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Essential hypertension: A filtered serum based metabolomics study.

ABSTRACT: Despite the easy and reliable methods of blood pressure measurement, the screening of essential hypertension (EH) is usually ignored due to delayed onset of symptoms. A probe into the biochemical changes in hypertension would serve as a welcome asset to provide insight into the mechanistic aspects of EH. Filtered serum samples from 64 EH patients and 59 healthy controls (HC) were analysed using 800?MHz nuclear magnetic resonance (NMR) spectroscopy. Application of principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) following receiver operating characteristic (ROC) curve of NMR data reveals significantly perturbed metabolites: alanine, arginine, methionine, pyruvate, adenine, and uracil. This set of metabolites correctly classified 99% of cases from HC and also showed excellent correlation in both isolated elevated diastolic blood pressure (DBP) cases and combined elevated systolic-diastolic blood pressure cases. Proton NMR metabolomics of EH may prove helpful in defining associated biomarkers and serve as an alternate diagnostic tool with judicious clinical assessment.

SUBMITTER: Ameta K

PROVIDER: S-EPMC5438387 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Essential hypertension: A filtered serum based metabolomics study.

Ameta Keerti K Gupta Ashish A Kumar Sudeep S Sethi Rishi R Kumar Deepak D Mahdi Abbas Ali AA

Scientific reports 20170519 1

Despite the easy and reliable methods of blood pressure measurement, the screening of essential hypertension (EH) is usually ignored due to delayed onset of symptoms. A probe into the biochemical changes in hypertension would serve as a welcome asset to provide insight into the mechanistic aspects of EH. Filtered serum samples from 64 EH patients and 59 healthy controls (HC) were analysed using 800 MHz nuclear magnetic resonance (NMR) spectroscopy. Application of principal component analysis (PC ...[more]

PMID: 28526818

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Project description:Background: Cigarette smoking is an important environmental risk factor for cardiovascular events of hypertension (HTN). Existing studies have provided evidence supporting altered gut microbiota by cigarette smoking, especially in hypertensive patients. Metabolic biomarkers play a central role in the functional potentials of the gut microbiome but are poorly characterized in hypertensive smokers. To explore whether serum metabolomics signatures and compositions of HTN patients were varied in smokers, and investigate their connecting relationship to gut microbiota, the serum metabolites were examined in untreated hypertensive patients using untargeted liquid chromatography-mass spectrometry (LC/MS) analysis. Results: A dramatic difference and clear separation in community features of circulating metabolomics members were seen in smoking HTN patients compared with the non-smoking controls, according to partial least squares discrimination analysis (PLS-DA) and orthogonal partial least squares discrimination analysis (OPLS-DA). Serum metabolic profiles and compositions of smoking patients with HTN were significantly distinct from the controls, and were characterized by enrichment of 12-HETE, 7-Ketodeoxycholic acid, Serotonin, N-Stearoyl tyrosine and Deoxycholic acid glycine conjugate, and the depletion of Tetradecanedioic acid, Hippuric acid, Glyceric acid, 20-Hydroxyeicosatetraenoic acid, Phenylpyruvic acid and Capric acid. Additionally, the metabolome displayed prominent functional signatures, with a majority proportion of the metabolites identified to be discriminating between groups distributed in Starch and sucrose metabolism, Caffeine metabolism, Pyruvate metabolism, Glycine, serine and threonine metabolism, and Phenylalanine metabolic pathways. Furthermore, the observation of alterations in metabolites associated with intestinal microbial taxonomy indicated that these metabolic members might mediate the effects of gut microbiome on the smoking host. Indeed, the metabolites specific to smoking HTNs were strongly organized into co-abundance networks, interacting with an array of clinical parameters, including uric acid (UA), low-denstiy lipoprotein cholesterol (LDLC) and smoking index. Conclusions: In conclusion, we demonstrated disparate circulating blood metabolome composition and functional potentials in hypertensive smokers, showing a linkage between specific metabolites in blood and the gut microbiome.

Project description:BackgroundEssential hypertension (EH) is a key risk factor for cardiovascular disease. However, the etiology of EH is complex and unknown. So far, there is no good protein biomarker for screening EH. The purpose of this study was to discover potential biomarkers for EH by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and establish a decision-tree classification model.MethodsA total of 108 patients with clinically confirmed EH and 105 HC were enrolled in the present study from September 2020 to April 2021 and were randomly divided into the training group and the blind-test group. The serum protein expression profiles were performed using MALDI-TOF MS combined with magnetic beads with weak cation exchange (MB-WCX). The training group, which comprised 54 EH patients and 53 HC, was used to screen the statistically differential protein peaks by SPSS 19.0 and construct a decision-tree classification model by C5.0 algorithms of SPSS Modeler 18.0. All protein peak intensities of samples in the blind-test group, which comprised 54 EH patients and 52 HC, were used to verify the diagnostic capabilities of the model by classification model.ResultsEH patients had higher age, systolic and diastolic blood pressures than HC group. The intensities of 60 protein peaks differed significantly between the EH patients and HC. An optimal decision-tree classification model of EH was successfully established with mass-to-charge ratios of 1,326.7, 1,785.3, 4,228.0, and 8,963.8 as differential protein peaks by the software analysis. The decision-tree classification model was able to distinguish between EH patients and HC and had a sensitivity of 94.44%, a specificity of 94.33%, an accuracy of 94.39%, and an area under the receiver operating characteristic (ROC) curve of 0.96. The blind-test results indicated a sensitivity of 87.04%, a specificity of 88.46%, an accuracy of 87.74%, and an area under the ROC curve of 0.928.ConclusionsMALDI-TOF MS combined with MB-WCX can be used to screen for serum differential protein expression profiles in EH patients. The decision-tree classification model based on mass-to-charge ratios of 1,326.7, 1,785.3, 4,228.0, and 8,963.8 could provide a new and reliable method for screening and identifying EH with high sensitivity and specificity.

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Essential hypertension: A filtered serum based metabolomics study.

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Essential hypertension: A filtered serum based metabolomics study.

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