Slowing starch digestibility in foods
de Bruijn, Hanny Margriet
IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below.
Document Version
Publisher's PDF, also known as Version of record
Publication date: 2018
Link to publication in University of Groningen/UMCG research database
Citation for published version (APA):
de Bruijn, H. M. (2018). Slowing starch digestibility in foods: Formulation, substantiation and metabolic effects related to health. Rijksuniversiteit Groningen.
Copyright
Other than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons).
Take-down policy
If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.
Downloaded from the University of Groningen/UMCG research database (Pure): http://www.rug.nl/research/portal. For technical reasons the number of authors shown on this cover page is limited to 10 maximum.
Slowing starch digestibility in foods
Formulation, substantiation and metabolic effects related
to health
Hanny Boers
ISBN: 978-94-034-1150-7 (Printed book) ISBN: 978-94-034-1149-1 (Ebook)
Cover: Ilse Modder, www.ilsemodder.nl (impression of human gastrointestinal tract and polarized microscope image of starch grains).
Lay-out: Hanny Boers
Printing: Gildeprint, Enschede
The publication of this thesis was financially supported by Unilever R&D Vlaardingen, The Netherlands.
© 2018, H.M. Boers, The Netherlands
All rights reserved. No parts of this thesis may be reproduced or transmitted in any form, by any means, without prior written permission from the author.
Slowing starch digestibility in foods
Formulation, substantiation and metabolic effects related to health
Proefschrift
ter verkrijging van de graad van doctor aan de Rijksuniversiteit Groningen
op gezag van de
rector magnificus prof. dr. E. Sterken en volgens besluit van het College voor Promoties.
De openbare verdediging zal plaatsvinden op woensdag 5 december 2018 om 12.45 uur
door
Hanny Margriet de Bruijn
geboren op 6 januari 1966 te 's-Gravenhage
Copromotors
Dr. M.G. Priebe Dr. D.J. Mela
Beoordelingscommissie
Prof. dr. A.J.W. Scheurink Prof. dr. F. Kuipers Prof. dr. A.F.H. Pfeiffer
Chapter 1 General Introduction 9
Chapter 2 A systematic review of the influence of rice characteristics and 29 processing methods on post-prandial glycaemic and insulinaemic responses.
Br J Nutr 2015; 114(7): 1035-1045
Chapter 3 Effect of hydrocolloids on lowering blood glucose. 61 Gums and stabilisers for the Food industry 18 – hydrocolloid
functionality for affordable and sustainable global food solutions 2016; 191-208. Glyndwr University Wrexham, UK
Chapter 4 Efficacy of different fibres and flour mixes in South-Asian 77 flatbreads for reducing post-prandial glucose responses in healthy adults.
Eur J Nutr 2017; 56(6): 2049-2060
Chapter 5 Efficacy of fibre additions to flatbread flour mixes for reducing 111 post-meal glucose and insulin responses in healthy Indian subjects
Br J Nutr 2017; 117(3): 386-394
Chapter 6 Effect of fibre additions to flatbread flour mixes on glucose kinetics: 139 A randomised controlled trial
Br J Nutr 2017; 118(10): 777-787
Chapter 7 The effect of the rate of glucose appearance on 165 post-prandial glucose and insulin responses: a systematic review and meta-analysis of stable isotope studies
Submitted for publication
Chapter 8 Fiber mix addition to wheat-based flatbreads delays the appearance 195 of exogenous glucose and its downstream metabolites in plasma of healthy male subjects
Manuscript in preparation
Dankwoord 249
About the author 253
List of publications 255
Abbreviations 257
CHAPTER 1
1. General Introduction
Worldwide, the number of people with diabetes mellitus type 2 (T2DM) is rapidly increasing, especially in South-East Asia (1). T2DM is the most common form of diabetes and characterised by either high fasting or high postprandial blood glucose concentrations or a combination of both (hyperglycaemia) (2). Pre-diabetes is the state before diabetes defined by a high blood glucose levels not meeting the conventional criteria for diabetes, but yet higher than normal (2). Prediabetes is classified into two subtypes: high fasting plasma glucose [Impaired Fasting Glucose] and/or by high 2 hour plasma glucose during an oral glucose tolerance test [Impaired Glucose Tolerance] (2). Lifestyle-related factors such as diet and physical activity can contribute to prevention of T2DM. (3). Repeated exposures to high postprandial glucose (PPG) responses are implicated in the development of pre-diabetes and T2DM (4).
Reducing PPG by slowing the rates of carbohydrate digestion seems to reduce the progression from pre-diabetes to T2DM (5-7). This is indicated by studies with the drug acarbose (5, 8) and from meta-analyses and reviews of studies with low glycaemic index (GI)/glycaemic load diets (6, 7, 9, 10).
The most effective way to turn starchy foods into more-slowly digestible versions and the post-absorptive effects of this are still not well understood. The present research was undertaken with four aims:
1. To investigate how starchy foods can be made more slowly digestible 2. To predict the rate of digestion (in vitro methods)
3. To study the impact on the PPG and associated insulin (PPI) responses in humans
4. To understand the associated glucose fluxes and metabolic mechanisms and their implications for health
In this introduction chapter some basic terminology in the area of starch digestion, absorption and glucose metabolism and regulation will be discussed. The technology of in vitro digestion and dual stable isotope technique used in in vivo studies will also be addressed. In addition some aspects of pathophysiology will be discussed.
1.1. Carbohydrates: basic terminology, classifications and chemistry and their influence on digestion
Dietary carbohydrates are a diverse group of substances with a wide range of chemical, physical and physiological characteristics (11). Dietary carbohydrates should be classified according to their chemical form, i.e. the individual monomers, degree of polymerization (DP) and type of linkage (alpha or beta), as recommended at the 1997 FAO/WHO Expert Consultation (12). This divides carbohydrates in three main groups: sugars (DP 1-2; mono- and
state, association with other molecules such as protein, lipid and divalent cations and aggregation into complex structures in cell walls are important for the availability of starch. The solubility, water holding capacity, viscosity and gel formation, binding and adsorptive capacity and fermentability are important determinants of the action of dietary fibres under gastrointestinal conditions (13, 14).
Neither chemical nor physical descriptions of carbohydrates can fully predict their range of physiological effects and health implications. The most important physiological division within carbohydrates is whether they are bio-available (can be digested by human intestinal enzymes, so-called glycaemic carbohydrates) versus bio-unavailable carbs (such as dietary fibre and resistant starch) (11). Starch consists of amylopectin, comprised of glucose chains with frequent branching, and amylose which is characterized by very few branches (15). Resistant starch is the sum of starch and products of starch digestion (such as maltose, maltotriose and alpha-limit dextrins) that have not been digested in the small bowel (16). Resistant starch (RS) can be divided into different types reflecting the source of resistance to digestion: RS1 is due to physical barriers to digestion, RS2 to ungelatinized starch granules, RS3 to retrogradation, RS4 is chemically-modified starch and RS5 is lipid-complexed starch (17). All dietary fibre definitions (including CODEX) identify dietary fibre as carbohydrate polymers and oligomers materials that escape digestion in the small intestine and pass into the large intestine, where they are slightly or nearly completely fermented (18). There is some evidence that legume flour can lower the PPG due to its higher content of resistant starch (19) and high concentration of slowly digestible starch (20).
The main factors which determine starch digestibility are the intrinsic starch characteristics such as the amylose/amylopectin ratio, intactness of the grain and the botanical source (21). In addition, processing factors also play an important role in starch digestibility (22). Processing factors such as cooking, baking and cooling determine the blood glucose response via intermediate processes such as gelatinization and retrogradation. Gelatinization is the collapse (disruption) of molecular order (breaking of H-bonds) within the starch granule manifested in irreversible changes in properties such as granular swelling, native crystallite melting, loss of birefringence and starch solubilisation during hydrothermal treatment (23). On the other hand, retrogradation is the recrystallization of the amorphous phases created by gelatinization, into double helical crystalline structures (24) when amylose is available (25).
Dietary fibres can also have an impact on digestion, depending on the nature of the fibre. Non-viscous fibres do not have an effect on digestion. For example wheat bran does not reduce glycaemic response or digestibility in bread (26). Especially viscous soluble fibres can reduce starch digestion and absorption in the intestine due to viscosity formation under gastrointestinal conditions (27).
1.2. Starch digestion, absorption and fermentation
Chewing and digestion of starch in the mouth
The role of the mouth in digestion is to grind food into a more homogenous, softer mass (bolus) that can be swallowed and pass through the oesophagus to the stomach (28). Lingual alpha-amylase is secreted during oral digestion, and may even survive gastric conditions to exert its effect in the stomach and small intestine (29). However, it is uncertain whether this salivary amylase has any significant effects on starch digestion, because the digestion process is dominated by the action of pancreatin (30). The estimation is that some 15% of total starch in a meal is digested by lingual alpha-amylase (5% in the mouth and 10% in the small intestine) (31). Nevertheless, a study by Ranawana (32) showed that the GI of starch-rich products (rice) is increased by the degree of mastication (32).
Gastric emptying (GE)
An important role of the stomach is to control the rate of nutrient delivery to the body through the regulation of GE (33). GE is an important determinant of the rate of entry of glucose into the systemic circulation (34) and therefore the PPG response (35), given the rapidity and completeness of absorption of glucose and other monosaccharides in the small intestine (36). The rate of GE has been shown to account for ~35% of the variance in PPG levels after glucose loads and following intake of solid carbohydrate-containing meals in healthy individuals (35) and in patients with T2DM (37).
Gastric emptying is regulated by both gastric factors (characteristics of the ingesta) and to a greater extent by duodenal factors (feedback effects) (38). Gastric factors include food volume, caloric content (39), acidity, fluid viscosity, and food physical properties such as texture and density (40). For example GE is controlled in such a way that contents are delivered to the duodenum at about 2.3 kcal/min (39) though a more recent article gives a wider range of 2-4 kcal/min (38). Duodenal receptors which regulate GE respond to distension, the presence of acid, carbohydrate, fat and protein digestion products, and osmolarity differences from that of plasma (41). Prevailing blood glucose levels also regulate GE, such that acute elevations of blood glucose levels slow GE and GE is accelerated during hypoglycaemia (42). Viscous fibres (43) or
gel-under “Glucose metabolism and regulation”, in a subparagraph on hormones involved.
Intestinal digestion of starch
The major hydrolysis products from the intraluminal phase of starch digestion are maltose, maltotriose and other fragments containing alpha-1,6 bonds (alpha-limit dextrins) (31). These sugars and short oligosaccharides are hydrolyzed to glucose by two dual-enzyme protein complexes, maltase-glucoamylase (MGAM) and sucrase-isomaltase (SI), in the brush border of the small intestine. All four enzymes represented in the 2 complexes are exohydrolytic, thus hydrolyze alpha-1,4 and alpha-1,6 linkages from non-reducing ends of glucose oligomers and polymers (45), the difference being their degree of specificity for particular glycosydic linkages at the nonreducing termini of alpha-glucans (46). SI displays more hydrolytic activity on branched alpha-1,6 linkages than MGAM. MGAM substrate specificity somewhat overlaps with that of SI (47).
Glucose absorption across intestinal wall
The glucose resulting from MGAM and SI hydrolysis is transported across the intestinal mucosa. Glucose absorption across the intestinal brush-border membrane is predominantly mediated by SGLT1, a membrane protein that couples two molecules of Na+ together with one molecule of glucose, although
glucose transporter type 2 (GLUT2) may also play a role especially in higher luminal glucose concentrations (48).
Carbohydrate fermentation in the colon
The overall capacity of the human body to digest and absorb bio-available carbohydrates is very high (at least up to 300g starch per meal) (49). In healthy individuals, significant amounts of material arrive in the colon only when the carbohydrates are indigestible or partly indigestible (as is the case with e.g. resistant starch, sugar alcohols and fructo-oligosaccharides). The indigestible carbohydrates will be fermented by the colonic microbiota into short-chain fatty acids (SCFAs) and gases (hydrogen (H2), carbon dioxide and methane) (31).
H2 is absorbed and mostly excreted in expired air. The degree of this so-called
colonic spillover can be measured by H2 in breath (50) which is used as a
qualitative indicator of carbohydrate arrival and fermentation in the colon. The fermentation of indigestible carbohydrates can be accompanied by borborygmi and flatulence at low doses and at higher doses by painful symptoms like bloating, cramps and abdominal pain (51).
1.3. In vitro starch digestion models
There are a number of in vitro protocols varying in complexity that model different aspects of carbohydrate digestion (52, 53). One of the purposes of using in vitro models is for screening carbohydrates (e.g. legume flours) and/or dietary fibres for their potential digestibility and glycaemic effects when incorporated in a food format (pre-clinical testing). In addition, these models can be used for innovation for research and development and for getting more mechanistic insights. However, these models cannot cover all phases of starch digestion described in section 1.2 and cannot replace human clinical testing. Furthermore, for predicting glycaemic responses, a major limitation is absence of any post-absorptive components (e.g. reflecting insulin release and glucose disposal). Separate models are also available for fermentation (54).
Static versus dynamic models
The intestinal digestion models can roughly be divided into static (e.g. Englyst model) (53) and dynamic models. The Englyst method is based on an in vitro enzymatic method to determine the response of food carbohydrates to enzymatic digestion (53). Starch that is hydrolyzed within 20 min is designated rapidly digestible starch (RDS), and that which releases glucose within 20-120 min is slowly digestible starch (SDS), while starch that is not hydrolyzed after 120 min is identified as RS (53). The in vitro estimates of starch digestibility by the Englyst method has been shown to be qualitatively predictive of post-prandial blood glucose concentrations for many foods (55).
An example of a dynamic model, which includes both chemical and physical breakdown in the stomach as well as the intestine, is the TIM-Carbo model as described by Bellman et al (52). Dynamic mechanical models of digestion have
an advantage over static models, as they allow for examination of both physical and chemical breakdown of food products during the different digestion steps. However, these models are more complex in design and fabrication and, as is the case for all models, always require validation with human clinical data (56).
Enzymes involved
The standard Englyst method uses the combination of porcine pancreatin and fungal glucoamylase (53) and these were also used for our in vitro flat bread digestion assay (57). However, fungal glucoamylase directly converts starches and alpha-amylase hydrolysates to glucose (58). In humans in vivo as noted previously, this requires the action of mucosal alpha-glucosidase together with alpha-amylase.
fluxes are discussed, because they eventually make the distinction possible between the origins of the glucose (e.g. glucose from food versus from the liver) and ultimately determine the PPG response.
Glucose as fuel
Glucose is the key energy substrate for life. All human cells can metabolize glucose through glycolysis and tricarboxylic acid cycle coupled with mitochondrial respiratory chain to synthesize adenosine triphosphate (ATP) (59). It is the preferred fuel for the brain and the nervous system, which can also survive on ketones (60). The rate of glucose utilization by the brain is estimated to be 117-142 g/day (61)
Hormones involved
Insulin and glucagon are two opposing hormones central in the regulation of glucose metabolism. By modulating the relative concentrations of glucagon and insulin the pancreas is able to respond homeostatically to high and low blood glucose levels (62). Insulin is secreted from beta-cells of the pancreas and is stimulated by glucose, amino acids (especially branched-chain) and gastrointestinal hormones (such as the incretin hormones (next paragraph), and secretin, gastrin and cholecystokinin) (62). Insulin facilitates transport of glucose from the bloodstream into peripheral tissues such as skeletal muscle and adipose tissue (63). It regulates the translocation of intracellular vesicles containing the GLUT4 glucose transporters to the plasma membrane by binding to the insulin receptors on skeletal muscle cells and adipocytes. After fusion the GLUT4 transporters are able to transport glucose into the cells (64). In addition, insulin encourages biosynthesis of proteins, inhibits the production of glucose by the liver and lipolysis and free fatty acid efflux from adipose tissue (62). The insulin response to an oral glucose load is three- to fourfold greater than observed after an “isoglycaemic” intravenous infusion of glucose (65). This so-called incretin effect led to the discovery of hormones, secreted from the gastrointestinal tract in response to nutrients that stimulate insulin secretion in a glucose-dependent manner (66). The two known incretin hormones are glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-peptide-1) and together they account for up to 60% of the postprandial insulin response in healthy humans (67). They are an important regulating factor in glucose homeostasis (68). GIP secretion from K cells in the upper small intestine is enhanced in response to ingestion of meals or glucose (69). GLP-1 is released by the L-cells in the ileum and secretion is potently stimulated by
glucose, fatty acids and essential amino acids and other endocrine hormones, as well as neurotransmitters (70). The length of the small intestine exposed to carbohydrate is an important determinant of GLP-1 release (71). Poorly absorbed carbohydrates (e.g. tagatose) which probably expose a greater length of gut to nutrients, result in delayed GLP-1 secretion but not in delayed GIP release (72). GLP-1 for example can delay GE which acts to sustain the release of nutrients over time into and from the small intestine (73). In addition, GLP-1 and GIP together, inhibit beta-cell apoptosis and promote beta-cell proliferation, thereby expanding pancreatic beta-cell mass, while GIP enhances postprandial glucagon response under certain circumstances and GLP-1 suppresses it (74). GIP has no effect on glucagon responses during hyperglycaemia, while strongly potentiating insulin secretion. In contrast, GIP increases glucagon levels during fasting and hypoglycaemia, when it has little or no effect on insulin secretion (75). In adipose tissues, GIP but not GLP-1 facilitates fat deposition (74). GLP-1 and GIP exert their effects by binding to their specific receptors, the GIP receptor (GIPR) (76) and the GLP-1 receptor (GLP-1R) (77). Secreted GIP and GLP-1 are rapidly degraded by Dipeptidyl peptidase-4, which diminishes the insulinotrophic effects of these hormones (78).
Glucagon is secreted from alpha-cells in the pancreas in response to hypoglycaemia (79) and its secretion also rises following increases in circulating levels of amino acids and fatty acids and response to adrenergic stimulation and to some regulatory peptides (80). Glucagon mobilizes stored nutrients, increases glycogenolysis and gluconeogenesis, and promotes lipolysis (62). Another glucoregulatory hormone is amylin, which is produced by the beta-cells and co-secreted with insulin (81). Amylin improves postprandial blood glucose levels by suppressing GE and glucagon secretion and a synthetic analogue of human amylin is used as an anti-diabetic drug (82). Amylin was not taken into account in our research, because there was not a good analytical method available.
Organs involved
The amount of glucose in plasma is tightly regulated, because of harmful effects of low or high glucose levels. Many organs are involved such as the liver, muscles, adipose tissue and intestine. The liver has a central role in the regulation of systemic glucose and lipid fluxes during feeding and fasting (83). In short-term starvation glucose is derived from 1) glycogenolysis, the release of glucose from stored glycogen in the liver (84) and from 2) gluconeogenesis (85), i.e. the de novo formation of glucose from common metabolites in the body such as amino acids, glycerol, lactate, pyruvate and intermediate metabolites of the citric acid cycle (84).
generates an abundance of ATP and reducing equivalents that sustain the conversion of pyruvate and other intermediates (e.g. gluconeogenic amino acids) into glucose (83).
In the fed state there is an abundance of different nutrients in the portal vein, together with high levels of insulin, which promote hepatic glycogen synthesis and under specific circumstances de novo lipogenesis (DNL), while fatty acid oxidation and endogenous glucose production are suppressed (86). Glycogen synthesis and glycogenolysis can occur simultaneously in the liver, so-called ‘glycogen cycling’ (87). Skeletal muscle is the largest site for insulin- and exercise-stimulated glucose disposal and utilization (88). The intestine can contribute to the control of glucose homeostasis via its high glucose utilization capacity (89). Recently a novel function of intestinal glucose metabolism (gluconeogenesis) has been described and suggests the intestine contributes to about 20-25% of total endogenous glucose production (90).
Measuring postprandial glucose and insulin
PPG response can be measured in venous and capillary blood. Venous blood gives a lower PPG response than capillary blood (factor ~0.67) (91, 92), because the tissue will consume glucose and the glucose concentration in the peripheral vein will be lower than in the artery (93). Capillary blood is a mixture of arterial and venous blood. Another measure of postprandial glucose response is the GI, which is the ratio of the glycaemic response (capillary blood, +iAUC for 2 hours) of 50g of available carbohydrates of the test food and glycaemic response of reference food (glucose or bread) (93). Insulin is normally measured in serum and another measure is the insulinaemic index, which can be determined in the same way as the glycaemic index (94). Glucose fluxes: why are they important and how can they be measured
In many studies PPG response to different foods has been measured and where it is relatively low, it has been assumed that this is because the process of digesting and releasing the glucose from that food is slow (95). However, the PPG response also reflect rates of glucose disposal and endogenous production. Only the use of stable isotopes can really determine whether there is a slower digestion, as shown by a delayed influx of 13C labelled glucose units
in the food (96). In practice, a dual stable isotope technique is necessary to distinguish between glucose originating from the meal and the glucose from the liver.
The dual tracer method utilizes two distinct glucose tracers that can be differentiated analytically, e,g, [U-13C] in the meal and [6,6-2H2] glucose infused
intravenously (97). Glucose fluxes are then calculated using Steele’s non-steady-state one compartment model (98). The rate of appearance of total glucose (RaT) is calculated from isotopic dilution of the infused glucose tracer. The rate of appearance of oral or exogenous glucose (RaE) is calculated from the rate of appearance of ingested glucose tracer and the glucose tracer enrichment of the meal. The endogenous glucose production (EGP) is than calculated by subtraction of RaE and the infused glucose from RaT (97). The rate of disappearance of total glucose (RdT, also called glucose disposal) is the total amount of glucose which is taken up by the tissues. The RdT can be calculated from the glucose clearance rate (GCR) and the glucose concentrations. The GCR can be calculated from the non-steady-state elimination rate of the infused tracer.
Pathophysiology
The potential pathophysiological mechanisms of actions of hyperglycaemia are an increase in 1) flux in the polyol pathway, 2) formation of advanced glycation end-products, 3) protein kinase C activation and 4) flux through hexosamine pathway leading to vasoconstriction, inflammation and thrombosis (99). It is important to know which pathways are mostly involved in the pathophysiological aspects of a high glucose load.
1.5. Study questions and outline
Carbohydrate-rich staple foods are key candidates for reducing PPG exposures. This thesis comprises information on how to delay the absorption of carbohydrates in staple foods and how this delay in absorption will cause further post-absorptive effects, as reflected by changes in various flux parameters and levels of gastrointestinal hormones.
The following specific questions were addressed:
1. How can starchy staple foods be made more slowly digestible? 2. How can the rate of digestion be predicted in an in vitro assay?
3. What is the impact of the slowly digestible staple foods on PPG and PPI in humans?
4. What are the associated glucose fluxes and metabolic mechanisms and their implications for health?
1.1 How can rice characteristics and processing methods applied to rice influence the post-prandial glycaemic and insulinaemic responses?
We performed a systematic review to elucidate which rice characteristics and processing methods influence PPG and PPI, by summarizing and evaluating the results from randomized controlled trials with diverse varieties of rice around the world. In addition, post-harvest processing (such as parboiling) and consumer processing were also taken into account (Chapter 2).
1.2 How can food hydrocolloids influence post-prandial blood glucose response?
In a narrative review we explained how food hydrocolloids are able to lower blood glucose response. One of the important characteristics of food hydrocolloids is their viscosity under gastrointestinal conditions, and we discuss which characteristics of the hydrocolloids are responsible for the level of viscosity. We also discuss mechanisms independent of viscosity by which food hydrocolloids could influence PPG (Chapter 3).
2. How well does an in vitro digestibility assay, specifically adapted for flatbreads, predict the observed in vivo results in this product format?
We developed an in vitro digestibility assay based on the method of Englyst, but modified to reflect more realistic physiological conditions (including an oral digestion step, optimization of the intestinal pH and amount of digestive enzymes). In addition, a statistical model was developed for estimating the in vitro rate of starch digestibility (k) based on the Chapman-Richards model. In a regression model variables of in vitro starch digestion were correlated with the in vivo plasma glucose response (Chapter 4)
3. What is the effect of guar gum in combination with chickpea flour incorporated in flatbreads on the PPG and PPI response?
The insights on viscous fibres and different starches were applied for slowing the rate of starch digestibility in optimized food products. In this series of human clinical trials South-Asian flatbreads were used as the optimized food products, because they are important carbohydrate-rich staple foods for a sizable population and therefore important contributors to their glycaemic load (Chapter 4).
3.1 How much do the individual viscous fibres guar gum and glucomannan alone or in combination with chickpea flour contribute to the PPG lowering effect of South-Asian flatbreads?
The effect of South-Asian flatbreads, varying in the levels and combinations of viscous fibres (guar gum and konjac mannan) with or without chickpea flour were initially examined in healthy Caucasian subjects in a balanced incomplete block design. We assessed the effect on PPG. (Chapter 4).
3.2 What is the effect of guar gum (2-4%) in combination with chickpea flour incorporated in flatbreads on the PPG and PPI response in an Indian population?
Based on the results in an exploratory study (Chapter 4), we tested the effect of additions of specific combinations of chickpea flour with lower doses of GG added to a flatbread flour mix, for their impacts on PPG and PPI responses in a South-Asian population (Chapter 5).
4. What are the glucose fluxes and metabolic pathways associated with the PPG-lowering interventions we tested?
4.1 What is the effect of guar gum in combination with chickpea flour incorporated in flatbreads on the rate of appearance of exogenous glucose (RaE) and on the other fluxes (endogenous glucose production (EGP) and rate of disappearance of total glucose (RdT)?
In earlier studies, we saw an effect of high-fibre flatbreads on PPG and presumed that the influx of glucose was delayed due to the viscous fibres. To test this we executed a study using the dual stable isotope technique to differentiate between the different glucose fluxes. In addition, we assessed the insulin and incretin responses and examined their association with the different fluxes (Chapter 6).
4.2 What is the effect of a change in the rate of influx of glucose from the intestine on the PPG, PPI and EGP and RdT?
Up to now, it has been largely assumed a delay in digestion of carbohydrates only or mainly leads to a reduced PPG by a reduced RaE, but the actual quantitative contribution of RaE and the other glucose fluxes (EGP and RdT) was not clear. We therefore performed a systematic review and a meta-analysis of human clinical studies with 13C-labelled
carbohydrate substrates to quantify the effect of variation in the rate of uptake of exogenous glucose (RaE) on PPG and PPI responses and to estimate the effect of a change in RaE on the other flux parameters EGP and RdT (Chapter 7).
glucose, but also to a reduction in uptake of glucose into the tissues. By metabolomic analyses we assessed the different 13C- glucose metabolites
derived from samples of the earlier dual stable isotope study to identify whether the delay in glucose influx induced by a fibre mix altered specific metabolic pathways related to the disposal and metabolism of glucose in the tissues and endogenous glucose production (Chapter 8).
REFERENCES
1. Anjana RM, Deepa M, Pradeepa R, Mahanta J, Narain K, Das HK, Adhikari P, Rao PV, Saboo B, Kumar A, et al. Prevalence of diabetes and prediabetes in 15 states of India: Results from the ICMR-INDIAB population-based cross-sectional study. Lancet Diabet Endocrinol 2017. doi: 10.1016/S2213-8587(17)30174-2.
2. Organization WHO. Global report on diabetes: World Health Organization, 2016.
3. Tuomilehto J, Lindstrom J, Eriksson JG, Valle TT, Hamalainen H, Ianne-Parikka P, Keinanen-Kiukaanniemi S, Laakso M, Louheranta A, Rastas M, et al. Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. New Engl J Med 2001;344(18):1343-50.
4. Federation ID. Guideline for management of postmeal glucose, 2011.
5. Chiasson JL, Josse RG, Gomis R, Hanefeld M, Karasik A, Laakso M. Acarbose for prevention of type 2 diabetes mellitus: The STOP-NIDDM randomised trial. Lancet 2002;359(9323):2072-7. 6. Thomas D, Elliott EJ. Low glycaemic index, or low glycaemic load, diets for diabetes mellitus.
Cochrane Database of Systematic Reviews, 2009.
7. Blaak EE, Antoine JM, Benton D, Bjorck IM, Bozzetto L, Brouns F, Diamant M, Dye L, Hulshof T, Holst JJ, et al. Impact of postprandial glycaemia on health and prevention of disease. Obes Rev 2012;13(10):923-84.
8. Van De Laar FA, Lucassen PLBJ, Akkermans RP, Van De Lisdonk EH, De Grauw WJC. Alpha-glucosidase inhibitors for people with impaired glucose tolerance or impaired fasting blood glucose. Cochrane Database of Systematic Reviews 2006(4).
9. Livesey G, Taylor R, Hulshof T, Howlett J. Glycemic response and health - A systematic review and meta-analysis: Relations between dietary glycemic properties and health outcomes. Am J Clin Nutr 2008;87(1):258S-68S.
10. Brand-Miller J, McMillan-Price J, Steinbeck K, Caterson I. Dietary glycemic index: Health implications. J Am Coll Nutr 2009;28:446S-9S.
11. Cummings JH, Stephen AM. Carbohydrate terminology and classification. Eur J Clin Nutr 2007;61(SUPPL. 1):S5-S18.
12. FAO. Carbohydrates in human nutrition. Report of a Joint FAO/WHO Expert Consultation. FAO food and nutrition paper, 1998:1-140.
13. Schneeman BO. Gastrointestinal physiology and functions. Br J Nutr 2002;88(SUPPL. 2):S159-S63.
14. Schneeman BO. Dietary fiber and gastrointestinal function. Nutrition Research 1998;18(4):625-32. 15. Hizukuri S, Takeda J, Abe I, Hanashiro G. Starch: structure and functionality. London: The Royal
Society of Chemistry, 1997.
16. Champ M, Langkilde AM, Brouns F, Kettlitz B, Le Bail-Collet Y. Advances in dietary fibre characterisation. 2. Consumption, chemistry, physiology and measurement of resistant starch; implications for health and food labelling. Nutr Res Rev 2003;16(2):143-61.
17. Svihus B, Hervik AK. Digestion and metabolic fates of starch, and its relation to major nutrition-related health problems: A review. Starch/Staerke 2016;68(3-4):302-13.
18. Jones JM. CODEX-aligned dietary fiber definitions help to bridge the 'fiber gap'. Nutr J 2014;13(1). 19. Jukanti AK, Gaur PM, Gowda CLL, Chibbar RN. Nutritional quality and health benefits of chickpea
(Cicer arietinum L.): A review. Br J Nutr 2012;108(SUPPL. 1):S11-S26.
20. Nestel P, Cehun M, Chronopoulos A. Effects of long-term consumption and single meals of chickpeas on plasma glucose, insulin, and triacylglycerol concentrations. Am J Clin Nutr 2004;79(3):390-5.
21. Bjorck I, Granfeldt Y, Liljeberg H, Tovar J, Asp NG. Food properties affecting the digestion and absorption of carbohydrates. Am J Clin Nutr 1994;59(3 SUPPL.):699S-705S.
Biomacromol 2010;11(3275):3289.
24. Faraj A, Vasanthan T, Hoover R. The effect of extrusion cooking on resistant starch formation in waxy and regular barley flours. Food Res Int 2004;37(5):517-25.
25. Mitra A, Bhattacharya D, Roy S. Role of resistant starches particularly rice containing resistant starches in type 2 diabetes. J Human Ecol 2007;21(1):47-51.
26. Kristensen M, Jensen MG, Riboldi G, Petronio M, Bugel S, Toubro S, Tetens I, Astrup A. Wholegrain vs. refined wheat bread and pasta. Effect on postprandial glycemia, appetite, and subsequent ad libitum energy intake in young healthy adults. Appetite 2010;54:163-9.
27. Jenkins DJA, Kendall CWC, Axelsen M, Augustin LSA, Vuksan V. Viscous and nonviscous fibres, nonabsorbable and low glycaemic index carbohydrates, blood lipids and coronary heart disease. Curr Opin Lipidol 2000;11(1):49-56.
28. Brownlee I. The impact of dietary fibre intake on the physiology and health of the stomach and upper gastrointestinal tract. Bioactive Carbohydrates and Dietary Fibre 2014;4:155-69.
29. Butterworth PJ, Warren FJ, Ellis PR. Human alpha-amylase and starch digestion: An interesting marriage. Starch/Staerke 2011;63(7):395-405.
30. Woolnough JW, Bird AR, Monro JA, Brennan CS. The effect of a brief Salivary alpha-Amylase exposure during chewing on subsequent in vitro starch digestion curve profiles. Int J Mol Sci 2010;11(8):2780-90.
31. Lee BH, Bello-Perez LA, Lin AH-M, Kim CY, Hamaker BR. Importance of location of digestion and colonic fermentation of starch related to its quality.Cer Chem 2013;90(4):335-43.
32. Ranawana V, Leow MK-S, Henry CJK. Mastication effects on the glycaemic index: Impact on variability and practical implications.Eur J Clin Nutr 2014;68(1):137-9.
33. Delzenne N, Blundell J, Brouns F, Cunningham K, De Graaf K, Erkner A, Lluch A, Mars M, Peters HPF, Westerp-Plantenga M. Gastrointestinal targets of appetite regulation in humans. Obes Rev 2010;11:234-50.
34. Woerle HJ, Albrecht M, Linke R, Zschau S, Neumann C, Nicolaus M, Gerich J, Goeke B, Schirra J. Importance of changes in gastric emptying for postprandial plasma glucose fluxes in healthy humans. Am J Physiol - Endocrinol Metab, 2008:E103-E9.
35. Horowitz M, Edelbroek MAL, Wishart JM, Straathof JW. Relationship between oral glucose tolerance and gastric emptying in normal healthy subjects. Diabetologia 1993;36(9):857-62. 36. Camilleri M. The Stomach in Diabetes: From Villain to Ally. Clin Gastroenterol Hepatol
2009;7(3):285-7.
37. Jones KL, Horowitz M, Carney BI, Wishart JM, Guha S, Green L. Gastric emptying in early noninsulin-dependent diabetes mellitus. J Nuclear Med 1996;37(10):1643-8.
38. Kong F, Singh RP. Disintegration of solid foods in human stomach. J Food Sci 2008;73(5):R67-R80.
39. Hunt JN, Stubbs DF. The volume and energy content of meals as determinants of gastric emptying. J Physiol 1975;245(1):209-25.
40. Arora S, Ahuja A, Khar RK, Baboota S. Floating drug delivery systems: a review. AAPS Pharm Sci Tech 2005;6(3):E372-E90.
41. Versantvoort CHM, Oomen AG, Van De Kamp E, Rompelberg CJM, Sips AJAM. Applicability of an in vitro digestion model in assessing the bioaccessibility of mycotoxins from food. Food Chem Toxicol 2005;43(1):31-40.
42. Phillips LK, Deane AM, Jones KL, Rayner CK, Horowitz M. Gastric emptying and glycaemia in health and diabetes mellitus. Nat Rev Endocrinol 2015;11(2):112-28.
43. Marciani L, Gowland PA, Spiller RC, Manoj P, Moore RJ, Young P, Fillery-Travis AJ. Effect of meal viscosity and nutrients on satiety, intragastric dilution, and emptying assessed by MRI. American J Phsysiol - Gastrointest Liver Physiol 2001;280(6 43-6):G1227-G33.
44. Torsdottir I, Alpsten M, Holm G, Sandberg AS, Tolli J. A small dose of soluble alginate-fiber affects postprandial glycemia and gastric emptying in humans with diabetes. J Nutr 1991;121(6):795-9. 45. Ao Z, Quezada-Cavillo R, Nichols BL, Rose DR, Sterchi EE, Hamaker BR. The nature of raw starch
digestion. Journal of Pediatric Gastroenterol Nutr 2012;55(2):S42-S3.
46. Quezada-Calvillo R, Robayo-Torres CC, Ao Z, Hamaker BR, Quaroni A, Brayer GD, Sterchi EE, Baker SS, Nichols BL. Luminal substrate "brake" on mucosal maltase-glucoamylase activity regulates total rate of starch digestion to glucose. J Pediatr Gastroenterol Nutr 2007;45(1):32-43. 47. Sim L, Quezada-Calvillo R, Sterchi EE, Nichols BL, Rose DR. Human Intestinal Maltase-Glucoamylase: Crystal Structure of the N-Terminal Catalytic Subunit and Basis of Inhibition and Substrate Specificity. J Mol Biol 2008;375(3):782-92.
48. Chen L, Tuo B, Dong H. Regulation of intestinal glucose absorption by ion channels and transporters. Nutrients 2016;8(1).
49. Flourie B, Leblond A, Florent C, Rautureau M, Bisalli A, Rambaud JC. Starch malabsorption and breath gas excretion in healthy humans consuming low- and high-starch diets. Gastroenterol 1988;95(2):356-63.
50. Nikaki K, Gupte GL. Assessment of intestinal malabsorption. Best Practice and Research: Clin Gastroenterol 2016;30(2):225-35.
51. Marteau P, Flourie B. Tolerance to low-digestible carbohydrates: Symptomatology and methods. Br J Nutr 2001:S17-S21.
52. Bellman S, Minekus M, Zeijdner E, Verwei M, Sanders P, Basten W, Havenaar R. TIM-Carbo: a rapid, cost-efficient and reliable in vitro method for glycemic response after carbohydrate ingestion. Edtion ed. In: Van der Kamp JW, Jones J, McCleary B, Topping D, eds. Dietary fibre: New frontiers for food and health. Wageningen: Wageningen Academic publishers, The Netherlands, 2010:467-73.
53. Englyst HN, Kingman SM, Cummings JH. Classification and measurement of nutritionally important starch fractions. Eur J Clin Nutr 1992;46(SUPPL. 2):S33-S50.
54. Bender A, Breves G, Stein J, Leonhard-Marek S, Schröder B, Winckler C. Colonic fermentation as affected by antibiotics and acidic pH: Application of an in vitro model. Zeitschrift fur Gastroenterologie 2001;39(11):911-8.
55. Englyst KN, Englyst HN, Hudson GJ, Cole TJ, Cummings JH. Rapidly available glucose in foods: An in vitro measurement that reflects the glycemic response.Am J Clin Nutr 1999;69(3):448-54. 56. Bornhorst GM, Singh RP. Gastric digestion in vivo and in vitro: How the structural aspects of food
influence the digestion process. Ann Rev Food Sci Technol 2014;5(1):111-32.
57. Boers HM, MacAulay K, Murray P, Seijen ten Hoorn J, Hoogenraad A-R, Peters HPF, Vente-Spreeuwenberg MAM, Mela DJ. Efficacy of different fibres and flour mixes in South-Asian flatbreads for reducing post-prandial glucose responses in healthy adults. Eur J Nutr 2016;56(6):2049-60.
58. Lin AHM, Lee BH, Chang WJ. Small intestine mucosal alpha-glucosidase: A missing feature of in vitro starch digestibility. Food Hydrocoll 2016; 53: 163-171.
59. Campos VC, Tappy L. Physiological handling of dietary fructose-containing sugars: Implications for health.Int J Obes 2016;40(S1):S6-S11.
60. Hevor TK. Some aspects of carbohydrate metabolism in the brain. Biochimie 1994;76(2):111-20. 61. Felig P, Owen OE, Morgan AP, Cahill J. Utilization of metabolic fuels in obese subjects. Am J Clin
Nutr 1968;21(12):1429-33.
62. Kalra S, Gupta Y. The Insulin:Glucagon Ratio and the Choice of Glucose-Lowering Drugs. Diabet Ther 2016;7(1):1-9.
64. Cushman SW, Wardzala LJ. Potential mechanism of insulin action on glucose transport in the isolated rat adipose cell. Apparent translocation of intracellular transport systems to the plasma membrane. J Biol Chem 1980;255(10):4758-62.
65. Perley MJ, Kipnis DM. Plasma insulin responses to oral and intravenous glucose: studies in normal and diabetic subjects. J Clin Invest 1967;46:1954-62.
66. Ma J, Rayner CK, Jones KL, Horowitz M. Insulin secretion in healthy subjects and patients with type 2 diabetes - role of the gastrointestinal tract. Best Pract Res Clin Endocrinol Metab 2009;23:413-24.
67. Nauck MA, Homberger E, Siegel EG, Allen RC, Eaton RP, Ebert R, Creutzfeldt W. Incretin effects of increasing glucose loads in man calculated from venous insulin and c-peptide responses. J Clin Endocrinol Metab 1986;63:492-8.
68. Zhang G, Hasek LY, Lee BH, Hamaker BR. Gut feedback mechanisms and food intake: A physiological approach to slow carbohydrate bioavailability. Food Funct 2015;6(4):1072-89. 69. Vollmer K, Hoist JJ, Bailer B, Ellrlchmann M, Nauck MA, Schmidt WE, Meier JJ. Predictors of
incretin concentrations in subjects with normal, impaired, and diabetic glucose tolerance. Diabetes 2008;57(3):678-87.
70. Lim GE, Brubaker PL. Glucagon-like peptide 1 secretion by the L-cell: The view from within. Diabetes 2006;55(SUPPL. 2):S70-S7.
71. Little TJ, Doran S, Meyer JH, Smout AJPM, O'Donovan DG, Wu KL, Jones KL, Wishart J, Rayner CK, Horowitz M, et al. The release of GLP-1 and ghrelin, but not GIP and CCK, by glucose is dependent upon the length of small intestine exposed. Am J Physiol - Endocrino Metab 2006;291(3):E647-E55.
72. Wu T, Zhao BR, Bound MJ, Checklin HL, Bellon M, Little TJ, Young RL, Jones KL, Horowitz M, Rayner CK. Effects of different sweet preloads on incretin hormone secretion, gastric emptying, and postprandial glycemia in healthy humans. Am J Clin Nutr 2012;95(1):78-83.
73. Donnelly D. The structure and function of the glucagon-like peptide-1 receptor and its ligand. Br J Pharmacol 2012;166:27-41.
74. Seino Y, Fukushima M, Yabe D. GIP and GLP-1, the two incretin hormones: similarities and differences. J Diabet Invest 2010;1(1/2):8-23.
75. Christensen M, Vedtofte J, Holst JJ, Vilsboll T, Knop FK. A bifunctional glucose-dependent regulator of glucagon and insulin secretion in humans. Diabetes 2011;60:3103-9.
76. Yamada Y, Hayami T, Nakamura K, Kaisaki PJ, Someya Y, Wang CZ, Seino S, Seino Y. Human gastric inhibitory polypeptide receptor: cloning of the gene (GIPR) and cDNA. Genomics 1995;29:773-6.
77. Dillon JS, Tanizawa Y, Wheeler MB, Leng XH, Ligon RB, Rabin DU, Yoo-Warren H, Permutt MA, Boyd AE. Cloning and functional expression of the human glucagon-like peptide-1 (GLP-1) receptor. Endocrinology 1993;133:1907-10.
78. Deacon CF, Johnsen AH, Holst J, J. Degradation of glucagon-like peptide-1 by human plasma in vitro yields an N-terminally truncated peptide that is a major endogenous metabolite in vivo. J Clin Endocrinol Metab 1995;80:952-7.
79. Campbell JE, Drucker DJ. Islet alpha cells and glucagon - critical regulators of energy homeostasis. J Nat Rev Endocrinol 2015;11:329-38.
80. Gromada J, Franklin I, Wollheim CB. Alpha-cells of the endocrine pancreas: 35 years of research but the enigma remains. Endocrinol Rev 2007;28:84-116.
81. Hay DL, Chen S, Lutz TA, Parkes DG, Roth JD. Amylin: pharmacology, physiology, and clinical potential. Pharmacol Rev 2015;67:564-600.
82. Mietlicki-Baase EG. Amylin-mediated control of glycemia, energy balance, and cognition. Physiol Behav 2016;162:130-40
83. Jones JG. Hepatic glucose and lipid metabolism. Diabetologia 2016;59:1098-103.
84. Nuttall FQ, Ngo A, Gannon MC. Regulation of hepatic glucose production and the role of gluconeogenesis in humans: Is the rate of gluconeogenesis constant? Diab Metab Res Rev 2008;24(6):438-58.
85. Landau BR, Wahren R, Chandramouli V, Schumann WC, Ekberg K. Contributions of gluconeogenesis to glucose production in the fasted state. J Clin Invest 1996;98:378-85.
86. Randle PJ. Regulatory interactions between lipids and carbohydrates: The glucose fatty acid cycle after 35 years. Diab Metab Rev 1998;14(4):263-83.
87. Stingl H, Chandramouli V, Schumann WC, Brehm A, Nowotny P, Waldh+ñusl W, Landau BR, Roden M. Changes in hepatic glycogen cycling during a glucose load in healthy humans. Diabetologia 2006;49(2):360-8.
88. Mizgier ML, Casas M, Contreras-Ferrat A, Llanos P, Galgani JE. Potential role of skeletal muscle glucose metabolism on the regulation of insulin secretion. Obes Rev 2014;15(7):587-97. 89. Krebs HA. Some aspects of the regulation of fuel supply in omnivorous animals. Adv Enzym Reg
1972;10:397-420.
90. Mithieux G, Gautier-Stein A. Intestinal glucose metabolism revisited. Diabet Res Clin Pract 2014;105(3):295-301.
91. Kuwa K, Nakayama T, Hoshino T, Tominaga M. Relationships of glucose concentrations in capillary whole blood, venous whole blood and venous plasma. Clin Chim Acta 2001;307(1-2):187-92.
92. Larsson-Cohn U. Differences between capillary and venous blood glucose during oral glucose tolerance tests. Scan J Clin Lab Invest 1976;36(8):805-8.
93. Brouns F, Bjorck I, Frayn KN, Gibbs AL, Lang V, Slama G, Wolever TMS. Glycaemic index methodology. Nutr Res Rev 2005;18(1):145-71.
94. Ray KS, Singhania PR. Glycemic and insulinemic responses to carbohydrate rich whole foods. J Food Sci Technol 2014;51(2):347-52.
95. Schenk S, Davidson CJ, Zderic TW, Byerley LO, Coyle EF. Different glycemic indexes of breakfast cereals are not due to glucose entry into blood but to glucose removal by tissue. Am J Clin Nutr 2003;78(4):742-8.
96. Eelderink C, Moerdijk-Poortvliet TCW, Wang H, Schepers M, Preston T, Boer T, Vonk RJ, Schierbeek H, Priebe MG. The glycemic response does not reflect the in vivo starch digestibility of fiber-rich wheat products in healthy men. J Nutr 2012;142(2):258-63.
97. Beysen C, Hellerstein MK, Turner SM. Isotopic tracers for the measurement of metabolic flux rates. Edtion ed. Translational Research Methods for Diabetes, Obesity and Cardiometabolic Drug Development. London, UK: Springer-Verlag, 2015:71-97.
98. Steele R, Bjerknes C, Rathgeb I, Altszuler N. Glucose uptake and production during the oral glucose tolerance test. Diabetes 1968;17(7):415-21.
99. Jindal R, Gupta N, Asim Siddiqui M, Kumar Wangnoo S. Post-prandial hyperglycaemia. J Ind Acad Clin Med 2013;14(3-4):242-6.
CHAPTER 2
A systematic review of the influence of rice characteristics and
processing methods on postprandial glycaemic and
insulinaemic responses
Hanny M. Boers
Jack Seijen ten Hoorn
David J. Mela
Adapted from
ABSTRACT
Rice is an important staple food for more than half of the world’s population. Especially in Asian countries rice is a major contributor to the dietary glycaemic load (GL). Sustained consumption of higher GL diets has been implicated in the development of chronic diseases such as diabetes mellitus type 2. Given that reduction in post-prandial glycaemic and insulinaemic responses is generally seen as a beneficial dietary change, it is useful to determine the variation in the range of postprandial glucose (PPG) and insulin (PPI) responses to rice and the primary intrinsic and processing factors known to affect such responses. We therefore identified relevant original research on glycaemic response to rice through a systematic search of literature in Scopus, Medline and Scifinder databases up to July 2014.
Based on a reference value of glucose = 100, the observed glycaemic index (GI) values for rices ranged from 48 to 93, while the insulinaemic index (II) ranged from 39 to 95. There are three main factors that appear to explain most of variation in the glycaemic and insulinaemic responses to rice: 1) inherent starch characteristics (amylose-amylopectin ratio and rice cultivar), 2) post-harvest processing (particularly parboiling) and 3) consumer processing (cooking, storage and re-heating). Milling shows a clear effect when compared at identical cooking times, with brown rice always producing a lower PPG and PPI response than white rise. However, at the longer cooking times normally used for preparation of brown rice, smaller and inconsistent differences between brown and white rice are observed.
countries (1). In the South of India for example, nearly half of daily energy intake may
come from refined grains, and white polished rice constitutes > 75% of that (2). In China
brown rice is rarely consumed (3). As a result, in Asian populations white rice makes
large contributions to the dietary glycaemic load (GL), an index reflecting the acute blood glucose raising potential of foods or diets (4). Higher levels of postprandial
glycaemic exposures have been implicated in the development of chronic metabolic diseases, particularly type 2 diabetes mellitus (T2DM) and cardiovascular diseases (5).
A recent systematic review and meta-analysis has shown a clear relationship between white rice intakes and T2DM, with higher rice intake levels being more strongly associated with risk in Asian than in Western populations (6, 7).
There are many varieties of rice grain in the world, and these vary considerably in the postprandial blood glucose (PPG) response they produce (8). Results in GI studies
around the world (9) reported values ranging from 64 to 93. Moreover, the post-harvest
treatment of rice and the method of consumer preparation can also play a significant role in this. Starch is comprised of two glucose polymers, amylose and amylopectin. Amylose is a linear and relatively short polymer of glucose units linked by α(1→4) bonds. Amylopectin is a branched and longer polymer where glucose units are arranged linearly through α(1→4) with branches emerging via α(1→6) bonds occurring every 24-30 glucose units (10). It is already generally known that starches with a higher
amount of amylose are more resistant to digestion (11).
In addition to the variation in the amylose content, cooking (and cooling) processes can influence the starch digestibility via the degree of gelatinization and retrogradation of rice starch. Gelatinization is the collapse (disruption) of molecular order (breaking of H-bonds) within the starch granule, manifested in irreversible changes in properties such as granular swelling, native crystallite melting, loss of birefringence and starch solubilisation during hydrothermal treatment (12). This leads to dissociation of the
crystalline regions in starch with associated hydration and swelling of the starch granules, leading to higher starch availability to human digestive enzymes (13).
Retrogradation is the recrystallization of the amorphous phases created by gelatinization (14) and in the case of amylose results in formation of type 3 resistant
starch (RS3) (15). RS3 is resistant for digestion, because it is heat stable and melts
above 120 0C (16). In contrast retrograded amylopectin is thought to melt upon
reheating (cooking), due to the low melting point (46-65 0C) of these crystallites and is
therefore digestible upon cooking.
Post-harvest processing include milling, parboiling and quick-cooking. The rice milling process starts with the husking stage to remove the husk from the paddy rice, followed
by the whitening-polishing stage to transform brown rice into polished white rice, and finally the grading and blending stage to obtain head rice with pre-defined amounts of broken rice. However, while this may affect the overall nutritional value, effects on digestibility and PPG are less clear (17). Other post-harvest treatments such as
parboiling can also play a role in digestibility. Parboiling is a hydrothermal treatment that includes soaking in water, heating, drying and milling of the paddy rice. During the parboiling process the crystalline structure of the starch present in rice is transformed into an amorphous form. Pressure parboiling is accomplished by soaking the paddy rice in warm water (65-680C) for 4-5h followed by steaming under pressure
and drying (18). Other post-harvest processes are used to produce quick-cooking rice.
This is rice where the starch has been partially gelatinized by soaking in water and heating (19). Additional processes for consumer consumption include cooking, storage
and reheating. There are different ways of rice cooking depending on the ratios between rice and water, equipment (pressure cooking and steaming), and consumer preference (sticky rice, aromatic Basmati, etc.). Cooking of polished white rice strongly affects gelatinization. Retrogradation is affected by cooling and storage conditions (see also figure 3).
Given that reductions in PPG responses is generally seen as a beneficial dietary change (5) it is useful to objectively establish the variation in the range of PPG
responses to rice and the primary intrinsic and processing factors known to affect such responses. We have therefore undertaken a systematic search of the literature characterizing the range of PPG and PPI responses to different rice types, and considered this alongside available data on rice grain and processing characteristics. The main emphasis is on in vivo studies in humans, supplemented in places by in vitro literature related to specific mechanisms that may be relevant (e.g. the influence of microstructure in rice).
METHODS
The literature database ‘Scopus’ was searched for the following combinations of keywords (without language or time restrictions): rice* AND glycaem* or glycem* or digestib* or glucose* or insulin* or hyperglycaem* or hyperglycem* or hypoglycaem* or hypoglycem* or normoglycaem* or normoglycem* AND combined with title from 1980 through July 2014 resulting in 94 records. In addition Pubmed + Scifinder were also searched with the same search string and one extra article was found. Three further ‘missed’ articles were identified from the cited references in the articles identified in the formal searches resulting in 98 articles. From manual inspection of the 98 abstracts, we identified 28 original articles describing results of 32 randomized clinical trials (RCTs) with rice as the test food and a measure of PPG (and in some cases also PPI) as an outcome measure (for detailed flow chart see figure 1).
Rice r ev ie w 3 3 Fig . 1. Fl ow c ha rt of the s ys te m atic r ev iew ar ticl e s el ectio n pr oc es s, R CT , r ando m ised c ontr oll ed tr ia l
Ch ap te r 2 34 Fig ure 2 : Rice pr oc es si ng step s
Studies identified in the search and the key relevant results from those are shown in tabular form in Table 1, and arranged for specific comparisons of amylose content,
parboiling and milling respectively in Tables 2, 3 and 4 in the supplemental material.
The 32 RCTs on PPG responses to rice include different rice types (e.g. regional varieties) and different processes (milling, (par)boiling, ‘quick cook’, (pressure) cooking). Outcome measures for blood glucose include Glycaemic Index (GI, 27 studies) and/or the incremental area under the PPG response curve (iAUC, 19 studies), or peak glucose values (8 studies). The iAUC is the actual blood glucose response to a given serving of rice, whereas GI and the corresponding insulinaemic index (II) use a fixed available carbohydrate load (usually 50 g) and represent responses as a comparison to a reference assigned a value of 100. Except where noted, the GI and II studies compared rice to glucose as the reference. A subset of studies report II (7 studies) or insulin AUC (8 studies). Two studies also took breath hydrogen into account as an indicator of carbohydrate malabsorption (20,21).
Characterization of rice and processing
In most studies the rice was well characterized with respect to % amylose (9 studies), dietary fibre (4 studies), resistant starch (RS) (2 studies) and available starch (16 studies). In some studies gelatinization or amylograph measures of the milled rice flour were taken into account (22, 23, 24, 25, 26), while in others in vitro glucose release assays
were included (24, 27, 21). A few studies reported grain sizes, rheology, or retrogradation
determined by differential scanning calorimetry (DSC; a thermo-analytical technique to identify phase transition) (28). The processes explored in the studies involved
post-harvest treatment such as parboiling and milling.
Variation observed in GI and II and causes for this variation
The observed GI values ranged from 48 to 93, while the II (0-120 min) ranged from 39 to 95 (Table 1).
Amongst the studies which specifically tested or varied the amylose content and its quantitative relationship with glycaemic and insulinaemic responses (9, 18, 20, 22, 23, 29-33)
most show that the latter measures are significantly inversely related to the amylose content (9, 18, 20, 29-32) (see also Table 2 in supplemental material). However, some
studies tested for but did not find this inverse relationship for all glycaemic parameters
(22, 23, 33). Large differences in amylose content (2% versus ~30% amylose) were often
associated with relatively large glycaemic and insulinaemic effects (≈300% decrease in PPG; ≈55% decrease in PPI) (9, 18, 29). However, there were also studies where this
Post-harvest treatments such as parboiling (21,29,34) and quick-cook rice (18,21) generally
gave a lower GI compared to white rice not undergoing these post-harvest treatments (see also Table 3 in supplemental material). Larsen et al. (28) reported that an
increased severity of parboiling conditions leads to significant decreases in PPG due to the formation of RS. In that study mild traditional parboiling had no effect on the GI, whereas severely pressure parboiling reduced the GI by almost 30% compared to non-parboiled rice. However, one study did not show an effect of parboiling (32), and the
reported GI of a thermally treated Indian Basmati rice variety (thermal treatment not specified) gave a GI of 55(35), which is in the range of 52-59 that Henry et al. (36)
reported for non-thermally treated Basmati rice. The influence of another post-harvest treatment, milling, by which brown rice is transformed into white rice, has been considered in several studies (9, 18, 26, 30, 37) (Table 4 in supplemental material). In
those studies where cooking times were identical (26,30,37), brown rice always produces
lower PPG and PPI responses. However, when realistic (longer) cooking times for brown rice are applied (9,18), the difference between brown and white is smaller and
inconsistent.
Consumer processing can also make a large contribution to the RS formation in rice. Chiu and Stewart (38) quantified the RS content in 4 white rice varieties (jasmine, long
grain, medium grain and short grain) cooked in three manners (oven baked, conventional rice cooker, and pressure cooker), and analyzed RS content immediately after preparation or after 3 days of refrigeration at 40C. Refrigerated long-grain rice
cooked in a conventional rice cooker had the highest RS content, while the refrigerated short-grain rice cooked in a pressure cooker had the lowest RS content. However, in this case the GI values did not differ significantly between higher RS and lower RS rices. Consumer processing can also have a large effect on gelatinization. Wolever et al (39) showed that GI generally increased with cooking time of rice, while Jung et al. (40) showed a marked increase in gelatinization upon cooking rice and a somewhat
higher GI and II.
DISCUSSION
The literature reveals considerable variation in the the glycaemic or insulin response to rice. This is largely attributable to 1) starch characteristics, 2) post-harvest processing (particularly parboiling and to a much lesser extent de-hulling and milling) and 3) consumer processing (cooking, storage and re-heating). The relationships amongst rice characteristics and processing factors, and their physico-chemical effects and impact on glycaemic response are qualitatively illustrated in Figure 3.
Figure 3: Relationship between rice characteristics, processing factors, physico-chemical processes and glycaemic response (+ is increased effect, - is decreased effect). This is a general figure, depending on specific processes e.g. conditions of parboiling, the effects may differ.
Influence of the composition and processing of the rice
The most consistently important source of variation in PPG responses to rice is amylose content. The amylose content of rice varies between 0% (waxy rice) and 30% (Doongara) (9), with Basmati having an intermediate value (20-25% amylose; (41)). One
of the reasons for the lower PPG responses to high amylose varieties is incomplete gelatinization of amylose under normal cooking conditions, while amylopectin is fully gelatinized under these conditions (42). Gelatinization temperature is known to be
positively correlated with amylose content (43), implying that rice with a higher amylose
content requires a higher gelatinization temperature due to the restrained swelling by amylose, resulting in a longer required cooking time (44). The formation of complexes
between amylose and lipids upon heating further contributes to reduced access to the starch by gut enzymes (33). These complexes with lipids are only found in association
with amylose, therefore the rice with highest amylose content would have more lipid-amylose complexes (33). In addition, a higher amylose content leads (after cooking and
cooling) to a greater degree of retrogradation (18). In a recent study the major gene
associated with variation in GI was the waxy gene (44), which codes for different
structures of amylose within the grain and different retrogradation rates (45).
In vitro literature shows that the rice cultivar, clustered as Indica, Japonica and Hybrid rice type, is also of importance for the rate and degree of starch digestion: low-amylose Indica shows a faster and higher degree of digestion compared to low-amylose Japonica, while a high-amylose Japonica is faster and more completely digested
(shown by a higher content of rapidly digestible starch and a lower content of slowly digestible and RS) than a high-amylose Indica (11). In addition, Benmoussa et al. (46)
showed that rice amylopectin fine structure affects starch digestion properties in vitro: cultivars with the highest amount of slowly digestible starch contained mainly long-chain amylopectin.
Post-harvest treatments such as parboiling (21, 29, 34) and quick-cook rice (18, 21) also
have a large influence on GI (Table 3 in supplemental material). Gelatinization and
re-crystallization are the major changes in rice starch that occur during parboiling (47).
Parboiling process increases the gelatinization temperature of rice which is proportional with the severity of the heat treatment (48). This is probably the reason why
pressure parboiling lowers the GI to such a large extent, especially of high-amylose starches (49). The pressure parboiling process increases the gelatinization temperature
due to the formation of retrograded amylose and amylopectin. The wet heating and subsequent drying during these processing resulted in the gelatinization of the starch, followed by retrogradation of amylose and amylopectin (18) resulting in higher levels of
RS. It is possible that the amylopectin crystallites (part of the RS) retain some of the associating forces during the reheating, and are partly responsible for the low glucose response observed for pressure parboiling. The amylose-lipid complexes have a melting temperature above 100 0C and are not melted during the cooking process
resulting in higher RS levels (28).
Another way of getting a high RS content is having multiple heating/cooling cycles (50).
Thrice heated /cooled legumes, cereals and tubers increased the RS content from 4.18%, 1.86% and 1.51% to 8.16%, 3.25% and 2.51% respectively on dry matter basis. A ten times greater RS content in rice had however no effect on GI (38). It is
possible that the tested range of difference in RS in that study was not sufficient to observe a change in GI (38) and this is confirmed by the fact that only large differences
in amylose content (leading to high RS after cooking and cooling) lead to relatively large effects in GI (9).
Another final process shown to have a major influence on the PPG response is the gelatinization process during cooking, which needs moisture and a high temperature (above gelatinization temperature) for a particular period of time. Using different rice types with the same high amylose content, Panlasigui (25) reported that PPG responses
differed between rice types when a fixed cooking time was used, but these differences disappeared when the minimum cooking time for each particular rice type was used. This likely is attributed to the other physico-chemical properties of the rice types. Physico-chemical parameters which predict lower blood glucose response are high gelatinization temperature, high minimum cooking time, lower viscosity measured by amylograph consistency (amylograph is an instrument for measuring gelatinization temperature and viscosity of flour and starch pastes), and low volume expansion upon
