The current and potential impact of genetics and genomics on neuropsychopharmacology
Introduction
Neuropsychopharmacology continues to search for new and improved treatments for psychiatric disorders, as well as to make more effective and safe use of current medications. It is widely hoped, and often assumed, that genetic information can contribute in both respects, taking advantage of the remarkable technological progress of the past decade. Indeed, one justification and rationale for the massive investments in psychiatric genetics has been the hope that the findings will lead to therapeutic benefits. This review considers the extent to which genetic discoveries have already made a difference to neuropsychopharmacology, and the extent to which they are likely to do so in the next few years. It focuses primarily on current and future drugs for the treatment of schizophrenia, but the principles, problems, and potential which it illustrates apply broadly across neuropsychopharmacology (Malhotra et al., 2012b).
Before proceeding, two prefatory comments are worth making. The first concerns the methods used to find the genetic contributions to drug effects. These have paralleled the approaches taken to finding genes contributing to diseases and other phenotypes. Until recently, most studies were ‘candidate gene’ or ‘pharmacogenetic’ in nature, whereby one (or a few) genes, selected on the basis of a plausible relationship to the target or metabolism of the drug were investigated to identify allelic variants (mostly single nucleotide polymorphisms [SNPs]) which showed genetic association (i.e. a statistical over-representation) in one group compared to another (e.g. responders vs. non-responders). Whilst the candidate gene approach has produced a wealth of data, and continues to be employed, it has largely been supplanted by pharmacogenomic (i.e. genome-wide) association studies (GWAS), in which hundreds of thousands of SNPs across the genome are assayed simultaneously (Kingsmore et al., 2008, Daly, 2010). The main advantage of a genomics rather than a genetics approach is that the search is unbiased, and not limited to candidate genes. However, because of the large number of statistical tests performed in a GWAS, and the need to control for multiple testing, very large samples (many thousands) are required in order to have sufficient power. To date, only a few pharmacogenomic GWAS have been reported, and all have been much smaller than this. The second comment is that, in addition to SNPs, an important source of genetic variation arises from copy number variants (CNVs, also known as structural variants), in which a length of DNA (from hundreds to millions of nucleotides) is either deleted or duplicated. Major psychiatric disorders, especially schizophrenia and autism, are associated with an increased frequency of CNVs at several genomic loci (Malhotra and Sebat, 2012). Any given CNV is very rare but, if present, can represent a major risk factor. There may also be similar rare but penetrant pharmacogenetic effects of CNVs (e.g., a CNV which involves the dopamine D2 receptor might affect response to antipsychotics), but these have not yet been investigated; as such, this review only considers SNPs.
Section snippets
Genetic predictors of efficacy or side-effects of current psychotropic drugs
Genetic factors can affect pharmacodynamics or pharmacokinetics; the former concerns allelic variation in the target of the drug (e.g. receptor, transporter), whereas the latter primarily refers to the cytochrome P450 (CYP) enzymes which metabolise most drugs. It is worth noting however that this does not translate simply into genotype-associated efficacy differences being due to pharmacodynamics factors, and side-effects to pharmacokinetic ones. For example, a drug causing many side-effects
From interesting discoveries to clinical utility
There is a marked discrepancy between the large number of positive pharmacogenetic results in the literature, and the lack of impact which they have had on current clinical practice. Currently, there are a few psychotropic drugs for which the FDA suggests CYP genotyping to help predict dosing (see http://www.fda.gov/drugs/scienceresearch/researchareas/pharmacogenetics/ucm083378.htm; also Swen et al., 2011). However, none have become incorporated into routine practice, and debate as to the
Using genetics to inform and discover novel drug targets
In the longer term, the real potential of genetics and genomics in neuropsychopharmacology is to facilitate the discovery of new drug targets and thence treatments. In the work to date, a distinction can be made between targets which were already of interest before genetic data emerged which supported their candidacy, and those targets which emerged specifically because of genetic findings, having not previously been considered as such.
Conclusions
Genetics and genomics will undoubtedly continue to be an integral part of neuropsychopharmacology in the coming years, both in terms of identifying SNPs and other genetic variants which can explain and predict individual differences in response to a drug (Lotrich, 2012), but also as a driver for the target (and thence drug) discovery process (De Leon, 2009). The examples given in this review are testament to the many discoveries already made, and the potential of the field, in both respects. As
Role of the funding source
My group's work has been supported by various funders, notably the Wellcome Trust, Medical Research Council, and Stanley Medical Research Institute. None of these funders had any role in the writing of this review or the decision to submit it for publication.
Contributors
I was the author of this manuscript and take sole responsibility for it.
Conflict of interest
In the past three years, I have received honoraria for lectures from AstraZeneca, Janssen, Otsuka and Takeda, for consulting from Merck, and an unrestricted educational grant from Takeda. I have acted as an expert witness in a pharmaceutical patent case.
Acknowledgement
I am grateful to the many current and past members of the group, and our collaborators, whose ideas and findings have shaped my thoughts and the opinions expressed here. Particular thanks are due to Elizabeth Tunbridge, Amanda Law and Daniel Weinberger.
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