Comparison between dietary assessment methods and biomarkers in estimating dietary (poly)phenol intake

Extended recommendations on the nomenclature for microbial catabolites of dietary (poly)phenols, with a focus on isomers

There is an increasing body of evidence indicating that phenolic compounds derived from microbiota-mediated breakdown of dietary (poly)phenolics in the colon are at least partially responsible for the beneficial effects of a plant-based diet. Investigating the role of these catabolites and defining their particular biological effects is challenging due to the complex microbial pathways and the diversity of structures that are produced. When reviewing the data this is further exacerbated by the inconsistency and lack of standardization in naming the microbial phenolics. Here we update the nomenclature of colonic catabolites of dietary (poly)phenols, extending the proposals of Kay et al. (Am. J. Clin. Nutr., 2020, 112, 1051-1068, DOI: 10.1093/ajcn/nqaa204), by providing additional structures, and addressing the difficulties that can arise when investigating regioisomers and stereoisomers, where subtle differences in structure can have a substantial impact on bioactivity. The information provided will help to better harmonize the literature, facilitate data retrieval and provide a reference for researchers in several fields, especially nutrition and biochemistry.

Development of a food frequency questionnaire for the estimation of dietary (poly)phenol intake

Background: (Poly)phenol intake has been associated with reduced risk of non-communicable diseases in epidemiological studies. However, there are currently no dietary assessment tools specifically developed to estimate (poly)phenol intake in the UK population. Objectives: This study aimed to develop a novel food frequency questionnaire (FFQ) to capture the dietary (poly)phenol intake in the UK and assess its relative validity with 7 day diet diaries (7DDs) and plasma and urine (poly)phenol metabolites. Methods: The KCL (poly)phenol FFQ (KP-FFQ) was developed based on the existing EPIC (European Prospective Investigation into Diet and Cancer)-Norfolk FFQ, which has been validated for energy and nutrient intake estimation in the UK population. Participants aged 18-29 years (n = 255) completed both the KP-FFQ and the EPIC-Norfolk FFQ. In a subgroup (n = 60), 7DD, spot urine, and fasting plasma samples were collected. An in-house (poly)phenol database was used to estimate (poly)phenol intake from FFQs and 7DDs. Plasma and urinary (poly)phenol metabolite levels were analysed using a validated ultra-high-performance liquid chromatography-triple quadrupole mass spectrometry method. The agreements between (poly)phenol intake estimated using the KP-FFQ, EPIC-Norfolk FFQ and 7DDs, as well as plasma and urinary biomarkers, were evaluated by intraclass correlation coefficients (ICC), weighted kappa, quartile cross-classification, and Spearman's correlations, and the associations were investigated using linear regression models adjusting for energy intake and multiple testing (false discovery rate (FDR) < 0.05). Results: The mean (standard deviation, SD) of total (poly)phenol intake estimated from KP-FFQs was 1366.5 (1151.7) mg d-1. Fair agreements were observed between ten (poly)phenol groups estimated from KP-FFQs and 7DDs (kappa: 0.41-0.73), including total (poly)phenol intake (kappa = 0.45), while the agreements for the rest of the 17 classes and subclasses were poor (kappa: 0.07-0.39). Strong positive associations with KP-FFQ were found in ten (poly)phenols estimated from 7DDs, including dihydroflavonols, theaflavins, thearubigins, flavones, isoflavonoids, ellagitannins, hydroxyphenylacetic acids, total stilbenes, resveratrol, and tyrosols with stdBeta ranged from 0.61 (95% confidence interval CI: 0.42 to 0.81) to 0.95 (95% CI: 0.86 to 1.03) (all FDR adjusted p < 0.05). KP-FFQs estimated (poly)phenol intake exhibited positive associations with 76 urinary metabolites (stdBeta: 0.28 (95% CI: 0.07-0.49) to 0.81 (0.62-1.00)) and 19 plasma metabolites (stdBeta: 0.40 (0.17-0.62)-0.83 (0.64-1.02)) (all FDR p < 0.05). The agreement between KP-FFQs and the EPIC-Norfolk FFQs was moderate (ICC 0.51-0.69) for all (poly)phenol subclasses after adjusting for energy intake. Compared with the EPIC-Norfolk FFQs estimated (poly)phenol intake, stronger and more agreements and associations were found in KP-FFQs estimated (poly)phenol with 7DDs and biomarkers. Conclusion: (Poly)phenol intake estimated from KP-FFQ exhibited fair agreements and moderate to strong associations with 7DDs and biomarkers, indicating the novel questionnaire may be a promising tool to assess dietary (poly)phenol intake.

Association between Higher Intake of Flavonols and Lignans and Better Mood: Evidence from Dietary and Biomarker Evaluation in Healthy Individuals

SCOPE

The aim of this study is to investigate associations between (poly)phenol consumption, circulating (poly)phenol metabolites, and mood states in healthy individuals.

METHODS AND RESULTS

The study included 333 healthy individuals. Mood state was assessed with the Positive and Negative Affect Schedule questionnaire. Dietary (poly)phenol intake was estimated  matching food consumption data collected using a Food Frequency Questionnaire(FFQ) with a comprehensive in-house (poly)phenol database. A total of 102 (poly)phenol metabolites were quantified in fasting plasma and 24 h urine samples by Liquid Chromatography-Mass Spectrometry using a validated method. A higher intake of lignans, flavanones, and flavonols estimated from FFQs was associated with positive mood after adjusting for age and sex (β: 0.118 to 0.134). A total of 11 urinary (poly)phenol metabolites, including lignan and flavonol metabolites were associated with less negative mood (β: -0.387 to -0.205). No association was found between mood and plasma (poly)phenols.

CONCLUSION

  A higher consumption of lignans flavanones and flavonols is associated with a better mood, while certain urinary metabolites are associated with less negative mood. The lack of associations between fasting plasma (poly)phenols and mood may be due to their transient nature incirculation compared with 24 h urinary metabolites, which reflect longer-term exposure.

Development of a (Poly)phenol Metabolic Signature for Assessing (Poly)phenol-Rich Dietary Patterns

The objective assessment of habitual (poly)phenol-rich diets in nutritional epidemiology studies remains challenging. This study developed and evaluated the metabolic signature of a (poly)phenol-rich dietary score (PPS) using a targeted metabolomics method comprising 105 representative (poly)phenol metabolites, analyzed in 24 h of urine samples collected from healthy volunteers. The metabolites that were significantly associated with PPS after adjusting for energy intake were selected to establish a metabolic signature using a combination of linear regression followed by ridge regression to estimate penalized weights for each metabolite. A metabolic signature comprising 51 metabolites was significantly associated with adherence to PPS in 24 h urine samples, as well as with (poly)phenol intake estimated from food frequency questionnaires and diaries. Internal and external data sets were used for validation, and plasma, spot urine, and 24 h urine samples were compared. The metabolic signature proposed here has the potential to accurately reflect adherence to (poly)phenol-rich diets, and may be used as an objective tool for the assessment of (poly)phenol intake.

Exploring and disentangling the production of potentially bioactive phenolic catabolites from dietary (poly)phenols, phenylalanine, tyrosine and catecholamines

Following ingestion of fruits, vegetables and derived products, (poly)phenols that are not absorbed in the upper gastrointestinal tract pass to the colon, where they undergo microbiota-mediated ring fission resulting in the production of a diversity of low molecular weight phenolic catabolites, which appear in the circulatory system and are excreted in urine along with their phase II metabolites. There is increasing interest in these catabolites because of their potential bioactivity and their use as biomarkers of (poly)phenol intake. Investigating the fate of dietary (poly)phenolics in the colon has become confounded as a result of the recent realisation that many of the phenolics appearing in biofluids can also be derived from the aromatic amino acids, l-phenylalanine and l-tyrosine, and to a lesser extent catecholamines, in reactions that can be catalysed by both colonic microbiota and endogenous mammalian enzymes. The available evidence, albeit currently rather limited, indicates that substantial amounts of phenolic catabolites originate from phenylalanine and tyrosine, while somewhat smaller quantities are produced from dietary (poly)phenols. This review outlines information on this topic and assesses procedures that can be used to help distinguish between phenolics originating from dietary (poly)phenols, the two aromatic amino acids and catecholamines.

Dietary (poly)phenols and cardiometabolic health: from antioxidants to modulators of the gut microbiota

(Poly)phenols are plant secondary metabolites widely abundant in plant foods and beverages comprising a very large number of compounds with diverse structure and biological activities. Accumulating evidence indicates that these compounds exert beneficial effects against cardiometabolic diseases, and this review will provide a summary of current knowledge in this area. Epidemiological and clinical data collectively suggest that intake of flavonoids reduces the risk of cardiovascular disease (CVD), with the evidence being particularly strong for the flavan-3-ol subclass. However, to provide adequate dietary recommendations, a better understanding of their estimated content in foods and intake among the general public is needed. Regarding mechanisms of action, we now know that it is unlikely that (poly)phenols act as direct antioxidants in vivo, as it was hypothesised for decades with the popularity of in vitro antioxidant capacity assays. One of the reasons is that upon ingestion, (poly)phenols are extensively metabolised into a wide array of circulating metabolites with different bioactivities than their precursors. Well-conducted in vitro and in vivo studies and human nutrigenomic analysis have revealed new molecular targets that may be underlying the health benefits of (poly)phenols, such as the nitric oxide pathway. Recently, a bi-directional relationship was established between (poly)phenols and the gut microbiota, suggesting that individual gut microbial metabolising capacity may be a key factor explaining the variability in the cardiometabolic response to (poly)phenols. Future research is needed to elucidate which are the key factors affecting such capacity, and whether it can be modulated, along with the mechanisms of action.

A critical examination of human data for the biological activity of quercetin and its phase-2 conjugates

This critical review examines evidence for beneficial effects of quercetin phase-2 conjugates from clinical intervention studies, volunteer feeding trials, and in vitro work. Plasma concentrations of quercetin-3-O-glucuronide (Q3G) and 3'-methylquercetin-3-O-glucuronide (3'MQ3G) after supplementation may produce beneficial effects in macrophages and endothelial cells, respectively, especially if endogenous deglucuronidation occurs, and lower blood uric acid concentration via quercetin-3'-O-sulfate (Q3'S). Unsupplemented diets produce much lower concentrations (<50 nmol/l) rarely investigated in vitro. At 10 nmol/l, Q3'S and Q3G stimulate or suppress, respectively, angiogenesis in endothelial cells. Statistically significant effects have been reported at 100 nmol/l in breast cancer cells (Q3G), primary neuron cultures (Q3G), lymphocytes (Q3G and3'MQ3G) and HUVECs (QG/QS mixture), but it is unclear whether these translate to a health benefit in vivo. More sensitive and more precise methods to measure clinically significant endpoints are required before a conclusion can be drawn regarding effects at normal dietary concentrations. Future requirements include better understanding of inter-individual and temporal variation in plasma quercetin phase-2 conjugates, their mechanisms of action including deglucuronidation and desulfation both in vitro and in vivo, tissue accumulation and washout, as well as potential for synergy or antagonism with other quercetin metabolites and metabolites of other dietary phytochemicals.

Automated High-Throughput Quantification of Phenyl-γ-valerolactones and Creatinine in Urine by Laser Diode Thermal Desorption

Quantification of nutritional biomarkers is crucial to accurately assess the dietary intake of different classes of (poly)phenols in large epidemiological studies. High-throughput analysis is mandatory to apply this methodology in large cohorts. However, the current validated methods to quantify (poly)phenols metabolites in biological fluids use ultra performance liquid chromatography (UPLC), leading to analysis time of several minutes per sample. To significantly reduce the run time, we developed and validated a method to quantify in urine the flavan-3-ols biomarkers, phenyl-γ-valerolactones (PVLs), using laser diode thermal desorption (LDTD). This mass spectrometry source allows direct introduction of sample extracts, resulting in analysis time of less than 10 s per sample. Also, to encompass the problem associated with the cost and availability of sulfated and glucuronide analytical standards, urine samples were subjected to enzymatic hydrolysis. Creatinine was also quantified to normalize the results obtained from the urinary spot. Results obtained with LDTD-MS/MS were cross-validated by UPLC-MS/MS using 155 urine samples. Coefficient of correlation was above 0.975 for PVLs and creatinine. For all analytes, the accuracy was between 90% and 113% by LDTD-MS/MS. Altogether, sample preparation was fully automated to demonstrate the application potential of this method to large cohorts.

Development of a novel (poly)phenol-rich diet score and its association with urinary (poly)phenol metabolites

Background: Estimating (poly)phenol intake is challenging due to inadequate dietary assessment tools and limited food content data. Currently, a priori diet scores to characterise (poly)phenol-rich diets are lacking. This study aimed to develop a novel (poly)phenol-rich diet score (PPS) and explore its relationship with circulating (poly)phenol metabolites. Methods: A total of 543 healthy free-living participants aged 18-80 years completed a food frequency questionnaire (FFQ) (EPIC-Norfolk) and provided 24 h urine samples. The PPS was developed based on the relative intake (quintiles) of 20 selected (poly)phenol-rich food items abundant in the UK diet, including tea, coffee, red wine, whole grains, chocolate and cocoa products, berries, apples and juice, pears, grapes, plums, citrus fruits and juice, potatoes and carrots, onions, peppers, garlic, green vegetables, pulses, soy and soy products, nuts, and olive oil. Foods included in the PPS were chosen based on their (poly)phenol content, main sources of (poly)phenols, and consumption frequencies in the UK population. Associations between the PPS and urinary phenolic metabolites were investigated using linear models adjusting energy intake and multiple testing (FDR adjusted p < 0.05). Result: The total PPS ranged from 25 to 88, with a mean score of 54. A total of 51 individual urinary metabolites were significantly associated with the PPS, including 39 phenolic acids, 5 flavonoids, 3 lignans, 2 resveratrol and 2 other (poly)phenol metabolites. The total (poly)phenol intake derived from FFQs also showed a positive association with PPS (stdBeta 0.32, 95% CI (0.24, 0.40), p < 0.01). Significant positive associations were observed in 24 of 27 classes and subclasses of estimated (poly)phenol intake and PPS, with stdBeta values ranging from 0.12 (0.04, 0.20) for theaflavins/thearubigins to 0.43 (0.34, 0.51) for flavonols (p < 0.01). Conclusion: High adherence to the PPS diet is associated with (poly)phenol intake and urinary biomarkers, indicating the utility of the PPS to characterise diets rich in (poly)phenols at a population level.

Excretion by subjects on a low (poly)phenol diet of phenolic gut microbiota catabolites sequestered in tissues or associated with catecholamines and surplus amino acids

Phenolic catabolites excreted by fasting subjects with a functioning colon and ileostomists on a low (poly)phenol diet have been investigated. Urine was collected over a 12 h fasting period after adherence to a low (poly)phenol diet for 36 h. UHPLC-HR-MS quantified 77 phenolics. Some were present in the urine of both groups in similar trace amounts and others were excreted in higher amounts by participants with a colon indicating the involvement of the microbiota. Most were present in sub- or low-µmol amounts, but hippuric acid dominated accounting on average for 60% of the total for both volunteer categories indicating significant production from sources other than non-nutrient dietary (poly)phenols. The potential origins of the phenolics associated with the low (poly)phenol diet, include endogenous catecholamines, surplus tyrosine and phenylalanine, and washout of catabolites derived from pre-study intakes of non-nutrient dietary (poly)phenols.

Interplay between the (Poly)phenol Metabolome, Gut Microbiome, and Cardiovascular Health in Women: A Cross-Sectional Study from the TwinsUK Cohort

BACKGROUND

Dietary (poly)phenol consumption is inversely associated with cardiovascular disease (CVD) risk in epidemiological studies, but little is known about the role of the gut microbiome in this relationship.

METHODS

In 200 healthy females, aged 62.0 ± 10.0 years, from the TwinsUK cohort, 114 individual (poly)phenol metabolites were measured from spot urine using ultra-high-performance liquid chromatography-mass spectrometry. The associations between metabolites, the gut microbiome (alpha diversity and genera), and cardiovascular scores were investigated using linear mixed models adjusting age, BMI, fibre, energy intake, family relatedness, and multiple testing (FDR < 0.1).

RESULTS

Significant associations were found between phenolic acid metabolites, CVD risk, and the gut microbiome. A total of 35 phenolic acid metabolites were associated with the Firmicutes phylum, while 5 metabolites were associated with alpha diversity (FDR-adjusted p < 0.05). Negative associations were observed between the atherosclerotic CVD (ASCVD) risk score and five phenolic acid metabolites, two tyrosol metabolites, and daidzein with stdBeta (95% (CI)) ranging from -0.05 (-0.09, -0.01) for 3-(2,4-dihydroxyphenyl)propanoic acid to -0.04 (-0.08, -0.003) for 2-hydroxycinnamic acid (FDR-adjusted p < 0.1). The genus 5-7N15 in the Bacteroidetes phylum was positively associated with the same metabolites, including 3-(3,5-dihydroxyphenyl)propanoic acid, 3-(2,4-dihydroxyphenyl)propanoic acid, 3-(3,4-dihydroxyphenyl)propanoic acid), 3-hydroxyphenylethanol-4-sulfate, and 4-hydroxyphenylethanol-3-sulfate)(stdBeta (95% CI): 0.23 (0.09, 0.36) to 0.28 (0.15, 0.42), FDR-adjusted p < 0.05), and negatively associated with the ASCVD score (stdBeta (95% CI): -0.05 (-0.09, -0.01), FDR-adjusted p = 0.02). Mediation analysis showed that genus 5-7N15 mediated 23.8% of the total effect of 3-(3,4-dihydroxyphenyl)propanoic acid on the ASCVD score.

CONCLUSIONS

Coffee, tea, red wine, and several vegetables and fruits, especially berries, are the most abundant food sources of phenolic acids that have the strongest associations with CVD risk. We found that the gut microbiome, particularly the genus 5-7N15, partially mediates the negative association between urinary (poly)phenols and cardiovascular risk, supporting a key role of the gut microbiome in the health benefits of dietary (poly)phenols.