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Abstract

Introduction:  AMI is one of the severe clinical conditions that affects the majority of patients with cardiovascular diseases within a short period, with significant risks of morbidity and mortality noted globally. Identifying the at-risk patients and prioritizing them into risk groups is critical. Comparative proteomics is planned to identify biomarkers that would help increase the accuracy of AMI patients' diagnosis and prognosis. Objective: To identify novel protein biomarkers for the early diagnosis and risk prediction of AMI using proteomic techniques, with the goal of improving clinical decision-making and patient management. Materials and Methods:   In the study, 100 AMI patients and 50 healthy individuals were taken. The blood plasma sample was collected as early as possible in the disease course, preferably within 24 hours after the onset of the symptoms. Quantitative proteomics was done using the Tandem Mass Tag (TMT), and bioinformatic tools analyzed the data. Results:  Forty-three proteins were significantly altered in AMI patients, with troponin 1, myosin light chain, and interleukin-6 exhibiting the most significant differential expression. High diagnostic accuracy was demonstrated with a multi-marker panel. Conclusion:  There is evidence that proteomic biomarkers could improve the diagnosis and prognosis of AMI, providing clinicians with targets for individualized treatments.