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Opportunities for microRNAs in the crowded field of cardiovascular biomarkers

Halushka, Perry V., Goodwin, Andrew J., Halushka, Marc K.·2019·Annual Review of Pathology: Mechanisms of Disease

Abstract

Cardiovascular diseases exist across all developed countries. Biomarkers that can predict or diagnose diseases early in their pathogeneses can reduce their morbidity and mortality in afflicted individuals. microRNAs are small regulatory RNAs that modulate translation and have been identified as potential fluid-based biomarkers across numerous maladies. We describe the current state of cardiovascular disease biomarkers across a range of diseases, including myocardial infarction, acute coronary syndrome, myocarditis, hypertension, heart failure, heart transplantation, aortic stenosis, diabetic cardiomyopathy, atrial fibrillation, and sepsis. We present the current understanding of microRNAs as possible biomarkers in these categories and where their best opportunities exist to enter clinical practice.

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  • miRNAs demonstrate altered expression levels in disease states that may have biomarker potential.

    “They also demonstrate altered expression levels in disease states that may have biomarker potential [3, 4].”

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Sorted by citations

Authors
Halushka, P. V., Goodwin, A. J., & Halushka, M. K.
Affiliations
  • Department of Pharmacology, South Carolina Clinical and Translational Research Institute, Medical University of South Carolina, Charleston, South Carolina 29425, USA;
  • Division of Pulmonary, Critical Care, Allergy, and Sleep Medicine, Medical University of South Carolina, Charleston, South Carolina 29425, USA;
  • Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA;
Venue
Annual Review of Pathology: Mechanisms of Disease
Published
2019-01-24
Volume
14
Issue
1
Pages
211-238
ISSN
  • 1553-4006
  • 1553-4014
Cited by
61
References
10
Language
en

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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