Impaired neural replay of inferred relationships in schizophrenia.

An ability to build structured mental maps of the world underpins our capacity to imagine relationships between objects that extend beyond experience. In rodents, such representations are supported by sequential place cell reactivations during rest, known as replay. Schizophrenia is proposed to reflect a compromise in structured mental representations, with animal models reporting abnormalities in hippocampal replay and associated ripple activity during rest. Here, utilizing magnetoencephalography (MEG), we tasked patients with schizophrenia and control participants to infer unobserved relationships between objects by reorganizing visual experiences containing these objects. During a post-task rest session, controls exhibited fast spontaneous neural reactivation of presented objects that replayed inferred relationships. Replay was coincident with increased ripple power in hippocampus. Patients showed both reduced replay and augmented ripple power relative to controls, convergent with findings in animal models. These abnormalities are linked to impairments in behavioral acquisition and subsequent neural representation of task structure.

Transforming lives through genetics.

Mary-Claire King's approach to genetics has had a major impact on breast and ovarian cancer and, more recently, mental illnesses including schizophrenia. Science writer Kendall Morgan talked with Mary-Claire, recipient of a 2021 Canada Gairdner International Award, about her life, her lengthy quest to discover the genetic basis of susceptibility to breast cancer, the struggles for women in science, and much more. An edited version of this conversation is presented below.

Genetic Control of Expression and Splicing in Developing Human Brain Informs Disease Mechanisms.

Tissue-specific regulatory regions harbor substantial genetic risk for disease. Because brain development is a critical epoch for neuropsychiatric disease susceptibility, we characterized the genetic control of the transcriptome in 201 mid-gestational human brains, identifying 7,962 expression quantitative trait loci (eQTL) and 4,635 spliceQTL (sQTL), including several thousand prenatal-specific regulatory regions. We show that significant genetic liability for neuropsychiatric disease lies within prenatal eQTL and sQTL. Integration of eQTL and sQTL with genome-wide association studies (GWAS) via transcriptome-wide association identified dozens of novel candidate risk genes, highlighting shared and stage-specific mechanisms in schizophrenia (SCZ). Gene network analysis revealed that SCZ and autism spectrum disorder (ASD) affect distinct developmental gene co-expression modules. Yet, in each disorder, common and rare genetic variation converges within modules, which in ASD implicates superficial cortical neurons. More broadly, these data, available as a web browser and our analyses, demonstrate the genetic mechanisms by which developmental events have a widespread influence on adult anatomical and behavioral phenotypes.

Genomic Dissection of Bipolar Disorder and Schizophrenia, Including 28 Subphenotypes.

Schizophrenia and bipolar disorder are two distinct diagnoses that share symptomology. Understanding the genetic factors contributing to the shared and disorder-specific symptoms will be crucial for improving diagnosis and treatment. In genetic data consisting of 53,555 cases (20,129 bipolar disorder [BD], 33,426 schizophrenia [SCZ]) and 54,065 controls, we identified 114 genome-wide significant loci implicating synaptic and neuronal pathways shared between disorders. Comparing SCZ to BD (23,585 SCZ, 15,270 BD) identified four genomic regions including one with disorder-independent causal variants and potassium ion response genes as contributing to differences in biology between the disorders. Polygenic risk score (PRS) analyses identified several significant correlations within case-only phenotypes including SCZ PRS with psychotic features and age of onset in BD. For the first time, we discover specific loci that distinguish between BD and SCZ and identify polygenic components underlying multiple symptom dimensions. These results point to the utility of genetics to inform symptomology and potential treatment.

Synaptic Neurexin Complexes: A Molecular Code for the Logic of Neural Circuits.

Synapses are specialized junctions between neurons in brain that transmit and compute information, thereby connecting neurons into millions of overlapping and interdigitated neural circuits. Here, we posit that the establishment, properties, and dynamics of synapses are governed by a molecular logic that is controlled by diverse trans-synaptic signaling molecules. Neurexins, expressed in thousands of alternatively spliced isoforms, are central components of this dynamic code. Presynaptic neurexins regulate synapse properties via differential binding to multifarious postsynaptic ligands, such as neuroligins, cerebellin/GluD complexes, and latrophilins, thereby shaping the input/output relations of their resident neural circuits. Mutations in genes encoding neurexins and their ligands are associated with diverse neuropsychiatric disorders, especially schizophrenia, autism, and Tourette syndrome. Thus, neurexins nucleate an overall trans-synaptic signaling network that controls synapse properties, which thereby determines the precise responses of synapses to spike patterns in a neuron and circuit and which is vulnerable to impairments in neuropsychiatric disorders.

A concerted neuron-astrocyte program declines in ageing and schizophrenia.

Human brains vary across people and over time; such variation is not yet understood in cellular terms. Here we describe a relationship between people's cortical neurons and cortical astrocytes. We used single-nucleus RNA sequencing to analyse the prefrontal cortex of 191 human donors aged 22-97 years, including healthy individuals and people with schizophrenia. Latent-factor analysis of these data revealed that, in people whose cortical neurons more strongly expressed genes encoding synaptic components, cortical astrocytes more strongly expressed distinct genes with synaptic functions and genes for synthesizing cholesterol, an astrocyte-supplied component of synaptic membranes. We call this relationship the synaptic neuron and astrocyte program (SNAP). In schizophrenia and ageing-two conditions that involve declines in cognitive flexibility and plasticity1,2-cells divested from SNAP: astrocytes, glutamatergic (excitatory) neurons and GABAergic (inhibitory) neurons all showed reduced SNAP expression to corresponding degrees. The distinct astrocytic and neuronal components of SNAP both involved genes in which genetic risk factors for schizophrenia were strongly concentrated. SNAP, which varies quantitatively even among healthy people of similar age, may underlie many aspects of normal human interindividual differences and may be an important point of convergence for multiple kinds of pathophysiology.

The Relationship Between the Human Genome and Microbiome Comes into View.

The body's microbiome, composed of microbial cells that number in the trillions, is involved in human health and disease in ways that are just starting to emerge. The microbiome is assembled at birth, develops with its host, and is greatly influenced by environmental factors such as diet and other exposures. Recently, a role for human genetic variation has emerged as also influential in accounting for interpersonal differences in microbiomes. Thus, human genes may influence health directly or by promoting a beneficial microbiome. Studies of the heritability of gut microbiotas reveal a subset of microbes whose abundances are partly genetically determined by the host. However, the use of genome-wide association studies (GWASs) to identify human genetic variants associated with microbiome phenotypes has proven challenging. Studies to date are small by GWAS standards, and cross-study comparisons are hampered by differences in analytical approaches. Nevertheless, associations between microbes or microbial genes and human genes have emerged that are consistent between human populations. Most notably, higher levels of beneficial gut bacteria called Bifidobacteria are associated with the human lactase nonpersister genotype, which typically confers lactose intolerance, in several different human populations. It is time for the microbiome to be incorporated into studies that quantify interactions among genotype, environment, and the microbiome in order to predict human disease susceptibility.

Inflammation-related pathology in the olfactory epithelium: its impact on the olfactory system in psychotic disorders.

Smell deficits and neurobiological changes in the olfactory bulb (OB) and olfactory epithelium (OE) have been observed in schizophrenia and related disorders. The OE is the most peripheral olfactory system located outside the cranium, and is connected with the brain via direct neuronal projections to the OB. Nevertheless, it is unknown whether and how a disturbance of the OE affects the OB in schizophrenia and related disorders. Addressing this gap would be the first step in studying the impact of OE pathology in the disease pathophysiology in the brain. In this cross-species study, we observed that chronic, local OE inflammation with a set of upregulated genes in an inducible olfactory inflammation (IOI) mouse model led to a volume reduction, layer structure changes, and alterations of neuron functionality in the OB. Furthermore, IOI model also displayed behavioral deficits relevant to negative symptoms (avolition) in parallel to smell deficits. In first episode psychosis (FEP) patients, we observed a significant alteration in immune/inflammation-related molecular signatures in olfactory neuronal cells (ONCs) enriched from biopsied OE and a significant reduction in the OB volume, compared with those of healthy controls (HC). The increased expression of immune/inflammation-related molecules in ONCs was significantly correlated to the OB volume reduction in FEP patients, but no correlation was found in HCs. Moreover, the increased expression of human orthologues of the IOI genes in ONCs was significantly correlated with the OB volume reduction in FEP, but not in HCs. Together, our study implies a potential mechanism of the OE-OB pathology in patients with psychotic disorders (schizophrenia and related disorders). We hope that this mechanism may have a cross-disease implication, including COVID-19-elicited mental conditions that include smell deficits.

Using normative modeling to assess pharmacological treatment effect on brain state in patients with schizophrenia.

Quantifying individual differences in neuroimaging metrics is attracting interest in clinical studies with mental disorders. Schizophrenia is diagnosed exclusively based on symptoms, and the biological heterogeneity makes it difficult to accurately assess pharmacological treatment effects on the brain state. Using the Cambridge Centre for Ageing and Neuroscience data set, we built normative models of brain states and mapped the deviations of the brain characteristics of each patient, to test whether deviations were related to symptoms, and further investigated the pharmacological treatment effect on deviation distributions. Specifically, we found that the patients can be divided into 2 groups: the normalized group had a normalization trend and milder symptoms at baseline, and the other group showed a more severe deviation trend. The baseline severity of the depression as well as the overall symptoms could predict the deviation of the static characteristics for the dorsal and ventral attention networks after treatment. In contrast, the positive symptoms could predict the deviations of the dynamic fluctuations for the default mode and dorsal attention networks after treatment. This work evaluates the effect of pharmacological treatment on static and dynamic brain states using an individualized approach, which may assist in understanding the heterogeneity of the illness pathology as well as the treatment response.

The relationship between gray/white matter contrast and cognitive performance in first-episode schizophrenia.

Previous postmortem brain studies have revealed disturbed myelination in the intracortical regions in patients with schizophrenia, possibly reflecting anomalous brain maturational processes. However, it currently remains unclear whether this anomalous myelination is already present in early illness stages and/or progresses during the course of the illness. In this magnetic resonance imaging study, we examined gray/white matter contrast (GWC) as a potential marker of intracortical myelination in 63 first-episode schizophrenia (FESz) patients and 77 healthy controls (HC). Furthermore, we investigated the relationships between GWC findings and clinical/cognitive variables in FESz patients. GWC in the bilateral temporal, parietal, occipital, and insular regions was significantly higher in FESz patients than in HC, which was partly associated with the durations of illness and medication, the onset age, and lower executive and verbal learning performances. Because higher GWC implicates lower myelin in the deeper layers of the cortex, these results suggest that schizophrenia patients have less intracortical myelin at the time of their first psychotic episode, which underlies lower cognitive performance in early illness stages.

Compensatory thickening of cortical thickness in early stage of schizophrenia.

Brain structural abnormality has been observed in the prodromal and early stages of schizophrenia, but the mechanism behind it is not clear. In this study, to explore the association between cortical abnormalities, metabolite levels, inflammation levels and clinical symptoms of schizophrenia, 51 drug-naive first-episode schizophrenia (FES) patients, 51 ultra-high risk for psychosis (UHR), and 51 healthy controls (HC) were recruited. We estimated gray matter volume (GMV), cortical thickness (CT), concentrations of different metabolites, and inflammatory marks among four groups (UHR converted to psychosis [UHR-C], UHR unconverted to psychosis [UHR-NC], FES, HC). UHR-C group had more CT in the right lateral occipital cortex and the right medial orbito-frontal cortex (rMOF), while a significant reduction in CT of the right fusiform cortex was observed in FES group. UHR-C group had significantly higher concentration of IL-6, while IL-17 could significantly predict CT of the right fusiform and IL-4 and IL-17 were significant predictors of CT in the rMOF. To conclude, it is reasonable to speculate that the increased CT in UHR-C group is related to the inflammatory response, and may participate in some compensatory mechanism, but might become exhaustive with the progress of the disease due to potential neurotoxic effects.

Sex-related cortical asymmetry in antipsychotic-naïve first-episode schizophrenia.

Schizophrenia has been considered to exhibit sex-related clinical differences that might be associated with distinctly abnormal brain asymmetries between sexes. One hundred and thirty-two antipsychotic-naïve first-episode patients with schizophrenia and 150 healthy participants were recruited in this study to investigate whether cortical asymmetry would exhibit sex-related abnormalities in schizophrenia. After a 1-yr follow-up, patients were rescanned to obtain the effect of antipsychotic treatment on cortical asymmetry. Male patients were found to show increased lateralization index while female patients were found to exhibit decreased lateralization index in widespread regions when compared with healthy participants of the corresponding sex. Specifically, the cortical asymmetry of male and female patients showed contrary trends in the cingulate, orbitofrontal, parietal, temporal, occipital, and insular cortices. This result suggested male patients showed a leftward shift of asymmetry while female patients showed a rightward shift of asymmetry in these above regions that related to language, vision, emotion, and cognition. Notably, abnormal lateralization indices remained stable after antipsychotic treatment. The contrary trends in asymmetry between female and male patients with schizophrenia together with the persistent abnormalities after antipsychotic treatment suggested the altered brain asymmetries in schizophrenia might be sex-related disturbances, intrinsic, and resistant to the effect of antipsychotic therapy.

Modified climbing fiber/Purkinje cell synaptic connectivity in the cerebellum of the neonatal phencyclidine model of schizophrenia.

Environmental perturbations during the first years of life are a major factor in psychiatric diseases. Phencyclidine (PCP), a drug of abuse, has psychomimetic effects, and neonatal subchronic administration of PCP in rodents leads to long-term behavioral changes relevant for schizophrenia. The cerebellum is increasingly recognized for its role in diverse cognitive functions. However, little is known about potential cerebellar changes in models of schizophrenia. Here, we analyzed the characteristics of the cerebellum in the neonatal subchronic PCP model. We found that, while the global cerebellar cytoarchitecture and Purkinje cell spontaneous spiking properties are unchanged, climbing fiber/Purkinje cell synaptic connectivity is increased in juvenile mice. Neonatal subchronic administration of PCP is accompanied by increased cFos expression, a marker of neuronal activity, and transient modification of the neuronal surfaceome in the cerebellum. The largest change observed is the overexpression of Ctgf, a gene previously suggested as a biomarker for schizophrenia. This neonatal increase in Ctgf can be reproduced by increasing neuronal activity in the cerebellum during the second postnatal week using chemogenetics. However, it does not lead to increased climbing fiber/Purkinje cell connectivity in juvenile mice, showing the complexity of PCP action. Overall, our study shows that administration of the drug of abuse PCP during the developmental period of intense cerebellar synaptogenesis and circuit remodeling has long-term and specific effects on Purkinje cell connectivity and warrants the search for this type of synaptic changes in psychiatric diseases.

Kinesin Kif3b mutation reduces NMDAR subunit NR2A trafficking and causes schizophrenia-like phenotypes in mice.

The transport of N-methyl-d-aspartate receptors (NMDARs) is crucial for neuronal plasticity and synapse formation. Here, we show that KIF3B, a member of the kinesin superfamily proteins (KIFs), supports the transport of vesicles simultaneously containing NMDAR subunit 2A (NR2A) and the adenomatous polyposis coli (APC) complex. Kif3b+/- neurons exhibited a reduction in dendritic levels of both NR2A and NR2B due to the impaired transport of NR2A and increased degradation of NR2B. In Kif3b+/- hippocampal slices, electrophysiological NMDAR response was found decreased and synaptic plasticity was disrupted, which corresponded to a common feature of schizophrenia (SCZ). The histological features of Kif3b+/- mouse brain also mimicked SCZ features, and Kif3b+/- mice exhibited behavioral defects in prepulse inhibition (PPI), social interest, and cognitive flexibility. Indeed, a mutation of KIF3B was specifically identified in human SCZ patients, which was revealed to be functionally defective in a rescue experiment. Therefore, we propose that KIF3B transports NR2A/APC complex and that its dysfunction is responsible for SCZ pathogenesis.

BrainAGE: Revisited and reframed machine learning workflow.

Since the introduction of the BrainAGE method, novel machine learning methods for brain age prediction have continued to emerge. The idea of estimating the chronological age from magnetic resonance images proved to be an interesting field of research due to the relative simplicity of its interpretation and its potential use as a biomarker of brain health. We revised our previous BrainAGE approach, originally utilising relevance vector regression (RVR), and substituted it with Gaussian process regression (GPR), which enables more stable processing of larger datasets, such as the UK Biobank (UKB). In addition, we extended the global BrainAGE approach to regional BrainAGE, providing spatially specific scores for five brain lobes per hemisphere. We tested the performance of the new algorithms under several different conditions and investigated their validity on the ADNI and schizophrenia samples, as well as on a synthetic dataset of neocortical thinning. The results show an improved performance of the reframed global model on the UKB sample with a mean absolute error (MAE) of less than 2 years and a significant difference in BrainAGE between healthy participants and patients with Alzheimer's disease and schizophrenia. Moreover, the workings of the algorithm show meaningful effects for a simulated neocortical atrophy dataset. The regional BrainAGE model performed well on two clinical samples, showing disease-specific patterns for different levels of impairment. The results demonstrate that the new improved algorithms provide reliable and valid brain age estimations.

SAN: Mitigating spatial covariance heterogeneity in cortical thickness data collected from multiple scanners or sites.

In neuroimaging studies, combining data collected from multiple study sites or scanners is becoming common to increase the reproducibility of scientific discoveries. At the same time, unwanted variations arise by using different scanners (inter-scanner biases), which need to be corrected before downstream analyses to facilitate replicable research and prevent spurious findings. While statistical harmonization methods such as ComBat have become popular in mitigating inter-scanner biases in neuroimaging, recent methodological advances have shown that harmonizing heterogeneous covariances results in higher data quality. In vertex-level cortical thickness data, heterogeneity in spatial autocorrelation is a critical factor that affects covariance heterogeneity. Our work proposes a new statistical harmonization method called spatial autocorrelation normalization (SAN) that preserves homogeneous covariance vertex-level cortical thickness data across different scanners. We use an explicit Gaussian process to characterize scanner-invariant and scanner-specific variations to reconstruct spatially homogeneous data across scanners. SAN is computationally feasible, and it easily allows the integration of existing harmonization methods. We demonstrate the utility of the proposed method using cortical thickness data from the Social Processes Initiative in the Neurobiology of the Schizophrenia(s) (SPINS) study. SAN is publicly available as an R package.

Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders-ENIGMA study in people with bipolar disorders and obesity.

Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. PRACTITIONER POINTS: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.

Aberrant Hippocampal Neuroregenerative Plasticity in Schizophrenia: Reactive Neuroblastosis as a Possible Pathocellular Mechanism of Hallucination.

Hallucination is a sensory perception that occurs in the absence of external stimuli during abnormal neurological disturbances and various mental diseases. Hallucination is recognized as a core psychotic symptom and is particularly more prevalent in individuals with schizophrenia. Strikingly, a significant number of subjects with Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), and other neurological diseases like cerebral stroke and epileptic seizure also experience hallucination. While aberrant neurotransmission has been linked to the neuropathogenic events of schizophrenia, the precise cellular mechanism accounting for hallucinations remains obscure. Neurogenesis is a cellular process of producing new neurons from the neural stem cells (NSC)-derived neuroblasts in the brain that contribute to the regulation of pattern separation, mood, olfaction, learning, and memory in adulthood. Impaired neurogenesis in the hippocampus of the adult brain has been linked to stress, anxiety, depression, and dementia. Notably, many neurodegenerative disorders are characterized by the mitotic and functional activation of neuroblasts and cell cycle re-entry of mature neurons leading to a drastic alteration in neurogenic process, known as reactive neuroblastosis. Considering their neurophysiological properties, the abnormal integration of neuroblasts into the existing neural network or withdrawal of their connections can lead to abnormal synaptogenesis, and neurotransmission. Eventually, this would be expected to result in altered perception accounting for hallucination. Thus, this article emphasizes a hypothesis that aberrant neurogenic processes at the level of reactive neuroblastosis could be an underlying mechanism of hallucination in schizophrenia and other neurological diseases.

Enlarged pituitary gland volume: a possible state rather than trait marker of psychotic disorders.

BACKGROUND: Enlarged pituitary gland volume could be a marker of psychotic disorders. However, previous studies report conflicting results. To better understand the role of the pituitary gland in psychosis, we examined a large transdiagnostic sample of individuals with psychotic disorders. METHODS: The study included 751 participants (174 with schizophrenia, 114 with schizoaffective disorder, 167 with psychotic bipolar disorder, and 296 healthy controls) across six sites in the Bipolar-Schizophrenia Network on Intermediate Phenotypes consortium. Structural magnetic resonance images were obtained, and pituitary gland volumes were measured using the MAGeT brain algorithm. Linear mixed models examined between-group differences with controls and among patient subgroups based on diagnosis, as well as how pituitary volumes were associated with symptom severity, cognitive function, antipsychotic dose, and illness duration. RESULTS: Mean pituitary gland volume did not significantly differ between patients and controls. No significant effect of diagnosis was observed. Larger pituitary gland volume was associated with greater symptom severity (F = 13.61, p = 0.0002), lower cognitive function (F = 4.76, p = 0.03), and higher antipsychotic dose (F = 5.20, p = 0.02). Illness duration was not significantly associated with pituitary gland volume. When all variables were considered, only symptom severity significantly predicted pituitary gland volume (F = 7.54, p = 0.006). CONCLUSIONS: Although pituitary volumes were not increased in psychotic disorders, larger size may be a marker associated with more severe symptoms in the progression of psychosis. This finding helps clarify previous inconsistent reports and highlights the need for further research into pituitary gland-related factors in individuals with psychosis.

Specific association between retinal neural layer thinning and neurological soft signs in schizophrenia.

There is growing evidence of disproportionate retinal thinning in schizophrenia, but doubts are still raised regarding its significance in the context of the neurobiology of the disease. Therefore, we examined whether these abnormalities are significantly associated with neurological soft signs (NSS) which are closely related to the risk of schizophrenia. This cross-sectional study analyzing linear correlations between variables involved 56 schizophrenia inpatients and 60 controls. The results confirmed such relationships, and only in the patient sample. In addition, retinal abnormalities and NSS were significantly correlated with duration of illness. These findings provide further evidence for linked neurodevelopmental and neurodegenerative aspects of schizophrenia.