Editorial

The mood and anxiety disorders issue of Current Opinion in Psychiatry deals with distinct aspects of the heterogeneity in major depressive disorder (MDD), and the quest for clinical/biophenotypes to improve diagnosis and treatment selection. Frank et al. (pp. 3–6) highlight the future of digital technologies to evaluate moods, activities and behaviours. On the plus side, they remind us that currently 4 billion people worldwide own a smartphone, and this will increase to approximately 7 billion by 2022. The ability to carry out active reporting as well as passive sensing provides opportunities for digital phenotyping through ecological momentary assessment. Digital phenotyping involves collecting various data from smartphones including sensor, keyboard, voice and speech to measure mood, behaviour and cognition. As the field advances, the authors point out the need to address issues of privacy and data protection, the gap between availability of apps and scientific validation of what they measure, as well as the potential to harm, which has resulted in Food and Drug Administration risk monitoring. Lopez et al. (pp. 7–16) take a very different perspective on ‘biotyping’ depression in their review of small, noncoding microRNAs and their role in regulating brain processes including mood. These microRNAs have been identified as potential biomarkers in cancer, and the fact that they are abundantly expressed in brain, are involved in regulation of neurogenesis and can be stably transported in blood within exosomes supports their role as potential depression biomarkers. As always, replication is an essential component of any biomarker discovery, and Lopez describes the careful step-by-step replication from change in microRNA levels with antidepressant and placebo medications, to differences in postmortem brain between depressed individuals who died by suicide and matched controls, with additional back translation in a rodent model. Like Frank, Lopez argues that biosignatures, rather than single markers, will be required to predict treatment outcomes. Gaspersz et al. (pp. 17–25) provide a timely update on the controversial concepts of ‘anxious depression’, pointing out the many disadvantages of this potential clinical phenotype: various definitions, lower rates of remission, quality of life, social and occupational function, in addition to higher risk of suicide, readmission to hospital and comorbidity with various medical conditions. The authors also link ‘anxious depression’ to an increased stress diathesis, including greater elevations of inflammatory markers, cortical thinning in temporal and prefrontal regions, and elevated resting-state functional connectivity in cortico-limbic networks involved in emotion regulation. Overall, the authors make a cogent argument to recognize ‘anxious depression’ based on historical, clinical and biological grounds, highlighting the need of a more coherent definition. Knight and Baune (pp. 26–31) review the substantial literature highlighting cognitive dysfunction in depression, with particular emphasis on executive function. They provide useful information on screening for cognitive dysfunction in MDD and identify treatments such as cognitive remediation and cognitive training, which may be more effective in combination with antidepressants than either intervention alone. In contrast to other authors, they do not argue for a distinct major depressive episode subtype ‘with cognitive deficits’. Finally, at a more macro level, Kessler (pp. 32–39) takes a pragmatic view, emphasizing the enormous cost associated with multiple biomarkers in a large dataset. In his review of ‘Heterogeneity of Treatment Effects’, he includes childhood adversity, low socio-economic status and age in addition to hypercortisolism and Electroencephalography profiles as current broad candidate markers, before arguing for a stepwise approach to identify responder subgroups. He advocates starting with large observational studies before moving to more expensive prospective trials to evaluate decision support tools. Again, he concurs with the majority position that ‘no single test or measure is a strong enough predictor’ to guide optimal treatment selection. Acknowledgements None. Financial support and sponsorship None. Conflicts of interest There are no conflicts of interest.

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