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Chapter-1

Introduction

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1.1 Diabetes mellitus

Diabetes mellitus is a metabolic disorder defined by disturbances in glucose metabolism

leading to chronic hyperglycemia. It is diagnosed by elevated levels of glucose in the fasting

state or reduced glucose clearance after an oral glucose tolerance test (OGTT) [1, 2]. It is a

group of heterogeneous disorders with the common elements of hyperglycemia and glucose

intolerance due to reduced insulin, ineffectiveness of insulin or both [3]. Based on etiology

and clinical representation, diabetes mellitus is classified into four types-

a. Type 1 diabetes (T1D)

b. Type 2 diabetes (T2D)

c. Gestational diabetes

d. Other specific types

T1D is also known as insulin dependent, auto immune or juvenile onset diabetes. It is

caused because of the auto immune destruction of insulin producing pancreatic beta cells. As

a result, there is no or little insulin, the hormone responsible for maintaining blood glucose

homeostasis. T1D can affect people of any age, but is mostly diagnosed in children or young

adults [4]. People with T1D need daily insulin injection and hence the nomenclature insulin

dependent diabetes mellitus. Gestational diabetes on the other hand is glucose intolerance of

varying severity often diagnosed during pregnancy [5]. Women who develop gestational

diabetes are at risk for the development of T2D in the future [6]. The offspring is also at a

risk of developing obesity and abnormal glucose metabolism during their adult life [7]. Other

specific types of diabetes include a number of different types of diabetes both due to genetic

as well as non genetic factors [8]. Monogenic forms of diabetes like maturity onset diabetes

of the young (MODY), neonatal diabetes mellitus (NDM), latent autoimmune diabetes in

adults (LADA), maternally inherited diabetes and deafness (MIDD), drug induced diabetes,

diabetes due to rare immune mediated disorders such as stiff-man syndrome are example of

other specific types of diabetes.

T2D, also known as non-insulin dependent diabetes mellitus (NIDDM), is the most

common form of diabetes and is characterized by chronic hyperglycemia associated with

insulin resistance and relative insulin deficiency. T2D accounts for more than 90% of all

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forms of diabetes [4, 8]. It is often diagnosed in subjects above 40yrs of age but could occur

earlier also, especially in populations with high prevalence of diabetes. This form of diabetes

is most commonly associated with obesity, older age, family history of T2D, physical

inactivity and certain ethnicities [4, 8]. The symptom of T2D develop gradually and include

fatigue, excessive thirst and hunger, weight loss, frequent urination and slow healing of

wounds and sores [8]. In contrast to subjects with T1D, subjects having T2D do not require

insulin for survival, but may use insulin if control of blood sugar levels is not achieved by

diet or other oral hypoglycemic agents.

1.1.1 Diabetes epidemiology

According to the diabetes atlas 2009 the estimated global burden of diabetes in 2010 has

increased to 285 million with a further 344 million people estimated to have impaired

glucose tolerance [9]. The estimated prevalence of diabetes in South-East Asia by 2010 is

58.7 million with an increase to 101 million by 2030. About 85% of the adult population of

South East Asia is accounted by India and the prevalence of diabetes in Indian population is

estimated to be around 50.8 million. Among these, around 113 thousand people are estimated

to have T1D by 2010 [9]. The anticipated increase in diabetes estimate in South East Asia is

very much a consequence of increasing life expectancy and urbanization of the population

[9]. A summary of estimated diabetes prevalence from diabetes atlas 2009 is provided in

Table 1.1.

Table 1.1 Estimated prevalence of diabetes in 2010 and 2030 2010 2030

Diabetes IGT Diabetes IGT

Global prevalence (%)

6.6 (285 million)

7.9 (344 million)

7.8 (435 million)

8.4 (472 million)

Prevalence in South East Asia (85% India) (%)

7.0 (58.7 million)

5.8 (48.6 million)

8.4 (101 million )

6.4 (76.4 million)

IGT- Impaired glucose tolerance. Prevalence represented in %.

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1.1.2 Diabetes in South India

The National Urban Diabetes Survey (NUDS) conducted across 6 major metropolitan cities

in India revealed that the prevalence of T2D is comparatively higher in Southern part of

India. The survey reported a prevalence of 13.5% in Chennai, 12.4% in Bangalore and 16.6%

in Hyderabad [10]. The Chennai Urban Rural Epidemiology Study (CURES) conducted in a

representative Chennai population estimated the prevalence of diabetes at 14.3 % (age

adjusted). The study reported a significant increase of 72.3% in the prevalence of diabetes in

the span of 14 years [11]. The Amrita Diabetes and Endocrine Population Survey (ADEPS)

recorded a very high prevalence (19.5%) of diabetes in Ernakulam, Kerala [12]. An earlier

study has reported a prevalence of 16.3% in Thiruvananthpuram, Kerala [13]. An overall

summary of different surveys indicating the prevalence of diabetes in different regions of

India is given in Table 1.2.

According to a study conducted in Southern Kerala, the prevalence of diabetes was

different in different geographic divisions within a region. The highest prevalence was in

urban areas (12.4%) followed by midland (8.1%), highland (5.8%) and coastal division

(2.5%) [14].

Table 1.2 Prevalence of type 2 diabetes in different regions of India Regions % prevalence Reference*

Kashmir valley 6.1 Zargar et al., 2000

New Delhi 10.3 Ramachandran et al., 2001

Jaipur 8.6 Gupta et al., 2003

Guwahati 8.3 Shah et al., 1999

Kolkatta 11.7 Ramachandran et al., 2001

Mumbai 9.3 Ramachandran et al., 2001

Hyderabad 16.6 Ramachandran et al., 2001

Bengaluru 12.4 Ramachandran et al., 2001

Chennai 14.3 Ramachandran et al., 2001

Ernakulam 19.5 Menon et al.,2006

Thiruvananthapuram 16.3 Raman Kutty et al., 1999

* Table summarized from Reference [11].

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1.1.3 Diabetes associated complications

There are basically two types of complications associated with diabetes, macrovascular

complications and microvascular complications [11, 15]. Macrovascular complications occur

due to the damage to the large vessels and particularly because of the damage to the arterial

walls and often leads to cardiovascular diseases and stroke. Microvascular complications

arise due to the damage to smaller vessels and results in reduced blood supply to specific

organs [15]. It can result in a number of other clinical complications like diabetic neuropathy,

diabetic retinopathy and diabetic nephropathy [15]. A recently conducted multicentric Indian

study on subjects with T2D reports the prevalence of diabetic neuropathy at 82% among the

study population (Indian population) [16]. It results due to the damage to nerve tissues due to

low blood supply and high glucose. One of the major problems related to diabetic neuropathy

is injury to feet due to loss of feeling and often results in amputation. According to the study

the prevalence of diabetic retinopathy and diabetic nephropathy (renal insufficiency) were

34.8% and 21.4% respectively among diabetic subjects [16]. The presence of cardiovascular

diseases, one of the major reasons for heart attack, among type 2 diabetic subjects was

estimated to be around 24.2% [16]. According to the data from Chennai urban population

study (CUPS) and CURES the prevalence of coronary artery disease was found to be 21.4%

among diabetic subjects [17]. Similarly prevalence for diabetic retinopathy and nephropathy

were reported at 17.6% and 26.9% (microalbuminaria), while 2.2% of the subjects had overt

nephropathy [18, 19]. According to diabetes atlas 2009, the South-East Asia region, of which

85% of the population is accounted by India, has the highest number of deaths due to

diabetes. An estimated 1.1 million adults are expected to die of diabetes related causes by

2010 of which the majority is because of diabetes associated complications [9].

1.1.4 Risk Factors for the development of T2D in Indian population

It has been seen that there is a high familial aggregation of T2D in Indian population,

especially in South India. Genetic predisposition plays a major role in the development of

T2D in Indian population as compared to other ethnic groups [20, 21]. Though the exact

reason for this is unknown, certain unique clinical and biochemical features play an

important role in the increased predisposition towards T2D [11]. Prevalence of obesity as

measured by body mass index (BMI) is lesser in this population but tend to have greater

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waist circumference and waist to hip ratio (WHR) [22]. Additionally Asian Indians have

comparatively more abdominal and visceral fat and hence are more insulin resistant [23]. The

levels of protective adipokines like adiponectin are also lower in Asian Indians whereas other

adipocyte metabolites are increased [24]. All these phenotypes contribute to the increased

genetic predisposition of Asian Indians for the development of T2D. Another interesting

feature in Asian Indians is the birth weight. Indian babies are born smaller but fatter

compared to the Caucasian babies and are called the “thin fat Indian baby” [25, 26]. A recent

study confirmed the findings and provided evidence that the “thin fat Indian” phenotype

could be a forerunner for the diabetogenic adult phenotype [27].

A sedentary life style is also an important risk factor for the development of T2D. It

was observed that the prevalence of diabetes was almost three times higher in individuals

with light physical activity as compared to individuals with heavy physical activity [28].

Prevalence of metabolic syndrome and hypertension was also high in individuals with light

physical activity. Gestational diabetes which is predominant in non-European groups is also

an important risk factor for the development of T2D in latter stages [29]. Mothers who have

had gestational diabetes are at two fold increased risk of developing T2D in the future [30].

1.2 Genetic and environmental factors in T2D.

T2D is a heterogeneous disease caused by interaction between environmental and genetic

factors. The increased genetic predisposition of T2D is evidenced by the familial aggregation

of T2D, high concordance rate in twins and higher predisposition of certain ethnic groups for

the development of T2D [31,32]. However, difference in the prevalence of T2D in

populations living in different environmental conditions but sharing the same background

points at the role of environmental factors in T2D [33]. The nature vs. nurture debate about

the origin of T2D is going on for a long time. However, it is yet to be fully understood

whether it is the genetic factors or the environmental factors that play a predominant role in

the origin of T2D. In this regard the “Thrifty genotype hypothesis” [34] and the “Thrifty

phenotype hypothesis” [35] shed some light on the origin of T2D.

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1.2.1 Thrifty Genotype hypothesis

The “Thrifty genotype hypothesis” or the “Thrifty gene hypothesis” was proposed by the

geneticist James V Neel [34]. The basis for the hypothesis was to understand how a

phenotype which renders an individual susceptible to the development of type 2 diabetes was

favored by the process of natural selection.

Figure 1.1 Thrifty genotype hypothesis.

According to the hypothesis (Figure 1.1), the genes (thrifty genes) that predispose to

diabetes were historically advantageous but they became detrimental in the modern world.

The thrifty genotype would have been advantageous for the hunter-gatherer populations and

allow better fat storage when food was in abundance. And hence the fatter individuals who

carry the thrifty gene would be better prepared for the time of food scarcity. But in the

modern society with abundance of food, this genotype efficiently prepares the individuals for

a famine that never comes and hence results in chronic obesity and related problems like

T2D [34].

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1.2.2 Thrifty Phenotype hypothesis

The Thrifty Phenotype hypothesis relates the development of metabolic syndrome and T2D

to low birth weight (Figure 1.2). It proposes that the epidemiological relation between fetal

and infant growth and the subsequent development of metabolic syndrome and T2D is a

result of poor nutrition in the early life which produces permanent changes in glucose/insulin

metabolism [35].

Figure 1.2 Thrifty phenotype hypothesis [35].

results in the development of type 2 diabetes due to a decreased β cell function and decreased

insulin secretion [35].

The rapid increase in the prevalence of T2D in Indian population is mostly a result of

progressive urbanisation [9, 11]. This related increase in T2D due to urbanisation can be

explained based on the above mentioned hypothesis. The rapid urbanisation and economic

growth results in the continuous availability of high fat/high calorie diet and lower physical

activity, as a result, the thrifty genes which were advantageous initially predisposes these

Maternal malnutrition and fetal

malnutrition results in reduced

pancreatic growth and in

combination with childhood

malnutrition results in reduced

β cell function and decreased

insulin secretion. This

reprogramming of the

pancreatic β cells will not be

detrimental if the nutritional

intake is maintained similar

throughout the lifetime.

However as adult life

approaches, increase in age and

intake of obesity inducing food

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individuals to obesity and subsequent T2D. Also the excesses of modern day living

contribute significantly in rendering the susceptible individuals prone to the development of

T2D [36].

1.3 Cellular basis of type 2 diabetes

The hormone insulin is secreted from the pancreatic β cells in response to elevated blood

glucose levels. This insulin results in the uptake of glucose into adipocytes and skeletal

muscles and inhibits the endogenous production of glucose from the liver [37, 38]. Both

adipocytes and skeletal muscles have a predominantly insulin sensitive glucose transporter

(GLUT4) which in the absence of insulin is sequestered in the cytoplasm in specialized

vesicles [39]. The binding of insulin to its cognate tyrosine kinase receptor leads to the

autophosphorylation of the insulin receptor (IR) which then initiates a signal cascade leading

to the activation of protein kinase B (PKB/AKT) via phosphotidyl inositol 3 kinase

(PI3K)[39]. The activation of PKB/AKT results in the translocation of the sequestered

GLUT4 to the plasma membrane and the subsequent uptake of glucose by adipocytes and

skeletal muscles [39]. In comparison, insulin signaling in liver leads to the down regulation

of gluconeogenic enzymes and also inhibits the endogenous glucose production from liver

[38, 40]. The cumulative effect of both these processes is the lowering of blood glucose

levels and maintaining blood glucose homeostasis. The pathogenesis of T2D often involves

abnormalities in both insulin action (insulin resistance) as well as insulin secretion.

1.3.1 Insulin resistance

Insulin resistance is the hallmark of T2D. It is a condition in which the normal biological

response of one or more insulin sensitive tissues to insulin is reduced resulting in decreased

glucose disposal [41]. In order to substantiate for the degree of insulin resistance, the

pancreas starts producing greater than physiological levels of insulin resulting in

hyperinsulinemia. However chronic hyperinsulinemia aggravates the condition of insulin

resistance and contributes directly to pancreatic β cell failure and T2D [42].

Though there are many factors which can induce insulin resistance, obesity is one of

the major factors [43]. Intake of high fat/calorie diet, lack of physical activity and genetic

makeup of an individual leads to the development of obesity. In condition of obesity there is

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an expansion of adipose tissue mass which involves both hypertrophy and hyperplasia of

adipocytes (fat cells) [44]. These adipocytes produce and secrete a number of adipokines like

adiponectin, resistin, leptin and cytokines like interleukin-6 (IL-6), monocyte

chemoattractant protein-1 (MCP-1), tumor necrosis factor alpha (TNFα) that can act at both

local and systemic levels to modulate insulin sensitivity [41]. In fact TNFα has been

proposed as a major link between adiposity and insulin resistance. It has been reported that

TNFα is highly expressed in adipose tissues of obese subjects and obese mice lacking either

TNFα or its receptors show protection from developing insulin resistance [45, 46]. TNFα

also mediates insulin resistance by promoting the production of free fatty acids (FFA) in

adipocytes which in turn induce insulin resistance in skeletal muscles [47]. TNFα mediated

insulin resistance stems from the direct inhibition of insulin signaling at the IRS-1 level [48].

TNFα mediates the serine phosphorylation of insulin receptor substrate-1(IRS-1) and hence

prevents the tyrosine phosphorylation and subsequent insulin signaling pathways [48]. TNF-

α impairs the action of insulin in myocytes at the level of IRS-1 by a double mechanism that

involves (i) serine phosphorylation by IKK and p38MAPK at the Ser307 residue and (ii)

tyrosine dephosphorylation by protein tyrosine phosphatase 1B (PTP1B) which is a negative

regulator of insulin signaling cascade [41]. Apart from TNFα, other adipocytokines like IL-6

are also known to mediate insulin resistance.

Suppressor of cytokine signaling 3 (SOCS3) is another mediator between obesity and

insulin resistance [49]. SOCS family protein is involved in the negative feedback loop in

cytokine signaling. Studies have shown that SOCS3 can directly interact with the IR leading

to the inhibition of tyrosine phosphorylation of insulin receptor substrate-1(IRS-1) blocking

insulin signaling [49]. SOCS3 is also known to mediate leptin resistance whereas other

SOCS proteins like SOCS1, SOCS3, SOCS6 and SOCS7 play a role in the mediation of

insulin resistance [49].

Defects in glucose oxidation and glycogen synthesis in skeletal muscles also

contribute to insulin resistance [50]. Studies have shown that in muscles, elevated circulating

FFA contributes to insulin resistance by reducing glucose oxidation through the glucose fatty

acid cycle (Randle cycle) [51]. These studies proposed that an increase in fatty acids caused

an increase in the intra mitochondrial acetyl CoA/CoA and NADH/NAD+ ratios, with

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subsequent inactivation of pyruvate dehydrogenase. This in turn would cause intracellular

citrate concentrations to increase, leading to inhibition of phosphofructokinase, a key rate-

controlling enzyme in glycolysis. Subsequent accumulation of glucose-6-phosphate would

inhibit hexokinase II activity, resulting in an increase in intracellular glucose concentrations

and decreased glucose uptake [52-55]. On the contrary, other studies have shown that

increase in FFA concentration in muscle can lead to insulin resistance by directly affecting

insulin signaling [55].

The end result of insulin resistance is hyperglycemia due to decreased uptake of

glucose into adipocytes and skeletal muscles because of impaired insulin action.

1.3.2 Insulin Secretion

The normal response of pancreatic β cells to hyperglycemia associated with insulin resistance

is increased secretion of insulin in order to maintain physiological blood glucose level [56-

57]. Type 2 diabetes develops in subjects who are unable to maintain this compensatory

response by pancreatic β cells [56]. Studies have shown that in subjects that develop T2D

there is a rise in insulin levels (hyperinsulinemia) in normoglycemic and prediabetic phases

to keep blood glucose level near normal despite insulin resistance (β cell compensation). This

is followed by a decline in insulin levels over the course of time (β cell failure) [57]. A

longitudinal study in Pima Indians provide evidence that β cell dysfunction is the major

factor responsible for the progression from normoglycemia to T2D [58]. This β cell failure is

associated with a loss in the β cell mass due to apoptosis [58].

Studies have shown that subjects with susceptible β cells are not able to compensate

and adapt according to the degree of insulin resistance and over a period of time develop β

cell dysfunction and T2D [59]. β cell failure occurs due to the combination of a number of

factors like mitochondrial dysfunction, genetic and acquired defects, intrauterine

environment, insulin biosynthesis, coupling mechanisms, anaplerosis/cataplerosis, TG/FFA

cycling [59]. Insulin resistance associated hyperglycemia leads to increased metabolism of

glucose and FFA in beta cells, this in turn leads to production of reactive oxygen species

(ROS) and subsequent activation of uncoupling protein-2 (UCP-2) leading to lower ATP

synthesis via uncoupling of oxidative phosphorylation [60-61]. Due to this, the cells maintain

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a high ATP/AMP ratio leading to reduced insulin secretion [59-60]. Additionally, it is also

known that pancreatic β cells have limited defense against increased ROS production.

Elevated ROS levels leads to β cell apoptosis and hence ROS play an important role in β cell

failure [62].

Another mechanism for β cell failure is glucose toxicity. Studies have shown that

chronic exposure to glucose results in reduced transcription of the insulin gene and hence

reduced insulin secretion [63]. Also the compensating β cells places an increased demand for

insulin biosynthesis on the endoplasmic reticulum (ER) and the resultant stress may lead to β

cell failure particularly if the β cell mass is suboptimal [64]. In support of this fact, studies

have shown β cell resting by the use of somatostatin or diazoxide results in the recovery of β

cell function [65, 66]. Gut hormones like incretins also play a role in insulin release and β

cell compensation. Incretins stimulate the secretion of insulin from β cells in response to food

intake and are responsible for more than 70% post prandial insulin release [67, 68]. Hence

defects in the incretin effect can also lead to reduced insulin secretion promoting β cell

failure. Additionally incretins also promote β cell differentiation and survival, so the loss of

the incretin effect can promote β cell apoptosis and reduction in β cell mass [68, 69].

Therefore β cell dysfunction and the inability of β cells to compensate for the degree of

insulin resistance leads to chronic hyperglycemia with overt T2D. However, it is the hepatic

glucose production that decides the magnitude of fasting blood glucose and hence liver plays

the final role in the progression to severe hyperglycemia and uncontrolled diabetes [38].

1.3.3 Role of Liver in the progression of T2D.

Liver acts as the storage organ for glucose in the body. It also acts as the site of endogenous

glucose production (EGP) by gluconeogenesis and glycogenolysis [70]. Impaired EGP is one

of the major contributors towards fasting and post prandial hyperglycemia in subjects with

T2D. In normal subjects, EGP is the source for glucose during fasting and restricted food

access, however in subjects with T2D, EGP is excessive before eating and fails to suppress

appropriately after eating [70]. Insulin is the main hormone responsible for the suppression of

EGP from the liver. Insulin signaling in the liver results in the down regulation of key

gluconeogenic enzymes like phospho enol pyruvate carboxy kinase (PEPCK) and glucose 6

phosphatase (G6pase) [71]. In subjects with T2D, due to β cell dysfunction and reduced β

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cell mass there is suboptimal production of insulin [72, 73]. Additionally, in subjects with

T2D, an increased TG/FFA metabolism and certain adipokines induces hepatic insulin

resistance [74]. Both these factors contribute towards the excessive EGP in subjects with

T2D and the inability of insulin to suppress EGP [70]. This excessive EGP results in severe

fasting and post prandial hyperglycemia leading to uncontrollable T2D.

Thus, a combination of insulin resistance, defects in insulin secretion and excessive

EGP leads to severe hyperglycemia and overt T2D. Figure 1.3 explains the possible

mechanism of pathogenesis of type 2 diabetes. However, as discussed earlier, both cellular as

well as genetic factors contribute towards the development of conditions leading to T2D and

the genetic identification of many key genes have provided a better understanding about the

etiology of prediabetic events and the subsequent development of T2D.

Figure 1.3 Progression of type 2 diabetes. Predisposing and environmental factors leads to obesity and insulin resistance. In order to compensate for the resulting hyperglycemia the pancreatic beta cells starts producing increased levels of insulin. However over a period of time this leads to beta cell exhaustion and decreased production of insulin initiating overt type 2 diabetes. This in combination with excessive EGP from liver due to hepatic insulin resistance leads to severe hyperglycemia and overt type 2 diabetes.

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1.4 Genetics of T2D

1.4.1 Genetic studies in T2D

The high familial aggregation of T2D suggests a strong genetic basis of the disease [75]. And

accordingly large efforts have been made for the identification of mutations and variations in

susceptibility genes (candidate genes) responsible for the pathogenesis of T2D. Initial studies

for the identification of susceptibility genes were done by family based linkage analysis and

focused candidate gene studies. These studies were effective in the identification of genes

responsible for monogenic forms of diabetes like MODY, MIDD and neonatal diabetes [76]

(Table 1.3).

Table1.3 Genes identified for monogenic forms of diabetes. Genes Disease type Mutation phenotype

MODY

HNF4α MODY 1 Decreased glucose sensing and metabolism GCK MODY 2 Decreased glucose sensing and metabolism HNF1α MODY 3 Decreased glucose sensing and metabolism IPF-1 MODY 4 Reduced β cell number or maturation HNF1β MODY 5 Reduced β cell number or maturation NEUROD1 MODY 6 Reduced development of endocrine pancreasINS MODY 7 Increased destruction rate of the β-cell

NDM/MDI KCNJ11

NDM/MDI Failure of the membrane depolarization

ABCC8 Failure of the membrane depolarization INS Increased destruction rate of the β-cell

Rare mutations

IPF1 Pancreas agenesis Reduced β cell number or maturation

EIF2AK3 Wolcott-Rallison

syndrome Increased destruction rate of the β-cell MODY- Maturity onset diabetes of the young, NDM- neonatal diabetes mellitus, MDI – monogenic diabetes of infancy, HNF- hepatocyte nuclear factor, GCK- glucokinase, IPF- insulin promoting factor, INS-insulin NEUROD1- neurogenic differentiation1, ABCC8- ATP-binding cassette transporter sub-family C member 8, EIF2AK3 - Eukaryotic translation initiation factor 2-alpha kinase 3. Summarized from Vaxillaire et al.2009 [262].

Attempts to apply similar strategies for polygenic forms of diabetes had limited or

no success [77]. Therefore more effective strategies like tests for association were

developed. Though more powerful than linkage analysis, association studies suffer from a

disadvantage that one has to directly analyze the causal variant or a marker linked to the

variant for desirable outcome [78]. And hence attention was focused on the common

variations in candidate genes for the identification of genetic factors responsible for the

more common forms of T2D. Such studies led to the identification of many candidate

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* Adapted from McCarthy et al. 2010.

genes, the most common and confirmed were the common coding variants in peroxisome

proliferator activated receptor gamma (PPARϒ) and potassium inwardly rectifying channel,

subfamily j, member 11(KCNJ11) gene [79, 80].

Table 1.4 Summary of major Genome Wide Association (GWA) studies in type 2 diabetes. Ethnic Group Study Type Major Findings Reference*

French Single GWA study HHEX and SLC30A8 association with type 2 diabetes

Sladek et al., 200784

Finnish Single GWA study CDKAL1,CDKN2A and IGF2BP2 association with type 2 diabetes

Scott et al., 200786

Swedish, Finnish Single GWA study CDKAL1,CDKN2A and IGF2BP2 association

with type 2 diabetes

Diabetes Genetics Initiative et al., 2007 87

British Single GWA study CDKAL1,CDKN2A and IGF2BP2 association with type 2 diabetes

Zeggini et al.,200788

Icelandic Single GWA study CDKAL1 association with type 2 diabetes Steinthorsdottir et al.,200789

European GWA meta-analysis NOTCH2,JAZF1,ADAMTS9,TSPAN8,THADA & CDC123- 6 new loci for type 2 diabetes

Zeggini et al.,200891

Japanese, Korean, Chinese

Single GWA study KCNQ1 association with type 2 diabetes in East Asians

Yasuda et al., 200895

Japanese, Singaporean Single GWA study KCNQ1 association with type 2 diabetes in East

Asians Unoki et al., 200896

French, Danish Single GWA study IRS1 association with type 2 diabetes Rung et

al.,2009105

European Follow-up signals for type 2 diabetes from GWA scan for

fasting glucose

MTNR1B association with type 2 diabetes and fasting glucose

Prokopenko et al., 2009102

Swedish, Finnish

Follow-up signals for type 2 diabetes from GWA scan for

insulin secretion

MTNR1B association with type 2 diabetes and fasting glucose

Lyssenko et al., 2009103

French, Danish, Finnish

Follow-up signals for type 2 diabetes from GWA scan for

fasting glucose

MTNR1B association with type 2 diabetes and fasting glucose

Bouatia-Naji et al., 2009104

European Follow-up signals for type 2 diabetes from GWA scan for

fasting glucose

ADCY5, PROX1,GCK, GCKR, and DGKB associations with type 2 diabetes and fasting glucose

Dupuis et al.,201092

Taiwanese Single GWA study SRR and PTPRD associations with type 2 diabetes in Taiwanese

Tsai et al., 201097

European GWA meta-analysis RBMS1 association with type 2 diabetes Qi et al., 201093

European GWA meta-analysis DUSP9, KLF14, CENTD2, HMGA2,and HNF1A- 12 new loci for type 2 diabetes

Voight et al., 201094

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Further systematic, large scale surveys of association analysis led to the identification

of common variants in TCF7L2 (transcription factor 7 like 2) to be strongly associated with

T2D [81]. Common variants in TCF7L2 were positively replicated in number of study

populations with very strong effects [82]. Ever since the introduction of genome wide

association studies (GWAS) in 2007, an increase in the number of susceptibility loci

conferring risk for the development of T2D was observed [83]. Various GWAS studies in

different ethnic groups have provided evidence for more than 40 susceptibility loci playing a

role in T2D [83-104]. Most of these susceptibility loci had a role in insulin secretion,

however only limited number of loci identified by GWAS studies, such as the variants in

IRS-1, play a role in insulin resistance [105]. A summary of major GWAS studies is provided

in Table 1.4. Even though GWAS studies have tremendously increased our knowledge in the

genetics of T2D, still these loci account for only a minor fraction of the observed familial

clustering leaving much of the variance unexplained.

1.4.2 Genetics of T2D in Indian population

Several candidate gene based association analysis has been carried out for confirming and

identifying susceptibility genes playing a role in type 2 diabetes in Indian population [106-

108, 110-133]. Most of these studies have further confirmed the association as well as

provided evidence for the different effects of causal variants in Indian population than that

observed in western populations [106-108]. For example, two studies provide evidence that

the common variants in fat mass and obesity associated gene (FTO) are strongly associated

with T2D in Indian population but the association does not seem to be mediated by BMI

[106,107]. Whereas in Europeans, FTO variants are strongly associated with obesity [109]. In

contrast Remya et al. in a South Indian population study (CURES 79) reported that, out of

the many variants analyzed in FTO with relation to T2D and obesity, three variants are

associated with T2D whereas one of the variant was shown to be associated with obesity

[110]. Another study reported that the effect of common variants in PPARϒ is different in

Indians when compared to European population [108].

Common variants in TCF7L2 which were found to be associated in many different ethnic

groups was shown to be associated with T2D in Indian population (South Indian population)

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as well [111,112]. A recent study by Chauhan et al. positively replicated the association of

common variants in PPAR , KCNJ11, TCF7L2, SLC30A8, HHEX, CDKN2A, IGF2BP2,

* Summarized from different studies in Indian population

and CDKAL1, identified by GWAS studies in European population, on the risk of T2D in

5,164 Indians [113]. Common variants in PPARϒ, KCNJ11, FTO, ENPP1, MTNR1B,

IGF2B2, leptin receptor, ADIPOQ, lipoprotein lipase, glutathione S transferase, IL-4 and Il-

1RN, PGC-1α were also shown to be associated with T2D in different Indian populations

[107, 114-128]. A list of candidate genes identified in different Indian populations is

provided in Table 1.5. There have been no reports of GWAS studies with respect to T2D in

Indian population.

Table 1.5 List of important candidate gene associated with type 2 diabetes in Indian population. Candidate genes Population Reference* FTO South Indian population, Asian

Indian Sikhs Yajnik et al., 2009; Ramya et al., 2011; Sanghera et al. 2008.

TCF7L2 South Indian population, Asian Indian Sikhs, Asian Indians, Indo Europeans.

Chandak et al., 2007; Sanghera et al., 2008; Humphries et al., 2006; Chauhan et al., 2010.

PPARγ South Indian population, Asian Indian Sikhs, Indo Europeans

Radha et al., 2006; Haseeb et al., 2009; Vimleswaran et al., 2010; Chauhan et al., 2010.

KCNJ11,SLC30A8, HHEX, CDKN2A, IGF2BP2, and CDKAL1

Indo Europeans Chauhan et al., 2010.

CDKAL1,CDKN2A/B, HHEX

South Indian population Chidambaram et al., 2010.

Calpain -10 South Indian population, Eastern Indian population

Adak et al., 2010; Bodhini et al., 2011.

MTNR1B Asian Indians Chambers et al., 2009. Lipoprotein lipase Asian Indians Radha et al., 2007. ENPP1/PC-1 North Indian population Bhatti et al., 2010. Leptin receptor South Indian population Murugesan et al., 2010. Glutathione s-transferase

North Indian population Bid et al., 2010.

IL-4 and IL-1RN North Indian population Bid et al., 2010. PGC-1α North Indian population Bhat et al., 2007. APOE and ACE Northwest Indian population Singh et al., 2006. ADIPOQ Asian Indian Sikhs Sanghera et al., 2010. TNFLTA Northern Indian population Mahajan et al., 2010. DOK5 Northern Indian population Tabassum et al., 2010. FOXA2 Northern Indian population Tabassum et al., 2008. UCP2 and UCP3 Asian Indian population Vimleswaran et al., 2011.

18

1.5 Overview of the present study

The present study aims at the identification of candidate genes increasing the susceptibility to

T2D in a South Indian Dravidian population from Kerala. As mentioned above (section

1.1.2), epidemiological surveys have identified the state of Kerala as having one of the

highest prevalence rates in T2D [11, 12]. This high prevalence of T2D in Kerala as well as in

Indian population can be attributed to increased central obesity and high familial aggregation

of type 2 diabetes [11, 75]. Genetic predisposition as evidenced by high familial aggregation

of T2D also plays an important role. Genetic studies to identify candidate genes that increase

the susceptibility to T2D are important in understanding the molecular mechanism of the

disease as well as in designing better therapeutical agents to prevent or control T2D.

Although genetic studies have been undertaken for the identification of variations in

candidate genes associated with T2D, these genes did not completely explain the observed

variance and many causal factors still need to be identified [83].

The current work utilized a candidate gene approach to further increase the understanding of

the genetics of T2D in South Indian population. As described above in section 1.3, the

development of overt T2D is believed to be the combined effect of insulin resistance, defects

in insulin secretion and impaired EGP. Most of the genetic studies undertaken till date have

identified susceptibility genes for T2D playing a role in insulin secretion [111-112] and only

a limited number of genes have been identified having a direct role in insulin action [105].

The identification of majority of these genes affecting insulin secretion is in accordance with

the fact that defects in insulin secretion (β cell dysfunction) is detrimental in the development

of T2D. However, since insulin resistance is the hall mark of T2D and is often the first step

in pathogenesis of type 2 diabetes, further genetic studies with candidate genes involved in

the pathogenesis of insulin resistance may provide beneficial insights into its cellular

mechanism [41]. In this study we have selected candidate genes based on their known role in

insulin resistance, insulin signaling and EGP. The selected candidate genes were not studied

in any population with respect to genetics of T2D except for two genes, which were analyzed

in western population but not in Indian population.

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1.6 Candidate genes selected for the present study.

1.6.1 Candidate genes for insulin resistance (GLUT4, RBP4 and STRA6) - Study I.

Glucose transporter 4 (GLUT4)

Insulin resistance is the hallmark of T2D. Insulin resistance is defined as the inability of

insulin responsive cells to respond to insulin in the normal manner (41). Adipocytes, muscles

and liver are the major insulin responsive sites in the body. Both adipocytes and muscle

harbor a predominantly insulin sensitive glucose transporter, GLUT4 [37-38]. GLUT4 is a

twelve transmembrane protein which under normal physiological conditions (absence of

insulin) is sequestered in specialized vesicles in the cytoplasm. Insulin signaling via its

receptor results in the translocation of GLUT4 to the plasma membrane and subsequent

uptake of glucose into the cells [39,134]. It has been observed that the process of GLUT4

translocation in response to insulin signaling is impaired in conditions of insulin resistance

and T2D [135]. This is a major node for therapeutic research and a number of works have

been undertaken for the identification and characterization of synthetic as well as plant

derived compounds which may stimulate the process of GLUT4 translocation and hence help

maintain blood glucose homeostasis [136-138]. Work from our own laboratory has resulted

in the identification of natural products that modulate GLUT4 translocation and subsequent

glucose uptake [139-140]. Though no crystal structure is available for GLUT4, a work by

Mohan et al. has succeeded in generating a homology model for GLUT4 which is used for

the validation and characterization of these identified compounds [139,141-142]. It has also

been reported that there is an adipocyte specific down regulation of GLUT4 in T2D

[143,144]. Though the exact reason for this down regulation is still not clear it may be a

primary or a secondary effect of insulin resistance and can be brought about by genetic as

well as other cellular factors. Common variations in the putative promoter of GLUT4 or

other functional non coding regions may be responsible for this effect. Subsequent

knockdown studies confirmed that an adipocyte specific knock down of GLUT4 causes

insulin resistance secondarily in muscles and liver [143]. Search for the identification of an

adipocyte derived factor responsible for this process led to the identification of retinol

binding protein 4 (RBP4), a vitamin A/retinol transporter [144].

20

Retinol binding protein 4 (RBP4)

Serum RBP4 levels were found to be markedly increased in patients with insulin resistance,

which correlated with reduced expression of GLUT4 in adipocytes [144]. A study by Yang

et. al. found that, adipocyte specific knockdown of GLUT4 leads to an increased expression

of RBP4 which in turn causes insulin resistance in muscles and liver by modulating the

activity of PI3K in muscles and PEPCK in liver [144]. It was also reported that RBP4

inhibits insulin signaling at the IRS-1 level [145]. Conversely, genetic deletion of RBP4 was

found to enhance insulin sensitivity [144]. Figure 1.4 describes the inverse relation between

GLUT4 and RBP4 and how it effects the pathogenesis of type 2 diabetes.

Further studies also reported elevated serum RBP4 levels in subjects with insulin

resistance, obesity and T2D [146]. Similar observations were made in other insulin resistant

states like non alcoholic fatty liver disease and metabolic syndrome [147]. Circulating RBP4

concentration was found to correlate positively with adiposity measures and with

inflammatory parameters [148]. It has been reported that circulating RBP4 is more strongly

associated with visceral fat than with BMI indicating an important role for visceral fat rather

than subcutaneous fat in relationship between RBP4 and insulin resistance [149].

Accordingly, increased expression of RBP4 has been observed in visceral fat compared to

Figure 1.4 Inverse relation of GLUT4 and RBP4 and pathogenesis of type 2 diabetes. A decrease in the expression of GLUT4 leads to an increased RBP4 expression. This in turn leads to insulin resistance in skeletal muscles and liver via PI3K and PEPCK respectively. And hence RBP4 acts as an adipocyte derived signal for the pathogenesis of type 2 diabetes.

21

subcutaneous fat [150]. Circulating RBP4 levels correlated positively with ectopic fat

accumulation at hepatic and skeletal muscles [151].

Further studies on RBP4 have identified iron stores as a major predictor for RBP4

levels. Iron intake and raised iron stores have been recognized as significant independent

contributors to insulin resistance. Interestingly, serum ferritin concentration was positively

associated with serum RBP4 concentration in two independent samples [152]. Furthermore it

was observed that serum RBP4 concentration decreased after iron depletion in subjects with

T2D. Insulin sensitizing effects of exercise were also found to be associated with decreased

RBP4 levels. It was observed that transgenic over expression of human RBP4 or injection of

recombinant RBP4 in normal mice causes insulin resistance. Fenretinide, a synthetic retinoid

that increases urinary excretion of RBP4, was found to normalize serum RBP4 levels and

improve insulin resistance and glucose intolerance in mice with obesity induced by a high-fat

diet [144].

Stimulated by retinoic acid 6 (STRA6)

All these studies provide evidence for the fact that RBP4 is a putative adipocyte derived

signal responsible for insulin resistance in muscle and liver subsequently leading to T2D and

related metabolic disorders. But the exact mechanism by which RBP4 effects these processes

and hence insulin sensitivity is still unclear and it was suggested that RBP4 can affect insulin

sensitivity both in a retinoid dependent and independent manner [144].

In this respect, the recent identification of STRA6 as the high affinity cell surface

receptor of RBP4 may give further insight into the mode of action of RBP4 [153]. STRA6 is

a multitransmembrane domain protein that mediates the cellular uptake of vitamin A. In

accordance with its role as the transmembrane transporter of vitamin A, STRA6 plays a

major role in embryonic development [153,154]. Various studies have identified mutations in

STRA6 to cause a broad spectrum of malformations like anopthalmia, congenital heart

defects, diaphragmatic hernia, alveolar capillary dysplasia, lung hypoplasia and mental

retardation. Truncating mutations in STRA6 has been identified in patients with Mathew

Wood syndrome [154-158]. Studies have shown that STRA6 is over expressed in colon

cancer [159]. But neither functional nor genetic studies were carried out to identify how

22

STRA6 may play a role in imparting the effect of RBP4 on muscle and liver insulin

resistance and subsequently T2D.

Genetic studies have been carried out with respect to SNPs in GLUT4 and RBP4 but

with varied results [160-168]. SNPs in RBP4 were found to be associated with T2D in

Mongolian population and a regulatory SNP, rs3758539, in the promoter was found to be

associated with increased serum expression of RBP4 in type 2 diabetic patients [160]. Follow

up studies in European population led to the identification of a haplotype of 6 SNPs to be

associated with T2D. Furthermore 2 SNPs (rs10882283 and rs10882273) were found to be

associated with body mass index (BMI), waist hip ratio (WHR) and fasting plasma insulin

[161]. Several SNPs were also identified to be associated with FFAs. They also reported that

the subjects carrying a previously reported haplotype in RBP4 have higher RBP4 mRNA in

visceral adipose tissue [161]. Studies in Chinese population also revealed the association of a

rare haplotype to be associated with T2D though none of the single SNP analyzed was

associated with T2D [162]. Studies have also reported SNPs in RBP4 to be associated with

serum triglyceride levels in Chinese population and serum high density lipoprotein levels

(HDL) in Newfoundland population [162,163]. But no study has been carried out in South

Indian population either for association with T2D or related biochemical parameters.

GLUT4 is a potential candidate gene for T2D because of its role in insulin dependent

transport of glucose into the cells in adipocytes and skeletal muscles. In a study on Welsh

population, researcher found that a mutation (383 V-I) was only seen in diabetic subjects (3

out of 160) but none of the control subjects and they also found a common silent

polymorphism (130 N-N) to be associated with T2D [164]. Further study in British and

Welsh population by screening all the exons of GLUT4 by SSCP analysis and direct DNA

sequencing also revealed the presence of these polymorphism (130 N-N, and 383 V-I) but

did not show significant association [165]. Other studies in GLUT4 include RFLP studies

with KpnI enzyme in Italian, Caucasians, Chinese, and Asian Indians, American black and

Japanese population [166-168]. None of these studies focused on SNPs present in the

promoter and coding region of GLUT4. These studies failed to establish an association

between the KpnI allele and T2D [166-168]. Interestingly genetic studies pertaining to the

23

role of SNPs in STRA6, the high affinity receptor for RBP4, in the pathogenesis of T2D were

not reported.

1.6.2 The incretins, GIP and GLP-1- Study II

The hormone insulin, secreted by the pancreatic β cells plays a very important role in blood

glucose homeostasis. Insulin is secreted by the pancreatic β cells in response to increased

blood glucose levels. Post prandial insulin secretion from the β cells is also facilitated by

certain gastrointestinal hormones like incretins which include glucose-dependent

insulinotropic polypeptide (GIP) and glucagon like peptide-1 (GLP-1) [169]. It was observed

that oral administration of glucose triggers a greater insulin secretory response than when it is

administered intravenously [170]. Subsequent studies identified the incretin hormones, GIP

and GLP-1 secreted by the small intestine as playing a role in this insulin release [171, 172].

The biologically active forms of GLP-1 and GIP are formed from post translational

modifications of their precursors pro-GIP and proglucagon respectively [169]. GIP is a

single, 42 amino acid peptide derived from the post-translational processing of a 153 amino

acid precursor [173]. It is secreted predominantly by k-cells and released from the upper

small intestine (duodenum and proximal jejunum) in response to nutrient ingestion, mainly

glucose or fat rich meal and induces insulin secretion [171, 174]. This GIP induced insulin

secretion is responsible for about 70% of postprandial insulin secretion and thus plays a

crucial physiological role in the blood glucose regulation [175]. GIP stimulates glucose-

dependent insulin secretion via the activation of their specific GIP receptors (GIPR)

expressed on the membrane of pancreatic β cells. This in turn activates adnenylyl cyclase,

phospholipase A and extracellular kinase (ERK and MAP), as a result of which, there is a

change in the cellular ion flux ultimately aiding insulin secretion from the pancreatic β cells

[176-181].

In addition to its insulinotropic effect, GIP has also been shown to bioregulate fat metabolism

in adipocytes; inhibit gastric acid secretion, increase glucagon secretion, increase β cell

proliferation and decrease beta cell apoptosis [169,182, 183]. Recent studies have provided

evidence for the presence of GIPR in adipocytes, osteoblasts and central nervous system

(CNS) [169]. In adipocytes GIP has been shown to stimulate the synthesis and release of

lipoprotein lipase which hydrolyses lipoprotein associated triglycerides and facilitates its

24

local uptake as FFAs into adipocytes [183]. It was also seen that there is enhanced level of

GIP in obese subjects with type 2 diabetes. Subsequent studies with GIPR-/- mice revealed

that GIP is an obesity promoting factor. In further studies it was seen that genetic ablation of

GIP signaling not only ameliorates obesity through increased energy expenditure but also

insulin insensitivity and dyslipidemia [184-186]. In osteoblasts it was seen that GIP

stimulates bone formation by preventing the apoptosis of osteoblasts directly through GIPR

[187]. Hence it was suggested that the insulinotropic effect of GIP is only one of the

physiological roles of GIP and it also plays a crucial role in fat accumulation in adipocytes

and bone formation. Though there is no conclusive evidence in the literature suggesting an

altered expression of GIP in T2D, the incretin effect is markedly reduced in subjects with

T2D. This reduction in the incretin effect is mainly attributed to an altered functioning of GIP

[188, 189]. This in combination with the fact that GIP also plays an important role in fat

metabolism makes GIP and its receptor suitable candidate genes for genetic studies in

relation to T2D and related biochemical parameters.

Similar to the secretion of GIP, GLP-1 is secreted by the intestinal L cells in the

distant ileum and colon [190, 191]. GLP-1 exerts insulinotropic effects similar to GIP by

binding to its respective receptor on the pancreatic β cells [169]. GLP-1 receptors are also

expressed on the pancreatic glucagon containing α and δ cells wherein GLP-1 inhibits

glucose dependent glucagon secretion from these cells [169]. In animal studies it has been

shown that GLP-1 induces the transcriptional activation of the insulin gene and promotes

insulin biosynthesis. Additionally GLP-1 is known to stimulate a CNS mediated pathway for

insulin secretion, slows gastric emptying, decreases satiety leading to reduced food intake,

indirectly increases insulin sensitivity and promotes nutrient uptake into skeletal muscle and

adipose tissues [169].

In contrast to GIP, the secretion of GLP-1 is decreased in subjects with T2D [192].

But it is unknown as to whether this decreased secretion is a cause or a consequence of T2D.

Despite the reduced secretion of GLP-1 in patients with T2D, the insulinotropic effect of

GLP-1 is maintained and also its effect on gastric emptying and glucagon secretion [193-

196]. The exogenous GLP-1 has shown to help maintain blood glucose homeostasis to near

normal in patients with T2D [196]. Several studies have provided evidence supporting the

25

beneficial effects of synthetic GLP-1 on insulin secretion and blood glucose levels.

Additionally incretin based drug therapies are now a days commonly used in the treatment of

T2D. Both GLP-1 agonists and DPP-IV (incretin degrading protein) inhibitors have shown to

have beneficial effects on patients with T2D [169].

The important role played by the incretin hormones GIP and GLP-1 in the regulation

of blood glucose homeostasis and in the pathogenesis of T2D makes both GIP and GLP-

1suitable candidate genes for genetic studies in relation to T2D. Though many genetic studies

have been carried out to understand the role played by GIPR and GLP-1R, very rarely have

studies focused on the genetic role of the incretins in T2D. In a recent study by Inke et al.,

they analyzed two SNPs, rs2291725 (G>A, Ser103Gly) and rs2291726 (A>G, a putative

splice site SNP) in GIP, for association with traits of the metabolic syndrome in a case-

control study in European population but failed to observe any significant difference [197].

Further analysis of these two SNPs to analyze the association with T2D proved to be

negative [197]. However, the sample size used to detect association with T2D was small and

this study was carried out only in one population. No reports of studies pertaining to

variations or mutations in GLP-1 in a relation to T2D are available.

1.6.3 Forkhead box O3 (FOXO3) – Study III

Liver is one of the major metabolic organs in the body which acts as the principle glucose

storage site apart from muscles and adipocytes [38]. Glucose is primarily stored in liver and

muscles as glycogen and as fat in white adipocytes. During fasting condition, glycogen is

converted to glucose in the liver (glycogenolysis) and released into the blood stream, whereas

in fed state insulin inhibits the production of glucose and promotes the synthesis of glycogen

to be stored in the liver [38]. Liver is also responsible for the production of glucose from

other sources by a process named gluconeogenesis. The production of glucose in liver is

controlled by several proteins like Glucose 6 phosphatase complex and PEPCK [38, 70, 71].

Forkhead box group O (FOXO) subfamily of proteins play a major role in the

transcriptional regulation of many proteins which are directly involved in metabolism,

including insulin like growth factor binding protein-1(IGFBP-1) [198], G6Pase [199] and

26

PEPCK [200] (Table 1.6). Both G6Pase and PEPCK are key enzymes playing an important

role in EGP by liver.

Table 1.6 FOXO target genes involved in metabolism*.

Genes Organs/ Cell type Effect of FOXO Metabolic effects

G6Pase Liver, kidney Upregulation Increased gluconeogenesis G6Pase transporter Liver Upregulation Increased gluconeogenesis HMG-CoA synthase Liver Upregulation Ketone body production IGFBP-1 Liver Upregulation Inhibition of IGF-1 PGC-1α Liver Upregulation Increased gluconeogenesis PDK4 Muscle, liver Upregulation Glucose saving

LPL Muscle Upregulation Triglyceride clearance;fatty acid metabolism

PEPCK Liver, kidney Upregulation Increased gluconeogenesis PDX-1 Pancreatic β-cell Downregulation Inhibition of β-cell differentiation p21 Adipocyte Upregulation Inhibition of fat cell differentiation AdipoR1/2 Muscle, liver Upregulation Glucose uptake, fatty acid oxidation

*Adapted from Barthel et al. 2005 [210].

Among FOXO proteins, FOXO1 is the major regulator of transcription of these

genes, but a recent study has shown that the triple ablation of FOXO genes viz. FOXO1,

FOXO3 and FOXO4 causes much more pronounced hypoglycemia, improved glucose

tolerance and improved insulin sensitivity as compared to single knock out of FOXO1 [201].

This indicates that other FOXO proteins in addition to FOXO1 also play a role in hepatic

glucose production. FOXO transcription factors are Daf-16 homologues, which in C. elegans

regulates the transcription of genes involved in the regulation of glucose and lipid

metabolism, stress response, fertility and defense mechanism [202-204]. In mammals, there

are four FOXO proteins identified which include FOXO1 (Foxo1a), FOXO3 (FoxO3a),

FOXO4 (FoxO4) and FOXO6 (FoxO6) [205]. Early studies with IGFBP-1 provided

important evidence that FOXO transcription factors can bind to insulin response sequences

(IRSs) similar to IRS first identified in PEPCK [206, 207]. Reporter gene studies with

promoters containing IRS provided evidence that signaling through PI3K and PKB is

necessary and sufficient to mediate sequence specific effect of insulin on gene expression

through IRS [208]. Insulin signaling results in the phosphorylation of PKB/AKT via PI3K

activation. The activated PKB/AKT directly leads to the phosphorylation of FOXO

27

subfamily of proteins and hence regulates their intracellular localization and transcriptional

activity, thus providing the link for the regulation of FOXO proteins by insulin signaling

[209, 210].

Further studies with FOXO1, FOXO3 and FOXO4 confirmed that they can bind to

IRSs in a sequence specific manner and signaling through PI3K-PKB pathway suppresses

transactivation of target genes by FOXO proteins [211-214]. Cell culture studies further

confirmed that signaling and inhibition of FOXO proteins contributes to the ability of insulin

to suppress the gene expression through related IRS in IGFBP-1, G6Pase and PEPCK.

Additionally FOXO proteins also play an important role in the regulation of many other

proteins involved in metabolism [215-217]. FOXO proteins can also modulate the

transcriptional activity of promoters lacking a FOXO binding site by binding to other

transcription factors like signal transducer and activator of transcription-3 (STAT3) or

nuclear hormone receptors [218-220]. The ability of FOXO transcription factors particularly

FOXO1 to interact with PPARγ and HNF-4 is of particular interest [218, 221]. Both these

proteins play an important role in the transcription of genes involved in metabolism. A list of

such proteins, the expression of which is modulated by FOXO subfamily of proteins is given

in Table 1.6. Taken together, these studies confirm that FOXO proteins are key targets of

insulin signaling and play a crucial role in glucose metabolism and hence in the pathogenesis

of T2D.

Knockout studies of FOXO family members have revealed that FOXO1 is the most

vital member of this family as FOXO1 knockouts are not viable [205, 222]. In comparison,

FOXO3 knockouts are viable but show suppression of follicular activation and hence play a

role in regulation of fertility [205, 223]. FOXO3 knockouts also revealed some physiological

abnormalities consistent with the diverse functions of FOXO3. Interestingly FOXO3

knockout mice showed decreased rate of glucose uptake in glucose tolerant test after an

overnight fast [223]. A recent study also provided further evidence that FOXO proteins act

synergistically to regulate hepatic glucose production [224]. FOXO1 has been primarily

implicated in the regulation of hepatic glucose production via transcriptional regulation of

key genes like G6Pase and PEPCK [201]. The study shows that, compared to single

knockout of FOXO1, triple ablation of FOXO genes (FOXO1, FOXO3 and FOXO4) causes

28

more pronounced fasting hypoglycemia, enhanced glucose tolerance, insulin sensitivity and

lower levels of plasma insulin [201]. This indicates that other FOXO proteins apart from

FOXO1 also play a role in the regulation of hepatic glucose production. In fact FOXO3

binding sites have been identified in the promoters of key genes like G6Pase and PEPCK

[225]. FOXO3 is also expressed in major insulin sensitive tissues like adipocytes, muscles

and liver and also in insulin producing pancreatic beta cells [226-228]. Despite these

evidences the genetic role of FOXO genes other than of FOXO1 with respect to T2D has

been hardly assessed.

Recent genetic studies revealed that common variants in FOXO1 is associated with an

increased risk of T2D and associates with insulin secretion and glucose tolerance [229].

Another study also identified common protective haplotype in FOXO1 against T2D [230].

But no studies have been carried out for studying the role of common variants in FOXO3

with T2D. Common variants in FOXO3 were found to be strongly associated with longevity

and the study has been positively replicated in other populations as well [231-234]. It is a

well known fact that calorie restriction is perhaps the only way to extend life span and has

been successfully proved in yeasts, worms, flies, rodents and non- primates [235]. Calorie

restriction without malnutrition has also shown to decrease the incidence of age related

disorders like diabetes and cancer [235, 236]. The role of causal variants in FOXO3 with

longevity has been well proved in different populations. But whether these variants also play

a role in the pathogenesis of T2D has not been yet studied. Additionally, one study also

reported that the minor allele of the SNP rs2802292 in FOXO3 is associated with improved

peripheral and hepatic insulin sensitivity and increased skeletal muscle mRNA expression in

twins [237]. Also the results from various biochemical studies provide increasing evidence

towards the role of other FOXO transcription factors in hepatic glucose production and the

regulation of beta cell dysfunction and hence playing a role in the pathogenesis of T2D [225,

228].

29

1.7 Specific Aims of the Study.

1. Study I: Case-control analysis of SNPs in STRA6, RBP4 and GLUT4 in a South Indian

population with T2D.

2. Study II: Analysis of the genetic role of incretins in the pathogenesis of T2D and

related biochemical parameters.

3. Study III: Case control analysis of common variants in FOXO3 for association with

T2D and related biochemical parameters.