Nominee: Mar Garcia-Aloy, Postdoctoral Researcher, University of Barcelona, Spain
Nominated By: Cristina Andres-Lacueva, Tenured University Lecturer, University of Barcelona, Spain
Supporting Comments: Mar Garcia-Aloy has been working in the Biomarkers and Nutritional & Food Metabolomics research group since the end of 2010. Mar has recently finished her PhD Thesis under my supervision, results of which have been published in relevant peer-reviewed journals in the field of metabolomics. She has been working in human nutritional metabolomics using MS-based metabolomics as a tool to improve the predictive capacity of dietary exposition using multimetabolite combined models. Mar is an outstanding scientist, combining curiosity and rigor at work in a very efficient way. She is an extremely hard working and dedicated to her work, which involves the use of the newest techniques in metabolomics. She always tries to overcome challenges faced in an effective manor with a positive attitude, motivation and self-confidence. Mar has been capable of working in multi-disciplinary fields very comfortably, from human nutrition to the high-throughput transversal technologies in analytical chemistry, biochemistry and bioinformatics, facing programming in R (programming language). For all these reasons I highly recommend Mar Garcia-Aloy for the 2015 Bioanalysis Young Investigator Award, not only enthusiastically but from the objectivity that provides the proven scientific evidence and the results obtained and published in journals of the highest scientific impact in her development research area.
What made you choose a career in bioanalysis?
In my Master’s studies I learned about metabolomics capacity in nutritional research for the first time. After finishing these studies I had the chance to join the experienced research group in this field in the University of Barcelona. There, I had the opportunity to be involved in human nutritional metabolomics as a predoctoral student with public financial support from Catalan Government. I found the application of MS-based metabolomics as a tool to discover new dietary biomarkers very interesting. Thus, I explored deeper into the use of untargeted metabolomics in nutritional research during my PhD research period.
Describe the main highlights of your bioanalytical research, and its importance to the bioanalytical community.
My research has been focused on the improvement of the predictive capacity of dietary exposition using dietary biomarkers. It was not easy to define robust biomarkers of dietary exposure as previously work was mainly focused on the study of one biomarker for each food. However, taking into account the peculiarities of this research field we purposed to combine different food-derived metabolites in panels of biomarkers in order to improve their predictive capacity. Thus, we reinforced the concept of ‘multimetabolite combined models’ and applied it to improve the predictive capacity of dietary exposition. Additionally I am currently involved in the metabolomic study of samples from subjects who followed a nutritional intervention to deepen the knowledge on the effects of diet on health, as well as the discovery of new clinical and nutritional biomarkers by a metabolomics approach using liquid chromatography coupled to mass spectrometry (HPLC-Q-ToF-MS).
Describe the most difficult challenge you have encountered in the laboratory and how you overcame it.
In the study of the association between diet and health, the use of accurate measurement of intake is required. Due to the complexity and limitation of traditional dietary assessment tools, there is growing interest in the implementation of dietary biomarkers in epidemiology as objective measures of dietary exposure. Recently, the interest in using metabolomics for the discovery of new dietary biomarkers has risen remarkably. Biomarkers of dietary consumption are defined as the compounds characteristic of a dietary constituent that discriminate consumers from nonconsumers. However, most food constituents are broadly present in different foods, hence they are not unique to a specific food item. Additionally, sometimes distinct compounds can converge on common metabolites, as a result of being involved in various metabolic processes in the body. For that reason, very few compounds can be considered robust biomarkers. To overcome this issue, and although this field was practically unexplored for the discovery of dietary biomarkers, we purposed and demonstrated that combining food-derived metabolites could provide a more accurate and precise measurement of consumption. This proposal allowed us to cover a wide range of characteristic compounds of the food studied. Our results reinforced the improved ability of multimetabolite biomarker models to selectively define dietary exposure.
Where do you see your career in bioanalysis taking you?
In the future I would like to participate prominently in the improvement of the application of metabolomics analysis in biological samples to study the interactions between diet and health. I would like to be involved in different international research groups and at the same time to have interaction with private companies. I am particularly interested in the reproducibility of measurements among different study designs and laboratories, as well as in the improvement of the most appropriated data processing techniques and statistical tools for metabolomics data. Finally, I would also like to be involved in the integration of different omics technologies and traditional clinical markers of health in order to obtain a more holistic view of health status.
How do you envisage the field of bioanalysis evolving in the future?
I foresee nutrimetabolomics in the future playing a key role in the field of human health in order to elucidate the underlying mechanisms between diet and chronic diseases. This field is clearly multidisciplinary, with emerging applications in analytical chemistry, chemometrics, bioinformatics, human metabolism and biomedicine. Furthermore, given the increasing interest of the food industry in developing new functional foods, there is a need for objective biomarkers of food exposure that enable accurate measurements of their bioavailability. One of the strategic plans of the international community, including both the U.S. FDA and the European Commission, concerns the need for the development and validation of biomarkers of food intake using omics-based approaches such as food metabolomics. Therefore, the development of new biomarkers of food exposure and even the proposal of new strategies to obtain novel biomarker patterns could contribute to the advancement in this important field in terms of both health and economics. At the same time, the application of untargeted metabolomics studies in the discovery of new biomarkers of dietary exposure can lead to the discovery of bioactive compounds with potential applications in the design of novel functional foods or dietary supplements.
Please list up to five of your publications in the field of bioanalysis:
1. Garcia-Aloy M, Llorach R, Andres-Lacueva C et al. A metabolomics-driven approach to predict cocoa product consumption by designing a multimetabolite biomarker model in free-living subjects from the PREDIMED study. Mol. Nutr. Food Res. 59(2), 212—20 (2015).
2. Garcia-Aloy M, Llorach R, Andres-Lacueva C et al. Nutrimetabolomics fingerprinting to identify biomarkers of bread exposure in a free-living population from the PREDIMED study cohort. Metabolomics 11(1), 155—165 (2015).
3. Garcia-Aloy M, Llorach R, Andres-Lacueva C et al. Novel multimetabolite prediction of walnut consumption by a urinary biomarker model in a free-living population: the PREDIMED study. J. Proteome Res. 13(7), 3476—3483 (2014).
4. Llorach R, Garcia-Aloy M, Tulipani S, Vazquez-Fresno R, Andres-Lacueva C. Nutrimetabolomic strategies to develop new biomarkers of intake and health effects. J. Agric. Food Chem. 60(36), 8797—8808 (2012).
5. Tulipani S, Garcia-Aloy M, Andrés-Lacueva C et al. Metabolomics unveils urinary changes in subjects with metabolic syndrome following 12-week nut consumption. J. Proteome Res. 10 (11), 5047—5058 (2011).
Please select one publication from above that best highlights your career to date in the field of bioanalysis and provide an explanation for your choice.
3. Garcia-Aloy M, Llorach R, Andres-Lacueva C,et al. Novel multimetabolite prediction of walnut consumption by a urinary biomarker model in a free-living population: the PREDIMED study. J. Proteome Res. 13(7), 3476—3483 (2014).
In this paper we introduced the concept of ‘multimetabolite combined models’ and applied it to characterize dietary walnut fingerprinting in spot urine using an untargeted metabolomics approach, in two differentiated free-living populations. In this study we replicated urinary biomarkers of nut exposure proposed in a previous clinical trial analyzing the urinary metabolomic changes that occurred in subjects under specific controlled dietary conditions. Increasingthe level of evidence from previously observed associations. Furthermore, we showed that when biomarkers are merged in a multimetabolite prediction model, a better prediction performance is obtained than from any metabolite individually.