Detecting Differentially Methylated Genes Associated with Drug Response

Hongyan Xu, Fengjiao Hu, Santu Ghosh, Sunil Mathur and Varghese George
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Varghese George: Department of Population Health Sciences, Augusta University, USA

Biostatistics and Biometrics Open Access Journal, 2019, vol. 9, issue 3, 69-71

Abstract: DNA methylation has long been involved in inter-individual variations in drug response. In this study, we focused on the methylation changes associated with the response in terms of triglyceride changes before and after the treatment with fenofibrate using the real data set. We analyzed samples that are independent (founders and marry-ins) from each pedigree. Subjects were categorized into responders and non-responders according to percent changes in triglyceride. We then applied a novel spatial scan statistic to identify genes that are differentially methylated between the responders and non-responders. All the CpG sites within a gene were analyzed together. The spatial scan statistic approach uses a mixed-effects model to incorporate correlations of methylation rates among CpG sites. We analyzed the methylation data at visit 2, accounting for the effects of age, sex, and smoking status as covariates. Methylation levels at 312 genes from 22 autosomes were significantly associated with drug response with p

Keywords: Biometrics Open Access Journal; Biostatistics and Biometrics; Biostatistics and Biometrics Open Access Journal; Open Access Journals; biometrics journal; biometrics articles; biometrics journal reference; biometrics journal impact factor; biometrics and biostatistics journal impact factor; journal of biometrics; open access juniper publishers; juniper publishers reivew (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:adp:jbboaj:v:9:y:2019:i:3:p:69-71

DOI: 10.19080/BBOAJ.2019.09.555763

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