Classification and characteristics of interferon-related diabetes mellitus in Japan

Kazuhisa Muraishi; Yuko Sasaki; Tomoko Kato; Chizuko Inada; Yuji Tajiri; Kentaro Yamada

doi:10.1111/j.1872-034X.2010.00753.x

Classification and characteristics of interferon-related diabetes mellitus in Japan

Hepatol Res. 2011 Feb;41(2):184-8. doi: 10.1111/j.1872-034X.2010.00753.x.

Authors

Kazuhisa Muraishi¹, Yuko Sasaki, Tomoko Kato, Chizuko Inada, Yuji Tajiri, Kentaro Yamada

Affiliation

¹ Division of Endocrinology and Metabolism, Department of Medicine, Kurume University School of Medicine Inada Naika Clinic, Kurume, Japan.

PMID: 21269387
DOI: 10.1111/j.1872-034X.2010.00753.x

Abstract

Aim: The aim of this study was to assess the classification and clinical characteristics of interferon (IFN)-related diabetes.

Methods: Cases with IFN-related diabetes in Japan were retrieved through web search engines for medical literature until July in 2009, and unreported data were obtained from the authors by letter or e-mail.

Results: We collected 143 cases with IFN-related diabetes consisting of 104 type 1 diabetes including 4 own cases, and 39 non-autoimmune type 2-like diabetes. We found a marked increase in IFN-related type 1 diabetes for these 3 years. In contrast, no increase was observed in IFN-related type 2-like diabetes in the literature. Polyethylene glycol (PEG)-IFN and ribavirin had been more frequently used in patients with type 1 diabetes than in patients with type 2-like diabetes. The age of diabetes onset was comparable between type 1 and type 2-like diabetes, while the ratio of male patients was higher and the latency before diabetes was shorter in type 2-like diabetes. Patients with IFN-related type 1 diabetes had HLA types susceptible to Japanese type 1 diabetic patients, and a high positive rate of GAD antibodies.

Conclusion: Potent combination therapy with PEG-IFN and ribavirin is likely associated with the increase in IFN-related type 1 diabetes. The combined measurement of GAD antibody and HLA-typing could be an effective strategy to predict the onset of type 1 diabetes associated with IFN therapy.