Summary of Study ST001386

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 PR000950. The data can be accessed directly via it's Project DOI: 10.21228/M8WM4P This work is supported by NIH grant, U2C- DK119886.

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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 IDST001386
Study TitleTEDDY Metabolomics Study
Study SummaryPrimary metabolites were quantified in human plasma from the 1:3 matched TEDDY case-control subjects. Information on the nested case-control study design can found in: Biomarker discovery study design for type 1 diabetes in The Environmental Determinants of Diabetes in the Young (TEDDY) study. Lee HS, Burkhardt B, McLeod W, Smith S, Eberhard C, Lynch K, Hadley D, Rewers M, Simell O, She JX, Hagopian W, Lernmark A, Akolkar B, Ziegler AG, Krischer J, and the TEDDY Study Group. Diabetes/Metabolism Research and Reviews. Epub 2013 December 15. doi: 10.1002/dmrr.2510 (PubMed ID: 24339168). Primary metabolites were extracted from 30 µl plasma aliquots by adding 1 ml of a carefully degassed -20 °C cold isopropanol/acetonitrile/water mixture (3:3:2, v/v/v) for 5 min at 4 °C which simultaneously precipitates proteins. After centrifugation, half of the extract was dried and cleaned up from triglycerides by a 50% acetonitrile mixture. After drying, internal standards were added as C08-C30 fatty acid methyl esters in chloroform as retention index markers (Kind et. al, 2009). Primary metabolites were derivatized by methoximation and trimethylsilylation. Primary metabolites were analyzed by cold injection/automatic liner exchange gas chromatography time-of- flight mass spectrometry (CIS/ALEX GC-TOF MS) (Fiehn et. al, 2008). In order to limit buildup of involatile material in the GC system and to prevent any carry over, an automatic liner exchange with multi-baffled liners and cold injection procedures was used instead of classic hot injections into standard s/sl liners. Multi-baffled inert glass liners were used because classic glass wool liners might hamper derivatization of amino groups for amino acid analysis. Robotic derivatization was further used to control reaction times (Ji et. al, 2011); and GC-columns were employed with integrated 10 meter guard columns, which could cut multiple times in 10 cm increments whenever quality control samples determined out-of-control situations. A temperature of 280 °C was determined to be the optimum transfer line temperature at which even higher-boiling compounds did not show tailing effects and at which the electron ionization filaments could still be operated at their optimal temperature of 250 °C and -70 eV. The mass spectrometer was operated using daily mass calibration auto-tuning using FC43 (perfluorotributyl-amine) and acquired 17 spectra per second and 1850-1950 V detector voltage. This high spectral acquisition rate was necessary to obtain enough data for mass spectral deconvolution of co-eluting compounds. Under these conditions, the system was around 10-times more sensitive than classic quadrupole GC-MS instruments and also clearly outperformed GC-triple quadrupole mass spectrometers. For select compounds, even lower limits of detection were achieved than for optimized MRM conditions in UPLC-QTRAP MS analysis. Around 144 unique metabolites were detectable in blood plasma (Fiehn & Kind, 2007); in addition to 221 unidentified compounds that were captured in the BinBase database system and hence, were comparable across studies. References: 1) Kind T, Wohlgemuth G, Lee DY, Lu Y, Palazoglu M, Shahbaz S, Fiehn O: FiehnLib: mass spectral and retention index libraries for metabolomics based on quadrupole and time-of-flight gas chromatography/mass spectrometry. Anal Chem 2009, 81(24):10038-10048. 2) Fiehn O, Wohlgemuth G, Scholz M, Kind T, Lee DY, Lu Y, Moon S, Nikolau B: Quality control for plant metabolomics: reporting MSI-compliant studies. Plant J 2008, 53(4):691-704. 3) Ji Y, Hebbring S, Zhu H, Jenkins GD, Biernacka J, Snyder K, Drews M, Fiehn O, Zeng Z, Schaid D et al: Glycine and a glycine dehydrogenase (GLDC) SNP as citalopram/escitalopram response biomarkers in depression: pharmacometabolomics-informed pharmacogenomics. Clin Pharmacol Ther 2011, 89(1):97-104. 4) Fiehn O, Kind T: Metabolite profiling in blood plasma. Methods Mol Biol 2007, 358:3-17. An explanation of the study design variables are explained in detail in a data dictionary provided in the raw data download section.
Institute
University of South Florida
LaboratoryUC Davis Genome Center
Last NameKrischer
First NameJeffrey
Address3650 Spectrum Blvd, Tampa, FL 33612
EmailTEDDYDataPlatform@epi.usf.edu
Phone8133969512
Submit Date2017-05-19
Publicationsdoi: 10.2337/db19-0756. Epub 2020 Feb 6. Longitudinal Metabolome-Wide Signals Prior to the Appearance of a First Islet Autoantibody in Children Participating in the TEDDY Study
Raw Data File Type(s)cdf
Analysis Type DetailGC-MS
Release Date2020-06-30
Release Version1
Jeffrey Krischer Jeffrey Krischer
https://dx.doi.org/10.21228/M8WM4P
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

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Factors:

Subject type: Human; Subject species: Homo sapiens (Factor headings shown in green)

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