Evidence map›Paper›PMID 32151313›Full record

ArticleeLife2020

Can education be personalised using pupils' genetic data?

Tim T Morris, Neil M Davies, George Davey Smith

Open access · goldAbstract read
In one paragraph

Article in eLife, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
6.5field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 52 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Principles and Policy Recommendations for Comprehensive Genetic Data Governance.Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society · 2025
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Tim T MorrisMRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom.ORCID 0000-0001-8178-6815
Neil M DaviesMRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom.ORCID 0000-0002-2460-0508
George Davey SmithMRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom.ORCID 0000-0002-1407-8314
University of Bristol · GB

Funding

Economic and Social Research Council ES/N000757/1Economic and Social Research Council ES/S011021/1Medical Research Council G9815508Medical Research Council MC_PC_15018Medical Research Council MC_PC_19009Medical Research Council MC_UU_00011/1Medical Research Council MC_UU_12013/1Medical Research Council MC_UU_12013/9Norwegian Research Council 295989Wellcome MC_UU_00011/1Wellcome MC_UU_12013/1Wellcome MC_UU_12013/9Wellcome Trust
6 · The paper itself

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 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.

Indexed as

Educational StatusGenetic Association StudiesAchievementAdolescentAdultBiological Variation, PopulationChildFemaleGenome-Wide Association StudyHumansMaleModels, TheoreticalPolymorphism, Single NucleotideROC CurveSocioeconomic FactorsYoung AdultachievementALSPACeducationgeneticsgenomicshumanpolygenic scoreprediction

Identifiers

PMID32151313
PMCPMC7064332
OpenAlexW3002250695

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.