Can education be personalised using pupils' genetic data?
Can education be personalised using pupils' genetic data?
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可以利用学生的基因数据实现个性化教育吗？
DOI：
10.1101/645218
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Morris T
中科院分区：
文献类型：
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作者：
Morris T
多基因分数对教育的预测能力越来越强，导致一些人将其作为遗传信息政策的潜在工具进行推广。然而，多基因分数如何准确地预测一个学生在其他表型数据的条件下的教育表现还没有得到很好的理解。使用来自英国队列研究的数据与国家教育记录的数据链接，我们调查了多基因教育分数预测学生考试成绩的准确性。我们还评估了多基因分数的表现，以及学校可用的表型数据。在我们的样本中，多基因得分和成就分布之间存在高度重叠，导致个体水平的预测准确性较差。多基因得分对教育结果的预测不如父母的社会经济因素。有条件的先前的成就，多基因得分未能准确预测后来的成就。我们的研究结果表明，虽然多基因分数可以为识别组水平差异提供信息，但它们目前在准确预测个人教育表现或个性化教育方面的用途有限。
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 accurately polygenic scores predict an individual pupil's educational performance conditional on other phenotypic data is however not well understood. Using data from a UK cohort study with data linkage to national schooling records, we investigated how accurately polygenic scores for education predicted pupils’ test score achievement. We also assessed the performance of polygenic scores over and above phenotypic data that are available to schools. Across our sample, there was high overlap between the polygenic score and achievement distributions, leading to poor predictive accuracy at the individual level. Prediction of educational outcomes from polygenic scores were inferior to those from parental socioeconomic factors. Conditional on prior achievement, polygenic scores failed to accurately predict later achievement. Our results suggest that while polygenic scores can be informative for identifying group level differences, they currently have limited use for accurately predicting individual educational performance or for personalised education.