The relationships between markers of tubular injury and intrarenal haemodynamic function in adults with and without type 1 diabetes: Results from the Canadian Study of Longevity in Type 1 Diabetes

Minireview: Understanding and targeting inflammatory, hemodynamic and injury markers for cardiorenal protection in type 1 diabetes

The coexistence of cardiovascular disease (CVD) and diabetic kidney disease (DKD) is common in people with type 1 diabetes (T1D) and is strongly associated with an increased risk of morbidity and mortality. Hence, it is imperative to explore robust tools that can accurately reflect the development and progression of cardiorenal complications. Several cardiovascular and kidney biomarkers have been identified to detect at-risk individuals with T1D. The primary aim of this review is to highlight biomarkers of injury, inflammation, or renal hemodynamic changes that may influence T1D susceptibility to CVD and DKD. We will also examine the impact of approved pharmacotherapies for type 2 diabetes, including renin-angiotensin-aldosterone system (RAAS) inhibitors, sodium-glucose cotransporter-2 (SGLT2) inhibitors and glucagon-like peptide-1 receptor agonists (GLP-1RAs) on candidate biomarkers for cardiorenal complications in people with T1D and discuss how these changes may potentially mediate kidney and cardiovascular protection. Identifying predictive and prognostic biomarkers for DKD and CVD may highlight potential drug targets to attenuate cardiorenal disease progression, implement novel risk stratification measures in clinical trials, and improve the assessment, diagnosis, and treatment of at-risk individuals with T1D.

Neutrophil Gelatinase-Associated Lipocalin (NGAL) as a potential early biomarker for diabetic nephropathy: a meta-analysis

BACKGROUND

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.

METHODOLOGY

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.

RESULT

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).

CONCLUSION

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.

Unveiling the Hidden Power of Uromodulin: A Promising Potential Biomarker for Kidney Diseases

Uromodulin, also known as Tamm-Horsfall protein, represents the predominant urinary protein in healthy individuals. Over the years, studies have revealed compelling associations between urinary and serum concentrations of uromodulin and various parameters, encompassing kidney function, graft survival, cardiovascular disease, glucose metabolism, and overall mortality. Consequently, there has been a growing interest in uromodulin as a novel and effective biomarker with potential applications in diverse clinical settings. Reduced urinary uromodulin levels have been linked to an elevated risk of acute kidney injury (AKI) following cardiac surgery. In the context of chronic kidney disease (CKD) of different etiologies, urinary uromodulin levels tend to decrease significantly and are strongly correlated with variations in estimated glomerular filtration rate. The presence of uromodulin in the serum, attributable to basolateral epithelial cell leakage in the thick ascending limb, has been observed. This serum uromodulin level is closely associated with kidney function and histological severity, suggesting its potential as a biomarker capable of reflecting disease severity across a spectrum of kidney disorders. The UMOD gene has emerged as a prominent locus linked to kidney function parameters and CKD risk within the general population. Extensive research in multiple disciplines has underscored the biological significance of the top UMOD gene variants, which have also been associated with hypertension and kidney stones, thus highlighting the diverse and significant impact of uromodulin on kidney-related conditions. UMOD gene mutations are implicated in uromodulin-associated kidney disease, while polymorphisms in the UMOD gene show a significant association with CKD. In conclusion, uromodulin holds great promise as an informative biomarker, providing valuable insights into kidney function and disease progression in various clinical scenarios. The identification of UMOD gene variants further strengthens its relevance as a potential target for better understanding kidney-related pathologies and devising novel therapeutic strategies. Future investigations into the roles of uromodulin and regulatory mechanisms are likely to yield even more profound implications for kidney disease diagnosis, risk assessment, and management.

Selected Serum Markers Associated with Pathogenesis and Clinical Course of Type 1 Diabetes in Pediatric Patients—The Effect of Disease Duration

Biochemical abnormalities in the course of type 1 diabetes (T1D) may cause the production/activation of various proteins and peptides influencing treatment and causing a risk of complications. The aim of this study was to assess concentrations of selected serum substances involved in the pathogenesis and course of T1D and to correlate their concentrations with the duration of T1D. The study included patients with T1D (n = 156) at the age of 3–17, who were divided according to the duration of the disease into those newly diagnosed (n = 30), diagnosed after 3–5 (n = 77), 6–7 (n = 25), and over 7 (n = 24) years from the onset of T1D, and age-matched healthy controls (n = 30). Concentrations of amylin (IAPP), proamylin (proIAPP), catestatin (CST), chromogranin A (ChgA), nerve growth factor (NFG), platelet-activating factor (PAF), uromodulin (UMOD), and intestinal fatty acid binding protein (I-FABP) were measured in sera using immunoenzymatic tests. There were significant differences in concentrations of all the substances except UMOD and NGF between T1D patients and healthy children. The duration of the disease affected concentrations of CST, ChgA, PAF, and NGF, i.e., proteins/peptides which could have an impact on the course of T1D and the development of complications. In long-term patients, a decrease in concentrations of CST and ChgA, and an increase in PAF concentrations were found. In the case of NGF, a decrease was observed after the initial high values, followed by an increase over 7 years after T1D diagnosis. Concluding, the results show that concentrations of selected serum indicators may change in the course of T1D. Further studies are needed to establish whether these indicators could be used in the context of predicting long-term complications.

Identification of a novel immune landscape signature as effective diagnostic markers related to immune cell infiltration in diabetic nephropathy

Background

The study aimed to identify core biomarkers related to diagnosis and immune microenvironment regulation and explore the immune molecular mechanism of diabetic nephropathy (DN) through bioinformatics analysis.

Methods

GSE30529, GSE99325, and GSE104954 were merged with removing batch effects, and different expression genes (DEGs) were screened at a criterion |log2FC| >0.5 and adjusted P <0.05. KEGG, GO, and GSEA analyses were performed. Hub genes were screened by conducting PPI networks and calculating node genes using five algorithms with CytoHubba, followed by LASSO and ROC analysis to accurately identify diagnostic biomarkers. In addition, two different GEO datasets, GSE175759 and GSE47184, and an experiment cohort with 30 controls and 40 DN patients detected by IHC, were used to validate the biomarkers. Moreover, ssGSEA was performed to analyze the immune microenvironment in DN. Wilcoxon test and LASSO regression were used to determine the core immune signatures. The correlation between biomarkers and crucial immune signatures was calculated by Spearman analysis. Finally, cMap was used to explore potential drugs treating renal tubule injury in DN patients.

Results

A total of 509 DEGs, including 338 upregulated and 171 downregulated genes, were screened out. “chemokine signaling pathway” and “cell adhesion molecules” were enriched in both GSEA and KEGG analysis. CCR2, CX3CR1, and SELP, especially for the combination model of the three genes, were identified as core biomarkers with high diagnostic capabilities with striking AUC, sensitivity, and specificity in both merged and validated datasets and IHC validation. Immune infiltration analysis showed a notable infiltration advantage for APC co-stimulation, CD8+ T cells, checkpoint, cytolytic activity, macrophages, MHC class I, and parainflammation in the DN group. In addition, the correlation analysis showed that CCR2, CX3CR1, and SELP were strongly and positively correlated with checkpoint, cytolytic activity, macrophages, MHC class I, and parainflammation in the DN group. Finally, dilazep was screened out as an underlying compound for DN analyzed by CMap.

Conclusions

CCR2, CX3CR1, and SELP are underlying diagnostic biomarkers for DN, especially in their combination. APC co-stimulation, CD8+ T cells, checkpoint, cytolytic activity, macrophages, MHC class I, and parainflammation may participate in the occurrence and development of DN. At last, dilazep may be a promising drug for treating DN.

Review of potential biomarkers of inflammation and kidney injury in diabetic kidney disease

Diabetic kidney disease is expected to increase rapidly over the coming decades with rising prevalence of diabetes worldwide. Current measures of kidney function based on albuminuria and estimated glomerular filtration rate do not accurately stratify and predict individuals at risk of declining kidney function in diabetes. As a result, recent attention has turned towards identifying and assessing the utility of biomarkers in diabetic kidney disease. This review explores the current literature on biomarkers of inflammation and kidney injury focussing on studies of single or multiple biomarkers between January 2014 and February 2020. Multiple serum and urine biomarkers of inflammation and kidney injury have demonstrated significant association with the development and progression of diabetic kidney disease. Of the inflammatory biomarkers, tumour necrosis factor receptor-1 and -2 were frequently studied and appear to hold most promise as markers of diabetic kidney disease. With regards to kidney injury biomarkers, studies have largely targeted markers of tubular injury of which kidney injury molecule-1, beta-2-microglobulin and neutrophil gelatinase-associated lipocalin emerged as potential candidates. Finally, the use of a small panel of selective biomarkers appears to perform just as well as a panel of multiple biomarkers for predicting kidney function decline.

Discoveries from the study of longstanding type 1 diabetes

Award programmes that acknowledge the remarkable accomplishments of long-term survivors with type 1 diabetes have naturally evolved into research programmes to determine the factors associated with survivorship and resistance to chronic complications. In this review, we present an overview of the methodological sources of selection bias inherent in survivorship research (selection of those with early-onset diabetes, incidence-prevalence bias and bias from losses to follow-up in cohort studies) and the breadth and depth of literature focusing on this special study population. We focus on the learnings from the study of longstanding type 1 diabetes on discoveries about the natural history of insulin production loss and microvascular complications, and mechanisms associated with them that may in future offer therapeutic targets. We detail descriptive findings about the prevalence of preserved insulin production and resistance to complications, and the putative mechanisms associated with such resistance. To date, findings imply that the following mechanisms exist: strategies to maintain or recover beta cells and their function; activation of specific glycolytic enzymes such as pyruvate kinase M2; modification of AGE production and processing; novel mechanisms for modification of renin-angiotensin-aldosterone system activation, in particular those that may normalise afferent rather than efferent renal arteriolar resistance; and activation and modification of processes such as retinol binding and DNA damage checkpoint proteins. Among the many clinical and public health insights, research into this special study population has identified putative mechanisms that may in future serve as therapeutic targets, knowledge that likely could not have been gained without studying long-term survivors.

Vasopressin associated with renal vascular resistance in adults with longstanding type 1 diabetes with and without diabetic kidney disease

OBJECTIVE

Arginine vasopressin (AVP) and its surrogate, copeptin, have been implicated in diabetic kidney disease (DKD) pathogenesis, which develops in a subset of people with longstanding type 1 diabetes, but not in others (DKD Resistors). We hypothesized that patients with DKD would exhibit higher copeptin concentrations vs. DKD Resistors.

METHODS

Participants with type 1 diabetes (n = 62, duration ≥50 years) were stratified into 42 DKD Resistors and 20 with DKD (eGFR ≤60 mL/min/1.73m² or ≥30 mg/day urine albumin), and age/sex-matched controls (HC, n = 74) were included. Glomerular filtration rate (GFR) and effective renal plasma flow (ERPF) were calculated by inulin and p-aminohippurate clearance before and after angiotensin II (ang II) infusion. Renal vascular resistance (RVR) was calculated as mean arterial pressure/renal blood flow. Plasma copeptin, renin, aldosterone, neutrophil gelatinase-associated lipocalin (NGAL), and urea concentrations were measured, along with 24-h urine volume.

RESULTS

DKD resistors had lower copeptin (95% CI: 4.0 [3.4-4.8] pmol/l) compared to DKD (5.8 [4.5-7.6] pmol/l, p = 0.02) and HC (4.8 [4.1-5.5] pmol/l, p = 0.01) adjusting for age, sex and HbA1c. In type 1 diabetes, higher copeptin correlated with lower GFR (r: -0.32, p = 0.01) and higher renin concentration (r: 0.40, p = 0.002) after multivariable adjustments. These relationships were not evident in HC. Copeptin inversely associated with RVR change following exogenous ang II only in participants with type 1 diabetes (β ± SE: -6.9 ± 3.4, p = 0.04).

CONCLUSIONS

In longstanding type 1 diabetes, copeptin was associated with intrarenal renin-angiotensin-aldosterone system (RAAS) activation and renal hemodynamic function, suggesting interplay between AVP and RAAS in DKD pathogenesis.

Identification of Key Candidate Genes and Chemical Perturbagens in Diabetic Kidney Disease Using Integrated Bioinformatics Analysis

Globally, nearly 40 percent of all diabetic patients develop serious diabetic kidney disease (DKD). The identification of the potential early-stage biomarkers and elucidation of their underlying molecular mechanisms in DKD are required. In this study, we performed integrated bioinformatics analysis on the expression profiles GSE111154, GSE30528 and GSE30529 associated with early diabetic nephropathy (EDN), glomerular DKD (GDKD) and tubular DKD (TDKD), respectively. A total of 1,241, 318 and 280 differentially expressed genes (DEGs) were identified for GSE30258, GSE30529, and GSE111154 respectively. Subsequently, 280 upregulated and 27 downregulated DEGs shared between the three GSE datasets were identified. Further analysis of the gene expression levels conducted on the hub genes revealed SPARC (Secreted Protein Acidic And Cysteine Rich), POSTN (periostin), LUM (Lumican), KNG1 (Kininogen 1), FN1 (Fibronectin 1), VCAN (Versican) and PTPRO (Protein Tyrosine Phosphatase Receptor Type O) having potential roles in DKD progression. FN1, LUM and VCAN were identified as upregulated genes for GDKD whereas the downregulation of PTPRO was associated with all three diseases. Both POSTN and SPARC were identified as the overexpressed putative biomarkers whereas KNG1 was found as downregulated in TDKD. Additionally, we also identified two drugs, namely pidorubicine, a topoisomerase inhibitor (LINCS ID- BRD-K04548931) and Polo-like kinase inhibitor (LINCS ID- BRD-K41652870) having the validated role in reversing the differential gene expression patterns observed in the three GSE datasets used. Collectively, this study aids in the understanding of the molecular drivers, critical genes and pathways that underlie DKD initiation and progression.

Individual uromodulin serum concentration is independent of glomerular filtration rate in healthy kidney donors

OBJECTIVES

The mucoprotein uromodulin is considered to correlate with glomerular filtration rates (GFR) in patients with chronic kidney disease (CKD). Here we investigated how serum uromodulin is associated with measured GFR using inulin-clearance and GFR estimated by CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration) equation in healthy subjects.

METHODS

We assessed possible correlations between uromodulin serum concentrations, inulin-GFR and CKD-EPI-GFR in a well characterized study cohort of 112 healthy living kidney donors with two kidneys before and 64 with one kidney after kidney donation. A subgroup of 32 individuals, which presented data before and after nephrectomy, was assessed separately.

RESULTS

All 112 healthy living kidney donors with two kidneys revealed individual serum uromodulin concentrations between 60.1 and 450.5 µg/L. Sixty-four healthy kidney donors after nephrectomy had significantly lower median (interquartile range) serum uromodulin concentrations (124 [101-166] vs. 185 [152-238] µg/L), inulin-GFR (67.3 [60.6-74.6] vs. 93.5 [82.1-104.4] mL/min/1.73 m²), and CKD-EPI-GFR (61.2 [53.1-69.7] vs. 88.6 [80.0-97.1] mL/min/1.73 m²) as compared to the 112 donors before donation (p<0.001). The subgroup of 32 subjects, which presented data before and after nephrectomy, showed almost the same pattern of kidney function. No statistically relevant associations were found between serum uromodulin and inulin-GFR or CKD-EPI-GFR regarding this healthy population.

CONCLUSIONS

These novel findings indicate that - in contrast to patients with CKD - serum uromodulin concentrations are not correlated with measured and estimated GFR in healthy individuals.

Precision medicine in distinct heart failure phenotypes: Focus on clinical epigenetics

Heart failure (HF) management is challenging due to high clinical heterogeneity of this disease which makes patients responding differently to evidence-based standard therapy established by the current reductionist approach. Better understanding of the genetic and epigenetic interactions may clarify molecular signatures underlying maladaptive responses in HF, including metabolic shift, myocardial injury, fibrosis, and mitochondrial dysfunction. DNA methylation, histone modifications and micro-RNA (miRNAs) may be major epigenetic players in the pathogenesis of HF. DNA hypermethylation of the kruppel-like factor 15 (KLF15) gene plays a key role in switching the failing heart from oxidative to glycolytic metabolism. Moreover, hypomethylation at H3K9 promoter level of atrial natriuretic peptide (ANP) and brain natriuretic peptide (BNP) genes also leads to reactivation of fetal genes in man. The role of miRNAs has been investigated in HF patients undergoing heart transplantation, for whom miR-10a, miR-155, miR-31, and miR-92 may be putative useful prognostic biomarkers. Recently, higher RNA methylation levels have been observed in ischemic human hearts, opening the era of "epitranscriptome" in the pathogenesis of HF. Currently, hydralazine, statins, apabetalone, and omega-3 polyunsatured fatty acids (PUFA) are being tested in clinical trials to provide epigenetic-driven therapeutic interventions. Moreover, network-oriented analysis could advance current medical practice by focusing on protein-protein interactions (PPIs) perturbing the "cardiac" interactome. In this review, we provide an epigenetic map of maladaptive responses in HF patients. Furthermore, we propose the "EPi-transgeneratIonal network mOdeling for STratificatiOn of heaRt Morbidity" (EPIKO-STORM), a clinical research strategy offering novel opportunities to stratify the natural history of HF.