Informing Educational Interventions using Genome-Wide Data, 2016-2019

Data sources include UK Biobank https://www.ukbiobank.ac.uk/enable-your-research, ALSPAC http://www.bristol.ac.uk/alspac/researchers/access, and the NCDS https://cls.ucl.ac.uk/data-access-training/. This collection provides the links to the code for the analysis used in this project available under Related Resources.<p>During this fellowship, I will use the wealth of genetic data from longitudinal cohort studies in the 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 various 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 worldwide, 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 that 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 associated 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 educational attainment. However, 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. In addition, I will seek to replicate my findings and investigate these relationships in more detail using the rich and highly detailed information 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 that 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 that 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).</p>本研究的数据来源包括英国生物样本库（UK Biobank，https://www.ukbiobank.ac.uk/enable-your-research）、雅芳父母与儿童纵向研究（Avon Longitudinal Study of Parents and Children，ALSPAC，http://www.bristol.ac.uk/alspac/researchers/access）以及国家儿童发展研究（NCDS，https://cls.ucl.ac.uk/data-access-training/）。本数据集收录了本项目所用分析代码的相关链接，相关资源可通过关联资源栏目获取。 在本研究员资助项目期内，我将依托英国及海外多项纵向队列研究中丰富的遗传数据，针对现代经济学、心理学与社会学领域的三大核心议题开展创新性研究，分别为学业成就、非认知技能，以及婚恋中的选型婚配。上述议题是各社会科学领域中被广泛探讨的核心主题之一（1-4）。诸多研究者指出，基因组在上述各类议题中均发挥着重要作用，但目前针对该问题的直接实证证据仍相对匮乏。当前该领域的多数研究存在一项显著局限：难以有效控制个体间的固有差异。为此，我将结合英国及全球其他地区八项纵向队列研究中不断丰富的生物社会与全基因组数据（genome-wide data），以及用于因果推断（causal inference）的前沿计量经济学与统计学方法，突破这一研究瓶颈。这些全新的数据与研究方法，将为解决此前难以甚至无法开展的相关研究问题提供新的实证依据与发现契机（5,6）。 本研究的核心目标为探究以下三大研究问题： 1. 与学业成就相关的三种遗传变异的作用介导机制是什么？其对劳动力市场结局的长期影响如何？ 截至目前，学界已确认三种与学业成就相关的单个遗传变异，但尚未明确介导此类效应的生物社会机制。在本资助期内，我将借助英国生物样本库（UK Biobank）的数据开展相关研究。该队列研究涵盖了50万名个体的全基因组数据，凭借其庞大的样本量，英国生物样本库可为探究此类关联的病因学机制及其长期后果提供前所未有的统计效力。此外，我还将依托英国老龄化纵向研究（English Longitudinal Study of Aging，样本量N=8000）与「理解社会」纵向研究（Understanding Society，样本量N=10000）中丰富且精细的信息，对研究发现进行重复验证，并更深入地剖析上述关联。 2. 整个人生历程中，认知与非认知技能及教育成果的遗传结构是怎样的？ 非认知技能是指一系列影响学业与职场成功的心理特质，例如动机、毅力、情绪智力、韧性与自控力等（7）。针对非认知技能重要性的研究已催生了旨在提升儿童非认知技能的政策干预措施（2,8-10）。然而，尽管学界已证实此类技能与各类结局存在关联，但仍无法明确其是否会直接促成学业或职场成功。我将借助雅芳父母与儿童纵向研究（Avon Longitudinal Study of Parents and Children，ALSPAC）子代队列（样本量N=8365）的全基因组数据，为该问题提供新的实证证据，并将在国家儿童发展研究（National Child Development Study，NCDS，样本量N=5595）与双胞胎早期发展研究（The Twins Early Development Study，样本量N=3500）中对研究结果进行重复验证。 3. 选型婚配如何影响人类基因组？利用全基因组数据集解读社会科学研究结果时，选型婚配会带来哪些影响？ 尽管有「异性相吸」的说法，但现实中配偶双方往往比从人群中随机选取的两名个体更为相似。在本项目中，我将探究此种现象的成因：究竟是配偶双方源自相似的社会背景，还是他们携带相似遗传变异的概率也显著高于随机预期水平。该研究结论将对利用全基因组数据开展的社会科学研究的结果解读产生重要影响。本研究将使用英国生物样本库（UK Biobank）、ALSPAC父母队列（母亲样本N=10107，父亲样本N=2000）、健康与退休研究（Health and Retirement Study，样本量N=15620）以及苏格兰世代研究（Generation Scotland study，样本量N=10399）的数据。