@article {259, title = {Differences in exam performance between pupils attending selective and non-selective schools mirror the genetic differences between them}, volume = {3}, year = {2018}, month = {2018/03/23}, pages = {3}, abstract = {

On average, students attending selective schools outperform their non-selective counterparts in national exams. These differences are often attributed to value added by the school, as well as factors schools use to select pupils, including ability, achievement and, in cases where schools charge tuition fees or are located in affluent areas, socioeconomic status. However, the possible role of DNA differences between students of different schools types has not yet been considered. We used a UK-representative sample of 4814 genotyped students to investigate exam performance at age 16 and genetic differences between students in three school types: state-funded, non-selective schools (\‘non-selective\’), state-funded, selective schools (\‘grammar\’) and private schools, which are selective (\‘private\’). We created a genome-wide polygenic score (GPS) derived from a genome-wide association study of years of education (EduYears). We found substantial mean genetic differences between students of different school types: students in non-selective schools had lower EduYears GPS compared to those in grammar (d\ =\ 0.41) and private schools (d\ =\ 0.37). Three times as many students in the top EduYears GPS decile went to a selective school compared to the bottom decile. These results were mirrored in the exam differences between school types. However, once we controlled for factors involved in pupil selection, there were no significant genetic differences between school types, and the variance in exam scores at age 16 explained by school type dropped from 7\% to \<1\%. These results show that genetic and exam differences between school types are primarily due to the heritable characteristics involved in pupil admission.

}, isbn = {2056-7936}, url = {https://doi.org/10.1038/s41539-018-0019-8}, author = {Emily Smith-Woolley and Pingault, Jean-Baptiste and Saskia Selzam and Kaili Rimfeld and Eva Krapohl and Sophie von Stumm and Asbury, Kathryn and Philip S. Dale and Young, Toby and Allen, Rebecca and Yulia Kovas and Robert Plomin} } @article {279, title = {The genetics of university success}, volume = {8}, year = {2018}, month = {2018/10/18}, pages = {14579}, abstract = {

University success, which includes enrolment in and achievement at university, as well as quality of the university, have all been linked to later earnings, health and wellbeing. However, little is known about the causes and correlates of differences in university-level outcomes. Capitalizing on both quantitative and molecular genetic data, we perform the first genetically sensitive investigation of university success with a UK-representative sample of 3,000 genotyped individuals and 3,000 twin pairs. Twin analyses indicate substantial additive genetic influence on university entrance exam achievement (57\%), university enrolment (51\%), university quality (57\%) and university achievement (46\%). We find that environmental effects tend to be non-shared, although the shared environment is substantial for university enrolment. Furthermore, using multivariate twin analysis, we show moderate to high genetic correlations between university success variables (0.27\–0.76). Analyses using DNA alone also support genetic influence on university success. Indeed, a genome-wide polygenic score, derived from a 2016 genome-wide association study of years of education, predicts up to 5\% of the variance in each university success variable. These findings suggest young adults select and modify their educational experiences in part based on their genetic propensities and highlight the potential for DNA-based predictions of real-world outcomes, which will continue to increase in predictive power.

}, isbn = {2045-2322}, url = {https://doi.org/10.1038/s41598-018-32621-w}, author = {Emily Smith-Woolley and Ayorech, Ziada and Philip S. Dale and Sophie von Stumm and Robert Plomin} } @article {278, title = {The stability of educational achievement across school years is largely explained by genetic factors}, volume = {3}, year = {2018}, month = {2018/09/04}, pages = {16}, abstract = {

Little is known about the etiology of developmental change and continuity in educational achievement. Here, we study achievement from primary school to the end of compulsory education for 6000 twin pairs in the UK-representative Twins Early Development Study sample. Results showed that educational achievement is highly heritable across school years and across subjects studied at school (twin heritability ~60\%; SNP heritability ~30\%); achievement is highly stable (phenotypic correlations ~0.70 from ages 7 to 16). Twin analyses, applying simplex and common pathway models, showed that genetic factors accounted for most of this stability (70\%), even after controlling for intelligence (60\%). Shared environmental factors also contributed to the stability, while change was mostly accounted for by individual-specific environmental factors. Polygenic scores, derived from a genome-wide association analysis of adult years of education, also showed stable effects on school achievement. We conclude that the remarkable stability of achievement is largely driven genetically even after accounting for intelligence.

}, isbn = {2056-7936}, url = {https://doi.org/10.1038/s41539-018-0030-0}, author = {Kaili Rimfeld and Malanchini, Margherita and Eva Krapohl and Hannigan, Laurie J. and Philip S. Dale and Robert Plomin} } @article {200, title = {Genome-Wide Polygenic Scores Predict Reading Performance Throughout the School Years}, journal = {Scientific Studies of Reading}, volume = {21}, year = {2017}, month = {2017/07/04}, pages = {334 - 349}, abstract = {

It is now possible to create individual-specific genetic scores, called genome-wide polygenic scores (GPS). We used a GPS for years of education (EduYears) to predict reading performance assessed at UK National Curriculum Key Stages 1 (age 7), 2 (age 12) and 3 (age 14) and on reading tests administered at ages 7 and 12 in a UK sample of 5,825 unrelated individuals. EduYears GPS accounts for up to 5\% of the variance in reading performance at age 14. GPS predictions remained significant after accounting for general cognitive ability and family socioeconomic status. Reading performance of children in the lowest and highest 12.5\% of the EduYears GPS distribution differed by a mean growth in reading ability of approximately two school years. It seems certain that polygenic scores will be used to predict strengths and weaknesses in education.

}, isbn = {1088-84381532-799X}, url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5490720/}, author = {Saskia Selzam and Philip S. Dale and Wagner, Richard K and John C DeFries and Cederl{\"o}f, Martin and Paul F O{\textquoteright}Reilly and Eva Krapohl and Robert Plomin} } @article {199, title = {Predicting educational achievement from DNA}, journal = {Mol Psychiatry}, volume = {22}, year = {2017}, month = {2017/02//print}, pages = {267 - 272}, abstract = {

A genome-wide polygenic score (GPS), derived from a 2013 genome-wide association study (N=127,000), explained 2\% of the variance in total years of education (EduYears). In a follow-up study (N=329,000), a new EduYears GPS explains up to 4\%. Here, we tested the association between this latest EduYears GPS and educational achievement scores at ages 7, 12 and 16 in an independent sample of 5825 UK individuals. We found that EduYears GPS explained greater amounts of variance in educational achievement over time, up to 9\% at age 16, accounting for 15\% of the heritable variance. This is the strongest GPS prediction to date for quantitative behavioral traits. Individuals in the highest and lowest GPS septiles differed by a whole school grade at age 16. Furthermore, EduYears GPS was associated with general cognitive ability (~3.5\%) and family socioeconomic status (~7\%). There was no evidence of an interaction between EduYears GPS and family socioeconomic status on educational achievement or on general cognitive ability. These results are a harbinger of future widespread use of GPS to predict genetic risk and resilience in the social and behavioral sciences.

}, isbn = {1359-4184}, url = {http://dx.doi.org/10.1038/mp.2016.107}, author = {Saskia Selzam and Eva Krapohl and Sophie von Stumm and Paul F O{\textquoteright}Reilly and Kaili Rimfeld and Yulia Kovas and Philip S. Dale and Lee,J J and Robert Plomin} }