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Miranda GG, Gonen C, Kraft JN, Rodrigue KM, Kennedy KM. Lifespan longitudinal changes in mesocortical thickness and executive function: Role of dopaminergic genetic predisposition. Neurobiol Aging 2025; 146:58-73. [PMID: 39613505 PMCID: PMC12024007 DOI: 10.1016/j.neurobiolaging.2024.11.005] [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: 09/19/2023] [Revised: 11/11/2024] [Accepted: 11/13/2024] [Indexed: 12/01/2024]
Abstract
Dopamine (DA) signaling is critical for optimal cognitive aging, especially in prefrontal-parietal and fronto-striatal networks. Single nucleotide polymorphisms associated with dopamine regulation, COMTVal158Met and DRD2C957T, stand to exert influence on executive function performance via neural properties. The current study investigated whether longitudinal thinning of mesocortical regions is related to COMT and DRD2 genetic predisposition and associated with decline in executive function over four-years. N=235 healthy adults aged 20-94 years were recruited, with n=124 returning 4-years later. Latent mixed effects modeling revealed dopamine-related thinning in several frontal, parietal, and cingulate regions as well as decline in verbal fluency category switching across 4-years. Mesocortical thinning was also related to switching performance. Greater cortical thinning interacted with DA-genotype risk for lower DA-availability to predict poorer switching performance in parietal and posterior cingulate cortex. These findings lend support to the notion that early-life factors, such as genetic influence on neurotransmitter function, play a role in cognitive and brain aging and their linked association.
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Affiliation(s)
- Giuseppe G Miranda
- Department of Psychology, School of Behavioral and Brain Sciences, Center for Vital Longevity, The University of Texas at Dallas, 1600 Viceroy Dr, Ste 800, Dallas, TX 75235 USA, United States
| | - Chen Gonen
- Department of Psychology, School of Behavioral and Brain Sciences, Center for Vital Longevity, The University of Texas at Dallas, 1600 Viceroy Dr, Ste 800, Dallas, TX 75235 USA, United States
| | - Jessica N Kraft
- Department of Psychology, School of Behavioral and Brain Sciences, Center for Vital Longevity, The University of Texas at Dallas, 1600 Viceroy Dr, Ste 800, Dallas, TX 75235 USA, United States
| | - Karen M Rodrigue
- Department of Psychology, School of Behavioral and Brain Sciences, Center for Vital Longevity, The University of Texas at Dallas, 1600 Viceroy Dr, Ste 800, Dallas, TX 75235 USA, United States
| | - Kristen M Kennedy
- Department of Psychology, School of Behavioral and Brain Sciences, Center for Vital Longevity, The University of Texas at Dallas, 1600 Viceroy Dr, Ste 800, Dallas, TX 75235 USA, United States.
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2
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Silva RF, Damaraju E, Li X, Kochunov P, Ford JM, Mathalon DH, Turner JA, van Erp TGM, Adali T, Calhoun VD. A Method for Multimodal IVA Fusion Within a MISA Unified Model Reveals Markers of Age, Sex, Cognition, and Schizophrenia in Large Neuroimaging Studies. Hum Brain Mapp 2024; 45:e70037. [PMID: 39560198 PMCID: PMC11574741 DOI: 10.1002/hbm.70037] [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: 03/21/2023] [Revised: 09/13/2024] [Accepted: 09/19/2024] [Indexed: 11/20/2024] Open
Abstract
With the increasing availability of large-scale multimodal neuroimaging datasets, it is necessary to develop data fusion methods which can extract cross-modal features. A general framework, multidataset independent subspace analysis (MISA), has been developed to encompass multiple blind source separation approaches and identify linked cross-modal sources in multiple datasets. In this work, we utilized the multimodal independent vector analysis (MMIVA) model in MISA to directly identify meaningful linked features across three neuroimaging modalities-structural magnetic resonance imaging (MRI), resting state functional MRI and diffusion MRI-in two large independent datasets, one comprising of control subjects and the other including patients with schizophrenia. Results show several linked subject profiles (sources) that capture age-associated decline, schizophrenia-related biomarkers, sex effects, and cognitive performance. For sources associated with age, both shared and modality-specific brain-age deltas were evaluated for association with non-imaging variables. In addition, each set of linked sources reveals a corresponding set of cross-modal spatial patterns that can be studied jointly. We demonstrate that the MMIVA fusion model can identify linked sources across multiple modalities, and that at least one set of linked, age-related sources replicates across two independent and separately analyzed datasets. The same set also presented age-adjusted group differences, with schizophrenia patients indicating lower multimodal source levels. Linked sets associated with sex and cognition are also reported for the UK Biobank dataset.
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Affiliation(s)
- Rogers F. Silva
- Tri‐Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS)Georgia State University, Georgia Institute of Technology, and Emory UniversityAtlantaGeorgiaUSA
| | - Eswar Damaraju
- Tri‐Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS)Georgia State University, Georgia Institute of Technology, and Emory UniversityAtlantaGeorgiaUSA
| | - Xinhui Li
- Tri‐Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS)Georgia State University, Georgia Institute of Technology, and Emory UniversityAtlantaGeorgiaUSA
- School of Electrical and Computer EngineeringGeorgia Institute of TechnologyAtlantaGeorgiaUSA
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of PsychiatryUniversity of Maryland School of MedicineBaltimoreMarylandUSA
| | - Judith M. Ford
- Veterans Affairs San Francisco Healthcare SystemSan FranciscoCaliforniaUSA
- Department of Psychiatry and Behavioral SciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Daniel H. Mathalon
- Veterans Affairs San Francisco Healthcare SystemSan FranciscoCaliforniaUSA
- Department of Psychiatry and Behavioral SciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Jessica A. Turner
- Tri‐Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS)Georgia State University, Georgia Institute of Technology, and Emory UniversityAtlantaGeorgiaUSA
- Psychology DepartmentGeorgia State UniversityAtlantaGeorgiaUSA
- Department of Psychiatry and Behavioral HealthThe Ohio State University Medical CenterColumbusOhioUSA
| | - Theo G. M. van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
- Center for the Neurobiology of Learning and MemoryUniversity of California IrvineIrvineCaliforniaUSA
| | - Tulay Adali
- Department of Computer Science and Electrical EngineeringUniversity of Maryland Baltimore CountyBaltimoreMarylandUSA
| | - Vince D. Calhoun
- Tri‐Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS)Georgia State University, Georgia Institute of Technology, and Emory UniversityAtlantaGeorgiaUSA
- School of Electrical and Computer EngineeringGeorgia Institute of TechnologyAtlantaGeorgiaUSA
- Psychology DepartmentGeorgia State UniversityAtlantaGeorgiaUSA
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3
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Schinz D, Schmitz-Koep B, Tahedl M, Teckenberg T, Schultz V, Schulz J, Zimmer C, Sorg C, Gaser C, Hedderich DM. Lower cortical thickness and increased brain aging in adults with cocaine use disorder. Front Psychiatry 2023; 14:1266770. [PMID: 38025412 PMCID: PMC10679447 DOI: 10.3389/fpsyt.2023.1266770] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Accepted: 10/16/2023] [Indexed: 12/01/2023] Open
Abstract
Background Cocaine use disorder (CUD) is a global health issue with severe behavioral and cognitive sequelae. While previous evidence suggests a variety of structural and age-related brain changes in CUD, the impact on both, cortical thickness and brain age measures remains unclear. Methods Derived from a publicly available data set (SUDMEX_CONN), 74 CUD patients and 62 matched healthy controls underwent brain MRI and behavioral-clinical assessment. We determined cortical thickness by surface-based morphometry using CAT12 and Brain Age Gap Estimate (BrainAGE) via relevance vector regression. Associations between structural brain changes and behavioral-clinical variables of patients with CUD were investigated by correlation analyses. Results We found significantly lower cortical thickness in bilateral prefrontal cortices, posterior cingulate cortices, and the temporoparietal junction and significantly increased BrainAGE in patients with CUD [mean (SD) = 1.97 (±3.53)] compared to healthy controls (p < 0.001, Cohen's d = 0.58). Increased BrainAGE was associated with longer cocaine abuse duration. Conclusion Results demonstrate structural brain abnormalities in CUD, particularly lower cortical thickness in association cortices and dose-dependent, increased brain age.
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Affiliation(s)
- David Schinz
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen- (FAU), Nürnberg, Germany
| | - Benita Schmitz-Koep
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Marlene Tahedl
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Timo Teckenberg
- Digital Management & Transformation, SRH Fernhochschule - The Mobile University, Riedlingen, Germany
| | - Vivian Schultz
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Julia Schulz
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Claus Zimmer
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Christian Sorg
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
- Department of Psychiatry, School of Medicine, Technical University of Munich, Munich, Germany
| | - Christian Gaser
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
- Department of Neurology, Jena University Hospital, Jena, Germany
- German Center for Mental Health (DZPG), Site Jena-Magdeburg-Halle, Germany
- Center for Intervention and Research on Adaptive and Maladaptive Brain Circuits Underlying Mental Health (C-I-R-C), Jena-Magdeburg-Halle, Germany
| | - Dennis M. Hedderich
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
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4
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Smith ET, Hennessee JP, Wig GS, Frank S, Gonzalez H, Bacci J, Chan M, Carreno CA, Kennedy KM, Rodrigue KM, Hertzog C, Park DC. Longitudinal changes in gray matter correspond to changes in cognition across the lifespan: implications for theories of cognition. Neurobiol Aging 2023; 129:1-14. [PMID: 37247578 PMCID: PMC10524455 DOI: 10.1016/j.neurobiolaging.2023.04.014] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 04/30/2023] [Accepted: 04/30/2023] [Indexed: 05/31/2023]
Abstract
The present study examines the association between gray matter volume and cognition. Studies that have examined this issue have focused primarily on older adults, whereas the present study examines the issue across the entire adult lifespan. A total of 463 adults, ages 20-88 at first assessment, were followed longitudinally across three assessments over 8-10years. Significant individual differences in a general cognition measure comprised of measures of speed of processing, working memory, and episodic memory were observed, as well as in measures of cortical and subcortical gray matter. Parallel process latent growth curve modeling showed a reliable relationship between decreases in cortical matter and cognitive decline across the entire adult lifespan, which persisted after controlling for age effects. Implications of these findings in relation to progression toward dementia, risk assessment, cognitive intervention, and environmental factors are discussed, as well as implications for theories of cognitive aging.
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Affiliation(s)
- Evan T Smith
- School of Behavioral and Brain Sciences, Department of Psychology, Center for Vital Longevity, University of Texas at Dallas, Dallas, TX, USA.
| | - Joseph P Hennessee
- School of Behavioral and Brain Sciences, Department of Psychology, Center for Vital Longevity, University of Texas at Dallas, Dallas, TX, USA
| | - Gagan S Wig
- School of Behavioral and Brain Sciences, Department of Psychology, Center for Vital Longevity, University of Texas at Dallas, Dallas, TX, USA; Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Sarah Frank
- School of Behavioral and Brain Sciences, Department of Psychology, Center for Vital Longevity, University of Texas at Dallas, Dallas, TX, USA
| | - Hector Gonzalez
- School of Behavioral and Brain Sciences, Department of Psychology, Center for Vital Longevity, University of Texas at Dallas, Dallas, TX, USA
| | - Julia Bacci
- School of Behavioral and Brain Sciences, Department of Psychology, Center for Vital Longevity, University of Texas at Dallas, Dallas, TX, USA
| | - Micaela Chan
- School of Behavioral and Brain Sciences, Department of Psychology, Center for Vital Longevity, University of Texas at Dallas, Dallas, TX, USA
| | - Claudia A Carreno
- School of Behavioral and Brain Sciences, Department of Psychology, Center for Vital Longevity, University of Texas at Dallas, Dallas, TX, USA
| | - Kristen M Kennedy
- School of Behavioral and Brain Sciences, Department of Psychology, Center for Vital Longevity, University of Texas at Dallas, Dallas, TX, USA
| | - Karen M Rodrigue
- School of Behavioral and Brain Sciences, Department of Psychology, Center for Vital Longevity, University of Texas at Dallas, Dallas, TX, USA
| | | | - Denise C Park
- School of Behavioral and Brain Sciences, Department of Psychology, Center for Vital Longevity, University of Texas at Dallas, Dallas, TX, USA
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5
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Nyberg L, Andersson M, Lundquist A, Baaré WFC, Bartrés-Faz D, Bertram L, Boraxbekk CJ, Brandmaier AM, Demnitz N, Drevon CA, Duezel S, Ebmeier KP, Ghisletta P, Henson R, Jensen DEA, Kievit RA, Knights E, Kühn S, Lindenberger U, Plachti A, Pudas S, Roe JM, Madsen KS, Solé-Padullés C, Sommerer Y, Suri S, Zsoldos E, Fjell AM, Walhovd KB. Individual differences in brain aging: heterogeneity in cortico-hippocampal but not caudate atrophy rates. Cereb Cortex 2023; 33:5075-5081. [PMID: 36197324 PMCID: PMC10151879 DOI: 10.1093/cercor/bhac400] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 09/13/2022] [Accepted: 09/14/2022] [Indexed: 11/13/2022] Open
Abstract
It is well documented that some brain regions, such as association cortices, caudate, and hippocampus, are particularly prone to age-related atrophy, but it has been hypothesized that there are individual differences in atrophy profiles. Here, we document heterogeneity in regional-atrophy patterns using latent-profile analysis of 1,482 longitudinal magnetic resonance imaging observations. The results supported a 2-group solution reflecting differences in atrophy rates in cortical regions and hippocampus along with comparable caudate atrophy. The higher-atrophy group had the most marked atrophy in hippocampus and also lower episodic memory, and their normal caudate atrophy rate was accompanied by larger baseline volumes. Our findings support and refine models of heterogeneity in brain aging and suggest distinct mechanisms of atrophy in striatal versus hippocampal-cortical systems.
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Affiliation(s)
- Lars Nyberg
- Department of Radiation Sciences (Radiology), Umeå University, 901 87 Umeå, Sweden
- Department of Integrative Medical Biology, Umeå University, 901 87 Umeå, Sweden
- Umeå Center for Functional Brain Imaging, Umeå University, 901 87 Umeå, Sweden
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Department of Psychology, University of Oslo, 0373 Oslo, Norway
| | - Micael Andersson
- Department of Integrative Medical Biology, Umeå University, 901 87 Umeå, Sweden
- Umeå Center for Functional Brain Imaging, Umeå University, 901 87 Umeå, Sweden
| | - Anders Lundquist
- Umeå Center for Functional Brain Imaging, Umeå University, 901 87 Umeå, Sweden
- Department of Statistics, USBE, Umeå University, Umeå S-90187, Sweden
| | - William F C Baaré
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, 2650 Copenhagen, Denmark
| | - David Bartrés-Faz
- Department of Medicine, Faculty of Medicine and Health Sciences, Institut de Neurociències, Universitat de Barcelona, and Institut d’Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), 08036 Barcelona, Spain
| | - Lars Bertram
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Department of Psychology, University of Oslo, 0373 Oslo, Norway
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, 23562 Lübeck, Germany
| | - Carl-Johan Boraxbekk
- Department of Radiation Sciences (Radiology), Umeå University, 901 87 Umeå, Sweden
- Umeå Center for Functional Brain Imaging, Umeå University, 901 87 Umeå, Sweden
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, 2650 Copenhagen, Denmark
- Faculty of Medical and Health Sciences, Institute for Clinical Medicine, University of Copenhagen, 2400 Copenhagen, Denmark
- Department of Neurology, Institute of Sports Medicine Copenhagen (ISMC), Copenhagen University Hospital - Bispebjerg and Frederiksberg, 2400 Copenhagen, Denmark
| | - Andreas M Brandmaier
- Center for Lifespan Psychology, Max Planck Institute for Human Development, 14195 Berlin, Germany
- MSB Medical School Berlin, 14197 Berlin, Germany
- Max Plank UCL Centre for Computational Psychiatry and Ageing Research, 14195 Berlin, Germany, and London, UK
| | - Naiara Demnitz
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, 2650 Copenhagen, Denmark
| | - Christian A Drevon
- Vitas AS, Science Park, 0349 Oslo, Norway
- Department of Nutrition, Faculty of Medicine, Institute of Basic Medical Sciences, University of Oslo, 0317 Oslo Norway
| | - Sandra Duezel
- Center for Lifespan Psychology, Max Planck Institute for Human Development, 14195 Berlin, Germany
| | - Klaus P Ebmeier
- Department of Psychiatry, University of Oxford, OX3 7JX Oxford, UK
| | - Paolo Ghisletta
- Faculty of Psychology and Educational Sciences, University of Geneva, 1204 Geneva, Switzerland
- UniDistance Suisse, 3900 Brig, Switzerland
- Swiss National Centre of Competence in Research LIVES, University of Geneva, 1204 Geneva, Switzerland
| | - Richard Henson
- Medical Research Council Cognition and Brain Sciences Unit, Department of Psychiatry, University of Cambridge, Cambridge CB2 7EF, England
| | - Daria E A Jensen
- Department of Psychiatry, University of Oxford, OX3 7JX Oxford, UK
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, University of Oxford, OX3 9DU Oxford, UK
| | - Rogier A Kievit
- Cognitive Neuroscience Department, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, 6525 GD Nijmegen, The Netherlands
| | - Ethan Knights
- Medical Research Council Cognition and Brain Sciences Unit, Department of Psychiatry, University of Cambridge, Cambridge CB2 7EF, England
| | - Simone Kühn
- Lise Meitner Group for Environmental Neuroscience, Max Planck Institute for Human Development & Clinic for Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany
| | - Ulman Lindenberger
- Center for Lifespan Psychology, Max Planck Institute for Human Development, 14195 Berlin, Germany
- Max Plank UCL Centre for Computational Psychiatry and Ageing Research, 14195 Berlin, Germany, and London, UK
| | - Anna Plachti
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, 2650 Copenhagen, Denmark
| | - Sara Pudas
- Department of Integrative Medical Biology, Umeå University, 901 87 Umeå, Sweden
- Umeå Center for Functional Brain Imaging, Umeå University, 901 87 Umeå, Sweden
| | - James M Roe
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Department of Psychology, University of Oslo, 0373 Oslo, Norway
| | - Kathrine Skak Madsen
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, 2650 Copenhagen, Denmark
- Radiography, Department of Technology, University College Copenhagen, 2200 Copenhagen N, Denmark
| | - Cristina Solé-Padullés
- Department of Medicine, Faculty of Medicine and Health Sciences, Institut de Neurociències, Universitat de Barcelona, and Institut d’Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), 08036 Barcelona, Spain
| | - Yasmine Sommerer
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, 23562 Lübeck, Germany
| | - Sana Suri
- Department of Psychiatry, University of Oxford, OX3 7JX Oxford, UK
- Cognitive Neuroscience Department, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, 6525 GD Nijmegen, The Netherlands
| | - Enikő Zsoldos
- Department of Psychiatry, University of Oxford, OX3 7JX Oxford, UK
- Cognitive Neuroscience Department, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, 6525 GD Nijmegen, The Netherlands
| | - Anders M Fjell
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Department of Psychology, University of Oslo, 0373 Oslo, Norway
- Center for Computational Radiology and Artificial Intelligence, Oslo University Hospital, 0373 Oslo, Norway
| | - Kristine B Walhovd
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Department of Psychology, University of Oslo, 0373 Oslo, Norway
- Center for Computational Radiology and Artificial Intelligence, Oslo University Hospital, 0373 Oslo, Norway
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6
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Sun D, Rakesh G, Haswell CC, Logue M, Baird CL, O'Leary EN, Cotton AS, Xie H, Tamburrino M, Chen T, Dennis EL, Jahanshad N, Salminen LE, Thomopoulos SI, Rashid F, Ching CRK, Koch SBJ, Frijling JL, Nawijn L, van Zuiden M, Zhu X, Suarez-Jimenez B, Sierk A, Walter H, Manthey A, Stevens JS, Fani N, van Rooij SJH, Stein M, Bomyea J, Koerte IK, Choi K, van der Werff SJA, Vermeiren RRJM, Herzog J, Lebois LAM, Baker JT, Olson EA, Straube T, Korgaonkar MS, Andrew E, Zhu Y, Li G, Ipser J, Hudson AR, Peverill M, Sambrook K, Gordon E, Baugh L, Forster G, Simons RM, Simons JS, Magnotta V, Maron-Katz A, du Plessis S, Disner SG, Davenport N, Grupe DW, Nitschke JB, deRoon-Cassini TA, Fitzgerald JM, Krystal JH, Levy I, Olff M, Veltman DJ, Wang L, Neria Y, De Bellis MD, Jovanovic T, Daniels JK, Shenton M, van de Wee NJA, Schmahl C, Kaufman ML, Rosso IM, Sponheim SR, Hofmann DB, Bryant RA, Fercho KA, Stein DJ, Mueller SC, Hosseini B, Phan KL, McLaughlin KA, Davidson RJ, Larson CL, May G, Nelson SM, Abdallah CG, Gomaa H, Etkin A, Seedat S, Harpaz-Rotem I, Liberzon I, van Erp TGM, Quidé Y, Wang X, Thompson PM, Morey RA. A comparison of methods to harmonize cortical thickness measurements across scanners and sites. Neuroimage 2022; 261:119509. [PMID: 35917919 PMCID: PMC9648725 DOI: 10.1016/j.neuroimage.2022.119509] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Revised: 07/07/2022] [Accepted: 07/22/2022] [Indexed: 12/02/2022] Open
Abstract
Results of neuroimaging datasets aggregated from multiple sites may be biased by site-specific profiles in participants' demographic and clinical characteristics, as well as MRI acquisition protocols and scanning platforms. We compared the impact of four different harmonization methods on results obtained from analyses of cortical thickness data: (1) linear mixed-effects model (LME) that models site-specific random intercepts (LMEINT), (2) LME that models both site-specific random intercepts and age-related random slopes (LMEINT+SLP), (3) ComBat, and (4) ComBat with a generalized additive model (ComBat-GAM). Our test case for comparing harmonization methods was cortical thickness data aggregated from 29 sites, which included 1,340 cases with posttraumatic stress disorder (PTSD) (6.2-81.8 years old) and 2,057 trauma-exposed controls without PTSD (6.3-85.2 years old). We found that, compared to the other data harmonization methods, data processed with ComBat-GAM was more sensitive to the detection of significant case-control differences (Χ2(3) = 63.704, p < 0.001) as well as case-control differences in age-related cortical thinning (Χ2(3) = 12.082, p = 0.007). Both ComBat and ComBat-GAM outperformed LME methods in detecting sex differences (Χ2(3) = 9.114, p = 0.028) in regional cortical thickness. ComBat-GAM also led to stronger estimates of age-related declines in cortical thickness (corrected p-values < 0.001), stronger estimates of case-related cortical thickness reduction (corrected p-values < 0.001), weaker estimates of age-related declines in cortical thickness in cases than controls (corrected p-values < 0.001), stronger estimates of cortical thickness reduction in females than males (corrected p-values < 0.001), and stronger estimates of cortical thickness reduction in females relative to males in cases than controls (corrected p-values < 0.001). Our results support the use of ComBat-GAM to minimize confounds and increase statistical power when harmonizing data with non-linear effects, and the use of either ComBat or ComBat-GAM for harmonizing data with linear effects.
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Affiliation(s)
- Delin Sun
- Brain Imaging and Analysis Center, Duke University, Durham, NC, USA.; Department of Veteran Affairs (VA) Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham, NC, USA.; Department of Psychology, The Education University of Hong Kong, Hong Kong, China
| | - Gopalkumar Rakesh
- Brain Imaging and Analysis Center, Duke University, Durham, NC, USA.; Department of Veteran Affairs (VA) Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham, NC, USA
| | - Courtney C Haswell
- Brain Imaging and Analysis Center, Duke University, Durham, NC, USA.; Department of Veteran Affairs (VA) Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham, NC, USA
| | - Mark Logue
- National Center for PTSD, VA Boston Healthcare System, Boston, MA, USA.; Department of Psychiatry, Boston University School of Medicine, Boston, MA, USA.; Biomedical Genetics, Boston University School of Medicine, Boston, MA, USA.; Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - C Lexi Baird
- Brain Imaging and Analysis Center, Duke University, Durham, NC, USA.; Department of Veteran Affairs (VA) Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham, NC, USA
| | - Erin N O'Leary
- Department of Psychiatry, University of Toledo, Toledo, OH, USA
| | - Andrew S Cotton
- Department of Psychiatry, University of Toledo, Toledo, OH, USA
| | - Hong Xie
- Department of Psychiatry, University of Toledo, Toledo, OH, USA
| | | | - Tian Chen
- Department of Psychiatry, University of Toledo, Toledo, OH, USA.; Psychiatry Neuroimaging Laboratory, Brigham & Women's Hospital, Boston, MA, USA
| | - Emily L Dennis
- Psychiatry Neuroimaging Laboratory, Brigham & Women's Hospital, Boston, MA, USA.; Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA.; Department of Neurology, University of Utah, Salt Lake City, UT, USA.; Stanford Neurodevelopment, Affect, and Psychopathology Laboratory, Stanford, CA, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Lauren E Salminen
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Faisal Rashid
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Christopher R K Ching
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Saskia B J Koch
- Department of Psychiatry, Amsterdam University Medical Centers, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.; Donders Institute for Brain, Cognition and Behavior, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Jessie L Frijling
- Department of Psychiatry, Amsterdam University Medical Centers, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Laura Nawijn
- Department of Psychiatry, Amsterdam University Medical Centers, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.; Department of Psychiatry, Amsterdam University Medical Centers, VU University Medical Center, VU University, Amsterdam, The Netherlands
| | - Mirjam van Zuiden
- Department of Psychiatry, Amsterdam University Medical Centers, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Xi Zhu
- Department of Psychiatry, Columbia University Medical Center, New York, NY, USA.; New York State Psychiatric Institute, New York, NY, USA
| | - Benjamin Suarez-Jimenez
- Del Monte Institute for Neuroscience, University of Rochester Medical Center, Rochester, NY, USA.; Department of Psychiatry, Columbia University Medical Center, New York, NY, USA.; New York State Psychiatric Institute, New York, NY, USA
| | - Anika Sierk
- University Medical Centre Charité, Berlin, Germany
| | | | | | - Jennifer S Stevens
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Negar Fani
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Sanne J H van Rooij
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Murray Stein
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Jessica Bomyea
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Inga K Koerte
- Psychiatry Neuroimaging Laboratory, Brigham & Women's Hospital, Boston, MA, USA.; Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-Universität, Munich, Germany
| | - Kyle Choi
- Health Services Research Center, University of California, San Diego, La Jolla, CA, USA
| | - Steven J A van der Werff
- Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands.; Leiden Institute for Brain and Cognition, Leiden, The Netherlands
| | | | - Julia Herzog
- Department of Psychosomatic Medicine and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Lauren A M Lebois
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.; Division of Depression and Anxiety Disorders, McLean Hospital, Belmont, MA, USA
| | - Justin T Baker
- Institute for Technology in Psychiatry, McLean Hospital, Harvard University, Belmont, MA, USA
| | - Elizabeth A Olson
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.; Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, MA, USA
| | - Thomas Straube
- Institute of Medical Psychology and Systems Neuroscience, University of Münster, Münster, Germany
| | - Mayuresh S Korgaonkar
- Brain Dynamics Centre, Westmead Institute of Medical Research, University of Sydney, Westmead, NSW, Australia
| | - Elpiniki Andrew
- Department of Psychology, University of Sydney, Westmead, NSW, Australia
| | - Ye Zhu
- Laboratory for Traumatic Stress Studies, Chinese Academy of Sciences Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Gen Li
- Laboratory for Traumatic Stress Studies, Chinese Academy of Sciences Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Jonathan Ipser
- SA MRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Anna R Hudson
- Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium
| | - Matthew Peverill
- Department of Psychology, University of Washington, Seattle, WA, USA
| | - Kelly Sambrook
- Department of Radiology, University of Washington, Seattle, WA, USA
| | - Evan Gordon
- Department of Radiology, Washington University, St. Louis, MO, USA
| | - Lee Baugh
- Division of Basic Biomedical Sciences, Sanford School of Medicine, University of South Dakota, Vermillion, SD, USA.; Center for Brain and Behavior Research, University of South Dakota, Vermillion, SD, USA.; Sioux Falls VA Health Care System, Sioux Falls, SD, USA
| | - Gina Forster
- Division of Basic Biomedical Sciences, Sanford School of Medicine, University of South Dakota, Vermillion, SD, USA.; Center for Brain and Behavior Research, University of South Dakota, Vermillion, SD, USA.; Brain Health Research Centre, Department of Anatomy, University of Otago, Dunedin, New Zealand
| | - Raluca M Simons
- Center for Brain and Behavior Research, University of South Dakota, Vermillion, SD, USA.; Department of Psychology, University of South Dakota, Vermillion, SD, USA
| | - Jeffrey S Simons
- Sioux Falls VA Health Care System, Sioux Falls, SD, USA.; Department of Psychology, University of South Dakota, Vermillion, SD, USA
| | - Vincent Magnotta
- Department of Radiology, Psychiatry, and Biomedical Engineering, University of Iowa, Iowa City, IA, USA
| | - Adi Maron-Katz
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Stefan du Plessis
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Seth G Disner
- Minneapolis VA Health Care System, Minneapolis, MN, USA.; Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - Nicholas Davenport
- Minneapolis VA Health Care System, Minneapolis, MN, USA.; Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - Daniel W Grupe
- Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI, USA
| | - Jack B Nitschke
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, USA
| | - Terri A deRoon-Cassini
- Department of Surgery, Division of Trauma and Acute Care Surgery, Medical College of Wisconsin, Milwaukee, WI, USA
| | | | - John H Krystal
- Division of Clinical Neuroscience, National Center for PTSD, West Haven, CT, USA.; Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Ifat Levy
- Division of Clinical Neuroscience, National Center for PTSD, West Haven, CT, USA.; Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Miranda Olff
- Department of Psychiatry, Amsterdam University Medical Centers, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.; ARQ National Psychotrauma Centre, Diemen, The Netherlands
| | - Dick J Veltman
- Department of Psychiatry, Amsterdam University Medical Center, location VUMC, Amsterdam, The Netherlands
| | - Li Wang
- Laboratory for Traumatic Stress Studies, Chinese Academy of Sciences Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Yuval Neria
- Department of Psychiatry, Columbia University Medical Center, New York, NY, USA.; New York State Psychiatric Institute, New York, NY, USA
| | - Michael D De Bellis
- Healthy Childhood Brain Development Developmental Traumatology Research Program, Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
| | - Tanja Jovanovic
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, USA
| | - Judith K Daniels
- Department of Clinical Psychology, University of Groningen, Groningen, The Netherlands
| | - Martha Shenton
- Psychiatry Neuroimaging Laboratory, Brigham & Women's Hospital, Boston, MA, USA.; VA Boston Healthcare System, Brockton Division, Brockton, MA, USA
| | - Nic J A van de Wee
- Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands.; Leiden Institute for Brain and Cognition, Leiden, The Netherlands
| | - Christian Schmahl
- Department of Psychosomatic Medicine and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Milissa L Kaufman
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.; Division of Women's Mental Health, McLean Hospital, Belmont, MA, USA
| | - Isabelle M Rosso
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.; Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, MA, USA
| | - Scott R Sponheim
- Minneapolis VA Health Care System, Minneapolis, MN, USA.; Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - David Bernd Hofmann
- Institute of Medical Psychology and Systems Neuroscience, University of Münster, Münster, Germany
| | - Richard A Bryant
- School of Psychology, University of New South Wales, Sydney, NSW, Australia
| | - Kelene A Fercho
- Division of Basic Biomedical Sciences, Sanford School of Medicine, University of South Dakota, Vermillion, SD, USA.; Center for Brain and Behavior Research, University of South Dakota, Vermillion, SD, USA.; Sioux Falls VA Health Care System, Sioux Falls, SD, USA.; Civil Aerospace Medical Institute, US Federal Aviation Administration, Oklahoma City, OK, USA
| | - Dan J Stein
- SA MRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Sven C Mueller
- Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium
| | - Bobak Hosseini
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA
| | - K Luan Phan
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA.; Mental Health Service Line, Jesse Brown VA Chicago Health Care System, Chicago, IL, USA
| | | | - Richard J Davidson
- Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI, USA.; Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, USA.; Department of Psychology, University of Wisconsin-Madison, Madison, WI, USA
| | - Christine L Larson
- Department of Psychology, University of Wisconsin-Milwaukee, Milwaukee, WI, USA
| | - Geoffrey May
- Veterans Integrated Service Network-17 Center of Excellence for Research on Returning War Veterans, Waco, TX, USA.; Department of Psychology and Neuroscience, Baylor University, Waco, TX, USA.; Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX, USA.; Department of Psychiatry and Behavioral Science, Texas A&M University Health Science Center, Bryan, TX, USA
| | - Steven M Nelson
- Veterans Integrated Service Network-17 Center of Excellence for Research on Returning War Veterans, Waco, TX, USA.; Department of Psychology and Neuroscience, Baylor University, Waco, TX, USA.; Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX, USA.; Department of Psychiatry and Behavioral Science, Texas A&M University Health Science Center, Bryan, TX, USA
| | - Chadi G Abdallah
- Division of Clinical Neuroscience, National Center for PTSD, West Haven, CT, USA.; Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Hassaan Gomaa
- Department of Psychiatry and Behavioral Health, Pennsylvania State University, Hershey, PA, USA
| | - Amit Etkin
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA.; VA Palo Alto Health Care System, Palo Alto, CA, USA
| | - Soraya Seedat
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Ilan Harpaz-Rotem
- Division of Clinical Neuroscience, National Center for PTSD, West Haven, CT, USA.; Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Israel Liberzon
- Department of Psychiatry and Behavioral Science, Texas A&M University, College Station, TX, USA
| | - Theo G M van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA.; Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, CA, USA
| | - Yann Quidé
- School of Psychology, The University of New South Wales, Sydney, NSW, Australia.; Neuroscience Research Australia, Randwick, NSW, Australia
| | - Xin Wang
- Department of Mathematics and Statistics, University of Toledo, Toledo, OH, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Rajendra A Morey
- Brain Imaging and Analysis Center, Duke University, Durham, NC, USA.; Department of Veteran Affairs (VA) Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham, NC, USA..
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Gómez-Ramírez J, Fernández-Blázquez MA, González-Rosa JJ. A Causal Analysis of the Effect of Age and Sex Differences on Brain Atrophy in the Elderly Brain. Life (Basel) 2022; 12:1586. [PMID: 36295023 PMCID: PMC9656120 DOI: 10.3390/life12101586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 09/16/2022] [Accepted: 09/18/2022] [Indexed: 01/25/2023] Open
Abstract
We studied how brain volume loss in old age is affected by age, the APOE gene, sex, and the level of education completed. The quantitative characterization of brain volume loss at an old age relative to a young age requires-at least in principle-two MRI scans, one performed at a young age and one at an old age. There is, however, a way to address this problem when having only one MRI scan obtained at an old age. We computed the total brain losses of elderly subjects as a ratio between the estimated brain volume and the estimated total intracranial volume. Magnetic resonance imaging (MRI) scans of 890 healthy subjects aged 70 to 85 years were assessed. A causal analysis of factors affecting brain atrophy was performed using probabilistic Bayesian modelling and the mathematics of causal inference. We found that both age and sex were causally related to brain atrophy, with women reaching an elderly age with a 1% larger brain volume relative to their intracranial volume than men. How the brain ages and the rationale for sex differences in brain volume losses during the adult lifespan are questions that need to be addressed with causal inference and empirical data. The graphical causal modelling presented here can be instrumental in understanding a puzzling scientific area of study-the biological aging of the brain.
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Affiliation(s)
- Jaime Gómez-Ramírez
- Department of Psychology, University of Cadiz, 11003 Cadiz, Spain
- Institute of Biomedical Research Cadiz (INiBICA), 11009 Cadiz, Spain
| | | | - Javier J. González-Rosa
- Department of Psychology, University of Cadiz, 11003 Cadiz, Spain
- Institute of Biomedical Research Cadiz (INiBICA), 11009 Cadiz, Spain
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8
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Sele S, Liem F, Mérillat S, Jäncke L. Age-related decline in the brain: a longitudinal study on inter-individual variability of cortical thickness, area, volume, and cognition. Neuroimage 2021; 240:118370. [PMID: 34245866 DOI: 10.1016/j.neuroimage.2021.118370] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Revised: 06/28/2021] [Accepted: 07/05/2021] [Indexed: 12/21/2022] Open
Abstract
Magnetic Resonance Imaging (MRI) studies have shown that cortical volume declines with age. Although volume is a multiplicative measure consisting of thickness and area, few studies have focused on both its components. Information on decline variability and associations between person-specific changes of different brain metrics, brain regions, and cognition is sparse. In addition, the estimates have often been biased by the measurement error, because three repeated measures are minimally required to separate the measurement error from person-specific changes. With a sample size of N = 231, five repeated measures, and an observational time span of seven years, this study explores the associations between changes of different brain metrics, brain regions, and cognitive abilities in aging. Person-specific changes were obtained by latent growth curve models using Bayesian estimation. Our data indicate that both thickness and area are important contributors to volumetric changes. In most brain regions, area clearly declined on average over the years, while thickness showed only little decline. However, there was also substantial variation around the average slope in thickness and area. The correlation pattern of changes in thickness between brain regions was strong and largely homogenous. The pattern for changes in area was similar but weaker, indicating that factors affecting area may be more region-specific. Changes in thickness and volume were substantially correlated with changes in cognition. In some brain regions, changes in area were also related to changes in cognition. Overall, studying the associations between the trajectories of brain regions in different brain metrics provides insights into the regional heterogeneity of structural changes. SIGNIFICANCE STATEMENT: Many studies have described volumetric brain changes in aging. Few studies have focused on both its individual components: area and thickness. Longitudinal studies with three or more time points are highly needed, because they provide more precise average change estimates and, more importantly, allow us to quantify the associations between changes in the different brain metrics, brain regions, and other variables (e.g. cognitive abilities). Studying these associations is important because they can provide information regarding possible underlying factors of these changes. Our study, with a large sample size, five repeated measures, and an observational time span of seven years, provides new insights about the associations between person-specific changes in thickness, area, volume, and cognitive abilities.
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Affiliation(s)
- Silvano Sele
- Division Neuropsychology, Department of Psychology, University of Zurich, Zurich, Switzerland; University Research Priority Program "Dynamics of Healthy Aging", University of Zurich, Zurich, Switzerland.
| | - Franziskus Liem
- University Research Priority Program "Dynamics of Healthy Aging", University of Zurich, Zurich, Switzerland
| | - Susan Mérillat
- University Research Priority Program "Dynamics of Healthy Aging", University of Zurich, Zurich, Switzerland
| | - Lutz Jäncke
- Division Neuropsychology, Department of Psychology, University of Zurich, Zurich, Switzerland; University Research Priority Program "Dynamics of Healthy Aging", University of Zurich, Zurich, Switzerland.
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9
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Hou M, de Chastelaine M, Donley BE, Rugg MD. Specific and general relationships between cortical thickness and cognition in older adults: a longitudinal study. Neurobiol Aging 2021; 102:89-101. [PMID: 33765434 PMCID: PMC8110604 DOI: 10.1016/j.neurobiolaging.2020.11.004] [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: 06/26/2020] [Revised: 09/22/2020] [Accepted: 11/02/2020] [Indexed: 10/23/2022]
Abstract
Prior studies suggest that relationships between regional cortical thickness and domain-specific cognitive performance can be mediated by the relationship between global cortical thickness and domain-general cognition. Whether such findings extend to longitudinal cognitive change remains unclear. Here, we examined the relationships in healthy older adults between cognitive performance, longitudinal cognitive change over 3 years, and cortical thickness at baseline of the left and right inferior frontal gyrus (IFG) and left and right hemispheres. Both right IFG and right hemisphere thickness predicted baseline general cognition and domain-specific cognitive performance. Right IFG thickness was also predictive of longitudinal memory change. However, right IFG thickness was uncorrelated with cognitive performance and memory change after controlling for the mean thickness of other ipsilateral cortical regions. In addition, most identified associations between cortical thickness and specific cognitive domains were nonsignificant after controlling for the variance shared with other cognitive domains. Thus, relationships between right IFG thickness, cognitive performance, and memory change appear to be largely accounted for by more generic relationships between cortical thickness and cognition. This article is part of the Virtual Special Issue titled "COGNITIVE NEUROSCIENCE OF HEALTHY AND PATHOLOGICAL AGING". The full issue can be found on ScienceDirect athttps://www.sciencedirect.com/journal/neurobiology-of-aging/special-issue/105379XPWJP.
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Affiliation(s)
- Mingzhu Hou
- Center for Vital Longevity and School of Behavioral and Brain Sciences, The University of Texas at Dallas, Dallas, TX, USA.
| | - Marianne de Chastelaine
- Center for Vital Longevity and School of Behavioral and Brain Sciences, The University of Texas at Dallas, Dallas, TX, USA
| | - Brian E Donley
- Center for Vital Longevity and School of Behavioral and Brain Sciences, The University of Texas at Dallas, Dallas, TX, USA
| | - Michael D Rugg
- Center for Vital Longevity and School of Behavioral and Brain Sciences, The University of Texas at Dallas, Dallas, TX, USA; School of Psychology, University of East Anglia, Norwich, UK
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10
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Miranda GG, Rodrigue KM, Kennedy KM. Cortical thickness mediates the relationship between DRD2 C957T polymorphism and executive function across the adult lifespan. Brain Struct Funct 2021; 226:121-136. [PMID: 33179159 PMCID: PMC7855542 DOI: 10.1007/s00429-020-02169-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2020] [Accepted: 10/24/2020] [Indexed: 12/26/2022]
Abstract
Dopamine (DA) signaling is critical for optimal cognitive performance. Aging is accompanied by a change in the strength of this signaling, with a loss of striatal and extrastriatal D2 binding potential. The reduction in dopamine modulation with age negatively influences various aspects of cognition. DRD2 C957T (rs6277) impacts DA D2 receptor density and availability, with C homozygotes linked to lower striatal DA availability and reduced executive functioning (EF), but also high extrastriatal binding potential. Here, we investigated in 176 participants aged 20-94 years whether: (1) DRD2 C carriers differ from T carriers in cortical thickness or subcortical volume in areas of high concentrations of D2 receptors that receive projections from mesocortical or nigrostriatal dopaminergic pathways; (2) whether the DRD2*COMT relationship has any synergistic effects on cortical thickness; (3) whether the effect of DRD2 on brain structure depends upon age; and (4) whether DRD2-related regional thinning affects executive function performance. We show that DRD2 impacts cortical thickness in the superior parietal lobule, precuneus, and anterior cingulate (marginal after FDR correction), while statistically controlling sex, age, and COMT genotype. Specifically, C homozygotes demonstrated thinner cortices than both heterozygotes and/or T homozygotes in an age-invariant manner. Additionally, DRD2 predicted executive function performance via cortical thickness. The results highlight that genetic influences on dopamine availability impact cognitive performance via the contribution of brain structure in cortical regions influenced by DRD2.
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Affiliation(s)
- Giuseppe G Miranda
- Center for Vital Longevity, School of Behavioral and Brain Science, The University of Texas At Dallas, Dallas, TX, USA
| | - Karen M Rodrigue
- Center for Vital Longevity, School of Behavioral and Brain Science, The University of Texas At Dallas, Dallas, TX, USA
| | - Kristen M Kennedy
- Center for Vital Longevity, School of Behavioral and Brain Science, The University of Texas At Dallas, Dallas, TX, USA.
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11
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Nyberg L, Boraxbekk CJ, Sörman DE, Hansson P, Herlitz A, Kauppi K, Ljungberg JK, Lövheim H, Lundquist A, Adolfsson AN, Oudin A, Pudas S, Rönnlund M, Stiernstedt M, Sundström A, Adolfsson R. Biological and environmental predictors of heterogeneity in neurocognitive ageing: Evidence from Betula and other longitudinal studies. Ageing Res Rev 2020; 64:101184. [PMID: 32992046 DOI: 10.1016/j.arr.2020.101184] [Citation(s) in RCA: 62] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 09/04/2020] [Accepted: 09/15/2020] [Indexed: 12/15/2022]
Abstract
Individual differences in cognitive performance increase with advancing age, reflecting marked cognitive changes in some individuals along with little or no change in others. Genetic and lifestyle factors are assumed to influence cognitive performance in ageing by affecting the magnitude and extent of age-related brain changes (i.e., brain maintenance or atrophy), as well as the ability to recruit compensatory processes. The purpose of this review is to present findings from the Betula study and other longitudinal studies, with a focus on clarifying the role of key biological and environmental factors assumed to underlie individual differences in brain and cognitive ageing. We discuss the vital importance of sampling, analytic methods, consideration of non-ignorable dropout, and related issues for valid conclusions on factors that influence healthy neurocognitive ageing.
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Affiliation(s)
- Lars Nyberg
- Department of Radiation Sciences, Umeå University, S-90187 Umeå, Sweden; Umeå Center for Functional Brain Imaging (UFBI), Umeå University, S-90187 Umeå, Sweden; Department of Integrative Medical Biology, Umeå University, S-90187 Umeå, Sweden.
| | - Carl-Johan Boraxbekk
- Department of Radiation Sciences, Umeå University, S-90187 Umeå, Sweden; Umeå Center for Functional Brain Imaging (UFBI), Umeå University, S-90187 Umeå, Sweden; Danish Research Centre for Magnetic Resonance (DRCMR), Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Denmark; Institute of Sports Medicine Copenhagen (ISMC), Copenhagen University Hospital Bispebjerg, Copenhagen, Denmark
| | - Daniel Eriksson Sörman
- Department of Human Work Science, Luleå University of Technology, SE-97187 Luleå, Sweden
| | - Patrik Hansson
- Department of Psychology, Umeå University, S-90187 Umeå, Sweden
| | - Agneta Herlitz
- Department of Clinical Neuroscience, Division of Psychology, Karolinska Institutet, S-17177 Stockholm, Sweden
| | - Karolina Kauppi
- Department of Integrative Medical Biology, Umeå University, S-90187 Umeå, Sweden; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Jessica K Ljungberg
- Department of Human Work Science, Luleå University of Technology, SE-97187 Luleå, Sweden
| | - Hugo Lövheim
- Department of Community Medicine and Rehabilitation, Geriatric Medicine, Umeå University, Umeå, Sweden; Wallenberg Centre for Molecular Medicine (WCMM), Umeå University, Umeå, Sweden
| | - Anders Lundquist
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, S-90187 Umeå, Sweden; Department of Statistics, USBE, Umeå University, 901 87 Umeå, Sweden
| | | | - Anna Oudin
- Department of Public Health and Clinical Medicine, Umeå University, S-90187 Umeå, Sweden; Environment Society and Health, Occupational and Environmental Medicine, Lund University
| | - Sara Pudas
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, S-90187 Umeå, Sweden; Department of Integrative Medical Biology, Umeå University, S-90187 Umeå, Sweden
| | | | - Mikael Stiernstedt
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, S-90187 Umeå, Sweden; Department of Integrative Medical Biology, Umeå University, S-90187 Umeå, Sweden
| | - Anna Sundström
- Department of Psychology, Umeå University, S-90187 Umeå, Sweden; Centre for Demographic and Ageing Research (CEDAR), Umeå University, Umeå, S-90187, Sweden
| | - Rolf Adolfsson
- Department of Clinical Sciences, Umeå University, S-90187 Umeå, Sweden
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12
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Oschwald J, Guye S, Liem F. Brain structure and cognitive ability in healthy aging: a review on longitudinal correlated change. Rev Neurosci 2019; 31:1-57. [PMID: 31194693 PMCID: PMC8572130 DOI: 10.1515/revneuro-2018-0096] [Citation(s) in RCA: 149] [Impact Index Per Article: 24.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2018] [Accepted: 03/02/2019] [Indexed: 12/20/2022]
Abstract
Little is still known about the neuroanatomical substrates related to changes in specific cognitive abilities in the course of healthy aging, and the existing evidence is predominantly based on cross-sectional studies. However, to understand the intricate dynamics between developmental changes in brain structure and changes in cognitive ability, longitudinal studies are needed. In the present article, we review the current longitudinal evidence on correlated changes between magnetic resonance imaging-derived measures of brain structure (e.g. gray matter/white matter volume, cortical thickness), and laboratory-based measures of fluid cognitive ability (e.g. intelligence, memory, processing speed) in healthy older adults. To theoretically embed the discussion, we refer to the revised Scaffolding Theory of Aging and Cognition. We found 31 eligible articles, with sample sizes ranging from n = 25 to n = 731 (median n = 104), and participant age ranging from 19 to 103. Several of these studies report positive correlated changes for specific regions and specific cognitive abilities (e.g. between structures of the medial temporal lobe and episodic memory). However, the number of studies presenting converging evidence is small, and the large methodological variability between studies precludes general conclusions. Methodological and theoretical limitations are discussed. Clearly, more empirical evidence is needed to advance the field. Therefore, we provide guidance for future researchers by presenting ideas to stimulate theory and methods for development.
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Affiliation(s)
- Jessica Oschwald
- University Research Priority Program ‘Dynamics of Healthy Aging’, University of Zurich, Andreasstrasse 15, CH-8050 Zurich, Switzerland
| | - Sabrina Guye
- University Research Priority Program ‘Dynamics of Healthy Aging’, University of Zurich, Andreasstrasse 15, CH-8050 Zurich, Switzerland
| | - Franziskus Liem
- University Research Priority Program ‘Dynamics of Healthy Aging’, University of Zurich, Andreasstrasse 15, CH-8050 Zurich, Switzerland
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13
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Shi L, Cheng Y, Xu Y, Shen Z, Lu Y, Zhou C, Jiang L, Zhang Y, Zhu F, Xu X. Effects of hypertension on cerebral cortical thickness alterations in patients with type 2 diabetes. Diabetes Res Clin Pract 2019; 157:107872. [PMID: 31593745 DOI: 10.1016/j.diabres.2019.107872] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Revised: 08/31/2019] [Accepted: 09/30/2019] [Indexed: 01/09/2023]
Abstract
AIMS Although hypertension (HTN) is the high comorbidity of Type 2 diabetes mellitus (T2DM) and known to be a vascular risk factor for brain damage, the effects of HTN on brain function in T2DM patients are not well understood. Present study was performed to investigate whether HTN might accelerate the Cerebral cortical thickness (CT) alterations in patients with T2DM. METHODS We enrolled 35 participants with only T2DM, 25 T2DM patients with HTN (HT2DM) and 28 healthy controls (HCs). The cognitive function was assessed and brain image data was collected then the CT was calculated for each participant. Partial correlations between the CT of each brain region and standard laboratory testing data and neuropsychological scale scores were also analyzed. Multivariable regression analysis was performed to evaluated the vascular risk factors and brain regions with different CT in HT2DM patients. RESULTS Cognitive impairment is associated with thinning of the cerebral cortical thickness reduction in T2DM patients. CT thinning in the left inferior parietal lobe, left posterior cingulate and right precuneus were observed in HT2DM group relative to only T2DM group. Furthermore, the CT decreasing in the right precuneus was negatively correlated with duration of HTN. CONCLUSION The current study revealed that coexistent HTN may accelerate the CT reduction in T2DM patients.
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Affiliation(s)
- Li Shi
- Department of Endocrinology, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Yuqi Cheng
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Yushan Xu
- Department of Endocrinology, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Zonglin Shen
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Yi Lu
- Department of MRI, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Cong Zhou
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Linling Jiang
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Yan Zhang
- Department of Endocrinology, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Fangyu Zhu
- Department of MRI, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Xiufeng Xu
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, China.
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14
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Hoagey DA, Rieck JR, Rodrigue KM, Kennedy KM. Joint contributions of cortical morphometry and white matter microstructure in healthy brain aging: A partial least squares correlation analysis. Hum Brain Mapp 2019; 40:5315-5329. [PMID: 31452304 PMCID: PMC6864896 DOI: 10.1002/hbm.24774] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Revised: 06/30/2019] [Accepted: 07/29/2019] [Indexed: 01/10/2023] Open
Abstract
Cortical atrophy and degraded axonal health have been shown to coincide during normal aging; however, few studies have examined these measures together. To lend insight into both the regional specificity and the relative timecourse of structural degradation of these tissue compartments across the adult lifespan, we analyzed gray matter (GM) morphometry (cortical thickness, surface area, volume) and estimates of white matter (WM) microstructure (fractional anisotropy, mean diffusivity) using traditional univariate and more robust multivariate techniques to examine age associations in 186 healthy adults aged 20–94 years old. Univariate analysis of each tissue type revealed that negative age associations were largest in frontal GM and WM tissue and weaker in temporal, cingulate, and occipital regions, representative of not only an anterior‐to‐posterior gradient, but also a medial‐to‐lateral gradient. Multivariate partial least squares correlation (PLSC) found the greatest covariance between GM and WM was driven by the relationship between WM metrics in the anterior corpus callosum and projections of the genu, anterior cingulum, and fornix; and with GM thickness in parietal and frontal regions. Surface area was far less susceptible to age effects and displayed less covariance with WM metrics, while regional volume covariance patterns largely mirrored those of cortical thickness. Results support a retrogenesis‐like model of aging, revealing a coupled relationship between frontal and parietal GM and the underlying WM, which evidence the most protracted development and the most vulnerability during healthy aging.
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Affiliation(s)
- David A Hoagey
- Center for Vital Longevity, The University of Texas at Dallas, School of Behavioral and Brain Sciences, Dallas, Texas
| | - Jenny R Rieck
- Rotman Research Institute, Baycrest Health Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Karen M Rodrigue
- Center for Vital Longevity, The University of Texas at Dallas, School of Behavioral and Brain Sciences, Dallas, Texas
| | - Kristen M Kennedy
- Center for Vital Longevity, The University of Texas at Dallas, School of Behavioral and Brain Sciences, Dallas, Texas
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15
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Age moderates the relationship between cortical thickness and cognitive performance. Neuropsychologia 2019; 132:107136. [PMID: 31288025 DOI: 10.1016/j.neuropsychologia.2019.107136] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2019] [Revised: 06/15/2019] [Accepted: 07/05/2019] [Indexed: 12/30/2022]
Abstract
Findings from cross-sectional and longitudinal magnetic resonance imaging (MRI) studies indicate that cortical thickness declines across the adult lifespan, with regional differences in rate of decline. Global and regional thickness have also been found to co-vary with cognitive performance. Here we examined the relationships between age, mean cortical thickness, and associative recognition performance across three age groups (younger, middle-aged and older adults; total n = 133). Measures of cortical thickness were obtained using a semi-automated method. Older age was associated with decreased memory performance and a reduction in mean cortical thickness. After controlling for the potentially confounding effects of head motion, mean cortical thickness was negatively associated with associative memory performance in the younger participants, but was positively correlated with performance in older participants. A similar but weaker pattern was evident in the relationships between cortical thickness and scores on four cognitive constructs derived from a neuropsychological test battery. This pattern is consistent with prior findings indicating that the direction of the association between cortical thickness and cognitive performance reverses between early and later adulthood. In addition, head motion was independently and negatively correlated with associative recognition performance in younger and middle-aged, but not older, participants, suggesting that variance in head motion is determined by multiple factors that vary in their relative influences with age.
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16
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Morris BJ, Willcox BJ, Donlon TA. Genetic and epigenetic regulation of human aging and longevity. Biochim Biophys Acta Mol Basis Dis 2019; 1865:1718-1744. [PMID: 31109447 PMCID: PMC7295568 DOI: 10.1016/j.bbadis.2018.08.039] [Citation(s) in RCA: 83] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2018] [Revised: 08/02/2018] [Accepted: 08/28/2018] [Indexed: 02/06/2023]
Abstract
Here we summarize the latest data on genetic and epigenetic contributions to human aging and longevity. Whereas environmental and lifestyle factors are important at younger ages, the contribution of genetics appears more important in reaching extreme old age. Genome-wide studies have implicated ~57 gene loci in lifespan. Epigenomic changes during aging profoundly affect cellular function and stress resistance. Dysregulation of transcriptional and chromatin networks is likely a crucial component of aging. Large-scale bioinformatic analyses have revealed involvement of numerous interaction networks. As the young well-differentiated cell replicates into eventual senescence there is drift in the highly regulated chromatin marks towards an entropic middle-ground between repressed and active, such that genes that were previously inactive "leak". There is a breakdown in chromatin connectivity such that topologically associated domains and their insulators weaken, and well-defined blocks of constitutive heterochromatin give way to generalized, senescence-associated heterochromatin, foci. Together, these phenomena contribute to aging.
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Affiliation(s)
- Brian J Morris
- Basic & Clinical Genomics Laboratory, School of Medical Sciences and Bosch Institute, University of Sydney, New South Wales 2006, Australia; Honolulu Heart Program (HHP)/Honolulu-Asia Aging Study (HAAS), Department of Research, Kuakini Medical Center, Honolulu, HI 96817, United States; Department of Geriatric Medicine, John A. Burns School of Medicine, University of Hawaii, Kuakini Medical Center Campus, Honolulu, HI 96813, United States.
| | - Bradley J Willcox
- Honolulu Heart Program (HHP)/Honolulu-Asia Aging Study (HAAS), Department of Research, Kuakini Medical Center, Honolulu, HI 96817, United States; Department of Geriatric Medicine, John A. Burns School of Medicine, University of Hawaii, Kuakini Medical Center Campus, Honolulu, HI 96813, United States.
| | - Timothy A Donlon
- Honolulu Heart Program (HHP)/Honolulu-Asia Aging Study (HAAS), Department of Research, Kuakini Medical Center, Honolulu, HI 96817, United States; Departments of Cell & Molecular Biology and Pathology, John A. Burns School of Medicine, University of Hawaii, Honolulu, HI 96813, United States.
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17
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Armstrong NM, An Y, Beason-Held L, Doshi J, Erus G, Ferrucci L, Davatzikos C, Resnick SM. Sex differences in brain aging and predictors of neurodegeneration in cognitively healthy older adults. Neurobiol Aging 2019; 81:146-156. [PMID: 31280118 DOI: 10.1016/j.neurobiolaging.2019.05.020] [Citation(s) in RCA: 69] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2018] [Revised: 05/04/2019] [Accepted: 05/30/2019] [Indexed: 01/15/2023]
Abstract
We evaluated sex differences in MRI-based volume loss and differences in predictors of this neurodegeneration in cognitively healthy older adults. Mixed-effects regression was used to compare regional brain volume trajectories of 295 male and 328 female cognitively healthy Baltimore Longitudinal Study of Aging participants, aged 55-92 years, with up to 20 years of follow-up and to assess sex differences in the associations of age, hypertension, obesity, APOE e4 carrier status, and high-density lipoprotein cholesterol with regional brain volume trajectories. For both sexes, older age was associated with steeper volumetric declines in many brain regions, with sex differences in volume loss observed in frontal, temporal, and parietal regions. In males, hypertension and higher high-density lipoprotein cholesterol were protective against volume loss in the hippocampus, entorhinal cortex, and parahippocampal gyrus. In females, hypertension was associated with steeper volumetric decline in gray matter, and obesity was protective against volume loss in temporal gray matter. Predictors of volume change may affect annual rates of volume change differently between men and women.
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Affiliation(s)
- Nicole M Armstrong
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Yang An
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Lori Beason-Held
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Jimit Doshi
- Department of Radiology, Section of Biomedical Image Analysis, University of Pennsylvania, Philadelphia, PA, USA
| | - Guray Erus
- Department of Radiology, Section of Biomedical Image Analysis, University of Pennsylvania, Philadelphia, PA, USA
| | - Luigi Ferrucci
- Translational Gerontology Branch, Longitudinal Studies Section, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Christos Davatzikos
- Department of Radiology, Section of Biomedical Image Analysis, University of Pennsylvania, Philadelphia, PA, USA
| | - Susan M Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA.
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18
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Abstract
Hypertension has emerged as a leading cause of age-related cognitive impairment. Long known to be associated with dementia caused by vascular factors, hypertension has more recently been linked also to Alzheimer disease-the major cause of dementia in older people. Thus, although midlife hypertension is a risk factor for late-life dementia, hypertension may also promote the neurodegenerative pathology underlying Alzheimer disease. The mechanistic bases of these harmful effects remain to be established. Hypertension is well known to alter in the structure and function of cerebral blood vessels, but how these cerebrovascular effects lead to cognitive impairment and promote Alzheimer disease pathology is not well understood. Furthermore, critical questions also concern whether treatment of hypertension prevents cognitive impairment, the blood pressure threshold for treatment, and the antihypertensive agents to be used. Recent advances in neurovascular biology, epidemiology, brain imaging, and biomarker development have started to provide new insights into these critical issues. In this review, we will examine the progress made to date, and, after a critical evaluation of the evidence, we will highlight questions still outstanding and seek to provide a path forward for future studies.
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Affiliation(s)
- Costantino Iadecola
- From the Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York (C.I.)
| | - Rebecca F Gottesman
- Departments of Neurology (R.F.G.), Johns Hopkins University, Baltimore, MD
- Epidemiology (R.F.G.), Johns Hopkins University, Baltimore, MD
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19
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Ennis GE, Quintin EM, Saelzler U, Kennedy KM, Hertzog C, Moffat SD. Cortisol relates to regional limbic system structure in older but not younger adults. Psychoneuroendocrinology 2019; 101:111-120. [PMID: 30453123 PMCID: PMC8074622 DOI: 10.1016/j.psyneuen.2018.09.014] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2017] [Revised: 09/11/2018] [Accepted: 09/12/2018] [Indexed: 12/22/2022]
Abstract
We investigated if the relationship between age and regional limbic system brain structure would be moderated by diurnal cortisol output and diurnal cortisol slope. Participants aged 23-83 years collected seven salivary cortisol samples each day for 10 consecutive days and underwent magnetic resonance imaging. Age, sex, cortisol, and an age x cortisol interaction were tested as predictors of hippocampal and amygdalar volume and caudal and rostral anterior cingulate cortex (ACC) thickness. We found significant interactions between age and cortisol on left and right amygdalar volumes and right caudal ACC thickness. Older adults with higher cortisol output had smaller left and right amygdalar volumes than older adults with lower cortisol output and younger adults with higher cortisol output. Older and younger adults with lower cortisol output had similar amygdalar volumes. Older adults with a steeper decline in diurnal cortisol had a thicker right caudal ACC than younger adults with a similarly shaped cortisol slope. Hippocampal volume was not related to either cortisol slope or output, nor was pallidum volume which was assessed as an extra-limbic control region. Results suggest that subtle differences in cortisol output are related to differences in limbic system structure in older but not younger adults.
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Affiliation(s)
- Gilda E Ennis
- School of Psychology, Georgia Institute of Technology, 654 Cherry Street, Atlanta, GA 30332-0170, United states.
| | - Eve-Marie Quintin
- School of Psychology, Georgia Institute of Technology, 654 Cherry Street, Atlanta, GA 30332-0170, United states.
| | - Ursula Saelzler
- School of Psychology, Georgia Institute of Technology, 654 Cherry Street, Atlanta, GA 30332-0170, United states.
| | - Kristen M Kennedy
- Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, 1600 Viceroy Drive, Suite 800, Dallas, TX, 75235, United states.
| | - Christopher Hertzog
- School of Psychology, Georgia Institute of Technology, 654 Cherry Street, Atlanta, GA 30332-0170, United states.
| | - Scott D Moffat
- School of Psychology, Georgia Institute of Technology, 654 Cherry Street, Atlanta, GA 30332-0170, United states.
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20
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Squarzoni P, Duran FLS, Busatto GF, Alves TCTDF. Reduced Gray Matter Volume of the Thalamus and Hippocampal Region in Elderly Healthy Adults with no Impact of APOE ɛ4: A Longitudinal Voxel-Based Morphometry Study. J Alzheimers Dis 2019; 62:757-771. [PMID: 29480170 DOI: 10.3233/jad-161036] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
BACKGROUND Many cross-sectional voxel-based morphometry (VBM) investigations have shown significant inverse correlations between chronological age and gray matter (GM) volume in several brain regions in healthy humans. However, few VBM studies have documented GM decrements in the healthy elderly with repeated MRI measurements obtained in the same subjects. Also, the extent to which the APOE ɛ4 allele influences longitudinal findings of GM reduction in the healthy elderly is unclear. OBJECTIVE Verify whether regional GM changes are associated with significant decrements in cognitive performance taking in account the presence of the APOE ɛ4 allele. METHODS Using structural MRI datasets acquired in 55 cognitively intact elderly subjects at two time-points separated by approximately three years, we searched for voxels showing significant GM reductions taking into account differences in APOE genotype. RESULTS We found global GM reductions as well as regional GM decrements in the right thalamus and left parahippocampal gyrus (p < 0.05, family-wise error corrected for multiple comparisons over the whole brain). These findings were not affected by APOE ɛ4. CONCLUSIONS Irrespective of APOE ɛ4, longitudinal VBM analyses show that the hippocampal region and thalamus are critical sites where GM shrinkage is greater than the degree of global volume reduction in healthy elderly subjects.
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Affiliation(s)
- Paula Squarzoni
- Department of Psychiatry, Laboratory of Psychiatric Neuroimaging (LIM 21), Faculty of Medicine, University of São Paulo, São Paulo, Brazil.,Núcleo de Apoio à Pesquisa em Neurociência Aplicada (NAPNA), University of São Paulo, São Paulo, Brazil
| | - Fabio Luis Souza Duran
- Department of Psychiatry, Laboratory of Psychiatric Neuroimaging (LIM 21), Faculty of Medicine, University of São Paulo, São Paulo, Brazil.,Núcleo de Apoio à Pesquisa em Neurociência Aplicada (NAPNA), University of São Paulo, São Paulo, Brazil
| | - Geraldo F Busatto
- Department of Psychiatry, Laboratory of Psychiatric Neuroimaging (LIM 21), Faculty of Medicine, University of São Paulo, São Paulo, Brazil.,Núcleo de Apoio à Pesquisa em Neurociência Aplicada (NAPNA), University of São Paulo, São Paulo, Brazil
| | - Tania Correa Toledo de Ferraz Alves
- Department of Psychiatry, Laboratory of Psychiatric Neuroimaging (LIM 21), Faculty of Medicine, University of São Paulo, São Paulo, Brazil.,Núcleo de Apoio à Pesquisa em Neurociência Aplicada (NAPNA), University of São Paulo, São Paulo, Brazil
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21
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Miranda GG, Rodrigue KM, Kennedy KM. Frontoparietal cortical thickness mediates the effect of COMT Val 158Met polymorphism on age-associated executive function. Neurobiol Aging 2019; 73:104-114. [PMID: 30342271 PMCID: PMC6251730 DOI: 10.1016/j.neurobiolaging.2018.08.027] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2018] [Revised: 08/08/2018] [Accepted: 08/17/2018] [Indexed: 12/31/2022]
Abstract
Proper dopamine (DA) signaling is likely necessary for maintaining optimal cognitive performance as we age, particularly in prefrontal-parietal networks and in fronto-striatal networks. Thus, reduced DA availability is a salient risk factor for accelerated cognitive aging. A common polymorphism that affects DA D1 receptor dopamine availability, COMT Val158Met (rs4680), influences enzymatic breakdown of DA, with COMT Val carriers having a 3- to 4-fold reduction in synaptic DA compared to COMT Met carriers. Furthermore, dopamine receptors and postsynaptic availability are drastically reduced with aging, as is executive function performance that ostensibly relies on these pathways. Here, we investigated in 176 individuals aged 20-94 years whether: (1) COMT Val carriers differ from their Met counterparts in thickness of regional cortices receiving D1 receptor pathways: prefrontal, parietal, cingulate cortices; (2) this gene-brain association differs across the adult lifespan; and (3) COMT-related regional thinning evidences cognitive consequences. We found that COMT Val carriers evidenced thinner cortex in prefrontal, parietal, and posterior cingulate cortices than COMT Met carriers and this effect was not age-dependent. Further, we demonstrate that thickness of these regions significantly mediates the effect of COMT genotype on an executive function composite measure. These results suggest that poorer executive function performance is due partly to thinner association cortex in dopaminergic-rich regions, and particularly so in individuals who are genetically predisposed to lower postsynaptic dopamine availability, regardless of age.
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Affiliation(s)
- Giuseppe G Miranda
- Center for Vital Longevity, School of Behavioral and Brain Sciences, The University of Texas at Dallas, Dallas, TX, USA
| | - Karen M Rodrigue
- Center for Vital Longevity, School of Behavioral and Brain Sciences, The University of Texas at Dallas, Dallas, TX, USA
| | - Kristen M Kennedy
- Center for Vital Longevity, School of Behavioral and Brain Sciences, The University of Texas at Dallas, Dallas, TX, USA.
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