ArticleMicroorganisms2025
Comparative Analysis of Bacteriome in Hair Follicle Layers of Patients with Female Pattern Androgenic Alopecia.
Article in Microorganisms, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Scalp Microbiome Alterations in Androgenetic Alopecia: Patterns and Emerging Mechanistic Insights.International journal of dermatology · 2026Review
- The Scalp Microbiome-Hair Axis: Mechanisms and Therapeutic Translation.Research (Washington, D.C.) · 2026Review
- Novel Strategies for Androgenetic Alopecia Therapy: Integrating Multifunctional Plant Extracts with Nanotechnology for Advanced Cutaneous Drug Delivery.Pharmaceutics · 2025Review
Corrections and comments
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Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Androgenetic alopecia (AGA) is the most common form of patterned hair loss, exhibiting gender-specific clinical features. Recent studies highlight the importance of the skin microbiome in maintaining skin health, but the relationship between the hair follicle microbiome and hair loss, particularly AGA, remains understudied. Hair follicle layer samples were collected directly from the crown region of female pattern hair loss (FPHL), male pattern hair loss (MPHL), and healthy adult women (control) groups. Microbial DNA was extracted and analyzed using Illumina 16S rRNA V3-V4 gene amplicon sequencing. Alpha-diversity and beta-diversity analyses and taxonomic and functional profiling were conducted through relative abundance, LEfSe, and PICRUSt2 analyses. The alpha-diversity analysis showed a significant decrease in microbial richness in the hair loss groups. Unweighted UniFrac-based beta-diversity analysis revealed significant clustering between the control group and the FPHL group. Taxonomic profiling and LEfSe analysis identified differences in microbial composition and biomarkers. PICRUSt2 analysis further revealed altered pathways related to porphyrin metabolism, fatty acid biosynthesis, and steroid hormone metabolism. Additionally, differences in microbiome composition and potential functions were found between the FPHL and MPHL groups. This study provides comprehensive insights into the hair follicle microbiome, revealing unique microbial patterns and functional alterations associated with FPHL. Understanding these microbiome characteristics may contribute to targeted approaches for addressing AGA. Further research is warranted.
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