Metabolic signature associated with parameters of the complete blood count in apparently healthy individuals

Metabolomics studies now approach large sample sizes and the health characterization of the study population often include complete blood count (CBC) results. Upon careful interpretation the CBC aids diagnosis and provides insight into the health status of the patient within a clinical setting. Uncovering metabolic signatures associated with parameters of the CBC in apparently healthy individuals may facilitate interpretation of metabolomics studies in general and related to diseases. For this purpose 879 subjects from the population‐based Study of Health in Pomerania (SHIP)‐TREND were included. Using metabolomics data resulting from mass‐spectrometry based measurements in plasma samples associations of specific CBC parameters with metabolites were determined by linear regression models. In total, 118 metabolites significantly associated with at least one of the CBC parameters. Strongest associations were observed with metabolites of heme degradation and energy production/consumption. Inverse association seen with mean corpuscular volume and mean corpuscular haemoglobin comprised metabolites potentially related to kidney function. The presently identified metabolic signatures are likely derived from the general function and formation/elimination of blood cells. The wealth of associated metabolites strongly argues to consider CBC in the interpretation of metabolomics studies, in particular if mutual effects on those parameters by the disease of interest are known.     

Mealtime,Temporal, and Daily Variability of the Human Urinary and Plasma Metabolomes in a Tightly Controlled Environment

While metabolomics has tremendous potential for diagnostic biomarker and therapeutic target discovery, its utility may be diminished by the variability that occurs due to environmental exposures including diet and the influences of the human circadian rhythm. For successful translation of metabolomics findings into the clinical setting, it is necessary to exhaustively define the sources of metabolome variation. To address these issues and to measure the variability of urinary and plasma metabolomes throughout the day, we have undertaken a comprehensive inpatient study in which we have performed non-targeted metabolomics analysis of blood and urine in 26 volunteers (13 healthy subjects with no known disease and 13 healthy subjects with autosomal dominant polycystic kidney disease not taking medication). These individuals were evaluated in a clinical research facility on two separate occasions, over three days, while on a standardized, weight-based diet. Subjects provided pre- and post-prandial blood and urine samples at the same time of day, and all samples were analyzed by “fast lane” LC-MS-based global metabolomics. The largest source of variability in blood and urine metabolomes was attributable to technical issues such as sample preparation and analysis, and less variability was due to biological variables, meals, and time of day. Higher metabolome variability was observed after the morning as compared to the evening meal, yet day-to-day variability was minimal and urine metabolome variability was greater than that of blood. Thus we suggest that blood and urine are suitable biofluids for metabolomics studies, though nontargeted mass spectrometry alone may not offer sufficient precision to reveal subtle changes in the metabolome. Additional targeted analyses may be needed to support the data from nontargeted mass spectrometric analyses. In light of these findings, future metabolomics studies should consider these sources of variability to allow for appropriate metabolomics testing and reliable clinical translation of metabolomics data.     

Biomarkers in renal cell carcinoma: a metabolomics approach

Since Otto Warburg, many studies have explored the unique metabolic phenotype of cancer cells highlighting the value and applicability of metabolomics in the oncology field, particularly in the development of cancer biomarkers. With respect to renal cell carcinoma (RCC), a metabolomics approach would own a great potential since urinary system is intimately connected with urine and, this biofluid, offers some advantages allowing the development of an assay suitable for use in clinical practice. Moreover, the assessment of metabolic derangements characteristics of RCC might provide a complete health assessment of this pathology, enabling the development of novel targeted therapies and even the stratification of responsive patients to specific therapeutic options improving the effectiveness of therapy. Metabolomic studies performed so far showed that the RCC metabolic signature is characterized by alterations in metabolites related to energy metabolic pathways, particularly glycolysis, amino acid and fatty acid catabolism, known to be crucial to cell proliferation. Despite some of those alterations are common to carcinogenesis, the potential role of acylcarnitines, gentisate, α-ketoglutarate and quinolinate in RCC pathophysiology has been proposed recently. The ability of metabolomics to discriminate between RCC and normal samples shows convincing evidence of its applicability in RCC management. Furthermore, the studies already carried out have not only tried to unveil the metabolic profile of RCC but also to evaluate the impact of some factors, namely technical, in RCC-metabolomics research. This type of study is pivotal in the design of metabolomics studies, helping to increase the reliability of the results. The present review updates the current knowledge on the metabolic alterations recognized in the RCC, and provides insight to the characteristics, strengths, limitations, and recent advances in RCC-metabolomics studies, always keeping in mind its potential application in clinical/health areas as a biomarker discovery tool.     

Leveraging metabolomics for functional investigations in sequenced marine diatoms

Recent years have witnessed the genomic decoding of a wide range of photosynthetic organisms from the model plant Arabidopsis thaliana and the complex genomes of important crop species to single-celled marine phytoplankton. The comparative sequencing of green, red and brown algae has provided considerable insight into a number of important questions concerning their evolution, physiology and metabolism. The combinatorial application of metabolomics has further deepened our understanding both of the function of individual genes and of metabolic processes. Here we discuss the power of utilising metabolomics in conjunction with sequencing data to gain greater insight into the metabolic hierarchies underpinning the function of individual organisms, using unicellular marine diatoms as a case study to exemplify the advantages of this approach.     

Oncometabolomics in cancer research

Cancer is not only a complex genetic disease, but also a disease of dysregulated bioenergetic metabolism. With improved technological advancements, the focus has shifted from changes in an individual biochemical pathway or metabolite toward changes in the context of the global network of metabolic pathways in a cell, tissue or organism. This global approach allows identifying changes in the pattern of metabolite expression in addition to changes in individual metabolite or pathway. Such a metabolomics approach promises a better understanding of tumor biology and identification of potential biomarkers with applications as diagnostic, prognostic and therapeutic targets. In this review, we discuss various techniques used in metabolomics and analysis of the data generated and its specific uses in cancer research including novel biomarker identification, development of more sensitive and specific diagnostic methods, monitoring of currently used cancer therapeutics to evaluate the prognostic outcome with a given therapy and evaluating novel therapeutic strategies.     

Metabolomics as a diagnostic tool for hepatology: validation in a naturally occurring canine model

Human hepatopathies are a diagnostic challenge, with many distinct diseases having similar clinical signs and laboratory findings. Naturally occurring canine hepatic disease provides an excellent model for human diseases and similar diagnostic dilemmas exist; differentiating canine congenital portosystemic vascular anomalies (PVA) from acquired hepatopathies is difficult and traditionally requires invasive diagnostic procedures. The emerging post-genomic science of metabolomics is concerned with detecting global changes of populations of endogenous low molecular weight metabolites in biological samples and offers the possibility of identifying surrogate profiles of disease. Metabolomics couples sensitive metabolite analysis with sophisticated pattern recognition techniques. In this study, a metabolomic strategy has been employed to assess metabolite changes in the plasma of dogs with congenital PVA and acquired hepatic disease. Plasma samples were collected from 25 dogs, comprising 9 dogs with congenital PVA, 6 with acquired hepatopathy and 10 with non-hepatic disorders. Low molecular weight metabolites were analyzed by liquid chromatography-mass spectrometry (LC-MS). Following identification of metabolites, multivariate data analysis was used to compare profiles amongst groups. The analysis demonstrated significant disturbances in the plasma bile acid and phospholipid profiles of dogs with portovascular anomalies. In contrast to traditional laboratory parameters, the metabolomic strategy was able to produce a clear segregation between all three study groups. In conclusion, this study demonstrates the potential of metabolomics as a diagnostic tool for naturally occurring hepatic disease. With further validation, this approach will improve diagnostic capabilities, provide an insight into pathogenetic mechanisms, and ultimately inform therapeutic decision making in clinical hepatology. This work was supported in part by grants from The Royal Society, Petplan Charitable Trust and The Waltham Foundation.     

Untargeted plasma metabolite profiling reveals the broad systemic consequences of xanthine oxidoreductase inactivation in mice

A major challenge in systems biology is integration of molecular findings for individual enzyme activities into a cohesive high-level understanding of cellular metabolism and physiology/pathophysiology. However, meaningful prediction for how a perturbed enzyme activity will globally impact metabolism in a cell, tissue or intact organisms is precluded by multiple unknowns, including in vivo enzymatic rates, subcellular distribution and pathway interactions. To address this challenge, metabolomics offers the potential to simultaneously survey changes in thousands of structurally diverse metabolites within complex biological matrices. The present study assessed the capability of untargeted plasma metabolite profiling to discover systemic changes arising from inactivation of xanthine oxidoreductase (XOR), an enzyme that catalyzes the final steps in purine degradation. Using LC-MS coupled with a multivariate statistical data analysis platform, we confidently surveyed >3,700 plasma metabolites (50-1,000 Da) for differential expression in XOR wildtype vs. mice with inactivated XOR, arising from gene deletion or pharmacological inhibition. Results confirmed the predicted derangements in purine metabolism, but also revealed unanticipated perturbations in metabolism of pyrimidines, nicotinamides, tryptophan, phospholipids, Krebs and urea cycles, and revealed kidney dysfunction biomarkers. Histochemical studies confirmed and characterized kidney failure in xor-nullizygous mice. These findings provide new insight into XOR functions and demonstrate the power of untargeted metabolite profiling for systemic discovery of direct and indirect consequences of gene mutations and drug treatments.     

Understanding heart failure with preserved ejection fraction: where are we today?

Heart failure with preserved ejection fraction (HFpEF) represents a complex and heterogeneous clinical syndrome, which is increasingly prevalent and associated with poor outcome. In contrast to heart failure with reduced ejection fraction (HFrEF), modern heart failure pharmacotherapy did not improve outcome in HFpEF, which was attributed to incomplete understanding of HFpEF pathophysiology, patient heterogeneity and lack of insight into primary pathophysiological processes. HFpEF patients are frequently elderly females and patients demonstrate a high prevalence of non-cardiac comorbidities, which independently adversely affect myocardial structural and functional remodelling. Furthermore, although diastolic left ventricular dysfunction represents the dominant abnormality in HFpEF, numerous ancillary mechanisms are frequently present, which also negatively impact on cardiovascular reserve. Over the past decade, clinical and translational research has improved insight into HFpEF pathophysiology and the importance of comorbidities and patient heterogeneity. Recently, a new paradigm for HFpEF was proposed, which states that comorbidities drive myocardial dysfunction and remodelling in HFpEF through coronary microvascular inflammation. Regarding the conceptual framework of HFpEF treatment, emphasis may need to shift from a ‘one fits all’ strategy to an individualised approach based on phenotypic patient characterisation and diagnostic and pathophysiological stratification of myocardial disease processes. This review will describe these novel insights from a pathophysiological standpoint.     

Urine metabolomic analysis identifies potential biomarkers and pathogenic pathways in kidney cancer

Kidney cancer is the seventh most common cancer in the Western world, its incidence is increasing, and it is frequently metastatic at presentation, at which stage patient survival statistics are grim. In addition, there are no useful biofluid markers for this disease, such that diagnosis is dependent on imaging techniques that are not generally used for screening. In the present study, we use metabolomics techniques to identify metabolites in kidney cancer patients' urine, which appear at different levels (when normalized to account for urine volume and concentration) from the same metabolites in nonkidney cancer patients. We found that quinolinate, 4-hydroxybenzoate, and gentisate are differentially expressed at a false discovery rate of 0.26, and these metabolites are involved in common pathways of specific amino acid and energetic metabolism, consistent with high tumor protein breakdown and utilization, and the Warburg effect. When added to four different (three kidney cancer-derived and one "normal") cell lines, several of the significantly altered metabolites, quinolinate, α-ketoglutarate, and gentisate, showed increased or unchanged cell proliferation that was cell line-dependent. Further evaluation of the global metabolomics analysis, as well as confirmation of the specific potential biomarkers using a larger sample size, will lead to new avenues of kidney cancer diagnosis and therapy.     

ADAM-17: the enzyme that does it all

This review focuses on the role of ADAM-17 in disease. Since its debut as the tumor necrosis factor converting enzyme (TACE), ADAM-17 has been reported to be an indispensible regulator of almost every cellular event from proliferation to migration. The central role of ADAM-17 in cell regulation is rooted in its diverse array of substrates: cytokines, growth factors, and their receptors as well as adhesion molecules are activated or inactivated by their cleavage with ADAM-17. It is therefore not surprising that ADAM-17 is implicated in numerous human diseases including cancer, heart disease, diabetes, rheumatoid arthritis, kidney fibrosis, Alzheimer’s disease, and is a promising target for future treatments. The specific role of ADAM-17 in the pathophysiology of these diseases is very complex and depends on the cellular context. To exploit the therapeutic potential of ADAM-17, it is important to understand how its activity is regulated and how specific organs and cells can be targeted to inactivate or activate the enzyme.     

Metabolomics‐proteomics profiles delineate metabolic changes in kidney fibrosis disease

Kidney fibrosis (KF) is a common process that leads to the progression of various types of kidney disease including kidney‐yang deficiency syndrome, however, little is known regarding the underlying biology of this disorder. Fortunately, integrated omics approaches provide the molecule fingerprints related to the disease. In an attempt to address this issue, we integrated metabolomics–proteomics profiles analyzed pathogenic mechanisms of KF based on rat model. A total 37 serum differential metabolites were contributed to KF progress, involved several important metabolic pathways. Using iTRAQ‐based quantitative proteomics analysis, 126 differential serum proteins were identified and provide valuable insight into the underlying mechanisms of KF. These proteins appear to be involved in complement and coagulation cascades, regulation of actin cytoskeleton, MAPK signaling pathway, RNA transport, etc. Interestingly, pathway/network analysis of integrated proteomics and metabolomics data firstly reveals that these signaling pathways were closely related with KF. It further indicated that most of these proteins play a pivotal role in the regulation of metabolism pathways.     

Role of genetic modifiers in an orthologous rat model of ARPKD

Human data and animal models of autosomal recessive polycystic kidney disease (ARPKD) suggest that genetic factors modulate the onset and severity of the disease. We report here for the first time that ARPKD susceptibility is attenuated by introgressing the mutated Pkhd1 disease allele from the polycystic kidney (PCK) rat onto the FHH (Fawn-Hooded Hypertensive) genetic background. Compared with PCK, the FHH.Pkhd1 strain had significantly decreased renal cyst formation that coincided with a threefold reduction in mean kidney weights. Further analysis revealed that the FHH. Pkhd1 is protected from increased blood pressure as well as elevated plasma creatinine and blood urea nitrogen levels. On the other hand, liver weight and biliary cystogenesis revealed no differences between PCK and FHH.Pkdh1, indicating that genes within the FHH genetic background prevent the development of renal, but not hepatic, manifestations of ARPKD. Microarray expression analysis of kidneys from 30-day-old PCK rats revealed increased expression of genes previously identified in PKD renal expression profiles, such as inflammatory response, extracellular matrix synthesis, and cell proliferation genes among others, whereas the FHH.Pkhd1 did not show activation of these common markers of disease. This newly developed strain can serve as a tool to map modifier genes for renal disease in ARPKD and provides further insight into disease variability and pathophysiology.     

'Deep phenotyping': characterizing populations in the era of genomics and systems biology

PURPOSE OF REVIEW: Large-scale genomic studies establish genotype-phenotype associations, but they use phenotypes that represent current views of disease. There is an opportunity to enhance our understanding of genotype-phenotype associations by extending phenotypes into much greater detail ('deep phenotyping'). RECENT FINDINGS: We should engage in deep phenotyping for the following reasons. First, the current emphasis on clinical outcomes, although necessary for the advancement of clinical medicine, is not sufficient. Second, analytical and biological variance embedded in traditional phenotypes dilutes statistical power and strength of association. Finally, even relatively precise phenotypes may vary in terms of underlying pathophysiology across an individual's life history. Deep phenotyping focuses on the biological relevance of pathways and metabolic flux, increasing the 'granularity' of phenotypes. SUMMARY: Focus on medical phenotypes is critical, but long-term interests require additional studies that illuminate underlying biology. Deep phenotyping is less likely to yield dramatic changes in current medical practice but it offers an opportunity to gain scientific insight in an incremental manner and to make progress in redefining clinical outcomes with greater precision. It is expensive, and debate is needed to determine when and how it should be applied.     

A systemic insight into astrocytoma biology across different grades

Astrocytomas are the most common type of brain tumors, which originate from glial cells, and are classified into specific grades based on their histopathological behavior. To develop precise therapeutic strategies for the disease, it is important to identify the molecular signatures specific to each grade as well as the key factors responsible for the transition from one grade to the next. In this study, we have taken a systems approach to investigate the gene expression profiles of each grades of the disease by mapping shortest paths of gene interaction in each grade and also between one grade and the next. Module core genes govern the topology of these networks and serve as important functional players in each grade as well as help in grade transition events. Shortlisted among these module core genes are well-characterized players of glioma as well as novel molecules (32 grade-specific genes and 15 grade transition–specific genes), which influence important prooncogenic functions but have not been linked to glioma biology yet. These module core genes provide interesting insight into the biology of astrocytic tumors and are potential therapeutic targets for astrocytoma.     

Multivariate classification analysis of metabolomic data for candidate biomarker discovery in type 2 diabetes mellitus

Recent advances in genomics, metabolomics and proteomics have made it possible to interrogate disease pathophysiology and drug response on a systems level. The analysis and interpretation of the complex data obtained using these techniques is potentially fertile but equally challenging. We conducted a small clinical trial to explore the application of metabolomics data in candidate biomarker discovery. Specifically, serum and urine samples from patients with type 2 diabetes mellitus (T2DM) were profiled on metabolomics platforms before and after 8 weeks of treatment with one of three commonly used oral antidiabetic agents, the sulfonyurea glyburide, the biguanide metformin, or the thiazolidinedione rosiglitazone. Multivariate classification techniques were used to detect serum or urine analytes, obtained at baseline (pre-treatment) that could predict a significant treatment response after 8 weeks. Using this approach, we identified three analytes, measured at baseline, that were associated with response to a thiazolidinedione after 8 weeks of treatment. Although larger and longer-term studies are required to validate any of the candidate biomarkers, pharmacometabolomic profiling, in combination with multivariate classification, is worthy of further exploration as an adjunct to clinical decision making regarding treatment selection and for patient stratification within clinical trials. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Diagnosis, pathogenesis, and treatment prospects in cystic kidney disease

Cystic kidney diseases (CKDs) are a clinically and genetically heterogeneous group of disorders characterized by progressive fibrocystic renal and hepatobiliary changes. Recent findings have proven the cystogenic process to be compatible with cellular dedifferentiation, i. e. increased apoptosis and proliferation rates, altered protein sorting and secretory characteristics, as well as disorganization of the extracellular matrix. Compelling evidence suggests that cilia play a central pathogenic role and most cystic kidney disorders converge into a common pathogenic pathway. Recently, several promising trials have further extended our understanding of the pathophysiology of CKD and may have the potential for rational personalized therapies in future years. This review aims to summarize the current state of knowledge of the structure and function of proteins underlying polycystic kidney disease, to explore the clinical consequences of changes in respective genes, and to discuss potential therapeutic approaches.     

Proteomics and biomarkers in clinical trials for drug development

Proteomics allows characterization of protein structure and function, protein-protein interactions, and peptide modifications. It has given us insight into the perturbations of signaling pathways within tumor cells and has improved the discovery of new therapeutic targets and possible indicators of response to and duration of therapy. The discovery, verification, and validation of novel biomarkers are critical in streamlining clinical development of targeted compounds, and directing rational treatments for patients whose tumors are dependent upon select signaling pathways. Studies are now underway in many diseases to examine the immune or inflammatory proteome, vascular proteome, cancer or disease proteome, and other subsets of the specific pathology microenvironment. Successful assay verification and biological validation of such biomarkers will speed development of potential agents to targetable dominant pathways and lead to selection of individuals most likely to benefit. Reconsideration of analytical and clinical trials methods for acquisition, examination, and translation of proteomics data must occur before we march further into future of drug development.     

New therapeutic options for lysosomal storage disorders: enzyme replacement,small molecules and gene therapy

During the last few years, much progress has been made in the treatment of lysosomal storage disorders. In the past, no specific therapy was available for the affected patients, and management consisted solely of supportive care and treatment of complications. Since enzyme replacement therapy has been successfully introduced for patients with Gaucher disease, this principle of treatment has been taken into consideration for other lysosomal storage disorders as well. Clinical trials could demonstrate the clinical benefit of this therapeutic principle in Fabry disease, mucopolysaccharidoses type I, II and VI and in Pompe disease. However, the usefulness of enzyme replacement therapy is limited due to the fact that a given enzyme preparation does not have beneficial effects on all aspects of a disorder in the same degree. Additionally, clinical studies have shown that many symptoms of a lysosomal storage disorder even after long-term treatment are no more reversible. A further novel therapeutic option for lysosomal storage disorders consists of the application of small molecules that either inhibit a key enzyme which is responsible for substrate synthesis (substrate deprivation) or act as a chaperone to increase the residual activity of the lysosomal enzyme (enzyme enhancing therapy). Various gene therapeutic techniques (in vivo and ex vivo technique) have been developed in order to administer the gene that is defective in a patient to the bloodstream or directly to the brain in order to overcome the blood–brain barrier. This review will give an insight into these newly developed therapeutic strategies and will discuss their advantages and limitations.     

Modulation of gut microbiome in nonalcoholic fatty liver disease: pro-, pre-, syn-, and antibiotics

Nonalcoholic fatty liver disease (NAFLD) is one of the most common types of liver diseases worldwide and its incidence continues to increase. NAFLD occurs when the body can no longer effectively store excess energy in the adipose tissue. Despite the increasing prevalence of NAFLD, making lifestyle changes, including increased exercise, is often an elusive goal for patients with NAFLD. The liver directly connects to the gut-gastrointestinal milieu via the portal vein, which are all part of the gut-liver axis. Therefore, the gut-microbiome and microbial products have been actively studied as likely key factors in NAFLD pathophysiology. Hence, dysbiosis of the gut microbiome and therapeutic manipulation of the gut-liver axis are being investigated. Novel therapeutic approaches for modulating gut microbiota through the administration of probiotics, prebiotics, synbiotics, and antibiotics have been proposed with numerous promising initial reports on the effectiveness and clinical applications of these approaches. This review delves into the current evidence on novel therapies that modulate gut microbiota and discusses ongoing clinical trials targeting the gut-liver axis for the management and prevention of NAFLD.