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. 2023 Aug 25;42(3):427-436.
doi: 10.5937/jomb0-39636.

Principal component analysis of the oxidative stress, inflammation, and dyslipidemia influence in patients with different levels of glucoregulation

Maja Malenica  1 , Aleksandra Klisić  2 , Neven Meseldžić  1 , Tanja Dujić  1 , Tamer Bego  1 , Jelena Kotur-Stevuljević  3
Affiliations

Principal component analysis of the oxidative stress, inflammation, and dyslipidemia influence in patients with different levels of glucoregulation

Maja Malenica et al. J Med Biochem. .

Abstract
in English, Serbian

Background: The aim of the study was to explore the mutual relationship between oxidative stress, inflammation and metabolic biomarkers in subjects with prediabetes (PRE), newly diagnosed type 2 diabetes patients (NT2D) and overt type 2 diabetes (T2D) using principal component analysis (PCA) as a thorough statistical approach.

Methods: Glycated hemoglobin, lipid parameters, inflammation (IL-6, CRP and fibrinogen) and oxidative stress markers pro-oxidants (AOPP, PAB, TOS) and antioxidants (PON1, tSHG, TAS) were measured. PCA was applied to explore the factors that the most strongly influenced glucoregulation.

Results: A total of 278 subjects were (i.e., 37 PRE, 42 NT2D and 99 T2D) were compared with 100 healthy subjects as a control group (CG). PCA emphasized 4 different factors explaining 49% of the variance of the tested parameters: oxidative stress-dyslipidemia related factor (with positive loading of TG and tSHG, and with negative loading of HDL-c and TAS), dyslipidaemia related factor (i.e., total cholesterol and LDL-c, both with positive loading), Anthropometric related factor (i.e., waist and hip circumference, both with positive loading) and oxidative stressInflammation related factor (i.e., PAB, fibrinogen, and CRP all with positive loading). Out of these 4 factors, only oxidative stress - dyslipidaemia related factor showed a significant predictive capability towards poor glucoregulation. An increase in this factor by one unit showed a 1.6 times higher probability for poor glucoregulation.

Conclusions: Redox imbalance (determined with lower TAS and higher tSHG), in addition to higher TG and lower HDLc was associated with poor glucoregulation.

Uvod: Cilj istraživanja je bio da se ispita povezanost oksidativnog stresa, inflamacije i metaboličkih biomarkera kod pacijenata sa predijabetesom (PRE), de novo dijabetesom (NT2D) i ranije dijagnostikovanim dijabetesom (T2D) pomoću glavne komponentne analize (PCA).

Metode: Glikozilirani hemoglobin, lipidni status, markeri inflamacije (IL-6, CRP i fibrinogen), parametri oksidativnog stresa pro-oksidanti (AOPP, PAB, TOS) i antioksidansi (PON1, tSHG, TAS) su mereni. PCA je primenjena da bi se ispitali faktori koji najviše utiču na glikoregulaciju.

Rezultati: U istraživanje je uključeno 278 ispitanika: 37 PRE, 42 NT2D i 99 T2D, kao i 100 zdravih osoba koji su činili kontrolnu grupu (CG). PCA je izdvojila 4 različita faktora objašnjavajući 49% varijanse ispitivanih parametara: oksidativni stres-dislipidemija faktor (sa pozitivnim uticajem TG i tSHG, i negativnim uticajem HDL-c i TAS), dislipidemija faktor (tj, ukupni holesterol i LDL-c, oba sa pozitivnim uticajem), antropometrijski faktor (tj, obim struka i kukova, oba sa pozitivnim uticajem) i oksidativni stres-inflamacija faktor (tj, PAB, fibrinogen i CRP, svi sa pozitivnim uticajem). Od ova 4 faktora, jedino je oksidativni stres - dislipidemija faktor pokazao značajnu prediktivnu sposobnost za lošu glikoregulaciju. Porast ovog faktora za jednu jedinicu je pokazao 1,6 puta veću verovatnoću za lošu glikoregulaciju.

Zaključak: Redoks disbalans (određen nižim vrednostima TAS i višim vrednostima tSHG), kao dodatak većim vrednostima TG i nižim vrednostima HDL-c su povezane sa lošijom glikoregulacijom.

Keywords: antioxidants; dyslipidemia; glycemic control; inflammation; prooxidants.

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Conflict of interest statement

All the authors declare that they have no conflict of interest in this work.Conflict of Interest: The authors stated that they have no conflicts of interest regarding the publication of this article.

Figures

Figure 1
Figure 1. The values of ANTIOX, PROOX and OXY score in examined groups.
P- Kruskal-Wallis test; aaa p<0.001 vs. CG; b, bb, bbb P<0.05, 0.01, 0.001, respectively vs. PRE; c, cc, ccc P<0.05, 0.01, 0.001, respectively vs. NT2D. CG-Control group; PRE-Prediabetic patients; NT2D-Newly diagnosed type 2 diabetic patients; T2D-Type 2 diabetic patients.
See this image and copyright information in PMC

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