Augmented Virtual Crossmatch for Donor-Induced Antibody Prediction by Using High Resolution Human Leukocyte Antigen Typing and Human Leukocyte Antigen Epitope Mapping for Better Donor Match

dc.contributor.advisor Yelekçi, Kemal en_US
dc.contributor.author Karadeniz, Sedat Tanju
dc.contributor.author Yelekçi, Kemal
dc.contributor.other Molecular Biology and Genetics
dc.date 2023-01
dc.date.accessioned 2023-07-25T12:44:44Z
dc.date.available 2023-07-25T12:44:44Z
dc.date.issued 2023
dc.department Enstitüler, Lisansüstü Eğitim Enstitüsü, Biyoinformatik ve Genetik Ana Bilim Dalı en_US
dc.description.abstract The Human Leukocyte Antigen (HLA) disparity between donors and recipients is the primary driver of Donor Specific Antibodies (DSA) formation and graft rejection after transplantation. We aimed to predict the DSA by finding the HLA antigen mismatches, searching the eplets of antigens that bind to the recipient's anti-HLA antibodies, calculating the number of shared eplets between the mismatched donor HLA antigens and the recipient's pre-transplantation anti-HLA antibody-bound antigens. We have used recipient-donor HLA Typing results and the recipient's pre-transplantation and post-transplantation anti-HLA antibody detection results by Luminex single antigen bead (Luminex-SAB) assay as retrospective data for calculation in five steps. We have compared the HLA Typing results to find the mismatched antigens in the first step and searched the relevant eplets for the recipient's pre-transplantation anti-HLA antibodies in the second step. Then we calculated the shared eplets between the donor's mismatched HLA antigens and the recipient's pre-transplantation anti-HLA antibodies to find the highest number of shares, then listed the most shared anti-HLA antibodies as the most probable DSA in the fourth step. Then, we confirmed the possible epitope's peptide AA (amino acid) sequences with the IEDB Bepipred-1.0 Antibody Epitope Prediction method using the donor's HLA antigen AA sequence. en_US
dc.identifier.uri https://hdl.handle.net/20.500.12469/4386
dc.identifier.yoktezid 793509 en_US
dc.language.iso en en_US
dc.publisher Kadir Has Üniversitesi en_US
dc.relation.publicationcategory Tez en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.subject Virtual Crossmatch en_US
dc.subject Antibody Prediction en_US
dc.subject Epitope Mapping en_US
dc.subject Donor Specific Antibody en_US
dc.subject Kidney Transplantation en_US
dc.title Augmented Virtual Crossmatch for Donor-Induced Antibody Prediction by Using High Resolution Human Leukocyte Antigen Typing and Human Leukocyte Antigen Epitope Mapping for Better Donor Match en_US
dc.type Doctoral Thesis en_US
dspace.entity.type Publication
relation.isAuthorOfPublication 9407938e-3d31-453b-9199-aaa8280a66c5
relation.isAuthorOfPublication.latestForDiscovery 9407938e-3d31-453b-9199-aaa8280a66c5
relation.isOrgUnitOfPublication 71ce8622-7449-4a6a-8fad-44d881416546
relation.isOrgUnitOfPublication.latestForDiscovery 71ce8622-7449-4a6a-8fad-44d881416546

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Augmented virtual crossmatch for donor-induced antibody prediction by using high resolution human leukocyte antigen typing and human leukocyte antigen epitope mapping for better donor match

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