Estimating assortative mating, its history, and its future effect on genetic variance for health, behavioral, and ancestry phenotypes using crosssectionaldata

使用横截面数据估计选型交配、其历史及其对健康、行为和祖先表型遗传变异的未来影响

• 批准号: 9977581
• 负责人: Patrick Ansel Turley
• 金额: $ 25.97万
• 依托单位: BROAD INSTITUTE, INC.
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-05-01 至 2021-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9977581
• 关键词: Affect; Alleles; Behavioral; Biological; Biology; Birth; Characteristics; Child; Chromosomes; Correlation Studies; Data; Data Set; Disease; Elderly; Environment; Future; Generations; Genes; Genetic; Genetic Risk; Genome; Health; Heart; Heritability; Incidence; Individual; Inherited; Intuition; Lead; Light; Link; Measures; Methods; Modernization; Outcome; Paper; Parents; Partner in relationship; Past Trends; Pathway interactions; Phenotype; Plant Roots; Play; Population; Prevalence; Property; Public Health; Publishing; Recording of previous events; Research; Research Personnel; Retirement; Role; Severity of illness; Shock; Sorting - Cell Movement; Source; Spouses; Stratification; Study Section; Testing; Time; Variant; Work; behavioral health; behavioral phenotyping; biobank; cohort; comorbidity; disease phenotype; disorder risk; exhaustion; flexibility; health data; improved; next generation; simulation; theories; time use; tool; trait; trend

PROJECT SUMMARY/ABSTRACT Assortative mating (AM) is when parents are more similar genetically than if pairing were random. AM can lead to a greater prevalence and severity of disease in the population and can mislead researchers studying the relationships between phenotypes. A key objective of this project is to precisely estimate how parents have sorted over time to describe past and future trends in public health—and to show how to use those estimates to take AM into account when trying to narrow down the search for the biological roots of diseases. The key idea behind this project is that AM leads to the next generation having a larger variance of genetic risk—measured by polygenic scores (PGSs)—than it otherwise would. Greater variance leads to a larger range for the PGS and a greater incidence of extreme values. A key concern about AM is that for a disease PGS, a greater incidence of extreme values associated with a larger variance will lead to a greater overall incidence and a greater incidence of more severe forms of the disease. But that increase in variance also provides a valuable tool to study AM. For example, if the variance of a PGS is changing in the population, we can use this information to estimate how AM must also be changing. Genetic data on parent pairs is currently scarce—measuring in the tens of thousands—while cross-sectional data on unrelated individuals is measured in millions. This project is to develop and deploy approaches using cross-sectional data in unrelated individuals to study the dynamics and average level of assortative mating for different individual diseases and traits and across pairs of different diseases and traits. We will validate the results using data on spouse pairs. This project has three specific aims: 1. Develop a general theoretical framework to understand how AM affects the variance and correlation of PGSs across individuals. Importantly, AM can affect the distribution of genetic risk for many generations. 2. Use the theoretical framework to develop methods to estimate AM and its changes using data on unrelated individuals. This will include studying AM for individual phenotypes and AM between pairs of phenotypes. 3. Estimate the history of AM and cross-phenotype AM and study illustrative implications for health and health research, including (a) forecasting the effect of changes in AM on future disease incidence and future disease comorbidities, (b) parceling out the part of past trends in disease incidence and comorbidities that can be accounted for by changes in AM, (c) sorting out what part of the typical level of spousal similarity in disease risk is due to AM and what part is due to other forces, such as a common environment that is generative of that disease, (d) sorting out what portion of the similarity between genes that predict a disease and genes that predict another disease or trait is due to AM and therefore does not suggest a common biological pathway, (e) correcting other crucial genetic measures for AM.

项目概要/摘要 选型交配（AM）是指父母在遗传上比随机配对更相似。 导致人群中疾病的流行率和严重程度增加，并可能误导研究人员 该项目的一个关键目标是精确估计父母的表现型之间的关系。 随着时间的推移进行排序，以描述过去和未来的公共卫生趋势，并展示如何使用这些估计来 当试图缩小疾病的生物学根源的搜索范围时，应考虑 AM。 该项目背后的关键思想是 AM 导致下一代具有更大的遗传方差 风险（通过多基因评分（PGS）衡量）比其他方式更大的方差导致更大的范围。 对于 PGS 和极端值发生率较高，AM 的一个主要问题是对于疾病 PGS， 与较大方差相关的极端值的发生率越高，将导致总体发生率越高，并且 更严重的疾病的发病率更高，但方差的增加也提供了有价值的信息。 例如，如果 PGS 的方差在总体中发生变化，我们可以使用此信息。 估计 AM 也必须如何变化，目前关于父母对的遗传数据很少——在 数以万计，而无关个人的横截面数据则以数百万计。 该项目旨在开发和部署使用无关个体的横截面数据进行研究的方法 不同个体疾病和性状以及跨配对的选型交配的动态和平均水平 我们将使用配偶对的数据来验证结果。 具体目标： 1. 开发一个通用的理论框架来理解 AM 如何影响方差和相关性 重要的是，AM 可以影响多代人的遗传风险分布。 2. 使用理论框架开发使用以下数据来估计 AM 及其变化的方法 这将包括研究个体表型的 AM 和成对个体之间的 AM。 3. 估计 AM 和交叉表型 AM 的历史并研究说明性含义。 用于健康和健康研究，包括 (a) 预测 AM 变化对未来疾病的影响 发病率和未来的疾病合并症，(b) 划分疾病发病率和过去趋势的一部分 AM 变化可解释的合并症，(c) 找出配偶典型水平的哪一部分 疾病风险的相似性是由于 AM 造成的，部分是由于其他因素造成的，例如共同的环境 产生该疾病，(d) 找出预测疾病的基因之间的相似性部分 预测另一种疾病或性状的基因是由 AM 引起的，因此并不表明存在共同的生物学特征 途径，(e) 纠正 AM 的其他重要遗传测量。