Intrinsic Connectivity Network-Based Classification and Detection of Psychotic Symptoms in Youth With 22q11.2 Deletions

Robust and replicable functional brain signatures of 22q11.2 deletion syndrome and associated psychosis: a deep neural network-based multi-cohort study

A major genetic risk factor for psychosis is 22q11.2 deletion (22q11.2DS). However, robust and replicable functional brain signatures of 22q11.2DS and 22q11.2DS-associated psychosis remain elusive due to small sample sizes and a focus on small single-site cohorts. Here, we identify functional brain signatures of 22q11.2DS and 22q11.2DS-associated psychosis, and their links with idiopathic early psychosis, using one of the largest multi-cohort data to date. We obtained multi-cohort clinical phenotypic and task-free fMRI data from 856 participants (101 22q11.2DS, 120 idiopathic early psychosis, 101 idiopathic autism, 123 idiopathic ADHD, and 411 healthy controls) in a case-control design. A novel spatiotemporal deep neural network (stDNN)-based analysis was applied to the multi-cohort data to identify functional brain signatures of 22q11.2DS and 22q11.2DS-associated psychosis. Next, stDNN was used to test the hypothesis that the functional brain signatures of 22q11.2DS-associated psychosis overlap with idiopathic early psychosis but not with autism and ADHD. stDNN-derived brain signatures distinguished 22q11.2DS from controls, and 22q11.2DS-associated psychosis with very high accuracies (86-94%) in the primary cohort and two fully independent cohorts without additional training. Robust distinguishing features of 22q11.2DS-associated psychosis emerged in the anterior insula node of the salience network and the striatum node of the dopaminergic reward pathway. These features also distinguished individuals with idiopathic early psychosis from controls, but not idiopathic autism or ADHD. Our results reveal that individuals with 22q11.2DS exhibit a highly distinct functional brain organization compared to controls. Additionally, the brain signatures of 22q11.2DS-associated psychosis overlap with those of idiopathic early psychosis in the salience network and dopaminergic reward pathway, providing substantial empirical support for the theoretical aberrant salience-based model of psychosis. Collectively, our findings, replicated across multiple independent cohorts, advance the understanding of 22q11.2DS and associated psychosis, underscoring the value of 22q11.2DS as a genetic model for probing the neurobiological underpinnings of psychosis and its progression.

Synaptic-dependent developmental dysconnectivity in 22q11.2 deletion syndrome

Chromosome 22q11.2 deletion is among the strongest known genetic risk factors for neuropsychiatric disorders, including autism and schizophrenia. Brain imaging studies have reported disrupted large-scale functional connectivity in people with 22q11 deletion syndrome (22q11DS). However, the significance and biological determinants of these functional alterations remain unclear. Here, we use a cross-species design to investigate the developmental trajectory and neural underpinnings of brain dysconnectivity in 22q11DS. We find that LgDel mice, an established mouse model of 22q11DS, exhibit age-specific patterns of functional MRI (fMRI) dysconnectivity, with widespread fMRI hyper-connectivity in juvenile mice reverting to focal hippocampal hypoconnectivity over puberty. These fMRI connectivity alterations are mirrored by co-occurring developmental alterations in dendritic spine density, and are both transiently normalized by developmental GSK3β inhibition, suggesting a synaptic origin for this phenomenon. Notably, analogous hyper- to hypoconnectivity reconfiguration occurs also in human 22q11DS, where it affects hippocampal and cortical regions spatially enriched for synaptic genes that interact with GSK3β, and autism-relevant transcripts. Functional dysconnectivity in somatomotor components of this network is predictive of age-dependent social alterations in 22q11.2 deletion carriers. Taken together, these findings suggest that synaptic-related mechanisms underlie developmentally mediated functional dysconnectivity in 22q11DS.

Molecular and immunological origins of catatonia

Catatonia occurs secondary to both primary psychiatric and neuromedical etiologies. Emerging evidence suggests possible linkages between causes of catatonia and neuroinflammation. These include obvious infectious and inflammatory etiologies, common neuromedical illnesses such as delirium, and psychiatric entities such as depression and autism-spectrum disorders. Symptoms of sickness behavior, thought to be a downstream effect of the cytokine response, are common in many of these etiologies and overlap significantly with symptoms of catatonia. Furthermore, there are syndromes that overlap with catatonia that some would consider variants, including neuroleptic malignant syndrome (NMS) and akinetic mutism, which may also have neuroinflammatory underpinnings. Low serum iron, a common finding in NMS and malignant catatonia, may be caused by the acute phase response. Cellular hits involving either pathogen-associated molecular patterns (PAMP) danger signals or the damage-associated molecular patterns (DAMP) danger signals of severe psychosocial stress may set the stage for a common pathway immunoactivation state that could lower the threshold for a catatonic state in susceptible individuals. Immunoactivation leading to dysfunction in the anterior cingulate cortex (ACC)/mid-cingulate cortex (MCC)/medial prefrontal cortex (mPFC)/paralimbic cortico-striato-thalamo-cortical (CSTC) circuit, involved in motivation and movement, may be particularly important in generating the motor and behavioral symptoms of catatonia.

Methodological and Quality Flaws in the Use of Artificial Intelligence in Mental Health Research: Systematic Review

BACKGROUND

Artificial intelligence (AI) is giving rise to a revolution in medicine and health care. Mental health conditions are highly prevalent in many countries, and the COVID-19 pandemic has increased the risk of further erosion of the mental well-being in the population. Therefore, it is relevant to assess the current status of the application of AI toward mental health research to inform about trends, gaps, opportunities, and challenges.

OBJECTIVE

This study aims to perform a systematic overview of AI applications in mental health in terms of methodologies, data, outcomes, performance, and quality.

METHODS

A systematic search in PubMed, Scopus, IEEE Xplore, and Cochrane databases was conducted to collect records of use cases of AI for mental health disorder studies from January 2016 to November 2021. Records were screened for eligibility if they were a practical implementation of AI in clinical trials involving mental health conditions. Records of AI study cases were evaluated and categorized by the International Classification of Diseases 11th Revision (ICD-11). Data related to trial settings, collection methodology, features, outcomes, and model development and evaluation were extracted following the CHARMS (Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies) guideline. Further, evaluation of risk of bias is provided.

RESULTS

A total of 429 nonduplicated records were retrieved from the databases and 129 were included for a full assessment-18 of which were manually added. The distribution of AI applications in mental health was found unbalanced between ICD-11 mental health categories. Predominant categories were Depressive disorders (n=70) and Schizophrenia or other primary psychotic disorders (n=26). Most interventions were based on randomized controlled trials (n=62), followed by prospective cohorts (n=24) among observational studies. AI was typically applied to evaluate quality of treatments (n=44) or stratify patients into subgroups and clusters (n=31). Models usually applied a combination of questionnaires and scales to assess symptom severity using electronic health records (n=49) as well as medical images (n=33). Quality assessment revealed important flaws in the process of AI application and data preprocessing pipelines. One-third of the studies (n=56) did not report any preprocessing or data preparation. One-fifth of the models were developed by comparing several methods (n=35) without assessing their suitability in advance and a small proportion reported external validation (n=21). Only 1 paper reported a second assessment of a previous AI model. Risk of bias and transparent reporting yielded low scores due to a poor reporting of the strategy for adjusting hyperparameters, coefficients, and the explainability of the models. International collaboration was anecdotal (n=17) and data and developed models mostly remained private (n=126).

CONCLUSIONS

These significant shortcomings, alongside the lack of information to ensure reproducibility and transparency, are indicative of the challenges that AI in mental health needs to face before contributing to a solid base for knowledge generation and for being a support tool in mental health management.

Mitochondria in Early Forebrain Development: From Neurulation to Mid-Corticogenesis

Function of the mature central nervous system (CNS) requires a substantial proportion of the body’s energy consumption. During development, the CNS anlage must maintain its structure and perform stage-specific functions as it proceeds through discrete developmental stages. While key extrinsic signals and internal transcriptional controls over these processes are well appreciated, metabolic and mitochondrial states are also critical to appropriate forebrain development. Specifically, metabolic state, mitochondrial function, and mitochondrial dynamics/localization play critical roles in neurulation and CNS progenitor specification, progenitor proliferation and survival, neurogenesis, neural migration, and neurite outgrowth and synaptogenesis. With the goal of integrating neurodevelopmental biologists and mitochondrial specialists, this review synthesizes data from disparate models and processes to compile and highlight key roles of mitochondria in the early development of the CNS with specific focus on forebrain development and corticogenesis.

Structural and functional brain alterations revealed by neuroimaging in CNV carriers

Copy Number Variants (CNVs) are associated with elevated rates of neuropsychiatric disorders. A 'genetics-first' approach, involving the CNV effects on the brain, irrespective of clinical symptomatology, allows investigation of mechanisms underlying neuropsychiatric disorders in the general population. Recent years have seen an increasing number of larger multisite neuroimaging studies investigating the effect of CNVs on structural and functional brain endophenotypes. Alterations overlap with those found in idiopathic psychiatric conditions but effect sizes are twofold to fivefold larger. Here we review new CNV-associated structural and functional brain alterations and outline the future of neuroimaging genomics research, with particular emphasis on developing new resources for the study of high-risk CNVs and rare genomic variants.

Mutations associated with neuropsychiatric conditions delineate functional brain connectivity dimensions contributing to autism and schizophrenia

16p11.2 and 22q11.2 Copy Number Variants (CNVs) confer high risk for Autism Spectrum Disorder (ASD), schizophrenia (SZ), and Attention-Deficit-Hyperactivity-Disorder (ADHD), but their impact on functional connectivity (FC) remains unclear. Here we report an analysis of resting-state FC using magnetic resonance imaging data from 101 CNV carriers, 755 individuals with idiopathic ASD, SZ, or ADHD and 1,072 controls. We characterize CNV FC-signatures and use them to identify dimensions contributing to complex idiopathic conditions. CNVs have large mirror effects on FC at the global and regional level. Thalamus, somatomotor, and posterior insula regions play a critical role in dysconnectivity shared across deletions, duplications, idiopathic ASD, SZ but not ADHD. Individuals with higher similarity to deletion FC-signatures exhibit worse cognitive and behavioral symptoms. Deletion similarities identified at the connectivity level could be related to the redundant associations observed genome-wide between gene expression spatial patterns and FC-signatures. Results may explain why many CNVs affect a similar range of neuropsychiatric symptoms.

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

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

Cingulate-basal ganglia-thalamo-cortical aspects of catatonia and implications for treatment

The catatonic syndrome is an example of a multifactorial neurobehavioral disorder that causes much morbidity and mortality but also has the potential to unlock the mystery of how motivation and movement interact to produce behavior. In this chapter, an attempt is made to understand better the catatonic syndrome through the lens of neurobiology and neuropathophysiology updated by recent studies in molecular biology, genomics, inflammasomics, neuroimaging, neural network theory, and neuropsychopathology. This will result in a neurostructural model for the catatonic syndrome that centers on paralimbic regions including the anterior and midcingulate cortices, as they interface with striatal and thalamic nodes in the salience decision-making network. Examination of neurologic disorders like the abulic syndrome, which includes in its extreme catatonic form, akinetic mutism, will identify the cingulate cortex and paralimbic neighbors as regions of interest. This exploration has the potential to unlock mysteries of the brain cascade from motivation to movement and to clarify catatonia therapeutics. Such a synthesis may also help us discern meaning inherent in this complex neurobehavioral syndrome.

Divergent default mode network connectivity during social perception in 22q11.2 deletion syndrome

AIM

The 22q11.2 deletion (22q11DS) syndrome is a neurogenetic condition marked by social dysfunction. A major network involved in social cognition is the default mode network (DMN). To date, no study has investigated DMN functional connectivity during socio-cognitive paradigms in 22q11DS.

METHOD

We used the psychophysiological analysis (PPI) to investigate functional connectivity of the DMN during social perception in 22 participants with 22q11DS and 22 healthy controls. Association between DMN connectivity and prodromal symptoms was also examined.

RESULTS

22q11DS patients exhibited stronger connectivity between the inferior parietal lobule (IPL) and the posterior cingulate cortex (PCC)/precuneus as well as lower connectivity between the precuneus and middle/superior frontal regions compared to controls. Association between IPL-PCC/precuneus connectivity and negative symptoms was also found in individuals with 22q11DS.

CONCLUSION

Our results point to (1) divergent DMN connectivity in patients with 22q11DS compared to controls; (2) association between DMN connectivity and negative symptom severity in patients. Results support the role of the DMN in social deficits of the 22q11DS population.

Resting-State Functional Connectivity and Psychotic-like Experiences in Childhood: Results From the Adolescent Brain Cognitive Development Study

BACKGROUND

Psychotic-like experiences (PLEs) during childhood are associated with greater risk of developing a psychotic disorder (and other mental disorders), highlighting the importance of identifying neural correlates of childhood PLEs. Three major cortical networks-the cingulo-opercular network (CON), default mode network (DMN), and frontoparietal network-are consistently implicated in psychosis and PLEs in adults. However, it is unclear whether variation in functional connectivity is associated with PLEs in school-aged children.

METHODS

Using hierarchical linear models, we examined the relationships between childhood PLEs and resting-state functional connectivity of the CON, DMN, and frontoparietal network, as well as the other networks, using an a priori network parcellation, using data from 9- to 11-year-olds (n = 3434) in the ABCD (Adolescent Brain Cognitive Development) study. We examined within-network, between-network, and subcortical connectivity.

RESULTS

Decreased CON and DMN connectivity, as well as cinguloparietal (CPAR) network connectivity, were associated with greater PLEs, even after accounting for family history of psychotic disorders, internalizing symptoms, and cognitive performance. Decreased DMN connectivity was more strongly associated with increased delusional ideation, whereas decreased CON connectivity was more strongly associated with increased perceptual distortions. Increased CON-cerebellar and decreased CPAR-cerebellar connectivity were also associated with increased PLEs, and CPAR-cerebellar connectivity was more strongly associated with increased perceptual distortions.

CONCLUSIONS

Consistent with hypotheses about the dimensionality of psychosis, our results provide novel evidence that neural correlates of PLEs, such as reduced functional connectivity of higher-order cognitive networks, are present even in school-aged children. The results provide further validation for continuity of PLEs across the life span.

Mitochondrial Dysfunction Leads to Cortical Under-Connectivity and Cognitive Impairment

Under-connectivity between cerebral cortical association areas may underlie cognitive deficits in neurodevelopmental disorders, including the 22q11.2 deletion syndrome (22q11DS). Using the LgDel 22q11DS mouse model, we assessed cellular, molecular, and developmental origins of under-connectivity and its consequences for cognitive function. Diminished 22q11 gene dosage reduces long-distance projections, limits axon and dendrite growth, and disrupts mitochondrial and synaptic integrity in layer 2/3 but not 5/6 projection neurons (PNs). Diminished dosage of Txnrd2, a 22q11 gene essential for reactive oxygen species catabolism in brain mitochondria, recapitulates these deficits in WT layer 2/3 PNs; Txnrd2 re-expression in LgDel layer 2/3 PNs rescues them. Anti-oxidants reverse LgDel- or Txnrd2-related layer 2/3 mitochondrial, circuit, and cognitive deficits. Accordingly, Txnrd2-mediated oxidative stress reduces layer 2/3 connectivity and impairs cognition in the context of 22q11 deletion. Anti-oxidant restoration of mitochondrial integrity, cortical connectivity, and cognitive behavior defines oxidative stress as a therapeutic target in neurodevelopmental disorders.

Recent developments in understanding the relationship between 22q11.2 deletion syndrome and psychosis

PURPOSE OF REVIEW

Individuals with 22q11.2 deletion syndrome have high rates of comorbid mental illness, particularly psychosis and schizophrenia. The purpose of this review is to summarize recent research in the area of 22q11.2 deletion syndrome and psychosis.

RECENT FINDINGS

Research over the past year has identified negative symptoms, functional impairment, dysphoric mood and a childhood diagnosis of attention deficit hyperactivity disorder as important clinical predictors of psychosis risk in 22q11.2 deletion syndrome. As previously reported in nondeleted schizophrenia, recent studies have implicated neuroinflammation as a possible neurobiological mechanism for psychosis in 22q11.2 deletion syndrome. Recent neuroimaging findings suggest that the cortex is significantly thinner in those with 22q11.2 deletion syndrome and psychosis compared to those without psychosis, replicating similar findings in nondeleted schizophrenia. Further data from the International 22q11.2 Deletion Syndrome Brain and Behavior Consortium have suggested that chromosomal microdeletions are significantly more likely to involve protein-coding genes and several rare copy number variants are associated with the presence of psychosis in deleted individuals.

SUMMARY

There have been several significant recent advances to further characterize the high rates of psychosis in 22q11.2 deletion syndrome, to identify additional clinical predictors of psychosis and to increase our understanding of the neural substrate and genetic aetiology of psychosis in 22q11.2 deletion syndrome.

Dissociable Disruptions in Thalamic and Hippocampal Resting-State Functional Connectivity in Youth with 22q11.2 Deletions

The 22q11.2 deletion syndrome (22q11DS) is a recurrent copy number variant with high penetrance for developmental neuropsychiatric disorders. Study of individuals with 22q11DS therefore may offer key insights into neural mechanisms underlying such complex illnesses. Resting-state functional connectivity MRI studies in idiopathic schizophrenia have consistently revealed disruption of thalamic and hippocampal circuitry. Here, we sought to test whether this circuitry is similarly disrupted in the context of this genetic high-risk condition. To this end, resting-state functional connectivity patterns were assessed in a sample of human youth with 22q11DS (n = 42; 59.5% female) and demographically matched healthy controls (n = 39; 53.8% female). Neuroimaging data were acquired via single-band protocols and analyzed in line with methods provided by the Human Connectome Project. We computed functional relationships between individual-specific anatomically defined thalamic and hippocampal seeds and all gray matter voxels in the brain. Whole-brain Type I error protection was achieved through nonparametric permutation-based methods. The 22q11DS patients displayed dissociable disruptions in thalamic and hippocampal functional connectivity relative to control subjects. Thalamocortical coupling was increased in somatomotor regions and reduced across associative networks. The opposite effect was observed for the hippocampus in regards to somatomotor and associative network connectivity. The thalamic and hippocampal dysconnectivity observed in 22q11DS suggests that high genetic risk for psychiatric illness is linked with disruptions in large-scale corticosubcortical networks underlying higher-order cognitive functions. These effects highlight the translational importance of large-effect copy number variants for informing mechanisms underlying neural disruptions observed in idiopathic developmental neuropsychiatric disorders.SIGNIFICANCE STATEMENT Investigation of neuroimaging biomarkers in highly penetrant genetic syndromes represents a more biologically tractable approach to identify neural circuit disruptions underlying developmental neuropsychiatric conditions. The 22q11.2 deletion syndrome confers particularly high risk for psychotic disorders and is thus an important translational model in which to investigate systems-level mechanisms implicated in idiopathic illness. Here, we show resting-state fMRI evidence of large-scale sensory and executive network disruptions in youth with 22q11DS. In particular, this study provides the first evidence that these networks are disrupted in a dissociable fashion with regard to the functional connectivity of the thalamus and hippocampus, suggesting circuit-level dysfunction.

Frontal dysconnectivity in 22q11.2 deletion syndrome: an atlas-based functional connectivity analysis

BACKGROUND

22q11.2 deletion syndrome (22q11DS) is a neurodevelopmental syndrome associated with deficits in cognitive and emotional processing. This syndrome represents one of the highest risk factors for the development of schizophrenia. Previous studies of functional connectivity (FC) in 22q11DS report aberrant connectivity patterns in large-scale networks that are associated with the development of psychotic symptoms.

METHODS

In this study, we performed a functional connectivity analysis using the CONN toolbox to test for differential connectivity patterns between 54 individuals with 22q11DS and 30 healthy controls, between the ages of 17-25 years old. We mapped resting-state fMRI data onto 68 atlas-based regions of interest (ROIs) generated by the Desikan-Killany atlas in FreeSurfer, resulting in 2278 ROI-to-ROI connections for which we determined total linear temporal associations between each. Within the group with 22q11DS only, we further tested the association between prodromal symptoms of psychosis and FC.

RESULTS

We observed that relative to controls, individuals with 22q11DS displayed increased FC in lobar networks involving the frontal-frontal, frontal-parietal, and frontal-occipital ROIs. In contrast, FC between ROIs in the parietal-temporal and occipital lobes was reduced in the 22q11DS group relative to healthy controls. Moreover, positive psychotic symptoms were positively associated with increased functional connections between the left precuneus and right superior frontal gyrus, as well as reduced functional connectivity between the bilateral pericalcarine. Positive symptoms were negatively associated with increased functional connectivity between the right pericalcarine and right postcentral gyrus.

CONCLUSIONS

Our results suggest that functional organization may be altered in 22q11DS, leading to disruption in connectivity between frontal and other lobar substructures, and potentially increasing risk for prodromal psychosis.

A Mini Review on the Contribution of the Anterior Cingulate Cortex in the Risk of Psychosis in 22q11.2 Deletion Syndrome

22q11.2 deletion syndrome (22q11DS) is a neurogenetic disorder that causes a high risk of developing schizophrenia, thus representing a unique model for the investigation of biomarkers of psychosis. Cognitive and clinical risk factors have been identified as reliable predictors of schizophrenia in patients with 22q11DS and are currently used in the clinical practice. However, biomarkers based on neuroimaging are still lacking, mainly because of the analytic approaches adopted so far, which are almost uniquely based on the comparison of 22q11DS patients with healthy controls. Such comparisons do not take into account the heterogeneity within patients with 22q11DS, who indeed show various clinical manifestations. More recently, a number of studies compared measures of brain morphology and connectivity between patients with 22q11DS with different symptomatic profiles. The aim of this short review is to highlight the brain alterations found in patients with 22q11DS fulfilling ultra-high risk (UHR) criteria. Findings point to alterations in brain morphology and connectivity in frontal brain regions, and in particular in the anterior cingulate cortex, in patients with 22q11DS presenting UHR symptoms. These alterations may represent valuable biomarkers of psychosis in 22q11DS.