New peptide-based matrix redefines HLA heterozygosity, supporting its advantage in HIV disease
HLA class I heterozygote advantage is linked to beneficial outcomes after HIV infection, presumably through greater breadth of HIV epitope presentation and cytotoxic T cell response. Among heterozygotes, however, distinct allotype pairs differ in the extent to which they bind shared sets of peptides.
Using previously published mass spectrometry data, the HLA Immunogenetics Section within the Basic Science Program developed a functional divergence metric that measures pairwise complementarity of allotype-associated peptide binding profiles. Greater functional divergence for pairs of HLA-A and/or HLA-B allotypes associated with slower AIDS progression, and with enhanced viral load control in an independent cohort of infected persons.
The metric predicts immune breadth at the peptide level, rather than the gene level, and redefines HLA heterozygosity as a continuum differentially affecting disease outcome. We are currently refining the HLA functional divergence metric and applying it to additional infections, vaccination, immunotherapy, and other diseases where HLA heterozygote advantage occurs. The study was published in Science.
HLA class I signal peptide polymorphism regulates HLA-E-mediated immune responses
The nonclassical HLA-E molecule binds epitopes derived from HLA-A, HLA-B, HLA-C and HLA-G signal peptides (SPs) and serves as a ligand for the inhibitory CD94/NKG2A and activating CD94/NKG2C receptors expressed on natural killer cells (NK) and certain T cell subsets.
In a paper in Nature Immunology, we showed that only 6 of 16 common SP variants derived from classical HLA class I are efficiently processed to generate epitopes that enable CD94/NKG2 engagement. We termed these ‘functional SPs’. However, it remains unclear how multiple functional SP variants simultaneously expressed in the cell regulate HLA-E function. Thus, we have begun to conduct cellular assays to measure the influence of cognate SP genotypes (determined by HLA-A/-B and -C genotyping) on CD94/NKG2-mediated NK cell activity.
Functional data obtained in these experiments is being applied to the development of an algorithm that predicts NK cell responses based on HLA genotypes alone, which will be beneficial since DNA is available for many disease cohorts, whereas cells from these same patients are not. This algorithm will be tested in various disease and immunotherapy cohorts to determine which patients may benefit from therapies targeting CD94/NKG2 on effector NK or T cells.