人类疾病中蛋白质编码变异的遗传关联
Benjamin B Sun1,2, Mitja I Kurki3,4,5,6, Christopher N Foley7,8
1Translational Biology, Research and Development, Biogen Inc., Cambridge, MA, USA. bbsun92@outlook.com.
Nature
|February 24, 2022
概括
这项研究结合了超过65万个人的全外体测序和基因定型,以确定744种疾病的遗传关联. 这项研究显著提高了对疾病风险和机制的罕见和常见遗传变异的理解.
科学领域:
- 基因组学
- 人类遗传学
- 疾病关联研究
背景情况:
- 全基因组关联研究 (GWAS) 已经确定了与人类疾病风险相关的众多遗传变异.
- 然而,传统的GWAS对于罕见的变体是不足的,并且缺乏因果机制的解决方案.
- 弥合常见和罕见变异研究之间的差距对于全面的遗传洞察至关重要.
研究的目的:
- 在蛋白质编码等位基频谱中进行大规模的关联元分析.
- 确定各种疾病终点的新遗传关联.
- 将关联映射到因果基因,阐明疾病机制,并将变异与生物标志物和药物点联系起来.
主要方法:
- 结合整体外基因组测序 (392,814名英国生物库参与者) 与归算的基因型 (260,405名芬兰基因参与者).
- 对744个疾病终点进行了关联元分析.
- 对117种生物标志物和临床阶段药物标进行系统相关的基因关联.
主要成果:
- 确定了975个疾病终点的遗传关联,其中超过三分之一是新鲜的.
- 以往与单基因疾病相关的突变在人群层面的相关性.
- 将GWAS与可能的致病基因相关联,并解释疾病机制.
结论:
- 结合测序和基因型方法增加了检测和解释疾病关联的能力.
- 通过复制验证发现,并提出罕见遗传变异的医学可行性.
- 这项研究为疾病生物学和药物发现提供了宝贵的蛋白质编码变异关联.
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