ArticleJournal of biomedical science2025
Characterization of binding affinity changes of SARS-CoV-2 omicron variant peptides to population-specific HLA.
Article in Journal of biomedical science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
backgroundThe evolution of SARS-CoV-2, particularly through new variants, presents significant global health challenges due to their potential for immune evasion and reduced vaccine effectiveness. This study aims to investigate the impact of mutations in the Spike protein of Omicron EG.5 and XBB.1.16 variants on the binding affinities of viral peptides to common human leukocyte antigen (HLA) class I and II alleles across Taiwanese, British, and Russian populations. Understanding these interactions is crucial for elucidating differences in immune responses and disease severity among diverse populations.
methodsWe updated the T-CoV portal to incorporate and analyze EG.5 and XBB.1.16 variants. Binding affinities between mutated Spike protein peptides and HLA class I and II alleles were predicted and compared across the three populations. Statistical analyses, including chi-squared tests, were conducted to assess the significance of binding affinity differences across the three populations and between HLA classes.
resultsOur findings revealed that mutations in the Spike protein had a more pronounced effect on HLA class II binding affinities than on HLA class I. While binding affinity profiles for HLA class I were largely consistent across populations, significant population-specific variations were observed for HLA class II alleles. Specifically, the British population exhibited lower proportions of tightly binding mutated peptides compared to the Taiwanese and Russian populations. Furthermore, substantial differences were identified in the binding affinity changes of mutated Spike peptides for HLA class II across Taiwanese, British, and Russian populations, as well as between the Omicron EG.5 and XBB.1.16 variants. Subsequent analyses revealed significant differences in the conservation and evolutionary trajectories of binding affinities between mutated Spike peptides and common HLA class II alleles, both between the EG.5 and XBB.1.16 variants and across the three populations for the XBB.1.16 variant.
conclusionsIn summary, Spike protein mutations in SARS-CoV-2 variants significantly influence immune responses by altering HLA-peptide interactions, with pronounced population-specific effects on HLA class II alleles. These findings underscore the critical role of HLA class II diversity in shaping immune responses and susceptibility to COVID-19. Integrating population-specific HLA profiles into vaccine development and public health strategies is essential for improving interventions against evolving SARS-CoV-2 variants.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.