Cells (Feb 2022)

Dissecting miRNA–Gene Networks to Map Clinical Utility Roads of Pharmacogenomics-Guided Therapeutic Decisions in Cardiovascular Precision Medicine

  • Fani Chatzopoulou,
  • Konstantinos A. Kyritsis,
  • Christos I. Papagiannopoulos,
  • Eleftheria Galatou,
  • Nikolaos Mittas,
  • Nikoleta F. Theodoroula,
  • Andreas S. Papazoglou,
  • Efstratios Karagiannidis,
  • Maria Chatzidimitriou,
  • Anna Papa,
  • Georgios Sianos,
  • Lefteris Angelis,
  • Dimitrios Chatzidimitriou,
  • Ioannis S. Vizirianakis

DOI
https://doi.org/10.3390/cells11040607
Journal volume & issue
Vol. 11, no. 4
p. 607

Abstract

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MicroRNAs (miRNAs) create systems networks and gene-expression circuits through molecular signaling and cell interactions that contribute to health imbalance and the emergence of cardiovascular disorders (CVDs). Because the clinical phenotypes of CVD patients present a diversity in their pathophysiology and heterogeneity at the molecular level, it is essential to establish genomic signatures to delineate multifactorial correlations, and to unveil the variability seen in therapeutic intervention outcomes. The clinically validated miRNA biomarkers, along with the relevant SNPs identified, have to be suitably implemented in the clinical setting in order to enhance patient stratification capacity, to contribute to a better understanding of the underlying pathophysiological mechanisms, to guide the selection of innovative therapeutic schemes, and to identify innovative drugs and delivery systems. In this article, the miRNA–gene networks and the genomic signatures resulting from the SNPs will be analyzed as a method of highlighting specific gene-signaling circuits as sources of molecular knowledge which is relevant to CVDs. In concordance with this concept, and as a case study, the design of the clinical trial GESS (NCT03150680) is referenced. The latter is presented in a manner to provide a direction for the improvement of the implementation of pharmacogenomics and precision cardiovascular medicine trials.

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