Major depressive disorder (MDD: unipolar depression) is widely distributed in the USA and world-wide populations and it is one of the leading causes of disability in both adolescents and adults. Traditional diagnostic approaches for MDD are based on patient interviews, which provide a subjective assessment of clinical symptoms which are frequently shared with other maladies. Reliance upon clinical assessments and patient interviews for diagnosing MDD is frequently associated with misdiagnosis and suboptimal treatment outcomes. As such, there is increasing interest in the identification of objective methods for the diagnosis of depression. Newer technologies from genomics, transcriptomics, proteomics, metabolomics and imaging are technically sophisticated and objective but their application to diagnostic tests in psychiatry is still emerging. This brief overview evaluates the technical basis for these technologies and discusses how the extension of their clinical performance can lead to an objective diagnosis of MDD.
Neuropsychiatric diseases are the world’s leader in years lived with disability, accounting for almost 30% of total years lived with disability . Major depressive disorder (MDD, unipolar depression) is common, with an estimated lifetime prevalence of 13.2%. In primary care settings, prevalence estimates of MDD range from 5 to 13% in all adults [2,3], with lower estimates in those older than 55 years (6–9%) . Approximately a third to one half of adults and adolescents are diagnosed in primary care settings [3–5].