AUTHOR=Pinto Daniela , Calabrese Francesco Maria , De Angelis Maria , Celano Giuseppe , Giuliani Giammaria , Gobbetti Marco , Rinaldi Fabio 

TITLE=Predictive Metagenomic Profiling, Urine Metabolomics, and Human Marker Gene Expression as an Integrated Approach to Study Alopecia Areata

JOURNAL=Frontiers in Cellular and Infection Microbiology

VOLUME=Volume 10 - 2020

YEAR=2020

URL=https://www.frontiersin.org/journals/cellular-and-infection-microbiology/articles/10.3389/fcimb.2020.00146

DOI=10.3389/fcimb.2020.00146

ISSN=2235-2988

ABSTRACT=The involvement of microbiome in many different scalp conditions has been investigated over the years. The study of scalp microbiome in specific diseases such as those involving hair growth alterations i.e. no cicatricial (AGA, AA) and cicatricial alopecia Lichen Plano Pilaris (LPP) is of major importance. In the present work we highlighted the differences in microbial populations inhabiting the scalp of AA subjects compared to a healthy sample cohort. The significant differences in genera abundances (p<0.05) were found in hypodermis and, especially in dermis layer. Starting from 16S sequencing data, we explored the differences in predicted KEGG pathways and we obtained some significant difference in predicted pathways related to AA pathologic condition such as flagellar, assembly, bacterial chemotaxis, mineral absorption, ABC transporters, cellular antigens, glycosaminoglycan degradation, lysosome, sphingolipid metabolism, cell division, protein digestion and absorption, energy metabolism. All predicted pathways were found as significantly higher in AA than in healthy samples with the  only two exceptions dealt with “mineral absorption” and “ABC transporters”. 
We also determined the expression of TNF-α, FAS, KCNA3, NOD-2 and SOD-2 genes and we determined, by mean of Pearson’s correlation analysis, the relationships between human gene expression levels analyzed and microbiome composition and both positive and negative correlations were found. Finally we inspected VOM profiles in urinary samples and we detected statistically significant differences when comparing AA and healthy subjects. This multiple approach highlighted potential traits associated with the Alopecia areata and their relationship with microbiota inhabiting the scalp.