Plasma metabolomic profiling in subclinical atherosclerosis: the Diabetes Heart Study

Cardiovascular Diabetology

Megan E. Rudock¹  Nicholette D. Palmer¹  Jianzhao Xu¹  Fang-Chi Hsu²  Michael D. Shapiro³  Parag Anilkumar Chevli⁴  John S. Parks⁵  Barry I. Freedman⁶  Lijun Ma⁶ 

[1] Department of Biochemistry, Wake Forest School of Medicine, 1 Medical Center Blvd, 27157, Winston-Salem, NC, USA;Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA;Section of Cardiovascular Medicine, Center for Preventive Cardiology, Wake Forest School of Medicine, 1 Medical Center Blvd, 27157, Winston-Salem, NC, USA;Section on Hospital Medicine, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA;Section on Molecular Medicine, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA;Section on Nephrology, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA;

关键词: Diabetes mellitus;    Cardiovascular disease;    Coronary artery calcium;    Metabolomics;    African Americans;    European Americans;   

DOI  :  10.1186/s12933-021-01419-y

来源: Springer

【 摘 要 】

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.

【 授权许可】

CC BY