Development of a biomarker-based platform for comprehensive skin characterization using minimally invasive skin sampling and quantitative real-time PCR.

Autor: Kim SH; Cutis Biomedical Research Center Co. Ltd., Seoul, Republic of Korea., Kim JH; Cutis Biomedical Research Center Co. Ltd., Seoul, Republic of Korea., Choi YM; Cutis Biomedical Research Center Co. Ltd., Seoul, Republic of Korea., Seo SM; Cutis Biomedical Research Center Co. Ltd., Seoul, Republic of Korea., Jang EY; Cutis Biomedical Research Center Co. Ltd., Seoul, Republic of Korea., Lee SJ; Cutis Biomedical Research Center Co. Ltd., Seoul, Republic of Korea., Zhang HS; Biostatistics Collaboration Unit, Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea., Roh Y; Biostatistics Collaboration Unit, Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea., Jung YW; Department of Dermatology & Cutaneous Biology Research Institute, Yonsei University College of Medicine, Seoul, Republic of Korea., Park CO; Department of Dermatology & Cutaneous Biology Research Institute, Yonsei University College of Medicine, Seoul, Republic of Korea., Jeong DH; Raphas Co. Ltd., Seoul, Republic of Korea., Lee KH; Cutis Biomedical Research Center Co. Ltd., Seoul, Republic of Korea.
Jazyk: angličtina
Zdroj: 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) [Skin Res Technol] 2024 Aug; Vol. 30 (8), pp. e13908.
DOI: 10.1111/srt.13908
Abstrakt: Background: Classifying diverse skin types is crucial for promoting skin health. However, efficiently identifying and analyzing relevant biomarkers from a vast array of available genetic data is challenging. Therefore, this study aimed to develop a precise and efficient platform for analyzing specific skin biomarkers using quantitative real-time PCR (qRT-PCR) with the minimal invasive skin sampling method (MISSM).
Materials and Methods: MISSM was used for RNA extraction from skin samples, followed by qRT-PCR analysis to quantify the expression of 20 biomarkers associated with skin characteristics (four biomarkers each for five skin characteristics). Noninvasive measurements from 299 Korean participants were utilized to correlate biomarker expression with skin parameters. Statistical analyses were conducted between biomarker expression levels and noninvasive skin measurements to select the relatively best-performing biomarker for each skin characteristic.
Results: Collagen type 1 alpha 1 (COL1A1) and moesin (MSN) were identified as skin aging biomarkers. Krüppel-like factor 4 (KLF4) and serine peptidase inhibitor Kazal type 5 (SPINK5) were identified as skin dryness biomarkers, whereas melan-A (MLANA) was selected as a biomarker for understanding pigmentation dynamics. Myelin protein zero like 3 (MPZL3) and high mobility group box 2 (HMGB2) were identified as markers of oily skin and skin sensitivity, respectively. Statistically significant correlations were found between the biomarker expression levels and noninvasive skin characteristic measurements.
Conclusion: This study successfully developed a platform for the precise evaluation of individual skin characteristics using MISSM and qRT-PCR biomarker analysis. By selecting biomarkers that correlate with noninvasive measurements of skin characteristics, we demonstrated the platform's efficacy in assessing diverse skin conditions.
(© 2024 The Author(s). Skin Research and Technology published by John Wiley & Sons Ltd.)
Databáze: MEDLINE
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