Metabolic Profiling of the Cerebrospinal Fluid in Pediatric Epilepsy

To characterize metabolic profiles within the central nervous system in epilepsy, we performed gas chromatography-tandem mass spectrometry (GC-MS/MS)-based metabolome analysis of the cerebrospinal fluid (CSF) in pediatric patients with and without epilepsy. The CSF samples obtained from 64 patients were analyzed by GC-MS/MS. Multivariate analyses were performed for two age groups, 0-5 years of age and 6-17 years of age, to elucidate the effects of epilepsy and antiepileptic drugs on the metabolites. In patients aged 0-5 years (22 patients with epilepsy, 13 without epilepsy), epilepsy patients had reduced 2-ketoglutaric acid and elevated pyridoxamine and tyrosine. In patients aged 6-17 years (12 with epilepsy, 17 without epilepsy), epilepsy patients had reduced 1,5-anhydroglucitol. Valproic acid was associated with elevated 2-aminobutyric acid, 2-ketoisocaproic acid, 4-hydroxyproline, acetylglycine, methionine, N-acetylserine, and serine. Reduced energy metabolism and alteration of vitamin B6 metabolism may play a role in epilepsy in young children. The roles of 1,5-anhydroglucitol in epilepsy in older children and in levetiracetam and zonisamide treatment remain to be explained. Valproic acid influenced the levels of amino acids and related metabolites involved in the metabolism of serine, methionine, and leucine

Comparison of Kit-Based Metabolomics with Other Methodologies in a Large Cohort, towards Establishing Reference Values

Metabolic profiling is an omics approach that can be used to observe phenotypic changes, making it particularly attractive for biomarker discovery. Although several candidate metabolites biomarkers for disease expression have been identified in recent clinical studies, the reference values of healthy subjects have not been established. In particular, the accuracy of concentrations measured by mass spectrometry (MS) is unclear. Therefore, comprehensive metabolic profiling in large-scale cohorts by MS to create a database with reference ranges is essential for evaluating the quality of the discovered biomarkers. In this study, we tested 8700 plasma samples by commercial kit-based metabolomics and separated them into two groups of 6159 and 2541 analyses based on the different ultra-high-performance tandem mass spectrometry (UHPLC-MS/MS) systems. We evaluated the quality of the quantified values of the detected metabolites from the reference materials in the group of 2541 compared with the quantified values from other platforms, such as nuclear magnetic resonance (NMR), supercritical fluid chromatography tandem mass spectrometry (SFC-MS/MS) and UHPLC-Fourier transform mass spectrometry (FTMS). The values of the amino acids were highly correlated with the NMR results, and lipid species such as phosphatidylcholines and ceramides showed good correlation, while the values of triglycerides and cholesterol esters correlated less to the lipidomics analyses performed using SFC-MS/MS and UHPLC-FTMS. The evaluation of the quantified values by MS-based techniques is essential for metabolic profiling in a large-scale cohort

Identification of novel biomarkers of hepatocellular carcinoma by high‐definition mass spectrometry: Ultrahigh‐performance liquid chromatography quadrupole time‐of‐flight mass spectrometry and desorption electrospray ionization mass spectrometry imaging

RATIONALE:Hepatocellular carcinoma (HCC) is a highly malignant disease for which the development of prospective or prognostic biomarkers is urgently required. Although metabolomics is widely used for biomarker discovery, there are some bottlenecks regarding the comprehensiveness of detected features, reproducibility of methods, and identification of metabolites. In addition, information on localization of metabolites in tumor tissue is needed for functional analysis. Here, we developed a wide-polarity global metabolomics (G-Met) method, identified HCC biomarkers in human liver samples by high-definition mass spectrometry (HDMS), and demonstrated localization in cryosections using desorption electrospray ionization MS imaging (DESI-MSI) analysis. METHODS:Metabolic profiling of tumor (n = 38) and nontumor (n = 72) regions in human livers of HCC was performed by an ultrahigh-performance liquid chromatography quadrupole time-of-flight MS (UHPLC/QTOFMS) instrument equipped with a mixed-mode column. The HCC biomarker candidates were extracted by multivariate analyses and identified by matching values of the collision cross section and their fragment ions on the mass spectra obtained by HDMS. Cryosections of HCC livers, which included both tumor and nontumor regions, were analyzed by DESI-MSI. RESULTS:From the multivariate analysis, m/z 904.83 and m/z 874.79 were significantly high and low, respectively, in tumor samples and were identified as triglyceride (TG) 16:0/18:1(9Z)/20:1(11Z) and TG 16:0/18:1(9Z)/18:2(9Z,12Z) using the synthetic compounds. The TGs were clearly localized in the tumor or nontumor areas of the cryosection. CONCLUSIONS:Novel biomarkers for HCC were identified by a comprehensive and reproducible G-Met method with HDMS using a mixed-mode column. The combination analysis of UHPLC/QTOFMS and DESI-MSI revealed that the different molecular species of TGs were associated with tumor distribution and were useful for characterizing the progression of tumor cells and discovering prospective biomarkers