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Serreze DV, Dwyer JR, Racine JJ. Advancing Animal Models of Human Type 1 Diabetes. Cold Spring Harb Perspect Med 2024; 14:a041587. [PMID: 38886067 PMCID: PMC11444302 DOI: 10.1101/cshperspect.a041587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/20/2024]
Abstract
Multiple rodent models have been developed to study the basis of type 1 diabetes (T1D). However, nonobese diabetic (NOD) mice and derivative strains still provide the gold standard for dissecting the basis of the autoimmune responses underlying T1D. Here, we review the developmental origins of NOD mice, and how they and derivative strains have been used over the past several decades to dissect the genetic and immunopathogenic basis of T1D. Also discussed are ways in which the immunopathogenic basis of T1D in NOD mice and humans are similar or differ. Additionally reviewed are efforts to "humanize" NOD mice and derivative strains to provide improved models to study autoimmune responses contributing to T1D in human patients.
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McGrail C, Sears TJ, Kudtarkar P, Carter H, Gaulton K. Genetic association and machine learning improves discovery and prediction of type 1 diabetes. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.07.31.24311310. [PMID: 39132494 PMCID: PMC11312647 DOI: 10.1101/2024.07.31.24311310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
Type 1 diabetes (T1D) has a large genetic component, and expanded genetic studies of T1D can lead to novel biological and therapeutic discovery and improved risk prediction. In this study, we performed genetic association and fine-mapping analyses in 817,718 European ancestry samples genome-wide and 29,746 samples at the MHC locus, which identified 165 independent risk signals for T1D of which 19 were novel. We used risk variants to train a machine learning model (named T1GRS) to predict T1D, which highly differentiated T1D from non-disease and type 2 diabetes (T2D) in Europeans as well as African Americans at or beyond the level of current standards. We identified extensive non-linear interactions between risk loci in T1GRS, for example between HLA-DQB1*57 and INS, coding and non-coding HLA alleles, and DEXI, INS and other beta cell loci, that provided mechanistic insight and improved risk prediction. T1D individuals formed distinct clusters based on genetic features from T1GRS which had significant differences in age of onset, HbA1c, and renal disease severity. Finally, we provided T1GRS in formats to enhance accessibility of risk prediction to any user and computing environment. Overall, the improved genetic discovery and prediction of T1D will have wide clinical, therapeutic, and research applications.
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Affiliation(s)
- Carolyn McGrail
- Biomedical sciences graduate program, University of California San Diego, La Jolla CA
| | - Timothy J. Sears
- Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla CA
| | - Parul Kudtarkar
- Department of Pediatrics, University of California San Diego, La Jolla CA
| | - Hannah Carter
- Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla CA
- Moore’s Cancer Center, University of California San Diego, La Jolla CA
- Department of Medicine, University of California San Diego, La Jolla CA
| | - Kyle Gaulton
- Department of Pediatrics, University of California San Diego, La Jolla CA
- Pediatric Diabetes Research Center, University of California San Diego, La Jolla CA
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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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Lernmark Å, Akolkar B, Hagopian W, Krischer J, McIndoe R, Rewers M, Toppari J, Vehik K, Ziegler AG. Possible heterogeneity of initial pancreatic islet beta-cell autoimmunity heralding type 1 diabetes. J Intern Med 2023; 294:145-158. [PMID: 37143363 PMCID: PMC10524683 DOI: 10.1111/joim.13648] [Citation(s) in RCA: 1] [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] [Indexed: 05/06/2023]
Abstract
The etiology of type 1 diabetes (T1D) foreshadows the pancreatic islet beta-cell autoimmune pathogenesis that heralds the clinical onset of T1D. Standardized and harmonized tests of autoantibodies against insulin (IAA), glutamic acid decarboxylase (GADA), islet antigen-2 (IA-2A), and ZnT8 transporter (ZnT8A) allowed children to be followed from birth until the appearance of a first islet autoantibody. In the Environmental Determinants of Diabetes in the Young (TEDDY) study, a multicenter (Finland, Germany, Sweden, and the United States) observational study, children were identified at birth for the T1D high-risk HLA haploid genotypes DQ2/DQ8, DQ2/DQ2, DQ8/DQ8, and DQ4/DQ8. The TEDDY study was preceded by smaller studies in Finland, Germany, Colorado, Washington, and Sweden. The aims were to follow children at increased genetic risk to identify environmental factors that trigger the first-appearing autoantibody (etiology) and progress to T1D (pathogenesis). The larger TEDDY study found that the incidence rate of the first-appearing autoantibody was split into two patterns. IAA first peaked already during the first year of life and tapered off by 3-4 years of age. GADA first appeared by 2-3 years of age to reach a plateau by about 4 years. Prior to the first-appearing autoantibody, genetic variants were either common or unique to either pattern. A split was also observed in whole blood transcriptomics, metabolomics, dietary factors, and exposures such as gestational life events and early infections associated with prolonged shedding of virus. An innate immune reaction prior to the adaptive response cannot be excluded. Clarifying the mechanisms by which autoimmunity is triggered to either insulin or GAD65 is key to uncovering the etiology of autoimmune T1D.
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Affiliation(s)
- Åke Lernmark
- Department of Clinical Sciences, Lund University CRC, Skåne University Hospital, Malmö, Sweden
| | - Beena Akolkar
- National Institute of Diabetes & Digestive & Kidney Diseases, Bethesda, MD USA
| | | | - Jeffrey Krischer
- Health Informatics Institute, Morsani College of Medicine, University of South Florida, Tampa, FL USA
| | - Richard McIndoe
- Center for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta University, Augusta, GA USA
| | - Marian Rewers
- Barbara Davis Center for Diabetes, University of Colorado, Aurora, Colorado USA
| | - Jorma Toppari
- Department of Pediatrics, Turku University Hospital, and Institute of Biomedicine, Research Centre for Integrated Physiology and Pharmacology, University of Turku, Turku, Finland
| | - Kendra Vehik
- Health Informatics Institute, Morsani College of Medicine, University of South Florida, Tampa, FL USA
| | - Anette-G. Ziegler
- Institute of Diabetes Research, Helmholtz Zentrum München, and Klinikum rechts der Isar, Technische Universität München, and Forschergruppe Diabetes e.V., Neuherberg, Germany
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Perry DJ, Shapiro MR, Chamberlain SW, Kusmartseva I, Chamala S, Balzano-Nogueira L, Yang M, Brant JO, Brusko M, Williams MD, McGrail KM, McNichols J, Peters LD, Posgai AL, Kaddis JS, Mathews CE, Wasserfall CH, Webb-Robertson BJM, Campbell-Thompson M, Schatz D, Evans-Molina C, Pugliese A, Concannon P, Anderson MS, German MS, Chamberlain CE, Atkinson MA, Brusko TM. A genomic data archive from the Network for Pancreatic Organ donors with Diabetes. Sci Data 2023; 10:323. [PMID: 37237059 PMCID: PMC10219990 DOI: 10.1038/s41597-023-02244-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2022] [Accepted: 05/16/2023] [Indexed: 05/28/2023] Open
Abstract
The Network for Pancreatic Organ donors with Diabetes (nPOD) is the largest biorepository of human pancreata and associated immune organs from donors with type 1 diabetes (T1D), maturity-onset diabetes of the young (MODY), cystic fibrosis-related diabetes (CFRD), type 2 diabetes (T2D), gestational diabetes, islet autoantibody positivity (AAb+), and without diabetes. nPOD recovers, processes, analyzes, and distributes high-quality biospecimens, collected using optimized standard operating procedures, and associated de-identified data/metadata to researchers around the world. Herein describes the release of high-parameter genotyping data from this collection. 372 donors were genotyped using a custom precision medicine single nucleotide polymorphism (SNP) microarray. Data were technically validated using published algorithms to evaluate donor relatedness, ancestry, imputed HLA, and T1D genetic risk score. Additionally, 207 donors were assessed for rare known and novel coding region variants via whole exome sequencing (WES). These data are publicly-available to enable genotype-specific sample requests and the study of novel genotype:phenotype associations, aiding in the mission of nPOD to enhance understanding of diabetes pathogenesis to promote the development of novel therapies.
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Affiliation(s)
- Daniel J Perry
- Department of Pathology, Immunology and Laboratory Medicine, Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL, 32611, USA
| | - Melanie R Shapiro
- Department of Pathology, Immunology and Laboratory Medicine, Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL, 32611, USA
| | - Sonya W Chamberlain
- Diabetes Center, School of Medicine, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Irina Kusmartseva
- Department of Pathology, Immunology and Laboratory Medicine, Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL, 32611, USA
| | - Srikar Chamala
- Department of Pathology, Immunology and Laboratory Medicine, Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL, 32611, USA
| | - Leandro Balzano-Nogueira
- Department of Pathology, Immunology and Laboratory Medicine, Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL, 32611, USA
| | - Mingder Yang
- Department of Pathology, Immunology and Laboratory Medicine, Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL, 32611, USA
| | - Jason O Brant
- Department of Pathology, Immunology and Laboratory Medicine, Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL, 32611, USA
- Department of Biostatistics, College of Public Health and Health Professions, University of Florida, Gainesville, FL, 32610, USA
| | - Maigan Brusko
- Department of Pathology, Immunology and Laboratory Medicine, Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL, 32611, USA
| | - MacKenzie D Williams
- Department of Pathology, Immunology and Laboratory Medicine, Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL, 32611, USA
| | - Kieran M McGrail
- Department of Pathology, Immunology and Laboratory Medicine, Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL, 32611, USA
| | - James McNichols
- Department of Pathology, Immunology and Laboratory Medicine, Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL, 32611, USA
| | - Leeana D Peters
- Department of Pathology, Immunology and Laboratory Medicine, Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL, 32611, USA
| | - Amanda L Posgai
- Department of Pathology, Immunology and Laboratory Medicine, Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL, 32611, USA
| | - John S Kaddis
- Department of Diabetes and Cancer Discovery Science, Arthur Riggs Diabetes and Metabolism Research Institute, Beckman Research Institute, City of Hope, Duarte, CA, 91010, USA
| | - Clayton E Mathews
- Department of Pathology, Immunology and Laboratory Medicine, Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL, 32611, USA
- Department of Pediatrics, Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL, 32610, USA
| | - Clive H Wasserfall
- Department of Pathology, Immunology and Laboratory Medicine, Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL, 32611, USA
| | - Bobbie-Jo M Webb-Robertson
- Department of Pathology, Immunology and Laboratory Medicine, Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL, 32611, USA
- Biological Sciences Division, Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Martha Campbell-Thompson
- Department of Pathology, Immunology and Laboratory Medicine, Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL, 32611, USA
- Department of Biomedical Engineering, College of Engineering, University of Florida, Gainesville, FL, 32611, USA
| | - Desmond Schatz
- Department of Pediatrics, Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL, 32610, USA
| | - Carmella Evans-Molina
- Center for Diabetes and Metabolic Diseases and the Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Alberto Pugliese
- Diabetes Research Institute, Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, Department of Microbiology and Immunology, Miller School of Medicine, University of Miami, Miami, FL, 33021, USA
| | - Patrick Concannon
- Department of Pathology, Immunology and Laboratory Medicine, Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL, 32611, USA
- Genetics Institute, University of Florida, Gainesville, FL, 32601, USA
| | - Mark S Anderson
- Diabetes Center, School of Medicine, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Michael S German
- Diabetes Center, School of Medicine, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Chester E Chamberlain
- Diabetes Center, School of Medicine, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Mark A Atkinson
- Department of Pathology, Immunology and Laboratory Medicine, Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL, 32611, USA.
- Department of Pediatrics, Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL, 32610, USA.
| | - Todd M Brusko
- Department of Pathology, Immunology and Laboratory Medicine, Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL, 32611, USA.
- Department of Pediatrics, Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL, 32610, USA.
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Thomas NJ, Walkey HC, Kaur A, Misra S, Oliver NS, Colclough K, Weedon MN, Johnston DG, Hattersley AT, Patel KA. The relationship between islet autoantibody status and the genetic risk of type 1 diabetes in adult-onset type 1 diabetes. Diabetologia 2023; 66:310-320. [PMID: 36355183 PMCID: PMC9807542 DOI: 10.1007/s00125-022-05823-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 09/30/2022] [Indexed: 11/11/2022]
Abstract
AIMS/HYPOTHESIS The reason for the observed lower rate of islet autoantibody positivity in clinician-diagnosed adult-onset vs childhood-onset type 1 diabetes is not known. We aimed to explore this by assessing the genetic risk of type 1 diabetes in autoantibody-negative and -positive children and adults. METHODS We analysed GAD autoantibodies, insulinoma-2 antigen autoantibodies and zinc transporter-8 autoantibodies (ZnT8A) and measured type 1 diabetes genetic risk by genotyping 30 type 1 diabetes-associated variants at diagnosis in 1814 individuals with clinician-diagnosed type 1 diabetes (1112 adult-onset, 702 childhood-onset). We compared the overall type 1 diabetes genetic risk score (T1DGRS) and non-HLA and HLA (DR3-DQ2, DR4-DQ8 and DR15-DQ6) components with autoantibody status in those with adult-onset and childhood-onset diabetes. We also measured the T1DGRS in 1924 individuals with type 2 diabetes from the Wellcome Trust Case Control Consortium to represent non-autoimmune diabetes control participants. RESULTS The T1DGRS was similar in autoantibody-negative and autoantibody-positive clinician-diagnosed childhood-onset type 1 diabetes (mean [SD] 0.274 [0.034] vs 0.277 [0.026], p=0.4). In contrast, the T1DGRS in autoantibody-negative adult-onset type 1 diabetes was lower than that in autoantibody-positive adult-onset type 1 diabetes (mean [SD] 0.243 [0.036] vs 0.271 [0.026], p<0.0001) but higher than that in type 2 diabetes (mean [SD] 0.229 [0.034], p<0.0001). Autoantibody-negative adults were more likely to have the more protective HLA DR15-DQ6 genotype (15% vs 3%, p<0.0001), were less likely to have the high-risk HLA DR3-DQ2/DR4-DQ8 genotype (6% vs 19%, p<0.0001) and had a lower non-HLA T1DGRS (p<0.0001) than autoantibody-positive adults. In contrast to children, autoantibody-negative adults were more likely to be male (75% vs 59%), had a higher BMI (27 vs 24 kg/m2) and were less likely to have other autoimmune conditions (2% vs 10%) than autoantibody-positive adults (all p<0.0001). In both adults and children, type 1 diabetes genetic risk was unaffected by the number of autoantibodies (p>0.3). These findings, along with the identification of seven misclassified adults with monogenic diabetes among autoantibody-negative adults and the results of a sensitivity analysis with and without measurement of ZnT8A, suggest that the intermediate type 1 diabetes genetic risk in autoantibody-negative adults is more likely to be explained by the inclusion of misclassified non-autoimmune diabetes (estimated to represent 67% of all antibody-negative adults, 95% CI 61%, 73%) than by the presence of unmeasured autoantibodies or by a discrete form of diabetes. When these estimated individuals with non-autoimmune diabetes were adjusted for, the prevalence of autoantibody positivity in adult-onset type 1 diabetes was similar to that in children (93% vs 91%, p=0.4). CONCLUSIONS/INTERPRETATION The inclusion of non-autoimmune diabetes is the most likely explanation for the observed lower rate of autoantibody positivity in clinician-diagnosed adult-onset type 1 diabetes. Our data support the utility of islet autoantibody measurement in clinician-suspected adult-onset type 1 diabetes in routine clinical practice.
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Affiliation(s)
- Nicholas J Thomas
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, UK
- Department of Diabetes and Endocrinology, Royal Devon and Exeter NHS Foundation Trust, Exeter, UK
| | - Helen C Walkey
- Faculty of Medicine, Imperial College London, London, UK
| | - Akaal Kaur
- Faculty of Medicine, Imperial College London, London, UK
| | - Shivani Misra
- Faculty of Medicine, Imperial College London, London, UK
| | - Nick S Oliver
- Faculty of Medicine, Imperial College London, London, UK
| | - Kevin Colclough
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, UK
| | - Michael N Weedon
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, UK
| | | | - Andrew T Hattersley
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, UK
- Department of Diabetes and Endocrinology, Royal Devon and Exeter NHS Foundation Trust, Exeter, UK
| | - Kashyap A Patel
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, UK.
- Department of Diabetes and Endocrinology, Royal Devon and Exeter NHS Foundation Trust, Exeter, UK.
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7
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Long SA, Buckner JH. Clinical and experimental treatment of type 1 diabetes. Clin Exp Immunol 2022; 210:105-113. [PMID: 35980300 PMCID: PMC9750829 DOI: 10.1093/cei/uxac077] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 07/26/2022] [Accepted: 08/17/2022] [Indexed: 01/25/2023] Open
Abstract
Type 1 diabetes (T1D) is an autoimmune disease resulting in the destruction of the insulin-producing pancreatic beta cells. Disease progression occurs along a trajectory from genetic risk, the development of islet autoantibodies, and autoreactive T cells ultimately progressing to clinical disease. Natural history studies and mechanistic studies linked to clinical trials have provided insight into the role of the immune system in disease pathogenesis. Here, we review our current understanding of the underlying etiology of T1D, focusing on the immune cell types that have been implicated in progression from pre-symptomatic T1D to clinical diagnosis and established disease. This knowledge has been foundational for the development of immunotherapies aimed at the prevention and treatment of T1D.
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Affiliation(s)
- S Alice Long
- Center for Translational Immunology, Benaroya Research Institute at Virginia Mason, Seattle, WA, USA
| | - Jane H Buckner
- Center for Translational Immunology, Benaroya Research Institute at Virginia Mason, Seattle, WA, USA
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8
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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: 32] [Impact Index Per Article: 16.0] [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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9
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Zajec A, Trebušak Podkrajšek K, Tesovnik T, Šket R, Čugalj Kern B, Jenko Bizjan B, Šmigoc Schweiger D, Battelino T, Kovač J. Pathogenesis of Type 1 Diabetes: Established Facts and New Insights. Genes (Basel) 2022; 13:genes13040706. [PMID: 35456512 PMCID: PMC9032728 DOI: 10.3390/genes13040706] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 04/13/2022] [Accepted: 04/13/2022] [Indexed: 01/08/2023] Open
Abstract
Type 1 diabetes (T1D) is an autoimmune disease characterized by the T-cell-mediated destruction of insulin-producing β-cells in pancreatic islets. It generally occurs in genetically susceptible individuals, and genetics plays a major role in the development of islet autoimmunity. Furthermore, these processes are heterogeneous among individuals; hence, different endotypes have been proposed. In this review, we highlight the interplay between genetic predisposition and other non-genetic factors, such as viral infections, diet, and gut biome, which all potentially contribute to the aetiology of T1D. We also discuss a possible active role for β-cells in initiating the pathological processes. Another component in T1D predisposition is epigenetic influences, which represent a link between genetic susceptibility and environmental factors and may account for some of the disease heterogeneity. Accordingly, a shift towards personalized therapies may improve the treatment results and, therefore, result in better outcomes for individuals in the long-run. There is also a clear need for a better understanding of the preclinical phases of T1D and finding new predictive biomarkers for earlier diagnosis and therapy, with the final goal of reverting or even preventing the development of the disease.
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Affiliation(s)
- Ana Zajec
- Division of Paediatrics, University Medical Centre Ljubljana, 1000 Ljubljana, Slovenia; (A.Z.); (K.T.P.); (T.T.); (R.Š.); (B.Č.K.); (B.J.B.); (D.Š.S.); (T.B.)
- Department of Paediatrics, Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, Slovenia
| | - Katarina Trebušak Podkrajšek
- Division of Paediatrics, University Medical Centre Ljubljana, 1000 Ljubljana, Slovenia; (A.Z.); (K.T.P.); (T.T.); (R.Š.); (B.Č.K.); (B.J.B.); (D.Š.S.); (T.B.)
- Department of Paediatrics, Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, Slovenia
| | - Tine Tesovnik
- Division of Paediatrics, University Medical Centre Ljubljana, 1000 Ljubljana, Slovenia; (A.Z.); (K.T.P.); (T.T.); (R.Š.); (B.Č.K.); (B.J.B.); (D.Š.S.); (T.B.)
| | - Robert Šket
- Division of Paediatrics, University Medical Centre Ljubljana, 1000 Ljubljana, Slovenia; (A.Z.); (K.T.P.); (T.T.); (R.Š.); (B.Č.K.); (B.J.B.); (D.Š.S.); (T.B.)
| | - Barbara Čugalj Kern
- Division of Paediatrics, University Medical Centre Ljubljana, 1000 Ljubljana, Slovenia; (A.Z.); (K.T.P.); (T.T.); (R.Š.); (B.Č.K.); (B.J.B.); (D.Š.S.); (T.B.)
- Department of Paediatrics, Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, Slovenia
| | - Barbara Jenko Bizjan
- Division of Paediatrics, University Medical Centre Ljubljana, 1000 Ljubljana, Slovenia; (A.Z.); (K.T.P.); (T.T.); (R.Š.); (B.Č.K.); (B.J.B.); (D.Š.S.); (T.B.)
- Department of Paediatrics, Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, Slovenia
| | - Darja Šmigoc Schweiger
- Division of Paediatrics, University Medical Centre Ljubljana, 1000 Ljubljana, Slovenia; (A.Z.); (K.T.P.); (T.T.); (R.Š.); (B.Č.K.); (B.J.B.); (D.Š.S.); (T.B.)
- Department of Paediatrics, Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, Slovenia
| | - Tadej Battelino
- Division of Paediatrics, University Medical Centre Ljubljana, 1000 Ljubljana, Slovenia; (A.Z.); (K.T.P.); (T.T.); (R.Š.); (B.Č.K.); (B.J.B.); (D.Š.S.); (T.B.)
- Department of Paediatrics, Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, Slovenia
| | - Jernej Kovač
- Division of Paediatrics, University Medical Centre Ljubljana, 1000 Ljubljana, Slovenia; (A.Z.); (K.T.P.); (T.T.); (R.Š.); (B.Č.K.); (B.J.B.); (D.Š.S.); (T.B.)
- Department of Paediatrics, Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, Slovenia
- Correspondence:
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10
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Toren E, Burnette KS, Banerjee RR, Hunter CS, Tse HM. Partners in Crime: Beta-Cells and Autoimmune Responses Complicit in Type 1 Diabetes Pathogenesis. Front Immunol 2021; 12:756548. [PMID: 34691077 PMCID: PMC8529969 DOI: 10.3389/fimmu.2021.756548] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Accepted: 09/13/2021] [Indexed: 12/11/2022] Open
Abstract
Type 1 diabetes (T1D) is an autoimmune disease characterized by autoreactive T cell-mediated destruction of insulin-producing pancreatic beta-cells. Loss of beta-cells leads to insulin insufficiency and hyperglycemia, with patients eventually requiring lifelong insulin therapy to maintain normal glycemic control. Since T1D has been historically defined as a disease of immune system dysregulation, there has been little focus on the state and response of beta-cells and how they may also contribute to their own demise. Major hurdles to identifying a cure for T1D include a limited understanding of disease etiology and how functional and transcriptional beta-cell heterogeneity may be involved in disease progression. Recent studies indicate that the beta-cell response is not simply a passive aspect of T1D pathogenesis, but rather an interplay between the beta-cell and the immune system actively contributing to disease. Here, we comprehensively review the current literature describing beta-cell vulnerability, heterogeneity, and contributions to pathophysiology of T1D, how these responses are influenced by autoimmunity, and describe pathways that can potentially be exploited to delay T1D.
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Affiliation(s)
- Eliana Toren
- Department of Medicine, Division of Endocrinology Diabetes and Metabolism, University of Alabama at Birmingham, Birmingham, AL, United States
- Comprehensive Diabetes Center, University of Alabama at Birmingham, Birmingham, AL, United States
| | - KaLia S. Burnette
- Comprehensive Diabetes Center, University of Alabama at Birmingham, Birmingham, AL, United States
- Department of Microbiology, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Ronadip R. Banerjee
- Division of Endocrinology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Chad S. Hunter
- Department of Medicine, Division of Endocrinology Diabetes and Metabolism, University of Alabama at Birmingham, Birmingham, AL, United States
- Comprehensive Diabetes Center, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Hubert M. Tse
- Comprehensive Diabetes Center, University of Alabama at Birmingham, Birmingham, AL, United States
- Department of Microbiology, University of Alabama at Birmingham, Birmingham, AL, United States
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Abstract
This review focuses on the human pancreatic islet-including its structure, cell composition, development, function, and dysfunction. After providing a historical timeline of key discoveries about human islets over the past century, we describe new research approaches and technologies that are being used to study human islets and how these are providing insight into human islet physiology and pathophysiology. We also describe changes or adaptations in human islets in response to physiologic challenges such as pregnancy, aging, and insulin resistance and discuss islet changes in human diabetes of many forms. We outline current and future interventions being developed to protect, restore, or replace human islets. The review also highlights unresolved questions about human islets and proposes areas where additional research on human islets is needed.
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Affiliation(s)
- John T Walker
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Diane C Saunders
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Marcela Brissova
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Alvin C Powers
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- VA Tennessee Valley Healthcare System, Nashville, Tennessee, USA
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12
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Shapiro MR, Thirawatananond P, Peters L, Sharp RC, Ogundare S, Posgai AL, Perry DJ, Brusko TM. De-coding genetic risk variants in type 1 diabetes. Immunol Cell Biol 2021; 99:496-508. [PMID: 33483996 PMCID: PMC8119379 DOI: 10.1111/imcb.12438] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Revised: 01/08/2021] [Accepted: 01/20/2021] [Indexed: 12/13/2022]
Abstract
The conceptual basis for a genetic predisposition underlying the risk for developing type 1 diabetes (T1D) predates modern human molecular genetics. Over half of the genetic risk has been attributed to the human leukocyte antigen (HLA) class II gene region and to the insulin (INS) gene locus - both thought to confer direction of autoreactivity and tissue specificity. Notwithstanding, questions still remain regarding the functional contributions of a vast array of minor polygenic risk variants scattered throughout the genome that likely influence disease heterogeneity and clinical outcomes. Herein, we summarize the available literature related to the T1D-associated coding variants defined at the time of this review, for the genes PTPN22, IFIH1, SH2B3, CD226, TYK2, FUT2, SIRPG, CTLA4, CTSH and UBASH3A. Data from genotype-selected human cohorts are summarized, and studies from the non-obese diabetic (NOD) mouse are presented to describe the functional impact of these variants in relation to innate and adaptive immunity as well as to β-cell fragility, with expression profiles in tissues and peripheral blood highlighted. The contribution of each variant to progression through T1D staging, including environmental interactions, are discussed with consideration of how their respective protein products may serve as attractive targets for precision medicine-based therapeutics to prevent or suspend the development of T1D.
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Affiliation(s)
- Melanie R Shapiro
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, Diabetes Institute, University of Florida, Gainesville, FL, 32610, USA
| | - Puchong Thirawatananond
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, Diabetes Institute, University of Florida, Gainesville, FL, 32610, USA
| | - Leeana Peters
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, Diabetes Institute, University of Florida, Gainesville, FL, 32610, USA
| | - Robert C Sharp
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, Diabetes Institute, University of Florida, Gainesville, FL, 32610, USA
| | - Similoluwa Ogundare
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, Diabetes Institute, University of Florida, Gainesville, FL, 32610, USA
| | - Amanda L Posgai
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, Diabetes Institute, University of Florida, Gainesville, FL, 32610, USA
| | - Daniel J Perry
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, Diabetes Institute, University of Florida, Gainesville, FL, 32610, USA
| | - Todd M Brusko
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, Diabetes Institute, University of Florida, Gainesville, FL, 32610, USA
- Department of Pediatrics, College of Medicine, Diabetes Institute, University of Florida, Gainesville, FL, 32610, USA
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13
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Abstract
As part of the centennial celebration of insulin's discovery, this review summarizes the current understanding of the genetics, pathogenesis, treatment, and outcomes in type 1 diabetes (T1D). T1D results from an autoimmune response that leads to destruction of the β cells in the pancreatic islet and requires lifelong insulin therapy. While much has been learned about T1D, it is now clear that there is considerable heterogeneity in T1D with regard to genetics, pathology, response to immune-based therapies, clinical course, and susceptibility to diabetes-related complications. This Review highlights knowledge gaps and opportunities to improve the understanding of T1D pathogenesis and outlines emerging therapies to treat or prevent T1D and reduce the burden of T1D.
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14
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Ramos-Rodríguez M, Pérez-González B, Pasquali L. The β-Cell Genomic Landscape in T1D: Implications for Disease Pathogenesis. Curr Diab Rep 2021; 21:1. [PMID: 33387073 PMCID: PMC7778620 DOI: 10.1007/s11892-020-01370-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/19/2020] [Indexed: 11/15/2022]
Abstract
PURPOSE OF REVIEW Type 1 diabetes (T1D) develops as a consequence of a combination of genetic predisposition and environmental factors. Combined, these events trigger an autoimmune disease that results in progressive loss of pancreatic β cells, leading to insulin deficiency. This article reviews the current knowledge on the genetics of T1D with a specific focus on genetic variation in pancreatic islet regulatory networks and its implication to T1D risk and disease development. RECENT FINDINGS Accumulating evidence suggest an active role of β cells in T1D pathogenesis. Based on such observation several studies aimed in mapping T1D risk variants acting at the β cell level. Such studies unravel T1D risk loci shared with type 2 diabetes (T2D) and T1D risk variants potentially interfering with β-cell responses to external stimuli. The characterization of regulatory genomics maps of disease-relevant states and cell types can be used to elucidate the mechanistic role of β cells in the pathogenesis of T1D.
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Affiliation(s)
- Mireia Ramos-Rodríguez
- Endocrine Regulatory Genomics, Department of Experimental & Health Sciences, University Pompeu Fabra, 08003, Barcelona, Spain
| | - Beatriz Pérez-González
- Endocrine Regulatory Genomics, Department of Experimental & Health Sciences, University Pompeu Fabra, 08003, Barcelona, Spain
| | - Lorenzo Pasquali
- Endocrine Regulatory Genomics, Department of Experimental & Health Sciences, University Pompeu Fabra, 08003, Barcelona, Spain.
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