How much are we missing in SNP-by-SNP analyses of genome-wide association studies?
How much are we missing in SNP-by-SNP analyses of genome-wide association studies?
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在全基因组关联研究的逐个 SNP 分析中我们遗漏了多少？
DOI：
10.1097/ede.0b013e31822ffbe7
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发表时间：
2011
期刊：
影响因子：
--
通讯作者：
Weinberg,ClariceR
中科院分区：
文献类型：
--
作者：
Shi,Min;Weinberg,ClariceR
全基因组关联研究发现了与几种复杂疾病易感性相关的常见遗传变异，但对于许多其他疾病却没有成果。通常，分析是“不可知的”进行的，即一次考虑一个单核苷酸多态性 (SNP)，并通过纠正多个测试来控制总体 I 型错误率。这种一次性分析可能不足以在现实因果模型下筛选基因。我们使用口腔裂作为疾病模型来开发一系列玩具示例场景：风险可能仅涉及基因，或基因和暴露，或基因、暴露及其超乘相互作用。这些例子说明，当多个生物途径和多个基因共同影响病因时，一次一个 SNP 分析可能会掩盖多么重要的遗传变异。这些例子强调需要更好的方法来进行逐个环境和逐个基因的分析。
Genome-wide association studies have discovered common genetic variants associated with susceptibility for several complex diseases, but they have been unfruitful for many others. Typically, analysis is done “agnostically,” by considering one single nucleotide polymorphism (SNP) at a time and controlling the overall type I error rate by correcting for multiple testing. Such one-at-a-time analyses may be inadequate for screening genes under realistic causal models. We use oral clefting as a disease model to develop a range of toy example scenarios: risk might involve only genes, or genes and exposure, or genes, exposure, and their supermultiplicative interaction. These examples illustrate how dramatically important genetic variants can be obscured by a one-SNP-at-a-time analysis when multiple biologic pathways and multiple genes jointly influence etiology. These examples highlight the need for better methods for gene-by-environment and gene-by-gene analyses.