Abstract
Performance of a recently developed test for association between multivariate phenotypes and sets of genetic variants (MURAT) is demonstrated using measures of bone mineral density (BMD). By combining individual-level whole genome sequenced data from the UK10K study, and imputed genome-wide genetic data on individuals from the Study of Osteoporotic Fractures (SOF) and the Osteoporotic Fractures in Men Study (MrOS), a data set of 8810 individuals was assembled; tests of association were performed between autosomal gene-sets of genetic variants and BMD measured at lumbar spine and femoral neck. Distributions of p-values obtained from analyses of a single BMD phenotype are compared to those from the multivariate tests, across several region definitions and variant weightings. There is evidence of increased power with the multivariate test, although no new loci for BMD were identified. Among 17 genes highlighted either because there were significant p-values in region-based association tests or because they were in well-known BMD genes, 4 windows in 2 genes as well as 6 single SNPs in one of these genes showed association at genome-wide significant thresholds with the multivariate phenotype test but not with the single-phenotype test, Sequence Kernel Association Test (SKAT).
Highlights
The massive advances and cost decreases in sequencing technologies have led to identification of millions of rare minor alleles (defined here as those minor allele frequency (MAF) less than 0.05)
To create a data set with reasonable power for rare-variant analyses, a single data set was created by combining individual-level data from three large cohorts: whole-genome sequencing data from a subset of the UK10K project[18], and genome-wide genotyping data that had undergone imputation from the Study of Osteoporotic Fractures (SOF)[19] and Osteoporotic Fractures in Men (MrOS) Study[20,21]
Tests of association between genetic variation in the genetic regions and bone mineral density (BMD) are performed with a recently developed multivariate rare-variant set-based association test (MURAT)[12] that is built on a mixed effect model, and the well-known single phenotype Sequence Kernel Association Test (SKAT) test[4], which is derived from a mixed effect model
Summary
The massive advances and cost decreases in sequencing technologies have led to identification of millions of rare minor alleles (defined here as those minor allele frequency (MAF) less than 0.05). Set-based tests have been proposed to try and improve power by jointly testing association with multiple rare variants in a pre-defined set. We use a well-studied phenotype, bone mineral density (BMD)[16,17], to investigate the potential benefits associated with a multivariate-phenotype analysis of correlated BMD phenotypes and associations with genetic variation using set-based methods. To create a data set with reasonable power for rare-variant analyses, a single data set was created by combining individual-level data from three large cohorts: whole-genome sequencing data from a subset of the UK10K project[18] (http://www.uk10k.org/ and www.gefos.org), and genome-wide genotyping data that had undergone imputation from the Study of Osteoporotic Fractures (SOF)[19] We first perform an exome-wide gene-based analysis, and study more intensively some selected candidate genes
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