Dyslipidemias play a large role in the occurrence of cardiovascular disease, which has fueled interest to better understand environmental factors responsible for dyslipidemias, especially hypertriglyceridemia. Epigenetic variations may affect triglyceride (TG) metabolism and response to environmental challenges. Our goal is to conduct the first experiments that will comprehensively scan the epigenome for determinants of TG and other dyslipidemic responses to two "environmental" interventions, one to raise TGs (a high-fat meal), and one to lower TGs (3-week fenofibrate treatment). These experiments will be conducted in the NHLBI Program in Gene-Environment Interaction Network's "Genetics of Lipid Lowering and Diet" (GOLDN) study. GOLDN recruited family members from field centers in Minnesota and Utah and phenotyped them extensively for enzymatic and NMR lipids and inflammatory markers in response to the two interventions. The proposed study will build upon this unique resource using previously collected samples to implement the following aims: (1) Conduct genome-wide CpG methylation analysis, using next generation sequencing method, specifically, Reduced Representation Bisulfite Sequencing, in 1,048 individuals from 184 families to identify epigenetic variation contributing to the response of TGs and TG-related phenotypes to a fat meal, fenofibrate, and a fat meal in the context of fenofibrate treatment. From these results, we will select 20 candidate genes with the best evidence for further characterization in Aim 2. (2) Characterize the methylation state of these 20 genes using bisulfite sequencing of promoters and other regions of interest in all 1,048 family members. (3) Replicate significant findings from Aims 1 and 2 in external cohorts. (4) Conduct gene expression studies to identify the functional impact of methylation findings from Aims 1-3 since DNA methylation may affect the expression of nearby genes in a variety of ways, including transcription rates, alternative splicing, microRNA inhibition, or allele specific expression. We will apply next-generation sequencing to both mRNA and microRNA from 150 subjects using a method called RNAseq. If successful, we will identify novel epigenetic variations that predict individuals who respond poorly to dietary fat or favorably to fenofibrate which will lead to the development of targeted interventions to more effectively prevent and treat hypertriglyceridemia.

Public Health Relevance

Epigenetics is a relatively new area of study which seeks to understand how gene activity rather than gene structure influences people's traits. Epigenetic factors may explain why the levels of fat and cholesterol in some people's blood change dramatically after eating a high-fat meal or after taking fat-lowering drugs while fat and cholesterol levels in other people change very little under the same conditions. This study aims to discover the epigenetic factors that cause people's bodies to respond so differently to diet and drugs with the belief that such knowledge could ultimately help lower people's risk for cardiovascular disease.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
5R01HL104135-03
Application #
8300134
Study Section
Special Emphasis Panel (ZRG1-PSE-J (03))
Program Officer
Jaquish, Cashell E
Project Start
2010-08-15
Project End
2014-05-31
Budget Start
2012-07-01
Budget End
2013-06-30
Support Year
3
Fiscal Year
2012
Total Cost
$1,083,646
Indirect Cost
$162,325
Name
University of Alabama Birmingham
Department
Public Health & Prev Medicine
Type
Schools of Public Health
DUNS #
063690705
City
Birmingham
State
AL
Country
United States
Zip Code
35294
Aslibekyan, Stella; Claas, Steven A; Arnett, Donna K (2015) Clinical applications of epigenetics in cardiovascular disease: the long road ahead. Transl Res 165:143-53
Irvin, Marguerite R; Zhi, Degui; Joehanes, Roby et al. (2014) Epigenome-wide association study of fasting blood lipids in the Genetics of Lipid-lowering Drugs and Diet Network study. Circulation 130:565-72
Wu, Guodong; Yi, Nengjun; Absher, Devin et al. (2011) Statistical quantification of methylation levels by next-generation sequencing. PLoS One 6:e21034