Beyond the monoamine hypothesis: mechanisms, molecules and methods

SummaryThe first effective antidepressants (monoamine oxidase inhibitors and tricyclic antidepressants) relied on their ability to augment serotonin and noradrenaline levels at the synapse. Forty years later, the same biological model led to the supremacy of the serotonergic hypothesis to explain not only the pathophysiology of depressive illness, but also the neuropharmacological basis for obsessive compulsive disorder, phobias, posttraumatic stress disorder, and even generalized anxiety disorder. It could be argued that the blinkered view of depression as a solely serotonergic phenomenon has not only restrained and limited research into other potential systems, but has also slowed down the discovery of putative antidepressant drugs. While some might argue that the hypothalamic-pituitary-adrenal (HPA) axis explains an individual’s sensitivity to depression, there are others who equally claim that the most likely explanations are to be found in the neuropsychopharmacology of the immune system or even through reductions in hippocampal volume. There is a richness of possibilities regarding the mechanisms for antidepressant activity embracing theoretical, pharmacological and clinical data. However, the methods by which putative antidepressants are assessed and their clinical efficacy demonstrated are not always robust. That current clinical comparisons of antidepressants rarely show major differences in efficacy between existing molecules could be taken as an indication that “all drugs are the same” or perhaps, more insightfully, as an indication that the ubiquitous Hamilton depression (HAM-D) rating scales are not sensitive to inter-drug differences, even though pronounced pharmacodynamic differences between molecules are easily demonstrated. Any advances in the development of new antidepressants will have to find not only original compounds but also unique psychometric tests by which the drugs can be assessed in a sensitive, reliable, and valid manner.