Data driven clusters derived from resting state functional connectivity: Findings from the EMBARC study. (February 2023)
- Record Type:
- Journal Article
- Title:
- Data driven clusters derived from resting state functional connectivity: Findings from the EMBARC study. (February 2023)
- Main Title:
- Data driven clusters derived from resting state functional connectivity: Findings from the EMBARC study
- Authors:
- Chin Fatt, Cherise R.
Minhajuddin, Abu
Jha, Manish K.
Mayes, Taryn
Rush, A. John
Trivedi, Madhukar H. - Abstract:
- Abstract: Background: To address the clinical heterogeneity of Major Depressive Disorder (MDD), this investigation determined whether resting state functional magnetic resonance imaging (fMRI) could be deployed to identify circuit based homogeneous subgroups, and whether subgroups identified show differential treatment outcomes. Methods: Pretreatment resting state fMRIs obtained from 278 outpatients with nonpsychotic MDD from Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression Study were used to create data-driven subgroups using CLICK clustering. These subgroups were then compared using baseline clinical data, as well as baseline-to-week 8 changes in depression severity measured using the 17-item Hamilton Rating Scale for Depression (HAMD17 ) and response/remission rates by treatment group. Results: Three subgroups were identified. Cluster-1 was characterized by overall hyper connectivity coupled with profound hypoconnectivity between the supramarginal gyrus (executive control network; ECN) and the superior frontal cortex (dorsal attention network; DAN). Cluster-2 was characterized by overall hypoconnectivity coupled with hyperconnectivity between supramarginal gyrus (ECN) and superior frontal cortex (DAN). Cluster-3 showed hypoconnectivity, especially profound between the angular cortex (default mode network; DMN) and middle frontal cortex (ECN). While baseline clinical measures did not differentiate the three clusters,Abstract: Background: To address the clinical heterogeneity of Major Depressive Disorder (MDD), this investigation determined whether resting state functional magnetic resonance imaging (fMRI) could be deployed to identify circuit based homogeneous subgroups, and whether subgroups identified show differential treatment outcomes. Methods: Pretreatment resting state fMRIs obtained from 278 outpatients with nonpsychotic MDD from Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression Study were used to create data-driven subgroups using CLICK clustering. These subgroups were then compared using baseline clinical data, as well as baseline-to-week 8 changes in depression severity measured using the 17-item Hamilton Rating Scale for Depression (HAMD17 ) and response/remission rates by treatment group. Results: Three subgroups were identified. Cluster-1 was characterized by overall hyper connectivity coupled with profound hypoconnectivity between the supramarginal gyrus (executive control network; ECN) and the superior frontal cortex (dorsal attention network; DAN). Cluster-2 was characterized by overall hypoconnectivity coupled with hyperconnectivity between supramarginal gyrus (ECN) and superior frontal cortex (DAN). Cluster-3 showed hypoconnectivity, especially profound between the angular cortex (default mode network; DMN) and middle frontal cortex (ECN). While baseline clinical measures did not differentiate the three clusters, Cluster-3 had the remission rate (51.6%) compared to Cluster-1 and Cluster-2 (32.7% and 31.9%) when treated with sertraline. Limitations: Due to the exploratory nature of these analyses, there were no adjustments for multiple comparisons. Conclusions: Baseline functional connectivity can be used to subgroup patients with MDD that differ in acute phase treatment outcomes. Measures of connectivity may address the heterogeneity of MDD. … (more)
- Is Part Of:
- Journal of psychiatric research. Volume 158(2023)
- Journal:
- Journal of psychiatric research
- Issue:
- Volume 158(2023)
- Issue Display:
- Volume 158, Issue 2023 (2023)
- Year:
- 2023
- Volume:
- 158
- Issue:
- 2023
- Issue Sort Value:
- 2023-0158-2023-0000
- Page Start:
- 150
- Page End:
- 156
- Publication Date:
- 2023-02
- Subjects:
- Functional connectivity -- Data driven -- EMBARC -- Major depressive disorder -- CLICK -- Remission
Psychiatry -- Periodicals
Mental Disorders -- Periodicals
Maladies mentales -- Périodiques
Psychiatry
Electronic journals
Periodicals
616.89005 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00223956 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.jpsychires.2022.12.002 ↗
- Languages:
- English
- ISSNs:
- 0022-3956
- Deposit Type:
- Legaldeposit
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