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Relating drug response to epigenetic and genetic markers using a region-based kernel score test

In GAW20, we investigated the association of specific genetic regions of interest (ROIs) with log-transformed triglyceride (TG) levels following lipid-lowering medication using epigenetic and genetic markers. The goal was to incorporate kernels for cytosine-phosphate-guanine (CpG) markers and compar...

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Autores principales: Yasmeen, Summaira, Burger, Patricia, Friedrichs, Stefanie, Papiol, Sergi, Bickeböller, Heike
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6157113/
https://www.ncbi.nlm.nih.gov/pubmed/30275895
http://dx.doi.org/10.1186/s12919-018-0154-5
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author Yasmeen, Summaira
Burger, Patricia
Friedrichs, Stefanie
Papiol, Sergi
Bickeböller, Heike
author_facet Yasmeen, Summaira
Burger, Patricia
Friedrichs, Stefanie
Papiol, Sergi
Bickeböller, Heike
author_sort Yasmeen, Summaira
collection PubMed
description In GAW20, we investigated the association of specific genetic regions of interest (ROIs) with log-transformed triglyceride (TG) levels following lipid-lowering medication using epigenetic and genetic markers. The goal was to incorporate kernels for cytosine-phosphate-guanine (CpG) markers and compare the kernels to a purely parametric model. Post-treatment TG levels were investigated for post-methylation data at CpG sites and region-specific SNPs and adjusted for pre-treatment TG levels and age, in independent individuals only (real data: n = 150; simulated data, replicate 84: n = 111). In both data sets, our single-CpG-marker results using kernels and linear regression were in good agreement. In the real data, we investigated the introns of the CPT1A gene previously reported as associated with TG levels as separate ROIs, and were able to find hints of an association of cg17058475 and cg00574958 with post-treatment TG levels. In the simulated data, we investigated a total of 10 regions, in which the 5 causal and 5 non-causal markers lie, respectively, with increased methylation variances, yielding plausible results for the 3 window sizes. Overall, this indicates that kernels for CpG markers are feasible. An interaction regression model for the causal SNP with the nearest CpG marker identified an effect for the SNPs with the three greatest heritabilities simulated. The simulation model assumed full SNP effect only for unmethylated regions decreasing to zero in the case of full methylation. Thus, in the context of a clear candidate setting, interaction between epigenetic and genetic data may enhance information, albeit nominally, even with small sample sizes. Relieving the burden of multiple testing, developing kernels further to analyze data from multiple omics jointly is well warranted.
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spelling pubmed-61571132018-10-01 Relating drug response to epigenetic and genetic markers using a region-based kernel score test Yasmeen, Summaira Burger, Patricia Friedrichs, Stefanie Papiol, Sergi Bickeböller, Heike BMC Proc Proceedings In GAW20, we investigated the association of specific genetic regions of interest (ROIs) with log-transformed triglyceride (TG) levels following lipid-lowering medication using epigenetic and genetic markers. The goal was to incorporate kernels for cytosine-phosphate-guanine (CpG) markers and compare the kernels to a purely parametric model. Post-treatment TG levels were investigated for post-methylation data at CpG sites and region-specific SNPs and adjusted for pre-treatment TG levels and age, in independent individuals only (real data: n = 150; simulated data, replicate 84: n = 111). In both data sets, our single-CpG-marker results using kernels and linear regression were in good agreement. In the real data, we investigated the introns of the CPT1A gene previously reported as associated with TG levels as separate ROIs, and were able to find hints of an association of cg17058475 and cg00574958 with post-treatment TG levels. In the simulated data, we investigated a total of 10 regions, in which the 5 causal and 5 non-causal markers lie, respectively, with increased methylation variances, yielding plausible results for the 3 window sizes. Overall, this indicates that kernels for CpG markers are feasible. An interaction regression model for the causal SNP with the nearest CpG marker identified an effect for the SNPs with the three greatest heritabilities simulated. The simulation model assumed full SNP effect only for unmethylated regions decreasing to zero in the case of full methylation. Thus, in the context of a clear candidate setting, interaction between epigenetic and genetic data may enhance information, albeit nominally, even with small sample sizes. Relieving the burden of multiple testing, developing kernels further to analyze data from multiple omics jointly is well warranted. BioMed Central 2018-09-17 /pmc/articles/PMC6157113/ /pubmed/30275895 http://dx.doi.org/10.1186/s12919-018-0154-5 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Proceedings
Yasmeen, Summaira
Burger, Patricia
Friedrichs, Stefanie
Papiol, Sergi
Bickeböller, Heike
Relating drug response to epigenetic and genetic markers using a region-based kernel score test
title Relating drug response to epigenetic and genetic markers using a region-based kernel score test
title_full Relating drug response to epigenetic and genetic markers using a region-based kernel score test
title_fullStr Relating drug response to epigenetic and genetic markers using a region-based kernel score test
title_full_unstemmed Relating drug response to epigenetic and genetic markers using a region-based kernel score test
title_short Relating drug response to epigenetic and genetic markers using a region-based kernel score test
title_sort relating drug response to epigenetic and genetic markers using a region-based kernel score test
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6157113/
https://www.ncbi.nlm.nih.gov/pubmed/30275895
http://dx.doi.org/10.1186/s12919-018-0154-5
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