A Metabolomics Approach to the Identification of Urinary Biomarkers of Pea Intake

Pedapati S C Sri Harsha, Roshaida Abdul Wahab, Catalina Cuparencu, Lars Ove Dragsted, Lorraine Brennan, Pedapati S C Sri Harsha, Roshaida Abdul Wahab, Catalina Cuparencu, Lars Ove Dragsted, Lorraine Brennan

Abstract

A significant body of evidence demonstrates that isoflavone metabolites are good markers of soy intake, while research is lacking on specific markers of other leguminous sources such as peas. In this context, the objective of our current study was to identify biomarkers of pea intake using an untargeted metabolomics approach. A randomized cross-over acute intervention study was conducted on eleven participants who consumed peas and couscous (control food) in random order. The urine samples were collected in fasting state and postprandially at regular intervals and were further analysed by ultra-performance liquid chromatography coupled to quadrupole time of flight mass spectrometry (UPLC-QTOF-MS). Multivariate statistical analysis resulted in robust Partial least squares Discriminant Analysis (PLS-DA) models obtained for comparison of fasting against the postprandial time points (0 h vs. 4 h, (R²X = 0.41, Q² = 0.4); 0 h vs. 6 h, ((R²X = 0.517, Q² = 0.495)). Variables with variable importance of projection (VIP) scores ≥1.5 obtained from the PLS-DA plot were considered discriminant between the two time points. Repeated measures analysis of variance (ANOVA) was performed to identify features with a significant time effect. Assessment of the time course profile revealed that ten features displayed a differential time course following peas consumption compared to the control food. The interesting features were tentatively identified using accurate mass data and confirmed by tandem mass spectrometry (MS using commercial spectral databases and authentic standards. 2-Isopropylmalic acid, asparaginyl valine and N-carbamoyl-2-amino-2-(4-hydroxyphenyl) acetic acid were identified as markers reflecting pea intake. The three markers also increased in a dose-dependent manner in a randomized intervention study and were further confirmed in an independent intervention study. Overall, key validation criteria were met for the successfully identified pea biomarkers. Future work will examine their use in nutritional epidemiology studies.

Keywords: biomarkers; dietary assessment; metabolomics; peas.

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Partial least square discriminant analysis (PLS-DA) of Ultra-Performance Liquid Chromatography coupled to Quadrupole Time of Flight Mass Spectrometry (UPLC-QTOF-MS) urine data of time point 0 (■) and time point 4 h post consumption of peas (□). Q2, 0.4; R2X, 0.41; t [1], PLS component 1; t [2], PLS component 2. At the timepoint 4 h, urine samples were unavailable for two participants.
Figure 2
Figure 2
Kinetics of the selected discriminating negative ion mode features obtained from the discovery study represented with accurate mass (176.06838 (A); 231.1221 (B); 103.9369 (C); 398.0101 (D); and 556.2011 (E)) after pea intake and compared with control food couscous (p < 0.05). Values are mean ± SEMs. X-axis values represent time course in hours and Y-axis values represent osmolality normalized peak intensity.
Figure 2
Figure 2
Kinetics of the selected discriminating negative ion mode features obtained from the discovery study represented with accurate mass (176.06838 (A); 231.1221 (B); 103.9369 (C); 398.0101 (D); and 556.2011 (E)) after pea intake and compared with control food couscous (p < 0.05). Values are mean ± SEMs. X-axis values represent time course in hours and Y-axis values represent osmolality normalized peak intensity.
Figure 3
Figure 3
Kinetics of the selected discriminating positive ion mode features obtained from the discovery study represented with accurate mass (231.1221 (A); 168.0288 (B); 152.0706 (C); 325.0796 (D); and 210.0642 (E)) after pea intake and compared with control food couscous (p < 0.05). Values are mean ± SEMs. X-axis values represent time course in hours and Y-axis values represent osmolality normalized peak intensity.
Figure 3
Figure 3
Kinetics of the selected discriminating positive ion mode features obtained from the discovery study represented with accurate mass (231.1221 (A); 168.0288 (B); 152.0706 (C); 325.0796 (D); and 210.0642 (E)) after pea intake and compared with control food couscous (p < 0.05). Values are mean ± SEMs. X-axis values represent time course in hours and Y-axis values represent osmolality normalized peak intensity.
Figure 4
Figure 4
MS/MS spectra of 2-Isopropylmalic acid at average collision energies (10, 20, 40 eV) of: a pure analytical standard (A); and in the urine sample (B); extracted ion chromatogram (EIC) (C); and Find by Formula spectrum (D).
Figure 4
Figure 4
MS/MS spectra of 2-Isopropylmalic acid at average collision energies (10, 20, 40 eV) of: a pure analytical standard (A); and in the urine sample (B); extracted ion chromatogram (EIC) (C); and Find by Formula spectrum (D).
Figure 5
Figure 5
Urinary 2-Isopropylmalic acid (2-IPMA) (A); Asparaginyl valine (Asp-Val) (B); and N-Carbamoyl-2-amino-2-(4-hydroxyphenyl) acetic acid (NC) (C) demonstrated a dose–response to intake of peas from the dose–response study. Values are means ± SEMs (n = 12). Participants consumed a low (40 g) (L), medium (75 g) or high (165 g) portion of peas as part of their habitual diet for four consecutive days for each intervention week and first void urine sample collected on the fifth day was analysed. X-axis values represent pea intake (g); Y-axis values represent peak area ratio. Peak area ratio is obtained by dividing the peak area of the sample with that of the internal standard.

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