The nuclear magnetic resonance (NMR)-based metabolomic approach was used as analytical methodology to study the urine samples of chronic inflammatory rheumatic disease (CIRD) patients. The urine samples of CIRD patients were compared to the ones of both healthy subjects and pa- tients with multiple sclerosis (MS), another immuno-mediated disease. Urine samples collected from 39 CIRD patients, 25 healthy subjects, and 26 MS patients were analyzed using 1 H NMR spectroscopy, and the NMR spectra were examined using partial least squares-discriminant analysis (PLS-DA). PLS-DA models were validated by a double cross-validation procedure and randomization tests. Clear discriminations be- tween CIRD patients and healthy controls (average diagnostic accuracy 83.5 ± 1.9%) as well as between CIRD patients and MS patients (diagnostic accuracy 81.1 ± 1.9%) were obtained. Leucine, alanine, 3-hydroxyisobutyric acid, hippuric acid, citric acid, 3-hydroxyisovaleric acid, and creatinine contribut- ed to the discrimination; all of them being in a lower concen- tration in CIRD patients as compared to controls or to MS patients. The application of NMR metabolomics to study these still poorly understood diseases can be useful to better clarify the pathologic mechanisms; moreover, as a holistic approach, it allowed the detection of, by means of anomalous metabolic traits, the presence of other pathologies or pharmaceutical treatments not directly connected to CIRDs, giving comprehensive information on the general health state of individuals.
NMR-based metabolomics approach to study urines of chronic inflammatory rheumatic diseases patients / Vignoli, Alessia; Rodio, DONATELLA MARIA; Bellizzi, Anna; Sobolev, Anatoly Petrovich; Anzivino, Elena; Mischitelli, Monica; Tenori, Leonardo; Marini, Federico; Priori, Roberta; Scrivo, Rossana; Valesini, Guido; Francia, Ada; Morreale, Manuela; Ciardi, Maria Rosa; Iannetta, Marco; Campanella, Cristiana; Capitani, Donatella; Luchinat, Claudio; Pietropaolo, Valeria Antonietta; Mannina, Luisa. - In: ANALYTICAL AND BIOANALYTICAL CHEMISTRY. - ISSN 1618-2650. - ELETTRONICO. - 409(2017), pp. 1405-1413. [10.1007/s00216-016-0074-z]
NMR-based metabolomics approach to study urines of chronic inflammatory rheumatic diseases patients.
RODIO, DONATELLA MARIA;BELLIZZI, ANNA;ANZIVINO, ELENA;MISCHITELLI, MONICA;MARINI, Federico;PRIORI, ROBERTA;SCRIVO, Rossana;VALESINI, Guido;FRANCIA, Ada;MORREALE, MANUELA;CIARDI, Maria Rosa;IANNETTA, MARCO;CAPITANI, DONATELLA;PIETROPAOLO, Valeria Antonietta;MANNINA, LUISA
2017
Abstract
The nuclear magnetic resonance (NMR)-based metabolomic approach was used as analytical methodology to study the urine samples of chronic inflammatory rheumatic disease (CIRD) patients. The urine samples of CIRD patients were compared to the ones of both healthy subjects and pa- tients with multiple sclerosis (MS), another immuno-mediated disease. Urine samples collected from 39 CIRD patients, 25 healthy subjects, and 26 MS patients were analyzed using 1 H NMR spectroscopy, and the NMR spectra were examined using partial least squares-discriminant analysis (PLS-DA). PLS-DA models were validated by a double cross-validation procedure and randomization tests. Clear discriminations be- tween CIRD patients and healthy controls (average diagnostic accuracy 83.5 ± 1.9%) as well as between CIRD patients and MS patients (diagnostic accuracy 81.1 ± 1.9%) were obtained. Leucine, alanine, 3-hydroxyisobutyric acid, hippuric acid, citric acid, 3-hydroxyisovaleric acid, and creatinine contribut- ed to the discrimination; all of them being in a lower concen- tration in CIRD patients as compared to controls or to MS patients. The application of NMR metabolomics to study these still poorly understood diseases can be useful to better clarify the pathologic mechanisms; moreover, as a holistic approach, it allowed the detection of, by means of anomalous metabolic traits, the presence of other pathologies or pharmaceutical treatments not directly connected to CIRDs, giving comprehensive information on the general health state of individuals.File | Dimensione | Formato | |
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