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            <name>Title</name>
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                <text>Coronavirus</text>
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            <description>An account of the resource</description>
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                <text>Dominio científico: Coronavirus</text>
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          <name>Title</name>
          <description>A name given to the resource</description>
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              <text>Modification effect of fenofibrate therapy, a longitudinal epigenomic-wide methylation study of triglycerides levels in the GOLDN study</text>
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          <name>Creator</name>
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              <text>Runmin Wei, Yanyan Wu</text>
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          <name>Description</name>
          <description>An account of the resource</description>
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              <text>Abstract Background Identification of interactions between epigenetic factors and treatments might lead to personalized intervention of diseases. This paper aims to examine the modification effect of fenofibrate therapy on the association of methylation levels and fasting blood triglycerides (TG), and the related biological pathways among methylation sites. Results Mixed-effects models were employed to assess pre- and posttreatment associations and drug modification effects simultaneously. Five cytosine-phosphate-guanine (CpG) sites were found to be associated with TG levels before and after the fenofibrate therapy: cg00574958, cg17058475, and cg01082498 on CPT1A gene, chromosome 11; cg03725309 on SARS, chromosome 1; and cg06500161 on ABCG1, chromosome 21. In addition, fenofibrate therapy modified the methylation levels on the following 4 CpG sites: cg20015535 (gene EGLN1, chromosome 1); cg24870738 (gene RNF220, chromosome 1); cg06891775 (gene LOC283050, chromosome 10); and cg00607630 (gene USP7, chromosome 16). Further, gene set enrichment analysis (GSEA) identified cancer- and metabolism-related pathways that were associated with TG-related CpG sites. Conclusions We identified modification effects of fenofibrate on the associations between blood TG levels and several CpG sites. Pathway enrichment analysis indicated the alternations in some metabolism and cancer-related pathways. Our findings have important implications for future research in pharmacoepigenetics and personalized medicine.</text>
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          <name>Date</name>
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              <text>2018</text>
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          <name>Subject</name>
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              <text>methylation, TG, repeated-measures, mixed models, interaction, GSEA</text>
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          <name>Identifier</name>
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              <text>DOI: 10.1186/s12863-018-0643-6</text>
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          <name>Source</name>
          <description>A related resource from which the described resource is derived</description>
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              <text>BMC Genetics</text>
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          <name>Publisher</name>
          <description>An entity responsible for making the resource available</description>
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              <text>BMC</text>
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          <name>Coverage</name>
          <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
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              <text>Genetics</text>
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              <text>EN</text>
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