Projects per year
Abstract / Description of output
Background: Sex differences are a common feature of human traits; however, the role sex determination plays in human genetic variation remains unclear. The presence of gene-by-sex (GxS) interactions implies that trait genetic architecture differs between men and women. Here, we show that GxS interactions and genetic heterogeneity among sexes are small but common features of a range of high-level complex traits.
Results: We analyzed 19 complex traits measured in 54,040 unrelated men and 59,820 unrelated women from the UK Biobank cohort to estimate autosomal genetic correlations and heritability differences between men and women. For 13 of the 19 traits examined, there is evidence that the trait measured is genetically different between males and females. We find that estimates of genetic correlations, based on ~114,000 unrelated individuals and ~19,000 related individuals from the same cohort, are largely consistent. Genetic predictors using a sex-specific model that incorporated GxS interactions led to a relative improvement of up to 4 % (mean 1.4 % across all relevant phenotypes) over those provided by a sex-agnostic model. This further supports the hypothesis of the presence of sexual genetic heterogeneity across high-level phenotypes.
Conclusions: The sex-specific environment seems to play a role in changing genotype expression across a range of human complex traits. Further studies of GxS interactions for high-level human traits may shed light on the molecular mechanisms that lead to biological differences between men and women. However, this may be a challenging endeavour due to the likely small effects of the interactions at individual loci.
Results: We analyzed 19 complex traits measured in 54,040 unrelated men and 59,820 unrelated women from the UK Biobank cohort to estimate autosomal genetic correlations and heritability differences between men and women. For 13 of the 19 traits examined, there is evidence that the trait measured is genetically different between males and females. We find that estimates of genetic correlations, based on ~114,000 unrelated individuals and ~19,000 related individuals from the same cohort, are largely consistent. Genetic predictors using a sex-specific model that incorporated GxS interactions led to a relative improvement of up to 4 % (mean 1.4 % across all relevant phenotypes) over those provided by a sex-agnostic model. This further supports the hypothesis of the presence of sexual genetic heterogeneity across high-level phenotypes.
Conclusions: The sex-specific environment seems to play a role in changing genotype expression across a range of human complex traits. Further studies of GxS interactions for high-level human traits may shed light on the molecular mechanisms that lead to biological differences between men and women. However, this may be a challenging endeavour due to the likely small effects of the interactions at individual loci.
Original language | English |
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Article number | 166 |
Number of pages | 8 |
Journal | Genome Biology |
Volume | 17 |
DOIs | |
Publication status | Published - 29 Jul 2016 |
Keywords / Materials (for Non-textual outputs)
- gene-by-sex interactions
- sex specific genetic architecture
- genomic prediction
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Dive into the research topics of 'Evidence for sex-specific genetic architectures across a spectrum of human complex traits'. Together they form a unique fingerprint.Projects
- 1 Finished
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ISP1: Analysis and prediction in complex animal systems
Tenesa, A., Archibald, A., Beard, P., Bishop, S., Bronsvoort, M., Burt, D., Freeman, T., Haley, C., Hocking, P., Houston, R., Hume, D., Joshi, A., Law, A., Michoel, T., Summers, K., Vernimmen, D., Watson, M., Wiener, P., Wilson, A., Woolliams, J., Ait-Ali, T., Barnett, M., Carlisle, A., Finlayson, H., Haga, I., Karavolos, M., Matika, O., Paterson, T., Paton, B., Pong-Wong, R., Robert, C. & Robertson, G.
1/04/12 → 31/03/17
Project: Research
Profiles
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Oriol Canela Xandri
- Deanery of Molecular, Genetic and Population Health Sciences - Chancellor's Fellow
- MRC Human Genetics Unit
Person: Academic: Research Active
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Albert Tenesa
- Royal (Dick) School of Veterinary Studies - Personal chair of Quantitative Genetics
Person: Academic: Research Active