Publications by authors named "Neda Jahanshad"

239 Publications

Robust Cortical Thickness Morphometry of Neonatal Brain and Systematic Evaluation Using Multi-Site MRI Datasets.

Front Neurosci 2021 17;15:650082. Epub 2021 Mar 17.

Department of Neurology, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States.

The human brain grows the most dramatically during the perinatal and early post-natal periods, during which pre-term birth or perinatal injury that may alter brain structure and lead to developmental anomalies. Thus, characterizing cortical thickness of developing brains remains an important goal. However, this task is often complicated by inaccurate cortical surface extraction due to small-size brains. Here, we propose a novel complex framework for the reconstruction of neonatal WM and pial surfaces, accounting for large partial volumes due to small-size brains. The proposed approach relies only on T1-weighted images unlike previous T2-weighted image-based approaches while only T1-weighted images are sometimes available under the different clinical/research setting. Deep neural networks are first introduced to the neonatal magnetic resonance imaging (MRI) pipeline to address the mis-segmentation of brain tissues. Furthermore, this pipeline enhances cortical boundary delineation using combined models of the cerebrospinal fluid (CSF)/GM boundary detection with edge gradient information and a new skeletonization of sulcal folding where no CSF voxels are seen due to the limited resolution. We also proposed a systematic evaluation using three independent datasets comprising 736 pre-term and 97 term neonates. Qualitative assessment for reconstructed cortical surfaces shows that 86.9% are rated as accurate across the three site datasets. In addition, our landmark-based evaluation shows that the mean displacement of the cortical surfaces from the true boundaries was less than a voxel size (0.532 ± 0.035 mm). Evaluating the proposed pipeline (namely NEOCIVET 2.0) shows the robustness and reproducibility across different sites and different age-groups. The mean cortical thickness measured positively correlated with post-menstrual age (PMA) at scan ( < 0.0001); Cingulate cortical areas grew the most rapidly whereas the inferior temporal cortex grew the least rapidly. The range of the cortical thickness measured was biologically congruent (1.3 mm at 28 weeks of PMA to 1.8 mm at term equivalent). Cortical thickness measured on T1 MRI using NEOCIVET 2.0 was compared with that on T2 using the established dHCP pipeline. It was difficult to conclude that either T1 or T2 imaging is more ideal to construct cortical surfaces. NEOCIVET 2.0 has been open to the public through CBRAIN (https://mcin-cnim.ca/technology/cbrain/), a web-based platform for processing brain imaging data.
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http://dx.doi.org/10.3389/fnins.2021.650082DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8010150PMC
March 2021

Neuroimaging Advances in Diagnosis and Differentiation of HIV, Comorbidities, and Aging in the cART Era.

Curr Top Behav Neurosci 2021 Mar 30. Epub 2021 Mar 30.

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

In the "cART era" of more widely available and accessible treatment, aging and HIV-related comorbidities, including symptoms of brain dysfunction, remain common among HIV-infected individuals on suppressive treatment. A better understanding of the neurobiological consequences of HIV infection is essential for developing thorough treatment guidelines and for optimizing long-term neuropsychological outcomes and overall brain health. In this chapter, we first summarize magnetic resonance imaging (MRI) methods used in over two decades of neuroHIV research. These methods evaluate brain volumetric differences and circuitry disruptions in adults living with HIV, and help map clinical correlations with brain function and tissue microstructure. We then introduce and discuss aging and associated neurological complications in people living with HIV, and processes by which infection may contribute to the risk for late-onset dementias. We describe how new technologies and large-scale international collaborations are helping to disentangle the effect of genetic and environmental risk factors on brain aging and neurodegenerative diseases. We provide insights into how these advances, which are now at the forefront of Alzheimer's disease research, may advance the field of neuroHIV. We conclude with a summary of how we see the field of neuroHIV research advancing in the decades to come and highlight potential clinical implications.
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http://dx.doi.org/10.1007/7854_2021_221DOI Listing
March 2021

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

Authors:
Ida E Sønderby Dennis van der Meer Clara Moreau Tobias Kaufmann G Bragi Walters Maria Ellegaard Abdel Abdellaoui David Ames Katrin Amunts Micael Andersson Nicola J Armstrong Manon Bernard Nicholas B Blackburn John Blangero Dorret I Boomsma Henry Brodaty Rachel M Brouwer Robin Bülow Rune Bøen Wiepke Cahn Vince D Calhoun Svenja Caspers Christopher R K Ching Sven Cichon Simone Ciufolini Benedicto Crespo-Facorro Joanne E Curran Anders M Dale Shareefa Dalvie Paola Dazzan Eco J C de Geus Greig I de Zubicaray Sonja M C de Zwarte Sylvane Desrivieres Joanne L Doherty Gary Donohoe Bogdan Draganski Stefan Ehrlich Else Eising Thomas Espeseth Kim Fejgin Simon E Fisher Tormod Fladby Oleksandr Frei Vincent Frouin Masaki Fukunaga Thomas Gareau Tian Ge David C Glahn Hans J Grabe Nynke A Groenewold Ómar Gústafsson Jan Haavik Asta K Haberg Jeremy Hall Ryota Hashimoto Jayne Y Hehir-Kwa Derrek P Hibar Manon H J Hillegers Per Hoffmann Laurena Holleran Avram J Holmes Georg Homuth Jouke-Jan Hottenga Hilleke E Hulshoff Pol Masashi Ikeda Neda Jahanshad Christiane Jockwitz Stefan Johansson Erik G Jönsson Niklas R Jørgensen Masataka Kikuchi Emma E M Knowles Kuldeep Kumar Stephanie Le Hellard Costin Leu David E J Linden Jingyu Liu Arvid Lundervold Astri Johansen Lundervold Anne M Maillard Nicholas G Martin Sandra Martin-Brevet Karen A Mather Samuel R Mathias Katie L McMahon Allan F McRae Sarah E Medland Andreas Meyer-Lindenberg Torgeir Moberget Claudia Modenato Jennifer Monereo Sánchez Derek W Morris Thomas W Mühleisen Robin M Murray Jacob Nielsen Jan E Nordvik Lars Nyberg Loes M Olde Loohuis Roel A Ophoff Michael J Owen Tomas Paus Zdenka Pausova Juan M Peralta G Bruce Pike Carlos Prieto Erin B Quinlan Céline S Reinbold Tiago Reis Marques James J H Rucker Perminder S Sachdev Sigrid B Sando Peter R Schofield Andrew J Schork Gunter Schumann Jean Shin Elena Shumskaya Ana I Silva Sanjay M Sisodiya Vidar M Steen Dan J Stein Lachlan T Strike Ikuo K Suzuki Christian K Tamnes Alexander Teumer Anbupalam Thalamuthu Diana Tordesillas-Gutiérrez Anne Uhlmann Magnus O Ulfarsson Dennis van 't Ent Marianne B M van den Bree Pierre Vanderhaeghen Evangelos Vassos Wei Wen Katharina Wittfeld Margaret J Wright Ingrid Agartz Srdjan Djurovic Lars T Westlye Hreinn Stefansson Kari Stefansson Sébastien Jacquemont Paul M Thompson Ole A Andreassen

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

NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.

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

Analysis of structural brain asymmetries in attention-deficit/hyperactivity disorder in 39 datasets.

Authors:
Merel C Postema Martine Hoogman Sara Ambrosino Philip Asherson Tobias Banaschewski Cibele E Bandeira Alexandr Baranov Claiton H D Bau Sarah Baumeister Ramona Baur-Streubel Mark A Bellgrove Joseph Biederman Janita Bralten Daniel Brandeis Silvia Brem Jan K Buitelaar Geraldo F Busatto Francisco X Castellanos Mara Cercignani Tiffany M Chaim-Avancini Kaylita C Chantiluke Anastasia Christakou David Coghill Annette Conzelmann Ana I Cubillo Renata B Cupertino Patrick de Zeeuw Alysa E Doyle Sarah Durston Eric A Earl Jeffery N Epstein Thomas Ethofer Damien A Fair Andreas J Fallgatter Stephen V Faraone Thomas Frodl Matt C Gabel Tinatin Gogberashvili Eugenio H Grevet Jan Haavik Neil A Harrison Catharina A Hartman Dirk J Heslenfeld Pieter J Hoekstra Sarah Hohmann Marie F Høvik Terry L Jernigan Bernd Kardatzki Georgii Karkashadze Clare Kelly Gregor Kohls Kerstin Konrad Jonna Kuntsi Luisa Lazaro Sara Lera-Miguel Klaus-Peter Lesch Mario R Louza Astri J Lundervold Charles B Malpas Paulo Mattos Hazel McCarthy Leyla Namazova-Baranova Rosa Nicolau Joel T Nigg Stephanie E Novotny Eileen Oberwelland Weiss Ruth L O'Gorman Tuura Jaap Oosterlaan Bob Oranje Yannis Paloyelis Paul Pauli Felipe A Picon Kerstin J Plessen J Antoni Ramos-Quiroga Andreas Reif Liesbeth Reneman Pedro G P Rosa Katya Rubia Anouk Schrantee Lizanne J S Schweren Jochen Seitz Philip Shaw Tim J Silk Norbert Skokauskas Juan C Soliva Vila Michael C Stevens Gustavo Sudre Leanne Tamm Fernanda Tovar-Moll Theo G M van Erp Alasdair Vance Oscar Vilarroya Yolanda Vives-Gilabert Georg G von Polier Susanne Walitza Yuliya N Yoncheva Marcus V Zanetti Georg C Ziegler David C Glahn Neda Jahanshad Sarah E Medland Paul M Thompson Simon E Fisher Barbara Franke Clyde Francks

J Child Psychol Psychiatry 2021 Mar 22. Epub 2021 Mar 22.

Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands.

Objective: Some studies have suggested alterations of structural brain asymmetry in attention-deficit/hyperactivity disorder (ADHD), but findings have been contradictory and based on small samples. Here, we performed the largest ever analysis of brain left-right asymmetry in ADHD, using 39 datasets of the ENIGMA consortium.

Methods: We analyzed asymmetry of subcortical and cerebral cortical structures in up to 1,933 people with ADHD and 1,829 unaffected controls. Asymmetry Indexes (AIs) were calculated per participant for each bilaterally paired measure, and linear mixed effects modeling was applied separately in children, adolescents, adults, and the total sample, to test exhaustively for potential associations of ADHD with structural brain asymmetries.

Results: There was no evidence for altered caudate nucleus asymmetry in ADHD, in contrast to prior literature. In children, there was less rightward asymmetry of the total hemispheric surface area compared to controls (t = 2.1, p = .04). Lower rightward asymmetry of medial orbitofrontal cortex surface area in ADHD (t = 2.7, p = .01) was similar to a recent finding for autism spectrum disorder. There were also some differences in cortical thickness asymmetry across age groups. In adults with ADHD, globus pallidus asymmetry was altered compared to those without ADHD. However, all effects were small (Cohen's d from -0.18 to 0.18) and would not survive study-wide correction for multiple testing.

Conclusion: Prior studies of altered structural brain asymmetry in ADHD were likely underpowered to detect the small effects reported here. Altered structural asymmetry is unlikely to provide a useful biomarker for ADHD, but may provide neurobiological insights into the trait.
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http://dx.doi.org/10.1111/jcpp.13396DOI Listing
March 2021

White matter microstructure and its relation to clinical features of obsessive-compulsive disorder: findings from the ENIGMA OCD Working Group.

Transl Psychiatry 2021 Mar 17;11(1):173. Epub 2021 Mar 17.

Laboratory of Neuropsychiatry, Department of Clinical and Behavioral Neurology, IRCCS Santa Lucia Foundation, Rome, Italy.

Microstructural alterations in cortico-subcortical connections are thought to be present in obsessive-compulsive disorder (OCD). However, prior studies have yielded inconsistent findings, perhaps because small sample sizes provided insufficient power to detect subtle abnormalities. Here we investigated microstructural white matter alterations and their relation to clinical features in the largest dataset of adult and pediatric OCD to date. We analyzed diffusion tensor imaging metrics from 700 adult patients and 645 adult controls, as well as 174 pediatric patients and 144 pediatric controls across 19 sites participating in the ENIGMA OCD Working Group, in a cross-sectional case-control magnetic resonance study. We extracted measures of fractional anisotropy (FA) as main outcome, and mean diffusivity, radial diffusivity, and axial diffusivity as secondary outcomes for 25 white matter regions. We meta-analyzed patient-control group differences (Cohen's d) across sites, after adjusting for age and sex, and investigated associations with clinical characteristics. Adult OCD patients showed significant FA reduction in the sagittal stratum (d = -0.21, z = -3.21, p = 0.001) and posterior thalamic radiation (d = -0.26, z = -4.57, p < 0.0001). In the sagittal stratum, lower FA was associated with a younger age of onset (z = 2.71, p = 0.006), longer duration of illness (z = -2.086, p = 0.036), and a higher percentage of medicated patients in the cohorts studied (z = -1.98, p = 0.047). No significant association with symptom severity was found. Pediatric OCD patients did not show any detectable microstructural abnormalities compared to controls. Our findings of microstructural alterations in projection and association fibers to posterior brain regions in OCD are consistent with models emphasizing deficits in connectivity as an important feature of this disorder.
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http://dx.doi.org/10.1038/s41398-021-01276-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7969744PMC
March 2021

White matter brain aging in relationship to schizophrenia and its cognitive deficit.

Schizophr Res 2021 Mar 2;230:9-16. Epub 2021 Mar 2.

Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA; Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, USA. Electronic address:

We hypothesized that cerebral white matter deficits in schizophrenia (SZ) are driven in part by accelerated white matter aging and are associated with cognitive deficits. We used a machine learning model to predict individual age from diffusion tensor imaging features and calculated the delta age (Δage) as the difference between predicted and chronological age. Through this approach, we translated multivariate white matter imaging features into an age-scaled metric and used it to test the temporal trends of accelerated aging-related white matter deficit in SZ and its association with the cognition. A feature selection procedure was first employed to choose fractional anisotropy values in 34 of 43 white fiber tracts. Using these features, a machine learning model was trained based on a training set consisted of 107 healthy controls (HC). The brain age of 166 SZs and 107 HCs in the testing set were calculated using this model. Then, we examined the SZ-HC group effect on Δage and whether this effect was moderated by chronological age using the regression spline model. The results showed that Δage was significantly elevated in the age > 30 group in patients (p < 0.001) but not in age ≤ 30 group (p = 0.364). Δage in patients was significantly and negatively associated with both working memory (β = -0.176, p = 0.007) and processing speed (β = -0.519, p = 0.035) while adjusting sex and chronological age. Overall, these findings indicate that the Δage is elevated in SZs and become significantly from the third decade of life; the increase of Δage in SZs is associated with the declined neurocognitive performance.
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http://dx.doi.org/10.1016/j.schres.2021.02.003DOI Listing
March 2021

Overlap in genetic risk for cross-disorder vulnerability to mental disorders and genetic risk for altered subcortical brain volumes.

J Affect Disord 2021 Mar 12;282:740-756. Epub 2021 Jan 12.

Department of Psychiatry and MRC Unit on Risk & Resilience, University of Cape Town, Cape Town, South Africa.

Background: There have been considerable recent advances in understanding the genetic architecture of psychiatric disorders as well as the underlying neurocircuitry. However, there is little work on the concordance of genetic variations that increase risk for cross-disorder vulnerability, and those that influence subcortical brain structures. We undertook a genome-wide investigation of the genetic overlap between cross-disorder vulnerability to psychiatric disorders (p-factor) and subcortical brain structures.

Methods: Summary statistics were obtained from the PGC cross-disorder genome-wide association study (GWAS) (N= 232,964, N= 494,162) and the CHARGE-ENIGMA subcortical brain volumes GWAS (N=38,851). SNP effect concordance analysis (SECA) was used to assess pleiotropy and concordance. Linkage Disequilibrium (LD) Score Regression and ρ-HESS were used to assess genetic correlation and conditional false discovery (cFDR) was used to identify variants associated with p-factor, conditional on the variants association with subcortical brain volumes.

Results: Evidence of global pleiotropy between p-factor and all subcortical brain regions was observed. Risk variants for p-factor correlated negatively with brainstem. A total of 787 LD-independent variants were significantly associated with p-factor when conditioned on the subcortical GWAS results. Gene set enrichment analysis of these variants implicated actin binding and neuronal regulation.

Limitations: SECA could be biased due to the potential presence of overlapping study participants in the p-factor and subcortical GWASs.

Conclusion: Findings of genome-wide pleiotropy and possible concordance between genetic variants that contribute to p-factor and smaller brainstem volumes, are consistent with previous work. cFDR results highlight actin binding and neuron regulation as key underlying mechanisms. Further fine-grained delineation of these mechanisms is needed to advance the field.
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http://dx.doi.org/10.1016/j.jad.2020.12.062DOI Listing
March 2021

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

Authors:
Sophia Frangou Amirhossein Modabbernia Steven C R Williams Efstathios Papachristou Gaelle E Doucet Ingrid Agartz Moji Aghajani Theophilus N Akudjedu Anton Albajes-Eizagirre Dag Alnaes Kathryn I Alpert Micael Andersson Nancy C Andreasen Ole A Andreassen Philip Asherson Tobias Banaschewski Nuria Bargallo Sarah Baumeister Ramona Baur-Streubel Alessandro Bertolino Aurora Bonvino Dorret I Boomsma Stefan Borgwardt Josiane Bourque Daniel Brandeis Alan Breier Henry Brodaty Rachel M Brouwer Jan K Buitelaar Geraldo F Busatto Randy L Buckner Vincent Calhoun Erick J Canales-Rodríguez Dara M Cannon Xavier Caseras Francisco X Castellanos Simon Cervenka Tiffany M Chaim-Avancini Christopher R K Ching Victoria Chubar Vincent P Clark Patricia Conrod Annette Conzelmann Benedicto Crespo-Facorro Fabrice Crivello Eveline A Crone Anders M Dale Udo Dannlowski Christopher Davey Eco J C de Geus Lieuwe de Haan Greig I de Zubicaray Anouk den Braber Erin W Dickie Annabella Di Giorgio Nhat Trung Doan Erlend S Dørum Stefan Ehrlich Susanne Erk Thomas Espeseth Helena Fatouros-Bergman Simon E Fisher Jean-Paul Fouche Barbara Franke Thomas Frodl Paola Fuentes-Claramonte David C Glahn Ian H Gotlib Hans-Jörgen Grabe Oliver Grimm Nynke A Groenewold Dominik Grotegerd Oliver Gruber Patricia Gruner Rachel E Gur Ruben C Gur Tim Hahn Ben J Harrison Catharine A Hartman Sean N Hatton Andreas Heinz Dirk J Heslenfeld Derrek P Hibar Ian B Hickie Beng-Choon Ho Pieter J Hoekstra Sarah Hohmann Avram J Holmes Martine Hoogman Norbert Hosten Fleur M Howells Hilleke E Hulshoff Pol Chaim Huyser Neda Jahanshad Anthony James Terry L Jernigan Jiyang Jiang Erik G Jönsson John A Joska Rene Kahn Andrew Kalnin Ryota Kanai Marieke Klein Tatyana P Klyushnik Laura Koenders Sanne Koops Bernd Krämer Jonna Kuntsi Jim Lagopoulos Luisa Lázaro Irina Lebedeva Won Hee Lee Klaus-Peter Lesch Christine Lochner Marise W J Machielsen Sophie Maingault Nicholas G Martin Ignacio Martínez-Zalacaín David Mataix-Cols Bernard Mazoyer Colm McDonald Brenna C McDonald Andrew M McIntosh Katie L McMahon Genevieve McPhilemy Susanne Meinert José M Menchón Sarah E Medland Andreas Meyer-Lindenberg Jilly Naaijen Pablo Najt Tomohiro Nakao Jan E Nordvik Lars Nyberg Jaap Oosterlaan Víctor Ortiz-García de la Foz Yannis Paloyelis Paul Pauli Giulio Pergola Edith Pomarol-Clotet Maria J Portella Steven G Potkin Joaquim Radua Andreas Reif Daniel A Rinker Joshua L Roffman Pedro G P Rosa Matthew D Sacchet Perminder S Sachdev Raymond Salvador Pascual Sánchez-Juan Salvador Sarró Theodore D Satterthwaite Andrew J Saykin Mauricio H Serpa Lianne Schmaal Knut Schnell Gunter Schumann Kang Sim Jordan W Smoller Iris Sommer Carles Soriano-Mas Dan J Stein Lachlan T Strike Suzanne C Swagerman Christian K Tamnes Henk S Temmingh Sophia I Thomopoulos Alexander S Tomyshev Diana Tordesillas-Gutiérrez Julian N Trollor Jessica A Turner Anne Uhlmann Odile A van den Heuvel Dennis van den Meer Nic J A van der Wee Neeltje E M van Haren Dennis van 't Ent Theo G M van Erp Ilya M Veer Dick J Veltman Aristotle Voineskos Henry Völzke Henrik Walter Esther Walton Lei Wang Yang Wang Thomas H Wassink Bernd Weber Wei Wen John D West Lars T Westlye Heather Whalley Lara M Wierenga Katharina Wittfeld Daniel H Wolf Amanda Worker Margaret J Wright Kun Yang Yulyia Yoncheva Marcus V Zanetti Georg C Ziegler Paul M Thompson Danai Dima

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

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

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.

Authors:
Danai Dima Amirhossein Modabbernia Efstathios Papachristou Gaelle E Doucet Ingrid Agartz Moji Aghajani Theophilus N Akudjedu Anton Albajes-Eizagirre Dag Alnaes Kathryn I Alpert Micael Andersson Nancy C Andreasen Ole A Andreassen Philip Asherson Tobias Banaschewski Nuria Bargallo Sarah Baumeister Ramona Baur-Streubel Alessandro Bertolino Aurora Bonvino Dorret I Boomsma Stefan Borgwardt Josiane Bourque Daniel Brandeis Alan Breier Henry Brodaty Rachel M Brouwer Jan K Buitelaar Geraldo F Busatto Randy L Buckner Vincent Calhoun Erick J Canales-Rodríguez Dara M Cannon Xavier Caseras Francisco X Castellanos Simon Cervenka Tiffany M Chaim-Avancini Christopher R K Ching Victoria Chubar Vincent P Clark Patricia Conrod Annette Conzelmann Benedicto Crespo-Facorro Fabrice Crivello Eveline A Crone Udo Dannlowski Anders M Dale Christopher Davey Eco J C de Geus Lieuwe de Haan Greig I de Zubicaray Anouk den Braber Erin W Dickie Annabella Di Giorgio Nhat Trung Doan Erlend S Dørum Stefan Ehrlich Susanne Erk Thomas Espeseth Helena Fatouros-Bergman Simon E Fisher Jean-Paul Fouche Barbara Franke Thomas Frodl Paola Fuentes-Claramonte David C Glahn Ian H Gotlib Hans-Jörgen Grabe Oliver Grimm Nynke A Groenewold Dominik Grotegerd Oliver Gruber Patricia Gruner Rachel E Gur Ruben C Gur Tim Hahn Ben J Harrison Catharine A Hartman Sean N Hatton Andreas Heinz Dirk J Heslenfeld Derrek P Hibar Ian B Hickie Beng-Choon Ho Pieter J Hoekstra Sarah Hohmann Avram J Holmes Martine Hoogman Norbert Hosten Fleur M Howells Hilleke E Hulshoff Pol Chaim Huyser Neda Jahanshad Anthony James Terry L Jernigan Jiyang Jiang Erik G Jönsson John A Joska Rene Kahn Andrew Kalnin Ryota Kanai Marieke Klein Tatyana P Klyushnik Laura Koenders Sanne Koops Bernd Krämer Jonna Kuntsi Jim Lagopoulos Luisa Lázaro Irina Lebedeva Won Hee Lee Klaus-Peter Lesch Christine Lochner Marise W J Machielsen Sophie Maingault Nicholas G Martin Ignacio Martínez-Zalacaín David Mataix-Cols Bernard Mazoyer Colm McDonald Brenna C McDonald Andrew M McIntosh Katie L McMahon Genevieve McPhilemy Susanne Meinert José M Menchón Sarah E Medland Andreas Meyer-Lindenberg Jilly Naaijen Pablo Najt Tomohiro Nakao Jan E Nordvik Lars Nyberg Jaap Oosterlaan Víctor Ortiz-García de la Foz Yannis Paloyelis Paul Pauli Giulio Pergola Edith Pomarol-Clotet Maria J Portella Steven G Potkin Joaquim Radua Andreas Reif Daniel A Rinker Joshua L Roffman Pedro G P Rosa Matthew D Sacchet Perminder S Sachdev Raymond Salvador Pascual Sánchez-Juan Salvador Sarró Theodore D Satterthwaite Andrew J Saykin Mauricio H Serpa Lianne Schmaal Knut Schnell Gunter Schumann Kang Sim Jordan W Smoller Iris Sommer Carles Soriano-Mas Dan J Stein Lachlan T Strike Suzanne C Swagerman Christian K Tamnes Henk S Temmingh Sophia I Thomopoulos Alexander S Tomyshev Diana Tordesillas-Gutiérrez Julian N Trollor Jessica A Turner Anne Uhlmann Odile A van den Heuvel Dennis van den Meer Nic J A van der Wee Neeltje E M van Haren Dennis Van't Ent Theo G M van Erp Ilya M Veer Dick J Veltman Aristotle Voineskos Henry Völzke Henrik Walter Esther Walton Lei Wang Yang Wang Thomas H Wassink Bernd Weber Wei Wen John D West Lars T Westlye Heather Whalley Lara M Wierenga Steven C R Williams Katharina Wittfeld Daniel H Wolf Amanda Worker Margaret J Wright Kun Yang Yulyia Yoncheva Marcus V Zanetti Georg C Ziegler Paul M Thompson Sophia Frangou

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

Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, 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

Comparison of regional brain deficit patterns in common psychiatric and neurological disorders as revealed by big data.

Neuroimage Clin 2021 26;29:102574. Epub 2021 Jan 26.

Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA. Electronic address:

Neurological and psychiatric illnesses are associated with regional brain deficit patterns that bear unique signatures and capture illness-specific characteristics. The Regional Vulnerability Index (RVI) was developed toquantify brain similarity by comparing individual white matter microstructure, cortical gray matter thickness and subcortical gray matter structural volume measures with neuroanatomical deficit patterns derived from large-scale meta-analytic studies. We tested the specificity of the RVI approach for major depressive disorder (MDD) and Alzheimer's disease (AD) in a large epidemiological sample of UK Biobank (UKBB) participants (N = 19,393; 9138 M/10,255F; age = 64.8 ± 7.4 years). Compared to controls free of neuropsychiatric disorders, participants with MDD (N = 2,248; 805 M/1443F; age = 63.4 ± 7.4) had significantly higher RVI-MDD values (t = 5.6, p = 1·10), but showed no detectable difference in RVI-AD (t = 2.0, p = 0.10). Subjects with dementia (N = 7; 4 M/3F; age = 68.6 ± 8.6 years) showed significant elevation in RVI-AD (t = 4.2, p = 3·10) but not RVI-MDD (t = 2.1, p = 0.10) compared to controls. Even within affective illnesses, participants with bipolar disorder (N = 54) and anxiety disorder (N = 773) showed no significant elevation in whole-brain RVI-MDD. Participants with Parkinson's disease (N = 37) showed elevation in RVI-AD (t = 2.4, p = 0.01) while subjects with stroke (N = 247) showed no such elevation (t = 1.1, p = 0.3). In summary, we demonstrated elevation in RVI-MDD and RVI-AD measures in the respective illnesses with strong replicability that is relatively specific to the respective diagnoses. These neuroanatomic deviation patterns offer a useful biomarker for population-wide assessments of similarity to neuropsychiatric illnesses.
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http://dx.doi.org/10.1016/j.nicl.2021.102574DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7851406PMC
January 2021

Mapping cortical and subcortical asymmetries in substance dependence: Findings from the ENIGMA Addiction Working Group.

Addict Biol 2021 Jan 28:e13010. Epub 2021 Jan 28.

Department of Psychiatry, University of Vermont College of Medicine, Burlington, Vermont, USA.

Brain asymmetry reflects left-right hemispheric differentiation, which is a quantitative brain phenotype that develops with age and can vary with psychiatric diagnoses. Previous studies have shown that substance dependence is associated with altered brain structure and function. However, it is unknown whether structural brain asymmetries are different in individuals with substance dependence compared with nondependent participants. Here, a mega-analysis was performed using a collection of 22 structural brain MRI datasets from the ENIGMA Addiction Working Group. Structural asymmetries of cortical and subcortical regions were compared between individuals who were dependent on alcohol, nicotine, cocaine, methamphetamine, or cannabis (n = 1,796) and nondependent participants (n = 996). Substance-general and substance-specific effects on structural asymmetry were examined using separate models. We found that substance dependence was significantly associated with differences in volume asymmetry of the nucleus accumbens (NAcc; less rightward; Cohen's d = 0.15). This effect was driven by differences from controls in individuals with alcohol dependence (less rightward; Cohen's d = 0.10) and nicotine dependence (less rightward; Cohen's d = 0.11). These findings suggest that disrupted structural asymmetry in the NAcc may be a characteristic of substance dependence.
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http://dx.doi.org/10.1111/adb.13010DOI Listing
January 2021

A gyrification analysis approach based on Laplace Beltrami eigenfunction level sets.

Neuroimage 2021 04 15;229:117751. Epub 2021 Jan 15.

Department of Biomedical Engineering, University of Melbourne, Melbourne, Australia; Melbourne Brain Centre Imaging Unit, University of Melbourne, Melbourne, Australia.

An accurate measure of the complexity of patterns of cortical folding or gyrification is necessary for understanding normal brain development and neurodevelopmental disorders. Conventional gyrification indices (GIs) are calculated based on surface curvature (curvature-based GI) or an outer hull surface of the cortex (outer surface-based GI). The latter is dependent on the definition of the outer hull surface and a corresponding function between surfaces. In the present study, we propose the Laplace Beltrami-based gyrification index (LB-GI). This is a new curvature-based local GI computed using the first three Laplace Beltrami eigenfunction level sets. As with outer surface-based GI methods, this method is based on the hypothesis that gyrification stems from a flat surface during development. However, instead of quantifying gyrification with reference to corresponding points on an outer hull surface, LB-GI quantifies the gyrification at each point on the cortical surface with reference to their surrounding gyral points, overcoming several shortcomings of existing methods. The LB-GI was applied to investigate the cortical maturation profile of the human brain from preschool to early adulthood using the PING database. The results revealed more detail in patterns of cortical folding than conventional curvature-based methods, especially on frontal and posterior tips of the brain, such as the frontal pole, lateral occipital, lateral cuneus, and lingual. Negative associations of cortical folding with age were observed at cortical regions, including bilateral lingual, lateral occipital, precentral gyrus, postcentral gyrus, and superior frontal gyrus. The results also indicated positive significant associations between age and the LB-GI of bilateral insula, the medial orbitofrontal, frontal pole and rostral anterior cingulate regions. It is anticipated that the LB-GI will be advantageous in providing further insights in the understanding of brain development and degeneration in large clinical neuroimaging studies.
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http://dx.doi.org/10.1016/j.neuroimage.2021.117751DOI Listing
April 2021

Structural brain imaging studies offer clues about the effects of the shared genetic etiology among neuropsychiatric disorders.

Mol Psychiatry 2021 Jan 17. Epub 2021 Jan 17.

Departments of Psychiatry and of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY, USA.

Genomewide association studies have found significant genetic correlations among many neuropsychiatric disorders. In contrast, we know much less about the degree to which structural brain alterations are similar among disorders and, if so, the degree to which such similarities have a genetic etiology. From the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium, we acquired standardized mean differences (SMDs) in regional brain volume and cortical thickness between cases and controls. We had data on 41 brain regions for: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), epilepsy, major depressive disorder (MDD), obsessive compulsive disorder (OCD), and schizophrenia (SCZ). These data had been derived from 24,360 patients and 37,425 controls. The SMDs were significantly correlated between SCZ and BD, OCD, MDD, and ASD. MDD was positively correlated with BD and OCD. BD was positively correlated with OCD and negatively correlated with ADHD. These pairwise correlations among disorders were correlated with the corresponding pairwise correlations among disorders derived from genomewide association studies (r = 0.494). Our results show substantial similarities in sMRI phenotypes among neuropsychiatric disorders and suggest that these similarities are accounted for, in part, by corresponding similarities in common genetic variant architectures.
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http://dx.doi.org/10.1038/s41380-020-01002-zDOI Listing
January 2021

Association of Immunosuppression and Viral Load With Subcortical Brain Volume in an International Sample of People Living With HIV.

JAMA Netw Open 2021 01 4;4(1):e2031190. Epub 2021 Jan 4.

Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey.

Importance: Despite more widely accessible combination antiretroviral therapy (cART), HIV-1 infection remains a global public health challenge. Even in treated patients with chronic HIV infection, neurocognitive impairment often persists, affecting quality of life. Identifying the neuroanatomical pathways associated with infection in vivo may delineate the neuropathologic processes underlying these deficits. However, published neuroimaging findings from relatively small, heterogeneous cohorts are inconsistent, limiting the generalizability of the conclusions drawn to date.

Objective: To examine structural brain associations with the most commonly collected clinical assessments of HIV burden (CD4+ T-cell count and viral load), which are generalizable across demographically and clinically diverse HIV-infected individuals worldwide.

Design, Setting, And Participants: This cross-sectional study established the HIV Working Group within the Enhancing Neuro Imaging Genetics Through Meta Analysis (ENIGMA) consortium to pool and harmonize data from existing HIV neuroimaging studies. In total, data from 1295 HIV-positive adults were contributed from 13 studies across Africa, Asia, Australia, Europe, and North America. Regional and whole brain segmentations were extracted from data sets as contributing studies joined the consortium on a rolling basis from November 1, 2014, to December 31, 2019.

Main Outcomes And Measures: Volume estimates for 8 subcortical brain regions were extracted from T1-weighted magnetic resonance images to identify associations with blood plasma markers of current immunosuppression (CD4+ T-cell counts) or detectable plasma viral load (dVL) in HIV-positive participants. Post hoc sensitivity analyses stratified data by cART status.

Results: After quality assurance, data from 1203 HIV-positive individuals (mean [SD] age, 45.7 [11.5] years; 880 [73.2%] male; 897 [74.6%] taking cART) remained. Lower current CD4+ cell counts were associated with smaller hippocampal (mean [SE] β = 16.66 [4.72] mm3 per 100 cells/mm3; P < .001) and thalamic (mean [SE] β = 32.24 [8.96] mm3 per 100 cells/mm3; P < .001) volumes and larger ventricles (mean [SE] β = -391.50 [122.58] mm3 per 100 cells/mm3; P = .001); in participants not taking cART, however, lower current CD4+ cell counts were associated with smaller putamen volumes (mean [SE] β = 57.34 [18.78] mm3 per 100 cells/mm3; P = .003). A dVL was associated with smaller hippocampal volumes (d = -0.17; P = .005); in participants taking cART, dVL was also associated with smaller amygdala volumes (d = -0.23; P = .004).

Conclusions And Relevance: In a large-scale international population of HIV-positive individuals, volumes of structures in the limbic system were consistently associated with current plasma markers. Our findings extend beyond the classically implicated regions of the basal ganglia and may represent a generalizable brain signature of HIV infection in the cART era.
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http://dx.doi.org/10.1001/jamanetworkopen.2020.31190DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7811179PMC
January 2021

FreeSurfer-based segmentation of hippocampal subfields: A review of methods and applications, with a novel quality control procedure for ENIGMA studies and other collaborative efforts.

Hum Brain Mapp 2020 Dec 27. Epub 2020 Dec 27.

Orygen, Parkville, Australia.

Structural hippocampal abnormalities are common in many neurological and psychiatric disorders, and variation in hippocampal measures is related to cognitive performance and other complex phenotypes such as stress sensitivity. Hippocampal subregions are increasingly studied, as automated algorithms have become available for mapping and volume quantification. In the context of the Enhancing Neuro Imaging Genetics through Meta Analysis Consortium, several Disease Working Groups are using the FreeSurfer software to analyze hippocampal subregion (subfield) volumes in patients with neurological and psychiatric conditions along with data from matched controls. In this overview, we explain the algorithm's principles, summarize measurement reliability studies, and demonstrate two additional aspects (subfield autocorrelation and volume/reliability correlation) with illustrative data. We then explain the rationale for a standardized hippocampal subfield segmentation quality control (QC) procedure for improved pipeline harmonization. To guide researchers to make optimal use of the algorithm, we discuss how global size and age effects can be modeled, how QC steps can be incorporated and how subfields may be aggregated into composite volumes. This discussion is based on a synopsis of 162 published neuroimaging studies (01/2013-12/2019) that applied the FreeSurfer hippocampal subfield segmentation in a broad range of domains including cognition and healthy aging, brain development and neurodegeneration, affective disorders, psychosis, stress regulation, neurotoxicity, epilepsy, inflammatory disease, childhood adversity and posttraumatic stress disorder, and candidate and whole genome (epi-)genetics. Finally, we highlight points where FreeSurfer-based hippocampal subfield studies may be optimized.
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http://dx.doi.org/10.1002/hbm.25326DOI Listing
December 2020

Ten years of enhancing neuro-imaging genetics through meta-analysis: An overview from the ENIGMA Genetics Working Group.

Hum Brain Mapp 2020 Dec 10. Epub 2020 Dec 10.

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

Here we review the motivation for creating the enhancing neuroimaging genetics through meta-analysis (ENIGMA) Consortium and the genetic analyses undertaken by the consortium so far. We discuss the methodological challenges, findings, and future directions of the genetics working group. A major goal of the working group is tackling the reproducibility crisis affecting "candidate gene" and genome-wide association analyses in neuroimaging. To address this, we developed harmonized analytic methods, and support their use in coordinated analyses across sites worldwide, which also makes it possible to understand heterogeneity in results across sites. These efforts have resulted in the identification of hundreds of common genomic loci robustly associated with brain structure. We have found both pleiotropic and specific genetic effects associated with brain structures, as well as genetic correlations with psychiatric and neurological diseases.
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http://dx.doi.org/10.1002/hbm.25311DOI Listing
December 2020

Brain structural correlates of insomnia severity in 1053 individuals with major depressive disorder: results from the ENIGMA MDD Working Group.

Transl Psychiatry 2020 12 8;10(1):425. Epub 2020 Dec 8.

Department of Sleep and Cognition, Netherlands Institute for Neuroscience, an Institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands.

It has been difficult to find robust brain structural correlates of the overall severity of major depressive disorder (MDD). We hypothesized that specific symptoms may better reveal correlates and investigated this for the severity of insomnia, both a key symptom and a modifiable major risk factor of MDD. Cortical thickness, surface area and subcortical volumes were assessed from T1-weighted brain magnetic resonance imaging (MRI) scans of 1053 MDD patients (age range 13-79 years) from 15 cohorts within the ENIGMA MDD Working Group. Insomnia severity was measured by summing the insomnia items of the Hamilton Depression Rating Scale (HDRS). Symptom specificity was evaluated with correlates of overall depression severity. Disease specificity was evaluated in two independent samples comprising 2108 healthy controls, and in 260 clinical controls with bipolar disorder. Results showed that MDD patients with more severe insomnia had a smaller cortical surface area, mostly driven by the right insula, left inferior frontal gyrus pars triangularis, left frontal pole, right superior parietal cortex, right medial orbitofrontal cortex, and right supramarginal gyrus. Associations were specific for insomnia severity, and were not found for overall depression severity. Associations were also specific to MDD; healthy controls and clinical controls showed differential insomnia severity association profiles. The findings indicate that MDD patients with more severe insomnia show smaller surfaces in several frontoparietal cortical areas. While explained variance remains small, symptom-specific associations could bring us closer to clues on underlying biological phenomena of MDD.
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http://dx.doi.org/10.1038/s41398-020-01109-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7723989PMC
December 2020

The Evolutionary History of Common Genetic Variants Influencing Human Cortical Surface Area.

Cereb Cortex 2021 Mar;31(4):1873-1887

Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA.

Structural brain changes along the lineage leading to modern Homo sapiens contributed to our distinctive cognitive and social abilities. However, the evolutionarily relevant molecular variants impacting key aspects of neuroanatomy are largely unknown. Here, we integrate evolutionary annotations of the genome at diverse timescales with common variant associations from large-scale neuroimaging genetic screens. We find that alleles with evidence of recent positive polygenic selection over the past 2000-3000 years are associated with increased surface area (SA) of the entire cortex, as well as specific regions, including those involved in spoken language and visual processing. Therefore, polygenic selective pressures impact the structure of specific cortical areas even over relatively recent timescales. Moreover, common sequence variation within human gained enhancers active in the prenatal cortex is associated with postnatal global SA. We show that such variation modulates the function of a regulatory element of the developmentally relevant transcription factor HEY2 in human neural progenitor cells and is associated with structural changes in the inferior frontal cortex. These results indicate that non-coding genomic regions active during prenatal cortical development are involved in the evolution of human brain structure and identify novel regulatory elements and genes impacting modern human brain structure.
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http://dx.doi.org/10.1093/cercor/bhaa327DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7945014PMC
March 2021

Cortical volume abnormalities in posttraumatic stress disorder: an ENIGMA-psychiatric genomics consortium PTSD workgroup mega-analysis.

Authors:
Xin Wang Hong Xie Tian Chen Andrew S Cotton Lauren E Salminen Mark W Logue Emily K Clarke-Rubright John Wall Emily L Dennis Brian M O'Leary Chadi G Abdallah Elpiniki Andrew Lee A Baugh Jessica Bomyea Steven E Bruce Richard Bryant Kyle Choi Judith K Daniels Nicholas D Davenport Richard J Davidson Michael DeBellis Terri deRoon-Cassini Seth G Disner Negar Fani Kelene A Fercho Jacklynn Fitzgerald Gina L Forster Jessie L Frijling Elbert Geuze Hassaan Gomaa Evan M Gordon Dan Grupe Ilan Harpaz-Rotem Courtney C Haswell Julia I Herzog David Hofmann Michael Hollifield Bobak Hosseini Anna R Hudson Jonathan Ipser Neda Jahanshad Tanja Jovanovic Milissa L Kaufman Anthony P King Saskia B J Koch Inga K Koerte Mayuresh S Korgaonkar John H Krystal Christine Larson Lauren A M Lebois Ifat Levy Gen Li Vincent A Magnotta Antje Manthey Geoffrey May Katie A McLaughlin Sven C Mueller Laura Nawijn Steven M Nelson Yuval Neria Jack B Nitschke Miranda Olff Elizabeth A Olson Matthew Peverill K Luan Phan Faisal M Rashid Kerry Ressler Isabelle M Rosso Kelly Sambrook Christian Schmahl Martha E Shenton Anika Sierk Jeffrey S Simons Raluca M Simons Scott R Sponheim Murray B Stein Dan J Stein Jennifer S Stevens Thomas Straube Benjamin Suarez-Jimenez Marijo Tamburrino Sophia I Thomopoulos Nic J A van der Wee Steven J A van der Werff Theo G M van Erp Sanne J H van Rooij Mirjam van Zuiden Tim Varkevisser Dick J Veltman Robert R J M Vermeiren Henrik Walter Li Wang Ye Zhu Xi Zhu Paul M Thompson Rajendra A Morey Israel Liberzon

Mol Psychiatry 2020 Dec 7. Epub 2020 Dec 7.

Department of Psychiatry and Behavioral Science, Texas A&M University College of Medicine, College Station, TX, USA.

Studies of posttraumatic stress disorder (PTSD) report volume abnormalities in multiple regions of the cerebral cortex. However, findings for many regions, particularly regions outside commonly studied emotion-related prefrontal, insular, and limbic regions, are inconsistent and tentative. Also, few studies address the possibility that PTSD abnormalities may be confounded by comorbid depression. A mega-analysis investigating all cortical regions in a large sample of PTSD and control subjects can potentially provide new insight into these issues. Given this perspective, our group aggregated regional volumes data of 68 cortical regions across both hemispheres from 1379 PTSD patients to 2192 controls without PTSD after data were processed by 32 international laboratories using ENIGMA standardized procedures. We examined whether regional cortical volumes were different in PTSD vs. controls, were associated with posttraumatic stress symptom (PTSS) severity, or were affected by comorbid depression. Volumes of left and right lateral orbitofrontal gyri (LOFG), left superior temporal gyrus, and right insular, lingual and superior parietal gyri were significantly smaller, on average, in PTSD patients than controls (standardized coefficients = -0.111 to -0.068, FDR corrected P values < 0.039) and were significantly negatively correlated with PTSS severity. After adjusting for depression symptoms, the PTSD findings in left and right LOFG remained significant. These findings indicate that cortical volumes in PTSD patients are smaller in prefrontal regulatory regions, as well as in broader emotion and sensory processing cortical regions.
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http://dx.doi.org/10.1038/s41380-020-00967-1DOI Listing
December 2020

In vivo hippocampal subfield volumes in bipolar disorder-A mega-analysis from The Enhancing Neuro Imaging Genetics through Meta-Analysis Bipolar Disorder Working Group.

Authors:
Unn K Haukvik Tiril P Gurholt Stener Nerland Torbjørn Elvsåshagen Theophilus N Akudjedu Martin Alda Dag Alnaes Silvia Alonso-Lana Jochen Bauer Bernhard T Baune Francesco Benedetti Michael Berk Francesco Bettella Erlend Bøen Caterina M Bonnín Paolo Brambilla Erick J Canales-Rodríguez Dara M Cannon Xavier Caseras Orwa Dandash Udo Dannlowski Giuseppe Delvecchio Ana M Díaz-Zuluaga Theo G M van Erp Mar Fatjó-Vilas Sonya F Foley Katharina Förster Janice M Fullerton José M Goikolea Dominik Grotegerd Oliver Gruber Bartholomeus C M Haarman Beathe Haatveit Tomas Hajek Brian Hallahan Mathew Harris Emma L Hawkins Fleur M Howells Carina Hülsmann Neda Jahanshad Kjetil N Jørgensen Tilo Kircher Bernd Krämer Axel Krug Rayus Kuplicki Trine V Lagerberg Thomas M Lancaster Rhoshel K Lenroot Vera Lonning Carlos López-Jaramillo Ulrik F Malt Colm McDonald Andrew M McIntosh Genevieve McPhilemy Dennis van der Meer Ingrid Melle Elisa M T Melloni Philip B Mitchell Leila Nabulsi Igor Nenadić Viola Oertel Lucio Oldani Nils Opel Maria C G Otaduy Bronwyn J Overs Julian A Pineda-Zapata Edith Pomarol-Clotet Joaquim Radua Lisa Rauer Ronny Redlich Jonathan Repple Maria M Rive Gloria Roberts Henricus G Ruhe Lauren E Salminen Raymond Salvador Salvador Sarró Jonathan Savitz Aart H Schene Kang Sim Marcio G Soeiro-de-Souza Michael Stäblein Dan J Stein Frederike Stein Christian K Tamnes Henk S Temmingh Sophia I Thomopoulos Dick J Veltman Eduard Vieta Lena Waltemate Lars T Westlye Heather C Whalley Philipp G Sämann Paul M Thompson Christopher R K Ching Ole A Andreassen Ingrid Agartz

Hum Brain Mapp 2020 Oct 19. Epub 2020 Oct 19.

Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway.

The hippocampus consists of anatomically and functionally distinct subfields that may be differentially involved in the pathophysiology of bipolar disorder (BD). Here we, the Enhancing NeuroImaging Genetics through Meta-Analysis Bipolar Disorder workinggroup, study hippocampal subfield volumetry in BD. T1-weighted magnetic resonance imaging scans from 4,698 individuals (BD = 1,472, healthy controls [HC] = 3,226) from 23 sites worldwide were processed with FreeSurfer. We used linear mixed-effects models and mega-analysis to investigate differences in hippocampal subfield volumes between BD and HC, followed by analyses of clinical characteristics and medication use. BD showed significantly smaller volumes of the whole hippocampus (Cohen's d = -0.20), cornu ammonis (CA)1 (d = -0.18), CA2/3 (d = -0.11), CA4 (d = -0.19), molecular layer (d = -0.21), granule cell layer of dentate gyrus (d = -0.21), hippocampal tail (d = -0.10), subiculum (d = -0.15), presubiculum (d = -0.18), and hippocampal amygdala transition area (d = -0.17) compared to HC. Lithium users did not show volume differences compared to HC, while non-users did. Antipsychotics or antiepileptic use was associated with smaller volumes. In this largest study of hippocampal subfields in BD to date, we show widespread reductions in nine of 12 subfields studied. The associations were modulated by medication use and specifically the lack of differences between lithium users and HC supports a possible protective role of lithium in BD.
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http://dx.doi.org/10.1002/hbm.25249DOI Listing
October 2020

Testing a convolutional neural network-based hippocampal segmentation method in a stroke population.

Hum Brain Mapp 2020 Oct 16. Epub 2020 Oct 16.

Neural Plasticity and Neurorehabilitation Laboratory, University of Southern California, Los Angeles, California, USA.

As stroke mortality rates decrease, there has been a surge of effort to study poststroke dementia (PSD) to improve long-term quality of life for stroke survivors. Hippocampal volume may be an important neuroimaging biomarker in poststroke dementia, as it has been associated with many other forms of dementia. However, studying hippocampal volume using MRI requires hippocampal segmentation. Advances in automated segmentation methods have allowed for studying the hippocampus on a large scale, which is important for robust results in the heterogeneous stroke population. However, most of these automated methods use a single atlas-based approach and may fail in the presence of severe structural abnormalities common in stroke. Hippodeep, a new convolutional neural network-based hippocampal segmentation method, does not rely solely on a single atlas-based approach and thus may be better suited for stroke populations. Here, we compared quality control and the accuracy of segmentations generated by Hippodeep and two well-accepted hippocampal segmentation methods on stroke MRIs (FreeSurfer 6.0 whole hippocampus and FreeSurfer 6.0 sum of hippocampal subfields). Quality control was performed using a stringent protocol for visual inspection of the segmentations, and accuracy was measured as volumetric correlation with manual segmentations. Hippodeep performed significantly better than both FreeSurfer methods in terms of quality control. All three automated segmentation methods had good correlation with manual segmentations and no one method was significantly more correlated than the others. Overall, this study suggests that both Hippodeep and FreeSurfer may be useful for hippocampal segmentation in stroke rehabilitation research, but Hippodeep may be more robust to stroke lesion anatomy.
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http://dx.doi.org/10.1002/hbm.25210DOI Listing
October 2020

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

Authors:
Lara M Wierenga Gaelle E Doucet Danai Dima Ingrid Agartz Moji Aghajani Theophilus N Akudjedu Anton Albajes-Eizagirre Dag Alnaes Kathryn I Alpert Ole A Andreassen Alan Anticevic Philip Asherson Tobias Banaschewski Nuria Bargallo Sarah Baumeister Ramona Baur-Streubel Alessandro Bertolino Aurora Bonvino Dorret I Boomsma Stefan Borgwardt Josiane Bourque Anouk den Braber Daniel Brandeis Alan Breier Henry Brodaty Rachel M Brouwer Jan K Buitelaar Geraldo F Busatto Vince D Calhoun Erick J Canales-Rodríguez Dara M Cannon Xavier Caseras Francisco X Castellanos Tiffany M Chaim-Avancini Christopher Rk Ching Vincent P Clark Patricia J Conrod Annette Conzelmann Fabrice Crivello Christopher G Davey Erin W Dickie Stefan Ehrlich Dennis Van't Ent Simon E Fisher Jean-Paul Fouche Barbara Franke Paola Fuentes-Claramonte Eco Jc de Geus Annabella Di Giorgio David C Glahn Ian H Gotlib Hans J Grabe Oliver Gruber Patricia Gruner Raquel E Gur Ruben C Gur Tiril P Gurholt Lieuwe de Haan Beathe Haatveit Ben J Harrison Catharina A Hartman Sean N Hatton Dirk J Heslenfeld Odile A van den Heuvel Ian B Hickie Pieter J Hoekstra Sarah Hohmann Avram J Holmes Martine Hoogman Norbert Hosten Fleur M Howells Hilleke E Hulshoff Pol Chaim Huyser Neda Jahanshad Anthony C James Jiyang Jiang Erik G Jönsson John A Joska Andrew J Kalnin Marieke Klein Laura Koenders Knut K Kolskår Bernd Krämer Jonna Kuntsi Jim Lagopoulos Luisa Lazaro Irina S Lebedeva Phil H Lee Christine Lochner Marise Wj Machielsen Sophie Maingault Nicholas G Martin Ignacio Martínez-Zalacaín David Mataix-Cols Bernard Mazoyer Brenna C McDonald Colm McDonald Andrew M McIntosh Katie L McMahon Genevieve McPhilemy Dennis van der Meer José M Menchón Jilly Naaijen Lars Nyberg Jaap Oosterlaan Yannis Paloyelis Paul Pauli Giulio Pergola Edith Pomarol-Clotet Maria J Portella Joaquim Radua Andreas Reif Geneviève Richard Joshua L Roffman Pedro Gp Rosa Matthew D Sacchet Perminder S Sachdev Raymond Salvador Salvador Sarró Theodore D Satterthwaite Andrew J Saykin Mauricio H Serpa Kang Sim Andrew Simmons Jordan W Smoller Iris E Sommer Carles Soriano-Mas Dan J Stein Lachlan T Strike Philip R Szeszko Henk S Temmingh Sophia I Thomopoulos Alexander S Tomyshev Julian N Trollor Anne Uhlmann Ilya M Veer Dick J Veltman Aristotle Voineskos Henry Völzke Henrik Walter Lei Wang Yang Wang Bernd Weber Wei Wen John D West Lars T Westlye Heather C Whalley Steven Cr Williams Katharina Wittfeld Daniel H Wolf Margaret J Wright Yuliya N Yoncheva Marcus V Zanetti Georg C Ziegler Greig I de Zubicaray Paul M Thompson Eveline A Crone Sophia Frangou Christian K Tamnes

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

Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.

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

Intelligence, educational attainment, and brain structure in those at familial high-risk for schizophrenia or bipolar disorder.

Authors:
Sonja M C de Zwarte Rachel M Brouwer Ingrid Agartz Martin Alda Silvia Alonso-Lana Carrie E Bearden Alessandro Bertolino Aurora Bonvino Elvira Bramon Elizabeth E L Buimer Wiepke Cahn Erick J Canales-Rodríguez Dara M Cannon Tyrone D Cannon Xavier Caseras Josefina Castro-Fornieles Qiang Chen Yoonho Chung Elena De la Serna Caterina Del Mar Bonnin Caroline Demro Annabella Di Giorgio Gaelle E Doucet Mehmet Cagdas Eker Susanne Erk Mar Fatjó-Vilas Scott C Fears Sonya F Foley Sophia Frangou Janice M Fullerton David C Glahn Vina M Goghari Jose M Goikolea Aaron L Goldman Ali Saffet Gonul Oliver Gruber Tomas Hajek Emma L Hawkins Andreas Heinz Ceren Hidiroglu Ongun Manon H J Hillegers Josselin Houenou Hilleke E Hulshoff Pol Christina M Hultman Martin Ingvar Viktoria Johansson Erik G Jönsson Fergus Kane Matthew J Kempton Marinka M G Koenis Miloslav Kopecek Bernd Krämer Stephen M Lawrie Rhoshel K Lenroot Machteld Marcelis Venkata S Mattay Colm McDonald Andreas Meyer-Lindenberg Stijn Michielse Philip B Mitchell Dolores Moreno Robin M Murray Benson Mwangi Leila Nabulsi Jason Newport Cheryl A Olman Jim van Os Bronwyn J Overs Aysegul Ozerdem Giulio Pergola Marco M Picchioni Camille Piguet Edith Pomarol-Clotet Joaquim Radua Ian S Ramsay Anja Richter Gloria Roberts Raymond Salvador Aybala Saricicek Aydogan Salvador Sarró Peter R Schofield Esma M Simsek Fatma Simsek Jair C Soares Scott R Sponheim Gisela Sugranyes Timothea Toulopoulou Giulia Tronchin Eduard Vieta Henrik Walter Daniel R Weinberger Heather C Whalley Mon-Ju Wu Nefize Yalin Ole A Andreassen Christopher R K Ching Sophia I Thomopoulos Theo G M van Erp Neda Jahanshad Paul M Thompson René S Kahn Neeltje E M van Haren

Hum Brain Mapp 2020 Oct 7. Epub 2020 Oct 7.

Department of Psychiatry, University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands.

First-degree relatives of patients diagnosed with schizophrenia (SZ-FDRs) show similar patterns of brain abnormalities and cognitive alterations to patients, albeit with smaller effect sizes. First-degree relatives of patients diagnosed with bipolar disorder (BD-FDRs) show divergent patterns; on average, intracranial volume is larger compared to controls, and findings on cognitive alterations in BD-FDRs are inconsistent. Here, we performed a meta-analysis of global and regional brain measures (cortical and subcortical), current IQ, and educational attainment in 5,795 individuals (1,103 SZ-FDRs, 867 BD-FDRs, 2,190 controls, 942 schizophrenia patients, 693 bipolar patients) from 36 schizophrenia and/or bipolar disorder family cohorts, with standardized methods. Compared to controls, SZ-FDRs showed a pattern of widespread thinner cortex, while BD-FDRs had widespread larger cortical surface area. IQ was lower in SZ-FDRs (d = -0.42, p = 3 × 10 ), with weak evidence of IQ reductions among BD-FDRs (d = -0.23, p = .045). Both relative groups had similar educational attainment compared to controls. When adjusting for IQ or educational attainment, the group-effects on brain measures changed, albeit modestly. Changes were in the expected direction, with less pronounced brain abnormalities in SZ-FDRs and more pronounced effects in BD-FDRs. To conclude, SZ-FDRs and BD-FDRs show a differential pattern of structural brain abnormalities. In contrast, both had lower IQ scores and similar school achievements compared to controls. Given that brain differences between SZ-FDRs and BD-FDRs remain after adjusting for IQ or educational attainment, we suggest that differential brain developmental processes underlying predisposition for schizophrenia or bipolar disorder are likely independent of general cognitive impairment.
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http://dx.doi.org/10.1002/hbm.25206DOI Listing
October 2020

Intracranial and subcortical volumes in adolescents with early-onset psychosis: A multisite mega-analysis from the ENIGMA consortium.

Hum Brain Mapp 2020 Oct 5. Epub 2020 Oct 5.

Norwegian Center for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway.

Early-onset psychosis disorders are serious mental disorders arising before the age of 18 years. Here, we investigate the largest neuroimaging dataset, to date, of patients with early-onset psychosis and healthy controls for differences in intracranial and subcortical brain volumes. The sample included 263 patients with early-onset psychosis (mean age: 16.4 ± 1.4 years, mean illness duration: 1.5 ± 1.4 years, 39.2% female) and 359 healthy controls (mean age: 15.9 ± 1.7 years, 45.4% female) with magnetic resonance imaging data, pooled from 11 clinical cohorts. Patients were diagnosed with early-onset schizophrenia (n = 183), affective psychosis (n = 39), or other psychotic disorders (n = 41). We used linear mixed-effects models to investigate differences in intracranial and subcortical volumes across the patient sample, diagnostic subgroup and antipsychotic medication, relative to controls. We observed significantly lower intracranial (Cohen's d = -0.39) and hippocampal (d = -0.25) volumes, and higher caudate (d = 0.25) and pallidum (d = 0.24) volumes in patients relative to controls. Intracranial volume was lower in both early-onset schizophrenia (d = -0.34) and affective psychosis (d = -0.42), and early-onset schizophrenia showed lower hippocampal (d = -0.24) and higher pallidum (d = 0.29) volumes. Patients who were currently treated with antipsychotic medication (n = 193) had significantly lower intracranial volume (d = -0.42). The findings demonstrate a similar pattern of brain alterations in early-onset psychosis as previously reported in adult psychosis, but with notably low intracranial volume. The low intracranial volume suggests disrupted neurodevelopment in adolescent early-onset psychosis.
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http://dx.doi.org/10.1002/hbm.25212DOI Listing
October 2020

Genetic correlations and genome-wide associations of cortical structure in general population samples of 22,824 adults.

Authors:
Edith Hofer Gennady V Roshchupkin Hieab H H Adams Maria J Knol Honghuang Lin Shuo Li Habil Zare Shahzad Ahmad Nicola J Armstrong Claudia L Satizabal Manon Bernard Joshua C Bis Nathan A Gillespie Michelle Luciano Aniket Mishra Markus Scholz Alexander Teumer Rui Xia Xueqiu Jian Thomas H Mosley Yasaman Saba Lukas Pirpamer Stephan Seiler James T Becker Owen Carmichael Jerome I Rotter Bruce M Psaty Oscar L Lopez Najaf Amin Sven J van der Lee Qiong Yang Jayandra J Himali Pauline Maillard Alexa S Beiser Charles DeCarli Sherif Karama Lindsay Lewis Mat Harris Mark E Bastin Ian J Deary A Veronica Witte Frauke Beyer Markus Loeffler Karen A Mather Peter R Schofield Anbupalam Thalamuthu John B Kwok Margaret J Wright David Ames Julian Trollor Jiyang Jiang Henry Brodaty Wei Wen Meike W Vernooij Albert Hofman André G Uitterlinden Wiro J Niessen Katharina Wittfeld Robin Bülow Uwe Völker Zdenka Pausova G Bruce Pike Sophie Maingault Fabrice Crivello Christophe Tzourio Philippe Amouyel Bernard Mazoyer Michael C Neale Carol E Franz Michael J Lyons Matthew S Panizzon Ole A Andreassen Anders M Dale Mark Logue Katrina L Grasby Neda Jahanshad Jodie N Painter Lucía Colodro-Conde Janita Bralten Derrek P Hibar Penelope A Lind Fabrizio Pizzagalli Jason L Stein Paul M Thompson Sarah E Medland Perminder S Sachdev William S Kremen Joanna M Wardlaw Arno Villringer Cornelia M van Duijn Hans J Grabe William T Longstreth Myriam Fornage Tomas Paus Stephanie Debette M Arfan Ikram Helena Schmidt Reinhold Schmidt Sudha Seshadri

Nat Commun 2020 09 22;11(1):4796. Epub 2020 Sep 22.

Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, USA.

Cortical thickness, surface area and volumes vary with age and cognitive function, and in neurological and psychiatric diseases. Here we report heritability, genetic correlations and genome-wide associations of these cortical measures across the whole cortex, and in 34 anatomically predefined regions. Our discovery sample comprises 22,824 individuals from 20 cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank. We identify genetic heterogeneity between cortical measures and brain regions, and 160 genome-wide significant associations pointing to wnt/β-catenin, TGF-β and sonic hedgehog pathways. There is enrichment for genes involved in anthropometric traits, hindbrain development, vascular and neurodegenerative disease and psychiatric conditions. These data are a rich resource for studies of the biological mechanisms behind cortical development and aging.
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http://dx.doi.org/10.1038/s41467-020-18367-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7508833PMC
September 2020

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

Commun Biol 2020 Sep 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

Virtual Histology of Cortical Thickness and Shared Neurobiology in 6 Psychiatric Disorders.

Authors:
Yash Patel Nadine Parker Jean Shin Derek Howard Leon French Sophia I Thomopoulos Elena Pozzi Yoshinari Abe Christoph Abé Alan Anticevic Martin Alda Andre Aleman Clara Alloza Silvia Alonso-Lana Stephanie H Ameis Evdokia Anagnostou Andrew A McIntosh Celso Arango Paul D Arnold Philip Asherson Francesca Assogna Guillaume Auzias Rosa Ayesa-Arriola Geor Bakker Nerisa Banaj Tobias Banaschewski Cibele E Bandeira Alexandr Baranov Núria Bargalló Claiton H D Bau Sarah Baumeister Bernhard T Baune Mark A Bellgrove Francesco Benedetti Alessandro Bertolino Premika S W Boedhoe Marco Boks Irene Bollettini Caterina Del Mar Bonnin Tiana Borgers Stefan Borgwardt Daniel Brandeis Brian P Brennan Jason M Bruggemann Robin Bülow Geraldo F Busatto Sara Calderoni Vince D Calhoun Rosa Calvo Erick J Canales-Rodríguez Dara M Cannon Vaughan J Carr Nicola Cascella Mara Cercignani Tiffany M Chaim-Avancini Anastasia Christakou David Coghill Annette Conzelmann Benedicto Crespo-Facorro Ana I Cubillo Kathryn R Cullen Renata B Cupertino Eileen Daly Udo Dannlowski Christopher G Davey Damiaan Denys Christine Deruelle Annabella Di Giorgio Erin W Dickie Danai Dima Katharina Dohm Stefan Ehrlich Benjamin A Ely Tracy Erwin-Grabner Thomas Ethofer Damien A Fair Andreas J Fallgatter Stephen V Faraone Mar Fatjó-Vilas Jennifer M Fedor Kate D Fitzgerald Judith M Ford Thomas Frodl Cynthia H Y Fu Janice M Fullerton Matt C Gabel David C Glahn Gloria Roberts Tinatin Gogberashvili Jose M Goikolea Ian H Gotlib Roberto Goya-Maldonado Hans J Grabe Melissa J Green Eugenio H Grevet Nynke A Groenewold Dominik Grotegerd Oliver Gruber Patricia Gruner Amalia Guerrero-Pedraza Raquel E Gur Ruben C Gur Shlomi Haar Bartholomeus C M Haarman Jan Haavik Tim Hahn Tomas Hajek Benjamin J Harrison Neil A Harrison Catharina A Hartman Heather C Whalley Dirk J Heslenfeld Derrek P Hibar Eva Hilland Yoshiyuki Hirano Tiffany C Ho Pieter J Hoekstra Liesbeth Hoekstra Sarah Hohmann L E Hong Cyril Höschl Marie F Høvik Fleur M Howells Igor Nenadic Maria Jalbrzikowski Anthony C James Joost Janssen Fern Jaspers-Fayer Jian Xu Rune Jonassen Georgii Karkashadze Joseph A King Tilo Kircher Matthias Kirschner Kathrin Koch Peter Kochunov Gregor Kohls Kerstin Konrad Bernd Krämer Axel Krug Jonna Kuntsi Jun Soo Kwon Mikael Landén Nils I Landrø Luisa Lazaro Irina S Lebedeva Elisabeth J Leehr Sara Lera-Miguel Klaus-Peter Lesch Christine Lochner Mario R Louza Beatriz Luna Astri J Lundervold Frank P MacMaster Luigi A Maglanoc Charles B Malpas Maria J Portella Rachel Marsh Fiona M Martyn David Mataix-Cols Daniel H Mathalon Hazel McCarthy Colm McDonald Genevieve McPhilemy Susanne Meinert José M Menchón Luciano Minuzzi Philip B Mitchell Carmen Moreno Pedro Morgado Filippo Muratori Clodagh M Murphy Declan Murphy Benson Mwangi Leila Nabulsi Akiko Nakagawa Takashi Nakamae Leyla Namazova Janardhanan Narayanaswamy Neda Jahanshad Danai D Nguyen Rosa Nicolau Ruth L O'Gorman Tuura Kirsten O'Hearn Jaap Oosterlaan Nils Opel Roel A Ophoff Bob Oranje Victor Ortiz García de la Foz Bronwyn J Overs Yannis Paloyelis Christos Pantelis Mara Parellada Paul Pauli Maria Picó-Pérez Felipe A Picon Fabrizio Piras Federica Piras Kerstin J Plessen Edith Pomarol-Clotet Adrian Preda Olga Puig Yann Quidé Joaquim Radua J Antoni Ramos-Quiroga Paul E Rasser Lisa Rauer Janardhan Reddy Ronny Redlich Andreas Reif Liesbeth Reneman Jonathan Repple Alessandra Retico Vanesa Richarte Anja Richter Pedro G P Rosa Katya K Rubia Ryota Hashimoto Matthew D Sacchet Raymond Salvador Javier Santonja Kelvin Sarink Salvador Sarró Theodore D Satterthwaite Akira Sawa Ulrich Schall Peter R Schofield Anouk Schrantee Jochen Seitz Mauricio H Serpa Esther Setién-Suero Philip Shaw Devon Shook Tim J Silk Kang Sim Schmitt Simon Helen Blair Simpson Aditya Singh Antonin Skoch Norbert Skokauskas Jair C Soares Noam Soreni Carles Soriano-Mas Gianfranco Spalletta Filip Spaniel Stephen M Lawrie Emily R Stern S Evelyn Stewart Yoichiro Takayanagi Henk S Temmingh David F Tolin David Tomecek Diana Tordesillas-Gutiérrez Michela Tosetti Anne Uhlmann Therese van Amelsvoort Nic J A van der Wee Steven J A van der Werff Neeltje E M van Haren Guido A van Wingen Alasdair Vance Javier Vázquez-Bourgon Daniela Vecchio Ganesan Venkatasubramanian Eduard Vieta Oscar Vilarroya Yolanda Vives-Gilabert Aristotle N Voineskos Henry Völzke Georg G von Polier Esther Walton Thomas W Weickert Cynthia Shannon Weickert Andrea S Weideman Katharina Wittfeld Daniel H Wolf Mon-Ju Wu T T Yang Kun Yang Yuliya Yoncheva Je-Yeon Yun Yuqi Cheng Marcus V Zanetti Georg C Ziegler Barbara Franke Martine Hoogman Jan K Buitelaar Daan van Rooij Ole A Andreassen Christopher R K Ching Dick J Veltman Lianne Schmaal Dan J Stein Odile A van den Heuvel Jessica A Turner Theo G M van Erp Zdenka Pausova Paul M Thompson Tomáš Paus

JAMA Psychiatry 2021 Jan;78(1):47-63

Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada.

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.
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http://dx.doi.org/10.1001/jamapsychiatry.2020.2694DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7450410PMC
January 2021

White matter abnormalities across different epilepsy syndromes in adults: an ENIGMA-Epilepsy study.

Brain 2020 08;143(8):2454-2473

Department of Psychiatry, Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla 92093 CA, USA.

The epilepsies are commonly accompanied by widespread abnormalities in cerebral white matter. ENIGMA-Epilepsy is a large quantitative brain imaging consortium, aggregating data to investigate patterns of neuroimaging abnormalities in common epilepsy syndromes, including temporal lobe epilepsy, extratemporal epilepsy, and genetic generalized epilepsy. Our goal was to rank the most robust white matter microstructural differences across and within syndromes in a multicentre sample of adult epilepsy patients. Diffusion-weighted MRI data were analysed from 1069 healthy controls and 1249 patients: temporal lobe epilepsy with hippocampal sclerosis (n = 599), temporal lobe epilepsy with normal MRI (n = 275), genetic generalized epilepsy (n = 182) and non-lesional extratemporal epilepsy (n = 193). A harmonized protocol using tract-based spatial statistics was used to derive skeletonized maps of fractional anisotropy and mean diffusivity for each participant, and fibre tracts were segmented using a diffusion MRI atlas. Data were harmonized to correct for scanner-specific variations in diffusion measures using a batch-effect correction tool (ComBat). Analyses of covariance, adjusting for age and sex, examined differences between each epilepsy syndrome and controls for each white matter tract (Bonferroni corrected at P < 0.001). Across 'all epilepsies' lower fractional anisotropy was observed in most fibre tracts with small to medium effect sizes, especially in the corpus callosum, cingulum and external capsule. There were also less robust increases in mean diffusivity. Syndrome-specific fractional anisotropy and mean diffusivity differences were most pronounced in patients with hippocampal sclerosis in the ipsilateral parahippocampal cingulum and external capsule, with smaller effects across most other tracts. Individuals with temporal lobe epilepsy and normal MRI showed a similar pattern of greater ipsilateral than contralateral abnormalities, but less marked than those in patients with hippocampal sclerosis. Patients with generalized and extratemporal epilepsies had pronounced reductions in fractional anisotropy in the corpus callosum, corona radiata and external capsule, and increased mean diffusivity of the anterior corona radiata. Earlier age of seizure onset and longer disease duration were associated with a greater extent of diffusion abnormalities in patients with hippocampal sclerosis. We demonstrate microstructural abnormalities across major association, commissural, and projection fibres in a large multicentre study of epilepsy. Overall, patients with epilepsy showed white matter abnormalities in the corpus callosum, cingulum and external capsule, with differing severity across epilepsy syndromes. These data further define the spectrum of white matter abnormalities in common epilepsy syndromes, yielding more detailed insights into pathological substrates that may explain cognitive and psychiatric co-morbidities and be used to guide biomarker studies of treatment outcomes and/or genetic research.
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http://dx.doi.org/10.1093/brain/awaa200DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7567169PMC
August 2020

A White Matter Connection of Schizophrenia and Alzheimer's Disease.

Schizophr Bull 2021 Jan;47(1):197-206

Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD.

Schizophrenia (SZ) is a severe psychiatric illness associated with an elevated risk for developing Alzheimer's disease (AD). Both SZ and AD have white matter abnormalities and cognitive deficits as core disease features. We hypothesized that aging in SZ patients may be associated with the development of cerebral white matter deficit patterns similar to those observed in AD. We identified and replicated aging-related increases in the similarity between white matter deficit patterns in patients with SZ and AD. The white matter "regional vulnerability index" (RVI) for AD was significantly higher in SZ patients compared with healthy controls in both the independent discovery (Cohen's d = 0.44, P = 1·10-5, N = 173 patients/230 control) and replication (Cohen's d = 0.78, P = 9·10-7, N = 122 patients/64 controls) samples. The degree of overlap with the AD deficit pattern was significantly correlated with age in patients (r = .21 and .29, P < .01 in discovery and replication cohorts, respectively) but not in controls. Elevated RVI-AD was significantly associated with cognitive measures in both SZ and AD. Disease and cognitive specificities were also tested in patients with mild cognitive impairment and showed intermediate overlap. SZ and AD have diverse etiologies and clinical courses; our findings suggest that white matter deficits may represent a key intersecting point for these 2 otherwise distinct diseases. Identifying mechanisms underlying this white matter deficit pattern may yield preventative and treatment targets for cognitive deficits in both SZ and AD patients.
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http://dx.doi.org/10.1093/schbul/sbaa078DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7825012PMC
January 2021

How do substance use disorders compare to other psychiatric conditions on structural brain abnormalities? A cross-disorder meta-analytic comparison using the ENIGMA consortium findings.

Hum Brain Mapp 2020 Jul 9. Epub 2020 Jul 9.

Department of Psychiatry, Université de Montreal, CHU Ste Justine Hospital, CHU Ste-Justine, Montreal, Canada.

Alcohol use disorder (AUD) and cannabis use disorder (CUD) are associated with brain alterations particularly involving fronto-cerebellar and meso-cortico-limbic circuitry. However, such abnormalities have additionally been reported in other psychiatric conditions, and until recently there has been few large-scale investigations to compare such findings. The current study uses the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium method of standardising structural brain measures to quantify case-control differences and to compare brain-correlates of substance use disorders with those published in relation to other psychiatric disorders. Using the ENIGMA protocols, we report effect sizes derived from a meta-analysis of alcohol (seven studies, N = 798, 54% are cases) and cannabis (seven studies, N = 447, 45% are cases) dependent cases and age- and sex-matched controls. We conduct linear analyses using harmonised methods to process and parcellate brain data identical to those reported in the literature for ENIGMA case-control studies of major depression disorder (MDD), schizophrenia (SCZ) and bipolar disorder so that effect sizes are optimally comparable across disorders. R elationships between substance use disorder diagnosis and subcortical grey matter volumes and cortical thickness were assessed with intracranial volume, age and sex as co-variates . After correcting for multiple comparisons, AUD case-control meta-analysis of subcortical regions indicated significant differences in the thalamus, hippocampus, amygdala and accumbens, with effect sizes (0.23) generally equivalent to, or larger than |0.23| those previously reported for other psychiatric disorders (except for the pallidum and putamen). On measures of cortical thickness, AUD was associated with significant differences bilaterally in the fusiform gyrus, inferior temporal gyrus, temporal pole, superior frontal gyrus, and rostral and caudal anterior cingulate gyri. Meta-analysis of CUD case-control studies indicated reliable reductions in amygdala, accumbens and hippocampus volumes, with the former effect size comparable to, and the latter effect size around half of that reported for alcohol and SCZ. CUD was associated with lower cortical thickness in the frontal regions, particularly the medial orbitofrontal region, but this effect was not significant after correcting for multiple testing. This study allowed for an unbiased cross-disorder comparison of brain correlates of substance use disorders and showed alcohol-related brain anomalies equivalent in effect size to that found in SCZ in several subcortical and cortical regions and significantly greater alterations than those found in MDD in several subcortical and cortical regions. Although modest, CUD results overlapped with findings reported for AUD and other psychiatric conditions, but appear to be most robustly related to reduce thickness of the medial orbitofrontal cortex.
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http://dx.doi.org/10.1002/hbm.25114DOI Listing
July 2020