Construction and analysis of tag single nucleotide polymorphism maps for six human-mouse orthologous candidate genes in type 1 diabetes
- Lisa M Maier†1Email author,
- Deborah J Smyth†1,
- Adrian Vella1,
- Felicity Payne1,
- Jason D Cooper1,
- Rebecca Pask1,
- Christopher Lowe1,
- John Hulme1,
- Luc J Smink1,
- Heather Fraser1,
- Carolyn Moule1,
- Kara M Hunter1,
- Giselle Chamberlain1,
- Neil Walker1,
- Sarah Nutland1,
- Dag E Undlien2,
- Kjersti S Rønningen3,
- Cristian Guja4,
- Constantin Ionescu-Tîrgovişte4,
- David A Savage5,
- David P Strachan6,
- Laurence B Peterson7,
- John A Todd1,
- Linda S Wicker1 and
- Rebecca C Twells1Email author
© Maier et al; licensee BioMed Central Ltd. 2005
Received: 01 December 2004
Accepted: 18 February 2005
Published: 18 February 2005
One strategy to help identify susceptibility genes for complex, multifactorial diseases is to map disease loci in a representative animal model of the disorder. The nonobese diabetic (NOD) mouse is a model for human type 1 diabetes. Linkage and congenic strain analyses have identified several NOD mouse Idd (insulin dependent diabetes) loci, which have been mapped to small chromosome intervals, for which the orthologous regions in the human genome can be identified. Here, we have conducted re-sequencing and association analysis of six orthologous genes identified in NOD Idd loci: NRAMP1/SLC11A1 (orthologous to Nramp1/Slc11a1 in Idd5.2), FRAP1 (orthologous to Frap1 in Idd9.2), 4-1BB/CD137/TNFRSF9 (orthologous to 4-1bb/Cd137/Tnrfrsf9 in Idd9.3), CD101/IGSF2 (orthologous to Cd101/Igsf2 in Idd10), B2M (orthologous to B2m in Idd13) and VAV3 (orthologous to Vav3 in Idd18).
Re-sequencing of a total of 110 kb of DNA from 32 or 96 type 1 diabetes cases yielded 220 single nucleotide polymorphisms (SNPs). Sixty-five SNPs, including 54 informative tag SNPs, and a microsatellite were selected and genotyped in up to 1,632 type 1 diabetes families and 1,709 cases and 1,829 controls.
None of the candidate regions showed evidence of association with type 1 diabetes (P values > 0.2), indicating that common variation in these key candidate genes does not play a major role in type 1 diabetes susceptibility in the European ancestry populations studied.
Type 1 diabetes is a common, multifactorial disease believed to be caused in a proportion of cases by an autoimmune destruction of pancreatic β-cells by an inflammatory infiltrate comprising T lymphocytes, dendritic cells and macrophages. This process results from a complex interaction between genetic and environmental risk factors. Genetically, it is under the control of the major histocompatibility complex (MHC)  and many other genes of smaller effect and mostly unknown identity.
A murine model of type 1 diabetes, the NOD mouse, spontaneously develops an autoimmune-mediated diabetes that has many similarities to the human disease. It is likely that components of the pathophysiology and genetic predisposition are conserved across species, and indeed two loci have already been shown to affect type 1 diabetes susceptibility in both species, namely the immunoregulatory MHC HLA class II and CTLA-4 genes. The other causative gene(s) in the known Idd regions controlling type 1 diabetes susceptibility in the NOD mouse could also determine susceptibility in humans, even though this depends on the frequency of susceptibility alleles in human populations, which affects statistical power, and that the correct candidate gene has been chosen from the Idd interval. These Idd intervals might contain many genes, including several involved in the immune response . Nevertheless, in contrast to studies in humans based on linkage, the localisation of a type 1 diabetes locus to a specific chromosome region in the mouse genome using congenic strain breeding defines with certainty a set of genes, one or more of which is definitely a susceptibility gene [3, 4].
The central importance of T cell development and function in type 1 diabetes is evident from the susceptibility genes identified so far. The MHC class II genes are important etiologically in two rat models of type 1 diabetes, the Biobreeding (BB) and KDP strains [5, 6], the NOD mouse strain  and in humans , with their essential function not only in T cell activation and expansion but also in T cell repertoire formation in the thymus and clonal deletion of autoreactive cells. The BB rat type 1 diabetes susceptibility locus Ian4/Iddm1  affects T lymphocyte development whereas the Cblb (KDP rat)  and CTLA4  (in humans and NOD mice) susceptibility genes highlight the importance of the regulation of T cell activation, expansion and homeostasis in the periphery, and perhaps in the thymus as well.
NOD mouse Idd loci, location of their human orthologous regions, and selected functional candidate genes.
Interval size (Mb)
Number of genes
Functional candidate genes in mouse Idd intervals
Location of human orthologous region
Human orthologue genes
Known gene function and previously reported disease associations
Endosomal/lysosomal acidification and associated with protection from infectious disease and susceptibility to autoimmune disease
FKBP12-rapamycin associated protein of mTOR. Candidate tumour suppressor gene, whose function in apoptosis is influenced by allelic variation
Role in enhancing and regulating CD4+, CD8+ T cells and dendritic cells
Co-stimulatory receptor of T cells
Required for antigen presentation by MHC class I molecules and the development of diabetes in NOD mice
Guanine nucleotide exchange factor involved in signalling of T and B cell receptors
Results and discussion
A tag SNP approach to test for association was adopted for all genes, except for 4-1BB , in order to achieve cost-savings in genotyping. A multi-locus test was used to evaluate the association between type 1 diabetes and the tag SNPs due to linkage disequilibrium (LD) with one or more causal variants . Coding and untranslated regions of NRAMP1 (MIM 600266), FRAP1 (MIM 601231), 4-1BB (MIM 602250), CD101 (MIM 604516), B2M (MIM 109700) and VAV3 (MIM 605541) were re-sequenced in 32 or 96 randomly chosen UK white patients with type 1 diabetes to identify SNPs and for the selection of tag SNPs. As LD between 4-1BB SNPs was weak, eight out of nine common SNPs were genotyped (minor allele frequency, MAF ≥ 0.03; one SNP could not be genotyped due to assay technical difficulties) and analysed using single-locus tests.
Summary of the re-sequencing study. Gene size, number of exons, amount of re-sequenced DNA for each gene (including 5' and 3' regions of gene), sequencing panel, and number of SNPs identified.
Genomic size (kb)
Re-sequenced region (kb)
n cases re-sequenced
Two common nsSNPs (MAF ≥ 0.05; DIL1521/rs7528153 and DIL3809/ss23142432) from VAV3 and a microsatellite from NRAMP1 were genotyped a priori in the whole family collection (step 1 and 2) and a single nsSNP from CD101 in step 1 families only (DIL3794/rs3754112). The nsSNP DIL3810/ss23142433 in VAV3 was not tested because it was in quite strong LD with DIL3809/ss23142432 (R2 = 0.64), so that only DIL3809/ss23142432 was genotyped. Note that in our tag approach, the two VAV3 nsSNPs (DIL1521/rs7528153 and DIL3809/ss23142432) were chosen deliberately as tag SNPs.
Study design. Lengths of re-sequenced genomic regions, and number of tag SNPs or single SNPs genotyped in a pragmatic two-step genotyping design for NRAMP1, 4-1BB, FRAP1, CD101, B2M, and VAV3.
Re-sequenced region (kb)
n common SNPs*
n tag SNPs
Genotyping strategy (step 1 → step 2)
Case-control → Family set 1+2
Family set 1
Family set 1
Family set 1
Case-control → Family set 1
19 (block 1)
18 (block 2)
15 (block 3)
7 (block 1)
11 (block 2)
10 (block 3)
Family set 1
Disease association results. Multi-locus test P values, lengths of re-sequenced genomic regions, and number of tag SNPs or single SNPs genotyped in a two-step genotyping design for NRAMP1, 4-1BB, FRAP1, CD101, B2M, and VAV3.
Multilocus test P value/ Single-locus TDT P value
Combined test P value
Family set 1
Family set 1 + 2
0.26 (block 1)
0.80 (block 2)
0.86 (block 3)
Association analysis of non-synonymous SNPs. SNPs with allele frequencies above 0.05 and the NRAMP1 (GT)n microsatellite in up to 1,476 families with at least one affected offspring. N, number; T, number of transmissions; NT, number of untransmitted alleles; %T, percentage transmission of minor allele from heterozygous parents to type 1 diabetes offspring (obtained by transmission/disequilibrium test (TDT)); GTRR, genotype relative risk; P, probability value (two-sided).
Amino acid change/ alleles
Minor allele frequency
With regards to our association study in humans, intronic and potential regulatory regions were not sequenced in the candidate genes since these cover large genomic regions, which will have to wait for much more extensive polymorphism maps . For example, for VAV3, which spans almost 400 kb, less than 10% of the genomic region of VAV3 was re-sequenced to identify SNPs. The general importance of intronic and intergenic regulatory sequences as candidates for disease susceptibility is well recognised. Hence, potential unidentified causal variants in introns or flanking regions of the genes may have been missed, and remain a target for future analyses. Despite finding no evidence of association, it remains possible that there exists a common disease variant in one or more of the six candidate genes tested, which either has an effect smaller than would be detected with this study or is in much weaker LD with the tag SNPs than any other SNP known to us .
Finally, the possibility of one or more rare disease variants in a locus needs to be considered . The best candidates for rare disease variants in the six genes studied here were thus genotyped in an expanded case-control collection of up to 3,704 type 1 diabetes cases and 3,930 controls: DIL5202/ss23142243 causes a non-conservative change in NRAMP (Asp543Asn, MAF = 0.02) and DIL3799/ss23142349 in CD101 (Val839Ile; MAF = 0.03). For both SNPs, P values above 0.05 were obtained (P = 0.19 for DIL5202/ss23142243 and P = 0.80 for DIL3799/ss23142349), therefore, making it less likely that these rare variants contribute to susceptibility to type 1 diabetes. Nevertheless, causal variants with MAFs less than 0.01  may well remain undetected in our re-sequencing panels of 32 or 96 case DNAs. However, the re-sequencing of several hundred cases and controls is beyond the scope of the present study in which we have investigated variants with MAF ≥ 0.03.
Taken together, these data make an association between type 1 diabetes and common variation in coding and untranslated regions of the six functional candidate genes in the investigated human-mouse orthologue regions less likely. Several possibilities may account for this. A gene (or several genes) in an Idd interval may account for disease susceptibility in the NOD mouse, but the human orthologous region may lack this susceptibility variant. The scenario, in which candidate genes in the NOD Idd interval may not necessarily be harbouring a functional, causal variant in their human orthologue genes, was discussed previously . It is also possible that the selected candidate gene in the Idd interval may not be the gene causing susceptibility to disease.
The tag SNP maps described here will be useful for association studies of other diseases. They will be integrated into future SNP maps encompassing the entire orthologous regions and all regulatory sequences and genes encoded within them.
All family members were white and of European ancestral origin. The type 1 diabetes families comprised two parents and a least one affected child. The 748 type 1 diabetes families used in 'step 1' were as described previously : 472 UK Warren 1 multiplex and 276 multiplex Human Biological Data Interchange families ascertained in the U.S.A. The case-control DNA set for the tag SNP approach consisted of 1,709 Caucasian type 1 diabetes cases, which were recruited from across Britain in the Juvenile Diabetes Research Foundation/Wellcome Trust funded UK Genetic Resource Investigating Diabetes (GRID) study , and 1,829 population-based controls from the 1958 British Birth Cohort (BBC) . The mean age-at-onset of the cases, with almost all under 16 years of age at diagnosis, is 7.5 years (with a standard deviation of 4 years). The 1958 BBC controls are part of an ongoing longitudinal study and the subjects are British citizens born in a particular week in 1958. In order to test association for type 1 diabetes susceptibility and the rare variants in CD101 and NRAMP1, DIL3799/ss23142349 and DIL5202/ss23142243, a total of 3,704 type 1 diabetes cases and 3,930 controls were used.
For 'step 2' genotyping of NRAMP1, the 748 type 1 diabetes families described above were used in addition to 343 multiplex/simplex families from the UK, 159 Norwegian simplex families, 322 Romanian simplex families, and 60 multiplex families from the USA totalling the combined DNA sets to 1,632 type 1 diabetes families, as described previously .
Nested PCR products from DNA from 96 or 32 type 1 diabetes patients were sequenced using an Applied Biosystems (ABI) 3700 capillary sequencer (Foster City, CA), and SNPs identified using the Staden Package .
SNPs were genotyped using the Invader® assay (Third Wave Technologies, Inc. Madison WI)  and TaqMan MGB chemistry (ABI) . The NRAMP1 microsatellite was genotyped on an ABI3700 sequencer using fluorescent primers as previously described . Full details of primers and probes used for genotyping are available upon request. All genotyping data was double-scored independently.
Annotation of NRAMP1 (European Molecular Biology Laboratory [EMBL] accession numbers D50402, D50403, BC041787, L32185, BC033754), FRAP1 (UO88966), 4-1BB (UO3387), CD101 (Z33642), B2M (BC032589) and VAV3 (AF118887, VAV3; AF118886, VAV3β; AF118887, VAV3.1) was performed by importing Ensembl information into a temporary ACeDB database as described in Burren et al. . After confirmation of gene structures by BLAST analysis, these were re-extracted in GFF format and submitted to a local Gbrowse database (National Center for Biotechnology Information build 34) (DIL annotations viewable at T1DBase .
The program for the selection of tag SNPs  and association analysis used here are implemented in the Stata statistical system and may be downloaded from our website . All genotyping data were in Hardy-Weinberg equilibrium (P > 0.05).
This work was funded by the Wellcome Trust and the Juvenile Diabetes Research Foundation International. L.M.M. was the recipient of a Wellcome Trust Prize Studentship. A.V. was a Mayo Foundation Scholar. We thank the Human Biological Data Interchange and Diabetes U.K. for USA and U.K. multiplex families, respectively and the Norwegian Study Group for Childhood Diabetes for the collection of Norwegian families. We acknowledge use of DNA from the 1958 British Birth Cohort collection, funded by the Medical Research Council grant G0000934 and Wellcome Trust grant 068545/Z/02. DNA samples were prepared by Jayne Hutchings, Gillian Coleman, Trupti Mistry, Kirsi Bourget, Sally Clayton, Matthew Hardy, Jennifer Keylock, Pamela Lauder, Meeta Maisuria, William Meadows, Meera Sebastian, Sarah Wood, The Avon Longitudinal Study of Parents and Children laboratory in Bristol, including Susan Ring, Wendy McArdle, Richard Jones, for preparing DNA samples.
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