Widespread white matter microstructural differences in schizophrenia across 4322 individuals: results from the ENIGMA Schizophrenia DTI Working Group

Aberrant effective connectivity is associated with positive symptoms in first-episode schizophrenia

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We use DCM in patients newly diagnosed with schizophrenia.

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Patients were naïve to therapeutic antipsychotics, but not completely drug naïve.

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Patients have stronger feedforward connectivity than matched healthy controls.

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Stronger positive symptoms are associated with disinhibition in the temporal lobe.

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In active inference, this may relate to aberrant precision and prediction errors.

Schizophrenia is a neurodevelopmental psychiatric disorder thought to result from synaptic dysfunction that affects distributed brain connectivity, rather than any particular brain region. While symptomatology is traditionally divided into positive and negative symptoms, abnormal social cognition is now recognized a key component of schizophrenia. Nonetheless, we are still lacking a mechanistic understanding of effective brain connectivity in schizophrenia during social cognition and how it relates to clinical symptomatology. To address this question, we used fMRI and dynamic causal modelling (DCM) to test for abnormal brain connectivity in twenty-four patients with first-episode schizophrenia (FES) compared to twenty-five matched controls performing the Human Connectome Project (HCP) social cognition paradigm. Patients had not received regular therapeutic antipsychotics, but were not completely drug naïve. Whilst patients were less accurate than controls in judging social stimuli from non-social stimuli, our results revealed an increase in feedforward connectivity from motion-sensitive V5 to posterior superior temporal sulcus (pSTS) in patients compared to matched controls. At the same time, patients with a higher degree of positive symptoms had more disinhibition within pSTS, a region computationally involved in social cognition. We interpret these findings the framework of active inference, where increased feedforward connectivity may encode aberrant prediction errors from V5 to pSTS and local disinhibition within pSTS may reflect aberrant encoding of the precision of cortical representations about social stimuli.

Alterations in white matter microstructure in individuals at persistent risk for psychosis

Abnormalities in brain white matter (WM) are reported in youth at-risk for psychosis. Yet, the neurodevelopmental time course of these abnormalities remains unclear. Thus, longitudinal diffusion-weighted imaging (DWI) was used to investigate WM abnormalities in youth at-risk for psychosis. A subset of individuals from the Philadelphia Neurodevelopmental Cohort (PNC) completed two DWI scans approximately 20 months apart. Youths were identified through structured interview as having subthreshold persistent psychosis risk symptoms (n = 46), and were compared to healthy typically developing participants (TD; n = 98). Analyses were conducted at voxelwise and regional levels. Nonlinear developmental patterns were examined using penalized splines within a generalized additive model. Compared to TD, youth with persistent psychosis risk symptoms had lower whole-brain WM fractional anisotropy (FA) and higher radial diffusivity (RD). Voxelwise analyses revealed clusters of significant WM abnormalities within the temporal and parietal lobes. Lower FA within the cingulum bundle of hippocampus and cerebrospinal tracts were the most robust deficits in individuals with persistent psychosis symptoms. These findings were consistent over two visits. Thus, it appears that WM abnormalities are present early in youth with persistent psychosis risk symptoms, however, there is little evidence to suggest that these features emerge in late adolescence or early adulthood. Future studies should seek to characterize WM abnormalities in younger individuals and follow individuals as subthreshold psychotic symptoms emerge.

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.

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.

Evidence for Altered Metabolism of Sphingosine-1-Phosphate in the Corpus Callosum of Patients with Schizophrenia

The disturbed integrity of myelin and white matter, along with dysregulation of the lipid metabolism, may be involved in schizophrenia pathophysiology. Considering the crucial role of sphingolipids in neurodevelopment, particularly in oligodendrocyte differentiation and myelination, we examined the role of sphingolipid dynamics in the pathophysiology of schizophrenia. We performed targeted mass spectrometry-based analysis of sphingolipids from the cortical area and corpus callosum of postmortem brain samples from patients with schizophrenia and controls. We observed lower sphingosine-1-phosphate (S1P) levels, specifically in the corpus callosum of patients with schizophrenia, but not in major depressive disorder or bipolar disorder, when compared with the controls. Patient data and animal studies showed that antipsychotic intake did not contribute to the lowered S1P levels. We also found that lowered S1P levels in the corpus callosum of patients with schizophrenia may stem from the upregulation of genes for S1P-degrading enzymes; higher expression of genes for S1P receptors suggested a potential compensatory mechanism for the lowered S1P levels. A higher ratio of the sum of sphingosine and ceramide to S1P, which can induce apoptosis and cell-cycle arrest, was also observed in the samples of patients with schizophrenia than in controls. These results suggest that an altered S1P metabolism may underlie the deficits in oligodendrocyte differentiation and myelin formation, leading to the structural and molecular abnormalities of white matter reported in schizophrenia. Our findings may pave the way toward a novel therapeutic strategy.

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.

Estimating Brain Connectivity With Diffusion-Weighted Magnetic Resonance Imaging: Promise and Peril

Diffusion-weighted magnetic resonance imaging (dMRI) is a popular tool for noninvasively assessing properties of white matter in the brain. Among other uses, dMRI data can be used to produce estimates of anatomical connectivity on the basis of tractography. However, direct comparisons of anatomical connectivity as estimated through invasive neural tract-tracing experiments and dMRI-derived connectivity have shown only a moderate relationship in nonhuman primate (particularly macaque) studies. Tractography is plagued by known problems associated with resolution, crossing fibers, and curving fibers, among others. These problems lead to deficits in both sensitivity and specificity, which trade off with each other in multiple datasets. Although not yet examined quantitatively, there is reason to believe that some large white matter bundles, those with more topographic organization, may produce more accurate results than others. Moving forward, sophisticated analytical approaches and anatomical constraints may improve tractography accuracy. However, broadly speaking, dMRI-derived estimates of brain connectivity should be approached with caution.

Multiparametric mapping of white matter microstructure in catatonia

Catatonia is characterized by motor, affective and behavioral abnormalities. To date, the specific role of white matter (WM) abnormalities in schizophrenia spectrum disorders (SSD) patients with catatonia is largely unknown. In this study, diffusion magnetic resonance imaging (dMRI) data were collected from 111 right-handed SSD patients and 28 healthy controls. Catatonic symptoms were examined on the Northoff Catatonia Rating Scale (NCRS). We used whole-brain tract-based spatial statistics (TBSS), tractometry (along tract statistics using TractSeg) and graph analytics (clustering coefficient-CCO, local betweenness centrality-BC) to provide a framework of specific WM microstructural abnormalities underlying catatonia in SSD. Following a categorical approach, post hoc analyses showed differences in fractional anisotrophy (FA) measured via tractometry in the corpus callosum, corticospinal tract and thalamo-premotor tract as well as increased CCO as derived by graph analytics of the right superior parietal cortex (SPC) and left caudate nucleus in catatonic patients (NCRS total score ≥ 3; n = 30) when compared to non-catatonic patients (NCRS total score = 0; n = 29). In catatonic patients according to DSM-IV-TR (n = 43), catatonic symptoms were associated with FA variations (tractometry) of the left corticospinal tract and CCO of the left orbitofrontal cortex, primary motor cortex, supplementary motor area and putamen. This study supports the notion that structural reorganization of WM bundles connecting orbitofrontal/parietal, thalamic and striatal regions contribute to catatonia in SSD patients.

Altered structural connectivity and cytokine levels in Schizophrenia and Genetic high-risk individuals: Associations with disease states and vulnerability

BACKGROUND

Alterations of white matter (WM) integrity have been observed in both schizophrenia (SZ) and individuals at genetic high risk for SZ (GHR-SZ); however, the molecular mechanisms underlying WM disruption remain unclear. Cytokines are chemical messengers of the immune system that are closely related to inflammation and neurogenesis in the brain. This study aimed to identify abnormalities in WM integrity, cytokine levels, and their association in SZ and GHR-SZ.

METHODS

A total of 355 participants (126 with SZ, 99 GHR-SZ, and 130 healthy controls [HCs]) were recruited. All participants underwent diffusion tensor imaging and blood samples were obtained from 113 participants within 24 h of imaging.

RESULTS

In SZ, there was decreased fractional anisotropy(FA) in the genu and body of the corpus callosum (GCC/BCC), anterior corona radiata, anterior and posterior limbs of the internal capsule (ALIC/PLIC), superior fronto-occipital fasciculus, external capsule, and fornix, and elevated IL-6 levels. In both SZ and GHR-SZ, decreased FA in the splenium of the corpus callosum (SCC), posterior corona radiate (PCR), and posterior thalamic radiation (PTR) was observed, and elevated leptin levels were present. Additionally, the IL-6 levels were negatively correlated with FA in the GCC and ALIC in SZ, and leptin levels were negatively correlated with the SCC, PCR, and PTR in SZ and GHR-SZ.

CONCLUSIONS

Abnormal WM integrity in SZ may reflect the state of disease and is associated with increased IL-6 levels. In addition, these leptin-associated WM integrity abnormalities in both SZ and GHR-SZ may reflect a genetic vulnerability to SZ.

White Matter Microstructural Properties Associated with Impaired Attention in Chronic Schizophrenia: A Multi-Center Study

Attention as a key cognitive function is impaired in schizophrenia, interfering with the normal daily life of the patients. Previous studies on the microstructural correlates of attention in schizophrenia were limited to single fibers, did not include a control group, or did not adjust for drug dosage. In the current study, we investigated the association between microstructural properties of the white matter fibers and attention tests in 81 patients and 79 healthy controls from the Mind Clinical Imaging Consortium database. Integrity measures of superior longitudinal fasciculus, cingulum, genu, and splenium were extracted after tractography. Using an interaction model between diagnosis and microstructural properties, and adjusting for age, gender, acquisition site, education, and cumulative drug usage dose, and after correcting for family-wise error, we showed decreased integrity in the patients and a significant negative association between fractional anisotropy of the tracts and trail making test part A with a greater expected decrease in the attention per unit of decrease of integrity in the patients compared to the healthy controls. Our findings suggest that decreased integrity of the bilateral cingulum, and splenium, are independent of the cumulative drug dosage, age, gender, and site, and may underlie the impaired attention in the schizophrenia.

Reduced white matter integrity associated with cognitive deficits in patients with drug-naive first-episode schizophrenia revealed by diffusion tensor imaging

Patients with schizophrenia have shown widespread white matter microstructural abnormalities and cognitive deficits, but the definitive relationship between white matter and cognitive performance remains unclear. In this study, we investigated the possible associations between white matter integrity and cognitive deficits in drug-naive first-episode schizophrenia (dn-FES) using diffusion tensor imaging (DTI). A total of 96 participants, including 46 dn-FES patients and 50 healthy individuals, underwent 3.0 T magnetic resonance diffusion-weighted imaging and cognitive assessments using the Chinese version of the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery (MCCB). Group differences were tested using tract-based spatial statistics (TBSS). Compared with the control group, the dn-FES group exhibited reduced white matter integrity, as indexed using fractional anisotropy (FA) metrics, in the right-hemispheric cluster comprising the posterior thalamic radiation, posterior corona radiata, superior longitudinal fasciculus, retrolenticular part of the internal capsule, tapetum, splenium of the corpus callosum, sagittal stratum, and inferior longitudinal fasciculus. We found that social cognitive deficit is significantly correlated with reduced FA in these white matter regions, except the sagittal stratum and inferior longitudinal fasciculus. Furthermore, we found that speed of processing is positively correlated with reduced FA in the right superior longitudinal fasciculus of dn-FES patients. In summary, white matter deficits were validated in dn-FES patients and could be associated with speed of processing and social cognition, providing clues about a neural basis of schizophrenia and a potential biomarker for clinical studies.

Potential Roles of Redox Dysregulation in the Development of Schizophrenia

Converging evidence implicates redox dysregulation as a pathological mechanism driving the emergence of psychosis. Increased oxidative damage and decreased capacity of intracellular redox modulatory systems are consistent findings in persons with schizophrenia as well as in persons at clinical high risk who subsequently developed frank psychosis. Levels of glutathione, a key regulator of cellular redox status, are reduced in the medial prefrontal cortex, striatum, and thalamus in schizophrenia. In humans with schizophrenia and in rodent models recapitulating various features of schizophrenia, redox dysregulation is linked to reductions of parvalbumin containing gamma-aminobutyric acid (GABA) interneurons and volumes of their perineuronal nets, white matter abnormalities, and microglia activation. Importantly, the activity of transcription factors, kinases, and phosphatases regulating diverse aspects of neurodevelopment and synaptic plasticity varies according to cellular redox state. Molecules regulating interneuron function under redox control include NMDA receptor subunits GluN1 and GluN2A as well as KEAP1 (regulator of transcription factor NRF2). In a rodent schizophrenia model characterized by impaired glutathione synthesis, the Gclm knockout mouse, oxidative stress activated MMP9 (matrix metalloprotease 9) via its redox-responsive regulatory sites, causing a cascade of molecular events leading to microglia activation, perineural net degradation, and impaired NMDA receptor function. Molecular pathways under redox control are implicated in the etiopathology of schizophrenia and are attractive drug targets for individualized drug therapy trials in the contexts of prevention and treatment of psychosis.

Effect of DAOA genetic variation on white matter alteration in corpus callosum in patients with first-episode schizophrenia

D-amino acid oxidase activator (DAOA) gene, which plays a crucial role in the process of glutamatergic transmission and mitochondrial function, is frequently linked with the liability for schizophrenia. We aimed to investigate whether the variation of DAOA rs2391191 is associated with alterations in white matter integrity of first-episode schizophrenia (FES) patients; and whether it influences the association between white matter integrity, cognitive function and clinical symptoms of schizophrenia. Forty-six patients with FES and forty-nine healthy controls underwent DTI and were genotyped for DAOA rs2391191. Psychopathological assessments were performed by Brief Psychiatric Rating Scale (BPRS) and Scale for Assessment of Negative Symptoms (SANS). Cognitive function was assessed by MATRICS Consensus Cognitive Battery (MCCB). Schizophrenia patients presented lower fractional anisotropy (FA) and higher radial diffusivity (RD), mainly spreading over the corpus callosum and corona radiata compared with healthy controls. Compared with patients carrying G allele, patients with AA showed lower FA in the body of corpus callosum, and higher RD in the genu of corpus callosum, right superior and anterior corona radiata, and left posterior corona radiata. In patients carrying G allele, FA in body of corpus callosum was positively correlated with working memory, RD in genu of corpus callosum was negatively associated with the speed of processing, working memory, and the composite score of MCCB, while no significant correlations were found in AA homozygotes. In our study, patients with FES presented abnormal white matter integrity in corpus callosum and corona radiata. Furthermore, this abnormality was associated with the genetic variation of DAOA rs2391191, with AA homozygotes showing less white matter integrity in the corpus callosum. Our findings possibly provide further support to the evidence that DAOA regulates the process of glutamatergic neurotransmission and mitochondrial function in the pathophysiological mechanism of schizophrenia.

Latent Clinical-Anatomical Dimensions of Schizophrenia

Widespread structural brain abnormalities have been consistently reported in schizophrenia, but their relation to the heterogeneous clinical manifestations remains unknown. In particular, it is unclear whether anatomical abnormalities in discrete regions give rise to discrete symptoms or whether distributed abnormalities give rise to the broad clinical profile associated with schizophrenia. Here, we apply a multivariate data-driven approach to investigate covariance patterns between multiple-symptom domains and distributed brain abnormalities in schizophrenia. Structural magnetic resonance imaging and clinical data were derived from one discovery sample (133 patients and 113 controls) and one independent validation sample (108 patients and 69 controls). Disease-related voxel-wise brain abnormalities were estimated using deformation-based morphometry. Partial least-squares analysis was used to comprehensively map clinical, neuropsychological, and demographic data onto distributed deformation in a single multivariate model. The analysis identified 3 latent clinical-anatomical dimensions that collectively accounted for 55% of the covariance between clinical data and brain deformation. The first latent clinical-anatomical dimension was replicated in an independent sample, encompassing cognitive impairments, negative symptom severity, and brain abnormalities within the default mode and visual networks. This cognitive-negative dimension was associated with low socioeconomic status and was represented across multiple races. Altogether, we identified a continuous cognitive-negative dimension of schizophrenia, centered on 2 intrinsic networks. By simultaneously taking into account both clinical manifestations and neuroanatomical abnormalities, the present results open new avenues for multi-omic stratification and biotyping of individuals with schizophrenia.

Intersection of verbal memory and expressivity on cortical contrast and thickness in first episode psychosis

BACKGROUND

Longitudinal studies of first episode of psychosis (FEP) patients are critical to understanding the dynamic clinical factors influencing functional outcomes; negative symptoms and verbal memory (VM) deficits are two such factors that remain a therapeutic challenge. This study uses white-gray matter contrast at the inner edge of the cortex, in addition to cortical thickness, to probe changes in microstructure and their relation with negative symptoms and possible intersections with verbal memory.

METHODS

T1-weighted images and clinical data were collected longitudinally for patients (N = 88) over a two-year period. Cognitive data were also collected at baseline. Relationships between baseline VM (immediate/delayed recall) and rate of change in two negative symptom dimensions, amotivation and expressivity, were assessed at the behavioral level, as well as at the level of brain structure.

RESULTS

VM, particularly immediate recall, was significantly and positively associated with a steeper rate of expressivity symptom decline (r = 0.32, q = 0.012). Significant interaction effects between baseline delayed recall and change in expressivity were uncovered in somatomotor regions bilaterally for both white-gray matter contrast and cortical thickness. Furthermore, interaction effects between immediate recall and change in expressivity on cortical thickness rates were uncovered across higher-order regions of the language processing network.

CONCLUSIONS

This study shows common neural correlates of language-related brain areas underlying expressivity and VM in FEP, suggesting deficits in these domains may be more linked to speech production rather than general cognitive capacity. Together, white-gray matter contrast and cortical thickness may optimally inform clinical investigations aiming to capture peri-cortical microstructural changes.

Neonatal white matter damage and the fetal inflammatory response

In 1962 a long-recognized pathologic abnormality in neonatal brains characterized by multiple telencephalic focal white matter necroses was renamed periventricular leukomalacia (PVL) and the authors inappropriately asserted that their entity was caused by anoxia. They also failed to include three other white matter histologic abnormalities. In this essay, we identify the breadth of white matter pathology, especially in very preterm newborns, and show that none of the four histologic expressions of white matter damage, including focal necrosis, are associated with hypoxemia or correlates as hypotension, but are instead associated with markers of fetal or perinatal inflammation, particularly in preterm babies. We begin with the background needed to evaluate the evidence.

Reciprocal Copy Number Variations at 22q11.2 Produce Distinct and Convergent Neurobehavioral Impairments Relevant for Schizophrenia and Autism Spectrum Disorder

BACKGROUND

22q11.2 deletions and duplications are copy number variations (CNVs) that predispose to developmental neuropsychiatric disorders. Both CNVs are associated with autism spectrum disorder (ASD), while the deletion confers disproportionate risk for schizophrenia. Neurobehavioral profiles associated with these reciprocal CNVs in conjunction with brain imaging measures have not been reported.

METHODS

We profiled the impact of 22q11.2 CNVs on neurobehavioral measures relevant to ASD and psychosis in 106 22q11.2 deletion carriers, 38 22q11.2 duplication carriers, and 82 demographically matched healthy control subjects. To determine whether brain-behavior relationships were altered in CNV carriers, we further tested for interactions between group and regional brain structure on neurobehavioral domains.

RESULTS

Cognitive deficits were observed in both CNV groups, with the lowest IQs in deletion carriers. ASD and dimensionally measured ASD traits were elevated in both CNV groups; however, duplication carriers exhibited increased stereotypies compared to deletion carriers. Moreover, discriminant analysis using ASD subdomains distinguished between CNV cases with 76% accuracy. Both psychotic disorder diagnosis and dimensionally measured positive and negative symptoms were elevated in deletion carriers. Finally, healthy control subjects showed an inverse relationship between processing speed and cortical thickness in heteromodal association areas, which was absent in both CNV groups.

CONCLUSIONS

22q11.2 CNVs differentially modulate intellectual functioning and psychosis-related symptomatology but converge on broad ASD-related symptomatology. However, subtle differences in ASD profiles distinguish CNV groups. Processing speed impairments, coupled with the lack of normative relationship between processing speed and cortical thickness in CNV carriers, implicate aberrant development of the cortical mantle in the pathology underlying impaired processing speed ability.

Frontal white matter abnormalities reveal the pathological basis underlying negative symptoms in antipsychotic-naïve, first-episode patients with adolescent-onset schizophrenia: Evidence from multimodal brain imaging

A major challenge in schizophrenia is to uncover the pathophysiological basis of its negative symptoms. Recent neuroimaging studies revealed that disrupted structural properties of frontal white matter (FWM) are associated with the negative symptoms of schizophrenia. However, there is little direct functional evidence of FWM for negative symptoms in schizophrenia. To address this issue, we combined resting-state connectome-wide functional connectivity (FC) and diffusion tensor imaging tractography to investigate the alteration of FWM underlying the negative symptoms in 39 drug-naive patients with adolescent-onset schizophrenia (AOS) and 31 age- and sex- matched healthy controls (HCs). Results revealed that the intrinsic FC and structural properties (fraction anisotropy and fibers) of the left FWM correspond to individual negative symptoms in AOS. Moreover, the serotonin network (raphe nuclei, anterior and posterior cingulate cortices, and prefrontal and inferior parietal cortices) and FWM-cingulum network were found to contributed to the negative symptom severity in AOS. Furthermore, the patients showed abnormal functional and structural connectivities between the interhemispheric FWM compared with HCs. Importantly, the decreased fiber counts between the interhemispheric FWM were inversely correlated with the negative symptoms in AOS. Our findings demonstrated the association between FWM and negative symptoms, and offered initial evidence by using WM connectome to uncover WM functional information in schizophrenia.

Altered grey matter volume and white matter integrity in individuals with high schizo-obsessive traits, high schizotypal traits and obsessive-compulsive symptoms

Altered brain structures have been found in patients with schizo-obsessive disorder, schizophrenia and obsessive-compulsive disorder in previous studies. However, it is unclear whether similar brain changes are also found in individuals with high schizo-obsessive traits (SOT), high schizotypal traits (SCT) and obsessive-compulsive symptoms (OCS). We examined grey matter volume (GMV) and white matter integrity (WMI, including fractional anisotropy, mean diffusivity, axial diffusivity and radial diffusivity) in 26 individuals with high SOT, 30 individuals with high SCT, 25 individuals with OCS and 30 individuals with low trait scores (LT) in this study. Correlation analysis between GMV, WMI, Schizotypal Personality Questionnaire (SPQ) scores and Obsessive-Compulsive Inventory-Revised (OCI-R) scores in the subclinical groups was also carried out. We found that the SOT group exhibited increased GMV at the right superior occipital gyrus and the left postcentral gyrus compared with the LT group. The SCT group exhibited increased GMV at the right precentral gyrus and the bilateral cuneus compared with the LT group, and decreased fractional anisotropy at the anterior corona radiata compared with the other three groups. The OCS group exhibited increased GMV at the left superior temporal gyrus and decreased GMV at the left pre-supplementary motor area compared with the LT group. These findings highlight specific brain changes in individuals with high SOT, high SCT and OCS, and may thus provide new insights into the neurobiological changes that occur in sub-clinical populations of these disorders.

Brain Age Prediction Reveals Aberrant Brain White Matter in Schizophrenia and Bipolar Disorder: A Multisample Diffusion Tensor Imaging Study

BACKGROUND

Schizophrenia (SZ) and bipolar disorder (BD) share substantial neurodevelopmental components affecting brain maturation and architecture. This necessitates a dynamic lifespan perspective in which brain aberrations are inferred from deviations from expected lifespan trajectories. We applied machine learning to diffusion tensor imaging (DTI) indices of white matter structure and organization to estimate and compare brain age between patients with SZ, patients with BD, and healthy control (HC) subjects across 10 cohorts.

METHODS

We trained 6 cross-validated models using different combinations of DTI data from 927 HC subjects (18-94 years of age) and applied the models to the test sets including 648 patients with SZ (18-66 years of age), 185 patients with BD (18-64 years of age), and 990 HC subjects (17-68 years of age), estimating the brain age for each participant. Group differences were assessed using linear models, accounting for age, sex, and scanner. A meta-analytic framework was applied to assess the heterogeneity and generalizability of the results.

RESULTS

Tenfold cross-validation revealed high accuracy for all models. Compared with HC subjects, the model including all feature sets significantly overestimated the age of patients with SZ (Cohen's d = -0.29) and patients with BD (Cohen's d = 0.18), with similar effects for the other models. The meta-analysis converged on the same findings. Fractional anisotropy-based models showed larger group differences than the models based on other DTI-derived metrics.

CONCLUSIONS

Brain age prediction based on DTI provides informative and robust proxies for brain white matter integrity. Our results further suggest that white matter aberrations in SZ and BD primarily consist of anatomically distributed deviations from expected lifespan trajectories that generalize across cohorts and scanners.

Elevated Extracellular Free-Water in a Multicentric First-Episode Psychosis Sample, Decrease During the First 2 Years of Illness

Recent diffusion imaging studies using free-water (FW) elimination have shown increased FW in gray matter (GM) and white matter (WM) in first-episode psychosis (FEP) and lower corrected fractional anisotropy (FAt) in WM in chronic schizophrenia. However, little is known about the longitudinal stability and clinical significance of these findings. To determine tissue-specific FW and FAt abnormalities in FEP, as part of a multicenter Spanish study, 132 FEP and 108 healthy controls (HC) were clinically characterized and underwent structural and diffusion-weighted MRI scanning. FEP subjects were classified as schizophrenia spectrum disorder (SSD) or non-SSD. Of these subjects, 45 FEP and 41 HC were longitudinally assessed and rescanned after 2 years. FA and FW tissue-specific measurements were cross-sectional and longitudinally compared between groups using voxel-wise analyses in the skeletonized WM and vertex-wise analyses in the GM surface. SSD and non-SSD subjects showed (a) higher baseline FW in temporal regions and in whole GM average (P.adj(SSD vs HC) = .003, P.adj(Non-SSD vs HC) = .040) and (b) lower baseline FAt in several WM tracts. SSD, but not non-SSD, showed (a) higher FW in several WM tracts and in whole WM (P.adj(SSD vs HC)= .049) and (b) a significant FW decrease over time in temporal cortical regions and in whole GM average (P.adj = .011). Increased extracellular FW in the brain is a reliable finding in FEP, and in SSD appears to decrease over the early course of the illness. FAt abnormalities are stable during the first years of psychosis.

Neuroimaging Heterogeneity in Psychosis: Neurobiological Underpinnings and Opportunities for Prognostic and Therapeutic Innovation

Heterogeneity in symptom presentation, outcomes, and treatment response has long been problematic for researchers aiming to identify biological markers of schizophrenia or psychosis. However, there is increasing recognition that there may likely be no such general illness markers, which is consistent with the notion of a group of schizophrenia(s) that may have both shared and unique neurobiological pathways. Instead, strategies aiming to capitalize on or leverage such heterogeneity may help uncover neurobiological pathways that may then be used to stratify groups of patients for prognostic purposes or for therapeutic trials. A shift toward larger sample sizes with adequate statistical power to overcome small effect sizes and disentangle the shared variance among different brain-imaging or behavioral variables has become a priority for the field. In addition, recognition that two individuals with the same clinical diagnosis may be more different from each other (at brain, genetic, and behavioral levels) than from another individual in a different disorder or nonclinical control group-coupled with computational advances-has catapulted data-driven efforts forward. Emerging challenges for this new approach include longitudinal stability of new subgroups, demonstration of validity, and replicability. The "litmus test" will be whether computational approaches that are successfully identifying groups of patients who share features in common, more than current DSM diagnostic constructs, also provide better prognostic accuracy over time and in addition lead to enhancements in treatment response and outcomes. These are the factors that matter most to patients, families, providers, and payers.

Effects of Antipsychotic Medication on Brain Structure in Patients With Major Depressive Disorder and Psychotic Features: Neuroimaging Findings in the Context of a Randomized Placebo-Controlled Clinical Trial

IMPORTANCE

Prescriptions for antipsychotic medications continue to increase across many brain disorders, including off-label use in children and elderly individuals. Concerning animal and uncontrolled human data suggest antipsychotics are associated with change in brain structure, but to our knowledge, there are no controlled human studies that have yet addressed this question.

OBJECTIVE

To assess the effects of antipsychotics on brain structure in humans.

DESIGN, SETTING, AND PARTICIPANTS

Prespecified secondary analysis of a double-blind, randomized, placebo-controlled trial over a 36-week period at 5 academic centers. All participants, aged 18 to 85 years, were recruited from the multicenter Study of the Pharmacotherapy of Psychotic Depression II (STOP-PD II). All participants had major depressive disorder with psychotic features (psychotic depression) and were prescribed olanzapine and sertraline for a period of 12 to 20 weeks, which included 8 weeks of remission of psychosis and remission/near remission of depression. Participants were then were randomized to continue receiving this regimen or to be switched to placebo and sertraline for a subsequent 36-week period. Data were analyzed between October 2018 and February 2019.

INTERVENTIONS

Those who consented to the imaging study completed a magnetic resonance imaging (MRI) scan at the time of randomization and a second MRI scan at the end of the 36-week period or at time of relapse.

MAIN OUTCOMES AND MEASURES

The primary outcome measure was cortical thickness in gray matter and the secondary outcome measure was microstructural integrity of white matter.

RESULTS

Eighty-eight participants (age range, 18-85 years) completed a baseline scan; 75 completed a follow-up scan, of which 72 (32 men and 40 women) were useable for final analyses. There was a significant treatment-group by time interaction in cortical thickness (left, t = 3.3; P = .001; right, t = 3.6; P < .001) but not surface area. No significant interaction was found for fractional anisotropy, but one for mean diffusivity of the white matter skeleton was present (t = -2.6, P = .01). When the analysis was restricted to those who sustained remission, exposure to olanzapine compared with placebo was associated with significant decreases in cortical thickness in the left hemisphere (β [SE], 0.04 [0.009]; t34.4 = 4.7; P <.001), and the right hemisphere (β [SE], 0.03 [0.009]; t35.1 = 3.6; P <.001). Post hoc analyses showed that those who relapsed receiving placebo experienced decreases in cortical thickness compared with those who sustained remission.

CONCLUSIONS AND RELEVANCE

In this secondary analysis of a randomized clinical trial, antipsychotic medication was shown to change brain structure. This information is important for prescribing in psychiatric conditions where alternatives are present. However, adverse effects of relapse on brain structure support antipsychotic treatment during active illness.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT01427608.

Stress-Induced Microstructural Alterations Correlate With the Cognitive Performance of Rats: A Longitudinal in vivo Diffusion Tensor Imaging Study

Background: Stress-induced cellular changes in limbic brain structures contribute to the development of various psychopathologies. In vivo detection of these microstructural changes may help us to develop objective biomarkers for psychiatric disorders. Diffusion tensor imaging (DTI) is an advanced neuroimaging technique that enables the non-invasive examination of white matter integrity and provides insights into the microstructure of pathways connecting brain areas.

Objective: Our aim was to examine the temporal dynamics of stress-induced structural changes with repeated in vivo DTI scans and correlate them with behavioral alterations.

Methods: Out of 32 young adult male rats, 16 were exposed to daily immobilization stress for 3 weeks. Four DTI measurements were done: one before the stress exposure (baseline), two scans during the stress (acute and chronic phases), and a last one 2 weeks after the end of the stress protocol (recovery). We used a 4.7T small-animal MRI system and examined 18 gray and white matter structures calculating the following parameters: fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD). T2-weighted images were used for volumetry. Cognitive performance and anxiety levels of the animals were assessed in the Morris water maze, novel object recognition, open field, and elevated plus maze tests.

Results: Reduced FA and increased MD and RD values were found in the corpus callosum and external capsule of stressed rats. Stress increased RD in the anterior commissure and reduced MD and RD in the amygdala. We observed time-dependent changes in several DTI parameters as the rats matured, but we found no evidence of stress-induced volumetric alterations in the brains. Stressed rats displayed cognitive impairments and we found numerous correlations between the cognitive performance of the animals and between various DTI metrics of the inferior colliculus, corpus callosum, anterior commissure, and amygdala.

Conclusions: Our data provide further support to the translational value of DTI studies and suggest that chronic stress exposure results in similar white matter microstructural alterations that have been documented in stress-related psychiatric disorders. These DTI findings imply microstructural abnormalities in the brain, which may underlie the cognitive deficits that are often present in stress-related mental disorders.

Identificacion of MRI-based psychosis subtypes: Replication and refinement

The identification of the cerebral substrates of psychoses such as schizophrenia and bipolar disorder is likely hampered by its biological heterogeneity, which may contribute to the low replication of results in the field. In this study we aimed to replicate in a completely new sample and supplement the results of a previous study with additional data on this topic. In the aforementioned study we identified a schizophrenia cluster characterized by high mean cortical curvature and low cortical thickness, subcortical hypometabolism and progressive negative symptoms. Here, we have used magnetic resonance images from 61 schizophrenia and 28 bipolar patients, as well as 51 healthy controls and a cluster analysis to search for possible subgroups primarily characterized by cerebral structural data. Diffusion tensor imaging (fractional anisotropy, FA), cognition, clinical data and electroencephalographic (EEG) modulation during a P300 task were used to validate the possible clusters. Two clusters of patients were identified. The first cluster (29 schizophrenia and 18 bipolar patients) showed decreased cortical thickness and area values, as well as lower subcortical volumes and higher cortical curvature in some regions, as compared to the second cluster. This first cluster also showed decreased FA in frontal lobe connections and worse cognitive performance. Although this cluster also showed longer illness duration, there were first episode patients in both clusters and treatment doses and types were not different between clusters. Both clusters of patients showed decreased EEG task-related modulation. In conclusion, our data give additional support to a distinct biologically based cluster encompassing schizophrenia and bipolar disorder patients with cortical and subcortical alterations, hampered cortical connectivity and lower cognitive performance.

White matter microstructural organizations in patients with severe treatment-resistant schizophrenia: A diffusion tensor imaging study

Previous diffusion tensor imaging (DTI) studies have reported white matter alterations in patients with schizophrenia. Notably, one third of this population does not respond to first-line antipsychotics and is thus referred to as treatment-resistant schizophrenia (TRS). Despite potentially distinct neural bases between TRS and non-TRS, few studies have compared white matter integrity between these groups. In order to reflect clinical picture of TRS, we enrolled TRS patients who had severe symptoms. According to the consensus criteria for TRS. TRS was defined by severe positive symptomatology despite optimal antipsychotic treatment. Fractional anisotropy (FA), an index of white matter integrity, was examined by DTI and analyzed with tract-based spatial statistics in 24 TRS patients (mean PANSS = 108.9), 28 non-TRS patients (mean PANSS = 50.0), and 27 healthy controls (HCs) for group comparison. Additionally, correlation analyses were conducted between FA values and symptomatology. The TRS group had lower FA values in multiple tracts (cerebral peduncle, corona radiata, corpus callosum, external and internal capsules, posterior thalamic radiation, sagittal stratum, superior longitudinal fasciculus, tapetum, and uncinate fasciculus) compared to the HC group as well as the non-TRS group (p < .05; family-wise error-corrected), while no differences were found between the non-TRS and HC groups. In the TRS group, FA values in most of the tracts (other than the left anterior limb of internal capsule, left cerebral peduncle, and right uncinate fasciculus) were negatively correlated with the Positive and Negative Syndrome Scale total scores, and negative and general symptom scores. No such relationships were found in the non-TRS group. The identified white matter integrity deficits may reflect the pathophysiology of TRS.

Neuroimaging studies within Cognitive Genetics Collaborative Research Organization aiming to replicate and extend works of ENIGMA

Reproducibility is one of the most important issues for generalizing the results of clinical research; however, low reproducibility in neuroimaging studies is well known. To overcome this problem, the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) consortium, an international neuroimaging consortium, established standard protocols for imaging analysis and employs either meta‐ and mega‐analyses of psychiatric disorders with large sample sizes. The Cognitive Genetics Collaborative Research Organization (COCORO) in Japan promotes neurobiological studies in psychiatry and has successfully replicated and extended works of ENIGMA especially for neuroimaging studies. For example, (a) the ENIGMA consortium showed subcortical regional volume alterations in patients with schizophrenia (n = 2,028) compared to controls (n = 2,540) across 15 cohorts using meta‐analysis. COCORO replicated the volumetric changes in patients with schizophrenia (n = 884) compared to controls (n = 1,680) using the ENIGMA imaging analysis protocol and mega‐analysis. Furthermore, a schizophrenia‐specific leftward asymmetry for the pallidum volume was demonstrated; and (b) the ENIGMA consortium identified white matter microstructural alterations in patients with schizophrenia (n = 1,963) compared to controls (n = 2,359) across 29 cohorts. Using the ENIGMA protocol, a study from COCORO showed similar results in patients with schizophrenia (n = 696) compared to controls (n = 1,506) from 12 sites using mega‐analysis. Moreover, the COCORO study found that schizophrenia, bipolar disorder (n = 211) and autism spectrum disorder (n = 126), but not major depressive disorder (n = 398), share similar white matter microstructural alterations, compared to controls. Further replication and harmonization of the ENIGMA consortium and COCORO will contribute to the generalization of their research findings.

Abnormal Effective Connectivity Underlying Auditory Mismatch Negativity Impairments in Schizophrenia

BACKGROUND

Auditory mismatch negativity (MMN) is a translatable event-related potential biomarker, and its reduction in schizophrenia is associated with the severity of clinical symptoms. While MMN recorded at the scalp is generated by a distributed network of temporofrontal neural sources, the primary contributing sources and the dynamic interactions among sources underlying MMN impairments in schizophrenia have not been previously characterized.

METHODS

A novel data-driven analytic framework was applied to large cohorts of healthy comparison subjects (n = 449) and patients with schizophrenia (n = 589) to identify the independent contributing sources of MMN, characterize the patterns of effective connectivity underlying reduced MMN in patients, and explore the clinical significance of these abnormal source dynamics in schizophrenia.

RESULTS

A network of 11 independent contributing sources underlying MMN distributed across temporofrontal cortices was identified. Orderly shifts in peak source activity were detected in a steplike manner, starting at temporal structures and progressing across frontal brain regions. MMN reduction in patients was predominantly associated with reduced contributions from 3 frontal midline sources: orbitofrontal, anterior cingulate, and middle cingulate cortices. Patients showed increased connectivity from temporal to prefrontal regions in conjunction with decreased cross-hemispheric connectivity to prefrontal regions. The decreased connectivity strength of precentral to prefrontal regions in patients with schizophrenia was associated with greater severity of negative symptoms.

CONCLUSIONS

Alterations in the dynamic interactions among temporofrontal sources underlie MMN abnormalities in schizophrenia. These results advance our understanding of the neural substrates and temporal dynamics of normal and impaired information processing with novel applications for translatable biomarkers of neuropsychiatric disorders.

The Relationship Between White Matter Microstructure and General Cognitive Ability in Patients With Schizophrenia and Healthy Participants in the ENIGMA Consortium

OBJECTIVE

Schizophrenia has recently been associated with widespread white matter microstructural abnormalities, but the functional effects of these abnormalities remain unclear. Widespread heterogeneity of results from studies published to date preclude any definitive characterization of the relationship between white matter and cognitive performance in schizophrenia. Given the relevance of deficits in cognitive function to predicting social and functional outcomes in schizophrenia, the authors carried out a meta-analysis of available data through the ENIGMA Consortium, using a common analysis pipeline, to elucidate the relationship between white matter microstructure and a measure of general cognitive performance, IQ, in patients with schizophrenia and healthy participants.

METHODS

The meta-analysis included 760 patients with schizophrenia and 957 healthy participants from 11 participating ENIGMA Consortium sites. For each site, principal component analysis was used to calculate both a global fractional anisotropy component (gFA) and a fractional anisotropy component for six long association tracts (LA-gFA) previously associated with cognition.

RESULTS

Meta-analyses of regression results indicated that gFA accounted for a significant amount of variation in cognition in the full sample (effect size [Hedges' g]=0.27, CI=0.17-0.36), with similar effects sizes observed for both the patient (effect size=0.20, CI=0.05-0.35) and healthy participant groups (effect size=0.32, CI=0.18-0.45). Comparable patterns of association were also observed between LA-gFA and cognition for the full sample (effect size=0.28, CI=0.18-0.37), the patient group (effect size=0.23, CI=0.09-0.38), and the healthy participant group (effect size=0.31, CI=0.18-0.44).

CONCLUSIONS

This study provides robust evidence that cognitive ability is associated with global structural connectivity, with higher fractional anisotropy associated with higher IQ. This association was independent of diagnosis; while schizophrenia patients tended to have lower fractional anisotropy and lower IQ than healthy participants, the comparable size of effect in each group suggested a more general, rather than disease-specific, pattern of association.

Visual Cortical Alterations and their Association with Negative Symptoms in Antipsychotic-Naïve First Episode Psychosis

Visual perceptual and processing deficits are common in schizophrenia and possibly point towards visual pathway alterations. However, no studies have examined visual cortical morphology in first-episode psychosis (FEP). In an antipsychotic-naïve FEP population, we investigated primary visual (V1), association area (V2), and motion perception (V5/MT) morphology compared to controls. We found reductions in the V1 and V2 areas, greater MT area and lower MT thickness in the FEP-schizophrenia group when compared to controls. Also, lower MT thickness was associated with worse negative symptoms. Our results shed light on this poorly studied area of visual cortex morphology in FEP.

Relationship between white matter glucose metabolism and fractional anisotropy in healthy and schizophrenia subjects

Decreased fractional anisotropy and increased glucose utilization in the white matter have been reported in schizophrenia. These findings may be indicative of an inverse relationship between these measures of white matter integrity and metabolism. We used ¹⁸F-fluorodeoxyglucose positron emission tomography and diffusion-tensor imaging in 19 healthy and 25 schizophrenia subjects to assess and compare coterritorial correlation patterns between glucose utilization and fractional anisotropy on a voxel-by-voxel basis and across a range of automatically placed representative white matter regions of interest. We found a pattern of predominantly negative correlations between white matter metabolism and fractional anisotropy in both healthy and schizophrenia subjects. The overall strength of the relationship was attenuated in subjects with schizophrenia, who displayed significantly fewer and weaker correlations in all regions assessed with the exception of the corpus callosum. This attenuation was most prominent in the left prefrontal white matter and this region also best predicted the diagnosis of schizophrenia. There exists an inverse relationship between the measures of white matter integrity and metabolism, which may therefore be physiologically linked. In subjects with schizophrenia, hypermetabolism in the white matter may be a function of lower white matter integrity, with lower efficiency and increased energetic cost of task-related computations.

Exploring white matter microstructure and the impact of antipsychotics in adolescent-onset psychosis

White matter abnormalities are well-established in adult patients with psychosis. Less is known about abnormalities in the rarely occurring adolescent early onset psychosis (EOP). In particular, whether antipsychotic medication might impact white matter microstructure is not known. Using 3T diffusion weighted imaging, we investigated differences in white matter microstructure and the impact of antipsychotic medication status in medicated (n = 11) and unmedicated (n = 11) EOP patients relative to healthy controls (n = 33), aged between 12–18 years. Using Tract-based Spatial Statistics, we calculate case-control differences in scalar diffusion measures, i.e. fractional anisotropy (FA), axial diffusion (AD) and radial diffusion (RD), and investigated their association with antipsychotic medication in patients. We found significantly lower FA in the left genu of the corpus callosum, the left anterior corona radiata (ACR) and the right superior longitudinal fasciculus in EOP patients relative to healthy controls. AD values were also lower in the left ACR, largely overlapping with the FA findings. Mean FA in the left ACR was significantly associated with antipsychotic medication status (Cohen's d = 1.37, 95% CI [0.01, 2.68], p = 0.008), showing higher FA values in medicated compared to unmedicated EOP patients. The present study is the first to link antipsychotic medication status to altered regional FA in the left ACR, a region hypothesized to contribute to the etiology of psychosis. Replications are warranted to draw firm conclusions about putatively enhancing effects of antipsychotic medication on white matter microstructure in adolescent-onset psychosis.

The ENIGMA-Epilepsy working group: Mapping disease from large data sets

Epilepsy is a common and serious neurological disorder, with many different constituent conditions characterized by their electro clinical, imaging, and genetic features. MRI has been fundamental in advancing our understanding of brain processes in the epilepsies. Smaller-scale studies have identified many interesting imaging phenomena, with implications both for understanding pathophysiology and improving clinical care. Through the infrastructure and concepts now well-established by the ENIGMA Consortium, ENIGMA-Epilepsy was established to strengthen epilepsy neuroscience by greatly increasing sample sizes, leveraging ideas and methods established in other ENIGMA projects, and generating a body of collaborating scientists and clinicians to drive forward robust research. Here we review published, current, and future projects, that include structural MRI, diffusion tensor imaging (DTI), and resting state functional MRI (rsfMRI), and that employ advanced methods including structural covariance, and event-based modeling analysis. We explore age of onset- and duration-related features, as well as phenomena-specific work focusing on particular epilepsy syndromes or phenotypes, multimodal analyses focused on understanding the biology of disease progression, and deep learning approaches. We encourage groups who may be interested in participating to make contact to further grow and develop ENIGMA-Epilepsy.

Translating ENIGMA schizophrenia findings using the regional vulnerability index: Association with cognition, symptoms, and disease trajectory

Patients with schizophrenia have patterns of brain deficits including reduced cortical thickness, subcortical gray matter volumes, and cerebral white matter integrity. We proposed the regional vulnerability index (RVI) to translate the results of Enhancing Neuro Imaging Genetics Meta-Analysis studies to the individual level. We calculated RVIs for cortical, subcortical, and white matter measurements and a multimodality RVI. We evaluated RVI as a measure sensitive to schizophrenia-specific neuroanatomical deficits and symptoms and studied the timeline of deficit formations in: early (≤5 years since diagnosis, N = 45, age = 28.8 ± 8.5); intermediate (6-20 years, N = 30, age 43.3 ± 8.6); and chronic (21+ years, N = 44, age = 52.5 ± 5.2) patients and healthy controls (N = 76, age = 38.6 ± 12.4). All RVIs were significantly elevated in patients compared to controls, with the multimodal RVI showing the largest effect size, followed by cortical, white matter and subcortical RVIs (d = 1.57, 1.23, 1.09, and 0.61, all p < 10^-6 ). Multimodal RVI was significantly correlated with multiple cognitive variables including measures of visual learning, working memory and the total score of the MATRICS consensus cognitive battery, and with negative symptoms. The multimodality and white matter RVIs were significantly elevated in the intermediate and chronic versus early diagnosis group, consistent with ongoing progression. Cortical RVI was stable in the three disease-duration groups, suggesting neurodevelopmental origins of cortical deficits. In summary, neuroanatomical deficits in schizophrenia affect the entire brain; the heterochronicity of their appearance indicates both the neurodevelopmental and progressive nature of this illness. These deficit patterns may be useful for early diagnosis and as quantitative targets for more effective treatment strategies aiming to alter these neuroanatomical deficit patterns.

Cerebral white matter changes in deficit and non-deficit subtypes of schizophrenia

The considerable clinical heterogeneity in schizophrenia makes elucidation of its neurobiology challenging. Subtyping the disorder is one way to reduce this heterogeneity and deficit status is one such categorization based on the prominence of negative symptoms. We aimed to utilize diffusion tensor imaging (DTI) to identify unique white matter cerebral changes in deficit schizophrenia (DS) compared with non-deficit schizophrenia (NDS) and healthy controls (HC) in an Asian sample. A total of 289 subjects (111 HC, 133 NDS and 45 DS) underwent DTI and completed rating scales which assessed the severity of psychopathology, psychosocial functioning and premorbid intelligence.We found that DS patients had fractional anisotropy (FA) reductions in the Body of the Corpus Callosum (BCC) and right Posterior Thalamic Radiation (PTR) regions relative to HCs, and FA reductions in the right PTR relative to NDS patients. NDS patients had FA reductions of the BCC and right PTR relative to HCs. Binomial logistic regression analyses revealed that FA reductions of the right PTR FA was an independent predictor of deficit status. The identified brain white matter changes especially in the PTR relate to deficits of cognitive control and emotional awareness, which may underlie psychopathology associated with deficit status like inattention and affective blunting. These potential biomarkers of DS warrant further examination to determine their utility for monitoring illness progression and intervention response in schizophrenia.

Anti-PDHA1 antibody is detected in a subset of patients with schizophrenia

Autoantibodies have been implicated in schizophrenia aetiology. Here, novel autoantibodies were isolated from patients with schizophrenia. Autoantibody candidates were searched using two-dimensional gel electrophoresis and western blotting with rat brain proteins as antigens and two sera pools (25 schizophrenia patients versus 25 controls) as antibodies. Immunoreactive antigens were identified by mass spectrometry. Antibody prevalence were evaluated by western blotting using human recombinant proteins. Furthermore, brain magnetic resonance imaging data (regional brain volumes and diffusion tensor imaging measures) were compared. Two proteins of the mitochondrial respiration pathway were identified as candidate antigens. Three patients with schizophrenia, but no controls, expressed antibodies targeting one of the candidate antigens, i.e., pyruvate dehydrogenase E1 component subunit alpha, somatic form, mitochondrial (PDHA1, EC 1.2.4.1), which is related to mitochondrial energy production. Anti-PDHA1 antibody-positive patients (n = 3) had increased volumes in the left occipital fusiform gyrus compared to both controls (n = 23, p = 0.017) and antibody-negative patients (n = 16, p = 0.009), as well as in the left cuneus compared to antibody-negative patients (n = 16, p = 0.018). This is the first report of an anti-PDHA1 antibody in patients with schizophrenia. Compatible with recent findings of mitochondrial dysfunction in schizophrenia, this antibody may be involved in the pathogenesis of a specific subgroup of schizophrenia.

Common gray and white matter abnormalities in schizophrenia and bipolar disorder

This study aimed to investigate abnormalities in the gray matter and white matter (GM and WM, respectively) that are shared between schizophrenia (SZ) and bipolar disorder (BD). We used 3T-magnetic resonance imaging to examine patients with SZ, BD, or healthy control (HC) subjects (aged 20–50 years, N = 65 in each group). We generated modulated GM maps through voxel-based morphometry (VBM) for T1-weighted images and skeletonized fractional anisotropy, mean diffusion, and radial diffusivity maps through tract-based special statistics (TBSS) methods for diffusion tensor imaging (DTI) data. These data were analyzed using a generalized linear model with pairwise comparisons between groups with a family-wise error corrected P < 0.017. The VBM analysis revealed widespread decreases in GM volume in SZ compared to HC, but patients with BD showed GM volume deficits limited to the right thalamus and left insular lobe. The TBSS analysis showed alterations of DTI parameters in widespread WM tracts both in SZ and BD patients compared to HC. The two disorders had WM alterations in the corpus callosum, superior longitudinal fasciculus, internal capsule, external capsule, posterior thalamic radiation, and fornix. However, we observed no differences in GM volume or WM integrity between SZ and BD. The study results suggest that GM volume deficits in the thalamus and insular lobe along with widespread disruptions of WM integrity might be the common neural mechanisms underlying the pathologies of SZ and BD.

Harmonization of Brain Diffusion MRI: Concepts and Methods

MRI diffusion data suffers from significant inter- and intra-site variability, which hinders multi-site and/or longitudinal diffusion studies. This variability may arise from a range of factors, such as hardware, reconstruction algorithms and acquisition settings. To allow a reliable comparison and joint analysis of diffusion data across sites and over time, there is a clear need for robust data harmonization methods. This review article provides a comprehensive overview of diffusion data harmonization concepts and methods, and their limitations. Overall, the methods for the harmonization of multi-site diffusion images can be categorized in two main groups: diffusion parametric map harmonization (DPMH) and diffusion weighted image harmonization (DWIH). Whereas DPMH harmonizes the diffusion parametric maps (e.g., FA, MD, and MK), DWIH harmonizes the diffusion-weighted images. Defining a gold standard harmonization technique for dMRI data is still an ongoing challenge. Nevertheless, in this paper we provide two classification tools, namely a feature table and a flowchart, which aim to guide the readers in selecting an appropriate harmonization method for their study.

Psychotic-like experiences, polygenic risk scores for schizophrenia, and structural properties of the salience, default mode, and central-executive networks in healthy participants from UK Biobank

Schizophrenia is a highly heritable disorder with considerable phenotypic heterogeneity. Hallmark psychotic symptoms can be considered as existing on a continuum from non-clinical to clinical populations. Assessing genetic risk and psychotic-like experiences (PLEs) in non-clinical populations and their associated neurobiological underpinnings can offer valuable insights into symptom-associated brain mechanisms without the potential confounds of the effects of schizophrenia and its treatment. We leveraged a large population-based cohort (UKBiobank, N = 3875) including information on PLEs (obtained from the Mental Health Questionnaire (MHQ); UKBiobank Category: 144; N auditory hallucinations = 55, N visual hallucinations = 79, N persecutory delusions = 16, N delusions of reference = 13), polygenic risk scores for schizophrenia (PRSSZ) and multi-modal brain imaging in combination with network neuroscience. Morphometric (cortical thickness, volume) and water diffusion (fractional anisotropy) properties of the regions and pathways belonging to the salience, default-mode, and central-executive networks were computed. We hypothesized that these anatomical concomitants of functional dysconnectivity would be negatively associated with PRSSZ and PLEs. PRSSZ was significantly associated with a latent measure of cortical thickness across the salience network (r = -0.069, p = 0.010) and PLEs showed a number of significant associations, both negative and positive, with properties of the salience and default mode networks (involving the insular cortex, supramarginal gyrus, and pars orbitalis, pFDR < 0.050); with the cortical thickness of the insula largely mediating the relationship between PRSSZ and auditory hallucinations. Generally, these results are consistent with the hypothesis that higher genetic liability for schizophrenia is related to subtle disruptions in brain structure and may predispose to PLEs even among healthy participants. In addition, our study suggests that networks engaged during auditory hallucinations show structural associations with PLEs in the general population.

Scanner invariant representations for diffusion MRI harmonization

Purpose

In the present work, we describe the correction of diffusion‐weighted MRI for site and scanner biases using a novel method based on invariant representation.

Theory and Methods

Pooled imaging data from multiple sources are subject to variation between the sources. Correcting for these biases has become very important as imaging studies increase in size and multi‐site cases become more common. We propose learning an intermediate representation invariant to site/protocol variables, a technique adapted from information theory‐based algorithmic fairness; by leveraging the data processing inequality, such a representation can then be used to create an image reconstruction that is uninformative of its original source, yet still faithful to underlying structures. To implement this, we use a deep learning method based on variational auto‐encoders (VAE) to construct scanner invariant encodings of the imaging data.

Results

To evaluate our method, we use training data from the 2018 MICCAI Computational Diffusion MRI (CDMRI) Challenge Harmonization dataset. Our proposed method shows improvements on independent test data relative to a recently published baseline method on each subtask, mapping data from three different scanning contexts to and from one separate target scanning context.

Conclusions

As imaging studies continue to grow, the use of pooled multi‐site imaging will similarly increase. Invariant representation presents a strong candidate for the harmonization of these data.

Overdispersed gene expression in schizophrenia

Schizophrenia (SCZ) is a severe, highly heterogeneous psychiatric disorder with varied clinical presentations. The polygenic genetic architecture of SCZ makes identification of causal variants a daunting task. Gene expression analyses hold the promise of revealing connections between dysregulated transcription and underlying variants in SCZ. However, the most commonly used differential expression analysis often assumes grouped samples are from homogeneous populations and thus cannot be used to detect expression variance differences between samples. Here, we applied the test for equality of variances to normalized expression data, generated by the CommonMind Consortium (CMC), from brains of 212 SCZ and 214 unaffected control (CTL) samples. We identified 87 genes, including VEGFA (vascular endothelial growth factor) and BDNF (brain-derived neurotrophic factor), that showed a significantly higher expression variance among SCZ samples than CTL samples. In contrast, only one gene showed the opposite pattern. To extend our analysis to gene sets, we proposed a Mahalanobis distance-based test for multivariate homogeneity of group dispersions, with which we identified 110 gene sets with a significantly higher expression variability in SCZ, including sets of genes encoding phosphatidylinositol 3-kinase (PI3K) complex and several others involved in cerebellar cortex morphogenesis, neuromuscular junction development, and cerebellar Purkinje cell layer development. Taken together, our results suggest that SCZ brains are characterized by overdispersed gene expression-overall gene expression variability among SCZ samples is significantly higher than that among CTL samples. Our study showcases the application of variability-centric analyses in SCZ research.

Additive Burden of Abnormal Diffusivity in the Brain with Schizophrenia: A Diffusion Tensor Imaging Study with Public Neuroimaging Data

OBJECTIVE

Diffusion tensor imaging has been extensively applied to schizophrenia research. In this study, we counted the number of abnormal brain regions with altered diffusion measures in patients with schizophrenia to enumerate the burden of abnormal diffusivity in the brain.

METHODS

The public neuroimaging data of the COBRE project from SchizConnect were used for the study. The studied dataset consisted of data from 57 patients with schizophrenia and 71 healthy participants. FreeSurfer and FSL were applied for image processing and analysis. After verifying 161 regions of interest (ROIs), mean diffusion measures in every single ROI in all study participants were measured and normalized into Z-scores. Each ROI was then defined as normal or abnormal on the basis of a cutoff absolute Z-score of 1.96. The number of abnormal ROIs was obtained by each diffusion measure.

RESULTS

The numbers of ROIs with increased radial diffusivity and increased trace were significantly larger in the patient group than in healthy participants.

CONCLUSION

Thus, the patient group showed a significant increase in abnormal ROIs, strongly indicating that schizophrenia is not caused by the pathology of a single brain region, but is instead attributable to the additive burden of structural alterations within multiple brain regions.

Polygenic disruption of retinoid signalling in schizophrenia and a severe cognitive deficit subtype

Retinoid metabolites of vitamin A are intrinsically linked to neural development, connectivity and plasticity, and have been implicated in the pathophysiology of schizophrenia. We hypothesised that a greater burden of common and rare genomic variation in genes involved with retinoid biogenesis and signalling could be associated with schizophrenia and its cognitive symptoms. Common variants associated with schizophrenia in the largest genome-wide association study were aggregated in retinoid genes and used to formulate a polygenic risk score (PRSRet) for each participant in the Australian Schizophrenia Research Bank. In support of our hypothesis, we found PRSRet to be significantly associated with the disorder. Cases with severe cognitive deficits, while not further differentiated by PRSRet, were enriched with rare variation in the retinoic acid receptor beta gene RARB, detected through whole-genome sequencing. RARB rare variant burden was also associated with reduced cerebellar volume in the cases with marked cognitive deficit, and with covariation in grey matter throughout the brain. An excess of rare variation was further observed in schizophrenia in retinoic acid response elements proximal to target genes, which we show are differentially expressed in the disorder in two RNA sequencing datasets. Our results suggest that genomic variation may disrupt retinoid signalling in schizophrenia, with particular significance for cases with severe cognitive impairment.

Cingulum and abnormal psychological stress response in schizophrenia

Stress is implicated in many aspects of schizophrenia, including heightened distress intolerance. We examined how affect and microstructure of major brain tracts involved in regulating affect may contribute to distress intolerance in schizophrenia. Patients with schizophrenia spectrum disorders (n = 78) and community controls (n = 95) completed diffusion weighted imaging and performed psychological stress tasks. Subjective affect was collected pre and post stressors. Individuals who did not persist during one or both stress tasks were considered distress intolerant (DI), and otherwise distress tolerant (DT). Fractional anisotropy (FA) of the dorsal cingulum showed a significant diagnosis x DT/DI phenotype interaction (p = 0.003). Post-hoc tests showed dorsal cingulum FA was significantly lower in DI patients compared with DI controls (p < 0.001), but not different between DT groups (p = 0.27). Regarding affect responses to stress, irritability showed the largest stress-related change (p < 0.001), but irritability changes were significantly reduced in DI patients compared to DI controls (p = 0.006). The relationship between irritability change and performance errors also differed among patients (ρ = -0.29, p = 0.011) and controls (ρ = 0.21, p = 0.042). Further modeling highlighted the explanatory power of dorsal cingulum for predicting DI even after performance and irritability were taken into account. Distress intolerance during psychological stress exposure is related to microstructural properties of the dorsal cingulum, a key structure for cognitive control and emotion regulation. In schizophrenia, the affective response to psychological stressors is abnormal, and distress intolerant patients had significantly reduced dorsal cingulum FA compared to distress intolerant controls. The findings provide new insight regarding distress intolerance in schizophrenia.

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.

The anterior limb of the internal capsule: Anatomy, function, and dysfunction

The last two decades have seen a re-emergence of neurosurgery for severe, refractory psychiatric diseases, largely due to the advent of more precise and safe operative techniques. Nevertheless, the optimal targets for these surgeries remain a matter of debate, and are often grandfathered from experiences in the late 20th century. To better explore the rationale for one target in particular - the anterior limb of the internal capsule (ALIC) - we comprehensively reviewed all available literature on its role in the pathophysiology and treatment of mental illness. We first provide an overview of its functional anatomy, followed by a discussion on its role in several prevalent psychiatric diseases. Given its structural integration into the limbic system and involvement in a number of cognitive and emotional processes, the ALIC is a robust target for surgical treatment of refractory psychiatric diseases. The advent of novel neuroimaging techniques, coupled with image-guided therapeutics and neuromodulatory treatments, will continue to enable study on the ALIC in mental illness.

Schizophrenia research in the era of Team Science and big data

The last decade has provided new insights into the genetic architecture of schizophrenia. For the first time researchers have identified genetic factors conferring risk that can be mapped to tissue and cell specific perturbations of the molecular machinery underlying disease processes. However, it has also become clear that attempts to gain mechanistic insights into disease processes that span multiple levels of biological complexity, from genes to cells to circuits to behaviors, are inherently difficult and will require interdisciplinary efforts. Here we discuss the opportunities and pitfalls of developing causal models of SCZ that will lead to novel treatments and prevention strategies. We make the case that integrated large-scale Team Science efforts will be necessary to achieve this goal and that a systems level approach that includes genetics and integrative modelling is needed.