| Title: | Genome-wide association study of susceptibility to hospitalised respiratory infections |
| Journal: | Wellcome Open Research |
| Published: | 21 Nov 2023 |
| DOI: | https://doi.org/10.12688/wellcomeopenres.17230.2 |
Publication 8280
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Abstract
Background : Globally, respiratory infections contribute to significant morbidity and mortality. However, genetic determinants of respiratory infections are understudied and remain poorly understood. Methods : We conducted a genome-wide association study in 19,459 hospitalised respiratory infection cases and 101,438 controls from UK Biobank (Stage 1). We followed-up well-imputed top signals from our Stage 1 analysis in 50,912 respiratory infection cases and 150,442 controls from 11 cohorts (Stage 2). We aggregated effect estimates across studies using inverse variance-weighted meta-analyses. Additionally, we investigated the function of the top signals in order to gain understanding of the underlying biological mechanisms. Results : From our Stage 1 analysis, we report 56 signals at P <5 × 10 -6 , one of which was genome-wide significant ( P <5 × 10 -8 ). The genome-wide significant signal was in an intron of PBX3 , a gene that encodes pre-B-cell leukaemia transcription factor 3, a homeodomain-containing transcription factor. Further, the genome-wide significant signal was found to colocalise with gene-specific expression quantitative trait loci (eQTLs) affecting expression of PBX3 in lung tissue, where the respiratory infection risk alleles were associated with decreased PBX3 expression in lung tissue, highlighting a possible biological mechanism. Of the 56 signals, 40 were well-imputed in UK Biobank and were investigated in Stage 2. None of the 40 signals replicated, with effect estimates attenuated. Conclusions : Our Stage 1 analysis implicated PBX3 as a candidate causal gene and suggests a possible role of transcription factor binding activity in respiratory infection susceptibility. However, the PBX3 signal, and the other well-imputed signals, did not replicate in the meta-analysis of Stages 1 and 2. Significant phenotypic heterogeneity and differences in study ascertainment may have contributed to this lack of statistical replication. Overall, our study highlighted putative associations and possible biological mechanisms that may provide insight into respiratory infection susceptibility. </p>
47 Authors
- Alexander T. Williams
- Nick Shrine
- Hardeep Naghra-van Gijzel
- Joanna C. Betts
- Jing Chen
- Edith M. Hessel
- Catherine John
- Richard Packer
- Nicola F. Reeve
- Astrid J. Yeo
- Erik Abner
- Bjørn Olav Åsvold
- Juha Auvinen
- Traci M. Bartz
- Yuki Bradford
- Ben Brumpton
- Archie Campbell
- Michael H. Cho
- Su Chu
- David R. Crosslin
- QiPing Feng
- Tõnu Esko
- Sina A. Gharib
- Caroline Hayward
- Scott Hebbring
- Kristian Hveem
- Marjo-Riitta Järvelin
- Gail P. Jarvik
- Sarah H. Landis
- Eric B. Larson
- Jiangyuan Liu
- Ruth J.F. Loos
- Yuan Luo
- Arden Moscati
- Hana Mullerova
- Bahram Namjou
- David J. Porteous
- Jennifer K. Quint
- Marylyn D. Ritchie
- Eeva Sliz
- Ian B. Stanaway
- Laurent Thomas
- James F. Wilson
- Ian P. Hall
- Louise V. Wain
- David Michalovich
- Martin D. Tobin
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