Evidence map›Paper›PMID 41667138›Full record

ArticleJournal of periodontal & implant science2026

Comparison of microbiome profiles across sample types in patients with peri-implantitis using 16S rRNA sequencing.

Da-Mi Kim, Inpyo Hong, Joo-Yeon Lee, Seulbin Im, Kyeong-Won Paeng, Ui-Won Jung, Jae-Kook Cha

Abstract read
In one paragraph

Article in Journal of periodontal & implant science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Da-Mi Kim *Department of Periodontology, Research Institute for Periodontal Regeneration, Yonsei University College of Dentistry, Seoul, Korea.ORCID https://orcid.org/0009-0008-1124-7929
Inpyo Hong *Department of Periodontology, Research Institute for Periodontal Regeneration, Yonsei University College of Dentistry, Seoul, Korea.ORCID https://orcid.org/0000-0002-0486-9593
Joo-Yeon LeeDepartment of Periodontology, Research Institute for Periodontal Regeneration, Yonsei University College of Dentistry, Seoul, Korea.ORCID https://orcid.org/0000-0002-6424-3605
Seulbin ImDepartment of Periodontology, Research Institute for Periodontal Regeneration, Yonsei University College of Dentistry, Seoul, Korea.ORCID https://orcid.org/0009-0001-3741-3007
Kyeong-Won PaengDepartment of Periodontology, Research Institute for Periodontal Regeneration, Yonsei University College of Dentistry, Seoul, Korea.ORCID https://orcid.org/0000-0001-7262-7345
Ui-Won JungDepartment of Periodontology, Research Institute for Periodontal Regeneration, Yonsei University College of Dentistry, Seoul, Korea.ORCID https://orcid.org/0000-0001-6371-4172
Jae-Kook ChaDepartment of Periodontology, Research Institute for Periodontal Regeneration, Yonsei University College of Dentistry, Seoul, Korea. chajaekook@gmail.com.ORCID https://orcid.org/0000-0002-6906-7209

Funding

Biobank of Yonsei University Dental Hospital 2024ER050700National Research Foundation of Korea 2022M3A9F3016364National Research Foundation of Korea RS-2025-00522998
6 · The paper itself

Abstract

purposeNumerous studies have applied microbial analyses to peri-implantitis, including analyses of samples collected from various sites. While characteristics of the peri-implantitis microbiome have been identified, differences in sampling methods between studies have not been considered. The present study aimed to (1) characterize microbial similarities among saliva, gingival crevicular fluid (GCF), subgingival plaque (SGP) and inflammatory connective tissue (ICT) within the same participant with peri-implantitis; and (2) determine the microbial profiles of peri-implantitis sites.

methodsSaliva, GCF, and SGP samples were collected from 18 patients undergoing peri-implantitis surgery, and ICT samples were obtained after flap elevation. The collected samples were analyzed using 16S rRNA sequencing.

resultsThe sampling sites showed a mean bone loss of 6.9 mm and a maximum probing depth (PD) of 8.3 mm. Alpha diversity did not differ significantly among ICT, GCF, and SGP, whereas saliva exhibited a distinct diversity profile. Additionally, beta diversity analyses indicated that the microbial community structure differed significantly between saliva and the other samples. In taxonomic analyses, the microbial profiles of ICT, GCF, and SGP were clearly distinguishable from those of saliva. Saliva had lower proportions of Bacteroidetes and higher proportions of Proteobacteria and Actinobacteria species, especially at sites with deep PD. Pearson correlation analyses revealed strong correlations between ICT and both GCF and SGP, but not between ICT and saliva. Pathogenic species such as

conclusionsICT, GCF, and SGP shared similar microbial profiles, whereas saliva exhibited a significantly different profile. ICT, GCF, and SGP had higher abundances of peri-implant pathogenic species, whereas saliva tended to have lower abundances; this difference was especially pronounced in deep pockets.

Indexed as

16S rRNAMicrobiomePeri-implantitisRNA sequencing

Identifiers

PMID41667138
PMCPMC13150361

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