Genome-wide analyses of variance in blood cell phenotypes provide new insights into complex trait biology and prediction
Blood cell phenotypes are routinely tested in healthcare to inform clinical decisions. Genetic variants influencing mean blood cell phenotypes have been used to understand disease aetiology and improve prediction; however, additional information may be captured by genetic effects on observed variance. Here, we mapped variance quantitative trait loci (vQTL), i.e. genetic loci associated with trait variance, for 29 blood cell phenotypes from the UK Biobank (N ~ 408,111). We discovered 176 independent blood cell vQTLs, of which 147 were not found by additive QTL mapping. vQTLs displayed on average 1.8-fold stronger negative selection than additive QTL, highlighting that selection acts to reduce extreme blood cell phenotypes. Variance polygenic scores (vPGSs) were constructed to stratify individuals in the INTERVAL cohort (N ~ 40,466), where the genetically most variable individuals had increased conventional PGS accuracy (by ~19%) relative to the genetically least variable individuals. Genetic prediction of blood cell traits improved by ~10% on average combining PGS with vPGS. Using Mendelian randomisation and vPGS association analyses, we found that alcohol consumption significantly increased blood cell trait variances highlighting the utility of blood cell vQTLs and vPGSs to provide novel insight into phenotype aetiology as well as improve prediction.
Authors
- David J. Roberts (ORCID: https://orcid.org/0000-0003-0648-6585)
- Samuel A. Lambert (ORCID: https://orcid.org/0000-0001-8222-008X)
- Scott C. Ritchie (ORCID: https://orcid.org/0000-0002-8454-9548)
- Chief Ben-Eghan (ORCID: https://orcid.org/0000-0001-7743-5991)
- Michael Inouye (ORCID: https://orcid.org/0000-0001-9413-6520)
- Ruidong Xiang (ORCID: https://orcid.org/0000-0002-1584-7605)
- Yu Xu (ORCID: https://orcid.org/0000-0002-7304-5045)
- Fumihiko Takeuchi (ORCID: https://orcid.org/0000-0003-3185-5661)
- Yang Liu (ORCID: https://orcid.org/0000-0002-6023-3776)
Institutions
- Baker Heart and Diabetes Institute (AU)
- The University of Melbourne (AU)
- La Trobe University (AU)
- University of Cambridge (GB)
- John Radcliffe Hospital (GB)
- British Heart Foundation (GB)
- National Institute for Health and Care Research (GB)
- National Center for Global Health and Medicine (JP)
- Bridge University (SS)
- Lung Institute (US)
- Agriculture Victoria (AU)
- Health Data Research UK (GB)
- AgriBio (AU)
- Genomics (United Kingdom) (GB)
Publication Details
- Journal
- Nature Communications
- Published
- 2025-05-07
- DOI
- https://doi.org/10.1038/s41467-025-59525-4
- Citations
- 3
- Primary Topic
- Genetic Associations and Epidemiology
- Type
- article
- Field-Weighted Citation Impact
- 5.45
Funders
- Scottish Government
- National Institute for Health and Care Research
- British Heart Foundation
- Department of Health and Social Care
- Public Health Agency
- National Institutes of Health
- Goddard Space Flight Center
- Chief Scientist Office, Scottish Government Health and Social Care Directorate
- Medical Research Council
- Engineering and Physical Sciences Research Council
- Economic and Social Research Council
- Health and Social Care Research and Development Division
- NIHR Cambridge Biomedical Research Centre