Summary of Study ST000911

This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR000631. The data can be accessed directly via it's Project DOI: 10.21228/M83T1G This work is supported by NIH grant, U2C- DK119886.

See: https://www.metabolomicsworkbench.org/about/howtocite.php

This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.

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Study IDST000911
Study TitleInsights into the pathogenesis of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) through metabolomic profiling of cerebrospinal fluid (part II)
Study SummaryMyalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a disabling illness characterized by six months or more of unexplained profound fatigue with post-exertional malaise, sleep abnormalities, cognitive dysfunction and autonomic disturbances. Focusing on the pathogenesis of central nervous system abnormalities in ME/CFS, we pursued metabolomics analysis of cerebrospinal fluid (CSF) in 32 ME/CFS cases, 40 subjects with multiple sclerosis (MS), another fatiguing illness, and 19 healthy subjects with no neurological disease (ND). MS/ND subjects were frequency matched for age and sex to ME/CFS subjects. Three untargeted metabolomic assays for primary metabolites, biogenic amines and complex lipids were performed with gas chromatography time-of-flight (GC-TOF) and liquid chromatography–tandem mass spectrometry (LC-MS/MS) yielding profiles for 525 known metabolites. Mannose was a cardinal biomarker in ME/CFS subjects with reduced levels in ME/CFS compared to both MS and ND subjects. Levels of acetylcarnitine were reduced in ME/CFS vs. MS subjects. The predictive power of metabolomic analysis for diagnosis of ME/CFS vs. ND was higher (cross-validated AUC 0.875; 95% CI: 0.726~0.949) than with cytokine analysis alone (cross-validated AUC 0.865; 95% CI: 0.673~0.952) and improved with integration of both metabolomics and cytokine analyses (cross-validated AUC 0.916; 95% CI: 0.791~0.969). Our findings confirm the biological basis of ME/CFS, and may enable new methods for diagnosis and insight into cognitive and autonomic disturbances in this syndrome.
Institute
University of California, Davis
DepartmentGenome and Biomedical Sciences Facility
LaboratoryWCMC Metabolomics Core
Last NameFiehn
First NameOliver
Address1315 Genome and Biomedical Sciences Facility, 451 Health Sciences Drive, Davis, CA 95616
Emailofiehn@ucdavis.edu
Phone(530) 754-8258
Submit Date2017-12-11
Raw Data AvailableYes
Raw Data File Type(s)d
Analysis Type DetailLC-MS
Release Date2018-08-27
Release Version1
Oliver Fiehn Oliver Fiehn
https://dx.doi.org/10.21228/M83T1G
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

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Sample Preparation:

Sampleprep ID:SP000956
Sampleprep Summary:1) Thaw each 100 μL CSF aliquot at room temperature (see Aliquoting TEDDY samples SOP). Once thawed (~10min) place CSF plasma samples on ice. 2) Add 225 μL cold “MeOH with QC mix” (see SOP “QC mix for LC-MS lipid analysis”). Keep MeOH on ice during extraction 3) Vortex each sample for 10s, keeping the rest on ice during all the extraction. 4) Add 750 μL of cold MTBE with 22:1 CE, keep MTBE on ice during extraction 5) Vortex for 10s 6) Shake for 6min at 4°C in the orbital mixer. 7) Add 188 μL room temperature LC/MS grade water. 8) Vortex for 20 s 9) Centrifuge for 2 min @ 14,000 rcf (12300 rpm) 10) Remove supernatant (upper phase), splitting into two aliquots of 300 μL, keeping one at –20°C for backup 11) Dry samples to complete dryness in the speed vacuum concentration system
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