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The amygdala is a key region in emotional regulation, which is often impaired in psychosis. However, it is unclear if amygdala dysfunction directly contributes to psychosis, or whether it contributes to psychosis through symptoms of emotional dysregulation. We studied the functional connectivity of amygdala subdivisions in patients with 22q11.2DS, a known genetic model for psychosis susceptibility. We investigated how dysmaturation of each subdivision’s connectivity contributes to positive psychotic symptoms and impaired tolerance to stress in deletion carriers.Longitudinally-repeated MRI scans from 105 patients with 22q11.2DS (64 at high-risk for psychosis and 37 with impaired tolerance to stress) and 120 healthy controls between the ages of 5 to 30 years were included. We calculated seed-based whole-brain functional connectivity for amygdalar subdivisions and employed a longitudinal multivariate approach to evaluate the developmental trajectory of functional connectivity across groups.Patients with 22q11.2DS presented a multivariate pattern of decreased basolateral amygdala (BLA)-frontal connectivity alongside increased BLA-hippocampal connectivity. Moreover, associations between developmental drops in centro-medial amygdala (CMA)-frontal connectivity to both impaired tolerance to stress and positive psychotic symptoms in deletion carriers were detected. SFA hyperconnectivity to the striatum was revealed as a specific pattern arising in patients who develop mild to moderate positive psychotic symptoms.Overall, CMA-frontal dysconnectivity was found as a mutual neurobiological substrate in both impaired tolerance to stress and psychosis, suggesting a role in prodromal dysregulation of emotions in psychosis. While BLA dysconnectivity was presented as an early finding in patients with 22q11.2DS, contributing to impaired tolerance to stress.

BACKGROUND: Hippocampal alterations are among the most replicated neuroimaging findings across the psychosis spectrum. Moreover, there is strong translational evidence that preserving the maturation of hippocampal networks in mice models prevents the progression of cognitive deficits. However, the developmental trajectory of hippocampal functional connectivity (HFC) and its contribution to psychosis is not well characterized in the human population. 22q11 deletion syndrome (22q11DS) offers a unique model for characterizing early neural correlates of schizophrenia., METHODS: We acquired resting-state functional magnetic resonance imaging in 242 longitudinally repeated scans from 84 patients with 22q11DS (30 with moderate to severe positive psychotic symptoms) and 94 healthy control subjects in the age span of 6 to 32 years. We obtained bilateral hippocampus to whole-brain functional connectivity and employed a novel longitudinal multivariate approach by means of partial least squares correlation to evaluate the developmental trajectory of HFC across groups., RESULTS: Relative to control subjects, patients with 22q11DS failed to increase HFC with frontal regions such as the dorsal part of the anterior cingulate cortex, prefrontal cortex, and supplementary motor area. Concurrently, carriers of the deletion had abnormally higher HFC with subcortical dopaminergic areas. Remarkably, this aberrant maturation of HFC was more prominent during midadolescence and was mainly driven by patients exhibiting subthreshold positive psychotic symptoms., CONCLUSIONS: Our findings suggest a critical period of prefrontal cortex & ndash;hippocampal & ndash;striatal circuit dysmaturation, particularly during late adolescence, which in light of current translation evidence could be a target for short-term interventions to potentially achieve long-lasting rescue of circuit dysfunctions associated with psychosis.

22q11.2 deletion syndrome (22q11DS) contributes dramatically increased genetic risk for psychopathology, and in particular schizophrenia. Sleep disorders, including obstructive sleep apnea (OSA), are also highly prevalent, making 22q11DS a unique model to explore their impact on psychosis vulnerability. Still, the contribution of sleep disturbances to psychosis vulnerability remains unclear.We characterized the sleep phenotype of 69 individuals with 22q11DS and 38 healthy controls with actigraphy and sleep questionnaires. Psychiatric symptoms were measured concomitantly with the baseline sleep assessment and at longitudinal follow-up, 3.58±0.85 years later. We used a novel multivariate partial-least-square-correlation (PLSC) approach to identify sleep patterns combining objective and subjective variables, which correlated with psychiatric symptoms. We dissected longitudinal pathways linking sleep disturbances to psychosis, using multi-layer-network-analysis.22q11DS was characterized by a non-restorative sleep pattern, combining increased daytime fatigue despite longer sleep duration. Non-restorative sleep combined with OSA symptoms correlated with both emotional and psychotic symptoms. Moreover, a sleep pattern evocative of OSA predicted longitudinal worsening of positive and negative symptoms, by accentuating the effects of emotional dysregulation. These results suggest that sleep disturbances could significantly increase psychosis risk, along an affective pathway. If confirmed, this suggests that systematic screening of sleep quality could mitigate psychosis vulnerability in 22q11DS.

Atypical deployment of social gaze is present early on in toddlers with autism spectrum disorders (ASDs). Yet, studies characterizing the developmental dynamic behind it are scarce. Here we used a data-driven method to delineate the developmental change in visual exploration of social interaction over childhood years in autism. Longitudinal eye-tracking data were acquired as children with ASD and their typically developing (TD) peers freely explored a short cartoon movie. We found divergent moment-to-moment gaze patterns in children with ASD compared to their TD peers. This divergence was particularly evident in sequences that displayed social interactions between characters and even more so in children with lower developmental and functional levels. The basic visual properties of the animated scene did not account for the enhanced divergence. Over childhood years, these differences dramatically increased to become more idiosyncratic. These findings suggest that social attention should be targeted early in clinical treatments.

There is a growing recognition that psychiatric symptoms have the potential to causally interact with one another. Particularly in the earliest stages of psychopathology dynamic interactions between symptoms could contribute heterogeneous and cross-diagnostic clinical evolutions. Current clinical approaches attempt to merge clinical manifestations that co-occur across subjects and could therefore significantly hinder our understanding of clinical pathways connecting individual symptoms. Network approaches have the potential to shed light on the complex dynamics of early psychopathology. In the present manuscript we attempt to address 2 main limitations that have in our opinion hindered the application of network approaches in the clinical setting. The first limitation is that network analyses have mostly been applied to cross-sectional data, yielding results that often lack the intuitive interpretability of simpler categorical or dimensional approaches. Here we propose an approach based on multi-layer network analysis that offers an intuitive low-dimensional characterization of longitudinal pathways involved in the evolution of psychopathology, while conserving high-dimensional information on the role of specific symptoms. The second limitation is that network analyses typically characterize symptom connectivity at the level of a population, whereas clinical practice deals with symptom severity at the level of the individual. Here we propose an approach based on graph signal processing that exploits knowledge of network interactions between symptoms to predict longitudinal clinical evolution at the level of the individual. We test our approaches in two independent samples of individuals with genetic and clinical vulnerability for developing psychosis.

Schizophrenia occurs in about one in four individuals with 22q11.2 deletion syndrome (22q11.2DS). The aim of this International Brain and Behavior 22q11.2DS Consortium (IBBC) study was to identify genetic factors that contribute to schizophrenia, in addition to the ~20-fold increased risk conveyed by the 22q11.2 deletion. Using whole-genome sequencing data from 519 unrelated individuals with 22q11.2DS, we conducted genome-wide comparisons of common and rare variants between those with schizophrenia and those with no psychotic disorder at age ≥25 years. Available microarray data enabled direct comparison of polygenic risk for schizophrenia between 22q11.2DS and independent population samples with no 22q11.2 deletion, with and without schizophrenia (total n = 35,182). Polygenic risk for schizophrenia within 22q11.2DS was significantly greater for those with schizophrenia (padj = 6.73 × 10−6). Novel reciprocal case–control comparisons between the 22q11.2DS and population-based cohorts showed that polygenic risk score was significantly greater in individuals with psychotic illness, regardless of the presence of the 22q11.2 deletion. Within the 22q11.2DS cohort, results of gene-set analyses showed some support for rare variants affecting synaptic genes. No common or rare variants within the 22q11.2 deletion region were significantly associated with schizophrenia. These findings suggest that in addition to the deletion conferring a greatly increased risk to schizophrenia, the risk is higher when the 22q11.2 deletion and common polygenic risk factors that contribute to schizophrenia in the general population are both present. ispartof: Molecular Psychiatry vol:26 issue:8 pages:1-15 ispartof: location:England status: published

Background: Dysconnectivity has been consistently proposed as a major key mechanism in psychosis. Indeed, disruptions in large-scale structural and functional brain networks have been associated with psychotic symptoms. However, brain activity is largely constrained by underlying white matter pathways and the study of function-structure dependency, compared to conventional unimodal analysis, allows a biologically relevant assessment of neural mechanisms. The 22q11.2 deletion syndrome (22q11DS) constitutes a remarkable opportunity to study the pathophysiological processes of psychosis. Methods: 58 healthy controls and 57 deletion carriers, aged from 16 to 32 years old, underwent resting-state functional and diffusion-weighted magnetic resonance imaging. Deletion carriers were additionally fully assessed for psychotic symptoms. Firstly, we used a graph signal processing method to combine brain activity and structural connectivity measures to obtain regional structural decoupling indexes (SDIs). We use SDI to assess the differences of functional structural dependency (FSD) across the groups. Subsequently we investigated how alterations in FSDs are associated with the severity of positive psychotic symptoms in participants with 22q11DS. Results: In line with previous findings, participants in both groups showed a spatial gradient of FSD ranging from sensory-motor regions (stronger FSD) to regions involved in higher-order function (weaker FSD). Compared to controls, in participants with 22q11DS, and further in deletion carriers with more severe positive psychotic symptoms, the functional activity was more strongly dependent on the structure in parahippocampal gyrus and subcortical dopaminergic regions, while it was less dependent within the cingulate cortex. This analysis revealed group differences not otherwise detected when assessing the structural and functional nodal measures separately. Conclusions: Our findings point toward a disrupted modulation of functional activity on the underlying structure, which was further associated to psychopathology for candidate critical regions in 22q11DS. This study provides the first evidence for the clinical relevance of function-structure dependency and its contribution to the emergence of psychosis.

22q11.2 Deletion Syndrome (22q11.2DS) is the single highest molecular risk factor for psychosis with over a third of affected patients developing schizophrenia by adulthood. Patients are moreover characteristically identified as children, due to their somatic phenotype, leading to the realization that the syndrome could serve as a unique window into the earliest clinical and neurodevelopmental stages of the pathophysiology of psychosis. Here we firstly present key notions regarding the syndrome's epidemiology, genetic pathophysiology, and somatic manifestations. We then offer a comprehensive overview of several aspects of the syndrome's complex neurocognitive and psychiatric phenotype stressing both parallels and specificities compared to idiopathic psychosis. Finally, we review key findings regarding the neurodevelopmental pathophysiology of 22q11DS, coming from both neuroimaging studies and from translational animal models. We argue that a multimodal, longitudinal, and translational approach to the study of 22q11.2DS promises to contribute important insights for understanding the neurodevelopmental origins of schizophrenia.

Late human development is characterized by the maturation of high-level functional processes, which rely on reshaping of white matter connections, as well as synaptic density. However, the relationship between the whole-brain dynamics and the underlying white matter networks in neurodevelopment is largely unknown. In this study, we focused on how the structural connectome shapes the emerging dynamics of cerebral development between the ages of 6 and 33 years, using functional and diffusion magnetic resonance imaging combined into a spatiotemporal connectivity framework. We defined two new measures of brain dynamics, namely the system diversity and the spatiotemporal diversity, which quantify the level of integration/segregation between functional systems and the level of temporal self-similarity of the functional patterns of brain dynamics, respectively. We observed a global increase in system diversity and a global decrease and local refinement in spatiotemporal diversity values with age. In support of these findings, we further found an increase in the usage of long-range and inter-system white matter connectivity and a decrease in the usage of short-range connectivity with age. These findings suggest that dynamic functional patterns in the brain progressively become more integrative and temporally self-similar with age. These functional changes are supported by a greater involvement of long-range and inter-system axonal pathways., AUTHOR SUMMARY, Maturation in human development is represented by changes in both functional dynamics and structural connectivity in the human brain. By constructing a spatiotemporal connectome for a cohort of 81 subjects ranging from 6 to 33 years of age, we demonstrate how these changes can be studied in a unified framework. We do so by defining two new measures of brain dynamics, namely the spatiotemporal diversity, mapping the level of temporal self-similarity of the functional patterns of brain dynamics, and system diversity, quantifying the level of integration/segregation between functional systems. These measures, we argue, represent a novel way of looking at brain dynamics constraints by structural connectivity. Using these measures, we show that dynamic functional patterns in the brain progressively become more integrative and temporally self-similar with age.

Autism spectrum disorders (ASD) and non-affective psychoses such as schizophrenia are commonly acknowledged as discrete entities. Previous research has revealed evidence of high comorbidity between these conditions, but their differential diagnosis proves difficult in routine clinical practice due to the similarities between core symptoms of each disorder. The prevalence of comorbid non-affective psychoses in individuals with ASD is uncertain, with studies reporting rates ranging from 0% to 61.5%. We therefore performed a systematic review and pooled analysis of the available studies reporting the prevalence of non-affective psychosis in ASD. Fourteen studies, including a total of 1708 participants, were included, with a weighted pooled prevalence assessed at 9.5% (95% CI 2.6 to 16.0). In view of significant heterogeneity amongst the studies, subgroup analyses were conducted. We observed higher prevalence of non-affective psychoses among ASD inpatients versus outpatients, when operationalised criteria were used, and in studies with smaller sample sizes, whereas the figures were comparable between children and adults with ASD. Our results suggest that future studies involving larger samples should implement both operationalized criteria and specific scales for the assessment of psychotic symptoms in individuals with ASD. A deeper understanding of both differential and comorbid features of ASD and non-affective psychosis will be required for the development of optimized clinical management protocols.

How the brain’s white-matter anatomy constrains brain activity is an open question that might give insights into the mechanisms that underlie mental disorders such as schizophrenia. Chromosome 22q11.2 deletion syndrome (22q11DS) is a neurodevelopmental disorder with an extremely high risk for psychosis providing a test case to study developmental aspects of schizophrenia. In this study, we used principles from network control theory to probe the implications of aberrant structural connectivity for the brain’s functional dynamics in 22q11DS. We retrieved brain states from resting-state functional magnetic resonance images of 78 patients with 22q11DS and 85 healthy controls. Then, we compared them in terms of persistence control energy; i.e., the control energy that would be required to persist in each of these states based on individual structural connectivity and a dynamic model. Persistence control energy was altered in a broad pattern of brain states including both energetically more demanding and less demanding brain states in 22q11DS. Further, we found a negative relationship between persistence control energy and resting-state activation time, which suggests that the brain reduces energy by spending less time in energetically demanding brain states. In patients with 22q11DS, this behavior was less pronounced, suggesting a dynamic inefficiency of brain function in the disease. In summary, our results provide initial insights into the dynamic implications of altered structural connectivity in 22q11DS, which might improve our understanding of the mechanisms underlying the disease.

Background Prodromal positive psychotic symptoms and anxiety are two strong risk factors for schizophrenia in 22q11.2 deletion syndrome (22q11DS). The analysis of large-scale brain network dynamics during rest is promising to investigate aberrant brain function and identify potentially more reliable biomarkers. Methods We retrieved and examined dynamic properties of large-scale functional brain networks using innovation-driven coactivation patterns. The study included resting-state functional magnetic resonance scans from 78 patients with 22q11DS and 85 healthy control subjects. After group comparison of temporal brain network activation properties, functional signatures of prodromal psychotic symptoms and anxiety were extracted using multivariate partial least squares correlation. Results Patients with 22q11DS had shorter activation in cognitive brain networks, longer activation in emotion processing networks, and generally increased segregation between brain networks. The functional signature of prodromal psychotic symptoms confirmed an implication of cingulo-prefrontal salience network activation duration and coupling. Further, the functional signature of anxiety uncovered an implication of amygdala activation and coupling, indicating differential roles of dorsal and ventral subdivisions of the anterior cingulate and medial prefrontal cortices. Coupling of amygdala with the dorsal anterior cingulate and medial prefrontal cortices was promoting anxiety, whereas coupling with the ventral anterior cingulate and medial prefrontal cortices had a protective function. Conclusions Using innovation-driven coactivation patterns for dynamic large-scale brain network analysis, we uncovered patterns of brain network activation duration and coupling that are relevant in clinical risk factors for psychosis in 22q11DS. Our results confirm that the dynamic nature of brain network activation contains essential function to develop clinically relevant imaging markers of psychosis vulnerability.

Low hippocampal volume is a consistent finding in schizophrenia and across the psychosis spectrum. However, there is a lack of studies investigating longitudinal hippocampal development and its relationship with psychotic symptoms. The 22q11.2 deletion syndrome (22q11DS) has proven to be a remarkable model for the prospective study of individuals at high risk of schizophrenia to unravel the pathophysiological processes predating the onset of psychosis. Repeated cerebral MRIs were acquired from 140 patients with 22q11DS (53 experiencing moderate-to-severe psychotic symptoms) and 135 healthy controls aged from 6 to 35 years and with up to 5 time points per participant. Hippocampal subfield analysis was conducted using FreeSurfer-v.6 and FIRST-FSL. Then, whole hippocampal and subfield volumes were compared across the groups. Relative to controls, patients with 22q11DS showed a remarkably lower volume of all subfields except for CA2/3. No divergent trajectories in hippocampal development were found. When comparing patients with 22q11DS exhibiting psychotic symptoms to those without psychosis, we detected a volume decrease during late adolescence, starting in CA1 and spreading to other subfields. Our findings suggested that hippocampal volume is consistently smaller in patients with 22q11DS. Moreover, we have demonstrated that patients with 22q11DS and psychotic symptoms undergo a further decrease in volume during adolescence, a vulnerable period for the emergence of psychosis. Interestingly, CA2/3, despite being affected in patients with psychotic symptoms, was the only area not reduced in patients with 22q11DS relative to controls, thus suggesting that its atrophy exclusively correlates with the presence of positive psychotic symptoms. ispartof: MOLECULAR PSYCHIATRY vol:25 issue:11 pages:2844-2859 ispartof: location:England status: published

Background 22q11.2 Deletion Syndrome (22q11DS) confers strongly increased genetic risk for multiple psychiatric disorders. Similarly to the general population, rates of psychiatric comorbidity suggest that common disease mechanisms are shared across dimensions of psychopathology. Such pleiotropic disease mechanisms remain however currently unknown. We hypothesized that pituitary dysmaturation, indicative of HPA-axis dysregulation, could correlate to reduced tolerance to daily life stressors and reflect pleiotropic risk factor for psychopathology. Moreover HPA-axis dysregulation could affect atypical cortical and hippocampal development previously described in 22q11DS. Methods Pituitary volume, hippocampal volume and cortical thickness measures were obtained from T1-weighted MRI images in a large longitudinal cohort of youth with 22q11DS (115 subjects, 260 scans, age-range = 5.4–31.6) and healthy controls (151 subjects, 280 scans, age-range = 5.1–32.3). We explored effects of pituitary dysmaturation on tolerance to stress, psychopathology and neurodevelopment employing mixed-models linear regression. Associations of pituitary and cortical development were correlated with the expression pattern of glucocorticoid receptor gene NR3C1 obtained from the Allen-Human-Brain-Atlas. Results We observed aberrant pituitary developmental trajectories in 22q11DS, with volumetric reductions emerging by young-adulthood (P = 0.0006). Longitudinal pituitary decline was associated with to reduced tolerance to stress (P = 0.04), higher overall psychopathology (P = 0.0003) and increased risk of psychiatric comorbidity (P = 0.02). Moreover, pituitary decline correlated with blunted growth of the right hippocampus (P = 0.03) and to increased cortical thinning of mostly temporal and orbitofrontal regions mediated by NR3C1 gene expression. Conclusion Atypical pituitary development could reflect progressive extinction of HPAA due to chronic hyper-activation, in agreement with existing biochemical evidence in 22q11DS. HPAA dysregulation could represent and endophenotype that confers pleiotropic vulnerability to psychopathology and atypical neurodevelopment in 22q11DS.

Converging evidence suggests that psychosis emerges from the complex interaction of genetic and environmental factors. Stressful life events (SLEs) play a prominent role in combination with coping strategies and with a dysfunctional hypothalamus-pituitary-adrenal axis (HPAA). It has been proposed that the framework of schizotypy might help disentangle the interaction between genetic and environmental factors in the pathogenesis of psychosis. Similarly, 22q11.2 deletion syndrome (22q11DS) is considered as a genetic model of psychosis vulnerability. However, SLE and coping strategies remain largely unexplored in 22q11DS. Moreover, the HPAA has not been systematically investigated in this population. Here, we explored the correlation between SLE, emotional coping strategies, schizotypal personality traits, subthreshold psychotic symptoms in a sample of 43 healthy controls (HCs) compared with 59 individuals with 22q11DS. In the latter, we also explored the correlation with pituitary volume as estimated from structural magnetic resonance imaging. We found that SLE and negative coping strategies were correlated with schizotypal personality traits in both HCs and 22q11DS, and with psychotic symptoms in the 22q11DS group only, whereas reduced pituitary volume correlated with general psychopathology. Moreover, dysfunctional coping mediated the effect of SLE on schizotypal personality traits and psychotic symptoms in 22q11DS. Our findings recapitulate evidence in nonsyndromic patients and confirm the central role of stress and coping in the pathogenesis of psychosis. More broadly, they highlight the importance of environmental factors in the pathway to psychosis in 22q11DS, suggesting a strong rationale for the implementation of stress and particularly coping-oriented interventions in this population.

Background. Patients with 22q11.2 deletion syndrome (22q11DS) present a high risk of developing psychosis. While clinical and cognitive predictors for the conversion towards a full-blown psychotic disorder are well defined and largely used in practice, neural biomarkers do not yet exist. However, a number of investigations indicated an association between abnormalities in cortical morphology and higher symptoms severities in patients with 22q11DS. Nevertheless, few studies included homogeneous groups of patients differing in their psychotic symptoms profile., Methods. In this study, we included 22 patients meeting the criteria for an ultra-high-risk (UHR) psychotic state and 22 age-, gender- and IQ-matched non-UHR patients. Measures of cortical morphology, including cortical thickness, volume, surface area and gyrification, were compared between the two groups using mass-univariate and multivariate comparisons. Furthermore, the development of these measures was tested in the two groups using a mixed-model approach., Results. Our results showed differences in cortical volume and surface area in UHR patients compared with non-UHR. In particular, we found a positive association between surface area and the rate of change of global functioning, suggesting that higher surface area is predictive of improved functioning with age. We also observed accelerated cortical thinning during adolescence in UHR patients with 22q11DS., Conclusions. These results, although preliminary, suggest that alterations in cortical volume and surface area as well as altered development of cortical thickness may be associated to a greater probability to develop psychosis in 22q11DS.

Background 22q11.2 deletion syndrome (22q11DS) is the third-largest known genetic risk factor for the development of psychosis. Dysconnectivity has consistently been implicated in the physiopathology of psychosis. Structural covariance of cortical morphology is a method of exploring connectivity among brain regions that to date has not been employed in 22q11DS. Methods In the present study we employed structural covariance of cortical thickness to explore connectivity alterations in a group of 108 patients with 22q11DS compared with 96 control subjects. We subsequently divided patients into two subgroups of 31 subjects each according to the presence of attenuated psychotic symptoms. FreeSurfer software was used to obtain the mean cortical thickness in 148 brain regions from T1-weighted 3T images. For each population we reconstructed a brain graph using Pearson correlation between the average thickness of each couple of brain regions, which we characterized in terms of mean correlation strength and in terms of network architecture using graph theory. Results Patients with 22q11DS presented increased mean correlation strength, but there was no difference in global architecture compared with control subjects. However, symptomatic patients presented increased mean correlation strength coupled with increased segregation and decreased integration compared with both control subjects and nonsymptomatic patients. They also presented increased centrality for a cluster of anterior cingulate and dorsomedial prefrontal regions. Conclusions These results confirm the importance of cortical dysconnectivity in the physiopathology of psychosis. Moreover they support the significance of aberrant anterior cingulate connectivity.

Chromosome 22q11.2 deletion syndrome (22q11DS) is a neurodevelopmental disorder associated with a broad phenotype of clinical, cognitive and psychiatric features. Due to the very high prevalence of schizophrenia (30-40%), the investigation of psychotic symptoms in the syndrome is promising to reveal biomarkers for the development of psychosis, also in the general population. Since schizophrenia is seen as a disorder of the dynamic interactions between brain networks, we here investigated brain dynamics, assessed by the variability of blood oxygenation level dependent (BOLD) signals, in patients with psychotic symptoms. We included 28 patients with 22q11DS presenting higher positive psychotic symptoms, 29 patients with lower positive psychotic symptoms and 69 healthy controls between 10 and 30years old. To overcome limitations of mass-univariate approaches, we employed multivariate analysis, namely partial least squares correlation, combined with proper statistical testing, to analyze resting-state BOLD signal variability and its age-relationship in patients with positive psychotic symptoms. Our results revealed a missing positive age-relationship in the dorsal anterior cingulate cortex (dACC) in patients with higher positive psychotic symptoms, leading to globally lower variability in the dACC in those patients. Patients without positive psychotic symptoms and healthy controls had the same developmental trajectory in this region. Alterations of brain structure and function in the ACC have been previously reported in 22q11DS and linked to psychotic symptoms. The present results support the implication of this region in the development of psychotic symptoms and suggest aberrant BOLD signal variability development as a potential biomarker for psychosis.

Chromosome 22q11.2 deletion syndrome (22q11.2DS) is a genetic disease associated with an increased risk for schizophrenia and a specific cognitive profile. In this paper, we challenge the current view of spared verbal memory in 22q11.2DS by investigating verbal memory consolidation processes over an extended time span to further qualify the neuropsychological profile. Our hypotheses are based on brain anomalies of the medial temporal lobes consistently reported in this syndrome. Eighty-four participants (45 with 22q11.2DS), aged 8-24 years old, completed a verbal episodic memory task to investigate long-term memory on four different time delays. We compared trajectories of forgetting between groups (22q11.2DS vs. controls) and analyzed performance inside the 22q11.2DS sample through cluster analyses. Potential links between memory performance and volume of the hippocampal subfields were examined. We showed accelerated long-term forgetting (ALF) in the 22q11.2DS group, visible after a delay of one day. Using mixed models, we showed significant differences in the shape of memory trajectories between subgroups of participants with 22q11.2DS. These sub-groups differed in terms of memory recognition, intellectual functioning, positive psychotic symptoms and grey matter volume of hippocampal subfields but not in terms of age. In conclusion, by investigating memory processes on longer delays than standardized memory tasks, we identified deficits in long-term memory consolidation leading to ALF in 22q11.2DS. Nevertheless, we showed that a subgroup of patients had larger memory consolidation deficit associated with lower intellectual functioning, higher rates of positive psychotic symptoms and hippocampal alterations.

There is a growing recognition that psychiatric symptoms have the potential to causally interact with one another. Particularly in the earliest stages of psychopathology dynamic interactions between symptoms could contribute heterogeneous and cross-diagnostic clinical evolutions. Current clinical approaches attempt to merge clinical manifestations that co-occur across subjects and could therefore significantly hinder our understanding of clinical pathways connecting individual symptoms. Network approaches have the potential to shed light on the complex dynamics of early psychopathology. In the present manuscript we attempt to address 2 main limitations that have in our opinion hindered the application of network approaches in the clinical setting. The first limitation is that network analyses have mostly been applied to cross-sectional data, yielding results that often lack the intuitive interpretability of simpler categorical or dimensional approaches. Here we propose an approach based on multi-layer network analysis that offers an intuitive low-dimensional characterization of longitudinal pathways involved in the evolution of psychopathology, while conserving high-dimensional information on the role of specific symptoms. The second limitation is that network analyses typically characterize symptom connectivity at the level of a population, whereas clinical practice deals with symptom severity at the level of the individual. Here we propose an approach based on graph signal processing that exploits knowledge of network interactions between symptoms to predict longitudinal clinical evolution at the level of the individual. We test our approaches in two independent samples of individuals with genetic and clinical vulnerability for developing psychosis.