ArticlemSystems2021
Fungal and Bacterial Loads: Noninvasive Inflammatory Bowel Disease Biomarkers for the Clinical Setting.
Article in mSystems, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
24 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.
- A Systematic Review of Artificial Intelligence and Machine Learning Applications to Inflammatory Bowel Disease, with Practical Guidelines for Interpretation.Inflammatory bowel diseases · 2022Pooled it
- Fungal abundance across flare and remission in ulcerative colitis patients.Gut pathogens · 2026Article
- A Review on the Molecular Dynamics of EnterotypeInternational journal of molecular sciences · 2026Review
- Purification and Transcriptomic Characterization of Hypertrophied Hepatic Stellate Cells From CDAHFD Mouse Liver.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026Article
- Scale reliant mixed effects models enhance microbiome data analysis.Microbiome · 2026Article
- Host-microbe multi-omics and succinotype profiling have prognostic value for future relapse in patients with inflammatory bowel disease.Gut microbes · 2025Article
- Identification of a 10-species microbial signature of inflammatory bowel disease by machine learning and external validation.Cell regeneration (London, England) · 2025Article
- Incorporating scale uncertainty in microbiome and gene expression analysis as an extension of normalization.Genome biology · 2025Article
- The Gut Mycobiome for Precision Medicine.Journal of fungi (Basel, Switzerland) · 2025Review
- Artificial intelligence use for precision medicine in inflammatory bowel disease: a systematic review.American journal of translational research · 2025Review
- Multi-marker comparative analysis of 18S, ITS1, and ITS2 primers for human gut mycobiome profiling.Frontiers in bioinformatics · 2025Article
- Machine learning in the differential diagnosis of ulcerative colitis and Crohn's disease: a systematic review.Translational gastroenterology and hepatology · 2025Review
- Beyond Normalization: Incorporating Scale Uncertainty in Microbiome and Gene Expression Analysis.bioRxiv : the preprint server for biology · 2024Article
- Predicting short-term major postoperative complications in intestinal resection for Crohn's disease: A machine learning-based study.World journal of gastrointestinal surgery · 2024Article
- Erythropoietin supplementation induces dysbiosis of the gut microbiota and impacts mucosal immunity in a non-diseased mouse model.Frontiers in immunology · 2024Article
- A Machine Learning-Based Diagnostic Model for Crohn's Disease and Ulcerative Colitis Utilizing Fecal Microbiome Analysis.Microorganisms · 2023Article
- Performance of Machine Learning Algorithms for Predicting Disease Activity in Inflammatory Bowel Disease.Inflammation · 2023Article
- The role of gut microbiome in inflammatory bowel disease diagnosis and prognosis.United European gastroenterology journal · 2022Review
- Individuals with Inflammatory Bowel Disease Have an Altered Gut Microbiome Composition of Fungi and Protozoa.Microorganisms · 2022Article
- Gut Microbiome in Inflammatory Bowel Disease: Role in Pathogenesis, Dietary Modulation, and Colitis-Associated Colon Cancer.Microorganisms · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Microbiome sequence data have been used to characterize Crohn's disease (CD) and ulcerative colitis (UC). Based on these data, we have previously identified microbiomarkers at the genus level to predict CD and CD relapse. However, microbial load was underexplored as a potential biomarker in inflammatory bowel disease (IBD). Here, we sought to study the use of fungal and bacterial loads as biomarkers to detect both CD and UC and CD and UC relapse. We analyzed the fecal fungal and bacterial loads of 294 stool samples obtained from 206 participants using real-time PCR amplification of the ITS2 region and the 16S rRNA gene, respectively. We combined the microbial data with demographic and standard laboratory data to diagnose ileal or ileocolonic CD and UC and predict disease relapse using the random forest algorithm. Fungal and bacterial loads were significantly different between healthy relatives of IBD patients and nonrelated healthy controls, between CD and UC patients in endoscopic remission, and between UC patients in relapse and non-UC individuals. Microbial load data combined with demographic and standard laboratory data improved the performance of the random forest models by 18%, reaching an average area under the receiver operating characteristic curve (AUC) of 0.842 (95% confidence interval [CI], 0.65 to 0.98), for IBD diagnosis and enhanced CD and UC discrimination and CD and UC relapse prediction. Our findings show that fecal fungal and bacterial loads could provide physicians with a noninvasive tool to discriminate disease subtypes or to predict disease flare in the clinical setting.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.