Insights into Diabetic Kidney Disease Using Urinary Proteomics and Bioinformatics

DNA Methyltransferase Isoforms Regulate Endothelial Cell Exosome Proteome Composition

Extrinsic and intrinsic pathological stimuli in vascular disorders induce DNA methylation based epigenetic reprogramming in endothelial cells, leads to perturbed gene expression and subsequently results in endothelial dysfunction (ED). ED is also characterized by release of exosomes with altered proteome leading to paracrine interactions in vasculature and subsequently contributing to manifestation, progression and severity of vascular complications. However, epigenetic regulation of exosome proteome is not known. Hence, our present study aimed to understand influence of DNA methylation on exosome proteome composition and their influence on endothelial cell (EC) function. DNMT isoforms (DNMT1, DNMT3A, and DNMT3B) were overexpressed using lentivirus in ECs. Exosomes were isolated from all groups, as well as from ECs and C57BL/6 mice treated with 5-aza-2'-deoxycytidine. 3D spheroid assay was performed to understand the influence of exosomes derived from cells overexpressing DNMTs on EC functions. Further, the exosomes were subjected to TMT labelled proteomics analysis followed by validation.3D spheroid assay showed increase in the pro-angiogenic activity in response to exosomes derived from overexpressing cells which was impeded by inclusion of 5-aza-2'-deoxycytidine. Our results showed that exosome proteome and PTMs are significantly modulated and are associated with dysregulation of vascular homeostasis, metabolism, inflammation and endothelial cell functions. In vitro and in vivo validation showed elevated DNMT1 and TGF-β1 exosome proteins due to DNMT1 and DNMT3A overexpression, not DNMT3B which was mitigated by 5-aza-2'-deoxycytidine indicating epigenetic regulation. Further, exosomes induced ED as evidenced by reduced expression of phospho-eNOSser1177. Our study unveils epigenetically regulated exosome proteins, aiding management of vascular complications.

New insights into the role of immunity and inflammation in diabetic kidney disease in the omics era

Diabetic kidney disease (DKD) is becoming the leading cause of chronic kidney disease, especially in the industrialized world. Despite mounting evidence has demonstrated that immunity and inflammation are highly involved in the pathogenesis and progression of DKD, the underlying mechanisms remain incompletely understood. Substantial molecules, signaling pathways, and cell types participate in DKD inflammation, by integrating into a complex regulatory network. Most of the studies have focused on individual components, without presenting their importance in the global or system-based processes, which largely hinders clinical translation. Besides, conventional technologies failed to monitor the different behaviors of resident renal cells and immune cells, making it difficult to understand their contributions to inflammation in DKD. Recently, the advancement of omics technologies including genomics, epigenomics, transcriptomics, proteomics, and metabolomics has revolutionized biomedical research, which allows an unbiased global analysis of changes in DNA, RNA, proteins, and metabolites in disease settings, even at single-cell and spatial resolutions. They help us to identify critical regulators of inflammation processes and provide an overview of cell heterogeneity in DKD. This review aims to summarize the application of multiple omics in the field of DKD and emphasize the latest evidence on the interplay of inflammation and DKD revealed by these technologies, which will provide new insights into the role of inflammation in the pathogenesis of DKD and lead to the development of novel therapeutic approaches and diagnostic biomarkers.

Sympathetic skin response for early detection of type 2 diabetic peripheral neuropathy and nephropathy

BACKGROUND

Diabetic peripheral neuropathy (DPN) and diabetic nephropathy (DN) are common complications of type 2 diabetes mellitus (T2DM). Although nerve conduction studies (NCS) and sympathetic skin response (SSR) can detect DPN, the more sensitive method for early diagnosis remains unclear. Furthermore, whether DPN can be used as a predictor for diabetic nephropathy needs clarification.

METHODS

We evaluated nerve conduction studies, sympathetic skin response, and the diabetic nephropathy indicator microalbuminuria (MAU) in 192 patients with type 2 diabetes mellitus and 50 healthy controls.

RESULTS

Patients with type 2 diabetes mellitus showed a lower sensory nerve conduction velocity (SCV), sensory active nerve potential (SNAP), motor nerve conduction velocity (MCV), and compound motor action potential (CMAP) than the controls on NCS. Abnormal rates for nerve conduction studies and sympathetic skin response were 75.0% and 83.3%, respectively, in patients with type 2 diabetes mellitus. Interestingly, 54.2% of patients with normal nerve conduction studies had an abnormal sympathetic skin response. Moreover, we found a positive correlation between sympathetic skin response and microalbuminuria for the first time. The abnormal rate of microalbuminuria was 53.8%, lower than that of abnormal nerve conduction studies or sympathetic skin response patients.

CONCLUSION

Sympathetic skin response is a more sensitive method than nerve conduction studies for the early diagnosis of diabetic peripheral neuropathy. Abnormal sympathetic skin response might serve as an indicator for early diabetic nephropathy. Additionally, diabetic peripheral neuropathy may occur earlier than diabetic nephropathy in the development of type 2 diabetes mellitus.

ACSL1: A preliminary study that provides a new target for the treatment of renal fibrosis could bring new insights in diabetic kidney disease

BACKGROUND

Renal fibrosis is the main cause of the development of diabetic kidney disease (DKD). ACSL1 plays an important role in colon cancer and liver fibrosis.

METHODS

We screened ACSL1 by proteomics analysis and then verified the expression of ACSL1 in the urine of diabetic nephropathy patients by WB and ELISA. Then, a total of 12db/m and db/db mice were used to verify the association between renal fibrosis and ACSL1. Periodic acid-Schiff (PAS) staining, Masson staining, and immunostaining were performed for histological studies. The relationship between ACSL1 and renal fibrosis was studied by knocking down ACSL1 in cell experiments.

RESULTS

The expression of ACSL1 was significantly increased in the exfoliated urine cells and urine supernatant of diabetic nephropathy patients and was closely related to renal function. In addition, the expression of ACSL1 was significantly increased in the renal tissues of db/db mice with fibrosis. Knocking down ACSL1 in HK-2 cells was shown to reverse renal fibrosis induced by high glucose.

CONCLUSIONS

We found a potential therapeutic target for preventing or ameliorating the progression of DKD fibrosis. Reducing ACSL1 expression may be a new strategy for the treatment of renal fibrosis caused by DKD, which provides an experimental theoretical basis for new drug research.

In-depth urinary and exosome proteome profiling analysis identifies novel biomarkers for diabetic kidney disease

Diabetic kidney disease (DKD) is a major microvascular complication of type 2 diabetes mellitus (T2DM). Monitoring the early diagnostic period and disease progression plays a crucial role in treating DKD. In this study, to comprehensively elucidate the molecular characteristics of urinary proteins and urinary exosome proteins in type 2 DKD, we performed large-scale urinary proteomics (n=144) and urinary exosome proteomics (n=44) analyses on T2DM patients with albuminuria in varying degrees. The dynamics analysis of the urinary and exosome proteomes in our study provides a valuable resource for discovering potential urinary biomarkers in patients with DKD. A series of potential biomarkers, such as SERPINA1 and transferrin (TF), were detected and validated to be used for DKD diagnosis or disease monitoring. The results of our study comprehensively elucidated the changes in the urinary proteome and revealed several potential biomarkers reflecting the progression of DKD, which provide a reference for DKD biomarker screening.

Precision Medicine in Diabetic Kidney Disease: A Narrative Review Framed by Lived Experience

Purpose of review

Diabetic kidney disease (DKD) is a leading cause of chronic kidney disease (CKD) for which many treatments exist that have been shown to prevent CKD progression and kidney failure. However, DKD is a complex and heterogeneous etiology of CKD with a spectrum of phenotypes and disease trajectories. In this narrative review, we discuss precision medicine approaches to DKD, including genomics, metabolomics, proteomics, and their potential role in the management of diabetes mellitus and DKD. A patient and caregivers of patients with lived experience with CKD were involved in this review.

Sources of information

Original research articles were identified from MEDLINE and Google Scholar using the search terms "diabetes," "diabetic kidney disease," "diabetic nephropathy," "chronic kidney disease," "kidney failure," "dialysis," "nephrology," "genomics," "metabolomics," and "proteomics."

Methods

A focused review and critical appraisal of existing literature regarding the precision medicine approaches to the diagnosis, prognosis, and treatment of diabetes and DKD framed by a patient partner's/caregiver's lived experience.

Key findings

Distinguishing diabetic nephropathy from CKD due to other types of DKD and non-DKD is challenging and typically requires a kidney biopsy for a diagnosis. Biomarkers have been identified to assist with the prediction of the onset and progression of DKD, but they have yet to be incorporated and evaluated relative to clinical standard of care CKD and kidney failure risk prediction tools. Genomics has identified multiple causal genetic variants for neonatal diabetes mellitus and monogenic diabetes of the young that can be used for diagnostic purposes and to specify antiglycemic therapy. Genome-wide-associated studies have identified genes implicated in DKD pathophysiology in the setting of type 1 and 2 diabetes but their translational benefits are lagging beyond polygenetic risk scores. Metabolomics and proteomics have been shown to improve diagnostic accuracy in DKD, have been used to identify novel pathways involved in DKD pathogenesis, and can be used to improve the prediction of CKD progression and kidney failure as well as predict response to DKD therapy.

Limitations

There are a limited number of large, high-quality prospective observational studies and no randomized controlled trials that support the use of precision medicine based approaches to improve clinical outcomes in adults with or at risk of diabetes and DKD. It is unclear which patients may benefit from the clinical use of genomics, metabolomics and proteomics along the spectrum of DKD trajectory.

Implications

Additional research is needed to evaluate the role of the use of precision medicine for DKD management, including diagnosis, differentiation of diabetic nephropathy from other etiologies of DKD and CKD, short-term and long-term risk prognostication kidney outcomes, and the prediction of response to and safety of disease-modifying therapies.

Machine-learning algorithm-based prediction of a diagnostic model based on oxidative stress-related genes involved in immune infiltration in diabetic nephropathy patients

Diabetic nephropathy (DN) is the most prevalent microvascular consequence of diabetes and has recently risen to the position of the world's second biggest cause of end-stage renal diseases. Growing studies suggest that oxidative stress (OS) responses are connected to the advancement of DN. This study aimed to developed a novel diagnostic model based on OS-related genes. The differentially expressed oxidative stress-related genes (DE-OSRGs) experiments required two human gene expression datasets, which were given by the GEO database (GSE30528 and GSE96804, respectively). The potential diagnostic genes were identified using the SVM-RFE assays and the LASSO regression model. CIBERSORT was used to determine the compositional patterns of the 22 different kinds of immune cell fraction seen in DN. These estimates were based on the combined cohorts. DN serum samples and normal samples were both subjected to RT-PCR in order to investigate the degree to which certain genes were expressed. In this study, we were able to locate 774 DE-OSRGs in DN. The three marker genes (DUSP1, PRDX6 and S100A8) were discovered via machine learning on two different machines. The high diagnostic value was validated by ROC tests, which focused on distinguishing DN samples from normal samples. The results of the CIBERSORT study suggested that DUSP1, PRDX6, and S100A8 may be associated to the alterations that occur in the immunological microenvironment of DN patients. Besides, the results of RT-PCR indicated that the expression of DUSP1, PRDX6, and S100A8 was much lower in DN serum samples compared normal serum samples. The diagnostic value of the proposed model was likewise verified in our cohort, with an area under the curve of 9.946. Overall, DUSP1, PRDX6, and S100A8 were identified to be the three diagnostic characteristic genes of DN. It's possible that combining these genes will be effective in diagnosing DN and determining the extent of immune cell infiltration.

Integrin β6 mediates epithelial-mesenchymal transition in diabetic kidney disease

The progression of diabetic kidney disease (DKD) is associated with increased fibronectin (FN) levels in proximal tubular epithelial cells. Bioinformatics analysis showed that integrin β6 and cell adhesion function were significantly changed in the cortices of db/db mice. Remodelling of cell adhesion is one of the core changes during epithelial-mesenchymal transition (EMT) in DKD. Integrin is a family of transmembrane proteins that regulates cell adhesion and migration, and extracellular FN is the major ligand of integrin β6. We found that the expression of integrin β6 was elevated in the proximal tubules of db/db mice and FN-induced renal proximal tubule cells. The levels of EMT were also significantly increased in vivo and in vitro. In addition, FN treatment activated the Fak/Src pathway, increased the expression of p-YAP, and then upregulated the Notch1 pathway in diabetic proximal tubules. Knockdown of integrin β6 or Notch1 attenuated reversed the EMT aggravation induced by FN. Furthermore, urinary integrin β6 was significantly increased in DKD patients. Our findings reveal a critical role of integrin β6 in regulating EMT in proximal tubular epithelial cells and identify a novel direction for the detection and treatment of DKD.

Peptidome and Transcriptome Analysis of Plant Peptides Involved in Bipolaris maydis Infection of Maize

Southern corn leaf blight (SCLB) caused by Bipolaris maydis threatens maize growth and yield worldwide. In this study, TMT-labeled comparative peptidomic analysis was established between infected and uninfected maize leaf samples using liquid-chromatography-coupled tandem mass spectrometry. The results were further compared and integrated with transcriptome data under the same experimental conditions. Plant peptidomic analysis identified 455 and 502 differentially expressed peptides (DEPs) in infected maize leaves on day 1 and day 5, respectively. A total of 262 common DEPs were identified in both cases. Bioinformatic analysis indicated that the precursor proteins of DEPs are associated with many pathways generated by SCLB-induced pathological changes. The expression profiles of plant peptides and genes in maize plants were considerably altered after B. maydis infection. These findings provide new insights into the molecular mechanisms of SCLB pathogenesis and offer a basis for the development of maize genotypes with SCLB resistance.

Understanding the Current Landscape of Kidney Disease in Canada to Advance Precision Medicine Guided Personalized Care

Purpose of Review

To understand the impact of kidney disease in Canada and the priority areas of kidney research that can benefit from patient-oriented, precision medicine research using novel technologies.

Sources of Information

Information was collected through discussions between health care professionals, researchers, and patient partners. Literature was compiled using search engines (PubMed, PubMed central, Medline, and Google) and data from the Canadian Organ Replacement Register.

Methods

We reviewed the impact, prevalence, economic burden, causes of kidney disease, and priority research areas in Canada. After reviewing the priority areas for kidney research, potential avenues for future research that can integrate precision medicine initiatives for patient-oriented research were outlined.

Key Findings

Chronic kidney disease (CKD) remains among the top causes of morbidity and mortality in the world and exerts a large financial strain on the health care system. Despite the increasing number of people with CKD, funding for basic kidney research continues to trail behind other diseases. Current funding strategies favor existing clinical treatment and patient educational strategies. The identification of genetic factors for various forms of kidney disease in the adult and pediatric populations provides mechanistic insight into disease pathogenesis. Allocation of resources and funding toward existing high-yield personalized research initiatives have the potential to significantly affect patient-oriented research outcomes but will be difficult due to a constant decline of funding for kidney research.

Limitations

This is an overview primarily focused on Canadian-specific literature rather than a comprehensive systematic review of the literature. The scope of our findings and conclusions may not be applicable to health care systems in other countries.

An in vitro approach to understand contribution of kidney cells to human urinary extracellular vesicles

Extracellular vesicles (EV) are membranous particles secreted by all cells and found in body fluids. Established EV contents include a variety of RNA species, proteins, lipids and metabolites that are considered to reflect the physiological status of their parental cells. However, to date, little is known about cell-type enriched EV cargo in complex EV mixtures, especially in urine. To test whether EV secretion from distinct human kidney cells in culture differ and can recapitulate findings in normal urine, we comprehensively analysed EV components, (particularly miRNAs, long RNAs and protein) from conditionally immortalised human kidney cell lines (podocyte, glomerular endothelial, mesangial and proximal tubular cells) and compared to EV secreted in human urine. EV from cell culture media derived from immortalised kidney cells were isolated by hydrostatic filtration dialysis (HFD) and characterised by electron microscopy (EM), nanoparticle tracking analysis (NTA) and Western blotting (WB). RNA was isolated from EV and subjected to miRNA and RNA sequencing and proteins were profiled by tandem mass tag proteomics. Representative sets of EV miRNAs, RNAs and proteins were detected in each cell type and compared to human urinary EV isolates (uEV), EV cargo database, kidney biopsy bulk RNA sequencing and proteomics, and single-cell transcriptomics. This revealed that a high proportion of the in vitro EV signatures were also found in in vivo datasets. Thus, highlighting the robustness of our in vitro model and showing that this approach enables the dissection of cell type specific EV cargo in biofluids and the potential identification of cell-type specific EV biomarkers of kidney disease.

Molecular profiling of urinary extracellular vesicles in chronic kidney disease and renal fibrosis

Chronic kidney disease (CKD) is a long-term kidney damage caused by gradual loss of essential kidney functions. A global health issue, CKD affects up to 16% of the population worldwide. Symptoms are often not apparent in the early stages, and if left untreated, CKD can progress to end-stage kidney disease (ESKD), also known as kidney failure, when the only possible treatments are dialysis and kidney transplantation. The end point of nearly all forms of CKD is kidney fibrosis, a process of unsuccessful wound-healing of kidney tissue. Detection of kidney fibrosis, therefore, often means detection of CKD. Renal biopsy remains the best test for renal scarring, despite being intrinsically limited by its invasiveness and sampling bias. Urine is a desirable source of fibrosis biomarkers as it can be easily obtained in a non-invasive way and in large volumes. Besides, urine contains biomolecules filtered through the glomeruli, mirroring the pathological state. There is, however, a problem of highly abundant urinary proteins that can mask rare disease biomarkers. Urinary extracellular vesicles (uEVs), which originate from renal cells and carry proteins, nucleic acids, and lipids, are an attractive source of potential rare CKD biomarkers. Their cargo consists of low-abundant proteins but highly concentrated in a nanosize-volume, as well as molecules too large to be filtered from plasma. Combining molecular profiling data (protein and miRNAs) of uEVs, isolated from patients affected by various forms of CKD, this review considers the possible diagnostic and prognostic value of uEVs biomarkers and their potential application in the translation of new experimental antifibrotic therapeutics.

The single-cell landscape of kidney immune cells reveals transcriptional heterogeneity in early diabetic kidney disease

The pathogenesis of diabetic kidney disease (DKD) involves multifactorial processes that converge to initiate and advance the disease. Although DKD is not typically classified as an inflammatory glomerular disease, mounting evidence supports the involvement of kidney inflammation as a key contributor in DKD pathogenesis, particularly through macrophages. However, detailed identification and corresponding phenotypic changes of macrophages in DKD remain poorly understood. To capture the gene expression changes in specific macrophage cell subsets in early DKD, we performed single-cell transcriptomic analysis of CD45-enriched kidney immune cells from type 1 diabetic OVE26 mice at two time points during the disease development. We also undertook a focused analysis of mononuclear phagocytes (macrophages and dendritic cells). Our results show increased resident and infiltrating macrophage subsets in the kidneys of mice with diabetes over time, with heightened expression of pro-inflammatory or anti-inflammatory genes in a subset-specific manner. Further analysis of macrophage polarization states in each subset in the kidneys showed changes consistent with the continuum of activation and differentiation states, with gene expression tending to shift toward undifferentiated phenotypes but with increased M1-like inflammatory phenotypes over time. By deconvolution analysis of RNAseq samples and by immunostaining of biopsies from patients with DKD, we further confirmed a differential expression of select genes in specific macrophage subsets essentially recapitulating the studies in mice. Thus, our study provides a comprehensive analysis of macrophage transcriptomic profiles in early DKD that underscores the dynamic macrophage phenotypes in disease progression.

Early renal structural changes and potential biomarkers in diabetic nephropathy

Diabetic nephropathy is one of the most serious microvascular complications of diabetes mellitus, with increasing prevalence and mortality. Currently, renal function is assessed clinically using albumin excretion rate and glomerular filtration rate. But before the appearance of micro-albumin, the glomerular structure has been severely damaged. Glomerular filtration rate based on serum creatinine is a certain underestimate of renal status. Early diagnosis of diabetic nephropathy has an important role in improving kidney function and delaying disease progression with drugs. There is an urgent need for biomarkers that can characterize the structural changes associated with the kidney. In this review, we focus on the early glomerular and tubular structural alterations, with a detailed description of the glomerular injury markers SMAD1 and Podocalyxin, and the tubular injury markers NGAL, Netrin-1, and L-FABP in the context of diabetic nephropathy. We have summarized the currently studied protein markers and performed bioprocess analysis. Also, a brief review of proteomic and scRNA-seq method in the search of diabetic nephropathy.

Clinical applications of plasma proteomics and peptidomics: Towards precision medicine

In the context of precision medicine, disease treatment requires individualized strategies based on the underlying molecular characteristics to overcome therapeutic challenges posed by heterogeneity. For this purpose, it is essential to develop new biomarkers to diagnose, stratify, or possibly prevent diseases. Plasma is an available source of biomarkers that greatly reflects the physiological and pathological conditions of the body. An increasing number of studies are focusing on proteins and peptides, including many involving the Human Proteome Project (HPP) of the Human Proteome Organization (HUPO), and proteomics and peptidomics techniques are emerging as critical tools for developing novel precision medicine preventative measures. Excitingly, the emerging plasma proteomics and peptidomics toolbox exhibits a huge potential for studying pathogenesis of diseases (e.g., COVID-19 and cancer), identifying valuable biomarkers and improving clinical management. However, the enormous complexity and wide dynamic range of plasma proteins makes plasma proteome profiling challenging. Herein, we summarize the recent advances in plasma proteomics and peptidomics with a focus on their emerging roles in COVID-19 and cancer research, aiming to emphasize the significance of plasma proteomics and peptidomics in clinical applications and precision medicine.

Clinical Evidence and Proposed Mechanisms for Cardiovascular and Kidney Benefits from Sodium-Glucose Co-transporter-2 Inhibitors

The number of people living with type 2 diabetes (T2D) and its complications worldwide is increasing at an alarming rate. Fortunately, our understanding of the benefits of glucose-lowering agents from the sodium-glucose co-transporter-2 (SGLT2) inhibitor and glucagon-like peptide-1 (GLP-1) receptor agonist classes on cardiovascular and kidney outcomes is advancing; this means we now have new options to mitigate the risks of these complications in patients with T2D. The SGLT2 inhibitors have consistently demonstrated benefits on atherosclerotic cardiovascular disease (ASCVD), chronic kidney disease (CKD) and heart failure (HF) events in dedicated outcome trials. Large guidelines groups now recommend SGLT2 inhibitors as a standard of care in patients with T2D and comorbid ASCVD, CKD and/ or HF. Evolving evidence additionally indicates kidney and HF benefits of SGLT2 inhibitors in populations without diabetes. These agents likely provide heart and kidney benefits through multiple mechanisms, as their impact on heart and kidney outcomes cannot be fully explained by their direct metabolic effects. On-going work to elucidate the beneficial mechanisms at play with SGLT2 inhibitors will help further optimize these life-saving therapies in patients with and without T2D.

Identification of the molecular mechanism and candidate markers for diabetic nephropathy

Background

Diabetic nephropathy (DN) is one of the most common complications in diabetic patients. New strategies are needed to delay the occurrence and development of this pathology.

Methods

Differentially expressed genes (DEGs) in glomeruli and renal tubules were identified using the GSE30122 dataset, and a co-expression network was constructed to identify the hub genes of modules. The biological function and signaling pathway of the module genes were also analyzed. In addition, the expression of 24 immune cells and the area under the receiver operating characteristic (ROC) curve (AUC) values of the hub genes were also calculated.

Results

A total of 1,778 DEGs were isolated from glomeruli and 1,996 DEGs were isolated from renal tubules. Nine modules and their hub genes were identified using the co-expression network. Enrichment analysis showed that the module genes were mainly enriched in immune inflammation and oxidative stress. The expressions of B cells, activated dendritic cell, and T cells in the glomeruli and renal tubules of DN patients were higher than those in the controls, and the correlation between these immune cells was the strongest. Collagen type I alpha 2 chain (COL1A2), the hub gene of the brown module, had the highest AUC values and may have a better clinical diagnostic ability.

Conclusions

In conclusion, the module genes and related biological functions and signaling pathways found in this study can deepen our understanding of the molecular mechanism of DN progression. COL1A2 may be a potential biomarker for DN.

Exosomal miR-7002-5p derived from highglucose-induced macrophages suppresses autophagy in tubular epithelial cells by targeting Atg9b

Macrophage infiltration plays an important role in the progression of diabetic nephropathy (DN). Previously, we demonstrated that highglucose-stimulated macrophage-derived exosomes (HG-exo) induces proliferation and extracellular matrix accumulation in glomerular mesangial cells, but its effect on tubular cells is unclear. This study aimed to explore the role of HG-exo on renal tubular injury in DN. The results show that HG-exo could induce dysfunction, autophagy inhibition, and inflammation in mouse tubular epithelial cell (mTEC) and C57 mouse kidney. Moreover, miR-7002-5p was differentially expressed in HG-exo based on miRNAs sequencing and bioinformatics analysis. A dual-luciferase reporter assay confirmed that Atg9b was the direct target gene of miR-7002-5p. Further experimentation showed that miR-7002-5p inhibition in vivo and vitro reserves HG-exo effects. These results demonstrated that HG-exo carries excessive miR-7002-5p and inhibits autophagy through targeting Atg9b; this process then induces renal tubular dysfunction and inflammation. In conclusion, our study clarifies the important role of macrophage-derived exosomes in DN and is expected to provide new insight on DN prevention and treatment.

Identification and validation of key biomarkers for the early diagnosis of diabetic kidney disease

Background: Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease. This study explored the core genes and pathways associated with DKD to identify potential diagnostic and therapeutic targets.

Methods: We downloaded microarray datasets GSE96804 and GSE104948 from the Gene Expression Omnibus (GEO) database. The dataset includes a total of 53 DKD samples and 41 normal samples. Differentially expressed genes (DEGs) were identified using the R package “limma”. The Metascape database was subjected to Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses to identify the pathway and functional annotations of DEGs. A WGCAN network was constructed, the hub genes in the turquoise module were screened, and the core genes were selected using LASSO regression to construct a diagnostic model that was then validated in an independent dataset. The core genes were verified by in vitro and in vivo experiments.

Results: A total of 430 DEGs were identified in the GSE96804 dataset, including 285 upregulated and 145 downregulated DEGs. WGCNA screened out 128 modeled candidate gene sets. A total of eight genes characteristic of DKD were identified by LASSO regression to build a prediction model. The results showed accuracies of 99.15% in the training set (GSE96804) and 94.44% and 100%, respectively, in the test (GSE104948-GPL22945 and GSE104948-GPL24120). Three core genes (OAS1, SECTM1, and SNW1) with high connectivity were selected among the modeled genes. In vitro and in vivo experiments confirmed the upregulation of these genes.

Conclusion: Bioinformatics analysis combined with experimental validation identified three novel DKD-specific genes. These findings may advance our understanding of the molecular basis of DKD and provide potential therapeutic targets for its clinical management.

In-silico analysis of interacting pathways through KIM-1 protein interaction in diabetic nephropathy

Background

Human Kidney Injury Molecule-1, also known as HAVCR-1 (Hepatitis A virus cellular receptor 1), belongs to the cell-surface protein of immunoglobulin superfamily involved in the phagocytosis by acting as scavenger receptor epithelial cells. The study focused on pinpointing the mechanisms and genes that interact with KIM-1.

Methods

This in-silico study was done from March 2019 to December 2019. The Enrichment and protein-protein interaction (PPI) network carefully choose proteins. In addition, the diagramed gene data sets were accomplished using FunRich version 3.1.3. It was done to unveil the proteins that may affect the regulation of HAVCR1 or may be regulated by this protein. These genes were then further considered in pathway analysis to discover the dysregulated pathways in diabetic nephropathy. The long list of differentially expressed genes is meaningless without pathway analysis.

Results

Critical pathways that are dysregulated in diabetic nephropathy patients have been identified. These include Immune System (Total = 237, P < 0.05), Innate Immune System (Total = 140, P < 0.05), Cytokine Signaling Immune system (Total = 116, P < 0.05), Adaptive Immune System (Total = 85) and Neutrophil degranulation (Total = 78).

Conclusion

The top 5 genes that are interacting directly with HIVCR1 include CASP3, CCL2, SPP1, B2M, and TIMP1 with degrees 161, 144, 108, 107, and 105 respectively for Immune system pathways (Innate Immune System, Cytokine Signaling Immune system, Adaptive Immune System and Neutrophil degranulation).

Urinary Proteomics Identifies Cathepsin D as a Biomarker of Rapid eGFR Decline in Type 1 Diabetes

OBJECTIVE

Understanding mechanisms underlying rapid estimated glomerular filtration rate (eGFR) decline is important to predict and treat kidney disease in type 1 diabetes (T1D).

RESEARCH DESIGN AND METHODS

We performed a case-control study nested within four T1D cohorts to identify urinary proteins associated with rapid eGFR decline. Case and control subjects were categorized based on eGFR decline ≥3 and <1 mL/min/1.73 m2/year, respectively. We used targeted liquid chromatography-tandem mass spectrometry to measure 38 peptides from 20 proteins implicated in diabetic kidney disease. Significant proteins were investigated in complementary human cohorts and in mouse proximal tubular epithelial cell cultures.

RESULTS

The cohort study included 1,270 participants followed a median 8 years. In the discovery set, only cathepsin D peptide and protein were significant on full adjustment for clinical and laboratory variables. In the validation set, associations of cathepsin D with eGFR decline were replicated in minimally adjusted models but lost significance with adjustment for albuminuria. In a meta-analysis with combination of discovery and validation sets, the odds ratio for the association of cathepsin D with rapid eGFR decline was 1.29 per SD (95% CI 1.07-1.55). In complementary human cohorts, urine cathepsin D was associated with tubulointerstitial injury and tubulointerstitial cathepsin D expression was associated with increased cortical interstitial fractional volume. In mouse proximal tubular epithelial cell cultures, advanced glycation end product-BSA increased cathepsin D activity and inflammatory and tubular injury markers, which were further increased with cathepsin D siRNA.

CONCLUSIONS

Urine cathepsin D is associated with rapid eGFR decline in T1D and reflects kidney tubulointerstitial injury.

Maternal serum proteomic profiles of pregnant women with type 1 diabetes

Despite improvement in the care of diabetes over the years, pregnancy complicated by type 1 diabetes (T1DM) is still associated with adverse maternal and neonatal outcomes. To date, proteomics studies have been conducted to identify T1DM biomarkers in non-pregnant women, however, no studies included T1DM pregnant women. In this study serum proteomic profiling was conducted in pregnant women with T1DM in the late third trimester. Serum samples were collected from 40 women with T1DM and 38 healthy controls within 3 days before delivery at term pregnancy. Significant differences between serum proteomic patterns were revealed, showing discriminative peaks for complement C3 and C4-A, kininogen-1, and fibrinogen alpha chain. Quantification of selected discriminative proteins by ELISA kits was also performed. The serum concentration of kininogen-1 was significantly lower in women with T1DM than in controls. There were no significant differences in serum concentrations of complement C3 and complement C4-A between study groups. These data indicate that pregnant women with T1DM have a distinct proteomic profile involving proteins in the coagulation and inflammatory pathways. However, their utility as biomarkers of pregnancy complications in women with T1DM warrants further investigation.

Identification of Key Genes and Pathways in Peripheral Blood Mononuclear Cells of Type 1 Diabetes Mellitus by Integrated Bioinformatics Analysis

BACKGROUND

The onset and progression of type 1 diabetes mellitus (T1DM) is closely related to autoimmunity. Effective monitoring of the immune system and developing targeted therapies are frontier fields in T1DM treatment. Currently, the most available tissue that reflects the immune system is peripheral blood mononuclear cells (PBMCs). Thus, the aim of this study was to identify key PBMC biomarkers of T1DM.

METHODS

Common differentially expressed genes (DEGs) were screened from the Gene Expression Omnibus (GEO) datasets GSE9006, GSE72377, and GSE55098, and PBMC mRNA expression in T1DM patients was compared with that in healthy participants by GEO2R. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and protein-protein interaction (PPI) network analyses of DEGs were performed using the Cytoscape, DAVID, and STRING databases. The vital hub genes were validated by reverse transcription-polymerase chain reaction using clinical samples. The disease-gene-drug interaction network was built using the Comparative Toxicogenomics Database (CTD) and Drug Gene Interaction Database (DGIdb).

RESULTS

We found that various biological functions or pathways related to the immune system and glucose metabolism changed in PBMCs from T1DM patients. In the PPI network, the DEGs of module 1 were significantly enriched in processes including inflammatory and immune responses and in pathways of proteoglycans in cancer. Moreover, we focused on four vital hub genes, namely, chitinase-3-like protein 1 (CHI3L1), C-X-C motif chemokine ligand 1 (CXCL1), matrix metallopeptidase 9 (MMP9), and granzyme B (GZMB), and confirmed them in clinical PBMC samples. Furthermore, the disease-gene-drug interaction network revealed the potential of key genes as reference markers in T1DM.

CONCLUSION

These results provide new insight into T1DM pathogenesis and novel biomarkers that could be widely representative reference indicators or potential therapeutic targets for clinical applications.

Bioinformatic Analysis Reveals Hub Immune-Related Genes of Diabetic Foot Ulcers

Diabetic foot ulcer (DFU) is a complex and devastating complication of diabetes mellitus that are usually stagnant in the inflammatory phase. However, oral wound healing, which is characterized by a rapid and scarless healing process, is regarded an ideal model of wound healing. Thus, we performed a comprehensive bioinformatics analysis of the previously published data regarding oral ulcers and DFUs and found that compared to oral wound healing, the activated pathways of DFUs were enriched in cellular metabolism-related pathways but lacked the activation of inflammatory and immune-related pathways. We also found that CXCL11, DDX60, IFI44, and IFI44L were remarkable nodes since they had the most connections with other members of the module. Meanwhile, CXCL10, IRF7, and DDX58 together formed a closed-loop relationship and occupied central positions in the entire network. The real-time polymerase chain reaction and western blot was applied to validate the gene expression of the hub immune-related genes in the DFU tissues, it was found that CXCL11, IFI44, IFI44L, CXCL10 and IRF7 have a significant difference compared with normal wound tissues. Our research reveals some novel potential immune-related biomarkers and provides new insights into the molecular basis of this debilitating disease.

Gender differences in new hypoglycemic drug effects on renal outcomes: a systematic review

INTRODUCTION

Lifetime diabetes risk is greater in women than in men. Women with diabetes mellitus (DM) have a greater prevalence of diabetic kidney disease (DKD) risk factors. The diagnosis of DM is often delayed in women, with poorer outcomes and with expected therapeutic goals missed.

AREA COVERED

A systematic literature review following PRISMA guidelines was conducted in the PubMed gateway of the MEDLINE database and Clinicaltrials.gov. The purpose of our research was to establish the sex differences on renal outcomes in users of the new hypoglycemic drugs: sodium-glucose transport protein 2 inhibitors (SGLT-2i), dipeptidyl peptidase-IV Inhibitors (DPP-IVi) and glucagon-like peptide-1 inhibitors (GLP-1i).

EXPERT OPINION

New hypoglycemic drugs represent promising tools in the treatment and prevention of severe complications of diabetes, cardiovascular diseases and chronic kidney disease. Even if renal outcomes are investigated in both randomized controlled trials and cardiovascular outcome trials, gender-based analysis is not always performed. This may lead to relevant information for risk-benefit evaluation and therapeutic choices being missed, with gender-based equality in outcomes lacking. Our systematic review demonstrated that the gap among sexes in DKD can be partially filled using new hypoglycemic drugs. Sexual dimorphism analysis could represent a keystone for the development of adequate gender-specific therapies.

Urinary Proteome Differences in Canine Diabetes with and without the Presence of Microalbuminuria

Simple Summary

Canine diabetes is a serious disease, which can lead to numerous complications. There are limited data on urine proteomics in dogs, and none of the effect of diabetes mellitus on the urine proteome. In this study we aimed to analyze the protein composition of the urine collected from the healthy animals and compare it with two diabetic groups (normoalbuminuric and microalbuminuric). There are significant differences between these three groups, and we believe that the identified proteins hold promise as a potential diagnostic tool, which can be later on used in clinical practice, and for better understanding of the disease.

Abstract

In this study we aimed to analyze the protein composition of the urine collected from the healthy animals and compare it to the two diabetic groups (DM I normoalbuminuric diabetic dogs; DM II diabetic dogs with microalbuminuria). We tried to identify potential urinary proteins which could be up- or downregulated in diabetic patients even before the appearance of microalbuminuria. Methods: After obtaining urine, we performed two-dimensional electrophoresis, followed by Delta2D software analysis, which allowed for selection and identification with MALDI-TOF spectrometry, statistically significant differentially expressed proteins. Our study revealed 286 common protein spots on 2D gels from the diabetic and control group. From these proteins five were positively identified by MALDI-TOF MS. To further evaluate the five differentiating proteins, the Panther program was used to assign them to appropriate biological process. Conclusion: Significant number of identified proteins play a role in intracellular signaling—vesicle formation, bonding, transport through membranes. This may suggest that first signs of kidney diabetic cellular impairment may be seen in the urine composition before any clinical signs occur.

Comprehensive Diagnostics of Diabetic Nephropathy by Transcriptome RNA Sequencing

BACKGROUND

Diabetic nephropathy (DN) is a primary driver of end-stage renal disease. Given the heterogeneity of renal lesions and the complex mechanisms of DN, the present-day diagnostic approach remains highly controversial. We aimed to design a diagnostic model by bioinformatics methods for discriminating DN patients from normal subjects.

METHODS

In this study, transcriptome sequencing was performed on 6 clinical samples (3 from DN patients and 3 from healthy volunteers) from the Second Affiliated Hospital of Kunming Medical University. Construction of a competing endogenous RNA (ceRNA) network based on differentially expressed (DE)-mRNAs and -long noncoding RNAs (lncRNAs). Subsequently, the CytoHubba plugin was used to identify hub genes from DE-mRNAs in the ceRNA network and to perform functional enrichment analysis on them. The least absolute shrinkage and selection operator (LASSO) regression analysis was responsible for screening the diagnostic biomarkers from hub genes and assessing their diagnostic power using ROC curves. The pathways involved in hub genes were revealed by single-gene Gene Set Enrichment Analysis (GSEA). Moreover, we verified the expression levels of diagnostic biomarkers by quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot.

RESULTS

A total of 10 hub genes were screened from the ceRNA network, which appeared to be associated with the viral infection, kidney development, and regulation of immune and inflammatory responses. Subsequently, LASSO regression analysis established a diagnostic model consisting of DDX58, SAMD9L, and TLR6 with a robust diagnostic potency (AUC = 1). Similarly, single-gene GSEA showed a strong association of these diagnostic biomarkers with the viral infection. Furthermore, PCR and Western blot demonstrated showed that DDX58, SAMD9L, and TLR6 were upregulated in DN patients at both transcriptome and protein levels compared to healthy controls.

CONCLUSION

We confirmed that differentially expressed hub genes may be novel diagnostic biomarkers in DN.

Urine proteomics identifies biomarkers for diabetic kidney disease at different stages

BACKGROUND

Type 2 diabetic kidney disease is the most common cause of chronic kidney diseases (CKD) and end-stage renal diseases (ESRD). Although kidney biopsy is considered as the 'gold standard' for diabetic kidney disease (DKD) diagnosis, it is an invasive procedure, and the diagnosis can be influenced by sampling bias and personal judgement. It is desirable to establish a non-invasive procedure that can complement kidney biopsy in diagnosis and tracking the DKD progress.

METHODS

In this cross-sectional study, we collected 252 urine samples, including 134 uncomplicated diabetes, 65 DKD, 40 CKD without diabetes and 13 follow-up diabetic samples, and analyzed the urine proteomes with liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). We built logistic regression models to distinguish uncomplicated diabetes, DKD and other CKDs.

RESULTS

We quantified 559 ± 202 gene products (GPs) (Mean ± SD) on a single sample and 2946 GPs in total. Based on logistic regression models, DKD patients could be differentiated from the uncomplicated diabetic patients with 2 urinary proteins (AUC = 0.928), and the stage 3 (DKD3) and stage 4 (DKD4) DKD patients with 3 urinary proteins (AUC = 0.949). These results were validated in an independent dataset. Finally, a 4-protein classifier identified putative pre-DKD3 patients, who showed DKD3 proteomic features but were not diagnosed by clinical standards. Follow-up studies on 11 patients indicated that 2 putative pre-DKD patients have progressed to DKD3.

CONCLUSIONS

Our study demonstrated the potential for urinary proteomics as a noninvasive method for DKD diagnosis and identifying high-risk patients for progression monitoring.

Urinary peptidomics reveals proteases involved in idiopathic membranous nephropathy

BACKGROUND

Idiopathic membranous nephropathy (IMN) is a cause of nephrotic syndrome that is increasing in incidence but has unclear pathogenesis. Urinary peptidomics is a promising technology for elucidating molecular mechanisms underlying diseases. Dysregulation of the proteolytic system is implicated in various diseases. Here, we aimed to conduct urinary peptidomics to identify IMN-related proteases.

RESULTS

Peptide fingerprints indicated differences in naturally produced urinary peptide components among 20 healthy individuals, 22 patients with IMN, and 15 patients with other kidney diseases. In total, 1,080 peptide-matched proteins were identified, 279 proteins differentially expressed in the urine of IMN patients were screened, and 32 proteases were predicted; 55 of the matched proteins were also differentially expressed in the kidney tissues of IMN patients, and these were mainly involved in the regulation of proteasome-, lysosome-, and actin cytoskeleton-related signaling pathways. The 32 predicted proteases showed abnormal expression in the glomeruli of IMN patients based on Gene Expression Omnibus databases. Western blot revealed abnormal expression of calpain, matrix metalloproteinase 14, and cathepsin S in kidney tissues of patients with IMN.

CONCLUSIONS

This work shown the calpain/matrix metalloproteinase/cathepsin axis might be dysregulated in IMN. Our study is the first to systematically explore the role of proteases in IMN by urinary peptidomics, which are expected to facilitate discovery of better biomarkers for IMN.

Exploration of novel biomarkers for hypertensive disorders of pregnancy by comprehensive analysis of peptide fragments in blood: their potential and technologies supporting quantification

Among the many complications associated with pregnancy, hypertensive disorders of pregnancy (HDP) constitute one of the most important. Since the pathophysiology of HDP is complex, new disease biomarkers (DBMs) are needed to serve as indicators of disease activity. However, in the current status of laboratory medicine, despite the fact that blood pressure measurement has been used for a long time, not many DBMs contribute adequately to the subsequent diagnosis and treatment. In this article, we discuss studies focusing on peptide fragments in blood identified by comprehensive quantitative methods, among the currently proposed DBM candidates. Furthermore, we describe the basic techniques of peptidomics, especially quantitative proteomics, and outline the current status and challenges of measuring peptides in blood as DBM for HDP.

Subproteomic profiling from renal cortices in OLETF rats reveals mutations of multiple novel genes in diabetic nephropathy

BACKGROUND

Diabetic nephropathy (DN) is a serious threat to human health, but its pathogenesis is not fully understood. Otsuka Long-Evans Tokushima Fatty (OLETF) rats are very similar to human DN in many aspects such as pathological changes and processes, and are deemed to be an ideal rodent model.

OBJECTIVE

This study was aimed to explore the pathogenesis of DN by analyzing the protein expression profile from renal cortices in OLETF rats.

METHODS

Thirty-six-week-old diabetic OLETF rats and normal control Long-Evans Tokushima Otsuka (LETO) rats were nephrectomized, and the renal cortices were isolated. The proteins were separated by soluble and insoluble high-resolution subproteomics methods for the analysis and identification of differential proteins.

RESULTS

Thirty-six differentially expressed proteins were found. Among them, 11 proteins had different isoelectric points and molecular weights between OLETF and LETO rats. Further sequencing identified point mutations in genes encoding eight of these proteins, which are involved in many biological processes closely related to DN, including oxidative stress and inflammation. Five of these eight proteins have not been reported in DN.

CONCLUSION

This study reveals mutations of multiple novel genes in diabetic OLETF rats, providing some new potential targets for the pathogenesis of DN and helping to better understand the pathogenesis of DN.

Exosomes: Advances, development and potential therapeutic strategies in diabetic nephropathy

Exosomes, a major type of extracellular vesicles (EVs), are nanoscale vesicles excreted by almost all cell types via invagination of the endosomal membrane pathway. Exosomes play a crucial role in the mediation of intercellular communication both in health and disease, which can be ascribed to their capacity to be transported to neighboring or distant cells, thus regulating the biological function of recipient cells through cargos such as DNA, mRNA, proteins and microRNA. Diabetic nephropathy (DN) is a serious microvascular complication associated with diabetes mellitus as well as a significant cause of end-stage renal disease worldwide, which has resulted in a substantial economic burden on individuals and society. However, despite extensive efforts, therapeutic approaches that prevent the progression of DN do not exist, which implies new approaches are required. An increasing number of studies suggest that exosomes are involved in the pathophysiological processes associated with DN, which may potentially provide novel biomarkers and therapeutic targets for DN. Hence, this review summarizes recent advances involving exosome mechanisms in DN and their potential as biomarkers and therapeutic targets.

The Aggressive Diabetic Kidney Disease in Youth-Onset Type 2 Diabetes: Pathogenetic Mechanisms and Potential Therapies

Youth-onset Type 2 Diabetes Mellitus (T2DM) represents a major burden worldwide. In the last decades, the prevalence of T2DM became higher than that of Type 1 Diabetes Mellitus (T1DM), helped by the increasing rate of childhood obesity. The highest prevalence rates of youth-onset T2DM are recorded in China (520 cases/100,000) and in the United States (212 cases/100,000), and the numbers are still increasing. T2DM young people present a strong hereditary component, often unmasked by social and environmental risk factors. These patients are affected by multiple coexisting risk factors, including obesity, hyperglycemia, dyslipidemia, insulin resistance, hypertension, and inflammation. Juvenile T2DM nephropathy occurs earlier in life compared to T1DM-related nephropathy in children or T2DM-related nephropathy in adult. Diabetic kidney disease (DKD) is T2DM major long term microvascular complication. This review summarizes the main mechanisms involved in the pathogenesis of the DKD in young population and the recent evolution of treatment, in order to reduce the risk of DKD progression.

Urinary small extracellular vesicles derived CCL21 mRNA as biomarker linked with pathogenesis for diabetic nephropathy

Background

Diabetic nephropathy (DN) is a leading cause of renal failure, whereas the effective and early diagnostic biomarkers are still lacking.

Methods

Fourteen cytokines and chemokines mRNA were detected in urinary extracellular vesicles (EVs) from the screening cohort including 4 healthy controls (HC), 4 diabetes mellitus (DM) and 4 biopsy-proven DN patients, and was validated in another 16 HC and 15 DM and 28 DN patients. Correlation analysis was performed between the candidate biomarkers and clinic parameters as well as kidney histological changes. The findings were also confirmed in DN rat model with single injection of STZ.

Results

The number of small EVs secreted in urine was increased in DN patients compared to DM patients and healthy controls, with expression of AQP1 (a marker of proximal tubules) and AQP2 (a marker of distal/collecting tubules). Small EVs derived CCL21 mRNA increased significantly in DN patients and correlated with level of proteinuria and eGFR. Interestingly, elevated CCL21 mRNA from urine small EVs was observed in DN patients with normal renal function and could discriminate early DN patients from DM more efficiently compared to eGFR and proteinuria. CCL21 also showed an accurate diagnostic ability in distinguishing incipient from overt DN. Histologically, CCL21 mRNA expression increased progressively with the deterioration of tubulointerstitial inflammation and showed the highest level in nodular sclerosis group (class III) in DN patients. Remarkable infiltration of CD3 positive T cells including both CD4 and CD8 positive T cell population were observed in DN patients with high-CCL21 expression. Besides, accumulation of CD3 positive T cells correlated with level of urinary small EVs derived CCL21 and co-localized with CCL21 in the tubulointerstitium in DN patients. Finally, the correlation of CCL21 expression in renal cortex and urinary small EVs was confirmed in STZ-induced DN rat model.

Conclusions

Urinary small EVs derived CCL21 mRNA may serve as early biomarker for identifying DN linked with pathogenesis. CCL21 mRNA mediated T cell infiltration may constitute the key mechanism of chronic inflammation in DN.

Urinary proteomics for kidney dysfunction: insights and trends

Introduction: Kidney dysfunction poses a high burden on patients and health care systems. Early detection and accurate prediction of kidney disease progression remains a major challenge. Compared to existing clinical parameters, urinary proteomics has the potential to reveal molecular alterations within the kidney that may alter its function before the onset of clinical symptoms. Thus, urinary proteomics has greater prognostic potential for assessment of kidney dysfunction progression.Areas covered: Advances in urinary proteomics for major causes of kidney dysfunction are discussed. The application of urinary extracellular vesicles for studying kidney dysfunction are discussed. Technological advances in urinary proteomics are discussed. The literature was identified using a database search for titles containing 'proteom*' and 'urin*' and published within the past 5 years. Retrieved literature was manually filtered to retain kidney dysfunctions-related studies.Expert opinion: Despite major advances, diagnosis by urinary proteomics has not been fully applied in any clinical settings. This could be attributed to the complex nature of kidney diseases, in addition to the constraints on study power and feasibility of incorporating mass spectrometry techniques in daily routine analysis. Nevertheless, we are confident that advances in urinary proteomics will soon provide superior insights into kidney disease beyond existing clinical parameters.

Mining the Biomarker Potential of the Urine Peptidome: From Amino Acids Properties to Proteases

Native biofluid peptides offer important information about diseases, holding promise as biomarkers. Particularly, the non-invasive nature of urine sampling, and its high peptide concentration, make urine peptidomics a useful strategy to study the pathogenesis of renal conditions. Moreover, the high number of detectable peptides as well as their specificity set the ground for the expansion of urine peptidomics to the identification of surrogate biomarkers for extra-renal diseases. Peptidomics further allows the prediction of proteases (degradomics), frequently dysregulated in disease, providing a complimentary source of information on disease pathogenesis and biomarkers. Then, what does urine peptidomics tell us so far? In this paper, we appraise the value of urine peptidomics in biomarker research through a comprehensive analysis of all datasets available to date. We have mined > 50 papers, addressing > 30 different conditions, comprising > 4700 unique peptides. Bioinformatic tools were used to reanalyze peptide profiles aiming at identifying disease fingerprints, to uncover hidden disease-specific peptides physicochemical properties and to predict the most active proteases associated with their generation. The molecular patterns found in this study may be further validated in the future as disease biomarker not only for kidney diseases but also for extra-renal conditions, as a step forward towards the implementation of a paradigm of predictive, preventive and personalized (3P) medicine.

Higher prevalence of incidental findings identified upon coronary calcium score assessment in type 2 and type 3 diabetes versus type 1 diabetes

Aim

Noninvasive assessment of infraclinic coronary atherosclerosis by coronary artery calcium score (CAC) measurement leads to the identification of incidental findings. The aim of this study was to determine the prevalence of incidental findings following systematic CAC assessment in diabetic patients with high cardiovascular risk, to identify the determinants, and to assess the midterm consequences of these findings in patient care.

Methods

732 consecutive asymptomatic patients (187 type 1 diabetes (TD1), 482 type 2 diabetes (TD2) and 63 type 3 diabetes (TD3)) aged 60.6±0.7 years who had a CAC assessment by Multiple Detector Computed Tomography between 2015 and 2017 were systematically included. Clinical and biological data were collected from medical electronic files.

Results

117/732 diabetic patients (16.0%) had incidental findings of which 105 (14.3%) were unknown. Incidental findings were more frequent in TD3 (23.8%) and TD2 (17.0%) than in TD1 (10.7%) (p = 0.05). 76 diabetic patients (10.4%) had lung abnormalities, mainly pulmonary nodules (31 patients, 4.2%). The other incidental finding were pericardial (1.5%), vascular (1.2%), thymic (0.7%) and digestive diseases (0.5%). 42.6% of patients with incidental findings had an additional TDM and 56.8% a specialized medical advice. In 10 patients (9.3% of incidental findings), the identification of incidental finding led to a specific treatment of the underlying disease. In multivariate analysis, microalbuminuria, type of diabetes (TD2/TD3 vs TD1) and smoking were significantly associated with incidental findings (p = 0.003; p = 0.026; p = 0.050 respectively).

Conclusions

Incidental findings are not rare in diabetic patients upon CAC assessment. A fraction of them are accessible to specific treatment. These findings raise the question if a systematic low dose chest TDM should be conducted in TD2 or TD3 patients and in any diabetic smokers by enlarging the window used for CAC assessment.

Urinary Extracellular Vesicles for Diabetic Kidney Disease Diagnosis

Diabetic kidney disease (DKD) is the leading cause of end stage renal disease (ESRD) in developed countries, affecting more than 40% of diabetes mellitus (DM) patients. DKD pathogenesis is multifactorial leading to a clinical presentation characterized by proteinuria, hypertension, and a gradual reduction in kidney function, accompanied by a high incidence of cardiovascular (CV) events and mortality. Unlike other diabetes-related complications, DKD prevalence has failed to decline over the past 30 years, becoming a growing socioeconomic burden. Treatments controlling glucose levels, albuminuria and blood pressure may slow down DKD evolution and reduce CV events, but are not able to completely halt its progression. Moreover, one in five patients with diabetes develop DKD in the absence of albuminuria, and in others nephropathy goes unrecognized at the time of diagnosis, urging to find novel noninvasive and more precise early diagnosis and prognosis biomarkers and therapeutic targets for these patient subgroups. Extracellular vesicles (EVs), especially urinary (u)EVs, have emerged as an alternative for this purpose, as changes in their numbers and composition have been reported in clinical conditions involving DM and renal diseases. In this review, we will summarize the current knowledge on the role of (u)EVs in DKD.

BoxCar increases the depth and reproducibility of diabetic urinary proteome analysis

PURPOSE

Mass spectrometry-based proteomics performs well in high throughput detection of urinary proteins. Nonetheless, protein identification depth and reproducibility remain the challenges in diabetic urinary proteome with high complexity and broad dynamic range, especially for low-abundant proteins. As a new data acquisition strategy, the BoxCar method was reported to benefit for low-abundant protein identification. Whether it is propitious to diabetic samples with high dynamic range proteomes has not been discussed yet. We aimed to apply BoxCar method to diabetic urine sample analysis, and to compare it with standard data dependent acquisition (DDA) method on protein identification in detail.

EXPERIMENTAL DESIGN

We performed seven technical replicates analysis on two urine samples from healthy individuals and diabetic patients to evaluate protein detection of BoxCar and standard DDA methods on single sample. Further comparison of two methods was made on multiple diabetic urine samples.

RESULTS

BoxCar could increase over 20% of identified proteins and performed better quantitative reproducibility than standard DDA method either in single or multiple diabetic urinary samples. BoxCar also improved the detection of low-abundant proteins. Functional enrichment analysis of normal albuminuria or microalbuminuria samples indicated that BoxCar acquired more diabetes-related biological information.

CONCLUSIONS AND CLINICAL RELEVANCE

The study demonstrates that BoxCar could enhance the depth and reproducibility in diabetic urinary proteome analysis, which provides reference for mass spectrometry approach selection in clinical urinary proteomic research.

The unique molecular mechanism of diabetic nephropathy: a bioinformatics analysis of over 250 microarray datasets

Background/Aims

Diabetic nephropathy (DN) is one of the main causes of end-stage kidney disease worldwide. Emerging studies have suggested that its pathogenesis is distinct from nondiabetic renal diseases in many aspects. However, it still lacks a comprehensive understanding of the unique molecular mechanism of DN.

Methods

A total of 255 Affymetrix U133 microarray datasets (Affymetrix, Santa Calra, CA, USA) of human glomerular and tubulointerstitial tissues were collected. The 22 215 Affymetrix identifiers shared by the Human Genome U133 Plus 2.0 and U133A Array were extracted to facilitate dataset pooling. Next, a linear model was constructed and the empirical Bayes method was used to select the differentially expressed genes (DEGs) of each kidney disease. Based on these DEG sets, the unique DEGs of DN were identified and further analyzed using gene ontology and pathway enrichment analysis. Finally, the protein–protein interaction networks (PINs) were constructed and hub genes were selected to further refine the results.

Results

A total of 129 and 1251 unique DEGs were identified in the diabetic glomerulus (upregulated n = 83 and downregulated n = 203) and the diabetic tubulointerstitium (upregulated n = 399 and downregulated n = 874), respectively. Enrichment analysis revealed that the DEGs in the diabetic glomerulus were significantly associated with the extracellular matrix, cell growth, regulation of blood coagulation, cholesterol homeostasis, intrinsic apoptotic signaling pathway and renal filtration cell differentiation. In the diabetic tubulointerstitium, the significantly enriched biological processes and pathways included metabolism, the advanced glycation end products–receptor for advanced glycation end products signaling pathway in diabetic complications, the epidermal growth factor receptor (EGFR) signaling pathway, the FoxO signaling pathway, autophagy and ferroptosis. By constructing PINs, several nodes, such as AGR2, CSNK2A1, EGFR and HSPD1, were identified as hub genes, which might play key roles in regulating the development of DN.

Conclusions

Our study not only reveals the unique molecular mechanism of DN but also provides a valuable resource for biomarker and therapeutic target discovery. Some of our findings are promising and should be explored in future work.

Pectin-Lyase-Modified Ginseng Extract and Ginsenoside Rd Inhibits High Glucose-Induced ROS Production in Mesangial Cells and Prevents Renal Dysfunction in db/db Mice

Diabetes increases the incidence rate of chronic renal disease. Pectin-lyase-modified ginseng (GS-E3D), with enhanced ginsenoside Rd content, has been newly developed. In this study, renal protective roles of GS-E3D in type-2 diabetic db/db mice were investigated. The generation of reactive oxygen species (ROS) induced by high glucose (25 mM) was reduced by ES-E3D (75%) and ginsenoside Rd (60%). Diabetic db/db mice received 100 or 250 mg/kg/day of GS-E3D daily via oral gavage for 6 weeks. Albuminuria and urinary 8-hydroxy-2'-deoxyguanosine (8-OhdG, an oxidative stress marker) levels were increased in db/db mice and the levels recovered after GS-E3D treatment. In renal tissues, TUNEL-positive cells were decreased after GS-E3D treatment, and the increased apoptosis-related protein expressions were restored after GS-E3D treatment. Therefore, GS-E3D has a potent protective role in diabetes-induced renal dysfunction through antioxidative and antiapoptotic activities. These results may help patients to select a dietary supplement for diabetes when experiencing renal dysfunction.

Current Challenges and Future Perspectives of Renal Tubular Dysfunction in Diabetic Kidney Disease

Over decades, substantial progress has been achieved in understanding the pathogenesis of proteinuria in diabetic kidney disease (DKD), biomarkers for DKD screening, diagnosis, and prognosis, as well as novel hypoglycemia agents in clinical trials, thereby rendering more attention focused on the role of renal tubules in DKD. Previous studies have demonstrated that morphological and functional changes in renal tubules are highly involved in the occurrence and development of DKD. Novel tubular biomarkers have shown some clinical importance. However, there are many challenges to transition into personalized diagnosis and guidance for individual therapy in clinical practice. Large-scale clinical trials suggested the clinical relevance of increased proximal reabsorption and hyperfiltration by sodium-glucose cotransporter-2 (SGLT2) to improve renal outcomes in patients with diabetes, further promoting the emergence of renal tubulocentric research. Therefore, this review summarized the recent progress in the pathophysiology associated with involved mechanisms of renal tubules, potential tubular biomarkers with clinical application, and renal tubular factors in DKD management. The mechanism of kidney protection and impressive results from clinical trials of SGLT2 inhibitors were summarized and discussed, offering a comprehensive update on therapeutic strategies targeting renal tubules.

Integrated Bioinformatics-Based Identification of Potential Diagnostic Biomarkers Associated with Diabetic Foot Ulcer Development

The present study was designed to detect possible biomarkers associated with diabetic foot ulcer (DFU) incidence in an effort to develop novel treatments for this condition. The GSE7014 and GSE29221 gene expression datasets were downloaded from the Gene Expression Omnibus (GEO) database, after which differentially expressed genes (DEGs) were identified between DFU and healthy samples. These DEGs were then arranged into a protein-protein interaction (PPI) network, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) term enrichment analyses were performed to explore the functional roles of these genes. In total, 1192 DEGs were identified in the GSE7014 dataset (900 upregulated, 292 downregulated), while 1177 were identified in the GSE29221 dataset (257 upregulated, 919 downregulated). GO analyses revealed these DEGs to be significantly enriched in biological processes including sarcomere organization, muscle filament sliding, and the regulation of cardiac conduction, molecular functions including structural constituent of muscle, protein binding, and calcium ion binding, and cellular components including Z disc, myosin filament, and M band. These DEGs were also enriched in the adrenergic signaling in cardiomyoctes, dilated cardiomyopathy, and tight junction KEGG pathways. Together, the findings of these bioinformatics analyses thus identified key hub genes associated with DFU development.

Central Proteins of Plasma in Response to Low-Level Laser Therapy Involve in Body Hemostasis and Wound Repair

Introduction: Low-level laser therapy (LLLT) is accompanied by protein expression change in the body. There are many efforts to find a clear relationship between the differentially expressed proteins. This study aims to find the central differentiated expressed proteins of plasma after LLLT. Methods: Six proteins are extracted from a proteomics study and the network including these query proteins plus 100 first neighbors was constructed. The central proteins were determined based on degree value, betweenness centrality, closeness centrality (CC), and stress (The centrality parameters). Results: Among 106 nodes of the network, 10 proteins were characterized with the most values of degree, betweenness centrality, CC, and stress. These proteins were determined as central proteins in response to LLLT in plasma. Conclusion: Three query proteins, AHSG, FGG, and SERPINA1, plus 7 first neighbors, namely FGA, ALB, KNG1, FN1, APP, TIMP1, and F5, were identified as central proteins which were dysregulated.

Multi-Omics Analysis of Diabetic Nephropathy Reveals Potential New Mechanisms and Drug Targets

Diabetic nephropathy (DN) is one of the most common diabetic complications, which is the major course of end-stage renal disease (ESRD). However, the systematical molecular characterizations during DN pathogenesis and progression has not been not well understood. To identify the fundamental mediators of the pathogenesis and progression of DN. we performed a combination RNASeq, proteomics, and metabolomics analyses of both patients’ derived kidney biopsy samples and kidneys from in vivo DN model. As a result, molecular changes of DN contain extracellular matrix accumulation, abnormal activated inflamed microenvironment, and metabolism disorders, bringing about glomerular sclerosis and tubular interstitial fibrosis. Specificity, Further integration analyses have identified that the linoleic acid metabolism and fatty-acids β-oxidation are significantly inhibited during DN pathogenesis and progression, the transporter protein ABCD3, the fatty acyl-CoA activated enzymes ACOX1, ACOX2, and ACOX3, and some corresponding metabolites such as 13′-HODE, stearidonic acid, docosahexaenoic acid, (±)10(11)-EpDPA were also significantly reduced. Our study thus provides potential molecular mechanisms for DN progression and suggests that targeting the key enzymes or supplying some lipids may be a promising avenue in the treatment of DN, especially advanced-stage DN.

Kidney iron deposition by R2* is associated with haemolysis and urinary iron

Kidney iron deposition measured by R2* (magnetic resonance imaging) MRI is posited to result from tubular reabsorption of filtered haemoglobin due to intravascular haemolysis. In chronically transfused sickle cell disease (SCD), R2* is elevated and positively correlated with lactate dehydrogenase (LDH). To account for contributions to renal iron from systemic iron overload, we evaluated kidney R2*, urinary iron and haemolysis markers in 62 non-transfused SCD patients. On multivariate analysis, kidney R2* was associated with urinary iron and LDH (R²  = 0·55, P < 0·0001). Our study confirms that kidney R2* is associated with intravascular haemolysis and raises important questions regarding the role of iron in SCD nephropathy.

Diabetic nephropathy associates with deregulation of enzymes involved in kidney sulphur metabolism

Nephropathy is a major chronic complication of diabetes. A crucial role in renal pathophysiology is played by hydrogen sulphide (H₂S) that is produced excessively by the kidney; however, the data regarding H₂S bioavailability are inconsistent. We hypothesize that early type 1 diabetes (T1D) increases H₂S production by a mechanism involving hyperglycaemia‐induced alterations in sulphur metabolism. Plasma and kidney tissue collected from T1D double transgenic mice were subjected to mass spectrometry‐based proteomic analysis, and the results were validated by immunological and gene expression assays.T1D mice exhibited a high concentration of H₂S in the plasma and kidney tissue and histological, showed signs of subtle kidney fibrosis, characteristic for early renal disease. The shotgun proteomic analyses disclosed that the level of enzymes implicated in sulphate activation modulators, H₂S‐oxidation and H₂S‐production were significantly affected (ie 6 up‐regulated and 4 down‐regulated). Gene expression results corroborated well with the proteomic data. Dysregulation of H₂S enzymes underly the changes occurring in H₂S production, which in turn could play a key role in the initiation of renal disease. The new findings lead to a novel target in the therapy of diabetic nephropathy. Mass spectrometry data are available via ProteomeXchange with identifier PXD018053.

Reckoning the Dearth of Bioinformatics in the Arena of Diabetic Nephropathy (DN)—Need to Improvise

Diabetic nephropathy (DN) is a recent rising concern amongst diabetics and diabetologist. Characterized by abnormal renal function and ending in total loss of kidney function, this is becoming a lurking danger for the ever increasing population of diabetics. This review touches upon the intensity of this complication and briefly reviews the role of bioinformatics in the area of diabetes. The advances made in the area of DN using proteomic approaches are presented. Compared to the enumerable inputs observed through the use of bioinformatics resources in the area of proteomics and even diabetes, the existing scenario of skeletal application of bioinformatics advances to DN is highlighted and the reasons behind this discussed. As this review highlights, almost none of the well-established tools that have brought breakthroughs in proteomic research have been applied into DN. Laborious, voluminous, cost expensive and time-consuming methodologies and advances in diagnostics and biomarker discovery promised through beckoning bioinformatics mechanistic approaches to improvise DN research and achieve breakthroughs. This review is expected to sensitize the researchers to fill in this gap, exploiting the available inputs from bioinformatics resources.