Deep phenotyping towards precision psychiatry of first-episode depression - the Brain Drugs-Depression cohort.

BACKGROUND: Major Depressive Disorder (MDD) is a heterogenous brain disorder, with potentially multiple psychosocial and biological disease mechanisms. This is also a plausible explanation for why patients do not respond equally well to treatment with first- or second-line antidepressants, i.e., one-third to one-half of patients do not remit in response to first- or second-line treatment. To map MDD heterogeneity and markers of treatment response to enable a precision medicine approach, we will acquire several possible predictive markers across several domains, e.g., psychosocial, biochemical, and neuroimaging. METHODS: All patients are examined before receiving a standardised treatment package for adults aged 18-65 with first-episode depression in six public outpatient clinics in the Capital Region of Denmark. From this population, we will recruit a cohort of 800 patients for whom we will acquire clinical, cognitive, psychometric, and biological data. A subgroup (subcohort I, n = 600) will additionally provide neuroimaging data, i.e., Magnetic Resonance Imaging, and Electroencephalogram, and a subgroup of patients from subcohort I unmedicated at inclusion (subcohort II, n = 60) will also undergo a brain Positron Emission Tomography with the [11C]-UCB-J tracer binding to the presynaptic glycoprotein-SV2A. Subcohort allocation is based on eligibility and willingness to participate. The treatment package typically lasts six months. Depression severity is assessed with the Quick Inventory of Depressive Symptomatology (QIDS) at baseline, and 6, 12 and 18 months after treatment initiation. The primary outcome is remission (QIDS ≤ 5) and clinical improvement (≥ 50% reduction in QIDS) after 6 months. Secondary endpoints include remission at 12 and 18 months and %-change in QIDS, 10-item Symptom Checklist, 5-item WHO Well-Being Index, and modified Disability Scale from baseline through follow-up. We also assess psychotherapy and medication side-effects. We will use machine learning to determine a combination of characteristics that best predict treatment outcomes and statistical models to investigate the association between individual measures and clinical outcomes. We will assess associations between patient characteristics, treatment choices, and clinical outcomes using path analysis, enabling us to estimate the effect of treatment choices and timing on the clinical outcome. DISCUSSION: The BrainDrugs-Depression study is a real-world deep-phenotyping clinical cohort study of first-episode MDD patients. TRIAL REGISTRATION: Registered at clinicaltrials.gov November 15th, 2022 (NCT05616559).

EEG-vigilance regulation is associated with and predicts ketamine response in major depressive disorder.

Ketamine offers promising new therapeutic options for difficult-to-treat depression. The efficacy of treatment response, including ketamine, has been intricately linked to EEG measures of vigilance. This research investigated the interplay between intravenous ketamine and alterations in brain arousal, quantified through EEG vigilance assessments in two distinct cohorts of depressed patients (original dataset: n = 24; testing dataset: n = 24). Clinical response was defined as a decrease from baseline of >33% on the Montgomery-Åsberg Depression Rating Scale (MADRS) 24 h after infusion. EEG recordings were obtained pre-, start-, end- and 24 h post- infusion, and the resting EEG was automatically scored using the Vigilance Algorithm Leipzig (VIGALL). Relative to placebo (sodium chloride 0.9%), ketamine increased the amount of low-vigilance stage B1 at end-infusion. This increase in B1 was positively related to serum concentrations of ketamine, but not to norketamine, and was independent of clinical response. In contrast, treatment responders showed a distinct EEG pattern characterized by a decrease in high-vigilance stage A1 and an increase in low-vigilance B2/3, regardless of whether placebo or ketamine had been given. Furthermore, pretreatment EEG differed between responders and non-responders with responders showing a higher percentage of stage A1 (53% vs. 21%). The logistic regression fitted on the percent of A1 stages was able to predict treatment outcomes in the testing dataset with an area under the ROC curve of 0.7. Ketamine affects EEG vigilance in a distinct pattern observed only in responders. Consequently, the percentage of pretreatment stage A1 shows significant potential as a predictive biomarker of treatment response.Clinical Trials Registration: https://www.clinicaltrialsregister.eu/ctr-search/trial/2013-000952-17/CZ Registration number: EudraCT Number: 2013-000952-17.

Effect of Antidepressant Treatment on 5-HT4 Receptor Binding and Associations With Clinical Outcomes and Verbal Memory in Major Depressive Disorder.

BACKGROUND: Brain serotonin 4 receptor (5-HT4R) levels are lower in untreated patients with major depressive disorder (MDD) and are linked to verbal memory. Here, we investigated the relationship between 5-HT4R levels, clinical outcomes, and cognitive function in patients with MDD who initiated selective serotonin reuptake inhibitor drug treatment. METHODS: Ninety patients with moderate to severe depression underwent molecular brain imaging to measure 5-HT4R binding prior to antidepressant treatment with escitalopram. Pretreatment 5-HT4R binding was assessed for its ability to predict treatment outcome at weeks 4, 8, or 12. In 40 patients who were rescanned 8 weeks posttreatment, change in cerebral 5-HT4R binding was correlated with change in verbal memory and with change in depressive symptoms, as evaluated by the 6-item Hamilton Depression Rating Scale. RESULTS: After 8 weeks of serotonergic intervention, neostriatal 5-HT4R binding was reduced by 9%. Global change in 5-HT4R binding from baseline was associated with verbal memory outcomes, but not with overall clinical depressive symptom outcomes. Pretreatment 5-HT4R binding did not predict clinical recovery status at week 8 and was not associated with change in the 6-item Hamilton Depression Rating Scale scores. CONCLUSIONS: In patients with moderate to severe MDD, treatment with selective serotonin reuptake inhibitors downregulated neostriatal 5-HT4R levels, which is consistent with the notion that the drugs increase cerebral extracellular serotonin. The less global brain 5-HT4R levels were downregulated after selective serotonin reuptake inhibitors, the more verbal memory improved, highlighting the potential importance of 5-HT4R as a treatment target in MDD. The findings offer insights into mechanisms that underlie antidepressant effects and point to new directions for precision medicine treatments for MDD.

EEG wakefulness regulation in transdiagnostic patients after a recent suicide attempt.

OBJECTIVE: Decades of research have not yet produced statistically reliable predictors of preparatory behavior eventually leading to suicide attempts or deaths by suicide. As the nature of suicidal behavior is complex, it is best investigated in a transdiagnostic approach, while assessing objective markers, as proposed by the Research Domain Criteria (Cuthbert, 2013). METHODS: A 15-min resting-state EEG was recorded in 45 healthy controls, and 49 transdiagnostic in-patients with a recent (<6 months) suicide attempt. Brain arousal regulation in eyes-closed condition was assessed with the Vigilance Algorithm Leipzig (VIGALL) (Sander et al., 2015). RESULTS: A significant incline of median vigilance and vigilance slope was observed in patients within the first 3-min of the EEG recording. Additionally, a significant positive correlation of self-reported suicidal ideation with the vigilance slope over 15-min recording time, as well as a significant negative correlation with EEG vigilance stage A1 during the first 3-min was found. CONCLUSIONS: Transdiagnostic patients with a recent suicide attempt show a distinct vigilance regulation pattern. Further studies including a control group consisting of patients without life-time suicide attempts are needed to increase the clinical utility of the findings. SIGNIFICANCE: These findings might serve as potential objective markers of suicidal behavior.

A recent suicide attempt and the heartbeat: Electrophysiological findings from a trans-diagnostic cohort of patients and healthy controls.

Suicidal behavior is influenced by a multitude of factors, making prediction and prevention of suicide attempts (SA) a challenge. A useful tool to uncover underlying pathophysiology or propose new therapy approaches are biomarkers, especially within the context of point-of-care tests. Heart rate variability (HRV) is a well-established biomarker of mental health, and measures the activity of the sympathetic and parasympathetic nervous system (PNS). Previous studies reported a correlation between lower PNS activity and suicidality. However, most studies involved participants from a healthy population, patients without history of suicide attempts, or patients with a single diagnosis. 52 in-patients with a recent suicide attempt (<6 months), and 43 controls without history of SA or psychiatric diagnoses confirmed study participation. The included patients age ranged between 18 and 65 years, 65% had psychiatric comorbidities. Patients with dementia, cognitive impairments, acute psychosis, chronic non suicidal self-harming behavior, or current electroconvulsive therapy were excluded. A 15-min resting state electrocardiography was recorded with two bipolar electrodes attached to the right and left insides of the wrists. The multiple regression analyses showed lower parasympathetic, and higher sympathetic activity in patients compared to controls. Partial correlation found a positive trend result between self-reported suicidality and the very low frequency band. ROC curve analysis revealed an acceptable to excellent clinical accuracy of HRV parameters. Therefore, HRV parameters could be reliable discriminative biomarkers between in-patients with a recent SA and healthy controls. One limitation is the lack of a control group consisting of in-patients without life-time suicidal ideation or attempts.

Association between the loudness dependence of auditory evoked potential, serotonergic neurotransmission and treatment outcome in patients with depression.

Previous studies have suggested that the loudness dependence of auditory evoked potential (LDAEP) is associated with the effectiveness of antidepressant treatment in patients with major depressive disorders (MDD). Furthermore, both LDAEP and the cerebral serotonin 4 receptor (5-HT4R) density is inversely related to brain serotonin levels. We included 84 patients with MDD and 22 healthy controls to examined the association between LDAEP and treatment response and its association with cerebral 5-HT4R density. Participants underwent both EEG and 5-HT4R neuroimaging with [11C]SB207145 PET. Thirty-nine patients with MDD were re-examined after 8 weeks of treatment with selective serotonin reuptake inhibitors/serotonin noradrenaline reuptake inhibitor (SSRI/SNRI). We found that the cortical source of LDAEP was higher in untreated patients with MDD compared to healthy controls (p=0.03). Prior to SSRI/SNRI treatment, subsequent treatment responders had a negative association between LDAEP and depressive symptoms and a positive association between scalp LDAEP and symptom improvement at week 8. This was not found in source LDAEP. In healthy controls, we found a positive correlation between both scalp and source LDAEP and cerebral 5-HT4R binding but that was not observed in patients with MDD. We did not see any changes in scalp and source LDAEP in response to SSRI/SNRI treatment. These results support a theoretical framework where both LDAEP and cerebral 5-HT4R are indices of cerebral 5-HT levels in healthy individuals while this association seems to be disrupted in MDD. The combination of the two biomarkers may be useful for stratifying patients with MDD. Clinical Trials Registration:https://clinicaltrials.gov/ct2/show/NCT02869035?draw=1Registration number: NCT0286903.

Serotonin 4 Receptor Brain Binding in Major Depressive Disorder and Association With Memory Dysfunction.

Importance: The cerebral serotonin 4 (5-HT4) receptor is a promising novel target for treatment of major depressive disorder (MDD), and pharmacological stimulation of the 5-HT4 receptor has been associated with improved learning and memory in healthy individuals. Objective: To map the neurobiological signatures of patients with untreated MDD compared with healthy controls and to examine the association between cerebral 5-HT4 receptor binding and cognitive functions in the depressed state. Design, Setting, and Participants: This case-control study used baseline data from the NeuroPharm clinical depression trial in Denmark. Adult participants included antidepressant-free outpatients with a current moderate to severe depressive episode and healthy controls. All participants completed positron emission tomography (PET) scanning with [11C]SB207145 for quantification of brain 5-HT4 receptor binding, but only the patients underwent cognitive testing. Data analyses were performed from January 21, 2020, to April 22, 2022. Main Outcomes and Measures: The main study outcome was the group difference in cerebral 5-HT4 receptor binding between patients with MDD and healthy controls. In addition, the association between 5-HT4 receptor binding and verbal memory performance in the patient group was tested. Other cognitive domains (working memory, reaction time, emotion recognition bias, and negative social emotions) were assessed as secondary outcomes. Results: A total of 90 patients with untreated MDD (mean [SD] age, 27.1 [8.2] years; 64 women [71.1%]) and 91 healthy controls (mean [SD] age, 27.1 [8.0] years; 55 women [60.4%]) were included in the analysis. Patients with current MDD had significantly lower cerebral 5-HT4 receptor binding than healthy controls (-7.0%; 95% CI, -11.2 to -2.7; P = .002). In patients with MDD, there was a correlation between cerebral 5-HT4 receptor binding and verbal memory (r = 0.29; P = .02). Conclusions and Relevance: Results of this study show that cerebral 5-HT4 receptor binding was lower in patients with MDD than in healthy controls and that the memory dysfunction in patients with MDD was associated with lower cerebral 5-HT4 receptor binding. The cerebral 5-HT4 receptor is a promising treatment target for memory dysfunction in patients with MDD.

Accuracy of high-density EEG electrode position measurement using an optical scanner compared with the photogrammetry method.

Objective: To determine the feasibility and accuracy of a handheld optical scanner to measure the three-dimensional (3D) EEG electrode coordinates in a high-density array of 256 electrodes. Methods: We compared the optical scanning with a previously validated method, based on photogrammetry. Electrode coordinates were co-registered with the MRI of the patients, and mean distance error relative to the three-dimensional MRI reconstruction was determined for each patient. We included 60 patients: 30 were measured using the photogrammetry method, and 30 age and gender matched patients were measured with the optical scanner. Results: Using the optical scanner, the mean distance error was 1.78 mm (95% confidence interval: 1.59-1.98 mm) which was significantly lower (p < 0.001) compared with the photogrammetry method (mean distance error: 2.43 mm; 95% confidence interval: 2.28-2.57 mm). The real-time scanning took 5-10 min per patient. Conclusions: The handheld optical scanner is more accurate and feasible, compared to the photogrammetry method. Significance: Measuring EEG electrode positions in high-density array, using the optical scanner is suitable for clinical implementation in EEG source imaging for presurgical evaluation.

Concurrent anxiety in patients with major depression and cerebral serotonin 4 receptor binding. A NeuroPharm-1 study.

Concurrent anxiety is frequent in major depressive disorder and a shared pathophysiological mechanism between anxiety and other depressive symptoms is plausible. The serotonin 4 receptor (5-HT4R) has been implicated in both depression and anxiety. This is the first study to investigate the association between the cerebral 5-HT4R binding and anxiety in patients with depression before and after antidepressant treatment and the association to treatment response. Ninety-one drug-free patients with depression were positron emission tomography scanned with the 5-HT4R ligand [11C]-SB207145. Depression severity and concurrent anxiety was measured at baseline and throughout 8 weeks of antidepressant treatment. Anxiety measures included four domains: anxiety/somatization factor score; Generalized Anxiety Disorder 10-items (GAD-10) score; anxiety/somatization factor score ≥7 (anxious depression) and syndromal anxious depression. Forty patients were rescanned at week 8. At baseline, we found a negative association between global 5-HT4R binding and both GAD-10 score (p < 0.01) and anxiety/somatization factor score (p = 0.06). Further, remitters had a higher baseline anxiety/somatization factor score compared with non-responders (p = 0.04). At rescan, patients with syndromal anxious depression had a greater change in binding relative to patients with non-syndromal depression (p = 0.04). Concurrent anxiety in patients with depression measured by GAD-10 score and anxiety/somatization factor score is negatively associated with cerebral 5-HT4R binding. A lower binding may represent a subtype with reduced natural resilience against anxiety in a depressed state, and concurrent anxiety may influence the effect on the 5-HT4R from serotonergic antidepressants. The 5-HT4R is a promising neuroreceptor for further understanding the underpinnings of concurrent anxiety in patients with depression.

Deep learning applied to electroencephalogram data in mental disorders: A systematic review.

In recent medical research, tremendous progress has been made in the application of deep learning (DL) techniques. This article systematically reviews how DL techniques have been applied to electroencephalogram (EEG) data for diagnostic and predictive purposes in conducting research on mental disorders. EEG-studies on psychiatric diseases based on the ICD-10 or DSM-V classification that used either convolutional neural networks (CNNs) or long -short-term-memory (LSTMs) networks for classification were searched and examined for the quality of the information they contained in three domains: clinical, EEG-data processing, and deep learning. Although we found that the description of EEG acquisition and pre-processing was sufficient in most of the studies, we found, that many of them lacked a systematic characterization of clinical features. Furthermore, many studies used misguided model selection procedures or flawed testing. It is recommended that the study of psychiatric disorders using DL in the future must improve the quality of clinical data and follow state of the art model selection and testing procedures so as to achieve a higher research standard and head toward a clinical significance.

NeuroPharm study: EEG wakefulness regulation as a biomarker in MDD.

While several electroencephalogram (EEG)-based biomarkers have been proposed as diagnostic or predictive tools in major depressive disorder (MDD), there is a clear lack of replication studies in this field. Markers that link clinical features such as disturbed wakefulness regulation in MDD with neurophysiological patterns are particularly promising candidates for e.g., EEG-informed choices of antidepressive treatment. We investigate if we in an independent MDD sample can replicate abnormal findings of EEG-vigilance regulation during rest and as a predictor for antidepressive treatment response. EEG-resting state was recorded in 91 patients and 35 healthy controls from the NeuroPharm trial. EEG-vigilance was assessed using the Vigilance Algorithm Leipzig (VIGALL). We compared the vigilance regulation during rest between patients and healthy controls and between remitters/responders and non-remitters/non-responders after eight weeks of SSRI/SNRI treatment using two different sets of response criteria (NeuroPharm and iSPOT-D). We replicated previous findings showing hyperstable EEG-wakefulness regulation in patients in comparison to healthy subjects. Responders defined by the iSPOT-D criteria showed a higher propensity toward low vigilance stages in comparison to patients with no response at pretreatment, however, this did not apply when using the NeuroPharm criteria. EEG-wakefulness regulation patterns normalized toward patterns of healthy controls after 8 weeks of treatment. This replication study supports the diagnostic value of EEG-vigilance regulation and its usefulness as a biomarker for the choice of treatment in MDD.

Pretreatment qEEG biomarkers for predicting pharmacological treatment outcome in major depressive disorder: Independent validation from the NeuroPharm study.

Several electroencephalogram (EEG) biomarkers for prediction of drug response in major depressive disorder (MDD) have been proposed, but validations in larger independent datasets are missing. In the current study, we investigated the prognostic value of previously suggested EEG biomarkers. We gathered data that matched prior studies in terms of EEG methodology, clinical criteria for MDD, and statistical approach as closely as possible. The NeuroPharm study is a non-randomized and open label prospective clinical trial. One hundred antidepressant free patients with MDD were enrolled in the study and 79 (57 female) were included in the per-protocol analysis. The biomarkers candidates for cross-validation were derived from prior studies such as iSPOT-D and EMBARC and include frontal and occipital alpha power and asymmetry and delta and theta activity at anterior cingulate cortex (ACC). The alpha asymmetry, reported in two out of six prior studies, could be partially validated. We found that in female patients, larger right than left frontal alpha power prior to drug treatment was associated with better clinical outcome 8 weeks later. Moreover, female non-responder had higher central left alpha power relative to the right. In contrast to prior reports, we found that lower theta activity at ACC was present in remitters and was associated with greater improvement at week 8. We provide evidence that in women with MDD, alpha asymmetry seems to be the most promising EEG biomarker for prediction of treatment response. Registration number: NCT02869035.

Predicting Treatment Outcome in Major Depressive Disorder Using Serotonin 4 Receptor PET Brain Imaging, Functional MRI, Cognitive-, EEG-Based, and Peripheral Biomarkers: A NeuroPharm Open Label Clinical Trial Protocol.

BACKGROUND: Between 30 and 50% of patients with major depressive disorder (MDD) do not respond sufficiently to antidepressant regimens. The conventional pharmacological treatments predominantly target serotonergic brain signaling but better tools to predict treatment response and identify relevant subgroups of MDD are needed to support individualized and mechanistically targeted treatment strategies. The aim of this study is to investigate antidepressant-free patients with MDD using neuroimaging, electrophysiological, molecular, cognitive, and clinical examinations and evaluate their ability to predict clinical response to SSRI treatment as individual or combined predictors. METHODS: We will include 100 untreated patients with moderate to severe depression (>17 on the Hamilton Depression Rating Scale 17) in a non-randomized open clinical trial. We will collect data from serotonin 4 receptor positron emission tomography (PET) brain scans, functional magnetic resonance imaging (fMRI), electroencephalogram (EEG), cognitive tests, psychometry, and peripheral biomarkers, before (at baseline), during, and after 12 weeks of standard antidepressant treatment. Patients will be treated with escitalopram, and in case of non-response at week 4 or intolerable side effects, offered to switch to a second line treatment with duloxetine. Our primary outcome (treatment response) is assessed using the Hamilton depression rating subscale 6-item scores at week 8, compared to baseline. In a subset of the patients (n = ~40), we will re-assess the neurobiological response (using PET, fMRI, and EEG) 8 weeks after initiated pharmacological antidepressant treatment, to map neurobiological signatures of treatment responses. Data from matched controls will either be collected or is already available from other cohorts. DISCUSSION: The extensive investigational program with follow-up in this large cohort of participants provides a unique possibility to (a) uncover potential biomarkers for antidepressant treatment response, (b) apply the findings for future stratification of MDD, (c) advance the understanding of pathophysiological underpinnings of MDD, and (d) uncover how putative biomarkers change in response to 8 weeks of pharmacological antidepressant treatment. Our data can pave the way for a precision medicine approach for optimized treatment of MDD and also provides a resource for future research and data sharing. CLINICAL TRIAL REGISTRATION: The study was registered at clinicaltrials.gov prior to initiation (NCT02869035; 08.16.2016, URL: https://clinicaltrials.gov/ct2/results?cond=&term=NCT02869035&cntry=&state=&city=&dist=).

Pre-intervention test-retest reliability of EEG and ERP over four recording intervals.

In this study we present the test-retest reliability of pre-intervention EEG/ERP (electroencephalogram/event-related potentials) data across four recording intervals separated by a washout period (18-22 days). POz-recording-reference EEG/ERP (28 sites, average reference) were recorded from thirty-two healthy male participants. Participants were randomly allocated into different intervention sequences, each with four intervention regimens: 10 mg vortioxetine, 20 mg vortioxetine, 15 mg escitalopram and Placebo. We report classical EEG spectra: δ (1-4 Hz), θ (4-8 Hz), α (8-12 Hz), ß (12-30 Hz), γ1 (30-45 Hz) and γ2 (45-80 Hz) of resting state and vigilance-controlled, and of auditory steady state response, as well as ERP components N100, P200 and P300 in auditory oddball task and error related negativity (ERN) and error positivity (Pe) in hybrid flanker task. Reliability was quantified using intra-class correlation coefficient (ICC). We found that θ, α and ß of continuous EEG were highly reliable (ICCs ≥ 0.84). Evoked power of other tasks demonstrated larger variability and less reliability compared to the absolute power of continuous EEG. Furthermore, reliabilities of ERP measures were lower compared to those of the EEG spectra. We saw fair to excellent reliability of the amplitude of the components such as Pe (0.60-0.82) and P300 (0.55-0.80). Moreover, blood tests confirmed that there was no measurable drug carry-over from the previous intervention. The results support that EEG/ERP is reliable across four recording intervals, thus it can be used to assess the effect of different doses and types of drugs with CNS effects.