Gut dysbiosis is linked to severe steatosis and enhances its diagnostic performance in MASLD

dc.contributor.authorBorges-Canha, Marta
dc.contributor.authorCentelles-Lodeiro, Javier
dc.contributor.authorLeite, Ana Rita
dc.contributor.authorChaves, Joana
dc.contributor.authorLourenço, Inês Mariana
dc.contributor.authorVon-Hafe, Madalena
dc.contributor.authorVale, Catarina
dc.contributor.authorMartins, Diana
dc.contributor.authorSilva, Cláudia
dc.contributor.authorFerreira, António Carlos
dc.contributor.authorFalony, Gwen
dc.contributor.authorLiberal, Rodrigo
dc.contributor.authorFragão-Marques, Mariana
dc.contributor.authorBarros, António
dc.contributor.authorMiranda, Isabel
dc.contributor.authorLeite-Moreira, Adelino
dc.contributor.authorPimentel- Nunes, Pedro
dc.contributor.authorVieira-Silva, Sara
dc.contributor.authorNeves, João Sérgio
dc.date.accessioned2025-12-18T10:59:23Z
dc.date.issued2025
dc.description.abstractBackground Metabolic dysfunction-associated steatotic liver disease (MASLD) is the leading cause of chronic liver disease globally, with rising prevalence linked to metabolic syndrome (MetS). Excessive liver fat accumulation (steatosis) worsens disease progression and MASLD prognosis. Moreover, gut microbiota dysbiosis might promote steatosis, accelerating the disease progression to severe stages. Identifying gut microbiota signatures specific to steatosis severity might improve its diagnosis and inform personalised interventions in MASLD. This study aimed to characterise associations between gut microbiota composition and hepatic steatosis severity in a cohort of patients with MASLD/MetS. Ultimately, we aimed to assess the potential for microbiota features to enhance the diagnosis of severe steatosis. Methods A cross-sectional cohort of 61 patients with MetS with extensive clinical history was recruited at different stages of MASLD. Transient elastography was used to evaluate liver fibrosis and steatosis severity. Participants’ faecal microbiota were profiled using 16S rRNA gene sequencing. Statistical analyses first identified correlations between microbiota profiles and patients’ phenotypes, while disentangling important confounders such as medication. Identified features were then used to build predictive models for diagnosing severe steatosis. Results High steatosis severity was distinctly associated with a higher prevalence of the inflammation-associated Bacteroides 2 (Bact2)-enterotype, accompanied by a lower proportion of beneficial commensals (eg, Akkermansia) and a higher proportion of opportunistic bacteria (eg, Streptococcus). Patients harbouring a Bact2-enterotype reached severe steatosis at lower Fatty Liver Index (FLI) thresholds. Using Bact2-carrier status together with FLI in a predictive model significantly improved the classification of severe steatosis (accuracy 90%, receiver operating characteristics 96%) when compared with FLI alone. Conclusion Gut microbiota composition and dysbiosis (defined as Bact2-enterotype) are distinctly associated with steatosis severity in MASLD/MetS. Patient stratification by microbiota composition enhances the diagnostic classification of severe steatosis in MASLD, suggesting a potential for personalised interventions in patients with microbiota dysbiosis.en
dc.identifier.doihttps://doi.org/10.25358/openscience-13953
dc.identifier.urihttps://openscience.ub.uni-mainz.de/handle/20.500.12030/13974
dc.language.isoeng
dc.rightsCC-BY-NC-4.0
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/
dc.subject.ddc610 Medizinde
dc.subject.ddc610 Medical sciencesen
dc.titleGut dysbiosis is linked to severe steatosis and enhances its diagnostic performance in MASLDen
dc.typeZeitschriftenaufsatz
jgu.identifier.uuid87028f84-0ec0-4927-b547-cb3e5f170b20
jgu.journal.titleeGastroenterology
jgu.journal.volume3
jgu.organisation.departmentFB 04 Medizin
jgu.organisation.nameJohannes Gutenberg-Universität Mainz
jgu.organisation.number2700
jgu.organisation.placeMainz
jgu.organisation.rorhttps://ror.org/023b0x485
jgu.pages.alternativee100204
jgu.publisher.doi10.1136/egastro-2025-100204
jgu.publisher.eissn2976-7296
jgu.publisher.nameBMJ
jgu.publisher.placeLondon
jgu.publisher.year2025
jgu.rights.accessrightsopenAccess
jgu.subject.ddccode610
jgu.subject.dfgLebenswissenschaften
jgu.type.dinitypeArticleen_GB
jgu.type.resourceText
jgu.type.versionPublished version

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