Severity Of Diabetic Kidney Disease Research Articles

Association between Albumin Alterations and Renal Function in Patients with Type 2 Diabetes Mellitus.

Diabetic kidney disease (DKD) is a major cause of morbidity and mortality in individuals with type 2 diabetes mellitus (T2DM). The aim of this study was to investigate whether albumin structural alterations correlate with DKD severity and evaluate whether native and reduced albumin concentrations could complement the diagnosis of DKD. To this end, one hundred and seventeen T2DM patients without (n = 42) and with (n = 75) DKD (DKD I-III upon KDIGO classification) were evaluated; the total albumin concentration (tHA) was quantified by a bromocresol green assay, while structural alterations were profiled via liquid chromatography-high-resolution mass spectrometry (LC-HRMS). The concentrations of native albumin (eHA, effective albumin) and reduced albumin (rHA) were subsequently assessed. The HRMS analyses revealed a reduced relative amount of native albumin in DKD patients along with an increased abundance of altered forms, especially those bearing oxidative modifications. Accordingly, both eHA and rHA values varied during the stages of progressive renal failure, and these alterations were dose-dependently correlated with renal dysfunction. A ROC curve analysis revealed a significantly greater sensitivity and specificity of eHA and rHA than of tHA for diagnosing DKD. Importantly, according to the multivariate logistic regression analysis, the eHA was identified as an independent predictor of DKD.

Low Levels of Metrnl are Linked to the Deterioration of Diabetic Kidney Disease.

Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease. Metrnl is a secreted protein that plays an important role in kidney disease. The aim of this study was to investigate DKD-related factors and the correlation between serum Metrnl levels and the severity of DKD. Ninety-six type 2 diabetes mellitus (T2DM) patients and 45 DKD patients were included in the study. A range of parameters were measured simultaneously, including waist-to-hip ratio (WHR), body mass index (BMI), urinary albumin/creatinine ratio (UACR), monocyte-lymphocyte ratio (MLR), albumin/globulin (A/G), liver and kidney function, blood lipid profile, islet function, and others. Subsequently, the related factors and predictive significance of DKD were identified. The correlation between the relevant factors of DKD and serum Metrnl levels with DKD was evaluated. The duration of the disease (OR: 1.12, 95% CI: 1.01-1.24, P=0.031), hypertension (OR: 4.86, 95% CI: 1.16-20.49, P=0.031), fasting blood glucose (OR: 1.23, 95% CI: 1.03-1.48, P=0.025), WHR (OR: 2.53, 95% CI: 1.03-6.22, P=0.044), and MLR (OR: 1.91, 95% CI: 1.18-3.08, P=0.008) are independent risk factors for DKD (P < 0.05). Conversely, A/G (OR: 0.13, 95% CI: 0.02-0.76, P=0.024) and Metrnl (OR: 0.99, 95% CI: 0.98-1.00, P=0.001) have been identified as protective factors against DKD. Furthermore, the level of Metrnl was negatively correlated with the severity of DKD (rs=-0.447, P<0.001). The area under receiver operating characteristic (ROC) curves for the diagnostic accuracy of Metrnl for DKD is 0.765 (95% CI: 0.686-0.844). The duration of the disease, hypertension, fasting blood glucose, WHR, and MLR are major risk factors for DKD. Metrnl and A/G are protective factors for DKD. Serum Metrnl concentrations are inversely correlated with DKD severity.

Association of systemic immune-inflammation index with diabetic kidney disease in patients with type 2 diabetes: a cross-sectional study in Chinese population.

Systemic immune-inflammation index (SII), a novel inflammatory marker, has been reported to be associated with diabetic kidney disease (DKD) in the U.S., however, such a close relationship with DKD in other countries, including China, has not been never determined. We aimed to explore the association between SII and DKD in Chinese population. A total of 1922 hospitalized patients with type 2 diabetes mellitus (T2DM) included in this cross-sectional study were divided into three groups based on estimated glomerular filtration rate (eGFR) and urinary albumin-to-creatinine ratio (ACR): non-DKD group, DKD stages 1-2 Alb group, and DKD-non-Alb+DKD stage 3 Alb group. The possible association of SII with DKD was investigated by correlation and multivariate logistic regression analysis, and receiver-operating characteristic (ROC) curves analysis. Moving from the non-DKD group to the DKD-non-Alb+DKD stage 3 Alb group, SII level was gradually increased (P for trend <0.01). Partial correlation analysis revealed that SII was positively associated with urinary ACR and prevalence of DKD, and negatively with eGFR (all P<0.01). Multivariate logistic regression analysis showed that SII remained independently significantly associated with the presence of DKD after adjustment for all confounding factors [(odds ratio (OR), 2.735; 95% confidence interval (CI), 1.840-4.063; P < 0.01)]. Moreover, compared with subjects in the lowest quartile of SII (Q1), the fully adjusted OR for presence of DKD was 1.060 (95% CI 0.773-1.455) in Q2, 1.167 (95% CI 0.995-1.368) in Q3, 1.266 (95% CI 1.129-1.420) in the highest quartile (Q4) (P for trend <0.01). Similar results were observed in presence of DKD stages 1-2 Alb or presence of DKD-non- Alb+DKD stage 3 Alb among SII quartiles. Last, the analysis of ROC curves revealed that the best cutoff values for SII to predict DKD, Alb DKD stages 1- 2, and DKD-non-Alb+ DKD stage 3 Alb were 609.85 (sensitivity: 48.3%; specificity: 72.8%), 601.71 (sensitivity: 43.9%; specificity: 72.3%), and 589.27 (sensitivity: 61.1%; specificity: 71.1%), respectively. Higher SII is independently associated with an increased risk of the presence and severity of DKD, and SII might be a promising biomarker for DKD and its distinct phenotypes in Chinese population.

Clinical value of noninvasive lens advanced glycation end product detection in early screening and severity evaluation of patients with diabetic kidney disease

BackgroundAdvanced glycation end products (AGEs) deposited in the lens are correlated with those in the kidneys, indicating a possible value in evaluating diabetic kidney disease (DKD). This study explored the value of noninvasively measuring lens AGEs to diagnose and evaluate the severity of diabetic nephropathy in patients with type 2 diabetes mellitus (T2DM).MethodologyA total of 134 T2DM patients admitted to the Fifth People's Hospital of Shanghai from March 2020 to May 2021 were selected randomly. Patients were divided into low-, medium-and high-risk groups according to the risk assessment criteria for DKD progression and into DKD and non-DKD (non-DKD) groups according to the Guidelines for the Prevention and Treatment of Diabetic Nephropathy in China. The concentrations of noninvasive AGEs in the lens in all the groups were retrospectively analyzed.ResultsThe concentration of noninvasive lens AGEs in the high-risk patients, according to the 2012 guidelines of the Global Organization for Improving the Prognosis of Kidney Diseases, was significantly higher than that in the remaining groups. Regression analysis suggested the value of lens AGEs in diagnosing DKD and evaluating DKD severity. Cox regression analysis indicated that the noninvasive lens AGE concentration was positive correlated with the course of disease.ConclusionThe receiver operating characteristic (ROC) curve suggested that using noninvasive lens AGE measurements has clinical value in the diagnosis of DKD (area under the curve 62.4%,95% confidence interval (CI) 52.4%–73.9%, p = 0.014) and in assessing the severity of DKD (area under the curve 83.2%, 95% CI 74.1%–92.3%, P < 0.001). Noninvasive lens AGE testing helps screen T2DM patients for DKD and evaluate the severity of DKD.

Cross-Sectional and Longitudinal Associations between Skin Autofluorescence and Tubular Injury Defined by Urinary Excretion of Liver-Type Fatty Acid-Binding Protein in People with Type 2 Diabetes.

It has previously been unclear whether the accumulation of advanced glycation end products, which can be measured using skin autofluorescence (SAF), has a significant role in diabetic kidney disease (DKD), including glomerular injury and tubular injury. This study was therefore carried out to determine whether SAF correlates with the progression of DKD in people with type 2 diabetes (T2D). In 350 Japanese people with T2D, SAF values were measured using an AGE Reader®, and both urine albumin-to-creatinine ratio (uACR), as a biomarker of glomerular injury, and urine liver-type fatty acid-binding protein (uLFABP)-to-creatinine ratio (uL-FABPCR), as a biomarker of tubular injury, were estimated as indices of the severity of DKD. Significant associations of SAF with uACR (p < 0.01), log-transformed uACR (p < 0.001), uL-FABPCR (p < 0.001), and log-transformed uL-FABPCR (p < 0.001) were found through a simple linear regression analysis. Although SAF was positively associated with increasing uL-FABPCR (p < 0.05) and increasing log-transformed uL-FABPCR (p < 0.05), SAF had no association with increasing uACR or log-transformed uACR after adjusting for clinical confounding factors. In addition, the annual change in SAF showed a significant positive correlation with annual change in uL-FABPCR regardless of confounding factors (p = 0.026). In conclusion, SAF is positively correlated with uL-FABP but not with uACR in people with T2D. Thus, there is a possibility that SAF can serve as a novel predictor for the development of diabetic tubular injury.

Jiangtang Decoction Ameliorates Diabetic Kidney Disease Through the Modulation of the Gut Microbiota.

This study aimed to elucidate the impact of Jiangtang decoction (JTD) on diabetic kidney disease (DKD) and its association with alterations in the gut microbiota. Using a diabetic mouse model (KK-Ay mice), daily administration of JTD for eight weeks was undertaken. Weekly measurements of body weight and blood glucose were performed, while kidney function, uremic toxins, inflammation factors, and fecal microbiota composition were assessed upon sacrifice. Ultra-structural analysis of kidney tissue was conducted to observe the pathological changes. The study findings demonstrated that JTD improve metabolism, kidney function, uremic toxins and inflammation, while also exerting a modulatory effect on the gut microbiota. Specifically, the genera Rikenella, Lachnoclostridium, and unclassified_c_Bacilli exhibited significantly increased abundance following JTD treatment, accompanied by reduced abundance of norank_f_Lachnospiraceae compared to the model group. Importantly, Rikenella and unclassified_c_Bacilli demonstrated negative correlations with urine protein levels. Lachnoclostridium and norank_f_Lachnospiraceae were positively associated with creatinine (Cr), indoxyl sulfate (IS) and interleukin (IL)-6. Moreover, norank_f_Lachnospiraceae exhibited positive associations with various indicators of DKD severity, including weight, blood glucose, urea nitrogen (UN), kidney injury molecule-1 (KIM-1) levels, trimethylamine-N-oxide (TMAO), p-cresyl sulfate (pCS), nucleotide-binding oligomerization domain (Nod)-like receptor family pyrin domain-containing 3 (NLRP3) and IL-17A production. These findings suggested that JTD possess the ability to modulate the abundance of Rikenella, Lachnoclostridium, unclassified_c_Bacilli and norank_f_Lachnospiraceae within the gut microbiota. This modulation, in turn, influenced metabolic processes, kidney function, uremic toxin accumulation, and inflammation, ultimately contributing to the amelioration of DKD.

#4646 CT-DERIVED RADIOMICS ANALYSIS OF DIABETIC NEPHROPATHY BY MACHINE LEARNING MODELS

Abstract Background and Aims Kidney radiomics has been used to develop more accurate diagnostic tools of renal tumor and predict outcomes. However, radiomics studies for diabetic kidney disease (DKD) remain few. In this light, we hypothesized that computed tomography (CT) radiomics features could differentiate DKD from normal kidneys and assess the severity of DKD. Method This retrospective study included 343 subjects with type 2 diabetes mellitus (T2DM) (male 65.5%, mean age 63.6±14.8) and 90 healthy controls (HC) (male 34.4%, mean age 41.9±8.5) who underwent abdominal CT. Whole volumetric CT data of both kidneys were automatically extracted using a deep-learning based model and radiomics features were extracted. T2DM were categorized into three groups according to eGFR (mL/min/1.73 m^2) (group 1, eGFR &amp;gt; 60; group 2, 15 ≤ eGFR ≤ 60; and group 3, eGFR &amp;lt;15). The capability of CT radiomics features to distinguish not only DKD from HC but also various DKD groups based on eGFR, was evaluated using machine learning models. Results A total of 1,723 radiomics features were extracted from the volumetric CT data of both kidneys. A combination of LASSO filter and random forest showed best performance in differentiating between HC and DKD, with an area under curve (AUC) of 0.98 and accuracy of 95.7%. It also showed an excellent performance in differentiating between HC and DKD group 1 with AUC of 0.97 and accuracy of 91.7%, and also it was able to differentiate between DKD groups (AUCs &amp;gt; 0.78). CT radiomics features and eGFR had a moderate degree of correlation (R=-0.50 to R=0.63, all P&amp;lt;.00). Conclusion CT-derived radiomics analysis of kidneys using machine learning models can be useful in differentiating DKD from normal kidneys as well as assessing the severity of DKD.

Diagnostic value of serum cathepsin S in type 2 diabetic kidney disease.

Identification of risk factors that have causal effects on the occurrence of diabetic kidney disease (DKD), is of great significance in early screening and intervening for DKD, and in delaying the progression of DKD to end-stage renal disease. Cathepsin S (Cat-S), a novel non-invasive diagnostic marker, mediates vascular endothelial dysfunction. The diagnostic value of Cat-S for DKD has rarely been reported in clinical studies. To analyze whether Cat-S is a risk factor for DKD and evaluate the diagnostic value of serum Cat-S for DKD. Forty-three healthy subjects and 200 type 2 diabetes mellitus (T2DM) patients were enrolled. T2DM patients were divided into subgroups according to various criteria. Enzyme-linked immunosorbent assay was used to detect serum Cat-S levels among different subgroups. Spearman correlation analysis was used to analyze correlations between serum Cat-S and clinical indicators. Multivariate logistic regression analysis was performed to analyze risk factors for the occurrence of DKD and decreased renal function in T2DM patients. Spearman analysis showed that serum Cat-S level was positively correlated with urine albumin creatinine ratio (r=0.76, P<0.05) and negatively correlated with estimated glomerular filtration rate (r=-0.54, P<0.01). Logistic regression analysis showed that increased serum Cat-S and cystatin C(CysC) were independent risk factors for DKD and decreased renal function in T2DM patients (P<0.05). The area under the receiver operating characteristic (ROC) curve was 0.900 of serum Cat-S for diagnosing DKD, and when the best cut-off value was 827.42 pg/mL the sensitivity and specificity were 71.6% and 98.8%, respectively. Thus, serum Cat-S was better than CysC for diagnosing DKD (for CysC, the area under the ROC curve was 0.791, and when the cut-off value was 1.16 mg/L the sensitivity and specificity of CysC were 47.4% and 98.8%, respectively). Increased serum Cat-S were associated with the progression of albuminuria and decreased renal function in T2DM patients. The diagnostic value of serum Cat-S was better than that of CysC for DKD. Monitoring of serum Cat-S levels could be helpful for early screening DKD and assessing the severity of DKD and could provide a new strategy for diagnosing DKD.

Antagonistes du récepteur minéralocorticoïde

Diabetic kidney disease (DKD) and its associated cardiovascular morbidity represent a major complication in diabetic patients. Over the past two decades, several experimental studies have shown benefits of mineralocorticoid receptor (MR) antagonists on the cardiorenal outcomes in animal models of non-diabetic or diabetic kidney diseases. Here, we summarize the role of MR activation in promoting inflammatory and fibrotic mechanisms that contribute to DKD pathophysiology. We also review the key findings of two recent large clinical trials FIDELIO-DKD and FIGARO-DKD which showed for the first time a major benefit of the non-steroidal MR antagonist, finerenone, on renal and cardiac specific outcomes across the spectrum of DKD severity. We finally discuss the place of finerenone compared to other DKD therapeutic approaches.

Macrophage inflammatory protein-1β as a novel therapeutic target for renal protection in diabetic kidney disease

Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease worldwide and the prevalence of DKD has increased over recent decades. Inflammation is involved in the development and progression of DKD. In this study, we explored the potential role of macrophage inflammatory protein-1β (MIP-1β) in DKD. Clinical non-diabetic subjects and DKD patients with different levels of urine albumin-to-creatinine ratio (ACR) were enrolled in the study. Leprdb/db mice and MIP-1β knockout mice were also used as mouse models for DKD. We found that serum MIP-1β levels were elevated in the DKD patients, especially those with ACRs that were less than or equal to 300, suggesting that MIP-1β is activated in clinical DKD. The administration of anti-MIP-1β antibodies attenuated DKD severity in the Leprdb/db mice, which also showed reduced glomerular hypertrophy and podocyte injury, as well as decreased inflammation and fibrosis, suggesting that MIP-1β plays a role in the development of DKD. The MIP-1β knockout mice showed improved renal function and decreased renal glomerulosclerosis and fibrosis in DKD. Furthermore, podocytes from the MIP-1β knockout mice showed less high glucose-induced inflammation and fibrosis compared to those from wild-type mice. In conclusion, the inhibition or deletion of MIP-1β protected podocytes, modulated renal inflammation, and ameliorated experimental DKD, suggesting that novel anti-MIP-1β strategies could potentially be used to treat DKD.

A generalized covariate-adjusted top-scoring pair algorithm with applications to diabetic kidney disease stage classification in the Chronic Renal Insufficiency Cohort (CRIC) Study

BackgroundThe growing amount of high dimensional biomolecular data has spawned new statistical and computational models for risk prediction and disease classification. Yet, many of these methods do not yield biologically interpretable models, despite offering high classification accuracy. An exception, the top-scoring pair (TSP) algorithm derives parameter-free, biologically interpretable single pair decision rules that are accurate and robust in disease classification. However, standard TSP methods do not accommodate covariates that could heavily influence feature selection for the top-scoring pair. Herein, we propose a covariate-adjusted TSP method, which uses residuals from a regression of features on the covariates for identifying top scoring pairs. We conduct simulations and a data application to investigate our method, and compare it to existing classifiers, LASSO and random forests.ResultsOur simulations found that features that were highly correlated with clinical variables had high likelihood of being selected as top scoring pairs in the standard TSP setting. However, through residualization, our covariate-adjusted TSP was able to identify new top scoring pairs, that were largely uncorrelated with clinical variables. In the data application, using patients with diabetes (n = 977) selected for metabolomic profiling in the Chronic Renal Insufficiency Cohort (CRIC) study, the standard TSP algorithm identified (valine-betaine, dimethyl-arg) as the top-scoring metabolite pair for classifying diabetic kidney disease (DKD) severity, whereas the covariate-adjusted TSP method identified the pair (pipazethate, octaethylene glycol) as top-scoring. Valine-betaine and dimethyl-arg had, respectively, ≥ 0.4 absolute correlation with urine albumin and serum creatinine, known prognosticators of DKD. Thus without covariate-adjustment the top-scoring pair largely reflected known markers of disease severity, whereas covariate-adjusted TSP uncovered features liberated from confounding, and identified independent prognostic markers of DKD severity. Furthermore, TSP-based methods achieved competitive classification accuracy in DKD to LASSO and random forests, while providing more parsimonious models.ConclusionsWe extended TSP-based methods to account for covariates, via a simple, easy to implement residualizing process. Our covariate-adjusted TSP method identified metabolite features, uncorrelated from clinical covariates, that discriminate DKD severity stage based on the relative ordering between two features, and thus provide insights into future studies on the order reversals in early vs advanced disease states.

The harmful intestinal microbial community accumulates during DKD exacerbation and microbiome-metabolome combined validation in a mouse model.

Diabetic kidney disease (DKD) is one of the most prevalent complications of diabetes mellitus (DM) and is associated with gut microbial dysbiosis. We aim to build a diagnostic model to aid clinical practice and uncover a crucial harmful microbial community that contributes to DKD pathogenesis and exacerbation. A total of 528 fecal samples from 180 DKD patients and 348 non-DKD populations (138 DM and 210 healthy volunteers) from the First Affiliated Hospital of Zhengzhou University were recruited and randomly divided into a discovery phase and a validation phase. The gut microbial composition was compared using 16S rRNA sequencing. Then, the 180 DKD patients were stratified into four groups based on clinical stages and underwent gut microbiota analysis. We established DKD mouse models and a healthy fecal microbiota transplantation (FMT) model to validate the effects of gut microbiota on DKD and select the potential harmful microbial community. Untargeted metabolome-microbiome combined analysis of mouse models helps decipher the pathogenetic mechanism from a metabolic perspective. The diversity of the gut microbiome was significantly decreased in DKD patients when compared with that of the non-DKD population and was increased in the patients with more advanced DKD stages. The DKD severity in mice was relieved after healthy gut microbiota reconstruction. The common harmful microbial community was accumulated in the subjects with more severe DKD phenotypes (i.e., DKD and DKD5 patients and DKD mice). The harmful microbial community was positively associated with the serum injurious metabolites (e.g., cholic acid and hippuric acid). The fecal microbial community was altered markedly in DKD. Combining the fecal analysis of both human and animal models selected the accumulated harmful pathogens. Partially recovering healthy gut microbiota can relieve DKD phenotypes via influencing pathogens' effect on DKD mice's metabolism.

Reversal of the renal hyperglycemic memory in diabetic kidney disease by targeting sustained tubular p21 expression

A major obstacle in diabetes is the metabolic or hyperglycemic memory, which lacks specific therapies. Here we show that glucose-mediated changes in gene expression largely persist in diabetic kidney disease (DKD) despite reversing hyperglycemia. The senescence-associated cyclin-dependent kinase inhibitor p21 (Cdkn1a) was the top hit among genes persistently induced by hyperglycemia and was associated with induction of the p53-p21 pathway. Persistent p21 induction was confirmed in various animal models, human samples and in vitro models. Tubular and urinary p21-levels were associated with DKD severity and remained elevated despite improved blood glucose levels in humans. Mechanistically, sustained tubular p21 expression in DKD is linked to demethylation of its promoter and reduced DNMT1 expression. Two disease resolving agents, protease activated protein C (3K3A-aPC) and parmodulin-2, reversed sustained tubular p21 expression, tubular senescence, and DKD. Thus, p21-dependent tubular senescence is a pathway contributing to the hyperglycemic memory, which can be therapeutically targeted.

Mitochondrial Dysfunction in Individuals with Diabetic Kidney Disease: A Systematic Review.

Mitochondrial dysfunction is implicated in the pathogenesis of diabetic kidney disease (DKD). Compared to the vast body of evidence from preclinical in vitro and in vivo studies, evidence from human studies is limited. In a comprehensive search of the published literature, findings from studies that reported evidence of mitochondrial dysfunction in individuals with DKD were examined. Three electronic databases (PubMed, Embase, and Scopus) were searched in March 2022. A total of 1339 articles were identified, and 22 articles met the inclusion criteria. Compared to non-diabetic controls (NDC) and/or individuals with diabetes but without kidney disease (DC), individuals with DKD (age ~55 years; diabetes duration ~15 years) had evidence of mitochondrial dysfunction. Individuals with DKD had evidence of disrupted mitochondrial dynamics (11 of 11 articles), uncoupling (2 of 2 articles), oxidative damage (8 of 8 articles), decreased mitochondrial respiratory capacity (1 of 1 article), decreased mtDNA content (5 of 6 articles), and decreased antioxidant capacity (3 of 4 articles) compared to ND and/or DC. Neither diabetes nor glycemic control explained these findings, but rather presence and severity of DKD may better reflect degree of mitochondrial dysfunction in this population. Future clinical studies should include individuals closer to diagnosis of diabetes to ascertain whether mitochondrial dysfunction is implicated in the development of, or is a consequence of, DKD.

Neutrophil Extracellular Traps Promote NLRP3 Inflammasome Activation and Glomerular Endothelial Dysfunction in Diabetic Kidney Disease.

Diabetes mellitus is a metabolic disease largely due to lifestyle and nutritional imbalance, resulting in insulin resistance, hyperglycemia and vascular complications. Diabetic kidney disease (DKD) is a major cause of end-stage renal failure contributing to morbidity and mortality worldwide. Therapeutic options to prevent or reverse DKD progression are limited. Endothelial and glomerular filtration barrier (GFB) dysfunction and sterile inflammation are associated with DKD. Neutrophil extracellular traps (NETs), originally identified as an innate immune mechanism to combat infection, have been implicated in sterile inflammatory responses in non-communicable diseases. However, the contribution of NETs in DKD remains unknown. Here, we show that biomarkers of NETs are increased in diabetic mice and diabetic patients and that these changes correlate with DKD severity. Mechanistically, NETs promote NLRP3 inflammasome activation and glomerular endothelial dysfunction under high glucose stress in vitro and in vivo. Inhibition of NETs (PAD4 inhibitor) ameliorate endothelial dysfunction and renal injury in DKD. Taken together, NET-induced sterile inflammation promotes diabetes-associated endothelial dysfunction, identifying a new pathomechanism contributing to DKD. Inhibition of NETs may be a promising therapeutic strategy in DKD.

Association Between Serum Homocysteine Levels and Severity of Diabetic Kidney Disease in 489 Patients with Type 2 Diabetes Mellitus: A Single-Center Study.

BackgroundThis study from a single center aimed to investigate the association between serum homocysteine (Hcy) levels and severity of diabetic kidney disease (DKD) in 489 patients with type 2 diabetes mellitus (T2DM).Material/MethodsA total of 1163 patients with T2DM, including 674 T2DM without kidney disease (T2DM group) and 489 T2DM with DKD (DKD group), were evaluated. The DKD group was subdivided according to the chronic kidney disease (CKD) and albuminuria staging criteria in “Kidney Disease: Improving Global Outcomes 2012 clinical practice guideline” to quantify the severity of DKD: CKD stage 1 (n=164), CKD stage 2 (n=103), CKD stage 3 (n=95), CKD stage 4 (n=71), and CKD stage 5 (n=56) and stage A1 (n=57), stage A2 (n=250), and stage A3 (n=182), respectively. Peripheral blood was collected after 8 hours of fasting to test Hcy levels.ResultsIn CKD stages, Hcy levels gradually increased with increasing DKD severity (CKD stage 1 to 5); while in albuminuria stages, Hcy levels did not gradually increase with increasing DKD severity (stage A1 to A3). Hcy was an independent risk factor for CKD stages 2–5 (P<0.05), and had no effect on the albuminuria stages (P>0.05), while it may indirectly affect the occurrence of albuminuria stages through its impact on estimated glomerular filtration rate.ConclusionsThe relationship between Hcy level and DKD severity was related to the different staging methods used. Hcy was an independent risk factor for CKD stages but not albuminuria stages.

Plasma or Urine Neutrophil Gelatinase-Associated Lipocalin (NGAL): Which Is Better at Detecting Chronic Kidney Damage in Type 2 Diabetes?

Background and study aims—Albuminuria, defined as an enhanced urine albumin/creatinine ratio (ACR) on a spot sample, is a validated biomarker of glomerular damage. However, it cannot always detect early renal failures in patients with type 2 diabetes (T2D), thus prompting the search for more sensitive and specific parameters. Herein, we investigated the differential role of plasma and urine neutrophil-gelatinase-associated lipocalin (NGALp,—NGALu) for the detection of diabetic kidney disease (DKD). Methods—Traditional glomerular (serum creatinine, cystatin C, ACR) damage biomarkers were evaluated in 84 patients with T2D and in 21 metabolically healthy controls. Diabetic patients were stratified into four groups based on T2D duration (less or more than 5 years) and presence and severity of DKD (early- or advanced-stage), as defined by the ACR and estimated glomerular filtration rate (eGFR). NGALp and NGALu were determined by ELISA methodology and compared among groups. Results—There was no difference in NGALp and NGALu levels between the metabolically healthy individuals and the age-matched, newly diagnosed diabetic patients in the absence of DKD. However, in contrast to NGALu, NGALp was found to be substantially increased in patients with long-standing diabetes without biochemical evidence of DKD, closely mirroring the modest, but still accelerated, decline in the eGFR typical of this chronic dysmetabolic condition, and remained overexpressed throughout the stages of DKD progression. Increased NGALu levels were, instead, rather specific in patients with biochemical evidence of DKD (i.e., marked by increased albuminuria), regardless of T2D duration. Spearman’s correlation and regression analyses showed that patient age and T2D duration could exert a strong positive impact exclusively on NGALp concentrations (ρ = 0.419, p &lt; 0.001 for age; ρ = 0.581, p &lt; 0.001 for T2D), and none on NGALu. Furthermore, receiver operating characteristic (ROC) analysis showed the best performance of NGALp compared to NGALu for the detection of DKD (AUC = 0.817 for NGALp, AUC = 0.711 for NGALu). Conclusions—Our data suggest a different pathophysiological and predictive role for urine and plasma NGAL in the context of T2D and DKD.

The Association of Expression Patterns of Lncrna Taurine Upregulated Gene 1 (Tug1) with Progression and Severity of Diabetic Kidney Disease

The Association of Expression Patterns of Lncrna Taurine Upregulated Gene 1 (Tug1) with Progression and Severity of Diabetic Kidney Disease

Interaction of circulating TGFβ regulatory miRNAs in different severity of diabetic kidney disease

Aims To explore the interaction of TGFβ regulatory microRNAs (miRNAs) with different severities of diabetic kidney disease (DKD). Methods According to different UACR (30 and 300 mg/g), 436 subjects were included, and high glucose induced RMCs were cultured. Real-time PCR, ELISA, and automatic biochemical analysis were used to measure miRNAs, TGFβ1, and other biochemical indicators in serum and RMCs. Target genes of miRNA were predicted and visualised by bioinformatics. Results HbA1c, TGFβ1, miR-217, and miR-224 in T2DM patients increased with UACR, while miR-192 and miR-216a decreased. Ln UACR was positively correlated with HbA1c, TGFβ1, miR-217, and miR-224, and negatively correlated with miR-192 and miR-216a. High glucose and TGFβ1 affected miRNAs and these miRNAs affected each other. The miRNA target genes mainly revolve around PTEN, PI3K/Akt, and MAPK signalling pathways. Conclusion TGFβ regulatory miRNAs and different severity of DKD have a potential interaction regulating fibrosis through PTEN, PI3K/Akt, and MAPK pathways.

Serum zonulin levels in type 2 diabetes patients with diabetic kidney disease.

Recent data have shown that diabetic kidney disease (DKD) is associated with abnormal gut microbiota composition. Zonulin is a physiological tight junction modulator and an intestinal permeability marker. In this study we aimed to investigate serum levels of zonulin and interleukin 6 (IL-6) in patients with type 2 diabetes mellitus (T2DM) and different levels of albuminuria. Ninety patients with T2DM and 30 healthy controls (HC) aged between 18 and 65 years were enrolled in the study. T2DM patients were divided into three groups as patients with normoalbuminuria (n = 30), microalbuminuria (n = 30), and macroalbuminuria (n = 30). Serum zonulin and IL-6 levels were measured by ELISA method. There was no significant difference between groups in terms of age, gender, serum ALT, LDL-C, HDL-C, and zonulin levels (p > 0.05). Significant differences between groups were present for the duration of diabetes (p < 0.001), body mass index (p < 0.001), fasting blood glucose (p < 0.001), creatinine (p < 0.001), uric acid (p = 0.037), triglyceride (p = 0.003), total cholesterol (p < 0.001), glycated haemoglobin (p < 0.001), and IL-6 (p < 0.001) levels. IL-6 levels were significantly increased in the microalbuminuria and macroalbuminuria groups compared to the HC group, but no significant difference was determined between the HC and normoalbuminuria group. In patients with diabetic kidney disease, a significant positive correlation was found between zonulin with IL-6 and proteinuria (rho = 0.296, p = 0.008; rho = 0.190, p < 0.047, respectively). The serum IL-6 level was positively correlated with microalbuminuria and proteinuria (rho = 0.451, p < 0.001; rho = 0.425, p < 0.001, respectively). We suggest that the serum zonulin level is not a promising biomarker to assess the severity of DKD in patients with long-standing T2DM.