Search

Synaptic dysfunction and loss are core pathological features in Alzheimer disease (AD). In the vicinity of amyloid‐β plaques in animal models, synaptic toxicity occurs and is associated with chronic activation of the phosphatase calcineurin (CN). Indeed, pharmacological inhibition of CN blocks amyloid‐β synaptotoxicity. We therefore hypothesized that CN‐mediated transcriptional changes may contribute to AD neuropathology and tested this by examining the impact of CN over‐expression on neuronal gene expression in vivo. We found dramatic transcriptional down‐regulation, especially of synaptic mRNAs, in neurons chronically exposed to CN activation. Importantly, the transcriptional profile parallels the changes in human AD tissue. Bioinformatics analyses suggest that both nuclear factor of activated T cells and numerous microRNAs may all be impacted by CN, and parallel findings are observed in AD. These data and analyses support the hypothesis that at least part of the synaptic failure characterizing AD may result from aberrant CN activation leading to down‐regulation of synaptic genes, potentially via activation of specific transcription factors and expression of repressive microRNAs. Open Practices: Open Science: This manuscript was awarded with the Open Materials Badge. For more information see: https://cos.io/our-services/open-science-badges/ Read the Editorial Highlight for this article on page 8. We hypothesized that calcineurin‐mediated transcriptional changes may contribute to neuropathological changes in Alzheimer's disease because of its involvement in amyloid‐mediated synaptic defects. We tested this hypothesis by examining the impact of constitutively active calcineurin on neuronal gene expression in vivo by intrahippocampal viral transduction followed by laser capture of neuronal cell bodies and microarray analysis of gene expression. We found dramatic transcriptional down‐regulation, especially of synaptic mRNAs, in hippocampal neurons chronically transduced with constitutively active calcineurin. Importantly, the transcriptional profile parallels the changes in human Alzheimer's disease tissue. Additional bioinformatics analyses suggest that both nuclear factor of activated T cells (NFAT) and numerous microRNAs may all be impacted by calcineurin, and parallel findings are observed in Alzheimer's disease. These data and analyses support the hypothesis that at least part of the synaptic failure characterizing Alzheimer's disease may result from aberrant calcineurin activation leading to down‐regulation of synaptic genes, potentially via activation of specific transcription factors and expression of repressive microRNAs. Read the Editorial Highlight for this article on page 8. [ABSTRACT FROM AUTHOR]

Objective: In schizophrenia, alterations in markers of cortical GABA neurotransmission are prominent in parvalbumin-containing neurons. Parvalbumin neurons selectively express KCNS3, the gene encoding the Kv9.3 potassium channel α-subunit. Kv9.3 subunits are present in voltage-gated potassium channels that contribute to the precise detection of coincident excitatory synaptic inputs to parvalbumin neurons. This distinctive feature of parvalbumin neurons appears important for the synchronization of cortical neural networks in γ-oscillations. Because impaired prefrontal cortical γ-oscillations are thought to underlie the cognitive impairments in schizophrenia, the authors investigated whether KCNS3 mRNA levels are altered in the prefrontal cortex of schizophrenia subjects. Method: KCNS3 mRNA expression was evaluated by in situ hybridization in 22 matched pairs of schizophrenia and comparison subjects and by microarray analyses of pooled samples of individually dissected neurons that were labeled with Vicia villosa agglutinin (VVA), a parvalbumin neuron-selective marker, in a separate cohort of 14 pairs. Effects of chronic antipsychotic treatments on KCNS3 expression were tested in the prefrontal cortex of antipsychotic-exposed monkeys. Results: By in situ hybridization, KCNS3 mRNA levels were 23% lower in schizophrenia subjects. At the cellular level, both KCNS3 mRNA-expressing neuron density and KCNS3 mRNA level per neuron were significantly lower. By microarray, KCNS3 mRNA levels were lower by 40% in VVA-labeled neurons from schizophrenia subjects. KCNS3 mRNA levels were not altered in antipsychotic-exposed monkeys. Conclusions: These findings reveal lower KCNS3 expression in prefrontal cortical parvalbumin neurons in schizophrenia, providing a molecular basis for compromised detection of coincident synaptic inputs to parvalbumin neurons that could contribute to altered γ-oscillations and impaired cognition in schizophrenia. [ABSTRACT FROM AUTHOR]

Delirium is a serious medical complication associated with poor outcomes. Given the complexity of the syndrome, prevention and early detection are critical in mitigating its effects. We used Confusion Assessment Method (CAM) screening and Electronic Health Record (EHR) data for 64,038 inpatient visits to train and test a model predicting delirium arising in hospital. Incident delirium was defined as the first instance of a positive CAM occurring at least 48 h into a hospital stay. A Random Forest machine learning algorithm was used with demographic data, comorbidities, medications, procedures, and physiological measures. The data set was randomly partitioned 80% / 20% for training and validating the predictive model, respectively. Of the 51,240 patients in the training set, 2774 (5.4%) experienced delirium during their hospital stay; and of the 12,798 patients in the validation set, 701 (5.5%) experienced delirium. Under-sampling of the delirium negative population was used to address the class imbalance. The Random Forest predictive model yielded an area under the receiver operating characteristic curve (ROC AUC) of 0.909 (95% CI 0.898 to 0.921). Important variables in the model included previously identified predisposing and precipitating risk factors. This machine learning approach displayed a high degree of accuracy and has the potential to provide a clinically useful predictive model for earlier intervention in those patients at greatest risk of developing delirium. [ABSTRACT FROM AUTHOR]