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高血压与全基因组关联研究:结合高保真表型分析与超对照

Hypertension and genome-wide association studies: combining high fidelity phenotyping and hypercontrols.

作者信息

Padmanabhan Sandosh, Melander Olle, Hastie Claire, Menni Cristina, Delles Christian, Connell John M, Dominiczak Anna F

机构信息

BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, UK.

出版信息

J Hypertens. 2008 Jul;26(7):1275-81. doi: 10.1097/HJH.0b013e3282ff634f.

DOI:10.1097/HJH.0b013e3282ff634f
PMID:18550997
Abstract

Among the common complex diseases, hypertension has been particularly unlucky in the recent surge of positive results from genome-wide association studies. We summarize the evidence that would support continuing the effort in the hunt for a genetic basis for hypertension. The problems facing the genetic studies for hypertension are not unique, but phenotypic characterization, heterogeneity and high prevalence make it a special case requiring a more individualized approach. We argue that, even in the presence of a strong environmental component to hypertension risk, the common disease/common variant model is relevant for hypertension and discuss the issues involved in designing a genome-wide association study for hypertension. It is likely that the individual odds ratios for disease variants will be less than 1.3 and, although individually these effect sizes are minor, the combination of even a few such common polymorphisms can have substantial population attributable risks. The identification of hypertension gene variants should provide new insight into the disease susceptibility, progression and severity. This will lead to the identification of potential targets for lifestyle and pharmacological interventions, with the ultimate goal of improving prevention, diagnosis and treatment.

摘要

在常见的复杂疾病中,在近期全基因组关联研究取得大量阳性结果的热潮中,高血压却尤为不走运。我们总结了支持继续努力寻找高血压遗传基础的证据。高血压遗传研究面临的问题并非独一无二,但表型特征、异质性和高患病率使其成为一个需要更个性化方法的特殊案例。我们认为,即使高血压风险存在很强的环境因素,常见疾病/常见变异模型仍适用于高血压,并讨论了设计高血压全基因组关联研究中涉及的问题。疾病变异的个体优势比可能小于1.3,而且尽管这些效应大小单独来看较小,但即使是少数此类常见多态性的组合也可能具有相当大的人群归因风险。高血压基因变异的识别应能为疾病易感性、进展和严重程度提供新的见解。这将有助于识别生活方式和药物干预的潜在靶点,最终目标是改善预防、诊断和治疗。

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