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Published in: Endocrine 1/2019

Open Access 01-04-2019 | Maturity-Onset Diabetes of the Young | Original Article

A decision algorithm to identify patients with high probability of monogenic diabetes due to HNF1A mutations

Authors: Magdalena Szopa, Tomasz Klupa, Maria Kapusta, Bartlomiej Matejko, Damian Ucieklak, Wojciech Glodzik, Barbara Zapala, Cyrus Maurice Sani, Jerzy Hohendorff, Maciej T. Malecki, Jan Skupien

Published in: Endocrine | Issue 1/2019

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Abstract

Purpose

To investigate the utility of biomarkers of maturity-onset diabetes of the young (MODY), high-sensitivity C-reactive protein (hsCRP), and 1,5-anhydroglucitol (1,5-AG) in conjunction with other clinical and laboratory features to improve diagnostic accuracy and provide a diagnostic algorithm for HNF1A MODY.

Methods

We examined 77 patients with HNF1A MODY, 88 with GCK MODY mutations, 99 with type 1 diabetes, and 92 with type 2 diabetes. In addition to 1,5-AG and hsCRP, we considered body mass index (BMI), fasting glucose, and fasting serum C-peptide as potential biomarkers. Logistic regression and receiver operating characteristic curves were used in marker evaluation.

Results

Concentration of hsCRP was lowest in HNF1A MODY (0.51 mg/l) and highest in type 2 diabetes (1.33 mg/l). The level of 1,5-AG was lowest in type 1 diabetes and HNF1A MODY, 3.8 and 4.7 μg/ml, respectively, and highest (11.2 μg/ml) in GCK MODY. In the diagnostic algorithm, we first excluded patients with type 1 diabetes based on low C-peptide (C-statistic 0.98) before using high BMI and C-peptide to identify type 2 diabetes patients (C-statistic 0.92). Finally, 1,5-AG and hsCRP in conjunction yielded a C-statistic of 0.86 in discriminating HNF1A from GCK MODY. We correctly classified 92.9% of patients with type 1 diabetes, 84.8% with type 2 diabetes, 64.9% HNF1A MODY, and 52.3% GCK MODY patients.

Conclusions

Plasma 1,5-AG and serum hsCRP do not discriminate sufficiently HNF1A MODY from common diabetes types, but could be potentially useful in prioritizing Sanger sequencing of HNF1A gene.
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Metadata
Title
A decision algorithm to identify patients with high probability of monogenic diabetes due to HNF1A mutations
Authors
Magdalena Szopa
Tomasz Klupa
Maria Kapusta
Bartlomiej Matejko
Damian Ucieklak
Wojciech Glodzik
Barbara Zapala
Cyrus Maurice Sani
Jerzy Hohendorff
Maciej T. Malecki
Jan Skupien
Publication date
01-04-2019
Publisher
Springer US
Published in
Endocrine / Issue 1/2019
Print ISSN: 1355-008X
Electronic ISSN: 1559-0100
DOI
https://doi.org/10.1007/s12020-019-01863-7

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