Zöggeler Thomas, Kavallar Anna Maria, Pollio Adam Robert, Aldrian Denise, Decristoforo Cornelia, Scholl-Bürgi Sabine, Müller Thomas, Vogel Georg Friedrich
Department of Paediatrics I, Medical University of Innsbruck, Innsbruck, Austria.
Institute of Cell Biology, Medical University of Innsbruck, Innsbruck, Austria.
Gut Microbes. 2025 Dec;17(1):2508951. doi: 10.1080/19490976.2025.2508951. Epub 2025 May 21.
Alterations in the gut microbiome affect the development and severity of metabolic dysfunction-associated steatotic liver disease (MASLD) or metabolic dysfunction-associated steatohepatitis (MASH). We analyzed microbiomes of obese children with and without MASLD, MASH, and healthy controls. Electronic databases were searched for studies on the gut microbiome in children with obesity with/without MASLD or MASH, providing shotgun-metagenomic-sequencing data. Nine studies and an additionally recruited cohort were included. Fecal microbiomes of children with MASLD ( = 153) and MASH ( = 70) were significantly different in alpha- and beta-diversity ( < 0.001) compared to obese ( = 58) and healthy ( = 132). Species and are differentially abundant between obese, MASLD and MASH groups. XGBoost and random forest-models accurately predict MASLD over obesity with an AUROC of 87% and MASH over MASLD with 89%. Pathway-abundance-based models accurately predict MASLD over obesity with an AUROC of 81% and MASH over MASLD with 88%. The composition of the gut microbiome is altered with increasing hepatic fibrosis and concomitant species-abundance increase of ( = 0.0082). Machine-learning models discriminate pediatric from adult MASH with an AUROC of 97%. The gut microbial composition is increasingly altered in children with the progression of MASLD toward MASH. This can be utilized as a fecal biomarker and highlights the impact of diet on the gut microbiome for disease intervention.
肠道微生物群的改变会影响代谢功能障碍相关脂肪性肝病(MASLD)或代谢功能障碍相关脂肪性肝炎(MASH)的发生发展及严重程度。我们分析了患有和未患有MASLD、MASH的肥胖儿童以及健康对照的微生物群。通过电子数据库搜索了有关患有/未患有MASLD或MASH的肥胖儿童肠道微生物群的研究,并提供鸟枪法宏基因组测序数据。纳入了9项研究和一个额外招募的队列。与肥胖儿童(n = 58)和健康儿童(n = 132)相比,患有MASLD(n = 153)和MASH(n = 70)的儿童粪便微生物群在α-多样性和β-多样性方面存在显著差异(P < 0.001)。在肥胖、MASLD和MASH组之间,物种[具体物种1]和[具体物种2]的丰度存在差异。XGBoost和随机森林模型能够准确预测MASLD与肥胖,曲线下面积(AUROC)为87%,预测MASH与MASLD的AUROC为89%。基于通路丰度的模型能够准确预测MASLD与肥胖,AUROC为81%,预测MASH与MASLD的AUROC为88%。随着肝纤维化的增加以及[具体物种]物种丰度的增加(P = 0.0082),肠道微生物群的组成发生改变。机器学习模型区分儿童和成人MASH的AUROC为97%。随着MASLD向MASH进展,儿童肠道微生物组成的改变越来越明显。这可作为粪便生物标志物,并突出了饮食对肠道微生物群在疾病干预方面的影响。