Glycaemic control in type 2 diabetic patients with chronic kidney disease: the impacts on enzymatic antioxidants and soluble RAGE

Identification of novel therapeutic targets for chronic kidney disease and kidney function by integrating multi-omics proteome with transcriptome

BACKGROUND

Chronic kidney disease (CKD) is a progressive disease for which there is no effective cure. We aimed to identify potential drug targets for CKD and kidney function by integrating plasma proteome and transcriptome.

METHODS

We designed a comprehensive analysis pipeline involving two-sample Mendelian randomization (MR) (for proteins), summary-based MR (SMR) (for mRNA), and colocalization (for coding genes) to identify potential multi-omics biomarkers for CKD and combined the protein-protein interaction, Gene Ontology (GO), and single-cell annotation to explore the potential biological roles. The outcomes included CKD, extensive kidney function phenotypes, and different CKD clinical types (IgA nephropathy, chronic glomerulonephritis, chronic tubulointerstitial nephritis, membranous nephropathy, nephrotic syndrome, and diabetic nephropathy).

RESULTS

Leveraging pQTLs of 3032 proteins from 3 large-scale GWASs and corresponding blood- and tissue-specific eQTLs, we identified 32 proteins associated with CKD, which were validated across diverse CKD datasets, kidney function indicators, and clinical types. Notably, 12 proteins with prior MR support, including fibroblast growth factor 5 (FGF5), isopentenyl-diphosphate delta-isomerase 2 (IDI2), inhibin beta C chain (INHBC), butyrophilin subfamily 3 member A2 (BTN3A2), BTN3A3, uromodulin (UMOD), complement component 4A (C4a), C4b, centrosomal protein of 170 kDa (CEP170), serologically defined colon cancer antigen 8 (SDCCAG8), MHC class I polypeptide-related sequence B (MICB), and liver-expressed antimicrobial peptide 2 (LEAP2), were confirmed. To our knowledge, 20 novel causal proteins have not been previously reported. Five novel proteins, namely, GCKR (OR 1.17, 95% CI 1.10-1.24), IGFBP-5 (OR 0.43, 95% CI 0.29-0.62), sRAGE (OR 1.14, 95% CI 1.07-1.22), GNPTG (OR 0.90, 95% CI 0.86-0.95), and YOD1 (OR 1.39, 95% CI 1.18-1.64,) passed the MR, SMR, and colocalization analysis. The other 15 proteins were also candidate targets (GATM, AIF1L, DQA2, PFKFB2, NFATC1, activin AC, Apo A-IV, MFAP4, DJC10, C2CD2L, TCEA2, HLA-E, PLD3, AIF1, and GMPR1). These proteins interact with each other, and their coding genes were mainly enrichment in immunity-related pathways or presented specificity across tissues, kidney-related tissue cells, and kidney single cells.

CONCLUSIONS

Our integrated analysis of plasma proteome and transcriptome data identifies 32 potential therapeutic targets for CKD, kidney function, and specific CKD clinical types, offering potential targets for the development of novel immunotherapies, combination therapies, or targeted interventions.

Current updates on metabolites and its interlinked pathways as biomarkers for diabetic kidney disease: A systematic review

Diabetic kidney disease (DKD) is a major microvascular complication of diabetes mellitus (DM) that poses a serious risk as it can lead to end-stage renal disease (ESRD). DKD is linked to changes in the diversity, composition, and functionality of the microbiota present in the gastrointestinal tract. The interplay between the gut microbiota and the host organism is primarily facilitated by metabolites generated by microbial metabolic processes from both dietary substrates and endogenous host compounds. The production of numerous metabolites by the gut microbiota is a crucial factor in the pathogenesis of DKD. However, a comprehensive understanding of the precise mechanisms by which gut microbiota and its metabolites contribute to the onset and progression of DKD remains incomplete. This review will provide a summary of the current scenario of metabolites in DKD and the impact of these metabolites on DKD progression. We will discuss in detail the primary and gut-derived metabolites in DKD, and the mechanisms of the metabolites involved in DKD progression. Further, we will address the importance of metabolomics in helping identify potential DKD markers. Furthermore, the possible therapeutic interventions and research gaps will be highlighted.

Altered expression of a disintegrin and metalloproteinase 10 in peripheral blood mononuclear cells in type 2 diabetes mellitus patients with the acute coronary syndrome: a pilot study

PURPOSE

Advanced glycation end products (AGEs) are responsible for the complications in type 2 diabetes mellitus (T2DM) patients by acting via its receptor (RAGE). The soluble form of RAGE (sRAGE) prevents the harmful effects of AGE-RAGE signalling. The sRAGE is produced either by alternate splicing (esRAGE) or proteolytic RAGE cleavage by a disintegrin and metalloproteinase 10 (ADAM10). Hence, the study aimed to compare the expression of ADAM10 in peripheral blood mononuclear cell (PBMC), serum sRAGE and esRAGE levels in T2DM patients with and without acute coronary syndrome (ACS).

METHODS

Forty-five T2DM patients with ACS and 45 age, gender and duration of DM-matched T2DM patients without ACS were recruited. Serum sRAGE and esRAGE levels were measured by enzyme-linked immunosorbent assay. The expression of ADAM10 in PBMC was determined by quantitative reverse transcription-polymerase chain reaction.

RESULTS

The expression of ADAM10 in PBMC and serum sRAGE levels were significantly lower in T2DM patients with ACS than in T2DM patients without ACS (p < 0.001). Serum sRAGE levels and expression of ADAM10 in PBMC were positively correlated with each other and negatively correlated with markers of cardiac injury and glycaemic status (p < 0.05). Simple logistic regression showed that the models containing the expression of ADAM10 and serum sRAGE level could predict the ACS risk among T2DM patients. ROC analysis showed that both might be used for ACS diagnosis in T2DM patients.

CONCLUSION

Reduced expression of ADAM10 in PBMC might be responsible for lower serum sRAGE levels, predisposing T2DM patients to high ACS risk.

The Role of Advanced Glycation End Products and Its Soluble Receptor in Kidney Diseases

Patients with chronic kidney disease (CKD) are more prone to oxidative stress and chronic inflammation, which may lead to an increase in the synthesis of advanced glycation end products (AGEs). Because AGEs are mostly removed by healthy kidneys, AGE accumulation is a result of both increased production and decreased kidney clearance. On the other hand, AGEs may potentially hasten decreasing kidney function in CKD patients, and are independently related to all-cause mortality. They are one of the non-traditional risk factors that play a significant role in the underlying processes that lead to excessive cardiovascular disease in CKD patients. When AGEs interact with their cell-bound receptor (RAGE), cell dysfunction is initiated by activating nuclear factor kappa-B (NF-κB), increasing the production and release of inflammatory cytokines. Alterations in the AGE-RAGE system have been related to the development of several chronic kidney diseases. Soluble RAGE (sRAGE) is a decoy receptor that suppresses membrane-bound RAGE activation and AGE-RAGE-related toxicity. sRAGE, and more specifically, the AGE/sRAGE ratio, may be promising tools for predicting the prognosis of kidney diseases. In the present review, we discuss the potential role of AGEs and sRAGE as biomarkers in different kidney pathologies.

Advanced Glycation End Products (AGE) and Soluble Forms of AGE Receptor: Emerging Role as Mortality Risk Factors in CKD

Advanced glycation end-products (AGE) can promote chronic kidney disease (CKD) progression and CKD-related morbidities. The soluble receptor for AGE (sRAGE) is a potential biomarker of inflammation and oxidative stress. Here, we explored the role of AGE, glycated albumin, sRAGE and its different forms, cRAGE and esRAGE, as prognostic factors for mortality in 111 advanced CKD patients. The median follow-up time was 39 months. AGE were quantified by fluorescence, sRAGE and its forms by ELISA. Malnutrition was screened by the Malnutrition Inflammation Score (MIS). The Cox proportional hazards regression model was used to assess the association of variables with all-cause mortality. Mean levels of sRAGE, esRAGE and cRAGE were 2318 ± 1224, 649 ± 454 and 1669 ± 901 pg/mL. The mean value of cRAGE/esRAGE was 2.82 ± 0.96. AGE were 3026 ± 766 AU and MIS 6.0 ± 4.7. eGFR correlated negatively with AGE, sRAGE, esRAGE and cRAGE, but not with cRAGE/esRAGE. Twenty-eight patients died. No difference was observed between diabetic and non-diabetic patients. Starting dialysis was not associated with enhanced risk of death. AGE, esRAGE and cRAGE/esRAGE were independently associated with all-cause mortality. AGE, esRAGE and cRAGE/esRAGE may help to stratify overall mortality risk. Implementing the clinical evaluation of CKD patients by quantifying these biomarkers can help to improve patient outcomes.

The role of soluble receptor for advanced glycation end-products (sRAGE) in the general population and patients with diabetes mellitus with a focus on renal function and overall outcome

Isoforms of the receptor for advanced glycation end-product (RAGE) protein, which lack the transmembrane and the signaling (soluble RAGE or sRAGE) domains are hypothesized to counteract the detrimental action of the full-length receptor by acting as a decoy, and they provide a potential tool to treat RAGE-associated diseases. Multiple studies have explored the relationship between sRAGE and endogenous secretory RAGE and its polymorphism and obesity, metabolic syndrome, atherosclerosis, kidney function, and increased mortality in the general population. In addition, sRAGE may be a key player in the pathogenesis of diabetes mellitus and its microvascular (e.g. kidney disease) as well as macrovascular (e.g. cardiovascular disease) complications. In this review, we focus on the role of sRAGE as a biomarker in these specific areas. As there is a lack of an underlying unifying hypothesis about how sRAGE changes according to the disease condition or risk factor, there is a call to incorporate all three players of the AGE-RAGE axis into a new universal biomarker/risk marker: (AGE + RAGE)/sRAGE. However, the measurement of RAGE in humans is not practical as it is a cell-bound receptor for which tissue is required for analysis. A high AGE/sRAGE ratio may be a valuable alternative and practical universal biomarker/risk marker for diseases associated with the AGE-RAGE axis, irrespective of low or high serum sRAGE concentrations.

Triglyceride is independently correlated with insulin resistance and islet beta cell function: a study in population with different glucose and lipid metabolism states

BACKGROUND

Previous studies on the effects of lipotoxicity and oxidative stress on islet beta cell function mainly focused on patients with diabetes, whereas studies on normal glucose tolerance (NGT) are few. The aim of this study was to explore the relationships among triglyceride (TG), high-density lipoprotein cholesterol (HDL-c), low-density lipoprotein cholesterol (LDL-c), oxidative stress indicators, insulin resistance, and beta cell function in populations with different glucose and lipid metabolism states.

METHODS

A total of 517 individuals were recruited from a rural community in Beijing, China. Glucose metabolism status was defined according to the results of a 75-g oral glucose tolerance test (OGTT). Dyslipidemia was defined as abnormal TG, HDL-c, or LDL-c levels. The population was divided into four groups: individuals with normal glucose and lipid levels (group A, n = 62); those with dyslipidemia alone (group B, n = 82); those with dysglycemia alone (group C, n = 121); and those with dysglycemia and dyslipidemia (group D, n = 247). Oxidative stress indicators, including superoxide dismutase (SOD), glutathione reductase (GR) and 8-hydroxydeoxyguanosine (8-OHdG), were measured. Homeostasis model assessment of insulin resistance (HOMA-IR) and glucose disposition index (DI₃₀, DI₁₂₀) were calculated to assess insulin resistance and islet beta cell function, respectively. Stratified multiple linear regression analysis was used to explore relationships between TG, HDL-c, LDL-c, oxidative stress indicators, and insulin resistance (natural log transformation of HOMA-IR, LnHOMA-IR) and beta cell function (natural log transformation of DI₃₀, Ln DI₃₀).

RESULTS

Compared with the control group, populations with dyslipidemia and/or dysglycemia showed significantly increased insulin resistance. Dyslipidemia aggravated insulin resistance and beta cell dysfunction in individuals with dysglycemia. Stratified regression analysis showed that TG positively correlated with LnHOMA-IR in individuals with normal glucose levels (beta = 0.321, 0.327, P = 0.011, 0.003 in groups A and B, respectively) and negatively correlated with LnDI₃₀ in participants with dyslipidemia (beta = - 0.225, - 0.122, P = 0.035, 0.048 in groups B and D, respectively). Reduced serum SOD levels in individuals with dysglycemia plus dyslipidemia were observed, and a negative association between TG and SOD levels was found (r = - 0.461, P < 0.001).

CONCLUSION

TG correlated with both insulin resistance and beta cell function in individuals with dyslipidemia alone. SOD negatively correlated with TG, indicating a close relationship between oxidative stress and glucose-lipid metabolism. Due to the adverse effect of hypertriglyceridemia on insulin sensitivity and islet beta cell function, more attention should be paid to the detection and management of hypertriglyceridemia.

Association between Glycated Hemoglobin with the Levels of Serum Proinflammatory Cytokines and Antioxidants in Patients with Type 2 Diabetes Mellitus in Universitas Sumatera Utara Hospital

BACKGROUND:

Hyperglycemia condition in diabetes mellitus (DM) influences proinflammatory cytokine levels and disrupts antioxidant balances. Glycated Hemoglobin is used as a biomarker of glycemic control in DM.

AIM:

This study aimed to analyse the association between glycated Hemoglobin with the levels of serum proinflammatory cytokines (interleukin (IL)-6) and antioxidants (glutathione peroxidase (GPx) and glutathione (GSH)) in type 2 diabetes mellitus (T2DM) patients in Universitas Sumatera Utara (USU) Hospital.

METHODS:

A total of eighty-nine T2DM patients were recruited at USU Hospital. Glycated Hemoglobin levels were measured using routine laboratory tests at USU Hospital. The IL-6, GPx, and GSH levels were measured using enzyme-linked immunosorbent (ELISA) method. The statistical significance was determined using the Kruskal Wallis test, followed by Mann-Whitney test (p < 0.05).

RESULTS:

The mean of glycated hemoglobin (%), IL-6 (pg/ml), GPx (ng/ml), and GSH (ng/ml) levels in T2DM patients were 8.96 ± 2.28, 59.27 ± 16.04, 32.13 ± 12.10, and 7.42 ± 3.50, respectively. Regarding the glycated Hemoglobin levels, 28.09% of patients had controlled diabetes, 24.72% of patients had poorly controlled diabetes, and 47.19% of patients had uncontrolled diabetes. The IL-6 levels of the three study groups based on glycated Hemoglobin levels were related significantly (p < 0.05), but there was no statistically significant difference observed between the GPx and GSH levels (p > 0.05).

CONCLUSION:

The present study suggests that the glycated Hemoglobin was associated with the levels of serum IL-6 levels but not GPx and GSH levels in T2DM patients in USU Hospital.