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Strike LT, Kerestes R, McMahon KL, de Zubicaray GI, Harding IH, Medland SE. Heritability of cerebellar subregion volumes in adolescent and young adult twins. Hum Brain Mapp 2024; 45:e26717. [PMID: 38798116 PMCID: PMC11128777 DOI: 10.1002/hbm.26717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Revised: 04/23/2024] [Accepted: 05/06/2024] [Indexed: 05/29/2024] Open
Abstract
Twin studies have found gross cerebellar volume to be highly heritable. However, whether fine-grained regional volumes within the cerebellum are similarly heritable is still being determined. Anatomical MRI scans from two independent datasets (QTIM: Queensland Twin IMaging, N = 798, mean age 22.1 years; QTAB: Queensland Twin Adolescent Brain, N = 396, mean age 11.3 years) were combined with an optimised and automated cerebellum parcellation algorithm to segment and measure 28 cerebellar regions. We show that the heritability of regional volumetric measures varies widely across the cerebellum (h 2 $$ {h}^2 $$ 47%-91%). Additionally, the good to excellent test-retest reliability for a subsample of QTIM participants suggests that non-genetic variance in cerebellar volumes is due primarily to unique environmental influences rather than measurement error. We also show a consistent pattern of strong associations between the volumes of homologous left and right hemisphere regions. Associations were predominantly driven by genetic effects shared between lobules, with only sparse contributions from environmental effects. These findings are consistent with similar studies of the cerebrum and provide a first approximation of the upper bound of heritability detectable by genome-wide association studies.
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Affiliation(s)
- Lachlan T. Strike
- Psychiatric Genetics, QIMR Berghofer Medical Research InstituteBrisbaneAustralia
- School of Psychology and Counselling, Faculty of HealthQueensland University of TechnologyKelvin GroveQueenslandAustralia
- School of Biomedical Sciences, Faculty of MedicineUniversity of QueenslandBrisbaneAustralia
| | - Rebecca Kerestes
- Department of Neuroscience, Central Clinical SchoolMonash UniversityMelbourneAustralia
| | - Katie L. McMahon
- School of Clinical Sciences, Centre for Biomedical TechnologiesQueensland University of TechnologyBrisbaneQueenslandAustralia
| | - Greig I. de Zubicaray
- School of Psychology and Counselling, Faculty of HealthQueensland University of TechnologyKelvin GroveQueenslandAustralia
| | - Ian H. Harding
- Department of Neuroscience, Central Clinical SchoolMonash UniversityMelbourneAustralia
- Cerebellum and Neurodegeneration, QIMR Berghofer Medical Research InstituteBrisbaneAustralia
| | - Sarah E. Medland
- Psychiatric Genetics, QIMR Berghofer Medical Research InstituteBrisbaneAustralia
- School of Psychology and Counselling, Faculty of HealthQueensland University of TechnologyKelvin GroveQueenslandAustralia
- School of PsychologyUniversity of QueenslandBrisbaneAustralia
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2
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Hodgson L, Li Y, Iturria-Medina Y, Stratton JA, Wolf G, Krishnaswamy S, Bennett DA, Bzdok D. Supervised latent factor modeling isolates cell-type-specific transcriptomic modules that underlie Alzheimer's disease progression. Commun Biol 2024; 7:591. [PMID: 38760483 PMCID: PMC11101463 DOI: 10.1038/s42003-024-06273-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Accepted: 05/01/2024] [Indexed: 05/19/2024] Open
Abstract
Late onset Alzheimer's disease (AD) is a progressive neurodegenerative disease, with brain changes beginning years before symptoms surface. AD is characterized by neuronal loss, the classic feature of the disease that underlies brain atrophy. However, GWAS reports and recent single-nucleus RNA sequencing (snRNA-seq) efforts have highlighted that glial cells, particularly microglia, claim a central role in AD pathophysiology. Here, we tailor pattern-learning algorithms to explore distinct gene programs by integrating the entire transcriptome, yielding distributed AD-predictive modules within the brain's major cell-types. We show that these learned modules are biologically meaningful through the identification of new and relevant enriched signaling cascades. The predictive nature of our modules, especially in microglia, allows us to infer each subject's progression along a disease pseudo-trajectory, confirmed by post-mortem pathological brain tissue markers. Additionally, we quantify the interplay between pairs of cell-type modules in the AD brain, and localized known AD risk genes to enriched module gene programs. Our collective findings advocate for a transition from cell-type-specificity to gene modules specificity to unlock the potential of unique gene programs, recasting the roles of recently reported genome-wide AD risk loci.
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Affiliation(s)
- Liam Hodgson
- School of Computer Science, McGill University, Montréal, QC, Canada
- Mila - Quebec Artificial Intelligence Institute, Montréal, QC, Canada
| | - Yue Li
- School of Computer Science, McGill University, Montréal, QC, Canada
| | - Yasser Iturria-Medina
- McConnell Brain Imaging Centre (BIC), MNI, Faculty of Medicine, McGill University, Montréal, Canada
- Neurology and Neurosurgery Department, Montreal Neurological Institute (MNI), Faculty of Medicine, McGill University, Montréal, Canada
- Ludmer Centre for Neuroinformatics and Mental Health, McGill University, Montréal, Canada
| | - Jo Anne Stratton
- Neurology and Neurosurgery Department, Montreal Neurological Institute (MNI), Faculty of Medicine, McGill University, Montréal, Canada
| | - Guy Wolf
- Mila - Quebec Artificial Intelligence Institute, Montréal, QC, Canada
- Department of Mathematics & Statistics, Université de Montréal, Montréal, Canada
| | - Smita Krishnaswamy
- Department of Computer Science, Department of Genetics, Yale University, New Haven, CT, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Danilo Bzdok
- Mila - Quebec Artificial Intelligence Institute, Montréal, QC, Canada.
- Department of Biomedical Engineering, Faculty of Medicine, McGill University, Montréal, QC, Canada.
- The Neuro - Montréal Neurological Institute, McConnell Brain Imaging Centre, Faculty of Medicine, McGill University, Montréal, QC, Canada.
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3
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Ghanem K, Saltoun K, Suvrathan A, Draganski B, Bzdok D. Longitudinal microstructural changes in 18 amygdala nuclei resonate with cortical circuits and phenomics. Commun Biol 2024; 7:477. [PMID: 38637627 PMCID: PMC11026520 DOI: 10.1038/s42003-024-06187-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 04/11/2024] [Indexed: 04/20/2024] Open
Abstract
The amygdala nuclei modulate distributed neural circuits that most likely evolved to respond to environmental threats and opportunities. So far, the specific role of unique amygdala nuclei in the context processing of salient environmental cues lacks adequate characterization across neural systems and over time. Here, we present amygdala nuclei morphometry and behavioral findings from longitudinal population data (>1400 subjects, age range 40-69 years, sampled 2-3 years apart): the UK Biobank offers exceptionally rich phenotyping along with brain morphology scans. This allows us to quantify how 18 microanatomical amygdala subregions undergo plastic changes in tandem with coupled neural systems and delineating their associated phenome-wide profiles. In the context of population change, the basal, lateral, accessory basal, and paralaminar nuclei change in lockstep with the prefrontal cortex, a region that subserves planning and decision-making. The central, medial and cortical nuclei are structurally coupled with the insular and anterior-cingulate nodes of the salience network, in addition to the MT/V5, basal ganglia, and putamen, areas proposed to represent internal bodily states and mediate attention to environmental cues. The central nucleus and anterior amygdaloid area are longitudinally tied with the inferior parietal lobule, known for a role in bodily awareness and social attention. These population-level amygdala-brain plasticity regimes in turn are linked with unique collections of phenotypes, ranging from social status and employment to sleep habits and risk taking. The obtained structural plasticity findings motivate hypotheses about the specific functions of distinct amygdala nuclei in humans.
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Affiliation(s)
- Karam Ghanem
- The Neuro - Montreal Neurological Institute (MNI), McConnell Brain Imaging Centre, Department of Biomedical Engineering, Faculty of Medicine, School of Computer Science, McGill University, Montreal, Canada.
- Mila - Quebec Artificial Intelligence Institute, Montreal, QC, Canada.
| | - Karin Saltoun
- The Neuro - Montreal Neurological Institute (MNI), McConnell Brain Imaging Centre, Department of Biomedical Engineering, Faculty of Medicine, School of Computer Science, McGill University, Montreal, Canada
- Mila - Quebec Artificial Intelligence Institute, Montreal, QC, Canada
| | - Aparna Suvrathan
- Department of Neurology and Neurosurgery, Department of Pediatrics, McGill University, Montreal, QC, Canada
- Brain Repair and Integrative Neuroscience (BRaIN) Research Program, Montreal, QC, Canada
- Research Institute of the McGill University Health Centre, Montreal, QC, Canada
| | - Bogdan Draganski
- LREN, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
- Neurology Department, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Danilo Bzdok
- The Neuro - Montreal Neurological Institute (MNI), McConnell Brain Imaging Centre, Department of Biomedical Engineering, Faculty of Medicine, School of Computer Science, McGill University, Montreal, Canada.
- Mila - Quebec Artificial Intelligence Institute, Montreal, QC, Canada.
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4
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Korbmacher M, van der Meer D, Beck D, de Lange AMG, Eikefjord E, Lundervold A, Andreassen OA, Westlye LT, Maximov II. Brain asymmetries from mid- to late life and hemispheric brain age. Nat Commun 2024; 15:956. [PMID: 38302499 PMCID: PMC10834516 DOI: 10.1038/s41467-024-45282-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 01/19/2024] [Indexed: 02/03/2024] Open
Abstract
The human brain demonstrates structural and functional asymmetries which have implications for ageing and mental and neurological disease development. We used a set of magnetic resonance imaging (MRI) metrics derived from structural and diffusion MRI data in N=48,040 UK Biobank participants to evaluate age-related differences in brain asymmetry. Most regional grey and white matter metrics presented asymmetry, which were higher later in life. Informed by these results, we conducted hemispheric brain age (HBA) predictions from left/right multimodal MRI metrics. HBA was concordant to conventional brain age predictions, using metrics from both hemispheres, but offers a supplemental general marker of brain asymmetry when setting left/right HBA into relationship with each other. In contrast to WM brain asymmetries, left/right discrepancies in HBA are lower at higher ages. Our findings outline various sex-specific differences, particularly important for brain age estimates, and the value of further investigating the role of brain asymmetries in brain ageing and disease development.
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Affiliation(s)
- Max Korbmacher
- Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen, Norway.
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway.
- Mohn Medical Imaging and Visualization Centre (MMIV), Bergen, Norway.
| | - Dennis van der Meer
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
- Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, Netherlands
| | - Dani Beck
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Ann-Marie G de Lange
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Eli Eikefjord
- Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen, Norway
- Mohn Medical Imaging and Visualization Centre (MMIV), Bergen, Norway
| | - Arvid Lundervold
- Mohn Medical Imaging and Visualization Centre (MMIV), Bergen, Norway
- Department of Biomedicine, University of Bergen, Bergen, Norway
| | - Ole A Andreassen
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Lars T Westlye
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Ivan I Maximov
- Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen, Norway.
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway.
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Omont-Lescieux S, Menu I, Salvia E, Poirel N, Oppenheim C, Houdé O, Cachia A, Borst G. Lateralization of the cerebral network of inhibition in children before and after cognitive training. Dev Cogn Neurosci 2023; 63:101293. [PMID: 37683326 PMCID: PMC10498008 DOI: 10.1016/j.dcn.2023.101293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 08/31/2023] [Accepted: 09/01/2023] [Indexed: 09/10/2023] Open
Abstract
Inhibitory control (IC) plays a critical role in cognitive and socio-emotional development. IC relies on a lateralized cortico-subcortical brain network including the inferior frontal cortex, anterior parts of insula, anterior cingulate cortex, caudate nucleus and putamen. Brain asymmetries play a critical role for IC efficiency. In parallel to age-related changes, IC can be improved following training. The aim of this study was to (1) assess the lateralization of IC network in children (N = 60, 9-10 y.o.) and (2) examine possible changes in neural asymmetry of this network from anatomical (structural MRI) and functional (resting-state fMRI) levels after 5-week computerized IC vs. active control (AC) training. We observed that IC training, but not AC training, led to a leftward lateralization of the putamen anatomy, similarly to what is observed in adults, supporting that training could accelerate the maturation of this structure.
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Affiliation(s)
- Sixtine Omont-Lescieux
- Université Paris Cité, LaPsyDÉ, CNRS, F-75005, Paris, France; Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, Imaging biomarkers for brain development and disorders, 75014 Paris, France; GHU-Paris Psychiatrie et Neurosciences, Hôpital Sainte Anne, F-75014 Paris, France
| | - Iris Menu
- Université Paris Cité, LaPsyDÉ, CNRS, F-75005, Paris, France; Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, Imaging biomarkers for brain development and disorders, 75014 Paris, France; GHU-Paris Psychiatrie et Neurosciences, Hôpital Sainte Anne, F-75014 Paris, France
| | - Emilie Salvia
- Université Paris Cité, LaPsyDÉ, CNRS, F-75005, Paris, France; GHU-Paris Psychiatrie et Neurosciences, Hôpital Sainte Anne, F-75014 Paris, France
| | - Nicolas Poirel
- Université Paris Cité, LaPsyDÉ, CNRS, F-75005, Paris, France; GIP Cyceron, Caen, France
| | - Catherine Oppenheim
- Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, Imaging biomarkers for brain development and disorders, 75014 Paris, France; GHU-Paris Psychiatrie et Neurosciences, Hôpital Sainte Anne, F-75014 Paris, France
| | - Olivier Houdé
- Université Paris Cité, LaPsyDÉ, CNRS, F-75005, Paris, France; GHU-Paris Psychiatrie et Neurosciences, Hôpital Sainte Anne, F-75014 Paris, France; Institut Universitaire de France, Paris, France
| | - Arnaud Cachia
- Université Paris Cité, LaPsyDÉ, CNRS, F-75005, Paris, France; Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, Imaging biomarkers for brain development and disorders, 75014 Paris, France; GHU-Paris Psychiatrie et Neurosciences, Hôpital Sainte Anne, F-75014 Paris, France
| | - Grégoire Borst
- Université Paris Cité, LaPsyDÉ, CNRS, F-75005, Paris, France; GHU-Paris Psychiatrie et Neurosciences, Hôpital Sainte Anne, F-75014 Paris, France; Institut Universitaire de France, Paris, France.
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6
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Wang J, Ma S, Yu P, He X. Evolution of Human Brain Left-Right Asymmetry: Old Genes with New Functions. Mol Biol Evol 2023; 40:msad181. [PMID: 37561991 PMCID: PMC10473864 DOI: 10.1093/molbev/msad181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Revised: 06/21/2023] [Accepted: 07/10/2023] [Indexed: 08/12/2023] Open
Abstract
The human brain is generally anatomically symmetrical, boasting mirror-like brain regions in the left and right hemispheres. Despite this symmetry, fine-scale structural asymmetries are prevalent and are believed to be responsible for distinct functional divisions within the brain. Prior studies propose that these asymmetric structures are predominantly primate specific or even unique to humans, suggesting that the genes contributing to the structural asymmetry of the human brain might have evolved recently. In our study, we identified approximately 1,500 traits associated with human brain asymmetry by collecting paired brain magnetic resonance imaging features from the UK Biobank. Each trait is measured in a specific region of one hemisphere and mirrored in the corresponding region of the other hemisphere. Conducting genome-wide association studies on these traits, we identified over 1,000 quantitative trait loci. Around these index single nucleotide polymorphisms, we found approximately 200 genes that are enriched in brain-related Gene Ontology terms and are predominantly upregulated in brain tissues. Interestingly, most of these genes are evolutionarily old, originating just prior to the emergence of Bilateria (bilaterally symmetrical animals) and Euteleostomi (bony vertebrates with a brain), at a significantly higher ratio than expected. Further analyses of these genes reveal a brain-specific upregulation in humans relative to other mammalian species. This suggests that the structural asymmetry of the human brain has been shaped by evolutionarily ancient genes that have assumed new functions over time.
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Affiliation(s)
- Jianguo Wang
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong Province, China
| | - Sidi Ma
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong Province, China
| | - Peijie Yu
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong Province, China
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Labache L, Ge T, Yeo BTT, Holmes AJ. Language network lateralization is reflected throughout the macroscale functional organization of cortex. Nat Commun 2023; 14:3405. [PMID: 37296118 PMCID: PMC10256741 DOI: 10.1038/s41467-023-39131-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Accepted: 05/30/2023] [Indexed: 06/12/2023] Open
Abstract
Hemispheric specialization is a fundamental feature of human brain organization. However, it is not yet clear to what extent the lateralization of specific cognitive processes may be evident throughout the broad functional architecture of cortex. While the majority of people exhibit left-hemispheric language dominance, a substantial minority of the population shows reverse lateralization. Using twin and family data from the Human Connectome Project, we provide evidence that atypical language dominance is associated with global shifts in cortical organization. Individuals with atypical language organization exhibit corresponding hemispheric differences in the macroscale functional gradients that situate discrete large-scale networks along a continuous spectrum, extending from unimodal through association territories. Analyses reveal that both language lateralization and gradient asymmetries are, in part, driven by genetic factors. These findings pave the way for a deeper understanding of the origins and relationships linking population-level variability in hemispheric specialization and global properties of cortical organization.
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Affiliation(s)
- Loïc Labache
- Department of Psychology, Yale University, New Haven, CT, 06520, US.
| | - Tian Ge
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, 02114, US
- Center for Precision Psychiatry, Department of Psychiatry, Massachusetts General Hospital, Boston, MA, 02114, US
- Stanley Center for Psychiatric Research, Broad Institute, Cambridge, MA, 02142, US
| | - B T Thomas Yeo
- Department of Electrical and Computer Engineering, Centre for Sleep and Cognition, National University of Singapore, Singapore, SG, 119077, Singapore
- Department of Electrical and Computer Engineering, Centre for Translational Magnetic Resonance Research, National University of Singapore, Singapore, SG, 119077, Singapore
- N.1 Institute for Health, National University of Singapore, Singapore, SG, 119077, Singapore
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, 02129, US
- National University of Singapore Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore, SG, 119077, Singapore
| | - Avram J Holmes
- Department of Psychology, Yale University, New Haven, CT, 06520, US.
- Department of Psychiatry, Yale University, New Haven, CT, 06520, US.
- Wu Tsai Institute, Yale University, New Haven, CT, 06520, US.
- Department of Psychiatry, Brain Health Institute, Rutgers University, Piscataway, NJ, 08854, US.
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8
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Yan X, Kong R, Xue A, Yang Q, Orban C, An L, Holmes AJ, Qian X, Chen J, Zuo XN, Zhou JH, Fortier MV, Tan AP, Gluckman P, Chong YS, Meaney MJ, Bzdok D, Eickhoff SB, Yeo BTT. Homotopic local-global parcellation of the human cerebral cortex from resting-state functional connectivity. Neuroimage 2023; 273:120010. [PMID: 36918136 PMCID: PMC10212507 DOI: 10.1016/j.neuroimage.2023.120010] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 02/25/2023] [Accepted: 03/08/2023] [Indexed: 03/13/2023] Open
Abstract
Resting-state fMRI is commonly used to derive brain parcellations, which are widely used for dimensionality reduction and interpreting human neuroscience studies. We previously developed a model that integrates local and global approaches for estimating areal-level cortical parcellations. The resulting local-global parcellations are often referred to as the Schaefer parcellations. However, the lack of homotopic correspondence between left and right Schaefer parcels has limited their use for brain lateralization studies. Here, we extend our previous model to derive homotopic areal-level parcellations. Using resting-fMRI and task-fMRI across diverse scanners, acquisition protocols, preprocessing and demographics, we show that the resulting homotopic parcellations are as homogeneous as the Schaefer parcellations, while being more homogeneous than five publicly available parcellations. Furthermore, weaker correlations between homotopic parcels are associated with greater lateralization in resting network organization, as well as lateralization in language and motor task activation. Finally, the homotopic parcellations agree with the boundaries of a number of cortical areas estimated from histology and visuotopic fMRI, while capturing sub-areal (e.g., somatotopic and visuotopic) features. Overall, these results suggest that the homotopic local-global parcellations represent neurobiologically meaningful subdivisions of the human cerebral cortex and will be a useful resource for future studies. Multi-resolution parcellations estimated from 1479 participants are publicly available (https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/brain_parcellation/Yan2023_homotopic).
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Affiliation(s)
- Xiaoxuan Yan
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Electrical and Computer Engineering, National University of Singapore, Singapore; N.1 Institute for Health and Institute for Digital Medicine (WisDM), National University of Singapore, Singapore; Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore
| | - Ru Kong
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Electrical and Computer Engineering, National University of Singapore, Singapore; N.1 Institute for Health and Institute for Digital Medicine (WisDM), National University of Singapore, Singapore
| | - Aihuiping Xue
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Electrical and Computer Engineering, National University of Singapore, Singapore; N.1 Institute for Health and Institute for Digital Medicine (WisDM), National University of Singapore, Singapore
| | - Qing Yang
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Electrical and Computer Engineering, National University of Singapore, Singapore; N.1 Institute for Health and Institute for Digital Medicine (WisDM), National University of Singapore, Singapore
| | - Csaba Orban
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Electrical and Computer Engineering, National University of Singapore, Singapore; N.1 Institute for Health and Institute for Digital Medicine (WisDM), National University of Singapore, Singapore
| | - Lijun An
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Electrical and Computer Engineering, National University of Singapore, Singapore; N.1 Institute for Health and Institute for Digital Medicine (WisDM), National University of Singapore, Singapore
| | - Avram J Holmes
- Yale University, Departments of Psychology and Psychiatry, New Haven, CT, Unites States of America
| | - Xing Qian
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Jianzhong Chen
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Electrical and Computer Engineering, National University of Singapore, Singapore; N.1 Institute for Health and Institute for Digital Medicine (WisDM), National University of Singapore, Singapore
| | - Xi-Nian Zuo
- State Key Laboratory of Cognitive Neuroscience and Learning/IDG McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; National Basic Public Science Data Center, China
| | - Juan Helen Zhou
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Electrical and Computer Engineering, National University of Singapore, Singapore; Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore
| | - Marielle V Fortier
- Department of Diagnostic and Interventional Imaging, KK Women's and Children's Hospital, Singapore; Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore
| | - Ai Peng Tan
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore; Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Peter Gluckman
- UK Centre for Human Evolution, Adaptation and Disease, Liggins Institute, University of Auckland, Auckland, New Zealand
| | - Yap Seng Chong
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore; Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Michael J Meaney
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore; Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Danilo Bzdok
- Department of Biomedical Engineering, Montreal Neurological Institute, McGill University, Montreal, QC, Canada; Mila - Quebec AI Institute, Montreal, QC, Canada
| | - Simon B Eickhoff
- Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Center Jülich, Jülich, Germany
| | - B T Thomas Yeo
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Electrical and Computer Engineering, National University of Singapore, Singapore; N.1 Institute for Health and Institute for Digital Medicine (WisDM), National University of Singapore, Singapore; Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore; Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, Unites States of America.
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Xu Z, Dong Y, Wang Y, Song L, Niu S, Wang S, Zhao M, Wang J, Cong L, Han X, Hou T, Tang S, Zhang Q, Du Y, Qiu C. Associations of macular microvascular parameters with cerebral small vessel disease in rural older adults: A population-based OCT angiography study. Front Neurol 2023; 14:1133819. [PMID: 37006481 PMCID: PMC10060796 DOI: 10.3389/fneur.2023.1133819] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 02/27/2023] [Indexed: 03/18/2023] Open
Abstract
ObjectiveTo explore the associations of macular microvascular parameters with cerebral small vessel disease (CSVD) in rural-dwelling older adults in China.MethodsThis population-based cross-sectional study included 195 participants (age ≥ 60 years; 57.4% women) in the optical coherence tomographic angiography (OCTA) sub-study within the Multimodal Interventions to delay Dementia and disability in rural China (MIND-China). Macular microvascular parameters were measured using the OCTA. We automatically estimated volumes of gray matter, white matter, and white matter hyperintensity (WMH), and manually assessed numbers of enlarged perivascular spaces (EPVS) and lacunes on brain magnetic resonance imaging. Data were analyzed with the general linear models.ResultsAdjusting for multiple confounders, lower vessel skeleton density (VSD) and higher vessel diameter index (VDI) were significantly associated with larger WMH volume (P < 0.05). Lower VSD and foveal density-300 (FD-300) of left eye were significantly associated with lower brain parenchymal volume (P < 0.05). In addition, lower areas of foveal avascular zone (FAZ) and FD-300 of left eye were significantly associated with more EPVS (P < 0.05). The associations of abnormal macular microvascular parameters with WMH volume were evident mainly among females. Macular microvascular parameters were not associated with lacunes.ConclusionMacular microvascular signs are associated with WMH, brain parenchymal volume, and EPVS in older adults. The OCTA-assessed macular microvascular parameters can be valuable markers for microvascular lesions in the brain.
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Affiliation(s)
- Zhe Xu
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Yi Dong
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, China
| | - Yongxiang Wang
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, China
| | - Lin Song
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, China
| | - Sijie Niu
- Shandong Provincial Key Laboratory of Network Based Intelligent Computing, School of Information Science and Engineering, University of Jinan, Jinan, Shandong, China
| | - Shanshan Wang
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, China
| | - Mingqing Zhao
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Jiafeng Wang
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Lin Cong
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, China
| | - Xiaojuan Han
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, China
| | - Tingting Hou
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, China
| | - Shi Tang
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, China
| | - Qinghua Zhang
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, China
- *Correspondence: Qinghua Zhang
| | - Yifeng Du
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, China
- Yifeng Du
| | - Chengxuan Qiu
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Aging Research Center and Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet-Stockholm University, Stockholm, Sweden
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