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

Anomalous brain gyrification patterns in major psychiatric disorders: a systematic review and transdiagnostic integration

Anomalous patterns of brain gyrification have been reported in major psychiatric disorders, presumably reflecting their neurodevelopmental pathology. However, previous reports presented conflicting results of patients having hyper-, hypo-, or normal gyrification patterns and lacking in transdiagnostic consideration. In this article, we systematically review previous magnetic resonance imaging studies of brain gyrification in schizophrenia, bipolar disorder, major depressive disorder, and autism spectrum disorder at varying illness stages, highlighting the gyral pattern trajectory for each disorder. Patients with each psychiatric disorder may exhibit deviated primary gyri formation under neurodevelopmental genetic control in their fetal life and infancy, and then exhibit higher-order gyral changes due to mechanical stress from active brain changes (e.g., progressive reduction of gray matter volume and white matter integrity) thereafter, representing diversely altered pattern trajectories from those of healthy controls. Based on the patterns of local connectivity and changes in neurodevelopmental gene expression in major psychiatric disorders, we propose an overarching model that spans the diagnoses to explain how deviated gyral pattern trajectories map onto clinical manifestations (e.g., psychosis, mood dysregulation, and cognitive impairments), focusing on the common and distinct gyral pattern changes across the disorders in addition to their correlations with specific clinical features. This comprehensive understanding of the role of brain gyrification pattern on the pathophysiology may help to optimize the prediction and diagnosis of psychiatric disorders using objective biomarkers, as well as provide a novel nosology informed by neural circuits beyond the current descriptive diagnostics.

Sparse deep neural networks on imaging genetics for schizophrenia case-control classification

Deep learning methods hold strong promise for identifying biomarkers for clinical application. However, current approaches for psychiatric classification or prediction do not allow direct interpretation of original features. In the present study, we introduce a sparse deep neural network (DNN) approach to identify sparse and interpretable features for schizophrenia (SZ) case–control classification. An L₀‐norm regularization is implemented on the input layer of the network for sparse feature selection, which can later be interpreted based on importance weights. We applied the proposed approach on a large multi‐study cohort with gray matter volume (GMV) and single nucleotide polymorphism (SNP) data for SZ classification. A total of 634 individuals served as training samples, and the classification model was evaluated for generalizability on three independent datasets of different scanning protocols (N = 394, 255, and 160, respectively). We examined the classification power of pure GMV features, as well as combined GMV and SNP features. Empirical experiments demonstrated that sparse DNN slightly outperformed independent component analysis + support vector machine (ICA + SVM) framework, and more effectively fused GMV and SNP features for SZ discrimination, with an average error rate of 28.98% on external data. The importance weights suggested that the DNN model prioritized to select frontal and superior temporal gyrus for SZ classification with high sparsity, with parietal regions further included with lower sparsity, echoing previous literature. The results validate the application of the proposed approach to SZ classification, and promise extended utility on other data modalities and traits which ultimately may result in clinically useful tools.

Brain Magnetic Resonance Imaging Phenome-Wide Association Study With Metal Transporter Gene SLC39A8

The SLC39A8 gene encodes a divalent metal transporter, ZIP8. SLC39A8 is associated with pleiotropic effects across multiple tissues, including the brain. We determine the different brain magnetic resonance imaging (MRI) phenotypes associated with SLC39A8. We used a phenome-wide association study approach followed by joint and conditional association analysis. Using the summary statistics datasets from a brain MRI genome-wide association study on adult United Kingdom (UK) Biobank participants, we systematically selected all brain MRI phenotypes associated with single-nucleotide polymorphisms (SNPs) within 500 kb of the SLC39A8 genetic locus. For all significant brain MRI phenotypes, we used GCTA-COJO to determine the number of independent association signals and identify index SNPs for each brain MRI phenotype. Linkage equilibrium for brain phenotypes with multiple independent signals was confirmed by LDpair. We identified 24 brain MRI phenotypes that vary due to MRI type and brain region and contain a SNP associated with the SLC39A8 locus. Missense ZIP8 polymorphism rs13107325 was associated with 22 brain MRI phenotypes. Rare ZIP8 variants present in a published UK Biobank dataset are associated with 6 brain MRI phenotypes also linked to rs13107325. Among the 24 datasets, an additional 4 association signals were identified by GCTA-COJO and confirmed to be in linkage equilibrium with rs13107325 using LDpair. These additional association signals represent new probable causative SNPs in addition to rs13107325. This study provides leads into how genetic variation in SLC39A8, a trace mineral transport gene, is linked to brain structure differences and may affect brain development and nervous system function.

Enrichment of Disease-Associated Genes in Cortical Areas Defined by Transcriptome-Based Parcellation

BACKGROUND

Parcellation of the cerebral cortex serves the investigation of the emergence of uniquely human brain functions and disorders. Transcriptome data enable the characterization of the molecular properties of cortical areas in unprecedented detail. Previously, we predicted the expression of 18,686 genes in the entire human brain based on microarray data. Here, we employed these data to parcellate the cortex and study the regional enrichment of disease-associated genes.

METHODS

We performed agglomerative hierarchical clustering based on normalized transcriptome data to delineate areas with distinct gene expression profiles. Subsequently, we tested these profiles for the enrichment of gene sets associated with brain disorders by genome-wide association studies and expert-curated databases using gene set enrichment analysis.

RESULTS

Transcriptome-based parcellation identified borders in line with major anatomical landmarks and the functional differentiation of primary motor, somatosensory, visual, and auditory areas. Gene set enrichment analysis based on curated databases suggested new roles of specific areas in psychiatric and neurological disorders while reproducing well-established links for movement and neurodegenerative disorders, for example, amyotrophic lateral sclerosis (motor cortex) and Alzheimer's disease (entorhinal cortex). Meanwhile, gene sets derived from genome-wide association studies on psychiatric disorders exhibited similar enrichment patterns driven by pleiotropic genes expressed in the posterior fusiform gyrus and inferior parietal lobule.

CONCLUSIONS

The identified enrichment patterns suggest the vulnerability of specific cortical areas to various influences that might alter the risk of developing one or several brain disorders. For several diseases, specific genes were highlighted, which could lead to the discovery of novel disease mechanisms and urgently needed treatments.

Association between complement component 4A expression, cognitive performance and brain imaging measures in UK Biobank

Abstract.

BACKGROUND

Altered expression of the complement component C4A gene is a known risk factor for schizophrenia. Further, predicted brain C4A expression has also been associated with memory function highlighting that altered C4A expression in the brain may be relevant for cognitive and behavioral traits.

METHODS

We obtained genetic information and performance measures on seven cognitive tasks for up to 329 773 individuals from the UK Biobank, as well as brain imaging data for a subset of 33 003 participants. Direct genotypes for variants (n = 3213) within the major histocompatibility complex region were used to impute C4 structural variation, from which predicted expression of the C4A and C4B genes in human brain tissue were predicted. We investigated if predicted brain C4A or C4B expression were associated with cognitive performance and brain imaging measures using linear regression analyses.

RESULTS

We identified significant negative associations between predicted C4A expression and performance on select cognitive tests, and significant associations with MRI-based cortical thickness and surface area in select regions. Finally, we observed significant inconsistent partial mediation of the effects of predicted C4A expression on cognitive performance, by specific brain structure measures.

CONCLUSIONS

These results demonstrate that the C4 risk locus is associated with the central endophenotypes of cognitive performance and brain morphology, even when considered independently of other genetic risk factors and in individuals without mental or neurological disorders.

The clinical relevance of gray matter atrophy and microstructural brain changes across the psychosis continuum

Patients with psychotic spectrum disorders (PSD) exhibit similar patterns of atrophy and microstructural changes that may be associated with common symptomatology (e.g., symptom burden and/or cognitive impairment). Gray matter concentration values (proxy for atrophy), fractional anisotropy (FA), mean diffusivity (MD), intracellular neurite density (Vic) and isotropic diffusion volume (Viso) measures were therefore compared in 150 PSD (schizophrenia, schizoaffective disorder, and bipolar disorder Type I) and 63 healthy controls (HC). Additional analyses evaluated whether regions showing atrophy and/or microstructure abnormalities were better explained by DSM diagnoses, symptom burden or cognitive dysfunction. PSD exhibited increased atrophy within bilateral medial temporal lobes and subcortical structures. Gray matter along the left lateral sulcus showed evidence of increased atrophy and MD. Increased MD was also observed in homotopic fronto-temporal regions, suggesting it may serve as a precursor to atrophic changes. Global cognitive dysfunction, rather than DSM diagnoses or psychotic symptom burden, was the best predictor of increased gray matter MD. Regions of decreased FA (i.e., left frontal gray and white matter) and Vic (i.e., frontal and temporal regions and along central sulcus) were also observed for PSD, but were neither spatially concurrent with atrophic regions nor associated with clinical symptoms. Evidence of expanding microstructural spaces in gray matter demonstrated the greatest spatial overlap with current and potentially future regions of atrophy, and was associated with cognitive deficits. These results suggest that this particular structural abnormality could potentially underlie global cognitive impairment that spans traditional diagnostic categories.

The temporal pole: From anatomy to function-A literature appraisal

Historically, the anterior part of the temporal lobe was labelled as a unique structure named Brain Area 38 by Brodmann or Temporopolar Area TG by Von Economo, but its functions were unknown at that time. Later on, a few studies proposed to divide the temporal pole in several different subparts, based on distinct cytoarchitectural structure or connectivity patterns, while a still growing number of studies have associated the temporal pole with many cognitive functions. In this review, we provide an overview of the temporal pole anatomical and histological structure and its various functions. We performed a literature review of articles published prior to September 30, 2020 that included 112 articles. The temporal pole has thereby been associated with several high-level cognitive processes: visual processing for complex objects and face recognition, autobiographic memory, naming and word-object labelling, semantic processing in all modalities, and socio-emotional processing, as demonstrated in healthy subjects and in patients with neurological or psychiatric diseases, especially in the field of neurodegenerative disorders. A good knowledge of those functions and the symptoms associated with temporal pole lesions or dysfunctions is helpful to identify these diseases, whose diagnosis may otherwise be difficult.

Personalized Estimates of Brain Structural Variability in Individuals With Early Psychosis

BACKGROUND

Early psychosis in first-episode psychosis (FEP) and clinical high-risk (CHR) individuals has been associated with alterations in mean regional measures of brain morphology. Examination of variability in brain morphology could assist in quantifying the degree of brain structural heterogeneity in clinical relative to healthy control (HC) samples.

METHODS

Structural magnetic resonance imaging data were obtained from CHR (n = 71), FEP (n = 72), and HC individuals (n = 55). Regional brain variability in cortical thickness (CT), surface area (SA), and subcortical volume (SV) was assessed with the coefficient of variation (CV). Furthermore, the person-based similarity index (PBSI) was employed to quantify the similarity of CT, SA, and SV profile of each individual to others within the same diagnostic group. Normative modeling of the PBSI-CT, PBSI-SA, and PBSI-SV was used to identify CHR and FEP individuals whose scores deviated markedly from those of the healthy individuals.

RESULTS

There was no effect of diagnosis on the CV for any regional measure (P > .38). CHR and FEP individuals differed significantly from the HC group in terms of PBSI-CT (P < .0001), PBSI-SA (P < .0001), and PBSI-SV (P = .01). In the clinical groups, normative modeling identified 32 (22%) individuals with deviant PBSI-CT, 12 (8.4%) with deviant PBSI-SA, and 21 (15%) with deviant PBSI-SV; differences of small effect size indicated that individuals with deviant PBSI scores had lower IQ and higher psychopathology.

CONCLUSIONS

Examination of brain structural variability in early psychosis indicated heterogeneity at the level of individual profiles and encourages further large-scale examination to identify individuals that deviate markedly from normative reference data.

Pattern classification as decision support tool in antipsychotic treatment algorithms

Pattern classification aims to establish a new approach in personalized treatment. The scope is to tailor treatment on individual characteristics during all phases of care including prevention, diagnosis, treatment, and clinical outcome. In psychotic disorders, this need results from the fact that a third of patients with psychotic symptoms do not respond to antipsychotic treatment and are described as having treatment-resistant disorders. This, in addition to the high variability of treatment responses among patients, enhances the need of applying advanced classification algorithms to identify antipsychotic treatment patterns. This review comprehensively summarizes advancements and challenges of pattern classification in antipsychotic treatment response to date and aims to introduce clinicians and researchers to the challenges of including pattern classification into antipsychotic treatment decision algorithms.

Effects of genomic copy number variants penetrant for schizophrenia on cortical thickness and surface area in healthy individuals: analysis of the UK Biobank

BACKGROUND

Schizophrenia is a highly heritable disorder with undetermined neurobiological causes. Understanding the impact on brain anatomy of carrying genetic risk for the disorder will contribute to uncovering its neurobiological underpinnings.

AIMS

To examine the effect of rare copy number variants (CNVs) associated with schizophrenia on brain cortical anatomy in a sample of unaffected participants from the UK Biobank.

METHOD

We used regression analyses to compare cortical thickness and surface area (total and across gyri) between 120 unaffected carriers of rare CNVs associated with schizophrenia and 16 670 participants without any pathogenic CNV. A measure of cortical thickness and surface area covariance across gyri was also compared between groups.

RESULTS

Carrier status was associated with reduced surface area (β = -0.020 mm2, P < 0.001) and less robustly with increased cortical thickness (β = 0.015 mm, P = 0.035), and with increased covariance in thickness (carriers z = 0.31 v. non-carriers z = 0.22, P < 0.0005). Associations were mainly present in frontal and parietal areas and driven by a limited number of rare risk alleles included in our analyses (mainly 15q11.2 deletion for surface area and 16p13.11 duplication for thickness covariance).

CONCLUSIONS

Results for surface area conformed with previous clinical findings, supporting surface area reductions as an indicator of genetic liability for schizophrenia. Results for cortical thickness, though, argued against its validity as a potential risk marker. Increased structural thickness covariance across gyri also appears related to risk for schizophrenia. The heterogeneity found across the effects of rare risk alleles suggests potential different neurobiological gateways into schizophrenia's phenotype.

Structural brain abnormalities in schizophrenia in adverse environments: examining the effect of poverty and violence in six Latin American cities

BACKGROUND

Social and environmental factors such as poverty or violence modulate the risk and course of schizophrenia. However, how they affect the brain in patients with psychosis remains unclear.

AIMS

We studied how environmental factors are related to brain structure in patients with schizophrenia and controls in Latin America, where these factors are large and unequally distributed.

METHOD

This is a multicentre study of magnetic resonance imaging in patients with schizophrenia and controls from six Latin American cities. Total and voxel-level grey matter volumes, and their relationship with neighbourhood characteristics such as average income and homicide rates, were analysed with a general linear model.

RESULTS

A total of 334 patients with schizophrenia and 262 controls were included. Income was differentially related to total grey matter volume in both groups (P = 0.006). Controls showed a positive correlation between total grey matter volume and income (R = 0.14, P = 0.02). Surprisingly, this relationship was not present in patients with schizophrenia (R = -0.076, P = 0.17). Voxel-level analysis confirmed that this interaction was widespread across the cortex. After adjusting for global brain changes, income was positively related to prefrontal cortex volumes only in controls. Conversely, the hippocampus in patients with schizophrenia, but not in controls, was relatively larger in affluent environments. There was no significant correlation between environmental violence and brain structure.

CONCLUSIONS

Our results highlight the interplay between environment, particularly poverty, and individual characteristics in psychosis. This is particularly important for harsh environments such as low- and middle-income countries, where potentially less brain vulnerability (less grey matter loss) is sufficient to become unwell in adverse (poor) environments.

Psychiatric neuroimaging research in Brazil: historical overview, current challenges, and future opportunities

The last four decades have witnessed tremendous growth in research studies applying neuroimaging methods to evaluate pathophysiological and treatment aspects of psychiatric disorders around the world. This article provides a brief history of psychiatric neuroimaging research in Brazil, including quantitative information about the growth of this field in the country over the past 20 years. Also described are the various methodologies used, the wealth of scientific questions investigated, and the strength of international collaborations established. Finally, examples of the many methodological advances that have emerged in the field of in vivo neuroimaging are provided, with discussion of the challenges faced by psychiatric research groups in Brazil, a country of limited resources, to continue incorporating such innovations to generate novel scientific data of local and global relevance.

Multiple overlapping dynamic patterns of the visual sensory network in schizophrenia

Although visual processing impairments have been explored in schizophrenia (SZ), their underlying neurobiology of the visual processing impairments has not been widely studied. Also, while some research has hinted at differences in information transfer and flow in SZ, there are few investigations of the dynamics of functional connectivity within visual networks. In this study, we analyzed resting-state fMRI data of the visual sensory network (VSN) in 160 healthy control (HC) subjects and 151 SZ subjects. We estimated 9 independent components within the VSN. Then, we calculated the dynamic functional network connectivity (dFNC) using the Pearson correlation. Next, using k-means clustering, we partitioned the dFNCs into five distinct states, and then we calculated the portion of time each subject spent in each state, which we termed the occupancy rate (OCR). Using OCR, we compared HC with SZ subjects and investigated the link between OCR and visual learning in SZ subjects. Besides, we compared the VSN functional connectivity of SZ and HC subjects in each state. We found that this network is indeed highly dynamic. Each state represents a unique connectivity pattern of fluctuations in VSN FNC, and all states showed significant disruption in SZ. Overall, HC showed stronger connectivity within the VSN in states. SZ subjects spent more time in a state in which the connectivity between the middle temporal gyrus and other regions of VNS is highly negative. Besides, OCR in a state with strong positive connectivity between the middle temporal gyrus and other regions correlated significantly with visual learning scores in SZ.

Independent components of human brain morphology

Quantification of brain morphology has become an important cornerstone in understanding brain structure. Measures of cortical morphology such as thickness and surface area are frequently used to compare groups of subjects or characterise longitudinal changes. However, such measures are often treated as independent from each other. A recently described scaling law, derived from a statistical physics model of cortical folding, demonstrates that there is a tight covariance between three commonly used cortical morphology measures: cortical thickness, total surface area, and exposed surface area. We show that assuming the independence of cortical morphology measures can hide features and potentially lead to misinterpretations. Using the scaling law, we account for the covariance between cortical morphology measures and derive novel independent measures of cortical morphology. By applying these new measures, we show that new information can be gained; in our example we show that distinct morphological alterations underlie healthy ageing compared to temporal lobe epilepsy, even on the coarse level of a whole hemisphere. We thus provide a conceptual framework for characterising cortical morphology in a statistically valid and interpretable manner, based on theoretical reasoning about the shape of the cortex.

N-methyl-D-aspartate Receptor Antibody and White Matter Deficits in Schizophrenia Treatment-Resistance

Insufficient or lack of response to antipsychotic medications in some patients with schizophrenia is a major challenge in psychiatry, but the underlying mechanisms remain unclear. Two seemingly unrelated observations, cerebral white matter and N-methyl-D-aspartate receptor (NMDAR) hypofunction, have been linked to treatment-resistant schizophrenia (TRS). As NMDARs are critical to axonal myelination and signal transduction, we hypothesized that NMDAR antibody (Ab), when present in schizophrenia, may impair NMDAR functions and white matter microstructures, contributing to TRS. In this study, 50 patients with TRS, 45 patients with nontreatment-resistant schizophrenia (NTRS), 53 patients with schizophrenia at treatment initiation schizophrenia (TIS), and 90 healthy controls were enrolled. Serum NMDAR Ab levels and white matter diffusion tensor imaging fractional anisotropy (FA) were assessed. The white matter specificity effects by NMDAR Ab were assessed by comparing with effects on cortical and subcortical gray matter. Serum NMDAR Ab levels of the TRS were significantly higher than those of the NTRS (P = .035). In patients with TRS, higher NMDAR Ab levels were significantly associated with reduced whole-brain average FA (r = -.37; P = .026), with the strongest effect at the genu of corpus callosum (r = -.50; P = .0021, significant after correction for multiple comparisons). Conversely, there was no significant correlation between whole-brain or regional cortical thickness or any subcortical gray matter structural volume and NMDAR Ab levels in TRS. Our finding highlights a potential NMDAR mechanism on white matter microstructure impairment in schizophrenia that may contribute to their treatment resistance to antipsychotic medications.

Divergent relationship between brain structure and cognitive functioning in patients with prominent negative symptomatology

Investigating commonalities in underlying pathology of cognitive dysfunction and negative symptoms in schizophrenia is important, as both are core features of the disorder and linked to brain structure abnormalities. We aimed to explore the relationship between cognition, negative symptoms and brain structure in schizophrenia. A total of 225 patients with Schizophrenia spectrum disorder and 283 healthy controls from the Norwegian Thematically Organized Psychosis (TOP) cohort were included in this study. Patients were categorized into four patient subgroups based on severity of negative symptoms: no-negative- (NNS), threshold-negative- (TNS), moderate-negative- (MNS), and prominent-negative (PNS) subgroups. MRI measures of brain volume, mean cortical thickness and surface area from pre-selected brain regions were tested for relationships with general cognitive ability and negative symptom subgroups. Positive associations were found between brain volume, thickness, surface area and cognition in the dorsolateral prefrontal cortex (DLPFC), orbitofrontal cortex (OFC), fusiform gyrus (FG) and the left anterior cingulate cortex (ACC), but with no differences between subgroups. In the PNS subgroup, cognition was conversely negatively associated with brain volume in the left ACC. These results indicate that patients with prominent negative symptoms have different associations between cognition and brain structure in the left ACC, which may point to abnormal neurodevelopment.

Comparison of regional brain deficit patterns in common psychiatric and neurological disorders as revealed by big data

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RVI for MDD and AD was derived based on large meta-analytical findings.

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RVI-MDD and AD were significantly elevated in UKBB subjects with respective illnesses.

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There was no elevation of RVI-MDD in subjects with AD or RVI-AD in subjects with MDD.

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RVI captures neuroanatomic deviation patterns.

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RVI is a useful biomarker for assessing similarity to neuropsychiatric illnesses.

Neurological and psychiatric illnesses are associated with regional brain deficit patterns that bear unique signatures and capture illness-specific characteristics. The Regional Vulnerability Index (RVI) was developed to quantify brain similarity by comparing individual white matter microstructure, cortical gray matter thickness and subcortical gray matter structural volume measures with neuroanatomical deficit patterns derived from large-scale meta-analytic studies. We tested the specificity of the RVI approach for major depressive disorder (MDD) and Alzheimer’s disease (AD) in a large epidemiological sample of UK Biobank (UKBB) participants (N = 19,393; 9138 M/10,255F; age = 64.8 ± 7.4 years). Compared to controls free of neuropsychiatric disorders, participants with MDD (N = 2,248; 805 M/1443F; age = 63.4 ± 7.4) had significantly higher RVI-MDD values (t = 5.6, p = 1·10⁻⁸), but showed no detectable difference in RVI-AD (t = 2.0, p = 0.10). Subjects with dementia (N = 7; 4 M/3F; age = 68.6 ± 8.6 years) showed significant elevation in RVI-AD (t = 4.2, p = 3·10⁻⁵) but not RVI-MDD (t = 2.1, p = 0.10) compared to controls. Even within affective illnesses, participants with bipolar disorder (N = 54) and anxiety disorder (N = 773) showed no significant elevation in whole-brain RVI-MDD. Participants with Parkinson’s disease (N = 37) showed elevation in RVI-AD (t = 2.4, p = 0.01) while subjects with stroke (N = 247) showed no such elevation (t = 1.1, p = 0.3). In summary, we demonstrated elevation in RVI-MDD and RVI-AD measures in the respective illnesses with strong replicability that is relatively specific to the respective diagnoses. These neuroanatomic deviation patterns offer a useful biomarker for population-wide assessments of similarity to neuropsychiatric illnesses.

Grey and white matter associations of psychotic-like experiences in a general population sample (UK Biobank)

There has been a substantial amount of research reporting the neuroanatomical associations of psychotic symptoms in people with schizophrenia. Comparatively little attention has been paid to the neuroimaging correlates of subclinical psychotic symptoms, so-called "psychotic-like experiences" (PLEs), within large healthy populations. PLEs are relatively common in the general population (7-13%), can be distressing and negatively affect health. This study therefore examined gray and white matter associations of four different PLEs (auditory or visual PLEs, and delusional ideas about conspiracies or communications) in subjects of the UK Biobank study with neuroimaging data (N = 21,390, mean age = 63 years). We tested for associations between any PLE (N = 768) and individual PLEs with gray and white matter brain structures, controlling for sex, age, intracranial volume, scanning site, and position in the scanner. Individuals that reported having experienced auditory hallucinations (N = 272) were found to have smaller volumes of the caudate, putamen, and accumbens (β = -0.115-0.134, pcorrected = 0.048-0.036), and reduced temporal lobe volume (β = -0.017, pcorrected = 0.047) compared to those that did not. People who indicated that they had ever believed in unreal conspiracies (N = 111) had a larger volume of the left amygdala (β = 0.023, pcorrected = 0.038). Individuals that reported a history of visual PLEs (N = 435) were found to have reduced white matter microstructure of the forceps major (β = -0.029, pcorrected = 0.009), an effect that was more marked in participants who reported PLEs as distressing. These associations were not accounted for by diagnoses of psychotic or depressive illness, nor the known risk factors for psychotic symptoms of childhood adversity or cannabis use. These findings suggest altered regional gray matter volumes and white matter microstructure in association with PLEs in the general population. They further suggest that these alterations may appear more frequently with the presentation of different psychotic symptoms in the absence of clinically diagnosed psychotic disorders.

On the relation of white matter brain abnormalities and the asociality symptoms in schizophrenia outpatients - a DTI study

Recent MRI studies have shown that abnormal functional connections in schizophrenia coexist with subtle changes in the structure of axons in the brain. However, there is a discrepancy in the literature concerning the relationship between white matter abnormalities and the occurrence of negative psychopathological symptoms. In the present study, we investigate the relationship between the altered white matter structure and specific psychopathology symptoms, i.e., subscales of Positive and Negative Syndrome Scale (PANSS) and Brief Negative Symptoms Scale (BNSS) in a sample of schizophrenia outpatients. For investigation on white matter abnormalities in schizophrenia, the diffusion tensor imaging analysis of between-group differences in main diffusion parameters by tract-based spatial statistics was conducted on schizophrenia outpatients and healthy controls. Hence, the correlation of PANSS and BNSS psychopathology subscales in the clinical group with fractional anisotropy was analyzed in the 17 selected cortical regions of interest. Presented between-group results revealed widespread loss of white matter integrity located across the brain in schizophrenia outpatients. Results on the white matter relationship with psychopathology revealed the negative correlation between fractional anisotropy in the left orbital prefrontal cortex, right Heschl's gyrus, bilateral precuneus and posterior cingulate cortex and the severity of asociality, as assessed with the BNSS. In conclusion, the presented study confirms the previous evidence on the widespread white matter abnormalities in schizophrenia outpatients and indicates the existence of the subtle but specific association between fractional anisotropy in the fronto-temporo-parietal regions with the asociality.

Recent MRI studies have shown that abnormal functional connections in schizophrenia coexist with subtle changes in the structure of axons in the brain. However, there is a discrepancy in the literature concerning the relationship between white matter abnormalities and the occurrence of negative psychopathological symptoms. In the present study, we investigate the relationship between the altered white matter structure and specific psychopathology symptoms, i.e., subscales of Positive and Negative Syndrome Scale (PANSS) and Brief Negative Symptoms Scale (BNSS) in a sample of schizophrenia outpatients. For investigation on white matter abnormalities in schizophrenia, the diffusion tensor imaging analysis of between-group differences in main diffusion parameters by tract-based spatial statistics was conducted on schizophrenia outpatients and healthy controls. Hence, the correlation of PANSS and BNSS psychopathology subscales in the clinical group with fractional anisotropy was analyzed in the 17 selected cortical regions of interest. Presented between-group results revealed widespread loss of white matter integrity located across the brain in schizophrenia outpatients. Results on the white matter relationship with psychopathology revealed the negative correlation between fractional anisotropy in the left orbital prefrontal cortex, right Heschl’s gyrus, bilateral precuneus and posterior cingulate cortex and the severity of asociality, as assessed with the BNSS. In conclusion, the presented study confirms the previous evidence on the widespread white matter abnormalities in schizophrenia outpatients and indicates the existence of the subtle but specific association between fractional anisotropy in the fronto-temporo-parietal regions with the asociality.

Distress severity in perceptual anomalies moderates the relationship between prefrontal brain structure and psychosis proneness in nonclinical individuals

In the general population, psychosis risk phenotypes occur independently of attenuated prodromal syndromes. Neurobiological correlates of vulnerability could help to understand their meaningfulness. Interactions between the occurrence of psychotic-like experiences (PLE) and other psychological factors e.g., distress related to PLE, may distinguish psychosis-prone individuals from those without risk of future psychotic disorder. We aimed to investigate whether (a) correlates of total PLE and distress, and (b) symptom dimension-specific moderation effects exist at the brain structural level in non-help-seeking adults reporting PLE below and above the screening criterion for clinical high-risk (CHR). We obtained T1-weighted whole-brain MRI scans from 104 healthy adults from the community without psychosis CHR states for voxel-based morphometry (VBM). Brain structural associations with PLE and PLE distress were analysed with multiple linear regression models. Moderation of PLE by distress severity of two types of positive symptoms from the Prodromal Questionnaire (PQ-16) screening inventory was explored in regions-of-interest after VBM. Total PQ-16 score was positively associated with grey matter volume (GMV) in prefrontal regions, occipital fusiform and lingual gyri (p < 0.05, FDR peak-level corrected). Overall distress severity and GMV were not associated. Examination of distress severity on the positive symptom dimensions as moderators showed reduced strength of the association between PLE and rSFG volume with increased distress severity for perceptual PLE. In this study, brain structural variation was related to PLE level, but not distress severity, suggesting specificity. In healthy individuals, positive relationships between PLE and prefrontal volumes may indicate protective features, which supports the insufficiency of PLE for the prediction of CHR. Additional indicators of vulnerability, such as distress associated with perceptual PLE, change the positive brain structure relationship. Brain structural findings may strengthen clinical objectives through disentanglement of innocuous and risk-related PLE.

Cognitive Empathy and Longitudinal Changes in Temporo-Parietal Junction Thickness in Schizophrenia

Objective: Deficits in cognitive empathy are well-documented in individuals with schizophrenia and are related to reduced community functioning. The temporoparietal junction (TPJ) is closely linked to cognitive empathy. We compared the relationship between baseline cognitive empathy and changes in TPJ thickness over 24 months between individuals with schizophrenia and healthy controls. Methods: Individuals with schizophrenia (n = 29) and healthy controls (n = 26) completed a cognitive empathy task and underwent structural neuroimaging at baseline and approximately 24 months later. Symmetrized percent change scores were calculated for right and left TPJ, as well as whole-brain volume, and compared between groups. Task accuracy was examined as a predictor of percent change in TPJ thickness and whole-brain volume in each group. Results: Individuals with schizophrenia demonstrated poorer accuracy on the cognitive empathy task (p < 0.001) and thinner TPJ cortex relative to controls at both time points (p = 0.01). In schizophrenia, greater task accuracy was uniquely related to less thinning of the TPJ over time (p = 0.02); task accuracy did not explain changes in left TPJ or whole-brain volume. Among controls, task accuracy did not explain changes in right or left TPJ, or whole-brain volume. Conclusions: Our findings suggest that greater cognitive empathy may explain sustained integrity of the right TPJ in individuals with schizophrenia, suggesting a contributory substrate for the long-term maintenance of this process in psychosis. Cognitive empathy was not related to changes in whole-brain volume, demonstrating the unique role of the TPJ in cognitive empathy.

Longitudinal Structural MRI Findings in Individuals at Genetic and Clinical High Risk for Psychosis: A Systematic Review

Background: Several cross-sectional studies report brain structure differences between healthy volunteers and subjects at genetic or clinical high risk of developing schizophrenia. However, longitudinal studies are important to determine whether altered trajectories of brain development precede psychosis onset. Methods: We conducted a systematic review to determine if brain trajectories differ between (i) those with psychotic experiences (PE), genetic (GHR) or clinical high risk (CHR), compared to healthy volunteers, and (ii) those who transition to psychosis compared to those who do not. Results: Thirty-eight studies measured gray matter and 18 studies measured white matter in 2,473 high risk subjects and 990 healthy volunteers. GHR, CHR, and PE subjects show an accelerated decline in gray matter primarily in temporal, and also frontal, cingulate and parietal cortex. In those who remain symptomatic or transition to psychosis, gray matter loss is more pronounced in these brain regions. White matter volume and fractional anisotropy, which typically increase until early adulthood, did not change or reduced in high risk subjects in the cingulum, thalamic radiation, cerebellum, retrolenticular part of internal capsule, and hippocampal-thalamic tracts. In those who transitioned, white matter volume and fractional anisotropy reduced over time in the inferior and superior fronto-occipital fasciculus, corpus callosum, anterior limb of the internal capsule, superior corona radiate, and calcarine cortex. Conclusion: High risk subjects show deficits in white matter maturation and an accelerated decline in gray matter. Gray matter loss is more pronounced in those who transition to psychosis, but may normalize by early adulthood in remitters.

Neuroanatomical abnormalities in first-episode psychosis across independent samples: a multi-centre mega-analysis

BACKGROUND

Neuroanatomical abnormalities in first-episode psychosis (FEP) tend to be subtle and widespread. The vast majority of previous studies have used small samples, and therefore may have been underpowered. In addition, most studies have examined participants at a single research site, and therefore the results may be specific to the local sample investigated. Consequently, the findings reported in the existing literature are highly heterogeneous. This study aimed to overcome these issues by testing for neuroanatomical abnormalities in individuals with FEP that are expressed consistently across several independent samples.

METHODS

Structural Magnetic Resonance Imaging data were acquired from a total of 572 FEP and 502 age and gender comparable healthy controls at five sites. Voxel-based morphometry was used to investigate differences in grey matter volume (GMV) between the two groups. Statistical inferences were made at p < 0.05 after family-wise error correction for multiple comparisons.

RESULTS

FEP showed a widespread pattern of decreased GMV in fronto-temporal, insular and occipital regions bilaterally; these decreases were not dependent on anti-psychotic medication. The region with the most pronounced decrease - gyrus rectus - was negatively correlated with the severity of positive and negative symptoms.

CONCLUSIONS

This study identified a consistent pattern of fronto-temporal, insular and occipital abnormalities in five independent FEP samples; furthermore, the extent of these alterations is dependent on the severity of symptoms and duration of illness. This provides evidence for reliable neuroanatomical alternations in FEP, expressed above and beyond site-related differences in anti-psychotic medication, scanning parameters and recruitment criteria.

Structural Imaging in OCD

Anatomical imaging in OCD using magnetic resonance imaging (MRI) has been performed since the late 1980s. MRI research was further stimulated with the advent of automated image processing techniques such as voxel-based morphometry (VBM) and surface-based methods (e.g., FreeSurfer) which allow for detailed whole-brain data analyses. Early studies suggesting involvement of corticostriatal circuitry (particularly orbitofrontal cortex and ventral striatum) have been complemented by meta-analyses and pooled analyses indicating additional involvement of posterior brain regions, in particular parietal cortex. Recent large-scale meta-analyses from the ENIGMA consortium have revealed greater pallidum and smaller hippocampus volume in adult OCD, coupled with parietal cortical thinning. Frontal cortical thinning was only observed in medicated patients. Previous reports of symptom dimension-specific alterations were not confirmed. In paediatric OCD, thalamus enlargement has been a consistent finding. Studies investigating white matter volume (VBM) or integrity (using diffusion tensor imaging (DTI)) have shown mixed results, with recent DTI meta-analyses mainly showing involvement of posterior cortical-subcortical tracts in addition to subcortical-prefrontal connections. To which extent these abnormalities are unique to OCD or common to other psychiatric disorders is unclear, as few comparative studies have been performed. Overall, neuroanatomical alterations in OCD appear to be subtle and may vary with time, stressing the need for adequately powered longitudinal studies. Although multivariate approaches using machine learning methodologies have so far been disappointing in distinguishing individual OCD patients from healthy controls, including multimodal data in such analyses may aid in further establishing a neurobiological profile of OCD.

Virtual Histology of Cortical Thickness and Shared Neurobiology in 6 Psychiatric Disorders

IMPORTANCE

Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood.

OBJECTIVE

To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia.

DESIGN, SETTING, AND PARTICIPANTS

Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244.

MAIN OUTCOMES AND MEASURES

Interregional profiles of group difference in cortical thickness between cases and controls.

RESULTS

A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (except for OCD); collectively, gene-expression profiles of the 3 cell types explain between 25% and 54% of variance in interregional profiles of group differences in cortical thickness. Principal component analysis revealed a shared profile of difference in cortical thickness across the 6 disorders (48% variance explained); interregional profile of this principal component 1 was associated with that of the pyramidal-cell gene expression (explaining 56% of interregional variation). Coexpression analyses of these genes revealed 2 clusters: (1) a prenatal cluster enriched with genes involved in neurodevelopmental (axon guidance) processes and (2) a postnatal cluster enriched with genes involved in synaptic activity and plasticity-related processes. These clusters were enriched with genes associated with all 6 psychiatric disorders.

CONCLUSIONS AND RELEVANCE

In this study, shared neurobiologic processes were associated with differences in cortical thickness across multiple psychiatric disorders. These processes implicate a common role of prenatal development and postnatal functioning of the cerebral cortex in these disorders.

Altered cortical thickness development in 22q11.2 deletion syndrome and association with psychotic symptoms

Schizophrenia has been extensively associated with reduced cortical thickness (CT), and its neurodevelopmental origin is increasingly acknowledged. However, the exact timing and extent of alterations occurring in preclinical phases remain unclear. With a high prevalence of psychosis, 22q11.2 deletion syndrome (22q11DS) is a neurogenetic disorder that represents a unique opportunity to examine brain maturation in high-risk individuals. In this study, we quantified trajectories of CT maturation in 22q11DS and examined the association of CT development with the emergence of psychotic symptoms. Longitudinal structural MRI data with 1-6 time points were collected from 324 participants aged 5-35 years (N = 148 22q11DS, N = 176 controls), resulting in a total of 636 scans (N = 334 22q11DS, N = 302 controls). Mixed model regression analyses were used to compare CT trajectories between participants with 22q11DS and controls. Further, CT trajectories were compared between participants with 22q11DS who developed (N = 61, 146 scans), or remained exempt of (N = 47; 98 scans) positive psychotic symptoms during development. Compared to controls, participants with 22q11DS showed widespread increased CT, focal reductions in the posterior cingulate gyrus and superior temporal gyrus (STG), and accelerated cortical thinning during adolescence, mainly in frontotemporal regions. Within 22q11DS, individuals who developed psychotic symptoms showed exacerbated cortical thinning in the right STG. Together, these findings suggest that genetic predisposition for psychosis is associated with increased CT starting from childhood and altered maturational trajectories of CT during adolescence, affecting predominantly frontotemporal regions. In addition, accelerated thinning in the STG may represent an early biomarker associated with the emergence of psychotic symptoms.

Baseline structural and functional magnetic resonance imaging predicts early treatment response in schizophrenia with radiomics strategy

Multimodal neuroimaging features provide opportunities for accurate classification and personalized treatment options in the psychiatric domain. This study aimed to investigate whether brain features predict responses to the overall treatment of schizophrenia at the end of the first or a single hospitalization. Structural and functional magnetic resonance imaging (MRI) data from two independent samples (N = 85 and 63, separately) of schizophrenia patients at baseline were included. After treatment, patients were classified as responders and non-responders. Radiomics features of gray matter morphology and functional connectivity were extracted using Least Absolute Shrinkage and Selection Operator. Support vector machine was used to explore the predictive performance. Prediction models were based on structural features (cortical thickness, surface area, gray matter regional volume, mean curvature, metric distortion, and sulcal depth), functional features (functional connectivity), and combined features. There were 12 features after dimensionality reduction. The structural features involved the right precuneus, cuneus, and inferior parietal lobule. The functional features predominately included inter-hemispheric connectivity. We observed a prediction accuracy of 80.38% (sensitivity: 87.28%; specificity 82.47%) for the model using functional features, and 69.68% (sensitivity: 83.96%; specificity: 72.41%) for the one using structural features. Our model combining both structural and functional features achieved a higher accuracy of 85.03%, with 92.04% responder and 80.23% non-responders to the overall treatment to be correctly predicted. These results highlight the power of structural and functional MRI-derived radiomics features to predict early response to treatment in schizophrenia. Prediction models of the very early treatment response in schizophrenia could augment effective therapeutic strategies.

Antipsychotic ffects on ortical Morphology in chizophrenia and ipolar isorders

Background: Previous studies of atypical antipsychotic effects on cortical structures in schizophrenia (SZ) and bipolar disorder (BD) have findings that vary between the short and long term. In particular, there has not been a study exploring the effects of atypical antipsychotics on age-related cortical structural changes in SZ and BD. This study aimed to determine whether mid- to long-term atypical antipsychotic treatment (mean duration = 20 months) is associated with cortical structural changes and whether age-related cortical structural changes are affected by atypical antipsychotics. Methods: Structural magnetic resonance imaging images were obtained from 445 participants consisting of 88 medicated patients (67 with SZ, 21 with BD), 84 unmedicated patients (50 with SZ, 34 with BD), and 273 healthy controls (HC). Surface-based analyses were employed to detect differences in thickness and area among the three groups. We examined the age-related effects of atypical antipsychotics after excluding the potential effects of illness duration. Results: Significant differences in cortical thickness were observed in the frontal, temporal, parietal, and insular areas and the isthmus of the cingulate gyrus. The medicated group showed greater cortical thinning in these regions than the unmediated group and HC; furthermore, there were age-related differences in the effects of atypical antipsychotics, and these effects did not relate to illness duration. Moreover, cortical thinning was significantly correlated with lower symptom scores and Wisconsin Card Sorting Test (WCST) deficits in patients. After false discovery rate correction, cortical thinning in the right middle temporal gyrus in patients was significantly positively correlated with lower HAMD scores. The unmedicated group showed only greater frontotemporal thickness than the HC group. Conclusion: Mid- to long-term atypical antipsychotic use may adversely affect cortical thickness over the course of treatment and ageing and may also result in worsening cognitive function.

Personalized estimates of morphometric similarity in bipolar disorder and schizophrenia

Bipolar disorder and schizophrenia are associated with brain morphometry alterations. This study investigates inter-individual variability in brain structural profiles, both within diagnostic groups and between patients and healthy individuals. Brain morphometric measures from three independent samples of patients with schizophrenia (n = 168), bipolar disorder (n = 122), and healthy individuals (n = 180) were modeled as single vectors to generated individualized profiles of subcortical volumes and regional cortical thickness. These profiles were then used to compute a person-based similarity index (PBSI) for subcortical volumes and for regional cortical thickness, to quantify the within-group similarity of the morphometric profile of each individual to that of the other participants in the same diagnostic group. There was no effect of diagnosis on the PBSI for subcortical volumes. In contrast, compared to healthy individuals, the PBSI for cortical thickness was lower in patients with schizophrenia (effect size = 0.4, p ≤ 0.0002), but not in patients with bipolar disorder. The results were robust and reproducible across samples. We conclude that disease mechanisms for these disorders produce modest inter-individual variations in brain morphometry that should be considered in future studies attempting to cluster patients in subgroups.

Orbitofrontal-Striatal Structural Alterations Linked to Negative Symptoms at Different Stages of the Schizophrenia Spectrum

Negative symptoms such as anhedonia and apathy are among the most debilitating manifestations of schizophrenia (SZ). Imaging studies have linked these symptoms to morphometric abnormalities in 2 brain regions implicated in reward and motivation: the orbitofrontal cortex (OFC) and striatum. Higher negative symptoms are generally associated with reduced OFC thickness, while higher apathy specifically maps to reduced striatal volume. However, it remains unclear whether these tissue losses are a consequence of chronic illness and its treatment or an underlying phenotypic trait. Here, we use multicentre magnetic resonance imaging data to investigate orbitofrontal-striatal abnormalities across the SZ spectrum from healthy populations with high schizotypy to unmedicated and medicated first-episode psychosis (FEP), and patients with chronic SZ. Putamen, caudate, accumbens volume, and OFC thickness were estimated from T1-weighted images acquired in all 3 diagnostic groups and controls from 4 sites (n = 337). Results were first established in 1 discovery dataset and replicated in 3 independent samples. There was a negative correlation between apathy and putamen/accumbens volume only in healthy individuals with schizotypy; however, medicated patients exhibited larger putamen volume, which appears to be a consequence of antipsychotic medications. The negative association between reduced OFC thickness and total negative symptoms also appeared to vary along the SZ spectrum, being significant only in FEP patients. In schizotypy, there was increased OFC thickness relative to controls. Our findings suggest that negative symptoms are associated with a temporal continuum of orbitofrontal-striatal abnormalities that may predate the occurrence of SZ. Thicker OFC in schizotypy may represent either compensatory or pathological mechanisms prior to the disease onset.

Effects of Antipsychotic Drugs: Cross Talk Between the Nervous and Innate Immune System

Converging lines of evidence suggest that activation of microglia (innate immune cells in the central nervous system [CNS]) is present in a subset of patients with schizophrenia. The extent to which antipsychotic drug treatment contributes to or combats this effect remains unclear. To address this question, we reviewed the literature for evidence that antipsychotic exposure influences brain microglia as indexed by in vivo neuroimaging and post-mortem studies in patients with schizophrenia and experimental animal models. We found no clear evidence from clinical studies for an effect of antipsychotics on either translocator protein (TSPO) radioligand binding (an in vivo neuroimaging measure of putative gliosis) or markers of brain microglia in post-mortem studies. In experimental animals, where drug and illness effects may be differentiated, we also found no clear evidence for consistent effects of antipsychotic drugs on TSPO radioligand binding. By contrast, we found evidence that chronic antipsychotic exposure may influence central microglia density and morphology. However, these effects were dependent on the dose and duration of drug exposure and whether an immune stimulus was present or not. In the latter case, antipsychotics were generally reported to suppress expression of inflammatory cytokines and inducible inflammatory enzymes such as cyclooxygenase and microglia activation. No clear conclusions could be drawn with regard to any effect of antipsychotics on brain microglia from current clinical data. There is evidence to suggest that antipsychotic drugs influence brain microglia in experimental animals, including possible anti-inflammatory actions. However, we lack detailed information on how these drugs influence brain microglia function at the molecular level. The clinical relevance of the animal data with regard to beneficial treatment effects and detrimental side effects of antipsychotic drugs also remains unknown, and further studies are warranted.

Hallucination-Specific structure-function associations in schizophrenia

Combining structural (sMRI) and functional magnetic resonance imaging (fMRI) data in schizophrenia patients with and without auditory hallucinations (9 SZ_AVH, 12 SZ_nAVH), 18 patients with bipolar disorder, and 22 healthy controls, we examined whether cortical thinning was associated with abnormal activity in functional brain networks associated with auditory hallucinations. Language-task fMRI data were combined with mean cortical thickness values from 148 brain regions in a constrained principal component analysis (CPCA) to identify brain structure-function associations predictable from group differences. Two components emerged from the multimodal analysis. The "AVH component" highlighted an association of frontotemporal and cingulate thinning with altered brain activity characteristic of hallucinations among patients with AVH. In contrast, the "Bipolar component" distinguished bipolar patients from healthy controls and linked increased activity in the language network with cortical thinning in the left occipital-temporal lobe. Our findings add to a body of evidence of the biological underpinnings of hallucinations and illustrate a method for multimodal data analysis of structure-function associations in psychiatric illness.

Parahippocampal area three gray matter is reduced in first-episode schizophrenia spectrum: Discovery and replication samples

Early course schizophrenia is associated with reduced gray matter. The specific structures affected first and how deficits impact symptoms and cognition remain unresolved. We used the Human Connectome Project multimodal parcellation (HCP‐MMP) to precisely identify cortical areas and investigate thickness abnormalities in discovery and replication samples of first‐episode schizophrenia spectrum individuals (FESz). In the discovery sample, T1w scans were acquired from 31 FESz and 31 matched healthy controls (HC). Thickness was calculated for 360 regions in Freesurfer. In the replication sample, high‐resolution T1w, T2w, and BOLD‐rest scans were acquired from 23 FESz and 32 HC and processed with HCP protocols. Thickness was calculated for regions significant in the discovery sample. After FDR correction (q < .05), left and right parahippocampal area 3 (PHA3) were significantly thinner in FESz. In the replication sample, bilateral PHA3 were again thinner in FESz (q < .05). Exploratory correlation analyses revealed left PHA3 was positively associated with hallucinations and right PHA3 was positively associated with processing speed, working memory, and verbal learning. The novel use of the HCP‐MMP in two independent FESz samples revealed thinner bilateral PHA3, suggesting this byway between cortical and limbic processing is a critical site of pathology near the emergence of psychosis.

Assessment of brain cholesterol metabolism biomarker 24S-hydroxycholesterol in schizophrenia

Plasma 24S-hydroxycholesterol mostly originates in brain tissue and likely reflects the turnover of cholesterol in the central nervous system. As cholesterol is disproportionally enriched in many key brain structures, 24S-hydroxycholesterol is a promising biomarker for psychiatric and neurologic disorders that impact brain structure. We hypothesized that, as schizophrenia patients have widely reported gray and white matter deficits, they would have abnormal levels of plasma 24S-hydroxycholesterol, and that plasma levels of 24S-hydroxycholesterol would be associated with brain structural and functional biomarkers for schizophrenia. Plasma levels of 24S-hydroxycholesterol were measured in 226 individuals with schizophrenia and 204 healthy controls. The results showed that levels of 24S-hydroxycholesterol were not significantly different between patients and controls. Age was significantly and negatively correlated with 24S-hydroxycholesterol in both groups, and in both groups, females had significantly higher levels of 24S-hydroxycholesterol compared to males. Levels of 24S-hydroxycholesterol were not related to average fractional anisotropy of white matter or cortical thickness, or to cognitive deficits in schizophrenia. Based on these results from a large sample and using multiple brain biomarkers, we conclude there is little to no value of plasma 24S-hydroxycholesterol as a brain metabolite biomarker for schizophrenia.

N-acetylcysteine prevents olanzapine-induced oxidative stress in mHypoA-59 hypothalamic neurons

Olanzapine is a second-generation antipsychotic (AP) drug commonly prescribed for the treatment of schizophrenia. Recently, olanzapine has been found to cause brain tissue volume loss in rodent and primate studies; however, the underlying mechanism remains unknown. Abnormal autophagy and oxidative stress have been implicated to have a role in AP-induced neurodegeneration, while N-acetylcysteine (NAC) is a potent antioxidant, shown to be beneficial in the treatment of schizophrenia. Here, we investigate the role of olanzapine and NAC on cell viability, oxidative stress, mitochondrial mass and mitophagy in hypothalamic cells. Firstly, cell viability was assessed in mHypoA-59 and mHypoA NPY/GFP cells using an MTS assay and flow cytometric analyses. Olanzapine treated mHypoA-59 cells were then assessed for mitophagy markers and oxidative stress; including quantification of lysosomes, autophagosomes, LC3B-II, p62, superoxide anion (O₂^–) and mitochondrial mass. NAC (10 mM) was used to reverse the effects of olanzapine (100 µM) on O₂⁻, mitochondrial mass and LC3B-II. We found that olanzapine significantly impacted cell viability in mHypoA-59 hypothalamic cells in a dose and time-dependent manner. Olanzapine inhibited mitophagy, instigated oxidative stress and prompted mitochondrial abnormalities. NAC was able to mitigate olanzapine-induced effects. These findings suggest that high doses of olanzapine may cause neurotoxicity of hypothalamic neurons via increased production of reactive oxygen species (ROS), mitochondrial damage and mitophagy inhibition. This could in part explain data suggesting that APs may reduce brain volume.

Cross-Disorder Analysis of Brain Structural Abnormalities in Six Major Psychiatric Disorders: A Secondary Analysis of Mega- and Meta-analytical Findings From the ENIGMA Consortium

BACKGROUND

Neuroimaging studies have consistently reported similar brain structural abnormalities across different psychiatric disorders. Yet, the extent and regional distribution of shared morphometric abnormalities between disorders remains unknown.

METHODS

Here, we conducted a cross-disorder analysis of brain structural abnormalities in 6 psychiatric disorders based on effect size estimates for cortical thickness and subcortical volume differences between healthy control subjects and psychiatric patients from 11 mega- and meta-analyses from the ENIGMA (Enhancing Neuro Imaging Genetics Through Meta Analysis) consortium. Correlational and exploratory factor analyses were used to quantify the relative overlap in brain structural effect sizes between disorders and to identify brain regions with disorder-specific abnormalities.

RESULTS

Brain structural abnormalities in major depressive disorder, bipolar disorder, schizophrenia, and obsessive-compulsive disorder were highly correlated (r = .443 to r = .782), and one shared latent underlying factor explained between 42.3% and 88.7% of the brain structural variance of each disorder. The observed shared morphometric signature of these disorders showed little similarity with brain structural patterns related to physiological aging. In contrast, patterns of brain structural abnormalities independent of all other disorders were observed in both attention-deficit/hyperactivity disorder and autism spectrum disorder. Brain regions showing high proportions of independent variance were identified for each disorder to locate disorder-specific morphometric abnormalities.

CONCLUSIONS

Taken together, these results offer novel insights into transdiagnostic as well as disorder-specific brain structural abnormalities across 6 major psychiatric disorders. Limitations comprise the uncertain contribution of risk factors, comorbidities, and medication effects to the observed pattern of results that should be clarified by future research.

Assessment of Neurobiological Mechanisms of Cortical Thinning During Childhood and Adolescence and Their Implications for Psychiatric Disorders

Importance

Many psychiatric disorders can be conceptualized as disorders of brain maturation during childhood and adolescence. Discovering the neurobiological underpinnings of brain maturation may elucidate molecular pathways of vulnerability and resilience to such disorders.

Objective

To investigate the underlying neurobiological mechanisms of age-associated cortical thinning during maturation and their implications for psychiatric disorders.

Design, Setting, and Participants

This multicohort analysis used data from 3 community-based studies. The Saguenay Youth Study provided data from 1024 adolescents who were recruited at a single site in Quebec, Canada. The IMAGEN cohort provided data from 1823 participants who were recruited in 8 European cities. The Brazil High Risk Cohort Study for the Development of Childhood Psychiatric Disorders provided data from 815 participants who were recruited in 2 Brazilian cities. Cortical thickness was estimated from the results of magnetic resonance imaging (MRI) scans, and age-associated cortical thinning was estimated in 34 cortical regions. Gene expression from the Allen Human Brain Atlas was aligned with the same regions. Similarities in the interregional profiles of gene expression and the profiles of age-associated cortical thinning were measured. The involvement of dendrites, dendritic spines, and myelin was tested using 3 gene panels. Enrichment for genes associated with psychiatric disorders was tested among the genes associated with thinning and their coexpression networks. Data analysis was conducted between March and October 2019.

Main Outcomes and Measures

MRI-derived estimates of age-associated cortical thinning and gene expression in 34 cortical regions.

Results

A total of 3596 individuals aged 9 to 21 years were included in this study. Of those, 1803 participants (50.1%) were female, and the mean (SD) age was 15.2 (2.6) years. Interregional profiles of age-associated cortical thinning were associated with interregional gradients in the expression of genes associated with dendrites, dendritic spines, and myelin; the variance in thinning explained by the gene panels across different points ranged from 0.45% to 10.55% for the dendrite panel, 0.00% to 9.98% for the spine panel, and 0.19% to 26.39% for the myelin panel. These genes and their coexpression networks were enriched for genes associated with several psychiatric disorders.

Conclusions and Relevance

In this study, genetic similarity between interregional variation in cortical thinning during maturation and multiple psychiatric disorders suggests overlapping molecular underpinnings. This finding adds to the understanding of the neurodevelopmental mechanisms of psychiatric disorders.

Finding specificity in structural brain alterations through Bayesian reverse inference

In the field of neuroimaging reverse inferences can lead us to suppose the involvement of cognitive processes from certain patterns of brain activity. However, the same reasoning holds if we substitute "brain activity" with "brain alteration" and "cognitive process" with "brain disorder." The fact that different brain disorders exhibit a high degree of overlap in their patterns of structural alterations makes forward inference-based analyses less suitable for identifying brain areas whose alteration is specific to a certain pathology. In the forward inference-based analyses, in fact, it is impossible to distinguish between areas that are altered by the majority of brain disorders and areas that are specifically affected by certain diseases. To address this issue and allow the identification of highly pathology-specific altered areas we used the Bayes' factor technique, which was employed, as a proof of concept, on voxel-based morphometry data of schizophrenia and Alzheimer's disease. This technique allows to calculate the ratio between the likelihoods of two alternative hypotheses (in our case, that the alteration of the voxel is specific for the brain disorder under scrutiny or that the alteration is not specific). We then performed temporal simulations of the alterations' spread associated with different pathologies. The Bayes' factor values calculated on these simulated data were able to reveal that the areas, which are more specific to a certain disease, are also the ones to be early altered. This study puts forward a new analytical instrument capable of innovating the methodological approach to the investigation of brain pathology.

Intelligence, educational attainment, and brain structure in those at familial high-risk for schizophrenia or bipolar disorder

First-degree relatives of patients diagnosed with schizophrenia (SZ-FDRs) show similar patterns of brain abnormalities and cognitive alterations to patients, albeit with smaller effect sizes. First-degree relatives of patients diagnosed with bipolar disorder (BD-FDRs) show divergent patterns; on average, intracranial volume is larger compared to controls, and findings on cognitive alterations in BD-FDRs are inconsistent. Here, we performed a meta-analysis of global and regional brain measures (cortical and subcortical), current IQ, and educational attainment in 5,795 individuals (1,103 SZ-FDRs, 867 BD-FDRs, 2,190 controls, 942 schizophrenia patients, 693 bipolar patients) from 36 schizophrenia and/or bipolar disorder family cohorts, with standardized methods. Compared to controls, SZ-FDRs showed a pattern of widespread thinner cortex, while BD-FDRs had widespread larger cortical surface area. IQ was lower in SZ-FDRs (d = -0.42, p = 3 × 10^-5 ), with weak evidence of IQ reductions among BD-FDRs (d = -0.23, p = .045). Both relative groups had similar educational attainment compared to controls. When adjusting for IQ or educational attainment, the group-effects on brain measures changed, albeit modestly. Changes were in the expected direction, with less pronounced brain abnormalities in SZ-FDRs and more pronounced effects in BD-FDRs. To conclude, SZ-FDRs and BD-FDRs show a differential pattern of structural brain abnormalities. In contrast, both had lower IQ scores and similar school achievements compared to controls. Given that brain differences between SZ-FDRs and BD-FDRs remain after adjusting for IQ or educational attainment, we suggest that differential brain developmental processes underlying predisposition for schizophrenia or bipolar disorder are likely independent of general cognitive impairment.

Gesture deficits and apraxia in schizophrenia

Aberrant performance of skilled action has long been noted in schizophrenia and relatedly, recent reports have demonstrated impaired use, performance, and perception of hand gestures in this group. Still, this deficit is not acknowledged as apraxia, which to the broader medical field, characterizes impairments in skilled actions. Understanding the relationship between apraxia and schizophrenia may shed an invaluable new perspective on disease mechanism, and highlight novel treatment opportunities as well. To examine this potential link, we reviewed the evidence for the types of praxis errors, associated psychopathology, and cerebral correlates of the praxis deficit in schizophrenia. Notably, the review indicated that gesture deficits are severe enough to be considered genuine apraxia in a substantial proportion of patients (about 25%). Further, other potential contributors (e.g., hypokinetic motor abnormalities, cognitive impairment) are indeed associated with gesture deficits in schizophrenia, but do not sufficiently explain the abnormality. Finally, patients with praxis deficits have altered brain structure and function including the left parieto-premotor praxis network and these neural correlates are specific to the praxis deficit. Therefore, we argue that the gestural disorder frequently observed in schizophrenia shares both the clinical and neurophysiological features of true apraxia, as in other neuropsychiatric disorders with impaired higher order motor control, such as Parkinson's disease.

Meta-analysis of generalized additive models in neuroimaging studies

Analyzing data from multiple neuroimaging studies has great potential in terms of increasing statistical power, enabling detection of effects of smaller magnitude than would be possible when analyzing each study separately and also allowing to systematically investigate between-study differences. Restrictions due to privacy or proprietary data as well as more practical concerns can make it hard to share neuroimaging datasets, such that analyzing all data in a common location might be impractical or impossible. Meta-analytic methods provide a way to overcome this issue, by combining aggregated quantities like model parameters or risk ratios. Most meta-analytic tools focus on parametric statistical models, and methods for meta-analyzing semi-parametric models like generalized additive models have not been well developed. Parametric models are often not appropriate in neuroimaging, where for instance age-brain relationships may take forms that are difficult to accurately describe using such models. In this paper we introduce meta-GAM, a method for meta-analysis of generalized additive models which does not require individual participant data, and hence is suitable for increasing statistical power while upholding privacy and other regulatory concerns. We extend previous works by enabling the analysis of multiple model terms as well as multivariate smooth functions. In addition, we show how meta-analytic p-values can be computed for smooth terms. The proposed methods are shown to perform well in simulation experiments, and are demonstrated in a real data analysis on hippocampal volume and self-reported sleep quality data from the Lifebrain consortium. We argue that application of meta-GAM is especially beneficial in lifespan neuroscience and imaging genetics. The methods are implemented in an accompanying R package metagam, which is also demonstrated.

Individual Variation of Human Cortical Structure Is Established in the First Year of Life

BACKGROUND

Individual differences in cortical gray matter (GM) structure are associated with cognitive function and psychiatric disorders with developmental origins. Identifying when individual differences in cortical structure are established in childhood is critical for understanding the timing of abnormal cortical development associated with neuropsychiatric disorders.

METHODS

We studied the development of cortical GM and white matter volume, cortical thickness, and surface area using structural magnetic resonance imaging in two unique cohorts of singleton (121 male and 131 female) and twin (99 male and 83 female) children imaged longitudinally from birth to 6 years.

RESULTS

Cortical GM volume increases rapidly in the first year of life, with more gradual growth thereafter. Between ages 1 and 6 years, total surface area expands 29%, while average cortical thickness decreases about 3.5%. In both cohorts, a large portion of individual variation in cortical GM volume (81%-87%) and total surface area (73%-83%) at age 6 years is present by age 1 year. Regional heterogeneity of cortical thickness observed at age 6 is largely in place at age 1.

CONCLUSIONS

These findings indicate that individual differences in cortical GM structure are largely established by the end of the first year of life, following a period of rapid postnatal GM growth. This suggests that alterations in GM structure associated with psychiatric disorders with developmental origins may largely arise in the first year of life and that interventions to normalize or mitigate abnormal GM development may need to be targeted to very early childhood.

What a Clinician Should Know About the Neurobiology of Schizophrenia: A Historical Perspective to Current Understanding

The brain is no doubt the "organ" of psychiatry; yet, over the years, few evidence-based classifications of psychiatric disorders have been based on brain mechanisms. The National Institute of Mental Health notably proposed one such system, known as Research Domain Criteria, although it has not yet influenced any changes in the DSM. Of all the major psychiatric disorders, the brain has been studied most extensively in schizophrenia, with its speculative pathology first documented by Emil Kraepelin as early as the beginning of the 20th century. Subsequently, the revolution in technology over the past 50 years has changed how investigators are able to view the brain before death without performing biopsies. Schizophrenia is thus found to have both structural and functional widespread brain anomalies that likely lead to its clinical deterioration. At the onset of illness, acquiring an MRI scan could be part of the routine evaluation to determine how progressive the disease has so far been. However, this practice is not yet recognized by the American Psychiatric Association in any of its guidelines on the treatment of schizophrenia.

Higher Body-Mass Index and Lower Gray Matter Volumes in First Episode of Psychosis

BACKGROUND

Neurostructural alterations are often reported in first episode of psychosis (FEP), but there is heterogeneity in the direction and location of findings between individual studies. The reasons for this heterogeneity remain unknown. Obesity is disproportionately frequent already early in the course of psychosis and is associated with smaller brain volumes. Thus, we hypothesized that obesity may contribute to brain changes in FEP.

METHOD

We analyzed MRI scans from 120 participants with FEP and 114 healthy participants. In primary analyses, we performed voxel-based morphometry (VBM) with small volume corrections to regions associated with FEP or obesity in previous meta-analyses. In secondary analyses, we performed whole-brain VBM analyses.

RESULTS

In primary analyses, we found that when controlling for BMI, FEP had lower GM volume than healthy participants in a) left fronto-temporal region (pTFCE = 0.008) and b) left postcentral gyrus (pTFCE = 0.043). When controlling for FEP, BMI was associated with lower GM volume in left cerebellum (pTFCE < 0.001). In secondary analyses, we found that when controlling for BMI, FEP had lower GM volume than healthy participants in the a) cerebellum (pTFCE = 0.004), b) left frontal (pTFCE = 0.024), and c) right temporal cortex (pTFCE = 0.031). When controlling for FEP, BMI was associated with lower GM volume in cerebellum (pTFCE = 0.004). Levels of C-reactive protein, HDL and LDL-cholesterol correlated with obesity related neurostructural alterations.

CONCLUSIONS

This study suggests that higher BMI, which is frequent in FEP, may contribute to cerebellar alterations in schizophrenia. As previous studies showed that obesity-related brain alterations may be reversible, our findings raise the possibility that improving the screening for and treatment of obesity and associated metabolic changes could preserve brain structure in FEP.

Dissimilarity in Sulcal Width Patterns in the Cortex can be Used to Identify Patients With Schizophrenia With Extreme Deficits in Cognitive Performance

Schizophrenia is a biologically complex disorder with multiple regional deficits in cortical brain morphology. In addition, interindividual heterogeneity of cortical morphological metrics is larger in patients with schizophrenia when compared to healthy controls. Exploiting interindividual differences in the severity of cortical morphological deficits in patients instead of focusing on group averages may aid in detecting biologically informed homogeneous subgroups. The person-based similarity index (PBSI) of brain morphology indexes an individual's morphometric similarity across numerous cortical regions amongst a sample of healthy subjects. We extended the PBSI such that it indexes the morphometric similarity of an independent individual (eg, a patient) with respect to healthy control subjects. By employing a normative modeling approach on longitudinal data, we determined an individual's degree of morphometric dissimilarity to the norm. We calculated the PBSI for sulcal width (PBSI-SW) in patients with schizophrenia and healthy control subjects (164 patients and 164 healthy controls; 656 magnetic resonance imaging scans) and associated it with cognitive performance and cortical sulcation index. A subgroup of patients with markedly deviant PBSI-SW showed extreme deficits in cognitive performance and cortical sulcation. Progressive reduction of PBSI-SW in the schizophrenia group relative to healthy controls was driven by these deviating individuals. By explicitly leveraging interindividual differences in the severity of PBSI-SW deficits, neuroimaging-driven subgrouping of patients is feasible. As such, our results pave the way for future applications of morphometric similarity indices for subtyping of clinical populations.

Neuroimaging Phenotypes Associated With Risk and Resilience for Psychosis and Autism Spectrum Disorders in 22q11.2 Microdeletion Syndrome

Identification of biological risk factors that contribute to the development of complex neuropsychiatric disorders such as psychosis and autism spectrum disorder (ASD) is key for early intervention and detection. Furthermore, parsing the biological heterogeneity associated with these neuropsychiatric syndromes will help us understand the neural mechanisms underlying psychiatric symptom development. The 22q11.2 microdeletion syndrome (22q11DS) is caused by a recurrent genetic mutation that carries significantly increased risk for developing psychosis and/or ASD. In this review, I provide an brief introduction to 22q11DS and discuss common phenotyping strategies that are used to assess psychosis and ASD in this population. I then summarize neuroimaging phenotypes associated with psychosis and ASD in 22q11.DS. Next, I discuss challenges within the field and provide practical suggestions to overcome these obstacles. Finally, I discuss future directions for moving 22q11DS risk and resilience research forward.

Major Neuropsychological Impairments in Schizophrenia Patients: Clinical Implications

PURPOSE OF REVIEW

Schizophrenia is a complex severe mental illness with high morbidity and mortality. It is characterized by positive symptoms, negative symptoms, and cognitive impairment. Cognitive impairment is strongly associated with functional impairment and presents a major barrier to recovery. This article reviews some of the most recent research on cognition in schizophrenia and the clinical implications.

RECENT FINDINGS

There have been recent studies related to the genomics of cognition and neural structures involved in cognition. We review recent investigations into the assessment of social cognition and the implications of impaired introspective accuracy. A recent network analysis assessed the relationship of neurocognition and social cognition to functional capacity. We further discuss the role of specific symptoms in functioning, including negative symptoms and symptoms related to autism spectrum disorder. We conclude with a discussion of a novel computerized treatment for social cognition. Recent research has sought to better understand several dimensions of cognition including genomics, brain structure, social cognition, functional capacity, and symptomatology. This recent research brings us closer to understanding the complex clinical picture of schizophrenia and the best treatments to achieve recovery.

Do neurobiological differences exist between paranoid and non-paranoid schizophrenia? Findings from the bipolar schizophrenia network on intermediate phenotypes study

Subtypes of schizophrenia, constructed using clinical phenomenology to resolve illness heterogeneity, have faced criticism due to overlapping symptomatology and longitudinal instability; they were therefore dropped from the Diagnostic Statistical Manual-5. Cognitive and imaging findings comparing paranoid (P-SZ) and non-paranoid (disorganized, residual and undifferentiated; NP-SZ) schizophrenia have been limited due to small sample sizes. We assessed P-SZ and NP-SZ using symptomatology, cognition and brain structure and predicted that there would be few neurobiological differences. P-SZ (n = 237), NP-SZ (n = 127) and controls (n = 430) were included from a multi-site study. In a subset of this sample, structural imaging measures (P-SZ, n = 133; NP-SZ, n = 67; controls, n = 310) were calculated using Freesurfer 6.0. Group contrasts were run using analysis of covariance, controlling for age, sex, race and site, p-values were corrected using False Discovery Rate (FDR) and were repeated excluding the residual subtype. Compared to NP-SZ (with and without the residual subtype), P-SZ displayed fewer negative symptoms, faster speed of processing, larger bilateral hippocampus, right amygdala and their subfield volumes. Additionally, NP-SZ (with residual subtype) displayed fewer depressive symptoms and higher left transverse temporal cortical thickness (CT) but NP-SZ without residual subtype showed lower GAF scores and worse digit sequencing compared to P-SZ. No differences in positive symptoms and functioning (global or social) were detected. Subtle but significant differences were seen in cognition, symptoms, CT and subcortical volumes between P-SZ and NP-SZ. While the magnitude of these differences is not large enough to justify them as distinct categories, the paranoid- nonparanoid distinction in schizophrenia merits further investigation.