Identification of Lumican and Fibromodulin as Hub Genes Associated with Accumulation of Extracellular Matrix in Diabetic Nephropathy

Lumican, a Multifunctional Cell Instructive Biomarker Proteoglycan Has Novel Roles as a Marker of the Hypercoagulative State of Long Covid Disease

This study has reviewed the many roles of lumican as a biomarker of tissue pathology in health and disease. Lumican is a structure regulatory proteoglycan of collagen-rich tissues, with cell instructive properties through interactions with a number of cell surface receptors in tissue repair, thereby regulating cell proliferation, differentiation, inflammation and the innate and humoral immune systems to combat infection. The exponential increase in publications in the last decade dealing with lumican testify to its role as a pleiotropic biomarker regulatory protein. Recent findings show lumican has novel roles as a biomarker of the hypercoagulative state that occurs in SARS CoV-2 infections; thus, it may also prove useful in the delineation of the complex tissue changes that characterize COVID-19 disease. Lumican may be useful as a prognostic and diagnostic biomarker of long COVID disease and its sequelae.

Molecular cues for immune cells from small leucine-rich repeat proteoglycans in their extracellular matrix-associated and free forms

In this review we highlight emerging immune regulatory functions of lumican, keratocan, fibromodulin, biglycan and decorin, which are members of the small leucine-rich proteoglycans (SLRP) of the extracellular matrix (ECM). These SLRPs have been studied extensively as collagen-fibril regulatory structural components of the skin, cornea, bone and cartilage in homeostasis. However, SLRPs released from a remodeling ECM, or synthesized by activated fibroblasts and immune cells contribute to an ECM-free pool in tissues and circulation, that may have a significant, but poorly understood foot print in inflammation and disease. Their molecular interactions and the signaling networks they influence also require investigations. Here we present studies on the leucine-rich repeat (LRR) motifs of SLRP core proteins, their evolutionary and functional relationships with other LRR pathogen recognition receptors, such as the toll-like receptors (TLRs) to bring some molecular clarity in the immune regulatory functions of SLRPs. We discuss molecular interactions of fragments and intact SLRPs, and how some of these interactions are likely modulated by glycosaminoglycan side chains. We integrate findings on molecular interactions of these SLRPs together with what is known about their presence in circulation and lymph nodes (LN), which are important sites of immune cell regulation. Recent bulk and single cell RNA sequencing studies have identified subsets of stromal reticular cells that express these SLRPs within LNs. An understanding of the cellular source, molecular interactions and signaling consequences will lead to a fundamental understanding of how SLRPs modulate immune responses, and to therapeutic tools based on these SLRPs in the future.

Discovering genetic linkage between periodontitis and type 1 diabetes: A bioinformatics study

Background: Relationship between periodontitis (PD) and type 1 diabetes (T1D) has been reported, but the detailed pathogenesis requires further elucidation. This study aimed to reveal the genetic linkage between PD and T1D through bioinformatics analysis, thereby providing novel insights into scientific research and clinical treatment of the two diseases.

Methods: PD-related datasets (GSE10334, GSE16134, GSE23586) and T1D-related datasets(GSE162689)were downloaded from NCBI Gene Expression Omnibus (GEO). Following batch correction and merging of PD-related datasets as one cohort, differential expression analysis was performed (adjusted p-value <0.05 and ∣log2  fold change| > 0.5), and common differentially expressed genes (DEGs) between PD and T1D were extracted. Functional enrichment analysis was conducted via Metascape website. The protein-protein interaction (PPI) network of common DEGs was generated in The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. Hub genes were selected by Cytoscape software and validated by receiver operating characteristic (ROC) curve analysis.

Results: 59 common DEGs of PD and T1D were identified. Among these DEGs, 23 genes were commonly upregulated, and 36 genes were commonly downregulated in both PD- and T1D-related cohorts. Functional enrichment analysis indicated that common DEGs were mainly enriched in tube morphogenesis, supramolecular fiber organization, 9 + 0 non-motile cilium, plasma membrane bounded cell projection assembly, glomerulus development, enzyme-linked receptor protein signaling pathway, endochondral bone morphogenesis, positive regulation of kinase activity, cell projection membrane and regulation of lipid metabolic process. After PPI construction and modules selection, 6 hub genes (CD34, EGR1, BBS7, FMOD, IGF2, TXN) were screened out and expected to be critical in linking PD and T1D. ROC analysis showed that the AUC values of hub genes were all greater than 70% in PD-related cohort and greater than 60% in T1D-related datasets.

Conclusion: Shared molecular mechanisms between PD and T1D were revealed in this study, and 6 hub genes were identified as potential targets in treating PD and T1D.

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.

Fibromodulin, a Multifunctional Matricellular Modulator

Fibromodulin (FMOD) is an archetypal member of the class II small leucine-rich proteoglycan family. By directly binding to extracellular matrix structural components, such as collagen and lysyl oxidase, FMOD regulates collagen cross-linking, packing, assembly, and fibril architecture via a multivalent interaction. Meanwhile, as a pluripotent molecule, FMOD acts as a ligand of various cytokines and growth factors, especially those belonging to the transforming growth factor (TGF) β superfamily, by interacting with the corresponding signaling molecules involved in cell adhesion, spreading, proliferation, migration, invasion, differentiation, and metastasis. Consequently, FMOD exhibits promigratory, proangiogenic, anti-inflammatory, and antifibrogenic properties and plays essential roles in cell fate determination and maturation, progenitor cell recruitment, and tissue regeneration. The multifunctional nature of FMOD thus enables it to be a promising therapeutic agent for a broad repertoire of diseases, including but not limited to arthritis, temporomandibular joint disorders, caries, and fibrotic diseases among different organs, as well as to be a regenerative medicine candidate for skin, muscle, and tendon injuries. Moreover, FMOD is also considered a marker for tumor diagnosis and prognosis prediction and a potential target for cancer treatment. Furthermore, FMOD itself is sufficient to reprogram somatic cells into a multipotent state, creating a safe and efficient cell source for various tissue reconstructions and thus opening a new avenue for regenerative medicine. This review focuses on the recent preclinical efforts bringing FMOD research and therapies to the forefront. In addition, a contemporary understanding of the mechanism underlying FMOD's function, particularly its interaction with TGFβ superfamily members, is also discussed at the molecular level to aid the discovery of novel FMOD-based treatments.

Screening of Diabetic Nephropathy Progression-Related Genes Based on Weighted Gene Co-expression Network Analysis

The purpose of this study is to explore the progression-related genes of diabetic nephropathy (DN) through weighted gene co-expression network analysis (WGCNA). The gene expression dataset GSE14202 was downloaded from the GEO database for differential expression analysis. WGCNA v1.69 was used to perform co-expression analysis on differentially expressed genes. 25 modular genes were selected through WGCNA. The motif enrichment analysis was performed on 25 genes, and 34 motifs were obtained, of which 8 transcription factors (TFs) were differentially expressed. GENIE3 was applied to analyze the expression correlation of 8 differentially expressed TFs and 25 genes. Combined with the predicted TF-target gene relationship, 69 interactions between 8 TFs and 18 genes were obtained. The functional enrichment analysis of 18 genes showed that 7 key genes were obviously enriched in adaptive immune response and were clearly up-regulated in advanced DN patients. The expression of C1S, LAIR1, CD84, SIT1, SASH3, and CD180 in glomerular samples from DN patients was significantly up-regulated in compared with normal samples, and the expression of these genes was negatively correlated with GFR. We observed that in the in vitro cell model of DN, the relative expression levels of 5 key genes (except SASH3) were obviously elevated in the high-glucose group. Five key genes were identified to be related to the progression of DN. The findings of this study may provide new ideas and therapeutic targets for exploring the pathogenesis of DN.

Title: Bioinformatic Identification of Genes Involved in Diabetic Nephropathy Fibrosis and their Clinical Relevance

Tubulointerstitial fibrosis is an important pathological feature of diabetic nephropathy that is associated with impaired renal function. However, the mechanism by which fibrosis occurs in diabetic nephropathy is unclear. Differentially expressed genes were identified from transcriptome profiles of renal tissue from diabetic patients and unilateral ureteral obstruction mice and intersected to obtain genes that may be involved in diabetic fibrosis. Biological function analysis and protein-protein interaction network analysis were performed. ROC curve and Pearson correlation analysis between hub genes were performed and glomerular filtration rate estimated. Finally, the RNA levels of hub genes were measured using real-time PCR. A total of 283 genes were identified as potentially involved in diabetic nephropathy fibrosis. TYROBP, CTSS, LCP2, LUM and TLR7 were identified as aberrantly expressed hub genes. Immune cell infiltration analysis demonstrated higher numbers of cytotoxic lymphocytes, B lineage cells, monocyte lineage cells, myeloid dendritic cells, neutrophils, and fibroblasts in the diabetic nephropathy group. The areas under ROC curves for TYROBP, CTSS, LCP2, LUM and TLR7 were 0.9167, 0.9583, 0.9917, 0.93333, and 0.9583, respectively (P < 0.001), and their correlation coefficients with estimated glomerular filtration rate were - 0.8332, - 0.752, - 0.7875, - 0.7567, and - 0.7136, respectively (P < 0.001). The RNA levels of TYROBP, CTSS, LUM and TLR7 were upregulated in high-glucose-treated human renal tubular epithelial cells (P < 0.005). Our study identified TYROBP, CTSS, LCP2, LUM and TLR7 as potentially involved in diabetic nephropathy fibrosis. Furthermore, TYROBP, CTSS, LUM and TLR7 may be associated with epithelial-mesenchymal transition of tubular epithelial cells.

HS, an Ancient Molecular Recognition and Information Storage Glycosaminoglycan, Equips HS-Proteoglycans with Diverse Matrix and Cell-Interactive Properties Operative in Tissue Development and Tissue Function in Health and Disease

Heparan sulfate is a ubiquitous, variably sulfated interactive glycosaminoglycan that consists of repeating disaccharides of glucuronic acid and glucosamine that are subject to a number of modifications (acetylation, de-acetylation, epimerization, sulfation). Variable heparan sulfate chain lengths and sequences within the heparan sulfate chains provide structural diversity generating interactive oligosaccharide binding motifs with a diverse range of extracellular ligands and cellular receptors providing instructional cues over cellular behaviour and tissue homeostasis through the regulation of essential physiological processes in development, health, and disease. heparan sulfate and heparan sulfate-PGs are integral components of the specialized glycocalyx surrounding cells. Heparan sulfate is the most heterogeneous glycosaminoglycan, in terms of its sequence and biosynthetic modifications making it a difficult molecule to fully characterize, multiple ligands also make an elucidation of heparan sulfate functional properties complicated. Spatio-temporal presentation of heparan sulfate sulfate groups is an important functional determinant in tissue development and in cellular control of wound healing and extracellular remodelling in pathological tissues. The regulatory properties of heparan sulfate are mediated via interactions with chemokines, chemokine receptors, growth factors and morphogens in cell proliferation, differentiation, development, tissue remodelling, wound healing, immune regulation, inflammation, and tumour development. A greater understanding of these HS interactive processes will improve therapeutic procedures and prognoses. Advances in glycosaminoglycan synthesis and sequencing, computational analytical carbohydrate algorithms and advanced software for the evaluation of molecular docking of heparan sulfate with its molecular partners are now available. These advanced analytic techniques and artificial intelligence offer predictive capability in the elucidation of heparan sulfate conformational effects on heparan sulfate-ligand interactions significantly aiding heparan sulfate therapeutics development.

Bibliometric analysis of scientific papers on extracellular vesicles in kidney disease published between 1999 and 2022

Background: In recent years, there has been an increasing interest in using extracellular vesicles (EVs) as potential therapeutic agents or natural drug delivery systems in kidney-related diseases. However, a detailed and targeted report on the current condition of extracellular vesicle research in kidney-related diseases is lacking. Therefore, this prospective study was designed to investigate the use of bibliometric analysis to comprehensively overview the current state of research and frontier trends on extracellular vesicle research in kidney-related diseases using visualization tools. Methods: The Web of Science Core Collection (WoSCC) database was searched to identify publications related to extracellular vesicle research in kidney-related diseases since 1999. Citespace, Microsoft Excel 2019, VOSviewer software, the R Bibliometrix Package, and an online platform were used to analyze related research trends to stratify the publication data and collaborations. Results: From 1 January 1999 to 26 June 2022, a total of 1,122 EV-related articles and reviews were published, and 6,486 authors from 1,432 institutions in 63 countries or regions investigated the role of extracellular vesicles in kidney-related diseases. We found that the number of articles on extracellular vesicles in kidney-related diseases increased every year. Dozens of publications were from China and the United States. China had the most number of related publications, in which the Southeast University (China) was the most active institution in all EV-related fields. Liu Bi-cheng published the most papers on extracellular vesicles, while Clotilde Théry had the most number of co-citations. Most papers were published by The International Journal of Molecular Sciences, while Kidney International was the most co-cited journal for extracellular vesicles. We found that exosome-related keywords included exosome, exosm, expression, extracellular vesicle, microRNA, microvesicle, and liquid biopsy, while disease- and pathological-related keywords included biomarker, microRNA, apoptosis, mechanism, systemic lupus erythematosus, EGFR, acute kidney injury, and chronic kidney disease. Acute kidney disease (AKI), CKD, SLE, exosome, liquid biopsy, and extracellular vesicle were the hotspot in extracellular vesicle and kidney-related diseases research. Conclusion: The field of extracellular vesicles in kidney-related disease research is rapidly growing, and its domain is likely to expand in the next decade. The findings from this comprehensive analysis of extracellular vesicles in kidney-related disease research could help investigators to set new diagnostic, therapeutic, and prognostic ideas or methods in kidney-related diseases.

Potential Urine Proteomic Biomarkers for Focal Segmental Glomerulosclerosis and Minimal Change Disease

Primary focal segmental glomerulosclerosis (FSGS), along with minimal change disease (MCD), are diseases with primary podocyte damage that are clinically manifested by the nephrotic syndrome. The pathogenesis of these podocytopathies is still unknown, and therefore, the search for biomarkers of these diseases is ongoing. Our aim was to determine of the proteomic profile of urine from patients with FSGS and MCD. Patients with a confirmed diagnosis of FSGS (n = 30) and MCD (n = 9) were recruited for the study. For a comprehensive assessment of the severity of FSGS a special index was introduced, which was calculated as follows: the first score was assigned depending on the level of eGFR, the second score—depending on the proteinuria level, the third score—resistance to steroid therapy. Patients with the sum of these scores of less than 3 were included in group 1, with 3 or more—in group 2. The urinary proteome was analyzed using liquid chromatography/mass spectrometry. The proteome profiles of patients with severe progressive FSGS from group 2, mild FSGS from group 1 and MCD were compared. Results of the label free analysis were validated using targeted LC-MS based on multiple reaction monitoring (MRM) with stable isotope labelled peptide standards (SIS) available for 47 of the 76 proteins identified as differentiating between at least one pair of groups. Quantitative MRM SIS validation measurements for these 47 proteins revealed 22 proteins with significant differences between at least one of the two group pairs and 14 proteins were validated for both comparisons. In addition, all of the 22 proteins validated by MRM SIS analysis showed the same direction of change as at the discovery stage with label-free LC-MS analysis, i.e., up or down regulation in MCD and FSGS1 against FSGS2. Patients from the FSGS group 2 showed a significantly different profile from both FSGS group 1 and MCD. Among the 47 significantly differentiating proteins, the most significant were apolipoprotein A-IV, hemopexin, vitronectin, gelsolin, components of the complement system (C4b, factors B and I), retinol- and vitamin D-binding proteins. Patients with mild form of FSGS and MCD showed lower levels of Cystatin C, gelsolin and complement factor I.

Biochemical composition of the glomerular extracellular matrix in patients with diabetic kidney disease

In the glomeruli, mesangial cells produce mesangial matrix while podocytes wrap glomerular capillaries with cellular extensions named foot processes and tether the glomerular basement membrane (GBM). The turnover of the mature GBM and the ability of adult podocytes to repair injured GBM are unclear. The actin cytoskeleton is a major cytoplasmic component of podocyte foot processes and links the cell to the GBM. Predominant components of the normal glomerular extracellular matrix (ECM) include glycosaminoglycans, proteoglycans, laminins, fibronectin-1, and several types of collagen. In patients with diabetes, multiorgan composition of extracellular tissues is anomalous, including the kidney, so that the constitution and arrangement of glomerular ECM is profoundly altered. In patients with diabetic kidney disease (DKD), the global quantity of glomerular ECM is increased. The level of sulfated proteoglycans is reduced while hyaluronic acid is augmented, compared to control subjects. The concentration of mesangial fibronectin-1 varies depending on the stage of DKD. Mesangial type III collagen is abundant in patients with DKD, unlike normal kidneys. The amount of type V and type VI collagens is higher in DKD and increases with the progression of the disease. The GBM contains lower amount of type IV collagen in DKD compared to normal tissue. Further, genetic variants in the α3 chain of type IV collagen may modulate susceptibility to DKD and end-stage kidney disease. Human cellular models of glomerular cells, analyses of human glomerular proteome, and improved microscopy procedures have been developed to investigate the molecular composition and organization of the human glomerular ECM.

Identification of candidate biomarkers and pathways associated with type 1 diabetes mellitus using bioinformatics analysis

Type 1 diabetes mellitus (T1DM) is a metabolic disorder for which the underlying molecular mechanisms remain largely unclear. This investigation aimed to elucidate essential candidate genes and pathways in T1DM by integrated bioinformatics analysis. In this study, differentially expressed genes (DEGs) were analyzed using DESeq2 of R package from GSE162689 of the Gene Expression Omnibus (GEO). Gene ontology (GO) enrichment analysis, REACTOME pathway enrichment analysis, and construction and analysis of protein–protein interaction (PPI) network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network, and validation of hub genes were performed. A total of 952 DEGs (477 up regulated and 475 down regulated genes) were identified in T1DM. GO and REACTOME enrichment result results showed that DEGs mainly enriched in multicellular organism development, detection of stimulus, diseases of signal transduction by growth factor receptors and second messengers, and olfactory signaling pathway. The top hub genes such as MYC, EGFR, LNX1, YBX1, HSP90AA1, ESR1, FN1, TK1, ANLN and SMAD9 were screened out as the critical genes among the DEGs from the PPI network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network. Receiver operating characteristic curve (ROC) analysis confirmed that these genes were significantly associated with T1DM. In conclusion, the identified DEGs, particularly the hub genes, strengthen the understanding of the advancement and progression of T1DM, and certain genes might be used as candidate target molecules to diagnose, monitor and treat T1DM.

Urinary sediment CCL5 messenger RNA as a potential prognostic biomarker of diabetic nephropathy

Background

Urinary sediment messenger RNAs (mRNAs) have been shown as novel biomarkers of kidney disease. We aimed to identify targeted urinary mRNAs in diabetic nephropathy (DN) based on bioinformatics analysis and clinical validation.

Methods

Microarray studies of DN were searched in the GEO database and Nephroseq platform. Gene modules negatively correlated with estimated glomerular filtration rate (eGFR) were identified by informatics methods. Hub genes were screened within the selected modules. In validation cohorts, a quantitative polymerase chain reaction assay was used to compare the expression levels of candidate mRNAs. Patients with renal biopsy–confirmed DN were then followed up for a median time of 21 months. End-stage renal disease (ESRD) was defined as the primary endpoint. Multivariate Cox proportional hazards regression was developed to evaluate the prognostic values of candidate mRNAs.

Results

Bioinformatics analysis revealed four chemokines (CCL5, CXCL1, CXLC6 and CXCL12) as candidate mRNAs negatively correlated with eGFR, of which CCL5 and CXCL1 mRNA levels were upregulated in the urinary sediment of patients with DN. In addition, urinary sediment mRNA of CXCL1 was negatively correlated with eGFR (r = −0.2275, P = 0.0301) and CCL5 level was negatively correlated with eGFR (r = −0.4388, P &lt; 0.0001) and positively correlated with urinary albumin:creatinine ratio (r = 0.2693, P = 0.0098); also, CCL5 and CXCL1 were upregulated in patients with severe renal interstitial fibrosis. Urinary sediment CCL5 mRNA was an independent predictor of ESRD [hazard ratio 1.350 (95% confidence interval 1.045–1.745)].

Conclusions

Urinary sediment CCL5 and CXCL1 mRNAs were upregulated in DN patients and associated with a decline in renal function and degree of renal interstitial fibrosis. Urinary sediment CCL5 mRNA could be used as a potential prognostic biomarker of DN.