NMR-based metabolomic approach to study urine samples of chronic inflammatory rheumatic disease patients

Vignoli, Alessia; Rodio, Donatella Maria; Bellizzi, Anna; Sobolev, Anatoly P.; Anzivino, Elena; Mischitelli, Monica; Tenori, Leonardo; Marini, Federico; Priori, Roberta; Scrivo, Rossana; Valesini, Guido; Francia, Ada; Morreale, Manuela; Ciardi, Maria; Iannetta, Marco; Campanella, Cristiana; Capitani, Donatella; Luchinat, Claudio; Pietropaolo, Valeria; Mannina, Luisa

doi:10.1007/s00216-016-0074-z

Cited by 28 publications

(20 citation statements)

References 30 publications

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“…1 H-NMR spectroscopy was used to compare the 1 H spectra of patients’ urines after meals with and without blueberry addition. The 1 H-NMR spectra were analyzed according to the methods described in recent literature [24,25]. In particular, spectra were divided in 75 bins which were integrated and normalized (see Material and Methods section).…”

Section: Resultsmentioning

confidence: 99%

Blueberry-Based Meals for Obese Patients with Metabolic Syndrome: A Multidisciplinary Metabolomic Pilot Study

et al. 2019

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A pilot study was carried out on five obese/overweight patients suffering from metabolic syndrome, with the aim to evaluate postprandial effects of high fat/high glycemic load meals enriched by blueberries. Postprandial urine samples were analyzed by 1H-NMR spectroscopy after 2 and 4 h from ingestion to identify potential markers of blueberry intake. Significant decrease of methylamines, acetoacetate, acetone and succinate, known indicators of type 2 diabetes mellitus, were observed after the intake of meals enriched with blueberries. On the other hand, an accumulation of p-hydroxyphenyl-acetic acid and 3-(3’-hydroxyphenyl)-3-hydropropionic acid originating from gut microbial dehydrogenation of proanthocyanidins and procyanidins was detected. Real-time PCR-analysis of mRNAs obtained from mononuclear blood cells showed significant changes in cytokine gene expression levels after meals integrated with blueberries. In particular, the mRNAs expression of interleukin-6 (IL-6) and Transforming Growth Factor-β (TGF-β), pro and anti-inflammation cytokines, respectively, significantly decreased and increased after blueberry supplementation, indicating a positive impact of blueberry ingestion in the reduction of risk of inflammation. The combined analysis of the urine metabolome and clinical markers represents a promising approach in monitoring the metabolic impact of blueberries in persons with metabolic syndrome.

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Section: Resultsmentioning

confidence: 99%

Blueberry-Based Meals for Obese Patients with Metabolic Syndrome: A Multidisciplinary Metabolomic Pilot Study

et al. 2019

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“…A metabolic fingerprint can be deemed as a holistic super-biomarker with a discriminative and predictive power undoubtedly higher than that of the sum of the few quantified metabolites [47]. AMI, as with the majority of human diseases, has a multifactorial etiology and a complex physiopathology that concurrently alters several metabolic pathways [48].…”

Section: Discussionmentioning

confidence: 99%

NMR-based metabolomics identifies patients at high risk of death within two years after acute myocardial infarction in the AMI-Florence II cohort

Vignoli

Tenori

Giusti

et al. 2019

BMC Med

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BackgroundRisk stratification and management of acute myocardial infarction patients continue to be challenging despite considerable efforts made in the last decades by many clinicians and researchers. The aim of this study was to investigate the metabolomic fingerprint of acute myocardial infarction using nuclear magnetic resonance spectroscopy on patient serum samples and to evaluate the possible role of metabolomics in the prognostic stratification of acute myocardial infarction patients.MethodsIn total, 978 acute myocardial infarction patients were enrolled in this study; of these, 146 died and 832 survived during 2 years of follow-up after the acute myocardial infarction. Serum samples were analyzed via high-resolution 1H-nuclear magnetic resonance spectroscopy and the spectra were used to characterize the metabolic fingerprint of patients. Multivariate statistics were used to create a prognostic model for the prediction of death within 2 years after the cardiovascular event.ResultsIn the training set, metabolomics showed significant differential clustering of the two outcomes cohorts. A prognostic risk model predicted death with 76.9% sensitivity, 79.5% specificity, and 78.2% accuracy, and an area under the receiver operating characteristics curve of 0.859. These results were reproduced in the validation set, obtaining 72.6% sensitivity, 72.6% specificity, and 72.6% accuracy. Cox models were used to compare the known prognostic factors (for example, Global Registry of Acute Coronary Events score, age, sex, Killip class) with the metabolomic random forest risk score. In the univariate analysis, many prognostic factors were statistically associated with the outcomes; among them, the random forest score calculated from the nuclear magnetic resonance data showed a statistically relevant hazard ratio of 6.45 (p = 2.16×10−16). Moreover, in the multivariate regression only age, dyslipidemia, previous cerebrovascular disease, Killip class, and random forest score remained statistically significant, demonstrating their independence from the other variables.ConclusionsFor the first time, metabolomic profiling technologies were used to discriminate between patients with different outcomes after an acute myocardial infarction. These technologies seem to be a valid and accurate addition to standard stratification based on clinical and biohumoral parameters.Electronic supplementary materialThe online version of this article (10.1186/s12916-018-1240-2) contains supplementary material, which is available to authorized users.

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“…NMR metabolomics, one of the most preferred methods, can detect a wide variety of compound families and can thus be particularly suitable for untargeted analysis [6]. In the past few years, an NMR-based metabonomics approach has been proved to be successfully applied for biological samples, such as plasma, serum, urine, brain tissue, and cerebrospinal fluid [7,8,9,10,11].…”

Section: Introductionmentioning

confidence: 99%

A NMR-Based Metabonomics Approach to Determine Protective Effect of a Combination of Multiple Components Derived from Naodesheng on Ischemic Stroke Rats

Luo

Kang

et al. 2019

Molecules

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Naodesheng (NDS) is a widely used traditional Chinese medicine (TCM) prescription for the treatment of ischemic stroke. A combination of 10 components is derived from NDS. They are: Notoginsenoside R1, ginsenoside Rg1, ginsenoside b1, ginsenoside Rd, hydroxysafflor yellow A, senkyunolide I, puerarin, daidzein, vitexin, and ferulic acid. This study aimed to investigate the protective effect of the ten-component combination derived from NDS (TCNDS) on ischemic stroke rats with a middle cerebral artery occlusion (MCAO) model by integrating an NMR-based metabonomics approach with biochemical assessment. Our results showed that TCNDS could improve neurobehavioral function, decrease the cerebral infarct area, and ameliorate pathological features in MCAO model rats. In addition, TCNDS was found to decrease plasma lactate dehydrogenase (LDH) and malondialdehyde (MDA) production and increase plasma superoxide dismutase (SOD) production. Furthermore, 1H-NMR metabonomic analysis indicated that TCNDS could regulate the disturbed metabolites in the plasma, urine, and brain tissue of MCAO rats, and the possible mechanisms were involved oxidative stress, energy metabolism, lipid metabolism, amino acid metabolism, and inflammation. Correlation analysis were then performed to further confirm the metabolites involved in oxidative stress. Correlation analysis showed that six plasma metabolites had high correlations with plasma LDH, MDA, and SOD. This study provides evidence that an NMR-based metabonomics approach integrated with biochemical assessment can help to better understand the underlying mechanisms as well as the holistic effect of multiple compounds from TCM.

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NMR-based metabolomic approach to study urine samples of chronic inflammatory rheumatic disease patients

Cited by 28 publications

References 30 publications

Blueberry-Based Meals for Obese Patients with Metabolic Syndrome: A Multidisciplinary Metabolomic Pilot Study

Blueberry-Based Meals for Obese Patients with Metabolic Syndrome: A Multidisciplinary Metabolomic Pilot Study

NMR-based metabolomics identifies patients at high risk of death within two years after acute myocardial infarction in the AMI-Florence II cohort

A NMR-Based Metabonomics Approach to Determine Protective Effect of a Combination of Multiple Components Derived from Naodesheng on Ischemic Stroke Rats

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