A Microbiome-Based Index for Assessing Skin Health and Treatment Effects for Atopic Dermatitis in Children

ABSTRACT A 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...

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Autores principales:	Zheng Sun, Shi Huang, Pengfei Zhu, Feng Yue, Helen Zhao, Ming Yang, Yueqing Niu, Gongchao Jing, Xiaoquan Su, Huiying Li, Chris Callewaert, Rob Knight, Jiquan Liu, Ed Smith, Karl Wei, Jian Xu
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2019
Materias:	atopic dermatitis personalized skin care skin microbiome spatial variation suboptimal health Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/0f00ca1fdb7246819e2f4a05af0d669a
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spelling	oai:doaj.org-article:0f00ca1fdb7246819e2f4a05af0d669a2021-12-02T18:44:37ZA Microbiome-Based Index for Assessing Skin Health and Treatment Effects for Atopic Dermatitis in Children10.1128/mSystems.00293-192379-5077https://doaj.org/article/0f00ca1fdb7246819e2f4a05af0d669a2019-08-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mSystems.00293-19https://doaj.org/toc/2379-5077ABSTRACT A 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.Zheng SunShi HuangPengfei ZhuFeng YueHelen ZhaoMing YangYueqing NiuGongchao JingXiaoquan SuHuiying LiChris CallewaertRob KnightJiquan LiuEd SmithKarl WeiJian XuAmerican Society for Microbiologyarticleatopic dermatitispersonalized skin careskin microbiomespatial variationsuboptimal healthMicrobiologyQR1-502ENmSystems, Vol 4, Iss 4 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	atopic dermatitis personalized skin care skin microbiome spatial variation suboptimal health Microbiology QR1-502
spellingShingle	atopic dermatitis personalized skin care skin microbiome spatial variation suboptimal health Microbiology QR1-502 Zheng Sun Shi Huang Pengfei Zhu Feng Yue Helen Zhao Ming Yang Yueqing Niu Gongchao Jing Xiaoquan Su Huiying Li Chris Callewaert Rob Knight Jiquan Liu Ed Smith Karl Wei Jian Xu A Microbiome-Based Index for Assessing Skin Health and Treatment Effects for Atopic Dermatitis in Children
description	ABSTRACT A 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.
format	article
author	Zheng Sun Shi Huang Pengfei Zhu Feng Yue Helen Zhao Ming Yang Yueqing Niu Gongchao Jing Xiaoquan Su Huiying Li Chris Callewaert Rob Knight Jiquan Liu Ed Smith Karl Wei Jian Xu
author_facet	Zheng Sun Shi Huang Pengfei Zhu Feng Yue Helen Zhao Ming Yang Yueqing Niu Gongchao Jing Xiaoquan Su Huiying Li Chris Callewaert Rob Knight Jiquan Liu Ed Smith Karl Wei Jian Xu
author_sort	Zheng Sun
title	A Microbiome-Based Index for Assessing Skin Health and Treatment Effects for Atopic Dermatitis in Children
title_short	A Microbiome-Based Index for Assessing Skin Health and Treatment Effects for Atopic Dermatitis in Children
title_full	A Microbiome-Based Index for Assessing Skin Health and Treatment Effects for Atopic Dermatitis in Children
title_fullStr	A Microbiome-Based Index for Assessing Skin Health and Treatment Effects for Atopic Dermatitis in Children
title_full_unstemmed	A Microbiome-Based Index for Assessing Skin Health and Treatment Effects for Atopic Dermatitis in Children
title_sort	microbiome-based index for assessing skin health and treatment effects for atopic dermatitis in children
publisher	American Society for Microbiology
publishDate	2019
url	https://doaj.org/article/0f00ca1fdb7246819e2f4a05af0d669a
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A Microbiome-Based Index for Assessing Skin Health and Treatment Effects for Atopic Dermatitis in Children

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