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Kesmir, C.

Publications and source records attributed to Kesmir, C..

2 recordsLinked to original sources
bioRxiv2018

Estimating HLA disease associations using similarity trees

The human leukocyte antigen (HLA) is associated with many (infectious) disease outcomes. These associations are perhaps best documented for HIV-1. For example, the HLA-B*58:01 allele is associated with control of the virus, while HLA-B*18:01 is considered detrimental. In HLA disease association studies, it is often ignored that certain HLA molecules are functionally very similar to others. For instance, HLA-B*18:03 differs \"only\" at 3 positions in its peptide binding site from HLA-B*18:01, and not surprisingly, HLA-B*18:03 is also associated with fast progression to AIDS. Here, we present a Bayesian method that takes functional HLA similarities into account to find HLA associations with quantitative traits such as HIV-1 viral load. The method is based on the so-called phylogenetic mixed model (a model for the evolution of a quantitative trait on the branches of a phylogeny), and can easily be modified to study a wide range of research questions, like the role of the heterozygote advantage, or KIR ligands on disease outcomes. We show that in the case of HIV-1, our model is significantly better at predicting set-point virus load than a model that ignores HLA similarities altogether. Furthermore, our method provides a comprehensible visualization of HLA associations. The software is available online at www.github.com/chvandorp/MHCshrubs

immunology↗
bioRxiv2018

Robust self-nonself discrimination requires negative T cell selection on non-random peptides

Self-foreign discrimination by the immune system was long thought to arise because negative selection in the thymus silences self-reactive T cells. Yet recent data show that this silencing is remarkably incomplete. Here we ask how a repertoire containing many self-reactive cells can nevertheless discriminate self from foreign. We address this question using realistic-scale computational models of the T cell repertoire. Our models show that when foreign peptides dif-fer systematically from self, moderate T cell cross-reactivity skews the post-selection repertoire towards foreign recognition. When no such systematic differences exist, self-foreign discrim-ination is only possible if peptide presentation in the thymus minimizes the co-occurrence of similar, redundant self peptides. These results imply that negative selection needs to be based on non-random self peptides to allow robust self-foreign discrimination for both self-similar and -dissimilar pathogens.

immunology↗