Systems biology of polycystic kidney disease: a critical review

The utility of serum neutrophil gelatinase-associated lipocalin level on predicting autosomal dominant polycystic kidney disease progression

INTRODUCTION

We focused on neutrophil gelatinase-associated lipocalin (NGAL) and autosomal dominant polycystic kidney disease (ADPKD) progression.

METHODS

ADPKD patients with an estimated glomerular filtration rate (eGFR) ≥ 30 mL/min/1.73 m2 were included. Serum NGAL level and NGAL to eGFR ratio (NGR), height-adjusted total kidney volume (hTKV) were assessed initially. Patients were followed-up for 5 years.

RESULTS

Sixty one patients were enrolled and initial eGFR was 73.6 (48.9-101.5) ml/min/1.73m2. EGFR declined by 3.7 mL/min/1.73m2 per year. Thirty four patients (55.7%) exhibited rapid progression. Rapid progression group had lower serum NGAL levels (p < 0.001) and higher hTKV (p < 0.001). Lower serum NGAL level was a risk factor for rapid progression (p < 0.001). NGR was not associated with rapid progression. Serum NGAL level was predictive in for rapid progression ROC analysis (cut-off <10.62 ng/mL).

CONCLUSION

Relatively lower serum NGAL levels can predict worse outcomes in ADPKD and can provide risk stratification in patients with ADPKD.

Transcriptomic profiling of Polycystic Kidney Disease identifies paracrine factors in the early cyst microenvironment

Initial cysts that are formed upon Pkd1 loss in mice impose persistent stress on surrounding tissue and trigger a cystic snowball effect, in which local aberrant PKD-related signaling increases the likelihood of new cyst formation, ultimately leading to accelerated disease progression. Although many pathways have been associated with PKD progression, the knowledge of early changes near initial cysts is limited. To perform an unbiased analysis of transcriptomic alterations in the cyst microenvironment, microdomains were collected from kidney sections of iKsp-Pkd1del mice with scattered Pkd1-deletion using Laser Capture Microdissection. These microdomains were defined as F4/80-low cystic, representing early alterations in the cyst microenvironment, F4/80-high cystic, with more advanced alterations, or non-cystic. RNA sequencing and differential gene expression analysis revealed 953 and 8088 dysregulated genes in the F4/80-low and F4/80-high cyst microenvironment, respectively, when compared to non-cystic microdomains. In the early cyst microenvironment, several injury-repair, growth, and tissue remodeling-related pathways were activated, accompanied by mild metabolic changes. In the more advanced F4/80-high microdomains, these pathways were potentiated and the metabolism was highly dysregulated. Upstream regulator analysis revealed a series of paracrine factors with increased activity in the early cyst microenvironment, including TNFSF12 and OSM. In line with the upstream regulator analysis, TWEAK and Oncostatin-M promoted cell proliferation and inflammatory gene expression in renal epithelial cells and fibroblasts in vitro. Collectively, our data provide an overview of molecular alterations that specifically occur in the cyst microenvironment and identify paracrine factors that may mediate early and advanced alterations in the cyst microenvironment.

Mechanisms of Cyst Development in Polycystic Kidney Disease

Autosomal dominant polycystic kidney disease is the most common inherited cause of end-stage kidney disease worldwide. Most cases result from mutation of either of 2 genes, PKD1 and PKD2, which encode proteins that form a probable receptor/channel complex. Studies suggest that a loss of function of the complex below an indeterminate threshold triggers cyst initiation, which ultimately results in dysregulation of multiple metabolic processes and downstream pathways and subsequent cyst growth. Noncell autonomous factors may also promote cyst growth. In this report, we focus primarily on the process of early cyst formation and factors that contribute to its variability with brief consideration of how new studies suggest this process may be reversible.

Predicting Progression of Autosomal Dominant Polycystic Kidney Disease by Changes in the Telomeric Epigenome

Autosomal dominant polycystic kidney disease (ADPKD) is the most common inherited cause of chronic kidney disease with Polycystin (PKD) 1 and 2 gene mutation. However, the intra-familial variability in symptoms further suggests a non-Mendelian contribution to the disease. Our goal was to find a marker to track the epigenetic changes common to rapidly progressing forms of the disease. The risk of ADPKD increases with age, and aging shortens the telomere length (TL). Telomeres are a nucleoprotein structure composed mainly of three complexes, shelterin, CST and RNA-containing telomere repeat(TERRA), which protects the ends of chromosomes from degradation and fusion, and plays a role in maintaining cellular stability and in the repair of telomeric damage. TERRAs are transcribed from telomeric regions and a part of them is engaged in a DNA/RNA hybrid (R-loop) at each chromosome end. We tracked TL and TERRA levels in blood samples of 78 patients and 20 healthy control. Our study demonstrates that TL was shortened and TERRA expression levels in the DNA-attached fraction increased in autosomal dominant polycystic kidney patients with mutations in PKD1 and PKD2 compared to the control group. Moreover, it was observed that the expression of TERRA engaged in the R-loop was higher and the length of telomeres shorter in patients with ADPKD who showed rapid disease progression. Intrafamilial variation in TL and TERRA levels with the same mutation would indicate reliable epigenetic potential biomarkers in disease monitoring.

Coregulation Analysis of Mechanistic Biomarkers in Autosomal Dominant Polycystic Kidney Disease

Autosomal dominant polycystic kidney disease (ADPKD) is the most common hereditary kidney disorder leading to deterioration of kidney function and end stage kidney disease (ESKD). A number of molecular processes are dysregulated in ADPKD but the exact mechanism of disease progression is not fully understood. We measured protein biomarkers being linked to ADPKD-associated molecular processes via ELISA in urine and serum in a cohort of ADPKD patients as well as age, gender and eGFR matched CKD patients and healthy controls. ANOVA and t-tests were used to determine differences between cohorts. Spearman correlation coefficient analysis was performed to assess coregulation patterns of individual biomarkers and renal function. Urinary epidermal growth factor (EGF) and serum apelin (APLN) levels were significantly downregulated in ADPKD patients. Serum vascular endothelial growth factor alpha (VEGFA) and urinary angiotensinogen (AGT) were significantly upregulated in ADPKD patients as compared with healthy controls. Arginine vasopressin (AVP) was significantly upregulated in ADPKD patients as compared with CKD patients. Serum VEGFA and VIM concentrations were positively correlated and urinary EGF levels were negatively correlated with urinary AGT levels. Urinary EGF and AGT levels were furthermore significantly associated with estimated glomerular filtration rate (eGFR) in ADPKD patients. In summary, altered protein concentrations in body fluids of ADPKD patients were found for the mechanistic markers EGF, APLN, VEGFA, AGT, AVP, and VIM. In particular, the connection between EGF and AGT during progression of ADPKD warrants further investigation.

The tissue proteome in the multi-omic landscape of kidney disease

Kidney research is entering an era of 'big data' and molecular omics data can provide comprehensive insights into the molecular footprints of cells. In contrast to transcriptomics, proteomics and metabolomics generate data that relate more directly to the pathological symptoms and clinical parameters observed in patients. Owing to its complexity, the proteome still holds many secrets, but has great potential for the identification of drug targets. Proteomics can provide information about protein synthesis, modification and degradation, as well as insight into the physical interactions between proteins, and between proteins and other biomolecules. Thus far, proteomics in nephrology has largely focused on the discovery and validation of biomarkers, but the systematic analysis of the nephroproteome can offer substantial additional insights, including the discovery of mechanisms that trigger and propagate kidney disease. Moreover, proteome acquisition might provide a diagnostic tool that complements the assessment of a kidney biopsy sample by a pathologist. Such applications are becoming increasingly feasible with the development of high-throughput and high-coverage technologies, such as versatile mass spectrometry-based techniques and protein arrays, and encourage further proteomics research in nephrology.

Pathway identification through transcriptome analysis

Systems-based, agnostic approaches focusing on transcriptomics data have been employed to understand the pathogenesis of polycystic kidney diseases (PKD). While multiple signaling pathways, including Wnt, mTOR and G-protein-coupled receptors, have been implicated in late stages of disease, there were few insights into the transcriptional cascade immediately downstream of Pkd1 inactivation. One of the consistent findings has been transcriptional evidence of dysregulated metabolic and cytoskeleton remodeling pathways. Recent technical developments, including bulk and single-cell RNA sequencing technologies and spatial transcriptomics, offer new angles to investigate PKD. In this article, we review what has been learned based on transcriptional approaches and consider future opportunities.

Metabolomics Approaches for the Diagnosis and Understanding of Kidney Diseases

Diseases of the kidney are difficult to diagnose and treat. This review summarises the definition, cause, epidemiology and treatment of some of these diseases including chronic kidney disease, diabetic nephropathy, acute kidney injury, kidney cancer, kidney transplantation and polycystic kidney diseases. Numerous studies have adopted a metabolomics approach to uncover new small molecule biomarkers of kidney diseases to improve specificity and sensitivity of diagnosis and to uncover biochemical mechanisms that may elucidate the cause and progression of these diseases. This work includes a description of mass spectrometry-based metabolomics approaches, including some of the currently available tools, and emphasises findings from metabolomics studies of kidney diseases. We have included a varied selection of studies (disease, model, sample number, analytical platform) and focused on metabolites which were commonly reported as discriminating features between kidney disease and a control. These metabolites are likely to be robust indicators of kidney disease processes, and therefore potential biomarkers, warranting further investigation.

Single-cell transcriptomics of the mouse kidney reveals potential cellular targets of kidney disease

Our understanding of kidney disease pathogenesis is limited by an incomplete molecular characterization of the cell types responsible for the organ's multiple homeostatic functions. To help fill this knowledge gap, we characterized 57,979 cells from healthy mouse kidneys by using unbiased single-cell RNA sequencing. On the basis of gene expression patterns, we infer that inherited kidney diseases that arise from distinct genetic mutations but share the same phenotypic manifestation originate from the same differentiated cell type. We also found that the collecting duct in kidneys of adult mice generates a spectrum of cell types through a newly identified transitional cell. Computational cell trajectory analysis and in vivo lineage tracing revealed that intercalated cells and principal cells undergo transitions mediated by the Notch signaling pathway. In mouse and human kidney disease, these transitions were shifted toward a principal cell fate and were associated with metabolic acidosis.

A Report of the 24th Annual Congress on Women's Health-Workshop on Transforming Women's Health: From Research to Practice

Sex and gender are critical contributors to overall health and disease, and considering both in research informs the development of prevention strategies and treatment interventions for both men and women. The National Institutes of Health (NIH) Office of Research on Women's Health sponsored a preconference workshop on this topic at the 24th Annual Women's Health Congress, which was held in Crystal City, VA, in April 2016. The workshop featured presentations by NIH intramural and extramural scientists who presented data on a variety of topics including polycystic kidney disease, vaccine protection, depression, drug addiction, and cardiovascular disease. In this publication, we discuss the major points of each presentation and demonstrate the importance of considering sex and gender in biomedical research.

Rapamycin treatment dose-dependently improves the cystic kidney in a new ADPKD mouse model via the mTORC1 and cell-cycle-associated CDK1/cyclin axis

Although translational research into autosomal dominant polycystic kidney disease (ADPKD) and its pathogenesis has made considerable progress, there is presently lack of standardized animal model for preclinical trials. In this study, we developed an orthologous mouse model of human ADPKD by cross‐mating Pkd2 conditional‐knockout mice (Pkd2^f3) to Cre transgenic mice in which Cre is driven by a spectrum of kidney‐related promoters. By systematically characterizing the mouse model, we found that Pkd2^f3/f3 mice with a Cre transgene driven by the mouse villin‐1 promoter (Vil‐Cre;Pkd2^f3/f3) develop overt cysts in the kidney, liver and pancreas and die of end‐stage renal disease (ESRD) at 4–6 months of age. To determine whether these Vil‐Cre;Pkd2^f3/f3 mice were suitable for preclinical trials, we treated the mice with the high‐dose mammalian target of rapamycin (mTOR) inhibitor rapamycin. High‐dose rapamycin significantly increased the lifespan, lowered the cystic index and kidney/body weight ratio and improved renal function in Vil‐Cre;Pkd2^f3/f3 mice in a time‐ and dose‐dependent manner. In addition, we further found that rapamycin arrested aberrant epithelial‐cell proliferation in the ADPKD kidney by down‐regulating the cell‐cycle‐associated cyclin‐dependent kinase 1 (CDK1) and cyclins, namely cyclin A, cyclin B, cyclin D1 and cyclin E, demonstrating a direct link between mTOR signalling changes and the polycystin‐2 dysfunction in cystogenesis. Our newly developed ADPKD model provides a practical platform for translating in vivo preclinical results into ADPKD therapies. The newly defined molecular mechanism by which rapamycin suppresses proliferation via inhibiting abnormally elevated CDK1 and cyclins offers clues to new molecular targets for ADPKD treatment.

Meta-analysis of polycystic kidney disease expression profiles defines strong involvement of injury repair processes

Polycystic kidney disease (PKD) is a major cause of end-stage renal disease. The disease mechanisms are not well understood and the pathogenesis toward renal failure remains elusive. In this study, we present the first RNASeq analysis of a Pkd1-mutant mouse model in a combined meta-analysis with other published PKD expression profiles. We introduce the PKD Signature, a set of 1,515 genes that are commonly dysregulated in PKD studies. We show that the signature genes include many known and novel PKD-related genes and functions. Moreover, genes with a role in injury repair, as evidenced by expression data and/or automated literature analysis, were significantly enriched in the PKD Signature, with 35% of the PKD Signature genes being directly implicated in injury repair. NF-κB signaling, epithelial-mesenchymal transition, inflammatory response, hypoxia, and metabolism were among the most prominent injury or repair-related biological processes with a role in the PKD etiology. Novel PKD genes with a role in PKD and in injury were confirmed in another Pkd1-mutant mouse model as well as in animals treated with a nephrotoxic agent. We propose that compounds that can modulate the injury-repair response could be valuable drug candidates for PKD treatment.

Transcriptome analysis reveals manifold mechanisms of cyst development in ADPKD

Background

Autosomal dominant polycystic kidney disease (ADPKD) causes progressive loss of renal function in adults as a consequence of the accumulation of cysts. ADPKD is the most common genetic cause of end-stage renal disease. Mutations in polycystin-1 occur in 87% of cases of ADPKD and mutations in polycystin-2 are found in 12% of ADPKD patients. The complexity of ADPKD has hampered efforts to identify the mechanisms underlying its pathogenesis. No current FDA (Federal Drug Administration)-approved therapies ameliorate ADPKD progression.

Results

We used the de Almeida laboratory’s sensitive new transcriptogram method for whole-genome gene expression data analysis to analyze microarray data from cell lines developed from cell isolates of normal kidney and of both non-cystic nephrons and cysts from the kidney of a patient with ADPKD. We compared results obtained using standard Ingenuity Volcano plot analysis, Gene Set Enrichment Analysis (GSEA) and transcriptogram analysis. Transcriptogram analysis confirmed the findings of Ingenuity, GSEA, and published analysis of ADPKD kidney data and also identified multiple new expression changes in KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways related to cell growth, cell death, genetic information processing, nucleotide metabolism, signal transduction, immune response, response to stimulus, cellular processes, ion homeostasis and transport and cofactors, vitamins, amino acids, energy, carbohydrates, drugs, lipids, and glycans. Transcriptogram analysis also provides significance metrics which allow us to prioritize further study of these pathways.

Conclusions

Transcriptogram analysis identifies novel pathways altered in ADPKD, providing new avenues to identify both ADPKD’s mechanisms of pathogenesis and pharmaceutical targets to ameliorate the progression of the disease.

Electronic supplementary material

The online version of this article (doi:10.1186/s40246-016-0095-x) contains supplementary material, which is available to authorized users.