Current Pharmacogenomics - Volume 5, Issue 1, 2007

Several enzymes belonging to the CYP450 group are involved in the biosynthesis and metabolism of estrogen. Polymorphisms of the genes encoding for these enzymes have been linked to hormone-related diseases, notably breast cancer. These associations are based on the notion that certain variants of these enzymes have altered activity resulting in an alteration in estrogenic state, which in turn leads to differences in the risk for hormone-related disorders. Recent studies have indicated that these same polymorphisms are also important determinants of bone mineral density (BMD) and osteoporosis, another hormone-dependent condition. To name some, certain polymorphisms in the CYP19, CYP17, CYP1A1 and CYP1B1 genes have been found to affect BMD. So far, in this context, the most extensively investigated polymorphisms are those of the CYP19, the gene that codes for aromatase, an important enzyme in the estrogen biosynthetic pathway that converts androgenic steroids to estrogen. To our knowledge, four important polymorphisms of the aromatase gene are associated with differences in BMD and the risk for osteoporosis. Newer data further suggest that response to estrogen or hormone therapy may also be influenced by polymorphisms in the aromatase gene. And finally, a recent report indicates that polymorphisms of the genes encoding for the enzymes that metabolize estrogen are also important determinants of BMD. The C4887A polymorphism in the CYP1A1 gene is found to be associated with increased estrogen catabolism and lower femoral BMD in women carrying the A allele, present in 19% of the population. A similar (unpublished) observation is also noted for one of the CYP1B1 gene polymorphisms. The main focus of this review is to examine the effects of polymorphisms of the CYP 450 enzyme genes involved in estrogen biosynthesis and metabolism on BMD and the risk for osteoporosis.

Chemogenomics integrates genomic datasets with biological and chemical characteristics of compounds. It uses genomic or proteomic profiling combined with chemoinformatics and statistics to study the response of a biological system to chemical compounds. This large-scale approach is particularly suitable for addressing chemotherapeutic resistance, a main obstacle to successful treatment of cancer patients. Chemogenomics as a discipline has been molded by a suite of datasets derived from a panel of 60 cancer cell lines that are used for drug discovery by the National Cancer Institute (NCI-60). Offering cytotoxic potencies for >50,000 compounds across the NCI-60, and mRNA profiles, proteomes, mutations, and epigenetic factors, this unparalleled public resource enables rapid discovery of molecular targets and mechanisms of chemosensitivity/resistance. While chemogenomics holds much promise, broader impact in all fields of biology and medicine requires expansion of curated and accessible datasets of diverse biological systems, biological and chemical properties of compound libraries, and novel informatics tools for extracting the valuable information embedded in high-dimensional data. Exploiting the effects of diverse chemical probes, chemogenomics adds an important dimension to systems biology for understanding cellular functions.

Recent research has linked the polymorphic metabotropic glutamate receptors to the pathogenesis of schizophrenia contributing to the development of the “glutamate hypothesis”. These receptors regulate glutamate through NMDA inotropic receptors. At the neurotransmitter level, antipsychotics developed to treat schizophrenia have been found to significantly increase serum glutamate levels and potentially affect the expression of various metabotropic glutamate receptors (mGluRs). Additionally, type-3 metabotropic glutamate receptor gene (GRM3) polymorphisms have been associated with schizophrenia as well as being linked to reductions in prefrontal cortex N-acetylaspartate concentrations. Thus, glutamate has become an increasingly important area of interest for therapeutic intervention in schizophrenia and pharmaceutical companies are rapidly focusing on the development of agents that directly modulate this neurotransmitter; however the reality is that the clinical use of such drugs is still years away. Taken together, investigations of how genetic variability in genes coding for mGluRs relate to treatment outcomes are becoming increasingly important. The goal of this review is to discuss the genetics, pharmacology, and pharmacogenetics of the metabotropic glutamate receptors focusing on receptor subtypes with the most evidence for involvement with current and/or future antipsychotic activity.

Dihydropyrimidine dehydrogenase (DPD), which is the initial and rate-limiting enzyme of the degradation of pyrimidine base, plays an important role in the pharmacogenetic syndrome of 5-fluorouracil (5-FU). Deficiency of DPD activity leads to severe toxicities, even death, in patients after administering 5-FU. Several studies demonstrate that the molecular defects of the dihydropyrimidine dehydrogenase gene (DPYD) lead to the deficiency of DPD activity and cause this pharmacogenetic syndrome. However, polymorphic DPD activity and complex nature of the DPYD sometimes result in conflicting findings. To date, more than 40 variant alleles, including 2 splice-site mutations, 2 nonsense mutations, 5 deletion mutations, 32 missense mutations and 2 slice mutations have been reported in the coding area of the DPYD gene. The IVS14+1G>A, which leads to the skipping of the exon 14 resulting in profound DPD deficiency and severe toxicities, is the most common mutation with 5-FU toxicity in Europeans. In addition, the epigenetic factors also participate in the clinical presentations of the syndrome. Due to the fact that the regulation mechanism of DPD itself has not been clearly clarified yet, high-throughput techniques to screen the whole DPYD and the measurement of the DPD activity are warranted to draw a clear relationship between the phenotype and genotype for this pharmacogenetic syndrome. Screening for genetic DPYD defects, at least IVS14+1G>A, and/or the DPD activity before 5-FU therapy to protect patients from hazardous outcome is also suggested, especially in specific populations.

Advances in nanoscience are having a significant impact on many scientific fields, boosting the development of a variety of important technologies. The impact of these new technologies is particularly large in biodiagnostics, where a number of nanoparticle-based assays have been introduced for biomolecular detection. The physicochemical malleability and high surface areas of nanoparticle surfaces make them ideal candidates for developing biomarker platforms. Given the variety of strategies afforded through nanoparticle technologies, a significant goal is to tailor nanoparticle surfaces to selectively bind a subset of biomarkers, either for direct detection and characterization or to sequester the target molecules for later study using other available techniques. To date, applications of nanoparticles have largely focused on DNA- or protein-functionalized gold nanoparticles used as the target-specific probes. These unique biophysical properties displayed by gold nanoparticles have huge advantages over conventional detection methods (e.g., molecular fluorophores, microarray technologies). These gold-nanoparticle based systems can then be used for the detection of specific sequences of DNA (pathogen detection, characterization of mutation and/or SNPs) or RNA (without previous retro-transcription and amplification).

Remarkable ethnic differences in drug response are well known, and many of these can be attributed to differences in genetic backgrounds. Accumulating evidence has shown that genetic polymorphisms can cause the alteration or even loss of activity in drug metabolizing enzymes, transporters and receptors. Thus, genetic polymorphisms may be important in understanding these ethnic differences in drug response. Furthermore, haplotypes, linked combinations of genetic polymorphisms on a chromosome, have the advantage of providing more useful information on phenotype- genotype links than individual polymorphisms. In the past 6 years, mostly as a Japanese national project, we resequenced the exons and enhancer/promoter regions of more than 30 drug metabolizing enzymes, transporters and receptors using genomic DNA from 100 to 500 Japanese subjects, analyzed linkage-disequilibrium (LD), and estimated haplotype structures. Regarding CYP2C9 and 2C19, we found linkages between CYP2C19*2 or *3 and CYP2C9*1, and between CYP2C9*3 and CYP2C19*1 haplotypes. Haplotype structures of CYP2D6 are complicated by gene duplication or recombination. In contrast, the haplotype structure of CYP3A4 was simple, but close linkages were observed with other CYP3As. As for UGT1As, the 8 first exons encoding active isoforms and common exons 2-5 were divided into 5 blocks by LD analysis, and intra- and inter-block haplotypes were estimated. Several linkages of haplotypes with functional importance were revealed, such as UGT1A7*3 - UGT1A6*2 - UGT1A1*28 or *6. In this review, we summarize polymorphisms and haplotype structures of these clinically important drug metabolizing enzymes in East Asians, mainly from our Japanese data, and compare them with those of other ethnicities.

Researchers are using pathway information for both pharmacogenomics study design and data analysis. Candidate gene approaches for the design of pharmacogenomic studies need reliable pathway information to choose the best candidate genes and SNPs, especially when using low to medium throughput genotyping technologies, to maximize the likelihood of success. With the mainstream use of high throughput gene expression microarrays and genome wide SNP assays, pathway-based approaches can also be valuable tool for data analysis. This review will discuss sources of pathway data and mechanisms for applying it to pharmacogenomics research.