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采用双变量线性混合模型分析来检验基因变异与收缩压和舒张压的联合关联。

Bivariate linear mixed model analysis to test joint associations of genetic variants on systolic and diastolic blood pressure.

作者信息

Neupane Binod, Beyene Joseph

机构信息

Population Genomics Program, McMaster University, 1200 Main Street West, Hamilton, Ontario, L8N 3Z5, Canada.

出版信息

BMC Proc. 2014 Jun 17;8(Suppl 1 Genetic Analysis Workshop 18Vanessa Olmo):S75. doi: 10.1186/1753-6561-8-S1-S75. eCollection 2014.

Abstract

Genetic variants that predispose adults and the elderly to high blood pressure are largely unknown. We used a bivariate linear mixed model approach to jointly test the associations of common single-nucleotide polymorphisms with systolic and diastolic blood pressure using data from a genome-wide association study consisting of genetic variants from chromosomes 3 and 9 and longitudinal measured phenotypes and environment variables from unrelated individuals of Mexican American ethnicity provided by the Genetic Analysis Workshop 18. Despite the small sample size of a maximum of 131 unrelated subjects, a few single-nucleotide polymorphisms appeared significant at the genome-wide level. Simulated data, which was also provided by Genetic Analysis Workshop 18 organizers, showed higher power of the bivariate approach over univariate analysis to detect the association of a selected single-nucleotide polymorphism with modest effect. This suggests that the bivariate approach to longitudinal data of jointly measured and correlated phenotypes can be a useful strategy to identify candidate single-nucleotide polymorphisms that deserve further investigation.

摘要

导致成年人和老年人患高血压的基因变异在很大程度上尚不明确。我们使用双变量线性混合模型方法,利用遗传分析研讨会18提供的来自墨西哥裔美国人的无关个体的全基因组关联研究数据,共同检验常见单核苷酸多态性与收缩压和舒张压的关联,该数据包含来自3号和9号染色体的基因变异以及纵向测量的表型和环境变量。尽管最大样本量仅131名无关受试者,仍有一些单核苷酸多态性在全基因组水平上显示出显著性。遗传分析研讨会18的组织者提供的模拟数据表明,与单变量分析相比,双变量方法在检测具有适度效应的选定单核苷酸多态性的关联方面具有更高的效能。这表明,对于联合测量且相关的表型的纵向数据,双变量方法可能是识别值得进一步研究的候选单核苷酸多态性的有用策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc1a/4143667/1ee380642279/1753-6561-8-S1-S75-1.jpg

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