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  5. Multi-ancestry meta-analysis of host genetic susceptibility to tuberculosis identifies shared genetic architecture
 
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Multi-ancestry meta-analysis of host genetic susceptibility to tuberculosis identifies shared genetic architecture
File(s)
elife-84394-v2.pdf (1.61 MB)
Published version
Author(s)
Schurz, Haiko
Naranbhai, Vivek
Yates, Tom A
Gilchrist, James
Parks, Tom
more
Type
Journal Article
Abstract
The heritability of susceptibility to tuberculosis (TB) disease has been well recognized. Over 100 genes have been studied as candidates for TB susceptibility, and several variants were identified by genome-wide association studies (GWAS), but few replicate. We established the International Tuberculosis Host Genetics Consortium to perform a multi-ancestry meta-analysis of GWAS, including 14,153 cases and 19,536 controls of African, Asian, and European ancestry. Our analyses demonstrate a substantial degree of heritability (pooled polygenic h2 = 26.3%, 95% CI 23.7–29.0%) for susceptibility to TB that is shared across ancestries, highlighting an important host genetic influence on disease. We identified one global host genetic correlate for TB at genome-wide significance (p<5 × 10-8) in the human leukocyte antigen (HLA)-II region (rs28383206, p-value=5.2 × 10-9) but failed to replicate variants previously associated with TB susceptibility. These data demonstrate the complex shared genetic architecture of susceptibility to TB and the importance of large-scale GWAS analysis across multiple ancestries experiencing different levels of infection pressure.
Date Issued
2024-01-15
Date Acceptance
2023-11-23
Citation
eLife, 2024, 12
URI
http://hdl.handle.net/10044/1/108711
URL
http://dx.doi.org/10.7554/elife.84394
DOI
https://www.dx.doi.org/10.7554/elife.84394
ISSN
2050-084X
Publisher
eLife Sciences Publications Ltd
Journal / Book Title
eLife
Volume
12
Copyright Statement
Copyright Schurz et al. This
article is distributed under the
terms of the Creative Commons
Attribution License, which
permits unrestricted use and
redistribution provided that the
original author and source are
credited.
License URL
Attribution 4.0 International
Identifier
http://dx.doi.org/10.7554/elife.84394
Publication Status
Published
Article Number
e84394
Date Publish Online
2024-01-15
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