Joint analysis of multiple blood pressure phenotypes in GAW19 data by using a multivariate rare-variant association test
نویسندگان
چکیده
INTRODUCTION Large-scale sequencing studies often measure many related phenotypes in addition to the genetic variants. Joint analysis of multiple phenotypes in genetic association studies may increase power to detect disease-associated loci. METHODS We apply a recently developed multivariate rare-variant association test to the Genetic Analysis Workshop 19 data in order to test associations between genetic variants and multiple blood pressure phenotypes simultaneously. We also compare this multivariate test with a widely used univariate test that analyzes phenotypes separately. RESULTS The multivariate test identified 2 genetic variants that have been previously reported as associated with hypertension or coronary artery disease. In addition, our region-based analyses also show that the multivariate test tends to give smaller p values than the univariate test. CONCLUSIONS Hence, the multivariate test has potential to improve test power, especially when multiple phenotypes are correlated.
منابع مشابه
Genome-wide joint analysis of single-nucleotide variant sets and gene expression for hypertension and related phenotypes
BACKGROUND With the advance of next-generation sequencing technologies, the study of rare variants in targeted genome regions or even the whole genome becomes feasible. Nevertheless, the massive amount of sequencing data brings great computational and statistical challenges for association analyses. Aside from sequencing variants, other high-throughput omic data (eg, gene expression data) also ...
متن کاملComparing family-based rare variant association tests for dichotomous phenotypes
BACKGROUND It has been repeatedly stressed that family-based samples suffer less from genetic heterogeneity and that association analyses with family-based samples are expected to be powerful for detecting susceptibility loci for rare disease. Various approaches for rare-variant analysis with family-based samples have been proposed. METHODS In this report, performances of the existing methods...
متن کاملExamination of previously identified associations within the Genetic Analysis Workshop 19 data
We investigate the possible replication of "known" associated single-nucleotide polymorphisms (SNPs) with blood pressure and expression phenotypes. Previous studies have provided a list of 95 SNPs thought to be associated with blood pressure phenotypes, of which 44 were present in the Genetic Analysis Workshop 19 (GAW19) family-imputed genome-wide association studies (GWAS) data and 4 in the GA...
متن کاملConstrained multivariate association with longitudinal phenotypes
BACKGROUND The incorporation of longitudinal data into genetic epidemiological studies has the potential to provide valuable information regarding the effect of time on complex disease etiology. Yet, the majority of research focuses on variables collected from a single time point. This aim of this study was to test for main effects on a quantitative trait across time points using a constrained ...
متن کاملRare-Variant Kernel Machine Test for Longitudinal Data from Population and Family Samples.
OBJECTIVE The kernel machine (KM) test reportedly performs well in the set-based association test of rare variants. Many studies have been conducted to measure phenotypes at multiple time points, but the standard KM methodology has only been available for phenotypes at a single time point. In addition, family-based designs have been widely used in genetic association studies; therefore, the dat...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره 10 شماره
صفحات -
تاریخ انتشار 2016