Literature DB >> 31141242

Circulating microRNAs in suspected stable coronary artery disease: A coronary computed tomography angiography study.

David de Gonzalo-Calvo1,2,3, David Vilades4, Pablo Martínez-Camblor5, Àngela Vea2, Laura Nasarre2, Jesus Sanchez Vega4, Rubén Leta4, Francesc Carreras3,4, Vicenta Llorente-Cortés1,2,3.   

Abstract

OBJECTIVES: To explore the diagnostic performance of circulating microRNAs (miRNAs) as biomarkers in patients with suspected stable coronary artery disease (CAD).
METHODS: Plasma samples were collected from 237 consecutive patients referred for coronary computed tomography angiography (CCTA). Presence, extension and severity of coronary stenosis were evaluated using the indexes: presence of diameter stenosis ≥ 50%, segment involvement score (SIS), segment stenosis score (SSS) and 3-vessel plaque score. A panel of 10 miRNAs previously associated with CAD was analysed using RT-qPCR. Multivariate analyses were used to analyse the associations between biomarkers and indexes. Discrimination was evaluated using the area under the ROC curve (AUC). Decision trees were generated using chi-squared Automatic Interaction Detector (CHAID) prediction models.
RESULTS: After comprehensive adjustment including cardiovascular risk factors, medication use, confounding factors and protein-based biomarkers (hs-TnT and hs-CRP), several circulating miRNAs were inversely associated with coronary atherosclerosis extension (SIS and 3-vessel plaque score) and severity (SSS). In the whole population, circulating miRNAs showed a poor discrimination value for all indexes (AUC = 0.539-0.644) and did not increase the discrimination capacity of a clinical model of coronary stenosis presence, extension and severity based on conventional cardiovascular risk factors. Conversely, the inclusion of circulating miRNAs in decision trees produces models that improve the classification of cases and controls in specific patient subgroups.
CONCLUSIONS: This study identifies a group of circulating miRNAs that failed to improve the discrimination capacity of cardiovascular risk factors but that has the potential to define specific subpopulations of patients with suspected stable CAD.
© 2019 The Association for the Publication of the Journal of Internal Medicine.

Entities:  

Keywords:  biomarker; coronary artery disease; coronary atherosclerosis; coronary heart disease; microRNA

Mesh:

Substances:

Year:  2019        PMID: 31141242     DOI: 10.1111/joim.12921

Source DB:  PubMed          Journal:  J Intern Med        ISSN: 0954-6820            Impact factor:   8.989


  7 in total

Review 1.  Peripheral blood microRNAs and the COVID-19 patient: methodological considerations, technical challenges and practice points.

Authors:  Lucía Pinilla; Ivan D Benitez; Jessica González; Gerard Torres; Ferran Barbé; David de Gonzalo-Calvo
Journal:  RNA Biol       Date:  2021-02-15       Impact factor: 4.652

2.  Development and Validation of a Predictive Model for Coronary Artery Disease Using Machine Learning.

Authors:  Chen Wang; Yue Zhao; Bingyu Jin; Xuedong Gan; Bin Liang; Yang Xiang; Xiaokang Zhang; Zhibing Lu; Fang Zheng
Journal:  Front Cardiovasc Med       Date:  2021-02-02

3.  Challenges of microRNA-based biomarkers in clinical application for cardiovascular diseases.

Authors:  David de Gonzalo-Calvo; Jennifer Pérez-Boza; Joao Curado; Yvan Devaux
Journal:  Clin Transl Med       Date:  2022-02

4.  The Profile of Circulating Blood microRNAs in Outpatients with Vulnerable and Stable Atherosclerotic Plaques: Associations with Cardiovascular Risks.

Authors:  Andrey N Rozhkov; Dmitry Yu Shchekochikhin; Yaroslav I Ashikhmin; Yulia O Mitina; Veronika V Evgrafova; Andrey V Zhelankin; Daria G Gognieva; Anna S Akselrod; Philippe Yu Kopylov
Journal:  Noncoding RNA       Date:  2022-06-29

5.  Monocyte-to-albumin ratio as a novel predictor of long-term adverse outcomes in patients after percutaneous coronary intervention.

Authors:  Zeng-Lei Zhang; Qian-Qian Guo; Jun-Nan Tang; Jian-Chao Zhang; Meng-Die Cheng; Feng-Hua Song; Zhi-Yu Liu; Kai Wang; Li-Zhu Jiang; Lei Fan; Xiao-Ting Yue; Yan Bai; Xin-Ya Dai; Ru-Jie Zheng; Ying-Ying Zheng; Jin-Ying Zhang
Journal:  Biosci Rep       Date:  2021-07-30       Impact factor: 3.840

6.  Association of Circulating microRNAs with Coronary Artery Disease and Usefulness for Reclassification of Healthy Individuals: The REGICOR Study.

Authors:  Irene R Dégano; Anna Camps-Vilaró; Isaac Subirana; Nadia García-Mateo; Pilar Cidad; Dani Muñoz-Aguayo; Eulàlia Puigdecanet; Lara Nonell; Joan Vila; Felipe M Crepaldi; David de Gonzalo-Calvo; Vicenta Llorente-Cortés; María Teresa Pérez-García; Roberto Elosua; Montserrat Fitó; Jaume Marrugat
Journal:  J Clin Med       Date:  2020-05-09       Impact factor: 4.241

7.  Improved cardiovascular risk prediction in patients with end-stage renal disease on hemodialysis using machine learning modeling and circulating microribonucleic acids.

Authors:  David de Gonzalo-Calvo; Pablo Martínez-Camblor; Christian Bär; Kevin Duarte; Nicolas Girerd; Bengt Fellström; Roland E Schmieder; Alan G Jardine; Ziad A Massy; Hallvard Holdaas; Patrick Rossignol; Faiez Zannad; Thomas Thum
Journal:  Theranostics       Date:  2020-07-09       Impact factor: 11.556

  7 in total

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