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对最近确定的阿尔茨海默病风险基因座致病机制的初步评估。

Initial assessment of the pathogenic mechanisms of the recently identified Alzheimer risk Loci.

作者信息

Holton Patrick, Ryten Mina, Nalls Michael, Trabzuni Daniah, Weale Michael E, Hernandez Dena, Crehan Helen, Gibbs J Raphael, Mayeux Richard, Haines Jonathan L, Farrer Lindsay A, Pericak-Vance Margaret A, Schellenberg Gerard D, Ramirez-Restrepo Manuel, Engel Anzhelika, Myers Amanda J, Corneveaux Jason J, Huentelman Matthew J, Dillman Allissa, Cookson Mark R, Reiman Eric M, Singleton Andrew, Hardy John, Guerreiro Rita

机构信息

Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK.

出版信息

Ann Hum Genet. 2013 Mar;77(2):85-105. doi: 10.1111/ahg.12000. Epub 2013 Jan 30.

Abstract

Recent genome wide association studies have identified CLU, CR1, ABCA7 BIN1, PICALM and MS4A6A/MS4A6E in addition to the long established APOE, as loci for Alzheimer's disease. We have systematically examined each of these loci to assess whether common coding variability contributes to the risk of disease. We have also assessed the regional expression of all the genes in the brain and whether there is evidence of an eQTL explaining the risk. In agreement with other studies we find that coding variability may explain the ABCA7 association, but common coding variability does not explain any of the other loci. We were not able to show that any of the loci had eQTLs within the power of this study. Furthermore the regional expression of each of the loci did not match the pattern of brain regional distribution in Alzheimer pathology. Although these results are mainly negative, they allow us to start defining more realistic alternative approaches to determine the role of all the genetic loci involved in Alzheimer's disease.

摘要

近期全基因组关联研究除了已确定的载脂蛋白E(APOE)外,还发现了CLU、CR1、ABCA7、BIN1、PICALM和MS4A6A/MS4A6E是阿尔茨海默病的基因座。我们系统地研究了这些基因座中的每一个,以评估常见编码变异是否会增加疾病风险。我们还评估了所有基因在大脑中的区域表达情况,以及是否有证据表明存在解释该风险的表达数量性状基因座(eQTL)。与其他研究一致,我们发现编码变异可能解释ABCA7的关联,但常见编码变异无法解释其他任何基因座。在本研究的能力范围内,我们无法证明任何一个基因座存在eQTL。此外,每个基因座的区域表达与阿尔茨海默病病理学中脑区分布模式不匹配。尽管这些结果大多为阴性,但它们使我们能够开始定义更现实的替代方法,以确定所有参与阿尔茨海默病的基因座的作用。

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