Literature DB >> 30977832

Identifying Pathogenic Variants of Monogenic Diabetes Using Targeted Panel Sequencing in an East Asian Population.

Seung Shin Park1, Se Song Jang2, Chang Ho Ahn1, Jung Hee Kim1, Hye Seung Jung1, Young Min Cho1,3, Young Ah Lee4, Choong Ho Shin4,5, Jong Hee Chae4,5, Jae Hyun Kim6, Sung Hee Choi3,7, Hak C Jang3,7, Jee Cheol Bae8, Jong Cheol Won9, Sung-Hoon Kim10,11, Jong-Il Kim2,12,13, Soo Heon Kwak1, Kyong Soo Park1,3,14.   

Abstract

PURPOSE: Monogenic diabetes is a specific type of diabetes in which precision medicine could be applied. In this study, we used targeted panel sequencing to investigate pathogenic variants in Korean patients clinically suspected to have monogenic diabetes.
METHODS: The eligibility criteria for inclusion were non-type 1 diabetes patients with an age of onset ≤ 30 years and a BMI (body mass index) ≤ 30 kg/m2. Among the 2,090 non-type 1 diabetes patients, 109 were suspected to have monogenic diabetes and subjected to genetic testing. We analyzed 30 monogenic diabetes genes using targeted panel sequencing. The pathogenicity of the genetic variants was evaluated according to the American College of Medical Genetics and Genomics and the Association for Molecular Pathology guidelines.
RESULTS: Among the 109 suspected monogenic diabetes patients, 23 (21.1%) patients harbored pathogenic/likely pathogenic variants. A total of 14 pathogenic/likely pathogenic variants of common maturity onset diabetes of the young (MODY) genes were identified in GCK, HNF1A, HNF4A, and HNF1B. Other pathogenic/likely pathogenic variants were identified in WFS1, INS, ABCC8 and FOXP3. The mitochondrial DNA 3243 A>G variant was identified in five participants. Patients with pathogenic/likely pathogenic variants had a significantly higher MODY probability, a lower BMI, and a lower C-peptide level than those without pathogenic/likely pathogenic variants (P=0.007, P=0.001, and P=0.012, respectively).
CONCLUSIONS: Using targeted panel sequencing followed by pathogenicity evaluation, we were able to make molecular genetic diagnoses for 23 (21.1%) suspected monogenic diabetes patients. Lower BMI, higher MODY probability, and lower C-peptide levels were characteristics of these participants.
Copyright © 2019 Endocrine Society.

Entities:  

Year:  2019        PMID: 30977832     DOI: 10.1210/jc.2018-02397

Source DB:  PubMed          Journal:  J Clin Endocrinol Metab        ISSN: 0021-972X            Impact factor:   5.958


  6 in total

1.  Etiologic distribution and clinical characteristics of pediatric diabetes in 276 children and adolescents with diabetes at a single academic center.

Authors:  Ja Hye Kim; Yena Lee; Yunha Choi; Gu-Hwan Kim; Han-Wook Yoo; Jin-Ho Choi
Journal:  BMC Pediatr       Date:  2021-03-04       Impact factor: 2.125

2.  Syndromic Monogenic Diabetes Genes Should Be Tested in Patients With a Clinical Suspicion of Maturity-Onset Diabetes of the Young.

Authors:  Kevin Colclough; Sian Ellard; Andrew Hattersley; Kashyap Patel
Journal:  Diabetes       Date:  2022-03-01       Impact factor: 9.337

3.  Clinical and Genetic Characteristics of ABCC8 Nonneonatal Diabetes Mellitus: A Systematic Review.

Authors:  Meng Li; Xueyao Han; Linong Ji
Journal:  J Diabetes Res       Date:  2021-09-30       Impact factor: 4.011

4.  Early-onset diabetes involving three consecutive generations had different clinical features from age-matched type 2 diabetes without a family history in China.

Authors:  Da-Wei Wang; Jing Yuan; Fang-Yuan Yang; Hai-Yan Qiu; Jing Lu; Jin-Kui Yang
Journal:  Endocrine       Date:  2022-08-03       Impact factor: 3.925

5.  MODY2 in Asia: analysis of GCK mutations and clinical characteristics.

Authors:  Yuan Zhou; ShengNan Wang; Jing Wu; JianJun Dong; Lin Liao
Journal:  Endocr Connect       Date:  2020-05       Impact factor: 3.335

6.  Clinical and genetic analysis in a Chinese cohort of children and adolescents with diabetes/persistent hyperglycemia.

Authors:  Yu Ding; Niu Li; Dan Lou; Qianwen Zhang; Guoying Chang; Juan Li; Xin Li; Qun Li; Xiaodong Huang; Jian Wang; Fan Jiang; Xiumin Wang
Journal:  J Diabetes Investig       Date:  2020-07-23       Impact factor: 4.232

  6 in total

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