Effects of sex chromosome dosage on corpus callosum morphology in supernumerary sex chromosome aneuploidies.

BackgroundSupernumerary sex chromosome aneuploidies (sSCA) are characterized by the presence of one or more additional sex chromosomes in an individual's karyotype; they affect around 1 in 400 individuals. Although there is high variability, each sSCA subtype has a characteristic set of cognitive and physical phenotypes. Here, we investigated the differences in the morphometry of the human corpus callosum (CC) between sex-matched controls 46,XY (N =99), 46,XX (N =93), and six unique sSCA karyotypes: 47,XYY (N =29), 47,XXY (N =58), 48,XXYY (N =20), 47,XXX (N =30), 48,XXXY (N =5), and 49,XXXXY (N =6).MethodsWe investigated CC morphometry using local and global area, local curvature of the CC boundary, and between-landmark distance analysis (BLDA). We hypothesized that CC morphometry would vary differentially along a proposed spectrum of Y:X chromosome ratio with supernumerary Y karyotypes having the largest CC areas and supernumerary X karyotypes having significantly smaller CC areas. To investigate this, we defined an sSCA spectrum based on a descending Y:X karyotype ratio: 47,XYY, 46,XY, 48,XXYY, 47,XXY, 48,XXXY, 49,XXXXY, 46,XX, 47,XXX. We similarly explored the effects of both X and Y chromosome numbers within sex. Results of shape-based metrics were analyzed using permutation tests consisting of 5,000 iterations.ResultsSeveral subregional areas, local curvature, and BLDs differed between groups. Moderate associations were found between area and curvature in relation to the spectrum and X and Y chromosome counts. BLD was strongly associated with X chromosome count in both male and female groups.ConclusionsOur results suggest that X- and Y-linked genes have differential effects on CC morphometry. To our knowledge, this is the first study to compare CC morphometry across these extremely rare groups

Mapping cortical anatomy in preschool aged children with autism using surface-based morphometry☆

The challenges of gathering in-vivo measures of brain anatomy from young children have limited the number of independent studies examining neuroanatomical differences between children with autism and typically developing controls (TDCs) during early life, and almost all studies in this critical developmental window focus on global or lobar measures of brain volume. Using a novel cohort of young males with Autistic Disorder and TDCs aged 2 to 5 years, we (i) tested for group differences in traditional measures of global anatomy (total brain, total white, total gray and total cortical volume), and (ii) employed surface-based methods for cortical morphometry to directly measure the two biologically distinct sub-components of cortical volume (CV) at high spatial resolution—cortical thickness (CT) and surface area (SA). While measures of global brain anatomy did not show statistically significant group differences, children with autism showed focal, and CT-specific anatomical disruptions compared to TDCs, consisting of relative cortical thickening in regions with central roles in behavioral regulation, and the processing of language, biological movement and social information. Our findings demonstrate the focal nature of brain involvement in early autism, and provide more spatially and morphometrically specific anatomical phenotypes for subsequent translational study

Differential tangential expansion as a mechanism for cortical gyrification.

Gyrification, the developmental buckling of the cortex, is not a random process-the forces that mediate expansion do so in such a way as to generate consistent patterns of folds across individuals and even species. Although the origin of these forces is unknown, some theories have suggested that they may be related to external cortical factors such as axonal tension. Here, we investigate an alternative hypothesis, namely, whether the differential tangential expansion of the cortex alone can account for the degree and pattern-specificity of gyrification. Using intrinsic curvature as a measure of differential expansion, we initially explored whether this parameter and the local gyrification index (used to quantify the degree of gyrification) varied in a regional-specific pattern across the cortical surface in a manner that was replicable across independent datasets of neurotypicals. Having confirmed this consistency, we further demonstrated that within each dataset, the degree of intrinsic curvature of the cortex was predictive of the degree of cortical folding at a global and regional level. We conclude that differential expansion is a plausible primary mechanism for gyrification, and propose that this perspective offers a compelling mechanistic account of the co-localization of cytoarchitecture and cortical folds

Leveraging big data for causal understanding in mental health: a research framework

Over the past 30 years there have been numerous large-scale and longitudinal psychiatric research efforts to improve our understanding and treatment of mental health conditions. However, despite the huge effort by the research community and considerable funding, we still lack a causal understanding of most mental health disorders. Consequently, the majority of psychiatric diagnosis and treatment still operates at the level of symptomatic experience, rather than measuring or addressing root causes. This results in a trial-and-error approach that is a poor fit to underlying causality with poor clinical outcomes. Here we discuss how a research framework that originates from exploration of causal factors, rather than symptom groupings, applied to large scale multi-dimensional data can help address some of the current challenges facing mental health research and, in turn, clinical outcomes. Firstly, we describe some of the challenges and complexities underpinning the search for causal drivers of mental health conditions, focusing on current approaches to the assessment and diagnosis of psychiatric disorders, the many-to-many mappings between symptoms and causes, the search for biomarkers of heterogeneous symptom groups, and the multiple, dynamically interacting variables that influence our psychology. Secondly, we put forward a causal-orientated framework in the context of two large-scale datasets arising from the Adolescent Brain Cognitive Development (ABCD) study, the largest long-term study of brain development and child health in the United States, and the Global Mind Project which is the largest database in the world of mental health profiles along with life context information from 1.4 million people across the globe. Finally, we describe how analytical and machine learning approaches such as clustering and causal inference can be used on datasets such as these to help elucidate a more causal understanding of mental health conditions to enable diagnostic approaches and preventative solutions that tackle mental health challenges at their root cause

Through Thick and Thin: a Need to Reconcile Contradictory Results on Trajectories in Human Cortical Development

Abstract Understanding how brain development normally proceeds is a premise of understanding neurodevelopmental disorders. This has sparked a wealth of magnetic resonance imaging (MRI) studies. Unfortunately, they are in marked disagreement on how the cerebral cortex matures. While cortical thickness increases for the first 8-9 years of life have repeatedly been reported, others find continuous cortical thinning from early childhood, at least from age 3 or 4 years. We review these inconsistencies, and discuss possible reasons, including the use of different scanners, recording parameters and analysis tools, and possible effects of variables such as head motion. When tested on the same subsample, 2 popular thickness estimation methods (CIVET and FreeSurfer) both yielded a continuous thickness decrease from 3 years. Importantly, MRI-derived measures of cortical development are merely our best current approximations, hence the term "apparent cortical thickness" may be preferable. We recommend strategies for reaching consensus in the field, including multimodal neuroimaging to measure phenomena using different techniques, for example, the use of T 1 /T 2 ratio, and data sharing to allow replication across analysis methods. As neurodevelopmental origins of early-and late-onset disease are increasingly recognized, resolving inconsistencies in brain maturation trajectories is important

Transitions Into Underage and Problem Drinking: Summary of Developmental Processes and Mechanisms: Ages 10–15

Adolescents ages 10–15 experience dramatic changes in their biological, cognitive, emotional, and social development as well as in their physical and social environments. These include the physiological and psychological changes associated with puberty; further development of the brain; changes in family, peer, and romantic relationships; and exposure to new societal and cultural influences. During this period, many adolescents also begin to use alcohol. Alcohol use during adolescence has adverse effects on the body and increases the risk of alcohol dependence later in life. To better understand why some children drink whereas others do not, researchers are examining nonspecific and alcohol-specific factors that put adolescents at risk for, or which protect them from, early alcohol use and its associated problems. Nonspecific risk factors include certain temperamental and personality traits, family factors, and nonnormative development. Examples of nonspecific protective factors include certain temperamental characteristics, religiosity, and parenting factors (e.g., parental nurturance and monitoring). Among the most influential alcohol-specific risk and protective factors are a family history of alcoholism and the influences of siblings and peers, all of which shape an adolescent’s expectancies about the effects of alcohol, which in turn help determine alcohol use behaviors

Basal ganglia morphometry and repetitive behavior in young children with autism spectrum disorder

We investigated repetitive and stereotyped behavior (RSB) and its relationship to morphometric measures of the basal ganglia and thalami in 3-4 year old children with autism spectrum disorder (ASD; n=77) and developmental delay without autism (DD; n=34). Children were assessed through clinical evaluation and parent report using RSB-specific scales extracted from the Autism Diagnostic Observation Schedule (ADOS), the Autism Diagnostic Interview, and the Aberrant Behavior Checklist. A subset of children with ASD (n=45), DD (n=14) and a group of children with typical development (TD; n=25) were also assessed by magnetic resonance imaging (MRI). Children with ASD demonstrated elevated RSB across all measures compared to children with DD. Enlargement of the left and right striatum, more specifically the left and right putamen, and left caudate, was observed in the ASD compared to the TD group. However, nuclei were not significantly enlarged after controlling for cerebral volume. The DD group, in comparison to the ASD group, demonstrated smaller thalami and basal ganglia regions even when scaled for cerebral volume, with the exception of the left striatum, left putamen, and right putamen. Elevated RSB, as measured by the ADOS, was associated with decreased volumes in several brain regions: left thalamus, right globus pallidus, left and right putamen, right striatum and a trend for left globus pallidus and left striatum within the ASD group. These results confirm earlier reports that RSB is common early in the clinical course of ASD and, furthermore, demonstrate that such behaviors may be associated with decreased volumes of the basal ganglia and thalamus

Transitions Into Underage and Problem Drinking: Developmental Processes and Mechanisms Between 10 and 15 Years of Age

Adolescents ages 10–15 experience dramatic changes in their biological, cognitive, emotional, and social development as well as in their physical and social environments. These include the physiological and psychological changes associated with puberty; further development of the brain; changes in family, peer, and romantic relationships; and exposure to new societal and cultural influences. During this period, many adolescents also begin to use alcohol. Alcohol use during adolescence has adverse effects on the body and increases the risk of alcohol dependence later in life. To better understand why some children drink whereas others do not, researchers are examining nonspecific and alcohol-specific factors that put adolescents at risk for, or which protect them from, early alcohol use and its associated problems. Nonspecific risk factors include certain temperamental and personality traits, family factors, and nonnormative development. Examples of nonspecific protective factors include certain temperamental characteristics, religiosity, and parenting factors (e.g., parental nurturance and monitoring). Among the most influential alcohol-specific risk and protective factors are a family history of alcoholism and the influences of siblings and peers, all of which shape an adolescent’s expectancies about the effects of alcohol, which in turn help determine alcohol use behaviors

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.PEV is supported by the Medical Research Council (grant number MR/K020706/1). This work was supported by the Neuroscience in Psychiatry Network (NSPN) which is funded by a Wellcome Trust strategy award to the University of Cambridge and University College London. ETB is employed half-time by the University of Cambridge and half-time by GlaxoSmithKline; he holds stock in GSK.This is the final published version. It first appeared at http://onlinelibrary.wiley.com/doi/10.1111/jcpp.12365/full

Correspondence Between Perceived Pubertal Development and Hormone Levels in 9-10 Year-Olds From the Adolescent Brain Cognitive Development Study.

Aim: To examine individual variability between perceived physical features and hormones of pubertal maturation in 9-10-year-old children as a function of sociodemographic characteristics. Methods: Cross-sectional metrics of puberty were utilized from the baseline assessment of the Adolescent Brain Cognitive Development (ABCD) Study—a multi-site sample of 9–10 year-olds (n = 11,875)—and included perceived physical features via the pubertal development scale (PDS) and child salivary hormone levels (dehydroepiandrosterone and testosterone in all, and estradiol in females). Multi-level models examined the relationships among sociodemographic measures, physical features, and hormone levels. A group factor analysis (GFA) was implemented to extract latent variables of pubertal maturation that integrated both measures of perceived physical features and hormone levels. Results: PDS summary scores indicated more males (70%) than females (31%) were prepubertal. Perceived physical features and hormone levels were significantly associated with child\u27s weight status and income, such that more mature scores were observed among children that were overweight/obese or from households with low-income. Results from the GFA identified two latent factors that described individual differences in pubertal maturation among both females and males, with factor 1 driven by higher hormone levels, and factor 2 driven by perceived physical maturation. The correspondence between latent factor 1 scores (hormones) and latent factor 2 scores (perceived physical maturation) revealed synchronous and asynchronous relationships between hormones and concomitant physical features in this large young adolescent sample. Conclusions: Sociodemographic measures were associated with both objective hormone and self-report physical measures of pubertal maturation in a large, diverse sample of 9-10 year-olds. The latent variables of pubertal maturation described a complex interplay between perceived physical changes and hormone levels that hallmark sexual maturation, which future studies can examine in relation to trajectories of brain maturation, risk/resilience to substance use, and other mental health outcomes