使用弹性网回归的肺功能下降的全基因组关联研究:在韩国队列中进行前性分析
Eunhye Bae1, Sohee Oh2, Jung-Kyu Lee3
1Division of Pulmonary, Allergy and Critical Care Medicine, Department of Internal Medicine, Chung-Ang University Gwangmyeong Hospital, Gwangmyeong-si, Republic of Korea.
Human genomics
|December 2, 2025
概括
研究人员确定了与加速肺功能下降相关的新型单核酸多态 (SNP). 已开发的遗传风险评分 (GRS) 可以预测个体在一个秒内 (FEV1) 快速强迫呼气体积下降的更高风险.
科学领域:
- 肺部医学 肺部医学
- 遗传学 遗传学 是一个
- 流行病学 流行病学
背景情况:
- 一秒内强迫呼气体积的快速下降 (FEV1) 与慢性呼吸道疾病和预后不佳有关.
- 识别影响FEV1下降的遗传因素对于早期干预至关重要.
研究的目的:
- 确定与FEV1下降的年率相关的单核酸多态 (SNP).
- 为了研究不同表型的基因差异效应.
- 开发一种基因风险评分 (GRS) 以预测快速FEV1下降.
主要方法:
- 在韩国基因组和流行病学研究 (KoGES) 队列中进行的全基因组关联研究 (GWAS).
- 用于评估SNP与年度FEV1下降率相关的线性回归模型.
- 弹性网回归用于SNP选择和GRS开发.
主要成果:
- 在7,357名参与者中发现了21个与快速FEV1下降相关的SNP.
- 弹性网确定了12个具有高复制潜力的SNP.
- GRS显著与年度FEV1变化相关 (调整后R2=0.308);一个GRS< -17表示加速下降.
结论:
- 确定了与FEV1下降相关的新型SNP.
- 开发了一个用于快速FEV1下降的预测GRS.
- 影响FEV1下降率的遗传因素可能由表型特征调节.
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