Tommaso Gabbani1, Maria Marsico2, Patrizia Bernini3, Elisabetta Lorefice4, Cecilia Grappone5, Maria Rosa Biagini5, Stefano Milani5, Vito Annese6. 1. Gastroenterology Unit, Morgagni-Pierantoni Hospital, AUSL Romagna, Forlì, Italy. Electronic address: tom.gabbani@gmail.com. 2. Gastroenterology Unit, Modena University Hospital, Modena, Italy. 3. CERM, Chemistry Department, Florence University, Sesto Fiorentino, Italy. 4. Gastroenterology UO, Azienda USL 11, Empoli, Italy. 5. Gastroenterology SOD, AOU Careggi University Hospital, Florence, Italy. 6. Gastroenterology Department, Valiant Clinic, Dubai, UAE.
Abstract
BACKGROUND: The assessment of fibrosis degree in liver diseases is based on several non-invasive techniques, but none has been accurate. AIM: This study employed proton nuclear magnetic resonance spectroscopy to identify metabolic profiles in serum and urine, specific for different fibrosis degree in chronic hepatitis C patients. METHOD: 71 plasma, 73 serum, and 578 urine samples were collected. All samples were analyzed using 1H-NMR spectroscopy technique and three different NMR spectra were acquired for each serum/plasma sample. The data analyses were performed by partial least square regression, principal component analysis, and Monte Carlo cross-validation in a supervised methodology. RESULTS: The cross-validation test correctly assigned each sample to its specific donor with 98.44% accuracy for urine samples and 65% for serum/plasma samples. Advanced fibrosis and cirrhosis were recognized with 71% sensitivity for CPMG plasma spectra and 69% specificity for NOESY serum spectra. Accuracy for NOESY serum spectra was 68%. Noesy spectra recognized advanced fibrosis and cirrhosis with 71% sensitivity, 30% specificity, and 50% accuracy in urine samples. CONCLUSION: Metabolomic analysis of urine spectra using 1H-NMR spectroscopy can recognize a specific individual profile in all patients with chronic hepatitis C. However, this method cannot yet differentiate with sufficient accuracy, patients with advanced fibrosis from patients with milder disease.
BACKGROUND: The assessment of fibrosis degree in liver diseases is based on several non-invasive techniques, but none has been accurate. AIM: This study employed proton nuclear magnetic resonance spectroscopy to identify metabolic profiles in serum and urine, specific for different fibrosis degree in chronic hepatitis Cpatients. METHOD: 71 plasma, 73 serum, and 578 urine samples were collected. All samples were analyzed using 1H-NMR spectroscopy technique and three different NMR spectra were acquired for each serum/plasma sample. The data analyses were performed by partial least square regression, principal component analysis, and Monte Carlo cross-validation in a supervised methodology. RESULTS: The cross-validation test correctly assigned each sample to its specific donor with 98.44% accuracy for urine samples and 65% for serum/plasma samples. Advanced fibrosis and cirrhosis were recognized with 71% sensitivity for CPMG plasma spectra and 69% specificity for NOESY serum spectra. Accuracy for NOESY serum spectra was 68%. Noesy spectra recognized advanced fibrosis and cirrhosis with 71% sensitivity, 30% specificity, and 50% accuracy in urine samples. CONCLUSION: Metabolomic analysis of urine spectra using 1H-NMR spectroscopy can recognize a specific individual profile in all patients with chronic hepatitis C. However, this method cannot yet differentiate with sufficient accuracy, patients with advanced fibrosis from patients with milder disease.