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• W940582803 abstract "Identifying biological and clinical markers of treatment response in major depressive disorder (MDD) is an area of research that holds promise for increasing the efficiency and efficacy of treating a major depressive episode (MDE). Work to date has not revealed any consistently validated candidate markers of outcome, and it has been suggested a unitary marker is unlikely to have adequate predictive validity. Studies of clinical characteristics and genetic, neuroimaging, and various biochemical markers have all shown promise in discrete studies, but these findings have not translated into a personalized medicine approach to treating individual patients in the clinic. In the absence of a single adequate marker of outcome, researchers have begun to examine whether advanced mathematical modelling and pattern recognition methods can detect important biological signatures associated with treatment outcome. Through an informatics-based integration of the clinical, molecular, and imaging parameters that are important in the pathophysiology of depression, it may be possible to encompass the complexity of contributing factors and phenotypic presentations of depression, and identify core markers of treatment response.'Neuroimaging and electrophysiological techniques each offer a measure of brain function, bridging the gap between the clinical symptoms of psychiatric illness and the genomic and proteomic mechanisms that are disrupted in illness. Neuroimaging and electrophysiology may also reveal whether the clinical profile of an MDE represents a specific subtype of illness that may be associated with an optimal treatment strategy. It is notable that the investigation of neuroimaging and electrophysiological markers of outcome and treatment response in depression is at a relatively early stage; most studies examining predictors of outcome have only been reported within the last 5 years. Nonetheless, there is significant enthusiasm for this approach, with numerous large trials now committed to using multimodal imaging as part of a comprehensive strategy to examine predictors of treatment responsiveness in people with MDD. Therefore, the reviews of Dr Cynthia H Y Fu and Dr Sergi G Costafreda2 and Dr Natalia Jaworska and Dr Andrea Protzner3 in this issue are timely. They examine the magnetic resonance imaging and electrophysiological paradigms that have been examined as possible predictors of treatment response, outlining the promise-and limitations-of various approaches. For future studies to use neuroimaging and electrophysiology as part of large-scale -omics studies (genomics, proteomics, metabolomics) investigating treatment responsiveness, it is critical to understand the relative strengths and limitations of various imaging approaches.Dr Fu and Dr Costrafreda2 have provided a superb outline of the advances in neuroimaging that are associated not only with better understanding of psychiatric illness but also with providing clinically relevant predictive ability. They outline how neuroimaging is already becoming an integral component of diagnosis and prognosis in various neurological conditions, and make a compelling case that advances in signal processing and pattern matching could allow for individual patient-relevant data to be obtained from various imaging paradigms.As Dr Jaworska and Dr Protzner3 succinctly summarize, electroencephalograms (EEGs) permit near-instantaneous detection of brain activity via scalp electrical signals, which directly reflect postsynaptic potentials. Therefore, EEGs can be linked to specific transmitter systems and to neuronal activity. Various analytic approaches are available, including spectral analyses, time-locked signal averaging, and frequency domain analysis, to reveal evoked and induced oscillations. As with neuroimaging, electrophysiological studies of other disease states may point the way forward for studies in patients with MDD. Analyses of signal variability have shown some clinical utility in predicting recovery in conditions such as traumatic brain injury. …" @default.
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• W940582803 date "2013-09-01" @default.
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• W940582803 title "Neuroimaging and electrophysiology in predicting treatment responsiveness in depression: bridging the lab-to-clinic divide?" @default.
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