China, Hefei, Anhui, P. R. ChinaKey Laboratory of Precision and Intelligent Chemistry, iChEM (Collaborative Innovation Center of Chemistry for Energy Materials), Department of Chemistry, University of Science and Technology of China, Hefei, Anhui, P. R. ChinaInstitute of Cardiovascular Disease, First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, PR ChinaInstitute of Cardiovascular Disease, First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, PR ChinaKey Laboratory of Precision and Intelligent Chemistry, iChEM (Collaborative Innovation Center of Chemistry for Energy Materials), Department of Chemistry, University of Science and Technology of China, Hefei, Anhui, P. R. ChinaKey Laboratory of Precision and Intelligent Chemistry, iChEM (Collaborative Innovation Center of Chemistry for Energy Materials), Department of Chemistry, University of Science and Technology of China, Hefei, Anhui, P. R. ChinaKey Laboratory of Precision and Intelligent Chemistry, iChEM (Collaborative Innovation Center of Chemistry for Energy Materials), Department of Chemistry, University of Science and Technology of China, Hefei, Anhui, P. R. ChinaKey Laboratory of Precision and Intelligent Chemistry, iChEM (Collaborative Innovation Center of Chemistry for Energy Materials), Department of Chemistry, University of Science and Technology of China, Hefei, Anhui, P. R. ChinaInstitute of Cardiovascular Disease, First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, PR ChinaInstitute of Cardiovascular Disease, First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, PR ChinaKey Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, Anhui, P. R. ChinaKey Laboratory of Precision and Intelligent Chemistry, iChEM (Collaborative Innovation Center of Chemistry for Energy Materials), Department of Chemistry, University of Science and Technology of China, Hefei, Anhui, P. R. ChinaAcute myocardial infarction (AMI) represents a leading cause of death globally. Key to AMI recovery is timely diagnosis and initiation of treatment, ideally within 3 h of symptom onset. Cardiac troponin T (cTnT) is the gold standard yet a low cTnT result cannot rule out AMI at early times. Here, we develop a three-biomarker joint strategy for early and accurate diagnosis of AMI via an electrochemiluminescence (ECL) immunoarray coupled with robust machine learning. The ECL immunoarray is based on an array microchip with a single-electrode and chemiluminescent immuno-Gold (ciGold) nanoassemblies. The ciGold immunoarray was obtained by successively assembling nanocomposites of Cu2+/cysteine complexes and N-(aminobutyl)-N-(ethylisoluminol) bifunctionalized gold nanoparticles combined with chitosan and antibody conjugated gold nanoparticles on the surface of a microchip. Three biomarkers, including cardiac troponin I, heart type fatty acid binding protein, and copeptin, were simultaneously detected in 260 serum samples from patients presenting with chest pain by an innovative multiplexed ECL immunoarray, and classified via the three-biomarker joint assessment model using support vector machines. The model achieved perfect discrimination (100% sensitivity and specificity) for AMI vs non-AMI patients, substantially higher than cTnT alone. Within 12 h of symptom onset, high-sensitivity cardiac troponin T (hs-cTnT) misclassified >20% of patients, while the joint biomarker assessment model retained perfect accuracy. As the time between symptom onset and testing became shorter, the degree to which the joint assessment model outperformed hs-cTnT increased. The proposed three-biomarker joint strategy is obviously superior to hs-cTnT for early and accurate diagnosis of AMI, hopefully reducing AMI mortality and saving limited medical resources.https://doi.org/10.1021/cbmi.3c00035 |
| spellingShingle | Mingquan Guo Dexin Du Jue Wang Yao Ma Di Yang Mohammad A. Haghighatbin Jiangnan Shu Wei Nie Ruoxian Zhang Zhiping Bian Liansheng Wang Zachary J. Smith Hua Cui Three-Biomarker Joint Strategy for Early and Accurate Diagnosis of Acute Myocardial Infarction via a Multiplex Electrochemiluminescence Immunoarray Coupled with Robust Machine Learning Chemical & Biomedical Imaging |
| title | Three-Biomarker Joint Strategy for Early and Accurate Diagnosis of Acute Myocardial Infarction via a Multiplex Electrochemiluminescence Immunoarray Coupled with Robust Machine Learning |
| title_full | Three-Biomarker Joint Strategy for Early and Accurate Diagnosis of Acute Myocardial Infarction via a Multiplex Electrochemiluminescence Immunoarray Coupled with Robust Machine Learning |
| title_fullStr | Three-Biomarker Joint Strategy for Early and Accurate Diagnosis of Acute Myocardial Infarction via a Multiplex Electrochemiluminescence Immunoarray Coupled with Robust Machine Learning |
| title_full_unstemmed | Three-Biomarker Joint Strategy for Early and Accurate Diagnosis of Acute Myocardial Infarction via a Multiplex Electrochemiluminescence Immunoarray Coupled with Robust Machine Learning |
| title_short | Three-Biomarker Joint Strategy for Early and Accurate Diagnosis of Acute Myocardial Infarction via a Multiplex Electrochemiluminescence Immunoarray Coupled with Robust Machine Learning |
| title_sort | three biomarker joint strategy for early and accurate diagnosis of acute myocardial infarction via a multiplex electrochemiluminescence immunoarray coupled with robust machine learning |
| url | https://doi.org/10.1021/cbmi.3c00035 |
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