Patterns of white matter microstructure in individuals at ultra-high-risk for psychosis: associations to level of functioning and clinical symptoms

Multivariate brain-behaviour associations in psychiatric disorders

Mapping brain-behaviour associations is paramount to understand and treat psychiatric disorders. Standard approaches involve investigating the association between one brain and one behavioural variable (univariate) or multiple variables against one brain/behaviour feature ('single' multivariate). Recently, large multimodal datasets have propelled a new wave of studies that leverage on 'doubly' multivariate approaches capable of parsing the multifaceted nature of both brain and behaviour simultaneously. Within this movement, canonical correlation analysis (CCA) and partial least squares (PLS) emerge as the most popular techniques. Both seek to capture shared information between brain and behaviour in the form of latent variables. We provide an overview of these methods, review the literature in psychiatric disorders, and discuss the main challenges from a predictive modelling perspective. We identified 39 studies across four diagnostic groups: attention deficit and hyperactive disorder (ADHD, k = 4, N = 569), autism spectrum disorders (ASD, k = 6, N = 1731), major depressive disorder (MDD, k = 5, N = 938), psychosis spectrum disorders (PSD, k = 13, N = 1150) and one transdiagnostic group (TD, k = 11, N = 5731). Most studies (67%) used CCA and focused on the association between either brain morphology, resting-state functional connectivity or fractional anisotropy against symptoms and/or cognition. There were three main findings. First, most diagnoses shared a link between clinical/cognitive symptoms and two brain measures, namely frontal morphology/brain activity and white matter association fibres (tracts between cortical areas in the same hemisphere). Second, typically less investigated behavioural variables in multivariate models such as physical health (e.g., BMI, drug use) and clinical history (e.g., childhood trauma) were identified as important features. Finally, most studies were at risk of bias due to low sample size/feature ratio and/or in-sample testing only. We highlight the importance of carefully mitigating these sources of bias with an exemplar application of CCA.

White matter microstructural abnormalities in individuals with attenuated positive symptom syndromes

White matter (WM) microstructural alterations have been extensively studied in patients with psychosis, but research on the microstructure of WM in individuals with attenuated positive symptom syndrome (APSS) is currently limited. To improve the understanding of the neuropathology in APSS, this study investigated the WM of individuals with APSS using diffusion tensor and T1-weighted imaging. Automated fiber quantification was used to calculate the diffusion index values along the trajectories of 20 major fiber tracts in 42 individuals with APSS and 51 age-and sex-matched healthy control (HC) individuals. The diffusion index values in each of fiber tracts were compared node-by-node between the 2 groups. Compared with the HC group, the APSS group showed differences in the diffusion index values in partial segments of the callosum forceps minor, left and right cingulum cingulate, inferior fronto-occipital fasciculus, right corticospinal tract, left superior longitudinal fasciculus, and arcuate fasciculus. Notably, in the APSS group positive associations were found between the axial diffusivity values of the partial nodes of the left and right cingulum cingulate and the current Global Assessment of Functioning scores, as well as between the axial diffusivity values of the partial nodes of the right corticospinal tract and negative symptoms scores and reasoning and problem-solving scores. These findings suggest that individuals with APSS exhibit reduced WM integrity or possible impaired myelin in certain segments of WM tracts involved in the frontal- and limbic-cortical connections. Additionally, abnormal WM tracts appear to be associated with impaired general function and neurocognitive function. This study provides important new insights into the neurobiology of APSS and highlights potential targets for future intervention and treatment.

A Review of Potential Neuroimaging Biomarkers of Schizophrenia-Risk

The risk for developing schizophrenia is increased among first-degree relatives of those with psychotic disorders, but the risk is even higher in those meeting established criteria for clinical high risk (CHR), a clinical construct most often comprising of attenuated psychotic experiences. Conversion to psychosis among CHR youth has been reported to be about 15-35% over three years. Accurately identifying individuals whose psychotic symptoms will worsen would facilitate earlier intervention, but this has been difficult to do using behavior measures alone. Brain-based risk markers have the potential to improve the accuracy of predicting outcomes in CHR youth. This narrative review provides an overview of neuroimaging studies used to investigate psychosis risk, including studies involving structural, functional, and diffusion imaging, functional connectivity, positron emission tomography, arterial spin labeling, magnetic resonance spectroscopy, and multi-modality approaches. We present findings separately in those observed in the CHR state and those associated with psychosis progression or resilience. Finally, we discuss future research directions that could improve clinical care for those at high risk for developing psychotic disorders.

Identification of Homogeneous Subgroups from Resting-State fMRI Data

The identification of homogeneous subgroups of patients with psychiatric disorders can play an important role in achieving personalized medicine and is essential to provide insights for understanding neuropsychological mechanisms of various mental disorders. The functional connectivity profiles obtained from functional magnetic resonance imaging (fMRI) data have been shown to be unique to each individual, similar to fingerprints; however, their use in characterizing psychiatric disorders in a clinically useful way is still being studied. In this work, we propose a framework that makes use of functional activity maps for subgroup identification using the Gershgorin disc theorem. The proposed pipeline is designed to analyze a large-scale multi-subject fMRI dataset with a fully data-driven method, a new constrained independent component analysis algorithm based on entropy bound minimization (c-EBM), followed by an eigenspectrum analysis approach. A set of resting-state network (RSN) templates is generated from an independent dataset and used as constraints for c-EBM. The constraints present a foundation for subgroup identification by establishing a connection across the subjects and aligning subject-wise separate ICA analyses. The proposed pipeline was applied to a dataset comprising 464 psychiatric patients and discovered meaningful subgroups. Subjects within the identified subgroups share similar activation patterns in certain brain areas. The identified subgroups show significant group differences in multiple meaningful brain areas including dorsolateral prefrontal cortex and anterior cingulate cortex. Three sets of cognitive test scores were used to verify the identified subgroups, and most of them showed significant differences across subgroups, which provides further confirmation of the identified subgroups. In summary, this work represents an important step forward in using neuroimaging data to characterize mental disorders.

Identification of texture MRI brain abnormalities on first-episode psychosis and clinical high-risk subjects using explainable artificial intelligence

Structural MRI studies in first-episode psychosis and the clinical high-risk state have consistently shown volumetric abnormalities. Aim of the present study was to introduce radiomics texture features in identification of psychosis. Radiomics texture features describe the interrelationship between voxel intensities across multiple spatial scales capturing the hidden information of underlying disease dynamics in addition to volumetric changes. Structural MR images were acquired from 77 first-episode psychosis (FEP) patients, 58 clinical high-risk subjects with no later transition to psychosis (CHR_NT), 15 clinical high-risk subjects with later transition (CHR_T), and 44 healthy controls (HC). Radiomics texture features were extracted from non-segmented images, and two-classification schemas were performed for the identification of FEP vs. HC and FEP vs. CHR_NT. The group of CHR_T was used as external validation in both schemas. The classification of a subject's clinical status was predicted by importing separately (a) the difference of entropy feature map and (b) the contrast feature map, resulting in classification balanced accuracy above 72% in both analyses. The proposed framework enhances the classification decision for FEP, CHR_NT, and HC subjects, verifies diagnosis-relevant features and may potentially contribute to identification of structural biomarkers for psychosis, beyond and above volumetric brain changes.

White matter microstructure and sleep-wake disturbances in individuals at ultra-high risk of psychosis

Aim

White matter changes in individuals at ultra-high risk for psychosis (UHR) may be involved in the transition to psychosis. Sleep-wake disturbances commonly precede the first psychotic episode and predict development of psychosis. We examined associations between white matter microstructure and sleep-wake disturbances in UHR individuals compared to healthy controls (HC), as well as explored the confounding effect of medication, substance use, and level of psychopathology.

Methods

Sixty-four UHR individuals and 35 HC underwent clinical interviews and diffusion weighted imaging. Group differences on global and callosal mean fractional anisotropy (FA) was tested using general linear modeling. Sleep-wake disturbances were evaluated using the subjective measures disturbed sleep index (DSI) and disturbed awakening index (AWI) from the Karolinska Sleep Questionnaire, supported by objective sleep measures from one-night actigraphy. The primary analyses comprised partial correlation analyses between global FA/callosal FA and sleep-wake measures. Secondary analyses investigated multivariate patterns of covariance between measures of sleep-wake disturbances and FA in 48 white matter regions of interest using partial least square correlations.

Results

Ultra-high risk for psychosis individuals displayed lower global FA (F = 14.56, p < 0.001) and lower callosal FA (F = 11.34, p = 0.001) compared to HC. Subjective sleep-wake disturbances were significantly higher among the UHR individuals (DSI: F = 27.59, p < 0.001, AWI: F = 36.42, p < 0.001). Lower callosal FA was correlated with increased wake after sleep onset (r = -0.34, p = 0.011) and increased sleep fragmentation index (r = -0.31, p = 0.019) in UHR individuals. Multivariate analyses identified a pattern of covariance in regional FA which were associated with DSI and AWI in UHR individuals (p = 0.028), but not in HC. Substance use, sleep medication and antipsychotic medication did not significantly confound these associations. The association with objective sleep-wake measures was sustained when controlling for level of depressive and UHR symptoms, but symptom level confounded the covariation between FA and subjective sleep-wake measures in the multivariate analyses.

Conclusion

Compromised callosal microstructure in UHR individuals was related to objectively observed disruptions in sleep-wake functioning. Lower FA in ventrally located regions was associated with subjectively measured sleep-wake disturbances and was partly explained by psychopathology. These findings call for further investigation of sleep disturbances as a potential treatment target.

White matter microstructure and the clinical risk for psychosis: A diffusion tensor imaging study of individuals with basic symptoms and at ultra-high risk

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This DTI cross-sectional study compared UHR, basic symptom & control groups (n = 112).

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The splenium of UHR individuals exhibited differences in fractional anisotropy (FA).

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Basic symptoms alone were not associated with white matter microstructure changes.

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Large differences in FA & radial diffusivity were found in converters to psychosis.

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Regional FA was inversely correlated with the general psychopathology domain.

Background

Widespread white matter abnormalities are a frequent finding in chronic schizophrenia patients. More inconsistent results have been provided by the sparser literature on at-risk states for psychosis, i.e., emerging subclinical symptoms. However, considering risk as a homogenous construct, an approach of earlier studies, may impede our understanding of neuro-progression into psychosis.

Methods

An analysis was conducted of 3-Tesla MRI diffusion and symptom data from 112 individuals (mean age, 21.97 ± 4.19) within two at-risk paradigm subtypes, only basic symptoms (n = 43) and ultra-high risk (n = 37), and controls (n = 32). Between-group comparisons (involving three study groups and further split based on the subsequent transition to schizophrenia) of four diffusion-tensor-imaging-derived scalars were performed using voxelwise tract-based spatial statistics, followed by correlational analyses with Structured Interview for Prodromal Syndromes responses.

Results

Relative to controls, fractional anisotropy was lower in the splenium of the corpus callosum of ultra-high-risk individuals, but only before stringent multiple-testing correction, and negatively correlated with General Symptom severity among at-risk individuals. At-risk participants who transitioned to schizophrenia within 3 years, compared to those that did not transition, had more severe WM differences in fractional anisotropy and radial diffusivity (particularly in the corpus callosum, anterior corona radiata, and motor/sensory tracts), which were even more extensive compared to healthy controls.

Conclusions

These findings align with the subclinical symptom presentation and more extensive disruptions in converters, suggestive of severity-related demyelination or axonal pathology. Fine-grained but detectable differences among ultra-high-risk subjects (i.e., with brief limited intermittent and/or attenuated psychotic symptoms) point to the splenium as a discrete site of emerging psychopathology, while basic symptoms alone were not associated with altered fractional anisotropy.

Different patterns of association between white matter microstructure and plasma unsaturated fatty acids in those with high risk for psychosis and healthy participants

Background

Disrupted white matter (WM) microstructure has been commonly identified in youth at clinical high risk (CHR) for psychosis. Several lines of evidence suggest that fatty acids, especially unsaturated fatty acids (UFAs), might play a crucial role in the WM pathology of early onset psychosis. However, evidence linking UFA and WM microstructure in CHR is quite sparse.

Aims

We investigated the relationship between the plasma UFA level and WM microstructure in CHR participants and healthy controls (HC).

Methods

Plasma fatty acids were assessed and diffusion tensor imaging (DTI) data were performed with tract-based spatial statistics (TBSS) analysis for 66 individuals at CHR for psychosis and 70 HC.

Results

Both the global and regional diffusion measures showed significant between-group differences, with decreased fractional anisotropy (FA) but increased mean diffusivity (MD) and radial diffusivity (RD) found in the CHR group compared with the HC group. On top of that, we found that in the HC group, plasma arachidic acid showed obvious trend-level associations with higher global FA, lower global MD and lower global RD, which regionally spread over the corpus callosum, right anterior and superior corona radiata, bilateral anterior and posterior limb of the internal capsule, and bilateral superior longitudinal fasciculus. However, there were no associations between global WM measures and any UFA in the CHR group. Conversely, we even found negative associations between arachidic acid levels and regional FA values in the right superior longitudinal fasciculus and right retrolenticular part of the internal capsule in the CHR group.

Conclusions

Compared with the HC group, CHR subjects exhibited a different pattern of association between WM microstructure and plasma UFA, with a neuroprotective effect found in the HC group but not in the CHR group. Such discrepancy could be due to the excessively upregulated UFAs accumulated in the plasma of the CHR group, highlighting the role of balanced plasma-membrane fatty acids homeostasis in WM development.

Changes in negative symptoms are linked to white matter changes in superior longitudinal fasciculus in individuals at ultra-high risk for psychosis

AIM

Growing evidence suggests that subtle white matter (WM) alterations are associated with psychopathology in individuals at ultra-high risk for psychosis (UHR). However, the longitudinal relationship between symptom progression and WM changes over time remains under-explored. Here, we examine associations between changes in clinical symptoms and changes in WM over six months in a large UHR-cohort.

METHODS

110 UHR-individuals and 59 healthy controls underwent diffusion weighted imaging at baseline and after six months. Group × time effects on fractional anisotropy (FA) were tested globally and in four predefined regions of interest (ROIs) bilaterally using linear modelling with repeated measures. Correlations between the changes in clinical symptoms and FA changes in the ROIs were examined with Pearson's correlation. A partial least squares correlation-technique (PLS-C) explored multivariate associations between patterns of changes in psychopathology, regional FA and additional WM indices.

RESULTS

At baseline, UHR-individuals displayed significantly lower FA globally (p = 0.018; F = 12.274), in right superior longitudinal fasciculus (p = 0.02; Adj R² = 0.07) and in left uncinate fasciculus (p = 0.048; Adj R² = 0.058) compared to controls (corrected). We identified a group × time interaction in global FA and right superior longitudinal fasciculus, but the finding did not survive multiple comparisons. However, an increase of negative symptoms in UHR-individuals correlated with FA increase in right superior longitudinal fasciculus (p = 0.048, corrected, r = 0.357), and this finding was supported by the multivariate PLS-C.

CONCLUSION

We found a positive correlation with a moderate effect between change in negative symptoms and FA change over 6 months in right superior longitudinal fasciculus. This link appeared mainly to reflect a subgroup of UHR-individuals, which already at baseline presented as vulnerable.

Social functioning and brain imaging in individuals at clinical high-risk for psychosis: A systematic review

Impairments in social functioning are a core impairment in psychosis and are associated with poor outcomes. These deficits are found in those at clinical high-risk (CHR) for psychosis, and can persist even in the absence of transition. However, the neurobiological underpinnings of social functioning remain unclear, therefore we conducted a systematic review of brain metrics that have been associated with social functioning in youth at CHR for psychosis. Five databases (MEDLINE, CINAHL, EBM reviews, Embase, and PsycINFO) were searched from inception to May 5, 2020. Studies were selected if they examined brain imaging, and social functioning in youth at CHR for psychosis. Of the 9629 citations found through online database searching, 12 studies with 696 CHR participants met inclusion criteria. Too few studies were focused on the same brain region using the same methodology to perform a meta-analysis, however, loci within the prefrontal cortex were most often associated with social functioning. Few studies have linked social functioning to brain imaging metrics, suggesting that future work should focus on this relationship.

Disturbances in White Matter Integrity in the Ultra-High-Risk Psychosis State-A Systematic Review

Schizophrenia is a severe and disabling mental illness whose etiology still remains unclear. The available literature indicates that there exist white matter (WM) abnormalities in people with schizophrenia spectrum disorders. Recent developments in modern neuroimaging methods have enabled the identification of the structure, morphology, and function of the underlying WM fibers in vivo. The purpose of this paper is to review the existing evidence about WM abnormalities in individuals at ultra-high risk of psychosis (UHR) with the use of diffusion tensor imaging (DTI) available from the National Center for Biotechnology Information PubMed (Medline) and Health Source: Nursing/Academic Edition databases. Of 358 relevant articles identified, 25 papers published in the years 2008–2020 were ultimately included in the review. Most of them supported the presence of subtle aberrations in WM in UHR individuals, especially in the superior longitudinal fasciculus (SLF), the inferior longitudinal fasciculus (ILF), and the inferior fronto-occipital fasciculus (IFOF). These alterations may therefore be considered a promising neurobiological marker for the risk of psychosis. However, due to methodological discrepancies and the relative scarcity of evidence, further investigation is called for, especially into connectome analysis in UHR patients.

Multimodal assessment of white matter microstructure in antipsychotic-naïve schizophrenia patients and confounding effects of recreational drug use

Cerebral white matter (WM) aberrations in schizophrenia have been linked to multiple neurobiological substrates but the underlying mechanisms remain unknown. Moreover, antipsychotic treatment and substance use constitute potential confounders. Multimodal studies using diffusion tensor imaging (DTI) and magnetization transfer imaging (MTI) may provide deeper insight into the whole brain WM pathophysiology in schizophrenia. We combined DTI and MTI to investigate WM integrity in 51 antipsychotic-naïve, first-episode schizophrenia patients and 55 matched healthy controls, using 3 T magnetic resonance imaging (MRI). Psychopathology was assessed with the positive and negative syndrome scale (PANSS). A whole brain partial least squares correlation (PLSC) method was used to conjointly analyze DTI-derived measures (fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), mode of anisotropy (MO)) and the magnetization transfer ratio (MTR) to identify group differences, and associations with psychopathology. In secondary analyses, we excluded recreational substance users from both groups resulting in 34 patients and 51 healthy controls. The primary PLSC group difference analysis identified a significant pattern of lower FA, AD, MO and higher RD in patients (p = 0.04). This pattern suggests disorganized WM microstructure in patients. The secondary PLSC group difference analysis without recreational substance users revealed a significant pattern of lower FA and higher AD, RD, MO, MTR in patients (p = 0.04). This pattern in the substance free patients is consistent with higher extracellular free-water concentrations, which may reflect neuroinflammation. No significant associations with psychopathology were observed. Recreational substance use appears to be a confounding issue, which calls for attention in future WM studies.

Associations between cognition and white matter microstructure in first-episode antipsychotic-naïve patients with schizophrenia and healthy controls: A multivariate pattern analysis

BACKGROUND

Cognitive functions have been associated with white matter (WM) microstructure in schizophrenia, but most studies are limited by examining only select cognitive measures and single WM tracts in chronic, medicated patients. It is unclear if the cognition-WM relationship differs between antipsychotic-naïve patients with schizophrenia and healthy controls, as differential associations have not been directly examined. Here we examine if there are differential patterns of associations between cognition and WM microstructure in first-episode antipsychotic-naïve patients with schizophrenia and healthy controls, and we characterize reliable contributors to the pattern of associations across multiple cognitive domains and WM regions, in order to elucidate white matter contribution to the neural underpinnings of cognitive deficits.

METHODS

Thirty-six first-episode antipsychotic-naïve patients with schizophrenia and 52 matched healthy controls underwent cognitive tests and diffusion-weighted imaging on a 3T Magnetic Resonance Imaging scanner. Using a multivariate partial least squares correlation analysis, we included 14 cognitive variables and mean fractional anisotropy values of 48 WM regions.

RESULTS

Initial analyses showed significant group differences in both measures of WM and cognition. There was no group interaction effect in the pattern of associations between cognition and WM microstructure. The combined analysis of patients and controls lead to a significant pattern of associations (omnibus test p = .015). Thirty-four regions and seven cognitive functions contributed reliably to the associations.

CONCLUSIONS

The lack of an interaction effect suggests similar associations in first-episode antipsychotic-naïve patients with schizophrenia and healthy controls. This, together with the differences in both WM and cognitive measurements, supports the involvement of WM in cognitive deficits in schizophrenia. Our findings add to the field by showing a coherent picture of the overall pattern of association between cognition and WM. These findings increase our understanding of the impact of WM on cognition, contributing to the search for neuromarkers of cognitive deficits in schizophrenia.

Generalized neurocognitive impairment in individuals at ultra-high risk for psychosis: The possible key role of slowed processing speed

OBJECTIVE

Widespread neurocognitive impairment is well-established in individuals at ultra-high risk (UHR) for developing psychoses, but it is unknown whether slowed processing speed may underlie impairment in other neurocognitive domains, as found in schizophrenia. The study delineated domain functioning in a UHR sample and examined if neurocognitive slowing might account for deficits across domains.

METHODS

The cross-sectional study included 50 UHR individuals with no (n = 38) or minimal antipsychotic exposure (n = 12; mean lifetime dose of haloperidol equivalent = 17.56 mg; SD = 13.04) and 50 matched healthy controls. Primary analyses compared group performance across neurocognitive domains before and after covarying for processing speed. To examine the specificity of processing speed effects, post hoc analyses examined the impact of the other neurocognitive domains and intelligence as covariates.

RESULTS

UHR individuals exhibited significant impairment across all neurocognitive domains (all ps ≤ .010), with medium to large effect sizes (Cohen's ds = -0.53 to -1.12). Only processing speed used as covariate eliminated significant between-group differences in all other domains, reducing unadjusted Cohen's d values with 68% on average, whereas the other domains used as covariates averagely reduced unadjusted Cohen's d values with 20% to 48%. When covarying each of the other domains after their shared variance with speed of processing was removed, all significant between-group domain differences remained (all ps ≤ .024).

CONCLUSION

Slowed processing speed may underlie generalized neurocognitive impairment in UHR individuals and represent a potential intervention target.

Cellular and extracellular white matter alterations indicate conversion to psychosis among individuals at clinical high-risk for psychosis

OBJECTIVES

It is important to find biomarkers associated with transition to illness in individuals at clinical high-risk for psychosis (CHR). Here, we use free-water imaging, an advanced diffusion MRI technique, to identify white matter alterations in the brains of CHR subjects who subsequently develop psychosis (CHR-P) compared to those who do not (CHR-NP).

METHODS

Twenty-four healthy controls (HC) and 30 CHR individuals, 8 of whom converted to schizophrenia after a mean follow-up of 15.16 months, received baseline MRI scans. Maps of fractional anisotropy (FA), FA of cellular tissue (FA_T), and extracellular free-water (FW) were extracted using tract-based spatial statistics after which voxel-wise non-parametric group statistics and correlations with symptom severity were performed.

RESULTS

There were no significant differences between HCs and the combined CHR group. However, prior to conversion, CHR-P showed widespread lower FA compared to CHR-NP (p_FWE < 0.05). FA changes in CHR-P were associated with significantly lower FA_T and higher FW, compared to CHR-NP. Positive symptoms correlated significantly with diffusion parameters in similar regions as those discriminating CHR-P from CHR-NP.

CONCLUSIONS

Our study suggests that cellular (FA_T) and extracellular (FW) white matter alterations are associated with positive symptom severity and indicate an elevated illness risk among CHR individuals.

Interview and questionnaire assessment of cognitive impairment in subjects at ultra-high risk for psychosis: Associations with cognitive test performance, psychosocial functioning, and positive symptoms

Impaired cognitive test performance is well-documented in subjects at ultra-high risk (UHR) for psychosis. However, assessment of cognitive deficits as manifested in real life is a neglected area of UHR research that may add to the understanding of cognitive impairment and its relationship with psychosocial functioning and positive symptomatology. This study applied the interview-based Schizophrenia Cognition Rating Scale (SCoRS) and the questionnaire-based Behavior Rating Inventory of Executive Function - Adult Version (BRIEF-A) in a cross-sectional sample of 39 UHR subjects and 50 healthy controls. Cognitive test performance, psychosocial functioning, and positive symptoms were also assessed. The UHR subjects demonstrated significant cognitive impairment, with large effect sizes for the SCoRS and BRIEF-A composite outcome variables (rs = -0.67 to -0.80) and a neurocognitive composite score (d = -0.97). Within the UHR group, several significant associations between worse cognitive ratings and worse cognitive test performance (rs = -0.210 to -0.343), poorer psychosocial functioning (rs = -0.058 to -0.728), and worse positive symptoms (rs= 0.415 to 0.478) were found. Worse cognitive test performance showed significant associations with more pronounced positive symptoms (rs = -0.299 to -0.457). Interview and questionnaire assessment may hold promise for supplementing traditional performance-based cognitive assessment in identifying treatment targets in the UHR population.

Can reduced leftward asymmetry of white matter integrity be a marker of transition to psychosis in at-risk mental state?

As a biomarker for the degree of psychosis development, the lateral asymmetry of white matter (WM) integrity in each area of the cerebrum has been investigated; as a result, a reduced leftward asymmetry of WM integrity has been reported in patients with schizophrenia. Although individuals with an at-risk mental state for psychosis (ARMS) who subsequently develop psychosis are believed to have poorer social functioning, only a few studies have actually examined the associations between WM abnormalities and social functioning. The aim of the present study was to clarify the possibly predictive association between a reduced asymmetry of WM integrity and impairments in social functioning in patients with ARMS. Thirty ARMS subjects underwent MRI scanning and were assessed using the Social Functioning Scale (SFS). We examined the fractional anisotropy (FA) values in the cingulum bundle (CB) and the uncinate fasciculus (UF) using a tract-specific analysis. Lateral asymmetry was assessed using the laterality index (LI). The LI of the FA value was positive (leftward) in the CB and negative (rightward) in the UF. Although the LI was not correlated with the Scale of Prodromal Symptoms (SOPS) score, the LI in the CB was positively correlated with the SFS score. In ARMS patients, the degree of reduced leftward asymmetry in the CB might affect deteriorations in social functioning and may be useful as a biomarker for predicting future outcomes at an early stage of psychosis.

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.

No Effects of Cognitive Remediation on Cerebral White Matter in Individuals at Ultra-High Risk for Psychosis-A Randomized Clinical Trial

BACKGROUND

Individuals at ultra-high risk for psychosis (UHR) present with subtle alterations in cerebral white matter (WM), which appear to be associated with clinical and functional outcome. The effect of cognitive remediation on WM organization in UHR individuals has not been investigated previously.

METHODS

In a randomized, clinical trial, UHR individuals aged 18 to 40 years were assigned to treatment as usual (TAU) or TAU plus cognitive remediation for 20 weeks. Cognitive remediation comprised 20 x 2-h sessions of neurocognitive and social-cognitive training. Primary outcome was whole brain fractional anisotropy derived from diffusion weighted imaging, statistically tested as an interaction between timepoint and treatment group. Secondary outcomes were restricted to five predefined region of interest (ROI) analyses on fractional anisotropy, axial diffusivity, radial diffusivity and mean diffusivity. For significant timepoint and treatment group interactions within these five ROIs, we explored associations between longitudinal changes in WM and cognitive functions/clinical symptoms. Finally, we explored dose-response effects of cognitive remediation on WM.

RESULTS

A total of 111 UHR individuals were included. Attrition-rate was 26%. The cognitive remediation group completed on average 12 h of neurocognitive training, which was considerably lower than per protocol. We found no effect of cognitive remediation on whole-brain FA when compared to treatment as usual. Secondary ROI analyses revealed a nominal significant interaction between timepoint*treatment of AD in left medial lemniscus (P=0.016) which did not survive control for multiple comparisons. The exploratory test showed that this change in AD correlated to improvements of mental flexibility in the cognitive remediation group (p=0.001). We found no dose-response effect of neurocognitive training on WM.

CONCLUSIONS

Cognitive remediation comprising 12 h of neurocognitive training on average did not improve global or regional WM organization in UHR individuals. Further investigations of duration and intensity of cognitive training as necessary prerequisites of neuroplasticity-based changes are warranted.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov, identifier NCT02098408.

Brain changes associated with negative symptoms in clinical high risk for psychosis: A systematic review

The negative symptoms of schizophrenia are linked to poorer functional outcomes and decreases in quality of life, and are often the first to develop in individuals who are at clinical high risk (CHR) for psychosis. However, the accompanying neurobiological changes are poorly understood. Therefore, we conducted a systematic review of the studies that have examined the brain metrics associated with negative symptoms in those at CHR. Electronic databases were searched from inception to August 2019. Studies were selected if they mentioned negative symptoms in youth at CHR for psychosis, and brain imaging. Of 261 citations, 43 studies with 2144 CHR participants met inclusion criteria. Too few studies were focused on the same brain regions using similar neuroimaging methods to perform a meta-analysis, however, the results of this systematic review suggest a relationship between negative symptom increases and decreases in grey matter. The paucity of studies linking changes in brain structure and function with negative symptoms in those at CHR suggests that future work should focus on examining these relationships.

Associations between facial affect recognition and neurocognition in subjects at ultra-high risk for psychosis: A case-control study

The nature of facial affect recognition (FAR) deficits in subjects at ultra-high risk (UHR) for psychosis remains unclear. In schizophrenia, associations between FAR impairment and poor neurocognition have been demonstrated meta-analytically, but this potential link is understudied in the UHR population. Our study investigated a cross-sectional sample of UHR subjects (n = 22) and healthy controls (n = 50), with the Degraded Facial Affect Recognition (DFAR) Task and a neurocognitive test battery. Our primary aims were 1. to examine associations between FAR and neurocognition in UHR subjects and 2. to examine if associations differed between cases and controls. The secondary aim was to examine group differences in FAR and neurocognitive performance. In UHR subjects, FAR was significantly associated with working memory, a neurocognitive composite score and intelligence, and at trend level with most other assessed neurocognitive domains, with moderate to large effect sizes. There were no significant associations in controls. Associations between FAR and working memory and the neurocognitive composite score differed significantly between cases and controls. UHR subjects did not differ from controls on DFAR Task performance but showed significant deficits in three of six neurocognitive domains. Results may suggest that FAR is associated with working memory in UHR subjects, possibly reflecting a neurocognitive compensatory mechanism.

White Matter Microstructure across the Psychosis Spectrum

Diffusion-weighted imaging (DWI) is a neuroimaging technique that has allowed us an unprecedented look at the role that white matter microstructure may play in mental illnesses, such as psychosis. Psychosis-related illnesses, including schizophrenia, are increasingly viewed as existing along a spectrum; spectrums may be defined based on factors such as stage of illness, symptom severity, or genetic liability. This review first focuses on an overview of some of the recent findings from DWI studies. Then, it examines the ways in which DWI analyses have been extended across the broader psychosis spectrum, or spectrums, and what we have learned from such approaches.

Cingulum bundle abnormalities and risk for schizophrenia

BACKGROUND

The cingulum bundle (CB) is a major white matter fiber tract of the limbic system that underlies cingulate cortex, passing longitudinally over the corpus callosum. The connectivity of this white matter fiber tract plays a major role in emotional expression, attention, motivation, and working memory, all of which are affected in schizophrenia. Myelin related CB abnormalities have also been implicated in schizophrenia. The purpose of this study is to determine whether or not CB abnormalities are evident in individuals at clinical high risk (CHR) for psychosis, and whether or not cognitive deficits in the domains subserved by CB are related to its structural abnormalities.

METHODS

Diffusion Tensor Imaging (DTI) was performed on a 3 T magnet. DT tractography was used to evaluate CB in 20 individuals meeting CHR criteria (13 males/7 females) and 23 healthy controls (12 males/11 females) group matched on age, gender, parental socioeconomic status, education, and handedness. Fractional anisotropy (FA), a measure of white matter coherence and integrity, radial diffusivity (RD), thought to reflect myelin integrity, trace, a possible marker of atrophy, and axial diffusivity (AD), thought to reflect axonal integrity, were averaged over the entire tract and used to investigate CB abnormalities in individuals at CHR for psychosis compared with healthy controls.

RESULTS

Significant group differences were found between individuals at CHR for psychosis and controls for FA (p = 0.028), RD (p = 0.03) and trace (p = 0.031), but not for AD (p = 0.09). We did not find any significant correlations between DTI measures and clinical symptoms.

CONCLUSION

These findings suggest abnormalities (possibly myelin related) in the CB in individuals at CHR for psychosis.

Selective Review of Neuroimaging Findings in Youth at Clinical High Risk for Psychosis: On the Path to Biomarkers for Conversion

First episode psychosis (FEP), and subsequent diagnosis of schizophrenia or schizoaffective disorder, predominantly occurs during late adolescence, is accompanied by a significant decline in function and represents a traumatic experience for patients and families alike. Prior to first episode psychosis, most patients experience a prodromal period of 1-2 years, during which symptoms first appear and then progress. During that time period, subjects are referred to as being at Clinical High Risk (CHR), as a prodromal period can only be designated in hindsight in those who convert. The clinical high-risk period represents a critical window during which interventions may be targeted to slow or prevent conversion to psychosis. However, only one third of subjects at clinical high risk will convert to psychosis and receive a formal diagnosis of a primary psychotic disorder. Therefore, in order for targeted interventions to be developed and applied, predicting who among this population will convert is of critical importance. To date, a variety of neuroimaging modalities have identified numerous differences between CHR subjects and healthy controls. However, complicating attempts at predicting conversion are increasingly recognized co-morbidities, such as major depressive disorder, in a significant number of CHR subjects. The result of this is that phenotypes discovered between CHR subjects and healthy controls are likely non-specific to psychosis and generalized for major mental illness. In this paper, we selectively review evidence for neuroimaging phenotypes in CHR subjects who later converted to psychosis. We then evaluate the recent landscape of machine learning as it relates to neuroimaging phenotypes in predicting conversion to psychosis.

Widespread higher fractional anisotropy associates to better cognitive functions in individuals at ultra-high risk for psychosis

In schizophrenia patients, cognitive functions appear linked to widespread alterations in cerebral white matter microstructure. Here we examine patterns of associations between regional white matter and cognitive functions in individuals at ultra-high risk for psychosis. One hundred and sixteen individuals at ultra-high risk for psychosis and 49 matched healthy controls underwent 3 T magnetic resonance diffusion-weighted imaging and cognitive assessments. Group differences on fractional anisotropy were tested using tract-based spatial statistics. Group differences in cognitive functions, voxel-wise as well as regional fractional anisotropy were tested using univariate general linear modeling. Multivariate partial least squares correlation analyses tested for associations between patterns of regional fractional anisotropy and cognitive functions. Univariate analyses revealed significant impairments on cognitive functions and lower fractional anisotropy in superior longitudinal fasciculus and cingulate gyrus in individuals at ultra-high risk for psychosis. Partial least squares correlation analysis revealed different associations between patterns of regional fractional anisotropy and cognitive functions in individuals at ultra-high risk for psychosis compared to healthy controls. Widespread higher fractional anisotropy was associated with better cognitive functioning for individuals at ultra-high risk for psychosis, but not for the healthy controls. Furthermore, patterns of cognitive functions were associated with an interaction-effect on regional fractional anisotropy in fornix, medial lemniscus, uncinate fasciculus, and superior cerebellar peduncle. Aberrant associations between patterns of cognitive functions to white matter may be explained by dysmyelination.

Childhood Trauma in Schizophrenia: Current Findings and Research Perspectives

Schizophrenia is a severe neuropsychiatric disorder with persistence of symptoms throughout adult life in most of the affected patients. This unfavorable course is associated with multiple episodes and residual symptoms, mainly negative symptoms and cognitive deficits. The neural diathesis-stress model proposes that psychosocial stress acts on a pre-existing vulnerability and thus triggers the symptoms of schizophrenia. Childhood trauma is a severe form of stress that renders individuals more vulnerable to developing schizophrenia; neurobiological effects of such trauma on the endocrine system and epigenetic mechanisms are discussed. Childhood trauma is associated with impaired working memory, executive function, verbal learning, and attention in schizophrenia patients, including those at ultra-high risk to develop psychosis. In these patients, higher levels of childhood trauma were correlated with higher levels of attenuated positive symptoms, general symptoms, and depressive symptoms; lower levels of global functioning; and poorer cognitive performance in visual episodic memory end executive functions. In this review, we discuss effects of specific gene variants that interact with childhood trauma in patients with schizophrenia and describe new findings on the brain structural and functional level. Additive effects between childhood trauma and brain-derived neurotrophic factor methionine carriers on volume loss of the hippocampal subregions cornu ammonis (CA)4/dentate gyrus and CA2/3 have been reported in schizophrenia patients. A functional magnetic resonance imaging study showed that childhood trauma exposure resulted in aberrant function of parietal areas involved in working memory and of visual cortical areas involved in attention. In a theory of mind task reflecting social cognition, childhood trauma was associated with activation of the posterior cingulate gyrus, precuneus, and dorsomedial prefrontal cortex in patients with schizophrenia. In addition, decreased connectivity was shown between the posterior cingulate/precuneus region and the amygdala in patients with high levels of physical neglect and sexual abuse during childhood, suggesting that disturbances in specific brain networks underlie cognitive abilities. Finally, we discuss some of the questionnaires that are commonly used to assess childhood trauma and outline possibilities to use recent biostatistical methods, such as machine learning, to analyze the resulting datasets.

Patterns of Cortical Structures and Cognition in Antipsychotic-Naïve Patients With First-Episode Schizophrenia: A Partial Least Squares Correlation Analysis

BACKGROUND

Schizophrenia is associated with alterations in cortical structures and cognitive impairments, but antipsychotic medication may affect these measures. We investigated patterns of relationships between cortical structures and cognitive domains in antipsychotic-naïve patients with first-episode schizophrenia.

METHODS

T1-weighted 3T magnetic resonance imaging was performed in 105 patients and 136 healthy control subjects. Using FreeSurfer, we obtained measurements of cortical thickness, surface area, and mean curvature. Using an extensive neurocognitive battery including the Danish Adult Reading Test and subtests from the Cambridge Neuropsychological Test Automated Battery, we obtained estimates of premorbid intelligence, spatial working memory, spatial planning, intra-extradimensional set shifting, and reaction and movement times. With univariate analyses, we tested group differences between cortical structures and cognition. With partial least squares correlation analyses, we investigated patterns of associations between cortical structures and cognition.

RESULTS

Patients had significantly higher mean curvature and were impaired on 7 of 11 cognitive parameters. The between-group partial least squares correlation analysis revealed two cortical thickness/cognition patterns that differentiated patients and healthy control subjects (omnibus test, p = .011). Most cortical regions contributed reliably to these patterns. In patients, spatial working memory, spatial planning, reaction and movement times, and premorbid intelligence contributed reliably to the pattern; in healthy control subjects, spatial planning and intra-extradimensional set shifting contributed reliably.

CONCLUSIONS

Antipsychotic-naïve patients with first-episode schizophrenia displayed a higher mean curvature, but no significant difference in other gray matter indices was found. Nevertheless, the pattern of associations between global cortical thickness and cognitive functions was markedly different between groups. These multivariate analyses reveal a novel linkage between regional cortical brain structure and cognitive deficits at the earliest, never-medicated illness stage.

Youth at-risk for serious mental illness: methods of the PROCAN study

BACKGROUND

Most mental disorders begin in adolescence; however, there are gaps in our understanding of youth mental health. Clinical and policy gaps arise from our current inability to predict, from amongst all youth who experience mild behavioural disturbances, who will go on to develop a mental illness, what that illness will be, and what can be done to change its course and prevent its worsening to a serious mental illness (SMI). There are also gaps in our understanding of how known risk factors set off neurobiological changes that may play a role in determining who will develop a SMI. Project goals are (i) to identify youth at different stages of risk of SMI so that intervention can begin as soon as possible and (ii) to understand the triggers of these mental illnesses.

METHOD

This 2-site longitudinal study will recruit 240 youth, ages 12-25, who are at different stages of risk for developing a SMI. The sample includes (a) healthy individuals, (b) symptom-free individuals who have a first-degree relative with a SMI, (c) youth who are experiencing distress and may have mild symptoms of anxiety or depression, and (d) youth who are already demonstrating attenuated symptoms of SMI such as bipolar disorder or psychosis. We will assess, every 6 months for one year, a wide range of clinical and psychosocial factors to determine which factors can be used to predict key outcomes. We will also assess neuroimaging and peripheral markers. We will develop and validate a prediction algorithm that includes demographic, clinical and psychosocial predictors. We will also determine if adding biological markers to our algorithm improves prediction.

DISCUSSION

Outcomes from this study include an improved clinical staging model for SMI and prediction algorithms that can be used by health care providers as decision-support tools in their practices. Secondly, we may have a greater understanding of clinical, social and cognitive factors associated with the clinical stages of development of a SMI, as well as new insights from neuroimaging and later neurochemical biomarker studies regarding predisposition to SMI development and progression through the clinical stages of illness.

Support Vector Machine Classification of Obsessive-Compulsive Disorder Based on Whole-Brain Volumetry and Diffusion Tensor Imaging

Magnetic resonance imaging (MRI) methods have been used to detect cerebral anatomical distinction between obsessive-compulsive disorder (OCD) patients and healthy controls (HC). Machine learning approach allows for the possibility of discriminating patients on the individual level. However, few studies have used this automatic technique based on multiple modalities to identify potential biomarkers of OCD. High-resolution structural MRI and diffusion tensor imaging (DTI) data were acquired from 48 OCD patients and 45 well-matched HC. Gray matter volume (GMV), white matter volume (WMV), fractional anisotropy (FA), and mean diffusivity (MD) were extracted as four features were examined using support vector machine (SVM). Ten brain regions of each feature contributed most to the classification were also estimated. Using different algorithms, the classifier achieved accuracies of 72.08, 61.29, 80.65, and 77.42% for GMV, WMV, FA, and MD, respectively. The most discriminative gray matter regions that contributed to the classification were mainly distributed in the orbitofronto-striatal "affective" circuit, the dorsolateral, prefronto-striatal "executive" circuit and the cerebellum. For WMV feature and the two feature sets of DTI, the shared regions contributed the most to the discrimination mainly included the uncinate fasciculus, the cingulum in the hippocampus, corticospinal tract, as well as cerebellar peduncle. Based on whole-brain volumetry and DTI images, SVM algorithm revealed high accuracies for distinguishing OCD patients from healthy subjects at the individual level. Computer-aided method is capable of providing accurate diagnostic information and might provide a new perspective for clinical diagnosis of OCD.

White matter maturation during 12 months in individuals at ultra-high-risk for psychosis

OBJECTIVE

The neurodevelopmental hypothesis of psychosis suggests that disrupted white matter (WM) maturation underlies disease onset. In this longitudinal study, we investigated WM connectivity and compared WM changes between individuals at ultra-high-risk for psychosis (UHR) and healthy controls (HCs).

METHOD

Thirty UHR individuals and 23 HCs underwent MR diffusion tensor imaging before and after 12 months of non-manualized standard care. Positive and negative symptoms and level of functioning were assessed. Tract-based spatial statistics were employed.

RESULTS

During 12 months, none of the UHR individuals transitioned to psychosis. Both UHR individuals and HCs increased significantly in fractional anisotropy (FA). UHR individuals showed significant FA increases predominantly in the left superior longitudinal fasciculus (SLF) (P = 0.01), and HCs showed significant FA increases in the left uncinate fasciculus (P = 0.03). Within UHR individuals, a significant positive correlation between FA change and age was observed predominantly in the left SLF (P = 0.02). Within HCs, no significant correlation between FA change and age was observed. No significant correlations between baseline FA and clinical outcomes were observed; however, FA changes were significantly positively correlated to changes in negative symptoms (P = 0.04).

CONCLUSION

As normal brain maturation occurs in a posterior to frontal direction, our findings could suggest disturbed WM maturation in UHR individuals.