M156. CORTICAL NEUROANATOMICAL SIGNATURE OF SCHIZOTYPY IN 2,695 INDIVIDUALS ASSESSED IN A WORLDWIDE ENIGMA STUDY

Abstract Background Cortical neuroanatomical abnormalities have been reported along a continuum between individuals with chronic schizophrenia, first-episode psychosis, clinical high risk for psychosis, and healthy individuals self-reporting subclinical psychotic-like experiences (or schizotypy). Recently, the Schizophrenia Working Group within the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) consortium provided meta-analytic evidence for robust cortical thickness abnormalities in schizophrenia, while also indicating that these abnormalities are influenced by illness severity and treatment with antipsychotic medications. In this context, schizotypy research allows the investigation of cortical neuroanatomy associated with the expression of subclinical psychotic-like symptoms without the potential influence of a psychotic illness, its severity, or the use of antipsychotics. This study presents the first large-scale imaging meta-analysis of cortical thickness in schizotypy using standardized methods from 23 datasets worldwide. Methods Cortical thickness and surface area were assessed in MRI scans of 2,695 healthy individuals (mean [range] age of 29.1 [17–55.8], 46.3% male) who had also completed validated self-report schizotypy questionnaires. Each site processed their local T1-weighted MRI scans using FreeSurfer and, following the protocol outlined in the ENIGMA Schizophrenia Working Group study, extracted cortical thickness for 70 Desikan-Killiany (DK) atlas regions (34 regions per hemisphere + left and right hemisphere mean thickness). At each site, partial correlation analyses were performed between regional cortical thickness by ROI and total schizotypy scores in R, predicting the left, right and mean cortical thickness, adjusting for sex, age and site. Random-effects meta-analyses of partial correlation effect sizes for each of the DK atlas regions were performed using R’s metafor package. False discovery rate (pFDR < .05) was used to control for multiple comparisons. Results We found significant positive associations between subclinical psychotic-like experiences and mean cortical thickness of the medial orbitofrontal cortex (r = .077; pFDR = .006) and the frontal pole (r = .073; pFDR = .006). When assessed separately by hemisphere, meta-analysis revealed a significant positive association between subclinical psychotic-like experiences and cortical thickness of the left medial orbitofrontal cortex (r = .066; pFDR = .044), and at trend-level with the right medial orbitofrontal cortex (r = .062; pFDR = .053) and the left frontal pole (r = .062; pFDR = .053). No significant associations were observed for surface area. Discussion Worldwide cooperative analyses of large-scale brain imaging data support a profile of cortical thickness abnormalities involving prefrontal cortical regions positively related to schizotypy in healthy individuals. These findings are not secondary to potential influences of disease chronicity or antipsychotic medication on the neuroanatomical correlates of psychotic-like experiences. The directionality of the observed meta-analytical effects in schizotypy is opposite to those previously reported in patients with schizophrenia (i.e., thinner cortex). The present findings of increased thickness may indicate early microstructural deficits (e.g. in myelination) that contribute to vulnerability for psychosis. Alternatively, these may reflect mechanisms of resilience associated with the expression of subclinical manifestations of psychotic symptoms in otherwise healthy individuals.

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Thinner cortex is associated with psychosis onset in individuals at Clinical High Risk for Developing Psychosis: An ENIGMA Working Group mega-analysis

10.1101/2021.01.05.20248768 ◽

2021 ◽

Author(s):

Maria Jalbrzikowski ◽

Rebecca A. Hayes ◽

Stephen J. Wood ◽

Dorte Nordholm ◽

Juan H. Zhou ◽

...

Keyword(s):

High Risk ◽

Surface Area ◽

Cortical Thickness ◽

Working Group ◽

Large Scale ◽

Meta Analysis ◽

Clinical High Risk ◽

Postnatal Brain ◽

Mri Scans ◽

Subcortical Volume

AbstractImportanceThe ENIGMA clinical high risk for psychosis (CHR) initiative, the largest pooled CHR-neuroimaging sample to date, aims to discover robust neurobiological markers of psychosis risk in a sample with known heterogeneous outcomes.ObjectiveWe investigated baseline structural neuroimaging differences between CHR subjects and healthy controls (HC), and between CHR participants who later developed a psychotic disorder (CHR-PS+) and those who did not (CHR-PS-). We assessed associations with age by group and conversion status, and similarities between the patterns of effect size maps for psychosis conversion and those found in other large-scale psychosis studies.Design, Setting, and ParticipantsBaseline T1-weighted MRI data were pooled from 31 international sites participating in the ENIGMA CHR Working Group. MRI scans were processed using harmonized protocols and analyzed within a mega- and meta-analysis framework from January-October 2020.Main Outcome(s) and Measure(s)Measures of regional cortical thickness (CT), surface area (SA), and subcortical volumes were extracted from T1-weighted MRI scans. Independent variables were group (CHR, HC) and conversion status (CHR-PS+, CHR-PS-, HC).ResultsThe final dataset consisted of 3,169 participants (CHR=1,792, HC=1,377, age range: 9.5 to 39.8 years, 45% female). Using longitudinal clinical information, we identified CHR-PS+ (N=253) and CHR-PS-(N=1,234). CHR exhibited widespread thinner cortex compared to HC (average d=-0.125, range: −0.09 to −0.17), but not SA or subcortical volume. Thinner cortex in the fusiform, superior temporal, and paracentral regions was associated with psychosis conversion (average d=-0.22). Age showed a stronger negative association with left fusiform and left paracentral CT in HC, compared to CHR-PS+. Regional CT psychosis conversion effect sizes resembled patterns of CT alterations observed in other ENIGMA studies of psychosis.Conclusions and RelevanceWe provide evidence for widespread subtle CT reductions in CHR. The pattern of regions displaying greater CT alterations in CHR-PS+ were similar to those reported in other large-scale investigations of psychosis. Additionally, a subset of these regions displayed abnormal age associations. Widespread CT disruptions coupled with abnormal age associations in CHR may point to disruptions in postnatal brain developmental processes.Key PointsQuestionHow do baseline brain morphometric features relate to later psychosis conversion in individuals at clinical high risk (CHR)?FindingsIn the largest coordinated international analysis to date, reduced baseline cortical thickness, but not cortical surface area or subcortical volume, was more pronounced in CHR, in a manner highly consistent with thinner cortex in established psychosis. Regions that displayed greater cortical thinning in future psychosis converters additionally displayed abnormal associations with age.MeaningCHR status and later transition to psychosis is robustly associated with reduced cortical thickness. Abnormal age associations and specificity to cortical thickness may point to aberrant postnatal brain development in CHR, including pruning and myelination.

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Mapping cortical brain asymmetry in 17,141 healthy individuals worldwide via the ENIGMA Consortium

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1718418115 ◽

2018 ◽

Vol 115 (22) ◽

pp. E5154-E5163 ◽

Cited By ~ 115

Author(s):

Xiang-Zhen Kong ◽

Samuel R. Mathias ◽

Tulio Guadalupe ◽

David C. Glahn ◽

Barbara Franke ◽

...

Keyword(s):

Surface Area ◽

Cortical Thickness ◽

Meta Analysis ◽

Inferior Frontal Gyrus ◽

Population Level ◽

Brain Asymmetry ◽

Parahippocampal Gyrus ◽

Intracranial Volume ◽

Healthy Individuals ◽

Brain Organization

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.

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Cortical Thickness Trajectories across the Lifespan: Data from 17,075 healthy individuals aged 3-90 years

10.1101/2020.05.05.077834 ◽

2020 ◽

Cited By ~ 2

Author(s):

Sophia Frangou ◽

Amirhossein Modabbernia ◽

Gaelle E Doucet ◽

Efstathios Papachristou ◽

Steven CR Williams ◽

...

Keyword(s):

Cortical Thickness ◽

Large Scale ◽

Meta Analysis ◽

General Pattern ◽

Individual Variability ◽

Anterior Cingulate ◽

Healthy Individuals ◽

Large Scale Analysis ◽

Age Related ◽

Steep Decrease

AbstractDelineating age-related cortical trajectories in healthy individuals is critical given the association of cortical thickness with cognition and behaviour. Previous research has shown that deriving robust estimates of age-related brain morphometric changes requires large-scale studies. In response, we conducted a large-scale analysis of cortical thickness in 17,075 individuals aged 3-90 years by pooling data through the Lifespan Working group of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium. We used fractional polynomial (FP) regression to characterize age-related trajectories in cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma (LMS) method. Inter-individual variability was estimated using meta-analysis and one-way analysis of variance. Overall, cortical thickness peaked in childhood and had a steep decrease during the first 2-3 decades of life; thereafter, it showed a gradual monotonic decrease which was steeper in men than in women particularly in middle-life. Notable exceptions to this general pattern were entorhinal, temporopolar and anterior cingulate cortices. Inter-individual 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 reconcile uncertainties about age-related trajectories of cortical thickness; the centile values provide estimates of normative variance in cortical thickness, and may assist in detecting abnormal deviations in cortical thickness, and associated behavioural, cognitive and clinical outcomes.

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Quantifying the Polygenic Architecture of the Human Cerebral Cortex: Extensive Genetic Overlap between Cortical Thickness and Surface Area

Cerebral Cortex ◽

10.1093/cercor/bhaa146 ◽

2020 ◽

Vol 30 (10) ◽

pp. 5597-5603 ◽

Cited By ~ 3

Author(s):

Dennis van der Meer ◽

Oleksandr Frei ◽

Tobias Kaufmann ◽

Chi-Hua Chen ◽

Wesley K Thompson ◽

...

Keyword(s):

Surface Area ◽

Cortical Thickness ◽

Large Scale ◽

Gaussian Mixture ◽

Total Surface Area ◽

Brain Morphology ◽

Genetic Determinants ◽

Genetic Predictors ◽

Genetic Overlap ◽

Causal Variants

Abstract The thickness of the cerebral cortical sheet and its surface area are highly heritable traits thought to have largely distinct polygenic architectures. Despite large-scale efforts, the majority of their genetic determinants remain unknown. Our ability to identify causal genetic variants can be improved by employing brain measures that better map onto the biology we seek to understand. Such measures may have fewer variants but with larger effects, that is, lower polygenicity and higher discoverability. Using Gaussian mixture modeling, we estimated the number of causal variants shared between mean cortical thickness and total surface area, as well as the polygenicity and discoverability of regional measures. We made use of UK Biobank data from 30 880 healthy White European individuals (mean age 64.3, standard deviation 7.5, 52.1% female). We found large genetic overlap between total surface area and mean thickness, sharing 4016 out of 7941 causal variants. Regional surface area was more discoverable (P = 2.6 × 10−6) and less polygenic (P = 0.004) than regional thickness measures. These findings may serve as a roadmap for improved future GWAS studies; knowledge of which measures are most discoverable may be used to boost identification of genetic predictors and thereby gain a better understanding of brain morphology.

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Brain Cortical Thickness and Surface Area Correlates of Neurocognitive Performance in Patients with Schizophrenia, Bipolar Disorder, and Healthy Adults

Journal of the International Neuropsychological Society ◽

10.1017/s1355617711001081 ◽

2011 ◽

Vol 17 (6) ◽

pp. 1080-1093 ◽

Cited By ~ 52

Author(s):

C.B. Hartberg ◽

K. Sundet ◽

L.M. Rimol ◽

U.K. Haukvik ◽

E.H. Lange ◽

...

Keyword(s):

Bipolar Disorder ◽

Working Memory ◽

Surface Area ◽

Cortical Thickness ◽

Negative Relationship ◽

Anterior Cingulate ◽

Neurocognitive Functioning ◽

Healthy Controls ◽

Neurocognitive Performance ◽

Mri Scans

AbstractRelationships between cortical brain structure and neurocognitive functioning have been reported in schizophrenia, but findings are inconclusive, and only a few studies in bipolar disorder have addressed this issue. This is the first study to directly compare relationships between cortical thickness and surface area with neurocognitive functioning in patients with schizophrenia (n = 117) and bipolar disorder (n = 121) and healthy controls (n = 192). MRI scans were obtained, and regional cortical thickness and surface area measurements were analyzed for relationships with test scores from 6 neurocognitive domains. In the combined sample, cortical thickness in the right rostral anterior cingulate was inversely related to working memory, and cortical surface area in four frontal and temporal regions were positively related to neurocognitive functioning. A positive relationship between left transverse temporal thickness and processing speed was specific to schizophrenia. A negative relationship between right temporal pole thickness and working memory was specific to bipolar disorder. In conclusion, significant cortical structure/function relationships were found in a large sample of healthy controls and patients with schizophrenia or bipolar disorder. The differences that were found between schizophrenia and bipolar may indicate differential relationship patterns in the two disorders, which may be of relevance for understanding the underlying pathophysiology. (JINS, 2011, 17, 1080–1093)

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Toward a Global and Reproducible Science for Brain Imaging in Neurotrauma: The ENIGMA Adult Moderate/Severe Traumatic Brain Injury Working Group

10.31234/osf.io/jnsb2 ◽

2019 ◽

Cited By ~ 1

Author(s):

Alexander Olsen ◽

Talin Babikian ◽

Erin D. Bigler ◽

Karen Caeyenberghs ◽

Virginia Conde ◽

...

Keyword(s):

Traumatic Brain Injury ◽

Data Analysis ◽

Brain Injury ◽

Working Group ◽

Large Scale ◽

Functional Neuroimaging ◽

Meta Analysis ◽

Small Sample ◽

Mortality And Morbidity ◽

Neuroimaging Data

The global burden of mortality and morbidity caused by traumatic brain injury (TBI) is significant and the heterogeneity of TBI patients and the relatively small sample sizes of most current neuroimaging studies is a major challenge for scientific advances and clinical translation. The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Adult moderate/severe TBI (AMS-TBI) working group aims to be a driving force for new discoveries in AMS-TBI by providing researchers world-wide with an effective framework and platform for large-scale cross-border collaboration and data sharing. Based on the principles of transparency, rigor, reproducibility and collaboration, we will facilitate the development and dissemination of multiscale and big data analysis pipelines for harmonized analyses in AMS-TBI using structural and functional neuroimaging in combination with nonimaging biomarkers, genetics, as well as clinical and behavioral measures. Ultimately, we will offer investigators an unprecedented opportunity to test important hypotheses about recovery and morbidity in AMS-TBI by taking advantage of our robust methods for largescale neuroimaging data analysis. In this consensus statement we outline the working group’s short-term, intermediate, and long-term goals.

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Enigma-collaborative Analyses of Neuroimaging eop Data: What have we Achieved?

European Psychiatry ◽

10.1016/j.eurpsy.2017.01.048 ◽

2017 ◽

Vol 41 (S1) ◽

pp. S60-S60

Author(s):

I. Agartz ◽

V. Lonning ◽

R. Smelror ◽

M. Lundberg ◽

T. Edbom ◽

...

Keyword(s):

Working Group ◽

Developmental Trajectories ◽

Meta Analysis ◽

Third Ventricle ◽

Grey Matter Volume ◽

Intracranial Volume ◽

Significant Group ◽

Brain Volumes ◽

Patients Âgés ◽

Mri Scans

IntroductionThe ENIGMA-EOP collaboration aims to identify structural phenotypic markers that robustly discriminate adolescents with early-onset psychosis (EOP) from healthy controls through mega- or meta-analysis of magnetic resonance imaging (MR) data. Through larger samples we will obtain sufficient power to detect the brain structural correlates, overcome some of the clinical heterogeneity and characterize the developmental trajectories.MethodsMultiple linear regression was used to investigate structural brain differences in two Scandinavian adolescent EOP cohorts (altogether 50 patients; ages 12.1-18.3 years (mean 16.4 years), 60% female; 68 controls; ages 12.0-18.8 years (mean 16.2 years), 62% female) acquired on two different 3 T GE MRI scanners. The statistical analysis included site as a covariate in addition to age, sex and intracranial volume (ICV). The results are presented by p-values, Cohens's-d effect size and with an indication of directionality. MRI scans were processed following the ENIGMA (http://enigma.ini.usc.edu/) structural image processing protocols using FreeSurfer (Fischl 2012) version 5.3.0 to measure subcortical brain volumes.ResultsPreliminary results show significant or trend-significant group effects on right amygdala (P = 0.001, d = 0.33, patients < controls), total grey matter volume (P = 0.037, d = 0.21, patients < controls), ICV (P = 0.028, d = 0.22, patients < controls) and third ventricle (P = 0.067, d = 0.19, patients > controls). Sub-analyses in the two individual groups show overlapping findings in right amygdala. Previously reported enlarged lateral and 4th ventricles, and caudate, from a similar Scandinavian adolescent EOP cohort (Juuhl-Langseth, 2012) were not replicated.ConclusionThere is a need for larger subject samples in EOP to better capture disease mechanisms. Research groups interested in participating can join ENIGMA-EOP through: http://enigma.ini.usc.edu/ongoing/enigma-eop-working-group/.Disclosure of interestThe authors have not supplied their declaration of competing interest.

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The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain-behavior relationships after stroke

10.31234/osf.io/wu7mh ◽

2020 ◽

Cited By ~ 1

Author(s):

Sook-Lei Liew ◽

Artemis Zavaliangos-Petropulu ◽

Neda Jahanshad ◽

Catherine E. Lang ◽

Kathryn S. Hayward ◽

...

Keyword(s):

Big Data ◽

Working Group ◽

Large Scale ◽

Meta Analysis ◽

Brain Magnetic Resonance Imaging ◽

Stroke Recovery ◽

Data Harmonization ◽

Stroke Research ◽

Brain And Behavior ◽

Data Collaboration

The goal of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Stroke Recovery working group is to understand brain and behavior relationships using well-powered meta- and mega-analytic approaches. ENIGMA Stroke Recovery has data from over 1,800 stroke patients collected across 32 research sites and 10 countries around the world, comprising the largest multi-site retrospective stroke data collaboration to date. This paper outlines the efforts taken by the ENIGMA Stroke Recovery working group to develop neuroinformatics protocols and methods to manage multi-site stroke brain magnetic resonance imaging (MRI), behavioral and demographics data. Specifically, the processes for scalable data intake and pre-processing, multi-site data harmonization, and large-scale stroke lesion analysis are described, and challenges unique to this type of big data collaboration in stroke research are discussed. Finally, future directions and limitations, as well as recommendations for improved data harmonization through prospective data collection and data management, are provided.

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Altered structural brain asymmetry in autism spectrum disorder: large-scale analysis via the ENIGMA Consortium

10.1101/570655 ◽

2019 ◽

Cited By ~ 2

Author(s):

Merel C. Postema ◽

Daan van Rooij ◽

Evdokia Anagnostou ◽

Celso Arango ◽

Guillaume Auzias ◽

...

Keyword(s):

Autism Spectrum Disorder ◽

Surface Area ◽

Cortical Thickness ◽

Large Scale ◽

Autism Spectrum ◽

Brain Asymmetry ◽

Scale Analysis ◽

Large Scale Analysis ◽

Cortical Regions ◽

Structural Brain

AbstractBackgroundLeft-right asymmetry is an important organizing feature of the healthy brain. Various studies have reported altered structural brain asymmetry in autism spectrum disorder (ASD). However, findings have been inconsistent, likely due to limited sample sizes and low statistical power.MethodsWe investigated 1,774 subjects with ASD and 1,809 controls, from 54 datasets, for differences in the asymmetry of thickness and surface area of 34 cerebral cortical regions. We also examined global hemispheric measures of cortical thickness and area asymmetry, and volumetric asymmetries of subcortical structures. Data were obtained via the ASD Working Group of the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) consortium. T1-weighted MRI data were processed with a single protocol using FreeSurfer and the Desikan-Killiany atlas.ResultsASD was significantly associated with reduced leftward asymmetry of total hemispheric average cortical thickness, compared to controls. Eight regional thickness asymmetries, distributed over the cortex, also showed significant associations with diagnosis after correction for multiple comparisons, for which asymmetry was again generally lower in ASD versus controls. In addition, the medial orbitofrontal surface area was less rightward asymmetric in ASD than controls, and the putamen volume was more leftward asymmetric in ASD than controls. The largest effect size had Cohen’sd= 0.15. Most effects did not depend on age, sex, IQ, or disorder severity.ConclusionAltered lateralized neurodevelopment is suggested in ASD, affecting widespread cortical regions with diverse functions. Large-scale analysis was necessary to reliably detect, and accurately describe, subtle alterations of structural brain asymmetry in this disorder.

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Quantifying the polygenic architecture of the human cerebral cortex: Extensive genetic overlap between cortical thickness and surface area

10.1101/868307 ◽

2019 ◽

Author(s):

Dennis van der Meer ◽

Oleksandr Frei ◽

Tobias Kaufmann ◽

Chi-Hua Chen ◽

Wesley K. Thompson ◽

...

Keyword(s):

Surface Area ◽

Cortical Thickness ◽

Large Scale ◽

Gaussian Mixture ◽

Total Surface Area ◽

Brain Morphology ◽

Genetic Determinants ◽

Genetic Predictors ◽

Genetic Overlap ◽

Causal Variants

ABSTRACTIntroductionThe thickness of the cerebral cortical sheet and its surface area are highly heritable traits thought to have largely distinct polygenic architectures. Despite large-scale efforts, the majority of their genetic determinants remains unknown. Our ability to identify causal genetic variants can be improved by employing better delineated, less noisy brain measures that better map onto the biology we seek to understand. Such measures may have fewer variants but with larger effects, i.e. lower polygenicity and higher discoverability.MethodsUsing Gaussian mixture modeling, we estimated the number of causal variants shared between mean cortical thickness and total surface area. We further determined the polygenicity and discoverability of regional cortical measures from five often-employed parcellation schemes. We made use of UK Biobank data from 31,312 healthy White European individuals (mean age 55.5, standard deviation (SD) 7.4, 52.1% female).ResultsContrary to previous reports, we found large genetic overlap between total surface area and mean thickness, sharing 4427 out of 7150 causal variants. Regional surface area was more discoverable (p=4.1×10−6) and less polygenic (p=.007) than regional thickness measures. We further found that genetically-informed and less granular parcellation schemes had highest discoverability, with no differences in polygenicity.ConclusionsThese findings may serve as a roadmap for improved future GWAS studies; Knowledge of which measures or parcellations are most discoverable, as well as the genetic overlap between these measures, may be used to boost identification of genetic predictors and thereby gain a better understanding of brain morphology.

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