Genetic Analysis of Metabolite Levels in Europeans
Author Information
Author(s): George Nicholson, Mattias Rantalainen, Jia V. Li, Anthony D. Maher, Daniel Malmodin, Kourosh R. Ahmadi, Johan H. Faber, Amy Barrett, Josine L. Min, N. William Rayner, Henrik Toft, Maria Krestyaninova, Juris Viksna, Sudeshna Guha Neogi, Marc-Emmanuel Dumas, Ugis Sarkans, Peter Donnelly, Thomas Illig, Jerzy Adamski, Karsten Suhre, Maxine Allen, Krina T. Zondervan, Tim D. Spector, Jeremy K. Nicholson, John C. Lindon, Dorrit Baunsgaard, Elaine Holmes, Mark I. McCarthy, Chris C. Holmes
Primary Institution: University of Oxford
Hypothesis
Are there 1H NMR-detectable metabolites in urine or plasma that are strongly influenced by common single-locus genetic variation?
Conclusion
The study identified four metabolites whose concentrations are significantly associated with specific genetic variations, with two of the regions showing evidence of recent positive selection.
Supporting Evidence
- Four metabolites' concentrations exhibited significant, replicable association with SNP variation.
- Two of the three hit regions lie within haplotype blocks that carry the genetic signature of strong, recent, positive selection in European populations.
- The mQTLs explained 40%–64% of biological population variation in the corresponding metabolites' concentrations.
- By re-analyzing plasma samples using the Biocrates platform, the study replicated previous mQTL findings.
Takeaway
Scientists studied how certain genes affect the levels of small molecules in our body fluids, finding that some genes can strongly influence these levels.
Methodology
The study used 1H NMR spectroscopy to analyze plasma and urine samples from two cohorts, testing for associations between metabolite concentrations and genome-wide SNP data.
Potential Biases
Potential biases may arise from the twin study design and the specific populations sampled.
Limitations
The study primarily focused on individuals of European descent, which may limit the generalizability of the findings to other populations.
Participant Demographics
The study included 142 female twins and 69 participants from the Oxford Biobank, primarily of Northern European descent.
Statistical Information
P-Value
p<2.8×10−23
Confidence Interval
40%–64%
Statistical Significance
p<0.001
Digital Object Identifier (DOI)
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