The relationship between weight-adjusted-waist index and diabetic kidney disease in patients with type 2 diabetes mellitus.

Purpose: Obesity, particularly abdominal obesity, is seen as a risk factor for diabetic complications. The weight-adjusted-waist index (WWI) is a recently developed index for measuring adiposity. Our goal was to uncover the potential correlation between the WWI index and diabetic kidney disease (DKD) risk. Methods: This cross-sectional study included adults with type 2 diabetes mellitus (T2DM) who participated in the NHANES database (2007-2018). The WWI index was calculated as waist circumference (WC, cm) divided by the square root of weight (kg). DKD was diagnosed based on impaired estimated glomerular filtration rate (eGFR<60 mL/min/1.73m2), albuminuria (urinary albumin to urinary creatinine ratio>30 mg/g), or both in T2DM patients. The independent relationship between WWI index and DKD risk was evaluated. Results: A total of 5,028 participants with T2DM were included, with an average WWI index of 11.61 ± 0.02. As the quartile range of the WWI index increased, the prevalence of DKD gradually increased (26.76% vs. 32.63% vs. 39.06% vs. 42.96%, P<0.001). After adjusting for various confounding factors, the WWI index was independently associated with DKD risk (OR=1.32, 95%CI:1.12-1.56, P<0.001). The area under the ROC curve (AUC) of the WWI index was higher than that of body mass index (BMI, kg/m2) and WC. Subgroup analysis suggested that the relationship between the WWI index and DKD risk was of greater concern in patients over 60 years old and those with cardiovascular disease. Conclusions: Our findings suggest that higher WWI levels are linked to DKD in T2DM patients. The WWI index could be a cost-effective and simple way to detect DKD, but further prospective studies are needed to confirm this.

Diabetic kidney disease screening status and related factors: a cross-sectional study of patients with type 2 diabetes in six provinces in China.

OBJECTIVE: To understand the awareness and practice of diabetic kidney disease (DKD) or nephropathy screening among community-based patients with type 2 diabetes in six provinces and cities in China, and to analyse the related factors affecting screening practices. METHODS: From December 2021 to March 2022, a cross-sectional survey was conducted using a structured questionnaire in 6230 patients with type 2 diabetes aged 18 years and older. The content of the questionnaire includes three parts: the general situation of diabetic patients (gender, age, ethnicity, marriage, education, occupation, etc.), DKD screening practices, and the evaluation of DKD screening services. RESULTS: 89.70% of the patients had their fasting blood glucose measured every six months, 21.12% of the patients had their glycosylated hemoglobin measured every six months, and only 13.11% and 9.34% of the patients had a urine protein-creatinine ratio test and estimated glomerular filtration rate test every 12 months. The proportions of glycosylated hemoglobin, urine protein-creatinine ratio, and estimated glomerular filtration rate were relatively high in young, northern, highly educated, and long-duration type 2 diabetic patients. CONCLUSION: The results of this survey found that the proportion of urine protein-creatinine ratio testing, estimated glomerular filtration rate testing, and glycosylated hemoglobin testing in Chinese patients with type 2 diabetes was very low. Patients with type 2 diabetes in rural areas, southern areas, with low education level, and short course of disease have lower detection rates for DKD, and hence lower rates of prevention and treatment.

Association between lactate dehydrogenase and the risk of diabetic kidney disease in patients with type 2 diabetes.

Objective: This study aims to investigate the association between lactate dehydrogenase (LDH) and the risk of diabetic kidney disease (DKD) in patients with type 2 diabetes (T2D). Methods: The study enrolled patients with diagnosis of T2D between 2009 and 2018 from the National Nutrition and Health Examination Survey (NHANES) database. Demographic information, laboratory test, and diagnostic data were collected. Restricted cubic spline (RCS) plots were used to assess the dose-effect relationship between LDH levels and the risk of DKD in patients with T2D. Based on LDH levels, individuals were divided into higher and lower groups using dichotomy, and multivariate logistic regression analysis was conducted to explore the relationship between different LDH levels and the risk of DKD in T2D patients. Stratified analysis was performed to assess the consistency of the result. Results: A total of 4888 patients were included in the study, with 2976 (60.9%) patients without DKD and 1912 (39.1%) patients with DKD. RCS plots showed that the risk of DKD increased with increasing LDH levels. Multifactorial logistic regression analysis revealed that T2D patients with higher LDH levels had a 45% increased risk of DKD compared to those with lower LDH levels (OR=1.45; 95% CI: 1.11-1.89). Furthermore, each standard deviation increase in LDH level was associated with a 24% increase in DKD incidence among T2D patients (OR=1.24; 95% CI: 1.07-1.44). Stratified analysis consistently supported these findings. Conclusions: LDH can serve as a valuable biomarker for screening DKD in patients with T2D.

Association of the systemic immuno-inflammation index, neutrophil-to-lymphocyte ratio, and platelet-to-lymphocyte ratio with diabetic microvascular complications.

Background: The systemic immuno-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) are widely used and have been shown to be predictive indicators of various diseases. Diabetic nephropathy (DN), retinopathy (DR), and peripheral neuropathy (DPN) are the most prominent and common microvascular complications, which have seriously negative impacts on patients, families, and society. Exploring the associations with these three indicators and diabetic microvascular complications are the main purpose. Methods: There were 1058 individuals with type 2 diabetes mellitus (T2DM) in this retrospective cross-sectional study. SII, NLR, and PLR were calculated. The diseases were diagnosed by endocrinologists. Logistic regression and subgroup analysis were applied to evaluate the association between SII, NLP, and PLR and diabetic microvascular complications. Results: SII, NLR, and PLR were significantly associated with the risk of DN [odds ratios (ORs): 1.52, 1.71, and 1.60, respectively] and DR [ORs: 1.57, 1.79, and 1.55, respectively] by multivariate logistic regression. When NLR ≥2.66, the OR was significantly higher for the risk of DPN (OR: 1.985, 95% confidence interval: 1.29-3.05). Subgroup analysis showed no significant positive associations across different demographics and comorbidities, including sex, age, hypertension, HbA1c (glycated hemoglobin), and dyslipidemia. Conclusion: This study found a positive relationship between NLR and DN, DR, and DPN. In contrast, SII and PLR were found to be only associated with DN and DR. Therefore, for the diagnosis of diabetic microvascular complications, SII, NLR and PLR are highly valuable.

Secretory leukocyte protease inhibitor as a novel predictive biomarker in patients with diabetic kidney disease.

Background: Secretory leukocyte protease inhibitor (SLPI) is a multifunctional protein involved in the chronic inflammatory process, implicated in the pathogenesis of diabetic kidney disease (DKD). However, its potential as a diagnostic and prognostic biomarker of DKD has yet to be evaluated. This study explored the clinical utility of SLPI in the diagnosis and prognosis of renal endpoint events in patients with DKD. Methods: A multi-center cross-sectional study comprised of 266 patients with DKD and a predictive cohort study comprised of 120 patients with stage IV DKD conducted between December 2016 and January 2022. The clinical parameters were collected for statistical analysis, a multivariate Cox proportional hazards model was used to evaluate the independent risk factors for renal endpoints. Results: Serum SLPI levels gradually increased with DKD progression (p<0.01). A significant correlation was observed between serum SLPI levels and renal function in patients with DKD. The mean follow-up duration in this cohort study was 2.32 ± 1.30 years. Multivariate Cox regression analysis showed SLPI levels≥51.61ng/mL (HR=2.95, 95% CI[1.55, 5.60], p<0.01), 24h urinary protein levels≥3500 mg/24h (HR=3.02, 95% CI[1.66, 5.52], p<0.01), Alb levels<30g/l (HR=2.19, 95% CI[1.12, 4.28], p<0.05), HGB levels<13g/dl (HR=3.18, 95% CI[1.49, 6.80], p<0.01), and urea levels≥7.1 mmol/L (HR=8.27, 95% CI[1.96, 34.93], p<0.01) were the independent risk factors for renal endpoint events in DKD patients. Conclusions: Serum SLPI levels increased with DKD progression and were associated with clinical parameters of DKD. Moreover, elevated SLPI levels showed potential prognostic value for renal endpoint events in individuals with DKD. These findings validate the results of previous studies on SLPI in patients with DKD and provide new insights into the role of SLPI as a biomarker for the diagnosis and prognosis of DKD that require validation.

Clinical metabolomics characteristics of diabetic kidney disease: A meta-analysis of 1875 cases with diabetic kidney disease and 4503 controls.

AIMS: Diabetic Kidney Disease (DKD), one of the major complications of diabetes, is also a major cause of end-stage renal disease. Metabolomics can provide a unique metabolic profile of the disease and thus predict or diagnose the development of the disease. Therefore, this study summarises a more comprehensive set of clinical biomarkers related to DKD to identify functional metabolites significantly associated with the development of DKD and reveal their driving mechanisms for DKD. MATERIALS AND METHODS: We searched PubMed, Embase, the Cochrane Library and Web of Science databases through October 2022. A meta-analysis was conducted on untargeted or targeted metabolomics research data based on the strategy of standardized mean differences and the process of ratio of means as the effect size, respectively. We compared the changes in metabolite levels between the DKD patients and the controls and explored the source of heterogeneity through subgroup analyses, sensitivity analysis and meta-regression analysis. RESULTS: The 34 clinical-based metabolomics studies clarified the differential metabolites between DKD and controls, containing 4503 control subjects and 1875 patients with DKD. The results showed that a total of 60 common differential metabolites were found in both meta-analyses, of which 5 metabolites (p < 0.05) were identified as essential metabolites. Compared with the control group, metabolites glycine, aconitic acid, glycolic acid and uracil decreased significantly in DKD patients; cysteine was significantly higher. This indicates that amino acid metabolism, lipid metabolism and pyrimidine metabolism in DKD patients are disordered. CONCLUSIONS: We have identified 5 metabolites and metabolic pathways related to DKD which can serve as biomarkers or targets for disease prevention and drug therapy.

Physicians' Practices in Diabetic Nephropathy in Primary Healthcare Centers in Jazan City, Saudi Arabia, 2023.

Background and Objectives: Diabetes is one of the most common diseases dealt with by physicians in primary healthcare centers (PHCs). The disease is associated with macrovascular and microvascular complications, especially in those with long disease duration and uncontrolled diabetic nephropathy, which is one of the most common microvascular complications among diabetic patients. This investigation assessed the practices of physicians working at PHCs in terms of diabetic nephropathy screening, management, and referral. Materials and Methods: This study is a cross-sectional investigation targeting physicians working at PHCs in the Jazan region of Saudi Arabia between March and August of 2023. Data were collected via a self-administered questionnaire, which was distributed via online platforms. The questionnaire included sections measuring physicians' demographic data and associated factors regarding training, the availability of resources, and practices in diabetic nephropathy, including screening, management, and referral. Chi-squared tests were used to assess associations between the practices of physicians and the measured demographics. Result: A total of 234 physicians participated in the investigation. The median age of the participants was 35 years. The adherence level of practice toward diabetic nephropathy according to American Diabetes Association (ADA) guidelines ranged from 40 points (the highest adherence level of participants) to 19 points (the lowest adherence level of participants), with a median of 33 points. Higher adherence levels were noted among physicians in Saudi Arabia, physicians with higher education levels, physicians specializing as family physicians or diabetologists, physicians who reported attending online and on-site training at diabetic centers, physicians who reported continuous access to urine and serum creatinine tests, and physicians who reported continuous access to the American Diabetes Association guidelines (p < 0.05). Conclusions: There are several factors associated with the level of adherence in diabetic nephropathy practice, such as physicians' education level, specialty, training, and access to guidelines. The findings suggest the need for more training for PHC physicians in the care of patients affected by or at risk of diabetic nephropathy.

Serum high mobility group box 1 as a potential biomarker for the progression of kidney disease in patients with type 2 diabetes.

Background: As a damage-associated molecular pattern protein, high mobility group box 1 (HMGB1) is associated with kidney and systemic inflammation. The predictive and therapeutic value of HMGB1 as a biomarker has been confirmed in various diseases. However, its value in diabetic kidney disease (DKD) remains unclear. Therefore, this study aimed to investigate the correlation between serum and urine HMGB1 levels and DKD progression. Methods: We recruited 196 patients with type 2 diabetes mellitus (T2DM), including 109 with DKD and 87 T2DM patients without DKD. Additionally, 60 healthy participants without T2DM were also recruited as controls. Serum and urine samples were collected for HMGB1 analysis. Simultaneously, tumor necrosis factor receptor superfamily member 1A (TNFR-1) in serum and kidney injury molecule (KIM-1) in urine samples were evaluated for comparison. Results: Serum and urine HMGB1 levels were significantly higher in patients with DKD than in patients with T2DM and healthy controls. Additionally, serum HMGB1 levels significantly and positively correlated with serum TNFR-1 (R 2 = 0.567, p<0.001) and urine KIM-1 levels (R 2 = 0.440, p<0.001), and urine HMGB1 has a similar correlation. In the population with T2DM, the risk of DKD progression increased with an increase in serum HMGB1 levels. Multivariate logistic regression analysis showed that elevated serum HMGB1 level was an independent risk factor for renal function progression in patients with DKD, and regression analysis did not change in the model corrected for multiple variables. The restricted cubic spline depicted a nonlinear relationship between serum HMGB1 and renal function progression in patients with DKD (p-nonlinear=0.007, p<0.001), and this positive effect remained consistent across subgroups. Conclusion: Serum HMGB1 was significantly correlated with DKD and disease severity. When the HMGB1 level was ≥27 ng/ml, the risk of renal progression increased sharply, indicating that serum HMGB1 can be used as a potential biomarker for the diagnosis of DKD progression.

Determinants of non-diabetic kidney diseases in type 2 diabetic patients: Twenty years of single center experience.

BACKGROUND: Diabetic nephropathy is one of the most common complications associated with diabetes. However, non-diabetic kidney disease has been reported in patients with type 2 diabetes at varying incidence rates. The objective of our study is to investigate the occurrence, clinicopathological characteristics, and inflammatory markers linked to diabetic and non-diabetic nephropathy (NDN) in patients with type 2 diabetes mellitus (DM). Additionally, we aimed to explore the possibility of identifying non-diabetic pathology using different biopsy indications. MATERIALS AND METHODS: A total of 159 patients with type 2 DM who underwent renal biopsy at a tertiary care nephrology clinic between January 2000 and January 2022 were enrolled in the study. We collected comprehensive data, including patient demographics, co-morbidities, diabetes duration, renal biopsy indications and results, serological markers, renal function, diabetic retinopathy (DRP), full blood count, blood biochemistry, urinalysis, and inflammatory markers. Patients were categorized based on their biopsy indications, and their biopsy results were classified into three groups: isolated NDN, isolated diabetic nephropathy (DN), and mixed nephropathy with concurrent NDN. We evaluated the relationship between biopsy indications and accompanying pathologies and statistically assessed the likelihood of each biopsy indication detecting non-diabetic renal pathology. Additionally, differences in other data, including demographic and laboratory results and medical histories, among the three groups were investigated. RESULTS: The most frequent indication of renal biopsy was atypical presentations of nephrotic syndrome or nephrotic range proteinuria (ANS/ANP) in 25.1% of patients. Other indications included unexplained renal failure (URF) in 22.6%, atypical presentations of non-nephrotic range proteinuria (ANNP) in 18.2%, acute kidney injury or rapidly progressive kidney dysfunction (AKI/RPKD) in 16.9%, microscopic hematuria in 15.7%, URF with ANNP in 11.3%, and severe nephrotic range proteinuria (SNP) in 9.4%. Renal biopsy revealed isolated NDN in 64.8%, DN in 25.1%, and mixed nephropathy in 10.1% of patients. Primary glomerular diseases were the main non-diabetic renal pathology, predominantly focal segmental glomerulosclerosis (FSGS) (36.4%) followed by MN (10.6%) and IgA nephropathy (7.5%). In comparison with the isolated DN and mixed nephropathy groups, patients in the isolated NDN group had significantly shorter diabetes duration, fewer DRP, as well as lower serum creatinine and neutrophil-to-lymphocyte ratio (NLR). Multivariate logistic regression analysis revealed that presence of hematuria (OR 4.40; 95% CI 1.34 - 14.46, p = 0.014), acute nephrotic range proteinuria (OR 11.93; 95% CI 1.56 - 90.77, p = 0.017), and AKI/APKD (OR 41.08; 95% CI 3.40 - 495.39, p = 0.003) were strong predictors of NDN. Lower NLR (OR 0.77; 95% CI 0.60 - 0.98, p = 0.035), shorter duration of diabetes (OR 0.90; 95% CI 0.84 - 0.97, p = 0.010), and absence of DRP (OR 0.35; 95% CI 0.12 - 0.98, p = 0.046) were also found to be independent indicators of NDN. Receiver operating characteristic curve (ROC) analysis revealed a cut-off value of ≤ 3.01 for NLR (sensitivity of 63.1%, specificity of 63.5%) with regards to predicting non-diabetic renal pathology (p = 0.006). CONCLUSION: Renal biopsy findings in patients with type 2 DM highlight that the prevalence of NDN may be higher than assumed, as presented mainly in the form of primary glomerular disease. The presence of AKI/RPKD, hematuria, and ANS/ANP serves as a reliable indicator of non-diabetic renal pathology. In more ambiguous situations, factors such as a shorter duration of diabetes, absence of DRP, and a lower NLR value may assist clinicians in biopsy decision.

Co-differential genes between DKD and aging: implications for a diagnostic model of DKD.

Objective: Diabetic kidney disease (DKD) is a serious complication of diabetes mellitus (DM) that is closely related to aging. In this study, we found co-differential genes between DKD and aging and established a diagnostic model of DKD based on these genes. Methods: Differentially expressed genes (DEGs) in DKD were screened using GEO datasets. The intersection of the DEGs of DKD and aging-related genes revealed DKD and aging co-differential genes. Based on this, a genetic diagnostic model for DKD was constructed using LASSO regression. The characteristics of these genes were investigated using consensus clustering, WGCNA, functional enrichment, and immune cell infiltration. Finally, the expression of diagnostic model genes was analyzed using single-cell RNA sequencing (scRNA-seq) in DKD mice (model constructed by streptozotocin (STZ) injection and confirmed by tissue section staining). Results: First, there were 159 common differential genes between DKD and aging, 15 of which were significant. These co-differential genes were involved in stress, glucolipid metabolism, and immunological functions. Second, a genetic diagnostic model (including IGF1, CETP, PCK1, FOS, and HSPA1A) was developed based on these genes. Validation of these model genes in scRNA-seq data revealed statistically significant variations in FOS, HSPA1A, and PCK1 gene expression between the early DKD and control groups. Validation of these model genes in the kidneys of DKD mice revealed that Igf1, Fos, Pck1, and Hspa1a had lower expression in DKD mice, with Igf1 expression being statistically significant. Conclusion: Our findings suggest that DKD and aging co-differential genes are significant in DKD diagnosis, providing a theoretical basis for novel research directions on DKD.

Study of Neutrophil Gelatinase Associated Lipocalin and Kidney Injury Molecule-1 in Patients with Type 2 Diabetes Mellitus Nephropathy.

BACKGROUND: There is a need for accurate and rapid biomarkers for the early diagnosis of diabetic nephropathy (DN). We aimed to study the accuracy of urinary neutrophil gelatinase-associated lipocalin (uNGAL), urinary kidney injury molecule-1 (uKIM-1), and blood NGAL (bNGAL) in type 2 diabetics as biomarkers for diagnosis of DN. METHODS: The study was a retrospective case-control study that included 30 control subjects, 40 diabetics with normo-albuminuria < 30 mg/g and eGFR > 60 mL/minute/1.73 m2, and 30 diabetics with albuminuria > 30mg/g and eGFR < 60mL/minute/1.73 m2. Blood and urine samples were obtained to determine levels of bNGAL, uNAGAL, and uKIM1. RESULTS: There was a significant increase in bNGAL, uNGAL, uKIM 1, uNGAL/creatinine and uKIM 1/creatinine among diabetics with albuminuria compared to diabetics with normoalbuminuria and normal control (p < 0.001 for all markers). For diagnosis of early DN, both bNGAL and uKIM 1 had sensitivity and specificity of 100% for each at cutoff values of 322.5 pg/mL and 74.25 ng/mL, respectively. uNGAL had a sensitivity of 97.5% and a spec-ificity of 100% at a cutoff point of 565 ng/mL. uKIM1/creatinine at a cutoff of 51.2 had a sensitivity of 100% and specificity of 100%. CONCLUSIONS: The present study highlights the accuracy of urinary KIM1 and NGAL and blood NGAL as biomarkers for the diagnosis of nephropathy in the early stage of diabetic nephropathy. There were positive correlations with kidney function tests creatinine, blood urea nitrogen, and the presence of albuminuria.

Early choroidal and retinal changes detected by swept-source oct in type 2 diabetes and their association with diabetic kidney disease: a longitudinal prospective study.

BACKGROUND: To evaluate structural changes in retina and choroid in patients with type 2 diabetes (T2D) and their association with diabetic kidney disease (DKD). METHODS: T2D patients with mild or no diabetic retinopathy (DR) were followed for 3 years using structural SS-OCT and OCT angiography (OCT-A) taken every 6 months. Parameters were compared longitudinally and according to the DKD status on baseline. RESULTS: One hundred and sixty eyes from 80 patients were followed for 3 years, 72 with no DKD (nDKD) at baseline and 88 with DKD. Trend analysis of T2D showed significant thinning in GCL + and circumpapillary retinal fiber neural layer (cRFNL), choroid, and decreased vascular density (VD) in superficial plexus and central choriocapillaris with foveal avascular zone (FAZ) enlargement. Patients with no DKD on baseline presented more significant declines in retinal center and choroidal thickness, increased FAZ and loss of nasal and temporal choriocapillaris volume. In addition, the nDKD group had worse glycemic control and renal parameters at the end of the study. CONCLUSION: Our data suggests the potential existence of early and progressive neurovascular damage in the retina and choroid of patients with Type 2 Diabetes (T2D) who have either no or mild Diabetic Retinopathy (DR). The progression of neurovascular damage appears to be correlated with parameters related to glycemic control and renal damage.

Utilizing machine learning algorithms to identify biomarkers associated with diabetic nephropathy: A review.

Diabetic nephropathy (DN), a multifaceted disease with various contributing factors, presents challenges in understanding its underlying causes. Uncovering biomarkers linked to this condition can shed light on its pathogenesis and support the creation of new diagnostic and treatment methods. Gene expression data were sourced from accessible public databases, and Weighted Gene Co-expression Network Analysis (WGCNA)was employed to pinpoint gene co-expression modules relevant to DN. Subsequently, various machine learning techniques, such as random forest, lasso regression algorithm (LASSO), and support vector machine-recursive feature elimination (SVM-REF), were utilized for distinguishing DN cases from controls using the identified gene modules. Additionally, functional enrichment analyses were conducted to explore the biological roles of these genes. Our analysis revealed 131 genes showing distinct expression patterns between controlled and uncontrolled groups. During the integrated WCGNA, we identified 61 co-expressed genes encompassing both categories. The enrichment analysis highlighted involvement in various immune responses and complex activities. Techniques like Random Forest, LASSO, and SVM-REF were applied to pinpoint key hub genes, leading to the identification of VWF and DNASE1L3. In the context of DN, they demonstrated significant consistency in both expression and function. Our research uncovered potential biomarkers for DN through the application of WGCNA and various machine learning methods. The results indicate that 2 central genes could serve as innovative diagnostic indicators and therapeutic targets for this disease. This discovery offers fresh perspectives on the development of DN and could contribute to the advancement of new diagnostic and treatment approaches.

Identification and validation of immune and cuproptosis - related genes for diabetic nephropathy by WGCNA and machine learning.

Background: As the leading cause of chronic kidney disease, diabetic kidney disease (DKD) is an enormous burden for all healthcare systems around the world. However, its early diagnosis has no effective methods. Methods: First, gene expression data in GEO database were extracted, and the differential genes of diabetic tubulopathy were obtained. Immune-related genesets were generated by WGCNA and immune cell infiltration analyses. Then, differentially expressed immune-related cuproptosis genes (DEICGs) were derived by the intersection of differential genes and genes related to cuproptosis and immune. To investigate the functions of DEICGs, volcano plots and GO term enrichment analysis was performed. Machine learning and protein-protein interaction (PPI) network analysis helped to finally screen out hub genes. The diagnostic efficacy of them was evaluated by GSEA analysis, receiver operating characteristic (ROC) curve, single-cell RNA sequencing and the Nephroseq website. The expression of hub genes at the animal level by STZ -induced and db/db DKD mouse models was further verified. Results: Finally, three hub genes, including FSTL1, CX3CR1 and AGR2 that were up-regulated in both the test set GSE30122 and the validation set GSE30529, were screened. The areas under the curve (AUCs) of ROC curves of hub genes were 0.911, 0.935 and 0.922, respectively, and 0.946 when taking as a whole. Correlation analysis showed that the expression level of three hub genes demonstrated their negative relationship with GFR, while those of FSTL1 displayed a positive correlation with the level of serum creatinine. GSEA was enriched in inflammatory and immune-related pathways. Single-nucleus RNA sequencing indicated the main distribution of FSTL1 in podocyte and mesangial cells, the high expression of CX3CR1 in leukocytes and the main localization of AGR2 in the loop of Henle. In mouse models, all three hub genes were increased in both STZ-induced and db/db DKD models. Conclusion: Machine learning was combined with WGCNA, immune cell infiltration and PPI analyses to identify three hub genes associated with cuproptosis, immunity and diabetic nephropathy, which all have great potential as diagnostic markers for DKD and even predict disease progression.

The relationship between diabetic retinopathy and diabetic nephropathy in type 2 diabetes.

Context: Diabetic retinopathy (DR) and diabetic nephropathy (DN), are major microvascular complications of diabetes. DR is an important predictor of DN, but the relationship between the severity of DR and the pathological severity of diabetic glomerulopathy remains unclear. Objective: To investigate the relationship between severity of diabetic retinopathy (DR) and histological changes and clinical indicators of diabetic nephropathy (DN) in patients with type 2 diabetes mellitus (T2DM). Methods: Patients with T2DM (n=272) who underwent a renal biopsy were eligible. Severity of DR was classified as non-diabetic retinopathy, non-proliferative retinopathy, and proliferative retinopathy (PDR). Relationship between DN and DR and the diagnostic efficacy of DR for DN were explored. Results: DN had a higher prevalence of DR (86.4%) and DR was more severe. The sensitivity and specificity of DR in DN were 86.4% and 78.8%, while PDR was 26.4% and 98.5%, respectively. In DN patients, the severity of glomerular lesions (p=0.001) and prevalence of KW nodules (p<0.001) significantly increased with increasing severity of DR. The presence of KW nodules, lower hemoglobin levels, and younger age were independent risk factors associated with more severe DR in patients with DN. Conclusion: DR was a good predictor of DN. In DN patients, the severity of DR was associated with glomerular injury, and presence of KW nodules, lower hemoglobin levels and younger age were independent risk factors associated with more severe DR. Trial registration: ClinicalTrails.gov, NCT03865914.

Clinical significance of amphiregulin in patients with chronic kidney disease.

BACKGROUND: Amphiregulin (AREG) is a ligand of epidermal growth factor receptor (EGFR), which plays an important role in injury-induced kidney fibrosis. However, the clinical significance of serum soluble AREG in chronic kidney disease (CKD) is unclear. In this study, we elucidated the clinical significance of serum soluble AREG in CKD by analyzing the association of serum soluble AREG levels with renal function and other clinical parameters in patients with CKD. METHODS: In total, 418 Japanese patients with CKD were enrolled, and serum samples were collected for the determination of soluble AREG and creatinine (Cr) levels, and other clinical parameters. Additionally, these parameters were evaluated after 2 and 3 years. Moreover, immunohistochemical assay was performed ate AREG expression in the kidney tissues of patients with CKD. RESULTS: Soluble AREG levels were positively correlated with serum Cr (p < 0.0001). Notably, initial AREG levels were positively correlated with changes in renal function (ΔCr) after 2 (p < 0.0001) and 3 years (P = 0.048). Additionally, soluble AREG levels were significantly higher (p < 0.05) in patients with diabetic nephropathy or primary hypertension. Moreover, AREG was highly expressed in renal tubular cells in patients with advanced CKD, but only weakly expressed in patients with preserved renal function. CONCLUSION: Serum soluble AREG levels were significantly correlated with renal function, and changes in renal function after 2 and 3 years, indicating that serum soluble AREG levels might serve as a biomarker of renal function and renal prognosis in CKD.

Prevalence of chronic kidney disease in Tunisian diabetics: the TUN-CKDD survey.

BACKGROUND: In Tunisia, the prevalence of diabetes mellitus increased from 15.5% on 2016 to 23% by 2023. While Chronic Kidney Disease (CKD) stills the most dreaded complications of diabetes, studies on the prevalence of chronic kidney disease non-dialysis diet are scarce. The aim of this study was to assess the prevalence of chronic kidney disease among the Tunisian diabetic population based on investigators' specialty, demographic criteria (gender, age, duration of diabetes and geographic distribution) and diagnosis criteria (albuminuria and/or eGFR). METHODS: This observational, multicentric, and cross-sectional study enrolled all diabetic subjects from all regions of Tunisia with at least 3 months of follow-up before the inclusion date, from 09 January to 08 February 2023. CKD diagnosis was established based on the KDIGO guidelines. The study was carried out at medical departments and ambulatory clinics of different healthcare providers. Baseline data were collected by investigators using an electronic case report form (eCRF). Continuous variables were described by means, median, standard deviation, and quartiles. Categorical data were tabulated in frequencies and percentages. RESULTS: The overall prevalence of CKD among the 10,145 enrolled patients with diabetes mellitus was 38.7% with a 95%CI [37.8-39.6%]. 50.9% were male, with a mean age of 67.5 (± 11.3) years. The mean diabetes duration was 16.1 years (± 8.9). The highest CKD prevalence was noted among nephrologists (82.2%), while it was similar between the cardiologists and the primary care physicians (30.0%). CKD prevalence was highest among males (43.0% versus 35.1%) and increased proportionally with patients' age and diabetes duration. CKD was more frequent in the Mid-East Area when compared to other regions (49.9% versus 25.3 to 40.1% in other regions). Albuminuria was present within 6.6% of subjects with CKD, and it was found an estimated glomerular filtration rate (eGFR) < 60 ml/min/1.73 m² within 13.3% of subjects wit h CKD. 18.9% had both criteria. CONCLUSIONS: In Tunisia, CKD among diabetics had a prevalence of 38.7%, approaching European prevalence. The prevalence discrepancy worldwide of CKD can be improved with a larger population size and by implementing standardized practices.

The predictive value of miR-377 and phospholipase A2 in the early diagnosis of diabetic kidney disease and their relationship with inflammatory factors.

OBJECTIVE: The value of novel biomarkers for DKD has received increasing attention, and there is an urgent need for novel biomarkers with sensitivity, specificity and ability to detect kidney damage.miR-377 regulates many basic biological processes, plays a key role in tumor cell proliferation, migration and inflammation, and can also increase the expression of matrix proteins and fibronectin, leading to renal tubulointerstitial inflammation and renal fibrosis. Lipoprotein-associated phospholipase A2, as an inflammatory marker, is involved in the pathological process of microalbuminuria production and renal function decline, and is a predictive factor of microalbuminuria production and renal function decline, and can be used as an indicator to evaluate the progression of DKD.The aim of this study was to investigate the effects of miR-377 and phospholipase A2 on the development of diabetic kidney disease through regulation of inflammatory factors and the mechanism of action. METHODS: 80 diabetic patients were divided into two groups according to urinary albumin-to-creatinine ratio (UACR): diabetic normal proteinuria group (n = 42) and diabetic proteinuria group (n = 38). Forty-three healthy people were selected as the normal control group. The serum levels of TGF-ß, IL-6, and IL-18 were measured by ELISA, miR-377 was detected by qPCR, and the serum levels of phospholipase A2 were detected by electrochemiluminescence. Analyze the correlation of study group indicators, ROC curve was used to evaluate the diagnostic efficacy of miR-377 and phospholipase A2 in diabetic kidney disease. RESULTS: The average levels of serum TGF-ß, IL-6, IL-18, miR-377 and phospholipase A2 in diabetic proteinuria group were significantly higher than those in normal control group and diabetic proteinuria normal group(P < 0.05). miR-377, phospholipase A2 were significantly correlated with inflammatory factors such as glomerular filtration rate and TGF-ß. miR-377 and phospholipase A2 are independent predictors of diabetic kidney disease. The area under the curve of miR-377 and phospholipase A2 in the normal diabetic proteinuria group and the diabetic proteinuria group were 0.731 and 0.744, respectively. CONCLUSION: miR-377 and phospholipase A2 have good diagnostic efficiency for the early diagnosis of diabetic kidney disease. They can be used as early biomarkers.miR-377 and phospholipase A2 were positively correlated with inflammatory factors and involved in the occurrence and development of diabetic kidney disease.

Development of a clinical prediction model for diabetic kidney disease with glucose and lipid metabolism disorders based on machine learning and bioinformatics technology.

OBJECTIVE: In this study, we investigated the internal relationship between the pathogenesis of diabetic kidney disease (DKD) and abnormal glucose and lipid metabolism to identify potential biomarkers for diagnosis and treatment and investigated the role of the immune microenvironment of glucose and lipid metabolism disorders in the occurrence and progression of DKD. MATERIALS AND METHODS: The chip datasets GSE104948 and GSE96804 from the Gene Expression Common Database (GEO) were merged using the "lima" and "sva" software packages in R Software (4.2.3), and the merged dataset was used as the validation set. The intersection between the differential genes of DKD and the glucose and lipid metabolism genes in the MSigDB database was identified, and a nomogram of the incidence risk of DKD was built using three machine learning methods, namely LASSO regression, support vector machine (SVM), and random forest (RF), to validate the accuracy of the prediction model. Immune scores were conducted using the unsupervised clustering method, and patients were divided into two subgroups. The two subgroups were screened for differential genes for enrichment analysis. The differential genes of patients diagnosed with DKD were clustered into two gene subgroups for co-expression analysis. In this study, we utilized the Cytoscape software to construct a network of interactions among key genes. RESULTS: Using machine learning, a diagnostic model was developed with G6PC and HSD17B14 as key factors. Enrichment analysis and immune scoring demonstrated that the development of DKD was related to the imbalance in the microenvironment brought about by glucose lipid metabolism disorders. CONCLUSIONS: G6PC and HSD17B14 may be potential biomarkers for DKD, and the established predictive model is more helpful in predicting the incidence of DKD.

Effect of Repeated Structured Diabetes Education on Lifestyle Knowledge and Self-Care Diabetes Management in Kidney Transplant Patients With Posttransplant Diabetes.

OBJECTIVES: Diabetes knowledge among kidney transplant recipients with posttransplant diabetes has not been clearly assessed. We evaluated whether diabetes education in kidney transplant recipients with posttransplant diabetes affected self-care, metabolic control variables, and reversibility of early diabetic microangiopathies. MATERIALS AND METHODS: In this prospective randomized controlled study, we enrolled 210 renal transplant recipients with posttransplant diabetes. Group 1 patients (n = 140) received structured diabetes education, and group 2 patients (n = 70) received conventional education. Patient data were collected through patient identification and metabolic control parameter forms and a diabetes self-care scale questionnaire (scores between 0 and 7). RESULTS: Diet knowledge improved and waist circumference was reduced with mild to moderate exercise in group 1 (P < .001), despite no differences between the 2 groups in mean body weight or body mass index. Patients in group 1 (structured diabetes education with repeated reinforcement) showed significant improvement in healthy lifestyle parameter scores versus group 2 (P < .05) and versus values before education (P < .05). At end of study, these achievements were translated into proper blood sugar monitoring, management of both hypoand hyperglycemia, improvements in logbook use and healthy sharp disposal, Ramadan fasting, sick day management, and knowledge on the importance of HbA1c (P < .05), which translated to decrease of HbA1c in group 1 by 1.35%. In group 1, proteinuria decreased significantly compared with before education and compared with group 2 values (P = .016). Diabetic retinopathy and neuropathy remained comparable between groups (P > .05). CONCLUSIONS: Structured diabetes education improved lifestyle knowledge, self-care diabetes management, and metabolic control variables among kidney transplant recipients with posttransplant diabetes. Structured diabetes education also resulted in partial reversibility of the present early diabetic nephropathy. We recommended such education to be delivered to all kidney transplant recipients with diabetes.