估计直接和间接的多基因效应和基因-环境相互作用使用多基因分数在案例-家长三组研究中的估计
Ziqiao Wang1, Luke Grosvenor2,3, Debashree Ray1,4
1Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States of America 21205.
medRxiv : the preprint server for health sciences
|October 17, 2024
概括
我们开发了PGS-TRI,这是一种在家庭研究中分析多基因分数 (PGS) 的新方法. 这个框架准确地估计了遗传遗传分数,父母影响和基因与环境相互作用的疾病风险.
科学领域:
- 遗传学 遗传学 是一个
- 生物统计学 生物统计学
- 人类遗传学 人类遗传学
背景情况:
- 家庭研究对于了解遗传疾病风险至关重要.
- 人口结构和分类交配等复杂因素影响遗传风险评估.
- 现有的方法可能无法充分考虑间接的遗传影响和基因环境相互作用.
研究的目的:
- 引入PGS-TRI,这是一个用于分析案例-家长三组研究中的多基因分数 (PGS) 的新框架.
- 为了估计疾病风险,考虑直接遗传的PGS影响,间接的父母PGS影响和基因环境相互作用.
- 为复杂的特征提供基于传输的风险估计.
主要方法:
- 开发PGS-TRI分析框架.
- 进行广泛的模拟研究,以评估对人口结构和分类交配的强度.
- PGS-TRI应用于自闭症谱系障碍和面腔裂三组数据集的应用.
主要成果:
- 在复杂的种群结构和各种交配场景中,PGS-TRI表现出稳健性.
- 第一个基于传输的风险估计自闭症谱系障碍和口面裂使用预定义的PGS.
- 探索与多基因基因环境相互作用和遗传预测分子特征相关的后代风险.
结论:
- PGS-TRI提供了一种可靠的方法来分析家族研究中的PGS,并考虑复杂的遗传结构.
- 该框架为自闭症谱系障碍和耳鼻裂的遗传病因提供了宝贵的见解.
- 未来的研究可以利用PGS-TRI来研究基因环境相互作用和疾病风险的分子基础.
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