ArticleFrontiers in microbiology2022
Integrative analysis of gut microbiota and fecal metabolites in metabolic associated fatty liver disease patients.
Article in Frontiers in microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.
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Who cites it
18 citing papers in PubMed, 2 syntheses or guidelines pooled it, 22 citations in OpenAlex.
- Frontiers and emerging trends in research on metabolic syndrome and metabolic dysfunction-associated fatty liver disease: a bibliometric analysis (2005-2024).Frontiers in endocrinology · 2026Pooled it
- Pooled it
- Article
- Association between the subcellular localization of host proteins and gut microbiome and metabolome in metabolic dysfunction-associated steatotic liver disease: a pilot study.Frontiers in molecular biosciences · 2026Article
- Targeting the gut microbiota: the application and prospects of probiotics, fecal microbiota transplantation, and natural products in MASLD.Frontiers in nutrition · 2026Review
- Review
- Exploring the interplay between metabolic dysfunction-associated fatty liver disease and gut dysbiosis: Pathophysiology, clinical implications, and emerging therapies.World journal of hepatology · 2025Review
- Gut microbiota in non-alcoholic fatty liver disease: Pathophysiology, diagnosis, and therapeutics.World journal of hepatology · 2025Review
- Gut microbiota differences, metabolite changes, and disease intervention during metabolic - dysfunction - related fatty liver progression.World journal of hepatology · 2025Review
- The oral-gut microbiota axis: a link in cardiometabolic diseases.NPJ biofilms and microbiomes · 2025Review
- "Trust your gut": exploring the connection between gut microbiome dysbiosis and the advancement of Metabolic Associated Steatosis Liver Disease (MASLD)/Metabolic Associated Steatohepatitis (MASH): a systematic review of animal and human studies.Frontiers in nutrition · 2025Review
- Effect of Toxocara canis infection on liver and lung microbial flora diversity and composition in dogs.Parasite (Paris, France) · 2025Article
- Network Pharmacology and Experimental Validation of the Effects of Shenling Baizhu San, Quzhi Ruangan Fang and Gexia Zhuyu Tang on the Intestinal Flora of Rats with NAFLD.Diabetes, metabolic syndrome and obesity : targets and therapy · 2025Article
- Integrated analysis of fecal microbiota and metabolomics reveals unique characteristics of asymptomatic and classic celiac disease.Frontiers in microbiology · 2025Article
- Ampelopsis grossedentata tea alleviating liver fibrosis in BDL-induced mice via gut microbiota and metabolite modulation.NPJ science of food · 2024Article
- Application of intelligent tongue image analysis in Conjunction with microbiomes in the diagnosis of MAFLD.Heliyon · 2024Article
- Metabolic-Dysfunction-Associated Fatty Liver Disease and Gut Microbiota: From Fatty Liver to Dysmetabolic Syndrome.Medicina (Kaunas, Lithuania) · 2023Review
- Hepatic Mitochondria-Gut Microbiota Interactions in Metabolism-Associated Fatty Liver Disease.Metabolites · 2023Review
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Metabolic associated fatty liver disease (MAFLD) affects nearly a quarter of the world's population. Our study aimed to characterize the gut microbiome and overall changes in the fecal and serum metabolomes in MAFLD patients. Methods: Thirty-two patients diagnosed with MAFLD and 30 healthy individuals (control group, CG) were included in this study, the basic clinical characteristics and laboratory test results including routine biochemistry, etc. were recorded for all, and their serum and fecal samples were collected. A portion of the fecal samples was subjected to 16S rDNA sequencing, and the other portion of the fecal samples and serum samples were subjected to non-targeted metabolomic detection based on liquid chromatography-mass spectrometry (LC-MS). Statistical analysis of clinical data was performed using SPSS software package version 25.0 (SPSS Inc., Chicago, IL, United States). The analysis of 16S rDNA sequencing results was mainly performed by R software (V. 2.15.3), and the metabolomics data analysis was mainly performed by CD 3.1 software. Two-tailed Results: The 16S sequencing data suggested that the species richness and diversity of MAFLD patients were reduced compared with controls. At the phylum level, the relative abundance of Conclusion: Microbial sequencing data suggested decreased species richness and diversity and altered β-diversity in feces. Metabolomic analysis identified overall changes in fecal and serum metabolites dominated by lipid molecules. And the association analysis with gut microbes provided potentially pivotal gut microbiota-metabolite combinations in MAFLD patients, which might provide new clues for further research on the disease mechanism and the development of new diagnostic markers and treatments.
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