Christian BOITARD, MD
Institut National Circulation, Métabolisme, Nutrition
Service d’Immunologie et Diabétologie, INSERM U561
& Hôtel Dieu, Paris FRANCE

IGIS after a decade of β-cell research: where do we stand today?

by C. Boitard,France

Type 2 diabetes (T2D) is among the most striking examples of the challenges that medicine will face over the coming decade. First, as a highly multigenic disease in which medical research has failed to identify a unique abnormality behind causative β-cell defects, designing efficient therapies will require original strategies that are much more complex by far than the classic identification of a cause and its pharmacologic targeting for a definitive cure. Second, the worldwide epidemic of T2D and geographical variations in its incidence cannot be explained on a genetic basis. What will need to be understood is the interaction between a complex genetic background and environmental factors that have dramatically changed over the last sixty years. We still lack relevant animal models for T2D, and these are crucial for designing new therapeutic strategies to overcome the disease process. We need to delineate the true part of chronic inflammation, as it could pave the way for a new window for therapeutic prevention of the disease. We are all waiting for techniques to quantify β-cell mass in vivo to better understand the natural history of the disease and to open the way for drugs that will restore physiological β-cell mass. Although a defect in β-cell function has now been unequivocally identified as the central cause of T2D development, currently available therapies that restore early β-cell defects, namely the loss of the firstphase insulin response, only do so on a short-term basis. This may be the most complex challenge we have in front of us.

Medicographia. 2011;33:83-89 (see French abstract on page 89)

“A Decade of Islet Research: Implications for Understanding and Treating Type 2 Diabetes” was the focus of the 10th IGIS (International Group on Insulin Secretion) meeting held on 26-29 March, 2009, in St Jean Cap Ferrat, France, with the support of Servier’s unrestricted educational grant. Topics covered by the first 10 symposia provide a summary of the major advances made over the last 10 years both in the field of β-cell research and type 2 diabetes (T2D) (Table I, page 84).1 T2D has risen in prevalence dramatically in the past two generations with dramatic lifestyle and nutritional changes. It is associated with defects in insulin secretion and in the action of insulin on peripheral tissues. Insulin resistance does not lead to diabetes in the absence of defective cells; patients with impaired glucose tolerance or in the early stages of type 2 diabetes invariably show β-cell secretion defects. The disruption of oscillatory insulin secretion and the loss of the first-phase insulin response to glucose occurs in the early stages of T2D, despite the relative enhancement of second-phase secretion, but, ultimately, the evolution toward loss of both first- and second-phase response are characteristic of type 2 diabetes. The IGIS symposia, as major T2D publications have also done, have put β-cell dysfunction and the islet of Langerhans back under the scope in T2D pathophysiology. Indeed, the 1980s and 1990s were times when T2D was regarded as purely a disease of insulin resistance. A striking change has been brought about in the past decade; even the staunchest proponents of insulin resistance agree that T2D does not develop unless cells fail. More importantly, many leading research groups that in the past exclusively worked on insulin action are now including β cells and the islets of Langerhans in the picture.

Genetic background of type 2 diabetes

The completion of the human genome sequence in 20012 is a landmark accomplishment in genomics and genetics. Set as a major goal in the late 1980s, it discovered an unprecedented amount of biological information, opening the way for new research strategies, new understanding of diseases, and “breakthrough” technological developments. Moreover, the availability in 2010 of genome sequences from different individuals is paving the way in the molecular understanding of human diversity, a key feature of survival in all species, but also of disease susceptibility. Identification of well over 106 single nucleotide polymorphisms (SNPs), differing by single base changes that span the whole genome, is providing us with a unique set of genetic tools. Variations in the genome underlie phenotypic variations in monogenic diseases as well susceptibility to or protection from a vast array of complex polygenic disorders. High throughput techniques now allow the routine assessment of up to 500 000 SNPs in large populations.

Table I
Table I. List of IGIS (International Group on Insulin Secretion)
symposia in the last decade.

Genome-wide association studies have confirmed the involvement of T2D susceptibility genes that have previously been identified using the candidate gene approach. They have also come up with a set of new gene variants, most of which impacton β-cell function.3 The risk attached to each individual gene is low. It is multigene association that drives genetic risk. The gene variant with the highest relative risk (≈1.4-1.5, ie, a 40%-50% risk increase) in T2D is transcription factor 7–like 2 (TCF7L2TCF7L2 has now been implicated in key functions that control insulin secretion and glucose metabolism. It controls the secretion of incretins, in particular glucagon-like peptide 1 (GLP-1). Insulin secretion in subjects with the at-risk genotype is also reduced in response to IV glucose and arginine, and not only oral glucose, suggesting a direct role on β cells.4 Unequivocal evidence for common variants involved in T2D also include the E23K variant in the potassium inwardly-rectifying channel, subfamily J, member 11 (KCNJ11) gene, the P12A variant in the peroxisome proliferator-activated receptor gamma (PPARG) gene, and the Wolfram syndrome 1 (WFS1) gene. Rare mutations in all these genes have been reported in rare forms of monogenic diabetes, and two—KCNJ11 that encodes a component of a potassium channel and PPARG that encodes a transcription factor involved in adipocyte differentiation— are the targets of major antidiabetic drugs, sulfonylureas and thiazolidinediones, respectively.3 An FTO gene variant has been found in only one study, but could hardly have been identified in case control studies in which patients and controls were matched for weight, as this gene is associated with obesity.5 Other genes include genes coding: the insulinlike growth factor 2 mRNA-binding protein 2 (IGF2BP2) that binds to a key growth and insulin-signaling molecule, insulinlike growth factor 2 (IGF-2), and is also expressed in pancre-atic islets; and SLC30A8, which codes for a zinc transporter that is selectively expressed in β cells, is a major autoantigen in type 1 diabetes, and is associated with posttransplant diabetes in renal allograft recipients. Other genes variants are listed in Table II. Interestingly, the majority of associated variants (80%) fall outside coding regions.

Table II
Table II. Genes/loci for which variants have been consistently associated
with type 2 diabetes.

Genes 1-17 are loci associated with type 2 diabetes, while genes 18-26 are loci
associated with type 2 diabetes and fasting blood glucose.

Overall, the genetic component to T2D risk is astonishingly low compared with many other common diseases. The sibling relative risk is 3-4 at most for T2D, compared with 15 for type 1 diabetes, 7-10 for bipolar disorder, and 17-35 for Crohn’s disease, but 2-7 for early myocardial infarction and 2.5-3.5 for hypertension. Clinical translation of genetic risk estimates remains uncertain. In both the Malmöe and Botnia studies and the Framingham Offspring study, examination of the impact of up to 18 variants led to a relative risk of 1.12 per risk allele for T2D and allowed the reclassification of only 4.1% patients, which was inversely correlated with age, while a family history of T2D, increased body mass index (BMI) and waist circumference, increased systolic and diastolic blood pressure, and increased alanine aminotransferase, and, to a lesser extent, increased ϒ-glutamyl transferase and triglycerides, current smoking status, and reduced measures of insulin secretion and action, remain the strongest predictors of T2D.6,7 Despite major advances in defining new T2D genes, the limited success of linkage studies has been attributed to the low power of resolution of variants of modest effect and to poor detection of the contribution of rare variants by available genotyping arrays.8 Effects of variants may also depend on the parent from whom they are inherited.9 Limitations of gene variant characterization may also point to the need for studies integrating genetic risk and interactions with the environment.8 Beyond the characterization of gene variants associated with T2D, association studies for diabetes-related quantitative traits in subjects without diabetes have also identified loci that influence fasting glucose levels, fasting insulin, indices of β-cell function (HOMA [homeostatic model assessment]-B) and insulin resistance (HOMA-IR),10 and glucose and insulin responses to oral glucose challenge.11 Finally, several studies have been published in which the response to antidiabetic drugs was dependent on the genetic background of the treated individuals.

Pathophysiology of type 2 diabetes

Disruption of the adaptation of insulin secretion to insulin requirements, especially in response to insulin resistance, as seen in physically inactive obese individuals, leads to T2D.

_ Animal models of type 2 diabetes
This type of multigenic background points to T2D being associated with multiple defects. The genes involved also point toward β-cell defects as being central to T2D development. Monogenic diabetes syndromes, such as maturity onset diabetes of the young, are mostly related with gene mutations that impact β-cell function. In mice, glucose intolerance or diabetes have been reported in multiple models in which the knock-out of key genes in β-cell function, action of insulin on peripheral tissues, control of fat mass, or key biological functions has occurred. With few exceptions, however, the underlying genetic background in which genes are rendered defective has seldom been considered, although it possibly underlies the β-cell defects that lead to diabetes as a failed response to insulin resistance. For example, the db mutation and insulin receptor silencing lead to very different phenotypes depending on the genetic background into which it is introduced. In common mouse strains, diabetes has been elicited with a highly unphysiological high-fat diet. In these models, differential risk is seen as being dependent on the underlying genetic background. However, although many animal models of T2D have now been described,12,13 none of them seems to closely mimic human disease. The Psammo-mys (sand rat) is especially interesting since it clearly identifies the failing interaction between a genome and the environment, as is likely to be the case in human T2D. The sand rat has an essentially vegetarian diet in its natural habitat. Once fed laboratory chow, it becomes insulin resistant and hyperglycemic and eventually is struck by β-cell apoptosis that is irreversible if its diet is not reversed.14

_ The inflammatory component
An important component that links nutrients, increase in visceral adipocyte mass, and insulin resistance is inflammation.15 There is epidemiological evidence that markers of inflammation are predictive of T2D.16 The integration of metabolism and innate immunity through nutrient-sensing pathways, which are shared by pathogen-sensing pathways, trace the role of inflammation in insulin resistance, especially in obesity. Nutrients, ie, free fatty acids, glucose, and amino acids, signal through receptors and pathways that are shared by pathogens and/or cytokines. Macrophages and adipocytes also share many functions. Preadipocytes can transdifferentiate into macrophages. Both macrophages and adipocytes secrete cytokines. Nutrients can directly activate macrophages and adipocytes through common receptors, such as Toll-like receptors (TLRs), which have been shown to sense broad classes of molecular structures common to groups of pathogens. TLRs are central to innate immunity and inflammation. TLR4, a receptor of lipopolysaccharides, and TLR2, a receptor for pathogen lipoproteins, are activated by free fatty acids.17,18 TLR4 knockout mice are partially protected from fat-induced inflammation and insulin resistance. TLR5, a receptor for bacterial flagellin, has been shown to control metabolic pathways through sensing gut microbiota. TLR5 knockout mice exhibit hyperphagia and develop the hallmark features of metabolic syndrome, including hyperlipidemia, hypertension, insulin resistance, and increased adiposity. TLR signaling pathways have also been linked to atherosclerosis in mice.19

Infiltration of visceral adipose tissue by macrophages, and subsequently lymphocytes, is seen in obesity.15,20,21 The flood of free fatty acids and cytokines (eg, tumor necrosis factor ) linked to obesity and the metabolic stress driven by nutrient overload directly impact the action of insulin on the liver. In addition to the production of cytokines and to the overproduction of reactive oxygen species (ROS), many inflammatory signaling pathways that inhibit insulin-receptor signaling are directly triggered by nutrients, such as circulating lipids. The role of endoplasmic reticulum (ER) stress, the consequence of the accumulation of unfolded proteins in the ER, has also been underscored in these processes. Activation of kinases, such as Jun n-terminal kinase (JNK), inhibitor of nuclear factor κB kinase subunit β (IKK-β), extracellular-signal regulated kinase (ERK), ribosomal protein S6 kinase (S6K), mammalian target of rapamycin (mTOR), protein kinase C, and glycogen synthase kinase 3β, through inflammation leads to serine phosphorylation of insulin receptor substrate 1 (IRS-1), reducing both tyrosine phosphorylation of IRS-1 in response to insulin, the ability of IRS-1 to associate with the insulin receptor, and downstream signaling by insulin. The activation of macrophages, via the sensing of fatty acids by TLR4 leading to the production of proinflammatory cytokines and activation of TLRs expressed by adipocytes, can result in nuclear factor κB–driven proinflammatory responses.

_ β-Cell mass in type 2 diabetes
While a defect in β-cell function is now considered central to the T2D process, whether it is related to a decrease in β-cell mass or not remains an open issue. The lack of in vivo techniques to quantify β-cell mass has hampered its study in patients with various stages of T2D development. Currently, all studies rely on immunocytochemical techniques to quantify β-cell mass, in most cases on autopsy material. The strongest reductions reported in some publications remain largely above the minimal threshold that allows accurate insulin secretion and glycemic control, as shown by studies following partial pancreatectomy.22 Most studies have shown at least a moderate reduction in β-cell volume and/or β-cell mass in T2D patients compared with normal controls. One study has shown a reduction of up to 63% in β-cell volume in obese T2D patients compared with nondiabetic obese subjects, and a 41% reduction in nonobese T2D patients, but it did not assess β-cell mass. A 40% reduction was observed in impaired fasting glucose patients. The frequency of β-cell apoptosis increased 10-fold in lean T2D patients and 3-fold in obese T2D patients in the same study.23 A study that assessed β-cell mass found that it was reduced by 41% and 38% in T2D patients with a BMI <25 and 26-40, respectively, compared with nondiabetic controls. One of the most striking features in this study, as in previous studies, is the marked intersubject variability within each group, in the controls as well as the T2D patients, and, as a consequence, the large overlap between the nondiabetic and T2D groups. Pancreatic insulin concentrations were 30% lower in T2D patients than in controls. β-Cell mass did not correlate with age at diagnosis, but it did decrease with duration of clinical diabetes (24% and 54% reduction in subjects with <5 and >15 years of overt diabetes, respectively).24 The decrease with diabetes duration was postulated to be a consequence, rather than a cause, of T2D. Again, the small difference in β-cell mass observed in this study within 5 years of diabetes onset was capable of causing diabetes in the absence of β-cell dysfunction.

_ β-Cell defects in type 2 diabetes
As reduction in β-cell mass does not directly explain defective insulin secretion, a major focus of ongoing research is the clarification of mechanisms of β-cell failure in T2D.25 Early mechanisms of β-cell failure leading to T2D do not necessarily correspond with mechanisms of progressive silencing of cells and reduction of β-cell mass seen throughout the development of the disease once diagnosed. T2D subjects show early alteration of plasma insulin levels, with both quantitative and qualitative changes. Qualitative changes include impaired acute insulin response to glucose, attenuation of pulsatile insulin concentration, and exaggerated proinsulin-to-insulin ratio. These abnormalities have tentatively been attributed to a loss of the first-phase insulin response to glucose and of the oscillations during the second phase of insulin secretion. Defects in proinsulin processing at the β-cell and islet levels have been witnessed. However, the mechanisms of the defects of stimulussecretion coupling in the cells of T2D subjects still remain unidentified.26

The highly multigenic form of T2D points to β cells as the driving force in diabetes. Multiple functional pathways are involved, including pathways controlling β-cell development, growth, survival, and response to glucose, but also those controlling the response to a wide variety of secretagogues, each of which imprints a subphenotype that by itself does not drive β-cell failure. It is their association that explains the progressive demise of β cells through interactions with a suboptimal environment. In most individuals, β cells adapt to high metabolic demand and maintain normoglycemia at the price of increased insulin secretion and hyperinsulinemia. This implies increased β-cell function and increased β-cell mass. A β-cell mass increase is indeed seen with increasing BMI in both nondiabetic subjects and T2D subjects in studies that quantified β-cell mass.23,24 It is postulated that, in genetically susceptible individuals, defective adaptation of β cells beyond a threshold that is likely to vary between individuals leads to the development of impaired tolerance to glucose and T2D. Early factors that are often present before the onset of T2D, including hyperlipidemia and low-grade inflammation, contribute to the initiation of impaired glucose tolerance, in addition to chronic overstimulation of insulin secretion.

Pancreatic β cells exposed to increased metabolic demand display modified gene expression profiles and altered function, survival, and growth that are likely to contribute to the slow deterioration of functional β-cell mass that is characteristic of T2D. In vitro data obtained by exposing islets to high glucose concentrations show an adaptive response, including increased glucose sensitivity, which seems detrimental in the long term (glucotoxicity). Similar observations have been made by exposing islets to high free fatty acid concentrations (lipotoxicity). Pancreases obtained from T2D patients show altered gene expression that affects multiple β-cell pathways.27 While glucose-stimulated insulin secretion by T2D islets is profoundly altered, secretion stimulated by arginine and by sulfonylureas is partially conserved. These defects are accompanied by reduced mRNA expression of glucose transporter 1 (GLUT-1), GLUT-2, and glucokinase, and by diminished glucose oxidation. In addition, 5′ adenosine monophosphate– activated protein kinase (AMPK) activation is reduced. The expression of insulin decreases, while that of pancreatic duodenal homeobox 1 (PDX-1) and forkhead box protein O1 (FOXO-1) increases. Nitrotyrosine and 8-hydroxy-2-deoxyguanosine concentrations point to oxidative stress within the islets. These modifications may be at least partially reversible, a key issue in T2D.27 The physiological role of cytokines, some of them produced by β cells, such as interleukin 1, remains elusive. Overexposure of the islets or local overproduction of these cytokines leads to oxidative stress.28 The low levels of radical scavengers characteristic of β cells is one factor that may explain the high sensitivity of β cells to oxidative stress.

Furthermore, many models have shown that markers of ER stress correlate with β-cell failure in experimental models. In humans, this occurs in patients who carry mutations of the insulin gene that impact proinsulin processing throughout the insulin secretion process.29 Again, ER stress is an adaptive response of cells exposed to an accumulation of misfolded proteins, also known as the “unfolded-protein response.” It leads to an increase in the transcription of genes that activate genes that are crucial for secretory functions, cause transcriptional arrest of most proteins, and induce genes that restore the proper folding of proteins. In the long term and when overloaded, it leads to cell apoptosis.

In many regards, the pathological β-cell failure seen in T2D is an age-related process. Many aspects of βcell physiology that directly impact aging have been underscored. The relationship between the progressive failure of cells and mitochondria in T2D cannot be ignored. Apart from the many reports citing the role of mitochondrial mutations or defects that lead to β-cell failure and diabetes,30 a 50% decrease in mitochondrial DNA (mtDNA) copy-number in skeletal muscle and peripheral blood cells of T2D patients has been observed.

The diabetic state is generally characterized by accelerated tissue aging, which is perhaps related to mitochondrial dysfunction. Among modifications that may be related to “mitochondrial aging” in the form of point mutations in mtDNA, there is an age-related increase in the production of ROS, with a concurrent weakening of the defense mechanisms against these free radicals. This deleterious process is amplified in β cells due to their low level of natural enzymatic defenses, ie, reactive oxygen species scavengers (catalase and superoxide dismutase). ROS may play a role in the impairment of glucoseinduced insulin secretion seen both in aging and in T2D. The direct study of diabetic islets from T2D patients shows parallel events: reduced insulin response to glucose, low adenosine triphosphate (ATP) levels, a low ATP/ADP (adenosine diphosphate) ratio, impaired hyperpolarization of the mitochondrial membrane, and increased expression of mitochondrial uncoupling protein 2 (UCP-2), complex I, and complex V of the respiratory chain. Morphology shows higher mitochondrial density volume, despite normal numbers of mitochondria in T2D islets.30


The human genome sequence provides an unprecedented catalogue of markers and genes to fill the gap between disease phenotypes/subphenotypes or identification of the loci associated with diabetes and the characterization of genes involved. We can now foresee the integration of gene products into metabolic networks with the global perspective of comprehensively viewing cell and organ function on a genomewide basis. This will require combining genetic approaches with technologies to characterize gene and protein expression. New advances will be required to apply gene expression to large scale studies and allow computational integration of the data generated. The perspectives of genomics have been examined from the point of view of medical genetics. Other avenues will open the field of pharmacogenetics to diabetes. Dramatic examples of pharmacogenetics’ power to predict the action of drugs and their adverse effects have long been reported. Availability of the genome sequence will allow the systematic search for gene variants that influence the effects of drugs. The forthcoming challenge is to design therapies that can correct the highly multigenic state attributed to the T2D β cell. Some of the currently available therapies restore functional features primarily affected in the early stages of T2D development, for instance, the loss of first-phase insulin release, but they only do so on a short-term basis. _

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Keywords: diabetes; insulin; β cell; insulinoresistance; genome