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      Biomarkers of food intake for nuts and vegetable oils: an extensive literature search

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          Abstract

          Nuts and vegetable oils are important sources of fat and of a wide variety of micronutrients and phytochemicals. Following their intake, several of their constituents, as well as their derived metabolites, are found in blood circulation and in urine. As a consequence, these could be used to assess the compliance to a dietary intervention or to determine habitual intake of nuts and vegetable oils. However, before these metabolites can be widely used as biomarkers of food intake (BFIs), several characteristics have to be considered, including specificity, dose response, time response, stability, and analytical performance. We have, therefore, conducted an extensive literature search to evaluate current knowledge about potential BFIs of nuts and vegetable oils. Once identified, the strengths and weaknesses of the most promising candidate BFIs have been summarized. Results from selected studies have provided a variety of compounds mainly derived from the fatty fraction of these foods, but also other components and derived metabolites related to their nutritional composition. In particular, α-linolenic acid, urolithins, and 5-hydroxyindole-3-acetic acid seem to be the most plausible candidate BFIs for walnuts, whereas for almonds they could be α-tocopherol and some catechin-derived metabolites. Similarly, several studies have reported a strong association between selenium levels and consumption of Brazil nuts. Intake of vegetable oils has been mainly assessed through the measurement of specific fatty acids in different blood fractions, such as oleic acid for olive oil, α-linolenic acid for flaxseed (linseed) and rapeseed (canola) oils, and linoleic acid for sunflower oil. Additionally, hydroxytyrosol and its metabolites were the most promising distinctive BFIs for (extra) virgin olive oil. However, most of these components lack sufficient specificity to serve as BFIs. Therefore, additional studies are necessary to discover new candidate BFIs, as well as to further evaluate the specificity, sensitivity, dose-response relationships, and reproducibility of these candidate biomarkers and to eventually validate them in other populations. For the discovery of new candidate BFIs, an untargeted metabolomics approach may be the most effective strategy, whereas for increasing the specificity of the evaluation of food consumption, this could be a combination of different metabolites.

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          The online version of this article (10.1186/s12263-019-0628-8) contains supplementary material, which is available to authorized users.

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          Most cited references171

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          HMDB: a knowledgebase for the human metabolome

          The Human Metabolome Database (HMDB, http://www.hmdb.ca) is a richly annotated resource that is designed to address the broad needs of biochemists, clinical chemists, physicians, medical geneticists, nutritionists and members of the metabolomics community. Since its first release in 2007, the HMDB has been used to facilitate the research for nearly 100 published studies in metabolomics, clinical biochemistry and systems biology. The most recent release of HMDB (version 2.0) has been significantly expanded and enhanced over the previous release (version 1.0). In particular, the number of fully annotated metabolite entries has grown from 2180 to more than 6800 (a 300% increase), while the number of metabolites with biofluid or tissue concentration data has grown by a factor of five (from 883 to 4413). Similarly, the number of purified compounds with reference to NMR, LC-MS and GC-MS spectra has more than doubled (from 380 to more than 790 compounds). In addition to this significant expansion in database size, many new database searching tools and new data content has been added or enhanced. These include better algorithms for spectral searching and matching, more powerful chemical substructure searches, faster text searching software, as well as dedicated pathway searching tools and customized, clickable metabolic maps. Changes to the user-interface have also been implemented to accommodate future expansion and to make database navigation much easier. These improvements should make the HMDB much more useful to a much wider community of users.
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            Paleolithic nutrition. A consideration of its nature and current implications.

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              Health Benefits of Nut Consumption

              Emilio Ros (2010)
              Nuts (tree nuts and peanuts) are nutrient dense foods with complex matrices rich in unsaturated fatty and other bioactive compounds: high-quality vegetable protein, fiber, minerals, tocopherols, phytosterols, and phenolic compounds. By virtue of their unique composition, nuts are likely to beneficially impact health outcomes. Epidemiologic studies have associated nut consumption with a reduced incidence of coronary heart disease and gallstones in both genders and diabetes in women. Limited evidence also suggests beneficial effects on hypertension, cancer, and inflammation. Interventional studies consistently show that nut intake has a cholesterol-lowering effect, even in the context of healthy diets, and there is emerging evidence of beneficial effects on oxidative stress, inflammation, and vascular reactivity. Blood pressure, visceral adiposity and the metabolic syndrome also appear to be positively influenced by nut consumption. Thus it is clear that nuts have a beneficial impact on many cardiovascular risk factors. Contrary to expectations, epidemiologic studies and clinical trials suggest that regular nut consumption is unlikely to contribute to obesity and may even help in weight loss. Safety concerns are limited to the infrequent occurrence of nut allergy in children. In conclusion, nuts are nutrient rich foods with wide-ranging cardiovascular and metabolic benefits, which can be readily incorporated into healthy diets.
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                Author and article information

                Contributors
                margarcia@ub.edu
                paul.hulshof@wur.nl
                sheilaestruel@ub.edu
                m.c.j.oste@umcg.nl
                maria.lankinen@uef.fi
                marianne.geleijnse@wur.nl
                janettedegoede78@gmail.com
                maria.ulaszewska@fmach.it
                fulvio.mattivi@unitn.it
                s.j.l.bakker@umcg.nl
                ursula.schwab@uef.fi
                candres@ub.edu
                Journal
                Genes Nutr
                Genes Nutr
                Genes & Nutrition
                BioMed Central (London )
                1555-8932
                1865-3499
                19 March 2019
                19 March 2019
                2019
                : 14
                : 7
                Affiliations
                [1 ]ISNI 0000 0004 1937 0247, GRID grid.5841.8, Biomarkers and Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XaRTA, INSA, Faculty of Pharmacy and Food Sciences, Campus Torribera, , University of Barcelona, ; Barcelona, Spain
                [2 ]ISNI 0000 0000 9314 1427, GRID grid.413448.e, CIBER de Fragilidad y Envejecimiento Saludable (CIBERFES), , Instituto de Salud Carlos III, ; Barcelona, Spain
                [3 ]ISNI 0000 0001 0791 5666, GRID grid.4818.5, Division of Human Nutrition and Health, , Wageningen University, ; Wageningen, the Netherlands
                [4 ]Department of Internal Medicine, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
                [5 ]ISNI 0000 0001 0726 2490, GRID grid.9668.1, School of Medicine, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, ; Kuopio, Finland
                [6 ]ISNI 0000 0004 1755 6224, GRID grid.424414.3, Department of Food Quality and Nutrition, Research Innovation Center, , Fondazione Edmund Mach, ; Via Mach 1, 38010 San Michele all’Adige, TN Italy
                [7 ]ISNI 0000 0004 1937 0351, GRID grid.11696.39, Center Agriculture Food Environment, , University of Trento, ; San Michele all’Adige, Italy
                [8 ]ISNI 0000 0004 0628 207X, GRID grid.410705.7, Department of Medicine, Endocrinology and Clinical Nutrition, Kuopio University Hospital, ; Kuopio, Finland
                Article
                628
                10.1186/s12263-019-0628-8
                6423890
                30923582
                de6bbd41-5eef-4d84-852f-2c4c32503684
                © The Author(s) 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 29 October 2018
                : 25 January 2019
                Categories
                Review
                Custom metadata
                © The Author(s) 2019

                Nutrition & Dietetics
                nuts,oils,biomarker,intake,metabolomics
                Nutrition & Dietetics
                nuts, oils, biomarker, intake, metabolomics

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