Introduction
After decades of nutrition research, it is now well recognised that diet has a major influence on health and disease outcomes. The consumption of legumes has been associated with reduced risk of developing several noncommunicable diseases.(1) Accurate determination of intake of these foods is challenging with traditional methods of dietary assessment as these are susceptible to errors such as recall bias and difficulty estimating portion sizes.(2) Dietary biomarkers have emerged as a potential objective method of intake assessment, with a number of candidate biomarkers suggested for specific foods.(3) Currently, there are no validated biomarkers for green beans. Therefore, the objective of the current work is to discover and validate dietary biomarkers of green beans intake.
Methods
A randomised cross-over acute intervention study was performed with 27 healthy participants that consumed a large portion of green beans, mixed berries, and mixed vegetables on 3 separate occasions over 3 weeks. Following an overnight fast, participants provided a first void urine sample and collected samples after 2, 4, 6, and 24 hours post-consumption of the foods. Urinary metabolites were measured by liquid chromatography – mass spectrometry (LC-MS) in both positive and negative ionisation modes, and multivariate statistical analysis was performed to determine the features that changed post-consumption of green beans. Samples were further analysed by tandem mass spectrometry to obtain fragmentation patterns for metabolite identification. The putative biomarkers were assessed for a dose-response relationship in a follow-up study where 33 participants consumed 3 portion sizes of green beans.
Results
Partial least squares discriminant analysis models demonstrated that the urinary metabolome was distinctly different following consumption of green beans (0h v 4h, Positive Mode (R²X=0.51, Q²=0.35); Negative Mode (R²X=0.28, Q²=0.43)). Variable importance in projection lists generated from the models and a repeated measures ANOVA identified the most discriminant features between pre and post-consumption of green beans (p <0.05). Examination of the features revealed that a total of 16 positive and 62 negative features displayed a differential time course after green beans intake compared to the control food.  Putative identifications from spectral databases and the literature were assigned to metabolites, including trigonelline with mass to charge ratio (m/z) 138.055 and retention time (RT) 0.706, eucomic acid (m/z 239.0563, RT 10.196), 5-hydroxyanthranillic acid (m/z 154.0498, RT 4.697), hydroxyabscisic acid glucuronide (m/z 455.154, RT 12.573), and 3-hydroxysuberic acid (m/z 189.0767, RT 11.314). These metabolites, among others, displayed a dose-response relationship with increased urinary concentrations following increased green beans consumption.
Conclusion
Confirmation of the metabolite identifications with authentic standards is on-going. Moreover, data from the does-response study indicates that certain features can distinguish between portions of green beans intake. These metabolites will be combined into biomarker panels and assessed for their ability to predict intake.
References
1. Sri Harsha P.S.C, Wahab RA, Brennan L et al (2018) Genes Nutr 13, 25.
2. Neuhouser ML, Tinker L, Prentice RL et al (2008) Am J Epidemiol 167, 1247-59.
3. Rafiq T, Azab SM, Teo KK et al (2021) Adv Nutr 12, 2333-2357.

Introduction
After decades of nutrition research, it is now well recognised that diet has a major influence on health and disease outcomes. The consumption of legumes has been associated with reduced risk of developing several noncommunicable diseases.(1) Accurate determination of intake of these foods is challenging with traditional methods of dietary assessment as these are susceptible to errors such as recall bias and difficulty estimating portion sizes.(2) Dietary biomarkers have emerged as a potential objective method of intake assessment, with a number of candidate biomarkers suggested for specific foods.(3) Currently, there are no validated biomarkers for green beans. Therefore, the objective of the current work is to discover and validate dietary biomarkers of green beans intake.
Methods
A randomised cross-over acute intervention study was performed with 27 healthy participants that consumed a large portion of green beans, mixed berries, and mixed vegetables on 3 separate occasions over 3 weeks. Following an overnight fast, participants provided a first void urine sample and collected samples after 2, 4, 6, and 24 hours post-consumption of the foods. Urinary metabolites were measured by liquid chromatography – mass spectrometry (LC-MS) in both positive and negative ionisation modes, and multivariate statistical analysis was performed to determine the features that changed post-consumption of green beans. Samples were further analysed by tandem mass spectrometry to obtain fragmentation patterns for metabolite identification. The putative biomarkers were assessed for a dose-response relationship in a follow-up study where 33 participants consumed 3 portion sizes of green beans.
Results
Partial least squares discriminant analysis models demonstrated that the urinary metabolome was distinctly different following consumption of green beans (0h v 4h, Positive Mode (R²X=0.51, Q²=0.35); Negative Mode (R²X=0.28, Q²=0.43)). Variable importance in projection lists generated from the models and a repeated measures ANOVA identified the most discriminant features between pre and post-consumption of green beans (p <0.05). Examination of the features revealed that a total of 16 positive and 62 negative features displayed a differential time course after green beans intake compared to the control food.  Putative identifications from spectral databases and the literature were assigned to metabolites, including trigonelline with mass to charge ratio (m/z) 138.055 and retention time (RT) 0.706, eucomic acid (m/z 239.0563, RT 10.196), 5-hydroxyanthranillic acid (m/z 154.0498, RT 4.697), hydroxyabscisic acid glucuronide (m/z 455.154, RT 12.573), and 3-hydroxysuberic acid (m/z 189.0767, RT 11.314). These metabolites, among others, displayed a dose-response relationship with increased urinary concentrations following increased green beans consumption.
Conclusion
Confirmation of the metabolite identifications with authentic standards is on-going. Moreover, data from the does-response study indicates that certain features can distinguish between portions of green beans intake. These metabolites will be combined into biomarker panels and assessed for their ability to predict intake.
**References**
1. Sri Harsha P.S.C, Wahab RA, Brennan L et al (2018) _Genes Nutr_ 13, 25.
2. Neuhouser ML, Tinker L, Prentice RL et al (2008) _Am J Epidemiol_ 167, 1247-59.
3. Rafiq T, Azab SM, Teo KK et al (2021) Adv Nutr 12, 2333-2357.

A metabolomics approach to discover and validate dietary biomarkers of green beans intake

Modern nutrition science is young: It is less than one century since the first vitamin was isolated in 1926. Nutrition science stands upon research conducted by academia, the private sector, and nongovernmental organisations, often in collaboration across these sectors. Its evidence base is of fundamental importance to the solving of current challenges and complexities, optimising outcomes, and the prevention of harm.

In order to remain relevant, nutrition science must address the global challenges, including ensuring nutrition security for all, in line with the UN Sustainable Development Goals and in the context of the post-COVID era. It is timely to take stock and consider how nutrition science must move forward.

The conference is designed integrate three symposium sessions which will commence with reflection on historical exemplars of nutrition achievements, then moving the discussion to current challenges which face the discipline and will culminate in scoping the outlook for nutrition science going forward.