Biomarkers of food intake (BFIs) are a promising tool for limiting misclassification in nutrition research where more subjective dietary assessment instruments are used. They may also be used to assess compliance to dietary guidelines or to a dietary intervention. Biomarkers therefore hold promise for direct and objective measurement of food intake. However, the number of comprehensively validated biomarkers of food intake is limited to just a few. Many new candidate biomarkers emerge from metabolic profiling studies and from advances in food chemistry. Furthermore, candidate food intake biomarkers may also be identified based on extensive literature reviews such as described in the guidelines for Biomarker of Food Intake Reviews (BFIRev). To systematically and critically assess the validity of candidate biomarkers of food intake, it is necessary to outline and streamline an optimal and reproducible validation process. A consensus-based procedure was used to provide and evaluate a set of the most important criteria for systematic validation of BFIs. As a result, a validation procedure was developed including eight criteria, plausibility, dose-response, time-response, robustness, reliability, stability, analytical performance, and inter-laboratory reproducibility. The validation has a dual purpose: (1) to estimate the current level of validation of candidate biomarkers of food intake basedonanobjective andsystematicapproachand (2)topinpoint which additional studies are needed to provide full validation of each candidate biomarker of food intake. This position paper on biomarker of food intake validation outlines the second step of the BFIRev procedure but may also be used as such for validation of new candidate biomarkers identified, e.g., in food metabolomic studies. Keywords: Biomarker, Validation, Nutrition, Assessment of food intake, Metabolomics, Review Background used in nutrition-related health research . According to Quantitative assessment of food intake is normally done this scheme, the biomarker classification is determined by by the use of questionnaires, diaries, or interviews [1, 2]. the intended use of the biomarker measurement. An im- These instruments are error-prone due to their subject- portant additional issue relates to biomarker validation. ive nature . The use of qualitative biomarkers to as- Such validation will also depend on the purpose of using sess recent food intake could be a qualification tool to the biomarker, i.e., on how the measurement may be inter- improve the value of current instruments for food intake preted. The development of a validation scheme would assessment. Further development of such biomarkers of therefore be necessary for each of the different biomarker food intake to improve their use for quantitative assess- classes. Within the FoodBAll consortium (www.foodmeta- ment of recent or more long-term food intake could be bolome.org), the class of biomarkers of food intake (BFIs) a long-term goal in this field. In a recent paper, we have is the main focus area. A large number of candidate BFIs suggested a flexible classification scheme for biomarkers are currently being observed in food metabolomic studies, and others are found by extensive literature reviews such as those following the BFIRev guidelines . There are * Correspondence: firstname.lastname@example.org Department of Nutrition, Exercise and Sports, University of Copenhagen, also intervention studies covering a range of foods Copenhagen, Denmark performed in the FoodBAll project to discover new Full list of author information is available at the end of the article © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Dragsted et al. Genes & Nutrition (2018) 13:14 Page 2 of 14 biomarkers of food intake. This gives hope that candidate Methods biomarkers may be found for a large number of foods. In order to identify papers dealing with the validation of However, they must be validated to assure that they accur- BFIs, we carried out an extensive literature search fol- ately represent the level of intake of the food considered, lowing the BFIRev methodology proposed previously . that the sample type and time of sampling is appropriate Briefly, searches were carried out in three databases for the intended use, and that the analytical method is (PubMed, Scopus, and ISI Web of Knowledge) in No- valid according to current standards. vember 2016. In PubMed, the search terms were (nutri- Validation of a BFI is not only a matter of analytical tion*[Title/Abstract]) AND (biomarker*[Title] OR validity measured according to standards  but also a marker*[Title]) AND (validation*[Title/Abstract] OR matter of biological (nutritional) validity, i.e., what it validity*[Title/Abstract] OR validate*[Title/Abstract] OR represents in terms of intake of a specific food under the assessment*[Title/Abstract]) NOT (animal OR rat OR conditions of the study. Clearly, this will depend on fac- mouse OR mice OR pig) NOT (disease*[Title] OR risk*[- tors such as variability of the content of biomarker pre- Title] OR inflammat*[Title/Abstract] OR patient*[Title]). cursors in foods and of their metabolism and kinetics in To avoid all the studies concerned with a single bio- individuals. Therefore, validation criteria must include marker while keeping studies on validation in general, also biological aspects of the biomarker . It is also im- we avoided using nutrient* or food* in the search strat- portant that the validity of a BFI is reconsidered for the egy. The fields used for the other two databases were intended purpose whenever it is applied. Some efforts [Article Title/Abstract/Keywords] for Scopus and have been made previously to evaluate biomarkers for [Topic] for ISI Web of Science to replace [Title/Ab- food or dietary intake in nutrition studies. For instance, stract] for PubMed. The search was limited to papers in de Vries et al. proposed criteria to assess the meaningful- English language and with no restriction applied for the ness of surrogate markers and pointed out that no clear publication dates. The review papers discussing the de- criteria could be set up for dietary intake markers, diet- velopment and application of biomarkers in the nutri- ary exposure markers, and nutritional status markers tion field were selected in the process outlined in Fig. 1. due to the lack of established validation criteria ; Scal- The first draft scheme of validation criteria was based bert et al. suggested a grading system for BFIs to indicate on criteria proposed in the review papers found by this their level of validation. This approach introduces the literature search. This list was revised by three rounds of concept of stepwise improvement of validity, e.g., by the commenting by co-authors as well as feedback from pre- use of a score or a set of criteria . Several authors sentations at international conferences. have pointed out that a number of factors such as kin- etic variables, factors related to sampling and storage, Results and factors related to the variability of food composition The literature search provided a range of factors to be are important determinants of measurement error be- considered for the validation and application of bio- yond simple analytical error [10–14]. However, there is markers in general or for BFIs in particular. These were no systematic method established to validate BFIs. Here, sub-grouped to provide eight separate characteristics we propose a validation scheme for this particular group that may together comprise biomarker validity for BFIs of biomarkers. For newly discovered candidate BFIs, the (Table 1). There is no intended hierarchy in the order. suggested validation criteria incorporate analytical and A validation assessment system (questions 1–8) was biological aspects into a common system using eight developed based on these characteristics. Validation can aspects of validation to allow partial or full validation. be assessed for each candidate biomarker by evaluating Our purpose was to review the current stage of BFI the current evidence related to each of the characteris- validation and to suggest appropriate steps for asses- tics proposed, thereby answering the related question. sing the validity of candidate BFIs. By applying this Possible answers are Y (yes, the criterion is fulfilled for validation scheme, researchers could obtain the infor- at least some use of the biomarker), N (the criterion has mation needed to make good use of the BFIs and an been investigated but it was not fulfilled), or U (the cri- overview of the additional studies needed for the de- terion has not been investigated or data is not available). velopment of the BFIs. To our knowledge, this is the Following the commenting rounds, the eight aspects of first comprehensive scheme developed for this area. validation remained although some of them are clearly The resulting validation criteria and methodology complex and may therefore only be answered positively have been tested using Allium intake biomarkers as under certain conditions and these conditions must an example and will subsequently be applied on can- therefore be stated. The validation questions and their didate BFIs for all major foods or food groups. These sub-criteria for answering “yes” are shown in Table 2. reviews will be published in this thematic issue of The first five criteria are related to the biological valid- Genes & Nutrition. ity and applicability in nutrition research; the remaining Dragsted et al. Genes & Nutrition (2018) 13:14 Page 3 of 14 Fig. 1 Flow diagram of search for papers on criteria for biomarker validation in nutrition field three criteria are related to their analytical performance. since each criterion may have different weight in differ- Many of these aspects may depend on the intended ap- ent applications of a biomarker. So validity may be suffi- plication of the BFI, and the validity cannot therefore be cient without eight Ys for some use of a biomarker. For answered unambiguously in all cases. The criteria should instance, the short-term kinetics would normally be ir- be seen as representative of the most important aspects relevant for biomarkers to be measured in hair samples of the validation to be considered in the systematic where only multiple-dose kinetics is of importance. evaluation of each BFI. The conditions under which the BFI is valid must therefore be added to qualify the valid- Discussion ation. In their most simple form, the validation criteria Based on literature review and a consensus procedure, we would translate into the questions added in the table. divided aspects of biological (nutritional) and analytical Assessment of validity should consequently be possible validity into eight criteria. The underlying aspects of each to perform in a reliable and documented manner using criterion may include several potential sources of unin- these questions. For Y and N answers, the conditions tended variability in food intake assessments using the BFI under which the validity has been assessed may be stated in question. While a similar procedure has been suggested as a comment. For instance, trimethylamine oxide previously , this is to our knowledge the first attempt to (TMAO) may be a valid short-term biomarker for intake comprehensively and systematically develop a validation of cold-water fish from the sea when measured in urine procedure for BFIs. When applying this validation proced- samples . However, contents of TMAO may be lower ure, it is important to be specific about the intended use. in some other fish making the marker unreliable for cer- This could be assessment of intake of a specific food or tain geographical areas . the whole food group. For instance, biofluid measure- The validation criteria may also be seen as criteria for ments of caffeine may be seen as a BFI for the food group prioritization of further work on biomarker validation. of caffeinated foods and drinks while being less useful for Whenever a question is answered by “N” or “U,” there is any specific drink such as coffee. It may also be reasonable a need for an additional work to provide the lacking to include aspects of variability such as that caused by information. However, a conditional “Y” would also indi- metabolism. Caffeine measurement would reveal recent cate that further work may be needed. This should help intake of caffeine-containing products, but it is extensively to identify the most promising BFIs and to plan any val- metabolized. Caffeine metabolism has variable kinetics idation work still needed in order to fully validate them. based on common variation in genetics and lifestyle The system is not geared towards scoring of validity factors [17, 18], and this might cause limitations for Dragsted et al. Genes & Nutrition (2018) 13:14 Page 4 of 14 Table 1 Factors to be considered for the validation and application of biomarkers suggested in previous literature Characteristic Factors to be considered for the validation and application of biomarkers References 1. Plausibility � Biomarkers should be specific to the food (having the ability to distinguish the food or food [71–81] component of interest from other foods or food components). � There should be a food chemistry or experimentally based explanation for why the food intake should increase the biomarker, e.g., the biomarker should be a metabolite of a food component. 2. Dose-response � Evaluation of the dose-response relationship should be performed to assess the suitability [9, 10, 12, 13, 71, of the biomarker over a range of intakes. 73–88] � Limit of detection should be evaluated to provide the information about how responsive (sensitive) the biomarker is. � Baseline habitual level needs to be established. � Bioavailability of (the precursor of) the biomarker should be evaluated to provide the information about its sensitivity to intake. � Detailed information about saturation effects of the biomarker should be known. 3. Time-response � The half-life of the biomarker should be evaluated to specify the degree to which a [9, 10, 12, 71, 74, 76, biomarker reflects exposure, e.g., days, weeks, months or years. 77, 79, 82, 85–87, 89] � Kinetics (comprises “formation, distribution, metabolism and excretion”) should be known to make choices, such as on sampling time and matrices. � Timing of measurement in relation to bioavailability and bioefficacy must be considered. � Temporal relation of the biomarker with dietary intake should be considered to provide information for choosing types of specimen. � Repeated measures of the biomarker over time should be evaluated to provide insight into the reproducibility of biomarker concentrations, and thus, the likelihood that the biomarker is a stable estimate of long-term intake. 4. Robustness � Suitability of the biomarker in a free-living population should be investigated using a (controlled) [12, 76, 80, 85] habitual diet to provide information such as its interactions with other foods and its applicability to a certain group of population. � The biomarker should be validated in a controlled dietary intervention studies as well as in cross-sectional studies. � Validation of the biomarker in different subjects and study settings is needed. � Information such as interactions with other food components and influence of food matrix should be excluded or known to be manageable. 5. Reliability � Comparison of the biomarker and a gold standard or reference method that provides [9, 11, 13, 71, 72, 74, a good measure of the true exposure is necessary. 75, 77, 84, 87, 90] � Biomarkers identified using samples from cohort studies should ideally be combined with intervention studies to demonstrate their direct relationships with intake. � Comparison between the biomarker and an appropriate dietary assessment method should be performed. � A biomarker should be confirmed in accordance with other biomarkers for the same food or foods. � Validation of a biomarker can be attempted by measuring it in animals fed different nutrient intake under tightly controlled conditions. 6. Stability � Suitable protocols for sample collection, processing, and storage are needed to  keep the sample quality for several years. � Trials should be carried out to determine whether analytes undergo decomposition during storage. 7. Analytical performance � Precision, accuracy, and detection limits of the method should be evaluated. [10–13, 71–74, 76, � Comparison against validated methodology or references or references materials 82, 84, 91] is needed. � The calculation of inter- and intra-batch variation should be performed. � Statistical quality control procedures (coefficient of variance, standard deviation and inaccuracy limits for data) should be established. 8. Reproducibility � There is the need to develop and use accurate and validated analytical methods to [12, 71, 78] adequately compare the data obtained in different laboratories. quantitative use. It could therefore be considered whether grain) wheat and rye intake are a good example of this the sum of major caffeine metabolites in a 24-h urine [20, 21]. More recently, BFIs are frequently suggested might perform better as a quantitative BFI for this class of from metabolomic studies. For instance, proline betaine foods . was observed in several early studies and further con- Candidate BFIs have often been based mainly on infor- firmed as a BFI for citrus by Heinzmann et al. . The mation from food chemistry pointing to special com- metabolic profiling studies can have highly variable de- pounds found only in specific foods or food groups. The signs, e.g., experimental meal studies, dietary intervention relatively well-studied alkylresorcinols BFIs of (whole studies, or cross-sectional studies [9, 23]. The study in Dragsted et al. Genes & Nutrition (2018) 13:14 Page 5 of 14 Table 2 Eight groups of validity criteria for biomarkers of food intake Validation criterion Validation questions and their sub-criteria for answering “yes” 1. Plausibility Q: Is the marker compound plausible as a specific BFI for the food or food group (chemical/biological plausibility)? ((The BFI is likely to be a metabolite or process-related derivative of a compound known to occur in the food or food group) OR (the BFI has been identified as a putative biomarker for the food/food group) OR (the compound was identified as a putative biomarker in a metabolomics investigation)) AND (variability of (parent) compound within food or food group (if known) is limited) AND ((the level of the (parent) compound in other foods is comparatively low) OR (presence only in other foods not commonly consumed)) 2. Dose-response Q: Is there a dose-response relationship at relevant intake levels of the targeted food (quantitative aspect)? (The dose-response relationship of the BFI has been established using several intake levels (in a meal study) OR (in different meal studies where the results were comparable) OR (in cross-sectional study or longitudinal observational studies)) AND (the background level of the BFI is 0 or low) Information about the limits for common background levels and saturation kinetics of the BFI should be provided as a comment 3. Time-response Q: Is the biomarker kinetics described adequately to make a wise choice of sample type, frequency and time window (time-response)? a. (The single-meal time-response relationship of the BFI has been described for a defined sample type and time window in a meal study) OR b. (The kinetics of the BFI after repeated intakes has been described for a defined sample type in a meal study) OR (accumulation of the BFI in certain sample types has been observed) Information about ADME and enzyme induction, inhibition, or altered excretion in the metabolism of the BFI or its precursor could be provided as a comment. 4. Robustness Q: Has the marker been shown to be robust after intake of complex meals reflecting dietary habits of the targeted population (robustness)? ((The BFI has been measured and shown to be robust after intake of complex meals (in intervention studies) OR (in observational studies)) AND ((There is no confounding food observed) OR (The level of the BFI from the confounding food is low) OR (The confounding foods are not commonly consumed)) 5. Reliability Q: Has the marker been shown to compare well with other markers or questionnaire data for the same food/food group (reliability)? (The BFI has been compared well (with other biomarkers for the same food or food group) OR (with dietary assessment instruments) OR (with data in studies with highly controlled setting and supervised intake) 6. Stability Q: Is the marker chemically and biologically stable during biospecimen collection and storage, making measurements reliable and feasible (stability)? (The BFI is chemically and biologically stable during biospecimen collection, processing and storage) OR (The BFI is not stable but suitable protocol has been established to achieve the stabilisation of the BFI) 7. Analytical performance Q: Are analytical variability (CV%), accuracy, sensitivity and specificity known as adequate for at least one reported analytical method (analytical performance)? (The protocol of the method has been well described and could be repeated) AND (The method has been compared with validated method or references) AND (The analytical variability (CV%), accuracy, sensitivity and specificity have been described) 8. Reproducibility Q: Has the analysis been successfully reproduced in another laboratory (reproducibility)? (The analysis with the same method has been performed in at least 2 different laboratories) AND (The measurements of the BFI obtained from different laboratories are comparable) which a BFI is initially discovered may additionally provide or more other criteria, the discussion of each criterion some information related to one or more criteria of valid- also includes some of the interrelations with the others. ation. This depends on the study design, e.g., plausibility based on food chemistry studies, kinetics based on post- 1. Plausibility. The amount of analytical information prandial concentrations in plasma or urine from meal on foods and food groups is extensive and studies, quantitative aspect based on different levels of increasing rapidly with the use of metabolomics in exposures in dietary interventions, or robustness based on food chemistry. Available knowledge on food findings from a cross-sectional or other observational composition and food compound metabolism is setting. more and more integrated into online databases Each of the eight criteria defined above is further dis- (FooDB, Phenol-Explorer, PhytoHub, etc.), which cussed below along with suggestions on the studies and facilitate the identification of biomarkers specific for sample methods most suitable for validation. Since none individual foods. A candidate BFI may therefore be of the validation questions in Table 2 may be answered suggested and evaluated based on the food chemistry without influence of some of the aspects covered by one literature as already exemplified in the case of the Dragsted et al. Genes & Nutrition (2018) 13:14 Page 6 of 14 alkylresorcinols. An important aspect here is the are transferred into deeper compartments and only variability of contents within the food source, e.g., as slowly released it is not possible to assess their a result of different varieties, and growth conditions. short-term kinetics in blood after a single exposure High and unpredictable variability may reduce the . Postprandial dose-response is therefore usefulness of a food compound as a BFI; this may for obviously not always needed for validation and must instance be the case for feed and pasture-derived therefore often be answered together with a compounds in dairy products . Another possible comment explaining the possible reason for the lack origin of a candidate BFI could be the food processing of dose-response. The presence of postprandial such as fermentation or heating. For instance, during dose-response indicates that the marker has the cooking of meat, heterocyclic aromatic amines relatively fast kinetics into the body fluid sampled could be formed from creatinine, creatine, and amino and that background levels are low compared to the acids at high temperature, which may be a biomarker change following food intake. This would happen of intensively cooked meat intake . As an example for relatively water soluble, uniquely food-derived of more complex markers based on food production, compounds that diffuse or are transported into the four different beer metabolites have been proposed as blood, that are not removed by the liver in the first a combined marker of beer intake, two of them pass, that are not the subject of multiple pathways reflecting beer raw materials (hops and barley) and of degradation, and that are excreted at a similar the other two reflecting the production processes rate in most subjects. A typical example of such a (malting and fermentation), respectively . If a BFI is proline betaine, which is almost inert to candidate biomarker is highly specific (only minor human metabolism while reflecting recent exposure interference is expected from other food sources), or to citrus fruit products . For the measurement unique for the food or food group in question, it is of urinary 1-methylhistidine, representing meat likely to have good plausibility. Interference from intake, postprandial dose-response is visible in other sources may be expected to be low because highly controlled studies but the background level other potential sources have either low content or a is too high so that lower meat intakes cannot be very low level of consumption in the population detected [29–31]. Excretion of 3-methylhistidine is considered. For newly suggested BFIs, this check therefore preferred, but this compound is not found based on current knowledge from food chemistry in in all meats and seems to be a better marker for combination with knowledge on possible host chicken than for others . Actually, the situation metabolism may represent the first step to evaluate for 1-methylhistidine is not unusual and many chemical and biological plausibility. Plausibility is an biomarkers may have background levels due to low essential criterion for any BFI but not sufficient, as a levels in some other foods and/or to endogenous very specific compound may for example be too formation. Even proline betaine is present at 100– variable in contents in the food, too unstable in the 1000 times lower levels in other fruits and food or in body fluids, or be unreliable due to a high vegetables, so a low background level may be seen inter-individual variation in ADME; some of these even without citrus exposure . Whenever aspects are covered below. possible, the limits for common background levels 2. Dose-response after a single exposure. This may therefore be added in a comment to this criter- validation criterion may be satisfied if short-term or ion to describe levels that do not indicate exposure long-term dose-response relationship in humans to the target food. Any indication of saturation kin- has been clearly established for the candidate etics at higher intake levels may be another biomarker. For compounds with short half-lives, phenomenon that may be relevant to note in BFI this may be accomplished with meal studies using short-term dose-response studies although several intake levels of a single food having a known saturation phenomena in nutrition are currently content of the BFI or its precursor. Short-term best known from nutrient intake biomarkers (NIBs) dose-response information may also be achieved by such as ascorbate. analyzing cross-sectional or longitudinal data where 3. a. Time-response after a single exposure. This 24 h records of food intake is available together question relates to the optimal time window for with appropriate biological samples. BFIs with measurement of a BFI. This depends on the uptake longer half-lives may not show postprandial dose- or elimination half-life of the BFI determined after a response kinetics at all and still be good biomarkers single exposure to the food. The importance of this for assessing longer term ingestion of a food. Lipid- criterion may again depend on the intended soluble compounds such as lycopene are examples application; it is important in order to point out of this . For compounds like carotenoids, which whether there is evidence to use the BFI for a Dragsted et al. Genes & Nutrition (2018) 13:14 Page 7 of 14 defined sample type and time window. The factors instance, the measurement of alcoholic beverage in- causing variability in postprandial dose-response take by ethyl glucuronide in hair may be suitable (variable contents in foods, variable ADME) would for estimating habitual intakes since it builds up in also apply here. Qualifying statements relating to hair after exposure to multiple doses in the longer food and individual variability may consequently be term . This would not be the case for urine or needed in addition to Y or N. Absorption that leads blood where the presence of the marker reflects to measurable levels of the BFI in blood over an only recent intake. However, further extended number of hours would mean that blood characterization of this marker for different kinds of samples may be useful for food intake assessment hair, for subjects with different polymorphisms of within that specified time interval after food intake. ethanol metabolism, etc. may still be needed in BFIs with fast metabolism or excretion would order to fully validate this marker for quantitative narrow the useful time window for blood samples. longer term intake assessment . Most BFIs have Proline betaine showing fast absorption and not been studied in hair and more studies are excretion may be measured in blood in only a short needed to evaluate the usefulness of hair or nail time interval, whereas collection of urine over a clippings for BFIs currently measured mainly in time span of a few hours or more would recover blood or urine. For the medium-range or slowly ex- almost all proline betaine ingested in that time creted food-derived compounds such as lycopene, interval. Urine samples would therefore represent quercetin, or lipids, plasma levels may build up. For recent intakes before or during biospecimen instance, after consumption of tomato, the plasma collection for these BFIs. This is important because level of lycopene needs 3–4 days to return to base- repeated urine sampling over a time period may be line, which makes it a good biomarker for habitual used to represent the frequency of intake of the tomato intake in most cases where the frequency of target food in the study period or in the habitual tomato ingestion is more than once a week . diet of the study subjects . The urine sampling For quercetin with an excretion half-life of around plan (frequency and duration of collection) will 16–20 h, this would still allow plasma kinetics to be therefore determine the ability of a study to provide studied after a single meal in most cases, whereas food intake information for BFIs with shorter half- plasma levels of C22:6 fatty acids from seafood may lives. Late absorption and excretion occurs for BFIs not change appreciably after a single seafood meal that depend on release by the gut microbiota. An in habitual consumers of fatty fish but only as a example of such markers is the urolithins which are consequence of repeated exposures making blood formed by certain microbes during degradation of samples potentially useful for measuring habitual in- ellagic acid from berries and nuts [32, 33]. These takes [38, 39]. The accumulation as a consequence markers are only excreted after 24–36 h following of different dietary levels should therefore be evalu- intake of ellagitannins and may peak at 48–72 h ated for this BFI. Enzyme induction, inhibition, or [34, 35]. For BFIs with complex absorption kinetics altered excretion may affect kinetics of elimination and/or a very long elimination half-life after absorp- after repeated exposures. Foods such as coffee, gar- tion such as the carotenoids, the single-dose lic, and cabbages contain inducers of phase 1 or exposure kinetics may be of less relevance because phase 2 metabolism, including diterpenes, disul- background levels are usually high. Repeated-dose phides, indoles, and isothiocyanates. These phenom- kinetics (criterion 3b) is more important for these ena are not well studied in humans while animal BFIs studies indicate efficacy of these compounds in en- b. Time-response after multiple exposures. The zyme induction . When induction may be ex- time-response after single exposures may need add- pected, it should be evaluated whether it might itional considerations related to repeated intakes of affect the use of the BFI, in particular whether this the same food or food group. The time-response effect may dominate over other sources of variabil- after multiple exposures includes phenomena such ity. Other commonly ingested foods might also in- as accumulation in hair or blood plasma or cumula- fluence the ADME of a candidate BFI so that its tive increases in excretion. This information is of kinetics may depend on the food matrix or even cu- importance to select the best possible sample type linary culture as shortly discussed below under cri- and timing of the sample collection for the assess- terion 4. ment of habitual intake. Accumulation of the bio- 4. Robustness in studies with complex diets. It is marker in blood, hair, or nails is affected by important to evaluate the robustness of the BFI repeated exposures to some foods, and therefore, it when it is intended for use in observational studies could reflect the current habitual intakes. For with complex meals or diets. Many candidate BFIs Dragsted et al. Genes & Nutrition (2018) 13:14 Page 8 of 14 have been suggested based on a limited number of 5. Reliability based on other markers of intake for the intervention studies with highly controlled diets or food in question. Reliability is traditionally the on food chemistry knowledge. However, these data comparison of a new biomarker against the current may not be sufficient to identify all other possible best (gold) standard methodology . This dietary sources of the BFI. For instance, limonene validation of a BFI should ideally be done in a metabolites may be observed as good candidate highly controlled setting with supervised intake so markers of citrus intake in a controlled intervention that the exact amount of the food consumed is study. Since limonene is also very abundant in monitored for each volunteer in the study. In such citrus flavored foods (sweets, cakes, etc.), the use of a study, direct comparison by plots such as Bland- it as a BFI would potentially lead to wrong Altman and/or Passing-Bablok can be performed conclusions counting unhealthy foods as fruit . for exact validation and outlier detection [48, 49]. Whereas criterion 1, plausibility, is based on food Alternatively, the new BFI is validated against a chemistry literature, robustness is evaluated based previously validated “gold standard” for intake on actual proof of the uniqueness of the BFI under assessment of the food in question, but such a conditions where multiple other foods are method is only rarely available for BFIs. So the consumed at the same time. Such studies are current best practice may be the use of dietary typically cross-sectional or prospective studies assessment instruments. Validated questionnaire where intake is monitored by food diaries or dietary data, food records, or diaries may be available to recalls. For example, robustness of proline betaine judge the reliability of the marker. This is not ideal was confirmed as it appeared as a biomarker since it implies validation of a potentially more predicting citrus intake versus no intake objective and precise instrument by less precise and independently of study design; this included a subjective information. Depending on the precision cross-sectional study where citrus fruit intake was of the dietary instrument, the quality of the monitored by 24 h records in a free-living validation by this criterion will vary. Food diaries population, a fully controlled meal study with citrus, and 24-h dietary recalls covering the day of blood and a 4-week intervention with orange juice . In or urine collections for BFI measurement should be a few cases, robustness may also be judged based on preferred over food frequency questionnaires for multiple complex meals containing one of the foods reliability assessments. A useful resource is the of interest . Applicability of a BFI in populations Exposome-Explorer database in which over 8000 with different food cultures or production systems correlation values between biomarker levels and may require an examination of the BFI robustness intake of a large diversity of foods have been curated in each population. For instance, δ C has been for a large number of BFIs . In some cases, several suggested as a BFI of added sugar refined from C4 new candidate markers are found simultaneously by plants such as corn, sugar cane, and sorghum. It metabolomics . Such new BFIs representing the works well in a population whose major source of same food may be validated for reliability against each sugar is C4 plants such as subjects in Mexico, other in a separate analysis to compare their capacity Canada, and USA. However, for Europeans or to accurately predict food intake . This latter Japanese who largely rely on sugar beet, a C3 plant, strategy is not without pitfalls as exemplified above the use of δ C may underestimate the intake of with proline betaine and limonene metabolites, both added sugar [44, 45]. Another aspect of markers of citrus intake but with vastly different robustness is the influence of other foods on robustness in mixed meal studies . This strategy the metabolism and kinetics of the BFI. This for evaluating reliability should therefore be aspect is not well studied but may be indicated interpreted with care, preferably using data from from some observations. For instance, the different study designs; observational evidence of disruption of fat micelle formation in the gut reliability may for instance be confirmed in a by foods rich in plant sterols leading to reduced controlled trial or evidence from controlled studies cholesterol uptake  may also affect other may find confirmation from a cross-sectional setting lipid-soluble compounds, but so far, this has only where several different intake levels can provide been shown to affect carotenoids . So in a information about concordance between the comparison of subjects with differences in habitual candidate BFIs. Simultaneous use of information plant sterol intake, carotenoids may in theory not from dietary assessment instruments in such studies estimate intake of plant foods in a balanced way. as described above would help to assure that the However, direct evidence for quantitative importance markers also agree reasonably with subjective food is still lacking. intake data. Dragsted et al. Genes & Nutrition (2018) 13:14 Page 9 of 14 6. Stability of the BFI. This validation criterion is analytical performance of the BFI analysis method. related to best practices for sample collection and Few BFIs have been thoroughly validated in targeted storage. Compound structure, sample collection, analytical procedures by modern standards of storage and handling, and sample pre-processing analytical quality and what is sufficient may depend should be considered when evaluating the stability heavily on the intended use, e.g., qualitative or aspect for an intended use of a candidate biomarker. quantitative use. A candidate biomarker found by Many metabolites have been found to be quite metabolomics must obviously have been measured at stable over time under conditions of low- different levels in a body fluid under the conditions of temperature storage . However, both the untargeted analysis applied. This indicates temperature and environment are important potential for qualitative (or so-called semi- determinants. It is generally accepted that storage at quantitative) use and reflects the minimal temperatures of − 20 °C or higher is suboptimal and requirement for Y with the comment, “qualitative leads to oxidative degradation. However, systematic analysis only.” In studies where the BFI additionally studies of storage stability at − 80 °C over a longer reflected known graded differences in exposures, the time period are very few beyond a few years  development of the method applied into a targeted, and have not covered many food compounds, so quantitative analysis may be judged as feasible under the practice of sample storage for 5–10 years used similar experimental conditions. This would reflect for many cohorts and experimental studies is not the minimal evidence to indicate potential for well documented. Storage stability in these cases development of a quantitative analytical method for may be evaluated by comparing the distribution of the BFI, and this information may be added as a concentrations measured in a set of stored and comment but quantitative use would still be fresh samples of comparable origin or by repeated uncertain until an analytically validated method has analyses of a set of QC samples, stored in been developed. The adequacy of an intended multiplicates. Storage at even lower temperature analytical method should therefore be carefully and under a nitrogen atmosphere is probably ideal considered before application of a BFI with this kind and even enzyme activities seem to be in the of minimal evidence for analytical performance. In normal range after more than 10 years of storage most instances, a thorough analytical method under such conditions [55, 56]. Inherent compound validation for a biomarker is not made until a stability and potential for enzymatic breakdown dedicated targeted method is being developed. This during sampling is another issue that must be question should therefore be answered positively only carefully considered under this validation criterion. with an accompanying comment on its potential for For instance, highly oxidizable compounds such as use in qualitative and quantitative applications. For beer humulones may degrade during storage of the the former, a sufficient limit of detection may be beverage as well as during collection of urine sam- adequate. For the latter, a targeted method which has ples voided into an oxygen-containing collection jar. been analytically validated according to current Such compounds may only serve as BFIs when both recommendations by analytical chemistry journals or the parent compound and the products are known societies [60–62] is needed to assure uncompromised and measured . Other potential degradation use of the BFI. For full validation, it is necessary to pathways include pH instability and metabolism by use an isotope-labelled standard for the BFI as enzymes or cells present in the preparation. Special reference in every sample, but such standards are not collection conditions may be needed for stabilizing available for most compounds. However, new certain BFIs, e.g., special tubes for ascorbate and methods for derivatization with labelled agents may glucose stabilization as well as urine collection at help solve this issue, depending on the compound pH below 2 for anthocyanins [57–59]. structure [63–65]. For instance, free short-chain fatty 7. Analytical performance of the BFI measurement. acids may be measured quantitatively using both a la- Reliable chemical analysis is of central importance belled and an unlabelled agent for derivatization of for any BFI. Several analytical quality aspects exist, carboxylic acids . including precision, accuracy, and intra-batch and 8. Reproducibility across laboratories. Measurement of inter-batch variability; however, these are a BFI should give the same result when analyzed in concatenated here into a single validation criterion different laboratories. Repeatability is indicated to assess whether qualitative or quantitative analysis when the same analysis of the marker has been of the BFI is feasible. Comments to Y answers are reproduced in at least two different laboratories but therefore mandatory for this criterion in order to should eventually be evaluated by inter-laboratory qualify the statement by providing details of the comparison tests. Such tests apply the final, targeted Dragsted et al. Genes & Nutrition (2018) 13:14 Page 10 of 14 analysis of the BFI in a common set of samples The dose-response curve clearly indicated considerable distributed in a blinded fashion to the participating variability; such variability may be due to variation in the laboratories. Inter-laboratory comparisons are often presence of the parent betalain in the beetroot dishes con- used for assessment of laboratory performance , sumed or to differences between individuals in betalain and this must also be considered if the procedure is metabolism. This could be caused by large inter-individual used for validation; if one of the laboratories does not variations in its endogenous metabolism (hydrolysis and follow the analytical procedure well, the outcome conjugation) and in metabolism by the microbiota. Exten- may erroneously indicate that the BFI is not sive metabolism or degradation could therefore constitute repeatable across laboratories. It is therefore a drawback for the use of this BFI considering that its vari- preferable that several laboratories contribute. Inter- ation is high compared with the variations in intake. For laboratory comparisons may even be performed with microbial metabolites in general, their presence may de- metabolomic methodology, i.e., before a fully pend on the presence of a certain metabolic functionality validated analytical procedure has been developed of the microbiota. As a consequence, they may show [68, 69]; however, a carefully standardized major variation between individuals, making them less metabolomics procedure should then be used by all useful as BFIs, as demonstrated for the urolithins . Fi- participating laboratories to avoid misinterpretation nally, apparent variation in sample concentrations at a cer- of biomarker validity. tain food intake may be caused by the use of food diaries as reference measurement since volunteers may not cor- Variable levels of a BFI at a fixed food intake could come rectly note the ingested amount of the food in question. from differences in metabolism due to the age, sex, smok- Controlled dietary studies are therefore needed to investi- ing, medicine; from influence of other dietary factors or gate variability. Most of these sources of variability are not microbiota; from factors affecting stability of the marker; only affecting the validation process but also affect the in- or from variable contents of the biomarker precursor in terpretation of validated food intake biomarkers. Careful the food. Variability is also seen within an individual due and repeated sampling and/or use of markers with longer to several of these factors. Biomarker variability is an im- half-lives tend to reduce the influence of variable contents portant issue across most criteria but has not been consid- in the food or intake levels. Variable metabolism is more ered a criterion as such because many aspects of variation difficult to control by technical means and could render a can be controlled technically by careful sampling, analyt- BFI useful only at the group or population level. ical procedures, and statistical handling. The un- By these eight validation questions, the current status controllable factors are the individual differences in me- of biological/analytical validation, including reliability tabolism, variable contents in the food, and food matrix and robustness of a biomarker, can be assessed. For the effects. When they are large compared to the variation in purpose of reviews on BFIs including their validation ac- intakes of the food in question, the biomarker may not be cording to the current criteria, the number of questions useful and this will be observed in careful dose-response answered “Y” may be used as a score; however, since the and time-response studies (criteria 2 and 3) and in studies questions may not be equally important for all BFIs, the of robustness (criterion 4). For instance, the sulphate con- application of such a score to rank BFIs according to jugate of 4-ethyl-5-methylamino-pyrocatechol was ob- validity may be misleading. More rigid criteria for when served having an apparent dose-response relationship to answer Y or N to each of the criteria could be helpful; with beetroot intake in a parallel intervention study . however, the number of different scenarios to consider is Table 3 Criteria need to be fulfilled for different uses of BFIs Criterion Experimental study (compliance biomarker) Observational study Qualitative Quantitative Qualitative Quantitative 1 Plausibility √√ √ √ 2 Dose-response √√ 3a Time-response (single dose) √√ √ √ 3b Time-response (multiple doses) √√ √ 4 Robustness √√ 5 Reliability √√ √ √ 6 Stability √√ √ √ 7 Analytical performance √√ 8 Reproducibility √√ Dragsted et al. Genes & Nutrition (2018) 13:14 Page 11 of 14 very large and further work will be needed to delineate repeatability, comparability, and analytical perform- stricter criteria. The current validation approach is ance. These criteria include all aspects of validation therefore based on explanatory comments to supplement suggested in previous reviews on this topic. Although the evaluation of Y or N. Although the validation is some of the criteria may simply be answered Y or N, intended to provide a more authoritative guidance re- commenting on specific conditions for the judgement garding the potential of a candidate biomarker, validity of validity of a BFI may often be needed in order to of a BFI will depend on the intended application and pinpoint limitations on its use. must always be considered by the user. The explanatory Funding comments are therefore important for the end user to FoodBAll is a project funded by the BioNH call (grant number 529051002) judge a given application. under the Joint Programming Initiative, “A Healthy Diet for a Healthy Life.” When the validation criteria are applied for use of BFIs The project is funded nationally by the respective Research Councils; the work was funded in part by a grant from the Danish Innovation Foundation as qualitative markers, the scheme may be followed less (#4203-00002B) and a Semper Ardens grant from the Carlsberg Foundation stringently (Table 3). For instance, dose-response charac- to LOD; a postdoc grant from the University of Rome La Sapienza (“Borsa di teristics and analytical validation do not need to be docu- studio per la frequenza di corsi o attività di perfezionamento all’estero” erogata ai sensi della legge 398/89) to GP; the Swiss National Science mented in detail for qualitative BFIs since an all-or-none Foundation (40HD40_160618) in the frame of the national research program response is all that would be required. The presence of “Healthy nutrition and sustainable food protection” (NRP69) to GV; a grant ethyl glucuronide in a blood sample, for instance, would from the China Scholarship Council (201506350127) to QG; a grant from Science Foundation Ireland (SFI 14/JPI-HDHL/B3076) and ERC (647783) to LB; clearly indicate that an alcoholic beverage has been a grant from the Canadian Institutes of Health Research (CIHR) to DSW; a ingested within the last 24 h. This measurement would grant from the Agence Nationale de la Recherche (#ANR-14-HDHL-0002-02) suffice for assessment of compliance even if the analytical to CM; a grant from the Spanish National Grants from the Ministry of Economy and Competitiveness (MINECO) (PCIN-2014-133-MINECO Spain), an procedure is not done with internal standards. For this award of 2014SGR1566 from the Generalitat de Catalunya’s Agency AGAUR, biomarker, the use of an internal standard would provide and fundings from CIBERFES (co-funded by the FEDER Program from EU) to an accurate concentration and for a 24 h urine sample also CAL; a grant from the Italian Ministry of Agriculture, Food and Forestry Policies (MiPAAF) within the JPI-HDHL (MIUR D.M. 115/2013) to HA. the amount of beverage ingested recently. The number of criteria met as such may not be very informative, except Authors’ contributions for a rough estimate of how much further validation may This manuscript was drafted by LOD and GP and revised by LOD and QG. be needed. For example, a biomarker having five Ys but All other authors critically commented the manuscript. All authors read and approved the final manuscript. with N for questions 1, 4, and 5 may not be useful at all. However, in case the lacking evidence is for questions 1 Ethics approval and consent to participate (parent food compound still unknown), 3b, and 8, it would Not applicable. seem quite reliable even for quantitative use since only inter-laboratory comparisons may additionally be needed. Competing interests The author Hans Verhagen is employed with the European Food Safety So as already underlined repeatedly, the user must still Authority (EFSA). However, the present article is published under the sole take care to check that any of the validation criteria may responsibility of Hans Verhagen and the positions and opinions presented in apply for the intended use and appreciate that overall val- this article are those of the authors alone and are not intended to represent the views or scientific works of EFSA. idation can only be made for a defined application. The other authors declare that they have no competing interests. Conclusions This paper outlines a simple validation system for candi- Publisher’sNote Springer Nature remains neutral with regard to jurisdictional claims in date BFIs identified from a literature search, from meta- published maps and institutional affiliations. bolomic studies, or from food chemistry. The validation criteria were identified from the literature and further Author details Department of Nutrition, Exercise and Sports, University of Copenhagen, grouped by the authors. The validation system has the Copenhagen, Denmark. Department of Food Science, University of advantage of pointing out the specific areas where a BFI 3 Copenhagen, Copenhagen, Denmark. International Agency for Research on is sufficiently validated while also highlighting those as- Cancer (IARC), Nutrition and Metabolism Section, Biomarkers Group, Lyon, France. Agroscope, Federal Office of Agriculture, Berne, Switzerland. pects where additional studies would be needed in order 5 6 University of Eastern Finland, Kuopio, Finland. INRA, Human Nutrition Unit, to provide improved validation. An important strength 7 Université Clermont Auvergne, F63000 Clermont-Ferrand, France. UCD of this approach is therefore that it provides a stepwise Institute of Food and Health, UCD School of Agriculture and Food Science, University College Dublin, Dublin, Ireland. Division of Human Nutrition, strategy to improve the validity of existing BFIs as well Wageningen University and Research, Wageningen, The Netherlands. as a test strategy for new candidate BFIs emerging from 9 Department of Biological Sciences, University of Alberta, Edmonton, Canada. metabolomic studies, literature review, or from food Biomarkers and Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences and Gastronomy, University of Barcelona, Barcelona, Spain. chemistry. The validation system for BFIs proposed here CIBER de Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de includes aspects of plausibility, precision, stability, sin- 12 Salud Carlos III, Barcelona, Spain. European Food Safety Authority (EFSA), gle or repeated intake kinetics, reliability, robustness, Parma, Italy. University of Ulster, Coleraine, NIR, UK. Dragsted et al. Genes & Nutrition (2018) 13:14 Page 12 of 14 Received: 22 August 2017 Accepted: 19 April 2018 Brennan L, editors. 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Genes & Nutrition – Springer Journals
Published: May 30, 2018
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