Next Article in Journal
β1 Integrin as a Prognostic and Predictive Marker in Triple-Negative Breast Cancer
Next Article in Special Issue
Effect of Genetic Polymorphisms and Long-Term Tobacco Exposure on the Risk of Breast Cancer
Previous Article in Journal
Lipid Droplets: A Key Cellular Organelle Associated with Cancer Cell Survival under Normoxia and Hypoxia
Previous Article in Special Issue
Chromosome 9p21 and ABCA1 Genetic Variants and Their Interactions on Coronary Heart Disease and Ischemic Stroke in a Chinese Han Population
Article Menu
Issue 9 (September) cover image

Export Article

Open AccessArticle
Int. J. Mol. Sci. 2016, 17(9), 1385; doi:10.3390/ijms17091385

A Genomics-Based Model for Prediction of Severe Bioprosthetic Mitral Valve Calcification

1
Research Institute for Complex Issues of Cardiovascular Diseases, Sosnovy Boulvevard 6, Kemerovo 650002, Russia
2
Department of Oncology, Cancer Research UK and Medical Research Council Oxford Institute for Radiation Oncology, University of Oxford, Old Road Campus Research Building, Roosevelt Drive, Oxford OX3 7DQ, UK
*
Author to whom correspondence should be addressed.
Academic Editor: Emil Alexov
Received: 23 June 2016 / Revised: 9 August 2016 / Accepted: 19 August 2016 / Published: 31 August 2016
(This article belongs to the Collection Human Single Nucleotide Polymorphisms and Disease Diagnostics)
View Full-Text   |   Download PDF [1095 KB, uploaded 31 August 2016]   |  

Abstract

Severe bioprosthetic mitral valve calcification is a significant problem in cardiovascular surgery. Unfortunately, clinical markers did not demonstrate efficacy in prediction of severe bioprosthetic mitral valve calcification. Here, we examined whether a genomics-based approach is efficient in predicting the risk of severe bioprosthetic mitral valve calcification. A total of 124 consecutive Russian patients who underwent mitral valve replacement surgery were recruited. We investigated the associations of the inherited variation in innate immunity, lipid metabolism and calcium metabolism genes with severe bioprosthetic mitral valve calcification. Genotyping was conducted utilizing the TaqMan assay. Eight gene polymorphisms were significantly associated with severe bioprosthetic mitral valve calcification and were therefore included into stepwise logistic regression which identified male gender, the T/T genotype of the rs3775073 polymorphism within the TLR6 gene, the C/T genotype of the rs2229238 polymorphism within the IL6R gene, and the A/A genotype of the rs10455872 polymorphism within the LPA gene as independent predictors of severe bioprosthetic mitral valve calcification. The developed genomics-based model had fair predictive value with area under the receiver operating characteristic (ROC) curve of 0.73. In conclusion, our genomics-based approach is efficient for the prediction of severe bioprosthetic mitral valve calcification. View Full-Text
Keywords: bioprosthetic heart valve; calcification; interleukin-6; genetic association; predictive model bioprosthetic heart valve; calcification; interleukin-6; genetic association; predictive model
Figures

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Ponasenko, A.V.; Khutornaya, M.V.; Kutikhin, A.G.; Rutkovskaya, N.V.; Tsepokina, A.V.; Kondyukova, N.V.; Yuzhalin, A.E.; Barbarash, L.S. A Genomics-Based Model for Prediction of Severe Bioprosthetic Mitral Valve Calcification. Int. J. Mol. Sci. 2016, 17, 1385.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Int. J. Mol. Sci. EISSN 1422-0067 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top