Incorporating a developmental perspective into gene identification models for alcohol outcomes

将发育视角纳入酒精结果的基因识别模型中

基本信息

批准号：
10491732
负责人：
Nathaniel Stembridge Thomas
金额：
$ 3.3万
依托单位：
VIRGINIA COMMONWEALTH UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-09-13 至 2023-06-25
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10491732
关键词：
Adolescence Adolescent Adult Alcohol consumption Alcohols Applications Grants Behavioral Genetics Cessation of life Child Cohort Studies Collaborations Communities Complex Data Development Fostering Future Genes Genetic Genetic Models Genetic Variation Genomics Goals Gold Grant Health Lead Longevity Longitudinal Studies Longitudinal cohort study Manuscripts Measures Mentors Meta-Analysis Methodology Methods Modeling Molecular Genetics National Institute on Alcohol Abuse and Alcoholism National Longitudinal Survey of Adolescent to Adult Health Outcome Parents Phenotype Publications Research Research Personnel Risk Sampling Science Single Nucleotide Polymorphism Strategic Planning Testing Time Training Twin Multiple Birth Unit of Measure United States National Institutes of Health Work alcohol measurement alcohol use disorder behavior test burden of illness cost emerging adulthood experience gene discovery genetics of alcoholism genome wide association study improved indexing longitudinal analysis longitudinal dataset novel phenotypic data polygenic risk score precision medicine predictive modeling skills statistics

项目摘要

Project Summary Frequent alcohol use can lead to alcohol use disorder, which accounts for three million deaths and over 133 million life years lost to disability and death worldwide per year. Alcohol use outcomes are under genetic influence. Genome-wide association represents the state-of-the-science statistical methodology for identifying genes associated with alcohol use outcomes. However, contemporary GWAS methods typically do not account for variability in genetic effects throughout development. For example, when analyzing longitudinal data, most contemporary GWAS are developmentally agnostic and average across timepoints to construct a phenotype that disregards developmental variability in genetic effects. GWAS summary statistics are used as the starting point for phenotype prediction via polygenic risk scores (PRS), which aggregate measured genetic effects on a phenotype into a score that indexes the statistical association between SNPs and the phenotype. Models of genetic influences on alcohol use might be improved if they consider the phenotype as dynamic over time, rather than a fixed maximum or average. No previous studies have constructed PRS from developmentally- informative GWAS, that measure genetic effects that are specific to developmental stage and change over time. In this project, I will apply novel multivariate genomic methods to incorporate developmentally-informative phenotype data into GWAS, create PRS that reflect change over time in alcohol use and PRS that are specific to developmental stage, and validate findings in an independent sample. Longitudinal cohort studies targeted for gene-identification analyses include the Avon Longitudinal Study of Parents and Children (ALSPAC, n~10,000), the Collaborative Study on the Genetics of Alcoholism (COGA, n~2,000), and The National Longitudinal Study of Adolescent to Adult Health (Add Health, n~6,000). Genetic prediction analyses will be conducted in the Finnish Twin Cohort Study (Finn Twin, n~1,400). This project is consistent with NIAAA’s goal to take a lifespan approach to alcohol use and disorder, and provides an analytical approach for doing this for alcohol gene identification efforts. These novel methods will advance the field of behavior genetics beyond the study of aggregated longitudinal phenotypes and represents an important step towards the broader NIH goal of advancing precision medicine strategies for alcohol use outcomes.

项目概要频繁饮酒会导致酒精使用障碍，导致 300 万人死亡和超过 133 人死亡全世界每年因饮酒导致残疾和死亡损失的生命年数由遗传决定。全基因组关联代表了用于识别的最科学的统计方法。然而，当代的 GWAS 方法通常不考虑与饮酒结果相关的基因。例如，在纵向分析数据时，大多数情况下都会出现遗传效应的变异性。当代 GWAS 在发育上是不可知的，并且在构建表型的时间点上进行平均忽略遗传效应的发育变异性。通过多基因风险评分 (PRS) 进行表型预测的点，该评分汇总了测量到的遗传效应表型转化为索引 SNP 和表型模型之间统计关联的分数。如果他们认为表型随着时间的推移是动态的，那么遗传对饮酒的影响可能会得到改善，而不是固定的最大值或平均值。以前没有研究从发育角度构建 PRS。 GWAS，测量对发育阶段和转变提供信息的遗传效应在这个项目中，我将应用新颖的多变量基因组方法来整合发育信息。将表型数据导入 GWAS，创建反映饮酒随时间变化的 PRS 和特定的 PRS 到发育阶段，并验证目标独立样本的研究结果。基因识别分析包括雅芳父母和儿童纵向研究（ALSPAC， n~10,000)、酒精中毒遗传学合作研究 (COGA, n~2,000) 和国家青少年到成人健康的纵向研究（Add Health，n~6,000）将进行遗传预测分析。芬兰双胞胎队列研究（Finn Twin，n~1,400）中进行的该项目与 NIAAA 的目标一致。对酒精使用和酒精障碍采取生命周期方法，并提供一种分析方法这些新方法将推动行为遗传学领域超越酒精基因鉴定。对聚合纵向表型的研究，代表着朝着更广泛的 NIH 目标迈出的重要一步推进针对酒精使用结果的精准医学策略。