Two-thirds of American adults can be classified as either overweight or obese [1
]. Obesity leads to an increased risk for cardiovascular disease, diabetes, cancer, and other morbidities; it also burdens our health care system at a level of $
147 billion annually [2
]. Lifestyle modification remains an attractive strategy for combating obesity, as dietary approaches offer solutions to weight loss and improved health without negative side effects. To date, medical and pharmacological approaches to obesity treatment have failed to produce an alternative to improved/informed diet choices and increased physical activity [3
]. Within the realm of diet choices, the protective effects of fruit and vegetable consumption against all-cause mortality and cardiovascular disease are notable [4
], and these effects may be related to their polyphenol content. As reported in the Predimed study, there is a protective effect of higher intakes of polyphenol-rich foods against all-cause mortality [6
]. Anthocyanins are one of the main classes of flavonoids (a type of polyphenol) garnering substantial attention in regard to prevention of obesity and related morbidities. Anthocyanins are responsible for the red, blue, and purple hues of fruits and vegetables. Of the fruits and vegetables found in a typical American diet, berries provide one of the greatest sources for anthocyanin consumption [7
A common dietary anthocyanin, cyanidin-3-O
-β-glucoside (C3G), was demonstrated to potentially influence obesity risk when delivered in the form of purple corn color. Tsuda et al. [8
] fed mice a high fat (60% energy from fat) diet for twelve weeks supplemented with or without purple corn color that provided 2–4 mg of C3G per day. Mice fed C3G had reduced body weight, adipocyte size, and reduced expression of lipogenic enzymes in hepatic and adipose tissues [8
]. These findings were followed by a number of berry anthocyanin research studies in rodent models of obesity with mixed, but mostly positive effects [9
]. Several of these studies have also reported improvements in insulin sensitivity [10
To facilitate translation of preclinical findings to humans, we used indirect calorimetry to test the hypothesis that berries would influence substrate trafficking in humans and to give clues to the potential of anthocyanin-rich foods to reduce obesity. Blackberries were chosen as the anthocyanin source due to their high content of cyanidin 3-glucoside, an especially common anthocyanin in the food supply. In addition, potential glucoregulatory effects were also investigated. The objective of this study was to evaluate the effects of berry intake on energy substrate use and glucoregulation in volunteers consuming a high-fat diet.
2. Materials and Methods
Subjects were recruited from the Washington D.C. metropolitan area via email advertisements. Eligibility was determined by review of a health history questionnaire in addition to blood and urine clinical chemistries. Only males were recruited so as to avoid added variability in calorimetry measures due to women’s menstrual cycles [17
]. Overweight/obese men (BMI > 25 kg/m2
) were recruited as a population with potential to benefit from anti-obesity effects of blackberries. Volunteers were excluded from participation if they had gastrointestinal or metabolic diseases or disorders, type-2 diabetes under pharmaceutical treatment, fasting glucose ≥126 mg/dL, fasting triglycerides ≥300 mg/dL, use of anti-obesity medication/supplements for the preceding 6 months, cardiovascular disease, use of tobacco products, use of antibiotics in the preceding month, use of polyphenol-rich supplements, dietary pattern of high polyphenol intake, or adverse reactions to blackberries. Volunteers were excluded if they had a weight change of greater than 10% in the past 12 months. The study protocol (Medstar IRB project # 2013-037) was approved by Medstar Health Research Institute institutional review board (Hyattsville, MD, USA), and all subjects provided written, informed consent. The study was conducted at the USDA Beltsville Human Nutrition Research Center in Beltsville, MD, USA. Clinical trial registry number: This trial was registered at www.clinicaltrials.gov
2.1. Study Design
The study was a randomized, placebo controlled, cross-over with two treatments. Participants were not blinded to the treatments due to difficulty in blinding to food treatments. Participants consumed either 600 g of whole blackberries (BBs) (frozen, removed from freezer within 12 h of consumption) or a calorically matched amount of artificially flavored gelatin (GEL) daily for one week as part of a fully controlled diet. Frozen blackberries were purchased in bulk as one lot from Sysco (Jessup, MD, USA) and stored at −20 °C. Gelatin was prepared from a commercially available powdered mix (Kraft Jell-O brand, strawberry, Chicago, IL, USA). Treatment periods were separated by a one-week washout during which participants were instructed to avoid red and purple pigmented fruits and vegetables. Treatment doses were divided in two equal sized portions of 300 g each and consumed at breakfast and dinner. In an effort to maximize treatment differences, the subjects consumed the blackberries at twice the amount of fruit intake recommended in the 2015–2020 Dietary Guidelines for Americans (600 g of blackberries is approximately 4 cups) [18
]. The blackberry treatment provided ~1476 mg of flavonoids and ~361 mg of total anthocyanins daily as analyzed using a published LC/MS method (Table 1
]. Participants were randomly assigned to one of the two treatment orders by the study coordinator, and treatments were color coded to conceal treatment identities from staff.
Participants were fed a controlled diet with a macronutrient profile of 40% of energy from fat, 45% from carbohydrate, and 15% from protein; the diet was devoid of anthocyanins except for the blackberry treatment. Food intake was scaled according to energy needs for each participant based on the Harris–Benedict equation and an activity factor. Meals were provided as a 2-day menu rotation using common American menu items. Participants were instructed to eat only the food provided to them by the Nutrition Center. Monday through Friday, participants were required to eat both breakfast and dinner at the Nutrition Center, while both lunch and weekend meals were packed for consumption off-site. Diet adherence was assessed by monitoring changes to body weight. To encourage compliance, subjects were under observation by dietetic technicians when consuming breakfast and dinner meals at the Nutrition Center.
2.3. Assessments Sample Collection and Analysis
The final twenty-four hours of each diet period was completed with participants residing in a room-sized indirect calorimetry chamber [20
] for measurement of respiratory gasses and subsequent calculation of respiratory quotient (RQ), energy expenditure, and substrate oxidation. Participants arrived at the center between 4:00 p.m. and 5:00 p.m. for their 24-h chamber stay. Participants were instructed to engage only in quiet activities with the exception of thirty minutes of scheduled, supervised treadmill walking (treadmill programmed for 3 mph for 30 min) in the early afternoon of the final day of each calorimeter session. Meals and bottled water were delivered through an air lock, and each chamber had a ceiling fan set to low to promote even mixing of respiratory gases.
Chamber air was sampled every 100 s, and gas concentrations were measured simultaneously with a Perkin Elmer MGA 1200 multiple gas analyzer (Waltham, MA, USA). Prior to the subjects’ stay, each chamber was calibrated via ethanol combustion. A deconvolution algorithm [21
] was applied to gas data to reduce instrumental noise and to generate minute-by-minute estimates for CO2
production and O2
consumption. RQ, energy expenditure, and substrate oxidation were calculated for the 24-h period, as well as for 5 time isolations: Evening—4 h starting with the first bite of dinner, ~6:00 p.m. to 10:00 p.m.; Nighttime—two hours at night (between 2:00 a.m. and 4:00 a.m.), which would provide an estimate of resting metabolic rate; Morning—4 h starting with the first bite of breakfast, ~7:00 a.m.–11:00 a.m.; Afternoon—2 h starting with the first bite of lunch, ~12:00 p.m.–2:00 p.m.; Exercise—30 min during treadmill walking (2:00 p.m.–2:30 p.m.).
In order to determine modulation of insulin sensitivity and glucose tolerance by blackberries, a meal-based oral glucose tolerance test (MTT) was administered on the morning of day 7 while the participants were completing their 24-h calorimeter stay. Participants were awakened at approximately 6:00 a.m., and an indwelling catheter was placed in the antecubital vein, after which 2 blood draws were collected before consumption of their meal. Participants were able to extend their arm to the outside of the chamber by way of a small arm port that was only opened for catheter setting and subsequent blood collections. Subjects were then provided with approximately 75 g of carbohydrate in the form of toaster waffles and syrup in combination with either 302 g of blackberries or 273 g of gelatin closely matched for carbohydrate and energy (Table 2)
Participants had ten minutes to consume both the waffle meal and their respective treatment foods. Subsequent blood sampling was collected at 30, 60, 90, 120, 180, and 240 min after the first bite of breakfast. Blood was collected in serum, plasma-EDTA, and sodium-fluoride tubes, centrifuged, aliquoted, and stored at −80 °C until analyzed. Serum glucose, non-esterified fatty acids (NEFAs), and triglycerides were analyzed using standard protocols on an automated clinical chemistry analyzer (Vitros 5,1 FS, www.orthoclinical.com
). Insulin was measured using ELISA kits (EMD Millipore, Burlington, MA, USA, inter-assay CV = 2.83%) per the manufacturer’s instructions on an automated plating and spectrophotometry system (DSX workstation, Dynex Technologies, Chantilly, VA, USA).
2.4. Calculations and Statistics
Due to lack of data on the effect of polyphenols on fat oxidation, this study was conducted as a pilot study. The target enrollment was n
= 16 based on previous calorimetry studies at the Beltsville Human Nutrition Research Center [22
]. Additional subjects were enrolled due to weather related electrical disruptions in data collection. Each calorimetry outcome parameter (averaged RQ and summed fat oxidation, carbohydrate oxidation, and energy expenditure) was calculated for each of the time isolations (24 h, evening, nighttime, morning, afternoon, and exercise). Energy expenditure was calculated using the Weir equation, and substrate oxidation (g of fat or carbohydrate used for energy) was calculated using the equations of Livesey and Elia [23
]. Because the participants were weight stable and on a controlled protein intake that was the same for both feeding periods, they were assumed to be in nitrogen balance. Thus, the rate of protein oxidation (required to calculate oxidation of fat and carbohydrate with Livesey equations) was determined using protein intake from the controlled feeding menu. MTT incremental area under the curve (iAUC) was calculated for glucose and insulin, and area under the curve (AUC) for NEFAs using central Riemann-sum. Fasting concentrations of glucose and insulin were used to calculate homeostasis model assessment of insulin resistance and β-cell function (HOMA-IR and HOMA-B) as follows: HOMA-IR = (fasting serum insulin × fasting serum glucose)/22.5 and HOMA-B = (20 × fasting serum insulin)/(fasting serum glucose − 3.5), where fasting serum insulin concentrations were expressed as µU insulin/mL serum and fasting serum glucose concentrations were expressed as mmol glucose/L serum [24
Linear mixed models were used to test for statistically significant differences between the blackberry and gelatin treatments using “proc mixed” repeated measures analysis of covariance with SAS version 9.4 (SAS institute, Cary, NC, USA). Normality and homoscedasticity of residuals were determined by the Shapiro–Wilk test and visual inspection of residual plots, respectively. Non-normality of residuals was addressed by mathematical transformation. Model estimates of response variables from each treatment were repeated on subject fit with the best covariance structure, which was determined by information criteria as well as visual inspection of residual plots for each covariance structure used in preliminary analyses. The main effect of treatment and covariates of subject BMI, age, and sequence order were included in the model statement. Interactions of BMI and age with treatment were determined with backward elimination of non-significant terms. Random side error effects were estimated for subjects nested in sequence. Data are presented as LSmeans for each treatment and p < 0.05 was considered statistically significant.
Augmentation of lifestyle modifications with micronutrient and phytochemical rich foods as a means to promote weight loss remains an attractive approach for dieticians, physicians, and the consumer. They are relatively inexpensive and consumers have easy access to these “functional” foods when compared to pharmacotherapies or invasive surgeries. In order to improve the chances of increased weight loss, or curbed weight gain, nutritionists must be able to demonstrate which foods promote this activity in order to equip dieticians with the most effective dietary approaches to combat obesity.
Rodent studies have successfully demonstrated the anti-obesity effects of anthocyanin-rich foods or treatments such as berries and purple corn [8
]. Alongside reductions in weight gain and adiposity, these same studies reported an increase in insulin sensitivity. Human studies using freeze-dried berries or purified anthocyanin extracts have reported less consistent results [27
]. One limiting factor of the human research to date has been the lack of control on the diet of the study participants.
Our study subjects exhibited increased fat oxidation when blackberries were included in the diet. This is in agreement with the one other published study using calorimetry to assess fuel use in humans consuming anthocyanins [37
]. In that study, fat oxidation increased 27% when the athletes consumed the black currant extract for seven days compared to placebo during moderate intensity cycling (65% of VO2max
]. Our findings of increased fat oxidation during a 30-min bout of low intensity treadmill walking with the blackberry treatment support their findings and the concept that anthocyanins can promote fat oxidation during physical activity. Wei et al. [26
] observed an increase in skeletal muscle lipoprotein lipase (LPL) activity and lower adipose tissue LPL activity in mice fed C3G, which would be in accordance with increased fat oxidation. How exactly the blackberries are acting to influence substrate oxidation, but less-so energy expenditure requires future work.
Tea, another flavonoid-rich dietary component, has also been investigated for its ability to influence energy expenditure and substrate oxidation. Rumpler et al. [38
] investigated the effects of oolong tea on measures of indirect calorimetry after noting weight loss interventions with oolong tea [39
]. Twelve men consumed 1.5 L per day of full-strength oolong tea, a caffeine-matched positive water control, or a placebo water control in a crossover, randomized design for three days with a 23 hr stay in a room-sized calorimetry chamber on the third day. Subjects expended 280 more calories when consuming oolong tea and there was a 12% increase in 24-h fat oxidation when compared to placebo water [39
], though these values were not different from those for the caffeine control. Alternatively, Dulloo et al. [40
] observed a significant reduction in RQ, and an increase in EE in healthy, sedentary men receiving a single daily dose of green tea extract compared to a caffeine placebo. In addition, a study by Rudelle et al. [41
] reported a 4.6% increase in EE after consumption of a beverage containing green tea catechins, caffeine, and calcium, though no effect was observed on specific substrate oxidation. In contrast to the null findings on substrate oxidation by Rudelle et al., Gahreman et al. [42
] showed that green tea extract administered along with sprinting exercises increased fat oxidation in healthy weight, untrained young females both before and shortly after exercise by increments of 24% and 29%, respectively. In another study, 12 overweight men showed an increase in postprandial fat oxidation, measured using a ventilated hood, after consuming a dose of the tea flavonoid EGCG for three days compared to placebo [43
], though a higher dose of the tea flavonoid did not result in the same effect. These human studies involving tea products may act through different mechanisms compared to the blackberry intervention of this study, as they show more pronounced effects on energy expenditure with less evidence on affecting the partitioning of a fuel substrate, whereas the opposite appears to be the case with the blackberry treatment in this study. One obvious difference in comparing these interventions is the caffeine content of tea.
Our study demonstrated an age dependent improvement in insulin sensitivity with blackberry intake, with younger subjects being most responsive. Other studies have also described an anti-diabetic effect of berry consumption [32
] and have been described in two meta-analyses [28
]. One possible explanation for the insulin sensitizing effect of berries is the activation of adenosine monophosphate protein kinase across several tissues involved in glucoregulation [16
]. Furthermore, amelioration of fatty acid overload may be possible by the beige-adipocyte phenotype invoked by cyanidin-3-glucoside, thereby improving insulin signaling [49
]. Other mechanistic work highlights the potential to inhibit adipogenic enzymes of the liver as well as reduce the absorption of glucose from the gut [8
]. Thus, berry anthocyanins likely invoke positive effects in myriad pathways related to glucoregulatory control. An unexpected finding from this study was the higher serum NEFA AUC with the BB treatment during the MTT, which occurred in parallel to the significant reduction in insulin AUC, despite no change in the glucose curve. Higher circulating NEFAs are classically perceived as an instigator in reduced insulin sensitivity and increased hepatic glucose output [51
]. NEFA overload from the visceral adipose depot is believed to complicate the metabolic syndrome [53
]. However, a recent tracer study modeling NEFA kinetics in obese men and women reported the dual-action of insulin in the regulation of fatty acid release and uptake by peripheral tissues [54
]. One possible explanation for our observation may be that the increase in insulin sensitivity (reduced insulin secretion during the MTT) with BBs may have yielded higher circulating NEFAs due to less constraints on these insulin-dependent regulatory mechanisms. Alternatively, as described by Lambert and Parks, berries may have an effect on the “spillover” pathway of lipoprotein clearance [55
]. Fatty acid “spillover” refers to the release of fatty acids into the blood stream after cleavage from chylomicron triglycerides by LPL. Thus, the increase in NEFAs may be related to Wei et al.’s [26
] finding that C3G activates LPL associated with skeletal muscle.
One limitation of this study was that the treatments could not be blinded, since we were using whole foods. Another limitation of this study was that, while the total carbohydrate content of the two meals was matched extremely closely (106 g CHO for the gelatin/pancake meal vs. 108 g CHO for the blackberry/pancake meal), the sugar content of the two meals used for the glucose tolerance test were slightly different (81.9 g sugar for the gelatin/pancake meal vs. 70.9 g sugar for the blackberry/pancake meal). Since the insulin response would be driven by the total carbohydrate load rather than just sugar, and since the glucose responses were not different between treatments, the slight difference in sugar content of the treatment and control is likely not the cause of the improved insulin response when subjects were consuming berries.