Lack of association of CTLA-4 +49 A/G polymorphism with predisposition to type 1 diabetes in a cohort of Egyptian families

Abstract

BackgroundType 1 diabetes is one of the most common chronic childhood illnesses. Interplay between genetic susceptibility and environmental factors is thought to provide the fundamental element for the disease. Apart from the Major Histocompatibility locus which is the main contributor to risk susceptibility, more than 40 loci are recognized. One among these is the CTLA-4, however data from the literature are controversial. The aim of our study was to investigate the role of CTLA4 49 A/G as a risk susceptibility factor for the development of type 1 diabetes in a cohort of Egyptian families. Subjects and methodsThis is a case control study including 88 Egyptian families with one or more index cases (<18years). The control group comprised 369 healthy unrelated subjects with no family history of diabetes or autoimmune disease.Using PCR-RFLP methodology, CTLA4 49 A/G was analyzed in 738 samples representing 88 families (88 patients, 125 siblings and 156 parents) and 369 control. ResultsThe age of onset was 6days-12.5years with a mean of 5.3±3.6 and a median of 5years. The mode of presentation was classic symptoms in 51 and diabetic ketoacidosis in 37 cases. Twenty-two cases had a history of viral infection or exanthematous disease and four had associated autoimmune diseases. No significant differences were encountered between the different groups with regard to CTLA4 +49 A/G genotype or allele frequencies. Neither was there a relation between the various genotypes and age of onset or the mode of presentation. ConclusionsCTLA4 49 A/G polymorphism was not recognized as a risk susceptibility factor in our cohort. This may be attributed to the low co-incidence of autoimmune diseases. Up to our best knowledge, this is the first study involving families. We recommend that all studies performed on risk susceptibility to type 1 diabetes should include proper investigation for other autoimmune diseases to exclude their confounding effect on data analysis.