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Published on: September 20, 2024
Epigenetic Contributions to Clinical Risk Prediction of Cardiovascular Disease
Aleksandra D Chybowska1, Danni A Gadd1, Yipeng Cheng1
1Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer (A.D.C., D.A.G., Y.C., E.B., A.C., D.L.M., K.L.E., R.E.M.), The University of Edinburgh, United Kingdom.
Insights
New epigenetic scores (EpiScores) for protein levels show promise in predicting cardiovascular disease (CVD) risk. These novel biomarkers may enhance current risk assessment tools and deepen our understanding of CVD development.
Area of Science:
- Genomics and Proteomics
- Biomarker Discovery
- Cardiovascular Disease Research
Background:
- Cardiovascular disease (CVD) remains a leading global cause of mortality.
- Advancements in omics biomarkers are crucial for improving CVD risk stratification and understanding disease mechanisms.
- The study evaluated the ASSIGN cardiovascular risk prediction tool alongside epigenetic and proteomic data in a large cohort.
Purpose of the Study:
- To investigate the utility of DNA methylation-derived epigenetic scores (EpiScores) for protein levels in predicting cardiovascular disease (CVD) risk.
- To assess whether these EpiScores offer added value beyond existing risk prediction tools like ASSIGN and cardiac troponin I (cTnI) levels.
- To develop a composite CVD EpiScore for enhanced risk prediction.
Main Methods:
- Utilized previously generated EpiScores for 109 proteins and measured levels, plus an EpiScore for cTnI.
- Employed Cox regression analysis to examine associations between protein EpiScores and CVD risk in a large cohort (n_cases ≥1274; n_controls ≥11,383).
- Developed a composite CVD EpiScore using independent training and testing subsets of the Generation Scotland cohort.
Main Results:
- Sixty-five protein EpiScores were independently associated with incident CVD over 16 years of follow-up (P<0.05).
- Key associated proteins were involved in metabolic, immune response, and tissue development/regeneration pathways.
- A composite CVD EpiScore, derived from 45 protein EpiScores, significantly predicted CVD risk independently of ASSIGN and cTnI (HR, 1.32; P=3.7×10⁻³), improving the C-statistic by 0.3%.
Conclusions:
- EpiScores for circulating proteins are associated with CVD risk, independent of traditional risk factors.
- These protein-based EpiScores may offer new insights into the underlying etiology of cardiovascular disease.
- The findings suggest that EpiScores could be valuable additions to CVD risk assessment strategies.
Background:
Cardiovascular disease (CVD) is among the leading causes of death worldwide. The discovery of new omics biomarkers could help to improve risk stratification algorithms and expand our understanding of molecular pathways contributing to the disease. Here, ASSIGN-a cardiovascular risk prediction tool recommended for use in Scotland-was examined in tandem with epigenetic and proteomic features in risk prediction models in ≥12 657 participants from the Generation Scotland cohort.
Methods:
Previously generated DNA methylation-derived epigenetic scores (EpiScores) for 109 protein levels were considered, in addition to both measured levels and an EpiScore for cTnI (cardiac troponin I). The associations between individual protein EpiScores and the CVD risk were examined using Cox regression (ncases≥1274; ncontrols≥11 383) and visualized in a tailored R application. Splitting the cohort into independent training (n=6880) and test (n=3659) subsets, a composite CVD EpiScore was then developed.
Results:
Sixty-five protein EpiScores were associated with incident CVD independently of ASSIGN and the measured concentration of cTnI (P<0.05), over a follow-up of up to 16 years of electronic health record linkage. The most significant EpiScores were for proteins involved in metabolic, immune response, and tissue development/regeneration pathways. A composite CVD EpiScore (based on 45 protein EpiScores) was a significant predictor of CVD risk independent of ASSIGN and the concentration of cTnI (hazard ratio, 1.32; P=3.7×10-3; 0.3% increase in C-statistic).
Conclusions:
EpiScores for circulating protein levels are associated with CVD risk independent of traditional risk factors and may increase our understanding of the etiology of the disease.
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