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HLA class I allele promiscuity revisited

Overview of attention for article published in Immunogenetics, June 2011
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Title
HLA class I allele promiscuity revisited
Published in
Immunogenetics, June 2011
DOI 10.1007/s00251-011-0552-6
Pubmed ID
Authors

Xiangyu Rao, Ilka Hoof, Ana Isabel C. A. Fontaine Costa, Debbie van Baarle, Can Keşmir

Abstract

The peptide repertoire presented on human leukocyte antigen (HLA) class I molecules is largely determined by the structure of the peptide binding groove. It is expected that the molecules having similar grooves (i.e., belonging to the same supertype) might present similar/overlapping peptides. However, the extent of promiscuity among HLA class I ligands remains controversial: while in many studies T cell responses are detected against epitopes presented by alternative molecules across HLA class I supertypes and loci, peptide elution studies report minute overlaps between the peptide repertoires of even related HLA molecules. To get more insight into the promiscuous peptide binding by HLA molecules, we analyzed the HLA peptide binding data from the large epitope repository, Immune Epitope Database (IEDB), and further performed in silico analysis to estimate the promiscuity at the population level. Both analyses suggest that an unexpectedly large fraction of HLA ligands (> 50%) bind two or more HLA molecules, often across supertype or even loci. These results suggest that different HLA class I molecules can nevertheless present largely overlapping peptide sets, and that "functional" HLA polymorphism on individual and population level is probably much lower than previously anticipated.

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Mendeley readers

The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
India 1 2%
Nigeria 1 2%
Unknown 42 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 27%
Researcher 9 20%
Student > Master 6 13%
Student > Bachelor 4 9%
Professor 4 9%
Other 6 13%
Unknown 4 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 23 51%
Biochemistry, Genetics and Molecular Biology 8 18%
Immunology and Microbiology 6 13%
Nursing and Health Professions 1 2%
Computer Science 1 2%
Other 3 7%
Unknown 3 7%