ArticleBMC microbiology2024
Gut microbes on the risk of advanced adenomas.
Article in BMC microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Gut microbiome biomarkers for colorectal cancer detection: a systematic review highlighting age as a key confounder.Frontiers in oncology · 2026Pooled it
- metaFun: An analysis pipeline for metagenomic big data with fast and unified functional searches.Gut microbes · 2026Article
- Effects of dietary mulberry anthocyanins on meat quality, antioxidant capacity, gut microbiota, and plasma anthocyanin exposure in North China Chai chickens.Poultry science · 2026Article
- Metagenomic analysis of fecal microbial communities in dairy goats from different farms.Protoplasma · 2026Article
- The study on the identification of cross-boundary microbiome enterotypes between high-altitude and coastal populations and their predictive value.BMC microbiology · 2026Article
- Impact of gut microbiota on atypical endometrial hyperplasia and endometrial cancer: a comprehensive analysis of microbial composition and metabolomic profiling.BMC microbiology · 2026Article
- The role of theFrontiers in microbiology · 2026Review
- Construction of a gene-metabolite-microbiome regulatory network reveals novel therapeutic targets in bladder cancer through multi-omics analysis.Annals of medicine · 2025Article
- Article
- Revolutionizing gastroenterology and hepatology with artificial intelligence: From precision diagnosis to equitable healthcare through interdisciplinary practice.World journal of gastroenterology · 2025Review
- Alteration of gut microbiota associated with hypertension in children.BMC microbiology · 2025Article
- DMoVGPE: predicting gut microbial associated metabolites profiles with deep mixture of variational Gaussian Process experts.BMC bioinformatics · 2025Article
- Metagenomic and Metabolomic Analyses Reveal the Role of a Bacteriocin-Producing Strain ofMicroorganisms · 2025Article
- Characterization of microbiota signatures in Iberian pig strains using machine learning algorithms.Animal microbiome · 2025Article
- Deciphering the causality of gut microbiota, circulating metabolites and heart failure: a mediation mendelian.Frontiers in pharmacology · 2025Article
- Cu-Ag nanoparticles positively modulating the endophytic bacterial community in tomato roots affected by bacterial wilt.Frontiers in microbiology · 2025Article
- Butyric Acid Modulates Gut Microbiota to Alleviate Inflammation and Secondary Bone Loss in Ankylosing Spondylitis.Biomedicines · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
backgroundMore than 90% of colorectal cancer (CRC) arises from advanced adenomas (AA) and gut microbes are closely associated with the initiation and progression of both AA and CRC.
objectiveTo analyze the characteristic microbes in AA.
methodsFecal samples were collected from 92 AA and 184 negative control (NC). Illumina HiSeq X sequencing platform was used for high-throughput sequencing of microbial populations. The sequencing results were annotated and compared with NCBI RefSeq database to find the microbial characteristics of AA. R-vegan package was used to analyze α diversity and β diversity. α diversity included box diagram, and β diversity included Principal Component Analysis (PCA), principal co-ordinates analysis (PCoA), and non-metric multidimensional scaling (NMDS). The AA risk prediction models were constructed based on six kinds of machine learning algorithms. In addition, unsupervised clustering methods were used to classify bacteria and viruses. Finally, the characteristics of bacteria and viruses in different subtypes were analyzed.
resultsThe abundance of Prevotella sp900557255, Alistipes putredinis, and Megamonas funiformis were higher in AA, while the abundance of Lilyvirus, Felixounavirus, and Drulisvirus were also higher in AA. The Catboost based model for predicting the risk of AA has the highest accuracy (bacteria test set: 87.27%; virus test set: 83.33%). In addition, 4 subtypes (B1V1, B1V2, B2V1, and B2V2) were distinguished based on the abundance of gut bacteria and enteroviruses (EVs). Escherichia coli D, Prevotella sp900557255, CAG-180 sp000432435, Phocaeicola plebeiuA, Teseptimavirus, Svunavirus, Felixounavirus, and Jiaodavirus are the characteristic bacteria and viruses of 4 subtypes. The results of Catboost model indicated that the accuracy of prediction improved after incorporating subtypes. The accuracy of discovery sets was 100%, 96.34%, 100%, and 98.46% in 4 subtypes, respectively.
conclusionPrevotella sp900557255 and Felixounavirus have high value in early warning of AA. As promising non-invasive biomarkers, gut microbes can become potential diagnostic targets for AA, and the accuracy of predicting AA can be improved by typing.
Indexed as
Identifiers
What OpenQuestion holds
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.