Noninvasive biomarkers implicated in urea and TCA cycles for metabolic liver disease
Abstract Bile acid (BA) and its receptor FXR play crucial roles in metabolism, and dysregulated BA synthesis regulated by hepatic and bacterial enzymes causes metabolic dysfunction-associated steatohepatitis (MASH) and hepatocellular carcinoma (HCC). Moreover, because ~ 75% of hepatic blood is from...
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BMC
2024-11-01
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| Series: | Biomarker Research |
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| Online Access: | https://doi.org/10.1186/s40364-024-00694-7 |
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| author | Guiyan Yang Yu-Jui Yvonne Wan |
| author_facet | Guiyan Yang Yu-Jui Yvonne Wan |
| author_sort | Guiyan Yang |
| collection | DOAJ |
| description | Abstract Bile acid (BA) and its receptor FXR play crucial roles in metabolism, and dysregulated BA synthesis regulated by hepatic and bacterial enzymes causes metabolic dysfunction-associated steatohepatitis (MASH) and hepatocellular carcinoma (HCC). Moreover, because ~ 75% of hepatic blood is from the gut, liver metabolism is influenced by intestinal bacteria and their metabolites. Thus, we used gut microbiota and metabolites from the urine and serum to uncover biomarkers for metabolic distress caused by Western diet (WD) intake, aging, and FXR inactivity. Hepatic transcriptomes were profiled to define liver phenotypes. There were 654 transcriptomes commonly altered by differential diet intake, ages, and FXR functional status, representing the signatures of liver dysfunction, and 76 of them were differentially expressed in healthy human livers and HCC. Machine learning approaches classified urine and serum metabolites for differential dietary intake and age difference. Additionally, the gut microbiota could predict FXR functional status. Furthermore, FXR was essential for differentiating dietary effects in colonizing age-related gut microbes. The integrated analysis established the relationships between the metabolites and gut microbiota correlated with hepatic transcripts commonly altered by diet, age, and FXR functionality. Remarkably, the changes in metabolites involved in the urea cycle, mitochondrial metabolism, and amino acid metabolism are associated with hepatic dysfunction (i.e. FXF deactivation). Taken together, noninvasive specimens and biomarkers are promising resources for identifying metabolic distress. |
| format | Article |
| id | doaj-art-e0dcee7a599d43a9992c272b2b6fb4c3 |
| institution | Kabale University |
| issn | 2050-7771 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | BMC |
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| series | Biomarker Research |
| spelling | doaj-art-e0dcee7a599d43a9992c272b2b6fb4c32024-11-24T12:37:06ZengBMCBiomarker Research2050-77712024-11-011211710.1186/s40364-024-00694-7Noninvasive biomarkers implicated in urea and TCA cycles for metabolic liver diseaseGuiyan Yang0Yu-Jui Yvonne Wan1College of Veterinary Medicine, China Agricultural UniversityDepartment of Pathology and Laboratory Medicine, University of California, DavisAbstract Bile acid (BA) and its receptor FXR play crucial roles in metabolism, and dysregulated BA synthesis regulated by hepatic and bacterial enzymes causes metabolic dysfunction-associated steatohepatitis (MASH) and hepatocellular carcinoma (HCC). Moreover, because ~ 75% of hepatic blood is from the gut, liver metabolism is influenced by intestinal bacteria and their metabolites. Thus, we used gut microbiota and metabolites from the urine and serum to uncover biomarkers for metabolic distress caused by Western diet (WD) intake, aging, and FXR inactivity. Hepatic transcriptomes were profiled to define liver phenotypes. There were 654 transcriptomes commonly altered by differential diet intake, ages, and FXR functional status, representing the signatures of liver dysfunction, and 76 of them were differentially expressed in healthy human livers and HCC. Machine learning approaches classified urine and serum metabolites for differential dietary intake and age difference. Additionally, the gut microbiota could predict FXR functional status. Furthermore, FXR was essential for differentiating dietary effects in colonizing age-related gut microbes. The integrated analysis established the relationships between the metabolites and gut microbiota correlated with hepatic transcripts commonly altered by diet, age, and FXR functionality. Remarkably, the changes in metabolites involved in the urea cycle, mitochondrial metabolism, and amino acid metabolism are associated with hepatic dysfunction (i.e. FXF deactivation). Taken together, noninvasive specimens and biomarkers are promising resources for identifying metabolic distress.https://doi.org/10.1186/s40364-024-00694-7LiverMetabolic diseaseMachine learningBile acidFXRGut-liver axis |
| spellingShingle | Guiyan Yang Yu-Jui Yvonne Wan Noninvasive biomarkers implicated in urea and TCA cycles for metabolic liver disease Biomarker Research Liver Metabolic disease Machine learning Bile acid FXR Gut-liver axis |
| title | Noninvasive biomarkers implicated in urea and TCA cycles for metabolic liver disease |
| title_full | Noninvasive biomarkers implicated in urea and TCA cycles for metabolic liver disease |
| title_fullStr | Noninvasive biomarkers implicated in urea and TCA cycles for metabolic liver disease |
| title_full_unstemmed | Noninvasive biomarkers implicated in urea and TCA cycles for metabolic liver disease |
| title_short | Noninvasive biomarkers implicated in urea and TCA cycles for metabolic liver disease |
| title_sort | noninvasive biomarkers implicated in urea and tca cycles for metabolic liver disease |
| topic | Liver Metabolic disease Machine learning Bile acid FXR Gut-liver axis |
| url | https://doi.org/10.1186/s40364-024-00694-7 |
| work_keys_str_mv | AT guiyanyang noninvasivebiomarkersimplicatedinureaandtcacyclesformetabolicliverdisease AT yujuiyvonnewan noninvasivebiomarkersimplicatedinureaandtcacyclesformetabolicliverdisease |