Externalizing behavior in its more extreme form is often considered a problem to the individual, their families, teachers, and society as a whole. Several brain structures have been linked to ...externalizing behavior and such associations may arise if the (co)development of externalizing behavior and brain structures share the same genetic and/or environmental factor(s). We assessed externalizing behavior with the Child Behavior Checklist and Youth Self Report, and the brain volumes and white matter integrity (fractional anisotropy FA and mean diffusivity MD) with magnetic resonance imaging in the BrainSCALE cohort, which consisted of twins and their older siblings from 112 families measured longitudinally at ages 10, 13, and 18 years for the twins. Genetic covariance modeling based on the classical twin design, extended to also include siblings of twins, showed that genes influence externalizing behavior and changes therein (
up to 88%). More pronounced externalizing behavior was associated with higher FA (observed correlation
up to +0.20) and lower MD (
up to -0.20), with sizeable genetic correlations (FA
up to +0.42; MD
up to -0.33). The cortical gray matter (CGM;
up to -0.20) and cerebral white matter (CWM;
up to +0.20) volume were phenotypically but not genetically associated with externalizing behavior. These results suggest a potential mediating role for global brain structures in the display of externalizing behavior during adolescence that are both partially explained by the influence of the same genetic factor.
Adolescence represents an important period during which considerable changes in the brain take place, including increases in integrity of white matter bundles, and increasing efficiency of the ...structural brain network. A more efficient structural brain network has been associated with higher intelligence. Whether development of structural network efficiency is related to intelligence, and if so to which extent genetic and environmental influences are implicated in their association, is not known. In a longitudinal study, we mapped FA-weighted efficiency of the structural brain network in 310 twins and their older siblings at an average age of 10, 13, and 18 years. Age-trajectories of global and local FA-weighted efficiency were related to intelligence. Contributions of genes and environment were estimated using structural equation modeling. Efficiency of brain networks changed in a non-linear fashion from childhood to early adulthood, increasing between 10 and 13 years, and leveling off between 13 and 18 years. Adolescents with higher intelligence had higher global and local network efficiency. The dependency of FA-weighted global efficiency on IQ increased during adolescence (r
=0.007 at age 10; 0.23 at age 18). Global efficiency was significantly heritable during adolescence (47% at age 18). The genetic correlation between intelligence and global and local efficiency increased with age; genes explained up to 87% of the observed correlation at age 18. In conclusion, the brain's structural network differentiates depending on IQ during adolescence, and is under increasing influence of genes that are also associated with intelligence as it develops from late childhood to adulthood.
Several large imaging-genetics consortia aim to identify genetic variants influencing subcortical brain volumes. We investigated the extent to which genetic variation accounts for the variation in ...subcortical volumes, including thalamus, amygdala, putamen, caudate nucleus, globus pallidus and nucleus accumbens and obtained the stability of these brain volumes over a five-year period. The heritability estimates for all subcortical regions were high, with the highest heritability estimates observed for the thalamus (.80) and caudate nucleus (.88) and lowest for the left nucleus accumbens (.44). Five-year stability was substantial and higher for larger e.g., thalamus (.88), putamen (.86), caudate nucleus (.87) compared to smaller nucleus accumbens (.45) subcortical structures. These results provide additional evidence that subcortical structures are promising starting points for identifying genetic variants that influence brain structure.
•The volumes of subcortical brain structures are highly heritable.•Automatically segmented subcortical volumes are stable over a 5-year time period.•Mean differences are observed between men and women.•However, no sex by genotype interactions for subcortical volumes were found.
Summary Our brain operates by the way of interconnected networks. Connections between brain regions have been extensively studied at a functional and structural level, and impaired connectivity has ...been postulated as an important pathophysiological mechanism underlying several neuropsychiatric disorders. Yet the neurobiological mechanisms contributing to the development of functional and structural brain connections remain to be poorly understood. Interestingly, animal research has convincingly shown that sex steroid hormones (estrogens, progesterone and testosterone) are critically involved in myelination, forming the basis of white matter connectivity in the central nervous system. To get insights, we reviewed studies into the relation between sex steroid hormones, white matter and functional connectivity in the human brain, measured with neuroimaging. Results suggest that sex hormones organize structural connections, and activate the brain areas they connect. These processes could underlie a better integration of structural and functional communication between brain regions with age. Specifically, ovarian hormones (estradiol and progesterone) may enhance both cortico-cortical and subcortico-cortical functional connectivity, whereas androgens (testosterone) may decrease subcortico-cortical functional connectivity but increase functional connectivity between subcortical brain areas. Therefore, when examining healthy brain development and aging or when investigating possible biological mechanisms of ‘brain connectivity’ diseases, the contribution of sex steroids should not be ignored.
As executive functioning (EF) is especially sensitive to age-related cognitive decline, EF was evaluated by using a multi-method assessment. Fifty males (60–85 years) with a late adulthood autism ...spectrum condition (ASC) diagnosis and 51 non-ASC males (60–83 years) were compared on cognitive tests across EF domains (cognitive flexibility, planning, processing speed, and working memory) and a self- and proxy report of the Behavior Rating Inventory of Executive Function-Adult Version. While no objective performance differences emerged, autistic males and their proxies did report more EF challenges than non-ASC males on the subjective measure. In order to know how to support the older autistic men who received their ASC diagnosis in late adulthood with their daily life EF challenges, it is important to understand what underlies these subjective EF problems.
Contemporary preclinical models suggest that abnormal functioning of a brain network consisting of the hippocampus, midbrain and striatum plays a critical role in the pathophysiology of ...schizophrenia. Previous neuroimaging studies examined individual aspects of this model in schizophrenia patients and individuals at clinical high risk for psychosis. However, this exact preclinical brain network has not been translated to human neuroimaging studies with schizophrenia patients and therefore it is currently unknown how functioning of this network is altered in patients. Here we investigated resting state functional connectivity in the hippocampus-midbrain-striatum network of schizophrenia patients, using functional Magnetic Resonance Imaging. Based on preclinical models, a network of functionally validated brain regions comprising the anterior subiculum (SUB), limbic striatum (LS), ventral tegmental area (VTA) and associative striatum (AS) was examined in 47 schizophrenia patients and 51 healthy controls. Schizophrenia patients demonstrated significantly lower functional connectivity in this hippocampus-midbrain-striatum network compared with healthy controls (p = 0.036). Particular reductions in connectivity were found between the SUB and LS (0.002 ± 0.315 and 0.116 ± 0.224, p = 0.040) and between the VTA and AS (0.230 ± 0.268 and 0.356 ± 0.285, p = 0.026). In patients, functional connectivity was not significantly associated with positive, negative or general symptom scores. Reduced connectivity is consistent with the concept of functional brain dysconnectivity as a key feature of the disorder. Our results support the notion that functioning of the hippocampus-midbrain-striatum network is significantly altered in the pathophysiology of schizophrenia.
Schizophrenia is accompanied by a loss of integrity of white matter connections that compose the structural brain network, which is believed to diminish the efficiency of information transfer among ...brain regions. However, it is unclear to what extent these abnormalities are influenced by the genetic liability for developing the disease.
To determine whether white matter integrity is associated with the genetic liability for developing schizophrenia.
In 70 individual twins discordant for schizophrenia and 130 matched individual healthy control twins, structural equation modeling was applied to quantify unique contributions of genetic and environmental factors on brain connectivity and disease liability. The data for this study were collected from October 1, 2008, to September 30, 2013. The data analysis was performed between November 1, 2013, and March 30, 2015.
Structural connectivity and network efficiency were assessed through diffusion-weighted imaging, measuring fractional anisotropy (FA) and streamlines.
The sample included 30 monozygotic twins matched to 72 control participants and 40 dizygotic twins matched to 58 control participants. Lower global FA was significantly correlated with increased schizophrenia liability (phenotypic correlation, -0.25; 95% CI, -0.38 to -0.10; P = .001), with 83.4% explained by common genes. In total, 8.1% of genetic variation in global FA was shared with genetic variance in schizophrenia liability. Local reductions in network connectivity (as defined by FA-weighted local efficiency) of frontal, striatal, and thalamic regions encompassed 85.7% of genetically affected areas. Multivariate genetic modeling revealed that global FA contributed independently of other genetic markers, such as white matter volume and cortical thickness, to schizophrenia liability.
Global reductions in white matter integrity in schizophrenia are largely explained by the genetic risk of developing the disease. Network analysis revealed that genetic liability for schizophrenia is primarily associated with reductions in connectivity of frontal and subcortical regions, indicating a loss of integrity along the white matter fibers in these regions. The reported reductions in white matter integrity likely represent a separate and novel genetic vulnerability marker for schizophrenia.
Abstract The human brain is a complex network of interconnected brain regions. In adulthood, the brain's network was recently found to be under genetic influence. However, the extent to which genes ...influence the functional brain network early in development is not yet known. We report on the heritability of functional brain efficiency during early brain development. Using a twin design, young children underwent resting-state functional magnetic resonance imaging brain scans ( N =86 from 21 MZ and 22 DZ twin-pairs, age=12 years). Functional connectivity, defined as the temporal dependency of neuronal activation patterns of anatomically separated brain regions, was explored using graph theory and its heritability was examined using structural equation modeling. Our findings suggest that ‘global efficiency of communication’ among brain regions is under genetic control ( h2 lambda =42%), irrespectively of the total number of brain connections (connectivity density). In addition, no influence of genes or common environment to local clustering ( gamma ) was found, suggesting a less pronounced effect of genes on local information segregation. Thus our findings suggest that a set of genes is shaping the underlying architecture of functional brain communication during development.
Recent volumetric magnetic resonance imaging (MRI) studies have suggested brain volume changes in schizophrenia to be progressive in nature. Whether this is a global process or some brain areas are ...more affected than others is not known. In a 5-year longitudinal study, MRI whole brain scans were obtained from 96 patients with schizophrenia and 113 matched healthy comparison subjects. Changes over time in focal gray and white matter were measured with voxel-based morphometry throughout the brain. Over the 5-year interval, excessive decreases in gray matter density were found in patients in the left superior frontal area (Brodmann areas 9/10), left superior temporal gyrus (Brodmann area 42), right caudate nucleus, and right thalamus as compared to healthy individuals. Excessive gray matter density decrease in the superior frontal gray matter was related to increased number of hospitalizations, whereas a higher cumulative dose of clozapine and olanzapine during the scan interval was related to lesser decreases in this area. In conclusion, gray matter density loss occurs across the course of the illness in schizophrenia, predominantly in left frontal and temporal cortices. Moreover, the progression in left frontal density loss appears to be related to an increased number of psychotic episodes, with atypical antipsychotic medication attenuating these changes.
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