RESEARCH ARTICLE
Open Access

MicroRNA-21 and MicroRNA-208a as Biomarkers of Myocardial Remodeling Post-Infarction

Alessandro Conti1, Francesca Rinaldi2 ORCID 

1Department of Cardiology, Sapienza University of Rome, Rome, Italy.
2Department of Molecular Medicine, University of Milan, Milan, Italy.
DOI: 10.18081/ajbm.2026.2.82

Publication History: Received 12 December 2025, Revised 04 February 2026, Accepted 30 March 2026, Available online 10 April 2026
Copyright: © 2026 Moreau, et al. This is an open-access article under a Creative Commons license (CC BY 4.0).

ABSTRACT

Background

Myocardial remodeling following acute myocardial infarction (AMI) is a critical determinant of long-term cardiac function and progression to heart failure. Conventional biomarkers provide limited insight into the molecular mechanisms underlying this process. MicroRNAs (miRNAs), particularly microRNA-21 (miR-21) and microRNA-208a (miR-208a), have emerged as potential regulators of fibrosis and myocardial injury, respectively, and may serve as novel biomarkers of post-infarction remodeling.

Methods

This prospective observational study was conducted at two tertiary centers in Italy and included 60 patients with confirmed AMI and 20 healthy controls. Plasma levels of miR-21 and miR-208a were measured using quantitative real-time PCR at admission (T0), 72 hours (T1), and 3 months (T2). Echocardiographic assessment of left ventricular function and volumes was performed at baseline and 3-month follow-up. Adverse remodeling was defined as a ≥20% increase in left ventricular end-diastolic volume. Statistical analysis included correlation studies, receiver operating characteristic (ROC) curve analysis, and multivariate logistic regression.

Results

Both miR-21 and miR-208a levels were significantly elevated in AMI patients compared to controls (p < 0.001). MiR-21 peaked at 72 hours (5.2 ± 1.6-fold increase), while miR-208a showed highest levels at admission (4.5 ± 1.5-fold). Adverse remodeling occurred in 36.7% of patients. MiR-21 levels were significantly higher in patients with remodeling (5.9 ± 1.4 vs 3.7 ± 1.1; p < 0.001) and showed strong correlations with left ventricular ejection fraction (r = −0.62) and LVEDV (r = 0.58). MiR-208a correlated with troponin levels (r = 0.65, p < 0.001) and remodeling status (p = 0.002). ROC analysis demonstrated good predictive performance for miR-21 (AUC = 0.87) and miR-208a (AUC = 0.82), with improved accuracy when combined (AUC = 0.91). Multivariate analysis identified miR-21 and miR-208a as independent predictors of remodeling.

Conclusion

Circulating miR-21 and miR-208a are promising non-invasive biomarkers for assessing myocardial remodeling following AMI. MiR-21 is strongly associated with fibrotic remodeling, whereas miR-208a reflects myocardial injury severity. Their combined use enhances predictive accuracy and may support early risk stratification and personalized management of patients with post-infarction conditions.

Keywords: MicroRNA-21; MicroRNA-208a; Myocardial Infarction; Cardiac Remodeling; Biomarkers; Left Ventricular Dysfunction; Fibrosis.

Recommended Citation

Conti A, Rinaldi F. MicroRNA-21 and MicroRNA-208a as Biomarkers of Myocardial Remodeling Post-Infarction. Advanced Journal of Biomedicine & Medicine. 2026;14(1):82-98. doi:10.18081/ajbm.2026.2.82

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Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.


References

  1. Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020. CA Cancer J Clin. 2021;71(3):209-249. doi:10.3322/caac.21660
  2. Herbst RS, Morgensztern D, Boshoff C. The biology and management of NSCLC. 2018;553(7689):446-454. doi:10.1038/nature25183
  3. Mok TSK, Wu YL, Ahn MJ, et al. Osimertinib or platinum-pemetrexed in EGFR T790M NSCLC. N Engl J Med. 2017;376:629-640. doi:10.1056/NEJMoa1612674
  4. Soria JC, Ohe Y, Vansteenkiste J, et al. Osimertinib in untreated EGFR NSCLC. N Engl J Med. 2018;378:113-125. doi:10.1056/NEJMoa1713137
  5. Reck M, Rodríguez-Abreu D, Robinson AG, et al. Pembrolizumab vs chemotherapy. N Engl J Med. 2016;375:1823-1833. doi:10.1056/NEJMoa1606774
  6. Gandhi L, Rodríguez-Abreu D, Gadgeel S, et al. Pembrolizumab plus chemotherapy. N Engl J Med. 2018;378:2078-2092. doi:10.1056/NEJMoa1801005
  7. Hellmann MD, Ciuleanu TE, Pluzanski A, et al. Nivolumab plus ipilimumab. N Engl J Med. 2018;378:2093-2104. doi:10.1056/NEJMoa1716948
  8. Bettegowda C, Sausen M, Leary RJ, et al. Detection of ctDNA. Sci Transl Med. 2014;6:224ra24. doi:10.1126/scitranslmed.3007094
  9. Wan JCM, Massie C, Garcia-Corbacho J, et al. Liquid biopsies. Nat Rev Cancer. 2017;17:223-238. doi:10.1038/nrc.2017.7
  10. Newman AM, Bratman SV, To J, et al. Error suppression for ctDNA detection. Nat Biotechnol. 2016;34:547-555. doi:10.1038/nbt.3520
  11. Chaudhuri AA, Chabon JJ, Lovejoy AF, et al. Early detection of residual disease. 2017;545:446-451. doi:10.1038/nature22364
  12. Dawson SJ, Tsui DWY, Murtaza M, et al. ctDNA biomarker. N Engl J Med. 2013;368:1199-1209. doi:10.1056/NEJMoa1213261
  13. Oxnard GR, Paweletz CP, Kuang Y, et al. Noninvasive resistance detection. Clin Cancer Res. 2014;20:1698-1705. doi:10.1158/1078-0432.CCR-13-2482
  14. Thress KS, Paweletz CP, Felip E, et al. EGFR C797S resistance. Nat Med. 2015;21:560-562. doi:10.1038/nm.3854
  15. Piotrowska Z, Isozaki H, Lennerz JK, et al. MET amplification resistance. Cancer Discov. 2015;5:1281-1287. doi:10.1158/2159-8290.CD-15-0566
  16. Engelman JA, Zejnullahu K, Mitsudomi T, et al. MET pathway resistance. 2007;316:1039-1043. doi:10.1126/science.1141478
  17. Merker JD, Oxnard GR, Compton C, et al. ctDNA applications. J Clin Oncol. 2018;36:1631-1641. doi:10.1200/JCO.2017.76.8671
  18. Rolfo C, Mack P, Scagliotti GV, et al. Liquid biopsy standardization. J Thorac Oncol. 2018;13:1248-1268. doi:10.1016/j.jtho.2018.05.030
  19. Abbosh C, Birkbak NJ, Wilson GA, et al. Evolutionary NSCLC. 2017;545:446-451. doi:10.1038/nature22364
  20. Goldberg SB, Narayan A, Kole AJ, et al. ctDNA and immunotherapy. Clin Cancer Res. 2018;24:1872-1880. doi:10.1158/1078-0432.CCR-17-3465
  21. Hellmann MD, Nabet BY, Rizvi H, et al. ctDNA predicts response. Cancer Discov. 2020;10:1876-1889. doi:10.1158/2159-8290.CD-20-0923
  22. Cristiano S, Leal A, Phallen J, et al. Fragmentomics. 2019;570:385-389. doi:10.1038/s41586-019-1272-6
  23. Phallen J, Sausen M, Adleff V, et al. Early cancer detection. Sci Transl Med. 2017;9:eaan2415. doi:10.1126/scitranslmed.aan2415
  24. Tie J, Cohen JD, Wang Y, et al. ctDNA-guided therapy. Sci Transl Med. 2019;11:eaay5680. doi:10.1126/scitranslmed.aay5680
  25. Yarchoan M, Hopkins A, Jaffee EM. TMB biomarker. Nat Rev Cancer. 2017;17:209-222. doi:10.1038/nrc.2017.7
  26. Rizvi NA, Hellmann MD, Snyder A, et al. Mutational landscape. 2015;348:124-128. doi:10.1126/science.aaa1348
  27. McGranahan N, Furness AJ, Rosenthal R, et al. Neoantigens. 2016;351:1463-1469. doi:10.1126/science.aaf1490
  28. Havel JJ, Chowell D, Chan TA. Biomarkers. Nat Rev Cancer. 2019;19:133-150. doi:10.1038/s41568-019-0116-x
  29. Litchfield K, Reading JL, Lim EL, et al. Neoantigen quality. 2021;184:1135-1151. doi:10.1016/j.cell.2021.01.018
  30. Swanton C, McGranahan N. APOBEC mutagenesis. Cancer Discov. 2018;8:430-452. doi:10.1158/2159-8290.CD-18-0107
  31. Brown BP, Moser RJ, Jones JD. Multi-omics. Nat Biotechnol. 2020;38:1180-1193. doi:10.1038/s41587-020-0649-2
  32. Casadevall D, Clavé S, Taus Á, et al. Multi-omics in cancer. Clin Cancer Res. 2022;28:4699-4712. doi:10.1158/1078-0432.CCR-22-0621
  33. Cristescu R, Mogg R, Ayers M, et al. Genomic biomarkers. 2018;362:eaar3593. doi:10.1126/science.aar3593
  34. Chowell D, Morris LGT, Grigg CM, et al. HLA genotype. 2018;359:582-587. doi:10.1126/science.aao4572
  35. Oh DY, Kwek S, Raju SS, et al. Immune transcriptomics. Nat Med. 2020;26:1931-1939. doi:10.1038/s41591-020-1138-8
  36. Pinato DJ, Howlett S, Ottaviani D, et al. Antibiotics impact. J Clin Oncol. 2019;37:3168-3177. doi:10.1200/JCO.19.01472
  37. Routy B, Le Chatelier E, Derosa L, et al. Microbiome and ICI. 2018;359:91-97. doi:10.1126/science.aan3706
  38. Gopalakrishnan V, Spencer CN, Nezi L, et al. Microbiome modulates ICI. 2018;359:97-103. doi:10.1126/science.aan4236
  39. Matson V, Fessler J, Bao R, et al. Microbiome and immunity. 2018;359:104-108. doi:10.1126/science.aao3290
  40. Baruch EN, Youngster I, Ben-Betzalel G, et al. FMT restores response. 2021;371:602-609. doi:10.1126/science.abb5920
  41. Lee KA, Thomas AM, Bolte LA, et al. Cross-cohort microbiome. Nat Med. 2022;28:774-785. doi:10.1038/s41591-022-01695-5
  42. Greathouse KL, White JR, Vargas AJ, et al. Microbiome interactions. Nat Rev Immunol. 2023;23:32-45. doi:10.1038/s41577-022-00746-7
  43. Wu SY, Sharma R, Kok M, et al. Future of multi-omics. Nat Rev Clin Oncol. 2022;19:563-582. doi:10.1038/s41571-022-00644-1
  44. Gettinger SN, Choi J, Hastings K, et al. HLA loss resistance. Cancer Discov. 2017;7:1420-1435. doi:10.1158/2159-8290.CD-17-0899
  45. Arora S, Velichinskii R, Lesh RW. Biomarkers lung cancer. J Thorac Dis. 2019;11:S1787-S1798. doi:10.21037/jtd.2019.08.63
  46. Sequist LV, Han JY, Ahn MJ, et al. Combination targeted therapy. J Clin Oncol. 2020;38:950-957. doi:10.1200/JCO.19.03163
  47. Tie J, Wang Y, Tomasetti C, et al. ctDNA in colorectal cancer. Sci Transl Med. 2016;8:346ra92. doi:10.1126/scitranslmed.aaf6219
  48. Bivona TG, Doebele RC. Resistance mechanisms. Nat Rev Cancer. 2016;16:321-335. doi:10.1038/nrc.2016.38
  49. Rolfo C, Castiglia M, Hong D, et al. Liquid biopsy advances. Cancer Treat Rev. 2020;86:102013. doi:10.1016/j.ctrv.2020.102013
  50. Siravegna G, Marsoni S, Siena S, et al. Integrating ctDNA. Nat Rev Clin Oncol. 2017;14:531-548. doi:10.1038/nrclinonc.2017.14

2026 Vol 14, Issue 2 Pages 82-98

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Laurent P, Martin S, Moreau J (2026). MicroRNA-21 and MicroRNA-208a as Biomarkers of Myocardial Remodeling Post-Infarction<br /> . Advanced Journal of Biomedicine & Medicine, 14(1), 57-81. https://doi.org/10.18081/ajbm.2026.2.82
Laurent P, Martin S, Moreau J. "MicroRNA-21 and MicroRNA-208a as Biomarkers of Myocardial Remodeling Post-Infarction<br /> ." Advanced Journal of Biomedicine & Medicine, vol. 14, no. 1, 2026, pp. 57-81. DOI: 10.18081/ajbm.2026.2.82.
Laurent P, Martin S, Moreau J. MicroRNA-21 and MicroRNA-208a as Biomarkers of Myocardial Remodeling Post-Infarction<br /> . AJBM. 2026;14(1):57-81. DOI: 10.18081/ajbm.2026.2.82. PMID: .
Laurent P, Martin S, Moreau J 2026, "MicroRNA-21 and MicroRNA-208a as Biomarkers of Myocardial Remodeling Post-Infarction<br /> ", Advanced Journal of Biomedicine & Medicine, vol. 14, no. 1, pp. 57-81.
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Laurent P, Martin S, Moreau J (2026). MicroRNA-21 and MicroRNA-208a as Biomarkers of Myocardial Remodeling Post-Infarction<br /> . Advanced Journal of Biomedicine & Medicine, 14(1), 57-81. https://doi.org/10.18081/ajbm.2026.2.82

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