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Ferrat LA, Vehik K, Sharp SA, Lernmark Å, Rewers MJ, She JX, Ziegler AG, Toppari J, Akolkar B, Krischer JP, Weedon MN, Oram RA, Hagopian WA, Barbour A, Bautista K, Baxter J, Felipe-Morales D, Driscoll K, Frohnert BI, Stahl M, Gesualdo P, Hoffman M, Karban R, Liu E, Norris J, Peacock S, Shorrosh H, Steck A, Stern M, Villegas E, Waugh K, Simell OG, Adamsson A, Ahonen S, Åkerlund M, Hakola L, Hekkala A, Holappa H, Hyöty H, Ikonen A, Ilonen J, Jäminki S, Jokipuu S, Karlsson L, Kero J, Kähönen M, Knip M, Koivikko ML, Koskinen M, Koreasalo M, Kurppa K, Kytölä J, Latva-aho T, Lindfors K, Lönnrot M, Mäntymäki E, Mattila M, Miettinen M, Multasuo K, Mykkänen T, Niininen T, Niinistö S, Nyblom M, Oikarinen S, Ollikainen P, Othmani Z, Pohjola S, Rajala P, Rautanen J, Riikonen A, Riski E, Pekkola M, Romo M, Ruohonen S, Simell S, Sjöberg M, Stenius A, Tossavainen P, Vähä-Mäkilä M, Vainionpää S, Varjonen E, Veijola R, Viinikangas I, Virtanen SM, Schatz D, Hopkins D, Steed L, Bryant J, Silvis K, Haller M, Gardiner M, McIndoe R, Sharma A, Anderson SW, Jacobsen L, Marks J, Towe PD, Bonifacio E, Gezginci C, Heublein A, Hohoff E, Hummel S, Knopff A, Koch C, Koletzko S, Ramminger C, Roth R, Schmidt J, Scholz M, Stock J, Warncke K, Wendel L, Winkler C, Agardh D, Aronsson CA, Ask M, Bennet R, Cilio C, Dahlberg S, Engqvist H, Ericson-Hallström E, Fors AB, Fransson L, Gard T, Hansen M, Jisser H, Johansen F, Jonsdottir B, Elding Larsson H, Lindström M, Lundgren M, Maziarz M, Månsson-Martinez M, Melin J, Mestan Z, Nilsson C, Ottosson K, Rahmati K, Ramelius A, Salami F, Sjöberg A, Sjöberg B, Törn C, Wimar Å, Killian M, Crouch CC, Skidmore J, Chavoshi M, Meyer A, Meyer J, Mulenga D, Powell N, Radtke J, Romancik M, Roy S, Schmitt D, Zink S, Becker D, Franciscus M, Smith MDE, Daftary A, Klein MB, Yates C, Austin-Gonzalez S, Avendano M, Baethke S, Burkhardt B, Butterworth M, Clasen J, Cuthbertson D, Eberhard C, Fiske S, Garmeson J, Gowda V, Heyman K, Hsiao B, Karges C, Laras FP, Li Q, Liu S, Liu X, Lynch K, Maguire C, Malloy J, McCarthy C, Parikh H, Remedios C, Shaffer C, Smith L, Smith S, Sulman N, Tamura R, Tewey D, Toth M, Uusitalo U, Vijayakandipan P, Wood K, Yang J, Yu L, Miao D, Bingley P, Williams A, Chandler K, Kelland I, Khoud YB, Zahid H, Randell M, Chavoshi M, Radtke J, Zink S, Ke S, Mulholland N, Rich SS, Chen WM, Onengut-Gumuscu S, Farber E, Pickin RR, Davis J, Davis J, Gallo D, Bonnie J, Campolieto P, Petrosino JF, Ajami NJ, Lloyd RE, Ross MC, O’Brien JL, Hutchinson DS, Smith DP, Wong MC, Tian X, Ayvaz T, Tamegnon A, Truong N, Moreno H, Riley L, Moreno E, Bauch T, Kusic L, Metcalf G, Muzny D, Doddapaneni H, Gibbs R, Bourcier K, Briese T, Johnson SB, Triplett E, Ziegler AG, Tamura R, Norris J, Virtanen SM, Frohnert BI, Gesualdo P, Koreasalo M, Miettinen M, Niinistö S, Riikonen A, Silvis K, Hohoff E, Hummel S, Winkler C, Aronsson CA, Skidmore J, Smith MDE, Butterworth M, Li Q, Liu X, Tamura R, Uusitalo U, Yang J, Rich SS, Norris J, Steck A, Ilonen J, Ziegler AG, Törn C, Li Q, Liu X, Parikh H, Erlich H, Chen WM, Onengut-Gumuscu S, Schatz D, Ziegler AG, Cilio C, Bonifacio E, Knip M, Schatz D, Burkhardt B, Lynch K, Yu L, Bingley P, Bourcier K, Hyöty H, Triplett E, Lloyd R, Gesualdo P, Waugh K, Lönnrot M, Agardh D, Cilio C, Larsson HE, Killian M, Burkhardt B, Lynch K, Briese T, Waugh K, Schatz D, Killian M, Johnson SB, Roth R, Baxter J, Driscoll K, Schatz D, Stock J, Fiske S, Liu X, Lynch K, Smith L, Baxter J, Lernmark Å, Baxter J, Killian M, Bautista K, Gesualdo P, Hoffman M, Karban R, Norris J, Waugh K, Adamsson A, Kähönen M, Niininen T, Stenius A, Varjonen E, Hopkins D, Steed L, Bryant J, Gardiner M, Marks J, Ramminger C, Stock J, Winkler C, Aronsson CA, Jonsdottir B, Melin J, Killian M, Crouch CC, Mulenga D, McCarthy C, Smith L, Smith S, Tamura R, Johnson SB, Agardh D, Liu E, Koletzko S, Kurppa K, Stahl M, Hoffman M, Kurppa K, Lindfors K, Simell S, Steed L, Aronsson CA, Killian M, Tamura R, Haller M, Larsson HE, Frohnert BI, Gesualdo P, Hoffman M, Steck A, Kähönen M, Veijola R, Steed L, Jacobsen L, Marks J, Stock J, Warncke K, Lundgren M, Wimar Å, Crouch CC, Liu X, Tamura R. Author Correction: A combined risk score enhances prediction of type 1 diabetes among susceptible children. Nat Med 2022; 28:599. [DOI: 10.1038/s41591-021-01631-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Carr ALJ, Perry DJ, Lynam AL, Chamala S, Flaxman CS, Sharp SA, Ferrat LA, Jones AG, Beery ML, Jacobsen LM, Wasserfall CH, Campbell-Thompson ML, Kusmartseva I, Posgai A, Schatz DA, Atkinson MA, Brusko TM, Richardson SJ, Shields BM, Oram RA. Histological validation of a type 1 diabetes clinical diagnostic model for classification of diabetes. Diabet Med 2020; 37:2160-2168. [PMID: 32634859 PMCID: PMC8086995 DOI: 10.1111/dme.14361] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Revised: 05/31/2020] [Accepted: 07/01/2020] [Indexed: 12/21/2022]
Abstract
AIMS Misclassification of diabetes is common due to an overlap in the clinical features of type 1 and type 2 diabetes. Combined diagnostic models incorporating clinical and biomarker information have recently been developed that can aid classification, but they have not been validated using pancreatic pathology. We evaluated a clinical diagnostic model against histologically defined type 1 diabetes. METHODS We classified cases from the Network for Pancreatic Organ donors with Diabetes (nPOD) biobank as type 1 (n = 111) or non-type 1 (n = 42) diabetes using histopathology. Type 1 diabetes was defined by lobular loss of insulin-containing islets along with multiple insulin-deficient islets. We assessed the discriminative performance of previously described type 1 diabetes diagnostic models, based on clinical features (age at diagnosis, BMI) and biomarker data [autoantibodies, type 1 diabetes genetic risk score (T1D-GRS)], and singular features for identifying type 1 diabetes by the area under the curve of the receiver operator characteristic (AUC-ROC). RESULTS Diagnostic models validated well against histologically defined type 1 diabetes. The model combining clinical features, islet autoantibodies and T1D-GRS was strongly discriminative of type 1 diabetes, and performed better than clinical features alone (AUC-ROC 0.97 vs. 0.95; P = 0.03). Histological classification of type 1 diabetes was concordant with serum C-peptide [median < 17 pmol/l (limit of detection) vs. 1037 pmol/l in non-type 1 diabetes; P < 0.0001]. CONCLUSIONS Our study provides robust histological evidence that a clinical diagnostic model, combining clinical features and biomarkers, could improve diabetes classification. Our study also provides reassurance that a C-peptide-based definition of type 1 diabetes is an appropriate surrogate outcome that can be used in large clinical studies where histological definition is impossible. Parts of this study were presented in abstract form at the Network for Pancreatic Organ Donors Conference, Florida, USA, 19-22 February 2019 and Diabetes UK Professional Conference, Liverpool, UK, 6-8 March 2019.
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Affiliation(s)
- A L J Carr
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, UK
| | - D J Perry
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida Diabetes Institute, Gainesville, FL, USA
| | - A L Lynam
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, UK
| | - S Chamala
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida Diabetes Institute, Gainesville, FL, USA
| | - C S Flaxman
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, UK
| | - S A Sharp
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, UK
| | - L A Ferrat
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, UK
| | - A G Jones
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, UK
| | - M L Beery
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida Diabetes Institute, Gainesville, FL, USA
| | - L M Jacobsen
- Department of Pediatrics, College of Medicine, University of Florida Diabetes Institute, Gainesville, FL, USA
| | - C H Wasserfall
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida Diabetes Institute, Gainesville, FL, USA
| | - M L Campbell-Thompson
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida Diabetes Institute, Gainesville, FL, USA
| | - I Kusmartseva
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida Diabetes Institute, Gainesville, FL, USA
| | - A Posgai
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida Diabetes Institute, Gainesville, FL, USA
| | - D A Schatz
- Department of Pediatrics, College of Medicine, University of Florida Diabetes Institute, Gainesville, FL, USA
| | - M A Atkinson
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida Diabetes Institute, Gainesville, FL, USA
- Department of Pediatrics, College of Medicine, University of Florida Diabetes Institute, Gainesville, FL, USA
| | - T M Brusko
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida Diabetes Institute, Gainesville, FL, USA
| | - S J Richardson
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, UK
| | - B M Shields
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, UK
| | - R A Oram
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, UK
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Ferrat LA, Vehik K, Sharp SA, Lernmark Å, Rewers MJ, She JX, Ziegler AG, Toppari J, Akolkar B, Krischer JP, Weedon MN, Oram RA, Hagopian WA. A combined risk score enhances prediction of type 1 diabetes among susceptible children. Nat Med 2020; 26:1247-1255. [PMID: 32770166 PMCID: PMC7556983 DOI: 10.1038/s41591-020-0930-4] [Citation(s) in RCA: 68] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Accepted: 05/08/2020] [Indexed: 11/08/2022]
Abstract
Type 1 diabetes (T1D)-an autoimmune disease that destroys the pancreatic islets, resulting in insulin deficiency-often begins early in life when islet autoantibody appearance signals high risk1. However, clinical diabetes can follow in weeks or only after decades, and is very difficult to predict. Ketoacidosis at onset remains common2,3 and is most severe in the very young4,5, in whom it can be life threatening and difficult to treat6-9. Autoantibody surveillance programs effectively prevent most ketoacidosis10-12 but require frequent evaluations whose expense limits public health adoption13. Prevention therapies applied before onset, when greater islet mass remains, have rarely been feasible14 because individuals at greatest risk of impending T1D are difficult to identify. To remedy this, we sought accurate, cost-effective estimation of future T1D risk by developing a combined risk score incorporating both fixed and variable factors (genetic, clinical and immunological) in 7,798 high-risk children followed closely from birth for 9.3 years. Compared with autoantibodies alone, the combined model dramatically improves T1D prediction at ≥2 years of age over horizons up to 8 years of age (area under the receiver operating characteristic curve ≥ 0.9), doubles the estimated efficiency of population-based newborn screening to prevent ketoacidosis, and enables individualized risk estimates for better prevention trial selection.
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Affiliation(s)
- Lauric A Ferrat
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, UK
| | - Kendra Vehik
- Health Informatics Institute, Morsani College of Medicine, University of South Florida, Tampa, FL, USA
| | - Seth A Sharp
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, UK
| | - Åke Lernmark
- Department of Clinical Sciences, Lund University and Skåne University Hospital, Malmö, Sweden
| | - Marian J Rewers
- Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Aurora, CO, USA
| | - Jin-Xiong She
- Center for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta University, Augusta, GA, USA
| | - Anette-G Ziegler
- Institute of Diabetes Research, Helmholtz Zentrum München, Munich, Germany
- Forschergruppe Diabetes, Klinikum Rechts der Isar, Technische Universität München, Munich, Germany
- Forschergruppe Diabetes e.V., Munich, Germany
| | - Jorma Toppari
- Department of Pediatrics, Turku University Hospital, Turku, Finland
- Research Centre for Integrative Physiology and Pharmacology, Institute of Biomedicine, University of Turku, Turku, Finland
| | - Beena Akolkar
- National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Jeffrey P Krischer
- Health Informatics Institute, Morsani College of Medicine, University of South Florida, Tampa, FL, USA
| | - Michael N Weedon
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, UK
| | - Richard A Oram
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, UK
- Academic Renal Unit, Royal Devon and Exeter NHS Foundation Trust, Exeter, UK
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