A clinical experience-based Chinese herbal formula improves ethanol-induced drunken behavior and hepatic steatohepatitis in mice models.

BACKGROUND: Bao-Gan-Xing-Jiu-Wan (BGXJW) is a clinical experience-based Chinese herbal formula. Its efficacy, pharmacological safety, targeted function, process quality, and other aspects have met the evaluation standards and the latest requirements of preparations. It could prevent and alleviate the symptoms of drunkenness and alcoholic liver injury clinically. The present work aims to elucidate whether BGXJW could protect against drunkenness and alcoholic liver disease in mice and explore the associated mechanism. MATERIAL AND METHODS: We used acute-on-chronic (NIAAA) mice model to induce alcoholic steatosis, and alcohol binge-drinking model to reappear the drunk condition. BGXJW at indicated doses were administered by oral gavage respectively to analyze its effects on alcoholic liver injury and the associated molecular mechanisms. RESULTS: BGXJW had no cardiac, hepatic, renal, or intestinal toxicity in mice. Alcoholic liver injury and steatosis in the NIAAA mode were effectively prevented by BGXJW treatment. BGXJW increased the expression of alcohol metabolizing enzymes ADH, CYP2E1, and ALDH2 to enhance alcohol metabolism, inhibited steatosis through regulating lipid metabolism, counteracted alcohol-induced upregulation of lipid synthesis related proteins SREBP1, FASN, and SCD1, meanwhile it enhanced fatty acids ß-oxidation related proteins PPAR-α and CPT1A. Alcohol taken enhanced pro-inflammatory TNF-α, IL-6 and down-regulated the anti-inflammatory IL-10 expression in the liver, which were also reversed by BGXJW administration. Moreover, BGXJW significantly decreased the blood ethanol concentration and alleviated drunkenness in the alcohol binge-drinking mice model. CONCLUSIONS: BGXJW could effectively relieve drunkenness and prevent alcoholic liver disease by regulating lipid metabolism, inflammatory response, and alcohol metabolism.

New Insights into Herb-Induced Liver Injury.

Significance: Herbs are widely used worldwide. However, inappropriate use of some of the herbs can lead to herb-induced liver injury (HILI). Intriguingly, HILI incidents are on the rise, and our understanding of the underlying etiologies is in progress, and hence, an update on the current status of incidents as well as our understanding on the etiologies of HILI is appropriate. Recent Advances: HILI reports due to the use of some herbs that are traditionally considered to be safe are also on the rise. Furthermore, HILI due to the use of certain herbs in combination with other herbs (herb-herb interaction [HHI]) or non-herb components (herb-drug interaction [HDI]) has also been reported, suggesting a potentially important new type of inappropriate use of herbs. Critical Issues: Updated overviews focus on the epidemiology, etiology, phenotypes, and risk factors of HILI, as well as HDI and HHI, and analysis on several types of newly reported "toxic" effects of herbs based on types of hepatotoxicity and the HILI mechanisms. Future Directions: HILI will continue to be a significant public health challenge in the near future. In the light of the lack of broadly available guidelines and regulations for proper and safe uses of herbs worldwide, raising the public awareness of HILI will remain one of the most effective measures. In particular, it should include a better understanding of the contributing factors; a more detail subclassification and description of HILI, better characterization of the components/substances that could induce HILI; and development of HILI diagnosis based on the Roussel Uclaf Causality Assessment Method (RUCAM). Antioxid. Redox Signal. 38, 1138-1149.

Metabolomic profiling for drug-induced liver injury with autoantibodies.

BACKGROUNDS: Drug induced liver injury (DILI) is sometimes similar to autoimmune hepatitis (AIH) in serology and histology. Clinicians empirically screened DILI with significant autoimmune characteristics to implement clinical intervention. We tried to characterize DILI with autoantibodies by metabolomics. METHODS: Untargeted metabolomics coupled with pattern recognition approaches were performed on sera samples including AIH (n = 59), DILI with autoantibodies (DILIAb+, n = 68), and DILI without autoantibodies (DILIAb-, n = 75). The differential metabolites and fingerprint metabolites between AIH and DILIAb- were screened by orthogonal partial least squares-discriminant analysis and hierarchical clustering respectively. RESULTS: Of the 388 annotated differential metabolites between AIH and DILIAb-, 74 fingerprint metabolites were screened. The eigenmetabolite compressed from the fingerprint possessed high discrimination efficacy (AUC:0.891; 95 %CI, 0.838-0.944). In the fingerprint-based PCA model, AIH and DILIAb- were separated into three regions: the "pure region" of AIH (Region 1), the "pure region" of DILIAb- (Region 3), the mixture region of AIH and DILIAb- (Region 2). After incorporated into the PCA model, DILIAb+ samples were distributed into the three regions, indicating that DILIAb+ samples had different etiological tendencies. Moreover, the fingerprint-based radar model verified the results of PCA model characterizing DILIAb+. Notably, the antibody titers of DILIAb+ in the three regions did not differ significantly, while the response rates for glucocorticoids were obviously different. The metabolic difference among DILIAb+ in different regions mainly lies in energy metabolism. CONCLUSIONS: In terms of metabolic signature, DILIAb+ may not be a community of same pathogenesis, including AIH-inclined parts. Which deserves further study.

Metabolomic Profiling for Histologically Fibrotic Stage in Chronic Drug-Induced Liver Injury.

Background and aims: Chronic drug-induced liver injury (DILI) is a rare but under-researched adverse drug reaction-related disease, which is highly likely to progress into liver fibrosis and even cirrhosis. In this study, metabolomics was used to screen out characteristic metabolites related to the histological progression of fibrosis in chronic DILI and analyze the metabolic changes during the development of fibrosis to explain the underlying mechanism. Methods: Chronic DILI patients who underwent liver biopsy were divided into different fibrosis grades. Serum was analyzed by untargeted metabolomics to find serological characteristic metabolite fingerprints. The screened fingerprints were validated by the validation group patients, and the identification ability of fingerprints was compared using FibroScan. Results: A total of 31 metabolites associated with fibrosis and 11 metabolites associated with advanced fibrosis were identified. The validation group confirmed the accuracy of the two metabolite fingerprints [area under the curve (AUC) value 0.753 and 0.944]. In addition, the fingerprints showed the ability to distinguish the grades of fibrosis by comparing using FibroScan. The metabolite fingerprint pathway showed that bile acid synthesis is disturbed while lipid metabolism is extremely active, resulting in an overload of lipid metabolites in the occurrence and development of chronic DILI-associated fibrosis. Conclusions: Our metabolomic analysis reveals the unique metabolomic fingerprints associated with chronic DILI fibrosis, which have potential clinical diagnostic and prognostic significances. The metabolomic fingerprints suggest the disturbance of the lipid metabolites as the most important factor in the development of DILI fibrosis.

Metabolomic Analysis Uncovers Lipid and Amino Acid Metabolism Disturbance During the Development of Ascites in Alcoholic Liver Disease.

Ascites is one of the most common complications of cirrhosis, and there is a dearth of knowledge about ascites-related pathologic metabolism. In this study, 122 alcoholic liver disease (ALD) patients, including 49 cases without ascites, 18 cases with mild-ascites, and 55 cases with large-ascites (1) were established according to the International Ascites Club (2), and untargeted metabolomics coupled with pattern recognition approaches were performed to profile and extract metabolite signatures. A total of 553 metabolites were uniquely discovered in patients with ascites, of which 136 metabolites had been annotated in the human metabolome database. Principal component analysis (PCA) analysis was used to further identify 21 ascites-related fingerprints. The eigenmetabolite calculated by reducing the dimensions of the 21 metabolites could be used to effectively identify those ALD patients with or without ascites. The eigenmetabolite showed a decreasing trend during ascites production and accumulation and was negatively related to the disease progress. These metabolic fingerprints mainly belong to the metabolites in lipid metabolism and the amino acid pathway. The results imply that lipid and amino acid metabolism disturbance may play a critical role in the development of ascites in ALD patients and could be a potent prognosis marker.