Sign in
GeneticseLife
Peer-reviewed journal article

Can education be personalised using pupils' genetic data?

Tim MorrisiD, Neil M DaviesiD, George Davey SmithiD

Abstract

The increasing predictive power of polygenic scores for education has led to their promotion by some as a potential tool for genetically informed policy. How well polygenic scores predict educational performance conditional on other phenotypic data is however not well understood. Using data from a UK cohort study, we investigated how well polygenic scores for education predicted pupils realised achievement over and above phenotypic data that are available to schools. Across our sample, prediction of educational outcomes from polygenic scores were inferior to those from parental socioeconomic factors. There was high overlap between the polygenic score and achievement distributions, leading to weak predictive accuracy at the individual level. Furthermore, conditional on prior achievement polygenic scores were not predictive of later achievement. Our results suggest that while polygenic scores can be informative for identifying group level differences, they currently have limited use for predicting individual educational performance or for personalised education.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISStumm '19Cheesman '20Demange '22Domingue '20Allegrini '20Lin '26
77% semantic matchGenomics
Sophie von Stumm, Emily Smith‐Woolley, Ziada Ayorech+4 more·Developmental Science·Nov 23, 2019· 139 citations