Abstract
T cells are critical components of the 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 individual's TCR repertoire. TCR repertoire-wide association studies (TReWAS) aim to evaluate the associations between individual TCRs and disease or exposure status. Previous studies have shown that TCRs associated with viral infections can be identified using TReWAS, and these TCRs can be used to predict current or past infection with high accuracy. Many TCRs are strongly associated with specific HLA alleles, suggesting that the incorporation of HLA information could improve the precision of TReWAS analyses and predictions based on TCRs. In this study, we evaluated TCR-based predictions while conditioning on individual HLA alleles or their k-nearest neighbors. We observed improved prediction accuracy for some HLA alleles. Furthermore, these HLA-specific predictions provide insight into the role of specific HLAs in coordinating immune response to immunogenic antigens, demonstrating the benefit of HLA-aware analysis of TCR data.