Skin microbiome-biophysical association: a first integrative approach to classifying Korean skin types and aging groups
IntroductionThe field of human microbiome research is rapidly expanding beyond the gut and into the facial skin care industry. However, there is still no established criterion to define the objective relationship between the microbiome and clinical trials for developing personalized skin solutions t...
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Frontiers Media S.A.
2025-07-01
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| Series: | Frontiers in Cellular and Infection Microbiology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fcimb.2025.1561590/full |
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| author | Seyoung Mun Seyoung Mun Seyoung Mun HyungWoo Jo HyungWoo Jo Young Mok Heo Chaeyun Baek Hye-Been Kim Haeun Lee Kyeongeui Yun Kyeongeui Yun Jinuk Jeong Wooseok Lee Dasom Jeon Dasom Jeon So Min Kang So Min Kang Seunghyun Kang Young-Bong Choi Young-Bong Choi Sangjin Han Gabriel Kim Kung Ahn Dong Hun Lee Yong Ju Ahn Dong-Geol Lee Dong-Geol Lee Kyudong Han Kyudong Han Kyudong Han Kyudong Han |
| author_facet | Seyoung Mun Seyoung Mun Seyoung Mun HyungWoo Jo HyungWoo Jo Young Mok Heo Chaeyun Baek Hye-Been Kim Haeun Lee Kyeongeui Yun Kyeongeui Yun Jinuk Jeong Wooseok Lee Dasom Jeon Dasom Jeon So Min Kang So Min Kang Seunghyun Kang Young-Bong Choi Young-Bong Choi Sangjin Han Gabriel Kim Kung Ahn Dong Hun Lee Yong Ju Ahn Dong-Geol Lee Dong-Geol Lee Kyudong Han Kyudong Han Kyudong Han Kyudong Han |
| author_sort | Seyoung Mun |
| collection | DOAJ |
| description | IntroductionThe field of human microbiome research is rapidly expanding beyond the gut and into the facial skin care industry. However, there is still no established criterion to define the objective relationship between the microbiome and clinical trials for developing personalized skin solutions that consider individual diversity.ObjectivesIn this study, we conducted an integrated analysis of skin measurements, clinical Baumann skin type indicator (BSTI) surveys, and the skin microbiome of 950 Korean subjects to examine the ideal skin microbiome-biophysical associations.MethodsBy utilizing four skin biophysical parameters, we identified four distinct Korean Skin Cutotypes (KSCs) and categorized the subjects into three aging groups: the Young (under 34 years old), the Aging I group (35-50), and the Old group (over 51). To unravel the intricate connection between the skin’s microbiome and KSC types, we conducted DivCom clustering analysis.ResultsThis endeavor successfully classified 726 out of 740 female skin microbiomes into three subclusters: DC1-sub1, DC1-sub2, and DC2 with 15 core genera. To further amplify our findings, we harnessed the potent capabilities of the CatBoost boosting algorithm and achieved a reliable framework for predicting skin types based on microbial composition with an impressive average accuracy of 0.96 AUC value. Our study conclusively demonstrated that these 15 core genera could serve as objective indicators, differentiating the microbial composition among the aging groups.ConclusionIn conclusion, this study sheds light on the complex relationship between the skin microbiome and biophysical properties, and the findings provide a promising approach to advance the field of skincare, cosmetics, and broader microbial research. |
| format | Article |
| id | doaj-art-56e42f0a0b934e2ba0e3534664baf7da |
| institution | Kabale University |
| issn | 2235-2988 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Cellular and Infection Microbiology |
| spelling | doaj-art-56e42f0a0b934e2ba0e3534664baf7da2025-08-20T03:33:18ZengFrontiers Media S.A.Frontiers in Cellular and Infection Microbiology2235-29882025-07-011510.3389/fcimb.2025.15615901561590Skin microbiome-biophysical association: a first integrative approach to classifying Korean skin types and aging groupsSeyoung Mun0Seyoung Mun1Seyoung Mun2HyungWoo Jo3HyungWoo Jo4Young Mok Heo5Chaeyun Baek6Hye-Been Kim7Haeun Lee8Kyeongeui Yun9Kyeongeui Yun10Jinuk Jeong11Wooseok Lee12Dasom Jeon13Dasom Jeon14So Min Kang15So Min Kang16Seunghyun Kang17Young-Bong Choi18Young-Bong Choi19Sangjin Han20Gabriel Kim21Kung Ahn22Dong Hun Lee23Yong Ju Ahn24Dong-Geol Lee25Dong-Geol Lee26Kyudong Han27Kyudong Han28Kyudong Han29Kyudong Han30Department of Microbiology, College of Science & Technology, Dankook University, Cheonan, Republic of KoreaCenter for Bio-Medical Engineering Core Facility, Dankook University, Cheonan, Republic of KoreaDepartment of Cosmedical Materials, College of Bio-convergence, Dankook University, Cheonan, Republic of KoreaDepartment of Microbiology, College of Science & Technology, Dankook University, Cheonan, Republic of KoreaResearch & Innovation (R&I) Center, COSMAX BTI, Seongnam, Republic of KoreaResearch & Innovation (R&I) Center, COSMAX BTI, Seongnam, Republic of KoreaResearch & Innovation (R&I) Center, COSMAX BTI, Seongnam, Republic of KoreaResearch & Innovation (R&I) Center, COSMAX BTI, Seongnam, Republic of KoreaResearch & Innovation (R&I) Center, COSMAX BTI, Seongnam, Republic of KoreaDepartment of Microbiology, College of Science & Technology, Dankook University, Cheonan, Republic of KoreaHuNBiome Co., Ltd., Research and Development (R&D) Center, Seoul, Republic of KoreaDepartment of Bioconvergence Engineering, Dankook University, Yongin, Republic of KoreaCenter for Bio-Medical Engineering Core Facility, Dankook University, Cheonan, Republic of KoreaDepartment of Clinical Research, Korea Biomedical Research Institute, Seongnam, Republic of KoreaCenter for Digital Health, Medical Science Research Institute, Kyung Hee University Medical Center, Kyung Hee University College of Medicine, Seoul, Republic of KoreaDepartment of Clinical Research, Korea Biomedical Research Institute, Seongnam, Republic of KoreaCenter for Digital Health, Medical Science Research Institute, Kyung Hee University Medical Center, Kyung Hee University College of Medicine, Seoul, Republic of KoreaResearch & Innovation (R&I) Center, COSMAX BTI, Seongnam, Republic of KoreaCenter for Bio-Medical Engineering Core Facility, Dankook University, Cheonan, Republic of KoreaDepartment of Cosmedical Materials, College of Bio-convergence, Dankook University, Cheonan, Republic of KoreaHuNBiome Co., Ltd., Research and Development (R&D) Center, Seoul, Republic of KoreaHuNBiome Co., Ltd., Research and Development (R&D) Center, Seoul, Republic of KoreaHuNBiome Co., Ltd., Research and Development (R&D) Center, Seoul, Republic of KoreaDepartment of Dermatology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of KoreaHuNBiome Co., Ltd., Research and Development (R&D) Center, Seoul, Republic of KoreaDepartment of Microbiology, College of Science & Technology, Dankook University, Cheonan, Republic of KoreaResearch & Innovation (R&I) Center, COSMAX BTI, Seongnam, Republic of KoreaDepartment of Microbiology, College of Science & Technology, Dankook University, Cheonan, Republic of KoreaCenter for Bio-Medical Engineering Core Facility, Dankook University, Cheonan, Republic of KoreaHuNBiome Co., Ltd., Research and Development (R&D) Center, Seoul, Republic of KoreaDepartment of Bioconvergence Engineering, Dankook University, Yongin, Republic of KoreaIntroductionThe field of human microbiome research is rapidly expanding beyond the gut and into the facial skin care industry. However, there is still no established criterion to define the objective relationship between the microbiome and clinical trials for developing personalized skin solutions that consider individual diversity.ObjectivesIn this study, we conducted an integrated analysis of skin measurements, clinical Baumann skin type indicator (BSTI) surveys, and the skin microbiome of 950 Korean subjects to examine the ideal skin microbiome-biophysical associations.MethodsBy utilizing four skin biophysical parameters, we identified four distinct Korean Skin Cutotypes (KSCs) and categorized the subjects into three aging groups: the Young (under 34 years old), the Aging I group (35-50), and the Old group (over 51). To unravel the intricate connection between the skin’s microbiome and KSC types, we conducted DivCom clustering analysis.ResultsThis endeavor successfully classified 726 out of 740 female skin microbiomes into three subclusters: DC1-sub1, DC1-sub2, and DC2 with 15 core genera. To further amplify our findings, we harnessed the potent capabilities of the CatBoost boosting algorithm and achieved a reliable framework for predicting skin types based on microbial composition with an impressive average accuracy of 0.96 AUC value. Our study conclusively demonstrated that these 15 core genera could serve as objective indicators, differentiating the microbial composition among the aging groups.ConclusionIn conclusion, this study sheds light on the complex relationship between the skin microbiome and biophysical properties, and the findings provide a promising approach to advance the field of skincare, cosmetics, and broader microbial research.https://www.frontiersin.org/articles/10.3389/fcimb.2025.1561590/fulldermatologic conditionsmicrobiomeKorean skin cutotypesskin microbiome-biophysical associationcore genera |
| spellingShingle | Seyoung Mun Seyoung Mun Seyoung Mun HyungWoo Jo HyungWoo Jo Young Mok Heo Chaeyun Baek Hye-Been Kim Haeun Lee Kyeongeui Yun Kyeongeui Yun Jinuk Jeong Wooseok Lee Dasom Jeon Dasom Jeon So Min Kang So Min Kang Seunghyun Kang Young-Bong Choi Young-Bong Choi Sangjin Han Gabriel Kim Kung Ahn Dong Hun Lee Yong Ju Ahn Dong-Geol Lee Dong-Geol Lee Kyudong Han Kyudong Han Kyudong Han Kyudong Han Skin microbiome-biophysical association: a first integrative approach to classifying Korean skin types and aging groups Frontiers in Cellular and Infection Microbiology dermatologic conditions microbiome Korean skin cutotypes skin microbiome-biophysical association core genera |
| title | Skin microbiome-biophysical association: a first integrative approach to classifying Korean skin types and aging groups |
| title_full | Skin microbiome-biophysical association: a first integrative approach to classifying Korean skin types and aging groups |
| title_fullStr | Skin microbiome-biophysical association: a first integrative approach to classifying Korean skin types and aging groups |
| title_full_unstemmed | Skin microbiome-biophysical association: a first integrative approach to classifying Korean skin types and aging groups |
| title_short | Skin microbiome-biophysical association: a first integrative approach to classifying Korean skin types and aging groups |
| title_sort | skin microbiome biophysical association a first integrative approach to classifying korean skin types and aging groups |
| topic | dermatologic conditions microbiome Korean skin cutotypes skin microbiome-biophysical association core genera |
| url | https://www.frontiersin.org/articles/10.3389/fcimb.2025.1561590/full |
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