Conections between platelets amino acids profile and known cardiometabolic risk factors in patients with coronary artery disease and atrial fibrillation

Автор(и)

DOI:

https://doi.org/10.26641/2307-0404.2024.2.307572

Ключові слова:

coronary artery disease, atrial fibrillation, amino acids, blood platelets, cardiometabolic risk factors

Анотація

The aim of our work was to identify the relationship between platelet amino acid profile and cardiometabolic risk factors in patients with coronary heart disease and atrial fibrillation. 300 patients were examined, who were divided into 3 groups: the first (I) – 149 patients with coronary artery disease (CAD) and without arrhythmias, the second (II) – 123 patients with CAD and paroxysm of atrial fibrillation (AF) and the control group (CG) – 28 patients without CAD and arrhythmia. The platelets amino acid (AA) profile was determined by ion exchange liquid column chromatography. Cardiometabolic risk factors studied: total cholesterol (TC), triglycerides (TG), low-density lipoprotein (LDL), high-density lipoprotein (HDL), lipoprotein α (Lpα), apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB), C-reactive protein (CRP), interleukin-6 (IL-6), trimethylamine (TMA) and trimethylamine-N-oxide (TMAO). Significant increase of isoleucine (10.73%), leucine (12.63%) and decrease of threonine (23.05%), serine (5.06%), glycine (32.21%), valine (30.83%) levels in platelet AA profile was observed in patients with CAD and AF compared to patients with CAD without arrhythmias, p<0.05. Also, significant increase of apolipoprotein B (29.91%), CRP (40.93%), IL-6 (22.93%), TMA (16.13%) and TMAO (57.54%) and decrease of TMA/TMAO ratio (26.16%) was found in CAD with AF patients compared to CAD patients without arrhythmia, p<0.05. The highest number of correlations was found between platelets AA profile and TMA/TMAO ratio (total number =7), TC (total number =7) and fibrinogen levels (total number =6). In addition, most correlations were found between glycine (total =12), threonine (total =6), glutamate (total =6), valine (total =6), and cardiometabolic risk factors. The level of glycine in platelets is correlated with most cardiometabolic risk factors, such as: age (r=-0.305), BMI (r=-0.351), TC (r=-0.304), LDL (r=-0.348), ApoA1 (r=0.373 ), ApoB (r=-0.347), IL-6 (r=-0.315), TMAO (r=-0.654), TMA/TMAO ratio (r=0.688), prothrombin index (r=0.317), activated partial thromboplastin time (r=-0.365) and fibrinogen level (r=-0.396), p<0.05. So, in our work, the relationship between platelets AA profile and cardiometabolic risk factors in patients with CAD with AF was revealed. According to the results of the correlation analysis with known cardiometabolic risk factors, an important pathogenetic role of the glycine, threonine, valine and glutamate platelets levels in CAD and AF patients was revealed.

Посилання

Hindricks G, Potpara T, Dagres N, et al. ESC Guidelines for the diagnosis and management of atrial fibrillation developed in collaboration with the European Association for Cardio-Thoracic Surgery (EACTS). European Heart Journal. 2020;42:373498. doi: https://doi.org/10.1093/eurheartj/ehaa612

Knuuti J, Wijns W, Saraste A, et al. ESC Guide-lines for the diagnosis and management of chronic coronary syndromes. European Heart Journal. 2020;41:407477. doi: https://doi.org/10.1093/eurheartj/ehz425

Xu Y, Jiang H, Li L, Chen F, Liu Y, Zhou M, et al. Branched-Chain Amino Acid Catabolism Promotes Thrombosis Risk by Enhancing Tropomodulin-3 Pro-pionylation in Platelets. Circulation. 2020;142(1):49-64. doi: https://doi.org/10.1161/CIRCULATIONAHA.119.043581

Biswas S, Hilser JR, Woodward NC, Wang Z, Gukasyan J, Nemet I, et al. Effect of Genetic and Dietary Perturbation of Glycine Metabolism on Atherosclerosis in Humans and Mice. medRxiv [Preprint]. 2023 Dec 11:2023.12.08.23299748. doi: https://doi.org/10.1101/2023.12.08.23299748

Roşca AE, Vlădăreanu AM, Mirica R, Anghel-Timaru CM, Mititelu A, Popescu BO, et al. Taurine and Its Derivatives: Analysis of the Inhibitory Effect on Platelet Function and Their Antithrombotic Potential. Journal of clinical medicine. 2022;11(3):666. doi: https://doi.org/10.3390/jcm11030666

Chen D, Zhao X, Sui Z, Niu H, Chen L, Hu C, et al. A multi-omics investigation of the molecular characteristics and classification of six metabolic syndrome relevant diseases. Theranostics. 2020;10(5):2029-46. doi: https://doi.org/10.7150/thno.41106

Li JJ, Liu HH, Li S. Landscape of cardiometabolic risk factors in Chinese population: a narrative review. Cardiovascular diabetology. 2022;21(1):113. doi: https://doi.org/10.1186/s12933-022-01551-3

Schmidt AF, Joshi R, Gordillo-Marañón M, Dre-nos F, Charoen P, Giambartolomei C, et al. Biomedical consequences of elevated cholesterol-containing lipopro-teins and apolipoproteins on cardiovascular and non-cardiovascular outcomes. Communications medicine. 2023;3(1):9. doi: https://doi.org/10.1038/s43856-022-00234-0

Kamstrup PR. Lipoprotein(a) and Cardiovascular Disease. Clinical chemistry. 2021;67(1):154-66. doi: https://doi.org/10.1093/clinchem/hvaa247

Lizogub VG, Kramarova VN, Melnychuk IO. The role of gut microbiota changes in the pathogenesis of heart disease. Zaporozhye medical journal. 2019;21,5 (116):672-8. doi: https://doi.org/10.14739/2310-1210.2019.5.179462

Carling RS, McDonald BA, Austin D, Burden D, Correia J, Leung J, et al. Challenging the status quo: A comparison of ion exchange chromatography with liquid chromatography-mass spectrometry and liquid chroma-tography-tandem mass spectrometry methods for the measurement of amino acids in human plasma. Annals of clinical biochemistry. 2020;57(4):277-90. doi: https://doi.org/10.1177/0004563220933303

Montante S, Brinkman RR. Flow cytometry data analysis: Recent tools and algorithms. International journal of laboratory hematology. 2019;41(Suppl 1):56-62. doi: https://doi.org/10.1111/ijlh.13016

Tabatabaei MS, Ahmed M. Enzyme-Linked Immu¬nosorbent Assay (ELISA). Methods in molecular biology. 2022;2508:115-34. doi: https://doi.org/10.1007/978-1-0716-2376-3_10

Faizi N, Alvi Y. Biostatistics Manual for Health Research. A Practical Guide to Data Analysis. 1st ed. Elsevier; 2023.

Jiang H, Zhang L, Yang M, Li G, Ding C, Xin M, et al. Branched-chain amino acids promote thrombo-cytopoiesis by activating mTOR signaling. Journal of thrombosis and haemostasis: JTH. 2023 Nov;21(11):3224-3235. doi: https://doi.org/10.1016/j.jtha.2023.06.039

Bishop CA, Schulze MB, Klaus S, Weitkunat K. The branched-chain amino acids valine and leucine have differential effects on hepatic lipid metabolism. FASEB journal: official publication of the Federation of American Societies for Experimental Biology. 2020;34(7):9727-39. doi: https://doi.org/10.1096/fj.202000195R

Wu T, Wang M, Ning F, Zhou S, Hu X, Xin H, et al. Emerging role for branched-chain amino acids meta¬bolism in fibrosis. Pharmacological research. 2023;187:106604. doi: https://doi.org/10.1016/j.phrs.2022.106604

Tang Q, Tan P, Ma N, Ma X. Physiological Functions of Threonine in Animals: Beyond Nutrition Metabolism. Nutrients. 2021;13(8):2592. doi: https://doi.org/10.3390/nu13082592

Yang H, Zhang C, Turkez H, Uhlen M, Boren J, Mardinoglu A. Revisiting the role of serine metabolism in hepatic lipogenesis. Nature metabolism. 2023;5(5):760-1. doi: https://doi.org/10.1038/s42255-023-00792-0

Li DH, Wu Q, Lan JS, Chen S, Huang YY, Wu LJ, et al. Plasma metabolites and risk of myocardial infarction: a bidirectional Mendelian randomization study. Journal of geriatric cardiology: JGC. 2024;21(2):219-31. doi: https://doi.org/10.26599/1671-5411.2024.02.002

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Опубліковано

2024-06-28

Як цитувати

1.
Melnychuk I. Conections between platelets amino acids profile and known cardiometabolic risk factors in patients with coronary artery disease and atrial fibrillation. Med. perspekt. [інтернет]. 28, Червень 2024 [цит. за 21, Грудень 2024];29(2):72-9. доступний у: https://journals.uran.ua/index.php/2307-0404/article/view/307572

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