ArticlebioRxiv : the preprint server for biology2024
Data-Driven Image Analysis to Determine Antibody-Induced Dissociation of Cell-Cell Adhesion and Antibody Pathogenicity in Pemphigus Vulgaris.
Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
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.
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