Thermo finnigan trace dsq fast scanning single quadrupole mass spectrometer

The first experiment was completed using the first set of samples (N = 48) (referred to as “batch 1”).
Metabolite extraction and detection as previously described (10 (link)). Briefly, liver sample preparation was conducted using a proprietary series of organic and aqueous extractions to remove the protein fraction and optimize recovery of small molecules through the automated MicroLab STAR® system (Hamilton Company, UT, USA), centrifuged, and the resulting supernatants were analyzed by analyzed by ultra-performance liquid chromatography mass spectrometry (UPLC-MS/MS) in a positive and negative ion mode (UPLC: Waters, Milford, MA; mass spectrometer: Thermo-Finnigan LTQ, Thermo Fisher Scientific, Waltham, MA, scan range, 80–1,000 m/z) and by GC-MS (Thermo-Finnigan Trace DSQ fast-scanning single-quadrupole mass spectrometer, scan range 50–750 m/z). The final experiment 1 metabolomic dataset comprised a total of 751 biochemicals, 478 compounds of known identity (named biochemicals) and 273 compounds of unknown structural identity. As initial statistical analysis revealed an age-dependent effect that could not be distinguished from a tissue source-related effect, a replication set of group 1 samples was obtained through collaboration with the Erasmus Medical Center/Sophia Children's Hospital.

Targeted metabolomic analysis of 459 named biochemicals in 100 µL aliquots of AF was performed by Metabolon Inc., (Durham, NC, USA). Analytes were extracted and prepared using a standard solvent extraction method [48 (link)]. The extracted samples were split into equal parts for analysis on complementary gas chromatography (GC) (mass spectrometry (MS) (Thermo-Finnigan Trace DSQ fast-scanning single-quadrupole mass spectrometer (Thermo Scientific, Waltham, Mass, USA), and liquid chromatography (LC)/MS platforms (Waters ACQUITY ultra-performance liquid chromatography (UPLC) (Waters Corp, Milford, Mass, USA) and a Thermo Scientific Q-Exactive high resolution/accurate mass spectrometer (Thermo Scientific, Waltham, Mass, USA) [48 (link)]. Welch’s unequal variances two-sample t-test, and ANOVA, were used to identify biochemicals that differed significantly between groups. Two-way ANOVA was used to identify biochemicals exhibiting significant interaction and main effects of GDM. FDR was used to account for multiple comparisons [49 ,50 (link)]. Principal component analysis, and unbiased and supervised classification analysis using a random forest (RF), were performed [49 ]. Please see Supplementary Methods for additional details.