Ponasenko Anastasia V, Khutornaya Maria V, Kutikhin Anton G, Rutkovskaya Natalia V, Tsepokina Anna V, Kondyukova Natalia V, Yuzhalin Arseniy E, Barbarash Leonid S
Research Institute for Complex Issues of Cardiovascular Diseases, Sosnovy Boulvevard 6, Kemerovo 650002, Russia.
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.
Int J Mol Sci. 2016 Aug 31;17(9):1385. doi: 10.3390/ijms17091385.
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.
严重生物瓣二尖瓣钙化是心血管外科中的一个重大问题。不幸的是，临床标志物在预测严重生物瓣二尖瓣钙化方面未显示出有效性。在此，我们研究了基于基因组学的方法在预测严重生物瓣二尖瓣钙化风险方面是否有效。共招募了124例连续接受二尖瓣置换手术的俄罗斯患者。我们研究了先天免疫、脂质代谢和钙代谢基因的遗传变异与严重生物瓣二尖瓣钙化之间的关联。使用TaqMan分析法进行基因分型。八个基因多态性与严重生物瓣二尖瓣钙化显著相关，因此被纳入逐步逻辑回归分析，该分析确定男性性别、TLR6基因内rs3775073多态性的T/T基因型、IL6R基因内rs2229238多态性的C/T基因型以及LPA基因内rs10455872多态性的A/A基因型为严重生物瓣二尖瓣钙化的独立预测因素。所建立的基于基因组学的模型具有较好的预测价值，受试者操作特征（ROC）曲线下面积为0.73。总之，我们基于基因组学的方法在预测严重生物瓣二尖瓣钙化方面是有效的。
