Drug therapy and personalized health care: pharmacogenomics in perspective

Essential(ist) medicine: promoting social explanations for racial variation in biomedical research

Biomedical research has a long and complicated history as a tool of oppression, exemplary of the racial science used to legitimise and maintain racial hierarchies in the USA and abroad. While the explicit racism and racial inferiority supported by this research has dissipated and modern methods of inquiry have increased in sophistication and rigor, contemporary biomedical research continues to essentialise race by distilling racial differences and disparities in health to an underlying, biogenetic source. Focusing on the persistence of essentialism in an era of genomic medicine, this paper examines the deep social origins and social implications of the essentialist viewpoint in biomedicine and how it relates to the broader construction of social and scientific knowledge. Invoking Hacking's 'looping effects' as a useful conceptual tool, I then demonstrate how sociohistorical forces influence scientific and medical research in producing evidence that favours and legitimises a biological construction of race. I extend the looping framework to consider a parallel 'louping' process whereby applying a socially rooted meaning to race in biomedical research results becomes magnified to influence social norms and ideas about race. As many biomedical researchers are motivated by a desire to eliminate racial disparities in outcomes, I argue that greater social acuity allows scientists to avoid individualising and racialising health, challenge preconceived assumptions about the meaning of racial variation in health and medicine and thus promote and strengthen a socioenvironmental focus on how to best improve individuals' and population health. Concluding with a call for structural competency in biomedical research, I suggest that empowering scientists to more freely discuss sociostructural factors in their work allows for the continued use of race in biological and medical research, while social scientists and medical humanities scholars stand to benefit from seeing their work imbued with the cultural authority currently granted to biomedicine.

Pharmacogenomics and pharmacoepigenomics in pediatric medicine

In the past several years, human genetics studies have progressed from monogenic to complex and common diseases because of the advancement in technologies. There is increased knowledge of the pharmacokinetics and pharmacogenomics of the drugs in adults as well as in children. These technological developments provided new diagnostic, prognostic, and therapeutic opportunities. We are now in a position to address many additional ambitious questions. For instance, in clinical medicine, interindividual variation in drug response is a major problem. Some of the heterogeneity of drug safety and efficacy among individuals can be explained by pharmacogenomics. It has also the potential to improve the treatment in both adults and children. In pediatrics however, there is ontogeny and metabolic capacity in children is different compared to adults. Several specific developmental changes may underlie some of the variability in drug response seen in children. They may also be responsible for adverse drug reactions (ADRs). Therefore, much of the diversity in drug effects cannot be explained by studying the genomic diversity alone. It is necessary to include the effect of growth (involves variations in gene expression) along with genetic differences when explaining the variability in treatment response. In this respect epigenomics may expand the scope of pharmacogenomics towards optimization of drug therapy. Future studies must focus on periods of maturation of the drug-metabolizing enzymes and polymorphisms in their genes by using candidate gene approach, gene expression analysis, genome-wide haplotype mapping, and proteomics. The integration of genetic data and clinical phenotypes along with the role of other factors is necessary to evaluate both efficacy and ADRs of any drug. It may require extensive genetic epidemiological studies spanning over many years.

Genomics and personalized medicine

The role of genomics in personalized medicine continues to undergo profound changes, in step with dramatic technological advances. Ability to sequence the entire human genome with relative ease raises expectations that we can use an individual's complete genomic blueprint to understand disease risk and predicting therapy outcomes, thereby, optimizing drug therapy. Yet, doubts persist as to what extent genetic/genomic factors influence disease and treatment outcomes or whether robust predictive biomarker tests can be developed. Encompassing more than just DNA sequences, the definition of genomics now often is taken to include transcriptomics, proteomics, metabolomics, and epigenomics, with integration of genomic and environmental factors, in an area referred to systems biology. While we can learn much about a cell's innermost workings, summation of these diverse areas is far from enabling the prediction of therapeutic outcomes. Typically, only a handful of specific biomarkers, genetic or otherwise, are 'actionable', i.e., they can be used to guide therapy. I will focus on pharmacogenetic biomarkers, highlighting current successes but also the main challenges that remain in optimizing individualized therapy.

Pharmacogenomics of human ABC transporter ABCC11 (MRP8): potential risk of breast cancer and chemotherapy failure

Some genetic polymorphisms of human ABC transporter genes are reportedly related to the risk of certain diseases and patients’ responses to medication. Human ABCC11 functions as an ATP-dependent efflux pump for amphipathic anions. One non-synonymous SNP 538G>A (Gly180Arg) has been found to greatly affect the function and stability of de novo synthesized ABCC11 (Arg180) variant protein. The SNP variant lacking N-linked glycosylation is recognized as a misfolded protein in the endoplasmic reticulum (ER) and readily undergoes proteasomal degradation. This ER-associated degradation of ABCC11 protein underlies the molecular mechanism of affecting the function of apocrine glands. On the other hand, the wild type (Gly180) of ABCC11 is associated with wettype earwax, axillary osmidrosis, colostrum secretion from the mammary gland, and the potential susceptibility of breast cancer. Furthermore, the wild type of ABCC11 reportedly has ability to efflux cyclic nucleotides and nucleoside-based anticancer drugs. The SNP (538G>A) of the ABCC11 gene is suggested to be a clinical biomarker for prediction of chemotherapeutic efficacy. Major obstacle to the successful chemotherapy of human cancer is development of resistance, and nucleoside-based chemotherapy is often characterized by inter-individual variability. This review provides an overview about the discovery and the genetic polymorphisms in human ABCC11. Furthermore, we focus on the impact of ABCC11 538G>A on the apocrine phenotype, patients’ response to nucleoside-based chemotherapy, and the potential risk of breast cancer.

Maternal-fetal and neonatal pharmacogenomics: a review of current literature

Pharmacogenomics, the study of specific genetic variations and their effect on drug response, will likely give rise to many applications in maternal-fetal and neonatal medicine; yet, an understanding of these applications in the field of obstetrics and gynecology and neonatal pediatrics is not widespread. This review describes the underpinnings of the field of pharmacogenomics and summarizes the current pharmacogenomic inquiries in relation to maternal-fetal medicine-including studies on various fetal and neonatal genetic cytochrome P450 (CYP) enzyme variants and their role in drug toxicities (for example, codeine metabolism, sepsis and selective serotonin reuptake inhibitor (SSRI) toxicity). Potential future directions, including alternative drug classification, improvements in drug efficacy and non-invasive pharmacogenomic testing, will also be explored.

Rapid and cost-effective SNP detection method: application of SmartAmp2 to pharmacogenomics research

Pharmacogenomics data can facilitate our understanding of the sources of variability in drug response, which can potentially lead to improved safety and efficacy of drug therapy for individual patients. A key requirement for the development of individualized medicine or personalized therapy is the ability to rapidly and conveniently test patients for genetic polymorphisms and/or mutations. However, in today's world, genotyping technology remains a bottleneck in clinical applications because of its slow speed and high cost. Therefore, we have recently developed a rapid and cost-effective method for SNP detection, named Smart Amplification Process 2 (SmartAmp2), which enables us to detect genetic polymorphisms or mutations in 30-45 min under isothermal conditions without DNA isolation and PCR amplification. This article presents the SNP detection method and its underlying molecular mechanism as well as clinical research applications.

'Principled' personalized medicine?

The advent of both population genomic studies and direct-to-consumer personal genetic testing raises ethical challenges for researchers and physicians alike. Quality and solidarity can now be added to traditional ethical principles, such as autonomy and privacy. There is no doubt that genetic information is going 'public'. Informatic technologies allow for greater accessibility and integration, but can researchers and physicians handle the challenges? Are ethics committees equipped to handle this shift towards greater openness and towards a conflation of research and traditional medical ethics?

Delivered dose: a drug-centric phenotype for chemotherapy dose individualization

It is pointed out that genotype-based approaches are unlikely to be effective at dose individualization. Delivered dose, which refers to the amount of drug delivered to the point of action to be measured by quantitative imaging techniques, is a drug-centric phenotype that separates pharmacokinetic effects from pharmacodynamic effects. Delivered dose serves as a midway measurable numeric parameter between drug administration and therapy outcome. One potential way to reduce chemotherapy outcome variation is to individualize prescribed drug so that uniform delivered dose is achieved across the patient population.