1
|
Zhao J, Chen Y, Ma F, Shu H, Zheng L, Liu Y, Li X, Xu T, Zhou Z, Zhou K. MODY Probability Calculator Is Suitable for MODY Screening in China: A Population-based Study. J Endocr Soc 2024; 8:bvae047. [PMID: 38562131 PMCID: PMC10983078 DOI: 10.1210/jendso/bvae047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2024] [Indexed: 04/04/2024] Open
Abstract
Context Selecting appropriate individuals for genetic testing is essential due to the optimal treatment for maturity-onset diabetes of the young (MODY). However, how to effectively screen for MODY in China remains unclear. Objective To validate the performance of current screening strategies in selecting patients with MODY based on a nationwide type 2 diabetes cohort. Methods A panel of 14 MODY genes was analyzed from 1911 type 2 diabetes patients who were ages 15 to 35 years. Variants were evaluated according to the American College of Medical Genetics and Genomics guidelines. Based on this cohort, we simulated the 2 most frequently used screening strategies, including the traditional MODY criteria and the MODY probability calculator (MPC), to assess their ability to select patients with MODY. Results From a total of 1911 participants, 42 participants harbored pathogenic/likely pathogenic variants. The performance of the traditional criteria was sensitivity: 19.0%, specificity: 72.9%, positive predictive value (PPV): 1.6%, and missing rate: 81.0%. The optimal cut-off for MPC was 40.7%. Based on this cut-off value, the performance was sensitivity: 54.8%, specificity: 81.0%, PPV: 6.1%, and missing rate: 45.2%. Moreover, hemoglobin A1c, insulin treatment, and family history of diabetes have poor discrimination between MODY and young-onset type 2 diabetes. Conclusion The MPC is better than traditional criteria in terms of both sensitivity and PPV. To ensure more MODY patients benefit from optimal treatment, we therefore suggest that routine genetic testing be performed on all type 2 diabetes patients who are between the ages of 15 and35 years and have MPC probability value over 40.7%.
Collapse
Affiliation(s)
- Jing Zhao
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 101408, China
| | - Yan Chen
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Fuhui Ma
- Department of Endocrinology and Metabolic Diseases, People's Hospital of Xinjiang Uygur Autonomous Region, Xinjiang Clinical Research Center for Diabetes, Urumqi, 830001, China
| | - Hua Shu
- Department of Endocrinology and Metabolism, Tianjin Medical University General Hospital, Heping District, Tianjin, 300052, China
| | - Li Zheng
- Key Laboratory of RNA Biology, Center for Big Data Research in Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Yang Liu
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 101408, China
| | - Xia Li
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Tao Xu
- Guangzhou Laboratory, Guangdong Province, Guangdong 510005, China
| | - Zhiguang Zhou
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Kaixin Zhou
- Guangzhou Laboratory, Guangdong Province, Guangdong 510005, China
- School of Public Health, Guangzhou Medical University, Xinzao, Panyu District, Guangzhou, 511436, China
| |
Collapse
|