ArticleFrontiers in microbiology2021
Predictive Metagenomic Analysis of Autoimmune Disease Identifies Robust Autoimmunity and Disease Specific Microbial Signatures.
Article in Frontiers in microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 2 of them syntheses that pooled it.
What it found
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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
29 citing papers in PubMed, 2 syntheses or guidelines pooled it, 42 citations in OpenAlex.
- Using artificial intelligence to predict post-operative outcomes in congenital heart surgeries: a systematic review.BMC cardiovascular disorders · 2024Pooled it
- A Systematic Review of Artificial Intelligence and Machine Learning Applications to Inflammatory Bowel Disease, with Practical Guidelines for Interpretation.Inflammatory bowel diseases · 2022Pooled it
- Trial
- Recent advances in the positive role ofFrontiers in immunology · 2026Review
- An overview of the role of the gut microbiota in rheumatoid arthritis.Microbiome research reports · 2026Review
- Host-microbe multi-omics and succinotype profiling have prognostic value for future relapse in patients with inflammatory bowel disease.Gut microbes · 2025Article
- Breaking down barriers: is intestinal mucus degradation byInfection and immunity · 2025Review
- Machine learning approaches to identify neonates and young children at risk for postdischarge mortality in Dar es Salaam, Tanzania and Monrovia, Liberia.BMJ paediatrics open · 2025Observational
- Fasting elicits gut microbiome signature changes that extend to type 1 diabetes patients.Frontiers in endocrinology · 2025Article
- Interpretable machine learning algorithms reveal gut microbiome features associated with atopic dermatitis.Frontiers in immunology · 2025Article
- Artificial intelligence in autoimmune diseases: a bibliometric exploration of the past two decades.Frontiers in immunology · 2025Review
- Lupus and inflammatory bowel disease share a common set of microbiome features distinct from other autoimmune disorders.Annals of the rheumatic diseases · 2025Observational
- Using Machine Learning and Feature Importance to Identify Risk Factors for Mortality in Pediatric Heart Surgery.Diagnostics (Basel, Switzerland) · 2024Article
- The Future Exploring of Gut Microbiome-Immunity Interactions: From In Vivo/Vitro Models to In Silico Innovations.Microorganisms · 2024Review
- Bronchoalveolar Lavage Fluid Microbiota is Associated with the Diagnosis and Prognosis Evaluation of Lung Cancer.Phenomics (Cham, Switzerland) · 2024Article
- Advancing precision rheumatology: applications of machine learning for rheumatoid arthritis management.Frontiers in immunology · 2024Review
- Review
- Relationship between gut microbiota and rheumatoid arthritis: A bibliometric analysis.Frontiers in immunology · 2023Article
- Machine Learning Model for Predicting Risk of In-Hospital Mortality after Surgery in Congenital Heart Disease Patients.Reviews in cardiovascular medicine · 2022Article
- Mining the microbiota to identify gut commensals modulating neuroinflammation in a mouse model of multiple sclerosis.Microbiome · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Within the last decade, numerous studies have demonstrated changes in the gut microbiome associated with specific autoimmune diseases. Due to differences in study design, data quality control, analysis and statistical methods, many results of these studies are inconsistent and incomparable. To better understand the relationship between the intestinal microbiome and autoimmunity, we have completed a comprehensive re-analysis of 42 studies focusing on the gut microbiome in 12 autoimmune diseases to identify a microbial signature predictive of multiple sclerosis (MS), inflammatory bowel disease (IBD), rheumatoid arthritis (RA) and general autoimmune disease using both 16S rRNA sequencing data and shotgun metagenomics data. To do this, we used four machine learning algorithms, random forest, eXtreme Gradient Boosting (XGBoost), ridge regression, and support vector machine with radial kernel and recursive feature elimination to rank disease predictive taxa comparing disease vs. healthy participants and pairwise comparisons of each disease. Comparing the performance of these models, we found the two tree-based methods, XGBoost and random forest, most capable of handling sparse multidimensional data, to consistently produce the best results. Through this modeling, we identified a number of taxa consistently identified as dysregulated in a general autoimmune disease model including
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Registered trials
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.