title: Does diabetes appear in distinct phenotypes in young people? Results of the diabetes mellitus incidence Cohort Registry (DiMelli).
abstract: BACKGROUND
  The diabetes mellitus Incidence Cohort Registry (DiMelli) aims to characterize diabetes phenotypes by immunologic, metabolic, and genetic markers. We classified patients into three groups according to islet autoantibody status and examined whether patients with multiple diabetes-associated autoantibodies, one autoantibody, or without autoantibodies differed with respect to clinical, metabolic, and genetic parameters, including an insulin sensitivity (IS) score based on waist, HbA1c, and triglycerides. We also assessed whether metabolic markers predicted the immune status.
  
  
  METHODS
  As of June 2012, 630 patients in Bavaria, Germany, aged <20 years diagnosed with any type of diabetes within the preceding 6 months were registered in DiMelli. We compared the clinical and laboratory parameters between islet autoantibody status defined patient groups. Parameters showing the strongest associations were included in principal component analysis. Receiver operating characteristic curves were used to assess the ability of the IS Score to predict islet autoantibody status.
  
  
  RESULTS
  Patients with multiple islet autoantibodies, one autoantibody, or without autoantibodies were significantly different in terms of BMI percentile, weight loss before diagnosis, fasting C-peptide (all, P<0.001), and IS Score (P=0.034). However, principal component analysis revealed no distinct patterns according to autoantibody status. At the optimal IS Score cut-off for predicting islet autoantibody positivity (single compared to none), the specificity was 52.0% and the sensitivity was 86.8%. With respect to prediction of multiple autoantibodies (compared to none), specificity and sensitivity were slightly lower and in combination inferior to those obtained using the BMI percentile and fasting C-peptide.
  
  
  CONCLUSIONS
  The DiMelli study indicated that patients with and without islet autoantibodies differed with respect to metabolic and genetic markers but there was considerable overlap of phenotypes, and autoantibody status could not be predicted by these parameters. Thus, our results suggest that refined diabetes classification may require both immune and metabolic phenotyping.
authors.affiliation: The Institute of Diabetes Research, Helmholtz Zentrum München, and Forschergruppe Diabetes, Klinikum Rechts der Isar, Technische Universität München, Neuherberg, Germany ; Forschergruppe Diabetes e.V., Neuherberg, Germany ; The Department of Pediatrics, Klinikum Rechts der Isar, Technische Universität München, München, Germany.
authors.forename: Katharina
authors.initials: K
authors.lastname: Warncke
authors.forename: Miriam
authors.initials: M
authors.lastname: Krasmann
authors.forename: Ramona
authors.initials: R
authors.lastname: Puff
authors.forename: Desirée
authors.initials: D
authors.lastname: Dunstheimer
authors.forename: Anette-Gabriele
authors.initials: AG
authors.lastname: Ziegler
authors.forename: Andreas
authors.initials: A
authors.lastname: Beyerlein
mesh_terms: D000293:Adolescent; D001323:Autoantibodies / Q000097:blood; D015992:Body Mass Index; D002096:C-Peptide / Q000097:blood; D002648:Child; D002675:Child, Preschool; D015331:Cohort Studies; D003920:Diabetes Mellitus / Q000097:blood / Q000453:epidemiology* / Q000276:immunology / Q000503:physiopathology; D005260:Female; D006801:Humans; D015994:Incidence; D007223:Infant; D007333:Insulin Resistance; D007515:Islets of Langerhans / Q000276:immunology / Q000503:physiopathology; D008297:Male; D010641:Phenotype; D012042:Registries; D055815:Young Adult
chemical_list: D001323:Autoantibodies; D002096:C-Peptide
references.citation: Diabetes Care. 2011 Jul;34(7):1628-33
references.pmid: 21636800
references.citation: Diabetes Care. 2010 Feb;33(2):338-40
references.pmid: 19903753
references.citation: Rev Diabet Stud. 2010 Fall;7(3):202-8
references.pmid: 21409312
references.citation: Pediatr Diabetes. 2007 Oct;8(5):286-98
references.pmid: 17850472
references.citation: Diabetologia. 2010 Dec;53(12):2611-20
references.pmid: 20871974
references.citation: Horm Res Paediatr. 2010;74(4):285-91
references.pmid: 20516654
references.citation: Diabetologia. 2011 Jan;54(1):78-86
references.pmid: 20886205
references.citation: Diabetes Care. 2003 Jan;26 Suppl 1:S5-20
references.pmid: 12502614
references.citation: Diabetes. 1965 Dec;14(12):771-9
references.pmid: 5850216
references.citation: Diabetologia. 2008 May;51(5):846-52
references.pmid: 18373080
references.citation: Proc Natl Acad Sci U S A. 2007 Oct 23;104(43):17040-5
references.pmid: 17942684
references.citation: Diabetologia. 2012 Aug;55(8):2142-7
references.pmid: 22638547
references.citation: JAMA. 2007 Jun 27;297(24):2716-24
references.pmid: 17595272
references.citation: Eur J Pediatr. 2005 Nov;164(11):705-7
references.pmid: 16012857
references.citation: Endocrinol Metab Clin North Am. 1999 Dec;28(4):709-29, viii
references.pmid: 10609116
references.citation: Clin Chem. 2011 Dec;57(12):1693-702
references.pmid: 21980171
references.citation: Diabetes. 1999 Mar;48(3):460-8
references.pmid: 10078544
references.citation: Curr Diab Rep. 2012 Feb;12(1):75-81
references.pmid: 22139556
references.citation: Diabetes Care. 2012 Dec;35(12):2515-20
references.pmid: 23173134
references.citation: Diabetologia. 2006 Sep;49(9):1989-95
references.pmid: 16821044
references.citation: Diabetes Care. 2010 Sep;33(9):2010-2
references.pmid: 20551013
references.citation: J Clin Endocrinol Metab. 2003 Apr;88(4):1417-27
references.pmid: 12679416
references.citation: Stat Med. 2000 Mar 15;19(5):649-63
references.pmid: 10700737
references.citation: Diabetologia. 2009 Sep;52(9):1881-8
references.pmid: 19590848
references.citation: Diabetologia. 2002 Mar;45(3):457-8
references.pmid: 11914757