Key result
Clustering CVD risk factors is linked to distinct urinary amino acid and acylcarnitine metabolite dysregulation.
Observational (n=1,202)
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AIM: Risk factors contributes to a dysregulated metabolism and may ultimately increase the predisposition for cardiovascular disease (CVD) development. To increase our understanding of mechanistic pathways associated with CVD risk, we profiled the urinary metabolome according to individual and clusters of CVD risk factors in comparison with a control group without any risk factors. METHODS AND RESULTS: Healthy black and white women and men ( N = 1202), aged 20-30 years with a detailed CVD risk factor profile were included. CVD risk groups: obese, physical inactive, smoking, excessive alcohol intake, masked hypertensive, hyperglycaemic, dyslipidemic and low socioeconomic status. CVD risk clusters were based on the presence of 1, 2 and 3 or more risk factors. Liquid chromatography-tandem mass spectrometry was used to obtain urinary metabolomics data (amino acids and acylcarnities). Compared with the control group, higher levels of metabolites associated with aromatic and branched chain amino acid metabolism including phenylalanine, tyrosine and leucine/isoleucine were found in the obese, masked hypertensive, hyperglycaemic, low socioeconomic groups (all q ≤ 0.032) and 3+ CVD risk cluster (all P ≤ 0.034). Metabolites associated with the y-glutamyl cycle including glycine, histidine, serine, glutamine, methionine, cystine and pyroglutamic acid were found in the hyperglycaemic, low socioeconomic groups (all q ≤ 0.050), 2 and 3+ CVD risk clusters (all P ≤ 0.041). Metabolites associated with energetics including acetylcarnitine (lower levels), hexanoylcarnitine and decanoylcarnitine were found in the low socioeconomic group, 1 and 3+ CVD risk clusters ( q / P ≤ 0.050) ( β -oxidation). In addition to the above-mentioned amino acids, alanine and threonine were found in the hyperglycaemic, low socioeconomic groups, 2 and 3+ CVD risk clusters (all q / P ≤ 0.047) (glycolysis). Creatine in the obese, hyperglycaemic groups (all q ≤ 0.049) and 3+ CVD risk cluster (all P ≤ 0.041) (creatine pathway). CONCLUSION: Exposure to CVD risk factors is associated with a dysregulated metabolism in the above-mentioned pathways that may precede the development of CVD.
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Toit et al. (2022) conducted an observational in Cardiovascular disease risk factors (n=1,202). Cardiovascular disease risk factors and risk clusters (1, 2, and 3+ risk factors) vs. Control group without any cardiovascular disease risk factors was evaluated on Urinary metabolomics profile (amino acids and acylcarnitines) (p=≤0.034). Exposure to CVD risk factors and 3+ risk clusters was associated with dysregulated urinary amino acid, γ-glutamyl, and acylcarnitine metabolites vs controls (all q/P ≤ 0.050).
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