Variability Analysis of Human Plasma and Cerebral Spinal Fluid Reveals Statistical Significance of Changes in Mass Spectrometry-Based Metabolomics Data

Abstract

Analytical and biological variability are issues of central importance to human metabolomics studies. Here both types of variation are examined in human plasma and cerebrospinal fluid (CSF) using a global liquid chromatography-mass spectrometry (LC/MS) metabolomics strategy. The platform shows small analytical variation with a median coefficient of variation (CV) of 15–16% for both plasma and CSF sample matrices when the integrated area of each peak in the mass spectra is considered. Analysis of biological variation shows that human CSF has a median CV of 35% and plasma has a median CV of 46%. To understand the difference in CV between the biofluids, we compared plasma and CSF independently obtained from different healthy humans. Additionally, we analyzed another group of patients from whom we compared matched CSF and plasma (plasma and CSF obtained from the same human subject). A similar number of features was observed in both biofluids, although the majority of features appeared with greater intensity in plasma. More than a dozen metabolites shared between the human CSF and plasma metabolomes were identified based on accurate mass measurements, retention times, and MS/MS spectra. The fold change in these metabolites was consistent with the median biological CV determined for all peaks. The measured median biological CV together with analysis of intra-group variation of healthy individuals suggests that fold changes above 2 in metabolomics studies investigating plasma or CSF are statistically relevant with respect to the inherent variability of a healthy control group. These data demonstrate the reproducibility of the global metabolomics platform using LC/MS and reveal the robustness of the approach for biomarker discovery.

Cross-Platform Comparison of Caenorhabditis elegans Tissue Extraction Strategies for Comprehensive Metabolome Coverage

“…GC-MS and UPLC-MS both showed a median repeated injection (RI) and quality control sample (QC) variability of 5 % and 10 %, respectively. For GC-MS, we could not find any published data on distributions of CV for repeated injection (instrument) variation to compare to, but for LC-MS data our median CV is lower than reported values 45,46 . This might be due to fewer replicates or our minimum quantification criterion (5 out of 5 detected features).…”

Qualitative Metabolome Analysis of Human Cerebrospinal Fluid by13C-/12C-Isotope Dansylation Labeling Combined with Liquid Chromatography Fourier Transform Ion Cyclotron Resonance Mass Spectrometry

“…The purity and confirmation of 13 C-dansyl chloride was tested against the commercial 12 C-dansyl chloride using LC-FTICR MS and LC-UV. The purity of 13 C-dansyl chloride is over 99% based on the LC-MS and LC-UV results.…”

“…Figure 1 shows the work flow for generating a qualitative metabolome profile from a CSF sample. Briefly, a sample is divided into two equal aliquots, one labeled with the heavy or 13 C-dansyl-chloride reagent and another one labeled with the light or 12 C-reagent. The labeled aliquots are mixed and then injected into LC-FTICR MS for analysis.…”

“…Among them, only about 75 metabolites were reported to have concentrations of above 1 μM. Analyzing metabolites in CSF is mostly done by using NMR [6][7][8][9][10], GC-MS [10,11], and LC-MS [10,[12][13][14]. In a report that compares different techniques for human CSF metabolome analysis [5], it was shown that the NMR technique could positively identify about 53 metabolites, GC-MS could identify 41 metabolites and LC-MS using Fourier-transfom ion cyclotron resonance (FTICR) MS could identify 17 metabolites.…”

“…For example, 23 metabolites of neurotransmitters were analyzed using MRM MS/MS [15]. However, there are only a few reports of untargeted metabolome analysis of CSF by LC-MS [12][13][14][16][17][18][19]. Because of low abundance of metabolites present in CSF, less than 5000 features could be detected from LC-MS and many of the features were likely from non-metabolite signals.…”