Diagnosis in bile acid-CoA: Amino acid N-acyltransferase deficiency

Apigenin Ameliorates Dyslipidemia, Hepatic Steatosis and Insulin Resistance by Modulating Metabolic and Transcriptional Profiles in the Liver of High-Fat Diet-Induced Obese Mice

Several in vitro and in vivo studies have reported the anti-inflammatory, anti-diabetic and anti-obesity effects of the flavonoid apigenin. However, the long-term supplementary effects of low-dose apigenin on obesity are unclear. Therefore, we investigated the protective effects of apigenin against obesity and related metabolic disturbances by exploring the metabolic and transcriptional responses in high-fat diet (HFD)-induced obese mice. C57BL/6J mice were fed an HFD or apigenin (0.005%, w/w)-supplemented HFD for 16 weeks. In HFD-fed mice, apigenin lowered plasma levels of free fatty acid, total cholesterol, apolipoprotein B and hepatic dysfunction markers and ameliorated hepatic steatosis and hepatomegaly, without altering food intake and adiposity. These effects were partly attributed to upregulated expression of genes regulating fatty acid oxidation, tricarboxylic acid cycle, oxidative phosphorylation, electron transport chain and cholesterol homeostasis, downregulated expression of lipolytic and lipogenic genes and decreased activities of enzymes responsible for triglyceride and cholesterol ester synthesis in the liver. Moreover, apigenin lowered plasma levels of pro-inflammatory mediators and fasting blood glucose. The anti-hyperglycemic effect of apigenin appeared to be related to decreased insulin resistance, hyperinsulinemia and hepatic gluconeogenic enzymes activities. Thus, apigenin can ameliorate HFD-induced comorbidities via metabolic and transcriptional modulations in the liver.

Adult bile acid amino transferase deficiency

Patient: Female, 70

Final Diagnosis: Bile acid amino transferase deficiency

Symptoms: Headache • indigestion • itching skin • nausea • vomiting

Medication: —

Clinical Procedure: —

Specialty: Gastroenterology and Hepatology

Determining molecular predictors of adverse drug reactions with causality analysis based on structure learning

OBJECTIVE

Adverse drug reaction (ADR) can have dire consequences. However, our current understanding of the causes of drug-induced toxicity is still limited. Hence it is of paramount importance to determine molecular factors of adverse drug responses so that safer therapies can be designed.

METHODS

We propose a causality analysis model based on structure learning (CASTLE) for identifying factors that contribute significantly to ADRs from an integration of chemical and biological properties of drugs. This study aims to address two major limitations of the existing ADR prediction studies. First, ADR prediction is mostly performed by assessing the correlations between the input features and ADRs, and the identified associations may not indicate causal relations. Second, most predictive models lack biological interpretability.

RESULTS

CASTLE was evaluated in terms of prediction accuracy on 12 organ-specific ADRs using 830 approved drugs. The prediction was carried out by first extracting causal features with structure learning and then applying them to a support vector machine (SVM) for classification. Through rigorous experimental analyses, we observed significant increases in both macro and micro F1 scores compared with the traditional SVM classifier, from 0.88 to 0.89 and 0.74 to 0.81, respectively. Most importantly, identified links between the biological factors and organ-specific drug toxicities were partially supported by evidence in Online Mendelian Inheritance in Man.

CONCLUSIONS

The proposed CASTLE model not only performed better in prediction than the baseline SVM but also produced more interpretable results (ie, biological factors responsible for ADRs), which is critical to discovering molecular activators of ADRs.

Treatment of mouse liver slices with cholestatic hepatotoxicants results in down-regulation of Fxr and its target genes

BACKGROUND

Unexpected cholestasis substantially contributes to drug failure in clinical trials. Current models used for safety assessment in drug development do not accurately predict cholestasis in humans. Therefore, it is of relevance to develop new screening models that allow identifying drugs with cholestatic properties.

METHODS

We employed mouse precision cut liver slices (PCLS), which were incubated 24 h with two model cholestatic compounds: cyclosporin A (CsA) and chlorpromazine (CPZ). Subsequently, transcriptome analysis using DNA microarrays and q-PCR were performed to identify relevant biological processes and biomarkers. Additionally, histology was carried out and levels of triglycerides (TG) and bile acids (BA) were measured. To verify the ex vivo mouse data, these were compared with publically available human data relevant for cholestasis.

RESULTS

Whole genome gene expression analysis showed that CsA up-regulated pathways related to NF-κB, ER stress and inflammation. Both CsA and CPZ down-regulated processes related to extracellular matrix (ECM) remodelling, BA homeostasis, Fxr signalling, and energy metabolism. The differential expression of a number of characteristic genes (e.g. Abcg5, Abcg8, Klf15, and Baat) could be confirmed by q-PCR. Histology revealed that CsA but not CPZ induced "ballooning" of hepatocytes. No effects on TG and BA levels were observed after incubation of PCLS with CsA and CPZ. A substantial number of processes altered in CsA- and CPZ-treated mouse PCLS ex vivo was also found to be affected in liver biopsies of cholestatic patients.

CONCLUSION

The present study demonstrated that mouse PCLS can be used as a tool to identify mechanisms of action of cholestatic model compounds. The induction of general stress responses and down-regulated Fxr signalling could play a role in the development of drug induced cholestasis. Importantly, comparative data analysis showed that the ex vivo mouse findings are also relevant for human pathology. Moreover, this work provides a set of genes that are potentially useful to assess drugs for cholestatic properties.

Genetic defects in bile acid conjugation cause fat-soluble vitamin deficiency

BACKGROUND & AIMS

The final step in bile acid synthesis involves conjugation with glycine and taurine, which promotes a high intraluminal micellar concentration to facilitate lipid absorption. We investigated the clinical, biochemical, molecular, and morphologic features of a genetic defect in bile acid conjugation in 10 pediatric patients with fat-soluble vitamin deficiency, some with growth failure or transient neonatal cholestatic hepatitis.

METHODS

We identified the genetic defect that causes this disorder using mass spectrometry analysis of urine, bile, and serum samples and sequence analysis of the genes encoding bile acid-CoA:amino acid N-acyltransferase (BAAT) and bile acid-CoA ligase (SLC27A5).

RESULTS

Levels of urinary bile acids were increased (432 ± 248 μmol/L) and predominantly excreted in unconjugated forms (79.4% ± 3.9%) and as sulfates and glucuronides. Glycine or taurine conjugates were absent in the urine, bile, and serum. Unconjugated bile acids accounted for 95.7% ± 5.8% of the bile acids in duodenal bile, with cholic acid accounting for 82.4% ± 5.5% of the total. Duodenal bile acid concentrations were 12.1 ± 5.9 mmol/L, which is too low for efficient lipid absorption. The biochemical profile was consistent with defective bile acid amidation. Molecular analysis of BAAT confirmed 4 different homozygous mutations in 8 patients tested.

CONCLUSIONS

Based on a study of 10 pediatric patients, genetic defects that disrupt bile acid amidation cause fat-soluble vitamin deficiency and growth failure, indicating the importance of bile acid conjugation in lipid absorption. Some patients developed liver disease with features of a cholangiopathy. These findings indicate that patients with idiopathic neonatal cholestasis or later onset of unexplained fat-soluble vitamin deficiency should be screened for defects in bile acid conjugation.