Resting-state connectivity biomarkers define neurophysiological subtypes of depression.

Publication Type	Academic Article
Authors	Drysdale A, Grosenick L, Downar J, Dunlop K, Mansouri F, Meng Y, Fetcho R, Zebley B, Oathes D, Etkin A, Schatzberg A, Sudheimer K, Keller J, Mayberg H, Gunning F, Alexopoulos G, Fox M, Pascual-Leone A, Voss H, Casey B, Dubin M, Liston C
Journal	Nat Med
Volume	23
Issue	1
Pagination	28-38
Date Published	12/05/2016
ISSN	1546-170X
Keywords	Brain, Depressive Disorder, Major
Abstract	Biomarkers have transformed modern medicine but remain largely elusive in psychiatry, partly because there is a weak correspondence between diagnostic labels and their neurobiological substrates. Like other neuropsychiatric disorders, depression is not a unitary disease, but rather a heterogeneous syndrome that encompasses varied, co-occurring symptoms and divergent responses to treatment. By using functional magnetic resonance imaging (fMRI) in a large multisite sample (n = 1,188), we show here that patients with depression can be subdivided into four neurophysiological subtypes ('biotypes') defined by distinct patterns of dysfunctional connectivity in limbic and frontostriatal networks. Clustering patients on this basis enabled the development of diagnostic classifiers (biomarkers) with high (82-93%) sensitivity and specificity for depression subtypes in multisite validation (n = 711) and out-of-sample replication (n = 477) data sets. These biotypes cannot be differentiated solely on the basis of clinical features, but they are associated with differing clinical-symptom profiles. They also predict responsiveness to transcranial magnetic stimulation therapy (n = 154). Our results define novel subtypes of depression that transcend current diagnostic boundaries and may be useful for identifying the individuals who are most likely to benefit from targeted neurostimulation therapies.
DOI	10.1038/nm.4246
PubMed ID	27918562
PubMed Central ID	PMC5624035