Metabolomics: From liver chiromancy to personalized precision medicine in advanced chronic liver disease

Polydatin: A Critical Promising Natural Agent for Liver Protection via Antioxidative Stress

Polydatin, one of the natural active small molecules, was commonly applied in protecting and treating liver disorders in preclinical studies. Oxidative stress plays vital roles in liver injury caused by various factors, such as alcohol, viral infections, dietary components, drugs, and other chemical reagents. It is reported that oxidative stress might be one of the main reasons in the progressive development of alcohol liver diseases (ALDs), nonalcoholic liver diseases (NAFLDs), liver injury, fibrosis, hepatic failure (HF), and hepatocellular carcinoma (HCC). In this paper, we comprehensively summarized the pharmacological effects and potential molecular mechanisms of polydatin for protecting and treating liver disorders via regulation of oxidative stress. According to the previous studies, polydatin is a versatile natural compound and exerts significantly protective and curative effects on oxidative stress-associated liver diseases via various molecular mechanisms, including amelioration of liver function and insulin resistance, inhibition of proinflammatory cytokines, lipid accumulation, endoplasmic reticulum stress and autophagy, regulation of PI3K/Akt/mTOR, and activation of hepatic stellate cells (HSCs), as well as increase of antioxidant enzymes (such as catalase (CAT), glutathione peroxidase (GPx), glutathione (GSH), superoxide dismutase (SOD), glutathione reductase (GR), and heme oxygenase-1 (HO-1)). In addition, polydatin acts as a free radical scavenger against reactive oxygen species (ROS) by its phenolic and ethylenic bond structure. However, further clinical investigations are still needed to explore the comprehensive molecular mechanisms and confirm the clinical treatment effect of polydatin in liver diseases related to regulation of oxidative stress.

Metabolic analysis of early nonalcoholic fatty liver disease in humans using liquid chromatography-mass spectrometry

BACKGROUND

Nonalcoholic fatty liver disease (NAFLD) is a common metabolic disease that affects 20-30% of individuals worldwide. Liver puncture remains the gold standard for the diagnosis of liver diseases despite limitations regarding invasive nature and sample variability. It is of great clinical significance to find noninvasive biomarkers to detect and predict NAFLD.

OBJECTIVE

The aims of this study were to identify potential serum markers in individuals with early-stage NAFLD and to advance the mechanistic understanding of this disease using a high-throughput mass spectrometry-based untargeted metabolomics approach.

METHODS

One hundred and twelve patients with early-stage NAFLD aged 18-55 were recruited according to the guidelines. The control group included 112 healthy participants. The demographic, anthropometric, clinical and laboratory data of all participants were systematically collected. Serum samples were obtained after an overnight fast. The comprehensive serum metabolomic analysis was performed by ultra-performance liquid chromatography-Orbitrap mass spectrometry. The resultant data was processed by Compound Discover and SIMCA-P software to validate the potential biomarkers. Significantly altered metabolites were evaluated by variable importance in projection value (VIP > 1) and ANOVA (p < 0.01). Pathway analysis was performed using MetaboAnalyst 4.0.

RESULTS

The liver function test of early NAFLD patients showed no statistical differences to control group (p > 0.05). However, obvious differences in blood lipids were observed between subjects with NAFLD and controls (p < 0.001). In total, 55 metabolites showed significant changes in experimental group were identified. The area under curve (AUC) values deduced by receiver operating curve (ROC) analysis indicated that these newly identified biomarkers have high predictability and reliability. Of these, 15 metabolites with AUC greater than 0.9 were of great diagnostic value in early NAFLD patients.

CONCLUSION

In this study, a total of 15 serum metabolites were found to strongly associate with early NAFLD. These biomarkers may have great clinical significance in the early diagnosis of NAFLD, as well as to follow response to therapeutic interventions.

Topic Evolution Analysis for Omics Data Integration in Cancers

One of the vital challenges for cancer diseases is efficient biomarkers monitoring formation and development are limited. Omics data integration plays a crucial role in the mining of biomarkers in the human condition. As the link between omics study on biomarkers discovery and cancer diseases is deepened, defining the principal technologies applied in the field is a must not only for the current period but also for the future. We utilize topic modeling to extract topics (or themes) as a probabilistic distribution of latent topics from the dataset. To predict the future trend of related cases, we utilize the Prophet neural network to perform a prediction correction model for existing topics. A total of 2,318 pieces of literature (from 2006 to 2020) were retrieved from MEDLINE with the query on “omics” and “cancer.” Our study found 20 topics covering current research types. The topic extraction results indicate that, with the rapid development of omics data integration research, multi-omics analysis (Topic 11) and genomics of colorectal cancer (Topic 10) have more studies reported last 15 years. From the topic prediction view, research findings in multi-omics data processing and novel biomarker discovery for cancer prediction (Topic 2, 3, 10, 11) will be heavily focused in the future. From the topic visuallization and evolution trends, metabolomics of breast cancer (Topic 9), pharmacogenomics (Topic 15), genome-guided therapy regimens (Topic 16), and microRNAs target genes (Topic 17) could have more rapidly developed in the study of cancer treatment effect and recurrence prediction.

Plasma metabolomic fingerprint of advanced cirrhosis stages among HIV/HCV-coinfected and HCV-monoinfected patients

BACKGROUND & AIMS

Hepatitis C virus (HCV), human immunodeficiency virus (HIV) and cirrhosis induce metabolic disorders. Here, we aimed to evaluate the association of plasma metabolites with Child-Turcotte-Pugh (CTP) score and hepatic decompensation in HIV/HCV-coinfected and HCV-monoinfected patients with advanced cirrhosis.

METHODS

A cross-sectional study was carried out in 62 HIV/HCV-coinfected and 28 HCV-monoinfected patients. Metabolomics analysis was performed by gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS). The statistical association analysis was performed by partial least squares discriminant analysis (PLS-DA) and generalized linear model (GLM) with binomial distribution (to analyse HIV coinfection, high alcohol intake, treatment with statins, previous HCV therapy failure and decompensation) and ordinal logistic regression (OLR) models to analyse different stages of cirrhosis (CTP score).

RESULTS

The statistical analysis identified plasma metabolites associated with HIV coinfection, high alcohol intake, CTP score and hepatic decompensation. Overall, fatty acids, bile acids, aromatic and sulphur amino acids, butyrate derivatives, oxidized phospholipids, energy-related metabolites and bacterial fermentation-related metabolites were increased in more advanced cirrhosis stages; while lysophosphatidylcholines and lysophosphatidylethanolamines, branched-chain amino acids (BCAA) and metabolites of tricarboxylic acid cycle, among others, were decreased in more advanced cirrhosis. Most of the significant metabolites displayed a similar trend after stratifying for HIV/HCV- and HCV-infected patients. Glycolic acid, LPC (16:0) and taurocholic acid had high accuracy for discriminating patients according to decompensated cirrhosis (CTP ≥ 7).

CONCLUSION

Altered plasma metabolomic profile was associated with advanced stages of cirrhosis in HIV/HCV-coinfected and HCV-monoinfected patients.

Metabolomic Analysis Identifies Glycometabolism Pathways as Potential Targets of Qianggan Extract in Hyperglycemia Rats

Qianggan formula, a designed prescription according to the Traditional Chinese Medicine (TCM) theory, is widely used in treating chronic liver diseases, and indicated to prevent blood glucose increase in patients via unknown mechanisms. To unravel the effects and underlying mechanisms of Qianggan formula on hyperglycemia, we administrated Qianggan extract to high fat and high sucrose (HFHS) diet rats. Results showed that four-week Qianggan extract intervention significantly decreased serum fasting blood glucose, hemoglobin A1c, and liver glycogen levels. Gas chromatography-mass spectrometry (GC-MS) approach was employed to explore metabolomic profiles in liver and fecal samples. By multivariate and univariate statistical analysis (variable importance of projection value > 1 and p value < 0.05), 44 metabolites (18 in liver and 30 in feces) were identified as significantly different. Hierarchical cluster analysis revealed that most differential metabolites had opposite patterns between pair-wise groups. Qianggan extract restored the diet induced metabolite perturbations. Metabolite sets enrichment and pathway enrichment analysis revealed that the affected metabolites were mainly enriched in glycometabolism pathways such as glycolysis/gluconeogenesis, pentose phosphate pathway, fructose, and mannose metabolism. By compound-reaction-enzyme-gene network analysis, batches of genes (e.g. Hk1, Gck, Rpia, etc) or enzymes (e.g. hexokinase and glucokinase) related to metabolites in enriched pathways were obtained. Our findings demonstrated that Qianggan extract alleviated hyperglycemia, and the effects might be partially due to the regulation of glycometabolism related pathways.

Metabolic Signature of Hepatic Fibrosis: From Individual Pathways to Systems Biology

Hepatic fibrosis is a major cause of morbidity and mortality worldwide, as it ultimately leads to cirrhosis, which is estimated to affect up to 2% of the global population. Hepatic fibrosis is confirmed by liver biopsy, and the erroneous nature of this technique necessitates the search for noninvasive alternatives. However, current biomarker algorithms for hepatic fibrosis have many limitations. Given that the liver is the largest organ and a major metabolic hub in the body, probing the metabolic signature of hepatic fibrosis holds promise for the discovery of new markers and therapeutic targets. Regarding individual metabolic pathways, accumulating evidence shows that hepatic fibrosis leads to alterations in carbohydrate metabolism, as aerobic glycolysis is aggravated in activated hepatic stellate cells (HSCs) and the whole fibrotic liver; in amino acid metabolism, as Fischer’s ratio (branched-chain amino acids/aromatic amino acids) decreases in patients with hepatic fibrosis; and in lipid metabolism, as HSCs lose vitamin A-containing lipid droplets during transdifferentiation, and cirrhotic patients have decreased serum lipids. The current review also summarizes recent findings of metabolic alterations relevant to hepatic fibrosis based on systems biology approaches, including transcriptomics, proteomics, and metabolomics in vitro, in animal models and in humans.

Metabolomic Analysis of Liver Tissues for Characterization of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) causes more than half a million annual deaths worldwide. Understanding the mechanisms contributing to HCC development is highly desirable for improved surveillance, diagnosis, and treatment. Liver tissue metabolomics has the potential to reflect the physiological changes behind HCC development. Also, it allows identification of biomarker candidates for future evaluation in biofluids and investigation of racial disparities in HCC. Tumor and nontumor tissues from 40 patients were analyzed by both gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) platforms to increase the metabolome coverage. The levels of the metabolites extracted from solid liver tissue of the HCC area and adjacent non-HCC area were compared. Among the analytes detected by GC-MS and LC-MS with significant alterations, 18 were selected based on biological relevance and confirmed metabolite identification. These metabolites belong to TCA cycle, glycolysis, purines, and lipid metabolism and have been previously reported in liver metabolomic studies where high correlation with HCC progression is implied. We demonstrated that metabolites related to HCC pathogenesis can be identified through liver tissue metabolomic analysis. Additionally, this study has enabled us to identify race-specific metabolites associated with HCC.

Advanced Hepatocellular Carcinoma with Bone Metastases: Prevalence, Associated Factors, and Survival Estimation

BACKGROUND The objective of the present research was to explore the prevalence, risk, and prognostic factors associated with bone metastases (BM) in newly diagnosed hepatocellular carcinoma (HCC) patients. MATERIAL AND METHODS From 36 507 HCC patients who were registered in Surveillance, Epidemiology, and End Results (SEER) database, we enrolled 1263 with BM at the initial diagnosis of HCC from 2010 to 2014. Kaplan-Meier curves and log-rank tests were used to estimate overall survival for different subgroups. Univariate and multivariate logistic and Cox regression analyses were performed to identify risk factors and independent prognostic factors for BM. RESULTS A total of 1567 (4.29%) HCC patients were detected with BM at initial diagnosis. Male sex, unmarried status, higher T stage, lymph node involvement, intrahepatic metastases, and extrahepatic metastases (lung or brain) were positively associated with BM. The median survival of the patients was 3.00 months (95% CI: 2.77-3.24 months). Marital status and primary tumor surgery were independently associated with the better survival. CONCLUSIONS A list of factors associated with BM occurrence and the prognosis of the advanced HCC patients with BM were found. These associated factors may provide a reference for BM screening in HCC and guide prophylactic treatment in clinical settings.