Cortical Brain Abnormalities in 4474 Individuals With Schizophrenia and 5098 Control Subjects via the Enhancing Neuro Imaging Genetics Through Meta Analysis (ENIGMA) Consortium

Neurotransmission-related gene expression in the frontal pole is altered in subjects with bipolar disorder and schizophrenia

The frontal pole (Brodmann area 10, BA10) is the largest cytoarchitectonic region of the human cortex, performing complex integrative functions. BA10 undergoes intensive adolescent grey matter pruning prior to the age of onset for bipolar disorder (BP) and schizophrenia (SCHIZ), and its dysfunction is likely to underly aspects of their shared symptomology. In this study, we investigated the role of BA10 neurotransmission-related gene expression in BP and SCHIZ. We performed qPCR to measure the expression of 115 neurotransmission-related targets in control, BP, and SCHIZ postmortem samples (n = 72). We chose this method for its high sensitivity to detect low-level expression. We then strengthened our findings by performing a meta-analysis of publicly released BA10 microarray data (n = 101) and identified sources of convergence with our qPCR results. To improve interpretation, we leveraged the unusually large database of clinical metadata accompanying our samples to explore the relationship between BA10 gene expression, therapeutics, substances of abuse, and symptom profiles, and validated these findings with publicly available datasets. Using these convergent sources of evidence, we identified 20 neurotransmission-related genes that were differentially expressed in BP and SCHIZ in BA10. These results included a large diagnosis-related decrease in two important therapeutic targets with low levels of expression, HTR2B and DRD4, as well as other findings related to dopaminergic, GABAergic and astrocytic function. We also observed that therapeutics may produce a differential expression that opposes diagnosis effects. In contrast, substances of abuse showed similar effects on BA10 gene expression as BP and SCHIZ, potentially amplifying diagnosis-related dysregulation.

Differential effects of parental socioeconomic status on cortical thickness in patients with schizophrenia spectrum disorders and healthy controls

OBJECTIVES

Widespread changes in cortical thickness (CT) have been repeatedly reported in schizophrenia (SZ). The nature of the pathophysiologic process underlying such changes remains to be elucidated. The aims of the present study were to measure the CT; evaluate parent socioeconomic status (pSES), childhood trauma (ChT) and premorbid adjustment (PA) in patients with schizophrenia spectrum disorders (SSDs); and investigate group differences in CT (i.e., SSD vs. healthy controls (HCs)), pSES, PA, and/or ChT, as well as the interactions among these factors.

METHODS

164 patients with SSD and 245 age-, sex- and education-matched healthy controls have participated. The pSES, ChT and PA were evaluated using Korean version of Polyenvironmental Risk Score, Early Trauma Inventory Self Report-Short Form and Premorbid Adjustment Scale, respectively. Vertex-wise measure of CT was estimated using the FreeSurfer. To investigate the main effects and interactions, multilevel regression was employed.

RESULTS

We found widespread cortical thinning in patients with SSDs compared to HCs. The cortical thinning was associated with ChT, symptom severity and chlorpromazine equivalent dose and duration of illness in patients. In multilevel regression, main effects of group and pSES and interaction between group and pSES were found whereas a significant interaction between ChT and CPZ equivalent was found in patients.

CONCLUSION

Our findings indicate that compared to HCs, patients with SSDs have cortical structural abnormalities, and that group and pSES interaction determines CT. Further studies are needed to explore the effects of psychosocial factors on brain structural and functional abnormalities in SZ.

Large-scale analysis of structural brain asymmetries in schizophrenia via the ENIGMA consortium

Left-right asymmetry is an important organizing feature of the healthy brain that may be altered in schizophrenia, but most studies have used relatively small samples and heterogeneous approaches, resulting in equivocal findings. We carried out the largest case-control study of structural brain asymmetries in schizophrenia, with MRI data from 5,080 affected individuals and 6,015 controls across 46 datasets, using a single image analysis protocol. Asymmetry indexes were calculated for global and regional cortical thickness, surface area, and subcortical volume measures. Differences of asymmetry were calculated between affected individuals and controls per dataset, and effect sizes were meta-analyzed across datasets. Small average case-control differences were observed for thickness asymmetries of the rostral anterior cingulate and the middle temporal gyrus, both driven by thinner left-hemispheric cortices in schizophrenia. Analyses of these asymmetries with respect to the use of antipsychotic medication and other clinical variables did not show any significant associations. Assessment of age- and sex-specific effects revealed a stronger average leftward asymmetry of pallidum volume between older cases and controls. Case-control differences in a multivariate context were assessed in a subset of the data (N = 2,029), which revealed that 7% of the variance across all structural asymmetries was explained by case-control status. Subtle case-control differences of brain macrostructural asymmetry may reflect differences at the molecular, cytoarchitectonic, or circuit levels that have functional relevance for the disorder. Reduced left middle temporal cortical thickness is consistent with altered left-hemisphere language network organization in schizophrenia.

[Toward a better understanding of fatigue in schizophrenia]

Despite being one of the most common complaints of people with schizophrenia, fatigue remains largely unexplored in this population. The lack of knowledge regarding this complex symptom makes it often underdiagnosed and undertreated in schizophrenia. The aim of this brief perspective review is to outline the potential origins (distinguishing primary and secondary fatigue) and consequences of fatigue and to explore some potential treatments in this population. The current literature in schizophrenia has mainly investigated fatigue as a trait, using a self-administered questionnaire. Beyond this observational approach, which does not allow to capture the symptom in real life situations where high levels of fatigue can emerge rapidly, we propose to consider the state level of fatigue, for instance occurring after a prolonged period of cognitive activity (i.e. mental fatigue). We elaborate on the potential relationships between mental fatigue and negative symptoms of schizophrenia and propose some research avenues to test the effects of acute fatigue on effort intentions and behaviours. The consideration of the multidimensional aspects of fatigue will allow to move beyond the sole pharmacological approach to treat fatigue in schizophrenia. Targeting the cognitive as well as the performance components of fatigue through interventions such as concomitant aerobic exercise - mental training offers attractive prospects to reduce fatigue in this population and minimize its functional negative impact.

The contribution of copy number variants to psychiatric symptoms and cognitive ability

Copy number variants (CNVs) are deletions and duplications of DNA sequence. The most frequently studied CNVs, which are described in this review, are recurrent CNVs that occur in the same locations on the genome. These CNVs have been strongly implicated in neurodevelopmental disorders, namely autism spectrum disorder (ASD), intellectual disability (ID), and developmental delay (DD), but also in schizophrenia. More recent work has also shown that CNVs increase risk for other psychiatric disorders, namely, depression, bipolar disorder, and post-traumatic stress disorder. Many of the same CNVs are implicated across all of these disorders, and these neuropsychiatric CNVs are also associated with cognitive ability in the general population, as well as with structural and functional brain alterations. Neuropsychiatric CNVs also show incomplete penetrance, such that carriers do not always develop any psychiatric disorder, and may show only mild symptoms, if any. Variable expressivity, whereby the same CNVs are associated with many different phenotypes of varied severity, also points to highly complex mechanisms underlying disease risk in CNV carriers. Comprehensive and longitudinal phenotyping studies of individual CNVs have provided initial insights into these mechanisms. However, more work is needed to estimate and predict the effect of non-recurrent, ultra-rare CNVs, which also contribute to psychiatric and cognitive outcomes. Moreover, delineating the broader phenotypic landscape of neuropsychiatric CNVs in both clinical and general population cohorts may also offer important mechanistic insights.

Antipsychotic treatment effects and structural MRI brain changes in schizophrenia

BACKGROUND

Progressive brain structural MRI changes are described in schizophrenia and have been ascribed to both illness progression and antipsychotic treatment. We investigated treatment effects, in terms of total cumulative antipsychotic dose, efficacy and tolerability, on brain structural changes over the first 24 months of treatment in schizophrenia.

METHODS

A prospective, 24-month, single-site cohort study in 99 minimally treated patients with first-episode schizophrenia, schizophreniform and schizoaffective disorder, and 98 matched healthy controls. We treated the patients according to a fixed protocol with flupenthixol decanoate, a long-acting injectable antipsychotic. We assessed psychopathology, cognition, extrapyramidal symptoms and BMI, and acquired MRI scans at months 0, 12 and 24. We selected global cortical thickness, white matter volume and basal ganglia volume as the regions of interest.

RESULTS

The only significant group × time interaction was for basal ganglia volumes. However, patients, but not controls, displayed cortical thickness reductions and increases in white matter and basal ganglia volumes. Cortical thickness reductions were unrelated to treatment. White matter volume increases were associated with lower cumulative antipsychotic dose, greater improvements in psychopathology and cognition, and more extrapyramidal symptoms. Basal ganglia volume increases were associated with greater improvements in psychopathology, greater increases in BMI and more extrapyramidal symptoms.

CONCLUSIONS

We provide evidence for plasticity in white matter and basal ganglia associated with antipsychotic treatment in schizophrenia, most likely linked to the dopamine blocking actions of these agents. Cortical changes may be more closely related to the neurodevelopmental, non-dopaminergic aspects of the illness.

Dysregulation of Long Intergenic Non-Coding RNA Expression in the Schizophrenia Brain

BACKGROUND

Transcriptomic studies of the brains of schizophrenia (SZ) patients have produced abundant but largely inconsistent findings about the disorders pathophysiology. These inconsistencies might stem not only from the heterogeneous nature of the disorder, but also from the unbalanced focus on particular cortical regions and protein-coding genes. Compared to protein-coding transcripts, long intergenic non-coding RNA (lincRNA) display substantially greater brain region and disease response specificity, positioning them as prospective indicators of SZ-associated alterations. Further, a growing understanding of the systemic character of the disorder calls for a more systematic screening involving multiple diverse brain regions.

AIM

We aimed to identify and interpret alterations of the lincRNA expression profiles in SZ by examining the transcriptomes of 35 brain regions.

METHODS

We measured the transcriptome of 35 brain regions dissected from eight adult brain specimens, four SZ patients, and four healthy controls, using high-throughput RNA sequencing. Analysis of these data yielded 861 annotated human lincRNAs passing the detection threshold.

RESULTS

Of the 861 detected lincRNA, 135 showed significant region-dependent expression alterations in SZ (two-way ANOVA, BH-adjusted p 0.05) and 37 additionally showed significant differential expression between HC and SZ individuals in at least one region (post hoc Tukey test, p 0.05). For these 37 differentially expressed lincRNAs (DELs), 88% of the differences occurred in a cluster of brain regions containing axon-rich brain regions and cerebellum. Functional annotation of the DEL targets further revealed stark enrichment in neurons and synaptic transmission terms and pathways.

CONCLUSION

Our study highlights the utility of a systematic brain transcriptome analysis relying on the expression profiles measured across multiple brain regions and singles out white matter regions as a prospective target for further SZ research.

Discriminative analysis of schizophrenia patients using graph convolutional networks: A combined multimodal MRI and connectomics analysis

INTRODUCTION

Recent studies in human brain connectomics with multimodal magnetic resonance imaging (MRI) data have widely reported abnormalities in brain structure, function and connectivity associated with schizophrenia (SZ). However, most previous discriminative studies of SZ patients were based on MRI features of brain regions, ignoring the complex relationships within brain networks.

METHODS

We applied a graph convolutional network (GCN) to discriminating SZ patients using the features of brain region and connectivity derived from a combined multimodal MRI and connectomics analysis. Structural magnetic resonance imaging (sMRI) and resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired from 140 SZ patients and 205 normal controls. Eighteen types of brain graphs were constructed for each subject using 3 types of node features, 3 types of edge features, and 2 brain atlases. We investigated the performance of 18 brain graphs and used the TopK pooling layers to highlight salient brain regions (nodes in the graph).

RESULTS

The GCN model, which used functional connectivity as edge features and multimodal features (sMRI + fMRI) of brain regions as node features, obtained the highest average accuracy of 95.8%, and outperformed other existing classification studies in SZ patients. In the explainability analysis, we reported that the top 10 salient brain regions, predominantly distributed in the prefrontal and occipital cortices, were mainly involved in the systems of emotion and visual processing.

DISCUSSION

Our findings demonstrated that GCN with a combined multimodal MRI and connectomics analysis can effectively improve the classification of SZ at an individual level, indicating a promising direction for the diagnosis of SZ patients. The code is available at https://github.com/CXY-scut/GCN-SZ.git.

Transitions between cognitive topographies: contributions of network structure, neuromodulation, and disease

Patterns of neural activity underlie human cognition. Transitions between these patterns are orchestrated by the brain's network architecture. What are the mechanisms linking network structure to cognitively relevant activation patterns? Here we implement principles of network control to investigate how the architecture of the human connectome shapes transitions between 123 experimentally defined cognitive activation maps (cognitive topographies) from the NeuroSynth meta-analytic engine. We also systematically incorporate neurotransmitter receptor density maps (18 receptors and transporters) and disease-related cortical abnormality maps (11 neurodegenerative, psychiatric and neurodevelopmental diseases; N = 17 000 patients, N = 22 000 controls). Integrating large-scale multimodal neuroimaging data from functional MRI, diffusion tractography, cortical morphometry, and positron emission tomography, we simulate how anatomically-guided transitions between cognitive states can be reshaped by pharmacological or pathological perturbation. Our results provide a comprehensive look-up table charting how brain network organisation and chemoarchitecture interact to manifest different cognitive topographies. This computational framework establishes a principled foundation for systematically identifying novel ways to promote selective transitions between desired cognitive topographies.

Evidence for embracing normative modeling

In this work, we expand the normative model repository introduced in Rutherford et al., 2022a to include normative models charting lifespan trajectories of structural surface area and brain functional connectivity, measured using two unique resting-state network atlases (Yeo-17 and Smith-10), and an updated online platform for transferring these models to new data sources. We showcase the value of these models with a head-to-head comparison between the features output by normative modeling and raw data features in several benchmarking tasks: mass univariate group difference testing (schizophrenia versus control), classification (schizophrenia versus control), and regression (predicting general cognitive ability). Across all benchmarks, we show the advantage of using normative modeling features, with the strongest statistically significant results demonstrated in the group difference testing and classification tasks. We intend for these accessible resources to facilitate the wider adoption of normative modeling across the neuroimaging community.

Cerebral blood flow in schizophrenia: A systematic review and meta-analysis of MRI-based studies

INTRODUCTION

Schizophrenia-spectrum disorders (SSD) represent one of the leading causes of disability worldwide and are usually underpinned by neurodevelopmental brain abnormalities observed on a structural and functional level. Nuclear medicine imaging studies of cerebral blood flow (CBF) have already provided insights into the pathophysiology of these disorders. Recent developments in non-invasive MRI techniques such as arterial spin labeling (ASL) have allowed broader examination of CBF across SSD prompting us to conduct an updated literature review of MRI-based perfusion studies. In addition, we conducted a focused meta-analysis of whole brain studies to provide a complete picture of the literature on the topic.

METHODS

A systematic OVID search was performed in Embase, MEDLINEOvid, and PsycINFO. Studies eligible for inclusion in the review involved: 1) individuals with SSD, first-episode psychosis or clinical-high risk for psychosis, or; 2) had healthy controls for comparison; 3) involved MRI-based perfusion imaging methods; and 4) reported CBF findings. No time span was specified for the database queries (last search: 08/2022). Information related to participants, MRI techniques, CBF analyses, and results were systematically extracted. Whole-brain studies were then selected for the meta-analysis procedure. The methodological quality of each included studies was assessed.

RESULTS

For the systematic review, the initial Ovid search yielded 648 publications of which 42 articles were included, representing 3480 SSD patients and controls. The most consistent finding was that negative symptoms were linked to cortical fronto-limbic hypoperfusion while positive symptoms seemed to be associated with hyperperfusion, notably in subcortical structures. The meta-analysis integrated results from 13 whole-brain studies, across 426 patients and 401 controls, and confirmed the robustness of the hypoperfusion in the left superior and middle frontal gyri and right middle occipital gyrus while hyperperfusion was found in the left putamen.

CONCLUSION

This updated review of the literature supports the implication of hemodynamic correlates in the pathophysiology of psychosis symptoms and disorders. A more systematic exploration of brain perfusion could complete the search of a multimodal biomarker of SSD.

Functional dysconnectivity of anterior cingulate subregions in schizophrenia and psychotic and nonpsychotic bipolar disorder

Aberrant resting-state functional connectivity (FC) of anterior cingulate cortex (ACC) has been implicated in the pathophysiology of schizophrenia and bipolar disorder (BP). This study investigated the subregional FC of ACC across schizophrenia and psychotic (PBP) and nonpsychotic BP (NPBP) and the relationship between brain functional alterations and clinical manifestations. A total of 174 first-episode medication-naive patients with schizophrenia (FES), 80 patients with PBP, 77 patients with NPBP and 173 demographically matched healthy controls (HCs) underwent resting-state functional magnetic resonance imaging. Brain-wide FC of ACC subregions was computed for each individual, and compared between the groups. General intelligence was evaluated using the short version of the Wechsler Adult Intelligence Scale. Relationships between FC and various clinical and cognitive variables were estimated using the skipped correlation. The FES, PBP and NPBP groups showed differing connectivity patterns in the left caudal, dorsal and perigenual ACC. Transdiagnostic dysconnectivity was found in the subregional ACC associated with cortical, limbic, striatal and cerebellar regions. Disorder-specific dysconnectivity in FES was identified between the left perigenual ACC and bilateral orbitofrontal cortex, and the left caudal ACC coupling with the default mode network (DMN) and visual processing region was correlated with psychotic symptoms. In the PBP group, FC between the left dorsal ACC and the right caudate was correlated with psychotic symptoms, and FC connected with the DMN was associated with affective symptoms. The current findings confirmed that subregional ACC dysconnectivity could be a key transdiagnostic feature and associated with differing clinical symptomology across schizophrenia and PBP.

Increased cortical surface area but not altered cortical thickness or gyrification in bipolar disorder following stabilisation from a first episode of mania

BACKGROUND

Despite reports of altered brain morphology in established bipolar disorder (BD), there is limited understanding of when these morphological abnormalities emerge. Assessment of patients during the early course of illness can help to address this gap, but few studies have examined surface-based brain morphology in patients at this illness stage.

METHODS

We completed a secondary analysis of baseline data from a randomised control trial of BD individuals stabilised after their first episode of mania (FEM). The magnetic resonance imaging scans of n = 35 FEM patients and n = 29 age-matched healthy controls were analysed. Group differences in cortical thickness, surface area and gyrification were assessed at each vertex of the cortical surface using general linear models. Significant results were identified at p < 0.05 using cluster-wise correction.

RESULTS

The FEM group did not differ from healthy controls with regards to cortical thickness or gyrification. However, there were two clusters of increased surface area in the left hemisphere of FEM patients, with peak coordinates falling within the lateral occipital cortex and pars triangularis.

CONCLUSIONS

Cortical thickness and gyrification appear to be intact in the aftermath of a first manic episode, whilst cortical surface area in the inferior/middle prefrontal and occipitoparietal cortex is increased compared to age-matched controls. It is possible that increased surface area in the FEM group is the outcome of abnormalities in a premorbidly occurring process. In contrast, the findings raise the hypothesis that cortical thickness reductions seen in past studies of individuals with more established BD may be more attributable to post-onset factors.

Brain ageing in schizophrenia: evidence from 26 international cohorts via the ENIGMA Schizophrenia consortium

Schizophrenia (SZ) is associated with an increased risk of life-long cognitive impairments, age-related chronic disease, and premature mortality. We investigated evidence for advanced brain ageing in adult SZ patients, and whether this was associated with clinical characteristics in a prospective meta-analytic study conducted by the ENIGMA Schizophrenia Working Group. The study included data from 26 cohorts worldwide, with a total of 2803 SZ patients (mean age 34.2 years; range 18-72 years; 67% male) and 2598 healthy controls (mean age 33.8 years, range 18-73 years, 55% male). Brain-predicted age was individually estimated using a model trained on independent data based on 68 measures of cortical thickness and surface area, 7 subcortical volumes, lateral ventricular volumes and total intracranial volume, all derived from T1-weighted brain magnetic resonance imaging (MRI) scans. Deviations from a healthy brain ageing trajectory were assessed by the difference between brain-predicted age and chronological age (brain-predicted age difference [brain-PAD]). On average, SZ patients showed a higher brain-PAD of +3.55 years (95% CI: 2.91, 4.19; I2 = 57.53%) compared to controls, after adjusting for age, sex and site (Cohen's d = 0.48). Among SZ patients, brain-PAD was not associated with specific clinical characteristics (age of onset, duration of illness, symptom severity, or antipsychotic use and dose). This large-scale collaborative study suggests advanced structural brain ageing in SZ. Longitudinal studies of SZ and a range of mental and somatic health outcomes will help to further evaluate the clinical implications of increased brain-PAD and its ability to be influenced by interventions.

Polygenic risk score for five major psychiatric disorders associated with volume of distinct brain regions in the general population

Risk genes and abnormal brain structural indices of psychiatric disorders have been extensively studied. However, whether genetic risk influences brain structure in the general population has been rarely studied. The current study enrolled 483 young Chinese adults, calculated their polygenic risk scores (PRS) for psychiatric disorders based on Psychiatric Genomics Consortium GWAS results, and examined the association between PRSs and brain volume. We found that PRSs were associated with the volume of many brain regions, with differences between PRS for different disorder, calculated at different threshold, and calculated using European or East Asian ancestry. Of them, the PRS for Major Depressive Disorder based on European ancestry was positively associated with right temporal gyrus; the PRS for schizophrenia based on East Asian ancestry was negatively associated with right precentral and postcentral gyrus; the PRS for schizophrenia based on European ancestry was positively associated with right superior temporal gyrus. All these brain regions are critical for corresponding disorders. However, no significant associations were found between PRS for Autism Spectrum Disorder / Bipolar Disorder and brain volume; and the association between PRS for Attention Deficit Hyperactivity Disorder at different thresholds and brain volume was inconsistent. These findings suggest distinct brain mechanisms underlying different psychiatric disorders.

Symptom-circuit mappings of the schizophrenia connectome

OBJECTIVE

This paper aims to model the anatomical circuits underlying schizophrenia symptoms, and to explore patterns of abnormal connectivity among brain networks affected by psychopathology.

METHODS

T1 magnetic resonance imaging (MRI), diffusion weighted imaging (DWI), and resting-state functional MRI (rsfMRI) were obtained from a total of 126 patients with schizophrenia who were recruited for the study. The images were processed using the Omniscient software (https://www.o8t. com). We further apply the use of the Hollow-tree Super (HoTS) method to gain insights into what brain regions had abnormal connectivity that might be linked to the symptoms of schizophrenia.

RESULTS

The Positive and Negative Symptom Scale is characterised into 6 factors. Each symptom is mapped with specific anatomical abnormalities and circuits. Comparison between factors reveals co-occurrence in parcels in Factor 1 and Factor 2. Multiple large-scale networks are involved in SCZ symptomatology, with functional connectivity within Default Mode Network (DMN) and Central Executive Network (CEN) regions most frequently associated with measures of psychopathology.

CONCLUSION

We present a summary of the relevant anatomy for regions of the cortical areas as part of a larger effort to understand its contribution in schizophrenia. This unique machine learning-type approach maps symptoms to specific brain regions and circuits by bridging the diagnostic subtypes and analysing the features of the connectome.

Functional connectivity and gray matter deficits within the auditory attention circuit in first-episode psychosis

Background

Selective attention deficits in first episode of psychosis (FEP) can be indexed by impaired attentional modulation of auditory M100. It is unknown if the pathophysiology underlying this deficit is restricted to auditory cortex or involves a distributed attention network. We examined the auditory attention network in FEP.

Methods

MEG was recorded from 27 FEP and 31 matched healthy controls (HC) while alternately ignoring or attending tones. A whole-brain analysis of MEG source activity during auditory M100 identified non-auditory areas with increased activity. Time-frequency activity and phase-amplitude coupling were examined in auditory cortex to identify the attentional executive carrier frequency. Attention networks were defined by phase-locking at the carrier frequency. Spectral and gray matter deficits in the identified circuits were examined in FEP.

Results

Attention-related activity was identified in prefrontal and parietal regions, markedly in precuneus. Theta power and phase coupling to gamma amplitude increased with attention in left primary auditory cortex. Two unilateral attention networks were identified with precuneus seeds in HC. Network synchrony was impaired in FEP. Gray matter thickness was reduced within the left hemisphere network in FEP but did not correlate with synchrony.

Conclusion

Several extra-auditory attention areas with attention-related activity were identified. Theta was the carrier frequency for attentional modulation in auditory cortex. Left and right hemisphere attention networks were identified, with bilateral functional deficits and left hemisphere structural deficits, though FEP showed intact auditory cortex theta phase-gamma amplitude coupling. These novel findings indicate attention-related circuitopathy early in psychosis potentially amenable to future non-invasive interventions.

Morphological fingerprinting: Identifying patients with first-episode schizophrenia using auto-encoded morphological patterns

Although a large number of case-control statistical and machine learning studies have been conducted to investigate structural brain changes in schizophrenia, how best to measure and characterize structural abnormalities for use in classification algorithms remains an open question. In the current study, a convolutional 3D autoencoder specifically designed for discretized volumes was constructed and trained with segmented brains from 477 healthy individuals. A cohort containing 158 first-episode schizophrenia patients and 166 matched controls was fed into the trained autoencoder to generate auto-encoded morphological patterns. A classifier discriminating schizophrenia patients from healthy controls was built using 80% of the samples in this cohort by automated machine learning and validated on the remaining 20% of the samples, and this classifier was further validated on another independent cohort containing 77 first-episode schizophrenia patients and 58 matched controls acquired at a different resolution. This specially designed autoencoder allowed a satisfactory recovery of the input. With the same feature dimension, the classifier trained with autoencoded features outperformed the classifier trained with conventional morphological features by about 10% points, achieving 73.44% accuracy and 0.8 AUC on the internal validation set and 71.85% accuracy and 0.77 AUC on the external validation set. The use of features automatically learned from the segmented brain can better identify schizophrenia patients from healthy controls, but there is still a need for further improvements to establish a clinical diagnostic marker. However, with a limited sample size, the method proposed in the current study shed insight into the application of deep learning in psychiatric disorders.

Brain regions associated with olfactory dysfunction in first episode psychosis patients

OBJECTIVES

Olfactory dysfunction is reproducibly reported in psychotic disorders, particularly in association with negative symptoms. The superior frontal gyrus (SFG) has been frequently studied in patients with psychotic disorders, in particular with their associations with negative symptoms. The relationship between olfactory functions and brain structure has been studied in healthy controls (HCs). Nevertheless, the studies with patients with psychotic disorders are limited. Here we report the olfactory-brain relationship in a first episode psychosis (FEP) cohort through both hypothesis-driven (centred on the SFG) and data-driven approaches.

METHODS

Using data from 88 HCs and 76 FEP patients, we evaluated the correlation between olfactory functions and structural/resting-state functional magnetic resonance imaging (MRI) data.

RESULTS

We found a significant correlation between the left SFG volume and odour discrimination in FEP patients, but not in HCs. We also observed a significant correlation between rs-fMRI connectivity involving the left SFG and odour discrimination in FEP patients, but not in HCs. The data-driven approach didn't observe any significant correlations, possibly due to insufficient statistical power.

CONCLUSION

The left SFG may be a promising brain region in the context of olfactory dysfunction and negative symptoms in FEP.

Editorial: Irritable Imaging: Interpreting Null Results in Psychiatric Neuroimaging

There is a growing appreciation that clinically impairing irritability is an important transdiagnostic symptom among children and adolescents with mental illness. Severe irritability, defined by frequent, developmentally inappropriate temper outbursts and low frustration tolerance, is one of the most common reasons that youths are referred for psychiatric evaluation and care.¹ Although chronic irritability is the primary symptom in disruptive mood dysregulation disorder, the symptom is common in a diverse set of DSM-5 diagnoses, including major depressive disorder, autism spectrum disorder, oppositional defiant disorder, bipolar disorder, and generalized anxiety disorder.¹ Given that clinically impairing irritability is often predictive of poor outcomes in childhood and worse clinical course in adulthood, a concerted effort is being made to refine the definition of this symptom and determine if severe irritability could be better understood and treated as an independent diagnosis.¹.

Cortical profiles of numerous psychiatric disorders and normal development share a common pattern

The neurobiological bases of the association between development and psychopathology remain poorly understood. Here, we identify a shared spatial pattern of cortical thickness (CT) in normative development and several psychiatric and neurological disorders. Principal component analysis (PCA) was applied to CT of 68 regions in the Desikan-Killiany atlas derived from three large-scale datasets comprising a total of 41,075 neurotypical participants. PCA produced a spatially broad first principal component (PC1) that was reproducible across datasets. Then PC1 derived from healthy adult participants was compared to the pattern of CT differences associated with psychiatric and neurological disorders comprising a total of 14,886 cases and 20,962 controls from seven ENIGMA disease-related working groups, normative maturation and aging comprising a total of 17,697 scans from the ABCD Study® and the IMAGEN developmental study, and 17,075 participants from the ENIGMA Lifespan working group, as well as gene expression maps from the Allen Human Brain Atlas. Results revealed substantial spatial correspondences between PC1 and widespread lower CT observed in numerous psychiatric disorders. Moreover, the PC1 pattern was also correlated with the spatial pattern of normative maturation and aging. The transcriptional analysis identified a set of genes including KCNA2, KCNS1 and KCNS2 with expression patterns closely related to the spatial pattern of PC1. The gene category enrichment analysis indicated that the transcriptional correlations of PC1 were enriched to multiple gene ontology categories and were specifically over-represented starting at late childhood, coinciding with the onset of significant cortical maturation and emergence of psychopathology during the prepubertal-to-pubertal transition. Collectively, the present study reports a reproducible latent pattern of CT that captures interregional profiles of cortical changes in both normative brain maturation and a spectrum of psychiatric disorders. The pubertal timing of the expression of PC1-related genes implicates disrupted neurodevelopment in the pathogenesis of the spectrum of psychiatric diseases emerging during adolescence.

Genomic insights into schizophrenia

Schizophrenia is a common, complex, heterogeneous psychiatric syndrome which can have profound impacts on affected individuals and imposes significant burdens on society. Despite intensive research, it has been challenging to understand basic mechanisms and to identify novel therapeutic targets. Given its high heritability and the complexity and inaccessibility of the human brain, much hope has been invested in the application of genomics as a route to better understanding. This work has identified many common and rare risk alleles and laid the foundations for a new generation of mechanistic studies. Genomics has also thrown new light on the relationship between schizophrenia and other psychiatric disorders and revealed its previously unappreciated aetiological relationship with childhood neurodevelopmental disorders, providing further evidence that it has its origins in disturbances of brain development. In addition, genomic findings suggest that the condition reflects fundamental disturbances in neuronal, and particularly synaptic, function that impact broadly on brain function, rather than being a disorder of specific brain regions and circuits. Finally, genomics has provided a plausible solution to the evolutionary paradox of how the condition persists in the face of high heritability and reduced fecundity.

New insights from the last decade of research in psychiatric genetics: discoveries, challenges and clinical implications

Psychiatric genetics has made substantial progress in the last decade, providing new insights into the genetic etiology of psychiatric disorders, and paving the way for precision psychiatry, in which individual genetic profiles may be used to personalize risk assessment and inform clinical decision-making. Long recognized to be heritable, recent evidence shows that psychiatric disorders are influenced by thousands of genetic variants acting together. Most of these variants are commonly occurring, meaning that every individual has a genetic risk to each psychiatric disorder, from low to high. A series of large-scale genetic studies have discovered an increasing number of common and rare genetic variants robustly associated with major psychiatric disorders. The most convincing biological interpretation of the genetic findings implicates altered synaptic function in autism spectrum disorder and schizophrenia. However, the mechanistic understanding is still incomplete. In line with their extensive clinical and epidemiological overlap, psychiatric disorders appear to exist on genetic continua and share a large degree of genetic risk with one another. This provides further support to the notion that current psychiatric diagnoses do not represent distinct pathogenic entities, which may inform ongoing attempts to reconceptualize psychiatric nosology. Psychiatric disorders also share genetic influences with a range of behavioral and somatic traits and diseases, including brain structures, cognitive function, immunological phenotypes and cardiovascular disease, suggesting shared genetic etiology of potential clinical importance. Current polygenic risk score tools, which predict individual genetic susceptibility to illness, do not yet provide clinically actionable information. However, their precision is likely to improve in the coming years, and they may eventually become part of clinical practice, stressing the need to educate clinicians and patients about their potential use and misuse. This review discusses key recent insights from psychiatric genetics and their possible clinical applications, and suggests future directions.

Normative modeling of brain morphometry in Clinical High-Risk for Psychosis

Importance

The lack of robust neuroanatomical markers of psychosis risk has been traditionally attributed to heterogeneity. A complementary hypothesis is that variation in neuroanatomical measures in the majority of individuals at psychosis risk may be nested within the range observed in healthy individuals.

Objective

To quantify deviations from the normative range of neuroanatomical variation in individuals at clinical high-risk for psychosis (CHR-P) and evaluate their overlap with healthy variation and their association with positive symptoms, cognition, and conversion to a psychotic disorder.

Design Setting and Participants

Clinical, IQ and FreeSurfer-derived regional measures of cortical thickness (CT), cortical surface area (SA), and subcortical volume (SV) from 1,340 CHR-P individuals [47.09% female; mean age: 20.75 (4.74) years] and 1,237 healthy individuals [44.70% female; mean age: 22.32 (4.95) years] from 29 international sites participating in the ENIGMA Clinical High Risk for Psychosis Working Group.

Main Outcomes and Measures

For each regional morphometric measure, z-scores were computed that index the degree of deviation from the normative means of that measure in a healthy reference population (N=37,407). Average deviation scores (ADS) for CT, SA, SV, and globally across all measures (G) were generated by averaging the respective regional z-scores. Regression analyses were used to quantify the association of deviation scores with clinical severity and cognition and two-proportion z-tests to identify case-control differences in the proportion of individuals with infranormal (z<-1.96) or supranormal (z>1.96) scores.

Results

CHR-P and healthy individuals overlapped in the distributions of the observed values, regional z-scores, and all ADS vales. The proportion of CHR-P individuals with infranormal or supranormal values in any metric was low (<12%) and similar to that of healthy individuals. CHR-P individuals who converted to psychosis compared to those who did not convert had a higher percentage of infranormal values in temporal regions (5-7% vs 0.9-1.4%). In the CHR-P group, only the ADSSA showed significant but weak associations (|β|<0.09; PFDR<0.05) with positive symptoms and IQ.

Conclusions and Relevance

The study findings challenge the usefulness of macroscale neuromorphometric measures as diagnostic biomarkers of psychosis risk and suggest that such measures do not provide an adequate explanation for psychosis risk.

Longitudinal Changes in Cortical Surface Area Associated With Transition to Psychosis in Adolescents at Clinical High Risk for the Disease

OBJECTIVE

Identifying biomarkers of transition to psychosis in individuals at clinical high risk for psychosis (CHR-P) is essential to understanding the mechanisms underlying the disease. Although cross-sectional abnormalities in cortical surface area (CSA) have been demonstrated in individuals at CHR-P who transition to psychosis (CHR-P-T) compared with those who do not (CHR-P-NT), how CSA longitudinally develops remains unclear, especially in younger individuals. We set out to compare CSA in adolescents at CHR-P and healthy controls (HC) over 2 points in time.

METHOD

A longitudinal multicenter study was performed in adolescents at CHR-P in comparison to HC and according to transition to psychosis. Magnetic resonance imaging scans were acquired at baseline, at 18-month follow-up, or at the time of transition. Images were pre-processed and hemisphere and regional CSA were computed using FreeSurfer. Between-group analyses were performed with linear mixed-effects models.

RESULTS

A total of 313 scans (107 CHR-P and 102 HC) were included in the analysis. At 18 months, the rate of transition to psychosis in CHR-P was 23.4%. Adolescents at CHR-P-T presented greater age-related decrease in CSA in the left parietal and occipital lobes compared with HC, and in the bilateral parietal lobe and right frontal lobe relative to CHR-P-NT. These results were not influenced by antipsychotic treatment, cannabis use, or intelligence quotient (IQ).

CONCLUSION

Adolescents at CHR-P that developed a psychotic disorder presented different developmental trajectories of CSA relative to those who did not. A relatively greater decrease in CSA in the parietal and frontal lobes may index clinical transition to psychosis in adolescents at CHR-P.

Biological hypotheses, risk factors, and biomarkers of schizophrenia

Both the discovery of biomarkers of schizophrenia and the verification of biological hypotheses of schizophrenia are an essential part of the process of understanding the etiology of this mental disorder. Schizophrenia has long been considered a neurodevelopmental disease whose symptoms are caused by impaired synaptic signal transduction and brain neuroplasticity. Both the onset and chronic course of schizophrenia are associated with risk factors-induced disruption of brain function and the establishment of a new homeostatic setpoint characterized by biomarkers. Different risk factors and biomarkers can converge to the same symptoms of schizophrenia, suggesting that the primary cause of the disease can be highly individual. Schizophrenia-related biomarkers include measurable biochemical changes induced by stress (elevated allostatic load), mitochondrial dysfunction, neuroinflammation, oxidative and nitrosative stress, and circadian rhythm disturbances. Here is a summary of selected valid biological hypotheses of schizophrenia formulated based on risk factors and biomarkers, neurodevelopment, neuroplasticity, brain chemistry, and antipsychotic medication. The integrative neurodevelopmental-vulnerability-neurochemical model is based on current knowledge of the neurobiology of the onset and progression of the disease and the effects of antipsychotics and psychotomimetics and reflects the complex and multifactorial nature of schizophrenia.

Harmonization of multi-scanner in vivo magnetic resonance spectroscopy: ENIGMA consortium task group considerations

Magnetic resonance spectroscopy is a powerful, non-invasive, quantitative imaging technique that allows for the measurement of brain metabolites that has demonstrated utility in diagnosing and characterizing a broad range of neurological diseases. Its impact, however, has been limited due to small sample sizes and methodological variability in addition to intrinsic limitations of the method itself such as its sensitivity to motion. The lack of standardization from a data acquisition and data processing perspective makes it difficult to pool multiple studies and/or conduct multisite studies that are necessary for supporting clinically relevant findings. Based on the experience of the ENIGMA MRS work group and a review of the literature, this manuscript provides an overview of the current state of MRS data harmonization. Key factors that need to be taken into consideration when conducting both retrospective and prospective studies are described. These include (1) MRS acquisition issues such as pulse sequence, RF and B0 calibrations, echo time, and SNR; (2) data processing issues such as pre-processing steps, modeling, and quantitation; and (3) biological factors such as voxel location, age, sex, and pathology. Various approaches to MRS data harmonization are then described including meta-analysis, mega-analysis, linear modeling, ComBat and artificial intelligence approaches. The goal is to provide both novice and experienced readers with the necessary knowledge for conducting MRS data harmonization studies.

Psychotic Symptom, Mood, and Cognition-associated Multimodal MRI Reveal Shared Links to the Salience Network Within the Psychosis Spectrum Disorders

Schizophrenia (SZ), schizoaffective disorder (SAD), and psychotic bipolar disorder share substantial overlap in clinical phenotypes, associated brain abnormalities and risk genes, making reliable diagnosis among the three illness challenging, especially in the absence of distinguishing biomarkers. This investigation aims to identify multimodal brain networks related to psychotic symptom, mood, and cognition through reference-guided fusion to discriminate among SZ, SAD, and BP. Psychotic symptom, mood, and cognition were used as references to supervise functional and structural magnetic resonance imaging (MRI) fusion to identify multimodal brain networks for SZ, SAD, and BP individually. These features were then used to assess the ability in discriminating among SZ, SAD, and BP. We observed shared links to functional and structural covariation in prefrontal, medial temporal, anterior cingulate, and insular cortices among SZ, SAD, and BP, although they were linked with different clinical domains. The salience (SAN), default mode (DMN), and fronto-limbic (FLN) networks were the three identified multimodal MRI features within the psychosis spectrum disorders from psychotic symptom, mood, and cognition associations. In addition, using these networks, we can classify patients and controls and distinguish among SZ, SAD, and BP, including their first-degree relatives. The identified multimodal SAN may be informative regarding neural mechanisms of comorbidity for psychosis spectrum disorders, along with DMN and FLN may serve as potential biomarkers in discriminating among SZ, SAD, and BP, which may help investigators better understand the underlying mechanisms of psychotic comorbidity from three different disorders via a multimodal neuroimaging perspective.

Neuroimaging in schizophrenia: an overview of findings and their implications for synaptic changes

Over the last five decades, a large body of evidence has accrued for structural and metabolic brain alterations in schizophrenia. Here we provide an overview of these findings, focusing on measures that have traditionally been thought to reflect synaptic spine density or synaptic activity and that are relevant for understanding if there is lower synaptic density in the disorder. We conducted literature searches to identify meta-analyses or other relevant studies in patients with chronic or first-episode schizophrenia, or in people at high genetic or clinical risk for psychosis. We identified 18 meta-analyses including over 50,000 subjects in total, covering: structural MRI measures of gyrification index, grey matter volume, grey matter density and cortical thickness, neurite orientation dispersion and density imaging, PET imaging of regional glucose metabolism and magnetic resonance spectroscopy measures of N-acetylaspartate. We also review preclinical evidence on the relationship between ex vivo synaptic measures and structural MRI imaging, and PET imaging of synaptic protein 2A (SV2A). These studies show that schizophrenia is associated with lower grey matter volumes and cortical thickness, accelerated grey matter loss over time, abnormal gyrification patterns, and lower regional SV2A levels and metabolic markers in comparison to controls (effect sizes from ~ -0.11 to -1.0). Key regions affected include frontal, anterior cingulate and temporal cortices and the hippocampi. We identify several limitations for the interpretation of these findings in terms of understanding synaptic alterations. Nevertheless, taken with post-mortem findings, they suggest that schizophrenia is associated with lower synaptic density in some brain regions. However, there are several gaps in evidence, in particular whether SV2A findings generalise to other cohorts.

Genetic Heterogeneity Shapes Brain Connectivity in Psychiatry

BACKGROUND

Polygenicity and genetic heterogeneity pose great challenges for studying psychiatric conditions. Genetically informed approaches have been implemented in neuroimaging studies to address this issue. However, the effects on functional connectivity of rare and common genetic risks for psychiatric disorders are largely unknown. Our objectives were to estimate and compare the effect sizes on brain connectivity of psychiatric genomic risk factors with various levels of complexity: oligogenic copy number variants (CNVs), multigenic CNVs, and polygenic risk scores (PRSs) as well as idiopathic psychiatric conditions and traits.

METHODS

Resting-state functional magnetic resonance imaging data were processed using the same pipeline across 9 datasets. Twenty-nine connectome-wide association studies were performed to characterize the effects of 15 CNVs (1003 carriers), 7 PRSs, 4 idiopathic psychiatric conditions (1022 individuals with autism, schizophrenia, bipolar conditions, or attention-deficit/hyperactivity disorder), and 2 traits (31,424 unaffected control subjects).

RESULTS

Effect sizes on connectivity were largest for psychiatric CNVs (estimates: 0.2-0.65 z score), followed by psychiatric conditions (0.15-0.42), neuroticism and fluid intelligence (0.02-0.03), and PRSs (0.01-0.02). Effect sizes of CNVs on connectivity were correlated to their effects on cognition and risk for disease (r = 0.9, p = 5.93 × 10-6). However, effect sizes of CNVs adjusted for the number of genes significantly decreased from small oligogenic to large multigenic CNVs (r = -0.88, p = 8.78 × 10-6). PRSs had disproportionately low effect sizes on connectivity compared with CNVs conferring similar risk for disease.

CONCLUSIONS

Heterogeneity and polygenicity affect our ability to detect brain connectivity alterations underlying psychiatric manifestations.

The Microbiome and Mental Health Across the Lifespan

INTRODUCTION

The combined genetic material of the microorganisms in the human body, known as the microbiome, is being increasingly recognized as a major determinant of human health and disease. Although located predominantly on mucosal surfaces, these microorganisms have profound effects on brain functioning through the gut-brain axis.

METHOD

The content of the chapter is based on a study group session at the annual meeting of the American College of Neuropsychopharmacology (ACNP). The objective was to discuss the emerging relationship between the human microbiome and mental health as relevant to ACNP's interests in developing and evaluating novel neuropsychiatric treatment strategies. The focus is on specific brain disorders, such as schizophrenia, substance use, and Alzheimer's disease, as well as on broader clinical issues such as suicidality, loneliness and wisdom in old age, and longevity.

RESULTS

Studies of schizophrenia indicate that the microbiome of individuals with this disorder differs from that of non-psychiatric comparison groups in terms of diversity and composition. Differences are also found in microbial metabolic pathways. An early study in substance use disorders found that individuals with this disorder have lower levels of beta diversity in their oral microbiome than a comparison group. This measure, along with others, was used to distinguish individuals with substance use disorders from controls. In terms of suicidality, there is preliminary evidence that persons who have made a suicide attempt differ from psychiatric and non-psychiatric comparison groups in measures of beta diversity. Exploratory studies in Alzheimer's disease indicate that gut microbes may contribute to disease pathogenesis by regulating innate immunity and neuroinflammation and thus influencing brain function. In another study looking at the microbiome in older adults, positive associations were found between wisdom and alpha diversity and negative associations with subjective loneliness. In other studies of older adults, here with a focus on longevity, individuals with healthy aging and unusually long lives had an abundance of specific microorganisms which distinguished them from other individuals.

DISCUSSION

Future studies would benefit from standardizing methods of sample collection, processing, and analysis. There is also a need for the standardized collection of relevant demographic and clinical data, including diet, medications, cigarette smoking, and other potentially confounding factors. While still in its infancy, research to date indicates a role for the microbiome in mental health disorders and conditions. Interventions are available which can modulate the microbiome and lead to clinical improvements. These include microbiome-altering medications as well as probiotic microorganisms capable of modulating the inflammation in the brain through the gut-brain axis. This research holds great promise in terms of developing new methods for the prevention and treatment of a range of human brain disorders.

Decreased cortical gyrification and surface area in the left medial parietal cortex in patients with treatment-resistant and ultratreatment-resistant schizophrenia

AIM

Validating the vulnerabilities and pathologies underlying treatment-resistant schizophrenia (TRS) is an important challenge in optimizing treatment. Gyrification and surface area (SA), reflecting neurodevelopmental features, have been linked to genetic vulnerability to schizophrenia. The aim of this study was to identify gyrification and SA abnormalities specific to TRS.

METHODS

We analyzed 3T magnetic resonance imaging findings of 24 healthy controls (HCs), 20 responders to first-line antipsychotics (FL-Resp), and 41 patients with TRS, including 19 clozapine responders (CLZ-Resp) and 22 FL- and clozapine-resistant patients (patients with ultratreatment-resistant schizophrenia [URS]). The local gyrification index (LGI) and associated SA were analyzed across groups. Diagnostic accuracy was verified by receiver operating characteristic curve analysis.

RESULTS

Both CLZ-Resp and URS had lower LGI values than HCs (P = 0.041, Hedges g [g_H ] = 0.75; P = 0.013, g_H  = 0.96) and FL-Resp (P = 0.007, g_H  = 1.00; P = 0.002, g_H  = 1.31) in the left medial parietal cortex (Lt-MPC). In addition, both CLZ-Resp and URS had lower SA in the Lt-MPC than FL-Resp (P < 0.001, g_H  = 1.22; P < 0.001, g_H  = 1.75). LGI and SA were positively correlated in non-TRS (FL-Resp) (ρ = 0.64, P = 0.008) and TRS (CLZ-Resp + URS) (ρ = 0.60, P < 0.001). The areas under the receiver operating characteristic curve for non-TRS versus TRS with LGI and SA in the Lt-MPC were 0.79 and 0.85, respectively. SA in the Lt-MPC was inversely correlated with negative symptoms (ρ = -0.40, P = 0.018) and clozapine plasma levels (ρ = -0.35, P = 0.042) in TRS.

CONCLUSION

LGI and SA in the Lt-MPC, a functional hub in the default-mode network, were abnormally reduced in TRS compared with non-TRS. Thus, altered LGI and SA in the Lt-MPC might be structural features associated with genetic vulnerability to TRS.

Mendelian Randomization Analyses Accounting for Causal Effect of COVID-19 on Brain Imaging-Derived Phenotypes

BACKGROUND

The coronavirus disease 2019 (COVID-19) has been a major challenge to global health and a financial burden. Little is known regarding the possible causal effects of COVID-19 on the macro- and micro-structures of the human brain.

OBJECTIVE

To determine the causal links between susceptibility, hospitalization, and the severity of COVID-19 and brain imaging-derived phenotypes (IDPs).

METHODS

Mendelian randomization (MR) analyses were performed to investigate the causal effect of three COVID-19 exposures (SARS-CoV-2 infection, hospitalized COVID-19, and critical COVID-19) on brain structure employing summary datasets of genome-wide association studies.

RESULTS

In terms of cortical phenotypes, hospitalization due to COVID-19 was associated with a global decrease in the surface area (SA) of the cortex structure (β= -624.77, 95% CI: -1227.88 to -21.66, p = 0.042). At the regional level, SARS-CoV-2 infection was found to have a nominally causal effect on the thickness (TH) of the postcentral region (β= -0.004, 95% CI: -0.007 to -0.001, p = 0.01), as well as eight other IDPs. Hospitalized COVID-19 has a nominally causal relationship with TH of postcentral (β= -0.004, 95% CI: -0.007 to -0.001, p = 0.01) and other 6 IDPs. The nominally causal effects of critical COVID-19 on TH of medial orbitofrontal (β=0.004, 95% CI: 0.001to 0.007, p = 0.004) and other 7 IDPs were revealed.

CONCLUSIONS

Our study provides compelling genetic evidence supporting causal relationships between three COVID-19 traits and brain IDPs. This discovery holds promise for enhancing predictions and interventions in brain imaging.

Higher polygenic risk scores for anxiety disorders are associated with reduced area in the anterior cingulate gyrus

Anxiety disorders are heterogeneous, show a moderate genetic contribution and are associated with inconsistent cortical structure alterations. Here, we investigated whether genetic factors for anxiety disorders contribute to cortical alterations by conducting polygenic risk score (PRS) analyses. We calculated PRSs for anxiety disorders at several P value thresholds (from P_T ≤ 5.0 × 10^-8 to P_T ≤ 1.0) based on the latest large-scale genome-wide association study of anxiety disorders from the UK biobank (25,453 cases; 58,113 controls) in an independent sample of psychiatrically and physically healthy subjects (n = 174). Using regression after adjusting for confounding factors, we tested whether these PRSs were associated with the surface area and cortical thickness in 34 bilateral brain regions extracted using FreeSurfer. A higher PRS for anxiety disorders at P_T ≤ 1.0 was significantly associated with a reduced right caudal anterior cingulate area (beta = -0.25, p_uncorrected = 9.51 × 10^-4, p_corrected = 0.032). PRSs based on more common SNPs, especially from P_T ≤ 0.01 to P_T ≤ 1.0, were associated with the right caudal anterior cingulate area (a maximum at P_T ≤ 0.5: R² = 0.066, beta = -0.27, p_uncorr = 3.81 × 10^-4, p_corr = 0.013). Furthermore, individuals in the highest quartile for anxiety disorder PRS had lower surface area and volume in the right anterior cingulate gyrus than those in the lowest quartile. We suggest a shared genetic etiology between anxiety disorders and structural features of the anterior cingulate gyrus, possibly contributing to the pathogenesis of anxiety disorders via emotional dysregulations. Our findings suggest the potential usefulness of PRS to reduce pathological heterogeneity among anxiety disorders.

Cumulative Impact of Morphometric Features in Schizophrenia in Two Independent Samples

Schizophrenia and bipolar disorder share a common structural brain alteration profile. However, there is considerable between- and within-diagnosis variability in these features, which may underestimate informative individual differences. Using a recently established morphometric risk score (MRS) approach, we aim to provide confirmation that individual MRS scores are higher in individuals with a psychosis diagnosis, helping to parse individual heterogeneity. Using the Human Connectome Project Early Psychosis (N = 124), we estimate MRS for psychosis and specifically for bipolar/schizophrenia using T1-weighted MRI data and prior meta-analysis effect sizes. We confirm associations in an independent replication sample (N = 69). We assess (1) the impact of diagnosis on these MRS, (2) compare effect sizes of MRS to all individual, cytoarchitecturally defined brain regions, and (3) perform negative control analyses to assess MRS specificity. The MRS specifically for SCZ was higher in the whole psychosis group (Cohen's d = 0.56; P = 0.003) and outperformed any single region of interest in standardized mean difference (ZMRS>75 ROIS = 2.597; P = 0.009) and correlated with previously reported effect sizes (PSPIN/SHUFFLE < 0.005). MRS without Enhancing Neuroimaging Genomics through Meta-Analysis weights did not delineate groups with empirically null associations (t = 2.29; P = 0.02). We replicate MRS specifically for SCZ associations in the independent sample. Akin to polygenic risk scoring and individual allele effect sizes, these observations suggest that assessing the combined impact of regional structural alterations may be more informative than any single cytoarchitecturally constrained cortical region, where well-powered, meta-analytical samples are informative in the delineation of diagnosis and within psychosis case differences, in smaller independent samples.

[An effect of antipsychotic and anticholinergic treatment on cognitive function in patients with schizophrenia]

OBJECTIVE

To reveal the relationships between antipsychotic and anticholinergic drugs and cognitive functions in patients with schizophrenia.

MATERIAL AND METHODS

The observational prospective study was conducted at the Bekhterev National Medical Center of Psychiatry and Neurology. The study involved 41 patients (22 men and 19 women) with paranoid schizophrenia, according to ICD 10 criteria, aged 30.12±8.24 years on stable antipsychotic monotherapy or in combination with anticholinergic drug (trihexiphenidyl). Cognitive functions were assessed using the «Brief Assessment of Cognitive Function in Patients with Schizophrenia» (BACS) scale, severity of mental state and extrapyramidal disturbances were measured using the «Positive and Negative Syndrome Scale (PANSS) and the Simpson-Angus Scale for Assessment of Extrapyramidal Side Effects (SAS). All examination procedures were performed twice at weeks 2 and 8 of therapy. Patients were divided into 2 groups according to the type of antipsychotic therapy. Twelve patients received first generation antipsychotics (FGAs) (group 1), 29 patients received second generation antipsychotics (SGAs) (group 2).

RESULTS

Patients receiving SGAs had a significant decrease in the overall SAS score at week 8 of therapy compared with data at week 2, and there was an improvement in cognitive function, unlike patients receiving FGAs. There were also changes on BACS tests the digit sequencing (V=51.5, p=0.007), token motor task (V=75.5, p=0.007) and Tower of London (V=52, p=0.027) only in patients of group 2.

CONCLUSION

The improved tolerance to the drug, as well as cognitive measures, was shown in patients taking SGAs by week 8. Our study confirms the importance of adhering to the minimum effective dose of antipsychotic drugs for the treatment of schizophrenia to prevent cognitive impairment, and to give preference to SGAs in the choice of treatment.

Atypical frontotemporal cortical activity in first-episode adolescent-onset schizophrenia during verbal fluency task: A functional near-infrared spectroscopy study

Background

Frontotemporal cortex dysfunction has been found to be associated with cognitive impairment in patients with schizophrenia (SCZ). In patients with adolescent-onset SCZ, a more serious type of SCZ with poorer functional outcome, cognitive impairment appeared to occur at an early stage of the disease. However, the characteristics of frontotemporal cortex involvement in adolescent patients with cognitive impairment are still unclear. In the present study, we aimed to illustrate the frontotemporal hemodynamic response during a cognitive task in adolescents with first-episode SCZ.

Methods

Adolescents with first-episode SCZ who were aged 12-17 and demographically matched healthy controls (HCs) were recruited. We used a 48-channel functional near-infrared spectroscopy (fNIRS) system to record the concentration of oxygenated hemoglobin (oxy-Hb) in the participants' frontotemporal area during a verbal fluency task (VFT) and analyzed its correlation with clinical characteristics.

Results

Data from 36 adolescents with SCZ and 38 HCs were included in the analyses. Significant differences were found between patients with SCZ and HCs in 24 channels, mainly covering the dorsolateral prefrontal cortex, superior and middle temporal gyrus and frontopolar area. Adolescents with SCZ showed no increase of oxy-Hb concentration in most channels, while the VFT performance was comparable between the two groups. In SCZ, the intensity of activation was not associated with the severity of symptoms. Finally, receiver operating characteristic analysis indicated that the changes in oxy-Hb concentration could help distinguish the two groups.

Conclusion

Adolescents with first-episode SCZ showed atypical cortical activity in the frontotemporal area during the VFT, and fNIRS features might be more sensitive indicators in cognitive assessment, indicating that the characteristic hemodynamic response pattern might be potential imaging biomarkers for this population.

Association of cortical thickness and cognition with schizophrenia treatment resistance

AIM

Approximately a third of patients with schizophrenia fail to adequately respond to antipsychotic medications, a condition known as treatment resistance (TR). We aimed to assess cognitive and cortical thickness deficits and their relationship to TR in schizophrenia.

METHOD

We recruited patients with schizophrenia (n = 127), including patients at treatment initiation (n = 45), treatment-responsive patients (n = 40) and TR patients (n = 42), and healthy controls (n = 83). Clinical symptoms, neurocognitive function, and structural images were assessed. We performed group comparisons, and explored association of cortical thickness and cognition with TR.

RESULTS

The TR patients showed significantly more severe clinical symptoms and cognitive impairment relative to the treatment-responsive group. Compared to healthy controls, 56 of 68 brain regions showed significantly reduced cortical thickness in patients with schizophrenia. Reductions in five regions were significantly associated with TR (reduction in TR relative to treatment-responsive patients), i.e. in the right caudal middle frontal gyrus, superior frontal cortex, fusiform gyrus, pars opercularis of the inferior frontal cortex, and supramarginal cortex. Cognition deficits were also significantly correlated with cortical thickness in these five regions in patients with schizophrenia. Cortical thickness of the right caudal middle frontal gyrus, superior frontal cortex and pars opercularis of the inferior frontal cortex also significantly mediated effects of cognitive deficits on TR.

CONCLUSION

Treatment resistance in schizophrenia was associated with reduced thickness in the right caudal middle frontal gyrus, superior frontal cortex, fusiform gyrus, pars opercularis of the inferior frontal cortex, and supramarginal cortex. Cortical abnormalities further mediate cognitive deficits known to be associated with TR.

The Difficult Path to the Discovery of Novel Treatments in Psychiatric Disorders

CNS diseases, including psychiatric disorders, represent a significant opportunity for the discovery and development of new drugs and therapeutic treatments with the potential to have a significant impact on human health. CNS diseases, however, present particular challenges to therapeutic discovery efforts, and psychiatric diseases/disorders may be among the most difficult. With specific exceptions such as psychostimulants for ADHD, a large number of psychiatric patients are resistant to existing treatments. In addition, clinicians have no way of knowing which psychiatric patients will respond to which drugs. By definition, psychiatric diagnoses are syndromal in nature; determinations of efficacy are often self-reported, and drug discovery is largely model-based. While such models of psychiatric disease are amenable to screening for new drugs, whether cellular or whole-animal based, they have only modest face validity and, more importantly, predictive validity. Multiple academic, pharmaceutical industry, and government agencies are dedicated to the translation of new findings about the neurobiology of major psychiatric disorders into the discovery and advancement of novel therapies. The collaboration of these agencies provide a pathway for developing new therapeutics. These efforts will be greatly helped by recent advances in understanding the genetic bases of psychiatric disorders, the ongoing search for diagnostic and therapy-responsive biomarkers, and the validation of new animal models.

Longitudinal multi-omics alterations response to 8-week risperidone monotherapy: Evidence linking cortical thickness, transcriptomics and epigenetics

Background

Antipsychotic treatment-related alterations of cortical thickness (CT) and clinical symptoms have been previously corroborated, but less is known about whether the changes are driven by gene expression and epigenetic modifications.

Methods

Utilizing a prospective design, we recruited 42 treatment-naive first-episode schizophrenia patients (FESP) and 38 healthy controls. Patients were scanned by TI weighted imaging before and after 8-week risperidone monotherapy. CT estimation was automatically performed with the FreeSurfer software package. Participants' peripheral blood genomic DNA methylation (DNAm) status, quantified by using Infinium^® Human Methylation 450K BeadChip, was examined in parallel with T1 scanning. In total, CT measures from 118 subjects and genomic DNAm status from 114 subjects were finally collected. Partial least squares (PLS) regression was used to detect the spatial associations between longitudinal CT variations after treatment and cortical transcriptomic data acquired from the Allen Human Brain Atlas. Canonical correlation analysis (CCA) was then performed to identify multivariate associations between DNAm of PLS1 genes and patients' clinical improvement.

Results

We detected the significant PLS1 component (2,098 genes) related to longitudinal alterations of CT, and the PLS1 genes were significantly enriched in neurobiological processes, and dopaminergic- and cancer-related pathways. Combining Laplacian score and CCA analysis, we further linked DNAm of 33 representative genes from the 2,098 PLS1 genes with patients' reduction rate of clinical symptoms.

Conclusions

This study firstly revealed that changes of CT and clinical behaviors after treatment may be transcriptionally and epigenetically underlied. We define a "three-step" roadmap which represents a vital step toward the exploration of treatment- and treatment response-related biomarkers on the basis of multiple omics rather than a single omics type as a strategy for advancing precise care.

Schizophrenia: One Name, Many Different Manifestations

Schizophrenia is a disabling condition impacting approximately 1% of the worldwide population. Symptoms include positive symptoms (eg, hallucinations, delusions), negative symptoms (eg, avolition, anhedonia), and cognitive impairment. There are likely many different environmental and pathophysiologic etiologies involving distinct neurotransmitters and neurocircuits. Pharmacologic treatment at present consists of dopamine receptor antagonists, which are reasonably effective at treating positive symptoms, but less effective at treating cognitive and negative symptoms. Nondopaminergic medications targeting alternative receptors are under investigation. Supportive psychosocial treatments can work in tandem with antipsychotic medications and optimize patient care.

Association between brain similarity to severe mental illnesses and comorbid cerebral, physical, and cognitive impairments

Severe mental illnesses (SMIs) are often associated with compromised brain health, physical comorbidities, and cognitive deficits, but it is incompletely understood whether these comorbidities are intrinsic to SMI pathophysiology or secondary to having SMIs. We tested the hypothesis that cerebral, cardiometabolic, and cognitive impairments commonly observed in SMIs can be observed in non-psychiatric individuals with SMI-like brain patterns of deviation as seen on magnetic resonance imaging. 22,883 participants free of common neuropsychiatric conditions from the UK Biobank (age = 63.4 ± 7.5 years, range = 45-82 years, 50.9% female) were split into discovery and replication samples. The regional vulnerability index (RVI) was used to quantify each participant's respective brain similarity to meta-analytical patterns of schizophrenia spectrum disorder, bipolar disorder, and major depressive disorder in gray matter thickness, subcortical gray matter volume, and white matter integrity. Cluster analysis revealed five clusters with distinct RVI profiles. Compared with a cluster with no RVI elevation, a cluster with RVI elevation across all SMIs and brain structures showed significantly higher volume of white matter hyperintensities (Cohen's d = 0.59, p_FDR < 10^-16), poorer cardiovascular (Cohen's d = 0.30, p_FDR < 10^-16) and metabolic (Cohen's d = 0.12, p_FDR = 1.3 × 10^-4) health, and slower speed of information processing (|Cohen's d| = 0.11-0.17, p_FDR = 1.6 × 10^-3-4.6 × 10^-8). This cluster also had significantly higher level of C-reactive protein and alcohol use (Cohen's d = 0.11 and 0.28, p_FDR = 4.1 × 10^-3 and 1.1 × 10^-11). Three other clusters with respective RVI elevation in gray matter thickness, subcortical gray matter volume, and white matter integrity showed intermediate level of white matter hyperintensities, cardiometabolic health, and alcohol use. Our results suggest that cerebral, physical, and cognitive impairments in SMIs may be partly intrinsic via shared pathophysiological pathways with SMI-related brain anatomical changes.

Pragmatic deficits in patients with schizophrenia and right hemisphere damage: A pilot study

BACKGROUND

While pragmatic deficits are well documented in patients with schizophrenia (SCZ) and right hemisphere damage (RHD), there is a paucity of research comparing the pragmatic deficits of these two groups. Do they experience similar cognitive dysfunction or is there a dissociation between the two patient groups?

AIMS

To investigate the nature of pragmatic deficits in these two groups and to gain an understanding of the underlying cognitive mechanisms that might be associated with these deficits to further future investigations.

METHODS & PROCEDURES

A total of 60 participants (15 patients with SCZ; 15 with RHD; 30 (15 + 15) healthy controls (HC) were administered the Bengali Audio-Visual Test-Battery for Assessment of Pragmatic Skills.

OUTCOMES & RESULTS

Both SCZ and RHD patients were found to have significant pragmatic deficits compared with their matched controls. SCZ patients were found to score significantly better than the RHD group in six out of the 10 pragmatic skills when controlled for age and education. Discriminant function analysis was performed and 86.7% of the cases (HC = 100%, SCZ = 73.3% and RHD = 86.7%) were correctly reclassified into their original categories using the test scores.

CONCLUSIONS & IMPLICATIONS

The study suggests that there is heterogeneity in the nature of the pragmatic breakdown within and across patient groups. Therefore, individualized restorative measures targeting the disrupted cognitive mechanism(s) might help elevate pragmatic competence and enhance the social functioning of patients with pragmatic deficits.

WHAT THIS PAPER ADDS

What is already known on the subject Pragmatic deficits are common in adults with cognitive impairments of different etiologies. However, few studies have explored pragmatic deficits across clinical populations. Consequently, very little is known about the nature of pragmatic deficits in patients with schizophrenia and right hemisphere damage. What this paper adds to existing knowledge This work offers preliminary data on pragmatic difficulties in patients with schizophrenia and right hemisphere damage. This study overrides the boundaries of traditional classifications and evaluates pragmatic difficulties in these two clinical populations with reference to the underlying cognitive mechanisms, which might be disrupted. What are the potential or actual clinical implications of this work? The study adds a transdiagnostic perspective suggesting that there might be heterogeneity in pragmatic deficits, both within and across patient groups, and stresses the need for individualized therapy.

Auditory Cortex Thickness Is Associated With N100 Amplitude in Schizophrenia Spectrum Disorders

Background and Hypothesis

The auditory cortex (AC) may play a central role in the pathophysiology of schizophrenia and auditory hallucinations (AH). Previous schizophrenia studies report thinner AC and impaired AC function, as indicated by decreased N100 amplitude of the auditory evoked potential. However, whether these structural and functional alterations link to AH in schizophrenia remain poorly understood.

Study Design

Patients with a schizophrenia spectrum disorder (SCZspect), including patients with a lifetime experience of AH (AH+), without (AH-), and healthy controls underwent magnetic resonance imaging (39 SCZspect, 22 AH+, 17 AH-, and 146 HC) and electroencephalography (33 SCZspect, 17 AH+, 16 AH-, and 144 HC). Cortical thickness of the primary (AC1, Heschl's gyrus) and secondary (AC2, Heschl's sulcus, and the planum temporale) AC was compared between SCZspect and controls and between AH+, AH-, and controls. To examine if the association between AC thickness and N100 amplitude differed between groups, we used regression models with interaction terms.

Study Results

N100 amplitude was nominally smaller in SCZspect (P = .03, d = 0.42) and in AH- (P = .020, d = 0.61), while AC2 was nominally thinner in AH+ (P = .02, d = 0.53) compared with controls. AC1 thickness was positively associated with N100 amplitude in SCZspect (t = 2.56, P = .016) and AH- (t = 3.18, P = .008), while AC2 thickness was positively associated with N100 amplitude in SCZspect (t = 2.37, P = .024) and in AH+ (t = 2.68, P = .019).

Conclusions

The novel findings of positive associations between AC thickness and N100 amplitude in SCZspect, suggest that a common neural substrate may underlie AC thickness and N100 amplitude alterations.

SARS-CoV-2 (COVID-19) as a possible risk factor for neurodevelopmental disorders

Pregnant women constitute one of the most vulnerable populations to be affected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, the cause of coronavirus disease 2019. SARS-CoV-2 infection during pregnancy could negatively impact fetal brain development via multiple mechanisms. Accumulating evidence indicates that mother to fetus transmission of SARS-CoV-2 does occur, albeit rarely. When it does occur, there is a potential for neuroinvasion via immune cells, retrograde axonal transport, and olfactory bulb and lymphatic pathways. In the absence of maternal to fetal transmission, there is still the potential for negative neurodevelopmental outcomes as a consequence of disrupted placental development and function leading to preeclampsia, preterm birth, and intrauterine growth restriction. In addition, maternal immune activation may lead to hypomyelination, microglial activation, white matter damage, and reduced neurogenesis in the developing fetus. Moreover, maternal immune activation can disrupt the maternal or fetal hypothalamic-pituitary-adrenal (HPA) axis leading to altered neurodevelopment. Finally, pro-inflammatory cytokines can potentially alter epigenetic processes within the developing brain. In this review, we address each of these potential mechanisms. We propose that SARS-CoV-2 could lead to neurodevelopmental disorders in a subset of pregnant women and that long-term studies are warranted.

Closing the life-cycle of normative modeling using federated hierarchical Bayesian regression

Clinical neuroimaging data availability has grown substantially in the last decade, providing the potential for studying heterogeneity in clinical cohorts on a previously unprecedented scale. Normative modeling is an emerging statistical tool for dissecting heterogeneity in complex brain disorders. However, its application remains technically challenging due to medical data privacy issues and difficulties in dealing with nuisance variation, such as the variability in the image acquisition process. Here, we approach the problem of estimating a reference normative model across a massive population using a massive multi-center neuroimaging dataset. To this end, we introduce a federated probabilistic framework using hierarchical Bayesian regression (HBR) to complete the life-cycle of normative modeling. The proposed model provides the possibilities to learn, update, and adapt the model parameters on decentralized neuroimaging data. Our experimental results confirm the superiority of HBR in deriving more accurate normative ranges on large multi-site neuroimaging datasets compared to the current standard methods. In addition, our approach provides the possibility to recalibrate and reuse the learned model on local datasets and even on datasets with very small sample sizes. The proposed method will facilitate applications of normative modeling as a medical tool for screening the biological deviations in individuals affected by complex illnesses such as mental disorders.

Glutamatergic dysfunction in Schizophrenia

The NMDA-R hypofunction model of schizophrenia started with the clinical observation of the precipitation of psychotic symptoms in patients with schizophrenia exposed to PCP or ketamine. Healthy volunteers exposed to acute low doses of ketamine experienced mild psychosis but also negative and cognitive type symptoms reminiscent of the full clinical picture of schizophrenia. In rodents, acute systemic ketamine resulted in a paradoxical increase in extracellular frontal glutamate as well as of dopamine. Similar increase in prefrontal glutamate was documented with acute ketamine in healthy volunteers with 1H-MRS. Furthermore, sub-chronic low dose PCP lead to reductions in frontal dendritic tree density in rodents. In post-mortem ultrastructural studies in schizophrenia, a broad reduction in dendritic complexity and somal volume of pyramidal cells has been repeatedly described. This most likely accounts for the broad, subtle progressive cortical thinning described with MRI in- vivo. Additionally, prefrontal reductions in the obligatory GluN1 subunit of the NMDA-R has been repeatedly found in post-mortem tissue. The vast 1H-MRS literature in schizophrenia has documented trait-like small increases in glutamate concentrations in striatum very early in the illness, before antipsychotic treatment (the same structure where increased pre-synaptic release of dopamine has been reported with PET). The more recent genetic literature has reliably detected very small risk effects for common variants involving several glutamate-related genes. The pharmacological literature has followed two main tracks, directly informed by the NMDA-R hypo model: agonism at the glycine site (as mostly add-on studies targeting negative and cognitive symptoms); and pre-synaptic modulation of glutamatergic release (as single agents for acute psychosis). Unfortunately, both approaches have failed so far. There is little doubt that brain glutamatergic abnormalities are present in schizophrenia and that some of these are related to the etiology of the illness. The genetic literature directly supports a non- specific etiological role for glutamatergic dysfunction. Whether NMDA-R hypofunction as a specific mechanism accounts for any important component of the illness is still not evident. However, a glutamatergic model still has heuristic value to guide future research in schizophrenia. New tools to jointly examine brain glutamatergic, GABA-ergic and dopaminergic systems in-vivo, early in the illness, may lay the ground for a next generation of clinical trials that go beyond dopamine D2 blockade.

Anxiety symptoms and puberty interactively predict lower cingulum microstructure in preadolescent Latina girls

Preadolescence is a period of increased vulnerability for anxiety, especially among Latina girls. Reduced microstructure (fractional anisotropy; FA) of white matter tracts between limbic and prefrontal regions may underlie regulatory impairments in anxiety. However, developmental research on the association between anxiety and white matter microstructure is mixed, possibly due to interactive influences with puberty. In a sample of 39 Latina girls (8-13 years), we tested whether pubertal stage moderated the association between parent- and child-reported anxiety symptoms and FA in the cingulum and uncinate fasciculus. Parent- but not child-reported anxiety symptoms predicted lower cingulum FA, and this effect was moderated by pubertal stage, such that this association was only significant for prepubertal girls. Neither anxiety nor pubertal stage predicted uncinate fasciculus FA. These findings suggest that anxiety is associated with disruptions in girls' cingulum white matter microstructure and that this relationship undergoes maturational changes during puberty.