| Title: | No Evidence of Interaction Between FADS2 Genotype and Breastfeeding on Cognitive or Other Traits in the UK Biobank |
| Journal: | Behavior Genetics |
| Published: | 9 Dec 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/39652205/ |
| DOI: | https://doi.org/10.1007/s10519-024-10210-0 |
Publication 14033
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Abstract
Breastfeeding is hypothesised to benefit child health and cognitive functioning by providing long-chain polyunsaturated fatty acids, which are essential for brain development. In 2007, Caspi et al. found evidence in two cohorts for an interaction between genetic variation in the FADS2 gene (a gene involved in fatty acid metabolism) and breastfeeding on IQ. However, subsequent studies have provided mixed evidence for the existence of an interaction. We investigated the relationship between genetic variation in the FADS2 region, breastfeeding, and their interaction in up to 335,650 individuals from the UK Biobank. We tested for the interaction over a range of cognitive functioning tests, as well as educational attainment and other traits thought to be influenced by breastfeeding, including cardiometabolic traits, number of offspring, and atopic allergy. FADS2 alleles associated with an increase in docosahexaenoic acid in blood serum (the C allele of rs174575) were associated with decreased verbal-numerical reasoning (p=2.28×10-5$$p=2.28\times {10}^{-5}$$) and triglycerides (p=1.40×10-41$$p=1.40\times {10}^{-41}$$), increased number of offspring (p=3.40×10-5$$p=3.40\times {10}^{-5}$$), total cholesterol (p=5.28×10-36$$p=5.28\times {10}^{-36}$$), HDL (p=1.42×10-51$$p=1.42\times {10}^{-51}$$), and LDL cholesterol (p=1.46×10-21$$p=1.46\times {10}^{-21}$$). We observed no evidence of an interaction in any of the traits, regardless of the modelling strategy on any cognitive or non-cognitive traits. We postulate that the previous positive findings are likely to be spurious, perhaps due to lack of appropriate control for latent population structure.</p>
6 Authors
- Giulio Centorame
- Nicole M. Warrington
- Gibran Hemani
- Geng Wang
- George Davey Smith
- David M. Evans
1 Application
| Application ID | Title |
|---|---|
| 53641 | Determining the genetic and environmental aetiology of complex traits and diseases using existing and novel statistical methodologies |
Enabling scientific discoveries that improve human health