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. 2018 Sep 17;19(Suppl 1):64.
doi: 10.1186/s12863-018-0652-5.

Detecting responses to treatment with fenofibrate in pedigrees

Affiliations

Detecting responses to treatment with fenofibrate in pedigrees

Svetlana Cherlin et al. BMC Genet. .

Abstract

Background: Fenofibrate (Fb) is a known treatment for elevated triglyceride (TG) levels. The Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study was designed to investigate potential contributors to the effects of Fb on TG levels. Here, we summarize the analyses of 8 papers whose authors had access to the GOLDN data and were grouped together because they pursued investigations into Fb treatment responses as part of GAW20. These papers report explorations of a variety of genetics, epigenetics, and study design questions. Data regarding treatment with 160 mg of micronized Fb per day for 3 weeks included pretreatment and posttreatment TG and methylation levels (ML) at approximately 450,000 epigenetic markers (cytosine-phosphate-guanine [CpG] sites). In addition, approximately 1 million single-nucleotide polymorphisms (SNPs) were genotyped or imputed in each of the study participants, drawn from 188 pedigrees.

Results: The analyses of a variety of subsets of the GOLDN data used a number of analytic approaches such as linear mixed models, a kernel score test, penalized regression, and artificial neural networks.

Conclusions: Results indicate that (a) CpG ML are responsive to Fb; (b) CpG ML should be included in models predicting the TG level responses to Fb;

Keywords: Epigenetics; Fenofibrate treatment; GOLDN study; Predictive modeling; Triglycerides.

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Competing interests

The authors declare that they have no competing interests.

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References

    1. Irvin MR, Zhi D, Aslibekyan S, Claas SA, Absher DM, Ordovas JM, Tiwari HK, Watkins S, Arnett DK. Genomics of post-prandial lipidomic phenotypes in the genetics of lipid lowering drugs and diet network (GOLDN) study. PLoS One. 2014;9(6):e99509. doi: 10.1371/journal.pone.0099509. - DOI - PMC - PubMed
    1. Cantor R, Navarro L, Pan C. Identifying fenofibrate responsive CpG sites. BMC Proc. 2018;12(Suppl 9). 10.1186/s12919-018-0148-3. - PMC - PubMed
    1. Cherlin S, Howey RAJ, Cordell HJ. Using penalized regression to predict phenotype from SNP data. BMC Proc. 2018;12(Suppl 9). 10.1186/s12919-018-0149-2. - PMC - PubMed
    1. Hsu Y, Auerbach J, Zheng T, Lo S-h. Coping with family structure in genome-wide association studies: a comparative evaluation. BMC Proc. 2018;12(Suppl 9). 10.1186/s12919-018-0151-8. - PMC - PubMed
    1. Wu J, Patel D, Chung J, Zhu C, Lent S, Fisher V, Pitsillides A, Farrer L, Zhang X. An efficient analytic approach in genome-wide identification of methylation quantitative trait loci response to fenofibrate treatment. BMC Proc. 2018;12(Suppl 9). 10.1186/s12919-018-0152-7. - PMC - PubMed

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