Publication Details

AFRICAN RESEARCH NEXUS

SHINING A SPOTLIGHT ON AFRICAN RESEARCH

immunology and microbiology

A population response analysis approach to assign class II HLA-epitope restrictions

Journal of Immunology, Volume 194, No. 12, Year 2015

Identification of the specific HLA locus and allele presenting an epitope for recognition by specific TCRs (HLA restriction) is necessary to fully characterize the immune response to Ags. Experimental determination of HLA restriction is complex and technically challenging. As an alternative, the restricting HLA locus and allele can be inferred by genetic association, using response data in an HLA-typed population. However, simple odds ratio (OR) calculations can be problematic when dealing with large numbers of subjects and Ags, and because the same epitope can be presented by multiple alleles (epitope promiscuity). In this study, we develop a tool, denominated Restrictor Analysis Tool for Epitopes, to extract inferred restriction from HLA class II-typed epitope responses. This automated method infers HLA class II restriction from large datasets of T cell responses in HLA class II-typed subjects by calculating ORs and relative frequencies from simple data tables. The program is validated by: 1) analyzing data of previously determined HLA restrictions; 2) experimentally determining in selected individuals new HLA restrictions using HLA-transfected cell lines; and 3) predicting HLA restriction of particular peptides and showing that corresponding HLA class II tetramers efficiently bind to epitope-specific T cells. We further design a specific iterative algorithm to account for promiscuous recognition by calculation of OR values for combinations of different HLA molecules while incorporating predicted HLA binding affinity. The Restrictor Analysis Tool for Epitopes program streamlines the prediction of HLA class II restriction across multiple T cell epitopes and HLA types.
Statistics
Citations: 36
Authors: 10
Affiliations: 3
Identifiers
Research Areas
Genetics And Genomics
Study Design
Cross Sectional Study
Case-Control Study