Methods to evaluate rare variants gene-age interaction for triglycerides
AbstractTriglycerides are an important measure of heart health. Although more than 90 genes have been found to be associated to lipids, they only explain 12 to 15% of the variance in lipid levels. Evidence suggests that age may interact with the genetic effect on lipid levels. Existing methods to detect the main effect of rare variants cannot be readily applied for testing the gene environment interaction effect of rare variants, as those methods either have unstable results or inflated Type I error rates when the main effect exists. To overcome these difficulties, we developed two statistical methods: testing of optimally...
Source: BMC Proceedings - September 17, 2018 Category: Biomedical Science Source Type: research
Application of Bayesian networks to GAW20 genetic and blood lipid data
ConclusionsEven when the causal relationships between variables are known, as with the simulated data, if the relationships are not strong then it is challenging to reproduce them in a Bayesian network. (Source: BMC Proceedings)
Source: BMC Proceedings - September 17, 2018 Category: Biomedical Science Source Type: research
Network analysis of drug effect on triglyceride-associated DNA methylation
ConclusionsThe same 3 modules, which were differentially methylated between pre- and posttreatment, were identified using both WGCNA module-preservation and GHD methods. Pathway analysis revealed that triglyceride-associated modules contain groups of genes that are involved in lipid signaling and metabolism. These 3 modules may provide insight into the effect of fenofibrate on changes in triglyceride levels and these methylation sites. (Source: BMC Proceedings)
Source: BMC Proceedings - September 17, 2018 Category: Biomedical Science Source Type: research
Identifying fenofibrate responsive CpG sites
AbstractAs part of GAW20, we analyzed the familiality and variability of methylation to identify cytosine-phosphate-guanine (CpG) sites responsive to treatment with fenofibrate. Methylation was measured at approximately 450,000 sites in pedigree members, prior to and after 3 weeks of treatment. Initially, we aimed to identify responsive sites by analyzing the pre- and posttreatment methylation changes within individuals, but these data exhibited a confounding treatment/batch effect. We applied an alternative indirect approach by searching for CpG sites whose methylati on levels exhibit a genetic response to the drug. We ...
Source: BMC Proceedings - September 17, 2018 Category: Biomedical Science Source Type: research
Evidence of batch effects masking treatment effect in GAW20 methylation data
AbstractUsing the real data set from GAW20, we examined changes in the distribution of DNA methylation before and after treatment. Paired analysis of differences in both mean and variance had grossly inflated type 1 error, suggesting either a very large number of changes across the entire epigenome or major non-biological issues, such as batch effects. Separate analysis of Infinium I and II probes indicated differences in the pairedt-test statistics between these two types of probes. Examination of combined principal components showed that the first and fourth principal components discriminate between the before and after ...
Source: BMC Proceedings - September 17, 2018 Category: Biomedical Science Source Type: research
An efficient analytic approach in genome-wide identification of methylation quantitative trait loci response to fenofibrate treatment
ConclusionsBy using a novel analytic approach, we efficiently identified thousands ofcis re-meQTLs that provide a unique resource for further characterizing functional roles and gene targets of the SNPs that are most responsive to fenofibrate treatment. Our efficient analytic approach can be extended to large response quantitative trait locus studies with large sample sizes and multiple time points data. (Source: BMC Proceedings)
Source: BMC Proceedings - September 17, 2018 Category: Biomedical Science Source Type: research
Assessment of fenofibrate-methylation interactions on triglycerides using longitudinal family data
ConclusionsOur analyses suggest that DNA methylation likely modified the effect of fenofibrate on TG concentrations. Differential fenofibrate-associated methylation sites on TGs differed with and without adjusting for HDL concentrations, suggesting that these HDLs and TGs might share some common epigenetic processes. (Source: BMC Proceedings)
Source: BMC Proceedings - September 17, 2018 Category: Biomedical Science Source Type: research
Methods for detecting methylation by SNP interaction in GAW20 simulation
AbstractTo examine whether single-nucleotide polymorphism (SNP) by methylation interactions can be detected, we analyzed GAW20 simulated triglycerides at visits 3 and 4 against baseline (visits 1 and 2) under 4 general linear models and 2 tree-based models in 200 replications of a sample of 680 individuals. Effects for SNPs, methylation cytosine-phosphate-guanine (CpG) effects, and interactions for SNP/CpG pairs were included. Causative SNPs/CpG pairs distributed on autosomal chromosomes 1 to 20 were tested to examine sensitivity. We also tested noncausative SNP/CpG pairs on chromosomes 21 and 22 to estimate the empirical ...
Source: BMC Proceedings - September 17, 2018 Category: Biomedical Science Source Type: research
Using penalized regression to predict phenotype from SNP data
ConclusionsLASSO regression results in a heavy shrinkage of the regression coefficients, and also requires large sample sizes (several thousand individuals) to achieve good prediction. (Source: BMC Proceedings)
Source: BMC Proceedings - September 17, 2018 Category: Biomedical Science Source Type: research
Analysis of genetic and nongenetic factors influencing triglycerides-lowering drug effects based on paired observations
In this study, we assessed both genetic and nongenetic factors that influence drug responses and stratified patients into groups based on differential drug effect and sensitivity. Our methodology of investigating genetic factors and nongenetic factors is applicable to studying differential effects of other drugs, such as statins, and provides an approach to the development of personalized medicine. (Source: BMC Proceedings)
Source: BMC Proceedings - September 17, 2018 Category: Biomedical Science Source Type: research
Heritability and genetic associations of triglyceride and HDL-C levels using pedigree-based and empirical kinships
This study compares the use of pedigree and empirical kinships in the GAW20 data set. Two phenotypes were assessed: triglyceride levels and high-density lipoprotein cholesterol (HDL-C) levels pre- and postintervention with the cholesterol-reducing drug fenofibrate. Using SOLAR (Sequential Oligogenic Linkage Analysis Routines), pedigree-based kinships and empirically calculated kinships (using IBDLD and LDAK) were used to calculate phenotype heritability. In addition, a genome-wide association study was conducted using each kinship model for each phenotype to identify genetic variants significantly associated with phenotypi...
Source: BMC Proceedings - September 17, 2018 Category: Biomedical Science Source Type: research
Evaluation of a phenotype imputation approach using GAW20 simulated data
AbstractStatistical power, which is the probability of correctly rejecting a false null hypothesis, is a limitation of genome-wide association studies (GWAS). Sample size is a major component of statistical power that can be easily affected by missingness in phenotypic data and restrain the ability to detect associated single-nucleotide polymorphisms (SNPs) with small effect sizes. Although some phenotypes are hard to collect because of cost and loss to follow-up, correlated phenotypes that are easily collected can be leveraged for association analysis. In this paper, we evaluate a phenotype imputation method that incorpor...
Source: BMC Proceedings - September 17, 2018 Category: Biomedical Science Source Type: research
Family-based genome-wide association of inflammation biomarkers and fenofibrate treatment response in the GOLDN study
AbstractIn this paper we analyzed whole-genome genetic information provided by GAW20 from the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study for family data. Lipid levels such as triglycerides (TGs) and high-density lipoprotein (HDL) are measured at different time points before and after administration of an anti-inflammatory drug fenofibrate. Apart from that, the data contain some covariates and whole-genome genotype information. We propose 2 novel approaches based on Henderson ’s iterative mixed model to identify associated loci corresponding to (a) inflammatory biomarkers like TGs and HDLs together ov...
Source: BMC Proceedings - September 17, 2018 Category: Biomedical Science Source Type: research
CpG-set association assessment of lipid concentration changes and DNA methylation
This study ’s goals were to investigate region-based associations between DNA methylation sites and lipid-level changes in response to the treatment with fenofibrate in the GAW20 data and to investigate whether improvements in power could be obtained by taking into account correlations between DNA methylatio n at neighboring cytosine-phosphate-guanine (CpG) sites. To this end, we applied both a recently developed block-based data-dimension-reduction approach and a region-based variance-component (VC) linear mixed model to GAW20 data. We compared analyses of unrelated individuals with familial data. The region-based VC ap...
Source: BMC Proceedings - September 17, 2018 Category: Biomedical Science Source Type: research
A deep neural network based regression model for triglyceride concentrations prediction using epigenome-wide DNA methylation profiles
ConclusionsWe demonstrated the superiority of our proposed DNN models over the SVM model for predicting triglyceride concentrations. This study also suggests that the DNN approach has advantages over other traditional machine-learning methods to model high-dimensional epigenome-wide DNAm data and other genomic data. (Source: BMC Proceedings)
Source: BMC Proceedings - September 17, 2018 Category: Biomedical Science Source Type: research
