Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Cambridge Institute for Medical Research, University of Cambridge, Addenbrookes Hospital, Cambridge, U.K
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ABSTRACT |
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Development of diabetes in the BB rat involves at least three genes: Iddm1/lyp on chromosome 4, RT1u (at Iddm2) in the major histocompatibility complex (MHC) on chromosome 20, and a third unmapped gene (1,2). One unusual feature of this animal model is the severe lymphopenia that is essential for the development of the diabetic phenotype and that is inherited as a Mendelian trait (3). Life-long and profound T-cell lymphopenia is characterized by a reduction in peripheral CD4+ T-cells, an even greater reduction of CD8+ T-cells (4), and an almost total absence of RT6+ T-cells (5). The lymphopenia gene is involved in the regulation of apoptosis in the T-cell lineage and is, therefore, responsible for loss of critical T-cells, resulting in autoimmunity (6). Recently, two groups have independently shown, by positional cloning of Iddm1/lyp, that lymphopenia is due to a frameshift deletion in Ian4 (also called Ian5) of the immune-associated nucleotide (Ian)-related gene family (6,7), resulting in a truncated protein product. This deletion was only found in strains that have lymphopenia and diabetes (6). The human orthologue of Ian4 (IAN4L1) belongs to a family of at least 10 genes that encode GTP-binding proteins and are located in a 300-kb interval of human chromosome 7q36.
The KDP rat was derived as a substrain of the Long-Evans Tokushima lean (LETL) rat and shows 100% development of moderate to severe insulitis within 220 days of age (8,9). The LETL rat is characterized by sudden onset of polyuria, polyphagia, hyperglycemia, weight loss, and autoimmune destruction of pancreatic B-cells, while showing no significant T-cell lymphopenia and no sex-specific differences in rate of onset or severity (8). As with the BB rat, the KDP rat possesses the diabetogenic RT1u haplotype, adding to its relevance as a model of type 1 diabetes. In addition to the MHC, another unlinked locus, Iddm/kdp1, is essential in the development of moderate to severe insulitis and the onset of diabetes (10). Iddm/kdp1 has been mapped to a nonsense mutation in CBLB (Casitas B-lineage lymphoma b, or Cas-Br-M murine ecotropic retroviral transforming sequence b), a gene shown to have a role in the regulation of tyrosine kinase signaling pathways (1114). This mutation results in the removal of 484 amino acids, including the proline-rich and leucine zipper domains of the protein, and is specific to the KDP rat and the original LETL strain. It is not found in the nondiabetic KND (Komeda nondiabetic) or LETO (Long-Evans Tokushima Otsuka) strains (15). Homozygous mice generated to be deficient in Cblb develop spontaneous autoimmunity, characterized by T- and B-cell infiltration of multiple organs (16). Taken together, this evidence suggests that Cblb is probably the disease susceptibility gene at Iddm/Kdp1 and, consequently, a major susceptibility gene for diabetes in the rat.
We, therefore, resequenced both IAN4L1 and CBLB as candidates for human type 1 diabetes susceptibility. For IAN4L1, we resequenced the entire gene, covering 12.2 kb, comprising three exons and introns and 3 kb 3' and 5' of the gene in 32 type 1 diabetic subjects, identifying 30 single nucleotide polymorphisms (SNPs), 19 of which were novel (Table 1). Of the 30 SNPs, 7 were exonic: 1 in exon 1, which contains the 5' untranslated region, and 6 in exon 3. At CBLB, which extends over 230 kb (including three alternative, untranslated exon 1s), we resequenced 12.6 kb in 96 type 1 diabetic subjects, encompassing exons, intron/exon boundaries, and 2.5 kb 3' and 5' of the gene. From the CBLB sequence data, we identified 37 polymorphisms, of which 26 were novel (Table 2). These comprised 32 SNPs and five insertion/deletions. Of the 37 polymorphisms, 7 were exonic: 1 in each of exons 6, 9, 11, and 12 and 3 in exon 10. However, no nonsynonymous variants were observed in either gene, nor were there any other obvious candidates for variants that might change function or expression (Tables 1 and 2). For CBLB, we were unable to sequence exons 18, 1A, or 1B (although we covered 135 of 195 bp of exon 1C), and consequently, it was not possible to fully represent them directly with our haplotype tag SNP (htSNP) selection.
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Approaches to the statistical analysis of htSNPs have been described by Chapman et al. (17). It was demonstrated that in regions of strong LD, simple models considering only the main effects of htSNP genotypes were optimal or near optimal for detecting disease association. Consequently, the multilocus TDT is considered the most appropriate test. In stage 1, the multilocus TDT P value for association between type 1 diabetes and IAN4L1 was 0.484 and for CBLB was 0.692. Therefore, we did not proceed to genotype the additional set 2 families in either gene. To illustrate the predictions of ungenotyped markers that are possible using this new approach, Tables 1 and 2 include single-locus tests for all the common polymorphisms in set 1 families.
These results suggest that common alleles of IAN4L1 and CBLB do not contribute significantly to the familial clustering of human type 1 diabetes in the two populations analyzed. We cannot exclude the possibility that a common variant exists in either gene with an effect that is too small to be detected in a study of this size or that there is an unidentified polymorphism that is in much weaker LD with the htSNPs we analyzed. Had we genotyped all identified markers, our probability of detecting disease association would not have been substantially increased. Large introns and more extensive flanking DNA regions can be analyzed for association in the future by using the genome-wide SNP map that is under construction (18). By adopting an htSNP and a two-stage strategy, these candidate genes were quickly and economically evaluated for association with type 1 diabetes. This approach has allowed us to significantly reduce the genotyping burden (by 84% for CBLB and
87% for IAN4L1) and decrease turnaround time 1) by avoiding redundant genotyping of markers that can be imputed easily from the genotyping data of other markers and the patterns of LD across the gene and 2) by refraining from genotyping additional families in which there is limited possibility of obtaining an overall significant result. Although, in these data, common allelic variation in neither the IAN4L1 nor CBLB coding regions is associated with type 1 diabetes, genetic susceptibility data obtained from animal models can be directly applicable to humans, as has been found with the MHC (19) and CTLA4 (20). In addition, in our study, we have not excluded the possibility that alleles with frequencies <3% affect susceptibility to type 1 diabetes, and this remains a possibility. Whether or not exactly the same disease susceptibility genes in animal models are contributors to the familial clustering of disease in humans depends on the frequencies of causal alleles of the gene orthologues in human populations, a parameter that is subject to wide random variation. Nevertheless, even if a direct genetic susceptibility concordance is not found, the pathways that emerge from genetic studies of representative models and humans improve our understanding of disease mechanisms and how these might be modulated to reduce the risk of disease.
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RESEARCH DESIGN AND METHODS |
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SNP identification and genotyping.
Direct sequencing of nested PCR products from 96 type 1 diabetic individuals for CBLB and 32 for IAN4L1 was performed using an Applied Biosystems (ABI) 3700 capillary sequencer (Foster City, CA). Polymorphisms were identified using the Staden Package (http://www.mrc-lmb.cam.ac.uk/pubseq/) and mapped to the golden path sequence (NCBI build 33). htSNPs were selected from the polymorphisms with >3% minor allele frequency in our sequencing panel using Stata (http://www.stata.com) and the htSNP package available from http://www-gene.cimr.cam.ac.uk/clayton/software/stata/.
Genotyping was performed using either Taqman MGB chemistry (Applied Biosystems) (23) or the Invader biplex assay (Third Wave Technologies, Madison, WI) (24). All genotyping data were double scored to minimize error. All SNP sequences are in dbSNP; sequencing and genotyping data can be obtained upon request (http://www-gene.cimr.cam.ac.uk/todd/human_data.shtml).
Annotation.
CBLB (European Molecular Biology Laboratory [EMBL] accession nos. U26710, full-length human CBLB mRNA; U26711, truncated form 1, human CBLB, lacking leucine zipper mRNA; amd U26712, truncated form 2, human CBLB, lacking leucine zipper mRNA) and IAN4L1 (EMBL accession no. AK002158) were annotated locally, importing Ensembl information into a temporary ACeDB database. Here, the gene structure was verified following a more thorough Blast analysis and then reextracted from ACeDB in GFF format and submitted to a local Gbrowse database (National Center for Biotechnology Information build 33) (DIL annotations viewable at http://dil-gbrowse.cimr.cam.ac.uk).
Statistical analysis.
All statistical analyses were performed within Stata making specific use of the Genassoc package (http://www-gene.cimr.cam.ac.uk/clayton/software/stata). All genotyping data were assessed for, and found to be in, Hardy-Weinberg equilibrium (P > 0.05).
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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Address correspondence and reprint requests to John A. Todd, Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust/MRC Building, Addenbrookes Hospital, Cambridge CB2 2XY, U.K. E-mail: john.todd{at}cimr.cam.ac.uk
Received for publication September 24, 2003 and accepted in revised form October 31, 2003
htSNP, haplotype tag single nucleotide polymorphism; LD, linkage disequilibrium; MHC, major histocompatibility complex; SNP, single nucleotide polymorphism
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REFERENCES |
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