Development of a skin microbiome diagnostic method to assess skin condition in healthy individuals: Application of research on skin microbiomes and skin condition
Objective Skin microbiomes vary across individuals. They are known to play essential roles in maintaining homeostasis and preventing infectious pathogens. In recent years, cosmetic product development has begun to focus on the relationship between skin microbiomes and skin conditions. However, the s...
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| Veröffentlicht in: | International journal of cosmetic science 2021-12, Vol.43 (6), p.677-690 |
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| creator | Kotakeyama, Yuki Nakamura, Rie Kurosawa, Masaharu Ota, Seiko Suzuki, Ruka Nakanishi, Miki Kanno, Kohei Watanabe, Kosuke Ishitsuka, Yukiko |
| description | Objective
Skin microbiomes vary across individuals. They are known to play essential roles in maintaining homeostasis and preventing infectious pathogens. In recent years, cosmetic product development has begun to focus on the relationship between skin microbiomes and skin conditions. However, the statistical methods used in many studies include the standard t‐test and small‐scale correlation analysis, which do not take into account the internal correlation structure in data on skin microbiomes and skin features. In this study, we aimed to understand the relationship between skin microbiomes and skin features by analysing complex microbiomes and skin data.
Methods
We obtained data on 19 skin characteristics and skin microbiomes based on 16s ribosomal RNA (16S rRNA) gene analysis of 276 healthy Japanese women. We then performed the principal component analysis (PCA), a method that takes into account the internal correlation structure, on 234 panels of them that did not contain outliers or missing values. We confirmed the relationship between skin microbiomes and skin features with principal component regression analysis and hierarchical clustering analysis (HCA).
Results
The principal component regression analysis showed strong relationships between skin microbiomes and sebum‐related skin characteristics and skin pH. In the HCA, the female panel was classified into two major groups based on the skin microbiome. Furthermore, there were significant differences in sebum‐related skin characteristics and the way skin condition changes with ageing between those groups, suggesting the possibility of measuring skin condition and age‐related skin risk based on microbiome data. In addition, sebum‐related characteristics differed significantly among middle‐aged participants, suggesting a strong relationship between skin microbiomes and sebum‐related characteristics.
Conclusion
Analysis of skin condition and skin microbiome in Japanese women, taking into account the correlation between variables, showed that skin microbiome was significantly related to the number of pores and the amount of sebum. Furthermore, it was suggested that the skin condition and the way the skin condition changes with ageing may differ depending on the type of skin microbiome. The finding of a relationship between skin condition and skin microbiome suggests the possibility of proposing a new beauty method focusing on the skin microbiome in the future.
Résumé
Objectif
Les microbiomes de la peau |
| doi_str_mv | 10.1111/ics.12744 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2583444231</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2609205809</sourcerecordid><originalsourceid>FETCH-LOGICAL-c4194-49cbc05391db11717d91f6ddbd619cf4e15fa2155d9770b6f7081c69095aa6c3</originalsourceid><addsrcrecordid>eNp1kcFu1DAQhi0EotvCgRdAlrjQQ1pP4jgxt2qhpVIlDvRuOfaEdUnikEmK9nX6pJim9LASvoxH-vTNjH7G3oE4g_TOg6MzyCspX7ANSFVnudTyJdsIkHlWSlUcsWOiOyGE1HXxmh0VUilZCLFhD5_xHrs49jjMPLbccvoZBt4HN8UmxB65D_bHEGkOjvc476Lnc-SWCIlW1sXBhznEgadmh7abd_v09eE--MV29IlfjGMXnH1k0owJCe3kdjy1B9OI28EfaN-wV23S4NunesJuL7_cbr9mN9-urrcXN5mToGUmtWucKAsNvgGooPIaWuV94xVo10qEsrU5lKXXVSUa1VaiBqe00KW1yhUn7OOqHaf4a0GaTR_IYdfZAeNCJi_rQkqZF5DQDwfoXVymIS1nciV0Lspa6ESdrlQ6jmjC1oxT6O20NyDM39xMys085pbY90_GpenRP5P_gkrA-Qr8Dh3u_28y19vvq_IPwQGkag</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2609205809</pqid></control><display><type>article</type><title>Development of a skin microbiome diagnostic method to assess skin condition in healthy individuals: Application of research on skin microbiomes and skin condition</title><source>MEDLINE</source><source>Wiley Online Library Journals Frontfile Complete</source><creator>Kotakeyama, Yuki ; Nakamura, Rie ; Kurosawa, Masaharu ; Ota, Seiko ; Suzuki, Ruka ; Nakanishi, Miki ; Kanno, Kohei ; Watanabe, Kosuke ; Ishitsuka, Yukiko</creator><creatorcontrib>Kotakeyama, Yuki ; Nakamura, Rie ; Kurosawa, Masaharu ; Ota, Seiko ; Suzuki, Ruka ; Nakanishi, Miki ; Kanno, Kohei ; Watanabe, Kosuke ; Ishitsuka, Yukiko</creatorcontrib><description>Objective
Skin microbiomes vary across individuals. They are known to play essential roles in maintaining homeostasis and preventing infectious pathogens. In recent years, cosmetic product development has begun to focus on the relationship between skin microbiomes and skin conditions. However, the statistical methods used in many studies include the standard t‐test and small‐scale correlation analysis, which do not take into account the internal correlation structure in data on skin microbiomes and skin features. In this study, we aimed to understand the relationship between skin microbiomes and skin features by analysing complex microbiomes and skin data.
Methods
We obtained data on 19 skin characteristics and skin microbiomes based on 16s ribosomal RNA (16S rRNA) gene analysis of 276 healthy Japanese women. We then performed the principal component analysis (PCA), a method that takes into account the internal correlation structure, on 234 panels of them that did not contain outliers or missing values. We confirmed the relationship between skin microbiomes and skin features with principal component regression analysis and hierarchical clustering analysis (HCA).
Results
The principal component regression analysis showed strong relationships between skin microbiomes and sebum‐related skin characteristics and skin pH. In the HCA, the female panel was classified into two major groups based on the skin microbiome. Furthermore, there were significant differences in sebum‐related skin characteristics and the way skin condition changes with ageing between those groups, suggesting the possibility of measuring skin condition and age‐related skin risk based on microbiome data. In addition, sebum‐related characteristics differed significantly among middle‐aged participants, suggesting a strong relationship between skin microbiomes and sebum‐related characteristics.
Conclusion
Analysis of skin condition and skin microbiome in Japanese women, taking into account the correlation between variables, showed that skin microbiome was significantly related to the number of pores and the amount of sebum. Furthermore, it was suggested that the skin condition and the way the skin condition changes with ageing may differ depending on the type of skin microbiome. The finding of a relationship between skin condition and skin microbiome suggests the possibility of proposing a new beauty method focusing on the skin microbiome in the future.
Résumé
Objectif
Les microbiomes de la peau varient selon les individus. Ils sont connus pour jouer des rôles essentiels dans le maintien de l'homéostasie et la prévention des agents pathogènes infectieux. Ces dernières années, le développement de produits cosmétiques a commencé à se concentrer sur la relation entre les microbiomes cutanés et les conditions de la peau. Cependant, les méthodes statistiques utilisées dans de nombreuses études comprennent le t‐test standard et l'analyse de corrélation à petite échelle, qui ne tiennent pas compte de la structure de corrélation interne dans les données sur les microbiomes cutanés et les caractéristiques de la peau. Dans cette étude, nous avons cherché à comprendre la relation entre les microbiomes cutanés et les caractéristiques de la peau en analysant des données complexes sur les microbiomes et la peau.
Méthodes
Nous avons obtenu des données sur 19 caractéristiques de la peau et sur les microbiomes cutanés à partir de l'analyse du gène de l'ARNr 16S (16S rRNA) de 276 femmes japonaises en bonne santé. Nous avons ensuite effectué l'analyse en composantes principales (PCA: principal component analysis), une méthode qui prend en compte la structure de corrélation interne, sur 234 d'entre elles qui ne contenaient pas de valeurs aberrantes ou manquantes. Nous avons confirmé la relation entre les microbiomes cutanés et les caractéristiques de la peau à l'aide d'une analyse de régression en composantes principales et d'une analyse de regroupement hiérarchique (HCA: hierarchical clustering analysis).
Résultats
L'analyse de régression en composantes principales a montré des relations fortes entre les microbiomes cutanés et les caractéristiques de la peau liées au sébum et au pH de la peau. Dans l'étude HCA, le panel de femmes a été classé en deux grands groupes sur la base du microbiome cutané. En outre, il y avait des différences significatives dans les caractéristiques de la peau liées au sébum et dans la façon dont l'état de la peau change avec l'âge entre ces groupes, ce qui suggère la possibilité de mesurer l'état de la peau et le risque cutané lié à l'âge à partir des données du microbiome. En outre, les caractéristiques liées au sébum différaient de manière significative chez les participants d'âge moyen, ce qui suggère une forte relation entre les microbiomes cutanés et les caractéristiques liées au sébum.
Conclusion
L'analyse de l'état de la peau et du microbiome cutané chez les femmes japonaises, en tenant compte de la corrélation entre les variables, a montré que le microbiome cutané était significativement lié au nombre de pores et à la quantité de sébum. En outre, il a été suggéré que l'état de la peau et la façon dont l'état de la peau évolue avec le vieillissement peuvent différer en fonction du type de microbiome cutané. La découverte d'une relation entre l'état de la peau et le microbiome cutané suggère la possibilité de proposer à l'avenir une nouvelle méthode de beauté axée sur le microbiome cutané.
Hierarchical clustering analysis revealed that the panel of Japanese women could be classified into two major groups according to their skin microbiome. Furthermore, these two groups differed in their skin conditions and in the way their skin conditions changed with age. The results suggest the possibility of estimating skin condition and skin risk based on skin microbiome.</description><identifier>ISSN: 0142-5463</identifier><identifier>EISSN: 1468-2494</identifier><identifier>DOI: 10.1111/ics.12744</identifier><identifier>PMID: 34664300</identifier><language>eng</language><publisher>England: Wiley Subscription Services, Inc</publisher><subject>Adult ; Aged ; Aged, 80 and over ; Aging ; Cluster analysis ; Clustering ; Correlation analysis ; Female ; Healthy Volunteers ; Homeostasis ; Humans ; Microbiology ; microbiology (skin)/preservation (products) ; Microbiomes ; Microbiota - physiology ; Middle Aged ; Outliers (statistics) ; pH effects ; Pores ; Principal components analysis ; Product development ; Regression analysis ; rRNA 16S ; Sebum - microbiology ; Skin ; Skin - microbiology ; skin physiology/structure ; skin repair/acne/rosacea/dandruff/striae ; Statistical analysis ; Statistical methods ; statistics ; Young Adult</subject><ispartof>International journal of cosmetic science, 2021-12, Vol.43 (6), p.677-690</ispartof><rights>2021 Society of Cosmetic Scientists and the Société Française de Cosmétologie</rights><rights>2021 Society of Cosmetic Scientists and the Société Française de Cosmétologie.</rights><rights>Copyright © 2021 Society of Cosmetic Scientists and the Société Française de Cosmétologie</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4194-49cbc05391db11717d91f6ddbd619cf4e15fa2155d9770b6f7081c69095aa6c3</citedby><cites>FETCH-LOGICAL-c4194-49cbc05391db11717d91f6ddbd619cf4e15fa2155d9770b6f7081c69095aa6c3</cites><orcidid>0000-0002-3775-5840</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fics.12744$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fics.12744$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27903,27904,45553,45554</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34664300$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Kotakeyama, Yuki</creatorcontrib><creatorcontrib>Nakamura, Rie</creatorcontrib><creatorcontrib>Kurosawa, Masaharu</creatorcontrib><creatorcontrib>Ota, Seiko</creatorcontrib><creatorcontrib>Suzuki, Ruka</creatorcontrib><creatorcontrib>Nakanishi, Miki</creatorcontrib><creatorcontrib>Kanno, Kohei</creatorcontrib><creatorcontrib>Watanabe, Kosuke</creatorcontrib><creatorcontrib>Ishitsuka, Yukiko</creatorcontrib><title>Development of a skin microbiome diagnostic method to assess skin condition in healthy individuals: Application of research on skin microbiomes and skin condition</title><title>International journal of cosmetic science</title><addtitle>Int J Cosmet Sci</addtitle><description>Objective
Skin microbiomes vary across individuals. They are known to play essential roles in maintaining homeostasis and preventing infectious pathogens. In recent years, cosmetic product development has begun to focus on the relationship between skin microbiomes and skin conditions. However, the statistical methods used in many studies include the standard t‐test and small‐scale correlation analysis, which do not take into account the internal correlation structure in data on skin microbiomes and skin features. In this study, we aimed to understand the relationship between skin microbiomes and skin features by analysing complex microbiomes and skin data.
Methods
We obtained data on 19 skin characteristics and skin microbiomes based on 16s ribosomal RNA (16S rRNA) gene analysis of 276 healthy Japanese women. We then performed the principal component analysis (PCA), a method that takes into account the internal correlation structure, on 234 panels of them that did not contain outliers or missing values. We confirmed the relationship between skin microbiomes and skin features with principal component regression analysis and hierarchical clustering analysis (HCA).
Results
The principal component regression analysis showed strong relationships between skin microbiomes and sebum‐related skin characteristics and skin pH. In the HCA, the female panel was classified into two major groups based on the skin microbiome. Furthermore, there were significant differences in sebum‐related skin characteristics and the way skin condition changes with ageing between those groups, suggesting the possibility of measuring skin condition and age‐related skin risk based on microbiome data. In addition, sebum‐related characteristics differed significantly among middle‐aged participants, suggesting a strong relationship between skin microbiomes and sebum‐related characteristics.
Conclusion
Analysis of skin condition and skin microbiome in Japanese women, taking into account the correlation between variables, showed that skin microbiome was significantly related to the number of pores and the amount of sebum. Furthermore, it was suggested that the skin condition and the way the skin condition changes with ageing may differ depending on the type of skin microbiome. The finding of a relationship between skin condition and skin microbiome suggests the possibility of proposing a new beauty method focusing on the skin microbiome in the future.
Résumé
Objectif
Les microbiomes de la peau varient selon les individus. Ils sont connus pour jouer des rôles essentiels dans le maintien de l'homéostasie et la prévention des agents pathogènes infectieux. Ces dernières années, le développement de produits cosmétiques a commencé à se concentrer sur la relation entre les microbiomes cutanés et les conditions de la peau. Cependant, les méthodes statistiques utilisées dans de nombreuses études comprennent le t‐test standard et l'analyse de corrélation à petite échelle, qui ne tiennent pas compte de la structure de corrélation interne dans les données sur les microbiomes cutanés et les caractéristiques de la peau. Dans cette étude, nous avons cherché à comprendre la relation entre les microbiomes cutanés et les caractéristiques de la peau en analysant des données complexes sur les microbiomes et la peau.
Méthodes
Nous avons obtenu des données sur 19 caractéristiques de la peau et sur les microbiomes cutanés à partir de l'analyse du gène de l'ARNr 16S (16S rRNA) de 276 femmes japonaises en bonne santé. Nous avons ensuite effectué l'analyse en composantes principales (PCA: principal component analysis), une méthode qui prend en compte la structure de corrélation interne, sur 234 d'entre elles qui ne contenaient pas de valeurs aberrantes ou manquantes. Nous avons confirmé la relation entre les microbiomes cutanés et les caractéristiques de la peau à l'aide d'une analyse de régression en composantes principales et d'une analyse de regroupement hiérarchique (HCA: hierarchical clustering analysis).
Résultats
L'analyse de régression en composantes principales a montré des relations fortes entre les microbiomes cutanés et les caractéristiques de la peau liées au sébum et au pH de la peau. Dans l'étude HCA, le panel de femmes a été classé en deux grands groupes sur la base du microbiome cutané. En outre, il y avait des différences significatives dans les caractéristiques de la peau liées au sébum et dans la façon dont l'état de la peau change avec l'âge entre ces groupes, ce qui suggère la possibilité de mesurer l'état de la peau et le risque cutané lié à l'âge à partir des données du microbiome. En outre, les caractéristiques liées au sébum différaient de manière significative chez les participants d'âge moyen, ce qui suggère une forte relation entre les microbiomes cutanés et les caractéristiques liées au sébum.
Conclusion
L'analyse de l'état de la peau et du microbiome cutané chez les femmes japonaises, en tenant compte de la corrélation entre les variables, a montré que le microbiome cutané était significativement lié au nombre de pores et à la quantité de sébum. En outre, il a été suggéré que l'état de la peau et la façon dont l'état de la peau évolue avec le vieillissement peuvent différer en fonction du type de microbiome cutané. La découverte d'une relation entre l'état de la peau et le microbiome cutané suggère la possibilité de proposer à l'avenir une nouvelle méthode de beauté axée sur le microbiome cutané.
Hierarchical clustering analysis revealed that the panel of Japanese women could be classified into two major groups according to their skin microbiome. Furthermore, these two groups differed in their skin conditions and in the way their skin conditions changed with age. The results suggest the possibility of estimating skin condition and skin risk based on skin microbiome.</description><subject>Adult</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Aging</subject><subject>Cluster analysis</subject><subject>Clustering</subject><subject>Correlation analysis</subject><subject>Female</subject><subject>Healthy Volunteers</subject><subject>Homeostasis</subject><subject>Humans</subject><subject>Microbiology</subject><subject>microbiology (skin)/preservation (products)</subject><subject>Microbiomes</subject><subject>Microbiota - physiology</subject><subject>Middle Aged</subject><subject>Outliers (statistics)</subject><subject>pH effects</subject><subject>Pores</subject><subject>Principal components analysis</subject><subject>Product development</subject><subject>Regression analysis</subject><subject>rRNA 16S</subject><subject>Sebum - microbiology</subject><subject>Skin</subject><subject>Skin - microbiology</subject><subject>skin physiology/structure</subject><subject>skin repair/acne/rosacea/dandruff/striae</subject><subject>Statistical analysis</subject><subject>Statistical methods</subject><subject>statistics</subject><subject>Young Adult</subject><issn>0142-5463</issn><issn>1468-2494</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1kcFu1DAQhi0EotvCgRdAlrjQQ1pP4jgxt2qhpVIlDvRuOfaEdUnikEmK9nX6pJim9LASvoxH-vTNjH7G3oE4g_TOg6MzyCspX7ANSFVnudTyJdsIkHlWSlUcsWOiOyGE1HXxmh0VUilZCLFhD5_xHrs49jjMPLbccvoZBt4HN8UmxB65D_bHEGkOjvc476Lnc-SWCIlW1sXBhznEgadmh7abd_v09eE--MV29IlfjGMXnH1k0owJCe3kdjy1B9OI28EfaN-wV23S4NunesJuL7_cbr9mN9-urrcXN5mToGUmtWucKAsNvgGooPIaWuV94xVo10qEsrU5lKXXVSUa1VaiBqe00KW1yhUn7OOqHaf4a0GaTR_IYdfZAeNCJi_rQkqZF5DQDwfoXVymIS1nciV0Lspa6ESdrlQ6jmjC1oxT6O20NyDM39xMys085pbY90_GpenRP5P_gkrA-Qr8Dh3u_28y19vvq_IPwQGkag</recordid><startdate>202112</startdate><enddate>202112</enddate><creator>Kotakeyama, Yuki</creator><creator>Nakamura, Rie</creator><creator>Kurosawa, Masaharu</creator><creator>Ota, Seiko</creator><creator>Suzuki, Ruka</creator><creator>Nakanishi, Miki</creator><creator>Kanno, Kohei</creator><creator>Watanabe, Kosuke</creator><creator>Ishitsuka, Yukiko</creator><general>Wiley Subscription Services, Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QR</scope><scope>7U7</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>P64</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-3775-5840</orcidid></search><sort><creationdate>202112</creationdate><title>Development of a skin microbiome diagnostic method to assess skin condition in healthy individuals: Application of research on skin microbiomes and skin condition</title><author>Kotakeyama, Yuki ; Nakamura, Rie ; Kurosawa, Masaharu ; Ota, Seiko ; Suzuki, Ruka ; Nakanishi, Miki ; Kanno, Kohei ; Watanabe, Kosuke ; Ishitsuka, Yukiko</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4194-49cbc05391db11717d91f6ddbd619cf4e15fa2155d9770b6f7081c69095aa6c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Adult</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Aging</topic><topic>Cluster analysis</topic><topic>Clustering</topic><topic>Correlation analysis</topic><topic>Female</topic><topic>Healthy Volunteers</topic><topic>Homeostasis</topic><topic>Humans</topic><topic>Microbiology</topic><topic>microbiology (skin)/preservation (products)</topic><topic>Microbiomes</topic><topic>Microbiota - physiology</topic><topic>Middle Aged</topic><topic>Outliers (statistics)</topic><topic>pH effects</topic><topic>Pores</topic><topic>Principal components analysis</topic><topic>Product development</topic><topic>Regression analysis</topic><topic>rRNA 16S</topic><topic>Sebum - microbiology</topic><topic>Skin</topic><topic>Skin - microbiology</topic><topic>skin physiology/structure</topic><topic>skin repair/acne/rosacea/dandruff/striae</topic><topic>Statistical analysis</topic><topic>Statistical methods</topic><topic>statistics</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kotakeyama, Yuki</creatorcontrib><creatorcontrib>Nakamura, Rie</creatorcontrib><creatorcontrib>Kurosawa, Masaharu</creatorcontrib><creatorcontrib>Ota, Seiko</creatorcontrib><creatorcontrib>Suzuki, Ruka</creatorcontrib><creatorcontrib>Nakanishi, Miki</creatorcontrib><creatorcontrib>Kanno, Kohei</creatorcontrib><creatorcontrib>Watanabe, Kosuke</creatorcontrib><creatorcontrib>Ishitsuka, Yukiko</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Chemoreception Abstracts</collection><collection>Toxicology Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>International journal of cosmetic science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kotakeyama, Yuki</au><au>Nakamura, Rie</au><au>Kurosawa, Masaharu</au><au>Ota, Seiko</au><au>Suzuki, Ruka</au><au>Nakanishi, Miki</au><au>Kanno, Kohei</au><au>Watanabe, Kosuke</au><au>Ishitsuka, Yukiko</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Development of a skin microbiome diagnostic method to assess skin condition in healthy individuals: Application of research on skin microbiomes and skin condition</atitle><jtitle>International journal of cosmetic science</jtitle><addtitle>Int J Cosmet Sci</addtitle><date>2021-12</date><risdate>2021</risdate><volume>43</volume><issue>6</issue><spage>677</spage><epage>690</epage><pages>677-690</pages><issn>0142-5463</issn><eissn>1468-2494</eissn><abstract>Objective
Skin microbiomes vary across individuals. They are known to play essential roles in maintaining homeostasis and preventing infectious pathogens. In recent years, cosmetic product development has begun to focus on the relationship between skin microbiomes and skin conditions. However, the statistical methods used in many studies include the standard t‐test and small‐scale correlation analysis, which do not take into account the internal correlation structure in data on skin microbiomes and skin features. In this study, we aimed to understand the relationship between skin microbiomes and skin features by analysing complex microbiomes and skin data.
Methods
We obtained data on 19 skin characteristics and skin microbiomes based on 16s ribosomal RNA (16S rRNA) gene analysis of 276 healthy Japanese women. We then performed the principal component analysis (PCA), a method that takes into account the internal correlation structure, on 234 panels of them that did not contain outliers or missing values. We confirmed the relationship between skin microbiomes and skin features with principal component regression analysis and hierarchical clustering analysis (HCA).
Results
The principal component regression analysis showed strong relationships between skin microbiomes and sebum‐related skin characteristics and skin pH. In the HCA, the female panel was classified into two major groups based on the skin microbiome. Furthermore, there were significant differences in sebum‐related skin characteristics and the way skin condition changes with ageing between those groups, suggesting the possibility of measuring skin condition and age‐related skin risk based on microbiome data. In addition, sebum‐related characteristics differed significantly among middle‐aged participants, suggesting a strong relationship between skin microbiomes and sebum‐related characteristics.
Conclusion
Analysis of skin condition and skin microbiome in Japanese women, taking into account the correlation between variables, showed that skin microbiome was significantly related to the number of pores and the amount of sebum. Furthermore, it was suggested that the skin condition and the way the skin condition changes with ageing may differ depending on the type of skin microbiome. The finding of a relationship between skin condition and skin microbiome suggests the possibility of proposing a new beauty method focusing on the skin microbiome in the future.
Résumé
Objectif
Les microbiomes de la peau varient selon les individus. Ils sont connus pour jouer des rôles essentiels dans le maintien de l'homéostasie et la prévention des agents pathogènes infectieux. Ces dernières années, le développement de produits cosmétiques a commencé à se concentrer sur la relation entre les microbiomes cutanés et les conditions de la peau. Cependant, les méthodes statistiques utilisées dans de nombreuses études comprennent le t‐test standard et l'analyse de corrélation à petite échelle, qui ne tiennent pas compte de la structure de corrélation interne dans les données sur les microbiomes cutanés et les caractéristiques de la peau. Dans cette étude, nous avons cherché à comprendre la relation entre les microbiomes cutanés et les caractéristiques de la peau en analysant des données complexes sur les microbiomes et la peau.
Méthodes
Nous avons obtenu des données sur 19 caractéristiques de la peau et sur les microbiomes cutanés à partir de l'analyse du gène de l'ARNr 16S (16S rRNA) de 276 femmes japonaises en bonne santé. Nous avons ensuite effectué l'analyse en composantes principales (PCA: principal component analysis), une méthode qui prend en compte la structure de corrélation interne, sur 234 d'entre elles qui ne contenaient pas de valeurs aberrantes ou manquantes. Nous avons confirmé la relation entre les microbiomes cutanés et les caractéristiques de la peau à l'aide d'une analyse de régression en composantes principales et d'une analyse de regroupement hiérarchique (HCA: hierarchical clustering analysis).
Résultats
L'analyse de régression en composantes principales a montré des relations fortes entre les microbiomes cutanés et les caractéristiques de la peau liées au sébum et au pH de la peau. Dans l'étude HCA, le panel de femmes a été classé en deux grands groupes sur la base du microbiome cutané. En outre, il y avait des différences significatives dans les caractéristiques de la peau liées au sébum et dans la façon dont l'état de la peau change avec l'âge entre ces groupes, ce qui suggère la possibilité de mesurer l'état de la peau et le risque cutané lié à l'âge à partir des données du microbiome. En outre, les caractéristiques liées au sébum différaient de manière significative chez les participants d'âge moyen, ce qui suggère une forte relation entre les microbiomes cutanés et les caractéristiques liées au sébum.
Conclusion
L'analyse de l'état de la peau et du microbiome cutané chez les femmes japonaises, en tenant compte de la corrélation entre les variables, a montré que le microbiome cutané était significativement lié au nombre de pores et à la quantité de sébum. En outre, il a été suggéré que l'état de la peau et la façon dont l'état de la peau évolue avec le vieillissement peuvent différer en fonction du type de microbiome cutané. La découverte d'une relation entre l'état de la peau et le microbiome cutané suggère la possibilité de proposer à l'avenir une nouvelle méthode de beauté axée sur le microbiome cutané.
Hierarchical clustering analysis revealed that the panel of Japanese women could be classified into two major groups according to their skin microbiome. Furthermore, these two groups differed in their skin conditions and in the way their skin conditions changed with age. The results suggest the possibility of estimating skin condition and skin risk based on skin microbiome.</abstract><cop>England</cop><pub>Wiley Subscription Services, Inc</pub><pmid>34664300</pmid><doi>10.1111/ics.12744</doi><tpages>0</tpages><orcidid>https://orcid.org/0000-0002-3775-5840</orcidid></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0142-5463 |
| ispartof | International journal of cosmetic science, 2021-12, Vol.43 (6), p.677-690 |
| issn | 0142-5463 1468-2494 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_2583444231 |
| source | MEDLINE; Wiley Online Library Journals Frontfile Complete |
| subjects | Adult Aged Aged, 80 and over Aging Cluster analysis Clustering Correlation analysis Female Healthy Volunteers Homeostasis Humans Microbiology microbiology (skin)/preservation (products) Microbiomes Microbiota - physiology Middle Aged Outliers (statistics) pH effects Pores Principal components analysis Product development Regression analysis rRNA 16S Sebum - microbiology Skin Skin - microbiology skin physiology/structure skin repair/acne/rosacea/dandruff/striae Statistical analysis Statistical methods statistics Young Adult |
| title | Development of a skin microbiome diagnostic method to assess skin condition in healthy individuals: Application of research on skin microbiomes and skin condition |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-26T23%3A41%3A28IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Development%20of%20a%20skin%20microbiome%20diagnostic%20method%20to%20assess%20skin%20condition%20in%20healthy%20individuals:%20Application%20of%20research%20on%20skin%20microbiomes%20and%20skin%20condition&rft.jtitle=International%20journal%20of%20cosmetic%20science&rft.au=Kotakeyama,%20Yuki&rft.date=2021-12&rft.volume=43&rft.issue=6&rft.spage=677&rft.epage=690&rft.pages=677-690&rft.issn=0142-5463&rft.eissn=1468-2494&rft_id=info:doi/10.1111/ics.12744&rft_dat=%3Cproquest_cross%3E2609205809%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2609205809&rft_id=info:pmid/34664300&rfr_iscdi=true |