| Title: | Association of metabolomics measurements with blood cell phenotypes |
| Journal: | Blood Cells Molecules and Diseases |
| Published: | 4 Nov 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/41289847/ |
| DOI: | https://doi.org/10.1016/j.bcmd.2025.102966 |
| URL: | https://pmc.ncbi.nlm.nih.gov/articles/PMC12888047/ |
Publication 19040
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Abstract
Complete blood counts (CBCs) are commonly measured in clinical practice and are associated with different diseases and traits. Statistical adjustment for blood cell abundance or related traits in these metabolomic epidemiology studies is not a common practice. However, it is plausible that common and cheaply measured blood cells would capture some of the variation also captured by metabolomic measures. Here, we assessed the association between metabolites and blood cell traits with a multi-ethnic meta-analysis of named metabolites from untargeted panels in the JHS, MESA, ARIC, and the HCHS/SOL cohorts. Among 2859 metabolite and blood cell trait pairs measured in at least two cohorts, 734 (25.6 %) were significantly associated. We also tested metabolite-blood cell trait pairs in the UK Biobank with a targeted NMR-based metabolomics panel. A large percentage (92 %) of the tested pairs was significant, and adjustment for blood cells altered relationships between metabolites and age and sex. We evaluated metabolite effect size changes for metabolite association with different incident diseases adjusting for CBC traits using the UK Biobank. Most notably, the metabolomic effect sizes on COPD were downweighted after adjustment. Blood cell trait adjustment showed similar but not overlapping effect size changes when compared to adjusting for eGFR, which is a common covariate in metabolomics analyses to account for kidney function. Our results show that statistical adjustment for blood cell traits may reduce confounding and clarify additional predictive power above existing clinical biomarkers in metabolomic studies.</p>
11 Keywords
- Aged
- Biomarkers
- Blood Cell Count
- Blood Cells
- Female
- Humans
- Male
- Metabolome
- Metabolomics
- Middle Aged
- Phenotype
20 Authors
- Brian D Chen
- Amanda Tapia
- Eric Boerwinkle
- Clary B Clish
- Robert Gerszten
- Misa Graff
- Karen L Mohlke
- Alanna C Morrison
- Wimal Pathmasiri
- Stephen S Rich
- Jerome I Rotter
- Blake R Rushing
- Susan Sumner
- Russell P Tracy
- Kristin L Young
- Bing Yu
- Bharat Thyagarajan
- Alex P Reiner
- Yun Li
- Laura Raffield
1 Application
| Application ID | Title |
|---|---|
| 25953 | Transcriptome-wide Association Study of Cardiometabolic Traits in the UK Biobank Cohort |
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