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.

Optimizing Behavioral Paradigms to Facilitate Development of New Treatments for Anhedonia and Reward Processing Deficits in Schizophrenia and Major Depressive Disorder: Study Protocol.

Background: Behavioral tasks focusing on different subdomains of reward processing may provide more objective and quantifiable measures of anhedonia and impaired motivation compared with clinical scales. Typically, single tasks are used in relatively small studies to compare cases and controls in one indication, but they are rarely included in larger multisite trials. This is due to limited systematic standardization as well as the challenges of deployment in international studies and stringent adherence to the high regulatory requirements for data integrity. The Reward Task Optimization Consortium (RTOC) was formed to facilitate operational implementation of reward processing tasks, making them suitable for use in future large-scale, international, multisite drug development studies across multiple indications. The RTOC clinical study aims to conduct initial optimization of a set of tasks in patients with major depressive disorder (MDD) or schizophrenia (SZ). Methods: We will conduct a multicenter study across four EU countries. Participants (MDD = 37, SZ = 37, with ≤80 age- and gender-matched healthy volunteers) will attend a study visit comprising screening, self-report and clinically rated assessments of anhedonia and symptom severity, and three reward processing tasks; specifically, the Grip Strength Effort task, the Doors task, and the Reinforcement Learning Working Memory task. The Grip Strength Effort and Doors tasks include simultaneous electroencephalography/event-related potential recordings. Outcomes will be compared using a two-way group design of MDD and SZ with matched controls, respectively. Further analyses will include anhedonia assessment scores as covariates. Planned analyses will assess whether our findings replicate previously published data, and multisite deployment will be evaluated through assessments of quality and conduct. A subset of participants will complete a second visit, to assess test-retest reliability of the task battery. Discussion: This study will evaluate the operational deployment of three reward processing tasks to the regulatory standards required for use in drug development trials. We will explore the potential of these tasks to differentiate patients from controls and to provide a quantitative marker of anhedonia and/or impaired motivation, establishing their usefulness as endpoints in multisite clinical trials. This study should demonstrate where multifaceted reward deficits are similar or divergent across patient populations. Registration: ClinicalTrials.gov (NCT04024371).

Postprandial prolactin suppression appears absent in antipsychotic-treated male patients.

INTRODUCTION: Hyperprolactinemia is a common side-effect of antipsychotic treatment. Antipsychotics and hyperprolactinemia are both considered risk factors of metabolic disturbances and diabetes. Investigations on prolactin response to meal ingestion in antipsychotic-treated patients are missing. MATERIAL AND METHODS: In a case-control design, 49 antipsychotic-treated, clinically stable, non-diabetic, schizophrenia spectrum male patients were compared with 93 healthy male controls by age (33.1, SD 7.4 vs. 32.9, SD 6.6 years), body mass index (26.2, SD 4.6 vs. 26.1, SD 3.9 kg/m(2)) and waist circumference (96.4, SD 13.0 vs. 96.7, SD 11.9 cm). Serum-prolactin was measured in the morning and 90 min after ingestion of a standardized liquid meal (2268 kJ). RESULTS: Fasting prolactin levels varied considerably, and mean fasting prolactin levels did not significantly differ between patients and controls (12.33, SD 11.58 vs. 10.06, SD 8.67 ng/ml, p = 0.623). In the controls, postprandial serum prolactin was significantly reduced (Δ -2.53, SD 9.75 ng/ml, p = 0.016). In antipsychotic-treated patients postprandial serum prolactin tended to increase (Δ 2.62, SD 10.96 ng/ml, p = 0.081). Analyses of subgroups based on the prolactinogenic liability of their antipsychotic treatment indicated 22 to 65% higher postprandial prolactin levels with high and intermediate prolactinogenic antipsychotics. DISCUSSION: A physiological postprandial suppression of serum prolactin appears absent in antipsychotic-treated males. Marked variability in fasting prolactin levels may reflect individual variations in the diurnal cycle. Uniform acquisition procedures accounting for diurnal variation and food intake may enhance reliability of prolactin levels in antipsychotic-treated male patients.

Glucometabolic hormones and cardiovascular risk markers in antipsychotic-treated patients.

OBJECTIVE: Treatment with antipsychotic drugs is widely associated with metabolic side effects such as weight gain and disturbed glucose metabolism, but the pathophysiologic mechanisms are unclear. METHOD: Fifty nondiabetic (fasting plasma glucose ≤ 7.0 mmol/L), antipsychotic-treated male patients (ICD-10 diagnosis code F20, F21, F22, F25, F28, or F60; mean ± SD age = 33.0 ± 6.7 years; body mass index [BMI; kg/m²] = 26.0 ± 4.7; waist circumference = 95.9 ± 13.3 cm; glycated hemoglobin A1c [HbA1c] = 5.7% ± 0.3%) and 93 age- and waist circumference-matched healthy male controls (age = 33 ± 7.3 years; BMI = 26.1 ± 3.9; waist circumference = 94.6 ± 11.9 cm; HbA1c = 5.7% ± 0.3%) participated in this cross-sectional study. Blood was sampled in the fasting state and 90 minutes after ingestion of a standardized liquid meal (2,268 kJ). The primary outcomes were glucometabolic hormones and cardiovascular risk markers. Data were collected between March 2008 and February 2010. RESULTS: Compared to healthy controls, patients were characterized by elevated fasting levels of proinsulin, C-peptide, and glucose-dependent insulinotropic polypeptide (GIP) (P < .05) and higher postprandial levels of insulin, proinsulin, C-peptide, and GIP (P ≤ .02). Also, patients exhibited elevated plasma levels of C-reactive protein and signs of dyslipidemia. Fasting plasma levels of insulin, glucagon, glucagon-like peptide-1 (GLP-1), ghrelin, leptin, adiponectin, tumor necrosis factor-α, plasminogen activator inhibitor-1, and interleukin-6 and postprandial levels of glucagon, GLP-1, ghrelin, leptin, and adiponectin did not differ between groups. CONCLUSIONS: Presenting with an insulin resistant-like pattern, including beta cell hypersecretion and elevated GIP levels, nondiabetic antipsychotic-treated patients display emerging signs of dysmetabolism and a compromised cardiovascular risk profile. The appetite-regulating hormones GLP-1 and ghrelin appear not to be influenced by antipsychotic treatment. Our findings provide new clinical insight into the pathophysiology associated with metabolic side effects of antipsychotic treatment and put emphasis on the importance of implementing metabolic screening into psychiatric practice. TRIAL REGISTRATION: ClinicalTrials.gov identifier NCT00627757.

The clinical pharmacokinetics of Lu AA21004 and its major metabolite in healthy young volunteers.

Lu AA21004 is a novel multimodal antidepressant that is currently in phase 3 development. The objective of this report was to detail the clinical pharmacokinetics of Lu AA21004 and its major but inactive metabolite Lu AA34443 (3-methyl-4-(2-piperazine-1-yl-phenylsulfanyl)-benzoic acid) in healthy men and women aged between 18 and 53 years. Data from two single-dose and one multiple-dose study were combined; the total number of volunteers was 97 (64 men, 33 women). Blood and urine samples were collected after p.o. and i.v. administrations to determine the content of Lu AA21004 and Lu AA34443 performed with a validated method. Standard pharmacokinetic parameters were estimated with non-compartmental analysis. The absolute bioavailability was 75%. After oral administration, Lu AA21004 showed an extended absorption phase, a medium clearance and a large volume of distribution resulting in late t(max) values and a mean elimination half-life of 57 hr. The exposure of Lu AA21004 showed a linear relationship with dose in the dose ranges studied (up to 75-mg single dosing and 60-mg multiple dosing). After weight correction, no differences in exposure for Lu AA21004 and Lu AA34443 were observed between men and women. The renal clearance of Lu AA21004 was negligible. The major metabolite Lu AA34443 had a half-life similar to that of Lu AA21004 but a lower accumulation ratio at steady-state, indicating formation-rate-limited elimination. In conclusion, Lu AA21004 showed an extended absorption phase, a medium clearance and a large volume of distribution.