The food metabolome: a window over dietary exposure
Open accessAbstract
The food metabolome is defined as the part of the human metabolome directly derived from the digestion and biotransformation of foods and their constituents. With >25,000 compounds known in various foods, the food metabolome is extremely complex, with a composition varying widely according to the diet. By its very nature it represents a considerable and still largely unexploited source of novel dietary biomarkers that could be used to measure dietary exposures with a high level of detail and precision. Most dietary biomarkers currently have been identified on the basis of our knowledge of food compositions by using hypothesis-driven approaches. However, the rapid development of metabolomics resulting from the development of highly sensitive modern analytic instruments, the availability of metabolite databases, and progress in (bio)informatics has made agnostic approaches more attractive as shown by the recent identification of novel biomarkers of intakes for fruit, vegetables, beverages, meats, or complex diets. Moreover, examples also show how the scrutiny of the food metabolome can lead to the discovery of bioactive molecules and dietary factors associated with diseases. However, researchers still face hurdles, which slow progress and need to be resolved to bring this emerging field of research to maturity. These limits were discussed during the First International Workshop on the Food Metabolome held in Glasgow. Key recommendations made during the workshop included more coordination of efforts; development of new databases, software tools, and chemical libraries for the food metabolome; and shared repositories of metabolomic data. Once achieved, major progress can be expected toward a better understanding of the complex interactions between diet and human health.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
0 of 159 cited sources checked · 0 supported · 0 flagged
- Findingcitation
About 100 dietary biomarkers have been identified in the Exposome-Explorer database.
“Information on these biomarkers has been systematically collected in the novel Exposome-Explorer database (V Neveu, DS Wishart, and A Scalbert, unpublished data, 2014); w100 biomarkers could be identified”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites V Neveu, DS Wishart, and A Scalbert, unpublished data, 2014
Not checked in the free run.
- Findingreasoning
Except for two studies on dietary fiber and milk protein diet, all discovery studies listed used urine samples rather than blood samples.
“With the exception of 2 studies on dietary fiber and milk protein diet, all discovery studies were conducted on urine samples as opposed to blood samples (Table 3).”
Quote in the paperSubstantial claim - Premisecitation
Alkylresorcinols have been used as surrogate biomarkers of whole-grain cereal intake.
“alkylresorcinols for whole-grain cereals (19,20)”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [19] Ross, 2012, Plasma alkylresorcinols as a biomarker of whole-grain food consumption in a large population: results from the WHOLEheart Intervention Study, Am J Clin Nutr source
Not checked in the free run.
- cites [20] Andersson, 2011, Plasma alkylresorcinol concentrations correlate with whole grain wheat and rye intake and show moderate reproducibility over a 2-to 3-month period in free-living Swedish adults, J Nutr source
Not checked in the free run.
- Premisecitation
Dietary exposure has traditionally been assessed with self-reported methods such as dietary recalls or food-frequency questionnaires.
“Dietary exposure has traditionally been measured with self-reported methods, namely dietary recalls or food-frequency questionnaires (10).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [10] Rutishauser, 2005, Dietary intake measurements, Public Health Nutr source
Not checked in the free run.
- Premisecitation
Biomarkers are useful when little or no food composition data exist, as is often the case for bioactive molecules such as glucosinolates or contaminants such as aflatoxins.
“Biomarkers are also useful when little or no data exist on food composition, as is often the case for bioactive molecules such as glucosinolates or food contaminants such as aflatoxins (15,16).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [15] London, 2000, Isothiocyanates, glutathione S-transferase M1 and T1 polymorphisms, and lung-cancer risk: a prospective study of men in Shanghai, China, Lancet source
Not checked in the free run.
- cites [16] Kensler, 2011, Aflatoxin: a 50-year odyssey of mechanistic and translational toxicology, Toxicol Sci source
Not checked in the free run.
- Premisecitation
Dietary biomarkers have been used as more objective measures of dietary exposure in nutritional epidemiology.
“The application of dietary biomarkers as more objective measures of dietary exposure in nutritional epidemiology has been particularly significant (13).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [13] Jenab, 2009, Biomarkers in nutritional epidemiology: applications, needs and new horizons, Hum Genet source
Not checked in the free run.
- Premisecitation
Polyphenols, carotenoids, and vitamin C have been used as surrogate biomarkers of fruit and vegetable intake.
“polyphenols, carotenoids, and vitamin C for fruit and vegetables (17,18)”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [17] Baldrick, 2011, Biomarkers of fruit and vegetable intake in human intervention studies: a systematic review, Crit Rev Food Sci Nutr source
Not checked in the free run.
- cites [18] Mennen, 2006, Urinary flavonoids and phenolic acids as biomarkers of intake for polyphenol-rich foods, Br J Nutr source
Not checked in the free run.
- Interpretationreasoning
Biomarkers with half-lives of 24 hours or less may be useful only in populations that regularly and frequently consume their dietary sources.
“These biomarkers may thus be useful only in populations who regularly and frequently consume these dietary sources.”
Quote in the paperSubstantial claim - Premisecitation
Serotonin metabolism is altered by acute alcohol intake.
“serotonin metabolism is altered by acute alcohol intake (28)”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [28] Kroke, 2001, Comparison of self-reported alcohol intake with the urinary excretion of 5-hydroxytryptophol: 5-hydroxyindole-3-acetic acid, a biomarker of recent alcohol intake, Br J Nutr source
Not checked in the free run.
- Premisecitation
The activity of selenium-containing enzymes such as erythrocyte glutathione peroxidase depends on selenium intake.
“the activity of selenium-containing enzymes such as erythrocyte glutathione peroxidase depends on selenium intake”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [29] Crews, 2001, A critical assessment of some biomarker approaches linked with dietary intake, Br J Nutr source
Not checked in the free run.
- Premisecitation
Amino acids and fatty acids have been used as surrogate biomarkers of meat intake.
“amino acids and fatty acids for meat (22,23)”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [22] Allen, 2008, Phytanic acid: measurement of plasma concentrations by gas-liquid chromatography-mass spectrometry analysis and associations with diet and other plasma fatty acids, Br J Nutr source
Not checked in the free run.
- cites [23] Myint, 2000, Urinary 1-methylhistidine is a marker of meat consumption in black and in white California Seventh-day Adventists, Am J Epidemiol source
Not checked in the free run.
- Premisecitation
Polyphenols have been used as surrogate biomarkers of tea and wine intake.
“polyphenols for tea and wine (18,25)”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [18] Mennen, 2006, Urinary flavonoids and phenolic acids as biomarkers of intake for polyphenol-rich foods, Br J Nutr source
Not checked in the free run.
- cites [25] Hodgson, 2004, Phenolic acid metabolites as biomarkers for tea- and coffee-derived polyphenol exposure in human subjects, Br J Nutr source
Not checked in the free run.
- Interpretationreasoning
Analytic approaches based on combinations of dietary constituents may provide more accurate measurements of dietary exposure than single global assays.
“In contrast to these global assays, analytic approaches based on the estimation of combinations of dietary constituents may provide more accurate measurements of dietary exposure.”
Quote in the paperSubstantial claim - Premisecitation
Ceramide synthase is inhibited by exposure to the mycotoxin fumonisins.
“ceramide synthase is inhibited by exposure to the mycotoxin fumonisins (29).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [29] Crews, 2001, A critical assessment of some biomarker approaches linked with dietary intake, Br J Nutr source
Not checked in the free run.
- Premisecitation
Vitamin C or the sum of carotenoids or flavonoids have been used as generic biomarkers for fruit and vegetable intake.
“Vitamin C or the sum of carotenoids or flavonoids have been used as generic biomarkers for fruit and vegetable intake (18,45).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [18] Mennen, 2006, Urinary flavonoids and phenolic acids as biomarkers of intake for polyphenol-rich foods, Br J Nutr source
Not checked in the free run.
- cites [45] Al-Delaimy, 2005, Plasma carotenoids as biomarkers of intake of fruits and vegetables: individual-level correlations in the European Prospective Investigation into Cancer and Nutrition (EPIC), Eur J Clin Nutr source
Not checked in the free run.
- Interpretationreasoning
Intraindividual variability in biomarkers leads to exposure measurement errors when characterizing habitual exposure in epidemiologic studies with few measurements per subject.
“Intraindividual variability leads to exposure measurement errors when the objective is to characterize habitual exposure in epidemiologic studies and small numbers of measurements are available across subjects.”
Quote in the paperSubstantial claim - Premisecitation
Ratios of two alkylresorcinols characteristic of whole-grain wheat or rye were found to be good indicators of the relative consumption of these cereals.
“The ratios of 2 alkylresorcinols characteristic of whole-grain wheat or rye were found to be good indicators of the relative consumption of these cereals (20,48).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [20] Andersson, 2011, Plasma alkylresorcinol concentrations correlate with whole grain wheat and rye intake and show moderate reproducibility over a 2-to 3-month period in free-living Swedish adults, J Nutr source
Not checked in the free run.
- cites [48] Ross, 2003, Alkylresorcinols in cereals and cereal products, J Agric Food Chem source
Not checked in the free run.
- Premisenone given
A large majority of metabolites produced by the gut microbiota are derived from biotransformation of both the endogenous metabolome and the food metabolome and are integral parts of these two metabolomes.
“However, a large majority of the metabolites produced by the gut microbiota are derived from the biotransformation of both the endogenous metabolome and the food metabolome and are therefore an integral part of these 2 metabolomes.”
Quote in the paperSubstantial claim - Premisecitation
Isoflavones have been used as surrogate biomarkers of soy intake.
“isoflavones for soy (21)”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [21] Verkasalo, 2001, Soya intake and plasma concentrations of daidzein and genistein: validity of dietary assessment among eighty British women (Oxford arm of the European Prospective Investigation into Cancer and Nutrition), Br J Nutr source
Not checked in the free run.
- Premisereasoning
The gut microbiota is particularly adept at processing polyphenols to phenolic breakdown products.
“The gut microbiota is particularly adept at processing polyphenols to phenolic breakdown products.”
Quote in the paperNot a substantial claim - Premisenone given
There are very few examples in which combinations of biomarkers were used to improve the specificity of dietary exposure measurements.
“However, there are very few such examples in which combinations of biomarkers were used to improve the specificity of dietary exposure measurements.”
Quote in the paperSubstantial claim - Premisecitation
The gut microbiota contributes metabolites to the human metabolome.
“The importance of the gut microbiota in contributing metabolites to the human metabolome has also recently emerged (50,66).”
Quote in the paperNot a substantial claim0 of 2 sources checked - Interpretationreasoning
Exogenously derived host-transformed metabolites can be useful as specific food biomarkers.
“Consequently, these exogenously derived metabolites can be quite useful as specific food biomarkers.”
Quote in the paperSubstantial claim - Premisecitation
For polyphenols, more than 230 phase I/II metabolites have been identified and associated with consumption of specific polyphenol-containing foods.
“For polyphenols, .230phase I/II metabolites have been identified and associated with the consumption of specific polyphenol-containing foods (70).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [70] Rothwell, 2012, Phenol-Explorer 2.0: a major update of the Phenol-Explorer database integrating data on polyphenol metabolism and pharmacokinetics in humans and experimental animals, Database source
Not checked in the free run.
- Premisecitation
Fatty acids have been used as surrogate biomarkers of dairy product and fish intake.
“fatty acids for dairy products and fish (22,24)”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [22] Allen, 2008, Phytanic acid: measurement of plasma concentrations by gas-liquid chromatography-mass spectrometry analysis and associations with diet and other plasma fatty acids, Br J Nutr source
Not checked in the free run.
- cites [24] Arsenault, 2009, Validity of estimated dietary eicosapentaenoic acid and docosahexaenoic acid intakes determined by interviewer-administered food frequency questionnaire among older adults with mild-to-moderate cognitive impairment or dementia, Am J Epidemiol source
Not checked in the free run.
- Premisecitation
A meta-analysis of the metabolic fate of more than 1000 xenobiotics showed that cytochrome P450-catalyzed oxidations (40%) and UDP-glucuronosyltransferase glucuronidations (14%) were most common, followed by dehydrogenases (8%), hydrolases (7%), glutathione-S-transferases (6%), and sulfatases (5%).
“A recent meta-analysis (68) of the metabolic fate of .1000xenobiotics showed that cytochrome P450 catalyzed oxidations (40%) and UDP-glucuronosyltransferase glucuronidations (14%) were the most common followed by reactions involving dehydrogenases (8%), hydrolases (7%), glutathione-S-transferases (6%), and sulfatases (5%).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [68] Testa, 2012, Foundation review: reactions and enzymes in the metabolism of drugs and other xenobiotics, Drug Discov Today source
Not checked in the free run.
- Premisecitation
Metabolomics constitutes a comprehensive approach to identify new panels of biomarkers that are specific or common to particular foods or food groups, as shown for citrus fruit.
“Metabolomics constitutes a comprehensive approach to identify new panels of biomarkers that are specific or common to particular foods or food groups, as shown recently for citrus fruit (49).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [49] Pujos-Guillot, 2013, Mass spectrometry-based metabolomics for the discovery of biomarkers of fruit and vegetable intake: citrus fruit as a case study, J Proteome Res source
Not checked in the free run.
- Premisecitation
Identification of candidate dietary biomarkers is complicated because most food compounds are treated as xenobiotics by the human body in phase I and phase II reactions or undergo fermentation in the colon by gut microbiota.
“As previously described, the identification of candidate dietary biomarkers is complicated by the fact that the majority of food compounds are treated as xenobiotics by the human body in phase I and phase II reactions or undergo fermentation in the colon by the gut microbiota (139).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [139] Del Rio, 2013, Dietary (poly)phenolics in human health: structures, bioavailability, and evidence of protective effects against chronic diseases, Antioxid Redox Signal source
Not checked in the free run.
- Premisenone given
All available software tools differ in their peak picking algorithms.
“All available software tools differ in their peak picking algorithms.”
Quote in the paperNot a substantial claim - Interpretationreasoning
Consequently, it is often difficult to assess confidence in biomarker identification.
“For this reason, it is often difficult to evaluate the degree of confidence in biomarker identification.”
Quote in the paperSubstantial claim - Interpretationnone given
It is essentially impossible to use standards or isotopically labeled references to quantify the thousands of compounds in the food metabolome.
“It is essentially impossible to use standards or isotopically labeled references to quantify the thousands of compounds in the food metabolome.”
Quote in the paperNot a substantial claim - Interpretationnone given
The available targeted analysis methods combined still do not cover the entire chemical space of the food metabolome.
“However, the combination of available targeted analysis methods is still far from covering the whole chemical space of the food metabolome.”
Quote in the paperSubstantial claim - Premisenone given
Depending on the predominant microbiota, polyphenols can be transformed by ring cleavage to aromatic compounds such as benzoate and derivatives of hydroxyphenylacetic and hydroxypropionic acids.
“For instance, depending on the predominant microbiota, polyphenols can be transformed by ring cleavage to a variety of aromatic compounds such as benzoate and various derivatives of hydroxyphenylacetic and hydroxypropionic acids.”
Quote in the paperNot a substantial claim - Interpretationnone given
Despite some increase in availability, these highly diverse metabolites are largely absent from most databases.
“Despite some increase in their availability over the past few years, these highly diverse metabolites are largely absent from most databases.”
Quote in the paperSubstantial claim - Interpretationreasoning
Because of its sensitivity and breadth of coverage, LC-MS has become the method of choice for untargeted analysis of the food metabolome.
“However, because of its sensitivity and breadth of coverage, LC-MS has certainly become the method of choice for untargeted analysis of the food metabolome.”
Quote in the paperNot a substantial claim - Interpretationreasoning
Analysis of the food metabolome is particularly challenging for three reasons.
“Analyzing the food metabolome is a particularly challenging task for 3 reasons.”
Quote in the paperNot a substantial claim - Premisecitation
Mass spectrometry coupled with gas or liquid chromatography and NMR are currently the most widely used technologies for food metabolome analysis.
“As is the case for the other parts of the metabolome, mass spectrometry (MS) coupled with gas chromatography or liquid chromatography and NMR are currently the most widely used technologies for food metabolome analysis (Table 3).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Table 3
Not checked in the free run.
- Interpretationreasoning
The lack of a gap-filling algorithm creates major problems for normalization and statistical analysis.
“The lack of a gap-filling algorithm creates major problems for normalization and for statistical analysis.”
Quote in the paperNot a substantial claim - Interpretationreasoning
These advances may allow targeting larger areas of the food metabolome chemical space with standardized quantitative methods.
“These advances may allow researchers to target larger areas of the food metabolome chemical space with the use of standardized quantitative methods.”
Quote in the paperNot a substantial claim - Premisecitation
Chain length and degree of saturation of fatty acids in glycerophosphatidylcholines were associated with intake of specific foods or nutrients such as fish and dietary fiber.
“Furthermore, chain length and degree of saturation of fatty acids in glycerophosphatidylcholines were associated with intake of specific foods or nutrients such as fish and dietary fiber.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [109] Altmaier, 2011, Questionnaire-based self-reported nutrition habits associate with serum metabolism as revealed by quantitative targeted metabolomics, Eur J Epidemiol source
Not checked in the free run.
- Premisecitation
There is only a 50-70% overlap between peaks detected by different software packages from the same raw data set, even with similar settings.
“There is only a 50-70% overlap between the peaks detected by different packages from the same raw data set, even with similar settings (125).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [125] Gürdeniz, 2012, The effect of LC-MS data preprocessing methods on the selection of plasma biomarkers in fed vs. fasted rats, Metabolites source
Not checked in the free run.
- Premisecitation
High-resolution LC-Q-TOF MS with electrospray ionization has successfully detected compounds such as terpene metabolites, diketopiperazine metabolites, phenylvalerolactones, and benzoxazinoid metabolites, which are candidate biomarkers of food intake not easily detected by NMR or GC-MS.
“This technique has been successful in detecting compounds such as terpene metabolites, diketopiperazine metabolites, phenylvalerolactones, and benzoxazinoid metabolites, which are interesting candidate biomarkers of food intake that would not be easily detected in biofluids by NMR or GC-MS (49,86,96).”
Quote in the paperSubstantial claim0 of 3 sources checked- cites [49] Pujos-Guillot, 2013, Mass spectrometry-based metabolomics for the discovery of biomarkers of fruit and vegetable intake: citrus fruit as a case study, J Proteome Res source
Not checked in the free run.
- cites [86] Bondia-Pons, 2013, UPLC-QTOF/MS metabolic profiling unveils urinary changes in humans after a whole grain rye versus refined wheat bread intervention, Mol Nutr Food Res source
Not checked in the free run.
- cites [96] Llorach, 2009, An LC-MS-based metabolomics approach for exploring urinary metabolome modifications after cocoa consumption, J Proteome Res source
Not checked in the free run.
- Interpretationnone given
No single chromatographic method can cover the wide range of polarity of food metabolome compounds.
“No single chromatographic method is able to cover the wide range of polarity existing for the food metabolome compounds.”
Quote in the paperSubstantial claim - Premisecitation
New biomarkers for citrus fruit intake and coffee have been successfully identified using 24-hour dietary recalls and food-frequency questionnaires.
“Both 24-h dietary recalls and food-frequency questionnaires have been used, and new biomarkers for citrus fruit intake or coffee were successfully identified (49, 88) (Table 3).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [49] Pujos-Guillot, 2013, Mass spectrometry-based metabolomics for the discovery of biomarkers of fruit and vegetable intake: citrus fruit as a case study, J Proteome Res source
Not checked in the free run.
- cites [88] Lang, 2011, Urinary N-methylpyridinium and trigonelline as candidate dietary biomarkers of coffee consumption, Mol Nutr Food Res source
Not checked in the free run.
- Premisecitation
New approaches using isotope labeling and multiple reaction monitoring-based profiling are being developed for families of compounds sharing distinctive chemical functionalities.
“New approaches are being developed with isotope labeling and multiple reaction monitoring-based profiling for families of compounds sharing distinctive chemical functionalities (118).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [118] Guo, 2012, Liquid chromatography-mass spectrometric multiple reaction monitoring-based strategies for expanding targeted profiling towards quantitative metabolomics, Curr Drug Metab source
Not checked in the free run.
- Interpretationnone given
The likelihood of identifying robust dietary biomarkers depends on both the sensitivity of the analytical equipment and the quality of the dietary data used for correlation with metabolic profiles.
“However, the chances to identify robust biomarkers will rely both on the sensitivity of the analytic equipment used and on the quality of the dietary data against which metabolic profiles are correlated.”
Quote in the paperSubstantial claim - Interpretationnone given
Lipophilic biomarkers, which may be more stable over time, are more likely to be found in blood.
“Also, lipophilic biomarkers, which may be more stable over time (see Pharmacokinetics and reliability of dietary biomarkers section), are more likely to be found in blood.”
Quote in the paperNot a substantial claim - Premisecitation
Weaker correlations with intakes of foods or their constituents were observed for microbial metabolites compared with untransformed food compounds and host-transformed metabolites.
“Consequently, weaker correlations with intakes of foods or of their constituents were observed for microbial metabolites when compared with untransformed food compounds and host-transformed metabolites (41).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [41] Pérez-Jiménez, 2010, Urinary metabolites as biomarkers of polyphenol intake in humans—a systematic review, Am J Clin Nutr source
Not checked in the free run.
- Premisecitation
No standard currently exists for reporting chemical identification of biomarkers in metabolomic studies.
“In addition, no standard yet exists to report chemical identification of biomarkers in metabolomic studies (110).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [110] Sumner, 2007, Proposed minimum reporting standards for chemical analysis, Metabolomics source
Not checked in the free run.
- Interpretationnone given
The vast majority of food metabolome components are not yet represented in curated metabolite databases, making structural elucidation difficult.
“However, the vast majority of the food metabolome components are not yet represented in these databases, which makes the elucidation of their structure difficult.”
Quote in the paperSubstantial claim - Premisecitation
Recent advances have produced more efficient time-of-flight and single-stage Orbitrap instruments with improved linearity, resolution, and mass accuracy, which are critically important for food metabolome analysis.
“Rapid advances in technology have led to a new generation of much more efficient time-of-flight and single-stage Orbitrap (Exactive; Thermo Scientific) instruments, offering improved linearity, resolution, and mass accuracy, which will be critically important for the analysis of the food metabolome (115).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [115] He, 2012, Ultra-sensitive measurements of 11-nor-delta(9)-tetrahydrocannabinol-9-carboxylic acid in oral fluid by microflow liquid chromatography-tandem mass spectrometry using a benchtop quadrupole/Orbitrap mass spectrometer, Anal Chem source
Not checked in the free run.
- Interpretationreasoning
No standardized method exists yet for food metabolome analysis.
“No standardized method exists yet, and the need for improved harmonization is certainly desirable for further progress on the food metabolome.”
Quote in the paperNot a substantial claim - Premisecitation
Sparse PCA overcomes the limitation of PCA in identifying the most prominent part of the pattern.
“Sparse PCA overcomes this limitation (128, 129).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [128] Acar, 2012, Coupled matrix factorization with sparse factors to identify potential biomarkers in metabolomics, Int J Knowledge Discov Bioinformatics source
Not checked in the free run.
- cites [129] Gürdeniz, 2013, Patterns of time since last meal revealed by sparse PCA in an observational LC-MS based metabolomics study, Metabolomics source
Not checked in the free run.
- Premisecitation
In regression analyses of 363 plasma metabolites against dietary variables from a food-frequency questionnaire, the highest correlations were with phospholipid concentrations.
“Regression analyses of the concentrations of 363 metabolites in plasma with a number of dietary variables measured with a food-frequency questionnaire showed the highest correlations with phospholipid concentrations (109).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [109] Altmaier, 2011, Questionnaire-based self-reported nutrition habits associate with serum metabolism as revealed by quantitative targeted metabolomics, Eur J Epidemiol source
Not checked in the free run.
- Premisecitation
Intervention studies comparing a whole food with one of its bioactive constituents have demonstrated that these compounds may contribute to the health effects of the food.
“Although these compounds may actually contribute to the health effects of the food, as has been well demonstrated in intervention studies in which a whole food has been compared with one of its bioactive constituents (177)”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [177] Morand, 2011, Hesperidin contributes to the vascular protective effects of orange juice: a randomized crossover study in healthy volunteers, Am J Clin Nutr source
Not checked in the free run.
- Premisecitation
Hippurate has been associated with microbiota colonization of the gut.
“hippurate has been associated with microbiota colonization of the gut (170).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [170] Nicholson, 2005, Gut microorganisms, mammalian metabolism and personalized health care, Nat Rev Microbiol source
Not checked in the free run.
- Premisecitation
In an initial untargeted LC-MS/MS investigation, choline and its major metabolites betaine and TMAO were associated with cardiovascular disease risk, particularly TMAO.
“In their initial untargeted LC-MS/MS investigation (171), the authors showed that the nutrient choline, along with its major metabolites, betaine and TMAO, were associated with risks of cardiovascular disease, particularly TMAO.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [171] Wang, 2011, Gut flora metabolism of phosphatidylcholine promotes cardiovascular disease, Nature source
Not checked in the free run.
- Interpretationreasoning
The agnostic nature of the untargeted design permits identification of all potentially useful biomarkers, including dietary, endogenous, pollution, drug, and disease-progression biomarkers.
“The agnostic nature of the untargeted design allows all potentially useful biomarkers to be identified, including not only dietary biomarkers but also those related to endogenous factors (including the microbiota), pollution, and drugs as well as biomarkers of disease progression.”
Quote in the paperSubstantial claim - Premisecitation
Metabolome-wide association studies (MWASs) have been proposed as useful tools for discovering low-molecular-weight biomarkers predictive of causal exposures or disease progression.
“MWASs have been proposed as useful tools for discovering low-molecular-weight biomarkers that are predictive of either causal exposures or disease progression (59, 165, 166).”
Quote in the paperSubstantial claim0 of 3 sources checked- cites [59] Holmes, 2008, Human metabolic phenotype diversity and its association with diet and blood pressure, Nature source
Not checked in the free run.
- cites [165] Nicholson, 2008, The Metabolome-Wide Association Study: a new look at human disease risk factors, J Proteome Res source
Not checked in the free run.
- cites [166] Bictash, 2010, Opening up the “black box”: metabolic phenotyping and metabolome-wide association studies in epidemiology, J Clin Epidemiol source
Not checked in the free run.
- Interpretationcitation
Potentially useful biomarkers may be identified through rigorous comparisons of quantitative or semiquantitative profiles of biospecimens from subjects with and without a particular disease.
“In either case, potentially useful biomarkers may be identified through rigorous comparisons of quantitative or semiquantitative profiles of biospecimens obtained from subjects with and without a particular disease (59).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [59] Holmes, 2008, Human metabolic phenotype diversity and its association with diet and blood pressure, Nature source
Not checked in the free run.
- Premisecitation
Saadatian-Elahi et al. correlated food consumption from 24-hour dietary recall with plasma concentrations of 22 fatty acids measured by gas chromatography in 3000 subjects from the European Prospective Investigation into Cancer and Nutrition cohort.
“A good example of this approach is given by Saadatian-Elahi et al (168), who correlated food consumption, as determined by 24-h dietary recall, with plasma concentrations of 22 fatty acids determined by gas chromatography in 3000 subjects from the European Prospective Investigation into Cancer and Nutrition cohort.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [168] Saadatian-Elahi, 2009, Plasma phospholipid fatty acid profiles and their association with food intakes: results from a cross-sectional study within the European Prospective Investigation into Cancer and Nutrition, Am J Clin Nutr source
Not checked in the free run.
- Premisecitation
Phenol-Explorer is an exception, providing a comprehensive overview of human and animal metabolites formed from polyphenols.
“One exception is Phenol-Explorer, which gives a comprehensive overview of the human and animal metabolites formed from polyphenols (70).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [70] Rothwell, 2012, Phenol-Explorer 2.0: a major update of the Phenol-Explorer database integrating data on polyphenol metabolism and pharmacokinetics in humans and experimental animals, Database source
Not checked in the free run.
- Premisecitation
Metabolites such as S-methyl-L-cysteine sulfoxide and proline betaine, biomarkers of cruciferous vegetables and citrus fruit respectively, could be identified in NMR studies based on characteristic chemical shifts.
“Metabolites such as S-methyl-L-cysteine sulfoxide or proline betaine as biomarkers of cruciferous vegetables or citrus fruit, respectively, could be identified in NMR studies on the basis of their characteristic chemical shifts (Table 3) (80,84).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [80] Heinzmann, 2010, Metabolic profiling strategy for discovery of nutritional biomarkers: proline betaine as a marker of citrus consumption, Am J Clin Nutr source
Not checked in the free run.
- cites [84] Edmands, 2011, Identification of human urinary biomarkers of cruciferous vegetable consumption by metabonomic profiling, J Proteome Res source
Not checked in the free run.
- Interpretationreasoning
Because diet and lifestyle strongly affect the metabolome, any pending disease may lead to reverse causation in MWASs.
“Because diets and lifestyle strongly affect the metabolome, any pending disease may lead to reverse causation in MWASs; study design and interpretation must therefore take into account the common responses to early signs of disease in the population under study and other potential confounders.”
Quote in the paperSubstantial claim - Premisecitation
Recently developed bioinformatics approaches aim to narrow the number of possible candidate structures matching an unknown query metabolite by taking into account the chemical and biological background of the sample.
“Moreover, recently developed bioinformatics approaches aim to narrow the number of possible candidate structures that match with an unknown query metabolite by taking into account the chemical and biological background of the sample (164).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [164] Kirchmair, 2013, How do metabolites differ from their parent molecules and how are they excreted?, J Chem Inf Model source
Not checked in the free run.
- Premisecitation
Metabolomics applied to foods has enabled identification of many novel food constituents that are naturally present in food species or formed during food processing.
“The application of metabolomics to foods has allowed the identification of a large variety of novel food constituents that are either naturally present in the food species or formed during food processing (65,173,174).”
Quote in the paperSubstantial claim0 of 3 sources checked- cites [65] Iijima, 2008, Metabolite annotations based on the integration of mass spectral information, Plant J source
Not checked in the free run.
- cites [173] Lee, 2011, Metabolomic approach for determination of key volatile compounds related to beef flavor in glutathione-Maillard reaction products, Anal Chim Acta source
Not checked in the free run.
- cites [174] Mena, 2012, Rapid and comprehensive evaluation of (poly)phenolic compounds in pomegranate (Punica granatum L.) juice by UHPLC-MSn, Molecules source
Not checked in the free run.
- Premisecitation
The recent description of benzoxazinoids in rye helped identify some of their metabolites (2,4-dihydroxy-1,4-benzoxazin-3-one, 2-aminophenol sulfate, and hydroxylated phenylacetamides) in urinary profiles after rye bread consumption.
“As an example, the recent description of benzoxazinoids in rye facilitated the identification of some of their metabolites (2,4-dihydroxy-1,4-benzoxazin-3-one, 2-aminophenol sulfate, and hydroxylated phenylacetamides) in urinary metabolic profiles observed after rye bread consumption (86,114).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [86] Bondia-Pons, 2013, UPLC-QTOF/MS metabolic profiling unveils urinary changes in humans after a whole grain rye versus refined wheat bread intervention, Mol Nutr Food Res source
Not checked in the free run.
- cites [114] Beckmann, 2013, Hydroxylated phenylacetamides derived from bioactive benzoxazinoids are bioavailable in humans after habitual consumption of whole grain sourdough rye bread, Mol Nutr Food Res source
Not checked in the free run.
- Premisecitation
Three fatty acids-oleic acid, α-linolenic acid, and dihomo-γ-linolenic acid-were found to be associated with the risk of gastric cancer.
“Three fatty acids-oleic acid, a-linolenic acid, and di-homo-g-linolenic acid-were found to be associated with the risk of gastric cancer (169).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [169] Chajès, 2011, Plasma phospholipid fatty acid concentrations and risk of gastric adenocarcinomas in the European Prospective Investigation into Cancer and Nutrition (EPIC-EURGAST), Am J Clin Nutr source
Not checked in the free run.
- Premisecitation
In the INTERMAP study, untargeted NMR of more than 4000 urine specimens from geographically diverse populations showed that metabolite concentrations differed substantially between Asian and Western populations.
“The investigators showed that metabolite concentrations differed substantially between Asian and Western populations, suggesting important effects of diet and related risk factors, including the microbiota, on the risk of coronary artery disease and stroke.”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [59] Holmes, 2008, Human metabolic phenotype diversity and its association with diet and blood pressure, Nature source
Not checked in the free run.
- cites [166] Bictash, 2010, Opening up the “black box”: metabolic phenotyping and metabolome-wide association studies in epidemiology, J Clin Epidemiol source
Not checked in the free run.
- Interpretationreasoning
Better characterization of the chemicals in a given food should markedly improve understanding of food-derived exposures and their biological effects.
“This example shows that a better characterization of chemicals contained in a given food should markedly improve our understanding of food-derived exposures and their biological effects.”
Quote in the paperSubstantial claim - Premisecitation
In a cohort of more than 2000 cardiovascular disease patients, those in the highest quartile of plasma TMAO had a 2-fold risk of heart attack or stroke compared with those in the lowest quartile.
“Subjects from a cohort of .2000patients with cardiovascular disease, who were in the highest quartile for plasma TMAO concentrations, had a .2-foldrisk of a heart attack or stroke compared with subjects from the lowest quartile (108, 172).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [108] Koeth, 2013, Intestinal microbiota metabolism of l-carnitine, a nutrient in red meat, promotes atherosclerosis, Nat Med source
Not checked in the free run.
- cites [172] Tang, 2013, Intestinal microbial metabolism of phosphatidylcholine and cardiovascular risk, N Engl J Med source
Not checked in the free run.
- Interpretationcitation
Using accurate fragmentation mass data as input can enhance metabolite identification by selecting the most likely candidates based on similarities in fragmentation pathways and elemental formula with the unknown query metabolite, as exemplified by dietary polyphenols.
“In particular, the use of accurate fragmentation mass data as input can enhance the metabolite identification process by selecting the most likely candidates on the basis of similarities in fragmentation pathways and their readily assigned elemental formula with the unknown query metabolite as exemplified by dietary polyphenols (144).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [144] van der Hooft, 2011, Polyphenol identification based on systematic and robust high-resolution accurate mass spectrometry fragmentation, Anal Chem source
Not checked in the free run.
- Premisecitation
NMR spectroscopy and MS are the two essential tools for elucidating the structure of unknown metabolites in metabolomic studies.
“NMR spectroscopy and MS are the 2 essential tools for elucidation of the structure of unknown metabolites in metabolomic studies (140, 141).”
Quote in the paperNot a substantial claim0 of 2 sources checked - Premisecitation
Benzoxazinoid metabolites have documented anti-inflammatory, immunoregulatory, and appetite-suppressing properties.
“These benzoxazinoid metabolites certainly deserve further investigation as potential contributors to the health effects of rye products because of some documented anti-inflammatory, immunoregulatory, and appetite-suppressing properties (176).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [176] Adhikari, 2012, bioactive benzoxazinoids in rye bread are absorbed and metabolized in pigs, J Agric Food Chem source
Not checked in the free run.
- Premisecitation
Software tools such as MetFrag, MyCompoundID, MetiTree, and Mass Frontier can handle metabolite fragmentation data and permit library searches for candidates using in silico fragmentation predictions or comparisons to previously fragmented metabolites or standards.
“Software tools such as MetFrag, MyCompoundID, MetiTree, and Mass Frontier can handle metabolite fragmentation data and permit library searches for potential candidates using in silico fragmentation predictions of metabolites or comparisons to previously fragmented metabolites or standards (146, 153-155).”
Quote in the paperNot a substantial claim0 of 4 sources checked- cites [146] Li, 2013, MyCompoundID: using an evidence-based metabolome library for metabolite identification, Anal Chem source
Not checked in the free run.
- cites [153] Wolf, 2010, In silico fragmentation for computer assisted identification of metabolite mass spectra, BMC Bioinformatics source
Not checked in the free run.
- cites [154] Rojas-Cherto, 2012, Metabolite identification using automated comparison of high resolution MSn spectral trees, Anal Chem source
Not checked in the free run.
- cites [155] HighChem. Mass Frontier. Available from: http://www.highchem.com/index.php/massfrontier (cited 3 September 2013).
Not checked in the free run.
- Interpretationnone given
Major online chemical resources such as PubChem, KEGG, and ChemSpider contain limited information on human metabolites derived from food compounds.
“As described earlier, the major online chemical resources (typified by PubChem, Kyoto Encyclopedia of Genes and Genomes, and ChemSpider) contain limited information on human metabolites derived from food compounds.”
Quote in the paperSubstantial claim - Premisecitation
Despite many initiatives, publicly accessible spectral data are still scattered across numerous web-based databases, printed tables, Excel files, and scientific books.
“Despite the many initiatives to make spectral data sets available to the scientific community, the publicly accessible existing spectral data are still scattered over numerous Web-based (searchable) databases, printed tables in scientific journals, Excel files in supporting information, and scientific books (140, 149, 150).”
Quote in the paperNot a substantial claim0 of 3 sources checked- cites [140] van der Hooft, 2013, Structural elucidation of low abundant metabolites in complex sample matrices, Metabolomics source
Not checked in the free run.
- cites [149] Tohge, 2009, Web-based resources for mass-spectrometry-based metabolomics: a user’s guide, Phytochemistry source
Not checked in the free run.
- cites [150] Scalbert, 2011, Databases on food phytochemicals and their health promoting effects, J Agric Food Chem source
Not checked in the free run.
- Interpretationcitation
Strong correlations between regional dietary factors and fatty acid concentrations allowed food metabolome components to be used as predictor variables in a prospective investigation of gastric cancer in the EPIC cohort.
“Strong correlations between regional dietary factors and fatty acid concentrations allowed components of the food metabolome to be used as predictor variables in a prospective investigation of gastric cancer in the European Prospective Investigation into Cancer and Nutrition cohort.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [168] Saadatian-Elahi, 2009, Plasma phospholipid fatty acid profiles and their association with food intakes: results from a cross-sectional study within the European Prospective Investigation into Cancer and Nutrition, Am J Clin Nutr source
Not checked in the free run.
- Interpretationcitation
The INTERMAP metabolite differences suggest important effects of diet and related risk factors, including microbiota, on coronary artery disease and stroke risk.
“The investigators showed that metabolite concentrations differed substantially between Asian and Western populations, suggesting important effects of diet and related risk factors, including the microbiota, on the risk of coronary artery disease and stroke.”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [59] Holmes, 2008, Human metabolic phenotype diversity and its association with diet and blood pressure, Nature source
Not checked in the free run.
- cites [166] Bictash, 2010, Opening up the “black box”: metabolic phenotyping and metabolome-wide association studies in epidemiology, J Clin Epidemiol source
Not checked in the free run.
- Premisecitation
In the semitargeted approach, preliminary cross-sectional studies connect dietary records with the food metabolome to identify dietary biomarkers highly correlated with consumption of particular foods.
“In the semitargeted approach, preliminary cross-sectional studies are developed to connect dietary records with the food metabolome and thereby identify dietary biomarkers that are highly correlated with the consumption of particular foods.”
Quote in the paperSubstantial claim - Premisecitation
Follow-up targeted studies with choline challenge and microbiota characterization/manipulation showed that consuming foods rich in choline or carnitine (eggs, milk, liver, meat, fish) produced high TMAO concentrations in humans and animals that had the requisite microbiota for converting choline or carnitine to trimethylamine, the immediate TMAO precursor.
“Hazen and coworkers showed that consumption of foods rich in choline or carnitine, such as eggs, milk, liver, meat, or fish, produced high concentrations of TMAO in both humans and animals who possessed the requisite microbiota for metabolizing choline or carnitine to trimethylamine, the immediate precursor of TMAO (108, 171, 172).”
Quote in the paperSubstantial claim0 of 3 sources checked- cites [108] Koeth, 2013, Intestinal microbiota metabolism of l-carnitine, a nutrient in red meat, promotes atherosclerosis, Nat Med source
Not checked in the free run.
- cites [171] Wang, 2011, Gut flora metabolism of phosphatidylcholine promotes cardiovascular disease, Nature source
Not checked in the free run.
- cites [172] Tang, 2013, Intestinal microbial metabolism of phosphatidylcholine and cardiovascular risk, N Engl J Med source
Not checked in the free run.
- Premisecitation
More markers of food intake have been identified in MS-based metabolomic studies based on accurate mass and mass fragmentation spectra.
“More markers of food intake have been identified in MS-based metabolomic studies on the basis of their accurate mass and mass fragmentation spectra (142-144).”
Quote in the paperNot a substantial claim0 of 3 sources checked- cites [142] Draper, 2009, Metabolite signal identification in accurate mass metabolomics data with MZedDB, an interactive m/z annotation tool utilising predicted ionisation behaviour ’rules’, BMC Bioinformatics source
Not checked in the free run.
- cites [143] Draper, 2013, Flow infusion electrospray ionisation mass spectrometry for high throughput, non-targeted metabolite fingerprinting: a review, Metabolomics source
Not checked in the free run.
- cites [144] van der Hooft, 2011, Polyphenol identification based on systematic and robust high-resolution accurate mass spectrometry fragmentation, Anal Chem source
Not checked in the free run.
- Interpretationcitation
Given thousands of potentially important exposures, MWASs and exposome-wide association studies move away from knowledge-driven designs focused on a priori hypotheses toward data-driven designs using untargeted or semitargeted sets of analytes.
“Given the thousands of potentially important exposures to consider, MWASs and exposome-wide association studies move away from knowledge-driven designs that focus on a priori hypotheses about particular exposures toward data-driven designs using untargeted or semitargeted sets of analytes (167).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [167] Rappaport, 2012, Biomarkers intersect with the exposome, Biomarkers source
Not checked in the free run.
- Interpretationreasoning
Major progress in assessing complex dietary exposures at the individual level is expected from these biomarkers.
“Major progress in assessing complex dietary exposures at the individual level is expected from these biomarkers.”
Quote in the paperNot a substantial claim - Premisecitation
New metabolites formed from nutrients and other food constituents are continuously being identified, even for widely studied compounds.
“new metabolites formed from nutrients and other food constituents are continuously being identified, even for widely studied compounds (101, 179).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [101] Stanstrup, 2013, Intakes of whey protein hydrolysate and whole whey proteins are discriminated by LC-MS metabolomics, Metabolomics
Not checked in the free run.
- cites [179] Johnson, 2012, Novel metabolites and roles for alpha-tocopherol in humans and mice discovered by mass spectrometry-based metabolomics, Am J Clin Nutr source
Not checked in the free run.
- Premisecitation
Metabolomics is already used to characterize multicomponent drugs and herbal medicines.
“the approach is already being used in the characterization of multicomponent drugs and herbal medicines (178).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [178] Lan, 2013, Towards polypharmacokinetics: pharmacokinetics of multicomponent drugs and herbal medicines using a metabolomics approach, Evid Based Complement Alternat Med source
Not checked in the free run.
- Interpretationreasoning
Recent analyses of the food metabolome with modern analytic and bioinformatic tools have shown that human biospecimens contain considerable information on dietary exposure.
“Recent analyses of the food metabolome with modern analytic and bioinformatic tools have shown the considerable extent of information on dietary exposure contained in human biospecimens.”
Quote in the paperSubstantial claim - Premisecitation
Databases specific to the food metabolome are still largely missing, except for Phenol-Explorer, a database of all known polyphenol metabolites.
“Databases specific for the food metabolome are still largely missing apart from Phenol-Explorer, a database on all known polyphenol metabolites (70).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [70] Rothwell, 2012, Phenol-Explorer 2.0: a major update of the Phenol-Explorer database integrating data on polyphenol metabolism and pharmacokinetics in humans and experimental animals, Database source
Not checked in the free run.
- Interpretationreasoning
Some proof-of-principle studies have established that metabolomic approaches can identify novel dietary biomarkers.
“Some proof-of-principle studies have established the feasibility of metabolomic approaches to identify novel dietary biomarkers and suggest that these approaches could greatly expand the field of molecular nutritional epidemiology and contribute to future progress in nutrition research.”
Quote in the paperSubstantial claim - Premisecitation
After cocoa intake, plasma epicatechin metabolite concentrations paralleled increases in plasma nitroso species concentrations and the vascular response.
“Epicatechin metabolite concentrations in plasma after cocoa intake paralleled the increase of plasma nitroso species concentrations and the vascular response (187).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [187] Schroeter, 2006, (-)-Epicatechin mediates beneficial effects of flavanol-rich cocoa on vascular function in humans, Proc Natl Acad Sci USA source
Not checked in the free run.
- Premisecitation
Various enzymes involved in biotransformation of xenobiotics and dietary compounds show genetic polymorphisms.
“Various enzymes involved in the biotransformation of xenobiotics and dietary compounds also show genetic polymorphisms (183, 184).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [183] Lampe, 2009, Interindividual differences in response to plant-based diets: implications for cancer risk, Am J Clin Nutr source
Not checked in the free run.
- cites [184] Reszka, 2006, Genetic polymorphism of xenobiotic metabolising enzymes, diet and cancer susceptibility, Br J Nutr
Not checked in the free run.
- May combine two claims. 48
- Classified as probably not a substantial claim. 32
- The quote only partly states this claim. 1
May combine two claims.
FindingreasoningMany proposed biomarkers in Table 3 (marked with asterisks) have not been fully validated with proper chemical standards because such standards are often not commercially available.
“It is important to point out that the identities of many of the proposed biomarkers in Table 3 (marked with an asterisk) have not been fully validated with proper chemical standards because these standards are often not commercially available.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationMisclassification of subjects by dietary intake can influence observed associations between dietary exposures and disease outcomes and underlies inconsistencies in nutritional epidemiology.
“The resulting misclassification of subjects, especially when sorting them according to dietary intake, can influence observed associations between dietary exposures and disease outcomes and underlies inconsistencies in published findings in the field of nutritional epidemiology (12).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [12] Marshall, 1999, Diet and health risk: risk patterns and disease-specific associations, Am J Clin Nutr source
Not checked in the free run.
May combine two claims.
InterpretationreasoningThe food metabolome is highly complex and highly variable.
“The food metabolome is therefore highly complex and also highly variable.”
Quote in the paperSubstantial claimMay combine two claims.
PremisecitationFoods eaten by humans contain roughly 25,000 compounds, and most of these are further metabolized in the human body.
“The various foods consumed by humans contain .25,000compounds, most of them being further metabolized in the human body (9).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [9] Wishart, 2013, HMDB 3.0—the Human Metabolome Database in 2013, Nucleic Acids Res
Not checked in the free run.
May combine two claims.
PremisecitationSelf-reported dietary assessment methods contain random and systematic errors, including recall bias and difficulty in assessing portion sizes.
“However, a number of random and systematic errors are inherent in such methods, including recall bias and difficulty in assessing portion sizes (11).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [11] Bingham, 2007, Epidemiologic assessment of sugars consumption using biomarkers: comparisons of obese and nonobese individuals in the European Prospective Investigation of Cancer Norfolk, Cancer Epidemiol Biomarkers Prev source
Not checked in the free run.
May combine two claims.
PremisecitationIsothiocyanates and acrylamide form adducts with blood albumin and hemoglobin, with half-lives of 3 to 8 weeks, and may be used as longer-term biomarkers.
“Some dietary compounds such as isothiocyanates and acrylamide also form adducts with blood albumin and hemoglobin (37,38), with half-lives varying between 3 and 8 wk, and may be used as longer-term biomarkers.”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [37] Kumar, 2010, Determination of new biomarkers to monitor the dietary consumption of isothiocyanates, Biomarkers source
Not checked in the free run.
- cites [38] Outzen, 2011, Dietary determinants for Hb-acrylamide and Hb-glycidamide adducts in Danish non-smoking women, Br J Nutr source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationUp to 200,000 different metabolites are estimated to occur in the plant kingdom, and combinations of several hundreds of secondary metabolites generally characterize each edible plant.
“Up to 200,000 different metabolites are estimated to occur in the plant kingdom, and combinations of several hundreds of secondary metabolites generally characterize each edible plant (6,64,65).”
Quote in the paperNot a substantial claim0 of 3 sources checked- cites [6] Manach, 2009, The complex links between dietary phytochemicals and human health deciphered by metabolomics, Mol Nutr Food Res source
Not checked in the free run.
- cites [64] Fiehn, 2002, Metabolomics—the link between genotypes and phenotypes, Plant Mol Biol source
Not checked in the free run.
- cites [65] Iijima, 2008, Metabolite annotations based on the integration of mass spectral information, Plant J source
Not checked in the free run.
May combine two claims.
PremisecitationProline betaine and lycopene are well-established biomarkers for citrus fruit and tomato products, respectively.
“Proline betaine and lycopene are well-established biomarkers for citrus fruit and tomato products, respectively (44,45).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [44] Lloyd, 2011, Proline betaine and its biotransformation products in fasting urine samples are potential biomarkers of habitual citrus fruit consumption, Br J Nutr source
Not checked in the free run.
- cites [45] Al-Delaimy, 2005, Plasma carotenoids as biomarkers of intake of fruits and vegetables: individual-level correlations in the European Prospective Investigation into Cancer and Nutrition (EPIC), Eur J Clin Nutr source
Not checked in the free run.
Probably not a substantial claim: may not pass S4 (based). May combine two claims.
Premisenone givenEssential amino acids, essential fatty acids, most vitamins, and minerals cannot be produced by humans and must originate from external dietary sources.
“The possible exceptions are the essential amino acids, essential fatty acids along with most vitamins, and minerals, which cannot be produced by humans and must originate from external dietary sources.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisereasoningIntermediary metabolites formed by digestion of lipids, polysaccharides, and proteins are common to all living organisms and identical to human endogenous metabolites, and generally cannot be used as dietary biomarkers because of their common identity and the impossibility of tracing their dietary origin.
“Most of these compounds are common to all living organisms and identical to human endogenous metabolites.They cannot generally be used as dietary biomarkers because of their common identity and the impossibility to trace their dietary origin.”
Quote in the paperSubstantial claimMay combine two claims.
PremisecitationThe Folin assay, commonly used to estimate total polyphenols in foods, has been applied to urine to compare polyphenol intake, but such use may be inappropriate because of interfering reducing metabolites.
“The Folin assay, commonly used to estimate total polyphenols in foods (46), has also been applied to urine samples to compare polyphenol intake (47), but such use may be inappropriate because of the presence of interfering reducing metabolites in such complex biological matrices (46).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [46] Scalbert, 2005, Dietary polyphenols and the prevention of diseases, Crit Rev Food Sci Nutr source
Not checked in the free run.
- cites [47] Medina-Remón, 2011, Total polyphenol excretion and blood pressure in subjects at high cardiovascular risk, Nutr Metab Cardiovasc Dis source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationMore than 300 empirical rules allow prediction of the fate of metabolites based on their chemical structure.
“In fact, there are .300different empirical rules that allow one to predict the fate of metabolites on the basis of their chemical structure (69).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [69] Langowski, 2002, Computer systems for the prediction of xenobiotic metabolism, Adv Drug Deliv Rev source
Not checked in the free run.
May combine two claims.
PremisecitationLipophilic markers such as carotenoids and lipids, and erythrocyte-associated biomarkers such as folate and fatty acids, have longer half-lives of weeks to months.
“Lipophilic markers (carotenoids, lipids) (36) or biomarkers associated with erythrocytes (folate, fatty acids) (29) have longer half-lives (week to month) because of the equilibrium of biomarkers between blood and fatty tissues, or because of their integration into erythrocytes.”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [36] Burri, 2001, Serum carotenoid depletion follows first-order kinetics in healthy adult women fed naturally low carotenoid diets, J Nutr source
Not checked in the free run.
- cites [29] Crews, 2001, A critical assessment of some biomarker approaches linked with dietary intake, Br J Nutr source
Not checked in the free run.
May combine two claims.
PremisecitationDietary biomarkers include natural food constituents and also food additives such as iodine in milk and contaminants such as polychlorinated biphenyls in fatty fish.
“Dietary biomarkers not only include natural food constituents but also certain food additives such as iodine in milk (26) or food contaminants such as polychlorinated biphenyls in fatty fish (27).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [26] Brantsaeter, 2009, Evaluation of urinary iodine excretion as a biomarker for intake of milk and dairy products in pregnant women in the Norwegian Mother and Child Cohort Study (MoBa), Eur J Clin Nutr source
Not checked in the free run.
- cites [27] Turunen, 2010, Dioxins, polychlorinated biphenyls, methyl mercury and omega-3 polyunsaturated fatty acids as biomarkers of fish consumption, Eur J Clin Nutr source
Not checked in the free run.
May combine two claims.
PremisecitationMicrobial metabolites include short-chain fatty acids, secondary bile acids, protein and amino acid metabolites, and plant polyphenol metabolites.
“These microbial metabolites include short-chain fatty acids, secondary bile acids, protein and amino acid metabolites, as well as plant polyphenol metabolites (67).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [67] Nicholson, 2012, Host-gut microbiota metabolic interactions, Science source
Not checked in the free run.
May combine two claims.
PremisecitationPolyphenols, alkylresorcinols, and amino acids have half-lives that do not exceed 24 hours.
“Some of the biomarkers listed in Table 1 have half-lives that do not exceed 24 h [polyphenols, alkylresorcinols, and amino acids (34,35)].”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [34] Manach, 2005, Bioavailability and bioefficacy of polyphenols in humans. I. Review of 97 bioavailability studies, Am J Clin Nutr source
Not checked in the free run.
- cites [35] Söderholm, 2009, Plasma pharmacokinetics of alkylresorcinol metabolites: new candidate biomarkers for whole-grain rye and wheat intake, Am J Clin Nutr source
Not checked in the free run.
May combine two claims.
PremisecitationNoticeable differences in human metabolomes depend strongly on diet, sex, health status, genetics, kinetics, physiology, and age, with diet being most important.
“noticeable differences in human metabolomes could be detected that appeared to depend strongly on diet, sex, health status, genetics, kinetics, physiology, and age-with diet being most important (59)(60)(61)(62).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites (59)(60)(61)(62)
Not checked in the free run.
May combine two claims.
PremisecitationThe yield of phase I/II reactions is often very high, and host-transformed metabolites retain many features of their parent compounds.
“The yield of phase I/II reactions are often very high (68,71), and host-transformed metabolites retain many of the features of their parent compounds.”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [68] Testa, 2012, Foundation review: reactions and enzymes in the metabolism of drugs and other xenobiotics, Drug Discov Today source
Not checked in the free run.
- cites [71] Silberberg, 2006, The bioavailability of polyphenols is highly governed by the capacity of the intestine and of the liver to secrete conjugated metabolites, Eur J Nutr source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Premisenone givenThe human body maintains a complex defense system of dozens of enzymes and membrane transporters to recognize foreign and potentially toxic chemicals and neutralize them by rapid biotransformation and/or elimination.
“The human body maintains a complex defense system consisting of dozens of enzymes and membrane transporters to recognize these foreign and potentially toxic chemicals and to neutralize them by rapid biotransformation and/or elimination.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Premisenone givenFood compounds that are not useful for basic metabolism or that do not correspond to familiar endogenous metabolites are treated as foreign or as xenobiotics.
“Food compounds that are not useful for basic metabolism or that do not correspond to familiar endogenous metabolites are treated as”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationVitamin C and selenium in erythrocyte glutathione peroxidase show saturable effects and may not be suitable at high exposure levels.
“Biomarkers such as vitamin C or selenium in erythrocyte glutathione peroxidase show saturable effects and may not be suitable for use at high levels of exposure (29,42).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [29] Crews, 2001, A critical assessment of some biomarker approaches linked with dietary intake, Br J Nutr source
Not checked in the free run.
- cites [42] Levine, 1996, Vitamin C pharmacokinetics in healthy volunteers: evidence for a recommended dietary allowance, Proc Natl Acad Sci USA source
Not checked in the free run.
Classified as probably not a substantial claim. May combine two claims.
Premisenone givenFood constituents can be metabolized in three ways: digestion in the mouth, stomach, and small intestine; transformation by host tissues; or processing by the gut microbiota.
“Food constituents can be metabolized in 3 different ways: 1) they can be digested in the mouth, stomach, and small intestine into simple nutrients that can be absorbed through the gut barrier; 2) they can be further transformed by host tissues, especially the liver and kidney; or 3) they can be processed by the gut microbiota in the large intestine.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Premisenone givenBiotransformation consists of phase I and phase II reactions, both of which occur primarily in the liver, kidney, and intestine.
“Classically, the biotransformation process consists of 2 types of chemical reactions, phase I and phase II transformations, both of which occur primarily in the liver, kidney, and intestine.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationThe human gut contains more than 1000 different species of microbes, giving an enormous diversity of enzymatic processes that act on food-derived compounds.
“Microbes have a very different set of enzymes from mammals, and given that there are .1000different species of microbes in the human gut (72) there is an enormous diversity of enzymatic processes that act on foodderived compounds.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [72] Peris-Bondia, 2011, The active human gut microbiota differs from the total microbiota, PLoS ONE source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe human metabolome contains at least 50,000 different detectable compounds.
“Minimally, the human metabolome contains 50,000 different detectable compounds (9,63), but as instrument sensitivity and separation technologies improve, this number is expected to increase.”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [9] Wishart, 2013, HMDB 3.0—the Human Metabolome Database in 2013, Nucleic Acids Res
Not checked in the free run.
- cites [63] Smith, 2005, METLIN—a metabolite mass spectral database, Ther Drug Monit source
Not checked in the free run.
May combine two claims.
PremisecitationDietary biomarker concentrations can be altered by genetic factors, physiologic or health status, dietary factors, and lifestyle factors.
“They may be altered because of possible interactions with genetic factors, physiologic or health status (ie, age or obesity) (30), dietary factors such as fats for lipophilic biomarkers (31), and lifestyle factors such as alcohol intake or smoking (32).”
Quote in the paperSubstantial claim0 of 3 sources checked- cites [30] Vioque, 2007, Plasma concentrations of carotenoids and vitamin C are better correlated with dietary intake in normal weight than overweight and obese elderly subjects, Br J Nutr source
Not checked in the free run.
- cites [31] Brown, 2004, Carotenoid bioavailability is higher from salads ingested with full-fat than with fat-reduced salad dressings as measured with electrochemical detection, Am J Clin Nutr source
Not checked in the free run.
- cites [32] Albanes, 1997, Effects of supplemental beta-carotene, cigarette smoking, and alcohol consumption on serum carotenoids in the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study, Am J Clin Nutr source
Not checked in the free run.
Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
InterpretationreasoningIn explorative science, there is no fixed rule for the acceptability level of the false discovery rate, and any level from 5% to 50% may be useful depending on further data analysis steps.
“In explorative science there is no fixed rule for the acceptability level of the FDR, and any level from 5% to 50% may be useful, depending on further data analysis steps.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Premisenone givenMetabolite identification in metabolomic studies relies on comparing generated spectra with those in curated metabolite databases.
“Metabolite identification in metabolomic studies relies on the comparison of generated spectra with those in curated metabolite databases.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Premisenone givenThe gut microbiota processes indigestible carbohydrates through fermentative pathways yielding short-chain fatty acids such as butyric acid and propionic acid.
“The gut microbiota also processes indigestible carbohydrates through a variety of fermentative pathways yielding short-chain fatty acids such as butyric acid and propionic acid.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Interpretationnone givenMultiple variables can substantially affect the final data set in any experimentally based analytic method.
“As with any experimentally based analytic method, multiple variables can substantially affect the final data set.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationnone givenUntargeted metabolomics provides wider coverage and is likely to reveal new metabolites in biofluids and tissues.
“In principle, untargeted metabolomics provides a wider coverage and is likely to show the presence of new metabolites in biofluids and tissues.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Premisenone givenPhenolic acids can be further conjugated to glycine as in hippurate.
“These phenolic acids can be further conjugated to glycine as in hippurate.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationNMR is robust, nondestructive, and quantitative but has relatively low sensitivity, limiting its coverage of the food metabolome to predominant nutrients, sugars, and microbial metabolites at millimolar to micromolar concentrations.
“Briefly, NMR is robust, nondestructive, and quantitative but has a relatively low sensitivity, which narrows its coverage of the food metabolome to predominant nutrients, sugars, and microbial metabolites present at millimolar to micromolar concentrations.”
Quote in the paperNot a substantial claim0 of 3 sources checked- cites [111] Theodoridis, 2008, LC-MS-based methodology for global metabolite profiling in metabonomics/metabolomics, Trends Analyt Chem source
Not checked in the free run.
- cites [112] Scalbert, 2009, Mass-spectrometry-based metabolomics: limitations and recommendations for future progress with particular focus on nutrition research, Metabolomics source
Not checked in the free run.
- cites [113] Issaq, 2009, Analytical and statistical approaches to metabolomics research, J Sep Sci source
Not checked in the free run.
May combine two claims.
InterpretationcitationSupervised multivariate analysis is commonly the next step in many data analysis methods but has a strong tendency to overfit the data.
“Supervised multivariate analysis is commonly the next step in many data analysis methods but has a strong tendency to overfit the data.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThere are many supervised methods, with partial least-squares discriminant analysis (PLS-DA) or its variants being the most commonly used for comparing two groups.
“There are a large number of supervised methods (120, 127), with the most commonly used analysis for comparing 2 groups being partial least-squares discriminant analysis (PLS-DA) (132) or one of its several variants.”
Quote in the paperNot a substantial claim0 of 3 sources checked- cites [120] Sugimoto, 2012, bioinformatics tools for mass spectroscopy-based metabolomic data processing and analysis, Current Bioinformatics source
Not checked in the free run.
- cites [127] Worley, 2013, Utilities for quantifying separation in PCA/PLS-DA scores plots, Anal Biochem source
Not checked in the free run.
- cites [132] Wold, 1983, The multivariate calibration problem in chemistry solved by the PLS methods source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
InterpretationreasoningIt is crucial to align different sample profiles, which do not match exactly because of small variations in retention times, masses, or chemical shifts.
“It is crucial to align the different sample profiles, which do not match exactly because of small variations in retention times, masses, or chemical shifts.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationThese steps include data preprocessing, alignment, normalization, and signal correction, followed by statistical analysis.
“These include data preprocessing, data alignment, data normalization, and signal correction followed by the analysis through various statistical methods.”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [119] Katajamaa, 2007, Data processing for mass spectrometry-based metabolomics, J Chromatogr A source
Not checked in the free run.
- cites [120] Sugimoto, 2012, bioinformatics tools for mass spectroscopy-based metabolomic data processing and analysis, Current Bioinformatics source
Not checked in the free run.
May combine two claims.
Interpretationnone givenFeatures associated with a pattern can be shown by loadings in a PCA plot, but PCA is generally not well suited to identify the most prominent part of the pattern.
“The features associated with any pattern can be shown by the loadings in a PCA plot; however, PCA is generally not well suited to identify the most prominent part of the pattern.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationCertain microbial metabolites can be useful as food biomarkers, although there is a complex relation between the food source, the predominant gut microbial species, and the resulting food metabolites.
“Certain microbial metabolites can be useful as food biomarkers, although there is a complex relation between the food source, the predominant gut microbial species, and the resulting food metabolites (73).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [73] Moco, 2012, A metabolomics view on gut microbiome modulation by polyphenol-rich foods, J Proteome Res source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Premisenone givenThe food metabolome comprises much greater chemical diversity than any other part of the metabolome.
“First, it comprises a much greater chemical diversity than any other part of the metabolome (see Food metabolome and metabolite databases section).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Interpretationnone givenThe main current limitation of MS is the challenging and burdensome structural elucidation of detected ions.
“The main current limitation of MS is the very challenging and burdensome task of the structural elucidation of the detected ions (see below).”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationDirect flow injection-MS has been used and offers the advantage of high-throughput analysis required for large-scale epidemiologic studies.
“Direct flow injection-MS has also been used (82,114), which offers the advantage of high-throughput analysis, as would be required for large-scale epidemiologic studies.”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [82] Lloyd, 2011, Use of mass spectrometry fingerprinting to identify urinary metabolites after consumption of specific foods, Am J Clin Nutr source
Not checked in the free run.
- cites [114] Beckmann, 2013, Hydroxylated phenylacetamides derived from bioactive benzoxazinoids are bioavailable in humans after habitual consumption of whole grain sourdough rye bread, Mol Nutr Food Res source
Not checked in the free run.
May combine two claims.
PremisereasoningMS is the most sensitive technique and the only method able to cover nonnutrient food metabolome metabolites occurring at low concentrations in biological samples.
“MS is by far the most sensitive technique and the only method able to cover the nonnutrient metabolites of the food metabolome occurring at low concentrations in biological samples.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing). May combine two claims.
Interpretationnone givenThe field of metabolomics is rich with data analysis options, and the future challenge is to optimally apply these to food metabolomic studies.
“Overall, the field of metabolomics is rich with data analysis options, and the challenge in the future will be to optimally apply these to food metabolomic studies.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationcitationUsing food-frequency questionnaires may directly identify biomarkers of habitual dietary exposure, but their lower accuracy and smaller number of documented foods may limit their usefulness for discovery studies.
“The use of food-frequency questionnaires may directly lead to the identification of biomarkers of habitual dietary exposure, but the lower accuracy and lower number of foods documented may limit their value for such discovery studies (105).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [105] May, 2013, Metabolomic profiling of urine: response to a randomised, controlled feeding study of select fruits and vegetables, and application to an observational study, Br J Nutr source
Not checked in the free run.
May combine two claims.
InterpretationreasoningThe predominance of urine samples is partly due to higher concentrations of food-derived metabolites in urine than in blood and the absence of interfering proteins.
“The reason for this is partly technical because of the higher concentrations of food-derived metabolites in urine as compared with blood and because of the lack of interfering proteins.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
InterpretationreasoningUnsupervised multivariate analysis provides an objective assessment of principal patterns in the data set, such as intake or no intake of a specific food component or diet.
“This provides an objective assessment of the principal patterns in the data set (eg, intake or no intake of a specific food component or diet).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing). May combine two claims.
Interpretationnone givenStatistical analysis of untargeted metabolomic data is often an initial step in biomarker discovery and should not be confused with hypothesis testing because there is no a priori hypothesis.
“Statistical analysis of untargeted metabolomic data is often an initial step in the biomarker discovery process that should not be confused with hypothesis testing, because there is no a priori hypothesis.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationVariables affecting the final data set include sample preparation mode, chromatography method, detection mode, and choice of data reduction methods.
“These include the mode of sample preparation, method of chromatography, mode of detection, and the choice of data reduction methods (116, 117).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [116] Barri, 2012, Metabolic fingerprinting of high-fat plasma samples processed by centrifugation- and filtration-based protein precipitation delineates significant differences in metabolite information coverage, Anal Chim Acta source
Not checked in the free run.
- cites [117] Gika, 2010, Does the mass spectrometer define the marker? A comparison of global metabolite profiling data generated simultaneously via UPLC-MS on two different mass spectrometers, Anal Chem source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe metabolic profile of raw data from spectrometric analysis of biological samples can be analyzed in several steps.
“The metabolic profile of raw data generated by the spectrometric analysis of biological samples can be analyzed in several steps (119, 120).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [119] Katajamaa, 2007, Data processing for mass spectrometry-based metabolomics, J Chromatogr A source
Not checked in the free run.
- cites [120] Sugimoto, 2012, bioinformatics tools for mass spectroscopy-based metabolomic data processing and analysis, Current Bioinformatics source
Not checked in the free run.
May combine two claims.
InterpretationreasoningIon suppression effects and inability to discriminate isomers limit the use of direct flow injection-MS.
“However, ion suppression effects, due to inefficient ionization of certain ions in complex matrices and the inability to discriminate between isomers, limit the use of this approach.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationMultivariate analysis is most commonly used for explorative analysis of metabolic profiling data.
“Multivariate analysis is most commonly used for explorative analysis of metabolic profiling data (127).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [127] Worley, 2013, Utilities for quantifying separation in PCA/PLS-DA scores plots, Anal Biochem source
Not checked in the free run.
May combine two claims.
InterpretationreasoningIn cross-sectional studies, the large contrast seldom applies, but approximate dose-response relations from food-frequency questionnaires may help identify food intake biomarkers.
“In cross-sectional studies this large contrast seldom applies, but approximate dose-response relations from food-frequency questionnaires may help in the identification of food intake biomarkers.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationIn dietary intervention studies with single foods, the contrast for a good biomarker can be large, sometimes infinite, allowing robust work with small sample sets and discrimination of potential intake biomarkers from subtle changes in endogenous metabolites.
“In dietary intervention studies with single foods, the contrast observed for a good biomarker can be large, sometimes even infinite, making it possible to work robustly with small sample sets and discriminate potential intake biomarkers from more subtle changes in endogenous metabolites (126).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [126] Kristensen, 2012, LC-MS metabolomics top-down approach reveals new exposure and effect biomarkers of apple and apple-pectin intake, Metabolomics source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisenone givenUnlike univariate analysis, multivariate analysis can be performed unsupervised, without group assignment information.
“As opposed to univariate analysis, multivariate analysis can be performed in an unsupervised manner (ie, without including information on group assignment for the analysis).”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningThese discriminatory biomarkers point to dietary sources, sometimes with cometabolism by gut microbiota.
“All of these discriminatory biomarkers point to dietary sources, sometimes in combination with cometabolism by gut microbiota.”
Quote in the paperSubstantial claim- Rests on an assumption: Alanine is associated with diets that emphasize animal products rather than vegetables.
Probably not a substantial claim: may not pass S3 (load-bearing).
InterpretationreasoningAlthough not specific to the food metabolome, these resources are useful for metabolite identification because fragmentation data or NMR signals of known metabolites can be compared with an unknown query to gain structural information.
“Although they are not specific to the food metabolome, these resources are useful for metabolite identification because fragmentation data or NMR signals of known metabolites can be compared with the unknown query to gain structural information.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
InterpretationcitationMWASs can be regarded as a special case of the exposome-wide association study, which investigates disease associations with all exposures to low- and high-molecular-weight compounds.
“In fact, MWASs can be regarded as a special case of the exposome-wide association study, which investigates disease associations with all exposures to low-and high-molecular-weight compounds (167).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [167] Rappaport, 2012, Biomarkers intersect with the exposome, Biomarkers source
Not checked in the free run.
May combine two claims.
PremisecitationRecently, many food compounds have been added to the HMDB, enabling searches based on accurate masses, but it currently contains few mass fragmentation spectra useful for food metabolite identification.
“Recently, a large number of food compounds have been added to the HMDB, which makes searches on the basis of their accurate masses possible (9); however, to date it contains few mass fragmentation spectra useful for food metabolite identification.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [9] Wishart, 2013, HMDB 3.0—the Human Metabolome Database in 2013, Nucleic Acids Res
Not checked in the free run.
May combine two claims.
PremisereasoningThe untargeted metabolomic approach does not presuppose which exposure sources cause a given disease; it compares comprehensive metabolomic profiles between cases and controls to find discriminating exposure biomarkers.
“The alternative untargeted approach makes no a priori assumptions regarding sources of exposure that are causal for a particular disease but instead relies on comparisons of comprehensive profiles of metabolomic features between cases and controls to find discriminating exposure biomarkers.”
Quote in the paperSubstantial claimMay combine two claims. The quote only partly states this claim.
PremisecitationThree highly discriminating biomarkers were identified in the INTERMAP study: alanine was directly correlated with blood pressure, while formate and hippurate were inversely correlated with blood pressure.
“biomarkers were identified, namely alanine, which was directly correlated with blood pressure, and formate and hippurate, both of which were inversely correlated with blood pressure.”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [59] Holmes, 2008, Human metabolic phenotype diversity and its association with diet and blood pressure, Nature source
Not checked in the free run.
- cites [166] Bictash, 2010, Opening up the “black box”: metabolic phenotyping and metabolome-wide association studies in epidemiology, J Clin Epidemiol source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Interpretationnone givenThese associations were tentatively explained by either different amounts of dietary intake or differential fatty acid metabolism in cases and controls.
“These associations were tentatively explained by either different amounts of dietary intake or differential fatty acid metabolism in cases and controls.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationSciFinder is currently the most comprehensive and best-curated commercial chemical database, including many food metabolome compounds collected from the literature.
“The most comprehensive and best-curated chemical (commercial) database is currently SciFinder, which includes many food metabolome compounds collected from the literature (151).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [151] American Chemical Society. SciFinder. Available from: https://scifinder.cas.org (cited 3 September 2013).
Not checked in the free run.
May combine two claims.
PremisecitationThe Human Metabolome Database has recently expanded to include compounds found in common foods because, before metabolism, these compounds are also present in the human body.
“The human metabolome database has recently expanded to include compounds found in common foods because these are, at least initially before metabolism, also present within the human body (9).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [9] Wishart, 2013, HMDB 3.0—the Human Metabolome Database in 2013, Nucleic Acids Res
Not checked in the free run.
May combine two claims.
PremisecitationGenome-wide analysis studies have identified loci associated with variations in endogenous metabolite concentrations, and many of these genes coded for metabolic enzymes.
“A number of loci associated with variations in the concentration of endogenous metabolites could be identified in genome-wide analysis studies, and many of these genes were coding for metabolic enzymes (180-182).”
Quote in the paperNot a substantial claim0 of 3 sources checked- cites [180] Suhre, 2011, Human metabolic individuality in biomedical and pharmaceutical research, Nature source
Not checked in the free run.
- cites [181] Illig, 2010, A genome-wide perspective of genetic variation in human metabolism, Nat Genet source
Not checked in the free run.
- cites [182] Kettunen, 2012, Genome-wide association study identifies multiple loci influencing human serum metabolite levels, Nat Genet source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe Metabolomics Standards Initiative launched by the Metabolomics Society has already had significant impact on reporting formats in metabolomics.
“The Metabolomics Standards Initiative (MSI) launched by the Metabolomics Society is an example of such an initiative, and the MSI has already had significant impact on reporting formats in metabolomics (110, 188).”
Quote in the paperNot a substantial claim0 of 2 sources checkedMay combine two claims.
PremisecitationMany studies have been conducted with oranges, but broad coverage of all citrus and many other fruits, as well as kinetic studies, were necessary to interpret proline betaine as a short-term marker of citrus dominated by orange and orange juice intake.
“For example, many studies have been conducted with oranges (Table 3), but a broad coverage of all citrus and many other fruit as well as kinetic studies have been necessary to interpret proline betaine as a short-term marker of citrus that is dominated by orange and orange juice intake (80).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [80] Heinzmann, 2010, Metabolic profiling strategy for discovery of nutritional biomarkers: proline betaine as a marker of citrus consumption, Am J Clin Nutr source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationSome commercial software exists for the pharmaceutical area and covers many phase I and II reactions.
“Some commercial software exists for the pharmaceutical area (192,193) and covers many phase I and II reactions.”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [192] T’Jollyn, 2011, Evaluation of three state-of-the-art metabolite prediction software packages (Meteor, MetaSite, and StarDrop) through independent and synergistic use, Drug Metab Dispos source
Not checked in the free run.
- cites [193] Piechota, 2013, pragmatic approaches to using computational methods to predict xenobiotic metabolism, J Chem Inf Model source
Not checked in the free run.
Probably not a substantial claim: may not pass S2 (checkable).
InterpretationreasoningThese biomarkers should also significantly contribute to better understanding of the complex interactions between diet and human health.
“They should also significantly contribute to a better understanding of the complex interactions between diet and human health.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe Metabolomics Standards Initiative has already issued several reference articles on good practice for metabolomic research.
“The MSI, initiated by the Metabolomics Society, has already issued several reference articles on good practice for metabolomic research.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [189] Metabolomics Standards Initiative. Homepage. Available from: http://msi-workgroups.sourceforge.net/ (cited 3 September 2013).
Not checked in the free run.
May combine two claims.
InterpretationreasoningMetabolomic approaches could greatly expand molecular nutritional epidemiology and contribute to future progress in nutrition research.
“Some proof-of-principle studies have established the feasibility of metabolomic approaches to identify novel dietary biomarkers and suggest that these approaches could greatly expand the field of molecular nutritional epidemiology and contribute to future progress in nutrition research.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationSeveral training workshops on metabolomics and nutrition were supported by the Nutrigenomics Organization.
“Several training workshops on metabolomics and nutrition were supported by the Nutrigenomics Organization (112).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [112] Scalbert, 2009, Mass-spectrometry-based metabolomics: limitations and recommendations for future progress with particular focus on nutrition research, Metabolomics source
Not checked in the free run.
The paper relies on this without support.
The food metabolome spans a huge range of concentrations, from picomolar or nanomolar for some contaminants or phytochemical metabolites to millimolar for nutrients such as sugars.
“A second feature of the food metabolome is the huge range of concentrations, from picomolar or nanomolar concentrations for some contaminants or phytochemical metabolites to millimolar concentrations for nutrients such as sugars.”
The paper relies on this without support.
Many components of the food metabolome are unknown.
“Third, many components of the food metabolome are unknown.”
The paper relies on this without support.
The metabolism of a large proportion of nonnutrients in humans has never been studied, and the chemical structures of their circulating metabolites have not been identified.
“Indeed, the metabolism for a large proportion of nonnutrients in humans has never been studied and the chemical structures of their circulating metabolites have not been identified.”
The paper relies on this without support.
Plasma or serum samples are more commonly available in biobanks than other biospecimens.
“More metabolomic studies using blood samples should be carried out because of the more common availability of plasma or serum samples in biobanks.”
The paper relies on this without support.
Alanine is associated with diets that emphasize animal products rather than vegetables.
“alanine is associated with diets that emphasize animal products rather than vegetables”
The paper relies on this without support.
Many compounds in foods have structures that are uncommon in pharmaceuticals.
“many compounds in foods have structures that are uncommon in pharmaceuticals.”
The paper relies on this without support.
Food constituents may be degraded by specialized enzymes and may also be extensively metabolized by gut microbiota.
“Food constituents may be degraded by specialized enzymes and may also be extensively metabolized by the gut microbiota”
The paper relies on this without support.
The large majority of components of the food metabolome are not commercially available.
“The large majority of the components of the food metabolome are not commercially available.”
The paper relies on this without support.
Definitive identification of biomarkers is often hampered by the lack of available chemical standards.
“The definitive identification of biomarkers is often hampered by the lack of available chemical standards.”
The paper relies on this without support.
The food metabolome is exceedingly complex because it encompasses metabolites derived from as many metabolomes as there are edible species.
“The food metabolome is exceedingly complex because it encompasses metabolites derived from as many metabolomes as there are edible species.”
The paper relies on this without support.
Within one group, it is difficult to cover all the techniques and methods required to perform a comprehensive metabolomic study.
“Within one group, it is difficult to cover all the techniques and methods required to perform a comprehensive metabolomic study.”
The paper relies on this without support.
For many funding agencies, data sharing is becoming a key condition of funding.
“for many funding agencies, this is becoming a key condition of funding.”
The paper relies on this without support.
There is no current standardization initiative for the food metabolome.
“there is no current standardization initiative for the food metabolome”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Gut microbiota are affected by environmental factors such as dietary intakes, which may in turn influence blood levels of TMAO and its precursors.
“Fourth, the gut microbiota are affected by environmental factors37, 38 such as dietary intakes,39, 40, 41 which may, in turn, influence blood levels of TMAO and its precursors.4”
From Gut Microbiota Metabolites and Risk of Major Adverse Cardiovascular Disease Events and Death: A Systematic Review and Meta‐Analysis of Prospective Studies (2017) · cites this paper as [37]
Cites
NCBI GEO: archive for functional genomics data sets—update
Barrett, T., Wilhite, S. E., Ledoux, P., Evangelista, C., Kim, I. F., Tomashevsky, M., Marshall, K. A., Phillippy, K. H., Sherman, P. M., Holko, M., et al. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1193 · Cited by 10,418 · see citing works
Enterotypes of the human gut microbiome
MetaHIT Consortium (additional members), Arumugam, M., Raes, J., Pelletier, E., Le Paslier, D., Yamada, T., Mende, D. R., Fernandes, G. R., Tap, J., Bruls, T., et al. (2011) · Nature · doi:10.1038/nature09944 · Cited by 7,548 · see citing works
Davey Smith, G., & Ebrahim, S. (2003) · International Journal of Epidemiology · doi:10.1093/ije/dyg070 · Cited by 5,882 · see citing works
Gut flora metabolism of phosphatidylcholine promotes cardiovascular disease
Wang, Z., Klipfell, E., Bennett, B. J., Koeth, R., Levison, B. S., DuGar, B., Feldstein, A. E., Britt, E. B., Fu, X., Chung, Y.-M., et al. (2011) · Nature · doi:10.1038/nature09922 · Cited by 5,597 · see citing works
Sumner, L. W., Amberg, A., Barrett, D., Beale, M. H., Beger, R., Daykin, C. A., Fan, T. W.-M., Fiehn, O., Goodacre, R., Griffin, J. L., et al. (2007) · Metabolomics · doi:10.1007/s11306-007-0082-2 · Cited by 5,368 · see citing works
Smith, C. A., Want, E. J., O’Maille, G., Abagyan, R. A., & Siuzdak, G. E. (2006) · Analytical Chemistry · doi:10.1021/ac051437y · Cited by 5,296 · see citing works
Host-gut microbiota metabolic interactions
Nicholson, J. K., Holmes, E., Kinross, J., Burcelin, R., Gibson, G., Jia, W., & Pettersson, S. (2012) · Science · doi:10.1126/science.1223813 · Cited by 4,760 · see citing works
Intestinal microbiota metabolism of l-carnitine, a nutrient in red meat, promotes atherosclerosis
Koeth, R. A., Wang, Z., Levison, B. S., Buffa, J. A., Org, E., Sheehy, B. T., Britt, E. B., Fu, X., Wu, Y., Li, L., et al. (2013) · Nature Medicine · doi:10.1038/nm.3145 · Cited by 4,386 · see citing works
Bioavailability and bioefficacy of polyphenols in humans. I. Review of 97 bioavailability studies
Manach, C., Williamson, G., Morand, C., Scalbert, A., & Rémésy, C. (2005) · The American Journal of Clinical Nutrition · doi:10.1093/ajcn/81.1.230s · Cited by 4,219 · see citing works
Pluskal, T., Castillo, S., Villar‐Briones, A., & Orešič, M. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-395 · Cited by 3,852 · see citing works
Metabolomics—the link between genotypes and phenotypes
Fiehn, O. (2002) · Plant Molecular Biology · doi:10.1023/a:1013713905833 · Cited by 3,445 · see citing works
Intestinal microbial metabolism of phosphatidylcholine and cardiovascular risk
Tang, W. H. W., Wang, Z., Levison, B. S., Koeth, R. A., Britt, E. B., Fu, X., Wu, Y., & Hazen, S. L. (2013) · New England Journal of Medicine · doi:10.1056/nejmoa1109400 · Cited by 3,402 · cited 10× · see citing works
“Other biomarkers, particularly those identified in controlled intervention studies, may prove to be less robust in populations because of the possible existence of a variety of precursors as seen for TMAO, or the occurrence of the same precursor in various foods.”
BackgroundMethodInfluentialBenson, D. A., Cavanaugh, M., Clark, K., Karsch-Mizrachi, I., Lipman, D. J., Ostell, J., & Sayers, E. W. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1195 · Cited by 3,261 · see citing works
Metabolomics — the link between genotypes and phenotypes
Fiehn, O. (2002) · Springer eBooks · doi:10.1007/978-94-010-0448-0_11 · Cited by 3,168 · see citing works
Dietary polyphenols and the prevention of diseases
Scalbert, A., Manach, C., Morand, C., Rémésy, C., & Jiménez, L. (2005) · Critical Reviews in Food Science and Nutrition · doi:10.1080/1040869059096 · Cited by 2,999 · see citing works
HMDB 3.0—The Human Metabolome Database in 2013
Wishart, D. S., Jewison, T., Guo, A. C., Wilson, M., Knox, C., Liu, Y., Djoumbou-Feunang, Y., Mandal, R., Aziat, F., Dong, E., et al. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1065 · Cited by 2,845 · see citing works
Self-citationMore powerful procedures for multiple significance testing
Hochberg, Y., & Benjamini, Y. (1990) · Statistics in Medicine · doi:10.1002/sim.4780090710 · Cited by 2,715 · see citing works
Del Rio, D., Rodriguez-Mateos, A., Spencer, J. P. E., Tognolini, M., Borges, G., & Crozier, A. (2013) · Antioxidants & Redox Signaling · doi:10.1089/ars.2012.4581 · Cited by 2,601 · see citing works
METLIN—a metabolite mass spectral database
Smith, C. A., Maille, G. O., Want, E. J., Qin, C., Trauger, S. A., Brandon, T. R., Custodio, D. E., Abagyan, R., & Siuzdak, G. (2005) · Therapeutic Drug Monitoring · doi:10.1097/01.ftd.0000179845.53213.39 · Cited by 2,226 · see citing works
Psychogios, N., Hau, D., Peng, J., Guo, A. C., Mandal, R., Bouatra, S., Sinelnikov, I. V., Krishnamurthy, R., Eisner, R., Gautam, B., et al. (2011) · PLoS ONE · doi:10.1371/journal.pone.0016957 · Cited by 1,718 · see citing works
Self-citationVitamin C pharmacokinetics in healthy volunteers: evidence for a recommended dietary allowance
Levine, M., Conry-Cantilena, C., Wang, Y., Welch, R. W., Washko, P. W., Dhariwal, K. R., Park, J. B., Lazarev, A., Graumlich, J. F., King, J., et al. (1996) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.93.8.3704 · Cited by 1,325 · see citing works
Kuhl, C., Tautenhahn, R., Böttcher, C., Larson, T. R., & Neumann, S. (2011) · Analytical Chemistry · doi:10.1021/ac202450g · Cited by 1,208 · see citing works
The multivariate calibration problem in chemistry solved by the PLS method
Wold, S., Martens, H., & Wold, H. (1983) · Lecture notes in mathematics · doi:10.1007/bfb0062108 · Cited by 1,185 · see citing works
Human metabolic phenotype diversity and its association with diet and blood pressure
Holmes, E., Loo, R. L., Stamler, J., Bictash, M., Yap, I. K. S., Chan, Q., Ebbels, T., De Iorio, M., Brown, I. J., Veselkov, K. A., et al. (2008) · Nature · doi:10.1038/nature06882 · Cited by 1,054 · see citing works
(–)-Epicatechin mediates beneficial effects of flavanol-rich cocoa on vascular function in humans
Schroeter, H., Heiss, C., Balzer, J., Kleinbongard, P., Keen, C. L., Hollenberg, N. K., Sies, H., Kwik-Uribe, C., Schmitz, H. H., & Kelm, M. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0510168103 · Cited by 1,052 · see citing works
Human metabolic individuality in biomedical and pharmaceutical research
CARDIoGRAM, Suhre, K., Shin, S.-Y., Petersen, A.-K., Mohney, R. P., Meredith, D., Wägele, B., Altmaier, E., Deloukas, P., Erdmann, J., et al. (2011) · Nature · doi:10.1038/nature10354 · Cited by 1,017 · see citing works
Translational biomarker discovery in clinical metabolomics: an introductory tutorial
Xia, J., Broadhurst, D., Wilson, M., & Wishart, D. S. (2012) · Metabolomics · doi:10.1007/s11306-012-0482-9 · Cited by 958 · see citing works
Self-citationGut microorganisms, mammalian metabolism and personalized health care
Nicholson, J. K., Holmes, E., & Wilson, I. D. (2005) · Nature Reviews Microbiology · doi:10.1038/nrmicro1152 · Cited by 945 · see citing works
Balancing Life-Style and Genomics Research for Disease Prevention
Willett, W. C. (2002) · Science · doi:10.1126/science.1071055 · Cited by 871 · see citing works
Dunn, W. B., Broadhurst, D., Atherton, H. J., Goodacre, R., & Griffin, J. L. (2010) · Chemical Society Reviews · doi:10.1039/b906712b · Cited by 870 · see citing works
Genetics meets metabolomics: a genome-wide association study of metabolite profiles in human serum
Gieger, C., Geistlinger, L., Altmaier, E., Hrabé de Angelis, M., Kronenberg, F., Meitinger, T., Mewes, H.-W., Wichmann, H.-E., Weinberger, K. M., Adamski, J., et al. (2008) · PLoS Genetics · doi:10.1371/journal.pgen.1000282 · Cited by 737 · see citing works
Aflatoxin: a 50-year odyssey of mechanistic and translational toxicology
Kensler, T. W., Roebuck, B. D., Wogan, G. N., & Groopman, J. D. (2011) · Toxicological Sciences · doi:10.1093/toxsci/kfq283 · Cited by 703 · see citing works
In silico fragmentation for computer assisted identification of metabolite mass spectra
Wolf, S., Schmidt, S., Müller-Hannemann, M., & Neumann, S. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-148 · Cited by 698 · see citing works
Metabolomics: applications to food science and nutrition research
Wishart, D. S. (2008) · Trends in Food Science & Technology · doi:10.1016/j.tifs.2008.03.003 · Cited by 672 · see citing works
Self-citationANOVA-simultaneous component analysis (ASCA): a new tool for analyzing designed metabolomics data
Smilde, A. K., Jansen, J. J., Hoefsloot, H. C. J., Lamers, R.-J. A. N., van der Greef, J., & Timmerman, M. E. (2005) · Computer applications in the biosciences · doi:10.1093/bioinformatics/bti476 · Cited by 669 · see citing works
A genome-wide perspective of genetic variation in human metabolism
Illig, T., Gieger, C., Zhai, G., Römisch-Margl, W., Wang-Sattler, R., Prehn, C., Altmaier, E., Kastenmüller, G., Kato, B. S., Mewes, H.-W., et al. (2010) · Nature Genetics · doi:10.1038/ng.507 · Cited by 653 · see citing works
Haug, K., Salek, R. M., Conesa, P., Hastings, J., de Matos, P., Rijnbeek, M. L., Mahendraker, T., Williams, M., Neumann, S., Rocca‐Serra, P., et al. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1004 · Cited by 647 · see citing works
Data processing for mass spectrometry-based metabolomics
Katajamaa, M., & Orešič, M. (2007) · Journal of Chromatography A · doi:10.1016/j.chroma.2007.04.021 · Cited by 616 · see citing works
Scalbert, A., Brennan, L., Fiehn, O., Hankemeier, T., Kristal, B. S., van Ommen, B., Pujos-Guillot, E., Verheij, E., Wishart, D., & Wopereis, S. (2009) · Metabolomics · doi:10.1007/s11306-009-0168-0 · Cited by 565 · see citing works
Self-citationGenome-wide association study identifies multiple loci influencing human serum metabolite levels
Kettunen, J., Tukiainen, T., Sarin, A.-P., Ortega-Alonso, A., Tikkanen, E., Lyytikäinen, L.-P., Kangas, A. J., Soininen, P., Würtz, P., Silander, K., et al. (2012) · Nature Genetics · doi:10.1038/ng.1073 · Cited by 553 · see citing works
Metabolomic analysis in food science: a review
Cevallos‐Cevallos, J. M., Reyes-De-Corcuera, J. I., Etxeberria, E., Danyluk, M. D., & Rodrick, G. E. (2009) · Trends in Food Science & Technology · doi:10.1016/j.tifs.2009.07.002 · Cited by 545 · see citing works
The Metabolomics Standards Initiative (MSI)
Fiehn, O., Robertson, D., Griffin, J., van der Werf, M., Nikolau, B., Morrison, N., Sumner, L. W., Goodacre, R., Hardy, N. W., Taylor, C., et al. (2007) · Metabolomics · doi:10.1007/s11306-007-0070-6 · Cited by 518 · see citing works
The Metabolomics Standards Initiative
MSI Board Members: (2007) · Nature Biotechnology · doi:10.1038/nbt0807-846b · Cited by 454 · see citing works
Biomarkers in nutritional epidemiology: applications, needs and new horizons
Jenab, M., Slimani, N., Bictash, M., Ferrari, P., & Bingham, S. A. (2009) · Human Genetics · doi:10.1007/s00439-009-0662-5 · Cited by 448 · see citing works
Morand, C., Dubray, C., Milenkovic, D., Lioger, D., Martin, J. F., Scalbert, A., & Mazur, A. (2011) · The American Journal of Clinical Nutrition · doi:10.3945/ajcn.110.004945 · Cited by 439 · see citing works
Self-citationLondon, S. J., Yuan, J.-M., Chung, F.-L., Gao, Y.-T., Coetzee, G. A., Ross, R. K., & Yu, M. C. (2000) · The Lancet · doi:10.1016/s0140-6736(00)02631-3 · Cited by 436 · see citing works
Stalmach, A., Mullen, W., Barron, D., Uchida, K., Yokota, T., Cavin, C., Steiling, H., Williamson, G., & Crozier, A. (2009) · Drug Metabolism and Disposition · doi:10.1124/dmd.109.028019 · Cited by 401 · see citing works
Slupsky, C. M., Rankin, K. N., Wagner, J., Fu, H., Chang, D., Weljie, A. M., Saude, E. J., Lix, B., Adamko, D. J., Shah, S. L., et al. (2007) · Analytical Chemistry · doi:10.1021/ac0708588 · Cited by 398 · see citing works
Susceptibility of Human Metabolic Phenotypes to Dietary Modulation
Stella, C., Beckwith-Hall, B., Cloarec, O., Holmes, E., Lindon, J. C., Powell, J., van der Ouderaa, F., Bingham, S., Cross, A. J., & Nicholson, J. K. (2006) · Journal of Proteome Research · doi:10.1021/pr060265y · Cited by 376 · see citing works
Brown, M. J., Ferruzzi, M. G., Nguyen, M. L., Cooper, D. A., Eldridge, A. L., Schwartz, S. J., & White, W. S. (2004) · The American Journal of Clinical Nutrition · doi:10.1093/ajcn/80.2.396 · Cited by 376 · see citing works
LC-MS-based methodology for global metabolite profiling in metabonomics/metabolomics
Theodoridis, G., Gika, H. G., & Wilson, I. D. (2008) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2008.01.008 · Cited by 371 · see citing works
Alkylresorcinols in cereals and cereal products
Ross, A. B., Shepherd, M. J., Schüpphaus, M., Sinclair, V., Alfaro, B., Kamal-Eldin, A., & Åman, P. (2003) · Journal of Agricultural and Food Chemistry · doi:10.1021/jf0340456 · Cited by 351 · see citing works
The dynamic range of the human metabolome revealed by challenges
Krug, S., Kastenmüller, G., Stückler, F., Rist, M. J., Skurk, T., Sailer, M., Raffler, J., Römisch‐Margl, W., Adamski, J., Prehn, C., et al. (2012) · The FASEB Journal · doi:10.1096/fj.11-198093 · Cited by 327 · see citing works
Mena, P., Calani, L., Dall'Asta, C., Galaverna, G., García-Viguera, C., Bruni, R., Crozier, A., & Del Rio, D. (2012) · Molecules · doi:10.3390/molecules171214821 · Cited by 321 · see citing works
bioinformatics tools for mass spectroscopy-based metabolomic data processing and analysis
Sugimoto, M., Kawakami, M., Robert, M., Soga, T., & Tomita, M. (2012) · Current Bioinformatics · doi:10.2174/157489312799304431 · Cited by 307 · see citing works
Rutishauser, I. H. (2005) · Public Health Nutrition · doi:10.1079/phn2005798 · Cited by 307 · see citing works
O'Sullivan, A., Gibney, M. J., & Brennan, L. (2011) · The American Journal of Clinical Nutrition · doi:10.3945/ajcn.110.000950 · Cited by 297 · see citing works
Self-citationAdvances in metabolite identification
Wishart, D. S. (2011) · Bioanalysis · doi:10.4155/bio.11.155 · Cited by 284 · see citing works
Self-citationMetabolite annotations based on the integration of mass spectral information
Iijima, Y., Nakamura, Y., Ogata, Y., Tanaka, K., Sakurai, N., Suda, K., Suzuki, T., Suzuki, H., Okazaki, K., Kitayama, M., et al. (2008) · The Plant Journal · doi:10.1111/j.1365-313x.2008.03434.x · Cited by 283 · see citing works
Nutritional metabonomics: applications and perspectives.
Rezzi, S., Ramadan, Z., Fay, L., & Kochhar, S. (2007) · Journal of Proteome Research · doi:10.1021/pr060522z · Cited by 274 · see citing works
Heinzmann, S. S., Brown, I. J., Chan, Q., Bictash, M., Dumas, M.-E., Kochhar, S., Stamler, J., Holmes, E., Elliott, P., & Nicholson, J. K. (2010) · The American Journal of Clinical Nutrition · doi:10.3945/ajcn.2010.29672 · Cited by 271 · see citing works
Reactions and enzymes in the metabolism of drugs and other xenobiotics
Testa, B., Pedretti, A., & Vistoli, G. (2012) · Drug Discovery Today · doi:10.1016/j.drudis.2012.01.017 · Cited by 254 · see citing works
Some common misunderstandings in chemometrics
Kjeldahl, K., & Bro, R. (2010) · Journal of Chemometrics · doi:10.1002/cem.1346 · Cited by 250 · see citing works
Wang, Y., Tang, H., Nicholson, J. K., Hylands, P. J., Sampson, J. N., & Holmes, E. C. (2004) · Journal of Agricultural and Food Chemistry · doi:10.1021/jf0403282 · Cited by 237 · see citing works
Tikunov, Y. M., Laptenok, S. P., Hall, R. D., et al. (2011) · Metabolomics · doi:10.1007/s11306-011-0368-2 · Cited by 237 · see citing works
Metabolomics View on Gut Microbiome Modulation by Polyphenol-Rich Foods
Moco, S., Martin, F.-P. J., & Rezzi, S. (2012) · Journal of Proteome Research · doi:10.1021/pr300581s · Cited by 234 · see citing works
MyCompoundID: using an evidence-based metabolome library for metabolite identification
Li, L., Li, R., Zhou, J., Zuniga, A., Stanislaus, A. E., Wu, Y., Huan, T., Zheng, J., Shi, Y., Wishart, D. S., et al. (2013) · Analytical Chemistry · doi:10.1021/ac400099b · Cited by 229 · see citing works
Self-citationMeasuring the exposome: A powerful basis for evaluating environmental exposures and cancer risk
Wild, C. P., Scalbert, A., & Herceg, Z. (2013) · Environmental and Molecular Mutagenesis · doi:10.1002/em.21777 · Cited by 228 · see citing works
Self-citationAnalytical and statistical approaches to metabolomics research
Issaq, H. J., Van, Q. N., Waybright, T. J., Muschik, G. M., & Veenstra, T. D. (2009) · Journal of Separation Science · doi:10.1002/jssc.200900152 · Cited by 227 · see citing works
The complex links between dietary phytochemicals and human health deciphered by metabolomics
Manach, C., Hubert, J., Llorach, R., & Scalbert, A. (2009) · Molecular Nutrition & Food Research · doi:10.1002/mnfr.200800516 · Cited by 218 · see citing works
Self-citationUtilities for quantifying separation in PCA/PLS-DA scores plots
Worley, B., Halouska, S., & Powers, R. (2013) · Analytical Biochemistry · doi:10.1016/j.ab.2012.10.011 · Cited by 214 · see citing works
Saadatian-Elahi, M., Slimani, N., Chajès, V., Jenab, M., Goudable, J., Biessy, C., Ferrari, P., Byrnes, G., Autier, P., Peeters, P. H., et al. (2009) · The American Journal of Clinical Nutrition · doi:10.3945/ajcn.2008.26834 · Cited by 213 · see citing works
Al‐Delaimy, W. K., Slimani, N., Ferrari, P., Key, T. J., Spencer, E. A., Johansson, I., Johansson, G., Mattisson, I., Wirfält, E., Sieri, S., et al. (2005) · European Journal of Clinical Nutrition · doi:10.1038/sj.ejcn.1602253 · Cited by 212 · see citing works
Databases on food phytochemicals and their health promoting effects
Scalbert, A., Andres-Lacueva, C., Arita, M., Kroon, P., Manach, C., Urpi-Sarda, M., & Wishart, D. (2011) · Journal of Agricultural and Food Chemistry · doi:10.1021/jf200591d · Cited by 211 · see citing works
Self-citationMetAlign 3.0: performance enhancement by efficient use of advances in computer hardware
Lommen, A., & Kools, H. J. (2011) · Metabolomics · doi:10.1007/s11306-011-0369-1 · Cited by 211 · see citing works
Microbial metabolomics: toward a platform with full metabolome coverage
Werf, M. J. V. D., Overkamp, K. M., Muilwijk, B., Coulier, L., & Hankemeier, T. (2007) · Analytical Biochemistry · doi:10.1016/j.ab.2007.07.022 · Cited by 207 · see citing works
Biomarkers of Nutritional Exposure and Nutritional Status: An Overview
Potischman, N. A., & Freudenheim, J. L. (2003) · Journal of Nutrition · doi:10.1093/jn/133.3.873s · Cited by 206 · see citing works
YMDB: the Yeast Metabolome Database
Jewison, T., Knox, C., Neveu, V., Djoumbou, Y., Guo, A. C., Lee, J., Liu, P., Mandal, R., Krishnamurthy, R., Sinelnikov, I., et al. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr916 · Cited by 194 · see citing works
Self-citationRothwell, J. A., Urpi-Sarda, M., Boto-Ordonez, M., Knox, C., Llorach, R., Eisner, R., Cruz, J., Neveu, V., Wishart, D., Manach, C., et al. (2012) · Database · doi:10.1093/database/bas031 · Cited by 188 · see citing works
Self-citationUnderstanding the human salivary metabolome
Takeda, I., Stretch, C., Barnaby, P., Bhatnager, K., Rankin, K. N., Fu, H., Weljie, A. M., Jha, N., & Slupsky, C. M. (2009) · NMR in Biomedicine · doi:10.1002/nbm.1369 · Cited by 188 · see citing works
Adductomics: Characterizing exposures to reactive electrophiles
Rappaport, S. M., Li, H., Grigoryan, H., Funk, W. E., & Williams, E. R. (2011) · Toxicology Letters · doi:10.1016/j.toxlet.2011.04.002 · Cited by 181 · see citing works
Self-citationMetFusion: integration of compound identification strategies
Gerlich, M., & Neumann, S. (2013) · Journal of Mass Spectrometry · doi:10.1002/jms.3123 · Cited by 178 · see citing works
Al-Delaimy, W. K., Ferrari, P., Slimani, N., Pala, V, Johansson, I., Nilsson, S., Mattisson, I., Wirfalt, E., Galasso, R., Palli, D., et al. (2005) · European Journal of Clinical Nutrition · doi:10.1038/sj.ejcn.1602252 · Cited by 176 · see citing works
Urinary flavonoids and phenolic acids as biomarkers of intake for polyphenol-rich foods
Mennen, L. I., Sapinho, D., Ito, H., Bertrais, S., Galan, P., Hercberg, S., & Scalbert, A. (2006) · British Journal Of Nutrition · doi:10.1079/bjn20061808 · Cited by 174 · see citing works
Self-citationMetabonomics Approach To Determine Metabolic Differences between Green Tea and Black Tea Consumption
van Dorsten, F. A., Daykin, C. A., MULDER, T. P. J., & van Duynhoven, J. (2006) · Journal of Agricultural and Food Chemistry · doi:10.1021/jf061016x · Cited by 170 · see citing works
Draper, J., Enot, D. P., Parker, D., Beckmann, M., Snowdon, S., Lin, W., & Zubair, H. (2009) · BMC Bioinformatics · doi:10.1186/1471-2105-10-227 · Cited by 169 · see citing works
Self-citationPujos-Guillot, E., Hubert, J., Martin, J.-F., Lyan, B., Quintana, M., Claude, S., Chabanas, B., Rothwell, J. A., Bennetau-Pelissero, C., Scalbert, A., et al. (2013) · Journal of Proteome Research · doi:10.1021/pr300997c · Cited by 166 · see citing works
Selective inference in complex research
Benjamini, Y., Heller, R., & Yekutieli, D. (2009) · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rsta.2009.0127 · Cited by 166 · see citing works
The metabolic fate of red wine and grape juice polyphenols in humans assessed by metabolomics
van Dorsten, F. A., Grün, C. H., van Velzen, E. J. J., Jacobs, D. M., Draijer, R., & van Duynhoven, J. (2009) · Molecular Nutrition & Food Research · doi:10.1002/mnfr.200900212 · Cited by 165 · see citing works
Silberberg, M., Morand, C., Mathevon, T., Besson, C., Manach, C., Scalbert, A., & Remesy, C. (2006) · European Journal of Nutrition · doi:10.1007/s00394-005-0568-5 · Cited by 164 · cited 1× · see citing works
“The yield of phase I/II reactions are often very high (68, 71), and host-transformed metabolites retain many of the features of their parent compounds.”
BackgroundECMDB: the E-coli Metabolome Database
Guo, A. C., Jewison, T., Wilson, M., Liu, Y., Knox, C., Djoumbou, Y., Lo, P., Mandal, R., Krishnamurthy, R., & Wishart, D. S. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks992 · Cited by 164 · see citing works
Self-citationAlbanes, D., Virtamo, J., Taylor, P., Rautalahti, M., Pietinen, P., & Heinonen, O. (1997) · The American Journal of Clinical Nutrition · doi:10.1093/ajcn/66.2.366 · Cited by 164 · see citing works
Multilevel data analysis of a crossover designed human nutritional intervention study
van Velzen, E. J. J., Westerhuis, J. A., van Duynhoven, J. P. M., van Dorsten, F. A., Hoefsloot, H. C. J., Jacobs, D. M., Smit, S., Draijer, R., Kroner, C. I., & Smilde, A. K. (2008) · Journal of Proteome Research · doi:10.1021/pr800145j · Cited by 161 · see citing works
Urinary metabolites as biomarkers of polyphenol intake in humans—a systematic review
Pérez-Jiménez, J., Hubert, J., Hooper, L., Cassidy, A., Manach, C., Williamson, G., & Scalbert, A. (2010) · The American Journal of Clinical Nutrition · doi:10.3945/ajcn.2010.29924 · Cited by 159 · see citing works
Web-based resources for mass-spectrometry-based metabolomics: a user’s guide
Tohge, T., & Fernie, A. R. (2009) · Phytochemistry · doi:10.1016/j.phytochem.2009.02.004 · Cited by 152 · see citing works
Lloyd, A. J., Beckmann, M., Favé, G., Mathers, J. C., & Draper, J. (2011) · British Journal Of Nutrition · doi:10.1017/s0007114511001164 · Cited by 152 · see citing works
Self-citationDoets, E. L., de Wit, L. S., Dhonukshe-Rutten, R. A. M., et al. (2008) · European Journal of Nutrition · doi:10.1007/s00394-008-1003-5 · Cited by 150 · see citing works
Solanky, K. S., Bailey, N. J. C., Beckwith-Hall, B. M., Bingham, S. A., Davis, A. L., Holmes, E. C., Nicholson, J. K., & Cassidy, A. (2005) · The Journal of Nutritional Biochemistry · doi:10.1016/j.jnutbio.2004.12.005 · Cited by 148 · see citing works
Draper, J., Lloyd, A. J., Goodacre, R., & Beckmann, M. (2013) · Metabolomics · doi:10.1007/s11306-012-0449-x · Cited by 144 · see citing works
Llorach, R., Urpi-Sarda, M., Jauregui, O., Monagas, M., & Andres-Lacueva, C. (2009) · Journal of Proteome Research · doi:10.1021/pr900470a · Cited by 144 · see citing works
Self-citationVioque, J., Weinbrenner, T., Asensio, L., Castelló, A., Young, I. S., & Fletcher, A. (2007) · British Journal Of Nutrition · doi:10.1017/s0007114507659017 · Cited by 141 · see citing works
Bictash, M., Ebbels, T. M., Chan, Q., Loo, R. L., Yap, I. K. S., Brown, I. J., de Iorio, M., Daviglus, M. L., Holmes, E., Stamler, J., et al. (2010) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2009.10.001 · Cited by 140 · see citing works
Urinary Biomarkers of Meat Consumption
Cross, A. J., Major, J. M., & Sinha, R. R. (2011) · Cancer Epidemiology Biomarkers & Prevention · doi:10.1158/1055-9965.epi-11-0048 · Cited by 139 · see citing works
Computer systems for the prediction of xenobiotic metabolism
Langowski, J., & Long, A. (2002) · Advanced Drug Delivery Reviews · doi:10.1016/s0169-409x(02)00011-x · Cited by 138 · see citing works
Untargeted Metabolomics as a Screening Tool for Estimating Compliance to a Dietary Pattern
Andersen, M.-B. S., Rinnan, Å., Manach, C., Poulsen, S. K., Pujos‐Guillot, E., Larsen, T. M., Astrup, A. V., & Dragsted, L. O. (2014) · Journal of Proteome Research · doi:10.1021/pr400964s · Cited by 133 · see citing works
Self-citationInterindividual differences in response to plant-based diets: implications for cancer risk
Lampe, J. W. (2009) · The American Journal of Clinical Nutrition · doi:10.3945/ajcn.2009.26736d · Cited by 133 · see citing works
van der Hooft, J. J. J., de Vos, R. C. H., Mihaleva, V. V., Bino, R. J., Ridder, L., de Roo, N., Jacobs, D. M., van Duynhoven, J., & Vervoort, J. J. M. (2012) · Analytical Chemistry · doi:10.1021/ac3017339 · Cited by 131 · see citing works
Self-citationLloyd, A. J., Favé, G., Beckmann, M., Lin, W., Tailliart, K., Xie, L., Mathers, J. C., & Draper, J. (2011) · The American Journal of Clinical Nutrition · doi:10.3945/ajcn.111.017921 · Cited by 130 · see citing works
Self-citationAutomatic Chemical Structure Annotation of an LC–MSn Based Metabolic Profile from Green Tea
Ridder, L., van der Hooft, J. J. J., Verhoeven, S., de Vos, R. C. H., Bino, R. J., & Vervoort, J. J. M. (2013) · Analytical Chemistry · doi:10.1021/ac400861a · Cited by 130 · see citing works
Self-citationStability and Robustness of Human Metabolic Phenotypes in Response to Sequential Food Challenges
Heinzmann, S. S., Merrifield, C. A., Rezzi, S., Kochhar, S., Lindon, J. C., Holmes, E. C., & Nicholson, J. K. (2011) · Journal of Proteome Research · doi:10.1021/pr2005764 · Cited by 128 · see citing works
Edmands, W. M. B., Beckonert, O. P., Stella, C., Campbell, A., Lake, B. G., Lindon, J. C., Holmes, E., & Gooderham, N. J. (2011) · Journal of Proteome Research · doi:10.1021/pr200326k · Cited by 119 · see citing works
Biomarkers intersect with the exposome
Rappaport, S. M. (2012) · Biomarkers · doi:10.3109/1354750x.2012.691553 · Cited by 114 · see citing works
Self-citationDaykin, C. A., van Duynhoven, J., Groenewegen, A., Dachtler, M., van Amelsvoort, J. M. M., & MULDER, T. P. J. (2005) · Journal of Agricultural and Food Chemistry · doi:10.1021/jf048439o · Cited by 114 · see citing works
The active human gut microbiota differs from the total microbiota
Peris-Bondia, F., Latorre, A., Artacho, A., Moya, A., & D'Auria, G. (2011) · PLoS ONE · doi:10.1371/journal.pone.0022448 · Cited by 113 · see citing works
Biomarkers of fruit and vegetable intake in human intervention studies: a systematic review
Baldrick, F. R., Woodside, J. V., Elborn, J. S., Young, I. S., & McKinley, M. C. (2011) · Critical Reviews in Food Science and Nutrition · doi:10.1080/10408398.2010.482217 · Cited by 109 · see citing works
Brantsæter, A. L., Haugen, M., Julshamn, K., Alexander, J., & Meltzer, H. M. (2009) · European Journal of Clinical Nutrition · doi:10.1038/sj.ejcn.1602952 · Cited by 105 · see citing works
Llorach, R., Garrido, I., Monagas, M., Urpí-Sardà, M., Tulipani, S., Bartolomé, B., & Andrés‐Lacueva, C. (2010) · Journal of Proteome Research · doi:10.1021/pr100639v · Cited by 104 · see citing works
Self-citationBertram, H. C., Hoppe, C., Petersen, B. O., et al. (2007) · British Journal Of Nutrition · doi:10.1017/s0007114507450322 · Cited by 104 · see citing works
Tulipani, S., Llorach, R., Jáuregui, O., López-Uriarte, P. J., Garcia‐Aloy, M., Bulló, M., Salas‐Salvadó, J., & Andrés‐Lacueva, C. (2011) · Journal of Proteome Research · doi:10.1021/pr200514h · Cited by 103 · see citing works
Self-citationRoss, A. B., Bourgeois, A., Macharia, H. N., Kochhar, S., Jebb, S. A., Brownlee, I. A., & Seal, C. J. (2012) · The American Journal of Clinical Nutrition · doi:10.3945/ajcn.110.008508 · Cited by 103 · see citing works
Impact of Short-Term Intake of Red Wine and Grape Polyphenol Extract on the Human Metabolome
Jacobs, D. M., Fuhrmann, J. C., van Dorsten, F. A., Rein, D., Peters, S., van Velzen, E. J. J., Hollebrands, B., Draijer, R., van Duynhoven, J., & Garczarek, U. (2012) · Journal of Agricultural and Food Chemistry · doi:10.1021/jf2044247 · Cited by 102 · see citing works
Verkasalo, P. K., Appleby, P. N., Allen, N. E., Davey, G., Adlercreutz, H., & Key, T. J. (2001) · British Journal Of Nutrition · doi:10.1079/bjn2001424 · Cited by 101 · see citing works
A critical assessment of some biomarker approaches linked with dietary intake
Crews, H., Alink, G., Andersen, R., Braesco, V., Holst, B., Maiani, G., Ovesen, L., Scotter, M., Solfrizzo, M., van den Berg, R., et al. (2001) · British Journal Of Nutrition · doi:10.1079/bjn2001337 · Cited by 99 · see citing works
van der Hooft, J. J. J., Vervoort, J., Bino, R. J., Beekwilder, J., & de Vos, R. C. H. (2011) · Analytical Chemistry · doi:10.1021/ac102546x · Cited by 99 · see citing works
Self-citationPhenotyping Tea Consumers by Nutrikinetic Analysis of Polyphenolic End-Metabolites
van Velzen, E. J. J., Westerhuis, J. A., van Duynhoven, J., van Dorsten, F. A., Grün, C. H., Jacobs, D. M., Duchateau, G. S. M. J. E., Vis, D. J., & Smilde, A. K. (2009) · Journal of Proteome Research · doi:10.1021/pr801071p · Cited by 96 · see citing works
PlantMetabolomics.org: A Web Portal for Plant Metabolomics Experiments
Bais, P., Moon, S. M., He, K., Leitao, R. M., Dreher, K. A., Walk, T., Sucaet, Y., Barkan, L., Wohlgemuth, G., Roth, M. R., et al. (2010) · PLANT PHYSIOLOGY · doi:10.1104/pp.109.151027 · Cited by 93 · see citing works
Andersen, M.-B. S., Kristensen, M., Manach, C., Pujos‐Guillot, E., Poulsen, S. K., Larsen, T. M., Astrup, A. V., & Dragsted, L. O. (2014) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-013-7498-5 · Cited by 93 · see citing works
Self-citationThe Metabolome-Wide Association Study: a new look at human disease risk factors
Nicholson, J. K., Holmes, E., & Elliott, P. (2008) · Journal of Proteome Research · doi:10.1021/pr8005099 · Cited by 93 · see citing works
Genetic polymorphism of xenobiotic metabolising enzymes, diet and cancer susceptibility.
Reszka, E., Wąsowicz, W., & Gromadzińska, J. (2006) · PubMed · Cited by 93 · see citing works
Rojas-Cherto, M., Peironcely, J. E., Kasper, P. T., van der Hooft, J. J. J., de Vos, R. C. H., Vreeken, R., Hankemeier, T., & Reijmers, T. (2012) · Analytical Chemistry · doi:10.1021/ac2034216 · Cited by 92 · see citing works
Burri, B. J., Neidlinger, T. R., & Clifford, A. J. (2001) · The Journal of Nutrition · doi:10.1093/jn/131.8.2096 · Cited by 90 · see citing works
Lang, R., Wahl, A., Stark, T., & Hofmann, T. (2011) · Molecular Nutrition & Food Research · doi:10.1002/mnfr.201000656 · Cited by 90 · see citing works
Bingham, S., Luben, R., Welch, A., Tasevska, N., Wareham, N., & Khaw, K. T. (2007) · Cancer Epidemiology, Biomarkers & Prevention · doi:10.1158/1055-9965.epi-06-1050 · Cited by 88 · see citing works
Xu, J., Yang, S., Cai, S., Dong, J., Li, X., & Chen, Z. (2010) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-009-3338-z · Cited by 85 · see citing works
Moco, S., Forshed, J., de Vos, R. C. H., et al. (2008) · Metabolomics · doi:10.1007/s11306-008-0112-8 · Cited by 85 · see citing works
Altmaier, E., Kastenmüller, G., Römisch-Margl, W., Thorand, B., Weinberger, K. M., Illig, T., Adamski, J., Döring, A., & Suhre, K. (2011) · European Journal of Epidemiology · doi:10.1007/s10654-010-9524-7 · Cited by 84 · see citing works
Bondia‐Pons, I., Barri, T., Hanhineva, K., Juntunen, K., Dragsted, L. O., Mykkänen, H., & Poutanen, K. (2013) · Molecular Nutrition & Food Research · doi:10.1002/mnfr.201200571 · Cited by 83 · see citing works
Self-citationGuo, B., Chen, B., Liu, A., Zhu, W., & Yao, S. (2012) · Current Drug Metabolism · doi:10.2174/138920012803341401 · Cited by 80 · see citing works
Total polyphenol excretion and blood pressure in subjects at high cardiovascular risk
Medina-Remón, A., Zamora-Ros, R., Rotchés-Ribalta, M., Andres-Lacueva, C., Martínez-González, M. A., Covas, M. I., Corella, D., Salas-Salvadó, J., Gómez-Gracia, E., Ruiz-Gutiérrez, V., et al. (2011) · Nutrition Metabolism and Cardiovascular Diseases · doi:10.1016/j.numecd.2009.10.019 · Cited by 80 · cited 1× · see citing works
“The Folin assay, commonly used to estimate total polyphenols in foods (46), has also been applied to urine samples to compare polyphenol intake (47), but such use may be inappropriate because of the presence of interfering reducing metabolites in such complex biological matrices (46).”
MethodAllen, N. E., Grace, P. B., Ginn, A., Travis, R. C., Roddam, A. W., Appleby, P. N., & Key, T. (2008) · British Journal Of Nutrition · doi:10.1017/s000711450782407x · Cited by 76 · see citing works
Andersson, A., Marklund, M., Diana, M., & Landberg, R. (2011) · The Journal of Nutrition · doi:10.3945/jn.111.139238 · Cited by 75 · see citing works
van Ommen, B., Bouwman, J., Dragsted, L. O., Drevon, C. A., Elliott, R. M., de Groot, P., Kaput, J., Mathers, J. C., Müller, M. M., Pepping, F., et al. (2010) · Genes & Nutrition · doi:10.1007/s12263-010-0167-9 · Cited by 73 · see citing works
Self-citationMyint, T. (2000) · American Journal of Epidemiology · doi:10.1093/aje/152.8.752 · Cited by 73 · see citing works
Hodgson, J. M., Yee Chan, S., Puddey, I. B., Devine, A., Wattanapenpaiboon, N., Wahlqvist, M. L., Lukito, W., Burke, V., Ward, N. C., Prince, R. L., et al. (2004) · British Journal Of Nutrition · doi:10.1079/bjn20031046 · Cited by 73 · cited 1× · see citing works
“Some have been used as surrogate biomarkers of food intake, as follows: polyphenols, carotenoids, and vitamin C for fruit and vegetables (17, 18); alkylresorcinols for whole-grain cereals (19, 20); isoflavones for soy (21); amino acids and fatty acids for meat (22, 23); fatty acids for dairy products and fish (22, 24)…”
MethodMetabolomics Provide New Insight on the Metabolism of Dietary Phytochemicals in Rats
Fardet, A., Llorach, R., Orsoni, A., Martin, J., Pujos‐Guillot, E., Lapierre, C., & Scalbert, A. (2008) · Journal of Nutrition · doi:10.1093/jn/138.7.1282 · Cited by 70 · see citing works
Self-citationMay, D. H., Navarro, S. L., Ruczinski, I., Hogan, J., Ogata, Y., Schwarz, Y., Levy, L., Holzman, T., McIntosh, M. W., & Lampe, J. W. (2013) · British Journal Of Nutrition · doi:10.1017/s000711451300127x · Cited by 69 · see citing works
Urinary excretion of methylamines in men with varying intake of fish from the baltic sea
Svensson, B. ‐., Åkesson, B., Nilsson, A., & Paulsson, K. (1994) · Journal of Toxicology and Environmental Health · doi:10.1080/15287399409531853 · Cited by 66 · see citing works
Vázquez‐Fresno, R., Llorach, R., Alcaro, F. D., Rodriguez, M. A., Vinaixa, M., Chiva‐Blanch, G., Estruch, R., Correig, X., & Andrés‐Lacueva, C. (2012) · Electrophoresis · doi:10.1002/elps.201100646 · Cited by 65 · see citing works
Self-citationGong, P., Cui, N., Wu, L. L., Liang, Y., Hao, K., Xu, X., Tang, W., Wang, G., & Hao, H. (2012) · Analytical Chemistry · doi:10.1021/ac3002353 · Cited by 65 · see citing works
Söderholm, P. P., Koskela, A. H., Lundin, J. E., Tikkanen, M. J., & Adlercreutz, H. C. (2009) · The American Journal of Clinical Nutrition · doi:10.3945/ajcn.2009.28290 · Cited by 64 · see citing works
Data-driven strategy for the discovery of potential urinary biomarkers of habitual dietary exposure
Lloyd, A. J., Beckmann, M., Haldar, S., Seal, C. J., Brandt, K., & Draper, J. (2012) · American Journal of Clinical Nutrition · doi:10.3945/ajcn.112.048033 · Cited by 64 · see citing works
Self-citationGika, H. G., Theodoridis, G. A., Earll, M., Snyder, R. W., Sumner, S. J., & Wilson, I. D. (2010) · Analytical Chemistry · doi:10.1021/ac1016612 · Cited by 61 · see citing works
Cys34 Adducts of Reactive Oxygen Species in Human Serum Albumin
Grigoryan, H., Li, H., Iavarone, A. T., Williams, E. R., & Rappaport, S. M. (2012) · Chemical Research in Toxicology · doi:10.1021/tx300096a · Cited by 61 · see citing works
Self-citationGürdeniz, G., Kristensen, M., Skov, T., & Dragsted, L. O. (2012) · Metabolites · doi:10.3390/metabo2010077 · Cited by 61 · see citing works
Self-citationJohnson, C. H., Slanař, O., Krausz, K. W., Kang, D. W., Patterson, A. D., Kim, J.-H., Luecke, H., Gonzalez, F. J., & Idle, J. R. (2012) · The American Journal of Clinical Nutrition · doi:10.3945/ajcn.112.042929 · Cited by 58 · see citing works
Barri, T., Holmer-Jensen, J., Hermansen, K., & Dragsted, L. O. (2012) · Analytica Chimica Acta · doi:10.1016/j.aca.2011.12.065 · Cited by 57 · see citing works
Self-citationLC-QTOF/MS metabolomic profiles in human plasma after a 5-week high dietary fiber intake
Johansson‐Persson, A., Barri, T., Ulmius, M., Önning, G., & Dragsted, L. O. (2013) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-013-6874-5 · Cited by 56 · see citing works
Self-citationHuman Metabolome Database: Completing the ‘Human Parts List’
Wishart, D. S. (2007) · Pharmacogenomics · doi:10.2217/14622416.8.7.683 · Cited by 56 · see citing works
Self-citationBeckmann, M., Lloyd, A. J., Haldar, S., Seal, C., Brandt, K., & Draper, J. (2013) · Molecular Nutrition & Food Research · doi:10.1002/mnfr.201200777 · Cited by 55 · see citing works
Self-citationLaw, W. S., Huang, P. Y., Ong, E. S., Ong, C. N., Li, S. F. Y., Pasikanti, K. K., & Chan, E. C. Y. (2008) · Rapid Communications in Mass Spectrometry · doi:10.1002/rcm.3629 · Cited by 53 · see citing works
Pirro, V., Valente, V., Oliveri, P., et al. (2011) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-011-5314-7 · Cited by 52 · see citing works
Stanstrup, J., Gerlich, M., Dragsted, L. O., et al. (2013) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-013-6954-6 · Cited by 52 · see citing works
Self-citationChajès, V., Biessy, C., Byrnes, G. B., Deharveng, G., Saadatian‐Elahi, M., Jenab, M., Peeters, P. H. M., Ocké, M. C., Bueno-de-Mesquita, H. B., Johansson, I., et al. (2011) · Nutrition and Cancer · doi:10.1080/01635581.2011.617530 · Cited by 51 · see citing works
Chajès, V., Jenab, M., Romieu, I., Ferrari, P., Dahm, C. C., Overvad, K., Egeberg, R., Tjønneland, A., Clavel-Chapelon, F., Boutron-Ruault, M.-C., et al. (2011) · The American Journal of Clinical Nutrition · doi:10.3945/ajcn.110.005892 · Cited by 51 · see citing works
Metabolomic fingerprint in patients at high risk of cardiovascular disease by cocoa intervention
Llorach, R., Urpí-Sardà, M., Tulipani, S., Garcia‐Aloy, M., Monagas, M., & Andrés‐Lacueva, C. (2013) · Molecular Nutrition & Food Research · doi:10.1002/mnfr.201200736 · Cited by 49 · see citing works
Self-citationT’jollyn, H., Boussery, K., Mortishire-Smith, R. J., Coe, K., De Boeck, B., Van Bocxlaer, J. F., & Mannens, G. (2011) · Drug Metabolism and Disposition · doi:10.1124/dmd.111.039982 · Cited by 48 · see citing works
Kristensen, M., Engelsen, S. B., & Dragsted, L. O. (2012) · Metabolomics · doi:10.1007/s11306-011-0282-7 · Cited by 47 · see citing works
Self-citationRiffle, M. E., & Eng, J. K. (2009) · PROTEOMICS · doi:10.1002/pmic.200900216 · Cited by 47 · see citing works
Lan, K., Xie, G., & Jia, W. (2013) · Evidence-based Complementary and Alternative Medicine · doi:10.1155/2013/819147 · Cited by 47 · see citing works
Structural elucidation of low abundant metabolites in complex sample matrices
van der Hooft, J. J. J., de Vos, R. C. H., Ridder, L., Vervoort, J., & Bino, R. J. (2013) · Metabolomics · doi:10.1007/s11306-013-0519-8 · Cited by 46 · see citing works
Menikarachchi, L. C., Hill, D. W., Hamdalla, M. A., Măndoiu, I., & Grant, D. F. (2013) · Journal of Chemical Information and Modeling · doi:10.1021/ci400368v · Cited by 45 · see citing works
Lee, S. M., Kwon, G. Y., Kim, K.-O., & Kim, Y.-S. (2011) · Analytica Chimica Acta · doi:10.1016/j.aca.2011.07.028 · Cited by 44 · see citing works
Turunen, A. W., Männistö, S., Kiviranta, H., Marniemi, J., Jula, A., Tiittanen, P., Suominen-Taipale, L., Vartiainen, T., & Verkasalo, P. K. (2010) · European Journal of Clinical Nutrition · doi:10.1038/ejcn.2009.147 · Cited by 43 · see citing works
How do metabolites differ from their parent molecules and how are they excreted?
Kirchmair, J., Howlett, A., Peironcely, J. E., Murrell, D. S., Williamson, M. J., Adams, S. E., Hankemeier, T., van Buren, L., Duchateau, G., Klaffke, W., et al. (2013) · Journal of Chemical Information and Modeling · doi:10.1021/ci300487z · Cited by 43 · see citing works
Rasmussen, L. G., Winning, H., Savorani, F., Ritz, C., Engelsen, S. B., Astrup, A. V., Larsen, T. M., & Dragsted, L. O. (2011) · Genes & Nutrition · doi:10.1007/s12263-011-0250-x · Cited by 42 · see citing works
Self-citationAndersen, M.-B. S., Reinbach, H. C., Rinnan, Å., Barri, T., Mithril, C. E., & Dragsted, L. O. (2013) · Metabolomics · doi:10.1007/s11306-013-0522-0 · Cited by 42 · see citing works
Self-citationHanhineva, K., Barri, T., Kolehmainen, M., Pekkinen, J., Pihlajamäki, J., Vesterbacka, A., Solano-Aguilar, G. I., Mykkänen, H. M., Dragsted, L. O., Urban, J. F., et al. (2013) · Journal of Proteome Research · doi:10.1021/pr400257d · Cited by 40 · see citing works
Self-citationArsenault, L. N., Matthan, N., Scott, T. M., Dallal, G., Lichtenstein, A. H., Folstein, M. F., Rosenberg, I., & Tucker, K. L. (2009) · American Journal of Epidemiology · doi:10.1093/aje/kwp089 · Cited by 36 · see citing works
He, X., Kozak, M., & Nimkar, S. (2012) · Analytical Chemistry · doi:10.1021/ac3019476 · Cited by 36 · see citing works
Coupled matrix factorization with sparse factors to identify potential biomarkers in metabolomics
Acar, E., Gurdeniz, G., Rasmussen, M. A., Rago, D., Dragsted, L. O., & Bro, R. (2012) · International Journal of Knowledge Discovery in Bioinformatics · doi:10.4018/jkdb.2012070102 · Cited by 35 · see citing works
Self-citationMatsuda, F., Nakabayashi, R., Sawada, Y., Suzuki, M., Hirai, M. Y., Kanaya, S., & Saito, K. (2011) · Frontiers in Plant Science · doi:10.3389/fpls.2011.00040 · Cited by 34 · see citing works
bioactive benzoxazinoids in rye bread are absorbed and metabolized in pigs
Adhikari, K. B., Laursen, B. B., Lærke, H. N., & Fomsgaard, I. S. (2012) · Journal of Agricultural and Food Chemistry · doi:10.1021/jf2048492 · Cited by 34 · see citing works
Savorani, F., Kristensen, M., Larsen, F. H., Astrup, A. V., & Engelsen, S. B. (2010) · Nutrition & Metabolism · doi:10.1186/1743-7075-7-43 · Cited by 33 · see citing works
Intakes of whey protein hydrolysate and whole whey proteins are discriminated by LC–MS metabolomics
Stanstrup, J., Rasmussen, J. E., Ritz, C., Holmer-Jensen, J., Hermansen, K., & Dragsted, L. O. (2013) · Metabolomics · doi:10.1007/s11306-013-0607-9 · Cited by 32 · see citing works
Self-citationpragmatic approaches to using computational methods to predict xenobiotic metabolism
Piechota, P., Cronin, M. T. D., Hewitt, M., & Madden, J. C. (2013) · Journal of Chemical Information and Modeling · doi:10.1021/ci400050v · Cited by 30 · see citing works
Rago, D., Mette, K., Gürdeniz, G., Marini, F., Poulsen, M., & Dragsted, L. O. (2013) · Metabolomics · doi:10.1007/s11306-013-0534-9 · Cited by 29 · see citing works
Self-citationKroke, A., Klipstein-Grobusch, K., Hoffmann, K., Terbeck, I., Boeing, H., & Helander, A. (2001) · British Journal Of Nutrition · doi:10.1079/bjn2000289 · Cited by 29 · see citing works
Diet and health risk: risk patterns and disease-specific associations
Marshall, J. R., & Chen, Z. (1999) · The American Journal of Clinical Nutrition · doi:10.1093/ajcn/69.6.1351s · Cited by 20 · see citing works
Determination of new biomarkers to monitor the dietary consumption of isothiocyanates
Kumar, A., Vineis, P., Sacerdote, C., Fiorini, L., & Sabbioni, G. (2010) · Biomarkers · doi:10.3109/1354750x.2010.517567 · Cited by 19 · see citing works
Systems Biology Resources Arising from the Human Metabolome Project
Wishart, D. S. (2012) · Springer eBooks · doi:10.1007/978-1-4614-1689-0_11 · Cited by 13 · see citing works
Self-citationDietary determinants for Hb-acrylamide and Hb-glycidamide adducts in Danish non-smoking women
Outzen, M., Egeberg, R., Dragsted, L., Christensen, J., Olesen, P. T., Frandsen, H., Overvad, K., Tjønneland, A., & Olsen, A. (2011) · British Journal Of Nutrition · doi:10.1017/s0007114510005003 · Cited by 11 · see citing works
Self-citationGürdeniz, G., Hansen, L., Rasmussen, M. A., Acar, E., Olsen, A., Christensen, J., Barri, T., Tjønneland, A., & Dragsted, L. O. (2013) · Metabolomics · doi:10.1007/s11306-013-0525-x · Cited by 8 · see citing works
Self-citationSuhre, K. (2012) · Springer: New York · doi:10.1007/978-1-4614-1689-0 · Cited by 4 · see citing works
Flagged first, then by citations
5 of the 198 references couldn’t be matched to a known paper.
Research works printed but not linked: 1
- Zamora-Ros R, Touillaud M, Rothwell JA, Romieu I, Scalbert A. Measuring exposure to the polyphenol metabolome in epidemiological studies: current tools, applications and their limits. Am J Clin Nutr (in press).
Cited by
Sorted by citations
Metabolomics: beyond biomarkers and towards mechanisms
Johnson, C. H., Ivanisevic, J., & Siuzdak, G. (2016) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm.2016.25 · Cited by 2,829 · see citing works
Emerging applications of metabolomics in drug discovery and precision medicine
Wishart, D. S. (2016) · Nature Reviews Drug Discovery · doi:10.1038/nrd.2016.32 · Cited by 1,499 · see citing works
Self-citationMetabolomics for Investigating Physiological and Pathophysiological Processes
Wishart, D. S. (2019) · Physiological Reviews · doi:10.1152/physrev.00035.2018 · Cited by 1,247 · see citing works
“Several areas that were not covered include the very exciting area of immunometabolism and immunometabolomics (309, 356), the use of metabolomics in understanding nutrition or assessing nutritional intake (122, 412), the utilization of metabolomics in assessing environmental toxic exposures (348, 386, 503), the applic…”
BackgroundSelf-citationRodriguez‐Mateos, A., Vauzour, D., Krueger, C. G., Shanmuganayagam, D., Reed, J. D., Calani, L., Mena, P. R., Rio, D. D., & Crozier, A. (2014) · Archives of Toxicology · doi:10.1007/s00204-014-1330-7 · Cited by 608 · see citing works
“One of the few existing databases containing (poly)phenol metabolites is the Phenol-explorer, although the current information is still somewhat limited (Scalbert et al. 2014).”
BackgroundWilliamson, G., Kay, C. D., & Crozier, A. (2018) · Comprehensive Reviews in Food Science and Food Safety · doi:10.1111/1541-4337.12351 · Cited by 607 · see citing works
Heianza, Y., Ma, W., Manson, J. E., Rexrode, K. M., & Qi, L. (2017) · Journal of the American Heart Association · doi:10.1161/jaha.116.004947 · Cited by 544 · see citing works
Review of recent developments in GC–MS approaches to metabolomics-based research
Beale, D. J., Pinu, F. R., Kouremenos, K. A., Poojary, M. M., Narayana, V. K., Boughton, B. A., Kanojia, K., Dayalan, S., Jones, O. A. H., & Dias, D. A. (2018) · Metabolomics · doi:10.1007/s11306-018-1449-2 · Cited by 533 · see citing works
Intestinal Microbiota in Cardiovascular Health and Disease
Tang, W. H. W., Bäckhed, F., Landmesser, U., & Hazen, S. L. (2019) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2019.03.024 · Cited by 508 · see citing works
“Detection of this “food metabolome” provides a unique opportunity to gain insight not only for the quality and quantity of food intake, but also for the functional consequences as a result of complex microbial host metabolism (57).”
BackgroundFODMAPs alter symptoms and the metabolome of patients with IBS: a randomised controlled trial
McIntosh, K., Reed, D. E., Schneider, T., Dang, F., Keshteli, A. H., Palma, G. D., Madsen, K. L., Berčík, P., & Vanner, S. J. (2016) · Gut · doi:10.1136/gutjnl-2015-311339 · Cited by 480 · see citing works
The blood exposome and its role in discovering causes of disease
Rappaport, S. M., Barupal, D. K., Wishart, D., Vineis, P., & Scalbert, A. (2014) · Environmental Health Perspectives · doi:10.1289/ehp.1308015 · Cited by 393 · see citing works
Self-citationChallenges, progress and promises of metabolite annotation for LC–MS-based metabolomics
Chaleckis, R., Meister, I., Zhang, P., & Wheelock, C. E. (2018) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2018.07.010 · Cited by 373 · see citing works
Salem, M. A., de Souza, L. P., Serag, A., Fernie, A. R., Farag, M. A., Ezzat, S. M., & Alseekh, S. (2020) · Metabolites · doi:10.3390/metabo10010037 · Cited by 364 · see citing works
Rémond, D., Shahar, D., Gille, D., Pinto, P., Kachal, J., Peyron, M., dos Santos, C. D., Walther, B., Bordoni, A., Dupont, D., et al. (2015) · OncoTarget · doi:10.18632/oncotarget.4030 · Cited by 299 · see citing works
“These technologies should be used to deliver, not only biomarkers of food intake [452], but, more specifically, biomarkers of food bioavailability reflecting the specific functional changes taking place in the aging GIT.”
MethodUse of Metabolomics in Improving Assessment of Dietary Intake
Guasch‐Ferré, M., Bhupathiraju, S. N., & Hu, F. B. (2017) · Clinical Chemistry · doi:10.1373/clinchem.2017.272344 · Cited by 309 · see citing works
“Diet can have effects on 2 different components of the metabolome: the endogenous metabolome, referring to all metabolites present in a biological sample of the host, and the food metabolome, which includes metabolites that are derived from food consumption and their subsequent metabolism in the human body (6).”
BackgroundMeat: The balance between nutrition and health. A review
SMET, S. D., & Vossen, E. (2016) · Meat Science · doi:10.1016/j.meatsci.2016.04.008 · Cited by 302 · see citing works
Biomarkers of Nutrition and Health: New Tools for New Approaches
Picó, C., Serra, F., Rodríguez, A. M., Keijer, J., & Palou, A. (2019) · Nutrients · doi:10.3390/nu11051092 · Cited by 287 · see citing works
“1-Methylhistidine Urine Meat and oily fish consumption Original research [27,35,36] Reviewed in References [30,37]”
MethodDiet, nutrition, and cancer: past, present and future
Mayne, S. T., Playdon, M. C., & Rock, C. L. (2016) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2016.24 · Cited by 261 · see citing works
Mena, P. R., Bresciani, L., Brindani, N., Ludwig, I. A., Pereira‐Caro, G., Angelino, D., Llorach, R., Calani, L., Brighenti, F., Clifford, M. N., et al. (2018) · Natural Product Reports · doi:10.1039/c8np00062j · Cited by 263 · see citing works
Computational Metabolomics: A Framework for the Million Metabolome
Uppal, K., Walker, D. I., Liu, K., Li, S., Go, Y., & Jones, D. P. (2016) · Chemical Research in Toxicology · doi:10.1021/acs.chemrestox.6b00179 · Cited by 241 · see citing works
“3,8,24 27 Summation of these exposures indicates that humans are exposed to 1–3 million chemicals during their lifetime.”
Torkamani, A., Andersen, K. G., Steinhubl, S. R., & Topol, E. J. (2017) · Cell · doi:10.1016/j.cell.2017.08.007 · Cited by 245 · see citing works
García‐Pérez, I., Posma, J. M., Gibson, R., Chambers, E. S., Hansen, T. H., Vestergaard, H., Hansen, T. F., Beckmann, M., Pedersen, O. B., Elliott, P., et al. (2017) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(16)30419-3 · Cited by 244 · see citing works
Self-citationNutrition for the ageing brain: Towards evidence for an optimal diet
Vauzour, D., Camprubi-Robles, M., Miquel-Kergoat, S., Andres-Lacueva, C., Bánáti, D., Barberger-Gateau, P., Bowman, G. L., Caberlotto, L., Clarke, R., Hogervorst, E., et al. (2017) · Ageing Research Reviews · doi:10.1016/j.arr.2016.09.010 · Cited by 241 · see citing works
“In total, more than 145 candidate biomarkers have been proposed for about 20 foods through these food metabolome studies, and interestingly about 75% were phytochemical metabolites (Scalbert et al., 2014).”
InfluentialSelf-citationManach, C., Milenković, D., de Wiele, T. V., Rodriguez‐Mateos, A., de Roos, B., García‐Conesa, M., Landberg, R., Gibney, E. R., Heinonen, M., Tomás-Barberán, F. A., et al. (2016) · Molecular Nutrition & Food Research · doi:10.1002/mnfr.201600557 · Cited by 236 · see citing works
“Non-targeted metabolomics with highresolution mass spectrometry (Q-TOF and Orbitrap instruments) has emerged as a holistic and sensitive approach to analyse in human biofluids the food metabolome which encompasses all the metabolites derived from food intake and digestion, including the plant food bioactive metabolite…”
BackgroundSelf-citationValidation of biomarkers of food intake—critical assessment of candidate biomarkers
Dragsted, L. O., Gao, Q., Scalbert, A., Vergères, G., Kolehmainen, M., Manach, C., Brennan, L., Afman, L. A., Wishart, D. S., Andrés‐Lacueva, C., et al. (2018) · Genes & Nutrition · doi:10.1186/s12263-018-0603-9 · Cited by 232 · see citing works
“While a similar procedure has been suggested previously [9], this is to our knowledge the first attempt to comprehensively and systematically develop a validation procedure for BFIs.”
BackgroundMethodSelf-citationIdentifying biomarkers of dietary patterns by using metabolomics
Playdon, M. C., Moore, S. C., Derkach, A., Reedy, J., Subar, A. F., Sampson, J. N., Albanes, D., Gu, F., Kontto, J. P., Lassale, C. M., et al. (2016) · American Journal of Clinical Nutrition · doi:10.3945/ajcn.116.144501 · Cited by 222 · see citing works
“, recovery, concentration, replacement, or predictive biomarkers) would depend on the metabolite properties (29, 67, 73).”
BackgroundEsophageal cancer in high-risk areas of China: research progress and challenges
Lin, Y., Totsuka, Y., Shan, B., et al. (2016) · Annals of Epidemiology · doi:10.1016/j.annepidem.2016.11.004 · Cited by 199 · see citing works
Brunius, C. F., Shi, L. S., & Landberg, R. (2016) · Metabolomics · doi:10.1007/s11306-016-1124-4 · Cited by 184 · see citing works
“…of Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Insitutet, Box 210, 171 77 Stockholm, Sweden 3 Present Address: Department of Biology and Biological Engineering, Chalmers University of Technology, 412 96 Göteborg, Sweden (Scalbert et al. 2014; Rappaport et al. 2014).”
BackgroundMonitoring wastewater for assessing community health: Sewage Chemical-Information Mining (SCIM)
Daughton, C. G. (2017) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2017.11.102 · Cited by 190 · see citing works
“Foods comprise tens of thousands of chemical constituents (Scalbert et al., 2014).”
Ergothioneine is associated with reduced mortality and decreased risk of cardiovascular disease
Smith, E., Ottosson, F. A., Hellstrand, S., et al. (2019) · Heart · doi:10.1136/heartjnl-2019-315485 · Cited by 177 · see citing works
Radd-Vagenas, S., Duffy, S. L., Naismith, S. L., Brew, B. J., Flood, V. M., & Fiatarone Singh, M. A. (2018) · The American Journal of Clinical Nutrition · doi:10.1093/ajcn/nqx070 · Cited by 176 · see citing works
Comparing metabolite profiles of habitual diet in serum and urine
Playdon, M. C., Sampson, J. N., Cross, A. J., Sinha, R. R., Guertin, K. A., Moy, K. A., Rothman, N., Irwin, M. L., Mayne, S. T., Stolzenberg‐Solomon, R. Z., et al. (2016) · American Journal of Clinical Nutrition · doi:10.3945/ajcn.116.135301 · Cited by 175 · see citing works
Biochemistry of Antioxidants: Mechanisms and Pharmaceutical Applications
Losada‐Barreiro, S., Bayındır, Z. S., Paiva‐Martins, F., & Bravo‐Díaz, C. (2022) · Biomedicines · doi:10.3390/biomedicines10123051 · Cited by 178 · see citing works
Nutritional metabolomics and breast cancer risk in a prospective study
Playdon, M. C., Ziegler, R. G., Sampson, J. N., Stolzenberg‐Solomon, R. Z., Thompson, H. J., Irwin, M. L., Mayne, S. T., Hoover, R. N., & Moore, S. C. (2017) · American Journal of Clinical Nutrition · doi:10.3945/ajcn.116.150912 · Cited by 165 · see citing works
“We identified 113 metabolites that were associated with $1 food, beverage, or dietary supplement, thus providing possible biomarkers for these dietary exposures should they be replicated in future studies, conform to a classical measurement model, or be further identified as a metabolite constituent of the associated…”
BackgroundMetabolomics in the study of retinal health and disease
Laíns, I., Gantner, M., Murinello, S., Lasky-Su, J. A., Miller, J. W., Friedlander, M., & Husain, D. (2018) · Progress in Retinal and Eye Research · doi:10.1016/j.preteyeres.2018.11.002 · Cited by 150 · see citing works
“Additionally, for a more complete understanding of the role of nutrition on the profiles obtained, a nutritional assessment should be performed, for example, using a validated food frequency questionnaire (Scalbert et al., 2014).”
MethodHanhineva, K., Lankinen, M. A., Pedret, A., Schwab, U., Kolehmainen, M., Paananen, J., de Mello, V. D., Solà, R., Lehtonen, M., Poutanen, K. S., et al. (2014) · Journal of Nutrition · doi:10.3945/jn.114.196840 · Cited by 160 · see citing works
Foodomics: A new approach in food quality and safety
Balkir, P., Kemahlıoğlu, K., & Yücel, U. (2020) · Trends in Food Science & Technology · doi:10.1016/j.tifs.2020.11.028 · Cited by 156 · see citing works
Defining the Scope of Exposome Studies and Research Needs from a Multidisciplinary Perspective
Zhang, P., Carlsten, C., Chaleckis, R., Hanhineva, K., Huang, M., Isobe, T., Koistinen, V., Meister, I., Papazian, S., Sdougkou, K., et al. (2021) · Environmental Science & Technology Letters · doi:10.1021/acs.estlett.1c00648 · Cited by 160 · see citing works
Self-citationLipidome as a predictive tool in progression to type 2 diabetes in Finnish men
Suvitaival, T., Bondia‐Pons, I., Yetukuri, L., Pöhö, P., Nolan, J. J., Hyötyläinen, T., Kuusisto, J., & Orešič, M. (2017) · Metabolism · doi:10.1016/j.metabol.2017.08.014 · Cited by 147 · see citing works
“These factors have some influence on metabolism as well as on levels of blood lipids andmetabolites [48,49].”
BackgroundAnalysis of energy metabolism in humans: A review of methodologies
Lam, Y. Y., & Ravussin, É. (2016) · Molecular Metabolism · doi:10.1016/j.molmet.2016.09.005 · Cited by 154 · see citing works
“, the sum of all metabolites that are derived from the digestion and biotransformation of food components [114], enables the use of a combination of biomarkers to assess exposure to dietary components [115], food groups [116,117], or even dietary patterns with high specificity [118,119].”
BackgroundNeveu, V., Moussy, A., Rouaix, H., Wedekind, R., Pon, A., Knox, C., Wishart, D. S., & Scalbert, A. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw980 · Cited by 148 · see citing works
Self-citationPerspective: Dietary Biomarkers of Intake and Exposure—Exploration with Omics Approaches
Maruvada, P., Lampe, J. W., Wishart, D. S., Barupal, D. K., Chester, D. N., Dodd, D., Djoumbou-Feunang, Y., Dorrestein, P. C., Dragsted, L. O., Draper, J., et al. (2019) · Advances in Nutrition · doi:10.1093/advances/nmz075 · Cited by 151 · see citing works
“The application of metabolomics allows a better characterization of this bidirectional relationship between diet and physiology, enabling the measurement of both nutrient and nonnutrient metabolites that could serve as candidate biomarkers (11).”
BackgroundInfluentialSelf-citationBrouwer-Brolsma, E. M., Brennan, L., Drevon, C. A., van Kranen, H. J., Manach, C., Dragsted, L. O., Roche, H. M., Andrés‐Lacueva, C., Bakker, S. J. L., Bouwman, J., et al. (2017) · Proceedings of The Nutrition Society · doi:10.1017/s0029665117003949 · Cited by 148 · see citing works
Self-citationSchmidt, J. A., Rinaldi, S., Ferrari, P., Carayol, M., Achaintre, D., Scalbert, A., Cross, A. J., Gunter, M. J., Fensom, G. K., Appleby, P. N., et al. (2015) · American Journal of Clinical Nutrition · doi:10.3945/ajcn.115.111989 · Cited by 140 · see citing works
“In recent years, metabolomics has been introduced into epidemiologic research with the aims of identifying novel risk factors for disease and biomarkers of diet and improving our understanding of disease mechanisms (4).”
BackgroundSelf-citationEdmands, W. M. B., Ferrari, P., Rothwell, J. A., Rinaldi, S., Slimani, N., Barupal, D. K., Biessy, C., Jenab, M., Clavel‐Chapelon, F., Fagherazzi, G., et al. (2015) · American Journal of Clinical Nutrition · doi:10.3945/ajcn.114.101881 · Cited by 141 · see citing works
Self-citationZamora‐Ros, R., Touillaud, M. S., Rothwell, J. A., Romieu, I., & Scalbert, A. (2014) · American Journal of Clinical Nutrition · doi:10.3945/ajcn.113.077743 · Cited by 135 · see citing works
Self-citationMiMeDB: the Human Microbial Metabolome Database
Wishart, D. S., Oler, E., Peters, H., Guo, A., Girod, S., Han, S., Saha, S., Lui, V. W., LeVatte, M., Gautam, V., et al. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac868 · Cited by 119 · see citing works
“Human exposome and diet data is found in databases such as FooDB (21) or Exposome Explorer (22), while health effect data and microbial metabolite descriptions are available in the Human Metabolome Database (HMDB) (23) or the E.”
MethodSelf-citationMetabolomic profiles as reliable biomarkers of dietary composition
Esko, T., Hirschhorn, J. N., Feldman, H. A., Hsu, Y.-H. H., Deik, A., Clish, C. B., Ebbeling, C. B., & Ludwig, D. S. (2017) · American Journal of Clinical Nutrition · doi:10.3945/ajcn.116.144428 · Cited by 115 · see citing works
The Consortium of Metabolomics Studies (COMETS): Metabolomics in 47 Prospective Cohort Studies
Yu, B., Zanetti, K. A., Temprosa, M. G., Albanes, D., Appel, N., Barrios-Barrera, C., Ben‐Shlomo, Y., Boerwinkle, E., Casas, J. P., Clish, C. B., et al. (2019) · American Journal of Epidemiology · doi:10.1093/aje/kwz028 · Cited by 105 · see citing works
“Metabolomics studies have also identified biomarkers of blood pressure (21), obesity (22-24), diet and nutrition (25-35), physical activity/sedentary behavior (36), reproductive factors (37, 38), and pharmacological therapies (39).”
BackgroundNMR-based metabolomics: From sample preparation to applications in nutrition research
Brennan, L. (2014) · Progress in Nuclear Magnetic Resonance Spectroscopy · doi:10.1016/j.pnmrs.2014.09.001 · Cited by 112 · see citing works
Self-citationMetabolomics as a tool in nutritional research
Gibbons, H., O’Gorman, A., & Brennan, L. (2014) · Current Opinion in Lipidology · doi:10.1097/mol.0000000000000140 · Cited by 108 · see citing works
Self-citationEnhancing metabolomics research through data mining
Martínez‐Arranz, I., Mayo, R., Pérez-Cormenzana, M., Mincholé, I., Salazar, L., Alonso, C., & Mato, J. M. (2015) · Journal of Proteomics · doi:10.1016/j.jprot.2015.01.019 · Cited by 109 · see citing works
Brennan, L., & Hu, F. B. (2018) · Molecular Nutrition & Food Research · doi:10.1002/mnfr.201701064 · Cited by 108 · see citing works
Self-citationKöhler, I., Hankemeier, T., van der Graaf, P. H., Knibbe, C. A. J., & van Hasselt, J. G. C. (2017) · European Journal of Pharmaceutical Sciences · doi:10.1016/j.ejps.2017.05.018 · Cited by 107 · see citing works
“Diet and changes in bodyweight may also influence the metabolome (Scalbert et al. 2014).”
BackgroundHigh-resolution metabolomics of occupational exposure to trichloroethylene
Walker, D. I., Uppal, K., Zhang, L., Vermeulen, R., Smith, M., Hu, W., Purdue, M. P., Tang, X., Reiss, B., Kim, S., et al. (2016) · International Journal of Epidemiology · doi:10.1093/ije/dyw218 · Cited by 107 · see citing works
A review of nanoscale LC-ESI for metabolomics and its potential to enhance the metabolome coverage
Chetwynd, A. J., & David, A. (2018) · Talanta · doi:10.1016/j.talanta.2018.01.084 · Cited by 107 · see citing works
“In some cases, these metabolites may be exogenous in source (e.g., xenobiotics), such as food additives from the diet [5], pharmaceutical intake (e.g. anti-inflammatory drugs and mild analgesics, antidepressants) [6, 7] or use of cosmetics (e.g., parabens, UV filters) [8].”
BackgroundCosta, M., Bayındır, Z. S., Losada‐Barreiro, S., Paiva‐Martins, F., Saso, L., & Bravo‐Díaz, C. (2021) · Biomedicines · doi:10.3390/biomedicines9121909 · Cited by 108 · see citing works
“In contrast, polymeric polyphenols, such as proanthocyanidins, are poorly absorbed [60,67].”
BackgroundNutritional Metabolomics and the Classification of Dietary Biomarker Candidates: A Critical Review
Rafiq, T., Azab, S. M., Teo, K. K., Thabane, L., Anand, S. S., Morrison, K. M., de Souza, R. J., & Britz‐McKibbin, P. (2021) · Advances in Nutrition · doi:10.1093/advances/nmab054 · Cited by 105 · see citing works
A scheme for a flexible classification of dietary and health biomarkers
Gao, Q., Praticò, G., Scalbert, A., Vergères, G., Kolehmainen, M., Manach, C., Brennan, L., Afman, L. A., Wishart, D. S., Andrés‐Lacueva, C., et al. (2017) · Genes & Nutrition · doi:10.1186/s12263-017-0587-x · Cited by 99 · see citing works
“Therefore, it is a prerequisite that the biomarkers meet a sufficient level of validation so that both analytical and biological aspects of the biomarker measurement methods are validated [26].”
BackgroundSelf-citationDiet and Cardiovascular Disease: Advances and Challenges in Population-Based Studies
Pan, A., Lin, X., Hemler, E. C., & Hu, F. B. (2018) · Cell Metabolism · doi:10.1016/j.cmet.2018.02.017 · Cited by 96 · see citing works
“This approach can also identify biomarkers for specific dietary components, enabling us to achieve better diet and nutritional assessment in free-living populations (Scalbert et al., 2014).”
BackgroundEmerging new strategies for successful metabolite identification in metabolomics.
Bingol, K., Bruschweiler-Li, L., Li, D.-W., Zhang, B., Xie, M., & Brüschweiler, R. (2016) · Bioanalysis · doi:10.4155/bio-2015-0004 · Cited by 81 · see citing works
Nutrigenomics in the modern era
Mathers, J. C. (2016) · Proceedings of The Nutrition Society · doi:10.1017/s002966511600080x · Cited by 111 · see citing works
“This food metabolome can be used to identify biomarkers of intake of individual foods and of eating patterns (figure from Scalbert et al.((44))).”
BackgroundInfluentialPrimers on nutrigenetics and nutri(epi)genomics: Origins and development of precision nutrition
Bordoni, L., & Gabbianelli, R. (2019) · Biochimie · doi:10.1016/j.biochi.2019.03.006 · Cited by 95 · see citing works
“For all these reasons, it is clear that application of nutrigenomics research can offer considerable potential to improve public health [178].”
BackgroundTrôst, K., Ulaszewska, M., Stanstrup, J., Albanese, D., Filippo, C. D., Tuohy, K. M., Natella, F., Scaccini, C., & Mattivi, F. (2018) · Food Research International · doi:10.1016/j.foodres.2018.06.016 · Cited by 92 · see citing works
Microbiome and metabolome data integration provides insight into health and disease
Shaffer, M., Armstrong, A. J. S., Phelan, V. V., Reisdorph, N. A., & Lozupone, C. (2017) · Translational research · doi:10.1016/j.trsl.2017.07.001 · Cited by 85 · see citing works
The Role of the FODMAP Diet in IBS
Bertin, L., Zanconato, M., Crepaldi, M., Marasco, G., Cremon, C., Barbara, G., Barberio, B., Zingone, F., & Savarino, E. V. (2024) · Nutrients · doi:10.3390/nu16030370 · Cited by 95 · see citing works
Zamora‐Ros, R., Achaintre, D., Rothwell, J. A., Rinaldi, S., Assi, N., Ferrari, P., Leitzmann, M. F., Boutron‐Ruault, M., Fagherazzi, G., Auffret, A., et al. (2016) · Scientific Reports · doi:10.1038/srep26905 · Cited by 92 · see citing works
“All these phenolic compounds are known to be characteristic of the foods with which they are correlated or particularly abundant in these foods 34 and several of them have been proposed as biomarkers of intake for these foods 41,44–46 .”
Self-citationA computationally driven analysis of the polyphenol-protein interactome
Lacroix, S., Badoux, J. K., Scott‐Boyer, M., Parolo, S., Matone, A., Priami, C., Morine, M. J., Kaput, J., & Moco, S. (2018) · Scientific Reports · doi:10.1038/s41598-018-20625-5 · Cited by 87 · see citing works
“Characterizing the human polyphenol metabolome 5,6 is of high relevance for understanding how inter-individual variability results from polyphenol-rich foods consumption and their effects on metabolism and consequent benefits for health 36 .”
BackgroundWang, Y., Gapstur, S. M., Carter, B. D., Hartman, T. J., Stevens, V. L., Gaudet, M. M., & McCullough, M. L. (2018) · Journal of Nutrition · doi:10.1093/jn/nxy027 · Cited by 85 · see citing works
Applications of Metabolomics to Precision Nutrition
LeVatte, M., Keshteli, A. H., Zarei, P., & Wishart, D. S. (2021) · Lifestyle Genomics · doi:10.1159/000518489 · Cited by 85 · see citing works
Self-citationBarnes, S., Benton, H. P., Casazza, K., Cooper, S. J., Cui, X., Du, X., Engler, J. A., Kabarowski, J. H. S., Li, S., Pathmasiri, W., et al. (2016) · Journal of Mass Spectrometry · doi:10.1002/jms.3782 · Cited by 87 · see citing works
Grape and Wine Metabolomics to Develop New Insights Using Untargeted and Targeted Approaches
Pinu, F. R. (2018) · Fermentation · doi:10.3390/fermentation4040092 · Cited by 85 · see citing works
Schmidt, J. A., Fensom, G. K., Rinaldi, S., Scalbert, A., Appleby, P. N., Achaintre, D., Gicquiau, A., Gunter, M. J., Ferrari, P., Kaaks, R., et al. (2017) · BMC Medicine · doi:10.1186/s12916-017-0885-6 · Cited by 82 · see citing works
“Examination of the metabolome may help us identify novel risk factors for prostate cancer [3, 4].”
BackgroundSelf-citationGauglitz, J. M., Aceves, C. M., Aksenov, A. A., Aleti, G., Almaliti, J., Bouslimani, A., Brown, E. A. R., Campeau, A., Caraballo‐Rodríguez, A. M., Chaar, R., et al. (2019) · Food Chemistry · doi:10.1016/j.foodchem.2019.125290 · Cited by 76 · see citing works
Self-citationMetabolomic and Lipidomic Biomarkers for Premalignant Liver Disease Diagnosis and Therapy
Beyoğlu, D., & Idle, J. R. (2020) · Metabolites · doi:10.3390/metabo10020050 · Cited by 78 · see citing works
“It has been estimated that humans are probably exposed to some 1–3 million discrete chemicals in their lifetimes [11] of which >25,000 have already been described in the diet [25].”
BackgroundMünger, L. H., Trimigno, A., Picone, G., Freiburghaus, C., Pimentel, G., Burton, K. J., Pralong, F. P., Vionnet, N., Capozzi, F., Badertscher, R., et al. (2017) · Journal of Proteome Research · doi:10.1021/acs.jproteome.7b00319 · Cited by 78 · see citing works
Nutritional Cognitive Neuroscience: Innovations for Healthy Brain Aging
Zamroziewicz, M. K., & Barbey, A. K. (2016) · Frontiers in Neuroscience · doi:10.3389/fnins.2016.00240 · Cited by 78 · see citing works
“This method allows researchers to measure hundreds to thousands of metabolites at a time (Scalbert et al., 2014).”
BackgroundMethodInfluentialStructure Elucidation of Unknown Metabolites in Metabolomics by Combined NMR and MS/MS Prediction
Boiteau, R. M., Hoyt, D. W., Nicora, C., Kinmonth‐Schultz, H., Ward, J., & Bingol, K. (2018) · Metabolites · doi:10.3390/metabo8010008 · Cited by 78 · see citing works
Towards nutrition with precision: unlocking biomarkers as dietary assessment tools
Cuparencu, C., Bulmuş-Tüccar, T., Stanstrup, J., La Barbera, G., Roager, H. M., & Dragsted, L. O. (2024) · Nature Metabolism · doi:10.1038/s42255-024-01067-y · Cited by 77 · see citing works
“…a food group level, it was shown that certain food groups (for example, fish, fruit and vegetables) are overestimated, other food groups (for example, meat and sweets) are underestimated, and only some food groups (for example, dairy and cereals) are similar when comparing FFQs to 24-h recalls 94 .”
InfluentialSelf-citationNutriome–metabolome relationships provide insights into dietary intake and metabolism
Posma, J. M., García‐Pérez, I., Frost, G. S., Aljuraiban, G. S., Chan, Q. M., Horn, L. V., Daviglus, M. L., Stamler, J., Holmes, E. C., Elliott, P., et al. (2020) · Nature Food · doi:10.1038/s43016-020-0093-y · Cited by 72 · see citing works
Bingol, K., & Brüschweiler, R. (2015) · Current Opinion in Clinical Nutrition & Metabolic Care · doi:10.1097/mco.0000000000000206 · Cited by 73 · see citing works
“MS, on the other hand, is bound to the detection of ionizable metabolites that enter the gas phase, which can be detected at significantly lower concentration than NMR (pM – nM) [5].”
BackgroundPraticò, G., Gao, Q., Scalbert, A., Vergères, G., Kolehmainen, M., Manach, C., Brennan, L., Harsha, P. S. C. S., Afman, L. A., Wishart, D. S., et al. (2018) · Genes & Nutrition · doi:10.1186/s12263-018-0592-8 · Cited by 74 · see citing works
“Two main approaches to discover BFIs should be taken into account: the targeted hypothesisdriven approach, based on previous knowledge of food composition [17, 18], and the data-driven approach, provided typically by untargeted metabolomics studies [4].”
BackgroundSelf-citationHyperFoods: Machine intelligent mapping of cancer-beating molecules in foods
Veselkov, K., Gonzalez, G., Aljifri, S., Galea, D., Mirnezami, R., Youssef, J., Bronstein, M. M., & Laponogov, I. (2019) · Scientific Reports · doi:10.1038/s41598-019-45349-y · Cited by 69 · see citing works
Hörnell, A., Berg, C., Forsum, E., Larsson, C. L., Sonestedt, E., Åkesson, A., Lachat, C. K., Hawwash, D., Kolsteren, P. W., Byrnes, G. B., et al. (2017) · Advances in Nutrition · doi:10.3945/an.117.015941 · Cited by 73 · see citing works
“For example, novel biomarkers can be found in the “food metabolome,” the part of the metabolome directly derived from the digestion and biotransformation of foods and their constituents (116).”
BackgroundCurrent State of Metabolomics Research in Meat Quality Analysis and Authentication
Zhang, T., Chen, C., Xie, K., Wang, J., & Pan, Z. (2021) · Foods · doi:10.3390/foods10102388 · Cited by 74 · see citing works
“In food science, metabolomics can be described as the application of high-throughput analytic chemistry technologies directed at characterising the food metabolome [26].”
BackgroundBarnes, S., Benton, H. P., Casazza, K., Cooper, S. J., Cui, X., Du, X., Engler, J. A., Kabarowski, J. H. S., Li, S., Pathmasiri, W., et al. (2016) · Journal of Mass Spectrometry · doi:10.1002/jms.3672 · Cited by 70 · see citing works
“,[20] metabolites arising from gut microbiome and the edible plant metabolome far outnumber metabolites produced by human cells.”
BackgroundMetabolomic markers of healthy dietary patterns in US postmenopausal women
McCullough, M. L., Maliniak, M. L., Stevens, V. L., Carter, B. D., Hodge, R. A., & Wang, Y. (2018) · American Journal of Clinical Nutrition · doi:10.1093/ajcn/nqy385 · Cited by 68 · see citing works
Shanmuganathan, M., Kroezen, Z., Gill, B., Azab, S. M., de Souza, R. J., Teo, K. K., Atkinson, S. A., Subbarao, P., Desai, D., Anand, S. S., et al. (2021) · Nature Protocols · doi:10.1038/s41596-020-00475-0 · Cited by 59 · see citing works
Trifonova, O. P., Maslov, D. L., Balashova, E. E., et al. (2019) · Metabolites · doi:10.3390/metabo9110277 · Cited by 70 · see citing works
“Therefore, data-driven investigations, especially clinical trials, cohort- and papulation-based studies requiring collection, shipment, storage, and analysis of hundreds and thousands of samples could benefit from the DBS sampling advantages [39,40].”
BackgroundColby, S. E., Zhou, W., Allison, C., Mathews, A., Olfert, M. D., Morrell, J. S., Byrd‐Bredbenner, C., Greene, G. W., Brown, O. N., Kattelmann, K. K., et al. (2020) · Nutrients · doi:10.3390/nu12092611 · Cited by 66 · see citing works
“Biomarkers that can be used to measure different components of dietary intake include carotenoids, fatty acids, vitamins, polyphenols, food contaminants, inorganic compounds, and enzymes [34].”
BackgroundFoodomics for human health: current status and perspectives
Braconi, D., Bernardini, G., Millucci, L., & Santucci, A. (2017) · Expert Review of Proteomics · doi:10.1080/14789450.2018.1421072 · Cited by 67 · see citing works
Food intake biomarkers for green leafy vegetables, bulb vegetables, and stem vegetables: a review
Brouwer-Brolsma, E. M., Brandl, B., Buso, M. E. C., Skurk, T., & Manach, C. (2020) · Genes & Nutrition · doi:10.1186/s12263-020-00667-z · Cited by 71 · see citing works
Self-citationDietary biomarkers—an update on their validity and applicability in epidemiological studies
Landberg, R., Karra, P., Hoobler, R., Loftfield, E., Huybrechts, I., Rattner, J. I., Noerman, S., Claeys, L., Neveu, V., Vidkjær, N. H., et al. (2023) · Nutrition Reviews · doi:10.1093/nutrit/nuad119 · Cited by 76 · see citing works
Self-citationA metabolomics approach to the identification of biomarkers of sugar-sweetened beverage intake
Gibbons, H., McNulty, B. A., Nugent, A. P., Walton, J., Flynn, A., Gibney, M. J., & Brennan, L. (2015) · American Journal of Clinical Nutrition · doi:10.3945/ajcn.114.095604 · Cited by 67 · see citing works
“The food metabolome and metabolomic dietary biomarkers were recently presented in a review (27).”
BackgroundSelf-citationGetting the right answers: understanding metabolomics challenges
Beisken, S., Eiden, M. J., & Salek, R. M. (2014) · Expert Review of Molecular Diagnostics · doi:10.1586/14737159.2015.974562 · Cited by 62 · see citing works
“The biological chemical space does not only include endogenous metabolites but also food and environmental metabolites that interact with the biological system, being digested and biotransformed, making a comprehensive enumeration infeasible [121] .”
BackgroundKhakimov, B., Poulsen, S. K., Savorani, F., Acar, E., Gürdeniz, G., Larsen, T. M., Astrup, A. V., Dragsted, L. O., & Engelsen, S. B. (2016) · Journal of Proteome Research · doi:10.1021/acs.jproteome.6b00109 · Cited by 63 · see citing works
Self-citationKellogg, J. J., Graf, T. N., Paine, M. F., McCune, J. S., Kvalheim, O. M., Oberlies, N. H., & Cech, N. B. (2017) · Journal of Natural Products · doi:10.1021/acs.jnatprod.6b01156 · Cited by 67 · see citing works
Diet‐derived microbial metabolites in health and disease
Roager, H. M., & Dragsted, L. O. (2019) · Nutrition Bulletin · doi:10.1111/nbu.12396 · Cited by 60 · see citing works
Self-citationFu, J., Zhang, L., Li, W., Zhang, Y., Zhang, Y., Liu, F., & Zou, L. (2021) · Food Chemistry · doi:10.1016/j.foodchem.2021.130697 · Cited by 66 · see citing works
Garcia‐Aloy, M., Llorach, R., Urpí-Sardà, M., Tulipani, S., Estruch, R., Martínez‐González, M. Á., Corella, D., Fitó, M., Ros, E., Salas‐Salvadó, J., et al. (2014) · Journal of Proteome Research · doi:10.1021/pr500425r · Cited by 66 · see citing works
Self-citationMetabolomics as a tool in the identification of dietary biomarkers
Gibbons, H., & Brennan, L. (2016) · Proceedings of The Nutrition Society · doi:10.1017/s002966511600032x · Cited by 67 · see citing works
“Analysis of metabolomic data is commonly performed using multivariate statistics and there are an increasing selection of databases and tools available to assist in the interpretation of these multivariate results((20)).”
BackgroundMethodInfluentialSelf-citation
- Authors
- Scalbert, A., Brennan, L., Manach, C., Andres-Lacueva, C., Dragsted, L. O., Draper, J., Rappaport, S. M., van der Hooft, J. J., & Wishart, D. S.
- Affiliations
- University College Dublin (IE)
- ORCID
- Venue
- The American Journal of Clinical Nutrition
- Publisher
- Elsevier BV
- Published
- 2014-06
- Volume
- 99
- Issue
- 6
- Pages
- 1286-1308
- ISSN
- 0002-9165 (ISSN-L)
- OpenAlex
- W2169779482
- Cited by
- 519
- References
- 198
- Citations by year
- 2026: 19 · 2025: 32 · 2024: 38 · 2023: 27 · 2022: 39 · 2021: 50 · 2020: 49 · 2019: 40 · 2018: 61 · 2017: 60 · 2016: 61 · 2015: 25 · 2014: 16
- FWCI
- 5.08
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- American Journal of Clinical Nutrition (publishedVersion, other-oa)
- PubMed (publishedVersion)
- HAL (submittedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (submittedVersion)
- Funders
- World Health Organization
- European Commission (KBBE-2011-5, FP7-KBBE-2011–5, 289511, 260791)
- Agence Nationale de la Recherche (ANR-10-ALIA-0007, ANR-10)
- Medical Research Council (MR/J010308/1)
- FP7 Food, Agriculture and Fisheries, Biotechnology
- CHIST-ERA
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Nutrition, Genetics, and Disease
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Nutritional Studies and Diet
- Keywords
- dietary biomarkers, dietary exposure assessment, metabolomics, metabolomics databases, dietary bioactive compounds
- MeSH terms
- Animals, Diet, Digestion, Food, Humans, Models, Biological, Biomarkers, Nutritional Sciences, Metabolomics, Metabolome
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-07.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-07.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review