Cortical abnormalities in youth at clinical high-risk for psychosis: Findings from the NAPLS2 cohort

Cognitive subtypes in youth at clinical high risk for psychosis

Introduction

Schizophrenia is a mental health condition that severely impacts well-being. Cognitive impairment is among its core features, often presenting well before the onset of overt psychosis, underscoring a critical need to study it in the psychosis proneness (clinical high risk; CHR) stage, to maximize the benefits of interventions and to improve clinical outcomes. However, given the heterogeneity of cognitive impairment in this population, a one-size-fits-all approach to therapeutic interventions would likely be insufficient. Thus, identifying cognitive subtypes in this population is crucial for tailored and successful therapeutic interventions. Here we identify, validate, and characterize cognitive subtypes in large CHR samples and delineate their baseline and longitudinal cognitive and functional trajectories.

Methods

Using machine learning, we performed cluster analysis on cognitive measures in a large sample of CHR youth (n = 764), and demographically comparable controls (HC; n = 280) from the North American Prodrome Longitudinal Study (NAPLS) 2, and independently validated our findings with an equally large sample (NAPLS 3; n = 628 CHR, 84 HC). By utilizing several statistical approaches, we compared the clusters on cognition and functioning at baseline, and over 24 months of followup. We further delineate the conversion status within those clusters.

Results

Two main cognitive clusters were identified, "impaired" and "intact" across all cognitive domains in CHR compared to HC. Baseline differences between the cognitively intact cluster and HC were found in the verbal abilities and attention and working memory domains. Longitudinally, those in the cognitively impaired cluster group demonstrated an overall floor effect and did not deteriorate further over time. However, a "catch up" trajectory was observed in the attention and working memory domain. This group had higher instances of conversion overall, with these converters having significantly more non-affective psychotic disorder diagnosis versus bipolar disorder, than those with intact cognition. In the cognitively intact group, we observed differences in trajectory based on conversion status, where those who start with intact cognition and later convert demonstrate a sharp decline in attention and functioning. Functioning was significantly better in the cognitively intact than in the impaired group at baseline. Most of the cognitive trajectories demonstrate a positive relationship with functional ones.

Conclusion

Our findings provide evidence for intact and impaired cognitive subtypes in youth at CHR, independent of conversion status. They further indicate that attention and working memory are important to distinguish between the CHR with intact cognition and controls. The cognitively intact CHR group becomes less attentive after conversion, while the cognitively impaired one demonstrates a catch up trajectory on both attention and working memory. Overall, early evaluation, covering several cognitive domains, is crucial for identifying trajectories of improvement and deterioration for the purpose of tailoring intervention for improving outcomes in individuals at CHR for psychosis.

Excessive interstitial free-water in cortical gray matter preceding accelerated volume changes in individuals at clinical high risk for psychosis

Recent studies show that accelerated cortical gray matter (GM) volume reduction seen in anatomical MRI can help distinguish between individuals at clinical high risk (CHR) for psychosis who will develop psychosis and those who will not. This reduction is suggested to represent atypical developmental or degenerative changes accompanying an accumulation of microstructural changes, such as decreased spine density and dendritic arborization. Detecting the microstructural sources of these changes before they accumulate into volume loss is crucial. Our study aimed to detect these microstructural GM alterations using diffusion MRI (dMRI). We tested for baseline and longitudinal group differences in anatomical and dMRI data from 160 individuals at CHR and 96 healthy controls (HC) acquired in a single imaging site. Of the CHR individuals, 33 developed psychosis (CHR-P), while 127 did not (CHR-NP). Among all participants, longitudinal data was available for 45 HCs, 17 CHR-P, and 66 CHR-NP. Eight cortical lobes were examined for GM volume and GM microstructure. A novel dMRI measure, interstitial free water (iFW), was used to quantify GM microstructure by eliminating cerebrospinal fluid contribution. Additionally, we assessed whether these measures differentiated the CHR-P from the CHR-NP. In addition, for completeness, we also investigated changes in cortical thickness and in white matter (WM) microstructure. At baseline the CHR group had significantly higher iFW than HC in the prefrontal, temporal, parietal, and occipital lobes, while volume was reduced only in the temporal lobe. Neither iFW nor volume differentiated between the CHR-P and CHR-NP groups at baseline. However, in many brain areas, the CHR-P group demonstrated significantly accelerated changes (iFW increase and volume reduction) with time than the CHR-NP group. Cortical thickness provided similar results as volume, and there were no significant changes in WM microstructure. Our results demonstrate that microstructural GM changes in individuals at CHR have a wider extent than volumetric changes or microstructural WM changes, and they predate the acceleration of brain changes that occur around psychosis onset. Microstructural GM changes, as reflected by the increased iFW, are thus an early pathology at the prodromal stage of psychosis that may be useful for a better mechanistic understanding of psychosis development.

Longitudinal Trajectories of Premorbid Social and Academic Adjustment in Youth at Clinical High Risk for Psychosis: Implications for Conversion

BACKGROUND AND HYPOTHESIS

Social and academic adjustment deteriorate in the years preceding a psychotic disorder diagnosis. Analyses of premorbid adjustment have recently been extended into the clinical high risk for psychosis (CHR) syndrome to identify risk factors and developmental pathways toward psychotic disorders. Work so far has been at the between-person level, which has constrained analyses of premorbid adjustment, clinical covariates, and conversion to psychosis.

STUDY DESIGN

Growth-curve models examined longitudinal trajectories in retrospective reports of premorbid social and academic adjustment from youth at CHR (n = 498). Interaction models tested whether known covariates of premorbid adjustment problems (attenuated negative symptoms, cognition, and childhood trauma) were associated with different premorbid adjustment trajectories in converters vs non-converters (ie, participants who did/did not develop psychotic disorders within 2-year follow-up).

STUDY RESULTS

Converters reported poorer social adjustment throughout the premorbid period. Converters who developed psychosis with an affective component reported poorer academic adjustment throughout the premorbid period than those who developed non-affective psychosis. Tentatively, baseline attenuated negative symptoms may have been associated with worsening social adjustment in the premorbid period for non-converters only. Childhood trauma impact was associated with fewer academic functioning problems among converters. Cognition effects did not differ based on conversion status.

CONCLUSIONS

Premorbid social function is an important factor in risk for conversion to psychosis. Negative symptoms and childhood trauma had different relationships to premorbid functioning in converters vs non-converters. Mechanisms linking symptoms and trauma to functional impairment may be different in converters vs non-converters, suggesting possible new avenues for risk assessment.

Using brain structural neuroimaging measures to predict psychosis onset for individuals at clinical high-risk

Machine learning approaches using structural magnetic resonance imaging (sMRI) can be informative for disease classification, although their ability to predict psychosis is largely unknown. We created a model with individuals at CHR who developed psychosis later (CHR-PS+) from healthy controls (HCs) that can differentiate each other. We also evaluated whether we could distinguish CHR-PS+ individuals from those who did not develop psychosis later (CHR-PS-) and those with uncertain follow-up status (CHR-UNK). T1-weighted structural brain MRI scans from 1165 individuals at CHR (CHR-PS+, n = 144; CHR-PS-, n = 793; and CHR-UNK, n = 228), and 1029 HCs, were obtained from 21 sites. We used ComBat to harmonize measures of subcortical volume, cortical thickness and surface area data and corrected for non-linear effects of age and sex using a general additive model. CHR-PS+ (n = 120) and HC (n = 799) data from 20 sites served as a training dataset, which we used to build a classifier. The remaining samples were used external validation datasets to evaluate classifier performance (test, independent confirmatory, and independent group [CHR-PS- and CHR-UNK] datasets). The accuracy of the classifier on the training and independent confirmatory datasets was 85% and 73% respectively. Regional cortical surface area measures-including those from the right superior frontal, right superior temporal, and bilateral insular cortices strongly contributed to classifying CHR-PS+ from HC. CHR-PS- and CHR-UNK individuals were more likely to be classified as HC compared to CHR-PS+ (classification rate to HC: CHR-PS+, 30%; CHR-PS-, 73%; CHR-UNK, 80%). We used multisite sMRI to train a classifier to predict psychosis onset in CHR individuals, and it showed promise predicting CHR-PS+ in an independent sample. The results suggest that when considering adolescent brain development, baseline MRI scans for CHR individuals may be helpful to identify their prognosis. Future prospective studies are required about whether the classifier could be actually helpful in the clinical settings.

Combining Clinical With Cognitive or Magnetic Resonance Imaging Data for Predicting Transition to Psychosis in Ultra High-Risk Patients: Data From the PACE 400 Cohort

BACKGROUND

Multimodal modeling that combines biological and clinical data shows promise in predicting transition to psychosis in individuals who are at ultra-high risk. Individuals who transition to psychosis are known to have deficits at baseline in cognitive function and reductions in gray matter volume in multiple brain regions identified by magnetic resonance imaging.

METHODS

In this study, we used Cox proportional hazards regression models to assess the additive predictive value of each modality-cognition, cortical structure information, and the neuroanatomical measure of brain age gap-to a previously developed clinical model using functioning and duration of symptoms prior to service entry as predictors in the Personal Assessment and Crisis Evaluation (PACE) 400 cohort. The PACE 400 study is a well-characterized cohort of Australian youths who were identified as ultra-high risk of transitioning to psychosis using the Comprehensive Assessment of At Risk Mental States (CAARMS) and followed for up to 18 years; it contains clinical data (from N = 416 participants), cognitive data (n = 213), and magnetic resonance imaging cortical parameters extracted using FreeSurfer (n = 231).

RESULTS

The results showed that neuroimaging, brain age gap, and cognition added marginal predictive information to the previously developed clinical model (fraction of new information: neuroimaging 0%-12%, brain age gap 7%, cognition 0%-16%).

CONCLUSIONS

In summary, adding a second modality to a clinical risk model predicting the onset of a psychotic disorder in the PACE 400 cohort showed little improvement in the fit of the model for long-term prediction of transition to psychosis.

Fronto-temporal cortical grey matter thickness and surface area in the at-risk mental state and recent-onset schizophrenia: a magnetic resonance imaging study

BACKGROUND

Studies to date examining cortical thickness and surface area in young individuals At Risk Mental State (ARMS) of developing psychosis have revealed inconsistent findings, either reporting increased, decreased or no differences compared to mentally healthy individuals. The inconsistencies may be attributed to small sample sizes, varying age ranges, different ARMS identification criteria, lack of control for recreational substance use and antipsychotic pharmacotherapy, as well as different methods for deriving morphological brain measures.

METHODS

A surfaced-based approach was employed to calculate fronto-temporal cortical grey matter thickness and surface area derived from magnetic resonance imaging (MRI) data collected from 44 young antipsychotic-naïve ARMS individuals, 19 young people with recent onset schizophrenia, and 36 age-matched healthy volunteers. We conducted group comparisons of the morphological measures and explored their association with symptom severity, global and socio-occupational function levels, and the degree of alcohol and cannabis use in the ARMS group.

RESULTS

Grey matter thickness and surface areas in ARMS individuals did not significantly differ from their age-matched healthy counterparts. However, reduced left-frontal grey matter thickness was correlated with greater symptom severity and lower function levels; the latter being also correlated with smaller left-frontal surface areas. ARMS individuals with more severe symptoms showed greater similarities to the recent onset schizophrenia group. The morphological measures in ARMS did not correlate with the lifetime level of alcohol or cannabis use.

CONCLUSIONS

Our findings suggest that a decline in function levels and worsening mental state are associated with morphological changes in the left frontal cortex in ARMS but to a lesser extent than those seen in recent onset schizophrenia. Alcohol and cannabis use did not confound these findings. However, the cross-sectional nature of our study limits our ability to draw conclusions about the potential progressive nature of these morphological changes in ARMS.

Linking Polygenic Risk of Schizophrenia to Variation in Magnetic Resonance Imaging Brain Measures: A Comprehensive Systematic Review

BACKGROUND AND HYPOTHESIS

Schizophrenia is highly heritable, with a polygenic effect of many genes conferring risk. Evidence on whether cumulative risk also predicts alterations in brain morphology and function is inconsistent. This systematic review examined evidence for schizophrenia polygenic risk score (sczPRS) associations with commonly used magnetic resonance imaging (MRI) measures. We expected consistent evidence to emerge for significant sczPRS associations with variation in structure and function, specifically in frontal, temporal, and insula cortices that are commonly implicated in schizophrenia pathophysiology.

STUDY DESIGN

In accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched MEDLINE, Embase, and PsycINFO for peer-reviewed studies published between January 2013 and March 2022. Studies were screened against predetermined criteria and National Institutes of Health (NIH) quality assessment tools.

STUDY RESULTS

In total, 57 studies of T1-weighted structural, diffusion, and functional MRI were included (age range = 9-80 years, Nrange = 64-76 644). We observed moderate, albeit preliminary, evidence for higher sczPRS predicting global reductions in cortical thickness and widespread variation in functional connectivity, and to a lesser extent, region-specific reductions in frontal and temporal volume and thickness. Conversely, sczPRS does not predict whole-brain surface area or gray/white matter volume. Limited evidence emerged for sczPRS associations with diffusion tensor measures of white matter microstructure in a large community sample and smaller cohorts of children and young adults. These findings were broadly consistent across community and clinical populations.

CONCLUSIONS

Our review supports the hypothesis that schizophrenia is a disorder of disrupted within and between-region brain connectivity, and points to specific whole-brain and regional MRI metrics that may provide useful intermediate phenotypes.

Recent Updates on Predicting Conversion in Youth at Clinical High Risk for Psychosis

PURPOSE OF REVIEW

This review highlights recent advances in the prediction and treatment of psychotic conversion. Over the past 25 years, research into the prodromal phase of psychotic illness has expanded with the promise of early identification of individuals at clinical high risk (CHR) for psychosis who are likely to convert to psychosis.

RECENT FINDINGS

Meta-analyses highlight conversion rates between 20 and 30% within 2-3 years using existing clinical criteria while research into more specific risk factors, biomarkers, and refinement of psychosis risk calculators has exploded, improving our ability to predict psychotic conversion with greater accuracy. Recent studies highlight risk factors and biomarkers likely to contribute to earlier identification and provide insight into neurodevelopmental abnormalities, CHR subtypes, and interventions that can target specific risk profiles linked to neural mechanisms. Ongoing initiatives that assess longer-term (> 5-10 years) outcome of CHR participants can provide valuable information about predictors of later conversion and diagnostic outcomes while large-scale international biomarker studies provide hope for precision intervention that will alter the course of early psychosis globally.

Microstructural Cortical Gray Matter Changes Preceding Accelerated Volume Changes in Individuals at Clinical High Risk for Psychosis

Recent studies show that accelerated cortical gray matter (GM) volume reduction seen in anatomical MRI can help distinguish between individuals at clinical high risk (CHR) for psychosis who will develop psychosis and those who will not. This reduction is thought to result from an accumulation of microstructural changes, such as decreased spine density and dendritic arborization. Detecting the microstructural sources of these changes before they accumulate is crucial, as volume reduction likely indicates an underlying neurodegenerative process. Our study aimed to detect these microstructural GM alterations using diffusion MRI (dMRI). We tested for baseline and longitudinal group differences in anatomical and dMRI data from 160 individuals at CHR and 96 healthy controls (HC) acquired in a single imaging site. Eight cortical lobes were examined for GM volume and GM microstructure. A novel dMRI measure, interstitial free water (iFW), was used to quantify GM microstructure by eliminating cerebrospinal fluid contribution. Additionally, we assessed whether these measures differentiated the 33 individuals at CHR who developed psychosis (CHR-P) from the 127 individuals at CHR who did not (CHR-NP). At baseline the CHR group had significantly higher iFW than HC in the prefrontal, temporal, parietal, and occipital lobes, while volume was reduced only in the temporal lobe. Neither iFW nor volume differentiated between the CHR-P and CHR-NP groups at baseline. However, in most brain areas, the CHR-P group demonstrated significantly accelerated iFW increase and volume reduction with time than the CHR-NP group. Our results demonstrate that microstructural GM changes in individuals at CHR have a wider extent than volumetric changes and they predate the acceleration of brain changes that occur around psychosis onset. Microstructural GM changes are thus an early pathology at the prodromal stage of psychosis that may be useful for early detection and a better mechanistic understanding of psychosis development.

Cortical and subcortical brain morphometry abnormalities in youth at clinical high-risk for psychosis and individuals with early illness schizophrenia

Neuroimaging studies have documented morphometric brain abnormalities in schizophrenia, but less is known about them in individuals at clinical high-risk for psychosis (CHR-P), including how they compare with those observed in early schizophrenia (ESZ). Accordingly, we implemented multivariate profile analysis of regional morphometric profiles in CHR-P (n = 89), ESZ (n = 93) and healthy controls (HC; n = 122). ESZ profiles differed from HC and CHR-P profiles, including 1) cortical thickness: significant level reduction and regional non-parallelism reflecting widespread thinning, except for entorhinal and pericalcarine cortex, 2) basal ganglia volume: significant level increase and regional non-parallelism reflecting larger caudate and pallidum, and 3) ventricular volume: significant level increase with parallel regional profiles. CHR-P and ESZ cerebellar profiles showed significant non-parallelism with HC profiles. Regional profiles did not significantly differ between groups for cortical surface area or subcortical volume. Compared to CHR-P followed for ≥18 months without psychosis conversion (n = 31), CHR-P converters (n = 17) showed significant non-parallel ventricular volume expansion reflecting specific enlargement of lateral and inferolateral regions. Antipsychotic dosage in ESZ was significantly correlated with frontal cortical thinning. Results suggest that morphometric abnormalities in ESZ are not present in CHR-P, except for ventricular enlargement, which was evident in CHR-P who developed psychosis.

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.

Sex- and Age-Specific Deviations in Cerebellar Structure and Their Link With Symptom Dimensions and Clinical Outcome in Individuals at Clinical High Risk for Psychosis

BACKGROUND

The clinical high-risk (CHR) period offers a temporal window into neurobiological deviations preceding psychosis onset, but little attention has been given to regions outside the cerebrum in large-scale studies of CHR. Recently, the North American Prodrome Longitudinal Study (NAPLS)-2 revealed altered functional connectivity of the cerebello-thalamo-cortical circuitry among individuals at CHR; however, cerebellar morphology remains underinvestigated in this at-risk population, despite growing evidence of its involvement in psychosis.

STUDY DESIGN

In this multisite study, we analyzed T1-weighted magnetic resonance imaging scans obtained from N = 469 CHR individuals (61% male, ages = 12-36 years) and N = 212 healthy controls (52% male, ages = 12-34 years) from NAPLS-2, with a focus on cerebellar cortex and white matter volumes separately. Symptoms were rated by the Structured Interview for Psychosis-Risk Syndromes (SIPS). The outcome by two-year follow-up was categorized as in-remission, symptomatic, prodromal-progression, or psychotic. General linear models were used for case-control comparisons and tests for volumetric associations with baseline SIPS ratings and clinical outcomes.

STUDY RESULTS

Cerebellar cortex and white matter volumes differed between the CHR and healthy control groups at baseline, with sex moderating the difference in cortical volumes, and both sex and age moderating the difference in white matter volumes. Baseline ratings for major psychosis-risk dimensions as well as a clinical outcome at follow-up had tissue-specific associations with cerebellar volumes.

CONCLUSIONS

These findings point to clinically relevant deviations in cerebellar cortex and white matter structures among CHR individuals and highlight the importance of considering the complex interplay between sex and age when studying the neuromaturational substrates of psychosis risk.

Multi-ancestry phenome-wide association of complement component 4 variation with psychiatric and brain phenotypes in youth

BACKGROUND

Increased expression of the complement component 4A (C4A) gene is associated with a greater lifetime risk of schizophrenia. In the brain, C4A is involved in synaptic pruning; yet, it remains unclear the extent to which upregulation of C4A alters brain development or is associated with the risk for psychotic symptoms in childhood. Here, we perform a multi-ancestry phenome-wide association study in 7789 children aged 9-12 years to examine the relationship between genetically regulated expression (GREx) of C4A, childhood brain structure, cognition, and psychiatric symptoms.

RESULTS

While C4A GREx is not related to childhood psychotic experiences, cognition, or global measures of brain structure, it is associated with a localized reduction in regional surface area (SA) of the entorhinal cortex. Furthermore, we show that reduced entorhinal cortex SA at 9-10 years predicts a greater number and severity of psychosis-like events at 1-year and 2-year follow-up time points. We also demonstrate that the effects of C4A on the entorhinal cortex are independent of genome-wide polygenic risk for schizophrenia.

CONCLUSIONS

Our results suggest neurodevelopmental effects of C4A on childhood medial temporal lobe structure, which may serve as a biomarker for schizophrenia risk prior to symptom onset.

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

OBJECTIVE

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

METHOD

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

RESULTS

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

CONCLUSION

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

Genetic and Structural Brain Correlates of Cognitive Subtypes Across Youth at Family Risk for Schizophrenia and Bipolar Disorder

OBJECTIVE

Cognitive impairment is an important feature of schizophrenia (SZ) and bipolar disorder (BP) with severity across the two disorders characterized by significant heterogeneity. Youth at family risk for SZ and BP were clustered based on cognitive function and examined in terms of the clinical, genetic, and brain imaging correlates of cluster membership.

METHOD

One hundred sixty participants, 32 offspring of patients with SZ, 59 offspring of patients with BP and 69 offspring of healthy control parents underwent clinical and cognitive assessments, genotyping and structural MRI. K-means clustering was used to group family risk participants based on cognitive measures. Clusters were compared in terms of cortical and subcortical brain measures as well as polygenic risk scores.

RESULTS

Participants were grouped in 3 clusters with intact, intermediate, and impaired cognitive performance. The intermediate and impaired clusters had lower total brain surface area compared with the intact cluster, with prominent localization in frontal and temporal cortices. No between-cluster differences were identified in cortical thickness and subcortical brain volumes. The impaired cluster also had poorer psychosocial functioning and worse PRS-COG compared with the other 2 clusters and with offspring of healthy control parents, while there was no significant between-cluster difference in terms of PRS-SZ and PRS-BP. PRS-COG predicted psychosocial functioning, yet this effect did not appear to be mediated by an effect of PRS-COG on brain area.

CONCLUSION

Stratification based on cognition may help to elucidate the biological underpinnings of cognitive heterogeneity across SZ and BP risk.

Auditory N100 amplitude deficits predict conversion to psychosis in the North American Prodrome Longitudinal Study (NAPLS-2) cohort

BACKGROUND

The auditory N100 is an event related potential (ERP) that is reduced in schizophrenia, but its status in individuals at clinical high risk for psychosis (CHR) and its ability to predict conversion to psychosis remains unclear. We examined whether N100 amplitudes are reduced in CHR subjects relative to healthy controls (HC), and this reduction predicts conversion to psychosis in CHR.

METHODS

Subjects included CHR individuals (n = 552) and demographically similar HC subjects (n = 236) from the North American Prodrome Longitudinal Study. Follow-up assessments identified CHR individuals who converted to psychosis (CHRC; n = 73) and those who did not (CHR-NC; n = 225) over 24 months. Electroencephalography data were collected during an auditory oddball task containing Standard, Novel, and Target stimuli. N100 peak amplitudes following each stimulus were measured at electrodes Cz and Fz.

RESULTS

The CHR subjects had smaller N100 absolute amplitudes than HC subjects at Fz (F(1,786) = 4.00, p 0.046). A model comparing three groups (CHRC, CHR-NC, HC) was significant for Group at the Cz electrode (F(2,531) = 3.58, p = 0.029). Both Standard (p = 0.019) and Novel (p = 0.017) stimuli showed N100 absolute amplitude reductions in CHR-C relative to HC. A smaller N100 amplitude at Cz predicted conversion to psychosis in the CHR cohort (Standard: p = 0.009; Novel: p = 0.001) and predicted shorter time to conversion (Standard: p = 0.013; Novel: p = 0.001).

CONCLUSION

N100 amplitudes are reduced in CHR individuals which precedes the onset of psychosis. N100 deficits in CHR individuals predict a greater likelihood of conversion to psychosis. Our results highlight N100's utility as a biomarker of psychosis risk.

Age-dependent effects of schizophrenia genetic risk on cortical thickness and cortical surface area: Evaluating evidence for neurodevelopmental and neurodegenerative models of schizophrenia

Risk for schizophrenia peaks during early adulthood, a critical period for brain development. Although several influential theoretical models have been proposed for the developmental relationship between brain pathology and clinical onset, to our knowledge, no study has directly evaluated the predictions of these models for schizophrenia developmental genetic effects on brain structure. To address this question, we introduce a framework to estimate the effects of schizophrenia genetic variation on brain structure phenotypes across the life span. Five-hundred and six participants, including 30 schizophrenia probands, 200 of their relatives (aged 12-85 years) from 32 families with at least two first-degree schizophrenia relatives, and 276 unrelated controls, underwent MRI to assess regional cortical thickness (CT) and cortical surface area (CSA). Genetic variance decomposition analyses were conducted to distinguish among schizophrenia neurogenetic effects that are most salient before schizophrenia peak age-of-risk (i.e., early neurodevelopmental effects), after peak age-of-risk (late neurodevelopmental effects), and during the later plateau of age-of-risk (neurodegenerative effects). Genetic correlations between schizophrenia and cortical traits suggested early neurodevelopmental effects for frontal and insula CSA, late neurodevelopmental effects for overall CSA and frontal, parietal, and occipital CSA, and possible neurodegenerative effects for temporal CT and parietal CSA. Importantly, these developmental neurogenetic effects were specific to schizophrenia and not found with nonpsychotic depression. Our findings highlight the potentially dynamic nature of schizophrenia genetic effects across the lifespan and emphasize the utility of integrating neuroimaging methods with developmental behavior genetic approaches to elucidate the nature and timing of risk-conferring processes in psychopathology. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Accelerated Global and Local Brain Aging Differentiate Cognitively Impaired From Cognitively Spared Patients With Schizophrenia

Background

Accelerated aging has been proposed as a mechanism underlying the clinical and cognitive presentation of schizophrenia. The current study extends the field by examining both global and regional patterns of brain aging in schizophrenia, as inferred from brain structural data, and their association with cognitive and psychotic symptoms.

Methods

Global and local brain-age-gap-estimates (G-brainAGE and L-brainAGE) were computed using a U-Net Model from T1-weighted structural neuroimaging data from 84 patients (aged 16-35 years) with early-stage schizophrenia (illness duration <5 years) and 1,169 healthy individuals (aged 16-37 years). Multidomain cognitive data from the patient sample were submitted to Heterogeneity through Discriminative Analysis (HYDRA) to identify cognitive clusters.

Results

HYDRA classified patients into a cognitively impaired cluster (n = 69) and a cognitively spared cluster (n = 15). Compared to healthy individuals, G-brainAGE was significantly higher in the cognitively impaired cluster (+11.08 years) who also showed widespread elevation in L-brainAGE, with the highest deviance observed in frontal and temporal regions. The cognitively spared cluster showed a moderate increase in G-brainAGE (+8.94 years), and higher L-brainAGE localized in the anterior cingulate cortex. Psychotic symptom severity in both clusters showed a positive but non-significant association with G-brainAGE.

Discussion

Accelerated aging in schizophrenia can be detected at the early disease stages and appears more closely associated with cognitive dysfunction rather than clinical symptoms. Future studies replicating our findings in multi-site cohorts with larger numbers of participants are warranted.

Advanced Brain-Age in Psychotic Psychopathology: Evidence for Transdiagnostic Neurodevelopmental Origins

Schizophrenia is characterized by abnormal brain structure such as global reductions in gray matter volume. Machine learning models trained to estimate the age of brains from structural neuroimaging data consistently show advanced brain-age to be associated with schizophrenia. Yet, it is unclear whether advanced brain-age is specific to schizophrenia compared to other psychotic disorders, and whether evidence that brain structure is "older" than chronological age actually reflects neurodevelopmental rather than atrophic processes. It is also unknown whether advanced brain-age is associated with genetic liability for psychosis carried by biological relatives of people with schizophrenia. We used the Brain-Age Regression Analysis and Computation Utility Software (BARACUS) prediction model and calculated the residualized brain-age gap of 332 adults (163 individuals with psychotic disorders: 105 schizophrenia, 17 schizoaffective disorder, 41 bipolar I disorder with psychotic features; 103 first-degree biological relatives; 66 controls). The model estimated advanced brain-ages for people with psychosis in comparison to controls and relatives, with no differences among psychotic disorders or between relatives and controls. Specifically, the model revealed an enlarged brain-age gap for schizophrenia and bipolar disorder with psychotic features. Advanced brain-age was associated with lower cognitive and general functioning in the full sample. Among relatives, cognitive performance and schizotypal symptoms were related to brain-age gap, suggesting that advanced brain-age is associated with the subtle expressions associated with psychosis. Exploratory longitudinal analyses suggested that brain aging was not accelerated in individuals with a psychotic disorder. In sum, we found that people with psychotic disorders, irrespective of specific diagnosis or illness severity, show indications of non-progressive, advanced brain-age. These findings support a transdiagnostic, neurodevelopmental formulation of structural brain abnormalities in psychotic psychopathology.

Insula volumes in first-episode and chronic psychosis: A longitudinal MRI study

BACKGROUND

Alterations in insular grey matter (GM) volume has been consistently reported for affective and non-affective psychoses both in chronic and first-episode patients, ultimately suggesting that the insula might represent a good region to study in order to assess the longitudinal course of psychotic disorders. Therefore, in this longitudinal Magnetic Resonance Imaging (MRI) study, we aimed at further investigating the key role of insular volumes in psychosis.

MATERIAL AND METHODS

68 First-Episode Psychosis (FEP) patients, 68 patients with Schizophrenia (SCZ), 47 Bipolar Disorder (BD) patients, and 94 Healthy Controls (HC) were enrolled and underwent a 1.5 T MRI evaluation. A subsample of 99 subjects (10 HC, 23 BD, 29 SCZ, 37 FEP) was rescanned after 2,53 ± 1,68 years. The insular cortex was manually traced and then divided into an anterior and posterior portion. Group and correlation analyses were then performed both at baseline and at follow-up.

RESULTS

At baseline, greater anterior and lower posterior insular GM volumes were observed in chronic patients. At follow-up, we found that FEP patients had a significant GM volume increase from baseline to follow-up, especially in the posterior insula whereas chronic patients showed a relative stability. Finally, significant negative correlations between illness severity and pharmacological treatment and insular GM volumes were observed in the whole group of psychotic patients.

CONCLUSIONS

The longitudinal assessment of both chronic and first-episode patients allowed us to detect a complex pattern of GM abnormalities in selective sub-portions of insular volumes, ultimately suggesting that this structure could represent a key biological marker of psychotic disorders.

Longitudinal grey matter development associated with psychotic experiences in young people

Background

Gray matter abnormalities are observed across the psychosis spectrum. The trajectory of these abnormalities in healthy adolescents reporting subthreshold psychotic experiences (PEs) may provide insight into the neural mechanisms underlying psychotic symptoms. The risk of psychosis and additional psychopathology is even higher among these individuals who also report childhood adversity/DSM-5 diagnoses. Thus, the aims of this longitudinal study were to investigate PE-related volumetric changes in young people, noting any effects of childhood adversity/DSM-5 diagnosis.

Methods

A total of 211 young people 11 to 13 years of age participated in the initial Adolescent Brain Development study. PE classification was determined by expert consensus at each time point. Participants underwent neuroimaging at 3 time points over 6 years. A total of 76 participants with at least one scan were included in the final sample; 34 who met criteria for PEs at least once across all the time points (PE group) and 42 control subjects. Data from 20 bilateral regions of interest were extracted for linear mixed-effects analyses.

Results

Right hippocampal volume increased over time in the control group, with no increase in the PE group (p = .00352). DSM-5 diagnosis and childhood adversity were not significantly associated with right hippocampal volume. There was no significant effect of group or interaction in any other region.

Conclusions

These findings further implicate right hippocampal volumetric abnormalities in the pathophysiology underlying PEs. Furthermore, as suggested by previous studies in those at clinical high risk for psychosis and those with first-episode psychosis, it is possible that these deficits may be a marker for later clinical outcomes.

MR-Spectroscopy of GABA and Glutamate/Glutamine Concentrations in Auditory Cortex in Clinical High-Risk for Psychosis Individuals

Psychosis involves changes in GABAergic and glutamatergic neurotransmission in auditory cortex that could be important for understanding sensory deficits and symptoms of psychosis. However, it is currently unclear whether such deficits are present in participants at clinical high-risk for psychosis (CHR-P) and whether they are associated with clinical outcomes. Magnetic Resonance Spectroscopy (MEGAPRESS, 1H-MRS at 3 Tesla) was used to estimate GABA, glutamate, and glutamate-plus-glutamine (Glx) levels in auditory cortex in a large sample of CHR-P (n = 99), CHR-N (clinical high-risk negative, n = 32), and 45 healthy controls. Examined were group differences in metabolite concentrations as well as relationships with clinical symptoms, general cognition, and 1-year follow-up clinical and general functioning in the CHR-P group. Results showed a marginal (p = 0.039) main group effect only for Glx, but not for GABA and glutamate concentrations, and only in left, not right, auditory cortex. This effect did not survive multiple comparison correction, however. Exploratory post-hoc tests revealed that there were significantly lower Glx levels (p = 0.029, uncorrected) in the CHR-P compared to the CHR-N group, but not relative to healthy controls (p = 0.058, uncorrected). Glx levels correlated with the severity of perceptual abnormalities and disorganized speech scores. However, in the CHR-P group, Glx levels did not predict clinical or functional outcomes. Accordingly, the findings from the present study suggest that MRS-measured GABA, glutamate and Glx levels in auditory cortex of CHR-P individuals are largely intact.

Crossroad between current knowledge and new perspective of diagnostic and therapy of late-onset schizophrenia and very late-onset schizophrenia-like psychosis: An update

Schizophrenia is a chronic, highly individualized disease with many symptoms that can occur with varying severity in different patients. Schizophrenia affects 1% of the population, but occurs in almost 20% of patients after 40 years of age. It should be noted that the next peak in the incidence of schizophrenia occurs at the age of 60 years, affects mostly females, and is closely associated with a high risk of developing memory disorders. Therefore, postadolescent schizophrenia includes two distinct groups of patients: those whose symptoms onset at the age of 45 or 60. The purposes of this literature review were as follows: (1) synthetically characterize the clinical manifestations of schizophrenia; (2) discuss difficulties in the diagnosis of schizophrenia, especially in patients over 40 years of age; (3) discuss the clinical utility of different classes of marker in diagnostic and differentiating schizophrenia from neurodegenerative diseases in elderly people; (4) discuss therapeutic options for schizophrenia, pharmacotherapy, and psychotherapy, emphasizing the role of caregivers of people with psychosis in therapy, in preadolescence and postadolescence schizophrenia. We have tried to primarily discuss the findings of original articles from the last 10 years with an indication of their clinical implications with the issues discussed in the various subsections. Moreover, despite many years of research, no specific, precise algorithm has been developed that can be used in clinical practice during the diagnosis of schizophrenia. For this reason, the diagnosis of schizophrenia is primarily based on an interview with the patient and his family, as well as on the experience of a psychiatrist. It also seems that schizophrenia treatment should be carried out holistically, including pharmacotherapy, psychotherapy, and the support of caregivers of patients who have this psychosis, which increases the achievement of therapeutic success. Finally, we must be aware of the difficulties in diagnosing schizophrenia in the elderly and the need to modify pharmacological treatment. Currently, no guidelines have been developed for the differentiation of negative symptoms in elderly patients with schizophrenia from amotivation/avolition/apathy symptoms in elderly patients with neurodegenerative disorders.

Thalamic Shape Abnormalities Differentially Relate to Cognitive Performance in Early-Onset and Adult-Onset Schizophrenia

Early-onset schizophrenia (EOS) shares many biological and clinical features with adult-onset schizophrenia (AOS), but may represent a unique subgroup with greater susceptibility for disease onset and worsened symptomatology and progression, which could potentially derive from exaggerated neurodevelopmental abnormalities. Neurobiological explanations of schizophrenia have emphasized the involvement of deep-brain structures, particularly alterations of the thalamus, which have been linked to core features of the disorder. The aim of this study was to compare thalamic shape abnormalities between EOS and AOS subjects and determine whether unique behavioral profiles related to these differences. It was hypothesized abnormal thalamic shape would be observed in anterior, mediodorsal and pulvinar regions in both schizophrenia groups relative to control subjects, but exacerbated in EOS. Magnetic resonance T1-weighted images were collected from adult individuals with EOS (n = 28), AOS (n = 33), and healthy control subjects (n = 60), as well as collection of clinical and cognitive measures. Large deformation high-dimensional brain mapping was used to obtain three-dimensional surfaces of the thalamus. General linear models were used to compare groups on surface shape features, and Pearson correlations were used to examine relationships between thalamic shape and behavioral measures. Results revealed both EOS and AOS groups demonstrated significant abnormal shape of anterior, lateral and pulvinar thalamic regions relative to CON (all p < 0.007). Relative to AOS, EOS exhibited exacerbated abnormalities in posterior lateral, mediodorsal and lateral geniculate thalamic regions (p = 0.003). Thalamic abnormalities related to worse episodic memory in EOS (p = 0.03) and worse working memory (p = 0.047) and executive functioning (p = 0003) in AOS. Overall, findings suggest thalamic abnormalities are a prominent feature in both early- and late-onset schizophrenia, but exaggerated in EOS and have different brain-behavior profiles for each. The persistence of these abnormalities in adult EOS patients suggests they may represent markers of disrupted neurodevelopment that uniquely relate to the clinical and cognitive aspects of the illness.

Individualized Prediction of Prodromal Symptom Remission for Youth at Clinical High Risk for Psychosis

The clinical high-risk period before a first episode of psychosis (CHR-P) has been widely studied with the goal of understanding the development of psychosis; however, less attention has been paid to the 75%-80% of CHR-P individuals who do not transition to psychosis. It is an open question whether multivariable models could be developed to predict remission outcomes at the same level of performance and generalizability as those that predict conversion to psychosis. Participants were drawn from the North American Prodrome Longitudinal Study (NAPLS3). An empirically derived set of clinical and demographic predictor variables were selected with elastic net regularization and were included in a gradient boosting machine algorithm to predict prodromal symptom remission. The predictive model was tested in a comparably sized independent sample (NAPLS2). The classification algorithm developed in NAPLS3 achieved an area under the curve of 0.66 (0.60-0.72) with a sensitivity of 0.68 and specificity of 0.53 when tested in an independent external sample (NAPLS2). Overall, future remitters had lower baseline prodromal symptoms than nonremitters. This study is the first to use a data-driven machine-learning approach to assess clinical and demographic predictors of symptomatic remission in individuals who do not convert to psychosis. The predictive power of the models in this study suggest that remission represents a unique clinical phenomenon. Further study is warranted to best understand factors contributing to resilience and recovery from the CHR-P state.

Biomarkers for autism spectrum disorder: opportunities for magnetoencephalography (MEG)

This paper reviews a candidate biomarker for ASD, the M50 auditory evoked response component, detected by magnetoencephalography (MEG) and presents a position on the roles and opportunities for such a biomarker, as well as converging evidence from allied imaging techniques (magnetic resonance imaging, MRI and spectroscopy, MRS). Data is presented on prolonged M50 latencies in ASD as well as extension to include children with ASD with significant language and cognitive impairments in whom M50 latency delays are exacerbated. Modeling of the M50 latency by consideration of the properties of auditory pathway white matter is shown to be successful in typical development but challenged by heterogeneity in ASD; this, however, is capitalized upon to identify a distinct subpopulation of children with ASD whose M50 latencies lie well outside the range of values predictable from the typically developing model. Interestingly, this subpopulation is characterized by low levels of the inhibitory neurotransmitter GABA. Following from this, we discuss a potential use of the M50 latency in indicating “target engagement” acutely with administration of a GABA-B agonist, potentially distinguishing “responders” from “non-responders” with the implication of optimizing inclusion for clinical trials of such agents. Implications for future application, including potential evaluation of infants with genetic risk factors, are discussed. As such, the broad scope of potential of a representative candidate biological marker, the M50 latency, is introduced along with potential future applications.

This paper outlines a strategy for understanding brain dysfunction in individuals with intellectual and developmental disabilities (IDD). It is proposed that a multimodal approach (collection of brain structure, chemistry, and neuronal functional data) will identify IDD subpopulations who share a common disease pathway, and thus identify individuals with IDD who might ultimately benefit from specific treatments. After briefly demonstrating the need and potential for scope, examples from studies examining brain function and structure in children with autism spectrum disorder (ASD) illustrate how measures of brain neuronal function (from magnetoencephalography, MEG), brain structure (from magnetic resonance imaging, MRI, especially diffusion MRI), and brain chemistry (MR spectroscopy) can help us better understand the heterogeneity in ASD and form the basis of multivariate biological markers (biomarkers) useable to define clinical subpopulations. Similar approaches can be applied to understand brain dysfunction in neurodevelopmental disorders (NDD) in general. In large part, this paper represents our endeavors as part of the CHOP/Penn NICHD-funded intellectual and developmental disabilities research center (IDDRC) over the past decade.

Structural brain volumes of individuals at clinical high risk for psychosis: a meta-analysis

Background

Structural magnetic resonance imaging studies in individuals at clinical high risk (CHR) for psychosis have yielded conflicting results.

Methods

The aims of this study were to compare intracranial and structural brain volumes and variability of CHR individuals with those of healthy control (HC) subjects and to investigate brain volume differences and variability in CHR subjects with and without transition to psychosis. The PubMed and Embase databases were searched for relevant studies published before June 1, 2020.

Results

A total of 34 studies were deemed eligible, which included baseline data of 2111 CHR and 1472 HC participants. In addition, data were included for 401 CHR subjects who subsequently transitioned to psychosis and 1023 nontransitioned CHR participants. Whole-brain and left, right, and bilateral hippocampal volume were significantly smaller in CHR subjects than in HC subjects. Cerebrospinal fluid and lateral ventricle volumes were significantly larger in CHR subjects than in HC subjects. Variability was not significantly different in CHR subjects compared with HC subjects. CHR individuals with and without subsequent transition to psychosis did not show significant differences in any of the volumetric assessments or in variability.

Conclusions

This meta-analysis demonstrates reduced whole-brain and hippocampal volumes and increased cerebrospinal fluid and lateral ventricle volumes in CHR individuals. However, no significant differences were observed in any of the volumetric assessments between CHR individuals with and without subsequent transition to psychosis. These findings suggest that although structural brain alterations are present before the onset of the disorder, they may not significantly contribute to the identification of CHR individuals at the highest risk for the development of psychosis.

Association of Structural Magnetic Resonance Imaging Measures With Psychosis Onset in Individuals at Clinical High Risk for Developing Psychosis: An ENIGMA Working Group Mega-analysis

Importance

The ENIGMA clinical high risk (CHR) for psychosis initiative, the largest pooled neuroimaging sample of individuals at CHR to date, aims to discover robust neurobiological markers of psychosis risk.

Objective

To investigate baseline structural neuroimaging differences between individuals at CHR and healthy controls as well as between participants at CHR who later developed a psychotic disorder (CHR-PS+) and those who did not (CHR-PS-).

Design, Setting, and Participants

In this case-control study, baseline T1-weighted magnetic resonance imaging (MRI) data were pooled from 31 international sites participating in the ENIGMA Clinical High Risk for Psychosis Working Group. CHR status was assessed using the Comprehensive Assessment of At-Risk Mental States or Structured Interview for Prodromal Syndromes. MRI scans were processed using harmonized protocols and analyzed within a mega-analysis and meta-analysis framework from January to October 2020.

Main Outcomes and Measures

Measures of regional cortical thickness (CT), surface area, and subcortical volumes were extracted from T1-weighted MRI scans. Independent variables were group (CHR group vs control group) and conversion status (CHR-PS+ group vs CHR-PS- group vs control group).

Results

Of the 3169 included participants, 1428 (45.1%) were female, and the mean (SD; range) age was 21.1 (4.9; 9.5-39.9) years. This study included 1792 individuals at CHR and 1377 healthy controls. Using longitudinal clinical information, 253 in the CHR-PS+ group, 1234 in the CHR-PS- group, and 305 at CHR without follow-up data were identified. Compared with healthy controls, individuals at CHR exhibited widespread lower CT measures (mean [range] Cohen d = -0.13 [-0.17 to -0.09]), but not surface area or subcortical volume. Lower CT measures in the fusiform, superior temporal, and paracentral regions were associated with psychosis conversion (mean Cohen d = -0.22; 95% CI, -0.35 to 0.10). Among healthy controls, compared with those in the CHR-PS+ group, age showed a stronger negative association with left fusiform CT measures (F = 9.8; P < .001; q < .001) and left paracentral CT measures (F = 5.9; P = .005; q = .02). Effect sizes representing lower CT associated with psychosis conversion resembled patterns of CT differences observed in ENIGMA studies of schizophrenia (ρ = 0.35; 95% CI, 0.12 to 0.55; P = .004) and individuals with 22q11.2 microdeletion syndrome and a psychotic disorder diagnosis (ρ = 0.43; 95% CI, 0.20 to 0.61; P = .001).

Conclusions and Relevance

This study provides evidence for widespread subtle, lower CT measures in individuals at CHR. The pattern of CT measure differences in those in the CHR-PS+ group was similar to those reported in other large-scale investigations of psychosis. Additionally, a subset of these regions displayed abnormal age associations. Widespread disruptions in CT coupled with abnormal age associations in those at CHR may point to disruptions in postnatal brain developmental processes.

Baseline Cortical Thickness Reductions in Clinical High Risk for Psychosis: Brain Regions Associated with Conversion to Psychosis Versus Non-Conversion as Assessed at One-Year Follow-Up in the Shanghai-At-Risk-for-Psychosis (SHARP) Study

OBJECTIVE

To assess cortical thickness (CT) and surface area (SA) of frontal, temporal, and parietal brain regions in a large clinical high risk for psychosis (CHR) sample, and to identify cortical brain abnormalities in CHR who convert to psychosis and in the whole CHR sample, compared with the healthy controls (HC).

METHODS

Magnetic resonance imaging, clinical, and cognitive data were acquired at baseline in 92 HC, 130 non-converters, and 22 converters (conversion assessed at 1-year follow-up). CT and SA at baseline were calculated for frontal, temporal, and parietal subregions. Correlations between regions showing group differences and clinical scores and age were also obtained.

RESULTS

CT but not SA was significantly reduced in CHR compared with HC. Two patterns of findings emerged: (1) In converters, CT was significantly reduced relative to non-converters and controls in the banks of superior temporal sulcus, Heschl's gyrus, and pars triangularis and (2) CT in the inferior parietal and supramarginal gyrus, and at trend level in the pars opercularis, fusiform, and middle temporal gyri was significantly reduced in all high-risk individuals compared with HC. Additionally, reduced CT correlated significantly with older age in HC and in non-converters but not in converters.

CONCLUSIONS

These results show for the first time that fronto-temporo-parietal abnormalities characterized all CHR, that is, both converters and non-converters, relative to HC, while CT abnormalities in converters relative to CHR-NC and HC were found in core auditory and language processing regions.

Differential effects of cannabis exposure during early versus later adolescence on the expression of psychosis in homeless and precariously housed adults

Longitudinal studies of cannabis exposure during early adolescence in the general population frequently report an increased risk of subsequently developing psychotic symptoms or a psychotic illness. However, there is a dearth of knowledge about the effects of early cannabis exposure on psychosis in homeless and precariously housed adults, who represent a population afflicted with high rates of psychosis. The aim of the present study was to examine how early cannabis exposure (by age 15) compared to later first use (after age 15) affected the expression of adult psychosis in this population. Secondary measures of psychopathology, drug use, cognition and brain structure were also collected. 437 subjects were recruited from single room occupancy hotels in the urban setting of the Downtown Eastside of Vancouver, Canada. Psychiatric diagnoses were determined, and psychotic symptom severity was measured with the 5-factor PANSS. Participants completed a battery of neurocognitive tests, and brain structure was assessed using structural and diffusion tensor imaging MRI scans. Results indicated that early cannabis exposure was associated with an increased risk (OR = 1.09, p < .05) of developing substance induced psychosis, whereas later first use increased risk (OR = 2.19, p < .01) of developing schizophrenia or schizoaffective disorder. There was no group difference in neurocognitive function, although differences were observed in the lateral orbitofrontal cortex and white matter tract diffusivity. These findings indicate that early cannabis exposure in this population may increase the risk of developing drug associated psychoses, which could potentially be mediated in part through altered neurodevelopmental brain changes.

Pitch and Duration Mismatch Negativity are Associated With Distinct Auditory Cortex and Inferior Frontal Cortex Volumes in the First-Episode Schizophrenia Spectrum

Background

Pitch and duration mismatch negativity (pMMN/dMMN) are related to left Heschl's gyrus gray matter volumes in first-episode schizophrenia (FESz). Previous methods were unable to delineate functional subregions within and outside Heschl's gyrus. The Human Connectome Project multimodal parcellation (HCP-MMP) atlas overcomes this limitation by parcellating these functional subregions. Further, MMN has generators in inferior frontal cortex, and therefore, may be associated with inferior frontal cortex pathology. With the novel use of the HCP-MMP to precisely parcellate auditory and inferior frontal cortex, we investigated relationships between gray matter and pMMN and dMMN in FESz.

Methods

pMMN and dMMN were measured at Fz from 27 FESz and 27 matched healthy controls. T1-weighted MRI scans were acquired. The HCP-MMP atlas was applied to individuals, and gray matter volumes were calculated for bilateral auditory and inferior frontal cortex parcels and correlated with MMN. FDR correction was used for multiple comparisons.

Results

In FESz only, pMMN was negatively correlated with left medial belt in auditory cortex and area 47L in inferior frontal cortex. Duration MMN negatively correlated with the following auditory parcels: left medial belt, lateral belt, parabelt, TA2, and right A5. Further, dMMN was associated with left area 47L, right area 44, and right area 47L in inferior frontal cortex.

Conclusions

The novel approach revealed overlapping and distinct gray matter associations for pMMN and dMMN in auditory and inferior frontal cortex in FESz. Thus, pMMN and dMMN may serve as biomarkers of underlying pathological deficits in both similar and slightly different cortical areas.

Neuroimaging Markers of Resiliency in Youth at Clinical High Risk for Psychosis: A Qualitative Review

Psychotic disorders are highly debilitating and constitute a major public health burden. Identifying markers of psychosis risk and resilience is a necessary step toward understanding etiology and informing prevention and treatment efforts in individuals at clinical high risk (CHR) for psychosis. In this context, it is important to consider that neural risk markers have been particularly useful in identifying mechanistic determinants along with predicting clinical outcomes. Notably, despite a growing body of supportive literature and the promise of recent findings identifying potential neural markers, the current work on CHR resilience markers has received little attention. The present review provides a brief overview of brain-based risk markers with a focus on predicting symptom course. Next, the review turns to protective markers, examining research from nonpsychiatric and schizophrenia fields to build an understanding of framing, priorities, and potential, applying these ideas to contextualizing a small but informative body of resiliency-relevant CHR research. Four domains (neurocognition, emotion regulation, allostatic load, and sensory and sensorimotor function) were identified and are discussed in terms of behavioral and neural markers. Taken together, the literature suggests significant predictive value for brain-based markers for individuals at CHR for psychosis, and the limited but compelling resiliency work highlights the critical importance of expanding this promising area of inquiry.

Forecasting Remission From the Psychosis Risk Syndrome With Mismatch Negativity and P300: Potentials and Pitfalls

Clinical outcomes vary for individuals at clinical high risk (CHR) for psychosis, ranging from conversion to a psychotic disorder to full remission from the risk syndrome. Given that most CHR individuals do not convert to psychosis, recent research efforts have turned toward identifying specific predictors of CHR remission, a task that is conceptually and empirically dissociable from the identification of predictors of conversion to psychosis, and one that may reveal specific biological characteristics that confer resilience to psychosis and provide further insights into the mechanisms associated with the pathogenesis of schizophrenia and those underlying a transient CHR syndrome. Such biomarkers may ultimately facilitate the development of novel early interventions and support the optimization of individualized care. In this review, we focus on two event-related brain potential measures, mismatch negativity and P300, that have attracted interest as predictors of future psychosis among CHR individuals. We describe several recent studies examining whether mismatch negativity and P300 predict subsequent CHR remission and suggest that intact mismatch negativity and P300 may reflect the integrity of specific neurocognitive processes that confer resilience against the persistence of the CHR syndrome and its associated risk for future transition to psychosis. We also highlight several major methodological concerns associated with these studies that apply to the broader literature examining predictors of CHR remission. Among them is the concern that studies that predict dichotomous remission versus nonremission and/or dichotomous conversion versus nonconversion outcomes potentially confound remission and conversion effects, a phenomenon we demonstrate with a data simulation.

Attitudes towards Risk Prediction in a Help Seeking Population of Early Detection Centers for Mental Disorders-A Qualitative Approach

Big Data approaches raise hope for a paradigm shift towards illness prevention, while others are concerned about discrimination resulting from these approaches. This will become particularly important for people with mental disorders, as research on medical risk profiles and early detection progresses rapidly. This study aimed to explore views and attitudes towards risk prediction in people who, for the first time, sought help at one of three early detection centers for mental disorders in Germany (Cologne, Munich, Dresden). A total of 269 help-seekers answered an open-ended question on the potential use of risk prediction. Attitudes towards risk prediction and motives for its approval or rejection were categorized inductively and analyzed using qualitative content analysis. The anticipated impact on self-determination was a driving decision component, regardless of whether a person would decide for or against risk prediction. Results revealed diverse, sometimes contrasting, motives for both approval and rejection (e.g., the desire to control of one’s life as a reason for and against risk prediction). Knowledge about a higher risk as a potential psychological burden was one of the major reasons against risk prediction. The decision to make use of risk prediction is expected to have far-reaching effects on the quality of life and self-perception of potential users. Healthcare providers should empower those seeking help by carefully considering individual expectations and perceptions of risk prediction.

Social decline in the psychosis prodrome: Predictor potential and heterogeneity of outcome

BACKGROUND

While an established clinical outcome of high importance, social functioning has been emerging as possibly having a broader significance to the evolution of psychosis and long term disability. In the current study we explored the association between social decline, conversion to psychosis, and functional outcome in individuals at clinical high risk (CHR) for psychosis.

METHODS

585 subjects collected in the North American Prodrome Longitudinal Study (NAPLS2) were divided into 236 Healthy Controls (HCs), and CHR subjects that developed psychosis (CHR + C, N = 79), or those that did not (Non-Converters, CHR-NC, N = 270). CHR + C subjects were further divided into those that experienced an atypical decline in social functioning prior to baseline (beyond typical impairment levels) when in min-to-late adolescence (CHR + C-SD, N = 39) or those that did not undergoing a decline (CHR + C-NSD, N = 40).

RESULTS

Patterns of poor functional outcomes varied across the CHR subgroups: CHR-NC (Poor Social 36.3%, Role 42.2%) through CHR + C-NSD (Poor Social 50%, Poor Role 67.5%) to CHR + C-SD (Poor Social 76.9%, Poor Role 89.7%) functioning. The two Converter subgroups had comparable positive symptoms at baseline. At 12 months, the CHR + C-SD group stabilized, but social functioning levels remained significantly lower than the other two subgroups.

CONCLUSIONS

The current study demonstrates that pre-baseline social decline in mid-to-late adolescence predicts psychosis. In addition, we found that this social decline in converters is strongly associated with especially poor functional outcome and overall poorer prognosis. Role functioning, in contrast, has not shown similar predictor potential, and rather appears to be an illness indicator that worsens over time.

Hyperactivation of Posterior Default Mode Network During Self-Referential Processing in Children at Familial High-Risk for Psychosis

Patients with schizophrenia spectrum disorders show disturbances in self-referential processing and associated neural circuits including the default mode network (DMN). These disturbances may precede the onset of psychosis and may underlie early social and emotional problems. In this study, we examined self-referential processing in a group of children (7-12 years) at familial high risk (FHR) for psychosis (N = 17), compared to an age and sex-matched group of healthy control (HC) children (N = 20). The participants were presented with a list of adjectives and asked to indicate whether or not the adjectives described them (self-reference condition) and whether the adjectives described a good or bad trait (semantic condition). Three participants were excluded due to chance-level performance on the semantic task, leaving N = 15 FHR and N = 19 HC for final analysis. Functional MRI (fMRI) was used to measure brain activation during self-referential vs. semantic processing. Internalizing and externalizing problems were assessed with the Child Behavior Checklist (CBCL). Evaluating main effects of task (self > semantic) showed activation of medial prefrontal cortex in HC and precuneus/posterior cingulate cortex (PCC) in FHR. Group-comparison yielded significant results for the FHR > HC contrast, showing two clusters of hyperactivation in precuneus/ PCC (p = 0.004) and anterior cerebellum / temporo-occipital cortex (p = 0.009). Greater precuneus/PCC activation was found to correlate with greater CBCL internalizing (r = 0.60, p = 0.032) and total (r = 0.69, p = 0.009) problems. In all, this study shows hyperactivity of posterior DMN during self-referential processing in pre-adolescent FHR children. This finding posits DMN-related disturbances in self-processing as a developmental brain abnormality associated with familial risk factors that predates not just psychosis, but also the prodromal stage. Moreover, our results suggest that early disturbances in self-referential processing may be related to internalizing problems in at-risk children.

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

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

Structural and functional imaging markers for susceptibility to psychosis

The introduction of clinical criteria for the operationalization of psychosis high risk provided a basis for early detection and treatment of vulnerable individuals. However, about two-thirds of people meeting clinical high-risk (CHR) criteria will never develop a psychotic disorder. In the effort to increase prognostic precision, structural and functional neuroimaging have received growing attention as a potentially useful resource in the prediction of psychotic transition in CHR patients. The present review summarizes current research on neuroimaging biomarkers in the CHR state, with a particular focus on their prognostic utility and limitations. Large, multimodal/multicenter studies are warranted to address issues important for clinical applicability such as generalizability and replicability, standardization of clinical definitions and neuroimaging methods, and consideration of contextual factors (e.g., age, comorbidity).

Validation of the Bullying Scale for Adults - Results of the PRONIA-study

BACKGROUND

Bullying as a specific subtype of adverse life events is a major risk factor for poor mental health. Although many questionnaires on bullying are available, so far none covers bullying retrospectively throughout school and working life. To close this gap, the Bullying Scale for Adults (BSA) was designed.

METHODS

Based on data of 622 participants from five European countries collected in the prospective multicenter Personalized Prognostic Tools for Early Psychosis Management (PRONIA) study, we investigated whether the BSA is a reliable and valid measurement for bullying and whether there is a difference across different diagnostic groups of early mental disorders (recent onset depressive/ psychotic patients, patients at clinical high-risk of psychosis) and healthy controls.

RESULTS

Bullying experiences were significantly less frequent in healthy controls than in patient groups, with no significant differences between the three clinical groups. The BSA exhibited a high item scale discrimination (r > .3) and very good internal consistency (Cronbach's α = .93). Four factors were identified: 1. Sexual harassment, 2. Emotional Abuse, 3. Physical Abuse, 4. Problems at school. The highly significant correlation between bullying, and childhood adversities and trauma (r = .645, p < .001) indicated good concurrent validity.

DISCUSSION

The BSA is the first validated questionnaire that, in retrospective, reliably records various aspects of bullying (incl. its consequences) not only throughout childhood but also working life. It can be used to assess bullying as a transdiagnostic risk factor of mental disorders in different mental disorders, esp. psychosis and depression.

Developmental Trajectories of Cortical Thickness in Relation to Schizotypy During Adolescence

Investigating potential gray matter differences in adolescents presenting higher levels of schizotypy personality traits could bring further insights into the development of schizophrenia spectrum disorders. Research has yet to examine the morphological correlates of schizotypy features during adolescence prospectively, and no information is available on the developmental trajectories from adolescence to adulthood. We employed mixed model regression analysis to investigate developmental trajectories of cortical thickness (CT) in relation to schizotypy dimensions in a cohort of 109 adolescents from the general population for whom MRI-scans were acquired over a 5-year period, culminating in a total of 271 scans. Structural data were processed with FreeSurfer software, statistical analyses were conducted using mixed regression models following a ROI-based approach, and schizotypy was assessed with the Schizotypal Personality Questionnaire (SPQ). Accelerated thinning was observed in the posterior cingulate cortex in relation to high levels of positive schizotypy, whereas high levels of disorganized schizotypy were associated with a similar trajectory pattern in the anterior cingulate cortex. The developmental course of CT in the prefrontal, occipital, and cingulate cortices differed between adolescents expressing higher vs lower levels of negative schizotypy. Participants reporting high scores on all schizotypy dimensions were associated with differential trajectories of CT in posterior cingulate cortex and occipital cortex. Consistently with prospective developmental studies of clinical risk conversion, the negative schizotypy dimension appears to constitute the most informative dimension for psychosis-related psychopathology, as its cerebral correlates in adolescents most closely overlap with results found in clinical high risk for psychosis studies.

EEG microstates as biomarker for psychosis in ultra-high-risk patients

Resting-state EEG microstates are brief (50-100 ms) periods, in which the spatial configuration of scalp global field power remains quasi-stable before rapidly shifting to another configuration. Changes in microstate parameters have been described in patients with psychotic disorders. These changes have also been observed in individuals with a clinical or genetic high risk, suggesting potential usefulness of EEG microstates as a biomarker for psychotic disorders. The present study aimed to investigate the potential of EEG microstates as biomarkers for psychotic disorders and future transition to psychosis in patients at ultra-high-risk (UHR). We used 19-channel clinical EEG recordings and orthogonal contrasts to compare temporal parameters of four normative microstate classes (A-D) between patients with first-episode psychosis (FEP; n = 29), UHR patients with (UHR-T; n = 20) and without (UHR-NT; n = 34) later transition to psychosis, and healthy controls (HC; n = 25). Microstate A was increased in patients (FEP & UHR-T & UHR-NT) compared to HC, suggesting an unspecific state biomarker of general psychopathology. Microstate B displayed a decrease in FEP compared to both UHR patient groups, and thus may represent a state biomarker specific to psychotic illness progression. Microstate D was significantly decreased in UHR-T compared to UHR-NT, suggesting its potential as a selective biomarker of future transition in UHR patients.

Enhancing Psychosis Risk Prediction Through Computational Cognitive Neuroscience

Research suggests that early identification and intervention with individuals at clinical high risk (CHR) for psychosis may be able to improve the course of illness. The first generation of studies suggested that the identification of CHR through the use of specialized interviews evaluating attenuated psychosis symptoms is a promising strategy for exploring mechanisms associated with illness progression, etiology, and identifying new treatment targets. The next generation of research on psychosis risk must address two major limitations: (1) interview methods have limited specificity, as recent estimates indicate that only 15%-30% of individuals identified as CHR convert to psychosis and (2) the expertise needed to make CHR diagnosis is only accessible in a handful of academic centers. Here, we introduce a new approach to CHR assessment that has the potential to increase accessibility and positive predictive value. Recent advances in clinical and computational cognitive neuroscience have generated new behavioral measures that assay the cognitive mechanisms and neural systems that underlie the positive, negative, and disorganization symptoms that are characteristic of psychotic disorders. We hypothesize that measures tied to symptom generation will lead to enhanced sensitivity and specificity relative to interview methods and the cognitive intermediate phenotype measures that have been studied to date that are typically indicators of trait vulnerability and, therefore, have a high false positive rate for conversion to psychosis. These new behavioral measures have the potential to be implemented on the internet and at minimal expense, thereby increasing accessibility of assessments.

ENIGMA MDD: seven years of global neuroimaging studies of major depression through worldwide data sharing

A key objective in the field of translational psychiatry over the past few decades has been to identify the brain correlates of major depressive disorder (MDD). Identifying measurable indicators of brain processes associated with MDD could facilitate the detection of individuals at risk, and the development of novel treatments, the monitoring of treatment effects, and predicting who might benefit most from treatments that target specific brain mechanisms. However, despite intensive neuroimaging research towards this effort, underpowered studies and a lack of reproducible findings have hindered progress. Here, we discuss the work of the ENIGMA Major Depressive Disorder (MDD) Consortium, which was established to address issues of poor replication, unreliable results, and overestimation of effect sizes in previous studies. The ENIGMA MDD Consortium currently includes data from 45 MDD study cohorts from 14 countries across six continents. The primary aim of ENIGMA MDD is to identify structural and functional brain alterations associated with MDD that can be reliably detected and replicated across cohorts worldwide. A secondary goal is to investigate how demographic, genetic, clinical, psychological, and environmental factors affect these associations. In this review, we summarize findings of the ENIGMA MDD disease working group to date and discuss future directions. We also highlight the challenges and benefits of large-scale data sharing for mental health research.

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.

Discovery and Validation of Prediction Algorithms for Psychosis in Youths at Clinical High Risk

In the past 2 to 3 decades, clinicians have used the clinical high risk for psychosis (CHR-P) paradigm to better understand factors that contribute to the onset of psychotic disorders. While this paradigm is useful to identify individuals at risk, the CHR-P criteria are not sufficient to predict outcomes from the CHR-P population. Because approximately 25% of the CHR-P population will ultimately convert to psychosis, more precise methods of prediction are needed to account for heterogeneity in both risk factors and outcomes in the CHR-P population. To this end, several groups in recent years have used data-driven approaches to refine predictive algorithms to predict both conversion to psychosis and functional outcomes. These models have generally used either clinical and behavioral data, including demographics and measures of symptom severity, neurocognitive functioning, and social functioning, or neuroimaging data, including structural and functional measures, to predict conversion to psychosis in CHR-P samples. This review focuses on the empirical models that have been derived within each of these lines of research and evaluates the performance and methodology of these models. This review also serves to inform best practices for data-driven approaches and directions moving forward to improve our prediction of psychotic disorders and associated outcomes. Because sample size is still the most critical consideration in the current models, we urge that algorithms to predict conversion be conducted using multisite data in order to obtain the power necessary to conclusively determine predictive accuracy without overfitting.