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Serum and urine 1H NMR-based metabolomics in the diagnosis of selected thyroid diseases.

ABSTRACT: Early detection of nodular thyroid diseases including thyroid cancer is still primarily based on invasive procedures such as fine-needle aspiration biopsy. Therefore, there is a strong need for development of new diagnostic methods that could provide clinically useful information regarding thyroid nodular lesions in a non-invasive way. In this study we investigated 1H NMR based metabolic profiles of paired urine and blood serum samples, that were obtained from healthy individuals and patients with nodular thyroid diseases. Estimation of predictive potential of metabolites was evaluated using chemometric methods and revealed that both urine and serum carry information sufficient to distinguish between patients with nodular lesions and healthy individuals. Data fusion allowed to further improve prediction quality of the models. However, stratification of tumor types and their differentiation in relation to each other was not possible.

SUBMITTER: Wojtowicz W

PROVIDER: S-EPMC5567318 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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Serum and urine <sup>1</sup>H NMR-based metabolomics in the diagnosis of selected thyroid diseases.

Wojtowicz Wojciech W Zabek Adam A Deja Stanislaw S Dawiskiba Tomasz T Pawelka Dorota D Glod Mateusz M Balcerzak Waldemar W Mlynarz Piotr P

Scientific reports 20170822 1

Early detection of nodular thyroid diseases including thyroid cancer is still primarily based on invasive procedures such as fine-needle aspiration biopsy. Therefore, there is a strong need for development of new diagnostic methods that could provide clinically useful information regarding thyroid nodular lesions in a non-invasive way. In this study we investigated <sup>1</sup>H NMR based metabolic profiles of paired urine and blood serum samples, that were obtained from healthy individuals and ...[more]

PMID: 28831094

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Project description:Objective: Millions of sport-related concussions (SRC) occur annually in North America, and current diagnosis of concussion is based largely on clinical evaluations. The objective of this study was to determine whether urinary metabolites are significantly altered post-SRC compared to pre-injury. Setting: Outpatient sports medicine clinic. Participants: Twenty-six male youth sport participants. Methods: Urine was analyzed pre-injury and after SRC by 1H NMR spectroscopy. Data were analyzed using multivariate statistics, pairwise t-test, and metabolic pathway analysis. Variable importance analysis based on random variable combination (VIAVC) was applied to the entire data set and resulted in a panel of 18 features. Partial least square discriminant analysis was performed exploring the separation between pre-injury and post-SRC groups. Pathway topography analysis was completed to identify biological pathway involvement. Spearman correlations provide support for the relationships between symptom burden and length of return to play and quantifiable metabolic changes in the human urinary metabolome. Results: Phenylalanine and 3-indoxysulfate were upregulated, while citrate, propylene glycol, 1-methylhistidine, 3-methylhistidine, anserine, and carnosine were downregulated following SRC. A receiver operator curve (ROC) tool constructed using the 18-feature classifier had an area under the curve (AUC) of 0.887. A pairwise t-test found an additional 19 altered features, 7 of which overlapped with the VIAVC analysis. Pathway topology analysis indicated that aminoacyl-tRNA biosynthesis and beta-alanine metabolism were the two pathways most significantly changed. There was a significant positive correlation between post-SRC 2-hydroxybutyrate and the length of return to play (ρ = 0.482, p = 0.02) as well as the number of symptoms and post-SRC lactose (ρ = 0.422, p = 0.036). Conclusion: We found that 1H NMR metabolomic urinary analysis can identify a set of metabolites that can correctly classify SRC with an accuracy of 81.6%, suggesting potential for a more objective method of characterizing SRC. Correlations to both the number of symptoms and length of return to play indicated that 2-hydroxybutyrate and lactose may have potential applications as biomarkers for sport-related concussion.

Project description:IntroductionErythromycin (ERY) is known to induce hepatic toxicity which mimics other liver diseases. Thus, ERY is often used to produce experimental models of drug-induced liver-toxicity. The serum metabolic profiles can be used to evaluate the liver-toxicity and to further improve the understanding of underlying mechanism.ObjectiveTo establish the serum metabolic patterns of Erythromycin induced hepatotoxicity in albino wistar rats using 1H NMR based serum metabolomics.ExperimentalFourteen male rats were randomly divided into two groups (n = 7 in each group): control and ERY treated. After 28 days of intervention, the metabolic profiles of sera obtained from ERY and control groups were analyzed using high-resolution 1D 1H CPMG and diffusion-edited nuclear magnetic resonance (NMR) spectra. The histopathological and SEM examinations were employed to evaluate the liver toxicity in ERY treated group.ResultsThe serum metabolic profiles of control and ERY treated rats were compared using multivariate statistical analysis and the metabolic patterns specific to ERY-induced liver toxicity were established. The toxic response of ERY was characterized with: (a) increased serum levels of Glucose, glutamine, dimethylamine, malonate, choline, phosphocholine and phospholipids and (b) decreased levels of isoleucine, leucine, valine, alanine, glutamate, citrate, glycerol, lactate, threonine, circulating lipoproteins, N-acetyl glycoproteins, and poly-unsaturated lipids. These metabolic alterations were found to be associated with (a) decreased TCA cycle activity and enhanced fatty acid oxidation, (b) dysfunction of lipid and amino acid metabolism and (c) oxidative stress.Conclusion and recommendationsErythromycin is often used to produce experimental models of liver toxicity; therefore, the established NMR-based metabolic patterns will form the basis for future studies aiming to evaluate the efficacy of anti-hepatotoxic agents or the hepatotoxicity of new drug-formulations.

Project description:Precision medicine may significantly contribute to rapid disease diagnosis and targeted therapy, but relies on the availability of detailed, subject specific, clinical information. Proton nuclear magnetic resonance (¹H⁻NMR) spectroscopy of body fluids can extract individual metabolic fingerprints. Herein, we studied 64 patients admitted to the Florence main hospital emergency room with severe abdominal pain. A blood sample was drawn from each patient at admission, and the corresponding sera underwent ¹H⁻NMR metabolomics fingerprinting. Unsupervised Principal Component Analysis (PCA) analysis showed a significant discrimination between a group of patients with symptoms of upper abdominal pain and a second group consisting of patients with diffuse abdominal/intestinal pain. Prompted by this observation, supervised statistical analysis (Orthogonal Partial Least Squares⁻Discriminant Analysis (OPLS-DA)) showed a very good discrimination (>90%) between the two groups of symptoms. This is a surprising finding, given that neither of the two symptoms points directly to a specific disease among those studied here. Actually herein, upper abdominal pain may result from either symptomatic gallstones, cholecystitis, or pancreatitis, while diffuse abdominal/intestinal pain may result from either intestinal ischemia, strangulated obstruction, or mechanical obstruction. Although limited by the small number of samples from each of these six conditions, discrimination of these diseases was attempted. In the first symptom group, >70% discrimination accuracy was obtained among symptomatic gallstones, pancreatitis, and cholecystitis, while for the second symptom group >85% classification accuracy was obtained for intestinal ischemia, strangulated obstruction, and mechanical obstruction. No single metabolite stands up as a possible biomarker for any of these diseases, while the contribution of the whole ¹H⁻NMR serum fingerprint seems to be a promising candidate, to be confirmed on larger cohorts, as a first-line discriminator for these diseases.

Dataset Information

Serum and urine 1H NMR-based metabolomics in the diagnosis of selected thyroid diseases.

Publications

Serum and urine <sup>1</sup>H NMR-based metabolomics in the diagnosis of selected thyroid diseases.

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