Prediction of Marginal Mass Required for Successful Islet Transplantation

Klearchos K. PapasDepartment of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA and Diabetes Institute for Immunology and Transplantation, Department of Surgery, University of Minnesota, Minneapolis, Minnesota, USA

Clark K. ColtonDepartment of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USACorrespondence[email protected]

Andi QipoIslet Transplantation Laboratory, Massachusetts General Hospital, Boston, Massachusetts, USA

Haiyan WuDepartment of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

Rebecca A. NelsonAdministrative and Bioinformatics Coordinating Center, City of Hope National Medical Center, Duarte, California, USA

Bernhard J. HeringDiabetes Institute for Immunology and Transplantation, Department of Surgery, University of Minnesota, Minneapolis, Minnesota, USA

Gordon C. WeirJoslin Diabetes Center, Boston, Massachusetts, USA

Maria KoulmandaIslet Transplantation Laboratory, Massachusetts General Hospital, Boston, Massachusetts, USA and Transplant Research Center, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA Q1

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ABSTRACT

Islet quality assessment methods for predicting diabetes reversal (DR) following transplantation are needed. We investigated two islet parameters, oxygen consumption rate (OCR) and OCR per DNA content, to predict transplantation outcome and explored the impact of islet quality on marginal islet mass for DR. Outcomes in immunosuppressed diabetic mice were evaluated by transplanting mixtures of healthy and purposely damaged rat islets for systematic variation of OCR/DNA over a wide range. The probability of DR increased with increasing transplanted OCR and OCR/DNA. On coordinates of OCR versus OCR/DNA, data fell into regions in which DR occurred in all, some, or none of the animals with a sharp threshold of around 150-nmol/min mg DNA. A model incorporating both parameters predicted transplantation outcome with sensitivity and specificity of 93%% and 94%%, respectively. Marginal mass was not constant, depended on OCR/DNA, and increased from 2,800 to over 100,000 islet equivalents/kg body weight as OCR/DNA decreased. We conclude that measurements of OCR and OCR/DNA are useful for predicting transplantation outcome in this model system, and OCR/DNA can be used to estimate the marginal mass required for reversing diabetes. Because human clinical islet preparations in a previous study had OCR/DNA

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Prediction of Marginal Mass Required for Successful Islet Transplantation

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