Metabolomic Profiles, Ideal Cardiovascular Health, and Risk of Heart Failure and Atrial Fibrillation: Insights From the Framingham Heart Study

Abstract

Background The American Heart Association's framework "ideal cardiovascular health" (CVH) focuses on modifiable risk factors to reduce cardiovascular disease (CVD). Metabolomics provides important pathobiological insights into risk factors and CVD development. We hypothesized that metabolomic signatures associate with CVH status, and that metabolites, at least partially, mediate the association of CVH score with atrial fibrillation (AF) and heart failure (HF). Methods and Results We studied 3056 adults in the FHS (Framingham Heart Study) cohort to evaluate CVH score and incident outcomes of AF and HF. Metabolomics data were available in 2059 participants; mediation analysis was performed to evaluate the mediation of metabolites in the association of CVH score and incident AF and HF. In the smaller cohort (mean age, 54 years; 53% women), CVH score was associated with 144 metabolites, with 64 metabolites shared across key cardiometabolic components (body mass index, blood pressure, and fasting blood glucose) of the CVH score. In mediation analyses, 3 metabolites (glycerol, cholesterol ester 16:1, and phosphatidylcholine 32:1) mediated the association of CVH score with incident AF. Seven metabolites (glycerol, isocitrate, asparagine, glutamine, indole-3-proprionate, phosphatidylcholine C36:4, and lysophosphatidylcholine 18:2), partly mediated the association between CVH score and incident HF in multivariable-adjusted models. Conclusions Most metabolites that associated with CVH score were shared the most among 3 cardiometabolic components. Three main pathways: (1) alanine, glutamine, and glutamate metabolism; (2) citric acid cycle metabolism; and (3) glycerolipid metabolism mediated CVH score with HF. Metabolomics provides insights into how ideal CVH status contributes to the development of AF and HF.

Keywords: CVH score; atrial fibrillation; heart failure; mediation analysis; metabolomics.

Figure 1. Cohort flow diagram and sample sizes for cardiovascular health score and metabolite analyses.

In FHS (Framingham Heart Study), 3799 Generation 2 participants completed Exam 5. A total of 743 participants were excluded because of missing data related to cardiovascular health metrics, presence of prevalent atrial fibrillation or heart failure, or without follow‐up time. A total of 3056 participants were included in the cardiovascular health score and incident atrial fibrillation and heart failure Cox regression models (sample 1). An additional 997 individuals did not have metabolomic data available and were excluded from the metabolomics analysis; 2059 were ultimately used for statistical analyses with metabolomic data (sample 2). AF indicates atrial fibrillation; CVH, cardiovascular health; and HF, heart failure.

Figure 2. Statistical approach with a path diagram of the mediation analysis.

One‐way regression models were used to evaluate the relation between cardiovascular health score (predictor) and incident atrial fibrillation or heart failure (outcomes) (A); cardiovascular health score and metabolite (B); and metabolites and incident atrial fibrillation and heart failure (C). Significant variables in all 3 steps for each of the outcomes were then used in mediation analysis to determine whether the metabolite mediates the association between cardiovascular health score and incident atrial fibrillation or heart failure. AF indicates atrial fibrillation; CVH, cardiovascular health; and HF, heart failure.

Figure 3. Number of ideal cardiometabolic cardiovascular health components and proportion of atrial fibrillation and heart failure events.

Participants with a greater number of ideal cardiometabolic components (cardiometabolic cardiovascular health components defined using blood pressure, obesity, and fasting blood glucose metrics) was associated with a lower proportion of incident atrial fibrillation and heart failure events. AF indicates atrial fibrillation; CVH, cardiovascular health; and HF, heart failure.

Figure 4. Overlap of metabolites associated with cardiovascular health (CVH) score and cardiometabolic CVH components.

Of the 144 metabolites associated with the CVH score in multivariate models (false discovery rate adjusted P value ≤0.05), 64 metabolites were shared across the cardiometabolic components of the CVH score (body mass index, blood pressure, and fasting blood glucose) and composite CVH score (A). Pathway analysis of the 23 non‐lipid metabolites (of the 64 shared metabolites of the CVH score and cardiometabolic components) indicate that the glucose‐alanine, alanine, and lactose degradation pathways are enriched (B). Of the 64 shared metabolites between the CVH score and ideal cardiometabolic components (body mass index, blood pressure, fasting blood glucose), 23 were non‐lipid metabolites and 41 were lipid metabolites (cholesterol ester, diacylglycerol, lysophosphatidylcholine, phosphatidylcholine, triacylglycerol) (C). BMI indicates body mass index; BP, blood pressure; CVH, cardiovascular health; FBG, fasting blood glucose; and FDR, false discovery rate.

Figure 5. Metabolomic profile of incident atrial fibrillation, incident heart failure, and heart failure subtypes.

A series of volcano plots (A through D) depicting significant metabolites with atrial fibrillation, heart failure, and heart failure subtypes. Orange indicates significant lipid metabolites; green indicates significant non‐lipid metabolites. All analyses are age‐, sex‐, and estimated glomerular filtration rate‐adjusted models using a significance of 5% false discovery rate level. HFrEF indicates heart failure with reduced ejection fraction; and HFpEF, heart failure with preserved ejection fraction.