Genome-wide pharmacogenetic investigation of a hepatic adverse event without clinical signs of immunopathology suggests an underlying immune pathogenesis

One of the major goals of pharmacogenetics is to elucidate mechanisms and identify patients at increased risk of adverse events (AEs). To date, however, there have been only a few successful examples of this type of approach. In this paper, we describe a retrospective case-control pharmacogenetic study of an AE of unknown mechanism, characterized by elevated levels of serum alanine aminotransferase (ALAT) during long-term treatment with the oral direct thrombin inhibitor ximelagatran. The study was based on 74 cases and 130 treated controls and included both a genome-wide tag single nucleotide polymorphism and large-scale candidate gene analysis. A strong genetic association between elevated ALAT and the MHC alleles DRB1(*)07 and DQA1(*)02 was discovered and replicated, suggesting a possible immune pathogenesis. Consistent with this hypothesis, immunological studies suggest that ximelagatran may have the ability to act as a contact sensitizer, and hence be able to stimulate an adaptive immune response.

Cost-effective analysis of candidate genes using htSNPs: a staged approach

We have previously shown that the selection of haplotype tag single nucleotide polymorphisms (htSNPs) and their statistical analysis in a multi-locus transmission/disequilibrium test (TDT) results in a more cost-effective genotyping strategy in disease association studies of genes by minimising redundancy due to linkage disequilibrium between SNPs. Further savings can be achieved by the use of a two-stage genotyping strategy. This approach is illustrated here in conjunction with the multi-locus TDT in determining whether common alleles of the immune regulatory genes RANK and its ligand TRANCE (RANKL) are associated with type 1 diabetes (T1D). A saving of approximately 75% of potential genotyping reactions could be made with minimal loss of power. There was little evidence from our analysis for association between the TRANCE and RANK genes and T1D in the populations tested.

IDDM2/insulin VNTR modifies risk conferred by IDDM1/HLA for development of Type 1 diabetes and associated autoimmunity

AIM/HYPOTHESIS

Type 1 diabetes (T1D) is an autoimmune disease with multiple susceptibility genes. The aim of this study was to determine whether combining IDDM1/HLA and IDDM2/ insulin( INS) 5' variable number of tandem repeat locus (VNTR) genotypes improves T1D risk assessment.

METHODS

Patients with T1D (n=488), control subjects (n=846), and offspring of parents with T1D (n=1122) were IDDM1 and IDDM2 genotyped. Offspring were followed for islet autoantibodies and T1D from birth until the age of 2 to 12 years.

RESULTS

Compared to the I/I INS VNTR genotype, the I/III and III/III genotypes reduced T1D risk conferred by IDDM1/HLA in all HLA genotype categories of the case-control cohort by 1.6-fold to three-fold. The highest T1D risk was associated with INS VNTR class I/I plus HLA DR3/DR4-DQ8 (20.4% in patients, 0.6% in control subjects) or HLA DR4-DQ8/DR4-DQ8 (6.3% in patients, 0.2% in control subjects). In the offspring, HLA DR3/DR4-DQ8 and DR4-DQ8/DR4-DQ8 conferred increased risk for early development of islet autoantibodies (14.6% and 12.9% by age 2 years). Offspring with these high risk IDDM1 genotypes plus the INS VNTR class I/I genotype (n=71; 6.3%) had the highest risk of developing islet autoantibodies (21.8% by age 2 years vs 8.9% in offspring with high risk IDDM1 plus INS VNTR class I/III or III/III genotypes, p<0.05) and T1D (8.5% by age 6 years vs 4.3%). Offspring who developed autoantibodies to multiple antigens had increased frequencies of both high risk IDDM1 and IDDM2 genotypes (p<0.0001), whereas offspring who developed autoantibodies to GAD only had increased frequencies of high risk IDDM1 and protective IDDM2 genotypes, suggesting that IDDM2 influences the autoimmune target specificity.

CONCLUSION/INTERPRETATION

Combining IDDM1 and IDDM2 genotyping identifies a minority of children with an increased T1D risk.

Identification of the sources of error in allele frequency estimations from pooled DNA indicates an optimal experimental design

Genotyping costs still preclude analysis of a comprehensive SNP map in thousands of individual subjects in the search for disease susceptibility loci. Allele frequency estimation in DNA pools from cases and controls offers a partial solution, but variance in these estimates will result in some loss of statistical power. However, there has been no systematic attempt to quantify the several sources of error in previous studies. We report an analysis of the magnitude of variance components of each experimental stage in DNA pooling studies, and find that a design based on the formation of numerous small pools of approximately 50 individuals is superior to the formation of fewer, larger pools and the replication of any of the experimental stages. We conclude that this approach may retain an effective sample size greater than 68% of the true sample size, whilst offering a 60-fold reduction in DNA usage and a greater than 30-fold saving in cost, compared to individual genotyping. The possibility of combining pooling with informed selection of haplotype tag SNPs is also considered. In this way further savings in efficiency may be possible by using pooled allele frequency estimates to infer haplotype frequencies and hence, allele frequencies at untyped markers.

Haplotype tagging for the identification of common disease genes

Genome-wide linkage disequilibrium (LD) mapping of common disease genes could be more powerful than linkage analysis if the appropriate density of polymorphic markers were known and if the genotyping effort and cost of producing such an LD map could be reduced. Although different metrics that measure the extent of LD have been evaluated, even the most recent studies have not placed significant emphasis on the most informative and cost-effective method of LD mapping-that based on haplotypes. We have scanned 135 kb of DNA from nine genes, genotyped 122 single-nucleotide polymorphisms (SNPs; approximately 184,000 genotypes) and determined the common haplotypes in a minimum of 384 European individuals for each gene. Here we show how knowledge of the common haplotypes and the SNPs that tag them can be used to (i) explain the often complex patterns of LD between adjacent markers, (ii) reduce genotyping significantly (in this case from 122 to 34 SNPs), (iii) scan the common variation of a gene sensitively and comprehensively and (iv) provide key fine-mapping data within regions of strong LD. Our results also indicate that, at least for the genes studied here, the current version of dbSNP would have been of limited utility for LD mapping because many common haplotypes could not be defined. A directed re-sequencing effort of the approximately 10% of the genome in or near genes in the major ethnic groups would aid the systematic evaluation of the common variant model of common disease.

Evaluation of single nucleotide polymorphism typing with invader on PCR amplicons and its automation

Large-scale pharmacogenetics and complex disease association studies will require typing of thousands of single-nucleotide polymorphisms (SNPs) in thousands of individuals. Such projects would benefit from a genotyping system with accuracy >99% and a failure rate <5% on a simple, reliable, and flexible platform. However, such a system is not yet available for routine laboratory use. We have evaluated a modification of the previously reported Invader SNP-typing chemistry for use in a genotyping laboratory and tested its automation. The Invader technology uses a Flap Endonuclease for allele discrimination and a universal fluorescence resonance energy transfer (FRET) reporter system. Three hundred and eighty-four individuals were genotyped across a panel of 36 SNPs and one insertion/deletion polymorphism with Invader assays using PCR product as template, a total of 14,208 genotypes. An average failure rate of 2.3% was recorded, mostly associated with PCR failure, and the typing was 99.2% accurate when compared with genotypes generated with established techniques. An average signal-to-noise ratio (9:1) was obtained. The high degree of discrimination for single base changes, coupled with homogeneous format, has allowed us to deploy liquid handling robots in a 384-well microtitre plate format and an automated end-point capture of fluorescent signal. Simple semiautomated data interpretation allows the generation of approximately 25,000 genotypes per person per week, which is 10-fold greater than gel-based SNP typing and microsatellite typing in our laboratory. Savings on labor costs are considerable. We conclude that Invader chemistry using PCR products as template represents a useful technology for typing large numbers of SNPs rapidly and efficiently.