Multidimensional imaging techniques for prediction of treatment response in major depressive disorder

Abstract

A large number of studies have attempted to use neuroimaging tools to aid in treatment prediction models for major depressive disorder (MDD). Most such studies have reported on only one dimension of function and prediction at a time. In this study, we used three different tasks across domains of function (emotion processing, reward anticipation, and cognitive control, plus resting state connectivity completed prior to start of medication to predict treatment response in 13-36 adults with MDD. For each experiment, adults with MDD were prescribed only label duloxetine (all experiments), whereas another subset were prescribed escitalopram. We used a KeyNet (both Task derived masks and Key intrinsic Network derived masks) approach to targeting brain systems in a specific match to tasks. The most robust predictors were (Dichter et al., 2010) positive response to anger and (Gong et al., 2011) negative response to fear within relevant anger and fear TaskNets and Salience and Emotion KeyNet (Langenecker et al., 2018) cognitive control (correct rejections) within Inhibition TaskNet (negative) and Cognitive Control KeyNet (positive). Resting state analyses were most robust for Cognitive control Network (positive) and Salience and Emotion Network (negative). Results differed by whether an -fwhm or -acf (more conservative) adjustment for multiple comparisons was used. Together, these results implicate the importance of future studies with larger sample sizes, multidimensional predictive models, and the importance of using empirically derived masks for search areas.

Figure 1.

Salience and Emotion Network Intrinsic mask (green), with overlays of TaskNet for Anger (top row, red), Fear (middle row, yellow), and Reward Anticipation (bottom row, blue) derived from Neurosynth (http://neurosynth.org).

Figure 2.

Cognitive Control Network Intrinsic mask (cyan), with overlays of TaskNet for Errors (top row, red) and Inhibition/Rejections (middle row, yellow) derived from Neurosynth masks (http://neurosynth.org).

Figure 3.

Panel A. Significant Activation Prediction Models from Experiments 1 and 3. Red = Anger positive prediction for either Anger TaskNet or SEN KeyNet. Orange is overlap of significant predictors within Anger TaskNet and SEN KeyNey for anger positive prediction. Purple is prediction for fear with Fear TaskNet or SEN KeyNet in a negative direction. Yellow is prediction of treatment response with the Inhibition TaskNet mask for PGNG Rejections in an inverse direction (see Panel B for relationship between activation in right IFG/insula and treatment response), and green is significant prediction in the positive direction for the CCN KeyNet mask for Rejections. Image is radiological format.

Figure 3.

Panel A. Significant Activation Prediction Models from Experiments 1 and 3. Red = Anger positive prediction for either Anger TaskNet or SEN KeyNet. Orange is overlap of significant predictors within Anger TaskNet and SEN KeyNey for anger positive prediction. Purple is prediction for fear with Fear TaskNet or SEN KeyNet in a negative direction. Yellow is prediction of treatment response with the Inhibition TaskNet mask for PGNG Rejections in an inverse direction (see Panel B for relationship between activation in right IFG/insula and treatment response), and green is significant prediction in the positive direction for the CCN KeyNet mask for Rejections. Image is radiological format.

Figure 4.

KeyNet Intrinsic masks for DMN (red), CCN (green) and SEN (blue) used in the respective rs-fMRI analyses.

Figure 5.

Regions of resting state networks with significant seed to node connectivity that is predictive of treatment response in MDD (Experiment 4). Left Amygdala connectivity for SEN KeyNet is in purple, with negative prediction. Red illustrates positive prediction with left subgenual cingulate seed and uncus, and orange is negative connectivity prediction with left subgenual cingulate. Yellow displays the regions of positive connectivity with right DLPFC that are predictive of treatment response within the CCN KeyNet. Image is in radiological format.