The goal of this project is to identify connectome-specific correlates and predictors of successful treatment outcome in patients with severe depression followed prospectively while receiving one of three rapidly acting therapeutic interventions. These interventions include electroconvulsive therapy (ECT), serial ketamine infusion and total sleep deprivation (TSD). Via neurostimulation, pharmacological or behavioral perturbation, each elicits relatively robust antidepressant effects and has a distinct mode of access to the central nervous system. A related goal is to characterize variations in neural connectivity associated with individual clinical, behavioral or physiological factors that distinguish patients with severe depression from demographically similar non-depressed controls. Since response to standard antidepressant therapies is moderate, variable, and protracted, understanding how brain networks change with rapid clinical improvement could provide a key opportunity to devise more immediate, personalized and effective treatment and prevention strategies for refractory depression.
Project Timespan: Sept. 2, 2016 - May 31, 2020
Data Being Collected
Subjects include 200 patients with severe depression clinically eligible to receive ECT (n=60), serial ketamine (n=60) or TSD (n=80) and 140 controls, combining control data collected locally (n=40) with data from the HCP resource (n=100). Each patient will receive MRI, behavioral/cognitive testing and a blood draw before and after completing one of the interventions.
Major Depression, Mood Disorders, White Matter, Functional Connectivity, Structural Connectivity, Neuroplasticity, Antidepressant
One of the most effective interventions for intractable major depressive episodes is electroconvulsive therapy (ECT). Because ECT is also relatively fast-acting, longitudinal study of its neurobiological effects offers critical insight into the mechanisms underlying depression and antidepressant response. Here we assessed modulation of intrinsic brain activity in corticolimbic networks associated with ECT and clinical response.
Ketamine elicits an acute antidepressant effect in patients with major depressive disorder (MDD). Here, we used diffusion imaging to explore whether regional differences in white matter microstructure prior to treatment may predict clinical response 24h following ketamine infusion in 10 MDD patients.
Major depressive disorder (MDD) is associated with dysfunctional corticolimbic networks, making functional connectivity studies integral for understanding the mechanisms underlying MDD pathophysiology and treatment. Resting-state functional connectivity (RSFC) studies analyze patterns of temporally coherent intrinsic brain activity in "resting-state networks" (RSNs). The default-mode network (DMN) has been of particular interest to depression research; however, a single RSN is unlikely to capture MDD pathophysiology in its entirety, and the DMN itself can be characterized by multiple RSNs. This, coupled with conflicting previous results, underscores the need for further research. Here, we measured RSFC in MDD by targeting RSNs overlapping with corticolimbic regions and further determined whether altered patterns of RSFC were restored with electroconvulsive therapy (ECT). MDD patients exhibited hyperconnectivity between ventral striatum (VS) and the ventral default-mode network (vDMN), while simultaneously demonstrating hypoconnectivity with the anterior DMN (aDMN). ECT influenced this pattern: VS-vDMN hyperconnectivity was significantly reduced while VS-aDMN hypoconnectivity only modestly improved. RSFC between the salience RSN and dorsomedial prefrontal cortex was also reduced in MDD, but was not affected by ECT. Taken together, our results support a model of ventral/dorsal imbalance in MDD and further suggest that the VS is a key structure contributing to this desynchronization.
Whether plasticity of white matter (WM) microstructure relates to therapeutic response in major depressive disorder (MDD) remains uncertain. We examined diffusion tensor imaging (DTI) correlates of WM structural connectivity in patients receiving electroconvulsive therapy (ECT), a rapidly acting treatment for severe MDD. Tract-Based Spatial Statistics (TBSS) applied to DTI data (61 directions, 2.5 mm(3) voxel size) targeted voxel-level changes in fractional anisotropy (FA), and radial (RD), axial (AD) and mean diffusivity (MD) in major WM pathways in MDD patients (n=20, mean age: 41.15 years, 10.32 s.d.) scanned before ECT, after their second ECT and at transition to maintenance therapy. Comparisons made at baseline with demographically similar controls (n=28, mean age: 39.42 years, 12.20 s.d.) established effects of diagnosis. Controls were imaged twice to estimate scanning-related variance. Patients showed significant increases of FA in dorsal fronto-limbic circuits encompassing the anterior cingulum, forceps minor and left superior longitudinal fasciculus between baseline and transition to maintenance therapy (P<0.05, corrected). Decreases in RD and MD were observed in overlapping regions and the anterior thalamic radiation (P<0.05, corrected). Changes in DTI metrics associated with therapeutic response in tracts showing significant ECT effects differed between patients and controls. All measures remained stable across time in controls. Altered WM microstructure in pathways connecting frontal and limbic areas occur in MDD, are modulated by ECT and relate to therapeutic response. Increased FA together with decreased MD and RD, which trend towards normative values with treatment, suggest increased fiber integrity in dorsal fronto-limbic pathways involved in mood regulation.
The HCP provides imaging, behavioral, and demographic data from a large population of healthy adults. This poses special challenges for protecting the privacy of participants, especially because it is a family study including twins and their siblings. Unless these data are properly managed, there is a risk that participants might be recognizable to family members and others. In addition, some of the data elements collected might harm or embarrass participants if they were to be inadvertently identified.
To protect the privacy of our participants, the HCP has implemented a two-tiered plan for data sharing, with different provisions for handling Open Access data and Restricted Data.
Open Access Data (all imaging data and most of the behavioral data) is available to those who register an account at ConnectomeDB and agree to the Open Access Data Use Terms. This includes agreement to comply with institutional rules and regulations.
This means you may need the approval of your IRB or Ethics Committee to use the data. The released HCP data are not considered de-identified, since certain combinations of HCP Restricted Data (available through a separate process) might allow identification of individuals. Different national, state and local laws may apply and be interpreted differently, so it is important that you consult with your IRB or Ethics Committee before beginning your research. If needed and upon request, the HCP will provide a certificate stating that you have accepted the HCP Open Access Data Use Terms.
Please note that everyone who works with HCP open access data must review and agree to these terms, including those who are accessing shared copies of this data. If you are sharing HCP Open Access data, please advise your co-researchers that they must register with ConnectomeDB and agree to these terms.
Restricted Data Elements include a number of categories, such as family structure (twin or non-twin status), age by year, and handedness.
Each qualified investigator wanting to use Restricted Data must agree to the Restricted Data Use Terms. These terms explain how Restricted Data may and may not be used and shared, and they reiterate the need for compliance with institutional requirements. They include major limitations on how Restricted Data can be incorporated into publications and public presentations.
You must comply with your institutional rules and regulations regarding research on human subjects. The released HCP data are not considered de-identified, since certain combinations of HCP Restricted Data might allow identification of individuals. Different national, state and local laws may apply and be interpreted differently, so it is important that you consult with your IRB or Ethics Committee before beginning your research. If needed and upon request, the HCP will provide a certificate stating that you have accepted the HCP Open and Restricted Access Data Use Terms.