Metabolite profiling of hemodialysate using gas chromatography time-of-flight mass spectrometry

Metabolite profiling analysis of hepatitis B virus-induced liver cirrhosis patients with minimal hepatic encephalopathy using gas chromatography-time-of-flight mass spectrometry and ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry

This study used gas chromatography-time-of-flight mass spectrometry (GC-TOFMS) and ultra-performance liquid chromatography-quadrupole TOFMS (UPLC-QTOFMS) metabonomic analytical techniques in combination with bioinformatics and pattern recognition analysis methods to analyze the serum metabolite profiling of hepatitis B virus (HBV)-induced liver cirrhosis patients with minimal hepatic encephalopathy (MHE), to find the specific biomarkers of MHE, to reveal the pathogenesis of MHE, and to determine a promising approach for early diagnosis of MHE. Serum samples of 100 normal controls (NC group), 29 HBV-induced liver cirrhosis patients with MHE (MHE group), and 24 HBV-induced liver cirrhosis patients without MHE [comprising 12 cases of compensated cirrhosis (CS group) and 12 cases of decompensated cirrhosis (DS group)] were collected and employed into GC-TOFMS and UPLC-QTOFMS platforms for serum metabolite detection; the outcome data were then analyzed using principal component analysis and orthogonal partial least squares-discriminant analysis (OPLS-DA). There were no significant differential metabolites between the NC group and the CS group. A series of key differential metabolites were detected. According to the variable influence in projection values and P-values, 60 small-molecule metabolites were considered to be dysregulated in the MHE group (compared to the NC group); 27 of these 60 dysregulated differential metabolites were considered to be the potential biomarkers (see Table 4, marked in bold); 66 small-molecule metabolites were considered to be dysregulated in the DS group (compared to the NC group); 34 of these 66 dysregulated differential metabolites were considered to be the potential biomarkers (see Table 5, marked in bold). According to the fold-change values, 9 of these 27 metabolites, namely valine, oxalic acid, erythro-sphingosine, 4,7,10,13,16,19-docosahexaenoic acid, isoleucine, allo-isoleucine, thyroxine, rac-octanoyl carnitine, and tocopherol (vitamin E), were downregulated in the MHE group (compared to the NC group); the other 18, namely adenine, glycochenodeoxycholic acid, fucose, allothreonine, glycohyocholic acid, glycoursodeoxycholic acid, tyrosine, taurocheno-deoxycholate, phenylalanine, 2-hydroxy-3-methyl-butanoic acid, hydroxyacetic acid, taurocholate, sorbitol, rhamnose, tauroursodeoxycholate, tolbutamide, pyroglutamic acid, and malic acid, were upregulated; 6 of these 34 metabolites were downregulated in the DS group (compared to the NC group), and the other 28 were upregulated, as shown in Table 5. (a) GC-TOFMS and UPLC-QTOFMS metabonomic analytical platforms can detect a range of metabolites in the serum; this might be of great help to study the pathogenesis of MHE and may provide a new approach for the early diagnosis of MHE. (b) Metabonomics analysis in combination with pattern recognition analysis might have great potential to distinguish the HBV-induced liver cirrhosis patients who have MHE from the normal healthy population and HBV-induced liver cirrhosis patients without MHE.

Bioanalysis of INCB000928 in hemodialysate: prevention of nonspecific binding and validation of surrogate matrices

Aim: To develop and validate a bioanalytical method for the quantification of INCB000928 in hemodialysate. Materials & methods: Blank dialysate and phosphate-buffered saline were compared with hemodialysate for surrogate matrix selection. Direct addition of internal standard without analyte extraction and a high-performance LC-MS/MS were used for analysis. Results & conclusion: INCB000928 in hemodialysate exhibited strong nonspecific binding to polypropylene containers. In the presence of 10% isopropyl alcohol, the loss of INCB000928 was fully recovered, regardless of pre- or post-addition of the solvent. Blank dialysate and phosphate-buffered saline were determined to be appropriate surrogate matrices by using a three-way cross-comparison and were subsequently validated in the quantitative analysis of INCB000928 in hemodialysate.

A convenient online desalination tube coupled with mass spectrometry for the direct detection of iodinated contrast media in untreated human spent hemodialysates

Background

Mass spectrometry (MS) analysis using direct infusion of biological fluids is often problematic due to high salts/buffers. Iodinated contrast media (ICM) are frequently used for diagnostic imaging purposes, sometimes inducing acute kidney injury (AKI) in patients with reduced kidney function. Therefore, detection of ICM in spent hemodialysates is important for AKI patients who require urgent continuous hemodiafiltration (CHDF) because it allows noninvasive assessment of the patient’s treatment. In this study, we used a novel desalination tube before MS to inject the sample directly and detect ICM.

Methods

Firstly, spent hemodialysates of one patient were injected directly into the electrospray ionization (ESI) source equipped with a quadrupole time-of-flight mass spectrometer (Q-TOF MS) coupled to an online desalination tube for the detection of ICM and other metabolites. Thereafter, spent hemodialysates of two patients were injected directly into the ESI source equipped with a triple quadrupole mass spectrometer (TQ-MS) connected to that online desalination tube to confirm the detection of ICM.

Results

We detected iohexol (an ICM) from untreated spent hemodialysates of the patient-administered iohexol for computed tomography using Q-TOF MS. Using MRM profile analysis, we have confirmed the detection of ICM in the untreated spent hemodialysates of the patients administered for coronary angiography before starting CHDF. Using the desalination tube, we observed approximately 178 times higher signal intensity and 8 times improved signal-to-noise ratio for ioversol (an ICM) compared to data obtained without the desalination tube. This system was capable of tracking the changes of ioversol in spent hemodialysates of AKI patients by measuring spent hemodialysates.

Conclusion

The online desalination tube coupled with MS showed the capability of detecting iohexol and ioversol in spent hemodialysates without additional sample preparation or chromatographic separation. This approach also demonstrated the capacity to monitor the ioversol changes in patients’ spent hemodialysates.

A computational strategy for metabolic network construction based on the overlapping ratio: Study of patients' metabolic responses to different dialysis patterns

BACKGROUND

Uremia is a worldwide epidemic disease and poses a serious threat to human health. Both maintenance hemodialysis (HD) and maintenance high flux hemodialysis (HFD) are common treatments for uremia and are generally used in clinical applications. In-depth exploration of patients' metabolic responses to different dialysis patterns can facilitate the understanding of pathological alterations associated with uremia and the effects of different dialysis methods on uremia, which may be used for future personalized therapy. However, due to variations of multiple factors (i.e., genetic, epigenetic and environment) in the process of disease treatments, identification of the similarities and differences in plasma metabolite changes in uremic patients in response to HD and HFD remains challenging.

METHODS

In this study, a computational strategy for metabolic network construction based on the overlapping ratio (MNC-OR) was proposed for disease treatment effect research. In MNC-OR, the overlapping ratio was introduced to measure metabolic reactions and to construct metabolic networks for analysis of different treatment options. Then, MNC-OR was employed to analyze HD-pattern-dependent changes in plasma metabolites to explore the pathological alterations associated with uremia and the effectiveness of different dialysis patterns (i.e., HD and HFD) on uremia. Based on the networks constructed by MNC-OR, two network analysis techniques, namely, similarity analysis and difference analysis of network topology, were used to find the similarity and differences in metabolic signals in patients under treatment with either HD or HFD, which can facilitate the understanding of pathological alterations associated with uremia and provide the guidance for personalized dialysis therapy.

RESULTS

Similarity analysis of network topology suggested that abnormal energy metabolism, gut metabolism and pyrimidine metabolism might occur in uremic patients, and maintenance of both HFD and HD therapies have beneficial effects on uremia. Then, difference analysis of network topology was employed to extract the crucial information related to HD-pattern-dependent changes in plasma metabolites. Experimental results indicated that the amino acid metabolism was closer to the normal status in HFD-treated patients; however, in HD-treated patients, the ability of antioxidation showed greater reduction, and the protein O-GlcNAcylation level was higher. Our findings demonstrate the potential of MNC-OR for explaining the metabolic similarities and differences of patients in response to different dialysis methods, thereby contributing to the guidance of personalized dialysis therapy.

Ornithine is a key mediator in hyperphosphatemia-mediated human umbilical vein endothelial cell apoptosis: Insights gained from metabolomics

AIMS

Hyperphosphatemia is associated with accelerated vascular endothelial dysfunction in patients with chronic kidney disease (CKD). The purpose of this study is to investigate the molecular mechanisms underlying hyperphosphatemia-caused endothelial dysfunction.

MAIN METHODS

The metabolic fingerprinting of human umbilical vein endothelial cells (HUVECs) subjected to hyperphosphatemia was characterized using an integrated metabolomics approach. HUVECs cultured in physiologically simulated hyperphosphatemia with or without phosphonoformic acid, a sodium-dependent phosphate transporter inhibitor (N=6) were collected for metabolomics analysis. Multivariate principle component analysis and partial least squares discriminant analysis were applied to analyze the metabolic data. The key metabolites were confirmed by quantitative analysis using liquid chromatography coupled with tandem mass spectrometer (LC-MS/MS).

KEY FINDINGS

36 metabolites were significantly altered in HUVECs following the challenges of hyperphosphatemia mimic, involving several metabolic pathways (all P<0.05). Among them, ornithine increased significantly in the HUVECs mediated by hyperphosphatemia mimic, and its levels positively correlated with cell apoptosis rate (r=0.674, P=0.002), and several additional metabolites in multiple metabolic pathways. The changes in the levels of ornithine and other several metabolites were supported by subsequent quantitative analyses using LC-MS/MS. Further study demonstrated that the increase in ornithine level may result from the increased expression of arginase 2 in HUVECs, which mediates the hydrolysis of arginine to form ornithine.

SIGNIFICANCE

This is the first study demonstrating ornithine a key molecule mediating hyperphosphatemia-induced apoptosis of ECs. Arginase 2 may be a therapeutic target for hyperphosphatemia-associated cardiovascular events.

Separation technique for the determination of highly polar metabolites in biological samples

Metabolomics is a new approach that is based on the systematic study of the full complement of metabolites in a biological sample. Metabolomics has the potential to fundamentally change clinical chemistry and, by extension, the fields of nutrition, toxicology, and medicine. However, it can be difficult to separate highly polar compounds. Mass spectrometry (MS), in combination with capillary electrophoresis (CE), gas chromatography (GC), or high performance liquid chromatography (HPLC) is the key analytical technique on which emerging "omics" technologies, namely, proteomics, metabolomics, and lipidomics, are based. In this review, we introduce various methods for the separation of highly polar metabolites.