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Updated: Jan 8, 2026
Noninvasive Sampling of Mucosal Lining Fluid for the Quantification of In Vivo Upper Airway Immune-mediator Levels
Published on: August 7, 2017
Environmental and skin-nasal microbiome variation in South African children with atopic dermatitis
Yang Chen1,2,3, Anna Dan Nguyen1,4, Nonhlanhla Lunjani5,6
1Dept. of Dermatology, University of California San Diego (UCSD), La Jolla, CA, USA.
Background:
Atopic dermatitis (AD) in early childhood is associated with microbial dysbiosis. Skin and nasal microbiomes have been linked to AD severity; this relationship has not yet been studied in an African cohort. Here, we aimed to explore how urban and rural stratification, disease severity, and inter-site bacterial overlap shape the skin and nasal microbiomes of South African children with AD.
Methods:
Children were recruited from urban Cape Town (CT) and rural Umtata (UM), South Africa. We profiled the skin and nasal microbiomes of 183 children (84 healthy controls and 99 with AD; ages 9-37 months), totaling 462 samples, including both lesional and non-lesional skin sites in children with AD, in a cross-sectional study design. Using 16S rRNA V4-V5 sequencing for its accessibility, we applied random forest (RF) models to classify AD status based on amplicon sequence variants (ASVs) and analyzed microbiome composition and diversity by region.
Results:
We found that RF models could predict AD status using both skin and nasal microbiomes (AUCs: skin = 0.69-0.79; nasal = 0.65), strongly driven by both Streptococcus and Staphylococcus. The correlations between skin and nasal microbiomes were significantly stronger in children with AD compared to controls, with higher correlations observed in rural UM (healthy r = 0.45 to AD r = 0.67) compared to urban CT (healthy r = 0.27 to AD r = 0.65). The skin microbiome diversity was higher in children from rural UM with healthy skin than in those from urban CT (p = 0.004). However, children with AD in both groups showed significant alterations in their microbiome, with those in rural UM exhibiting greater beta diversity changes (p = 0.001-0.002) than their urban CT counterparts (p = 0.002-0.349).
Conclusion:
In South African children with AD, skin-nasal microbiomes reflect shared reservoirs, and differences in the AD microbiome were observed between environmental regions. These findings highlight the need for geographically diverse studies incorporating skin and mucocutaneous sampling to better understand pediatric AD.
