Psychosis spectrum features, neurocognition and functioning in a longitudinal study of youth with 22q11.2 deletion syndrome.

BACKGROUND: Neuropsychiatric disorders are common in 22q11.2 Deletion Syndrome (22q11DS) with about 25% of affected individuals developing schizophrenia spectrum disorders by young adulthood. Longitudinal evaluation of psychosis spectrum features and neurocognition can establish developmental trajectories and impact on functional outcome. METHODS: 157 youth with 22q11DS were assessed longitudinally for psychopathology focusing on psychosis spectrum symptoms, neurocognitive performance and global functioning. We contrasted the pattern of positive and negative psychosis spectrum symptoms and neurocognitive performance differentiating those with more prominent Psychosis Spectrum symptoms (PS+) to those without prominent psychosis symptoms (PS-). RESULTS: We identified differences in the trajectories of psychosis symptoms and neurocognitive performance between the groups. The PS+ group showed age associated increase in symptom severity, especially negative symptoms and general nonspecific symptoms. Correspondingly, their level of functioning was worse and deteriorated more steeply than the PS- group. Neurocognitive performance was generally comparable in PS+ and PS- groups and demonstrated a similar age-related trajectory. However, worsening executive functioning distinguished the PS+ group from PS- counterparts. Notably, of the three executive function measures examined, only working memory showed a significant difference between the groups in rate of change. Finally, structural equation modeling showed that neurocognitive decline drove the clinical change. CONCLUSIONS: Youth with 22q11DS and more prominent psychosis features show worsening of symptoms and functional decline driven by neurocognitive decline, most related to executive functions and specifically working memory. The results underscore the importance of working memory in the developmental progression of psychosis.

Computer-vision analysis of craniofacial dysmorphology in 22q11.2 deletion syndrome and psychosis spectrum disorders.

BACKGROUND: Minor physical anomalies (MPAs) are congenital morphological abnormalities linked to disruptions of fetal development. MPAs are common in 22q11.2 deletion syndrome (22q11DS) and psychosis spectrum disorders (PS) and likely represent a disruption of early embryologic development that may help identify overlapping mechanisms linked to psychosis in these disorders. METHODS: Here, 2D digital photographs were collected from 22q11DS (n = 150), PS (n = 55), and typically developing (TD; n = 93) individuals. Photographs were analyzed using two computer-vision techniques: (1) DeepGestalt algorithm (Face2Gene (F2G)) technology to identify the presence of genetically mediated facial disorders, and (2) Emotrics-a semi-automated machine learning technique that localizes and measures facial features. RESULTS: F2G reliably identified patients with 22q11DS; faces of PS patients were matched to several genetic conditions including FragileX and 22q11DS. PCA-derived factor loadings of all F2G scores indicated unique and overlapping facial patterns that were related to both 22q11DS and PS. Regional facial measurements of the eyes and nose were smaller in 22q11DS as compared to TD, while PS showed intermediate measurements. CONCLUSIONS: The extent to which craniofacial dysmorphology 22q11DS and PS overlapping and evident before the impairment or distress of sub-psychotic symptoms may allow us to identify at-risk youths more reliably and at an earlier stage of development.

A Comprehensive Analysis of Cerebellar Volumes in the 22q11.2 Deletion Syndrome.

BACKGROUND: The presence of a 22q11.2 microdeletion (22q11.2 deletion syndrome [22q11DS]) ranks among the greatest known genetic risk factors for the development of psychotic disorders. There is emerging evidence that the cerebellum is important in the pathophysiology of psychosis. However, there is currently limited information on cerebellar neuroanatomy in 22q11DS specifically. METHODS: High-resolution 3T magnetic resonance imaging was acquired in 79 individuals with 22q11DS and 70 typically developing control subjects (N = 149). Lobar and lobule-level cerebellar volumes were estimated using validated automated segmentation algorithms, and subsequently group differences were compared. Hierarchical clustering, principal component analysis, and graph theoretical models were used to explore intercerebellar relationships. Cerebrocerebellar structural connectivity with cortical thickness was examined via linear regression models. RESULTS: Individuals with 22q11DS had, on average, 17.3% smaller total cerebellar volumes relative to typically developing subjects (p < .0001). The lobules of the superior posterior cerebellum (e.g., VII and VIII) were particularly affected in 22q11DS. However, all cerebellar lobules were significantly smaller, even after adjusting for total brain volumes (all cerebellar lobules p < .0002). The superior posterior lobule was disproportionately associated with cortical thickness in the frontal lobes and cingulate cortex, brain regions known be affected in 22q11DS. Exploratory analyses suggested that the superior posterior lobule, particularly Crus I, may be associated with psychotic symptoms in 22q11DS. CONCLUSIONS: The cerebellum is a critical but understudied component of the 22q11DS neuroendophenotype.

Neuroimaging predictors of cognitive performance across a standardized neurocognitive battery.

OBJECTIVE: The advent of functional MRI (fMRI) enables the identification of brain regions recruited for specific behavioral tasks. Most fMRI studies focus on group effects in single tasks, which limits applicability where assessment of individual differences and multiple brain systems is needed. METHOD: We demonstrate the feasibility of concurrently measuring fMRI activation patterns and performance on a computerized neurocognitive battery (CNB) in 212 healthy individuals at 2 sites. Cross-validated sparse regression of regional brain amplitude and extent of activation were used to predict concurrent performance on 6 neurocognitive tasks: abstraction/mental flexibility, attention, emotion processing, and verbal, face, and spatial memory. RESULTS: Brain activation was task responsive and domain specific, as reported in previous single-task studies. Prediction of performance was robust for most tasks, particularly for abstraction/mental flexibility and visuospatial memory. CONCLUSIONS: The feasibility of administering a comprehensive neuropsychological battery in the scanner was established, and task-specific brain activation patterns improved prediction beyond demographic information. This benchmark index of performance-associated brain activation can be applied to link brain activation with neurocognitive performance during standardized testing. This first step in standardizing a neurocognitive battery for use in fMRI may enable quantitative assessment of patients with brain disorders across multiple cognitive domains. Such data may facilitate identification of neural dysfunction associated with poor performance, allow for identification of individuals at risk for brain disorders, and help guide early intervention and rehabilitation of neurocognitive deficits.

Neurocognitive performance stability in a multiplex multigenerational study of schizophrenia.

Certain cognitive measures are heritable and differentiate individuals at risk for schizophrenia from unaffected family members and healthy comparison subjects. These deficits in neurocognitive performance in patients with schizophrenia appear stable in the short-term. However, the duration of most, but not all, longitudinal studies is modest and the majority have relied on traditional average performance measures to examine stability. Using a computerized neurocognitive battery (CNB), we assessed mean performance (accuracy and speed) and intra-individual variability (IIV) in a longitudinal study aimed to examine neurocognitive stability in European-American multiplex families with schizophrenia. Thirty-four patients with schizophrenia, 65 unaffected relatives, and 45 healthy comparison subjects completed the same computerized neurocognitive assessment over approximately 5 years. Measures of mean performance showed that patients had stable accuracy performance but were slower in many neurocognitive domains over time as compared with unaffected family members and healthy subjects. Furthermore, patients and family members showed dissociable patterns of change in IIV for speed across cognitive domains: compared with controls, patients showed higher across-task IIV in performance compared with family members, who showed lower across-task IIV. Patients showed an increase in IIV over time, whereas family members showed a decrease. These findings suggest that measures of mean performance and IIV of speed during a CNB may provide useful information about the genetic susceptibility in schizophrenia.