Evaluating empirical bounds on complex disease genetic architecture.

Evaluating empirical bounds on complex disease genetic architecture.
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DOI:
10.1038/ng.2804
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发表时间:
2013-12
期刊:
影响因子:
30.8
通讯作者:
Altshuler, David
Altshuler, David
中科院分区:
生物学1区
文献类型:
--
作者:
Agarwala, Vineeta;Flannick, Jason;Sunyaev, Shamil;Altshuler, David

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人类疾病的遗传结构决定着遗传图谱的成功和个性化医疗的未来。尽管许多研究质疑常见疾病的遗传基础,但关于遗传结构特征的相互矛盾的假设一直存在(例如,罕见与常见变异的贡献)。我们开发了一个集成的模拟框架,校准的经验数据,使系统的评估这些假设。对于2型糖尿病(T2 D),两个简单的参数-(a)因果突变的目标大小和(B)选择和表型效应之间的耦合-定义了广阔的架构空间。虽然排除了极端模型,但许多模型仍然与T2 D的流行病学,连锁和全基因组关联研究一致,包括那些罕见变异解释很少(<25%)或大部分(>80%)遗传性的模型。正在进行的测序和基因分型研究将进一步限制结构,但非常大的样本(例如,> 25万个个体)将需要定位大部分遗传性潜在性状,如T2 D。
The genetic architecture of human diseases governs the success of genetic mapping and the future of personalized medicine. Although numerous studies have queried the genetic basis of common disease, contradictory hypotheses have been advocated about features of genetic architecture (e.g., the contribution of rare vs. common variants). We developed an integrated simulation framework, calibrated to empirical data, to enable systematic evaluation of such hypotheses. For type 2 diabetes (T2D), two simple parameters – (a) the target size for causal mutation and (b) the coupling between selection and phenotypic effect – define a broad space of architectures. While extreme models are excluded, many models remain consistent with epidemiology, linkage, and genome-wide association studies for T2D, including those where rare variants explain little (<25%) or most (>80%) of heritability. Ongoing sequencing and genotyping studies will further constrain architecture, but very large samples (e.g., >250K unselected individuals) will be required to localize most of the heritability underlying traits like T2D.
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