Abstract
Abstract Background and Aims Due to its numerous complications, type 2 diabetes mellitus (T2DM) has a major impact on the global economic burden and overall mortality. This condition modifies the metabolic microenvironment in targeted organs, such as the kidney and the brain, by its hyperglycemic nature. Gut microbiota seems to have significant interference with the renal-cerebral axis, especially in a dysbiosis state. The aim of the study was to quantify gut derived metabolites by metabolomic techniques and to evaluate their association with markers of endothelial, podocyte and proximal tubule damage and with cerebro-vascular hemodynamic indices. Method The metabolomic profiling was realized on serum and urine samples originated from 90 T2DM patients, divided into three subgroups, such as the following: 30 normal to mildly-, 30 moderately-, and 30 severely increased albuminuria, respectively, and 20 healthy subjects. The samples were examined by using untargeted and targeted ultra-high performance liquid chromatography coupled with electrospray-ionization quadroupole time-of-flight mass spectrometry (UHPLC-QTOF-ESI+-MS), in order to obtain the metabolic profile. The markers of renal damage such as synaptopodin (SP), podocalyxin (PD), N-acetyl-β-D-glucosaminidase (NAG), kidney injury molecule 1 (KIM-1), monocyte chemotactic protein 1 (MCP-1), and intercellular adhesion molecule 1 (ICAM-1) were assessed by ELISA technique. The hemodynamic cerebro-vascular indices were obtained by high resolution Doppler ultrasound of common carotid arteries (CCAs), internal carotid arteries (ICAs), and middle cerebral arteries (MCAs), bilaterally. The correlations between the metabolites, the markers of renal damage, and neurosonological indices were realized by univariable and multivariable linear regression analyses. Results UHPLC-QTOF-ESI+-MS targeted analysis and subsequent statistical assessments revealed a subset of metabolites with a specific pattern for the normal to mildly increased albuminuria subgroup. The metabolites identified as significant were, in serum: arginine (sArg), hippuric acid (sHA), indoxyl sulfate (sIS), butenoylcarnitine (sBCA), sorbitol (sSorb); and in urine, arginine (uArg), butenoylcarnitine (uBCA), indoxyl sulfate (uIS) and p-cresyl sulfate (uPCS). The univariable linear regression analysis revealed that sArg correlated positively with the breath-holding index (BHI) and negatively with intima media thickness (IMT) in ACI, MCP-1 and ICAM-1; sIS, sSorb, and sBCA correlated inversely with these parametes. The multivariable linear regression analysis displayed the specific correlations between metabolites, markers of endothelial dysfunction, and neurosonological indices, such as follows: sArg correlated with IMT and ICAM-1; sIS followed a predictive pattern along with resistance index (RI) in ACIs and ICAM-1; sBCA correlated with IMT and MCP-1 and sSorb correlated with ICAM-1 and BHI. The urine metabolites were correlated with markers of podocyte and proximal tubule dysfunction: uIS and uBCA were correlated with PD and urinary albumin to-creatinin ratio (uACR), and uPCR correlated with KIM-1 and uACR. Conclusion This study revealed a set of metabolites potentially derived from the intestinal microflora which may act as biomarkers for the early detection of both CMA and DKD in T2DM patients. SArg, sIS and, sBCA are indicators of renal endothelial dysfunction. Moreover, sArg and sIS reflect incipient common and internal carotid artery atherosclerosis, suggesting vascular remodeling at these levels. SSorb correlated with BHI, indicating blood-brain barrier dysfunction and CMA development. In urine, uBCA and uIS are indicators of podocytopathy, whereas uPCS is associated with proximal tubule damage in incipient DKD.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have