Mostra i principali dati dell'item

dc.creatorVittoraki A.G., Fylaktou A., Tarassi K., Tsinaris Z., Petasis G.C., Gerogiannis D., Kheav V.-D., Carmagnat M., Lehmann C., Doxiadis I., Iniotaki A.G., Theodorou I.en
dc.date.accessioned2023-01-31T11:36:53Z
dc.date.available2023-01-31T11:36:53Z
dc.date.issued2020
dc.identifier10.3389/fimmu.2020.01667
dc.identifier.issn16643224
dc.identifier.urihttp://hdl.handle.net/11615/80633
dc.description.abstractAllele specific antibody response against the polymorphic system of HLA is the allogeneic response marker determining the immunological risk for graft acceptance before and after organ transplantation and therefore routinely studied during the patient's workup. Experimentally, bead bound antigen- antibody reactions are detected using a special multicolor flow cytometer (Luminex). Routinely for each sample, antibody responses against 96 different HLA antigen groups are measured simultaneously and a 96-dimensional immune response vector is created. Under a common experimental protocol, using unsupervised clustering algorithms, we analyzed these immune intensity vectors of anti HLA class II responses from a dataset of 1,748 patients before or after renal transplantation residing in a single country. Each patient contributes only one serum sample in the analysis. A population view of linear correlations of hierarchically ordered fluorescence intensities reveals patterns in human immune responses with striking similarities with the previously described CREGs but also brings new information on the antigenic properties of class II HLA molecules. The same analysis affirms that “public” anti-DP antigenic responses are not correlated to anti DR and anti DQ responses which tend to cluster together. Principal Component Analysis (PCA) projections also demonstrate ordering patterns clearly differentiating anti DP responses from anti DR and DQ on several orthogonal planes. We conclude that a computer vision of human alloresponse by use of several dimensionality reduction algorithms rediscovers proven patterns of immune reactivity without any a priori assumption and might prove helpful for a more accurate definition of public immunogenic antigenic structures of HLA molecules. Furthermore, the use of Eigen decomposition on the Immune Response generates new hypotheses that may guide the design of more effective patient monitoring tests. © Copyright © 2020 Vittoraki, Fylaktou, Tarassi, Tsinaris, Petasis, Gerogiannis, Kheav, Carmagnat, Lehmann, Doxiadis, Iniotaki and Theodorou.en
dc.language.isoenen
dc.sourceFrontiers in Immunologyen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85089349174&doi=10.3389%2ffimmu.2020.01667&partnerID=40&md5=17646c3c6e72f4c2e108319c8330c9b7
dc.subjectadolescenten
dc.subjectalgorithmen
dc.subjectantibody responseen
dc.subjectArticleen
dc.subjectCD8+ T lymphocyteen
dc.subjectcluster analysisen
dc.subjectenzyme linked immunosorbent assayen
dc.subjectfemaleen
dc.subjectfollow upen
dc.subjecthumanen
dc.subjectimmune responseen
dc.subjectimmunofluorescence testen
dc.subjectimmunologyen
dc.subjectimmunoreactivityen
dc.subjectimmunosuppressive treatmenten
dc.subjectkidney transplantationen
dc.subjectmachine learningen
dc.subjectmajor clinical studyen
dc.subjectmaleen
dc.subjectorgan transplantationen
dc.subjectprincipal component analysisen
dc.subjectrisk factoren
dc.subjectvaccinationen
dc.subjectadulten
dc.subjectadverse eventen
dc.subjectautomated pattern recognitionen
dc.subjectblooden
dc.subjectflow cytometryen
dc.subjectgraft rejectionen
dc.subjectgraft survivalen
dc.subjecthistocompatibilityen
dc.subjecthistocompatibility testen
dc.subjectimmunologyen
dc.subjectkidney transplantationen
dc.subjectmiddle ageden
dc.subjecttreatment outcomeen
dc.subjectalloantibodyen
dc.subjectalloantigenen
dc.subjectHLA antigenen
dc.subjectimmunosuppressive agenten
dc.subjectAdulten
dc.subjectCluster Analysisen
dc.subjectFemaleen
dc.subjectFlow Cytometryen
dc.subjectGraft Rejectionen
dc.subjectGraft Survivalen
dc.subjectHistocompatibilityen
dc.subjectHistocompatibility Testingen
dc.subjectHLA Antigensen
dc.subjectHumansen
dc.subjectImmunosuppressive Agentsen
dc.subjectIsoantibodiesen
dc.subjectIsoantigensen
dc.subjectKidney Transplantationen
dc.subjectMachine Learningen
dc.subjectMaleen
dc.subjectMiddle Ageden
dc.subjectPattern Recognition, Automateden
dc.subjectPrincipal Component Analysisen
dc.subjectTreatment Outcomeen
dc.subjectFrontiers Media S.A.en
dc.titlePatterns of 1,748 Unique Human Alloimmune Responses Seen by Simple Machine Learning Algorithmsen
dc.typejournalArticleen


Files in questo item

FilesDimensioneFormatoMostra

Nessun files in questo item.

Questo item appare nelle seguenti collezioni

Mostra i principali dati dell'item