July 22, 2014
Genetic research regarding blood lipids has largely focused on DNA sequence variation; few studies have explored epigenetic effects. Genome-wide surveys of DNA methylation may uncover epigenetic factors influencing lipid metabolism. To identify whether differential methylation of cytosine-guanine dinucleotides (CpGs) correlated with lipid phenotypes, M. Ryan Irvin, PhD, assistant professor in the Department of Epidemiology, recently isolated DNA from CD4+ T-cells and quantified proportion of sample methylation at over 450,000 CpGs, using the Illumina Infinium HumanMethylation450 Beadchip in 991 participants of the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN). Co-investigators include department colleagues Stella Aslibekyan, PhD, assistant professor; Steven A. Claas, Program Manager II; and Donna K. Arnett, PhD, MSPH, chair and professor; along with Degui Zhi, PhD, assistant professor, and Hemant K. Tiwari, PhD, professor, in the Department of Biostatistics.
The team modeled percent methylation at individual CpGs as a function of fasting very low density lipoprotein cholesterol (VLDL-C) and triglycerides (TG), using mixed linear regression adjusted for age, gender, study site, cell purity, and family structure. Four CpGs (cg00574958, cg17058475, cg01082498, cg09737197) in intron 1 of carnitine palmitoyltransferase 1A (CPT1A) were strongly associated with VLDL-C. Array findings were validated by bisulfite sequencing. They performed qPCR experiments demonstrating that methylation of the top CpG (cg00574958) was correlated with CPT1A expression. The association of cg00574958 with TG and CPT1A expression was replicated in the Framingham Heart Study. DNA methylation at CPT1A cg00574958 explained 11.6 percent and 5.5 percent of the variation in TG in the discovery and replication cohorts, respectively.
The researchers concluded that this genome-wide epigenomic study identified CPT1A methylation as strongly and robustly associated with fasting VLDL-C and TG. Identifying novel epigenetic contributions to lipid traits may inform future efforts to identify new treatment targets and/or biomarkers of disease risk.