Accurate non-invasive diagnosis and staging of non-alcoholic fatty liver disease using the urinary steroid metabolome

Metabonomics and pharmacodynamics studies of Gentiana radix and wine-processed Gentiana radix in damp-heat jaundice syndrome rats

ETHNOPHARMACOLOGICAL RELEVANCE

Gentiana radix (GR) and wine-processed Gentiana radix (WGR) have been commonly used in folk medicine for the treatment of bile or liver disorders, including jaundice, hepatitis, swelling and inflammation for thousands of years. However, the therapeutic effects of gentian root (GR) and wine-made gentian root (WGR) treatment on damp-heat jaundice syndrome (DHJS) have not been studied in animal experiments.

AIM OF THE STUDY

This study aimed to investigate the protective effects and mechanisms of GR and WGR on DHJS in rats.

MATERIALS AND METHODS

In a high-fat and high-sugar diet in a humidified hot environment, hepatic injury induced by giving alpha-naphthalene isothiocyanate (ANIT) in rats were used as a DHJS model. Histological analysis, enzyme-linked immunosorbent assay (ELISA), PCR analysis, and metabolomics were used to elucidate the mechanism of GR and WGR for DHJS.

RESULTS

The results indicated that GR and WGR affected DHJS by inhibiting the release of aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), direct bilirubin (D-BIL), total bilirubin (TBIL), total bile acid (TBA), malondialdehyde (MDA), glutathione S-transferase (GST) (P < 0.05). In addition, they significantly reduced the gene expression levels of Na+/taurocholate cotransporting polypeptide (NTCP), bile salt export pump (BESP), multidrug resistance-associated protein 2 (MRP2) and multidrug resistance-associated protein 3 (MRP3) (P < 0.05). The WGR group improved the above function indicators better than the GR group. GR and WGR could restore 11 potential biomarkers in rats with DHJS tended to return to normal levels, these biomarkers were involved in arachidonic acid metabolism, steroid hormone biosynthesis, biosynthesis of unsaturated fatty acids, porphyrin and chlorophyll metabolism, retinol metabolism, arginine biosynthesis. The results of the metabolic pathway showed that WGR was significantly better than GR in the improvement of porphyrin and chlorophyll metabolism.

CONCLUSIONS

These findings suggest that treatment with GR and WGR has a beneficial effect on DHJS in rats, the major mechanisms may be involved in improving functional indicators of the body and endogenous metabolism, and WGR is more effective than GR. It provides important evidence for the clinical application of GR and WGR in the treatment of DHJS.

Perinatal exposure to perfluorooctane sulfonate and the risk of hepatic inflammation in rat offspring: Perturbation of gut-liver crosstalk

Perfluorooctane sulfonate (PFOS) exposure is associated with harmful hepatic outcomes. Growing evidence indicates that crosstalk between the gut microbiome, immune system, and liver plays a vital role in the pathogenesis of liver diseases. However, the underlying mechanism is not fully understood. In the present study, we aimed to investigate the effects of PFOS exposure during pregnancy and lactation on hepatic inflammation in rat offspring. Features of hepatic inflammation and increased levels of aspartate-amino transferase (AST) were found in pups on postnatal day 28 (PND28) in PFOS-exposed groups. Gut microbiota analysis identified Chitinophaga, Ralstonia, and Alloprevotella as the key genera in distinguishing the PFOS-exposed group from the control group. Metabolic and transcriptomic analyses found that PFOS exposure resulted in 48 differentially expressed metabolites (DEMs) in the serum, 62 DEMs in the liver, and 289 differentially expressed genes (DEGs) in the liver of PND28 pups. The immune response is significantly enriched in PFOS-exposed liver on PND28; multi-omics analysis indicated that PFOS might lead to immune response perturbation by disturbing the metabolic profiling in the liver. The changed gut microbiota was significantly related to the serum level of the liver function index. Specifically, Alloprevotella, Chitinophage, Ruminococcus, and Allobaculum were significantly associated with the metabolic abundance changes of 4-Hydroxydebrisoquine, L-Norvaline, and Eremopetasinorol, and the gene expression changes of Acat211, Msmol, Idi1, Sqle, and Gadd45b in the liver. These findings suggest that early-life PFOS exposure may be associated with adverse hepatic inflammation in young offspring via disruption of the gut-liver crosstalk, which may provide mechanistic clues for clarifying the hepatotoxicity in offspring associated with perinatal PFOS exposure.

Translating the potential of the urine steroid metabolome to stage NAFLD (TrUSt-NAFLD): study protocol for a multicentre, prospective validation study

INTRODUCTION

Non-alcoholic fatty liver disease (NAFLD) affects approximately one in four individuals and its prevalence continues to rise. The advanced stages of NAFLD with significant liver fibrosis are associated with adverse morbidity and mortality outcomes. Currently, liver biopsy remains the 'gold-standard' approach to stage NAFLD severity. Although generally well tolerated, liver biopsies are associated with significant complications, are resource intensive, costly, and sample only a very small area of the liver as well as requiring day case admission to a secondary care setting. As a result, there is a significant unmet need to develop non-invasive biomarkers that can accurately stage NAFLD and limit the need for liver biopsy. The aim of this study is to validate the use of the urine steroid metabolome as a strategy to stage NAFLD severity and to compare its performance against other non-invasive NAFLD biomarkers.

METHODS AND ANALYSIS

The TrUSt-NAFLD study is a multicentre prospective test validation study aiming to recruit 310 patients with biopsy-proven and staged NAFLD across eight centres within the UK. 150 appropriately matched control patients without liver disease will be recruited through the Oxford Biobank. Blood and urine samples, alongside clinical data, will be collected from all participants. Urine samples will be analysed by liquid chromatography-tandem mass spectroscopy to quantify a panel of predefined steroid metabolites. A machine learning-based classifier, for example, Generalized Matrix Relevance Learning Vector Quantization that was trained on retrospective samples, will be applied to the prospective steroid metabolite data to determine its ability to identify those patients with advanced, as opposed to mild-moderate, liver fibrosis as a consequence of NAFLD.

ETHICS AND DISSEMINATION

Research ethical approval was granted by West Midlands, Black Country Research Ethics Committee (REC reference: 21/WM/0177). A substantial amendment (TrUSt-NAFLD-SA1) was approved on 26 November 2021.

TRIAL REGISTRATION NUMBER

ISRCTN19370855.

Dysregulation of steroid metabolome in follicular fluid links phthalate exposure to diminished ovarian reserve of childbearing-age women

The widespread use of phthalates (PAEs) has drawn increasing attention due to their endocrine disruption and reproductive toxicity, while the steroid metabolome is essential for follicular development. However, the mechanism by which PAE exposure affects ovarian reserve through the steroid metabolome remains unclear. This study recruited 264 childbearing-age women in Tianjin (China) from April 2019 to August 2020 in a cross-sectional design. Target metabolome analysis of 16 steroids was performed in follicular fluid (FF) to compare diminished ovarian reserve (DOR) against normal ovarian reserve (NOR) women and differential steroids were identified using binary logistic analyses. Further analysis of eleven PAE metabolites (mPAEs) in FF was conducted, and the retrieved oocyte number (RON) representing ovarian reserve was counted. Multiple linear regression and quantile-based g-computation (qgcomp) models were used to associate individual mPAEs and mPAE mixture with the DOR-related differential steroids in FF. Mediation analysis was used to discuss the mediating effect of DOR-related steroids on the association between mPAEs and RON. Androstenedione (A4), corticosterone (CORT), cortisol (COR) and cortisone were significantly down-regulated in FF from women with DOR. Nine mPAEs with detection frequencies greater than 60% and median concentrations of 0.02-4.86 ng/mL were incorporated into statistical models. Negative associations with COR and CORT were found for mono-ethyl phthalate (mEP), mono-(2-ethyl-5-oxohexyl) phthalate (mEOHP), and mono-2-ethylhexyl phthalate (mEHP). A positive association with cortisone was found for mEOHP, mEHP, monobutyl phthalate (mBP), and mono (2-isobutyl) phthalate (miBP). The qgcomp and mediation analyses revealed that mEP and mEOHP not only significantly contributed to the decline of COR and CORT in the mixed exposure but also indirectly reduced RON through the mediating effects of COR and CORT. In conclusion, PAE exposure may decrease ovarian reserve by downregulating COR and CORT.

Artificial intelligence applied to omics data in liver diseases: Enhancing clinical predictions

Rapid development of biotechnology has led to the generation of vast amounts of multi-omics data, necessitating the advancement of bioinformatics and artificial intelligence to enable computational modeling to diagnose and predict clinical outcome. Both conventional machine learning and new deep learning algorithms screen existing data unbiasedly to uncover patterns and create models that can be valuable in informing clinical decisions. We summarized published literature on the use of AI models trained on omics datasets, with and without clinical data, to diagnose, risk-stratify, and predict survivability of patients with non-malignant liver diseases. A total of 20 different models were tested in selected studies. Generally, the addition of omics data to regular clinical parameters or individual biomarkers improved the AI model performance. For instance, using NAFLD fibrosis score to distinguish F0-F2 from F3-F4 fibrotic stages, the area under the curve (AUC) was 0.87. When integrating metabolomic data by a GMLVQ model, the AUC drastically improved to 0.99. The use of RF on multi-omics and clinical data in another study to predict progression of NAFLD to NASH resulted in an AUC of 0.84, compared to 0.82 when using clinical data only. A comparison of RF, SVM and kNN models on genomics data to classify immune tolerant phase in chronic hepatitis B resulted in AUC of 0.8793-0.8838 compared to 0.6759-0.7276 when using various serum biomarkers. Overall, the integration of omics was shown to improve prediction performance compared to models built only on clinical parameters, indicating a potential use for personalized medicine in clinical setting.

Application of metabolomics in the diagnosis of non-alcoholic fatty liver disease and the treatment of traditional Chinese medicine

Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease around the world, and it often coexists with insulin resistance-related diseases including obesity, diabetes, hyperlipidemia, and hypertension, which seriously threatens human health. Better prevention and treatment strategies are required to improve the impact of NAFLD. Although needle biopsy is an effective tool for diagnosing NAFLD, this method is invasive and difficult to perform. Therefore, it is very important to develop more efficient approaches for the early diagnosis of NAFLD. Traditional Chinese medicine (TCM) can play a certain role in improving symptoms and protecting target organs, and its mechanism of action needs to be further studied. Metabolomics, the study of all metabolites that is thought to be most closely associated with the patients’ characters, can provide useful clinically biomarkers that can be applied to NAFLD and may open up new methods for diagnosis. Metabolomics technology is consistent with the overall concept of TCM, and it can also be used as a potential mechanism to explain the effects of TCM by measuring biomarkers by metabolomics. Based on PubMed/MEDLINE and other databases, this paper retrieved relevant literature NAFLD and TCM intervention in NAFLD using metabolomics technology in the past 5 years were searched, and the specific metabolites associated with the development of NAFLD and the potential mechanism of Chinese medicine on improving symptoms were summarized.

Predictive value of liver cirrhosis using metabolite biomarkers of bile acid in the blood: A protocol for systematic review and meta-analysis

BACKGROUND

Previous studies have indicated that the changes of bile acids are associated with liver cirrhosis. The objective of our study is to perform a systematic review to explore the relationship between bile acids and the pathologic process of cirrhosis, and to find minimally invasive, accurate and reliable potential biomarkers for predicting cirrhosis.

METHODS

EMBASE, the Cochrane Library, PubMed, Web of Science, WanFang Data and Chinese National Knowledge Infrastructure (CNKI) will be searched, using the search strategy of liver cirrhosis, bile acids and metabolomic. The screening process will be conducted strictly based on inclusion and exclusion criteria. Clinical studies based on human including randomized controlled trial, cohort study and case control study will be included without restriction of time. Cochrane collaboration's tool for assessing risk of bias and Newcastle-Ottawa Scale (NOS) will be applied to assess the risk of bias to randomized controlled trial and observational study, respectively. The bile acids and their concentrate which are different between liver cirrhosis and control group will be the mainly outcome. A qualitative analysis will be performed to profile the trajectory change of bile acids, then the meta-analysis will be done for quantitative analysis.

RESULTS

The bile acids profile of liver cirrhosis that has potential predictive value for cirrhosis will be identified.

CONCLUSION

The conclusion of this systematic review will finding potential biomarkers for predicting cirrhosis.

ETHICS AND DISSEMINATION

This systematic review is based on published researches, so there is no ethical approval required. We intend to disseminate our findings in a peer-reviewed journal.

Hepatoprotective effect and metabonomics studies of radix gentianae in rats with acute liver injury

CONTEXT

As a well-known traditional Chinese medicine for protecting the liver, the mechanism of Radix Gentianae (RG) remains unclear.

OBJECTIVE

The hepatoprotective effect and metabonomics of RG were studied to explore the molecular and metabolic mechanisms of RG protecting the liver.

MATERIALS AND METHODS

Sprague-Dawley rats were divided into control and model group (n = 10, orally given distilled water), intervention group (4 subgroups, n = 10, prophylactically and orally given 0.63, 2.5 and 5.6 g/kg RG and 0.2 g/kg bifendatatum for 7 d). On day 7 of the intervention, all rats except the control were injected intraperitoneally with 2.5% carbon tetrachloride vegetable oil solution (1.5 mL/kg) to induce liver injury. After 24 h of carbon tetrachloride injection, rat serum and liver tissue were collected for determining AST, ALT, TNF-α, MCP-1, IL-6, SOD, MDA, GSH, and GSH-PX. Rat serum was used for analysing endogenous metabolism by UPLC-Q-TOF-MS.

RESULTS

Different doses of RG can significantly decrease the levels of AST, ALT, TNF-α, MCP-1, IL-6 and MDA, and increase the levels of SOD, GSH, and GSH-PX in rats with liver injury (p < 0.05; TNF-α, and IL-6, p < 0.05 only at 5.6 g/kg dose). Eight biomarkers of liver injury were obtained in serum metabonomics, involving five significant metabolic pathways. RG can improve steroid biosynthesis, linoleic acid metabolism, porphyrin and chlorophyll metabolism, and fatty acid biosynthesis.

CONCLUSION

RG demonstrated a good ability to protect the liver and improving endogenous metabolism in rats with liver injury. This can help us understand the mechanism of RG and more clinical verifications were inspired.

The Role of Diagnostic Biomarkers, Omics Strategies, and Single-Cell Sequencing for Nonalcoholic Fatty Liver Disease in Severely Obese Patients

Liver disease due to metabolic dysfunction constitute a worldwide growing health issue. Severe obesity is a particularly strong risk factor for non-alcoholic fatty liver disease, which affects up to 93% of these patients. Current diagnostic markers focus on the detection of advanced fibrosis as the major predictor of liver-related morbidity and mortality. The most accurate diagnostic tools use elastography to measure liver stiffness, with diagnostic accuracies similar in normal-weight and severely obese patients. The effectiveness of elastography tools are however hampered by limitations to equipment and measurement quality in patients with very large abdominal circumference and subcutaneous fat. Blood-based biomarkers are therefore attractive, but those available to date have only moderate diagnostic accuracy. Ongoing technological advances in omics technologies such as genomics, transcriptomics, and proteomics hold great promise for discovery of biomarkers and increased pathophysiological understanding of non-alcoholic liver disease and steatohepatitis. Very recent developments have allowed for single-cell sequencing and cell-type resolution of gene expression and function. In the near future, we will therefore likely see a multitude of breakthrough biomarkers, developed from a deepened understanding of the biological function of individual cell types in the healthy and injured liver.

The role of omics in the pathophysiology, diagnosis and treatment of non-alcoholic fatty liver disease

Non-alcoholic fatty liver disease (NAFLD) is a multifaceted metabolic disorder, whose spectrum covers clinical, histological and pathophysiological developments ranging from simple steatosis to non-alcoholic steatohepatitis (NASH) and liver fibrosis, potentially evolving into cirrhosis, hepatocellular carcinoma and liver failure. Liver biopsy remains the gold standard for diagnosing NAFLD, while there are no specific treatments. An ever-increasing number of high-throughput Omics investigations on the molecular pathobiology of NAFLD at the cellular, tissue and system levels produce comprehensive biochemical patient snapshots. In the clinical setting, these applications are considerably enhancing our efforts towards obtaining a holistic insight on NAFLD pathophysiology. Omics are also generating non-invasive diagnostic modalities for the distinct stages of NAFLD, that remain though to be validated in multiple, large, heterogenous and independent cohorts, both cross-sectionally as well as prospectively. Finally, they aid in developing novel therapies. By tracing the flow of information from genomics to epigenomics, transcriptomics, proteomics, metabolomics, lipidomics and glycomics, the chief contributions of these techniques in understanding, diagnosing and treating NAFLD are summarized herein.