Neuroanatomic correlates of psychopathologic components of major depressive disorder
- PMID: 15809407
- DOI: 10.1001/archpsyc.62.4.397
Neuroanatomic correlates of psychopathologic components of major depressive disorder
Abstract
Background: The Hamilton Depression Rating Scale (HDRS) is widely used to measure the severity of depression in mood disorders. Total HDRS score correlates with brain metabolism as measured by fludeoxyglucose F 18 ([(18)F]-FDG) positron emission tomography. The HDRS comprises distinct symptom clusters that may be associated with different patterns of regional brain glucose metabolism.
Objective: To examine associations between HDRS component psychopathologic clusters and resting glucose cerebral metabolism assessed by [(18)F]-FDG positron emission tomography. Patients We evaluated 298 drug-free patients who met the DSM-III-R criteria for major depressive disorder.
Main outcome measures: Five principal components were extracted from the 24-item HDRS for all subjects and ProMax rotated: psychic depression, loss of motivated behavior, psychosis, anxiety, and sleep disturbance. The [(18)F]-FDG scans were acquired in a subgroup of 43 drug-free patients in twelve 5-minute frames. Voxel-level correlation maps were generated with HDRS total and factor scores.
Results: Total HDRS score correlated positively with activity in a large bilateral ventral cortical and subcortical region that included limbic, thalamic, and basal ganglia structures. Distinct correlation patterns were found with the 3 individual HDRS factors. Psychic depression correlated positively with metabolism in the cingulate gyrus, thalamus, and basal ganglia. Sleep disturbance correlated positively with metabolism in limbic structures and basal ganglia. Loss of motivated behavior was negatively associated with parietal and superior frontal cortical areas.
Conclusions: Different brain regions correlate with discrete symptom components that compose the overall syndrome of major depression. Future studies should extend knowledge about specific regional networks by identifying responsible neurotransmitters related to specific psychopathologic components of mood disorders.
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