Original Article

European Journal of Clinical Nutrition (2010) 64, 1465–1471; doi:10.1038/ejcn.2010.173; published online 8 September 2010

Postprandial hyperglycemia and insulin response are affected by sea buckthorn (Hippophaë rhamnoides ssp. turkestanica) berry and its ethanol-soluble metabolites

Author Contributions: H-M Lehtonen, R Järvinen, M Viitanen, H Alanko and H Kallio designed research, H-M Lehtonen, R Järvinen and K Linderborg conducted research, H-M Lehtonen performed statistical analysis, H-M Lehtonen, R Järvinen, M Viitanen, K Linderborg and H Kallio wrote paper, and H-M Lehtonen had primary responsibility for final content.
All authors read and approved the final paper.

H-M Lehtonen1, R Järvinen1, K Linderborg1, M Viitanen2,3, M Venojärvi4, H Alanko2 and H Kallio1

  1. 1Department of Biochemistry and Food Chemistry, University of Turku, Turku, Finland
  2. 2Department of Geriatrics, University of Turku, Turku City Hospital, Turku, Finland
  3. 3Karolinska Institutet, Karolinska University Hospital Huddinge, Stockholm, Sweden
  4. 4Medical Laboratory Technology, Turku University of Applied Sciences, Turku, Finland

Correspondence: H-M Lehtonen, Department of Biochemistry and Food Chemistry, University of Turku, Vatselankatu 2, FI-20014 Turku, Finland. E-mail: henna-maria.lehtonen@utu.fi

Received 19 April 2010; Revised 10 June 2010; Accepted 10 June 2010; Published online 8 September 2010.

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Abstract

Background/Objectives:

 

Repeated postprandial hyperglycemia and subsequent mild, late hypoglycemia as well as high postprandial insulin response lead to metabolic events that may eventually develop into type 2 diabetes. The aim of this study was to assess how sea buckthorn berries as well as two sea buckthorn extraction residues modulate the postprandial metabolism after a high-glucose meal.

Subjects/Methods:

 

Ten healthy normal-weight male volunteers consumed four study breakfasts, one control (A) and three sea buckthorn meals on four distinct study days. All the meals contained yoghurt and glucose (50g). The sea buckthorn ingredients used were dried and crushed whole berries (meal B1), supercritical fluid (SF)-carbon dioxide (CO2)-extracted oil-free berries (meal B2) or ethanol-extracted SF-CO2-extraction residue (meal B3). Blood samples for glucose, insulin and tumor necrosis factor-α analyses were collected before and during the 6-h study period.

Results:

 

Meal B1 suppressed the postprandial peak insulin response when compared with meal A (Δconcentration of 30-min peak value −21.8mU/l, P=0.039), and stabilized postprandial hyperglycemia and subsequent hypoglycemia (Δconcentration of 30-min peak value—120-min value −30.4mU/l, P=0.036). Furthermore, meal B2 resulted in a more stable insulin response than the control meal (Δconcentration of 30-min peak value—120-min value −25.9mU/l, P=0.037).

Conclusions:

 

Removal of the CO2-soluble oil component from the berries did not show a significant change in the studied postprandial effects of the berries. The EtOH soluble components, again showed advantageous properties in both insulin and glucose responses.

Keywords:

glycemia; insulinemia; postprandial state; sea buckthorn

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Introduction

Sea buckthorn (Hippophaë rhamnoides L.) is distributed over a wide area of Eurasia. Currently, sea buckthorn is widely cultivated in China, Russia, India and Europe and readily available in markets. Sea buckthorn has been shown to have antiatherogenic properties (Basu et al., 2007), and to decrease oxidative stress (Suleyman et al., 2002) in animal trials. It has also been indicated to decrease the risk of coronary heart disease (Eccleston et al., 2002), prevent platelet aggregation (Johansson et al., 2000) and lower the plasma high sensitivity c-reactive protein level (Larmo et al., 2007) in human trials. Sea buckthorn and blueberry concentrate was shown to have a regenerative effect on pancreatic β cells in type 1 diabetic children (Nemes-Nagy et al., 2008).

Diet rich in food items that result in a lower postprandial insulin response modulates the inflammation status (Kallio et al., 2008). Repeated high postprandial insulin response and early postprandial hyperglycemia increase oxidative stress (Ceriello et al., 2008), inflammation (Dandona et al., 2005) and possibly insulin resistance and β-cell dysfunction (Ludwig, 2002). High postprandial glycemia and insulinemia are also significant risk factors of cardiovascular diseases in patients with type 2 diabetes (Ginsberg and Illingworth, 2001). As Westerners spend most of their time in a postprandial state, it is important to investigate the metabolism of the fed state instead of fasting values only (Lairon et al., 2007).

Metabolic disorders are related to chronic low-grade inflammation (Sholeson et al., 2006). Hyperinsulinemia has been shown to increase both tumor necrosis factor-α (TNF-α) mRNA in adipose tissue (Krogh-Madsen et al., 2004) and TNF-α concentrations in plasma (Ruge et al., 2009). Interactions between inflammation and metabolic dysregulation are, however, largely unknown. In a recent double-blind placebo-controlled trial in humans, a quite modest daily amount of 28g of sea buckthorn reduced the plasma high sensitivity c-reactive protein level (Larmo et al., 2007). Animal trials have shown that TNF-α concentrations directly correlate with insulin resistance (Hotamisligil et al., 1993), and thus the importance of this inflammatory cytokine in energy nutrient metabolism is evident.

As sea buckthorn is a rich source of many bioactive compounds (Kallio et al., 2002, 2009; Määttä-Riihinen et al., 2004; Yang et al., 2009), it has potential to alleviate the negative metabolic progression by various antioxidative as well as signal-modulating mechanisms. Therefore, the aim of this study was to assess how sea buckthorn berries as well as two different extraction residues (supercritical fluid carbon dioxide (SF-CO2)-extraction residue and ethanol (EtOH)-extracted SF-CO2-extraction residue) from sea buckthorn modulate the postprandial metabolism after a high-glucose meal. Recently, mixed berries were shown to suppress postprandial hyperglycemia (Törrönen et al., 2009), but to our knowledge no reports have been published on the effects of berries and berry products on postprandial insulin response.

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Subjects and methods

Subjects

Ten healthy non-smoking males aged 20–34 (average 24.7, s.d. 4.6) years, body mass index 19.8–26.9kg/m2 (excluding one bodybuilder whose body mass index was 30.0kg/m2, average (n=10) 23.7, s.d. 3.1), were recruited for the study. The study subjects had normal liver, kidney and thyroid functions (inclusion criteria plasma alanine aminotransferase <60U/l, creatinine <115μmol/l and thyroid-stimulating hormone 0.3–4.2mU/l).

Reagents

The EtOH used for berry fractionation was 96% ETAX A (Altia, Helsinki, Finland). Methanol, acetonitrile and acetic acid used for analyses were high-performance liquid chromatography grade and purchased from Sigma-Aldrich (Steinheim, Germany). Flavonol glycosides were purchased from Extrasynthese (Genay, France). D-fructose, D-quinic acid and L-ascorbic acid were purchased from Sigma Chemical Co. (St Louis, MO, USA). D-glucose and D-sorbitol (for sugars) were from Fluka (Buchs, Switzerland). Malic acid and L-tartaric acid (for acids) were purchased from Merck (Darmstedt, Germany). Sucrose and citric acid were from JT Baker (Deventer, The Netherlands).

Stock solutions of flavonol glycosides (0.5mg/ml) were prepared in methanol or dimethylsulfoxide-methanol (1:9 v/v, for isorhamnetin-3-O-glucoside, isorhamnetin-3-O-rutinoside) and stored at –70°C.

Analysis of sea buckthorn flavonol glycosides

Flavonol glycosides were analyzed with a method previously reported by the authors (Lehtonen et al., 2010a). The berry product (0.2g) was weighed, homogenized and extracted once with 4ml of 0.1% trifluoroacetic acid (TFA)-H2O and twice with 1ml of 0.1% TFA-methanol. Supernatants were combined and diluted with 8ml of 0.1% TFA-H2O. Extracts were applied in Supelco (C18 500mg) solid phase extraction tubes preconditioned with 2ml of methanol and 2ml of 0.1% TFA-H2O. The tubes were washed with 2ml of 0.1% TFA-H2O and the analytes were eluted with 1ml of TFA-methanol-H2O (40% of 0.1% TFA-H2O, 60% methanol). The samples were analyzed as such with the ultra high performance liquid chromatography-tandem mass spectrometry method. Ultra high performance liquid chromatography-tandem mass spectrometry equipment consisted of an Acquity UPLC system with a 50 × 2.1mm, 1.7μm, Acquity UPLC BEH C18 column and a Quattro Premier tandem quadrupole mass spectrometer (Waters, Milford, MA, USA). The elution of the samples was performed using 1% acetic acid in water as solvent A and acetonitrile as solvent B. The flow rate was 0.45ml/min. The initial solvent composition for 0.45min was 90% A and 10% B. Subsequently, the compounds were eluted with a gradient from 0.45min to 2min resulting in 82.5% A and 17.5% B. After that, the proportion of B was increased to 70% for column wash and the initial conditions were stabilized for 0.5min. The total run time was 5.3min. Analysis was carried out by using electrospray ionization in the positive ion mode. The MS/MS data were collected in the multiple reaction monitoring mode, and syringetin-3-glucoside was used as an internal standard (m/z 509.4/347.0).

Sugars and acids

Triplicate extractions of sugars and acids of each sample were performed without fractionation, as described earlier (Tiitinen et al., 2006). Powdered sample (2–4g) was weighed accurately and mixed with H2O to a final volume of 50ml. The sample was sonicated for 30min and centrifuged at 4360 × g for 10min. The supernatant was separated and diluted with H2O to 2:5 and the internal standards (0.25ml of sorbitol (0.5g/100ml) and 0.25ml of tartaric acid (0.5g/100ml)) were added. An aliquot of 300μl of the sample was evaporated to dryness under nitrogen stream at 40°C and kept in a desiccator over P2O5 overnight.

The sugars and acids were analyzed as trimethylsilyl- derivatives of the dried juice samples by gas chromatography (Zheng et al., 2009). Briefly, the analysis was carried out with a Hewlett-Packard 5890 Series II GC (Hewlett-Packard Co., Palo Alto, CA, USA) equipped with a Hewlett-Packard 7673 autosampler, Supelco Simplicity-1 fused silica column and a flame ionization detector. A sample of 1μl was injected into the split/splitless injector. The average flow rate of the carrier gas helium was 1.4ml/min. The temperature of the injector was 210°C and that of the detector 290°C.

Study meal composition

Sea buckthorn (Hippophaë rhamnoides L. ssp. turkestanica) berries grown in China were used as dried whole berries. The crushed whole berries were extracted by supercritical CO2 by a commercial ISO 9001 and ISO 2004 validated procedure of Aromtech Ltd (Tornio, Finland) under controlled good manufacturing practice. Seeds were broken with cutting mill to enable the removal of seed oil. The EtOH extraction of the SF-CO2-extraction residue was carried out with 70% EtOH in water, by a similar batch procedure as previously used by Sandell et al. (2009). EtOH and the residue were mixed and continuously stirred by a magnetic stirrer for 30min for four times. The EtOH solution of each batch was filtered (Whatman 1, Whatman International Ltd, Maidstone, UK) and evaporated with a vacuum rotary evaporator (Heidolph VV2000, Heidolph Elektro GmbH & Co. KG, Keilheim, Germany). The residue of the EtOH extraction was air dried. The process flow of the different fractions in illustrated in Figure 1.

Figure 1.
Figure 1 - Unfortunately we are unable to provide accessible alternative text for this. If you require assistance to access this image, please contact help@nature.com or the author

Composition of the berry meals (B1, B2 and B3) and the extracts (E1 and E2) removed in the processing steps of the fractions B2 and B3.

Full figure and legend (73K)

Yoghurt (lactose-free and fat-free non-flavored natural yoghurt, Valio Ltd, Helsinki, Finland, 200g) was used as a base of the meal. Glucose (50g) was served blended to the yoghurt with dried and ground berries or berry extraction residues (meal B1: 40g of dried and crushed sea buckthorn berries, meal B2: 32.4g of berry residue extracted by SF-CO2 and meal B3: 18g of EtOH-extracted CO2-extraction residue), or without them (meal A, control). The amounts of fractions correspond to 200g of fresh sea buckthorn berries. Water (0.2l) was served with the meal.

The total amount of flavonol glycosides, as well as the main flavonols in the products are presented in Table 1, and the amounts of sugars, acids and inositols in Table 2. SF-CO2-extracted residue of sea buckthorn had the highest amount of flavonol glycosides and inositols and acids. Sea buckthorn berry residue had the lowest content of each of the components and also the lowest sugar–acid ratio. SF-CO2-extraction removed the lipophilic compounds of the seeds, skin and pulp, namely triacylglycerols, tocopherols, tocotrienols, carotenoids and part of glycerophospholipids. We have previously characterized the composition of the lipophilic part of the sea buckthorn seeds and pulp (Kallio et al., 2002).



Postprandial study design

To investigate the effect of sea buckthorn and its extraction residues on postprandial hyperglycemia and postprandial insulin response in humans, a clinical postprandial trial was designed. Study subjects acted as their own controls and consumed three different berry meals and a placebo on distinct study days. Before the study, the subjects were informed about the investigation and their right to discontinue the study at any time without explanation, and they had an opportunity to ask questions. All subjects provided a written consent. The protocol was evaluated and approved by the ethics committee of the Hospital District of Southwestern Finland.

The subjects ate a standardized evening snack with low flavonoid content (wheat bread, cucumber, water and a banana) the night before the study visits. The study subjects were asked about their adherence to the instructions on each study morning. After a 10-h fast, the subjects consumed either the berry meal or the control meal, in a randomized order.

Before the meal, a basal sample of blood was collected, and after consumption of the breakfast, blood samples were collected at 30, 60, 90, 120, 180, 270 and 360min. The subjects fasted during the 6-h study day.

Clinical analyses

Blood samples were drawn from the forearms of each subject into glucose tubes (VF-053SFX, for glucose analysis, Oriola, Helsinki, Finland), and serum tubes containing coagulant activator (VF-054 SPW, Oriola). Plasma glucose and serum insulin were analyzed with standard biochemical analyses at Turku University Hospital Laboratory. Serum glucose was determined by a photometric method and insulin by an electro-chemiluminescence immunoassay (TYKSLAB, Turku, Finland). All analytes were measured from a single tube with Roche Modular PPEE analyzer, with commercial reagents provided by Roche Diagnostics GmbH (Mannheim, Germany). TNF-α was analyzed from plasma collected into EDTA-tubes with Millipore's singleplex kit (VF-054 SPW, Oriola) according to the manufacturer's instructions, using Bio-Rad Bio-Plex 200 System (Bio-Rad, Hercules, Canada). Analyses were performed in Laboratory for Population Research, National Public Health Institute, Turku, Finland. TNF-α analyses were performed only for the baseline and for the 60-min samples drawn after meals B1 and A.

Statistical analyses

Insulin responses were expressed as the incremental area under the curve (iAUC) with the fasting concentration as baseline. Also, the peak values of insulin and glucose at 30min, and the values of insulin at 120min, and TNF-α at 60min were used for statistical analyses. General linear model repeated measurements variance analysis was used for all results as they were normally distributed. Statistical significance was indicated by P<0.05. Statistical analyses were performed with SPSS 14.0 (SPSS Finland Oy, Espoo, Finland).

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Results

The insulin peak concentrations were lower after the whole berry meal (meal B1) than after the control meal (meal A) (Δconcentration of 30-min peak value −22mU/l, P=0.039). Differences between meals B1 and A were even greater when the 120-min value was also considered, because the berries suppressed the subsequent drop in insulin values after the peak concentration (Δconcentration of 30-min peak value—120-min value −30.4mU/l, P=0.036) (Figure 2). The phenomenon could also be observed as a trend of lower iAUC values (ΔiAUC30min −297.2, P=0.062, ΔiAUC120min −363.1, P=0.507). Similarly, the oil-free berry meal (meal B2) had a positive effect on insulin metabolism (Δconcentration of 30-min peak value—120-min value −25.9mU/l, P=0.037). In contrast, the berry residue (meal B3) had no effect on the peak insulin concentration, and the iAUC of 120m was even slightly higher than of the control meal. The results are available in Table 3 and Figure 2. Furthermore, the difference in the curve shape of the insulin concentration after the consumption of meal A and meal B3 compared with the concentration after consumption of meal B1 and meal B2 is clearly visible (Figure 2) because the peak concentration is lower and the subsequent drop in insulin concentration is slower.

Figure 2.
Figure 2 - Unfortunately we are unable to provide accessible alternative text for this. If you require assistance to access this image, please contact help@nature.com or the author

The postprandial insulinemia as serum insulin values of study subjects after the control meal (A) and sea buckthorn meals (B1, B2 and B3).

Full figure and legend (47K)


Removal of the lipophilic compounds (E1 in Figure 1) did not affect the advantageous effects of the berries on insulin metabolism (P=0.608) but the removal of the fraction soluble in 70% EtOH (E2 in Figure 1) eliminated the observed effects. The effective compounds seem thus to be in the EtOH soluble fraction rather than in the lipophilic fractions.

Meal B1 had a balancing effect on postprandial hyperglycemia when compared with the control meal (meal A) (Δconcentration of 30-min peak value—120-min value −1.0mmol/l, P=0.042). Meal B1 modified the postprandial plasma glucose levels in a similar manner as was observed in the postprandial insulin levels. Plasma glucose peak values at 30min after meal B1 meal remained lower and further decreased less below the fasting concentrations 120min after meal B1 than after meal A, thereby averting the drop in blood glucose levels following peak glucose values. In contrast, meals B2 and B3 had no impact on postprandial hyperglycemia. Figure 3 illustrates the postprandial glycemia of study subjects after the control meal (meal A) and whole sea buckthorn meals (meal B1).

Figure 3.
Figure 3 - Unfortunately we are unable to provide accessible alternative text for this. If you require assistance to access this image, please contact help@nature.com or the author

The postprandial glycemia as plasma glucose values of study subjects after the control meal (A) and whole sea buckthorn meal (B1).

Full figure and legend (44K)

Moreover, there was a statistically significant difference between meals B1 and B3 (P=0.018) indicating that the insoluble berry fiber was not the cause of the observed effects. In contrast, there was no statistically significant difference (P=0.808) between whole berry meal (B1) and oil-free berry meal (B2) indicating that lipophilic compounds had only minor importance in inhibiting postprandial hyperglycemia.

Plasma TNF-α concentrations were analyzed before and 60min after the consumption of the control meal and meal B1. Before the consumption of the meals, the baseline TNF-α concentrations varied slightly, although there were no statistical differences. After meal A, the TNF-α concentration increased slightly (Δconcentration 0.2pg/ml), whereas after meal B1, the TNF-α concentration decreased (Δconcentration −0.6pg/ml). There were, however, considerable differences between the study subjects, and observed trends remained statistically insignificant (P=0.175).

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Discussion

Elevated glucose concentrations are thought to alter metabolism, create oxidative stress and induce apoptosis in many cell types (Evans et al., 2002). Chronic elevations in glucose have a key role in the development of not only the late complications of type 2 diabetes, but also in the insulin resistance and impaired insulin secretion seen in type 2 diabetes (Evans et al., 2003). Oscillating glucose has been shown to be an even more important risk factor of metabolic diseases and their further complications than the mean glucose (Ceriello et al., 2008). The rapid absorption of glucose challenges the homeostasis mechanisms of the body, complicating in effect the transition from the postprandial state to the post-absorptive state (Wolever et al., 1995). High-GI diets alter nutrient partitioning in favor of fat deposition, shunting metabolic fuels from oxidation in muscle to storage in fat (Brand-Miller et al., 2002).

Effect of carbohydrate composition on postprandial hyperglycemia and postprandial insulin response is commonly accepted (Ludwig, 2000; Kallio et al., 2008). Yet, although there is some emerging evidence of the ability of other than macronutrient components of food to alter postprandial sugar metabolism, such evidence is to date scarce and mainly produced by in vitro and animal trials. In a recent study, the inclusion of cinnamon in a rice pudding meal lowered the postprandial glucose response (Hlebowicz et al., 2007). Moreover, blueberries were reported to have potential in the attenuation of insulin resistance in an animal trial (DeFuria et al., 2009). Some exotic fruits or their phenolic extracts have also shown positive effects on sugar metabolism in animal models, as Zunino (2009) recently reviewed. However, before this study, no previous investigations were available concerning the potential of northern berries to alter postprandial metabolism. In this study, sea buckthorn berries had a stabilizing effect on postprandial hyperglycemia. Furthermore, these berries suppressed the peak postprandial insulin response after a high-glucose meal. Thus, sea buckthorn berries consumed as part of a high-glucose meal containing simple carbohydrates seemed to be able to modify the postprandial glucose metabolism toward a metabolic response typical after ingestion of complex carbohydrates. According to accumulating evidence, diets designed to lower the insulin response to ingested carbohydrate may improve access to stored metabolic fuels, decrease hunger and promote weight loss (Brand-Miller et al., 2002).

This study indicates that the diluted EtOH soluble compounds of sea buckthorn form the most active fraction in improving postprandial glycemic control. Previously, Hanamura et al. (2006) have shown that crude aeriola polyphenol fraction had a preventive effect on postprandial hyperglycemia. However, also controversial results have been reported. Gruendel et al. (2007) found out that carob pulp preparation rich in polyphenols deteriorated postprandial glycemic control. Evidently, food matrix and other components present can modulate the effect of polyphenols on glycemic response.

Although diluted EtOH soluble fraction (meal B2) had the major contribution, the sea buckthorn oil slightly enhanced the positive effects on glycemia. Synergism might be due to the previously established ability of the sea buckthorn lipids to enhance the absorption of the sea buckthorn flavonoids (Suomela et al., 2006). When consumed in modest quantities that can easily be obtained from berries and berry products, insoluble berry fiber did not seem to affect postprandial glucose metabolism.

A high postprandial insulin response may result in metabolic processes similar to those seen after a high-GI meal (Kallio et al., 2008). In addition, it may influence the adipocyte function and increase c-reactive protein concentrations in plasma (McCarty, 2005). Sea buckthorn has been shown to reduce plasma c-reactive protein (Larmo et al., 2007) and a mixed berry diet enhanced liver function in our recent clinical trial (Lehtonen et al., 2010b). Meals that evoke high glycemic or insulinemic responses induce subsequent mild, late postprandial hypoglycemia and -insulinemia (Brand-Miller et al., 2002), resulting in a surge in adrenaline output (Ludwig et al., 1999) and inflammation mediator secretion (McCarty, 2005). This study suggests that also other food components than energy nutrients are able to modify postprandial metabolism.

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Conflict of interest

The authors declare no conflict of interest.

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Acknowledgements

The study was performed as part of LUMABS-project funded by ABS graduate school, Finnish Food and Drink Industries’ Federation (ETL), Turku University Foundation and Raisio Oyj Reseach Foundation. We thank Katja Tanner, Hannele Jokioinen, Jie Zheng, Salla Palmu and Eveliina Upmeier for skilful technical assistance, the group of Mika Venojärvi from Turku University of Applied Sciences for carrying out the TNF-α analyses, and Aromtech Ltd for providing the SC-CO2-extraction. This study was supported by ABS graduate school, Finnish Food and Drink Industries’ Federation (ETL), Turku University Foundation and Raisio Oyj Reseach Foundation.

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