Defining Blood Plasma and Serum Metabolome by GC-MS.
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ABSTRACT:
SUBMITTER: Kiseleva O
PROVIDER: S-EPMC8779220 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundEarly diagnosis of hypoxic-ischaemic encephalopathy (HIE) is crucial in preventing neurodevelopmental disabilities and reducing morbidity and mortality. The study was to investigate the plasma metabolic signatures in the peripheral blood of HIE newborns and explore the potential diagnostic biomarkers.MethodIn the present study, 24 newborns with HIE and 24 healthy controls were recruited. The plasma metabolites were measured by gas chromatography-mass spectrometry (GC-MS), and the raw data was standardized by the EigenMS method. Significantly differential metabolites were identified by multivariate statistics. Pathway enrichment was performed by bioinformatics analysis. Meanwhile, the diagnostic value of candidate biomarkers was evaluated.ResultThe multivariate statistical models showed a robust capacity to distinguish the HIE cases from the controls. 52 metabolites were completely annotated. 331 significantly changed pathways were enriched based on seven databases, including 33 overlapped pathways. Most of them were related to amino acid metabolism, energy metabolism, neurotransmitter biosynthesis, pyrimidine metabolism, the regulation of HIF by oxygen, and GPCR downstream signaling. 14 candidate metabolites showed great diagnostic potential on HIE. Among them, alpha-ketoglutaric acid has the potential to assess the severity of HIE in particular.ConclusionThe blood plasma metabolic profile could comprehensively reflect the metabolic disorders of the whole body under hypoxia-ischaemic injury. Several candidate metabolites may serve as promising biomarkers for the early diagnosis of HIE. Further validation based on large clinical samples and the establishment of guidelines for the clinical application of mass spectrometry data standardization methods are imperative in the future.
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Project description:We compared the performance of gas chromatography time-of-flight mass spectrometry (GC-MS) and comprehensive two-dimensional gas chromatography mass spectrometry (GC×GC-MS) for metabolite biomarker discovery. Metabolite extracts from 109 human serum samples were analyzed on both platforms with a pooled serum sample analyzed after every 9 biological samples for the purpose of quality control (QC). The experimental data derived from the pooled QC samples showed that the GC×GC-MS platform detected about three times as many peaks as the GC-MS platform at a signal-to-noise ratio SNR ? 50, and three times the number of metabolites were identified by mass spectrum matching with a spectral similarity score Rsim ? 600. Twenty-three metabolites had statistically significant abundance changes between the patient samples and the control samples in the GC-MS data set while 34 metabolites in the GC×GC-MS data set showed statistically significant differences. Among these two groups of metabolite biomarkers, nine metabolites were detected in both the GC-MS and GC×GC-MS data sets with the same direction and similar magnitude of abundance changes between the control and patient sample groups. Manual verification indicated that the difference in the number of the biomarkers discovered using these two platforms was mainly due to the limited resolution of chromatographic peaks by the GC-MS platform, which can result in severe peak overlap making subsequent spectrum deconvolution for metabolite identification and quantification difficult.
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Project description:Phenotyping of 1,200 'healthy' adults from the UK has been performed through the investigation of diverse classes of hydrophilic and lipophilic metabolites present in serum by applying a series of chromatography-mass spectrometry platforms. These data were made robust to instrumental drift by numerical correction; this was prerequisite to allow detection of subtle metabolic differences. The variation in observed metabolite relative concentrations between the 1,200 subjects ranged from less than 5 % to more than 200 %. Variations in metabolites could be related to differences in gender, age, BMI, blood pressure, and smoking. Investigations suggest that a sample size of 600 subjects is both necessary and sufficient for robust analysis of these data. Overall, this is a large scale and non-targeted chromatographic MS-based metabolomics study, using samples from over 1,000 individuals, to provide a comprehensive measurement of their serum metabolomes. This work provides an important baseline or reference dataset for understanding the 'normal' relative concentrations and variation in the human serum metabolome. These may be related to our increasing knowledge of the human metabolic network map. Information on the Husermet study is available at http://www.husermet.org/. Importantly, all of the data are made freely available at MetaboLights (http://www.ebi.ac.uk/metabolights/).
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Project description:BackgroundWhole-blood concentrations of Delta(9)-tetrahydrocannabinol (THC), 11-hydroxy-THC (11-OH-THC), and 11-nor-9-carboxy-THC (THCCOOH) are approximately half of those in plasma due to high plasma protein binding and poor cannabinoid distribution into erythrocytes. Whole blood is frequently the only specimen available in forensic investigations; controlled cannabinoid administration studies provide scientific data for interpretation of cannabinoid tests but usually report plasma concentrations. Whole-blood/plasma cannabinoid ratios from simultaneously collected authentic specimens are rarely reported.MethodsWe collected whole blood for 7 days from 32 individuals residing on a closed research unit. Part of the whole blood was processed to obtain plasma, and the whole blood and plasma were stored at -20 degrees C until analysis by validated 2-dimensional GC-MS methods.ResultsWe measured whole-blood/plasma cannabinoid ratios in 187 specimen pairs. Median (interquartile range) whole-blood/plasma ratios were 0.39 (0.28-0.48) for THC (n = 75), 0.56 (0.43-0.73) for 11-OH-THC (n = 17), and 0.37 (0.24-0.56) for THCCOOH (n = 187). Intrasubject variability was determined for the first time: 18.1%-56.6% CV (THC) and 10.8%-38.2% CV (THCCOOH). The mean whole-blood/plasma THC ratio was significantly lower than the THCCOOH ratio (P = 0.0001; 4 participants' mean THCCOOH ratios were >0.8).ConclusionsIntra- and intersubject whole-blood/plasma THC and THCCOOH ratios will aid interpretation of whole-blood cannabinoid data.
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