Search

Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Left-right asymmetry of the human brain is one of its cardinal features, and also a complex, multivariate trait. Decades of research have suggested that brain asymmetry may be altered in psychiatric disorders. However, findings have been inconsistent and often based on small sample sizes. There are also open questions surrounding which structures are asymmetrical on average in the healthy population, and how variability in brain asymmetry relates to basic biological variables such as age and sex. Over the last 4 years, the ENIGMA-Laterality Working Group has published six studies of gray matter morphological asymmetry based on total sample sizes from roughly 3,500 to 17,000 individuals, which were between one and two orders of magnitude larger than those published in previous decades. A population-level mapping of average asymmetry was achieved, including an intriguing fronto-occipital gradient of cortical thickness asymmetry in healthy brains. ENIGMA's multi-dataset approach also supported an empirical illustration of reproducibility of hemispheric differences across datasets. Effect sizes were estimated for gray matter asymmetry based on large, international, samples in relation to age, sex, handedness, and brain volume, as well as for three psychiatric disorders: autism spectrum disorder was associated with subtly reduced asymmetry of cortical thickness at regions spread widely over the cortex; pediatric obsessive-compulsive disorder was associated with altered subcortical asymmetry; major depressive disorder was not significantly associated with changes of asymmetry. Ongoing studies are examining brain asymmetry in other disorders. Moreover, a groundwork has been laid for possibly identifying shared genetic contributions to brain asymmetry and disorders., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.)

MRI-derived brain measures offer a link between genes, the environment and behavior and have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of BD have been underpowered, leading to varied results and uncertainty regarding effects. The Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Bipolar Disorder Working Group was formed in 2012 to empower discoveries, generate consensus findings and inform future hypothesis-driven studies of BD. Through this effort, over 150 researchers from 20 countries and 55 institutions pool data and resources to produce the largest neuroimaging studies of BD ever conducted. The ENIGMA Bipolar Disorder Working Group applies standardized processing and analysis techniques to empower large-scale meta- and mega-analyses of multimodal brain MRI and improve the replicability of studies relating brain variation to clinical and genetic data. Initial BD Working Group studies reveal widespread patterns of lower cortical thickness, subcortical volume and disrupted white matter integrity associated with BD. Findings also include mapping brain alterations of common medications like lithium, symptom patterns and clinical risk profiles and have provided further insights into the pathophysiological mechanisms of BD. Here we discuss key findings from the BD working group, its ongoing projects and future directions for large-scale, collaborative studies of mental illness., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Although previous studies have highlighted associations of cannabis use with cognition and brain morphometry, critical questions remain with regard to the association between cannabis use and brain structural and functional connectivity. In a cross-sectional community sample of 205 African Americans (age 18-70) we tested for associations of cannabis use disorder (CUD, n = 57) with multi-domain cognitive measures and structural, diffusion, and resting state brain-imaging phenotypes. Post hoc model evidence was computed with Bayes factors (BF) and posterior probabilities of association (PPA) to account for multiple testing. General cognitive functioning, verbal intelligence, verbal memory, working memory, and motor speed were lower in the CUD group compared with non-users (p < .011; 1.9 < BF < 3,217). CUD was associated with altered functional connectivity in a network comprising the motor-hand region in the superior parietal gyri and the anterior insula (p < .04). These differences were not explained by alcohol, other drug use, or education. No associations with CUD were observed in cortical thickness, cortical surface area, subcortical or cerebellar volumes (0.12 < BF < 1.5), or graph-theoretical metrics of resting state connectivity (PPA < 0.01). In a large sample collected irrespective of cannabis used to minimize recruitment bias, we confirm the literature on poorer cognitive functioning in CUD, and an absence of volumetric brain differences between CUD and non-CUD. We did not find evidence for or against a disruption of structural connectivity, whereas we did find localized resting state functional dysconnectivity in CUD. There was sufficient proof, however, that organization of functional connectivity as determined via graph metrics does not differ between CUD and non-user group., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Importance: Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood., Objective: To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia., Design, Setting, and Participants: Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244., Main Outcomes and Measures: Interregional profiles of group difference in cortical thickness between cases and controls., Results: A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (except for OCD); collectively, gene-expression profiles of the 3 cell types explain between 25% and 54% of variance in interregional profiles of group differences in cortical thickness. Principal component analysis revealed a shared profile of difference in cortical thickness across the 6 disorders (48% variance explained); interregional profile of this principal component 1 was associated with that of the pyramidal-cell gene expression (explaining 56% of interregional variation). Coexpression analyses of these genes revealed 2 clusters: (1) a prenatal cluster enriched with genes involved in neurodevelopmental (axon guidance) processes and (2) a postnatal cluster enriched with genes involved in synaptic activity and plasticity-related processes. These clusters were enriched with genes associated with all 6 psychiatric disorders., Conclusions and Relevance: In this study, shared neurobiologic processes were associated with differences in cortical thickness across multiple psychiatric disorders. These processes implicate a common role of prenatal development and postnatal functioning of the cerebral cortex in these disorders.

Cortical folds help drive the parcellation of the human cortex into functionally specific regions. Variations in the length, depth, width, and surface area of these sulcal landmarks have been associated with disease, and may be genetically mediated. Before estimating the heritability of sulcal variation, the extent to which these metrics can be reliably extracted from in-vivo MRI must be established. Using four independent test-retest datasets, we found high reliability across the brain (intraclass correlation interquartile range: 0.65-0.85). Heritability estimates were derived for three family-based cohorts using variance components analysis and pooled (total N > 3000); the overall sulcal heritability pattern was correlated to that derived for a large population cohort (N > 9000) calculated using genomic complex trait analysis. Overall, sulcal width was the most heritable metric, and earlier forming sulci showed higher heritability. The inter-hemispheric genetic correlations were high, yet select sulci showed incomplete pleiotropy, suggesting hemisphere-specific genetic influences.

In recent years, replicability of neuroscientific findings, specifically those concerning correlates of morphological properties of gray matter (GM), have been subject of major scrutiny. Use of different processing pipelines and differences in their estimates of the macroscale GM may play an important role in this context. To address this issue, here, we investigated the cortical thickness estimates of three widely used pipelines. Based on analyses in two independent large-scale cohorts, we report high levels of within-pipeline reliability of the absolute cortical thickness-estimates and comparable spatial patterns of cortical thickness-estimates across all pipelines. Within each individual, absolute regional thickness differed between pipelines, indicating that in-vivo thickness measurements are only a proxy of actual thickness of the cortex, which shall only be compared within the same software package and thickness estimation technique. However, at group level, cortical thickness-estimates correlated strongly between pipelines, in most brain regions. The smallest between-pipeline correlations were observed in para-limbic areas and insula. These regions also demonstrated the highest interindividual variability and the lowest reliability of cortical thickness-estimates within each pipeline, suggesting that structural variations within these regions should be interpreted with caution., (© The Author(s) 2020. Published by Oxford University Press.)

Previous studies suggest that gyrification is associated with superior cognitive abilities in humans, but the strength of this relationship remains unclear. Here, in two samples of related individuals (total N = 2882), we calculated an index of local gyrification (LGI) at thousands of cortical surface points using structural brain images and an index of general cognitive ability (g) using performance on cognitive tests. Replicating previous studies, we found that phenotypic and genetic LGI-g correlations were positive and statistically significant in many cortical regions. However, all LGI-g correlations in both samples were extremely weak, regardless of whether they were significant or nonsignificant. For example, the median phenotypic LGI-g correlation was 0.05 in one sample and 0.10 in the other. These correlations were even weaker after adjusting for confounding neuroanatomical variables (intracranial volume and local cortical surface area). Furthermore, when all LGIs were considered together, at least 89% of the phenotypic variance of g remained unaccounted for. We conclude that the association between LGI and g is too weak to have profound implications for our understanding of the neurobiology of intelligence. This study highlights potential issues when focusing heavily on statistical significance rather than effect sizes in large-scale observational neuroimaging studies., (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.)

Importance: Recurrent microdeletions and duplications in the genomic region 15q11.2 between breakpoints 1 (BP1) and 2 (BP2) are associated with neurodevelopmental disorders. These structural variants are present in 0.5% to 1.0% of the population, making 15q11.2 BP1-BP2 the site of the most prevalent known pathogenic copy number variation (CNV). It is unknown to what extent this CNV influences brain structure and affects cognitive abilities., Objective: To determine the association of the 15q11.2 BP1-BP2 deletion and duplication CNVs with cortical and subcortical brain morphology and cognitive task performance., Design, Setting, and Participants: In this genetic association study, T1-weighted brain magnetic resonance imaging were combined with genetic data from the ENIGMA-CNV consortium and the UK Biobank, with a replication cohort from Iceland. In total, 203 deletion carriers, 45 247 noncarriers, and 306 duplication carriers were included. Data were collected from August 2015 to April 2019, and data were analyzed from September 2018 to September 2019., Main Outcomes and Measures: The associations of the CNV with global and regional measures of surface area and cortical thickness as well as subcortical volumes were investigated, correcting for age, age2, sex, scanner, and intracranial volume. Additionally, measures of cognitive ability were analyzed in the full UK Biobank cohort., Results: Of 45 756 included individuals, the mean (SD) age was 55.8 (18.3) years, and 23 754 (51.9%) were female. Compared with noncarriers, deletion carriers had a lower surface area (Cohen d = -0.41; SE, 0.08; P = 4.9 × 10-8), thicker cortex (Cohen d = 0.36; SE, 0.07; P = 1.3 × 10-7), and a smaller nucleus accumbens (Cohen d = -0.27; SE, 0.07; P = 7.3 × 10-5). There was also a significant negative dose response on cortical thickness (β = -0.24; SE, 0.05; P = 6.8 × 10-7). Regional cortical analyses showed a localization of the effects to the frontal, cingulate, and parietal lobes. Further, cognitive ability was lower for deletion carriers compared with noncarriers on 5 of 7 tasks., Conclusions and Relevance: These findings, from the largest CNV neuroimaging study to date, provide evidence that 15q11.2 BP1-BP2 structural variation is associated with brain morphology and cognition, with deletion carriers being particularly affected. The pattern of results fits with known molecular functions of genes in the 15q11.2 BP1-BP2 region and suggests involvement of these genes in neuronal plasticity. These neurobiological effects likely contribute to the association of this CNV with neurodevelopmental disorders.

Recent progress in deciphering mechanisms of human brain cortical folding leave unexplained whether spatially patterned genetic influences contribute to this folding. High-resolution in vivo brain MRI can be used to estimate genetic correlations (covariability due to shared genetic factors) in interregional cortical thickness, and biomechanical studies predict an influence of cortical thickness on folding patterns. However, progress has been hampered because shared genetic influences related to folding patterns likely operate at a scale that is much more local (<1 cm) than that addressed in prior imaging studies. Here, we develop methodological approaches to examine local genetic influences on cortical thickness and apply these methods to two large, independent samples. We find that such influences are markedly heterogeneous in strength, and in some cortical areas are notably stronger in specific orientations relative to gyri or sulci. The overall, phenotypic local correlation has a significant basis in shared genetic factors and is highly symmetric between left and right cortical hemispheres. Furthermore, the degree of local cortical folding relates systematically with the strength of local correlations, which tends to be higher in gyral crests and lower in sulcal fundi. The relationship between folding and local correlations is stronger in primary sensorimotor areas and weaker in association areas such as prefrontal cortex, consistent with reduced genetic constraints on the structural topology of association cortex. Collectively, our results suggest that patterned genetic influences on cortical thickness, measurable at the scale of in vivo MRI, may be a causal factor in the development of cortical folding., Competing Interests: The authors declare no competing interest., (Copyright © 2020 the Author(s). Published by PNAS.)

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Altered structural brain asymmetry in autism spectrum disorder (ASD) has been reported. However, findings have been inconsistent, likely due to limited sample sizes. Here we investigated 1,774 individuals with ASD and 1,809 controls, from 54 independent data sets of the ENIGMA consortium. ASD was significantly associated with alterations of cortical thickness asymmetry in mostly medial frontal, orbitofrontal, cingulate and inferior temporal areas, and also with asymmetry of orbitofrontal surface area. These differences generally involved reduced asymmetry in individuals with ASD compared to controls. Furthermore, putamen volume asymmetry was significantly increased in ASD. The largest case-control effect size was Cohen's d = -0.13, for asymmetry of superior frontal cortical thickness. Most effects did not depend on age, sex, IQ, severity or medication use. Altered lateralized neurodevelopment may therefore be a feature of ASD, affecting widespread brain regions with diverse functions. Large-scale analysis was necessary to quantify subtle alterations of brain structural asymmetry in ASD.

White matter microstructure is affected by immune system activity via the actions of circulating pro-inflammatory cytokines. Although white matter microstructure and inflammatory measures are significantly heritable, it is unclear if overlapping genetic factors influence these traits in humans. We conducted genetic correlation analyses of these traits using randomly ascertained extended pedigrees from the Genetics of Brain Structure and Function Study (N = 1862, 59% females, ages 18-97 years; 42 ± 15.7). White matter microstructure was assessed using fractional anisotropy (FA) calculated from diffusion tensor imaging (DTI). Circulating levels (pg/mL) of pro-inflammatory cytokines (IL-6, IL-8, and TNFα) phenotypically associated with white matter microstructure were quantified from blood serum. All traits were significantly heritable (h 2 ranging from 0.41 to 0.66 for DTI measures and from 0.18 to 0.30 for inflammatory markers). Phenotypically, higher levels of circulating inflammatory markers were associated with lower FA values across the brain (r = -.03 to r = -.17). There were significant negative genetic correlations between most DTI measures and IL-8 and TNFα, although effects for TNFα were no longer significant when covarying for body mass index. Genetic correlations between DTI measures and IL-6 were not significant. Understanding the genetic correlation between specific inflammatory markers and DTI measures may help researchers focus questions related to inflammatory processes and brain structure., (© 2019 Wiley Periodicals, Inc.)

Objective: Although lower brain volume has been routinely observed in individuals with substance dependence compared with nondependent control subjects, the brain regions exhibiting lower volume have not been consistent across studies. In addition, it is not clear whether a common set of regions are involved in substance dependence regardless of the substance used or whether some brain volume effects are substance specific. Resolution of these issues may contribute to the identification of clinically relevant imaging biomarkers. Using pooled data from 14 countries, the authors sought to identify general and substance-specific associations between dependence and regional brain volumes., Method: Brain structure was examined in a mega-analysis of previously published data pooled from 23 laboratories, including 3,240 individuals, 2,140 of whom had substance dependence on one of five substances: alcohol, nicotine, cocaine, methamphetamine, or cannabis. Subcortical volume and cortical thickness in regions defined by FreeSurfer were compared with nondependent control subjects when all sampled substance categories were combined, as well as separately, while controlling for age, sex, imaging site, and total intracranial volume. Because of extensive associations with alcohol dependence, a secondary contrast was also performed for dependence on all substances except alcohol. An optimized split-half strategy was used to assess the reliability of the findings., Results: Lower volume or thickness was observed in many brain regions in individuals with substance dependence. The greatest effects were associated with alcohol use disorder. A set of affected regions related to dependence in general, regardless of the substance, included the insula and the medial orbitofrontal cortex. Furthermore, a support vector machine multivariate classification of regional brain volumes successfully classified individuals with substance dependence on alcohol or nicotine relative to nondependent control subjects., Conclusions: The results indicate that dependence on a range of different substances shares a common neural substrate and that differential patterns of regional volume could serve as useful biomarkers of dependence on alcohol and nicotine.

The cerebral cortex may be organized into anatomical genetic modules, communities of brain regions with shared genetic influences via pleiotropy. Such modules could represent novel phenotypes amenable to large-scale gene discovery. This modular structure was investigated with network analysis of in vivo MRI of extended pedigrees, revealing a "multiscale" structure where smaller and larger modules exist simultaneously and in partially overlapping fashion across spatial scales, in contrast to prior work suggesting a specific number of cortical thickness modules. Inter-regional genetic correlations, gene co-expression patterns and computational models indicate that two simple organizational principles account for a large proportion of the apparent complexity in the network of genetic correlations. First, regions are strongly genetically correlated with their homologs in the opposite cerebral hemisphere. Second, regions are strongly genetically correlated with nearby regions in the same hemisphere, with an initial steep decrease in genetic correlation with anatomical distance, followed by a more gradual decline. Understanding underlying organizational principles of genetic influence is a critical step towards a mechanistic model of how specific genes influence brain anatomy and mediate neuropsychiatric risk.

We measured and compared heritability estimates for measures of functional brain connectivity extracted using the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) rsfMRI analysis pipeline in two cohorts: the genetics of brain structure (GOBS) cohort and the HCP (the Human Connectome Project) cohort. These two cohorts were assessed using conventional (GOBS) and advanced (HCP) rsfMRI protocols, offering a test case for harmonization of rsfMRI phenotypes, and to determine measures that show consistent heritability for in-depth genome-wide analysis. The GOBS cohort consisted of 334 Mexican-American individuals (124M/210F, average age = 47.9 ± 13.2 years) from 29 extended pedigrees (average family size = 9 people; range 5-32). The GOBS rsfMRI data was collected using a 7.5-min acquisition sequence (spatial resolution = 1.72 × 1.72 × 3 mm 3 ). The HCP cohort consisted of 518 twins and family members (240M/278F; average age = 28.7 ± 3.7 years). rsfMRI data was collected using 28.8-min sequence (spatial resolution = 2 × 2 × 2 mm 3 ). We used the single-modality ENIGMA rsfMRI preprocessing pipeline to estimate heritability values for measures from eight major functional networks, using (1) seed-based connectivity and (2) dual regression approaches. We observed significant heritability (h 2 = 0.2-0.4, p < .05) for functional connections from seven networks across both cohorts, with a significant positive correlation between heritability estimates across two cohorts. The similarity in heritability estimates for resting state connectivity measurements suggests that the additive genetic contribution to functional connectivity is robustly detectable across populations and imaging acquisition parameters. The overarching genetic influence, and means to consistently detect it, provides an opportunity to define a common genetic search space for future gene discovery studies., (© 2018 Wiley Periodicals, Inc.)

Hemispheric asymmetry is a cardinal feature of human brain organization. Altered brain asymmetry has also been linked to some cognitive and neuropsychiatric disorders. Here, the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium presents the largest-ever analysis of cerebral cortical asymmetry and its variability across individuals. Cortical thickness and surface area were assessed in MRI scans of 17,141 healthy individuals from 99 datasets worldwide. Results revealed widespread asymmetries at both hemispheric and regional levels, with a generally thicker cortex but smaller surface area in the left hemisphere relative to the right. Regionally, asymmetries of cortical thickness and/or surface area were found in the inferior frontal gyrus, transverse temporal gyrus, parahippocampal gyrus, and entorhinal cortex. These regions are involved in lateralized functions, including language and visuospatial processing. In addition to population-level asymmetries, variability in brain asymmetry was related to sex, age, and intracranial volume. Interestingly, we did not find significant associations between asymmetries and handedness. Finally, with two independent pedigree datasets ( n = 1,443 and 1,113, respectively), we found several asymmetries showing significant, replicable heritability. The structural asymmetries identified and their variabilities and heritability provide a reference resource for future studies on the genetic basis of brain asymmetry and altered laterality in cognitive, neurological, and psychiatric disorders., Competing Interests: Conflict of interest statement: B.F. received educational speaking fees from Merz and Shire. Some ENIGMA members listed in SI Appendix also declare a conflict of interest. The other authors declare no conflict of interest.

Objective: Bipolar disorder is a heritable disorder characterized by mood dysregulation associated with brain functional dysconnectivity. Previous research has focused on the detection of risk- and disease-associated dysconnectivity in individuals with bipolar disorder and their first-degree relatives. The present study seeks to identify adaptive brain connectivity features associated with resilience, defined here as avoidance of illness or delayed illness onset in unaffected siblings of patients with bipolar disorder., Method: Graph theoretical methods were used to examine global and regional brain network topology in head-motion-corrected resting-state functional MRI data acquired from 78 patients with bipolar disorder, 64 unaffected siblings, and 41 healthy volunteers., Results: Global network properties were preserved in patients and their siblings while both groups showed reductions in the cohesiveness of the sensorimotor network. In the patient group, these sensorimotor network abnormalities were coupled with reduced integration of core default mode network regions in the ventromedial cortex and hippocampus. Conversely, integration of the default mode network was increased in the sibling group compared with both the patient group and the healthy volunteer group., Conclusions: The authors found that trait-related vulnerability to bipolar disorder was associated with reduced resting-state cohesiveness of the sensorimotor network in patients with bipolar disorder. However, integration of the default mode network emerged as a key feature differentiating disease expression and resilience between the patients and their siblings. This is indicative of the presence of neural mechanisms that may promote resilience, or at least delay illness onset.

Analyses of gray matter concentration (GMC) deficits in patients with schizophrenia (Sz) have identified robust changes throughout the cortex. We assessed the relationships between diagnosis, overall symptom severity, and patterns of gray matter in the largest aggregated structural imaging dataset to date. We performed both source-based morphometry (SBM) and voxel-based morphometry (VBM) analyses on GMC images from 784 Sz and 936 controls (Ct) across 23 scanning sites in Europe and the United States. After correcting for age, gender, site, and diagnosis by site interactions, SBM analyses showed 9 patterns of diagnostic differences. They comprised separate cortical, subcortical, and cerebellar regions. Seven patterns showed greater GMC in Ct than Sz, while 2 (brainstem and cerebellum) showed greater GMC for Sz. The greatest GMC deficit was in a single pattern comprising regions in the superior temporal gyrus, inferior frontal gyrus, and medial frontal cortex, which replicated over analyses of data subsets. VBM analyses identified overall cortical GMC loss and one small cluster of increased GMC in Sz, which overlapped with the SBM brainstem component. We found no significant association between the component loadings and symptom severity in either analysis. This mega-analysis confirms that the commonly found GMC loss in Sz in the anterior temporal lobe, insula, and medial frontal lobe form a single, consistent spatial pattern even in such a diverse dataset. The separation of GMC loss into robust, repeatable spatial patterns across multiple datasets paves the way for the application of these methods to identify subtle genetic and clinical cohort effects., (© The Author 2014. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Schizophrenia is a devastating neuropsychiatric syndrome associated with distributed brain dysconnectivity that may involve large-scale thalamo-cortical systems. Incomplete characterization of thalamic connectivity in schizophrenia limits our understanding of its relationship to symptoms and to diagnoses with shared clinical presentation, such as bipolar illness, which may exist on a spectrum. Using resting-state functional magnetic resonance imaging, we characterized thalamic connectivity in 90 schizophrenia patients versus 90 matched controls via: (1) Subject-specific anatomically defined thalamic seeds; (2) anatomical and data-driven clustering to assay within-thalamus dysconnectivity; and (3) machine learning to classify diagnostic membership via thalamic connectivity for schizophrenia and for 47 bipolar patients and 47 matched controls. Schizophrenia analyses revealed functionally related disturbances: Thalamic over-connectivity with bilateral sensory-motor cortices, which predicted symptoms, but thalamic under-connectivity with prefrontal-striatal-cerebellar regions relative to controls, possibly reflective of sensory gating and top-down control disturbances. Clustering revealed that this dysconnectivity was prominent for thalamic nuclei densely connected with the prefrontal cortex. Classification and cross-diagnostic results suggest that thalamic dysconnectivity may be a neural marker for disturbances across diagnoses. Present findings, using one of the largest schizophrenia and bipolar neuroimaging samples to date, inform basic understanding of large-scale thalamo-cortical systems and provide vital clues about the complex nature of its disturbances in severe mental illness., (Published by Oxford University Press 2013. This work is written by (a) US Government employee(s) and is in the public domain in the US.)

It is now well established that regional indices of brain structure such as cortical thickness, surface area or grey matter volume exhibit spatially variable patterns of heritability. However, a recent study found these patterns to change with age during development, a result supported by gene expression studies. Changes in heritability have not been investigated in adulthood so far and could have important implications in the study of heritability and genetic correlations in the brain as well as in the discovery of specific genes explaining them. Herein, we tested for genotype by age (G ×A) interactions, an extension of genotype by environment interactions, through adulthood and healthy aging in 902 subjects from the Genetics of Brain Structure (GOBS) study. A "jackknife" based method for the analysis of stable cortical thickness clusters (JASC) and scale selection is also introduced. Although additive genetic variance remained constant throughout adulthood, we found evidence for incomplete pleiotropy across age in the cortical thickness of paralimbic and parieto-temporal areas. This suggests that different genetic factors account for cortical thickness heritability at different ages in these regions.

Introduction: We performed a whole-transcriptome correlation analysis, followed by the pathway enrichment and testing of innate immune response pathway analyses to evaluate the hypothesis that transcriptional activity can predict cortical gray matter thickness (GMT) variability during normal cerebral aging., Methods: Transcriptome and GMT data were available for 379 individuals (age range=28-85) community-dwelling members of large extended Mexican American families. Collection of transcriptome data preceded that of neuroimaging data by 17 years. Genome-wide gene transcriptome data consisted of 20,413 heritable lymphocytes-based transcripts. GMT measurements were performed from high-resolution (isotropic 800 μm) T1-weighted MRI. Transcriptome-wide and pathway enrichment analysis was used to classify genes correlated with GMT. Transcripts for sixty genes from seven innate immune pathways were tested as specific predictors of GMT variability., Results: Transcripts for eight genes (IGFBP3, LRRN3, CRIP2, SCD, IDS, TCF4, GATA3, and HN1) passed the transcriptome-wide significance threshold. Four orthogonal factors extracted from this set predicted 31.9% of the variability in the whole-brain and between 23.4 and 35% of regional GMT measurements. Pathway enrichment analysis identified six functional categories including cellular proliferation, aggregation, differentiation, viral infection, and metabolism. The integrin signaling pathway was significantly (p<10(-6)) enriched with GMT. Finally, three innate immune pathways (complement signaling, toll-receptors and scavenger and immunoglobulins) were significantly associated with GMT., Conclusion: Expression activity for the genes that regulate cellular proliferation, adhesion, differentiation and inflammation can explain a significant proportion of individual variability in cortical GMT. Our findings suggest that normal cerebral aging is the product of a progressive decline in regenerative capacity and increased neuroinflammation., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Genetic and environmental influences on brain morphology were assessed in an extended-pedigree design by extracting depth-position profiles (DPP) of the central sulcus (CS). T1-weighted magnetic resonance images were used to measure CS length and depth in 467 human subjects from 35 extended families. Three primary forms of DPPs were observed. The most prevalent form, present in 70% of subjects, was bimodal, with peaks near hand and mouth regions. Trimodal and unimodal configurations accounted for 15 and 8%, respectively. Genetic control accounted for 56 and 66% of between-subject variance in average CS depth and length, respectively, and was not significantly influenced by environmental factors. Genetic control over CS depth ranged from 1 to 50% across the DPP. Areas of peak heritability occurred at locations corresponding to hand and mouth areas. Left and right analogous CS depth measurements were strongly pleiotropic. Shared genetic influence lessened as the distance between depth measurements was increased. We argue that DPPs are powerful phenotypes that should inform genetic influence of more complex brain regions and contribute to gene discovery efforts.

Fractional anisotropy (FA) of water diffusion in cerebral white matter (WM), derived from diffusion tensor imaging (DTI), is a sensitive index of microscopic WM integrity. Physiological and metabolic factors that explain intersubject variability in FA values were evaluated in two cohorts of healthy adults of different age spans (N=65, range: 28-50years; and N=25, age=66.6±6.2, range: 57-80years). Single voxel magnetic resonance spectroscopy (MRS) was used to measure N-acetylaspartate (NAA), total choline-containing compounds, and total creatine, bilaterally in an associative WM tract: anterior corona radiata (ACR). FA values were calculated for the underlying, proximal and two distal WM regions. Two-stage regression analysis was used to calculate the proportion of variability in FA values explained by spectroscopy measurements, at the first stage, and subject's age, at the second stage. WM NAA concentration explained 23% and 66% of intersubject variability (p<0.001) in the FA of the underlying WM in the younger and older cohorts, respectively. WM NAA concentration also explained a significant proportion of variability in FA of the genu of corpus callosum (CC), a proximal WM tract where some of the fibers contained within the spectroscopic voxel decussate. NAA concentrations also explained a significant proportion of variability in the FA values in the splenium of CC, a distal WM tract that also carries associative fibers, in both cohorts. These results suggest that MRS measurements explained a significant proportion of variability in FA values in both proximal and distal WM tracts that carry similar fiber-types., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Structural analysis of MRI data on the cortical surface usually focuses on cortical thickness. Cortical surface area, when considered, has been measured only over gross regions or approached indirectly via comparisons with a standard brain. Here we demonstrate that direct measurement and comparison of the surface area of the cerebral cortex at a fine scale is possible using mass conservative interpolation methods. We present a framework for analyses of the cortical surface area, as well as for any other measurement distributed across the cortex that is areal by nature. The method consists of the construction of a mesh representation of the cortex, registration to a common coordinate system and, crucially, interpolation using a pycnophylactic method. Statistical analysis of surface area is done with power-transformed data to address lognormality, and inference is done with permutation methods. We introduce the concept of facewise analysis, discuss its interpretation and potential applications., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Although disrupted in schizophrenia 1 (DISC1) has been implicated in many psychiatric disorders, including schizophrenia, bipolar disorder, schizoaffective disorder and major depression, its biological role in these disorders is unclear. To better understand this gene and its role in psychiatric disease, we conducted transcriptional profiling and genome-wide association analysis in 1232 pedigreed Mexican-American individuals for whom we have neuroanatomic images, neurocognitive assessments and neuropsychiatric diagnoses. SOLAR was used to determine heritability, identify gene expression patterns and perform association analyses on 188 quantitative brain-related phenotypes. We found that the DISC1 transcript is highly heritable (h(2)=0.50; P=1.97 × 10(-22)), and that gene expression is strongly cis-regulated (cis-LOD=3.89) but is also influenced by trans-effects. We identified several DISC1 polymorphisms that were associated with cortical gray matter thickness within the parietal, temporal and frontal lobes. Associated regions affiliated with memory included the entorhinal cortex (rs821639, P=4.11 × 10(-5); rs2356606, P=4.71 × 10(-4)), cingulate cortex (rs16856322, P=2.88 × 10(-4)) and parahippocampal gyrus (rs821639, P=4.95 × 10(-4)); those affiliated with executive and other cognitive processing included the transverse temporal gyrus (rs9661837, P=5.21 × 10(-4); rs17773946, P=6.23 × 10(-4)), anterior cingulate cortex (rs2487453, P=4.79 × 10(-4); rs3738401, P=5.43 × 10(-4)) and medial orbitofrontal cortex (rs9661837; P=7.40 × 10(-4)). Cognitive measures of working memory (rs2793094, P=3.38 × 10(-4)), as well as lifetime history of depression (rs4658966, P=4.33 × 10(-4); rs12137417, P=4.93 × 10(-4)) and panic (rs12137417, P=7.41 × 10(-4)) were associated with DISC1 sequence variation. DISC1 has well-defined genetic regulation and clearly influences important phenotypes related to psychiatric disease.

We examined age trajectories of fractional anisotropy (FA) of cerebral white matter (WM) and thickness of cortical gray matter (GM) in 1031 healthy human subjects (aged 11-90 years). Whole-brain FA and GM thickness values followed quadratic trajectories with age but the relationship between them was linear, indicating that a putative biological mechanism may explain the non-linearity of their age trajectories. Inclusion of the FA values into the quadratic model of the whole-brain and regional GM thickness changes with age made the effect of the age(2) term no longer significant for the whole-brain GM thickness and greatly reduced its significance for regional GM thickness measurements. The phylogenetic order of cerebral myelination helped to further explain the intersubject variability in GM thickness. FA values for the early maturing WM were significantly better (p=10(-6)) at explaining variability in GM thickness in maturing (aged 11-20) subjects than FA values for the late maturing WM. The opposite trend was observed for aging subjects (aged 40-90) where FA values for the late maturing WM were better (p=10(-16)) at explaining the variability in GM thickness. We concluded that the non-linearity of the age trajectory for GM thickness, measured from T1-weighted MRI, was partially explained by the heterogeneity and the heterochronicity of the age-related changes in the microintegrity of cerebral WM. We consider these findings as the evidence that the measurements of age-related changes in GM thickness and FA are driven, in part, by a common biological mechanism, presumed to be related to changes in cerebral myelination., (Copyright © 2011 Elsevier Inc. All rights reserved.)

Understanding the evolutionary forces that produced the human brain is a central problem in neuroscience and human biology. Comparisons across primate species show that both brain volume and gyrification (the degree of folding in the cerebral cortex) have progressively increased during primate evolution and there is a strong positive correlation between these two traits across primate species. The human brain is exceptional among primates in both total volume and gyrification, and therefore understanding the genetic mechanisms influencing variation in these traits will improve our understanding of a landmark feature of our species. Here we show that individual variation in gyrification is significantly heritable in both humans and an Old World monkey (baboons, Papio hamadryas). Furthermore, contrary to expectations based on the positive phenotypic correlation across species, the genetic correlation between cerebral volume and gyrification within both humans and baboons is estimated as negative. These results suggest that the positive relationship between cerebral volume and cortical folding across species cannot be explained by one set of selective pressures or genetic changes. Our data suggest that one set of selective pressures favored the progressive increase in brain volume documented in the primate fossil record, and that a second independent selective process, possibly related to parturition and neonatal brain size, may have favored brains with progressively greater cortical folding. Without a second separate selective pressure, natural selection favoring increased brain volume would be expected to produce less folded, more lissencephalic brains. These results provide initial evidence for the heritability of gyrification, and possibly a new perspective on the evolutionary mechanisms underlying long-term changes in the nonhuman primate and human brain., (Copyright 2010 Elsevier Inc. All rights reserved.)

We analyzed the degree of genetic control over intersubject variability in the microstructure of cerebral white matter (WM) using diffusion tensor imaging (DTI). We performed heritability, genetic correlation and quantitative trait loci (QTL) analyses for the whole-brain and 10 major cerebral WM tracts. Average measurements for fractional anisotropy (FA), radial (L( perpendicular)) and axial (L( vertical line)) diffusivities served as quantitative traits. These analyses were done in 467 healthy individuals (182 males/285 females; average age 47.9+/-13.5 years; age range: 19-85 years), recruited from randomly-ascertained pedigrees of extended families. Significant heritability was observed for FA (h(2)=0.52+/-0.11; p=10(-7)) and L( perpendicular) (h(2)=0.37+/-0.14; p=0.001), while L( vertical line) measurements were not significantly heritable (h(2)=0.09+/-0.12; p=0.20). Genetic correlation analysis indicated that the FA and L( perpendicular) shared 46% of the genetic variance. Tract-wise analysis revealed a regionally diverse pattern of genetic control, which was unrelated to ontogenic factors, such as tract-wise age-of-peak FA values and rates of age-related change in FA. QTL analysis indicated linkages for whole-brain average FA (LOD=2.36) at the marker D15S816 on chromosome 15q25, and for L( perpendicular) (LOD=2.24) near the marker D3S1754 on the chromosome 3q27. These sites have been reported to have significant co-inheritance with two psychiatric disorders (major depression and obsessive-compulsive disorder) in which patients show characteristic alterations in cerebral WM. Our findings suggest that the microstructure of cerebral white matter is under a strong genetic control and further studies in healthy as well as patients with brain-related illnesses are imperative to identify the genes that may influence cerebral white matter., (Copyright 2010 Elsevier Inc. All rights reserved.)

Context: Visual masking procedures assess the earliest stages of visual processing. Patients with schizophrenia reliably show deficits on visual masking, and these procedures have been used to explore vulnerability to schizophrenia, probe underlying neural circuits, and help explain functional outcome., Objective: To identify and compare regional brain activity associated with one form of visual masking (ie, backward masking) in schizophrenic patients and healthy controls., Design: Subjects received functional magnetic resonance imaging scans. While in the scanner, subjects performed a backward masking task and were given 3 functional localizer activation scans to identify early visual processing regions of interest (ROIs)., Setting: University of California, Los Angeles, and the Department of Veterans Affairs Greater Los Angeles Healthcare System., Participants: Nineteen patients with schizophrenia and 19 healthy control subjects. Main Outcome Measure The magnitude of the functional magnetic resonance imaging signal during backward masking., Results: Two ROIs (lateral occipital complex [LO] and the human motion selective cortex [hMT+]) showed sensitivity to the effects of masking, meaning that signal in these areas increased as the target became more visible. Patients had lower activation than controls in LO across all levels of visibility but did not differ in other visual processing ROIs. Using whole-brain analyses, we also identified areas outside the ROIs that were sensitive to masking effects (including bilateral inferior parietal lobe and thalamus), but groups did not differ in signal magnitude in these areas., Conclusions: The study results support a key role in LO for visual masking, consistent with previous studies in healthy controls. The current results indicate that patients fail to activate LO to the same extent as controls during visual processing regardless of stimulus visibility, suggesting a neural basis for the visual masking deficit, and possibly other visual integration deficits, in schizophrenia.

The 22q11.2 deletion syndrome (velocardiofacial/DiGeorge syndrome, 22q11.2DS) involves cardiac and craniofacial anomalies, marked deficits in visuospatial cognition, and elevated rates of psychosis. Although the mechanism is unknown, characteristic brain alterations may predispose to development of psychosis and cognitive deficits in 22q11DS. We applied cortical pattern matching and new methods for measuring cortical thickness in millimeters to structural magnetic resonance images of 21 children with confirmed 22q11.2 deletions and 13 demographically matched healthy comparison subjects. Thickness was mapped at 65 536 homologous points, based on 3-dimensional distance from the cortical gray-white matter interface to the external gray-cerebrospinal fluid boundary. A pattern of regionally specific cortical thinning was observed in superior parietal cortices and right parietooccipital cortex, regions critical for visuospatial processing, and bilaterally in the most inferior portion of the inferior frontal gyrus (pars orbitalis), a key area for language development. Several of the 30 genes encoded in the deleted segment are highly expressed in the developing brain and known to affect early neuronal migration. These brain maps reveal how haploinsufficiency for such genes can affect cortical development and suggest a possible underlying pathophysiology of the neurobehavioral phenotype.

Background: The neurobiological underpinnings of bipolar disorder are not well understood. Previous neuroimaging findings have been inconsistent; however, new methods for three-dimensional (3-D) computational image analysis may better characterize neuroanatomic changes than standard volumetric measures., Methods: We used high-resolution magnetic resonance imaging and cortical pattern matching methods to map gray matter differences in 28 adults with bipolar disorder, 70% of whom were lithium-treated (mean age = 36.1 +/- 10.5; 13 female subject), and 28 healthy control subjects (mean age = 35.9 +/- 8.5; 11 female subjects). Detailed spatial analyses of gray matter density (GMD) were conducted by measuring local proportions of gray matter at thousands of homologous cortical locations., Results: Gray matter density was significantly greater in bipolar patients relative to control subjects in diffuse cortical regions. Greatest differences were found in bilateral cingulate and paralimbic cortices, brain regions critical for attentional, motivational, and emotional modulation. Secondary region of interest (ROI) analyses indicated significantly greater GMD in the right anterior cingulate among lithium-treated bipolar patients (n = 20) relative to those not taking lithium (n = 8)., Conclusions: These brain maps are consistent with previous voxel-based morphometry reports of greater GMD in portions of the anterior limbic network in bipolar patients and suggest neurotrophic effects of lithium as a possible etiology of these neuroanatomic differences.

Despite decades of research, the pathophysiology of bipolar disorder (BD) is still not well understood. Structural brain differences have been associated with BD, but results from neuroimaging studies have been inconsistent. To address this, we performed the largest study to date of cortical gray matter thickness and surface area measures from brain magnetic resonance imaging scans of 6503 individuals including 1837 unrelated adults with BD and 2582 unrelated healthy controls for group differences while also examining the effects of commonly prescribed medications, age of illness onset, history of psychosis, mood state, age and sex differences on cortical regions. In BD, cortical gray matter was thinner in frontal, temporal and parietal regions of both brain hemispheres. BD had the strongest effects on left pars opercularis (Cohen's d=-0.293; P=1.71 × 10-21), left fusiform gyrus (d=-0.288; P=8.25 × 10-21) and left rostral middle frontal cortex (d=-0.276; P=2.99 × 10-19). Longer duration of illness (after accounting for age at the time of scanning) was associated with reduced cortical thickness in frontal, medial parietal and occipital regions. We found that several commonly prescribed medications, including lithium, antiepileptic and antipsychotic treatment showed significant associations with cortical thickness and surface area, even after accounting for patients who received multiple medications. We found evidence of reduced cortical surface area associated with a history of psychosis but no associations with mood state at the time of scanning. Our analysis revealed previously undetected associations and provides an extensive analysis of potential confounding variables in neuroimaging studies of BD.