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Felix TROPF (University of Oxford) – “How gene-environment interaction shapes genetic discovery in the social sciences”
November 28, 12:00 pm - 1:00 pm
The Sociology Seminar: Thursdays
Time: 12:00 pm – 1:00 pm
Date: 28th of November 2018 Wednesday exceptionnally
Place: Room 3105, ENSAE.
Felix TROPF (University of Oxford) – “How gene-environment interaction shapes genetic discovery in the social sciences“
Abstract : The emerging field of sociogenomics has great potential to improve empirical, quantitative social science research. Genetic scores measuring an individual’s genetic predisposition for a trait can be used to control for genetic confounding in statistical models, to estimate the differential individual response to (social) environmental conditions, to increase power for the estimation of social science determinants and as instrumental variables in causal analysis of associations between social science variables. Genetic scores derived from genome-wide association studies, however, explain only a fraction of what we would expect based on heritability estimates obtained from whole-genome studies on single populations, known as the ‘hidden heritability’ puzzle. Using seven sampling populations (n=35,062), we test whether hidden heritability is attributed to heterogeneity across sampling populations and time, showing that estimates are substantially smaller across populations compared with within populations. We show that the hidden heritability varies substantially: from zero for height to 20% for body mass index, 37% for education, 40% for age at first birth and up to 75% for number of children. Simulations demonstrate that our results are more likely to reflect heterogeneity in phenotypic measurement or gene–environment interactions than genetic heterogeneity. These findings have substantial implications for genetic discovery, suggesting that large homogenous datasets are required for behavioural phenotypes and that gene–environment interaction may be a central challenge for genetic discovery. Nonetheless, the potential for implementing genetic scores based on such studies into social science research remains immense.
Jeanne GANAULT, Céline GOFFETTE, Sander WAGNER (Laboratoire de sociologie quantitative – CREST)