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PubMed2026

New insights into diagnostic values and mechanisms of ferroptosis associated with immune infiltration in diabetic kidney disease.

The pathogenesis of diabetic kidney disease (DKD) is complex and closely related to ferroptosis and immune dysregulation, but the relevance is unclear. The present study investigates the potential mechanisms of ferroptosis-related genes (FRGs) in DKD and their relationship with the immune-inflammatory response. It searches for new diagnostic biomarkers to help diagnose and treat DKD. Four Gene Expression Omnibus (GEO) datasets, GSE30528, GSE30529 and GSE30122 as the test set, and GSE96804 for validation, were analyzed. FRGs were obtained from GeneCards, and 47 ferroptosis-related differentially expressed genes (FRDEGs) were identified by intersecting with DKD-related differentially expressed genes. Functional enrichment analyses, including Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, Gene Set Enrichment Analysis and Gene Set Variation Analysis, revealed that these FRDEGs are primarily associated with ferroptosis, hypoxia response and immune inflammation. Subsequently, the weighted gene co-expression network analysis (WGCNA) was employed to expand the ferroptosis-related gene network, and intersection of the 47 FRDEGs with key WGCNA module genes yielded 10 key genes. Based on the 10 key genes, the least absolute shrinkage and selection operator and support vector machine algorithms identified three hub genes [chemokine ligand 5 (CCL5), forkhead box C1 (FOXC1) and lactotransferrin (LTF)] for DKD diagnosis. Receiver operating characteristic curves confirmed their diagnostic value, with FOXC1 and LTF validated in the independent dataset. Immune infiltration analysis via CIBERSORT revealed eight immune cell types with significantly different infiltration levels between the DKD and control group in the integrated GEO datasets. Notably, both LTF and CCL5 showed a significant positive correlation with gamma delta T cells (γδT). Quantitative PCR results confirmed differential expression of the three hub genes in the DKD group, with elevated expression observed in DKD mice following intervention with rosiglitazone and hyperoside.

bioinformatics analysis↗

PubMed2025

Dual-approach analysis of gut microbiome in patients with type 1 diabetes and diabetic kidney disease.

BACKGROUND: Type 1 diabetes (T1D) is a multifactorial autoimmune disease mediated by genetic, epigenetic, and environmental factors. Diabetic kidney disease (DKD) is a major complication of diabetes mellitus which affects 30-40% of T1D patients. Increasing evidence suggests the significant role of the microbiome in the progression of both T1D and DKD. MATERIALS AND METHODS: Here we recruited 76 T1D patients and 22 healthy controls and combined data from sigmoid colon biopsy samples analysed with V3-V4 region amplification of 16S rRNA gene and shotgun metagenomics data obtained from faecal samples. Additionally, we compared T1D patients with and without progression of DKD. RESULTS: We observed significant differences within both sample types at various taxonomic and functional levels. T1D patient microbiota detected using biopsy samples had a lower abundance of the Bacteroides genus when compared to healthy controls. Significantly, despite only a few taxonomic differences patients with and without DKD progression were vastly different at the functional pathway level within the faecal samples - we observed 2 and 61 enriched pathways in these groups. respectively, with several of these pathways linked to the mediation of renal function. CONCLUSION: Altogether, we present novel data about microbial signatures relevant to T1D and DKD progression, which partly supports previous data and also presents possible tissue type or population-specific elements. DKD progression is characterized with significant differences within the functional level of the gut microbiome.

Humans↗

PubMed2025

Integrative metabolomic and proteomic analysis of diabetic kidney disease progression with younger-onset type 2 diabetes.

AIM: Younger-onset type 2 diabetes (YT2D) confers a disproportionately high risk of diabetic kidney disease (DKD), yet early biomarkers and underlying mechanisms remain poorly defined. We aimed to identify metabolites associated with DKD progression and integrate metabolomic and proteomic data to elucidate pathways involved in a multi-ethnic Asian cohort. MATERIALS AND METHODS: In this prospective study, 787 YT2D patients (diagnosed at ≤ age 40) were followed for a median of 5.7 years. DKD progression was defined as an annual decline in estimated glomerular filtration rate (eGFR) of ≥3 mL/min/1.73 m2 or ≥ 40% reduction in eGFR from baseline. Plasma metabolites were measured by nuclear magnetic resonance spectroscopy. Multivariable regression analysis was performed in a discovery (N = 550) and internal validation cohort (N = 237). Integrative metabolomic-proteomic analysis (N = 428) was performed using sparse partial least squares discriminant analysis (sPLS-DA). RESULTS: Ninety-eight metabolites were differentially expressed between DKD progressors and non-progressors, of which total branched-chain amino acids (BCAAs) (OR = 0.60, 95% CI 0.46-0.79), valine (OR = 0.62, 95% CI 0.48-0.81), and leucine (OR = 0.56, 95% CI 0.43-0.74) associated with DKD progression, independent of metabolic risk factors. Integrative analysis identified three components comprising 23 proteins and 30 metabolites, involved in the citrate cycle and apoptosis, which improved prediction of DKD progression beyond clinical risk factors (AUC 0.69-0.83). CONCLUSION: Lower plasma BCAA levels are independently associated with DKD progression in YT2D. Integrative multi-omics analysis highlights disruptions in metabolic and apoptotic pathways, providing insights into DKD pathophysiology and potential biomarkers for early risk stratification.

Humans↗

PubMed2026

Normoalbuminuric and albuminuric diabetic kidney disease exhibit divergent renal proteomic characteristics: implications for management.

BACKGROUND: The pathogenesis of diabetic kidney disease (DKD) is complex. Normoalbuminuric diabetic kidney disease (NADKD) is a special subtype of DKD that often progresses insidiously without detectable albuminuria, posing diagnostic and therapeutic challenges. Its pathogenesis remains unclear. Proteomic analysis of renal tissues may offer insights into its pathogenesis and identify biomarkers. METHODS: Clinicopathological data from 295 biopsy-proven DKD patients were collected and classified into normoalbuminuric (UACR < 30 mg/g, n = 25), microalbuminuric (UACR 30-300 mg/g, n = 26), and macroalbuminuric (UACR > 300 mg/g, n = 244) groups. Laser microdissection combined with mass spectrometry (LMD/MS) was used to analyze glomerular and proximal tubule proteomics in 5 patients per DKD subgroup and 5 control subjects. Associations with clinical features were examined. RESULTS: Glomerular proteomic analysis revealed that oxidative stress and metabolic pathways (UQCRC1) were upregulated in NADKD group, whereas the complement and coagulation cascades (C3, C5, C6, C9, CFH, CFHR1) were significantly upregulated in the microalbuminuric and macroalbuminuric DKD groups. The proximal tubule proteomics analysis showed that oxidative phosphorylation-related proteins (SDHA, CYCS, UQCRQ) were upregulated in NADKD, and collagen I related proteins (COL1A1, COL1A2) were significantly upregulated. CONCLUSION: Oxidative stress and mitochondrial dysfunction are involved in the progression of NADKD, lesions predominantly located in the tubulointerstitium. The complement pathway participates in the pathogenesis and progression of albuminuric DKD (ADKD). These divergent molecular profiles suggest that NADKD and ADKD may reflect different pathophysiological mechanisms and have important implications for therapeutic strategies in diabetes management.

Humans↗

PubMed2025

Genomic mapping of diabetic kidney disease biomarkers and identification of potential inhibitors through virtual screening.

BACKGROUND: Diabetic kidney disease (DKD) is a common and serious complication of diabetes mellitus, marked by a multifactorial pathogenesis and the absence of sensitive diagnostic biomarkers. Identifying novel molecular targets and therapeutic options is essential to improve early diagnosis and treatment outcomes. METHODS: To uncover potential biomarkers and therapeutic candidates, we performed an integrated genomic analysis using microarray and RNA-seq datasets from the Gene Expression Omnibus (GEO) and Sequence Read Archive (SRA) databases. Differentially expressed genes (DEGs) were identified and subjected to protein-protein interaction (PPI) network analysis. Key genes were further explored through virtual screening of an FDA-approved compound library using molecular docking techniques. Drug-likeness was assessed via Lipinski's rule of five. RESULTS: A total of 40 DEGs were identified, among which ISCU (downregulated; involved in iron-sulfur cluster biogenesis) and AP1S2 (upregulated; associated with vesicular trafficking) emerged as potential biomarkers. PPI analysis revealed their involvement in critical DKD-related pathways, such as extracellular matrix remodeling and oxidative stress. Virtual screening identified six FDA-approved compounds with high binding affinity (≤-7.96 kcal/mol) to ISCU, notably ZINC000001576020, all of which complied with Lipinski's rule. CONCLUSIONS: This in-silico study nominates ISCU and AP1S2 as candidate diagnostic biomarkers for DKD and identifies computationally prioritized inhibitors targeting ISCU. These findings require experimental validation but provide a molecular framework for precision diagnosis and therapeutic development. These findings offer new molecular insights that could inform precision diagnosis and personalized treatment strategies for diabetic kidney disease.

Diabetic Nephropathies↗

PubMed2026

Predictive Models for Hypoglycemia Risk in Haemodialysis Patients With Diabetic Kidney Disease: Systematic Review and Meta-Analysis.

AIM: To provide evidence for selecting and developing reliable clinical assessment tools for hypoglycemia in diabetic kidney disease patients during haemodialysis. DESIGN: Review. METHODS: Systematic searches were performed in 9 Chinese and English databases to collect literature regarding the development of hypoglycemia risk prediction models in haemodialysis patients with diabetic kidney disease. Two reviewers independently performed literature screening, data extraction, risk-of-bias assessment, and applicability evaluation. The Prediction Model Risk of Bias Assessment Tool was used to assess the risk of bias and applicability of the included studies. Meta-analysis was conducted using R software. DATA SOURCES: CNKI, Wanfang, VIP, CBM, PubMed, Cochrane Library, EMbase, Web of Science, and CINAHL. The search period covered from the establishment date of each database to December 2025. RESULTS: Six studies, comprising six prediction models, were included. Two studies performed internal validation, and three conducted external validation. All models reported the area under the curve, ranging from 0.813 to 0.866, and calibration measures. Four studies were rated as having a high risk of bias, while all six demonstrated good overall applicability. The meta-analysis showed that the pooled AUC value of the six studies was 0.846 (95% CI: 0.823-0.867). CONCLUSION: Research on hypoglycemia risk prediction models in haemodialysis patients with diabetic kidney disease remains in the developmental stage. Although the included prediction models exhibited satisfactory apparent discriminatory ability and clinical applicability, most of the original studies suffered from a high risk of bias and lacked adequate validation. The true predictive performance and clinical application value of these models remain to be further verified. Accordingly, routine and unconditional clinical application is not recommended at this stage. Future studies should include more high-quality, multicenter external validation and develop models with high generalizability, favourable clinical applicability, and robust predictive performance to facilitate early identification of hypoglycemia risk in this population. IMPACT: This study systematically evaluated the hypoglycemia risk prediction models for diabetic kidney disease patients during haemodialysis, and the research on hypoglycemia risk prediction models for maintenance haemodialysis patients during dialysis is still in the development stage. This study provides a reference for clinical medical staff to select or develop hypoglycemia risk prediction and assessment tools for diabetic kidney disease patients during haemodialysis. REPORTING METHOD: This study was conducted in accordance with the relevant guidelines of the EQUATOR Network and followed the TRIPOD-SRMA Checklist. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution. TRIAL REGISTRATION: PROSPERO: CRD420251243352.

Humans↗

PubMed2024

Deciphering the molecular nexus of BTG2 in periodontitis and diabetic kidney disease.

OBJECTIVE: To investigate the role of BTG2 in periodontitis and diabetic kidney disease (DKD) and its potential underlying mechanism. METHODS: Gene expression data for periodontitis and DKD were acquired from the Gene Expression Omnibus (GEO) database. Differential expression analysis identified co-expressed genes between these conditions. The Nephroseq V5 online nephropathy database validated the role of these genes in DKD. Pearson correlation analysis identified genes associated with our target gene. We employed Gene Set Enrichment Analysis (GSEA) and Protein-Protein Interaction (PPI) networks to elucidate potential mechanisms. Expression levels of BTG2 mRNA were examined using quantitative polymerase Chain Reaction (qPCR) and immunofluorescence assays. Western blotting quantified proteins involved in epithelial-to-mesenchymal transition (EMT), apoptosis, mTORC1 signaling, and autophagy. Additionally, wound healing and flow cytometric apoptosis assays evaluated podocyte migration and apoptosis, respectively. RESULTS: Analysis of GEO database data revealed BTG2 as a commonly differentially expressed gene in both DKD and periodontitis. BTG2 expression was reduced in DKD compared to normal conditions and correlated with proteinuria. GSEA indicated enrichment of BTG2 in the EMT and mTORC1 signaling pathways. The PPI network highlighted BTG2's relevance to S100A9, S100A12, and FPR1. Immunofluorescence assays demonstrated significantly lower BTG2 expression in podocytes under high glucose (HG) conditions. Reduced BTG2 expression in HG-treated podocytes led to increased levels of EMT markers (α-SMA, vimentin) and the apoptotic protein Bim, alongside a decrease in nephrin. Lower BTG2 levels were associated with increased podocyte mobility and apoptosis, as well as elevated RPS6KB1 and mTOR levels, but reduced autophagy marker LC3. CONCLUSION: Our findings suggest that BTG2 is a crucial intermediary gene linking DKD and periodontitis. Modulating autophagy via inhibition of the mTORC1 signaling pathway, and consequently suppressing EMT, may be pivotal in the interplay between periodontitis and DKD.

Periodontitis↗

PubMed2026

Discovery and validation of a multi-protein panel for predicting non-fatal major adverse cardiovascular events in diabetic kidney disease.

OBJECTIVE: To identify plasma protein biomarkers associated with incident non-fatal major adverse cardiovascular events (MACE) in diabetic kidney disease (DKD) patients. RESEARCH DESIGN AND METHODS: We analyzed 317 DKD patients from the UK Biobank. Plasma proteomics and clinical data (demographics, metabolism, renal function) were integrated. In an exploratory discovery phase, three sequential Cox regression models (crude, socio-demographic-adjusted, socio-demographic-metabolic adjusted) screened non-fatal MACE-associated proteins. To prevent information leakage, the cohort was then randomly split into training (70%) and testing (30%) sets; machine-learning feature selection, hyperparameter optimization, and final model development were performed exclusively within the training set. The associated proteins were input into the four-step machine-learning pipeline (LASSO-Cox, random survival forest, Boruta, XGBoost-Cox). Predictive performance was validated using Kaplan-Meier survival analyses, longitudinal trajectory modeling, and ROC benchmarking. An interactive web application was deployed for clinical implementation. RESULTS: Of 1,463 plasma proteins, 561 were associated with non-fatal MACE across Cox models, with 14 overlapping proteins. Nine core proteins (ANG, IL1R1, CXCL14, ESAM, PTGDS, HAVCR1, FGFR2, IGSF8, CCL3) were validated: ANG showed the strongest non-fatal MACE association (HR = 3.88, 95%CI 2.33-6.48, p<0.001), and all high-expression groups had elevated non-fatal MACE risk. GO/KEGG enrichment highlighted inflammatory-immune pathways like positive regulation of MAPK cascade, Cytokine-cytokine receptor interaction and PI3K-Akt signaling pathway as key mechanisms. The model integrating proteins, demographic factors, and clinical variables achieved the highest predictive performance across non-fatal MACE (AUC = 0.768), myocardial infarction (MI) (0.808), and stroke (0.816) outcomes, with superior stability in cross-validation. CoxBoost + Elastic Net framework was selected as the optimal framework via benchmarking of 101 algorithms. The model demonstrated favorable calibration in high-risk patients and yielded positive net clinical benefit across decision thresholds of 5% to 45%. The web tool (https://jiangli2941.github.io/MACE-prediction-v2/) enables input of 28 variables, outputs non-fatal MACE risk status, risk probability, and highlights abnormal indicators. CONCLUSION: Plasma proteomics combined with machine learning identifies robust non-fatal MACE predictors in DKD.

Humans↗

PubMed2025

Caffeic acid phenethyl ester protects renal tubular epithelial cells against ferroptosis in diabetic kidney disease via restoring PINK1-mediated mitophagy.

Mounting evidence indicates that renal tubular ferroptosis plays a crucial role in the progression of diabetic kidney disease (DKD). Caffeic acid phenethyl ester (CAPE), derived from propolis, a precious resinous substance synthesized by various bee species, has garnered broad attention in biomedical research. This study aims to explore the mechanism by which CAPE protects renal tubular epithelial cells (TECs) against ferroptosis in DKD. DBA/2J mice were administered streptozotocin (STZ) by intraperitoneal injection, fed a high-fat diet (HFD) and treated with CAPE. The findings revealed significant changes in ferroptosis markers. In diabetic mice and TECs under high-glucose (HG) conditions, levels of glutathione peroxidase 4 (GPX4) and solute carrier family 7 member 11 (SLC7A11) decreased, while transferrin receptor 1 (TFR1) increased. These changes were accompanied by a reduction in antioxidant capability and the accumulation of malondialdehyde (MDA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that the intersection targets of CAPE and ferroptosis were mainly located in the mitochondria and exhibited high enrichment values in mitophagy. Further investigations revealed that HG induced a depolarization of mitochondrial membrane potential and an excessive level of mitochondrial reactive oxygen species (ROS), accompanied by defective mitophagy. The administration of CAPE inhibited exacerbated ferroptosis and rescued defective mitophagy induced by DKD. In addition, CAPE restored PTEN-induced putative kinase 1 (PINK1) levels, which were markedly diminished in the kidneys of DKD mice and TECs subjected to HG. Molecular docking simulation experiments suggested that CAPE is steadily bound to the PINK1 active pocket. Cellular Thermal Shift Assay (CETSA) and Drug Affinity Responsive Target Stability assay (DARTS) showed that CAPE enhances the thermal stability of the PINK1 protein within a specific temperature range and protects the PINK1 protein from degradation by proteolytic enzymes. These results confirm that CAPE interacts with PINK1 as its specific target. However, the positive outcomes of CAPE treatment on ferroptosis were nullified by the PINK1 siRNA. This research indicates that CAPE has potential therapeutic benefits for DKD by protecting renal TECs against ferroptosis via rescuing PINK1-mediated mitophagy. These findings suggest that CAPE shows potential as a therapeutic agent to prevent tubular injury in DKD.

Animals↗

PubMed2024

The association between vitamin D receptor gene polymorphism FokI and type 2 diabetic kidney disease and its molecular mechanism: a case control study.

BACKGROUND: The role of the vitamin D receptor single nucleotide polymorphism FOKI (VDR-FOKI) (rs2228570) in genetic susceptibility to type 2 diabetic kidney disease (T2DKD) remains uncertain. This study investigated the relationship between VDR-FOKI and T2DKD within the Chinese Plateau Han population and analyzed the underlying mechanisms. METHODS: A total of 316 subjects were enrolled, including 44 healthy adults, 114 individuals with type 2 diabetes mellitus (T2DM), and 158 patients with T2DKD. According to the 2023 American Diabetes Association Diabetes Guidelines, patients with T2DKD were categorized into low-medium-risk and high-risk groups based on estimates of glomerular filtration rate and urinary albumin-to-creatinine ratio. The VDR-FokI genotypes of all participants were identified using the Taqman probe and classified as homozygous mutant genotypes (C/C or FF), heterozygous mutant genotypes (C/T or Ff), and homozygous wild genotypes (T/T or ff). Plasma levels of malondialdehyde (MDA), glutathione (GSH), and superoxide dismutase activity (SOD) were assessed in T2DKD patients with FF and ff genotypes. Additionally, the levels of plasma VDR, GPX4, and P53 were determined using ELISA, while the relative expressions of VDR mRNA, GPX4 mRNA, and TP53 mRNA in whole blood were measured by RT-qPCR. RESULTS: The T2DM patients with the ff genotype exhibited a 2.93-fold increased likelihood of developing T2DKD compared to those with the FF genotype (ORadjusted = 2.93; 95% CI: 1.142-7.513). Additionally, they were 2.01 times more likely to develop T2DKD than individuals with the FF and Ff genotypes (ORadjusted = 2.01; 95% CI: 1.008-4.006). However, no significant differences in VDR-FokI genotype distribution were observed between the healthy control group and the T2DM group, as well as between the low-medium-risk and high-risk groups of T2DKD. Furthermore, T2DKD patients with the ff genotype had significantly higher plasma levels of MDA compared to those with the FF genotype. In contrast, plasma GSH and SOD content was significantly lower in the ff genotype patients (P < 0.05). Additionally, the GPX4 concentration in ff genotype patients was significantly lower than in FF genotype patients [14.88 (11.32,22.39) vs. 12.76 (8.55,13.75), P = 0.037]. Nevertheless, no statistically significant difference was observed in the expression of VDRmRNA, GPX4mRNA, TP53mRNA, plasma VDR, and plasma P53. CONCLUSIONS: The ff genotype of VDR-FokI is a risk factor for T2DKD, and the potential mechanism may be related to ferroptosis. However, It is not associated with T2DM or the progression of T2DKD.

Humans↗

PubMed1979

The treatment of diabetic kidney disease.

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Adrenal Cortex Hormones↗

PubMed2025

Dual-specific phosphatases-8: a new target for clinical disease intervention.

Dual-specific phosphatase-8 (DUSP8), identified as the first gene in a genome-wide association study (GWAS), is implicated in cellular oxidative stress, proliferation, apoptosis, and drug resistance through its negative regulation of the dephosphorylation activities of JNK, ERK, and p38 within the MAPK pathway. Recent studies have shown that DUSP8 plays a pivotal role in the progression of several human diseases, notably colorectal cancer, diabetic kidney disease, and breast cancer. This suggests that DUSP8 may represent a novel target for clinical intervention in these diseases. This review first introduces the biological structure and function of DUSP8, with a focus on its relationship with a series of diseases and the regulatory mechanisms involved. Furthermore, we concentrate on unresolved scientific questions in the current research, aiming to establish a new theoretical foundation for the diagnosis and treatment of related diseases.

Humans↗

PubMed2026

Protein mediators of chronic kidney disease in Type 2 diabetes: A mendelian randomization study.

BACKGROUND: Chronic kidney disease (CKD) occurs in 20-50% of the people living with Type 2 diabetes (T2D) and is the leading cause of kidney failure worldwide. The cause of CKD is not fully understood, and few interventions prevent CKD in individuals living with diabetes. Here, we use large-scale proteomics data to identify circulating proteins that mediate the relationship between T2D and kidney disorders. METHODS AND FINDINGS: First, we used two-sample mendelian randomization (MR) and identified 71 circulating proteins whose levels were altered by genetic predisposition to T2D based on circulating proteomic GWAS from deCODE with 35,559 individuals and T2D GWAS with 80,154 cases. Then, we used cis-genetic variants to proxy the causal effect of some of these T2D-influenced circulating proteins and found that, collectively, five proteins (INHBC, GNPTG, LPO, AGRN, and CTSD) affected three kidney traits (blood urea nitrogen [BUN], estimated glomerular filtration rate [eGFR] and CKD risk) based on GWAS with up to 1,004,040 participants. Notably, we found that higher levels of circulating INHBC protein were estimated to lead to a lower eGFR and higher BUN based on MR analyses. We then replicated this MR analysis with proteomic GWAS from four additional cohorts, namely, UKB-PPP, Fenland, ARIC, and EPIC-Norfolk. We observed a consistent direction of effect across all four proteomic GWAS datasets, supporting the robustness of our results against platform and cohort variation. In observational analyses, increased circulating INHBC levels were associated with increased hazard for kidney disease diagnosis in 37,854 UK Biobank participants. We estimated that circulating INHBC levels mediate 1.3% (95% confidence interval [0.85%, 1.9%]) of the association between T2D and kidney disease diagnosis. There are important limitations in this study. Firstly, although we observed limited evidence for violations to the MR assumptions, some are untestable. Secondly, our study was not based on individuals with diabetic kidney diseases, but rather independent population-based studies assessing diabetes and kidney function separately. Therefore, additional functional analyses in disease specific cohort are needed. CONCLUSIONS: Collectively, these findings suggest that T2D influences the risk of CKD, in part, through increased circulating INHBC levels.

Humans↗

PubMed2026

SSB deficiency-induced R-loop accumulation triggers podocyte inflammation in DKD.

INTRODUCTION: Diabetic kidney disease (DKD) is fundamentally a podocytopathy in which sterile inflammation plays a central pathogenic role, yet the upstream triggers that initiate inflammatory cascades in podocytes remain elusive. R-loops are critical regulators of genomic stability, and their pathological accumulation triggers DNA damage and innate immune activation. Whether R-loop dysregulation contributes to podocyte-driven inflammation in DKD is unknown. METHODS: We integrated single-cell transcriptomic profiling, dual machine learning algorithms, and functional experiments to dissect the R-loop regulatory network in the diabetic kidney. RESULTS: Integrated analysis of human diabetic kidney single-cell RNA-seq data revealed a globally compromised R-loop regulatory network selectively within podocytes. Intersection of podocyte-specific transcriptomic shifts with validated R-loop regulators identified 93 candidate genes, from which dual machine learning algorithms pinpointed SSB (Sjögren syndrome antigen B) as the principal podocyte-selective R-loop resolver and a superior diagnostic biomarker (AUC = 0.983). SSB expression was selectively downregulated in diabetic podocytes and showed the strongest positive correlation with the R-loop resolution module. Mechanistically, SSB loss impaired RNA splicing and stability pathways, leading to aberrant R-loop accumulation that activated the cGAS-dependent inflammatory signaling in podocytes. In two murine DKD models and high glucose-challenged podocytes, SSB was markedly reduced. Remarkably, SSB knockdown in podocytes alone sufficed to trigger R-loop accumulation and pro-inflammatory cytokine expression, whereas both RNase H1-mediated R-loop removal and cGAS co-depletion blunted this response. DISCUSSION: These findings suggest that an SSB-governed R-loop -cGAS -inflammatory signaling axis may link genomic instability to podocyte inflammation and contribute to DKD progression, nominating R-loop homeostasis as a previously unrecognized potential therapeutic target.

Podocytes↗

PubMed2026

Impact of Albuminuria-Lowering Treatments on Cardiovascular Predictive Ceramides in Diabetes: Post Hoc Analysis of the ROTATE Trials.

AIM: Cardiovascular disease (CVD) is the leading cause of mortality in individuals with diabetes. Diabetic kidney disease, closely related to CVD risk, is prevalent in up to 40% of this population. Emerging evidence suggests ceramide lipids as accurate biomarkers for CVD. We assessed the effect of four albuminuria-lowering drugs on CVD-related ceramides in diabetes by post hoc analysis of the ROTATE trials. MATERIALS AND METHODS: Twenty six adults with type 1 (T1D) as well as 37 with type 2 diabetes (T2D) with a urine albumin-creatinine ratio (UACR) of 30-500 mg/g participated in a 4-week 4-time randomized crossover study with periods of telmisartan, empagliflozin, linagliptin and baricitinib treatment, each separated by a 4-week washout period. Blood samples were collected at the beginning and end of each period and ceramide lipids (Cer16, Cer18, Cer20, Cer22, Cer24 and Cer24:1) were measured. The effect of each treatment was evaluated using linear mixed-effect models. RESULTS: At baseline, individuals with T2D had greater levels of Cer22 and Cer24 compared to the individuals with T1D. Among the treatments, linagliptin was the only drug that demonstrated a reduction of Cer22, Cer24 and Cer24:1 from baseline by 22.6% (95% CI: -33.58; -9.79, p = 0.001), 25.7% (95% CI: -38.94; -9.69, p = 0.003) and 19.6% (95% CI: -31.34; -5.95, p = 0.007), respectively. No changes in the ceramides were observed for the other drugs. CONCLUSION: Our exploratory findings suggest that certain albuminuria-lowering drugs may affect ceramide levels as a secondary effect. However, further mechanistic investigations are needed.

Humans↗

PubMed2026

The Association Between NT-Pro BNP, Nephropathy and Endothelial Dysfunction in Patients With Type 2 Diabetes Mellitus.

BACKGROUND: N-terminal pro-B-type natriuretic peptide (NT-Pro BNP) is an established biomarker of heart failure and has been recommended for cardiovascular risk stratification in type 2 diabetes mellitus (T2DM). However, its relationship with diabetic nephropathy and endothelial dysfunction across varying stages of kidney impairment remains unclear. This study examined the associations of NT-Pro BNP, renal impairment, albuminuria and endothelial dysfunction in patients with T2DM without overt heart failure. METHODS: A comparative cross-sectional study was conducted among 192 adults with T2DM. Participants were stratified by KDIGO eGFR groups (≥ 90, 60-89, 30-59 mL/min/1.73m2). NT-Pro BNP was considered abnormal at a cut-off of ≥ 125 pg/mL. Albuminuria was categorized using the urinary albumin-to-creatinine ratio (uACR). Endothelial function was assessed by brachial artery flow-mediated dilatation (FMD). Logistic regression analysis was performed to identify independent factors of elevated NT-Pro BNP, with p-values < 0.05 considered statistically significant. RESULTS: NT-Pro BNP levels were significantly higher in the lower eGFR groups compared with normal eGFR (204.3 vs. 96.8 vs. 62.2 pg/mL, p < 0001). A weak but significant positive correlation was observed between NT-Pro BNP and uACR (r = 0.31, p < 0.001). However, no significant association was found between NT-Pro BNP and FMD (p = 0.388). Following multivariable adjustments, older age (adjusted OR 1.14, 95% CI: 1.06-1.23, p < 0.001), higher systolic blood pressure (adjusted OR 1.05, 95% CI: 1.02-1.08, p = 0.010), lower eGFR (adjusted OR 0.97, 95% CI: 0.95-0.99, p = 0.003) and beta-blocker use (adjusted OR 4.65, 95% CI: 1.61-13.45, p < 0.001) were independently associated with elevated NT-Pro BNP. CONCLUSION: In patients with T2DM without overt heart failure, elevated NT-Pro BNP showed a statistically significant association with lower eGFR and higher albuminuria. Moderate to severe albuminuria becomes an independent factor for elevated NT-Pro BNP after adjustment excluding eGFR. The lack of association with endothelial dysfunction suggests that NT-Pro BNP may reflect different pathophysiological pathways. NT-Pro BNP may serve as a useful biomarker for early cardiovascular risk stratification and identification of individuals at risk of pre-heart failure in diabetic kidney disease.

NT‐Pro BNP↗

PubMed2023

Estimated Lifetime Cardiovascular, Kidney, and Mortality Benefits of Combination Treatment With SGLT2 Inhibitors, GLP-1 Receptor Agonists, and Nonsteroidal MRA Compared With Conventional Care in Patients With Type 2 Diabetes and Albuminuria.

BACKGROUND: Sodium glucose cotransporter 2 inhibitors (SGLT2i), glucagon-like peptide-1 receptor agonists (GLP-1 RA), and the nonsteroidal mineralocorticoid receptor antagonist (ns-MRA) finerenone all individually reduce cardiovascular, kidney, and mortality outcomes in patients with type 2 diabetes and albuminuria. However, the lifetime benefits of combination therapy with these medicines are not known. METHODS: We used data from 2 SGLT2i trials (CANVAS [Canagliflozin Cardiovascular Assessment] and CREDENCE [Canagliflozin and Renal Events in Diabetes with Established Nephropathy Clinical Evaluation]), 2 ns-MRA trials (FIDELIO-DKD [Finerenone in Reducing Kidney Failure and Disease Progression in Diabetic Kidney Disease] and FIGARO-DKD [Efficacy and Safety of Finerenone in Subjects With Type 2 Diabetes Mellitus and the Clinical Diagnosis of Diabetic Kidney Disease]), and 8 GLP-1 RA trials to estimate the relative effects of combination therapy versus conventional care (renin-angiotensin system blockade and traditional risk factor control) on cardiovascular, kidney, and mortality outcomes. Using actuarial methods, we then estimated absolute risk reductions with combination SGLT2i, GLP-1 RA, and ns-MRA in patients with type 2 diabetes and at least moderately increased albuminuria (urinary albumin:creatinine ratio ≥30 mg/g) by applying estimated combination treatment effects to participants receiving conventional care in CANVAS and CREDENCE. RESULTS: Compared with conventional care, the combination of SGLT2i, GLP-1 RA, and ns-MRA was associated with a hazard ratio of 0.65 (95% CI, 0.55-0.76) for major adverse cardiovascular events (nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death). The corresponding estimated absolute risk reduction over 3 years was 4.4% (95% CI, 3.0-5.7), with a number needed to treat of 23 (95% CI, 18-33). For a 50-year-old patient commencing combination therapy, estimated major adverse cardiovascular event-free survival was 21.1 years compared with 17.9 years for conventional care (3.2 years gained [95% CI, 2.1-4.3]). There were also projected gains in survival free from hospitalized heart failure (3.2 years [95% CI, 2.4-4.0]), chronic kidney disease progression (5.5 years [95% CI, 4.0-6.7]), cardiovascular death (2.2 years [95% CI, 1.2-3.0]), and all-cause death (2.4 years [95% CI, 1.4-3.4]). Attenuated but clinically relevant gains in event-free survival were observed in analyses assuming 50% additive effects of combination therapy, including for major adverse cardiovascular events (2.4 years [95% CI, 1.1-3.5]), chronic kidney disease progression (4.5 years [95% CI, 2.8-5.9]), and all-cause death (1.8 years [95% CI, 0.7-2.8]). CONCLUSIONS: In patients with type 2 diabetes and at least moderately increased albuminuria, combination treatment of SGLT2i, GLP-1 RA, and ns-MRA has the potential to afford relevant gains in cardiovascular and kidney event-free and overall survival.

Humans↗

PubMed2025

Development and Validation of a Novel LC-MS/MS Based Proteomics Method for Quantitation of Retinol Binding Protein 4 (RBP4) and Transthyretin (TTR).

Retinol binding protein 4 (RBP4), the circulating carrier of retinol, complexes with transthyretin (TTR) and is a potential biomarker of cardiometabolic disease. However, RBP4 quantitation relies on immunoassays and western blots without retinol and TTR measurement. A liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for simultaneous absolute quantitation of circulating RBP4 and TTR is critical to establishing their biomarker potential. Surrogate peptides with reproducible, linear LC-MS/MS response were selected. Purified proteins were used as quantitation standards and heavy-labelled peptides as internal standards. Matrix effects were evaluated. The validated method was applied to measure inter- and intra-individual variability in RBP4 and TTR concentrations in healthy individuals and patients with diabetic kidney disease. Quantitation was linear for the clinically relevant concentration ranges of RBP4 (0.5-6 μM) and TTR (5.8-69 μM). Assay inter-day variability was <12% and precision within 5%. The inter-individual variability for RBP4 and TTR concentrations was 18-26%, while intra-individual variability was similar to assay variability. RBP4 and TTR quantitation correlated with commercially available ELISA assays. The developed LC-MS/MS method enables simultaneous absolute quantitation of RBP4 and TTR in serum and plasma that can be applied to clinical biomarker studies and stoichiometric measurements of circulating RBP4, TTR, and retinol.

Retinol binding protein 4 (RBP4)↗