Abstract
Introduction
Blueberries are a well-known source of flavonoids and (poly)phenols. The major group of (poly)phenols present in blueberries are anthocyanins, followed by proanthocyanidins, flavonols and chlorogenic acids [1–7]. In recent years, blueberries have received much attention due to their positive role in human health and disease prevention [8]. For example, blueberry consumption has been shown to improve endothelial function in young healthy men and in people with metabolic syndrome [9, 10], and decrease blood pressure and arterial stiffness in pre- and hypertensive postmenopausal women and people with the metabolic syndrome [11, 12]. Increasing evidence also suggests that the high polyphenol content of berries may be responsible for their beneficial effects [8, 13–18].
Recent work suggests that the bioavailability of berry (poly)phenols is higher and more complex than previously thought [9, 19–21]. Highly unstable anthocyanins are degraded into smaller compounds as early as 1 hour post-consumption, before or after being absorbed in the small intestine, leading to a vast array of phenolic metabolites that can be glucuronidated, sulfated and/or methylated and circulate in much higher concentrations than the structurally related anthocyanin metabolites [19, 23]. Many of the (poly)phenols present in berries are not absorbed in the small intestine and they reach the colon intact, where they are degraded by the gut microbiota into smaller phenolic metabolites that are absorbed, metabolized and appear in circulation at later timepoints[9, 23].
Although there is scientific evidence showing that different (poly)phenol levels can affect the magnitude of health outcomes [12, 24–29], most of these studies included only two levels of (poly)phenol amounts, limiting the evaluation of dose-response relationships. Furthermore, most studies highlight the health benefits without investigating (poly)phenol bioavailability in a dose-response manner, so it is crucial to understand how (poly)phenol dosage can affect the metabolism and disposition of these compounds in humans. Limited work exists on the impact of different levels of intake on the kinetics of (poly)phenol metabolites. Some work has been conducted with tea flavanols, showing that there seems not to be a linear response between catechin metabolites and the ingested amount of tea [30, 31]. A dose-response was found for the area under the curve (AUC) of catechin metabolites after green tea intake but only when comparing the low with medium intake levels, suggesting that saturation might occur between medium and high levels of intake [31]. Other works have reported even a decrease of (poly)phenol metabolites, such as pelargonidin-
We have recently reported on the effects of ingesting different amounts of wild blueberry (poly)phenols on vascular function in healthy volunteers [9]. In this work, we provide additional information on the absorption and metabolism of wild blueberry (poly)phenols in plasma after intake of different amounts of wild blueberry.
Methods
Study design
A detailed description of the study design and the characteristics of the study population have been published elsewhere [9]. Briefly, a randomized, double-blind, crossover, controlled intervention trial was performed in 9 healthy young men between 18 to 40 years old. Volunteers were asked to consume a blueberry drink consisting of a freeze-dried wild blueberry powder dissolved in water on three different days separated by one week (washout period). Before the intervention day, volunteers were asked to follow a 24 h low polyphenol diet. On arrival at the Nutrition Unit, subjects rested for 30 minutes in a quiet, temperature controlled room before they were cannulated and blood samples were collected in the fasted state and at 1, 2, 4, and 6 h after consumption of each intervention. Blood samples were drawn into EDTA-containing vials, and immediately centrifuged at 1700
Blueberry-containing test materials
Freeze-dried wild blueberry powder was kindly supplied by the Wild Blueberry Association of North America (WBANA, Maine, US). Freeze-dried wild blueberry powder was stored at –20°C until consumption. Volunteers consumed either a blueberry drink containing 34, 56 or 80 g freeze-dried blueberry powder dissolved in 500 ml water, equivalent to 240, 400 or 560 g of fresh blueberry, and containing 766 mg (low), 1278 mg (medium) and 1791 (high) mg of total (poly)phenols. Drinks contained 310, 517 and 724 mg of total anthocyanins; 137, 228 and 320 mg of total procyanidins, and 273, 455 and 637 mg of chlorogenic acid, respectively. Small amounts of quercetin, caffeic,
Materials
All individual flavonoid and phenolic acid standards were obtained from Sigma-Aldrich Co. Ltd (Poole, UK) or Extrasynthese (Genay, France). The chemical structures of these compounds have been previously presented [23]. Water, methanol, acetic acid and acetonitrile (HPLC grade) were purchased from Fisher Scientific (Loughborough, UK). HPLC columns were from Hichrom (Reading, UK). β-glucuronidase and sulfatase (
Plasma analysis of (poly)phenol metabolites
Plasma flavonoid and phenolic acid analysis was performed using enzymatic treatment with β-glucuronidase and sulfatase, followed by solid phase extraction and LC-Q-TOF-MS analysis as previously described [9].
Statistical analysis
The maximum concentration in plasma (Cmax) and the time needed to reach Cmax (Tmax), as well as the area under the plasma curve over time (AUC) were calculated using Microsoft Excel. The statistical significance of these parameters was determined for each metabolite using paired
Two-way ANOVA was used to compare the concentration of each metabolite in plasma for each timepoint in plasma to the baseline within each treatment and
Linear regression analysis was performed between (poly)phenol amounts supplied in each intervention and respective average AUC, yielding regression equations and corresponding
Results
Plasma kinetics of blueberry (poly)phenols
A total of 32 compounds were detected in the plasma of volunteers who consumed different amounts of blueberry (poly)phenols, as previously reported [9]. However, 9 of them were below the LOQ so their kinetics will not be presented here. The maximum concentration detected in plasma (Cmax) ranged between 11 and 4874 nM, 19 and 5169 nM and 24 and 5456 nM for the lower, medium and higher intakes, respectively (Table 1). The highest Cmax was achieved for hippuric acid in all the interventions and the lowest Cmax was detected for
The time that each plasma metabolite reached their Cmax (Tmax) varied between 1.5 h for the lower intake and 2 h for the medium and higher intake regimens and 6 h for all the interventions (Table 1), but they were not statistically significant.
The area under the curve of plasma concentration over time (AUC) was calculated for each metabolite between 0 and 6 h and ranged between 50 and 13250 nM*h, 74 and 14581 nM*h and 103 and 15533 nM*h for the lower, medium and higher intake of blueberry (poly)phenols (Table 1). Dihydroferulic, ferulic and isoferulic acids displayed a significant increase in AUC when comparing lower and higher intake of wild blueberry (poly)phenols. The sum of plasma AUC of the 23 metabolites was calculated for each volunteer and statistical significance was achieved when comparing the lower (32.6 ± 5.3 μM*h) and higher blueberry intakes (39.8 ± 5.7 μM*h) (Fig. 1).
The plasma curves of ten selected compounds are represented in Fig. 2. 2,5-Dihydroxybenzoic acid, vanillic acid, homovanillic acid, 3–(3-hydroxyphenyl)-propionic acid, 3–(4-hydroxy-3-methoxyphenyl)propionic acid (dihydroferulic acid), ferulic acid, isoferulic acid, caffeic acid, hippuric acid and
Regression analysis
Regression curves were plotted between the (poly)phenol amount for each blueberry intervention and average AUC: 11 compounds presented a strong dose-dependent correlation after linear regression analysis with R2 > 0.85 (2,4-dihydroxybenzoic acid, 3,4-dihydroxybenzoic acid, syringic acid, vanillic acid, 3-hydroxyphenylacetic acid, 3–(4-hydroxy-3-methoxyphenyl)propionic acid, ferulic acid, isoferulic acid, hippuric acid,
Inter-individual variability
The inter-individual variability of (poly)phenol metabolites detected in plasma was expressed as coefficient of variation (CV%). The CV for Cmax, Tmax and AUC were calculated for all the compounds and the sum of total (poly)phenols (Table 2). CV for Cmax varied between 8% for benzoic acid for the higher intake level and 253 % for syringic acid for the medium (poly)phenol intake. Tmax had CV as low as 0% for dihydroferulic, hippuric and
Discussion
In this work, hippuric and
When comparing the three different amounts of wild blueberry consumed and the sum of AUC of all metabolites detected in plasma, only the lower and the higher (poly)phenol intake were significantly different, suggesting a non-linear dose response relationship between polyphenol intake and plasma levels of total (poly)phenol metabolites. It is important to point out though that in this study the amount of (poly)phenols given to volunteers was not linearly allocated, which may affect the results. The maximum dose chosen was 1791 mg of total (poly)phenols which corresponded to 560 g of fresh blueberries. A linear increase from the lowest dosage would result in a high level of intake of 3064 mg of (poly)phenols which corresponds to almost 1 Kg of blueberries which is not feasible or dietary relevant to feed in a human intervention trial.
When looking at dose-responses of individual compounds, which can be more informative than the overall pattern of (poly)phenol metabolites in plasma [31], we found that nearly half (
When looking at statistically significant differences between doses, ferulic, isoferulic and dihydroferulic acids were the only compounds that showed a significant increase in AUC when comparing medium and higher (poly)phenol intake with the low (poly)phenol group intake, but no differences were found between medium and higher dosage interventions. Although increases in Cmax of homovanillic, phenylacetic and 4-hydroxyphenylacetic acids were observed when comparing the medium and the low intake interventions, these increases were not statistically significant and the plasma levels plateaued, remaining constant for the higher (poly)phenol intake. This plateau effect was also observed after the consumption of strawberry beverages for pelargonidin-based anthocyanins for even lower (poly)phenol amounts (97, 194 and 388 mg) than reported here [32], which is likely due to decreased absorption and/or increase in the elimination efficiency.
The remaining compounds showed either non-significant increases with dosage or maintained their Cmax and AUC constant across the different interventions. These results suggest that the metabolic pathways that lead to the formation of (poly)phenol metabolites, other than ferulic, isoferulic and dihydroferulic acids, might already been saturated for the lower dosage and therefore a true dose-response effect could not observed. Since the inter-individual variability was high, the linear regression analysis was conducted in this study including the average AUC for each blueberry intervention and not the AUC for each volunteer individually, revealing metabolites with a high R2 which could not reach statistical significance when the
No statistical differences between Tmax for the different (poly)phenol dosages were found, showing that independently of the amount consumed, all the metabolites displayed a similar time appearance in the plasma. These results are consistent with previous finding after consumption of different green tea amounts [31]. Metabolites which showed up early in plasma after blueberry consumption (Tmax <2h) such as 2-hydroxybenzoic acid, protocatechuic acid, syringic acid, vanillic acid, phenylacetic acid, 4-hydroxyphenylacetic acid, ferulic acid, isoferulic acid, caffeic acid and sinapic acid likely undergo early absorption at the small intestine level. However, metabolites as 3–(3-hydroxyphenyl)-propionic acid, homovanillic acid, dihydroferulic acid, hippuric and
It is well known that the inter-individual variation in the absorption and metabolism of (poly)phenols is considerably high and it depends not only on age [35], gender [36], gut microbiota [37], but also on genetic polymorphisms of each individual [38], among other factors. However, the determination of this inter-individual variability is often underreported and most works present the data as average or mean and use the standard error of the mean as a dispersion parameter. Data concerning inter-individual variability after (poly)phenol intake has somewhat been buried in the published scientific literature in the form of plasma concentration ranges [31, 33] or box-and-plot whisker graphs [39, 40], which give a more accurate picture of the actual variation in a dataset but very few papers have described the CV for each kinetic parameter after (poly)phenol intake. We recently reported that the CV of the AUC of the sum of epicatechin metabolites was 38%, which was comparable to the CV of acetaminophen, consumed by the same individuals [35]. In the present work, we obtained for the sum of the AUC of total (poly)phenol metabolites a CV of 49, 56 and 41% for the low, medium and high intake levels, respectively, which is slightly higher but of similar magnitude to our previous work with cocoa [35]. It is important to highlight that the variability of each individual metabolite was much higher, with CV as low as 21–40% and as high as 183–270% depending on each compound and timepoint after blueberry consumption. This is due to the fact that in certain volunteers some metabolites were not detected while in others, high concentrations were found in the plasma. For instance, phenylacetic acid was only detected in three volunteers in all the treatments. Syringic acid also displayed a high CV because while two volunteers had undetectable concentrations, two different individuals had Cmax in the micromolar range.
Although the present data reports important and novel information regarding the plasma kinetics of blueberry (poly)phenols at different intake amounts, future studies are needed in order to investigate dose-response relationships with lower concentration of blueberry (poly)phenols at equidistant amounts. A limitation of this work is that enzymatic treatment was used for the analysis of plasma metabolites, so information on glucuronidation and sulfation of polyphenols is lacking and might confound data interpretation.
In conclusion, our data suggests that some blueberry (poly)phenols quantified in this work are absorbed in an intake-dependent manner at the amounts tested while others did not display such a linear dose-response behavior, tending to plateau at the lower or medium dosages, illustrating a complex kinetics mechanism that depends on each metabolic pathway.
Conflict of Interest
We declare that we received by way of a gift the experimental diets from Wild Blueberry Association of North America. There are no other conflicts of interest the authors wish to declare.
