ArticleScientific reports2026
A cross-sectional study of supragingival microbiome depending on age in Korean population.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Harmonized multi-cohort analysis of oral microbiome development during early lifetime.Journal of oral microbiology · 2026Article
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7 authors.
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Abstract
Age is a key factor influencing the composition of the oral microbiome, but its age-related dynamics remain unclear as most studies focus on specific age groups or disease-related changes. The objective of this study was to characterize age-related differences in the supragingival microbiome. Supragingival plaque samples were collected from 533 participants across four age groups including Child (3 ~ 5 year), Young adult (18 ~ 34 year), Mid-age (35 ~ 65 year) and Elder (over 65 year) groups. Microbial DNA was extracted and analyzed using 16S rRNA gene sequencing. Alpha and beta diversity were assessed. Taxonomic classification was performed using a Naïve Bayes classifier trained on the eHOMD database. Differential abundance analysis was conducted using LEfSe, and microbial network interactions were examined using SparCC. Alpha diversity differed among age groups, and beta diversity also showed significant differences among groups, except between the Mid-age and Elder groups. The relative abundance of Firmicutes and Proteobacteria was lower in the Mid-age and Elder groups, whereas Bacteroidetes and Fusobacteria were more abundant. Early colonizers such as Streptococcus, Veillonella, and Haemophilus were less abundant in these groups, while periodontopathogens including Porphyromonas, Fusobacterium, and Treponema were more abundant. Core microbiome analysis revealed Streptococcus dominance in the Child group, the presence of Rothia and Actinomyces in the Young adult group, and more pathogen-enriched microbiome in the Mid-age and Elder groups. Microbial network complexity also differed across age groups, with denser and more pathogen-centered networks observed in the older groups. Distinct age-related differences in the oral microbiome were observed in this cross-sectional study, with microbial diversity, taxonomic composition, and microbial interaction patterns. These findings suggest that understanding age-related microbial variation may be important for long-term oral health.
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