Neurocognitive signatures predicting risk of recurrent depression

点击翻译按钮获取中文摘要

Depression is a leading cause of disability, because many people who have recovered from its symptoms ("symptomatic phase") will experience recurring episodes. Most research has focused on the symptomatic phase of depression and often assumed that when people have no symptoms, they are cured. A disorder can, however, be ongoing even when patients do not experience symptoms. In this "asymptomatic" state people can be at high risk of developing symptoms in the future. Many patients take antidepressant medication over years to reduce the risk of recurrence, because our current way of predicting their risk based on number of previous episodes is very inaccurate. It is usually assumed that those treatments working to reduce symptoms of depression will also be beneficial in their future prevention, but this is largely unproven. The development of new treatments that prevent recurrence has been hampered by a lack of knowledge about psychological and brain changes that are risk factors. In an MRC-funded study, we have identified such risk factors in recovered depression patients that predict, on an individual basis, which patient will have another episode in the next year. By adding functional MRI scans, and a novel test of being inclined to self-blame to standard measures, we achieved 83% accuracy, exceeding the recommended target for useful so-called "prognostic markers". In contrast, standard measures alone were no better than chance guessing who would develop another episode. Patients were scanned whilst they experienced self-blame, which is thought to play an important role in depression by decreasing self-worth and hope. We have demonstrated that asymptomatic patients who go on to develop depression show altered connections in the self-blame-related brain network which differed from those who remained well. Despite these encouraging results in 50 patients, it is unknown: 1) whether we can confirm the result that functional MRI and psychological tests of self-blame predict subsequent recurrence of depression in a larger independent group2) whether MRI is needed for predicting who will develop depression at an individual level or could be replaced by adding further psychological and hormonal measures 3) whether the brain networks found to be disrupted when blaming oneself in depression are linked to abnormal stress hormones, the only established chemical risk factor for recurrence 4) whether the disruption in brain networks when blaming oneself makes people more vulnerable to develop depression after a stressful life event measured weekly via a mobile appTo answer these questions, we propose to enrol 150 patients recovered from depression who have stopped their antidepressant medication in accordance with guidelines (as in our previous study). An initial MRI scan, cognitive tests, and stress hormones will be used to predict recurrence after one year. This will deliver much needed evidence for reproducible psychological and brain-based risk factors to 1) inform novel psychological and brain training, as well as brain stimulation treatment approaches and 2) develop a so-called "prognostic marker" to predict recurrence risk for affected individuals. This marker could be used in future clinical trials to select patients that are at high risk of recurrence. This would greatly reduce the number of patients needed for a trial and thereby reduce its cost. Further, if we can replace expensive MRI scans with cheaper measures, the prognostic marker could be studied in future trials to determine whether it helps people with depression to make decisions about continuing their antidepressant medication. After completing this project, our future goal is to facilitate the development of novel treatments more likely to remedy depression in the long-term by preventing recurrence rather than to only treat its symptoms. Our collaborator, Janssen, are actively developing markers for depression recurrence and are highly committed.