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http://purl.uniprot.org/citations/21744463http://www.w3.org/1999/02/22-rdf-syntax-ns#typehttp://purl.uniprot.org/core/Journal_Citation
http://purl.uniprot.org/citations/21744463http://www.w3.org/2000/01/rdf-schema#comment"

Background

Type 1 diabetes (T1D) is a clinically heterogeneous disease. The presence of associated autoimmune diseases (AAIDs) may represent a distinct form of autoimmune diabetes, with involvement of specific mechanisms. The aim of this study was to find predictors of AAIDs in the Type 1 Diabetes Genetics Consortium data set.

Methods

Three thousand two hundred and sixty-three families with at least two siblings with T1D were included. Clinical information was obtained using questionnaires, anti-GAD (glutamic acid decarboxylase) and anti-protein tyrosine phosphatase (IA-2) were measured and human leukocyte antigen (HLA) genotyping was performed. Siblings with T1D with and without AAIDs were compared and a multivariate regression analysis was performed to find predictors of AAIDs. T1D-associated HLA haplotypes were defined as the four most susceptible and protective, respectively.

Results

One or more AAIDs were present in 14.4% of the T1D affected siblings. Age of diabetes onset, current age and time since diagnosis were higher, there was a female predominance and more family history of AAIDs in the group with AAIDs, as well as more frequent anti-GAD and less frequent anti-IA-2 antibodies. Risk and protective HLA haplotype distributions were similar, though DRB1*0301-DQA1*0501-DQB1*0201 was more frequent in the group with AAIDs. In the multivariate analysis, female gender, age of onset, family history of AAID, time since diagnosis and anti-GAD positivity were significantly associated with AAIDs.

Conclusions

In patients with T1D, the presence of AAIDs is associated with female predominance, more frequent family history of AAIDs, later onset of T1D and more anti-GAD antibodies, despite longer duration of the disease. The predominance of certain HLA haplotypes suggests that specific mechanisms of disease may be involved."xsd:string
http://purl.uniprot.org/citations/21744463http://purl.org/dc/terms/identifier"doi:10.1002/dmrr.1189"xsd:string
http://purl.uniprot.org/citations/21744463http://purl.uniprot.org/core/author"Santana A."xsd:string
http://purl.uniprot.org/citations/21744463http://purl.uniprot.org/core/author"Wagner A.M."xsd:string
http://purl.uniprot.org/citations/21744463http://purl.uniprot.org/core/author"Mauricio D."xsd:string
http://purl.uniprot.org/citations/21744463http://purl.uniprot.org/core/author"Hernndez M."xsd:string
http://purl.uniprot.org/citations/21744463http://purl.uniprot.org/core/author"Novoa J."xsd:string
http://purl.uniprot.org/citations/21744463http://purl.uniprot.org/core/author"Wiebe J.C."xsd:string
http://purl.uniprot.org/citations/21744463http://purl.uniprot.org/core/date"2011"xsd:gYear
http://purl.uniprot.org/citations/21744463http://purl.uniprot.org/core/name"Diabetes Metab Res Rev"xsd:string
http://purl.uniprot.org/citations/21744463http://purl.uniprot.org/core/pages"493-498"xsd:string
http://purl.uniprot.org/citations/21744463http://purl.uniprot.org/core/title"Predictors of associated autoimmune diseases in families with type 1 diabetes: results from the Type 1 Diabetes Genetics Consortium."xsd:string
http://purl.uniprot.org/citations/21744463http://purl.uniprot.org/core/volume"27"xsd:string
http://purl.uniprot.org/citations/21744463http://www.w3.org/2004/02/skos/core#exactMatchhttp://purl.uniprot.org/pubmed/21744463
http://purl.uniprot.org/citations/21744463http://xmlns.com/foaf/0.1/primaryTopicOfhttps://pubmed.ncbi.nlm.nih.gov/21744463
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http://purl.uniprot.org/uniprot/#_A0A0A7C853-mappedCitation-21744463http://www.w3.org/1999/02/22-rdf-syntax-ns#objecthttp://purl.uniprot.org/citations/21744463