Systems biology of kidney diseases

Chronic kidney disease and gut microbiota

Chronic kidney disease (CKD) refers to a range of various pathophysiological processes correlated with abnormal renal function and a progressive loss in GFR. Just as dysbiosis and altered pathology of the gut are accompanied with hypertension, which is a significant CKD risk factor. Gut dysbiosis in CKD patients is associated with an elevated levels of uremic toxins, which in turn increases the CKD progression. According to research results, the gut-kidney axis has a role in the formation of kidney stones, also in IgAN. A number of researchers have categorized the gut microbiota as enterotypes, and others, skeptical of theory of enterotypes, have suggested biomarkers to describe taxa that related to lifestyle, nutrition, and disease status. Metabolome-microbiome studies have been used to investigate the interactions of host-gut microbiota in terms of the involvement of metabolites in these interactions and are yielded promising results. The correlation between gut microbiota and CKD requires further multi-omic researches. Also, with regard to systems biology, studies on the communication network of proteins and transporters such as SLC and ABC, can help us achieve a deeper understanding of the gut-liver-kidney axis communication and can thus provide promising new horizons in the treatment of CKD patients. Probiotic-based treatment is an approach to reduce uremic poisoning, which is accomplished by swallowing microbes those can catalyze URS in the gut. If further comprehensive studies are carried out, we will know about the probiotics impact in slowing the renal failure progression and reducing inflammatory markers.

Pretransplant kidney transcriptome captures intrinsic donor organ quality and predicts 24-month outcomes

With the development of novel prognostic tools derived from omics technologies, transplant medicine is entering the era of precision medicine. Currently, there are no established predictive biomarkers for posttransplant kidney function. A total of 270 deceased donor pretransplant kidney biopsies were collected and posttransplant function was prospectively monitored. This study first assessed the utility of pretransplant gene expression profiles in predicting 24-month outcomes in a training set (n = 174). Nearly 600 differentially expressed genes were associated with 24-month graft function. Grafts that progressed to low function at 24 months exhibited upregulated immune responses and downregulated metabolic processes at pretransplantation. Using penalized logistic regression modeling, a 55 gene model area under the receiver operating curve (AUROC) for 24-month graft function was 0.994. Gene expression for a subset of candidate genes was then measured in an independent set of pretransplant biopsies (n = 96) using quantitative polymerase chain reaction. The AUROC when using 13 genes with three donor characteristics (age, race, body mass index) was 0.821. Subsequently, a risk score was calculated using this combination for each patient in the validation cohort, demonstrating the translational feasibility of using gene markers as prognostic tools. These findings support the potential of pretransplant transcriptomic biomarkers as novel instruments for improving posttransplant outcome predictions and associated management.

Revisiting the therapeutic potential of tocotrienol

The therapeutic potential of the tocotrienol group stems from its nutraceutical properties as a dietary supplement. It is largely considered to be safe when consumed at low doses for attenuating pathophysiology as shown by animal models, in vitro assays, and ongoing human trials. Medical researchers and the allied sciences have experimented with tocotrienols for many decades, but its therapeutic potential was limited to adjuvant or concurrent treatment regimens. Recent studies have focused on targeted drug delivery by enhancing the bioavailability through carriers, self-sustained emulsions, nanoparticles, and ethosomes. Epigenetic modulation and computer remodeling are other means that will help increase chemosensitivity. This review will focus on the systemic intracellular anti-cancer, antioxidant, and anti-inflammatory mechanisms that are stimulated and/or regulated by tocotrienols while highlighting its potent therapeutic properties in a diverse group of clinical diseases.

Omics Strategies in Current Advancements of Infectious Fish Disease Management

Aquaculture is an important industry globally as it remains one of the significant alternatives of animal protein source supplies for humankind. Yet, the progression of this industry is being dampened by the increasing rate of fish mortality, mainly the outbreak of infectious diseases. Consequently, the regress in aquaculture ultimately results in the economy of multiple countries being affected due to the decline of product yields and marketability. By 2025, aquaculture is expected to contribute approximately 57% of fish consumption worldwide. Without a strategic approach to curb infectious diseases, the increasing demands of the aquaculture industry may not be sustainable and hence contributing to the over-fishing of wild fish. Recently, a new holistic approach that utilizes multi-omics platforms including transcriptomics, proteomics, and metabolomics is unraveling the intricate molecular mechanisms of host-pathogen interaction. This approach aims to provide a better understanding of how to improve the resistance of host species. However, no comprehensive review has been published on multi-omics strategies in deciphering fish disease etiology and molecular regulation. Most publications have only covered particular omics and no constructive reviews on various omics findings across fish species, particularly on their immune systems, have been described elsewhere. Our previous publication reviewed the integration of omics application for understanding the mechanism of fish immune response due to microbial infection. Hence, this review provides a thorough compilation of current advancements in omics strategies for fish disease management in the aquaculture industry. The discovery of biomarkers in various fish diseases and their potential advancement to complement the recent progress in combatting fish disease is also discussed in this review.

Connectivity Mapping Identifies BI-2536 as a Potential Drug to Treat Diabetic Kidney Disease

Diabetic kidney disease (DKD) remains the most common cause of kidney failure, and the treatment options are insufficient. Here, we used a connectivity mapping approach to first collect 15 gene expression signatures from 11 DKD-related published independent studies. Then, by querying the Library of Integrated Network-based Cellular Signatures (LINCS) L1000 data set, we identified drugs and other bioactive small molecules that are predicted to reverse these gene signatures in the diabetic kidney. Among the top consensus candidates, we selected a PLK1 inhibitor (BI-2536) for further experimental validation. We found that PLK1 expression was increased in the glomeruli of both human and mouse diabetic kidneys and localized largely in mesangial cells. We also found that BI-2536 inhibited mesangial cell proliferation and extracellular matrix in vitro and ameliorated proteinuria and kidney injury in DKD mice. Further pathway analysis of the genes predicted to be reversed by the PLK1 inhibitor was of members of the TNF-α/NF-κB, JAK/STAT, and TGF-β/Smad3 pathways. In vitro, either BI-2536 treatment or knockdown of PLK1 dampened the NF-κB and Smad3 signal transduction and transcriptional activation. Together, these results suggest that the PLK1 inhibitor BI-2536 should be further investigated as a novel therapy for DKD.

Serum-Targeted HILIC-MS Metabolomics-Based Analysis in Infants with Ureteropelvic Junction Obstruction

Ureteropelvic junction obstruction (UPJO) constitutes the predominant cause of obstructive nephropathy in both neonates and infants. Fundamental questions regarding UPJO's mechanism, assessment, and treatment still remain unanswered. The aim of the present study was to elucidate potential differences through serum metabolic profiling of surgical cases of infants with UPJO compared to both nonsurgical cases and healthy age-matched controls. Early diagnosis of renal dysfunction in this cohort based on highlighted biomarkers was the ultimate goal. Thus, serum samples were collected from 20 patients preoperatively, 19 patients with mild stenosis treated conservatively, and 17 healthy controls. All samples were subjected to targeted metabolomics analysis by hydrophilic interaction liquid chromatography coupled to mass spectrometry (HILIC LC-MS/MS). Both univariate and multivariate statistical analyses were performed. Principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) score plots showed that the studied groups differed significantly, with a panel of metabolites, including creatinine, tryptophan, choline, and aspartate, distinguishing patients who required surgery from those followed by systematical monitoring as well as from healthy controls, showing high performance as indicators of UPJO disease.

Systems Biology and Kidney Disease

The kidney is a complex organ responsible for maintaining multiple aspects of homeostasis in the human body. The combination of distinct, yet interrelated, molecular functions across different cell types make the delineation of factors associated with loss or decline in kidney function challenging. Consequently, there has been a paucity of new diagnostic markers and treatment options becoming available to clinicians and patients in managing kidney diseases. A systems biology approach to understanding the kidney leverages recent advances in computational technology and methods to integrate diverse sets of data. It has the potential to unravel the interplay of multiple genes, proteins, and molecular mechanisms that drive key functions in kidney health and disease. The emergence of large, detailed, multilevel biologic and clinical data from national databases, cohort studies, and trials now provide the critical pieces needed for meaningful application of systems biology approaches in nephrology. The purpose of this review is to provide an overview of the current state in the evolution of the field. Recent successes of systems biology to identify targeted therapies linked to mechanistic biomarkers in the kidney are described to emphasize the relevance to clinical care and the outlook for improving outcomes for patients with kidney diseases.

Big science and big data in nephrology

There have been tremendous advances during the last decade in methods for large-scale, high-throughput data generation and in novel computational approaches to analyze these datasets. These advances have had a profound impact on biomedical research and clinical medicine. The field of genomics is rapidly developing toward single-cell analysis, and major advances in proteomics and metabolomics have been made in recent years. The developments on wearables and electronic health records are poised to change clinical trial design. This rise of 'big data' holds the promise to transform not only research progress, but also clinical decision making towards precision medicine. To have a true impact, it requires integrative and multi-disciplinary approaches that blend experimental, clinical and computational expertise across multiple institutions. Cancer research has been at the forefront of the progress in such large-scale initiatives, so-called 'big science,' with an emphasis on precision medicine, and various other areas are quickly catching up. Nephrology is arguably lagging behind, and hence these are exciting times to start (or redirect) a research career to leverage these developments in nephrology. In this review, we summarize advances in big data generation, computational analysis, and big science initiatives, with a special focus on applications to nephrology.

The analysis of a time-course transcriptome profile by systems biology approaches reveals key molecular processes in acute kidney injury

Background:

Acute kidney injury is a common debilitating disease with no curative treatment. The recent development of big biological data is expected to expand our understanding of the disorder if appropriately analyzed to generate translational knowledge. We have here re-analyzed a time-course microarray data on mRNA expression of rat kidneys exposed to ischemia-reperfusion to identify key underlying biological processes.

Materials and Methods:

The dataset was quality controlled by principal component analysis and hierarchical clustering. Using limma R package, differentially expressed (DE) genes were detected which were then clustered according to their expression trajectories. The biological processes related to each cluster were harvested using gene ontology enrichment analysis. In addition, the interaction map of proteins encoded by the DE genes was constructed, and the functions related to network central genes were determined. Furthermore, signaling pathways related to the DE genes were harvested using pathway enrichment analysis.

Results:

We found 8139 DE genes that drive critical processes such as the control of blood circulation, reactive species metabolism, mitochondrial respiration, apoptosis, cell proliferation, as well as inflammatory and immunological reactions. The role of less recognized pathways such as olfactory signaling in acute kidney injury is also proposed that remains to be investigated in future studies.

Conclusion:

Using systems biology top-down approach, we have suggested novel potential genes and pathways to be intervened toward kidney regeneration.

A Systems-Level View of Renal Metabolomics

The measurement of select circulating metabolites such as creatinine, glucose, and cholesterol are integral to clinical medicine, with implications for diagnosis, prognosis, and treatment. Metabolomics studies in nephrology research seek to build on this paradigm, with the goal to identify novel markers and causal participants in the pathogenesis of kidney disease and its complications. This article reviews three themes pertinent to this goal. Each is rooted in long-established principles of human physiology, with recent updates enabled by metabolomics and other tools. First, the kidney has a broad and heterogeneous impact on circulating metabolites, with progressive loss of kidney function resulting in a multitude of small molecule alterations. Second, an increasing number of circulating metabolites have been shown to possess functional roles, in some cases acting as ligands for specific G-protein-coupled receptors. Third, circulating metabolites traffic through varied, and sometimes complex, interorgan circuits. Taken together, these themes emphasize the importance of viewing renal metabolomics at the systems level, recognizing the diverse origins and physiologic effects of blood metabolites. However, how to synthesize these themes and how to establish clinical relevance remain uncertain and will require further investigation.

An integrative systems biology approach for precision medicine in diabetic kidney disease

Current therapeutic approaches are ineffective in many patients with established diabetic kidney disease (DKD), an epidemic affecting one in three patients with diabetes. Early identification of patients at high risk for progression and individualizing therapies have the potential to mitigate kidney complications due to diabetes. To achieve this, a better understanding of the complex pathophysiology of DKD is needed. A system biology approach integrating large-scale omic data is well suited to unravel the molecular mechanisms driving DKD and may offer new perspectives how to personalize therapy. Recent studies indeed show that integrating genome scale data sets generated from prospectively designed clinical cohort studies with model systems using innovative bioinformatics analysis revealed critical molecular pathways in DKD and led to the development of candidate prognostic molecular biomarkers. This review seeks to provide an overview of the recent progress in the application of the integrative systems biology approaches specifically in the field of molecular biomarkers for DKD. We will mainly focus the discussion on how to use integrative system biology approach to first identify patients at high risk of progression, and second to identify patients who may or may not respond to treatment. Challenges and opportunities in applying precision medicine in DKD will also be discussed.

Inflammation-Related Mechanisms in Chronic Kidney Disease Prediction, Progression, and Outcome

Persistent, low-grade inflammation is now considered a hallmark feature of chronic kidney disease (CKD), being involved in the development of all-cause mortality of these patients. Although substantial improvements have been made in clinical care, CKD remains a major public health burden, affecting 10–15% of the population, and its prevalence is constantly growing. Due to its insidious nature, CKD is rarely diagnosed in early stages, and once developed, its progression is unfortunately irreversible. There are many factors that contribute to the setting of the inflammatory status in CKD, including increased production of proinflammatory cytokines, oxidative stress and acidosis, chronic and recurrent infections, altered metabolism of adipose tissue, and last but not least, gut microbiota dysbiosis, an underestimated source of microinflammation. In this scenario, a huge step forward was made by the increasing progression of omics approaches, specially designed for identification of biomarkers useful for early diagnostic and follow-up. Recent omics advances could provide novel insights in deciphering the disease pathophysiology; thus, identification of circulating biomarker panels using state-of-the-art proteomic technologies could improve CKD early diagnosis, monitoring, and prognostics. This review aims to summarize the recent knowledge regarding the relationship between inflammation and CKD, highlighting the current proteomic approaches, as well as the inflammasomes and gut microbiota dysbiosis involvement in the setting of CKD, culminating with the troubling bidirectional connection between CKD and renal malignancy, raised on the background of an inflammatory condition.

Proteo-metabolomics reveals compensation between ischemic and non-injured contralateral kidneys after reperfusion

Ischaemia and reperfusion injury (IRI) is the leading cause of acute kidney injury (AKI), which contributes to high morbidity and mortality rates in a wide range of injuries as well as the development of chronic kidney disease. The cellular and molecular responses of the kidney to IRI are complex and not fully understood. Here, we used an integrated proteomic and metabolomic approach to investigate the effects of IRI on protein abundance and metabolite levels. Rat kidneys were subjected to 45 min of warm ischaemia followed by 4 h and 24 h reperfusion, with contralateral and separate healthy kidneys serving as controls. Kidney tissue proteomics after IRI revealed elevated proteins belonging to the acute phase response, coagulation and complement pathways, and fatty acid (FA) signalling. Metabolic changes were already evident after 4 h reperfusion and showed increased level of glycolysis, lipids and FAs, whilst mitochondrial function and ATP production was impaired after 24 h. This deficit was partially compensated for by the contralateral kidney. Such a metabolic balance counteracts for the developing energy deficit due to reduced mitochondrial function in the injured kidney.

Digital pathology in nephrology clinical trials, research, and pathology practice

PURPOSE OF REVIEW

In this review, we will discuss (i) how the recent advancements in digital technology and computational engineering are currently applied to nephropathology in the setting of clinical research, trials, and practice; (ii) the benefits of the new digital environment; (iii) how recognizing its challenges provides opportunities for transformation; and (iv) nephropathology in the upcoming era of kidney precision and predictive medicine.

RECENT FINDINGS

Recent studies highlighted how new standardized protocols facilitate the harmonization of digital pathology database infrastructure and morphologic, morphometric, and computer-aided quantitative analyses. Digital pathology enables robust protocols for clinical trials and research, with the potential to identify previously underused or unrecognized clinically useful parameters. The integration of digital pathology with molecular signatures is leading the way to establishing clinically relevant morpho-omic taxonomies of renal diseases.

SUMMARY

The introduction of digital pathology in clinical research and trials, and the progressive implementation of the modern software ecosystem, opens opportunities for the development of new predictive diagnostic paradigms and computer-aided algorithms, transforming the practice of renal disease into a modern computational science.

How Omics Data Can Be Used in Nephrology

Advances in technology and computing now permit the high-throughput analysis of multiple domains of biological information, including the genome, transcriptome, proteome, and metabolome. These omics approaches, particularly comprehensive analysis of the genome, have catalyzed major discoveries in science and medicine, including in nephrology. However, they also generate large complex data sets that can be difficult to synthesize from a clinical perspective. This article seeks to provide an overview that makes omics technologies relevant to the practicing nephrologist, framing these tools as an extension of how we approach patient care in the clinic. More specifically, omics technologies reinforce the impact that genetic mutations can have on a range of kidney disorders, expand the catalogue of uremic molecules that accumulate in blood with kidney failure, enhance our ability to scrutinize urine beyond urinalysis for insight on renal pathology, and enable more extensive characterization of kidney tissue when a biopsy is performed. Although assay methodologies vary widely, all omics technologies share a common conceptual framework that embraces unbiased discovery at the molecular level. Ultimately, the application of these technologies seeks to elucidate a more mechanistic and individualized approach to the diagnosis and treatment of human disease.

New perspectives on CKD-induced dyslipidemia

INTRODUCTION

Chronic kidney disease (CKD) is a world-wide health concern associated with a significantly higher cardiovascular morbidity and mortality. One of the principal cardiovascular risk factors is the lipid profile. CKD patients have a more frequent and progressive atheromatous disease that cannot be explained by the classical lipid parameters used in the daily clinical practice. Areas covered: The current review summarizes prevailing knowledge on the role of lipids in atheromathosis in CKD patients, including an overview of lipoprotein metabolism highlighting the CKD-induced alterations. Moreover, to obtain information beyond traditional lipid parameters, new state-of-the-art technologies such as lipoprotein subfraction profiling and lipidomics are also reviewed. Finally, we analyse the potential of new lipoprotein subclasses as therapeutic targets in CKD. Expert opinion: The CKD-induced lipid profile has specific features distinct from the general population. Besides quantitative alterations, renal patients have a plethora of qualitative lipid alterations that cannot be detected by routine determinations and are responsible for the excess of cardiovascular risk. New parameters, such as lipoprotein particle number and size, together with new biomarkers obtained by lipidomics will personalize the management of these patients. Therefore, nephrologists need to be aware of new insights into lipoprotein metabolism to improve cardiovascular risk assessment.

Integrating 3-omics data analyze rat lung tissue of COPD states and medical intervention by delineation of molecular and pathway alterations

Chronic obstructive pulmonary disease (COPD) is a serious health problem. However, the molecular pathogenesis of COPD remains unknown. Here, we explored the molecular effects of cigarette smoke and bacterial infection in lung tissues of COPD rats. We also investigated therapeutic effects of aminophylline (APL) on the COPD rats and integrated transcriptome, proteome, and metabolome data for a global view of molecular mechanisms of COPD progression. Using molecular function and pathway analyses, the genes and proteins regulated in COPD and APL-treated rats were mainly attributed to oxidoreductase, antioxidant activity, energy and fatty acid metabolism. Furthermore, we identified hub proteins such as Gapdh (glyceraldehyde-3-phosphate dehydrogenase), Pkm (pyruvate kinase isozymes M1/M2), and Sod1 (superoxide dismutase 1), included in energy metabolism and oxidative stress. Then, we identified the significantly regulated metabolic pathways in lung tissues of COPD- and APL-treated rats, such as arachidonic acid, linoleic acid, and α-linolenic acid metabolism, which belong to the lipid metabolism. In particular, we picked the arachidonic acid metabolism for a more detailed pathway analysis of transcripts, proteins, and metabolites. We could observe an increase in metabolites and genes involved in arachidonic acid metabolism in COPD rats and the decrease in these in APL-treated rats, suggesting that inflammatory responses were up-regulated in COPD rats and down-regulated in APL-treated rats. In conclusion, these system-wide results suggested that COPD progression and its treatment might be associated with oxidative stress, lipid and energy metabolism disturbance. Additionally, we demonstrated the power of integrated omics for the elucidation of genes, proteins, and metabolites’ changes and disorders that were associated with COPD.

Modular transcriptional repertoire analyses identify a blood neutrophil signature as a candidate biomarker for lupus nephritis

Objective

LN is a severe complication of SLE. Non-invasive biomarkers are needed for identifying patients at risk of a renal flare, for differentiating proliferative from non-proliferative forms and for assessing prognoses for LN.

Methods

We assessed the link between blood transcriptional signatures and LN using blood samples from patients with biopsy-proven LN, extra-renal SLE flares or quiescent SLE. Healthy controls, and control patients with glomerular diseases or bacterial sepsis were included. Modular repertoire analyses from microarray data were confirmed by PCR.

Results

A modular neutrophil signature (upregulation of module M5.15) was present in 65% of SLE patients and was strongly associated with LN. M5.15 activity was stronger in LN than in extra-renal flares (88 vs 17%). M5.15 was neither correlated to IFN modules, nor to SLEDAI or anti-dsDNA antibodies, but moderately to CS dose. M5.15 activity was associated with severity of LN, was stronger when proliferative, and decreased in patients responding to treatment. M5.15 activation was not caused by higher CS dose because it correlated only moderately to neutrophil count and was also observed among quiescent patients. Among quiescent patients, those with a past history of LN had higher M5.15 activity (50 vs 8%). M5.15 activation was present in patients with bacterial sepsis or ANCA-associated vasculitis, but not in patients with other glomerular diseases. Overall, M5.15 activation was associated with past, present or future flares of LN.

Conclusion

Modular neutrophil signature could be a biomarker for stratifying LN risk and for monitoring its response to treatment.

Trial registration

ClinicalTrials.gov, http://clinicaltrials.gov , NCT00920114.

Clinical proteomics in kidney disease as an exponential technology: heading towards the disruptive phase

Exponential technologies double in power or processing speed every year, whereas their cost halves. Deception and disruption are two key stages in the development of exponential technologies. Deception occurs when, after initial introduction, technologies are dismissed as irrelevant, while they continue to progress, perhaps not as fast or with so many immediate practical applications as initially thought. Twenty years after the first publications, clinical proteomics is still not available in most hospitals and some clinicians have felt deception at unfulfilled promises. However, there are indications that clinical proteomics may be entering the disruptive phase, where, once refined, technologies disrupt established industries or procedures. In this regard, recent manuscripts in CKJ illustrate how proteomics is entering the clinical realm, with applications ranging from the identification of amyloid proteins in the pathology lab, to a new generation of urinary biomarkers for chronic kidney disease (CKD) assessment and outcome prediction. Indeed, one such panel of urinary peptidomics biomarkers, CKD273, recently received a Food and Drug Administration letter of support, the first ever in the CKD field. In addition, a must-read resource providing information on kidney disease-related proteomics and systems biology databases and how to access and use them in clinical decision-making was also recently published in CKJ.

The nephrologist of tomorrow: towards a kidney-omic future

Omics refers to the collective technologies used to explore the roles and relationships of the various types of molecules that make up the phenotype of an organism. Systems biology is a scientific discipline that endeavours to quantify all of the molecular elements of a biological system. Therefore, it reflects the knowledge acquired by omics in a meaningful manner by providing insights into functional pathways and regulatory networks underlying different diseases. The recent advances in biotechnological platforms and statistical tools to analyse such complex data have enabled scientists to connect the experimentally observed correlations to the underlying biochemical and pathological processes. We discuss in this review the current knowledge of different omics technologies in kidney diseases, specifically in the field of pediatric nephrology, including biomarker discovery, defining as yet unrecognized biologic therapeutic targets and linking omics to relevant standard indices and clinical outcomes. We also provide here a unique perspective on the field, taking advantage of the experience gained by the large-scale European research initiative called "Systems Biology towards Novel Chronic Kidney Disease Diagnosis and Treatment" (SysKid). Based on the integrative framework of Systems biology, SysKid demonstrated how omics are powerful yet complex tools to unravel the consequences of diabetes and hypertension on kidney function.

Biomarker Discovery in Human Prostate Cancer: an Update in Metabolomics Studies

Prostate cancer (PCa) is the most frequently diagnosed cancer and the second leading cause of cancer death among men in Western countries. Current screening techniques are based on the measurement of serum prostate specific antigen (PSA) levels and digital rectal examination. A decisive diagnosis of PCa is based on prostate biopsies; however, this approach can lead to false-positive and false-negative results. Therefore, it is important to discover new biomarkers for the diagnosis of PCa, preferably noninvasive ones. Metabolomics is an approach that allows the analysis of the entire metabolic profile of a biological system. As neoplastic cells have a unique metabolic phenotype related to cancer development and progression, the identification of dysfunctional metabolic pathways using metabolomics can be used to discover cancer biomarkers and therapeutic targets. In this study, we review several metabolomics studies performed in prostatic fluid, blood plasma/serum, urine, tissues and immortalized cultured cell lines with the objective of discovering alterations in the metabolic phenotype of PCa and thus discovering new biomarkers for the diagnosis of PCa. Encouraging results using metabolomics have been reported for PCa, with sarcosine being one of the most promising biomarkers identified to date. However, the use of sarcosine as a PCa biomarker in the clinic remains a controversial issue within the scientific community. Beyond sarcosine, other metabolites are considered to be biomarkers for PCa, but they still need clinical validation. Despite the lack of metabolomics biomarkers reaching clinical practice, metabolomics proved to be a powerful tool in the discovery of new biomarkers for PCa detection.

Epigenetics in Kidney Transplantation: Current Evidence, Predictions, and Future Research Directions

Epigenetic modifications are changes to the genome that occur without any alteration in DNA sequence. These changes include cytosine methylation of DNA at cytosine-phosphate diester-guanine dinucleotides, histone modifications, microRNA interactions, and chromatin remodeling complexes. Epigenetic modifications may exert their effect independently or complementary to genetic variants and have the potential to modify gene expression. These modifications are dynamic, potentially heritable, and can be induced by environmental stimuli or drugs. There is emerging evidence that epigenetics play an important role in health and disease. However, the impact of epigenetic modifications on the outcomes of kidney transplantation is currently poorly understood and deserves further exploration. Kidney transplantation is the best treatment option for end-stage renal disease, but allograft loss remains a significant challenge that leads to increased morbidity and return to dialysis. Epigenetic modifications may influence the activation, proliferation, and differentiation of the immune cells, and therefore may have a critical role in the host immune response to the allograft and its outcome. The epigenome of the donor may also impact kidney graft survival, especially those epigenetic modifications associated with early transplant stressors (e.g., cold ischemia time) and donor aging. In the present review, we discuss evidence supporting the role of epigenetic modifications in ischemia-reperfusion injury, host immune response to the graft, and graft response to injury as potential new tools for the diagnosis and prediction of graft function, and new therapeutic targets for improving outcomes of kidney transplantation.

Body fluid peptide and protein signatures in diabetic kidney diseases

Body fluid protein-based biomarkers carry the hope of improving patient management in diabetes by enabling more accurate and earlier detection of diabetic kidney disease (DKD), but also of defining the most suitable therapeutic targets. We present the data on some of the best studied individual protein markers in body fluids and conclude that their potential in clinical application for assessing DKD is moderate. Proteome-based approaches aiming at the identification of panels of body fluid biomarkers might be a valid alternative. We discuss the past (first) clinical proteomics studies in DKD, stressing their drawbacks but also the lessons that could be learned from them, as well as the more recent studies that have a potential for actual clinical implementation. We also highlight relevant issues and current problems associated with clinical proteomics from discovery towards application, and give suggestions for solutions that may help guiding proteomic studies, thereby removing some of the current hurdles for implementation of potentially beneficial results.

Renal microRNA- and RNA-profiles in progressive chronic kidney disease

BACKGROUND

MicroRNAs (miRNAs) contribute to chronic kidney disease (CKD) progression via regulating mRNAs involved in renal homeostasis. However, their association with clinical outcome remains poorly understood.

MATERIALS AND METHODS

We performed miRNA and mRNA expression profiling on renal biopsy sections by qPCR (miRNA) and microarrays (mRNA) in a discovery (n = 43) and in a validation (n = 29) cohort. miRNAs differentiating stable and progressive cases were inversely correlated with putative target mRNAs, which were further characterized by pathway analysis using KEGG pathways.

RESULTS

miR-30d, miR-140-3p, miR-532-3p, miR-194, miR-190, miR-204 and miR-206 were downregulated in progressive cases. These seven miRNAs correlated with upregulated 29 target mRNAs involved in inflammatory response, cell-cell interaction, apoptosis and intra-cellular signalling. In particular, miR-206 and miR-532-3p were associated with distinct biological processes via the expression of their target mRNAs: Reduced expression of miR-206 in progressive disease correlated with the upregulation of target mRNAs participating in inflammatory pathways (CCL19, CXCL1, IFNAR2, NCK2, PTK2B, PTPRC, RASGRP1 and TNFRSF25). Progressive cases also showed a lower expression of miR-532-3p and an increased expression of target transcripts involved in apoptosis pathways (MAP3K14, TNFRSF10B/TRAIL-R2, TRADD and TRAF2). In the validation cohort, we confirmed the decreased expression of miR-206 and miR-532-3p, and the inverse correlation of these miRNAs with the expression of nine of the 12 target genes. The levels of the identified miRNAs and the target mRNAs correlated with clinical parameters and histological damage indices.

CONCLUSIONS

These results suggest the involvement of specific miRNAs and mRNAs in biological pathways associated with the progression of CKD.

Blood, urine and faecal metabolite profiles in the study of adult renal disease

Chronic kidney disease (CKD) is a major public health burden and to date traditional biomarkers of renal function (such as serum creatinine and cystatin C) are unable to identify at-risk individuals before the disease process is well under way. To help preventive strategies and maximize the potential for effective interventions, it is important to characterise the molecular changes that take place in the development of renal damage. Metabolomics is a promising tool to identify markers of renal disease since the kidneys are involved in the handling of major biochemical classes of metabolites. These metabolite levels capture a snap-shot of the metabolic profile of the individual, allowing for the potential identification of early biomarkers, and the monitoring of real-time kidney function. In this review, we describe the current status of the identification of blood/urine/faecal metabolic biomarkers in different entities of kidney diseases including: acute kidney injury, chronic kidney disease, renal transplant, diabetic nephropathy and other disorders.

Integrative Biology of Diabetic Kidney Disease

BACKGROUND

The leading cause of ESRD in the U.S. is diabetic kidney disease (DKD). Despite significant efforts to improve outcomes in DKD, the impact on disease progression has been disappointing. This has prompted clinicians and researchers to search for alternative approaches to identify persons at risk, and to search for more effective therapies to halt progression of DKD. Identification of novel therapies is critically dependent on a more comprehensive understanding of the pathophysiology of DKD, specifically at the molecular level. A more expansive and exploratory view of DKD is needed to complement more traditional research approaches that have focused on single molecules.

SUMMARY

In recent years, sophisticated research methodologies have emerged within systems biology that should allow for a more comprehensive disease definition of DKD. Systems biology provides an inter-disciplinary approach to describe complex interactions within biological systems including how these interactions influence systems' functions and behaviors. Computational modeling of large, system-wide, quantitative data sets is used to generate molecular interaction pathways, such as metabolic and cell signaling networks.

KEY MESSAGES

Importantly, interpretation of data generated by systems biology tools requires integration with enhanced clinical research data and validation using model systems. Such an integrative biological approach has already generated novel insights into pathways and molecules involved in DKD. In this review, we highlight recent examples of how combining systems biology with traditional clinical and model research efforts results in an integrative biology approach that has significantly added to the understanding of the complex pathophysiology of DKD.

Urine Monocyte Chemoattractant Protein-1 and Lupus Nephritis Disease Activity: Preliminary Report of a Prospective Longitudinal Study

Objective. This longitudinal study aimed to determine the urine monocyte chemoattractant protein-1 (uMCP-1) levels in patients with biopsy-proven lupus nephritis (LN) at various stages of renal disease activity and to compare them to current standard markers. Methods. Patients with LN—active or inactive—had their uMCP-1 levels and standard disease activity markers measured at baseline and 2 and 4 months. Urinary parameters, renal function test, serological markers, and renal SLE disease activity index-2K (renal SLEDAI-2K) were analyzed to determine their associations with uMCP-1. Results. A hundred patients completed the study. At each visit, uMCP-1 levels (pg/mg creatinine) were significantly higher in the active group especially with relapses and were significantly associated with proteinuria and renal SLEDAI-2K. Receiver operating characteristic (ROC) curves showed that uMCP-1 was a potential biomarker for LN. Whereas multiple logistic regression analysis showed that only proteinuria and serum albumin and not uMCP-1 were independent predictors of LN activity. Conclusion. uMCP-1 was increased in active LN. Although uMCP-1 was not an independent predictor for LN activity, it could serve as an adjunctive marker when the clinical diagnosis of LN especially early relapse remains uncertain. Larger and longer studies are indicated.

Advances in urinary proteome analysis and applications in systems biology

The urinary proteome is the focus of many studies due to the ease of urine collection and the relative proteome stability. Systems biology allows the combination of multiple omics studies, forming a link between proteomics, metabolomics, genomics and transcriptomics. In-depth data interpretation is achieved by bioinformatics analysis of -omics data sets. It is expected that the contribution of systems biology to the study of the urinary proteome will offer novel insights. The main focus of this review is on technical aspects of proteomics studies, available tools for systems biology analysis and the application of urinary proteomics in clinical studies and systems biology.

Urine Fetuin-A is a biomarker of autosomal dominant polycystic kidney disease progression

Background

Autosomal dominant polycystic kidney disease (ADPKD) is a genetic disorder characterized by numerous fluid-filled cysts that frequently result in end-stage renal disease. While promising treatment options are in advanced clinical development, early diagnosis and follow-up remain a major challenge. We therefore evaluated the diagnostic value of Fetuin-A as a new biomarker of ADPKD in human urine.

Results

We found that renal Fetuin-A levels are upregulated in both Pkd1 and Bicc1 mouse models of ADPKD. Measurement by ELISA revealed that urinary Fetuin-A levels were significantly higher in 66 ADPKD patients (17.5 ± 12.5 μg/mmol creatinine) compared to 17 healthy volunteers (8.5 ± 3.8 μg/mmol creatinine) or 50 control patients with renal diseases of other causes (6.2 ± 2.9 μg/mmol creatinine). Receiver operating characteristics (ROC) analysis of urinary Fetuin-A levels for ADPKD rendered an optimum cut-off value of 12.2 μg/mmol creatinine, corresponding to 94% of sensitivity and 60% of specificity (area under the curve 0.74 ; p = 0.0019). Furthermore, urinary Fetuin-A levels in ADPKD patients correlated with the degree of renal insufficiency and showed a significant increase in patients with preserved renal function followed for two years.

Conclusions

Our findings establish urinary Fetuin-A as a sensitive biomarker of the progression of ADPKD. Further studies are required to examine the pathogenic mechanisms of elevated renal and urinary Fetuin-A in ADPKD.

Electronic supplementary material

The online version of this article (doi:10.1186/s12967-015-0463-7) contains supplementary material, which is available to authorized users.

Proteomic biomarkers in kidney disease: issues in development and implementation

Proteomic biomarkers offer the hope of improving the management of patients with kidney diseases by enabling more accurate and earlier detection of renal pathology than is possible with currently available biomarkers, serum creatinine and urinary albumin. In addition, proteomic biomarkers could also be useful to define the most suitable therapeutic targets in a given patient or disease setting. This Review describes the current status of proteomic and protein biomarkers in the context of kidney diseases. The valuable lessons learned from early clinical studies of potential proteomic biomarkers in kidney disease are presented to give context to the newly identified biomarkers, which have potential for actual clinical implementation. This article also includes an overview of protein-based biomarker candidates that are undergoing development for use in nephrology, focusing on those with the greatest potential for clinical implementation. Relevant issues and problems associated with the discovery, validation and clinical application of proteomic biomarkers are discussed, along with suggestions for solutions that might help to guide the design of future proteomic studies. These improvements might remove some of the current obstacles to the utilization of proteomic biomarkers, with potentially beneficial results.

Translational nephrology: what translational research is and a bird's-eye view on translational research in nephrology

The ultimate aim of biomedical research is to preserve health and improve patient outcomes. However, by a variety of measures, preservation of kidney health and patient outcomes in kidney disease are suboptimal. Severe acute kidney injury has been treated solely by renal replacement therapy for over 50 years and mortality still hovers at around 50%. Worldwide deaths from chronic kidney disease (CKD) increased by 80% in 20 years--one of the greatest increases among major causes of death. This dramatic data concur with huge advances in the cellular and molecular pathophysiology of kidney disease and its consequences. The gap appears to be the result of sequential roadblocks that impede an adequate flow from basic research to clinical development [translational research type 1 (T1), bench-to-bed and back] and from clinical development to clinical practice and widespread implementation (translational research T2) that supported by healthcare policy-making reaches all levels of society throughout the globe (sometimes called translational research T3). Thus, it is more than 10 years since the introduction of the last new-concept drug for CKD patients, cinacalcet; and 30 years since the introduction of reninangiotensin system (RAS) blockade, the current mainstay to prevent progression of CKD, illustrating the basic science-clinical practice disconnect. Roadblocks from clinical advances to widespread implementation, together with lag time-to-benefit may underlie the 20 years since the description of the antiproteinuric effect of RAS blockade to the observation of decreased age-adjusted incidence of endstage renal disease due to diabetic kidney disease. Only a correct understanding of the roadblocks in translational medicine and a full embracement of a translational research culture will spread the benefits of the biomedical revolution to its ultimate destinatary, the society.

Defining nephrotic syndrome from an integrative genomics perspective

Nephrotic syndrome (NS) is a clinical condition with a high degree of morbidity and mortality, caused by failure of the glomerular filtration barrier, resulting in massive proteinuria. Our current diagnostic, prognostic and therapeutic decisions in NS are largely based upon clinical or histological patterns such as "focal segmental glomerulosclerosis" or "steroid sensitive". Yet these descriptive classifications lack the precision to explain the physiologic origins and clinical heterogeneity observed in this syndrome. A more precise definition of NS is required to identify mechanisms of disease and capture various clinical trajectories. An integrative genomics approach to NS applies bioinformatics and computational methods to comprehensive experimental, molecular and clinical data for holistic disease definition. A unique aspect is analysis of data together to discover NS-associated molecules, pathways, and networks. Integrating multidimensional datasets from the outset highlights how molecular lesions impact the entire individual. Data sets integrated range from genetic variation to gene expression, to histologic changes, to progression of chronic kidney disease (CKD). This review will introduce the tenets of integrative genomics and suggest how it can increase our understanding of NS from molecular and pathophysiological perspectives. A diverse group of genome-scale experiments are presented that have sought to define molecular signatures of NS. Finally, the Nephrotic Syndrome Study Network (NEPTUNE) will be introduced as an international, prospective cohort study of patients with NS that utilizes an integrated systems genomics approach from the outset. A major NEPTUNE goal is to achieve comprehensive disease definition from a genomics perspective and identify shared molecular drivers of disease.

Metabonomic profiling of bladder cancer

Early diagnosis and life-long surveillance are clinically important to improve the long-term survival of bladder cancer patients. Currently, a noninvasive biomarker that is as sensitive and specific as cystoscopy in detecting bladder tumors is lacking. Metabonomics is a complementary approach for identifying perturbed metabolic pathways in bladder cancer. Significant progress has been made using modern metabonomic techniques to characterize and distinguish bladder cancer patients from control subjects, identify marker metabolites, and shed insights on the disease biology and potential therapeutic targets. With its rapid development, metabonomics has the potential to impact the clinical management of bladder cancer patients in the future by revolutionizing the diagnosis and life-long surveillance strategies and stratifying patients for diagnostic, surgical, and therapeutic clinical trials. An introduction to metabonomics, typical metabonomic workflow, and critical evaluation of metabonomic investigations in identifying biomarkers for the diagnosis of bladder cancer are presented.

From molecular signatures to predictive biomarkers: modeling disease pathophysiology and drug mechanism of action

Omics profiling significantly expanded the molecular landscape describing clinical phenotypes. Association analysis resulted in first diagnostic and prognostic biomarker signatures entering clinical utility. However, utilizing Omics for deepening our understanding of disease pathophysiology, and further including specific interference with drug mechanism of action on a molecular process level still sees limited added value in the clinical setting. We exemplify a computational workflow for expanding from statistics-based association analysis toward deriving molecular pathway and process models for characterizing phenotypes and drug mechanism of action. Interference analysis on the molecular model level allows identification of predictive biomarker candidates for testing drug response. We discuss this strategy on diabetic nephropathy (DN), a complex clinical phenotype triggered by diabetes and presenting with renal as well as cardiovascular endpoints. A molecular pathway map indicates involvement of multiple molecular mechanisms, and selected biomarker candidates reported as associated with disease progression are identified for specific molecular processes. Selective interference of drug mechanism of action and disease-associated processes is identified for drug classes in clinical use, in turn providing precision medicine hypotheses utilizing predictive biomarkers.

Systems biology of cisplatin resistance: past, present and future

The platinum derivative cis-diamminedichloroplatinum(II), best known as cisplatin, is currently employed for the clinical management of patients affected by testicular, ovarian, head and neck, colorectal, bladder and lung cancers. For a long time, the antineoplastic effects of cisplatin have been fully ascribed to its ability to generate unrepairable DNA lesions, hence inducing either a permanent proliferative arrest known as cellular senescence or the mitochondrial pathway of apoptosis. Accumulating evidence now suggests that the cytostatic and cytotoxic activity of cisplatin involves both a nuclear and a cytoplasmic component. Despite the unresolved issues regarding its mechanism of action, the administration of cisplatin is generally associated with high rates of clinical responses. However, in the vast majority of cases, malignant cells exposed to cisplatin activate a multipronged adaptive response that renders them less susceptible to the antiproliferative and cytotoxic effects of the drug, and eventually resume proliferation. Thus, a large fraction of cisplatin-treated patients is destined to experience therapeutic failure and tumor recurrence. Throughout the last four decades great efforts have been devoted to the characterization of the molecular mechanisms whereby neoplastic cells progressively lose their sensitivity to cisplatin. The advent of high-content and high-throughput screening technologies has accelerated the discovery of cell-intrinsic and cell-extrinsic pathways that may be targeted to prevent or reverse cisplatin resistance in cancer patients. Still, the multifactorial and redundant nature of this phenomenon poses a significant barrier against the identification of effective chemosensitization strategies. Here, we discuss recent systems biology studies aimed at deconvoluting the complex circuitries that underpin cisplatin resistance, and how their findings might drive the development of rational approaches to tackle this clinically relevant problem.

Metabolomic investigation of human diseases biomarkers by CE and LC coupled to MS

Metabolomics is one of the most recent trends in the "omics" era that investigates the end products of an organism activity, that is, all metabolites in a biological system, which are small molecules (less than 1000 Da) from different chemical classes. Metabolomics represents a tool to assess the biochemical activity of a living system through the analysis of substrates and products processed during the metabolism. The analysis of the metabolic profile (nontargeted analysis, i.e. a comparison between samples profiles of individuals) and of specific metabolites (targeted analysis, which quantifies a selected group of metabolites) in biological samples provides an insight into the metabolic state and the biochemical processes of the organism and, therefore, may indicate the onset and the stage of different diseases. An early and accurate diagnosis is essential for successful treatment and probable cure of most illnesses; hence, the investigation of metabolites as disease biomarkers has increased considerably in recent years. This review aims to present the most relevant works that address the nontargeted and targeted analysis of metabolites in different diseases for the past 10 years, including kidney and neurological disorders, cardiovascular diseases, diabetes, and cancer, using CE and LC coupled with the accurate detection of mass spectroscopy.

Pericytes in kidney fibrosis

PURPOSE OF REVIEW

Pericytes and perivascular fibroblasts have emerged as poorly appreciated yet extensive populations of mesenchymal cells in the kidney that play important roles in homeostasis and responses to injury. This review will update readers on the evolving understanding of the biology of these cells.

RECENT FINDINGS

Fate mapping has identified pericytes and perivascular fibroblasts as the major source of pathological fibrillar matrix-forming cells in interstitial kidney disease. In other organs similar cells have been described and independent fate mapping indicates that pericytes or perivascular cells are myofibroblast progenitors in multiple organs. Over the last year, new insights into the function of pericytes in kidney homeostasis has been uncovered and new molecular pathways that regulate detachment and their transdifferentiation into pathological myofibroblasts, including Wingless/Int, ephrin, transforming growth factor β, platelet derived growth factor, and Hedgehog signaling pathways, have been reported. In addition provocative studies indicate that microRNAs, which regulate posttranscriptional gene expression, may also play important roles in their transdifferentiation.

SUMMARY

Pericytes and perivascular fibroblasts are the major source of pathological collagen fiber-forming cells in interstitial kidney diseases. New avenues of research into their activation and differentiation has identified new drug candidates for the treatment of interstitial kidney disease.

Molecular pathology of acute kidney injury in a choline-deficient model and fish oil protective effect

PURPOSE

The aim of this work was to investigate the potential protective effects of fish oil on the basis of kidney transcriptomic data on a nutritional experimental model.

METHODS

Male weanling Wistar rats were divided into four groups and fed choline-deficient (CD) and choline-supplemented (CS) diets with vegetable oil (VO) and menhaden oil (MO): CSVO, CDVO, CSMO and CDMO. Animals were killed after receiving the diets for 6 days. Total RNA was purified from the right kidney and hybridized to Affymetrix GeneChip Rat Gene 1.0 ST Array. Differentially expressed genes were analyzed.

RESULTS

All CSVO, CSMO and CDMO rats showed no renal alterations, while all CDVO rats showed renal cortical necrosis. A thorough analysis of the differential expression between groups CSMO and CDMO was carried out. There were no differential genes for p < 0.01. The analysis of the differential expression between groups CSVO and CSMO revealed 32 genes, 11 were over-expressed and 21 were under-expressed in CSMO rats.

CONCLUSIONS

This work was part of a large set of experiments and was used in a hypothesis-generating manner. The comprehensive analysis of genetic expression allowed confirming that menhaden oil has a protective effect on this nutritional experimental model and identifying 32 genes that could be responsible for that protection, including Gstp1. These results reveal that gene changes could play a role in renal injury.

Detection of renal tissue and urinary tract proteins in the human urine after space flight

The urine protein composition samples of ten Russian cosmonauts (male, aged of 35 up to 51) performed long flight missions and varied from 169 up to 199 days on the International Space Station (ISS) were analyzed. As a control group, urine samples of six back-up cosmonauts were analyzed. We used proteomic techniques to obtain data and contemporary bioinformatics approaches to perform the analysis. From the total number of identified proteins (238) in our data set, 129 were associated with a known tissue origin. Preflight samples contained 92 tissue-specific proteins, samples obtained on Day 1 after landing had 90 such proteins, while Day 7 samples offered 95 tissue-specific proteins. Analysis showed that consistently present proteins in urine (under physiological conditions and after space flight) are cubilin, epidermal growth factor, kallikrein-1, kininogen-1, megalin, osteopontin, vitamin K-dependent protein Z, uromodulin. Variably present proteins consists of: Na(+)/K(+) ATPase subunit gamma, β-defensin-1, dipeptidyl peptidase 4, maltasa-glucoamilasa, cadherin-like protein, neutral endopeptidase and vascular cell adhesion protein 1. And only three renal proteins were related to the space flight factors. They were not found in the pre-flight samples and in the back-up cosmonaut urine, but were found in the urine samples after space flight: AFAM (afamin), AMPE (aminopeptidase A) and AQP2 (aquaporin-2). This data related with physiological readaptation of water-salt balance. The proteomic analysis of urine samples in different phases of space missions with bioinformation approach to protein identification provides new data relative to biomechemical mechanism of kidney functioning after space flight.

Kidney failure: aims for the next 10 years and barriers to success

Although in some parts of the world acute and chronic kidney diseases are preventable or treatable disorders, in many other regions these diseases are left without any care. The nephrology community needs to commit itself to reduction of this divide between high-income and low-income regions. Moreover, new and exciting developments in fields such as pharmacology, genetic, or bioengineering, can give a boost, in the next decade, to a new era of diagnosis and treatment of kidney diseases, which should be made available to more patients.

The primary glomerulonephritides: a systems biology approach

Our understanding of the pathogenesis of most primary glomerular diseases, including IgA nephropathy, membranous nephropathy and focal segmental glomerulosclerosis, is limited. Advances in molecular technology now permit genome-wide, high-throughput characterization of genes and gene products from biological samples. Comprehensive examinations of the genome, transcriptome, proteome and metabolome (collectively known as omics analyses), have been applied to the study of IgA nephropathy, membranous nephropathy and focal segmental glomerulosclerosis in both animal models and human patients. However, most omics studies of primary glomerular diseases, with the exception of large genomic studies, have been limited by inadequate sample sizes and the lack of kidney-specific data sets derived from kidney biopsy samples. Collaborative efforts to develop a standardized approach for prospective recruitment of patients, scheduled monitoring of clinical outcomes, and protocols for sampling of kidney tissues will be instrumental in uncovering the mechanisms that drive these diseases. Integration of molecular data sets with the results of clinical and histopathological studies will ultimately enable these diseases to be characterized in a comprehensive and systematic manner, and is expected to improve the diagnosis and treatment of these diseases.

ESCAPE: database for integrating high-content published data collected from human and mouse embryonic stem cells

High content studies that profile mouse and human embryonic stem cells (m/hESCs) using various genome-wide technologies such as transcriptomics and proteomics are constantly being published. However, efforts to integrate such data to obtain a global view of the molecular circuitry in m/hESCs are lagging behind. Here, we present an m/hESC-centered database called Embryonic Stem Cell Atlas from Pluripotency Evidence integrating data from many recent diverse high-throughput studies including chromatin immunoprecipitation followed by deep sequencing, genome-wide inhibitory RNA screens, gene expression microarrays or RNA-seq after knockdown (KD) or overexpression of critical factors, immunoprecipitation followed by mass spectrometry proteomics and phosphoproteomics. The database provides web-based interactive search and visualization tools that can be used to build subnetworks and to identify known and novel regulatory interactions across various regulatory layers. The web-interface also includes tools to predict the effects of combinatorial KDs by additive effects controlled by sliders, or through simulation software implemented in MATLAB. Overall, the Embryonic Stem Cell Atlas from Pluripotency Evidence database is a comprehensive resource for the stem cell systems biology community. Database URL: http://www.maayanlab.net/ESCAPE

Genomics and proteomics: how long do we need to reach clinical results?

BACKGROUND

Discovery of the ideal biomarker for clinical care remains a major challenge. Recent progress in genomic and proteomic technologies has allowed the identification of thousands of potential markers, although the benefits of these findings in clinical routine use are not completely evident yet.

METHODS

Major genomics and proteomics approaches are outlined and their clinical applications are described. Future developments in clinical nephrology are discussed.

CONCLUSION

Genomics and proteomics technologies, used to measure gene expression at the transcript and at the protein levels, provide complementary information, which paves the way for systems biology. The fields of genomics and proteomics continue to develop rapidly, and it is evident that there is great potential for their ability to predict diseases and outcomes. However, there are several tasks that must be accomplished to convert all these '-omics' approaches into clinical practice. Collaboration between clinicians, scientists and healthcare funding organizations together with specific guideline development and high-throughput analytical automation will be crucial to reach the final potential of these technologies.

The baboon kidney transcriptome: analysis of transcript sequence, splice variants, and abundance

The baboon is an invaluable model for the study of human health and disease, including many complex diseases of the kidney. Although scientists have made great progress in developing this animal as a model for numerous areas of biomedical research, genomic resources for the baboon, such as a quality annotated genome, are still lacking. To this end, we characterized the baboon kidney transcriptome using high-throughput cDNA sequencing (RNA-Seq) to identify genes, gene variants, single nucleotide polymorphisms (SNPs), insertion-deletion polymorphisms (InDels), cellular functions, and key pathways in the baboon kidney to provide a genomic resource for the baboon. Analysis of our sequencing data revealed 45,499 high-confidence SNPs and 29,813 InDels comparing baboon cDNA sequences with the human hg18 reference assembly and identified 35,900 cDNAs in the baboon kidney, including 35,150 transcripts representing 15,369 genic genes that are novel for the baboon. Gene ontology analysis of our sequencing dataset also identified numerous biological functions and canonical pathways that were significant in the baboon kidney, including a large number of metabolic pathways that support known functions of the kidney. The results presented in this study catalogues the transcribed mRNAs, noncoding RNAs, and hypothetical proteins in the baboon kidney and establishes a genomic resource for scientists using the baboon as an experimental model.