Clinical Genetic Testing In Psychiatry: Prospects And Challenges

Abstract

Overall Abstract Diagnostic tests are an important tool in medical practice. Ideally, they provide the clinician with valid and accurate information as to whether a disease is present or absent in a particular patient or whether the patient can be expected to respond or not respond to a particular treatment or manifest adverse effects as a consequence thereof. Biomarkers of various types, including genetic biomarkers, can serve as diagnostic tests. Genetic markers that can be used to predict response to medication or adverse effects are a central research objective of pharmacogenomics. A pivotal requirement of diagnostic tests is that they be accurate and sensitive. A further characteristic that ensures generalizability is that the test be valid for different populations. Large scale clinical research is needed to fulfill such requirements. In the area of diagnostic testing, including genetic tests, regulatory requirements are considerably less stringent than in the licensing of pharmaceutical agents. This panel will focus on clinical genetic testing in psychiatry with an emphasis on pharmacogenomic tests that are used to predict response to and adverse effects of psychiatric drugs. Several such tests are currently being marketed in various countries and others are in development in commercial and academic research settings. This panel will present four such initiatives with an emphasis on empirical data regarding the validity of these tests and justification for their use. Anthony C. Altar will present data on GeneSight Psychotropic, a test that is based on a composite phenotype derived from allelic variations in six genes that encode cytochrome P450 (CYP) enzymes, two genes that encode UGT enzymes, and four pharmacodynamic genes. Miquel Tuson will present data on Neuropharmagen, a test that integrates pharmacogenomic data from the analysis of several pharmacokinetic and pharmacodynamic genes with drug-drug interactions to provide recommendations for psychoactive drug treatment, including a randomized clinical trial conducted in patients with major depressive disorder. Dekel Taliaz will describe the development of prediction algorithms for the efficacy and adverse effects of current antidepressants, with up to 77% accuracy (76% specificity and 79% sensitivity) based on the application of machine learning algorithms to genetic data combined with clinical and demographic information in large databases. Bernard Lerer will describe a series of experiments in which association of two single nucleotide polymorphisms with susceptibility to antipsychotic-induced parkinsonism was identified in clinical studies, validated and then tested in a large replication study. He will consider the difficulty in establishing the clinical utility of common genetic biomarkers even with a carefully recruited, well-powered sample. Francis McMahon will serve as Discussant of these presentations. The aim of this panel is to facilitate a discussion of genetic testing in clinical psychiatry that is based on data generated regarding tests currently in use or in development and, on this background, to consider the significant challenges that need to be addressed in the course of developing such instruments.