Metabolic accompaniment of plasma lipoproteins profile in persons with maladaptation
DOI:
https://doi.org/10.12775/JEHS.2023.42.01.016Keywords
lipoprotein profile of plasma, atherogenic indexes, metabolic parameters, males, females, cluster analysisAbstract
Background. During the implementation of the project "The relationship between the lipoprotein profile of the blood plasma and the parameters of the neuroendocrine-immune complex, and the influence of the factors of the Truskavets’ spa on them", we first divided observed cohort into 5 homogeneous groups that differed from each other by 6 discriminant variables. The purpose of this study is to identify the metabolic accompaniment of plasma lipoprotein profile in the same persons.
Material and research methods. The object of observation were 41 volunteers: 20 women aged 30-76 years and 21 men aged 24-69 years without clinical diagnose but with dysfunction of neuroendocrine-immune complex and dysmetabolism. We estimated lipoprotein profile of plasma, determined the levels of the proinflammatory cytokines, parameters of lipid peroxidation as well as routine biochemical and paraclinical parameters.
Results. The patients with increased, normal and decreased levels of Dobiásová’s&Frohlich’s Atherogenic Index of Plasma (D&FAIP) are characterized, together with levels of Triglycerides and HDLP Cholesterol by definition, by specific constellations of levels of IL-6, IL-1, Diene conjugates, Malondialdehyde, Katalase, Glucose, and Alanine aminotransferase (classification accuracy is 98.8%). A close canonical correlation was found between the parameters of the plasma lipoprotein profile, on the one hand, and metabolism and erythroon, on the other (R=0.920).
Conclusion. Atherogenic, normal and anti-atherogenic blood plasma is characterized by specific levels of markers of inflammation, lipid peroxidation, cytolysis and erythroon.
References
Andreyeva LI, Kozhemyakin LA, Kishkun AA. Modification of the method for determining the lipid peroxide in the test with thiobarbituric acid [in Russian]. Laboratornoye Delo. 1988;11:41-43.
Barylyak LG, Tsymbryla VV, Zukow W, Popovych IL. Variants of plasma lipoprotein profile in persons with maladaptation. Journal of Education, Health and Sport. 2015;5(3):381-394. doi.org/10.12775/JEHS.2015.05.03.032
Barylyak LG, Tsymbryla VV, Zukow W, Popovych IL. Relationships between parameters of plasma lipoproteines profile and heart rate variability. Journal of Education, Health and Sport. 2019;9(12):238-253. doi.org/10.12775/JEHS.2019.09.12.025
Dobiásová M & Frohlich J. The plasma parameter log (TG/HDL-C) as an atherogenic index: correlation with lipoprotein particle size and esterification rate in apoB-lipoprotein-depleted plasma (FER(HDL)). Clin Biochem. 2001;34(7):583-588. doi:10.1016/s0009-9120(01)00263-6
Dobiásová M. AIP - aterogenní index plazmy jako významný prediktor kardiovaskulárního rizika: od výzkumu do praxe [AIP - atherogenic index of plasma as a significant predictor of cardiovascular risk: from research to practice]. Vnitr Lek. 2006;52(1):64-71. Czech. PMID: 16526201.
Dobiásová M, Frohlich J, Sedová M, Cheung MC, Brown BG. Cholesterol esterification and atherogenic index of plasma correlate with lipoprotein size and findings on coronary angiography. J Lipid Res. 2011;52(3):566-571. doi:10.1194/jlr.P011668.
Dubinina YY, Yefimova LF, Sofronova LN, Geronimus AL. Comparative analysis of the activity of superoxide dismutase and catalase of erythrocytes and whole blood from newborn children with chronic hypoxia [in Russian]. Laboratornoye Delo. 1988;8:16-19.
Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem. 1972;18(6):499-502. PMID: 4337382.
Ganjali S, Gotto AM Jr, Ruscica M, Atkin SL, Butler AE, Banach M, Sahebkar A. Monocyte-to-HDL-cholesterol ratio as a prognostic marker in cardiovascular diseases. J Cell Physiol. 2018;233(12):9237-9246. doi: 10.1002/jcp.27028.
Gavrilov VB, Mishkorudnaya MI. Spectrophotometric determination of plasma levels of lipid hydroperoxides [in Russian]. Laboratornoye Delo. 1983;3:33-36.
Goryachkovskiy AM. Clinical biochemistry [in Russian]. Odesa. Astroprint;1998:608.
Gozhenko АІ, Korda MM, Popadynets OO, Popovych IL. Entropy, Harmony, Synchronization and their Neuro-endocrine-immune Correlates [in Ukrainian]. Odesa. Feniks;2021:232.
Hiller G. Test for the quantitative determination of HDL cholesterol in EDTA plasma with Reflotron®. Klin Chem. 1987;33:895-898.
Kılıç N, Tasci G, Yılmaz S, Öner P, Korkmaz S. Monocyte/HDL Cholesterol Ratios as a New Inflammatory Marker in Patients with Schizophrenia. J Pers Med. 2023;13(2):276. doi: 10.3390/jpm13020276.
Khmelevskyi YV, Usatenko OK. Basic Biochemical Constants of Humans at Norm and at Pathology [in Russian]. Kyїv. Zdorovya;1987:160.
Klecka WR. Discriminant Analysis [trans. from English in Russian] (Seventh Printing, 1986). In: Factor, Discriminant and Cluster Analysis. Moskva:Finansy i Statistika;1989:78-138.
Klimov AN, Nikulcheva NG. Lipids, Lipoproteides and Atherosclerosis [in Russian]. St-Pb. Piter Pres;1995:304.
Korolyuk MA, Ivanova MI, Mayorova IG, Tokarev VYe. The method for determining the activity of catalase [in Russian]. Laboratornoye Delo. 1988;1:16-19.
Makarenko YeV. A comprehensive definition of the activity of superoxide dismutase and glutathione reductase in red blood cells in patients with chronic liver disease [in Russian]. Laboratornoye Delo. 1988;11:48-50.
Niroumand S, Khajedaluee M, Khadem-Rezaiyan M, Abrishami M, Juya M, Khodaee G, Dadgarmoghaddam M. Atherogenic Index of Plasma (AIP): A marker of cardiovascular disease. Med J Islam Repub Iran. 2015;29:240. PMID: 26793631; PMCID: PMC4715400.
Petreski T, Piko N, Ekart R, Hojs R, Bevc S. Review on Inflammation Markers in Chronic Kidney Disease. Biomedicines. 2021;9(2):182. doi: 10.3390/biomedicines9020182.
Polovynko IS, Zajats LM, Zukow W, Yanchij RI, Popovych IL. Quantitative evaluation of integrated neuroendocrine and immune responses to chronic stress in rat male. Journal of Education, Health and Sport. 2016;6(8):154-166. doi.org/10.5281/zenodo.60023
Popovych IL, Gozhenko AI, Korda MM, Klishch IM, Popovych DV, Zukow W (editors). Mineral Waters, Metabolism, Neuro-Endocrine-Immune Complex. Odesa. Feniks;2022:252.
Shannon CE. A mathematical theory of information. Bell Syst Tech J. 1948;27:379-423.
Zoubiri H, Tahar A, AitAbderrhmane S, Saidani M, Koceir EA. Oral Cholecalciferol Supplementation in Sahara Black People with Chronic Kidney Disease Modulates Cytokine Storm, Oxidative Stress Damage and Athero-Thromboembolic Risk. Nutrients. 2022;14(11):2285. doi: 10.3390/nu14112285.
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