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

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.

Identiferoai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:84296
Date24 March 2023
CreatorsVittoraki, 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
PublisherFrontiers Research Foundation
Source SetsHochschulschriftenserver (HSSS) der SLUB Dresden
LanguageEnglish
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/publishedVersion, doc-type:article, info:eu-repo/semantics/article, doc-type:Text
Rightsinfo:eu-repo/semantics/openAccess
Relation1664-3224, 670956

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