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EFFECT OF PULSES IN A LOW GLYCEMIC INDEX DIET ON RENAL FUNCTION IN
PARTICIPANTS WITH TYPE 2 DIABETES MELLITUS
by
SONIA BLANCO MEJÍA
A thesis submitted in conformity with the requirements
for the degree of Master of Science
Department of Nutrition
University of Toronto
© Copyright by Sonia Blanco Mejía 2014
ii
Effect of pulses in a low glycemic index diet on renal function in participants with type 2
diabetes mellitus
Sonia Blanco Mejía
Master of Science
Department of Nutritional Sciences
University of Toronto
2014
ABSTRACT
Dietary pulses are rich sources of protein, dietary fiber and are amongst the lowest
glycemic index (GI) foods. We hypothesized that addition of pulses to a low GI (LGI-pulse) diet
in participants with type 2 diabetes mellitus may be associated with improvement in renal
markers resulting from replacement of animal by plant (pulse) protein. We attempted to develop
a low GI pulse bread for use in therapeutic diets. The pulse bread had a low GI but lacked the
required palatability. We determined the effect of increased plant protein intake on markers of
renal function. We included 109 participants with type 2 diabetes mellitus who completed the
diet. Pulses as part of a low GI diet in participants with type 2 diabetes mellitus did not adversely
affect markers of renal function.
Word count: 130
iii
Acknowledgments
I would like to express my sincere gratitude to my supervisor Dr. David Jenkins for
giving me one of my most valuable professional experiences during my master program and for
all his support during my professional development.
To my committee members Dr. Paul Pencharz, Dr. Thomas Wolever and Dr. Vladimir
Vuksan, I thank you all for being part of my continuous development and for supporting my
work with your very valuable experience.
Special thanks to Dr. David Jenkins, Dr. Cyril Kendall and to Dr. John Sievenpiper for
allowing me to take part in the clinical trial presented in this thesis and for their continuous
support.
I would like to express my gratitude to Dr. Pauline Darling for taking the time to serve as
my appraisal and for the meticulous revision of this thesis.
A very special thanks to Dr. Giuseppe Mazza for recommending me to work with Dr.
Jenkins and his team. Thank you for your encouragement and support throughout this thesis
work.
To the Risk Factor Modification Center Team, to all those people that participated in part
and throughout the study I thank you all for your support during clinical and research time, and
for making my work experience a very productive and enjoyable one.
With all my heart, I thank my parents Jesus, Arcelia, Anthony and Ida for their
unconditional love and support. This thesis is the product of all the effort they have put towards
my education.
And last, but not least, to the most important men in my life, my husband Mario who has
been a brilliant person in my everyday life. Words are not enough to express you my gratitude.
STATEMENT OF MY CONTRIBUTION TO THE CLINICAL TRIAL
Prepared ethics approval forms, helped with participant recruitment, saw participants with
dietitians reviewed and did data entry for food records and laboratory analysis reports, and
performed data analyses (for this thesis).
iv
Table of Contents
ABSTRACT ....................................................................................................................................... ii
Acknowledgments.......................................................................................................................... iii
Table of Contents ........................................................................................................................... iv
List of Tables ............................................................................................................................... viii
List of Figures ................................................................................................................................ ix
List of Abbreviations .......................................................................................................................x
List of Appendices ....................................................................................................................... xiv
INTRODUCTION ......................................................................................................................1 1
LITERATURE REVIEW............................................................................................................3 2
2.1 DIETARY PROTEIN ..........................................................................................................3
2.1.1 Pulses .......................................................................................................................3
2.2 GLYCEMIC INDEX ...........................................................................................................5
2.2.1 Glycemic index ........................................................................................................5
2.2.2 Glycemic response ...................................................................................................5
2.2.3 Effect of dietary factors on glycemic response ........................................................6
2.3 HYPERTENSION ...............................................................................................................7
2.3.1 Renin-Angiotensin-Aldosterone system ..................................................................7
2.3.2 Hyperglycemia .........................................................................................................8
2.3.3 Insulin resistance ......................................................................................................9
2.3.4 Reactive oxygen species ..........................................................................................9
2.3.5 Nitric oxide ..............................................................................................................9
2.3.6 Dietary sodium .......................................................................................................10
2.3.7 Treatment ...............................................................................................................10
2.4 DIETARY EFFECTS ON RENAL FUNCTION AND BLOOD PRESSURE. ................11
v
2.4.1 Effect of dietary protein on renal function and blood pressure .............................11
2.4.2 Effect of pulses on renal function and blood pressure ...........................................12
2.4.3 Effect of glycemic index on renal function and blood pressure. ...........................12
2.4.4 Effect of other dietary factors on renal function and blood pressure. ....................13
2.5 MARKERS OF RENAL FUNCTION ..............................................................................14
2.5.1 Albuminuria ...........................................................................................................15
2.5.2 Proteinuria ..............................................................................................................15
2.5.3 Urea ........................................................................................................................15
2.5.4 Creatinine ...............................................................................................................16
2.5.5 Cimetidine ..............................................................................................................17
2.5.6 Cystatin C...............................................................................................................17
2.5.7 Inulin ......................................................................................................................17
2.5.8 Others .....................................................................................................................18
HYPOTHESIS, OBJECTIVES AND RATIONALE ...............................................................21 3
3.1 HYPOTHESIS ...................................................................................................................21
3.2 OBJECTIVES ....................................................................................................................21
3.3 RATIONALE .....................................................................................................................21
PULSE BREAD DEVELOPMENT .........................................................................................22 4
4.1 ABSTRACT .......................................................................................................................22
4.2 INTRODUCTION .............................................................................................................23
4.3 MATERIALS AND METHODS .......................................................................................24
4.3.1 Bread development ................................................................................................24
4.3.2 Bread analyses .......................................................................................................25
4.3.3 Statistical analyses .................................................................................................26
4.4 RESULTS ..........................................................................................................................27
4.4.1 Macronutrient profile .............................................................................................27
vi
4.4.2 Glycemic index and palatability ............................................................................27
4.4.3 Amino acid content ................................................................................................27
4.5 DISCUSSION ....................................................................................................................28
EFFECT OF DIETARY PULSES IN A LOW GLYCEMIC INDEX DIET ON RENAL 5
FUNCTION IN PARTICIPANTS WITH TYPE 2 DIABETES MELLITUS .........................34
5.1 ABSTRACT .......................................................................................................................34
5.2 INTRODUCTION .............................................................................................................36
5.3 MATERIALS AND METHODS .......................................................................................37
5.3.1 Design ....................................................................................................................37
5.3.2 Participants .............................................................................................................37
5.3.3 Dietary interventions ..............................................................................................37
5.3.4 Measurements ........................................................................................................38
5.3.5 Calculations............................................................................................................39
5.3.6 Statistical analyses .................................................................................................40
5.4 RESULTS ..........................................................................................................................41
5.4.1 Anthropometric measurements and blood pressure ...............................................41
5.4.2 Macronutrient profile .............................................................................................42
5.4.3 Markers of renal function.......................................................................................43
5.4.4 Dietary aminoacids ................................................................................................44
5.4.5 Correlations by change in dietary protein intake with changes in markers of
renal function .........................................................................................................44
5.4.6 Correlations by changes in dietary protein intake with changes in blood
pressure, glycated hemoglobin, glycemic index, and glycemic load. ....................45
5.4.7 Correlations by changes in animal protein and plant protein, with changes in
glycated hemoglobin, blood glucose, dietary phosphorus, urinary phosphorus,
and ratio of urinary phosphorus to dietary phosphorus. ........................................46
5.5 DISCUSSION ....................................................................................................................47
INTEGRATIVE DISCUSSION ...............................................................................................55 6
vii
6.1 IMPLICATIONS ...............................................................................................................56
6.2 LIMITATIONS ..................................................................................................................57
6.3 FUTURE RESEARCH ......................................................................................................57
SUMMARY ...................................................................................................................................59
REFERENCES ..............................................................................................................................60
APPENDICES ...............................................................................................................................81
viii
List of Tables
Chapter 2
Table 2.1. Protein content and glycemic index of pulse products ................................................ 19
Table 2.2. Amino acid content of pulses and white bread ............................................................ 19
Chapter 4
Table 4.1. Bread development ...................................................................................................... 31
Table 4.2. Macronutrient profile for all breads based on 25 g of available carbohydrate ............ 31
Table 4.3. Glycemic Index and Palatability .................................................................................. 32
Chapter 5
Table 5.1. Baseline characteristics for completers........................................................................ 49
Table 5.2. Macronutrient profile for completers ........................................................................... 50
Table 5.3. Markers of renal function for completers .................................................................... 51
ix
List of Figures
Chapter 2
Figure 2.1. GI Scale ...................................................................................................................... 20
Chapter 4
Figure 4.1. Glycemic Index .......................................................................................................... 33
Figure 4.2. Correlation of protein and Glycemic Index in 25 g of available carbohydrate bread
portions ......................................................................................................................................... 33
Chapter 5
Figure 5.1. Study design and measurements ................................................................................. 52
Figure 5.2. Consort flow diagram ................................................................................................. 53
Figure 5.3. Changes in dietary protein intake ............................................................................... 54
x
List of Abbreviations
AA(s) Amino acid(s)
ACE Angiotensin-Converting-Enzyme
ACR Urinary Albumin to Creatinine Ratio
ADA American Diabetes Association
AGE Advance Glycation End products
ANOVA Analysis of Variance
ARBs Angiotensin II Receptor Blockers
AT1-R Angiotensin Receptor 1
BH4 Tetrahydrobiopterin
BMI Body Mass Index
BP Blood pressure
BUN Blood Urea Nitrogen
BUN/Cr ratio Blood Urea Nitrogen to Creatinine Ratio
C bread Control bread
C+ bread Control bread with added wheat bran and glutten
C3XG bread Control bread with added extra glutten
Ca2+
Calcium
CB bread Control bread with added wheat bran
CB3XG bread Control bread with added wheat bran and extra glutten
xi
CCrCl Corrected Creatinine Clearance
CDA Canadian Diabetes Association
CIs Confidence Intervals
CKD Chronic Kidney Disease
CrCl Creatinine Clearance
DASH DietaryApproaches to Stop Hypertension
DBP Diastolic Blood Pressure
DPI Dietary Protein Intake
ECM Extracelullar Matrix
eGFR Estimated Glomerular Filtration Rate
eNOS Endothelial Nitric Oxide Synthase
ESHA Food Processor SQL
ESRD End Stage Renal Disease
FAO Food and Agricultural Organization
GFR Glomerular Filtration Rate
GI Glycemic Index
GL Glycemic Load
GLP-1 Glucagon-like peptide-1
HbA1c Glycated Hemoglobin
HF-wheat High fiber diet with emphasis on wheat products
iAUC Incremental Area Under the Curve
xii
IR Insulin Resistance
KDIGO Kidney Disease Improving Global Outcomes
K/DOQI Kidney Disease Outcomes Quality Initiative
LC-PUFAs Long-chain polyunsaturated fatty acids
LGI-pulse Low Glycemic Index diet with emphasis on pulses
MDRD Modification of Diet in Renal Disease
n-3 Omega-3
Na+ Sodium
NADPH Nicotinamide Adenine Dinucleotide
NO Nitric Oxide
NOS Nitric Oxide Synthase
O2 Oxygen
O2- Superoxide
PCr Plasma Creatinine
PKC Protein Kinase C
RAAS Renin-Angiotensin-Aldosterone System
RCT(s) Randomized Controlled Trial(s)
RDA Recommended dietary allowance
ROS Reactive Oxygen Species
SBP Systolic Blood Pressure
SGLT Sodium-Glucose cotransporter
xiii
SNS Sympathetic Nervous System
T bread Chickpea bread
TGF-β1 Transforming Growth Factor-β1
UCr Urinary Creatinine
USDA United States Department of Agriculture
Uvol Urinary Volume
WC Waist Circumference
xiv
List of Appendices
Appendix tables
Appendix table 2.1.1. Amino acid content in foods ..................................................................... 81
Appendix table 4.1.2. Amino acid content in grams per 100 grams of total protein .................... 82
Appendix table 4.2.3. Glucogenic amino acids in grams per 100 grams of total protein ............. 83
Appendix table 4.3.4. Insulinogenic amino acids in grams per 100 grams of total protein ......... 84
Appendix table 5.1.5. Foods for the LGI-pulse diet ..................................................................... 85
Appendix table 5.2.6. Foods for the HF-wheat diet ...................................................................... 86
Appendix table 5.3.7. Compliance check list for the LGI-pulse diet ........................................... 87
Appendix table 5.4.8. Compliance check list for the HF-wheat diet ............................................ 88
Appendix table 5.5.9. Anthropometric measurements and BP ..................................................... 89
Appendix table 5.6.10. Dietary amino acid content...................................................................... 90
Appendix figures
Appendix figure 4.1.1. Total protein content measured and calculated for all breads based on 25
g of available carbohydrate ..................................................................... 91
Appendix figure 5.1.2. Percentage of plant protein from pulse source ........................................ 92
Appendix figure 5.2.3. Change in Glycemic Index ...................................................................... 92
Appendix figure 5.3.4. Microalbuminuria .................................................................................... 93
Appendix figure 5.4.5. Correlations between changes in DPI with changes in markers of renal
function .................................................................................................... 94
xv
Appendix figure 5.5.6. Correlations by changes in dietary protein with changes in BP, HbA1c,
GI, and GL. .............................................................................................. 95
Appendix figure 5.6.7. Correlations by changes in animal protein and plant protein, with changes
in HbA1c, blood glucose, dietary phosphorus, urinary phosphorus, and
ratio of urinary phosphorus to dietary phosphorus. ................................. 97
1
INTRODUCTION 1
Chronic kidney disease (CKD) leads to end stage renal disease (ESRD). ESRD is the
leading cause of renal transplantacion. In Canada, in 2010 there were an estimated 39,352 people
with ESRD from which 16,164 were living with functioning renal transplant[1]. A great
proportion of individuals with type 2 diabetes develop microalbuminuria, and fewer develop
macroalbuminuria. In these individuals who progress to macroalbuminuria, the death rate
exceeds the rate of progression to ESRD[2]. Factors such as hyperglycemia, hypertension,
dietary sodium (Na+), and dietary protein have been proposed to contribute to renal damage[3-5].
The dietary protein recommendation for the diabetic population is a topic where some
uncertainty has been expressed[6-9]. While a safe upper level in protein intake has not been
defined for the non-diabetic population, an acceptable macronutrient distribution range of 10-
35% of total energy intake has been proposed with the intention of reducing the risk of chronic
disease, while providing intakes of essential nutrients[10]. The RDA for total protein intake in
healthy individuals is 1.0 g/kg/d for adults[11]. The American Diabetes Association (ADA)
could not recommend an ideal amount of protein intake for individuals who have diabetes, and
with no evidence of diabetic kidney disease, for optimizing cardiovascular risk or glycemic
control, due to inconclusive evidence[12]. Currently, the ADA does not recommend a reduction
in protein intake for individuals with diabetes and with evidence of early stage diabetic kidney
disease since a reduction in protein intake has not been shown to alter glycemic levels[13-15],
measurements of cardiovascular risk[13, 15] or definitively to alter the course of glomerular
filtration rate (GFR) decline[16-19]. The Canadian Diabetes Association (CDA) Clinical Practice
Guidelines also state that there is no evidence that the usual protein intake (1-1.5 g/kg/day) for
most individuals should be modified for those with diabetes unless there is the need for an
energy reduced diet, in which case maintenance or increase in protein is advised [20].
Furthermore, the Kidney Disease Improving Global Outcomes (KDIGO) 2012 clinical practice
guidelines for the evaluation and management of CKD suggest that lowering dietary protein
intake (DPI) (0.8 g/kg/day) should be reserved for adults with or without diabetes mellitus and
GFR <30 ml/min/1.73m2, and to avoid high protein intake (>1.3 g/kg/day) in adults with CKD at
risk of progression.
2
By contrast, there are data suggesting that the use of high plant protein may benefit
diabetes to some extent by improving lipid profiles and therefore ameliorating diabetic
nephropathy[21], by decreasing urinary creatinine[22] and urinary albumin to creatinine
ratio[23], reducing coronary heart disease[24, 25] and preventing a decline in GFR[26]. Pulses
such as beans, lentils, peas and chickpeas are considered good sources of plant protein[27]. The
use of soy, an oil seed legume, as a substitute of animal protein has shown some promise in
improving renal function in people with type 2 diabetes mellitus[21].
In the two studies presented in this thesis, we aimed to determine the effect of an increase
in plant protein through an increased in pulse (dry legumes) intake as part of a low GI diet
compared to a diet emphasizing wheat products in participants with type 2 diabetes mellitus on
markers of renal function. Our hypothesis was that there may be benefits to increasing plant
protein and to facilitating higher pulse consumption in individuals with type 2 diabetes mellitus.
To this end we developed a pulse bread that might be useful in future higher plant protein studies
and undertook a secondary analysis of a trial to assess the effect of increased pulse intake on
renal function in people with type 2 diabetes mellitus.
3
LITERATURE REVIEW 3
3.1 DIETARY PROTEIN
According to the 2006 Health Canada dietary recommended intake tables for
macronutrients, and to the National Research Council 2002/2005 Dietary Reference Intakes, the
RDA for healthy individuals for total protein intake is 0.8 g/kg/day for adults, 0.85 g/kg/day for
individuals between 14-18 years old, 0.95 for individuals between 4-13 years old, 1.05 for
children between 1-3 years old, and 1.2 for infants between 7-12 months old[10, 28]. RDA is set
to meet the needs of 97-98% individuals. However, there is new evidence that these protein
requirements have been significantly underestimated when using the nitrogen balance method. A
re-analysis of the included studies for building previous evidence was re-assessed using a two-
phase linear regression analysis, a better way to determine protein requirements,concluded that
the RDA for protein intake is 1.0 g/kg/day[11, 29]. The same group of investigators analyzed the
RDA for protein intake usign their newly developed alternative method, the Indicator Amino
Acid Oxidation technique, a more reliable method to measure true nitrogen balance values.
According to this method, the RDA for protein intake is 1.2 g/kg/day, value comparable to the
re-analysis using a two-phase linear regression[11, 29]. To date, RDA for total protein intake in
relation to health outcomes has not been set due to insufficient evidence.
Dietary trials, in which the substitution of plant protein for animal protein has been used,
have shown a benefit on markers of renal function [30, 31]. The exact mechanism of the cause
and progression of renal damage has not been completely understood. It is unclear whether this
particular replacement alone might benefit renal function directly or indirectly by lowering blood
pressure (BP) and blood fasting glucose.
3.1.1 Pulses
The Food and Agricultural Organization (FAO) uses the term pulses to describe annual
leguminous crop low in fat and harvested exclusively for the dry seed, excluding green beans,
green peas and seeds used for oil extraction. Included under that definition are: beans, lentils,
peas, chickpeas, field beans and cow peas[6]. Pulses are considered high in protein and low GI
foods.
4
Table 2.1 shows the protein content of pulses based on the United States Department of
Agriculture (USDA) National Nutrient Database for Standard Reference[27], and the GI of dry
and boiled pulse products based on the International GI table[32]. Protein content for these
pulses ranges between 19.3 g to 25.8 g per 100 g dry weight, and their GI (on the bread scale)
ranges between 36-43. Table 2.2 shows the amino acid (AA) content of pulses based on the
USDA National Nutrient Database for Standard Reference based on g per 100 g of protein
content[27]. Pulses are generally high in leucine, lysine, phenylalanine, arginine and glutamic
acid and low in sulfur-containing AAs (Methionine and cystein) and tryptophan. All dietary
pulses (chickpea, lentils, navy beans, white beans and kidney beans) had a lower amount of
glutamic acid (range 15.91 g-18.14 g/100 g of protein) than white bread (32.48 g/100 g of
protein). However, all dietary pulses had a higher amount of arginine, the precursor of a potent
vasodilator nitric oxide (NO), (range 5.23 g-9.77 g/100 g of protein) than white bread (4.18
g/100 g of protein). Additionally, we looked at the AA content of the previous mentioned pulses
in comparison to other foods also in g per 100 g of protein content (Appendix table 2.1.1)
Glutamic acid is the most abundant AA in all these foods (range 13.6-22.1 g/100 g of protein)
and was followed by aspartic acid. Arginine content in dietary pulses (7.3 g/ 100 g of protein)
was equally found in soy (7.3 g/ 100 g of protein), higher than in beef (6.9 g/100 g of protein),
chicken (6.4 g/100 g of protein), fish (6.3 g/100 g of protein), eggs (6.1 g/100 g of protein) and
milk (2.7 g/100 g of protein). However, dietary pulses had a lower amount of arginine than nuts
(12.9 g/100 g of protein) and seeds (12.4 g/100 g of protein). Dietary pulses are considered to
have incomplete protein and should be supplemented with cereals, meat and/or dairy products in
order to meet the required dietary intake of essential AAs[33]. American civilizations used the
combination of pulses and corn to complement a good source of protein in diet; others
complemented pulse consumption with rice or other cereals because of their high methionine
content which is relatively low in pulses. In combination or alone, pulses have been a staple food
for some civilizations and are now been part of dietary recommendations[20, 34] due to their
nutritional properties.
Dietary pulses are high in plant protein, amylose, starch, soluble fiber and antioxidant
flavonoids[35, 36]. These properties that have been found to be beneficial to human health, for
example, pulses have shown to improve cardio vascular risk factors[37, 38], blood glucose[38,
39], serum lipids[40, 41], BP[38, 42] and body weight [43, 44].
5
3.2 GLYCEMIC INDEX
3.2.1 Glycemic index
The GI is used to classify carbohydrate-containing foods based on their physiological
effect of raising blood glucose[33]. The GI methodology has been established within the past
few decades[45, 46] and has been internationally tested[47]. The method recommended by the
Food and Agriculture Organization and most used to calculate GI is the one that uses the
incremental area under the curve (iAUC) as the area over the baseline under the glucose response
curve, not considering the area beneath the fasting level[48], and it is expressed as:
100xfoodreferencetheastecarbohydraofamountequalanforiAUC
foodtesttheofiAUCGI [46]. Figure 2.1
shows the GI of foods on the glucose and bread scales, in addition to the GI categories. Hence
(on glucose scale, where glucose=100): low GI (<55), medium GI (55-69) and high GI
(≥70)[49], although there is no solid evidence as yet to support these cut points.
3.2.2 Glycemic response
The glycemic response is the relationship between the glycemic load (GL) and the
observed response on blood glucose given by a range of different carbohydrate sources[50]. The
GL is the amount of available carbohydrate times the GI, and when it is applicable to foods, it is
divided by 100, as seen in the following formula:
100
gtecarbohydraAvailableGIGL
.
It is imperative to mention that the use of GI in mixed meals has raised concern because
of the misunderstanding about its use. Some incorrectly utilize the term GI, GL and glycemic
response[51-53] and also conduct the standardized methodology incorrectly[52], even health
institutions have questioned the use of the GI in food labeling with concerns of misinterpretation
by the general population[54]. Experts advised that the predicted response of GI in mixed meals
should derived from properly conducted methodology[55, 56], and that the use of GI and
glycemic response should not be interchangeably[48], the GI is used to classify carbohydrate
quality, whereas the GL is the product of the available carbohydrate content times the GI (which
varies in response of the total amount consumed and can be of use to consumers when choosing
carbohydrate foods)[57], while the glycemic response is the relationship between the GL and the
blood glucose response observed in vivo. Hence, dietary advice should be based on both: amount
and source of carbohydrate[20].
6
There are many dietary factors that might influence the glycemic response such as fat,
protein, dietary fiber, nature of the starch, micronutrients and phytochemicals.
3.2.3 Effect of dietary factors on glycemic response
It has been shown that fat influences the glycemic response, when fat has been added to
carbohydrates, it delays gastric emptying[58] and decreases postprandial glycemic response[59].
The mechanism by which fat delays gastric emptying has not been yet established, but it has
been proposed that it might be by potentiating insulin response through stimulation of gastric
inhibitory polypeptide[60] and glucagon-like peptide-1(GLP-1)[61]. This glycemic response has
not differed by fat type, but has been questioned in instances when fat was substituted by
carbohydrate (on an isocaloric diet)[62]. Another dietary factor affecting the glycemic response
is protein, the proposed mechanisms by which protein might improve the glycemic response
includes delaying gastric emptying[63] in addition to potentiate insulin response through an
increase in GLP-1with a decrease in glucagon secretion[64], stimulating insulin secretion
(perhaps by the type of AA)[65], and a combined effect of protein with fat[66] or with
starch[67]. Dietary fiber has been largely studied on the effect on glycemic response. The main
mechanism proposed is by reducing the rate of carbohydrate absorption, which might in fact be
due to the effect of viscous fiber[68] inhibiting intestinal motility[69], increased contractility in
the small intestine[70] or delaying gastric emptying[71].
Acarbose, an alpha-glucosidase inhibitor, has been found to lower the incidence of type 2
diabetes mellitus[72], and reduce incident hypertension and cardiovascular events[73, 74]. It has
been proposed that Acarbose increases glucose stimulated insulin secretion[75], suppresses
appetite, reduces glucagon secretion and might even have an effect on pancreatic β cell
function[76]. The suggested mechanism of which Acarbose improves postprandial glucose and
improves insulin sensitivity is by slowing the digestion and absorption of carbohydrates and
stimulating GLP-1[77]. In short, Acarbose improves insulin sensitivity and decreases
postprandial hyperglycemia[78, 79]. Low GI foods act similarly to Acarbose, they directly
reduce postprandial hyperglycemia by delaying the digestion of complex carbohydrates in the
small intestine[80].
7
3.3 HYPERTENSION
Hypertension has long been recognized as a risk factor for renal damage, coronary heart
disease and stroke[81]. Lowering intensively BP in participants with proteinuria has being shown
to lower the risk of developing renal failure[82], retinopathy and stroke[83]. A drastic decline in
BP could cause blood creatinine to raise, and GFR to decline. However, such change is due to
hemodynamic reasons and not secondary to structural renal damage[84].
Hypertension and hemodynamic renal changes are characterized by glomerular
hyperfiltration and increased glomerular pressure[4, 85]. Chronic increases in glomerular
pressures and flows can cause adaptive changes in the glomerular basement membrane[3]. In the
early stages of renal disease, a compensatory renal hypertrophy and hyperplasia are developed as
a consequence of reduced in number of nephron. Hypertrophy in the glomeruli is due to
mesangial expansion and thickening of the glomerular basement membrane, resulting in
markedly more proximal tubule[86]. The increase of the area in the proximal tubule, results in an
increase of the GFR (hyperfiltration)[85]. With hyperfiltration, an increase filtration of proteins
due to damage of the glomerular basement membrane and deposits of extracellular matrix
(ECM) within the glomerular tubule can lead to tubule-interstitial fibrosis and
glomerulosclerosis, both precursors of renal damage[85]. Factors such as high DPI and diabetes
mellitus (with long standing hyperglycemia) among others, can lead to chronic renal
hemodynamic changes, changes that according to Brenner, predispose to progressive glomerular
sclerosis and deterioration of renal function[3, 4].
Systemic hemodynamic changes that promote hypertension and consequently the
acceleration of renal damage are inappropriately high cardiac output, increased vascular
resistance and central arterial stiffness. Pathogenic factors preceding these changes include:
neurohumoral hyperactivity (through the sympathetic nervous system (SNS), Renin-
Angiotensin-Aldosterone System (RAAS), etc.), metabolic abnormalities (hyperglycemia,
insulin resistance (IR), reactive oxygen species (ROS), NO, etc.), vascular abnormalities
(Calcium (Ca2+
) deposits, hypertrophy, etc.) and salt-water retention.
3.3.1 Renin-Angiotensin-Aldosterone system
Renal hemodynamic changes are implicated largely through the RAAS. The
yuxtaglomerular granular cells synthesize and secrete renin, these cells are regulated by several
8
factors that include: a decreased in BP (or fluids) mediated by the glomerular perfusion pressure
(baroreceptors), a decrease in dietary Na+ intake measured by mediators in the macula densa, and
the SNS that controls BP through β1 adrenergic-receptors[87]. Within the macula densa, renin
secretion is also modulated in part by NO[88]. Within the RAAS, angiotensinogen is release to
the circulation in response to low BP or changes in Na+
concentration, and it is converted to
angiotensin I by renin. Angiotensin I is then converted to angiotensin II by the angiotensin-
converting-enzyme (ACE), an enzyme that also decreases bradykinin (required to decrease NO
synthesis). Angiotensin II promotes vasoconstriction, Na+ reabsorption and aldosterone release,
factors that increase BP. Therefore, inhibition of the RAAS (with ACE inhibitors, angiotensin II
receptor blockers (ARBs), and renin inhibitors) has been targeted to treat hypertension[5, 89].
3.3.2 Hyperglycemia
The active absorption of glucose from the diet and the glomerular filtrate mediated by the
Na+-glucose cotransporters (SGLT) 1 and 2[90], contribute to hyperglycemia. SGLT 2 inhibitors
are drugs to lower blood glucose by increasing urinary glucose loss. Hyperglycemia increases
ROS by activation of the four damaging-cell mechanisms[91, 92] that increase mitochondrial
superoxide (O2-) production through inhibition of the glyceraldehyde-3-phosphate
dehydrogenase[93]. These mechanisms are: the polyol pathway, where hyperglycemia increases
susceptibility to intracellular oxidative stress through a decreased in the reduced glutathione, and
increased in nicotinamide adenine dinucleotide phosphate (NADPH) oxidase[94]; the advance
glycation end products (AGE) pathway, where hyperglycemia modifies circulating proteins such
as albumin that binds to AGE receptors contributing to cellular damage; the protein kinase C
(PKC) pathway, where hyperglycemia-induced activation of PKC decreases endothelial NO
synthase (eNOS) and increases the vasoconstrictor endothelin-1[95]; and the hexosamine
pathway, where hyperglycemia increases the transforming growth factor-β1 (TGF-β1) and
plasminogen activator inhibitor-1[96] and the activation of angiotensin receptors 1 (AT1-R)[97]
implicated in renal disease by promoting accumulation and decreasing degradation of ECM in
the glomeruli. Acarbose inhibits α-glucosidase enzymes in the brush border of the small
intestine, reducing the rate of complex carbohydrates-digestion and improving glucose control in
the short (post-prandial) and long term (glycated hemoglobin (HbA1c)) glucose control[98]. It
also inhibits pancreatic α-amylase, which hydrolyzes complex carbohydrates into
oligosaccharides in the lumen of the small intestine. Even though Acarbose has not shown direct
9
renal improvement measured by GFR as it would be expected when decreasing hyperglycemia, it
has shown some benefit in terms of decreasing microalbuminuria[99].
3.3.3 Insulin resistance
Hyperinsulinemia, associated to IR in non-diabetic states, affects hemodynamic changes
that contribute to hypertension, it increases neurohumoral hyperactivity through activation of the
SNS as demonstrated by glucose clamp techniques[100], promotes Na+
and potassium retention
with no effect on GFR[101], and promotes renin release. IR, as does hyperglycemia, might
activate the four damaging-cell mechanisms (polyol, AGE, PKC and hexosamine) (see 2.3.2
Hyperglycemia)[102]. Blockage of these mechanisms, improves insulin sensitivity, insulin-
stimulated glucose transport in muscle, and reduced local oxidative stress[103]. Arginine, in high
plasmatic concentrations, enhances NO availability and improves vascular insulin
sensitivity[104]. Improvements on insulin sensitivity through a weight-loss diet such as low-
carbohydrate, Mediterranean and low-fat diets have shown to contribute to the
preservation/improvement of renal function[105].
3.3.4 Reactive oxygen species
ROS have a short life and are highly reactive byproducts of oxygen (O2) metabolism such
as O2-, hydroxyl anion and hydrogen peroxide. ROS are generated by uncoupling of NO synthase
(NOS), uncoupling occurs when NOS’ cofactors (NADPH oxidase, O2, L-Arginine, and
tetrahydrobiopterin (BH4)) are in suboptimal availability[106-108]. ROS may cause proteinuria
by depolymerizing glycosaminoglycan chains that are crucial for the barrier function of the
glomerular endothelial cells[109].
3.3.5 Nitric oxide
NO acts within the vascular endothelial cells relaxing smooth muscle, it is a potent
vasodilator. NOS catalyzes L-Arginine into NO and citrulline by coupling of cofactors such as
O2, NADP and BH4. NOS also regulates renin and inhibits ACE activity[110]. Some NOS have
been identified: constitutive eNOS, dependent on cytosolic Ca2+
and calmodulin, responds to
stress[111], regulates BP under physiological conditions[112] and it is decreased in
hyperglycemic state [93]; inducible NOS, independent of cytosolic Ca2+
, activated by cytokines
and can be inhibited by glucocorticoids[113]; and the third one, neuronal NOS, found in the
10
neural tissue, it modulates the activity of the SNS[114]. NO modulates the angiotensin II, the
expression of AT1-R in various sites and regulates Na+ channels in the nephron[108]. Dietary
Approaches to Stop Hypertension (DASH) diet emphasizes vegetables and low-fat dairy
products, dietary and soluble fibre, whole grains and protein from plant sources reduced in
saturated fat and cholesterol, and may lower BP through increasing NO bioavailability[115].
Statins might improve flow-mediated vasodilation by increasing vascular NO availability[116].
3.3.6 Dietary sodium
It is well known that increased dietary Na+ intake promotes and aggravates
hypertension[89], and may directly contribute to renal damage[117]. The mechanism of action
proposed is that high intakes of Na+ may promote inflammatory[118] and hemodynamic changes
in the kidney through decrease eNOS and increase TGF-β1[119]. The increase in TGF- β1
results in an increase of NADPH oxidase-derived ROS[120] and decrease NO[121]. These
hemodynamic changes may constrict the efferent and dilate the afferent arterioles, resulting in
hyperfiltration[117]. Furthermore, aldosterone promotes Na+
and water retention[122]. A modest
reduction in dietary Na+
intake has shown beneficial effects on BP[123, 124] as seen in the
DASH diet, a diet high in potassium, magnesium, Ca2+
, and antioxidants, when restricted or not
for Na+[125, 126]. Statins seem to reverse the side effects induced by chronic high dietary Na
+
intake[119]. The mechanism by which Statins and DASH diets lower BP has been suggested to
be through an increase in eNOS and a decrease in TGF-β1 that leads to a balance in NO[115,
119].
3.3.7 Treatment
Controlling BP especially in people with diabetes, has been the focus for delaying renal
disease[127, 128]. Canadian and American guidelines recommend a BP level <130/80 mmHg in
individuals with diabetes mellitus[89, 129, 130]. Treatment recommendations include but are not
restricted to: DASH diets; dietary Na+ intake of 1500 mg per day; and pharmacotherapy that
targets the RAAS such as ACE inhibitors and ARBs[89, 131, 132].
11
3.4 DIETARY EFFECTS ON RENAL FUNCTION AND BLOOD PRESSURE.
Diet plays an important role in the prevention and co-treatment of hypertension and renal
disease, since chronic exposure to hyperglycemia and hypertension can cause renal
damage[133]. The Modification of Diet in Renal Disease (MDRD) provides beneficial evidence
that lowering BP delays the progression of renal damage [134].
3.4.1 Effect of dietary protein on renal function and blood pressure
For more than 2 decades, it was believed that by lowering DPI it was possible to delay
the progression of renal disease[3]. Malnutrition associated with severe renal disease due to the
use of DPI below the RDA raised concerns about acceptable levels of protein intake for the
various stages of renal disease. Allowance for a DPI within the RDA for the most severe stage
(stage 5) was then recommended as long as dialysis was given. A meta-analysis on cross-
sectional and prospective studies in the non-renal population concluded that there is no
association between total protein intake and BP, but it might exist with plant protein[135]. In
randomized clinical trials (RCTs), DASH-like diets with higher plant protein such as the Optimal
macronutrient Intake Trial to Prevent Heart Disease[136, 137] and the Beef in an Optimal Lean
Diet with extra lean beef protein[138] have demonstrated to have a BP lowering effect in normo-
hypertensive participants. The exchange of plant protein for animal protein has somewhat shown
some promising results on reducing microalbuminuria in animal studies[139].
There is suggestive evidence of an inverse relationship of plant protein and BP[140]. The
mechanisms by which protein reduces BP has not been identified, it was believed that increased
in DPI might increase RAAS and therefore increase BP[141]. However, a suggested mechanism
is through increased in NO (increased vasodilation) as a result of increased arginine levels,
improving insulin sensitivity and glucose tolerance[142]. Recommended DPI levels have no
adverse effects on kidney function in individuals with diabetes, and plant protein might even
improve renal function as shown in short term trials [19, 30]. However, longer term trials in the
various stages of renal disease as well as in healthy individuals are needed in order to confirm
the evidence.
12
3.4.2 Effect of pulses on renal function and blood pressure
The direct effect of pulses on renal function is not well known due to lack of information
from clinical trials. However, the effect of pulses on renal function could be indirectly attributed
to the effect of pulses on improving insulin and lowering blood glucose and BP through
decreasing the proposed damaging-cell mechanisms of these conditions, decreasing ROS and
increasing NO. The improvement of blood glucose control through dietary pulse consumption
may be due to the nature of the starch and the protein content that influence starch
digestibility[143, 144].
Intensive BP control in participants with kidney disease has been found to be
beneficial[82]. An epidemiological study that examined the association of pulse consumption
with weight and BP among other physiological parameters using the National Health and
Examination Survey demonstrated an overall risk reduction of elevated systolic BP (SBP) for
their pulse subgroups (baked beans, variety beans, and variety beans and/or baked beans). SBP
was significantly different between baked bean consumers and non-consumers [145]. This effect
was attributed to the potassium, protein and dietary fiber content of beans. A recent meta-
analysis on controlled feeding trials looking at dietary pulse consumption and BP in the non-
renal population, has shown that dietary pulses significantly reduced SBP and mean arterial BP.
This meta-analysis acknowledges potential mechanisms such as dietary plant protein, dietary
fiber and potassium involved in pulses lowering BP, and even though none of these mechanisms
were proven, the possible effect of animal protein exchange for plant protein could not be
eliminated[42]. BP-lowering effect of pulses have also been attributed to the effect of pulses on
lowering body weight and improving lipid profile[41, 42, 146].
3.4.3 Effect of glycemic index on renal function and blood pressure.
Hyperglycemia and hypertension are 2 main risk factors involved in the development of
renal disease[31]. Even though there is enough evidence that the quality of dietary carbohydrates
as low GI diets influence postprandial glycemic control, there are no long term trials evaluating
the effect of a low GI diet on renal function[62, 147, 148]. Glycemic control in type 2 diabetes
mellitus has been found to reduce markers of renal damage such as albuminuria[149, 150].
Intensive glycemic control decreases the risk of new-onset micro and macroalbuminuria[151].
However, in microalbuminuric stages, intensive glycemic control reduces creatinine clearance
13
(CrCl), leading to an increase in serum creatinine[152]. Hyperfiltration is a normal response in
the early stages of hypertensive nephropathy[153]. The persistence of hyperfiltration may
accelerate renal damage[3]. Short term glycemic control during the hyperfiltration stage early on
in renal damage seem to benefit renal function by reducing GFR[154], and in the later stage,
glycemic control seem to decrease renal damage by reducing accumulation and increasing
degradation of ECM in the glomeruli as well as decreasing other cell-damaging mechanisms
involved with ROS production and NO depletion[91, 92]. Acarbose has shown promising results
in terms of renal function, it may decrease microalbuminuria in the diabetic population[99].
Reduction of the rate of complex carbohydrates-digestion improves glucose control and has been
achieved with the use of Acarbose[77, 98]. Pulses, low glycemic index foods, when integrated as
part of a low GI diet have shown beneficial effect on glucose control[38].
There is some evidence that low GI food lower BP. Pulses as part of a low GI diet
improve BP control in individuals with type 2 diabetes mellitus when compared to a high fiber
(insoluble) diet[38], the exact mechanism by which pulses lowers BP is not known. However, it
has been proposed that perhaps the effect may be due to the content of magnesium and
potassium, as well as the indirect effect of pulses as a low GI food in lowering postprandial
insulin, associated with lowering Na+ retention and BP[38]. Low GI foods as part of a DASH
diet with Na+ reduction, showed favorable effects on BP in hypertensive individuals when
compared to a regular diet with Na+ restriction[155]. However, this study did not isolate the
effect that low GI food could have on BP.
3.4.4 Effect of other dietary factors on renal function and blood pressure.
It has been suggested that some nutrients [136], minerals such as Na+[156], and dietary
patterns such as DASH [157], Mediterranean [158] and Vegetarian [159] diets have a beneficial
effect on BP [20].
A few decades ago, the consumption of a low saturated fat diet was not believed to
influence BP[160, 161]. However, within the past decade, this topic became of interest. In a
prospective randomized study, restriction of saturated fat intake in early life was shown to
decrease childhood and adolescent BP[162], and even though the treatment group had higher
intakes of magnesium and potassium, the effect was still attributable to fat intake. Whether this
benefit is due to lower saturated fat intake, higher polyunsaturated fat intake, higher protein
14
intake or a combination of all of them, still remains questionable. The effect that dietary fats
might have on kidney function is not well known. An analysis of the Diabetes Control and
Complications Trial was done looking at the association between dietary omega-3 (n-3) long-
chain polyunsaturated fatty acids (LC-PUFAs) and incident albuminuria and changes in urinary
albumin excretion rate in type 1 diabetes mellitus. In this study, n-3 LC-PUFAs was not
associated with incident albuminuria, but was associated with slower deterioration of albumin
excretion[163]. However, this benefit may have been attributed to glycemia, since a subanalysis
showed that the benefit was seen only in those participants with HbA1c above 7.7%.
Na+ has been the nutritional factor more widely linked to hypertension. Increased dietary
Na+ intake in individuals with type 2 diabetes mellitus and microalbuminuria has been shown to
increase BP and IR[164], suggesting a relationship between BP, glucose control and renal
function. A relationship between Na+ intake and urinary albumin excretion was also found[117,
165]. In addition, a recent meta-analysis found that Na+ intake reduction does not have adverse
effects on kidney function[124]. Dietary guidelines recommend individualized Na+ reduction in
hypertensive individuals[166] and in those with type 2 diabetes mellitus and hypertension that
require Na+ reduction under the level of 2,300 mg/day[12]. Furthermore, the KDIGO 2012
guidelines recommend a dietary Na+ intake level under 2,000 mg/day in adults, irrespectively of
health status unless there is a contraindication. Reduction in dietary Na+ intake seems to decrease
BP in healthy individuals and in those with hypertension irrespectively of sex and ethnic
group[123]. Even modest reduction in Na+ intake has shown benefit in terms decreasing BP and
proteinuria in hypertensive individuals[123, 167].
Overall, there is no enough evidence to establish an ideal macronutrient profile for people
with type 2 diabetes mellitus. Nutrition therapies are recommended to be tailored to each
individual in order to achieve an individual’s metabolic goal[12]. The general goal is to improve
body weight management, glycemic control and to reduce cardiovascular risk factors to reduced
macro and microvascular complications[20].
3.5 MARKERS OF RENAL FUNCTION
There are several markers of renal function, some are more popular in the research field
because of the high specificity, but not all are preferred in the clinical setting.
15
3.5.1 Albuminuria
Albuminuria is an established method in clinical practice to detect the earliest stage of
diabetic nephropathy. Small amounts of albumin and low molecular weight immunoglobulin are
normally excreted in the urine[168]. Levels of <30 mg/day are consider within the normal
range[169]. Guidelines on early diagnosis of CKD recommend albumin to be measured in either
a dipstick or urine analysis[170]. Urinary albumin to creatinine ratio (ACR) has greater
sensitivity for detecting low-grade albuminuria and is more precise at low but diagnostically
important concentrations[171]. This and the low cost of the measurement makes it a valuable
tool in clinical practice to further decrease or prevent the risk of progression of renal damage and
cardiovascular risk[172-176]. Urinary ACR in the normal population is considered <2.5
mg/mmol for males and <3.5 mg/mmol in females. Macroalbuminuria is considered with ACR
levels between 2.5-25 mg/mmol in males and 3.5-35 mg/mmol in females. Macroalbuminuria is
considered at levels >25 mg/mmol in males and >35 mg/mmol in females[169].
3.5.2 Proteinuria
Proteinuria, the loss of total protein in urine, is defined as total urinary protein of >150
mg/day, somehow equivalent to urinary albumin loss of >300 mg/day. Proteinuria is also
referred as macroalbuminuria or overt proteinuria at levels ≥500 mg/day[171]. Protein, other
than albumin, may reflect renal tubular impairment due to change in renal hemodynamics. This
changes produce podocyte loss that causes widening of the glomerular basement membrane and
protein filtration[85]. It has been proposed as a surrogate to measure changes in renal disease
progression[177].
3.5.3 Urea
Plasma urea was amongst the first indicators used to measure GFR[178], however, it was
found to be a poor indicator[179]. There are several factors that affect plasma urea concentration
or blood urea nitrogen (BUN) including medications, illnesses, substances and dietetic factors
such as DPI, which increases urea plasma levels[180]. Urea is freely filtered by the glomerulus,
but, its reabsorption is highly dependable of water reabsorption. Therefore, urea clearance is
affected by the state of hydration and generally underestimates GFR[181].
16
3.5.4 Creatinine
Creatinine is another marker that can be measured in both plasma and urine. Creatinine
does not bind to plasma protein and is freely filtered by the glomerulus. This property makes
serum creatinine convenient, and additionally, the low cost of the measurement makes it the most
widely used indirect measure of GFR. However, secretion of creatinine varies within and
between individuals overtime[182, 183]. Creatinine is also secreted by the glomerular tubule,
giving CrCl a disadvantage by overestimating the true GFR. Prolonged storage of the urine, high
temperature and low pH influence values of measured creatinine in urine by facilitating the
biochemical conversion of creatine into creatinine[184], hence, the need to instruct the patient
for an appropriate urine collection. Also some creatinine is found in muscle, as is dependent on
muscle mass, the diet must be meat free prior to creatinine CrCl.
Serum creatinine formulae to estimate kidney function have been the result of many
attempts to correct for the limitations of urinary collections. Several mathematical equations
were used to correct the serum creatinine and give a more accurate GFR. Jelliffe & Jelliffe
accounted for sex- differences[185], Bjornsson et al added age into the equation[186], while
others accounted for age[187-191] and serum albumin[192] in addition to previous mentioned
factors. The most widely used formula is that developed by Cockcroft and Gault[189], but does
not take into account the differences in creatinine production between individuals of same age
and sex or intra-individual fluctuation over time. Additionally, it does not account for extra renal
filtration, overestimating GFR in obese or edematous individuals[193].
A formula to estimate GFR from serum creatinine in the early stages of renal disease is
the one derived from the MDRD Study published in 1994[194]. The MDRD or Levey’s formula
uses creatinine, urea and albumin serum values as well as age, gender and race. It is able to
predict up to 90.3% of the variability of the measured GFR[192]. A modified and simplified
version that requires only serum creatinine values, age, race and gender was found to yield
similar results than the MDRD original formula. Furthermore, a modification was made in order
to use Isotope Dilution Mass Spectrometry traceable creatinine essay[195]. Despite the advice
from author to use this formula only in individuals resembling those that participated in the
MDRD study, the National Kidney Foundation Kidney Disease Outcomes Quality Initiative
(K/DOQI) guidelines consider this formula to be reliable in adults[196] and it is the most widely
use equation in Canada[197]. A new equation was develop to improve the MDRD study equation
17
accuracy at estimated GFR (eGFR) levels >60 ml/min/1.73 m2, the CKD Epidemiology
Collaboration creatinine equation, otherwise known by the short form of CKD-EPI
equation[198], currently recommended by the KDIGO 2012 clinical practice guidelines for the
evaluation and management of CKD[128].
3.5.5 Cimetidine
Cimetidine-Enhance CrCl is a method that was developed in order to account for the
tubular secretion of creatinine (a major limitation of CrCl). Patients were given cimetidine to
block the tubular creatinine secretion[199]. It requires little additional cooperation from the
patients, it has been proven to be a very safe method[200] and to be cost-effective in areas where
more expensive GFR measurement techniques are not available. Cimetidine has also been
implemented to enhance results from the Cockcroft and Gault formula in patients with mild to
moderate decrease in renal function[201].
3.5.6 Cystatin C
Serum cystatin C is another suggested method to estimate GFR, cystatin C, an
endogenous protein produced by nucleated cells, and has been found to be less affected by age,
race, and muscle mass or inflammatory processes[202, 203]. Cystatin C is freely filtered through
the mid and inner cortex membrane[204] and reabsorbed by the glomeruli largely by the
proximal tubule. Hence, filtration is affected by GFR and possibly other factors such as serum
albumin[205]. The inconclusive results when applied to the diabetic population, the high cost
and the difficulty of making assays widely available restricts its use in clinical practice[206].
3.5.7 Inulin
Inulin was considered the gold standard of exogenous administered markers to measure
GFR. Inulin does not bind to plasma proteins, is freely filtered at the glomerulus and it is not
reabsorbed or secreted in the renal tubules. The down side of this marker is that it is considered
an invasive technique, since it is given in a bolus intravenous injection and a urinary catheter is
needed in order to void the bladder for accuracy of the results. Additionally, blood samples need
to be drawn every 30 min and due to its cost it has not been recommended anymore[207].
18
3.5.8 Others
There are other invasive markers that have a constant renal excretion rate such as 125
I-
iothalamate, 51
Cr-EDTA and 125m
Tc-DTPA or others that are used in conjunction with new
technology such as the radiolabeling high performance liquid chromatography, the quantitative
renal imaging with 99m
Tc-DTPA, radioiodi-99m
Tc-mercaptoacetyltriglycine and iohexol but have
a higher risk of being allergenic. These markers are not routinely use due to their cost and for
being invasive nature.
In participants with type 2 diabetes mellitus and early renal disease, it seems that the best
predictor for kidney function independently of DPI is baseline GFR [208]. eGFR is currently the
main diagnostic recommended test worldwide such as in the Caring for Australasians with Renal
Impairment guidelines [169], in the Japanese guidelines for CKD[209], in the French National
Agency for Accreditation and Evaluation of Health guidelines[210], and in the National Health
Service guidelines of England[211] and it is widely use in Canada[197]. GFR can be estimated
from the serum creatinine by using an equation which corrects for some of the more significant
non-renal influences. eGFR is known to be more sensitive to detect CKD than serum creatinine
alone or than CrCl. In the detection of early CKD, the screening should comprise eGFR as well
as urianalysis[212, 213]. Direct urinary clearance markers are useful at more severe stages of
renal disease (eGFR <25 mL/min/1.73m2).
19
Table 2.1. Protein content and glycemic index of pulse products
PROTEIN CONTENT/100ga GI
b
Kidney Bean 23.6g 41
White Bean 23.4g 43 ± 5
Navy Bean 22.3g 43 ± 5
Green Lentil 25.8g 42 ± 6
Red Lentil 25.0g 36 ± 5
Chickpea 19.3g 39 ± 8
Abbreviations: GI, glycemic index. a USDA National Nutrient Database for Standard Reference, Release 26. Protein content for dry pulses.
bGI of dry, boiled pulses is based on the International table of glycemic index [32], values are expressed
based on the bread scale in mean ± SEM.
Table 2.2. Amino acid content of pulses and white bread
Amino acid
(g per 100 g of
protein)
White
breada Chickpea Lentils
Navy
Beans
White
Beans
Kidney
Beans
Tryptophan 1.29 1.02 0.97 1.28 1.26 1.25
Threonine 2.89 3.86 3.88 3.64 4.43 4.43
Isoleucine 3.54 4.46 4.72 4.87 4.65 4.65
Leucine 6.91 7.35 7.88 8.83 8.45 8.41
Lysine 2.57 6.92 7.59 6.57 7.23 7.25
Methionine 1.77 1.34 0.93 1.39 1.58 1.61
Cystine 2.09 1.40 1.43 0.97 1.13 1.16
Phenylalanine 4.98 5.53 5.35 5.95 5.69 5.72
Tyrosine 3.05 2.58 2.91 2.46 2.98 2.95
Valine 4.18 4.35 5.40 6.36 5.51 5.50
Arginine 4.18 9.77 8.39 5.23 6.55 6.53
Histidine 2.25 2.84 3.08 2.62 2.94 2.95
Alanine 3.38 4.46 4.55 4.67 4.43 4.43
Aspartic acid 4.66 12.18 12.06 13.34 12.78 12.75
Glutamic acid 32.48 18.14 16.86 15.91 16.08 16.10
Glycine 3.70 4.29 4.43 4.10 4.11 4.11
Proline 11.09 4.29 4.55 5.75 4.47 4.47
Serine 4.98 5.21 5.02 6.05 5.74 5.72
Protein 100 100 100 100 100 100
USDA National Nutrient Database for Standard Reference, Release 26. aBased on the white bread used as a control bread in the bread development (chapter 4) in this thesis.
20
GI SCALE
Glucose
Bread
High GI >70 >90
Medium GI 55-69 70-89
Low GI <55 ≤69
Figure 3.1. GI Scale
Abbreviations: GI, glycemic Index. GI Scale where glucose=100 and bread=71. GI in the bread
scale, multiply GI by 0.71 to convert to glucose scale.
The red, yellow and green shaded areas represent the incremental area under the curve (iAUC) as the area
over the baseline under the glucose response curve, not considering the area beneath the fasting level.
21
HYPOTHESIS, OBJECTIVES AND RATIONALE 4
4.1 HYPOTHESIS
1) A palatable low GI bread made from pulse flour will have a low-GI.
2) A low GI diet with an emphasis on pulses will not affect markers of renal function in
participants with type 2 diabetes mellitus.
4.2 OBJECTIVES
1) To develop, analyze the nutrient profile, assess palatability, and test the GI of a high
protein pulse based bread compared to other breads made with wheat bran and gluten.
2) To perform a secondary analysis of a randomized controlled trial to compare the effect
of a low GI-pulse based diet with a high wheat fiber control diet on markers of renal
function in type 2 diabetes mellitus.
4.3 RATIONALE
There is not enough evidence supporting the use of dietary protein and its effect on renal
function in the population with diabetes mellitus. Evidence suggests that a diet with insufficient
DPI (0.58 g/kg/day) and usual DPI (1.3 g/kg/day) in participants with chronic renal disease (GFR
~38 ml/min/1.73m2) show no difference on the progression of renal disease[194]. Furthermore,
plant protein might have less deterioration effect on renal function[22, 23, 26]. The exact
mechanism of the cause and progression of renal damage are not completely understood.
However, lowering BP and good glycemic control have shown beneficial effects on renal
function[82, 92, 154]. Dietary pulses are high in plant protein. We have therefore made a pulse-
based bread for future use in the general population and have assessed the role of pulses in a low
GI diet on markers of renal function in participants with type 2 diabetes mellitus.
22
PULSE BREAD DEVELOPMENT 5
5.1 ABSTRACT
Background: Pulses are low GI foods that have been found to have beneficial effects on blood
glucose control and other health factors. Due to widespread bread consumption and the low
availability of low GI breads for individuals with diabetes, there is the need to develop palatable
breads that meet the needs of these individuals.
Objective: To develop a low GI high protein pulse based bread with acceptable palatability.
Methods: We developed six different breads, a control bread (C bread), a bread made out of
chickpea flour (T bread) and 4 others made with white flour and added wheat bran and/or gluten.
Their macronutrient composition was analyzed and their AA content was calculated. These
breads were then tested for their GI response and palatability and were compared to the C bread
in healthy participants.
Results: T bread contained 10.4 g of protein, and 3.2 g of fat in 25 g of available carbohydrate.
GI and palatability (mean ± SEM) for each bread were as follow: T bread 80.1 ± 5.3, 63.6 ± 8.0;
control bread with added wheat bran and gluten (C+ bread) 90.5 ± 6.3, 58.7 ± 10.0; control bread
with added wheat bran and extra gluten (CB3XG bread) 82.7 ± 6.4, 50.4 ± 10.2; control bread
with extra gluten (C3XG bread) 78.7 ± 25.6, 51.5 ± 9.9; and control bread with wheat bran (CB
bread) 102.1±25.5, 64.9 ± 8.1. Palatability was not statistically different among breads.
Limitations: We developed and analyzed a single pulse bread (T bread) and with no dose effect
measurement. GI test was done solely in healthy individuals and AA content was calculated.
Conclusion: T bread had satisfactorily GI and palatability, but further work remains to make it
sufficiently palatable for general use.
23
5.2 INTRODUCTION
The term “Pulses” was given by the World Health Organization and Food and
Agriculture Organization to crops harvested solely for dry grain low in fat content such as dry
beans, chickpeas and lentils[141]. They are high in proteins, AA, dietary fiber, minerals and
vitamins in addition to being low GI foods[214]. A recent meta-analysis found that low GI and
high protein (~1.1 g/kg/day vs. 0.8 g/kg/day based on 2000 calories per day) diets (based on
RDA for protein intake[11] are normal protein vs. deficient protein diets), contributed to greater
improvement in glycemic control in participants with type 2 diabetes mellitus[215]. Adherence
to pulse-containing dietary patterns such as Mediterranean, Prudent and Dash diets have shown
to improve diabetes management[216]. Pulses such as chickpeas were found to have a modest
improvement in glycemic control in participants with diabetes, especially when taken for more
than 4 weeks as part of a dietary pattern or alone[39]. We have recently found that the addition
of pulses to a low GI diet improves glycemic control and BP[38]. Others found that pulses
contribute to lower the glycemic response when combined with high-GI foods[144]. For the
diabetic population, pulses have been suggested as carbohydrate substitutes[62], and as part of
healthy dietary patterns[20].
Incorporation of pulses into other carbohydrate rich foods such as tortillas and pasta has
shown to increase the nutritive value, improve GI response, and texture[217, 218]. However,
they still require improvement in palatability and the ability to hold together (binding
properties)[218]. Pulse consumption has been shown to improve satiation and bowel movement,
nonetheless, its consumption may be discourage due to gastrointestinal side effects including
flatulence[219]. Although some studies have reported low adverse effect[38]. Pulse benefits
include: lowering cholesterol levels[38, 146, 220-222]; decreasing postprandial blood glucose in
individuals with type 2 diabetes mellitus[38, 223]; improving biomarkers of insulin
sensitivity[224]; possible anti-inflammatory effects [41]; increasing satiety[225-227], promoting
weight loss [43] and improving bowel function[219, 227]; improving cardiovascular function
through their antioxidant effects[228, 229]; and possible anticarcinogenic activity due to their
isoflavonoids content[230].
Pulses such as beans, chickpeas and lentils are amongst the lowest GI foods[231, 232].
For over three decades, pulses have been suggested as a potential carbohydrate substitute food
24
for those individuals with impaired glucose tolerance[62, 214] due to their potential to lower the
postprandial blood glucose response when compared to other carbohydrates[227, 233]. A
systematic review and meta-analysis of randomized controlled trials showed pulse consumption
improved long term blood glucose control[39]. Based on these evidence, pulses have been
recommended in national diabetes guidelines[20].
Therefore, we aimed to develop a low GI high protein pulse based bread with acceptable
palatability for general use.
5.3 MATERIALS AND METHODS
This experimental study was achieved in two steps: bread development and bread
analyses.
5.3.1 Bread development
We developed 6 different breads, C (made out of 100% white flour) and was used as a
reference food for GI test, a T bread (made out of 100% chickpea flour), and 4 white breads with
added fiber as wheat bran and/or added protein as gluten. Breads were prepared and baked in the
kitchen of the Risk Factor Modification Center, at St. Michael’s Hospital. However, the C bread
was prepared at both sites: at St. Michael’s Hospital (for macronutrient profile test) and at the
Glycemic Index Laboratories (for GI test) (20 Victoria Street, 3rd Floor, Toronto ON, Canada,
M5C 2N8). The chickpea flour (Kabuli chickpea flour, lot # 0110) for the T bread was obtained
from Best Cooking Pulses Inc (124 - 10th Street NE, Portage la Prairie, Manitoba, Canada R1N
1B5). White flour (all-purpose flour, Robin Hood), gluten, wheat bran, yeast, salt and sugar were
obtained from a local market (Metro, 80 Front St E, Toronto, ON M5E 1T4). The 4 white breads
with added wheat bran and/or gluten were developed in order to evaluate if we could mimic the
response and benefits of pulses by adding potential GI-lowering agents (fiber and protein) into
white bread.
Table 4.1 shows bread development for all breads. The C bread was made with 340 g of
white flour, 7 g of sugar, 4 g of salt, 6.5 g of yeast, and 250 g of tap water. The T bread
contained 200g of kabuli chickpea flour, 6 g of sugar, 2.6 g of salt, 6 g of yeast, and 280 g of tap
water. The control bread for T bread with added wheat bran and gluten (C+ bread) or positive
control bread was made with 114g of white flour, 61 g wheat bran, 25 g of gluten, 6 g of sugar,
25
2.6 g of salt, 6 g of yeast, and 280 g of tap water. The control bread with added wheat bran and 3
times the amount of protein in T bread (CB3XG bread) was made with 147 g of white flour, 171
g of gluten, 122 g of wheat bran, 9 g of sugar, 4 g of salt, 9 g of yeast, and 460 g of tap water.
The control bread with 3 times the amount of protein in T bread (C3XG bread) was made with
215 g of white flour, 225 g of gluten, 22 g of sugar, 4 g of salt, 9 g of yeast, and 420 g of tap
water. And the control bread with added wheat bran (CB bread) was made with 262 g of white
flour, 178 g of wheat bran, 9 g of sugar, 4 g of salt, 9 g of yeast, and 535 g of tap water.
Ingredients were either whisked together into a smooth batter until forming a dough or were
mixed using an electric mixer (De'Longhi Canada, 199 Longside Drive, Mississauga, Ontario
L5W 1Z9) for 10 minutes. Then, they were left to rise, and baked in a pre-heated oven at 350ºF.
Breads were left to cool after baking. C bread was made in a bread machine (Black & Decker
ALL-IN-ONE B1561-3 lb. bread maker, 27-43 Wormwood St., Boston, MA 02210), all
ingredients were added together into the machine. The C bread took 70 min from mixing until
the bread was done; time included mixing, rising and baking time. Packages were then frozen in
plastic bags and kept at -10ºC for an average of 4 days prior to testing for macronutrient
composition. Based on analysis for 25g of available carbohydrate, serving size packages were
prepared and tested for GI. The T bread had difficulty holding together (the consistency was
breakable), perhaps due to the lack of a binding agent such as gluten or psyllium. However, the
samples were adequate for analyses and consumption to test for palatability.
5.3.2 Bread analyses
Macronutrients were tested by Covance Laboratories Inc. (3301 Kinsman Boulevard.
Madison, WI, USA, 53704). Carbohydrate content was obtained by difference[234]. Total
dietary fiber was obtained by Prosky Method, Modified version[235, 236]. Available
carbohydrate content was calculated as the difference between total carbohydrate and total fiber.
Protein content was obtained by the Dumas Method using the Modified version[237]. Fat was
obtained by a modified gravimetric weight technique[238, 239].
GI tests were done at Glycemic Index Laboratories. The C bread was prepared and baked
according to the standard formula and baking times used at the Glycemic Index Laboratories[45].
All breads were tested based on 25 g of available carbohydrate due to the volume of the pulse
bread for the standard 50 g. GI test is usually done in 50g of available carbohydrate, however the
26
ingestion of 220g of bread (the equivalent to 50g of available carbohydrate) was not a feasible
amount for participants to eat, and therefore test was done in 25g of available carbohydrate (110g
of bread). GI test was done according to the Glycemic Index Laboratories’ methodology[45].
Breads were tested on 2 groups of 10 participants. However, 60% of one group participated in
both groups. All breads were tested after a 12 h fasting period. The GI for each test bread was
calculated according to a pre-established method[45, 240] as the iAUC for the area under the
glucose-response for each bread, not considering the area beneath the curve, divided by the area
under the glucose-response for C bread and expressed as a percentage[48].
,100xbreadwhiteofiAUC
breadeachofiAUCGI where iAUC was calculated according to the trapezoid rule
applicable to the areas above the fasting concentration and excluding areas beneath it[241] . GI
values were given in the bread scale. The term palatability was used as agreeable to the palate or
acceptable taste to each participant. Palatability was assed using a 100 mm visual analog scale,
which consisted of a horizontal line with the text of very unpalatable at the far left, and very
palatable at the far right. Subjects were asked to mark a vertical line anywhere along the scale
that matched their palatability to each bread.
AA content was calculated using the Food Processor SQL version 10.9.0 (ESHA) based
on the USDA Nutrient database. Single ingredients used for bread development were added into
ESHA, AAs were exported and calculated based on 100 g of total protein content.
5.3.3 Statistical analyses
Macronutrient profile and AA content of breads are expressed as grams. GI and
palatability results are expressed as means ± SEMs. The iAUC for each subject’s test bread was
expressed as a percentage of the mean area for the subject’s corresponding C bread (two
different C breads were used), and the mean value of all subjects represented the GI of the test
breads (T, C+, CB3XG, C3XG and CB breads). The resulting GI was reported on the bread
scale, where the GI of bread is 71 when glucose is 100. Differences in GI amongst breads were
assessed each using repeated measures analysis of variance (ANOVA), when the F-test
identified a significant bread effect, proc GLM ANOVA with Tukey’s test was used to adjust for
multiple comparisons. A priori student’s t-test was used to calculate significance between C
27
bread and other breads. Data analysis was done using SAS version 9.3[242]. Significance was set
at p < 0.05.
5.4 RESULTS
5.4.1 Macronutrient profile
Table 4.2 shows the macronutrient profile for all breads based on 25 g of available
carbohydrate. By design, the T bread and the C+ bread had similar macronutrient profile, the two
breads with extra gluten (CB3XG and C3XG breads) had approximately 3 times the protein of
the T bread. The addition of fiber alone to the white bread (CB bread) to produce a similar fiber
content to the T bread had a protein content that was 7.5 g per serving and was therefore
intermediate between C bread (4.7 g) and T bread (10.4 g) due to the protein associated with the
wheat bran fiber.
5.4.2 Glycemic index and palatability
Table 4.3 shows the GI on the bread scale and palatability results. Most of the breads
were medium GI (GI 70-89), and two breads were high GI (GI > 90) (C+ and CB breads). There
were no statistical significant differences among breads. Palatability for C bread was 66.6 ± 8.3,
for T bread was 63.6 ± 8.0, for C+ bread was 58.7 ± 10.0, for CB3XG bread was 50.4 ± 10.2, for
C3XG bread was 51.5 ± 9.9 and for CB bread was 64.9 ± 8.1. Palatability was not statistically
different among breads. Figure 4.1 shows the GI results for all breads. When compared to C
bread (GI = 100 ± 0), we observed a statistical significantly lower GI in T bread (GI = 80.1 ± 5.3,
p < 0.01), CB3XG bread (GI = 82.7 ± 6.4, p < 0.05), and C3XG bread (GI = 78.7 ± 8.1, p <
0.05). Figure 4.2 shows the correlation of total protein content and the GI with (p = 0.10) and
without (p < 0.05) the T bread.
5.4.3 Amino acid content
Appendix table 4.1.2 shows the AAs by group, according to their ability to synthesized in
the human body (essential or non-essential), in grams per 100 grams of total protein. Some AAs
were almost two times higher in the T bread than in any other bread. These were lysine (6.8 g in
the T bread, 2.6 g in the C bread, 2.9 in the C+ bread, 2.5 g in the CB3XG bread, 2.3 g in the
C3XG bread and 3.4 g in the CB bread), arginine (9.2 g in the T bread, 4.1 g in the C bread, 4.8 g
in the C+ bread, 4.4 g in the CB3XG bread, 4.1 g in the C3XG bread and 5.5 g in the CB bread),
28
and aspartic acid (11.7 g in the T bread, 4.6 g in the C bread, 5.2 g in the C+ bread, 4.7 g in the
CB3XG bread, 4.3 g in the C3XG bread and 6.0 g in the CB bread). However, other AAs were
present in the T bread by almost half of the content that any other bread had. These AAs are:
cystein (1.3g in the T bread, 2.1 g each in the C, C+, CB3XG and C3XG breads, and 2.2 g in the
CB bread) and glutamic acid (17.4 g in the T bread, 32.5 g in the C bread, 29.3 g in the C+ bread,
31.6 g in the CB3XG bread, 33.4 g in the C3XG bread, and 25.4 g in the CB bread). Other AAs
were present in similar amounts in all breads. Appendix tables 4.2.3 and 4.3.4 shows glucogenic
and insulinogenic AAs respectively. Total glucogenic AAs (alanine, arginine, aspartic acid,
cysteine, glutamic acid, glycine, histidine, methionine, proline, serine and valine) and
insulinogenic AAs (histidine, isoleucine, leucine, lysine, methionine, phenylalanine, threonine,
tryptophan, valine, arginine, alanine, aspartic acid, glycine, proline, serine and tyrosine) were
present in similar amounts in all breads, 74.5 g and 65 g in the C bread, 65.6 g and 77.7 g in the
T bread, 72.2 g and 66 g in the C+ bread, 74 g and 65 in the CB3XG bread, 75.3 g and 64.5 in
the C3XG bread and 69.5 g and 67.1 g in the CB bread respectively. Appendix figure 4.1.1
shows the total protein content measured and calculated for all breads based on 25 g of available
carbohydrate. The total AA content calculated was similar to the total protein content measured
for all breads.
5.5 DISCUSSION
The pulse bread (T bread) development showed satisfactory results for GI, palatability,
macronutrient and total AA content compared to other test breads with similar amount of total
protein in the form of gluten and similar fiber content in the form of wheat bran. The pulse bread
(T bread) contained higher amounts of lysine, arginine and aspartic acid than any other bread.
Pulses have been shown to have low GI[214, 231] and since a few decades ago, they have
been suggested as part of the diabetic diet[62], pulses are now seen as a staple food due to their
nutritional profile and their health benefits[243]. Our results for GI of the pulse bread (T bread)
compare well with those published for the specialty grain bread from the international table of
GI 2008, and are lower than for whole wheat bread from the same table[231], both breads
commonly consumed by the diabetic population. The ability of pulses to lower the GI has been
proposed to be due to their rich fiber and protein content The addition of fiber has been shown to
improve GI, this improvement has been attributed to the viscous fiber effect on delaying gastric
29
emptying and delaying absorption of glucose from the small intestinal lumen[68]. In our results
we found that the addition of wheat bran into our breads did not significantly reduced the GI
when compared to the pulse bread (T bread). This could be due to the fact that fiber content in
the pulse bread (9.8 g) was similar to the fiber content in all wheat bran added breads (control
bread with added wheat bran and gluten (C+ bread) 7.9 g, control bread with added wheat bran
and extra gluten (CB3XG bread) 11.1 g, and control bread with added wheat bran (CB bread)
11.5 g).
It has been shown that in participants with type 2 diabetes mellitus, the addition of 25 g
of protein to 50 g of glucose stimulates insulin response by at least twice as much than with 50 g
of glucose alone[244] and that 50 g of protein in addition to 50 g of glucose insulin stimulation
was greater than adding the responses of 50 g of protein alone or 50 g of glucose alone,
suggesting a synergistic response when ingesting protein and glucose together[245]. In our
results, we did not measure the insulin response. It has been suggested that circulating AAs play
a role in insulin and glucagon response, about 60% of the insulin and 30-60% of the glucagon
response may be due to the major insulinogenic (tryptophan, leucine, asparagine, isoleucine,
glutamine and arginine) and glucagonogenic (asparagine, glycine, phenylalanine, serine and
aspartate) AAs[246]. The extra gluten added breads (control bread with added wheat bran and
extra gluten (CB3XG bread), and control bread with added extra gluten (C3XG bread)) had
provided significant decrease in GI when compared to the control bread (C bread), but not when
compared to the pulse bread (T bread). However, the protein content of these breads was almost
triple of that in the pulse bread (T bread) which might indicate the possibility that the type of AA
content (especially arginine) could be responsible for this response. L-Arginine has long been
known to be an endogenous precursor of NO synthesis and potentiates insulin-mediated glucose
uptake[247]. It has been proposed that in participants with impaired glucose tolerance and
metabolic syndrome, arginine improves insulin release, β-cell function and insulin
secretion[248]. The arginine content in the pulse bread (T bread) was higher by almost twice
than the content in other breads. The combination of several functional AAs, which participates
in the regulation of key metabolic pathways to improve health, and have promises in prevention
and treatment of metabolic diseases[249], have been found to have beneficial effects in various
health conditions such as obesity, diabetes and cardiovascular disease[250]. Examples of these
AAs include arginine, cysteine, glutamine, leucine, proline and tryptophan[246], of which
30
arginine content in the pulse bread (T bread) was higher than the estimated for any other bread,
but not for cysteine. Our results seem in line with Dhawan et al[251] who found that chickpeas
were high in glutamic acid, followed by aspartic acid and arginine, and deficient in sulphur-
containing AAs (methionine and cysteine). Other components in pulses such as vitamins,
minerals or phytochemicals might provide beneficial health effects[252]. Palatability plays an
important role in the desire to eat certain products[253]. The pulse bread (T bread) had
acceptable palatability (63.6 ± 8.0) when compared to the widely consumed white bread (C
bread) (66.6 ± 8.3). Additional work is needed to improve palatability that will enhance its
consumption.
This study had some limitations. First, we did not measure insulin or glucagon to assess
for the insulin response of pulse protein. Second, we only tested one pulse bread (T bread) and
included 100% chickpea flour, perhaps the use of a combination of chickpea flour with wheat
flour could have made bread palatability and consistency more acceptable while maintaining
similar nutrition properties. However, the GI might have resulted higher. Third, GI tests were
done in healthy individuals and not in participants with diabetes, since we are interested to offer
this bread to individuals with diabetes, pulse breads will need to be tested in these individuals.
Fourth, AA content was calculated and not analyzed chemically. And lastly, the metabolic
availability of AAs was not assessed. A more palatable low GI pulse bread would be an option to
increase daily pulse consumption in an easier and practical way.
In conclusion, pulse bread (T bread) had a satisfactorily GI and macronutrient content for
inclusion in the diets of individuals with diabetes mellitus. There is still need for improvement in
palatability and bread consistency. Pulse bread cooking processes need to be reviewed in order to
make it less brittle, crumbly and more palatable for the consumer. We see the need for
developing a pulse bread that could potentially be consumed by all populations seeking healthier
options.
31
Table 4.1. Bread development
BREAD C T C+ CB3XG C3XG CB
Chickpea flour (g) 0 200 0 0 0 0
White flour (g) 340 0 114 147 215 262
Wheat bran (g) 0 0 61 122 0 178
Gluten (g) 0 0 25 171 225 0
Sugar (g) 7 6 6 9 22 9
Salt (g) 4 2.6 2.6 4 4 4
Yeast (g) 6.5 6 6 9 9 9
Water (g) 250 280 280 460 420 535
Electrical mixer Yesa No No Yes Yes Yes
Rising time (min) 10 10 30 35 30
Baking time (min) 30 30 35 35 45
Abbreviations: GI, glycemic index; C, Control bread; T, test bread; C+, positive control bread with wheat
bran and gluten; CB3XG, C bread with wheat bran and extra gluten; C3XG, C bread with extra gluten;
CB, C bread with wheat bran. aMixing, rising and baking time = 70min in the bread machine
Table 4.2. Macronutrient profile for all breads based on 25 g of available carbohydrate
Bread C T C+ CB3XG C3XG CB
Calories (kcal) 128 209.3 189.4 291.0 250.5 189.2
Carbohydrates (g) 26.3 34.8 32.9 36.1 28.8 36.5
Fiber (g) 1.4 9.8 7.9 11.1 3.8 11.5
Available carbohydrate (g) 25 25 25 25 25 25
Protein (g) 4.7 10.4 11.3 29.8 28.9 7.5
Fat (g) 0.4 3.2 1.5 3.1 2.1 1.4
Abbreviations: GI, glycemic index; C, Control bread; T, test bread; C+, positive control bread with wheat
bran and gluten; CB3XG, C bread with wheat bran and extra gluten; C3XG, C bread with extra gluten;
CB, C bread with wheat bran.
32
Table 4.3. Glycemic Index and Palatability
BREAD C T C+ CB3XG C3XG CB
GI 100 80.1±5.3a 90.5±6.3 82.7±6.4
a 78.7±8.1
a 102.1±8.1
Palatability 66.6±8.3 63.6±8.0 58.7±10.0 50.4±10.2 51.5±9.9 64.9±8.1
Abbreviations: GI, glycemic index; C, Control bread; T, test bread; C+, positive control bread with wheat
bran and gluten; CB3XG, C bread with wheat bran and extra gluten; C3XG, C bread with extra gluten;
CB, C bread with wheat bran.
Values are reported in means ± SEMs. GI in the bread scale, multiply GI by 0.71 to convert to glucose
scale. Palatability is reported in a scale of 100, where 100 represent best taste. Significance among breads
was tested by proc GLM ANOVA and between control and other breads by student t-test. Significance
was set at p < 0.05. aStatistically significant from C bread by student t-test
33
Figure 4.1. Glycemic Index
Abbreviations: GI, glycemic index; C, Control bread; T, test bread; C+, positive control bread with wheat
bran and gluten; CB3XG, C bread with wheat bran and extra gluten; C3XG, C bread with extra gluten;
CB, C bread with wheat bran.
Glycemic Index is given in the bread scale, multiply GI by 0.71 to convert to glucose scale. Significance
among breads was tested by proc GLM ANOVA and between control and other breads by student t-test.
Significance was set at p < 0.05. aStatistically significant from C bread by student t-test
Figure 4.2. Correlation of protein and Glycemic Index in 25 g of available carbohydrate
bread portions
Abbreviations: GI, glycemic index; C, Control bread; T, test bread; C+, positive control bread with wheat
bran and gluten; CB3XG, C bread with wheat bran and extra gluten; C3XG, C bread with extra gluten;
CB, C bread with wheat bran.
0.0
20.0
40.0
60.0
80.0
100.0
120.0
0 1 2 3 4 5 6 7
Gly
cem
ic in
dex
(G
I)
Glycemic Index - Bread scale
C T C+ CBX3G CX3G CB BREADS
a a a
T
R² = -0.74 P= 0.10
0
20
40
60
80
100
120
0 5 10 15 20 25 30 35
Gly
cem
ic in
dex
(G
I)
Protein content (g)
All breads
C
CB
C3XG
CB3XG
C+
R² = -0.94 P= 0.02
0
20
40
60
80
100
120
0 5 10 15 20 25 30 35
Gly
cem
ic in
dex
(G
I)
Protein content (g)
Excluding T bread
34
EFFECT OF DIETARY PULSES IN A LOW GLYCEMIC 6INDEX DIET ON RENAL FUNCTION IN PARTICIPANTS WITH TYPE 2 DIABETES MELLITUS
6.1 ABSTRACT
Background: There is uncertainty in the effects of dietary pulses so far tested. Reducing the GI
of the diet using Acarbose, the α-glucosidase inhibitor, has been shown to reduce new onset
hypertension in people at risk for type 2 diabetes mellitus through an improvement in renal
function. Similar dietary maneuvers to lower the index of the diet using plant protein may be
beneficial in people with diabetes.
Aim: To determine the effect of a low GI diet through increase pulse consumption, on renal
function in study participants with type 2 diabetes mellitus.
Methods: We conducted a secondary analysis of a 12-week randomized controlled trial in
participants with type 2 diabetes mellitus. The intervention was a low GI diet with emphasis on
pulses (LGI-pulse diet, ~190 g/day) versus a high fiber control diet with emphasis on wheat
products (HF-wheat diet). Markers of renal function were assessed in those who completed the
study and provided 24h urine collections.
Results: We included 109 participants with type 2 diabetes mellitus who completed the study
and provided 24 hr. urine collections, 52 in the LGI-pulse diet, and 57 in the HF-wheat control
diet. DPI was no significantly difference between diets. The change in urinary urea was
positively correlated with the change of DPI (r=0.23, p=0.01) and animal protein (r=0.22,
p=0.02), but not with plant protein, No significant changes within and between treatments were
seen in markers of renal function. There was a lack of effect seen despite a significant relation
between dietary protein and urinary urea.
35
Conclusions: Increase in plant protein through increased dietary pulses consumption as part of a
low GI diet did not affect renal function in participants with type 2 diabetes mellitus.
Trial Registration: NCT01063361.
36
6.2 INTRODUCTION
Diabetic nephropathy continues to be the predominant cause of ESRD in Canada,
accounting for 26% of the prevalence of ESRD[1]. Renal dysfunction has been associated with
cardiovascular mortality[2], individuals with macroalbuminuria have a greater cardiovascular-
death risk than to progress to ESRD requiring renal replacement therapy. Hypertension has long
been known to contribute to renal dysfunction. Hyperglycemia, high DPI and Na+ intake are
factors that may also contribute to renal damage[254, 255]. Additionally, elevated serum levels
of phosphorus have been associated with increased risk of CKD and ESRD[256]. Controlling for
hypertension, reducing cardiovascular risk and implementing renoprotection measurements are
the main focus in this population[211].
Long term elevation of intra glomerular pressure and persistent hyperglycemia seem to
impair the glomerular basement membrane function, resulting in glomerular hyperfiltration[3,
257]. The increase transglomerular movement of plasma proteins results in their deposition in the
mesangial regions of the glomerulus, changes preceding glomerular sclerosis, stimulating a
compensatory hyperfiltration mechanism by the less affected glomeruli and contributing to
progressive glomerular injury[258]. During several years, numerous clinical trials have
addressed the question of reducing DPI in order to decrease the progression of renal damage.
Malnutrition and muscle wasting associated with lowering DPI in these diets drove investigators
into exchange animal protein for plant protein initially in animal studies[139].
Dietary protein exchange (animal protein for plant protein) has shown promising results
in terms of renal function with no adverse changes in GFR and urinary albumin excretion
rate[23, 259]. Pulses as part of a low GI diet have been shown to improve glycemic control and
BP in participants with type 2 diabetes mellitus[38]. Reducing the GI of the diet using Acarbose,
the α-glucosidase inhibitor, has been shown to reduce new onset hypertension in people at risk
for type 2 diabetes mellitus through an improvement in renal function[73]. Despite the large
number of trials of different dietary interventions, dietary protein recommendations in patients
who have type 2 diabetes mellitus are not clear. Hence, there remains a need for more
randomized controlled trials in this population.
37
The primary outcome of this study has been already published elsewhere[38]. Here, we
assessed the effect that dietary pulses may have as part of a LGI-pulse diet on markers of renal
function in participants with type 2 diabetes mellitus.
6.3 MATERIALS AND METHODS
6.3.1 Design
This trial had a randomized, parallel design with two treatment arms. It has a follow-up
of 12 weeks and was conducted from February 2010 to August 2011. Participants were
randomized to a LGI-pulse diet or a HF-wheat diet. Kidney function tests were assessed at
baseline and end of the study. Figure 5.1 shows the study design and measurements. The trial
was conducted in an outpatient setting. Participants attended clinic visits at the Risk Factor
Modification Center at St. Michael’s Hospital in Toronto, Ontario. The study was approved by
the Research Ethics Board at St. Michael’s Hospital and University of Toronto. Clinical trial
registration: www.clinicaltrials.gov, NCT01063361. Written informed consents were obtained
from all participants.
6.3.2 Participants
Participants were recruited from the city of Toronto, Canada. Details of the study
recruitment have been reported previously [38]. In short, there were 131 randomized eligible
participants (Figure 5.2) with type 2 diabetes mellitus for at least 6 months; these participants
were taking oral hypoglycemic agents to control their disease, with a stable dose for at least 2
months. Participants were clinically stable for cardiovascular, renal (creatinine level >1.70
mg/dL or >150 mmol/L), or liver disease (alanine aminotransferase level >3 times the upper
limit of normal (10-40 U/L) and did not have a history of cancer. For the present analysis, we
excluded participants who had urine sample(s) missing.
6.3.3 Dietary interventions
Participants were instructed to continue on their regular diabetic control diet until
randomization. Participants were stratified by sex and HbA1c. Randomization was done by a
statistician who was geographically separated from the study center and was done using a fixed
38
random generated block. Energy requirements were calculated according to the Harris Benedict
formula for weight maintenance[260] with allowance for light physical activity. Dietary
recommendations were based on the dietary guidelines from the CDA[20]. The intended
macronutrient profile (carbohydrate, protein and fat) was 43%, 25% and 32% for the LGI-pulse
diet and 48%, 20% and 32% for the HF-wheat diet. Glycemic index aims were <70 for the LGI-
pulse diet and ~84 for the HF-wheat diet. Recommended foods in the HF-wheat diet were aimed
for a GI >80 but <85.
All participants were provided with a 7-day check-list of 15 g carbohydrate portions, this
7-day check-list provided the expected quantity of portions specific to each individual for daily
consumption according to their randomization (Appendix tables 5.1.5 and 5.2.6). Compliance
checklists were assessed at every visit and were compared to 7-day food records. Participants
were provided with a digital scale (MY WEIGH KD-7000 or TANITA KD-200) for their 7-day
food record. Participants in the LGI-pulse diet were encouraged to increase pulse intake by at
least 1 cup/day (2 servings = 1 cup or ~190 g/day). Number of food servings was given
according to calorie requirement; however, one serving of carbohydrate was decreased in order
to compensate for the carbohydrates contained in pulses. Specific recommendations were given
to not eat products from the other side of the diet, a list of these foods was written in their diet
recommendation sheet for both diets (Appendix tables 5.3.7 and 5.4.8). All participants received
dietary advice by a registered dietitian, adherence to the diet has been reported elsewhere [38].
Neither dieticians nor participants could be blinded, but equal emphasis was placed on the
potential importance for health of both diets groups.
All participants were required to do a 7-day food record of the week prior to each visit
(Appendix figure 5.1.2). For beginning of study, participants were given instructions a week
prior (week -1). Diet records were analyzed with the ESHA program based on USDA [261] data
and International GI tables [231] with some additional GI measurements run on local foods
(Glycemic Index Laboratories).
6.3.4 Measurements
Weight and height were measured with a health-o-meter professional scale (Continental
Scale Corp., Bidgeview, ILL, USA). Waist circumference (WC) was measured at the level of the
navel in the standing position. BP was measured in an upright sitting position after 5 minute rest.
39
For BP three different measurements at intervals of 1 minute were taken by an automated Digital
BP monitor (OMRON HEM-907 XL®, OMRON Healthcare Inc. Burlington, Ontario, Canada).
All measurements were done in the morning, in a fasting state.
Urinary markers were analyzed on aliquots from 24 hr urine collections. Urine
collections were measured for volume and urine samples analyzed for albumin, creatinine, urea,
glucose, Na+ and phosphorus by the Core Lab at St. Michael’s Hospital, Toronto, Canada. All
analyses were done using the SYNCHRON LX System (Beckman Coulter, Inc., 250 South
Kraemer Blvd., Brea, CA 92821). Albumin was determined by the turbidimetric method,
minimal detection level was 2 mg/L; creatinine by means of the Jaffe rate method [262]; urea by
the enzymatic rate method[263]; glucose by using the glucose electrode based on the
amperometric principle, minimal detection level was 1 mmol/L; Na+ by indirect
potentiometry[264], minimal detection level was 10 mmol/L; and phosphorus by a timed
endpoint method using a phosphorus reagent[265], minimal detection level was 3 mmol/L. ACR
was calculated by the lab base on the formula: )/(
)/(min
daymmolCreatinineUrinary
daymgAlbuUrinaryACR
.
Whole blood samples were collected in EDTA Vacutainer tubes (Vacutainer®, Becton,
Dickinson and Company) and were analyzed by the Core Lab at St. Michael’s Hospital for
HbA1c, creatinine, urea, Na+ and phosphorus. HbA1c was analyzed by a turbidometric inhibition
latex immunoassay (TINIA Roche Diagnostics) with a coefficient of variation between assays of
3-4%. Creatinine, urea, Na+ and phosphorus were analyzed using the same methods as per the
urine samples.
6.3.5 Calculations
Calculated variables include: animal protein, protein in g/kg/day, GI, body mass index (BMI),
blood urea nitrogen:creatinine ratio (BUN/Cr ratio), eGFR (using the 4-variable Modification of
Diet in Renal Disease equation recommended by the National Kidney Foundation[211, 266]),
CrCl, and urinary phosphorus:dietary phosphorus ratio. They were calculated as follow:
proteinvegetableproteintotalproteinAnimal
)(//Pr
kgweightBody
daypergramsproteinTotaldaykggotein
40
100)(
xgtecarbohydraAvailable
loadGlycemicGI
2)(
)(
mHeight
kgweightBodyBMI
)/(
)/(/
daymmolCreatininePlasma
daymgNitrogenUreaBloodratioCrBUN
femaleifblackifagePCreGFR 742.0212.13.186 203.0154.1
725.0425.0007184.0
73.1min)/(
)/(
cmheightkgweightbody
TimedLmgPCr
mlUvoldLmgUCr
CrClC
Where CCrCl = corrected creatinine clearance, UCr = urinary creatinine, PCr = plasma
creatinine, Uvol = urinary volume. Formula corrected for body surface area in m2 according to
Dubois and Dubois formula[267].
)/(
)/(/
daymmolDP
daymmolUPratioDPUP
Where UP = urinary phosphorus and DP = dietary phosphorus.
6.3.6 Statistical analyses
Results are expressed as mean ± SD or number of participants (n) for baseline
characteristics, and in mean and mean differences with 95% confidence intervals (CIs) for
anthropometric measurements and BP, macronutrient profile, markers of renal function and AAs.
Dietary variables were derived from the mean of 7-day food records at each study visit. The
means of weeks -1 and 0 were taken for baseline (for blood variables only) and weeks 8, 10 and
12 for end of the study (for blood and dietary variables) in order to allow for stabilization of
plasma variables.
All analyses were performed with SAS statistical software, version 9.3[242]. Baseline
characteristics were evaluated using the FREQ procedure by Fisher's exact test and 2-tailed
paired t-test, data were evaluated for equality of variance, pooled method was used for equal
variance and Satterthwaite for unequal variance. Participants with microalbuminuria were
evaluated using the FREQ procedure by Fisher’s exact test for baseline and end of study by
41
randomization. Change differences were derived from the change in the LGI-pulse diet (end of
study – baseline) minus the change in the HF-wheat diet (end of study – baseline), and were
evaluated using LSMEANS – mixed model procedure. Glucose values were not normally
distributed and were Log transformed. There was no adjustment for baseline. However, post-hoc
analysis were conducted in the renal function markers that were statistically significant for
change between diet, using LSMEANS – mixed model procedure after adjusting for potential
confounders (BP, HbA1c, GI and GL). Data were analyzed for intention to treat and for
completers (those participants who had both 24 hr urine collections), no statistical difference was
seen between both analysis. Data are reported for completers only. Pearson’s correlation
coefficients were done by change in dietary protein (percentage of total protein intake, protein
per g/kg/day, percentage of plant protein, protein from pulses in g/day and percentage,
percentage of animal protein and pulses in g), BP, HbA1c, GI and GL, versus change in markers
of renal function differences (urinary urea, urinary creatinine, urinary albumin, ACR, BUN/Cr
ratio, urinary glucose, urinary Na+, urinary phosphorus, blood urea, blood creatinine, eGFR,
cCrCl and blood potassium). Statistical significance was considered at p < 0.05.
6.4 RESULTS
Figure 5.2 shows the flow diagram for participants. From the 121 participants who
started the study, seven participants dropped out, four from the LGI-pulse diet for issues
unrelated to the diet and three from the HF-wheat diet because they disliked the diet. Five more
participants had missing urine samples, four from the LGI-pulse diet and one from the HF-wheat
diet. We included a total of 109 participants, 52 in the LGI-pulse diet and 57 in the HF-wheat
diet. Table 5.1 shows baseline characteristics. Participants did not differ significantly between
diet groups in age, sex, ethnicity, diabetes mellitus duration, glycemic control, anthropometric
measurements, BP and kidney function markers.
6.4.1 Anthropometric measurements and blood pressure
Appendix table 5.5.9 shows anthropometric measurements and BP during the study
period. SBP and diastolic BP (DBP) were statistically different between diets (-3.9 mmHg (95%
CIs, -7.1, -0.8 mmHg) for SBP and -2.8 mmHg (95% CIs, -4.8, -0.8 mmHg) for DBP). Changes
from baseline in both, SBP and DBP within the LGI-pulse diet were statistically lower, -3.9
42
mmHg (95% CIs, -6.2, -1.7 mmHg) for SBP and -3.1 mmHg (95% CIs, -4.6, -1.6 mmHg). There
were not statistical changes within the HF-wheat diet for BP. Body weight, BMI and WC were
significantly decreased within both diets (LGI-pulse and HF-wheat diets), but there was no
statistical differences between diets for any of these measurements.
6.4.2 Macronutrient profile
Table 5.2 shows the macronutrient profile for baseline, end of study, and changes within
and between diets for the LGI-pulse diet and the HF-wheat diet. Figure 5.3 A shows the changes
in total DPI, and it was not significantly different between LGI-pulse diet and HF-wheat diet in
both, percentage of total energy intake (1.2 % (95% CIs, -0.1, 2.4%)) and grams per kilo per day
(0.06 g/kg/day (95% CIs, -0.02, 0.1 g/kg/day)). However, figure 5.3 B shows that the change in
type of protein was statistically different between diet for plant protein (10.1 g/day (95% CIs,
6.6, 13.6 g/day)) and animal protein intake (-6.6 g/day (95% CIs, -11.7, -1.5 g/day)). The LGI-
pulse diet increased plant protein consumption by 4.9 g/day (95% CIs, 28.1, 36.4 g/day), whereas
the HF-wheat diet lowered its consumption by 5.2 g/day (95% CIs, -7.7, -2.8 g/day). The change
from baseline in animal protein intake was inversely related to the change from baseline in plant
protein. The LGI-pulse diet decreased animal protein consumption by 2.4 g/day (95% CIs, -6.0,
1.2 g/day) whereas the HF-wheat diet increased its consumption by 4.2 g/day (95% CIs, 0.5, 7.9
g/day). Additionally, we looked at how much plant protein from pulses contributed to the total
protein intake. Appendix figure 5.1.2 shows the percentage of plant protein from pulse source at
end of study. At end of study, pulse protein contributed to most of the plant protein in the LGI-
pulse diet with a mean of 39.9 % (95% CIs, 36.1, 43.7 %), yielding to 15.7 g of pulse protein/day
(95% CIs, 13.9, 17.5 g of pulse protein/day) and contributed to a very small portion in the HF-
wheat diet with a mean of 1.1 % (95% CIs, 0.6, 1.7 %). Change in dietary pulse intake was
statistically different between diets (216.3 g/day (95% CIs, 189,243.4 g/day)), with a significant
increase in the LGI-pulse diet by 185.2 g/day (95% CIs, 159.2, 211.2 g/day) and a significant
decrease in the HF-wheat diet by 31.1 g/day (95% CIs, -42.3, -19.9 g/day). Change in fiber
intake was statistically different between diets (11.1 g/day (95% CIs, 7.4, 14.9 g/day)), the LGI-
pulse diet had a significant increase in fiber with 11.5 g/day (95% CIs, 8.5, 14.4 g/day) while the
change in fiber intake was not significant for the HF-wheat diet with only 0.3 g/day (95% CIs, -
2.1, 2.7 g/day). Change in SFA was statistically different between diets (-1.4% (95% CIs, -2.3, -
0.5%)), both diets significantly decreased their SFA intake, the change in the LGI-pulse diet (-
43
2.1% (95% CIs, -2.8, -1.5%) was greater than in the HF-wheat diet (-0.7% (95% CIs, -1.3, -
0.1%)). Change in HbA1c was statistically different between diets (-0.2% (95% CIs, -0.3, -
0.001%)), both diets had a significant reduction in HbA1c, the LGI-pulse diet (-0.5% (95% CIs,
0.6, -0.4%)) had a greater reduction than the HF-wheat diet (-0.3% (-0.5, -0.2%)). Appendix
figure 5.2.3 shows the change in glycemic index between diets. Change in GI between diets was
statistically different (-18.3 (95% CIs, -20.6, -16.1)), at end of study the mean GI for the LGI-
pulse diet was 65.2 (95% CIs, 63.5, 66.8) and for the HF-wheat diet was 82.2 (95% CIs, 81.2,
83.2). Similarly, change in GL was statistically different between diets (-31.5 (95% CIs, -42.3, -
20.7)). Change in dietary phosphorus was statistically different between diets (156.9 mg/day
(95% CIs, 50.9, 262.9 mg/day)), with a significant change within the LGI-pulse diet (178.7
mg/day (95% CIs, 104.8, 252.6 mg/day)), but not for the HF-wheat diet (21.8 mg/day (95% CIs,
-55.3, 98.9 mg/day)) i.e. significantly more dietary phosphorus on the low GI diet.
6.4.3 Markers of renal function
Table 5.3 shows the urinary and blood markers of renal function. Urinary glucose was
not normally distributed, log transformed data did not show a significant change difference
between diets for which data are presented as non-log transformed. No other urinary markers
(volume, urea, creatinine, albumin, ACR, Na+, phosphorus and urinary to dietary phosphorus
ratio) were significantly different in changes between the LGI-pulse diet and the HF-wheat diet.
Changes in plasma markers of renal function (urea, creatinine, BUN/Cr ratio, eGFR, cCrCl and
potassium) were not statistically different between the LGI-pulse diet and the HF-wheat diet.
Even though there were no significant changes in urinary albumin excretion, we looked at
the number of participants with microalbuminuria. Appendix figure 5.3.4 shows participants
with microalbuminuria. At baseline, most participants (89.9% (n = 98)) had urinary albumin
within the normal range, and the remaining participants (10.1% (n = 11)) had microalbuminuria
(urinary albumin ≥30 mg/L), there was no significant difference between diets with five
participants (45.5%) in the LGI-pulse diet and six participants (54.6%) in the HF-pulse diet. At
end of study, 97 participants (89%) had urinary albumin within the normal range, and the
remaining participants (11% (n= 12)) had microalbuminuria (≥30 mg/day), once again, the
difference between groups was not significant, with five participants (41.7%) in the LGI-pulse
diet and seven participants (58.3%) in the HF-wheat diet.
44
Additionally, we also looked at dietary AA intake, the correlations in DPI with changes
in markers of renal function, the correlations by changes in DPI with changes in BP, HbA1c, GI,
and GL, and the correlations by changes in animal protein and plant protein, with changes in
HbA1c, blood glucose, dietary phosphorus, urinary phosphorus, and ratio of urinary phosphorus
to dietary phosphorus.
6.4.4 Dietary aminoacids
Appendix table 5.6.10 shows the dietary AA intake in g/day. There was a significant
difference in the change in dietary intake for arginine (0.5 g/day (95% CIs, 0.2, 0.9 g/day)),
aspartic acid (0.8 g/day (95% CIs, 0.3, 1.4 g/day)), and proline (-0.4 g/day (95% CIs, -0.8, -0.01
g/day)). Arginine was statistically decreased within the HF-wheat diet (-0.3 g/day (95% CIs, -
0.6, -0.1 g/day)), while the increase of arginine within the LGI-pulse diet was not significant (3.8
g/day (95% CIs, 3.5, 4.1 g/day)). Aspartic acid was statistically increased in the LGI-pulse diet
(0.5 g/day (95% CIs, 0.0, 0.9 g/day)), while the decrease of aspartic acid within the HF-wheat
diet was not significant (-0.4 g/day (95% CIs, -0.7, 0.0 g/day)). Proline was statistically
decreased within the LGI-pulse diet (-0.4 g/day (95% CIs, -0.7, -0.1 g/day)), while there was no
change within the HF-wheat diet (0.0 g/day (95% CIs, -0.3, 0.1 g/day)). No other significant
changes were seen.
6.4.5 Correlations by change in dietary protein intake with changes in markers of renal function
Appendix figure 5.4.5 shows the significant correlations between changes in DPI (total
protein as percentage of total energy intake, total protein intake (g/kg/day), plant protein (g/day),
protein form dietary pulses (g/day), percentage of plant protein from pulses, animal protein
(g/day) and dietary pulses (g/day)) with markers of renal function (urinary urea, urinary
creatinine, urinary albumin, ACR, urinary glucose (logged transformed), urinary Na+, urinary
phosphorus, blood creatinine, BUN/Cr ratio, eGFR, CCrCl, and blood potassium). The change in
urinary urea was positively correlated with the change of total protein intake (r=0.23, p=0.01)
and animal protein (r=0.22, p=0.02), but not with total protein as percentage of total energy
intake, plant protein, protein from dietary pulses or percentage of plant protein from dietary
pulses. A positive correlation was seen on change in urinary creatinine with change in animal
protein (r=0.22, p=0.02), but not with total protein as percentage of total energy intake, total
45
protein intake, plant protein, protein from dietary pulses, percentage of plant protein from pulses,
or dietary pulses. The change in the urinary glucose was positively correlated with the change in
total protein intake (r=0.24, p=0.01) and with animal protein intake (r=0.29, p= 0.002), but not
with total protein as percentage of total energy intake, plant protein, protein form dietary pulses,
percentage of plant protein from pulses, or dietary pulses. The change in urinary phosphorus was
negatively correlated with the change in percentage of plant protein from pulses (r=-0.20,
p=0.04) but not with total protein as percentage of total energy intake, total protein intake, plant
protein, protein form dietary pulses, animal protein and dietary pulses. The change in blood urea
was positively correlated with the change in total protein as percentage of total energy intake
(r=0.26, p=0.01), and with animal protein intake (r=0.23, p=0.01) but not with total protein
intake, plant protein, protein form dietary pulses, percentage of plant protein from pulses, or
dietary pulses. The change in blood creatinine was positively correlated with the change in
animal protein intake (r=0.20, p=0.03) but not with total protein as percentage of total energy
intake, total protein intake, plant protein, protein form dietary pulses, percentage of plant protein
from pulses, or dietary pulses. The change in blood potassium was positively correlated with the
change in total protein intake (r=0.20, p=0.04), but not with total protein as percentage of total
energy intake, plant protein, protein form dietary pulses, percentage of plant protein from pulses,
animal protein or dietary pulses. No significant correlations were seen between changes in
dietary protein with changes in urinary albumin, ACR, urinary Na+, BUN/Cr ratio, eGFR and
cCrCl.
6.4.6 Correlations by changes in dietary protein intake with changes in blood pressure, glycated hemoglobin, glycemic index, and glycemic load.
Appendix figure 5.5.6 shows the significant correlations between changes in DPI (total
protein as percentage of total energy intake, total protein intake (g/kg/day), plant protein (g/day),
protein form dietary pulses (g/day), percentage of plant protein from pulses, animal protein
(g/day) and dietary pulses (g/day)) with changes in BP, HbA1c, GI and GL. The change in HbA1c
was negatively correlated with the change in protein form dietary pulses (r=-0.22, p=0.02),
protein form dietary pulses (r=-0.22, p=0.02), dietary pulses (r=-0.22, p=0.02), and in similar
magnitude but in opposite direction (positively correlated) to animal protein (r=0.22, p=0.02).
No significant correlations were seen for HbA1c with total protein as percentage of total energy
46
intake, total protein intake, or plant protein. The change in GI (in the bread scale) was negatively
correlated with plant protein (r=-0.48, p<0.001), protein form dietary pulses (r=-0.76, p<0.001)
percentage of plant protein from pulses (r=-0.76, p<0.001) and dietary pulses (r=-0.76, p<0.001).
The change in GI was on the other hand, positively correlated to animal protein (r=0.29,
p=0.002), but no significant correlations were seen with total protein as percentage of total
energy intake or total protein intake. The change in GL was negatively correlated with total
protein as percentage of total energy intake (r=-0.46, p<0.001), protein form dietary pulses (r=-
0.33, p<0.001), percentage of plant protein from pulses (r=-0.36, p<0.001) and dietary pulses
(r=-0.33, p<0.001), but positively correlated with total protein intake (r=0.24, p=0.01). No
significant correlations were seen for changes in GL with changes in plant protein or animal
protein. No significant correlations were seen for changes in SBP or DBP with changes on DPI.
6.4.7 Correlations by changes in animal protein and plant protein, with changes in glycated hemoglobin, blood glucose, dietary phosphorus, urinary phosphorus, and ratio of urinary phosphorus to dietary phosphorus.
Appendix figure 5.6.7 shows the significant correlations between changes in animal
protein and plant protein, with changes in HbA1c, dietary phosphorus, urinary phosphorus and
ratio of urinary phosphorus to dietary phosphorus (UP/DP ratio). The change in HbA1c was
positively correlated to the change in animal protein (r=0.23, p=0.02), and negatively but not
significant to plant protein. Dietary phosphorus was positively correlated to both, plant (r=0.59,
p<0.001) and animal (r=0.34, p<0.001) protein. The UP/DP ratio was negatively significant to
plant protein (r=-0.23, p=0.02), but not to animal protein. Blood glucose and urinary phosphorus
were not significantly correlated to either plant or animal protein.
47
6.5 DISCUSSION
Consumption of ~260 g of pulses a day as part of a LGI diet, did not show adverse effects
on markers of renal function (urinary urea, urinary creatinine, urinary albumin, ACR, ratio,
urinary glucose, urinary Na+, urinary phosphorus, urinary phosphorus:dietary phosphorus ratio,
blood urea, blood creatinine, BUN/Cr, eGFR, cCrCl and blood potassium) within a period of 3
months. The lack of effect seen despite a significant relation between dietary protein and urinary
urea (r=0.23, p=0.01). These data support current dietary recommendations for DPI in patients
with type 2 diabetes mellitus with normal renal function[20]. However, no treatment difference
in total protein was observed.
This is the first study, to our knowledge, to report the effect of dietary pulses as part of a
LGI diet in participants with type 2 diabetes mellitus on markers of kidney function. A
randomized controlled feeding trial tested the effect of a DASH diet on BP when compared to a
control diet based on the profile reported in the National Health and Nutrition Examination
Survey on hypertensive participants[115]. This trial suggested that the BP-lowering effect might
have been due to the increasing NO bioavailability perhaps as a result in the increase in L-
arginine (a precursor of NO) levels from nuts and other dietary foods. In our trial, we found a
significant reduction in SBP (3.9 mmHg) and DBP (3.1 mmHg) within the LGI-pulse diet.
However, we did not observe a significant increase in dietary arginine within the LGI-pulse diet
(3.8 g/day (95% CIs, 3.5, 4.1 g/day)), but a significant decrease in dietary arginine within the
HF-wheat diet (-0.3 g/day (95% CIs, -0.6, -0.1 g/day)). Another RCT suggested that plant protein
(40 g of isolated soybean protein supplement a day) had beneficial BP-lowering effect in
hypertensive individuals (reduced SBP by 7.9 mmHg and DBP by 5.3 mmHg)[159], at a bigger
magnitude than the one we observed. This effect was attributable to the replacement saturated fat
for soy protein. We also observed a significant decrease in saturated fat within the LGI-pulse diet
(2.1 %) and in a smaller magnitude, within the HF-wheat diet (0.7 %). However, individuals
within the LGI-pulse diet had a higher saturated fat level at baseline. The BP effect seen within
our trial for the LGI-pulse diet is in accordance with a systematic review looking at the effect of
biomarkers of dietary plant protein on BP[135]. This systematic review also showed an inverse
association between plant protein and BP, contrary to the results seen in the analysis of RCTs on
48
total protein and BP. However, there were only two RCTs contained within this systematic
review and included participants with albuminuria, a suggested predictor of hypertension.
Intensive long term glycemic control has been associated with delay in microalbuminuria
in participants with type 2 diabetes mellitus within a 2-year period[152]. We did not observe a
delay in microalbuminuria even though we observed a significant decrease in HbA1c within the
LGI-pulse diet (0.5 %, p<0.05) and within the HF-wheat diet (0.3 %, p<0.05). However, baseline
HbA1c levels within the participants of the intensive glycemic control trial (9.2% for the
treatment arm and 9.7% for the control arm) were of greater magnitude when compared to our
trial (7.3 % for the treatment arm and 7.2 % for the control arm). Additionally, end of study
HbA1c value for the treatment arm in the intensive glycemic control trial (7.1 %) was similar to
the values seen in our participants for their baseline.
Our study was limited in some aspects. This was a secondary analysis, therefore the
number of participants with microalbuminuria was very small and we could not detect any
significance. This was a short term trial, three months is the required interval of time for a
second evaluation on microalbuminuria to establish the diagnosis of persistent microalbuminuria.
Giving the fact that we did not have a previous evaluation of the renal function of these
participants, and considering that the deterioration rate from any stage of nephropathy is about 2-
3% per year[2], these three months were not adequate to evaluate the progression of
microalbuminuria. Serum phosphorus levels within the high-normal reference values has been
associated with doubling the risk of developing CKD and ESRD[256], in this study, serum
phosphorus was not measured due to budgetary restrictions. Even though we did see a significant
increase in dietary phosphorus for the LGI-pulse diet of a 178.7 mg/day (57.7 mmol/day), we
saw a non significant urinary phosphorus reduction (1.6 mmol/day) relative to the control and no
adverse effects on markers of renal function.
In conclusion, the consumption of approximately 1 ½ cups of pulses a day does not have
adverse effects on renal function in the short term, allowing consumers to benefit from other
pulse properties on glycemic control and BP. Longer term trials looking at kidney function as a
primary analysis that includes participants with kidney function at different stages are needed.
49
Table 5.1. Baseline characteristics for completers
LGI - Pulse diet
n = 52
HF - Wheat diet
n = 57 p values
b
age (y) 58.6 ± 9 61.8 ± 7.5 0.05
sex % (N)a 0.45
Female 44.2 (23) 52.6 (30)
Male 55.8 (29) 47.4 (27)
Ethnicity % (N)a 0.62
European 25 (13) 28.1 (16)
East Indian 11.5 (6) 7 (4)
Indian/South Asian 27 (14) 26.3 (15)
African 10 (5) 17.5 (10)
Other white/Caucasian 17.3 (9) 8.8 (5)
Other 9.6 (5) 12.3 (7)
Duration of DM (y) 9.1 ± 6.4 8.5 ± 6.7 0.62
HbA1c (%) 7.4 ± 0.5 7.3 ± 0.5 0.27
WC (cm) 106.7 ± 15.7 102 ± 13 0.10
Weight (kg) 86.6 ± 20.8 82.7 ± 17.3 0.28
BMI (Kg/m2) 31.6 ± 6.8 30 ± 5.7 0.19
SBP (mmHg) 121.8 ± 9.2 118.9 ± 13.1 0.19
DBP (mmHg) 71.4 ± 8 69.7 ± 9 0.30
Plasma creatinine (umol/l) 72.6 ± 14.9 74.4 ± 19 0.59
Urinary albumin (mg/ 20.2 ± 46.3 15.8 ± 27.3 0.54
ACR (mg/mmol creat) 1.6 ± 3.3 1.4 ± 2.4 0.72
BUN/Cr ratio 18.9 ± 4.9 18.4 ± 4.2 0.22
eGFR (ml/min/1.73m2) 94.9 ± 15.4 92.6 ± 21.2 0.51
CCrCl (ml/min/1.73m2) 199.1 ± 114 167.4 ± 102 0.13
Abbreviations: DM, diabetes mellitus; HbA1c, glycated haemoglobin A1c; WC, waist
circumference; BMI, body mass index (calculated as weight in kilograms divided by height in
meters squared); SBP, systolic blood pressure; DBP, diastolic blood pressure; ACR , urinary
albumin-urinary creatinine ratio; BUN/Cr ratio, blood urea nitrogen to creatinine ratio, urinary
albumin-urinary urea ratio; eGFR, estimated glomerular filtration rate, calculated using the
MDRD modified formula as:
femaleifblackifagePCreGFR 742.0212.13.186 203.0154.1 , where PCr, plasma
creatinine; CCrCl, corrected creatinine clearance, calculated correcting for body surface area
using Dubois and Dubois formula as:
725.0425.0007184.0
73.1min)/(
)/(
cmheightkgweightbody
TimedLmgPCr
mlUvoldLmgUCr
CrClC
, where
PCr, plasma creatinine; UCr, urinary creatinine; Uvol, urinary volume.
Values are expressed in Mean ± SD unless otherwise specified. aData were evaluated by Fisher's exact test.
bp-values were obtained by using 2-tailed paired t-test. Significance was set at p < 0.05
50
Table 5.2. Macronutrient profile for completers
LGI-pulse diet (n = 52) HF-wheat diet (n = 57) p-value
Baseline End of Study Baseline End of Study
Energy (kcal/day) 1738.1 (1623.8,
1852.4)
1533.3 (1439.0,
1627.6)a
1599.8 (1493.3,
1706.4)
1446.5 (1348.3,
1544.76)a 0.41
Protein (%) 19.7 (18.8, 20.6) 22.9 (22.0, 23.7)a 19.6 (18.7, 20.4) 21.5 (20.5, 22.6)a 0.07
Protein (g/kg/day) 1.03 (0.93, 1.12) 1.10 (0.99, 1.21)a 0.96 (0.89, 1.03) 0.98 (0.90, 1.05) 0.13
Plant protein (g/day) 34.7 (31.3, 38.1) 39.6 (36.6, 42.7)a 32.2 (29.3, 35.1) 27.0 (25.0, 29.0)a <0.0001
Pulse protein (g/day) 2.9 (1.8, 3.9) 15.7 (13.9, 17.5)a 2.4 (1.6, 3.2) 0.3 (0.1, 0.4)a <0.0001
Pulse PP (%) 7.7 (5.4, 9.9) 39.9 (36.1, 43.7)a 7.2 (4.9, 9.5) 1.1 (0.6, 1.7)a <0.0001
Animal protein (g/day) 49.5 (45.1, 54.0) 47.2 (43.1, 51.3) 45.6 (40.8, 50.4) 49.8 (45.3, 54.4)a 0.01
Pulse intake (g/day) 41.1 (26.4, 55.7) 266.3 (200.4, 252.1)a 34.9 (23.2, 46.6) 3.8 (2.01, 5.5)a <0.0001
Carbohydrates (%) 45.9 (43.8, 48.5) 45.4 (43.7, 47.2) 46.3 (44.5, 48.2) 48.2 (46.4, 50.0)a 0.07
Fiber (g/day) 27.2 (24.3, 30.1) 38.7 (35.5, 41.8)a 26.1 (23.6, 28.5) 26.4 (23.8, 28.9) <0.0001
Soluble Fiber (g/day) 4.5 (3.7, 5.2) 5.7 (5.1, 6.3)a 4.1 (3.5, 4.8) 3.5 (3.1, 3.9)a <0.001
Fat (%) 33.2 (31.5, 34.9) 30.4 (29.0, 31.8)a 32.8 (31.2, 34.4) 28.4 (27.0, 29.9)a 0.21
SFA (%) 10.4 (9.7, 11.2) 8.3 (7.7, 8.9)a 9.4 (8.8, 10.0) 8.7 (8.0, 9.3)a <0.01
HbA1c (%) 7.3 (7.2, 7.5) 6.9 (6.7, 7.0)a 7.2 (7.1. 7.3) 7.0 (6.8, 7.0)a 0.04
GI 79.9 (78.1, 81.6) 65.2 (63.5, 66.8)a 78.6 (77.2, 80.0) 82.2 (81.2, 83.2)a <0.0001
GL 114.1 (103.7, 124.6) 80.6 (74.1, 87.0)a 102.6 (95.0, 110.1) 100.5 (93.5, 107.5) <0.0001
Phosphorus (mg/day) 1332.2 (1247.8,
1416.6)
1510.8 (1418.1,
1603.6)a
1284.2 (1196.4,
1372.0)
1306.0 (1213.3,
1395.7) <0.01
Abbreviations: LGI, low glycemic index; HF, high fiber; PP, plant protein; SFA, saturated fatty
acids; GI, glycemic index in bread scale (to convert to glucose scale, multiply by 0.71); GL,
glycemic load. To convert phosphorus in mg/dl to mmol multiply by 0.323
Week 0 values represent baseline values, the average of weeks 8, 10 and 12 represent end of the
study values. Between diet differences was calculated as LGI-pulse diet minus HF-wheat diet.
Values are expressed in means (95% CIs). aSignificant difference (p < 0.05) within diet by LSMEANS
- mix model procedure.
51
Table 5.3. Markers of renal function for completers
LGI-pulse diet (n = 52) HF-wheat diet (n = 57) p-valuec
Baseline End of Study Baseline End of Study
24 hour urine collection
Volume (ml/day) 1875 (1667.0,
2083.0)
1984.1 (1763.5,
2204.8)
1776.3 (1564.1,
1988.6)
1863.7 (1619.9,
2107.5) 0.57
Urea (mmol/day) 349.8 (317.7,
381.9)
342.4 (307.5,
377.2)
317.5 (284.8,
350.2)
327.6 (290.1,
365.2) 0.86
Cr (mmol/day) 11.9 (10.7, 13.1) 10.7 (9.5, 11.9)a 10.4 (9.4, 11.4) 10.3 (9.3, 11.3) 0.46
Albumin (mg/day) 20.2 (7.3, 33.1) 20.9 (5.1, 36.7) 15.8 (8.5, 23.0) 16.4 (7.9, 25.0) 0.53
ACR (mg/mmol Cr) 1.6 (0.7, 2.5) 1.6 (0.7, 2.4) 1.4 (0.8, 2.1) 1.6 (0.7, 2.6) 0.21
Glucose (mmol/day)b 5.8 (2.9, 8.8) 9.9 (-3.4, 23.1) 3.4 (1.2, 5.7) 2.6 (1.2, 3.9) 0.29
Sodium (mmol/day) 85.4 (75.5, 95.4) 79.3 (70.4, 88.2) 77.8 (676, 87.9) 82.8 (71.8, 93.7). 0.89
Phosphorus (mmol/day) 13.1 (11.3, 15.0) 11.6 (10.1, 13.0) 11.4 (10.0, 12.8) 12.1 (10.0, 14.1) 0.61
UP/DP ratio 0.03 (0.03, 0.04) 0.02 (0.00, 0.02)a 0.03 (0.03, 0.4) 0.03 (0.02, 0.03) 0.88
Plasma
Urea (mmol/L) 5.4 (5.0, 5.7) 5.4 (5.0, 5.7) 5.5 (5.0, 5.9) 5.4 (5.0, 5.8) 0.06
Cr (umol/L) 72.5 (68.4, 76.7) 72.1 (68.2, 76.1) 74.4 (69.3, 79.4) 75.8 (70.9, 80.6)a 0.50
BUN/Cr ratio 18.9 (17.5, 20.2) 18.9 (17.6, 20.2) 18.4 (17.3, 19.5) 17.9 (16.7, 19.1) 0.13
eGFR (ml/min/1.73m2) 94.9 (90.6, 99.2) 95.4 (91.1, 99.7) 92.6 (86.9, 98.2) 90.3 (84.7, 96.0)a 0.85
cCrCl (ml/min/1.73 m2) 199.1 (167.4,
230.9)
197.1 (164.7,
229.4)
167.4 (140.3,
194.5)
173.2 (142.8,
203.6) 0.95
Potassium (mmol/L) 4.3 (4.2, 4.4) 4.3 (4.2, 4.4) 4.4 (4.3, 4.5) 4.4 (4.3, 4.5) 0.84
Abbreviations: LGI, low glycemic index; HF, high fiber; Cr, creatinine; ACR, albumin-creatinine ratio;
UP/DP ratio, urinary phosphorus to dietary phosphorus ratio; BUN/Cr ratio, blood urea nitrogen to
creatinine ratio; eGFR, estimated glomerular filtration rate, calculated using the MDRD modified formula
as: femaleifblackifagePCreGFR 742.0212.13.186 203.0154.1 , where PCr = plasma
creatinine; CCrCl, corrected creatinine clearance, calculated correcting for body surface area using Dubois
and Dubois formula as:
725.0425.0007184.0
73.1min)/(
)/(
cmheightkgweightbody
TimedLmgPCr
mlUvoldLmgUCr
CrClC
, where PCr, plasma creatinine;
UCr, urinary creatinine; Uvol, urinary volume. To convert creatinine in mmol/l to mg/dl divide by 88.4;
UP, urinary phosphorus; DP, dietary phosphorus. To convert phosphorus in mmol to mg/dl divide by
0.323.
Values are expressed in means (95% CIs). For plasma values, average of week -1 and week 0
represent baseline, and the average of weeks 8, 10 and 12 represent the end of the study. aSignificant difference (p < 0.05) within diet by LSMEANS
- mix model procedure.
bLog transformed values for statistical testing, change difference between diets was not statistically
different. Values expressed as non-Log transformed. cAdjusted for systolic and diastolic blood pressure, glycated hemoglobin, glycemic index and glycemic
load.
52
Figure 5.1. Study design and measurements
Anthropometric Measures & Blood Pressure
12 Weeks
Blood tests
7-day diet history
Pre-study STUDY
I Information session
S Screening visit
-1 Pre-study visit
24 hour urine collection
I S -1 0 2 4 8 10 12
53
57 Completed with 2 urine samples
3 Dropped out
3 Disliked diet
1 Urine sample missing
52 Completed with 2 urine samples
4 Dropped out
1 Busy, work related
1 Family issue
2 Unrelated health issues
4 Urine sample missing
64 Randomized to receive HF-wheat dietary
advice
1 Did not receive intervention and was
unaware of randomization
2 Randomized in error (HbA1c <6.5%)
249 Excluded
234 Ineligible
98 Health issues
85 HbA1c was too low (<6.5%)
51 HbA1c was too high (>8.5%)
15 Declined participation
11 Unable to start immediately
4 Could not be contacted
2131 Individuals responded to
study
768 Potentially eligible
380 Attended screening
131 Randomized
67 Randomized to receive LGI-pulse dietary
advice
1 Did not receive intervention and was
unaware of randomization
6 Randomized in error (HbA1c <6.5%)
60 Participants in the LGI-pulse diet
61 Participants in the HF-wheat diet
Figure 5.2. Consort flow diagram
54
.
Figure 5.3. Changes in dietary protein intake
Abbreviations: LGI, low glycemic index; HF, high fiber. Changes are given in means ± SEMs.
3.1
2
0
0.5
1
1.5
2
2.5
3
3.5
4
LGI-pulse diet HF-wheat diet
Tota
l pro
tein
inta
ke
(%
of
tota
l en
erg
y)
p = 0.068
0.07
0.01
-0.04
-0.02
0
0.02
0.04
0.06
0.08
0.1
0.12
LGI-pulse diet HF-wheat dietTota
l pro
tein
inta
ke
(g
/kg
/day
)
p = 0.128
A. Total protein intake
p = 0.012
-2.4
4.2
-8
-6
-4
-2
0
2
4
6
8
LGI-pulse diet HF-wheat diet
An
ima
l pro
tein
(g
/da
y)
p < 0.001
4.9
-5.2
-8
-6
-4
-2
0
2
4
6
8
LGI-pulse diet HF-wheat diet
Pla
nt
pro
tein
(g
/da
y)
B. Plant and animal protein intake
55
INTEGRATIVE DISCUSSION 7
Microalbuminuria has been consider as a marker of early renal damage and has been
considered a strong predictor of progression of renal disease in diabetes mellitus. Delaying
microalbuminuria by improving glycemic control and BP through blockage of the RAAS has
been proven in clinical trials[268-270]. The mechanisms are not yet established but it has been
suggested that active absorption of glucose from the diet and the glomerular filtrate mediated by
the SGLT 1 and 2, respectively[90], contribute to hyperglycemia, and this causes and increase in
ROS by activation of the four damaging-cell mechanisms (the polyol pathway, the AGE
pathway, the PKC pathway and the hexosamine pathway)[91, 92], resulting in an increase of O2-
production through inhibition of the glyceraldehyde-3-phosphate dehydrogenase[93] and
contributing to cellular damage and promotion of the accumulation and decrease of degradation
of the extra cellular membrane in the glomeruli. The mechanism by which hypertension can
contribute to renal damage has been hypothesized to be through and increase in the glomerular
pressure[4, 85] where chronic increases in glomerular pressures and blood flow can cause
adaptive changes in the glomerular basement membrane (hypertrophy and hyperplasia due to
mesangial expansion and thickening of the glomerular basement membrane resulting in deposits
of extra cellular membrane in the glomeruli)[3, 86]. Dietary pulses are low GI foods and rich in
high quality protein. The direct effect of pulses on renal function is not well known, but could be
indirectly attributed to the effect of pulses on improving blood glucose control and BP through
decreasing the proposed damaging-cell mechanisms of these conditions, decreasing ROS and
increasing NO.
We have previously observed an improvement in glycemic control and BP with the
consumption of a low GI diet in people with type 2 diabetes mellitus[38]. In an earlier
publication from the trial described in this thesis (chapter 5), we also showed that a LGI-pulse
diet improved glycemic control and BP in people with type 2 diabetes mellitus. Others have
suggested that plant protein could have a beneficial effects on renal function[21]. Even though
pulses have been recommended in national diabetes guidelines based on evidence for improving
long term blood glucose control[20], the general population in Canada do not consume dietary
pulses on regular basis. However, there is widespread bread consumption worldwide. We
therefore tested the hypothesis that a palatable low GI bread could be made from pulse flour that
56
would be suitable for higher plant protein diets and that the addition of pulses to a low GI diet of
patients with type 2 diabetes mellitus would be associated with an improvement in markers of
renal function. Our study demonstrated that a pulse bread with satisfactory GI, palatability and
high protein (compared to white bread) could be developed, making it a healthy choice for
individuals with diabetes. However, there is still a need for improvement in 2 aspects:
palatability and bread consistency. Our results also demonstrated that consumption of pulses as
part of a LGI diet did not show adverse effects on markers of kidney function (urinary urea,
urinary creatinine, urinary albumin, ACR, BUN/Cr ratio, urinary glucose, urinary Na+, urinary
phosphorus, blood urea, blood creatinine, eGFR, cCrCl and blood potassium) over 3 months,
allowing consumers to take advantage of the glycemic control and BP benefits. These data
support current dietary recommendations for DPI in patients with type 2 diabetes mellitus with
normal kidney function[20].
7.1 IMPLICATIONS
Dietary pulses are rich in high quality protein. Some of the most abundant AAs in pulses
are arginine and aspartic acid. Pulses are known to be high in lysine. High arginine to lysine ratio
has been implicated in lowering cardiovascular risk factors and progression of nephropathy[23].
Furthermore, arginine has been suggested to have a beneficial effect on vascular tone and
hemodynamics leading to lower BP[250], perhaps due to its function as a cofactor in NO (strong
vasodilator) production and RAAS inhibition[110]. Arginine, in high plasmatic concentrations,
enhances NO availability and improves vascular insulin sensitivity[104]. A meta-analysis on
controlled feeding trials looking at dietary pulse consumption and BP showed that dietary pulses
significantly reduced SBP and mean arterial pressure[42]. We also showed in the earlier
publication from our trial that a LGI-pulse diet improves long-term glycemic control and BP
compared with a high fiber diet[38]. In this trial, the increased in the arginine content of the LGI-
pulse diet was not statistically significant, however, it was for the HF-wheat diet which we could
hypothesize that levels of arginine within the LGI-pulse diet were sufficient enough to maintain
the coupling needed for NO production, but was perhaps not enough within the HF-wheat diet.
Although the mechanisms of action by which pulses may benefit on renal function still need to
be elucidated, pulses as part of a low GI diet seem to provide metabolic benefits, such as
glycemic and BP control in people with type 2 diabetes mellitus. Their lack of detrimental effects
57
on renal function in the short term, and their nutrient profile (rich in dietary fiber and high
protein) make pulses an appealing food for implementation in long term trials on renal function.
7.2 LIMITATIONS
This study had several limitations. 1) During the bread development, we only tested one
pulse bread that included 100% of pulse flour and was tested in healthy individuals only. Since
this bread was made with the intention to be use in all populations, it would have been ideal to
test it and compare it in individuals with type 2 diabetes mellitus. 2) The pulse bread palatability
was not statistically different from the control bread, in this case the control bread had low
palatability, and it may not have been representative of all white breads. 3) The AA content was
calculated and not chemically analyzed, even though the total AA content and total protein
analyzed were very similar, we are not certain that the total content of a single AA is what we are
expressing. 4) The RCT had a small number of participants with microalbuminuria and none
with CKD limiting the generalizability of the results. 5) The RCT may not have been long
enough to detect changes in microalbuminuria development. 6) We calculated eGFR with the
most appropriate formula, to our knowledge, for participants with type 2 diabetes mellitus with
normal renal function. However, there is uncertainty as to which method is the best way to
estimate the filtration rate. 7) Association of high-normal levels of serum phosphorus has been
seen with doubling the risk of developing CKD and ESRD, in our study, we saw an increase in
dietary phosphorus intake and a decrease in urinary phosphorus loss, but we did not have serum
phosphorus levels. 8) The GI, GL, HbA1c and BP might have confounded effects on markers of
renal function since they might be implicated in delaying the progression of renal dysfunction.
Even though we did not see any significant difference on markers of renal function between
diets, we believe that this lack of response was mainly due to the small sample size. Lastly, the
expected treatment difference in total protein intake was not seen. We aimed for a 5% of total
protein difference, but this was not achieved. This limitation, on the contrary, allowed us to
isolate the effect of plant protein, but unfortunately we believe that GI may have been a
confounding factor.
7.3 FUTURE RESEARCH
With respect to bread development, there is a need to develop a variety of pulse breads
mainly with black bean, kidney bean and lentils among others and to test them in combination
58
with wheat flour to compare GI, palatability and furthermore, the bread consistency. Since in our
study, the GI response to the pulse bread and the positive control bread (C+) were not similar
even though they were created with similar protein concentration and fiber content, makes us
wonder if future research should be done in more than 10 individuals. As per the RCT, the use of
a low GI diet was an important confounder since it has been shown within our previous
published results that a low GI diet could be the main responsible factor in lowering BP by 4.5
mmHg, and improving glycemic control by 0.5% in absolute HbA1c. Therefore, further trials
including ideally four groups with LGI diets with and without pulses and medium GI diets with
and without pulses, long term (>3months) and involving individuals at different stages of renal
disease are needed in order to provide more conclusive information on the benefits that pulses
could have on renal function.
59
SUMMARY
In summary, the aim of this thesis was to produce a palatable low GI bread from pulse flour
that could be suitable for higher plant protein diets, and to assess the effect of dietary pulses as
part of a low GI diet on markers of renal function in participants with type 2 diabetes mellitus.
We have demonstrated the following:
1) A pulse bread with acceptable GI and palatability was developed.
2) In the short term, consumption of dietary pulses as part of a low GI diet did not have
adverse effects on markers of renal function.
60
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81
APPENDICES
APPENDIX TABLES
Chapter 2
Appendix table 2.1.1. Amino acid content in foods
Amino acids
(g per 100 g of
protein)
FOODS
Pulsesa Nuts
b Soy Seeds
c Beef Chicken Fish
d Eggs Milk
Tryptophan 1.1 1.1 1.4 1.5 1.2 1.2 1.1 1.4 1.2
Threonine 4.1 3.0 4.1 3.4 4.7 4.5 4.6 4.3 3.9
Isoleucine 4.7 3.7 4.6 4.2 4.5 5.6 4.8 5.2 4.8
Leucine 8.2 7.0 7.7 6.8 8.5 8.0 8.3 8.5 8.9
Lysine 7.1 3.4 6.3 3.9 9.3 9.1 9.4 7.0 7.7
Methionine 1.4 2.0 1.3 1.9 3.0 2.9 3.0 2.9 2.4
Cystine 1.2 1.7 1.5 1.4 1.1 1.4 1.1 2.1 0.6
Phenylalanine 5.6 4.7 4.9 4.9 4.0 4.2 4.1 5.3 4.8
Tyrosine 2.8 2.7 3.6 2.9 3.7 3.6 3.5 3.9 4.8
Valine 5.5 4.9 4.7 5.1 4.7 5.3 5.2 6.7 6.3
Arginine 7.3 12.9 7.3 12.4 6.9 6.4 6.3 6.1 2.7
Histidine 2.9 2.5 2.5 2.4 3.4 3.3 2.8 2.5 3.0
Alanine 4.5 4.3 4.5 4.5 5.9 5.8 6.2 5.6 3.3
Aspartic acid 12.6 9.9 11.9 9.5 9.5 9.5 10.9 10.1 8.0
Glutamic acid 16.6 22.1 18.3 20.2 16.8 16.0 15.7 13.6 21.1
Glycine 4.2 5.0 4.4 5.8 4.6 5.2 5.1 3.3 1.8
Proline 4.7 4.1 5.5 4.2 4.2 4.4 3.7 4.4 9.2
Serine 5.6 5.0 5.5 4.7 4.1 3.7 4.2 7.3 5.7
Protein 100 100 100 100 100 100 100 100 100
USDA Nutrient Database for Standard Reference, Release 26. aMean content for chickpeas, lentils, navy beans, white beans and kidney beans.
bMean content for macadamia nut, pistachio, walnuts, almond, cashew, hazelnut, pecan, pine nut
and Brazil nut. cMean content for sunflower seed, pumpkin and squash seed, and flax seed.
dMean content for tilapia, Atlantic salmon and Atlantic cod fish.
82
Chapter 4
Appendix table 4.1.2. Amino acid content in grams per 100 grams of total protein
Bread C T C+ CB3XG C3XG CB
Essential or indispensable
Histidinefh
2.2 2.7 2.4 2.3 2.2 2.5
Isoleucinecgh
3.5 4.3 3.5 3.4 3.5 3.4
Leucinecgh
6.9 7.1 6.7 6.8 6.9 6.5
Lysinefh
2.6 6.8 2.9 2.5 2.3 3.4
Methionineach
1.7 1.3 1.7 1.7 1.8 1.6
Phenylalaninebch
5.0 5.3 4.7 4.9 5.0 4.4
Threoninedh
2.9 3.8 3.0 2.8 2.8 3.1
Tryptophanbch
1.2 1.0 1.4 1.3 1.2 1.5
Valinecgh
4.1 4.3 4.3 4.1 4.0 4.4
Non-essential or dispensable
Argininefh
4.1 9.2 4.8 4.4 4.1 5.5
Alaninech
3.4 4.4 3.7 3.5 3.3 4.2
Aspartic acideh
4.6 11.7 5.2 4.7 4.3 6.0
Cysteinead
2.1 1.3 2.1 2.1 2.1 2.2
Glutamic acide 32.5 17.4 29.3 31.6 33.4 25.4
Glycinebh
3.7 4.2 4.1 3.9 3.6 4.7
Prolinech
11.1 4.1 9.8 10.8 11.5 8.3
Serinedh
5.0 5.0 4.8 4.9 5.0 4.7
Tyrosinebdh
3.0 2.5 3.0 3.0 3.0 2.9
TOTAL 99.6 96.4 97.4 98.7 99.9 94.7
Abbreviations: GI, glycemic index; C, Control bread; T, test bread; C+, positive control bread with wheat
bran and gluten; CB3XG, C bread with wheat bran and extra gluten; C3XG, C bread with extra gluten; CB,
C bread with wheat bran.
Calculations were done using the Food Processor SQL version 10.9.0 and products from the USDA food
database. aSulfur containing amino acids.
bAromatic amino acids.
cNon-polar amino acids.
dPolar amino acids.
eAcid-polar amino acids.
fBasic-polar amino acids.
gBranched-chain amino acids.
hInsulinogenic amino acids.
83
Appendix table 4.2.3. Glucogenic amino acids in grams per 100 grams of total protein
Bread C T C+ CB3XG C3XG CB
Alanine 3.4 4.4 3.7 3.5 3.3 4.2
Arginine 4.1 9.2 4.8 4.4 4.1 5.5
Aspartic acid 4.6 11.7 5.2 4.7 4.3 6.0
Cysteine 2.1 1.3 2.1 2.1 2.1 2.2
Glutamic acid 32.5 17.4 29.3 31.6 33.4 25.4
Glycine 3.7 4.2 4.1 3.9 3.6 4.7
Histidine 2.2 2.7 2.4 2.3 2.2 2.5
Methionine 1.7 1.3 1.7 1.7 1.8 1.6
Proline 11.1 4.1 9.8 10.8 11.5 8.3
Serine 5.0 5.0 4.8 4.9 5.0 4.7
Valine 4.1 4.3 4.3 4.1 4.0 4.4
TOTAL 74.5 65.6 72.2 74 75.3 69.5
Abbreviations: GI, glycemic index; C, Control bread; T, test bread; C+, positive control bread with wheat
bran and gluten; CB3XG, C bread with wheat bran and extra gluten; C3XG, C bread with extra gluten; CB,
C bread with wheat bran.
Calculations were done using the Food Processor SQL version 10.9.0 and products from the USDA food
database.
84
Appendix table 4.3.4. Insulinogenic amino acids in grams per 100 grams of total protein
Bread C T C+ CB3XG C3XG CB
Histidine 2.2 2.7 2.4 2.3 2.2 2.5
Isoleucine 3.5 4.3 3.5 3.4 3.5 3.4
Leucine 6.9 7.1 6.7 6.8 6.9 6.5
Lysine 2.6 6.8 2.9 2.5 2.3 3.4
Methionine 1.7 1.3 1.7 1.7 1.8 1.6
Phenylalanine 5.0 5.3 4.7 4.9 5.0 4.4
Threonine 2.9 3.8 3.0 2.8 2.8 3.1
Tryptophan 1.2 1.0 1.4 1.3 1.2 1.5
Valine 4.1 4.3 4.3 4.1 4.0 4.4
Arginine 4.1 9.2 4.8 4.4 4.1 5.5
Alanine 3.4 4.4 3.7 3.5 3.3 4.2
Aspartic acid 4.6 11.7 5.2 4.7 4.3 6.0
Glycine 3.7 4.2 4.1 3.9 3.6 4.7
Proline 11.1 4.1 9.8 10.8 11.5 8.3
Serine 5.0 5.0 4.8 4.9 5.0 4.7
Tyrosine 3.0 2.5 3.0 3.0 3.0 2.9
TOTAL 65 77.7 66 65 64.5 67.1
Abbreviations: GI, glycemic index; C, Control bread; T, test bread; C+, positive control bread with wheat
bran and gluten; CB3XG, C bread with wheat bran and extra gluten; C3XG, C bread with extra gluten; CB,
C bread with wheat bran.
Calculations were done using the Food Processor SQL version 10.9.0 and products from the USDA food
database.
85
Chapter 5.
Appendix table 5.1.5. Foods for the LGI-pulse diet
Choose Portion Size AVOID
2
servings
Pulses Beans- red, navy, white, kidney.
Lentils-red, green
Chick peas
Hummus
1/2 c cooked,
canned,
½ c
½ c prepared
____
servings
Cereal All Bran Buds with Psyllium
Oat Bran
Red River Cereal
1/3 c
1/3c dry
2 Tbsp. dry
All other cereal
Pancakes, muffins,
Breads Linseed Bread (Mestemacher)
PC Blue Menu Tortilla
(Chipotle, Jalapeno)
½ pita
1 slice
1 piece
All other breads
Bagel, pita, tortilla,
buns, rolls
Donuts, pastries
Other
Starchy
Food
Barley (use as rice replacement)
Pasta (al dente)
Parboiled rice
Bulgur
½ c cooked
1/3 c cooked
“
“
Potatoes
White, brown rice
Basmati rice
Rice noodles
Crackers, cookies
3
servings
Fruits Apple,
Orange,
Blueberries, Raspberries
Strawberries
1 small
1 medium
1 cup
1 ½ cups
Ripe banana
Grapes, raisins
Pineapple, mango
Papaya, melon
Canned fruit
5 or
more
servings
Vegetables
All , except potato ½ cup Potato
3
servings
Dairy Low fat, low sugar yogurt
Skim, 1% milk; soy beverage
Cheese <15%mf
1 c
1 c
45 g
Cream, ice cream,
Cheese > 15%mf
Butter
2
servings
Meat, fish
and
alternates
Lean meat, poultry, fish,
Soy, tofu, seitan
Nuts (almonds, walnuts, …)
Egg
60-90 g
(deck of
cards)
10
1-2
Fatty meats, sausage
Snacks,
desserts
Fruit, vegetables
Nuts
Yogurt
As listed
above
Crackers,
Cakes, cookies
Chips, popcorn
Spreads Hummus, bean spread
Peanut/Nut butter
Soft Margarine
Jam (reduced sugar)
Low fat cottage cheese/ricotta
Red pepper spread, salsa
Jam with sugar
butter
Drinks Water, tea, coffee
Sugar-free drinks
Vegetable juice (low salt)
Fruit juice
Regular pop
86
Appendix table 5.2.6. Foods for the HF-wheat diet
Choose Portion Size AVOID
___
servings
Breads Dempster’s whole wheat,
Ryvita, Finn Crisp crackers
1 slice (40g)
3
White bread, bagels,
pita, buns
Cereal Bran flakes, Corn Bran
Weetabix, Shredded Wheat
Cream of wheat
¾ cup
1 biscuit
20 g. dry
Pancakes,muffins,donut
s Oatmeal, Red River,
Bran buds
Other
Starchy
Food
Potatoes – baked, boiled
Brown rice
Couscous
½ cup
1/3 cup
1/3 cup
Pasta, Barley
Beans/lentils/chickpeas
French fries
3
servings
Fruits
Banana
Grapes
Pineapple
Mango, Papaya
Watermelon
Raisins
Cantaloupe
guava
½ large ,4”
15
¾ cup
½ fruit
1 ½ cups
mini box
1 cup cubed
1 ½
Apples, Pears
Oranges , Citrus fruits
Peaches
All berries
5
servings
or more
Vegetables
All vegetables except > ½ cup Beans, lentils,
chickpeas
3
servings
Dairy
Low fat yogurt
Skim or 1% milk, soy
beverage
Hard cheese < 15% MF
250 g
250g
45 g.
Cream, Ice cream,
Cheese (>15% MF)
2
servings
Meat, fish
and
alternates
Lean meat, poultry, fish
Soy, tofu, seitan
egg
60-90 g
"
1-2
Fatty meats, sausage
nuts
Snacks
and
Desserts
Raw vegetables
Low fat yogurt
Fruit, as above
Breads, crackers as above
White crackers
Potato chips
Corn/tortilla chips
Cakes/cookies/wafers
Nuts
Spreads Red pepper spread
Guacamole (avocado spread)
Soft margarine, Jam (low
sugar)
Low-fat cottage/ricotta
cheese
Jam with sugar
Hummus
Butter
Peanut butter
Drinks Water, tea, coffee
Sugar-free drinks
Vegetable juice (low salt)
Fruit juice
Regular soft drinks
87
Appendix table 5.3.7. Compliance check list for the LGI-pulse diet
Patient I.D:________ Compliance Checklist: Diet Type: LGI-pulse
Week:_____
DIET CARBOHYDRATES 15 Gram Equivalents
Starchy Food Serving
Size
Day
1
Day
2
Day
3
Day
4
Day
5
Day
6
Day
7
Week
Total
2 Beans / Lentils /
hummus
½ cup
cooked
servings
All Bran Buds
with psyllium
fibre
⅓ cup
Oat bran ⅓ cup dry
Red River Cereal 2 Tbsp.
dry
Bread -Finland
Rye by Pita Break
Mestemacher –
Linseed Bread
PC Blue Menu
Tortillas
(Chipotle,
Jalapeno)
½ pita
1 slice
1 Tortilla
Barley ⅓ cup
cooked
Parboiled Rice “al
dente”
⅓ cup
cooked
Bulgur ½ cup
cooked
Pasta “al dente”
(undercooked)
⅓ cup
cooked
Peas / corn (fresh) ⅓ cup
3
servings
Fruit – apple,
orange, berries
See sheet
OTHER CARBOHYDRATE
Food Group Serving
Size
Day
1
Day
2
Day
3
Day
4
Day
5
Day
6
Day
7
Week
Total
5 or
more
Vegetables ½ cup
Milk , low fat
yogurt
1 cup
(250 g)
88
Appendix table 5.4.8. Compliance check list for the HF-wheat diet
Patient I.D.: ________ Compliance Checklist: Diet Type: HF-wheat
Week:_____ DIET CARBOHYDRATES 15 Gram Equivalents
Starchy Food Serving
Size
Day
1
Day
2
Day
3
Day
4
Day
5
Day
6
Day
7
Week
Total
servings
Dempster’s
whole wheat
bread
1 slice
(40g)
Ryvita, Finn
Crisp Crackers
3
Bran flakes,
corn bran
¾ cup
Weetabix,
shredded wheat
1 biscuit
Cream of
wheat
20 g dry
Potatoes ½
medium
Brown rice,
couscous
⅓ cup
cooked
3
servings
Fruit – banana,
cantaloupe,
watermelon,
grapes, raisins,
pineapple, mango,
papaya
(see sheet)
OTHER CARBOHYDRATE
Food Group Serving
Size
Day
1
Day
2
Day
3
Day
4
Day
5
Day
6
Day
7
Week
Total
5 or
more
Vegetables ½ cup
3 Milk / Yogurt 250 g
89
Appendix table 5.5.9. Anthropometric measurements and BP
LGI-pulse diet (n = 52) HF-wheat diet (n = 57)
p-
value
Baseline End of Study Baseline End of Study
Weight (kg) 86.6 (80.9, 92.4) 83.9 (78.4, 89.4)a 82.7 (78.1, 89.3) 80.8 (76.4, 85.2) a 0.07
BMI (kg/m2) 31.6 (29.7, 33.5) 30.6 (28.8, 32.3)a 30 (28.5, 31.5) 29.3 (27.9, 30.8) a 0.05
WC (cm) 106.7 (102.3, 111.0) 103.9 (99.7, 108.2)a 102 (98.6, 105.5) 100.2 (96.8, 103.5)a 0.28
SBP (mmHg) 121.8 (119.2, 124.3) 117.8 (115.2, 120.5)a 118.9 (115.4, 122.4) 118.9 (115.9, 121.9) 0.02
DBP (mmHg) 71.4 (69.2, 73.7) 68.4 (66.3, 70.4)a 69.7 (67.3, 72.1) 69.4 (67.2, 71.6) 0.01
Abbreviations: LGI, low glycemic index; HF, high fiber; BMI, body mass index (calculated as
weight in kilograms divided by height in meters squared); WC, waist circumference (measured at
navel level); SBP, systolic blood pressure; DBP, diastolic blood pressure.
Values are expressed in means (95% CIs). Average measurements were used for baseline and
end of the study values. Baseline values were obtained from screening and week 0. End of study
values were obtained from week 8, 10 and 12. aSignificant differences (p < 0.05) within or between LGI-pulse diet and HF-wheat diet using the
LSMEANS - mix model procedure.
90
Appendix table 5.6.10. Dietary amino acid content
Aminoacid
(g/day) LGI-pulse diet (n = 52) HF-wheat diet (n = 57)
p-
val
ue
Baseline End of Study Baseline End of Study
Alanine 3.4 (3.1, 3.6) 3.4 (3.1, 3.6) 3.1 (2.8, 3.3) 3.1 (2.8, 3.3) 0.76
Arginine 4.0 (3.7, 4.4) 4.2 (3.9, 4.6) 3.8 (3.5, 4.1) 3.4 (3.2, 3.7) a <0.01
Aspartic Acid 6.3 (5.8, 6.8) 6.7 (6.3, 7.2) a 5.9 (5.5, 6.4) 5.6 (5.2, 6.0) <0.01
Cystine 1.0 (1.0, 1.1) 1.0 (0.9, 1.0) 1.0 (0.9, 1.1) 1.0 (0.9, 1.0) 0.44
Glutamate 13.7 (12.7, 14.6) 12.4 (11.6, 13.3) a 12.6 (11.7, 13.4) 12.1 (11.3, 12.9) 0.19
Glycine 3.0 (2.8, 3.3) 3.0 (2.8, 3.3) 2.8 (2.6, 3.0) 2.6 (2.4, 2.8) 0.21
Histidine 1.9 (1.8, 2.1) 1.9 (1.8, 2.1) 1.8 (1.6, 1.9) 1.8 (1.6, 1.9) 0.93
Isoleucine 3.2 (3.0, 3.4) 3.2 (3.0, 3.4) 2.9 (2.7, 3.2) 3.0 (2.7, 3.2) 0.94
Leucine 5.4 (5.0, 5.8) 5.5 (5.1, 5.8) 5.0 (4.7, 5.4) 5.0 (4.6, 5.3) 0.70
Lysine 4.7 (4.3, 5.0) 4.9 (4.6, 5.3) 4.3 (3.9, 4.7) 4.5 (4.1, 4.9) 0.73
Methionine 1.6 (1.4, 1.7) 1.5 (1.4, 1.6) 1.4 (1.3, 1.6) 1.5 (1.4, 1.6) 0.19
Phenylalanine 3.1 (2.9, 3.3) 3.2 (3.0, 3.4) 2.9 (2.7, 3.1) 2.8 (2.6, 3.0) 0.28
Proline 4.3 (4.0, 4.6) 3.9 (3.7, 4.2) a 4.0 (3.7, 4.3) 4.0 (3.7, 4.3) 0.04
Serine 3.1 (2.9, 3.3) 3.2 (3.0, 3.4) 2.9 (2.7, 3.1) 2.8 (2.6, 3.0) 0.17
Theonine 2.6 (2.4, 2.9) 2.7 (2.5, 2.9) 2.4 (2.2, 2.6) 2.4 (2.2, 2.6) 0.90
Tryptophan 0.8 (0.7, 0.9) 0.8 (0.7, 0.8) 0.8 (0.7, 0.8) 0.7 (0.7, 0.8) 0.74
Tyrosine 2.3 (2.2, 2.5) 2.3 (2.1, 2.5) 2.2 (2.0, 2.3) 2.2 (2.0, 2.4) 0.75
Valine 3.6 (3.3, 3.8) 3.6 (3.4, 3.9) 3.3 (3.1, 3.6) 3.3 (3.1, 3.6) 0.73
Abbreviations: LGI, low glycemic index; HF, high fiber
Values are expressed in means (95% CIs). Average measurements were used for baseline and
end of the study values. Baseline values were obtained from screening and week 0. End of study
values were obtained from week 8, 10 and 12. aSignificant differences (p < 0.05) within or between LGI-pulse diet and HF-wheat diet using the
LSMEANS - mix model procedure.
91
APPENDIX FIGURES
Chapter 4
Appendix figure 4.1.1. Total protein content measured and calculated for all breads based
on 25 g of available carbohydrate
Abbreviations: C, Control bread (white flour); T, test bread (100% chickpea flour); C+, positive control
for T bread (white flour + wheat bran + gluten); CB3XG, C bread with fiber and protein added (white
flour + wheat bran + 3 times the amount of gluten in T bread); C3XG, C bread with protein added (white
flour + 3 times the amount of gluten in T bread); CB, C bread with fiber (white flour + wheat bran).
4.7
10.411.3
29.828.9
7.5
4.96
10.99 11.94
31.4830.53
7.92
0
5
10
15
20
25
30
35
C T C+ C3XG CB3XG CB
Tota
l pro
tein
(g)
BREAD
Total protein content per 25 g of available carbohydrate
Measured
Calculated
92
Chapter 5
Appendix figure 5.1.2. Percentage of plant protein from pulse source
Appendix figure 5.2.3. Change in Glycemic Index
Abbreviations: LGI, low glycemic index; HF, high fiber. Changes are given in means ± SEMs.
40%
60%
LGI-pulse diet
Plant protein from pulses
Plant protein from other vegetables
1%
99%
HF-wheat diet
LGI-puse dietMean plant protein intake: 39.6 g/day
HF-wheat dietMean plant protein intake: 27.0 g/day
-14.7
3.6
-20
-15
-10
-5
0
5
10
LGI-pulse diet HF-wheat diet
Chan
ge in
gly
cem
ic In
dex
p < 0.001
93
Appendix figure 5.3.4. Microalbuminuria
Data were evaluated by Fisher's exact test.
0
1
2
3
4
5
6
7
8
Baseline Baseline End of Study End of Study
# o
f p
arti
cip
ants
wit
h m
icro
alb
um
inu
ria
(>3
0 m
g/d
ay)
LGI-pulse diet (n =52) HF-wheat diet (n =57)
p = 0.76p = 0.25
58.3%
41.6%
54.5%
45.5%
94
Appendix figure 5.4.5. Correlations between changes in DPI with changes in markers of
renal function
r = 0.23, p=0.01
-0.5
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
0.5
0.6
-300 -200 -100 0 100 200 300
Ch
ange
in d
ieta
ry p
rote
in (
g/kg
/day
)
Change in urinary urea (mmol/day)
r=0.22, p=0.02
-30
-20
-10
0
10
20
30
40
-300 -200 -100 0 100 200 300
Ch
ange
in a
nim
al p
rote
in (
g/d
ay)
Change in urinary urea (mmol/day)
r=0.22, p=0.02
-30
-20
-10
0
10
20
30
40
-10 -5 0 5 10
Ch
ange
in a
nim
al p
rote
in (
g/d
ay)
Change in urinary creatinine (mmol/day)
r=0.25, p=0.01
-0.5
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
0.5
0.6
-4 -3 -2 -1 0 1 2 3
Ch
ange
in d
ieta
ry p
ort
ein
(g/
kg/d
ay)
Change in urinary glucose (mmol/day)
r=0.29, p=0.002
-30
-20
-10
0
10
20
30
40
-4 -3 -2 -1 0 1 2 3
Ch
ange
in a
nim
al p
ort
ein
(g/
day
)
Change in urinary glucose (mmol/day)
r=-0.20, p=0.04
-60
-40
-20
0
20
40
60
80
100
-30 -20 -10 0 10 20 30
Ch
ange
in p
rote
in f
rom
pu
lse
s (%
/ve
geta
ble
pro
tein
)
Change in urinary phosphorus (mmol/day)
r=-0.26, p=0.01
-10
-5
0
5
10
15
-3 -2 -1 0 1 2 3
Ch
ange
in d
ieta
ry p
rote
in
(% o
f to
tal e
ne
rgy
inta
ke)
Change in blood urea (mmol/day)
r=-0.23, p=0.02
-10
-5
0
5
10
15
-3 -2 -1 0 1 2 3
Ch
ange
in a
nim
al p
rote
in (
g/d
ay)
Change in blood urea (mmol/day)
r=-0.21, p=0.03
-10
-5
0
5
10
15
20
-20 -15 -10 -5 0 5 10 15 20
Ch
ange
in a
nim
al p
rote
in (
g/d
ay)
Change in blood creatinine (mmol/day)
r=-0.20, p=0.04
-0.5
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
0.5
0.6
0 20 40 60 80 100 120
Ch
ange
in d
ieta
ry p
rote
in (
g/kg
/day
)
Change in blood potassium (mmol/L)
95
Appendix figure 5.5.6. Correlations by changes in dietary protein with changes in BP,
HbA1c, GI, and GL.
r=-0.22, p=0.02
-15
-10
-5
0
5
10
15
20
25
30
35
40
-0.02 -0.015 -0.01 -0.005 0 0.005 0.01
Chan
ge in
prot
ein
from
pul
ses
(g/d
ay)
Change in HbA1c (%)
r=-0.22, p=0.02
-60
-40
-20
0
20
40
60
80
100
-0.02 -0.015 -0.01 -0.005 0 0.005 0.01
Ch
ange
inp
rote
in fr
om
pu
lses
(%
of
pla
nt
pro
tein
)
Change in HbA1c (%)
r=-0.22, p=0.02
-30
-20
-10
0
10
20
30
40
-0.02 -0.015 -0.01 -0.005 0 0.005 0.01
Chan
ge d
ieta
ry p
ulse
s (g
/day
)
Change in HbA1c (%)
r=-0.22, p=0.02
-30
-20
-10
0
10
20
30
40
-0.02 -0.015 -0.01 -0.005 0 0.005 0.01Ch
ange
an
imal
pro
tein
(g/d
ay)
Change in HbA1c (%)
r=--0.48, p<0.001
-50
-40
-30
-20
-10
0
10
20
30
40
-40 -30 -20 -10 0 10 20 30
Chan
ge in
pla
nt p
rote
in (g
/day
)
Change in GI (bread scale)
r=--0.76, p<0.001
-200
-100
0
100
200
300
400
500
600
-40 -30 -20 -10 0 10 20 30
Ch
ange
in d
ieta
ry p
uls
es
(g/d
ay)
Change in GI (bread scale)
r=--0.76, p<0.001
-60
-40
-20
0
20
40
60
80
100
-40 -30 -20 -10 0 10 20 30Ch
ange
in d
ieta
ry p
uls
es
(%
of
pla
nt
pro
tein
)
Change in GI (bread scale)
r=--0.76, p<0.001
-15
-10
-5
0
5
10
15
20
25
30
35
40
-40 -30 -20 -10 0 10 20 30
Ch
ange
in p
uls
e p
rote
in (
g/d
ay)
Change in GI (bread scale)
r=--0.29, p=0.002
-10
-5
0
5
10
15
20
-40 -30 -20 -10 0 10 20 30
Ch
ange
in a
nim
al p
rote
in (
g/d
ay)
Change in GI (bread scale)
96
Appendix figure 5.5.6. continues...
Abbreviations: HbA1c, glycated hemoglobin; GI, glycemic index.
r=-0.46, p<0.001
-10
-5
0
5
10
15
-150 -100 -50 0 50 100
Ch
ange
in d
ieta
ry p
rote
in
(% o
f to
tal e
ne
rgy
inta
ke)
Change in glycemic load
r=0.24, p=0.01
-0.5
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
0.5
0.6
-150 -100 -50 0 50 100
Ch
ange
in d
ieta
ry p
rote
in
(g/k
g/d
ay)
Change in glycemic load
r=-0.33, p<0.001
-15
-10
-5
0
5
10
15
20
25
30
35
40
-150 -100 -50 0 50 100
Ch
ange
in p
rote
in f
rom
die
tary
pu
lse
s
(g/d
ay)
Change in glycemic load
r=-0.36, p<0.001
-60
-40
-20
0
20
40
60
80
100
-150 -100 -50 0 50 100
Ch
ange
in p
uls
e p
rote
in
(% o
f to
tal v
ege
tab
le p
rote
in)
Change in glycemic load
r=-0.33, p<0.001
-200
-100
0
100
200
300
400
500
600
-150 -100 -50 0 50 100Ch
ange
in p
uls
e i
nta
ke (
g/d
ay)
Change in glycemic load
97
Appendix figure 5.6.7. Correlations by changes in animal protein and plant protein, with
changes in HbA1c, blood glucose, dietary phosphorus, urinary phosphorus, and ratio of
urinary phosphorus to dietary phosphorus.
Abbreviations: HbA1c, glycated hemoglobin; UP/DP ratio, urinary phosphorus to dietary phosphorus ratio.
r=0.23, p=0.02
-30
-20
-10
0
10
20
30
40
-0.02 -0.015 -0.01 -0.005 0 0.005 0.01
Ch
ange
in a
nim
al p
rote
in in
take
(g/
day
)
Change in HbA1c
r=0.59, p<0.001
-50
-40
-30
-20
-10
0
10
20
30
40
-1000 -500 0 500 1000 1500
Ch
ange
in p
lan
t p
rote
in in
take
(g/
day
)
Change in dietary phosphorus (mg/day)
r=0.34, p<0.001
-30
-20
-10
0
10
20
30
40
-1000 -500 0 500 1000 1500
Ch
ange
in a
nim
al p
rote
in in
take
(g/
day
)
Change in dietary phosphorus (mg/day)
r=-0.23, p=0.02-0.1
-0.08
-0.06
-0.04
-0.02
0
0.02
0.04
0.06
0.08
-50 -40 -30 -20 -10 0 10 20 30 40
Ch
ange
in p
lan
t p
rote
in in
take
(g/
day
)
Change in UP/DP ratio
