ß-cell reserve in insulin resistant pregnant mice

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Supervisor:

____________________________________ Amélia Maria Lopes Dias da Silva, Ph.D. (Assistant Professor, DeBA, UTAD, Portugal)

Co-Superviser:

____________________________________ Rohit N. Kulkarni, M.D., Ph.D.

(Associate Professor of Medicine, Harvard Medical School, USA)

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Mark:

____________________________

Evaluation Committee:

Chair ______________________________________

Member of the Board ______________________________________

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“The only place where success comes before

work is in the dictionary.”

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Abstract

β-cell reserve in insulin resistant pregnant mice

An overwhelming number of scientific reports suggest a direct correlation between obesity and diabetes. Interestingly, most obese individuals do not develop the overt form of the disease suggesting that the organism is able to compensate for the insulin resistance ambient. These findings raise the urgent importance of understanding the processes, and indentifying the mechanisms that regulate the ability of β-cells to enhance their mass and/or function. Since pregnancy is a robust physiological stimulus for β-cell mass expansion, we aimed to identify the mechanism(s) underlying the pathways that mediate this stimulus and to clarify whether the mechanisms of β-cell expansion during pregnancy are independent of those that occur in response to pathological insulin resistant states. We used pregnant and non-pregnant, liver-specific insulin receptor knockout (LIRKO) mice, and control mice (Lox +/+; Cre -/-) at gestational days 15.5 (G15.5), 17.5 (G17.5) and postpartum days 0 (P0) and 4 (P4) (n=3-6). The random-fed (or fasting) blood glucose levels were higher in LIRKOs at G0 (p<0.001), G17.7 (p<0.01), and P0 (p<0.05) whereas plasma insulin levels were elevated in all gestational days (p<0.001). To assess cell proliferation we immunostained pancreases for Ki67 and insulin and scored Ki67+ β-cells. Ki67+ β-cells reached a peak at G15.5 in both controls and LIRKO animals (p<0.01) and were higher in LIRKO animals. From G0 to G15.5 we observed a 2.9 fold-change in the number of Ki67+β-cells LIRKOs, in contrast to a 1.6 fold-change in controls. This rate decreased at G17.5 to 1.4 fold-change in LIRKOs versus 0.9 fold-change in controls. The proliferation reduced to control levels post-partum. The β-cell mass expansion was different between groups, with LIRKOs reaching a peak of 2.16% at P0 (p<0.001) versus a peak of 0.78% at G17.5 (p<0.001) in controls. At G0 and G15.5 control and LIRKO animals showed similar insulin levels after glucose-stimulated insulin secretion (GSIS) with a tendency to be higher in LIRKOs at baseline levels (3.3 mM glucose). Increasing glucose concentrations to 16.7 mM promoted stimulation of insulin secretion in both controls (p<0.01) and LIRKOs (p<0.01). Our data suggest that LIRKO mothers are able to increase their β-cell mass and function according to the physiological needs of pregnancy. Our results also indicate that there is a reserve of β-cells even in models that exhibit an insulin-resistance phenotype.

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Resumo

Reserva de células β em murganhos gestantes insulino-resistentes

Um número elevado de artigos científicos sugere uma correlação directa entre obesidade e diabetes. Curiosamente, a maioria dos indivíduos obesos não desenvolve diabetes de uma forma notória, sugerindo que os indivíduos conseguem compensar o ambiente de insulino-resistência. Uma vez que a gravidez é, ela própria, um estímulo abrupto ao aumento da massa celular das células β, foi nosso objectivo identificar os mecanismos envolvidos nesse estímulo, assim como clarificar se os estímulos que caracterizam o aumento do número de células β na gravidez são os mesmos responsáveis pelo mesmo fenótipo em estados de insulino-resistência. Neste estudo, utilizaram-se murganhos fêmea controlo (Lox +/+ Cre -/-) e “knockout” para o receptor de insulina dos hepatócitos (“liver-specific insulin knockout” – LIRKO) não gestantes e gestantes nos dias gestacionais 15,5 (G15.5) e 17,5 (G17,5) e nos dias postpartum 0 (P0) e 4 (P4), (n = 3-6). Os níveis de glucose medidos foram mais altos em LIRKOs em G0 (p<0,001), G17,5 (p<0,01) e P0 (p<0,05). Por sua vez, os níveis plasmáticos de insulina foram mais elevados nos animais LIRKO em todos os dias gestacionais estudados (p<0,001). Analisou-se a proliferação celular das células β e calculou-se a sua massa. Para avaliar a proliferação celular, secções pancreáticas foram processadas para imumocitoquímica, usando anticorpos anti-Ki67 (Ki67+) e para insulina. Verificou-se que o número de células β Ki67+ alcançou um pico em G15,5 em ambos os grupos controlo e LIRKO. Em LIRKOs, de G0 a G15,5 ocorreu um aumento na proliferação celular de 2,9 vezes, em contraste com um aumento de 1,6 vezes no grupo controlo. Em LIRKOs, a taxa de proliferação diminuiu em G17,5 para 1,4 vezes em contraste com 0,9 vezes nos controlos. A proliferação diminuiu significativamente “postpartum” para níveis controlo. A expansão da massa celular das células β foi diferente entre grupos, os LIRKOs atingiram um pico em P0 de 2,16 % (p<0,001), em contraste com o grupo controlo com um pico de 0,78 % em G17,5 (p<0,001). Os animais controlo e os LIRKO apresentaram níveis similares de insulina após estimulação com glucose (“glucose-stimulated insulin secretion” – GSIS) com uma tendência para níveis mais elevados no modelo “knockout” em condições basais (3,3 mM glucose). O aumento da concentração de glucose para 16,7 mM, promoveu um acréscimo na secreção de insulina em relação às condições basais, em ambos os grupos em estudo (p<0,01). Os nossos resultados indicam que as fêmeas LIRKO são capazes de responder às necessidades metabólicas da gravidez aumentando a massa celular das células β assim como a sua capacidade funcional. Os nossos resultados levam também a concluir a existência de uma reserva celular em células β mesmo em modelos que exibem um fenótipo de insulino-resistência.

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Acknowledgements

Without the guidance and support from the following people, this work would not have been finished.

In first place I would like to express my gratitude to my supervisor Professor Amélia M. Silva for her supervision, advice, guidance, and friendship. She always provided me unflinching encouragement and support in various ways. Her passion in science, which exeptionally inspire and enrich my growth as a student and researcher.

It is a pleasure to convey my gratitude for this amazing opportunity to my co-supervisor Professor Rohit N. Kulkarni. This work would not have been possible without the wise guidance of him. Always ready to help despite his many other academic and professional commitments, his truly scientist intuition has made him as a constant oasis of ideas. I will never forget our weekly meetings that resembled private lessons in islet cell biology.

I wish to thank my colleagues Jane Hu, Chong Wee, Abdelfattah El Ouaamari, Susana Silva, Shweta Bhatt, Helge Reader, and Massaru Akiyama at Kulkarni lab, Joslin Diabetes Center, for their warm welcome to the lab, advice, and their willingness to share their bright toughts and technical tips with me. My special gratitude goes to Ercument Dirice who shared his project, wide practical expertise, and friendship. I convey special acknowledgement to Kellianne Parlee for her administrative assistance, and to Ben Hambro, Rachael Martinez, Rebecca Windmueller, Geetha Sankaranarayanan, and Zhen Fu for their technical assistance.

My loving thankfulness is dedicated to my family, specially my parents, Alípio and Maria who have always believed in me, and the main reason why I keep working hard.

A special thank goes to my “Bostonian” friends: International Fellowship house (IFH) managers: Amy and Chris Stroup, IFH residents and friends: Tyler, Emil, Sam, Caleb, HyeonWoo, Fabien, Ivan, Benjamin, Ty, Tim, Charith, Hyungseok, Antoine, Kuna, Nathanael, and to my Portuguese mate Ana from hindering life from becoming all work and no play.

My last very special thank goes to my best friends whose names I don´t need to mention.

I have been financially supported by Fulbright Commission (IIE grantee ID: 15104174), which is gratefully acknowledged.

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Abbreviations

ACC ─ acetyl-CoA carboxylase APC ─ antigen presenting cells Atg7 ─ autophagy-related 7 ATP ─ adenosine triphosphate

BIRKO ─ β-cell insulin receptor knockout BrdU ─ bromodeoxyridine

BW ─ body weight

C3G ─ guanyl nucleotide-exchange protein C3G cAMP ─ cyclic adenoside monophosphate CAP ─ Cbl-associated protein

Cbl ─ c-Cbl proto-oncogene CDK ─ cyclin-dependent kinase CDKI ─ CDK inhibitor DAG ─ diacylglycerol DAPI ─ 4´,6-diamino-2-phenylindole DF ─ dilution factor

DNA ─ deoxyribonucleic acid DPP-4 ─ dipeptidyl peptidase-4 E ─ estradiol

EDTA ─ Ethylenediamine tetraacetic acid elF2b ─ guanine nucleotide exchange factor elF4E ─ initiation factor 4E binding protein-1 ELISA ─ enzyme-linked immunoabsorbant assay ER ─ endoplasmatic reticulum

ERK ─ extracellular signal-regulated kinase ERα ─ estrogen receptor-α

ES cells ─ embryonic stem cells

F-1, 6-Pase ─ fructose-1, 6-biphosphate FAS ─ fatty-acid synthase

FBS ─ fetal bovine serum FFA ─ free fatty acid

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G-6-P ─ glucose-6-phosphate GC ─ golgi complex

GD ─ gestational diabetes GFP ─ green fluorescent protein

GIP ─ glucagon-dependent insulinotropic polypeptide GK ─ glucokinase

GLP-1 ─ glucagon-like peptide-1 GP ─ guinea pig

Grb2 ─ adaptor protein of the SOS GS ─ glycogen synthase

GSIS ─ glucose-stimulated insulin secretion GSK3 ─ glycogen synthase kinase-3

H2B-GFP ─ histone 2B-green fluorescent protein Hb9 ─ homeiobox 9

HFD ─ high fat diet

HLA ─ human leukocyte antigen hPGH ─ placental growth hormone

Htr1d ─ serotonin receptor 5-hydroxytryptamine-1d Htr2b ─ serotonin receptor 5-hydroxytryptamine-2b IACUC ─ Institutional Animal Care and Use Committee IDDM ─ insulin-dependent diabetes mellitus

IGF-1 ─ insulin-like growth factor 1 iNOS ─ inducible NO synthase IP3 ─ inositol 1,4,5-triphosphate

IPGTT ─ intra-peritoneal glucose tolerance test iPS cells ─ induced pluripotent stem cells IR ─ insulin receptor

IRS1 ─ insulin receptor substrate 1 IRS2 ─ insulin receptor substrate 2 IRS3 ─ insulin receptor substrate 3 IRS4 ─ insulin receptor substrate 4 Isl1 ─ LIM homedomain protein islet 1 JDC ─ Joslin Diabetes Center

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KO ─ knockout

LIRKO ─ liver-specific insulin receptor knockout MAPK ─ mitogen-activated protein kinase MEK ─ ERK kinase

MEN1 ─ endocrine neoplasia type 1 MHC ─ histocompatibility complex

MIRKO ─ muscle insulin receptor knockout MODY ─ maturity-onset diabetes of the young mRNA ─ messenger RNA

mTert ─ mouse telomerase reverse transcriptase mTOR ─ mammalian target of rapamicin

NIDDM ─ non-insulin-dependent diabetes mellitus O/N ─ overnight

OGTT ─ oral glucose tolerance test P ─ progesterone

p70S6K ─ p70 ribossomal protein S6 kinase P90RSK ─ p90 ribossomal protein kinase

PDK1─ 3-phosphateinositide-dependent protein kinase 1 PDX-1 ─ pancreatic-duodenal homeobox1

PEPCK ─ phosphoenolpyruvate carboxylase PFK ─ phosphofructokinase

PGC-1 ─ peroxisome proliferator-activated receptor-γ coactivator 1α PHH3 ─ phosphohistone-H3

PI3K ─ phosphoinositide 3-kinase

PIP2 ─ phosphatidylinositol (4, 5) biphosphate

PIP3 ─ phosphatidylinositol (3, 4, 5) triphosphate

PK ─ pyruvate kinase PKA ─ protein kinase A PKB/AKT ─ protein kinase B PKC ─ protein kinase C PL ─ placental lactogen PP1 ─ protein phosphatase 1

PPAR-γ ─ peroxisome proliferator-activated receptor-γ pRb ─ retinoblastoma protein

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Prl ─ prolactin

PTEN ─ phosphatase and tensin homologue Ras ─ rat sarcoma

RIA ─ radioimmunoassay RNA ─ ribonucleic acid

ROS ─ reactive oxigen species RT ─ room temperature

SCF ─ Skp-1-Cullin-F-box protein SEM ─ standard error mean SH2 ─ Src-homology-2

SHIP2 ─ SH2-containing inositol 5´-phosphatase-2 siRNA ─ small interfering RNA

SNP ─ small nucleotide sequence SOS ─ son-of-sevenless proteins

SREBP ─ sterol regulatory element-binding protein T1D ─ type 1 diabetes

T2D ─ type 2 diabetes

TNF-α ─ tumor necrosis factor-α TSC1 ─ tuberous sclerosis complex-1 TSC2 ─ harmatin

UCP2 ─ uncoupling protein 2

VDCC ─ voltage-dependent calcium channel VLDL ─ very low density lipoprotein

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List of Figures and Tables

List of Figures

II - Literature Review

Figure II-1: Insulin has a broad spectrum of activity ... 8

Figure II-2: Pathway of insulin biosynthesis ... 9

Figure II-3: Insulin secretion ... 10

Figure II-4: Structure of α-and β-subunits of IR ... 12

Figure II-5: Different functions of the various IRS proteins ... 13

Figure II-6: Insulin signaling pathway ... 16

Figure II-7: Insulin-dependent regulation of glucose fate in liver ... 17

Figure II-8: Illustration of the autoimmune attack in T1D ... 20

Figure II-9: LIRKO mice exhibit hyperglycemia, hyperinsulinemia, glucose intolerance, and insulin resistance ... 27

Figure II-10: Representation of mouse pancreatic organogenesis ... 32

Figure II-11: Sources of new β-cells ... 34

Figure II-12: Control of β-cell mass in rodents and humans ... 40

Figure II-13: β-cell mass maintenance ... 41

Figure II-14: β-cell mass changes during pregnancy in mice ... 45

Figure II-15: Changes in the hormone levels during pregnancy in humans and rodents ... 47

Figure II-16: Mechanisms involved in the β-cell homeostasis during pregnancy and the downstream pathway ... 48

III – Methodology Figure III-1: Procedure to insufflate and remove the mouse pancreas ... 56

IV – Results Figure IV-1: BW of mothers at different time points during pregnancy ... 63

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Figure IV-2: Maternal body weight at different time points of pregnancy ... 64

Figure IV-3: Blood glucose measured at gestational time points G0, G15.5, G17.5, P0, and P4... 66

Figure IV-4: Blood glucose levels at different time points of pregnancy ... 67

Figure IV-5: Plasma insulin levels at getational days G0, G15.5, G17.5, P0, and P4 ... 68

Figure IV-6: Percentage of β-cells in control and LIRKO animals... 70

Figure IV-7: Percentage of β-cells change from G0 to gestational days G15.5, G17.5, P0, and P4 ... 70

Figure IV-8: Percentage of β-cell proliferation ... 71

Figure IV-9: Proliferation fold-change from G0 to gestational time points G15.5, G17.5, P0, and P4 ... 72

Figure IV-10: G0 insulin levels after GSIS at glucose concentration of 3.3 and 16.7 mM ... 74

Figure IV-11: G15.5 insulin levels after GSIS at glucose concentration of 3.3 and 16.7 mM ... 74

List of Tables

IV – Results Table IV-1: BW of mothers at different time points during pregnancy ... 62

Table IV-2: BG in control and LIRKO animals in different gestational days ... 65

Table IV-3: Plasma insulin levels in control and LIRKO animals at gestational days G0, G15.5, G17.5, P0, and P4 ... 68

Table IV-4: Calculated β-cell mass during different time points of pregancy ... 69

Table IV-5: β-cell proliferation (%Ki67+/INS+ cells) ... 71

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I - Introduction

1. Statement of the problem

Diabetes mellitus (DM) is a widespread metabolic disorder that is characterized by uncontrolled hyperglycemia. The disease occurs as a consequence of a complex interaction of genetic and environmental factors and the hyperglycemia is secondary to a combination of inadequate insulin secretion coupled with insulin resistance that manifest as decreased glucose utilization and increased glucose production.

The metabolic dysregulation associated with DM causes secondary physiologic alterations in multiple organ systems that inflict a tremendous burden on the diabetic individuals and on the health care system (Powers 2008).

The worldwide prevalence of DM has risen dramatically over the past two decades, from an estimated 30 million cases in 1985 to 177 million in 2000. Type 1 and type 2 diabetes mellitus together are predicted to affect more than 300 million people worldwide by the year 2020 (Paul Zimmet 2003; Dirice and Kulkarni 2011).

In Portugal, approximately 983 thousand individuals were estimated to have diabetes in 2010, with a higher incidence in older age groups (Diabetes 2010). In our country the disease has reached, without doubt, an epidemic status with devastating consequences at various levels (personal, social, familial and economic). It is expected to entail an undeniable influence in national terms, and this requires the urgent need for early measures for the prevention and control of this disease (Cardoso 2006).

Almost all cases of DM fit in one of the three main types namely, Type 1 or Type 2 diabetes (T1D or T2D) and gestational diabetes (GD). Other types are included in separated categories, including congenital diabetes, cystic fibrosis-related diabetes, and those related to several monogenic forms, termed maturity-onset diabetes of the young (MODY) (Dirice and Kulkarni 2011).

The endocrine pancreas is a plastic tissue capable of altering in response to metabolic variations of the organism, such as those occurring during pregnancy or obesity. In these two different metabolic alterations, peripheral insulin resistance is manifested, increasing the need for additional bioactive insulin to compensate for the lowered insulin sensitivity (Nadal, Alonso-Magdalena et al. 2009).

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Thus, pancreatic β-cells, in an attempt to fulfill the physiological needs, adapt by increasing their secretory response as well as their cell mass. If they fail to adapt, as in the case of pregnancy, GD will develop (Barbour, McCurdy et al. 2007). Barbour and colleagues (2007) reported a doubling in the incidence of GD in the past 6 to 8 years, mainly caused by the obesity epidemic. Data from Western countries suggest an alarming rise in the prevalence of GD to 10% of all pregnancies (Kaaja 2009).

GD carries long-term implications for the subsequent development of T2D in the mother and increased risk of obesity and glucose intolerance in the offspring (Barbour, McCurdy et al. 2007).

The liver-specific insulin receptor knockout (LIRKO) mice is a very good experimental model to examine the pathophysiology of T2D because, the LIRKO mouse model manifests insulin resistance and glucose intolerance and the pancreatic β-cells also attempt to compensate for the metabolic alterations by increasing their mass (Michael, Kulkarni et al. 2000; Okada, Liew et al. 2007).

Therefore, the experiments presented in this thesis provides novel information that is relevant to the diabetes field and also addresses challenging questions. With our work we will attempt to find the answers to specific questions related to the ability of the LIRKO model to compensate for the relative insulin resistance that occurs as a consequence of the pregnant state with the long-term goal of discovering new therapeutic approaches to counter the epidemic of T2D.

2. Aims

(a) To identify the mechanisms underlying the ability of a physiological stimulus such as pregnancy to expand β-cell mass with the long term aim of suggesting therapeutic approaches for the treatment of T2D.

(b) To characterize the factors controlling both β-cell proliferation and survival to suggest direct therapeutic strategies to enhance endogenous β-cells and/or to improve islet transplantation approaches.

(c) To characterize the contribution of β-cell dysfunction to the pathophysiology of gestational diabetes (GD), specifically in the context of an insulin resistant model.

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3. Questions

(a) Can β-cells compensate for an increased insulin demand in a physiological state of insulin resistance such as pregnancy, even in an insulin resistant model such as the LIRKO mouse, by an increment in β-cell mass, number, and/or secretion?

(b) Do LIRKO mice have a reserve of β-cells that allow them to further enhance their mass?

4. Hypothesis

(a) The balance between proliferation and apoptosis of β-cells in the LIRKO mouse favors proliferation during pregnancy.

(b) The LIRKO mouse has a robust reserve of β-cells that allows them to compensate for the physiological demand of insulin resistance in pregnancy.

(c) The overt form of gestational diabetes requires the presence of insulin-resistance and a failure of the β-cells to compensate even in insulin resistant models.

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II - Literature review

1. History of Diabetes Mellitus

The history of DM begins in 1552 B.C, with the findings of some writings from earliest civilizations (Savona-Ventura 2002). The Ebers papyrys is the first reference to the disease, this recommended a special diet of fruits, grains and honey, but despite the improvement in the health of the patient, this didn´t cure the patient (Savona-Ventura 2002; Eknoyan and Nagy 2005).

The name “diabetes” was first used around 250 B.C., Demetrius of Apameia is recognized for the introduction of the word (Eknoyan and Nagy 2005). The word has a Greece origin and means “to siphon”, reflecting how diabetes seemed to rapidly drain fluid from the affected individual (Ensminger, Ensminger et al. 1995; Dean and McEntyre 2004). Galen (129-200 A.D.) established an association between the kidney and diabetes (Eknoyan and Nagy 2005), from experimental results he obtained from dogs, concluding that kidneys were responsible for “attract the watery substance of the blood” he made a brilliant association between the high water consumption and the polyuria characteristic of DM.

Along the history we can find various descriptions and treatment attempts made by different physicians: Aulus Cornelius Celsus (10 A.D); Galen (160 A.D); Avicenna (980-1037); Paracelsus (1500s); Geronimo Cardona (1550); but only in the past 200 years, scientists began to realize what diabetes truly is and what are the causes of the disease (Ali, Anwar et al. 2006; dLife 2009).

A remarkable step in the diabetes field occurred in 1889, when Joseph von Mering and Oskar Minkowski, surgically removed the pancreas from dogs and established a link between the pancreas gland and diabetes (Luft 1989). In the twenty century, Eugene Opie links diabetes with islet cells (by the year 1901). Jean Meyer proposes, in 1909, the name “insulin” (Latin: insula, island) for the unknown substance produced in the pancreas. Frederick Madison Allen and Elliot P. Joslin were the leading diabetes specialists in the United States. Moses Baron (University of Minnesota, 1919) conclude that the islets secrete a hormone in the lymph or blood stream with the capacity of regulating the carbohydrate metabolism (Ali, Anwar et al. 2006).

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In July of 1921, Banting and his assistant Charles Best, collected a residue from which insulin could be extracted. A pancreatized dog was kept alive for eight days by regular injections until supplies of the extract, at that time called “isletin”, were exhausted. This extract caused a drop of blood glucose and produced an improvement in the clinical condition (Ensminger, Ensminger et al. 1995; Pyke 1997; Dean and McEntyre 2004).

Leonard Thompson, in January 1922, became the first patient to receive injections of pancreatic extract. Dr. J. Collip, a biochemist, improved the extract purity and several weeks later Leonard was treated again and showed a remarkable recovery (Ensminger, Ensminger et al. 1995; Pyke 1997; Dean and McEntyre 2004).

In 1923, Banting and Macloed won the Nobel Prize for the discovery of insulin, Banting split with Best and Macloed with Collip. The following years brought special insulin syringes, meters and one important fact on 1978, when recombinant human DNA insulin was produced by the first time (Ensminger, Ensminger et al. 1995).

Today the research continues with the final goal of finding a therapeutic solution for diabetes.

2. Classification of Diabetes

In contrast with the past (Ensminger, Ensminger et al. 1995) where diabetes mellitus was classified based on the onset age or therapy type, nowadays DM is classified on the basis of the pathogenic process that results on hyperglycemia (Powers 2008).

According to American Diabetes Association (American Diabetes 2010), diabetes can be classified into 4 main categories; type 1 diabetes (T1D), type 2 diabetes (T2D), gestational diabetes (GD) and other specific types (see American Diabetes 2010). From these, the more frequent are T1D and T2D.

T1D is characterized by a complete or close to total insulin deficiency, caused by β-cells auto-destruction through an autoimmune mechanism. T2D is characterized by different disorders, normally sharing together the insulin resistance, impaired insulin secretion and increased glucose production. (Dirice and Kulkarni 2011).

Consequently, with this classification, the old terms insulin-dependent diabetes

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many individuals with T2D require insulin treatment and age is not a criterion because autoimmunity against β-cells can develop at any age. (American Diabetes 2011).

3. Control of glucose and lipid metabolism by insulin signaling

Plasma glucose normally ranges between 4 and 7 mM, this balance is kept through a glucose control production by the liver, absorption from the intestine and uptake and metabolism by the peripheral tissues (Saltiel and Kahn 2001).

Insulin is the most important regulator of this metabolic balance (Figure II-1), insulin increases the glucose uptake by the muscle and fat, while have the capacity to inhibit the glucose production in the liver, but neural input, metabolic signals, and other hormones (e.g., glucagon) result in integrated control of glucose supply and utilization (Saltiel and Kahn 2001; Powers 2008; Kawamori, Kurpad et al. 2009)

Figure II-1: Insulin has a broad spectrum of activity. It promotes the storage of glucose and the synthesis of proteins and lipids, inhibits their degradation and prevents their release in the circulation. Insulin increase the activity of enzymes responsible for glycogen, lipid and protein synthesis, while inhibit enzymes responsible for the degradation of these metabolites. Figure extracted from (Saltiel and Kahn 2001).

´ The role of insulin is not restricted to the metabolic balance, insulin signaling also stimulates cell growth, differentiation and influences life spam (Taguchi and White 2008)

According to Bouche and colleagues (2004), the major pathways for glucose utilization consist in: i) glucose oxidation to pyruvate (glycolysis), which in turn can go through further oxidation steps in the citric acid cycle; ii) storage as glycogen (glycogen synthesis) for fast utilization at a later time and iii) conversion to other metabolites, utilized in different pathways, like pentose phosphate and hexosamine biosynthesis pathway.

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Therefore, in summary, a low insulin level (for example, in the fasting state) promotes an increase on glucose production by hepatic gluconeogenesis, glycogenolysis, and lipolysis (mobilization of free fatty acids), helped by glucagon secretion — secreted by alpha-cells (α-cells) — while reduces glucose uptake by the peripheral tissues (skeletal muscle and adipose tissue). When glucose levels rise, the balance is reversed and glucagon levels diminish, in contrast to the levels of insulin (Powers 2008).

As we will discuss later, in cases of insulin resistance, this equilibrium is affected, and is characterized by high levels of glucose and lipids in fasting and in the posprandial state.

3.1. Insulin biosynthesis, secretion and action

3.1.1. Insulin biosynthesis

The insulin gene encodes the information for preproinsulin. This polypeptide has 110-aminoacids and his produced in β-cells. This precursor is translocated into the endoplasmatic reticulum (ER) where its signal peptide is cleaved (Figure II-2A, gray bar) originating proinsulin, a 86 amino-acid peptide (Powers 2008; Liu, Wan et al. 2009).

Figure II-2: A, pathway of insulin biosynthesis, preproinsulin (top), signal peptide (gray), B-domain (blue), dibasic BC and CA junctions (green), C-domain (black), A-C-domain (red). B, Structural model of insulin, representing the domains (A and B) and disordered connecting peptide (black dashed line). C, Cellular pathway of insulin biosynthesis, proinsulin fold as monomer in ER, than is processed in GC by pro-hormone convertases and is stabilized by the formation of Zinc-insulin hexamers. Figure adapted from (Liu, Wan et al. 2009).

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Once in the ER, proinsulin suffers a folding, where two cystines provide the interior support (Figure 2B, A20-B19) and a third cystine provides the external staple (Figure II-2B, A7-B7) (Liu, Wan et al. 2009). After folding in the ER, proinsulin transits to the Golgi complex (GC) where the A (21 aminoacids) and B (30 aminoacids) are separated from the C-peptide by pro-hormone convertase (Figure II-2A, 2B), and is stored together with Zn2+

(Figure II-2C) (Powers 2008; Liu, Wan et al. 2009).

C-peptide is often used to discriminate between an endogenous or an exogenous source and is used to mark insulin secretion because is cleared more slowly comparatively to insulin (Powers 2008).

3.1.2. Insulin secretion

Different factors, such as, calcium ion (Ca2+_{), adenosine triphosphate (ATP), cyclic}

adenoside monophosphate (cAMP), inositol 1,4,5-triphosphate (IP3) and diacylglycerol

(DAG), controls insulin secretion from the β-cells (Figure II-3), but the main signal comes from glucose. When glucose levels go over 70 mg/dL, insulin synthesis is stimulated (Prentki and Matschinsky 1987; Bennett, James et al. 2010; Seno, Shbasaki et al. 2010).

Figure II-3: Insulin secretion. Glucose is transported by GLUT2, increasing the ATP production which closes the KATP

channel, resulting in a depolarization (∆ψ) of the β -cell membrane, this opens the VDCC´s allowing the Ca2+ influx, finishing with the release of insulin. Incretins, bind to G-protein coupled receptor (GPCR) activating adenylyl cyclase (AC), causing an increment in the cAMP concentration. cAMP activates PKA and Epac2 stimulating insulin release. Other hormones, as acetylcholine (ACh) bind to GPCRs activating phospholipase C (PLC) which produce different messengers, as DAG and IP3. DAG activates PKC and IP3 recruits Ca2+ from intracellular vesicles. Figure extracted

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The process starts with glucose transport into β-cells by GLUT2 transporters. From glucose metabolism, starting with glucose phosphorylation into glucose-6-phosphate by glucokinase (GK), there is an increase in the ATP/ADP ratio (Prentki and Matschinsky 1987; Bouche, Serdy et al. 2004; Powers 2008; Bennett, James et al. 2010; Seno, Shbasaki et al. 2010). The increased ATP/ADP ratio leads to ATP-sensitive K+_(K

ATP)

channels closure, causing β-cell membrane depolarization with consequent activation of voltage-dependent calcium channels (VDCC´s) permitting the Ca2+_{influx, causing the}

release of insulin granules (Seno, Shbasaki et al. 2010). The KATP is constituted by two

different proteins, one is SUR, where oral hypoglycemic as sulfonylureas act, the other is the rectifying K+ channel protein (Kir6.2) (Powers 2008).

Nevertheless glucose is not the only signal responsible for insulin release, incretins, including glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP) play an important role potentiating insulin release (Figure II-3) (Kulkarni 2010). Insulin secretion is also regulated by cAMP (Figure II-3), protein kinase A (PKA) - dependent way (Prentki and Matschinsky 1987) and by an independent route (Ozaki, Shibasaki et al. 2000; Zhang, Katoh et al. 2009). Nevertheless, the role of these metabolites in the insulin secretion process was not fully understood until the publication by Song and colleagues (2011), where they have shown an important role of Snapin in the insulin secretion by coordination between the incretins and PKA signal.

Recently, it was shown that a reduced insulin secretion in a mouse model knockout (KO) for the pik3r1 gene in the β-cells and a consequent inhibition of phosphoinositide 3-kinase (PI3K) (βDKO mouse), demonstrating an important role of the class IA PI3K pathway in the regulation of insulin secretion and a possibility for a therapeutic approach (Kaneko, Ueki et al. 2010).

3.1.3. Insulin action

3.1.3.1. Insulin receptor (IR)

Insulin signaling starts with the binding of insulin to its receptor (IR). The IR is a tetrameric protein with kinase activity (Figure II-4) constituted by two α- and two β-subunits (Saltiel and Kahn 2001; De Meyts and Whittaker 2002; Belfiore, Frasca et al. 2009).

The IR includes a family of tyrosine kinase receptors that include insulin-like growth factor 1 (IGF-1).The subunits inhibit β-subunits kinase activity. Insulin biding to the

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α-subunits causes a conformational change and auto-phosphoriyation of β-α-subunits causing an increase of β-subunits kinase activity (Patti and Kahn 1998; De Meyts and Whittaker 2002).

Figure II-4: Structure of α- and β-subunits of IR. The left part of the image “a” represent the boundaries of the 22 exons of the IR gene and the right part correspond to predicted boundaries of the protein modules. The image “b” represents the tridimensional scheme of the IR protein modules organization. Extracted from (De Meyts and Whittaker 2002).

3.1.3.2. Insulin receptor substrates (IRS)

The insulin receptor substrate 1 (IRS1) and the insulin receptor substrate 2 (IRS2) are essential for the downstream signaling of insulin and IGF-1 (Figure II-5). This substrates connect the IR to important phosphorylation cascades (Saltiel and Kahn 2001; Taguchi and White 2008). This family of IRS includes not only IRS1, IRS2, IRS3 (in Humans) and IRS4 (in rodents), but also, other proteins containing Src – homology – 2 (SH2) domains, like the adaptor proteins p85 (regulatory sub-unit of PI3K) and Grb2 (adaptor protein of the Son-of-sevenless (SOS)) (Saltiel and Kahn 2001).

To elucidate the role of the IRS1 and IRS2, knockout (KO) models have been created. Mice lacking IRS1, showed reduction in the intrauterine growth, impaired glucose tolerance and a decrease in the insulin stimulated glucose uptake (Araki, Lipes et al. 1994), defects in the insulin secretory responses, reduced islet insulin content, and increased number of autophagic vacuoles in the β-cells (Kulkarni 2002).

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Figure II-5: Different functions of the various IRS proteins. Based in knockdown and knockout studies Taniguchi and colleagues (2006) elaborated this figure were in purple boxes we can see the action of each IRS, in black the insulin action and the intensity of each pathway is represented by the thickness of the arrow.

In contrast, the mice KO for IRS2 (Withers, Gutierrez et al. 1998) were characterized by a deterioration of the glucose metabolism, caused by liver and skeletal muscle insulin resistance, while a lack in the compensation for the insulin resistance by the β-cells.

Nevertheless, the studies cited above (Araki, Lipes et al. 1994; Withers, Gutierrez et al. 1998; Kulkarni 2002) demonstrate a complementary role between IRS1 and IRS2 rather an independent function between the two substrates.

3.1.3.3. The PI3K – protein kinase B / AKT pathway

The PI3K is important in the regulation of mitogenics, cellular differentiation and glucose transportation. PI3K is constituted by a catalytic subunit – p100 and by a regulatory subunit – p85 which interact with the IRS protein by its SH2 domains (Folli, Saad et al. 1992). The PI3K is responsible for the formation of some lipid second messengers, like phosphatidylinositol (3, 4, 5) triphophate (PIP3). PIP3 regulates the AGC

superfamily of serine/threonine protein kinases, guanine-nucleotide-exchange protein of the Rho family and the TEC family of tyrosine kinases (Taniguchi, Emanuelli et al. 2006).

Insulin binding to IR, recruits the PI3K to the cell membrane, generating PIP3 from

phosphatidylinositol (4, 5) biphosphate (PIP2) (Lizcano and Alessi 2002). Conversion of

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the phosphatase and tensin homologue (PTEN), and SH2-containing inositol 5´- phosphatase - 2 (SHIP2) (Taniguchi, Emanuelli et al. 2006)

One of the most important elements of the AGC family, for the insulin signaling, is the 3-phosphateinositide-dependent protein kinase 1 (PDK1). PDK1 activates different targets (Figure II-6), as Akt (PKB) and PKC λ/ζ (Saltiel and Kahn 2001; Lizcano and Alessi 2002; Taniguchi, Emanuelli et al. 2006; Taguchi and White 2008). The Akt possesses a PH domain through which it is recruited by PIP3 to the cell membrane; here

the Akt can be phosphorylated by PDK1. Once activated, Akt modulates the activity of various targets (see Figure II-6) (Lizcano and Alessi 2002). Akt mediates the stimulation of glycogen synthesis by insulin. Akt phosphorylates and inactivate the glycogen synthase kinase-3 (GSK3), which is the main responsible for the inactivation o glycogen synthase (GS), this leads to the activation of GS — enzyme that catalyzes the conversion of UDP-glucose into glycogen — improving the liver UDP-glucose uptake. GSK is also responsible for the inhibition of the guanine nucleotide exchange factor (elF2b), therefore, like we explain above for the GS, this will implicate activation of the elF2b and as consequence a positive effect in the protein synthesis, because elF2b controls the initiation of protein translation (Lizcano and Alessi 2002; Taniguchi, Emanuelli et al. 2006).

Nevertheless, the role of Akt is not limited to the glycogen synthesis or protein translation, Akt phosphorylates and activates PDE3B, a cAMP phosphodiesterase isoform responsible for the decrease in the cAMP concentration, resulting in a diminish of lipolysis. Akt also controls GLUT4 exocytosis, by phosphorylation and inactivation of the Rab-GTPase-activating protein (AS160) and in addition activates some PKC isoforms (Lizcano and Alessi 2002; Taniguchi, Emanuelli et al. 2006; Cheng, Tseng et al. 2010).

Akt also phosphorylates and inhibits the tuberous sclerosis complex-2 (TSC1), which forms a complex with the hamartin (TSC2). This complex is responsible for the inactivation of the mammalian target of rapamicin (mTOR ). With the inactivation of the complex TSC2/TSC1, mTOR pathway is effectively activated resulting in the phosphorylation of p70 ribossomal protein S6 kinase (P70 S6K) and eukaryotic translation initiation factor 4E binding protein – 1 (elF4E), in other words regulating the protein synthesis, cell-cycle progression, lipid synthesis, etc (Laplante and Sabatini 2009).

In conclusion, other important role of Akt in the regulation of the glucose metabolism by insulin stimulation, is the effect of Akt in the forkhead transcription factors (FOXO). Akt causes the relocalisation of FOXO (FOXO1, FOXO2 and FOXO3) from the nucleus to the

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cytoplasm, inhibiting their function in gluconeogenesis (Lizcano and Alessi 2002; Taniguchi, Emanuelli et al. 2006; Taguchi and White 2008; Cheng, Guo et al. 2009; Cheng, Tseng et al. 2010).

3.1.3.4. The Ras – MAPK pathway

The Rat sarcoma (Ras) – mitogen-activated protein kinase (MAPK) pathway have an important function in the control of cell growth, survival and differentiation (Avruch, Khokhlatchev et al. 2001; Taniguchi, Emanuelli et al. 2006). Activation of this pathway by binding of insulin to the IR induces IRS phosphorylation, which in turn phosphorylates and activates the adaptor protein Grb2 recruiting the SOS (Figure II-6). The complex Grb2 – SOS activates the GTPase protein Ras, this is followed by c-Raf activation and the beginning of a cascade of phosphorylations, involving different sub-types of extracellular signal-regulated kinases (ERK) and MAPK / ERK kinases (MEK) (Avruch, Khokhlatchev et al. 2001).

Finally, the activated ERK controls the expression of different targets, like the transcription factor p62 or the p90 ribossomal protein kinase (p90RSK) (Avruch, Khokhlatchev et al. 2001; Saltiel and Kahn 2001; Taniguchi, Emanuelli et al. 2006)

3.1.2.5. The Cap – Cbl pathway

One of the most important roles of insulin is the stimulation of glucose uptake (Figure II-6), especially by the recruitment of GLUT4 transporters from intracellular sites (Lizcano and Alessi 2002). The c-Cbl proto-oncogene (Cbl) is phosphorylated in its tyrosine residue, forming a complex with an adaptor protein – Cbl-associated protein (CAP) (Taniguchi, Emanuelli et al. 2006). The Cbl - CAP complex interacts with the proteins Flotilin in the plasma membrane, recruiting the adaptor protein CrkII. CrkII forms a complex with the guanyl nucleotide-exchange protein C3G (C3G), this complex catalyzes the replace of GTP by GDP of the G protein TC10 (TC10), finally TC10 stimulates GLUT4 translocation probably through an effect in the stabilization of the cortical actin (Saltiel and Kahn 2001; Lizcano and Alessi 2002; Kanzaki 2006; Taniguchi, Emanuelli et al. 2006).

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Figure II-6: Insulin signaling pathway – The signal transduction of insulin is transmitted through the tyrosine kinase insulin receptor, which catalyses the phosphorylation of cellular proteins such as members of the IRS family – Shc and Cbl. This proteins act together with other secondary signaling molecules through their SH2 domains resulting in different pathways. Activation of IRS1 and IRS2 occur in nearly all cells, but other substrates exist in specific cells and tissues. The SOS/GRB2 branch activates the ras→RAF→MEK→ERK cascade. Activation of PI 3-kinase during recruitment to IRS1/2 produces PIP2 and PIP3 (antagonized by the action of PTEN or SHIP2), which recruit PDK1 and AKT to the plasma membrane, where AKT is activated by PDK-mediated phosphorylation. AKT phosphorylates many substrates, including the cyclin-dependent kinase inhibitor p21kip, GSK3β, BAD, eNOS, and FOXO1; phosphorylation of FOXO1 inactivates this transcription factor and causes its sequestration in the cytosol, which alters the expression of many genes. The mTOR kinase is activated by Rheb, which accumulates upon inhibition of the GAP activity of the TSC1/TSC2 complex by AKT mediated phosphorylation. The p70s6k is primed for activation by PDK1-mediated phosphorylation and ultimately activated by mTOR-mediated phosphorylation. Insulin stimulates protein synthesis by altering the intrinsic activity or binding properties of key translation initiation and elongation factors (eIFs and eEFs, respectively), including eIF4A and eIF4G. In particular, phosphorylation of 4E-BP1 releases eIF4E to form an active complex promoting translation initiation (Saltiel and Kahn 2001; Taguchi and White 2008). Figure from (Cell Signaling 2011).

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3.2. Glucose and Lipid regulation

3.2.1. Glycogen synthesis

Mainly, glycogen is formed in muscle being a source of energy to be used for the muscle contraction, while in liver is used to maintain glycaemia (Bouche, Serdy et al. 2004). As we briefly explain previous, insulin activates the formation of glycogen through the inhibition of GSK-3 by phosphorylation, this activates the GS by decreasing its phosphorylation (Figure II-7). Protein phosphatase 1 (PP1) also contributes for the activation of GS, for the reason that desphosphorylates GS and inactivate the glycogen phosphorylase (Saltiel and Kahn 2001; Bouche, Serdy et al. 2004).

Figure II-7: Insulin dependent regulation of glucose fate in liver. Insulin promotes glucose utilization and storage in the form of glycogen and lipids, this is achieved by the regulation of specific enzymes. Insulin activates glycogen synthase and citrate lyase by influencing their phosphorylation state. Insulin inhibits the expression of some gluconeogenic enzymes and transcription factors (in red), while activate glycolitic and lipogenic enzymes, as well as the transcription factor sterol regulatory element-binding proteins (SREBP) (in blue). Glucokinase (GK); glucose-6-phosphatase (G-6-Pase); fructose-1,6- biglucose-6-phosphatase (F-1,6-Pase); phosphoenolpyruvate carboxylase (PEPCK); phosphofructokinase (PFK); pyruvate kinase (PK); acetyl-CoA carboxylase (ACC); fatty-acid synthase (FAS). Figure extracted from (Saltiel and Kahn 2001).

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3.2.2. Gluconeogenesis

One important function of gluconeogenesis is the ability to convert some metabolic products, like lactate or glycerol into glucose, when glucose dietary sources are not available, this is very useful in the fasted state to control glycaemia, liver and kidney are the principal organs responsible for gluconeogenesis (Bouche, Serdy et al. 2004).

Nevertheless, in the pathophysiology state of T2D, the equilibrium between gluconeogenesis and glycogenesis is disturbed. Visceral fat is less sensitive to insulin comparing with subcutaneous fat for example; this means that even in a post-prandial state, lipolysis generate fatty acids that are sent by the portal vein to the liver, stimulating glucose production (gluconeogenesis) (Saltiel and Kahn 2001).

Many of the enzymes responsible for the glycolysis pathway are shared with gluconeogenesis (Bouche, Serdy et al. 2004), insulin regulates the expression of some important and rate-limiting enzymes (Figure II-7), for example, insulin inhibits the gene expression of phosphoenolpyruvate carboxylase (PEPCK), fructose-1, 6-biphosphatase (F-1,6-Pase), glucose-6-phosphatase (G-6-Pase). In other hand, insulin stimulates the transcription of glucokinase (GK), pyruvate kinase (PK), fatty acid synthase and acetyl-CoA carboxylase (Saltiel and Kahn 2001; Bouche, Serdy et al. 2004).

Finally, regardless the controversial results, the peroxisome proliferator-activated receptor-γ coactivator 1α (PGC-1) seems to have an important role in the regulation of gluconeogenesis. PGC-1 is responsible for the mitochondrial biosynthesis, being involved in the β-oxidation and in the expression of gluconeogenesis genes (Saltiel and Kahn 2001; Puigserver and Spiegelman 2003; Bouche, Serdy et al. 2004; Taniguchi, Emanuelli et al. 2006; Cheng, Guo et al. 2009).

3.2.3. Lipogenesis and Lipolysis

A family of transcription factors denominated sterol regulatory element-binding proteins (SREBP) regulates the lipid homeostasis. This transcription factors are responsible for the expression of genes encoding some important enzymes of lipogenesis: pyruvate dehydrogenase, fatty acid synthase and acetyl-CoA carboxylase (Saltiel and Kahn 2001; Ferré and Foufelle 2010).

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Thus, insulin signaling induces the SREBP expression (by PI3K / Akt pathway), promoting the synthesis of lipids (Figure II-7). However, there are some reports of an over-expression of SREBP in cases of insulin resistance in liver (where the insulin signaling is reduced), Ferré and Foufelle (2010) suggest an effect of endoplasmatic reticulum (ER) stress in the activation of SREBP.

Finally, insulin also inhibits lipolysis, specially inhibiting the enzyme lipase by the activation of PDE3B (Figure II-6), reducing the concentration o cAMP and inhibiting PKA activity (Saltiel and Kahn 2001; Ferré and Foufelle 2010).

4. Type 1 Diabetes (T1D)

4.1. Epidemiology

Insulin deficiency that characterizes T1D is caused by the destruction of β-cells by the immune system. It is a chronic and progressive process involving both genetic background and environmental factors where the immune system loose the capability of distinguish the self and the non-self (Pirot, Cardozo et al. 2008; Dirice and Kulkarni 2011).

T1D is responsible for 5 to 10% of all cases of diabetes and the prevalence varies between countries and between regions in the same country. According to Maahs and colleagues (2010), the worldwide prevalence is increasing by 2 to 5% and the prevalence of T1D in the United States (USA) is 0.33% by 18 years of age. In Portugal the prevalence of T1D (0-19 years old), in 2009, was 0.12%, the evolution from 2000 to 2009 was an average of 11.2 new cases per 100 000 individuals (Diabetes 2010).

Although the statistic analyses of risk factors should always be analyzed very carefully, age, sex, race, genotype, geographic location and seasonality seems to be risk factors for T1D (Maahs, West et al. 2010). Most of the T1D cases affect individuals younger than 20 years. Contrary to some autoimmune diseases, T1D affects both girls and boys (Maahs, West et al. 2010). Accordantly to a study performed by Mayer-Davis and colleagues (2009), the non-Hispanic white were the ethnicity group with higher prevalence.

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4.2. Pathophysiology

One of the most intriguing aspects of the T1D is the selectively attack of β-cells even they have the same embryological origin and share most of the proteins with other cell types in the islet cell.

As mentioned before, there are probably two main causes of T1D, one the genetic background and the other environmental effects. There are some genetic variations that characterize T1D patients, for example, the human leukocyte antigen (HLA) locus, containing genes expressing some histocompatibility complex (MHC) molecules (Pirot, Cardozo et al. 2008; Powers 2008; Diabetes 2010; Dirice and Kulkarni 2011). The

Figure II-8: Illustration of the autoimmune attack in T1D. Figure extracted from (Pirot, Cardozo et al. 2008).

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environmental causes of T1D include viral infections, dietary factors, vaccination and toxins that can have influence in the disease development (Pirot, Cardozo et al. 2008). Nevertheless, enteroviruses seems to have an important role in the pathogenesis of T1D (Dotta, Censini et al. 2007).

Figure II-8 illustrates some of the most important steps of the immune attack, in the early stage of T1D – insulitis, the antigen presenting cells (APC) migrate to lymph nodes activating CD4+_{helper T-cells (Figure II-8 – A), this stimulate APC cells to produce}

cytokines and nitric oxide (Figure II-8 – B) (Pirot, Cardozo et al. 2008; Dirice and Kulkarni 2011). These cytokines have an effect on endothelial cells inducing chemokines secretion recruiting other immune cells and activating CD8+ cytotoxic T-cells (Figure II-8 – C) (Pirot, Cardozo et al. 2008).

β-cells also secrete chemokines in response to cytokines or due to viral infection recruiting CD8+ cytotoxic T-cells (Figure 8 – D). The Fas interactions (Figure 8 - E) and the perforin system (Figure 8 - F) are used by the CD8+_{cytotoxic T-cells to induce the β-cell}

apoptosis. Some cytokines and their pathways are also involved in the process of T1D (Figure 8 – G, H, I) (Pirot, Cardozo et al. 2008; Dirice and Kulkarni 2011).

5. Type 2 Diabetes (T2D)

An overwhelming number of scientific articles report the high incidence of obesity among patients with type 2 diabetes (T2D), suggesting a direct correlation between obesity and diabetes. However, interestingly most obese individuals do not develop the overt form of the disease. In this context, it is interesting to know that the endocrine pancreas has an amazing plasticity and is able to adapt to different insulin resistant states (e.g., puberty, pregnancy, obesity). Consequently, the pathophysiology of T2D seems to be directly dependent on a previously β-cell dysfunction, probably caused through genetic and/or by β-cell citotoxic effects (Leaby 2010).

5.1. Epidemiology

As mentioned previously, T2D is today a health crisis. It is the seventh leading cause of dead in the US and the total health cost spent in 2007 was 173 billion dollars

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(CDC 2011). To have a better perception of the disease evolution, in 2002 accordingly to Hogan and colleagues (2003), in the U.S., 20.8 million people were affected while in 2010 the number is already 25.8 million (CDC 2011).

In Portugal, the prevalence of T2D in 2009 was 11.7 %, corresponding to 905 thousand patients. In 2009, the costs with the disease were 1.4 billion dollars – 0.7% of the GDP (Diabetes 2010).

In the origin of this outbreak, there is a genetic predisposition and the global shift from a rural living, in which people spent much time of their day performing high demanding duties in terms of energy expenditure, to a modern and sedentary life.

More than 50 years ago, Neel (1962) postulated the existence of metabolic thrifty genes, which represented an evolutionary advantage in times of famine and starvation. However, when the food turns abundant these genes constitute a survival disadvantage and were the responsible for the predisposition to diabetes.

Meanwhile, only 20 years after Neel postulation, diabetes was proved to be a genetic-based disease by the notorious study performed by Barnett and colleagues (1981), in which they have shown full concordance in monozygotic twins.

In contrast with many monogenic forms of diabetes, there was not a high improvement in the understanding of the genetic defects causing T2D until the genome-wide association screens. Specifically the analysis of small nucleotide sequences (SNP´s), which revealed that most of the identified patterns were associated in the β-cell biology, in contrast with insulin signaling or glucose transport systems (Leaby 2010).

5.2. β-cell failure

Insulin resistance and β-cell dysfunction characterize T2D (Leahy 2005). The β-cell insulin secretion capacity and the target tissues insulin sensitivity are directly correlated. Nevertheless, the fact that several high risk patients (i.e. obese) were still normoglycemic shaped a general idea that insulin resistance was the main characteristic of the disease and so, the most important, appearing always before β-cell dysfunction (Martin, Warram et al. 1992; Powers 2008).

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The β-cell function is usually accessed by measuring insulin and glucose levels after an oral glucose tolerance test (OGTT). However, in the past, the OGTT interpretation was based in the 2-hour insulin levels. This caused misinterpretation of the data, because the insulin secretion is biphasic, consisting in a first-phase lasting 30 minutes and then a later second-phase. What is visible in the OGTT data of T2D patients is an impaired first-phase and a greater second-first-phase. Based on the 2-hours insulin levels, the old studies concluded that even insulin resistance was present; this didn´t affect the β - cell function (Leahy 2005; Leaby 2010).

Genetic and environmental factors such as obesity, aging and sedentary lifestyles are important reasons for the development of insulin resistance. Nevertheless, this don´t explain the progression from an insulin resistance state but normoglycemic to a hyperglycemic state (Lillioja, Mott et al. 1993). Therefore, new studies using new techniques started to compare the insulin sensitivity and first-phase insulin secretion (i.e. disposition index) (Weyer, Bogardus et al. 1999). This new data changed the notion around T2D, from an initial point of view where insulin resistance was the main player in the pathophysiology of the disease to a new model in which insulin resistance is an important risk factor, but only a drop in the β-cell function causes an increase in the blood glucose levels (Lillioja, Mott et al. 1993; Leaby 2010).

With the perspective of finding a therapeutic approach for T2D, several possible mechanisms correlated with β-cell dysfunction were studied. Glucose itself is believed to be one of them, since it was reported that a strong gene expression alteration in some β-cell specific genes after exposure high glucose concentrations (Leahy 2005). Specifying the role of glucose in the β-cell dysfunction, Song and collaborators (2003) explored a concept of “β-cell exhaustion” in which the β-cell function is kept after challenging the cells with a high glucose concentration together with an inhibitor of insulin secretion - diazoxide, suggesting that if the β-cell can “rest” their function is maintain despite the glucose levels.

Unger created the concept of lipotoxicity in 1995, defining the effects of the lipids on the β-cell function, in particular their role impairing the glucose-stimulated insulin secretion (GSIS), and in reducing the β-cell mass (Lee, Wang et al. 2001). As mentioned in the topic 3.1.2., insulin is secreted by a membrane depolarization in which the ATP-sensitive K+ channels are important, free fatty acids (FFA´s) may stimulate this channels preventing their closure and so, inducing resistance (Bränström, Aspinwall et al. 2004).

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A considerable number of scientific articles demonstrate the role of FFA´s in inducing oxidative stress by different mechanisms, for example: through the accumulation of ceramides which activate the iNOS (inducible NO synthase) (Corbett, Lancaster et al. 1991); activation of uncoupling protein 2 (UCP2) which decrease the ATP concentration in the β-cell, being important for the insulin secretion (Lameloise, Muzzin et al. 2001; Krauss, Zhang et al. 2003), and finally throughout the activation of caspases by nitric oxide (NO) and free radicals leading to decrease of the β-cell mass (Shimabukuro, Zhou et al. 1998).

The β-cell mass decrease may be very important in the development of T2D, mainly because there are few publications reporting a reduction of the β-cell mass in T2D patients, despite the fact that normally β-cells increase their mass in compensation to insulin resistance. For example, Butler and colleagues (2003) found a 40% decrease in β-cell mass on T2D patients, in conjunction with a 3-fold increase in apoptosis, suggesting that this β-cell mass decrease can cause the earliest hyperglycemia.

Finally, other mechanisms involved in the etiology of β-cell dysfunction were already studied, for example the effect of FFA´s in the expression of GLUT2 (Bollheimer, Skelly et al. 1998) and GPR40 (Steneberg, Rubins et al. 2005) as while an impaired incretin effect, caused by a lower expression of GIP receptors on the β-cells and a decrease in the secretion of GLP-1(Vilsbøll, Krarup et al. 2001; Kulkarni 2010; Leaby 2010).

5.3. Insulin resistance

Insulin resistance is characterized by a diminished capacity to deactivate the liver glucose production in the fasting state and/or an impairment in glucose utilization by insulin-sensitive tissues (i.e. muscle, liver and fat). The pancreas compensates insulin resistance by rising insulin production, which eventually will normalize glucose levels (Dirice and Kulkarni 2011).

The mechanisms responsible for insulin resistance are being investigated since a long time. Concerning to insulin receptor and tyrosine phosphorylation, there is some evidence of a decreased insulin-stimulation of IRS1 tyrosine phosphorylation and insulin receptor activity, but the origin of both alterations seems to be the hyperinsulinemia. The main proposed mechanisms relates first, with the attenuation of the insulin-signaling trough serine phosphorylation of IRS1, and second with degradation of IRS1 (Pederson, Kramer et al. 2001; Gual, Le Marchand-Brustel et al. 2005).

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Other possible mechanism for insulin resistance is the existence of a mitochondrial dysfunction. T2D is associated with obesity and mitochondria have an important role in fuel utilization and energy production, consequently it would be expected a correlation between a defective mitochondria function and the pathophysiology of T2D. In fact there is a strong correlation between impaired mitochondria function and T2D, and this concept would explain the excess triglyceride accumulation and the impairment of insulin-mediated glucose uptake because of the reduced β-oxidation and ATP production, however this relationship needs further investigation (Petersen, Dufour et al. 2004; Patti and Corvera 2010).

Until recently, the importance of adipose tissue in the regulation of glucose metabolism was neglected. Increased adipocyte mass, associated with obesity, is responsible for increased FFA circulating levels which can impair skeletal muscle glucose utilization, promote liver glucose production and as mentioned before, impair β-cell function (Yuan, Konstantopoulos et al. 2001). Adipocytes produce a very broad number of biologic products important to the pathogenic process of T2D, such as, adiponectin (Sheng and Yang 2008), retinol binding protein 4 (Yang, Graham et al. 2005), resistin (Steppan, Bailey et al. 2001) and tumor necrosis factor-α (TNF-α) (Galic, Oakhill et al. 2010). These adipokines regulate body weight, appetite, energy expenditure and insulin sensitivity, being important in T2D etiology.

Finally, insulin’s capacity to suppress liver glucose production fails (gluconeogenesis), resulting in fast hyper-insulinemia which is accompanied by a decrease in glycogen synthesis by the liver in the postprandial state (Bouche, Serdy et al. 2004). Caused by adipose tissue insulin resistance , the flux of FFA from the adipocytes to the liver is high raising the very low density lipoprotein (VLDL) and triglyceride synthesis, which leads to the characteristic dyslipidemia of T2D (Powers 2008).

5.4. Models of insulin resistance

As mentioned previously, T2D is characterized by insulin resistance and impaired insulin resistance. Many variables enter in this equation, turning this pathology in a heterogeneous and heterogenic disease. Many environmental factors can modulate the manifestation of the genotype, subsequently; it is very difficult to scrutinize the mechanisms around the genetics of insulin resistance and β-cell dysfunction in humans.

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For that, investigators have generated transgenic and knockout mice in genes relevant for insulin action and/or insulin secretion (Kahn 2003; Nandi, Kitamura et al. 2004). The next topics, will give a brief review of the three main models of insulin resistance, i) the leptin - defective ob/ob mice; ii) high fat diet mice and, iii) liver-specific insulin receptor knockout mice — LIRKO.

5.4.1. Leptin-defective Ob/Ob mouse

The ob/ob mouse was discovered by chance at the Jackson Laboratories in 1949, the animal has a recessive mutation in the gene responsible for the hormone leptin which is important for the control of appetite (Ingalls, Dickie et al. 1950; Lindström 2007). At four weeks of age, the weight of these animals is already three-fold increased compared with controls. They are hyperglycemic, glucose intolerant, hyperinsulinemic, overweight, hyperphagic, hypometabolic and hypothermic. The fact that their islets have a high insulin release capacity made them an attractive model, but they also have been used as an obesity model as their obesity is characterized by an increased size and number of the adipocytes (Zhang, Proenca et al. 1994; Lindström 2007).

5.4.2. High Fat Diet model (HFD)

The high-fat fed-mouse model of T2D is of the inbred mice strain C57BL/6J, which is commonly used to investigate the disease pathophysiology. In contrast to other strains of mice, like A/J, in which obesity is associated with a moderate glucose intolerance and insulin resistance, the C57BL/6 mice usually show fasting glycaemias greater than 240 mg/dl and blood insulin levels higher than 150 microU/ml (Surwit, Kuhn et al. 1988).

Winzell and Ahrén (2004) characterized the HFD mouse as a model for impaired glucose tolerance test and T2D. HFD body weight, after the first week, was already high, caused by higher food intake and lower metabolic efficiency. Circulating insulin increased gradually and glucose levels increased, in the HFD, after 1 week ,and continued high throughout the all study.

The HFD C57BL/6 mouse model is a good model for glucose intolerance and T2D, however the time needed to induce and mimic the physiologic effect of obesity in the outcome etiology of T2D is a negative aspect.

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5.4.3. Liver-specific Insulin Receptor Knockout (LIRKO)

The liver has a central role controlling glucose homeostasis and is subject to a complex regulation by insulin, substrates and other hormones (Nandi, Kitamura et al. 2004). In an attempt to identify the exact site of insulin resistance leading to a diminish glucose disposal, Brüning and colleagues (1998) created a mouse model in which muscle insulin receptor was knockout (muscle insulin receptor knockout - MIRKO) and Kulkarni and colleagues (1999) inactivated the β-cells insulin receptor (β-cell insulin receptor knockout - BIRKO) using tissue-specific recombination. MIRKO exhibited normal whole-body glucose homeostasis and BIRKO showed defects in glucose-stimulated insulin secretion acute phase.

Figure II-9: LIRKO mice exhibit hyperglycemia,

hyper-insulinemia, glucose intolerance, and insulin resistance. (a) Fed blood glucose concentrations and serum insulin concentration; (b) Intra-peritoneal glucose tolerance test – (IPGTT) (2 g/kg body weight); (c) Insulin tolerance tests (1 U/kg body weight). Results representing the means ± SEM. Figure extracted from (Michael, Kulkarni et al. 2000).