A posterior-alpha ageing network is differentially associated with antidepressant effects of venlafaxine and rTMS.

Major depressive disorder (MDD) is a highly prevalent psychiatric disorder, but chances for remission largely decrease with each failed treatment attempt. It is therefore desirable to assign a given patient to the most promising individual treatment option as early as possible. We used a polygenic score (PGS) informed electroencephalography (EEG) data-driven approach to identify potential predictors for MDD treatment outcome. Post-hoc we conducted exploratory analyses in order to understand the results in depth. First, an EEG independent component analysis produced 54 functional brain networks in a large heterogeneous cohort of psychiatric patients (n = 4,045; 5-84 yrs.). Next, the network that was associated to PGS for antidepressant-response (PRS-AR) in an independent sample (n = 722) was selected: an age-related posterior alpha network that explained >60 % of EEG variance, and was highly stable over recording time. Translational analyses were performed in two other independent datasets to examine if the network was predictive of psychopharmacotherapy (n = 535) and/or repetitive transcranial magnetic stimulation (rTMS) and concomitant psychotherapy (PT; n = 186) outcome. The network predicted remission to venlafaxine (p = 0.015), resulting in a normalized positive predicted value (nPPV) of 138 %, and rTMS + PT - but in opposite direction for women (p = 0.002) relative to men (p = 0.018) - yielding a nPPV of 131 %. Blinded out-of-sample validations for venlafaxine (n = 29) and rTMS + PT (n = 36) confirmed the findings for venlafaxine, while results for rTMS + PT could not be replicated. These data suggest the existence of a relatively stable EEG posterior alpha aging network related to PGS-AR that has potential as MDD treatment predictor.

Associations between psychotropic drugs and rsEEG connectivity and network characteristics: a cross-sectional study in hospital-admitted psychiatric patients.

Introduction: Resting-state EEG (rsEEG) characteristics, such as functional connectivity and network topology, are studied as potential biomarkers in psychiatric research. However, the presence of psychopharmacological treatment in study participants poses a potential confounding factor in biomarker research. To address this concern, our study aims to explore the impact of both single and multi-class psychotropic treatments on aforementioned rsEEG characteristics in a psychiatric population. Methods: RsEEG was analyzed in a real-world cross-sectional sample of 900 hospital-admitted psychiatric patients. Patients were clustered into eight psychopharmacological groups: unmedicated, single-class treatment with antipsychotics (AP), antidepressants (AD) or benzodiazepines (BDZ), and multi-class combinations of these treatments. To assess the associations between psychotropic treatments and the macroscale rsEEG characteristics mentioned above, we employed a general linear model with post-hoc tests. Additionally, Spearman's rank correlation analyses were performed to explore potential dosage effects. Results: Compared to unmedicated patients, single-class use of AD was associated with lower functional connectivity in the delta band, while AP was associated with lower functional connectivity in both the delta and alpha bands. Single-class use of BDZ was associated with widespread rsEEG differences, including lower functional connectivity across frequency bands and a different network topology within the beta band relative to unmedicated patients. All of the multi-class groups showed associations with functional connectivity or topology measures, but effects were most pronounced for concomitant use of all three classes of psychotropics. Differences were not only observed in comparison with unmedicated patients, but were also evident in comparisons between single-class, multi-class, and single/multi-class groups. Importantly, multi-class associations with rsEEG characteristics were found even in the absence of single-class associations, suggesting potential cumulative or interaction effects of different classes of psychotropics. Dosage correlations were only found for antipsychotics. Conclusion: Our exploratory, cross-sectional study suggests small but significant associations between single and multi-class use of antidepressants, antipsychotics and benzodiazepines and macroscale rsEEG functional connectivity and network topology characteristics. These findings highlight the importance of considering the effects of specific psychotropics, as well as their interactions, when investigating rsEEG biomarkers in a medicated psychiatric population.

A polygenic-informed approach to a predictive EEG signature empowers antidepressant treatment prediction: A proof-of-concept study.

The treatment of major depressive disorder (MDD) is hampered by low chances of treatment response in each treatment step, which is partly due to a lack of firmly established outcome-predictive biomarkers. Here, we hypothesize that polygenic-informed EEG signatures may help predict antidepressant treatment response. Using a polygenic-informed electroencephalography (EEG) data-driven, data-reduction approach, we identify a brain network in a large cohort (N=1,123), and discover it is sex-specifically (male patients, N=617) associated with polygenic risk score (PRS) of antidepressant response. Subsequently, we demonstrate in three independent datasets the utility of the network in predicting response to antidepressant medication (male, N=232) as well as repetitive transcranial magnetic stimulation (rTMS) and concurrent psychotherapy (male, N=95). This network significantly improves a treatment response prediction model with age and baseline severity data (area under the curve, AUC=0.623 for medicaton; AUC=0.719 for rTMS). A predictive model for MDD patients, aimed at increasing the likelihood of being a responder to antidepressants or rTMS and concurrent psychotherapy based on only this network, yields a positive predictive value (PPV) of 69% for medication and 77% for rTMS. Finally, blinded out-of-sample validation of the network as predictor for psychotherapy response in another independent dataset (male, N=50) results in a within-subsample response rate of 50% (improvement of 56%). Overall, the findings provide a first proof-of-concept of a combined genetic and neurophysiological approach in the search for clinically-relevant biomarkers in psychiatric disorders, and should encourage researchers to incorporate genetic information, such as PRS, in their search for clinically relevant neuroimaging biomarkers.

Event-related potentials and use of psychotropic medication in major psychiatric disorders.

BACKGROUND: Attention deficits measured using event-related potentials (ERPs) have been frequently reported in several major psychiatric disorders, e.g. mood disorder (MD), psychotic disorder (PD) and substance use disorder (SUD). However, comparisons between these specific categories are lacking. Here we investigated if electrophysiological parameters of basic information processing are associated with the above-mentioned categories of psychiatric disorders, or instead were associated with general psychopathology. METHODS: 579 subjects with MD, PD or SUD and healthy controls (HC) were included. Participants were tested in a passive auditory and an active visual oddball paradigm to assess mismatch negativity (MMN), P3A and P3B amplitudes. Additionally, we examined associations between these measures and psychoactive medication treatments. RESULTS: All patients had significantly lower P3B amplitudes compared to healthy controls, while only SUD patients had lower P3A amplitudes than MD, PD and HC. PD patients also produced significantly less MMN than both MD and SUD patients. Additionally, we found significantly higher P3B amplitude in HC compared to patients without psychopharmacological treatment and patients treated with two or more psychoactive compounds (polypharmacy), but no significant associations with medication on P3A and MMN amplitudes. CONCLUSIONS: Our results add to the theory that P3B deficits are associated with general psychopathology, whereas P3A and MMN deficits appear to be associated with substance abuse and psychotic disorders respectively.

High-throughput analysis of amino acids in plant materials by single quadrupole mass spectrometry.

BACKGROUND: The amino acid profile of plants is an important parameter in assessments of their growth potential, resource-use efficiency and/or quality as food and feed. Screening studies may involve large number of samples but the classical amino acid analysis is limited by the fact that it is very time consuming with typical chromatographic run times of 70 min or more. RESULTS: We have here developed a high-throughput method for analysis of amino acid profiles in plant materials. The method combines classical protein hydrolysis and derivatization with fast separation by UHPLC and detection by a single quadrupole (QDa) mass spectrometer. The chromatographic run time is reduced to 10 min and the precision, accuracy and sensitivity of the method are in line with other recent methods utilizing advanced and more expensive mass spectrometers. The sensitivity of the method is at least a factor 10 better than that of methods relying on detection by fluorescence or UV. It is possible to downscale sample size to 20 mg without compromising reproducibility, which makes the method ideal for analysis of very small sample amounts. CONCLUSION: The developed method allows high-throughput analysis of amino acid profiles in plant materials. The analysis is robust and accurate as well as compatible with both free amino acids and protein hydrolysates. The QDa detector offers high sensitivity and accuracy, while at the same time being relatively simple to operate and cheap to purchase, thus significantly reducing the overall analytical costs compared to methods based on more advanced mass spectrometers.

Agitation after minor trauma: combativeness as a cardinal catatonic feature.

Catatonia is a syndrome of motor dysregulation, usually associated with psychiatric, neurological, systemic and drug-related diseases. Retarded and excited types exist, both of which often go unrecognised in clinical practice. We describe a 64-year-old woman who gradually developed insomnia, started communicating less, complained of feeling restless and ended up injuring relatives. Initiation of symptoms followed a fibula fracture. The patient was diagnosed with excited-type catatonia with prominent combativeness because of minor trauma and rapidly recovered after lorazepam treatment instatement. Our case demonstrates that catatonia can follow minor traumatic injury and how excited-type catatonic features may go unrecognised in general practitioner and specialist settings. Moreover, we show that catatonia may be recurrent, necessitating long-term treatment and very gradual lorazepam tapering.

Towards a solution for performance related confounds: frontal, striatal and parietal activation during a continuous spatiotemporal working memory manipulation task.

Working memory plays a role in various forms of psychopathology. However, working memory consists of multiple theoretical components that may be differently taxed by various specific types of task, and brain activation differences between patients and healthy controls may result from differences in task performance. This makes it difficult to interpret such results in terms of disease-related dysfunctions in affected regions or networks. The aim of the current study was to determine the brain activation related to the updating of spatiotemporal content of working memory, in such a way that performance-related confounds in future clinical studies would be minimized. Nineteen healthy volunteers performed a task involving a continuous updating process during fMRI measurement. A frontostriatal network including medial and lateral prefrontal cortex, inferior frontal cortex, premotor cortex, supplementary motor cortex, thalamus and putamen was found to be related to the updating process. The results constrain the set of brain regions plausibly related to the specific updating component of working memory. Further, the task design may be of use in future studies of pathological conditions such as schizophrenia due to the minimization of potential confounds.

Research projects in the collaborative antwerp psychiatric research institute.

INTRODUCTION: In the following article CAPRI presents its current research projects. SUBJECTS AND METHOD: The team leaders were asked to present and summarize the project they had been working on. The fields in which research was conducted are: Child and Adolescent Psychiatry, Cognitive and Psychomotor Dysfunctions in Schizophrenia, fMRI in Schizophrenia, Cognitive and Psychomotor Dysfunctions in Major Depressive Disorder, Chronic Fatigue Syndrome, Addiction Medicine and Forensic Psychiatry. RESULTS: An overview of recent and ongoing research projects is provided and the main results are summarized.

Prefrontal, parietal and basal activation associated with the reordering of a two-element list held in working memory.

A functional specialization in the prefrontal cortex along a dorsal-ventral gradient according to the type of processing in working memory, i.e. manipulation vs. maintenance, has been proposed based on previous neuroimaging studies. This seems particularly important for the further understanding of the functional architecture underlying working memory problems in patient populations. The current study examines the prefrontal involvement in the maintenance and manipulation of serial order of elements in working memory, with a task designed to be as simple as possible, to the aim of possible uses in clinical studies. Subjects held two-element ordered lists in memory and were presented with pseudo-random sequences of "reorder" and "maintain" cues. Reorder cues were found to be associated with activation in the dorsal prefrontal cortex, parietal cortex and the basal ganglia. The results show that the simple task was indeed sufficient to evoke the prefrontal activation of interest, add to the information on functional dorsal-ventral specialization in prefrontal cortex and provide support for a prefrontal-parietal monitoring-manipulation network.

The use of atypical antipsychotics in the treatment of catatonia.

PURPOSE: Evidence indicates that classical antipsychotics may aggravate non-malignant and malignant catatonia (MC). Atypical antipsychotics are less likely to cause movement disorders than classical antipsychotics and they are being frequently prescribed in disorders that can be associated with catatonia. Therefore, the important question that arises is whether atypical antipsychotics have a role to play in the treatment of catatonia. MATERIALS AND METHODS: A Medline search was performed to locate papers on the use of atypical antipsychotics in catatonia published between 1970 and 31st December 2004. RESULTS: The literature on the use of atypical antipsychotics in catatonia consists of case reports and retrospective studies. In most cases of non-MC a reduction of the catatonic symptoms is reported upon treatment with atypical antipsychotics. Cases of MC relate mainly to the neuroleptic malignant syndrome (NMS), which is considered as an iatrogenic stuporous variant of MC caused by antipsychotics. CONCLUSION: There are indications that atypical antipsychotics may be useful in non-MC. As a consequence, one should not only focus on the possible extrapyramidal and autonomic side effects of these drugs, but also on the possible beneficial effects on certain brain functions and on the catatonic symptomatology. However, randomized controlled trials are needed to evaluate the effect of these drugs, and caution is advisable, since cases of NMS have been linked to treatment with atypical antipsychotics. There is no evidence to prescribe atypical antipsychotics in MC.