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

eGastroenterology Pub Date : 2025-08-24 eCollection Date: 2025-01-01 DOI:10.1136/egastro-2025-100204
Marta Borges-Canha, Javier Centelles-Lodeiro, Ana Rita Leite, Joana Chaves, Inês Mariana Lourenço, Madalena Von-Hafe, Catarina Vale, Diana Martins, Cláudia Silva, António Carlos Ferreira, Gwen Falony, Rodrigo Liberal, Mariana Fragão-Marques, António Barros, Isabel Miranda, Adelino Leite-Moreira, Pedro Pimentel-Nunes, Sara Vieira-Silva, João Sérgio Neves
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Abstract

Background: 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.

Abstract Image

Abstract Image

肠道生态失调与严重的脂肪变性有关,并增强了其在MASLD中的诊断性能。
背景:代谢功能障碍相关脂肪变性肝病(MASLD)是全球慢性肝病的主要原因,与代谢综合征(MetS)相关的患病率不断上升。过多的肝脏脂肪堆积(脂肪变性)恶化疾病进展和MASLD的预后。此外,肠道菌群失调可能促进脂肪变性,加速疾病进展到严重阶段。识别特定于脂肪变性严重程度的肠道微生物群特征可能会改善其诊断,并为MASLD的个性化干预提供信息。本研究旨在确定MASLD/MetS患者队列中肠道微生物群组成与肝脏脂肪变性严重程度之间的关系。最终,我们的目的是评估微生物群特征的潜力,以提高严重脂肪变性的诊断。方法:在MASLD的不同阶段招募了61例具有广泛临床病史的MetS患者的横断面队列。瞬时弹性成像用于评估肝纤维化和脂肪变性的严重程度。使用16S rRNA基因测序对参与者的粪便微生物群进行分析。统计分析首先确定了微生物群特征与患者表型之间的相关性,同时解开了药物等重要混杂因素。确定的特征然后用于建立诊断严重脂肪变性的预测模型。结果:高脂肪变性严重程度明显与炎症相关的2型拟杆菌(Bact2)-肠型的较高患病率相关,并伴有较低比例的有益共生菌(如Akkermansia)和较高比例的机会性细菌(如链球菌)。携带bact2肠型的患者在较低的脂肪肝指数(FLI)阈值时达到严重的脂肪变性。与单独使用FLI相比,在预测模型中使用bact2载体状态和FLI可显著提高严重脂肪变性的分类(准确率90%,接受者工作特征96%)。结论:肠道菌群组成和生态失调(定义为Bact2-enterotype)与MASLD/MetS的脂肪变性严重程度明显相关。微生物群组成的患者分层增强了MASLD中严重脂肪变性的诊断分类,表明对微生物群失调患者进行个性化干预的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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