Why Personalized Medicine and Neuromodulation in ADHD and Depression?

Recently the landscape in psychiatry is undergoing a dramatic change. Some recent large-scale studies investigating the effects of conventional treatments for ADHD and depression in practice have demonstrated on the group-level limited efficacy of antidepressant medication and cognitive behavioral therapy in depression (STAR*D: Rush et al., 2006), an overestimation of the effects of cognitive-behavioural therapy for depression as a result of publication bias (Cuijpers, Smit, Bohlmeijer, Hollon, & Andersson, 2010) and limited long-term effects of stimulant medication, multicomponent behavior therapy and multimodal treatment in ADHD (NIMH-MTA trial: Molina et al., 2009). Furthermore, several large pharmaceutical companies have announced to ‘…pull the plug on drug discovery in some areas of neuroscience….’ (Miller, 2010) including GlaxoSmithKline (GSK) and AstraZeneca. This can be considered a worrying development, since there is still much to improve in treatments for depression and ADHD. Therefore, a move beyond data regarding the average effectiveness of treatment, to identify the best treatment for any individual (Simon & Perlis, 2010) or personalized medicine is crucial. In personalized medicine it is the goal to prescribe the right treatment, for the right person at the right time as opposed to the current ‘trial-and-error’ approach, by using biomarkers of endophenotypes.

In addition to this develoment we also witness a shift from a ‘systemic treatment approach’ (i.e. systemically applying medication to the whole body) to a more ‘focal treatment approach’ also subsumed under the term ‘Neuromodulation’. In this development there are currently many new treatments developed and applied such as deep-brain stimulation in depression (Hamani et al., 2011); Parkinson: (Zahodne et al., 2009), intracranial stimulation of primary and secondary auditory cortex in tinnitus (De Ridder et al., 2006); rTMS in depression (Schutter 2010; Schutter 2009a), fMRI neurofeedback in pain (deCharms et al., 2005), neurofeedback in ADHD (Arns, de Ridder, Strehl, Breteler & Coenen, 2009), Vagus Nerve Stimulation (VNS) in depression (Daban, Martinez-Aran, Cruz & Vieta, 2008) etc.

Figure 1 shows an overview of different milestones achieved for several non-pharmacological neuromodulation techniques such as approval of techniques by the EU or FDA and introductions of new techniques (From: Moreines, McClintock & Holtzheimer, 2011). This figure further illustrates the increase in milestones for neuromodulation techniques across the last 10-15 years.

 
 

 
Figure 1: A historical overview of milestones related to several neuromodulation techniques. Note the increase in milestones over the last 10-15 years. From: Moreines, McClintock & Holtzheimer (2011).

Along with the development of these new techniques it is interesting to note that the application of some of these neuromodulation approaches do not solely rely on a DSM-IV diagnosis, but lean more towards identifying dysfunctional brain networks and application of treatment to specifically modulate those networks. For example, deep brain stimulation studies specifically aim to modulate the subcallosal cingulate gyrus (Hamani et al., 2011), fMRI neurofeedback patients learn to specifically regulate activity in the rostral anterior cingulate (deCharms et al., 2005) and for neurofeedback treatment in ADHD, the protocol can be personalized to specific deviating EEG patterns (Arns et al. 2012).

As pointed out above, a focus on biomarkers and endophenotypes which can predict treatment outcome will become crucial to improving treatments for ADHD and depression. The development of personalized medicine is hence a very important development in psychiatry. The main aim of this thesis has been to investigate if there are reliable predictors for response and non-response to various treatments in ADHD and depression, with a focus on predictors for non-response. In the following we will summarize the main findings from the studies presented in this thesis and discuss the implications of these findings for the future of personalized medicine. Below also find an illustration of 'Why Personalized Medicine' with a wink ;-)