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Article: A microbiome-based index for assessing skin health and treatment effects for atopic dermatitis in children

TitleA microbiome-based index for assessing skin health and treatment effects for atopic dermatitis in children
Authors
KeywordsAtopic dermatitis
Personalized skin care
Skin microbiome
Spatial variation
Suboptimal health
Issue Date2019
Citation
mSystems, 2019, v. 4, n. 4, article no. e00293-19 How to Cite?
AbstractA quantitative and objective indicator for skin health via the microbiome is of great interest for personalized skin care, but differences among skin sites and across human populations can make this goal challenging. A three-city (two Chinese and one American) comparison of skin microbiota from atopic dermatitis (AD) and healthy pediatric cohorts revealed that, although city has the greatest effect size (the skin microbiome can predict the originated city with near 100% accuracy), a microbial index of skin health (MiSH) based on 25 bacterial genera can diagnose AD with 83 to 95% accuracy within each city and 86.4% accuracy across cities (area under the concentration-time curve [AUC], 0.90). Moreover, nonlesional skin sites across the bodies of AD-active children (which include shank, arm, popliteal fossa, elbow, antecubital fossa, knee, neck, and axilla) harbor a distinct but lesional state-like microbiome that features relative enrichment of Staphylococcus aureus over healthy individuals, confirming the extension of microbiome dysbiosis across body surface in AD patients. Intriguingly, pretreatment MiSH classifies children with identical AD clinical symptoms into two host types with distinct microbial diversity and treatment effects of corticosteroid therapy. These findings suggest that MiSH has the potential to diagnose AD, assess risk-prone state of skin, and predict treatment response in children across human populations. IMPORTANCE MiSH, which is based on the skin microbiome, can quantitatively assess pediatric skin health across cohorts from distinct countries over large geographic distances. Moreover, the index can identify a risk-prone skin state and compare treatment effect in children, suggesting applications in diagnosis and patient stratification.
Persistent Identifierhttp://hdl.handle.net/10722/311545
PubMed Central ID

 

DC FieldValueLanguage
dc.contributor.authorSun, Zheng-
dc.contributor.authorHuang, Shi-
dc.contributor.authorZhu, Pengfei-
dc.contributor.authorYue, Feng-
dc.contributor.authorZhao, Helen-
dc.contributor.authorYang, Ming-
dc.contributor.authorNiu, Yueqing-
dc.contributor.authorJing, Gongchao-
dc.contributor.authorSu, Xiaoquan-
dc.contributor.authorLi, Huiying-
dc.contributor.authorCallewaert, Chris-
dc.contributor.authorKnight, Rob-
dc.contributor.authorLiu, Jiquan-
dc.contributor.authorSmith, Ed-
dc.contributor.authorWei, Karl-
dc.contributor.authorXu, Jian-
dc.date.accessioned2022-03-22T11:54:11Z-
dc.date.available2022-03-22T11:54:11Z-
dc.date.issued2019-
dc.identifier.citationmSystems, 2019, v. 4, n. 4, article no. e00293-19-
dc.identifier.urihttp://hdl.handle.net/10722/311545-
dc.description.abstractA quantitative and objective indicator for skin health via the microbiome is of great interest for personalized skin care, but differences among skin sites and across human populations can make this goal challenging. A three-city (two Chinese and one American) comparison of skin microbiota from atopic dermatitis (AD) and healthy pediatric cohorts revealed that, although city has the greatest effect size (the skin microbiome can predict the originated city with near 100% accuracy), a microbial index of skin health (MiSH) based on 25 bacterial genera can diagnose AD with 83 to 95% accuracy within each city and 86.4% accuracy across cities (area under the concentration-time curve [AUC], 0.90). Moreover, nonlesional skin sites across the bodies of AD-active children (which include shank, arm, popliteal fossa, elbow, antecubital fossa, knee, neck, and axilla) harbor a distinct but lesional state-like microbiome that features relative enrichment of Staphylococcus aureus over healthy individuals, confirming the extension of microbiome dysbiosis across body surface in AD patients. Intriguingly, pretreatment MiSH classifies children with identical AD clinical symptoms into two host types with distinct microbial diversity and treatment effects of corticosteroid therapy. These findings suggest that MiSH has the potential to diagnose AD, assess risk-prone state of skin, and predict treatment response in children across human populations. IMPORTANCE MiSH, which is based on the skin microbiome, can quantitatively assess pediatric skin health across cohorts from distinct countries over large geographic distances. Moreover, the index can identify a risk-prone skin state and compare treatment effect in children, suggesting applications in diagnosis and patient stratification.-
dc.languageeng-
dc.relation.ispartofmSystems-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectAtopic dermatitis-
dc.subjectPersonalized skin care-
dc.subjectSkin microbiome-
dc.subjectSpatial variation-
dc.subjectSuboptimal health-
dc.titleA microbiome-based index for assessing skin health and treatment effects for atopic dermatitis in children-
dc.typeArticle-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1128/mSystems.00293-19-
dc.identifier.pmid31431508-
dc.identifier.pmcidPMC6702293-
dc.identifier.scopuseid_2-s2.0-85071030870-
dc.identifier.volume4-
dc.identifier.issue4-
dc.identifier.spagearticle no. e00293-19-
dc.identifier.epagearticle no. e00293-19-
dc.identifier.eissn2379-5077-

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