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Statistical modeling of interlocus interactions in a complex disease: rejection of the multiplicative model of epistasis in type 1 diabetes.

机译:复杂疾病中位间相互作用的统计模型:拒绝1型糖尿病上位性乘法模型。

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摘要

In general, common diseases do not follow a Mendelian inheritance pattern. To identify disease mechanisms and etiology, their genetic dissection may be assisted by evaluation of linkage in mouse models of human disease. Statistical modeling of multiple-locus linkage data from the nonobese diabetic (NOD) mouse model of type 1 diabetes has previously provided evidence for epistasis between alleles of several Idd (insulin-dependent diabetes) loci. The construction of NOD congenic strains containing selected segments of the diabetes-resistant strain genome allows analysis of the joint effects of alleles of different loci in isolation, without the complication of other segregating Idd loci. In this article, we analyze data from congenic strains carrying two chromosome intervals (a double congenic strain) for two pairs of loci: Idd3 and Idd10 and Idd3 and Idd5. The joint action of both pairs is consistent with models of additivity on either the log odds of the penetrance, or the liability scale, rather than with the previously proposed multiplicative model of epistasis. For Idd3 and Idd5 we would also not reject a model of additivity on the penetrance scale, which might indicate a disease model mediated by more than one pathway leading to beta-cell destruction and development of diabetes. However, there has been confusion between different definitions of interaction or epistasis as used in the biological, statistical, epidemiological, and quantitative and human genetics fields. The degree to which statistical analyses can elucidate underlying biologic mechanisms may be limited and may require prior knowledge of the underlying etiology.
机译:通常,常见疾病不遵循孟德尔遗传模式。为了确定疾病的机制和病因,可以通过评估人类疾病小鼠模型中的连锁反应来辅助其遗传解剖。来自1型糖尿病非肥胖糖尿病(NOD)小鼠模型的多位点连锁数据的统计模型先前为多个Idd(胰岛素依赖型糖尿病)基因座的等位基因之间的上位性提供了证据。包含糖尿病抗性菌株基因组选定片段的NOD同基因菌株的构建,可以单独分析不同基因座等位基因的联合效应,而不会导致其他分离的Idd基因座的复杂化。在本文中,我们分析了携带两个染色体间隔(两个同基因菌株)的两对基因座的同系菌株的数据:Idd3和Idd10以及Idd3和Idd5。这两对的共同作用与在渗透率的对数赔率或责任量表上的可加性模型一致,而不是与先前提出的上位性乘法模型一致。对于Idd3和Idd5,我们也不会拒绝在渗透率上具有可加性的模型,这可能表明疾病模型是由导致β细胞破坏和糖尿病发展的多种途径介导的。然而,在生物学,统计,流行病学,定量和人类遗传学领域中使用的相互作用或上位性的不同定义之间一直存在混淆。统计分析可以阐明潜在生物学机制的程度可能受到限制,并且可能需要事先了解潜在病因。

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