Evidence map›Paper›PMID 41887936›Full record

ArticleJournal of clinical periodontology2026

Salivary Microvesicle Methylome and Microbiome Profiles in Periodontitis: An Exploratory Study.

Pingping Han, Chaminda Seneviratne, Qiongyi Zhao, Carlos Salomon, Xiang Li, Sašo Ivanovski

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. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Pingping HanSchool of Dentistry, The University of Queensland, Brisbane, Queensland, Australia.ORCID 0000-0001-7546-1635
Chaminda SeneviratneSchool of Dentistry, The University of Queensland, Brisbane, Queensland, Australia.
Qiongyi ZhaoThe University of Queensland, Queensland Brain Institute, Brisbane, Queensland, Australia.
Carlos SalomonFaculty of Medicine, Translational Extracellular Vesicles in Obstetrics and Gynae-Oncology Group, Centre for Clinical Diagnostics, University of Queensland Centre for Clinical Research, Royal Brisbane and Women's Hospital, The University of Queensland, Brisbane, Queensland, Australia.ORCID 0000-0003-4474-0046
Xiang LiDepartment of Anesthesiology, Brain Research Center, Department of Neurosurgery, Zhongnan Hospital, Wuhan University, Wuhan, Hubei Province, China.
Sašo IvanovskiSchool of Dentistry, The University of Queensland, Brisbane, Queensland, Australia.ORCID 0000-0001-5339-0936

Funding

Australian Dental Research Foundation 534-2019National Health and Medical Research Council 2034591National Natural Science Foundation of China 82001421
6 · The paper itself

Abstract

aimSalivary microvesicles (MVs) are nanosized extracellular vesicles from the host and microbiota whose cargo may mirror the biological state of their parent cells. This cross-sectional study aimed to explore the diagnostic power of host methylome and microbiome profiles of MVs in various periodontal disease states. MATERIALS AND

methodsThis exploratory study recruited 20 healthy, 16 gingivitis and 26 stage III/IV periodontitis cases. The origins of salivary host-MVs were identified using a multiplex extracellular vesicle (EV) kit. The microbiome and host methylome profiles of MV DNA were analysed using 16S rRNA sequencing and methylated DNA immunoprecipitation sequencing (MeDIP-seq), respectively.

resultsThe periodontitis group showed increased CD63+, CD45+, CD29

conclusionThis exploratory study found that host methylome and microbiome profiles in salivary MVs reflect periodontal disease status, and hence supports their potential as non-invasive liquid biopsy biomarkers for periodontitis.

Indexed as

Cell-Derived MicroparticlesDNA MethylationEpigenomeMicrobiotaPeriodontitisSalivaAdultCross-Sectional StudiesFemaleGingivitisHumansMaleMiddle AgedRNA, Ribosomal, 16SRNA, Ribosomal, 16S

Identifiers

PMID41887936
PMCPMC13167645

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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.