Tumor necrosis factor stimulates fibroblast growth factor 23 levels in chronic kidney disease and non-renal inflammation.

Fibroblast growth factor 23 (FGF23) regulates phosphate homeostasis, and its early rise in patients with chronic kidney disease is independently associated with all-cause mortality. Since inflammation is characteristic of chronic kidney disease and associates with increased plasma FGF23 we examined whether inflammation directly stimulates FGF23. In a population-based cohort, plasma tumor necrosis factor (TNF) was the only inflammatory cytokine that independently and positively correlated with plasma FGF23. Mouse models of chronic kidney disease showed signs of renal inflammation, renal FGF23 expression and elevated systemic FGF23 levels. Renal FGF23 expression coincided with expression of the orphan nuclear receptor Nurr1 regulating FGF23 in other organs. Antibody-mediated neutralization of TNF normalized plasma FGF23 and suppressed ectopic renal Fgf23 expression. Conversely, TNF administration to control mice increased plasma FGF23 without altering plasma phosphate. Moreover, in Il10-deficient mice with inflammatory bowel disease and normal kidney function, plasma FGF23 was elevated and normalized upon TNF neutralization. Thus, the inflammatory cytokine TNF contributes to elevated systemic FGF23 levels and also triggers ectopic renal Fgf23 expression in animal models of chronic kidney disease.

Potentials and pitfalls of clinical peptidomics and metabolomics.

Clinical peptidomics and metabolomics are two emerging "-omics" technologies with the potential not only to detect disease-specific markers, but also to give insight into the disease dependency of degradation processes and metabolic pathway alterations. However, despite their rapid evolution and major investments, a clinical breakthrough, such as the approval of a major cancer biomarker, is still out of sight. What are the reasons for this failure? In this review we focus on three important factors: sensitivity, specificity and the avoidance of bias. The way to clinical implementation of peptidomics and metabolomics is still hampered by many of the problems that had to be solved for genomics and proteomics in the past, as well as new ones that require the creation of new analytic, computational and interpretative techniques. The greatest challenge, however, will be the integration of information from different "-omics" subdisciplines into straightforward answers to clinical questions, for example, in the form of new, superior "meta-markers".

Pancreatic carcinoma, pancreatitis, and healthy controls: metabolite models in a three-class diagnostic dilemma.

Metabolomics as one of the most rapidly growing technologies in the "-omics" field denotes the comprehensive analysis of low molecular-weight compounds and their pathways. Cancer-specific alterations of the metabolome can be detected by high-throughput mass-spectrometric metabolite profiling and serve as a considerable source of new markers for the early differentiation of malignant diseases as well as their distinction from benign states. However, a comprehensive framework for the statistical evaluation of marker panels in a multi-class setting has not yet been established. We collected serum samples of 40 pancreatic carcinoma patients, 40 controls, and 23 pancreatitis patients according to standard protocols and generated amino acid profiles by routine mass-spectrometry. In an intrinsic three-class bioinformatic approach we compared these profiles, evaluated their selectivity and computed multi-marker panels combined with the conventional tumor marker CA 19-9. Additionally, we tested for non-inferiority and superiority to determine the diagnostic surplus value of our multi-metabolite marker panels. Compared to CA 19-9 alone, the combined amino acid-based metabolite panel had a superior selectivity for the discrimination of healthy controls, pancreatitis, and pancreatic carcinoma patients [Formula: see text] We combined highly standardized samples, a three-class study design, a high-throughput mass-spectrometric technique, and a comprehensive bioinformatic framework to identify metabolite panels selective for all three groups in a single approach. Our results suggest that metabolomic profiling necessitates appropriate evaluation strategies and-despite all its current limitations-can deliver marker panels with high selectivity even in multi-class settings.

Hypercalcemia in the ED: prevalence, etiology, and outcome.

PURPOSES: The aim of the study was to describe the prevalence, demographic, and clinical characteristics and etiologies of hypercalcemia in emergency department patients. BASIC PROCEDURES: In this retrospective cross-sectional descriptive study, all patients admitted between April 1, 2008, and March 31, 2011, to the emergency department of Inselspital, University Hospital Bern, were screened for the presence of hypercalcemia, defined as a serum calcium exceeding 2.55 mmol/L after correction for serum albumin. Demographic, laboratory, and outcome data were gathered. A detailed medical record review was performed to identify causes of hypercalcemia. MAIN FINDINGS: During the study period, 14 984 patients (19% of all admitted patients) received a measurement of serum calcium. Of these, 116 patients (0.7%) presented with hypercalcemia. Median serum calcium was 2.72 mmol/L (first quartile, 2.64; third quartile, 2.88), with 4.3 mmol/L being the maximum serum calcium value observed. Underlying malignancy in 44% of patients and hyperparathyroidism in 20% (12% secondary and 8% primary) were the leading causes of hypercalcemia. Twenty-six percent of patients presented with symptomatic hypercalcemia. Weakness was the most common symptom of hypercalcemia, followed by nausea and disorientation. PRINCIPAL CONCLUSIONS: Hypercalcemia is a rare but harmful electrolyte disorder in emergency department patients. Unspecific symptoms such as a change in mental state, weakness, or gastrointestinal symptoms should prompt physicians to order serum calcium measurements, at least in patients with known malignancy or renal insufficiency.

Serum amino acid profiles and their alterations in colorectal cancer.

Mass spectrometry-based serum metabolic profiling is a promising tool to analyse complex cancer associated metabolic alterations, which may broaden our pathophysiological understanding of the disease and may function as a source of new cancer-associated biomarkers. Highly standardized serum samples of patients suffering from colon cancer (n = 59) and controls (n = 58) were collected at the University Hospital Leipzig. We based our investigations on amino acid screening profiles using electrospray tandem-mass spectrometry. Metabolic profiles were evaluated using the Analyst 1.4.2 software. General, comparative and equivalence statistics were performed by R 2.12.2. 11 out of 26 serum amino acid concentrations were significantly different between colorectal cancer patients and healthy controls. We found a model including CEA, glycine, and tyrosine as best discriminating and superior to CEA alone with an AUROC of 0.878 (95% CI 0.815-0.941). Our serum metabolic profiling in colon cancer revealed multiple significant disease-associated alterations in the amino acid profile with promising diagnostic power. Further large-scale studies are necessary to elucidate the potential of our model also to discriminate between cancer and potential differential diagnoses. In conclusion, serum glycine and tyrosine in combination with CEA are superior to CEA for the discrimination between colorectal cancer patients and controls.

Serum peptidome profiling revealed platelet factor 4 as a potential discriminating Peptide associated with pancreatic cancer.

PURPOSE: Mass spectrometry-based serum peptidome profiling is a promising tool to identify novel disease-associated biomarkers, but is limited by preanalytic factors and the intricacies of complex data processing. Therefore, we investigated whether standardized sample protocols and new bioinformatic tools combined with external data validation improve the validity of peptidome profiling for the discovery of pancreatic cancer-associated serum markers. EXPERIMENTAL DESIGN: For the discovery study, two sets of sera from patients with pancreatic cancer (n = 40) and healthy controls (n = 40) were obtained from two different clinical centers. For external data validation, we collected an independent set of samples from patients (n = 20) and healthy controls (n = 20). Magnetic beads with different surface functionalities were used for peptidome fractionation followed by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS). Data evaluation was carried out by comparing two different bioinformatic strategies. Following proteome database search, the matching candidate peptide was verified by MALDI-TOF MS after specific antibody-based immunoaffinity chromatography and independently confirmed by an ELISA assay. RESULTS: Two significant peaks (m/z 3884; 5959) achieved a sensitivity of 86.3% and a specificity of 97.6% for the discrimination of patients and healthy controls in the external validation set. Adding peak m/z 3884 to conventional clinical tumor markers (CA 19-9 and CEA) improved sensitivity and specificity, as shown by receiver operator characteristics curve analysis (AUROC(combined) = 1.00). Mass spectrometry-based m/z 3884 peak identification and following immunologic quantitation revealed platelet factor 4 as the corresponding peptide. CONCLUSIONS: MALDI-TOF MS-based serum peptidome profiling allowed the discovery and validation of platelet factor 4 as a new discriminating marker in pancreatic cancer.

Challenges and developments in tandem mass spectrometry based clinical metabolomics.

'Clinical metabolomics' aims at evaluating and predicting health and disease risk in an individual by investigating metabolic signatures in body fluids or tissues, which are influenced by genetics, epigenetics, environmental exposures, diet, and behaviour. Powerful analytical techniques like liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) offers a rapid, effective and economical way to analyze metabolic alterations of pre-defined target metabolites in biological samples. Novel hyphenated technical approaches like the combination of tandem mass spectrometry combined with linear ion trap (QTrap mass spectrometry) combines both identification and quantification of known and unknown metabolic targets. We describe new concepts and developments of mass spectrometry based multi-target metabolome profiling in the field of clinical diagnostics and research. Particularly, the experiences from newborn screening provided important insights about the diagnostic potential of metabolite profiling arrays and directs to the clinical aim of predictive, preventive and personalized medicine by metabolomics.

Standardized peptidome profiling of human cerebrospinal fluid by magnetic bead separation and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.

Peptidome profiling of human cerebrospinal fluid (CSF) is a promising tool to identify novel disease-associated biomarkers. Our aim was to develop a standardized protocol for reproducible peptidome profiling of CSF using magnetic bead (MB) separation followed by MALDI-TOF MS. Peptidome fractionation and profiling of CSF were performed using MBs with different surface functionalities. We investigated exogenous variables (storage conditions, freeze-thaw-cycles) and endogenous interferences (albumin, immunoglobulin, blood, leukocytes) in pooled CSF samples. We detected approximately 500 signals with an S/N ratio >10 and an overlap frequency of about 40% in non-pathological CSF. Within- and between-day imprecisions in relative signal intensities ranged from 3 to 28% and 7 to 47%, respectively. CSF storage at room temperature for up to 6 h and at 4 degrees C for up to 3 days did not significantly influence the mass spectra. Consecutive freeze-thaw-cycles significantly affected the mass spectra. High albumin and immunoglobulin content altered the CSF preparation using MB-HIC C8 beads. Blood contamination showed no effect on mass spectra up to a hemoglobin concentration of 0.075 micromol/L. The presence of leukocytes up to a cell number of 30 Mpt/L did not affect mass spectra. Our reliable pretreatment protocol allows standardization of preanalytical modalities and thereby enables reproducible peptidome profiling of human CSF using MB separation followed by MALDI-TOF MS.

Standardized peptidome profiling of human urine by magnetic bead separation and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.

BACKGROUND: Peptidome profiling of human urine is a promising tool to identify novel disease-associated biomarkers; however, a wide range of preanalytical variables influence the results of peptidome analysis. Our aim was to develop a standardized protocol for reproducible urine peptidome profiling by means of magnetic bead (MB) separation followed by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS). METHODS: MBs with defined surface functionalities (hydrophobic interaction, cation exchange, and metal ion affinity) were used for peptide fractionation of urine. Mass accuracy and imprecision were calculated for 9 characteristic mass signals (M(r), 1000-10,000). Exogenous variables (instrument performance, urine sampling/storage conditions, freezing conditions, and freeze-thaw cycles) and endogenous variables (pH, urine salt and protein concentrations, and blood and bacteria interferences) were investigated with urine samples from 10 male and 10 female volunteers. RESULTS: We detected 427 different mass signals in the urine of healthy donors. Within- and between-day imprecision in relative signal intensities ranged from 1% to 14% and from 4% to 16%, respectively. Weak cation-exchange and metal ion affinity MB preparations required adjustment of the urinary pH to 7. Storage time, storage temperature, the number of freeze-thaw cycles, and bacterial and blood contamination significantly influenced urine peptide patterns. Individual urine peptide patterns differed significantly within and between days. This imprecision was diminished by normalization to a urinary protein content of 3.5 microg. CONCLUSION: This reliable pretreatment protocol allows standardization of preanalytical modalities and facilitates reproducible peptidome profiling of human urine by means of MB separation in combination with MALDI-TOF MS.

Rapid simultaneous quantification of immunosuppressants in transplant patients by turbulent flow chromatography combined with tandem mass spectrometry.

BACKGROUND: Immunosuppressant therapeutic drug monitoring (TDM) is an important requirement in the management of post-transplant patients. Our aim was to develop and evaluate a robust high-throughput method using turbulent flow chromatography (TFC) coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS) for the simultaneous quantification of cyclosporin A (CsA), tacrolimus (FK 506) and sirolimus. METHODS: A total of 1483 EDTA-blood pre-dosage samples from 147 kidney, 67 liver, 15 kidney/pancreas, and 48 bone marrow recipients were collected. After hemolysis and protein precipitation of 50 microl blood, fast and efficient on-line matrix elimination was achieved using turbulent flow chromatography. Tandem mass spectrometric detection and quantification was performed using multiple reaction monitoring (MRM). RESULTS: The total analysis time of the column switching method was 3 min. The method was linear from 4.5 to 1500 ng/ml for cyclosporin A, from 0.2 to 100 ng/ml for tacrolimus, and from 0.4 to 100 ng/ml for sirolimus. The accuracy was >95%. Within and between-run assay variation coefficients ranged from 2.4% to 9.3%. Excellent correlation with other standard methods (immunoassay, HPLC) was observed. CONCLUSIONS: The presented turbulent flow chromatography-tandem mass spectrometric platform offers a very fast, simple and economical method with an excellent validation profile and is well suited for daily pre- and post-dosage immunosuppressant monitoring.

Changes of vasoregulatory gene expression following hepatic ischemia/reperfusion and treatment with endothelin-A receptor blockade.

The objective of this study was to investigate the effect of a specific endothelin-A receptor antagonist on mRNA expression of genes encoding vasoactive mediators and proinflammatory cytokines following complete vascular exclusion of the porcine liver. Fourteen adult German Landrace pigs were subjected to 120 minutes of warm hepatic ischemia by total vascular exclusion. The animals were divided into two groups: the control group received saline solution and the therapy group was given the selective endothelin-A receptor antagonist BSF 208075. Liver tissue samples were collected 1 hour after reperfusion and mRNA expression for preproendothelin-1, prointerleukin-1beta, prointerleukin- 6, pro-tumor necrosis factor-alpha and endothelial nitric oxide synthase was analyzed quantitatively using the TaqMan system. Additionally, immunohistochemical analysis using a semiquantitative score for endothelin-1 and endothelin-A receptor was performed. One hour after reperfusion, quantitative reverse transcriptase-polymerase chain reaction revealed significantly lower expression of preproendothelin-1, pro-tumor necrosis factor-alpha, and prointerleukin-6 in the therapy group compared to controls. Immunohistochemical analysis demonstrated significantly reduced endothelin-1 immunostaining after therapy. Treatment with the selective endothelin-A receptor antagonist exerts a protective effect on the microcirculation after liver ischemia and reperfusion. We were able to show that the endothelin-A receptor antagonist not only has effects on the expression of vasoactive genes, it also decreases gene expression of proinflammatory cytokines such as tumor necrosis factor-alpha and interleukin-6.