The relationship of selected biomarkers of gut microbiotadysbiosis with adiposity and metabolic risk factors in nascentmetabolic syndrome patients
Main Article Content
Keywords
Microbiome Dysbiosis Signature Determinants: Carnitine; Choline; γButyrobetaine; TMAO; Zonulin; Survivin; LECT2, Antioxidative Stressors: CATALASE; SOD %Inhibition; Trolox Equivalent Total Antioxidant Capacity, Adiposity, Surrogate (Non Insulin Based) Insulin Resistance and Atherogenecity Indices, Cardiometabolic risk factors of nascent metabolic syndrome and prediabetes
Abstract
Background: This study aimed to compare and correlate between non-diabetic MetS, newly diagnosed drug naive pre-diabetic MetS patients vs. lean, apparently healthy and normoglycemic controls the plasma levels of cardiometabolic risk biomarkers’ of pharmacotherapy (appraised using colorimetric and chromatography assays of gut dysbiosis carnitine, choline, γbutyrobetaine, TMAO, Zonulin, survivin, Leukocyte cell-derived chemotaxin 2 (LECT2) and antioxidative stressors (catalase, superoxide dismutase (SOD) and Trolox total antioxidative capacity), adiposity, and atherogenicity with non-insulin based surrogate insulin resistance (sIR) indices. Methods: ANOVA comparisons and Spearman’s rank correlations were conducted in this cross-sectional study of 30 normoglycemic lean subjects (control), 30 nonprediabetic MetS subjects and 30 MetS/pre-diabetic (PreDM) enrolled. Results: MetS-PreDM group presented significantly higher values of FPG (P2<0.001,P3 =0.009) and A1C (P values <0.001) than both normoglycemic MetS and control groups. However, MetS-PreDM and normoglycemic MetS recruits had appreciably higher values of DBP, SBP, TG, and non-HDL-C but significantly lower values of HDL-C (P values <0.001) than the controls. Explicitly no significance in variance was noticeable among any of the study arms (P value < 0.05) for any of the hematological indices. Nevertheless, Both MetS groups (nonprediabetic and PreDM) had substantially higher values for each of adiposity, atherogenecity and surrogate insulin resistance (non insulin based) indices (P2<0.001) vs. controls’ respectively. Both Survivin and LECT2 levels were significantly higher in PreDM MetS group (P value < 0.05 vs. nondiabetic MetS participants). Conversely all 5 gut dysbiosis biomarkers (carnitinine, choline, γBB, TMAo and Zonulin) which proved significantly lower vs. those of either controls (nondiabetic lean or MetS). Surprisingly, a significant variation in all tested 7 biomarkers’ plasma levels were found between nondiabetic MetS and PreDM-MetS groups (P3 < 0.05). Interestingly all 3 antioxidative stressors were on the decline as anticipated; where catalase, SOD % inhibitions and trolox total antioxidative capacities were significantly lower in both MetS recruits vs. controls. Importantly the discrepancy between normoglycemic nonprediabetic MetS vs. the MetS-PreDM (P3 < 0.05) may have not ranked up to significance in indices, clinical parameters or biomarkers. Notably in pooled MetS (both normoglycemic and pre-diabetics participants (N =60)). Most exquisitely survivin with dysbiosis choline and γBB correlated positively and pronouncedly with carnitine in pooled MetS participants. Also in a striking similarity, cardiometabolic LECT2 has a marked direct relation with each of dyasbiosis carnitine and γBB. TMAO, nevertheless, related inversely and significantly with all 3 dysbiosis biomarkers, likewise Zonulin associated disproportionally with both choline and γBB. Exceptionally TMAO- TYG and Zonulin-TYG-WHpR paired in substantial and inverse relations in pooled normoglycemic and preDM MetS participants (n=60). To superbly signify the anticipated deterioration in metabolism via gut microbiota-insulin insensitivity interconnectivity; all dysbiosis biomarkers (carnitine, choline, γBB, TMAO, Zonulin and survivin) correlated highly remarkably and proportionally with all non insulin based surrogate insulin resistance indices in 60 MetS recruits (both normoglycemic and prediabetic; equally). Unequivocally γBB associated directly and pronouncedly with almost all adiposity indices. Surprisingly VAI correlated negatively with Zonulin in the same MetS population. FBG associated exceptionally with carnitine and γButyrobetaine (γBB). Substantially A1c correlated proportionally (P values <0.05) with MetS pooled cases dysbiosis’ carnitine, choline, γBB, and cardiometabolic surviving. Outstandingly both SBP and DBP had direct and marked linkage to LECT2 and so did DBP with choline’s plasma levels. Remarkably TMAO related negatively and pronouncedly with MetS cases levels of FBG, A1c, TG, LDL-C, and so did also zonulin with both A1c and LDL-C. Conclusions: Given the intergroup discrepancies in dysbiosis and cardiometabolic biomarkers along with their elective correlations with MetS-related indices and clinical parameters; our study cannot rule out any potentiality in molecular crosstalk and interplay of those biomarekers with the pathophysiology of MetS and preDM with their related dysregularities. Carnitine, choline, γbutyrobetaine, TMAO, Zonulin, survivin, and LECT2 can be putatively surrogate biomarkers to use as prognostic/predictive tools for the diagnosis/prevention and potential targets for MetS treatment.
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The relationship of selected biomarkers of gut microbiotadysbiosis with adiposity and metabolic risk factors in nascentmetabolic syndrome patients. Pharm Pract (Granada) [Internet]. 2024 Aug. 20 [cited 2024 Oct. 7];22(3):1-17. Available from: https://pharmacypractice.org/index.php/pp/article/view/3017
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How to Cite
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The relationship of selected biomarkers of gut microbiotadysbiosis with adiposity and metabolic risk factors in nascentmetabolic syndrome patients. Pharm Pract (Granada) [Internet]. 2024 Aug. 20 [cited 2024 Oct. 7];22(3):1-17. Available from: https://pharmacypractice.org/index.php/pp/article/view/3017