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

atopic dermatitis personalized skin care skin microbiome spatial variation suboptimal health

Journal

mSystems
ISSN: 2379-5077
Titre abrégé: mSystems
Pays: United States
ID NLM: 101680636

Informations de publication

Date de publication:
20 Aug 2019
Historique:
entrez: 22 8 2019
pubmed: 23 8 2019
medline: 23 8 2019
Statut: epublish

Résumé

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

Identifiants

pubmed: 31431508
pii: 4/4/e00293-19
doi: 10.1128/mSystems.00293-19
pmc: PMC6702293
pii:
doi:

Types de publication

Journal Article

Langues

eng

Informations de copyright

Copyright © 2019 Sun et al.

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Auteurs

Zheng Sun (Z)

Single-Cell Center and Shandong Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China.
University of Chinese Academy of Sciences, Beijing, China.

Shi Huang (S)

Single-Cell Center and Shandong Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China.
University of Chinese Academy of Sciences, Beijing, China.

Pengfei Zhu (P)

Single-Cell Center and Shandong Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China.

Feng Yue (F)

Procter & Gamble Beijing Innovation Center, Beijing, China.

Helen Zhao (H)

Procter & Gamble Singapore Innovation Center, Singapore, Singapore.

Ming Yang (M)

Office of General Affairs, Chinese Academy of Sciences, Beijing, China.

Yueqing Niu (Y)

Procter & Gamble Beijing Innovation Center, Beijing, China.

Gongchao Jing (G)

Single-Cell Center and Shandong Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China.
University of Chinese Academy of Sciences, Beijing, China.

Xiaoquan Su (X)

Single-Cell Center and Shandong Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China.
University of Chinese Academy of Sciences, Beijing, China.

Huiying Li (H)

Department of Molecular and Medical Pharmacology, University of California at Los Angeles, Los Angeles, California, USA.

Chris Callewaert (C)

Center for Microbiome Innovation and Departments of Pediatrics, University of California at San Diego, La Jolla, California, USA.
Center for Microbial Ecology and Technology, Ghent University, Ghent, Belgium.

Rob Knight (R)

Center for Microbiome Innovation and Departments of Pediatrics, University of California at San Diego, La Jolla, California, USA.

Jiquan Liu (J)

Procter & Gamble Singapore Innovation Center, Singapore, Singapore.

Ed Smith (E)

Procter & Gamble Mason Business Center, Mason, Ohio, USA.

Karl Wei (K)

Procter & Gamble Mason Business Center, Mason, Ohio, USA.

Jian Xu (J)

Single-Cell Center and Shandong Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China xujian@qibebt.ac.cn.
University of Chinese Academy of Sciences, Beijing, China.

Classifications MeSH