Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Pervasive additive and non-additive effects within the HLA region contribute to disease risk in the UK Biobank

View ORCID ProfileGuhan Ram Venkataraman, Julia Eve Olivieri, View ORCID ProfileChristopher DeBoever, View ORCID ProfileYosuke Tanigawa, View ORCID ProfileJohanne Marie Justesen, View ORCID ProfileAlexander Dilthey, View ORCID ProfileManuel A. Rivas
doi: https://doi.org/10.1101/2020.05.28.119669
Guhan Ram Venkataraman
1Department of Biomedical Data Science, School of Medicine, Stanford University, Stanford, CA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Guhan Ram Venkataraman
  • For correspondence: mrivas@stanford.edu
Julia Eve Olivieri
2Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Christopher DeBoever
1Department of Biomedical Data Science, School of Medicine, Stanford University, Stanford, CA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Christopher DeBoever
Yosuke Tanigawa
1Department of Biomedical Data Science, School of Medicine, Stanford University, Stanford, CA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Yosuke Tanigawa
Johanne Marie Justesen
1Department of Biomedical Data Science, School of Medicine, Stanford University, Stanford, CA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Johanne Marie Justesen
Alexander Dilthey
3Bioinformatics Core Facility, University of Cologne, Cologne, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Alexander Dilthey
Manuel A. Rivas
1Department of Biomedical Data Science, School of Medicine, Stanford University, Stanford, CA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Manuel A. Rivas
  • For correspondence: mrivas@stanford.edu
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Data/Code
  • Preview PDF
Loading

Abstract

The human leukocyte antigen (HLA) region is one of the most disease-associated regions of the human genome, yet even well-studied alleles in the HLA region have unknown impact on disease. Here, we study the effect of 156 HLA alleles on 677 binary phenotypes for 337,138 individuals in the UK Biobank. We assess HLA allele associations and subsequently use Bayesian Model Averaging for conditional analysis, a) replicating 88 known associations between HLA alleles and binary disease phenotypes such as cancer, and b) discovering 90 novel associations to phenotypes such as skin and reproductive tract cancers and to other phenotypes not previously associated with the HLA region (e.g. anemias and acne). We find several non-additive effects, suggesting a more complex landscape of disease-modifying effects throughout the region. Finally, we discover associations between homozygous HLA allele burden and several cancer and other phenotypes, suggesting that peptide presentation spectra as coded for by the HLA region are important in determining disease risk. Our results demonstrate the HLA region’s complexity and richness while underscoring its clinical relevance.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • We have added a homozygosity analysis and have made minor changes throughout. We have added Dr Alexander Dilthey as an author.

  • https://bit.ly/hla_sup_1

  • https://bit.ly/hla_sup_2

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
Back to top
PreviousNext
Posted June 12, 2020.
Download PDF
Data/Code
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Pervasive additive and non-additive effects within the HLA region contribute to disease risk in the UK Biobank
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Pervasive additive and non-additive effects within the HLA region contribute to disease risk in the UK Biobank
Guhan Ram Venkataraman, Julia Eve Olivieri, Christopher DeBoever, Yosuke Tanigawa, Johanne Marie Justesen, Alexander Dilthey, Manuel A. Rivas
bioRxiv 2020.05.28.119669; doi: https://doi.org/10.1101/2020.05.28.119669
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
Pervasive additive and non-additive effects within the HLA region contribute to disease risk in the UK Biobank
Guhan Ram Venkataraman, Julia Eve Olivieri, Christopher DeBoever, Yosuke Tanigawa, Johanne Marie Justesen, Alexander Dilthey, Manuel A. Rivas
bioRxiv 2020.05.28.119669; doi: https://doi.org/10.1101/2020.05.28.119669

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Genetics
Subject Areas
All Articles
  • Animal Behavior and Cognition (4227)
  • Biochemistry (9107)
  • Bioengineering (6751)
  • Bioinformatics (23944)
  • Biophysics (12089)
  • Cancer Biology (9495)
  • Cell Biology (13740)
  • Clinical Trials (138)
  • Developmental Biology (7616)
  • Ecology (11661)
  • Epidemiology (2066)
  • Evolutionary Biology (15479)
  • Genetics (10617)
  • Genomics (14296)
  • Immunology (9462)
  • Microbiology (22792)
  • Molecular Biology (9078)
  • Neuroscience (48888)
  • Paleontology (355)
  • Pathology (1479)
  • Pharmacology and Toxicology (2565)
  • Physiology (3823)
  • Plant Biology (8308)
  • Scientific Communication and Education (1467)
  • Synthetic Biology (2290)
  • Systems Biology (6172)
  • Zoology (1297)