Analyzing schizophrenia-related phenotypes in mice caused by autoantibodies against NRXN1α in schizophrenia.

The molecular pathological mechanisms underlying schizophrenia remain unclear; however, genomic analysis has identified genes encoding important risk molecules. One such molecule is neurexin 1α (NRXN1α), a presynaptic cell adhesion molecule. In addition, novel autoantibodies that target the nervous system have been found in patients with encephalitis and neurological disorders. Some of these autoantibodies inhibit synaptic antigen molecules. Studies have examined the association between schizophrenia and autoimmunity; however, the pathological data remain unclear. Here, we identified a novel autoantibody against NRXN1α in patients with schizophrenia (n = 2.1%) in a Japanese cohort (n = 387). None of the healthy control participants (n = 362) were positive for anti-NRXN1α autoantibodies. Anti-NRXN1α autoantibodies isolated from patients with schizophrenia inhibited the molecular interaction between NRXN1α and Neuroligin 1 (NLGN1) and between NRXN1α and Neuroligin 2 (NLGN2). Additionally, these autoantibodies reduced the frequency of the miniature excitatory postsynaptic current in the frontal cortex of mice. Administration of anti-NRXN1α autoantibodies from patients with schizophrenia into the cerebrospinal fluid of mice reduced the number of spines/synapses in the frontal cortex and induced schizophrenia-related behaviors such as reduced cognition, impaired pre-pulse inhibition, and reduced social novelty preference. These changes were improved through the removal of anti-NRXN1α autoantibodies from the IgG fraction of patients with schizophrenia. These findings demonstrate that anti-NRXN1α autoantibodies transferred from patients with schizophrenia cause schizophrenia-related pathology in mice. Removal of anti-NRXN1α autoantibodies may be a therapeutic target for a subgroup of patients who are positive for these autoantibodies.

The subiculum sensitizes retrosplenial cortex layer 2/3 pyramidal neurons.

KEY POINTS: Neurons in the retrosplenial cortex (RSC), a cerebral region that connects synaptically with various brain regions, are known to increase neuronal activity in accordance with hippocampal sharp wave-ripples. Pyramidal cells in granular RSC (gRSC) layer 2/3, but not layer 5, exhibit slowly ramping depolarization and considerably delayed spikes in response to a step-pulse current injection. The latencies of delayed spikes in RSC layer 2/3 pyramidal neurons were shortened by a preceding current injection. This effect was mimicked by activation of axonal afferents from the subiculum, but not of neocortical afferents. The subiculum is likely to facilitate information processing and flow in the RSC. ABSTRACT: The retrosplenial cortex (RSC), a cerebral region involved in diverse cognitive functions, is an anatomical hub that forms monosynaptic connections with various brain areas. Here, we report a unique form of short-term intrinsic plasticity in mouse granular RSC layer 2/3 pyramidal cells. These cells exhibited delayed spikes in response to somatic current injection, but the spike latencies were shortened by a preceding brief depolarization (priming). This priming-induced sensitization is distinct from desensitization, which is commonly observed in other cortical neurons. The facilitatory priming effect lasted for more than 3 s, providing a time window for increased sensitivity to RSC inputs. Based on in vitro and in vivo patch-clamp recordings following optogenetic stimulation of axonal fibres, we found that preactivation of subicular afferents replicated the facilitatory priming effect. The results suggest that subicular inputs to RSC layer 2/3 neurons may modulate subsequent information integration in the RSC layer 2/3 circuits.

Maternal Immune Activation in Pregnant Mice Produces Offspring with Altered Hippocampal Ripples.

Psychiatric disorders, such as schizophrenia and autism spectrum disorder, are associated with sleep disturbances and deficits in memory consolidation; however, the relationship between these symptoms remains unclear. Here, we focused on hippocampal sharp-wave ripples (SWRs), a form of transient high-frequency oscillations that occur during sleep and behavioral immobility and contribute to memory consolidation. We activated the maternal immune system with polyinosinic-polycytidylic acid (poly(I : C)), one of the major pharmacological models of psychiatric disorders, to investigate whether SWR activity is altered in acute slices of the hippocampus from offspring born to poly(I : C)-treated mouse dams. Using robust continuous clustering in a low dimensional space defined by a uniform manifold approximation and projection, we found that mice with prenatal exposure to poly(I : C) exhibited different feature distributions of SWR waveforms without affecting the overall frequencies of SWR events. Based on our results, maternal immune activation leads to altered SWR patterns in offspring.

Immature electrophysiological properties of human-induced pluripotent stem cell-derived neurons transplanted into the mouse cortex for 7 weeks.

The transplantation of human-induced pluripotent stem cell (hiPSC)-derived cells has emerged as a potential clinical approach for the treatment of brain diseases. Recent studies with animal disease models have shown that hiPSC-derived neurons transplanted into the brain, especially the nigrostriatal area, could restore degenerated brain functions. Further works are required to test whether hiPSC-derived neurons can also gain functional properties for other cortical areas. In this study, hiPSC-derived neurospheres were transplanted into the adult mouse hippocampus and sensory cortex. Most transplanted hiPSC-derived neurons expressed both Nestin and NeuN at 7 weeks after transplantation. Whole-cell patch-clamp recordings from brain slices indicated that transplanted cells showed no action potentials upon current injection and few small inward currents, indicating that hiPSC-derived neurons did not become functionally mature within these time periods.

[Machine Learning-based Prediction of Seizure-inducing Action as an Adverse Drug Effect].

　During the preclinical research period of drug development, animal testing is widely used to help screen out a drug's dangerous side effects. However, it remains difficult to predict side effects within the central nervous system. Here, we introduce a machine learning-based in vitro system designed to detect seizure-inducing side effects before clinical trial. We recorded local field potentials from the CA1 alveus in acute mouse neocortico-hippocampal slices that were bath-perfused with each of 14 different drugs, and at 5 different concentrations of each drug. For each of these experimental conditions, we collected seizure-like neuronal activity and merged their waveforms as one graphic image, which was further converted into a feature vector using Caffe, an open framework for deep learning. In the space of the first two principal components, the support vector machine completely separated the vectors (i.e., doses of individual drugs) that induced seizure-like events, and identified diphenhydramine, enoxacin, strychnine and theophylline as "seizure-inducing" drugs, which have indeed been reported to induce seizures in clinical situations. Thus, this artificial intelligence-based classification may provide a new platform to pre-clinically detect seizure-inducing side effects of drugs.

Hippocampal ripples down-regulate synapses.

The specific effects of sleep on synaptic plasticity remain unclear. We report that mouse hippocampal sharp-wave ripple oscillations serve as intrinsic events that trigger long-lasting synaptic depression. Silencing of sharp-wave ripples during slow-wave states prevented the spontaneous down-regulation of net synaptic weights and impaired the learning of new memories. The synaptic down-regulation was dependent on the N-methyl-d-aspartate receptor and selective for a specific input pathway. Thus, our findings are consistent with the role of slow-wave states in refining memory engrams by reducing recent memory-irrelevant neuronal activity and suggest a previously unrecognized function for sharp-wave ripples.

Machine learning-based prediction of adverse drug effects: An example of seizure-inducing compounds.

Various biological factors have been implicated in convulsive seizures, involving side effects of drugs. For the preclinical safety assessment of drug development, it is difficult to predict seizure-inducing side effects. Here, we introduced a machine learning-based in vitro system designed to detect seizure-inducing side effects. We recorded local field potentials from the CA1 alveus in acute mouse neocortico-hippocampal slices, while 14 drugs were bath-perfused at 5 different concentrations each. For each experimental condition, we collected seizure-like neuronal activity and merged their waveforms as one graphic image, which was further converted into a feature vector using Caffe, an open framework for deep learning. In the space of the first two principal components, the support vector machine completely separated the vectors (i.e., doses of individual drugs) that induced seizure-like events and identified diphenhydramine, enoxacin, strychnine and theophylline as "seizure-inducing" drugs, which indeed were reported to induce seizures in clinical situations. Thus, this artificial intelligence-based classification may provide a new platform to detect the seizure-inducing side effects of preclinical drugs.

cAMP-Dependent Calcium Oscillations of Astrocytes: An Implication for Pathology.

Astrocytes in various brain regions exhibit spontaneous intracellular calcium elevations both in vitro and in vivo; however, neither the temporal pattern underlying this activity nor its function has been fully evaluated. Here, we utilized a long-term optical imaging technique to analyze the calcium activity of more than 4000 astrocytes in acute hippocampal slices as well as in the neocortex and hippocampus of head-restrained mice. Although astrocytic calcium activity was largely sparse and irregular, we observed a subset of cells in which the fluctuating calcium oscillations repeated at a regular interval of ∼30 s. These intermittent oscillations i) depended on type 2 inositol 1,4,5-trisphosphate receptors; ii) consisted of a complex reverberatory interaction between the soma and processes of individual astrocytes; iii) did not synchronize with those of other astrocytes; iv) did not require neuronal firing; v) were modulated through cAMP-protein kinase A signaling; vi) were facilitated under pathological conditions, such as energy deprivation and epileptiform hyperexcitation; and vii) were associated with enhanced hypertrophy in astrocytic processes, an early hallmark of reactive gliosis, which is observed in ischemia and epilepsy. Therefore, calcium oscillations appear to be associated with a pathological state in astrocytes.