The Role of Glomerular Epithelial Injury in Kidney Function Decline in Patients With Diabetic Kidney Disease in the TRIDENT Cohort.

INTRODUCTION: Although diabetic kidney disease (DKD) is responsible for more than half of all chronic and end-stage kidney disease (ESKD), the association of light (LM) and electron microscopic (EM) structural changes with clinical parameters and prognosis in DKD is incompletely understood. METHODS: This is an interim analysis of 62 patients diagnosed with biopsy-confirmed DKD from the multicenter TRIDENT (Transformative Research in Diabetic Nephropathy) study. Twelve LM and 8 EM descriptors, representing changes in glomeruli, tubulointerstitium, and vasculature were analyzed for their relationship with clinical measures of renal function. Patients were followed every 6 months. RESULTS: Multivariable linear regression analysis revealed that estimated glomerular filtration rate (eGFR) upon enrollment correlated the best with interstitial fibrosis. On the other hand, the rate of kidney function decline (eGFR slope) correlated the most with glomerular lesions including global glomerulosclerosis and mesangiolysis. Unbiased clustering analysis based on histopathologic data identified 3 subgroups. The first cluster, encompassing subjects with the mildest histologic lesions, had the most preserved kidney function. The second and third clusters had similar degrees of kidney dysfunction and structural damage, but differed in the degree of glomerular epithelial cell and podocyte injury (podocytopathy DKD subtype). Cox proportional hazard analysis showed that subjects in cluster 2 had the highest risk to reach ESKD (hazard ratio: 17.89; 95% confidence interval: 2.13-149.79). Glomerular epithelial hyperplasia and interstitial fibrosis were significant predictors of ESKD in the multivariate model. CONCLUSION: The study highlights the association between fibrosis and kidney function and identifies the role of glomerular epithelial changes and kidney function decline.

Urinary Single-Cell Profiling Captures the Cellular Diversity of the Kidney.

BACKGROUND: Microscopic analysis of urine sediment is probably the most commonly used diagnostic procedure in nephrology. The urinary cells, however, have not yet undergone careful unbiased characterization. METHODS: Single-cell transcriptomic analysis was performed on 17 urine samples obtained from five subjects at two different occasions, using both spot and 24-hour urine collection. A pooled urine sample from multiple healthy individuals served as a reference control. In total 23,082 cells were analyzed. Urinary cells were compared with human kidney and human bladder datasets to understand similarities and differences among the observed cell types. RESULTS: Almost all kidney cell types can be identified in urine, such as podocyte, proximal tubule, loop of Henle, and collecting duct, in addition to macrophages, lymphocytes, and bladder cells. The urinary cell-type composition was subject specific and reasonably stable using different collection methods and over time. Urinary cells clustered with kidney and bladder cells, such as urinary podocytes with kidney podocytes, and principal cells of the kidney and urine, indicating their similarities in gene expression. CONCLUSIONS: A reference dataset for cells in human urine was generated. Single-cell transcriptomics enables detection and quantification of almost all types of cells in the kidney and urinary tract.

The Nuclear Receptor ESRRA Protects from Kidney Disease by Coupling Metabolism and Differentiation.

Kidney disease is poorly understood because of the organ's cellular diversity. We used single-cell RNA sequencing not only in resolving differences in injured kidney tissue cellular composition but also in cell-type-specific gene expression in mouse models of kidney disease. This analysis highlighted major changes in cellular diversity in kidney disease, which markedly impacted whole-kidney transcriptomics outputs. Cell-type-specific differential expression analysis identified proximal tubule (PT) cells as the key vulnerable cell type. Through unbiased cell trajectory analyses, we show that PT cell differentiation is altered in kidney disease. Metabolism (fatty acid oxidation and oxidative phosphorylation) in PT cells showed the strongest and most reproducible association with PT cell differentiation and disease. Coupling of cell differentiation and the metabolism was established by nuclear receptors (estrogen-related receptor alpha [ESRRA] and peroxisomal proliferation-activated receptor alpha [PPARA]) that directly control metabolic and PT-cell-specific gene expression in mice and patient samples while protecting from kidney disease in the mouse model.

Natural Killer cell transcriptome during primary EBV infection and EBV associated Hodgkin Lymphoma in children-A preliminary observation.

Epstein Barr Viral infection is a common childhood infection in India and is also nearly 100 % etiologically associated with pediatric Hodgkin Lymphoma (HL). The main question in EBV immunobiology has been, why only a small subset of infected individuals develop EBV associated malignancies, while the vast majority carry this virus asymptomatically for life. Natural Killer (NK) cells, with a phenotype of CD56dim CD16+ exhibit potent cytotoxicity towards both virus infected cells and transformed cells and hence have been considered to be crucial in preventing the development of symptomatic EBV infection and lymphoma. In order to get an insight into the various possible molecular aspects of NK cells, in the pathogenesis of both these EBV mediated diseases in children we studied the whole transcriptome of MACS sorted CD56dim CD16 + NK cells from four patients from each of the three groups of children viz. Infectious Mononucleosis (IM), HL and age matched controls by using a massively parallel sequencing approach. NK cells from both IM and HL had down-regulated innate immunity and chemokine signaling genes. While down-regulation of genes responsible for polarization of the secretory apparatus, activated NK cell signaling and MAP kinase signaling were exclusive to NK cells in patients with IM, in NK cells of HL, specifically, genes involved in extracellular matrix (ECM) - receptor interaction, cytokine-cytokine receptor interaction, TNF signaling, Toll-like receptor signaling pathway and cytosolic DNA-sensing pathways were significantly down-regulated. Enrichment analysis showed STAT3 to be the most significant transcription factor (TF) for the down-regulated genes in IM, whereas, GATA1 was found to be the most significant TF for the genes down-regulated in HL. Analysis of protein interaction network identified functionally important protein clusters. Top clusters, comprised of down-regulated genes, involved in signaling and ubiquitin-related processes and pathways. These may perhaps be responsible for the hypo-responsiveness of NK cells in both diseases. These possibly point to different deficiencies in NK cell activation, loss of activating receptor signaling and degranulation in IM, versus loss of cytokine and chemokine signaling in HL, in the two EBV associated pathologies investigated. Various suppressed molecules and pathways were novel, which have not been reported earlier and could therefore be potential targets for immunotherapy of NK cell reactivation in both the diseases in future.

Comparison of tumour and serum specific microRNA changes dissecting their role in pancreatic ductal adenocarcinoma: a meta-analysis.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is considered as one of the most aggressive cancers lacking efficient early detection biomarkers. Circulating miRNAs are now being considered to have potency to be used as diagnostic and prognostic biomarkers in different diseases as well as cancers. In case of cancer, a fraction of the circulating miRNAs is actually derived from the tumour tissue. This fraction would function as stable biomarker for the disease and also would contribute to the understanding of the disease development. There are not many studies exploring this aspect in pancreatic cancer and even there is not much overlap of results between existing studies. METHODS: In order to address that gap, we performed a miRNA microarray analysis to identify differentially expressed circulating miRNAs between PDAC patients and normal healthy individuals and also found two more similar datasets to perform a meta-analysis using a total of 182 PDAC patients and 170 normal, identifying a set of miRNAs significantly altered in patient serum. Next, we found five datasets studying miRNA expression profile in tumour tissues of PDAC patients as compared to normal pancreas and performed a second meta-analysis using data from a total of 183 pancreatic tumour and 47 normal pancreas to detect significantly deregulated miRNAs in pancreatic carcinoma. Comparison of these two lists and subsequent search for their target genes which were also deregulated in PDAC in inverse direction to miRNAs was done followed by investigation of their role in disease development. RESULTS: We identified 21 miRNAs altered in both pancreatic tumour tissue and serum. While deciphering the functions of their target genes, we characterized key miR-Gene interactions perturbing the biological pathways. We identified important cancer related pathways, pancreas specific pathways, AGE-RAGE signaling, prolactin signaling and insulin resistance signaling pathways among the most affected ones. We also reported the possible involvement of crucial transcription factors in the process. CONCLUSIONS: Our study identified a unique meta-signature of 21 miRNAs capable of explaining pancreatic carcinogenesis and possibly holding the potential to act as biomarker for the disease detection which could be explored further.

Pre-operative progesterone benefits operable breast cancer patients by modulating surgical stress.

PURPOSE: We have reported a survival benefit of single injection of hydroxyprogesterone prior to surgery for primary tumour in patients with node-positive operable breast cancer. Hydroxyprogesterone was meant to recapitulate the luteal phase of menstrual cycle in these women. We wanted to understand the molecular basis of action of hydroxyprogesterone on primary breast tumours in a peri-operative setting. METHODS: We performed whole transcriptome sequencing (RNA-Seq) of primary breast tumour samples collected from patients before and after hydroxyprogesterone exposure and controls. Paired breast cancer samples were obtained from patients who were given hydroxyprogesterone before surgery and a group of patients who were subjected to only surgery. RESULTS: A test of significance between the two groups revealed 207 significantly altered genes, after correction for multiple hypothesis testing. We found significantly contrasting gene expression patterns in exposed versus unexposed groups; 142 genes were up-regulated post-surgery among exposed patients, and down-regulated post-surgery among unexposed patients. Significantly enriched pathways included genes that respond to progesterone, cellular stress, nonsense-mediated decay of proteins and negative regulation of inflammatory response. These results suggest that cellular stress is modulated by hydroxyprogesterone. Network analysis revealed that UBC, a mediator of stress response, to be a major node to which many of the significantly altered genes connect. CONCLUSIONS: Our study suggests that pre-operative exposure to progesterone favourably modulates the effect of surgical stress, and this might underlie its beneficial effect when administered prior to surgery.

Profiling conserved biological pathways in Autosomal Dominant Polycystic Kidney Disorder (ADPKD) to elucidate key transcriptomic alterations regulating cystogenesis: A cross-species meta-analysis approach.

PURPOSE: Initiation and progression of fluid filled cysts mark Autosomal Dominant Polycystic Kidney Disease (ADPKD). Thus, improved therapeutics targeting cystogenesis remains a constant challenge. Microarray studies in single ADPKD animal models species with limited sample sizes tend to provide scattered views on underlying ADPKD pathogenesis. Thus we aim to perform a cross species meta-analysis to profile conserved biological pathways that might be key targets for therapy. METHODS: Nine ADPKD microarray datasets on rat, mice and human fulfilled our study criteria and were chosen. Intra-species combined analysis was performed after considering removal of batch effect. Significantly enriched GO biological processes and KEGG pathways were computed and their overlap was observed. For the conserved pathways, biological modules and gene regulatory networks were observed. Additionally, Gene Set Enrichment Analysis (GSEA) using Molecular Signature Database (MSigDB) was performed for genes found in conserved pathways. RESULTS: We obtained 28 modules of significantly enriched GO processes and 5 major functional categories from significantly enriched KEGG pathways conserved in human, mice and rats that in turn suggest a global transcriptomic perturbation affecting cyst - formation, growth and progression. Significantly enriched pathways obtained from up-regulated genes such as Genomic instability, Protein localization in ER and Insulin Resistance were found to regulate cyst formation and growth whereas cyst progression due to increased cell adhesion and inflammation was suggested by perturbations in Angiogenesis, TGF-beta, CAMs, and Infection related pathways. Additionally, networks revealed shared genes among pathways e.g. SMAD2 and SMAD7 in Endocytosis and TGF-beta. CONCLUSION: Our study suggests cyst formation and progression to be an outcome of interplay between a set of several key deregulated pathways. Thus, further translational research is warranted focusing on developing a combinatorial therapeutic approach for ADPKD redressal.

RNA-Seq analysis of peripheral blood mononuclear cells reveals unique transcriptional signatures associated with disease progression in dengue patients.

Patients infected with Dengue virus usually present a mild, self-limiting febrile dengue infection (DI) that occasionally leads to a potentially lethal complication, called the severe dengue (DS). The ability to identify the prognostic markers of DS could allow an improved disease intervention and management. To identify the transcriptional signatures associated with the dengue disease progression, we carried out the high-throughput sequencing of the RNA isolated from the peripheral blood mononuclear cells (PBMCs) of the dengue patients of varying severity and compared with that in the patients with other febrile illnesses (OFIs) or the healthy controls. The transcriptional signatures that discriminated the DS patients from OFI and DI patients were broadly related to the pathways involving glycine, serine, and threonine metabolisms, extracellular matrix organization, ubiquitination, and cytokines and inflammatory response. Several upregulated genes in the inflammatory process (MPO, DEFA4, ELANE, AUZ1, CTSG, OLFM4, SLC16A14, and CRISP3) that were associated with the dengue disease progression are known to facilitate leukocyte-mediated migration, and neutrophil activation and degranulation process. High activity of MPO and ELANE in the plasma samples of the follow-up and recovered dengue patients, as well as and the presence of a larger amount of cell-free dsDNA in the DS patients, suggested an association of neutrophil-mediated immunity with dengue disease progression. Careful monitoring of some of these gene transcripts, and control of the activity of proteins encoded by them, may have a great translational significance for the prognosis and management of the dengue patients.

Detecting cognizable trends of gene expression in a time series RNA-sequencing experiment: a bootstrap approach.

Study of temporal trajectory of gene expression is important. RNA sequencing is popular in genome-scale studies of transcription. Because of high expenses involved, many time-course RNA sequencing studies are challenged by inadequacy of sample sizes. This poses difficulties in conducting formal statistical tests of significance of null hypotheses. We propose a bootstrap algorithm to identify 'cognizable' 'time-trends' of gene expression. Properties of the proposed algorithm are derived using a simulation study. The proposed algorithm captured known 'time-trends' in the simulated data with a high probability of success, even when sample sizes were small (n < 10). The proposed statistical method is efficient and robust to capture 'cognizable' 'time-trends' in RNA sequencing data.