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.

Nutrient removal from wastewaters using high performance materials.

Return side streams from anaerobic digesters and dewatering facilities at wastewater treatment plants (WWTPs) contribute a significant proportion of the total nitrogen load on a mainstream process. Similarly, significant phosphate loads are also recirculated in biological nutrient removal (BNR) wastewater treatment plants. Ion exchange using a new material, known by the name MesoLite, shows strong potential for the removal of ammonia from these side streams and an opportunity to concurrently reduce phosphate levels. A pilot plant was designed and operated for several months on an ammonia rich centrate from a dewatering centrifuge at the Oxley Creek WWTP, Brisbane, Australia. The system operated with a detention time in the order of one hour and was operated for between 12 and 24 hours prior to regeneration with a sodium rich solution. The same pilot plant was used to demonstrate removal of phosphate from an abattoir wastewater stream at similar flow rates. Using MesoLite materials, >90% reduction of ammonia was achieved in the centrate side stream. A full-scale process would reduce the total nitrogen load at the Oxley Creek WWTP by at least 18%. This reduction in nitrogen load consequently improves the TKN/COD ratio of the influent and enhances the nitrogen removal performance of the biological nutrient removal process.

Controlling misdiagnosis errors in preimplantation genetic diagnosis: a comprehensive model encompassing extrinsic and intrinsic sources of error.

We have developed a mathematical model to explore accuracy of preimplantation genetic diagnosis (PGD) using single cell polymerase chain reaction (PCR). The model encompasses both extrinsic technical errors and intrinsic errors related to nuclear and chromosomal abnormalities. Using estimates for these errors, we have calculated the probability of a serious error (affected embryo diagnosed as unaffected) using a variety of strategies designed to increase the accuracy of PGD. Additional information from genotyping a linked marker or a second biopsied cell reduces the probability of replacing an affected embryo, while ensuring that sufficient unaffected embryos can be replaced. For a recessive disease, two genotypes are required to ensure a low probability of replacing an affected embryo (<1%) with a high proportion of unaffected embryos eligible for replacement (68%). These genotypes may be from a single cell with linked marker, or disease genotypes from two cells. PGD of a dominant disease is more difficult, as it relies on the amplification of a single copy of the mutation. Genotypes from two biopsied cells are required to ensure that a high proportion of unaffected embryos are eligible for replacement. This model can be used as a clinical tool to prioritize embryos for transfer in a PGD cycle.

The single-nucleotide polymorphism lottery: how useful are a few common SNPs in identifying disease-associated alleles?

It has been proposed that using association analysis of single nucleotide polymorphism (SNP) markers in candidate genes may be more successful in identifying disease susceptibility genes for complex diseases. Finding all the SNPs within a candidate gene and genotyping a large case-control cohort is a resource-intensive process. As linkage disequilibrium extends across small regions of the genome, the expectation is that a few common anonymous SNPs will be sufficient to detect functional disease-associated alleles. The aim of this investigation was to compare the ability of a number of family- and population-based association methods to identify known susceptibility loci using the Genetic Analysis Workshop 12 simulated data set. As expected, case-control methods were more likely to detect association with individual SNPs but family-based haplotyping methods appeared better able to localize the position of functional polymorphism.