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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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Liu T, Sankareswaran A, Paterson G, Fraser DP, Hodgson S, Huang QQ, Heng TH, Ladwa M, Thomas N, van Heel DA, Weedon MN, Yajnik CS, Oram RA, Chandak GR, Martin HC, Finer S. Investigating misclassification of type 1 diabetes in a population-based cohort of British Pakistanis and Bangladeshis using polygenic risk scores. Sci Rep 2025; 15:1168. [PMID: 39805939 PMCID: PMC11729895 DOI: 10.1038/s41598-024-80348-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2024] [Accepted: 11/18/2024] [Indexed: 01/30/2025] Open
Abstract
Correct classification of type 1 (T1D) and type 2 diabetes (T2D) is challenging due to overlapping clinical features and the increasingly early onset of T2D, particularly in South Asians. Polygenic risk scores (PRSs) for T1D and T2D have been shown to work relatively well in South Asians, despite being derived from largely European-ancestry samples. Here we used PRSs to investigate the rate of potential misclassification of diabetes amongst British Bangladeshis and Pakistanis. Using linked health records from the Genes & Health cohort (n = 38,344) we defined two reference groups meeting stringent diagnostic criteria: 31 T1D cases, 1842 T2D cases, and after excluding these, two further groups: 839 insulin-treated diabetic individuals with ambiguous features and 5174 non-diabetic controls. Combining these with 307 confirmed T1D cases and 307 controls from India, we calculated ancestry-corrected PRSs for T1D and T2D, with which we estimated the proportion of T1D cases within the ambiguous group at ~ 6%, dropping to ~ 4.5% within the subset who had T2D codes in their health records (and are thus most likely to have been misclassified). We saw no significant association between the T1D or T2D PRS and BMI at diagnosis, time to insulin, or the presence of T1D or T2D diagnostic codes amongst the T2D or ambiguous cases, suggesting that these clinical features are not particularly helpful for aiding diagnosis in ambiguous cases. Our results emphasise that robust identification of T1D cases and appropriate clinical care may require routine measurement of diabetes autoantibodies and C-peptide.
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Affiliation(s)
- Timing Liu
- Wellcome Trust Sanger Institute, Saffron Walden, UK
| | - Alagu Sankareswaran
- Genomic Research on Complex diseases Group (GRC-Group), CSIR-Centre for Cellular and Molecular Biology, Hyderabad, India
- Academy of Scientific and Innovative Research, Ghaziabad, India
| | - Gordon Paterson
- Wolfson Institute of Population Health, Queen Mary University of London, London, UK
- Barts Health NHS Trust, London, UK
| | | | - Sam Hodgson
- Wolfson Institute of Population Health, Queen Mary University of London, London, UK
| | | | | | - Meera Ladwa
- Wolfson Institute of Population Health, Queen Mary University of London, London, UK
- Blizard Institute, Queen Mary University of London, London, UK
| | | | | | | | | | | | - Giriraj R Chandak
- Genomic Research on Complex diseases Group (GRC-Group), CSIR-Centre for Cellular and Molecular Biology, Hyderabad, India
- Academy of Scientific and Innovative Research, Ghaziabad, India
| | | | - Sarah Finer
- Wolfson Institute of Population Health, Queen Mary University of London, London, UK.
- Barts Health NHS Trust, London, UK.
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Alarcon G, Nguyen A, Jones A, Shields B, Redondo MJ, Tosur M. The Maturity-Onset Diabetes of the Young (MODY) Calculator Overestimates MODY Probability in Hispanic Youth. J Clin Endocrinol Metab 2024:dgae770. [PMID: 39492690 DOI: 10.1210/clinem/dgae770] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2024] [Revised: 10/15/2024] [Accepted: 10/31/2024] [Indexed: 11/05/2024]
Abstract
CONTEXT The applicability of the MODY risk calculator (Shields et al) to non- White European populations remains unknown. OBJECTIVE We aimed to test its real-world application in Hispanic youth. METHODS We conducted a retrospective chart review of Hispanic youth (<23 years) with diabetes (n=2033) in a large pediatric tertiary care center in the U.S. We calculated MODY probability for all subjects, splitting them into two cohorts based on the original model: Individuals who were started on insulin within 6 months of diabetes diagnosis (Cohort 1) and those who were not (Cohort 2). RESULTS Cohort 1 consisted of 1566 individuals (median age [25p, 75p]: 16 [13, 19] years, 49% female), while Cohort 2 comprised 467 youth (median age [25p, 75p]: 17 [15, 20] years, 62% female). The mean MODY probability was 5.9% and 61.9% in Cohort 1 and Cohort 2, respectively. The mean probability for both cohorts combined was 18.8% suggesting an expected 382 individuals with MODY, which is much higher than previous estimations (1-5%; i.e. 20-102 individuals in this cohort). A total of 18 individuals tested positive for MODY among the limited number of individuals tested based on clinical suspicion and genetic testing availability (n=44 out of 2033 tested, [2.2% of overall cohort]). CONCLUSIONS The MODY risk calculator likely overestimates the probability of MODY in Hispanic youth, largely driven by an overestimation in those not early-insulin treated (predominantly young-onset type 2 diabetes). The calculator needs updating to improve its applicability in this population. In addition, further research to help better identify MODY in Hispanic youth.
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Affiliation(s)
- Guido Alarcon
- Department of Pediatrics, The Division of Diabetes and Endocrinology, Baylor College of Medicine, Texas Children's Hospital, Houston, TX, USA
| | - Anh Nguyen
- Department of Pediatrics, The Division of Diabetes and Endocrinology, Baylor College of Medicine, Texas Children's Hospital, Houston, TX, USA
| | - Angus Jones
- Exeter Centre of Excellence in Diabetes (EXCEED), University of Exeter Medical School, Exeter, UK
| | - Beverley Shields
- Exeter Centre of Excellence in Diabetes (EXCEED), University of Exeter Medical School, Exeter, UK
| | - Maria J Redondo
- Department of Pediatrics, The Division of Diabetes and Endocrinology, Baylor College of Medicine, Texas Children's Hospital, Houston, TX, USA
| | - Mustafa Tosur
- Department of Pediatrics, The Division of Diabetes and Endocrinology, Baylor College of Medicine, Texas Children's Hospital, Houston, TX, USA
- Children's Nutrition Research Center, USDA/ARS, Houston, TX, USA
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De Sousa SMC, Wu KHC, Colclough K, Rawlings L, Dubowsky A, Monnik M, Poplawski N, Scott HS, Horowitz M, Torpy DJ. Identification of monogenic diabetes in an Australian cohort using the Exeter maturity-onset diabetes of the young (MODY) probability calculator and next-generation sequencing gene panel testing. Acta Diabetol 2024; 61:181-188. [PMID: 37812285 PMCID: PMC10866744 DOI: 10.1007/s00592-023-02193-x] [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: 07/10/2023] [Accepted: 09/20/2023] [Indexed: 10/10/2023]
Abstract
AIMS This study aims to describe the prevalence of monogenic diabetes in an Australian referral cohort, in relation to Exeter maturity-onset diabetes of the young (MODY) probability calculator (EMPC) scores and next-generation sequencing with updated testing where relevant. METHODS State-wide 5-year retrospective cohort study of individuals referred for monogenic diabetes genetic testing. RESULTS After excluding individuals who had cascade testing for a familial variant (21) or declined research involvement (1), the final cohort comprised 40 probands. Incorporating updated testing, the final genetic result was positive (likely pathogenic/pathogenic variant) in 11/40 (27.5%), uncertain (variant of uncertain significance) in 8/40 (20%) and negative in 21/40 (52.5%) participants. Causative variants were found in GCK, HNF1A, MT-TL1 and HNF4A. Variants of uncertain significance included a novel multi-exonic GCK duplication. Amongst participants with EMPC scores ≥ 25%, a causative variant was identified in 37%. Cascade testing was positive in 9/10 tested relatives with diabetes and 0/6 tested relatives with no history of diabetes. CONCLUSIONS Contemporary genetic testing produces a high yield of positive results in individuals with clinically suspected monogenic diabetes and their relatives with diabetes, highlighting the value of genetic testing for this condition. An EMPC score cutoff of ≥ 25% correctly yielded a positive predictive value of ≥ 25% in this multiethnic demographic. This is the first Australian study to describe EMPC scores in the Australian clinic setting, albeit a biased referral cohort. Larger studies may help characterise EMPC performance between ethnic subsets, noting differences in the expected probability of monogenic diabetes relative to type 2 diabetes.
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Affiliation(s)
- Sunita M C De Sousa
- Endocrine and Metabolic Unit, Royal Adelaide Hospital, Adelaide, Australia.
- Adult Genetics Unit, Royal Adelaide Hospital, Adelaide, Australia.
- Adelaide Medical School, University of Adelaide, Adelaide, Australia.
| | - Kathy H C Wu
- Clinical Genomics, St Vincent's Hospital, Darlinghurst, NSW, Australia
- School of Medicine, University of New South Wales, Sydney, NSW, Australia
- Discipline of Genomic Medicine, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
- School of Medicine, University of Notre Dame, Sydney, NSW, Australia
| | - Kevin Colclough
- Exeter Genomics Laboratory, Royal Devon University Healthcare NHS Foundation Trust, Exeter, UK
| | - Lesley Rawlings
- Department of Genetics and Molecular Pathology, SA Pathology, Adelaide, Australia
| | - Andrew Dubowsky
- Department of Genetics and Molecular Pathology, SA Pathology, Adelaide, Australia
| | - Melissa Monnik
- Adult Genetics Unit, Royal Adelaide Hospital, Adelaide, Australia
| | - Nicola Poplawski
- Adult Genetics Unit, Royal Adelaide Hospital, Adelaide, Australia
- Adelaide Medical School, University of Adelaide, Adelaide, Australia
| | - Hamish S Scott
- Adelaide Medical School, University of Adelaide, Adelaide, Australia
- Department of Genetics and Molecular Pathology, SA Pathology, Adelaide, Australia
- Centre for Cancer Biology, an alliance between SA Pathology, The University of South Australia, Adelaide, Australia
| | - Michael Horowitz
- Endocrine and Metabolic Unit, Royal Adelaide Hospital, Adelaide, Australia
- Adelaide Medical School, University of Adelaide, Adelaide, Australia
| | - David J Torpy
- Endocrine and Metabolic Unit, Royal Adelaide Hospital, Adelaide, Australia
- Adelaide Medical School, University of Adelaide, Adelaide, Australia
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Li M, Popovic N, Wang Y, Chen C, Polychronakos C. Incomplete penetrance and variable expressivity in monogenic diabetes; a challenge but also an opportunity. Rev Endocr Metab Disord 2023; 24:673-684. [PMID: 37165203 DOI: 10.1007/s11154-023-09809-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/01/2023] [Indexed: 05/12/2023]
Abstract
Monogenic Forms of Diabetes (MFD) account for about 3% of all diabetes, and their accurate diagnosis often results in life-changing therapeutic reassignment for the patients. Like other Mendelian diseases, reduced penetrance and variable expressivity are often seen in several different types of MFD, where symptoms develop only in a portion of the persons who carry the pathogenic variant or vary widely in symptom severity and age of onset. This complicates diagnosis and disease management in MFD. In addition to its clinical importance, knowledge of genetic modifiers that confer penetrance and expressivity variability opens possibilities to identify protective genetic variants which may help probe the mechanisms of more common forms of diabetes and shed light in new therapeutic strategies. In this review, we will mainly address penetrance and expressivity variation in different types of MFD, factors that confer such variations and opportunities that come with such knowledge. Related literature was searched in PubMed, Medline and Embase. Papers with publication year from 1974 to 2023 are included. Data are either sourced from literatures or from OMIM, Clinvar and 1000 genome browser.
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Affiliation(s)
- Meihang Li
- College of pharmacy, Jinan University, 601 Huangpu Avenue West, Guangzhou, Guangdong, China.
- Department of Emergency, Department of Endorinology, Maoming People's Hospital, 101 Weimin Road, Maoming, Guangdong, China.
- Montreal Children's Hospital and the Endocrine Genetics Laboratory, Child Health and Human Development Program, Research Institute of the McGill University Health Centre, Montreal, China.
- MaiDa Gene Technology, Zhoushan, China.
| | - Natalija Popovic
- Montreal Children's Hospital and the Endocrine Genetics Laboratory, Child Health and Human Development Program, Research Institute of the McGill University Health Centre, Montreal, China
| | - Ying Wang
- College of pharmacy, Jinan University, 601 Huangpu Avenue West, Guangzhou, Guangdong, China
| | - Chunbo Chen
- Department of Emergency, Department of Endorinology, Maoming People's Hospital, 101 Weimin Road, Maoming, Guangdong, China
- Department of Critical Care Medicine, Shenzhen People's Hospital, The Second Clinical Medical College of Jinan University, The First Affiliated Hospital of South University of Science and Technology, Shenzhen, China
- Department of Intensive Care Unit of Cardiovascular Surgery, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Constantin Polychronakos
- Montreal Children's Hospital and the Endocrine Genetics Laboratory, Child Health and Human Development Program, Research Institute of the McGill University Health Centre, Montreal, China
- MaiDa Gene Technology, Zhoushan, China
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Aarthy R, Aston-Mourney K, Amutha A, Mikocka-Walus A, Anjana RM, Unnikrishnan R, Jebarani S, Venkatesan U, Gopi S, Radha V, Mohan V. Identification of appropriate biochemical parameters and cut points to detect Maturity Onset Diabetes of Young (MODY) in Asian Indians in a clinic setting. Sci Rep 2023; 13:11408. [PMID: 37452084 PMCID: PMC10349068 DOI: 10.1038/s41598-023-37766-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 06/27/2023] [Indexed: 07/18/2023] Open
Abstract
Maturity Onset Diabetes of the Young (MODY) is a monogenic form of diabetes which is detected by genetic testing. We looked at clinical and biochemcial variables that could help detect possible MODY among Asian Indians with youth-onset diabetes. From the diabetes electronic medical records of a diabetes care centre in Chennai in southern India, demographic, anthropometric, and biochemical details of 34 genetically confirmed MODY participants were extracted. They were compared with patients with type 1 diabetes (T1D) (n = 1011) and type 2 diabetes (T2D) (n = 1605), diagnosed below 30 years of age. Clinical and biochemical variables including body mass index (BMI), glycated hemoglobin, HDL cholesterol, and C-peptide (fasting and stimulated) were analyzed to determine whether cut points could be derived to identify individuals who could be sent for genetic testing to diagnose or rule out MODY in this ethnic group. The age at diagnosis was higher for T2D (26.5 ± 4.0 years) compared to T1D (18.2 ± 6.1 years) and MODY (17.8 ± 6.0 years). Individuals with MODY had BMI, glycated hemoglobin, total cholesterol, triglycerides, HDL cholesterol, and C-peptide levels which were intermediate between T1D and T2D. The identified probable parameters and their cut points to identify cases for MODY genetic screening were BMI 21.2-22.7 kg/m2, glycated hemoglobin 7.2-10%, HDL cholesterol 43-45 mg/dl, fasting C -peptide, 1.2-2.1 ng/ml and stimulated C-peptide, 2.1-4.5 ng/ml. Asian Indians with MODY have clinical features that are intermediate between T1D and T2D and selected biochemical parameters, especially stimulated C peptide cut points were the most useful to diagnose MODY.
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Affiliation(s)
- Ramasamy Aarthy
- Madras Diabetes Research Foundation (ICMR Centre for Advanced Research on Diabetes), Chennai, India
- School of Medicine, IMPACT, Institute for Innovation in Physical and Mental Health and Clinical Translation, Deakin University Geelong, Geelong, Australia
| | - Kathryn Aston-Mourney
- School of Medicine, IMPACT, Institute for Innovation in Physical and Mental Health and Clinical Translation, Deakin University Geelong, Geelong, Australia
| | - Anandakumar Amutha
- Madras Diabetes Research Foundation (ICMR Centre for Advanced Research on Diabetes), Chennai, India
| | | | - Ranjit Mohan Anjana
- Madras Diabetes Research Foundation (ICMR Centre for Advanced Research on Diabetes), Chennai, India
- Dr. Mohan's Diabetes Specialties Centre (IDF Centre of Excellence in Diabetes Care), No 4, Conran Smith Road, Gopalapuram, Chennai, 600086, India
| | - Ranjit Unnikrishnan
- Madras Diabetes Research Foundation (ICMR Centre for Advanced Research on Diabetes), Chennai, India
- Dr. Mohan's Diabetes Specialties Centre (IDF Centre of Excellence in Diabetes Care), No 4, Conran Smith Road, Gopalapuram, Chennai, 600086, India
| | - Saravanan Jebarani
- Madras Diabetes Research Foundation (ICMR Centre for Advanced Research on Diabetes), Chennai, India
| | - Ulagamathesan Venkatesan
- Madras Diabetes Research Foundation (ICMR Centre for Advanced Research on Diabetes), Chennai, India
| | - Sundaramoorthy Gopi
- Madras Diabetes Research Foundation (ICMR Centre for Advanced Research on Diabetes), Chennai, India
| | - Venkatesan Radha
- Madras Diabetes Research Foundation (ICMR Centre for Advanced Research on Diabetes), Chennai, India
| | - Viswanathan Mohan
- Madras Diabetes Research Foundation (ICMR Centre for Advanced Research on Diabetes), Chennai, India.
- Dr. Mohan's Diabetes Specialties Centre (IDF Centre of Excellence in Diabetes Care), No 4, Conran Smith Road, Gopalapuram, Chennai, 600086, India.
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Abstract
Monogenic diabetes includes several clinical conditions generally characterized by early-onset diabetes, such as neonatal diabetes, maturity-onset diabetes of the young (MODY) and various diabetes-associated syndromes. However, patients with apparent type 2 diabetes mellitus may actually have monogenic diabetes. Indeed, the same monogenic diabetes gene can contribute to different forms of diabetes with early or late onset, depending on the functional impact of the variant, and the same pathogenic variant can produce variable diabetes phenotypes, even in the same family. Monogenic diabetes is mostly caused by impaired function or development of pancreatic islets, with defective insulin secretion in the absence of obesity. The most prevalent form of monogenic diabetes is MODY, which may account for 0.5-5% of patients diagnosed with non-autoimmune diabetes but is probably underdiagnosed owing to insufficient genetic testing. Most patients with neonatal diabetes or MODY have autosomal dominant diabetes. More than 40 subtypes of monogenic diabetes have been identified to date, the most prevalent being deficiencies of GCK and HNF1A. Precision medicine approaches (including specific treatments for hyperglycaemia, monitoring associated extra-pancreatic phenotypes and/or following up clinical trajectories, especially during pregnancy) are available for some forms of monogenic diabetes (including GCK- and HNF1A-diabetes) and increase patients' quality of life. Next-generation sequencing has made genetic diagnosis affordable, enabling effective genomic medicine in monogenic diabetes.
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Santomauro AC, Magalhães ÁLF, Motta FT, de Santana LS, Franco PC, de Freitas SM, Sanchez JJD, Costa-Riquetto AD, Teles MG. The performance of the MODY calculator in a non-Caucasian, mixed-race population diagnosed with diabetes mellitus before 35 years of age. Diabetol Metab Syndr 2023; 15:15. [PMID: 36747290 PMCID: PMC9900997 DOI: 10.1186/s13098-023-00985-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Accepted: 01/21/2023] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND A maturity-onset diabetes of the young (MODY) calculator has been described and validated for use in European Caucasians. This study evaluated its performance in Brazilians diagnosed with diabetes mellitus (DM) before 35 years of age. METHODS The electronic records of 391 individuals were reviewed in 2020 at the diabetes clinic of a quaternary hospital in São Paulo were analyzed: 231 with type 1 DM (T1DM), 46 with type 2 (T2DM) and 114 with MODY. The MODY calculator was applied to the three groups. A receiver operating characteristic curve was calculated to obtain cut-off points for this population. RESULTS The principal differences between the MODY and the T1DM and T2DM groups were body mass index, a positive family history of diabetes and mean HbA1c level. Age at diagnosis in the MODY group was only significantly different compared to the T2DM group. Specificity and sensitivity were good for the cut-off points of 40%, 50% and 60%, with the accuracy of the model for any of these cut-off points being > 95%. CONCLUSION The capacity of the calculator to identify Brazilian patients with MODY was good. Values ≥ 60% proved useful for selecting candidates for MODY genetic testing, with good sensitivity and specificity.
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Affiliation(s)
- Augusto Cezar Santomauro
- Grupo de Diabetes Monogênico (Monogenic Diabetes Group), Unidade de Endocrinologia, Genética (LIM25), Unidade de Diabetes, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo (HCFMUSP), São Paulo, SP 01246-903 Brazil
| | - Áurea Luiza Fernandes Magalhães
- Grupo de Diabetes Monogênico (Monogenic Diabetes Group), Unidade de Endocrinologia, Genética (LIM25), Unidade de Diabetes, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo (HCFMUSP), São Paulo, SP 01246-903 Brazil
| | - Flávia Tedesco Motta
- Grupo de Diabetes Monogênico (Monogenic Diabetes Group), Unidade de Endocrinologia, Genética (LIM25), Unidade de Diabetes, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo (HCFMUSP), São Paulo, SP 01246-903 Brazil
| | - Lucas Santos de Santana
- Grupo de Diabetes Monogênico (Monogenic Diabetes Group), Unidade de Endocrinologia, Genética (LIM25), Unidade de Diabetes, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo (HCFMUSP), São Paulo, SP 01246-903 Brazil
| | - Pedro Campos Franco
- Grupo de Diabetes Monogênico (Monogenic Diabetes Group), Unidade de Endocrinologia, Genética (LIM25), Unidade de Diabetes, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo (HCFMUSP), São Paulo, SP 01246-903 Brazil
| | - Silvia Maria de Freitas
- Department of Statistics and Applied Mathematics, Postgraduate Program in Modeling and Quantitative Methods, Science Center, Pici Campus, Federal University of Ceará (UFC), Fortaleza, CE 60440-900 Brazil
| | - Jeniffer Johana Duarte Sanchez
- Department of Statistics and Applied Mathematics, Postgraduate Program in Modeling and Quantitative Methods, Science Center, Pici Campus, Federal University of Ceará (UFC), Fortaleza, CE 60440-900 Brazil
| | - Aline Dantas Costa-Riquetto
- Grupo de Diabetes Monogênico (Monogenic Diabetes Group), Unidade de Endocrinologia, Genética (LIM25), Unidade de Diabetes, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo (HCFMUSP), São Paulo, SP 01246-903 Brazil
| | - Milena G. Teles
- Grupo de Diabetes Monogênico (Monogenic Diabetes Group), Unidade de Endocrinologia, Genética (LIM25), Unidade de Diabetes, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo (HCFMUSP), São Paulo, SP 01246-903 Brazil
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Chen Y, Zhao J, Li X, Xie Z, Huang G, Yan X, Zhou H, Zheng L, Xu T, Zhou K, Zhou Z. Prevalence of maturity-onset diabetes of the young in phenotypic type 2 diabetes in young adults: a nationwide, multi-center, cross-sectional survey in China. Chin Med J (Engl) 2023; 136:56-64. [PMID: 36723869 PMCID: PMC10106210 DOI: 10.1097/cm9.0000000000002321] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND Maturity-onset diabetes of the young (MODY) is the most common monogenic diabetes. The aim of this study was to assess the prevalence of MODY in phenotypic type 2 diabetes (T2DM) among Chinese young adults. METHODS From April 2015 to October 2017, this cross-sectional study involved 2429 consecutive patients from 46 hospitals in China, newly diagnosed between 15 years and 45 years, with T2DM phenotype and negative for standardized glutamic acid decarboxylase antibody at the core laboratory. Sequencing using a custom monogenic diabetes gene panel was performed, and variants of 14 MODY genes were interpreted as per current guidelines. RESULTS The survey determined 18 patients having genetic variants causing MODY (6 HNF1A , 5 GCK , 3 HNF4A , 2 INS , 1 PDX1 , and 1 PAX4 ). The prevalence of MODY was 0.74% (95% confidence interval [CI]: 0.40-1.08%). The clinical characteristics of MODY patients were not specific, 72.2% (13/18) of them were diagnosed after 35 years, 47.1% (8/17) had metabolic syndrome, and only 38.9% (7/18) had a family history of diabetes. No significant difference in manifestations except for hemoglobin A1c levels was found between MODY and non-MODY patients. CONCLUSION The prevalence of MODY in young adults with phenotypic T2DM was 0.74%, among which HNF1A -, GCK -, and HNF4A -MODY were the most common subtypes. Clinical features played a limited role in the recognition of MODY.
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Affiliation(s)
- 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
| | - Jing Zhao
- College of Life Sciences, The University of Chinese Academy of Sciences, Beijing 100049, 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
| | - Zhiguo Xie
- 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
| | - Gan Huang
- 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
| | - Xiang Yan
- 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
| | - Houde 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
| | - Li Zheng
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Tao Xu
- College of Life Sciences, The University of Chinese Academy of Sciences, Beijing 100049, China
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong 271016, China
| | - Kaixin Zhou
- College of Life Sciences, The University of Chinese Academy of Sciences, Beijing 100049, China
- Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong 271016, 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
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Colclough K, Patel K. How do I diagnose Maturity Onset Diabetes of the Young in my patients? Clin Endocrinol (Oxf) 2022; 97:436-447. [PMID: 35445424 PMCID: PMC9544561 DOI: 10.1111/cen.14744] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 03/21/2022] [Accepted: 04/13/2022] [Indexed: 11/28/2022]
Abstract
Maturity Onset Diabetes of the Young (MODY) is a monogenic form of diabetes diagnosed in young individuals that lack the typical features of type 1 and type 2 diabetes. The genetic subtype of MODY determines the most effective treatment and this is the driver for MODY genetic testing in diabetes populations. Despite the obvious clinical and health economic benefits, MODY is significantly underdiagnosed with the majority of patients being inappropriately managed as having type 1 or type 2 diabetes. Low detection rates result from the difficulty in identifying patients with a likely diagnosis of MODY from the high background population of young onset type 1 and type 2 diabetes, compounded by the lack of MODY awareness and education in diabetes care physicians. MODY diagnosis can be improved through (1) access to education and training, (2) the use of sensitive and specific selection criteria based on accurate prediction models and biomarkers to identify patients for testing, (3) the development and mainstream implementation of simple criteria-based selection pathways applicable across a range of healthcare settings and ethnicities to select the most appropriate patients for genetic testing and (4) the correct use of next generation sequencing technology to provide accurate and comprehensive testing of all known MODY and monogenic diabetes genes. The creation and public sharing of educational materials, clinical and scientific best practice guidelines and genetic variants will help identify the missing patients so they can benefit from the more effective clinical care that a genetic diagnosis brings.
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Affiliation(s)
- Kevin Colclough
- Exeter Genomics LaboratoryRoyal Devon & Exeter NHS Foundation TrustExeterUK
| | - Kashyap Patel
- Institute of Biomedical and Clinical ScienceUniversity of Exeter Medical SchoolExeterUK
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11
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Wang DW, Yuan J, Yang FY, Qiu HY, Lu J, Yang JK. Early-onset diabetes involving three consecutive generations had different clinical features from age-matched type 2 diabetes without a family history in China. Endocrine 2022; 78:47-56. [PMID: 35921062 PMCID: PMC9474578 DOI: 10.1007/s12020-022-03144-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Accepted: 07/12/2022] [Indexed: 11/29/2022]
Abstract
PURPOSE Early-onset, multigenerational diabetes is a heterogeneous disease, which is often simplistically classified as type 1 diabetes (T1D) or type 2 diabetes(T2D). However, its clinical and genetic characteristics have not been clearly elucidated. The aim of our study is to investigate the clinical features of early-onset diabetes involving three consecutive generations (eDia3) in a Chinese diabetes cohort. METHODS Of 6470 type 2 diabetic patients, 105 were identified as eDia3 (1.6%). After a case-control match on age, we compared the clinical characteristics of 89 eDia3 patients with 89 early-onset T2D patients without a family history of diabetes (eDia0). WES was carried out in 89 patients with eDia3. We primarily focused on 14 known maturity-onset diabetes of the young (MODY) genes. Variants were predicted by ten tools (SIFT, PolyPhen2_HDIV, PolyPhen2_HVAR, LRT, Mutation Assessor, Mutation Taster, FATHMM, GERP++, PhyloP, and PhastCons). All suspected variants were then validated by Sanger sequencing and further investigated in the proband families. RESULTS Compared to age-matched eDia0, eDia3 patients had a younger age at diagnosis (26.5 ± 5.8 vs. 29.4 ± 5.3 years, P = 0.001), lower body mass index (25.5 ± 3.9 vs. 27.4 ± 4.6 kg/m2, P = 0.003), lower systolic blood pressure (120 ± 15 vs. 128 ± 18 mmHg, P = 0.003), and better metabolic profiles (including glucose and lipids). Of the 89 eDia3 patients, 10 (11.2%) carried likely pathogenic variants in genes (KLF11, GCK, ABCC8, PAX4, BLK and HNF1A) of MODY. CONCLUSIONS eDia3 patients had unique clinical features. Known MODY genes were not common causes in these patients.
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Affiliation(s)
- Da-Wei Wang
- Department of Endocrinology, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, China
- Department of General Medicine, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, China
| | - Jing Yuan
- Department of Endocrinology, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, China
| | - Fang-Yuan Yang
- Department of Endocrinology, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, China
- Beijing Key Laboratory of Diabetes Research and Care, Beijing Diabetes Institute, Beijing, 100730, China
| | - Hai-Yan Qiu
- Department of Endocrinology, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, China
- Beijing Key Laboratory of Diabetes Research and Care, Beijing Diabetes Institute, Beijing, 100730, China
| | - Jing Lu
- Beijing Key Laboratory of Diabetes Research and Care, Beijing Diabetes Institute, Beijing, 100730, China
| | - Jin-Kui Yang
- Department of Endocrinology, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, China.
- Beijing Key Laboratory of Diabetes Research and Care, Beijing Diabetes Institute, Beijing, 100730, China.
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12
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da Silva Santos T, Fonseca L, Santos Monteiro S, Borges Duarte D, Martins Lopes A, Couto de Carvalho A, Oliveira MJ, Borges T, Laranjeira F, Couce ML, Cardoso MH. MODY probability calculator utility in individuals' selection for genetic testing: Its accuracy and performance. Endocrinol Diabetes Metab 2022; 5:e00332. [PMID: 35822264 PMCID: PMC9471596 DOI: 10.1002/edm2.332] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 02/17/2022] [Accepted: 02/20/2022] [Indexed: 11/25/2022] Open
Abstract
Introduction MODY probability calculator (MPC) represents an easy‐to‐use tool developed by Exeter University to help clinicians prioritize which individuals should be oriented to genetic testing. We aimed to assess the utility of MPC in a Portuguese cohort with early‐onset monogenic diabetes. Methods This single‐centre retrospective study enrolled 132 participants submitted to genetic testing between 2015 and 2020. Automatic sequencing and, in case of initial negative results, generation sequencing were performed. MODY probability was calculated using the probability calculator available online. Positive and negative predictive values (PPV and NPV, respectively), accuracy, sensitivity and specificity of the calculator were determined for this cohort. Results Seventy‐three individuals were included according to inclusion criteria: 20 glucokinase (GCK‐MODY); 16 hepatocyte nuclear factor 1A (HNF1A‐MODY); 2 hepatocyte nuclear factor 4A (HNF4A‐MODY) and 35 DM individuals with no monogenic mutations found. The median probability score of MODY was significantly higher in monogenic diabetes‐positive subgroup (75.5% vs. 24.2%, p < .001). The discriminative accuracy of the calculator, as expressed by area under the curve, was 75% (95% CI: 64%–85%). In our cohort, the best cut‐off value for the MODY calculator was found to be 36%, with a PPV of 74.4%, NPV of 73.5% and corresponding sensitivity and specificity of 76.2% and 71.4%, respectively. Conclusions In a highly pre‐selected group of probands qualified for genetic testing, the Exeter MODY probability calculator provided a useful tool in individuals' selection for genetic testing, with good discrimination ability under an optimal probability cut‐off of 36%. Further geographical and population adjustments are warranted for general use.
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Affiliation(s)
- Tiago da Silva Santos
- Division of Endocrinology, Diabetes and Metabolism Hospital de Santo António – Centro Hospitalar e Universitário do Porto Porto Portugal
| | - Liliana Fonseca
- Division of Endocrinology, Diabetes and Metabolism Hospital de Santo António – Centro Hospitalar e Universitário do Porto Porto Portugal
| | - Sílvia Santos Monteiro
- Division of Endocrinology, Diabetes and Metabolism Hospital de Santo António – Centro Hospitalar e Universitário do Porto Porto Portugal
| | - Diana Borges Duarte
- Division of Endocrinology, Diabetes and Metabolism Hospital de Santo António – Centro Hospitalar e Universitário do Porto Porto Portugal
| | - Ana Martins Lopes
- Division of Endocrinology, Diabetes and Metabolism Hospital de Santo António – Centro Hospitalar e Universitário do Porto Porto Portugal
| | - André Couto de Carvalho
- Division of Endocrinology, Diabetes and Metabolism Hospital de Santo António – Centro Hospitalar e Universitário do Porto Porto Portugal
| | - Maria João Oliveira
- Division of Pediatric Endocrinology Department of Pediatrics Centro Materno‐Infantil do Norte – Centro Hospitalar e Universitário do Porto Porto Portugal
| | - Teresa Borges
- Division of Pediatric Endocrinology Department of Pediatrics Centro Materno‐Infantil do Norte – Centro Hospitalar e Universitário do Porto Porto Portugal
| | | | - María Luz Couce
- University Clinical Hospital of Santiago de Compostela, IDIS CIBERER MetabERN Santiago de Compostela Spain
| | - Maria Helena Cardoso
- Division of Endocrinology, Diabetes and Metabolism Hospital de Santo António – Centro Hospitalar e Universitário do Porto Porto Portugal
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Mifsud F, Saint-Martin C, Dubois-Laforgue D, Bouvet D, Timsit J, Bellanné-Chantelot C. Monogenic diabetes in adults: A multi-ancestry study reveals strong disparities in diagnosis rates and clinical presentation. Diabetes Res Clin Pract 2022; 188:109908. [PMID: 35533745 DOI: 10.1016/j.diabres.2022.109908] [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: 03/20/2022] [Revised: 04/25/2022] [Accepted: 05/01/2022] [Indexed: 11/03/2022]
Abstract
AIM Identification of monogenic diabetes (MgD) conveys benefits for patients' care. Algorithms for selecting the patients to be genetically tested have been established in EuroCaucasians, but not in non-EuroCaucasian individuals. We assessed the diagnosis rate, the phenotype of MgD, and the relevance of selection criteria, according to ancestry in patients referred for a suspected MgD. METHODS Seven genes (GCK, HNF1A, HNF4A, HNF1B, ABCC8, KCNJ11, INS) were analyzed in 1975 adult probands (42% non-EuroCaucasians), selected on the absence of diabetes autoantibodies and ≥2 of the following criteria: age ≤40 years and body mass index <30 kg/m2 at diagnosis, and a family history of diabetes in ≥2 generations. RESULTS Pathogenic/likely pathogenic variants were identified in 6.2% of non-EuroCaucasian and 23.6% of EuroCaucasian patients (OR 0.21, [0.16-0.29]). Diagnosis rate was low in all non-EuroCaucasian subgroups (4.1-11.8%). Common causes of MgD (GCK, HNF1A, HNF4A), but not rare causes, were less frequent in non-EuroCaucasians than in EuroCaucasians (4.1%, vs. 21.1%, OR 0.16 [0.11-0.23]). Using ethnicity-specific body mass index cutoffs increased the diagnosis rate in several non-EuroCaucasian subgroups. CONCLUSION The diagnosis rate of MgD is low in non-EuroCaucasian patients, but may be improved by tailoring selection criteria according to patients'ancestry.
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Affiliation(s)
- F Mifsud
- Université de Paris, AP-HP, Cochin Hospital, Department of Diabetology, DMU ENDROMED, 27 rue du Faubourg Saint-Jacques, 75014 Paris, France; Université de Paris, BFA, CNRS UMR 8251, 75013 Paris, France; Diabetes Center, University of California San Francisco, San Francisco, CA, USA
| | - C Saint-Martin
- Sorbonne Université, AP-HP, Pitié-Salpêtrière Hospital, Department of Medical Genetics, DMU BioGeM, 47/83 Boulevard de l'Hôpital, 75013 Paris, France; PRISIS Reference Center for Rare Diseases, Paris, France
| | - D Dubois-Laforgue
- Université de Paris, AP-HP, Cochin Hospital, Department of Diabetology, DMU ENDROMED, 27 rue du Faubourg Saint-Jacques, 75014 Paris, France; PRISIS Reference Center for Rare Diseases, Paris, France; INSERM U1016, Cochin Hospital, 22 Rue Méchain, 75014 Paris, France
| | - D Bouvet
- Sorbonne Université, AP-HP, Pitié-Salpêtrière Hospital, Department of Medical Genetics, DMU BioGeM, 47/83 Boulevard de l'Hôpital, 75013 Paris, France; PRISIS Reference Center for Rare Diseases, Paris, France
| | - J Timsit
- Université de Paris, AP-HP, Cochin Hospital, Department of Diabetology, DMU ENDROMED, 27 rue du Faubourg Saint-Jacques, 75014 Paris, France; PRISIS Reference Center for Rare Diseases, Paris, France
| | - C Bellanné-Chantelot
- Sorbonne Université, AP-HP, Pitié-Salpêtrière Hospital, Department of Medical Genetics, DMU BioGeM, 47/83 Boulevard de l'Hôpital, 75013 Paris, France; PRISIS Reference Center for Rare Diseases, Paris, France.
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Lee DH, Kwak SH, Park HS, Ku EJ, Jeon HJ, Oh TK. Identification of candidate gene variants of monogenic diabetes using targeted panel sequencing in early onset diabetes patients. BMJ Open Diabetes Res Care 2021; 9:9/1/e002217. [PMID: 34135026 PMCID: PMC8211067 DOI: 10.1136/bmjdrc-2021-002217] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2021] [Accepted: 06/01/2021] [Indexed: 01/01/2023] Open
Abstract
INTRODUCTION Monogenic diabetes is attributed to genetic variations in a single gene. Maturity-onset diabetes of the young (MODY) is the most common phenotype associated with monogenic diabetes, but is frequently misdiagnosed as either type 1 or type 2 diabetes. Increasing our basic understanding of genetic variations in MODY may help to improve the accuracy of providing the correct diagnosis and personalize subsequent treatment regimens in different racial populations. For this reason, this study was designed to identify nucleotide variants in early onset diabetes patients with clinically suspected MODY in a Korean population. RESEARCH DESIGN AND METHODS Among 2908 Korean patients diagnosed with diabetes, we selected 40 patients who were diagnosed before 30 years old and were clinically suspected of MODY. Genetic testing was performed using a targeted gene sequencing panel that included 30 known monogenic diabetes genes. The pathogenicity of the identified variants was assessed according to the American College of Medical Genetics and Genomics and Association for Molecular Pathology (ACMG-AMP) guidelines. RESULTS A total of six rare missense variants (p.Ala544Thr in HNF1A, p.Val601Ile and p.His103Tyr in ABCC8, p.Pro33Ala in PDX1, p.Gly18Glu in INS, and p.Arg164Gln in PAX4) in five distinct MODY genes were identified in five patients. In addition, a variant was identified in mitochondrial DNA at 3243A>G in one patient. The identified variants were either absent or detected at a rare frequency in the 1000 Genomes Project. These variants were classified as uncertain significance using the ACMG-AMP guidelines. CONCLUSION Using a targeted gene sequencing panel, we identified seven variants in either MODY genes or mitochondrial DNA using a Korean patient population with early onset diabetes who were clinically suspected of MODY. This genetic approach provides the ability to compare distinct populations of racial and ethnic groups to determine whether specific gene is involved in their diagnosis of MODY.
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Affiliation(s)
- Dong-Hwa Lee
- Internal Medicine, Chungbuk National University Hospital, Cheongju, Korea (the Republic of)
| | - Soo-Heon Kwak
- Internal Medicine, Seoul National University Hospital, Jongno-gu, Korea (the Republic of)
| | - Hee Sue Park
- Laboratory Medicine, Chungbuk National University Hospital, Cheongju, Korea (the Republic of)
| | - Eu Jeong Ku
- Internal Medicine, Chungbuk National University Hospital, Cheongju, Korea (the Republic of)
| | - Hyun Jeong Jeon
- Internal Medicine, Chungbuk National University Hospital, Cheongju, Korea (the Republic of)
| | - Tae Keun Oh
- Internal Medicine, Chungbuk National University Hospital, Cheongju, Korea (the Republic of)
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15
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Broome DT, Pantalone KM, Kashyap SR, Philipson LH. Approach to the Patient with MODY-Monogenic Diabetes. J Clin Endocrinol Metab 2021; 106:237-250. [PMID: 33034350 PMCID: PMC7765647 DOI: 10.1210/clinem/dgaa710] [Citation(s) in RCA: 74] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2020] [Accepted: 10/02/2020] [Indexed: 12/14/2022]
Abstract
UNLABELLED Maturity-onset diabetes of the young, or MODY-monogenic diabetes, is a not-so-rare collection of inherited disorders of non-autoimmune diabetes mellitus that remains insufficiently diagnosed despite increasing awareness. These cases are important to efficiently and accurately diagnose, given the clinical implications of syndromic features, cost-effective treatment regimen, and the potential impact on multiple family members. Proper recognition of the clinical manifestations, family history, and cost-effective lab and genetic testing provide the diagnosis. All patients must undergo a thorough history, physical examination, multigenerational family history, lab evaluation (glycated hemoglobin A1c [HbA1c], glutamic acid decarboxylase antibodies [GADA], islet antigen 2 antibodies [IA-2A], and zinc transporter 8 [ZnT8] antibodies). The presence of clinical features with 3 (or more) negative antibodies may be indicative of MODY-monogenic diabetes, and is followed by genetic testing. Molecular genetic testing should be performed before attempting specific treatments in most cases. Additional testing that is helpful in determining the risk of MODY-monogenic diabetes is the MODY clinical risk calculator (>25% post-test probability in patients not treated with insulin within 6 months of diagnosis should trigger genetic testing) and 2-hour postprandial (after largest meal of day) urinary C-peptide to creatinine ratio (with a ≥0.2 nmol/mmol to distinguish HNF1A- or 4A-MODY from type 1 diabetes). Treatment, as well as monitoring for microvascular and macrovascular complications, is determined by the specific variant that is identified. In addition to the diagnostic approach, this article will highlight recent therapeutic advancements when patients no longer respond to first-line therapy (historically sulfonylurea treatment in many variants). LEARNING OBJECTIVES Upon completion of this educational activity, participants should be able to. TARGET AUDIENCE This continuing medical education activity should be of substantial interest to endocrinologists and all health care professionals who care for people with diabetes mellitus.
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Affiliation(s)
- David T Broome
- Department of Endocrinology, Diabetes & Metabolism, Cleveland Clinic Foundation, Cleveland, Ohio
- Correspondence and Reprint Requests: David T. Broome, MD, Department of Endocrinology, Diabetes & Metabolism, Cleveland Clinic Foundation, 9500 Euclid Avenue, Mail code: F-20, Cleveland, OH 44195, USA. E-mail:
| | - Kevin M Pantalone
- Department of Endocrinology, Diabetes & Metabolism, Cleveland Clinic Foundation, Cleveland, Ohio
| | - Sangeeta R Kashyap
- Department of Endocrinology, Diabetes & Metabolism, Cleveland Clinic Foundation, Cleveland, Ohio
| | - Louis H Philipson
- Kovler Diabetes Center, Departments of Medicine and Pediatrics, University of Chicago, Chicago, Illinois
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Vaxillaire M, Bonnefond A, Liatis S, Ben Salem Hachmi L, Jotic A, Boissel M, Gaget S, Durand E, Vaillant E, Derhourhi M, Canouil M, Larcher N, Allegaert F, Medlej R, Chadli A, Belhadj A, Chaieb M, Raposo JF, Ilkova H, Loizou D, Lalic N, Vassallo J, Marre M, Froguel P. Monogenic diabetes characteristics in a transnational multicenter study from Mediterranean countries. Diabetes Res Clin Pract 2021; 171:108553. [PMID: 33242514 DOI: 10.1016/j.diabres.2020.108553] [Citation(s) in RCA: 6] [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: 08/05/2020] [Revised: 11/01/2020] [Accepted: 11/10/2020] [Indexed: 02/07/2023]
Abstract
BACKGROUND Diagnosis of monogenic diabetes has important clinical implications for treatment and health expenditure. However, its prevalence remains to be specified in many countries, particularly from South Europe, North Africa and Middle-East, where non-autoimmune diabetes in young adults is increasing dramatically. AIMS To identify cases of monogenic diabetes in young adults from Mediterranean countries and assess the specificities between countries. METHODS We conducted a transnational multicenter study based on exome sequencing in 204 unrelated patients with diabetes (age-at-diagnosis: 26.1 ± 9.1 years). Rare coding variants in 35 targeted genes were evaluated for pathogenicity. Data were analyzed using one-way ANOVA, chi-squared test and factor analysis of mixed data. RESULTS Forty pathogenic or likely pathogenic variants, 14 of which novel, were identified in 36 patients yielding a genetic diagnosis rate of 17.6%. The majority of cases were due to GCK, HNF1A, ABCC8 and HNF4A variants. We observed highly variable diagnosis rates according to countries, with association to genetic ancestry. Lower body mass index and HbA1c at study inclusion, and less frequent insulin treatment were hallmarks of pathogenic variant carriers. Treatment changes following genetic diagnosis have been made in several patients. CONCLUSIONS Our data from patients in several Mediterranean countries highlight a broad clinical and genetic spectrum of diabetes, showing the relevance of wide genetic testing for personalized care of early-onset diabetes.
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Affiliation(s)
- Martine Vaxillaire
- Inserm UMR1283, CNRS UMR8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur Lille, Univ. Lille, Lille University Hospital, Lille, France.
| | - Amélie Bonnefond
- Inserm UMR1283, CNRS UMR8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur Lille, Univ. Lille, Lille University Hospital, Lille, France; Department of Metabolism, Section of Genomics of Common Disease, Imperial College London, London, United Kingdom.
| | - Stavros Liatis
- First Department of Propaedeutic Medicine, National and Kapodistrian University of Athens Medical School, Diabetes Center, Laiko General Hospital, Athens, Greece
| | - Leila Ben Salem Hachmi
- Department of Endocrinology and Metabolic Diseases, National Institut of Nutrition, Tunis, Tunisia
| | - Aleksandra Jotic
- Department of Endocrinology, Diabetes and Metabolic Diseases, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Mathilde Boissel
- Inserm UMR1283, CNRS UMR8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur Lille, Univ. Lille, Lille University Hospital, Lille, France
| | - Stefan Gaget
- Inserm UMR1283, CNRS UMR8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur Lille, Univ. Lille, Lille University Hospital, Lille, France
| | - Emmanuelle Durand
- Inserm UMR1283, CNRS UMR8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur Lille, Univ. Lille, Lille University Hospital, Lille, France
| | - Emmanuel Vaillant
- Inserm UMR1283, CNRS UMR8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur Lille, Univ. Lille, Lille University Hospital, Lille, France
| | - Mehdi Derhourhi
- Inserm UMR1283, CNRS UMR8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur Lille, Univ. Lille, Lille University Hospital, Lille, France
| | - Mickaël Canouil
- Inserm UMR1283, CNRS UMR8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur Lille, Univ. Lille, Lille University Hospital, Lille, France
| | - Nicolas Larcher
- Inserm UMR1283, CNRS UMR8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur Lille, Univ. Lille, Lille University Hospital, Lille, France
| | - Frédéric Allegaert
- Inserm UMR1283, CNRS UMR8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur Lille, Univ. Lille, Lille University Hospital, Lille, France
| | | | - Asma Chadli
- Department of Endocrinology, Ibn Rochd University Hospital, Casablanca, Morocco
| | - Azzedine Belhadj
- Department of Internal Medicine, CHU Dr Ben Badis University Hospital, Constantine, Algeria
| | - Molka Chaieb
- Department of Endocrinology, Farhat Hached Hospital, Sousse, Tunisia
| | | | - Hasan Ilkova
- Department of Endocrinology, School of Medicine, Istanbul University, Istanbul, Turkey
| | | | - Nebojsa Lalic
- Department of Endocrinology, Diabetes and Metabolic Diseases, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Josanne Vassallo
- Division of Endocrinology and University of Malta Medical School, Mater Dei Hospital; Centre of Molecular Medicine and Biobanking, University of Malta, Malta
| | - Michel Marre
- Department of Diabetology-Endocrinology-Nutrition, Hôpital Bichat, DHU FIRE, Assistance Publique Hôpitaux de Paris, Paris, France; Inserm U1138, Centre de Recherche des Cordeliers, Paris, France; UFR de Médecine, University Paris Diderot, Sorbonne Paris Cité, Paris, France.
| | - Philippe Froguel
- Inserm UMR1283, CNRS UMR8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur Lille, Univ. Lille, Lille University Hospital, Lille, France; Department of Metabolism, Section of Genomics of Common Disease, Imperial College London, London, United Kingdom
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Abstract
Monogenic diabetes, including maturity-onset diabetes of the young, neonatal diabetes, and other rare forms of diabetes, results from a single gene mutation. It has been estimated to represent around 1% to 6% of all diabetes. With the advances in genome sequencing technology, it is possible to diagnose more monogenic diabetes cases than ever before. In Korea, 11 studies have identified several monogenic diabetes cases, using Sanger sequencing and whole exome sequencing since 2001. The recent largest study, using targeted exome panel sequencing, found a molecular diagnosis rate of 21.1% for monogenic diabetes in clinically suspected patients. Mutations in glucokinase (GCK), hepatocyte nuclear factor 1α (HNF1A), and HNF4A were most commonly found. Genetic diagnosis of monogenic diabetes is important as it determines the therapeutic approach required for patients and helps to identify affected family members. However, there are still many challenges, which include a lack of simple clinical criterion for selecting patients for genetic testing, difficulties in interpreting the genetic test results, and high costs for genetic testing. In this review, we will discuss the latest updates on monogenic diabetes in Korea, and suggest an algorithm to screen patients for genetic testing. The genetic tests and non-genetic markers for accurate diagnosis of monogenic diabetes will be also reviewed.
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Affiliation(s)
- Ye Seul Yang
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea
- Department of Internal Medicine, Uijeongbu St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Uijeongbu, Korea
| | - Soo Heon Kwak
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea
| | - Kyong Soo Park
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University College of Medicine, Seoul, Korea
- Corresponding author: Kyong Soo Park Department of Internal Medicine, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul 03080, Korea E-mail:
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18
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Baldacchino I, Pace NP, Vassallo J. Screening for monogenic diabetes in primary care. Prim Care Diabetes 2020; 14:1-11. [PMID: 31253563 DOI: 10.1016/j.pcd.2019.06.001] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2019] [Revised: 05/24/2019] [Accepted: 06/03/2019] [Indexed: 10/26/2022]
Abstract
AIMS Updates on the latest diagnostic methods and features of MODY (Maturity Onset Diabetes of the Young) and promotion of education and awareness on the subject are discussed. METHOD Previous recommendations were identified using PubMed and using combinations of terms including "MODY" "monogenic diabetes" "mature onset diabetes" "MODY case review". The diabetesgenes.org website and the US Monogenic Diabetes Registry (University of Colorado) were directly referenced. The remaining referenced papers were taken from peer-reviewed journals. The initial literature search occurred in January 2017 and the final search occurred in September 2018. RESULTS A diagnosis of MODY has implications for treatment, quality of life, management in pregnancy and research. The threshold for referral and testing varies among different ethnic groups, and depends on body mass index, family history of diabetes and associated syndromes. Novel causative genetic variations are still being discovered however testing is currently limited by low referral rates. Educational material is currently being promoted in the UK in an effort to raise awareness. CONCLUSIONS The benefits and implications of life altering treatment such as termination of insulin administration are significant but little can be done without appropriate identification and referral.
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Affiliation(s)
- Ian Baldacchino
- Specialist Training Programme in Family Medicine, Birkirkara Health Centre, Birkirkara, Malta.
| | - Nikolai Paul Pace
- Faculty of Medicine & Surgery, Biomedical Sciences Building, University of Malta, Msida, Malta.
| | - Josanne Vassallo
- Division of Diabetes and Endocrinology, University of Malta Medical School, Mater Dei Hospital, Msida, Malta.
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Donath X, Saint-Martin C, Dubois-Laforgue D, Rajasingham R, Mifsud F, Ciangura C, Timsit J, Bellanné-Chantelot C. Next-generation sequencing identifies monogenic diabetes in 16% of patients with late adolescence/adult-onset diabetes selected on a clinical basis: a cross-sectional analysis. BMC Med 2019; 17:132. [PMID: 31291970 PMCID: PMC6621990 DOI: 10.1186/s12916-019-1363-0] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2019] [Accepted: 06/10/2019] [Indexed: 02/09/2023] Open
Abstract
BACKGROUND Monogenic diabetes (MgD) accounts for 1-2% of all diabetes cases. In adults, MgD is difficult to distinguish from common diabetes causes. We assessed the diagnosis rate and genetic spectrum of MgD using next-generation sequencing in patients with late adolescence/adult-onset diabetes referred for a clinical suspicion of MgD. METHODS This cross-sectional study was performed in 1564 probands recruited in 116 Endocrinology departments. Inclusion criteria were the absence of diabetes autoantibodies, and at least two of the three following criteria: an age ≤ 40 years and a body mass index (BMI) < 30 kg/m2 at diagnosis in the proband or in at least two relatives with diabetes, and a family history of diabetes in ≥ 2 generations. Seven genes (GCK, HNF1A, HNF4A, HNF1B, ABCC8, KCNJ11, and INS) were analyzed. Variant pathogenicity was assessed using current guidelines. RESULTS Pathogenic variants were identified in 254 patients (16.2%) and in 23.2% of EuroCaucasian patients. Using more stringent selection criteria (family history of diabetes in ≥ 3 generations, age at diabetes ≤ 40 years and BMI < 30 kg/m2 in the proband, EuroCaucasian origin) increased the diagnosis rate to 43%, but with 70% of the identified cases being missed. GCK (44%), HNF1A (33%), and HNF4A (10%) accounted for the majority of the cases. HNF1B (6%), ABCC8/KCNJ11 (4.4%), and INS (2.8%) variants accounted for 13% of the cases. As compared to non-monogenic cases, a younger age, a lower BMI and the absence of diabetes symptoms at diagnosis, a EuroCaucasian origin, and a family history of diabetes in ≥ 3 generations were associated with MgD, but with wide phenotype overlaps between the two groups. In the total population, two clusters were identified, that mainly differed by the severity of diabetes at onset. MgDs were more prevalent in the milder phenotypic cluster. The phenotypes of the 59 patients (3.8%) with variants of uncertain significance were different from that of patients with pathogenic variants, but not from that of non-monogenic patients. CONCLUSION Variants of HNF1B and the K-ATP channel genes were more frequently involved in MgD than previously reported. Phenotype overlapping makes the diagnosis of MgD difficult in adolescents/adults and underlies the benefit of NGS in clinically selected patients.
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Affiliation(s)
- Xavier Donath
- Department of Diabetology, Cochin Hospital, Assistance Publique-Hôpitaux de Paris (AP-HP), and Paris Descartes University, DHU AUTHORS, 27 rue du Faubourg Saint-Jacques, 75014, Paris, France
| | - Cécile Saint-Martin
- Department of Genetics, Pitié-Salpêtrière Hospital, AP-HP, Sorbonne University, 47/83 boulevard de l'Hôpital, 75013, Paris, France.,PRISIS Reference Center for Rare Diseases, Paris, France
| | - Danièle Dubois-Laforgue
- Department of Diabetology, Cochin Hospital, Assistance Publique-Hôpitaux de Paris (AP-HP), and Paris Descartes University, DHU AUTHORS, 27 rue du Faubourg Saint-Jacques, 75014, Paris, France.,PRISIS Reference Center for Rare Diseases, Paris, France.,INSERM U1016, Cochin Hospital, 22 rue Méchain, 75014, Paris, France
| | - Ramanan Rajasingham
- Department of Diagnostic and Interventional Radiology, and Neuroradiology, Bretonneau Hospital, University Hospital of Tours, 2 boulevard Tonnellé, 27000, Tours, France
| | - François Mifsud
- Department of Diabetology, Cochin Hospital, Assistance Publique-Hôpitaux de Paris (AP-HP), and Paris Descartes University, DHU AUTHORS, 27 rue du Faubourg Saint-Jacques, 75014, Paris, France
| | - Cécile Ciangura
- PRISIS Reference Center for Rare Diseases, Paris, France.,Department of Diabetology, Pitié-Salpêtrière Hospital, AP-HP, Sorbonne University, 47 Boulevard de l'Hôpital, 75013, Paris, France
| | - José Timsit
- Department of Diabetology, Cochin Hospital, Assistance Publique-Hôpitaux de Paris (AP-HP), and Paris Descartes University, DHU AUTHORS, 27 rue du Faubourg Saint-Jacques, 75014, Paris, France.,PRISIS Reference Center for Rare Diseases, Paris, France
| | - Christine Bellanné-Chantelot
- Department of Genetics, Pitié-Salpêtrière Hospital, AP-HP, Sorbonne University, 47/83 boulevard de l'Hôpital, 75013, Paris, France. .,PRISIS Reference Center for Rare Diseases, Paris, France.
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Park SS, Jang SS, Ahn CH, Kim JH, Jung HS, Cho YM, Lee YA, Shin CH, Chae JH, Kim JH, Choi SH, Jang HC, Bae JC, Won JC, Kim SH, Kim JI, Kwak SH, Park KS. Identifying Pathogenic Variants of Monogenic Diabetes Using Targeted Panel Sequencing in an East Asian Population. J Clin Endocrinol Metab 2019; 104:4188-4198. [PMID: 30977832 DOI: 10.1210/jc.2018-02397] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/06/2018] [Accepted: 04/08/2019] [Indexed: 02/05/2023]
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.
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Affiliation(s)
- Seung Shin Park
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea
| | - Se Song Jang
- Department of Biomedical Sciences, Seoul National University Graduate School, Seoul, Republic of Korea
| | - Chang Ho Ahn
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea
| | - Jung Hee Kim
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea
| | - Hye Seung Jung
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea
| | - Young Min Cho
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Young Ah Lee
- Department of Pediatrics, Seoul National University Hospital, Seoul, Republic of Korea
| | - Choong Ho Shin
- Department of Pediatrics, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Pediatrics, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jong Hee Chae
- Department of Pediatrics, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Pediatrics, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jae Hyun Kim
- Department of Pediatrics, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Sung Hee Choi
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
- Department of Internal Medicine, Seoul National University Bundang Hospital
| | - Hak C Jang
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
- Department of Internal Medicine, Seoul National University Bundang Hospital
| | - Jee Cheol Bae
- Department of Internal Medicine, Samsung Changwon Hospital, Changwon, Republic of Korea
| | - Jong Cheol Won
- Department of Internal Medicine, Sanggye Paik Hospital, Seoul, Republic of Korea
| | - Sung-Hoon Kim
- Department of Internal Medicine, Cheil General Hospital & Women's Healthcare Center, Seoul, Republic of Korea
- Department of Internal Medicine, Dankook University College of Medicine, Seoul, Republic of Korea
| | - Jong-Il Kim
- Department of Biomedical Sciences, Seoul National University Graduate School, Seoul, Republic of Korea
- Department of Biochemistry and Molecular Biology, Seoul National University College of Medicine, Seoul, Republic of Korea
- Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, Republic of Korea
| | - Soo Heon Kwak
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea
| | - Kyong Soo Park
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Republic of Korea
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Abstract
PURPOSE OF REVIEW Monogenic forms of diabetes have specific treatments that differ from the standard care provided for type 1 and type 2 diabetes, making the appropriate diagnosis essential. In this review, we discuss current clinical challenges that remain, including improving case-finding strategies, particularly those that have transethnic applicability, and understanding the interpretation of genetic variants as pathogenic, with clinically meaningful impacts. RECENT FINDINGS Biomarker approaches to the stratification for genetic testing now appear to be most effective in identifying cases of monogenic diabetes, and use of genetic risk scores may also prove useful. However, applicability in all ethnic groups is lacking. Challenges remain in the classification of genes as diabetes-causing and the interpretation of genetic variants at the clinical interface. Since the discovery that genetic defects can cause neonatal or young-onset diabetes, multiple causal genes have been identified and there have been many advances in strategies to detect genetic forms of diabetes and their treatments. Approaches learnt from monogenic diabetes are now being translated to polygenic diabetes.
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Affiliation(s)
- Shivani Misra
- Diabetes, Endocrinology & Metabolism, Imperial College London, Ground Floor Medical School, St Mary’s Campus, Norfolk Place, London, W2 1PG UK
| | - Katharine R. Owen
- Oxford Centre for Diabetes, Endocrinology & Metabolism, University of Oxford, Oxford, OX3 7LJ UK
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Pace NP, Craus J, Felice A, Vassallo J. Case Report: Identification of an HNF1B p.Arg527Gln mutation in a Maltese patient with atypical early onset diabetes and diabetic nephropathy. BMC Endocr Disord 2018; 18:28. [PMID: 29764441 PMCID: PMC5952643 DOI: 10.1186/s12902-018-0257-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2018] [Accepted: 05/03/2018] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND The diagnosis of atypical non-autoimmune forms of diabetes mellitus, such as maturity onset diabetes of the young (MODY) presents several challenges, in view of the extensive clinical and genetic heterogeneity of the disease. In this report we describe a case of atypical non autoimmune diabetes associated with a damaging HNF1β mutation. This is distinguished by a number of uncharacteristic clinical features, including early-onset obesity, the absence of renal cysts and diabetic nephropathy. HNF1β-MODY (MODY5) is an uncommon form of monogenic diabetes that is often complicated by a wide array of congenital morphological anomalies of the urinary tract, including renal cysts. This report expands on the clinical phenotypes that have been described in the context of HNF1β mutations, and is relevant as only isolated cases of diabetic nephropathy in the setting of MODY5 have been reported. CASE PRESENTATION An obese Maltese female with non-autoimmune diabetes, microalbuminuria, glomerular hyperfiltration, fatty liver and no renal cysts was studied by whole exome sequencing to investigate potential genes responsible for the proband's phenotype. A rare missense mutation at a highly conserved site in exon 8 of HNF1β was identified (c.1580G > A, NM_000458.3, p.Arg527Gln), with multiple in-silico predictions consistent with pathogenicity. This mutation has not been previously characterised. Additionally, several common susceptibility variants associated with early-onset obesity, polygenic type 2 diabetes and nephropathy were identified in the proband that could impose additional effects on the phenotype, its severity or its clinical course. CONCLUSION This report highlights several atypical features in a proband with atypical diabetes associated with an HNF1β missense mutation. It also reinforces the concept that monogenic causes of diabetes could be significant contributors to disease burden in obese individuals with atypical diabetes.
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Affiliation(s)
- Nikolai Paul Pace
- Centre for Molecular Medicine and Biobanking, University of Malta, Msida, Malta
| | - Johann Craus
- Department of Obstetrics and Gynaecology, University of Malta, Msida, Malta
| | - Alex Felice
- Centre for Molecular Medicine and Biobanking, University of Malta, Msida, Malta
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Abstract
PURPOSE OF REVIEW South Asia is one of the epicenters of the global diabetes pandemic. Diabetes in south Asians has certain peculiar features with respect to its pathophysiology, clinical presentation, and management. This review aims to summarize some of the recent evidence pertaining to the distinct diabetes phenotype in south Asians. RECENT FINDINGS South Asia has high incidence and prevalence rates of diabetes. The progression from "pre-diabetes" to diabetes also occurs faster in this population. Pancreatic beta cell dysfunction seems to be as important as insulin resistance in the pathophysiology of diabetes in south Asians. Recent evidence suggests that the epidemic of diabetes in south Asia is spreading to rural areas and to less affluent sections of society. Diabetes in south Asians differs significantly from that in white Caucasians, with important implications for prevention, diagnosis, and management.
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Affiliation(s)
- Ranjit Unnikrishnan
- Department of Diabetology, Dr. Mohan's Diabetes Specialities Centre & Madras Diabetes Research Foundation, ICMR Centre for Advanced Research on Diabetes, WHO Collaborating Centre, Non-Communicable Disease Prevention & Control & IDF Centre of Excellence in Diabetes Care, No 4, Conran Smith Road, Gopalapuram, Chennai, 600 086, India
| | - Prasanna Kumar Gupta
- Department of Diabetology, Dr. Mohan's Diabetes Specialities Centre & Madras Diabetes Research Foundation, ICMR Centre for Advanced Research on Diabetes, WHO Collaborating Centre, Non-Communicable Disease Prevention & Control & IDF Centre of Excellence in Diabetes Care, No 4, Conran Smith Road, Gopalapuram, Chennai, 600 086, India
| | - Viswanathan Mohan
- Department of Diabetology, Dr. Mohan's Diabetes Specialities Centre & Madras Diabetes Research Foundation, ICMR Centre for Advanced Research on Diabetes, WHO Collaborating Centre, Non-Communicable Disease Prevention & Control & IDF Centre of Excellence in Diabetes Care, No 4, Conran Smith Road, Gopalapuram, Chennai, 600 086, India.
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Davis TM, Makepeace AE, Ellard S, Colclough K, Peters K, Hattersley A, Davis WA. The prevalence of monogenic diabetes in Australia: the Fremantle Diabetes Study Phase II. Med J Aust 2017; 207:344-347. [PMID: 29020906 DOI: 10.5694/mja16.01201] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2016] [Accepted: 01/06/2017] [Indexed: 11/17/2022]
Abstract
OBJECTIVE To determine the prevalence of monogenic diabetes in an Australian community. DESIGN Longitudinal observational study of a cohort recruited between 2008 and 2011. SETTING Urban population of 157 000 people (Fremantle, Western Australia). PARTICIPANTS 1668 (of 4639 people with diabetes) who consented to participation (36.0% participation). MAIN OUTCOME MEASURES Prevalence of maturity-onset diabetes of the young (MODY) and permanent neonatal diabetes in patients under 35 years of age, from European and non-European ethnic backgrounds, who were at risk of MODY according to United Kingdom risk prediction models, and who were then genotyped for relevant mutations. RESULTS Twelve of 148 young participants with European ethnic backgrounds (8%) were identified by the risk prediction model as likely to have MODY; four had a glucokinase gene mutation. Thirteen of 45 with non-European ethnic backgrounds (28%) were identified as likely to have MODY, but none had a relevant mutation (DNA unavailable for one patient). Two patients with European ethnic backgrounds (one likely to have MODY) had neonatal diabetes. The estimated MODY prevalence among participants with diagnosed diabetes was 0.24% (95% confidence interval [CI], 0.08-0.66%), an overall population prevalence of 89 cases per million; the prevalence of permanent neonatal diabetes was 0.12% (95% CI, 0.02-0.48%) and the population prevalence 45 cases per million. CONCLUSIONS One in 280 Australians diagnosed with diabetes have a monogenic form; most are of European ethnicity. Diagnosing MODY and neonatal diabetes is important because their management (including family screening) and prognosis can differ significantly from those for types 1 and 2 diabetes.
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Affiliation(s)
| | | | - Sian Ellard
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, United Kingdom
| | - Kevin Colclough
- Royal Devon and Exeter NHS Foundation Trust, Exeter, United Kingdom
| | | | - Andrew Hattersley
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, United Kingdom
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