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多因素疾病遗传成分分析策略;生物统计学方面。

Strategies in analysis of the genetic component of multifactorial diseases; biostatistical aspects.

作者信息

Barnetche Thomas, Gourraud Pierre-Antoine, Cambon-Thomsen Anne

机构信息

Unité INSERM 558, Department of Epidemiology Faculté de médecine, 37 allées Jules Guesde, F-31073 Toulouse, France.

出版信息

Transpl Immunol. 2005 Aug;14(3-4):255-66. doi: 10.1016/j.trim.2005.03.015. Epub 2005 Apr 26.

Abstract

Complex polygenic and multifactorial diseases remain a challenge for human geneticists. Here we aim to remind basic definitions of multifactorial diseases and the genetic related concepts underlying classical methods. Knowledge on pathophysiological process and the genetic information available conditions the design of study. The choice of methodology, between candidate gene approach and genome scan approach, between linkage and association studies, is the most important step. Both methods, linkage analysis and association studies are usually considered as complementary approaches for a given disease. For this reason, in this article, we present the most important classical methodologies in genetic epidemiology of complex disorders. References and examples are given to illustrate.

摘要

复杂的多基因和多因素疾病仍然是人类遗传学家面临的挑战。在此,我们旨在回顾多因素疾病的基本定义以及经典方法背后的遗传相关概念。对病理生理过程和可用遗传信息的了解为研究设计提供了条件。在候选基因方法和全基因组扫描方法之间、连锁研究和关联研究之间选择方法,是最重要的一步。连锁分析和关联研究这两种方法通常被视为针对特定疾病的互补方法。因此,在本文中,我们介绍复杂疾病遗传流行病学中最重要的经典方法,并给出参考文献和示例进行说明。

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