Bile Acids as Metabolic Regulators and Nutrient Sensors

Chiang, John Y.L.; Ferrell, Jessica M.

doi:10.1146/annurev-nutr-082018-124344

Cited by 270 publications

(269 citation statements)

References 149 publications

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“…After meal intake, bile acids are released into the gastrointestinal tract to aid in absorption of nutrients, dietary fats, steroids, vitamins, and drugs. Recent advances in basic research have identified bile acids as nutrient sensors and metabolic integrators that activate farnesoid X receptor (FXR) and Takeda G protein‐coupled receptor 5 (TGR5) to regulate lipid, glucose, and energy metabolism, and maintain metabolic homeostasis . This review will briefly cover bile acid physiology and synthesis, pathophysiology of cholestatic liver diseases and nonalcoholic fatty liver disease (NAFLD), and bile acid–based therapy for liver‐related diseases.…”

Section: Cholestatic Liver Diseasesmentioning

confidence: 99%

“…Activation of TGR5 by secondary bile acids in enteroendocrine cells stimulates secretion of glucagon‐like peptide 1 (GLP‐1), which promotes insulin secretion in the pancreas to improve insulin sensitivity. TGR5 signaling also promotes adipose tissue browning and energy metabolism to reduce weight …”

Section: Cholestatic Liver Diseasesmentioning

confidence: 99%

“…In inborn errors of bile acid synthesis, accumulation of toxic bile acid intermediates cause neonatal cholestasis, fibrosis, and hepatitis . Obstruction of bile flow by stones, tumors, or inflammation of the intrahepatic small bile duct or extrahepatic common bile duct increases toxic bile acids and intermediates in the liver, leading to cholestatic liver injury and fibrosis.…”

Section: Cholestatic Liver Diseasesmentioning

confidence: 99%

“…TGR5 signaling also promotes adipose tissue browning and energy metabolism to reduce weight. 1 The global epidemic of obesity and type 2 diabetes (T2D) has contributed to the increased prevalence of NAFLD, which is about 25% of the adult population in the world. NAFLD is a spectrum of chronic liver diseases ranging from simple steatosis to nonalcoholic steatohepatitis (NASH) fibrosis and cirrhosis.…”

Section: An Official Learning Resource Of Aasldmentioning

confidence: 99%

“…5 In inborn errors of bile acid synthesis, accumulation of toxic bile acid intermediates cause neonatal cholestasis, fibrosis, and hepatitis. 1 Obstruction of bile flow by stones, tumors, or inflammation of the intrahepatic small bile duct or extrahepatic common bile duct increases toxic bile acids and intermediates in the liver, leading to cholestatic liver injury and fibrosis. Progressive familial intrahepatic cholestasis (PFIC) is a collection of cholestatic liver diseases Intestinal FXR induces FGF19, which circulates to the liver and binds to hepatic FGFR4, inhibiting bile acid synthesis.…”

Section: An Official Learning Resource Of Aasldmentioning

confidence: 99%

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Bile Acid Biology, Pathophysiology, and Therapeutics

Chiang

Ferrell

2020

Clinical Liver Disease

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Section: Cholestatic Liver Diseasesmentioning

confidence: 99%

Section: Cholestatic Liver Diseasesmentioning

confidence: 99%

Section: Cholestatic Liver Diseasesmentioning

confidence: 99%

Section: An Official Learning Resource Of Aasldmentioning

confidence: 99%

Section: An Official Learning Resource Of Aasldmentioning

confidence: 99%

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Bile Acid Biology, Pathophysiology, and Therapeutics

Chiang

Ferrell

2020

Clinical Liver Disease

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Metabolomics and Machine Learning Identify Metabolic Differences and Potential Biomarkers for Frequent Versus Infrequent Gout Flares

Wang

et al. 2023

Arthritis & Rheumatology

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ObjectivesTo discover differential metabolites and pathways underlying infrequent gout flares (InGF) and frequent gout flares (FrGF) using metabolomics and establish a predictive model by machine learning (ML) algorithms.MethodsSerum samples from a discovery cohort with 163 InGF and 239 FrGF patients were analyzed by mass spectrometry‐based untargeted metabolomics to profile differential metabolites and explore dysregulated metabolic pathways using pathway enrichment analysis and network propagation‐based algorithms. ML algorithms were performed to establish a predictive model based on selected metabolites, which was further optimized by a quantitative targeted metabolomics method and validated in an independent validation cohort with 97 participants with InGF and 139 participants with FrGF.Results439 differential metabolites between InGF and FrGF groups were identified. Top dysregulated pathways included carbohydrates, amino acids, bile acids, and nucleotide metabolism. Subnetworks with maximum disturbances in the global metabolic networks featured cross‐talk between purine metabolism and caffeine metabolism, as well as interactions among pathways involving primary bile acid biosynthesis, taurine and hypotaurine metabolism, alanine, aspartate and glutamate metabolism, suggesting epigenetic modifications and gut microbiome in metabolic alterations underlying InGF and FrGF. Potential metabolite biomarkers were identified using ML‐based multivariable selection and further validated by targeted metabolomics. Area under receiver operating characteristics curve for differentiating InGF and FrGF achieved 0.88 and 0.67 for the discovery and validation cohorts, respectively.ConclusionsSystematic metabolic alterations underlie InGF and FrGF, and distinct profiles are associated with differences in gout flare frequencies. Predictive modeling based on selected metabolites from metabolomics can differentiate InGF and FrGF.

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Emerging trends and hotspots in the links between the bile acids and NAFLD from 2002 to 2022: A bibliometric analysis

Shibo,

Sili,

Yanfang

et al. 2023

Endocrino Diabet & Metabol

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BackgroundNon‐alcoholic fatty liver disease (NAFLD) is a metabolic syndrome of the liver, and its incidence is increasing worldwide. Accumulating evidence suggests that bile acids are associated with NAFLD. Although many studies on bile acids and NAFLD have been published over the past 20 years, the authors of this study have not found a relevant bibliometric analysis in this field. Therefore, this study aimed to evaluate the trend of publications, summarize current research hotspots and predict future research directions through bibliometric analysis in this field.MethodArticles related to bile acids and NAFLD published between 2002 and 2022 were obtained from the Science Citation Index‐Expanded of Web of Science Core Collection. Microsoft Excel, CiteSpace, VOSviewer and Bibliometric Online Analysis Platform were used to analyse the publication trends and research hotspots in this field.ResultsAmong the articles published between 2002 and 2022, we retrieved 1284 articles related to bile acids and NAFLD, and finally included 568 articles. The USA was dominant until 2020, after which China surpassed the USA to become the dominant force. These two countries cooperate the most closely, and are also the most active in international cooperation. The University of California (UCL) was the most published institution, with a total of 31 publications. There were six authors who have published nine articles and ranked first. The keywords cluster labels show the 10 main clusters: #0fatty liver, #1obeticholic acid, #2oxidative stress, #37 alpha hydroxy 4 cholesten 3 one, #4deoxycholic acid, #5nonalcoholic fatty liver disease, #6mouse model, #7fibroblast growth factor 21, #8animal models, #9high‐fat diet. Keywords burst analysis revealed a higher intensity of study for the nuclear receptor, FXR, and metabolic syndrome.ConclusionBile acids have become an important research direction in the field of NAFLD, and the intervention of gut microbiota in NAFLD by acting on bile acids may become a potential hotspot for future research. This study provides reference and guidance for future research, and will help scholars better explore the field and innovatively discover the mechanisms and treatments of NAFLD.

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Bile Acids as Metabolic Regulators and Nutrient Sensors

Cited by 270 publications

References 149 publications

Bile Acid Biology, Pathophysiology, and Therapeutics

Bile Acid Biology, Pathophysiology, and Therapeutics

Metabolomics and Machine Learning Identify Metabolic Differences and Potential Biomarkers for Frequent Versus Infrequent Gout Flares

Emerging trends and hotspots in the links between the bile acids and NAFLD from 2002 to 2022: A bibliometric analysis

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