Neuroanatomical phenotypes in mental illness: identifying convergent and divergent cortical phenotypes across autism, ADHD and schizophrenia.

BACKGROUND: There is evidence suggesting neuropsychiatric disorders share genomic, cognitive and clinical features. Here, we ask if autism-spectrum disorders (ASD), attention-deficit/hyperactivity disorder (ADHD) and schizophrenia share neuroanatomical variations. METHODS: First, we used measures of cortical anatomy to estimate spatial overlap of neuroanatomical variation using univariate methods. Next, we developed a novel methodology to determine whether cortical deficits specifically target or are "enriched" within functional resting-state networks. RESULTS: We found cortical anomalies were preferentially enriched across functional networks rather than clustering spatially. Specifically, cortical thickness showed significant enrichment between patients with ASD and those with ADHD in the default mode network, between patients with ASD and those with schizophrenia in the frontoparietal and limbic networks, and between patients with ADHD and those with schizophrenia in the ventral attention network. Networks enriched in cortical thickness anomalies were also strongly represented in functional MRI results (Neurosynth; r = 0.64, p = 0.032). LIMITATIONS: We did not account for variable symptom dimensions and severity in patient populations, and our cross-sectional design prevented longitudinal analyses of developmental trajectories. CONCLUSION: These findings suggest that common deficits across neuropsychiatric disorders cannot simply be characterized as arising out of local changes in cortical grey matter, but rather as entities of both local and systemic alterations targeting brain networks.

Neuroanatomical phenotypes in mental illness: identifying convergent and divergent cortical phenotypes across autism, ADHD and schizophrenia.

BACKGROUND: There is evidence suggesting neuropsychiatric disorders share genomic, cognitive and clinical features. Here, we ask if autism-spectrum disorders (ASD), attention-deficit/hyperactivity disorder (ADHD) and schizophrenia share neuroanatomical variations. METHODS: First, we used measures of cortical anatomy to estimate spatial overlap of neuroanatomical variation using univariate methods. Next, we developed a novel methodology to determine whether cortical deficits specifically target or are "enriched" within functional resting-state networks. RESULTS: We found cortical anomalies were preferentially enriched across functional networks rather than clustering spatially. Specifically, cortical thickness showed significant enrichment between patients with ASD and those with ADHD in the default mode network, between patients with ASD and those with schizophrenia in the frontoparietal and limbic networks, and between patients with ADHD and those with schizophrenia in the ventral attention network. Networks enriched in cortical thickness anomalies were also strongly represented in functional MRI results (Neurosynth; r = 0.64, p = 0.032). LIMITATIONS: We did not account for variable symptom dimensions and severity in patient populations, and our cross-sectional design prevented longitudinal analyses of developmental trajectories. CONCLUSION: These findings suggest that common deficits across neuropsychiatric disorders cannot simply be characterized as arising out of local changes in cortical grey matter, but rather as entities of both local and systemic alterations targeting brain networks.

Genetic influences on individual differences in longitudinal changes in global and subcortical brain volumes: Results of the ENIGMA plasticity working group.

Structural brain changes that occur during development and ageing are related to mental health and general cognitive functioning. Individuals differ in the extent to which their brain volumes change over time, but whether these differences can be attributed to differences in their genotypes has not been widely studied. Here we estimate heritability (h2 ) of changes in global and subcortical brain volumes in five longitudinal twin cohorts from across the world and in different stages of the lifespan (N = 861). Heritability estimates of brain changes were significant and ranged from 16% (caudate) to 42% (cerebellar gray matter) for all global and most subcortical volumes (with the exception of thalamus and pallidum). Heritability estimates of change rates were generally higher in adults than in children suggesting an increasing influence of genetic factors explaining individual differences in brain structural changes with age. In children, environmental influences in part explained individual differences in developmental changes in brain structure. Multivariate genetic modeling showed that genetic influences of change rates and baseline volume significantly overlapped for many structures. The genetic influences explaining individual differences in the change rate for cerebellum, cerebellar gray matter and lateral ventricles were independent of the genetic influences explaining differences in their baseline volumes. These results imply the existence of genetic variants that are specific for brain plasticity, rather than brain volume itself. Identifying these genes may increase our understanding of brain development and ageing and possibly have implications for diseases that are characterized by deviant developmental trajectories of brain structure. Hum Brain Mapp 38:4444-4458, 2017. © 2017 Wiley Periodicals, Inc.

Disrupted sensorimotor and social-cognitive networks underlie symptoms in childhood-onset schizophrenia.

Schizophrenia is increasingly recognized as a neurodevelopmental disorder with altered connectivity among brain networks. In the current study we examined large-scale network interactions in childhood-onset schizophrenia, a severe form of the disease with salient genetic and neurobiological abnormalities. Using a data-driven analysis of resting-state functional magnetic resonance imaging fluctuations, we characterized data from 19 patients with schizophrenia and 26 typically developing controls, group matched for age, sex, handedness, and magnitude of head motion during scanning. This approach identified 26 regions with decreased functional correlations in schizophrenia compared to controls. These regions were found to organize into two function-related networks, the first with regions associated with social and higher-level cognitive processing, and the second with regions involved in somatosensory and motor processing. Analyses of across- and within-network regional interactions revealed pronounced across-network decreases in functional connectivity in the schizophrenia group, as well as a set of across-network relationships with overall negative coupling indicating competitive or opponent network dynamics. Critically, across-network decreases in functional connectivity in schizophrenia predicted the severity of positive symptoms in the disorder, such as hallucinations and delusions. By contrast, decreases in functional connectivity within the social-cognitive network of regions predicted the severity of negative symptoms, such as impoverished speech and flattened affect. These results point toward the role that abnormal integration of sensorimotor and social-cognitive processing may play in the pathophysiology and symptomatology of schizophrenia.

Dissociations in Cortical Morphometry in Youth with Down Syndrome: Evidence for Reduced Surface Area but Increased Thickness.

Detailed descriptions of cortical anatomy in youth with Down syndrome (DS), the most common genetic cause of intellectual disability (ID), are scant. Thus, the current study examined deviations in cortical thickness (CT) and surface area (SA), at high spatial resolution, in youth with DS, to identify focal differences relative to typically developing (TD) youth. Participants included 31 youth with DS and 45 age- and sex-matched TD controls (mean age ∼16 years; range = 5-24 years). All participants completed T1-weighted ASSET-calibrated magnetization prepared rapid gradient echo scans on a 3-T magnetic resonance imaging scanner. Replicating prior investigations, cortical volume was reduced in DS compared with controls. However, a novel dissociation for SA and CT was found-namely, SA was reduced (predominantly in frontal and temporal regions) while CT was increased (notably in several regions thought to belong to the default mode network; DMN). These findings suggest that reductions in SA rather than CT are driving the cortical volume reductions reported in prior investigations of DS. Moreover, given the link between DMN functionality and Alzheimer's symptomatology in chromosomally typical populations, future DS studies may benefit from focusing on the cortex in DMN regions, as such investigations may provide clues to the precocious onset of Alzheimer's disease in this at-risk group.

Striatal shape abnormalities as novel neurodevelopmental endophenotypes in schizophrenia: a longitudinal study.

There are varying, often conflicting, reports with respect to altered striatal volume and morphometry in the major psychoses due to the influences of antipsychotic medications on striatal volume. Thus, disassociating disease effects from those of medication become exceedingly difficult. For the first time, using a longitudinally studied sample of structural magnetic resonance images from patients with childhood onset schizophrenia (COS; neurobiologically contiguous with the adult onset form of schizophrenia), their nonpsychotic siblings (COSSIBs), and novel shape mapping algorithms that are volume independent, we report the familial contribution of striatal morphology in schizophrenia. The results of our volumetric analyses demonstrate age-related increases in overall striatal volumes specific only to COS. However, both COS and COSSIBs showed overlapping shape differences in the striatal head, which normalized in COSSIBs by late adolescence. These results mirror previous studies from our group, demonstrating cortical thickness deficits in COS and COSSIBs as these deficits normalize in COSSIBs in the same age range as our striatal findings. Finally, there is a single region of nonoverlapping outward displacement in the dorsal aspect of the caudate body, potentially indicative of a response to medication. Striatal shape may be considered complimentary to volume as an endophenotype, and, in some cases may provide information that is not detectable using standard volumetric techniques. Our striatal shape findings demonstrate the striking localization of abnormalities in striatal the head. The neuroanatomical localization of these findings suggest the presence of abnormalities in the striatal-prefrontal circuits in schizophrenia and resilience mechanisms in COSSIBs with age dependent normalization.

Functional and clinical insights from neuroimaging studies in childhood-onset schizophrenia.

Childhood-onset schizophrenia is a rare pediatric onset psychiatric disorder continuous with and typically more severe than its adult counterpart. Neuroimaging research conducted on this population has revealed similarly severe neural abnormalities. When taken as a whole, neuroimaging research in this population shows generally decreased cortical gray matter coupled with white matter connectivity abnormalities, suggesting an anatomical basis for deficits in executive function. Subcortical abnormalities are pronounced in limbic structures, where volumetric deficits are likely related to social skill deficits, and cerebellar deficits that have been correlated to cognitive abnormalities. Structures relevant to motor processing also show a significant alteration, with volumetric increase in basal ganglia structures likely due to antipsychotic administration. Neuroimaging of this disorder shows an important clinical image of exaggerated cortical loss, altered white matter connectivity, and differences in structural development of subcortical areas during the course of development and provides important background to the disease state.

Simple models of human brain functional networks.

Human brain functional networks are embedded in anatomical space and have topological properties--small-worldness, modularity, fat-tailed degree distributions--that are comparable to many other complex networks. Although a sophisticated set of measures is available to describe the topology of brain networks, the selection pressures that drive their formation remain largely unknown. Here we consider generative models for the probability of a functional connection (an edge) between two cortical regions (nodes) separated by some Euclidean distance in anatomical space. In particular, we propose a model in which the embedded topology of brain networks emerges from two competing factors: a distance penalty based on the cost of maintaining long-range connections; and a topological term that favors links between regions sharing similar input. We show that, together, these two biologically plausible factors are sufficient to capture an impressive range of topological properties of functional brain networks. Model parameters estimated in one set of functional MRI (fMRI) data on normal volunteers provided a good fit to networks estimated in a second independent sample of fMRI data. Furthermore, slightly detuned model parameters also generated a reasonable simulation of the abnormal properties of brain functional networks in people with schizophrenia. We therefore anticipate that many aspects of brain network organization, in health and disease, may be parsimoniously explained by an economical clustering rule for the probability of functional connectivity between different brain areas.

A family affair: brain abnormalities in siblings of patients with schizophrenia.

Schizophrenia is a severe mental disorder that has a strong genetic basis. Converging evidence suggests that schizophrenia is a progressive neurodevelopmental disorder, with earlier onset cases resulting in more profound brain abnormalities. Siblings of patients with schizophrenia provide an invaluable resource for differentiating between trait and state markers, thus highlighting possible endophenotypes for ongoing research. However, findings from sibling studies have not been systematically put together in a coherent story across the broader age span. We review here the cortical grey matter abnormalities in siblings of patients with schizophrenia from childhood to adulthood, by reviewing sibling studies from both childhood-onset schizophrenia, and the more common adult-onset schizophrenia. When reviewed together, studies suggest that siblings of patients with schizophrenia display significant brain abnormalities that highlight both similarities and differences between the adult and childhood populations, with shared developmental risk patterns, and segregating trajectories. Based on current research it appears that the cortical grey matter abnormalities in siblings are likely to be an age-dependent endophenotype, which normalize by the typical age of onset of schizophrenia unless there has been more genetic or symptom burdening. With increased genetic burdening (e.g. discordant twins of patients) the grey matter abnormalities in (twin) siblings are progressive in adulthood. This synthesis of the literature clarifies the importance of brain plasticity in the pathophysiology of the illness, indicating that probands may lack protective factors critical for healthy development.

The anatomical distance of functional connections predicts brain network topology in health and schizophrenia.

The human brain is a topologically complex network embedded in anatomical space. Here, we systematically explored relationships between functional connectivity, complex network topology, and anatomical (Euclidean) distance between connected brain regions, in the resting-state functional magnetic resonance imaging brain networks of 20 healthy volunteers and 19 patients with childhood-onset schizophrenia (COS). Normal between-subject differences in average distance of connected edges in brain graphs were strongly associated with variation in topological properties of functional networks. In addition, a club or subset of connector hubs was identified, in lateral temporal, parietal, dorsal prefrontal, and medial prefrontal/cingulate cortical regions. In COS, there was reduced strength of functional connectivity over short distances especially, and therefore, global mean connection distance of thresholded graphs was significantly greater than normal. As predicted from relationships between spatial and topological properties of normal networks, this disorder-related proportional increase in connection distance was associated with reduced clustering and modularity and increased global efficiency of COS networks. Between-group differences in connection distance were localized specifically to connector hubs of multimodal association cortex. In relation to the neurodevelopmental pathogenesis of schizophrenia, we argue that the data are consistent with the interpretation that spatial and topological disturbances of functional network organization could arise from excessive "pruning" of short-distance functional connections in schizophrenia.

Longitudinally mapping the influence of sex and androgen signaling on the dynamics of human cortical maturation in adolescence.

Humans have systematic sex differences in brain-related behavior, cognition, and pattern of mental illness risk. Many of these differences emerge during adolescence, a developmental period of intense neurostructural and endocrine change. Here, by creating "movies" of sexually dimorphic brain development using longitudinal in vivo structural neuroimaging, we show regionally specific sex differences in development of the cerebral cortex during adolescence. Within cortical subsystems known to underpin domains of cognitive behavioral sex difference, structural change is faster in the sex that tends to perform less well within the domain in question. By stratifying participants through molecular analysis of the androgen receptor gene, we show that possession of an allele conferring more efficient functioning of this sex steroid receptor is associated with "masculinization" of adolescent cortical maturation. Our findings extend models first established in rodents, and suggest that in humans too, sex and sex steroids shape brain development in a spatiotemporally specific manner, within neural systems known to underpin sexually dimorphic behaviors.

DSM-5-TR: Rationale, Process, and Overview of Changes.

The DSM-5 text revision (DSM-5-TR) is the first published revision of the DSM-5 since its publication in 2013. Like the previous text revision (DSM-IV-TR), the main goal of the DSM-5-TR is to comprehensively update the descriptive text accompanying each DSM disorder on the basis of reviews of the literature over the past 10 years. In contrast to the DSM-IV-TR, in which updates were confined almost exclusively to the text, the DSM-5-TR includes many other changes and enhancements of interest to practicing clinicians, such as the addition of diagnostic categories (prolonged grief disorder, stimulant-induced mild neurocognitive disorder, unspecified mood disorder, and a category to indicate the absence of a diagnosis); the provision of ICD-10-CM symptom codes for reporting suicidal and nonsuicidal self-injurious behavior; modifications, mostly for clarity, of the diagnostic criteria for more than 70 disorders; and updates in terminology (e.g., replacing "neuroleptic medications" with "antipsychotic medications or other dopamine receptor blocking agents" throughout the text and replacing "desired gender" with "experienced gender" in the text for gender dysphoria). Finally, the entire text was reviewed by an Ethnoracial Equity and Inclusion Work Group to ensure appropriate attention to risk factors such as the experience of racism and discrimination, as well as the use of nonstigmatizing language.

How does your cortex grow?

Understanding human cortical maturation is a central goal for developmental neuroscience. Significant advances toward this goal have come from two recent strands of in vivo structural magnetic resonance imaging research: (1) longitudinal study designs have revealed that factors such as sex, cognitive ability, and disease are often better related to variations in the tempo of anatomical change than to variations in anatomy at any one time point; (2) largely cross-sectional applications of new surface-based morphometry (SBM) methods have shown how the traditional focus on cortical volume (CV) can obscure information about the two evolutionarily and genetically distinct determinants of CV: cortical thickness (CT) and surface area (SA). Here, by combining these two strategies for the first time and applying SBM in >1250 longitudinally acquired brain scans from 647 healthy individuals aged 3-30 years, we deconstruct cortical development to reveal that distinct trajectories of anatomical change are hidden within, and give rise to, a curvilinear pattern of CV maturation. Developmental changes in CV emerge through the sexually dimorphic and age-dependent interaction of changes in CT and SA. Moreover, SA change itself actually reflects complex interactions between brain size-related changes in exposed cortical convex hull area, and changes in the degree of cortical gyrification, which again vary by age and sex. Knowing of these developmental dissociations, and further specifying their timing and sex-biases, provides potent new research targets for basic and clinical neuroscience.

The discovery of population differences in network community structure: new methods and applications to brain functional networks in schizophrenia.

The modular organization of the brain network can vary in two fundamental ways. The amount of inter- versus intra-modular connections between network nodes can be altered, or the community structure itself can be perturbed, in terms of which nodes belong to which modules (or communities). Alterations have previously been reported in modularity, which is a function of the proportion of intra-modular edges over all modules in the network. For example, we have reported that modularity is decreased in functional brain networks in schizophrenia: There are proportionally more inter-modular edges and fewer intra-modular edges. However, despite numerous and increasing studies of brain modular organization, it is not known how to test for differences in the community structure, i.e., the assignment of regional nodes to specific modules. Here, we introduce a method based on the normalized mutual information between pairs of modular networks to show that the community structure of the brain network is significantly altered in schizophrenia, using resting-state fMRI in 19 participants with childhood-onset schizophrenia and 20 healthy participants. We also develop tools to show which specific nodes (or brain regions) have significantly different modular communities between groups, a subset that includes right insular and perisylvian cortical regions. The methods that we propose are broadly applicable to other experimental contexts, both in neuroimaging and other areas of network science.

Climate Change and Mental Health: Implications for the Psychiatric Workforce.

Climate change is a major global public mental health crisis that is expected to increase the need for mental health services. Psychiatrists and other mental health care providers must address workforce needs through recruitment, training and education, prevention and intervention, public policy and advocacy, and direct efforts to reduce climate change. This column discusses concrete steps for the psychiatric workforce to take to prepare for growing mental health needs associated with climate change.

Genetic variants associated with longitudinal changes in brain structure across the lifespan.

Human brain structure changes throughout the lifespan. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental and neurodegenerative diseases. In this study, we identified common genetic variants that affect rates of brain growth or atrophy in what is, to our knowledge, the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal magnetic resonance imaging data from 15,640 individuals were used to compute rates of change for 15 brain structures. The most robustly identified genes GPR139, DACH1 and APOE are associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and aging.

Catechol-o-methyl transferase (COMT) val158met polymorphism and adolescent cortical development in patients with childhood-onset schizophrenia, their non-psychotic siblings, and healthy controls.

Non-psychotic individuals at increased risk for schizophrenia show alterations in fronto-striatal dopamine signaling and cortical gray matter maturation reminiscent of those seen in schizophrenia. It remains unclear however if variations in dopamine signaling influence rates of structural cortical maturation in typically developing individuals, and whether such influences are disrupted in patients with schizophrenia and their non-psychotic siblings. We sought to address these issues by relating a functional Val→Met polymorphism within the gene encoding catechol-o-methyltransferase (COMT)-a key enzymatic regulator of cortical dopamine levels-to longitudinal structural neuroimaging measures of cortical gray matter thickness. We included a total of 792 magnetic resonance imaging brain scans, acquired between ages 9 and 22 years from patients with childhood-onset schizophrenia (COS), their non-psychotic full siblings, and matched healthy controls. Whereas greater Val allele dose (which confers enhanced dopamine catabolism and is proposed to aggravate cortical deficits in schizophrenia) accelerated adolescent cortical thinning in both schizophrenia probands and their siblings, it attenuated cortical thinning in healthy controls. This similarity between COS patients and their siblings was accompanied by differences between the two groups in the timing and spatial distribution of disrupted COMT influences on cortical maturation. Consequently, whereas greater Val "dose" conferred persistent dorsolateral prefrontal cortical deficits amongst affected probands by adulthood, cortical thickness differences associated with varying Val dose in non-psychotic siblings resolved over the age-range studied. These findings suggest that cortical abnormalities in pedigrees affected by schizophrenia may be contributed to by a disruption of dopaminergic infleunces on cortical maturation.

Cerebellar development in childhood onset schizophrenia and non-psychotic siblings.

We explored regional and total volumetric cerebellar differences in probands and their unaffected full siblings relative to typically developing participants. Participants included 94 (51 males) patients diagnosed with childhood onset schizophrenia (COS), 80 related non-psychotic siblings (37 males) and 110 (64 males) typically developing participants scanned longitudinally. The sample mean age was 16.87(S.D.=4.7; range 6.5 to 29). We performed mixed model regressions to examine group differences in trajectory and volume. The COS group had smaller bilateral anterior lobes and anterior and total vermis volumes than controls. The COS group diverged from controls over time in total, left, right, and bilateral posterior inferior cerebellum. Siblings did not have any fixed volumetric differences relative to controls but differed from controls in developmental trajectories of total and right cerebellum, left inferior posterior, left superior posterior, and superior vermis. Results are consistent with previous COS findings and several reports of decreased cerebellar volume in adult onset schizophrenia. Sibling trajectories may represent a trait marker, although the effect size for volumetric differences in early adulthood may be small.

Three-dimensional brain growth abnormalities in childhood-onset schizophrenia visualized by using tensor-based morphometry.

Earlier studies revealed progressive cortical gray matter (GM) loss in childhood-onset schizophrenia (COS) across both lateral and medial surfaces of the developing brain. Here, we use tensor-based morphometry to visualize white matter (WM) growth abnormalities in COS throughout the brain. Using high-dimensional elastic image registration, we compared 3D maps of local WM growth rates in COS patients and healthy children over a 5-year period, based on analyzing longitudinal brain MRIs from 12 COS patients and 12 healthy controls matched for age, gender, and scan interval. COS patients showed up to 2.2% slower growth rates per year than healthy controls in WM (P = 0.02, all P values corrected). The greatest differences were in the right hemisphere (P = 0.006). This asymmetry was attributable to a right slower than left hemisphere growth rate mapped in COS patients (P = 0.037) but not in healthy controls. WM growth rates reached 2.6% per year in healthy controls (P = 0.0002). COS patients showed only a 1.3% per year trend for growth in the left hemisphere (P = 0.066). In COS, WM growth rates were associated with improvement in the Children's Global Assessment Scale (R = 0.64, P = 0.029). Growth rates were reduced throughout the brain in COS, but this process appeared to progress in a front-to-back (frontal-parietal) fashion, and this effect was not attributable to lower IQ. Growth rates were correlated with functional prognosis and were visualized as detailed 3D maps. Finally, these findings also confirm that the progressive GM deficits seen in schizophrenia are not the result of WM overgrowth.

Childhood psychiatric disorders as anomalies in neurodevelopmental trajectories.

Childhood psychiatric disorders are rarely static; rather they change over time and longitudinal studies are ideally suited to capture such dynamic processes. Using longitudinal data, insights can be gained into the nature of the perturbation away from the trajectory of typical development in childhood disorders. Thus, some disorders may reflect a delay in neurodevelopmental trajectories. Our studies in children with attention-deficit/hyperactivity disorder (ADHD) suggest that cortical development is delayed with a rightward shift along the age axis in cortical trajectories, most prominent in prefrontal cortical regions. Other disorders may be characterized by differences in the velocity of trajectories: the basic shape of neurodevelopmental curves remains intact, but with disrupted tempo. Thus, childhood onset schizophrenia is associated with a marked increase during adolescence in the velocity of loss of cerebral gray matter. By contrast, in childhood autism there is an early acceleration of brain growth, which overshoots typical dimensions leading to transient cerebral enlargement. Finally, there may be more profound deviations from typical neurodevelopment, with a complete "derailing" of brain growth and a loss of the features which characterize typical brain development. An example is the almost complete silencing of white matter growth during adolescence of patients with childhood onset schizophrenia. Adopting a longitudinal perspective also readily lends itself to the understanding of the neural bases of differential clinical outcomes. Again taking ADHD as an example, we found that remission is associated with convergence to the template of typical development, whereas persistence is accompanied by progressive divergence away from typical trajectories.