A Microbiome-Based Index for Assessing Skin Health and Treatment Effects for Atopic Dermatitis in Children
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
Affiliations
Zheng Sun
Single-Cell Center and Shandong Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China
Shi Huang
Single-Cell Center and Shandong Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China
Pengfei Zhu
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
Procter & Gamble Beijing Innovation Center, Beijing, China
Helen Zhao
Procter & Gamble Singapore Innovation Center, Singapore, Singapore
Ming Yang
Office of General Affairs, Chinese Academy of Sciences, Beijing, China
Yueqing Niu
Procter & Gamble Beijing Innovation Center, Beijing, China
Gongchao Jing
Single-Cell Center and Shandong Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China
Xiaoquan Su
Single-Cell Center and Shandong Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China
Huiying Li
Department of Molecular and Medical Pharmacology, University of California at Los Angeles, Los Angeles, California, USA
Chris Callewaert
Center for Microbiome Innovation and Departments of Pediatrics, University of California at San Diego, La Jolla, California, USA
Rob Knight
Center for Microbiome Innovation and Departments of Pediatrics, University of California at San Diego, La Jolla, California, USA
Jiquan Liu
Procter & Gamble Singapore Innovation Center, Singapore, Singapore
Ed Smith
Procter & Gamble Mason Business Center, Mason, Ohio, USA
Karl Wei
Procter & Gamble Mason Business Center, Mason, Ohio, USA
Jian Xu
Single-Cell Center and Shandong Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China
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.
