Application of a new procedure for liquid chromatography/mass spectrometry profiling of plasma amino acid-related metabolites and untargeted shotgun proteomics to identify mechanisms and biomarkers of calcific aortic stenosis

Abstract

Calcific aortic valve stenosis (CAS) increasingly affects our ageing population, but the mechanisms of the disease and its biomarkers are not well established. Recently, plasma amino acid-related metabolite (AA) profiling has attracted attention in studies on pathology and development of biomarkers of cardiovascular diseases, but has not been studied in CAS. To evaluate the potential relationship between CAS and AA metabolome, a new ion-pairing reversed-phase liquid chromatography-tandem mass spectrometry (IP-RPLC-MS/MS) method has been developed and validated for simultaneous determination of 43 AAs in plasma of stenotic patients and age-matched control subjects. Furthermore, untargeted mass spectrometry-based proteomic analysis and confirmatory ELISA assays were performed. The method developed offered high accuracy (intra-assay imprecision averaged 4.4% for all compounds) and sensitivity (LOQ within 0.01-0.5μM). We found that 22 AAs and three AA ratios significantly changed in the CAS group as compared to control. The most pronounced differences were observed in urea cycle-related AAs and branched-chain AA (BCAA)-related AAs. The contents of asymmetric dimethylarginine (ADMA) and its monomethylated derivative (NMMA) were increased by 30-64% with CAS. The arginine/ADMA and Fischer's ratios as well as arginine, homoarginine, ADMA, symmetric dimethylarginine, hydroxyproline, betaine and 3-methylhistidine correlated with cardiac function-related parameters and concomitant systemic factors in the CAS patients. The results of proteomic analysis were consistent with involvement of inflammation, lipid abnormalities, hemostasis and extracellular matrix remodeling in CAS. In conclusion, changes in plasma AA profile and protein pattern that we identified in CAS provide information relevant to pathomechanisms and may deliver new biomarkers of the disease.

Keywords: Amino acid metabolome; Biomarkers; Calcific aortic valve stenosis; Clinical correlations; Mass spectrometry; Untargeted proteomics.