Microbial Consortia-Immunoglobulin G Glycosylation Combination Scores Identify Severe Hepatic Steatosis and Significant Fibrosis in Patients with Metabolic Dysfunction-Associated Steatotic Liver Disease
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Le résumé fourni par la source
INTRODUCTION: Severe hepatic steatosis (HS) and significant hepatic fibrosis indicate severity of metabolic dysfunction-associated steatotic liver disease (MASLD), and the models for early detection are important. Recent studies suggest immunoglobulin G (IgG) glycosylation and microbial consortia may involve in the development of MASLD. This study investigates the utility of IgG glycosylation and microbial consortia in early detection models. METHODS: A total of 111 patients with MASLD categorized into high vs low controlled attenuation parameter (for HS) or high vs low FIB-4 (for fibrosis). We analyzed differences in microbial consortia and IgG1/IgG2 glycosylation features, creating scores for identifying severe HS and significant hepatic fibrosis. The combination scores for identifying severe HS and significant hepatic fibrosis in MASLD patients were derived based on the microbial consortia and IgG1/IgG2 glycosylation features accordingly. RESULTS: Megamonas was linked to severe HS, and Christensenellaceae R-7 , UCG-005 , CAG-56 , and Lachnospira were associated with significant hepatic fibrosis in patients with MASLD. The areas under curve of severe HS- and significant hepatic fibrosis-microbial scores were 0.731 and 0.773, respectively. The ratios of IgG2-N4H5F1/IgG1-N4H5F1 and bisected-IgG2/bisected-IgG1 predicted severe HS, while IgG2-N4H3F1/IgG1-N4H3F1, bisected-IgG1/bisected-IgG2, and IgG1-galactosylation/IgG2-galactosylation index identified significant hepatic fibrosis in MASLD. The combination scores including microbial consortia and glycosylation features achieved areas under curve of 0.776 and 0.810, showing comparable performance with established indices like HS index and FibroAST score. DISCUSSION: The study highlights the effectiveness of combining fecal microbiota and serum IgG glycosylation features in identifying MASLD severity, which are noninferior to the current regularly used models, and suggests the intervention of glycosylation as a promising therapeutic approach for MASLD.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Microbial Consortia-Immunoglobulin G Glycosylation Combination Scores Identify Severe Hepatic Steatosis and Significant Fibrosis in Patients with Metabolic Dysfunction-Associated Steatotic Liver Disease
- Date Crossref
- 24/11/2025
- Éditeur
- Ovid Technologies (Wolters Kluwer Health)
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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Fu Jen Catholic University pays non établi dans la noticeUniversité ou école supérieure
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National Yang Ming Chiao Tung University Institute of Clinical Medicine pays non établi dans la noticeUniversité ou école supérieure
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Memorial Hospital Department of Internal Medicine pays non établi dans la noticeÉtablissement de santé
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Taipei Veterans General Hospital Department of Medical Education pays non établi dans la noticeÉtablissement de santé
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National Cheng Kung University pays non établi dans la noticeUniversité ou école supérieure
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Genomics Research Center pays non établi dans la noticeStructure de recherche
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Taipei City Hospital pays non établi dans la noticeÉtablissement de santé
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School of Medicine pays non établi dans la noticeUniversité ou école supérieure
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College of Medicine Department of Medical Laboratory Science and Biotechnology pays non établi dans la noticeUniversité ou école supérieure
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Taipei Veteran General Hospital Department of Internal Medicine pays non établi dans la noticeÉtablissement de santé
Fu Jen Catholic University, Institute of Clinical Medicine — National Yang Ming Chiao Tung University et Department of Internal Medicine — Memorial Hospital, avec 7 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.