Non-invasive urinary metabolomic profiles discriminate biliary atresia from infantile hepatitis syndrome

Rhein modulates host purine metabolism in intestine through gut microbiota and ameliorates experimental colitis

Background: Gut microbiota, which plays a crucial role in inflammatory bowel diseases (IBD), might have therapeutic benefits for ulcerative colitis or Crohn's disease. Targeting gut microbiota represents a new treatment strategy for IBD patients. Rhein is one of the main components of rhubarb and exhibits poor oral bioavailability but still exerts anti-inflammatory effects in some diseases. Therefore, we investigated the effect of rhein on colitis and studied its possible mechanisms.

Methods: The chronic mouse colitis model was induced by four rounds of 2% dextran sulfate sodium (DSS) treatment. The mice were treated with 50 mg/kg and 100 mg/kg rhein daily, body weight, colon length, histological score, inflammatory cytokines in serum or intestine, and fecal lipocalin 2 concentration were determined. Th17 cell, Th1 cell and Th2 cell infiltration in the mesenteric lymph node were analyzed by flow cytometry. Metabolic profiles were collected by non-targeted metabolomics and key metabolic pathways were identified using MetaboAnalyst 4.0. We also assessed intestinal barrier permeability and performed 16s rDNA sequencing. Lactobacillus sp. was cultured, and fecal microbiota transplantation (FMT) was employed to evaluate the contribution of gut microbiota.

Results: Rhein could significantly alleviate DSS-induced chronic colitis. Uric acid was identified as a crucial modulator of colitis and rhein treatment led to decreased uric acid levels. We determined that rhein changed purine metabolism indirectly, while the probiotic Lactobacillus was involved in the regulation of host metabolism. Uric acid resulted in a worsened intestinal barrier, which could be rescued by rhein. We further confirmed that rhein-treated gut microbiota was sufficient to relieve DSS-induced colitis by FMT.

Conclusion: We showed that rhein could modulate gut microbiota, which indirectly changed purine metabolism in the intestine and subsequently alleviated colitis. Our study has identified a new approach to the clinical treatment of colitis.

Three-color risk stratification for improving the diagnostic accuracy for biliary atresia

OBJECTIVES

It is challenging to early differentiate biliary atresia from other causes of cholestasis. We aimed to develop an algorithm with risk stratification to distinguish biliary atresia from infantile cholestasis.

METHODS

In this study, we enrolled infants with cholestasis into 2 subgroups from January 2010 to April 2019. A prospective cohort (subgroup 2) of 187 patients (107 with biliary atresia and 80 without biliary atresia) underwent acoustic radiation force impulse elastography. Stepwise regression was used to identify significant predictors of biliary atresia. A sequential algorithm with risk stratification was constructed.

RESULTS

Among 187 patients, shear wave speed > 1.35 m/s and presence of the triangular cord sign were considered high risk for biliary atresia (red), in which 73 of 78 patients (accuracy of 93.6%) with biliary atresia were identified. Afterwards, γ-GT, abnormal gallbladder, and clay stool were introduced into the algorithm and 55 intermediate-risk infants were identified (yellow) with a diagnostic accuracy of 60% for biliary atresia. Of the remaining 54 infants who were classified as low-risk patients (green), the accuracy for excluding biliary atresia was 98.1%. By applying a three-color risk stratification tool, 70.6% patients were identified as either high risk or low risk for biliary atresia (area under the curve, 0.983; sensitivity, 98.7%; specificity, 91.4%). We also estimated the risk of biliary atresia in different color groups, which was 94.7% (95%CI, 94.3-95.5%) in the red group and 7.2% (95%CI, 6.6-8.3%) in the green group.

CONCLUSIONS

Our simple noninvasive approach was able to identify biliary atresia with high accuracy.

KEY POINTS

• Five predictors, namely shear wave speed, triangle cord sign, γ-glutamyl transferase, abnormal gallbladder, and clay stool, were selected to identify biliary atresia in cholestasis. • Shear wave speed > 1.35 m/s and presence of the triangle cord sign were considered high-risk patients with a diagnostic accuracy of 93.6% for biliary atresia. • Risk for biliary atresia was high (red), intermediate (yellow), or low (green). In the red and green group, we achieved an extremely high diagnostic performance (area under the curve, 0.983; sensitivity, 98.7%; specificity, 91.4%).

Metabolomic and Lipidomic Biomarkers for Premalignant Liver Disease Diagnosis and Therapy

In recent years, there has been a plethora of attempts to discover biomarkers that are more reliable than α-fetoprotein for the early prediction and prognosis of hepatocellular carcinoma (HCC). Efforts have involved such fields as genomics, transcriptomics, epigenetics, microRNA, exosomes, proteomics, glycoproteomics, and metabolomics. HCC arises against a background of inflammation, steatosis, and cirrhosis, due mainly to hepatic insults caused by alcohol abuse, hepatitis B and C virus infection, adiposity, and diabetes. Metabolomics offers an opportunity, without recourse to liver biopsy, to discover biomarkers for premalignant liver disease, thereby alerting the potential of impending HCC. We have reviewed metabolomic studies in alcoholic liver disease (ALD), cholestasis, fibrosis, cirrhosis, nonalcoholic fatty liver (NAFL), and nonalcoholic steatohepatitis (NASH). Specificity was our major criterion in proposing clinical evaluation of indole-3-lactic acid, phenyllactic acid, N-lauroylglycine, decatrienoate, N-acetyltaurine for ALD, urinary sulfated bile acids for cholestasis, cervonoyl ethanolamide for fibrosis, 16α-hydroxyestrone for cirrhosis, and the pattern of acyl carnitines for NAFL and NASH. These examples derive from a large body of published metabolomic observations in various liver diseases in adults, adolescents, and children, together with animal models. Many other options have been tabulated. Metabolomic biomarkers for premalignant liver disease may help reduce the incidence of HCC.

Brain Metabolomics Reveal the Antipyretic Effects of Jinxin Oral Liquid in Young Rats by Using Gas Chromatography⁻Mass Spectrometry

Pyrexia is considered as a part of host's defense response to the invasion of microorganisms or inanimate matter recognized as pathogenic or alien, which frequently occurs in children. Jinxin oral liquid (JXOL) is a traditional Chinese medicine formula that has been widely used to treat febrile children in China. Experimental fever was induced by injecting yeast into young male Sprague-Dawley rats (80 ± 20 g) and the rectal temperature subsequently changed. Four hours later, the excessive production of interleukin (IL)-1β and prostaglandin (PG) E2 induced by yeast was regulated to normal by JXOL administration. A rat brain metabolomics investigation of pyrexia of yeast and antipyretic effect of JXOL was performed using gas chromatography-mass spectrometry (GC-MS). Clear separation was achieved between the model and normal group. Twenty-two significantly altered metabolites were found in pyretic rats as potential biomarkers of fever. Twelve metabolites, significantly adjusted by JXOL to help relieve pyrexia, were selected out as biomarkers of antipyretic mechanism of JXOL, which were involved in glycolysis, purine metabolism, tryptophan mechanism, etc. In conclusion, the brain metabolomics revealed potential biomarkers in the JXOL antipyretic process and the associated pathways, which may aid in advanced understanding of fever and therapeutic mechanism of JXOL.

Ion-Pair Selection Method for Pseudotargeted Metabolomics Based on SWATH MS Acquisition and Its Application in Differential Metabolite Discovery of Type 2 Diabetes

The pseudotargeted metabolomics method integrates advantages of nontargeted and targeted analysis because it can acquire data of metabolites in the multireaction monitoring (MRM) mode of mass spectrometry (MS) without needing standards. The key is the ion-pair information collection from samples to be analyzed. It is well-known that sequential windowed acquisition of all theoretical Fragment ion (SWATH) MS mode can acquire MS2 information to a maximum extent. To expediently acquire as many ion-pairs as possible with optimal collision energy (CE), an ion-pair selection approach based on SWATH MS acquisition with variable isolation windows was developed in this study. Initially, nontargeted acquisition of all metabolites information in plasma Standard Reference Material (SRM 1950) was performed by ultra high-performance liquid chromatography (UHPLC)-quadrupole time-of-flight (Q-TOF) MS platform with three CEs. With the help of software tool, the ion-pairs of unique metabolites were gained. Then they were validated in scheduled MRM coupled with UHPLC. After removing false positive, the ion-pairs with an optimal CE was integrated. A total of 1373 unique metabolite ion-pairs were obtained at positive ion mode. And repeatability of the established pseudotargeted approach was evaluated by intraday and interday precision. The results demonstrated the method was stable, reliable, and suitable for metabolomics study. As an application example, alterations of serum metabolites in Type 2 diabetes were investigated by using the established method. This work provides a pseudotargeted ion-pair selection method based on SWATH MS acquisition with the characters of increased metabolite coverage, suitable CE, and convenient processing.