Biological predictors of treatment response in affective illness

Personalized medicine for depression: can we match patients with treatments?

OBJECTIVE

Response to specific depression treatments varies widely among individuals. Understanding and predicting that variation could have great benefits for people living with depression.

METHOD

The authors describe a conceptual model for identifying and evaluating evidence relevant to personalizing treatment for depression. They review evidence related to three specific treatment decisions: choice between antidepressant medication and psychotherapy, selection of a specific antidepressant medication, and selection of a specific psychotherapy. They then discuss potential explanations for negative findings as well as implications for research and clinical practice.

RESULTS

Many previous studies have examined general predictors of outcome, but few have examined true moderators (predictors of differential response to alternative treatments). The limited evidence indicates that some specific clinical characteristics may inform the choice between antidepressant medication and psychotherapy and the choice of specific antidepressant medication. Research to date does not identify any biologic or genetic predictors of sufficient clinical utility to inform the choice between medication and psychotherapy, the selection of specific medication, or the selection of a specific psychotherapy.

CONCLUSIONS

While individuals vary widely in response to specific depression treatments, the variability remains largely unpredictable. Future research should focus on identifying true moderator effects and should consider how response to treatments varies across episodes. At this time, our inability to match patients with treatments implies that systematic follow-up assessment and adjustment of treatment are more important than initial treatment selection.

A new paradigm for the prediction of antidepressant treatment response

Current treatment of Major Depressive Disorder utilizes a trial-and-error sequential treatment strategy that results in delays in achieving response and remission for a majority of patients. Protracted ineffective treatment prolongs patient suffering and increases health care costs. In addition, long and unsuccessful antidepressant trials may diminish patient expectations, reinforce negative cognitions, and condition patients not to respond during subsequent antidepressant trials, thus contributing to further treatment resistance. For these reasons, it is critical to identify reliable predictors of antidepressant treatment response that can be used to shorten or eliminate lengthy and ineffective trials. Research on possible endophenotypic as well as genomic predictors has not yet yielded reliable predictors. The most reliable predictors identified thus far are symptomatic and physiologic characteristics of patients that emerge early in the course of treatment. We propose here the term “response endophenotypes” (REs) to describe this class of predictors, defined as latent measurable symptomatic or neurobiologie responses of individual patients that emerge early in the course of treatment, and which carry strong predictive power for individual patient outcomes. Use of REs constitutes a new paradigm in which medication treatment trials that are likely to be ineffective could be stopped within 1 to 2 weeks and other medication more likely to be effective could be started. Data presented here suggest that early changes in symptoms, quantitative electroencephalography, and gene expression could be used to construct effective REs. We posit that this new paradigm could lead to earlier recovery from depressive illness and ultimately produce profound health and economic benefits.

Effects of socioeconomic status on brain development, and how cognitive neuroscience may contribute to levelling the playing field

The study of socioeconomic status (SES) and the brain finds itself in a circumstance unusual for Cognitive Neuroscience: large numbers of questions with both practical and scientific importance exist, but they are currently under-researched and ripe for investigation. This review aims to highlight these questions, to outline their potential significance, and to suggest routes by which they might be approached. Although remarkably few neural studies have been carried out so far, there exists a large literature of previous behavioural work. This behavioural research provides an invaluable guide for future neuroimaging work, but also poses an important challenge for it: how can we ensure that the neural data contributes predictive or diagnostic power over and above what can be derived from behaviour alone? We discuss some of the open mechanistic questions which Cognitive Neuroscience may have the power to illuminate, spanning areas including language, numerical cognition, stress, memory, and social influences on learning. These questions have obvious practical and societal significance, but they also bear directly on a set of longstanding questions in basic science: what are the environmental and neural factors which affect the acquisition and retention of declarative and nondeclarative skills? Perhaps the best opportunity for practical and theoretical interests to converge is in the study of interventions. Many interventions aimed at improving the cognitive development of low SES children are currently underway, but almost all are operating without either input from, or study by, the Cognitive Neuroscience community. Given that longitudinal intervention studies are very hard to set up, but can, with proper designs, be ideal tests of causal mechanisms, this area promises exciting opportunities for future research.

Cytochrome P450 genotyping and antidepressants

An imperfect measure of a modest predictor of response to antidepressants may not be ready for clinical application

Pharmacogenetic studies of antidepressant response: how far from the clinic?

Because the US FDA has begun to focus on disclosure of pharmacogenetic testing results in applications for new drug approval and review of existing drugs (see, eg, http://www.fda.gov/OHRMS/DOCKETS/AC/05/slides/2005-4194S1_Slide-Index.htm), the application of such testing in a clinical setting is likely to increase substantially. Instead of small cohorts of patients, potentially nearly every participant in the large pivotal trials required for drug approval could help inform the future application of that drug. Psychiatry as a whole, and antidepressant prescribing ni particular, stands to benefit in the near term from the identification of newer treatment targets that may overcome some of the limitations of current therapeutics. On the other hand, despite the excitement about the rapid pace of development in psychiatric pharmacogenetics, a number of key issues remain to be addressed before these discoveries are applied in a clinical setting. Close coordination will be required between those who study treatment efficacy and effectiveness and those who study genetic variation in populations to ensure that studies yield results that have scientific importance and clinical importance as well.