Genetic contributions to human brain morphology and intelligence

Variation in gray matter (GM) and white matter (WM) volume of the adult human brain is primarily genetically determined. Moreover, total brain volume is positively correlated with general intelligence, and both share a common genetic origin. However, although genetic effects on morphology of specific GM areas in the brain have been studied, the heritability of focal WM is unknown. Similarly, it is unresolved whether there is a common genetic origin of focal GM and WM structures with intelligence. We explored the genetic influence on focal GM and WM densities in magnetic resonance brain images of 54 monozygotic and 58 dizygotic twin pairs and 34 of their siblings. For genetic analyses, we used structural equation modeling and voxel-based morphometry. To explore the common genetic origin of focal GM and WM areas with intelligence, we obtained cross-trait/cross-twin correlations in which the focal GM and WM densities of each twin are correlated with the psychometric intelligence quotient of his/her cotwin. Genes influenced individual differences in left and right superior occipitofrontal fascicle (heritability up to 0.79 and 0.77), corpus callosum (0.82, 0.80), optic radiation (0.69, 0.79), corticospinal tract (0.78, 0.79), medial frontal cortex (0.78, 0.83), superior frontal cortex (0.76, 0.80), superior temporal cortex (0.80, 0.77), left occipital cortex (0.85), left postcentral cortex (0.83), left posterior cingulate cortex (0.83), right parahippocampal cortex (0.69), and amygdala (0.80, 0.55). Intelligence shared a common genetic origin with superior occipitofrontal, callosal, and left optical radiation WM and frontal, occipital, and parahippocampal GM (phenotypic correlations up to 0.35). These findings point to a neural network that shares a common genetic origin with human intelligence

Tract-based analysis in schizophrenia: measuring structure and function along white matter tracts

Schizophrenia is a severe psychiatric disorder that is characterized by hallucinations, delusions, thought disorder and impairments in cognitive functions. From about the time of its definition it was suggested that schizophrenia is a connectivity disease. Although the etiology of schizophrenia is still not known, recently evidence is accumulating that the integrity of white matter fibers is compromised in schizophrenia and that impaired functioning of white matter is part of its pathophysiology. Modern magnetic resonance imaging (MRI) methods such as diffusion tensor imaging (DTI) in combination with fiber-tracking algorithms allow us to reconstruct these fiber bundles and to study several aspects of these bundles in detail. Structure and function of white matter fiber bundles were studied in both healthy participants and in schizophrenia patients using a novel technique named tract-based analysis. With this type of analysis groups are compared at the level of complete fiber bundles. The average fractional anisotropy (FA) and magnetization transfer ratio (MTR) were measured along the genu of the corpus callosum and the left and right uncinate fasciculus (UF) in 40 schizophrenia patients and 40 healthy participants. These fiber bundles connect to the frontotemporal gray matter regions and are expected to be involved in schizophrenia. A significant negative correlation was found between age and mean FA in the left UF in patients but not in healthy participants which may be more prominent in patients with longer illness duration. The main finding was a significant increase in MTR of 1% in the right UF in patients compared to healthy participants. This increase in MTR in the right UF could reflect a compensatory role for myelin in these fibers or possibly represent aberrant frontotemporal connectivity. Moreover, DTI was combined with resting-state fMRI to determine whether there is a relation between the level of resting state of the precuneus and the posterior cingulate cortex, gray matter regions part of the default-mode network, and the “strength” (reflected by FA) of the connecting fiber bundle. DTI and resting-state fMRI scans of 45 healthy participants were acquired. A significant positive correlation was found between the mean FA value and the level of resting-state suggesting a direct relationship between structural and functional connectivity in the default-mode network. Importantly, a new method -which we dubbed functional diffusion tensor imaging (fDTI - was introduced which is based on tract-based analysis and allows to study functional aspects of fiber bundles. In a first study 8 subjects were scanned during repetitive visual and tactile stimulation. Fiber activation was found as expected in the contralateral thalamocortical tract and optic radiations for tactile and visual stimuli, respectively. These findings were successfully replicated in a second study a using the same stimuli but in a different group of 12 subjects, with a different scanner and an improved fDTI acquisition. The successful application of tract-based analysis to study various aspects of white matter suggests a prominent role for tract-based analysis in studying diseases for which white matter may be implicated, in particular schizophrenia

Do we measure gray matter activation with functional diffusion tensor imaging?

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Reduced fronto–striatal white matter integrity in schizophrenia patients and unaffected siblings: a DTI study

Background: Schizophrenia is characterized by impairments in the fronto–striatal network. Underlying these impairments may be disruptions in anatomical pathways connecting frontal and striatal regions. However, the specifics of these disruptions remain unclear and whether these impairments are related to the genetic vulnerability of schizophrenia is not known. Methods: Here, we investigated fronto–striatal tract connections in 24 schizophrenia patients, 30 unaffected siblings, and 58 healthy controls using diffusion tensor imaging. Mean fractional anisotropy (FA) was calculated for tracts connecting the striatum with frontal cortex regions including the dorsolateral prefrontal cortex (DLPFC), medial orbital frontal cortex, and inferior frontal gyrus. Specifically, the striatum was divided into three subregions (caudate nucleus, putamen, and nucleus accumbens) and mean FA was computed for tracts originating from these striatal subregions. Results: We found no differences between patients, siblings, and controls in mean FA when taking the whole striatum as a seed region. However, subregion analyses showed reduced FA in the tract connecting the left nucleus accumbens and left DLPFC in both patients (P=0.0003) and siblings (P=0.0008) compared with controls. Conclusions: The result of reduced FA in the tract connecting the left nucleus accumbens and left DLPFC indicates a possible reduction of white matter integrity, commonly associated with schizophrenia. As both patients and unaffected siblings show reduced FA, this may represent a vulnerability factor for schizophrenia

A stereotactic method for image-guided transcranial magnetic stimulation validated with fMRI and motor-evoked potentials

Item does not contain fulltextTranscranial Magnetic Stimulation (TMS) delivers short magnetic pulses that penetrate the skull unattenuated, disrupting neural processing in a noninvasive, reversible way. To disrupt specific neural processes, coil placement over the proper site is critical. Therefore, a neural navigator (NeNa) was developed. NeNa is a frameless stereotactic device using structural and functional magnetic resonance imaging (fMRI) data to guide TMS coil placement. To coregister the participant's head to his MRI, 3D cursors are moved to anatomical landmarks on a skin rendering of the participants MRI on a screen, and measured at the head with a position measurement device. A method is proposed to calculate a rigid body transformation that can coregister both sets of coordinates under realistic noise conditions. After coregistration, NeNa visualizes in real time where the device is located with respect to the head, brain structures, and activated areas, enabling precise placement of the TMS coil over a predefined target region. NeNa was validated by stimulating 5 x 5 positions around the 'motor hotspot' (thumb movement area), which was marked on the scalp guided by individual fMRI data, while recording motor-evoked potentials (MEPs) from the abductor pollicis brevis (APB). The distance between the center of gravity (CoG) of MEP responses and the location marked on the scalp overlying maximum fMRI activation was on average less then 5 mm. The present results demonstrate that NeNa is a reliable method for image-guided TMS coil placement

Development of the Brain’s Structural Network Efficiency in Early Adolescence: A Longitudinal DTI Twin Study

The brain is a network and our intelligence depends in part on the efficiency of this network. The network of adolescents differs from that of adults suggesting developmental changes. However, whether the network changes over time at the individual level and, if so, how this relates to intelligence, is unresolved in adolescence. In addition, the influence of genetic factors in the developing network is not known. Therefore, in a longitudinal study of 162 healthy adolescent twins and their siblings (mean age at baseline 9.9 [range 9.0-15.0] years), we mapped local and global structural network efficiency of cerebral fiber pathways (weighted with mean FA and streamline count) and assessed intelligence over a three-year interval. We find that the efficiency of the brain's structural network is highly heritable (locally up to 74%). FA-based local and global efficiency increases during early adolescence. Streamline count based local efficiency both increases and decreases, and global efficiency reorganizes to a net decrease. Local FA-based efficiency was correlated to IQ. Moreover, increases in FA-based network efficiency (global and local) and decreases in streamline count based local efficiency are related to increases in intellectual functioning. Individual changes in intelligence and local FA-based efficiency appear to go hand in hand in frontal and temporal areas. More widespread local decreases in streamline count based efficiency (frontal cingulate and occipital) are correlated with increases in intelligence. We conclude that the teenage brain is a network in progress in which individual differences in maturation relate to level of intellectual functioning. Hum Brain Mapp 36:4938-4953, 2015

Genes contributing to subcortical volumes and intellectual ability implicate the thalamus

It has been shown that brain volume and general intellectual ability are to a significant extent influenced by the same genetic factors. Several cortical regions of the brain also show a genetic correlation with intellectual ability, demonstrating that intellectual functioning is probably represented in a heritable distributed network of cortical regions throughout the brain. This study is the first to investigate a genetic association between subcortical volumes and intellectual ability, taking into account the thalamus, caudate nucleus, putamen, globus pallidus, hippocampus, amygdala, and nucleus accumbens using an extended twin design. Genetic modeling was performed on a healthy adult twin sample consisting of 106 twin pairs and 30 of their siblings, IQ data was obtained from 132 subjects. Our results demonstrate that of all subcortical volumes measured, only thalamus volume is significantly correlated with intellectual functioning. Importantly, the association found between thalamus volume and intellectual ability is significantly influenced by a common genetic factor. This genetic factor is also implicated in cerebral brain volume. The thalamus, with its widespread cortical connections, may thus play a key role in human intelligence. © 2013 Wiley Periodicals, Inc