Stability of Phosphatidylethanol 16:0/18:1 in Freshly Drawn, Authentic Samples from Healthy Volunteers

Due to its specificity, phosphatidylethanol (PEth) 16:0/18:1 has gained increased popularity as a marker for high alcohol consumption in recent years. As conflicting results regarding the stability of PEth 16:0/18:1 in whole blood have been published, there are still uncertainties related to optimum handling, transport and storage of blood samples for the analysis of PEth 16:0/18:1. A stability study where whole blood samples were drawn from healthy volunteers, who had ingested alcohol, is presented. The samples were collected in tubes with ethylenediamine tetraacetic acid (EDTA) and heparin as additives and stored under standardized conditions within 1 h of blood sampling. Storage times were 28 days in ambient temperature and at 4–8°C, and 90 days at −20°C and −80°C. All samples were analyzed regularly during the storage periods. PEth 16:0/18:1 concentrations were stable (defined as < 15% decrease compared with baseline values) at all temperatures up to 28 days, independent of additive. After 90 days of storage at −20°C, the mean concentrations had decreased by 18.8% in EDTA tubes and by 13.8% in heparin tubes. At −80°C, the concentrations were stable throughout the 90-day period. The present study shows that in samples containing PEth formed in vivo, PEth 16:0/18:1 is stable for 28 days irrespective of storage temperature. During long-term storage, samples should be stored at −80°C

Hight throughput UHPC-MSMS method for the analysis of phosphatidylethanol (PEth) 16:0/18:1, a specific biomarker for alcohol consumption, in whole blood

Phosphatidylethanol (PEth) is an alcohol biomarker formed in the presence of ethanol in the body. Both due to its specificity and because it has a detection window of up to several weeks after alcohol intake, its application potential is broader than for other ethanol biomarkers. The aim of this study was to develop and validate a robust method for PEth in whole blood with fast and efficient sample extraction and a short analytical runtime, suitable for high throughput routine purposes. A validated ultra-performance liquid chromatography tandem mass spectrometry (UPLC®-MSMS) method for quantification of PEth 16:0/18:1 in the range 0.05–4.00 μM (R2 ≥ 0.999) is presented. PEth 16:0/18:1 and the internal standard (IS) PEth-d5 (0.55 μM), were extracted from whole blood (150 μL) by simple protein precipitation with 2-propanol (450 μL). Chromatography was achieved using a BEH-phenyl (2.1 × 30 mm, 1.7 μm) column and a gradient elution combining ammonium formate (5 mM, pH 10.1) and acetonitrile at a flow rate of 0.5 mL/min. Runtime was 2.3 min. The mass spectrometer was monitored in negative mode with multiple reaction monitoring (MRM). The m/z 701.7 > 255.2 and 701.7 > 281.3 transitions were monitored for PEth 16:0/18:1 and the m/z 706.7 > 255.3 for PEth-d5. Limit of quantification was 0.03 μM (coefficient of variation, CV = 6.7%, accuracy = 99.3%). Within-assay and between-assay imprecision were 0.4–3.3% (CV ≤ 7.1%). Recoveries were 95–102% (CV ≤ 4.9%). Matrix effects after IS correction ranged from 107% to 112%. PEth 16:0/18:1 in patient samples were stable for several days at 30°C. Repeated freezing (−80°C) and thawing did not affect the concentration. After thawing and analysis patient samples were stable at 4–8°C for at least 4 weeks. Results from a proficiency test program, showing |Z| values ≤1.2, confirm the validity of the method. Analysis of the first 3,169 samples sent to our laboratory for routine use has demonstrated its properties as a robust method suitable for high throughput purposes

Metabolomic biomarkers in serum and urine in women with preeclampsia.

To explore the potential of magnetic resonance (MR) metabolomics for study of preeclampsia, for improved phenotyping and elucidating potential clues to etiology and pathogenesis.Urine and serum samples from pregnant women with preeclampsia (n = 10), normal pregnancies (n = 10) and non-pregnant women (n = 10) matched by age and gestational age were analyzed with MR spectroscopy and subjected to multivariate analysis. Metabolites were then quantified and compared between groups.Urine and serum samples revealed clear differences between women with preeclampsia and both control groups (normal pregnant and non-pregnant women). Nine urine metabolites were significantly different between preeclampsia and the normal pregnant group. Urine samples from women with early onset preeclampsia clustered together in the multivariate analysis. The preeclampsia serum spectra showed higher levels of low and very-low density lipoproteins and lower levels of high-density lipoproteins when compared to both non-pregnant and normal pregnant women.The MR determined metabolic profiles in urine and serum from women with preeclampsia are clearly different from normal pregnant women. The observed differences represent a potential to examine mechanisms underlying different preeclampsia phenotypes in urine and serum samples in larger studies. In addition, similarities between preeclampsia and cardiovascular disease in metabolomics are demonstrated

Results from serum analysis.

<p>Results from Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA) on the spectra of serum samples from women with preeclampsia (PE), pregnant controls (PC) and non-pregnant controls (NP). ppm: parts per million, resonance frequency of metabolite. <b>A</b>) Typical highly resolved serum CPMG (lipids suppressed) and LEDBPG (small metabolites suppressed) spectra from a woman with PE with some annotated metabolites. <b>B</b>) Scores plot and loading profile of the PCA separating CPMG spectra of the three groups. <b>C</b>) Scores plot and Loading Variable (LV) 1 from the PLS-DA of CPMG spectra showing class discrimination based on lipid level, where women with PE clearly have higher levels of total lipids in the serum compared to pregnant controls <b>D</b>) Score plot and LV1 of the LEDBPG showing distinction between PE and PC groups based on lipoprotein distribution. LV1 shows higher levels of VLDL-LDL and lower levels of HDL. VLDL: very low density lipoproteins. LDL: low density lipoproteins. HDL: high density lipoproteins.</p

Serum metabolite concentrations.

<p><i>Values given as mean±SD. PE: Women with preeclampsia. PC: Pregnant controls. NP: Non-pregnant controls.</i></p><p><i>*Significantly different metabolite concentration between PE and PC with a cutoff value at p = 0.05 after Benjamini-Hochberg correction using the Kruskal-Wallis test for nonparametric distributions of concentrations for three independent groups.</i></p>†<p><i>Significantly different metabolite concentration between PC and NP.</i></p

Characteristics of study participants.

<p><i>Values are given as median (min-max). PE: Women with preeclampsia. PC: Pregnant controls. NP: Non-pregnant controls. GA: Gestational age. BP: Blood pressure. Dia: Diastolic. Sys: Systolic. N/A: Not applicable. Statistical p-values computed by Kruskal-Wallis independent samples test.</i></p>a<p><i>Proteinuria measured with dipstick.</i></p

PLS-DA Classification of samples as healthy pregnant or from women with preeclampsia.

<p>The sensitivity is for detecting a preeclampsia sample using Partial Least Squares Discriminant Analysis. Classification accuracy, sensitivity and specificity are from the leave-one-out cross validation. The p-value is from permutation testing the model with 1000 repeats. LVs: number of loading variables in model. AUC: Area under the Receiver Operator Characteristic curve. CPMG: Lipid-suppressed. LEDBPG: Low molecular weight metabolite suppressed.</p

Urine metabolite concentrations.

<p><i>Values given as mean [metabolite/creatinine]±sample standard deviation. PE: Women with preeclampsia. PC: Pregnant controls. NP: Non-pregnant controls. TMAO: Trimethylamine-N-Oxide.</i></p>a<p><i>As suggested by Chenomx, may instead be phenylacetylglutamine.</i></p>b<p><i>Absolute creatinine concentration – not corrected for dilution.</i></p><p><i>*Significantly different metabolite concentration between PE and PC with a cutoff value at p = 0.05 after Benjamini-Hochberg correction using the Kruskal-Wallis test for nonparametric distributions of concentrations for three independent groups.</i></p>†<p><i>Significantly different metabolite concentration between PC and NP.</i></p

Results from urine analysis.

<p>Results from Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA) of urine samples from women with preeclampsia (PE, pregnant controls (PC) and non-pregnant controls (NP). <b>A</b>) Typical high resolution NMR spectrum of urine from a PE subject, most abundant metabolites annotated. <b>B</b>) PCA score plot separating all three groups in two dimensions. <b>C</b>) Loading Variables (LV) 1 and 2 of the PLS-DA used to create a model discriminating between PE and PC groups. Arrow direction indicates increased metabolite level. <b>D</b>) Scores on LV1 and LV2 showing a clustering of early onset PE samples (marked by arrows). TMAO: Trimethylamine-N-Oxide.</p