Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Reply to: Genotype by sex interactions in ankylosing spondylitis

The Original Article was published on 09 January 2023

This is a preview of subscription content, access via your institution

Access options

Buy article

Get time limited or full article access on ReadCube.

$32.00

All prices are NET prices.

Data availability

The data used pertain to the GTEx project v.8. Gene expression data are freely available at https://gtexportal.org/home/. GTEx genotype data are available on application through the database of Genotypes and Phenotypes. This research was conducted using the UK Biobank resource under project no. 788. The GTEx regulatory and consent protocols can be found at https://biospecimens.cancer.gov/resources/sops/library.asp.

Code availability

We used PLINK v.1.9 to run our eQTL analysis, which is freely available online at https://www.cog-genomics.org/plink2/. The custom Python code is openly available at Zenodo https://doi.org/10.5281/zenodo.7093777.

References

  1. Bernabeu, E. et al. Sex differences in genetic architecture in the UK Biobank. Nat. Genet. 53, 1283–1289 (2021).

    Article  CAS  Google Scholar 

  2. Li, Z. et al. Genotype by sex interactions in ankylosing spondylitis. Nat. Genet. https://doi.org/10.1038/s41588-022-01250-5 (2023).

  3. Zhou, X. & Reveille, J. D. Imputation-based analysis of MICA alleles in the susceptibility to ankylosing spondylitis. Ann. Rheum. Dis. 79, e1 (2020).

    Article  Google Scholar 

  4. Cortes, A. et al. Imputation-based analysis of MICA alleles in the susceptibility to ankylosing spondylitis. Ann. Rheum. Dis. 77, 1691–1692 (2018).

    Article  CAS  Google Scholar 

  5. Zhou, W. et al. Efficiently controlling for case-control imbalance and sample relatedness in large-scale genetic association studies. Nat. Genet. 50, 1335–1341 (2018).

    Article  CAS  Google Scholar 

  6. Mbatchou, J. et al. Computationally efficient whole-genome regression for quantitative and binary traits. Nat. Genet. 53, 1097–1103 (2021).

    Article  CAS  Google Scholar 

  7. Jiang, L., Zheng, Z., Fang, H. & Yang, J. A generalized linear mixed model association tool for biobank-scale data. Nat. Genet. 53, 1616–1621 (2021).

    Article  CAS  Google Scholar 

  8. Loh, P.-R., Kichaev, G., Gazal, S., Schoech, A. P. & Price, A. L. Mixed-model association for biobank-scale datasets. Nat. Genet. 50, 906–908 (2018).

    Article  CAS  Google Scholar 

  9. Auton, A. et al. A global reference for human genetic variation. Nature 526, 68–74 (2015).

    Article  Google Scholar 

  10. Porcu, E. et al. Limited evidence for blood eQTLs in human sexual dimorphism. Genome Med. 14, 89 (2022).

    Article  CAS  Google Scholar 

  11. Oliva, M. et al. The impact of sex on gene expression across human tissues. Science 369, eaba3066 (2020).

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Contributions

E.B. drafted the primary text with input from K.R., J.P., A. Tenesa, O.C.-X. and A. Talenti. All authors reviewed and approved the final draft.

Corresponding authors

Correspondence to Elena Bernabeu or Albert Tenesa.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Genetics thanks Seunggeun Lee and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Note containing Methods and Tables 1 and 2.

Reporting Summary

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Bernabeu, E., Rawlik, K., Canela-Xandri, O. et al. Reply to: Genotype by sex interactions in ankylosing spondylitis. Nat Genet 55, 17–18 (2023). https://doi.org/10.1038/s41588-022-01251-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41588-022-01251-4

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing