Biomarkers of food intake for Allium vegetables.
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ABSTRACT:
SUBMITTER: Pratico G
PROVIDER: S-EPMC6309086 | biostudies-other | 2018
REPOSITORIES: biostudies-other
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Project description:BACKGROUND:Numerous studies acknowledged the importance of an adequate vegetable consumption for human health. However, current methods to estimate vegetable intake are often prone to measurement errors due to self-reporting and/or insufficient detail. More objective intake biomarkers for vegetables, using biological specimens, are preferred. The only concentration biomarkers currently available are blood carotenoids and vitamin C, covering total fruit and vegetable intake. Identification of biomarkers for specific vegetables is needed for a better understanding of their relative importance for human health. Within the FoodBAll Project under the Joint Programming Initiative "A Healthy Diet for a Healthy Life", an ambitious action was undertaken to identify candidate intake biomarkers for all major food groups consumed in Europe by systematically reviewing the existent literature. This study describes the review on candidate biomarkers of food intake (BFIs) for leafy, bulb, and stem vegetables, which was conducted within PubMed, Scopus and Web of Science for studies published through March 2019. RESULTS:In total, 65 full-text articles were assessed for eligibility for leafy vegetables, and 6 full-text articles were screened for bulb and stem vegetables. Putative BFIs were identified for spinach, lettuce, endive, asparagus, artichoke, and celery, but not for rocket salad. However, after critical evaluation through a validation scheme developed by the FoodBAll consortium, none of the putative biomarkers appeared to be a promising BFI. The food chemistry data indicate that some candidate BFIs may be revealed by further studies. CONCLUSION:Future randomized controlled feeding studies combined with observational studies, applying a non-targeted metabolomics approach, are needed in order to identify valuable BFIs for the intake of leafy, bulb, and stem vegetables.
| S-EPMC7144047 | biostudies-literature
Project description:ScopeOnly a few studies analyzed the role of allium vegetables with reference to head and neck cancers (HNC), with mixed results. We investigated the potential favorable role of garlic and onion within the International Head and Neck Cancer Epidemiology (INHANCE) Consortium.Methods and resultsWe analyzed pooled individual-level data from eight case-control studies, including 4590 cases and 7082 controls. We estimated odds ratios (ORs) and 95% confidence intervals (CIs) for associations between garlic and onion intakes and HNC risk. Compared with no or low garlic use, the ORs of HNC were 0.95 (95% CI 0.71-1.27) for intermediate and 0.74 (95% CI 0.55-0.99) for high garlic use (p for trend = 0.02). The ORs of HNC for increasing categories of onion intake were 0.91 (95% CI 0.68-1.21) for >1 to ≤3 portions per week, and 0.83 (95% CI 0.60-1.13) for >3 portions per week (p for trend = 0.02), as compared to <1 portion per week. We found an inverse association between high onion intake and laryngeal cancer risk (OR = 0.69; 95% CI 0.54-0.88), but no significant association for other subsites.ConclusionThe results of this pooled-analysis support a possible moderate inverse association between garlic and onion intake and HNC risk.
| S-EPMC4579039 | biostudies-literature
Project description:Grapes and berries are two types of widely consumed fruits characterized by a high content in different phytochemicals. However, their accurate dietary assessment is particularly arduous, because of the already wide recognized bias associated with self-reporting methods, combined with the large range of species and cultivars and the fact that these fruits are popularly consumed not only in fresh and frozen forms but also as processed and derived products, including dried and canned fruits, beverages, jams, and jellies. Reporting precise type and/or quantity of grape and berries in FFQ or diaries can obviously be affected by errors. Recently, biomarkers of food intake (BFIs) rose as a promising tool to provide accurate information indicating consumption of certain food items. Protocols for performing systematic reviews in this field, as well as for assessing the validity of candidate BFIs have been developed within the Food Biomarker Alliance (FoodBAll) Project. This paper aims to evaluate the putative BIFs for blueberries, strawberries, raspberries, blackberries, cranberries, blackcurrant, and grapes. Candidate BFIs for grapes were resveratrol metabolites and tartaric acid. The metabolites considered as putative BFI for berries consumption were mostly anthocyanins derivatives together with several metabolites of ellagitannins and some aroma compounds. However, identification of BFIs for single berry types encountered more difficulties. In the absence of highly specific metabolites reported to date, we suggested some multi-metabolite panels that may be further investigated as putative biomarkers for some berry fruits.
| S-EPMC7509942 | biostudies-literature
Project description:BackgroundVegetables of the genus Allium are widely consumed but remain poorly understood genetically. Genetic mapping has been conducted in intraspecific crosses of onion (Allium cepa L.), A. fistulosum and interspecific crosses between A. roylei and these two species, but it has not been possible to access genetic maps and underlying data from these studies easily.DescriptionAn online comparative genomics database, AlliumMap, has been developed based on the GMOD CMap tool at http://alliumgenetics.org. It has been populated with curated data linking genetic maps with underlying markers and sequence data from multiple studies. It includes data from multiple onion mapping populations as well as the most closely related species A. roylei and A. fistulosum. Further onion EST-derived markers were evaluated in the A. cepa x A. roylei interspecific population, enabling merging of the AFLP-based maps. In addition, data concerning markers assigned in multiple studies to the Allium physical map using A. cepa-A. fistulosum alien monosomic addition lines have been compiled. The compiled data reveal extensive synteny between onion and A. fistulosum.ConclusionsThe database provides the first online resource providing genetic map and marker data from multiple Allium species and populations. The additional markers placed on the interspecific Allium map confirm the value of A. roylei as a valuable bridge between the genetics of onion and A. fistulosum and as a means to conduct efficient mapping of expressed sequence markers in Allium. The data presented suggest that comparative approaches will be valuable for genetic and genomic studies of onion and A. fistulosum. This online resource will provide a valuable means to integrate genetic and sequence-based explorations of Allium genomes.
| S-EPMC3423043 | biostudies-literature
Project description:OBJECTIVE:This study evaluates the effect of food intake on 92 neurological biomarkers in plasma. Moreover, it investigated if any of the biomarkers were correlated with body mass index. MATERIALS AND METHODS:Twenty-two healthy subjects (11 male and 11 female aged 25.9 ± 4.2 years) were investigated. A total of 92 biomarkers were measured before a standardized meal as well as 30 and 120 min afterward with the Proseek Multiplex Neurology I kit. RESULTS:The levels for 13 biomarkers decreased significantly (p < .001) 30 min after food intake. The levels for four biomarkers remained significantly decreased (p < .001) 120 min after food intake. One biomarker increased significantly (p < .001) 30 min after food intake. The changes were between 1% and 12%, with an average difference of about 5%. Only one biomarker showed a difference over 10% due to food intake. The biggest difference was observed for Plexin-B3 120 min after food intake (12%). Of all the 92 neurological biomarkers, only one was correlated with BMI, Kynureninase r = .46, p < .05. CONCLUSIONS:This study shows that food intake has a very modest effect on 92 different neurological biomarkers. Timing of blood sampling in relation to food intake, therefore, appears not to be a major concern. Only Kynureninase was correlated with BMI. Further studies are warranted in older healthy subjects and in patients with various neurological diseases to determine whether the findings are reproducible in such populations.
| S-EPMC5607537 | biostudies-literature
Project description:Metabolomics can be a tool to identify dietary biomarkers. However, reported food-metabolite associations have been inconsistent, and there is a need to explore further associations. Our aims were to confirm previously reported food-metabolite associations and to identify novel food-metabolite associations. We conducted a cross-sectional analysis of data from 849 participants (57% men) of the PopGen cohort. Dietary intake was obtained using FFQ and serum metabolites were profiled by an untargeted metabolomics approach. We conducted a systematic literature search to identify previously reported food-metabolite associations and analyzed these associations using linear regression. To identify potential novel food-metabolite associations, datasets were split into training and test datasets and linear regression models were fitted to the training datasets. Significant food-metabolite associations were evaluated in the test datasets. Models were adjusted for covariates. In the literature, we identified 82 food-metabolite associations. Of these, 44 associations were testable in our data and confirmed associations of coffee with 12 metabolites, of fish with five, of chocolate with two, of alcohol with four, and of butter, poultry and wine with one metabolite each. We did not identify novel food-metabolite associations; however, some associations were sex-specific. Potential use of some metabolites as biomarkers should consider sex differences in metabolism.
| S-EPMC7698441 | biostudies-literature
Project description:ObjectiveThe present study evaluates the effect of food intake on 92 biomarkers for cardiovascular disease (CVD).MethodsTwenty two healthy subjects (11 male and 11 female aged 25.9±4.2 years) were investigated. A total of 92 biomarkers were measured before a standardized meal as well as 30 and 120 minutes afterwards with the Proseek Multiplex CVD III kit.ResultsThe levels for eight biomarkers decreased significantly (P<0.05) 30 minutes after food intake. The levels for seven biomarkers remained significantly decreased 120 minutes after food intake. Nine biomarker decreased significantly at 120 minutes after food intake. The changes were between 4-30%, most commonly around 5%. Only six biomarkers showed a difference of 10% or more due to food intake. The biggest differences were observed for Insulin-like growth factor-binding protein 1 (30%); Azurocidin, Cystatin-B, and Myeloperoxidase (13%); Monocyte chemotactic protein 1 (11%); and Myeloblastin (10%), all 120 minutes after food intake.ConclusionsThis study shows that food intake affects several different CVD biomarkers, but the effect is predominantly modest. Timing of blood sampling in relation to food intake, therefore, appears not to be a major concern. Further studies are warranted in older healthy subjects and in patients with various cardiac diseases to determine whether the findings are reproducible.
| S-EPMC5460853 | biostudies-literature
Project description:BackgroundDiet affects the human gastrointestinal microbiota. Blood and urine samples have been used to determine nutritional biomarkers. However, there is a dearth of knowledge on the utility of fecal biomarkers, including microbes, as biomarkers of food intake.ObjectivesThis study aimed to identify a compact set of fecal microbial biomarkers of food intake with high predictive accuracy.MethodsData were aggregated from 5 controlled feeding studies in metabolically healthy adults (n = 285; 21-75 y; BMI 19-59 kg/m2; 340 data observations) that studied the impact of specific foods (almonds, avocados, broccoli, walnuts, and whole-grain barley and whole-grain oats) on the human gastrointestinal microbiota. Fecal DNA was sequenced using 16S ribosomal RNA gene sequencing. Marginal screening was performed on all species-level taxa to examine the differences between the 6 foods and their respective controls. The top 20 species were selected and pooled together to predict study food consumption using a random forest model and out-of-bag estimation. The number of taxa was further decreased based on variable importance scores to determine the most compact, yet accurate feature set.ResultsUsing the change in relative abundance of the 22 taxa remaining after feature selection, the overall model classification accuracy of all 6 foods was 70%. Collapsing barley and oats into 1 grains category increased the model accuracy to 77% with 23 unique taxa. Overall model accuracy was 85% using 15 unique taxa when classifying almonds (76% accurate), avocados (88% accurate), walnuts (72% accurate), and whole grains (96% accurate). Additional statistical validation was conducted to confirm that the model was predictive of specific food intake and not the studies themselves.ConclusionsFood consumption by healthy adults can be predicted using fecal bacteria as biomarkers. The fecal microbiota may provide useful fidelity measures to ascertain nutrition study compliance.
| S-EPMC7849973 | biostudies-literature
Project description:BackgroundThe fecal metabolome is affected by diet and includes metabolites generated by human and microbial metabolism. Advances in -omics technologies and analytic approaches have allowed researchers to identify metabolites and better utilize large data sets to generate usable information. One promising aspect of these advancements is the ability to determine objective biomarkers of food intake.ObjectivesWe aimed to utilize a multivariate, machine learning approach to identify metabolite biomarkers that accurately predict food intake.MethodsData were aggregated from 5 controlled feeding studies in adults that tested the impact of specific foods (almonds, avocados, broccoli, walnuts, barley, and oats) on the gastrointestinal microbiota. Fecal samples underwent GC-MS metabolomic analysis; 344 metabolites were detected in preintervention samples, whereas 307 metabolites were detected postintervention. After removing metabolites that were only detected in either pre- or postintervention and those undetectable in ≥80% of samples in all study groups, changes in 96 metabolites relative concentrations (treatment postintervention minus preintervention) were utilized in random forest models to 1) examine the relation between food consumption and fecal metabolome changes and 2) rank the fecal metabolites by their predictive power (i.e., feature importance score).ResultsUsing the change in relative concentration of 96 fecal metabolites, 6 single-food random forest models for almond, avocado, broccoli, walnuts, whole-grain barley, and whole-grain oats revealed prediction accuracies between 47% and 89%. When comparing foods with one another, almond intake was differentiated from walnut intake with 91% classification accuracy.ConclusionsOur findings reveal promise in utilizing fecal metabolites as objective complements to certain self-reported food intake estimates. Future research on other foods at different doses and dietary patterns is needed to identify biomarkers that can be applied in feeding study compliance and clinical settings.
| S-EPMC9840004 | biostudies-literature
Project description:BackgroundTo unravel true links between diet and health, it is important that dietary exposure is accurately measured. Currently, mainly self-reporting methods (e.g. food frequency questionnaires and 24-h recalls) are used to assess food intake in epidemiological studies. However, these traditional instruments are subjective measures and contain well-known biases. Especially, estimating the intake of the group of confectionary products, such as products containing cocoa and liquorice, remains a challenge. The use biomarkers of food intake (BFIs) may provide a more objective measurement. However, an overview of current candidate biomarkers and their validity is missing for both cocoa- and liquorice-containing foods.ObjectiveThe purpose of the current study was to (1) identify currently described candidate BFIs for cocoa (products) and liquorice, (2) to evaluate the validity of these identified candidate BFIs and (3) to address further validation and/or identification work to be done.MethodsThis systematic review was based on a comprehensive literature search of three databases (PubMed, Scopus and ISI web of Science), to identify candidate BFIs. Via a second search step in the Human Metabolome Database (HMDB), the Food Database (FooDB) and Phenol-Explorer, the specificity of the candidate BFIs was evaluated, followed by an evaluation of the validity of the specific candidate BFIs, via pre-defined criteria.ResultsIn total, 37 papers were included for cocoa and 8 papers for liquorice. For cocoa, 164 unique candidate BFIs were obtained, and for liquorice, four were identified in total. Despite the high number of identified BFIs for cocoa, none of the metabolites was specific. Therefore, the validity of these compounds was not further examined. For liquorice intake, 18-glycyrrhetinic acid (18-GA) was found to have the highest assumed validity.ConclusionsFor cocoa, specific BFIs were missing, mainly because the individual BFIs were also found in foods having a similar composition, such as tea (polyphenols) or coffee (caffeine). However, a combination of individual BFIs might lead to discriminating profiles between cocoa (products) and foods with a similar composition. Therefore, studies directly comparing the consumption of cocoa to these similar products are needed, enabling efforts to find a unique profile per product. For liquorice, we identified 18-GA as a promising BFI; however, important information on its validity is missing; thus, more research is necessary. Our findings indicate a need for more studies to determine acceptable BFIs for both cocoa and liquorice.
| S-EPMC6062926 | biostudies-literature