Multimodal MRI reveals structural connectivity differences in 22q11 deletion syndrome related to impaired spatial working memory

Neuroanatomical Correlates of Cognitive Dysfunction in 22q11.2 Deletion Syndrome

22q11.2 Deletion Syndrome (22q11.2DS), the most common chromosomal microdeletion, presents as a heterogeneous phenotype characterized by an array of anatomical, behavioral, and cognitive abnormalities. Individuals with 22q11.2DS exhibit extensive cognitive deficits, both in overall intellectual capacity and focal challenges in executive functioning, attentional control, perceptual abilities, motor skills, verbal processing, as well as socioemotional operations. Heterogeneity is an intrinsic factor of the deletion's clinical manifestation in these cognitive domains. Structural imaging has identified significant changes in volume, thickness, and surface area. These alterations are closely linked and display region-specific variations with an overall increase in abnormalities following a rostral-caudal gradient. Despite the extensive literature developing around the neurocognitive and neuroanatomical profiles associated with 22q11.2DS, comparatively little research has addressed specific structure-function relationships between aberrant morphological features and deficient cognitive processes. The current review attempts to categorize these limited findings alongside comparisons to populations with phenotypic and structural similarities in order to answer to what degree structural findings can explain the characteristic neurocognitive deficits seen in individuals with 22q11.2DS. In integrating findings from structural neuroimaging and cognitive assessments, this review seeks to characterize structural changes associated with the broad neurocognitive challenges faced by individuals with 22q11.2DS.

Executive functioning in preschoolers with 22q11.2 deletion syndrome and the impact of congenital heart defects

BACKGROUND

Executive functioning (EF) is an umbrella term for various cognitive functions that play a role in monitoring and planning to effectuate goal-directed behavior. The 22q11.2 deletion syndrome (22q11DS), the most common microdeletion syndrome, is associated with a multitude of both somatic and cognitive symptoms, including EF impairments in school-age and adolescence. However, results vary across different EF domains and studies with preschool children are scarce. As EF is critically associated with later psychopathology and adaptive functioning, our first aim was to study EF in preschool children with 22q11DS. Our second aim was to explore the effect of a congenital heart defects (CHD) on EF abilities, as CHD are common in 22q11DS and have been implicated in EF impairment in individuals with CHD without a syndromic origin.

METHODS

All children with 22q11DS (n = 44) and typically developing (TD) children (n = 81) were 3.0 to 6.5 years old and participated in a larger prospective study. We administered tasks measuring visual selective attention, visual working memory, and a task gauging broad EF abilities. The presence of CHD was determined by a pediatric cardiologist based on medical records.

RESULTS

Analyses showed that children with 22q11DS were outperformed by TD peers on the selective attention task and the working memory task. As many children were unable to complete the broad EF task, we did not run statistical analyses, but provide a qualitative description of the results. There were no differences in EF abilities between children with 22q11DS with and without CHDs.

CONCLUSION

To our knowledge, this is the first study measuring EF in a relatively large sample of young children with 22q11DS. Our results show that EF impairments are already present in early childhood in children with 22q11DS. In line with previous studies with older children with 22q11DS, CHDs do not appear to have an effect on EF performance. These findings might have important implications for early intervention and support the improvement of prognostic accuracy.

A methodological scoping review of the integration of fMRI to guide dMRI tractography. What has been done and what can be improved: A 20-year perspective

Combining MRI modalities is a growing trend in neurosciences. It provides opportunities to investigate the brain architecture supporting cognitive functions. Integrating fMRI activation to guide dMRI tractography offers potential advantages over standard tractography methods. A quick glimpse of the literature on this topic reveals that this technique is challenging, and no consensus or "best practices" currently exist, at least not within a single document. We present the first attempt to systematically analyze and summarize the literature of 80 studies that integrated task-based fMRI results to guide tractography, over the last two decades. We report 19 findings that cover challenges related to sample size, microstructure modelling, seeding methods, multimodal space registration, false negatives/positives, specificity/validity, gray/white matter interface and more. These findings will help the scientific community (1) understand the strengths and limitations of the approaches, (2) design studies using this integrative framework, and (3) motivate researchers to fill the gaps identified. We provide references toward best practices, in order to improve the overall result's replicability, sensitivity, specificity, and validity.

Brain microstructural abnormalities in 22q11.2 deletion syndrome: A systematic review of diffusion tensor imaging studies

22q11.2 deletion syndrome (22q11DS) is a severe genetic syndrome characterized by cognitive deficits and neuropsychiatric disorders, particularly schizophrenia. Neuroimaging alterations have been extensively reported in 22q11DS, both in gray and white matter structures. However, a considerable variability among the results affects the generalizability of the findings to date. Herein, we reviewed diffusion tensor imaging (DTI) findings in 22q11DS, their association with psychosis and cognition, and the implications of DTI studies on neurodevelopment in 22q11DS. We also investigated differences between 22q11DS and schizophrenic patients without 22q11DS. Using an online search of PubMed and Embase, we identified studies investigating DTI findings in 22q11DS. After selecting eligible studies in accordance with the preferred reporting items for systematic reviews and meta-analyses guideline, we included thirty-one studies. Overall, 22q11DS patients show altered structural connectivity and disrupted microstructural organization of most cortical and subcortical structures and white matter tracts. Moreover, despite a significant heterogeneity in the results, reduced diffusivity measures and elevated fractional anisotropy were observed. However controversial, compared to typically developing children, 22q11DS patients reached the peak of fractional anisotropy (FA) and the trough of radial diffusivity (RD) at an older age, which shows neurodevelopmental delay. DTI measures were also associated with psychotic symptoms and cognitive deficits. In conclusion, this study provides a comprehensive review of microstructural alterations in 22q11DS. Future larger investigations on this syndrome could potentially lead to the detection of early diagnostic imaging markers for genetically induced schizophrenia, thus improving the treatment and, ultimately, the outcome.

Oxidative-Antioxidant Imbalance and Impaired Glucose Metabolism in Schizophrenia

Schizophrenia is a neurodevelopmental disorder featuring chronic, complex neuropsychiatric features. The etiology and pathogenesis of schizophrenia are not fully understood. Oxidative-antioxidant imbalance is a potential determinant of schizophrenia. Oxidative, nitrosative, or sulfuric damage to enzymes of glycolysis and tricarboxylic acid cycle, as well as calcium transport and ATP biosynthesis might cause impaired bioenergetics function in the brain. This could explain the initial symptoms, such as the first psychotic episode and mild cognitive impairment. Another concept of the etiopathogenesis of schizophrenia is associated with impaired glucose metabolism and insulin resistance with the activation of the mTOR mitochondrial pathway, which may contribute to impaired neuronal development. Consequently, cognitive processes requiring ATP are compromised and dysfunctions in synaptic transmission lead to neuronal death, preceding changes in key brain areas. This review summarizes the role and mutual interactions of oxidative damage and impaired glucose metabolism as key factors affecting metabolic complications in schizophrenia. These observations may be a premise for novel potential therapeutic targets that will delay not only the onset of first symptoms but also the progression of schizophrenia and its complications.

The location discrimination reversal task in mice is sensitive to deficits in performance caused by aging, pharmacological and other challenges

Deficits in hippocampal-mediated pattern separation are one aspect of cognitive function affected in schizophrenia (SZ) or Alzheimer's disease (AD). To develop novel therapies, it is beneficial to explore this specific aspect of cognition preclinically. The location discrimination reversal (LDR) task is a hippocampal-dependent operant paradigm that evaluates spatial learning and cognitive flexibility using touchscreens. Here we assessed baseline performance as well as multimodal disease-relevant manipulations in mice. Mice were trained to discriminate between the locations of two images where the degree of separation impacted performance. Administration of putative pro-cognitive agents was unable to improve performance at narrow separation. Furthermore, a range of disease-relevant manipulations were characterized to assess whether performance could be impaired and restored. Pertinent to the cholinergic loss in AD, scopolamine (0.1 mg/kg) produced a disruption in LDR, which was attenuated by donepezil (1 mg/kg). Consistent with NMDA hypofunction in cognitive impairment associated with SZ, MK-801 (0.1 mg/kg) also disrupted performance; however, this deficit was not modified by rolipram. Microdeletion of genes associated with SZ (22q11) resulted in impaired performance, which was restored by rolipram (0.032 mg/kg). Since aging and inflammation affect cognition and are risk factors for AD, these aspects were also evaluated. Aged mice were slower to acquire the task than young mice and did not reach the same level of performance. A systemic inflammatory challenge (lipopolysaccharide (LPS), 1 mg/kg) produced prolonged (7 days) deficits in the LDR task. These data suggest that LDR task is a valuable platform for evaluating disease-relevant deficits in pattern separation and offers potential for identifying novel therapies.

Reading the (functional) writing on the (structural) wall: Multimodal fusion of brain structure and function via a deep neural network based translation approach reveals novel impairments in schizophrenia

This work presents a novel approach to finding linkage/association between multimodal brain imaging data, such as structural MRI (sMRI) and functional MRI (fMRI). Motivated by the machine translation domain, we employ a deep learning model, and consider two different imaging views of the same brain like two different languages conveying some common facts. That analogy enables finding linkages between two modalities. The proposed translation-based fusion model contains a computing layer that learns "alignments" (or links) between dynamic connectivity features from fMRI data and static gray matter patterns from sMRI data. The approach is evaluated on a multi-site dataset consisting of eyes-closed resting state imaging data collected from 298 subjects (age- and gender matched 154 healthy controls and 144 patients with schizophrenia). Results are further confirmed on an independent dataset consisting of eyes-open resting state imaging data from 189 subjects (age- and gender matched 91 healthy controls and 98 patients with schizophrenia). We used dynamic functional connectivity (dFNC) states as the functional features and ICA-based sources from gray matter densities as the structural features. The dFNC states characterized by weakly correlated intrinsic connectivity networks (ICNs) were found to have stronger association with putamen and insular gray matter pattern, while the dFNC states of profuse strongly correlated ICNs exhibited stronger links with the gray matter pattern in precuneus, posterior cingulate cortex (PCC), and temporal cortex. Further investigation with the estimated link strength (or alignment score) showed significant group differences between healthy controls and patients with schizophrenia in several key regions including temporal lobe, and linked these to connectivity states showing less occupancy in healthy controls. Moreover, this novel approach revealed significant correlation between a cognitive score (attention/vigilance) and the function/structure alignment score that was not detected when data modalities were considered separately.

JOINT EXPLORATION AND MINING OF MEMORY-RELEVANT BRAIN ANATOMIC AND CONNECTOMIC PATTERNS VIA A THREE-WAY ASSOCIATION MODEL

Early change in memory performance is a key symptom of many brain diseases, but its underlying mechanism remains largely unknown. While structural MRI has been playing an essential role in revealing potentially relevant brain regions, increasing availability of diffusion MRI data (e.g., Human Connectome Project (HCP)) provides excellent opportunities for exploration of their complex coordination. Given the complementary information held in these two imaging modalities, we hypothesize that studying them as a whole, rather than individually, and exploring their association will provide us valuable insights of the memory mechanism. However, many existing association methods, such as sparse canonical correlation analysis (SCCA), only manage to handle two-way association and thus cannot guarantee the selection of biomarkers and associations to be memory relevant. To overcome this limitation, we propose a new outcome-relevant SCCA model (OSCCA) together with a new algorithm to enable the three-way associations among brain connectivity, anatomic structure and episodic memory performance. In comparison with traditional SCCA, we demonstrate the effectiveness of our model with both synthetic and real data from the HCP cohort.