Ce area, LV end-systolic volume indexed to body surface area and

Ce area, LV end-systolic volume indexed to body surface area and S’ lat. As there is much debate over which ZM 447439 chemical information parameters of diastolic function should be measured as well as their variability in assessment, six diastolic parameters were assessed in a cluster analysis 3 / 10 eNOS Association with LVEF in Early CKD to separate the cohort into two risk categories of diastolic dysfunction; these were then assessed by eNOS genotype. The “diastolic” parameters included: e’ lat, E/e’ lat, mitral valve E/A, LVMI, mitral valve propagation velocity and LAVI. Statistical Analysis Baseline demographics and cardiac investigations were compared across the genotype groups, using Kruskal-Wallis and Fisher’s Exact tests as appropriate. The relationship between these was then MedChemExpress PF-8380 investigated using regression analysis. Initially, univariate linear regression models were produced, with variables being log-transformed where there was evidence of a non-linearity. Multivariate regression models were used in order to adjust for potentially confounding factors. A cluster analysis was then performed, to divide patients into groups based on the values of a range of diastolic parameters. The Two-Step cluster analysis in IBM SPSS 19 was used, with the number of clusters determined automatically. Demographic factors were then compared between the resulting clusters, using t-tests or Fisher’s Exact test, as applicable. All analyses were performed using IBM SPSS 19, with p<0.05 deemed to be indicative of statistical significance. Results Genomic DNA was successfully genotyped in 132 patients. The eNOS SNP rs1799983 patient genotype frequency was GG in 47 , TG in 39 , and TT in 14 . This distribution was within Hardy-Weinberg equilibrium bounds. Patient demographics are presented in 4 / 10 eNOS Association with LVEF in Early CKD A cluster analysis was performed based on diastolic parameters, in order to group patients based on their risk of diastolic function. The most important factor in defining the clusters was found to be e' lat, with mitral valve E/A and E/e' lat being moderate contributors, and the remaining parameters being minimally discriminative. The first cluster had lower levels of e' lat, MV E/A and MV VP and higher levels of E/e' lat and LAVI, hence represented those patients at most risk of diastolic dysfunction. Comparisons between the clusters found that increased age and reduced eGFR were significantly associated with the risk of diastolic dysfunction clusters on univariate analysis. Discussion In this cohort of white patients with non-dialysis dependent CKD, and without heart failure, GG genotype for eNOS SNP rs1799983 was associated with a significant lower LVEF, greater LVESVI and greater LVEDVI than those found in non-GG genotypes. The burden of myocardial disease in CKD suggests the investigation of stratification PubMed ID:http://jpet.aspetjournals.org/content/120/1/33 by genetic risk in this setting to be a worthwhile endeavour, and this study represents the first such attempt with this eNOS polymorphism. 5 / 10 eNOS Association with LVEF in Early CKD 2 GG genotype TG genotype TT genotype All p value 71 61 17 54.0 2.53 5.12 66 76 57 14 54.6 2.15 5.19 64 73 59 16 56.0 2.11 6.38 78 74 59 16 54.1 2.35 5.26 66 0.006 0.344 0.024 0.996 0.692 0.177 0.074 Key: CMR; S’ lat; e’ lat; E/e’ lat doi:10.1371/journal.pone.0116160.t002 Previous data from the general population suggest this gene variant represents an attractive candidate SNP, and support the findings of the current study. For instance Velloso et al studied.Ce area, LV end-systolic volume indexed to body surface area and S’ lat. As there is much debate over which parameters of diastolic function should be measured as well as their variability in assessment, six diastolic parameters were assessed in a cluster analysis 3 / 10 eNOS Association with LVEF in Early CKD to separate the cohort into two risk categories of diastolic dysfunction; these were then assessed by eNOS genotype. The “diastolic” parameters included: e’ lat, E/e’ lat, mitral valve E/A, LVMI, mitral valve propagation velocity and LAVI. Statistical Analysis Baseline demographics and cardiac investigations were compared across the genotype groups, using Kruskal-Wallis and Fisher’s Exact tests as appropriate. The relationship between these was then investigated using regression analysis. Initially, univariate linear regression models were produced, with variables being log-transformed where there was evidence of a non-linearity. Multivariate regression models were used in order to adjust for potentially confounding factors. A cluster analysis was then performed, to divide patients into groups based on the values of a range of diastolic parameters. The Two-Step cluster analysis in IBM SPSS 19 was used, with the number of clusters determined automatically. Demographic factors were then compared between the resulting clusters, using t-tests or Fisher’s Exact test, as applicable. All analyses were performed using IBM SPSS 19, with p<0.05 deemed to be indicative of statistical significance. Results Genomic DNA was successfully genotyped in 132 patients. The eNOS SNP rs1799983 patient genotype frequency was GG in 47 , TG in 39 , and TT in 14 . This distribution was within Hardy-Weinberg equilibrium bounds. Patient demographics are presented in 4 / 10 eNOS Association with LVEF in Early CKD A cluster analysis was performed based on diastolic parameters, in order to group patients based on their risk of diastolic function. The most important factor in defining the clusters was found to be e' lat, with mitral valve E/A and E/e' lat being moderate contributors, and the remaining parameters being minimally discriminative. The first cluster had lower levels of e' lat, MV E/A and MV VP and higher levels of E/e' lat and LAVI, hence represented those patients at most risk of diastolic dysfunction. Comparisons between the clusters found that increased age and reduced eGFR were significantly associated with the risk of diastolic dysfunction clusters on univariate analysis. Discussion In this cohort of white patients with non-dialysis dependent CKD, and without heart failure, GG genotype for eNOS SNP rs1799983 was associated with a significant lower LVEF, greater LVESVI and greater LVEDVI than those found in non-GG genotypes. The burden of myocardial disease in CKD suggests the investigation of stratification PubMed ID:http://jpet.aspetjournals.org/content/120/1/33 by genetic risk in this setting to be a worthwhile endeavour, and this study represents the first such attempt with this eNOS polymorphism. 5 / 10 eNOS Association with LVEF in Early CKD 2 GG genotype TG genotype TT genotype All p value 71 61 17 54.0 2.53 5.12 66 76 57 14 54.6 2.15 5.19 64 73 59 16 56.0 2.11 6.38 78 74 59 16 54.1 2.35 5.26 66 0.006 0.344 0.024 0.996 0.692 0.177 0.074 Key: CMR; S’ lat; e’ lat; E/e’ lat doi:10.1371/journal.pone.0116160.t002 Previous data from the general population suggest this gene variant represents an attractive candidate SNP, and support the findings of the current study. For instance Velloso et al studied.