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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Hidden Patterns of Anti-HLA Class I Alloreactivity Revealed Through Machine Learning

Vittoraki, Angeliki G., Fylaktou, Asimina, Tarassi, Katerina, Tsinaris, Zafeiris, Siorenta, Alexandra, Petasis, George Ch., Gerogiannis, Demetris, Lehmann, Claudia, Carmagnat, Maryvonnick, Doxiadis, Ilias, Iniotaki, Aliki G., Theodorou, Ioannis 24 March 2023 (has links)
Detection of alloreactive anti-HLA antibodies is a frequent and mandatory test before and after organ transplantation to determine the antigenic targets of the antibodies. Nowadays, this test involves the measurement of fluorescent signals generated through antibody–antigen reactions on multi-beads flow cytometers. In this study, in a cohort of 1,066 patients from one country, anti-HLA class I responses were analyzed on a panel of 98 different antigens. Knowing that the immune system responds typically to “shared” antigenic targets, we studied the clustering patterns of antibody responses against HLA class I antigens without any a priori hypothesis, applying two unsupervised machine learning approaches. At first, the principal component analysis (PCA) projections of intralocus specific responses showed that anti-HLA-A and anti-HLA-C were the most distantly projected responses in the population with the anti-HLA-B responses to be projected between them. When PCA was applied on the responses against antigens belonging to a single locus, some already known groupings were confirmed while several new crossreactive patterns of alloreactivity were detected. Anti-HLA-A responses projected through PCA suggested that three cross-reactive groups accounted for about 70% of the variance observed in the population, while anti-HLA-B responses were mainly characterized by a distinction between previously described Bw4 and Bw6 cross-reactive groups followed by several yet undocumented or poorly described ones. Furthermore, anti-HLA-C responses could be explained by two major cross-reactive groups completely overlapping with previously described C1 and C2 allelic groups. A second featurebased analysis of all antigenic specificities, projected as a dendrogram, generated a robust measure of allelic antigenic distances depicting bead-array defined cross reactive groups. Finally, amino acid combinations explaining major population specific crossreactive groups were described. The interpretation of the results was based on the current knowledge of the antigenic targets of the antibodies as they have been characterized either experimentally or computationally and appear at the HLA epitope registry.

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