Evidence map›Paper›PMID 36437544›Full record

ArticleSkin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)2023

Prediction and association analyses of skin phenotypes in Japanese females using genetic, environmental, and physical features.

Satoshi Amano, Tatsuya Yoshikawa, Chiaki Ito, Ikumi Mabuchi, Kumiko Kikuchi, Motoki Ooguri, Chie Yasuda

Open access · bronzeAbstract read
In one paragraph

Article in Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.3field-weighted citation impact, top 19% of its field
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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
  2. Review
  3. Prediction and association analyses of skin phenotypes in Japanese females using genetic, environmental, and physical features.Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) · 2023
    Article
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

7 authors at 2 institutions in 2 countries.

Satoshi AmanoShiseido Co. Ltd., MIRAI Technology Institute, Yokohama, Kanagawa, Japan.ORCID https://orcid.org/0000-0002-2873-8205
Tatsuya YoshikawaShiseido Co. Ltd., MIRAI Technology Institute, Yokohama, Kanagawa, Japan.
Chiaki ItoDYNACOM Co. Ltd., World Business Garden, Mihama-ku, Chiba, Japan.
Ikumi MabuchiDYNACOM Co. Ltd., World Business Garden, Mihama-ku, Chiba, Japan.
Kumiko KikuchiShiseido Co. Ltd., MIRAI Technology Institute, Yokohama, Kanagawa, Japan.
Motoki OoguriShiseido Co. Ltd., MIRAI Technology Institute, Yokohama, Kanagawa, Japan.
Chie YasudaShiseido Co. Ltd., MIRAI Technology Institute, Yokohama, Kanagawa, Japan.
Shiseido Group (Japan) · JPDeutsche Telekom (United Kingdom) · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSkin characteristics show great variation from person to person and are affected by multiple factors, including genetic, environmental, and physical factors, but details of the involvement and contributions of these factors remain unclear.

objectivesWe aimed to characterize genetic, environmental, and physical factors affecting 16 skin features by developing models to predict personal skin characteristics.

methodsWe analyzed the associations of skin phenotypes with genetic, environmental, and physical features in 1472 Japanese females aged 20-80 years. We focused on 16 skin characteristics, including melanin, brightness/lightness, yellowness, pigmented spots, wrinkles, resilience, moisture, barrier function, texture, and sebum amount. As genetic factors, we selected 74 single-nucleotide polymorphisms of genes related to skin color, vitamin level, hormones, circulation, extracellular matrix (ECM) components and ECM-degrading enzymes, inflammation, and antioxidants. Histories of ultraviolet (UV) exposure and smoking as environmental factors and age, height, and weight as physical factors were acquired by means of a questionnaire.

resultsA linear association with age was prominent for increase in the area of crow's feet, increase in number of pigmented spots, decrease in forehead sebum, and increase in VISIA wrinkle parameters. Associations were analyzed by constructing linear regression models for skin feature changes and logistic regression models to predict whether subjects show lower or higher skin measurement values in the same age groups. Multiple genetic factors, history of UV exposure and smoking, and body mass index were statistically selected for each skin characteristic. The most important association found for skin spots, such as lentigines and wrinkles, was adolescent sun exposure.

conclusionGenetic, environmental, and physical factors associated with interindividual differences of the selected skin features were identified. The developed models should be useful to predict the skin characteristics of individuals and their age-related changes.

Indexed as

Pigmentation DisordersSkin AgingAdultAgedAged, 80 and overEast Asian PeopleFemaleHumansMiddle AgedSkinSkin PigmentationYoung Adultassociation analysismultivariate analysisobesitypredictionsingle-nucleotide polymorphismskin phenotypessmokingultraviolet light

Identifiers

PMID36437544
PMCPMC9838785
OpenAlexW4310256209

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.