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 based on an objective and systematic approach and (2) to pinpoint 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.
Background and ImportanceAmikacin is commonly used as an empirical treatment for gram-negative infections in intensive care unit (ICU) patients. The pharmacokinetic/pharmacodynamic (PK/PD) index ...commonly used is the ratio maximal concentration: minimum inhibitory concentration (Cmax/MIC) and, to a lesser extent, the ratio area under the curve from 0 to 24h:MIC (AUC0– 24/MIC).Aim and ObjectivesTo evaluate the PK/PD indices Cmax/MIC and AUC0–24/CMI for amikacin in critically ill patients.Material and MethodsPatients admitted to a medical ICU with preserved renal function (CKD-EPI>60 ml/min) treated with empirical amikacin once-daily were included. Therapeutic Drug Monitoring (TDM) was carried out after the first dose (sample timing: Cmax and Cpost-8h, at 30 minutes and 8 hours respectively, after a 30-minute infusion). Targets for PK/PD Cmax/MIC and AUC0–24/MIC were 8–10 and 80, respectively. An empirical MIC of 4 mg/L was established for the calculation. Parametric AUC calculation was performed by empirical Bayesian estimation of pharmacokinetic parameter. Bayesian estimates were performed using PKS® software with a single compartment pharmacokinetic model. Patients were classified according to those who reached the target or not for both indices (Cmax/MIC and AUC0–24/MIC).ResultsResults expressed as median and percentile 25–75.N=48 Age 63 years Weight 83 kg Creatinine 0.6 mg/dL Starting dose After TDM p>0.05 Total dose (mg) 1225 (1000–1500) 1250 (1200–1500) Dose adjusted for total weight (mg/kg) 14.7 (11.8–18.3) 14.7 (12.5–17.1) Dose adjusted for ideal weight (mg/kg) 19 (15.3–22.8) 19 (17.6–22.2) Cmax (mg/L) 48.3 (45.9–50.9) Cmin (mg/L) 0.19 (0.03–0.61) AUC (mg·h/L) 235 (191–271) Cmax/MIC 12.1 (11.5–12.7) AUC0–24/MIC 58.7 (47.7–67.9) Due to TDM, 100% of patients reached the therapeutic objective according to the Cmax/MIC index, although the percentage was reduced to 17% when the PK/PD index of efficacy was AUC0–24/MIC ratio (concordance index kappa=0.275; p≤0.05). To achieve the AUC0–24/MIC target, the required dose was estimated to be 1760 mg (1300–2270) (p=<0.05).Conclusion and RelevanceNo correlation between the PK/PD Cmax/CMI and AUC0–24/MIC indices was observed. To achieve the AUC0–24/MIC target, a significant dose increase is necessary compared to the doses required for Cmax/MIC.References and/or AcknowledgementsConflict of InterestNo conflict of interest.
The exposome, defined as the cumulative measure of external exposures and associated biological responses throughout the lifespan, has emerged in recent years as a cornerstone in biomedical sciences. ...Metabolomics stands out here as one of the most powerful tools for investigating the interplay between the genetic background, exogenous, and endogenous factors within human health. However, to address the complexity of the exposome, novel methods are needed to characterize the human metabolome. In this work, we have optimized and validated a multianalyte metabolomics platform for large-scale quantitative exposome research in plasma and urine samples, based on the use of simple extraction methods and high-throughput metabolomic fingerprinting. The methodology enables, for the first time, the simultaneous characterization of the endogenous metabolome, food-related metabolites, pharmaceuticals, household chemicals, environmental pollutants, and microbiota derivatives, comprising more than 1000 metabolites in total. This comprehensive and quantitative investigation of the exposome is achieved in short run times, through simple extraction methods requiring small-sample volumes, and using integrated quality control procedures for ensuring data quality. This metabolomics approach was satisfactorily validated in terms of linearity, recovery, matrix effects, specificity, limits of quantification, intraday and interday precision, and carryover. Furthermore, the clinical potential of the methodology was demonstrated in a dietary intervention trial as a case study. In summary, this study describes the optimization, validation, and application of a multimetabolite platform for comprehensive and quantitative metabolomics-based exposome research with great utility in large-scale epidemiological studies.
Gut microbiota-related metabolites are potential clinical biomarkers for cardiovascular disease (CVD). Circulating succinate, a metabolite produced by both microbiota and the host, is increased in ...hypertension, ischemic heart disease, and type 2 diabetes. We aimed to analyze systemic levels of succinate in obesity, a major risk factor for CVD, and its relationship with gut microbiome. We explored the association of circulating succinate with specific metagenomic signatures in cross-sectional and prospective cohorts of Caucasian Spanish subjects. Obesity was associated with elevated levels of circulating succinate concomitant with impaired glucose metabolism. This increase was associated with specific changes in gut microbiota related to succinate metabolism: a higher relative abundance of succinate-producing Prevotellaceae (P) and Veillonellaceae (V), and a lower relative abundance of succinate-consuming Odoribacteraceae (O) and Clostridaceae (C) in obese individuals, with the (P + V/O + C) ratio being a main determinant of plasma succinate. Weight loss intervention decreased (P + V/O + C) ratio coincident with the reduction in circulating succinate. In the spontaneous evolution after good dietary advice, alterations in circulating succinate levels were linked to specific metagenomic signatures associated with carbohydrate metabolism and energy production with independence of body weight change. Our data support the importance of microbe-microbe interactions for the metabolite signature of gut microbiome and uncover succinate as a potential microbiota-derived metabolite related to CVD risk.
The biological properties of dietary polyphenols are greatly dependent on their bioavailability that, in turn, is largely influenced by their degree of polymerization. The gut microbiota play a key ...role in modulating the production, bioavailability and, thus, the biological activities of phenolic metabolites, particularly after the intake of food containing high-molecular-weight polyphenols. In addition, evidence is emerging on the activity of dietary polyphenols on the modulation of the colonic microbial population composition or activity. However, although the great range of health-promoting activities of dietary polyphenols has been widely investigated, their effect on the modulation of the gut ecology and the two-way relationship “polyphenols ↔ microbiota” are still poorly understood. Only a few studies have examined the impact of dietary polyphenols on the human gut microbiota, and most were focused on single polyphenol molecules and selected bacterial populations. This review focuses on the reciprocal interactions between the gut microbiota and polyphenols, the mechanisms of action and the consequences of these interactions on human health.
During the 5th International Conference on Polyphenols and Health that was held in Sitges (Spain) in October 2011, the latest advances in this area of active research were presented. Sessions on ...polyphenol effects on cardiovascular disease, polyphenols as ingredients of functional foods, the role of polyphenols in preventing obesity and diabetes, the interaction of polyphenols with gut microbiota, bioavailability and metabolism of polyphenols in humans, the mechanisms of action of these metabolites in different models, new methodologies for the study of the role of polyphenols in health, polyphenols and cancer, recent developments in phenolic compounds and neuroscience, and polyphenols in epidemiology and public health were organized. This highlight issue presents a selection of papers from invited speakers, oral presentations, and poster prize winners. The perspectives for this exciting area of very active research were also discussed at the meeting and are summarized in this introductory paper.
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