Glycerophospholipids

Glycerolipid and glycerophospholipid structures were used as the basis for the generation of a hierarchy of analytical outputs from mass spectrometry experiments (Liebisch et al., 2013 (link)). The lipid hierarchy was generated using custom software that takes as input a set of structures and a template file that specifies the required annotations for each of the corresponding higher levels and the relations that link them (Table 1). These annotations include lipid nomenclature and human readable descriptions, ChEBI identifiers for lipid parent classes and parent components, SMILES representations, formula, mass and m/z values for adducts, and InChI and InChI keys where applicable.
Table 1.

The hierarchical classification used in SwissLipids

Level	Example
Category	Glycerophospholipid
Class	Glycerophosphocholine
Class	Monoalkylmonoacylglycerophosphocholine
Species	PC(O-36:5)
Molecular subspecies	PC(O-16:1_20:4)
Structural subspecies	PC(P-16:0/20:4)
Isomeric subspecies	PC(P-16:0/20:4(5Z,8Z,11Z,14Z))

The hierarchy includes seven levels that are illustrated below with a single example. The hierarchy is compatible with that of LipidHome (Foster et al., 2013 (link)) but uses only known components in the generation of the base Isomeric subspecies. The hierarchy is fully mapped to ChEBI at all levels. The prefix ‘O−’ indicates an alkyl bond, the prefix ‘P−’ a 1Z-alkenyl bond and the absence of a prefix an ester bond. PC, phosphatidylcholine.

Serum samples were analysed using a combination of direct injection mass spectrometry with a reverse-phase liquid chromatography (LC)-MS/MS custom assay, in combination with an ABSciex 4000 QTrap (Applied Biosystems/MDS SCIEX, Macclesfield, UK) mass spectrometer [29 (link),30 (link)]. The method combines the derivatization and extraction of analytes, as well as the selective mass-spectrometric detection, using multiple reaction monitoring pairs. Isotope-labelled internal standards and other internal standards were used for metabolite quantification. The custom assay contained a 96 deep-well plate with a filter plate attached with sealing tape, and reagents and solvents were used to prepare the plate assay. First, 14 wells were used for 1 blank, 3 zero samples, 7 standards and 3 quality control samples. For all metabolites except organic acids, samples were thawed on ice and then vortexed and centrifuged at 13,000× g. Then, 10 µL of each sample was loaded onto the centre of the filter on the upper 96-well plate and dried in a stream of nitrogen. Subsequently, phenyl-isothiocyanate was added for derivatization. After incubation, the filter spots were dried again using an evaporator. Metabolites were then extracted by adding 300 µL of extraction solvent. The extracts were obtained by centrifugation into the lower 96-deep well plate, followed by a dilution step with MS running solvent.
For organic acid analysis, 150 µL of ice-cold methanol and 10 µL of isotope-labelled internal standard mixture were added to 50 µL of serum sample for overnight protein precipitation and centrifuged at 13,000× g for 20 min. Then, 50 µL of supernatant was loaded into the centre of wells of a 96-deep well plate, followed by the addition of 3-nitrophenylhydrazine reagent. After incubation for 2 h, butylated-hydroxytoluene stabilizer and water were added before LC-MS injection. Mass spectrometric analysis was performed using an ABSciex 4000 Qtrap tandem mass spectrometry instrument (Applied Biosystems/MDS Analytical Technologies, Foster City, CA, USA) equipped with an Agilent 1260 series ultra-high performance-LC system (Agilent Technologies, Palo Alto, CA, USA). The samples were delivered to the mass spectrometer by an LC method followed by a direct injection method. Data analysis was performed using Analyst version 1.6.2 (Applied Biosystems/MDS Analytical Technologies, Foster City, CA, USA). A total of 132 metabolites were quantified, including 39 acylcarnitines, 23 amino acids, 14 biogenic amines, 34 glycerophospholipids, 14 organic acids and 5 other metabolites. A full list of the metabolites measured are included in Table S1.

A total of 186 metabolites in the plasma of 148 participants were measured using AbsoluteIDQ^™ p180 kit (Biocrates Life Sciences AG, Innsbruck, Austria). The data quality of each metabolite was checked based on the following criteria: (1) half of the analyzed metabolite concentrations in the reference standards > limit of detection and (2) half of the analyzed metabolite concentrations in the experimental samples. We excluded 32 metabolites that failed the quality criteria. Finally, a total of 154 metabolites (37 acylcarnitines (ACs), 20 amino acids (AAs), 8 biogenic amines (BAs), 81 glycerophospholipids (GPLs), and 8 sphingolipids (SPLs)) were analyzed with the AbsoluteIDQ™ p180 kit using the protocol described in the AbsoluteIDQ™ p180 user manual. The ACs, GPLs, and SPLs were quantified by flow injection analysis by tandem mass spectrometry using an ABI 4000 Q-Trap mass spectrometer (Applied Biosystems/MDS Sciex, Foster city, CA). The AAs and BAs were quantified by stable isotope dilution in a liquid chromatography-tandem mass spectrometry. The biocrates MetIQ software was used to control the entire assay workflow, from sample registration to the automated calculation of metabolite concentrations to the export of data into other data analysis programs. The metabolite concentration measurements in μmol/L (μM) units were automatically carried out with the MetVal™ software package (Biocrates Life Sciences AG, Innsbruck, Austria).