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Smith DM, Parekh P, Kennedy J, Loughnan R, Frei O, Nichols TE, Andreassen OA, Jernigan TL, Dale AM. Partitioning variance in cortical morphometry into genetic, environmental, and subject-specific components. Cereb Cortex 2024; 34:bhae234. [PMID: 38850213 PMCID: PMC11161865 DOI: 10.1093/cercor/bhae234] [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: 12/12/2023] [Revised: 05/09/2024] [Accepted: 05/19/2024] [Indexed: 06/10/2024] Open
Abstract
The relative contributions of genetic variation and experience in shaping the morphology of the adolescent brain are not fully understood. Using longitudinal data from 11,665 subjects in the ABCD Study, we fit vertex-wise variance components including family effects, genetic effects, and subject-level effects using a computationally efficient framework. Variance in cortical thickness and surface area is largely attributable to genetic influence, whereas sulcal depth is primarily explained by subject-level effects. Our results identify areas with heterogeneous distributions of heritability estimates that have not been seen in previous work using data from cortical regions. We discuss the biological importance of subject-specific variance and its implications for environmental influences on cortical development and maturation.
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Affiliation(s)
- Diana M Smith
- Medical Scientist Training Program, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
- Neurosciences Graduate Program, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
- Center for Human Development, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
- Center for Multimodal Imaging and Genetics, University of California, San Diego School of Medicine, 9500 Gilman Drive, La Jolla, CA 92093, USA
| | - Pravesh Parekh
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Problemveien 11, 0313 Oslo, Norway
| | - Joseph Kennedy
- Center for Human Development, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
- Center for Multimodal Imaging and Genetics, University of California, San Diego School of Medicine, 9500 Gilman Drive, La Jolla, CA 92093, USA
| | - Robert Loughnan
- Population Neuroscience and Genetics Lab, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
| | - Oleksandr Frei
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Problemveien 11, 0313 Oslo, Norway
- Centre for Bioinformatics, Department of Informatics, University of Oslo, Problemveien 11, 0313 Oslo, Norway
| | - Thomas E Nichols
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7FZ, UK
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, Headington, Oxford, OX3 9DU, UK
| | - Ole A Andreassen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Problemveien 11, 0313 Oslo, Norway
| | - Terry L Jernigan
- Center for Human Development, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
- Department of Cognitive Science, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
- Department of Radiology, University of California San Diego School of Medicine, 9500 Gilman Drive, La Jolla, CA 92093, USA
- Department of Psychiatry, University of California San Diego School of Medicine, 9500 Gilman Drive, La Jolla, CA 92093, USA
| | - Anders M Dale
- Center for Multimodal Imaging and Genetics, University of California, San Diego School of Medicine, 9500 Gilman Drive, La Jolla, CA 92093, USA
- Department of Cognitive Science, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
- Department of Radiology, University of California San Diego School of Medicine, 9500 Gilman Drive, La Jolla, CA 92093, USA
- Department of Psychiatry, University of California San Diego School of Medicine, 9500 Gilman Drive, La Jolla, CA 92093, USA
- Department of Neuroscience, University of California San Diego School of Medicine, 9500 Gilman Drive, La Jolla, CA 92093, USA
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Parekh P, Fan CC, Frei O, Palmer CE, Smith DM, Makowski C, Iversen JR, Pecheva D, Holland D, Loughnan R, Nedelec P, Thompson WK, Hagler DJ, Andreassen OA, Jernigan TL, Nichols TE, Dale AM. FEMA: Fast and efficient mixed-effects algorithm for large sample whole-brain imaging data. Hum Brain Mapp 2024; 45:e26579. [PMID: 38339910 PMCID: PMC10823765 DOI: 10.1002/hbm.26579] [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: 04/28/2023] [Revised: 12/08/2023] [Accepted: 12/17/2023] [Indexed: 02/12/2024] Open
Abstract
The linear mixed-effects model (LME) is a versatile approach to account for dependence among observations. Many large-scale neuroimaging datasets with complex designs have increased the need for LME; however LME has seldom been used in whole-brain imaging analyses due to its heavy computational requirements. In this paper, we introduce a fast and efficient mixed-effects algorithm (FEMA) that makes whole-brain vertex-wise, voxel-wise, and connectome-wide LME analyses in large samples possible. We validate FEMA with extensive simulations, showing that the estimates of the fixed effects are equivalent to standard maximum likelihood estimates but obtained with orders of magnitude improvement in computational speed. We demonstrate the applicability of FEMA by studying the cross-sectional and longitudinal effects of age on region-of-interest level and vertex-wise cortical thickness, as well as connectome-wide functional connectivity values derived from resting state functional MRI, using longitudinal imaging data from the Adolescent Brain Cognitive DevelopmentSM Study release 4.0. Our analyses reveal distinct spatial patterns for the annualized changes in vertex-wise cortical thickness and connectome-wide connectivity values in early adolescence, highlighting a critical time of brain maturation. The simulations and application to real data show that FEMA enables advanced investigation of the relationships between large numbers of neuroimaging metrics and variables of interest while considering complex study designs, including repeated measures and family structures, in a fast and efficient manner. The source code for FEMA is available via: https://github.com/cmig-research-group/cmig_tools/.
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Affiliation(s)
- Pravesh Parekh
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical MedicineUniversity of OsloOsloNorway
| | - Chun Chieh Fan
- Center for Population Neuroscience and GeneticsLaureate Institute for Brain ResearchTulsaOklahomaUSA
- Department of Radiology, School of MedicineUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Oleksandr Frei
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical MedicineUniversity of OsloOsloNorway
- Centre for Bioinformatics, Department of InformaticsUniversity of OsloOsloNorway
| | - Clare E. Palmer
- Center for Human DevelopmentUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Diana M. Smith
- Center for Human DevelopmentUniversity of California San DiegoLa JollaCaliforniaUSA
- Center for Multimodal Imaging and GeneticsUniversity of California San DiegoLa JollaCaliforniaUSA
- Neurosciences Graduate ProgramUniversity of California San DiegoLa JollaCaliforniaUSA
- Medical Scientist Training ProgramUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Carolina Makowski
- Department of Radiology, School of MedicineUniversity of California San DiegoLa JollaCaliforniaUSA
- Center for Multimodal Imaging and GeneticsUniversity of California San DiegoLa JollaCaliforniaUSA
| | - John R. Iversen
- Center for Human DevelopmentUniversity of California San DiegoLa JollaCaliforniaUSA
- Institute for Neural ComputationUniversity of California San DiegoLa JollaCaliforniaUSA
- The Swartz Center for Computational NeuroscienceUniversity of California San DiegoLa JollaCaliforniaUSA
- Department of Psychology Neuroscience & BehaviourMcMaster UniversityHamiltonOntarioCanada
| | - Diliana Pecheva
- Department of Radiology, School of MedicineUniversity of California San DiegoLa JollaCaliforniaUSA
- Center for Multimodal Imaging and GeneticsUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Dominic Holland
- Department of Radiology, School of MedicineUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Robert Loughnan
- Population Neuroscience and Genetics LabUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Pierre Nedelec
- Department of Radiology and Biomedical ImagingUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Wesley K. Thompson
- Center for Population Neuroscience and GeneticsLaureate Institute for Brain ResearchTulsaOklahomaUSA
| | - Donald J. Hagler
- Department of Radiology, School of MedicineUniversity of California San DiegoLa JollaCaliforniaUSA
- Center for Multimodal Imaging and GeneticsUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Ole A. Andreassen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical MedicineUniversity of OsloOsloNorway
| | - Terry L. Jernigan
- Department of Radiology, School of MedicineUniversity of California San DiegoLa JollaCaliforniaUSA
- Center for Human DevelopmentUniversity of California San DiegoLa JollaCaliforniaUSA
- Department of Cognitive ScienceUniversity of California San DiegoLa JollaCaliforniaUSA
- Department of PsychiatryUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Thomas E. Nichols
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population HealthUniversity of OxfordOxfordUK
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUK
| | - Anders M. Dale
- Department of Radiology, School of MedicineUniversity of California San DiegoLa JollaCaliforniaUSA
- Center for Multimodal Imaging and GeneticsUniversity of California San DiegoLa JollaCaliforniaUSA
- Department of Cognitive ScienceUniversity of California San DiegoLa JollaCaliforniaUSA
- Department of PsychiatryUniversity of California San DiegoLa JollaCaliforniaUSA
- Department of NeuroscienceUniversity of California San DiegoLa JollaCaliforniaUSA
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Coffman C, Feczko E, Larsen B, Tervo-Clemmens B, Conan G, Lundquist JT, Houghton A, Moore LA, Weldon K, McCollum R, Perrone AJ, Fayzullobekova B, Madison TJ, Earl E, Dominguez OM, Fair DA, Basu S. Heritability estimation of subcortical volumes in a multi-ethnic multi-site cohort study. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.11.575231. [PMID: 38260520 PMCID: PMC10802572 DOI: 10.1101/2024.01.11.575231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Heritability of regional subcortical brain volumes (rSBVs) describes the role of genetics in middle and inner brain development. rSBVs are highly heritable in adults but are not characterized well in adolescents. The Adolescent Brain Cognitive Development study (ABCD), taken over 22 US sites, provides data to characterize the heritability of subcortical structures in adolescence. In ABCD, site-specific effects co-occur with genetic effects which can bias heritability estimates. Existing methods adjusting for site effects require additional steps to adjust for site effects and can lead to inconsistent estimation. We propose a random-effect model-based method of moments approach that is a single step estimator and is a theoretically consistent estimator even when sites are imbalanced and performs well under simulations. We compare methods on rSBVs from ABCD. The proposed approach yielded heritability estimates similar to previous results derived from single-site studies. The cerebellum cortex and hippocampus were the most heritable regions (> 50%).
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Affiliation(s)
- Christian Coffman
- Division of Biostatistics, University of Minnesota, 100 Church Street SE, Minneapolis, 55455-0213, MN, USA
| | - Eric Feczko
- Department of Pediatrics, University of Minnesota, 100 Church Street SE, Minneapolis, 55455-0213, MN, USA
- Masonic Institue for the Devloping Brain, University of Minnesota, 2025 East River Parkway, Minneapolis, 55414, MN, USA
| | - Bart Larsen
- Department of Pediatrics, University of Minnesota, 100 Church Street SE, Minneapolis, 55455-0213, MN, USA
- Masonic Institue for the Devloping Brain, University of Minnesota, 2025 East River Parkway, Minneapolis, 55414, MN, USA
| | - Brenden Tervo-Clemmens
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, 100 Church Street SE, Minneapolis, 55455-0213, MN, USA
- Masonic Institue for the Devloping Brain, University of Minnesota, 2025 East River Parkway, Minneapolis, 55414, MN, USA
| | - Gregory Conan
- Masonic Institue for the Devloping Brain, University of Minnesota, 2025 East River Parkway, Minneapolis, 55414, MN, USA
| | - Jacob T. Lundquist
- Masonic Institue for the Devloping Brain, University of Minnesota, 2025 East River Parkway, Minneapolis, 55414, MN, USA
| | - Audrey Houghton
- Masonic Institue for the Devloping Brain, University of Minnesota, 2025 East River Parkway, Minneapolis, 55414, MN, USA
| | - Lucille A. Moore
- Masonic Institue for the Devloping Brain, University of Minnesota, 2025 East River Parkway, Minneapolis, 55414, MN, USA
| | - Kimberly Weldon
- Masonic Institue for the Devloping Brain, University of Minnesota, 2025 East River Parkway, Minneapolis, 55414, MN, USA
| | - Rae McCollum
- Masonic Institue for the Devloping Brain, University of Minnesota, 2025 East River Parkway, Minneapolis, 55414, MN, USA
| | - Anders J. Perrone
- Masonic Institue for the Devloping Brain, University of Minnesota, 2025 East River Parkway, Minneapolis, 55414, MN, USA
| | - Begim Fayzullobekova
- Masonic Institue for the Devloping Brain, University of Minnesota, 2025 East River Parkway, Minneapolis, 55414, MN, USA
| | - Thomas J. Madison
- Masonic Institue for the Devloping Brain, University of Minnesota, 2025 East River Parkway, Minneapolis, 55414, MN, USA
| | - Eric Earl
- Masonic Institue for the Devloping Brain, University of Minnesota, 2025 East River Parkway, Minneapolis, 55414, MN, USA
| | - Oscar Miranda Dominguez
- Department of Pediatrics, University of Minnesota, 100 Church Street SE, Minneapolis, 55455-0213, MN, USA
- Masonic Institue for the Devloping Brain, University of Minnesota, 2025 East River Parkway, Minneapolis, 55414, MN, USA
| | - Damien A. Fair
- Department of Pediatrics, University of Minnesota, 100 Church Street SE, Minneapolis, 55455-0213, MN, USA
- Masonic Institue for the Devloping Brain, University of Minnesota, 2025 East River Parkway, Minneapolis, 55414, MN, USA
| | - Saonli Basu
- Division of Biostatistics, University of Minnesota, 100 Church Street SE, Minneapolis, 55455-0213, MN, USA
- Masonic Institue for the Devloping Brain, University of Minnesota, 2025 East River Parkway, Minneapolis, 55414, MN, USA
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