Recent years have seen great advances in our understanding of genetic contributors to drug response. Drug discovery and development around targeted genetic (somatic) mutations has led to a number of new drugs with genetic indications, particularly for the treatment of cancers. Our knowledge of genetic contributors to variable drug response for existing drugs has also expanded dramatically, such that the evidence now supports clinical use of genetic data to guide treatment in some situations, and across a variety of therapeutic areas. Clinical implementation of pharmacogenetics has seen substantial growth in recent years and groups are working to identify the barriers and best practices for pharmacogenetic-guided treatment. The advances and challenges in these areas are described and predictions about future use of genetics in drug therapy are discussed.

The kidney has attracted the attention of diabetologists as an organ involved in the regulation of glucose homeostasis not only by gluconeogenesis, but also by renal glucose excretion. Sodium-glucose cotransporters (SGLTs), particularly SGLT2, are responsible for reabsorption of up to 99% of the filtered glucose. SGLT2 is coded by the SLC5A2 gene, which maps on chromosome 16. Pharmacological reduction of tubular glucose reabsorption results in improved glycemic control in Type 2 diabetic patients. Since the SGLTs reabsorb most of the filtered glucose (90%), it is not surprising that mutations in SLC5A2 cause familial renal glucosuria. A recent study pointed out a possible role of common genetic variation in SLC5A2 in the control of glucose homeostasis. SLC5A2 polymorphisms might therefore represent potential candidates for pharmacogenomic studies targeting the impact of these variants on the efficacy of antidiabetic treatment that is based on inhibition of SGLT2 activity.

The OPRM1 gene encodes the µ-opioid receptor, which is the primary site of action of most opioids. Several studies and three meta-analyses have examined a possible link between the exonic OPRM1 A118G (rs1799971) polymorphism and opioid dependence; however, results have been inconclusive. Therefore, a systematic review and meta-analysis have been carried out to examine whether this polymorphism is associated with opioid dependence. Thirteen studies (n = 9385), comprising 4601 opioid dependents and 4784 controls, which evaluated association of the OPRM1 rs1799971 polymorphism with susceptibility to opioids, were included in this study. Our meta-analysis showed significant association between this polymorphism and susceptibility to opioid dependence in overall studies under a codominant model, as well as susceptibility to opioid dependence or heroin dependence in Asians under an autosomal dominant model. The nonsynonymous OPRM1 rs1799971 might be a risk factor for addiction to opioids or heroin in an Asian population.

5-fluorouracil (5-FU) remains the cornerstone of all currently applied regimens for the treatment of patients with cancers of the gastrointestinal tract, breast, and head and neck. Unfortunately, a large variation in the clearance of 5-FU has been observed between patients, suggesting that some patients might receive nonoptimal 5-FU doses. However, therapeutic drug monitoring of 5-FU has been shown to result in reduced intra- and inter-individual variability in 5-FU plasma levels and pharmacokinetically guided dose adjustments of 5-FU-containing therapy results in a significantly improved efficacy and tolerability. To date, compartmental Michaelis-Menten elimination-based modeling has proven to be a sensitive and accurate tool for analyzing the pharmacokinetics of 5-FU and to identify patients with a dihydropyrimidine dehydrogenase deficiency. These Michaelis-Menten models also allow the use of a limited sampling strategy and offer the opportunity to predict a priori the 5-FU plasma concentrations in patients receiving adapted doses of 5-FU.

Aim:

To assess the distribution of CDA activity from whole blood of 142 healthy subjects, determining its main predictors among genetic (six CDA SNPs) and physiological factors (age and gender). Moreover, we performed a kinetic study of the two CDA protein variants (Q27 and K27) determined by the rs2072671 SNP. Materials & methods: CDA activity was assessed by HPLC. Selected CDA SNPs were genotyped by PCR-based methods. Recombinant CDA protein variants (Q27 and K27) were expressed in an Escherichia coli strain SØ5201 and kinetic assays were performed.

Results:

The mean value of CDA activity was 0.051 ± 0.024 mU/mg and followed a normal distribution in the study population. Carriers of the CDA*2B (-451T/-92G/-31Del/79C/435C) haplotype displayed higher CDA activity compared with the others. CDA -451G>A, -92A>G and 79A>C (K27Q) SNPs displayed significant associations with CDA activity. The best predictive model of CDA activity included the variables gender and CDA 79A>C (K27Q). Cytidine is the preferential substrate for the variant Q27.

Conclusion:

We suggest the analysis of both CDA activity and CDA 79A>C (K27Q) SNP in future prospective trials with cytidine analogs, alone or in combination, in order to identify the best marker to secure the administration of these anticancer therapies. Original submitted 22 October 2012; Revision submitted 11 March 2013.

Advances in the management of patients after solid organ transplantation have led to dramatic decreases in rates of acute rejection, but long-term graft and patient survival have remained unchanged. Individualized therapy after transplant will ideally provide adequate immunosuppression while limiting the adverse effects of drug therapy that significantly impact graft survival. Therapeutic drug monitoring represents the best approximation of individualized drug therapy in transplant at this time; however, obtaining pharmacogenomic data in transplant patients has the potential to enhance our current practice. Polymorphisms of target genes that impact pharmacokinetics have been identified for most immunosuppressants, including tacrolimus, cyclosporine, mycophenolate, azathioprine and sirolimus. In the future, pre-emptive assessment of a patient's genetic profile may inform drug selection and provide information on specific doses that will improve efficacy and limit toxicity.