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Virtual optimization of nasal insulin therapy predicts immunization frequency to be crucial for diabetes protection.

Fousteri G, Chan JR, Zheng Y, Whiting C, Dave A, Bresson D, Croft M, von Herrath M - Diabetes (2010)

Bottom Line: The experimental aim was to evaluate the impact of dose, frequency of administration, and age at treatment on Treg induction and optimal therapeutic outcome.Here, the advantage of applying computer modeling in optimizing the therapeutic efficacy of nasal insulin immunotherapy was confirmed.In silico modeling was able to streamline the experimental design and to identify the particular time frame at which biomarkers associated with protection in live NODs were induced.

View Article: PubMed Central - PubMed

Affiliation: Diabetes Center, La Jolla Institute for Allergy and Immunology, La Jolla, California, USA.

ABSTRACT

Objective: Development of antigen-specific strategies to treat or prevent type 1 diabetes has been slow and difficult because of the lack of experimental tools and defined biomarkers that account for the underlying therapeutic mechanisms.

Research design and methods: The type 1 diabetes PhysioLab platform, a large-scale mathematical model of disease pathogenesis in the nonobese diabetic (NOD) mouse, was used to investigate the possible mechanisms underlying the efficacy of nasal insulin B:9-23 peptide therapy. The experimental aim was to evaluate the impact of dose, frequency of administration, and age at treatment on Treg induction and optimal therapeutic outcome.

Results: In virtual NOD mice, treatment efficacy was predicted to depend primarily on the immunization frequency and stage of the disease and to a lesser extent on the dose. Whereas low-frequency immunization protected from diabetes atrributed to Treg and interleukin (IL)-10 induction in the pancreas 1-2 weeks after treatment, high-frequency immunization failed. These predictions were confirmed with wet-lab approaches, where only low-frequency immunization started at an early disease stage in the NOD mouse resulted in significant protection from diabetes by inducing IL-10 and Treg.

Conclusions: Here, the advantage of applying computer modeling in optimizing the therapeutic efficacy of nasal insulin immunotherapy was confirmed. In silico modeling was able to streamline the experimental design and to identify the particular time frame at which biomarkers associated with protection in live NODs were induced. These results support the development and application of humanized platforms for the design of clinical trials (i.e., for the ongoing nasal insulin prevention studies).

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Validation of predicted nasal B:9-23 immunization frequency influence on diabetes incidence and Treg levels by laboratory measurements. A and B: High-frequency immunization decreases efficacy. A: In silico simulation showing expected impact on blood glucose (mmol/l) in a representative virtual NOD mouse. B: Nasal B:9-23 administration upon low-frequency immunization protects from type 1 diabetes. Percentage of mice developing diabetes after high- or low-frequency immunizations started at 4 weeks of age with 40 mg B:9-23 peptide. At least 12 mice were included in each experimental group. Each immunization protocol was repeated in at least two independent experiments. *P < 0.05 between immunization groups. C–E: High-frequency immunization is predicted to decrease efficacy because of the deletion of aTreg in the NALT. Simulation results for Treg levels in the NALT (C), PDLN (D), and peripheral blood (E) in a representative VM. The green boxes indicate the suggested-by-the-model-age window at which the laboratory measurements should be conducted. F–H: Nasal B:9-23 administration upon low-frequency immunization induces Treg and protects from type 1 diabetes. Treg frequency (%CD25+Foxp3+ gated on CD4+CD127low, >95% of CD4+ were CD127low) in the spleen (F), PDLN (G), and blood (H) over time after high- or low-frequency immunizations (n = 4 mice per group). *P < 0.05; **P < 0.01; ***P < 0.005 between immunization groups. Data are means ± SE.
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Figure 3: Validation of predicted nasal B:9-23 immunization frequency influence on diabetes incidence and Treg levels by laboratory measurements. A and B: High-frequency immunization decreases efficacy. A: In silico simulation showing expected impact on blood glucose (mmol/l) in a representative virtual NOD mouse. B: Nasal B:9-23 administration upon low-frequency immunization protects from type 1 diabetes. Percentage of mice developing diabetes after high- or low-frequency immunizations started at 4 weeks of age with 40 mg B:9-23 peptide. At least 12 mice were included in each experimental group. Each immunization protocol was repeated in at least two independent experiments. *P < 0.05 between immunization groups. C–E: High-frequency immunization is predicted to decrease efficacy because of the deletion of aTreg in the NALT. Simulation results for Treg levels in the NALT (C), PDLN (D), and peripheral blood (E) in a representative VM. The green boxes indicate the suggested-by-the-model-age window at which the laboratory measurements should be conducted. F–H: Nasal B:9-23 administration upon low-frequency immunization induces Treg and protects from type 1 diabetes. Treg frequency (%CD25+Foxp3+ gated on CD4+CD127low, >95% of CD4+ were CD127low) in the spleen (F), PDLN (G), and blood (H) over time after high- or low-frequency immunizations (n = 4 mice per group). *P < 0.05; **P < 0.01; ***P < 0.005 between immunization groups. Data are means ± SE.

Mentions: To test the hypothesis that too frequent immunization is detrimental for Treg induction in vivo, mice were divided into high- and low-frequency immunization groups. Two specific immunization protocols based on predictive outputs from the platform were implemented in the wet lab, described in Table 1. No protection was predicted in any of the VM following the high-frequency protocol (Fig. 3A). Evaluation of the antidiabetogenic properties of B:9-23 peptide immunizations in vivo according to both protocols showed that indeed in live NOD mice the low-frequency protocol was more effective than the high-frequency one (Fig. 3B). In all cases, treatment was initiated at the 4-week-old periinsulitis stage, and the mice were immunized with 40 μg of B:9-23. It is important to note here that simulated responses to alternate protocols provide insight into which protocols are most robust against variability or unknowns in the underlying disease and are to be interpreted as relative ranking of protocols rather than quantitative predictions of protection.


Virtual optimization of nasal insulin therapy predicts immunization frequency to be crucial for diabetes protection.

Fousteri G, Chan JR, Zheng Y, Whiting C, Dave A, Bresson D, Croft M, von Herrath M - Diabetes (2010)

Validation of predicted nasal B:9-23 immunization frequency influence on diabetes incidence and Treg levels by laboratory measurements. A and B: High-frequency immunization decreases efficacy. A: In silico simulation showing expected impact on blood glucose (mmol/l) in a representative virtual NOD mouse. B: Nasal B:9-23 administration upon low-frequency immunization protects from type 1 diabetes. Percentage of mice developing diabetes after high- or low-frequency immunizations started at 4 weeks of age with 40 mg B:9-23 peptide. At least 12 mice were included in each experimental group. Each immunization protocol was repeated in at least two independent experiments. *P < 0.05 between immunization groups. C–E: High-frequency immunization is predicted to decrease efficacy because of the deletion of aTreg in the NALT. Simulation results for Treg levels in the NALT (C), PDLN (D), and peripheral blood (E) in a representative VM. The green boxes indicate the suggested-by-the-model-age window at which the laboratory measurements should be conducted. F–H: Nasal B:9-23 administration upon low-frequency immunization induces Treg and protects from type 1 diabetes. Treg frequency (%CD25+Foxp3+ gated on CD4+CD127low, >95% of CD4+ were CD127low) in the spleen (F), PDLN (G), and blood (H) over time after high- or low-frequency immunizations (n = 4 mice per group). *P < 0.05; **P < 0.01; ***P < 0.005 between immunization groups. Data are means ± SE.
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Related In: Results  -  Collection

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Figure 3: Validation of predicted nasal B:9-23 immunization frequency influence on diabetes incidence and Treg levels by laboratory measurements. A and B: High-frequency immunization decreases efficacy. A: In silico simulation showing expected impact on blood glucose (mmol/l) in a representative virtual NOD mouse. B: Nasal B:9-23 administration upon low-frequency immunization protects from type 1 diabetes. Percentage of mice developing diabetes after high- or low-frequency immunizations started at 4 weeks of age with 40 mg B:9-23 peptide. At least 12 mice were included in each experimental group. Each immunization protocol was repeated in at least two independent experiments. *P < 0.05 between immunization groups. C–E: High-frequency immunization is predicted to decrease efficacy because of the deletion of aTreg in the NALT. Simulation results for Treg levels in the NALT (C), PDLN (D), and peripheral blood (E) in a representative VM. The green boxes indicate the suggested-by-the-model-age window at which the laboratory measurements should be conducted. F–H: Nasal B:9-23 administration upon low-frequency immunization induces Treg and protects from type 1 diabetes. Treg frequency (%CD25+Foxp3+ gated on CD4+CD127low, >95% of CD4+ were CD127low) in the spleen (F), PDLN (G), and blood (H) over time after high- or low-frequency immunizations (n = 4 mice per group). *P < 0.05; **P < 0.01; ***P < 0.005 between immunization groups. Data are means ± SE.
Mentions: To test the hypothesis that too frequent immunization is detrimental for Treg induction in vivo, mice were divided into high- and low-frequency immunization groups. Two specific immunization protocols based on predictive outputs from the platform were implemented in the wet lab, described in Table 1. No protection was predicted in any of the VM following the high-frequency protocol (Fig. 3A). Evaluation of the antidiabetogenic properties of B:9-23 peptide immunizations in vivo according to both protocols showed that indeed in live NOD mice the low-frequency protocol was more effective than the high-frequency one (Fig. 3B). In all cases, treatment was initiated at the 4-week-old periinsulitis stage, and the mice were immunized with 40 μg of B:9-23. It is important to note here that simulated responses to alternate protocols provide insight into which protocols are most robust against variability or unknowns in the underlying disease and are to be interpreted as relative ranking of protocols rather than quantitative predictions of protection.

Bottom Line: The experimental aim was to evaluate the impact of dose, frequency of administration, and age at treatment on Treg induction and optimal therapeutic outcome.Here, the advantage of applying computer modeling in optimizing the therapeutic efficacy of nasal insulin immunotherapy was confirmed.In silico modeling was able to streamline the experimental design and to identify the particular time frame at which biomarkers associated with protection in live NODs were induced.

View Article: PubMed Central - PubMed

Affiliation: Diabetes Center, La Jolla Institute for Allergy and Immunology, La Jolla, California, USA.

ABSTRACT

Objective: Development of antigen-specific strategies to treat or prevent type 1 diabetes has been slow and difficult because of the lack of experimental tools and defined biomarkers that account for the underlying therapeutic mechanisms.

Research design and methods: The type 1 diabetes PhysioLab platform, a large-scale mathematical model of disease pathogenesis in the nonobese diabetic (NOD) mouse, was used to investigate the possible mechanisms underlying the efficacy of nasal insulin B:9-23 peptide therapy. The experimental aim was to evaluate the impact of dose, frequency of administration, and age at treatment on Treg induction and optimal therapeutic outcome.

Results: In virtual NOD mice, treatment efficacy was predicted to depend primarily on the immunization frequency and stage of the disease and to a lesser extent on the dose. Whereas low-frequency immunization protected from diabetes atrributed to Treg and interleukin (IL)-10 induction in the pancreas 1-2 weeks after treatment, high-frequency immunization failed. These predictions were confirmed with wet-lab approaches, where only low-frequency immunization started at an early disease stage in the NOD mouse resulted in significant protection from diabetes by inducing IL-10 and Treg.

Conclusions: Here, the advantage of applying computer modeling in optimizing the therapeutic efficacy of nasal insulin immunotherapy was confirmed. In silico modeling was able to streamline the experimental design and to identify the particular time frame at which biomarkers associated with protection in live NODs were induced. These results support the development and application of humanized platforms for the design of clinical trials (i.e., for the ongoing nasal insulin prevention studies).

Show MeSH
Related in: MedlinePlus