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

Author:

Kim Seo Hyeong1,Kim Ji Hye1,Choi Yoon Mi1,Seo Su Min1,Jang Eun Young1,Lee Sung Jae1,Zhang Hyun‐Soo2,Roh Yunho2,Jung Yeon Woo3,Park Chang Ook3,Jeong Do Hyeon4,Lee Kwang Hoon1

Affiliation:

1. Cutis Biomedical Research Center Co. Ltd. Seoul Republic of Korea

2. Biostatistics Collaboration Unit Department of Biomedical Systems Informatics Yonsei University College of Medicine Seoul Republic of Korea

3. Department of Dermatology & Cutaneous Biology Research Institute Yonsei University College of Medicine Seoul Republic of Korea

4. Raphas Co. Ltd. Seoul Republic of Korea

Abstract

AbstractBackgroundClassifying 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 methodsMISSM 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.ResultsCollagen 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.ConclusionThis 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.

Publisher

Wiley

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