Exploration of the Roles of HLAs When Predicting Infection Status by T Cell Receptors

T cells are critical components of human immune system. When a cell is infected by a virus, it presents viral peptides on its surface using human leukocyte antigen (HLA) proteins. These peptide-HLA complexes are recognized by T cells through interactions with T cell receptors (TCRs). A human blood sample can contain millions of unique TCRs, which is a sample from the TCR repertoire of the individual. TCR repertoire-wide association studies (TReWAS) aim to evaluate the association between individual TCRs and disease or exposure status. Previous studies have demonstrated that TCRs associated with viral infections can be identified through TReWAS, and such TCRs can be used to predict current or past infection with high accuracy. Notably, many TCRs are strongly associated with specific HLA alleles, suggesting that incorporating HLA information could enhance the accuracy of TReWAS analyses and TCR-based predictions. In our study, we evaluated TCR-based predictions by conditioning on individual HLA alleles or their k-nearest neighbors. We observed improved prediction accuracy for certain HLA alleles. Furthermore, these HLA-specific predictions provide insights into the role of specific HLAs in the infection or disease of interest, offering potential applications in personalized medicine.