Browsing by Subject "Trial"

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    Comparisons of Metabolic Measures to Predict T1D vs Detect a Preventive Treatment Effect in High-Risk Individuals
    (Oxford University Press, 2024) Sims, Emily K.; Cuthbertson, David; Jacobsen, Laura; Ismail, Heba M.; Nathan, Brandon M.; Herold, Kevan C.; Redondo, Maria J.; Sosenko, Jay; Pediatrics, School of Medicine
    Context: Metabolic measures are frequently used to predict type 1 diabetes (T1D) and to understand effects of disease-modifying therapies. Objective: Compare metabolic endpoints for their ability to detect preventive treatment effects and predict T1D. Methods: Six-month changes in metabolic endpoints were assessed for (1) detecting treatment effects by comparing placebo and treatment arms from the randomized controlled teplizumab prevention trial, a multicenter clinical trial investigating 14-day intravenous teplizumab infusion and (2) predicting T1D in the TrialNet Pathway to Prevention natural history study. For each metabolic measure, t-Values from t tests for detecting a treatment effect were compared with chi-square values from proportional hazards regression for predicting T1D. Participants in the teplizumab prevention trial and participants in the Pathway to Prevention study selected with the same inclusion criteria used for the teplizumab trial were studied. Results: Six-month changes in glucose-based endpoints predicted diabetes better than C-peptide-based endpoints, yet the latter were better at detecting a teplizumab effect. Combined measures of glucose and C-peptide were more balanced than measures of glucose alone or C-peptide alone for predicting diabetes and detecting a teplizumab effect. Conclusion: The capacity of a metabolic endpoint to detect a treatment effect does not necessarily correspond to its accuracy for predicting T1D. However, combined glucose and C-peptide endpoints appear to be effective for both predicting diabetes and detecting a response to immunotherapy. These findings suggest that combined glucose and C-peptide endpoints should be incorporated into the design of future T1D prevention trials.
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    Inhibition of polyamine biosynthesis preserves β cell function in type 1 diabetes
    (Elsevier, 2023) Sims, Emily K.; Kulkarni, Abhishek; Hull, Audrey; Woerner, Stephanie E.; Cabrera, Susanne; Mastrandrea, Lucy D.; Hammoud, Batoul; Sarkar, Soumyadeep; Nakayasu, Ernesto S.; Mastracci, Teresa L.; Perkins, Susan M.; Ouyang, Fangqian; Webb-Robertson, Bobbie-Jo; Enriquez, Jacob R.; Tersey, Sarah A.; Evans-Molina, Carmella; Long, S. Alice; Blanchfield, Lori; Gerner, Eugene W.; Mirmira, Raghavendra G.; DiMeglio, Linda A.; Pediatrics, School of Medicine
    In preclinical models, α-difluoromethylornithine (DFMO), an ornithine decarboxylase (ODC) inhibitor, delays the onset of type 1 diabetes (T1D) by reducing β cell stress. However, the mechanism of DFMO action and its human tolerability remain unclear. In this study, we show that mice with β cell ODC deletion are protected against toxin-induced diabetes, suggesting a cell-autonomous role of ODC during β cell stress. In a randomized controlled trial (ClinicalTrials.gov: NCT02384889) involving 41 recent-onset T1D subjects (3:1 drug:placebo) over a 3-month treatment period with a 3-month follow-up, DFMO (125-1,000 mg/m2) is shown to meet its primary outcome of safety and tolerability. DFMO dose-dependently reduces urinary putrescine levels and, at higher doses, preserves C-peptide area under the curve without apparent immunomodulation. Transcriptomics and proteomics of DFMO-treated human islets exposed to cytokine stress reveal alterations in mRNA translation, nascent protein transport, and protein secretion. These findings suggest that DFMO may preserve β cell function in T1D through islet cell-autonomous effects.