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Bhattacharya S, Fernandez CJ, Kamrul-Hasan ABM, Pappachan JM. Monogenic diabetes: An evidence-based clinical approach. World J Diabetes 2025; 16:104787. [DOI: 10.4239/wjd.v16.i5.104787] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/31/2024] [Revised: 02/20/2025] [Accepted: 03/11/2025] [Indexed: 04/25/2025] Open
Abstract
Monogenic diabetes is a heterogeneous disorder characterized by hyperglycemia arising from defects in a single gene. Maturity-onset diabetes of the young (MODY) is the most common type with 14 subtypes, each linked to specific mutations affecting insulin synthesis, secretion and glucose regulation. Common traits across MODY subtypes include early-onset diabetes, a family history of autosomal dominant diabetes, lack of features of insulin resistance, and absent islet cell autoimmunity. Many cases are misdiagnosed as type 1 and type 2 diabetes mellitus. Biomarkers and scoring systems can help identify candidates for genetic testing. GCK-MODY, a common subtype, manifests as mild hyperglycemia and doesn’t require treatment except during pregnancy. In contrast, mutations in HNF4A, HNF1A, and HNF1B genes lead to progressive beta-cell failure and similar risks of complications as type 2 diabetes mellitus. Neonatal diabetes mellitus (NDM) is a rare form of monogenic diabetes that usually presents within the first six months. Half of the cases are lifelong, while others experience transient remission. Permanent NDM is most commonly due to activating mutations in genes encoding the adenosine triphosphate-sensitive potassium channel (KCNJ11 or ABCC8) and can be transitioned to sulfonylurea after confirmation of diagnosis. Thus, in many cases, monogenic diabetes offers an opportunity to provide precision treatment. The scope has broadened with next-generation sequencing (NGS) technologies, replacing older methods like Sanger sequencing. NGS can be for targeted gene panels, whole-exome sequencing (WES), or whole-genome sequencing. Targeted gene panels offer specific information efficiently, while WES provides comprehensive data but comes with bioinformatic challenges. The surge in testing has also led to an increase in variants of unknown significance (VUS). Deciding whether VUS is disease-causing or benign can be challenging. Computational models, functional studies, and clinical knowledge help to determine pathogenicity. Advances in genetic testing technologies offer hope for improved diagnosis and personalized treatment but also raise concerns about interpretation and ethics.
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Affiliation(s)
| | - Cornelius J Fernandez
- Department of Endocrinology and Metabolism, Pilgrim Hospital, United Lincolnshire Hospitals NHS Trust, Boston PE21 9QS, Lincolnshire, United Kingdom
| | | | - Joseph M Pappachan
- Faculty of Science, Manchester Metropolitan University, Manchester M15 6BH, Greater Manchester, United Kingdom
- Department of Endocrinology, Kasturba Medical College, Manipal Academy of Higher Education, Manipal 576104, India
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Cobry EC, Steck AK. Review of Monogenic Diabetes: Clinical Features and Precision Medicine in Genetic Forms of Diabetes. Diabetes Technol Ther 2025. [PMID: 40176772 DOI: 10.1089/dia.2024.0602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/04/2025]
Abstract
Monogenic diabetes is a group of diseases that encompasses a growing number of genetic abnormalities affecting pancreatic function/development leading to glycemic dysregulation. This includes conditions that have historically been referred to as maturity onset diabetes of the young or MODY in addition to neonatal diabetes mellitus. While recognition of a genetic or inherited form of diabetes has been known for decades, advances in molecular genetic testing have resulted in identification of specific forms of monogenic diabetes. Despite this, these genetic forms of diabetes remain widely underreported. It is important to be able to identify genetic forms of diabetes as treatment, monitoring for microvascular and macrovascular complications, and overall management varies for the different forms of monogenic diabetes. Furthermore, the identification of a specific monogenic form of diabetes can significantly impact the person's quality of life and other family members, as well as health care costs. This article highlights the identification, treatment, and management for various forms of monogenic diabetes and addresses some unmet needs in caring for people with monogenic forms of diabetes.
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Affiliation(s)
- Erin C Cobry
- Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora CO, USA
| | - Andrea K Steck
- Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora CO, USA
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Liu CH, Liao CJ, Gupta S, Huang DW, Lee CY, Lai YT, Tai NH. Cross-Linking-Enabled Core-shell Nanostructure Based on Conductive Polymer Hydrogels/Carbon Nanotubes for Salivary Glucose Biosensor. ACS APPLIED MATERIALS & INTERFACES 2025; 17:15836-15848. [PMID: 39924952 DOI: 10.1021/acsami.4c20667] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/11/2025]
Abstract
Due to the 3-fold increase in the number of people with diabetes, there is an urgent need for noninvasive, user-friendly glucose monitoring technologies. However, current noninvasive methods are limited by low accuracy and susceptibility to interference. In this work, we develop a noninvasive salivary glucose biosensor using a core-shell nanostructure of conductive polymer hydrogels/carbon nanotubes (CNTs) on carbon paper. With the electrostatic interaction between the functional groups on CNTs and pyrrole monomer, the cross-linked polypyrrole (PPy) hydrogel can form in situ on the CNTs surface. The 3D interconnected networks of core-shell PPy/CNTs feature high surface area, porosity, and flexibility, facilitating efficient electron and ion transport, thereby leading to a superior glucose sensing sensitivity of 119.74 μA mM-1 cm-2 in the region of 50-700 μM. Additionally, this biosensor exhibited an ultralow Michaelis-Menten constant of 0.33 mM and high specificity toward glucose, even in the presence of various interferences, demonstrating a high affinity for the enzyme toward PPy/CNTs. This facile, controlled synthesis of core-shell PPy/CNTs offers a promising avenue for constructing enzymatic biosensors for accurate and regular monitoring of blood glucose via saliva tests.
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Affiliation(s)
- Ching-Hao Liu
- Department of Materials Science and Engineering, National Tsing Hua University, Hsinchu 300, Taiwan, ROC
| | - Chen-Jie Liao
- Department of Materials Engineering, Ming Chi University of Technology, New Taipei City 24301, Taiwan, ROC
| | - Shivam Gupta
- Department of Materials Science and Engineering, National Tsing Hua University, Hsinchu 300, Taiwan, ROC
| | - Da-Wei Huang
- Department of Materials Engineering, Ming Chi University of Technology, New Taipei City 24301, Taiwan, ROC
| | - Chi-Young Lee
- Department of Materials Science and Engineering, National Tsing Hua University, Hsinchu 300, Taiwan, ROC
| | - Yi-Ting Lai
- Department of Materials Engineering, Ming Chi University of Technology, New Taipei City 24301, Taiwan, ROC
- Center for Plasma and Thin Film Technologies, Ming Chi University of Technology, New Taipei City 24301, Taiwan, ROC
- Biochemical Technology R&D Center, Ming Chi University of Technology, New Taipei City 24301, Taiwan, ROC
| | - Nyan-Hwa Tai
- Department of Materials Science and Engineering, National Tsing Hua University, Hsinchu 300, Taiwan, ROC
- Institute of Analytical and Environmental Science, National Tsing Hua University Hsinchu 300, Taiwan, ROC
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Lin Y, Leith D, Abbott M, Barrett R, Bell S, Croudace TJ, Cunningham S, Dillon J, Donnan P, Farre A, Hernández R, Lang C, McKenzie S, Mordi I, Morrow S, Munro C, Philip S, Ryan M, Wake D, Wang H, Win M, Pearson E. iDiabetes platform-enhanced phenotyping of patients with diabetes for precision diagnosis, prognosis and treatment: study protocol for a cluster-randomised controlled study in Tayside, Scotland. BMJ Open 2024; 14:e086594. [PMID: 39613429 PMCID: PMC11605812 DOI: 10.1136/bmjopen-2024-086594] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Accepted: 09/12/2024] [Indexed: 12/01/2024] Open
Abstract
INTRODUCTION AND AIM Diabetes is a global health emergency with increasing prevalence and diabetes-associated morbidity and mortality. One of the challenges in optimising diabetes care is translating research advances in this heterogeneous disease into clinical care. A potential solution is the introduction of precision medicine approaches into diabetes care.We aim to develop a digital platform called 'intelligent Diabetes' (iDiabetes) to support a precision diabetes care model in Scotland and assess its impact on the primary composite outcome of all-cause mortality, hospitalisation rate, renal function decline and glycaemic control. METHODS AND ANALYSIS The impact of iDiabetes will be evaluated through a cluster-randomised controlled study, recruiting up to 22 500 patients with diabetes. Primary care general practices (GPs) in the National Health Service (NHS) Scotland Tayside Health Board are the units (clusters) of randomisation. Each primary care GP will form one cluster (approximately 400 patients per cluster), with up to 60 clusters recruited. Randomisation will be to iDiabetes (guideline support), iDiabetesPlus or usual diabetes care (control arm). Patients of participating primary care GPs are automatically enrolled on the study when they attend for their annual diabetes screening or are newly diagnosed with diabetes. A composite hierarchical primary outcome, evaluated using Win-Ratio statistical methodology, will consist of (1) all-cause mortality, (2) all-cause hospitalisation rate, (3) proportion with >40% estimated glomerular filtration rate [eGFR] reduction from baseline or new development of end-stage renal disease, (4) proportion with absolute HbA1C reduction >0.5%. Outcomes will be evaluated after a 2-year median follow-up period. Comprehensive qualitative and health economic analyses will be conducted, assessing the cost-effectiveness, budget impact and user acceptability of the iDiabetes platform. ETHICS AND DISSEMINATION This study was reviewed by the NHS Health Research Authority and approved by the East of Scotland Research Ethics Committee (reference: 23/ES/0008). Study findings will be disseminated via publications, presented at scientific conferences and shared with patients and the public on the study website and social media. TRIAL REGISTRATION NUMBER ISRCTN18000901.
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Affiliation(s)
| | | | - Michael Abbott
- Health Economics Research Unit, University of Aberdeen, Aberdeen, UK
| | | | - Samira Bell
- University of Dundee, Dundee, UK
- NHS Tayside, Dundee, UK
| | | | | | | | - Peter Donnan
- Dundee Epidemiology and Biostatistics Unit, University of Dundee, Dundee, UK
| | | | - Rodolfo Hernández
- Health Economics Research Unit, University of Aberdeen, Aberdeen, UK
| | | | | | | | - Susan Morrow
- Edinburgh Surgery Online, University of Edinburgh Division of Clinical and Surgical Sciences, Edinburgh, Edinburgh, UK
| | | | - Sam Philip
- NHS Education for Scotland, Aberdeen, UK
| | - Mandy Ryan
- Health Economics Research Unit, University of Aberdeen, Aberdeen, UK
| | - Deborah Wake
- University of Dundee, Dundee, UK
- The University of Edinburgh Usher Institute of Population Health Sciences and Informatics, Edinburgh, Edinburgh, UK
| | | | - Mya Win
- University of Dundee, Dundee, UK
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Wang X, Cheng W, Wang Z, Liu C, Deng A, Li J. Chinese carrier of the HNF1A p.Gln444fs variant exhibits enhanced response to sulfonylureas. Heliyon 2024; 10:e35112. [PMID: 39170165 PMCID: PMC11336406 DOI: 10.1016/j.heliyon.2024.e35112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Revised: 07/18/2024] [Accepted: 07/23/2024] [Indexed: 08/23/2024] Open
Abstract
Background We assessed the response to sulfonylureas and the functional characteristics of HNF1A mutations in patients with maturity-onset diabetes of the young type 3 (MODY3). Methods We recruited a family with suspected MODY in this study, and gene sequencing (whole-exome sequencing) was used to screen germline mutations. Luciferase reporter assays were used to evaluate the activity of the mutated genes. Results Heterozygous HNF1A variant (NM_000545.8:c.1330_1331del, p.Gln444fs) was identified in the proband and was not found in his father, grandmother, and nonrelated healthy controls. The mutant protein had 552 amino acids, 110 fewer than the wild type protein. Furthermore, the amino acid sequence was completely different between the mutant protein and the wild type protein starting from the 444th amino acid. Luciferase reporter assays revealed that the variant had impaired HNF4A promoter-regulation activity. The patient did not achieve good hypoglycemic effects during long-term treatment with insulin and metformin. The effect of hypoglycemic treatment was highly significant after the addition of sulfonylurea drugs. Conclusions The HNF1A p.Gln444fs variant associated with MODY3, and most likely a truncated protein, impaired HNF1A transcriptional activity. The variant carrier experienced an enhanced response to sulfonylureas.
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Affiliation(s)
- Xiufang Wang
- Department of Pain, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Wenzhuo Cheng
- Department of Pediatric, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Zhongjing Wang
- Department of Endocrinology, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Chao Liu
- Hubei Key Laboratory of Diabetes and Angiopathy, Hubei University of Science and Technology, Xianning, Hubei, China
| | - Aiping Deng
- Department of Pharmacy, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Juyi Li
- Department of Pharmacy, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
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Cardoso P, McDonald TJ, Patel KA, Pearson ER, Hattersley AT, Shields BM, McKinley TJ. Comparison of Bayesian approaches for developing prediction models in rare disease: application to the identification of patients with Maturity-Onset Diabetes of the Young. BMC Med Res Methodol 2024; 24:128. [PMID: 38834992 PMCID: PMC11149229 DOI: 10.1186/s12874-024-02239-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Accepted: 05/06/2024] [Indexed: 06/06/2024] Open
Abstract
BACKGROUND Clinical prediction models can help identify high-risk patients and facilitate timely interventions. However, developing such models for rare diseases presents challenges due to the scarcity of affected patients for developing and calibrating models. Methods that pool information from multiple sources can help with these challenges. METHODS We compared three approaches for developing clinical prediction models for population screening based on an example of discriminating a rare form of diabetes (Maturity-Onset Diabetes of the Young - MODY) in insulin-treated patients from the more common Type 1 diabetes (T1D). Two datasets were used: a case-control dataset (278 T1D, 177 MODY) and a population-representative dataset (1418 patients, 96 MODY tested with biomarker testing, 7 MODY positive). To build a population-level prediction model, we compared three methods for recalibrating models developed in case-control data. These were prevalence adjustment ("offset"), shrinkage recalibration in the population-level dataset ("recalibration"), and a refitting of the model to the population-level dataset ("re-estimation"). We then developed a Bayesian hierarchical mixture model combining shrinkage recalibration with additional informative biomarker information only available in the population-representative dataset. We developed a method for dealing with missing biomarker and outcome information using prior information from the literature and other data sources to ensure the clinical validity of predictions for certain biomarker combinations. RESULTS The offset, re-estimation, and recalibration methods showed good calibration in the population-representative dataset. The offset and recalibration methods displayed the lowest predictive uncertainty due to borrowing information from the fitted case-control model. We demonstrate the potential of a mixture model for incorporating informative biomarkers, which significantly enhanced the model's predictive accuracy, reduced uncertainty, and showed higher stability in all ranges of predictive outcome probabilities. CONCLUSION We have compared several approaches that could be used to develop prediction models for rare diseases. Our findings highlight the recalibration mixture model as the optimal strategy if a population-level dataset is available. This approach offers the flexibility to incorporate additional predictors and informed prior probabilities, contributing to enhanced prediction accuracy for rare diseases. It also allows predictions without these additional tests, providing additional information on whether a patient should undergo further biomarker testing before genetic testing.
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Affiliation(s)
- Pedro Cardoso
- University of Exeter Medical School. Address: Clinical and Biomedical Sciences, RILD Building, Royal Devon & Exeter Hospital, Barrack Road, Exeter, EX2 5DW, UK
| | - Timothy J McDonald
- University of Exeter Medical School. Address: Clinical and Biomedical Sciences, RILD Building, Royal Devon & Exeter Hospital, Barrack Road, Exeter, EX2 5DW, UK
| | - Kashyap A Patel
- University of Exeter Medical School. Address: Clinical and Biomedical Sciences, RILD Building, Royal Devon & Exeter Hospital, Barrack Road, Exeter, EX2 5DW, UK
| | - Ewan R Pearson
- University of Dundee. Address: Division of Population Health & Genomics, Ninewells Hospital and Medical School, University of Dundee, Dundee, DD1 9SY, UK
| | - Andrew T Hattersley
- University of Exeter Medical School. Address: Clinical and Biomedical Sciences, RILD Building, Royal Devon & Exeter Hospital, Barrack Road, Exeter, EX2 5DW, UK
| | - Beverley M Shields
- University of Exeter Medical School. Address: Clinical and Biomedical Sciences, RILD Building, Royal Devon & Exeter Hospital, Barrack Road, Exeter, EX2 5DW, UK
| | - Trevelyan J McKinley
- University of Exeter Medical School. Address: Clinical and Biomedical Sciences, RILD Building, Royal Devon & Exeter Hospital, Barrack Road, Exeter, EX2 5DW, UK.
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Shields BM, Carlsson A, Patel K, Knupp J, Kaur A, Johnston D, Colclough K, Larsson HE, Forsander G, Samuelsson U, Hattersley A, Ludvigsson J. Development of a clinical calculator to aid the identification of MODY in pediatric patients at the time of diabetes diagnosis. Sci Rep 2024; 14:10589. [PMID: 38719926 PMCID: PMC11079008 DOI: 10.1038/s41598-024-60160-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Accepted: 04/19/2024] [Indexed: 05/12/2024] Open
Abstract
Maturity Onset Diabetes of the Young (MODY) is a young-onset, monogenic form of diabetes without needing insulin treatment. Diagnostic testing is expensive. To aid decisions on who to test, we aimed to develop a MODY probability calculator for paediatric cases at the time of diabetes diagnosis, when the existing "MODY calculator" cannot be used. Firth logistic regression models were developed on data from 3541 paediatric patients from the Swedish 'Better Diabetes Diagnosis' (BDD) population study (n = 46 (1.3%) MODY (HNF1A, HNF4A, GCK)). Model performance was compared to using islet autoantibody testing. HbA1c, parent with diabetes, and absence of polyuria were significant independent predictors of MODY. The model showed excellent discrimination (c-statistic = 0.963) and calibrated well (Brier score = 0.01). MODY probability > 1.3% (ie. above background prevalence) had similar performance to being negative for all 3 antibodies (positive predictive value (PPV) = 10% v 11% respectively i.e. ~ 1 in 10 positive test rate). Probability > 1.3% and negative for 3 islet autoantibodies narrowed down to 4% of the cohort, and detected 96% of MODY cases (PPV = 31%). This MODY calculator for paediatric patients at time of diabetes diagnosis will help target genetic testing to those most likely to benefit, to get the right diagnosis.
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Affiliation(s)
- Beverley M Shields
- The Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK.
| | | | - Kashyap Patel
- The Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Julieanne Knupp
- The Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Akaal Kaur
- Faculty of Medicine, Imperial College London, London, UK
| | - Des Johnston
- Faculty of Medicine, Imperial College London, London, UK
| | - Kevin Colclough
- Exeter Genomics Laboratory, The Royal Devon University Healthcare NHS Foundation Trust, Exeter, UK
| | - Helena Elding Larsson
- Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Department of Pediatrics, Skånes University Hospital, Malmö, Sweden
| | - Gun Forsander
- Department of Paediatrics, Institute for Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Region Västra Götaland, Department of Paediatrics, Sahlgrenska University Hospital, Queen Silvia Children's Hospital, Gothenburg, Sweden
| | - Ulf Samuelsson
- Crown Princess Victoria Children's Hospital and Division of Pediatrics, Linköping University, Linköping, Sweden
| | - Andrew Hattersley
- The Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Johnny Ludvigsson
- Crown Princess Victoria Children's Hospital and Division of Pediatrics, Linköping University, Linköping, Sweden.
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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: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [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%.
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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
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Thuesen ACB, Jensen RT, Maagensen H, Kristiansen MR, Sørensen HT, Vaag A, Beck-Nielsen H, Pedersen OB, Grarup N, Nielsen JS, Rungby J, Gjesing AP, Storgaard H, Vilsbøll T, Hansen T. Identification of pathogenic GCK variants in patients with common type 2 diabetes can lead to discontinuation of pharmacological treatment. Mol Genet Metab Rep 2023; 35:100972. [PMID: 37008541 PMCID: PMC10063379 DOI: 10.1016/j.ymgmr.2023.100972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 03/24/2023] [Accepted: 03/25/2023] [Indexed: 03/31/2023] Open
Abstract
Background Functionally disruptive variants in the glucokinase gene (GCK) cause a form of mild non-progressive hyperglycemia, which does not require pharmacological treatment. A substantial proportion of patients with type 2 diabetes (T2D) carry GCK variants. We aimed to investigate whether carriers of rare GCK variants diagnosed with T2D have a glycemic phenotype and treatment response consistent with GCK-diabetes. Methods Eight patients diagnosed with T2D from the Danish DD2 cohort who had previously undergone sequencing of GCK participated. Clinical examinations at baseline included an oral glucose tolerance test and continuous glucose monitoring. Carriers with a glycemic phenotype consistent with GCK-diabetes took part in a three-month treatment withdrawal. Results Carriers of pathogenic and likely pathogenic variants had lower median fasting glucose and C-peptide levels compared to carriers of variants of uncertain significance and benign variants (median fasting glucose: 7.3 (interquartile range: 0.4) mmol/l vs. 9.5 (1.6) mmol/l, p = 0.04; median fasting C-peptide 902 (85) pmol/l vs. 1535 (295) pmol/l, p = 0.03). Four participants who discontinued metformin treatment and one diet-treated participant were reevaluated after three months. There was no deterioration of HbA1c or fasting glucose (median baseline HbA1c: 49 (3) vs. 51 (6) mmol/mol after three months, p = 0.4; median baseline fasting glucose: 7.3 (0.4) mmol/l vs. 7.0 (0.6) mmol/l after three months, p = 0.5). Participants did not consistently fulfill best practice guidelines for GCK screening nor clinical criteria for monogenic diabetes. Discussion Carriers of pathogenic or likely pathogenic GCK variants identified by unselected screening in T2D should be reported, as they have a glycemic phenotype and treatment response consistent with GCK-diabetes. Variants of uncertain significance should be interpreted with care. Systematic genetic screening of patients with common T2D receiving routine care can lead to the identification and precise care of patients with misclassified GCK-diabetes who are not identifiable through common genetic screening criteria.
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Affiliation(s)
- Anne Cathrine Baun Thuesen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Clinical Research, Copenhagen University Hospital – Steno Diabetes Center Copenhagen, Herlev, Denmark
| | - Rasmus Tanderup Jensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Henrik Maagensen
- Clinical Research, Copenhagen University Hospital – Steno Diabetes Center Copenhagen, Herlev, Denmark
| | - Maja Refshauge Kristiansen
- Steno Diabetes Center Odense, the Danish Centre for Strategic Research in Type 2 Diabetes (DD2), Odense University Hospital, Odense, Denmark
| | - Henrik Toft Sørensen
- Department of Clinical Epidemiology, Aarhus University Hospital and Aarhus University, Aarhus, Denmark
| | - Allan Vaag
- Clinical Research, Copenhagen University Hospital – Steno Diabetes Center Copenhagen, Herlev, Denmark
- Department for Translational Type 2 Diabetes Research, Lund University Diabetes Center, Lund University, Sweden
| | - Henning Beck-Nielsen
- Steno Diabetes Center Odense, the Danish Centre for Strategic Research in Type 2 Diabetes (DD2), Odense University Hospital, Odense, Denmark
| | - Oluf B. Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jens Steen Nielsen
- Steno Diabetes Center Odense, the Danish Centre for Strategic Research in Type 2 Diabetes (DD2), Odense University Hospital, Odense, Denmark
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Jørgen Rungby
- Clinical Research, Copenhagen University Hospital – Steno Diabetes Center Copenhagen, Herlev, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Anette Prior Gjesing
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Heidi Storgaard
- Clinical Research, Copenhagen University Hospital – Steno Diabetes Center Copenhagen, Herlev, Denmark
| | - Tina Vilsbøll
- Clinical Research, Copenhagen University Hospital – Steno Diabetes Center Copenhagen, Herlev, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Corresponding author at: Blegdamsvej 3B, 07-8, 2200 København N, Denmark.
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10
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Samadli S, Zhou Q, Zheng B, Gu W, Zhang A. From glucose sensing to exocytosis: takes from maturity onset diabetes of the young. Front Endocrinol (Lausanne) 2023; 14:1188301. [PMID: 37255971 PMCID: PMC10226665 DOI: 10.3389/fendo.2023.1188301] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Accepted: 04/28/2023] [Indexed: 06/01/2023] Open
Abstract
Monogenic diabetes gave us simplified models of complex molecular processes occurring within β-cells, which allowed to explore the roles of numerous proteins from single protein perspective. Constellation of characteristic phenotypic features and wide application of genetic sequencing techniques to clinical practice, made the major form of monogenic diabetes - the Maturity Onset Diabetes of the Young to be distinguishable from type 1, type 2 as well as neonatal diabetes mellitus and understanding underlying molecular events for each type of MODY contributed to the advancements of antidiabetic therapy and stem cell research tremendously. The functional analysis of MODY-causing proteins in diabetes development, not only provided better care for patients suffering from diabetes, but also enriched our comprehension regarding the universal cellular processes including transcriptional and translational regulation, behavior of ion channels and transporters, cargo trafficking, exocytosis. In this review, we will overview structure and function of MODY-causing proteins, alterations in a particular protein arising from the deleterious mutations to the corresponding gene and their consequences, and translation of this knowledge into new treatment strategies.
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Affiliation(s)
- Sama Samadli
- Nanjing Key Laboratory of Pediatrics, Children’s Hospital of Nanjing Medical University, Nanjing, China
- Department of Pediatric Diseases II, Azerbaijan Medical University, Baku, Azerbaijan
| | - Qiaoli Zhou
- Department of Endocrinology, Children’s Hospital of Nanjing Medical University, Nanjing, China
| | - Bixia Zheng
- Nanjing Key Laboratory of Pediatrics, Children’s Hospital of Nanjing Medical University, Nanjing, China
| | - Wei Gu
- Department of Endocrinology, Children’s Hospital of Nanjing Medical University, Nanjing, China
| | - Aihua Zhang
- Nanjing Key Laboratory of Pediatrics, Children’s Hospital of Nanjing Medical University, Nanjing, China
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11
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Noohi F, Sundaresan MS, Naylor RN, Ross LF. Diagnosis, treatment and disclosure: A qualitative exploration of participant challenges in a Monogenic Diabetes Registry. Genet Med 2023; 25:100019. [PMID: 36681871 PMCID: PMC10620612 DOI: 10.1016/j.gim.2023.100019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 01/11/2023] [Accepted: 01/12/2023] [Indexed: 01/22/2023] Open
Abstract
PURPOSE Maturity-onset diabetes of the young (MODY) represents a heterogenous group of monogenic diabetes. Despite its autosomal dominant inheritance, many MODY participants in the University of Chicago Monogenic Diabetes Registry have no family members enrolled. We aimed to gather data on the Registry participants' experiences in (1) receipt of an accurate diagnosis, (2) decisions regarding disclosure of their MODY genetic test results with biological relatives, and (3) recommendations toward our Registry's processes and outreach. METHODS We conducted 20 one-on-one semistructured interviews with adult Registry participants. RESULTS All participants found navigating the health care system challenging because of the providers' unfamiliarity with MODY and dismissal of its importance post diagnosis. All had shared their results with at least 1 relative, however many found their relatives resistant to engaging with their providers. Participants wanted to receive targeted information on their condition and connect with other participants who have faced similar diagnostic and treatment challenges. CONCLUSION Our results demonstrate that our probands faced resistance to reclassification of their diabetes from both health care providers and relatives. In an effort to improve cascade testing, the Registry is designing a portal to facilitate participant-research team communication and provide additional supports for participants to involve family members in testing.
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Affiliation(s)
- Forough Noohi
- Department of Medicine, The University of Chicago, Chicago, IL.
| | | | - Rochelle N Naylor
- Department of Medicine, The University of Chicago, Chicago, IL; Department of Pediatrics, The University of Chicago, Chicago, IL
| | - Lainie Friedman Ross
- Department of Medicine, The University of Chicago, Chicago, IL; Department of Pediatrics, The University of Chicago, Chicago, IL
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12
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Santos Monteiro S, da Silva Santos T, Fonseca L, Assunção G, Lopes AM, Duarte DB, Soares AR, Laranjeira F, Ribeiro I, Pinto E, Rocha S, Barbosa Gouveia S, Vazquez-Mosquera ME, Oliveira MJ, Borges T, Cardoso MH. Maturity-onset diabetes of the young in a large Portuguese cohort. Acta Diabetol 2023; 60:83-91. [PMID: 36208343 DOI: 10.1007/s00592-022-01980-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 09/22/2022] [Indexed: 01/07/2023]
Abstract
AIMS Monogenic forms of diabetes that develop with autosomal dominant inheritance are classically aggregated in the Maturity-Onset Diabetes of the Young (MODY) categories. Despite increasing awareness, its true prevalence remains largely underestimated. We describe a Portuguese cohort of individuals with suspected monogenic diabetes who were genetically evaluated for MODY-causing genes. METHODS This single-center retrospective cohort study enrolled patients with positive genetic testing for MODY between 2015 and 2021. Automatic sequencing and, in case of initial negative results, next-generation sequencing were performed. Their clinical and molecular characteristics were described. RESULTS Eighty individuals were included, 55 with likely pathogenic/pathogenic variants in one of the MODY genes and 25 MODY-positive family members, identified by cascade genetic testing. The median age at diabetes diagnosis was 23 years, with a median HbA1c of 6.5%. The most frequently mutated genes were identified in HNF1A (40%), GCK (34%) and HNF4A (13%), followed by PDX1, HNF1B, INS, KCNJ11 and APPL1. Thirty-six unique variants were found (29 missense and 7 frameshift variants), of which ten (28%) were novel. CONCLUSIONS Our data highlights the importance of genetic testing in the diagnosis of MODY and the establishment of its subtypes, leading to more personalized treatment and follow-up strategies.
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Affiliation(s)
- Sílvia Santos Monteiro
- Division of Endocrinology, Diabetes and Metabolism, Centro Hospitalar Universitário do Porto, Largo Professor Abel Salazar, 4099-001, Porto, Portugal.
| | - Tiago da Silva Santos
- Division of Endocrinology, Diabetes and Metabolism, Centro Hospitalar Universitário do Porto, Largo Professor Abel Salazar, 4099-001, Porto, Portugal
| | - Liliana Fonseca
- Division of Endocrinology, Diabetes and Metabolism, Centro Hospitalar Universitário do Porto, Largo Professor Abel Salazar, 4099-001, Porto, Portugal
| | - Guilherme Assunção
- Division of Endocrinology, Diabetes and Metabolism, Centro Hospitalar Universitário do Porto, Largo Professor Abel Salazar, 4099-001, Porto, Portugal
| | - Ana M Lopes
- Division of Endocrinology, Diabetes and Metabolism, Centro Hospitalar Universitário do Porto, Largo Professor Abel Salazar, 4099-001, Porto, Portugal
| | - Diana B Duarte
- Division of Endocrinology, Diabetes and Metabolism, Centro Hospitalar Universitário do Porto, Largo Professor Abel Salazar, 4099-001, Porto, Portugal
| | - Ana Rita Soares
- Division of Medical Genetics, Centro de Genética Médica Doutor Jacinto Magalhães, Centro Hospitalar Universitário do Porto, Porto, Portugal
| | - Francisco Laranjeira
- Division of Genetic Biochemistry. Centro de Genética Médica Doutor Jacinto Magalhães, Centro Hospitalar Universitário do Porto, Porto, Portugal
- Unit for Multidisciplinar Biomedical Research (UMIB), Instituto de Ciências Biomédicas Abel Salazar. Universidade do Porto, Porto, Portugal
| | - Isaura Ribeiro
- Division of Genetic Biochemistry. Centro de Genética Médica Doutor Jacinto Magalhães, Centro Hospitalar Universitário do Porto, Porto, Portugal
- Unit for Multidisciplinar Biomedical Research (UMIB), Instituto de Ciências Biomédicas Abel Salazar. Universidade do Porto, Porto, Portugal
| | - Eugénia Pinto
- Division of Genetic Biochemistry. Centro de Genética Médica Doutor Jacinto Magalhães, Centro Hospitalar Universitário do Porto, Porto, Portugal
| | - Sónia Rocha
- Division of Genetic Biochemistry. Centro de Genética Médica Doutor Jacinto Magalhães, Centro Hospitalar Universitário do Porto, Porto, Portugal
| | - Sofia Barbosa Gouveia
- University Clinical Hospital of Santiago de Compostela. IDIS, CIBERER, MetabERN, 15701, Santiago de Compostela, Spain
| | | | - Maria João Oliveira
- Division of Pediatric Endocrinology. Department of Pediatrics. Centro Materno-Infantil do Norte, Centro Hospitalar Universitário do Porto, Porto, Portugal
| | - Teresa Borges
- Division of Pediatric Endocrinology. Department of Pediatrics. Centro Materno-Infantil do Norte, Centro Hospitalar Universitário do Porto, Porto, Portugal
| | - Maria Helena Cardoso
- Division of Endocrinology, Diabetes and Metabolism, Centro Hospitalar Universitário do Porto, Largo Professor Abel Salazar, 4099-001, Porto, Portugal
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13
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Harrington F, Greenslade M, Colclough K, Paul R, Jefferies C, Murphy R. Monogenic diabetes in New Zealand - An audit based revision of the monogenic diabetes genetic testing pathway in New Zealand. Front Endocrinol (Lausanne) 2023; 14:1116880. [PMID: 37033247 PMCID: PMC10080040 DOI: 10.3389/fendo.2023.1116880] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 02/20/2023] [Indexed: 04/11/2023] Open
Abstract
AIMS To evaluate (a) the diagnostic yield of genetic testing for monogenic diabetes when using single gene and gene panel-based testing approaches in the New Zealand (NZ) population, (b) whether the MODY (Maturity Onset Diabetes of the Young) pre-test probability calculator can be used to guide referrals for testing in NZ, (c) the number of referrals for testing for Māori/Pacific ethnicities compared to NZ European, and (d) the volume of proband vs cascade tests being requested. METHODS A retrospective audit of 495 referrals, from NZ, for testing of monogenic diabetes genes was performed. Referrals sent to LabPlus (Auckland) laboratory for single gene testing or small multi-gene panel testing, or to the Exeter Genomics Laboratory, UK, for a large gene panel, received from January 2014 - December 2021 were included. Detection rates of single gene, small multi-gene and large gene panels (neonatal and non-neonatal), and cascade testing were analysed. Pre-test probability was calculated using the Exeter MODY probability calculator and ethnicity data was also collected. RESULTS The diagnostic detection rate varied across genes, from 32% in GCK, to 2% in HNF4A, with single gene or small gene panel testing averaging a 12% detection rate. Detection rate by type of panel was 9% for small gene panel, 23% for non-neonatal monogenic diabetes large gene panel and 40% for neonatal monogenic diabetes large gene panel. 45% (67/147) of patients aged 1-35 years at diabetes diagnosis scored <20% on MODY pre-test probability, of whom 3 had class 4/5 variants in HNF1A, HNF4A or HNF1B. Ethnicity data of those selected for genetic testing correlated with population diabetes prevalence for Māori (15% vs 16%), but Pacific People appeared under-represented (8% vs 14%). Only 1 in 6 probands generated a cascade test. CONCLUSIONS A new monogenic diabetes testing algorithm for NZ is proposed, which directs clinicians to choose a large gene panel in patients without syndromic features who score a pre-test MODY probability of above 20%.
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Affiliation(s)
- Francesca Harrington
- Diagnostic Genetics, Department of Pathology and Laboratory Medicine, Te Whatu Ora – Health New Zealand, Te Toka Tumai Auckland, Auckland, New Zealand
- *Correspondence: Francesca Harrington, ; Rinki Murphy,
| | - Mark Greenslade
- Diagnostic Genetics, Department of Pathology and Laboratory Medicine, Te Whatu Ora – Health New Zealand, Te Toka Tumai Auckland, Auckland, New Zealand
| | - Kevin Colclough
- Exeter Genomics Laboratory, Royal Devon University Healthcare National Health Service (NHS) Foundation Trust, Exeter, United Kingdom
| | - Ryan Paul
- Te Huataki Waiora School of Health, University of Waikato, Hamilton, New Zealand
| | - Craig Jefferies
- Starship Children’s Health, Te Whatu Ora – Health New Zealand, Te Toka Tumai Auckland, Auckland, New Zealand
- The Liggins Institute, The University of Auckland, Auckland, New Zealand
| | - Rinki Murphy
- Department of Medicine, University of Auckland, Auckland, New Zealand
- *Correspondence: Francesca Harrington, ; Rinki Murphy,
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14
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Rapini N, Patera PI, Schiaffini R, Ciampalini P, Pampanini V, Cristina MM, Deodati A, Bracaglia G, Porzio O, Ruta R, Novelli A, Mucciolo M, Cianfarani S, Barbetti F. Monogenic diabetes clinic (MDC): 3-year experience. Acta Diabetol 2023; 60:61-70. [PMID: 36178555 PMCID: PMC9813184 DOI: 10.1007/s00592-022-01972-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Accepted: 09/06/2022] [Indexed: 01/29/2023]
Abstract
AIM In the pediatric diabetes clinic, patients with type 1 diabetes mellitus (T1D) account for more than 90% of cases, while monogenic forms represent about 6%. Many monogenic diabetes subtypes may respond to therapies other than insulin and have chronic diabetes complication prognosis that is different from T1D. With the aim of providing a better diagnostic pipeline and a tailored care for patients with monogenic diabetes, we set up a monogenic diabetes clinic (MDC). METHODS In the first 3 years of activity 97 patients with non-autoimmune forms of hyperglycemia were referred to MDC. Genetic testing was requested for 80 patients and 68 genetic reports were available for review. RESULTS In 58 subjects hyperglycemia was discovered beyond 1 year of age (Group 1) and in 10 before 1 year of age (Group 2). Genetic variants considered causative of hyperglycemia were identified in 25 and 6 patients of Group 1 and 2, respectively, with a pick up rate of 43.1% (25/58) for Group 1 and 60% (6/10) for Group 2 (global pick-up rate: 45.5%; 31/68). When we considered probands of Group 1 with a parental history of hyperglycemia, 58.3% (21/36) had a positive genetic test for GCK or HNF1A genes, while pick-up rate was 18.1% (4/22) in patients with mute family history for diabetes. Specific treatments for each condition were administered in most cases. CONCLUSION We conclude that MDC may contribute to provide a better diabetes care in the pediatric setting.
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Affiliation(s)
- Novella Rapini
- Diabetology and Growth Disorders Unit, Bambino Gesù Children's Hospital, IRCCS, 00164, Rome, Italy
| | - Patrizia I Patera
- Diabetology and Growth Disorders Unit, Bambino Gesù Children's Hospital, IRCCS, 00164, Rome, Italy
| | - Riccardo Schiaffini
- Diabetology and Growth Disorders Unit, Bambino Gesù Children's Hospital, IRCCS, 00164, Rome, Italy
| | - Paolo Ciampalini
- Diabetology and Growth Disorders Unit, Bambino Gesù Children's Hospital, IRCCS, 00164, Rome, Italy
| | - Valentina Pampanini
- Diabetology and Growth Disorders Unit, Bambino Gesù Children's Hospital, IRCCS, 00164, Rome, Italy
| | - Matteoli M Cristina
- Diabetology and Growth Disorders Unit, Bambino Gesù Children's Hospital, IRCCS, 00164, Rome, Italy
| | - Annalisa Deodati
- Diabetology and Growth Disorders Unit, Bambino Gesù Children's Hospital, IRCCS, 00164, Rome, Italy
| | - Giorgia Bracaglia
- Clinical Laboratory Unit, Bambino Gesù Children's Hospital, Piazza S Onofrio 4, 00165, Rome, Italy
| | - Ottavia Porzio
- Clinical Laboratory Unit, Bambino Gesù Children's Hospital, Piazza S Onofrio 4, 00165, Rome, Italy
- Department of Experimental Medicine, Univerisity of Rome 'Tor Vergata', 00131, Rome, Italy
| | - Rosario Ruta
- Translational Cytogenomics Research Unit, Bambino Gesù Children's Hospital, IRCCS, 00146, Rome, Italy
| | - Antonio Novelli
- Translational Cytogenomics Research Unit, Bambino Gesù Children's Hospital, IRCCS, 00146, Rome, Italy
| | - Mafalda Mucciolo
- Translational Cytogenomics Research Unit, Bambino Gesù Children's Hospital, IRCCS, 00146, Rome, Italy
| | - Stefano Cianfarani
- Diabetology and Growth Disorders Unit, Bambino Gesù Children's Hospital, IRCCS, 00164, Rome, Italy
- Department of Systems Medicine, University of Rome 'Tor Vergata', 00131, Rome, Italy
- Department of Women's and Children's Health, Karolinska Institutet, 17177, Stockholm, Sweden
| | - Fabrizio Barbetti
- Clinical Laboratory Unit, Bambino Gesù Children's Hospital, Piazza S Onofrio 4, 00165, Rome, Italy.
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15
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Yorifuji T, Watanabe Y, Kitayama K, Yamada Y, Higuchi S, Mori J, Kato M, Takahashi T, Okuda T, Aoyama T. Targeted gene panel analysis of Japanese patients with maturity-onset diabetes of the young-like diabetes mellitus: Roles of inactivating variants in the ABCC8 and insulin resistance genes. J Diabetes Investig 2022; 14:387-403. [PMID: 36504295 PMCID: PMC9951579 DOI: 10.1111/jdi.13957] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 10/23/2022] [Accepted: 11/24/2022] [Indexed: 12/14/2022] Open
Abstract
AIMS/INTRODUCTION To investigate the genetic background of Japanese patients with suspected maturity-onset diabetes of the young (MODY). MATERIALS AND METHODS On 340 proband patients referred from across Japan, genomic variants were analyzed using a targeted multigene panel analysis combined with the multiplex ligation probe amplification (MLPA) analysis, mitochondrial m.3243A > G analysis and methylation-specific polymerase chain reaction of the imprinted 6q24 locus. Pathogenic/likely pathogenic variants were listed according to the 2015 American College of Medical Genetics and Genomics and the Association for Molecular Pathology criteria. Additionally, variants with a population frequency <0.001 and Combined Annotation Dependent Depletion score >20 (CS >20) were listed as rare variants of uncertain significance-CS >20. RESULTS A total of 157 pathogenic/likely pathogenic variants and 44 rare variants of uncertain significance-CS >20 were identified. In the pathogenic/likely pathogenic variants, alterations in the GCK gene were the most common (82, 52.2%) followed by HNF1A (29, 18.5%), HNF4A (13, 8.3%) and HNF1B (13, 8.3%). One patient was a 29.5% mosaic with a truncating INSR variant. In the rare variants of uncertain significance-CS >20, 20 (45.5%) were in the genes coding for the adenosine triphosphate-sensitive potassium channel, KCNJ11 or ABCC8, and four were in the genes of the insulin-signaling pathway, INSR and PIK3R1. Four variants in ABCC8 were previously reported in patients with congenital hyperinsulinism, suggesting the inactivating nature of these variants, and at least two of our patients had a history of congenital hyperinsulinism evolving into diabetes. In two patients with INSR or PIK3R1 variants, insulin resistance was evident at diagnosis. CONCLUSIONS Causative genomic variants could be identified in at least 46.2% of clinically suspected MODY patients. ABCC8-MODY with inactivating variants could represent a distinct category of MODY. Genes of insulin resistance should be included in the sequencing panel for MODY.
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Affiliation(s)
- Tohru Yorifuji
- Division of Pediatric Endocrinology and MetabolismChildren's Medical Center, Osaka City General HospitalOsakaJapan,Department of Genetic MedicineOsaka City General HospitalOsakaJapan,Clinical Research CenterOsaka City General HospitalOsakaJapan,2nd Department of Internal MedicineDate Red Cross HospitalDate, HokkaidoJapan
| | - Yoh Watanabe
- Division of Pediatric Endocrinology and MetabolismChildren's Medical Center, Osaka City General HospitalOsakaJapan
| | - Kana Kitayama
- Division of Pediatric Endocrinology and MetabolismChildren's Medical Center, Osaka City General HospitalOsakaJapan
| | - Yuki Yamada
- Division of Pediatric Endocrinology and MetabolismChildren's Medical Center, Osaka City General HospitalOsakaJapan
| | - Shinji Higuchi
- Division of Pediatric Endocrinology and MetabolismChildren's Medical Center, Osaka City General HospitalOsakaJapan
| | - Jun Mori
- Division of Pediatric Endocrinology and MetabolismChildren's Medical Center, Osaka City General HospitalOsakaJapan
| | - Masaru Kato
- Department of Genetic MedicineOsaka City General HospitalOsakaJapan
| | - Toru Takahashi
- Department of Genetic MedicineOsaka City General HospitalOsakaJapan
| | - Tokuko Okuda
- Clinical Research CenterOsaka City General HospitalOsakaJapan
| | - Takane Aoyama
- Clinical Research CenterOsaka City General HospitalOsakaJapan
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16
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Mirshahi UL, Colclough K, Wright CF, Wood AR, Beaumont RN, Tyrrell J, Laver TW, Stahl R, Golden A, Goehringer JM, Frayling TF, Hattersley AT, Carey DJ, Weedon MN, Patel KA. Reduced penetrance of MODY-associated HNF1A/HNF4A variants but not GCK variants in clinically unselected cohorts. Am J Hum Genet 2022; 109:2018-2028. [PMID: 36257325 PMCID: PMC9674944 DOI: 10.1016/j.ajhg.2022.09.014] [Citation(s) in RCA: 45] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 09/28/2022] [Indexed: 01/26/2023] Open
Abstract
The true prevalence and penetrance of monogenic disease variants are often not known because of clinical-referral ascertainment bias. We comprehensively assess the penetrance and prevalence of pathogenic variants in HNF1A, HNF4A, and GCK that account for >80% of monogenic diabetes. We analyzed clinical and genetic data from 1,742 clinically referred probands, 2,194 family members, clinically unselected individuals from a US health system-based cohort (n = 132,194), and a UK population-based cohort (n = 198,748). We show that one in 1,500 individuals harbor a pathogenic variant in one of these genes. The penetrance of diabetes for HNF1A and HNF4A pathogenic variants was substantially lower in the clinically unselected individuals compared to clinically referred probands and was dependent on the setting (32% in the population, 49% in the health system cohort, 86% in a family member, and 98% in probands for HNF1A). The relative risk of diabetes was similar across the clinically unselected cohorts highlighting the role of environment/other genetic factors. Surprisingly, the penetrance of pathogenic GCK variants was similar across all cohorts (89%-97%). We highlight that pathogenic variants in HNF1A, HNF4A, and GCK are not ultra-rare in the population. For HNF1A and HNF4A, we need to tailor genetic interpretation and counseling based on the setting in which a pathogenic monogenic variant was identified. GCK is an exception with near-complete penetrance in all settings. This along with the clinical implication of diagnosis makes it an excellent candidate for the American College of Medical Genetics secondary gene list.
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Affiliation(s)
| | - Kevin Colclough
- Molecular Genetics, Royal Devon and Exeter NHS Foundation Trust, Exeter, UK
| | - Caroline F Wright
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, UK
| | - Andrew R Wood
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, UK
| | - Robin N Beaumont
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, UK
| | - Jessica Tyrrell
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, UK
| | - Thomas W Laver
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, UK
| | - Richard Stahl
- Geisinger Clinic, Geisinger Health System, Danville, PA, USA
| | - Alicia Golden
- Geisinger Clinic, Geisinger Health System, Danville, PA, USA
| | | | - Timothy F Frayling
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, UK
| | - Andrew T Hattersley
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, UK
| | - David J Carey
- Geisinger Clinic, Geisinger Health System, Danville, PA, USA
| | - Michael N Weedon
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, UK.
| | - Kashyap A Patel
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Exeter, UK.
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17
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Surendran A, Brackenridge A, White SL. Window of opportunity: screening for
GCK
monogenic diabetes in the antenatal diabetes clinic. PRACTICAL DIABETES 2022. [DOI: 10.1002/pdi.2427] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Affiliation(s)
- Aarthi Surendran
- Consultant in Diabetes and Endocrinology, University Hospital Lewisham, Lewisham and Greenwich NHS Trust London UK
| | - Anna Brackenridge
- Consultant, Department of Diabetes and Endocrinology, Guy's and St Thomas’ Hospitals NHS Foundation Trust London UK
| | - Sara L White
- Clinician Scientist, Department of Women and Children's Health, King's College London; Honorary Consultant in Metabolic Medicine (Clinical Biochemistry), Guy's and St Thomas’ Hospitals NHS Foundation Trust London UK
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18
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Schlegel A, Petersen WC, Holbrook AA, Iverson LK, Graham TE. A Novel INS Mutation in the C-Peptide Region Causing Hyperproinsulinemic Maturity Onset Diabetes of Youth Type 10. Lab Med 2022; 54:327-332. [PMID: 36242597 DOI: 10.1093/labmed/lmac115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
Abstract
Monogenetic diabetes mellitus (DM) describes a collection of single-gene diseases marked by hyperglycemia presenting in childhood or adulthood and the absence of immunological markers of type 1 DM. Mutations in the human insulin gene INS give rise to two separate clinical syndromes: permanent neonatal DM, type 4 (PNDM4), and maturity-onset diabetes of youth, type 10 (MODY10); the former presents shortly after birth and the latter presents in childhood and adulthood. We describe a 40-year-old man in a kindred with high prevalence of DM who presented with severe hyperglycemia but not ketoacidosis or hypertriglyceridemia. Twelve years after initial presentation, the patient had elevated proinsulin and normal plasma C-peptide when nearly euglycemic on treatment with insulin glargine. A novel INS mutation, Gln65Arg, within the C-peptide region was identified. The INS (p.Gln65Arg) mutation may cause MODY10 by disrupting proinsulin maturation.
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Affiliation(s)
- Amnon Schlegel
- Diabetes and Endocrine Treatment Specialists , Sandy, UT , USA
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