Evidence map›Paper›PMID 31431508›Full record

ArticlemSystems2019

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 and 6 more

Abstract read
In one paragraph

Article in mSystems, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. The inner elbow skin microbiome containsMicrobiome research reports · 2024
    Article
  6. Article
  7. Article
  8. Review
  9. [The skin microbiome-useful for diagnosis and therapy?]Der Hautarzt; Zeitschrift fur Dermatologie, Venerologie, und verwandte Gebiete · 2021
    Review
  10. Article
  11. Review
  12. Review
  13. Review
  14. Efficacy ofGut microbes
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

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 ZhuSingle-Cell Center and Shandong Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China.
Feng YueProcter & Gamble Beijing Innovation Center, Beijing, China.
Helen ZhaoProcter & Gamble Singapore Innovation Center, Singapore, Singapore.
Ming YangOffice of General Affairs, Chinese Academy of Sciences, Beijing, China.
Yueqing NiuProcter & Gamble Beijing Innovation Center, Beijing, China.
Gongchao JingSingle-Cell Center and Shandong Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China.
Xiaoquan SuSingle-Cell Center and Shandong Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China.
Huiying LiDepartment of Molecular and Medical Pharmacology, University of California at Los Angeles, Los Angeles, California, USA.
Chris CallewaertCenter for Microbiome Innovation and Departments of Pediatrics, University of California at San Diego, La Jolla, California, USA.
Rob KnightCenter for Microbiome Innovation and Departments of Pediatrics, University of California at San Diego, La Jolla, California, USA.
Jiquan LiuProcter & Gamble Singapore Innovation Center, Singapore, Singapore.
Ed SmithProcter & Gamble Mason Business Center, Mason, Ohio, USA.
Karl WeiProcter & Gamble Mason Business Center, Mason, Ohio, USA.
Jian XuSingle-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.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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

Indexed as

atopic dermatitispersonalized skin careskin microbiomespatial variationsuboptimal health

Identifiers

PMID31431508
PMCPMC6702293

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.