Childhood trauma is associated with reduced frontal gray matter volume: a large transdiagnostic structural MRI study.

BACKGROUND: Childhood trauma increases risk for psychopathology and cognitive impairment. Prior research mainly focused on the hippocampus and amygdala in single diagnostic categories. However, other brain regions may be impacted by trauma as well, and effects may be independent of diagnosis. This cross-sectional study investigated cortical and subcortical gray matter volume in relation to childhood trauma severity. METHODS: We included 554 participants: 250 bipolar-I patients, 84 schizophrenia-spectrum patients and 220 healthy individuals without a psychiatric history. Participants filled in the Childhood Trauma Questionnaire. Anatomical T1 MRI scans were acquired at 3T, regional brain morphology was assessed using Freesurfer. RESULTS: In the total sample, trauma-related gray matter reductions were found in the frontal lobe (ß = -0.049, p = 0.008; q = 0.048), this effect was driven by the right medial orbitofrontal, paracentral, superior frontal regions and the left precentral region. No trauma-related volume reductions were observed in any other (sub)cortical lobes nor the hippocampus or amygdala, trauma-by-group (i.e. both patient groups and healthy subjects) interaction effects were absent. A categorical approach confirmed a pattern of more pronounced frontal gray matter reductions in individuals reporting multiple forms of trauma and across quartiles of cumulative trauma scores. Similar dose-response patterns were revealed within the bipolar and healthy subgroups, but did not reach significance in schizophrenia-spectrum patients. CONCLUSIONS: Findings show that childhood trauma is linked to frontal gray matter reductions, independent of psychiatric morbidity. Our results indicate that childhood trauma importantly contributes to the neurobiological changes commonly observed across psychiatric disorders. Frontal volume alterations may underpin affective and cognitive disturbances observed in trauma-exposed individuals.

Volume increase in the dentate gyrus after electroconvulsive therapy in depressed patients as measured with 7T.

Electroconvulsive therapy (ECT) is the most effective treatment for depression, yet its working mechanism remains unclear. In the animal analog of ECT, neurogenesis in the dentate gyrus (DG) of the hippocampus is observed. In humans, volume increase of the hippocampus has been reported, but accurately measuring the volume of subfields is limited with common MRI protocols. If the volume increase of the hippocampus in humans is attributable to neurogenesis, it is expected to be exclusively present in the DG, whereas other processes (angiogenesis, synaptogenesis) also affect other subfields. Therefore, we acquired an optimized MRI scan at 7-tesla field strength allowing sensitive investigation of hippocampal subfields. A further increase in sensitivity of the within-subjects measurements is gained by automatic placement of the field of view. Patients receive two MRI scans: at baseline and after ten bilateral ECT sessions (corresponding to a 5-week interval). Matched controls are also scanned twice, with a similar 5-week interval. A total of 31 participants (23 patients, 8 controls) completed the study. A large and significant increase in DG volume was observed after ECT (M = 75.44 mm3, std error = 9.65, p < 0.001), while other hippocampal subfields were unaffected. We note that possible type II errors may be present due to the small sample size. In controls no changes in volume were found. Furthermore, an increase in DG volume was related to a decrease in depression scores, and baseline DG volume predicted clinical response. These findings suggest that the volume change of the DG is related to the antidepressant properties of ECT, and may reflect neurogenesis.

Neuroimaging auditory verbal hallucinations in schizophrenia patient and healthy populations.

BACKGROUND: Auditory verbal hallucinations (AVH) are a cardinal feature of schizophrenia, but they can also appear in otherwise healthy individuals. Imaging studies implicate language networks in the generation of AVH; however, it remains unclear if alterations reflect biologic substrates of AVH, irrespective of diagnostic status, age, or illness-related factors. We applied multimodal imaging to identify AVH-specific pathology, evidenced by overlapping gray or white matter deficits between schizophrenia patients and healthy voice-hearers. METHODS: Diffusion-weighted and T1-weighted magnetic resonance images were acquired in 35 schizophrenia patients with AVH (SCZ-AVH), 32 healthy voice-hearers (H-AVH), and 40 age- and sex-matched controls without AVH. White matter fractional anisotropy (FA) and gray matter thickness (GMT) were computed for each region comprising ICBM-DTI and Desikan-Killiany atlases, respectively. Regions were tested for significant alterations affecting both SCZ-AVH and H-AVH groups, relative to controls. RESULTS: Compared with controls, the SCZ-AVH showed widespread FA and GMT reductions; but no significant differences emerged between H-AVH and control groups. While no overlapping pathology appeared in the overall study groups, younger (<40 years) H-AVH and SCZ-AVH subjects displayed overlapping FA deficits across four regions (p < 0.05): the genu and splenium of the corpus callosum, as well as the anterior limbs of the internal capsule. Analyzing these regions with free-water imaging ascribed overlapping FA abnormalities to tissue-specific anisotropy changes. CONCLUSIONS: We identified white matter pathology associated with the presence of AVH, independent of diagnostic status. However, commonalities were constrained to younger and more homogenous groups, after reducing pathologic variance associated with advancing age and chronicity effects.

Widespread higher fractional anisotropy associates to better cognitive functions in individuals at ultra-high risk for psychosis.

In schizophrenia patients, cognitive functions appear linked to widespread alterations in cerebral white matter microstructure. Here we examine patterns of associations between regional white matter and cognitive functions in individuals at ultra-high risk for psychosis. One hundred and sixteen individuals at ultra-high risk for psychosis and 49 matched healthy controls underwent 3 T magnetic resonance diffusion-weighted imaging and cognitive assessments. Group differences on fractional anisotropy were tested using tract-based spatial statistics. Group differences in cognitive functions, voxel-wise as well as regional fractional anisotropy were tested using univariate general linear modeling. Multivariate partial least squares correlation analyses tested for associations between patterns of regional fractional anisotropy and cognitive functions. Univariate analyses revealed significant impairments on cognitive functions and lower fractional anisotropy in superior longitudinal fasciculus and cingulate gyrus in individuals at ultra-high risk for psychosis. Partial least squares correlation analysis revealed different associations between patterns of regional fractional anisotropy and cognitive functions in individuals at ultra-high risk for psychosis compared to healthy controls. Widespread higher fractional anisotropy was associated with better cognitive functioning for individuals at ultra-high risk for psychosis, but not for the healthy controls. Furthermore, patterns of cognitive functions were associated with an interaction-effect on regional fractional anisotropy in fornix, medial lemniscus, uncinate fasciculus, and superior cerebellar peduncle. Aberrant associations between patterns of cognitive functions to white matter may be explained by dysmyelination.

Cortical structures and their clinical correlates in antipsychotic-naïve schizophrenia patients before and after 6 weeks of dopamine D2/3 receptor antagonist treatment.

BACKGROUND: Schizophrenia has been associated with changes in both cortical thickness and surface area, but antipsychotic exposure, illness progression and substance use may confound observations. In antipsychotic-naïve schizophrenia patients, we investigated cortical thickness and surface area as well as mean curvature before and after monotherapy with amisulpride, a relatively selective dopamine D2/3 receptor antagonist. METHODS: Fifty-six patients and 59 matched healthy controls (HCs) underwent T1-weighted 3T magnetic resonance imaging. Forty-one patients and 51 HCs were re-scanned. FreeSurfer-processed baseline, follow-up values and symmetrized percentage changes (SPC) in cortical structures were analysed using univariate analysis of variance. Clinical measures comprised psychopathology ratings, assessment of functioning and tests of premorbid and current intelligence. We applied false discovery rate correction to account for multiple comparisons. RESULTS: At baseline, groups did not differ in cortical thickness or surface area; however, curvature in the left hemisphere was higher in patients (p = 0.015). In both patients and HCs, higher curvature was associated with lower premorbid (p = 0.009) and current intelligence (p 0.43). Cortical thickness SPC was negatively associated with symptom improvement (p = 0.002). CONCLUSIONS: Schizophrenia appears associated with subtle, yet clinically relevant aberrations in cortical structures. Mean curvature holds promise as a sensitive supplement to cortical thickness and surface area to detect complex structural brain abnormalities.

Minimum spanning tree analysis of the human connectome.

One of the challenges of brain network analysis is to directly compare network organization between subjects, irrespective of the number or strength of connections. In this study, we used minimum spanning tree (MST; a unique, acyclic subnetwork with a fixed number of connections) analysis to characterize the human brain network to create an empirical reference network. Such a reference network could be used as a null model of connections that form the backbone structure of the human brain. We analyzed the MST in three diffusion-weighted imaging datasets of healthy adults. The MST of the group mean connectivity matrix was used as the empirical null-model. The MST of individual subjects matched this reference MST for a mean 58%-88% of connections, depending on the analysis pipeline. Hub nodes in the MST matched with previously reported locations of hub regions, including the so-called rich club nodes (a subset of high-degree, highly interconnected nodes). Although most brain network studies have focused primarily on cortical connections, cortical-subcortical connections were consistently present in the MST across subjects. Brain network efficiency was higher when these connections were included in the analysis, suggesting that these tracts may be utilized as the major neural communication routes. Finally, we confirmed that MST characteristics index the effects of brain aging. We conclude that the MST provides an elegant and straightforward approach to analyze structural brain networks, and to test network topological features of individual subjects in comparison to empirical null models.

White matter abnormalities in 22q11.2 deletion syndrome patients showing cognitive decline.

BACKGROUND: Decline in cognitive functioning precedes the first psychotic episode in the course of schizophrenia and is considered a hallmark symptom of the disorder. Given the low incidence of schizophrenia, it remains a challenge to investigate whether cognitive decline coincides with disease-related changes in brain structure, such as white matter abnormalities. The 22q11.2 deletion syndrome (22q11DS) is an appealing model in this context, as 25% of patients develop psychosis. Furthermore, we recently showed that cognitive decline also precedes the onset of psychosis in individuals with 22q11DS. Here, we investigate whether the early cognitive decline in patients with 22q11DS is associated with alterations in white matter microstructure. METHODS: We compared the fractional anisotropy (FA) of white matter in 22q11DS patients with cognitive decline [n = 16; -18.34 (15.8) VIQ percentile points over 6.80 (2.39) years] to 22q11DS patients without cognitive decline [n = 18; 17.71 (20.17) VIQ percentile points over 5.27 (2.03) years] by applying an atlas-based approach to diffusion-weighted imaging data. RESULTS: FA was significantly increased (p < 0.05, FDR) in 22q11DS patients with a cognitive decline in the bilateral superior longitudinal fasciculus, the bilateral cingulum bundle, all subcomponents of the left internal capsule and the left superior frontal-occipital fasciculus as compared with 22q11DS patients without cognitive decline. CONCLUSIONS: Within 22q11DS, the early cognitive decline is associated with microstructural differences in white matter. At the mean age of 17.8 years, these changes are reflected in increased FA in several tracts. We hypothesize that similar brain alterations associated with cognitive decline take place early in the trajectory of schizophrenia.

Frontostriatal White Matter Integrity Predicts Development of Delay of Gratification: A Longitudinal Study.

The ability to delay gratification increases considerably across development. Here, we test the hypothesis that this impulse control capacity is driven by increased maturation of frontostriatal circuitry using a fiber-tracking approach combined with longitudinal imaging. In total, 192 healthy volunteers between 8 and 26 years underwent diffusion tensor imaging scanning and completed a delay-discounting task twice, separated by a 2-year interval. We investigated dynamic associations between frontostriatal white matter (WM) integrity and delay of gratification skills. Moreover, we examined the predictive value of frontostriatal WM integrity for future delay of gratification skills. Results showed that delay discounting increases with age in a quadratic fashion, with greatest patience during late adolescence. Data also indicated nonlinear development of frontostriatal WM, with relative fast development during childhood and early adulthood and--on average--little change during mid-adolescence. Furthermore, the positive association between age and delay discounting was further increased in individuals with higher WM integrity of the frontostriatal tracts. Predictive analysis showed that frontostriatal WM development explained unique variance in current and future delay of gratification skills. This study adds to a descriptive relation between WM integrity and delay of gratification by showing that maturation of frontostriatal connectivity predicts changes in delay of gratification skills. These findings have implications for studies examining deviances in impulse control by showing that the developmental path between striatum and prefrontal cortex may be an important predictor for when development goes astray. SIGNIFICANCE STATEMENT: During the transition from childhood to adulthood, individuals generally show increased patience and become better in delaying gratification. The exact neural correlates of delay of gratification, however, remain poorly understood. By measuring both frontostriatal white matter (WM) integrity and delay of gratification skills at two time points, we were able to provide links for our understanding of the neural mechanisms underlying this type of impulse regulation capacity. We demonstrate that the ability to delay gratification improves between childhood and young adulthood and this improvement is predicted by the integrity of frontostriatal WM connections. This study adds to a descriptive relation between WM quality and delay of gratification by showing that maturation of frontostriatal connectivity predicts improvements in delay of gratification skills.

Topology of genetic associations between regional gray matter volume and intellectual ability: Evidence for a high capacity network.

Intelligence is associated with a network of distributed gray matter areas including the frontal and parietal higher association cortices and primary processing areas of the temporal and occipital lobes. Efficient information transfer between gray matter regions implicated in intelligence is thought to be critical for this trait to emerge. Genetic factors implicated in intelligence and gray matter may promote a high capacity for information transfer. Whether these genetic factors act globally or on local gray matter areas separately is not known. Brain maps of phenotypic and genetic associations between gray matter volume and intelligence were made using structural equation modeling of 3T MRI T1-weighted scans acquired in 167 adult twins of the newly acquired U-TWIN cohort. Subsequently, structural connectivity analyses (DTI) were performed to test the hypothesis that gray matter regions associated with intellectual ability form a densely connected core. Gray matter regions associated with intellectual ability were situated in the right prefrontal, bilateral temporal, bilateral parietal, right occipital and subcortical regions. Regions implicated in intelligence had high structural connectivity density compared to 10,000 reference networks (p=0.031). The genetic association with intelligence was for 39% explained by a genetic source unique to these regions (independent of total brain volume), this source specifically implicated the right supramarginal gyrus. Using a twin design, we show that intelligence is genetically represented in a spatially distributed and densely connected network of gray matter regions providing a high capacity infrastructure. Although genes for intelligence have overlap with those for total brain volume, we present evidence that there are genes for intelligence that act specifically on the subset of brain areas that form an efficient brain network.

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.

Structural and functional aspects relating to cost and benefit of rich club organization in the human cerebral cortex.

Recent findings have demonstrated that a small set of highly connected brain regions may play a central role in enabling efficient communication between cortical regions, together forming a densely interconnected "rich club." However, the density and spatial layout of the rich club also suggest that it constitutes a costly feature of brain architecture. Here, combining anatomical T1, diffusion tensor imaging, magnetic transfer imaging, and functional MRI, several aspects of structural and functional connectivity of the brain's rich club were examined. Our findings suggest that rich club regions and rich club connections exhibit high levels of wiring volume, high levels of white matter organization, high levels of metabolic energy usage, long maturational trajectories, more variable regional time series, and more inter-regional functional couplings. Taken together, these structural and functional measures extend the notion that rich club organization represents a high-cost feature of brain architecture that puts a significant strain on brain resources. The high cost of the rich club may, however, be offset by significant functional benefits that the rich club confers to the brain network as a whole.

Multi-site study of additive genetic effects on fractional anisotropy of cerebral white matter: Comparing meta and megaanalytical approaches for data pooling.

Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9-85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large "mega-family". We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability.

Heritability of structural brain network topology: a DTI study of 156 twins.

Individual variation in structural brain network topology has been associated with heritable behavioral phenotypes such as intelligence and schizophrenia, making it a candidate endophenotype. However, little is known about the genetic influences on individual variation in structural brain network topology. Moreover, the extent to which structural brain network topology overlaps with heritability for integrity and volume of white matter remains unknown. In this study, structural network topology was examined using diffusion tensor imaging at 3T. Binary connections between 82 structurally defined brain regions per subject were traced, allowing for estimation of individual topological network properties. Heritability of normalized characteristic path length (λ), normalized clustering coefficient (γ), microstructural integrity (FA), and volume of the white matter were estimated using a twin design, including 156 adult twins from the newly acquired U-TWIN cohort. Both γ and λ were estimated to be under substantial genetic influence. The heritability of γ was estimated to be 68%, the heritability estimate for λ was estimated to be 57%. Genetic influences on network measures were found to be partly overlapping with volumetric and microstructural properties of white matter, but the largest component of genetic variance was unique to both network traits. Normalized clustering coefficient and normalized characteristic path length are substantially heritable, and influenced by independent genetic factors that are largely unique to network measures, but partly also implicated in white matter directionality and volume. Thus, network measures provide information about genetic influence on brain structure, independent of global white matter characteristics such as volume and microstructural directionality.

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.

Delay discounting and frontostriatal fiber tracts: a combined DTI and MTR study on impulsive choices in healthy young adults.

Delay discounting, a measure of impulsive choice, has been associated with decreased control of the prefrontal cortex over striatum responses. The anatomical connectivity between both brain regions in delaying gratification remains unknown. Here, we investigate whether the quality of frontostriatal (FS) white matter tracts can predict individual differences in delay-discounting behavior. We use tract-based diffusion tensor imaging and magnetization transfer imaging to measure the microstructural properties of FS fiber tracts in 40 healthy young adults (from 18 to 25 years). We additionally explored whether internal sex hormone levels affect the integrity of FS tracts, based on the hypothesis that sex hormones modulate axonal density within prefrontal dopaminergic circuits. We calculated fractional anisotropy (FA), mean diffusivity (MD), longitudinal diffusivity, radial diffusivity (RD), and magnetization transfer ratio (MTR), a putative measure of myelination, for the FS tract. Results showed that lower integrity within the FS tract (higher MD and RD and lower FA), predicts faster discounting in both sexes. MTR was unrelated to delay-discounting performance. In addition, testosterone levels in males were associated with a lower integrity (higher RD) within the FS tract. Our study provides support for the hypothesis that enhanced structural integrity of white matter fiber bundles between prefrontal and striatal brain areas is associated with better impulse control.

Multi-site genetic analysis of diffusion images and voxelwise heritability analysis: a pilot project of the ENIGMA-DTI working group.

The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium was set up to analyze brain measures and genotypes from multiple sites across the world to improve the power to detect genetic variants that influence the brain. Diffusion tensor imaging (DTI) yields quantitative measures sensitive to brain development and degeneration, and some common genetic variants may be associated with white matter integrity or connectivity. DTI measures, such as the fractional anisotropy (FA) of water diffusion, may be useful for identifying genetic variants that influence brain microstructure. However, genome-wide association studies (GWAS) require large populations to obtain sufficient power to detect and replicate significant effects, motivating a multi-site consortium effort. As part of an ENIGMA-DTI working group, we analyzed high-resolution FA images from multiple imaging sites across North America, Australia, and Europe, to address the challenge of harmonizing imaging data collected at multiple sites. Four hundred images of healthy adults aged 18-85 from four sites were used to create a template and corresponding skeletonized FA image as a common reference space. Using twin and pedigree samples of different ethnicities, we used our common template to evaluate the heritability of tract-derived FA measures. We show that our template is reliable for integrating multiple datasets by combining results through meta-analysis and unifying the data through exploratory mega-analyses. Our results may help prioritize regions of the FA map that are consistently influenced by additive genetic factors for future genetic discovery studies. Protocols and templates are publicly available at (http://enigma.loni.ucla.edu/ongoing/dti-working-group/).

Altered white matter connectivity in never-medicated patients with schizophrenia.

Numerous diffusion tensor imaging (DTI) studies have implicated white matter brain tissue abnormalities in schizophrenia. However, the vast majority of these studies included patient populations that use antipsychotic medication. Previous research showed that medication intake can affect brain morphology and the question therefore arises to what extent the reported white matter aberrations can be attributed to the disease rather than to the use of medication. In this study we included 16 medication-naïve patients with schizophrenia and compared them to 23 healthy controls to exclude antipsychotic medication use as a confounding factor. For each subject DTI scans and magnetization transfer imaging (MTI) scans were acquired. A new tract-based analysis was used that combines fractional anisoptropy (FA), mean diffusivity (MD) and magnetization transfer ratio (MTR) to examine group differences in 12 major white matter fiber bundles. Significant group differences in combined FA, MD, MTR values were found for the right uncinate fasciculus and the left arcuate fasciculus. Additional analysis revealed that the largest part of both tracts showed an increase in MTR in combination with an increase in MD for patients with schizophrenia. We interpret these group-related differences as disease-related axonal or glial aberrations that cannot be attributed to antipsychotic medication use.