Investigating potential causal relationships between SNPs, DNA methylation and HDL

Area of Science:

• Genetics
• Epigenetics
• Cardiovascular Disease Research

Background:

• High-density lipoprotein (HDL) cholesterol levels are crucial cardiovascular risk factors.
• Epigenetic modifications, such as DNA methylation, may influence HDL metabolism.
• Understanding the causal relationship between methylation and HDL is essential for targeted interventions.

Purpose of the Study:

• To investigate the causal effect of DNA methylation at specific CpG sites on high-density lipoprotein (HDL) changes (ΔHDL).
• To evaluate a novel constrained instrumental variables (CIV) method for Mendelian randomization (MR) analysis, accounting for pleiotropy.
• To identify specific genes and CpG sites causally linked to HDL changes.

Main Methods:

• Mendelian randomization (MR) analysis using the GAW20 real data set (680 patients).
• Employed single-nucleotide polymorphisms (SNPs) as instrumental variables to assess causality.
• Compared the novel CIV method with Egger regression and two-stage least squares (TSLS) for estimating causal effects.

Main Results:

• The study identified causal relationships between specific CpG sites and ΔHDL.
• The novel CIV method, along with Egger regression and TSLS, implicated CpG sites in the genes *RNMT;C18orf19* and *C6orf141*.
• These findings suggest a potential role for DNA methylation in these genes in regulating HDL levels.

Conclusions:

• DNA methylation at specific CpG sites, particularly within *RNMT;C18orf19* and *C6orf141*, may have a causal impact on HDL levels.
• The constrained instrumental variables (CIV) method is a promising tool for MR studies involving potential pleiotropy.
• Further research can explore these methylation sites for novel therapeutic targets in cardiovascular disease.