Publications by authors named "Greig I de Zubicaray"

148 Publications

Autism-related dietary preferences mediate autism-gut microbiome associations.

Cell 2021 Nov 11;184(24):5916-5931.e17. Epub 2021 Nov 11.

Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging & Informatics, Keck School of Medicine, University of Southern California, Los Angeles, USA.

There is increasing interest in the potential contribution of the gut microbiome to autism spectrum disorder (ASD). However, previous studies have been underpowered and have not been designed to address potential confounding factors in a comprehensive way. We performed a large autism stool metagenomics study (n = 247) based on participants from the Australian Autism Biobank and the Queensland Twin Adolescent Brain project. We found negligible direct associations between ASD diagnosis and the gut microbiome. Instead, our data support a model whereby ASD-related restricted interests are associated with less-diverse diet, and in turn reduced microbial taxonomic diversity and looser stool consistency. In contrast to ASD diagnosis, our dataset was well powered to detect microbiome associations with traits such as age, dietary intake, and stool consistency. Overall, microbiome differences in ASD may reflect dietary preferences that relate to diagnostic features, and we caution against claims that the microbiome has a driving role in ASD.
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http://dx.doi.org/10.1016/j.cell.2021.10.015DOI Listing
November 2021

A meta-analysis of deep brain structural shape and asymmetry abnormalities in 2,833 individuals with schizophrenia compared with 3,929 healthy volunteers via the ENIGMA Consortium.

Hum Brain Mapp 2021 Sep 8. Epub 2021 Sep 8.

Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) [Georgia State University, Georgia Institute of Technology], Emory University, Atlanta, Georgia, USA.

Schizophrenia is associated with widespread alterations in subcortical brain structure. While analytic methods have enabled more detailed morphometric characterization, findings are often equivocal. In this meta-analysis, we employed the harmonized ENIGMA shape analysis protocols to collaboratively investigate subcortical brain structure shape differences between individuals with schizophrenia and healthy control participants. The study analyzed data from 2,833 individuals with schizophrenia and 3,929 healthy control participants contributed by 21 worldwide research groups participating in the ENIGMA Schizophrenia Working Group. Harmonized shape analysis protocols were applied to each site's data independently for bilateral hippocampus, amygdala, caudate, accumbens, putamen, pallidum, and thalamus obtained from T1-weighted structural MRI scans. Mass univariate meta-analyses revealed more-concave-than-convex shape differences in the hippocampus, amygdala, accumbens, and thalamus in individuals with schizophrenia compared with control participants, more-convex-than-concave shape differences in the putamen and pallidum, and both concave and convex shape differences in the caudate. Patterns of exaggerated asymmetry were observed across the hippocampus, amygdala, and thalamus in individuals with schizophrenia compared to control participants, while diminished asymmetry encompassed ventral striatum and ventral and dorsal thalamus. Our analyses also revealed that higher chlorpromazine dose equivalents and increased positive symptom levels were associated with patterns of contiguous convex shape differences across multiple subcortical structures. Findings from our shape meta-analysis suggest that common neurobiological mechanisms may contribute to gray matter reduction across multiple subcortical regions, thus enhancing our understanding of the nature of network disorganization in schizophrenia.
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http://dx.doi.org/10.1002/hbm.25625DOI Listing
September 2021

Are Sex Differences in Human Brain Structure Associated With Sex Differences in Behavior?

Psychol Sci 2021 08 29;32(8):1183-1197. Epub 2021 Jul 29.

Centre for Psychology and Evolution, School of Psychology, University of Queensland.

On average, men and women differ in brain structure and behavior, raising the possibility of a link between sex differences in brain and behavior. But women and men are also subject to different societal and cultural norms. We navigated this challenge by investigating variability of sex-differentiated brain structure within each sex. Using data from the Queensland Twin IMaging study ( = 1,040) and Human Connectome Project ( = 1,113), we obtained data-driven measures of individual differences along a male-female dimension for brain and behavior based on average sex differences in brain structure and behavior, respectively. We found a weak association between these brain and behavioral differences, driven by brain size. These brain and behavioral differences were moderately heritable. Our findings suggest that behavioral sex differences are, to some extent, related to sex differences in brain structure but that this is mainly driven by differences in brain size, and causality should be interpreted cautiously.
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http://dx.doi.org/10.1177/0956797621996664DOI Listing
August 2021

Are Sex Differences in Human Brain Structure Associated With Sex Differences in Behavior?

Psychol Sci 2021 08 29;32(8):1183-1197. Epub 2021 Jul 29.

Centre for Psychology and Evolution, School of Psychology, University of Queensland.

On average, men and women differ in brain structure and behavior, raising the possibility of a link between sex differences in brain and behavior. But women and men are also subject to different societal and cultural norms. We navigated this challenge by investigating variability of sex-differentiated brain structure within each sex. Using data from the Queensland Twin IMaging study ( = 1,040) and Human Connectome Project ( = 1,113), we obtained data-driven measures of individual differences along a male-female dimension for brain and behavior based on average sex differences in brain structure and behavior, respectively. We found a weak association between these brain and behavioral differences, driven by brain size. These brain and behavioral differences were moderately heritable. Our findings suggest that behavioral sex differences are, to some extent, related to sex differences in brain structure but that this is mainly driven by differences in brain size, and causality should be interpreted cautiously.
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http://dx.doi.org/10.1177/0956797621996664DOI Listing
August 2021

1q21.1 distal copy number variants are associated with cerebral and cognitive alterations in humans.

Transl Psychiatry 2021 03 22;11(1):182. Epub 2021 Mar 22.

Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.

Low-frequency 1q21.1 distal deletion and duplication copy number variant (CNV) carriers are predisposed to multiple neurodevelopmental disorders, including schizophrenia, autism and intellectual disability. Human carriers display a high prevalence of micro- and macrocephaly in deletion and duplication carriers, respectively. The underlying brain structural diversity remains largely unknown. We systematically called CNVs in 38 cohorts from the large-scale ENIGMA-CNV collaboration and the UK Biobank and identified 28 1q21.1 distal deletion and 22 duplication carriers and 37,088 non-carriers (48% male) derived from 15 distinct magnetic resonance imaging scanner sites. With standardized methods, we compared subcortical and cortical brain measures (all) and cognitive performance (UK Biobank only) between carrier groups also testing for mediation of brain structure on cognition. We identified positive dosage effects of copy number on intracranial volume (ICV) and total cortical surface area, with the largest effects in frontal and cingulate cortices, and negative dosage effects on caudate and hippocampal volumes. The carriers displayed distinct cognitive deficit profiles in cognitive tasks from the UK Biobank with intermediate decreases in duplication carriers and somewhat larger in deletion carriers-the latter potentially mediated by ICV or cortical surface area. These results shed light on pathobiological mechanisms of neurodevelopmental disorders, by demonstrating gene dose effect on specific brain structures and effect on cognitive function.
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http://dx.doi.org/10.1038/s41398-021-01213-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7985307PMC
March 2021

Effects of copy number variations on brain structure and risk for psychiatric illness: Large-scale studies from the ENIGMA working groups on CNVs.

Hum Brain Mapp 2021 Feb 21. Epub 2021 Feb 21.

Center for Neuroimaging, Genetics and Genomics, School of Psychology, NUI Galway, Galway, Ireland.

The Enhancing NeuroImaging Genetics through Meta-Analysis copy number variant (ENIGMA-CNV) and 22q11.2 Deletion Syndrome Working Groups (22q-ENIGMA WGs) were created to gain insight into the involvement of genetic factors in human brain development and related cognitive, psychiatric and behavioral manifestations. To that end, the ENIGMA-CNV WG has collated CNV and magnetic resonance imaging (MRI) data from ~49,000 individuals across 38 global research sites, yielding one of the largest studies to date on the effects of CNVs on brain structures in the general population. The 22q-ENIGMA WG includes 12 international research centers that assessed over 533 individuals with a confirmed 22q11.2 deletion syndrome, 40 with 22q11.2 duplications, and 333 typically developing controls, creating the largest-ever 22q11.2 CNV neuroimaging data set. In this review, we outline the ENIGMA infrastructure and procedures for multi-site analysis of CNVs and MRI data. So far, ENIGMA has identified effects of the 22q11.2, 16p11.2 distal, 15q11.2, and 1q21.1 distal CNVs on subcortical and cortical brain structures. Each CNV is associated with differences in cognitive, neurodevelopmental and neuropsychiatric traits, with characteristic patterns of brain structural abnormalities. Evidence of gene-dosage effects on distinct brain regions also emerged, providing further insight into genotype-phenotype relationships. Taken together, these results offer a more comprehensive picture of molecular mechanisms involved in typical and atypical brain development. This "genotype-first" approach also contributes to our understanding of the etiopathogenesis of brain disorders. Finally, we outline future directions to better understand effects of CNVs on brain structure and behavior.
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http://dx.doi.org/10.1002/hbm.25354DOI Listing
February 2021

Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3-90 years.

Hum Brain Mapp 2021 Feb 17. Epub 2021 Feb 17.

Laboratory of Psychiatric Neuroimaging, Departamento e Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil.

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.
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http://dx.doi.org/10.1002/hbm.25364DOI Listing
February 2021

Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3-90 years.

Hum Brain Mapp 2021 Feb 11. Epub 2021 Feb 11.

Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, USA.

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.
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http://dx.doi.org/10.1002/hbm.25320DOI Listing
February 2021

A Sound Explanation for Motor Cortex Engagement during Action Word Comprehension.

J Cogn Neurosci 2021 01 15;33(1):129-145. Epub 2020 Oct 15.

Flinders University, Adelaide, Australia.

Comprehending action words often engages similar brain regions to those involved in perceiving and executing actions. This finding has been interpreted as support for grounding of conceptual processing in motor representations or that conceptual processing involves motor simulation. However, such demonstrations cannot confirm the nature of the mechanism(s) responsible, as word comprehension involves multiple processes (e.g., lexical, semantic, morphological, phonological). In this study, we tested whether this motor cortex engagement instead reflects processing of statistical regularities in sublexical phonological features. Specifically, we measured brain activity in healthy participants using functional magnetic resonance imaging while they performed an auditory lexical decision paradigm involving monosyllabic action words associated with specific effectors (face, arm, and leg). We show that nonwords matched to the action words in terms of their elicit common patterns of activation. In addition, we show that a measure of the action words' , the extent to which a word's phonology is typical of other words in the grammatical category to which it belongs (i.e., more or less verb-like), is responsible for their activating a significant portion of primary and premotor cortices. These results indicate motor cortex engagement during action word comprehension is more likely to reflect processing of statistical regularities in sublexical phonological features than conceptual processing. We discuss the implications for current neurobiological models of language, all of which implicitly or explicitly assume that the relationship between the sound of a word and its meaning is arbitrary.
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http://dx.doi.org/10.1162/jocn_a_01640DOI Listing
January 2021

Greater male than female variability in regional brain structure across the lifespan.

Hum Brain Mapp 2020 Oct 12. Epub 2020 Oct 12.

FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain.

For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium presents the largest-ever mega-analysis of sex differences in variability of brain structure, based on international data spanning nine decades of life. Subcortical volumes, cortical surface area and cortical thickness were assessed in MRI data of 16,683 healthy individuals 1-90 years old (47% females). We observed significant patterns of greater male than female between-subject variance for all subcortical volumetric measures, all cortical surface area measures, and 60% of cortical thickness measures. This pattern was stable across the lifespan for 50% of the subcortical structures, 70% of the regional area measures, and nearly all regions for thickness. Our findings that these sex differences are present in childhood implicate early life genetic or gene-environment interaction mechanisms. The findings highlight the importance of individual differences within the sexes, that may underpin sex-specific vulnerability to disorders.
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http://dx.doi.org/10.1002/hbm.25204DOI Listing
October 2020

The reliability and heritability of cortical folds and their genetic correlations across hemispheres.

Commun Biol 2020 09 15;3(1):510. Epub 2020 Sep 15.

Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA.

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.
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http://dx.doi.org/10.1038/s42003-020-01163-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7493906PMC
September 2020

Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group.

Mol Psychiatry 2021 Sep 18;26(9):5124-5139. Epub 2020 May 18.

Department of Psychiatry, University of Münster, Münster, Germany.

Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted "brain age" and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen's d = 0.14, 95% CI: 0.08-0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates.
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http://dx.doi.org/10.1038/s41380-020-0754-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8589647PMC
September 2021

Region-specific sex differences in the hippocampus.

Neuroimage 2020 07 9;215:116781. Epub 2020 Apr 9.

Queensland Brain Institute, University of Queensland, Brisbane, Australia; Centre for Advanced Imaging, University of Queensland, Brisbane, Australia.

The hippocampus is a brain region critical for learning and memory, and is also implicated in several neuropsychiatric disorders that show sex differences in prevalence, symptom expression, and mean age of onset. On average, males have larger hippocampal volumes than females, but findings are inconclusive after adjusting for overall brain size. Although the hippocampus is a heterogenous structure, few studies have focused on sex differences in the hippocampal subfields - with little consensus on whether there are regionally specific sex differences in the hippocampus after adjusting for brain size, or whether it is important to adjust for total hippocampal volume (HPV). Here, using two young adult cohorts from the Queensland Twin IMaging study (QTIM; N ​= ​727) and the Human Connectome Project (HCP; N ​= ​960), we examined differences between males and females in the volumes of 12 hippocampal subfields, extracted using FreeSurfer 6.0. After adjusting the subfield volumes for either HPV or brain size (brain segmentation volume (BSV)) using four controlling methods (allometric, covariate, residual and matching), we estimated the percentage difference of the sex effect (males versus females) and Cohen's d using hierarchical general linear models. Males had larger volumes compared to females in the parasubiculum (up to 6.04%; Cohen's d ​= ​0.46) and fimbria (up to 8.75%; d ​= ​0.54) after adjusting for HPV. These sex differences were robust across the two cohorts and multiple controlling methods, though within cohort effect sizes were larger for the matched approach, due to the smaller sub-sample. Additional sex effects were identified in the HCP cohort and combined (QTIM and HCP) sample (hippocampal fissure (up to 6.79%), presubiculum (up to 3.08%), and hippocampal tail (up to -0.23%)). In contrast, no sex differences were detected for the volume of the cornu ammonis (CA)2/3, CA4, Hippocampus-Amygdala Transition Area (HATA), or the granule cell layer of the dentate gyrus (GCDG). These findings show that, independent of differences in HPV, there are regionally specific sex differences in the hippocampus, which may be most prominent in the fimbria and parasubiculum. Further, given sex differences were less consistent across cohorts after controlling for BSV, adjusting for HPV rather than BSV may benefit future studies. This work may help in disentangling sex effects, and provide a better understanding of the implications of sex differences for behaviour and neuropsychiatric disorders.
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http://dx.doi.org/10.1016/j.neuroimage.2020.116781DOI Listing
July 2020

The genetic architecture of the human cerebral cortex.

Science 2020 03;367(6484)

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.
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http://dx.doi.org/10.1126/science.aay6690DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7295264PMC
March 2020

Epigenome-wide meta-analysis of blood DNA methylation and its association with subcortical volumes: findings from the ENIGMA Epigenetics Working Group.

Mol Psychiatry 2021 Aug 6;26(8):3884-3895. Epub 2019 Dec 6.

University Medical Centre Hamburg-Eppendorf, House W34, 3.OG, Martinistr. 52, 20246, Hamburg, Germany.

DNA methylation, which is modulated by both genetic factors and environmental exposures, may offer a unique opportunity to discover novel biomarkers of disease-related brain phenotypes, even when measured in other tissues than brain, such as blood. A few studies of small sample sizes have revealed associations between blood DNA methylation and neuropsychopathology, however, large-scale epigenome-wide association studies (EWAS) are needed to investigate the utility of DNA methylation profiling as a peripheral marker for the brain. Here, in an analysis of eleven international cohorts, totalling 3337 individuals, we report epigenome-wide meta-analyses of blood DNA methylation with volumes of the hippocampus, thalamus and nucleus accumbens (NAcc)-three subcortical regions selected for their associations with disease and heritability and volumetric variability. Analyses of individual CpGs revealed genome-wide significant associations with hippocampal volume at two loci. No significant associations were found for analyses of thalamus and nucleus accumbens volumes. Cluster-based analyses revealed additional differentially methylated regions (DMRs) associated with hippocampal volume. DNA methylation at these loci affected expression of proximal genes involved in learning and memory, stem cell maintenance and differentiation, fatty acid metabolism and type-2 diabetes. These DNA methylation marks, their interaction with genetic variants and their impact on gene expression offer new insights into the relationship between epigenetic variation and brain structure and may provide the basis for biomarker discovery in neurodegeneration and neuropsychiatric conditions.
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http://dx.doi.org/10.1038/s41380-019-0605-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8550939PMC
August 2021

Association of Copy Number Variation of the 15q11.2 BP1-BP2 Region With Cortical and Subcortical Morphology and Cognition.

JAMA Psychiatry 2020 04;77(4):420-430

Department of Biological Psychology and Netherlands Twin Register, VU University Amsterdam, Amsterdam, the Netherlands.

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.
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http://dx.doi.org/10.1001/jamapsychiatry.2019.3779DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6822096PMC
April 2020

Genetic architecture of subcortical brain structures in 38,851 individuals.

Nat Genet 2019 11 21;51(11):1624-1636. Epub 2019 Oct 21.

Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA.

Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.
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http://dx.doi.org/10.1038/s41588-019-0511-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7055269PMC
November 2019

Absolute and relative estimates of genetic and environmental variance in brain structure volumes.

Brain Struct Funct 2019 Nov 19;224(8):2805-2821. Epub 2019 Aug 19.

Queensland Brain Institute, University of Queensland, Brisbane, QLD, 4072, Australia.

Comparing estimates of the amount of genetic and environmental variance for different brain structures may elucidate differences in the genetic architecture or developmental constraints of individual brain structures. However, most studies compare estimates of relative genetic (heritability) and environmental variance in brain structure, which do not reflect differences in absolute variance between brain regions. Here we used a population sample of young adult twins and singleton siblings of twins (n = 791; M = 23 years, Queensland Twin IMaging study) to estimate the absolute genetic and environmental variance, standardised by the phenotypic mean, in the size of cortical, subcortical, and ventricular brain structures. Mean-standardised genetic variance differed widely across structures [23.5-fold range 0.52% (hippocampus) to 12.28% (lateral ventricles)], but the range of estimates within cortical, subcortical, or ventricular structures was more moderate (two to fivefold range). There was no association between mean-standardised and relative measures of genetic variance (i.e., heritability) in brain structure volumes. We found similar results in an independent sample (n = 1075, M = 29 years, Human Connectome Project). These findings open important new lines of enquiry: namely, understanding the bases of these variance patterns, and their implications regarding the genetic architecture, evolution, and development of the human brain.
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http://dx.doi.org/10.1007/s00429-019-01931-8DOI Listing
November 2019

Neural Mechanisms for Monitoring and Halting of Spoken Word Production.

J Cogn Neurosci 2019 12 16;31(12):1946-1957. Epub 2019 Aug 16.

Queensland University of Technology.

During conversation, speakers monitor their own and others' output so they can alter their production adaptively, including halting it if needed. We investigated the neural mechanisms of monitoring and halting in spoken word production by employing a modified stop signal task during fMRI. Healthy participants named target pictures and withheld their naming response when presented with infrequent auditory words as stop signals. We also investigated whether the speech comprehension system monitors inner (i.e., prearticulatory) speech via the output of phonological word form encoding as proposed by the perceptual loop theory [Levelt, W. J. M. . Cambridge, MA: MIT Press, 1989] by presenting stop signals phonologically similar to the target picture name (e.g., cabbage-CAMEL). The contrast of successful halting versus naming revealed extensive BOLD signal responses in bilateral inferior frontal gyrus, preSMA, and superior temporal gyrus. Successful versus unsuccessful halting of speech was associated with increased BOLD signal bilaterally in the posterior middle temporal, frontal, and parietal lobes and decreases bilaterally in the posterior and left anterior superior temporal gyrus and right inferior frontal gyrus. These results show, for the first time, the neural mechanisms engaged during both monitoring and interrupting speech production. However, we failed to observe any differential effects of phonological similarity in either the behavioral or neural data, indicating monitoring of inner versus external speech might involve different mechanisms.
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http://dx.doi.org/10.1162/jocn_a_01462DOI Listing
December 2019

Multi-Site Meta-Analysis of Morphometry.

IEEE/ACM Trans Comput Biol Bioinform 2019 Sep-Oct;16(5):1508-1514. Epub 2019 May 23.

Genome-wide association studies (GWAS) link full genome data to a handful of traits. However, in neuroimaging studies, there is an almost unlimited number of traits that can be extracted for full image-wide big data analyses. Large populations are needed to achieve the necessary power to detect statistically significant effects, emphasizing the need to pool data across multiple studies. Neuroimaging consortia, e.g., ENIGMA and CHARGE, are now analyzing MRI data from over 30,000 individuals. Distributed processing protocols extract harmonized features at each site, and pool together only the cohort statistics using meta analysis to avoid data sharing. To date, such MRI projects have focused on single measures such as hippocampal volume, yet voxelwise analyses (e.g., tensor-based morphometry; TBM) may help better localize statistical effects. This can lead to $10^{13}$1013 tests for GWAS and become underpowered. We developed an analytical framework for multi-site TBM by performing multi-channel registration to cohort-specific templates. Our results highlight the reliability of the method and the added power over alternative options while preserving single site specificity and opening the doors for well-powered image-wide genome-wide discoveries.
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http://dx.doi.org/10.1109/TCBB.2019.2914905DOI Listing
March 2020

Accelerated estimation and permutation inference for ACE modeling.

Hum Brain Mapp 2019 08 29;40(12):3488-3507. Epub 2019 Apr 29.

Department of Statistics, University of Warwick, Coventry, UK.

There are a wealth of tools for fitting linear models at each location in the brain in neuroimaging analysis, and a wealth of genetic tools for estimating heritability for a small number of phenotypes. But there remains a need for computationally efficient neuroimaging genetic tools that can conduct analyses at the brain-wide scale. Here we present a simple method for heritability estimation on twins that replaces a variance component model-which requires iterative optimisation-with a (noniterative) linear regression model, by transforming data to squared twin-pair differences. We demonstrate that the method has comparable bias, mean squared error, false positive risk, and power to best practice maximum-likelihood-based methods, while requiring a small fraction of the computation time. Combined with permutation, we call this approach "Accelerated Permutation Inference for the ACE Model (APACE)" where ACE refers to the additive genetic (A) effects, and common (C), and unique (E) environmental influences on the trait. We show how the use of spatial statistics like cluster size can dramatically improve power, and illustrate the method on a heritability analysis of an fMRI working memory dataset.
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http://dx.doi.org/10.1002/hbm.24611DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6680147PMC
August 2019

Homogenizing Estimates of Heritability Among SOLAR-Eclipse, OpenMx, APACE, and FPHI Software Packages in Neuroimaging Data.

Front Neuroinform 2019 12;13:16. Epub 2019 Mar 12.

Big Data Institute, University of Oxford, Oxford, United Kingdom.

Imaging genetic analyses use heritability calculations to measure the fraction of phenotypic variance attributable to additive genetic factors. We tested the agreement between heritability estimates provided by four methods that are used for heritability estimates in neuroimaging traits. SOLAR-Eclipse and OpenMx use iterative maximum likelihood estimation (MLE) methods. Accelerated Permutation inference for ACE (APACE) and fast permutation heritability inference (FPHI), employ fast, non-iterative approximation-based methods. We performed this evaluation in a simulated twin-sibling pedigree and phenotypes and in diffusion tensor imaging (DTI) data from three twin-sibling cohorts, the human connectome project (HCP), netherlands twin register (NTR) and BrainSCALE projects provided as a part of the enhancing neuro imaging genetics analysis (ENIGMA) consortium. We observed that heritability estimate may differ depending on the underlying method and dataset. The heritability estimates from the two MLE approaches provided excellent agreement in both simulated and imaging data. The heritability estimates for two approximation approaches showed reduced heritability estimates in datasets with deviations from data normality. We propose a data homogenization approach (implemented in solar-eclipse; www.solar-eclipse-genetics.org) to improve the convergence of heritability estimates across different methods. The homogenization steps include consistent regression of any nuisance covariates and enforcing normality on the trait data using inverse Gaussian transformation. Under these conditions, the heritability estimates for simulated and DTI phenotypes produced converging heritability estimates regardless of the method. Thus, using these simple suggestions may help new heritability studies to provide outcomes that are comparable regardless of software package.
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http://dx.doi.org/10.3389/fninf.2019.00016DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6422938PMC
March 2019

The Shape of Things to Come in Speech Production: A Functional Magnetic Resonance Imaging Study of Visual Form Interference during Lexical Access.

J Cogn Neurosci 2019 06 12;31(6):913-921. Epub 2019 Feb 12.

Queensland University of Technology.

Studies of context effects in speech production have shown that semantic feature overlap produces interference in naming of categorically related objects. In neuroimaging studies, this semantic interference effect is consistently associated with involvement of left superior and middle temporal gyri. However, at least part of this effect has recently been shown to be attributable to visual form similarity, as categorically related objects typically share visual features. This fMRI study examined interference produced by visual form overlap in the absence of a category relation in a picture-word interference paradigm. Both visually similar and visually dissimilar distractors led to increased BOLD responses in the left inferior frontal gyrus compared with the congruent condition. Naming pictures in context with a distractor word denoting an object visually similar in form slowed RTs compared with unrelated words and was associated with reduced activity in the left posterior middle temporal gyrus. This area is reliably observed in lexical level processing during language production tasks. No significant differential activity was observed in areas typically engaged by early perceptual or conceptual feature level processing or in areas proposed to be engaged by postlexical language processes, suggesting that visual form interference does not arise from uncertainty or confusion during perceptual or conceptual identification or after lexical processing. We conclude that visual form interference has a lexical locus, consistent with the predictions of competitive lexical selection models.
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http://dx.doi.org/10.1162/jocn_a_01382DOI Listing
June 2019

The neurobiology of taboo language processing: fMRI evidence during spoken word production.

Soc Cogn Affect Neurosci 2019 03;14(3):271-279

Faculty of Health, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia.

Every language has words deemed to be socially inappropriate or 'taboo' to utter. Taboo word production appears prominently in language disorders following brain injury. Yet, we know little about the cognitive and neural mechanisms involved in processing taboo compared to neutral language. In the present study, we introduced taboo distractor words in the picture word interference paradigm during functional magnetic resonance imaging to investigate how these words influence spoken word production. Taboo distractor words significantly slowed picture-naming latencies compared to neutral words. This interference effect was associated with increased blood oxygen level dependent signal across a distributed thalamo-cortical network including bilateral anterior cingulate cortex and left inferior frontal gyrus, left posterior middle temporal gyrus and right thalamus. We interpret our findings as being consistent with an account integrating both domain-general attention-capture/distractor blocking and language-specific mechanisms in processing taboo words during spoken word production.
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http://dx.doi.org/10.1093/scan/nsz009DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6399611PMC
March 2019

Correction: Dose response of the 16p11.2 distal copy number variant on intracranial volume and basal ganglia.

Mol Psychiatry 2020 Mar;25(3):692-695

Department of Psychiatry and Mental Health, Anzio Road, 7925, Cape Town, South Africa.

Prior to and following the publication of this article the authors noted that the complete list of authors was not included in the main article and was only present in Supplementary Table 1. The author list in the original article has now been updated to include all authors, and Supplementary Table 1 has been removed. All other supplementary files have now been updated accordingly. Furthermore, in Table 1 of this Article, the replication cohort for the row Close relative in data set, n (%) was incorrect. All values have now been corrected to 0(0%). The publishers would like to apologise for this error and the inconvenience it may have caused.
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http://dx.doi.org/10.1038/s41380-019-0358-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7608381PMC
March 2020

Associations between brain structure and perceived intensity of sweet and bitter tastes.

Behav Brain Res 2019 05 28;363:103-108. Epub 2019 Jan 28.

Queensland Brain Institute, University of Queensland, Brisbane, Queensland, Australia; Centre for Advanced Imaging, University of Queensland, Brisbane, Queensland, Australia.

Functional neuroimaging studies have identified brain regions associated with human taste perception, but only a few have investigated the associations with brain structure. Here, in this exploratory study, we examined the association between the volumes of 82 regions of interest (ROI) and the perceived intensities of sweet (a weighted mean rating of glucose, fructose, aspartame, neohesperidin dihydrochalcone) and bitter (propylthiouracil, quinine, caffeine) substances in a large Australian healthy cohort from the Queensland Twin IMaging (QTIM, n = 559) study and the perceived intensity of quinine in a large U.S. healthy cohort from the Human Connectome Project (HCP, n = 1101). In QTIM, the volumes of 3 cortical (right cuneus gyrus, left transverse temporal gyrus, right inferior temporal gyrus) and one subcortical structure (both left and right caudate) were associated with more than one taste stimulus (P < 0.05) and tended to be associated with both sweet and bitter tastes in the same direction, suggesting these ROIs were more broadly tuned for taste sensation. A further 11 ROIs were associated with a specific taste (sweetness: 4; propylthiouracil: 3; caffeine: 2; quinine: 2). In HCP, volumes of 5 ROIs were associated with quinine bitterness. The quinine-left entorhinal cortex association was found in both QTIM (r = -0.12, P = 3.7 × 10) and HCP (r = -0.06, P = 2.0 × 10). This study provides the first evidence that, even in healthy people, variation in brain structure is associated with taste intensity ratings, and provides new insights into the brain gustatory circuit.
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http://dx.doi.org/10.1016/j.bbr.2019.01.046DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6470356PMC
May 2019

A Fast Method for Estimating Statistical Power of Multivariate GWAS in Real Case Scenarios: Examples from the Field of Imaging Genetics.

Behav Genet 2019 01 15;49(1):112-121. Epub 2018 Nov 15.

Queensland Brain Institute, The University of Queensland, Brisbane, 4072, Australia.

In GWAS of imaging phenotypes (e.g., by the ENIGMA and CHARGE consortia), the growing number of phenotypes considered presents a statistical challenge that other fields are not experiencing (e.g. psychiatry and the Psychiatric Genetics Consortium). However, the multivariate nature of MRI measurements may also be an advantage as many of the MRI phenotypes are correlated and multivariate methods could be considered. Here, we compared the statistical power of a multivariate GWAS versus the current univariate approach, which consists of multiple univariate analyses. To do so, we used results from twin models to estimate pertinent vectors of SNP effect sizes on brain imaging phenotypes, as well as the residual correlation matrices, necessary to estimate analytically the statistical power. We showed that for subcortical structure volumes and hippocampal subfields, a multivariate GWAS yields similar statistical power to the current univariate approach. Our analytical approach is as accurate but ~ 1000 times faster than simulations and we have released the code to facilitate the investigation of other scenarios, may they be outside the field of imaging genetics.
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http://dx.doi.org/10.1007/s10519-018-9936-9DOI Listing
January 2019

Dose response of the 16p11.2 distal copy number variant on intracranial volume and basal ganglia.

Mol Psychiatry 2020 03 3;25(3):584-602. Epub 2018 Oct 3.

Department of Psychiatry and Mental Health, Anzio Road, 7925, Cape Town, South Africa.

Carriers of large recurrent copy number variants (CNVs) have a higher risk of developing neurodevelopmental disorders. The 16p11.2 distal CNV predisposes carriers to e.g., autism spectrum disorder and schizophrenia. We compared subcortical brain volumes of 12 16p11.2 distal deletion and 12 duplication carriers to 6882 non-carriers from the large-scale brain Magnetic Resonance Imaging collaboration, ENIGMA-CNV. After stringent CNV calling procedures, and standardized FreeSurfer image analysis, we found negative dose-response associations with copy number on intracranial volume and on regional caudate, pallidum and putamen volumes (β = -0.71 to -1.37; P < 0.0005). In an independent sample, consistent results were obtained, with significant effects in the pallidum (β = -0.95, P = 0.0042). The two data sets combined showed significant negative dose-response for the accumbens, caudate, pallidum, putamen and ICV (P = 0.0032, 8.9 × 10, 1.7 × 10, 3.5 × 10 and 1.0 × 10, respectively). Full scale IQ was lower in both deletion and duplication carriers compared to non-carriers. This is the first brain MRI study of the impact of the 16p11.2 distal CNV, and we demonstrate a specific effect on subcortical brain structures, suggesting a neuropathological pattern underlying the neurodevelopmental syndromes.
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http://dx.doi.org/10.1038/s41380-018-0118-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7042770PMC
March 2020

Genetic Complexity of Cortical Structure: Differences in Genetic and Environmental Factors Influencing Cortical Surface Area and Thickness.

Cereb Cortex 2019 03;29(3):952-962

Queensland Brain Institute, University of Queensland, Brisbane QLD, Australia.

Quantifying the genetic architecture of the cerebral cortex is necessary for understanding disease and changes to the brain across the lifespan. Prior work shows that both surface area (SA) and cortical thickness (CT) are heritable. However, we do not yet understand the extent to which region-specific genetic factors (i.e., independent of global effects) play a dominant role in the regional patterning or inter-regional associations across the cortex. Using a population sample of young adult twins (N = 923), we show that the heritability of SA and CT varies widely across regions, generally independent of measurement error. When global effects are controlled for, we detected a complex pattern of genetically mediated clusters of inter-regional associations, which varied between hemispheres. There were generally weak associations between the SA of different regions, except within the occipital lobe, whereas CT was positively correlated within lobar divisions and negatively correlated across lobes, mostly due to genetic covariation. These findings were replicated in an independent sample of twins and siblings (N = 698) from the Human Connectome Project. The different genetic contributions to SA and CT across regions reveal the value of quantifying sources of covariation to appreciate the genetic complexity of cortical structures.
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http://dx.doi.org/10.1093/cercor/bhy002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6373676PMC
March 2019

Lingual Gyrus Surface Area Is Associated with Anxiety-Depression Severity in Young Adults: A Genetic Clustering Approach.

eNeuro 2018 Jan-Feb;5(1). Epub 2018 Jan 19.

Queensland Brain Institute, University of Queensland, Brisbane 4072, Australia.

Here we aimed to identify cortical endophenotypes for anxiety-depression. Our data-driven approach used vertex-wise genetic correlations (estimated from a twin sample: 157 monozygotic and 194 dizygotic twin pairs) to parcellate cortical thickness (CT) and surface area (SA) into genetically homogeneous regions (Chen et al., 2013). In an overlapping twin and sibling sample ( = 834; aged 15-29, 66% female), in those with anxiety-depression Somatic and Psychological Health Report (SPHERE) scores (Hickie et al., 2001) above median, we found a reduction of SA in an occipito-temporal cluster, which comprised part of the right lingual, fusiform and parahippocampal gyrii. A similar reduction was observed in the Human Connectome Project (HCP) sample ( = 890, age 22-37, 56.5% female) in those with Adult Self Report (ASR) DSM-oriented scores (Achenbach et al., 2005) in the 25-95% quantiles. A vertex-wise analysis identified the right lingual and, to a lesser extent the fusiform gyrus. Overall, the surface reduction explained by the anxiety-depression scores was modest ( = -0.10, 3rd order spline, and = -0.040, 1st order spline in the HCP). The discordant results in the top 5% of the anxiety-depression scores may be explained by differences in recruitment between the studies. However, we could not conclude whether this cortical region was an endophenotype for anxiety-depression as the genetic correlations did not reach significance, which we attribute to the modest effect size ( statistical power <10%).
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http://dx.doi.org/10.1523/ENEURO.0153-17.2017DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5773884PMC
January 2019
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