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.     

Genome-wide association study identifies multiple loci influencing human serum metabolite levels

Nuclear magnetic resonance assays allow for measurement of a wide range of metabolic phenotypes. We report here the results of a GWAS on 8,330 Finnish individuals genotyped and imputed at 7.7 million SNPs for a range of 216 serum metabolic phenotypes assessed by NMR of serum samples. We identified significant associations (P < 2.31 × 10(-10)) at 31 loci, including 11 for which there have not been previous reports of associations to a metabolic trait or disorder. Analyses of Finnish twin pairs suggested that the metabolic measures reported here show higher heritability than comparable conventional metabolic phenotypes. In accordance with our expectations, SNPs at the 31 loci associated with individual metabolites account for a greater proportion of the genetic component of trait variance (up to 40%) than is typically observed for conventional serum metabolic phenotypes. The identification of such associations may provide substantial insight into cardiometabolic disorders.     

Points of View: A Conceptual Space Approach

Points of view are a central phenomenon in human cognition. Although the concept of point of view is ambiguous, there exist common elements in different notions. A point of view is a certain way to look at things around us. In conceptual points of view, things are looked at or interpreted through conceptual lenses. Conceptual points of view are important for epistemology, cognitive science, and philosophy of science. In this article, a new method to formalize conceptual points of view is introduced. It is based on the conceptual space approach, where concepts are regions of multi-dimensional quality spaces. Points of view, as defined in this article, consist of a selection of relevant dimensions, referred to here as determinables, and of a certain supposition, referred to here as a theory, about the subject content. After considering some early efforts to formalize points of view, the notion of conceptual space is defined and explored. One concept of point of view is defined and developed in the framework of conceptual space, and a new logic for points of view is also outlined. The problem of mind–body correlation is discussed as an example of the application of the notion of points of view. To conclude, the meaning and applications of the new concepts and tools developed in the article are discussed.     

Susceptibility loci for intracranial aneurysm in European and Japanese populations

Stroke is the world's third leading cause of death. One cause of stroke, intracranial aneurysm, affects approximately 2% of the population and accounts for 500,000 hemorrhagic strokes annually in mid-life (median age 50), most often resulting in death or severe neurological impairment. The pathogenesis of intracranial aneurysm is unknown, and because catastrophic hemorrhage is commonly the first sign of disease, early identification is essential. We carried out a multistage genome-wide association study (GWAS) of Finnish, Dutch and Japanese cohorts including over 2,100 intracranial aneurysm cases and 8,000 controls. Genome-wide genotyping of the European cohorts and replication studies in the Japanese cohort identified common SNPs on chromosomes 2q, 8q and 9p that show significant association with intracranial aneurysm with odds ratios 1.24-1.36. The loci on 2q and 8q are new, whereas the 9p locus was previously found to be associated with arterial diseases, including intracranial aneurysm. Associated SNPs on 8q likely act via SOX17, which is required for formation and maintenance of endothelial cells, suggesting a role in development and repair of the vasculature; CDKN2A at 9p may have a similar role. These findings have implications for the pathophysiology, diagnosis and therapy of intracranial aneurysm.     

The same sequence variant on 9p21 associates with myocardial infarction, abdominal aortic aneurysm and intracranial aneurysm

Recently, two common sequence variants on 9p21, tagged by rs10757278-G and rs10811661-T, were reported to be associated with coronary artery disease (CAD) and type 2 diabetes (T2D), respectively. We proceeded to further investigate the contributions of these variants to arterial diseases and T2D. Here we report that rs10757278-G is associated with, in addition to CAD, abdominal aortic aneurysm (AAA; odds ratio (OR) = 1.31, P = 1.2 x 10(-12)) and intracranial aneurysm (OR = 1.29, P = 2.5 x 10(-6)), but not with T2D. This variant is the first to be described that affects the risk of AAA and intracranial aneurysm in many populations. The association of rs10811661-T to T2D replicates in our samples, but the variant does not associate with any of the five arterial diseases examined. These findings extend our insight into the role of the sequence variant tagged by rs10757278-G and show that it is not confined to atherosclerotic diseases.     

Crossover clustering and rapid decay of linkage disequilibrium in the Xp/Yp pseudoautosomal gene SHOX

Crossover between the human sex chromosomes during male meiosis is restricted to the terminal pseudoautosomal pairing regions. An obligatory exchange occurs in PAR1, an Xp/Yp pseudoautosomal region of 2.6 Mb, which creates a male-specific recombination 'hot domain' with a recombination rate that is about 20 times higher than the genome average. Low-resolution analysis of PAR1 suggests that crossovers are distributed fairly randomly. By contrast, linkage disequilibrium (LD) and sperm crossover analyses indicate that crossovers in autosomal regions tend to cluster into 'hot spots' of 1-2 kb that lie between islands of disequilibrium of tens to hundreds of kilobases. To determine whether at high resolution this autosomal pattern also applies to PAR1, we have examined linkage disequilibrium over an interval of 43 kb around the gene SHOX. Here we show that in northern European populations, disequilibrium decays rapidly with physical distance, which is consistent with this interval of PAR1 being recombinationally active in male meiosis. Analysis of a subregion of 9.9 kb in sperm shows, however, that crossovers are not distributed randomly, but instead cluster into an intense recombination hot spot that is very similar in morphology to autosomal hot spots. Thus, PAR1 crossover activity may be influenced by male-specific hot spots that are highly suitable for characterization by sperm DNA analysis.