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<p>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&#xa0;year), Young adult (18 ~ 34&#xa0;year), Mid-age (35 ~ 65&#xa0;year) and Elder (over 65&#xa0;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 <i>Streptococcus</i>, <i>Veillonella</i>, and <i>Haemophilus</i> were less abundant in these groups, while periodontopathogens including <i>Porphyromonas</i>, <i>Fusobacterium</i>, and <i>Treponema</i> were more abundant. Core microbiome analysis revealed <i>Streptococcus</i> dominance in the Child group, the presence of <i>Rothia</i> and <i>Actinomyces</i> 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. </p>

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A cross-sectional study of supragingival microbiome depending on age in Korean population

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月14日

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  • Jung Hwa Park,
  • Si Yeong Kim,
  • Hoi-Soon Lim,
  • Hyun-Joo Kim,
  • Ju Youn Lee,
  • Jin Chung,
  • Hee Sam Na

摘要

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.