Personalized Therapy and Pharmacogenomics: Future Perspective

Abstract

expression of the gene (regulation, inhibition and induction) and, of course, at the protein level. A systems biology approach using all the different ‘omics’ is well adapted. The pathways that could be involved should be screened systematically [4]. The latest developments in the genome-wide search have considerably promoted the emergence of new biomarkers that could represent future drug targets. Current genome-wide studies are focusing on cardiovascular diseases including hypertension and related metabolic disturbances, diabetes, lipids, inflammation and also cancer, as well as various other psychological traits. These recent results represent a major shift from classical linkage and associationbased genetic studies, moving the focus towards deciphering the genomic variations network, thus identifying novel therapeutic targets and genetic biomarkers that will be useful for drug discovery. Bernhard Winkelmann (Cardiology Group Frankfurt-Sachsenhausen, Frankfurt, Germany) [5] and Laurent Becquemont (Hopital Bicetre, France) [6] both presented good examples of retrospective genome-wide association studies that confirmed that the most significant independent effect was associated with the VKORC1 polymorphisms (p = 6.2 × 10) and in the CYP2C9 polymorphism (rs1057910 CYP2C9*3 and rs4917639), with warfarin at moderate significance levels (p = 10) [7]. A more recent polymorphism found in the CYP4F2 gene has just been described but has not yet been clinically confirmed [8]. Recently, a new biomarker of statin effect was also highlighted by a genome-wide scan approach of the OATP1B1 rs4363657 SNP and was found to have a high degree of confidence (p = 4 × 10) [9]. Therefore, these three genes could explain a large fraction of the dose variance, which could help future clinical trials to produce meaningful and definitive results. A goal of pharmacogenomics is to guide drug development and selection in order to optimize therapeutic benefits and minimize the potential risk of toxicity. Genetic-based differences in drug metabolism have been recognized for 50 years, but these are better understood since two accidents occured 30 years ago with anti-anginal drug perhexiline and the antidiabetic phenylbiguanide. Accordingly, there is a growing need for ways to better identify individuals who have the highest probability of benefiting from pharmacological interventions, and those who have the lowest risk of developing side effects when exposed to drugs. Since the first Santorini meeting in 2002 with Klaus Lindpaintner (Roche Center for Medical Genomics, Basel, Switzerland), each Biologie Prospective conference has helped shape the field of pharmaco genomics, particularly, the 2006 and 2008 conferences [1,2] following the publication of recommendations by David Gurwitz (Tel Aviv University, Israel) [3], which were published after the second Santorini meeting in 2004.