The emergence of precision approaches to treating depression could hardly be more essential: depression is now deemed to have the highest disability burden worldwide of all illnesses, and inadequate response to treatment compounds the issue.1 A substantial minority of patients experience multiple treatment resistant depression (TRD) and consequential chronic and/or recurrent illness. The burden of TRD is challenging to quantify but extensive, partly due to the associations with increased physical as well as psychiatric morbidity and mortality that in turn present excessive costs to health care and economic sectors, in addition to being detrimental to individual and care-giver wellbeing. Despite this, TRD has received little attention; as a result, treatment guidelines have struggled to provide evidence-based recommendations for TRD, and we are unable to proactively prevent treatment-resistance.2
The field of precision medicine has initiated significant advancements in the treatment of various physical illnesses in recent years.3 Psychiatric research is currently looking at ways to predict response to treatment for a range of disorders including major depressive disorder (MDD) because of the multitude of treatment options and relatively poor response rates to commonly prescribed interventions.
Types of therapeutic markers
The use of biomarkers to assist with optimizing treatment decisions for depression has been receiving increasing attention. Streams of biomarker “omics” may be representative of one or more biological systems and may be measured directly or indirectly in humans. “Omics” describes biomarkers that can be measured across the whole of each level (see Figure). Findings of abnormal genomic, epigenomic, transcriptomic, proteomic, and metabolomic and microbiomic profiles in individuals with psychiatric diagnoses—particularly MDD—have been widespread.4 Although the findings represent potential diagnostic biomarkers, inconsistencies between studies render single biomarkers ineffectual as replacements for current diagnostic tools. Indeed, the potential for a diagnostic biomarker (or biomarkers) for depression are viewed with much skepticism, not least because it is difficult to see how they could ever outperform current diagnostic criteria. For example, neither diagnosis not antidepressant treatment would be recommended for a patient who biologically scored positive for depression but manifested no discernible psychological or functional symptoms.
“Prognostic” biomarkers might be useful for detecting patient vulnerabilities for TRD or chronic depression regardless of which treatment is selected, while “predictive” biomarkers assess the likelihood of success with a specific intervention.5 Both prognostic and predictive therapeutic markers for depression have been explored for a wide variety of biological and non-biological factors.
It is outside the scope of this article to detail which markers in particular can be used as aids for finding optimum treatment strategies for number of reasons: there are too many potential markers; we have not nearly enough evidence or knowledge to make useful prediction estimates; and, it is likely that the most accurate prediction models will be of such considerable complexity that they cannot be practically applied with current approaches. Instead, I first look at a few recent findings that indicate promise for this field and follow with an overview of the challenges and barriers that must be overcome before therapeutic markers can effectively be utilized in practice.
Dr Strawbridge is Post-Doctoral Research Associate, Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK.
The author reports no conflicts of interest concerning this article.
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