Haplotype effects on human survival: logistic regression models applied to unphased genotype data.

Haplotype effects on human survival: logistic regression models applied to unphased genotype data.
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单倍型对人类生存的影响:应用于非定相基因型数据的逻辑回归模型。

DOI:
10.1046/j.1529-8817.2004.00143.x
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发表时间:
2005
期刊:
Annals of human genetics.
影响因子:
--
通讯作者:
Kruse,TA
Kruse,TA
中科院分区:
--
文献类型:
--
作者:
Tan,Q;Christiansen,L;Bathum,L;Zhao,JH;Vach,W;Vaupel,JW;Christensen,K;Kruse,TA

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基于单体型的连锁不平衡(LD)作图比单基因座作图具有更高的功效,因为它利用了侧翼标记中包含的LD信息。已经提出了新的统计方法,以帮助推断单体型对人类疾病的影响,使用从无关个体收集的多位点基因型数据。在本文中,我们介绍了一个统计程序测量单体型对人类生存的影响,使用流行的逻辑回归模型与单体型为基础的参数化。通过将单倍型频率建模为年龄的函数,我们的模型通过估计和测试不同遗传机制(乘法,显性或隐性)下的斜率参数来推断单倍型效应。此外,通过估计性别特异性斜率参数,我们的模型允许检测性别特异性单倍型效应或单倍型-性别相互作用。作为一个例子,我们将我们的模型应用于压力相关基因白细胞介素-6的经验数据集,以寻找影响个体生存的单倍型和单倍型-性别相互作用。我们表明,我们的逻辑回归为基础的单倍型模型可以是一个有用的工具,研究人员感兴趣的遗传学的人类衰老和长寿。
Haplotype based linkage disequilibrium (LD) mapping exhibits higher power than the single locus approach because it makes use of the LD information contained in the flanking markers. New statistical methods have been proposed to help to infer haplotype effects on human diseases using multi‐locus genotype data collected from unrelated individuals. In this paper, we introduce a statistical procedure for measuring haplotype effects on human survival using the popular logistic regression model with haplotype based parameterizations. By modeling haplotype frequency as a function of age, our model infers haplotype effects by estimating and testing the slope parameters under different genetic mechanisms (multiplicative, dominant, or recessive). In addition, by estimating the sex‐specific slope parameters, our model allows the detection of sex‐specific haplotype effects or haplotype‐sex interactions. As an example, we apply our model to an empirical dataset on a stress related gene,interleukin‐6, to look for haplotypes that affect individual survival and for haplotype‐sex interactions. We show that our logistic regression based haplotype model can be a helpful tool for researchers interested in the genetics of human aging and longevity.
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发表时间: 2004-04-01
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影响因子: 30.8
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