Year: 2019
Type: article
Study design: Observational Study
Abstract: ABSTRACT Converging evidence indicates that groups of patients with nominally distinct psychiatric diagnoses are not separated by sharp or discontinuous neurobiological boundaries. In healthy populations, individual differences in behavior are reflected in variability across the collective set of functional brain connections (functional connectome). These data suggest that the spectra of transdiagnostic symptom profiles observed in psychiatric patients may map onto detectable patterns of network function. To examine the manner through which neurobiological variation might underlie clinical presentation we obtained functional magnetic resonance imaging (fMRI) data from over 1,000 individuals, including 210 diagnosed with a primary psychotic disorder or affective psychosis (bipolar disorder with psychosis and schizophrenia or schizoaffective disorder), 192 presenting with a primary affective disorder without psychosis (unipolar depression, bipolar disorder without psychosis), and 608 demographically and data-quality matched healthy comparison participants recruited through a large-scale study of brain imaging and genetics. Here, we examine variation in functional connectomes across psychiatric diagnoses, finding striking evidence for disease connectomic “fingerprints” that are commonly disrupted across distinct forms of pathology and appear to scale as a function of illness severity. Conversely, other properties of network connectivity were preferentially disrupted in patients with psychotic illness, but not patients without psychotic symptoms. This work allows us to establish key biological and clinical features of the functional connectomes of severe mental disease. SIGNIFICANCE STATEMENT Historically, most research on the biological origins of psychiatric illness has focused on individual diagnostic categories, studied in isolation. Mounting evidence suggests nominally distinct psychiatric diagnoses are not separated by clear neurobiological boundaries. Here, we derive functional connectomic signatures in over 1,000 individuals including patients presenting with specific categories of impairment (psychosis), clinical diagnoses, or severity of illness as reflected in treatment seeking. Our analyses revealed features of connectome functioning that are commonly disrupted across distinct forms of pathology, scaling with clinical severity. Conversely, other aspects of network connectivity were preferentially disrupted in patients with psychotic illness, but not patients without psychotic symptoms. These data have important implications for the establishment of functional connectome fingerprints of severe mental disease.
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: hybrid
Funders: Howard Hughes Medical Institute, Brain and Behavior Research Foundation, Simons Foundation, Massachusetts General Hospital, Harvard University, Centre d'Imagerie BioMédicale, National Institutes of Health, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, National Institute of Mental Health, National Center for Research Resources
Awards: G1689143091, Longitudinal Imaging Studies in Bipolar Disorder, G2310474037, Neuroscience of Reward-Related Learning and Memory in Depression, G2932629777, Neuroscience of Reward-Related Learning and Memory in Depression, Multi level Analysis of Positive Valence Systems Across Mood Disorders, Probing the White Matter in Schizophrenia Using Novel MRS Techniques, G393103480, G4663119878, G4855150021, G4902108064, MRI Studies of Folate-Related Genes, Diet, and Development: Promise for Psychosis, Frontoparietal Network Integrity and Risk for Psychosis, Emotion regulation in depression: neural bases of reappraisal, MRS Studies of Glutamate and GABA in Bipolar Dissorder, Dimensional Neurogenetic Markers of Limbic System Integrity & Psychiatric Illness, A Storage Area Network for Structural and Functional Image Analysis, Neuroimaging Studies of Reward Processing in Depression, Silicon Graphics Prism Extreme 128P/1TB
OpenAlex ID: W2949123561
