Connectome development and a novel extension to the neurodevelopmental model of schizophrenia

Brain Markers of Resilience to Psychosis in High-Risk Individuals: A Systematic Review and Label-Based Meta-Analysis of Multimodal MRI Studies

Background/Objectives: Most individuals who have a familial or clinical risk of developing psychosis remain free from psychopathology. Identifying neural markers of resilience in these at-risk individuals may help clarify underlying mechanisms and yield novel targets for early intervention. However, in contrast to studies on risk biomarkers, studies on neural markers of resilience to psychosis are scarce. The current study aimed to identify potential brain markers of resilience to psychosis. Methods: A systematic review of the literature yielded a total of 43 MRI studies that reported resilience-associated brain changes in individuals with an elevated risk for psychosis. Label-based meta-analysis was used to synthesize findings across MRI modalities. Results: Resilience-associated brain changes were significantly overreported in the default mode and language network, and among highly connected and central brain regions. Conclusions: These findings suggest that the DMN and language-associated areas and central brain hubs may be hotspots for resilience-associated brain changes. These neural systems are thus of key interest as targets of inquiry and, possibly, intervention in at-risk populations.

Schizophrenia and Neurodevelopment: Insights From Connectome Perspective

BACKGROUND

Schizophrenia is conceptualized as a brain connectome disorder that can emerge as early as late childhood and adolescence. However, the underlying neurodevelopmental basis remains unclear. Recent interest has grown in children and adolescent patients who experience symptom onset during critical brain development periods. Inspired by advanced methodological theories and large patient cohorts, Chinese researchers have made significant original contributions to understanding altered brain connectome development in early-onset schizophrenia (EOS).

STUDY DESIGN

We conducted a search of PubMed and Web of Science for studies on brain connectomes in schizophrenia and neurodevelopment. In this selective review, we first address the latest theories of brain structural and functional development. Subsequently, we synthesize Chinese findings regarding mechanisms of brain structural and functional abnormalities in EOS. Finally, we highlight several pivotal challenges and issues in this field.

STUDY RESULTS

Typical neurodevelopment follows a trajectory characterized by gray matter volume pruning, enhanced structural and functional connectivity, improved structural connectome efficiency, and differentiated modules in the functional connectome during late childhood and adolescence. Conversely, EOS deviates with excessive gray matter volume decline, cortical thinning, reduced information processing efficiency in the structural brain network, and dysregulated maturation of the functional brain network. Additionally, common functional connectome disruptions of default mode regions were found in early- and adult-onset patients.

CONCLUSIONS

Chinese research on brain connectomes of EOS provides crucial evidence for understanding pathological mechanisms. Further studies, utilizing standardized analyses based on large-sample multicenter datasets, have the potential to offer objective markers for early intervention and disease treatment.

Applications of MRI in Schizophrenia: Current Progress in Establishing Clinical Utility

Schizophrenia is a severe mental illness that significantly impacts the lives of affected individuals and with increasing mortality rates. Early detection and intervention are crucial for improving outcomes but the lack of validated biomarkers poses great challenges in such efforts. The use of magnetic resonance imaging (MRI) in schizophrenia enables the investigation of the disorder's etiological and neuropathological substrates in vivo. After decades of research, promising findings of MRI have been shown to aid in screening high-risk individuals and predicting illness onset, and predicting symptoms and treatment outcomes of schizophrenia. The integration of machine learning and deep learning techniques makes it possible to develop intelligent diagnostic and prognostic tools with extracted or selected imaging features. In this review, we aimed to provide an overview of current progress and prospects in establishing clinical utility of MRI in schizophrenia. We first provided an overview of MRI findings of brain abnormalities that might underpin the symptoms or treatment response process in schizophrenia patients. Then, we summarized the ongoing efforts in the computer-aided utility of MRI in schizophrenia and discussed the gap between MRI research findings and real-world applications. Finally, promising pathways to promote clinical translation were provided. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 3.

Distinct white matter abnormalities and cognitive impairments in deficit schizophrenia: A cross-sectional diffusion tensor imaging study

Deficit schizophrenia (DS), characterized by persistent and primary negative symptoms, is considered a promising homogeneous subtype of schizophrenia. According to the disconnection hypothesis, abnormalities in white matter fibers are common in schizophrenia. However, comprehensive measurement of white matter metrics and exploration of the relationships between neuroanatomical changes and cognitive functions in DS patients are still unknown. A cross-sectional study was conducted, including 35 DS patients, 37 non-deficit schizophrenia (NDS) patients, and 39 healthy controls (HC), all male and matched for age and education level. The tract-based spatial statistics method was performed to detect differences in fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) among these three groups. Cognitive function in DS and NDS patients was assessed using the Mini-Mental State Examination (MMSE) and Mattis Dementia Rating Scale. Correlation analyses were performed between diffusion metrics in regions showing differences and clinical scales. The results showed significant differences in diffusion metrics (FA, RD, AD, MD) across DS, NDS, and HC groups, particularly in the corpus callosum, corona radiata, and thalamic radiations. Compare to NDS, DS patients exhibited more reductions in FA and increases in RD, especially in the right posterior thalamic radiation and right superior longitudinal fasciculus. Correlation analysis revealed that lower FA in specific regions was linked to worse cognitive and clinical symptoms. These findings reinforce the dysconnectivity hypothesis of schizophrenia and highlight the distinct pathological mechanisms of white matter impairments in DS. Correlations in crucial white matter regions suggest disruptions in thalamo-cortical feedback loops, potentially contributing to the cognitive impairments observed. This provides a deeper understanding of how structural brain changes relate to clinical symptoms.

Functional Connectome Hierarchy in Schizotypy and Its Associations With Expression of Schizophrenia-Related Genes

BACKGROUND AND HYPOTHESIS

Schizotypy has been conceptualized as a continuum of symptoms with marked genetic, neurobiological, and sensory-cognitive overlaps to schizophrenia. Hierarchical organization represents a general organizing principle for both the cortical connectome supporting sensation-to-cognition continuum and gene expression variability across the cortex. However, a mapping of connectome hierarchy to schizotypy remains to be established. Importantly, the underlying changes of the cortical connectome hierarchy that mechanistically link gene expressions to schizotypy are unclear.

STUDY DESIGN

The present study applied novel connectome gradient on resting-state fMRI data from 1013 healthy young adults to investigate schizotypy-associated sensorimotor-to-transmodal connectome hierarchy and assessed its similarity with the connectome hierarchy of schizophrenia. Furthermore, normative and differential postmortem gene expression data were utilized to examine transcriptional profiles linked to schizotypy-associated connectome hierarchy.

STUDY RESULTS

We found that schizotypy was associated with a compressed functional connectome hierarchy. Moreover, the pattern of schizotypy-related hierarchy exhibited a positive correlation with the connectome hierarchy observed in schizophrenia. This pattern was closely colocated with the expression of schizophrenia-related genes, with the correlated genes being enriched in transsynaptic, receptor signaling and calcium ion binding.

CONCLUSIONS

The compressed connectome hierarchy suggests diminished functional system differentiation, providing a novel and holistic system-level basis for various sensory-cognition deficits in schizotypy. Importantly, its linkage with schizophrenia-altered hierarchy and schizophrenia-related gene expression yields new insights into the neurobiological continuum of psychosis. It also provides mechanistic insight into how gene variation may drive alterations in functional hierarchy, mediating biological vulnerability of schizotypy to schizophrenia.

Functional brain networks in clinical high-risk for bipolar disorder and psychosis

Abnormal connectivity in the brain has been linked to the pathophysiology of severe mental illnesses, including bipolar disorder and schizophrenia. The current study aimed to investigate large-scale functional networks and global network metrics in clinical high-risk for bipolardisorder (CHR-BD, n = 25), clinical high-risk for psychosis (CHR-P, n = 30), and healthy controls (HCs, n = 19). Help-seeking youth at CHR-BD and CHR-P were recruited from the early intervention program at Dokuz Eylul University, Izmir, Turkey. Resting-state functional magnetic resonance imaging scans were obtained from youth at CHR-BD, CHR-P, and HCs. Graph theoretical analysis and network-based statistics were employed to construct and examine the topological features of the whole-brain metrics and large-scale functional networks. Connectivity was increased (i) between the visual and default mode, (ii) between the visual and salience, (iii) between the visual and cingulo-opercular networks, and decreased (i) within the default mode and (ii) between the default mode and fronto-parietal networks in the CHR-P compared to HCs. Decreased global efficiency was found in CHR-P compared to CHR-BD. Functional networks were not different between CHR-BD and HCs. Global efficiency was negatively correlated with subthreshold positive symptoms and thought disorder in the high-risk groups. The current results suggest disrupted networks in CHR-P compared to HCs and CHR-BD. Moreover, transdiagnostic psychosis features are linked to functional brain networks in the at-risk groups. However, given the small, medicated sample, results are exploratory and hypothesis-generating.

Age-related change in cortical thickness in adolescents at clinical high risk for psychosis: a longitudinal study

Progression to psychosis has been associated with increased cortical thinning in the frontal, temporal and parietal lobes in individuals at clinical high risk for the disorder (CHR-P). The timing and spatial extent of these changes are thought to be influenced by age. However, most evidence so far stems from adult samples. Longitudinal studies are essential to understanding the neuroanatomical changes associated to transition to psychosis during adolescence, and their relationship with age. We conducted a longitudinal, multisite study including adolescents at CHR-P and healthy controls (HC), aged 10-17 years. Structural images were acquired at baseline and at 18-month follow-up. Images were processed with the longitudinal pipeline in FreeSurfer. We used a longitudinal two-stage model to compute the regional cortical thickness (CT) change, and analyze between-group differences controlling for age, sex and scan, and corrected for multiple comparisons. Linear regression was used to study the effect of age at baseline. A total of 103 individuals (49 CHR-P and 54 HC) were included in the analysis. During follow-up, the 13 CHR-P participants who transitioned to psychosis exhibited greater CT decrease over time in the right parietal cortex compared to those who did not transition to psychosis and to HC. Age at baseline correlated with longitudinal changes in CT, with younger individuals showing greater cortical thinning in this region. The emergence of psychosis during early adolescence may have an impact on typical neuromaturational processes. This study provides new insights on the cortical changes taking place prior to illness onset.

Connectome dysfunction in patients at clinical high risk for psychosis and modulation by oxytocin

Abnormalities in functional brain networks (functional connectome) are increasingly implicated in people at Clinical High Risk for Psychosis (CHR-P). Intranasal oxytocin, a potential novel treatment for the CHR-P state, modulates network topology in healthy individuals. However, its connectomic effects in people at CHR-P remain unknown. Forty-seven men (30 CHR-P and 17 healthy controls) received acute challenges of both intranasal oxytocin 40 IU and placebo in two parallel randomised, double-blind, placebo-controlled cross-over studies which had similar but not identical designs. Multi-echo resting-state fMRI data was acquired at approximately 1 h post-dosing. Using a graph theoretical approach, the effects of group (CHR-P vs healthy control), treatment (oxytocin vs placebo) and respective interactions were tested on graph metrics describing the topology of the functional connectome. Group effects were observed in 12 regions (all pFDR < 0.05) most localised to the frontoparietal network. Treatment effects were found in 7 regions (all pFDR < 0.05) predominantly within the ventral attention network. Our major finding was that many effects of oxytocin on network topology differ across CHR-P and healthy individuals, with significant interaction effects observed in numerous subcortical regions strongly implicated in psychosis onset, such as the thalamus, pallidum and nucleus accumbens, and cortical regions which localised primarily to the default mode network (12 regions, all pFDR < 0.05). Collectively, our findings provide new insights on aberrant functional brain network organisation associated with psychosis risk and demonstrate, for the first time, that oxytocin modulates network topology in brain regions implicated in the pathophysiology of psychosis in a clinical status (CHR-P vs healthy control) specific manner.

Brain Abnormalities in Schizophrenia: A Comparative Imagistic Study

Background and Objectives: Neuroimaging reveals a link between psychiatric conditions and brain structural-functional changes, prompting a paradigm shift in viewing schizophrenia as a neurodevelopmental disorder. This study aims to identify and compare structural brain changes found during the first schizophrenia episode with those found after more than 5 years of illness. Materials and Methods: This prospective study involved 149 participants enrolled between 1 January 2019 and 31 December 2021. The participants were categorized into three groups: the first comprises 51 individuals with an initial psychotic episode, the second consists of 49 patients diagnosed with schizophrenia for over 5 years, and a control group comprising 50 individuals without a diagnosis of schizophrenia or any other psychotic disorder. All participants underwent brain CT examinations. Results: The study examined all three groups: first-episode schizophrenia (FES), schizophrenia (SCZ), and the control group. The FES group had a mean age of 26.35 years and a mean duration of illness of 1.2 years. The SCZ group, with a mean age of 40.08 years, had been diagnosed with schizophrenia for an average of 15.12 years. The control group, with a mean age of 34.60 years, had no schizophrenia diagnosis. Structural measurements revealed widening of frontal horns and lateral ventricles in the SCZ group compared to FES and the FES group compared to the control group. Differences in the dimensions of the third ventricle were noted between SCZ and FES, while no distinction was observed between FES and the control group. The fourth ventricle had similar measurements in FES and SCZ groups, both exceeding those of the control group. Our results showed higher densities in the frontal lobe in schizophrenia patients compared to FES and the control group, with the control group consistently displaying the lowest densities. Conclusions: In summary, our comparative imaging analysis of schizophrenia patients, first-episode schizophrenia, and control patients revealed distinct ventricular patterns, with SCZ showing greater widening than FES and FES wider than the control group. Frontal lobe density, assessed via cerebral CT scans, indicated a higher density in the SCZ group in both anterior and posterior cortex portions compared to FES and the control group, while the left posterior cortex in FES had the highest density. These findings highlight unique neuroanatomical features across groups, shedding light on structural differences associated with different stages of schizophrenia.

Large-scale mechanism hypothesis and research prospects of cognitive impairment in schizophrenia based on magnetic resonance imaging

Cognitive impairments in schizophrenia are pivotal clinical issues that need to be solved urgently. However, the mechanism remains unknown. It has been suggested that cognitive impairments in schizophrenia are associated with connectome damage, and are especially relevant to the disrupted hub nodes in the frontal and parietal lobes. Activating the dorsolateral prefrontal cortex (DLPFC) via repetitive transcranial magnetic stimulation (rTMS) could result in improved cognition. Based on several previous magnetic resonance imaging (MRI) studies on schizophrenia, we found that the first-episode patients showed connectome damage, as well as abnormal activation and connectivity of the DLPFC and inferior parietal lobule (IPL). Accordingly, we proposed that DLPFC-IPL pathway destruction might mediate connectome damage of cognitive impairments in schizophrenia. In the meantime, with the help of multimodal MRI and noninvasive neuromodulation tool, we may not only validate the hypothesis, but also find IPL as the potential intervention target for cognitive impairments in schizophrenia.

The schizophrenia syndrome, circa 2024: What we know and how that informs its nature

With new data about different aspects of schizophrenia being continually generated, it becomes necessary to periodically revisit exactly what we know. Along with a need to review what we currently know about schizophrenia, there is an equal imperative to evaluate the construct itself. With these objectives, we undertook an iterative, multi-phase process involving fifty international experts in the field, with each step building on learnings from the prior one. This review assembles currently established findings about schizophrenia (construct, etiology, pathophysiology, clinical expression, treatment) and posits what they reveal about its nature. Schizophrenia is a heritable, complex, multi-dimensional syndrome with varying degrees of psychotic, negative, cognitive, mood, and motor manifestations. The illness exhibits a remitting and relapsing course, with varying degrees of recovery among affected individuals with most experiencing significant social and functional impairment. Genetic risk factors likely include thousands of common genetic variants that each have a small impact on an individual's risk and a plethora of rare gene variants that have a larger individual impact on risk. Their biological effects are concentrated in the brain and many of the same variants also increase the risk of other psychiatric disorders such as bipolar disorder, autism, and other neurodevelopmental conditions. Environmental risk factors include but are not limited to urban residence in childhood, migration, older paternal age at birth, cannabis use, childhood trauma, antenatal maternal infection, and perinatal hypoxia. Structural, functional, and neurochemical brain alterations implicate multiple regions and functional circuits. Dopamine D-2 receptor antagonists and partial agonists improve psychotic symptoms and reduce risk of relapse. Certain psychological and psychosocial interventions are beneficial. Early intervention can reduce treatment delay and improve outcomes. Schizophrenia is increasingly considered to be a heterogeneous syndrome and not a singular disease entity. There is no necessary or sufficient etiology, pathology, set of clinical features, or treatment that fully circumscribes this syndrome. A single, common pathophysiological pathway appears unlikely. The boundaries of schizophrenia remain fuzzy, suggesting the absence of a categorical fit and need to reconceptualize it as a broader, multi-dimensional and/or spectrum construct.

Biological hypotheses, risk factors, and biomarkers of schizophrenia

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

Novel approaches in schizophrenia-from risk factors and hypotheses to novel drug targets

Schizophrenia is a severe psychiatric disorder characterized by emotional, behavioral and cognitive disturbances, and the treatment of schizophrenia is often complicated by noncompliance and pharmacoresistance. The search for the pathophysiological mechanisms underlying schizophrenia has resulted in the proposal of several hypotheses to explain the impacts of environmental, genetic, neurodevelopmental, immune and inflammatory factors on disease onset and progression. This review discusses the newest insights into the pathophysiology of and risk factors for schizophrenia and notes novel approaches in antipsychotic treatment and potential diagnostic and theranostic biomarkers. The current hypotheses focusing on neuromediators (dopamine, glutamate, and serotonin), neuroinflammation, the cannabinoid hypothesis, the gut-brain axis model, and oxidative stress are summarized. Key genetic features, including small nucleotide polymorphisms, copy number variations, microdeletions, mutations and epigenetic changes, are highlighted. Current pharmacotherapy of schizophrenia relies mostly on dopaminergic and serotonergic antagonists/partial agonists, but new findings in the pathophysiology of schizophrenia have allowed the expansion of novel approaches in pharmacotherapy and the establishment of more reliable biomarkers. Substances with promising results in preclinical and clinical studies include lumateperone, pimavanserin, xanomeline, roluperidone, agonists of trace amine-associated receptor 1, inhibitors of glycine transporters, AMPA allosteric modulators, mGLUR_2-3 agonists, D-amino acid oxidase inhibitors and cannabidiol. The use of anti-inflammatory agents as an add-on therapy is mentioned.

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.

Specific white matter connectomic changes in schizophrenia compared with psychotic bipolar disorder

BACKGROUND

Schizophrenia (SZ) and bipolar disorder with psychosis (BDP) can be clinically confusing. The specific connectomic changes in SZ compared with BDP may lead to a deeper comprehension of the pathophysiological core of SZ. Therefore, this study explored the common and distinct white matter (WM) structural connectomic alterations between these two diseases.

METHOD

Diffusion tensor imaging data were collected from 19 drug-naïve patients with first episode SZ, 19 drug-naïve patients with BDP, and 19 healthy controls (HC). A graph theoretical approach was used to assess the brain WM network properties.

RESULTS

Except for the clustering coefficients, no significant differences in the global parameters was found between SZ and BDP. Five brain regions, the right precentral, right post-cingulum, right insula, left superior occipital, and left inferior temporal gyri, showed specific differences in the nodal parameters in SZ compared with BDP and HC. Nine brain regions, the left rectus, left lingual, right inferior parietal, left superior temporal, right precentral, right postcentral, bilateral middle frontal, and right post-cingulum gyri, showed specific differences in the nodal parameters in BDP. Significant correlations between clinical symptoms and connectomic changes were detected in the right insula and left superior occipital gyrus in patients with SZ but in the left lingual gyrus in patients with BDP.

CONCLUSIONS

Identifying shared and distinct WM structural networks between SZ and BDP may improve the understanding of the neuroanatomy of mental diseases. Specifically, the insula, the inferior temporal, superior temporal, and the lingual gyri may help to distinguish between SZ and BDP.

Functional connectome organization predicts conversion to psychosis in clinical high-risk youth from the SHARP program

The emergence of prodromal symptoms of schizophrenia and their evolution into overt psychosis may stem from an aberrant functional reorganization of the brain during adolescence. To examine whether abnormalities in connectome organization precede psychosis onset, we performed a functional connectome analysis in a large cohort of medication-naive youth at risk for psychosis from the Shanghai At Risk for Psychosis (SHARP) study. The SHARP program is a longitudinal study of adolescents and young adults at Clinical High Risk (CHR) for psychosis, conducted at the Shanghai Mental Health Center in collaboration with neuroimaging laboratories at Harvard and MIT. Our study involved a total of 251 subjects, including 158 CHRs and 93 age-, sex-, and education-matched healthy controls. During 1-year follow-up, 23 CHRs developed psychosis. CHRs who would go on to develop psychosis were found to show abnormal modular connectome organization at baseline, while CHR non-converters did not. In all CHRs, abnormal modular connectome organization at baseline was associated with a threefold conversion rate. A region-specific analysis showed that brain regions implicated in early-course schizophrenia, including superior temporal gyrus and anterior cingulate cortex, were most abnormal in terms of modular assignment. Our results show that functional changes in brain network organization precede the onset of psychosis and may drive psychosis development in at-risk youth.

Altered hippocampal centrality and dynamic anatomical covariance of intracortical microstructure in first episode psychosis

Hippocampal circuitry has been posited to be fundamental to positive symptoms in psychosis, but its contributions to other factors important for outcome remains unclear. We hypothesized that longitudinal changes in the hippocampal circuit and concomitant changes of intracortical microstructure are altered in first episode psychosis (FEP) patients and that such changes are associated with negative symptoms and verbal memory. Longitudinal brain scans (2-4 visits over 3-15 months) were acquired for 27 FEP and 29 age- and sex-matched healthy controls. Quantitative T1 maps, sensitive to myelin content, were used to sample the microstructure of the hippocampal subfields and output circuitry (fimbria, alveus, fornix, mammillary bodies), and intracortical regions. Dynamic anatomical covariance in pair-wise regional trajectories were assessed for each subject, and graph theory was used to calculate a participation coefficient metric that quantifies the similarity/divergence between hippocampal and intracortical microstructure. The mean participation coefficient of the hippocampus was significantly reduced in FEP patients compared with controls, reflecting differences in output hippocampal regions. Importantly, lower participation coefficient of the hippocampal circuit was associated with worse negative symptoms, a relationship that was mediated by changes in verbal memory. This study provides evidence for reduced hippocampal centrality in FEP and concomitant changes in intracortical anatomy. Myelin-rich output regions of the hippocampus may be an important biological trigger in early psychosis, with cascading effects on broader cortical networks and resultant clinical profiles.

Resting-State Functional Network Organization Is Stable Across Adolescent Development for Typical and Psychosis Spectrum Youth

BACKGROUND

Resting-state functional neuroimaging captures large-scale network organization; whether this organization is intact or disrupted during adolescent development across the psychosis spectrum is unresolved. We investigated the integrity of network organization in psychosis spectrum youth and those with first episode psychosis (FEP) from late childhood through adulthood.

METHODS

We analyzed data from Philadelphia Neurodevelopmental Cohort (PNC; typically developing = 450, psychosis spectrum = 273, 8-22 years), a longitudinal cohort of typically developing youth (LUNA; N = 208, 1-3 visits, 10-25 years), and a sample of FEP (N = 39) and matched controls (N = 34). We extracted individual time series and calculated correlations from brain regions and averaged them for 4 age groups: late childhood, early adolescence, late adolescence, adulthood. Using multiple analytic approaches, we assessed network stability across 4 age groups, compared stability between controls and psychosis spectrum youth, and compared group-level network organization of FEP to controls. We explored whether variability in cognition or clinical symptomatology was related to network organization.

RESULTS

Network organization was stable across the 4 age groups in the PNC and LUNA typically developing youth and PNC psychosis spectrum youth. Psychosis spectrum and typically developing youth had similar functional network organization during all age ranges. Network organization was intact in PNC youth who met full criteria for psychosis and in FEP. Variability in cognitive functioning or clinical symptomatology was not related to network organization in psychosis spectrum youth or FEP.

DISCUSSION

These findings provide rigorous evidence supporting intact functional network organization in psychosis risk and psychosis from late childhood through adulthood.

Brain functional connectivity data enhance prediction of clinical outcome in youth at risk for psychosis

The first episode of psychosis is typically preceded by a prodromal phase with subthreshold symptoms and functional decline. Improved outcome prediction in this stage is needed to allow targeted early intervention. This study assesses a combined clinical and resting-state fMRI prediction model in 137 adolescents and young adults at Clinical High Risk (CHR) for psychosis from the Shanghai At Risk for Psychosis (SHARP) program. Based on outcome at one-year follow-up, participants were separated into three outcome categories including good outcome (symptom remission, N = 71), intermediate outcome (ongoing CHR symptoms, N = 30), and poor outcome (conversion to psychosis or treatment-refractory, N = 36). Validated clinical predictors from the psychosis-risk calculator were combined with measures of resting-state functional connectivity. Using multinomial logistic regression analysis and leave-one-out cross-validation, a clinical-only prediction model did not achieve a significant level of outcome prediction (F₁ = 0.32, p = .154). An imaging-only model yielded a significant prediction model (F₁ = 0.41, p = .016), but a combined model including both clinical and connectivity measures showed the best performance (F₁ = 0.46, p < .001). Influential predictors in this model included functional decline, verbal learning performance, a family history of psychosis, default-mode and frontoparietal within-network connectivity, and between-network connectivity among language, salience, dorsal attention, sensorimotor, and cerebellar networks. These findings suggest that brain changes reflected by alterations in functional connectivity may be useful for outcome prediction in the prodromal stage.

Neuroimaging in Schizophrenia

Schizophrenia is a chronic psychotic disorder with a lifetime prevalence of about 1%. Onset is typically in adolescence or early adulthood; characteristic symptoms include positive symptoms, negative symptoms, and impairments in cognition. Neuroimaging studies have shown substantive evidence of brain structural, functional, and neurochemical alterations that are more pronounced in the association cortex and subcortical regions. These abnormalities are not sufficiently specific to be of diagnostic value, but there may be a role for imaging techniques to provide predictions of outcome. Incorporating multimodal imaging datasets using machine learning approaches may offer better diagnostic and predictive value in schizophrenia.