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A population-wide gene-environment interaction study on how genes, schools, and residential areas shape achievement
A child’s environment is thought to be composed of different levels that interact with their individual genetic propensities. However, studies have not tested this theory comprehensively across multiple environmental levels. Here, we quantify the contributions of child, parent, school, neighbourhood...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9613652/ https://www.ncbi.nlm.nih.gov/pubmed/36302785 http://dx.doi.org/10.1038/s41539-022-00145-8 |
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author | Cheesman, Rosa Borgen, Nicolai T. Lyngstad, Torkild H. Eilertsen, Espen M. Ayorech, Ziada Torvik, Fartein A. Andreassen, Ole A. Zachrisson, Henrik D. Ystrom, Eivind |
author_facet | Cheesman, Rosa Borgen, Nicolai T. Lyngstad, Torkild H. Eilertsen, Espen M. Ayorech, Ziada Torvik, Fartein A. Andreassen, Ole A. Zachrisson, Henrik D. Ystrom, Eivind |
author_sort | Cheesman, Rosa |
collection | PubMed |
description | A child’s environment is thought to be composed of different levels that interact with their individual genetic propensities. However, studies have not tested this theory comprehensively across multiple environmental levels. Here, we quantify the contributions of child, parent, school, neighbourhood, district, and municipality factors to achievement, and investigate interactions between polygenic indices for educational attainment (EA-PGI) and environmental levels. We link population-wide administrative data on children’s standardised test results, schools and residential identifiers to the Norwegian Mother, Father, and Child Cohort Study (MoBa), which includes >23,000 genotyped parent-child trios. We test for gene-environment interactions using multilevel models with interactions between EA-PGI and random effects for school and residential environments (thus remaining agnostic to specific features of environments). We use parent EA-PGI to control for gene-environment correlation. We found an interaction between students’ EA-PGI and schools suggesting compensation: higher-performing schools can raise overall achievement without leaving children with lower EA-PGI behind. Differences between schools matter more for students with lower EA-PGI, explaining 4 versus 2% of the variance in achievement for students 2 SD below versus 2 SD above the mean EA-PGI. Neighbourhood, district, and municipality variation contribute little to achievement (<2% of the variance collectively), and do not interact with children’s individual EA-PGI. Policy to reduce social inequality in achievement in Norway should focus on tackling unequal support across schools for children with difficulties. |
format | Online Article Text |
id | pubmed-9613652 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-96136522022-10-29 A population-wide gene-environment interaction study on how genes, schools, and residential areas shape achievement Cheesman, Rosa Borgen, Nicolai T. Lyngstad, Torkild H. Eilertsen, Espen M. Ayorech, Ziada Torvik, Fartein A. Andreassen, Ole A. Zachrisson, Henrik D. Ystrom, Eivind NPJ Sci Learn Article A child’s environment is thought to be composed of different levels that interact with their individual genetic propensities. However, studies have not tested this theory comprehensively across multiple environmental levels. Here, we quantify the contributions of child, parent, school, neighbourhood, district, and municipality factors to achievement, and investigate interactions between polygenic indices for educational attainment (EA-PGI) and environmental levels. We link population-wide administrative data on children’s standardised test results, schools and residential identifiers to the Norwegian Mother, Father, and Child Cohort Study (MoBa), which includes >23,000 genotyped parent-child trios. We test for gene-environment interactions using multilevel models with interactions between EA-PGI and random effects for school and residential environments (thus remaining agnostic to specific features of environments). We use parent EA-PGI to control for gene-environment correlation. We found an interaction between students’ EA-PGI and schools suggesting compensation: higher-performing schools can raise overall achievement without leaving children with lower EA-PGI behind. Differences between schools matter more for students with lower EA-PGI, explaining 4 versus 2% of the variance in achievement for students 2 SD below versus 2 SD above the mean EA-PGI. Neighbourhood, district, and municipality variation contribute little to achievement (<2% of the variance collectively), and do not interact with children’s individual EA-PGI. Policy to reduce social inequality in achievement in Norway should focus on tackling unequal support across schools for children with difficulties. Nature Publishing Group UK 2022-10-27 /pmc/articles/PMC9613652/ /pubmed/36302785 http://dx.doi.org/10.1038/s41539-022-00145-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Cheesman, Rosa Borgen, Nicolai T. Lyngstad, Torkild H. Eilertsen, Espen M. Ayorech, Ziada Torvik, Fartein A. Andreassen, Ole A. Zachrisson, Henrik D. Ystrom, Eivind A population-wide gene-environment interaction study on how genes, schools, and residential areas shape achievement |
title | A population-wide gene-environment interaction study on how genes, schools, and residential areas shape achievement |
title_full | A population-wide gene-environment interaction study on how genes, schools, and residential areas shape achievement |
title_fullStr | A population-wide gene-environment interaction study on how genes, schools, and residential areas shape achievement |
title_full_unstemmed | A population-wide gene-environment interaction study on how genes, schools, and residential areas shape achievement |
title_short | A population-wide gene-environment interaction study on how genes, schools, and residential areas shape achievement |
title_sort | population-wide gene-environment interaction study on how genes, schools, and residential areas shape achievement |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9613652/ https://www.ncbi.nlm.nih.gov/pubmed/36302785 http://dx.doi.org/10.1038/s41539-022-00145-8 |
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