Copy number variants (CNVs) are deletions and duplications of DNA sequence. The most frequently studied CNVs, which are described in this review, are recurrent CNVs that occur in the same locations ...on the genome. These CNVs have been strongly implicated in neurodevelopmental disorders, namely autism spectrum disorder (ASD), intellectual disability (ID), and developmental delay (DD), but also in schizophrenia. More recent work has also shown that CNVs increase risk for other psychiatric disorders, namely, depression, bipolar disorder, and post-traumatic stress disorder. Many of the same CNVs are implicated across all of these disorders, and these neuropsychiatric CNVs are also associated with cognitive ability in the general population, as well as with structural and functional brain alterations. Neuropsychiatric CNVs also show incomplete penetrance, such that carriers do not always develop any psychiatric disorder, and may show only mild symptoms, if any. Variable expressivity, whereby the same CNVs are associated with many different phenotypes of varied severity, also points to highly complex mechanisms underlying disease risk in CNV carriers. Comprehensive and longitudinal phenotyping studies of individual CNVs have provided initial insights into these mechanisms. However, more work is needed to estimate and predict the effect of non-recurrent, ultra-rare CNVs, which also contribute to psychiatric and cognitive outcomes. Moreover, delineating the broader phenotypic landscape of neuropsychiatric CNVs in both clinical and general population cohorts may also offer important mechanistic insights.
There is a growing appreciation that clinically impairing irritability is an important transdiagnostic symptom among children and adolescents with mental illness. Severe irritability, defined by ...frequent, developmentally inappropriate temper outbursts and low frustration tolerance, is one of the most common reasons that youths are referred for psychiatric evaluation and care.
Although chronic irritability is the primary symptom in disruptive mood dysregulation disorder, the symptom is common in a diverse set of DSM-5 diagnoses, including major depressive disorder, autism spectrum disorder, oppositional defiant disorder, bipolar disorder, and generalized anxiety disorder.
Given that clinically impairing irritability is often predictive of poor outcomes in childhood and worse clinical course in adulthood, a concerted effort is being made to refine the definition of this symptom and determine if severe irritability could be better understood and treated as an independent diagnosis.
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Schizophrenia is a devastating neuropsychiatric syndrome associated with distributed brain dysconnectivity that may involve large-scale thalamo-cortical systems. Incomplete characterization of ...thalamic connectivity in schizophrenia limits our understanding of its relationship to symptoms and to diagnoses with shared clinical presentation, such as bipolar illness, which may exist on a spectrum. Using resting-state functional magnetic resonance imaging, we characterized thalamic connectivity in 90 schizophrenia patients versus 90 matched controls via: (1) Subject-specific anatomically defined thalamic seeds; (2) anatomical and data-driven clustering to assay within-thalamus dysconnectivity; and (3) machine learning to classify diagnostic membership via thalamic connectivity for schizophrenia and for 47 bipolar patients and 47 matched controls. Schizophrenia analyses revealed functionally related disturbances: Thalamic over-connectivity with bilateral sensory-motor cortices, which predicted symptoms, but thalamic under-connectivity with prefrontal-striatal-cerebellar regions relative to controls, possibly reflective of sensory gating and top-down control disturbances. Clustering revealed that this dysconnectivity was prominent for thalamic nuclei densely connected with the prefrontal cortex. Classification and cross-diagnostic results suggest that thalamic dysconnectivity may be a neural marker for disturbances across diagnoses. Present findings, using one of the largest schizophrenia and bipolar neuroimaging samples to date, inform basic understanding of large-scale thalamo-cortical systems and provide vital clues about the complex nature of its disturbances in severe mental illness.
Classic cognitive theory conceptualizes executive functions as involving multiple specific domains, including initiation, inhibition, working memory, flexibility, planning, and vigilance. Lesion and ...neuroimaging experiments over the past two decades have suggested that both common and unique processes contribute to executive functions during higher cognition. It has been suggested that a superordinate fronto–cingulo–parietal network supporting cognitive control may also underlie a range of distinct executive functions. To test this hypothesis in the largest sample to date, we used quantitative meta-analytic methods to analyze 193 functional neuroimaging studies of 2,832 healthy individuals, ages 18–60, in which performance on executive function measures was contrasted with an active control condition. A common pattern of activation was observed in the prefrontal, dorsal anterior cingulate, and parietal cortices across executive function domains, supporting the idea that executive functions are supported by a superordinate cognitive control network. However, domain-specific analyses showed some variation in the recruitment of anterior prefrontal cortex, anterior and midcingulate regions, and unique subcortical regions such as the basal ganglia and cerebellum. These results are consistent with the existence of a superordinate cognitive control network in the brain, involving dorsolateral prefrontal, anterior cingulate, and parietal cortices, that supports a broad range of executive functions.
This study aimed to determine the relative extent of impairment in social and nonsocial cognitive domains in patients with bipolar disorder compared with schizophrenia patients and healthy comparison ...subjects.
Sixty-eight clinically stable outpatients with bipolar disorder, 38 clinically stable outpatients with schizophrenia, and 36 healthy comparison subjects completed a range of social (facial affect perception, emotional regulation, empathic accuracy, mental state attribution, and self-referential memory) and nonsocial (speed of processing, attention/vigilance, working memory, verbal memory, visual memory, and reasoning/problem solving) cognitive tasks.
For each social cognitive task, patients with bipolar disorder did not differ significantly from comparison subjects, and both groups performed better than schizophrenia patients. Within the bipolar group, clinical features and medication status were not related to social cognitive performance. Bipolar patients showed performance patterns across tasks (i.e., profiles) that were similar to those of comparison subjects on both social and nonsocial cognitive domains, whereas both groups differed from schizophrenia patients for both domains. Regarding relative impairment across the two cognitive domains, results revealed a significant group-by-domain interaction in which bipolar patients showed less impaired social than nonsocial cognition, while schizophrenia patients showed the opposite pattern.
Bipolar patients showed less impairment on social relative to nonsocial cognitive performance, whereas schizophrenia patients showed more impairment on social relative to nonsocial cognitive performance. These results suggest that these two cognitive domains play different roles in bipolar disorder compared with in schizophrenia.
A critical issue in many neuroimaging studies is the comparison between brain maps. Nonetheless, it remains unclear how one should test hypotheses focused on the overlap or spatial correspondence ...between two or more brain maps. This “correspondence problem” affects, for example, the interpretation of comparisons between task-based patterns of functional activation, resting-state networks or modules, and neuroanatomical landmarks. To date, this problem has been addressed with remarkable variability in terms of methodological approaches and statistical rigor. In this paper, we address the correspondence problem using a spatial permutation framework to generate null models of overlap by applying random rotations to spherical representations of the cortical surface, an approach for which we also provide a theoretical statistical foundation. We use this method to derive clusters of cognitive functions that are correlated in terms of their functional neuroatomical substrates. In addition, using publicly available data, we formally demonstrate the correspondence between maps of task-based functional activity, resting-state fMRI networks and gyral-based anatomical landmarks. We provide open-access code to implement the methods presented for two commonly-used tools for surface based cortical analysis (https://www.github.com/spin-test). This spatial permutation approach constitutes a useful advance over widely-used methods for the comparison of cortical maps, thereby opening new possibilities for the integration of diverse neuroimaging data.
•A new method is developed to test the anatomical correspondence between brain maps.•Random rotational permutations generate rigorous null models of correspondence.•The correspondence of structural, functional and resting-state maps is quantified.•These methods are publicly available for future applications.
Genetics of the connectome Thompson, Paul M.; Ge, Tian; Glahn, David C. ...
NeuroImage,
10/2013, Volume:
80
Journal Article
Peer reviewed
Open access
Connectome genetics attempts to discover how genetic factors affect brain connectivity. Here we review a variety of genetic analysis methods—such as genome-wide association studies (GWAS), linkage ...and candidate gene studies—that have been fruitfully adapted to imaging data to implicate specific variants in the genome for brain-related traits. Studies that emphasized the genetic influences on brain connectivity. Some of these analyses of brain integrity and connectivity using diffusion MRI, and others have mapped genetic effects on functional networks using resting state functional MRI. Connectome-wide genome-wide scans have also been conducted, and we review the multivariate methods required to handle the extremely high dimension of the genomic and network data. We also review some consortium efforts, such as ENIGMA, that offer the power to detect robust common genetic associations using phenotypic harmonization procedures and meta-analysis. Current work on connectome genetics is advancing on many fronts and promises to shed light on how disease risk genes affect the brain. It is already discovering new genetic loci and even entire genetic networks that affect brain organization and connectivity.
•Connectome genetics promises to shed light on how disease risk genes affect the brain.•We review a variety of genetic analysis methods and studies of brain connectivity.•We focus on DTI and resting state fMRI studies that used a genetic design.•New genetic loci have been discovered that impact brain organization and connectivity.
Abstract
In recent years, replicability of neuroscientific findings, specifically those concerning correlates of morphological properties of gray matter (GM), have been subject of major scrutiny. Use ...of different processing pipelines and differences in their estimates of the macroscale GM may play an important role in this context. To address this issue, here, we investigated the cortical thickness estimates of three widely used pipelines. Based on analyses in two independent large-scale cohorts, we report high levels of within-pipeline reliability of the absolute cortical thickness-estimates and comparable spatial patterns of cortical thickness-estimates across all pipelines. Within each individual, absolute regional thickness differed between pipelines, indicating that in-vivo thickness measurements are only a proxy of actual thickness of the cortex, which shall only be compared within the same software package and thickness estimation technique. However, at group level, cortical thickness-estimates correlated strongly between pipelines, in most brain regions. The smallest between-pipeline correlations were observed in para-limbic areas and insula. These regions also demonstrated the highest interindividual variability and the lowest reliability of cortical thickness-estimates within each pipeline, suggesting that structural variations within these regions should be interpreted with caution.
The authors sought to map gray matter changes in first-episode schizophrenia and to compare these with the changes in chronic schizophrenia. They postulated that the data would show a progression of ...changes from hippocampal deficits in first-episode schizophrenia to include volume reductions in the amygdala and cortical gray matter in chronic schizophrenia.
A systematic search was conducted for voxel-based structural MRI studies of patients with first-episode schizophrenia and chronic schizophrenia in relation to comparison groups. Meta-analyses of the coordinates of gray matter differences were carried out using anatomical likelihood estimation. Maps of gray matter changes were constructed, and subtraction meta-analysis was used to compare them.
A total of 27 articles were identified for inclusion in the meta-analyses. A marked correspondence was observed in regions affected by both first-episode schizophrenia and chronic schizophrenia, including gray matter decreases in the thalamus, the left uncus/amygdala region, the insula bilaterally, and the anterior cingulate. In the comparison of first-episode schizophrenia and chronic schizophrenia, decreases in gray matter volume were detected in first-episode schizophrenia but not in chronic schizophrenia in the caudate head bilaterally; decreases were more widespread in cortical regions in chronic schizophrenia.
Anatomical changes in first-episode schizophrenia broadly coincide with a basal ganglia-thalamocortical circuit. These changes include bilateral reductions in caudate head gray matter, which are absent in chronic schizophrenia. Comparing first-episode schizophrenia and chronic schizophrenia, the authors did not find evidence for the temporolimbic progression of pathology from hippocampus to amygdala, but there was evidence for progression of cortical changes.
De novo and inherited rare genetic disorders (RGDs) are a major cause of human morbidity, frequently involving neuropsychiatric symptoms. Recent advances in genomic technologies and data sharing have ...revolutionized the identification and diagnosis of RGDs, presenting an opportunity to elucidate the mechanisms underlying neuropsychiatric disorders by investigating the pathophysiology of high-penetrance genetic risk factors. Here we seek out the best path forward for achieving these goals. We think future research will require consistent approaches across multiple RGDs and developmental stages, involving both the characterization of shared neuropsychiatric dimensions in humans and the identification of neurobiological commonalities in model systems. A coordinated and concerted effort across patients, families, researchers, clinicians and institutions, including rapid and broad sharing of data, is now needed to translate these discoveries into urgently needed therapies.
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