Abstract
BackgroundIncidence rates of cardiovascular disease (CVD) are increasing, partly driven by the diabetes epidemic. Novel prediction tools and modifiable treatment targets are needed to enhance risk assessment and management. Plasma metabolite associations with subclinical atherosclerosis were investigated in the Diabetes Heart Study (DHS), a cohort enriched for type 2 diabetes (T2D).MethodsThe analysis included 700 DHS participants, 438 African Americans (AAs), and 262 European Americans (EAs), in whom coronary artery calcium (CAC) was assessed using ECG-gated computed tomography. Plasma metabolomics using liquid chromatography-mass spectrometry identified 853 known metabolites. An ancestry-specific marginal model incorporating generalized estimating equations examined associations between metabolites and CAC (log-transformed (CAC + 1) as outcome measure). Models were adjusted for age, sex, BMI, diabetes duration, date of plasma collection, time between plasma collection and CT exam, low-density lipoprotein cholesterol (LDL-C), and statin use.ResultsAt an FDR-corrected p-value < 0.05, 33 metabolites were associated with CAC in AAs and 36 in EAs. The androgenic steroids, fatty acid, phosphatidylcholine, and bile acid metabolism subpathways were associated with CAC in AAs, whereas fatty acid, lysoplasmalogen, and branched-chain amino acid (BCAA) subpathways were associated with CAC in EAs.ConclusionsStrikingly different metabolic signatures were associated with subclinical coronary atherosclerosis in AA and EA DHS participants.
Highlights
Incidence rates of cardiovascular disease (CVD) are increasing, partly driven by the diabetes epidemic
Given the dearth of evidence and the profound metabolic changes associated with diabetes, we aimed to identify metabolic pathways associated with subclinical atherosclerosis in individuals with type 2 diabetes (T2D) using targeted plasma metabolomic profiling
This study investigated the metabolomic profile of a high-risk population with longstanding T2D and assessed ancestry-specific associations with subclinical atherosclerosis
Summary
Incidence rates of cardiovascular disease (CVD) are increasing, partly driven by the diabetes epidemic. The burden of coronary artery atherosclerosis effectively predicts CVD events. Quantification of coronary artery calcium (CAC) with electrocardiographic gated computed tomography is a non-invasive method for determining subclinical atherosclerosis and is widely recommended for risk assessment [6,7,8,9]. The prevalence and severity of CAC vary based on ancestry, significant associations exist between CAC and CVD mortality irrespective of race/ethnicity in the CAC Consortium. These data include the largest racially heterogeneous cohort of CAC scores assembled [10]. CAC predicts CVD and all-cause mortality in individuals with diabetes [11]
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