Significant variation between SNP-based HLA imputations in diverse populations: the last mile is the hardest.
Identifieur interne : 000376 ( Main/Exploration ); précédent : 000375; suivant : 000377Significant variation between SNP-based HLA imputations in diverse populations: the last mile is the hardest.
Auteurs : D J Pappas [États-Unis] ; A. Lizee [États-Unis] ; V. Paunic [États-Unis] ; K R Beutner [États-Unis] ; A. Motyer [Australie] ; D. Vukcevic [Australie] ; S. Leslie [Australie] ; J. Biesiada [États-Unis] ; J. Meller [États-Unis] ; K D Taylor [États-Unis] ; X. Zheng [États-Unis] ; L P Zhao [États-Unis] ; P-A Gourraud [États-Unis] ; J A Hollenbach [États-Unis] ; S J Mack [États-Unis] ; M. Maiers [États-Unis]Source :
- The pharmacogenomics journal [ 1473-1150 ] ; 2017.
Abstract
Four single nucleotide polymorphism (SNP)-based human leukocyte antigen (HLA) imputation methods (e-HLA, HIBAG, HLA*IMP:02 and MAGPrediction) were trained using 1000 Genomes SNP and HLA genotypes and assessed for their ability to accurately impute molecular HLA-A, -B, -C and -DRB1 genotypes in the Human Genome Diversity Project cell panel. Imputation concordance was high (>89%) across all methods for both HLA-A and HLA-C, but HLA-B and HLA-DRB1 proved generally difficult to impute. Overall, <27.8% of subjects were correctly imputed for all HLA loci by any method. Concordance across all loci was not enhanced via the application of confidence thresholds; reliance on confidence scores across methods only led to noticeable improvement (+3.2%) for HLA-DRB1. As the HLA complex is highly relevant to the study of human health and disease, a standardized assessment of SNP-based HLA imputation methods is crucial for advancing genomic research. Considerable room remains for the improvement of HLA-B and especially HLA-DRB1 imputation methods, and no imputation method is as accurate as molecular genotyping. The application of large, ancestrally diverse HLA and SNP reference data sets and multiple imputation methods has the potential to make SNP-based HLA imputation methods a tractable option for determining HLA genotypes.The Pharmacogenomics Journal advance online publication, 25 April 2017; doi:10.1038/tpj.2017.7.
DOI: 10.1038/tpj.2017.7
PubMed: 28440342
Affiliations:
- Australie, États-Unis
- Californie, Minnesota, Ohio, Victoria (État), Washington (État)
- Melbourne, Seattle
- Université de Melbourne, Université de Washington
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Lizee</name><affiliation wicri:level="2"><nlm:affiliation>Department of Neurology, University of California, San Francisco, CA, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Neurology, University of California, San Francisco, CA</wicri:regionArea><placeName><region type="state">Californie</region></placeName></affiliation></author><author><name sortKey="Paunic, V" sort="Paunic, V" uniqKey="Paunic V" first="V" last="Paunic">V. Paunic</name><affiliation wicri:level="2"><nlm:affiliation>Bioinformatics Research Department, National Marrow Donor Program, Minneapolis, MN, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Bioinformatics Research Department, National Marrow Donor Program, Minneapolis, MN</wicri:regionArea><placeName><region type="state">Minnesota</region></placeName></affiliation></author><author><name sortKey="Beutner, K R" sort="Beutner, K R" uniqKey="Beutner K" first="K R" last="Beutner">K R Beutner</name><affiliation wicri:level="2"><nlm:affiliation>Department of Neurology, University of California, San Francisco, CA, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Neurology, University of California, San Francisco, CA</wicri:regionArea><placeName><region type="state">Californie</region></placeName></affiliation></author><author><name sortKey="Motyer, A" sort="Motyer, A" uniqKey="Motyer A" first="A" last="Motyer">A. Motyer</name><affiliation wicri:level="4"><nlm:affiliation>Centre for Systems Genomics, Schools of Mathematics and Statistics, and BioSciences, The University of Melbourne, Melbourne, VIC, Australia.</nlm:affiliation><country xml:lang="fr">Australie</country><wicri:regionArea>Centre for Systems Genomics, Schools of Mathematics and Statistics, and BioSciences, The University of Melbourne, Melbourne, VIC</wicri:regionArea><orgName type="university">Université de Melbourne</orgName><placeName><settlement type="city">Melbourne</settlement><region type="état">Victoria (État)</region></placeName></affiliation></author><author><name sortKey="Vukcevic, D" sort="Vukcevic, D" uniqKey="Vukcevic D" first="D" last="Vukcevic">D. Vukcevic</name><affiliation wicri:level="4"><nlm:affiliation>Centre for Systems Genomics, Schools of Mathematics and Statistics, and BioSciences, The University of Melbourne, Melbourne, VIC, Australia.</nlm:affiliation><country xml:lang="fr">Australie</country><wicri:regionArea>Centre for Systems Genomics, Schools of Mathematics and Statistics, and BioSciences, The University of Melbourne, Melbourne, VIC</wicri:regionArea><orgName type="university">Université de Melbourne</orgName><placeName><settlement type="city">Melbourne</settlement><region type="état">Victoria (État)</region></placeName></affiliation></author><author><name sortKey="Leslie, S" sort="Leslie, S" uniqKey="Leslie S" first="S" last="Leslie">S. Leslie</name><affiliation wicri:level="4"><nlm:affiliation>Centre for Systems Genomics, Schools of Mathematics and Statistics, and BioSciences, The University of Melbourne, Melbourne, VIC, Australia.</nlm:affiliation><country xml:lang="fr">Australie</country><wicri:regionArea>Centre for Systems Genomics, Schools of Mathematics and Statistics, and BioSciences, The University of Melbourne, Melbourne, VIC</wicri:regionArea><orgName type="university">Université de Melbourne</orgName><placeName><settlement type="city">Melbourne</settlement><region type="état">Victoria (État)</region></placeName></affiliation></author><author><name sortKey="Biesiada, J" sort="Biesiada, J" uniqKey="Biesiada J" first="J" last="Biesiada">J. Biesiada</name><affiliation wicri:level="2"><nlm:affiliation>Department of Biomedical Informatics, Cincinnati Children's Hospital Medical Center & Department of Environmental Health, University of Cincinnati, Cincinnati, OH, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biomedical Informatics, Cincinnati Children's Hospital Medical Center & Department of Environmental Health, University of Cincinnati, Cincinnati, OH</wicri:regionArea><placeName><region type="state">Ohio</region></placeName></affiliation></author><author><name sortKey="Meller, J" sort="Meller, J" uniqKey="Meller J" first="J" last="Meller">J. Meller</name><affiliation wicri:level="2"><nlm:affiliation>Department of Biomedical Informatics, Cincinnati Children's Hospital Medical Center & Department of Environmental Health, University of Cincinnati, Cincinnati, OH, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biomedical Informatics, Cincinnati Children's Hospital Medical Center & Department of Environmental Health, University of Cincinnati, Cincinnati, OH</wicri:regionArea><placeName><region type="state">Ohio</region></placeName></affiliation></author><author><name sortKey="Taylor, K D" sort="Taylor, K D" uniqKey="Taylor K" first="K D" last="Taylor">K D Taylor</name><affiliation wicri:level="2"><nlm:affiliation>Los Angeles Biomedical Research Institute, Torrance, CA, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Los Angeles Biomedical Research Institute, Torrance, CA</wicri:regionArea><placeName><region type="state">Californie</region></placeName></affiliation></author><author><name sortKey="Zheng, X" sort="Zheng, X" uniqKey="Zheng X" first="X" last="Zheng">X. Zheng</name><affiliation wicri:level="4"><nlm:affiliation>Department of Biostatistics, University of Washington, Seattle, WA, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biostatistics, University of Washington, Seattle, WA</wicri:regionArea><placeName><region type="state">Washington (État)</region><settlement type="city">Seattle</settlement></placeName><orgName type="university">Université de Washington</orgName></affiliation></author><author><name sortKey="Zhao, L P" sort="Zhao, L P" uniqKey="Zhao L" first="L P" last="Zhao">L P Zhao</name><affiliation wicri:level="2"><nlm:affiliation>Fred Hutchinson Cancer Research Center, Seattle, WA, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Fred Hutchinson Cancer Research Center, Seattle, WA</wicri:regionArea><placeName><region type="state">Washington (État)</region></placeName></affiliation></author><author><name sortKey="Gourraud, P A" sort="Gourraud, P A" uniqKey="Gourraud P" first="P-A" last="Gourraud">P-A Gourraud</name><affiliation wicri:level="2"><nlm:affiliation>Department of Neurology, University of California, San Francisco, CA, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Neurology, University of California, San Francisco, CA</wicri:regionArea><placeName><region type="state">Californie</region></placeName></affiliation></author><author><name sortKey="Hollenbach, J A" sort="Hollenbach, J A" uniqKey="Hollenbach J" first="J A" last="Hollenbach">J A Hollenbach</name><affiliation wicri:level="2"><nlm:affiliation>Department of Neurology, University of California, San Francisco, CA, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Neurology, University of California, San Francisco, CA</wicri:regionArea><placeName><region type="state">Californie</region></placeName></affiliation></author><author><name sortKey="Mack, S J" sort="Mack, S J" uniqKey="Mack S" first="S J" last="Mack">S J Mack</name><affiliation wicri:level="2"><nlm:affiliation>Center for Genetics, Children's Hospital Research Institute, Oakland, CA, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Center for Genetics, Children's Hospital Research Institute, Oakland, CA</wicri:regionArea><placeName><region type="state">Californie</region></placeName></affiliation></author><author><name sortKey="Maiers, M" sort="Maiers, M" uniqKey="Maiers M" first="M" last="Maiers">M. Maiers</name><affiliation wicri:level="2"><nlm:affiliation>Bioinformatics Research Department, National Marrow Donor Program, Minneapolis, MN, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Bioinformatics Research Department, National Marrow Donor Program, Minneapolis, MN</wicri:regionArea><placeName><region type="state">Minnesota</region></placeName></affiliation></author></analytic><series><title level="j">The pharmacogenomics journal</title><idno type="eISSN">1473-1150</idno><imprint><date when="2017" type="published">2017</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Four single nucleotide polymorphism (SNP)-based human leukocyte antigen (HLA) imputation methods (e-HLA, HIBAG, HLA*IMP:02 and MAGPrediction) were trained using 1000 Genomes SNP and HLA genotypes and assessed for their ability to accurately impute molecular HLA-A, -B, -C and -DRB1 genotypes in the Human Genome Diversity Project cell panel. Imputation concordance was high (>89%) across all methods for both HLA-A and HLA-C, but HLA-B and HLA-DRB1 proved generally difficult to impute. Overall, <27.8% of subjects were correctly imputed for all HLA loci by any method. Concordance across all loci was not enhanced via the application of confidence thresholds; reliance on confidence scores across methods only led to noticeable improvement (+3.2%) for HLA-DRB1. As the HLA complex is highly relevant to the study of human health and disease, a standardized assessment of SNP-based HLA imputation methods is crucial for advancing genomic research. Considerable room remains for the improvement of HLA-B and especially HLA-DRB1 imputation methods, and no imputation method is as accurate as molecular genotyping. The application of large, ancestrally diverse HLA and SNP reference data sets and multiple imputation methods has the potential to make SNP-based HLA imputation methods a tractable option for determining HLA genotypes.The Pharmacogenomics Journal advance online publication, 25 April 2017; doi:10.1038/tpj.2017.7.</div></front></TEI><affiliations><list><country><li>Australie</li><li>États-Unis</li></country><region><li>Californie</li><li>Minnesota</li><li>Ohio</li><li>Victoria (État)</li><li>Washington (État)</li></region><settlement><li>Melbourne</li><li>Seattle</li></settlement><orgName><li>Université de Melbourne</li><li>Université de Washington</li></orgName></list><tree><country name="États-Unis"><region name="Californie"><name sortKey="Pappas, D J" sort="Pappas, D J" uniqKey="Pappas D" first="D J" last="Pappas">D J Pappas</name></region><name sortKey="Beutner, K R" sort="Beutner, K R" uniqKey="Beutner K" first="K R" last="Beutner">K R Beutner</name><name sortKey="Biesiada, J" sort="Biesiada, J" uniqKey="Biesiada J" first="J" last="Biesiada">J. Biesiada</name><name sortKey="Gourraud, P A" sort="Gourraud, P A" uniqKey="Gourraud P" first="P-A" last="Gourraud">P-A Gourraud</name><name sortKey="Hollenbach, J A" sort="Hollenbach, J A" uniqKey="Hollenbach J" first="J A" last="Hollenbach">J A Hollenbach</name><name sortKey="Lizee, A" sort="Lizee, A" uniqKey="Lizee A" first="A" last="Lizee">A. Lizee</name><name sortKey="Mack, S J" sort="Mack, S J" uniqKey="Mack S" first="S J" last="Mack">S J Mack</name><name sortKey="Maiers, M" sort="Maiers, M" uniqKey="Maiers M" first="M" last="Maiers">M. Maiers</name><name sortKey="Meller, J" sort="Meller, J" uniqKey="Meller J" first="J" last="Meller">J. Meller</name><name sortKey="Paunic, V" sort="Paunic, V" uniqKey="Paunic V" first="V" last="Paunic">V. Paunic</name><name sortKey="Taylor, K D" sort="Taylor, K D" uniqKey="Taylor K" first="K D" last="Taylor">K D Taylor</name><name sortKey="Zhao, L P" sort="Zhao, L P" uniqKey="Zhao L" first="L P" last="Zhao">L P Zhao</name><name sortKey="Zheng, X" sort="Zheng, X" uniqKey="Zheng X" first="X" last="Zheng">X. Zheng</name></country><country name="Australie"><region name="Victoria (État)"><name sortKey="Motyer, A" sort="Motyer, A" uniqKey="Motyer A" first="A" last="Motyer">A. Motyer</name></region><name sortKey="Leslie, S" sort="Leslie, S" uniqKey="Leslie S" first="S" last="Leslie">S. Leslie</name><name sortKey="Vukcevic, D" sort="Vukcevic, D" uniqKey="Vukcevic D" first="D" last="Vukcevic">D. Vukcevic</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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