Increased mean aliphatic lipid chain length in left ventricular hypertrophy secondary to arterial hypertension: A cross-sectional study

About 77.9 million (1 in 4) American adults have high blood pressure. High blood pressure is the primary cause of left ventricular hypertrophy (LVH), which represents a strong predictor of future heart failure and cardiovascular mortality. Previous studies have shown an altered metabolic profile in hypertensive patients with LVH. The goal of this study was to identify blood metabolomic LVH biomarkers by H NMR to provide novel diagnostic tools for rapid LVH detection in populations of hypertensive individuals. This cross-sectional study included 48 hypertensive patients with LVH matched with 48 hypertensive patients with normal LV size, and 24 healthy controls. Two-dimensional targeted M-mode echocardiography was performed to measure left ventricular mass index. Partial least squares discriminant analysis was used for the multivariate analysis of the H NMR spectral data. From the H NMR-based metabolomic profiling, signals coming from methylene (-CH2-) and methyl (-CH3) moieties of aliphatic chains from plasma lipids were identified as discriminant variables. The -CH2-/-CH3 ratio, an indicator of the mean length of the aliphatic lipid chains, was significantly higher (P < 0.001) in the LVH group than in the hypertensive group without LVH and controls. Receiver operating characteristic curve showed that a cutoff of 2.34 provided a 52.08% sensitivity and 85.42% specificity for discriminating LVH (AUC = 0.703, P-value < 0.001). We propose the -CH2-/-CH3 ratio from plasma aliphatic lipid chains as a biomarker for the diagnosis of left ventricular remodeling in hypertension

Blood Signature of Pre-Heart Failure: A Microarrays Study

International audienceBACKGROUND: The preclinical stage of systolic heart failure (HF), known as asymptomatic left ventricular dysfunction (ALVD), is diagnosed only by echocardiography, frequent in the general population and leads to a high risk of developing severe HF. Large scale screening for ALVD is a difficult task and represents a major unmet clinical challenge that requires the determination of ALVD biomarkers. METHODOLOGY/PRINCIPAL FINDINGS: 294 individuals were screened by echocardiography. We identified 9 ALVD cases out of 128 subjects with cardiovascular risk factors. White blood cell gene expression profiling was performed using pangenomic microarrays. Data were analyzed using principal component analysis (PCA) and Significant Analysis of Microarrays (SAM). To build an ALVD classifier model, we used the nearest centroid classification method (NCCM) with the ClaNC software package. Classification performance was determined using the leave-one-out cross-validation method. Blood transcriptome analysis provided a specific molecular signature for ALVD which defined a model based on 7 genes capable of discriminating ALVD cases. Analysis of an ALVD patients validation group demonstrated that these genes are accurate diagnostic predictors for ALVD with 87% accuracy and 100% precision. Furthermore, Receiver Operating Characteristic curves of expression levels confirmed that 6 out of 7 genes discriminate for left ventricular dysfunction classification. CONCLUSIONS/SIGNIFICANCE: These targets could serve to enhance the ability to efficiently detect ALVD by general care practitioners to facilitate preemptive initiation of medical treatment preventing the development of HF