Literature DB >> 27634015

Genetic Confirmation Rate in Clinically Suspected Maturity-Onset Diabetes of the Young.

Amanda J Brahm1, Grace Wang1, Jian Wang1, Adam D McIntyre1, Henian Cao1, Matthew R Ban1, Robert A Hegele2.   

Abstract

OBJECTIVES: Maturity-onset diabetes of the young (MODY) is the most common form of monogenic diabetes, reportedly accounting for 2% to 5% of all cases of diabetes. In samples from Canadian patients referred for molecular genetic confirmation of a clinically suspected MODY, we determined the prevalence of likely disease-causing DNA variants in known MODY genes.
METHODS: Between 1999 and 2015, our centre received requests from colleagues for DNA sequencing of 96 samples from unrelated Canadian patients with clinically suspected MODY. Prior to 2012, we used Sanger sequencing, and since 2012 we have used targeted next-generation sequencing.
RESULTS: Of 96 samples received, 39 (40.6%) had a likely rare causal variant in 1 of 8 known MODY genes. Of these, 20 (51.3%) and 19 (48.7%) were diagnosed by Sanger and targeted next-generation sequencing, respectively. The 39 mutation-positive samples had 1 of 39 rare variants, of which the majority were in genes encoding either glucokinase (GCK, or MODY2) or hepatocyte nuclear factor 1-alpha (HNF1A, or MODY3). Furthermore, 12 (30.8%) of the detected rare variants had been unreported previously but were likely to have been clinically significant according to standard bioinformatic methods. An additional 6 samples had rare variants in MODY genes that were of uncertain clinical significance.
CONCLUSIONS: The findings suggest that clinical suspicion for MODY has a diagnostic yield of ~40% at the molecular level. Confirmatory genetic testing in patients suspected to have MODY allows for definitive diagnoses which, in turn, may guide management and provide rationales for screening other family members presymptomatically. Copyright Â
© 2016 Canadian Diabetes Association. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  corrélation génotype/phénotype; diabète monogénique; genetics; genotype-phenotype correlation; génétique; monogenic diabetes; mutations; next-generation DNA sequencing; séquençage de l'ADN de nouvelle génération

Mesh:

Substances:

Year:  2016        PMID: 27634015     DOI: 10.1016/j.jcjd.2016.05.010

Source DB:  PubMed          Journal:  Can J Diabetes        ISSN: 1499-2671            Impact factor:   4.190


  6 in total

1.  Copy Number Variation in GCK in Patients With Maturity-Onset Diabetes of the Young.

Authors:  Amanda J Berberich; Céline Huot; Henian Cao; Adam D McIntyre; John F Robinson; Jian Wang; Robert A Hegele
Journal:  J Clin Endocrinol Metab       Date:  2019-08-01       Impact factor: 5.958

2.  Negative autoimmunity in a Spanish pediatric cohort suspected of type 1 diabetes, could it be monogenic diabetes?

Authors:  Inés Urrutia; Rosa Martínez; Itxaso Rica; Idoia Martínez de LaPiscina; Alejandro García-Castaño; Anibal Aguayo; Begoña Calvo; Luis Castaño
Journal:  PLoS One       Date:  2019-07-31       Impact factor: 3.240

3.  Bioinformatic detection of copy number variation in HNF4A causing maturity onset diabetes of the young.

Authors:  Amanda J Berberich; Arati Mokashi; Adam D McIntyre; John F Robinson; Henian Cao; Jian Wang; Robert A Hegele
Journal:  Clin Genet       Date:  2019-07-15       Impact factor: 4.438

4.  Case Report: A Novel ABCC8 Variant in a Chinese Pedigree of Maturity-Onset Diabetes of the Young.

Authors:  Chaoyan Tang; Liheng Meng; Ping Zhang; Xinghuan Liang; Chaozhi Dang; Hui Liang; Junfeng Wu; Haiyun Lan; Yingfen Qin
Journal:  Front Endocrinol (Lausanne)       Date:  2021-12-23       Impact factor: 5.555

5.  First Japanese Family With PDX1-MODY (MODY4): A Novel PDX1 Frameshift Mutation, Clinical Characteristics, and Implications.

Authors:  Satoshi Yoshiji; Yukio Horikawa; Sodai Kubota; Mayumi Enya; Yorihiro Iwasaki; Yamato Keidai; Megumi Aizawa-Abe; Kanako Iwasaki; Sachiko Honjo; Kazuyoshi Hosomichi; Daisuke Yabe; Akihiro Hamasaki
Journal:  J Endocr Soc       Date:  2021-10-17

6.  Six years' experience with LipidSeq: clinical and research learnings from a hybrid, targeted sequencing panel for dyslipidemias.

Authors:  Jacqueline S Dron; Jian Wang; Adam D McIntyre; Michael A Iacocca; John F Robinson; Matthew R Ban; Henian Cao; Robert A Hegele
Journal:  BMC Med Genomics       Date:  2020-02-10       Impact factor: 3.063

  6 in total

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