Identifying gene-by-environment interplay in health behavior

项目摘要/摘要 吸烟、饮酒和肥胖是可预防的疾病和死亡的三大原因 美国每年仅烟草使用就导致近44万美国人死亡，他们的死亡时间比 非吸烟者。危险的健康行为在低社会经济地位(SES)群体中更为普遍，并且 这是他们之间在健康方面存在巨大差异的重要根源。这种差异是在早期形成的 并且随着个体年龄的增长而变得更加明显。 在这一应用中，我们试图检验保护性的社会经济和政策环境的假设 缓和吸烟、饮酒和肥胖的高危基因变异的影响；评估如何 这种基因与环境(GxE)的相互作用在生命周期中进化，以及它如何对健康做出贡献 差异；产生与决策者和卫生专业人员相关的信息；以及在可能的情况下 调查潜在的机制。利用全基因组关联研究(GWAS)的结果，我们 重点关注特定的遗传变异或综合遗传得分和社会经济的特定层面 和政策环境。 这项拟议的研究是我们项目的自然延续，“从了解健康到减少健康 差距：一种基于模型的评价“(R01AG037398)，我们在其中发展了一种形成和 在这一理论的启发下，社会经济共同体群体之间的健康差距的演变探索了 社会经济地位群体之间的健康和寿命差异是由于工作条件、健康状况、 行为、医疗和劳动力退出。我们还调查了可能的政策的影响 关于健康和健康差距的干预措施。这项研究的两个主要发现是：(I)健康行为 在社会经济地位群体之间的健康差异中起着非常重要的作用，以及(Ii)多种因素(具有 遗传基础)影响SES和健康，并在生产健康中与SES相互作用。这表明一种 基因和环境之间的相互作用在塑造健康行为方面的重要作用。带着非常 最近多基因预测能力的数量级增加，以及最近的基因发现 结果对于几种新的吸烟、饮酒和肥胖表型，现在有可能 在我们的分析中纳入遗传易感性的影响，与社会经济和 政策环境，对这三种危险健康行为。 拟议的项目将整合几种互补的方法：描述性分析以探索 不同水平的遗传风险与社会和政策环境的不同衡量标准之间的关联 生命的不同阶段；结构生命周期模型的估计，以更好地理解GxE的相互作用并使 预测；利用自然实验来解决因果关系；以及反事实分析，使用 结构模型，以评估干预备选方案。

Project summary / abstract Smoking, alcohol consumption, and obesity are the three leading causes of preventable disease and death in the U.S. Each year tobacco use alone kills nearly 440,000 Americans, who die up to 15 years earlier than nonsmokers. Risky health behaviors are more prevalent among low socioeconomic status (SES) groups, and significant sources of the substantial disparities in health between them. Such disparities are formed early in life and become more pronounced as individuals age. In this application we seek to test the hypothesis that protective socioeconomic and policy environments moderate the effects of high-risk genetic variants for smoking, alcohol consumption, and obesity; evaluate how such gene-by-environment (GxE) interplay evolves over the lifecycle and how it contributes to health disparities; generate information relevant to decision makers and health professionals; and when possible investigate the underlying mechanisms. Using results from genome-wide association studies (GWAS), we focus on specific genetic variants or aggregated genetic scores and specific dimensions of the socioeconomic and policy environment. The proposed research is a natural continuation of our project, “From understanding to reducing health disparities: a model-based evaluation” (R01 AG037398), in which we developed a theory of the formation and evolution of health disparities between SES groups, and informed by the theory, explored the extent to which disparities in health and longevity between SES groups are the result of differences in job-conditions, health behavior, medical care, and labor-force withdrawal. We also investigated the effects of possible policy interventions on health and health disparities. Two key findings of that research are that: (i) health behaviors play a very important role in health disparities between SES groups, and (ii) multiple factors (that have a genetic basis) influence both SES and health, and interact with SES in producing health. This suggests an important role for interactions between genes and the environment in shaping health behavior. With the very recent order of magnitude increases in the power of polygenic prediction, and the very recent genetic discovery results for several new smoking, alcohol consumption, and obesity phenotypes, it is now possible to incorporate into our analyses the effects of genetic predispositions, in interaction with the socioeconomic and policy environment, on these three risky health behaviors. The proposed project will integrate several complementary methods: descriptive analyses to explore associations for different levels of genetic risk and different measures of the social and policy environment at different stages of life; estimation of structural lifecycle models to better understand GxE interplay and make predictions; exploitation of natural experiments to address causality; and counterfactual analyses, using the structural models, to evaluate intervention alternatives.