Title: Informing educational interventions using genome-wide data: causal evidence from 573,586 participants of eight cohort studies
Funder: Economic and Social Research Council

Abstract: During this fellowship I will use the wealth genetic data from longitudinal cohort studies in UK and abroad to conduct innovative research into three core issues in modern economics, psychology and sociology: academic attainment, non-cognitive skills, and assortative matching in relationships. These are some of the most heavily researched topics across a range of social sciences (1-4). Many researchers have argued that the genome plays an important role in each of these topics, yet we have relatively little direct evidence about this. A major limitation of much of the existing research in this area is that it has struggled to account for intrinsic differences between individuals. I will overcome this limitation by combining the growing wealth of biosocial and genome-wide data, from eight longitudinal cohort studies from the UK and others around the world, with cutting edge econometric and statistical methods for causal inference. These novel data and methods offer an opportunity for new evidence and discoveries about research questions which were previously difficult or impossible to address (5, 6). My research objectives are to investigate the following three research questions: 1) How are the effects of three genetic variants which associate with educational attainment mediated? What are their long-term effects on labour market outcomes? To date, we know of three individual genetic variants that are associated with education attainment. We do not know which biosocial mechanisms mediate these effects. During this fellowship I will investigate this using data from the UK Biobank. This cohort study has genome-wide data on 500,000 individuals. Due to its size, the UK Biobank will offer unparalleled statistical power to investigate the aetiology of these associations and their long-term consequences. I will seek to replicate my findings, and investigate these relationships in more detail using rich and highly detailed information contained in the English Longitudinal Study of Aging (N=8,000), and Understanding Society (N=10,000). 2) What is the genetic architecture of cognitive and non-cognitive skills, and educational outcomes across the life course? Non-cognitive skills are a set of psychological character traits which are thought to influence success in school and at work, for example motivation, perseverance, emotional intelligence, resilience, and self-control (7). Research about the importance of non-cognitive skills has led to policy interventions which aim to improve children's non-cognitive skills (2, 8-10). However, whilst we know that these skills are associated with outcomes, we do not know if they cause success in school or work. I will add to the evidence about this question using genome-wide data from the Avon Longitudinal Study of Parents and Children (ALSPAC) offspring (N=8,365). I will seek to replicate these results in the National Child Development Study (N=5,595) and The Twins Early Development Study (N=3,500). 3) How does assortative mating affect the human genome? What are the consequences of assortative mating for interpreting the results of social-science studies using genome-wide datasets? Despite the saying 'opposites attract', spouses tend to be more alike than two randomly chosen individuals from the population. In this project I will investigate whether this is because spouses come from similar backgrounds, or if spouses are also more likely to have similar genetic variants than would be expected by chance. This has implications for interpreting the results of studies using genome-wide data. I will use data from UK Biobank, ALSPAC mothers and fathers (N=10,107 and 2000 respectively), the Health and Retirement Study (N=15,620) and the Generation Scotland study (N=10,399).


Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS;2.3 PSYCHOLOGICAL, SOCIAL AND ECONOMIC FACTORS
Health categories: MENTAL HEALTH