BackgroundDiagnosis of liver involvement due to schistosomiasis in asymptomatic patients from endemic areas previously diagnosed with chronic hepatitis B (HBV) or C (HCV) and periportal fibrosis is challenging. H-1 Nuclear Magnetic Resonance (NMR)-based metabonomics strategy is a powerful tool for providing a profile of endogenous metabolites of low molecular weight in biofluids in a non-invasive way. The aim of this study was to diagnose periportal fibrosis due to schistosomiasis mansoni in patients with chronic HBV or HCV infection through NMR-based metabonomics models.Methodology/Principal findingsThe study included 40 patients divided into two groups: (i) 18 coinfected patients with schistosomiasis mansoni and HBV or HCV; and (ii) 22 HBV or HCV monoinfected patients. The serum samples were analyzed through H-1 NMR spectroscopy and the models were based on Principal Component Analysis (PCA) and Partial Least Squares—Discriminant Analysis (PLS-DA). Ultrasonography examination was used to ascertain the diagnosis of periportal fibrosis. Exploratory analysis showed a clear separation between coinfected and monoinfected samples. The supervised model built from PLS-DA showed accuracy, R2 and Q2 values equal to 100%, 98.1% and 97.5%, respectively. According to the variable importance in the projection plot, lactate serum levels were higher in the coinfected group, while the signals attributed to HDL serum cholesterol were more intense in the monoinfected group.Conclusions/SignificanceThe metabonomics models constructed in this study are promising as an alternative tool for diagnosis of periportal fibrosis by schistosomiasis in patients with chronic HBV or HCV infection from endemic areas for Schistosoma mansoni.

AIMTo develop metabonomic models (MMs), using 1H nuclear magnetic resonance (NMR) spectra of serum, to predict significant liver fibrosis (SF: Metavir ≥ F2), advanced liver fibrosis (AF: METAVIR ≥ F3) and cirrhosis (C: METAVIR = F4 or clinical cirrhosis) in chronic hepatitis C (CHC) patients. Additionally, to compare the accuracy of the MMs with the aspartate aminotransferase to platelet ratio index (APRI) and fibrosis index based on four factors (FIB-4).METHODSSixty-nine patients who had undergone biopsy in the previous 12 mo or had clinical cirrhosis were included. The presence of any other liver disease was a criterion for exclusion. The MMs, constructed using partial least squares discriminant analysis and linear discriminant analysis formalisms, were tested by cross-validation, considering SF, AF and C.RESULTSResults showed that forty-two patients (61%) presented SF, 28 (40%) AF and 18 (26%) C. The MMs showed sensitivity and specificity of 97.6% and 92.6% to predict SF; 96.4% and 95.1% to predict AF; and 100% and 98.0% to predict C. Besides that, the MMs correctly classified all 27 (39.7%) and 25 (38.8%) patients with intermediate values of APRI and FIB-4, respectively.CONCLUSIONThe metabonomic strategy performed excellently in predicting significant and advanced liver fibrosis in CHC patients, including those in the gray zone of APRI and FIB-4, which may contribute to reducing the need for these patients to undergo liver biopsy.

Anti-rods and rings (anti-RR) antibodies are related to hepatitis C virus (HCV) in patients treated with pegylated interferon (PEG-IFN) and ribavirin (RBV). Only RBV induces rods/rings structures in vitro; but in vivo, the antibody appearance is related to the combination of these drugs, because data about patients using just one of these drugs alone is missing. Some studies suggest disappearance of these antibodies over time. The aim of this study was to describe the occurrence of anti-RR in patients with chronic hepatitis C treatment-naïve or previously PEG-IFN/RBV-experienced, evaluating the persistence of anti-RR antibodies long after PEG-IFN/RBV treatment. From 2016 to 2017, 70 HCV-infected patients were screened for anti-RR using indirect immunofluorescence. Demographic and clinical data about previous treatments against HCV were assessed. Thirty-four patients (49%) had been previously treated with PEG-IFN/RBV and the average time since they had received the last antiviral treatment was 85.4 months. Anti-RR seropositivity was detected in 16 patients (23%), and all of these had used PEG-IFN/RBV (corresponding to 47% of experienced patients). Previous antiviral treatment and previous exposure time to RBV were associated with anti-RR positivity. Median time elapsed since last treatment was similar between anti-RR-positive and anti-RR-negative patients. Anti-RR seropositivity was not observed in treatment-naïve patients, but was detected in almost half of patients previously treated with PEG-IFN and RBV, even after a long period without exposure to these drugs. This antibody was related to extended prior exposure to ribavirin.

BackgroundARFI elastrography has been used as a noninvasive method to assess the severity of liver fibrosis in viral hepatitis, although with few studies in schistosomiasis mansoni. We aimed to evaluate the performance of point shear wave elastography (pSWE) for predicting significant periportal fibrosis (PPF) in schistosomotic patients and to determine its best cutoff point.Methodology/principal findingsThis cross-sectional study included 358 adult schistosomotic patients subjected to US and pSWE on the right lobe. Two hundred two patients (62.0%) were women, with a median age of 54 (ranging 18–92) years. The pSWE measurements were compared to the US patterns of PPF, as gold standard, according to the Niamey classification. The performance of pSWE was calculated as the area under the ROC curve (AUC). Patients were further classified into two groups: 86 patients with mild PPF and 272 patients with significant PPF. The median pSWE of the significant fibrosis group was higher (1.40 m/s) than that of mild fibrosis group (1.14 m/s, p<0.001). AUC was 0.719 with ≤1.11 m/s as the best cutoff value for excluding significant PPF. Sensitivity and negative predictive values were 80.5% and 40.5%, respectively. Whereas, for confirming significant PPF, the best cutoff value was >1.39 m/s, with specificity of 86.1% and positive predictive value of 92.0%.Conclusions/significancepSWE was able to differentiate significant from mild PPF, with better performance to predict significant PPF.

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