Epigenetic contributions to clinical risk prediction of cardiovascular disease

Abstract

Background and AimsCardiovascular disease (CVD) is among the leading causes of death worldwide. Therefore, it is important to identify CVD risk as early as possible and to translate this knowledge into effective preventative strategies. Here, ASSIGN – a cardiovascular risk calculator recommended for use in Scotland – was examined in tandem with epigenetic and proteomic features in risk prediction models in 12,790 participants in the Generation Scotland cohort.MethodsPreviously generated DNA methylation-derived epigenetic scores (EpiScores) for 109 protein levels were considered, in addition to both measured levels and an EpiScore for cardiac troponins. The associations between potentially informative multi-omic features and the disease status were examined using univariate Cox PH models (ncases=1,288). Splitting the cohort into independent training (n≥3,681) and test (n≥1,996) subsets composed of unrelated individuals, two composite scores were developed: CVD TroponinScore and CVD EpiScore.ResultsThere were 65 protein EpiScores that associated with incident CVD (ncases=1,288) independently of ASSIGN (PBonferroni<0.05), over a follow up of up to 15 years of electronic health record linkage. The CVD TroponinScore (based on the concentration of two cardiac troponins) and CVD EpiScore (based on 52 protein EpiScores) were both associated with CVD risk in Cox models in test sets (Hazard Ratio HR=1.28 and 1.23, P=5.9×10−4and 3.8×10−3, ntest=1,996 and 3,711, respectively).ConclusionsEpiScores for circulating protein levels have the potential to improve the prediction of CVD and be useful tools for precision medicine.Structured graphical abstractStructural graphical abstractCVD – Cardiovascular Disease, EpiScore – Epigenetic Score, Cox PH – Cox Proportional Hazards Regression, DNAm – DNA methylationStructured abstract textKey QuestionCan we augment CVD prediction beyond clinical risk scores?Key FindingNewly derived multi-omic scores (CVD TroponinScore and CVD EpiScore) were both associated with CVD risk in holdout test sets.Take-home MessageMulti-omic data have the potential to augment CVD risk prediction tools such as ASSIGN or SCORE2.

Data Resource Profile: Whole Blood DNA Methylation Resource in Generation Scotland (MeGS)

“…methylation data acquired as part of STRADL) was used to generate signatures for 17 protein markers of brain health [41]. Finally, Chybowska et al demonstrated the utility of methylation-derived EpiScores and composite measures of these scores to identify CVD risk, independent of traditional risk factors [42].…”

DNAm scores for serum GDF15 and NT-proBNP levels associate with a range of traits affecting the body and brain

“…DNAm-based epigenetic scores (EpiScores) for blood proteins have been found to serve as markers of incident diseases (16) and augment clinically-used risk factors for risk stratification (17,18). DNAm reflects the body’s chronic response to low-grade inflammation, environmental and biological exposures (19–21).…”

“…Both protein markers have also been found to associate with vascular brain injury, poorer neurocognitive performance and incident dementias (14,15). DNAm-based epigenetic scores (EpiScores) for blood proteins have been found to serve as markers of incident diseases (16) and augment clinically-used risk factors for risk stratification (17,18). DNAm reflects the body's chronic response to low-grade inflammation, environmental and biological exposures (19)(20)(21).…”