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The islet autoantibody titres: their clinical relevance in latent autoimmune diabetes in adults (LADA) and the classification of diabetes mellitus
Author(s) -
Van Deutekom A. W.,
Heine R. J.,
Simsek S.
Publication year - 2008
Publication title -
diabetic medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.474
H-Index - 145
eISSN - 1464-5491
pISSN - 0742-3071
DOI - 10.1111/j.1464-5491.2007.02316.x
Subject(s) - medicine , autoantibody , diabetes mellitus , type 1 diabetes , autoimmune diabetes , glutamate decarboxylase , population , clinical significance , immunology , endocrinology , antibody , enzyme , biochemistry , chemistry , environmental health
Latent autoimmune diabetes in the adult (LADA) is a slowly progressive form of autoimmune diabetes, characterized by diabetes‐associated autoantibody positivity. A recent hypothesis proposes that LADA consists of a heterogeneous population, wherein several subgroups can be identified based on their autoimmune status. A systematic review of the literature was carried out to appraise whether the clinical characteristics of LADA patients correlate with the titre and numbers of diabetes‐associated autoantibodies. We found that the simultaneous presence of multiple autoantibodies and/or a high‐titre anti‐glutamic acid decarboxylase (GAD)—compared with single and low‐titre autoantibody—is associated with an early age of onset, low fasting C‐peptide values as a marker of reduced pancreatic B‐cell function, a high predictive value for future insulin requirement, the presence of other autoimmune disorders, a low prevalence of markers of the metabolic syndrome including high body mass index, hypertension and dyslipidaemia, and a high prevalence of the genotype known to increase the risk of Type 1 diabetes. We propose a more continuous classification of diabetes mellitus, based on the finding that the clinical characteristics gradually change from classic Type 1 diabetes to LADA and finally to Type 2 diabetes. Future studies should focus on determining optimal cut‐off points of anti‐GAD for differentiating clinically relevant diabetes mellitus subgroups.