Noncoding rare variant associations with blood traits in 166,740 UK Biobank genomes
Diogo M Ribeiro1, Robin J Hofmeister2, Simone Rubinacci3,4
1Department of Computational Biology, University of Lausanne, Lausanne, Switzerland. diogo.am.ribeiro@gmail.com.
Nature Genetics
|August 7, 2025
Summary
Researchers used whole-genome sequencing to analyze noncoding rare variants associated with blood traits in the UK Biobank. Most identified associations were not novel and likely due to linkage disequilibrium, highlighting challenges in rare variant analysis.
Area of Science:
- Genetics
- Genomics
- Bioinformatics
Background:
- Large biobanks with whole-genome sequencing (WGS) data facilitate the study of rare variants in complex human traits.
- Identifying relevant noncoding variants for association studies remains a significant challenge due to the vastness of the genome (>98%).
Purpose of the Study:
- To select and analyze noncoding variants associated with blood-related traits using gene regulation and deleteriousness information.
- To investigate the novelty and underlying mechanisms of noncoding rare variant associations with blood traits.
Main Methods:
- Integration of whole-genome sequencing (WGS) data with 42 blood cell count and biomarker measurements from 166,740 UK Biobank participants.
- Application of variant collapsing tests to identify gene-trait associations involving noncoding variants.
- Evaluation of identified associations for novelty and potential confounding by linkage disequilibrium (LD).
Main Results:
- Hundreds of gene-trait associations involving noncoding variants were identified.
- The majority of these associations were found to replicate previously known associations.
- A significant portion of the identified associations were attributed to linkage disequilibrium between common and rare variants.
Conclusions:
- The study highlights the difficulties in rare variant analysis, particularly for noncoding regions.
- Caution is advised when interpreting association results involving noncoding rare variants due to potential confounding factors like LD.
- Leveraging gene regulation and deleteriousness scores can aid in selecting pertinent noncoding variants, but validation remains crucial.
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