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在奠基者群体中寻找多因素疾病易感性基因。

Search for multifactorial disease susceptibility genes in founder populations.

作者信息

Bourgain C, Genin E, Quesneville H, Clerget-Darpoux F

机构信息

Unité de Recherche d'Epidémiologie Génétique, INSERM U535, Bâtiment Gregory Pincus, 78 rue du Géneral Leclerc, 94275 Le Kremlin-Bicêtre Cedex, France.

出版信息

Ann Hum Genet. 2000 May;64(Pt 3):255-65. doi: 10.1046/j.1469-1809.2000.6430255.x.

Abstract

The current challenge in biomedical research is to detect genetic risk factors involved in common complex diseases. The power to detect their role is generally poor in populations that have been large for a long time. It has been suggested that the power may be increased by taking advantage of the specificity of founder populations: linkage disequilibrium spanning larger regions and kinship coefficients being stronger than in large populations. A new method is proposed here, the Maximum Identity Length Contrast (MILC) which, in contrast with other existing methods, does not make the assumption of unique ancestry for the genetic risk factors. It is thus appropriate for a search for common genetic risk factors for complex diseases. Statistical properties of the method are discussed in realistic contexts.

摘要

生物医学研究当前面临的挑战是检测与常见复杂疾病相关的遗传风险因素。在长期以来规模较大的人群中,检测这些因素作用的能力通常较差。有人提出,利用奠基者群体的特异性可能会提高检测能力:与大规模人群相比,连锁不平衡跨越的区域更大,亲缘系数更强。本文提出了一种新方法,即最大同一性长度对比法(MILC),与其他现有方法不同,该方法不假设遗传风险因素具有单一祖先。因此,它适用于寻找复杂疾病的常见遗传风险因素。在实际背景下讨论了该方法的统计特性。

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