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Sesto Fiorentino, Italy

Aimetti M.,University of Turin | Cacciatore S.,University of Florence | Graziano A.,University of Turin | Graziano A.,Temple University | Tenori L.,FiorGen Foundation
Metabolomics | Year: 2012

The diagnoses of periodontal diseases (PD) are primarily based on clinical examination and radiographic parameters. In this pilot exploration we want to supply some evidence whether metabonomic profiling of saliva samples can provide a signature of the disease. Saliva samples were analyzed by Nuclear Magnetic Resonance (NMR) metabonomics from 22 healthy subjects (HS) and 32 patients with clinic and radiographic diagnosis of different PD: Gingivitis (G), Localized Chronic Periodontitis (LCP), Generalized Chronic Periodontitis (GCP), Localized Aggressive Periodontitis (LAP), and Generalized Aggressive Periodontitis (GAP). Pattern recognition analysis of NMR profiles can discriminate GCP patients (n = 21) from HS (n = 22) with an accuracy of 84.1%. Metabolic profiles of GCP patients exhibited higher concentrations of acetate, γ-aminobutyrate, n-butyrate, succinate, trimethylamine, propionate, phenylalanine and valine, and decreased concentrations of pyruvate and N-acetyl groups compared with controls. Our results can provide a contribution to the understanding of the biochemical network and pathway in the GCP and other PD, however at this stage the method can not be extended to the general population as a ready-to-use clinical tool, due to the limited cohort recruited and the exploratory nature of this work. Anyway, a further validation of the statistical model on a larger cohort is in progress with the aim to demonstrate the potential impact in clinical practice of our findings. © 2011 Springer Science+Business Media, LLC.

Santucci C.,University of Florence | Brizzolara S.,Piaggio | Tenori L.,FiorGen Foundation
Food Analytical Methods | Year: 2015

Metabolic profiling and metabolomics studies mainly deal with the multicomponent analysis of cell extracts, biological fluids, and tissues using nuclear magnetic resonance (NMR) spectroscopy, often flanked by mass spectrometry (MS). Technical improvements are needed for a better understanding of the mechanisms that regulate biological systems. In this work, we have utilized two different kinds of starting material for juice production—frozen and fresh apple pulp—monitoring metabolic profiles obtained through NMR analysis. The differences induced by these pre-analytical treatments have been statistically evaluated using unsupervised multivariate method (PCA) and through the analysis of the identified metabolites. Evaluating PCA score plot, it was possible to distinguish between the two juice preparations. Compounds as lactic, citramalic, malic, chlorogenic, and formic acid were identified only in juices obtained from fresh apple pulp. Furthermore, in these kind of juices, other metabolites, such as ethanol, were found at a higher level. Whereas, other compounds, such as threonine, showed higher values in juices deriving from frozen apple pulp. This study highlights the feasibility of 1H-NMR-based metabolomics as a tool for the analysis of apple juices. Our results suggest the use of juices obtained from fresh fruit tissue for the investigation of compositional changes due to physiological disorder, specific growth, or storage conditions. Our analyses emphasize the importance of technical improvement in metabolomics analysis. © 2015, Springer Science+Business Media New York.

Wallner-Liebmann S.,Medical University of Graz | Gralka E.,University of Florence | Tenori L.,FiorGen Foundation | Konrad M.,FH Joanneum University of Applied Sciences | And 5 more authors.
Genes and Nutrition | Year: 2015

Urine contains a clear individual metabolic signature, although embedded within a large daily variability. Given the potential of metabolomics to monitor disease onset from deviations from the “healthy” metabolic state, we have evaluated the effectiveness of a standardized lifestyle in reducing the “metabolic” noise. Urine was collected from 24 (5 men and 19 women) healthy volunteers over a period of 10 days: phase I, days 1–7 in a real-life situation; phase II, days 8–10 in a standardized diet and day 10 plus exercise program. Data on dietary intake and physical activity have been analyzed by a nation-specific software and monitored by published protocols. Urine samples have been analyzed by 1H NMR followed by multivariate statistics. The individual fingerprint emerged and consolidated with increasing the number of samples and reaches ~100 % cross-validated accuracy for about 40 samples. Diet standardization reduced both the intra-individual and the interindividual variability; the effect was due to a reduction in the dispersion of the concentration values of several metabolites. Under standardized diet, however, the individual phenotype was still clearly visible, indicating that the individual’s signature was a strong feature of the metabolome. Consequently, cohort studies designed to investigate the relation of individual metabolic traits and nutrition require multiple samples from each participant even under highly standardized lifestyle conditions in order to exploit the analytical potential of metabolomics. We have established criteria to facilitate design of urine metabolomic studies aimed at monitoring the effects of drugs, lifestyle, dietary supplements, and for accurate determination of signatures of diseases. © 2014, Springer-Verlag Berlin Heidelberg.

Bernini P.,University of Florence | Bertini I.,University of Florence | Luchinat C.,University of Florence | Tenori L.,FiorGen Foundation | Tognaccini A.,Immunohaematology and Transfusion Service
Journal of Proteome Research | Year: 2011

The identification and the present wide acceptance of cardiovascular risk factors such as age, sex, hypertension, hyperlipidemia, smoking, obesity, diabetes, and physical inactivity have led to dramatic reductions in cardiovascular morbidity and mortality. However, novel risk predictors present opportunities to identify more patients at risk and to more accurately define the biochemical signature of that risk. In this paper, we present a comprehensive metabonomic analysis of 864 plasma samples from healthy volunteers, through Nuclear Magnetic Resonance (NMR) and multivariate statistical analysis (regression and classification). We have found that subjects that are classified as at high or at low risk using the common clinical markers can also be discriminated using NMR metabonomics. This discrimination is not only due to common markers (such as total cholesterol, triglycerides, LDL, HDL), but also to (p < 0.05 after Bonferroni correction) other metabolites (e.g., 3-hydroxybutyrate, α-ketoglutarate, threonine, dimethylglycine) previously not associated with cardiovascular diseases. © 2011 American Chemical Society.

Cacciatore S.,Dana-Farber Cancer Institute | Cacciatore S.,Rovira i Virgili University | Tenori L.,FiorGen Foundation
Medical Hypotheses | Year: 2013

Wilson disease (WD) is an autosomal recessive inherited disorder of copper (Cu) metabolism, resulting in pathological accumulation of Cu in many organs and tissues, predominantly in the liver and brain. There clearly is a close and complex relationship between Cu and the cholesterol's metabolic pathway; therefore any theory about the cholesterol metabolism in the brain of patients with WD must take it into account. The hypothesis presented in this paper is that the imbalance in cerebral copper homeostasis caused by WD may plays a key role in the derangement of the cholesterol homeostasis in the brain, and thus promoting the observed WD related neurological disorders. © 2013.

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