Moghaddam Amir Ostadi, Jin Xiaowei, Zhai Haiwei, Safa Bahareh Tajvidi, Seiffert-Sinha Kristina, Leiker Merced, Rosenbohm Jordan, Meng Fanben, Sinha Animesh A, Yang Ruiguo
Department of Biomedical Engineering, Michigan State University, East Lansing, MI 48824.
Institute of Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI 48824.
bioRxiv. 2024 Oct 13:2024.10.09.617446. doi: 10.1101/2024.10.09.617446.
Pemphigus vulgaris (PV) is a blistering autoimmune disease that affects the skin and mucous membranes. The precise mechanisms by which PV antibodies induce a complete loss of cohesion of keratinocytes are not fully understood. But it is accepted that the process starts with antibody binding to desmosomal targets which leads to its disassembly and subsequent structural changes to cell-cell adhesions. In vitro immunofluorescence imaging of desmosome molecules has been used to characterize this initial phase, often qualitatively. However, there remains an untapped potential of image analysis in providing us more in-depth knowledge regarding ultrastructural changes after antibody binding. Currently, there is no such effort to establish a quantitative framework from immunofluorescence images in PV pathology. We take on this effort here in a comprehensive study to examine the effects of antibodies on key adhesion molecules and the cytoskeletal network, aiming to establish a correlation of ultrastructural changes in cell-cell adhesion with antibody pathogenicity. Specifically, we introduced a data-driven approach to quantitatively evaluate perturbations in adhesion molecules, including desmoglein 3, E-cadherin, as well as the cytoskeleton, following antibody treatment. We identify distinct immunofluorescence imaging signatures that mark the impact of antibody binding on the remodeling of the adhesion molecules and introduce a pathogenicity score to compare the relative effects of different antibodies. From this analysis, we showed that the biophysical response of keratinocytes to distinct PV associated antibodies is highly specific, allowing for accurate prediction of their pathogenicity. For instance, the high pathogenicity scores of the PVIgG and AK23 antibodies show strong agreement with their reported PV pathology. Our data-driven approach offers a more detailed framework for the action of autoantibodies in pemphigus and has the potential to pave the way for the development of effective novel diagnostic methods and therapeutic strategies.
寻常型天疱疮（PV）是一种影响皮肤和黏膜的水疱性自身免疫性疾病。PV抗体诱导角质形成细胞完全丧失黏附力的确切机制尚未完全明确。但人们认为该过程始于抗体与桥粒靶点结合，进而导致桥粒解体以及随后细胞间黏附的结构变化。桥粒分子的体外免疫荧光成像常被用于定性表征这一初始阶段。然而，在提供有关抗体结合后超微结构变化的更深入知识方面，图像分析仍有未被挖掘的潜力。目前，在PV病理学中尚未有从免疫荧光图像建立定量框架的相关努力。我们在此开展一项全面研究，以检验抗体对关键黏附分子和细胞骨架网络的影响，旨在建立细胞间黏附超微结构变化与抗体致病性之间的关联。具体而言，我们引入了一种数据驱动的方法，以定量评估抗体处理后黏附分子（包括桥粒芯糖蛋白3、E - 钙黏蛋白）以及细胞骨架的扰动情况。我们识别出了独特的免疫荧光成像特征，这些特征标志着抗体结合对黏附分子重塑的影响，并引入了一个致病性评分来比较不同抗体的相对作用。通过该分析，我们表明角质形成细胞对不同PV相关抗体的生物物理反应具有高度特异性，能够准确预测其致病性。例如，PVIgG和AK23抗体的高致病性评分与它们所报道的PV病理学表现高度一致。我们的数据驱动方法为天疱疮中自身抗体的作用提供了一个更详细的框架，并有潜力为开发有效的新型诊断方法和治疗策略铺平道路。
