Associations between acute and chronic lifetime stressors and psychosis-risk symptoms in individuals with 22q11.2 copy number variants.

BACKGROUND: The 22q11.2 deletion (22q11Del) is among the strongest known genetic risk factors for psychosis. Stress, a known risk factor for psychosis in the general population, has seldom been studied in 22q11Del. We investigated how lifetime stressors related to symptomatic outcomes in patients with 22q11Del. We also explored this association in individuals with 22q11.2 duplications (22q11Dup), which may be potentially protective against psychosis. METHOD: One hundred individuals (46 with 22q11Del, 30 with 22q11Dup, and 24 healthy controls; Mage = 17.30 years±10.15) were included. Logistic models were used to examine cross-sectional associations between lifetime acute and chronic stressors (severity and count) and the presence (score ⩾3) of positive, negative, and general symptoms, assessed via the Structured Interview for Psychosis-risk Syndromes (SIPS). RESULTS: The 22q11Dup group reported the greatest number and severity of acute lifetime stressors, but did not differ from 22q11Del in chronic stressor count or severity. Lifetime chronic and acute stressors were uniquely associated with positive symptoms in 22q11Del (chronic count: odds ratio [OR] = 2.35, p = 0.02; chronic severity: OR = 1.88, p = 0.03; acute count: OR = 1.78, p = 0.03), but not with negative or general symptoms (ps > 0.05). CONCLUSION: Findings suggest that stress may play a role in psychotic symptoms in 22q1Del, while the 22q11Dup CNV appears protective against psychotic symptoms despite higher rates of stressors. Interventions that mitigate effects of stressors in 22qDel may reduce the odds of psychosis in this group. Prospective longitudinal research is needed to replicate these findings.

Sleep in 22q11.2 Deletion Syndrome: Current Findings, Challenges, and Future Directions.

PURPOSE OF REVIEW: To summarize current literature available on sleep in 22q11.2 Deletion Syndrome (22q11.2DS; Velocardiofacial or DiGeorge Syndrome), a neurogenetic disorder caused by a hemizygous deletion in a genomic region critical for neurodevelopment. Due to the greatly increased risk of developmental psychiatric disorders (e.g., autism and schizophrenia) in 22q11.2DS, this review focuses on clinical correlates of sleep disturbances and potential neurobiological underpinnings of these relationships. RECENT FINDINGS: Sleep disturbances are widely prevalent in 22q11.2DS and are associated with worse behavioral, psychiatric, and physical health outcomes. There are reports of sleep architecture and sleep neurophysiology differences, but the literature is limited by logistical challenges posed by objective sleep measures, resulting in small study samples to date. Sleep disturbances in 22q11.2DS are prevalent and have a substantial impact on well-being. Further investigation of sleep in 22q11.2DS utilizing multimodal sleep assessments has the potential to provide new insight into neurobiological mechanisms and a potential trans-diagnostic treatment target in 22q11.2DS.

Longitudinal Development of Thalamocortical Functional Connectivity in 22q11.2 Deletion Syndrome.

BACKGROUND: The 22q11.2 deletion syndrome (22qDel) is a genetic copy number variant that strongly increases risk for schizophrenia and other neurodevelopmental disorders. Disrupted functional connectivity between the thalamus and the somatomotor/frontoparietal cortex has been implicated in cross-sectional studies of 22qDel, idiopathic schizophrenia, and youths at clinical high risk for psychosis. Here, we used a novel functional atlas approach to investigate longitudinal age-related changes in network-specific thalamocortical functional connectivity (TCC) in participants with 22qDel and typically developing (TD) control participants. METHODS: TCC was calculated for 9 functional networks derived from resting-state functional magnetic resonance imaging scans collected from 65 participants with 22qDel (63.1% female) and 69 demographically matched TD control participants (49.3% female) ages 6 to 23 years. Analyses included 86 longitudinal follow-up scans. Nonlinear age trajectories were characterized with generalized additive mixed models. RESULTS: In participants with 22qDel, TCC in the frontoparietal network increased until approximately age 13, while somatomotor TCC and cingulo-opercular TCC decreased from age 6 to 23. In contrast, no significant relationships between TCC and age were found in TD control participants. Somatomotor connectivity was significantly higher in participants with 22qDel than in TD control participants in childhood, but lower in late adolescence. Frontoparietal TCC showed the opposite pattern. CONCLUSIONS: 22qDel is associated with aberrant development of functional network connectivity between the thalamus and cortex. Younger individuals with 22qDel have lower frontoparietal connectivity and higher somatomotor connectivity than control individuals, but this phenotype may normalize or partially reverse by early adulthood. Altered maturation of this circuitry may underlie elevated neuropsychiatric disease risk in this syndrome.

Effects of gene dosage and development on subcortical nuclei volumes in individuals with 22q11.2 copy number variations.

The 22q11.2 locus contains genes critical for brain development. Reciprocal Copy Number Variations (CNVs) at this locus impact risk for neurodevelopmental and psychiatric disorders. Both 22q11.2 deletions (22qDel) and duplications (22qDup) are associated with autism, but 22qDel uniquely elevates schizophrenia risk. Understanding brain phenotypes associated with these highly penetrant CNVs can provide insights into genetic pathways underlying neuropsychiatric disorders. Human neuroimaging and animal models indicate subcortical brain alterations in 22qDel, yet little is known about developmental differences across specific nuclei between reciprocal 22q11.2 CNV carriers and typically developing (TD) controls. We conducted a longitudinal MRI study in a total of 385 scans from 22qDel (n = 96, scans = 191, 53.1% female), 22qDup (n = 37, scans = 64, 45.9% female), and TD controls (n = 80, scans = 130, 51.2% female), across a wide age range (5.5-49.5 years). Volumes of the thalamus, hippocampus, amygdala, and anatomical subregions were estimated using FreeSurfer, and the linear effects of 22q11.2 gene dosage and non-linear effects of age were characterized with generalized additive mixed models (GAMMs). Positive gene dosage effects (volume increasing with copy number) were observed for total intracranial and whole hippocampus volumes, but not whole thalamus or amygdala volumes. Several amygdala subregions exhibited similar positive effects, with bi-directional effects found across thalamic nuclei. Distinct age-related trajectories were observed across the three groups. Notably, both 22qDel and 22qDup carriers exhibited flattened development of hippocampal CA2/3 subfields relative to TD controls. This study provides novel insights into the impact of 22q11.2 CNVs on subcortical brain structures and their developmental trajectories.

Distinct Neurocognitive Profiles and Clinical Phenotypes Associated with Copy Number Variation at the 22q11.2 Locus.

Rare genetic variants that confer large effects on neurodevelopment and behavioral phenotypes can reveal novel gene-brain-behavior relationships relevant to autism. Copy number variation at the 22q11.2 locus offer one compelling example, as both the 22q11.2 deletion (22qDel) and duplication (22qDup) confer increased likelihood of autism spectrum disorders (ASD) and cognitive deficits, but only 22qDel confers increased psychosis risk. Here, we used the Penn Computerized Neurocognitive Battery (Penn-CNB) to characterized neurocognitive profiles of 126 individuals: 55 22qDel carriers (MAge=19.2 years, 49.1% male), 30 22qDup carriers (MAge=17.3 years, 53.3 % male), and 41 typically developing (TD) subjects (MAge=17.3 years, 39.0 % male). We performed linear mixed models to assess group differences in overall neurocognitive profiles, domain scores, and individual test scores. We found all three groups exhibited distinct overall neurocognitive profiles. 22qDel and 22qDup carriers showed significant accuracy deficits across all domains relative to controls (Episodic Memory, Executive Function, Complex Cognition, Social Cognition, and Sensorimotor Speed), with 22qDel carriers exhibiting more severe accuracy deficits, particularly in Episodic Memory. However, 22qDup carriers generally showed greater slowing than 22qDel carriers. Notably, slower social cognition speed was uniquely associated with increased global psychopathology and poorer psychosocial functioning in 22qDup. Compared to TD, 22q11.2 CNV carriers failed to show age-associated improvements in multiple cognitive domains. Exploratory analyses revealed 22q11.2 CNV carriers with ASD exhibited differential neurocognitive profiles, based on 22q11.2 copy number. These results suggest that there are distinct neurocognitive profiles associated with either a loss or gain of genomic material at the 22q11.2 locus.

Effects of Gene Dosage and Development on Subcortical Nuclei Volumes in Individuals with 22q11.2 Copy Number Variations.

The 22q11.2 locus contains genes critical for brain development. Reciprocal Copy Number Variations (CNVs) at this locus impact risk for neurodevelopmental and psychiatric disorders. Both 22q11.2 deletions (22qDel) and duplications (22qDup) are associated with autism, but 22qDel uniquely elevates schizophrenia risk. Understanding brain phenotypes associated with these highly penetrant CNVs can provide insights into genetic pathways underlying neuropsychiatric disorders. Human neuroimaging and animal models indicate subcortical brain alterations in 22qDel, yet little is known about developmental differences across specific nuclei between reciprocal 22q11.2 CNV carriers and typically developing (TD) controls. We conducted a longitudinal MRI study in 22qDel (n=96, 53.1% female), 22qDup (n=37, 45.9% female), and TD controls (n=80, 51.2% female), across a wide age range (5.5-49.5 years). Volumes of the thalamus, hippocampus, amygdala, and anatomical subregions were estimated using FreeSurfer, and the effect of 22q11.2 gene dosage was examined using linear mixed models. Age-related changes were characterized with general additive mixed models (GAMMs). Positive gene dosage effects (22qDel < TD < 22qDup) were observed for total intracranial and whole hippocampus volumes, but not whole thalamus or amygdala volumes. Several amygdala subregions exhibited similar positive effects, with bi-directional effects found across thalamic nuclei. Distinct age-related trajectories were observed across the three groups. Notably, both 22qDel and 22qDup carriers exhibited flattened development of hippocampal CA2/3 subfields relative to TD controls. This study provides novel insights into the impact of 22q11.2 CNVs on subcortical brain structures and their developmental trajectories.

Distinct neurocognitive profiles and clinical phenotypes associated with copy number variation at the 22q11.2 locus.

Rare genetic variants that confer large effects on neurodevelopment and behavioral phenotypes can reveal novel gene-brain-behavior relationships relevant to autism. Copy number variation at the 22q11.2 locus offer one compelling example, as both the 22q11.2 deletion (22qDel) and duplication (22qDup) confer increased likelihood of autism spectrum disorders (ASD) and cognitive deficits, but only 22qDel confers increased psychosis risk. Here, we used the Penn Computerized Neurocognitive Battery (Penn-CNB) to characterized neurocognitive profiles of 126 individuals: 55 22qDel carriers (MAge = 19.2 years, 49.1% male), 30 22qDup carriers (MAge = 17.3 years, 53.3% male), and 41 typically developing (TD) subjects (MAge = 17.3 years, 39.0% male). We performed linear mixed models to assess group differences in overall neurocognitive profiles, domain scores, and individual test scores. We found all three groups exhibited distinct overall neurocognitive profiles. 22qDel and 22qDup carriers showed significant accuracy deficits across all domains relative to controls (episodic memory, executive function, complex cognition, social cognition, and sensorimotor speed), with 22qDel carriers exhibiting more severe accuracy deficits, particularly in episodic memory. However, 22qDup carriers generally showed greater slowing than 22qDel carriers. Notably, slower social cognition speed was uniquely associated with increased global psychopathology and poorer psychosocial functioning in 22qDup. Compared to TD, 22q11.2 copy number variants (CNV) carriers failed to show age-associated improvements in multiple cognitive domains. Exploratory analyses revealed 22q11.2 CNV carriers with ASD exhibited differential neurocognitive profiles, based on 22q11.2 copy number. These results suggest that there are distinct neurocognitive profiles associated with either a loss or gain of genomic material at the 22q11.2 locus.

Neurocognitive Profiles of 22q11.2 and 16p11.2 Deletions and Duplications.

Rare recurrent copy number variants (CNVs) at chromosomal loci 22q11.2 and 16p11.2 are among the most common rare genetic disorders associated with significant risk for neuropsychiatric disorders across the lifespan. Microdeletions and duplications in these loci are associated with neurocognitive deficits, yet there are few studies comparing these groups using the same measures. We address this gap in a prospective international collaboration applying the same computerized neurocognitive assessment. The Penn Computerized Neurocognitive Battery (CNB) was administered in a multi-site study on rare genomic disorders: 22q11.2 deletion (n = 397); 22q11.2 duplication (n = 77); 16p11.2 deletion (n = 94); and 16p11.2 duplication (n = 26). Domains examined include executive functions, episodic memory, complex cognition, social cognition, and sensori-motor speed. Accuracy and speed for each neurocognitive domain were included as dependent measures in a mixed-model repeated measures analysis, with locus (22q11.2, 16p11.2) and copy number (deletion/duplication) as grouping factors and neurocognitive domain as a repeated measures factor, with age and sex as covariates. We also examined correlation with IQ and site effects. We found that 22q11.2 deletions were associated with greater deficits in overall performance accuracy than 22q11.2 duplications, while 16p11.2 duplications were associated with greater deficits than 16p11.2 deletions. Duplications at both loci were associated with reduced speed. Performance profiles differed among the groups with particularly poor performance of 16p11.2 duplication on non-verbal reasoning and social cognition. Average accuracy on the CNB was moderately correlated with Full Scale IQ. No site effects were observed. Deletions and duplications of 22q11.2 and 16p11.2 have varied effects on neurocognition indicating locus specificity, with performance profiles differing among the groups. These profile differences can help inform mechanistic substrates to heterogeneity in presentation and outcome. Future studies could aim to link performance profiles to clinical features and brain function.

Copy number variation at the 22q11.2 locus influences prevalence, severity, and psychiatric impact of sleep disturbance.

BACKGROUND: Sleep disturbance is common, impairing, and may affect symptomatology in developmental neuropsychiatric disorders. Here, we take a genetics-first approach to study the complex role of sleep in psychopathology. Specifically, we examine severity of sleep disturbance in individuals with a reciprocal copy number variant (CNV) at the 22q11.2 locus and determine sleep's effect on psychiatric symptoms. CNVs (deletion or duplication) at this locus confer some of the greatest known risks of neuropsychiatric disorders; recent studies suggest the 22q11.2 deletion negatively impacts sleep, but sleep disruption associated with 22q11.2 duplication has not been investigated. METHODS: We compared subjective sleep disturbance and its relationship to psychiatric symptoms cross-sectionally and longitudinally over 1 year in 107 22q11.2 deletion (22qDel) carriers (14.56±8.0 years; 50% male), 42 22q11.2 duplication (22qDup) carriers (16.26±13.1 years; 54.8% male), and 88 age- and sex-matched controls (14.65±7.4 years; 47.1% male). Linear mixed models were used to compare sleep disturbance, assessed via the Structured Interview for Psychosis-Risk Syndromes (SIPS), across groups. Next, CNV carriers were categorized as good or poor sleepers to investigate sleep effects on multiple neurobehavioral traits: psychosis-risk symptoms (SIPS), autism-related behaviors (Repetitive Behavior Scale (RBS) and Social Responsiveness Scale (SRS)), real-world executive function (Behavior Rating Inventory of Executive Function (BRIEF)), and emotional/behavioral problems (Child Behavior Checklist (CBCL)). Linear mixed models tested the effect of sleep category and a group-by-sleep interaction on each measure, cross-sectionally and longitudinally. RESULTS: 22qDel and 22qDup carriers both reported poorer sleep than controls, but did not differ from each other. Cross-sectionally and longitudinally, poor sleepers scored higher on positive symptoms, anxious/depressed, somatic complaints, thought problems, and aggressive behavior, as well as RBS and SRS total scores. There were significant group-by-sleep interactions for positive symptoms and the majority of CBCL subdomains, in which the difference between good and poor sleepers was larger in 22qDel compared to 22qDup. CONCLUSIONS: Our findings indicate that CNVs at the 22q11.2 locus impact sleep which, in turn, influences psychopathology. Sleep disturbances can differentially impact psychopathology, depending on 22q11.2 gene dosage. Our findings serve as a starting point for exploring a genetic basis for sleep disturbance in developmental neuropsychiatric disorders.

Viability of an Early Sleep Intervention to Mitigate Poor Sleep and Improve Well-being in the COVID-19 Pandemic: Protocol for a Feasibility Randomized Controlled Trial.

BACKGROUND: The COVID-19 pandemic has led to drastic increases in the prevalence and severity of insomnia symptoms. These increases in insomnia complaints have been paralleled by significant decreases in well-being, including increased symptoms of depression, anxiety, and suicidality and decreased quality of life. However, the efficacy and impact of early treatment of insomnia symptoms on future sleep and well-being remain unknown. OBJECTIVE: Here, we present the framework and protocol for a novel feasibility, pilot study that aims to investigate whether a brief telehealth insomnia intervention targeting new insomnia that developed during the pandemic prevents deterioration of well-being, including symptoms of insomnia, depression, anxiety, suicidality, and quality of life. METHODS: The protocol details a 2-arm randomized controlled feasibility trial to investigate the efficacy of a brief, telehealth-delivered, early treatment of insomnia and evaluate its potential to prevent deterioration of well-being. Participants with clinically significant insomnia symptoms that began during the pandemic were randomized to either a treatment group or a 28-week waitlist control group. Treatment consists of 4 telehealth sessions of cognitive behavioral therapy for insomnia (CBT-I) delivered over 5 weeks. All participants will complete assessments of insomnia symptom severity, well-being, and daily habits checklist at baseline (week 0) and at weeks 1-6, 12, 28, and 56. RESULTS: The trial began enrollment on June 3, 2020 and closed enrollment on June 17, 2021. As of October 2021, 49 participants had been randomized to either immediate treatment or a 28-week waitlist; 23 participants were still active in the protocol. CONCLUSIONS: To our knowledge, this protocol would represent the first study to test an early sleep intervention for improving insomnia that emerged during the COVID-19 pandemic. The findings of this feasibility study could provide information about the utility of CBT-I for symptoms that emerge in the context of other stressors before they develop a chronic course and deepen understanding of the relationship between sleep and well-being. TRIAL REGISTRATION: ClinicalTrials.gov NCT04409743; https://clinicaltrials.gov/ct2/show/NCT04409743. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/34409.

Neurobehavioral Dimensions of Prader Willi Syndrome: Relationships Between Sleep and Psychosis-Risk Symptoms.

Background: Prader Willi Syndrome (PWS) is a genetic disorder caused by the absence of expression of the paternal copies of maternally imprinted gene(s) located at 15q11-q13. While the physical and medical characteristics of PWS, including short stature, hyperphagia and endocrine dysfunction are well-characterized, systematic investigation of the long-recognized psychiatric manifestations has been recent. Methods: Here, we report on the first remote (web-based) assessment of neurobehavioral traits, including psychosis-risk symptoms (Prodromal Questionnaire-Brief Version; PQ-B) and sleep behaviors (Pittsburgh Sleep Quality Index), in a cohort of 128 participants with PWS, of whom 48% had a paternal deletion, 36% uniparental disomy, 2.4% an imprinting mutation and 13% unknown mutation (mean age 19.3 years ± 8.4; 53.9% female). We aimed to identify the most informative variables that contribute to psychosis-risk symptoms. Multiple domains of cognition (accuracy and speed) were also assessed in a subset of PWS participants (n = 39) using the Penn Computerized Neurocognitive Battery (Penn-CNB). Results: Individuals with PWS reported a range of psychosis-risk symptoms, with over half reporting cognitive disorganization (63.1%) and about one third reporting unusual beliefs (38.6%) and/or suspiciousness (33.3%). Subjectively-reported sleep quality, nap frequency, sleep duration, sleep disturbance, and daytime dysfunction were significant predictors of psychosis-risk symptom frequency and severity (all p's < 0.029). Sleep disturbance ratings were the strongest predictors of psychosis-risk symptoms. Regarding cognition, individuals with PWS showed the most prominent deficits in accuracy on measures of social cognition involving faces, namely Face Memory, Age Differentiation and Emotion Recognition, and greatest slowing on measures of Attention and Emotion Recognition. However, there were no significant differences in psychosis-risk symptoms or cognitive performance as a function of PWS genetic subtype. Conclusions: PWS is associated with a high prevalence of distressing psychosis-risk symptoms, which are associated with sleep disturbance. Findings indicate that self/parent-reported neurobehavioral symptoms and cognition can be assessed remotely in individuals with PWS, which has implications for future large-scale investigations of rare neurogenetic disorders.

Integrating sleep, neuroimaging, and computational approaches for precision psychiatry.

In advancing precision psychiatry, we focus on what imaging technology and computational approaches offer for the future of diagnostic subtyping and personalized tailoring of interventions for sleep impairment in mood and anxiety disorders. Current diagnostic criteria for mood and anxiety tend to lump different forms of sleep disturbance together. Parsing the biological features of sleep impairment and brain circuit dysfunction is one approach to identifying subtypes within these disorders that are mechanistically coherent and offer targets for intervention. We focus on two large-scale neural circuits implicated in sleep impairment and in mood and anxiety disorders: the default mode network and negative affective network. Through a synthesis of existing knowledge about these networks, we pose a testable framework for understanding how hyper- versus hypo-engagement of these networks may underlie distinct features of mood and sleep impairment. Within this framework we consider whether poor sleep quality may have an explanatory role in previously observed associations between network dysfunction and mood symptoms. We expand this framework to future directions including the potential for connecting circuit-defined subtypes to more distal features derived from digital phenotyping and wearable technologies, and how new discovery may be advanced through machine learning approaches.