Compositional changes in fecal microbiota associated with clinical phenotypes and prognosis in Korean patients with inflammatory bowel disease

Shin, Seung Yong; Kim, Young; Kim, Won-Seok; Moon, Jeong Min; Lee, Kang-Moon; Jung, Sung Ae; Park, Hyesook; Huh, Eun Young; Kim, Byung Chang; Lee, Soo Chan; Choi, Chang Hwan

doi:10.5217/ir.2021.00168

Cited by 16 publications

(18 citation statements)

References 59 publications

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“…Microbial arginine and isoprene pathways were at higher relative abundance in the gut microbiome of CD patients (Hu et al 2021 ). Recent analysis of the faecal microbiota of Korean patients with IBD (70 with UC, 39 with CD) and 100 healthy control individuals using Illumina MiSeq revealed that R. gnavus was a biomarker for prognosis in CD (Shin et al 2022 ). Whole genome sequencing of R. gnavus isolates coupled with metagenomic analyses from 20 IBD patients and 12 controls revealed two phylogenetically distinct R. gnavus strains that appeared differentially enriched in IBD (Hall et al 2017 ), highlighting the importance of analysing the effect of R. gnavus on IBD at the strain level.…”

Section: Association Between R Gnavus and Diseasesmentioning

confidence: 99%

Ruminococcus gnavus: friend or foe for human health

Crost

Coletto

Bell

et al. 2023

FEMS Microbiology Reviews

102

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Ruminococcus gnavus was first identified in 1974 as a strict anaerobe in the gut of healthy individuals, and for several decades, its study has been limited to specific enzymes or bacteriocins. With the advent of metagenomics, R. gnavus has been associated both positively and negatively with an increasing number of intestinal and extra-intestinal diseases from inflammatory bowel diseases to neurological disorders. This prompted renewed interest in understanding the adaptation mechanisms of R. gnavus to the gut, and the molecular mediators affecting its association with health and disease. From ca. 250 publications citing R. gnavus since 1990, 94% were published in the last 10 years. In this review, we describe the biological characterisation of R. gnavus, its occurrence in the infant and adult gut microbiota and the factors influencing its colonisation of the gastrointestinal tract; we also discuss the current state of our knowledge on its role in host health and disease. We highlight gaps in knowledge and discuss the hypothesis that differential health outcomes associated with R. gnavus in the gut are strain and niche specific.

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Section: Association Between R Gnavus and Diseasesmentioning

confidence: 99%

Ruminococcus gnavus: friend or foe for human health

Crost

Coletto

Bell

et al. 2023

FEMS Microbiology Reviews

102

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“…[30,31] Additionally, certain Lactobacillus species are proposed to be linked with extensive disease involvement and heightened disease activity. [32] Although no clear evidence supports the association of a speci c type of gut bacteria with UC development, these ndings suggest that as the disease progresses, the gut environment may change to favor the colonization and expression of certain bacteria. Thus, the changing gut environment should be considered with the progression of the disease through further research.…”

Section: Discussionmentioning

confidence: 92%

Dynamic Changes in the Gut Microbiota Composition during Adalimumab Therapy in Patients with Ulcerative Colitis: Implications for Treatment Response Prediction and Therapeutic Targets

Oh,

Shin,

Kim

et al. 2024

Preprint

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Background Little is known about the changes in the gut microbiota composition during anti-tumor necrosis factor-alpha (anti TNF-α) therapy. This study aimed to investigate the dynamics of gut microbiome changes during anti TNF-α (adalimumab) therapy in patients with ulcerative colitis (UC). Results The microbiota composition was affected by the disease severity and extent in patients with UC. Regardless of clinical remission status at each time point, patients with UC exhibited microbial community distinctions from healthy controls. Distinct amplicon sequence variants (ASVs) differences were identified throughout the course of ADA treatment at each time point. A notable reduction in gut microbiome dissimilarity was observed only in remitters. Remitters demonstrated a decrease in the relative abundances of Burkholderia-Caballeronia-Paraburkholderia and Staphylococcus, accompanied by an increase in Bifidobacterium and Dorea as the treatment progressed. Given the distribution of the 48 ASVs with high or low relative abundances in the pre-treatment samples according to clinical remission at week 8, a clinical remission at week 8 with a sensitivity and specificity of 72.4% and 84.3%, respectively, was predicted on the receiver operating characteristic curve (area under the curve, 0.851). Conclusions The gut microbiota undergoes diverse changes according to the treatment response during ADA treatment. These changes provide insights into predicting treatment responses to ADA and offer new therapeutic targets for UC.

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“…Recent studies have consistently reported a decrease in microbial diversity in IBD patients compared with HC [20][21][22]. Several studies have observed signi cant differences in the gut microbiome of patients with IBD compared with HC [23][24][25][26]. When the relative abundance was compared at the phylum level, both Firmicutes and Bacteroidetes decreased in IBD compared with HC, whereas Actinobacteria and Proteobacteria increased signi cantly [27,28].…”

Section: Discussionmentioning

confidence: 99%

Diagnosis of Crohn's Disease and Ulcerative Colitis Using the Microbiome

Kang

Park

Yeo

et al. 2023

Preprint

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Background: Inflammatory bowel disease (IBD) is a multifactorial chronic inflammatory disease resulting from dysregulation of the mucosal immune response and gut microbiota. Crohn's disease (CD) and ulcerative colitis (UC) are difficult to distinguish, and differential diagnosis is essential for establishing a long-term treatment plan for patients. Furthermore, the abundance of mucosal bacteria is associated with disease severity. This study aimed to differentiate and diagnose these two diseases using the microbiome and identify specific biomarkers associated with disease activity. Results: We observed differences in the abundance and composition of the microbiome between patients with IBD and healthy controls (HC). Compared to HC, the diversity of the gut microbiome in patients with IBD decreased; the diversity of the gut microbiome in patients with CD was significantly lower. We identified 68 members of the microbiota (28 for CD and 40 for UC) associated with these diseases. Additionally, as the disease progressed through different stages, the diversity of the bacteria decreased. The abundances of Alistipes shahii and Pseudodesulfovibrio aespoeensis were negatively correlated with the severity of CD, whereas the abundance of Polynucleobacter wianus was positively correlated. The severity of UC was negatively correlated with the abundance of A. shahii, Porphyromonas asaccharolytica and Akkermansia muciniphilla, while it was positively correlated with the abundance of Pantoea candidatus pantoea carbekii. A regularized logistic regression model was used for the differential diagnosis of the two diseases. The area under the curve(AUC) was used to examine the model performance. The model discriminated between UC and CD at an AUC of 0.886 (training set) and 0.826 (test set) and an area under the precision-recall curve (AUCPR) of 0.871 (test set). Conclusions: Based on fecal whole-metagenome shotgun (WMS) sequencing, CD and UC were diagnosed using a machine-learning predictive model. Additionally, microbiome biomarkers associated with disease activity (UC and CD) have been proposed.

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Compositional changes in fecal microbiota associated with clinical phenotypes and prognosis in Korean patients with inflammatory bowel disease

Cited by 16 publications

References 59 publications

Ruminococcus gnavus: friend or foe for human health

Ruminococcus gnavus: friend or foe for human health

Dynamic Changes in the Gut Microbiota Composition during Adalimumab Therapy in Patients with Ulcerative Colitis: Implications for Treatment Response Prediction and Therapeutic Targets

Diagnosis of Crohn's Disease and Ulcerative Colitis Using the Microbiome

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