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在对比特征进行全基因组关联研究的陷

Zachary R McCaw¹, Rounak Dey¹, Hari Somineni¹

¹Insitro, South San Francisco, CA, USA.

|January 17, 2025

概括

对特征比率的全基因组关联研究 (GWAS) 可以产生误导性的结果,因为关联可能仅由分母特征驱动. 研究人员应该考虑替代模型,以避免虚假的发现,并确保准确的遗传解释.

科学领域:

遗传学遗传学是一个
统计遗传学统计遗传学
生物信息学是一种生物信息学.

背景情况:

全基因组关联研究 (GWAS) 经常分析特征比率 (例如,体重指数),以隐式调整计数器-分母关联.
然而,分析比率并没有在统计学上对分母产生条件,这导致解释遗传关联的模两可.

研究的目的:

为了研究在特征比率上执行GWAS的有效性.
要确定在比率GWAS中发现的关联是否归因于分数,分母或两者.
将比率GWAS与调整后的模型进行比较,该模型以分母为条件.

主要方法:

使用GWAS分析了10个常见的比率特征.
从比率GWAS和调整的GWAS模型 (计数器GWAS取决于分母) 的结果进行比较.
检查身体质量指数 (BMI) 和腰比 (WHR) 作为案例研究.
应用一种新的方法来纠正基因碰撞器偏差,使用留下一个染色体的多基因评分.

主要成果:

在比率GWAS中的关联可以完全由分母特征驱动.
比率模型和调整后的模型显示,在10个常见比率特征中的大约三分之一的位置上存在分歧.
对比率模型独特的变体与分母 (例如,BMI的身高) 更强烈地相关,而对调整模型独特的变体与分数 (例如,BMI的体重) 更强烈地相关.
调整后的模型虽然提供了更清晰的解释,但容易受到碰撞机偏差的影响.

结论:

在特征比率上执行GWAS可以导致由分母驱动的虚假关联.
一个调整的模型 (GWAS在分数上,调节在分母上) 提供了更清晰的解释,但需要对碰撞机偏差进行校正.
建议使用多基因评分的验证方法来纠正对撞机偏差在调整模型中的遗传成分.

关键词:

身体质量指数 (BMI) 是指身体质量指数.碰撞机偏差是因为碰撞机偏差.同变量调整的调整.遗传发现的发现.全基因组关联研究研究.遗传性共变量偏差是一种遗传性共变量偏差.多基因分数的多基因分数一个比例,一个比例,一个比例.分数分数分数分数.这是一个比率比率的比率.

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