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HLA allele-calling using multi-ancestry whole-exome sequencing from the UK Biobank identifies 129 novel associations in 11 autoimmune diseases
The human leukocyte antigen (HLA) region on chromosome 6 is strongly associated with many immune-mediated and infection-related diseases. Due to its highly polymorphic nature and complex linkage disequilibrium patterns, traditional genetic association studies of single nucleotide polymorphisms do no...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10624861/ https://www.ncbi.nlm.nih.gov/pubmed/37923823 http://dx.doi.org/10.1038/s42003-023-05496-5 |
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author | Butler-Laporte, Guillaume Farjoun, Joseph Nakanishi, Tomoko Lu, Tianyuan Abner, Erik Chen, Yiheng Hultström, Michael Metspalu, Andres Milani, Lili Mägi, Reedik Nelis, Mari Hudjashov, Georgi Yoshiji, Satoshi Ilboudo, Yann Liang, Kevin Y. H. Su, Chen-Yang Willet, Julian D. S. Esko, Tõnu Zhou, Sirui Forgetta, Vincenzo Taliun, Daniel Richards, J. Brent |
author_facet | Butler-Laporte, Guillaume Farjoun, Joseph Nakanishi, Tomoko Lu, Tianyuan Abner, Erik Chen, Yiheng Hultström, Michael Metspalu, Andres Milani, Lili Mägi, Reedik Nelis, Mari Hudjashov, Georgi Yoshiji, Satoshi Ilboudo, Yann Liang, Kevin Y. H. Su, Chen-Yang Willet, Julian D. S. Esko, Tõnu Zhou, Sirui Forgetta, Vincenzo Taliun, Daniel Richards, J. Brent |
author_sort | Butler-Laporte, Guillaume |
collection | PubMed |
description | The human leukocyte antigen (HLA) region on chromosome 6 is strongly associated with many immune-mediated and infection-related diseases. Due to its highly polymorphic nature and complex linkage disequilibrium patterns, traditional genetic association studies of single nucleotide polymorphisms do not perform well in this region. Instead, the field has adopted the assessment of the association of HLA alleles (i.e., entire HLA gene haplotypes) with disease. Often based on genotyping arrays, these association studies impute HLA alleles, decreasing accuracy and thus statistical power for rare alleles and in non-European ancestries. Here, we use whole-exome sequencing (WES) from 454,824 UK Biobank (UKB) participants to directly call HLA alleles using the HLA-HD algorithm. We show this method is more accurate than imputing HLA alleles and harness the improved statistical power to identify 360 associations for 11 auto-immune phenotypes (at least 129 likely novel), leading to better insights into the specific coding polymorphisms that underlie these diseases. We show that HLA alleles with synonymous variants, often overlooked in HLA studies, can significantly influence these phenotypes. Lastly, we show that HLA sequencing may improve polygenic risk scores accuracy across ancestries. These findings allow better characterization of the role of the HLA region in human disease. |
format | Online Article Text |
id | pubmed-10624861 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-106248612023-11-05 HLA allele-calling using multi-ancestry whole-exome sequencing from the UK Biobank identifies 129 novel associations in 11 autoimmune diseases Butler-Laporte, Guillaume Farjoun, Joseph Nakanishi, Tomoko Lu, Tianyuan Abner, Erik Chen, Yiheng Hultström, Michael Metspalu, Andres Milani, Lili Mägi, Reedik Nelis, Mari Hudjashov, Georgi Yoshiji, Satoshi Ilboudo, Yann Liang, Kevin Y. H. Su, Chen-Yang Willet, Julian D. S. Esko, Tõnu Zhou, Sirui Forgetta, Vincenzo Taliun, Daniel Richards, J. Brent Commun Biol Article The human leukocyte antigen (HLA) region on chromosome 6 is strongly associated with many immune-mediated and infection-related diseases. Due to its highly polymorphic nature and complex linkage disequilibrium patterns, traditional genetic association studies of single nucleotide polymorphisms do not perform well in this region. Instead, the field has adopted the assessment of the association of HLA alleles (i.e., entire HLA gene haplotypes) with disease. Often based on genotyping arrays, these association studies impute HLA alleles, decreasing accuracy and thus statistical power for rare alleles and in non-European ancestries. Here, we use whole-exome sequencing (WES) from 454,824 UK Biobank (UKB) participants to directly call HLA alleles using the HLA-HD algorithm. We show this method is more accurate than imputing HLA alleles and harness the improved statistical power to identify 360 associations for 11 auto-immune phenotypes (at least 129 likely novel), leading to better insights into the specific coding polymorphisms that underlie these diseases. We show that HLA alleles with synonymous variants, often overlooked in HLA studies, can significantly influence these phenotypes. Lastly, we show that HLA sequencing may improve polygenic risk scores accuracy across ancestries. These findings allow better characterization of the role of the HLA region in human disease. Nature Publishing Group UK 2023-11-03 /pmc/articles/PMC10624861/ /pubmed/37923823 http://dx.doi.org/10.1038/s42003-023-05496-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Butler-Laporte, Guillaume Farjoun, Joseph Nakanishi, Tomoko Lu, Tianyuan Abner, Erik Chen, Yiheng Hultström, Michael Metspalu, Andres Milani, Lili Mägi, Reedik Nelis, Mari Hudjashov, Georgi Yoshiji, Satoshi Ilboudo, Yann Liang, Kevin Y. H. Su, Chen-Yang Willet, Julian D. S. Esko, Tõnu Zhou, Sirui Forgetta, Vincenzo Taliun, Daniel Richards, J. Brent HLA allele-calling using multi-ancestry whole-exome sequencing from the UK Biobank identifies 129 novel associations in 11 autoimmune diseases |
title | HLA allele-calling using multi-ancestry whole-exome sequencing from the UK Biobank identifies 129 novel associations in 11 autoimmune diseases |
title_full | HLA allele-calling using multi-ancestry whole-exome sequencing from the UK Biobank identifies 129 novel associations in 11 autoimmune diseases |
title_fullStr | HLA allele-calling using multi-ancestry whole-exome sequencing from the UK Biobank identifies 129 novel associations in 11 autoimmune diseases |
title_full_unstemmed | HLA allele-calling using multi-ancestry whole-exome sequencing from the UK Biobank identifies 129 novel associations in 11 autoimmune diseases |
title_short | HLA allele-calling using multi-ancestry whole-exome sequencing from the UK Biobank identifies 129 novel associations in 11 autoimmune diseases |
title_sort | hla allele-calling using multi-ancestry whole-exome sequencing from the uk biobank identifies 129 novel associations in 11 autoimmune diseases |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10624861/ https://www.ncbi.nlm.nih.gov/pubmed/37923823 http://dx.doi.org/10.1038/s42003-023-05496-5 |
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