**1. Introduction**

304 Type 1 Diabetes – Complications, Pathogenesis, and Alternative Treatments

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Type 1 diabetes is a chronic metabolic disease whose aetiology and pathogenesis remain not completely understood. Current criteria for the diagnosis of diabetes are: 1) haemoglobin A1c ≥ 6.5% (assayed using a method that is certified by the National Glycohemoglobin Standardization Program, NGSP, and standardised or traceable to the Diabetes Control and Complications Trial, DCCT, reference assay), 2) fasting plasma glucose (FPG) ≥ 126 mg/dl, 3) 2-hour plasma glucose ≥ 200 mg/dl during an oral glucose tolerance test (OGTT, 75 g), 4) a random plasma glucose ≥ 200 mg/dl (American Diabetes Association, 2011). The classification of diabetes includes: type 1 diabetes, type 2 diabetes, other specific types of diabetes due to other causes, and gestational diabetes mellitus. Type 2 diabetes, which is usually associated with obesity and older age, results from insulin resistance and progressive failure of pancreatic beta-cell function. Type 1 diabetes, which has usually an abrupt onset in younger people, is an organ-specific autoimmune disease characterised by absolute insulin deficiency resulting from beta-cell destruction. However, autoimmunity may not be the primary cause: environmental triggers are believed to precipitate type 1 diabetes in genetically susceptible individuals (van Belle et al., 2011). The overall incidence of type 1 diabetes is increasing; the majority of the increase is observed in the youngest age group, which also appeared to be the heaviest (Evertsen et al., 2009). Indeed, the accelerator hypothesis (Wilkin, 2009) suggests that type 1 and type 2 diabetes are the same disorder of insulin resistance set against different genetic backgrounds. Three processes could variably accelerate the loss of beta cells through apoptosis: constitution, insulin resistance, and autoimmunity. None of these accelerators leads to diabetes without excess weight, which causes an increase in insulin resistance and, thus, the weakening of glucose control. In turn, the glucotoxicity accelerates beta-cell apoptosis directly and by inducing beta-cell immunogens and autoimmunity in genetically predisposed subjects. Insulitis is commonly observed in recent-onset type 1 diabetes, but it does not uniformly affect all insulincontaining islets (differences in islet function?). It has been suggested that under increased insulin demand (puberty, adolescence, high sugar intake, etc.) a population of islets may be more prone to dysfunction or death, thereby attracting antigen presenting cells and

The Enlarging List of Phenotypic Characteristics That

zinc transporter 8 (ZnT8A) (Table 2).

**2. Identifying individuals at risk for type 1 diabetes** 

Might Allow the Clinical Identification of Families at Risk for Type 1 Diabetes 307

In Europe, the number of adults with diabetes was expected to reach 55.2 million (8.5% of the adult population) in 2010; about 112,000 children and adolescents were estimated to

Most diabetic cases are complex diseases resulting from interactions between genetic and environmental determinants in genetically predisposed individuals. Empirical evidence suggests a architecture of many genetic loci with many variants of small effect (Wray & Goddard, 2010). Genome-wide association studies have suggested that the majority of susceptible loci have small contributions to phenotypic variation and therefore there should be a large number of susceptibility loci involved in the genetic basis of complex diseases (consistent with the polygenic model). Moreover, the differentiation of sporadic and familial cases has implied that most complex diseases are genetically heterogeneous. Family history has a high positive predictive value, but a low negative predictive value. Yang et al. (2010) have shown that 1) the proportion of sporadic cases depends on disease prevalence and heritability of the underlying liability scale, and 2) a large proportion of sporadic cases is expected under the polygenic model due to the low prevalence rates of common complex genetic diseases. Thus, the causal mechanisms cannot be inferred from the observed proportion of sporadic cases alone. The prediction of disease risk to relatives from many risk loci or markers requires a model that combines the effects of these loci. The constrained multiplicative, Odds and Probit models fitted data on risk to relatives, but it is difficult to distinguish between them until genetic variants that explain the majority of the known genetic variance are identified (Wray & Goddard, 2010). Hence, genetic risk modelling to

have type 1 diabetes mellitus (http://www.diabetesatlas.org/content/europe).

derive prediction of individual risk and risk to relatives are still difficult to reconcile.

In most individuals with autoimmune type 1 diabetes, beta cell destruction is a chronically progressive and very slow process that starts long before overt disease. During this "silent" phase, autoantibodies are produced and self-reactive activated lymphocytes infiltrate the islets of Langerhans (Rowe et al., 2011). Autoantibodies that target self-antigens in the insulin-secreting beta cells of the pancreas include: islet cell autoantibodies (ICA), insulinoma-associated antigen-2 antibodies (IA-2A), antibodies against the related antigen IA-2 beta (IA-2), insulin autoantibodies (IAA), autoantibodies to the 65kDa isoform of glutamic acid decarboxylase 65 (GADA), and the recently identified autoantibodies to the

Islet autoantibodies are potent tools for the prediction of type 1 diabetes and are the basis for recruitment in prevention trials and immunointervention trials. In the general childhood population in Finland, one-time screening for GADA and IA-2A was capable of identifying about 60% of those individuals who will develop type 1 diabetes over the subsequent 27 years; both positive and negative seroconversions occurred over time reflecting a dynamic process of beta cell autoimmunity, but positivity for at least two diabetes-associated autoantibodies represented in most cases a point of no return (Knip et al., 2010). So far, however, the place of autoantibody-based risk assessment in routine clinical practice is limited because no proven therapeutic interventions is available for people at high risk of progression to type 1 diabetes. Until therapies modulating the disease process become available, the benefit to individual patients is questionable - awareness of risk is rather useless or even stressful - and diabetes antibody testing does not yet have a role in clinical care (Bingley, 2010). It is considered likely that islet-related autoantibodies are not directly pathogenetic, whereas autoreactive CD4 and CD8 T cells mediate beta cell damage.

promoting insulitis in susceptible individuals (Rowe et al., 2011). In a genome-wide association study, 41 distinct genomic locations provided evidence for association with type 1 diabetes in the meta-analysis (Barrett et al., 2009). The Type 1 Diabetes Genetics Consortium (T1DGC) has recruited families with at least two siblings who have type 1 diabetes in order to identify genes that determine an individual's risk of type 1 diabetes. T1DBase is the web-based resource focused on the genetics and genomics of type 1 diabetes susceptibility (https://www.t1dgc.org) that provides the updated table of human loci associated with type 1 diabetes (Table 1).


(from: http://t1dbase.org/page/PosterView/display/poster\_id/386)

Table 1. Human loci associated with type 1 diabetes.

With regards to the causative environmental triggers that have been implicated in the pathogenesis of type 1 diabetes, they have been recently reviewed (van Belle et al., 2011; Vehik & Dabelea, 2011) and include particularly viral infections, gut microbic flora and other bacteria, early life feeding patterns, wheat proteins, and vitamin D.
