Nontarget metabolomics profiling of neuromyelitis optica spectrum disorder

Abstract

To investigate the characteristic of neuromyelitis optica spectrum disorder (NMOSD) in plasma and cerebrospinal fluid, UHPLC–MS was used to identify metabolites by metabolite extraction and on‐machine detection. Multivariate analysis methods were used to complete differential metabolite screening and metabolic pathway analysis. The content of eight substances, such as tryptophan and l‐glutamic acid in the plasma of NMOSD patients, was higher than that of the healthy control group. Moreover, no differential metabolite was found in the plasma of patients with AQP‐4 antibody‐positive and antibody‐negative NMOSD. The content of five substances including 3‐hydroxybutyric acid in cerebrospinal fluid of patients with NMOSD was reduced. We demonstrated that the distribution of metabolites in plasma between NMOSD patients and healthy counterparts was significantly different. However, there is no significant difference in plasma metabolites between AQP‐4 antibody positive and negative NMOSD. There were some differences in metabolites between the cerebrospinal fluid of NMOSD patients and that of healthy controls. A variety of amino‐acid abnormalities, sphingomyelin dysfunction, energy metabolism and mitochondrial dysfunction are involved in the pathogenesis of NMOSD.

Tissue-based metabolomics profiling reveals metabolic signatures and major metabolic pathways of gastric cancer

“…As an unsupervised pattern recognition method, PCA shows distribution of origin data and general separation and OPLS-DA was used to obtain maximal covariance between variables and sample category in both positive and negative models. 7-Fold cross-validation and 200 permutation tests were used to estimate the robustness and the predictive ability of our mode (Deng et al 2019).…”

Compositional Differences between Preterm Milk of Different Gestational Ages with the Term Milk: A Comparative Lipidomic Study by LC‐MS/MS

“…The electrospray ionization (ESI) source conditions were as follows: sheath gas flow rate 30 Arb, Aux gas flow rate 10 Arb, capillary temperature 320 °C (positive) and 300 °C (negative), full MS resolution 70000, MS/MS resolution 17500, collision energy 15/30/45 in NCE mode, spray voltage 5 kV (positive) or −4.5 kV (negative). [24,25] At the beginning of the operation, the pooled "QC" sample was analyzed to ensure system equilibration, and this calibration was repeated every ten test samples to further monitor the stability of the analysis. Blank samples containing only sample solvent were also analyzed randomly between samples to allow for chromatographic carryover analysis.…”

“…The VIP scores ranked the components according to their role in the observed separation. [25,26] To prevent false-positive errors in OPLS-DA, the Student's t-test was also used, with p < 0.05 signifying significance between each preterm group and its term counterpart.…”

Compositional differences between preterm milk of different gestational ages with the term milk: a comparative lipidomic study by LC-MS/MS

“…In this mode, the acquisition software continuously evaluates the full-scan MS spectrum. The ESI source conditions were as follows: sheath gas ow rate 30 Arb, Aux gas ow rate 10 Arb, capillary temperature 320 ℃ (positive) and 300 ℃ (negative), full MS resolution 70000, MS/MS resolution 17500, collision energy 15/30/45 in NCE mode, spray voltage 5 kV (positive) or -4.5 kV (negative) [23,24].…”

“…The coe cient loading plots and variable importance in projection (VIP) of the OPLS-DA model were employed for identifying the spectral variables related to sample dissolution. The VIP scores ranked the components according to their role in the observed separation [24,25]. Statistical distinctness was established using Student's t-test, with P < 0.05 signifying signi cance.…”