Publication
Title
Memory T cell receptor repertoire data mining as a tool for identifying cytomegalovirus serostatus
Author
Abstract
Pathogens of past and current infections have been identified directly by means of PCR or indirectly by measuring a specific immune response (e.g., antibody titration). Using a novel approach, Emerson and colleagues showed that the cytomegalovirus serostatus can also be accurately determined by using a T cell receptor repertoire data mining approach. In this study, we have sequenced the CD4+ memory T cell receptor repertoire of a Belgian cohort with known cytomegalovirus serostatus. A random forest classifier was trained on the CMV specific T cell receptor repertoire signature and used to classify individuals in the Belgian cohort. This study shows that the novel approach can be reliably replicated with an equivalent performance as that reported by Emerson and colleagues. Additionally, it provides evidence that the T cell receptor repertoire signature is to a large extent present in the CD4+ memory repertoire.
Language
English
Source (journal)
Genes and immunity. - Place of publication unknown
Publication
Place of publication unknown : 2019
ISSN
1466-4879
Volume/pages
20 :3 (2019) , p. 255-260
ISI
000462596700008
Pubmed ID
29904098
Full text (Publisher's DOI)
Full text (open access)
Full text (publisher's version - intranet only)
UAntwerpen
Faculty/Department
Research group
Project info
Predicting Immune responses by Modeling immunoSequencing data (PIMS).
GENOMED - Genomics in Medicine.
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identification
Creation 16.06.2018
Last edited 14.09.2021
To cite this reference