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Can education be personalised using pupils’ genetic data?

View ORCID ProfileTim T Morris, View ORCID ProfileNeil M Davies, View ORCID ProfileGeorge Davey Smith
doi: https://doi.org/10.1101/645218
Tim T Morris
1MRC Integrative Epidemiology Unit at the University of Bristol, BS8 2BN, United Kingdom
2Population Health Sciences, Bristol Medical School, University of Bristol, Barley House, Oakfield Grove, Bristol, BS8 2BN, United Kingdom
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  • For correspondence: Tim.Morris@bristol.ac.uk
Neil M Davies
1MRC Integrative Epidemiology Unit at the University of Bristol, BS8 2BN, United Kingdom
2Population Health Sciences, Bristol Medical School, University of Bristol, Barley House, Oakfield Grove, Bristol, BS8 2BN, United Kingdom
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George Davey Smith
1MRC Integrative Epidemiology Unit at the University of Bristol, BS8 2BN, United Kingdom
2Population Health Sciences, Bristol Medical School, University of Bristol, Barley House, Oakfield Grove, Bristol, BS8 2BN, United Kingdom
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Abstract

The predictive power of polygenic scores for some traits now rivals that of more classical phenotypic measures, and as such they have been promoted as a potential tool for genetically informed policy. However, how predictive polygenic scores are conditional on other easily available phenotypic data is not well understood. Using data from a UK cohort study, the Avon Longitudinal Study of Parents and Children, we investigated how well polygenic scores for education predict individuals’ realised attainment over and above phenotypic data available to schools. Across our sample children’s polygenic scores predicted their educational outcomes almost as well as parent’s socioeconomic position or education. There was high overlap between the polygenic score and attainment distributions, leading to weak predictive accuracy at the individual level. Furthermore, conditional on prior attainment the polygenic score was not predictive of later attainment. Our results suggest that polygenic scores are informative for identifying group level differences, but they currently have limited use in predicting individual attainment.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted May 23, 2019.
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Can education be personalised using pupils’ genetic data?
Tim T Morris, Neil M Davies, George Davey Smith
bioRxiv 645218; doi: https://doi.org/10.1101/645218
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Can education be personalised using pupils’ genetic data?
Tim T Morris, Neil M Davies, George Davey Smith
bioRxiv 645218; doi: https://doi.org/10.1101/645218

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