Evidence map›Paper›PMID 41534871›Full record

ArticleJournal of clinical periodontology2026

Oral-Rinse-Sourced Microbiota in Oral Health and Diseases in a Representative US Adult Population: Implications for Diagnostics.

Yu Xie, Alejandro Artacho, Xiaoyu Yu, Mengning Bi, Hairui Li, Yuan Li, Andrea Roccuzzo, Alex Mira, Bob T Rosier, Maurizio S Tonetti

Abstract read
In one paragraph

Article in Journal of clinical periodontology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Yu XieShanghai Perio-Implant Innovation Center, Institute for Oral, Craniofacial and Sensory Research, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID 0000-0002-8713-8947
Alejandro ArtachoDepartment of Genomics and Health, FISABIO Foundation, Center for Advanced Research in Public Health, Valencia, Spain.
Xiaoyu YuShanghai Perio-Implant Innovation Center, Institute for Oral, Craniofacial and Sensory Research, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Mengning BiShanghai Perio-Implant Innovation Center, Institute for Oral, Craniofacial and Sensory Research, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID 0009-0002-1464-968X
Hairui LiShanghai Perio-Implant Innovation Center, Institute for Oral, Craniofacial and Sensory Research, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yuan LiShanghai Perio-Implant Innovation Center, Institute for Oral, Craniofacial and Sensory Research, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID 0000-0002-0133-7516
Andrea RoccuzzoShanghai Perio-Implant Innovation Center, Institute for Oral, Craniofacial and Sensory Research, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Alex MiraDepartment of Genomics and Health, FISABIO Foundation, Center for Advanced Research in Public Health, Valencia, Spain.ORCID 0000-0002-9127-3877
Bob T RosierDepartment of Genomics and Health, FISABIO Foundation, Center for Advanced Research in Public Health, Valencia, Spain.ORCID 0000-0002-3267-6561
Maurizio S TonettiShanghai Perio-Implant Innovation Center, Institute for Oral, Craniofacial and Sensory Research, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID 0000-0002-2743-0137

Funding

Clinical+ programme of the Ninth People's Hospital JYLJ202404
6 · The paper itself

Abstract

aimsTo investigate the associations between oral-rinse microbiota and distinct oral conditions, and further evaluate its potential ability to distinguish periodontitis severity.

methodsOral-rinse-sourced microbiota with 16S ribosomal RNA sequencing from 3770 adults in US National Health and Nutrition Examination Survey 2009-2012 were analysed across oral health, caries, periodontitis, co-existing caries and periodontitis and edentulism. Diagnostic potential of the oral-rinse microbiota for periodontitis severity was evaluated using multi-class random forest (RF) model with internal validation and external validation in an independent cohort (n = 392).

resultsOral condition accounted for substantial variance in oral-rinse microbiota, revealing disease or tooth loss-associated shifts. Increasing acidogenic/aciduric taxa (Veillonella, Lactobacillus, Atopobium) or periodontitis-associated taxa (Filifactor, Treponema, Tannerella) were identified in caries-only or periodontitis-only groups, respectively, while the co-existing disease group showed overlapping shifts. Taxa shifted dose-dependently with increasing periodontitis severity. The RF model achieved moderate performance in identifying severe periodontitis, with the area under the receiver operating characteristic curve (AUROC) of 0.81 (0.75-0.87) internally and 0.83 (0.77-0.88) externally. Key contributing taxa aligned with established periodontitis-associated genera, supporting model interpretability.

conclusionBased on our results, oral-rinse microbiota captures disease-specific signatures across oral conditions, supporting its potential as a non-invasive tool to monitor oral microbial ecology and assess periodontitis severity at the population level.

Indexed as

MicrobiotaOral HealthPeriodontitisAdultDental CariesFemaleHumansMaleNutrition SurveysRNA, Ribosomal, 16SUnited StatesRNA, Ribosomal, 16S16S rRNAdental cariesdiagnosismachine learningmicrobiotaperiodontitis

Identifiers

PMID41534871
PMCPMC13086544

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.