Overcoming the current approach in bipolar disorder research: towards DSM-V and beyond

Smith, Ghaemi and Craddock provide a brilliant and compelling summary of the most striking side effects of the current, and unfortunately defective, classification of mood disorders. Call it DSM-IV, DSM-IV-TR or ICD-10, the consequences of neglecting the evidence supporting that a significant proportion of patients presenting with depressive symptoms would be much better classified as belonging to the bipolar spectrum, are very well described, involving epidemiology, clinical care and research. Alternatives are not easy, though, and several task forces have been organized to deal with this challenge towards a 2012 deadline or so. In their proposal, Smith, et al., (2008) emphasize that recurrence, as opposed to polarity, is the hallmark of manic-depressive illness, supporting Goodwin and Jamison’s (2007) approach. Indeed, cyclicity, perhaps rather than recurrence, is paramount in bipolar disorder, but this may be also true for many other mental and somatic conditions (panic disorder, epilepsy, asthma.). The concept of cyclicity may be complemented with the concept of predominant polarity, which should not necessarily be restricted to bipolar disorder. Predominant polarity (Colom, et al., 2006) permits to classify patients with mood disorders according to their proneness to manic or depressive recurrences. This and other potential novel concepts aimed at improving the classification of mental disorders have in common that they introduce dimensions into the current rigid categorical paradigm (Vieta and Phillips, 2007). In fact, the spectrum model, as applied by Akiskal (1981) and others to mood disorders, is another way to ‘dimensionalize’ categories. What can be done to overcome the undesired consequences of unrecognized bipolarity? I am a believer on the long-term benefits of education and research. Data supporting the validity of the bipolar spectrum are still scant, although growing. The risk of over-diagnosing bipolar disorder has to be addressed, and this is one of the reasons why classificatory systems tend to be cautiously conservative. Clinical trials assessing the benefit-risk ratio of different pharmacotherapies across the mood spectrum should be implemented. For instance, despite the widespread use of antidepressants in patients with bipolar depression, we still do not know unequivocally whether they are effective (Gijsman, et al., 2004), ineffective (Sachs, et al., 2007), safe (Amsterdam, et al., 2004) or unsafe (Wehr and Goodwin, 1987). And they might end up being the four things at the same time, depending on their class (Vieta, et al., 2002; Vieta, 2003). The limitations of the current knowledge in this regard have to do with the lack of interest of the pharmaceutical companies marketing antidepressants, for which the nosological distinction between unipolar and bipolar depression is more a threat than an opportunity, the poor investment on independent clinical trials by governmental agencies and scientific societies and the practical absence of careful pharmacovigilance surveys particularly focused on mental disorders (Vieta, 2007; Klein and O’Brien, 2007). However, for the companies marketing mood stabilizers or antipsychotics, the common belief that antidepressants may cause switch and rapid cycling is perfectly in line with their marketing strategies, and they would not promote trials involving antidepressants as comparators unless otherwise required for registration purposes. Hence, because of different reasons, we are left with the uncertainty of whether we are actually helping or hurting a patient with bipolar depression when the decision to prescribe an antidepressant is made. Smith, et al., (2008) raise a crucial point when discussing the implications of bipolar misdiagnosis for research. There is no question that most of the research in the area of mood disorders is hampered by the difficulty to separate bipolar from unipolar disorder, and that a great deal of inconsistencies may be attributed to this fact. This is again a further reason to introduce significant changes in the classificatory system. It should be definitely more versatile (but not loose), more dimensional (but not blurred) and more data-driven. It should help researchers, educators and clinicians. A recent proposal advocates for the use of a modular approach, including a categorical module, which would represent a data-driven refinement of DSM-IV’s axis I and II; a dimensional module, allowing to score the main psychopathological domains; a laboratory module, addressing all kind of biomarkers; a somatic module, in Commentary