Periodic Reporting for period 1 - Debrasa (Deep brain targets for neurostimulation in affective disorders)
Período documentado: 2017-05-01 hasta 2019-04-30
Major depressive disorder and bipolar disorder are among the most serious psychiatric disorders with high prevalence and illness-related disability. Even with the multitude of methods used to treat depression, a significant portion of patients fails to respond, resulting in an estimated 1–3% prevalence of treatment-resistant depression (TRD). The most efficacious therapeutic alternative for TRD is an electroconvulsive therapy, which helps, however, in only about half of TRD cases. Deep brain stimulation (DBS), which is commonly used in neurological diseases, is now being applied as an alternative technique in the treatment of TRD. Nevertheless, the evidence for the efficacy and safety of DBS in depression is still weak and an optimal approach has yet to be established. Reliable biomarkers of brain abnormality in depression might help determine the suitability and efficacy of DBS treatment and personalized medicine might be the future outlook for DBS treatment of depression. Despite advanced neuroimaging methods developed in recent years, the pathophysiological mechanisms of depression remain poorly understood.
The main goal of the project was to provide necessary knowledge about neurobiology of major depressive disorder. We studied the human brain to gain insights and collect information on objective biomarkers of depression. We found conspicuous characteristics of the brain networks affected by depression using electroencephalography. Better characterization of the pathophysiology of depression can improve diagnostics and consequently ameliorate treatment of depressive patients. Objective evaluation of the brain impairment in depression could be potentially useful for early identification of the illness that could help better management of the disease. Faster and more efficacious treatment would lead to faster reintegration of patients into the society, thus reducing economic burdens of the disease.
The main goal of the project was to provide necessary knowledge about neurobiology of major depressive disorder. We studied the human brain to gain insights and collect information on objective biomarkers of depression. We found conspicuous characteristics of the brain networks affected by depression using electroencephalography. Better characterization of the pathophysiology of depression can improve diagnostics and consequently ameliorate treatment of depressive patients. Objective evaluation of the brain impairment in depression could be potentially useful for early identification of the illness that could help better management of the disease. Faster and more efficacious treatment would lead to faster reintegration of patients into the society, thus reducing economic burdens of the disease.
IIn this project we studied the neurobiology of depression using electroencephalographic (EEG) recordings of brain activity during resting condition. Spatiotemporal characteristics of this activity indicate how different brain networks re-organize themselves in time. In the upper section of the figure we see six scalp maps (A-F) derived from EEG recordings. Each map represents the spatial characteristic of one state of the brain activity, so called „microstate“. Temporal characteristics of these states can be evaluated on the EEG recordings as illustrated in the lower section of the figure. Periods of stable scalp maps are color-coded. Presence of each brain microstate can be examined and impairment in the dynamics of underlying brain activity can be assessed.
We investigated the spatiotemporal characteristics of electrical brain activity in 19 depressive patients and 19 healthy controls using microstate analysis. Patients with different affective disorders were examined during their depressive episode. The severity of depression, as measured with standard questionnaire, correlated with occurrence of one of the microstates in patients. Thus, we showed that microstate analysis might be useful for objective depression assessment. We performed the same analysis also on a homogenous group of 17 patients in remission of bipolar disorder and 17 healthy controls. These patients, even though not being depressed at the moment of examination, showed abnormally increased presence of two microstates. Thus, this abnormality might be considered as a candidate electrophysiological non-specific trait marker of bipolar disorder.
In another EEG study we investigated connectivity properties of deep brain structures potentially implicated in DBS treatment. We examined 26 patients during depressive episode within different affective disorders and 25 healthy controls. One of the investigated deep brain structures, i.e. amygdala, showed deviant connectivity patterns to other brain regions. Thus, this structure seems to play an important role in neurobiology of depression and as such might be considered as a potential future target for DBS in treating TRD.
We investigated the spatiotemporal characteristics of electrical brain activity in 19 depressive patients and 19 healthy controls using microstate analysis. Patients with different affective disorders were examined during their depressive episode. The severity of depression, as measured with standard questionnaire, correlated with occurrence of one of the microstates in patients. Thus, we showed that microstate analysis might be useful for objective depression assessment. We performed the same analysis also on a homogenous group of 17 patients in remission of bipolar disorder and 17 healthy controls. These patients, even though not being depressed at the moment of examination, showed abnormally increased presence of two microstates. Thus, this abnormality might be considered as a candidate electrophysiological non-specific trait marker of bipolar disorder.
In another EEG study we investigated connectivity properties of deep brain structures potentially implicated in DBS treatment. We examined 26 patients during depressive episode within different affective disorders and 25 healthy controls. One of the investigated deep brain structures, i.e. amygdala, showed deviant connectivity patterns to other brain regions. Thus, this structure seems to play an important role in neurobiology of depression and as such might be considered as a potential future target for DBS in treating TRD.
In current clinical practice, the diagnosis of depression is made by evaluation of symptoms using questionnaires and interviews. Such evaluation is, however, subjectively based on patients' responses. Patients are frequently misdiagnosed and often identified at late stages of disease progression, which can lead to inadequate treatment. Although objective neuroimaging techniques such as electroencephalography or magnetic resonance imaging are accessible, their use is only restricted to differential diagnostics to exclude epileptic activity or structural lesions. This is because no measurable neuroimaging biomarkers of depression are available. We showed that depression can be examined with objective tools such as microstate and connectivity analyses of scalp recorded EEG signal. The observed electrophysiological abnormalities could potentially become trait markers of affective disorders and/or markers of disease progression or can provide necessary information for targeted treatment with deep brain stimulation technique.
Although more studies on larger patient cohorts are needed to confirm our findings, first steps towards improving diagnostics and consequently treatment of depression has been done. Patients that will be adequately treated in clinical stages of the affective disorder will be sooner reintegrated into the society contributing to its economy.
Although more studies on larger patient cohorts are needed to confirm our findings, first steps towards improving diagnostics and consequently treatment of depression has been done. Patients that will be adequately treated in clinical stages of the affective disorder will be sooner reintegrated into the society contributing to its economy.