Decoding the restriction of T cell receptors to human leukocyte antigen alleles using statistical learning

Conventional T cells recognize peptides presented by the human leukocyte antigen (HLA) proteins through their T cell receptors (TCRs). Given that thousands of HLA proteins have been discovered, each presenting thousands of different peptide antigens, decoding the cognate HLA protein of a TCR experimentally is a challenging task. To address this problem, we combined statistical learning methods with a unique dataset of paired T cell repertoires and HLA allele information for 6,794 individuals. This enabled us to discover 53,870 T cell receptor alpha (TRA) and 1,095,576 beta (TRB) clonotypes that were associated with 437 unique HLA alleles. The identified clonotypes were targeting prevalent infections, e.g. influenza, cytomegalovirus and Epstein-Barr virus. Utilizing these clonotypes, we developed statistical models that impute the carriership of common HLA alleles from the TRA- or TRB-repertoire. In conclusion, the identified allele-associated clonotypes encode the HLA fingerprints and the immune exposure history of individuals and populations.