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Myers T, Bouslimani A, Huang S, Hansen ST, Clavaud C, Azouaoui A, Ott A, Gueniche A, Bouez C, Zheng Q, Aguilar L, Knight R, Moreau M, Song SJ. A multi-study analysis enables identification of potential microbial features associated with skin aging signs. Front Aging 2024; 4:1304705. [PMID: 38362046 PMCID: PMC10868648 DOI: 10.3389/fragi.2023.1304705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 12/12/2023] [Indexed: 02/17/2024]
Abstract
Introduction: During adulthood, the skin microbiota can be relatively stable if environmental conditions are also stable, yet physiological changes of the skin with age may affect the skin microbiome and its function. The microbiome is an important factor to consider in aging since it constitutes most of the genes that are expressed on the human body. However, severity of specific aging signs (one of the parameters used to measure "apparent" age) and skin surface quality (e.g., texture, hydration, pH, sebum, etc.) may not be indicative of chronological age. For example, older individuals can have young looking skin (young apparent age) and young individuals can be of older apparent age. Methods: Here we aim to identify microbial taxa of interest associated to skin quality/aging signs using a multi-study analysis of 13 microbiome datasets consisting of 16S rRNA amplicon sequence data and paired skin clinical data from the face. Results: We show that there is a negative relationship between microbiome diversity and transepidermal water loss, and a positive association between microbiome diversity and age. Aligned with a tight link between age and wrinkles, we report a global positive association between microbiome diversity and Crow's feet wrinkles, but with this relationship varying significantly by sub-study. Finally, we identify taxa potentially associated with wrinkles, TEWL and corneometer measures. Discussion: These findings represent a key step towards understanding the implication of the skin microbiota in skin aging signs.
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Affiliation(s)
- Tyler Myers
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, CA, United States
| | | | - Shi Huang
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, CA, United States
- Department of Pediatrics, University of California San Diego, La Jolla, CA, United States
| | - Shalisa T. Hansen
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, CA, United States
| | - Cécile Clavaud
- L’Oréal Research and Innovation, Aulnay sous Bois, France
| | | | - Alban Ott
- L’Oréal Research and Innovation, Aulnay sous Bois, France
| | | | - Charbel Bouez
- L’Oréal Research and Innovation, Clark, NJ, United States
| | - Qian Zheng
- L’Oréal Research and Innovation, Clark, NJ, United States
| | - Luc Aguilar
- L’Oréal Research and Innovation, Aulnay sous Bois, France
| | - Rob Knight
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, CA, United States
- Department of Pediatrics, University of California San Diego, La Jolla, CA, United States
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, United States
- Shu Chien-Gene Lay Department of Engineering, University of California San Diego, La Jolla, CA, United States
- Halıcıoğlu Data Science Institute, University of California San Diego, La Jolla, CA, United States
| | - Magali Moreau
- L’Oréal Research and Innovation, Clark, NJ, United States
- L’Oréal Research and Innovation, Aulnay sous Bois, France
| | - Se Jin Song
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, CA, United States
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