Recent advances in predicting responses to antidepressant treatment

F1000Research
Thomas Frodl

Abstract

Major depressive disorder is one of the leading causes of disability in the world since depression is highly frequent and causes a strong burden. In order to reduce the duration of depressive episodes, clinicians would need to choose the most effective therapy for each individual right away. A prerequisite for this would be to have biomarkers at hand that would predict which individual would benefit from which kind of therapy (for example, pharmacotherapy or psychotherapy) or even from which kind of antidepressant class. In the past, neuroimaging, electroencephalogram, genetic, proteomic, and inflammation markers have been under investigation for their utility to predict targeted therapies. The present overview demonstrates recent advances in all of these different methodological areas and concludes that these approaches are promising but also that the aim to have such a marker available has not yet been reached. For example, the integration of markers from different systems needs to be achieved. With ongoing advances in the accuracy of sensing techniques and improvement of modelling approaches, this challenge might be achievable.

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Citations

Feb 11, 2020·Acta Neuropsychiatrica·Alfredo B Cuellar-BarbozaMarisol Ibarra-Ramirez
Jun 17, 2020·Archives of Women's Mental Health·Verinder SharmaIsabel Boate
Sep 18, 2020·Annals of General Psychiatry·Alessandro CuomoAndrea Fagiolini
Apr 3, 2020·European Neuropsychopharmacology : the Journal of the European College of Neuropsychopharmacology·Benedetta VaiFrancesco Benedetti
Aug 15, 2019·Stereotactic and Functional Neurosurgery·Karim MithaniNir Lipsman

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Methods Mentioned

BETA
pharmacotherapy
cognitive behavioral therapy

Software Mentioned

LDAEP

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