Explore the vast range of titles available.

Since more than 3 decades, schizophrenia (SZ) has been regarded as a neurodevelopmental disorder. The neurodevelopmental hypothesis proposes that SZ is associated with genetic and environmental risk factors, which influence connectivity in neuronal circuits during vulnerable developmental periods. We carried out a non-systematic review of genetic/environmental factors that increase SZ risk in light of its neurodevelopmental hypothesis. We also reviewed the potential impact of SZ-related environmental and genetic risk factors on grey and white matter pathology and brain function based on magnetic resonance imaging and post-mortem studies. Finally, we reviewed studies that have used patient-derived neuronal models to gain knowledge of the role of genetic and environmental factors in early developmental stages. Taken together, these studies indicate that a variety of environmental factors may interact with genetic risk factors during the pre- or postnatal period and/or during adolescence to induce symptoms of SZ in early adulthood. These risk factors induce disturbances of macro- and microconnectivity in brain regions involving the prefrontal, temporal and parietal cortices and the hippocampus. On the molecular and cellular level, a disturbed synaptic plasticity, loss of oligodendrocytes and impaired myelination have been shown in brain regions of SZ patients. These cellular/histological phenotypes are related to environmental risk factors such as obstetric complications, maternal infections and childhood trauma and genetic risk factors identified in recent genome-wide association studies. SZ-related genetic risk may contribute to active processes interfering with synaptic plasticity in the adult brain. Advances in stem cell technologies are providing promising mechanistic insights into how SZ risk factors impact the developing brain. Further research is needed to understand the timing of the different complex biological processes taking place as a result of the interplay between genetic and environmental factors.

Our aim is to review the most recent evidence on novel antibody therapies for Alzheimer's disease directed against amyloid‐β. This is a joint statement of the European Association of Neurology and the European Psychiatric Association. After numerous unsuccessful endeavors to create a disease‐modifying therapy for Alzheimer's disease, substantial and consistent evidence supporting the clinical effectiveness of monoclonal antibodies aimed at amyloid‐β is finally emerging. The latest trials not only achieved their primary objective of slowing the progression of the disease over several months but also demonstrated positive secondary clinical outcomes and a decrease in amyloid‐β levels as observed through positron emission tomography scans. Taken as a whole, these findings mark a significant breakthrough by substantiating that reducing amyloid‐β yields tangible clinical benefits, beyond mere changes in biomarkers. Concurrently, the regular utilization of the new generation of drugs will determine whether statistical efficacy translates into clinically meaningful improvements. This may well signify the dawning of a new era in the development of drugs for Alzheimer's disease.

Severe psychiatric disorders such as schizophrenia are related to cognitive and negative symptoms, which often are resistant to current treatment approaches. The glutamatergic system has been implicated in the pathophysiology of schizophrenia and affective disorders. A key component is the dysfunction of the glutamatergic N -methyl- d -aspartate (NMDA) receptor. Substances regulating activation/inhibition of the NMDA receptor have been investigated in schizophrenia and major depression and are promising in therapeutic approaches of negative symptoms, cognition, and mood. In schizophrenia, add-on treatments with glycine, d -serine, d -alanine, d -cycloserine, d -amino acid oxidase inhibitors, glycine transporter-1 (GlyT-1) inhibitors (e.g., sarcosine, bitopertin) and agonists (e.g., LY2140023) or positive allosteric modulator (e.g., ADX71149) of group II metabotropic glutamate receptors (mGluRs) have been studied. In major depression, the NMDA receptor antagonists (e.g., ketamine, AZD6765), GluN2B subtype antagonists (e.g., traxoprodil, MK-0657), and partial agonists (e.g., d -cycloserine, GLYX-13) at the glycine site of the NMDA receptor have been proven to be effective in animal studies and first clinical trials. In addition, clinical studies of mGluR2/3 antagonist BCI-838 (a prodrug of BCI-632 (MGS0039)), mGluR2/3-negative allosteric modulators (NMAs) (e.g., RO499819, RO4432717), and mGluR5 NAMs (e.g., AZD2066, RO4917523) are in progress. Future investigations should include effects on brain structure and activation to elucidate neural mechanisms underlying efficacy of these drugs.

Schizophrenia is considered as a neurodevelopmental disorder with genetic and environmental factors playing a role. Animal models show that developmental hippocampal lesions are causing disconnectivity of the prefrontal cortex. Magnetic resonance imaging and postmortem investigations revealed deficits in the temporoprefrontal neuronal circuit. Decreased oligodendrocyte numbers and expression of oligodendrocyte genes and synaptic proteins may contribute to disturbances of micro- and macro-circuitry in the pathophysiology of the disease. Functional connectivity between cortical areas can be investigated with high temporal resolution using transcranial magnetic stimulation (TMS), electroencephalography (EEG), and magnetoencephalography (MEG). In this review, disconnectivity between different cortical areas in schizophrenia patients is described. The specificity and the neurobiological origin of these connectivity deficits and the relation to the symptom complex of schizophrenia and the glutamatergic and GABAergic system are discussed.

Transcranial magnetic stimulation (TMS) was introduced as a non-invasive tool for the investigation of the motor cortex. The repetitive application (rTMS), causing longer lasting effects, was used to study the influence on a variety of cerebral functions. High-frequency (>1 Hz) rTMS is known to depolarize neurons under the stimulating coil and to indirectly affect areas being connected and related to emotion and behavior. Researchers found selective cognitive improvement after high-frequency (HF) stimulation specifically over the left dorsolateral prefrontal cortex (DLPFC). This article provides a systematic review of HF-rTMS studies (1999–2009) stimulating over the prefrontal cortex of patients suffering from psychiatric/neurological diseases or healthy volunteers, where the effects on cognitive functions were measured. The cognitive effect was analyzed with regard to the impact of clinical status (patients/healthy volunteers) and stimulation type (verum/sham). RTMS at 10, 15 or 20 Hz, applied over the left DLPFC, within a range of 10–15 successive sessions and an individual motor threshold of 80–110%, is most likely to cause significant cognitive improvement. In comparison, patients tend to reach a greater improvement than healthy participants. Limitations concern the absence of healthy groups in clinical studies and partly the absence of sham groups. Thus, future investigations are needed to assess cognitive rTMS effects in different psychiatric disorders versus healthy subjects using an extended standardized neuropsychological test battery. Since the pathophysiological and neurobiological basis of cognitive improvement with rTMS remains unclear, additional studies including genetics, experimental neurophysiology and functional brain imaging are necessary to explore stimulation-related functional changes in the brain.

Multivariate pattern recognition approaches have recently facilitated the search for reliable neuroimaging-based biomarkers in psychiatric disorders such as schizophrenia. By taking into account the multivariate nature of brain functional and structural changes as well as their distributed localization across the whole brain, they overcome drawbacks of traditional univariate approaches. To evaluate the overall reliability of neuroimaging-based biomarkers, we conducted a comprehensive literature search to identify all studies that used multivariate pattern recognition to identify patterns of brain alterations that differentiate patients with schizophrenia from healthy controls. A bivariate random-effects meta-analytic model was implemented to investigate the sensitivity and specificity across studies as well as to assess the robustness to potentially confounding variables. In the total sample of n=38 studies (1602 patients and 1637 healthy controls), patients were differentiated from controls with a sensitivity of 80.3% (95% CI: 76.7-83.5%) and a specificity of 80.3% (95% CI: 76.9-83.3%). Analysis of neuroimaging modality indicated higher sensitivity (84.46%, 95% CI: 79.9-88.2%) and similar specificity (76.9%, 95% CI: 71.3-81.6%) of rsfMRI studies as compared with structural MRI studies (sensitivity: 76.4%, 95% CI: 71.9-80.4%, specificity of 79.0%, 95% CI: 74.6-82.8%). Moderator analysis identified significant effects of age (p=0.029), imaging modality (p=0.019), and disease stage (p=0.025) on sensitivity as well as of positive-to-negative symptom ratio (p=0.022) and antipsychotic medication (p=0.016) on specificity. Our results underline the utility of multivariate pattern recognition approaches for the identification of reliable neuroimaging-based biomarkers. Despite the clinical heterogeneity of the schizophrenia phenotype, brain functional and structural alterations differentiate schizophrenic patients from healthy controls with 80% sensitivity and specificity.

A recent increase in the literature regarding the evidence base for clozapine has made it increasingly difficult for clinicians to judge “best evidence” for clozapine use. As such, we aimed at elucidating the state-of-the-art for clozapine with regard to efficacy, effectiveness, tolerability, and management of clozapine and clozapine-related adverse events in neuropsychiatric disorders. We conducted a systematic PRISMA-conforming quantitative meta-review of available meta-analytic evidence regarding clozapine use. Primary outcome effect sizes were extracted and transformed into relative risk ratios (RR) and standardized mean differences (SMD). The methodological quality of meta-analyses was assessed using the AMSTAR-2 checklist. Of the 112 meta-analyses included in our review, 61 (54.5%) had an overall high methodological quality according to AMSTAR-2. Clozapine appears to have superior effects on positive, negative, and overall symptoms and relapse rates in schizophrenia (treatment-resistant and non-treatment-resistant subpopulations) compared to first-generation antipsychotics (FGAs) and to pooled FGAs/second-generation antipsychotics (SGAs) in treatment-resistant schizophrenia (TRS). Despite an unfavorable metabolic and hematological adverse-event profile compared to other antipsychotics, hospitalization, mortality and all-cause discontinuation (ACD) rates of clozapine surprisingly show a pattern of superiority. Our meta-review outlines the superior overall efficacy of clozapine compared to FGAs and most other SGAs in schizophrenia and suggests beneficial efficacy outcomes in bipolar disorder and Parkinson’s disease psychosis (PDP). More clinical studies and subsequent meta-analyses are needed beyond the application of clozapine in schizophrenia-spectrum disorders and future studies should be directed into multidimensional clozapine side-effect management to foster evidence and to inform future guidelines.

In psychiatric practice, classification systems are useful to improve communication among mental health professionals and researchers and to establish widely agreed descriptions of mental disorders, and should not be considered textbooks of psychopathology. [...]classification systems offer a framework for education on the most common clinical features of mental disorders through the organization of disorders into discrete diagnostic categories [3][4]. [...]diagnostic systems facilitate the identification and management of mental disorders in clinical settings and have a significant predictive power [5]. [...]the revision of the ICD-11 represents the biggest global, multidisciplinary, and participative process of revision of a classification system for mental disorders which has ever been implemented [9]. In order to adapt the classification system to the local countries’ laws, policies, health systems, and infrastructures, several multilevel actions have been subsequently implemented. [...]since education of health care professionals represents one of the most essential steps for the implementation and the dissemination of the new classification system in routine care, the WHO International Advisory Group led by G. M. Reed has organized training courses for professionals on the use of the ICD-11 chapter on mental, behavioral, and neurodevelopmental disorders and the relevant CDDG.