1
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Osaki A, Ozawa A, Morita A, Higeta D, Suda S, Ohtsu Y, Yoshino S, Matsumoto S, Horiguchi K, Yamada E. Hidden MODY in Young Lean Women with Mild Glucose Intolerance Detected during Health Check-ups: Potential for Improved Pregnancy Outcomes through Preconception Care. Intern Med 2025; 64:1603-1607. [PMID: 39462596 DOI: 10.2169/internalmedicine.4244-24] [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] [Indexed: 10/29/2024] Open
Abstract
Mild glucose intolerance (positive urine glucose or mild hyperglycemia) during health checkups in young, lean women may require specialist consultation. We herein report a 31-year-old Japanese woman with mild hyperglycemia detected during a checkup who was diagnosed with overt diabetes in pregnancy and HNF4A-MODY postpartum, without prior follow-up. This case highlights the following: MODY may be present in young, lean women with mild glucose intolerance, and preconception care may improve pregnancy outcomes. Fetal outcomes vary with MODY subtype. Preconception care is important.
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Affiliation(s)
- Aya Osaki
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Gunma University Graduate School of Medicine, Japan
| | - Atsushi Ozawa
- Division of Fundamental Nursing, Department of Nursing, Gunma University, Japan
| | - Akihito Morita
- Department of Obstetrics and Gynecology, Gunma University Graduate School of Medicine, Japan
| | - Daisuke Higeta
- Department of Obstetrics and Gynecology, Gunma University Graduate School of Medicine, Japan
| | - Shunpei Suda
- Department of Pediatrics, Gunma University Graduate School of Medicine, Japan
| | - Yoshiaki Ohtsu
- Department of Pediatrics, Gunma University Graduate School of Medicine, Japan
| | - Satoshi Yoshino
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Gunma University Graduate School of Medicine, Japan
| | - Syunichi Matsumoto
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Gunma University Graduate School of Medicine, Japan
| | - Kazuhiko Horiguchi
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Gunma University Graduate School of Medicine, Japan
| | - Eijiro Yamada
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Gunma University Graduate School of Medicine, Japan
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2
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Zaicenoka M, Ramensky VE, Kiseleva AV, Bukaeva AA, Blokhina AV, Ershova AI, Meshkov AN, Drapkina OM. On Penetrance Estimation in Family, Clinical, and Population Cohorts. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2025; 18:e004816. [PMID: 40151935 DOI: 10.1161/circgen.124.004816] [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: 03/29/2025]
Abstract
In recent years, there has been a considerable influx of publications assessing the penetrance of pathogenic variants associated with monogenic diseases with dominant inheritance. As large and diverse groups have been sequenced, it has become clear that incomplete penetrance is common to most hereditary diseases, as numerous molecular, genetic, or environmental factors can cause clinical diversity among the carriers of the same variant. In this review, we discuss some of these factors and focus on the existing approaches to estimating penetrance, depending on the data available and their application to different data sets. We also list some currently available large-scale data sets with penetrance estimates.
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Affiliation(s)
- Marija Zaicenoka
- Genome and Medical Bioinformatics Laboratory, Institute of Personalized Therapy and Prevention (M.Z., V.E.R.), Moscow, Russia
- Moscow Center for Advanced Studies, Moscow, Russia (M.Z.)
| | - Vasily E Ramensky
- Genome and Medical Bioinformatics Laboratory, Institute of Personalized Therapy and Prevention (M.Z., V.E.R.), Moscow, Russia
- Faculty of Bioengineering and Bioinformatics (V.E.R.), Lomonosov Moscow State University, Moscow, Russia
- Institute for Artificial Intelligence (V.E.R.), Lomonosov Moscow State University, Moscow, Russia
| | - Anna V Kiseleva
- Laboratory of Molecular Genetics, Institute of Personalized Therapy and Prevention (A.V.K.), Moscow, Russia
| | - Anna A Bukaeva
- Laboratory of Clinomics (A.A.B., A.V.B., A.I.E.), Moscow, Russia
| | | | | | - Alexey N Meshkov
- Institute of Personalized Therapy and Prevention (A.N.M.), Moscow, Russia
- National Medical Research Center for Cardiology, Moscow, Russia (A.N.M.)
- Research Center for Medical Genetics, Moscow, Russia (A.N.M.)
- Pirogov Russian National Research Medical University, Moscow, Russia, Moscow, Russia (A.N.M.)
| | - Oxana M Drapkina
- Department of Fundamental and Applied Aspects of Obesity (O.M.D.), Moscow, Russia
- National Medical Research Center for Therapy and Preventive Medicine, Moscow, Russia (O.M.D.)
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3
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Bazzazzadehgan S, Shariat-Madar Z, Mahdi F. Distinct Roles of Common Genetic Variants and Their Contributions to Diabetes: MODY and Uncontrolled T2DM. Biomolecules 2025; 15:414. [PMID: 40149950 PMCID: PMC11940602 DOI: 10.3390/biom15030414] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2024] [Revised: 01/26/2025] [Accepted: 03/10/2025] [Indexed: 03/29/2025] Open
Abstract
Type 2 diabetes mellitus (T2DM) encompasses a range of clinical manifestations, with uncontrolled diabetes leading to progressive or irreversible damage to various organs. Numerous genes associated with monogenic diabetes, exhibiting classical patterns of inheritance (autosomal dominant or recessive), have been identified. Additionally, genes involved in complex diabetes, which interact with environmental factors to trigger the disease, have also been discovered. These genetic findings have raised hopes that genetic testing could enhance diagnostics, disease surveillance, treatment selection, and family counseling. However, the accurate interpretation of genetic data remains a significant challenge, as variants may not always be definitively classified as either benign or pathogenic. Research to date, however, indicates that periodic reevaluation of genetic variants in diabetes has led to more consistent findings, with biases being steadily eliminated. This has improved the interpretation of variants across diverse ethnicities. Clinical studies suggest that genetic risk information may motivate patients to adopt behaviors that promote the prevention or management of T2DM. Given that the clinical features of certain monogenic diabetes types overlap with T2DM, and considering the significant role of genetic variants in diabetes, healthcare providers caring for prediabetic patients should consider genetic testing as part of the diagnostic process. This review summarizes current knowledge of the most common genetic variants associated with T2DM, explores novel therapeutic targets, and discusses recent advancements in the pharmaceutical management of uncontrolled T2DM.
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Affiliation(s)
- Shadi Bazzazzadehgan
- Department of Pharmacy Administration, School of Pharmacy, University of Mississippi, University, MS 38677, USA;
| | - Zia Shariat-Madar
- Division of Pharmacology, School of Pharmacy, University of Mississippi, Oxford, MS 38677, USA;
| | - Fakhri Mahdi
- Division of Pharmacology, School of Pharmacy, University of Mississippi, Oxford, MS 38677, USA;
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4
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Huerta-Chagoya A, Schroeder P, Mandla R, Li J, Morris L, Vora M, Alkanaq A, Nagy D, Szczerbinski L, Madsen JGS, Bonàs-Guarch S, Mollandin F, Cole JB, Porneala B, Westerman K, Li JH, Pollin TI, Florez JC, Gloyn AL, Carey DJ, Cebola I, Mirshahi UL, Manning AK, Leong A, Udler M, Mercader JM. Rare variant analyses in 51,256 type 2 diabetes cases and 370,487 controls reveal the pathogenicity spectrum of monogenic diabetes genes. Nat Genet 2024; 56:2370-2379. [PMID: 39379762 PMCID: PMC11549050 DOI: 10.1038/s41588-024-01947-9] [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: 10/31/2023] [Accepted: 09/10/2024] [Indexed: 10/10/2024]
Abstract
Type 2 diabetes (T2D) genome-wide association studies (GWASs) often overlook rare variants as a result of previous imputation panels' limitations and scarce whole-genome sequencing (WGS) data. We used TOPMed imputation and WGS to conduct the largest T2D GWAS meta-analysis involving 51,256 cases of T2D and 370,487 controls, targeting variants with a minor allele frequency as low as 5 × 10-5. We identified 12 new variants, including a rare African/African American-enriched enhancer variant near the LEP gene (rs147287548), associated with fourfold increased T2D risk. We also identified a rare missense variant in HNF4A (p.Arg114Trp), associated with eightfold increased T2D risk, previously reported in maturity-onset diabetes of the young with reduced penetrance, but observed here in a T2D GWAS. We further leveraged these data to analyze 1,634 ClinVar variants in 22 genes related to monogenic diabetes, identifying two additional rare variants in HNF1A and GCK associated with fivefold and eightfold increased T2D risk, respectively, the effects of which were modified by the individual's polygenic risk score. For 21% of the variants with conflicting interpretations or uncertain significance in ClinVar, we provided support of being benign based on their lack of association with T2D. Our work provides a framework for using rare variant GWASs to identify large-effect variants and assess variant pathogenicity in monogenic diabetes genes.
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Affiliation(s)
- Alicia Huerta-Chagoya
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Philip Schroeder
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Ravi Mandla
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
- Graduate Program in Genomics and Computational Biology, University of Pennsylvania, Philadelphia, PA, USA
| | - Jiang Li
- Department of Genomic Health, Geisinger, Danville, PA, USA
| | - Lowri Morris
- Section of Genetics and Genomics, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Maheak Vora
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Ahmed Alkanaq
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Dorka Nagy
- Section of Genetics and Genomics, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- National Heart and Lung Institute, Faculty of Medicine, London, UK
| | - Lukasz Szczerbinski
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Endocrinology, Diabetology and Internal Medicine, Medical University of Bialystok, Bialystok, Poland
- Clinical Research Centre, Medical University of Bialystok, Bialystok, Poland
| | - Jesper G S Madsen
- Institute of Mathematics and Computer Science, University of Southern Denmark, Odense, Denmark
- The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark
| | - Silvia Bonàs-Guarch
- Centre for Genomic Regulation, The Barcelona Institute of Science and Technology, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas, Madrid, Spain
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Fanny Mollandin
- Centre for Genomic Regulation, The Barcelona Institute of Science and Technology, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas, Madrid, Spain
| | - Joanne B Cole
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of Endocrinology, Boston Children's Hospital, Boston, MA, USA
- Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO, USA
| | - Bianca Porneala
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Kenneth Westerman
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Josephine H Li
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Toni I Pollin
- University of Maryland, School of Medicine, Baltimore, MD, USA
| | - Jose C Florez
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Endocrine Division, Massachusetts General Hospital, Boston, MA, USA
| | - Anna L Gloyn
- Department of Pediatrics, Division of Endocrinology, Stanford School of Medicine, Stanford, CA, USA
| | - David J Carey
- Department of Genomic Health, Geisinger, Danville, PA, USA
| | - Inês Cebola
- Section of Genetics and Genomics, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | | | - Alisa K Manning
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Aaron Leong
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Endocrine Division, Massachusetts General Hospital, Boston, MA, USA
| | - Miriam Udler
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Josep M Mercader
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA.
- Department of Medicine, Harvard Medical School, Boston, MA, USA.
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5
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Li Y, Polychronakos C. Parsing the spectrum of allelic architectures in diabetes. Nat Genet 2024; 56:2297-2298. [PMID: 39402157 DOI: 10.1038/s41588-024-01950-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2024]
Affiliation(s)
- Yangxi Li
- Children's Hospital of Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Regional Center for Children's Health, Hangzhou, Zhejiang, China
| | - Constantin Polychronakos
- Children's Hospital of Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Regional Center for Children's Health, Hangzhou, Zhejiang, China.
- Endocrine Genetics Laboratory, Department of Pediatrics, The Research Institute of the McGill University Health Centre, Montréal, Québec, Canada.
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6
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Wright CF, Sharp LN, Jackson L, Murray A, Ware JS, MacArthur DG, Rehm HL, Patel KA, Weedon MN. Guidance for estimating penetrance of monogenic disease-causing variants in population cohorts. Nat Genet 2024; 56:1772-1779. [PMID: 39075210 DOI: 10.1038/s41588-024-01842-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Accepted: 06/24/2024] [Indexed: 07/31/2024]
Abstract
Penetrance is the probability that an individual with a pathogenic genetic variant develops a specific disease. Knowing the penetrance of variants for monogenic disorders is important for counseling of individuals. Until recently, estimates of penetrance have largely relied on affected individuals and their at-risk family members being clinically referred for genetic testing, a 'phenotype-first' approach. This approach substantially overestimates the penetrance of variants because of ascertainment bias. The recent availability of whole-genome sequencing data in individuals from very-large-scale population-based cohorts now allows 'genotype-first' estimates of penetrance for many conditions. Although this type of population-based study can underestimate penetrance owing to recruitment biases, it provides more accurate estimates of penetrance for secondary or incidental findings. Here, we provide guidance for the conduct of penetrance studies to ensure that robust genotypes and phenotypes are used to accurately estimate penetrance of variants and groups of similarly annotated variants from population-based studies.
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Affiliation(s)
- Caroline F Wright
- Department of Clinical and Biomedical Sciences, Medical School, University of Exeter, Exeter, UK.
| | - Luke N Sharp
- Department of Clinical and Biomedical Sciences, Medical School, University of Exeter, Exeter, UK
| | - Leigh Jackson
- Department of Clinical and Biomedical Sciences, Medical School, University of Exeter, Exeter, UK
| | - Anna Murray
- Department of Clinical and Biomedical Sciences, Medical School, University of Exeter, Exeter, UK
| | - James S Ware
- National Heart and Lung Institute and MRC Laboratory of Medical Sciences, Imperial College London, London, UK
- Hammersmith Hospital, Imperial College Healthcare NHS Trust, London, UK
- Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Daniel G MacArthur
- Centre for Population Genomics, Garvan Institute of Medical Research and UNSW Sydney, Sydney, New South Wales, Australia
- Centre for Population Genomics, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Heidi L Rehm
- Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Kashyap A Patel
- Department of Clinical and Biomedical Sciences, Medical School, University of Exeter, Exeter, UK
| | - Michael N Weedon
- Department of Clinical and Biomedical Sciences, Medical School, University of Exeter, Exeter, UK.
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7
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Kind L, Molnes J, Tjora E, Raasakka A, Myllykoski M, Colclough K, Saint-Martin C, Adelfalk C, Dusatkova P, Pruhova S, Valtonen-André C, Bellanné-Chantelot C, Arnesen T, Kursula P, Njølstad PR. Molecular mechanism of HNF-1A-mediated HNF4A gene regulation and promoter-driven HNF4A-MODY diabetes. JCI Insight 2024; 9:e175278. [PMID: 38855865 PMCID: PMC11382887 DOI: 10.1172/jci.insight.175278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Accepted: 04/25/2024] [Indexed: 06/11/2024] Open
Abstract
Monogenic diabetes is a gateway to precision medicine through molecular mechanistic insight. Hepatocyte nuclear factor 1A (HNF-1A) and HNF-4A are transcription factors that engage in crossregulatory gene transcription networks to maintain glucose-stimulated insulin secretion in pancreatic β cells. Variants in the HNF1A and HNF4A genes are associated with maturity-onset diabetes of the young (MODY). Here, we explored 4 variants in the P2-HNF4A promoter region: 3 in the HNF-1A binding site and 1 close to the site, which were identified in 63 individuals from 21 families of different MODY disease registries across Europe. Our goal was to study the disease causality for these variants and to investigate diabetes mechanisms on the molecular level. We solved a crystal structure of HNF-1A bound to the P2-HNF4A promoter and established a set of techniques to probe HNF-1A binding and transcriptional activity toward different promoter variants. We used isothermal titration calorimetry, biolayer interferometry, x-ray crystallography, and transactivation assays, which revealed changes in HNF-1A binding or transcriptional activities for all 4 P2-HNF4A variants. Our results suggest distinct disease mechanisms of the promoter variants, which can be correlated with clinical phenotype, such as age of diagnosis of diabetes, and be important tools for clinical utility in precision medicine.
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Affiliation(s)
- Laura Kind
- Department of Biomedicine and
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Janne Molnes
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Medical Genetics and
| | - Erling Tjora
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Pediatrics and Adolescent Medicine, Haukeland University Hospital, Bergen, Norway
| | | | | | - Kevin Colclough
- Exeter Genomics Laboratory, Royal Devon and Exeter NHS Foundation Trust, Exeter, United Kingdom
| | - Cécile Saint-Martin
- Department of Medical Genetics, Sorbonne Université, AP-HP, Pitié-Salpêtrière Hospital, DMU BioGeM, Paris, France
- Monogenic Diabetes Study Group of the Société Francophone du Diabète, Paris, France
| | - Caroline Adelfalk
- Clinical Genetics, Pathology and Molecular Diagnostics, University Hospital Skåne, Lund, Sweden
| | - Petra Dusatkova
- Department of Pediatrics, 2nd Faculty of Medicine, Charles University and University Hospital Motol, Prague, Czech Republic
| | - Stepanka Pruhova
- Department of Pediatrics, 2nd Faculty of Medicine, Charles University and University Hospital Motol, Prague, Czech Republic
| | | | - Christine Bellanné-Chantelot
- Department of Medical Genetics, Sorbonne Université, AP-HP, Pitié-Salpêtrière Hospital, DMU BioGeM, Paris, France
- Monogenic Diabetes Study Group of the Société Francophone du Diabète, Paris, France
| | - Thomas Arnesen
- Department of Biomedicine and
- Department of Surgery, Haukeland University Hospital, Bergen, Norway
| | - Petri Kursula
- Department of Biomedicine and
- Faculty of Biochemistry and Molecular Medicine & Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Pål Rasmus Njølstad
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
- Section of Endocrinology and Metabolism, Children and Youth Clinic, Haukeland University Hospital, Bergen, Norway
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8
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Kaci A, Solheim MH, Silgjerd T, Hjaltadottir J, Hornnes LH, Molnes J, Madsen A, Sjøholt G, Bellanné-Chantelot C, Caswell R, Sagen JV, Njølstad PR, Aukrust I, Bjørkhaug L. Functional characterization of HNF4A gene variants identify promoter and cell line specific transactivation effects. Hum Mol Genet 2024; 33:894-904. [PMID: 38433330 PMCID: PMC11070132 DOI: 10.1093/hmg/ddae027] [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: 10/27/2023] [Revised: 01/26/2024] [Accepted: 02/11/2024] [Indexed: 03/05/2024] Open
Abstract
Hepatocyte nuclear factor-4 alpha (HNF-4A) regulates genes with roles in glucose metabolism and β-cell development. Although pathogenic HNF4A variants are commonly associated with maturity-onset diabetes of the young (MODY1; HNF4A-MODY), rare phenotypes also include hyperinsulinemic hypoglycemia, renal Fanconi syndrome and liver disease. While the association of rare functionally damaging HNF1A variants with HNF1A-MODY and type 2 diabetes is well established owing to robust functional assays, the impact of HNF4A variants on HNF-4A transactivation in tissues including the liver and kidney is less known, due to lack of similar assays. Our aim was to investigate the functional effects of seven HNF4A variants, located in the HNF-4A DNA binding domain and associated with different clinical phenotypes, by various functional assays and cell lines (transactivation, DNA binding, protein expression, nuclear localization) and in silico protein structure analyses. Variants R85W, S87N and R89W demonstrated reduced DNA binding to the consensus HNF-4A binding elements in the HNF1A promoter (35, 13 and 9%, respectively) and the G6PC promoter (R85W ~10%). While reduced transactivation on the G6PC promoter in HepG2 cells was shown for S87N (33%), R89W (65%) and R136W (35%), increased transactivation by R85W and R85Q was confirmed using several combinations of target promoters and cell lines. R89W showed reduced nuclear levels. In silico analyses supported variant induced structural impact. Our study indicates that cell line specific functional investigations are important to better understand HNF4A-MODY genotype-phenotype correlations, as our data supports ACMG/AMP interpretations of loss-of-function variants and propose assay-specific HNF4A control variants for future functional investigations.
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Affiliation(s)
- Alba Kaci
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Haukelandsbakken 1, Bergen 5020, Norway
- Center for Laboratory Medicine, Østfold Hospital Trust, Kalnesveien 300, Grålum 1714, Norway
| | - Marie Holm Solheim
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Haukelandsbakken 1, Bergen 5020, Norway
| | - Trine Silgjerd
- Department of Safety, Chemistry, and Biomedical Laboratory Sciences, Western Norway University of Applied Sciences, Inndalsveien 28, Bergen 5020, Norway
| | - Jorunn Hjaltadottir
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Haukelandsbakken 1, Bergen 5020, Norway
- Department of Safety, Chemistry, and Biomedical Laboratory Sciences, Western Norway University of Applied Sciences, Inndalsveien 28, Bergen 5020, Norway
| | - Lorentze Hope Hornnes
- Department of Medical Biochemistry and Pharmacology, Haukeland University Hospital, Jonas Lies veg 87, Bergen 5021, Norway
| | - Janne Molnes
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Haukelandsbakken 1, Bergen 5020, Norway
- Department of Medical Genetics, Haukeland University Hospital, Jonas Lies veg 87, Bergen 5021, Norway
| | - Andre Madsen
- Department of Clinical Science, University of Bergen, Jonas Lies veg 87, Bergen 5020, Norway
| | - Gry Sjøholt
- Department of Safety, Chemistry, and Biomedical Laboratory Sciences, Western Norway University of Applied Sciences, Inndalsveien 28, Bergen 5020, Norway
| | - Christine Bellanné-Chantelot
- Départment of Medical Genetics, Sorbonne University, AP-HP, Hôpital Pitié-Salpêtriére, 21 rue de l'école de médecine, 75006 Paris, France
| | - Richard Caswell
- Exeter Genomics Laboratory, Royal Devon University Healthcare NHS Foundation Trust, Barrack Rd, Exeter EX2 5DW, United Kingdom
| | - Jørn V Sagen
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Haukelandsbakken 1, Bergen 5020, Norway
- Department of Medical Biochemistry and Pharmacology, Haukeland University Hospital, Jonas Lies veg 87, Bergen 5021, Norway
| | - Pål R Njølstad
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Haukelandsbakken 1, Bergen 5020, Norway
- Children and Youth Clinic, Haukeland University Hospital, Haukelandsbakken 1, Bergen 5021, Norway
| | - Ingvild Aukrust
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Haukelandsbakken 1, Bergen 5020, Norway
- Department of Medical Genetics, Haukeland University Hospital, Jonas Lies veg 87, Bergen 5021, Norway
| | - Lise Bjørkhaug
- Department of Safety, Chemistry, and Biomedical Laboratory Sciences, Western Norway University of Applied Sciences, Inndalsveien 28, Bergen 5020, Norway
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Schmidt RJ, Steeves M, Bayrak-Toydemir P, Benson KA, Coe BP, Conlin LK, Ganapathi M, Garcia J, Gollob MH, Jobanputra V, Luo M, Ma D, Maston G, McGoldrick K, Palculict TB, Pesaran T, Pollin TI, Qian E, Rehm HL, Riggs ER, Schilit SLP, Sergouniotis PI, Tvrdik T, Watkins N, Zec L, Zhang W, Lebo MS. Recommendations for risk allele evidence curation, classification, and reporting from the ClinGen Low Penetrance/Risk Allele Working Group. Genet Med 2024; 26:101036. [PMID: 38054408 PMCID: PMC10939896 DOI: 10.1016/j.gim.2023.101036] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 11/28/2023] [Accepted: 11/30/2023] [Indexed: 12/07/2023] Open
Abstract
PURPOSE Genetic variants at the low end of the penetrance spectrum have historically been challenging to interpret because their high population frequencies exceed the disease prevalence of the associated condition, leading to a lack of clear segregation between the variant and disease. There is currently substantial variation in the classification of these variants, and no formal classification framework has been widely adopted. The Clinical Genome Resource Low Penetrance/Risk Allele Working Group was formed to address these challenges and promote harmonization within the clinical community. METHODS The work presented here is the product of internal and community Likert-scaled surveys in combination with expert consensus within the Working Group. RESULTS We formally recognize risk alleles and low-penetrance variants as distinct variant classes from those causing highly penetrant disease that require special considerations regarding their clinical classification and reporting. First, we provide a preferred terminology for these variants. Second, we focus on risk alleles and detail considerations for reviewing relevant studies and present a framework for the classification these variants. Finally, we discuss considerations for clinical reporting of risk alleles. CONCLUSION These recommendations support harmonized interpretation, classification, and reporting of variants at the low end of the penetrance spectrum.
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Affiliation(s)
- Ryan J Schmidt
- Children's Hospital Los Angeles, Keck School of Medicine of USC, Los Angeles, CA.
| | | | - Pinar Bayrak-Toydemir
- Department of Pathology, University of Utah Molecular Genetics and Genomics, ARUP Laboratories, Salt Lake City, UT
| | - Katherine A Benson
- School of Pharmacy and Biomolecular Sciences, Royal College of Surgeons in Ireland, Ireland
| | - Bradley P Coe
- Department of Pathology & Lab Medicine, BC Children's & BC Women's Hospitals, Vancouver, Canada
| | - Laura K Conlin
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA; Division of Genomic Diagnostics, Children's Hospital of Philadelphia, Philadelphia, PA
| | - Mythily Ganapathi
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY
| | | | - Michael H Gollob
- Inherited Arrhythmia and Cardiomyopathy Program, Division of Cardiology, Toronto General Hospital and Department of Physiology, University of Toronto, Toronto, Ontario, Canada
| | - Vaidehi Jobanputra
- New York Genome Center, New York, NY; Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY
| | - Minjie Luo
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA; Division of Genomic Diagnostics, Children's Hospital of Philadelphia, Philadelphia, PA
| | - Deqiong Ma
- DNA diagnostic lab, Department of Genetics, School of Medicine, Yale University, New Haven, CT
| | | | | | | | | | - Toni I Pollin
- University of Maryland School of Medicine, Baltimore, MD
| | - Emily Qian
- Department of Genetics, Yale University School of Medicine, New Haven, CT
| | - Heidi L Rehm
- Center for Genomics Medicine, Massachusetts General Hospital, Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
| | - Erin R Riggs
- Geisinger Autism & Developmental Medicine Institute, Lewisburg, PA
| | - Samantha L P Schilit
- Mass General Brigham, Brigham and Woman's Hospital, Harvard Medical School, Boston, MA
| | | | - Tatiana Tvrdik
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA
| | - Nicholas Watkins
- Department of Pathology and Laboratory Medicine, Sinai Health System, Toronto, Ontario, Canada Department of Molecular Genetics, University of Toronto, Toronto, Canada
| | | | - Wenying Zhang
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH
| | - Matthew S Lebo
- Mass General Brigham, Brigham and Woman's Hospital, Harvard Medical School, Broad Institute of MIT and Harvard, Cambridge, MA.
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10
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Murphy R, Colclough K, Pollin TI, Ikle JM, Svalastoga P, Maloney KA, Saint-Martin C, Molnes J, Misra S, Aukrust I, de Franco E, Flanagan SE, Njølstad PR, Billings LK, Owen KR, Gloyn AL. The use of precision diagnostics for monogenic diabetes: a systematic review and expert opinion. COMMUNICATIONS MEDICINE 2023; 3:136. [PMID: 37794142 PMCID: PMC10550998 DOI: 10.1038/s43856-023-00369-8] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Accepted: 09/21/2023] [Indexed: 10/06/2023] Open
Abstract
BACKGROUND Monogenic diabetes presents opportunities for precision medicine but is underdiagnosed. This review systematically assessed the evidence for (1) clinical criteria and (2) methods for genetic testing for monogenic diabetes, summarized resources for (3) considering a gene or (4) variant as causal for monogenic diabetes, provided expert recommendations for (5) reporting of results; and reviewed (6) next steps after monogenic diabetes diagnosis and (7) challenges in precision medicine field. METHODS Pubmed and Embase databases were searched (1990-2022) using inclusion/exclusion criteria for studies that sequenced one or more monogenic diabetes genes in at least 100 probands (Question 1), evaluated a non-obsolete genetic testing method to diagnose monogenic diabetes (Question 2). The risk of bias was assessed using the revised QUADAS-2 tool. Existing guidelines were summarized for questions 3-5, and review of studies for questions 6-7, supplemented by expert recommendations. Results were summarized in tables and informed recommendations for clinical practice. RESULTS There are 100, 32, 36, and 14 studies included for questions 1, 2, 6, and 7 respectively. On this basis, four recommendations for who to test and five on how to test for monogenic diabetes are provided. Existing guidelines for variant curation and gene-disease validity curation are summarized. Reporting by gene names is recommended as an alternative to the term MODY. Key steps after making a genetic diagnosis and major gaps in our current knowledge are highlighted. CONCLUSIONS We provide a synthesis of current evidence and expert opinion on how to use precision diagnostics to identify individuals with monogenic diabetes.
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Affiliation(s)
- Rinki Murphy
- Department of Medicine, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.
- Auckland Diabetes Centre, Te Whatu Ora Health New Zealand, Te Tokai Tumai, Auckland, New Zealand.
| | - Kevin Colclough
- Exeter Genomics Laboratory, Royal Devon University Healthcare NHS Foundation Trust, Exeter, United Kingdom
| | - Toni I Pollin
- Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Jennifer M Ikle
- Department of Pediatrics, Division of Endocrinology & Diabetes, Stanford School of Medicine, Stanford, CA, USA
- Stanford Diabetes Research Center, Stanford School of Medicine, Stanford, CA, USA
| | - Pernille Svalastoga
- Children and Youth Clinic, Haukeland University Hospital, Bergen, Norway
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Kristin A Maloney
- Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Cécile Saint-Martin
- Department of Medical Genetics, AP-HP Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
| | - Janne Molnes
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - Shivani Misra
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- Department of Diabetes and Endocrinology, Imperial College Healthcare NHS Trust, London, UK
| | - Ingvild Aukrust
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - Elisa de Franco
- Department of Clinical and Biomedical Science, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Sarah E Flanagan
- Department of Clinical and Biomedical Science, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Pål R Njølstad
- Children and Youth Clinic, Haukeland University Hospital, Bergen, Norway
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Liana K Billings
- Division of Endocrinology, NorthShore University HealthSystem, Skokie, IL, USA
- Department of Medicine, Pritzker School of Medicine, University of Chicago, Chicago, IL, USA
| | - Katharine R Owen
- Oxford Center for Diabetes, Endocrinology & Metabolism, University of Oxford, Oxford, UK
- NIHR Oxford Biomedical Research Centre, Oxford, UK
| | - Anna L Gloyn
- Department of Pediatrics, Division of Endocrinology & Diabetes, Stanford School of Medicine, Stanford, CA, USA.
- Stanford Diabetes Research Center, Stanford School of Medicine, Stanford, CA, USA.
- Department of Genetics, Stanford School of Medicine, Stanford, CA, USA.
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11
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Schroeder P, Mandla R, Huerta-Chagoya A, Alkanak A, Nagy D, Szczerbinski L, Madsen JGS, Cole JB, Porneala B, Westerman K, Li JH, Pollin TI, Florez JC, Gloyn AL, Cebola I, Manning A, Leong A, Udler M, Mercader JM. Rare variant association analysis in 51,256 type 2 diabetes cases and 370,487 controls informs the spectrum of pathogenicity of monogenic diabetes genes. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.09.28.23296244. [PMID: 37808701 PMCID: PMC10557807 DOI: 10.1101/2023.09.28.23296244] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
We meta-analyzed array data imputed with the TOPMed reference panel and whole-genome sequence (WGS) datasets and performed the largest, rare variant (minor allele frequency as low as 5×10-5) GWAS meta-analysis of type 2 diabetes (T2D) comprising 51,256 cases and 370,487 controls. We identified 52 novel variants at genome-wide significance (p<5 × 10-8), including 8 novel variants that were either rare or ancestry-specific. Among them, we identified a rare missense variant in HNF4A p.Arg114Trp (OR=8.2, 95% confidence interval [CI]=4.6-14.0, p = 1.08×10-13), previously reported as a variant implicated in Maturity Onset Diabetes of the Young (MODY) with incomplete penetrance. We demonstrated that the diabetes risk in carriers of this variant was modulated by a T2D common variant polygenic risk score (cvPRS) (carriers in the top PRS tertile [OR=18.3, 95%CI=7.2-46.9, p=1.2×10-9] vs carriers in the bottom PRS tertile [OR=2.6, 95% CI=0.97-7.09, p = 0.06]. Association results identified eight variants of intermediate penetrance (OR>5) in monogenic diabetes (MD), which in aggregate as a rare variant PRS were associated with T2D in an independent WGS dataset (OR=4.7, 95% CI=1.86-11.77], p = 0.001). Our data also provided support evidence for 21% of the variants reported in ClinVar in these MD genes as benign based on lack of association with T2D. Our work provides a framework for using rare variant imputation and WGS analyses in large-scale population-based association studies to identify large-effect rare variants and provide evidence for informing variant pathogenicity.
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Affiliation(s)
- Philip Schroeder
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Ravi Mandla
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine and Cardiovascular Research Institute, Cardiology Division, University of California, San Francisco, CA, USA
| | - Alicia Huerta-Chagoya
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Ahmed Alkanak
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Dorka Nagy
- Section of Genetics and Genomics, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- National Heart and Lung Institute, Faculty of Medicine, London, UK
| | - Lukasz Szczerbinski
- Department of Endocrinology, Diabetology and Internal Medicine, Medical University of Bialystok, Bialystok, 15-276, Poland
- Clinical Research Centre, Medical University of Bialystok, Bialystok, 15-276, Poland
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Jesper G S Madsen
- Institute of Mathematics and Computer Science, University of Southern Denmark, Odense M, 5230, Denmark
- The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Joanne B Cole
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of Endocrinology, Boston Children's Hospital, Boston, MA, USA
- Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO, 80045, USA
| | - Bianca Porneala
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Kenneth Westerman
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Josephine H Li
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Toni I Pollin
- Emory University, Atlanta, Georgia, USA., Atlanta, GA, USA
| | - Jose C Florez
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Endocrine Division, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Anna L Gloyn
- Department of Pediatrics, Division of Endocrinology, Stanford School of Medicine, Stanford, CA, USA
| | - Inês Cebola
- Section of Genetics and Genomics, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Alisa Manning
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Aaron Leong
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Endocrine Division, Massachusetts General Hospital, Boston, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Miriam Udler
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Josep M Mercader
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
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12
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Zhang J, Jiang Y, Li J, Zou H, Yin L, Yang Y, Yang L. Identification and precision therapy for three maturity-onset diabetes of the young (MODY) families caused by mutations in the HNF4A gene. Front Endocrinol (Lausanne) 2023; 14:1237553. [PMID: 37711893 PMCID: PMC10498112 DOI: 10.3389/fendo.2023.1237553] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 08/04/2023] [Indexed: 09/16/2023] Open
Abstract
Background Heterozygous pathogenic variants in HNF4A gene cause maturity-onset diabetes of the young type 1 (MODY1). The mutation carriers for MODY1 have been reported to be relatively rare, in contrast to the most frequently reported forms of MODY2 and MODY3. Methods Whole exome sequencing (WES) and Sanger sequencing were performed for genetic analysis of MODY pedigrees. Tertiary structures of the mutated proteins were predicted using PyMOL software. Results Three heterozygous missense mutations in the HNF4A gene, I159T, W179C, and D260N, were identified in the probands of three unrelated MODY families using WES, one of which (W179C) was novel. Cascade genetic screening revealed that the mutations co-segregated with hyperglycemic phenotypes in their families. The molecular diagnosis of MODY1 has partly transformed its management in clinical practice and improved glycemic control. The proband in family A successfully converted to sulfonylureas and achieved good glycemic control. Proband B responded well to metformin combined with diet therapy because of his higher body mass index (BMI). The proband in family C, with paternal-derived mutations, had markedly defective pancreatic β-cell function due to the superposition effect of T2DM susceptibility genes from the maternal grandfather, and he is currently treated with insulin. In silico analysis using PyMOL showed that the I159T and D260N mutations altered polar interactions with the surrounding residues, and W179C resulted in a smaller side chain. Discussion We identified three heterozygous missense mutations of HNF4A from Chinese MODY families. Structural alterations in these mutations may lead to defects in protein function, further contributing to the hyperglycemic phenotype of mutation carriers.
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Affiliation(s)
- Juan Zhang
- Institute of Monogenic Disease, School of Medicine, Huanghuai University, Zhumadian, China
- Department of Scientific Research Section, Zhumadian Central Hospital, Affiliated Hospital of Huanghuai University, Zhumadian, China
| | - Yanyan Jiang
- Department of Geriatric Endocrinology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jianhua Li
- Department of Emergency Intensive Care Unit, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Haiyin Zou
- Institute of Monogenic Disease, School of Medicine, Huanghuai University, Zhumadian, China
- Department of Scientific Research Section, Zhumadian Central Hospital, Affiliated Hospital of Huanghuai University, Zhumadian, China
| | - Li Yin
- Department of Ultrasound Medicine, The 990th Hospital of The People’s Liberation Army, Zhumadian, China
| | - Yang Yang
- Department of Scientific Research Section, Zhumadian Central Hospital, Affiliated Hospital of Huanghuai University, Zhumadian, China
| | - Lei Yang
- Department of Scientific Research Section, Zhumadian Central Hospital, Affiliated Hospital of Huanghuai University, Zhumadian, China
- Zhumadian Key Laboratory of Chronic Disease Research and Translational Medicine, Institute of Cardiovascular and Cerebrovascular Diseases, School of Medicine, Huanghuai University, Zhumadian, China
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13
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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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14
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Murphy R, Colclough K, Pollin TI, Ikle JM, Svalastoga P, Maloney KA, Saint-Martin C, Molnes J, Misra S, Aukrust I, de Franco A, Flanagan SE, Njølstad PR, Billings LK, Owen KR, Gloyn AL. A Systematic Review of the use of Precision Diagnostics in Monogenic Diabetes. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.04.15.23288269. [PMID: 37131594 PMCID: PMC10153302 DOI: 10.1101/2023.04.15.23288269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Monogenic forms of diabetes present opportunities for precision medicine as identification of the underlying genetic cause has implications for treatment and prognosis. However, genetic testing remains inconsistent across countries and health providers, often resulting in both missed diagnosis and misclassification of diabetes type. One of the barriers to deploying genetic testing is uncertainty over whom to test as the clinical features for monogenic diabetes overlap with those for both type 1 and type 2 diabetes. In this review, we perform a systematic evaluation of the evidence for the clinical and biochemical criteria used to guide selection of individuals with diabetes for genetic testing and review the evidence for the optimal methods for variant detection in genes involved in monogenic diabetes. In parallel we revisit the current clinical guidelines for genetic testing for monogenic diabetes and provide expert opinion on the interpretation and reporting of genetic tests. We provide a series of recommendations for the field informed by our systematic review, synthesizing evidence, and expert opinion. Finally, we identify major challenges for the field and highlight areas for future research and investment to support wider implementation of precision diagnostics for monogenic diabetes.
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Affiliation(s)
- Rinki Murphy
- Department of Medicine, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
- Auckland Diabetes Centre, Te Whatu Ora Health New Zealand, Te Tokai Tumai, Auckland, New Zealand
| | - Kevin Colclough
- Exeter Genomics Laboratory, Royal Devon University Healthcare NHS Foundation Trust, Exeter, United Kingdom
| | - Toni I Pollin
- Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Jennifer M Ikle
- Department of Pediatrics, Division of Endocrinology & Diabetes, Stanford School of Medicine, Stanford, CA, USA
- Stanford Diabetes Research Center, Stanford School of Medicine, Stanford, CA, USA
| | - Pernille Svalastoga
- Children and Youth Clinic, Haukeland University Hospital, Bergen, Norway
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Kristin A Maloney
- Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Cécile Saint-Martin
- Department of Medical Genetics, AP-HP Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
| | - Janne Molnes
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - Shivani Misra
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- Department of Diabetes and Endocrinology, Imperial College Healthcare NHS Trust, London, UK
| | - Ingvild Aukrust
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - aiElisa de Franco
- Department of Medicine, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Sarah E Flanagan
- Department of Clinical and Biomedical Science, Faculty of Health and Life Sciences, University of Exeter, UK
| | - Pål R Njølstad
- Children and Youth Clinic, Haukeland University Hospital, Bergen, Norway
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Liana K Billings
- Division of Endocrinology, NorthShore University HealthSystem, Skokie, IL, USA; Department of Medicine, Pritzker School of Medicine, University of Chicago, Chicago, IL, USA
| | - Katharine R Owen
- Oxford Center for Diabetes, Endocrinology & Metabolism, University of Oxford, UK
- NIHR Oxford Biomedical Research Centre, Oxford, UK
| | - Anna L Gloyn
- Department of Pediatrics, Division of Endocrinology & Diabetes, Stanford School of Medicine, Stanford, CA, USA
- Stanford Diabetes Research Center, Stanford School of Medicine, Stanford, CA, USA
- Department of Genetics, Stanford School of Medicine, Stanford, CA, USA
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15
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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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16
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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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17
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Firdous P, Hassan T, Nissar K, Masoodi SR, Ganai BA. Clinical profiling and screening for HNF4α and GCK gene mutations in Kashmiri patients with maturity-onset diabetes of the young (MODY). Prim Care Diabetes 2022; 16:325-332. [PMID: 35131168 DOI: 10.1016/j.pcd.2022.01.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 01/14/2022] [Accepted: 01/23/2022] [Indexed: 11/20/2022]
Abstract
AIM Maturity-onset Diabetes of Young (MODY) is a monogenic form of diabetes affecting 1-5% of young (often ≤25 years) diabetic patients exhibiting an autosomal dominant mode of inheritance. Considering the significance of genetic polymorphisms in a variety of diseases, this study aimed to determine the association between HNF4α and GCK gene polymorphisms and the risk of MODY in the Kashmir community, as well as their clinical differences. METHOD The study was conducted on clinically confirmed MODY patients (n = 50), and age and gender-matched controls (25 T1DM and 25 non-diabetic) recruited from the endocrinology department of the hospital, for evaluating the HNF4α and GCK mutation. Under standard conditions, PCR-mediated amplification was done to evaluate the respective exons. Preliminary mutations were detected using restriction enzymes (BfaI and HhaI), which were then followed by sequencing of representative samples. The diabetic history, clinical and biochemical data were obtained after proper consent. RESULTS Our data revealed no association of HNF4α (exon7) and GCK (exon8) gene mutation with MODY disease susceptibility in the Kashmiri population. On diagnosis, no MODY patient was given immediate insulin; instead, metformin (68%) or sulphonyl-urea (28%) and dietary changes (4%) were recommended. Later in life, 54% of MODY patients develop insulin dependency. The MODY probability was calculated to be 73.88% (±4.56). HbA1c levels were lower [7.48% (±1.64)] than in T1DM [9.17(±2.29%)]. CONCLUSIONS Young early-onset diabetic patients were able to keep their HbA1c and blood glucose levels stable with a modified diet and metformin/sulphonyl-urea, but they may become insulin-dependent in the future, as seen in our study. As a result, prompt diagnosis and management are essential for avoiding complications. Furthermore, no HNF4α (exon7) or GCK (exon 8) mutations were found in MODY patients or T1DM/healthy non-diabetic controls.
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Affiliation(s)
- Parveena Firdous
- Centre of Research for Development (CORD), University of Kashmir, Srinagar, Jammu and Kashmir 190006, India.
| | - Toyeeba Hassan
- Centre of Research for Development (CORD), University of Kashmir, Srinagar, Jammu and Kashmir 190006, India.
| | - Kamran Nissar
- Department of Biochemistry, University of Kashmir, Srinagar, Jammu and Kashmir 190006, India.
| | | | - Bashir Ahmad Ganai
- Centre of Research for Development (CORD), University of Kashmir, Srinagar, Jammu and Kashmir 190006, India.
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18
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Jungtrakoon Thamtarana P, Marucci A, Pannone L, Bonnefond A, Pezzilli S, Biagini T, Buranasupkajorn P, Hastings T, Mendonca C, Marselli L, Di Paola R, Abubakar Z, Mercuri L, Alberico F, Flex E, Ceròn J, Porta-de-la-Riva M, Ludovico O, Carella M, Martinelli S, Marchetti P, Mazza T, Froguel P, Trischitta V, Doria A, Prudente S. Gain of Function of Malate Dehydrogenase 2 and Familial Hyperglycemia. J Clin Endocrinol Metab 2022; 107:668-684. [PMID: 34718610 PMCID: PMC8852227 DOI: 10.1210/clinem/dgab790] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Indexed: 11/19/2022]
Abstract
CONTEXT Genes causing familial forms of diabetes mellitus are only partially known. OBJECTIVE We set out to identify the genetic cause of hyperglycemia in multigenerational families with an apparent autosomal dominant form of adult-onset diabetes not due to mutations in known monogenic diabetes genes. METHODS Existing whole-exome sequencing (WES) data were used to identify exonic variants segregating with diabetes in 60 families from the United States and Italy. Functional studies were carried out in vitro (transduced MIN6-K8 cells) and in vivo (Caenorhabditis elegans) to assess the diabetogenic potential of 2 variants in the malate dehydrogenase 2 (MDH2) gene linked with hyperglycemia in 2 of the families. RESULTS A very rare mutation (p.Arg52Cys) in MDH2 strongly segregated with hyperglycemia in 1 family from the United States. An infrequent MDH2 missense variant (p.Val160Met) also showed disease cosegregation in a family from Italy, although with reduced penetrance. In silico, both Arg52Cys and Val160Met were shown to affect MDH2 protein structure and function. In transfected HepG2 cells, both variants significantly increased MDH2 enzymatic activity, thereby decreasing the NAD+/NADH ratio-a change known to affect insulin signaling and secretion. Stable expression of human wild-type MDH2 in MIN6-K8 cell lines enhanced glucose- and GLP-1-stimulated insulin secretion. This effect was blunted by the Cys52 or Met160 substitutions. Nematodes carrying equivalent changes at the orthologous positions of the mdh-2 gene showed impaired glucose-stimulated insulin secretion. CONCLUSION Our findings suggest a central role of MDH2 in human glucose homeostasis and indicate that gain of function variants in this gene may be involved in the etiology of familial forms of diabetes.
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Affiliation(s)
- Prapaporn Jungtrakoon Thamtarana
- Research Division, Joslin Diabetes Center, and Harvard Medical School, Boston, MA, USA
- Cellular and Molecular Biology of Diabetes Research Group, Siriraj Center of Research Excellence for Diabetes and Obesity, Division of Molecular Medicine, Research Department, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Antonella Marucci
- Research Unit of Diabetes and Endocrine Diseases, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Luca Pannone
- Genetics and Rare Diseases Research Division, Ospedale Pediatrico Bambino Gesù, Rome, Italy
| | - Amélie Bonnefond
- Inserm UMR1283, CNRS UMR8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, Lille, France
- Université de Lille, CHU de Lille, Lille, France
- Department of Metabolism, Imperial College London, London, UK
| | - Serena Pezzilli
- Research Unit of Metabolic and Cardiovascular Diseases, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo,Italy
- Medical Genetics, University of Chieti, Chieti, Italy
| | - Tommaso Biagini
- Unit of Bioinformatics, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo,Italy
| | | | - Timothy Hastings
- Research Division, Joslin Diabetes Center, and Harvard Medical School, Boston, MA, USA
| | - Christine Mendonca
- Research Division, Joslin Diabetes Center, and Harvard Medical School, Boston, MA, USA
| | - Lorella Marselli
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Rosa Di Paola
- Research Unit of Diabetes and Endocrine Diseases, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Zuroida Abubakar
- Cellular and Molecular Biology of Diabetes Research Group, Siriraj Center of Research Excellence for Diabetes and Obesity, Division of Molecular Medicine, Research Department, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Luana Mercuri
- Research Unit of Metabolic and Cardiovascular Diseases, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo,Italy
| | - Federica Alberico
- Research Unit of Metabolic and Cardiovascular Diseases, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo,Italy
| | - Elisabetta Flex
- Department of Oncology and Molecular Medicine, Istituto Superiore di Sanità, Rome, Italy
| | - Julian Ceròn
- Modeling human diseases in C. elegans. Genes, Diseases and Therapies Program, Bellvitge Biomedical Research Institute – IDIBELL, L’Hospitalet de Llobregat, Barcelona, Spain
| | - Montserrat Porta-de-la-Riva
- Modeling human diseases in C. elegans. Genes, Diseases and Therapies Program, Bellvitge Biomedical Research Institute – IDIBELL, L’Hospitalet de Llobregat, Barcelona, Spain
| | - Ornella Ludovico
- Department of Clinical Sciences, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo,Italy
| | - Massimo Carella
- Research Unit of Medical Genetics, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo,Italy
| | - Simone Martinelli
- Department of Oncology and Molecular Medicine, Istituto Superiore di Sanità, Rome, Italy
| | - Piero Marchetti
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Tommaso Mazza
- Unit of Bioinformatics, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo,Italy
| | - Philippe Froguel
- Inserm UMR1283, CNRS UMR8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, Lille, France
- Université de Lille, CHU de Lille, Lille, France
- Department of Metabolism, Imperial College London, London, UK
| | - Vincenzo Trischitta
- Research Unit of Diabetes and Endocrine Diseases, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
- Department of Experimental Medicine, Sapienza University, Rome, Italy
| | - Alessandro Doria
- Research Division, Joslin Diabetes Center, and Harvard Medical School, Boston, MA, USA
- Alessandro Doria, MD, PhD, MPH, Research Division, Joslin Diabetes Center, One Joslin Place, Boston, MA 02215, USA.
| | - Sabrina Prudente
- Research Unit of Metabolic and Cardiovascular Diseases, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo,Italy
- Correspondence: Sabrina Prudente, PhD, Fondazione IRCCS Casa Sollievo della Sofferenza, CSS-Mendel Institute, Viale Regina Margherita 261, 00198 Rome, Italy.
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19
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Locke JM, Dusatkova P, Colclough K, Hughes AE, Dennis JM, Shields B, Flanagan SE, Shepherd MH, Dempster EL, Hattersley AT, Weedon MN, Pruhova S, Patel KA. Association of birthweight and penetrance of diabetes in individuals with HNF4A-MODY: a cohort study. Diabetologia 2022; 65:246-249. [PMID: 34618178 PMCID: PMC8660751 DOI: 10.1007/s00125-021-05581-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 08/16/2021] [Indexed: 11/29/2022]
Affiliation(s)
- Jonathan M Locke
- Institute of Biomedical & Clinical Science, College of Medicine & Health, University of Exeter, Exeter, UK.
| | - Petra Dusatkova
- Department of Pediatrics, Second Faculty of Medicine, Charles University and University Hospital Motol, Prague, Czech Republic
| | - Kevin Colclough
- Exeter Genomics Laboratory, Royal Devon and Exeter NHS Foundation Trust, Exeter, UK
| | - Alice E Hughes
- Institute of Biomedical & Clinical Science, College of Medicine & Health, University of Exeter, Exeter, UK
| | - John M Dennis
- Institute of Biomedical & Clinical Science, College of Medicine & Health, University of Exeter, Exeter, UK
| | - Beverley Shields
- Institute of Biomedical & Clinical Science, College of Medicine & Health, University of Exeter, Exeter, UK
| | - Sarah E Flanagan
- Institute of Biomedical & Clinical Science, College of Medicine & Health, University of Exeter, Exeter, UK
| | - Maggie H Shepherd
- Institute of Biomedical & Clinical Science, College of Medicine & Health, University of Exeter, Exeter, UK
- Exeter NIHR Clinical Research Facility, Royal Devon and Exeter NHS Foundation Trust, Exeter, UK
| | - Emma L Dempster
- Institute of Biomedical & Clinical Science, College of Medicine & Health, University of Exeter, Exeter, UK
| | - Andrew T Hattersley
- Institute of Biomedical & Clinical Science, College of Medicine & Health, University of Exeter, Exeter, UK
| | - Michael N Weedon
- Institute of Biomedical & Clinical Science, College of Medicine & Health, University of Exeter, Exeter, UK
| | - Stepanka Pruhova
- Department of Pediatrics, Second Faculty of Medicine, Charles University and University Hospital Motol, Prague, Czech Republic
| | - Kashyap A Patel
- Institute of Biomedical & Clinical Science, College of Medicine & Health, University of Exeter, Exeter, UK.
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20
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Gifford RM, Foteinopoulou E, Strachan MWJ. "Please see this man with a 69-year history of hypoglycaemia". J R Coll Physicians Edinb 2021; 51:266-268. [PMID: 34528616 DOI: 10.4997/jrcpe.2021.312] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Mutations in the HNF4A gene are associated with hyperinsulinaemic hypoglycaemia in infants, frequently evolving into relative deficiency of insulin in adulthood ---as maturity onset diabetes of the young (MODY). A 69-year-old male with a strong family history of adult-onset diabetes was referred with lifelong hypoglycaemia, found to be due to a pathogenic HNF4A mutation. HbA1c levels were low, continuous glucose monitoring demonstrated frequent low glucose events in the early morning, and he was successfully treated with diazoxide. This case represents a new phenotype of a known mutation associated more commonly with MODY. The same mutation in one family led to profoundly different manifestations. Genetic causes of hyperinsulinaemic hypoglycaemia can present late in life and identifying such cases is important to allow the correct treatment to be established.
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Affiliation(s)
- Robert M Gifford
- Edinburgh Centre for Endocrinology and Diabetes, Edinburgh, UK; Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK; Royal Centre of Defence Medicine, Birmingham, UK
| | | | - Mark W J Strachan
- Metabolic Unit, Western General Hospital, Crewe Road, Edinburgh EH4 7AL, UK,
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21
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NGS Analysis Revealed Digenic Heterozygous GCK and HNF1A Variants in a Child with Mild Hyperglycemia: A Case Report. Diagnostics (Basel) 2021; 11:diagnostics11071164. [PMID: 34202200 PMCID: PMC8306687 DOI: 10.3390/diagnostics11071164] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 06/22/2021] [Accepted: 06/22/2021] [Indexed: 11/16/2022] Open
Abstract
Monogenic diabetes (MD) represents a heterogeneous group of disorders whose most frequent form is maturity-onset diabetes of the young (MODY). MD is predominantly caused by a mutation in a single gene. We report a case of a female patient with suspected MD and a positive family history for diabetes and obesity. In this patient, two gene variants have been identified by next-generation sequencing (NGS): one in the Glucokinase (GCK) gene reported in the Human Gene Mutation Database (HGMD) and in the literature associated with GCK/MODY, and the other in the hepatocyte nuclear factor 1A (HNF1A) gene not previously described. The GCK variant was also identified in the hyperglycemic father, whereas the HNF1A variant was present in the mother. This new case of digenic GCK/HNF1A variants identified in a hyperglycemic subject, evidences the importance of NGS analysis in patients with suspected MD. In fact, this methodology will allow us to both increase the number of diagnoses and to identify mutations in more than one gene, with a better understanding of the genetic cause, and the clinical course, of the disease.
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22
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Durkie M, Chong J, Valluru MK, Harris PC, Ong ACM. Biallelic inheritance of hypomorphic PKD1 variants is highly prevalent in very early onset polycystic kidney disease. Genet Med 2021; 23:689-697. [PMID: 33168999 PMCID: PMC9782736 DOI: 10.1038/s41436-020-01026-4] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Revised: 10/13/2020] [Accepted: 10/21/2020] [Indexed: 12/27/2022] Open
Abstract
PURPOSE To investigate the prevalence of biallelic PKD1 and PKD2 variants underlying very early onset (VEO) polycystic kidney disease (PKD) in a large international pediatric cohort referred for clinical indications over a 10-year period (2010-2020). METHODS All samples were tested by Sanger sequencing and multiplex ligation-dependent probe amplification (MLPA) of PKD1 and PKD2 genes and/or a next-generation sequencing panel of 15 additional cystic genes including PKHD1 and HNF1B. Two patients underwent exome or genome sequencing. RESULTS Likely causative PKD1 or PKD2 variants were detected in 30 infants with PKD-VEO, 16 of whom presented in utero. Twenty-one of 30 (70%) had two variants with biallelic in trans inheritance confirmed in 16/21, 1 infant had biallelic PKD2 variants, and 2 infants had digenic PKD1/PKD2 variants. There was no known family history of ADPKD in 13 families (43%) and a de novo pathogenic variant was confirmed in 6 families (23%). CONCLUSION We report a high prevalence of hypomorphic PKD1 variants and likely biallelic disease in infants presenting with PKD-VEO with major implications for reproductive counseling. The diagnostic interpretation and reporting of these variants however remains challenging using current American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) and Association of Clinical Genetic Science (ACGS) variant classification guidelines in PKD-VEO and other diseases affected by similar variants with incomplete penetrance.
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Affiliation(s)
- Miranda Durkie
- Sheffield Diagnostics Genetic Service, Sheffield Children’s NHS Foundation Trust, Sheffield, UK
| | - Jiehan Chong
- Kidney Genetics Group, Academic Nephrology Unit, Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield Medical School, Sheffield, UK
| | - Manoj K. Valluru
- Kidney Genetics Group, Academic Nephrology Unit, Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield Medical School, Sheffield, UK
| | - Peter C. Harris
- Division of Nephrology and Hypertension, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Albert C. M. Ong
- Kidney Genetics Group, Academic Nephrology Unit, Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield Medical School, Sheffield, UK
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23
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Xiong XF, Yang Y, Wei L, Xiao Y, Li L, Sun L. Identification of two novel subgroups in patients with diabetes mellitus and their association with clinical outcomes: A two-step cluster analysis. J Diabetes Investig 2021; 12:1346-1358. [PMID: 33411406 PMCID: PMC8354513 DOI: 10.1111/jdi.13494] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 12/18/2020] [Accepted: 01/01/2021] [Indexed: 12/12/2022] Open
Abstract
Aims/Introduction The aim of this study was to determine whether distinct subphenotypes of patients with type 2 diabetes in the European classification exist in Chinese populations, and to further establish novel subphenotypes more suitable for Chinese populations. Material and Methods The research retrospectively analyzed 5414 patients with type 2 diabetes from the National Clinical Research Center for Metabolic Diseases Diabetes Center in China, and a two‐step cluster analysis was carried out. First, we confirmed the European classification in Chinese populations by six parameters, including age at disease onset, body mass index, glycosylated hemoglobin, homeostatic model assessment 2 to estimate β‐cell function and insulin resistance, and glutamate decarboxylase antibodies. Furthermore, triglycerides and uric acid were added to refine the cluster analysis, and Cox regression was used to evaluate the risk of diabetic complications. Results Just three clusters were replicated in our cohort according to Emma Ahlqvist's European classification. When other variables were added to the cluster analysis, seven subgroups were identified, including five clusters of the European classification and two novel subgroups, namely, uric acid‐related diabetes and inheritance‐related diabetes. Compared with patients with inheritance‐related diabetes, patients with severe insulin‐resistant diabetes showed a higher risk of diabetic peripheral neuropathy, hypertension and chronic kidney disease, and the uric acid‐related diabetes subgroup showed a higher risk of coronary heart disease, cerebral vascular disease and end‐stage renal disease. Patients with severe insulin‐deficient diabetes showed a higher risk of diabetic retinopathy and diabetic foot than those with inheritance‐related diabetes. Furthermore, there were sex‐specific associations between subgroups and clinical outcomes. No significant difference was observed in the prevalence of cancer in each subgroup. Conclusions Seven subgroups of type 2 diabetes were identified in Chinese populations, with distinct characteristics and disparate clinical outcomes. This etiology‐based stratification might contribute to the diagnosis and management of type 2 diabetes.
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Affiliation(s)
- Xiao-Fen Xiong
- Department of Nephrology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Yuan Yang
- Department of Nephrology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Ling Wei
- Department of Nephrology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Ying Xiao
- Department of Nephrology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Li Li
- Department of Nephrology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Lin Sun
- Department of Nephrology, The Second Xiangya Hospital, Central South University, Changsha, China
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24
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Zhang H, Colclough K, Gloyn AL, Pollin TI. Monogenic diabetes: a gateway to precision medicine in diabetes. J Clin Invest 2021; 131:142244. [PMID: 33529164 PMCID: PMC7843214 DOI: 10.1172/jci142244] [Citation(s) in RCA: 97] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Monogenic diabetes refers to diabetes mellitus (DM) caused by a mutation in a single gene and accounts for approximately 1%-5% of diabetes. Correct diagnosis is clinically critical for certain types of monogenic diabetes, since the appropriate treatment is determined by the etiology of the disease (e.g., oral sulfonylurea treatment of HNF1A/HNF4A-diabetes vs. insulin injections in type 1 diabetes). However, achieving a correct diagnosis requires genetic testing, and the overlapping of the clinical features of monogenic diabetes with those of type 1 and type 2 diabetes has frequently led to misdiagnosis. Improvements in sequencing technology are increasing opportunities to diagnose monogenic diabetes, but challenges remain. In this Review, we describe the types of monogenic diabetes, including common and uncommon types of maturity-onset diabetes of the young, multiple causes of neonatal DM, and syndromic diabetes such as Wolfram syndrome and lipodystrophy. We also review methods of prioritizing patients undergoing genetic testing, and highlight existing challenges facing sequence data interpretation that can be addressed by forming collaborations of expertise and by pooling cases.
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Affiliation(s)
- Haichen Zhang
- University of Maryland School of Medicine, Department of Medicine, Baltimore, Maryland, USA
| | - Kevin Colclough
- Exeter Genomics Laboratory, Royal Devon and Exeter Hospital, Exeter, United Kingdom
| | - Anna L. Gloyn
- Department of Pediatrics, Division of Endocrinology, and,Stanford Diabetes Research Center, Stanford School of Medicine, Stanford, California, USA
| | - Toni I. Pollin
- University of Maryland School of Medicine, Department of Medicine, Baltimore, Maryland, USA
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25
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Affiliation(s)
- Jan M Friedman
- Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada
| | | | - John C Carey
- Department of Pediatrics, University of Utah Health, Salt Lake City
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Turner H, Jackson L. Evidence for penetrance in patients without a family history of disease: a systematic review. Eur J Hum Genet 2020; 28:539-550. [PMID: 31937893 PMCID: PMC7170932 DOI: 10.1038/s41431-019-0556-5] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2019] [Revised: 10/08/2019] [Accepted: 11/26/2019] [Indexed: 01/21/2023] Open
Abstract
Family-based penetrance is frequently cited as a major challenge for translating penetrance estimates from familial populations to asymptomatic populations. A systematic review was performed to assess the literature evidencing penetrance estimates in patients without a family history of disease, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. Initially 1592 papers were identified, which were filtered to a final nine, through application of inclusion and exclusion criteria. Fundamental differences in the identified papers prevented combination of papers using meta-analysis, so thematic analysis to produce a narrative synthesis was performed. Key themes included disease risk modifiers, evidence, study limitations and bias. A methodological appraisal too was used to assess quality of included studies. It is evident from the findings that the evidence base for penetrance estimates in individuals without a family history of disease is limited. Future work is needed to refine design of penetrance studies and the impact of incorrect estimates.
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Affiliation(s)
- Heather Turner
- University of Exeter Medical School, 4.07 RILD, Royal Devon & Exeter Hospital, Barrack Road, Exeter, EX2 5DW, UK
| | - Leigh Jackson
- University of Exeter Medical School, 4.07 RILD, Royal Devon & Exeter Hospital, Barrack Road, Exeter, EX2 5DW, UK.
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Yahaya TO, Ufuoma SB. Genetics and Pathophysiology of Maturity-onset Diabetes of the Young (MODY): A Review of Current Trends. Oman Med J 2020; 35:e126. [PMID: 32489678 PMCID: PMC7254248 DOI: 10.5001/omj.2020.44] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2018] [Accepted: 02/04/2019] [Indexed: 02/05/2023] Open
Abstract
Single gene mutations have been implicated in the pathogenesis of a form of diabetes mellitus (DM) known as the maturity-onset diabetes of the young (MODY). However, there are diverse opinions on the suspect genes and pathophysiology, necessitating the need to review and communicate the genes to raise public awareness. We used the Google search engine to retrieve relevant information from reputable sources such as PubMed and Google Scholar. We identified 14 classified MODY genes as well as three new and unclassified genes linked with MODY. These genes are fundamentally embedded in the beta cells, the most common of which are HNF1A, HNF4A, HNF1B, and GCK genes. Mutations in these genes cause β-cell dysfunction, resulting in decreased insulin production and hyperglycemia. MODY genes have distinct mechanisms of action and phenotypic presentations compared with type 1 and type 2 DM and other forms of DM. Healthcare professionals are therefore advised to formulate drugs and treatment based on the causal genes rather than the current generalized treatment for all types of DM. This will increase the effectiveness of diabetes drugs and treatment and reduce the burden of the disease.
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Affiliation(s)
- Tajudeen O. Yahaya
- Department of Biology, Federal University Birnin Kebbi, Kebbi State, Nigeria
| | - Shemishere B. Ufuoma
- Department of Biochemistry and Molecular Biology, Federal University Birnin Kebbi, Kebbi State, Nigeria
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Sousa M, Bruges-Armas J. Monogenic Diabetes: Genetics and Relevance on Diabetes Mellitus Personalized Medicine. Curr Diabetes Rev 2020; 16:807-819. [PMID: 31886753 DOI: 10.2174/1573399816666191230114352] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/06/2019] [Revised: 11/11/2019] [Accepted: 12/12/2019] [Indexed: 02/06/2023]
Abstract
BACKGROUND Diabetes mellitus (DM) is a complex disease with significant impression in today's world. Aside from the most common types recognized over the years, such as type 1 diabetes (T1DM) and type 2 diabetes (T2DM), recent studies have emphasized the crucial role of genetics in DM, allowing the distinction of monogenic diabetes. METHODS Authors did a literature search with the purpose of highlighting and clarifying the subtypes of monogenic diabetes, as well as the accredited genetic entities responsible for such phenotypes. RESULTS The following subtypes were included in this literature review: maturity-onset diabetes of the young (MODY), neonatal diabetes mellitus (NDM) and maternally inherited diabetes and deafness (MIDD). So far, 14 subtypes of MODY have been identified, while three subtypes have been identified in NDM - transient, permanent, and syndromic. DISCUSSION Despite being estimated to affect approximately 2% of all the T2DM patients in Europe, the exact prevalence of MODY is still unknown, accentuating the need for research focused on biomarkers. Consequently, due to its impact in the course of treatment, follow-up of associated complications, and genetic implications for siblings and offspring of affected individuals, it is imperative to diagnose the monogenic forms of DM accurately. CONCLUSION Currently, advances in the genetics field allowed the recognition of new DM subtypes, which until now, were considered slight variations of the typical forms. Thus, it is imperative to act in the close interaction between genetics and clinical manifestations, to facilitate diagnosis and individualize treatment.
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MESH Headings
- Deafness/classification
- Deafness/diagnosis
- Deafness/genetics
- Diabetes Mellitus, Type 1/diagnosis
- Diabetes Mellitus, Type 1/genetics
- Diabetes Mellitus, Type 2/classification
- Diabetes Mellitus, Type 2/diagnosis
- Diabetes Mellitus, Type 2/genetics
- Genetic Testing
- Genotype
- Humans
- Infant
- Infant, Newborn
- Infant, Newborn, Diseases/classification
- Infant, Newborn, Diseases/diagnosis
- Infant, Newborn, Diseases/genetics
- Mitochondrial Diseases/classification
- Mitochondrial Diseases/diagnosis
- Mitochondrial Diseases/genetics
- Mutation
- Phenotype
- Precision Medicine
- Syndrome
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Affiliation(s)
- Madalena Sousa
- Serviço Especializado de Epidemiologia e Biologia Molecular (SEEBMO), Hospital de Santo Espírito da Ilha Terceira (HSEIT), Angra do Heroísmo, Azores, Portugal
| | - Jácome Bruges-Armas
- Serviço Especializado de Epidemiologia e Biologia Molecular (SEEBMO), Hospital de Santo Espírito da Ilha Terceira (HSEIT), Angra do Heroísmo, Azores, Portugal
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Affiliation(s)
- Rachel Horton
- Clinical Ethics and Law at Southampton (CELS), Faculty of Medicine, University of Southampton, UK
- Wessex Clinical Genetics Service, Princess Anne Hospital, Southampton, UK
| | - Gillian Crawford
- Clinical Ethics and Law at Southampton (CELS), Faculty of Medicine, University of Southampton, UK
- Wessex Clinical Genetics Service, Princess Anne Hospital, Southampton, UK
| | | | - Angela Fenwick
- Clinical Ethics and Law at Southampton (CELS), Faculty of Medicine, University of Southampton, UK
| | | | - Anneke Lucassen
- Clinical Ethics and Law at Southampton (CELS), Faculty of Medicine, University of Southampton, UK
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Vaxillaire M, Froguel P, Bonnefond A. How Recent Advances in Genomics Improve Precision Diagnosis and Personalized Care of Maturity-Onset Diabetes of the Young. Curr Diab Rep 2019; 19:79. [PMID: 31385057 DOI: 10.1007/s11892-019-1202-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
PURPOSE OF REVIEW Non-autoimmune monogenic diabetes (MD) in young people shows a broad spectrum of clinical presentations, which is largely explained by multiple genetic etiologies. This review discusses how the application of state-of-the-art genomics research to precision diagnosis of MD, particularly the various subtypes of maturity-onset diabetes of the young (MODY), has increasingly informed diabetes precision medicine and patient care throughout life. RECENT FINDINGS Due to extended genetic and clinical heterogeneity of MODY, diagnosis approaches based on next-generation sequencing have been worthwhile to better ascribe a specific subtype to each patient with young-onset diabetes. This guides the best appropriate treatment and clinical follow-up. Early etiological diagnosis of MD and individualized treatment are essential for achieving metabolic targets and avoiding long-term diabetes complications, as well as for drastically decreasing the financial and societal burden of diabetes-related healthcare. Genomic medicine-based practices help to optimize long-term clinical follow-up and patient care management.
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Affiliation(s)
- Martine Vaxillaire
- Univ. Lille, CNRS, CHU Lille, Institut Pasteur de Lille, UMR 8199 - European Genomic Institute for Diabetes (EGID), University Lille, F-59000, Lille, France.
- Faculty of Medicine, CNRS UMR 8199, 1 Place de Verdun, F-59045, Lille, France.
| | - Philippe Froguel
- Univ. Lille, CNRS, CHU Lille, Institut Pasteur de Lille, UMR 8199 - European Genomic Institute for Diabetes (EGID), University Lille, F-59000, Lille, France
- Department of Medicine, Section of Genomics of Common Disease, Imperial College London, London, UK
| | - Amélie Bonnefond
- Univ. Lille, CNRS, CHU Lille, Institut Pasteur de Lille, UMR 8199 - European Genomic Institute for Diabetes (EGID), University Lille, F-59000, Lille, France
- Department of Medicine, Section of Genomics of Common Disease, Imperial College London, London, UK
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Abstract
PURPOSE OF REVIEW Genomic tests offer increased opportunity for diagnosis, but their outputs are often uncertain and complex; results may need to be revised and/or may not be relevant until some future time. We discuss the challenges that this presents for consent and autonomy. RECENT FINDINGS Popular discourse around genomic testing tends to be strongly deterministic and optimistic, yet many findings from genomic tests are uncertain or unclear. Clinical conversations need to anticipate and potentially challenge unrealistic expectations of what a genomic test can deliver in order to enhance autonomy and ensure that consent to genomic testing is valid. SUMMARY We conclude that 'fully informed' consent is often not possible in the context of genomic testing, but that an open-ended approach is appropriate. We consider that such broad consent can only work if located within systems or organisations that are trustworthy and that have measures in place to ensure that such open-ended agreements are not abused. We suggest that a relational concept of autonomy has benefits in encouraging focus on the networks and relationships that allow decision making to flourish.
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Affiliation(s)
- Rachel Horton
- Clinical Ethics and Law at Southampton (CELS), Faculty of Medicine, University of Southampton, Centre for Cancer Immunology, Southampton General Hospital, Southampton, SO16 6YD UK
- Wessex Clinical Genetics Service, Princess Anne Hospital, Southampton, SO16 5YA UK
| | - Anneke Lucassen
- Clinical Ethics and Law at Southampton (CELS), Faculty of Medicine, University of Southampton, Centre for Cancer Immunology, Southampton General Hospital, Southampton, SO16 6YD UK
- Wessex Clinical Genetics Service, Princess Anne Hospital, Southampton, SO16 5YA UK
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32
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Estrella JFGL, Simmons D. Comment on Johnson et al. Cost-effectiveness Analysis of Routine Screening Using Massively Parallel Sequencing for Maturity-Onset Diabetes of the Young in a Pediatric Diabetes Cohort: Reduced Health System Costs and Improved Patient Quality of Life. Diabetes Care 2019;42:69-76. Diabetes Care 2019; 42:e78. [PMID: 31010947 DOI: 10.2337/dc19-0043] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Affiliation(s)
- Jane Frances Grace Lustre Estrella
- School of Medicine, Western Sydney University, Campbelltown, New South Wales, Australia.,Campbelltown Hospital, Campbelltown, New South Wales, Australia
| | - David Simmons
- School of Medicine, Western Sydney University, Campbelltown, New South Wales, Australia .,Campbelltown Hospital, Campbelltown, New South Wales, Australia
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Wright CF, West B, Tuke M, Jones SE, Patel K, Laver TW, Beaumont RN, Tyrrell J, Wood AR, Frayling TM, Hattersley AT, Weedon MN. Assessing the Pathogenicity, Penetrance, and Expressivity of Putative Disease-Causing Variants in a Population Setting. Am J Hum Genet 2019; 104:275-286. [PMID: 30665703 PMCID: PMC6369448 DOI: 10.1016/j.ajhg.2018.12.015] [Citation(s) in RCA: 141] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2018] [Accepted: 12/20/2018] [Indexed: 12/15/2022] Open
Abstract
More than 100,000 genetic variants are classified as disease causing in public databases. However, the true penetrance of many of these rare alleles is uncertain and might be over-estimated by clinical ascertainment. Here, we use data from 379,768 UK Biobank (UKB) participants of European ancestry to assess the pathogenicity and penetrance of putatively clinically important rare variants. Although rare variants are harder to genotype accurately than common variants, we were able to classify as high quality 1,244 of 4,585 (27%) putatively clinically relevant rare (MAF < 1%) variants genotyped on the UKB microarray. We defined as "clinically relevant" variants that were classified as either pathogenic or likely pathogenic in ClinVar or are in genes known to cause two specific monogenic diseases: maturity-onset diabetes of the young (MODY) and severe developmental disorders (DDs). We assessed the penetrance and pathogenicity of these high-quality variants by testing their association with 401 clinically relevant traits. 27 of the variants were associated with a UKB trait, and we were able to refine the penetrance estimate for some of the variants. For example, the HNF4A c.340C>T (p.Arg114Trp) (GenBank: NM_175914.4) variant associated with diabetes is <10% penetrant by the time an individual is 40 years old. We also observed associations with relevant traits for heterozygous carriers of some rare recessive conditions, e.g., heterozygous carriers of the ERCC4 c.2395C>T (p.Arg799Trp) variant that causes Xeroderma pigmentosum were more susceptible to sunburn. Finally, we refute the previous disease association of RNF135 in developmental disorders. In conclusion, this study shows that very large population-based studies will help refine our understanding of the pathogenicity of rare genetic variants.
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Affiliation(s)
- Caroline F Wright
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Research, Innovation, Learning and Development building, Royal Devon & Exeter Hospital, Barrack Road, Exeter EX2 5DW, UK.
| | - Ben West
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Research, Innovation, Learning and Development building, Royal Devon & Exeter Hospital, Barrack Road, Exeter EX2 5DW, UK
| | - Marcus Tuke
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Research, Innovation, Learning and Development building, Royal Devon & Exeter Hospital, Barrack Road, Exeter EX2 5DW, UK
| | - Samuel E Jones
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Research, Innovation, Learning and Development building, Royal Devon & Exeter Hospital, Barrack Road, Exeter EX2 5DW, UK
| | - Kashyap Patel
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Research, Innovation, Learning and Development building, Royal Devon & Exeter Hospital, Barrack Road, Exeter EX2 5DW, UK
| | - Thomas W Laver
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Research, Innovation, Learning and Development building, Royal Devon & Exeter Hospital, Barrack Road, Exeter EX2 5DW, UK
| | - Robin N Beaumont
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Research, Innovation, Learning and Development building, Royal Devon & Exeter Hospital, Barrack Road, Exeter EX2 5DW, UK
| | - Jessica Tyrrell
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Research, Innovation, Learning and Development building, Royal Devon & Exeter Hospital, Barrack Road, Exeter EX2 5DW, UK
| | - Andrew R Wood
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Research, Innovation, Learning and Development building, Royal Devon & Exeter Hospital, Barrack Road, Exeter EX2 5DW, UK
| | - Timothy M Frayling
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Research, Innovation, Learning and Development building, Royal Devon & Exeter Hospital, Barrack Road, Exeter EX2 5DW, UK
| | - Andrew T Hattersley
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Research, Innovation, Learning and Development building, Royal Devon & Exeter Hospital, Barrack Road, Exeter EX2 5DW, UK
| | - Michael N Weedon
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Research, Innovation, Learning and Development building, Royal Devon & Exeter Hospital, Barrack Road, Exeter EX2 5DW, UK.
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34
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Owen KR. Monogenic diabetes in adults: what are the new developments? Curr Opin Genet Dev 2018; 50:103-110. [DOI: 10.1016/j.gde.2018.04.006] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2018] [Revised: 04/16/2018] [Accepted: 04/19/2018] [Indexed: 12/13/2022]
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An Atypical HNF4A Mutation Which Does Not Conform to the Classic Presentation of HNF4A-MODY. Case Rep Endocrinol 2018; 2018:1560472. [PMID: 29998026 PMCID: PMC5994579 DOI: 10.1155/2018/1560472] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2018] [Revised: 03/23/2018] [Accepted: 04/26/2018] [Indexed: 01/06/2023] Open
Abstract
Objective To present the case of an atypical Hepatocyte Nuclear Factor 4 Alpha (HNF4A) mutation that is not consistent with the classically published presentation of HNF4A-Mature Onset Diabetes of the Young (MODY). Methods Clinical presentation and literature review. Results A 43-year-old nonobese man was referred to the endocrinology clinic for evaluation of elevated fasting blood glucose (FBG) measurements. Laboratory review revealed prediabetes and hypertriglyceridemia for the previous decade. Testing of autoantibodies for type 1 diabetes was negative. Genetic testing showed an autosomal dominant, heterozygous missense mutation (c.991C>T; p.Arg331Cys) in the HNF4A gene, which is correlated with HNF4A-MODY. Phenotypically, patients with an HNF4A-MODY tend to have early-onset diabetes, microvascular complications, low triglyceride levels, increased birth weight, fetal macrosomia, and less commonly neonatal hyperinsulinemic hypoglycemia. The patient did not demonstrate any of these features but instead presented with late-onset diabetes, an elevated triglyceride level, and a normal birth weight. Conclusion Our patient likely represents an atypical variant of HNF4A-MODY with a milder clinical presentation. Patients with atypical, less-severe presentations of HNF4A-MODY may be largely undiagnosed or misdiagnosed, but identification is important due to implications for treatment, pregnancy, and screening of family members.
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36
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Taniguchi H, Fujimoto A, Kono H, Furuta M, Fujita M, Nakagawa H. Loss-of-function mutations in Zn-finger DNA-binding domain of HNF4A cause aberrant transcriptional regulation in liver cancer. Oncotarget 2018; 9:26144-26156. [PMID: 29899848 PMCID: PMC5995239 DOI: 10.18632/oncotarget.25456] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2017] [Accepted: 05/02/2018] [Indexed: 11/25/2022] Open
Abstract
Hepatocyte nuclear factors (HNF) are transcription factors that crucially regulate cell-specific gene expression in many tissues, including the liver. Of these factors, HNF4A acts both as a master regulator of liver organogenesis and a tumor suppressor in the liver. In our whole genome sequencing analysis, we found seven somatic mutations (three Zn-finger mutations, three deletion mutants, and one intron mutation) of HNF4A in liver cancers. Interestingly, three out of seven mutations were clustered in its Zn-finger DNA-binding domain; G79 and F83 are positioned in the DNA recognition helix and the sidechain of M125 is sticking into the core of domain. These mutations are likely to affect DNA interaction from a structural point of view. We then generated these mutants and performed in-vitro promoter assays as well as DNA binding assays. These three mutations reduced HNF4 transcriptional activity at promoter sites of HNF4A-target genes. Expectedly, this decrease in transcriptional activity was associated with a change in DNA binding. RNA-Seq analysis observed a strong correlation between HNF4A expression and expression of its target genes, ApoB and HNF1A, in liver cancers. Since knockdown of HNF4A caused a reduction in ApoB and HNF1A expression, possibly loss of HNF4 reduces the expression of these genes and subsequently tumor growth is triggered. Therefore, we propose that HNF4A mutations G79C, F83C, and M125I are functional mutations found in liver cancers and that loss of HNF4A function, through its mutation, leads to a reduction in HNF1A and ApoB gene expression with a concomitant increased risk of liver tumorigenesis.
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Affiliation(s)
- Hiroaki Taniguchi
- Laboratory for Genome Sequencing Analysis, RIKEN Center for Integrative Medical Sciences, Tokyo 108-8639, Japan.,Institute of Genetics and Animal Breeding of the Polish Academy of Sciences, Jastrzebiec 05-552, Poland
| | - Akihiro Fujimoto
- Laboratory for Genome Sequencing Analysis, RIKEN Center for Integrative Medical Sciences, Tokyo 108-8639, Japan
| | - Hidetoshi Kono
- Molecular Modeling and Simulation Group, National Institutes for Quantum and Radiological Science and Technology, Kizugawa, Kyoto 619-0215, Japan
| | - Mayuko Furuta
- Laboratory for Genome Sequencing Analysis, RIKEN Center for Integrative Medical Sciences, Tokyo 108-8639, Japan
| | - Masashi Fujita
- Laboratory for Genome Sequencing Analysis, RIKEN Center for Integrative Medical Sciences, Tokyo 108-8639, Japan
| | - Hidewaki Nakagawa
- Laboratory for Genome Sequencing Analysis, RIKEN Center for Integrative Medical Sciences, Tokyo 108-8639, Japan
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Pezzilli S, Ludovico O, Biagini T, Mercuri L, Alberico F, Lauricella E, Dallali H, Capocefalo D, Carella M, Miccinilli E, Piscitelli P, Scarale MG, Mazza T, Trischitta V, Prudente S. Insights From Molecular Characterization of Adult Patients of Families With Multigenerational Diabetes. Diabetes 2018; 67:137-145. [PMID: 28993341 DOI: 10.2337/db17-0867] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2017] [Accepted: 10/01/2017] [Indexed: 11/13/2022]
Abstract
Multigenerational diabetes of adulthood is a mostly overlooked entity, simplistically lumped into the large pool of type 2 diabetes. The general aim of our research in the past few years is to unravel the genetic causes of this form of diabetes. Identifying among families with multigenerational diabetes those who carry mutations in known monogenic diabetes genes is the first step to then allow us to concentrate on remaining pedigrees in which to unravel new diabetes genes. Targeted next-generation sequencing of 27 monogenic diabetes genes was carried out in 55 family probands and identified mutations verified among their relatives by Sanger sequencing. Nine variants (in eight probands) survived our filtering/prioritization strategy. After likelihood of causality assessment by established guidelines, six variants were classified as "pathogenetic/likely pathogenetic" and two as "of uncertain significance." Combining present results with our previous data on the six genes causing the most common forms of maturity-onset diabetes of the young allows us to infer that 23.6% of families with multigenerational diabetes of adulthood carry mutations in known monogenic diabetes genes. Our findings indicate that the genetic background of hyperglycemia is unrecognized in the vast majority of families with multigenerational diabetes of adulthood. These families now become the object of further research aimed at unraveling new diabetes genes.
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Affiliation(s)
- Serena Pezzilli
- Department of Experimental Medicine, Sapienza University, Rome, Italy
- Research Unit of Metabolic and Cardiovascular Diseases, IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Ornella Ludovico
- Department of Medical Sciences, IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Tommaso Biagini
- Unit of Bioinformatics, IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Luana Mercuri
- Research Unit of Metabolic and Cardiovascular Diseases, IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Federica Alberico
- Research Unit of Metabolic and Cardiovascular Diseases, IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Eleonora Lauricella
- Department of Experimental Medicine, Sapienza University, Rome, Italy
- Research Unit of Metabolic and Cardiovascular Diseases, IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Hamza Dallali
- Research Unit of Metabolic and Cardiovascular Diseases, IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Daniele Capocefalo
- Unit of Bioinformatics, IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Massimo Carella
- Unit of Medical Genetics, IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Elide Miccinilli
- Research Unit of Metabolic and Cardiovascular Diseases, IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Pamela Piscitelli
- Department of Medical Sciences, IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Maria Giovanna Scarale
- Unit of Biostatistics, IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Tommaso Mazza
- Unit of Bioinformatics, IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Vincenzo Trischitta
- Department of Experimental Medicine, Sapienza University, Rome, Italy
- Research Unit of Metabolic and Cardiovascular Diseases, IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Sabrina Prudente
- Research Unit of Metabolic and Cardiovascular Diseases, IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
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Merino J, Florez JC. Precision medicine in diabetes: an opportunity for clinical translation. Ann N Y Acad Sci 2018; 1411:140-152. [PMID: 29377200 PMCID: PMC6686889 DOI: 10.1111/nyas.13588] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2017] [Revised: 11/27/2017] [Accepted: 12/04/2017] [Indexed: 12/12/2022]
Abstract
Metabolic disorders present a public health challenge of staggering proportions. In diabetes, there is an urgent need to better understand disease heterogeneity, clinical trajectories, and related comorbidities. A pressing and timely question is whether we are ready for precision medicine in diabetes. Some biological insights that have emerged during the last decade have already been used to direct clinical decision making, especially in monogenic forms of diabetes. However, much work is necessary to integrate high-dimensional explorations into complex disease architectures, less penetrant biological alterations, and broader phenotypes, such as type 2 diabetes. In addition, for precision medicine to take hold in diabetes, reproducibility, interpretability, and actionability remain key guiding objectives. In this review, we examine how mounting data sets generated during the last decade to understand biological variability are now inspiring new venues to clarify diabetes nosology and ultimately translate findings into more effective prevention and treatment strategies.
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Affiliation(s)
- Jordi Merino
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts
| | - Jose C. Florez
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
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39
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Brunerova L, Rahelić D, Ceriello A, Broz J. Use of oral antidiabetic drugs in the treatment of maturity-onset diabetes of the young: A mini review. Diabetes Metab Res Rev 2018; 34. [PMID: 28840639 DOI: 10.1002/dmrr.2940] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2017] [Revised: 08/17/2017] [Accepted: 08/18/2017] [Indexed: 12/29/2022]
Abstract
MODY (maturity-onset diabetes of the young) is a genetically linked group of clinically heterogeneous subtypes of diabetes. Roughly 5% of people with diabetes mellitus diagnosed prior to age 45 have MODY diabetes. Most of them have been erroneously diagnosed as patients with either type 1 or type 2 diabetes and, as a result, have been improperly treated. Genetic identification of MODY diabetes and its subtypes allows proper treatment and enables clinicians to switch many patients to oral antidiabetic agents, mainly sulphonylureas. However, some new classes of oral antidiabetic drugs have also been tested and found to be effective in MODY patients. We have searched for research articles and case reports written in full-text English or with an English abstract, using the following keywords: MODY and oral antidiabetic* in the databases Cochrane Library, PubMed, and Science Direct. Therapeutic options using currently standardized oral antidiabetic drugs (mainly sulphonylureas), as well as more experimental treatment with other classes of oral antidiabetic drugs in different types of MODY, are discussed, with special focus on the therapy of the most common MODY subtypes, including specific conditions such as pregnancy. This review article summarizes the currently available information about oral antidiabetic treatment of patients with MODY diabetes.
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Affiliation(s)
- Ludmila Brunerova
- Diabetes Center, 2nd Department of Medicine, Faculty Hospital Kralovske Vinohrady, Charles University 3rd Faculty of Medicine, Prague, Czech Republic
| | | | - Antonio Ceriello
- Institut d'Investigacions Biomèdiques August Pi i Sunyer, Centro de Investigación Biomedica en Red de Diabetes y Enfermedades Metabólicas Asociadas, Barcelona, Spain
- Department of Cardiovascular and Metabolic Diseases, IRCCS Multimedica Sesto San Giovanni (MI), Giovanni, Italy
| | - Jan Broz
- Department of Internal Medicine, Charles University 2nd Faculty of Medicine, Prague, Czech Republic
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Bansal V, Gassenhuber J, Phillips T, Oliveira G, Harbaugh R, Villarasa N, Topol EJ, Seufferlein T, Boehm BO. Spectrum of mutations in monogenic diabetes genes identified from high-throughput DNA sequencing of 6888 individuals. BMC Med 2017; 15:213. [PMID: 29207974 PMCID: PMC5717832 DOI: 10.1186/s12916-017-0977-3] [Citation(s) in RCA: 68] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2017] [Accepted: 11/11/2017] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Diagnosis of monogenic as well as atypical forms of diabetes mellitus has important clinical implications for their specific diagnosis, prognosis, and targeted treatment. Single gene mutations that affect beta-cell function represent 1-2% of all cases of diabetes. However, phenotypic heterogeneity and lack of family history of diabetes can limit the diagnosis of monogenic forms of diabetes. Next-generation sequencing technologies provide an excellent opportunity to screen large numbers of individuals with a diagnosis of diabetes for mutations in disease-associated genes. METHODS We utilized a targeted sequencing approach using the Illumina HiSeq to perform a case-control sequencing study of 22 monogenic diabetes genes in 4016 individuals with type 2 diabetes (including 1346 individuals diagnosed before the age of 40 years) and 2872 controls. We analyzed protein-coding variants identified from the sequence data and compared the frequencies of pathogenic variants (protein-truncating variants and missense variants) between the cases and controls. RESULTS A total of 40 individuals with diabetes (1.8% of early onset sub-group and 0.6% of adult onset sub-group) were carriers of known pathogenic missense variants in the GCK, HNF1A, HNF4A, ABCC8, and INS genes. In addition, heterozygous protein truncating mutations were detected in the GCK, HNF1A, and HNF1B genes in seven individuals with diabetes. Rare missense mutations in the GCK gene were significantly over-represented in individuals with diabetes (0.5% carrier frequency) compared to controls (0.035%). One individual with early onset diabetes was homozygous for a rare pathogenic missense variant in the WFS1 gene but did not have the additional phenotypes associated with Wolfram syndrome. CONCLUSION Targeted sequencing of genes linked with monogenic diabetes can identify disease-relevant mutations in individuals diagnosed with type 2 diabetes not suspected of having monogenic forms of the disease. Our data suggests that GCK-MODY frequently masquerades as classical type 2 diabetes. The results confirm that MODY is under-diagnosed, particularly in individuals presenting with early onset diabetes and clinically labeled as type 2 diabetes; thus, sequencing of all monogenic diabetes genes should be routinely considered in such individuals. Genetic information can provide a specific diagnosis, inform disease prognosis and may help to better stratify treatment plans.
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Affiliation(s)
- Vikas Bansal
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA.
| | | | - Tierney Phillips
- Scripps Translational Science Institute and Scripps Health, La Jolla, CA, USA
| | - Glenn Oliveira
- Scripps Translational Science Institute and Scripps Health, La Jolla, CA, USA
| | - Rebecca Harbaugh
- Scripps Translational Science Institute and Scripps Health, La Jolla, CA, USA
| | - Nikki Villarasa
- Scripps Translational Science Institute and Scripps Health, La Jolla, CA, USA
| | - Eric J Topol
- Scripps Translational Science Institute and Scripps Health, La Jolla, CA, USA
| | - Thomas Seufferlein
- Department of Internal Medicine I, Ulm University Medical Centre, Ulm, Germany
| | - Bernhard O Boehm
- Department of Internal Medicine I, Ulm University Medical Centre, Ulm, Germany. .,Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore. .,Imperial College London, London, UK.
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Prudente S, Ludovico O, Trischitta V. Familial diabetes of adulthood: A bin of ignorance that needs to be addressed. Nutr Metab Cardiovasc Dis 2017; 27:1053-1059. [PMID: 29174219 DOI: 10.1016/j.numecd.2017.10.017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2017] [Revised: 09/29/2017] [Accepted: 10/15/2017] [Indexed: 01/15/2023]
Abstract
AIMS The aim of this article was to share with a wide readership some data and related reasoning about a multigenerational form of diabetes mellitus of adulthood. DATA SYNTHESIS We have recently described a familial form of diabetes mellitus, which in the routine clinical setting of adult individuals is simplistically diagnosed as type 2 diabetes. Such misdiagnosis involves as much as 3% of adult unrelated diabetic patients with no evidence of autoimmune disease. More recent data, obtained by means of a next-generation sequencing, indicate that approximately 25% of such patients carry mutations in the genes involved in monogenic diabetes, thus leaving unraveled the molecular causes of the remaining 75% individuals. CONCLUSIONS Our proposal is to define the latter patients as being affected by familial diabetes of adulthood (FDA), a clear admission of ignorance and a limbo where adult patients with multigenerational diabetes with no genetic definition of their hyperglycemia have to wait for better times.
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Affiliation(s)
- S Prudente
- Research Unit of Metabolic and Cardiovascular Diseases, IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy.
| | - O Ludovico
- Department of Medical Sciences, IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - V Trischitta
- Research Unit of Metabolic and Cardiovascular Diseases, IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy; Department of Experimental Medicine, Sapienza University, Rome, Italy
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Shepherd M, Brook AJ, Chakera AJ, Hattersley AT. Management of sulfonylurea-treated monogenic diabetes in pregnancy: implications of placental glibenclamide transfer. Diabet Med 2017; 34:1332-1339. [PMID: 28556992 PMCID: PMC5612398 DOI: 10.1111/dme.13388] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/25/2017] [Indexed: 01/05/2023]
Abstract
The optimum treatment for HNF1A/HNF4A maturity-onset diabetes of the young and ATP-sensitive potassium (KATP ) channel neonatal diabetes, outside pregnancy, is sulfonylureas, but there is little evidence regarding the most appropriate treatment during pregnancy. Glibenclamide has been widely used in the treatment of gestational diabetes, but recent data have established that glibenclamide crosses the placenta and increases risk of macrosomia and neonatal hypoglycaemia. This raises questions about its use in pregnancy. We review the available evidence and make recommendations for the management of monogenic diabetes in pregnancy. Due to the risk of stimulating increased insulin secretion in utero, we recommend that in women with HNF1A/ HNF4A maturity-onset diabetes of the young, those with good glycaemic control who are on a sulfonylurea per conception either transfer to insulin before conception (at the risk of a short-term deterioration of glycaemic control) or continue with sulfonylurea (glibenclamide) treatment in the first trimester and transfer to insulin in the second trimester. Early delivery is needed if the fetus inherits an HNF4A mutation from either parent because increased insulin secretion results in ~800-g weight gain in utero, and prolonged severe neonatal hypoglycaemia can occur post-delivery. If the fetus inherits a KATP neonatal diabetes mutation from their mother they have greatly reduced insulin secretion in utero that reduces fetal growth by ~900 g. Treating the mother with glibenclamide in the third trimester treats the affected fetus in utero, normalising fetal growth, but is not desirable, especially in the high doses used in this condition, if the fetus is unaffected. Prospective studies of pregnancy in monogenic diabetes are needed.
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Affiliation(s)
- M. Shepherd
- Institute of Biomedical and Clinical ScienceUniversity of Exeter Medical SchoolExeterUK
- Exeter NIHR Clinical Research FacilityRoyal Devon and Exeter NHS Foundation TrustExeterUK
| | - A. J. Brook
- Institute of Biomedical and Clinical ScienceUniversity of Exeter Medical SchoolExeterUK
- Lancashire Women and Newborn CentreBurnley General Hospital, East Lancashire NHS Hospitals TrustBurnleyUK
- University of ManchesterManchesterUK
| | - A. J. Chakera
- Institute of Biomedical and Clinical ScienceUniversity of Exeter Medical SchoolExeterUK
- Royal Sussex County Hospital, Brighton and Sussex University HospitalsBrightonUK
| | - A. T. Hattersley
- Institute of Biomedical and Clinical ScienceUniversity of Exeter Medical SchoolExeterUK
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Abstract
The precision medicine approach of tailoring treatment to the individual characteristics of each patient or subgroup has been a great success in monogenic diabetes subtypes, MODY and neonatal diabetes. This review examines what has led to the success of a precision medicine approach in monogenic diabetes (precision diabetes) and outlines possible implications for type 2 diabetes. For monogenic diabetes, the molecular genetics can define discrete aetiological subtypes that have profound implications on diabetes treatment and can predict future development of associated clinical features, allowing early preventative or supportive treatment. In contrast, type 2 diabetes has overlapping polygenic susceptibility and underlying aetiologies, making it difficult to define discrete clinical subtypes with a dramatic implication for treatment. The implementation of precision medicine in neonatal diabetes was simple and rapid as it was based on single clinical criteria (diagnosed <6 months of age). In contrast, in MODY it was more complex and slow because of the lack of single criteria to identify patients, but it was greatly assisted by the development of a diagnostic probability calculator and associated smartphone app. Experience in monogenic diabetes suggests that successful adoption of a precision diabetes approach in type 2 diabetes will require simple, quick, easily accessible stratification that is based on a combination of routine clinical data, rather than relying on newer technologies. Analysing existing clinical data from routine clinical practice and trials may provide early success for precision medicine in type 2 diabetes.
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Affiliation(s)
- Andrew T Hattersley
- The Institute of Biomedical and Clinical Science, University of Exeter Medical School, RILD Building, Level 3, Royal Devon and Exeter Hospital, Barrack Road, Exeter, EX2 5DW, UK.
| | - Kashyap A Patel
- The Institute of Biomedical and Clinical Science, University of Exeter Medical School, RILD Building, Level 3, Royal Devon and Exeter Hospital, Barrack Road, Exeter, EX2 5DW, UK
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Shields B, Colclough K. Towards a systematic nationwide screening strategy for MODY. Diabetologia 2017; 60:609-612. [PMID: 28132100 DOI: 10.1007/s00125-017-4213-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2017] [Accepted: 01/11/2017] [Indexed: 12/13/2022]
Abstract
MODY is an early-onset monogenic form of diabetes. Correctly identifying MODY is of considerable importance as diagnosing the specific genetic subtype can inform the optimal treatment, with many patients being able to discontinue unnecessary insulin treatment. Diagnostic molecular genetic testing to confirm MODY is expensive, so screening strategies are required to identify the most appropriate patients for testing. In this issue of Diabetologia, Johansson and colleagues (DOI 10.1007/s00125-016-4167-1 ) describe a nationwide systematic screening approach to identify individuals with MODY in the paediatric age range. They focused testing on patients negative for both GAD and islet antigen 2 (IA-2) islet autoantibodies, thereby ruling out those with markers of type 1 diabetes, the most common form of diabetes in this age group. This commentary discusses the advantages and limitations of the approach, and the caution required when interpreting variants of uncertain pathogenicity identified from testing whole populations rather than targeting only patients with a strong MODY phenotype.
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Affiliation(s)
- Beverley Shields
- University of Exeter Medical School, University of Exeter, RILD Building - Level 3, Barrack Road, Exeter, EX2 5DW, UK.
| | - Kevin Colclough
- Department of Molecular Genetics, Royal Devon and Exeter NHS Foundation Trust, Exeter, UK
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