Pharmaco-metabonomic phenotyping and personalized drug treatment

There is a clear case for drug treatments to be selected according to the characteristics of an individual patient, in order to improve efficacy and reduce the number and severity of adverse drug reactions. However, such personalization of drug treatments requires the ability to predict how different individuals will respond to a particular drug/dose combination. After initial optimism, there is increasing recognition of the limitations of the pharmacogenomic approach, which does not take account of important environmental influences on drug absorption, distribution, metabolism and excretion. For instance, a major factor underlying inter-individual variation in drug effects is variation in metabolic phenotype, which is influenced not only by genotype but also by environmental factors such as nutritional status, the gut microbiota, age, disease and the co- or pre-administration of other drugs. Thus, although genetic variation is clearly important, it seems unlikely that personalized drug therapy will be enabled for a wide range of major diseases using genomic knowledge alone. Here we describe an alternative and conceptually new 'pharmaco-metabonomic' approach to personalizing drug treatment, which uses a combination of pre-dose metabolite profiling and chemometrics to model and predict the responses of individual subjects. We provide proof-of-principle for this new approach, which is sensitive to both genetic and environmental influences, with a study of paracetamol (acetaminophen) administered to rats. We show pre-dose prediction of an aspect of the urinary drug metabolite profile and an association between pre-dose urinary composition and the extent of liver damage sustained after paracetamol administration.     

Evidence for lateral gene transfer between Archaea and bacteria from genome sequence of Thermotoga maritima.

The 1,860,725-base-pair genome of Thermotoga maritima MSB8 contains 1,877 predicted coding regions, 1,014 (54%) of which have functional assignments and 863 (46%) of which are of unknown function. Genome analysis reveals numerous pathways involved in degradation of sugars and plant polysaccharides, and 108 genes that have orthologues only in the genomes of other thermophilic Eubacteria and Archaea. Of the Eubacteria sequenced to date, T. maritima has the highest percentage (24%) of genes that are most similar to archaeal genes. Eighty-one archaeal-like genes are clustered in 15 regions of the T. maritima genome that range in size from 4 to 20 kilobases. Conservation of gene order between T. maritima and Archaea in many of the clustered regions suggests that lateral gene transfer may have occurred between thermophilic Eubacteria and Archaea.     

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.     

Treatment-specific changes in gene expression discriminate in vivo drug response in human leukemia cells

To elucidate the genomics of cellular responses to cancer treatment, we analyzed the expression of over 9,600 human genes in acute lymphoblastic leukemia cells before and after in vivo treatment with methotrexate and mercaptopurine given alone or in combination. Based on changes in gene expression, we identified 124 genes that accurately discriminated among the four treatments. Discriminating genes included those involved in apoptosis, mismatch repair, cell cycle control and stress response. Only 14% of genes that changed when these medications were given as single agents also changed when they were given together. These data indicate that lymphoid leukemia cells of different molecular subtypes share common pathways of genomic response to the same treatment, that changes in gene expression are treatment-specific and that gene expression can illuminate differences in cellular response to drug combinations versus single agents.     

Identification of human CD4 residues affecting class II MHC versus HIV-1 gp120 binding

Interactions of CD4 with the class II major histocompatibility complex (MHC) are crucial during thymic ontogeny and subsequently for helper and cytotoxic functions of CD4+CD8- T lymphocytes. CD4 is the receptor for the T-lymphotropic human immunodeficiency virus and binds its envelope glycoprotein, gp120. The residues involved in gp120 binding have been localized to a region within the immunoglobulin-like domain I of CD4, which corresponds to CDR2 of an immunoglobulin variable region, but the CD4 residues important in MHC class II interaction have not been characterized. Here, using a cell-binding assay dependent specifically on the CD4-MHC class II association, we analyse the effects of mutations in CD4 on class II versus gp120 binding. Mutations in CDR2 that destroy gp120 binding affect CD4-MHC class II binding similarly. In addition, binding of soluble gp120 to CD4-transfected cells abrogates their ability to interact with class II-bearing B lymphocytes. In contrast, other mutations within domains I or II that have no effect on gp120 binding eliminate or substantially decrease class II interaction. Thus, the CD4 binding site for class II MHC is more complex than the gp120 binding site, possibly reflecting a broader area of contact with the former ligand and a requirement for appropriate juxtaposition of the two N-terminal domains. The ability of gp120 to inhibit the binding of class II MHC to CD4 could be important in disrupting normal T-cell physiology, acting both to inhibit immune responses and to prevent differentiation of CD4+CD8+ thymocytes into CD4+CD8- T lymphocytes.     

A genome-wide association study of nonsynonymous SNPs identifies a type 1 diabetes locus in the interferon-induced helicase (IFIH1) region

In this study we report convincing statistical support for a sixth type 1 diabetes (T1D) locus in the innate immunity viral RNA receptor gene region IFIH1 (also known as mda-5 or Helicard) on chromosome 2q24.3. We found the association in an interim analysis of a genome-wide nonsynonymous SNP (nsSNP) scan, and we validated it in a case-control collection and replicated it in an independent family collection. In 4,253 cases, 5,842 controls and 2,134 parent-child trio genotypes, the risk ratio for the minor allele of the nsSNP rs1990760 A --> G (A946T) was 0.86 (95% confidence interval = 0.82-0.90) at P = 1.42 x 10(-10).     

Methods for increasing sensitivity in immunoelectrophoresis

Résumé On décrit 2 modifications apportées à la méthode d'immunoélectrophorèse. L'une d'elles comprend l'électrophorèse dans 2 sens, aux pH divers, en milieu gélifié suivie par l'analyse immunologique, permettant une définition plus avantageuse. L'autre comprend l'électrophorèse sur un fil de rayonne ou d'acétate de cellulose suivie par l'analyse immunologique en milieu gélifié, permettant l'analyse des quantités d'antigène à partir de 3 µg.