Department of Biostatistics, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, Florida, USA.
Institute of Bioinformatics and Institute of Crop Science, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China.
Genet Epidemiol. 2021 Mar;45(2):171-189. doi: 10.1002/gepi.22363. Epub 2020 Sep 30.
Genes, including those with transgenerational effects, work in concert with behavioral, environmental, and social factors via complex biological networks to determine human health. Understanding complex relationships between causal factors underlying human health is an essential step towards deciphering biological mechanisms. We propose a new analytical framework to investigate the interactions between maternal and offspring genetic variants or their surrogate single nucleotide polymorphisms (SNPs) and environmental factors using family-based hybrid study design. The proposed approach can analyze diverse genetic and environmental factors and accommodate samples from a variety of family units, including case/control-parental triads, and case/control-parental dyads, while minimizing potential bias introduced by population admixture. Comprehensive simulations demonstrated that our innovative approach outperformed the log-linear approach, the best available method for case-control family data. The proposed approach had greater statistical power and was capable to unbiasedly estimate the maternal and child genetic effects and the effects of environmental factors, while controlling the Type I error rate against population stratification. Using our newly developed approach, we analyzed the associations between maternal and fetal SNPs and obstructive and conotruncal heart defects, with adjustment for demographic and lifestyle factors and dietary supplements. Fourteen and 11 fetal SNPs were associated with obstructive and conotruncal heart defects, respectively. Twenty-seven and 17 maternal SNPs were associated with obstructive and conotruncal heart defects, respectively. In addition, maternal body mass index was a significant risk factor for obstructive defects. The proposed approach is a powerful tool for interrogating the etiological mechanism underlying complex traits.
基因,包括具有跨代效应的基因,通过复杂的生物网络与行为、环境和社会因素协同作用,决定人类健康。理解人类健康潜在因果因素之间的复杂关系是破解生物学机制的关键步骤。我们提出了一种新的分析框架,用于使用基于家庭的混合研究设计来研究母体和后代遗传变异或其替代单核苷酸多态性(SNP)与环境因素之间的相互作用。该方法可以分析多种遗传和环境因素,并适用于各种家庭单位的样本,包括病例/对照-父母三胞胎和病例/对照-父母二联体,同时最小化由人群混合引起的潜在偏差。全面的模拟表明,我们的创新方法优于对数线性方法,对数线性方法是病例对照家庭数据的最佳可用方法。该方法具有更高的统计功效,能够无偏估计母体和儿童的遗传效应以及环境因素的效应,同时控制针对人群分层的Ⅰ型错误率。使用我们新开发的方法,我们分析了母体和胎儿 SNP 与阻塞性和圆锥动脉干心脏缺陷之间的关联,调整了人口统计学和生活方式因素以及膳食补充剂。14 个和 11 个胎儿 SNP 分别与阻塞性和圆锥动脉干心脏缺陷相关。27 个和 17 个母体 SNP 分别与阻塞性和圆锥动脉干心脏缺陷相关。此外,母体体重指数是阻塞性缺陷的一个重要危险因素。该方法是研究复杂特征潜在病因机制的有力工具。