1
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Triolo TM, Parikh HM, Tosur M, Ferrat L, You L, Gottlieb PA, Oram RA, Onengut-Gumuscu S, Krischer JP, Rich SS, Steck AK, Redondo MJ. Genetic Associations with C-peptide Levels before Type 1 Diabetes Diagnosis in At-Risk Relatives. J Clin Endocrinol Metab 2024:dgae349. [PMID: 38767115 DOI: 10.1210/clinem/dgae349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 05/13/2024] [Accepted: 05/16/2024] [Indexed: 05/22/2024]
Abstract
OBJECTIVE We sought to determine whether the type 1 diabetes genetic risk score-2 (T1D-GRS2) and single nucleotide polymorphisms (SNPs) are associated with C-peptide preservation before type 1 diabetes diagnosis. METHODS We conducted a retrospective analysis of 713 autoantibody-positive participants who developed type 1 diabetes in the TrialNet Pathway to Prevention Study who had T1DExomeChip data. We evaluated the relationships of 16 known SNPs and T1D-GRS2 with area under the curve (AUC) C-peptide levels during oral glucose tolerance tests conducted in the 9 months before diagnosis. RESULTS Higher T1D-GRS2 was associated with lower C-peptide AUC in the 9 months before diagnosis in univariate (β=-0.06, P<0.0001) and multivariate (β=-0.03, P=0.005) analyses. Participants with the JAZF1 rs864745 T allele had lower C-peptide AUC in both univariate (β=-0.11, P=0.002) and multivariate (β=-0.06, P=0.018) analyses. CONCLUSIONS The type 2 diabetes-associated JAZF1 rs864745 T allele and higher T1D-GRS2 are associated with lower C-peptide AUC prior to diagnosis of type 1 diabetes, with implications for the design of prevention trials.
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Affiliation(s)
- Taylor M Triolo
- Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus
| | - Hemang M Parikh
- Health Informatics Institute, Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA
| | - Mustafa Tosur
- Department of Pediatrics, Division of Diabetes and Endocrinology, Baylor College of Medicine, Texas Children's Hospital, Houston, TX, USA
- USDA/ARS Children's Nutrition Research Center, Houston, TX, USA
| | | | - Lu You
- Health Informatics Institute, Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA
| | - Peter A Gottlieb
- Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus
| | | | | | - Jeffrey P Krischer
- Health Informatics Institute, Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA
| | | | - Andrea K Steck
- Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus
| | - Maria J Redondo
- Department of Pediatrics, Division of Diabetes and Endocrinology, Baylor College of Medicine, Texas Children's Hospital, Houston, TX, USA
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2
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Koufakis T, Patoulias D, Zografou I, Papanas N, Popovic DS. Drawing lines in the sand: The growing threat of obesity in type 1 diabetes. World J Diabetes 2024; 15:823-827. [PMID: 38766422 PMCID: PMC11099370 DOI: 10.4239/wjd.v15.i5.823] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/23/2023] [Revised: 01/31/2024] [Accepted: 03/12/2024] [Indexed: 05/10/2024] Open
Abstract
In this editorial, we comment on the article by Zeng et al published in the recent issue of the World Journal of Diabetes in 2024. We focus on the epidemiological, pathophysiological, and clinical interplay between obesity and type 1 diabetes mellitus (T1DM). Overweight and obesity represent a growing threat for modern societies and people with T1DM could not be an exception to this rule. Chronic exogenous insulin administration, genetic and epigenetic factors, and psy-chosocial and behavioral parameters, along with the modern way of life that incorporates unhealthy eating patterns and physical inactivity, set the stage for the increasing obesity rates in T1DM. As our knowledge of the underlying mechanisms that lead to the development of obesity and hyperglycemia expands, it becomes clear that there are overlap zones in the pathophysiology of the two main types of diabetes. Stereotypes regarding strict dividing lines between "autoimmune" and "metabolic" phenotypes increase the risk of trapping physicians into ineffective therapeutic approaches, instead of individualized diabetes care. In this context, the use of adjuncts to insulin therapy that have the potential to alleviate cardiorenal risk and decrease body weight can reduce the burden of obesity in patients with T1DM.
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Affiliation(s)
- Theocharis Koufakis
- Second Propedeutic Department of Internal Medicine, Aristotle University of Thessaloniki, Thessaloniki 54642, Greece
| | - Dimitrios Patoulias
- Second Propedeutic Department of Internal Medicine, Aristotle University of Thessaloniki, Thessaloniki 54642, Greece
| | - Ioanna Zografou
- Second Propedeutic Department of Internal Medicine, Aristotle University of Thessaloniki, Thessaloniki 54642, Greece
| | - Nikolaos Papanas
- Diabetes Centre, Second Department of Internal Medicine, Democritus University of Thrace, Alexandroupolis 68100, Greece
| | - Djordje S Popovic
- Clinic for Endocrinology, Diabetes and Metabolic Disorders, Clinical Center of Vojvodina, Medical Faculty, University of Novi Sad, Novi Sad 21000, Serbia
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3
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Thomas NJ, Jones AG. The challenges of identifying and studying type 1 diabetes in adults. Diabetologia 2023; 66:2200-2212. [PMID: 37728732 PMCID: PMC10628058 DOI: 10.1007/s00125-023-06004-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 07/14/2023] [Indexed: 09/21/2023]
Abstract
Diagnosing type 1 diabetes in adults is difficult since type 2 diabetes is the predominant diabetes type, particularly with an older age of onset (approximately >30 years). Misclassification of type 1 diabetes in adults is therefore common and will impact both individual patient management and the reported features of clinically classified cohorts. In this article, we discuss the challenges associated with correctly identifying adult-onset type 1 diabetes and the implications of these challenges for clinical practice and research. We discuss how many of the reported differences in the characteristics of autoimmune/type 1 diabetes with increasing age of diagnosis are likely explained by the inadvertent study of mixed populations with and without autoimmune aetiology diabetes. We show that when type 1 diabetes is defined by high-specificity methods, clinical presentation, islet-autoantibody positivity, genetic predisposition and progression of C-peptide loss remain broadly similar and severe at all ages and are unaffected by onset age within adults. Recent clinical guidance recommends routine islet-autoantibody testing when type 1 diabetes is clinically suspected or in the context of rapid progression to insulin therapy after a diagnosis of type 2 diabetes. In this moderate or high prior-probability setting, a positive islet-autoantibody test will usually confirm autoimmune aetiology (type 1 diabetes). We argue that islet-autoantibody testing of those with apparent type 2 diabetes should not be routinely undertaken as, in this low prior-prevalence setting, the positive predictive value of a single-positive islet antibody for autoimmune aetiology diabetes will be modest. When studying diabetes, extremely high-specificity approaches are needed to identify autoimmune diabetes in adults, with the optimal approach depending on the research question. We believe that until these recommendations are widely adopted by researchers, the true phenotype of late-onset type 1 diabetes will remain largely misunderstood.
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Affiliation(s)
- Nicholas J Thomas
- Department of Clinical and Biological Sciences, University of Exeter, Exeter, UK
- Royal Devon University Healthcare NHS Foundation Trust, Exeter, UK
| | - Angus G Jones
- Department of Clinical and Biological Sciences, University of Exeter, Exeter, UK.
- Royal Devon University Healthcare NHS Foundation Trust, Exeter, UK.
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4
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Leslie RD, Ma RCW, Franks PW, Nadeau KJ, Pearson ER, Redondo MJ. Understanding diabetes heterogeneity: key steps towards precision medicine in diabetes. Lancet Diabetes Endocrinol 2023; 11:848-860. [PMID: 37804855 DOI: 10.1016/s2213-8587(23)00159-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 04/30/2023] [Accepted: 05/27/2023] [Indexed: 10/09/2023]
Abstract
Diabetes is a highly heterogeneous condition; yet, it is diagnosed by measuring a single blood-borne metabolite, glucose, irrespective of aetiology. Although pragmatically helpful, disease classification can become complex and limit advances in research and medical care. Here, we describe diabetes heterogeneity, highlighting recent approaches that could facilitate management by integrating three disease models across all forms of diabetes, namely, the palette model, the threshold model and the gradient model. Once diabetes has developed, further worsening of established diabetes and the subsequent emergence of diabetes complications are kept in check by multiple processes designed to prevent or circumvent metabolic dysfunction. The impact of any given disease risk factor will vary from person-to-person depending on their background, diabetes-related propensity, and environmental exposures. Defining the consequent heterogeneity within diabetes through precision medicine, both in terms of diabetes risk and risk of complications, could improve health outcomes today and shine a light on avenues for novel therapy in the future.
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Affiliation(s)
| | - Ronald Ching Wan Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China; Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, China; Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Paul W Franks
- Novo Nordisk Foundation, Hellerup, Denmark; Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Malmo, Sweden; Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK; Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Kristen J Nadeau
- Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Ewan R Pearson
- Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK
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5
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Abstract
Despite major advances over the past decade, prevention and treatment of type 1 diabetes mellitus (T1DM) remain suboptimal, with large and unexplained variations in individual responses to interventions. The current classification schema for diabetes mellitus does not capture the complexity of this disease or guide clinical management effectively. One of the approaches to achieve the goal of applying precision medicine in diabetes mellitus is to identify endotypes (that is, well-defined subtypes) of the disease each of which has a distinct aetiopathogenesis that might be amenable to specific interventions. Here, we describe epidemiological, clinical, genetic, immunological, histological and metabolic differences within T1DM that, together, suggest heterogeneity in its aetiology and pathogenesis. We then present the emerging endotypes and their impact on T1DM prediction, prevention and treatment.
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Affiliation(s)
- Maria J Redondo
- Paediatric Diabetes & Endocrinology, Texas Children's Hospital, Baylor College of Medicine, Houston, TX, USA.
| | - Noel G Morgan
- Exeter Centre of Excellence for Diabetes Research (EXCEED), Department of Clinical and Biomedical and Science, University of Exeter Medical School, Exeter, UK
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6
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Harsunen M, Haukka J, Harjutsalo V, Mars N, Syreeni A, Härkönen T, Käräjämäki A, Ilonen J, Knip M, Sandholm N, Miettinen PJ, Groop PH, Tuomi T. Residual insulin secretion in individuals with type 1 diabetes in Finland: longitudinal and cross-sectional analyses. Lancet Diabetes Endocrinol 2023; 11:465-473. [PMID: 37290465 DOI: 10.1016/s2213-8587(23)00123-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 04/18/2023] [Accepted: 04/18/2023] [Indexed: 06/10/2023]
Abstract
BACKGROUND Contrary to the presumption that type 1 diabetes leads to an absolute insulin deficiency, many individuals with type 1 diabetes have circulating C-peptide years after the diagnosis. We studied factors affecting random serum C-peptide concentration in individuals with type 1 diabetes and the association with diabetic complications. METHODS Our longitudinal analysis included individuals newly diagnosed with type 1 diabetes from Helsinki University Hospital (Helsinki, Finland) with repeated random serum C-peptide and concomitant glucose measurements from within 3 months of diagnosis and at least once later. The long-term cross-sectional analysis included data from participants from 57 centres in Finland who had type 1 diabetes diagnosed after 5 years of age, initiation of insulin treatment within 1 year from diagnosis, and a C-peptide concentration of less than 1·0 nmol/L (FinnDiane study) and patients with type 1 diabetes from the DIREVA study. We tested the association of random serum C-peptide concentrations and polygenic risk scores with one-way ANOVA, and association of random serum C-peptide concentrations, polygenic risk scores, and clinical factors with logistic regression. FINDINGS The longitudinal analysis included 847 participants younger than 16 years and 110 aged 16 years or older. In the longitudinal analysis, age at diagnosis strongly correlated with the decline in C-peptide secretion. The cross-sectional analysis included 3984 participants from FinnDiane and 645 from DIREVA. In the cross-sectional analysis, at a median duration of 21·6 years (IQR 12·5-31·2), 776 (19·4%) of 3984 FinnDiane participants had residual random serum C-peptide secretion (>0·02 nmol/L), which was associated with lower type 1 diabetes polygenic risk compared with participants without random serum C-peptide (p<0·0001). Random serum C-peptide was inversely associated with hypertension, HbA1c, and cholesterol, but also independently with microvascular complications (adjusted OR 0·61 [95% CI 0·38-0·96], p=0·033, for nephropathy; 0·55 [0·34-0·89], p=0·014, for retinopathy). INTERPRETATION Although children with multiple autoantibodies and HLA risk genotypes progressed to absolute insulin deficiency rapidly, many adolescents and adults had residual random serum C-peptide decades after the diagnosis. Polygenic risk of type 1 and type 2 diabetes affected residual random serum C-peptide. Even low residual random serum C-peptide concentrations seemed to be associated with a beneficial complications profile. FUNDING Folkhälsan Research Foundation; Academy of Finland; University of Helsinki and Helsinki University Hospital; Medical Society of Finland; the Sigrid Juselius Foundation; the "Liv and Hälsa" Society; Novo Nordisk Foundation; and State Research Funding via the Helsinki University Hospital, the Vasa Hospital District, Turku University Hospital, Vasa Central Hospital, Jakobstadsnejdens Heart Foundation, and the Medical Foundation of Vaasa.
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Affiliation(s)
- Minna Harsunen
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland; Research Program for Clinical and Molecular Metabolism, University of Helsinki, Helsinki, Finland; New Children's Hospital, Pediatric Research Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Jani Haukka
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland; Research Program for Clinical and Molecular Metabolism, University of Helsinki, Helsinki, Finland; Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Valma Harjutsalo
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland; Research Program for Clinical and Molecular Metabolism, University of Helsinki, Helsinki, Finland; Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Nina Mars
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland; Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Anna Syreeni
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland; Research Program for Clinical and Molecular Metabolism, University of Helsinki, Helsinki, Finland; Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Taina Härkönen
- Research Program for Clinical and Molecular Metabolism, University of Helsinki, Helsinki, Finland
| | - Annemari Käräjämäki
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland; Diabetes unit of Ostrobothnia, Wellbeing Services County of Ostrobothnia, Vaasa, Finland
| | - Jorma Ilonen
- Immunogenetics Laboratory, Institute of Biomedicine, University of Turku, Turku, Finland
| | - Mikael Knip
- Research Program for Clinical and Molecular Metabolism, University of Helsinki, Helsinki, Finland; Tampere Center for Child Health Research, Tampere University Hospital, Tampere, Finland
| | - Niina Sandholm
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland; Research Program for Clinical and Molecular Metabolism, University of Helsinki, Helsinki, Finland; Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Päivi Johanna Miettinen
- Translational Stem Cell Biology and Metabolism Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland; New Children's Hospital, Pediatric Research Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Per-Henrik Groop
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland; Research Program for Clinical and Molecular Metabolism, University of Helsinki, Helsinki, Finland; Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland; Department of Diabetes, Central Medical School, Monash University, Melbourne, VIC, Australia
| | - Tiinamaija Tuomi
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland; Research Program for Clinical and Molecular Metabolism, University of Helsinki, Helsinki, Finland; Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland; Abdominal Center, Endocrinology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland; Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Lund, Sweden.
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7
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Mameli C, Triolo TM, Chiarelli F, Rewers M, Zuccotti G, Simmons KM. Lessons and Gaps in the Prediction and Prevention of Type 1 Diabetes. Pharmacol Res 2023; 193:106792. [PMID: 37201589 DOI: 10.1016/j.phrs.2023.106792] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 05/01/2023] [Accepted: 05/08/2023] [Indexed: 05/20/2023]
Abstract
Type 1 diabetes (T1D) is a serious chronic autoimmune condition. Even though the root cause of T1D development has yet to be determined, enough is known about the natural history of T1D pathogenesis to allow study of interventions that may delay or even prevent the onset of hyperglycemia and clinical T1D. Primary prevention aims to prevent the onset of beta cell autoimmunity in asymptomatic people at high genetic risk for T1D. Secondary prevention strategies aim to preserve functional beta cells once autoimmunity is present, and tertiary prevention aims to initiate and extend partial remission of beta cell destruction after the clinical onset of T1D. The approval of teplizumab in the United States to delay the onset of clinical T1D marks an impressive milestone in diabetes care. This treatment opens the door to a paradigm shift in T1D care. People with T1D risk need to be identified early by measuring T1D related islet autoantibodies. Identifying people with T1D before they have symptoms will facilitate better understanding of pre-symptomatic T1D progression and T1D prevention strategies that may be effective.
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Affiliation(s)
- Chiara Mameli
- Department of Pediatrics, V. Buzzi Children's Hospital, Milan, Italy; Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy.
| | - Taylor M Triolo
- Barbara Davis Center for Diabetes, Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO 80045
| | | | - Marian Rewers
- Barbara Davis Center for Diabetes, Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO 80045
| | - Gianvincenzo Zuccotti
- Department of Pediatrics, V. Buzzi Children's Hospital, Milan, Italy; Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
| | - Kimber M Simmons
- Barbara Davis Center for Diabetes, Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO 80045
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8
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Royer-Bertrand B, Lebon S, Craig A, Maeder J, Mittaz-Crettol L, Fodstad H, Superti-Furga A, Good JM. Developmental disorder and spastic paraparesis in two sisters with a TCF7L2 truncating variant inherited from a mosaic mother. Am J Med Genet A 2023; 191:1658-1663. [PMID: 36905089 DOI: 10.1002/ajmg.a.63173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 02/01/2023] [Accepted: 02/21/2023] [Indexed: 03/12/2023]
Affiliation(s)
- Beryl Royer-Bertrand
- Division of Genetic Medicine, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
| | - Sébastien Lebon
- Unit of Pediatric Neurology and Neurorehabilitation, Department of Pediatrics, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
| | - Ailsa Craig
- Division of Genetic Medicine, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
| | - Johanna Maeder
- Unit of Pediatric Neurology and Neurorehabilitation, Department of Pediatrics, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
| | - Laureane Mittaz-Crettol
- Division of Genetic Medicine, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
| | - Heidi Fodstad
- Division of Genetic Medicine, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
| | - Andrea Superti-Furga
- Division of Genetic Medicine, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
| | - Jean-Marc Good
- Division of Genetic Medicine, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
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9
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Redondo MJ, Richardson SJ, Perry D, Minard CG, Carr ALJ, Brusko T, Kusmartseva I, Pugliese A, Atkinson MA. Milder loss of insulin-containing islets in individuals with type 1 diabetes and type 2 diabetes-associated TCF7L2 genetic variants. Diabetologia 2023; 66:127-131. [PMID: 36282337 PMCID: PMC9729318 DOI: 10.1007/s00125-022-05818-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 09/26/2022] [Indexed: 12/14/2022]
Abstract
AIMS/HYPOTHESIS TCF7L2 variants are the strongest genetic risk factor for type 2 diabetes. In individuals with type 1 diabetes, these variants are associated with a higher C-peptide AUC, a lower glucose AUC during an OGTT, single autoantibody positivity near diagnosis, particularly in individuals older than 12 years of age, and a lower frequency of type 1 diabetes-associated HLA genotypes. Based on initial observations from clinical cohorts, we tested the hypothesis that type 2 diabetes-predisposing TCF7L2 genetic variants are associated with a higher percentage of residual insulin-containing cells (ICI%) in pancreases of donors with type 1 diabetes, by examining genomic data and pancreatic tissue samples from the Network for Pancreatic Organ donors with Diabetes (nPOD) programme. METHODS We analysed nPOD donors with type 1 diabetes (n=110; mean±SD age at type 1 diabetes onset 12.2±7.9 years, mean±SD diabetes duration 15.3±13.7 years, 53% male, 80% non-Hispanic White, 12.7% African American, 7.3% Hispanic) using data pertaining to residual beta cell number; quantified islets containing insulin-positive beta cells in pancreatic tissue sections; and expressed these values as a percentage of the total number of islets from each donor (mean ± SD ICI% 9.8±21.5, range 0-92.2). RESULTS Donors with a high ICI% (≥5) (n=30; 27%) vs a low ICI% (<5) (n=80; 73%) were older at onset (15.3±6.9 vs 11.1±8 years, p=0.013), had a shorter diabetes duration at donor tissue procurement (7.0±7.4 vs 18.5±14.3 years, p<0.001), a higher African ancestry score (0.2±0.3 vs 0.1±0.2, p=0.043) and a lower European ancestry score (0.7±0.3 vs 0.9±0.3, p=0.023). After adjustment for age of onset (p=0.105), diabetes duration (p<0.001), BMI z score (p=0.145), sex (p=0.351) and African American race (p=0.053), donors with the TCF7L2 rs7903146 T allele (TC or TT, 45.5%) were 2.93 times (95% CI 1.02, 8.47) more likely to have a high ICI% than those without it (CC) (p=0.047). CONCLUSIONS/INTERPRETATION Overall, these data support the presence of a type 1 diabetes endotype associated with a genetic factor that predisposes to type 2 diabetes, with donors in this category exhibiting less severe beta cell loss. It is possible that in these individuals the disease pathogenesis may include mechanisms associated with type 2 diabetes and thus this may provide an explanation for the poor response to immunotherapies to prevent type 1 diabetes or its progression in a subset of individuals. If so, strategies that target both type 1 diabetes and type 2 diabetes-associated factors when they are present may increase the success of prevention and treatment in these individuals.
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Affiliation(s)
- Maria J Redondo
- Department of Pediatrics, Baylor College of Medicine, Texas Children's Hospital, Houston, TX, USA.
| | - Sarah J Richardson
- Islet Biology Group (IBEx), Exeter Centre of Excellence for Diabetes Research (EXCEED), University of Exeter College of Medicine and Health, Exeter, UK.
| | - Daniel Perry
- Departments of Pathology and Pediatrics, University of Florida Diabetes Institute, Gainesville, FL, USA
| | - Charles G Minard
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
| | - Alice L J Carr
- Islet Biology Group (IBEx), Exeter Centre of Excellence for Diabetes Research (EXCEED), University of Exeter College of Medicine and Health, Exeter, UK
| | - Todd Brusko
- Departments of Pathology and Pediatrics, University of Florida Diabetes Institute, Gainesville, FL, USA
| | - Irina Kusmartseva
- Departments of Pathology and Pediatrics, University of Florida Diabetes Institute, Gainesville, FL, USA
| | - Alberto Pugliese
- Diabetes Research Institute, Department of Medicine, Division of Endocrinology, Department of Microbiology and Immunology, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Mark A Atkinson
- Departments of Pathology and Pediatrics, University of Florida Diabetes Institute, Gainesville, FL, USA
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10
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Ergür E, Ergür E, Alnek K, Metsküla K, Peet A, Lubi M, Heilman K, Uibo R. Clinical signs of type 1 diabetes are associated with type 2 diabetes marker transcription factor 7-like 2 polymorphism. J Diabetes Investig 2022; 14:221-229. [PMID: 36300877 PMCID: PMC9889689 DOI: 10.1111/jdi.13933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 09/22/2022] [Accepted: 10/11/2022] [Indexed: 02/04/2023] Open
Abstract
AIMS/INTRODUCTION We aimed to assess the distribution of transcription factor 7-like 2 gene TCF7L2 (rs7903146) polymorphism and to find possible associations between TCF7L2 and the characteristics of type 1 diabetes. MATERIALS AND METHODS We studied 190 newly diagnosed type 1 diabetes patients (median age 12.7 years, range 2.0-72.5) and 246 controls (median age 23.8 years, range 1.4-81.5) for TCF7L2 single nucleotide polymorphism. We determined anti-islet autoantibodies, random C-peptide levels, diabetes associated HLA DR/DQ haplotypes and genotypes in all patients. RESULTS There were no differences in the distribution of TCF7L2 single nucleotide polymorphism between patients and controls. However, patients with in type 1 diabetes, after adjusting for age and sex, subjects carrying C allele were at risk for a C-peptide level lower than 0.5 nmol/L (OR 5.65 [95% CI: 1.14-27.92]) and for zinc transporter 8 autoantibody positivity (5.22 [1.34-20.24]). Participants without T allele were associated with a higher level of islet antigen-2 autoantibodies (3.51 [1.49-8.27]) and zinc transporter 8 autoantibodies (2.39 [1.14-4.99]). CONCLUSIONS The connection of TCF7L2 polymorphism with zinc transporter 8 and islet antigen-2 autoantibodies and C-peptide levels in patients supports the viewpoint that TCF7L2 is associated with the clinical signs and autoimmune characteristics of type 1 diabetes. The mechanisms of the interaction between the TCF7L2 risk genotype and anti-islet autoantibodies need to be studied further.
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Affiliation(s)
- Efe Ergür
- Department of Immunology, Institute of Bio‐ and Translational MedicineUniversity of TartuTartuEstonia
| | - Ege Ergür
- Department of Immunology, Institute of Bio‐ and Translational MedicineUniversity of TartuTartuEstonia
| | - Kristi Alnek
- Department of Immunology, Institute of Bio‐ and Translational MedicineUniversity of TartuTartuEstonia
| | - Kaja Metsküla
- Department of Immunology, Institute of Bio‐ and Translational MedicineUniversity of TartuTartuEstonia
| | - Aleksandr Peet
- Department of Pediatrics, Institute of Clinical MedicineUniversity of TartuTartuEstonia,Children's Clinic of Tartu University HospitalTartuEstonia
| | - Maire Lubi
- Department of Internal Medicine, Institute of Clinical MedicineUniversity of TartuTartuEstonia,Internal Medicine Clinic of Tartu University HospitalTartuEstonia
| | | | - Raivo Uibo
- Department of Immunology, Institute of Bio‐ and Translational MedicineUniversity of TartuTartuEstonia
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11
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Zucker I, Zloof Y, Bardugo A, Tsur AM, Lutski M, Cohen Y, Cukierman-Yaffe T, Minsky N, Derazne E, Tzur D, Melzer Cohen C, Pinhas-Hamiel O, Chodick G, Raz I, Afek A, Gerstein HC, Tirosh A, Twig G. Obesity in late adolescence and incident type 1 diabetes in young adulthood. Diabetologia 2022; 65:1473-1482. [PMID: 35665825 DOI: 10.1007/s00125-022-05722-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 03/08/2022] [Indexed: 01/25/2023]
Abstract
AIMS/HYPOTHESIS Studies in children have reported an association between increased BMI and risk for developing type 1 diabetes, but evidence in late adolescence is limited. We studied the association between BMI in late adolescence and incident type 1 diabetes in young adulthood. METHODS All Israeli adolescents, ages 16-19 years, undergoing medical evaluation in preparation for mandatory military conscription between January 1996 and December 2016 were included for analysis unless they had a history of dysglycaemia. Data were linked with information about adult onset of type 1 diabetes in the Israeli National Diabetes Registry. Weight and height were measured at study entry. Cox proportional models were applied, with BMI being analysed both as a categorical and as a continuous variable. RESULTS There were 777 incident cases of type 1 diabetes during 15,819,750 person-years (mean age at diagnosis 25.2±3.9 years). BMI was associated with incident type 1 diabetes. In a multivariable model adjusted for age, sex and sociodemographic variables, the HRs for type 1 diabetes were 1.05 (95% CI 0.87, 1.27) for the 50th-74th BMI percentiles, 1.41 (95% CI 1.11, 1.78) for the 75th-84th BMI percentiles, 1.54 (95% CI 1.23, 1.94) for adolescents who were overweight (85th-94th percentiles), and 2.05 (95% CI 1.58, 2.66) for adolescents with obesity (≥95th percentile) (reference group: 5th-49th BMI percentiles). One increment in BMI SD was associated with a 25% greater risk for incidence of type 1 diabetes (HR 1.25, 95% CI 1.17, 1.32). CONCLUSIONS Excessively high BMI in otherwise healthy adolescents is associated with increased risk for incident type 1 diabetes in early adulthood.
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Affiliation(s)
- Inbar Zucker
- Department of Preventive Medicine and Epidemiology, School of Public Health, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- The Israel Center for Disease Control, Ministry of Health, Ramat Gan, Israel
| | - Yair Zloof
- Department of Preventive Medicine and Epidemiology, School of Public Health, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- Israel Defense Forces Medical Corps, Ramat Gan, Israel
| | - Aya Bardugo
- Israel Defense Forces Medical Corps, Ramat Gan, Israel
- Department of Military Medicine, Hebrew University, Jerusalem, Israel
| | - Avishai M Tsur
- Department of Preventive Medicine and Epidemiology, School of Public Health, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- Israel Defense Forces Medical Corps, Ramat Gan, Israel
- Department of Medicine, Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel
| | - Miri Lutski
- Department of Preventive Medicine and Epidemiology, School of Public Health, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- The Israel Center for Disease Control, Ministry of Health, Ramat Gan, Israel
| | - Yaron Cohen
- Israel Defense Forces Medical Corps, Ramat Gan, Israel
- Department of Military Medicine, Hebrew University, Jerusalem, Israel
| | - Tali Cukierman-Yaffe
- Department of Preventive Medicine and Epidemiology, School of Public Health, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- Division of Endocrinology, Diabetes and Metabolism, Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel
| | - Noga Minsky
- Department of Preventive Medicine and Epidemiology, School of Public Health, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- Division of Endocrinology, Diabetes and Metabolism, Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel
| | - Estela Derazne
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Dorit Tzur
- Israel Defense Forces Medical Corps, Ramat Gan, Israel
- Department of Military Medicine, Hebrew University, Jerusalem, Israel
| | - Cheli Melzer Cohen
- Department of Preventive Medicine and Epidemiology, School of Public Health, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- MaccabiTech, Maccabi Health Services, Tel Aviv, Israel
| | - Orit Pinhas-Hamiel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- MaccabiTech, Maccabi Health Services, Tel Aviv, Israel
- Department of Pediatric Endocrinology, Edmond and Lilly Safra Children Hospital, Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel
| | - Gabriel Chodick
- Department of Preventive Medicine and Epidemiology, School of Public Health, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- MaccabiTech, Maccabi Health Services, Tel Aviv, Israel
| | - Itamar Raz
- The Diabetes Unit, Department of Internal Medicine, Hadassah Hebrew University Hospital, Jerusalem, Israel
| | - Arnon Afek
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- Central Management, Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel
| | - Hertzel C Gerstein
- Department of Medicine, McMaster University Hamilton, Hamilton, Ontario, Canada
| | - Amir Tirosh
- Division of Endocrinology, Diabetes and Metabolism, Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Gilad Twig
- Department of Preventive Medicine and Epidemiology, School of Public Health, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
- Israel Defense Forces Medical Corps, Ramat Gan, Israel.
- Department of Military Medicine, Hebrew University, Jerusalem, Israel.
- Division of Endocrinology, Diabetes and Metabolism, Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel.
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12
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Karamanakos G, Kokkinos A, Dalamaga M, Liatis S. Highlighting the Role of Obesity and Insulin Resistance in Type 1 Diabetes and Its Associated Cardiometabolic Complications. Curr Obes Rep 2022; 11:180-202. [PMID: 35931912 DOI: 10.1007/s13679-022-00477-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/29/2022] [Indexed: 11/30/2022]
Abstract
PURPOSE OF REVIEW This narrative review appraises research data on the potentially harmful effect of obesity and insulin resistance (IR) co-existence with type 1 diabetes mellitus (T1DM)-related cardiovascular (CVD) complications and evaluates possible therapeutic options. RECENT FINDINGS Obesity and IR have increasingly been emerging in patients with T1DM. Genetic, epigenetic factors, and subcutaneous insulin administration are implicated in the pathogenesis of this coexistence. Accumulating evidence implies that the concomitant presence of obesity and IR is an independent predictor of worse CVD outcomes. The prevalence of obesity and IR has increased in patients with T1DM. This increase can be partly attributed to general population trends but, additionally, to iatrogenic weight gain caused by insulin treatment. This association might be the missing link explaining the excess CVD burden observed in patients with T1DM despite optimal glycemic control. Data on newer agents for type 2 diabetes mellitus (T2DM) treatment are unraveling novel ways to challenge this aggravating coexistence.
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Affiliation(s)
- Georgios Karamanakos
- First Department of Propaedeutic Internal Medicine, Medical School, National Kapodistrian University of Athens, Laiko General Hospital, 17 Agiou Thoma Street, Athens, 11527, Greece.
| | - Alexander Kokkinos
- First Department of Propaedeutic Internal Medicine, Medical School, National Kapodistrian University of Athens, Laiko General Hospital, 17 Agiou Thoma Street, Athens, 11527, Greece
| | - Maria Dalamaga
- Department of Biological Chemistry, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Stavros Liatis
- First Department of Propaedeutic Internal Medicine, Medical School, National Kapodistrian University of Athens, Laiko General Hospital, 17 Agiou Thoma Street, Athens, 11527, Greece
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13
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Redondo MJ, Gignoux CR, Dabelea D, Hagopian WA, Onengut-Gumuscu S, Oram RA, Rich SS. Type 1 diabetes in diverse ancestries and the use of genetic risk scores. Lancet Diabetes Endocrinol 2022; 10:597-608. [PMID: 35724677 PMCID: PMC10024251 DOI: 10.1016/s2213-8587(22)00159-0] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 04/16/2022] [Accepted: 05/06/2022] [Indexed: 02/06/2023]
Abstract
Over 75 genetic loci within and outside of the HLA region influence type 1 diabetes risk. Genetic risk scores (GRS), which facilitate the integration of complex genetic information, have been developed in type 1 diabetes and incorporated into models and algorithms for classification, prognosis, and prediction of disease and response to preventive and therapeutic interventions. However, the development and validation of GRS across different ancestries is still emerging, as is knowledge on type 1 diabetes genetics in populations of diverse genetic ancestries. In this Review, we provide a summary of the current evidence on the evolutionary genetic variation in type 1 diabetes and the racial and ethnic differences in type 1 diabetes epidemiology, clinical characteristics, and preclinical course. We also discuss the influence of genetics on type 1 diabetes with differences across ancestries and the development and validation of GRS in various populations.
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Affiliation(s)
- Maria J Redondo
- Division of Diabetes and Endocrinology, Texas Children's Hospital, Baylor College of Medicine, Houston, TX, USA.
| | - Christopher R Gignoux
- Department of Medicine and Colorado Center for Personalized Medicine, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Dana Dabelea
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - William A Hagopian
- Division of Diabetes Programs, Pacific Northwest Research Institute, Seattle, WA, USA
| | - Suna Onengut-Gumuscu
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - Richard A Oram
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, University of Exeter, Exeter, UK; The Academic Kidney Unit, Royal Devon and Exeter NHS Foundation Trust, Exeter, UK
| | - Stephen S Rich
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
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14
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Achenbach P, Hippich M, Zapardiel-Gonzalo J, Karges B, Holl RW, Petrera A, Bonifacio E, Ziegler AG. A classification and regression tree analysis identifies subgroups of childhood type 1 diabetes. EBioMedicine 2022; 82:104118. [PMID: 35803018 PMCID: PMC9270253 DOI: 10.1016/j.ebiom.2022.104118] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2022] [Revised: 06/04/2022] [Accepted: 06/06/2022] [Indexed: 12/22/2022] Open
Abstract
Background Diabetes in childhood and adolescence includes autoimmune and non-autoimmune forms with heterogeneity in clinical and biochemical presentations. An unresolved question is whether there are subtypes, endotypes, or theratypes within these forms of diabetes. Methods The multivariable classification and regression tree (CART) analysis method was used to identify subgroups of diabetes with differing residual C-peptide levels in patients with newly diagnosed diabetes before 20 years of age (n=1192). The robustness of the model was assessed in a confirmation and prognosis cohort (n=2722). Findings The analysis selected age, haemoglobin A1c (HbA1c), and body mass index (BMI) as split parameters that classified patients into seven islet autoantibody-positive and three autoantibody-negative groups. There were substantial differences in genetics, inflammatory markers, diabetes family history, lipids, 25-OH-Vitamin D3, insulin treatment, insulin sensitivity and insulin autoimmunity among the groups, and the method stratified patients with potentially different pathogeneses and prognoses. Interferon-ɣ and/or tumour necrosis factor inflammatory signatures were enriched in the youngest islet autoantibody-positive groups and in patients with the lowest C-peptide values, while higher BMI and type 2 diabetes characteristics were found in older patients. The prognostic relevance was demonstrated by persistent differences in HbA1c at 7 years median follow-up. Interpretation This multivariable analysis revealed subgroups of young patients with diabetes that have potential pathogenetic and therapeutic relevance. Funding The work was supported by funds from the German Federal Ministry of Education and Research (01KX1818; FKZ 01GI0805; DZD e.V.), the Innovative Medicine Initiative 2 Joint Undertaking INNODIA (grant agreement No. 115797), the German Robert Koch Institute, and the German Diabetes Association.
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Affiliation(s)
- Peter Achenbach
- Institute of Diabetes Research, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich-Neuherberg, Germany; German Center for Diabetes Research (DZD), Munich, Germany; Technical University Munich, School of Medicine, Forschergruppe Diabetes at Klinikum rechts der Isar, Munich, Germany
| | - Markus Hippich
- Institute of Diabetes Research, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich-Neuherberg, Germany; German Center for Diabetes Research (DZD), Munich, Germany
| | - Jose Zapardiel-Gonzalo
- Institute of Diabetes Research, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich-Neuherberg, Germany
| | - Beate Karges
- Division of Endocrinology and Diabetes, Medical Faculty, RWTH Aachen University, D 52074 Aachen, Germany
| | - Reinhard W Holl
- German Center for Diabetes Research (DZD), Munich, Germany; Institute of Epidemiology and Medical Biometry, ZIBMT, University of Ulm, D 89081 Ulm, Germany
| | - Agnese Petrera
- Research Unit Protein Science and Metabolomics and Proteomics Core Facility, Helmholtz Zentrum Munich - German Research Center for Environmental Health, Neuherberg, Germany
| | - Ezio Bonifacio
- German Center for Diabetes Research (DZD), Munich, Germany; DFG Center for Regenerative Therapies Dresden, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany; Institute for Diabetes and Obesity, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich-Neuherberg, Germany
| | - Anette-G Ziegler
- Institute of Diabetes Research, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich-Neuherberg, Germany; German Center for Diabetes Research (DZD), Munich, Germany; Technical University Munich, School of Medicine, Forschergruppe Diabetes at Klinikum rechts der Isar, Munich, Germany.
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15
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Xu K, Lv H, Zhang J, Chen H, He Y, Shen M, Qian Y, Jiang H, Dai H, Zheng S, Yang T, Fu Q. The common rs13266634 C > T variant in SLC30A8 contributes to the heterogeneity of phenotype and clinical features of both type 1 and type 2 diabetic subtypes. Acta Diabetol 2022; 59:545-552. [PMID: 35034185 DOI: 10.1007/s00592-021-01831-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Accepted: 11/23/2021] [Indexed: 11/01/2022]
Abstract
AIMS T2D and T1D are phenotypically heterogeneous. This study aims to reveal the relationship between the common SLC30A8 rs13266634 variant and subgroups of T2D and T1D and their clinical characteristics. METHODS We included 3158 OGTT-based healthy controls, unrelated 1754 T2D, and 1675 autoantibody-positive T1D individuals. The associations between rs13266634 and subtypes of T2D, T1D, autoantibody status and glycemic-related quantitative traits were performed by binary logistic regression analysis under the additive model and multiple linear regression with appropriate adjustment. RESULTS We found that the T allele of rs13266634 was protectively associated with lean (OR = 0.810, P = 6.91E-04) but not obese T2D with considerable heterogeneity (P = 0.018). This allele also conferred significant protection with T1D of single (OR = 0.847, P = 9.76E-03), but not multi autoantibodies with substantial heterogeneity (P = 0.005). This variant significantly affected OGTT-related insulin release in lean (P = 2.66E-03, 3.88E-03 for CIR and DI, respectively) but not obese healthy individuals. Furthermore, rs13266634 T allele correlated with the risk of ZnT8A (OR = 1.440, P = 3.31E-05) and IA-2A (OR = 1.219, P = 1.32E-03) positivity, with more effect size in children/adolescents compared with adult-onset T1D subtypes. CONCLUSIONS These suggested that the SLC30A8 rs13266634 variant might be put into genetic risk scores to assess the risk of the subtypes of T1D and T2D and their related clinical features.
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Affiliation(s)
- Kuanfeng Xu
- Department of Endocrinology and Metabolism, First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China.
| | - Hui Lv
- Department of Endocrinology and Metabolism, First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Jie Zhang
- Department of Endocrinology and Metabolism, First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Heng Chen
- Department of Endocrinology and Metabolism, First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Yunqiang He
- Department of Endocrinology and Metabolism, First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Min Shen
- Department of Endocrinology and Metabolism, First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Yu Qian
- Department of Endocrinology and Metabolism, First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Hemin Jiang
- Department of Endocrinology and Metabolism, First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Hao Dai
- Department of Endocrinology and Metabolism, First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Shuai Zheng
- Department of Endocrinology and Metabolism, First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Tao Yang
- Department of Endocrinology and Metabolism, First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China.
| | - Qi Fu
- Department of Endocrinology and Metabolism, First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China.
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16
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Redondo MJ, Balasubramanyam A. Toward an Improved Classification of Type 2 Diabetes: Lessons From Research into the Heterogeneity of a Complex Disease. J Clin Endocrinol Metab 2021; 106:e4822-e4833. [PMID: 34291809 PMCID: PMC8787852 DOI: 10.1210/clinem/dgab545] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Indexed: 11/19/2022]
Abstract
CONTEXT Accumulating evidence indicates that type 2 diabetes (T2D) is phenotypically heterogeneous. Defining and classifying variant forms of T2D are priorities to better understand its pathophysiology and usher clinical practice into an era of "precision diabetes." EVIDENCE ACQUISITION AND METHODS We reviewed literature related to heterogeneity of T2D over the past 5 decades and identified a range of phenotypic variants of T2D. Their descriptions expose inadequacies in current classification systems. We attempt to link phenotypically diverse forms to pathophysiology, explore investigative methods that have characterized "atypical" forms of T2D on an etiological basis, and review conceptual frameworks for an improved taxonomy. Finally, we propose future directions to achieve the goal of an etiological classification of T2D. EVIDENCE SYNTHESIS Differences among ethnic and racial groups were early observations of phenotypic heterogeneity. Investigations that uncover complex interactions of pathophysiologic pathways leading to T2D are supported by epidemiological and clinical differences between the sexes and between adult and youth-onset T2D. Approaches to an etiological classification are illustrated by investigations of atypical forms of T2D, such as monogenic diabetes and syndromes of ketosis-prone diabetes. Conceptual frameworks that accommodate heterogeneity in T2D include an overlap between known diabetes types, a "palette" model integrated with a "threshold hypothesis," and a spectrum model of atypical diabetes. CONCLUSION The heterogeneity of T2D demands an improved, etiological classification scheme. Excellent phenotypic descriptions of emerging syndromes in different populations, continued clinical and molecular investigations of atypical forms of diabetes, and useful conceptual models can be utilized to achieve this important goal.
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Affiliation(s)
- Maria J Redondo
- Section of Diabetes and Endocrinology, Department of Pediatrics, Baylor College of Medicine, Houston, TX 77030, USA
- Texas Children’s Hospital, Houston, TX 77030, USA
| | - Ashok Balasubramanyam
- Division of Diabetes, Endocrinology and Metabolism, Baylor College of Medicine, Houston, TX 77030, USA
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17
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Charles MA, Leslie RD. Diabetes: Concepts of β-Cell Organ Dysfunction and Failure Would Lead to Earlier Diagnoses and Prevention. Diabetes 2021; 70:2444-2456. [PMID: 34711669 PMCID: PMC8564410 DOI: 10.2337/dbi21-0012] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2021] [Accepted: 08/09/2021] [Indexed: 12/24/2022]
Abstract
As the world endures a viral pandemic superimposed on a diabetes pandemic, the latter incorporates most of the comorbidities associated with the former, thereby exacerbating risk of death in both. An essential approach to both pandemics is prevention and unrealized earlier treatment. Thus, in this Perspective relating to diabetes, we emphasize a paradigm of, first, reversible β-cell organ dysfunction and then irreversible β-cell organ failure, which directly indicate the potential for earlier prevention, also unrealized in current guidelines. Four pillars support this paradigm: epidemiology, pathophysiology, molecular pathology, and genetics. A substantial worldwide knowledge base defines each pillar and informs a more aggressive preventive approach to most forms of the disorder. This analysis seeks to clarify the temporal and therapeutic relationships between lost β-cell function and content, illuminating the potential for earlier diagnoses and, thus, prevention. We also propose that myriad pathways leading to most forms of diabetes converge at the endoplasmic reticulum, where stress can result in β-cell death and content loss. Finally, genetic and nongenetic origins common to major types of diabetes can inform earlier diagnosis and, potentially, prevention, with the aim of preserving β-cell mass.
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18
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Del Bosque-Plata L, Hernández-Cortés EP, Gragnoli C. The broad pathogenetic role of TCF7L2 in human diseases beyond type 2 diabetes. J Cell Physiol 2021; 237:301-312. [PMID: 34612510 PMCID: PMC9292842 DOI: 10.1002/jcp.30581] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2020] [Revised: 08/16/2021] [Accepted: 08/18/2021] [Indexed: 12/20/2022]
Abstract
The TCF7L2 protein is a key transcriptional effector of the Wnt/β‐catenin signaling pathway, regulating gene expression. It was initially identified in cancer research and embryologic developmental studies. Later, the TCF7L2 gene was linked to type 2 diabetes (T2D), implicating TCF7L2 and Wnt‐signaling in metabolic disorders and homeostasis. In fact, TCF7L2‐T2D variants confer the greatest relative risk for T2D, unquestionably predicting conversion to T2D in individuals with impaired glucose tolerance. We aim to describe the relevance of TCF7L2 in other human disorders. The TCF7L2‐single nucleotide polymorphisms (SNPs) and T2D‐risk association have been replicated in numerous follow‐up studies, and research has now been performed in several other diseases. In this article, we discuss common TCF7L2‐T2D variants within the framework of their association with human diseases. The TCF7L2 functional regions need to be further investigated because the molecular and cellular mechanisms through which TCF7L2 contributes to risk associations with different diseases are still not fully elucidated. In this review, we show the association of common TCF7L2‐T2D variants with many types of diseases. However, the role of rare genetic variations in the TCF7L2 gene in distinct diseases and ethnic groups has not been explored, and understanding their impact on specific phenotypes will be of clinical relevance. This offers an excellent opportunity to gain a clearer picture of the role that the TCF7L2 gene plays in the pathophysiology of human diseases. The potential pleiotropic role of TCF7L2 may underlie a possible pathway for comorbidity in human disorders.
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Affiliation(s)
- Laura Del Bosque-Plata
- Laboratorio de Nutrigenética y Nutrigenómica, Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | | | - Claudia Gragnoli
- Department of Medicine, Division of Endocrinology, Diabetes, and Metabolic Disease, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, Pennsylvania.,Division of Endocrinology, Creighton University School of Medicine, Omaha, Nebraska, USA.,Department of Public Health Sciences, Penn State College of Medicine, Hershey, Pennsylvania, USA.,Molecular Biology Laboratory, Bios Biotech Multi-Diagnostic Health Center, Rome, Italy
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19
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Redondo MJ, Warnock MV, Libman IM, Bocchino LE, Cuthbertson D, Geyer S, Pugliese A, Steck AK, Evans-Molina C, Becker D, Sosenko JM, Bacha F. TCF7L2 Genetic Variants Do Not Influence Insulin Sensitivity or Secretion Indices in Autoantibody-Positive Individuals at Risk for Type 1 Diabetes. Diabetes Care 2021; 44:2039-2044. [PMID: 34326068 PMCID: PMC8740915 DOI: 10.2337/dc21-0531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Accepted: 06/10/2021] [Indexed: 02/03/2023]
Abstract
OBJECTIVE We aimed to test whether type 2 diabetes (T2D)-associated TCF7L2 genetic variants affect insulin sensitivity or secretion in autoantibody-positive relatives at risk for type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS We studied autoantibody-positive TrialNet Pathway to Prevention study participants (N = 1,061) (mean age 16.3 years) with TCF7L2 single nucleotide polymorphism (SNP) information and baseline oral glucose tolerance test (OGTT) to calculate indices of insulin sensitivity and secretion. With Bonferroni correction for multiple comparisons, P values < 0.0086 were considered statistically significant. RESULTS None, one, and two T2D-linked TCF7L2 alleles were present in 48.1%, 43.9%, and 8.0% of the participants, respectively. Insulin sensitivity (as reflected by 1/fasting insulin [1/IF]) decreased with increasing BMI z score and was lower in Hispanics. Insulin secretion (as measured by 30-min C-peptide index) positively correlated with age and BMI z score. Oral disposition index was negatively correlated with age, BMI z score, and Hispanic ethnicity. None of the indices were associated with TCF7L2 SNPs. In multivariable analysis models with age, BMI z score, ethnicity, sex, and TCF7L2 alleles as independent variables, C-peptide index increased with age, while BMI z score was associated with higher insulin secretion (C-peptide index), lower insulin sensitivity (1/IF), and lower disposition index; there was no significant effect of TCF7L2 SNPs on any of these indices. When restricting the analyses to participants with a normal OGTT (n = 743; 70%), the results were similar. CONCLUSIONS In nondiabetic autoantibody-positive individuals, TCF7L2 SNPs were not related to insulin sensitivity or secretion indices after accounting for BMI z score, age, sex, and ethnicity.
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Affiliation(s)
- Maria J Redondo
- Texas Children's Hospital, Baylor College of Medicine, Houston, TX
| | | | | | - Laura E Bocchino
- University of South Florida, Tampa, FL.,Jaeb Center for Health Research, Tampa, FL
| | | | - Susan Geyer
- University of South Florida, Tampa, FL.,Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN
| | | | - Andrea K Steck
- Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Carmella Evans-Molina
- Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, IN
| | | | - Jay M Sosenko
- Diabetes Research Institute, Miller School of Medicine, University of Miami, Miami, FL
| | - Fida Bacha
- Texas Children's Hospital, Baylor College of Medicine, Houston, TX.,Children's Nutrition Research Center, Agricultural Research Service, U.S. Department of Agriculture, Houston, TX
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20
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Untangling the genetic link between type 1 and type 2 diabetes using functional genomics. Sci Rep 2021; 11:13871. [PMID: 34230558 PMCID: PMC8260770 DOI: 10.1038/s41598-021-93346-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Accepted: 06/16/2021] [Indexed: 02/06/2023] Open
Abstract
There is evidence pointing towards shared etiological features between type 1 diabetes (T1D) and type 2 diabetes (T2D) despite both phenotypes being considered genetically distinct. However, the existence of shared genetic features for T1D and T2D remains complex and poorly defined. To better understand the link between T1D and T2D, we employed an integrated functional genomics approach involving extensive chromatin interaction data (Hi-C) and expression quantitative trait loci (eQTL) data to characterize the tissue-specific impacts of single nucleotide polymorphisms associated with T1D and T2D. We identified 195 pleiotropic genes that are modulated by tissue-specific spatial eQTLs associated with both T1D and T2D. The pleiotropic genes are enriched in inflammatory and metabolic pathways that include mitogen-activated protein kinase activity, pertussis toxin signaling, and the Parkinson's disease pathway. We identified 8 regulatory elements within the TCF7L2 locus that modulate transcript levels of genes involved in immune regulation as well as genes important in the etiology of T2D. Despite the observed gene and pathway overlaps, there was no significant genetic correlation between variant effects on T1D and T2D risk using European ancestral summary data. Collectively, our findings support the hypothesis that T1D and T2D specific genetic variants act through genetic regulatory mechanisms to alter the regulation of common genes, and genes that co-locate in biological pathways, to mediate pleiotropic effects on disease development. Crucially, a high risk genetic profile for T1D alters biological pathways that increase the risk of developing both T1D and T2D. The same is not true for genetic profiles that increase the risk of developing T2D. The conversion of information on genetic susceptibility to the protein pathways that are altered provides an important resource for repurposing or designing novel therapies for the management of diabetes.
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Zhang Z, Xu L, Xu X. The role of transcription factor 7-like 2 in metabolic disorders. Obes Rev 2021; 22:e13166. [PMID: 33615650 DOI: 10.1111/obr.13166] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Revised: 10/08/2020] [Accepted: 10/08/2020] [Indexed: 12/13/2022]
Abstract
Transcription factor 7-like 2 (TCF7L2), a member of the T cell factor/lymphoid enhancer factor family, generally forms a complex with β-catenin to regulate the downstream target genes as an effector of the canonical Wnt signalling pathway. TCF7L2 plays a vital role in various biological processes and functions in many organs and tissues, including the liver, islet and adipose tissues. Further, TCF7L2 down-regulates hepatic gluconeogenesis and promotes lipid accumulation. In islets, TCF7L2 not only affects the insulin secretion of the β-cells but also has an impact on other cells. In addition, TCF7L2 influences adipogenesis in adipose tissues. Thus, an out-of-control TCF7L2 expression can result in metabolic disorders. The TCF7L2 gene is composed of 17 exons, generating 13 different transcripts, and has many single-nucleotide polymorphisms (SNPs). The discovery that these SNPs have an impact on the risk of type 2 diabetes (T2D) has attracted thorough investigations in the study of TCF7L2. Apart from T2D, TCF7L2 SNPs are also associated with type 1, posttransplant and other types of diabetes. Furthermore, TCF7L2 variants affect the progression of other disorders, such as obesity, cancers, metabolic syndrome and heart diseases. Finally, the interaction between TCF7L2 variants and diet also needs to be investigated.
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Affiliation(s)
- Zhensheng Zhang
- Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, China.,Department of Hepatobiliary and Pancreatic Surgery, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.,NHC Key Laboratory of Combined Multi-organ Transplantation, Hangzhou, China.,Zhejiang University School of Medicine, Hangzhou, China
| | - Li Xu
- Department of Hepatobiliary and Pancreatic Surgery, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.,Zhejiang University Cancer Center, Hangzhou, China.,NHC Key Laboratory of Combined Multi-organ Transplantation, Hangzhou, China.,Zhejiang University School of Medicine, Hangzhou, China
| | - Xiao Xu
- Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, China.,Department of Hepatobiliary and Pancreatic Surgery, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.,Zhejiang University Cancer Center, Hangzhou, China
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Redondo MJ, Nathan BM, Jacobsen LM, Sims E, Bocchino LE, Pugliese A, Schatz DA, Atkinson MA, Skyler J, Palmer J, Geyer S, Sosenko JM. Index60 as an additional diagnostic criterion for type 1 diabetes. Diabetologia 2021; 64:836-844. [PMID: 33496819 PMCID: PMC7940596 DOI: 10.1007/s00125-020-05365-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Accepted: 10/28/2020] [Indexed: 12/12/2022]
Abstract
AIMS/HYPOTHESIS We aimed to compare characteristics of individuals identified in the peri-diagnostic range by Index60 (composite glucose and C-peptide measure) ≥2.00, 2 h OGTT glucose ≥11.1 mmol/l, or both. METHODS We studied autoantibody-positive participants in the Type 1 Diabetes TrialNet Pathway to Prevention study who, at their baseline OGTT, had 2 h blood glucose ≥11.1 mmol/l and/or Index60 ≥2.00 (n = 354, median age = 11.2 years, age range = 1.7-46.6; 49% male, 83% non-Hispanic White). Type 1 diabetes-relevant characteristics (e.g., age, C-peptide, autoantibodies, BMI) were compared among three mutually exclusive groups: 2 h glucose ≥11.1 mmol/l and Index60 <2.00 [Glu(+), n = 76], 2 h glucose <11.1 mmol/l and Index60 ≥2.00 [Ind(+), n = 113], or both 2 h glucose ≥11.1 mmol/l and Index60 ≥2.00 [Glu(+)/Ind(+), n = 165]. RESULTS Participants in Glu(+), vs those in Ind(+) or Glu(+)/Ind(+), were older (mean ages = 22.9, 11.8 and 14.7 years, respectively), had higher early (30-0 min) C-peptide response (1.0, 0.50 and 0.43 nmol/l), higher AUC C-peptide (2.33, 1.13 and 1.10 nmol/l), higher percentage of overweight/obesity (58%, 16% and 30%) (all comparisons, p < 0.0001), and a lower percentage of multiple autoantibody positivity (72%, 92% and 93%) (p < 0.001). OGTT-stimulated C-peptide and glucose patterns of Glu(+) differed appreciably from Ind(+) and Glu(+)/Ind(+). Progression to diabetes occurred in 61% (46/76) of Glu(+) and 63% (71/113) of Ind(+). Even though Index60 ≥2.00 was not a Pathway to Prevention diagnostic criterion, Ind(+) had a 4 year cumulative diabetes incidence of 95% (95% CI 86%, 98%). CONCLUSIONS/INTERPRETATION Participants in the Ind(+) group had more typical characteristics of type 1 diabetes than participants in the Glu(+) did and were as likely to be diagnosed. However, unlike Glu(+) participants, Ind(+) participants were not identified at the baseline OGTT.
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Affiliation(s)
- Maria J Redondo
- Texas Children's Hospital, Baylor College of Medicine, Houston, TX, USA.
| | - Brandon M Nathan
- Division of Pediatric Endocrinology, University of Minnesota, Minneapolis, MN, USA
| | | | - Emily Sims
- Indiana University School of Medicine, Indiana University, Indianapolis, IN, USA
| | - Laura E Bocchino
- University of South Florida, Tampa, FL, USA
- Jaeb Center for Health Research, Tampa, FL, USA
| | - Alberto Pugliese
- Diabetes Research Institute, Miller School of Medicine, University of Miami, Miami, FL, USA
| | | | - Mark A Atkinson
- University of Florida Diabetes Institute, Gainesville, FL, USA
| | - Jay Skyler
- Diabetes Research Institute, Miller School of Medicine, University of Miami, Miami, FL, USA
| | | | - Susan Geyer
- University of South Florida, Tampa, FL, USA
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, USA
| | - Jay M Sosenko
- Diabetes Research Institute, Miller School of Medicine, University of Miami, Miami, FL, USA
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Iafusco F, Maione G, Rosanio FM, Mozzillo E, Franzese A, Tinto N. Cystic Fibrosis-Related Diabetes (CFRD): Overview of Associated Genetic Factors. Diagnostics (Basel) 2021; 11:diagnostics11030572. [PMID: 33810109 PMCID: PMC8005125 DOI: 10.3390/diagnostics11030572] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2021] [Accepted: 03/19/2021] [Indexed: 12/21/2022] Open
Abstract
Cystic fibrosis (CF) is the most common autosomal recessive disease in the Caucasian population and is caused by mutations in the CF transmembrane conductance regulator (CFTR) gene that encodes for a chloride/bicarbonate channel expressed on the membrane of epithelial cells of the airways and of the intestine, as well as in cells with exocrine and endocrine functions. A common nonpulmonary complication of CF is cystic fibrosis-related diabetes (CFRD), a distinct form of diabetes due to insulin insufficiency or malfunction secondary to destruction/derangement of pancreatic betacells, as well as to other factors that affect their function. The prevalence of CFRD increases with age, and 40–50% of CF adults develop the disease. Several proposed hypotheses on how CFRD develops have emerged, including exocrine-driven fibrosis and destruction of the entire pancreas, as well as contrasting theories on the direct or indirect impact of CFTR mutation on islet function. Among contributors to the development of CFRD, in addition to CFTR genotype, there are other genetic factors related and not related to type 2 diabetes. This review presents an overview of the current understanding on genetic factors associated with glucose metabolism abnormalities in CF.
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Affiliation(s)
- Fernanda Iafusco
- Department of Molecular Medicine and Medical Biotechnology, University of Naples “Federico II”, 80131 Naples, Italy; (F.I.); (G.M.)
- CEINGE Advanced Biotechnology, 80131 Naples, Italy
| | - Giovanna Maione
- Department of Molecular Medicine and Medical Biotechnology, University of Naples “Federico II”, 80131 Naples, Italy; (F.I.); (G.M.)
- CEINGE Advanced Biotechnology, 80131 Naples, Italy
| | - Francesco Maria Rosanio
- Regional Center of Pediatric Diabetology, Department of Translational Medical Sciences, Section of Pediatrics, University of Naples “Federico II”, 80131 Naples, Italy; (F.M.R.); (E.M.); (A.F.)
| | - Enza Mozzillo
- Regional Center of Pediatric Diabetology, Department of Translational Medical Sciences, Section of Pediatrics, University of Naples “Federico II”, 80131 Naples, Italy; (F.M.R.); (E.M.); (A.F.)
| | - Adriana Franzese
- Regional Center of Pediatric Diabetology, Department of Translational Medical Sciences, Section of Pediatrics, University of Naples “Federico II”, 80131 Naples, Italy; (F.M.R.); (E.M.); (A.F.)
| | - Nadia Tinto
- Department of Molecular Medicine and Medical Biotechnology, University of Naples “Federico II”, 80131 Naples, Italy; (F.I.); (G.M.)
- CEINGE Advanced Biotechnology, 80131 Naples, Italy
- Correspondence:
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Vilarrasa N, San Jose P, Rubio MÁ, Lecube A. Obesity in Patients with Type 1 Diabetes: Links, Risks and Management Challenges. Diabetes Metab Syndr Obes 2021; 14:2807-2827. [PMID: 34188505 PMCID: PMC8232956 DOI: 10.2147/dmso.s223618] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Accepted: 05/19/2021] [Indexed: 12/15/2022] Open
Abstract
Obesity affects large numbers of patients with type 1 diabetes (T1D) across their lifetime, with rates ranging between 2.8% and 37.1%. Patients with T1D and obesity are characterized by the presence of insulin resistance, of high insulin requirements, have a greater cardiometabolic risk and an enhanced risk of developing chronic complications when compared to normal-weight persons with T1D. Dual treatment of obesity and T1D is challenging and no specific guidelines for improving outcomes of both glycemic control and weight management have been established for this population. Nevertheless, although evidence is scarce, a comprehensive approach based on a balanced hypocaloric diet, physical activity and cognitive behavioral therapy by a multidisciplinary team, expert in both obesity and diabetes, remains as the best clinical practice. However, weight loss responses with lifestyle changes alone are limited, so in the "roadmap" of the treatment of obesity in T1D, it will be helpful to include anti-obesity pharmacotherapy despite at present there is a lack of evidence since T1D patients have been excluded from anti-obesity drug clinical trials. In case of severe obesity, bariatric surgery has proven to be of benefit in obtaining a substantial and long-term weight loss and reduction in cardiovascular risk. The near future looks promising with the development of new and more effective anti-obesity treatments and strategies to improve insulin resistance and oxidative stress. Advances in precision medicine may help individualize and optimize the medical management and care of these patients. This review, by gathering current evidence, highlights the need of solid knowledge in all facets of the treatment of patients with obesity and T1D that can only be obtained through high quality well-designed studies.
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Affiliation(s)
- Nuria Vilarrasa
- Department of Endocrinology and Nutrition, Hospital Universitario de Bellvitge-IDIBELL, Barcelona, Spain
- CIBERDEM-CIBER de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, Madrid, Spain
- Correspondence: Nuria Vilarrasa Hospital Universitario de Bellvitge-IDIBELL, C/Feixa Llarga s/n, 08907 L´Hospitalet de Llobregat, Barcelona, SpainTel +34 93-5338511Fax +34 933375248 Email
| | - Patricia San Jose
- Department of Endocrinology and Nutrition, Hospital Universitario de Bellvitge-IDIBELL, Barcelona, Spain
| | - Miguel Ángel Rubio
- Department of Endocrinology & Nutrition, Hospital Clínico San Carlos, IDISSC, Madrid, 28040, Spain
| | - Albert Lecube
- CIBERDEM-CIBER de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, Madrid, Spain
- Endocrinology and Nutrition Department, Hospital Universitari Arnau de Vilanova, Lleida, 25198, Spain
- Obesity, Diabetes and Metabolism (ODIM) Research Group, Institut de Recerca Biomèdica de Lleida (IRBLleida), University of Lleida, Lleida, Spain
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March CA, Becker DJ, Libman IM. Nutrition and Obesity in the Pathogenesis of Youth-Onset Type 1 Diabetes and Its Complications. Front Endocrinol (Lausanne) 2021; 12:622901. [PMID: 33828529 PMCID: PMC8021094 DOI: 10.3389/fendo.2021.622901] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Accepted: 02/15/2021] [Indexed: 12/15/2022] Open
Abstract
Since the 1980s, there has been a dramatic rise in the prevalence of overweight and obesity in pediatric populations, in large part driven by sedentary lifestyles and changing dietary patterns with more processed foods. In parallel with the rise in pediatric obesity in the general population, the prevalence of overweight and obesity has increased among children and adolescents with type 1 diabetes. Adiposity has been implicated in a variety of mechanisms both potentiating the risk for type 1 diabetes as well as exacerbating long-term complications, particularly cardiovascular disease. Treatment options targeting the unique needs of obese pediatric patients, both before and after diagnosis of type 1 diabetes, are limited. In this review, we discuss the history of the epidemiology of the obesity epidemic in the context of pediatric type 1 diabetes, highlight the possible role of obesity in type 1 diabetes pathogenesis and review the concept of "double diabetes". The impact of obesity at and after diagnosis will be discussed, including noted differences in clinical and biochemical markers, lipid abnormalities, and long-term cardiovascular complications. Finally, we will review the existing literature on pharmacologic and nutritional interventions as potential treatment strategies for youth with coexisting type 1 diabetes and obesity.
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Bhatty A, Rubab Z, Jafri HSMO, Zano S. Identification of dysregulated pathways through <i>SLC30A8</i> protein interaction in type 1 diabetes mellitus. AIMS MOLECULAR SCIENCE 2021. [DOI: 10.3934/molsci.2021023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
<abstract><sec>
<title>Objective</title>
<p>The aim of the current study was to explore the gene enrichment and dysregulated pathways on the basis of interaction network analysis of <italic>SLC30A8</italic> in type 1 diabetes mellitus (T1DM). <italic>SLC30A8</italic> polymorphism could be characterized as a beneficial tool to identify the interacting gene in developing T1DM.</p>
</sec><sec>
<title>Materials and methods</title>
<p><italic>SLC30A8</italic> interacting protein interaction network was obtained by String Interaction network Version 11.0. Ten proteins were identified interacting with <italic>SLC30A8</italic> and were analysed by protein-protein interaction and enrichment network analysis along with Functional Enrichment analysis tool (FunRich 3.1.3) to map the gene data sets. In entire analysis, FunRich database was used as background against all annotated gene/protein list. Protein-protein interaction (PPI) and enrichment network analysis of the selected protein: <italic>SLC30A8</italic> gene along with gene mapping and pathway enrichment were performed using FunRich 3.1.3 and String Interaction network Version 11.0.</p>
</sec><sec>
<title>Results</title>
<p>Biological pathway grouping displayed enriched proteins in TRAIL signalling pathway (<italic>p</italic> < 0.001). <italic>PTPRN, GAD2</italic> and <italic>TCF7L2</italic> were enriched in TRAIL Signalling pathway when <italic>INS</italic> was made focused gene and directly interacting with <italic>SLC30A8</italic>.</p>
</sec><sec>
<title>Conclusions</title>
<p>TRAIL signalling pathways were enriched in T1DM. Therefore, <italic>SLC30A8</italic> along with <italic>PTPRN, GAD2</italic> and <italic>TCF7L2</italic> involved in TRAIL pathway must be further explored to understand their in vivo role in T1DM.</p>
</sec></abstract>
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Cousminer DL, Grant SFA. Insights into the Genetic Underpinnings of Endocrine Traits from Large-Scale Genome-Wide Association Studies. Endocrinol Metab Clin North Am 2020; 49:725-739. [PMID: 33153676 DOI: 10.1016/j.ecl.2020.07.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Great strides have been made in genetic association studies of endocrine traits and diseases, with hundreds or thousands of variants associated with height, body mass index, bone density, pubertal timing, and diabetes in recent years. The common variants associated with these traits explain up to half of the trait variation owing to genetic factors, and when aggregated into polygenic risk scores, can also impact clinically relevant phenotypes at the tail ends of the trait distributions. However, pediatric studies tend to lag behind, and it is often unclear how adult-associated variants behave across life.
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Affiliation(s)
- Diana L Cousminer
- Center for Spatial and Functional Genomics, Division of Human Genetics, Department of Pediatrics, Children's Hospital of Philadelphia, 3615 Civic Center Boulevard, Philadelphia, PA 19104, USA; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Clinical Research Building 500, 415 Curie Boulevard, Philadelphia, PA 19104, USA
| | - Struan F A Grant
- Center for Spatial and Functional Genomics, Division of Human Genetics, Department of Pediatrics, Children's Hospital of Philadelphia, 3615 Civic Center Boulevard, Philadelphia, PA 19104, USA; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Clinical Research Building 500, 415 Curie Boulevard, Philadelphia, PA 19104, USA.
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Abstract
PURPOSE OF REVIEW Diabetes is a spectrum of clinical manifestations, including latent autoimmune diabetes in adults (LADA). However, it has been questioned whether LADA exists or simply is a group of misclassified type 1 diabetes (T1D) and type 2 diabetes (T2D) patients. This review will provide an updated overview of the genetics of LADA, highlight what genetics tell us about LADA as a diabetes subtype, and point to future directions in the study of LADA. RECENT FINDINGS Recent studies have verified the genetic overlap between LADA and both T1D and T2D and have contributed identification of a novel LADA-specific locus, namely, PFKFB3, and subtype-specific signatures in the HLA region. Genetic risk scores comprising T1D-risk variants have been shown to be a promising tool for discriminating diabetes subtypes and identifying patients rapidly progressing to insulin dependence. Genetic data support the existence of LADA, but further studies are needed to fully determine the place of LADA in the diabetes spectrum.
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Affiliation(s)
- Mette K Andersen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3B, DK-2200, Copenhagen N, Denmark.
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Cause or effect? A review of clinical data demonstrating beta cell dysfunction prior to the clinical onset of type 1 diabetes. Mol Metab 2020; 27S:S129-S138. [PMID: 31500824 PMCID: PMC6768572 DOI: 10.1016/j.molmet.2019.06.010] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
Background Limited successes of conventional approaches to type 1 diabetes (T1D) prevention and treatment have highlighted the need for improved understanding of risk factors contributing to or hastening progression to clinical diagnosis. Scope of review This review summarizes beta cell function metabolic phenotyping data from clinical studies conducted in at-risk individuals before T1D onset and healthy controls. Data are drawn from studies comparing at-risk individuals who progress to T1D to at-risk individuals who do not progress to T1D, as well as from studies comparing at-risk individuals to controls without a T1D family history. Major conclusions Rapid loss of beta cell insulin secretion occurs in the months immediately preceding clinical onset. However, evidence of beta cell dysfunction is present even years earlier. Comparisons to controls without a family history suggest that many individuals in families impacted by T1D have evidence of beta cell dysfunction, even individuals who are unlikely to develop clinical disease. These findings may mean that underlying metabolic beta cell dysfunction contributes to T1D development and may explain some of the heterogeneity observed in the disease.
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Kakleas K, Basatemur E, Karavanaki K. Association Between Severity of Diabetic Ketoacidosis at Diagnosis and Multiple Autoimmunity in Children With Type 1 Diabetes Mellitus: A Study From a Greek Tertiary Centre. Can J Diabetes 2020; 45:33-38.e2. [PMID: 32800761 DOI: 10.1016/j.jcjd.2020.05.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Revised: 05/05/2020] [Accepted: 05/06/2020] [Indexed: 11/29/2022]
Abstract
OBJECTIVES Type 1 diabetes mellitus is a chronic disorder associated with development of autoimmunity. In this work, we studied the relationship between severity of acidosis at diagnosis and future risk for autoimmunity development in children with type 1 diabetes. METHODS We investigated the presence of associated autoimmunity in 144 children with type 1 diabetes (mean ± standard deviation: age, 12.44±4.76 years; diabetes duration, 4.41±3.70 years). We identified the presence of thyroid disease, celiac disease, autoimmune gastritis and adrenal autoimmunity, and retrospectively reviewed the files for presence of diabetic ketoacidosis at diagnosis. RESULTS Autoimmunity prevalence was 16.7% for thyroid autoimmunity, 9.5% for celiac disease, 5% for gastric autoimmunity and 8.0% for multiple autoimmunities. There were strong associations between severe acidosis at diabetes diagnosis (pH<7.10) and development of thyroid autoimmunity (odds ratio [OR], 5.34; 95% confidence interval [CI], 1.90‒15.1; p<0.001), celiac disease (OR, 5.83; 95% CI, 1.19‒28.6; p=0.013), gastric autoimmunity (OR, 13.1; 95% CI, 1.22‒140; p=0.006) and multiple autoimmunity (OR, 26.7; 95% CI, 2.36‒301; p<0.01). The associations persisted after adjustment for sex, age at diabetes diagnosis, age at assessment, time since diabetes diagnosis and antiglutamic acid decarboxylase autoantibody status. CONCLUSIONS The severity of acidosis at diagnosis is strongly associated with the development of associated autoimmune diseases in children with type 1 diabetes and could act as a predictive factor for multiple autoimmunity development. This association can be either due to effect of acidosis on immune system or to the presence of a more aggressive diabetes endotype.
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Affiliation(s)
- Kostas Kakleas
- Paediatric Department, Leicester Royal Infirmary, Leicester, United Kingdom.
| | - Emre Basatemur
- Population, Policy and Practice Programme, Institute of Child Health, University College of London, London, United Kingdom
| | - Kyriaki Karavanaki
- Diabetic Clinic, Second Department of Pediatrics, University of Athens, "P&A Kyriakou" Children's Hospital, Athens, Greece
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Redondo MJ, Sosenko J, Libman I, McVean JJF, Tosur M, Atkinson MA, Becker D, Geyer S. Single Islet Autoantibody at Diagnosis of Clinical Type 1 Diabetes is Associated With Older Age and Insulin Resistance. J Clin Endocrinol Metab 2020; 105:dgz296. [PMID: 31867614 PMCID: PMC7089846 DOI: 10.1210/clinem/dgz296] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2019] [Accepted: 12/19/2019] [Indexed: 12/11/2022]
Abstract
CONTEXT Multiple islet autoantibody positivity usually precedes clinical (stage 3) type 1 diabetes (T1D). OBJECTIVE To test the hypothesis that individuals who develop stage 3 T1D with only a single autoantibody have unique metabolic differences. DESIGN Cross-sectional analysis of participants in the T1D TrialNet study. SETTING Autoantibody-positive relatives of individuals with stage 3 T1D. PARTICIPANTS Autoantibody-positive relatives who developed stage 3 T1D (at median age 12.4 years, range = 1.4-58.6) and had autoantibody data close to clinical diagnosis (n = 786, 47.4% male, 79.9% non-Hispanic white). MAIN OUTCOME MEASURES Logistic regression modeling was used to assess relationships between autoantibody status and demographic, clinical, and metabolic characteristics, adjusting for potential confounders and correcting for multiple comparisons. RESULTS At diagnosis of stage 3 T1D, single autoantibody positivity, observed in 119 (15.1%) participants (72% GAD65, 13% microinsulin antibody assay, 11% insulinoma-associated antigen 2, 1% islet cell antibody, 3% autoantibodies to zinc transporter 8 [ZnT8]), was significantly associated with older age, higher C-peptide measures (fasting, area under the curve, 2-hour, and early response in oral glucose tolerance test), higher homeostatic model assessment of insulin resistance, and lower T1D Index60 (all P < 0.03). While with adjustment for age, 2-hour C-peptide remained statistically different, controlling for body mass index (BMI) attenuated the differences. Sex, race, ethnicity, human leukocyte antigen DR3-DQ2, and/or DR4-DQ8, BMI category, and glucose measures were not significantly associated with single autoantibody positivity. CONCLUSIONS Compared with multiple autoantibody positivity, single autoantibody at diagnosis of stage 3 T1D was associated with older age and insulin resistance possibly mediated by elevated BMI, suggesting heterogeneous disease pathogenesis. These differences are potentially relevant for T1D prevention and treatment.
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Affiliation(s)
- Maria J Redondo
- Baylor College of Medicine, Texas Children’s Hospital, Houston, Texas
| | | | | | | | - Mustafa Tosur
- Baylor College of Medicine, Texas Children’s Hospital, Houston, Texas
| | - Mark A Atkinson
- University of Florida Diabetes Institute, Gainesville, Florida
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Ferrara-Cook C, Geyer SM, Evans-Molina C, Libman IM, Becker DJ, Gitelman SE, Redondo MJ. Excess BMI Accelerates Islet Autoimmunity in Older Children and Adolescents. Diabetes Care 2020; 43:580-587. [PMID: 31937610 PMCID: PMC7035590 DOI: 10.2337/dc19-1167] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/12/2019] [Accepted: 12/14/2019] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Sustained excess BMI increases the risk of type 1 diabetes (T1D) in autoantibody-positive relatives without diabetes of patients. We tested whether elevated BMI also accelerates the progression of islet autoimmunity before T1D diagnosis. RESEARCH DESIGN AND METHODS We studied 706 single autoantibody-positive pediatric TrialNet participants (ages 1.6-18.6 years at baseline). Cumulative excess BMI (ceBMI) was calculated for each participant based on longitudinally accumulated BMI ≥85th age- and sex-adjusted percentile. Recursive partitioning analysis and multivariable modeling defined the age cut point differentiating the risk for progression to multiple positive autoantibodies. RESULTS At baseline, 175 children (25%) had a BMI ≥85th percentile. ceBMI range was -9.2 to 15.6 kg/m2 (median -1.91), with ceBMI ≥0 kg/m2 corresponding to persistently elevated BMI ≥85th percentile. Younger age increased the progression to multiple autoantibodies, with age cutoff of 9 years defined by recursive partitioning analysis. Although ceBMI was not significantly associated with progression from single to multiple autoantibodies overall, there was an interaction with ceBMI ≥0 kg/m2, age, and HLA (P = 0.009). Among children ≥9 years old without HLA DR3-DQ2 and DR4-DQ8, ceBMI ≥0 kg/m2 increased the rate of progression from single to multiple positive autoantibodies (hazard ratio 7.32, P = 0.004) and conferred a risk similar to that in those with T1D-associated HLA haplotypes. In participants <9 years old, the effect of ceBMI on progression to multiple autoantibodies was not significant regardless of HLA type. CONCLUSIONS These data support that elevated BMI may exacerbate islet autoimmunity prior to clinical T1D, particularly in children with lower risk based on age and HLA. Interventions to maintain normal BMI may prevent or delay the progression of islet autoimmunity.
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Affiliation(s)
| | | | | | - Ingrid M Libman
- Children's Hospital of Pittsburgh, University of Pittsburgh Medical Center, Pittsburgh, PA
| | - Dorothy J Becker
- Children's Hospital of Pittsburgh, University of Pittsburgh Medical Center, Pittsburgh, PA
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33
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Mishra R, Åkerlund M, Cousminer DL, Ahlqvist E, Bradfield JP, Chesi A, Hodge KM, Guy VC, Brillon DJ, Pratley RE, Rickels MR, Vella A, Ovalle F, Harris RI, Melander O, Varvel S, Hakonarson H, Froguel P, Lonsdale JT, Mauricio D, Schloot NC, Khunti K, Greenbaum CJ, Yderstræde KB, Tuomi T, Voight BF, Schwartz S, Boehm BO, Groop L, Leslie RD, Grant SFA. Genetic Discrimination Between LADA and Childhood-Onset Type 1 Diabetes Within the MHC. Diabetes Care 2020; 43:418-425. [PMID: 31843946 PMCID: PMC6971787 DOI: 10.2337/dc19-0986] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2019] [Accepted: 11/16/2019] [Indexed: 02/06/2023]
Abstract
OBJECTIVE The MHC region harbors the strongest loci for latent autoimmune diabetes in adults (LADA); however, the strength of association is likely attenuated compared with that for childhood-onset type 1 diabetes. In this study, we recapitulate independent effects in the MHC class I region in a population with type 1 diabetes and then determine whether such conditioning in LADA yields potential genetic discriminators between the two subtypes within this region. RESEARCH DESIGN AND METHODS Chromosome 6 was imputed using SNP2HLA, with conditional analysis performed in type 1 diabetes case subjects (n = 1,985) and control subjects (n = 2,219). The same approach was applied to a LADA cohort (n = 1,428) using population-based control subjects (n = 2,850) and in a separate replication cohort (656 type 1 diabetes case, 823 LADA case, and 3,218 control subjects). RESULTS The strongest associations in the MHC class II region (rs3957146, β [SE] = 1.44 [0.05]), as well as the independent effect of MHC class I genes, on type 1 diabetes risk, particularly HLA-B*39 (β [SE] = 1.36 [0.17]), were confirmed. The conditional analysis in LADA versus control subjects showed significant association in the MHC class II region (rs3957146, β [SE] = 1.14 [0.06]); however, we did not observe significant independent effects of MHC class I alleles in LADA. CONCLUSIONS In LADA, the independent effects of MHC class I observed in type 1 diabetes were not observed after conditioning on the leading MHC class II associations, suggesting that the MHC class I association may be a genetic discriminator between LADA and childhood-onset type 1 diabetes.
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Affiliation(s)
- Rajashree Mishra
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA.,Graduate Group in Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Mikael Åkerlund
- Lund University Diabetes Centre, Department of Clinical Sciences Malmö, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Diana L Cousminer
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA.,Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Emma Ahlqvist
- Lund University Diabetes Centre, Department of Clinical Sciences Malmö, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Jonathan P Bradfield
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA
| | - Alessandra Chesi
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA
| | - Kenyaita M Hodge
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA
| | - Vanessa C Guy
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA
| | | | - Richard E Pratley
- Translational Research Institute for Metabolism and Diabetes, Florida Hospital, FL
| | - Michael R Rickels
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | | | | | | | - Olle Melander
- Lund University Diabetes Centre, Department of Clinical Sciences Malmö, Lund University, Skåne University Hospital, Malmö, Sweden
| | | | - Hakon Hakonarson
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA.,Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Phillippe Froguel
- CNRS 8199, Université Lille Nord de France, Pasteur Institute, Lille, France.,Department of Genomics of Common Disease, Imperial College London, London, U.K
| | | | - Didac Mauricio
- Hospital de la Santa Creu i Sant Pau, CIBERDEM, Barcelona, Spain
| | | | - Kamlesh Khunti
- Diabetes Research Centre, University of Leicester, Leicester, U.K
| | | | | | - Tiinamaija Tuomi
- Department of Endocrinology, Helsinki University Hospital, Helsinki, Finland.,Folkhälsan Research Centre, Helsinki, Finland, and Research Programs Unit, Clinical and Molecular Metabolism, University of Helsinki, Helsinki, Finland.,Institute for Molecular Medicine Finland, Helsinki, Finland
| | - Benjamin F Voight
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.,Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.,Department of Systems, Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.,Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | | | - Bernhard O Boehm
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, and Imperial College London, London, U.K.,Department of Internal Medicine I, Ulm University Medical Centre, Ulm, Germany
| | - Leif Groop
- Lund University Diabetes Centre, Department of Clinical Sciences Malmö, Lund University, Skåne University Hospital, Malmö, Sweden.,Institute for Molecular Medicine Finland, Helsinki, Finland
| | - Richard David Leslie
- Department of Immunobiology, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, U.K
| | - Struan F A Grant
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA .,Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.,Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA.,Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.,Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
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34
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Affiliation(s)
- Maria J Redondo
- Section of Pediatric Diabetes and Endocrinology, Texas Children's Hospital, Baylor College of Medicine, Houston, TX
| | - Patrick Concannon
- Genetics Institute and Department of Pathology, Immunology, and Laboratory Medicine, University of Florida, Gainesville, FL
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35
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Battaglia M, Ahmed S, Anderson MS, Atkinson MA, Becker D, Bingley PJ, Bosi E, Brusko TM, DiMeglio LA, Evans-Molina C, Gitelman SE, Greenbaum CJ, Gottlieb PA, Herold KC, Hessner MJ, Knip M, Jacobsen L, Krischer JP, Long SA, Lundgren M, McKinney EF, Morgan NG, Oram RA, Pastinen T, Peters MC, Petrelli A, Qian X, Redondo MJ, Roep BO, Schatz D, Skibinski D, Peakman M. Introducing the Endotype Concept to Address the Challenge of Disease Heterogeneity in Type 1 Diabetes. Diabetes Care 2020; 43:5-12. [PMID: 31753960 PMCID: PMC6925574 DOI: 10.2337/dc19-0880] [Citation(s) in RCA: 198] [Impact Index Per Article: 49.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Accepted: 10/14/2019] [Indexed: 02/06/2023]
Abstract
The clinical diagnosis of new-onset type 1 diabetes has, for many years, been considered relatively straightforward. Recently, however, there is increasing awareness that within this single clinical phenotype exists considerable heterogeneity: disease onset spans the complete age range; genetic susceptibility is complex; rates of progression differ markedly, as does insulin secretory capacity; and complication rates, glycemic control, and therapeutic intervention efficacy vary widely. Mechanistic and immunopathological studies typically show considerable patchiness across subjects, undermining conclusions regarding disease pathways. Without better understanding, type 1 diabetes heterogeneity represents a major barrier both to deciphering pathogenesis and to the translational effort of designing, conducting, and interpreting clinical trials of disease-modifying agents. This realization comes during a period of unprecedented change in clinical medicine, with increasing emphasis on greater individualization and precision. For complex disorders such as type 1 diabetes, the option of maintaining the "single disease" approach appears untenable, as does the notion of individualizing each single patient's care, obliging us to conceptualize type 1 diabetes less in terms of phenotypes (observable characteristics) and more in terms of disease endotypes (underlying biological mechanisms). Here, we provide our view on an approach to dissect heterogeneity in type 1 diabetes. Using lessons from other diseases and the data gathered to date, we aim to delineate a roadmap through which the field can incorporate the endotype concept into laboratory and clinical practice. We predict that such an effort will accelerate the implementation of precision medicine and has the potential for impact on our approach to translational research, trial design, and clinical management.
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Affiliation(s)
- Manuela Battaglia
- San Raffaele Diabetes Research Institute, IRCCS San Raffaele Hospital, Milan, Italy
| | | | - Mark S Anderson
- Diabetes Center, University of California, San Francisco, San Francisco, CA
| | - Mark A Atkinson
- Department of Pathology, Immunology, and Laboratory Medicine, University of Florida, Gainesville, FL
| | - Dorothy Becker
- Division of Endocrinology and Diabetes, UPMC Children's Hospital of Pittsburgh, Pittsburgh, PA
| | - Polly J Bingley
- Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, U.K
| | - Emanuele Bosi
- San Raffaele Diabetes Research Institute, IRCCS San Raffaele Hospital, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy, and Department of Internal Medicine, IRCCS San Raffaele Hospital, Milan, Italy
| | - Todd M Brusko
- Department of Pathology, Immunology, and Laboratory Medicine, University of Florida, Gainesville, FL
| | - Linda A DiMeglio
- Division of Pediatric Endocrinology and Diabetology and Wells Center for Pediatric Research, Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN
| | - Carmella Evans-Molina
- Herman B Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN
| | - Stephen E Gitelman
- Division of Pediatric Endocrinology and Diabetes, University of California, San Francisco, San Francisco, CA
| | | | - Peter A Gottlieb
- Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Aurora, CO
| | - Kevan C Herold
- Department of Immunobiology, Yale University, New Haven, CT
| | - Martin J Hessner
- Department of Pediatrics, Medical College of Wisconsin, Milwaukee, WI
| | - Mikael Knip
- Children's Hospital, University of Helsinki and Helsinki University Hospital, Clinical and Molecular Metabolism Research Program, University of Helsinki, Helsinki, Finland
| | - Laura Jacobsen
- Department of Pediatrics, University of Florida, Gainesville, FL
| | - Jeffrey P Krischer
- Health Informatics Institute, Morsani College of Medicine, University of South Florida, Tampa, FL
| | - S Alice Long
- Diabetes Program, Benaroya Research Institute, Seattle, WA
| | - Markus Lundgren
- Department of Clinical Sciences, Clinical Research Centre, Faculty of Medicine, Lund University, and Skåne University Hospital, Malmö, Sweden
| | - Eoin F McKinney
- Department of Medicine, University of Cambridge School of Clinical Medicine, Addenbrooke's Hospital, Cambridge, U.K
| | - Noel G Morgan
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, U.K.,University of Exeter Medical School and Royal Devon and Exeter Hospital, Exeter, U.K
| | - Richard A Oram
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Royal Devon and Exeter Hospital, Exeter, U.K.,NIHR Exeter Clinical Research Facility, University of Exeter Medical School, Exeter, U.K.,Academic Renal Unit, Royal Devon and Exeter NHS Foundation Trust, Exeter, U.K
| | - Tomi Pastinen
- Center for Pediatric Genomic Medicine, Children's Mercy Kansas City, Kansas City, MO
| | - Michael C Peters
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, and Cardiovascular Research Institute, University of California, San Francisco, San Francisco, CA
| | - Alessandra Petrelli
- San Raffaele Diabetes Research Institute, IRCCS San Raffaele Hospital, Milan, Italy
| | - Xiaoning Qian
- Department of Electrical and Computer Engineering, TEES-AgriLife Center for Bioinformatics and Genomic Systems Engineering, Texas A&M University, College Station, TX
| | - Maria J Redondo
- Baylor College of Medicine, Texas Children's Hospital, Houston, TX
| | - Bart O Roep
- Department of Diabetes Immunology, Diabetes & Metabolism Research Institute, Beckman Research Institute, National Medical Center, City of Hope, Duarte, CA.,Department of Immunohaematology and Blood Transfusion, Leiden University Medical Center, Leiden, the Netherlands
| | - Desmond Schatz
- Department of Pediatrics, University of Florida, Gainesville, FL
| | | | - Mark Peakman
- Peter Gorer Department of Immunobiology, Faculty of Life Sciences and Medicine, King's College London, London, U.K. .,King's Health Partners Institute of Diabetes, Obesity and Endocrinology, London, U.K
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36
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Abstract
PURPOSE OF REVIEW To provide an updated summary of discoveries made to date resulting from genome-wide association study (GWAS) and sequencing studies, and to discuss the latest loci added to the growing repertoire of genetic signals predisposing to type 1 diabetes (T1D). RECENT FINDINGS Genetic studies have identified over 60 loci associated with T1D susceptibility. GWAS alone does not specifically inform on underlying mechanisms, but in combination with other sequencing and omics-data, advances are being made in our understanding of T1D genetic etiology and pathogenesis. Current knowledge indicates that genetic variation operating in both pancreatic β cells and in immune cells is central in mediating T1D risk. One of the main challenges is to determine how these recently discovered GWAS-implicated variants affect the expression and function of gene products. Once we understand the mechanism of action for disease-causing variants, we will be well placed to apply targeted genomic approaches to impede the premature activation of the immune system in an effort to ultimately prevent the onset of T1D.
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Affiliation(s)
- Marina Bakay
- The Center for Applied Genomics, Division of Human Genetics, The Children's Hospital of Philadelphia, 3615 Civic Center Boulevard, Abramson Research Center, Suite 1216B, Philadelphia, PA, 19104-4318, USA
| | - Rahul Pandey
- The Center for Applied Genomics, Division of Human Genetics, The Children's Hospital of Philadelphia, 3615 Civic Center Boulevard, Abramson Research Center, Suite 1216B, Philadelphia, PA, 19104-4318, USA
| | - Struan F A Grant
- The Center for Applied Genomics, Division of Human Genetics, The Children's Hospital of Philadelphia, 3615 Civic Center Boulevard, Abramson Research Center, Suite 1216B, Philadelphia, PA, 19104-4318, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Hakon Hakonarson
- The Center for Applied Genomics, Division of Human Genetics, The Children's Hospital of Philadelphia, 3615 Civic Center Boulevard, Abramson Research Center, Suite 1216B, Philadelphia, PA, 19104-4318, USA.
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
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37
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Grant SFA. The TCF7L2 Locus: A Genetic Window Into the Pathogenesis of Type 1 and Type 2 Diabetes. Diabetes Care 2019; 42:1624-1629. [PMID: 31409726 PMCID: PMC6702598 DOI: 10.2337/dci19-0001] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2019] [Accepted: 06/12/2019] [Indexed: 02/03/2023]
Abstract
Over the past ∼15 years there has been great progress in our understanding of the genetics of both type 1 diabetes and type 2 diabetes. This has been driven principally by genome-wide association studies (GWAS) in increasingly larger sample sizes, where many distinct loci have now been reported for both traits. One of the loci that dominates these studies is the TCF7L2 locus for type 2 diabetes. This genetic signal has been leveraged to explore multiple aspects of disease risk, including developments in genetic risk scores, genetic commonalities with cancer, and for gaining insights into diabetes-related molecular pathways. Furthermore, the TCF7L2 locus has aided in providing insights into the genetics of both latent autoimmune diabetes in adults and various presentations of type 1 diabetes. This review outlines the knowledge gained to date and highlights how work with this locus leads the way in guiding how many other genetic loci could be similarly used to gain insights into the pathogenesis of diabetes.
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Affiliation(s)
- Struan F A Grant
- Divisions of Human Genetics and Endocrinology, Children's Hospital of Philadelphia, Philadelphia, PA
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
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38
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Redondo MJ, Evans-Molina C, Steck AK, Atkinson MA, Sosenko J. The Influence of Type 2 Diabetes-Associated Factors on Type 1 Diabetes. Diabetes Care 2019; 42:1357-1364. [PMID: 31167894 PMCID: PMC6647039 DOI: 10.2337/dc19-0102] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2019] [Accepted: 04/27/2019] [Indexed: 02/03/2023]
Abstract
Current efforts to prevent progression from islet autoimmunity to type 1 diabetes largely focus on immunomodulatory approaches. However, emerging data suggest that the development of diabetes in islet autoantibody-positive individuals may also involve factors such as obesity and genetic variants associated with type 2 diabetes, and the influence of these factors increases with age at diagnosis. Although these factors have been linked with metabolic outcomes, particularly through their impact on β-cell function and insulin sensitivity, growing evidence suggests that they might also interact with the immune system to amplify the autoimmune response. The presence of factors shared by both forms of diabetes contributes to disease heterogeneity and thus has important implications. Characteristics that are typically considered to be nonimmune should be incorporated into predictive algorithms that seek to identify at-risk individuals and into the designs of trials for disease prevention. The heterogeneity of diabetes also poses a challenge in diagnostic classification. Finally, after clinically diagnosing type 1 diabetes, addressing nonimmune elements may help to prevent further deterioration of β-cell function and thus improve clinical outcomes. This Perspectives in Care article highlights the role of type 2 diabetes-associated genetic factors (e.g., gene variants at transcription factor 7-like 2 [TCF7L2]) and obesity (via insulin resistance, inflammation, β-cell stress, or all three) in the pathogenesis of type 1 diabetes and their impacts on age at diagnosis. Recognizing that type 1 diabetes might result from the sum of effects from islet autoimmunity and type 2 diabetes-associated factors, their interactions, or both affects disease prediction, prevention, diagnosis, and treatment.
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Affiliation(s)
- Maria J Redondo
- Baylor College of Medicine, Texas Children's Hospital, Houston, TX
| | - Carmella Evans-Molina
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN.,Department of Medicine, Indiana University School of Medicine, Indianapolis, IN.,Herman B Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN.,Richard L. Roudebush VA Medical Center, Indianapolis, IN
| | - Andrea K Steck
- Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Aurora, CO
| | - Mark A Atkinson
- Departments of Pathology and Pediatrics, University of Florida Diabetes Institute, Gainesville, FL
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39
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Abstract
PURPOSE OF REVIEW The genetic risk for type 1 diabetes has been studied for over half a century, with the strong genetic associations of type 1 diabetes forming critical evidence for the role of the immune system in pathogenesis. In this review, we discuss some of the original research leading to recent developments in type 1 diabetes genetics. RECENT FINDINGS We examine the translation of polygenic scores for type 1 diabetes into tools for prediction and diagnosis of type 1 diabetes, in particular, when used in combination with other biomarkers and clinical features, such as age and islet-specific autoantibodies. Furthermore, we review the description of age associations with type 1 diabetes genetic risk, and the investigation of loci linked to type 2 diabetes in progression of type 1 diabetes. Finally, we consider current limitations, including the scarcity of data from racial and ethnic minorities, and future directions. SUMMARY The development of polygenic risk scores has allowed the integration of type 1 diabetes genetics into diagnosis and prediction. Emerging information on the role of specific genes in subgroups of individuals with the disease, for example, early-onset, mild autoimmunity, and so forth, is facilitating our understanding of the heterogeneity of type 1 diabetes, with the ultimate goal of using genetic information in research and clinical practice.
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Affiliation(s)
- Richard A Oram
- RILD Level 3, Institute of Biomedical and Clinical Science, University of Exeter Medical School, Royal Devon and Exeter Hospital
- NIHR Exeter Clinical Research Facility, University of Exeter Medical School
- The Academic Renal Unit, Royal Devon and Exeter NHS Foundation Trust, Exeter, UK
| | - Maria J Redondo
- Pediatric Diabetes and Endocrinology, Texas Children's Hospital, Baylor College of Medicine, Houston, Texas, USA
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40
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Hughes JW, Bao YK, Salam M, Joshi P, Kilpatrick CR, Juneja K, Nieves D, Bouhairie V, Jordan OJ, Blustein EC, Tobin GS, McGill JB. Late-Onset T1DM and Older Age Predict Risk of Additional Autoimmune Disease. Diabetes Care 2019; 42:32-38. [PMID: 30361208 PMCID: PMC6300704 DOI: 10.2337/dc18-1157] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/26/2018] [Accepted: 10/02/2018] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Type 1 diabetes (T1DM) is associated with other autoimmune diseases (AIDs), which may have serious health consequences. The epidemiology of AIDs in T1DM is not well defined in adults with T1DM. In this cross-sectional cohort study, we sought to characterize the incident ages and prevalence of AIDs in adults with T1DM across a wide age spectrum. RESEARCH DESIGN AND METHODS A total of 1,212 adults seen at the Washington University Diabetes Center from 2011 to 2018 provided informed consent for the collection of their age, sex, race, and disease onset data. We performed paired association analyses based on age at onset of T1DM. Multivariate logistic regression was used to evaluate the independent effects of sex, race, T1DM age of onset, and T1DM duration on the prevalence of an additional AID. RESULTS Mean ± SD age of T1DM onset was 21.2 ± 14.4 years. AID incidence and prevalence increased with age. Female sex strongly predicted AID risk. The most prevalent T1DM-associated AIDs were thyroid disease, collagen vascular diseases, and pernicious anemia. T1DM age of onset and T1DM duration predicted AID risk. Patients with late-onset T1DM after 30 years of age had higher risks of developing additional AIDs compared with patients with younger T1DM onset. CONCLUSIONS The prevalence of AIDs in patients with T1DM increases with age and female sex. Later onset of T1DM is an independent and significant risk factor for developing additional AIDs. Individuals who are diagnosed with T1DM at older ages, particularly women, should be monitored for other autoimmune conditions.
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Affiliation(s)
- Jing W Hughes
- Division of Endocrinology, Metabolism and Lipid Research, Washington University School of Medicine in St. Louis, St. Louis, MO
| | - Yicheng K Bao
- Division of Endocrinology, Metabolism and Lipid Research, Washington University School of Medicine in St. Louis, St. Louis, MO.,University of Missouri-Kansas City School of Medicine, Kansas City, MO
| | - Maamoun Salam
- Division of Endocrinology, Metabolism and Lipid Research, Washington University School of Medicine in St. Louis, St. Louis, MO
| | - Prajesh Joshi
- Division of Endocrinology, Metabolism and Lipid Research, Washington University School of Medicine in St. Louis, St. Louis, MO.,Mercy Hospital Northwest Arkansas and University of Arkansas for Medical Sciences Northwest Regional Campus, Fayetteville, AR
| | - C Rachel Kilpatrick
- Division of Endocrinology, Metabolism and Lipid Research, Washington University School of Medicine in St. Louis, St. Louis, MO.,Washington Regional Medical Center, Fayetteville, AR
| | - Kavita Juneja
- Division of Endocrinology, Metabolism and Lipid Research, Washington University School of Medicine in St. Louis, St. Louis, MO.,Gilead Sciences, Foster City, CA
| | - David Nieves
- Division of Endocrinology, Metabolism and Lipid Research, Washington University School of Medicine in St. Louis, St. Louis, MO.,Northwell Health Lenox Hill Hospital, New York, NY
| | - Victoria Bouhairie
- Division of Endocrinology, Metabolism and Lipid Research, Washington University School of Medicine in St. Louis, St. Louis, MO.,Novant Health, Charlotte, NC
| | - Olivia J Jordan
- Division of Endocrinology, Metabolism and Lipid Research, Washington University School of Medicine in St. Louis, St. Louis, MO.,Pritzker School of Medicine, The University of Chicago, Chicago, IL
| | - Erica C Blustein
- Division of Endocrinology, Metabolism and Lipid Research, Washington University School of Medicine in St. Louis, St. Louis, MO.,John Peter Smith Hospital, Fort Worth, TX
| | - Garry S Tobin
- Division of Endocrinology, Metabolism and Lipid Research, Washington University School of Medicine in St. Louis, St. Louis, MO
| | - Janet B McGill
- Division of Endocrinology, Metabolism and Lipid Research, Washington University School of Medicine in St. Louis, St. Louis, MO
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41
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Abstract
The American Diabetes Association (ADA) "Standards of Medical Care in Diabetes" includes ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations, please refer to the Standards of Care Introduction Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.
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42
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Redondo MJ, Steck AK, Sosenko J, Anderson M, Antinozzi P, Michels A, Wentworth JM, Atkinson MA, Pugliese A, Geyer S. Transcription Factor 7-Like 2 ( TCF7L2) Gene Polymorphism and Progression From Single to Multiple Autoantibody Positivity in Individuals at Risk for Type 1 Diabetes. Diabetes Care 2018; 41:2480-2486. [PMID: 30275285 PMCID: PMC6245213 DOI: 10.2337/dc18-0861] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/19/2018] [Accepted: 08/10/2018] [Indexed: 02/03/2023]
Abstract
OBJECTIVE The type 2 diabetes-associated alleles at the TCF7L2 locus mark a type 1 diabetes phenotype characterized by single islet autoantibody positivity as well as lower glucose and higher C-peptide measures. Here, we studied whether the TCF7L2 locus influences progression of islet autoimmunity, from single to multiple (≥2) autoantibody positivity, in relatives of patients with type 1 diabetes. RESEARCH DESIGN AND METHODS We evaluated 244 participants in the Type 1 Diabetes TrialNet Pathway to Prevention study with confirmed single autoantibody positivity at screening and Immunochip single nucleotide polymorphism data (47.5% male; median age 12.8 years, range 1.2-45.9; 90.2% white). We analyzed risk allele frequency at TCF7L2 rs4506565 (in linkage disequilibrium with rs7903146). Altogether, 62.6% participants carried ≥1 risk allele. Univariate and multivariable Cox proportional hazards models and Kaplan-Meier statistical methods were used. RESULTS During follow-up (median 5.2 years, range 0.2-12.6), 62% of the single autoantibody-positive participants developed multiple autoantibody positivity. In the overall cohort, the TCF7L2 locus did not significantly predict progression to multiple autoantibody positivity. However, among single GAD65 autoantibody-positive participants (n = 158), those who carried ≥1 risk allele had a lower rate of progression to multiple autoantibody positivity (hazard ratio [HR] 0.65, P = 0.033) than those who did not, after adjustment for HLA risk haplotypes and age. Among subjects who were either IA-2 or insulin autoantibody positive only, carrying ≥1 TCF7L2 risk allele was not a significant factor overall, but in overweight or obese participants, it increased the risk of progression to multiple autoantibody positivity (HR 3.02, P = 0.016) even with adjustment for age. CONCLUSIONS The type 2 diabetes-associated TCF7L2 locus influences progression of islet autoimmunity, with differential effects by autoantibody specificity and interaction by obesity/overweight.
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Affiliation(s)
- Maria J Redondo
- Baylor College of Medicine, Texas Children's Hospital, Houston, TX
| | - Andrea K Steck
- Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Aurora, CO
| | | | - Mark Anderson
- University of California San Francisco, San Francisco, CA
| | | | - Aaron Michels
- Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Aurora, CO
| | - John M Wentworth
- Walter and Eliza Hall Institute and Royal Melbourne Hospital, Parkville, Australia
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Cousminer DL, Ahlqvist E, Mishra R, Andersen MK, Chesi A, Hawa MI, Davis A, Hodge KM, Bradfield JP, Zhou K, Guy VC, Åkerlund M, Wod M, Fritsche LG, Vestergaard H, Snyder J, Højlund K, Linneberg A, Käräjämäki A, Brandslund I, Kim CE, Witte D, Sørgjerd EP, Brillon DJ, Pedersen O, Beck-Nielsen H, Grarup N, Pratley RE, Rickels MR, Vella A, Ovalle F, Melander O, Harris RI, Varvel S, Grill VE, Hakonarson H, Froguel P, Lonsdale JT, Mauricio D, Schloot NC, Khunti K, Greenbaum CJ, Åsvold BO, Yderstræde KB, Pearson ER, Schwartz S, Voight BF, Hansen T, Tuomi T, Boehm BO, Groop L, Leslie RD, Grant SF, McCormack SE, Mitchell JA, Kelly A, Kalkwarf HJ, Lappe JM, Shepherd JA, Oberfield SE, Gilsanz V, Zemel BS. First Genome-Wide Association Study of Latent Autoimmune Diabetes in Adults Reveals Novel Insights Linking Immune and Metabolic Diabetes. Diabetes Care 2018; 41:2396-2403. [PMID: 30254083 PMCID: PMC6196829 DOI: 10.2337/dc18-1032] [Citation(s) in RCA: 82] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2018] [Accepted: 08/26/2018] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Latent autoimmune diabetes in adults (LADA) shares clinical features with both type 1 and type 2 diabetes; however, there is ongoing debate regarding the precise definition of LADA. Understanding its genetic basis is one potential strategy to gain insight into appropriate classification of this diabetes subtype. RESEARCH DESIGN AND METHODS We performed the first genome-wide association study of LADA in case subjects of European ancestry versus population control subjects (n = 2,634 vs. 5,947) and compared against both case subjects with type 1 diabetes (n = 2,454 vs. 968) and type 2 diabetes (n = 2,779 vs. 10,396). RESULTS The leading genetic signals were principally shared with type 1 diabetes, although we observed positive genetic correlations genome-wide with both type 1 and type 2 diabetes. Additionally, we observed a novel independent signal at the known type 1 diabetes locus harboring PFKFB3, encoding a regulator of glycolysis and insulin signaling in type 2 diabetes and inflammation and autophagy in autoimmune disease, as well as an attenuation of key type 1-associated HLA haplotype frequencies in LADA, suggesting that these are factors that distinguish childhood-onset type 1 diabetes from adult autoimmune diabetes. CONCLUSIONS Our results support the need for further investigations of the genetic factors that distinguish forms of autoimmune diabetes as well as more precise classification strategies.
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Affiliation(s)
- Diana L. Cousminer
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Emma Ahlqvist
- Department of Clinical Sciences Malmö, Lund University Diabetes Centre, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Rajashree Mishra
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA
- Graduate Group in Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Mette K. Andersen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Alessandra Chesi
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA
| | - Mohammad I. Hawa
- Department of Immunobiology, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, U.K
| | - Asa Davis
- Benaroya Research Institute, Seattle, WA
| | - Kenyaita M. Hodge
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA
| | | | - Kaixin Zhou
- Division of Molecular and Clinical Medicine, Medical Research Institute, University of Dundee, Dundee, U.K
| | - Vanessa C. Guy
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA
| | - Mikael Åkerlund
- Department of Clinical Sciences Malmö, Lund University Diabetes Centre, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Mette Wod
- Odense University Hospital, Odense, Denmark
| | - Lars G. Fritsche
- Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, Trondheim, Norway
| | - Henrik Vestergaard
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - James Snyder
- Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA
| | | | - Allan Linneberg
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Annemari Käräjämäki
- Vaasa Health Care Center and Department of Primary Health Care, Vaasa Central Hospital, Vaasa, Finland
| | | | - Cecilia E. Kim
- Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA
| | - Daniel Witte
- Odense University Hospital, Odense, Denmark
- Department of Public Health, Aarhus University, Aarhus, Denmark
| | - Elin Pettersen Sørgjerd
- Department of Public Health and Nursing, HUNT Research Centre, Norwegian University of Science and Technology, Levanger, Norway
| | | | - Oluf Pedersen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | - Niels Grarup
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Richard E. Pratley
- Florida Hospital Translational Research Institute for Metabolism and Diabetes, Orlando, FL
| | - Michael R. Rickels
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | | | | | - Olle Melander
- Department of Clinical Sciences Malmö, Lund University Diabetes Centre, Lund University, Skåne University Hospital, Malmö, Sweden
| | | | | | - Valdemar E.R. Grill
- Department of Endocrinology, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
- Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
| | - Hakon Hakonarson
- Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Philippe Froguel
- CNRS 8199, Université Lille Nord de France, Pasteur Institute, Lille, France
- Department of Genomics of Common Disease, Imperial College London, London, U.K
| | | | - Didac Mauricio
- Hospital Universitari Germans Trias i Pujol, Barcelona, Spain
| | | | - Kamlesh Khunti
- Diabetes Research Centre, University of Leicester, Leicester, U.K
| | | | - Bjørn Olav Åsvold
- Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Endocrinology, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | | | - Ewan R. Pearson
- Division of Molecular and Clinical Medicine, Medical Research Institute, University of Dundee, Dundee, U.K
| | | | - Benjamin F. Voight
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
- Department of Systems, Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
- Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Torben Hansen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Tiinamaija Tuomi
- Department of Endocrinology, Helsinki University Hospital, Helsinki, Finland
- Research Programs Unit, Diabetes and Obesity, Folkhälsan Research Centre, University of Helsinki, Helsinki, Finland
- Finnish Institute for Molecular Medicine, Helsinki, Finland
| | - Bernhard O. Boehm
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore and Imperial College, London, U.K
- Department of Internal Medicine I, Ulm University Medical Centre, Ulm, Germany
| | - Leif Groop
- Department of Clinical Sciences Malmö, Lund University Diabetes Centre, Lund University, Skåne University Hospital, Malmö, Sweden
- Finnish Institute for Molecular Medicine, Helsinki, Finland
| | - R. David Leslie
- Department of Immunobiology, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, U.K
| | - Struan F.A. Grant
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
- Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
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Corbin KD, Driscoll KA, Pratley RE, Smith SR, Maahs DM, Mayer-Davis EJ. Obesity in Type 1 Diabetes: Pathophysiology, Clinical Impact, and Mechanisms. Endocr Rev 2018; 39:629-663. [PMID: 30060120 DOI: 10.1210/er.2017-00191] [Citation(s) in RCA: 120] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2017] [Accepted: 06/21/2018] [Indexed: 02/07/2023]
Abstract
There has been an alarming increase in the prevalence of obesity in people with type 1 diabetes in recent years. Although obesity has long been recognized as a major risk factor for the development of type 2 diabetes and a catalyst for complications, much less is known about the role of obesity in the initiation and pathogenesis of type 1 diabetes. Emerging evidence suggests that obesity contributes to insulin resistance, dyslipidemia, and cardiometabolic complications in type 1 diabetes. Unique therapeutic strategies may be required to address these comorbidities within the context of intensive insulin therapy, which promotes weight gain. There is an urgent need for clinical guidelines for the prevention and management of obesity in type 1 diabetes. The development of these recommendations will require a transdisciplinary research strategy addressing metabolism, molecular mechanisms, lifestyle, neuropsychology, and novel therapeutics. In this review, the prevalence, clinical impact, energy balance physiology, and potential mechanisms of obesity in type 1 diabetes are described, with a special focus on the substantial gaps in knowledge in this field. Our goal is to provide a framework for the evidence base needed to develop type 1 diabetes-specific weight management recommendations that account for the competing outcomes of glycemic control and weight management.
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Affiliation(s)
- Karen D Corbin
- Translational Research Institute for Metabolism and Diabetes, Florida Hospital, Orlando, Florida
| | - Kimberly A Driscoll
- Department of Pediatrics, School of Medicine, University of Colorado Denver, Aurora, Colorado.,Barbara Davis Center for Diabetes, Aurora, Colorado
| | - Richard E Pratley
- Translational Research Institute for Metabolism and Diabetes, Florida Hospital, Orlando, Florida
| | - Steven R Smith
- Translational Research Institute for Metabolism and Diabetes, Florida Hospital, Orlando, Florida
| | - David M Maahs
- Division of Pediatric Endocrinology, Department of Pediatrics, Stanford University, Stanford, California
| | - Elizabeth J Mayer-Davis
- Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.,Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
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Ionescu-Tirgoviste C, Gagniuc P, Guja C. A COMMENTARY ON CLASSIFICATION OF DIABETES: LATENT AUTOIMMUNE DIABETES IN ADULTS (LADA) OR INTERMEDIARY DIABETES MELLITUS (IDM)? ACTA ENDOCRINOLOGICA (BUCHAREST, ROMANIA : 2005) 2018; 14:520-524. [PMID: 31149306 PMCID: PMC6516414 DOI: 10.4183/aeb.2018.520] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Diabetes Mellitus is a huge syndrome which can be detected from the first day of life until the last year of life of a centenarian. In the current classification of diabetes among the so-called "idiopathic phenotypes", apart Type 1 Diabetes (T1D) and Type 2 Diabetes (T2D) has been included provisionally term "Latent Autoimmune Diabetes in Adults" (LADA). This has unclear characterization regarding the age at onset, the presence of anti-β-cell antibodies and the level of insulin secretory function, in conformity with C-peptide levels. According to several recent publications, there are no specific biochemical or genetic markers for Latent Autoimmune Diabetes in Adults (LADA), but only a gradual transition from T1D to T2D. In addition, the word "latent" in the construction of "LADA" term is inaccurate because in this phenotype nothing is latent: both the autoimmunity and diabetes are present and are even parts of the diagnosis. So that, the best term should be what in reality this sub-phenotype is: an Intermediary Diabetes Mellitus (IDM). Some recent genetic data strongly support this designation.
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Affiliation(s)
| | - P. Gagniuc
- “Carol Davila” University of Medicine and Pharmacy, Bucharest, Romania
| | - C. Guja
- “Carol Davila” University of Medicine and Pharmacy, Bucharest, Romania
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46
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Leete P, Mallone R, Richardson SJ, Sosenko JM, Redondo MJ, Evans-Molina C. The Effect of Age on the Progression and Severity of Type 1 Diabetes: Potential Effects on Disease Mechanisms. Curr Diab Rep 2018; 18:115. [PMID: 30259209 PMCID: PMC10043737 DOI: 10.1007/s11892-018-1083-4] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
PURPOSE OF REVIEW To explore the impact of age on type 1 diabetes (T1D) pathogenesis. RECENT FINDINGS Children progress more rapidly from autoantibody positivity to T1D and have lower C-peptide levels compared to adults. In histological analysis of post-mortem pancreata, younger age of diagnosis is associated with reduced numbers of insulin containing islets and a hyper-immune CD20hi infiltrate. Moreover compared to adults, children exhibit decreased immune regulatory function and increased engagement and trafficking of autoreactive CD8+ T cells, and age-related differences in β cell vulnerability may also contribute to the more aggressive immune phenotype observed in children. To account for some of these differences, HLA and non-HLA genetic loci that influence multiple disease characteristics, including age of onset, are being increasingly characterized. The exception of T1D as an autoimmune disease more prevalent in children than adults results from a combination of immune, metabolic, and genetic factors. Age-related differences in T1D pathology have important implications for better tailoring of immunotherapies.
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Affiliation(s)
- Pia Leete
- Islet Biology Exeter (IBEx), Institute of Biomedical and Clinical Sciences, University of Exeter Medical School, Exeter, UK
| | - Roberto Mallone
- INSERM U1016, CNRS UMR8104, Cochin Institute, Sorbonne Paris Cité; Assistance Publique Hôpitaux de Paris, Service de Diabétologie, Cochin Hospital, INSERM and Assistance Publique Hôpitaux de Paris, Paris, France
| | - Sarah J Richardson
- Islet Biology Exeter (IBEx), Institute of Biomedical and Clinical Sciences, University of Exeter Medical School, Exeter, UK
| | - Jay M Sosenko
- Department of Medicine and the Diabetes Research Institute, Leonard Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Maria J Redondo
- Department of Pediatrics, Baylor College of Medicine and the Texas Children's Hospital, Houston, TX, USA
| | - Carmella Evans-Molina
- Departments of Medicine and Pediatrics and the Herman B Wells Center for Pediatric Research, Indiana University School of Medicine and the Roudebush VA Medical Center, 635 Barnhill Drive, MS 2031A, Indianapolis, IN, 46202, USA.
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47
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Tosur M, Geyer SM, Rodriguez H, Libman I, Baidal DA, Redondo MJ. Ethnic differences in progression of islet autoimmunity and type 1 diabetes in relatives at risk. Diabetologia 2018; 61:2043-2053. [PMID: 29931415 PMCID: PMC6611550 DOI: 10.1007/s00125-018-4660-9] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/16/2018] [Accepted: 05/17/2018] [Indexed: 01/13/2023]
Abstract
AIMS/HYPOTHESIS We hypothesised that progression of islet autoimmunity and type 1 diabetes mellitus differs among races/ethnicities in at-risk individuals. METHODS In this study, we analysed the data from the Type 1 Diabetes TrialNet Pathway to Prevention Study. We studied 4873 non-diabetic, autoantibody-positive relatives of individuals with type 1 diabetes followed prospectively (11% Hispanic, 80.9% non-Hispanic white [NHW], 2.9% non-Hispanic black [NHB] and 5.2% non-Hispanic other [NHO]). Primary outcomes were time from single autoantibody positivity confirmation to multiple autoantibody positivity, and time from multiple autoantibody positivity to type 1 diabetes mellitus diagnosis. RESULTS Conversion from single to multiple autoantibody positivity was less common in Hispanic individuals than in NHW individuals (HR 0.66 [95% CI 0.46, 0.96], p = 0.028) adjusting for autoantibody type, age, sex, Diabetes Prevention Trial Type 1 Risk Score and HLA-DR3-DQ2/DR4-DQ8 genotype. In participants who screened positive for multiple autoantibodies (n = 2834), time to type 1 diabetes did not differ by race/ethnicity overall (p = 0.91). In children who were <12 years old when multiple autoantibody positivity was determined, being overweight/obese had differential effects by ethnicity: type 1 diabetes risk was increased by 36% in NHW children (HR 1.36 [95% CI 1.04, 1.77], p = 0.024) and was nearly quadrupled in Hispanic children (HR 3.8 [95% CI 1.6, 9.1], p = 0.0026). We did not observe this interaction in participants who were ≥12 years old at determination of autoantibody positivity, although this group size was limited. No significant differential risks were observed between individuals of NHB and NHW ethnicity. CONCLUSIONS/INTERPRETATION The risk and rate of progression of islet autoimmunity were lower in Hispanic compared with NHW at-risk individuals, while significant differences in the development of type 1 diabetes were limited to children <12 years old and were modified by BMI.
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Affiliation(s)
- Mustafa Tosur
- Section of Diabetes and Endocrinology, Department of Pediatrics, Texas Children's Hospital, Baylor College of Medicine, 6701 Fannin St, Suite 10.20, Houston, TX, 77030, USA.
| | - Susan M Geyer
- Health Informatics Institute, Department of Pediatrics, University of South Florida, Tampa, FL, USA
| | - Henry Rodriguez
- University of South Florida Diabetes Center, Department of Pediatrics, University of South Florida, Tampa, FL, USA
| | - Ingrid Libman
- Division of Pediatric Endocrinology, Department of Pediatrics, Children's Hospital of Pittsburgh of University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - David A Baidal
- Endocrinology, Diabetes and Metabolism, Department of Medicine, University of Miami, Miami, FL, USA
| | - Maria J Redondo
- Section of Diabetes and Endocrinology, Department of Pediatrics, Texas Children's Hospital, Baylor College of Medicine, 6701 Fannin St, Suite 10.20, Houston, TX, 77030, USA
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Redondo MJ, Geyer S, Steck AK, Sharp S, Wentworth JM, Weedon MN, Antinozzi P, Sosenko J, Atkinson M, Pugliese A, Oram RA, Antinozzi P, Atkinson M, Battaglia M, Becker D, Bingley P, Bosi E, Buckner J, Colman P, Gottlieb P, Herold K, Insel R, Kay T, Knip M, Marks J, Moran A, Palmer J, Peakman M, Philipson L, Pugliese A, Raskin P, Rodriguez H, Roep B, Russell W, Schatz D, Wherrett D, Wilson D, Winter W, Ziegler A, Benoist C, Blum J, Chase P, Clare-Salzler M, Clynes R, Eisenbarth G, Fathman C, Grave G, Hering B, Kaufman F, Leschek E, Mahon J, Nanto-Salonen K, Nepom G, Orban T, Parkman R, Pescovitz M, Peyman J, Roncarolo M, Simell O, Sherwin R, Siegelman M, Steck A, Thomas J, Trucco M, Wagner J, Greenbaum ,CJ, Bourcier K, Insel R, Krischer JP, Leschek E, Rafkin L, Spain L, Cowie C, Foulkes M, Krause-Steinrauf H, Lachin JM, Malozowski S, Peyman J, Ridge J, Savage P, Skyler JS, Zafonte SJ, Kenyon NS, Santiago I, Sosenko JM, Bundy B, Abbondondolo M, Adams T, Amado D, Asif I, Boonstra M, Bundy B, Burroughs C, Cuthbertson D, Deemer M, Eberhard C, Fiske S, Ford J, Garmeson J, Guillette H, Browning G, Coughenour T, Sulk M, Tsalikan E, Tansey M, Cabbage J, Dixit N, Pasha S, King M, Adcock K, Geyer S, Atterberry H, Fox L, Englert K, Mauras N, Permuy J, Sikes K, Berhe T, Guendling B, McLennan L, Paganessi L, Hays B, Murphy C, Draznin M, Kamboj M, Sheppard S, Lewis V, Coates L, Moore W, Babar G, Bedard J, Brenson-Hughes D, Henderson C, Cernich J, Clements M, Duprau R, Goodman S, Hester L, Huerta-Saenz L, Karmazin A, Letjen T, Raman S, Morin D, Henry M, Bestermann W, Morawski E, White J, Brockmyer A, Bays R, Campbell S, Stapleton A, Stone N, Donoho A, Everett H, Heyman K, Hensley H, Johnson M, Marshall C, Skirvin N, Taylor P, Williams R, Ray L, Wolverton C, Nickels D, Dothard C, Hsiao B, Speiser P, Pellizzari M, Bokor L, Izuora K, Abdelnour S, Cummings P, Paynor S, Leahy M, Riedl M, Shockley S, Karges C, Saad R, Briones T, Casella S, Herz C, Walsh K, Greening J, Hay F, Hunt S, Sikotra N, Simons L, Keaton N, Karounos D, Oremus R, Dye L, Myers L, Ballard D, Miers W, Sparks R, Thraikill K, Edwards K, Fowlkes J, Kinderman A, Kemp S, Morales A, Holland L, Johnson L, Paul P, Ghatak A, Phelen K, Leyland H, Henderson T, Brenner D, Law P, Oppenheimer E, Mamkin I, Moniz C, Clarson C, Lovell M, Peters A, Ruelas V, Borut D, Burt D, Jordan M, Leinbach A, Castilla S, Flores P, Ruiz M, Hanson L, Green-Blair J, Sheridan R, Wintergerst K, Pierce G, Omoruyi A, Foster M, Linton C, Kingery S, Lunsford A, Cervantes I, Parker T, Price P, Urben J, Doughty I, Haydock H, Parker V, Bergman P, Liu S, Duncum S, Rodda C, Thomas A, Ferry R, McCommon D, Cockroft J, Perelman A, Calendo R, Barrera C, Arce-Nunez E, Lloyd J, Martinez Y, De la Portilla M, Cardenas I, Garrido L, Villar M, Lorini R, Calandra E, D’Annuzio G, Perri K, Minuto N, Malloy J, Rebora C, Callegari R, Ali O, Kramer J, Auble B, Cabrera S, Donohoue P, Fiallo-Scharer R, Hessner M, Wolfgram P, Maddox K, Kansra A, Bettin N, McCuller R, Miller A, Accacha S, Corrigan J, Fiore E, Levine R, Mahoney T, Polychronakos C, Martin J, Gagne V, Starkman H, Fox M, Chin D, Melchionne F, Silverman L, Marshall I, Cerracchio L, Cruz J, Viswanathan A, Miller J, Wilson J, Chalew S, Valley S, Layburn S, Lala A, Clesi P, Genet M, Uwaifo G, Charron A, Allerton T, Milliot E, Cefalu W, Melendez-Ramirez L, Richards R, Alleyn C, Gustafson E, Lizanna M, Wahlen J, Aleiwe S, Hansen M, Wahlen H, Moore M, Levy C, Bonaccorso A, Rapaport R, Tomer Y, Chia D, Goldis M, Iazzetti L, Klein M, Levister C, Waldman L, Muller S, Wallach E, Regelmann M, Antal Z, Aranda M, Reynholds C, Leech N, Wake D, Owens C, Burns M, Wotherspoon J, Nguyen T, Murray A, Short K, Curry G, Kelsey S, Lawson J, Porter J, Stevens S, Thomson E, Winship S, Wynn L, O’Donnell R, Wiltshire E, Krebs J, Cresswell P, Faherty H, Ross C, Vinik A, Barlow P, Bourcier M, Nevoret M, Couper J, Oduah V, Beresford S, Thalagne N, Roper H, Gibbons J, Hill J, Balleaut S, Brennan C, Ellis-Gage J, Fear L, Gray T, Pilger J, Jones L, McNerney C, Pointer L, Price N, Few K, Tomlinson D, Denvir L, Drew J, Randell T, Mansell P, Roberts A, Bell S, Butler S, Hooton Y, Navarra H, Roper A, Babington G, Crate L, Cripps H, Ledlie A, Moulds C, Sadler K, Norton R, Petrova B, Silkstone O, Smith C, Ghai K, Murray M, Viswanathan V, Henegan M, Kawadry O, Olson J, Stavros T, Patterson L, Ahmad T, Flores B, Domek D, Domek S, Copeland K, George M, Less J, Davis T, Short M, Tamura R, Dwarakanathan A, O’Donnell P, Boerner B, Larson L, Phillips M, Rendell M, Larson K, Smith C, Zebrowski K, Kuechenmeister L, Wood K, Thevarayapillai M, Daniels M, Speer H, Forghani N, Quintana R, Reh C, Bhangoo A, Desrosiers P, Ireland L, Misla T, Xu P, Torres C, Wells S, Villar J, Yu M, Berry D, Cook D, Soder J, Powell A, Ng M, Morrison M, Young K, Haslam Z, Lawson M, Bradley B, Courtney J, Richardson C, Watson C, Keely E, DeCurtis D, Vaccarcello-Cruz M, Torres Z, Alies P, Sandberg K, Hsiang H, Joy B, 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Espinoza O, Frank E, Liu J, Perry J, Pyle R, Rigby A, Riley K, Soto A, Gitelman S, Adi S, Anderson M, Berhel A, Breen K, Fraser K, Gerard-Gonzalez A, Jossan P, Lustig R, Moassesfar S, Mugg A, Ng D, Prahalod P, Rangel-Lugo M, Sanda S, Tarkoff J, Torok C, Wesch R, Aslan I, Buchanan J, Cordier J, Hamilton C, Hawkins L, Ho T, Jain A, Ko K, Lee T, Phelps S, Rosenthal S, Sahakitrungruang T, Stehl L, Taylor L, Wertz M, Wong J, Philipson L, Briars R, Devine N, Littlejohn E, Grant T, Gottlieb P, Klingensmith G, Steck A, Alkanani A, Bautista K, Bedoy R, Blau A, Burke B, Cory L, Dang M, Fitzgerald-Miller L, Fouts A, Gage V, Garg S, Gesauldo P, Gutin R, Hayes C, Hoffman M, Ketchum K, Logsden-Sackett N, Maahs D, Messer L, Meyers L, Michels A, Peacock S, Rewers M, Rodriguez P, Sepulbeda F, Sippl R, Steck A, Taki I, Tran BK, Tran T, Wadwa RP, Zeitler P, Barker J, Barry S, Birks L, Bomsburger L, Bookert T, Briggs L, Burdick P, Cabrera R, Chase P, Cobry E, Conley A, Cook G, Daniels J, DiDomenico D, 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Trunnel S, Transue D, Surhigh J, Bezzaire D, Moltz K, Zacharski E, Henske J, Desai S, Frizelis K, Khan F, Sjoberg R, Allen K, Manning P, Hendry G, Taylor B, Jones S, Couch R, Danchak R, Lieberman D, Strader W, Bencomo M, Bailey T, Bedolla L, Roldan C, Moudiotis C, Vaidya B, Anning C, Bunce S, Estcourt S, Folland E, Gordon E, Harrill C, Ireland J, Piper J, Scaife L, Sutton K, Wilkins S, Costelloe M, Palmer J, Casas L, Miller C, Burgard M, Erickson C, Hallanger-Johnson J, Clark P, Taylor W, Galgani J, Banerjee S, Banda C, McEowen D, Kinman R, Lafferty A, Gillett S, Nolan C, Pathak M, Sondrol L, Hjelle T, Hafner S, Kotrba J, Hendrickson R, Cemeroglu A, Symington T, Daniel M, Appiagyei-Dankah Y, Postellon D, Racine M, Kleis L, Barnes K, Godwin S, McCullough H, Shaheen K, Buck G, Noel L, Warren M, Weber S, Parker S, Gillespie I, Nelson B, Frost C, Amrhein J, Moreland E, Hayes A, Peggram J, Aisenberg J, Riordan M, Zasa J, Cummings E, Scott K, Pinto T, Mokashi A, McAssey K, Helden E, Hammond P, Dinning L, Rahman S, Ray S, Dimicri C, Guppy S, Nielsen H, Vogel C, Ariza C, Morales L, Chang Y, Gabbay R, Ambrocio L, Manley L, Nemery R, Charlton W, Smith P, Kerr L, Steindel-Kopp B, Alamaguer M, Tabisola-Nuesca E, Pendersen A, Larson N, Cooper-Olviver H, Chan D, Fitz-Patrick D, Carreira T, Park Y, Ruhaak R, Liljenquist D. A Type 1 Diabetes Genetic Risk Score Predicts Progression of Islet Autoimmunity and Development of Type 1 Diabetes in Individuals at Risk. Diabetes Care 2018; 41:1887-1894. [PMID: 30002199 PMCID: PMC6105323 DOI: 10.2337/dc18-0087] [Citation(s) in RCA: 94] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/11/2018] [Accepted: 06/06/2018] [Indexed: 02/03/2023]
Abstract
OBJECTIVE We tested the ability of a type 1 diabetes (T1D) genetic risk score (GRS) to predict progression of islet autoimmunity and T1D in at-risk individuals. RESEARCH DESIGN AND METHODS We studied the 1,244 TrialNet Pathway to Prevention study participants (T1D patients' relatives without diabetes and with one or more positive autoantibodies) who were genotyped with Illumina ImmunoChip (median [range] age at initial autoantibody determination 11.1 years [1.2-51.8], 48% male, 80.5% non-Hispanic white, median follow-up 5.4 years). Of 291 participants with a single positive autoantibody at screening, 157 converted to multiple autoantibody positivity and 55 developed diabetes. Of 953 participants with multiple positive autoantibodies at screening, 419 developed diabetes. We calculated the T1D GRS from 30 T1D-associated single nucleotide polymorphisms. We used multivariable Cox regression models, time-dependent receiver operating characteristic curves, and area under the curve (AUC) measures to evaluate prognostic utility of T1D GRS, age, sex, Diabetes Prevention Trial-Type 1 (DPT-1) Risk Score, positive autoantibody number or type, HLA DR3/DR4-DQ8 status, and race/ethnicity. We used recursive partitioning analyses to identify cut points in continuous variables. RESULTS Higher T1D GRS significantly increased the rate of progression to T1D adjusting for DPT-1 Risk Score, age, number of positive autoantibodies, sex, and ethnicity (hazard ratio [HR] 1.29 for a 0.05 increase, 95% CI 1.06-1.6; P = 0.011). Progression to T1D was best predicted by a combined model with GRS, number of positive autoantibodies, DPT-1 Risk Score, and age (7-year time-integrated AUC = 0.79, 5-year AUC = 0.73). Higher GRS was significantly associated with increased progression rate from single to multiple positive autoantibodies after adjusting for age, autoantibody type, ethnicity, and sex (HR 2.27 for GRS >0.295, 95% CI 1.47-3.51; P = 0.0002). CONCLUSIONS The T1D GRS independently predicts progression to T1D and improves prediction along T1D stages in autoantibody-positive relatives.
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Affiliation(s)
- Maria J. Redondo
- Texas Children’s Hospital, Baylor College of Medicine, Houston, TX
| | | | - Andrea K. Steck
- Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Aurora, CO
| | - Seth Sharp
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, U.K
| | - John M. Wentworth
- Walter and Eliza Hall Institute of Medical Research and Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - Michael N. Weedon
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, U.K
| | | | | | | | | | - Richard A. Oram
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, U.K
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Mishra R, Hodge KM, Cousminer DL, Leslie RD, Grant SFA. A Global Perspective of Latent Autoimmune Diabetes in Adults. Trends Endocrinol Metab 2018; 29:638-650. [PMID: 30041834 DOI: 10.1016/j.tem.2018.07.001] [Citation(s) in RCA: 52] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/22/2018] [Revised: 06/30/2018] [Accepted: 07/02/2018] [Indexed: 12/21/2022]
Abstract
Latent autoimmune diabetes in adults (LADA) is characterized by the presence of islet autoantibodies and initial insulin independence, which can lead to misdiagnosis of type 2 diabetes (T2D). As such, understanding the genetic etiology of LADA could aid in more accurate diagnosis. However, there is ongoing debate regarding the exact definition of LADA, so understanding its impact in different populations when contrasted with type 1 diabetes (T1D) and T2D is one potential strategy to gain insight into its etiology. Unfortunately, the lack of consistent and thorough autoantibody screening around the world has hampered well-powered genetic studies of LADA. This review highlights recent genetic and epidemiological studies of LADA in diverse populations as well as the importance of autoantibody screening in facilitating future research.
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Affiliation(s)
- Rajashree Mishra
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Graduate Group in Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; These authors contributed equally
| | - Kenyaita M Hodge
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; These authors contributed equally
| | - Diana L Cousminer
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Richard D Leslie
- Department of Immunobiology, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, E1 2AD, UK
| | - Struan F A Grant
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA; Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA; Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA; Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
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50
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Evans-Molina C, Sims EK, DiMeglio LA, Ismail HM, Steck AK, Palmer JP, Krischer JP, Geyer S, Xu P, Sosenko JM. β Cell dysfunction exists more than 5 years before type 1 diabetes diagnosis. JCI Insight 2018; 3:120877. [PMID: 30089716 DOI: 10.1172/jci.insight.120877] [Citation(s) in RCA: 60] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2018] [Accepted: 06/21/2018] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND The duration and patterns of β cell dysfunction during type 1 diabetes (T1D) development have not been fully defined. METHODS Metabolic measures derived from oral glucose tolerance tests (OGTTs) were compared between autoantibody-positive (aAb+) individuals followed in the TrialNet Pathway to Prevention study who developed diabetes after 5 or more years or less than 5 years of longitudinal follow-up (Progressors≥5, n = 75; Progressors<5, n = 474) and 144 aAb-negative (aAb-) relatives. RESULTS Mean age at study entry was 15.0 ± 12.6 years for Progressors≥5; 12.0 ± 9.1 for Progressors<5; and 16.3 ± 10.4 for aAb- relatives. At baseline, Progressors≥5 already exhibited significantly lower fasting C-peptide (P < 0.01), C-peptide AUC (P < 0.001), and early C-peptide responses (30- to 0-minute C-peptide; P < 0.001) compared with aAb- relatives, while 2-hour glucose (P = 0.03), glucose AUC (<0.001), and Index60 (<0.001) were all higher. Despite significant baseline impairment, metabolic measures in Progressors≥5 were relatively stable until 2 years prior to T1D diagnosis, when there was accelerated C-peptide decline and rising glycemia from 2 years until diabetes diagnosis. Remarkably, patterns of progression within 3 years of diagnosis were nearly identical between Progressors≥5 and Progressors<5. CONCLUSION These data provide insight into the chronicity of β cell dysfunction in T1D and indicate that β cell dysfunction may precede diabetes diagnosis by more than 5 years in a subset of aAb+ individuals. Even among individuals with varying lengths of aAb positivity, our findings indicate that patterns of metabolic decline are uniform within the last 3 years of progression to T1D. TRIAL REGISTRATION Clinicaltrials.gov NCT00097292. FUNDING The Type 1 Diabetes TrialNet Study Group is a clinical trials network currently funded by the NIH through the National Institute of Diabetes and Digestive and Kidney Diseases, the National Institute of Allergy and Infectious Diseases, and The Eunice Kennedy Shriver National Institute of Child Health and Human Development and the Juvenile Diabetes Research Foundation.
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Affiliation(s)
- Carmella Evans-Molina
- Departments of Medicine.,Cellular and Integrative Physiology.,Biochemistry and Molecular Biology.,Pediatrics, and the.,Herman B Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, Indiana, USA.,Roudebush VA Medical Center, Indianapolis, Indiana, USA
| | - Emily K Sims
- Pediatrics, and the.,Herman B Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Linda A DiMeglio
- Pediatrics, and the.,Herman B Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Heba M Ismail
- Children's Hospital of Pittsburgh of UPMC, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Andrea K Steck
- Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Denver, Colorado, USA
| | - Jerry P Palmer
- VA Puget Sound Health Care System and the University of Washington, Seattle, Washington, USA
| | - Jeffrey P Krischer
- Health Informatics Institute, University of South Florida, Tampa, Florida, USA
| | - Susan Geyer
- Health Informatics Institute, University of South Florida, Tampa, Florida, USA
| | - Ping Xu
- Health Informatics Institute, University of South Florida, Tampa, Florida, USA
| | - Jay M Sosenko
- Department of Medicine and the Diabetes Research Institute, Leonard Miller School of Medicine, University of Miami, Miami, Florida, USA
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