Abstract
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 GAW19 unrelateds sequence data. Using only the real (not simulated) GAW19 data, we show through the use of statistical tests that account for family relatedness, using FaST-LMM (Factored Spectrally Transformed Linear Mixed Model), that none of our candidate SNPs yields a significant p value. Furthermore, a study of epistasis, aiming to detect statistical interactions between loci with respect to their association with transcription levels has provided a list of 30 associated interacting SNP pairs, of which 13 are present in the GAW19 family GWAS and expression data. We show for this set of results, using the program GEMMA (genome-wide efficient mixed-model analysis) to account for family relatedness, that there is evidence of replication within the real GAW19 data. Two individual SNP pairs reach significance, and the set of remaining results give a combined p value of 0.017 that at least 1 of these remaining SNP pairs interacts to influence an expression phenotype.
Highlights
Previous studies using very large data sets have provided a list of single-nucleotide polymorphisms (SNPs) believed to be associated with blood pressure and expression phenotypes
We attempt to replicate these SNPs in the Genetic Analysis Workshop 19 (GAW19) family genomewide association studies (GWAS) data set and GAW19 sequence data, which may indicate the feasibility of finding novel SNPs in the GAW19 data sets
A meta-analysis study conducted by Tragante et al [3] of 87,736 individuals provided 95 candidate SNPs associated with blood pressure–related phenotypes; of these, 44 candidate SNPs were present in the GAW19 family data
Summary
A meta-analysis study conducted by Tragante et al [3] of 87,736 individuals provided 95 candidate SNPs associated with blood pressure–related phenotypes; of these, 44 candidate SNPs were present in the GAW19 family data. To examine the overall association of a set of SNPs we defined a statistic inspired by Dudbridge and Koeleman’s rank truncated product statistic [4]: −Xn i1⁄41. Log pi where pi is the p value of the ith SNP tested from n candidate SNPs. Candidate SNPs for each phenotype were considered together giving overall p values for DBP, MAP, PP, SBP, and HTN. The overall p value is given by the proportion of simulated test statistics greater than the observed test statistic, from 500,000 replicates generated under the null hypothesis. An alternative method to control the false discovery rate for correlated test statistics is given by Yekutieli and Benjamini [6]
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