Resting-state connectivity biomarkers define neurophysiological subtypes of depression

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.

Joint prediction of multiple scores captures better individual traits from brain images

“…Relating behavioral assessments to brain images helps grounding inter-individual vari-5 ability in anatomical and functional aspects of brain organization (Dubois and Adolphs, 2016;Abi-Dargham and Horga, 2016). The corresponding imaging-based biomarkers can then serve as intermediate phenotypes, or neurophenotypes to characterize the subjects (Drysdale et al, 2016). In this context, 10 recent years have witnessed the emergence of large-scale neuroimaging studies with rich assessments of subjects' traits and multiple brain-imaging modalities.…”

Neuroimaging tests for clinical psychiatry: Are we there yet?

“…31 The combination of symptoms plus connectivity patterns predicted responses to rTMS better than either feature alone. 10 As anticipated, the tentatively identified biomarkers do not map on to conventional diagnostic categories. 1,32 For example, Drysdale and colleagues 10 replicated the anxietyinsomnia-related depression biotype in patients with diagnoses of generalized anxiety disorder.…”

“…10 As anticipated, the tentatively identified biomarkers do not map on to conventional diagnostic categories. 1,32 For example, Drysdale and colleagues 10 replicated the anxietyinsomnia-related depression biotype in patients with diagnoses of generalized anxiety disorder. The studies by Sheffield and colleagues [20][21][22] found the same psychosis-related connectivity patterns, irrespective of whether the patient's formal diagnosis was schizophrenia, schizoaffective disorder, or a bipolar mood disorder.…”

“…[8][9][10][11][12] In a large multisite study 10 with a sample size of more than 1000 patients, 2 configurations were identified. One was characterized by psychomotor retardation and anhedonia linked to altered frontostriatal connectivity and diverse associations with the orbitofrontal cortex.…”

“…24 These cautions noted, there is reason for optimism. First, procedures for reducing artifacts are improving rapidly, and the studies described here are of generally high methodological quality (e.g., see Appendix 2, Figure S1 of the study by Drysdale and colleagues 10 ). Second, work in other areas of medicine suggests that biomarkers with even greater precision might be constructed from multidimensional indices, including combinations of genes, molecules and systems.…”