Diabetic nephropathy (DN) represents a major chronic kidney disorder and a leading cause of end-stage renal disease (ESRD). Small RNAs have been showing great promise as diagnostic markers as well as drug targets. Identifying dysregulated micro RNAs (miRNAs) could help in identifying disease biomarkers and investigation of downstream interactions, shedding light on the molecular pathophysiology of DN. In this study, we analyzed small RNAs within human urinary extracellular vesicles (ECVs) from DN patients using small RNA next-generation sequencing.

In this cross-sectional study, urine samples were collected from 88 participants who were divided into 3 groups: type 2 diabetes (T2D) with DN (T2D + DN, n = 20), T2D without DN (T2D - DN, n = 40), and healthy individuals (n = 28). The study focused on isolating urinary ECVs to extract and sequence small RNAs. Differentially expressed small RNAs were identified, and a functional enrichment analysis was conducted.

The study revealed a distinct subset of 13 miRNAs and 10 Piwi-interacting RNAs that were significantly dysregulated in urinary ECVs of the DN group when compared to other groups. Notably, miR-151a-3p and miR-182-5p exhibited a unique expression pattern, being downregulated in the T2D - DN group, and upregulated in the T2D + DN group, thus demonstrating their effectiveness in distinguishing patients between the 2 groups. Eight driver genes were identified PTEN, SMAD2, SMAD4, VEGFA, CCND2, CDK6, LIN28B, and CHD1.

Our findings contribute valuable insights into the pathogenesis of DN, uncovering novel biomarkers and identifying potential therapeutic targets that may aid in managing and potentially decelerating the progression of the disease.

Although programmed cell death (PCD) and diabetic nephropathy (DN) are intrinsically conneted, the interplay among various PCD forms remains elusive. In this study, We aimed at identifying independently DN-associated PCD pathways and biomarkers relevant to the related pathogenesis.

We acquired DN-related datasets from the GEO database and identified PCDs independently correlated with DN (DN-PCDs) through single-sample Gene Set Enrichment Analysis (ssGSEA) as well as, univariate and multivariate logistic regression analyses. Subsequently, applying differential expression analysis, weighted gene co-expression network analysis (WGCNA), and Mfuzz cluster analysis, we filtered the DN-PCDs pertinent to DN onset and progression. The convergence of various machine learning techniques ultimately spotlighted hub genes, substantiated through dataset meta-analyses and experimental validations, thereby confirming hub genes and related pathways expression consistencies.

We harmonized four DN-related datasets (GSE1009, GSE142025, GSE30528, and GSE30529) post-batch-effect removal for subsequent analyses. Our differential expression analysis yielded 709 differentially expressed genes (DEGs), comprising 446 upregulated and 263 downregulated DEGs. Based on our ssGSEA as well as univariate and multivariate logistic regressions, apoptosis and NETotic cell death were appraised as independent risk factors for DN (Odds Ratio > 1, p < 0.05). Next, we further refined 588 apoptosis- and NETotic cell death-associated genes through WGCNA and Mfuzz analysis, resulting in the identification of 17 DN-PCDs. Integrating protein-protein interaction (PPI) network analyses, network topology, and machine learning, we pinpointed hub genes (e.g., IL33, RPL11, and CX3CR1) as significant DN risk factors with expression corroborating in subsequent meta-analyses and experimental validations. Our GSEA enrichment analysis discerned differential enrichments between DN and control samples within pathways such as IL2/STAT5, IL6/JAK/STAT3, TNF-α via NF-κB, apoptosis, and oxidative phosphorylation, with related proteins such as IL2, IL6, and TNFα, which we subsequently submitted to experimental verification.

Innovatively stemming from from PCD interactions, in this study, we discerned PCDs with an independent impact on DN: apoptosis and NETotic cell death. We further screened DN evolution- and progression-related biomarkers, i.e. IL33, RPL11, and CX3CR1, all of which we empirically validated. This study not only poroposes a PCD-centric perspective for DN studies but also provides evidence for PCD-mediated immune cell infiltration exploration in DN regulation. Our results could motivate further exploration of DN pathogenesis, such as how the inflammatory microenvironment mediates NETotic cell death in DN regulation, representing a promising direction for future research.

Chronic pancreatitis (CP) is a progressive fibroinflammatory disorder lacking therapies and biomarkers. Neutrophil gelatinase-associated lipocalin (NGAL) is a proinflammatory cytokine elevated during inflammation that binds fatty acids (FAs) such as linoleic acid. We hypothesized that systemic NGAL could serve as a biomarker for CP and, with FAs, provide insights into inflammatory and metabolic alterations.

NGAL was measured by immunoassay, and FA composition was measured by gas chromatography in plasma (n = 171) from a multicenter study, including controls (n = 50), acute and recurrent acute pancreatitis (AP/RAP) (n = 71), and CP (n = 50). Peripheral blood mononuclear cells (PBMCs) from controls (n = 16), AP/RAP (n = 17), and CP (n = 15) were measured by cytometry by time-of-flight.

Plasma NGAL was elevated in subjects with CP compared with controls (area under the curve [AUC] = 0.777) or AP/RAP (AUC = 0.754) in univariate and multivariate analyses with sex, age, body mass index, and smoking (control AUC = 0.874; AP/RAP AUC = 0.819). NGAL was elevated in CP and diabetes compared with CP without diabetes ( P < 0.001). NGAL + PBMC populations distinguished CP from controls (AUC = 0.950) or AP/RAP (AUC = 0.941). Linoleic acid was lower, whereas dihomo-γ-linolenic and adrenic acids were elevated in CP ( P < 0.05). Linoleic acid was elevated in CP with diabetes compared with CP subjects without diabetes ( P = 0.0471).

Elevated plasma NGAL and differences in NGAL + PBMCs indicate an immune response shift that may serve as biomarkers of CP. The potential interaction of FAs and NGAL levels provide insights into the metabolic pathophysiology and improve diagnostic classification of CP.

Diabetic nephropathy (DN) is a prevalent and chronic, severe complication of diabetes, representing a serious global health concern. Early detection of DN is essential for initiating timely and effective therapeutic interventions and accurately assessing prognosis. Neutrophil Gelatinase-Associated Lipocalin (NGAL), a low molecular weight protein, has emerged as a potential biomarker for DN due to its association with renal injury and its ability to provide early indications of kidney damage. NGAL levels in both serum and urine are elevated in individuals with renal damage, making it a valuable biomarker for detecting early signs of kidney impairment in the context of diabetes. This study aims to investigate the utility of NGAL as an early biomarker for DN and explore its correlation with various clinical parameters associated with the disease. Understanding the relationship between NGAL levels and clinical parameters such as glycemic control, renal function, blood pressure, and duration of diabetes is crucial for comprehensively evaluating the potential of NGAL as a diagnostic and prognostic tool for DN. Furthermore, assessing the sensitivity and specificity of NGAL in detecting early-stage DN will provide valuable insights into its clinical applicability and reliability.

A planned meta-analysis was conducted following PRISMA and MOOSE guidelines. The PubMed database was searched from January 2016 to June 2023 for English-language studies on DN and NGAL. Fifteen eligible studies were included as per the criteria. Data on serum NGAL levels in DN patients and healthy controls were analyzed using Stata 16.0 software.

The study revealed a significantly higher mean serum NGAL level in DN patients (168.08 ng/ml, 95% CI: 105.50-230.67) compared to healthy controls (75.02 ng/ml, 95% CI: 43.02-107.03), demonstrating NGAL's potential as a biomarker (P=0.01).

NGAL offers a powerful tool for DN diagnosis, staging, and monitoring, surpassing traditional markers in sensitivity. Challenges include defining universal threshold values and ensuring consistent test performance across diverse clinical settings. The study underscores NGAL's potential in transforming DN diagnosis and management.

Objective: This study investigated to probe ferroptosis-related diagnostic biomarkers and underlying molecular mechanisms in Diabetic nephropathy (DN). Methods: GSE30122 and GSE1009 from GEO database were used as training and verification sets, respectively, to screen differentially expressed ferroptosis-related genes (FRGs). These genes were further analyzed using GO, KEGG, and GSEA methods, and screened with PPI, LASSO, and SVM-RFE to identify ferroptosis-related diagnostic biomarkers for DN. A diagnostic model was established using the Glm function and verified with ROC curve. The relationship between these biomarkers and immune cell was analyzed, and qRT-PCR and Western blot were used to detect the expression of these biomarkers in kidney tissues and identify the effect of TP53 on DN development. Results: Fifty one differentially expressed FRGs were enriched in bioprocesses such as p53 signaling pathway, oxidative stress and chemical stress response, and mTOR signaling pathway. TP53, RB1, NF2, RRM2, PRDX1, and CDC25A were identified as ferroptosis-related diagnostic biomarkers for DN. TP53 showed the most differential expression. ROC analysis showed that AUC values of TP53, RB1, NF2, RRM2, PRDX1, and CDC25A were 0.751, 0.705, 0.725, 0.882, 0.691, and 0.675, respectively. The AUC value of DN diagnosis model was 0.939 in training set and 1.000 in verification set. qRT-PCR results confirmed significant differences in these six biomarkers between DN and normal kidney tissue (p < 0.05), and correlation analysis showed that five biomarkers were significantly correlated with infiltrating immune cells (p < 0.05). Furthermore, western blots showed that TP53 promotes apoptosis through PI3K-AKT signaling in DN. Conclusion: TP53, RB1, NF2, RRM2, PRDX1, and CDC25A have potential as diagnostic biomarkers for DN. The diagnostic model containing the above six biomarkers performs well in the diagnosis of DN. Five of the six biomarkers are strongly associated with several infiltrating immune cells. TP53 may play an essential role in the development of DN.

Diabetic nephropathy (DN) is a serious complication of diabetes, and its pathogenesis has not been fully elucidated. Recently, communication between organs has gradually become a new focus in the study of diseases pathogenesis, and abnormal interorgan communication has been proven to be involved in the occurrence and progression of many diseases. As an important metabolic organ in the human body, the liver plays an important role in maintaining homeostasis in humans. The liver secretes a series of proteins called hepatokines that affect adjacent and distal organs through paracrine or endocrine signaling pathways. In this review, we summarize some of the hepatokines identified to date and describe their roles in DN to discuss the possibility that the liver-renal axis is potentially useful as a therapeutic target for DN. We summarize the important hepatokines identified thus far and discuss their relationship with DN. We propose for the first time that the "liver-renal axis" is a potential therapeutic target in individuals with DN.

Diabetic nephropathy (DN) is a serious complication of diabetes affecting about half the people with diabetes and the leading cause of end stage renal disease (ESRD). Albuminuria and creatinine levels are currently the classic markers for the diagnosis of DN. However, many shortcomings are arising from the use of these markers mainly because they are not specific to DN and their levels are altered by multiple non-pathological factors. Therefore, the aim of this study is to identify better markers for the accurate and early diagnosis of DN. The study was performed on 159 subjects including 42 control subjects, 50 T2D without DN and 67 T2D subjects with DN. Our data show that circulating N-cadherin levels are significantly higher in the diabetic patients who are diagnosed with DN (842.6 ± 98.6 mg/l) compared to the diabetic patients who do not have DN (470.8 ± 111.5 mg/l) and the non-diabetic control group (412.6 ± 41.8 mg/l). We also report that this increase occurs early during the developmental stages of the disease since N-cadherin levels are significantly elevated in the microalbuminuric patients when compared to the healthy control group. In addition, we show a significant correlation between N-cadherin levels and renal markers including creatinine (in serum and urine), urea and eGFR in all the diabetic patients. In conclusion, our study presents N-cadherin as a novel marker for diabetic nephropathy that can be used as a valuable prognostic and diagnostic tool to slow down or even inhibit ESRD.