Recent advances in genomics make it possible to predict individual differences in education from polygenic scores that are person-specific aggregates of inherited DNA differences. Here, we systematically reviewed and meta-analyzed the strength of these DNA-based predictions for educational attainment (e.g., years spent in full-time education) and educational achievement (e.g., school grades). For educational attainment (k = 20, n = 16, N_total = 314,757), a multilevel meta-analysis showed an association with polygenic scores of ρ = .27 (95% CI from .22 to .32). For educational achievement (k = 19, n = 10, N_total = 83,788), the association was ρ = .24 (95% CI from .18 to .30). Eurocentric biases were evident with only 15% of estimates being reported in samples of non-European ancestry. After accounting for sample ancestry, age at assessment, and education measure, the meta-analytic estimates increased to ρ = .29 (95% CI from .24 to .33) for educational attainment and ρ = .50 (95% CI from .39 to .61) for educational achievement, indicative of large effect sizes. All meta-analytic estimates were associated with significant heterogeneity. Our findings suggest that DNA-based predictions of education are sizeable but vary across samples and studies. We outline three steps to safeguard potential applications of polygenic score predictions in education to maximize their benefits for personalizing learning, while minimizing the bioethical risks of perpetuating social, cultural, and economic inequalities.

基因组学的最新进展使得通过多基因评分预测个体教育差异成为可能，多基因评分是遗传性 DNA 差异的个体特异性聚合。在这里，我们系统地回顾和元分析了这些基于 DNA 的教育程度（例如，全日制教育年限）和教育成就（例如，学校成绩）预测的强度。对于教育程度（ k = 20， n = 16， N_总数= 314,757），多级荟萃分析显示与ρ = 0.27 的多基因评分相关（95% CI 从 0.22 到 0.32）。对于教育成绩（ k = 19， n = 10， N_总数= 83,788），相关性为ρ = 0.24（95% CI 从 0.18 到 0.30）。欧洲中心主义偏见很明显，只有 15% 的估计是在非欧洲血统样本中报告的。在考虑了样本血统、评估年龄和教育程度后，教育程度的荟萃分析估计值增加到ρ = .29（95% CI 从 0.24 到 0.33），而ρ = .50（95% CI 从 0.33）。 39 至 .61) 的教育成就，表明效应量较大。所有荟萃分析估计都与显着的异质性相关。我们的研究结果表明，基于 DNA 的教育预测相当大，但因样本和研究而异。我们概述了三个步骤，以保障多基因分数预测在教育中的潜在应用，以最大限度地发挥其对个性化学习的好处，同时最大限度地减少社会、文化和经济不平等长期存在的生物伦理风险。