Distinct bacterial facial cutaneous microbiota composition in adolescents with acne vulgaris: a population-based cross-sectional observational study
Bibliographic record
Abstract
BACKGROUND: Acne vulgaris (acne) is a prevalent dermatological condition associated with distinct facial cutaneous microbiota compositions. However, existing research often has methodological limitations such as insufficient statistical power and the under-representation of diverse adolescent populations, which are highly relevant for understanding acne pathogenesis. OBJECTIVES: To compare bacterial facial cutaneous microbiota compositions between individuals with acne and healthy control participants in a large, multiethnic adolescent population, while adjusting for potential confounders. METHODS: In a population-based study, we compared bacterial facial cutaneous microbiota compositions using 16S rRNA sequencing in individuals with physician-evaluated acne (n = 399) and healthy control participants (n = 527); all included individuals were adolescents (median age 13 years). We also evaluated the independent associations of biological sex, puberty stage, perceived skin colour, ethnicity and weight with facial cutaneous microbiota compositions. Our analytical approaches included the assessment of alpha and beta diversity (including permutational multivariate analysis of variance), relative abundances, univariate coordinate analysis (analysis of compositions of microbiomes with bias correction 2) and phylogenetic analyses. RESULTS: The overall microbiota composition of individuals with acne was less rich and less diverse than that of control participants [Chao1 β -44.98 (SE 4.36), Shannon β -1.01 (SE 0.07); P < 0.01]. While acne status was a major contributor to variations in overall microbiota compositions (R2 = 4.32%, P < 0.01), skin colour, sex, puberty stage and weight also independently contributed to variations (R2 = 0.44-1.05%; P < 0.01). Specifically, individuals with acne had higher relative abundances of Cutibacterium and Staphylococcus species, and a lower abundance of Streptococcus species. Following confounder adjustment, bias correction and phylogenetic analysis, Cutibacterium granulosum, Cutibacterium acnes and Staphylococcus epidermidis emerged as the most differentially abundant species in individuals with acne vs. control participants (log fold changes = 0.75-2.17; P < 0.01). CONCLUSIONS: Our findings reveal distinct facial microbiota compositions in adolescents with acne, identifying C. granulosum, C. acnes and S. epidermidis as a key microbial signature. This study suggests a significant clinical relevance for C. granulosum in acne pathology and a potential protective role for Streptococcus species in acne-free skin. These results underscore the importance of representative study populations in microbiome research and provide important methodological and technical insights for future investigations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".