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

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...

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Autores principales: Szopa, Magdalena, Klupa, Tomasz, Kapusta, Maria, Matejko, Bartlomiej, Ucieklak, Damian, Glodzik, Wojciech, Zapala, Barbara, Sani, Cyrus Maurice, Hohendorff, Jerzy, Malecki, Maciej T., Skupien, Jan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6453873/
https://www.ncbi.nlm.nih.gov/pubmed/30778899
http://dx.doi.org/10.1007/s12020-019-01863-7
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author Szopa, Magdalena
Klupa, Tomasz
Kapusta, Maria
Matejko, Bartlomiej
Ucieklak, Damian
Glodzik, Wojciech
Zapala, Barbara
Sani, Cyrus Maurice
Hohendorff, Jerzy
Malecki, Maciej T.
Skupien, Jan
author_facet Szopa, Magdalena
Klupa, Tomasz
Kapusta, Maria
Matejko, Bartlomiej
Ucieklak, Damian
Glodzik, Wojciech
Zapala, Barbara
Sani, Cyrus Maurice
Hohendorff, Jerzy
Malecki, Maciej T.
Skupien, Jan
author_sort Szopa, Magdalena
collection PubMed
description 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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spelling pubmed-64538732019-04-26 A decision algorithm to identify patients with high probability of monogenic diabetes due to HNF1A mutations Szopa, Magdalena Klupa, Tomasz Kapusta, Maria Matejko, Bartlomiej Ucieklak, Damian Glodzik, Wojciech Zapala, Barbara Sani, Cyrus Maurice Hohendorff, Jerzy Malecki, Maciej T. Skupien, Jan Endocrine Original Article 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. Springer US 2019-02-18 2019 /pmc/articles/PMC6453873/ /pubmed/30778899 http://dx.doi.org/10.1007/s12020-019-01863-7 Text en © The Author(s) 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, duplication, adaptation, distribution, and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Original Article
Szopa, Magdalena
Klupa, Tomasz
Kapusta, Maria
Matejko, Bartlomiej
Ucieklak, Damian
Glodzik, Wojciech
Zapala, Barbara
Sani, Cyrus Maurice
Hohendorff, Jerzy
Malecki, Maciej T.
Skupien, Jan
A decision algorithm to identify patients with high probability of monogenic diabetes due to HNF1A mutations
title A decision algorithm to identify patients with high probability of monogenic diabetes due to HNF1A mutations
title_full A decision algorithm to identify patients with high probability of monogenic diabetes due to HNF1A mutations
title_fullStr A decision algorithm to identify patients with high probability of monogenic diabetes due to HNF1A mutations
title_full_unstemmed A decision algorithm to identify patients with high probability of monogenic diabetes due to HNF1A mutations
title_short A decision algorithm to identify patients with high probability of monogenic diabetes due to HNF1A mutations
title_sort decision algorithm to identify patients with high probability of monogenic diabetes due to hnf1a mutations
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6453873/
https://www.ncbi.nlm.nih.gov/pubmed/30778899
http://dx.doi.org/10.1007/s12020-019-01863-7
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