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Machine learning reveals limited contribution of trans-only encoded variants to the HLA-DQ immunopeptidome

Nilsson, Jonas Birkelund ; Kaabinejadian, Saghar ; Yari, Hooman ; Peters, Bjoern ; Barra, Carolina ; Gragert, Loren ; Hildebrand, William ; Nielsen, Morten

Communications biology, 2023-04, Vol.6 (1), p.442-442, Article 442 [Periódico revisado por pares]

England: Nature Publishing Group

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  • Título:
    Machine learning reveals limited contribution of trans-only encoded variants to the HLA-DQ immunopeptidome
  • Autor: Nilsson, Jonas Birkelund ; Kaabinejadian, Saghar ; Yari, Hooman ; Peters, Bjoern ; Barra, Carolina ; Gragert, Loren ; Hildebrand, William ; Nielsen, Morten
  • Assuntos: Antigen presentation ; Autoimmune Diseases ; Biology ; Chromosomes ; Data mining ; Histocompatibility antigen HLA ; HLA Antigens ; HLA-DQ Antigens - chemistry ; HLA-DQ Antigens - genetics ; Humans ; Immune response (cell-mediated) ; Lymphocytes T ; Machine Learning ; Mass spectroscopy ; Molecular modelling ; T-Lymphocytes
  • É parte de: Communications biology, 2023-04, Vol.6 (1), p.442-442, Article 442
  • Notas: ObjectType-Article-1
    SourceType-Scholarly Journals-1
    ObjectType-Feature-2
    content type line 23
  • Descrição: Human leukocyte antigen (HLA) class II antigen presentation is key for controlling and triggering T cell immune responses. HLA-DQ molecules, which are believed to play a major role in autoimmune diseases, are heterodimers that can be formed as both cis and trans variants depending on whether the α- and β-chains are encoded on the same (cis) or opposite (trans) chromosomes. So far, limited progress has been made for predicting HLA-DQ antigen presentation. In addition, the contribution of trans-only variants (i.e. variants not observed in the population as cis) in shaping the HLA-DQ immunopeptidome remains largely unresolved. Here, we seek to address these issues by integrating state-of-the-art immunoinformatics data mining models with large volumes of high-quality HLA-DQ specific mass spectrometry immunopeptidomics data. The analysis demonstrates highly improved predictive power and molecular coverage for models trained including these novel HLA-DQ data. More importantly, investigating the role of trans-only HLA-DQ variants reveals a limited to no contribution to the overall HLA-DQ immunopeptidome. In conclusion, this study furthers our understanding of HLA-DQ specificities and casts light on the relative role of cis versus trans-only HLA-DQ variants in the HLA class II antigen presentation space. The developed method, NetMHCIIpan-4.2, is available at https://services.healthtech.dtu.dk/services/NetMHCIIpan-4.2 .
  • Editor: England: Nature Publishing Group
  • Idioma: Inglês
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