No abstract

Geographic patterns of genetic variation, including variation at drug metabolizing enzyme (DME) loci and drug targets, indicate that geographic structuring of inter-individual variation in drug response may occur frequently. This raises two questions: how to represent human population genetic structure in the evaluation of drug safety and efficacy, and how to relate this structure to drug response. We address these by (i) inferring the genetic structure present in a heterogeneous sample and (ii) comparing the distribution of DME variants across the inferred genetic clusters of individuals. We find that commonly used ethnic labels are both insufficient and inaccurate representations of the inferred genetic clusters, and that drug-metabolizing profiles, defined by the distribution of DME variants, differ significantly among the clusters. We note, however, that the complexity of human demographic history means that there is no obvious natural clustering scheme, nor an obvious appropriate degree of resolution. Our comparison of drug-metabolizing profiles across the inferred clusters establishes a framework for assessing the appropriate level of resolution in relating genetic structure to drug response.

Association studies are widely seen as the most promising approach for finding polymorphisms that influence genetically complex traits, such as common diseases and responses to their treatment. Considerable interest has therefore recently focused on the development of methods that efficiently screen genomic regions or whole genomes for gene variants associated with complex phenotypes. One key element in this search is the use of linkage disequilibrium to gain maximal information from typing a selected subset of highly informative single-nucleotide polymorphism (SNP) markers, now often called "tagging SNPs" (tSNPs). Probably the most common approach to linkage-disequilibrium gene mapping involves a three-step program: (1) characterization of the haplotype structure in candidate genes or genomic regions of interest, (2) identification of tSNPs sufficient to represent the most common haplotypes, and (3) typing of tSNPs in clinical material. Early definitions of tSNPs focused on the amount of haplotype diversity that they explained. To select tSNPs that would have maximal power in a genetic association study, however, we have developed optimization criteria based on the r2 measure of association and have compared these with other criteria based on the haplotype diversity. To evaluate the full program and to assess how well the selected tags are likely to perform, we have determined the haplotype structure and have assessed tSNPs in the SCN1A gene, an important candidate gene for sporadic epilepsy. We find that as few as four tSNPs are predicted to maintain a consistently high r2 value with all other common SNPs in the gene, indicating that the tags could be used in an association study with only a modest reduction in power relative to direct assays of all common SNPs. This implies that very large case-control studies can be screened for variation in hundreds of candidate genes with manageable experimental effort, once tSNPs are identified. However, our results also show that tSNPs identified in one population may not necessarily perform well in another, indicating that the preliminary study to identify tSNPs and the later case-control study should be performed in the same population. Our results also indicate that tSNPs will not easily identify discrepant SNPs, which lie on importantly discriminating but apparently short genealogical branches. This could significantly complicate tagging approaches for phenotypes influenced by variants that have experienced positive selection.

We have analyzed the maternally inherited mitochondrial DNA from each of nine geographically separated Jewish groups, eight non-Jewish host populations, and an Israeli Arab/Palestinian population, and we have compared the differences found in Jews and non-Jews with those found using Y-chromosome data that were obtained, in most cases, from the same population samples. The results suggest that most Jewish communities were founded by relatively few women, that the founding process was independent in different geographic areas, and that subsequent genetic input from surrounding populations was limited on the female side. In sharp contrast to this, the paternally inherited Y chromosome shows diversity similar to that of neighboring populations and shows no evidence of founder effects. These sex-specific differences demonstrate an important role for culture in shaping patterns of genetic variation and are likely to have significant epidemiological implications for studies involving these populations. We illustrate this by presenting data from a panel of X-chromosome microsatellites, which indicates that, in the case of the Georgian Jews, the female-specific founder event appears to have resulted in elevated levels of linkage disequilibrium.

Patients with advanced chronic kidney disease (CKD), especially those on long-term dialysis, often suffer from muscle wasting and excessive fatigue. It is known that inactivity, muscle wasting and reduced physical functioning are associated with increased mortality in CKD. Known causes include uraemic myopathy and neuropathy, inactivity, and anaemia. Exercise in patients receiving regular dialysis treatment for end-stage renal disease was first introduced 3 decades ago, but is still only offered in a minority of renal units around the world, despite a significant body of evidence to support its use. Work is needed to increase awareness of the potential benefits of increased physical activity for patients with advanced CKD. This review summarizes the mechanisms of exercise intolerance and debility in advanced CKD patients, the methods used for the estimation of functional capacity, the options currently available for exercise training, and their influence on the well-being of this group of patients.