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J Autoimmun. 2007 Sep-Nov;29(2-3):69-77. Epub 2007 Jul 20.

Dissecting genetic heterogeneity in autoimmune thyroid diseases by subset analysis.

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  • 1Division of Endocrinology, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA. yaron.tomer@uc.edu

Abstract

Abundant epidemiological data point to a strong genetic susceptibility to the development of autoimmune thyroid diseases (AITD), Graves' disease (GD) and Hashimoto's thyroiditis (HT). However, identifying the AITD susceptibility genes has been confounded by significant genetic heterogeneity that exists in AITD. The goals of the present study were to dissect the genetic heterogeneity in AITD in order to identify novel AITD genes. We studied a dataset of 102 multiplex Caucasian AITD families (540 individuals) and divided them into three subsets: (1) families with young age of onset (AO< or =30), (2) families with females-only affected, and (3) Italian families. These subsets were analyzed separately for linkage with AITD in a whole genome screen. Four subset-specific loci were mapped: analyzing the families with AO< or =30, we identified a locus on 10q (linked with AITD) and a locus on Xp containing the FOXP3 gene (linked with GD); analysis of markers flanking the FOXP3 gene demonstrated association of one of the FOXP3 markers with juvenile GD in females (p=0.02); in the subset of families with females-only affected the thyroglobulin (Tg) gene locus was linked with AITD; and in the Italian subset, a novel locus on 3q was linked with GD. Finally, applying the predivided-sample test confirmed that all four loci were specific to the subsets. We conclude that distinct genes predispose to AITD in different subsets of patients. We have identified four subset-specific AITD loci, and two putative subset-specific AITD susceptibility genes; the FOXP3 gene in juvenile GD and the thyroglobulin gene in females with AITD. In view of the significant genetic heterogeneity observed in AITD, analyzing subsets is an efficient way to resolve heterogeneity and identify novel genes.

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