小儿克罗恩病的肠道微生物特征因疾病活动度而异，并受胃肠道转运时间替代物的影响：ImageKids 研究。

IF 4.5 3区医学 Q1 GASTROENTEROLOGY & HEPATOLOGY

Inflammatory Bowel Diseases Pub Date : 2025-06-13 DOI:10.1093/ibd/izae199

Ben Nichols, Richard K Russell, Bryn Short, Rodanthi Papadopoulou, Gili Focht, Umer Z Ijaz, Thomas D Walters, Malgorzata Sladek, Richard Hansen, David R Mack, Eytan Wine, Anne M Griffiths, Dan Turner, Konstantinos Gerasimidis

{"title":"小儿克罗恩病的肠道微生物特征因疾病活动度而异，并受胃肠道转运时间替代物的影响：ImageKids 研究。","authors":"Ben Nichols, Richard K Russell, Bryn Short, Rodanthi Papadopoulou, Gili Focht, Umer Z Ijaz, Thomas D Walters, Malgorzata Sladek, Richard Hansen, David R Mack, Eytan Wine, Anne M Griffiths, Dan Turner, Konstantinos Gerasimidis","doi":"10.1093/ibd/izae199","DOIUrl":null,"url":null,"abstract":"Introduction: We investigated relationships between disease activity measures and the gut microbiome in children with Crohn's disease (CD) and how these were confounded by gastrointestinal transit time.Methods: Microbiome was profiled (16S rRNA sequencing) in feces from 196 children with CD. Sixty participants also provided samples after 18 months. Mural inflammation (Pediatric Inflammatory Crohn's Magnetic Resonance Enterography Index, PICMI), the simple endoscopic score for CD, and the weighted pediatric Crohn's disease activity index (wPCDAI) were assessed. Fecal calprotectin, plasma C-reactive protein (CRP), and fecal water content (FWC), a proxy of gastrointestinal transit time, were measured too.Results: Microbiome α diversity, clustering, and differential taxa were related to disease status, but varied remarkably by disease activity measure used. The strongest relationships between microbiome and disease activity status were observed using wPCDAI; fewer or no relationships were seen using more objective measures like PICMI. Taxa predictive of disease activity status were dependent on the disease activity measure used with negligible overlap. Active disease was associated with more pathobionts (eg, Viellonella, Enterobacterales) and fewer fiber-fermenting organisms. The effect FWC had on microbiome superseded the effect of active disease for all disease activity measures, particularly with wPCDAI. Accounting for FWC, the differences in microbial signatures explained by disease activity status were attenuated or lost.Conclusions: In CD, microbiome signatures fluctuate depending on the measure used to assess disease severity; several of these signals might be secondary disease effects linked with changes in gut motility in active disease. PICMI appears to be less influenced when studying relationships between microbiome and mural inflammation in CD.","PeriodicalId":13623,"journal":{"name":"Inflammatory Bowel Diseases","volume":" ","pages":"1616-1629"},"PeriodicalIF":4.5000,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12166297/pdf/","citationCount":"0","resultStr":"{\"title\":\"Gut Microbial Signatures in Pediatric Crohn's Disease Vary According to Disease Activity Measures and Are Influenced by Proxies of Gastrointestinal Transit Time: An ImageKids Study.\",\"authors\":\"Ben Nichols, Richard K Russell, Bryn Short, Rodanthi Papadopoulou, Gili Focht, Umer Z Ijaz, Thomas D Walters, Malgorzata Sladek, Richard Hansen, David R Mack, Eytan Wine, Anne M Griffiths, Dan Turner, Konstantinos Gerasimidis\",\"doi\":\"10.1093/ibd/izae199\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Introduction: We investigated relationships between disease activity measures and the gut microbiome in children with Crohn's disease (CD) and how these were confounded by gastrointestinal transit time.Methods: Microbiome was profiled (16S rRNA sequencing) in feces from 196 children with CD. Sixty participants also provided samples after 18 months. Mural inflammation (Pediatric Inflammatory Crohn's Magnetic Resonance Enterography Index, PICMI), the simple endoscopic score for CD, and the weighted pediatric Crohn's disease activity index (wPCDAI) were assessed. Fecal calprotectin, plasma C-reactive protein (CRP), and fecal water content (FWC), a proxy of gastrointestinal transit time, were measured too.Results: Microbiome α diversity, clustering, and differential taxa were related to disease status, but varied remarkably by disease activity measure used. The strongest relationships between microbiome and disease activity status were observed using wPCDAI; fewer or no relationships were seen using more objective measures like PICMI. Taxa predictive of disease activity status were dependent on the disease activity measure used with negligible overlap. Active disease was associated with more pathobionts (eg, Viellonella, Enterobacterales) and fewer fiber-fermenting organisms. The effect FWC had on microbiome superseded the effect of active disease for all disease activity measures, particularly with wPCDAI. Accounting for FWC, the differences in microbial signatures explained by disease activity status were attenuated or lost.Conclusions: In CD, microbiome signatures fluctuate depending on the measure used to assess disease severity; several of these signals might be secondary disease effects linked with changes in gut motility in active disease. PICMI appears to be less influenced when studying relationships between microbiome and mural inflammation in CD.\",\"PeriodicalId\":13623,\"journal\":{\"name\":\"Inflammatory Bowel Diseases\",\"volume\":\" \",\"pages\":\"1616-1629\"},\"PeriodicalIF\":4.5000,\"publicationDate\":\"2025-06-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12166297/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Inflammatory Bowel Diseases\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1093/ibd/izae199\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GASTROENTEROLOGY & HEPATOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Inflammatory Bowel Diseases","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/ibd/izae199","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GASTROENTEROLOGY & HEPATOLOGY","Score":null,"Total":0}

引用次数: 0

摘要

简介：我们研究了克罗恩病（CD）患儿的疾病活动指标与肠道微生物组之间的关系，以及这些关系如何受到胃肠道转运时间的影响：我们研究了克罗恩病（CD）患儿的疾病活动指标与肠道微生物组之间的关系，以及这些关系如何受到胃肠道转运时间的影响：对196名克罗恩病患儿粪便中的微生物组进行了分析（16S rRNA测序）。60名参与者还提供了18个月后的样本。对壁层炎症（小儿炎症性克罗恩氏病磁共振肠造影指数，PICMI）、CD 简单内镜评分和加权小儿克罗恩氏病活动指数（wPCDAI）进行了评估。此外，还测量了粪便钙蛋白、血浆C反应蛋白（CRP）和粪便含水量（FWC）（FWC是胃肠道转运时间的代表）：结果：微生物组α的多样性、聚类和差异类群与疾病状态有关，但因疾病活动度的不同而有明显差异。使用 wPCDAI 观察到的微生物组与疾病活动状态之间的关系最密切；而使用 PICMI 等更客观的测量方法观察到的关系较少或没有关系。能预测疾病活动状态的分类群取决于所使用的疾病活动测量方法，其重叠程度几乎可以忽略不计。活动性疾病与较多的病原菌（如Viellonella、Enterobacterales）和较少的纤维发酵菌相关。就所有疾病活动指标而言，FWC 对微生物群的影响超过了活动性疾病的影响，尤其是 wPCDAI。考虑到FWC，由疾病活动状态解释的微生物特征差异减弱或消失：结论：在 CD 患者中，微生物组特征的波动取决于用于评估疾病严重程度的指标；其中一些信号可能是继发性疾病效应，与活动性疾病中肠道蠕动的变化有关。在研究 CD 中微生物组与壁层炎症之间的关系时，PICMI 似乎受到的影响较小。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Gut Microbial Signatures in Pediatric Crohn's Disease Vary According to Disease Activity Measures and Are Influenced by Proxies of Gastrointestinal Transit Time: An ImageKids Study.

Introduction: We investigated relationships between disease activity measures and the gut microbiome in children with Crohn's disease (CD) and how these were confounded by gastrointestinal transit time.

Methods: Microbiome was profiled (16S rRNA sequencing) in feces from 196 children with CD. Sixty participants also provided samples after 18 months. Mural inflammation (Pediatric Inflammatory Crohn's Magnetic Resonance Enterography Index, PICMI), the simple endoscopic score for CD, and the weighted pediatric Crohn's disease activity index (wPCDAI) were assessed. Fecal calprotectin, plasma C-reactive protein (CRP), and fecal water content (FWC), a proxy of gastrointestinal transit time, were measured too.

Results: Microbiome α diversity, clustering, and differential taxa were related to disease status, but varied remarkably by disease activity measure used. The strongest relationships between microbiome and disease activity status were observed using wPCDAI; fewer or no relationships were seen using more objective measures like PICMI. Taxa predictive of disease activity status were dependent on the disease activity measure used with negligible overlap. Active disease was associated with more pathobionts (eg, Viellonella, Enterobacterales) and fewer fiber-fermenting organisms. The effect FWC had on microbiome superseded the effect of active disease for all disease activity measures, particularly with wPCDAI. Accounting for FWC, the differences in microbial signatures explained by disease activity status were attenuated or lost.

Conclusions: In CD, microbiome signatures fluctuate depending on the measure used to assess disease severity; several of these signals might be secondary disease effects linked with changes in gut motility in active disease. PICMI appears to be less influenced when studying relationships between microbiome and mural inflammation in CD.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Inflammatory Bowel Diseases 医学-胃肠肝病学

CiteScore

9.70

自引率

6.10%

发文量

462

审稿时长

1 months

期刊介绍： Inflammatory Bowel Diseases® supports the mission of the Crohn''s & Colitis Foundation by bringing the most impactful and cutting edge clinical topics and research findings related to inflammatory bowel diseases to clinicians and researchers working in IBD and related fields. The Journal is committed to publishing on innovative topics that influence the future of clinical care, treatment, and research.