Abstract
Large biobanks with whole-genome sequencing (WGS) now enable the association of noncoding rare variants with complex human traits. Given that >98% of the genome is available for exploration, the selection of noncoding variants remains a critical yet unresolved challenge in these analyses. Here we leverage knowledge of blood gene regulation and deleteriousness scores to select noncoding variants pertinent for association with blood-related traits. Integrating WGS and 42 blood cell count and biomarker measurements for 166,740 UK Biobank samples, we perform variant collapsing tests, identifying hundreds of gene–trait associations involving noncoding variants. However, we demonstrate that most of these noncoding rare variant associations (1) reproduce associations known from previous studies and (2) are driven by linkage disequilibrium between nearby common and rare variants. This study underscores the prevailing challenges in rare variant analysis and the need for caution when interpreting noncoding rare variant association results.
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Data availability
The lists of gene–trait associations identified here are available as Supplementary Tables 1–12. These lists and other source data are available via Zenodo at https://doi.org/10.5281/zenodo.15546894 (ref. 68). The WGS data and individual phenotypes used for association testing can be accessed via the UKBB Research Analysis Platform: https://ukbiobank.dnanexus.com/landing. This platform is open to researchers who are listed as collaborators on UKBB-approved access applications. Public regulatory annotation datasets used include: the ABC models, available at https://www.engreitzlab.org/resources; promoter capture Hi-C data, obtained from ref. 28, accessible at https://osf.io/u8tzp; and CRDs obtained from the original publications29,30. CADD scores of deleteriousness are available at https://cadd.gs.washington.edu. Known gene–trait associations used are available in the GWAS catalog (https://www.ebi.ac.uk/gwas) and Genebass databases (https://app.genebass.org). Source data are provided with this paper.
Code availability
Code to reproduce analysis and plots are avilable via GitHub at https://github.com/diogomribeiro/noncoding_rarevariant and via Zenodo at https://doi.org/10.5281/zenodo.15546894.
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Acknowledgements
This work was funded by a Swiss National Science Foundation project grant (no. PP00P3_176977) to O.D. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. We thank Z. Kutalik for fruitful discussions and support.
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D.M.R. and R.J.H. performed the experiments. D.M.R. analyzed the data and wrote the manuscript with input from O.D. D.M.R., S.R. and O.D. conceived, designed and managed the study.
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O.D. is a current employee of Regeneron Genetics Center, which is a subsidiary of Regeneron Pharmaceuticals. D.M.R. currently works as a contractor for F. Hoffmann-La Roche AG. The other authors declare no competing interests.
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Ribeiro, D.M., Hofmeister, R.J., Rubinacci, S. et al. Noncoding rare variant associations with blood traits in 166,740 UK Biobank genomes. Nat Genet 57, 2146–2155 (2025). https://doi.org/10.1038/s41588-025-02288-x
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DOI: https://doi.org/10.1038/s41588-025-02288-x
