Frontiers in microbiology · 2026
Gut microbiota profiles in pediatric atopic dermatitis and their relationship with skin microbiota: an Indonesian case-control study.
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Effendi Raden Mohamad Rendy Ariezal, Thio Hok Bing, Kraaij Robert, Murad Chrysanti, Farah Dwiyana Reiva, Suwarsa Oki, Nijsten Tamar E C, Pardo Luba M
Аннотация
INTRODUCTION: The bacterial gut microbiota has been implicated in the pathophysiology of atopic dermatitis (AD), yet most studies have focused on Western populations and have typically examined the gut or skin microbiota in isolation. Evidence for interactions between skin and gut microbiota in inflammatory skin diseases remains limited, particularly in pediatric cohorts from non-Western settings. Here, we profiled the bacterial gut microbiota in children with AD from Indonesia, and evaluated the relationship with bacterial skin microbiota using paired gut and skin samples from the same individuals.
METHODS: Skin and fecal swabs were collected from children and adolescents aged 4-18 years (111 AD cases and 107 controls) recruited from the Pediatric Dermatology Clinic of Dr. Hasan Sadikin General Hospital, an urban tertiary-care referral center in Bandung, West Java, Indonesia. Both skin and gut bacterial microbiota was profiled using 16S rRNA sequencing and bacteria were identified using DADA2 pipeline, previously published skin microbiota data from the same participants were paired with the gut microbiota data for skin-gut analyses. Alpha diversity was compared between AD cases and controls, beta diversity assessed using permutational multivariate analysis of variance (PERMANOVA) and univariable differential analysis was tested using ANCOM-BC2. In silico functional pathway analyses was performed with PICRUSt2. Correlation analysis between the bacterial gut microbiota and the skin microbiota was performed using SparXCC.
RESULTS: Gut alpha diversity did not differ between AD cases and controls, although hand feeding was associated with a higher Shannon diversity (β = 0.20; adjusted p = 0.041). Gut microbiota composition was associated with birth method, maternal education, and age, while AD status was not significant. We found differences in the composition of between Dialister invisus, Parabacteroides, Lachnospiraceae UCG-009, and Flavonifractor in AD. Furthermore, we identified 24 differentially abundant predicted pathways. CMP-8-amino-3,8-dideoxy-D-manno-octulosonate biosynthesis was more abundant in AD, while palmitoyl ethanolamide biosynthesis was more abundant in control. Correlation analysis showed modest to weak correlations between skin and gut microbiota. Fourteen skin-gut pairs showed different correlation between AD and controls. ASV70 (Staphylococcus capitis/caprae)-Butyrivibrio pair was identified as an AD-enriched associations, whereas ASV173 (Staphylococcus nepalensis)-Odoribacter was identified as control-enriched association.
CONCLUSION: Gut microbiota differences by AD were modest. ASV-level, predicted stool functional pathways, and skin-gut correlation analyses suggested selective cross-site associations.
METHODS: Skin and fecal swabs were collected from children and adolescents aged 4-18 years (111 AD cases and 107 controls) recruited from the Pediatric Dermatology Clinic of Dr. Hasan Sadikin General Hospital, an urban tertiary-care referral center in Bandung, West Java, Indonesia. Both skin and gut bacterial microbiota was profiled using 16S rRNA sequencing and bacteria were identified using DADA2 pipeline, previously published skin microbiota data from the same participants were paired with the gut microbiota data for skin-gut analyses. Alpha diversity was compared between AD cases and controls, beta diversity assessed using permutational multivariate analysis of variance (PERMANOVA) and univariable differential analysis was tested using ANCOM-BC2. In silico functional pathway analyses was performed with PICRUSt2. Correlation analysis between the bacterial gut microbiota and the skin microbiota was performed using SparXCC.
RESULTS: Gut alpha diversity did not differ between AD cases and controls, although hand feeding was associated with a higher Shannon diversity (β = 0.20; adjusted p = 0.041). Gut microbiota composition was associated with birth method, maternal education, and age, while AD status was not significant. We found differences in the composition of between Dialister invisus, Parabacteroides, Lachnospiraceae UCG-009, and Flavonifractor in AD. Furthermore, we identified 24 differentially abundant predicted pathways. CMP-8-amino-3,8-dideoxy-D-manno-octulosonate biosynthesis was more abundant in AD, while palmitoyl ethanolamide biosynthesis was more abundant in control. Correlation analysis showed modest to weak correlations between skin and gut microbiota. Fourteen skin-gut pairs showed different correlation between AD and controls. ASV70 (Staphylococcus capitis/caprae)-Butyrivibrio pair was identified as an AD-enriched associations, whereas ASV173 (Staphylococcus nepalensis)-Odoribacter was identified as control-enriched association.
CONCLUSION: Gut microbiota differences by AD were modest. ASV-level, predicted stool functional pathways, and skin-gut correlation analyses suggested selective cross-site associations.