Pharmacogenomics – From Large Collaborations To Implementation and Drug Discovery

Abstract

Overall Abstract Introduction Recent genetic studies have identified variants in specific gene regions showing not only evidence of association but also biological mechanisms underlying the association. The goal of this symposium is to demonstrate how human genetic association findings can be translated into improved understanding of biological mechanism, disease prognosis, and treatment response using examples across different psychiatric disorders such as mood disorders, schizophrenia, eating disorder, and addiction. Methods A variety of methods are used including randomized treatment trials, large genome wide association studies or meta-analyses, bioinformatics, and epigenetics. Results The first talk by Dr. Schulze is on genotype-phenotype relationships in bipolar and related traits. He will demonstrate how applying the friendly data sharing approach spanning five continents has helped pave the way for a better understanding of the genetic basis of response to lithium treatment, serving as an example for successful precision medicine research. The 2nd talk by Dr. Muller is on current evidence, evidence adjudication, implementation challenges of pharmacogenetics testing for antidepressants and antipsychotics use. He will present a review of the evidence that was considered in formulating that guidance, along with a summary of the main recommendations and associated ethical issues. He will also discuss the kinds of evidence still needed to incorporate genetic testing in clinical decision-making. The 3rd talk by Dr. Breen is on translation of genetic findings from large GWAS studies in Psychiatric Genomics Consortium (PGC) into druggable genomes. He will discuss how discovery of the biological pathways can not only reveal etiological pathways but also lead to drug discovery. The 4th talk by Dr. Chen demonstrates the significant genetic variants that predict nicotine dependence, smoking cessation, and response to cessation pharmacotherapy. These data suggest that genetic risks may predict smoking cessation outcomes and moderate the effect of pharmacological treatments. Some pharmacogenetic findings have been replicated in meta-analyses of multiple smoking cessation trials. The variation in efficacy between smokers with different genetic markers suggests that personalized smoking cessation pharmacotherapy based upon genotype could maximize the efficiency of such treatment while minimizing side effects. As a result, these genetic markers are useful to predict clinical predictor such as the number needed to treat (NNT) and the number needed to harm. Conclusion Different psychiatric disorders serve as successful examples in how genetic findings in human association studies inform biological experiments to uncover the underlying mechanisms and treatments tailored to individual genetic background. Each presentation represents unique and complementary research paradigms in understanding how genomics inform personalized medicine by linking the biology and treatment in different psychiatric disorders. Learning Objectives 1) human genetic studies inform the biological mechanisms of psychiatric disorders, 2) pharmacogenetic studies inform personalized treatments with maximized efficacy and minimized risk of side effects.