Gluconephrotic Syndrome: A Comprehensive Review.

This article provides an overview of the diabetic kidney disease paradigm, explaining important aspects such as prognostic markers, clinical assessments, and therapeutic options. The importance of the term gluconephrotic syndrome (GlucoNS) is emphasized, highlighting its significant influence on clinical evaluations, research procedures, screening techniques, and patient care. This term encapsulates nephrotic syndrome (NS) within the diabetic milieu, shedding light on the intricate relationship between renal complications and diabetes. GlucoNS necessitates a refined approach, considering the unique challenges posed by diabetes in the context of NS. With this review, we want to highlight how important it is to assess diabetes in every case of NS and how important it is to assess albuminuria in every diabetic patient.

Study on PINK1 Expression and Its Clinical Value in Diabetic Nephropathy.

INTRODUCTION: To explore PTEN-induced putative kinase 1 (PINK1) expression and its clinical value in diabetic nephropathy. METHODS: Ninety patients with diabetic nephropathy were recruited and divided into metformin hydrochloride monotherapy group, telmisartan monotherapy group and combination therapy (metformin and telmisartan) group. Renal function indices and PINK1 expression, inflammatory factors, reactive oxygen species (ROS), mitochondrial membrane potential (MMP) levels were detected. The correlation between PINK1 and inflammatory factors, renal function indicators including estimated glomerular filtration rate (eGFR), urinary albumin-to-creatinine ratio (UACR) and serum creatinine (SCr)] were analyzed by Pearson correlation. RESULTS: Following treatments, the combination therapy group exhibited increased PINK1 expression levels and decreased ROS levels compared to the groups receiving metformin hydrochloride or telmisartan monotherapy. The combination therapy group showed significant improvements in renal function indices and inflammatory markers. Additionally, the MMP ratio in the combination therapy group was higher compared to the two monotherapy groups. Furthermore, PINK1 was negatively correlated with UACR, SCr, tumor necrosis factor (TNF-α) and interleukin-6 (IL-6), while positively correlated with eGFR and interleukin-2 (IL-2). CONCLUSION: PINK1 exhibits low expression levels in patients with diabetic nephropathy and its expression is strongly associated with the inhibition of disease progression, thereby offering significant clinical diagnostic value. Additionally, it may serve as a potential biological marker for clinical diagnosis and treatment of diabetic nephropathy.

Integrin subunit beta 6 is a potential diagnostic marker for acute kidney injury in patients with diabetic kidney disease: a single cell sequencing data analysis.

BACKGROUND: Diabetic kidney disease (DKD), a prevalent complication of diabetes mellitus, is often associated with acute kidney injury (AKI). Thus, the development of preventive and therapeutic strategies is crucial for delaying the progression of AKI and DKD. METHODS: The GSE183276 dataset, comprising the data of 20 healthy controls and 12 patients with AKI, was downloaded from the Gene Expression Omnibus (GEO) database to analyze the AKI group. For analyzing the DKD group, the GSE131822 dataset, comprising the data of 3 healthy controls and 3 patients with DKD, was downloaded from the GEO database. The common differentially expressed genes (DEGs) in renal tubular epithelial cells (TECs) were subjected to enrichment analyses. Next, a protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes database to analyze gene-related regulatory networks. Finally, the AKI animal models and the DKD and AKI cell models were established, and the reliability of the identified genes was validated using quantitative real-time polymerase chain reaction analysis. RESULTS: Functional analysis was performed with 40 common DEGs in TECs. Eight hub genes were identified using the PPI and gene-related networks. Finally, validation experiments with the in vivo animal model and the in vitro cellular model revealed the four common DEGs. Four DEGs that share molecular mechanisms in the pathogenesis of DKD and AKI were identified. In particular, the expression of Integrin Subunit Beta 6(ITGB6), a hub and commonly upregulated gene, was upregulated in the in vitro models. CONCLUSION: ITGB6 may serve as a biomarker for early AKI diagnosis in patients with DKD and as a target for early intervention therapies.

Significance of pyroptosis-related genes in the diagnosis and classification of diabetic kidney disease.

OBJECTIVE: This study aimed to identify the potential biomarkers associated with pyroptosis in diabetic kidney disease (DKD). METHODS: Three datasets from the Gene Expression Omnibus (GEO) were downloaded and merged into an integrated dataset. Differentially expressed genes (DEGs) were filtered and intersected with pyroptosis-related genes (PRGs). Pyroptosis-related DEGs (PRDEGs) were obtained and analyzed using functional enrichment analysis. Random forest, Least Absolute Shrinkage and Selection Operator, and logistic regression analyses were used to select the features of PRDEGs. These feature genes were used to build a diagnostic prediction model, identify the subtypes of the disease, and analyze their interactions with transcription factors (TFs)/miRNAs/drugs and small molecules. We conducted a comparative analysis of immune cell infiltration at different risk levels of pyroptosis. qRT-PCR was used to validate the expression of the feature genes. RESULTS: A total of 25 PRDEGs were obtained. These genes were coenriched in biological processes and pathways, such as the regulation of inflammatory responses. Five key genes (CASP1, CITED2, HTRA1, PTGS2, S100A12) were identified and verified using qRT-PCR. The diagnostic model based on key genes has a good diagnostic prediction ability. Five key genes interacted with TFs and miRNAs in 67 and 80 pairs, respectively, and interacted with 113 types of drugs or molecules. Immune infiltration of samples with different pyroptosis risk levels showed significant differences. Thus, CASP1, CITED2, HTRA1, PTGS2 and S100A12 are potential DKD biomarkers. CONCLUSION: Genes that regulate pyroptosis can be used as predictors of DKD. Early diagnosis of DKD can aid in its effective treatment.

Artificial Intelligence-Assisted Perfusion Density as Biomarker for Screening Diabetic Nephropathy.

Purpose: To identify a reliable biomarker for screening diabetic nephropathy (DN) using artificial intelligence (AI)-assisted ultra-widefield swept-source optical coherence tomography angiography (UWF SS-OCTA). Methods: This study analyzed data from 169 patients (287 eyes) with type 2 diabetes mellitus (T2DM), resulting in 15,211 individual data points. These data points included basic demographic information, clinical data, and retinal and choroidal data obtained through UWF SS-OCTA for each eye. Statistical analysis, 10-fold cross-validation, and the random forest approach were employed for data processing. Results: The degree of retinal microvascular damage in the diabetic retinopathy (DR) with the DN group was significantly greater than in the DR without DN group, as measured by SS-OCTA parameters. There were strong associations between perfusion density (PD) and DN diagnosis in both the T2DM population (r = -0.562 to -0.481, P < 0.001) and the DR population (r = -0.397 to -0.357, P < 0.001). The random forest model showed an average classification accuracy of 85.8442% for identifying DN patients based on perfusion density in the T2DM population and 82.5739% in the DR population. Conclusions: Quantitative analysis of microvasculature reveals a correlation between DR and DN. UWF PD may serve as a significant and noninvasive biomarker for evaluating DN in patients through deep learning. AI-assisted SS-OCTA could be a rapid and reliable tool for screening DN. Translational Relevance: We aim to study the pathological processes of DR and DN and determine the correspondence between their clinical and pathological manifestations to further clarify the potential of screening DN using AI-assisted UWF PD.

Urinary cyclophilin A as an early marker of chronic kidney disease with underlying type 2 diabetes.

Cyclophilin A (CypA) is a novel renal inflammation biomarker, with levels altered in various diseases, particularly in patients with diabetes mellitus (DM) and kidney damage. This study aimed to investigate the correlation between urinary cyclophilin A (uCypA) and chronic kidney disease (CKD) conditions with and without type 2 diabetes mellitus (T2DM) using an in-house enzyme-linked immunoassay (ELISA) method. A uCypA strip-test prototype was also developed. An indirect ELISA was performed to determine the uCypA levels. A 0.48 µg/mL uCypA cutoff differentiated healthy patients from those with early-stage CKD (stages I and II). The uCypA levels were significantly increased in patients with progression of renal deterioration, especially in the T2DM with late-stage CKD group, compared to the control group. Fasting blood sugar (FBS), estimated glomerular filtration rate (eGFR), albumin/creatinine ratio, and metformin use were associated with uCypA levels. Multinomial logistic regression analysis revealed an association between uCypA levels and T2DM diagnosed for over five years and early-stage CKD. This finding shows that uCypA could be used as a biomarker for distinguishing early-stage CKD as well as T2DM complications, which is beneficial for patients to be aware of their health status and change their behavior to slow kidney deterioration.

External validation and calibration of risk equations for prediction of diabetic kidney diseases among patients with type 2 diabetes in Taiwan.

BACKGROUND: Most existing risk equations for predicting/stratifying individual diabetic kidney disease (DKD) risks were developed using relatively dated data from selective and homogeneous trial populations comprising predominately Caucasian type 2 diabetes (T2D) patients. We seek to adapt risk equations for prediction of DKD progression (microalbuminuria, macroalbuminuria, and renal failure) using empiric data from a real-world population with T2D in Taiwan. METHODS: Risk equations from three well-known simulation models: UKPDS-OM2, RECODe, and CHIME models, were adapted. Discrimination and calibration were determined using the area under the receiver operating characteristic curve (AUROC), a calibration plot (slope and intercept), and the Greenwood-Nam-D'Agostino (GND) test. Recalibration was performed for unsatisfactory calibration (p-value of GND test < 0.05) by adjusting the baseline hazards of risk equations to address risk variations among patients. RESULTS: The RECODe equations for microalbuminuria and macroalbuminuria showed moderate discrimination (AUROC: 0.62 and 0.76) but underestimated the event risks (calibration slope > 1). The CHIME equation had the best discrimination for renal failure (AUROCs from CHIME, UKPDS-OM2 and RECODe: 0.77, 0.60 and 0.64, respectively). All three equations overestimated renal failure risk (calibration slope < 1). After rigorous updating, the calibration slope/intercept of the recalibrated RECODe for predicting microalbuminuria (0.87/0.0459) and macroalbuminuria (1.10/0.0004) risks as well as the recalibrated CHIME equation for predicting renal failure risk (0.95/-0.0014) were improved. CONCLUSIONS: Risk equations for prediction of DKD progression in real-world Taiwanese T2D patients were established, which can be incorporated into a multi-state simulation model to project and differentiate individual DKD risks for supporting timely interventions and health economic research.

Profiling of five urinary exosomal miRNAs for the differential diagnosis of patients with diabetic kidney disease and focal segmental glomerulosclerosis.

OBJECTIVE: The objective of this study is to investigate the diagnostic utility of microRNAs (miRNAs) for distinguishing between urine samples from patients with Diabetic Kidney Disease (DKD) and those with Focal Segmental Glomerulosclerosis (FSGS). METHODS: In this multicentric, cross-sectional investigation, we enrolled patients diagnosed with DKD, individuals with primary biopsy-proven FSGS, and healthy controls. The top 5 miRNAs (hsa-mir-21, hsa-mir-30a, hsa-mir-193a, hsa-mir-196a, hsa-mir-200a) were selected to quantify miRNAs in urine samples. Isolation of targeted miRNAs was performed from urinary exosomes, and the quantitative profile of the isolated miRNAs was measured by RT-qPCR. The ΔΔCt method was implemented to calculate the fold differences between disease and control samples. RESULTS: Thirteen DKD patients, 11 FSGS patients, and 14 healthy controls were included in this study. Hsa-mir-21 and hsa-mir-30a exhibited distinct regulation in both groups, with upregulation observed in FSGS and downregulation in DKD (hsa-mir-21 in DKD (0.668 ± 0.25, p < 0.0005) and FSGS (2.267 ± 1.138, p < 0.0077); hsa-mir-30a in DKD (0.874 ± 0.254, p = 0.079) and FSGS (1.378 ± 0.312, p < 0.0006)). Hsa-mir-193a exhibited significant dysregulation in DKD (1.017 ± 0.413, p < 0.029) but not in FSGS (4.18 ± 1.528, p = 0.058). Hsa-mir-196a and hsa-mir-200a showed upregulation in patient groups (hsa-mir-196a in DKD (1.278 ± 0.527, p = 0.074) and FSGS (2.47 ± 0.911, p < 0.0003); hsa-mir-200a in DKD (1.909 ± 0.825, p = 0.082) and FSGS (1.301 ± 0.358, p < 0.008)). CONCLUSION: Specific miRNAs, particularly miR-21, miR-30a, miR-196a, and miR-200a, might play a role in the pathogenesis of kidney diseases and could potentially serve as biomarkers to distinguish between FSGS and DKD patients.

Prognostic impact of switching to the 2021 chronic kidney disease epidemiology collaboration creatinine-based equation in Caucasian patients with type 2 diabetes: the Renal Insufficiency and Cardiovascular events (RIACE) Italian Multicenter Study.

BACKGROUND: A Chronic Kidney Disease (CKD) Epidemiology Collaboration (EPI) formula not including a Black race coefficient has been recently developed and is now recommended in the US. The new (2021) equation was shown to yield higher estimated glomerular filtration rate (eGFR) values than the old (2009) one in a non-Black general population sample, thus reclassifying a significant number of individuals to a better eGFR category. However, reclassified individuals were previously shown to have a lower risk of progression to end-stage kidney disease, but higher adjusted risks for all-cause death and morbidity and mortality from cardiovascular disease than those not reclassified. This study evaluated the prognostic impact of switching from the 2009 to the 2021 CKD-EPI equation in non-Black individuals with type 2 diabetes. METHODS: The Renal Insufficiency And Cardiovascular Events (RIACE) was a prospective cohort study enrolling 15,773 Caucasian patients in 19 Italian centers in 2006-2008. Cardiometabolic risk profile, treatments, complications, and comorbidities were assessed at baseline and eGFR was calculated with the two equations. Vital status was retrieved on 31 October 2015 for 15,656 participants (99.3%). RESULTS: With the 2021 equation, the eGFR value increased in all patients, except for 293 individuals with a 2009 eGFR ≥ 105 ml·min- 1·1.73 m- 2. The median difference was 4.10 ml·min- 1·1.73 m- 2 and was higher in males, older individuals and those in the G2 category. Reclassification decreased the percentage of patients with reduced eGFR from 17.28 to 13.96% and with any CKD from 36.23 to 34.03%. Reclassified individuals had better cardiometabolic risk profile and lower prevalence of complications and use of medications than non-reclassified individuals. Risk of death versus the 2009 G1 category was lower for reclassified than non-reclassified participants in all eGFR categories and, particularly, in each 2009 eGFR category, though difference was significant only in the G4-G5 category. The Receiver Operator Characteristic curves were statistically, but not clinically different with the two equations. CONCLUSION: Changing from the 2009 to the 2021 CKD-EPI equation results in higher eGFR and lower CKD prevalence, with a lower risk of death in reclassified patients with an eGFR < 30 ml·min- 1·1.73 m- 2, but virtually no impact on mortality prediction. TRIAL REGISTRATION: ClinicalTrials.gov, NCT00715481, retrospectively registered 15 July, 2008.

Associations of the TyG index with albuminuria and chronic kidney disease in patients with type 2 diabetes.

OBJECTIVE: Diabetes-related kidney disease reduces patients' quality of life, increases the risk of death, and is associated with insulin resistance (IR). The triglyceride-glucose (TyG) index is a simple and inexpensive alternative to IR measurement. Furthermore, the relationship between albuminuria and chronic kidney disease (CKD) in type 2 diabetes mellitus (T2DM) remains unclear. Therefore, we aimed to investigate the association of TyG index with albuminuria and CKD in patients with T2DM. METHODS: Data from 01/2013-12/2017 period were obtained from the Population Health Data Archive's Diabetes Complications Data Set. A total of 1048 patients with T2DM were included in this study. CKD is defined as an estimated glomerular filtration rate < 60 ml/min-1.1.73 m-2 or a urinary albumin-to-creatinine ratio (UACR) ≥ 30 mg/g. Albuminuria is defined as a UACR ≥ 30 mg/g. The TyG index is calculated by measuring the triglyceride and fasting blood glucose levels. Logistic regression models were used to analyze the association between albuminuria, CKD with T2DM and TyG index. RESULTS: We identified 1048 subjects, 63.03% of whom were men. The mean age was 46.21 years, and the mean body mass index was 26.742 kg/m2. CKD and albuminuria detection rates showed an increasing trend in the different TyG subgroups. (p = 0.008, p = 0.006). Using the Q1 group as a baseline, the risk of albuminuria and CKD was significantly greater in the group Q3 (OR = 1.514, 95% CI 1.121-2.047 P = 0.05), and the same result was obtained after adjusting for covariates (OR = 2.241, 95% CI 1.245-4.034, P = 0.007). Subgroup analyses revealed a significant increase in the incidence of albuminuria and CKD in the group Q3 compared to that in the Q1 group. CONCLUSIONS: The TyG index is positively associated with albuminuria and CKD in patients with T2DM and may be a marker for predicting the occurrence of early kidney injury in patients with T2DM. Clinicians should test this indicator early to detect lesions and improve patient prognosis.

Excessive occupational sitting increases risk of cardiovascular events among working individuals with type 1 diabetes in the prospective Finnish Diabetic Nephropathy Study.

BACKGROUND: Sedentary behavior, such as excessive sitting, increases risk of cardiovascular disease and premature mortality in the general population, but this has not been assessed in type 1 diabetes. Occupational sitting is increasingly ubiquitous and often constitutes the largest portion of daily sitting time. Our aim was to identify clinical factors associated with excessive occupational sitting in type 1 diabetes and, in a prospective setting, to explore its association with cardiovascular events and all-cause mortality, independent of leisure-time physical activity. METHODS: An observational follow-up study of 1,704 individuals (mean age 38.9 ± 10.1 years) from the Finnish Diabetic Nephropathy Study. Excessive occupational sitting, defined as ≥ 6 h of daily workplace sitting, was assessed using a validated self-report questionnaire. Data on cardiovascular events and mortality were retrieved from national registries. Multivariable logistic regression identified independently associated factors, while Kaplan-Meier curves and Cox proportional hazard models were used for prospective analyses. RESULTS: Factors independently and positively associated with excessive occupational sitting included a high occupational category [OR 6.53, 95% CI (4.09‒10.40)] and older age [1.02 (1.00‒1.03)], whereas negatively associated factors included current smoking [0.68 (0.50‒0.92)], moderate albuminuria [0.55 (0.38‒0.80)], and high leisure-time physical activity [0.52 (0.36‒0.74)]. During a median follow-up of 12.5 (6.5-16.4) years, 163 individuals (9.6%) suffered cardiovascular events, and during a median follow-up of 13.7 (9.4-16.6) years, 108 (6.3%) deaths occurred. Excessive occupational sitting increased cardiovascular event risk (hazard ratio [HR] 1.55 [95% CI 1.10‒2.18]) after adjustment for confounders and other covariates. Furthermore, in a stratified multivariable analysis among current smokers, excessive occupational sitting increased the risk of all-cause mortality (2.06 [1.02‒4.20]). CONCLUSIONS: Excessive occupational sitting is associated with a higher risk of cardiovascular events and all-cause mortality in individuals with type 1 diabetes. This association persists regardless of leisure-time physical activity, after adjusting for independently associated variables identified in our cross-sectional analyses. These findings underscore the need to update physical activity guidelines to better address sedentary behavior and improve outcomes for individuals with type 1 diabetes. Targeting occupational sitting should be considered a key focus for interventions aimed at reducing overall sedentary time.

Identification and validation of key extracellular proteins as the potential biomarkers in diabetic nephropathy.

OBJECTIVE: Accumulation of extracellular matrix (ECM) proteins in the glomerular mesangial region is a typical hallmark of diabetic nephropathy (DN). However, the molecular mechanism underlying ECM accumulation in the mesangium of DN patients remains unclear. The present study aims to establish a connection between extracellular proteins and DN with the goal of identifying potential biomarkers for this condition. METHODS: Differentially expressed genes (DEGs) between DN kidney tissue and healthy kidney tissue were analyzed using the public data GSE166239. Two gene lists encoding extracellular proteins were then utilized to identify extracellular protein-differentially expressed genes (EP-DEGs). Functional enrichment analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, were performed on these EP-DEGs. A protein-protein interaction (PPI) network was established to identify key EP-DEGs. Furthermore, the diagnostic ability, immune cell infiltration, and clinical relevance of these EP-DEGs were investigated. Immunohistochemistry (IHC) staining of paraffin-embedded renal tissues was performed to validate the accuracy of the bioinformatic results. RESULTS: A total of 1204 DEGs were identified, from which 162 EP-DEGs were further characterized by overlapping with extracellular protein gene lists. From the PPI network analysis, five EP-DEGs (e.g., TNF, COL1A1, FN1, MMP9, and TGFB1) were identified as candidate biomarkers. TNF, COL1A1, and MMP9 had a high diagnostic accuracy for DN. Assessment of immune cell infiltration revealed that the expression of TNF was positively associated with resting dendritic cells (DCs) (r = 0.85, P < 0.001) and M1 macrophages (r = 0.62, P < 0.05), whereas negatively associated with regulatory T cells (r = - 0.62, P < 0.05). Nephroseq v5 analysis demonstrated a negative correlation between the estimated glomerular filtration rate (eGFR) and TNF expression (r = - 0.730, P = 0.025). Gene set enrichment analysis (GSEA) revealed significant enrichment of glycosaminoglycan (GAG) degradation in the high-TNF subgroup. IHC staining of renal tissues confirmed significantly elevated TNF-a expression and decreased hyaluronic acid (HA) levels in the DN group compared to controls (both P < 0.05), with a negative correlation observed between TNF-a and HA (r = - 0.691, P = 0.026). CONCLUSION: Our findings suggest that TNF may play a pivotal role in the progress of DN by driving ECM accumulation, and this process might involve GAG degradation pathway activation.

Endothelial dysfunction markers syndecan-1 and thrombomodulin are associated with higher albuminuria levels in type 2 diabetes with no history of clinical cardiovascular disease.

INTRODUCTION: Individuals with type 2 diabetes and increased albuminuria, a well-established marker of microvascular complications, are at a higher risk for cardiovascular disease (CVD) and premature mortality. Therefore, a better understanding of the underlying pathophysiology is needed to improve risk stratification and tailor prevention and intervention. METHODS: We conducted a cross-sectional study including 463 individuals with type 2 diabetes, various degrees of albuminuria and without CVD. We analysed the association between albuminuria and markers of endothelial function (thrombomodulin and syndecan-1), thrombin generation (thrombin-antithrombin complex, prothrombin fragment 1 + 2), fibrinogen, platelet function (activation using soluble plasma selectin and aggregation using Multiplate® Analyzer) using regression models. RESULTS: In the study cohort 33 % were women, the mean ± SD age was 65 ± 9 years, and median [IQR] diabetes duration was 15 [9-20] years. In total, 344 (74 %) individuals had normal albuminuria, 87 (19 %) moderately- and 32 (7 %) severely increased albuminuria levels. Higher markers of endothelial function and fibrinogen were independently associated with higher albuminuria levels (p < 0.01). No association between albuminuria and markers of thrombin generation and platelet was demonstrated. CONCLUSION: We demonstrated an independent association between albuminuria and markers of endothelial function and fibrinogen in individuals with type 2 diabetes and no history of CVD.

VCAM1: an effective diagnostic marker related to immune cell infiltration in diabetic nephropathy.

Introduction: The role of immune cells in the pathogenesis and advancement of diabetic nephropathy (DN) is crucial. The objective of this study was to identify immune-cell-related biomarkers that could potentially aid in the diagnosis and management of DN. Methods: The GSE96804 dataset was obtained from the Gene Expression Omnibus (GEO) database. Then, screen for intersections between differentially expressed genes (DEGs) and immune-related genes (IRGs). Identify core genes through protein-protein interaction (PPI) networks and the Cytoscape plugin. Subsequently, functional enrichment analysis was conducted. In addition, ROC analysis is performed to accurately identify diagnostic biomarkers. Apply the CIBERSORT algorithm to evaluate the proportion of immune cell infiltration. Finally, the mRNA, protein, and immunofluorescence expression of the biomarker was validated in the DN rat model. Results: The study yielded 74 shared genes associated with DN. Enrichment analysis indicated significant enrichment of these genes in focal adhesion, the humoral immune response, activation of the immune response, Cytokine-cytokine receptor interaction, and IL-17 signaling pathway. The optimal candidate gene VCAM1 was identified. The presence of VCAM1 in DN was further validated using the ROC curve. Analysis of immune cell infiltration matrices revealed a high abundance of monocytes, naïve B cells, memory B cells, and Macrophages M1/M2 in DN tissues. Correlation analysis identified one hub biomarker associated with immune-infiltrated cells in DN. Furthermore, our findings were validated through in vivo RT qPCR, WB, and IF techniques. Conclusions: Our research indicates that VCAM1 is a signature gene associated with DN and is linked to the progression, treatment, and prognosis of DN. A comprehensive examination of immune infiltration signature genes may offer new perspectives on the clinical diagnosis and management of DN.

Vision loss and diabetic retinopathy prevalence and risk among a cohort of Indigenous and non-Indigenous Australians with type 2 diabetes receiving renal haemodialysis treatment: The retinopathy in people currently on renal dialysis (RiPCORD) study.

AIMS: Diabetic nephropathy, vision loss and diabetic retinopathy (DR) are frequent comorbidities among individuals with type 2 diabetes (T2D). The Retinopathy in People Currently On Renal Dialysis (RiPCORD) study sought to examine the epidemiology and risk of vision impairment (VI) and DR among a cohort of Indigenous and non-Indigenous Australians with T2D currently receiving haemodialysis for end-stage renal failure (ESRF). METHODS: A total of 106 Indigenous and 109 non-Indigenous Australians were recruited in RiPCORD across five haemodialysis centres in urban and remote settings. Clinical assessments, questionnaires and medical record data determined the rates of ocular complications and risk factor profiles. RESULTS: Prevalence rates include unilateral VI, 23.5 %; bilateral VI, 11.7 %; unilateral blindness, 14.2 %; and bilateral blindness, 3.7 %, with no significant differences between sub-cohorts (p=0.30). DR prevalence rates were 78.0 % among non-Indigenous Australians and 93.1 % among Indigenous Australians (p=<0.001). Non-Indigenous ethnicity (OR: 0.28) and pre-dialysis diastolic blood pressure (OR: 0.84 per 10-mmHg) were protective, while peripheral vascular disease (OR: 2.79) increased DR risk. CONCLUSIONS: Ocular complications among individuals with T2D and ESRF are disproportionately high, especially for Indigenous Australians, and beyond what can be accounted for by risk factor variation. Findings suggest a need to improve screening and preventative efforts within this high-risk population group.

The correlation between patients with type 2 diabetes mellitus and chronic microvascular complications during the glucose peak time.

INTRODUCTION: To assess the Type 2 Diabetes Mellitus (T2DM) patients in association with Chronic Microvascular Complications at Glucose Peak Time and the association among chronic microvascular complications in T2DM patients and the glucose peak period in the typical steamed bread meal test. METHODS: Overall 1095 T2DM patients were classified as three groups: (1) Group G1: glucose peak time ≤ 1 h (n = 84), Group G2: 1 h < glucose peak time ≤ 2 h (n = 648) and Group G3: glucose peak time > 2 h (n = 363). The clinical characteristics, insulin characteristics and glucose peak time and chronic microvascular complications markers of patients in each group was analyzed and compared. Statistical analyses were performed using SPSS 23.0, employing chi-square tests, Kruskal-Wallis tests, one-way ANOVA, and binary logistic regression analysis, with significance set at P < 0.05. RESULTS: Age, length of disease, glycated hemoglobin (HbA1c), urine albumin-creatinine ratio (UACR), and the number of patients with diabetic retinopathy (DR) increased (all P < 0.05) in those with postponed glucose peak time, while insulinogenic indexes, the AUC for C-p (AUCC-p), fasting, and 120-min C-peptide (C-p) decreased (all P < 0.05). Only age was connected to patients with diabetic kidney disease (DKD) independently in binary logistic regression analysis, although delayed glucose peak time was related to the presence of patients with DR. (all P < 0.05). CONCLUSION: Delayed glucose peak time contributed to DR. Attention should be paid to condition of chronic microvascular complications in T2DM patients with a postponed peak glucose timing.

Classification of longitudinal estimated glomerular filtration rate trajectories in Canadian adults with type 1 diabetes.

AIMS: Type 1 diabetes (T1D) increases the risk of chronic kidney disease (CKD) development. The aims of this study were to classify trajectories of estimated glomerular filtration rate (eGFR) in a cohort of Canadian adults with T1D, and to describe the risk factors associated with declining eGFR trajectories. METHODS: In this retrospective cohort of adults with T1D, data was collected between 1996 and 2020. CKD was defined as eGFR <60 mL/min/1.73 m2. Latent class mixed models were used to categorize eGFR trajectories. Multinomial logistic regression was used to identify factors associated with declining eGFR trajectories. RESULTS: In this study, 304 adults were analyzed, with baseline measurements at a median duration of T1D of 15.3 (5.4-24.2) years. Eight percent of the cohort developed CKD over a median duration of 24.3 (13.7-34.8) years. Four classes of longitudinal eGFR trajectories were identified, broadly categorized as steeply declining (SD1, SD2) and gradual declining (GD1, GD2). Female sex, poor glycemic control, elevated body mass index, and albuminuria were associated with a steeply declining trajectory. CONCLUSION: In this cohort, four distinctive eGFR trajectories were identified, including a subtype with steeply declining eGFR. Given the complex nature of CKD progression, further prospective study of this model for identification of individuals at risk for CKD based on their trajectory of kidney function may support clinicians in their decision-making.

Altered oxidant and antioxidant levels are associated with vascular stiffness and diabetic kidney disease in type 1 diabetes after exposure to acute and chronic hyperglycemia.

BACKGROUND: Hyperglycemia-induced oxidative stress is a well-established pathological mediator of vascular complications in diabetes. We assessed plasma oxidant and antioxidant levels in response to acute and chronic hyperglycemia in relation to vascular stiffness and varying degrees of kidney disease in type 1 diabetes individuals. METHODS: The acute hyperglycemia study included 22 type 1 diabetic individuals with normal albumin excretion rate (AER) and 13 non-diabetic controls. These individuals received an acute glucose challenge during a 120-minute hyperglycemic clamp. The chronic hyperglycemia study included 118 type 1 diabetic individuals with chronically low (n = 60) or high (n = 58) HbA1c concentrations and varying degrees of diabetic kidney disease (DKD) classified as normal, moderate, or severe albuminuria (AER). Levels of malondialdehyde (MDA), reactive oxygen metabolites (ROMs), total antioxidant capacity (TAC), biological antioxidant potential (BAP) and superoxide dismutase (SOD) were measured from plasma or serum samples in the FinnDiane study. RESULTS: Levels of MDA (p < 0.01) and ROMs (p < 0.01) were elevated in type 1 diabetes individuals compared to non-diabetic controls at baseline. Acute hyperglycemia further increased MDA levels (p < 0.05) and sustained the elevation of ROMs in type 1 diabetes individuals. Acute hyperglycemic challenge impaired TAC in both non-diabetic (p < 0.05) and type 1 diabetes (p < 0.01) individuals compared to baseline whereas BAP was increased (p < 0.05) with no difference observed in non-diabetic controls. There was a positive association between high circulating MDA and AIx (r2 = 0.611, p = 0.05), and between delta ROMs and delta AIx (r2 = 0.955, p = 0.014) in combined analysis of individuals with type 1 diabetes and non-diabetic controls. Type 1 diabetes individuals with varying status of DKD, showed elevated levels of ROMs in those with high HbA1c compared to their counterpart with low HbA1c (p < 0.05). Individuals with severe albuminuria showed elevated ROM levels (p < 0.01) and depressed antioxidant capacity (p < 0.01) compared to those with normal AER of comparable HbA1c concentrations. CONCLUSIONS: Biomarkers of oxidative stress are associated with vascular stiffness and DKD following acute and chronic hyperglycemic exposure and may provide added value to HbA1c in understanding disease pathology, predicting risk and assessing the status of secondary complications of type 1 diabetes.

Identification of mitochondria-related genes as diagnostic biomarkers for diabetic nephropathy and their correlation with immune infiltration: New insights from bioinformatics analysis.

BACKGROUND: Diabetic nephropathy (DN) is a common and severe microvascular complication of diabetes. Mitochondrial dysfunction and immune inflammation are important factors in the pathogenesis of DN. However, the specific mechanisms and their intricate interactions in DN remain unclear. Besides, there are no effective specific predictive or diagnostic biomarkers for DN so far. Therefore, this study aims to elucidate the role of mitochondrial-related genes and their possibility as predictive or diagnostic biomarkers, as well as their crosstalk with immune infiltration in the progression of DN. METHODS: Based on the GEO database and limma R package, the differentially expressed genes (DEGs) of DN were identified. Mitochondrial-related DEGs (MitoDEGs) were then obtained by intersecting these DEGs with mitochondria-related genes from the MitoCarta 3.0 database. Subsequently, the candidate hub genes were further screened by gene co-expression network analysis (WGCNA), and verified mRNA levels of these genes by real-time quantitative PCR (qRT-PCR) in high-glucose-treated human proximal tubular (HK-2) cells. The verified hub genes were utilized to construct a combined diagnostic model for DN, with its diagnostic efficacy assessed across the GSE30122 and GSE96804 datasets. Additionally, the immune infiltration pattern in DN was assessed with the CIBERSORT algorithm, and the Nephroseq v5 database was used to analyze the correlation between hub genes and clinical features of DN. RESULTS: Seven mitochondria-related candidate hub genes were screened from 56 MitoDEGs. Subsequently, the expression levels of six of them, namely EFHD1, CASP3, AASS, MPC1, NT5DC2, and BCL2A1, exhibited significant inter-group differences in the HK-2 cell model. The diagnostic model based on the six genes demonstrated good diagnostic efficacy in both training and validation sets. Furthermore, correlation analysis indicated that EFHD1 and AASS, downregulated in DN, are positively correlated with eGFR and negatively with serum creatinine. Conversely, CASP3, NT5DC2, and BCL2A1, upregulated in DN, show opposite correlations. In addition, spearman analysis revealed that the six hub genes were significantly associated with the infiltration of immune cells, including M1 and M2 macrophages, mast cells, resting NK cells, gamma delta T cells, and follicular helper T cells. CONCLUSION: This study elucidated the characteristics of mitochondria-related genes and their correlation with immune cell infiltration in DN, providing new insights for exploring the pathogenesis of DN and facilitating the identification of new potential biomarkers and therapeutic targets.

Low estimated glomerular filtration rate and proteinuria among adult diabetic patients in a tertiary hospital in Eastern Uganda - a cross-sectional study.

BACKGROUND: Chronic kidney disease (CKD) is one of the most common complications of diabetes mellitus (DM). Diabetes mellitus contributes to about 66% of CKD cases globally. CKD results in increased morbidity and mortality and advanced stages often require kidney replacement therapy that is unaffordable for the majority of the patients. Developing countries have scanty data regarding CKD burden in diabetic patients. OBJECTIVES: This study aimed at determining the prevalence of low estimated glomerular filtration rate (eGFR) and proteinuria and associated clinical and socio-demographic factors among adult diabetic patients attending the diabetic clinic of Mbale Regional Referral Hospital (MRRH). METHODS: A cross-sectional study was conducted at the adult diabetic clinic of MRRH in Eastern Uganda. A total of 374 adult diabetic patients were enrolled. A urine sample for urine albumin creatinine ratio (UACR) determination and a venous blood sample for measurement of serum creatinine were obtained from each participant. The eGFR was determined using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation and CKD was staged according to the Kidney Disease Improving Global Outcomes (KDIGO) classification. RESULTS: A total of 318 (85%) participants had an eGFR of ≤ 60 mL/min/1.73m2, UACR of ≥ 30g/g, or both. Only 6.1% were aware. Age, duration of DM, hypertension, and dyslipidemia were associated with low eGFR and proteinuria. CONCLUSION: There is a high prevalence of low eGFR and proteinuria among DM patients, 85% of the participants had these markers of CKD and the majority of them were undiagnosed. Over half of the DM patients had an eGFR consistent with advanced CKD. Strengthening routine screening for CKD biomarkers and equipping DM clinics with more diagnostic resources is recommended.