Background <p>The skin microbiome plays an important role in aging, yet most aging biomarkers predominantly focus on gut bacteria, overlooking the skin microbial communities, especially its fungal component.</p> Objectives <p>To comprehensively profile the skin bacterial and fungal microbiome across age, sex, and anatomical sites (sun-exposed forehead vs. non-sun-exposed back) and develop an integrated microbial model for age prediction.</p> Methods <p>A total of 160 skin swabs from 80 healthy individuals stratified into four age groups (centered at 10, 30, 50, 70 years) were conducted by DNA sequencing for microbial analysis. An age-predictive model was built using a random forest classifier trained on bacterial and fungal composition data.</p> Results <p>We found clear age- and sex-specific differences in the skin microbiome. Fungal diversity was significantly higher in females, while bacterial diversity decreased markedly around age 30 in both sexes. <i>Malassezia</i> dominated fungal communities; its abundance peaked at 30 years, declining with age, especially on female foreheads. Age-dependent shifts occurred in dominant <i>Malassezia</i> species (e.g., <i>M. globosa</i> in children, <i>M. arunalokei</i> in the elderly). Bacterial communities shifted from diverse childhood profiles (e.g., <i>Pseudomonas</i>, <i>Streptococcus</i>) to <i>Cutibacterium</i> dominance in young adulthood, which declined in older individuals. Correlation analysis revealed stronger age-microbe associations in males. Finally, we developed a predictive model using four key microbial markers—<i>Lactarius</i> (fungus), <i>Chryseobacterium</i>, <i>Gordonia</i>, and <i>Psychrobacter</i>—that showed good performance in age-group classification (AUC = 0.97).</p> Conclusion <p>Collectively, these findings reveal distinct age- and sex-related patterns in the skin microbiome, highlight the importance of including fungi in microbiome studies, and demonstrate the potential of microbial profiles as candidate age-associated signatures.</p>

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Dynamic shifts in cutaneous bacterial and fungal communities throughout human aging: a pilot study

  • Tingting Li,
  • Xin Ge,
  • Ganglian Chen,
  • Zhijian Huang,
  • Yuying Li,
  • Zhe Wan,
  • Ruoyu Li,
  • Ruojun Wang,
  • Wenjie Liu

摘要

Background

The skin microbiome plays an important role in aging, yet most aging biomarkers predominantly focus on gut bacteria, overlooking the skin microbial communities, especially its fungal component.

Objectives

To comprehensively profile the skin bacterial and fungal microbiome across age, sex, and anatomical sites (sun-exposed forehead vs. non-sun-exposed back) and develop an integrated microbial model for age prediction.

Methods

A total of 160 skin swabs from 80 healthy individuals stratified into four age groups (centered at 10, 30, 50, 70 years) were conducted by DNA sequencing for microbial analysis. An age-predictive model was built using a random forest classifier trained on bacterial and fungal composition data.

Results

We found clear age- and sex-specific differences in the skin microbiome. Fungal diversity was significantly higher in females, while bacterial diversity decreased markedly around age 30 in both sexes. Malassezia dominated fungal communities; its abundance peaked at 30 years, declining with age, especially on female foreheads. Age-dependent shifts occurred in dominant Malassezia species (e.g., M. globosa in children, M. arunalokei in the elderly). Bacterial communities shifted from diverse childhood profiles (e.g., Pseudomonas, Streptococcus) to Cutibacterium dominance in young adulthood, which declined in older individuals. Correlation analysis revealed stronger age-microbe associations in males. Finally, we developed a predictive model using four key microbial markers—Lactarius (fungus), Chryseobacterium, Gordonia, and Psychrobacter—that showed good performance in age-group classification (AUC = 0.97).

Conclusion

Collectively, these findings reveal distinct age- and sex-related patterns in the skin microbiome, highlight the importance of including fungi in microbiome studies, and demonstrate the potential of microbial profiles as candidate age-associated signatures.