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已发表论文
基于肠道微生物群预测炎症性肠病患者治疗后复发风险
Authors Zhang T , He B, Lan C, Liu J, Zeng Q, Pu W, Zhou L, Zhou Q, Hu D, Chen Y, Peng Y, Li G, Wang Q, Chen L, Du Z, Li S, Tang X, Chen J, Xiao C
Received 13 August 2025
Accepted for publication 7 November 2025
Published 19 November 2025 Volume 2025:18 Pages 16079—16092
DOI https://doi.org/10.2147/JIR.S558136
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Fatih Türker
Tao Zhang,1,* Binbo He,1,* Chao Lan,1,* Jie Liu,1 Qingyu Zeng,1 Wenfeng Pu,1 Lifeng Zhou,1 Qian Zhou,1 Dan Hu,1 Yanan Chen,1 Yiming Peng,1 Guobing Li,1 Qing Wang,1 Long Chen,1 Zonghan Du,1 Shiqing Li,1 Xiaobo Tang,1 Jian Chen,1 Chuanxing Xiao2
1Department of Gastroenterology, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Nanchong, Sichuan, 637000, People’s Republic of China; 2Xiamen Institutes of Respiratory Health, Xiamen, Fujian, 361000, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Tao Zhang, Department of Gastroenterology, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Nanchong, Sichuan, 637000, People’s Republic of China, Email 305514271@qq.com Chuanxing Xiao, Xiamen Institutes of Respiratory Health, Xiamen, Fujian, 361000, People’s Republic of China, Email xiaoxx@xmu.edu.cn
Background: Inflammatory bowel disease (IBD) is a chronic inflammatory disorder of the gastrointestinal tract. Post-treatment relapse is a major clinical challenge, and gut microbiota dysbiosis is hypothesized to be involved.
Methods: We enrolled 88 patients with IBD (46 UC, 42 CD) to investigate gut microbiota features associated with post-treatment relapse. Fecal samples collected before and after therapy were analyzed by 16S rRNA sequencing. A random forest (RF) model was developed to evaluate the predictive value of microbiota signatures for recurrence.
Results: At baseline (pre-treatment), no differences were observed in gut microbiota diversity between patients with UC and CD. However, significant compositional differences were observed, with Fusobacterium and Parabacteroides enriched in CD patients, and Anaerostipes and Enterococcus enriched in UC patients. Post-treatment, there was no significant difference in the α-diversity across IBD patients; however, β-diversity exhibited significant alterations, marked by enrichment of Akkermansia and Lachnoclostridium. Patients maintaining remission exhibited significant post-treatment beta-diversity shifts and enrichment of Erysipelatoclostridium, Delftia, Tyzzerella, Sphingomonas, Subdoligranulum, Proteus, and Enterococcus. Conversely, patients experiencing recurrence showed a significant reduction in Shannon alpha-diversity post-treatment and enrichment of UCG-002, Odoribacter, Delftia, Flavonifractor, and Erysipelotrichaceae_UCG-003. Post-treatment microbiota composition differed significantly between recurrent and non-recurrent patients, with higher alpha-diversity in the non-recurrent group. Non-recurrent patients exhibited enrichment of Eubacterium_hallii_group, Clostridioides, UCG-002, Paraprevotella, Bilophila, Desulfovibrio, Butyricimonas, Clostridium_sensu_stricto_1, Megamonas, Romboutsia, Parabacteroides, and Enterococcus, while Delftia was predominantly enriched in recurrent patients. The RF model, built using differentially abundant genera to distinguish recurrence status, achieved an area under the curve (AUC) of 0.721 in the validation set and 0.861 in the test cohort, indicating good predictive performance.
Conclusion: Our findings suggest that gut microbiota composition may hold clues for predicting IBD relapse. The RF model is a proof-of-concept that warrants external validation in prospective, multi-center studies before clinical application.
Keywords: inflammatory bowel disease, relapse, gut microbiota, random forest model, 16S rRNA sequencing
1Department of Gastroenterology, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Nanchong, Sichuan, 637000, People’s Republic of China; 2Xiamen Institutes of Respiratory Health, Xiamen, Fujian, 361000, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Tao Zhang, Department of Gastroenterology, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Nanchong, Sichuan, 637000, People’s Republic of China, Email 305514271@qq.com Chuanxing Xiao, Xiamen Institutes of Respiratory Health, Xiamen, Fujian, 361000, People’s Republic of China, Email xiaoxx@xmu.edu.cn
Background: Inflammatory bowel disease (IBD) is a chronic inflammatory disorder of the gastrointestinal tract. Post-treatment relapse is a major clinical challenge, and gut microbiota dysbiosis is hypothesized to be involved.
Methods: We enrolled 88 patients with IBD (46 UC, 42 CD) to investigate gut microbiota features associated with post-treatment relapse. Fecal samples collected before and after therapy were analyzed by 16S rRNA sequencing. A random forest (RF) model was developed to evaluate the predictive value of microbiota signatures for recurrence.
Results: At baseline (pre-treatment), no differences were observed in gut microbiota diversity between patients with UC and CD. However, significant compositional differences were observed, with Fusobacterium and Parabacteroides enriched in CD patients, and Anaerostipes and Enterococcus enriched in UC patients. Post-treatment, there was no significant difference in the α-diversity across IBD patients; however, β-diversity exhibited significant alterations, marked by enrichment of Akkermansia and Lachnoclostridium. Patients maintaining remission exhibited significant post-treatment beta-diversity shifts and enrichment of Erysipelatoclostridium, Delftia, Tyzzerella, Sphingomonas, Subdoligranulum, Proteus, and Enterococcus. Conversely, patients experiencing recurrence showed a significant reduction in Shannon alpha-diversity post-treatment and enrichment of UCG-002, Odoribacter, Delftia, Flavonifractor, and Erysipelotrichaceae_UCG-003. Post-treatment microbiota composition differed significantly between recurrent and non-recurrent patients, with higher alpha-diversity in the non-recurrent group. Non-recurrent patients exhibited enrichment of Eubacterium_hallii_group, Clostridioides, UCG-002, Paraprevotella, Bilophila, Desulfovibrio, Butyricimonas, Clostridium_sensu_stricto_1, Megamonas, Romboutsia, Parabacteroides, and Enterococcus, while Delftia was predominantly enriched in recurrent patients. The RF model, built using differentially abundant genera to distinguish recurrence status, achieved an area under the curve (AUC) of 0.721 in the validation set and 0.861 in the test cohort, indicating good predictive performance.
Conclusion: Our findings suggest that gut microbiota composition may hold clues for predicting IBD relapse. The RF model is a proof-of-concept that warrants external validation in prospective, multi-center studies before clinical application.
Keywords: inflammatory bowel disease, relapse, gut microbiota, random forest model, 16S rRNA sequencing