Richters Renée J H, Uzunbajakava Natallia E, Timofeeva Nadya, van de Kerkhof Peter C M, van Erp Piet E J
Department of Dermatology, Radboud university medical center, Nijmegen, The Netherlands.
Philips Research, Eindhoven, The Netherlands,
Skin Pharmacol Physiol. 2019;32(2):81-93. doi: 10.1159/000495070. Epub 2019 Jan 23.
BACKGROUND/AIMS: Aberrant skin barrier and intercorneocyte adhesion are potential contributors to the pathomechanism of sensitive skin (SS). Here we aimed to develop a novel and easy-to-apply method to analyze corneodesmosomes and to interrogate potential differences between corneocytes of subjects with SS and non-SS (NSS).
Corneocytes of the volar forearm and upper outer quadrant of the left buttock of SS (n = 10) and NSS (n = 8) subjects were extracted as a function of depth using adhesive tape and stained with anti-desmoglein 1 (DSG1) antibody. The total area of corneocytes and the number and average size of cells per tape was estimated using image processing.
The total area of extracted corneocytes and the quantity of DSG1 decreased with depth. The level of decrease, total area of corneocytes, and average area of individual cells differed between anatomical locations. In SS, a larger total area of extracted corneocytes and a larger average cell size per tape was found at all inspected depths.
The developed novel and easy-to-apply approach allows investigation of corneodesmosome components. We confirm a role of altered corneocytes in the pathomechanism of SS. The disclosed protocol can further be optimized in studies of skin conditions with strongly affected corneodesmosomes.
背景/目的:异常的皮肤屏障和角质形成细胞间黏附是敏感性皮肤(SS)发病机制的潜在因素。在此,我们旨在开发一种新颖且易于应用的方法来分析角质形成细胞桥粒,并探究SS患者与非SS(NSS)患者角质形成细胞之间的潜在差异。
使用胶带按照深度提取SS组(n = 10)和NSS组(n = 8)受试者掌侧前臂及左臀部上外象限的角质形成细胞,并用抗桥粒芯糖蛋白1(DSG1)抗体进行染色。使用图像处理技术估计每条胶带上角质形成细胞的总面积、细胞数量及平均大小。
提取的角质形成细胞总面积和DSG1数量随深度降低。角质形成细胞总面积的降低水平以及单个细胞的平均面积在不同解剖部位有所不同。在SS患者中,在所有检测深度均发现提取的角质形成细胞总面积更大,且每条胶带上的细胞平均大小更大。
所开发的新颖且易于应用的方法可用于研究角质形成细胞桥粒成分。我们证实角质形成细胞改变在SS发病机制中起作用。在对角质形成细胞桥粒受严重影响的皮肤状况的研究中,所公开的方案可进一步优化。