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February 21, 2026Journal of Atherosclerosis and Thrombosis0 citationsOpen Access

Simultaneous Assessment of Genetic and Epigenetic Contributions to the Plasma Lipid Levels with Respect to Cardiovascular Risk

FTFumihiko TakeuchiMYMasaya YamamotoSSSeiko Shimizu

Key Result

Composite model combining polygenic risk score, rare variant data, and methylation risk score improved correlation with plasma LDL-C levels to r=0.272 compared to PRS plus rare variants alone with r=0.263 in Japanese adults with high LDL-C or CAD.

Key Points

  • The aim is to assess how genetic and epigenetic factors contribute to plasma lipid levels and cardiovascular risk.
  • Simultaneous assessment of genetic factors and DNA methylation levels
  • Evaluation of plasma lipid levels in relation to cardiovascular risk
  • Proof-of-concept established for the relationship between genetic predisposition and plasma lipid levels
  • Highlighting the role of DNA methylation in dyslipidemia treatment

Study Design

Type

Observational (n=775)

Multicenter

Yes

Structured PICO

Does a combined genetic (PRS and rare variants) and epigenetic (MRS) risk model improve the prediction of plasma lipid levels compared to genetic risk alone in Japanese adults?

P
Population
4,576 adults of Japanese descent, including individuals with high LDL-C (N=296), coronary artery disease (CAD) (N=315), non-CAD individuals (N=164), and reference individuals (max N=3,801).
I
Intervention
Composite risk prediction model incorporating Polygenic Risk Score (PRS), rare familial hypercholesterolemia (FH)-related gene variants, and Methylation Risk Score (MRS) based on 17 CpG sites
C
Comparator
Conventional genetic risk prediction using Polygenic Risk Score (PRS) alone
O
Outcome
Correlation between predicted and measured plasma lipid levels (LDL-C, HDL-C, triglycerides)surrogate

Combining polygenic risk scores, rare variant analysis, and DNA methylation profiling significantly improves the prediction of plasma LDL-C levels compared to genetic risk scores alone.

Main Result

Effect estimate: r = 0.272 for composite model with PRS, rare variants, and MRS LDL-C

Absolute Event Rate: 0.272% vs 0.263%

p-value: p=3.7×10^-12

Limitations

  • Observational design limits causal inference
  • Sample size relatively modest for genetic studies (~775)
  • Cross-sectional measurements limit understanding of longitudinal changes
  • Methylation risk score based on 17 CpG sites whose optimal selection method is still undefined
  • Potential confounding from statin therapy and lifestyle factors not fully accounted for
  • Study population limited to Japanese individuals, limiting generalizability
  • Insufficient sample size in decile classes
  • Relative impact of other coronary risk factors (e.g., smoking history) on CAD not fully accounted for
  • No formal sample size calculations were performed

Abstract

Our results provide a proof-of-concept that assesses the relative contribution of genetic predisposition and DNA methylation levels, which may help individuals refine their dyslipidemia treatment.

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Cite This Study

Takeuchi et al. (2026) conducted an observational in Adult Japanese patients including high LDL-C subjects without coronary artery disease and subjects with coronary artery disease (n=775). Composite genetic risk model incorporating polygenic risk score (PRS) for LDL-C, rare variant genetic risk, and methylation risk score (MRS) vs. Models using PRS alone or PRS plus rare variants without MRS was evaluated on Correlation between predicted and measured LDL-C plasma levels (r = 0.272 for composite model with PRS, rare variants, and MRS LDL-C, p=3.7×10^-12). Composite model combining polygenic risk score, rare variant data, and methylation risk score improved correlation with plasma LDL-C levels to r=0.272 compared to PRS plus rare variants alone with r=0.263 in Japanese adults with high LDL-C or CAD.

synapsesocial.com/papers/69994ba9873532290d01fc95https://doi.org/10.5551/jat.66000
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