Validity of animal models of type 1 diabetes, and strategies to enhance their utility in translational research.

European Journal of Pharmacology ∎ (∎∎∎∎) ∎∎∎–∎∎∎

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European Journal of Pharmacology journal homepage: www.elsevier.com/locate/ejphar

Validity of animal models of type 1 diabetes, and strategies to enhance their utility in translational research Melanie L. Graham a,b,n, Henk-Jan Schuurman c a

University of Minnesota, Department of Surgery, St. Paul, MN, USA University of Minnesota, Veterinary Population Medicine Department, St. Paul, MN, USA c SchuBiomed Consultancy BV, Utrecht, The Netherlands b

art ic l e i nf o

a b s t r a c t

Article history: Received 28 December 2014 Received in revised form 15 January 2015 Accepted 9 February 2015

Type 1 diabetes currently affects 20–40 million people worldwide. Insulin treatment is standard, but a majority of patients still experience glycemic instability and associated comorbidity: there is an unmet medical need for novel therapeutics. Animal models have been indispensable in testing innovative medicinal approaches since the early testing of insulin in dogs almost a century ago. Models include mainly rodents with spontaneous diabetes, or rodents and nonhuman primates in which diabetes is induced by chemicals that are toxic to insulin-producing pancreatic β-cells, or by pancreatectomy. To a less extent models in pigs are used. Rodent models have shown value in studies on pathogenesis and disease prevention, while models in nonhuman primates have translational value in testing β-cell replacement products and immunosuppressives to prevent rejection. Evidently, for many immunosuppressives this validation follows from the close similarity in immune function. Gene therapy approaches are being tested in both rodents and nonhuman primates. We present an overview of models used to answer various research questions, with particular focus on their translational value. This includes a consideration of divergence between the animal model and the clinical condition, and a consideration of the species and model difference in pathogenesis, especially the induction of the diabetic state. Careful attention should be given to managing diabetic animals: outcome measures in the model are highly stress-sensitive and parameters that have potential for confounding should be addressed, i.e., environment, metabolic management, and handling. This review concludes with a few recommendations on how to make animal models more clinical-like. & 2015 Elsevier B.V. All rights reserved.

Keywords: Animal models Type 1 diabetes Cell therapy Immunosuppressives Rodent Nonhuman primate

1. Introduction, type 1 diabetes According to the Diabetes Atlas (International Diabetes Federation, 2013), 8–10% of the world population between 20 and 80 years suffers from diabetes. This amounts to 380 million people in 2013, growing to 590 million in 2035. In this population, 5–10% are type 1 diabetic (T1D) patients, i.e., the world population of T1D patients in 2013 is estimated at about 20–40 million people. The rise in diabetes about equally affects type 1 and type 2 diabetes, so that diabetes is presently among the major health conditions affecting the global population with increasing morbidity and mortality (Murray and Lopez, 2013). T1D is a complex multifactorial disease involving multiple genetic factors of susceptibility in combination with an environmental trigger that is not fully understood (Kyvik et al., 1995; Thomson et al., 1988; Tisch and McDevitt, 1996). Disease results n Corresponding author at: University of Minnesota, Animal Science/Veterinary Medicine 295, 1988 Fitch Avenue, St. Paul, MN 55108, USA. Tel.: þ 1 612 624 0192. E-mail addresses: [email protected] (M.L. Graham), [email protected] (H.-J. Schuurman).

from the subsequent autoimmune destruction of pancreatic β-cells and eventual total loss of endogenous insulin supply. Treatment of T1D patients requires frequent monitoring of blood glucose levels and lifelong exogenous insulin administration. Blood glucose fluctuations and impaired glycemic control inherent to exogenous insulin administration is associated with severe complications in the long term (Jacobson et al., 2013). Intensive insulin therapy (e.g., insulin pump therapy) reduces the risk of developing these diabetes-related complications but increases the risk of severe hypoglycaemia; relatively few patients are compliant with such rigorous protocols (DCCT, 1993; Davies et al., 2013; Wang et al., 1993). Thus, there is an unmet medical need for proper glucose control in this disease indication. New treatments are urgently needed and research spans preventative, curative, and complication-targeting therapies.

2. Modeling type 1 diabetes Historically and at present, the role of animals in diabetes research is regarded with the greatest respect, having held a

http://dx.doi.org/10.1016/j.ejphar.2015.02.054 0014-2999/& 2015 Elsevier B.V. All rights reserved.

Please cite this article as: Graham, M.L., Schuurman, H.-J., Validity of animal models of type 1 diabetes, and strategies to enhance their utility in translational research. Eur J Pharmacol (2015), http://dx.doi.org/10.1016/j.ejphar.2015.02.054i

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M.L. Graham, H.-J. Schuurman / European Journal of Pharmacology ∎ (∎∎∎∎) ∎∎∎–∎∎∎

central role in understanding pathophysiologic mechanisms of the diabetic state and its complications, and the successful interventions that in turn translated into therapeutic approaches for patients. Intervention studies started with rabbits and dogs by Banting and Best in the 1920s, resulting in perhaps one of the most well-known medical advances resulting from animal research—the discovery of insulin as a therapeutic (Bliss, 2000). Almost a century has passed since initial insulin trials in animals before important advances have been made in in vitro methodology and in silico computational models, in attempts to reduce our reliance on animal models: these attempts especially focused on predicting metabolic response (Boroujerdi et al., 1995; Kovatchev et al., 2009; Li et al., 2013; Magni et al., 2007; Vincent et al., 2005). However, presently these methods are somewhat limited in their application because there are no in vitro or computational methods that mimic the complex multifactorial state of diabetes onset or the interplay of a fully competent immune system in humans. Moreover, since culture methods often rely on proper sourcing of animal cells, it is not clear that reduction in animal use is fully realizable.

There are a number of aspects to be considered in the use of animals for diabetes research (Fig. 1). Starting at the top, the size of the disease population should be addressed. Evidently there is a strong potential for benefit, considering the significant percentage of the population affected by diabetes or being at risk for developing diabetes. Next, an assessment of research relevant to the health affecters is useful to categorize research areas and questions-to-answer so that a proper selection of the model can be made. In the absence of non-animal alternatives, animal models are generally categorized with respect to the research question. Fig. 1 demonstrates how animal models can overlap in studying treatments. Thus, it is necessary to fully understand the research question in detail, in order to select the lowest representative phylogenetic species that appreciates the important aspects of validity. Treatments may target symptoms or modify the disease process, or both, and also produce off-target effects. Depending on the outcome of interest, more emphasis may be placed on models that mimic the manifestation of symptoms in the clinical condition (face validity), underlying biological similarities (construct validity), or both (McGonigle and Ruggeri, 2014).

Fig. 1. Use of animals in diabetes research.



Ultimately the track record of a model to generate a similar response to the clinical situation (predictive validity) enables to decide on its usefulness and limitations. Nowadays mainly rodents and nonhuman primates (NHPs) are used to study immune interventions and novel strategies to replace the dysfunctional insulin-producing β-cells in the pancreas using gene- or cell-based therapies: occasionally pigs are used (Fig. 1, Table 1). Rodent models of spontaneous type 1 diabetes (Non-Obese Diabetic or NOD mice; BioBreeding or BB rats, also called BioBreeding Diabetes Prone BB-DP rats) and experimentally-induced diabetes (e.g., β-cell cytotoxic drugs like alloxan or streptozotocin, or pancreatectomy which is not usually done in rodents) are commonly applied, also in studies on prevention, immunologic mechanisms, and metabolic function (Van Belle et al., 2009). Pigs are primarily used to model type 2 diabetes and the mechanisms underlying dyslipidemia and atherosclerosis (Fricker, 2001; Gerrity et al., 2001), and also the effects of dietary interventions owing to closer similarity to humans in food intake patterns and metabolism (Koopmans et al., 2006, 2011). Pigs with experimentally-induced diabetes are used to model the T1D state, though less frequently (Grüßner et al., 1993; Larsen and Rolin, 2004). NHPs with experimentally-induced diabetes are preferentially used in translational safety and efficacy studies addressing insulin replacement strategies using gene- or cell-based therapies.

3. Modeling of type 1 diabetes prevention Studying the development of diabetes in humans is particularly challenging owing to the almost complete absence of symptoms until overt disease, although quite some progress has been made in clinicopathologic long-term follow-up studies in speciallyselected human cohorts that are in a presumed prediabetic state (Åkerman et al., 2013; Maahs et al., 2010; Rydén and Faresjö, 2013; Smith et al., 2014; Vehik et al., 2013). Therefore one objective is to detect the effector combination of, e.g., genetic background and environmental factors that triggers disease. Rodent models that ‘spontaneously’ develop diabetes have central importance in studying the pathophysiology of T1D. Most well-characterized are the NOD mouse and the BB-DP rat (Anderson and Bluestone, 2005; Chappel and Chappel, 1983; Lampeter et al., 1989; Leiter et al., 1987; Like et al., 1982; Thayer et al., 2010). These models have provided the foundation for understanding the dysregulation of immune cells in loss of self-tolerance to the pancreatic β-cell (Cheţa, 1998;Wong and Janeway, 1999). The BB diabetes-resistant (BB-DR) rat has also been used in combination with Kilham Rat Virus to model a viral infection eliciting an autoimmune response by the mechanism of breaking tolerance towards islet antigens (Guberski et al., 1991). Though the mechanism is not perfectly clear, it is a highly relevant model considering that several viruses have been linked with the development of T1D in humans (Jun and Yoon, 2001). Transgenic and knockout technology served to generate animals with specific expression of molecules or receptors, so that mouse models became available to study specific pathways of interest in diabetes development. This approach has been tremendously useful in modeling fundamental aspects of disease pathogenesis (Christopher et al., 2010; Rosmalen et al., 2000).

4. Models for

β-cell replacement therapy

Cell-based therapy, i.e., replacement of the defective insulinproducing pancreatic β-cells generally described as islet transplantation, is one approach that has shown remarkable promise in the clinic in restoring normoglycemia and reducing long-term diabetes complications such as retinopathy, nephropathy,

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neuropathy and peripheral vascular disease (Barton et al., 2012; Bassi and Fiorina, 2011; Cure et al., 2008; Figliuzzi et al., 2013; Thompson et al., 2011; Warnock et al., 2008). The clinical introduction followed studies on islet allotransplantation in a rat model and then in a rhesus macaque model providing successful proofof-concept data (Ballinger et al., 1972; Ricordi et al., 1992b; Scharp et al., 1975, 1990). Following these seminal studies, allotransplantation studies in NHPs have provided an excellent example of combined efficacy/safety studies with a high translational value so that these could properly be interpreted with respect to the clinical situation. Substantial improvements in graft survival and function have been realized under the cover of immunosuppressive regimens (efficacy) and the effect of these regimens on the recipient (tolerability/safety). One example where the model can be credited was the identification of islet-toxic effects of calcineurin inhibitors with concordant clinical data, and another example with similar credits is the demonstration of effective calcineurin inhibitor-sparing protocols that subsequently developed in effective protocols in the clinic (Adams et al., 2002; Alejandro et al., 2008; Berney et al., 2004; Chandrasekar and Mukherjee, 1988; Larsen et al., 2005; Posselt et al., 2010; Ricordi et al., 1991, 1992a; Vincenti et al., 2005). Also in-vivo product testing in the immunodeficient mouse model with spontaneous or induced diabetes (e.g., nude, SCID or beige) is used as a potency assay for pharmacologic activity, amongst others used in centers participating in the Clinical Islet Transplantation consortium (DAIT, NIAID, NIH, 2008). In the situation of transplantation, the primary outcome measures are generally related to metabolic status (restoration of normoglycemia or near-normoglycemia and insulin secretion) and immunoprotection of the graft. An induced status of insulindependent diabetes, either surgical induction by pancreatectomy or chemical induction by the β-cell-toxic nitrosourea drug streptozotocin (STZ), is mainly used in animal models of islet transplantation. Induction protocols are designed so to eliminate endogenous insulin secretion by destroying β-cells, so that efficacy of the intended therapy can be evaluated from a ‘zero’ baseline in which there is only exogenous insulin supply. Chemical induction has the advantage that it can be used with various strains of rodents and also large animals: however, STZ protocols using the effective single high-dose have potential for renal- and hepato-toxicity (Carney et al., 1979; Deeds et al., 2011; Graham et al., 2011b, 2011c, 2012a; Inoue et al., 1994; Junod et al., 1969; Kiesel and Kolb, 1982; Koulmanda et al., 2003; Leiter, 1982; Lenzen, 2008; Palm et al., 2004; Rood et al., 2006; Shibata et al., 2002; Wei et al., 2011; Wu et al., 2009). Multiple lowdose infusions have been used in small and large animals to provoke an immune response against islets in an attempt to more closely mimic the autoimmune process in patients (Kantwerk‐ Funke et al., 1991; Rossini et al., 1977; Wei et al., 2011). Surgical induction by total pancreatectomy is sometimes used to excise βcells but this procedure also eliminates the exocrine function provided by the pancreas with inherent gastro-intestinal related side effects (Yeo et al., 1997). In addition, total pancreatectomy requires a major surgery with its intrinsic adverse effects such as malabsorption syndrome leading to body weight loss, and with a substantial postoperative recovery period that requires extensive analgesic management. The existing shortage of human donor pancreases limits the number of patients that can benefit from islet allograft transplantation. Therefore, other sources of islet cells are being investigated, e.g., porcine islet cells, stem cells (Cardona et al., 2006; Dufrane et al., 2006; Hering et al., 2006; Pagliuca et al., 2014; Rezania et al., 2014; Van der Windt et al., 2009; Yamada et al., 2014), since at least a similar health economic benefit is expected and patient populations are similar to those presently eligible for allo-islet


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Model

Induction mechanism

Clinical features

Utility of the model and advantages

Insulitis Ketoacidosis Immune functional similarity NODb Spontaneous autoimmune Y mouse BB-DP ratb

Yd

þþ (þ þ þ)

Limitations

Translational Value

Outbred Functional Human outcome biological measuresc crossreactivity –

N

Few

humanized

Understanding mechanisms of T1D Treatments that may prevent βcell death

Treatments that may manipulate

Disease incidence highly variable

autoimmunity

Can be used to screen many interventions

Low cost, large sample size Humanized strains can more

Low/moderate

between centers, affecting interpretation Gender biased disease incidence in NOD Autoantigenic target epitope variability from the clinical situation, discordant biomarkers Leukocyte subset variability from the clinical situation

closely approximate auto/allo immunity expected in the clinical situation Rodent

Chemical induction (high- Y dose STZ,multiple lowdose STZb, or alloxan)

Y

þ ( þ þ þ)

-

Ne

Few

humanized

Transplantation/β-cell replacement Gene therapy Treatments that may prevent βcell death

Low cost, large sample size Humanized strains can more closely approximate auto/allo immunity expected in the clinical situation AKITA Mousef

Genetically induced

Y

Y

þ ( þ þ þ)

-

N

Few

humanized

Modeling diabetic nephropathy,

Rodent

Virally inducedg

Y

Y

þ ( þ þ þ)

-

N

Few

humanized

Establish potential role of viruses

Pig

Surgical (pancreatectomy) or chemical (high-dose STZ,multiple low-dose STZb)

Y

Y

þþ

-

Y

Y

renal phenotype Treatments that may prevent endoplasmic reticulum stress Low cost, large sample size Humanized strains can more closely approximate auto/allo immunity expected in the clinical situation

in the development of T1D Low cost, large sample size Humanized strains can more closely approximate auto/allo immunity expected in the clinical situation

Transplantation/ β-cell

replacement Gene therapy Treatments that may prevent βcell death Monitoring parallel to a phase 1/ 2 trial

Homologues required to mimic clinical

Leukocyte subset variability from the

Low/moderate

immunosuppression may have different PK/PD Lack of immune memory is more permissive in the situation of tolerance Leukocyte subset variability from the clinical situation Lacks the terminal Gal epitope

Low/moderate

clinical situation Limited lifespan

Leukocyte subset variability from the clinical Low/moderate situation

Moderate cost, medium sample size Requires a high level of model technical expertise

Cannot model recurrent autoimmunity Lacks the terminal Gal epitope

Moderate



Table 1 Animal models for type 1 diabetes: relationship to the clinical situationa.

Adapted from King (2012), Roep et al. (2004) and Thayer et al. (2010). BB-DP - biobreeding diabetes prone; STZ—streptozotocin; NHP—nonhuman primate; NOD—nonobese diabetic. c Ability to monitor animals in ways that parallel patient management (e.g., metabolic testing, physicals, hematology, chemistry). d Ketoacidosis is mild until the late stage in NOD mice. e Mostly inbred mice used, but outbred strains are also available for use in chemically induced models. f Data from Araki et al. (2003) and Chang and Gurley (2012). g Coxsackie B virus, Encephalomyocarditis virus, Kilham rat virus, Lymphocytic choriomeningitis virus under insulin promoter. h Data from Garkavenko et al. (2008). b

model technical expertise

Cannot model recurrent autoimmunity Lack receptor for Porcine Endogenous

cell death Monitoring parallel to a phase1/2 clinical trial Targeted immunosuppression with human directed biologics (e.g., monoclonal antibodies, recombinant proteins) Naturally existing anti-Gal antibodies

Retrovirus type A, hence not suitable to evaluate porcine endogenous retrovirus transmissionh

a

NHPb

Surgical (pancreatectomy) or chemical (high-dose STZb, multiple low-dose STZ)

Y

Y

þþþþ

þ

Y

Y

Transplantation/β-cell replacement Gene therapy Treatments that may prevent β-

High cost, low sample size Requires a very high level of specialized

High


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transplantation (Beckwith et al., 2012; O’Connell, 2009); however, extensive safety and efficacy testing are indicated before translation into the patient becomes an option (Cooper and Casu, 2009). Many immunosuppressive modalities in combination with various β-cell xenograft products are tested first in rodents offering a ‘soft filter’ of efficacy: but, these models have limited value as the situation in the rodent does not mimic the complexity of the human immune system. On the other hand, the NHP model is used to provide a higher level of stringency because the immune system in an NHP is essentially similar to that in humans so that the outcome of efficacy studies on immunosuppressive regimens is highly predictive of the human situation (Gaur, 2004; Haanstra and Jonker, 2008; Kirk, 1999; Schuurman, 2008). Note, that most human-directed biologicals show cross-reactivity to NHPs and immune monitoring can be performed like is done in humans (Chapman et al., 2007). Gene therapy is another innovative strategy of more recent date aimed to restore endogenous insulin production by way of reprogramming existing cell types. Most work thus far has been performed in rodents to demonstrate proof-of-concept that proinsulin might be synthesized by a non-β-cell and converted to insulin (Banga et al., 2012; Chen et al., 2000; Lee et al., 2000, 2013b; Zhou et al., 2008). As these therapeutic approaches move beyond basal insulin release to a more glucose-sensitive fully responsive ‘β-cells’ gene therapy products, these products require testing in well-characterized animal models to enable a full assessment of the metabolic state in a similar situation as in the clinical condition (Halban et al., 2001). Also, in the situation where immunosuppression is required in combination with a gene therapy approach, some of the same lessons from animal models in transplantation will drive model selection. For example, certain adeno-associated viruses that are favored for their capability to induce long-term gene expression are affected in their efficiency of transgene expression by the immune response: this is because humans, and NHPs, often exhibit naturally-existing antibodies. The rodent model may be more permissive regarding efficiency of transgene expression owing to inbred specific pathogen-free models. Likewise, the species specificity of certain vectors may play a role in transduction (Nemerow, 2000). Viral vectors must therefore be rigorously evaluated for safety in a clinically relevant model regarding immune response. NHPs have already demonstrated predictive relevance in this respect in the reverse translation approach: this was shown in correctly modeling a fatal immune reaction in a patient who participated in a gene therapy trial for ornithine transcarbamylase deficiency (Stephenson, 2001).

5. Enhancing the predictive value of animal models of T1D As outlined above, T1D animal models have the advantage of being well-established, and most are characterized and defined in detail. But, there are also unique challenges presented by the state of disease in the model. No single model will exactly replicate the human situation: therefore, the selection of the most appropriate model or combination of models starts with the selection of relevant outcome measures in addressing the various aspects related to validity. 5.1. Divergence between the model and the human individual in the pathogenesis of T1D The various animal models represent different features of the pathophysiology and progression of diabetes (Table 1). Lymphopenia is present in the BB-DP rat due to a chromosomal mutation that is characterized by a lack of RT6-positive (regulatory) T cells (Greiner et al., 1986, 2001; MacMurray et al., 2002). The role of


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regulatory T cells in clinical populations has been somewhat mixed making it difficult to assess the relevance of this deficit in the BBDP model with respect to the clinical situation (Agathocles, 2012). Diabetes in the NOD mouse is considered mild when compared to diabetes in patients or BB-DP rats since animals do not necessarily require insulin, and ketoacidosis is rare: females are more severely affected than males (Bao et al., 2002). Thus, to increase the confidence of results obtained with prevention treatments, it may be useful to demonstrate efficacy in more than one species (Greiner et al., 2001;Von Herrath and Nepom, 2009). Regarding models in which diabetes is induced, the severity and persistence of the diabetic state is affected by the induction protocols (e.g., dose, purity of the chemical) and species. At high dose STZ causes β-cell death by DNA fragmentation and at lower doses STZ elicits an immune reaction presumably related with the release of glutamic acid decarboxylase autoantigens (Eleazu et al., 2013; Graham et al., 2011b). Chemically-induced models have essentially the same phenotype as clinical T1D patients, except for the mechanism of β-cell damage: thus, the value of these models is primarily in studying treatment of diabetes but not in studying the onset. Although certain features of an autoimmune response have been observed in STZ-induction models (infiltration in islets, islet-reactive antibodies) it is not easy to disentangle the effect of direct toxicity versus indirect toxicity involving the immune response. Therefore, caution should be used in applying these models to assess recurrent autoimmunity (Anderson and Bluestone, 2005; Rossini et al., 1977; Wei et al., 2011). Diabetes-induction protocols may also provoke adverse effects that interfere with the interpretation of the experimental therapy of interest. This has been observed in the case of STZ where mild injury to the kidney can increase vulnerability to toxic insult later during therapeutic intervention using a compound with nephrotoxic adverse side effects (Wijkstrom et al., 2005). Finally, a very relevant complicating aspect of diabetes induction is the possibility of regeneration of the animal’s own β-cell function in case of insufficient elimination by the chemical. This restoration of endogenous insulin supply could confound the interpretation of function of β-cell replacement treatments, and therefore should be properly documented, for instance by (histologic) assessments at necropsy. 5.2. Species differences in T1D models Evidently immune targets are of substantial interest in both prevention models, and also in the situation of β-cell replacement therapy. From an immunological perspective the differences between mice and humans are substantial, especially where there might be interaction between multiple homeostatic pathways. This can contribute to clinical results that are not expected based on the outcome of animal modeling (Mestas and Hughes, 2004; Roep et al., 2004; Shoda et al., 2005). In an attempt to address some of the divergences, a number of humanized mouse models have been developed to represent unique aspects of the clinical response (Brehm et al., 2010). NHPs are thought to most accurately mimic the complexity of the human immune system because its principal features (e.g., major histocompatibility complex, peptide sequences, and xenoantibodies) have been highly conserved through primate evolution (Elferink et al., 1993; Geluk et al., 1993; Howard, 1982; Vaccari and Franchini, 2010). Species specificity also impacts utility in rodent models, in that rodents are generally not suitable to characterize safety of many biotechnology-derived products or pharmaceuticals like humandirected monoclonal antibodies and recombinant fusion proteins. This is because safety of these products relates to their efficacy, and efficacy does not exist because of lack of species

cross-reactivity. Also, it does not make sense to use rodents for testing xenotransplantation products containing the terminal galactose α(1-3) galactose (Gal) epitope because rodents lack naturally-existing anti-Gal antibodies: such antibodies represent the major component of hyperacute rejection of pig solid organs as documented in pig-to-NHP transplantation. To mimick hyperacute rejection in a natural manner like in the human situation, only oldworld NHPs can be studied because old-world NHPs are the only species sharing with humans the absence of galactosyl transferase. This enzyme is involved in synthesis of Gal, and its absence enables the elicitation of (naturally existing) anti-Gal antibodies by the intestinal microflora similar to the elicitation of red blood group ABO antibodies (Galili, 2005). Besides these impacts of differences in immune reactivity, there are other species incompatibilities to be considered in testing xenotransplantation products in animal models and in selecting the most appropriate species combination model. For example, it has been suggested that the rodent model is not ideal because rodents are resistant to porcine and human insulin so that compensation is necessary: at least this should be realized as a limitation of the model in the interpretation of results (Pepper et al., 2009). There are also differences in the metabolic demand between rodents, pigs, NHPs, and humans that should be considered when designing dose strategies for β-cell replacement therapies, and also when defining outcomes of success in various models. This has been observed for pig xenotransplantation cell therapy products where the much higher need for insulin in macaques (than in humans or pigs) creates an imbalance between the metabolic demand and the pig islet product; this situation is model-specific and is not anticipated in the clinical condition (Casu et al., 2008; Graham et al., 2011a; Graham and Schuurman, 2013; Wijkstrom et al., 2013). Dosing adaptations may be one way to successfully compensate this effect in short-term preclinical studies: this adaptation obviously lacks translational value (Lee et al., 2013a). 5.3. Experimental handling in T1D models Perhaps the most underappreciated aspect affecting validity in these models is the performance of the model itself. At first, this relates to reproducibility of data from studies in the same model performed at different institutions: unless a proper validation is performed it is logical that reproducibility can be affected. One aspect mentioned above is the difference in protocols using STZ in diabetes induction that may introduce confounding characteristics. As another example, it has been documented that different cohorts from the same strain of (nu/nu) mice manifest substantial differences in blood glucose levels at baseline, sensitivity to STZ, and subsequent response to insulin: these differences are presumably related to slight genetic drifts (Graham et al., 2011b; Pozzilli et al., 1993). A similar variability has also been observed in spontaneous inbred NOD mice regarding age of onset and incidence of diabetes: it was suggested that also here the cause is a degree of genetic drift. This makes a direct comparison between centers somewhat difficult; evidently proper controls are imperative (Pozzilli et al., 1993). Likewise, major differences in morbidity and mortality in NHPs following STZ administered at dose levels between 80 and 150 mg/kg have been observed (Zhu et al., 2014). Refinements in these models have suggested that it is possible (1) to identify animals that are at risk for adverse side effects, (2) to optimize dosing and administration, and (3) to develop supportive care protocols to avoid that animals have to be disqualified for atypical clinical pathology, or to avoid that later animals have to be considered noninformative because adverse effects resulting from model handling interfere with the proper interpretation of the treatment tested (Graham et al., 2011c).



Insulin management in the diabetic period both affects the health status of animals and might bias a study result: this has prompted a more detailed characterization of methods, and attempts to achieve standardization (Grant et al., 2012). Like in diabetic patients, the diabetic state of absolute absence of endogenous insulin supply creates a clinical condition that is complex to manage and creates instability that can result in serious physiological abnormalities (e.g., hyperglycemia, osmotic diuresis, ketoacidosis) and can result in death. Successful management relies on frequent evaluation of a complete clinical pathology assessment and quick intervention including intensive nutrition, fluid management, insulin, and supportive care: it is strongly recommended to have proper protocols in place (Graham et al., 2012a). In the case of the NHP, vascular access ports are recommended to enable frequent blood sampling and intensive fluid management protocols in the familiar homecage, to avoid additional stressors and separation from the social cohort (Graham et al., 2009, 2010). This should be combined with training for cooperative handling, also with the aim to avoid stressful situations especially in the case of animal wellbeing, and to enable the early detection of discomfort in animals so that an early and quick intervention can be started (Graham et al., 2012b). It seems evident that deviations in animal models from the proposed protocol in clinical application regarding the route of administration, ‘time course of treatment’, or dose of therapeutic agents can also contribute to failed translation of preclinical data into the clinical condition (Von Herrath and Nepom, 2009). An interesting example is the use of insulin antigen therapy, which was successful in preventing the onset of T1D in both NOD mice and BB-DP rats, but which was not successful in patients participating in the large-scale Diabetes Prevention Trial by the Type 1 Diabetes Study Group, Diabetes Prevention Trial (2002). This lack of translational value was attributed to immunological differences at time of onset as well as incongruent dosing of insulin: e.g., a 10fold lower dose was used in the clinical trial (Driver et al., 2011). Routine day-to-day handling of animals used in T1D experiments is also at a high level because of the need for frequent glucose monitoring and frequent insulin administration like in patients. Also, in the experimental situation of complex drug administration regimens, routine blood collection, and metabolic in vivo tests (e.g., intraperitoneal or intravenous glucose tolerance test, mixed-meal tolerance test, alternate side testing, and clamp studies), the contact between handlers and animals is intense. These metabolic models rely on stress-sensitive outcome measures, primarily blood glucose and insulin secretory capacity, and therefore stress should be kept minimal. In NHPs it has been shown that stress resulting from restraint can impair glucose tolerance and significantly increase blood glucose levels: this contrasts with cooperative handling that preserves normal pathophysiological features (Lapin et al., 2013; Shirasaki et al., 2013; Graham et al., 2012b).

6. Making animal modeling more clinical-trial like Maybe the most logical approach to improve translation of data from T1D animal models is to take lessons from the design and conduct of key clinical trials in prevention and β-cell replacement. A number of important advances have been achieved following trials in animals: together with aspects that affected translation this highlights the need to carefully consider how animal models are applied and interpreted. This should at first address the study design to evaluate “(1) time course of treatment; (2) animal characteristics and background; (3) subjective endpoints; (4) reproducibility of experimental animal results; (5) group size; and (6) reporting” (Denayer et al., 2014). Then, using the outcome measure of interest, individual animal

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models can be scored for validity using accepted criteria for face, predictive validity and target validity. This evaluation will assist in decisions on the acceptance or rejection of a distinct model (Denayer et al., 2014; Sams-Dodd, 2006). This combination of appropriate model selection and careful preclinical trial design to mimic the intended clinical application are pivotal to optimize the translational value of animal models, and models for T1D can serve as leading in this area.

Authorship contributions Design and outline: Melanie Graham, Henk-Jan Schuurman. Writing: Melanie Graham. Draft review and finalization: Melanie Graham, Henk-Jan Schuurman.

Conflict of interest The authors declare that there is no conflict of interest.

Submission declaration This review has not been published elsewhere, or is not under consideration to be published elsewhere. Both authors approved this manuscript. References Adams, A.B., Shirasugi, N., Durham, M.M., Strobert, E., Anderson, D., Rees, P., Cowan, S., Xu, H., Blinder, Y., Cheung, M., Hollenbaugh, D., Kenyon, N.S., Pearson, T.C., Larsen, C.P., 2002. Calcineurin inhibitor-free CD28 blockade-based protocol protects allogeneic islets in nonhuman primates. Diabetes 51, 265–270. Agathocles, T., 2012. The role of T regulatory cells (Tregs) in the development and prevention of type 1 diabetes. J. Clin. Cell. Immunol. S2, 003. Åkerman, L., Ludvigsson, J., Casas, R., 2013. Low C-peptide levels and decreased expression of TNF and CD45 in children with high risk of type 1 diabetes. Clin. Immunol. 148, 4–15. Alejandro, R., Barton, F.B., Hering, B.J., Wease, S., 2008. 2008 Update from the Collaborative Islet Transplant Registry Collaborative Islet Transplant Registry Investigators. Transplantation 86, 1783–1788. Anderson, M.S., Bluestone, J.A., 2005. The NOD mouse: a model of immune dysregulation. Annu. Rev. Immunol. 23, 447–485. Araki, E., Oyadomari, S., Mori, M., 2003. Impact of endoplasmic reticulum stress pathway on pancreatic beta-cells and diabetes mellitus. Exp. Biol. Med. (Maywood) 228, 1213–1217. Ballinger, W.F., Lacy, P.E., Gittes, R.F., Altwein, J.E., Yen, S.S., Lee, S., Miller, H.C., Alexander, J.W., Nathan, P., 1972. Transplantation of intact pancreatic islets in rats. Carbon 220, 228. Banga, A., Akinci, E., Greder, L.V., Dutton, J.R., Slack, J.M., 2012. In vivo reprogramming of Sox9 þ cells in the liver to insulin-secreting ducts. Proc. Natl. Acad. Sci. U.S.A. 109, 15336–15341. Bao, M., Yang, Y., Jun, H.S., Yoon, J.W., 2002. Molecular mechanisms for gender differences in susceptibility to T cell-mediated autoimmune diabetes in nonobese diabetic mice. J. Immunol. 168, 5369–5375. Barton, F.B., Rickels, M.R., Alejandro, R., Hering, B.J., Wease, S., Naziruddin, B., Oberholzer, J., Odorico, J.S., Garfinkel, M.R., Levy, M., Pattou, F., Berney, T., Secchi, A., Messinger, S., Senior, P.A., Maffi, P., Posselt, A., Stock, P.G., Kaufman, D.B., Luo, X., Kandeel, F., Cagliero, E., Turgeon, N.A., Witkowski, P., Naji, A., O’Connell, P.J., Greenbaum, C., Kudva, Y.C., Brayman, K.L., Aull, M.J., Larsen, C., Kay, T.W., Fernandez, L.A., Vantyghem, M.C., Bellin, M., Shapiro, A.M., 2012. Improvement in outcomes of clinical islet transplantation: 1999–2010. Diabetes Care 35, 1436–1445. Bassi, R., Fiorina, P., 2011. Impact of islet transplantation on diabetes complications and quality of life. Curr. Diab. Rep. 11, 355–363. Beckwith, J., Nyman, J.A., Flanagan, B., Schrover, R., Schuurman, H.-J., 2012. A health economic analysis of clinical islet transplantation. Clin. Transplant. 26, 23–33. Berney, T., Buhler, L., Majno, P., Mentha, G., Morel, P., 2004. Immunosuppression for pancreatic islet transplantation. Transplant. Proc. 36, S362–S366. Bliss, M., 2000. Discovery of Insulin. University of Chicago Press. Boroujerdi, M., Umpleby, A., Jones, R., Sonksen, P., 1995. A simulation model for glucose kinetics and estimates of glucose utilization rate in type 1 diabetic patients. Am. J. Physiol. 31, E766–E774. Brehm, M.A., Shultz, L.D., Greiner, D.L., 2010. Humanized mouse models to study human diseases. Curr. Opin. Endocrinol. Diabetes Obes. 17, 120–125. Cardona, K., Korbutt, G.S., Milas, Z., Lyon, J., Cano, J., Jiang, W., Bello-Laborn, H., Hacquoil, B., Strobert, E., Gangappa, S., 2006. Long-term survival of neonatal


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