Gene-environment interplay in early life cognitive development

Project overview

There is a broad consensus that differences in childhood cognitive development result from both genetic and environmental factors and the complex interplay between them. This project will use a novel, yet robust approach to investigate these relationships.

Children’s differences in early-life cognitive development have long-term impacts on their academic achievement, which in turn affects life outcomes. Interventions for children at risk for poor cognitive outcomes are more likely to be successful if we understand why children’s genetic characteristics produce different observable characteristics in different environments.

Although these differences are well established, no replicable gene-environment interactions (GxE) have been identified to date. Previous studies have been limited in sample size, estimated genetic influences indirectly or narrowly, or considered too few environmental variables.

For this project the researchers will use data from Twins Early Development Study (TEDS), a survey that includes 84.4% of all twins born between 1994 and 1996 in England and Wales, and is broadly representative of all families with children born in the 1990s. The data collected in this survey includes information on cognitive and socio-emotional development as well as some environmental variables.

The main analysis for this project will focus on modelling interactions between genome-wide polygenic scores (GPS) and a range of environmental variables, drawn from the TEDS self-report questions and postcode geo-coding. In order to control for statistical biases, the researchers will also compare the 3,320 pairs of non-identical twins for whom genotype data is available in TEDS to see if the association between their GPS and differences in cognitive development is moderated by environmental measures.

Owing to the limited evidence base related to GxE, robust projections for effect and sample sizes are scarce. While preliminary estimates suggest that the sample size (10,336) should be sufficient, the researchers also plan to run extensive power simulation studies to validate their statistical approach.

The findings of this research will help influence best practice and policy in early years education and childcare. The data and results will also be shared on the Open Science Framework, an online open source platform aimed at facilitating collaboration in science research.