Novel Biomarkers for Predicting Acute Myocardial Infarction: A Proteomics Approach

Faiz Ullah; Atiq Ur Rehman; Rahim Dil Khan; Ijaz Mahmood; Ajmal Khan; Khushal Khan

doi:10.70749/ijbr.v3i5.1264

Authors

Faiz Ullah Department of Cardiology, Hayatabad Medical Complex, Peshawar, KP, Pakistan.
Atiq Ur Rehman Peshawar Institute of Cardiology, KP, Pakistan.
Rahim Dil Khan Department of Cardiology, Hayatabad Medical Complex, Peshawar, KP, Pakistan.
Ijaz Mahmood Hayatabad Medical Complex, Peshawar, KP, Pakistan.
Ajmal Khan Rehman College of Allied Health Science, Rehman Medical Institute, Peshawar, KP, Pakistan.
Khushal Khan Institute of Paramedical Sciences, Khyber Medical University Peshawar, KP, Pakistan.

DOI:

https://doi.org/10.70749/ijbr.v3i5.1264

Keywords:

Acute Myocardial Infarction, Proteomics, Biomarkers, Troponin I, Risk Prediction, Inflammatory Markers

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.

Downloads

Download data is not yet available.

References

Khalil, H. (2022). Traditional and novel diagnostic biomarkers for acute myocardial infarction. The Egyptian Journal of Internal Medicine, 34(1).

https://doi.org/10.1186/s43162-022-00178-w

Zhang, M., Tong, Z., Wang, N., Lin, K., Zhang, Y., Wang, D., Wang, X., Wang, P., Yang, Q., Kong, Y., Wang, M., Cui, J., Wang, Z., Cao, M., Li, L., Liu, Y., Li, Z., Fang, S., Zhang, F., … Yu, B. (2025). Novel protein-based biomarkers of out-of-hospital sudden cardiac death after myocardial infarction. Circulation: Arrhythmia and Electrophysiology, 18(4).

https://doi.org/10.1161/circep.124.013217

Shavadia, J. S., Alemayehu, W., DeFilippi, C., Westerhout, C. M., Tromp, J., Granger, C. B., Armstrong, P. W., & Van Diepen, S. (2021). Novel multi-marker proteomics in phenotypically matched patients with ST-segment myocardial infarction: Association with clinical outcomes. Journal of Thrombosis and Thrombolysis, 53(4), 841-850.

https://doi.org/10.1007/s11239-021-02582-5

Shi, L., Han, Y., Chen, J., Li, Z., Li, J., & Jiang, T. (2021). Screening and identification of potential protein biomarkers for the early diagnosis of acute myocardial infarction. Annals of Translational Medicine, 9(9), 743-743.

https://doi.org/10.21037/atm-20-7891

Hou, J., Deng, Q., Qiu, X., Liu, S., Li, Y., Huang, C., Wang, X., Zhang, Q., Deng, X., Zhong, Z., & Zhong, W. (2024). Proteomic analysis of plasma proteins from patients with cardiac rupture after acute myocardial infarction using TMT-based quantitative proteomics approach. Clinical Proteomics, 21(1).

https://doi.org/10.1186/s12014-024-09474-9

Nurmohamed, N. S., Belo Pereira, J. P., Hoogeveen, R. M., Kroon, J., Kraaijenhof, J. M., Waissi, F., Timmerman, N., Bom, M. J., Hoefer, I. E., Knaapen, P., Catapano, A. L., Koenig, W., De Kleijn, D., Visseren, F. L., Levin, E., & Stroes, E. S. (2022). Targeted proteomics improves cardiovascular risk prediction in secondary prevention. European Heart Journal, 43(16), 1569-1577.

https://doi.org/10.1093/eurheartj/ehac055

Lind, L., Zanetti, D., Ingelsson, M., Gustafsson, S., Ärnlöv, J., & Assimes, T. L. (2021). Large‐scale plasma protein profiling of incident myocardial infarction, ischemic stroke, and heart failure. Journal of the American Heart Association, 10(23).

https://doi.org/10.1161/jaha.121.023330

Eggers, K. M., Lindhagen, L., Baron, T., Erlinge, D., Hjort, M., Jernberg, T., Marko-Varga, G., Rezeli, M., Spaak, J., & Lindahl, B. (2021). Predicting outcome in acute myocardial infarction: An analysis investigating 175 circulating biomarkers. European Heart Journal. Acute Cardiovascular Care, 10(7), 806-812.

https://doi.org/10.1093/ehjacc/zuaa014

Xie, Y., Zhang, H., & Huang, T. (2022). Quantitative proteomics reveal three potential biomarkers for risk assessment of acute myocardial infarction. Bioengineered, 13(3), 4939-4950.

https://doi.org/10.1080/21655979.2022.2037365

Zhang, J., Hou, H., Song, Y., Guo, M., Liu, X., Yang, Q., & He, G. (2023). Proteomics study and protein biomarkers of malignant ventricular arrhythmia in acute myocardial infarction patients. Clinical and Translational Medicine, 13(11).

https://doi.org/10.1002/ctm2.1435

Huang, F., Chen, Z., Tan, B., He, R., Zhang, X., Chen, Y., Gao, J., & Sun, B. (2025). An exploratory study of high-throughput transcriptomic analysis reveals novel mRNA biomarkers for acute myocardial infarction using integrated methods. Scientific Reports, 15(1).

https://doi.org/10.1038/s41598-025-92757-4

Debrabant, B., Halekoh, U., Soerensen, M., Møller, J. E., Hassager, C., Frydland, M., Palstrøm, N., Hjelmborg, J., Beck, H. C., & Rasmussen, L. M. (2020). STEMI, Cardiogenic shock, and mortality in patients admitted for acute angiography: Associations and predictions from plasma Proteome data. Shock, 55(1), 41-47.

https://doi.org/10.1097/shk.0000000000001595

Wei, D., Li, R., Si, T., He, H., & Wu, W. (2021). Screening and bioinformatics analysis of key biomarkers in acute myocardial infarction. Pteridines, 32(1), 79-92.

https://doi.org/10.1515/pteridines-2020-0031

Stătescu, C., Anghel, L., Tudurachi, B., Leonte, A., Benchea, L., & Sascău, R. (2022). From classic to modern prognostic biomarkers in patients with acute myocardial infarction. International Journal of Molecular Sciences, 23(16), 9168.

https://doi.org/10.3390/ijms23169168

Wu, P., Glerup, R. I., Svensson, M. H., Eriksson, N., Christensen, J. H., Laval, P. D., Soveri, I., Westerlund, M., Linde, T., Ljunggren, Ö., & Fellström, B. (2022). Novel biomarkers detected by Proteomics predict death and cardiovascular events in hemodialysis patients. Biomedicines, 10(4), 740.

https://doi.org/10.3390/biomedicines10040740