Four-week coffee consumption affects energy intake, satiety regulation, body fat, and protects DNA integrity

FRIN-05274; No of Pages 8 Food Research International xxx (2014) xxx–xxx

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Four-week coffee consumption affects energy intake, satiety regulation, body fat, and protects DNA integrity Tamara Bakuradze a, Gina Alejandra Montoya Parra a, Annett Riedel b, Veronika Somoza b, Roman Lang c, Natalie Dieminger c, Thomas Hofmann c, Swantje Winkler d, Ute Hassmann d, Doris Marko d, Dorothea Schipp e, Jochen Raedle f, Gerhard Bytof g, Ingo Lantz g, Herbert Stiebitz g, Elke Richling a,⁎ a

Department of Chemistry, Division of Food Chemistry and Toxicology, Technische Universität Kaiserslautern, Kaiserslautern, Germany Department of Nutritional and Physiological Chemistry, University of Vienna, Vienna, Austria c Chair of Food Chemistry and Molecular Sensory Science, Technische Universität München, Freising, Germany d Department of Food Chemistry and Toxicology, University of Vienna, Vienna, Austria e Rosenthal-Bielatal, Germany f Westpfalz-Klinikum, Medizinische Klinik III, Hellmut-Hartert-Straße 1, Kaiserslautern, Germany g Tchibo GmbH, Hamburg, Germany b

a r t i c l e

i n f o

Article history: Received 13 December 2013 Received in revised form 31 March 2014 Accepted 14 May 2014 Available online xxxx Keywords: Coffee Body fat Food intake Serotonin Ghrelin DNA protection Human intervention study

a b s t r a c t Recent epidemiological studies suggest that coffee, one of the most widely consumed beverages worldwide, may reduce risks of degenerative diseases such as diabetes type 2, cardiovascular disease and certain types of cancer. These effects have partly been ascribed to coffee's antioxidant and body weight-reducing capacities. To explore the mechanisms involved, effects of coffee consumption on body weight/composition, food intake, satiety markers (serotonin and ghrelin) and DNA integrity were monitored in a four-week double-blind randomized crossover intervention study with 84 healthy subjects. Subjects consumed two different coffee blends (study blend, SB, and market blend, MB), with similar caffeine contents but substantially differing contents of chlorogenic acids and N-methylpyridinium. The consumption of both coffees (3 × 250 mL per day) was associated with a decrease in body fat over the whole study period (p b 0.001), which was more pronounced with SB. During intervention with MB, plasma serotonin levels increased (p b 0.001) whereas plasma ghrelin levels decreased (p b 0.001) relative to levels recorded during the preceding washout period. Consumption of both coffee blends was associated with DNA-protective effects (p b 0.001). These findings suggest that regular coffee consumption may provide health benefits in terms of reducing energy intake and body fat, regulating satiety and protecting DNA integrity. © 2014 Elsevier Ltd. All rights reserved.

Introduction Coffee is a beverage that is prepared from dried and roasted seeds of Coffea varieties and consumed worldwide. Epidemiological evidence suggests that coffee consumption may be associated with the prevention or delayed onset of certain non-communicable diseases, such as diabetes type 2, cardiovascular disease and some types of cancer (Bidel et al.,

Abbreviations: BIA, bioelectrical impedance analysis; BMI, body-mass index; 5-CQA, 5caffeoylquinic acid; FFM, fat free mass; FM, fat mass; GIP, glucose-dependent insulinotropic polypeptide; GLP-1, glucagon-like peptide-1; 5-HT, 5-hydroxytryptamine (serotonin); MB, market blend coffee; NMP, N-methylpyridinium; PBMC, peripheral blood mononuclear cells; ROS, reactive oxygen species; SB, study blend coffee; TBW, total body water; WBC, white blood cells. ⁎ Corresponding author at: Division of Food Chemistry and Toxicology, Department of Chemistry, University of Kaiserslautern, Erwin-Schroedinger-Straße 52, D-67663 Kaiserslautern, Germany. Tel.: +49 631 205 4061. E-mail address: [email protected] (E. Richling). URL: http://ds-statistik.de (D. Schipp).

2010; Zhang, Lopez-Garcia, Li, Hu, & van Dam, 2009). These beneficial health effects have been partly attributed to the inhibitory effects of caffeine on adenosine receptors (Muller & Jacobson, 2011), and partly to the antioxidative effects of phenolics and chlorogenic acids (CGA) originating from green beans (Bakuradze et al., 2010) and compounds generated during roasting (Boettler et al., 2011; Somoza et al., 2003). However, structure–activity relationships have been elucidated for few coffee constituents to date (Arab, 2010; Hoelzl et al., 2010). The antioxidative activity of coffee is ascribed primarily to caffeoylquinic acid (CQA), and certain compounds generated by roasting, including N-methylpyridinium (NMP) and other Maillard reaction products (Antony, Han, Rieck, & Dawson, 2000; Borrelli, Visconti, Mennella, Anese, & Fogliano, 2002; Del Castillo, Ames, & Gordon, 2002; Farah, de Paulis, Moreira, Trugo, & Martin, 2006; Lang, Yagar, Eggers, & Hofmann, 2008; Stadler, Varga, Hau, Vera, & Welti, 2002; Stadler et al., 2002). It has been proposed that certain coffee constituents may offer protection against damage mediated by oxidative stress due to their ability to scavenge reactive oxygen species and in addition to induce the expression of

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Please cite this article as: Bakuradze, T., et al., Four-week coffee consumption affects energy intake, satiety regulation, body fat, and protects DNA integrity, Food Research International (2014), http://dx.doi.org/10.1016/j.foodres.2014.05.032

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antioxidant enzymes (Bakuradze et al., 2010; Boettler et al., 2011). In addition, it was also found in a human intervention study that coffee rich in compounds from both green coffee beans and roast products significantly reduced total DNA strand breaks (encompassing oxidative and other DNA damage) as well as background DNA strand breaks in white blood cells (WBC) (Bakuradze et al., 2011, 2014). In a further intervention study, a similar decrease in total DNA strand breaks was observed in isolated lymphocytes, together with an increased expression of genes involved in cellular antioxidant defense following the intake of instant coffee rich in chlorogenic acids (Hoelzl et al., 2010). Associations have also been found between regular coffee consumption and moderate decreases in body weight together with decreased diabetes risks in both normal and overweight population groups (Greenberg, Boozer, & Geliebter, 2006; Kempf et al., 2010; Thom, 2007; Tunnicliffe & Shearer, 2008). Furthermore, associations between moderate reductions of body weight and body fat of healthy subjects and consumption of coffee rich in both green bean constituents and roast products have been reported (Bakuradze et al., 2011). The observed reductions of energy and nutrient intakes suggest that coffee contains substances that influence the regulation of hunger and satiety in addition to increasing energy expenditure (Bracco, Ferrarra, Arnaud, Jequier, & Schutz, 1995; Greenberg et al., 2006). Caffeine reportedly induces thermogenesis, lipolysis and increases in metabolic rates in humans (Bracco et al., 1995; Greenberg et al., 2006; Tagliabue et al., 1994). However, similar effects on body weight have also been observed in studies with decaffeinated coffee, suggesting that other compounds are also involved (Thom, 2007; Vinson, Burnham, & Nagendran, 2012). Accordingly, several constituents of green coffee beans, such as CQA, have been found to inhibit glucose absorption and hepatic glucose-6-phosphatase activity (Hemmerle et al., 1997; Johnston, Clifford, & Morgan, 2003; Thom, 2007). CQA may also alter the secretion of gut peptides, such as glucagonlike peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP), both of which putatively play important roles in the shortterm regulation of energy intake (Johnston et al., 2003; Tunnicliffe & Shearer, 2008). Food intake is subject to complex regulation involving the gastrointestinal tract, hypothalamus and signaling networks mediated by various neurotransmitters and hormones (Halford & Harrold, 2012; Lopaschuk, Ussher, & Jaswal, 2010; Wren et al., 2000; Wurtman & Wurtman, 1995). Two signaling molecules thought to play important roles, via the regulation of hunger and satiety, are serotonin (5-HT) and ghrelin. Increases in the secretion of serotonin by neuronal cells in the intestine in response to intraluminal stimuli (Burton-Freeman, Gietzen, & Schneeman, 1999) reportedly reduce food intake, while increases in secretion of ghrelin by gastric cells stimulate appetite and food intake in rodents and humans (Wren et al., 2000). In order to elucidate the effects of coffee consumption on energy metabolism in healthy coffee drinkers a 20-week intervention study with a crossover design (four weeks of coffee intervention) was carried out with 84 healthy male (n = 46) and female (n = 38) volunteers. The aims of the study were firstly to investigate the effects of coffee on body weight/composition, food intake and satiety and secondly to monitor DNA-protective effects associated with coffee consumption. The effects of two coffees were compared in the study: a special blend (SB), with elevated levels of dark roast coffee constituents and green bean constituents such as chlorogenic acids, and a market blend (MB), reflecting the average composition of household coffee commercially available in Germany. Materials and methods Subjects and study design This study was approved by the local ethics committee of RhinelandPalatinate, approval no. 837.414.10 (7423). All subjects were volunteers and gave their informed written consent. They underwent baseline

medical examinations (including blood sample analysis) and anthropometric measurements. Ninety healthy, non-smoking, 20- to 44-year-old male and female (non-pregnant), volunteers with a BMI of 19–26 kg/m2 who were taking no pharmaceutical drugs and/or food supplements were recruited. Six individuals dropped out because of illness or personal reasons. The remaining 84 (mean ± SD age 25.6 ± 5.8 years and BMI 22.9 ± 1.9 kg/m2) were randomly allocated to one of two groups — group A, n = 43 (24♂, 19♀) or group B, n = 41, (22♂, 19♀) — who fully participated in a 20-week intervention study, from 18/19th January to 6/7th June 2011. The study had a prospective, randomized crossover design (Fig. 1) as follows: weeks 1–4 (1st washout phase), weeks 5–8 (1st coffee consumption phase), weeks 9–12 (2nd washout phase), weeks 13–16 (2nd coffee consumption phase) and weeks 17– 20 (3rd washout phase). The sample size (target significance level α = 5%, with 80% power) was determined on the basis of a previous intervention study (Bakuradze et al., 2011). During the first intervention phase, group A consumed MB coffee and group B SB coffee. In the second intervention phase the treatments were switched, with group A consuming SB coffee and group B MB coffee. Coffees were distributed in coded, plain packaging so that both experimenters and subjects were blind to the respective coffee type. Each subject was provided a sheet of instructions for coffee preparation. Overall variations of coffee machines concerning water supply and coffee extraction were b10% (Lang et al., 2013). During intervention periods subjects consumed 750 mL/day of black coffee (with/without sugar) in three equal portions (morning, midday and afternoon) that they freshly prepared using a commercially available coffee pad machine with 125 mL water for each 7.5 g coffee pad. Thus six coffee pads were required to obtain the daily total of 750 mL. During the washout phases coffee was replaced with an equivalent daily volume of water, also consumed in three equal portions. Subjects were instructed to maintain their usual dietary habits during the study but to abstain from any additional intake of coffee, caffeine-containing products, dietary supplements or foods rich in polyphenols. Volunteers receive written information to abstain from consumption of coffee and caffeine containing beverages, tea, malt coffee, dark chocolate and dietary supplements. Subjects recorded all food and beverage intakes in the seven days immediately prior to the study and in the last week of each study phase, in order to document individual dietary habits and ascertain their compliance with the instructions. This information was utilized to monitor the effect on energy/nutrient intakes (see the section ‘Nutrient intake’). On the first day of the study and the last day of each study phase each volunteer collected a 50 mL fasting urine sample in the morning. Anthropometric measurements (see below) were taken on an empty bladder then venous blood samples were collected. Women were additionally given a pregnancy test. Preparation and analysis of the coffee blends The SB coffee was a blend of 100% Arabica (Coffea arabica) roasts, composed largely of dark roast, particularly rich in roast products (including high NMP contents) together with some light roast, rich in green bean constituents. MB coffee was blended from equal portions of five major commercially available regular coffee brands, thus representing a typical medium roast filter coffee blend. Four of the five coffees were pure Arabicas, the fifth contained some Robusta (Coffea canephora), which contains significant amounts of 16-O-methylcafestol (Speer & Kölling-Speer, 2006). Both ground coffee blends were portioned into standard coffee pads (Tchibo GmbH, Hamburg, Germany) and packed into appropriate plastic bags, under inert gas. The bags were clearly distinguishable (red and silver, respectively) and carried a code. Color and code were not disclosed to volunteers and the staff conducting the intervention study (double blinding). The assignment of the two coffees was disclosed to the scientific staff only after all data associated with the intervention study had been collected.

Please cite this article as: Bakuradze, T., et al., Four-week coffee consumption affects energy intake, satiety regulation, body fat, and protects DNA integrity, Food Research International (2014), http://dx.doi.org/10.1016/j.foodres.2014.05.032

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Fig. 1. Study design: MB, market blend coffee; SB, study blend coffee; BS, blood sampling; wk, week.

The coffee samples were analytically characterized using HPLC– DAD and HPLC–MS/MS methods previously described: caffeine and caffeoylquinic acids (3-, 4-, and 5-CQA) were quantified using HPLC– DAD (324 nm, 272 nm) with external calibration (Weiss et al., 2010). NMP and trigonelline were quantified using stable isotope dilution analysis with synthetic d3-NMP following sample clean-up via solid phase extraction on RP18 (Lang, Wahl, Stark, & Hofmann, 2012).

Anthropometric measurements Subjects' body height and weight were measured (the latter using a Delta 707 digital scale, Seca, Hamburg, Germany) and their BMI (kg per m 2 ) calculated. Body composition — total body water (TBW), fat mass (FM) and fat-free mass (FFM) — was determined using three-compartment bioelectrical impedance analysis with a BIA 101 analyzer (SMT medical GmbH, Wuerzburg, Germany), in accordance with the manufacturer's instructions. In order to minimize the variability of the method a standard protocol was used: the measurements were performed at the same time in the morning with fasted subjects (no drinking and eating), at horizontal position and emptied bladder. Electrodes were placed at the right hand and foot (dry skin), following the manufacturer's instructions.

Processing and storage of blood, plasma and urine samples For DNA analysis venous blood samples were collected in serum tubes containing EDTA at 37 °C and immediately worked up for the Comet Assay (see the section ‘Determination of spontaneous and total DNA strand breaks (Comet Assay)’). For serotonin determination, whole blood was centrifuged (1800 ×g at 4 °C/15 min) and plasma aliquots were stored at −80 °C. For determination of ghrelin, a protease inhibitor cocktail (Sigmafast™ protein inhibitor cocktail, Sigma Aldrich, Vienna, Austria) was added to whole blood samples before centrifugation (1800 ×g at 4 °C for 15 min) in accordance with the supplier's instructions. The resulting blood plasma was mixed with hydrochloric acid to a final concentration of 0.1 M to stabilize acylghrelin. Aliquots were stored at −80 °C. In order to isolate peripheral blood mononuclear cells (PBMC) 10 mL of freshly collected human blood was layered on 10 mL of Histopaque1077 (Sigma Aldrich, Vienna, Austria) and centrifuged at room temperature at 400 ×g continuously for 20 min. Lymphocytes were extracted from the cloudy middle layer and transferred to 12 mL RPMI 1640 medium (Invitrogen Life Technologies, Vienna, Austria) supplemented with 10% fetal calf serum and 1% penicillin/streptomycin and tempered at 37 °C. This cell suspension was centrifuged for 10 min at 250 ×g, the supernatant was discarded and the pellet was redissolved in 8 mL RPMI 1640 medium. After centrifugation cells were transferred to 700 μL ice cold PBS and centrifuged again. The pellet was resuspended in 1 mL RNAlater (QIAGEN, Hilden, Germany) and stored at − 80 °C. Urine samples were immediately frozen at −80 °C.

Determination of spontaneous and total DNA strand breaks (Comet Assay) Alkaline single cell gel electrophoresis was performed to determine spontaneous and total (after additional treatment with formamidopyrimidine glycosylase) DNA strand breaks following Collins, Dusinska, Gedik, and Stetina (1996), with slight modifications, reported elsewhere (Bakuradze et al., 2011) and was expressed as mean tail intensity (TI%) from two gels. Determination of plasma serotonin and ghrelin concentrations Plasma serotonin and ghrelin concentrations were determined using a serotonin ELISA kit (DLD Diagnostika GmbH, Germany) and a ghrelin ELISA kit (Sceti K.K., Japan), respectively, in accordance with their manufacturer's instructions. Total RNA was extracted using a RNeasy mini kit (QIAGEN, Hilden, Germany), also in accordance with the manufacturer's instructions. In order to obtain cDNA from 1 μg RNA, a QuantiTect Reverse Transcription Kit (QIAGEN, Hilden, Germany) was used and qPCR was performed using QuantiTect SYBR Green PCR and QuantiTect Primer Assays (both QIAGEN, Hilden, Germany). The primers used were Hs_GHRL_1_SG QT00041377 (ghrelin), Hs_GAPDH_1_SG QT00079247 (GAPDH) and Hs_RPL13A_1_SG QT00089915 (RPL13a). All samples were analyzed at least twice and blank controls were included. The PCR protocol was: 15 min at 95 °C, followed by 40 cycles of 15 s at 94 °C, 30 s at 55 °C and 30 s at 72 °C. Ghrelin transcript levels, normalized to those of the endogenous control genes GAPDH (glyceraldehyde 3-phosphate dehydrogenase) and RPL13a (ribosomal protein L13a), were calculated using Ct values obtained using the 2−ΔΔCt method. LC–MS/MS determination of NMP and trigonelline concentrations in spot urine samples NMP, trigonelline and creatinine concentrations in the urine samples were determined using the HILIC–HPLC–MS/MS method described by Lang, Wahl, Stark, and Hofmann (2011). Briefly, spot urine samples (10 μL) were each mixed with a portion (1 mL) of a solution containing the internal standards d3-creatinine (10 μM), d3-trigonelline (1 μM) and d3-NMP (1 μM) in acetonitrile/water (95/5, v/v). After centrifugation, the clear supernatant (1 μL) was subjected to HPLC–MS/MS analysis. Concentrations of the analytes NMP and trigonelline were normalized to the individual creatinine concentrations and are given as nmol analyte per μmol creatinine. Dietary analysis The nutrient intake (kcal, carbohydrates, fat and proteins) of each subject during each phase was assessed using the five seven-day food and beverage records collected as described in the section ‘Subjects and study design’ and the nutrition software package PRODI 5 (NutriScience GmbH, Hausach, Germany).

Please cite this article as: Bakuradze, T., et al., Four-week coffee consumption affects energy intake, satiety regulation, body fat, and protects DNA integrity, Food Research International (2014), http://dx.doi.org/10.1016/j.foodres.2014.05.032

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Statistical analysis Statistical analysis involved testing for potential confounding effects associated with group, treatment, time, interaction and carry-over (Jones & Kenward, 1988). Data were tested for normality using Shapiro–Wilk's test. If normality requirements for parametric tests were met (following logarithmic transformation if necessary) t-tests were applied to detect significant effects. Where data did not meet these requirements, even after transformation, non-parametric tests were used. Where significant interactions or carry-over effects were identified, data from the second intervention period were excluded from the calculation of treatment-related effects. t-Tests between groups (or Wilcoxon's rank sum test) were used to compare the effectiveness of both coffees. t-Tests within groups (or Wilcoxon's signed rank tests) were applied to compare data between before and after consumption of either MB or SB coffee. If neither carry-over nor interaction was significant, the data from both groups A and B were pooled, then effects of both coffee blends, and data acquired in washout and intervention periods were compared. t-Tests between groups (or Wilcoxon's rank sum test) were used to compare the effects of the two coffee blends. t-Tests within groups (or Wilcoxon's signed rank tests) were used to compare data between washout and intervention with either coffee blend. The statistical model thus allowed for the estimation of product–effect differences between the two blends, although there may have been confounding effects due to the nature of the crossover design. Spearman correlations were used to identify relationships between the various parameters measured. Coefficients were calculated based on the changes between the first washout period and the first intervention period and significance was estimated using t-tests. Results and discussion Changes in body weight, body composition, food intake, biomarkers associated with satiety, and DNA integrity were monitored in a 20-week crossover intervention study with two different blends of coffee. Parameters related to the metabolism of fat/fatty acids, biotransformation of certain coffee constituents (including chlorogenic acids) and the coffees' effects on energy metabolism were also monitored and the results are currently in press (Riedel et al., 2014; Winkler et al., 2014). There are several limitations associated with the crossover methodology. The study was designed to compare the effects of two blends of coffee with differing constituent profiles. In a crossover trial subjects act as their own controls. Thus, the effects of each coffee could only be determined relative to the data from the preceding washout period.

Table 1 Mean ± SD concentrations of selected constituents in the market blend (MB) and study blend (SB). Compound

MB [mg/g]

SB [mg/g]

Caffeine Chlorogenic acidsa N-methylpyridinium (NMP) Trigonelline

12.39 19.31 0.39 6.27

12.83 10.01 1.20 3.42

a

± ± ± ±

0.1 0.3 0.0 0.1

± ± ± ±

0.2 0.3 0.0 0.2

Sum of 3-, 4- and 5-caffeoylquinic acid.

The design could not control for potential confounding factors such as variations in lifestyle, seasonal changes or variations in other factors with time. Other possible confounding factors are the temperaturerelated differences in physiological responses between consuming a hot beverage (coffee) during intervention periods and a cold beverage (water) during washout periods (Quinlan, Lane, & Aspinall, 1997). However, despite these limitations crossover designs are well established and widely used in clinical studies. Constituent profiles of the two coffee blends The coffees used in the study were characterized by the determination of the key constituents caffeine, NMP, trigonelline and chlorogenic acids (sum of 3-, 4- and 5-caffeoylquinic acids) (Table 1). The analysis showed that both coffees contained similar amounts of caffeine (ca 12 mg/g ground coffee), in line with published data (Barone & Roberts, 1996; Maier, 1981), corresponding to approximately 500– 600 mg/L caffeine in the brewed coffee. In contrast, their contents of chlorogenic acids, NMP and trigonelline significantly differed, reflecting differences in the roasting/blending process. Trigonelline decomposes during coffee roasting, giving rise to pyridine-related compounds such as nicotinic acid, and NMP (Lang et al., 2008; Stadler, Varga, Hau, Vera, & Welti, 2002; Stadler, Varga, Milo, et al., 2002). Similarly, the roasting process degrades chlorogenic acids, so dark roasts have lower chlorogenic acid contents than light roasts. It has been shown that N90% of these three substances are extracted into in the coffee beverage by brewing with a water:coffee ratio (v/w) N16 (Lang et al., 2013). NMP and trigonelline in urine Due to their negligible metabolic breakdown and high water solubility, NMP and trigonelline are excreted preferentially and rapidly via the urine. Thus, their urine levels provided valuable short-term biomarkers for compliance with the study protocol. In the washout phases NMP and trigonelline were virtually undetectable in urine samples (Fig. 2). In

Fig. 2. N-methylpyridinium (NMP) (nmol/μmol creatinine) (left) and trigonelline (nmol/μmol creatinine) (right) in urine samples of groups A and B after each study phase. 1. Coffee phase: group A, MB; group B, SB. 2. Coffee phase: group A, SB; group B, MB. WO: washout phase. *outlier, — median, □mean.

Please cite this article as: Bakuradze, T., et al., Four-week coffee consumption affects energy intake, satiety regulation, body fat, and protects DNA integrity, Food Research International (2014), http://dx.doi.org/10.1016/j.foodres.2014.05.032

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Table 2 Mean ± SD daily nutrient intake of 84 subjects during the intervention study (on the basis of seven-day food records). (WO — washout; MB — market blend coffee; SB — study blend coffee, ns — not significant). See the section ‘Statistical analysis’ for details.

Kcal

Protein [g]

Fat [g]

Carbohydrates [g]

Group

WO

A B A A B A A B A A B A

2049 ± 2075 ± 2061 ± 78.4 ± 76 ± 77.2 ± 77.3 ± 79.1 ± 78.2 ± 238.2 ± 238.3 ± 238 ±

+B

+B

+B

+B

MB 517 520 516 19.8 22.2 20.9 24.5 24 24.1 62.6 62.8 62.3

1939 2106 2021 73.8 77.8 75.7 71.6 78.9 75.1 230.8 242 236.2

MB vs WO p-value ± ± ± ± ± ± ± ± ± ± ± ±

467 495 486 16.5 24.1 20.5 21.7 21.4 21.8 53.4 56 54.6

ns

ns

ns

ns

WO 1968 2199 2081 76.3 80.7 78.4 73.2 86.9 79.9 225.5 253.3 239.1

contrast, all urine samples collected during the intervention periods contained NMP and trigonelline at concentrations consistent with the consumption of the required amount of the respective blend, indicating good compliance (Fig. 2). Furthermore, concentrations of NMP in urine from both groups were higher following the consumption of SB coffee than of MB, in accordance with the relative NMP concentrations in the blends (Table 1). Since dietary intake of NMP is largely restricted to coffee due to its roasting-induced formation, it represents an excellent biomarker for compliance control as a specific indicator of coffee consumption (Lang et al., 2011).

SB ± ± ± ± ± ± ± ± ± ± ± ±

485 473 490 17.1 18.4 17.4 21.9 23.7 23.6 58.9 55.6 58.6

1997 ± 1990 ± 1994 ± 75.1 ± 74.1 ± 74.6 ± 73.9 ± 77.5 ± 75.7 ± 233 ± 231.7 ± 232 ±

420 483 449 17 19.5 18.2 20.8 21.6 21.1 50 62.2 55.9

SB vs WO p-value

MB vs SB p-value

Interaction p-value

Carry-over p-value

0.026

ns

ns

ns

0.022

ns

ns

ns

0.046

ns

ns

ns

ns

ns

ns

ns

et al. (2011) that a dark roast coffee with high NMP contents reduced energy/nutrient intakes more effectively than a light roast. Body weight and body composition The body weight of subjects was nonsignificantly reduced following MB intervention (Table 3), significantly following SB intervention (p = 0.037). Notably, body fat was significantly reduced following consumption of each coffee blend, MB coffee being associated with a mean (±SD) reduction of −0.64 ± 1.75 kg (p = 0.001), while the reduction with SB was even greater at −0.90 ± 1.65 kg (p b 0.001). In addition, fat reduction was significantly more pronounced in males (SB − 1.7 ± 1.7 kg; MB −1.15 ± 2.04 kg, p b 0.001). The effect of NMP-rich SB coffee on body fat reduction was significantly higher (p = 0.02) than that of MB coffee. These results concur with previous findings regarding coffee blends rich in NMP and roast products (Bakuradze et al., 2011; Kotyczka et al., 2011). However, coffee constituents other than those associated with roasting also appear to be involved as a significant, but weaker, reduction in body fat was also observed with MB. Similar findings have been reported for chlorogenic acid-enriched coffee and green coffee bean extracts (Thom, 2007; Vinson et al., 2012). Thus certain constituents of coffee may stimulate energy metabolism, particularly the catabolism of endogenous body fat. The observed loss in body fat did not result in a similar total body weight change. This may be explained by a partially counterbalancing effect of some gain in FFM, for example with respect to muscle mass and TBW.

Nutrient intake The daily nutrient and energy intakes of subjects were calculated on the basis of the seven-day food and beverage records completed prior to the study and at the end of each study phase (Table 2). Their daily beverage intake during the study ranged from 1.5 to 2.5 L, and they maintained their usual fluid consumption throughout the study, so additional water intake had no effect on other parameters. The statistical analysis of total energy intake, protein, fat, and carbohydrates included data from both intervention periods. Energy and nutrient intakes were not significantly different between interventions with either coffee. In contrast, comparison of the data collected during the washout and intervention periods indicated significant reductions in caloric (p = 0.026), protein (p = 0.022), and fat (p = 0.046) intakes associated with the consumption of SB coffee. A slight but not significant reduction of carbohydrate intake was observed following consumption of SB coffee. Similar effects of coffee consumption on energy and nutrient intakes have been reported in other studies. Notably, Bakuradze et al. (2011) found that consumption of a coffee blend similar to SB was associated with a significant reduction in energy/nutrient intakes, and Kotyczka

Plasma serotonin and ghrelin levels The recorded plasma serotonin and ghrelin concentrations are summarized in Table 4. Plasma serotonin concentrations were significantly higher during the MB coffee consumption period (but not

Table 3 Mean ± SD body weight and body composition of 84 subjects during the intervention study (WO — washout; MB — market blend coffee; SB — study blend coffee, TBW — total body water; FFM — fat free mass; ns — not significant). See the section ‘Statistical analysis’ for details.

Body weight [kg]

Body fat [g]

TBW [l]

FFM [kg]

Group

WO

A B A A B A A B A A B A

70.79 69.86 70.34 16.50 16.17 16.34 39.74 39.15 39.75 54.29 53.03 53.7

+B

+B

+B

+B

MB ± ± ± ± ± ± ± ± ± ± ± ±

10.7 12.0 11.3 4.7 4.5 4.6 7.2 7.4 7.3 9.9 9.9 9.9

70.62 ± 69.6 ± 70.12 ± 16.62 ± 14.68 ± 15.70 ± 39.54 ± 40.2 ± 39.88 ± 54.01 ± 54.26 ± 54.14 ±

MB vs WO p-value 10.5 11.8 11.1 4.5 4.25 4.48 7.3 8.1 7.6 9.9 10.6 10.41

ns

0.001

0.011

0.015

WO 70.85 ± 69.62 ± 70.25 ± 16.52 ± 15.68 ± 16.12 ± 39.77 ± 39.76 ± 39.77 ± 54.33 ± 53.67 ± 54.00 ±

SB 10.6 11.8 11.2 4.7 4.1 4.39 7.4 7.5 7.4 10.1 10.5 10.1

70.54 69.51 70.04 15.21 15.24 15.22 40.10 39.76 40.17 55.32 53.70 54.51

± ± ± ± ± ± ± ± ± ± ± ±

10.7 11.9 11.3 5.04 4.43 4.73 8.1 8.0 8.0 11 10.6 10.9

SB vs WO p-value

MB vs SB p-value

Interaction p-value

Carry-over p-value

0.037

ns

ns

ns

0.001

0.02

ns

ns

0.034

ns

ns

ns

0.036

ns

ns

ns

Please cite this article as: Bakuradze, T., et al., Four-week coffee consumption affects energy intake, satiety regulation, body fat, and protects DNA integrity, Food Research International (2014), http://dx.doi.org/10.1016/j.foodres.2014.05.032

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Table 4 Mean ± SD plasma serotonin and ghrelin concentrations together with relative ghrelin expression in 84 subjects during the intervention study (WO — washout; MB — market blend coffee; SB — study blend coffee, ns — not significant). See the section ‘Statistical analysis’ for details.

Serotonin [ng/mL]

Ghrelin [pg/mL] Ghrelin relative transcription

Group

WO

MB

A B A+B A B A B A+B

64.03 ± 45.76 54.65 ± 35.35 59.34 ± 40.55 74.55 ± 33.2 74.88 ± 48.62⁎

89.55 72.44 80.99 54.61 84.43 0.59 1.14 0.86

1.00 1.00 1.00

MB vs WO p-value ± ± ± ± ± ± ± ±

47.57 47.57 46.07 28.2 44.10⁎ 0.3 0.8 0.7

0.001 0.001

0.001

WO

SB

64.85 ± 47.95 67.87 ± 41.52 66.36 ± 44.74 80.71 ± 36.01⁎ 73.0 ± 53.7 1.00 1.00 1.00

65.1 60.54 62.82 84.01 77.36 1.19 0.62 0.91

± ± ± ± ± ± ± ±

44.92 39.05 41.98 40.09⁎ 59.8 0.6 0.3 0.6

SB vs WO p-value

MB vs SB p-value

Interaction p-value

Carry-over p-value

ns

0.003 0.001

ns ns

ns 0.001 0.001

ns

ns

ns

ns

0.001

⁎ Due to carry-over effects data were excluded from statistical analyses.

when consuming SB coffee) than during the preceding washout period (p b 0.001). Due to significant carry-over effects (p b 0.001) for plasma ghrelin concentrations, data acquired for the second intervention period were excluded from statistical analyses. During the first intervention phase, plasma ghrelin concentrations were significantly lower with MB coffee (−16 ± 16.51 pg/mL, p b 0.001) than in the preceding washout period. In contrast, no difference was observed with SB coffee. Ghrelin transcript levels in the lymphocytes, normalized to those of two housekeeping genes (GAPDH and RPL13a) are also given in Table 4. Since no significant carry-over or time effects were detected, data acquired from both intervention periods were analyzed. Consumption of both coffees was associated with a decrease in ghrelin transcript levels, compared to the preceding washout period (both p b 0.001). Thus, whereas MB was associated with reductions in both ghrelin transcript and plasma ghrelin levels, SB only affected the hormone's transcript levels. These differences likely relate to the different constituents of the two blends. The findings suggest that MB increased the subjects' satiation, although their energy intake remained unchanged. A significant reduction in hunger with no significant alteration of plasma ghrelin levels has also been observed in a randomized clinical trial with

decaffeinated coffee (Greenberg & Geliebter, 2012). It is not yet clear which constituents of coffee are responsible for the observed effects.

DNA strand breaks The influence of coffee consumption on spontaneous and total (background plus FPG-sensitive) DNA strand breaks in WBC was also investigated. Since the statistical analysis revealed significant interactions (p b 0.001) and/or carry-over effects (p b 0.05) on spontaneous and total DNA strand breaks, the second crossover period was excluded (data not shown). In the first intervention period frequencies of spontaneous and total DNA strand breaks were significantly lower than during the preceding washout period (spontaneous: WO 0.43 TI%; MB 0.27 TI%, p b 0.001, WO 0.40 TI%; SB 0.27 TI%, p b 0.001; total: WO 1.41 TI%; MB 0.96 TI%, p b 0.001; WO 1.27 TI%; SB 1.08 TI%, p b 0.027). Despite the exclusion of data from the second intervention period, the results suggest that coffee contributes to maintain DNA integrity, corroborating evidence from several previous studies (Bakuradze et al., 2011, 2014 ; Bichler et al., 2007; Misik et al., 2010).

Fig. 3. Heat map correlation matrix of all parameters investigated during the course of the human intervention study. Colored fields: red, significant positive correlation; blue, significant negative correlation. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Please cite this article as: Bakuradze, T., et al., Four-week coffee consumption affects energy intake, satiety regulation, body fat, and protects DNA integrity, Food Research International (2014), http://dx.doi.org/10.1016/j.foodres.2014.05.032

T. Bakuradze et al. / Food Research International xxx (2014) xxx–xxx

Correlation analysis In total, about 80 parameters were investigated in this comprehensive human intervention study. This paper presents data on nutrient intake, body composition, and satiety. Data on energy metabolism and methylxanthines and the transcriptional activity of selected genes are published separately (Riedel et al., 2014; Winkler et al., 2014). Correlation analysis on the large amount of data collected provided insights into relationships between various pairs or groups of parameters, although of course pairwise correlations do not necessarily demonstrate causal relationships, as additional variables may also be involved. A heat map of Spearman correlations of all parameters determined in this study is shown in Fig. 3. For example, body fat was negatively correlated with the inflammation marker IL-6 (r = −0.25, p b 0.001) and more strongly correlated in male subjects (r = −0.36) than in females. IL-6 levels were also negatively correlated with spontaneous DNA strand breaks (r = − 0.24). Further negative correlations were found between body weight and the AMP/total adenosine nucleotide ratio (r = − 0.28) and oleoylcarnitine levels (r = −0.33). There was a marked positive correlation between the satiety marker leptin and body fat of both female (r = 0.37) and male subjects (r = 0.38). Although the correlation coefficients often appear relatively low, they may indicate relationships between the respective physiological variables associated with coffee consumption, without necessarily implying a causal effect. The accompanying papers (Riedel et al., 2014; Winkler et al., 2014) provide a more detailed analysis, where applicable. Conclusion The present study compared effects of a special coffee blend (SB), rich in both green bean constituents (such as chlorogenic acids) and roast products (such as NMP) compared to a reference (MB) coffee. Biomarkers associated with satiety, body composition, energy/nutrient intakes and DNA integrity were monitored. Both coffees were found to contribute to the maintenance of DNA integrity. Effects especially on body fat, and energy and nutrient intakes were found more pronounced after the consumption of SB coffee, as compared to MB. The overall results of this study thus indicate that regular coffee consumption is associated with beneficial health effects, including maintenance of DNA integrity, regulation of satiety, reductions of energy intake and increase of body fat catabolism. Acknowledgements First of all we want to thank all the volunteers for their participation. We are indebted to Sylvia Schmidt for her excellent assistance, Anja Beusch and Anika Wahl for their help with the quantitative analysis and Stefan Zepner for analyzing the food records. We are indebted to Gerhard Eisenbrand for many suggestions concerning an analysis of the results and preparation and improvement of the manuscript. We gratefully acknowledge the gift of FPG enzyme by Prof. Andrew R. Collins (University of Oslo, Norway). The authors Gerhard Bytof, Ingo Lantz and Herbert Stiebitz are employed by Tchibo GmbH. This work was supported by a grant from the German Federal Ministry of Education and Research (BMBF), grant no. (0315692), the DAAD (Deutscher Akademischer Austauschdienst), and Tchibo GmbH. All other authors have no declared conflict of interest, and all authors have approved the final manuscript. Author contributions Tamara Bakuradze organized, designed and performed the present intervention study, contributed to blood sample analyses, analyzed the results, contributed to the statistical analysis and wrote the manuscript. Gina Alejandra Montoya Parra contributed to blood sample analyses.

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Please cite this article as: Bakuradze, T., et al., Four-week coffee consumption affects energy intake, satiety regulation, body fat, and protects DNA integrity, Food Research International (2014), http://dx.doi.org/10.1016/j.foodres.2014.05.032