Functional magnetic resonance imaging (fMRI) could be used to predict which patients with recovered major depressive disorder are most likely to have more depressive episodes, according to a study published in JAMA Psychiatry.
Researchers from King’s College London and The University of Manchester, funded by the MRC, gave 64 patients who were in remission from major depressive disorder, and not on prescribed medication, fMRI scans to look for atypical connections in the brain.
During the scans the participants were asked to imagine acting badly towards their best friends and they experienced self-blaming emotions such as guilt. Over the following 14 months they were seen regularly and monitored for symptoms. At the end of the study 37 remained in remission while 27 had had a recurrence of their depression.
In the fMRI scans of those who went on to have another episode of depression there was a higher connectedness between two parts of the brain that have been previously linked to guilt – the anterior temporal lobe and the subgenual region.
People who remained in remission over the following year did not have this increased interconnectedness. The researchers also tested the approach on a control group of 39 people with no personal or family history of major depressive disorder, finding that they also did not have the increased interconnectedness.
Using this information the researchers were able to predict who would go on to have another depressive episode and who would remain in remission with an overall accuracy of 75 per cent (48 out of 64 predicted cases). For 25 per cent of patients the prediction failed (16 out of 64).
Dr. Roland Zahn, lead researcher based at the Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King’s College London, said: “This is the first study to show that fMRI can be used to make predictions about who will develop depression in the future, once they’ve recovered from a previous episode. These findings could mean that fMRI could help doctors make better decisions about who should continue their antidepressants and who should stop them.
“Before this approach can be rolled out and used in the clinic, we need to test it out in an independent group of patients and improve it, so that its accuracy reaches 80 per cent. If future studies can reach this mark, then this approach will be vitally important as there are currently no accurate ways to predict those who will have a recurrence following recovery.”
Dr. Kathryn Adcock, head of neurosciences and mental health at the MRC, said: “This exciting research has the potential to help identify those individuals who are more likely to suffer from recurrent episodes of depression and will therefore benefit most from long-term treatment and medication. This work could aid the discovery of new treatments for depression because clinical trials will be better able to focus on people with a more comparable disorder and experience.”
Funding: The study was funded by the Department of Science and Technology, Government of India, National Centre for Biological Sciences, and Tata Institute of Fundamental Research.
Source: Jack Stonebridge – King’s College London
Image Credit: The image is credited to the researchers and is adapted from a Medical Research Council version of the press release
Original Research: Abstract for “Self-blame–Selective Hyperconnectivity Between Anterior Temporal and Subgenual Cortices and Prediction of Recurrent Depressive Episodes” by Karen E. Lythe, PhD; Jorge Moll, MD, PhD; Jennifer A. Gethin, MRes; Clifford I. Workman, BS; Sophie Green, PhD; Matthew A. Lambon Ralph, PhD; John F. W. Deakin, PhD; and Roland Zahn, MD in JAMA Psychiatry. Published online October 7 2015 doi:10.1001/jamapsychiatry.2015.1813
Self-blame–Selective Hyperconnectivity Between Anterior Temporal and Subgenual Cortices and Prediction of Recurrent Depressive Episodes
Importance Patients with remitted major depressive disorder (MDD) were previously found to display abnormal functional magnetic resonance imaging connectivity (fMRI) between the right superior anterior temporal lobe (RSATL) and the subgenual cingulate cortex and adjacent septal region (SCSR) when experiencing self-blaming emotions relative to emotions related to blaming others (eg, “indignation or anger toward others”). This finding provided the first neural signature of biases toward overgeneralized self-blaming emotions (eg, “feeling guilty for everything”), known to have a key role in cognitive vulnerability to MDD. It is unknown whether this neural signature predicts risk of recurrence, a crucial step in establishing its potential as a prognostic biomarker, which is urgently needed for stratification into pathophysiologically more homogeneous subgroups and for novel treatments.
Objective To use fMRI in remitted MDD at baseline to test the hypothesis that RSATL-SCSR connectivity for self-blaming relative to other-blaming emotions predicts subsequent recurrence of depressive episodes.
Design, Setting, and Participants A prospective cohort study from June 16, 2011, to October 10, 2014, in a clinical research facility completed by 75 psychotropic medication–free patients with remitted MDD and no relevant comorbidity. In total, 31 remained in stable remission, and 25 developed a recurring episode over the 14 months of clinical follow-up and were included in the primary analysis. Thirty-nine control participants with no personal or family history of MDD were recruited for further comparison.
Main Outcomes and Measures Between-group difference (recurring vs stable MDD) in RSATL connectivity, with an a priori SCSR region of interest for self-blaming vs other-blaming emotions.
Results We corroborated our hypothesis that during the experience of self-blaming vs other-blaming emotions, RSATL-SCSR connectivity predicted risk of subsequent recurrence. The recurring MDD group showed higher connectivity than the stable MDD group (familywise error–corrected P < .05 over the a priori SCSR region of interest) and the control group. In addition, the recurring MDD group also exhibited RSATL hyperconnectivity with the right ventral putamen and claustrum and the temporoparietal junction. Together, these regions predicted recurrence with 75% accuracy.
Conclusions and Relevance To our knowledge, this study is the first to provide a demonstration of an fMRI signature of recurrence risk in remitted MDD. Additional studies are needed for its further optimization and validation as a prognostic biomarker.
“Self-blame–Selective Hyperconnectivity Between Anterior Temporal and Subgenual Cortices and Prediction of Recurrent Depressive Episodes” by Karen E. Lythe, PhD; Jorge Moll, MD, PhD; Jennifer A. Gethin, MRes; Clifford I. Workman, BS; Sophie Green, PhD; Matthew A. Lambon Ralph, PhD; John F. W. Deakin, PhD; and Roland Zahn, MD in JAMA Psychiatry. Published online October 7 2015 doi:10.1001/jamapsychiatry.2015.1813