Comparative Analysis of Skin Microbiome in Acne and Rosacea Patients

Thesis Abstract

The human skin microbiome is increasingly recognized as a dynamic ecosystem linked to inflammatory dermatoses, yet comparative microbial signatures between acne and rosacea remain underexplored, limiting targeted therapeutic strategies. This study aims to elucidate distinctive and shared microbiome profiles in acne and rosacea patients, investigate associations with clinical severity, and identify microbial predictors of disease phenotype to inform personalized management. Specific objectives include (i) to characterize skin microbial diversity and taxonomic composition across facial sites in acne and rosacea cohorts; (ii) to compare alpha and beta diversity indices between groups and correlate them with disease severity scores (IGA for acne and Rosacea Severity Scale); (iii) to identify differential abundance of bacterial and fungal taxa using compositional data analysis; (iv) to assess functional potential differences via metagenomic inference and pathway analysis; (v) to evaluate the influence of host factors (age, sex, BMI, sebum production) and environmental variables (hygiene practices, topical regimens) on microbiome structure; and (vi) to test predefined hypotheses grounded in the Salutogenic Theory of Microbiome-Host Interactions and the Bankov-Drivers framework for inflammatory skin disorders. A cross-sectional, observational design will be employed. Three cohorts will be recruited 80 individuals with clinically diagnosed acne vulgaris, 80 individuals with rosacea, and 60 healthy controls matched by age and sex. Facial swab samples will be collected from standardized sites (cheek, forehead, and nasal ala) using sterile techniques. Metadata will be gathered via structured questionnaires and clinical assessments, including disease duration, severity scales, and treatment history. DNA will be extracted using a validated skin microbiome protocol, followed by 16S rRNA gene sequencing for bacterial profiling and ITS region sequencing for fungal communities; a subset of samples (n=40 per patient group) will undergo shallow shotgun metagenomic sequencing to infer functional capabilities. Data will be processed with established pipelines (QIIME2 for amplicon data; DADA2 for denoising; PICRUSt2 or Tax4Fun2 for functional inference; QIIME2’s diversity metrics for alpha and beta diversity). Taxonomic differential abundance will be evaluated with compositional approaches (ANCOM-II) to mitigate false positives, while multivariate testing (PERMANOVA) will assess group-level dissimilarities in microbial community structure. Differentially abundant taxa will be validated using targeted qPCR assays. Multivariable regression models will examine associations between microbial features and clinical outcomes, adjusting for confounders. Functional pathway differences will be explored using shotgun data where available, with emphasis on pathways related to keratinocyte signaling, sebaceous gland activity, and innate immune modulation. Thematic analysis will be applied to qualitative data on topical regimens and hygiene practices to contextualize microbiome variation. Anticipated findings include higher Staphylococcus and Propionibacterium-dominant profiles in acne compared with rosacea, with rosacea showing greater representation of Demodex-associated microbial signatures and inflammatory pathway enrichment. Both patient groups are expected to diverge from controls in beta diversity, with acne aligning more with sebaceous microenvironment signatures and rosacea correlating with innate immune and vasculature-related pathways. The study may reveal distinct core microbiomes for acne and rosacea and identify shared taxa that contribute to inflammatory milieu, modulated by host and environmental factors. The contribution to knowledge encompasses (i) a comprehensive, cross-disease microbiome map for acne and rosacea, (ii) methodological integration of 16S, ITS, and metagenomics tailored to dermatological contexts, and (iii) identification of microbial biomarkers and functional pathways with potential as diagnostic indicators or therapeutic targets. The findings are expected to inform precision dermatology approaches, including microbiome-informed topical formulations, adjunctive antimicrobial strategies, and personalized regimens minimizing disruption to beneficial skin commensals. The study concludes that distinct microbiome signatures underpin acne and rosacea, though overlapping microbial networks exist, underscoring the need for disease-specific microbiome modulation while recognizing shared host-microbial determinants. Recommendations include longitudinal validation, expansion to diverse ethnic populations, exploration of probiotic or microbiome-targeted therapies, and integration of host genetic data to enhance predictive accuracy.