Resveratrol and Metformin Combination Therapy in

Transcription

Prevention and Treatment of Insulin Resistance
by
Scott Frendo-Cumbo
A Thesis
Presented to
The University of Guelph
In partial fulfillment of requirements
for the degree of
Master of Science
in
Human Health and Nutritional Sciences
Guelph, Ontario, Canada
© Scott Frendo-Cumbo, August, 2015
Abstract
Scott Frendo-Cumbo
University of Guelph, 2015
Advisor:
Dr. David C. Wright
We sought to examine the combined (COM) effects of resveratrol (RSV), a polyphenol,
and metformin (MET), a commonly prescribed anti-diabetic drug, in treatment and prevention of
insulin-resistance. For examination of treatment effects, mice were fed a low (LFD) or high
(HFD) fat diet to induce insulin-resistance. HFD mice were then separated into control HFD,
MET, RSV, and COM. COM improved glucose and insulin tolerance compared to HFD. MET
improved insulin tolerance, while RSV had no independent effects. COM increased insulinstimulated phosphorylation of Akt in triceps and scAT. To examine prevention effects, mice
were separated into LFD, HFD, MET, RSV and COM at the onset of dietary interventions. MET,
RSV and COM therapy prevented HFD-induced glucose intolerance and exhibited significantly
greater insulin tolerance compared to HFD. COM increased Akt phosphorylation in triceps and
scAT compared to HFD. RSV, MET and COM increased eWAT Akt phosphorylation compared
to HFD.
Acknowledgements
To my advisor, Dr. David Wright, thank you for giving me so many opportunities to succeed and
grow. Your guidance and insight into not only my project, but also science as a whole and the
political aspects that go with it has been amazing. You gave me the opportunity to work on
multiple projects and travel to other labs to learn additional techniques, which has helped me
gain an appreciation for the importance of being able to balance multiple projects and maintain
connections with other researchers. Thank you for putting up with me for 2 years and everything
you have done for me in that time.
To Dr. David Dyck, thank you for your help with the design of my study and your advice
throughout my Masters. I appreciate that you were always willing to stop and talk to me, whether
about science or just making conversation in the hallway. I’d like to thank Dr. Lindsay Robinson
for chairing my defense and giving me an understanding of inflammatory processes in her
graduate course that proved very useful in my project.
I would like to thank Dr. Matthew Watt for giving me the opportunity to work in his lab
and mentoring me. You taught me a lot of new techniques and gave me an appreciation for living
a balanced life-style of working hard but taking time to relax. To Dr. Sandra Peters, thank you
for introducing me to Dr. David Wright and helping me get set up with my Masters at Guelph.
But most of all, thank you for sparking my interest in scientific research and continuing to be
there for me to talk science. Thank you to Dr. Rebecca Macpherson for all of your help from my
undergraduate thesis at Brock to my Masters at Guelph. You have helped me understand things
in lab and are always there to talk to.
To my Guelph lab mates Will, Zac, Laura, Tara, Charlie and Laelie, thank you for all of
our science talks and putting up with me. I have really enjoyed working with all of you and I
don’t think I will ever again experience working with such a good group of people. A special
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thanks to the A-Team (Andra, Anne and Ann), Diana, Andy and Becky for all of their help
keeping me, my animals and our lab organized. I would also like to thank Jen, Tom, Dave, Pom,
Maria, Ruth, Stacey, Arthe and Ruzaidi from Dr. Watt’s lab at Monash for teaching me and
making it really easy for me to get comfortable in a new lab and new country. I really appreciate
everything you guys did for me and I hope to see you all again soon.
To my family, thank you for always being there and supporting me in whatever I do. You
have given me the confidence to pursue whatever I set my mind to. To my parents, I have
modeled my drive and sense of humour off you both and I really appreciate everything you do
for me. To Monika, thanks for everything you have done for me. You have really helped me get
through my Masters and were always there when I needed you. I can’t wait to begin the next
chapter of our lives together in Toronto.
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Table of Contents
Abstract ................................................................................................................................................... ii Acknowledgements ............................................................................................................................ iii Table of Contents .................................................................................................................................. v List of Tables ....................................................................................................................................... viii List of Figures ....................................................................................................................................... ix List of Abbreviations .......................................................................................................................... xi Chapter 1: Literature Review ........................................................................................................... 1 1.1. Introduction ........................................................................................................................................... 1 1.2. Insulin and Glucose Homeostasis ................................................................................................... 2 1.3. Insulin Resistance ................................................................................................................................ 3 1.3.1 The Pathophysiology of Insulin Resistance ............................................................................................... 5 1.3.2 Lipotoxicity .............................................................................................................................................................. 6 1.3.3 Inflammation ........................................................................................................................................................... 8 1.3.4 Mitochondrial Dysfunction ............................................................................................................................ 10 1.4. Current Treatments ......................................................................................................................... 12 1.4.1 Thiazolidinedione’s (TZDs) ........................................................................................................................... 12 1.4.2 Metformin (MET) ............................................................................................................................................... 15 1.4.3 Combination Therapy: Thiazolidinedione’s & Metformin ................................................................ 18 1.5. Resveratrol (RSV) ............................................................................................................................. 18 1.5.1 Combination Therapy: Potential of Resveratrol ................................................................................... 24 1.6. Conclusion & Future Directions ................................................................................................... 26 Chapter 2: Aims of Thesis ................................................................................................................ 28 Chapter 3: Resveratrol and Metformin Combination Therapy in Prevention and Treatment of Insulin Resistance ................................................................................................... 30 3.1 Methods ..................................................................................................................................................... 30 3.1.1 Materials ................................................................................................................................................................ 30 v
3.1.2 Experimental Design ......................................................................................................................................... 31 3.1.3 Glucose and Insulin Tolerance Testing ..................................................................................................... 33 3.1.4 Metabolic Caging ................................................................................................................................................ 34 3.1.5 Terminal Procedures ........................................................................................................................................ 34 3.1.6 Histological Analysis ......................................................................................................................................... 35 3.1.7 Western Blotting ................................................................................................................................................ 35 3.1.8 RT-‐PCR .................................................................................................................................................................... 36 3.1.9 Statistical Analysis ............................................................................................................................................. 37 3.2 Results ....................................................................................................................................................... 38 3.2.1 Treatment Study ................................................................................................................................................. 38 a. Diet-‐Induced Changes in Whole-‐Body Parameters ........................................................................................................ 38 b. Effects of MET, RSV and COM Therapy on Body and Tissue Weights ..................................................................... 39 c. Whole-‐Body Glucose Homeostasis and Insulin Sensitivity ........................................................................................... 40 d. Whole-‐Body Energy Expenditure ........................................................................................................................................... 42 e. Tissue Specific Insulin Action ................................................................................................................................................... 43 f. Adiponectin Expression ................................................................................................................................................................ 46 3.2.2 Prevention Study ................................................................................................................................................ 47 a. Body and Tissue Weights ........................................................................................................................................................... 47 b. Whole-‐Body Glucose Homeostasis and Insulin Sensitivity .......................................................................................... 47 c. Whole-‐Body Energy Expenditure ............................................................................................................................................ 48 d. Tissue Specific Insulin Action ................................................................................................................................................... 50 e. Protein content of Enzymes Regulating HGP .................................................................................................................... 53 f. Regulation of Inflammatory Pathways ................................................................................................................................. 53 Chapter 4: Discussion ....................................................................................................................... 55 4.1 Treatment Study .................................................................................................................................... 55 4.1.1 Whole-‐Body Glucose Homeostasis and Tissue Specific Insulin Action ...................................... 55 4.1.2 Association of Insulin Sensitivity with Body Weight .......................................................................... 57 4.2 Prevention Study ................................................................................................................................... 57 4.2.1 Whole-‐Body Glucose Homeostasis and Tissue Specific Insulin Action ...................................... 57 4.2.2 Association of Insulin Sensitivity with Body Weight .......................................................................... 59 4.3 Differences in Responses to Treatment and Prevention ......................................................... 59 4.4 Conclusion ................................................................................................................................................ 61 vi
References ............................................................................................................................................ 62 Appendix A ........................................................................................................................................... 76 Appendix B ........................................................................................................................................... 77 Appendix C ........................................................................................................................................... 78 Appendix D ........................................................................................................................................... 79 vii
List of Tables
Chapter 1:
Table 1.1: Summary of the therapeutic potential of TZDs, MET and RSV on factors
deemed to be important in the development of insulin resistance. ................................... 26
Chapter 3:
Table 3.1: Macronutrient composition of the low and high fat diets used, measured as
both a percentage of total grams and percentage of total kilocalories. ............................. 31
3.2.1 Treatment Study
Table 3.2: Body weight at onset of treatment and body and tissue weights at termination.
........................................................................................................................................... 38
3.2.2 Prevention Study
Table 3.3: Body and tissue weights at termination. ......................................................... 47
Appendix A: Treatment study body weight, IPITT AUC and IPGTT AUC averages for high-fat
fed groups prior to treatment......................................................................................................... 76
viii
List of Figures
Chapter 3:
Figure 3.1: Time-line of the experimental design............................................................ 32
Figure 3.2: HFD impairs glucose and insulin tolerance.. ................................................ 39
Figure 3.3: No differences in adipocyte cell size were observed between groups…...…40
Figure 3.4: COM therapy improves HFD induced glucose and insulin intolerance........ 41
Figure 3.5: Whole-body RER, oxygen consumption, heat and total activity are not
effected by diet or treatment. ............................................................................................ 42
Figure 3.6: Representative blots for total and phosphorylated Akt (S473 and T308) in
liver (a), triceps (b), eWAT (c) and scAT (d). .................................................................. 44
Figure 3.7: Differences in liver (a,b), triceps (c,d), eWAT (e,f) and scAT (g,h) Akt S473
and T308 phosphorylation at basal ( ) and following insulin stimulation ( ). ............... 45
Figure 3.8: Adiponectin expression is unaffected by HFD or treatment in eWAT (a) and
scAT (b). ........................................................................................................................... 46
Figure 3.9: MET, RSV and COM therapy prevent HFD induced glucose and insulin
intolerance. ........................................................................................................................ 48
Figure 3.10: MET reduces RER compared to LFD during the light and dark cycles (c,d).
No changes in oxygen consumption (a,b), heat (e,f) or total activity (g,h) were observed
between groups. ................................................................................................................ 49
Figure 3.11: Representative blots for total and phosphorylated Akt (S473 and T308) in
liver (a), triceps (b), eWAT (c) and scAT (d). .................................................................. 51
ix
Figure 3.12: Differences in liver (a,b), triceps (c,d), eWAT (e,f) and scAT (g,h) Akt
S473 and T308 phosphorylation at basal ( ) and following insulin stimulation ( ). ...... 52
Figure 3.13: Liver G6Pase (a,c) and PEPCK (b,c) expression are unaffected by HFD,
while MET and COM exhibit increased PEPCK content (b,c). ....................................... 53
Figure 3.14: Activation of key inflammation regulating pathways JNK, erk and p38 (a-b)
is unchanged by HFD and not reduced following MET, RSV and COM treatment in
scAT (a,c-e) and eWAT (b,f-h)......................................................................................... 54
Appendix C: MET doses for the treatment study were selected based on pilot work comparing
effects of various doses on glucose and insulin tolerance. ........................................................... 78
Appendix B: RSV doses for the treatment study were selected based on pilot work comparing
effects of various doses on glucose and insulin tolerance. ........................................................... 79 x
List of Abbreviations
AC
Adenylate cyclase
AMP
Adenosine monophosphate
AMPK
AMP activated protein kinase
ANOVA
Analysis of variance
AS160
Akt substrate of 160 kDa
ATP
Adenosine triphosphate
AUC
Area under the curve
cDNA
Complementary DNA
COM
Combined metformin and resveratrol treatment
COX
Cytochrome c oxidase subunit IV
DAG
Diacylglycerol
DGAT1
Diacylglycerol acyltransferase-1
ERK
Extracellular signal-regulated kinase
eWAT
Epididymal white adipose tissue
FFA
Free fatty acid
G6Pase
Glucose 6 phosphatase
GAPDH
Glyceraldehyde 3-phosphate dehydrogenase
GLUT
Glucose transporter
GNG
Glyceroneogenesis
GyK
Glycerol kinase
HFD
High-fat diet
HGP
Hepatic glucose production
HMB
Hydroxymethylbutyrate
IPGTT
Intraperitoneal glucose tolerance test
IPITT
Intraperitoneal insulin tolerance test
IR
Insulin receptor
xi
IRS
Insulin receptor substrate
ITT
Insulin tolerance test
JNK
c-Jun NH2-terminal protein kinase
LFD
Low-fat diet
MET
Metformin
NFκB
Nuclear factor kappa B
OGTT
Oral glucose tolerance test
p38
p38 mitogen-activated protein kinase
PDH
Pyruvate dehydrogenase
PDK
Phosphoinositide-dependent kinase
PEPCK
Phosphoenolpyruvate carboxykinase
PGC-1α
Peroxisome proliferator activating receptor γ co-activator 1 alpha
PI3K
Phosphatidylinositol 3-kinase
PIP2
Phosphatidylinositol-4,5-bisphosphate
PIP3
Phosphatidylinositol-3,4,5-triphosphate
PKCθ
Protein kinase C theta
PPARγ
Peroxisome proliferator activating receptor gamma
R3G
Trans-resveratrol-3-glucuronide
R3S
Trans-resveratrol-3-sulfate
RER
Respiratory exchange ratio
RSV
Resveratrol
scAT
Subcutaneous adipose tissue
SEM
Standard error of the mean
SFA
Saturated fatty acid
SIRT1
Sirtuin 1
TAG
Triacylglycerol
xii
TNF-α
Tumor necrosis factor α
TZD
Thiazolidinedione
UCP1
Uncoupling protein-1
VO2
Oxygen consumption
WAT
White adipose tissue
xiii
Chapter 1: Literature Review
1.1. Introduction
The incidence of type 2 diabetes is increasing in Canada, placing a rising economic
burden on the health care system1. In 2013 just under 2 million Canadians over the age of 12
were diabetic, costing the healthcare system $13.1 billion1,2. These factors, along with the
association of diabetes with cardiovascular risk factors3, establishes a need to understand the
contributing factors that lead to the development of diabetes and the necessity of developing cost
effective treatments. As type 2 diabetes is characterized by reduced insulin sensitivity and
associated impairments in glucose homeostasis, it is imperative that we understand the
mechanisms of insulin action and the means through which insulin signaling is impaired in order
to explore effective treatment strategies.
Insulin is the primary hormone responsible for mediating glucose disposal, particularly in
response to post-prandial increases in glucose absorption. Insulin reduces plasma glucose
concentration through binding to receptors on insulin sensitive tissues and subsequently
increasing glucose uptake as well as inhibiting hepatic glucose production4,5. However, insulin
resistance, a major contributor in the development of type 2 diabetes, is increasingly common in
Canada. Obesity6, lipotoxicity7, inflammation8 and mitochondrial dysfunction9,10 are commonly
associated with insulin resistance. Therefore, many pharmacological therapies have been
developed to target these players in the development of insulin resistance. Two medications are
commonly prescribed: thiazolidinedione’s (TZDs), which target mitochondrial biogenesis and
inflammation in adipose tissue11, and metformin (MET), which attenuates hepatic glucose
production12. These medications are often prescribed in combination to target multiple
contributors of impaired glucose homeostasis13. However, TZDs produce major adverse side
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effects14. Therefore, it is important to identify a safer and more effective alternative to improve
insulin sensitivity. Resveratrol (RSV), a natural compound found in red grapes, represents a
potential adjunct treatment for use with MET, as it has been shown to promote similar beneficial
effects to TZDs in adipose tissue15–17. This literature review aims to provide background on the
development of insulin resistance, identify the mechanisms through which TZDs and MET act,
and attempts to support the use of RSV as an anti-diabetic compound that could be used as a
substitute for TZDs in combination with MET.
1.2. Insulin and Glucose Homeostasis
Insulin is important for regulating postprandial blood glucose homeostasis through
increasing glucose uptake into various tissues, including skeletal muscle, liver and adipose
tissue, as well as inhibiting hepatic glucose production (HGP)4,5. As glucose uptake represents a
major step in glucose metabolism4, it is important to understand the processes responsible for
mediating insulin action under normal conditions. Although most glucose transporters (GLUT)
are expressed in plasma membranes and allow basal levels of glucose uptake at rest, such as
GLUT1 in skeletal muscle, insulin sensitive tissues also contain an intracellular pool of the
GLUT4 isoform, which may be localized to the plasma membrane following stimulation. Insulin
regulates the translocation of GLUT4 from intracellular vesicles to the plasma membrane and
increases the activity of these transporters in order to effectively increase the rate of glucose
uptake into insulin sensitive tissues5,18,19. This process involves a cascade of reactions that are
initiated by the binding of insulin to the insulin receptor (IR) on the extracellular surface of cells.
IRs are ligand-activated receptor tyrosine kinases, and once insulin binds a conformational
change within the IR activates the kinase domain, leading to autophosphorylation and increased
catalytic activity of the IR. Subsequent insulin receptor substrate (IRS) phosphorylation triggers
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IRS-induced activation of phosphoinositide 3-kinase (PI3K). PI3K is a lipid kinase that converts
phosphatidylinositol-4,5-bisphosphate (PIP2) to phosphatidylinositol-3,4,5-triphosphate (PIP3)
20,21
. PIP3 is then responsible for recruiting Akt to the plasma membrane for subsequent
phosphorylation by phosphoinositide-dependent kinase (PDK)20,21. Akt in turn phosphorylates
AS160, removing the inhibitory effect of AS160 on GLUT4 vesicles and allowing them to
translocate to the plasma membrane to increase glucose uptake20,22,23. In addition to initiating
GLUT4 translocation, insulin is believed to improve the activity of GLUT4 in the plasma
membrane through changes in the phosphorylation status of GLUT424.
1.3. Insulin Resistance
Although the insulin signaling pathway is highly regulated and conserved, dysfunction
may occur leading to insulin resistance and eventually diabetes; a pathological condition defined
by an inability to maintain plasma glucose concentrations. Insulin signaling may be effected
through two possible mechanisms; (I) reducing insulin delivery to the target tissues or (II)
impairing the target tissues’ response to insulin. Insulin resistance occurs when target tissues are
unable to respond appropriately to physiological levels of insulin. This attenuates insulinstimulated glucose uptake, and the inhibition of adipose tissue lipolysis and HGP25,26.
Whole-body insulin sensitivity and glucose homeostasis can be measured using various
methodologies27,28. Insulin tolerance (ITT) and oral glucose tolerance tests (OGTT) are measures
of insulin action and glucose homeostasis that may be used in human research27,28. The ITT is a
very simplistic measure, involving a bolus injection of insulin followed by blood glucose
measures at various time-points, with faster declines in glucose concentrations representative of
enhanced insulin sensitivity. The OGTT is also a simple measure, commonly used to examine
the efficiency of the body at clearing a glucose load. A large glucose load is ingested and blood
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glucose is measured at various time-points, with prolonged higher blood glucose indicative of
glucose intolerance. The OGTT is perhaps a more physiological measure than the ITT, as it more
closely mimics the dynamic glucose levels experienced post-prandially and very crudely
accounts for both insulin release and action. However, glucose tolerance is not an equivalent
measure to insulin sensitivity and therefore the latter cannot be measured using an OGTT
alone27–29. Similar to the measures observed in humans, in normal, healthy mice, intraperitoneal
injection with glucose (IPGTT) results in an acute spike in plasma glucose followed by rapid
clearance of glucose into insulin-stimulated tissues, while an insulin injection (IPITT) results in
an immediate reduction in plasma glucose. Glucose intolerant mice experience a similar initial
increase in plasma glucose following glucose injection, however the glucose concentration
remains high for a prolonged period, as these mice are incapable of efficiently clearing glucose.
In terms of insulin tolerance, insulin resistant mice experience an attenuated reduction in plasma
glucose following insulin injection. Normal plasma glucose concentrations can be maintained
initially in insulin resistance due to compensatory hyperinsulinemia, however type 2 diabetes
will likely develop over time due to an inability of the pancreas to maintain high insulin output30.
Although it may be promising to examine insulin resistance and anti-diabetic therapies in
humans, rodent models are important in order to first identify potential adverse effects and allow
for a greater ability to control extraneous variables, such as differences in diet, exercise and
hereditary factors. Although knockout rodent models have been developed, they fail to mirror the
complexity of effects occurring in human insulin resistance as they only target one factor of
insulin action31,32. Although these models have proven useful in clarifying the functions of
specific proteins in insulin signaling and identifying important factors, they fail to mimic the
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observed impairments of insulin resistance in humans and are not ideal when examining how
different treatments may affect humans31.
An alternative rodent model is that of diet-induced insulin resistance. As human obesity
results from excessive caloric intake and foods high in fat content have been shown to increase
the risk of diabetes, high-fat fed rodents represent an ideal model of insulin resistance32. These
models mirror the increased fat availability of foods in Western society, which is a major
contributor to insulin resistance32. However, certain rodent strains are resistant to high-fat diet
effects and it is therefore important to select the appropriate rodent model for such studies32.
C57BL/6 mice represent an ideal strain for rodent high-fat diet models of insulin resistance, as
they have been highly characterized and mimic the development of obesity and insulin resistance
observed in humans consuming a high-fat diet32. As such, this model has become important for
examining the effects of high-fat Western diets on obesity and insulin resistance32.
1.3.1 The Pathophysiology of Insulin Resistance
The pathophysiology of insulin resistance is multifactorial. Insulin resistance is typically
initiated by consumption of a high-fat diet (HFD) and the development of obesity, followed by
subsequent alterations in lipid metabolites, inflammation and mitochondrial content6,8,26,33,34.
This culmination of factors was demonstrated by Lee et al.26 using a time course HFD
intervention to examine the development and progression of insulin resistance. Consumption of a
60% kcal from fat HFD induced whole-body glucose intolerance and insulin resistance in as
early as 3 days in mice, with a simultaneous increase in body weight, epididymal adipose tissue
mass, and adipocyte size. These detrimental changes progressively worsened over time, with
maximal impairment occurring at 10 weeks. Lipid-derived metabolites may be responsible for
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short-term insulin resistance, as ceramides, free fatty acids (FFAs) and diacylglycerols (DAGs)
were increased in liver and skeletal muscle at 3 days, while inflammation may be responsible for
insulin resistance following a long-term HFD and the development of obesity26. However, the
role of inflammation in the development of short-term HFD-induced insulin resistance remains
controversial, as others have shown that adipose tissue inflammation is a key component in the
development of hepatic insulin resistance following a short-term HFD35. Although a relationship
between reduced skeletal muscle and adipose tissue mitochondrial content and insulin resistance
has been established, the role of mitochondrial dysfunction in insulin resistance remains
controversial9,10.
1.3.2 Lipotoxicity
Obesity and high-fat feeding are associated with lipotoxicity, induced by marked
increases in circulating lipids and intracellular triacylglycerol (TAG) and DAG in liver and
skeletal muscle26,36–39. HFD and lipid infusion models have been utilized to examine the effects
of lipotoxicity on whole-body and tissue specific insulin sensitivity38. Plasma FFA concentration
and skeletal muscle and liver TAG and DAG content are negatively associated with whole-body
insulin sensitivity7,26,30,40. This has been supported by reductions in insulin-stimulated glucose
infusion rate and glucose disposal as well as attenuated inhibition of HGP41–43. Interestingly,
lipid infusion and HFD studies also suggest that lipid accumulation may impair insulin action in
the absence of obesity and its related physiological abnormalities43. However, others have shown
that lipid infusion in healthy subjects was unable to induce whole body insulin resistance until
skeletal muscle lipid content increased, indicating that accumulation of plasma FFAs, unlike
cellular lipids, may not be directly causative in insulin resistance40,42,44. Moreover, endurance
trained individuals display high levels of intramuscular TAG storage, comparable to those of
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diabetic individuals, while maintaining a high degree of insulin sensitivity45,46. This association
of high TAG content in insulin sensitive muscle of endurance athletes is termed the athletes
paradox.
Although the association between lipid accumulation and insulin resistance is well
established in diabetic individuals, the mechanisms responsible have yet to be elucidated.
Various hypotheses have been proposed to ascertain the effects of lipids in liver and skeletal
muscle insulin signaling. One such example is the potential for FFA to indirectly induce insulin
resistance through propagation of inflammatory signaling in macrophages, resulting in proinflammatory molecule release, as will be discussed in detail below47. It has also been postulated
that increased fat oxidation associated with lipid accumulation, as measured by a reduced
respiratory exchange ratio, impairs glucose metabolism37,42,43,48. Within insulin resistant muscle,
intracellular DAGs and TAGs are associated with reduced tissue insulin sensitivity and glucose
uptake, resulting in diminished glycogen synthesis and glucose metabolism36,44,49. Additionally,
intrahepatic lipid accumulation inhibits insulin-induced suppression of HGP41,50. These effects in
muscle and liver appear to be mediated through reduced IRS-1 and Akt phosphorylation38,48–51.
Specifically, increases in FFA and DAG content activate protein kinase C theta (PKCθ) in
muscle, which in turn phosphorylates IRS-1 at serine-30738,40,49. This leads to attenuated insulinstimulated IRS-1 tyrosine phosphorylation, PI3K activity and Akt phosphorylation38,40,49,51.
Adding to the uncertainty of lipotoxicity induced insulin resistance, it has been suggested
that fatty acid composition affects insulin signaling, with certain fatty acids inducing resistance
and others playing a preventative role against resistance52. Saturated fatty acids (SFAs) in
particular are associated with the induction of insulin resistance52,53. Specifically, SFAs in
adipose tissue are implicated in the degradation of IRS1 as well as macrophage activation and
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subsequent pro-inflammatory molecule release as is discussed in detail below53,54. These effects
may be partially mediated through the production of ceramides, as inhibition of ceramide
production prevented lipid infusion induced insulin resistance in rodent models46,54,55. Excessive
accumulation of SFAs in hypertrophied adipocytes leads to an increase in SFA release into the
circulation, resulting in the activation of inflammatory pathways and IRS1 degradation in liver
and skeletal muscle, further promoting whole-body insulin resistance53. It is likely that the
various inhibitory effects of lipids listed above do not occur in isolation, but rather work in a
coordinated manner in order to attenuate whole body insulin sensitivity.
1.3.3 Inflammation
Obesity-induced inflammation has been shown to occur in skeletal muscle56 and liver25,57,
however adipose tissue experiences a greater degree of inflammation8,26,56,58 and may induce
insulin resistance in the aforementioned tissues through secretion of adipokines and proinflammatory molecules into the systemic circulation26,33,59. Because of this, our examination of
inflammation-mediated insulin resistance will focus on adipose tissue.
Increased adiposity is believed to play a role in the onset of inflammation through white
adipose tissue (WAT) hypoxia58,60 and FFA accumulation47,61. Hypoxia develops in
hypertrophied adipose tissue as angiogenesis is unable to match the rapid increase in adipose
tissue expansion60. Studies have shown that hypoxia increases pro-inflammatory gene expression
in adipocytes and machrophages58, serum levels of inflammatory markers60, and the infiltration
of macrophages and cytotoxic T-cells into adipose tissue58,60. Alternatively, FFAs may directly
effect immune cell activation through interacting with toll-like receptors on the cell surface,
although this has only been shown to occur at supraphysiological FFA concentrations47,62.
8
Classically activated, pro-inflammatory macrophages have previously been shown to express
toll-like receptors, which activate the c-Jun NH2-terminal protein kinase (JNK) inflammatory
pathway, leading to an increased expression of pro-inflammatory molecules such as tumor
necrosis factor α (TNF-α)33,47. Due to the close proximity of adipocytes and macrophages in
adipose tissue, it is likely that released fatty acids from insulin resistant adipose tissue will
activate macrophages, and subsequent release of TNF-α will in turn induce lipolysis in
adipocytes, leading to a pathological feed-forward cycle that preserves inflammation and insulin
resistance47,62.
Obesity induced inflammation is characterized by the infiltration of adipose tissue with a
variety of immune cells; including neutrophils63, B cells64 and T cells64–66. However,
macrophages are the most robustly increased and are suggested to be key components of obesityinduced insulin resistance8,26,33,67. Pro-inflammatory macrophages increase with obesity through
two processes: (I) monocyte infiltration into adipose tissue8,33,47,66 and (II) switches in
macrophage polarization, exhibited by a larger proportion of total macrophages displaying a proinflammatory phenotype26,47,67,68.
Infiltrating macrophages in WAT release a variety of pro-inflammatory cytokines with
paracrine and endocrine effects62. Macrophages in obese WAT exhibit stimulation of JNK,
extracellular signal-regulated kinase (ERK) and nuclear factor kappa B (NFκB) proinflammatory signaling47,62,69. These pathways subsequently amplify WAT pro-inflammatory
molecule expression and secretion in obesity, such as that of TNF-α47,62,69–71. Increased TNF-α
leads to a reduction in GLUT4 and WAT lipoprotein lipase expression71–73, effectively reducing
the availability of insulin stimulated glucose transporters and increasing circulating TAG
molecules. These pro-inflammatory molecules also appear to have direct detrimental effects on
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insulin signaling, as TNF-α has been found to inhibit insulin-stimulated IR autophosphorylation
and IRS phosphorylation74–77. Interestingly, a positive feedback system exists through which proinflammatory molecules propagate the inflammatory response by activating the pathways that
produce them76. Studies have shown a positive correlation between pro-inflammatory molecule
expression and whole-body insulin sensitivity, as measured by increased plasma insulin,
decreased glucose disposal and impaired inhibition of HGP70. Moreover, inhibition of
macrophage NFκB signaling promotes skeletal muscle and liver insulin sensitivity in high-fat fed
mice, elucidating the impact of inflammation in whole-body insulin sensitivity69.
1.3.4 Mitochondrial Dysfunction
Mitochondria are cellular organelles responsible for various metabolic processes geared
towards ATP production, including oxidative phosphorylation and beta-oxidation78. Importantly,
insulin resistance is associated with mitochondrial dysfunction in both skeletal muscle and
adipose tissue. Within skeletal muscle, mitochondrial content and size are reduced in obese and
diabetic subjects when compared to lean individuals34,79. Corresponding reductions in
mitochondrial DNA and peroxisome proliferator activating receptor γ co-activator 1 alpha (PGC1α) responsive oxidative phosphorylation genes have also been described9,80. Functional
consequences of these changes in skeletal muscle mitochondrial volume include reduced
oxidative capacity and electron transport chain activity, an increased reliance on anaerobic
metabolism and subsequent increases in lipid storage due to impaired beta oxidation9,34,81.
Therefore, mitochondrial dysfunction is believed to promote skeletal muscle lipotoxicity through
incomplete lipid oxidation, further worsening insulin sensitivity82. The oxidative capacity of
skeletal muscle is in fact a superior predictor of insulin sensitivity over markers of lipotoxicity39.
However, changes in mitochondrial content and oxidative capacity may not play a causative role
10
in insulin resistance, potentially representing a secondary manifestation following the
development of insulin resistance83.
Similar to the changes observed in skeletal muscle, mitochondrial content is reduced in
diabetic and insulin resistant mouse WAT and is inversely related to adiposity11,33,84. PGC-1β
and PGC-1α expression are also reduced in WAT, along with electron transport chain protein
expression, mitochondrial DNA and oxidative capacity10,11,84. The importance of PGC-1α in
WAT was further explored using a tissue specific PGC-1α knockout model85. Loss of PGC-1α
worsened HFD-induced insulin resistance, which may be mediated through observed reductions
in mitochondrial and thermogenic genes85. HFD-induced mitochondrial dysfunction in WAT is
suggested to be a result of increases in FFAs, as ex vivo studies show similar reductions in
mitochondrial protein expression following palmitate treatment10. FFAs may overwhelm WAT
mitochondrial oxidative capacity and result in accumulation of incompletely oxidized lipids, as
has been shown in skeletal muscle. Studies in 3T3-L1 adipocytes using TNFα induced insulin
resistance have shown that TNFα also induces mitochondrial dysfunction, with associated
reductions in mitochondrial size, PGC-1α expression, membrane potential and intracellular
adenosine triphosphate (ATP) production86. Inhibition of NFκB inflammatory signaling has also
been shown to improve insulin resistance induced mitochondrial dysfunction in 3T3-L1
adipocytes, through changes in mitochondrial fission and fusion and associated reductions in
TNFα production. NFκB inhibition further restored insulin stimulated glucose uptake in insulinresistant adipocytes87. As such, inflammation likely plays a causative role in insulin resistance
associated mitochondrial dysfunction in adipose tissue86,87. However, reduced WAT
mitochondrial content has been found to occur after impairments in glucose homeostasis have
been established and therefore likely does not play a causative role in insulin resistance10.
11
Regardless, a link between whole-body insulin resistance and mitochondrial dysfunction in the
aforementioned tissues is well established, and mitochondrial biogenesis remains a potential
target for anti-diabetic therapies.
1.4. Current Treatments
Given the increasing prevalence of diabetes1, it is important to explore potential treatment
options in order to reestablish insulin sensitivity and glucose homeostasis. This necessity is made
even more pressing given the understanding that insulin resistance is a prerequisite for the
development of the metabolic syndrome and chronic cardiovascular complications leading to an
increased risk of mortality3. Although exercise and dietary interventions have been shown to
have beneficial effects on improving insulin sensitivity88–90, the inability of many diabetic
individuals to commit to long-term lifestyle interventions illustrates the importance of
developing pharmacological interventions88–90. Two commonly prescribed anti-diabetic drugs are
thiazolidinediones (TZDs) and metformin (MET). Additionally, it has been determined that
many nutraceuticals have insulin-sensitizing effects, with resveratrol (RSV) being the most
highly studied.
1.4.1 Thiazolidinedione’s (TZDs)
The insulin sensitizing effects of TZDs are well established. TZDs significantly reduce
plasma glucose and insulin concentrations in models of insulin resistance11,91–93. Moreover,
TZDs increase whole-body insulin sensitivity and glucose disposal rates following
treatment91,92,94,95. This is associated with improvements in insulin-induced effects on wholebody glucose and lipid metabolism which will be discussed below94.
12
TZDs are a family of selective peroxisome proliferator activating receptor gamma
(PPARγ) agonists96. PPARγ in turn is an important regulator of adipogenesis, lipid metabolism
and mitochondrial genes96. Therefore, it is not surprising that the insulin sensitizing effects of
TZDs are mediated through these PPARγ targeted pathways96. PPARγ is highly expressed in
adipose tissue and, although TZDs promote insulin sensitivity at the liver and skeletal muscle,
TZD activity appears to be localized to the adipose tissue. This tissue specificity is evidenced by
the absence of TZD-induced insulin sensitizing effects in lipoatrophic mice, which lack adipose
tissue92,97.
Increased adipogenesis following TZD treatment results in increases in the number of
adipocytes and body weight84,94,97,98. The increase in adiposity appears to be localized to
subcutaneous adipose tissue (scAT), which is significant given that visceral adiposity is
associated with metabolic abnormalities98–100. Lipid release from adipose tissue is reduced and
lipid uptake is enhanced, while glyceroneogenesis (GNG), glycerol phosphorylation and TAG
synthesis enzymes are upregulated in order to promote lipid deposition following TZD
treatment94,101–103. Specifically, the expression and activity of phosphoenolpyruvate
carboxykinase (PEPCK) and glycerol kinase (GyK), key regulators of separate glycerol-3phosphate producing pathways important in fatty acid re-esterification, are upregulated in WAT
of human, rodent and cell culture models of insulin resistance following TZD treatment93,101–103.
Importantly, the expression of diacylglycerol acyltransferase-1 (DGAT1), which catalyzes the
committed step in TAG synthesis, has also been shown to increase with TZD treatment101. These
changes effectively counteract the increased lipolysis associated with TZDs and reduces fatty
acid secretion through promotion of FFA trapping in WAT93,101. Increases in TAG synthesis
regulating pathways in turn reduce local WAT inflammation by attenuating FFA-induced
13
increases in macrophage infiltration and inflammatory gene expression8,47,104. Importantly,
increased lipid storage capacity of WAT effectively reduces circulating lipids and ectopic lipid
storage91–94,101. Reduced ectopic lipid deposition may explain the whole-body insulin sensitizing
effects of TZDs, given the role of lipotoxicity in insulin resistance.
TZD-induced increases in fat oxidation and energy consumption may also explain the
reductions in circulating lipids and ectopic lipid storage97. Obesity and insulin resistance are
associated with reductions in WAT mitochondrial content and gene expression, resulting in a
reduced capacity to oxidize fat and carbohydrates11,84,105–107. Mitochondria are responsible for
energy production to facilitate the aforementioned TAG synthesis and GNG processes.
Treatment with TZDs has been shown to induce increases in WAT mitochondrial biogenesis and
mitochondrial function, as evidenced by enhanced oxidative capacity, fat oxidation and nonshivering thermogenesis, effectively reversing the effects of diabetes and insulin
resistance11,84,105–107. Mitochondrial gene expression is positively correlated to plasma insulin and
glucose levels, suggesting that mitochondrial biogenesis is essential to the insulin sensitizing
effects of TZDs106.
Mitochondria also appear to be important in the production of adiponectin, an adipocyte
derived cytokine involved in tissue communication and regulation of whole-body metabolism
and insulin sensitivity108. Specifically, adiponectin has been shown to increase glucose uptake
into skeletal muscle and improve insulin sensitivity through suppression of macrophage cytokine
production and increased fatty acid oxidation95,104,109–112. This has been supported by a high
correlation between adiponectin secretion and the rate of glucose disposal and negative
correlations with basal circulating insulin and TAG concentrations95,104,109–112. Interestingly,
circulating adiponectin is reduced in insulin resistant human and rodents and recovered following
14
associated increases in mitochondrial biogenesis with TZD treatment95,104,108,113. The importance
of adiponectin in mediating the insulin sensitizing effects of TZDs has been explored in
adiponectin null mouse models114,115. Reduced adiponectin secretion was associated with severe
liver specific insulin resistance and exposure to a HFD resulted in the rapid induction of
impaired glucose homeostasis115. TZD induced improvements in glucose tolerance were in fact
attenuated in adiponectin null mice, with associated reductions in liver and skeletal muscle
AMPK activation115. Higher doses of TZDs than required to elicit effects in control insulin
resistant mice were found to be capable of eliciting insulin sensitizing effects in insulin resistant
adiponectin null mice114. However, mice lacking adiponectin did not experience decreases in
HGP and improvements in insulin sensitivity were limited to increased skeletal muscle glucose
uptake, while insulin resistant control mice exhibited improvements in both HGP attenuation and
skeletal muscle glucose uptake114. Therefore, it appears that TZDs are capable of improving
insulin action through both adiponectin dependent and adiponectin independent mechanisms.
Although the insulin sensitizing effects of TZDs are promising, a multitude of adverse
side effects have been identified. TZDs are associated with weight gain, hepatic toxicity and
increased risk of congestive heart failure, myocardial infarction, osteoporosis and bladder
cancer14,116–119. Furthermore, there is an increase in the risk of mortality as a result of these
complications14,116–119.
1.4.2 Metformin (MET)
MET is a commonly prescribed anti-diabetic drug that has been shown to improve
glucose homeostasis120. This is supported by improvements in glucose tolerance and reduced
post-meal plasma glucose following metformin treatment120–124. In addition, MET reduces
15
fasting and basal plasma TAG, glucose and insulin concentrations in models of diabetes and
high-fat feeding12,124–127. These effects are thought to occur through two primary mechanisms;
improved peripheral glucose uptake121 and reduced HGP12,126.
Given the improved rate of glucose disposal during glucose tolerance testing, it is not
surprising that MET improves peripheral glucose uptake121,125,127. As such, increases in skeletal
muscle12,125, cardiac128,129 and liver130 glucose clearance have all been found to occur following
MET treatment. The fraction of glucose disposal accounted for by muscle has been found to
increase12 and MET induced improvements in muscle glucose uptake provides an additive effect
to insulin stimulation125. MET counteracts insulin-induced skeletal muscle, cardiac and liver
FFA incorporation into TAGs and prevents suppression of FFA oxidation125,128,131, which may
induce improvements in insulin sensitivity through reduced lipotoxicity. However, although
significant, these lipid effects were minor and therefore are unlikely to be the primary
mechanism through which MET increases glucose disposal. Research using cardiomyocytes
shows that MET increases Akt phosphorylation and reduces the rate of GLUT4 endocytosis postinsulin stimulation129. Increased IR tyrosine kinase activity in both muscle and liver treated with
MET suggest that MET increases insulin action in these tissues120,130. The metabolic fate of
increased glucose taken into peripheral tissues remains controversial, as some studies show
increased muscle glycogen content123,130 while others identify increased glucose oxidation121,122.
Although many studies have shown improved peripheral glucose uptake and insulin
sensitivity, the primary mechanism of MET action appears to be through reduced HGP12,122,126.
MET has been shown to reduce basal and glucagon-induced glucose output126. This effect is
likely the result of observed reductions in hepatic gluconeogenic transcription factor activity and
subsequent suppression of PEPCK and glucose-6-phosphatase (G6Pase) expression, two key
16
regulatory enzymes of glucose production132. Moreover, there appears to be a high correlation
between plasma glucose concentration and hepatic glucose output before and after administration
of MET12, suggesting that the reduced HGP is essential to the glucose lowering effects of MET.
MET treatment results in the dose-dependent accumulation of AMP and an increase in
the AMP:ATP ratio in the liver through direct inhibition of complex I of the electron transport
chain and subsequent impairments in oxygen consumption126,133–135. This reduced energy state
may be essential for mediating the beneficial effects of MET on insulin resistance and plasma
glucose concentration, as inhibition of the electron transport chain attenuates HGP and increases
skeletal muscle glucose utilization in a similar manner to that observed with MET135. AMP acts
as an allosteric inhibitor or activator of various molecules, including adenylate cyclase (AC) and
AMP-activated protein kinase (AMPK), respectively126,136. AC is responsible for mediating the
formation of cyclic-AMP from ATP and subsequent protein kinase A activation126. MET
effectively reduces glucagon-induced glucose output through AMP induced AC inhibition, as
cyclic-AMP is a required second messenger in glucagon signalling126. Additionally, AMPK is an
energy responsive enzyme that is indirectly activated by MET treatment in liver, muscle and the
heart125,129,131,136. AMPK regulates glucose and lipid metabolism and increases in AMPK activity
have been shown to inhibit HGP gene expression and stimulate FFA oxidation and glucose
uptake123,132. MET-induced inhibition of HGP is dependent on AMPK activation125.
In contrast to TZDs, MET does not adversely effect cardiac function and is associated
with weight loss and infrequent, minor adverse effects12,120,125,128,136. These include
gastrointestinal symptoms, such as diarrhea and nausea124,127,137. Due to the low risk of MET
treatment it has also been examined as a potential preventative therapy in individuals at risk of
diabetes, resulting in reduced fasting plasma glucose and incidence of diabetes similar to life 17
style intervention88. However, high-doses of MET are required in order to activate AMPK and
induce beneficial effects125,128. It is of interest to explore additional interventions that may be
used either independently or in combination with MET.
1.4.3 Combination Therapy: Thiazolidinedione’s & Metformin
Combinations of various pharmacological treatments have been widely examined138. As
the primary defects in impaired glucose homeostasis are attenuated insulin-stimulated glucose
uptake and increased HGP, utilizing individual therapies that target these pathways in
combination will enhance the efficacy of treatment. Numerous studies have directly compared
the effects of TZDs and MET in vivo, supporting improvements in whole-body insulin sensitivity
and plasma glucose concentrations, with MET acting through reduced HGP and TZDs increasing
muscle and WAT glucose uptake13,79,139–141. However, TZDs induced greater improvements in
insulin stimulated glucose disposal13,79,139,140. When utilized in combination, fasting plasma
glucose decreased to a greater extent than that of either therapy independently13. Importantly,
combination therapy also increased the rate of glucose disposal and decreased post-prandial
plasma glucose compared to when given separately13. However, the impact of combination
therapy on TZD-induced adverse effects has not been thoroughly examined. Therefore, it is
important to examine alternative molecules that may provide additive beneficial effects in
combination with MET without increasing the risk of adverse effects.
1.5. Resveratrol (RSV)
Resveratrol (RSV) is a polyphenol found in many plant species, red grapes and red
wine16,17. Within plants, RSV protects against fungal infections, functioning as a phytoalexin142.
Recently, RSV has gained attention for proposed anti-aging and anti-diabetic effects143,144.
18
Prophylactic administration of RSV produces a protective effect against genetic and diet-induced
insulin resistance. This effect has been supported with findings of improved whole-body insulin
sensitivity, reduced plasma glucose and insulin levels and increased plasma adiponectin15,143,145.
Beneficial effects of RSV do not appear to be limited to one mechanism of action, providing
diverse outcomes in various tissues that together promote whole-body insulin sensitivity.
Although RSV-induced improvements in insulin sensitivity are partially mediated through
enhanced mitochondrial biogenesis similar to the previously defined pharmacological
interventions, prophylactic administration of RSV does not appear to be tissue specific, as it
induces similar mitochondrial effects in skeletal muscle145, liver143 and adipose tissue15,145,146.
Moreover, RSV treatment enhances whole body energy expenditure, in the absence of changes in
respiratory exchange ratio and activity145,146.
The mechanism of action through which RSV establishes metabolic changes remains
controversial. The most commonly described mediator of RSV is activation of PGC-1α145,147.
However, the mechanism through which RSV stimulates PGC-1α is not clear, as studies have
shown that either sirtuin 1 (SIRT1), a deacetylase that regulates PGC-1α acetylation, or AMPK
may be responsible143,146–149. Studies have shown that SIRT1 is directly activated by RSV,
enhancing deacytlation activity148,149 which increases PGC-1α activity in liver and skeletal
muscle resulting in increased mitochondrial biogenesis143,145,147. Moreover, SIRT1 knockdown
was found to block RSV-induced expression of PGC-1α regulated mitochondrial genes in
muscle145. However, recent work has shown that measures of SIRT1 activation by RSV in vitro
are fraught with technical issues, as problems with activity assays have been identified148,149, and
in vivo work suggests that SIRT1 may play a small role in comparison to AMPK in regulating
insulin sensitizing effects of RSV147,150. Alternatively, AMPK phosphorylation is increased by
19
RSV in liver, skeletal muscle and WAT143,147. AMPK knockout and inhibitor studies have shown
that RSV induced improvements in insulin sensitivity, metabolic rate and skeletal muscle
mitochondrial biogenesis are AMPK dependent144,147. Importantly, AMPK knockout prevents
RSV-induced decreases in PGC-1α acetylation and SIRT1 knockout cells conserve RSV-induced
AMPK activation and subsequent PGC-1α expression147. Therefore, AMPK appears to regulate
SIRT1 activity upstream, which is believed to prolong a state of increased PGC-1α activity147.
However, recent work in PGC-1α knockout mice shows that although PGC-1α is necessary for
skeletal muscle mitochondrial biogenesis following RSV treatment, improvements in energy
expenditure and body composition are independent of PGC-1α146. Therefore, the exact
mechanisms through which RSV acts to produce an improved metabolic state require further
consideration.
Within skeletal muscle, RSV-induced mitochondrial biogenesis and content has been
well described145–147. Skeletal muscle mitochondrial respiration rates and oxidative capacity were
enhanced in glycolytic fibers following treatment145,151. These functional effects are stimulated
by increased expression of genes involved in electron transport, oxidative phosphorylation and
uncoupling145,146,151. Increases in skeletal muscle basal glucose uptake have been described and
found to be dependent on AMPK activation. Moreover, RSV augments insulin-stimulated
glucose uptake through AMPK dependent increases in Akt signaling144,151. However, the role of
skeletal muscle in RSV-induced whole-body metabolic effects appears to be minor146.
In the liver, RSV promotes mitochondrial biogenesis through deacetylation of PGC-1α in
the absence of changes in PGC-1α expression. Deacetylation results in PGC-1α activation,
subsequent increases in mitochondrial content and changes in TCA cycle and glycolysis
pathways143,145. As such, RSV-induced mitochondrial biogenesis in the liver appears to be
20
dependent on SIRT1, rather than AMPK as was found following MET treatment143. In addition
to promoting mitochondrial biogenesis, RSV attenuates increases in liver weight and hepatic
lipid droplet accumulation143. This is largely explained through reduced expression of genes
responsible for lipogenesis and FFA re-esterification in the liver, likely reducing obesity-induced
lipotoxicity146.
Adipose tissue plays an important role in RSVs beneficial effects on whole-body insulin
sensitivity. Mitochondrial biogenesis in WAT is promoted through PGC-1α and subsequent
increases in the expression of mitochondrial genes similar to TZDs, although the mechanisms of
action of these molecules are functionally distinct15,145,146. However, RSV effects are not limited
to WAT, as PGC-1α and uncoupling protein-1 (UCP-1) gene expression increased in both WAT
and brown adipose tissue, as did mitochondrial size and density of mitochondrial cristae145,147.
scAT and retroperitoneal white adipose tissue exhibit increased mitochondrial respiration, which
is associated with increased protein content of cytochrome c oxidase subunit IV (COX IV)15. In
parallel with increased mitochondrial biogenesis, RSV induces enhanced GNG and adiponectin
secretion in WAT, again mirroring the effects of TZDs15,146. Moreover, increased lipolytic rate
and re-esterification was observed in scAT with RSV15,146,152,153.
In keeping with the multifactorial causes of insulin resistance, it is of note that RSV
prevents pharmacological (lipopolysaccharide) and diet-induced production of TNF-α, reducing
inflammation-stimulated changes in adipokine expression and enhancing insulin action through
IR, IRS1 and Akt phosphorylation146,154,155. Although no differences in body weight were
observed in most studies, RSV decreases body fat content through reductions in retroperitoneal,
subcutaneous and epididymal adipose depot size15,145–147,156. This may be partially explained
through reductions in basal and insulin-stimulated lipogenesis from glucose in adipocytes152.
21
Therefore, RSV effectively prevents the development of the three main contributors to insulin
resistance through reduced lipotoxicity in liver, decreased inflammation in WAT and increased
mitochondrial biogenesis in skeletal muscle, liver and WAT.
Despite the overwhelming evidence supporting protective anti-diabetic effects of RSV
listed above, few studies have examined the treatment potential of RSV in animal models of
established insulin resistance. Chemically (streptozotocin-nicotinamide) induced type 1 diabetic
rats display reduced plasma glucose, reduced markers of inflammation including TNFα, and
increased plasma insulin following RSV treatment155,157. These improvements are associated
with increased hepatic glycogen content and changes in hepatic activity of carbohydrate
metabolism regulating enzymes, including glycogen phosphorylase, glycogen synthase, pyruvate
kinase, fructose-1,6-bisphosphatase, hexokinase and G6Pase157. Similarly, a genetic model of
obese rats exhibited improvements in plasma glucose and insulin concentrations and whole-body
insulin sensitivity following 4 weeks of treatment16. Plasma FFA and TAG concentrations were
also reduced in parallel with reductions in hepatic lipid content16. RSV treatment decreases
visceral fat content and TNFα expression and increases adiponectin expression16. Therefore,
WAT appears to be a major contributor to the metabolic effects of RSV treatment, as was
determined in prophylactic studies. Interestingly, although many prophylactic studies have
examined the protective effects of RSV in animal models of diet-induced insulin resistance, to
our knowledge no diet-induced insulin-resistant animal models have assessed the treatment
potential of RSV.
Although beneficial, anti-diabetic effects of RSV have been supported in animal and in
vitro models, human data is scarce and inconsistent158,159. Clinical trials have shown that RSV
improves energy expenditure and resting metabolic rate in diabetic subjects, with no
22
corresponding increases in average daily activity160. This was associated with increases in
skeletal muscle SIRT1 and AMPK expression160. Moreover, RSV has been found to reduce
lipoprotein production and post-prandial glucagon responses in diabetic subjects161,162. The
insulin sensitizing effects of RSV are however controversial in humans, with many studies
finding no significant improvements in insulin sensitivity, glucose production or oxidation, and
energy expenditure in obese, non-diabetic subjects following RSV treatment158,161. These finding
were further supported by no observable changes in ectopic lipid deposition, plasma lipid
concentrations or inflammation following treatment158,161. Given the inconsistent findings in
human studies, as well as between studies in obese subjects rather than diabetic, a meta-analysis
set out to evaluate RSV insulin sensitizing effects by investigating the findings of eleven clinical
trials comprising approximately 400 subjects159. It was determined that RSV significantly
reduced fasting glucose and insulin concentrations and improved insulin sensitivity in diabetic
subjects, but had no significant effects on non-diabetic subjects, explaining the inconsistent
results outlined above159. Moreover, the administration of RSV to diabetic individuals
concurrently taking metformin and other hypoglycemic agents was found to improve glycemic
control compared to the hypoglycemic agents alone, supporting potential synergistic effects of
RSV in improving insulin sensitivity in humans163.
Although the beneficial effects and mechanisms of action of RSV are highly supported,
studies examining the absorption and metabolism of RSV suggest that in vivo bioavailability is
low. RSV degradation is highly sensitive to light, pH and temperature. Transition to the less
active cis-RSV isoform occurs rapidly upon exposure to light, while degradation is exponentially
increased when exposed to an alkaline pH of 7.4164. Moreover, temperature has no effect on RSV
when maintained in acidic pH, although degradation in an alkaline environment is accelerated
23
when temperature is raised over 25°C164. Although the rate of oral RSV absorption is high, it is
rapidly metabolized in vivo into one of two metabolites, namely trans-resveratrol-3-sulfate (R3S)
and trans-resveratrol-3-glucuronide (R3G), in the liver, intestines and lungs of humans and
rodents prior to entering systemic circulation165–169. Approximately 70% of absorbed RSV is
metabolized, resulting in very low amounts of free RSV in plasma for tissue delivery166,170. In
fact, the majority of absorbed RSV is metabolized to R3G in the small intestine before entering
the blood stream165. These metabolites have increased solubility and, although they exhibit
reduced cell permeability, the in vivo effects of RSV regardless of low bioavailability suggests
that R3G and R3S may in fact be the bioactive forms of RSV166,170. Importantly, R3S possesses
biological activity, while biological activity of R3G has yet to be reported168. A recent study has
compared the concentrations of these metabolites in liver, adipose tissue and skeletal muscle of
rats and found that the greatest concentration of metabolites were found in liver, followed by
adipose tissue and low amounts in skeletal muscle171. The large concentration of metabolites in
liver is not surprising, given the role of the liver in metabolizing RSV, while the intermediate
concentrations in adipose tissue suggest potential targeting of adipose tissue by RSV. Given the
low bioavailability of RSV, recent studies have focused on identifying means of increasing
bioavailability of free RSV through structural modifications or modified delivery170,172,173.
1.5.1 Combination Therapy: Potential of Resveratrol
The low potency of RSV and correspondingly high doses required to elicit beneficial
effects establish a need to develop means of increasing its metabolic effectiveness. Using RSV in
conjunction with a pharmacological anti-diabetic therapy represents an interesting therapeutic
approach, as RSV induces similar metabolic effects to TZDs in WAT and TZDs are successfully
used with other medications15,138. Unlike TZDs, which are known to increase weight gain and the
24
risk of cardiovascular mortality14,116–118, RSV is well-tolerated in animals and produces
beneficial effects in the absence of adverse side effects145. RSV has in fact been found to produce
cardioprotective effects such as decreased blood pressure and increased aortic mitochondrial
biogenesis to pre-diabetic levels in diabetic mouse models16,155,174,175.
MET is a well-tolerated pharmaceutical that produces anti-diabetic effects through
targeting HGP and skeletal muscle insulin sensitivity, in the absence of WAT effects observed
with RSV. Given that MET has separate mechanisms of action and is known to produce
beneficial effects when provided in combination with TZDs138, MET provides an ideal
pharmaceutical to test in combination with RSV. One study to date has examined the therapeutic
potential of RSV and MET in combination. However, hydroxymethylbutyrate (HMB), a leucine
metabolite, was also used in this examination of RSV and MET combination, as it was
previously shown to synergistically improve insulin sensitivity with RSV at concentrations that
had no sensitizing effects independently. MET, RSV and HMB combination therapy was found
to increase fat oxidation and both AMPK and SIRT1 activity in adipocyte and skeletal muscle
cell cultures when compared to each compound in isolation176. In a mouse model of genetically
induced diabetes, combination therapy increased insulin sensitivity and decreased both visceral
fat and liver weight, although no improvements were seen with each compound independently at
the selected doses176. Therefore, RSV could not only provide a synergistic therapeutic potential
to MET, but also reduce the required dose necessary to promote anti-diabetic effects. However,
this study failed to examine the mechanisms through which these therapies acted to increase
insulin action and to our knowledge no studies have examined these effects in a more
physiologically relevant model, such as diet-induced insulin resistance. As such, more research is
required to validate these findings in models of diet-induced diabetes.
25
Table 1.1: Summary of the therapeutic potential of TZDs, MET and RSV on factors deemed to
be important in the development of insulin resistance.
1.6. Conclusion & Future Directions
Insulin resistance is a multifactorial pathology characterized by lipotoxicity,
inflammation and mitochondrial dysfunction. As insulin resistance is a prerequisite for many
other pathological conditions, such as type 2 diabetes and the metabolic syndrome, it is important
to explore potential therapeutic options. Although weight loss and life-style interventions are
successful in reversing insulin resistance, it is often difficult for individuals to commit to
prolonged exercise or dietary interventions. As such, many pharmacological interventions have
been developed to improve insulin resistance. However, many current medications have varying
adverse side effects, from MET-induced gastrointestinal discomfort to the increased risk of
cardiovascular related mortality associated with TZDs. RSV, a natural polyphenol, provides an
interesting therapeutic approach, as many studies have shown anti-diabetic effects. However,
RSV has a very low bioavailability and as a result requires high daily intake to achieve the
described effects. Moreover, more work is required to establish a treatment effect in animal
models of diet-induced insulin resistance, as most work has focused on utilizing RSV in
prevention through prophylactic administration.
Future work is required to identify means of reducing the adverse effects of current
medications, or alternatively improving the effectiveness of natural compounds. Studies have
been performed to examine RSV analogues in an attempt to increase biological activity, while
26
medications are commonly used in combination therapy to improve insulin sensitivity. Utilizing
RSV in combination with MET could provide various synergistic effects. RSV represents an
ideal adjunct for use in combination with MET, as RSV may target the same metabolic processes
as TZDs, although through separate means, and would remove the associated adverse effects.
Although RSV has low potency, using it alongside MET could reduce the required dose through
targeting multiple contributors of insulin resistance, given the divergent mechanisms of these
compounds.
27
Chapter 2: Aims of Thesis
The whole-body and tissue specific anti-diabetic effects of RSV and MET have been widely
examined. MET primarily targets HGP and is known to produce synergistic effects with other
anti-diabetic therapies, while RSV targets adipose tissue inflammation, mitochondrial biogenesis
and adiponectin secretion as well as skeletal muscle mitochondrial biogenesis. However, RSV
effects have been largely supported in preventative models, and support of therapeutic effects in
treatment of established insulin resistance is lacking. Moreover, the potential for RSV and MET
to produce synergistic beneficial effects on glucose homeostasis has yet to be evaluated.
Therefore, the purposes of this thesis were to:
1. To examine the treatment effects of RSV and MET, independently and in combination,
on whole-body glucose homeostasis in a mouse model of diet-induced insulin resistance;
2. To examine the preventative effects of RSV and MET, independently and in
combination, on the development of diet-induced insulin resistance;
3. To identify if changes in mitochondrial content, inflammation or HGP could explain any
differences in insulin resistance following RSV and MET treatment.
It was hypothesized that:
1. RSV and MET will synergistically improve whole-body insulin and glucose tolerance in
a model of established insulin resistance;
2. Prophylactic treatment with RSV and MET will both prevent the development of
impairments in glucose homeostasis with a HFD and the combined effects will be greater
than either treatment alone;
28
3. The treatment and prevention of impaired glucose homeostasis with RSV or MET will be
associated with enhanced WAT and skeletal muscle insulin signaling, mitochondrial
content, attenuated inflammation and reductions in enzymes involved in HGP. These
effects will be greater with combined treatment than either compound independently.
29
Chapter 3: Resveratrol and Metformin Combination Therapy in
3.1 Methods
3.1.1 Materials
Trans-resveratrol (CAT# 70675) and metformin (CAT# 13118) were purchased from Cayman
Chemicals (Ann Arbor, MI). Low-fat (LFD: 10% kcal from fat; CAT# D12450B) and high-fat
(HFD: 60% kcal from fat; CAT# D12492) diets (Table 3.1) were purchased from Research Diets
(New Brunswick, NJ). Insulin was from Eli Lilly and glucose from BioShop. Reagents,
molecular weight marker and nitrocellulose membranes for SDS-PAGE were purchased from
Bio-Rad. Antibodies against and GAPDH (CAT# ab8245) was obtained from Abcam, PEPCK
(CAT# 10004943) was from Cayman Chemicals and G6Pase (CAT# 25840) was from Santa
Cruz. Total Akt (CAT# 4685), p-AKT threonine 308 (CAT# 9275), p-AKT serine 473 (CAT#
9271), total JNK (CAT# 9252), P-JNK (CAT# 4671), total ERK (CAT# 4695S), P-ERK (CAT#
9101S), total p38 (CAT# 9212S) and P-p38 (CAT# 9211S) antibodies were from Cell Signaling
(Danvers, MA). Western Lightening Plus Enhanced Chemiluminescence substrate was
purchased from Perkin Elmer (CAT# NEL105001EA). Horseradish peroxidase-conjugated
donkey anti-rabbit and goat anti-mouse IgG secondary antibodies were from Jackson
ImmunoResearch Laboratories (West Grove, PA). SuperScript II Reverse Transcriptase, random
primers and dNTP were products from Invitrogen (Burlington, ON). RNeasy mini kits and
Quiazol were from Quiagen. Taqman gene expression assays for mouse GAPDH (CAT#
4352932) and adiponectin (CAT# Mm00456425) were from Applied Biosystems.
30
Table 3.1: Macronutrient composition of the low and high fat diets used, measured as both a
percentage of total grams and percentage of total kilocalories. Total kcal/g is also displayed.
LFD
HFD
Protein
Carbohydrate
Fat
Total kcal/g
Percent of total mass
(g%)
Percent of total kcal
(kcal%)
Percent of total mass
(g%)
Percent of total kcal
(kcal%)
19.2
67.3
4.3
20
70
10
26.2
26.3
34.9
20
20
60
3.85
5.24
3.1.2 Experimental Design
8 week old male C57BL/6 mice were purchased from Charles River (Wilmington, MA) and
individually housed with a 8:00 to 20:00 12:12 hour light:dark cycle and ad libitum access to
standard rodent chow and water. All protocols were approved by the University of Guelph
Animal Care Committee and met the Canadian Council on Animal Care (CCAC) guidelines.
Following 1 week of acclimatization, the standard rodent chow was replaced by either LFD
(n=12; 10% kcal from fat) or HFD (n=40; 60% kcal from fat). Although a 60% kcal from fat
HFD is not representative of the typical diet in obese humans, we are using this model to induce
obesity and ensure impairments in glucose homeostasis are achieved. This HFD formulation has
been suggested for use with the C57BL/6 mouse model32 and we have previously used this diet
to induce insulin and glucose intolerance177. Animal and food weights were monitored one and
three days/week, respectively. The dietary intervention continued for 9 weeks, at which point
glucose and insulin tolerance testing (IPGTT and IPITT) were performed, 48 hours apart, in
order to verify differences in glucose homeostasis between LFD and HFD fed animals (Figure
3.1). The HFD animals were randomly assigned to 4 groups, HFD control, HFD - metformin
(MET; 250 mg/kg/day), HFD - resveratrol (RSV; 100 mg/kg/day), and a combination of both
(COM; MET: 250 mg/kg/day and RSV: 100 mg/kg/day). Animals were matched so body
31
weights and measures of glucose and insulin tolerance were similar between groups at the onset
of treatment (Appendix A). Drug treatments were mixed into food weekly, with drug dilutions
determined based on average daily food consumption and body weight within each group
(Appendix B). Doses were selected based on pilot work comparing effects of various metformin
and resveratrol doses on glucose and insulin tolerance (Appendix C and D). During the fifth
week of drug treatment IPGTT and IPITT protocols were repeated, with 48 hours between tests.
In a separate study, 8 week old male C57BL/6 mice were assigned into the
aforementioned groups (LFD, HFD, MET, RSV and COM; n=11/group) at the onset of the HFD
intervention in order to examine the preventative effects of treatment during the development of
insulin resistance (Figure 3.1). Animal and food weights were monitored one and three
days/week, respectively. The dose of each drug was equal to that of the treatment study in order
to allow comparisons to be made between the treatment and prevention studies. IPGTTs and
IPITTs were performed in these mice during week thirteen of the dietary intervention (Figure
3.1).
Figure 3.1: Time-line of the experimental design. The design of the treatment study is displayed
above the line, while the prevention study is below the line. The initiation of the HFD and drug
interventions are displayed, along with the times of GTT and ITT measures.
32
3.1.3 Glucose and Insulin Tolerance Testing
Intraperitoneal (IP) glucose (IPGTT) and insulin (IPITT) tolerance testing were performed as
measures of glucose homeostasis. The IPGTT assesses the capacity of animals to clear a glucose
load. Mice were fasted for 6h prior to an IP injection of glucose (2 g/kg body weight) for the
IPGTT. Blood glucose concentrations were determined via tail vein sampling at baseline and 15,
30, 45, 60, 90 and 120 minutes post-injection using a hand-held glucometer (Freestyle Lite,
Abbott).
The IPITT measures the ability of insulin to reduce blood glucose concentrations and is a
rough measure of whole body insulin action. Food was removed immediately prior to an IP
injection of insulin (0.5 U/kg). Blood glucose concentrations were determined via tail vein
sampling at baseline and at 15, 30, 45, 60, 90 minutes as described above. IPGTT and IPITT
measures were performed 48 hours (2 days) apart, with ad libitum access to their respective diets
maintained between tests. Changes in glucose over time were plotted per mouse, and the average
total area under the curve (AUC) for each group was calculated using the trapezoid rule. As such,
ΔX*(Y1+Y2)/2 represents the AUC between two corresponding plots, with the ΔX denoting the
time difference between two plots and the Y values representing the mmol/L concentration of
glucose at each plot. Therefore, AUC is presented in mmol/L*time. Baseline was set to Y=0.
For the treatment study, the relative difference in IPGTT and IPITT measures from HFD
were calculated with treatment groups and MET and RSV measures were used to predict the
effects of combined therapy. HFD was set to 100 in order to allow differences from treatment
groups to be observed as a percent change. Observed COM and predicted combined effects on
IPGTT and IPITT measures were then compared.
33
3.1.4 Metabolic Caging
Two days following the final IPGTT and IPITT (week 13 and week 12 in the treatment and
prevention studies, respectively) mice were placed in a Comprehensive Lab Animal Monitoring
System (CLAMS, Columbus Instruments, Columbus, OH) for a 24-hour period beginning at
7:00 am. The light:dark cycle was maintained as described above, and water and respective diets
were provided ad libitum while in the CLAMS. Oxygen consumption (VO2), respiratory
exchange ratio (RER), heat production and activity levels were determined. VO2 and activity are
measured directly, while RER and heat production are calculated by the CLAMS. As such:
RER =
!"#$%& !"#$"%& !"#$%&'(#) (!"#!)
!"#$%& !"#$%&'()"# (!"!)
Heat production = 3.815 + 1.232 𝑥 𝑅𝐸𝑅 𝑥 𝑉𝑂2 VCO2 used in calculation of RER is measured directly. The calculation for heat is based
off a least squares linear fit model and VO2 must be in liters/hour to yield a heat value in
kcal/hour. Measures were not analyzed from the first 6 hours of the light cycle, allowing time for
the mice to acclimate to the metabolic caging. The light cycle data was averaged or summed (for
activity) per animal over a 6 hour period, from 14:00 – 20:00, and dark cycle data was averaged
or summed over a 12 hour period, from 20:00 – 7:00.
3.1.5 Terminal Procedures
Mice were anesthetized with sodium pentobarbital (5mg/100g body weight, IP injection) in week
14 in the treatment study and week 13 in the prevention study. Given our interest in insulin
action and glucose homeostasis, terminal surgeries were performed in order to allow examination
of tissue specific insulin action. Inguinal subcutaneous and epididymal adipose tissue depots as
34
well as triceps from the left side of mice were excised, weighed and flash frozen or fixed in
formalin. Mice were then injected with insulin (1.25 U/kg) and 10 minutes post injection
subcutaneous and epididymal adipose tissue and triceps from the right side of mice, as well as
liver were excised, weighed and flash frozen. Intrathoracic blood was collected at this time.
Tissues were stored at -80°C until further analysis.
3.1.6 Histological Analysis
Epididymal adipose tissue was fixed in 10% neutral-buffered formalin (VWR, Mississauga, ON,
Canada), dehydrated in 70% ethanol (Fisher Scientific) and embedded in paraffin.
Five micrometer sections were mounted on 1.2mm Superfrost slides, stained with Harris
hematoxylin and eosin stock (Fisher Scientific) and imaged (Olympus FSX 100 light
microscope, Olympus, Tokyo, Japan). Cells (>100/image) were sampled in each image (2
images/mouse) to determine cross-sectional area (>200 cells/mouse) (ImageJ software, National
Institute of Mental Health, Bethesda, MD).
3.1.7 Western Blotting
Samples were homogenized in 3 (adipose tissue), 20 (skeletal muscle), or 30 (liver) volumes of
NP40 Cell Lysis Buffer (Life Technologies; CAT# FNN0021) supplemented with
Phenylmethylsulfonyl Fluoride and Protease Inhibitor Cocktail (Sigma; CAT# 78830, CAT#
P2714) using a FastPrep-24 Tissue Homogenizer (MP Biomedicals). Homogenized samples
were centrifuged at 4°C for 10 minutes at 1,500 X g and the supernatant collected from liver and
skeletal muscle, while the infranatant was collected from adipose tissue. A Bicinchoninic Acid
assay was performed to determine protein content of the homogenate. Equal amounts of protein
were then electrophoretically separated on 10% SDS-PAGE gels and then transferred to
35
nitrocellulose membranes at 100V for 1 hour at 4°C. Membranes were then blocked for 1 hour at
room temperature in 5% non-fat dry milk-TBST (tris buffered saline/0.1% tween 20).
Membranes were then incubated in primary antibody diluted 1:1000 in 5% BSA (Bovine Serum
Albumin)-TBST overnight with gentle agitation at 4°C. Following a 1-hour incubation at room
temperature with appropriate donkey anti-rabbit or goat anti-mouse HRP-conjugated secondary
antibodies (diluted in 1% non-fat dry milk-TBST), membranes were briefly washed and proteins
visualized by Western Lightning Plus-ECL using a Flourochem HD2 imager (Cell Biosciences)
and bands quantified using Alpha Innotech software (Santa Clara, CA). A housekeeping protein
(GAPDH) was measured in each gel to ensure equal loading. Phosphorylated protein measures
were made relative to total protein content of the protein of interest.
3.1.8 RT-PCR
Changes in mRNA expression of adiponectin were determined using real time qPCR as
described in detail previously by our laboratory15. RNA was isolated from inguinal subcutaneous
and epididymal adipose tissue using the Qiagen RNeasy kit according to the manufacturer’s
instructions. Complementary DNA (cDNA) was synthesized from 1µg of total RNA using
SuperScript II Reverse Transcriptase, random primers and dNTP. Real time PCR was carried out
using the CFX Connect Real-Time PCR Detection System (Bio-Rad). Each well contained 1 µL
of cDNA template, 8 µL of RNase free water, 1 µL gene expression assay and 10 µL of Taqman
Fast Universal PCR Master Mix. Relative differences between groups were determined using the
2-∆∆CT method178. The amplification efficiencies of the gene of interest and the housekeeping
gene were equivalent and the expression of GAPDH did not change between groups.
36
3.1.9 Statistical Analysis
A two-way repeated measures ANOVA (diet and time), followed by Tukey’s post-hoc analysis,
was used to examine differences in LFD and HFD IPGTT and IPITT curves at individual timepoints (0, 15, 30, 45, 60, 90 and 120 minutes) at 9 weeks of the treatment study. An unpaired
one-tailed t-test was performed to measure differences between LFD and HFD IPGTT and IPITT
AUC’s prior to drug-intervention in the treatment study. A one tailed t-test was chosen a priori
based on the prevalence of literature demonstrating impaired glucose and insulin tolerance
following long-term HFD26,32,177.
One-way ANOVA with Tukey’s post-hoc analysis was used to determine differences in
body and tissue weights, eWAT cell size, metabolic caging outcomes, liver Akt phosphorylation,
inflammatory protein phosphorylation, protein content of HGP regulating enzymes and
mitochondrial proteins and adiponectin expression. To examine differences in Akt
phosphorylation between groups (LFD, HFD, MET, RSV and COM) and within groups (basil vs.
insulin stimulated) in triceps, eWAT and scAT, a two-way repeated measures ANOVA with
Tukey’s post-hoc analysis was used.
When data were not normally distributed, as measured with Shapiro-Wilk normality
testing, log transformation was performed in order to achieve normal distribution. If normality
was not achieved, a non-parametric Kruskal-Wallis test with Dunn’s multiple comparisons
testing was performed on measures of one-way ANOVA. Although scAT Akt S473
phosphorylation in the prevention study was not normally distributed, the repeated measures
two-way ANOVA with Tukey’s post-hoc was performed as described above. Statistical
significance was set at p<0.05.
37
3.2 Results
a. Diet-Induced Changes in Whole-Body Parameters
Prior to treatment intervention, high-fat fed animals (HFD, MET, RSV and COM) weighed
significantly more than LFD at 9 weeks of dietary intervention (Table 3.2). Importantly, no
differences in body weight were observed between high-fat fed groups at this time. 9 weeks of
high-fat feeding significantly reduced whole-body glucose and insulin tolerance, as evidenced by
a higher glucose area under the curve (AUC) in the IPGTT and IPITT, respectively (Figure 3.2).
Treatment interventions (MET, RSV and COM) were initiated at this time.
Table 3.2: Body weight at onset of treatment and body and tissue weights at termination.
Body Weight (g)
LFD
HFD
MET
RSV
COM
Onset of
Treatment
34.7 ± 0.9
a
41.2 ± 1.5
a
42.2 ± 0.7
a
43.4 ± 1.1
a
43.7 ± 0.6
Liver Weight
Post-treatment
Absolute (g)
40.2 ± 0.8
1.9 ± 0.1
1.9 ± 0.2
2.0 ± 0.1
2.3 ± 0.2
2.1 ± 0.1
a
46.6 ± 1.2
a
46.4 ± 0.7
a
47.3 ± 1.0
a
44.5 ± 0.6
eWAT Weight
Relative
(mg/g BW)
49.4 ± 1.8
41.7 ± 3.4
44.0 ± 2.4
53.6 ± 2.5
48.3 ± 2.5
b
Absolute (g)
2.0 ± 0.1
2.3 ± 0.2
2.5 ± 0.2
c,e
1.8 ± 0.2
2.3 ± 0.1
Relative
(mg/g BW)
49.0 ± 2.2
50.0 ± 4.8
53.8 ± 3.8
c,e
36.4 ± 2.9
53.1 ± 3.2
Values are presented as mean ± SEM for n=9-17/group. Significance (p<0.05) is denoted by
letters: a different than LFD, b different than HFD, c different than MET, d different than RSV
and e different than COM.
38
b)
IPGTT
*
*
*
15
*
10
5
0
30
60
90
1500
1000
500
0
120
LF
Time (min)
d)
IPITT
*
6
HFD
LFD
2
0
15
30
45
60
75
400
200
0
90
D
4
LF
*
*
600
Time (min)
FD
*
*
8
0
Insulin Tolerance
800
10
Blood Glucose AUC
(mmol/L*time)
Blood Glucose (mmol/L)
c)
H
0
*
2000
H
20
2500
FD
HFD
LFD
*
Glucose Tolerance
D
25
Blood Glucose AUC
(mmol/L*time)
a)
Figure 3.2: HFD impairs glucose and insulin tolerance. IPGTT (a), IPGTT AUC (b) (n=12 LFD,
n=51 HFD), IPITT (c) and IPITT AUC (d) (n=12 LFD, n=47 HFD) for LFD and HFD C57BL/6
mice. Values are mean ± SEM. Significance (*) = p<0.05 compared to LFD.
b. Effects of MET, RSV and COM Therapy on Body and Tissue Weights
Five weeks of MET (231.28 ± 12.24 mg/kg/day), RSV (93.68 ± 3.51 mg/kg/day) or COM (MET
232.01 ± 17.12 mg/kg/day; RSV 92.77 ± 6.92 mg/kg/day) therapy had no effect on HFD-induced
weight gain and high-fat fed groups remained significantly heavier than LFD at 14 weeks (Table
3.2). No differences in absolute liver weight were observed between groups, although relative
liver weight in RSV treated mice was increased compared to HFD (Table 3.2). Absolute and
relative eWAT weight was reduced in RSV compared to MET and COM. No differences were
39
observed between groups in adipocyte cell size in eWAT (Figure 3.3) or in food intake
(Kcal/day) (data not shown).
eWAT Adipocyte Cell Size
Cross Sectional Area (um)
4000
4000
LFD
72 um
HFD
72 um
MET
72 um
RSV
72 um
COM
72 um
3000 3000
2000 2000
1000
O CO
M M
C
V
RS
V RS
ET
M
ET
M
FD
LF
H
LF
D
0
FD
0
H
1000
D
Cross Sectional Area (um2)
eWAT Adipocyte Cell Size
Figure 3.3: No differences in adipocyte cell size were observed between groups (n=4/group).
Values are mean ± SEM.
c. Whole-Body Glucose Homeostasis and Insulin Sensitivity
Following 13 weeks of high-fat feeding, HFD mice continued to display glucose intolerance, as
glucose AUC was significantly higher in IPGTT compared to LFD mice (Figure 3.4b). Four
weeks of treatment with MET or RSV did not improve HFD induced glucose intolerance, as
IPGTT AUC’s of mice treated with each compound independently were not different from HFD
mice (Figure 3.4b). However, COM treatment significantly improved glucose tolerance, as
displayed by a lower IPGTT AUC compared to HFD (Figure 3.4b). The predicted change in
glucose tolerance with combined treatment was calculated based on the observed changes of
RSV and MET independently. The observed change in AUC for IPGTT, relative to HFD, with
COM mirrored the predicted effects of COM (Figure 3.4c).
40
Similarly to the IPGTT findings, HFD mice remained insulin intolerant at 13 weeks, as
IPITT glucose AUC was higher compared to LFD (Figure 3.4e). Although RSV failed to
significantly improve insulin tolerance compared to HFD, RSV treated mice were not
significantly impaired when compared to LFD IPITT glucose AUC measures (Figure 3.4e). MET
and COM significantly improved insulin tolerance compared to HFD (Figure 3.4e). The
predicted change in insulin tolerance with combined therapy was calculated, as described above,
and the observed change in blood glucose AUC for IPITT, relative to HFD, with COM was
similar to the predicted effects of COM (Figure 3.4c).
b)
100
50
O
M
C
O
C
FD
H
M
O
d
AUC Relative to HFD
M
O
M
C
O
Pr
ed
ic
te
d
C
RS
V
0
0
FD
90
50
M
ET
Time (min)
75
100
H
60
M
45
O
30
C
15
200
RS
V
0
b
400
M
ET
0
b
600
FD
5
a
800
H
10
D
LFD
HFD
MET
RSV
COM
Change in Insulin Tolerance
150
1000
LF
15
f)
Insulin Tolerance
Pr
e)
IPITT
Blood Glucose AUC
(mmol/L*time)
d)
ed
ic
te
Time (min)
M
0
0
120
C
90
RS
V
60
M
ET
30
D
0
1000
LF
0
b
RS
V
10
a
a
2000
FD
20
a
M
ET
LFD
HFD
MET
RSV
COM
Change in Glucose Tolerance
150
3000
H
30
c)
Glucose Tolerance
AUC Relative to HFD
IPGTT
Blood Glucose AUC
(mmol/L*time)
a)
Figure 3.4: COM therapy improves HFD induced glucose and insulin intolerance. Predicted
combined effects of MET and RSV mirror the observed effects of COM. IPGTT (a,b) and IPITT
(d,e) measures, as well as percent change in IPGTT (c) and IPITT (f) from HFD, are presented
as mean ± SEM (n=11-18/group). Significance (p<0.05) is denoted by letters: a different than
LFD, b different than HFD, c different than MET, d different than RSV and e different than
COM.
41
d. Whole-Body Energy Expenditure
No differences in oxygen consumption or RER were observed between groups during the light
(Figure 3.5a and 3.5c) or dark cycles (Figure 3.5b and 3.5d). Moreover, heat production and total
activity were similar between groups (Figure 3.5e-h). a)
b)
Light VO2
40
20
40
20
0
0.6
0.4
0.2
M
O
C
0.2
M
O
C
RS
V
M
ET
M
O
C
RS
V
M
ET
D
FD
0.000
M
O
Light Total Activity
FD
0.005
h)
C
RS
V
M
ET
FD
H
LF
D
0.000
0.010
LF
0.005
Dark Heat
0.015
H
Heat Production (kcal/h)
0.010
H
LF
D
M
O
C
RS
V
M
ET
FD
D
LF
H
f)
Light Heat
0.015
Dark Total Activity
40,000
Total Activity (count)
5,000
4,000
3,000
2,000
1,000
30,000
20,000
10,000
M
O
C
RS
V
M
ET
D
LF
M
O
RS
V
M
ET
FD
H
D
LF
FD
0
0
H
RS
V
0.4
0.0
e)
M
ET
0.6
0.0
g)
Dark RER
1.0
0.8
RER (VCO2/VO2)
RER (VCO2/VO2)
0.8
H
LF
d)
Light RER
1.0
FD
D
M
O
C
RS
V
M
ET
H
FD
D
0
LF
c)
Dark VO2
60
VO2 (ml/kg/min)
VO2 (ml/kg/min)
60
C
Figure 3.5: Whole-body RER, oxygen consumption, heat and total activity are not effected by
diet or treatment. Light and dark VO2 (a,b), RER (c,d), heat (e,f) and total activity (g,h) values
are presented as mean ± SEM (n=2-4/group).
42
e. Tissue Specific Insulin Action
In order to evaluate tissue specific effects of MET, RSV and COM on insulin action, Akt
phosphorylation at S473 and T308 was examined in liver, triceps, eWAT and scAT. Akt
phosphorylation was measured following insulin injection in the liver, and before and after
insulin injection in triceps, eWAT and scAT (Figure 3.6). Importantly, a maximal dose of insulin
was used to examine tissue specific insulin action, and as such these measures are representative
of maximal insulin action and are not to be interpreted as differences in insulin sensitivity at the
tissue level. Therefore, HFD does not exhibit reduced insulin action in liver, triceps or scAT
compared to LFD, although eWAT Akt phosphorylation at S473 and T308 was significantly
reduced with HFD (Figure 3.7).
COM significantly increased liver Akt phosphorylation at S473 compared to LFD (Figure
3.7a). No differences in liver T308 phosphorylation were observed between groups (Figure
3.7b). Insulin significantly increased S473 and T308 AKT phosphorylation in all groups
compared to basal (Figure 3.6 and Figure 3.7c-d). Insulin stimulated triceps S473
phosphorylation was significantly increased in COM compared to LFD, HFD and RSV. MET
increased insulin-induced S473 phosphorylation compared to RSV (Figure 3.7c). No differences
were observed in triceps T308 phosphorylation between groups (Figure 3.7d).
Insulin increased S473 and T308 AKT phosphorylation in eWAT in all groups compared
to basal, with the exception of RSV which did not exhibit increased Akt phosphorylation at
either site following insulin stimulation (Figure 3.6 and Figure 3.7e-f). Insulin-stimulated S473
phosphorylation was significantly reduced in HFD eWAT compared to LFD. RSV had no effect
on HFD induced impairments in S473 AKT phosphorylation and remained significantly reduced
compared to LFD. Interestingly, MET and COM Akt S473 phosphorylation was not impaired
43
compared to LFD (Figure 3.7e). HFD, RSV and COM exhibited significantly reduced insulin
stimulated Akt T308 phosphorylation compared to LFD, while MET was not different from LFD
or HFD. MET exhibited increased Akt T308 phosphorylation compared to RSV (Figure 3.7f).
Insulin increased scAT Akt phosphorylation on both sites, in all groups, compared to
basal (Figure 3.6 and Figure 3.7g-h). Although there was no overall treatment effect for scAT
S473 phosphorylation (p=0.0808), COM significantly increased insulin stimulated S473
phosphorylation compared to RSV (Figure 3.7g). COM exhibited significant increases in T308
phosphorylation with insulin stimulation compared to HFD and RSV (Figure 3.7h).
a)
Triceps
b)
Liver
LFD
LFD HFD MET RSV COM
P- Akt S473
P- Akt S473
P- Akt T308
P- Akt T308
MET
RSV
COM
-
-
T- Akt
T- Akt
GAPDH
GAPDH
Insulin
c)
LFD
HFD
-
+
MET
RSV
LFD
COM
P- Akt S473
P- Akt T308
P- Akt T308
-
+ -
+
+
+
scAT
d)
eWAT
P- Akt S473
HFD
MET
RSV
COM
-
-
T- Akt
T- Akt
GAPDH
GAPDH
Insulin
HFD
-
+
-
+ -
+
-
+
-
+
Insulin
-
+
-
+ -
+
+
+
Figure 3.6: Representative blots for total and phosphorylated Akt (S473 and T308) in liver (a),
triceps (b), eWAT (c) and scAT (d).
44
a)
b)
Liver P-Akt (S473)
4
a
2
1
LFD
c)
HFD
MET
RSV
HFD
MET
MET
RSV
RSV
eWAT P-Akt (S473)
*
COM
Basal
Insulin
*
*
LFD
HFD
*
*
1
MET
RSV
COM
LFD
LFD+HFD
HFD+MET
MET+RSV
RSV+COM
COM+
eWAT P-Akt (T308)
*
*
a
*
a
*
2
HFD
MET
RSV
COM
h)
5
a
*
*
a
*
a,c
1
0
LFD
HFD+MET
MET+RSV
RSV+COM
COM+
g) LFDLFD+HFD
scAT
P-Akt
(S473)
LFD
HFD
MET
RSV
COM
LFD
LFD+HFD
HFD+MET
MET+RSV
RSV+COM
COM+
scAT P-Akt (T308)
5
d
*
*
*
3
b,d
*
4
P-Akt/T-Akt
4
P-Akt/T-Akt
2
f)
COM
1
*
*
2
3
*
2
*
*
*
1
1
0
RSV
3
2
0
MET
Triceps P-Akt (T308)
0
COM
P-Akt/T-Akt
3
LFD
HFD
HFD
*
P-Akt/T-Akt
P-Akt/T-Akt
e)
LFD
LFD
3
2
0
0.5
d)
c
*
*
4
1.0
a,b,d
*
*
*
1.5
0.0
COM
Triceps P-Akt (S473)
6
P-Akt/T-Akt
P-Akt/T-Akt
P-Akt/T-Akt
3
0
Liver P-Akt (T308)
2.0
LFD
HFD
MET
RSV
0
COM
LFD
HFD
MET
RSV
COM
LFD
LFD+HFD
HFD+MET
MET+RSV
RSV+COM
COM+
LFD
LFD+HFD
HFD+MET
MET+RSV
RSV+COM
COM+
Figure 3.7: Differences in liver (a,b), triceps (c,d), eWAT (e,f) and scAT (g,h) Akt S473 and
T308 phosphorylation at basal ( ) and following insulin stimulation ( ). Values are mean ±
SEM (n=7-11/group). Significance compared to basal within group (*) = p<0.05. Between
groups significance (p<0.05) is denoted by letters: a different than LFD, b different than HFD, c
different than MET, d different than RSV and e different than COM.
45
f. Adiponectin Expression
As adiponectin is known to have insulin sensitizing and glucose lowering effects109–111, we
examined whether changes in adiponectin expression in eWAT and scAT were associated with
COM induced changes in insulin action and glucose homeostasis. No diet or treatment
intervention induced changes in adiponectin expression in eWAT or scAT were observed
between groups (Figure 3.8a and 3.8b).
b)
1
O
C
LF
M
0
D
M
O
C
RS
V
M
ET
H
LF
FD
0.0
2
RS
V
0.5
3
M
ET
1.0
4
FD
Adiponectin mRNA expression
(relative to LF)
1.5
SQ
H
eWAT
D
Adiponectin mRNA expression
(relative to LF)
a)
Figure 3.8: Adiponectin expression is unaffected by HFD or treatment in eWAT (a) and scAT
(b). Values are mean ± SEM (n=6/group).
46
a. Body and Tissue Weights
HFD mice weighed significantly more than LFD mice (Table 3.3). Mice prophylactically treated
with MET (244.76 ± 16.30 mg/kg/day), RSV (95.14 ± 4.11 mg/kg/day) or COM (MET 240.81 ±
11.49 mg/kg/day; RSV 96.49 ± 4.58) for 13 weeks weighed significantly less than HFD,
effectively preventing the high-fat diet induced increases in body weight (Table 3.3). MET
significantly decreased absolute liver weight compared to HFD and relative liver weight
compared to LFD (Table 3.3). No differences were observed in absolute eWAT weight, although
relative eWAT weight was significantly increased in MET compared to LFD and RSV (Table
3.3). Food intake (Kcal/day) was not different between high-fat fed groups (data not shown).
Table 3.3: Body and tissue weights at termination.
Body Weight (g)
LFD
HFD
MET
RSV
COM
Liver Weight
Post-treatment
Absolute (g)
39.2 ± 0.7
1.8 ± 0.1
2.0 ± 0.1
a
47.5 ± 0.7
b
40.7 ± 0.9
b
40.8 ± 1.5
b
39.7 ± 1.3
eWAT Weight
Relative
(mg/g BW)
45.1 ± 1.2
41.0 ± 1.4
b
1.5 ± 0.1
1.7 ± 0.1
1.7 ± 0.03
38.6 ± 1.5
41.2 ± 1.0
42.9 ± 1.2
a
Absolute (g)
1.8 ± 0.1
2.1 ± 0.2
2.3 ± 0.2
1.9 ± 0.1
1.9 ± 0.2
Relative
(mg/g BW)
45.5 ± 1.5
45.9 ± 4.1
a
56.3 ± 2.7
c
45.1 ± 2.0
47.8 ± 3.2
Values are presented as mean ± SEM for n=8-11/group. Significance (p<0.05) is denoted by
letters: a different than LFD, b different than HFD, c different than MET, d different than RSV
and e different than COM.
b. Whole-Body Glucose Homeostasis and Insulin Sensitivity
At 12 weeks, HFD mice were significantly glucose and insulin intolerant compared to LFD, as
measured through IPGTT AUC and IPITT AUC, respectively (Figure 3.9). MET, RSV and
COM therapy prevented HFD induced glucose intolerance, with no significant differences
between treatment groups and LFD (Figure 3.9a and 3.9b). Moreover, MET, RSV and COM all
47
prevented HFD induced insulin intolerance, and in fact displayed significantly higher insulin
tolerance compared to HFD mice (Figure 3.9c and 3.9d).
b)
IPGTT
30
LFD
HFD
MET
RSV
COM
20
10
a
2000
1500
1000
500
d)
IPITT
LFD
HFD
MET
RSV
COM
5
60
75
M
O
C
FD
500
0
90
Time (min)
M
45
b
O
30
b
C
15
b
D
0
a
1000
LF
0
1500
RS
V
10
Insulin Tolerance
M
ET
15
Blood Glucose AUC
(mmol/L*time)
c)
M
ET
Time (min)
H
120
FD
90
H
60
D
30
RS
V
0
0
LF
0
Glucose Tolerance
2500
Blood Glucose AUC
(mmol/L*time)
a)
Figure 3.9: MET, RSV and COM therapy prevent HFD induced glucose and insulin intolerance.
IPGTT (a), IPGTT AUC (b), IPITT (c) and IPITT AUC (d) for LFD, HFD, MET, RSV and
COM C57BL/6 mice (n=8-11/group). Values are mean ± SEM. Between groups significance
(p<0.05) is denoted by letters: a different than LFD, b different than HFD, c different than MET,
d different than RSV and e different than COM.
c. Whole-Body Energy Expenditure
Similar to the treatment study, no differences in oxygen consumption were observed between
groups during the light or dark cycle (Figure 3.10a and 3.10b). However, MET displayed lower
RER compared to LFD during the dark phase, indicating a greater reliance on fat for energy
production (Figure 3.10c and 3.10d). Heat production and total activity was similar between all
groups (Figure 3.10e and 3.10f).
48
a)
b)
Light VO2
40
20
40
20
1.0
0.8
0.8
0.6
0.4
0.2
M
O
C
RS
V
M
ET
FD
Dark RER
1.0
a
0.6
0.4
0.2
h)
Light Total Activity
M
O
RS
V
FD
M
ET
C
M
O
C
O
LF
D
M
0.000
C
RS
V
M
ET
FD
H
LF
D
0.000
0.005
RS
V
0.005
0.010
M
ET
0.010
Dark Heat
0.015
FD
0.015
g)
H
LF
D
M
O
RS
V
C
f)
Light Heat
H
e)
M
ET
H
LF
FD
0.0
D
0.0
Dark Total Activity
30,000
6,000
4,000
2,000
20,000
10,000
M
O
RS
V
M
ET
LF
D
M
O
RS
V
M
ET
FD
H
D
LF
FD
0
0
H
H
LF
D
M
O
RS
V
C
d)
Light RER
RER (VCO2/VO2)
RER (VCO2/VO2)
c)
M
ET
H
LF
FD
0
D
0
Dark VO2
60
VO2 (ml/kg/min)
VO2 (ml/kg/min)
60
49
C
C
Figure 3.10: MET reduces RER compared to LFD during the light and dark cycles (c,d). No
changes in oxygen consumption (a,b), heat (e,f) or total activity (g,h) were observed between
groups. Values are mean ± SEM (n=3-5/group). Between groups significance (p<0.05) is
denoted by letters: a different than LFD, b different than HFD, c different than MET, d different
than RSV and e different than COM.
d. Tissue Specific Insulin Action
As described for the treatment study, tissue specific effects of MET, RSV and COM on insulin
action were examined through measuring Akt phosphorylation in liver, triceps, eWAT and scAT
(Figure 3.11). Liver Akt S473 phosphorylation was significantly increased by MET compared to
LFD and HFD mice (Figure 3.12a). As was described in the treatment study, a maximal insulin
dose was used to examine changes in Akt phosphorylation and these measures are representative
of maximal insulin action, not insulin sensitivity, at the tissue level. Therefore, HFD does not
exhibit reduced insulin action at any tissue compared to LFD, with the exception of reduced
eWAT S473 Akt phosphorylation. No differences in liver T308 phosphorylation were observed
between groups (Figure 3.12b).
Insulin significantly increased Akt S473 and T308 phosphorylation in triceps in all
groups (Figure 3.11 and Figure 3.12c-d). Insulin stimulated Akt S473 phosphorylation in triceps
was significantly increased in COM compared to all other groups. No differences were observed
in triceps Akt T308 phosphorylation between groups (Figure 3.12d).
With the exception of the HFD group on S473, insulin significantly increased eWAT Akt
phosphorylation in all groups (Figure 3.11 and Figure 3.12e-f). Insulin-stimulated S473
phosphorylation was significantly reduced in HFD eWAT compared to LFD. MET, RSV and
COM therapy prevented HFD induced impairments in S473 phosphorylation, as all three
treatment groups exhibited significantly higher insulin stimulated S473 phosphorylation
compared to HFD (Figure 3.12e). Although there was no overall treatment effect for eWAT
T308 phosphorylation (p=0.0505), MET and COM significantly increased insulin stimulated
T308 phosphorylation compared to HFD (Figure 3.12f).
50
All groups exhibited significantly increased insulin stimulated scAT S473 and T308
phosphorylation compared to basal levels within each group (Figure 3.11 and Figure 3.12g-h).
COM had significantly higher insulin stimulated S473 phosphorylation compared to LFD, HFD
and RSV (Figure 3.12g). MET displayed significantly higher insulin stimulated T308
phosphorylation compared to HFD (Figure 3.12h). COM significantly increased insulin
stimulated T308 phosphorylation compared to all groups (Figure 3.12h).
a)
Triceps
b)
Liver
P- Akt S473
P- Akt S473
P- Akt T308
P- Akt T308
RSV
COM
T- Akt
T- Akt
GAPDH
GAPDH
Insulin
c)
MET
HFD
-
+
d)
eWAT
LFD
RSV
-
+
-
+ -
+
-
+
scAT
MET
HFD
LFD
COM
RSV
COM
P- Akt S473
P- Akt S473
P- Akt T308
P- Akt T308
T- Akt
T- Akt
GAPDH
GAPDH
Insulin
MET
HFD
LFD
LFD HFD MET RSV COM
-
+
-
+
-
+
-
+
-
Insulin
+
-
+
-
+
-
+
-
+ -
+
Figure 3.11: Representative blots for total and phosphorylated Akt (S473 and T308) in liver (a),
triceps (b), eWAT (c) and scAT (d).
51
a)
b)
Liver P-Akt (S473)
4
a,b
2
1
LFD
c)
HFD
1.5
P-Akt/T-Akt
P-Akt/T-Akt
3
0
MET
RSV
1.0
0.5
0.0
COM
*
*
2
*
P-Akt/T-Akt
P-Akt/T-Akt
a,b,c,d
*
*
1
LFD
HFD
MET
RSV
MET
RSV
COM
Triceps P-Akt (T308)
6
*
b
*
b
*
a
2
Basal
Insulin
*
*
*
2
*
1
f)
LFD
HFD
MET
RSV
COM
LFD
LFD+HFD
HFD+MET
MET+RSV
RSV+COM
COM+
eWAT P-Akt (T308)
10
8
P-Akt/T-Akt
b
*
*
3
0
COM
HFD+MET
MET+RSV
RSV+COM
COM+
e) LFDLFD+HFD
eWAT P-Akt (S473)
P-Akt/T-Akt
HFD
4
3
4
LFD
d)
Triceps P-Akt (S473)
4
0
Liver P-Akt (T308)
2.0
b
*
b
*
6
*
*
*
4
2
0
LFD
HFD
MET
RSV
HFD+MET
MET+RSV
RSV+COM
COM+
g)LFDLFD+HFD
scAT P-Akt (S473)
10
0
COM
a,b,d
*
h)
LFD
HFD
MET
RSV
COM
LFD
LFD+HFD
HFD+MET
MET+RSV
RSV+COM
COM+
scAT P-Akt (T308)
15
6
*
*
4
P-Akt/T-Akt
P-Akt/T-Akt
8
a,b,c,d
*
10
*
*
b
*
*
*
*
5
2
0
LFD
HFD
MET
RSV
COM
0
LFD
HFD
MET
RSV
COM
LFD
LFD+HFD
HFD+MET
MET+RSV
RSV+COM
COM+
LFD
LFD+HFD
HFD+MET
MET+RSV
RSV+COM
COM+
Figure 3.12: Differences in liver (a,b), triceps (c,d), eWAT (e,f) and scAT (g,h) Akt S473 and
T308 phosphorylation at basal ( ) and following insulin stimulation ( ). Values are mean ±
SEM (n=6-11/group). Significance compared to basal within group (*) = p<0.05. Between
groups significance (p<0.05) is denoted by letters: a different than LFD, b different than HFD, c
different than MET, d different than RSV and e different than COM.
52
e. Protein content of Enzymes Regulating HGP
MET is thought to act primarily through attenuation of HGP12,122,126. We therefore examined the
protein content of two key regulators of this process, glucose 6 phosphatase (G6Pase) and
phosphoenolpyruvate carboxykinase (PEPCK), in the liver. No differences in G6Pase protein
content were observed between groups (Figure 3.13a and 13.3c). Surprisingly, PEPCK content
increased in both MET and COM compared to LFD and HFD (Figure 3.13b-c). However, it is
important to note that protein content is not a direct measure of HGP.
b)
Liver G6Pase
1.5
1.5
1.0
1.0
PEPCK
0.5
a,b
a,b
LFD HFD MET RSV COM
G6Pase
PEPCK
GAPDH
0.5
M
O
C
RS
V
M
ET
FD
H
D
M
O
C
RS
V
M
ET
H
LF
FD
0.0
D
0.0
c)
Liver PEPCK
LF
G6Pase
a)
Figure 3.13: Liver G6Pase (a,c) and PEPCK (b,c) expression are unaffected by HFD, while
MET and COM exhibit increased PEPCK content (b,c). Values are mean ± SEM (n=6-11/group).
f. Regulation of Inflammatory Pathways
Inflammation has been established as a key contributor to the development of insulin
resistance8,56,57. We therefore sought to determine if the beneficial effects of MET, RSV and
COM on whole-body glucose homeostasis could be attributed to reductions in pro-inflammatory
signaling. HFD did not exhibit increased phosphorylation of JNK, Erk or p38 in scAT or eWAT,
three proteins important in pro-inflammatory signaling (Figure 3.14). Moreover, RSV, MET and
COM did not significantly reduce phosphorylation at any site, and MET in fact exhibited
increased p38 phosphorylation compared to LFD in scAT.
53
scAT
b)
eWAT
LFD HFD MET RSV COM
LFD HFD MET RSV COM
P- JNK
P- JNK
T- JNK
T- JNK
P- erk
P- erk
T- erk
T- erk
P- p38
T- p38
P- p38
T- p38
Ponceau
Ponceau
d)
2.0
1.0
0.5
P-p38/T-p38
0.5
M
O
RS
V
M
ET
1.0
0.5
M
O
M
O
C
RS
V
M
ET
FD
H
D
0.0
LF
M
O
C
RS
V
M
ET
FD
H
LF
D
0.0
1.5
C
P-Erk/T-Erk
P-JNK/T-JNK
1.0
0.5
0.0
eWAT P-p38
2.0
2.0
1.0
C
h)
1.5
1.5
FD
LF
D
M
O
C
RS
V
eWAT P-Erk
RS
V
2.5
M
ET
FD
H
LF
g)
M
ET
eWAT P-JNK
1.0
0.0
D
M
O
C
RS
V
M
ET
FD
H
LF
f)
1.5
0.5
0.0
D
0.0
1.5
H
0.5
a
2.0
FD
1.0
scAT P-p38
2.5
P-p38/T-p38
1.5
P-Erk/T-Erk
P-JNK/T-JNK
2.0
e)
scAT P-Erk
H
scAT P-JNK
D
c)
LF
a)
Figure 3.14: Activation of key inflammation regulating pathways JNK, erk and p38 (a-b) is
unchanged by HFD and not reduced following MET, RSV and COM treatment in scAT (a,c-e)
and eWAT (b,f-h) (n=6-11/group).
54
Chapter 4: Discussion
This thesis presents a novel examination of the potential synergistic effects of RSV and
MET in prevention and treatment of insulin resistance. The tissue specific effects of RSV, MET
and COM treatment on insulin action were examined, as well as potential mechanisms of action.
To our knowledge, this is the first study to examine the combined effects of RSV and MET on
insulin action and glucose homeostasis. Moreover, as most research on the anti-diabetic effects
of RSV has been performed in prophylactic models, and recent work in cell culture suggests that
RSV is only effective when given prior to establishing insulin resistance179, this study provides
novel insight into the differential effects of RSV in prevention and treatment of insulin resistance
in vivo.
4.1 Treatment Study
4.1.1 Whole-Body Glucose Homeostasis and Tissue Specific Insulin Action
The treatment study was performed in order to examine the synergistic effects of RSV
and MET. The selected doses were chosen as they did not independently reduce glucose and
insulin tolerance in preliminary experiments (Appendix A). RSV failed to significantly reduce
HFD induced insulin resistance when administered to mice with established insulin resistance. In
contrast, previous work has shown that 4-10 weeks of RSV treatment increases insulin
sensitivity, independent of changes in body weight16,145. Interestingly, insulin action was reduced
in eWAT by RSV compared to LFD, exhibiting similar reductions to those observed with HFD.
Perhaps more alarming, eWAT Akt phosphorylation was not significantly increased by insulin
stimulation in RSV treated mice compared to basal levels, indicating pronounced insulin
resistance in this tissue. This finding is supported by the identification of RSV induced
reductions in insulin action in 3T3-L1 adipocytes180.
55
Although MET induced improvements in insulin sensitivity are highly
supported120,127,139,176, we found that MET treatment in insulin resistant mice did not improve
glucose tolerance compared to HFD, although a non-significant reduction in IPGTT AUC was
observed. Moreover, MET remained significantly glucose intolerant compared to LFD.
However, MET significantly increased insulin tolerance compared to HFD. The lack of a MET
effect on liver insulin signaling was unexpected, as previous reports have identified increases in
liver insulin signaling in diabetic rats and potentiated insulin responsiveness in hepatocytes with
MET120,130.
Perhaps the most interesting finding is that COM therapy significantly improved wholebody insulin sensitivity in the treatment study. This is a novel finding, as RSV and MET were
incapable of improving glucose tolerance when administered independently, although MET
improved insulin tolerance. Therefore, RSV and MET additively improved glucose tolerance. In
fact, the observed COM improvements in glucose and insulin tolerance relative to HFD are
nearly identical to the sum of RSV and MET improvements independently. These findings are in
agreement with those of a previous study that found improved whole-body insulin sensitivity
with a combination of MET, RSV and HMB176. However, the RSV dose (12.5 mg/kg diet) was
much lower to that used in our study, while HMB (2 g/kg diet) was given at a comparatively
larger dose than both RSV and MET (0.25-0.75g/kg diet)176. Therefore, the findings of the
aforementioned study may be more representative of the combined effects of HMB and MET.
COM also induced superior tissue specific insulin signaling in scAT and triceps.
Although MET is not known to effect WAT insulin action, long-term RSV is known to increase
insulin action in this tissue146. However, it appears likely that RSV and MET act synergistically
to induce these improvements, as RSV and MET independently did not increase insulin signaling
56
in scAT. Alternatively, RSV has been shown to increase myotube insulin action and MET
induces increases in insulin action in muscle120,125,144, suggesting a potential for insulin
sensitizing effects to occur with COM in triceps. To our knowledge, this is the first study to
examine the combined effects of RSV and MET on tissue specific insulin action.
4.1.2 Association of Insulin Sensitivity with Body Weight
As obesity is a risk factor in the development of insulin resistance, it is not surprising that
weight loss is associated with increased insulin sensitivity. RSV did not reduce body weight
when given as a treatment for established insulin resistance, supporting the findings of
others16,145. MET therapy is commonly associated with reduced body weight, although this has
only been established with long-term treatment12,88,120,139,181. However, no differences in body
weight were observed from HFD with treatment in our model. This is supported by short-term
(2-4 weeks) MET treatment findings, as no differences in body weight or fat mass were
observed127,176. The effects of COM therapy on body weight were identical to those of RSV and
MET, as no changes were observed in treatment compared to HFD. Therefore, increased glucose
and insulin tolerance cannot be explained by weight loss in COM.
4.2 Prevention Study
4.2.1 Whole-Body Glucose Homeostasis and Tissue Specific Insulin Action
We found that RSV prevented HFD induced glucose and insulin intolerance when
administered prophylactically. These findings are similar to previous work from our lab, which
has shown that RSV prevents glucose and insulin tolerance in Zucker Diabetic Fatty (ZDF) rats,
a genetic model of insulin resistance15. Moreover, others have observed increased whole-body
insulin sensitivity with RSV in prophylactically treated rodents143,145,146. RSV also significantly
increased insulin action in eWAT compared to HFD. This was expected, as a similar 13 week
57
prevention model found that RSV induced increases in insulin signaling in WAT146. Targeting of
WAT insulin signaling by RSV is supported by bioavailability studies in rodents, which show
greater concentrations of RSV and its metabolites, R3G and R3S, in WAT compared to skeletal
muscle171. Therefore, it is not surprising that we did not observe increased insulin action in
skeletal muscle, as RSV concentrations have been shown to be below levels of detection in this
tissue171.
MET prevented HFD-induced glucose intolerance and significantly improved insulin
tolerance compared to HFD. These findings are supported not only by previous treatment
findings120,127,139,176, but also by reported reductions in the incidence of type 2 diabetes following
prophylactic administration of MET in at risk subjects88. Previous reports have identified
increases in liver insulin action in diabetic rats and potentiated insulin responsiveness in
hepatocytes with MET120,130. Our findings in the prevention study support this, as MET treatment
increased liver insulin action compared to HFD. No differences in triceps insulin action were
observed with MET, although MET may have improved glucose and insulin tolerance through an
indirect mechanism to additively increase insulin action in skeletal muscle120,125. Our novel
findings of increased insulin signaling in eWAT and scAT identify WAT as a potential target for
improved glucose homeostasis effects of MET.
The prevention effects of COM therapy on glucose and insulin tolerance are identical to
those of RSV and MET independently, and therefore there does not appear to be an additive
effect of RSV and MET in this model. However, it is plausible that reducing RSV and MET
doses would increase the potential to detect synergistic or additive effects, although this would
limit our ability to compare our prevention and treatment experiments. COM was found to
increase eWAT insulin signaling compared to HFD, similar to the effects of MET and RSV.
58
However, COM has greater effects on tissue specific insulin action in scAT and triceps and
therefore RSV and MET may synergistically increase tissue specific insulin action in these
tissues. The synergistic effects of RSV and MET in triceps are expected, given that RSV has
been shown to increase myotube insulin action and MET induces increases in insulin signaling in
muscle120,125,144.
4.2.2 Association of Insulin Sensitivity with Body Weight
The insulin sensitizing effects of RSV in the prevention study may be explained by our
observed reductions in body weight, as weight loss is associated with increased insulin
sensitivity. RSV has previously been shown to prevent HFD induced increases in body weight
when given prophylactically145–147. Similar to RSV, MET therapy reduced body weight
compared to HFD in the prevention study. This is in agreement with previous findings that body
weight is reduced with MET12,88,120,139,181. The effects of COM therapy on body weight were
identical to those of RSV and MET, as significant decreases compared to HFD were observed.
Body weight is regulated by caloric intake and energy expenditure145. However, reduced body
weight with RSV, MET and COM cannot be explained by food intake or energy expenditure, as
no differences were observed compared to HFD.
4.3 Differences in Responses to Treatment and Prevention
RSV produced opposing effects on glucose and insulin tolerance between treatment and
prevention studies, with only the prevention study exhibiting improved insulin sensitivity.
Although RSV is known to prevent HFD induced increases in body weight when given
prophylactically145–147, it does not appear to produce similar effects on body weight when given
as a treatment for established insulin resistance16,145. Therefore, it appears that although RSV
may effectively prevent increases in body weight, it is not capable of reducing body weight..
59
RSV induced insulin sensitizing effects in the prevention study may be mediated through
reduced body weight compared to HFD as obesity is associated with insulin resistance.
Differences in the length of RSV administration between the treatment and prevention studies
could explain the different responses to RSV, as the treatment persisted for 4 weeks and the
prevention persisted for 12 weeks. However, this is not likely to be the case, as a previous study
has examined the differences in response to RSV with 4 and 13 weeks of prophylactic
administration, with only the 4 week treatment exhibiting significantly decreased GTT AUC146.
Importantly, the insulin sensitivity responses to various lengths of RSV administration has yet to
be examined in a treatment model and thus the impact of treatment length cannot be conclusively
negated as a factor mediating the differential responses between our models.
Conversely, MET increased insulin tolerance in both prevention and treatment, although
glucose tolerance was only improved in prevention. Importantly, increased insulin tolerance by
MET in both studies may be mediated through indirect mechanisms on insulin action, as MET
has been shown to additively increase insulin-stimulated skeletal muscle glucose disposal
without changing insulin signaling directly120,125. Similar to RSV, MET had no effect on body
weight with treatment, although body weight was significantly reduced in the prevention study
compared to HFD. The length of the treatment period appears to be important in MET induced
changes in body weight, as no differences are observed following short-term (2-4 weeks) MET
administration127,176. Therefore, different MET effects on body weight in the prevention and
treatment studies are not surprising, as MET was administered for 12 weeks and 4 weeks,
respectively.
As COM increased glucose and insulin tolerance in a similar manner in both studies, it is
unlikely that improvements in glucose homeostasis can be solely attributed to weight loss, as the
60
treatment study did not exhibit weight loss. Therefore, other mechanisms are likely responsible.
Increased insulin action in scAT and triceps may explain improved whole body insulin
sensitivity with COM, as these effects were greater than RSV and MET independently in both
studies. To our knowledge, this is the first set of studies to examine the effects of RSV and MET,
independently and in combination, on insulin sensitivity in treatment and prevention in vivo.
4.4 Conclusion
In conclusion, this thesis presents novel insight into the combined effects of RSV and
MET in prevention and treatment of insulin resistance. We have shown that RSV and MET are
potent prophylactic treatments in preventing the development of insulin resistance, while
treatment effects were not observed in our model. Perhaps the most important finding of this
study is the improvement in whole-body glucose homeostasis and insulin sensitivity observed
with COM in the treatment study. This is interesting, given that RSV and MET had no
significant effects when provided at the same dose independently, although MET increased
insulin tolerance compared to HFD.
Combination therapy is important to examine in diabetic subjects, as they frequently experience
poor responses to monotherapy13. Although controversial158, a few studies have provided
evidence supporting that RSV improves whole body insulin sensitivity in humans159,163.
Moreover, MET is known to independently improve whole body insulin resistance in humans
and acts synergistically with other anti-diabetic therapies13 that induce similar effects to RSV15.
Therefore our findings may potentially extend to the human population. However, future work in
human clinical trials is required using RSV and MET combination therapy.
61
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75
Appendix A
Treatment study body weight, IPITT AUC and IPGTT AUC averages for high-fat fed groups
prior to treatment. Animals were matched for body weight and glucose and insulin tolerance to
ensure groups were similar at the onset of treatment.
Body Weight (g)
IPITT (AUC)
IPGTT (AUC)
HFD
41.18 ± 1.50
686.36 ± 40.17
1898.73 ± 173.67
MET
42.23 ± 0.72
695.18 ± 47.64
1838.98 ± 148.94
RSV
43.38 ± 1.10
688.88 ± 42.61
1952.18 ± 136.18
COM
43.65 ± 0.58
694.64 ± 36.38
1869.27 ± 105.09
76
Appendix B
Drug dilution calculation:
Dose (mg/kg/day) = drug consumed/day (mg) ÷ mouse weight (kg)
= [food consumed/day (g)*drug dilution in food (mg/g)] ÷ mouse weight (kg)
Desired dose (mg/kg/day), avg mouse weight (g) and avg food consumed/day (mg) are known.
Therefore,
Drug dilution in food (mg/g) = [dose (mg/kg/day)*mouse weight (kg)] ÷ food consumed/day (g)
77
Appendix C
MET doses for the treatment study were selected based on pilot work comparing effects of
various doses on glucose and insulin tolerance. High (HFD-HM; 250mg/kg/day), medium (HFDMM; 125mg/kg/day) and low (HFD-LM; 62.5mg/kg/day) doses of MET were compared to HFD
and HFD-HM was chosen for the treatment study, as it improved both glucose and insulin
tolerance although it was not significantly different from HFD.
Metformin
b)
LFD
HFD
HFD-HM
HFD-MM
HFD-LM
20
10
LFD
HFD
HFD-HM
HFD-MM
HFD-LM
5
M
-L
FD
-M
FD
H
M
-L
FD
H
H
Time (min)
M
0
90
-M
75
FD
60
M
45
200
-H
30
400
FD
15
600
D
0
800
LF
0
Insulin Tolerance
1000
FD
10
d)
H
IPITT
15
Blood Glucose AUC
(mmol/L*time)
c)
H
H
Time (min)
M
0
120
M
90
500
H
60
1000
-H
30
1500
D
0
2000
LF
0
a
FD
30
Glucose Tolerance
2500
FD
40
H
IPGTT
Blood Glucose AUC
(mmol/L*time)
a)
IPGTT (a), IPGTT AUC (b), IPITT (c) and IPITT AUC (d) for LFD, HFD, HFD-HM, HFD-MM
and HFD-LM C57BL/6 mice (n=6/group). Values are mean ± SEM. Between groups
significance (p<0.05) is denoted by letters: a different than LFD, b different than HFD, c
different than HFD-HM, d different than HFD-MM and e different than HFD-LM.
78
Appendix D
RSV doses for the treatment study were selected based on pilot work comparing effects of
various doses on glucose and insulin tolerance. High (HFD-HR; 200mg/kg/day) and low (HFDLR; 100mg/kg/day) doses of RSV were compared to HFD and HFD-LR was chosen for the
treatment study, as it improved both glucose and insulin tolerance although it was not
significantly different from HFD, while HFD-HR exhibited worsened glucose and insulin
tolerance. The worsening with HFD-HR may not be surprising, as a previous study has suggested
that larger doses of RSV may be associated with poor tolerance170.
Resveratrol
LFD
HFD
HFD-HR
HFD-LR
20
10
0
H
LFD
HFD
HFD-HR
HFD-LR
10
5
R
-L
0
H
Time (min)
R
-L
90
FD
75
H
60
R
45
200
-H
30
400
FD
15
600
D
0
800
LF
0
Insulin Tolerance
1000
FD
15
d)
H
IPITT
Blood Glucose AUC
(mmol/L*time)
c)
FD
Time (min)
H
120
R
90
-H
60
1000
FD
30
2000
D
0
a
LF
0
Glucose Tolerance
3000
FD
30
b)
H
IPGTT
40
Blood Glucose AUC
(mmol/L*time)
a)
IPGTT (a), IPGTT AUC (b), IPITT (c) and IPITT AUC (d) for LFD, HFD, HFD-HR and HFDLR C57BL/6 mice (n=6/group). Values are mean ± SEM. Between groups significance (p<0.05)
is denoted by letters: a different than LFD, b different than HFD, c different than HFD-HR and d
different than HFD-LR.
79

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