1
|
Liu P, Wang J, Mei P, Li J, Xu B, Ren X, Chen X, Wu D, Zhu F, Yang X, He M, Liu J, Huang H. The interaction effect of metals exposure and dietary habit on cognitive function in Chinese older adult cohort. J Nutr Health Aging 2024; 28:100284. [PMID: 38833765 DOI: 10.1016/j.jnha.2024.100284] [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: 11/10/2023] [Revised: 03/12/2024] [Accepted: 05/26/2024] [Indexed: 06/06/2024]
Abstract
BACKGROUND As the important factors in cognitive function, dietary habits and metal exposures are interactive with each other. However, fewer studies have investigated the interaction effect of them on cognitive dysfunction in older adults. METHODS 2,445 registered citizens aged 60-85 years from 51 community health centers in Luohu District, Shenzhen, were recruited in this study based on the Chinese older adult cohort. All subjects underwent physical examination and Mini-cognitive assessment scale. A semi quantitative food frequency questionnaire was used to obtain their food intake frequency, and 21 metal concentrations in their urine were measured. RESULTS Elastic-net regression model, a machine learning technique, identified six variables that were significantly associated with cognitive dysfunction in older adults. These variables included education level, gender, urinary concentration of arsenic (As) and cadmium (Cd), and the frequency of monthly intake of egg and bean products. After adjusting for multiple factors, As and Cd concentrations were positively associated with increased risk of mild cognitive impairment (MCI) in the older people, with OR values of 1.19 (95% CI: 1.05-1.42) and 1.32 (95% CI: 1.01-1.74), respectively. In addition, older adults with high frequency of egg intake (≥30 times/month) and bean products intake (≥8 times/month) had a reduced risk of MCI than those with low protein egg intake (<30 times/month) and low bean products intake (<8 times/month), respectively. Furthermore, additive interaction were observed between the As exposure and egg products intake, as well as bean products. Cd exposure also showed additive interactions with egg and bean products intake. CONCLUSIONS The consumption of eggs and bean products, as well as the levels of exposure to the heavy metals Cd and As, have been shown to have a substantial influence on cognitive impairment in the elderly population.
Collapse
Affiliation(s)
- Peiyi Liu
- Shenzhen Key Laboratory of Modern Toxicology, Shenzhen Medical Key Discipline of Health Toxicology, Shenzhen Center for Disease Control and Prevention, Shenzhen, 518055, China
| | - Jiahui Wang
- Shenzhen Key Laboratory of Modern Toxicology, Shenzhen Medical Key Discipline of Health Toxicology, Shenzhen Center for Disease Control and Prevention, Shenzhen, 518055, China
| | - Pengcheng Mei
- Shenzhen Key Laboratory of Modern Toxicology, Shenzhen Medical Key Discipline of Health Toxicology, Shenzhen Center for Disease Control and Prevention, Shenzhen, 518055, China
| | - Junyu Li
- Food Inspection and Quarantine Technology Center of Shenzhen Customs, Shenzhen, 518033, China
| | - Benhong Xu
- Shenzhen Key Laboratory of Modern Toxicology, Shenzhen Medical Key Discipline of Health Toxicology, Shenzhen Center for Disease Control and Prevention, Shenzhen, 518055, China
| | - Xiaohu Ren
- Shenzhen Key Laboratory of Modern Toxicology, Shenzhen Medical Key Discipline of Health Toxicology, Shenzhen Center for Disease Control and Prevention, Shenzhen, 518055, China
| | - Xiao Chen
- Shenzhen Key Laboratory of Modern Toxicology, Shenzhen Medical Key Discipline of Health Toxicology, Shenzhen Center for Disease Control and Prevention, Shenzhen, 518055, China
| | - Desheng Wu
- Shenzhen Key Laboratory of Modern Toxicology, Shenzhen Medical Key Discipline of Health Toxicology, Shenzhen Center for Disease Control and Prevention, Shenzhen, 518055, China
| | - Feiqi Zhu
- Cognitive Impairment Ward of Neurology Department, the Third Affiliated Hospital of Shenzhen University Medical College, Shenzhen, 518020, China
| | - Xifei Yang
- Shenzhen Key Laboratory of Modern Toxicology, Shenzhen Medical Key Discipline of Health Toxicology, Shenzhen Center for Disease Control and Prevention, Shenzhen, 518055, China
| | - Meian He
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan 430030, Hubei, China
| | - Jianjun Liu
- Shenzhen Key Laboratory of Modern Toxicology, Shenzhen Medical Key Discipline of Health Toxicology, Shenzhen Center for Disease Control and Prevention, Shenzhen, 518055, China.
| | - Haiyan Huang
- Shenzhen Key Laboratory of Modern Toxicology, Shenzhen Medical Key Discipline of Health Toxicology, Shenzhen Center for Disease Control and Prevention, Shenzhen, 518055, China.
| |
Collapse
|
2
|
Han L, Xu Q, Meng P, Xu R, Nan J. Brain identification of IBS patients based on GBDT and multiple imaging techniques. Phys Eng Sci Med 2024; 47:651-662. [PMID: 38416373 DOI: 10.1007/s13246-024-01394-0] [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: 06/28/2023] [Accepted: 01/16/2024] [Indexed: 02/29/2024]
Abstract
The brain biomarker of irritable bowel syndrome (IBS) patients is still lacking. The study aims to explore a new technology studying the brain alterations of IBS patients based on multi-source brain data. In the study, a decision-level fusion method based on gradient boosting decision tree (GBDT) was proposed. Next, 100 healthy subjects were used to validate the effectiveness of the method. Finally, the identification of brain alterations and the pain evaluation in IBS patients were carried out by the fusion method based on the resting-state fMRI and DWI for 46 patients and 46 controls selected randomly from 100 healthy subjects. The results showed that the method can achieve good classification between IBS patients and controls (accuracy = 95%) and pain evaluation of IBS patients (mean absolute error = 0.1977). Moreover, both the gain-based and the permutation-based evaluation instead of statistical analysis showed that left cingulum bundle contributed most significantly to the classification, and right precuneus contributed most significantly to the evaluation of abdominal pain intensity in the IBS patients. The differences seem to suggest a probable but unexplored separation about the central regions between the identification and progression of IBS. This finding may provide one new thought and technology for brain alteration related to IBS.
Collapse
Affiliation(s)
- Li Han
- School of Computer and Communication Engineering, Zhengzhou University of Light Industry, 136 Science Avenue, Zhengzhou, 450000, Henan, China
| | - Qian Xu
- School of Computer and Communication Engineering, Zhengzhou University of Light Industry, 136 Science Avenue, Zhengzhou, 450000, Henan, China
| | - Panting Meng
- School of Computer and Communication Engineering, Zhengzhou University of Light Industry, 136 Science Avenue, Zhengzhou, 450000, Henan, China
| | - Ruyun Xu
- School of Computer and Communication Engineering, Zhengzhou University of Light Industry, 136 Science Avenue, Zhengzhou, 450000, Henan, China
| | - Jiaofen Nan
- School of Computer and Communication Engineering, Zhengzhou University of Light Industry, 136 Science Avenue, Zhengzhou, 450000, Henan, China.
| |
Collapse
|
3
|
Murasko J. Height and cognitive assessments in a cohort of US schoolchildren, kindergarten through fifth grade. BIODEMOGRAPHY AND SOCIAL BIOLOGY 2024:1-13. [PMID: 38813839 DOI: 10.1080/19485565.2024.2358906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2024]
Abstract
An oft-repeated finding in child development research is that height and cognitive ability are positively related. Much of this work is limited in its ability to track height and cognitive development over time, with key constraints being the availability of longitudinal data and measures of ability that are comparable over time. This study evaluates the associations between height and assessments of reading, math, and science in a representative sample of US schoolchildren followed from kindergarten through fifth grade. Associations between height and assessment scores at each grade level, and height-growth and changes in scores over grade levels, are examined. The results suggest modest associations between concurrent height and assessment scores at each grade level that are robust to socioeconomic and school controls. There is limited association between height-growth and assessment outcomes, which is shown only for females. There is also little indication that height or height-growth is associated with improvements in scores. The findings suggest a modest association between height and cognitive ability in contemporary US schoolchildren, being attributed mostly to growth before kindergarten. The findings are consistent with the view that social and biological forces in early-life facilitate both physical and cognitive development.
Collapse
Affiliation(s)
- Jason Murasko
- Economics, University of Houston - Clear Lake, Houston, Texas, USA
| |
Collapse
|
4
|
Labounek R, Bondy MT, Paulson AL, Bédard S, Abramovic M, Alonso-Ortiz E, Atcheson NT, Barlow LR, Barry RL, Barth M, Battiston M, Büchel C, Budde MD, Callot V, Combes A, De Leener B, Descoteaux M, de Sousa PL, Dostál M, Doyon J, Dvorak AV, Eippert F, Epperson KR, Epperson KS, Freund P, Finsterbusch J, Foias A, Fratini M, Fukunaga I, Gandini Wheeler-Kingshott CAM, Germani G, Gilbert G, Giove F, Grussu F, Hagiwara A, Henry PG, Horák T, Hori M, Joers JM, Kamiya K, Karbasforoushan H, Keřkovský M, Khatibi A, Kim JW, Kinany N, Kitzler H, Kolind S, Kong Y, Kudlička P, Kuntke P, Kurniawan ND, Kusmia S, Laganà MM, Laule C, Law CSW, Leutritz T, Liu Y, Llufriu S, Mackey S, Martin AR, Martinez-Heras E, Mattera L, O’Grady KP, Papinutto N, Papp D, Pareto D, Parrish TB, Pichiecchio A, Prados F, Rovira À, Ruitenberg MJ, Samson RS, Savini G, Seif M, Seifert AC, Smith AK, Smith SA, Smith ZA, Solana E, Suzuki Y, Tackley GW, Tinnermann A, Valošek J, Van De Ville D, Yiannakas MC, Weber KA, Weiskopf N, Wise RG, Wyss PO, Xu J, Cohen-Adad J, Lenglet C, Nestrašil I. Body size interacts with the structure of the central nervous system: A multi-center in vivo neuroimaging study. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.29.591421. [PMID: 38746371 PMCID: PMC11092490 DOI: 10.1101/2024.04.29.591421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Clinical research emphasizes the implementation of rigorous and reproducible study designs that rely on between-group matching or controlling for sources of biological variation such as subject's sex and age. However, corrections for body size (i.e. height and weight) are mostly lacking in clinical neuroimaging designs. This study investigates the importance of body size parameters in their relationship with spinal cord (SC) and brain magnetic resonance imaging (MRI) metrics. Data were derived from a cosmopolitan population of 267 healthy human adults (age 30.1±6.6 years old, 125 females). We show that body height correlated strongly or moderately with brain gray matter (GM) volume, cortical GM volume, total cerebellar volume, brainstem volume, and cross-sectional area (CSA) of cervical SC white matter (CSA-WM; 0.44≤r≤0.62). In comparison, age correlated weakly with cortical GM volume, precentral GM volume, and cortical thickness (-0.21≥r≥-0.27). Body weight correlated weakly with magnetization transfer ratio in the SC WM, dorsal columns, and lateral corticospinal tracts (-0.20≥r≥-0.23). Body weight further correlated weakly with the mean diffusivity derived from diffusion tensor imaging (DTI) in SC WM (r=-0.20) and dorsal columns (-0.21), but only in males. CSA-WM correlated strongly or moderately with brain volumes (0.39≤r≤0.64), and weakly with precentral gyrus thickness and DTI-based fractional anisotropy in SC dorsal columns and SC lateral corticospinal tracts (-0.22≥r≥-0.25). Linear mixture of sex and age explained 26±10% of data variance in brain volumetry and SC CSA. The amount of explained variance increased at 33±11% when body height was added into the mixture model. Age itself explained only 2±2% of such variance. In conclusion, body size is a significant biological variable. Along with sex and age, body size should therefore be included as a mandatory variable in the design of clinical neuroimaging studies examining SC and brain structure.
Collapse
Affiliation(s)
- René Labounek
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Monica T. Bondy
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Amy L. Paulson
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Sandrine Bédard
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Mihael Abramovic
- Department of Radiology, Swiss Paraplegic Centre, Nottwil, Switzerland
| | - Eva Alonso-Ortiz
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Centre de recherche du CHU Sainte-Justine, Université de Montréal, Montreal, QC, Canada
| | - Nicole T Atcheson
- Centre for Advanced Imaging, Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, St Lucia, Australia
| | - Laura R. Barlow
- Department of Radiology, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Robert L. Barry
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
- Harvard-Massachusetts Institute of Technology Health Sciences & Technology, Cambridge, Massachusetts, USA
| | - Markus Barth
- Centre for Advanced Imaging, Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, St Lucia, Australia
- School of Electrical Engineering and Computer Science, The University of Queensland, St Lucia, Australia
| | - Marco Battiston
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK
| | - Christian Büchel
- Department for Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Matthew D. Budde
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, USA
- Clement J. Zablocki Veteran’s Affairs Medical Center, Milwaukee, WI, USA
| | - Virginie Callot
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France
- APHM, Hopital Universitaire Timone, CEMEREM, Marseille, France
| | - Anna Combes
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK
| | - Benjamin De Leener
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Centre de recherche du CHU Sainte-Justine, Université de Montréal, Montreal, QC, Canada
- Department of Computer Engineering and Software Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science department, Université de Sherbrooke, Sherbrooke, QC, Canada
| | | | - Marek Dostál
- Department of Radiology and Nuclear Medicine, University Hospital Brno and Masaryk University, Czech Republic
- Department of Biophysics, Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Julien Doyon
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Adam V. Dvorak
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
| | - Falk Eippert
- Max Planck Research Group Pain Perception, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | | | | | - Patrick Freund
- Spinal Cord Injury Center Balgrist, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Wellcome Trust Centre for Neuroimaging, Queen Square Institute of Neurology, University College London, London, UK
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103 Leipzig, Germany
| | - Jürgen Finsterbusch
- Department for Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Alexandru Foias
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Michela Fratini
- Institute of Nanotechnology, CNR, Rome, Italy
- IRCCS Santa Lucia Foundation, Neuroimaging Laboratory, Rome, Italy
| | - Issei Fukunaga
- Department of Radiology, Juntendo University School of Medicine, 1-2-1, Hongo, Bunkyo, Tokyo 113-8421, Japan
| | - Claudia A. M. Gandini Wheeler-Kingshott
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
| | - GianCarlo Germani
- Advanced Imaging and Artificial Intelligence Center, Neuroradiology Department, IRCCS Mondino Foundation, Pavia, Italy
| | | | - Federico Giove
- IRCCS Santa Lucia Foundation, Neuroimaging Laboratory, Rome, Italy
- CREF - Museo storico della fisica e Centro studi e ricerche Enrico Fermi, Rome, Italy
| | - Francesco Grussu
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK
- Vall d’Hebron Institute of Oncology (VHIO), Vall d’Hebron Barcelona Hospital Campus, Barcelona, Spain
| | - Akifumi Hagiwara
- Department of Radiology, Juntendo University School of Medicine, 1-2-1, Hongo, Bunkyo, Tokyo 113-8421, Japan
| | - Pierre-Gilles Henry
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Tomáš Horák
- Faculty of Medicine, Masaryk University, Brno, Czech Republic
- Department of Neurology, University Hospital Brno, Brno, Czech Republic
- Multimodal and Functional Imaging Laboratory, Central European Institute of Technology, Brno, Czech Republic
| | - Masaaki Hori
- Department of Radiology, Juntendo University School of Medicine, 1-2-1, Hongo, Bunkyo, Tokyo 113-8421, Japan
- Department of Radiology, Toho University Omori Medical Center, Tokyo, Japan
| | - James M. Joers
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Kouhei Kamiya
- Department of Radiology, Toho University Omori Medical Center, Tokyo, Japan
| | - Haleh Karbasforoushan
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Miloš Keřkovský
- Department of Radiology and Nuclear Medicine, University Hospital Brno and Masaryk University, Czech Republic
| | - Ali Khatibi
- Centre of Precision Rehabilitation for Spinal Pain (CPR Spine), University of Birmingham, Birmingham, UK
- Centre for Human Brain Health, University of Birmingham, Birmingham, UK
- Institute for Mental Health, University of Birmingham, Birmingham, UK
| | - Joo-won Kim
- Biomedical Engineering and Imaging Institute, Department of Radiology, Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, USA
- Department of Radiology, Baylor College of Medicine, Houston, Texas, USA
- Department of Psychiatry, Baylor College of Medicine, Houston, Texas, USA
| | - Nawal Kinany
- Neuro-X Institute, Ecole polytechnique fédérale de Lausanne, Geneva, Switzerland
- Department of Radiology and Medical Informatics, Faculty of Medicine, University of Geneva, Switzerland
| | - Hagen Kitzler
- Institute of Diagnostic and Interventional Neuroradiology, Faculty of Medicine and Carl Gustav Carus University Hospital, Technische Universität Dresden, Germany
| | - Shannon Kolind
- Department of Radiology, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
- Division of Neurology, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Yazhuo Kong
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Science, Beijing, 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Petr Kudlička
- Multimodal and Functional Imaging Laboratory, Central European Institute of Technology, Brno, Czech Republic
- First Department of Neurology, St. Anne’s University Hospital and Medical Faculty of Masaryk University, Brno, Czech Republic
| | - Paul Kuntke
- Institute of Diagnostic and Interventional Neuroradiology, Faculty of Medicine and Carl Gustav Carus University Hospital, Technische Universität Dresden, Germany
| | - Nyoman D. Kurniawan
- Centre for Advanced Imaging, Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, St Lucia, Australia
| | | | | | - Cornelia Laule
- Department of Radiology, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
- Department of Pathology & Laboratory Medicine, University of British Columbia, Vancouver, Canada
- International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, Canada
| | | | - Tobias Leutritz
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103 Leipzig, Germany
| | - Yaou Liu
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, China
| | - Sara Llufriu
- Neuroimmunology and Multiple Sclerosis Unit, Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM), Hospital Clinic Barcelona, Fundació de Recerca Clínic Barcelona-IDIBAPS and Universitat de Barcelona. Barcelona, Spain
| | - Sean Mackey
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Allan R. Martin
- Department of Neurological Surgery, University of California, Davis, CA, USA
| | - Eloy Martinez-Heras
- Neuroimmunology and Multiple Sclerosis Unit, Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM), Hospital Clinic Barcelona, Fundació de Recerca Clínic Barcelona-IDIBAPS and Universitat de Barcelona. Barcelona, Spain
- Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d’Hebron, Barcelona, Spain
| | - Loan Mattera
- Fondation Campus Biotech Geneva, Genève, Switzerland
| | - Kristin P. O’Grady
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Nico Papinutto
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Daniel Papp
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Wellcome Centre For Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Deborah Pareto
- Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d’Hebron, Barcelona, Spain
| | - Todd B. Parrish
- Department of Radiology, Northwestern University, Chicago, IL 60611, USA
| | - Anna Pichiecchio
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
- Advanced Imaging and Artificial Intelligence Center, Neuroradiology Department, IRCCS Mondino Foundation, Pavia, Italy
| | - Ferran Prados
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK
- e-Health Center, Universitat Oberta de Catalunya, Barcelona, Spain
- Centre for Medical Image Computing, University College London, London, UK
| | - Àlex Rovira
- Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d’Hebron, Barcelona, Spain
| | - Marc J. Ruitenberg
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, St Lucia, Australia
| | - Rebecca S. Samson
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK
| | - Giovanni Savini
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, 20072, Pieve Emanuele (MI), Italy
- Neuroradiology Unit, IRCCS Humanitas Research Hospital, Via Alessandro Manzoni 56, 20089, Rozzano (MI), Italy
| | - Maryam Seif
- Spinal Cord Injury Center Balgrist, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103 Leipzig, Germany
| | - Alan C. Seifert
- Biomedical Engineering and Imaging Institute, Department of Radiology, Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Alex K. Smith
- Wellcome Centre For Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Seth A. Smith
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN USA
| | - Zachary A. Smith
- Department of Neurosurgery, University of Oklahoma, Oklahoma City, OK, USA
| | - Elisabeth Solana
- Neuroimmunology and Multiple Sclerosis Unit, Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM), Hospital Clinic Barcelona, Fundació de Recerca Clínic Barcelona-IDIBAPS and Universitat de Barcelona. Barcelona, Spain
| | - Yuichi Suzuki
- The University of Tokyo Hospital, Radiology Center, Tokyo, Japan
| | - George W Tackley
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, Wales, UK
| | - Alexandra Tinnermann
- Department for Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jan Valošek
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Mila - Quebec AI Institute, Montreal, QC, Canada
- Department of Neurosurgery, Faculty of Medicine and Dentistry, Palacký University Olomouc, Olomouc, Czech Republic
- Department of Neurology, Faculty of Medicine and Dentistry, Palacký University Olomouc, Olomouc, Czech Republic
| | - Dimitri Van De Ville
- Neuro-X Institute, Ecole polytechnique fédérale de Lausanne, Geneva, Switzerland
- Department of Radiology and Medical Informatics, Faculty of Medicine, University of Geneva, Switzerland
| | - Marios C. Yiannakas
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK
| | - Kenneth A. Weber
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Nikolaus Weiskopf
- Wellcome Trust Centre for Neuroimaging, Queen Square Institute of Neurology, University College London, London, UK
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103 Leipzig, Germany
- Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Linnéstraße 5, 04103 Leipzig, Germany
| | - Richard G. Wise
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, Wales, UK
- Department of Neurosciences, Imaging, and Clinical Sciences, ‘G. D’Annunzio’ University of Chieti-Pescara, Chieti, Italy
- Institute for Advanced Biomedical Technologies, ‘G. D’Annunzio’ University of Chieti-Pescara, Chieti, Italy
| | - Patrik O. Wyss
- Department of Radiology, Swiss Paraplegic Centre, Nottwil, Switzerland
| | - Junqian Xu
- Biomedical Engineering and Imaging Institute, Department of Radiology, Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, USA
- Department of Radiology, Baylor College of Medicine, Houston, Texas, USA
- Department of Psychiatry, Baylor College of Medicine, Houston, Texas, USA
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Centre de recherche du CHU Sainte-Justine, Université de Montréal, Montreal, QC, Canada
- Mila - Quebec AI Institute, Montreal, QC, Canada
- Functional Neuroimaging Unit, CRIUGM, University of Montreal, Montreal, Canada
| | - Christophe Lenglet
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Igor Nestrašil
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| |
Collapse
|
5
|
Stauffer EM, Bethlehem RAI, Dorfschmidt L, Won H, Warrier V, Bullmore ET. The genetic relationships between brain structure and schizophrenia. Nat Commun 2023; 14:7820. [PMID: 38016951 PMCID: PMC10684873 DOI: 10.1038/s41467-023-43567-7] [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: 04/06/2023] [Accepted: 11/14/2023] [Indexed: 11/30/2023] Open
Abstract
Genetic risks for schizophrenia are theoretically mediated by genetic effects on brain structure but it has been unclear which genes are associated with both schizophrenia and cortical phenotypes. We accessed genome-wide association studies (GWAS) of schizophrenia (N = 69,369 cases; 236,642 controls), and of three magnetic resonance imaging (MRI) metrics (surface area, cortical thickness, neurite density index) measured at 180 cortical areas (N = 36,843, UK Biobank). Using Hi-C-coupled MAGMA, 61 genes were significantly associated with both schizophrenia and one or more MRI metrics. Whole genome analysis with partial least squares demonstrated significant genetic covariation between schizophrenia and area or thickness of most cortical regions. Genetic similarity between cortical areas was strongly coupled to their phenotypic covariance, and genetic covariation between schizophrenia and brain phenotypes was strongest in the hubs of structural covariance networks. Pleiotropically associated genes were enriched for neurodevelopmental processes and positionally concentrated in chromosomes 3p21, 17q21 and 11p11. Mendelian randomization analysis indicated that genetically determined variation in a posterior cingulate cortical area could be causal for schizophrenia. Parallel analyses of GWAS on bipolar disorder, Alzheimer's disease and height showed that pleiotropic association with MRI metrics was stronger for schizophrenia compared to other disorders.
Collapse
Affiliation(s)
| | - Richard A I Bethlehem
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Lena Dorfschmidt
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Hyejung Won
- Department of Genetics and the Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Varun Warrier
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Edward T Bullmore
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire & Peterborough NHS Foundation Trust, Cambridge, UK
| |
Collapse
|
6
|
Bann D, Wright L, Davies NM, Moulton V. Weakening of the cognition and height association from 1957 to 2018: Findings from four British birth cohort studies. eLife 2023; 12:e81099. [PMID: 37022953 PMCID: PMC10079289 DOI: 10.7554/elife.81099] [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: 06/15/2022] [Accepted: 03/19/2023] [Indexed: 04/07/2023] Open
Abstract
Background Taller individuals have been repeatedly found to have higher scores on cognitive assessments. Recent studies have suggested that this association can be explained by genetic factors, yet this does not preclude the influence of environmental or social factors that may change over time. We thus tested whether the association changed across time using data from four British birth cohorts (born in 1946, 1958, 1970, and 2001). Methods In each cohort height was measured and cognition via verbal reasoning, vocabulary/comprehension, and mathematical tests; at ages 10/11 and 14/17 years (N=41,418). We examined associations between height and cognition at each age, separately in each cohort, and for each cognitive test administered. Linear and quantile regression models were used. Results Taller participants had higher mean cognitive assessment scores in childhood and adolescence, yet the associations were weaker in later (1970 and 2001) cohorts. For example, the mean difference in height comparing the highest with lowest verbal cognition scores at 10/11 years was 0.57 SD (95% CI = 0.44-0.70) in the 1946 cohort, yet 0.30 SD (0.23-0.37) in the 2001 cohort. Expressed alternatively, there was a reduction in correlation from 0.17 (0.15-0.20) to 0.08 (0.06-0.10). This pattern of change in the association was observed across all ages and cognition measures used, was robust to adjustment for social class and parental height, and modeling of plausible missing-not-at-random scenarios. Quantile regression analyses suggested that these differences were driven by differences in the lower centiles of height, where environmental influence may be greatest. Conclusions Associations between height and cognitive assessment scores in childhood-adolescence substantially weakened from 1957-2018. These results support the notion that environmental and social change can markedly weaken associations between cognition and other traits. Funding DB is supported by the Economic and Social Research Council (grant number ES/M001660/1); DB and LW by the Medical Research Council (MR/V002147/1). The Medical Research Council (MRC) and the University of Bristol support the MRC Integrative Epidemiology Unit [MC_UU_00011/1]. NMD is supported by an Norwegian Research Council Grant number 295989. VM is supported by the CLOSER Innovation Fund WP19 which is funded by the Economic and Social Research Council (award reference: ES/K000357/1) and Economic and Social Research Council (ES/M001660/1). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Collapse
Affiliation(s)
- David Bann
- Centre for Longitudinal Studies, Social Research Institute, University College LondonLondonUnited Kingdom
| | - Liam Wright
- Centre for Longitudinal Studies, Social Research Institute, University College LondonLondonUnited Kingdom
| | - Neil M Davies
- MRC IEU, University of BristolBristolUnited Kingdom
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and TechnologyTrondheimNorway
| | - Vanessa Moulton
- Centre for Longitudinal Studies, Social Research Institute, University College LondonLondonUnited Kingdom
| |
Collapse
|
7
|
Kumar S, Voracek M. The relationships of family income and caste-status with religiousness: Mediation role of intolerance of uncertainty. PLoS One 2022; 17:e0273174. [PMID: 36026518 PMCID: PMC9417042 DOI: 10.1371/journal.pone.0273174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Accepted: 08/03/2022] [Indexed: 11/18/2022] Open
Abstract
The relationship between lower socioeconomic status (SES) and religiousness is well known; however, its (psychological mediation) mechanism is not clear. In the present study, we studied the mediation role of intolerance of uncertainty (IU; a personality measure of self-uncertainty) in the effect of SES on religiousness and its dimensions (i.e., believing, bonding, behaving, and belonging), in two different samples (students sample, N = 868, and community sample, N = 250), after controlling the effects of factors like age, sex, handedness, and self-reported risk-taking. The results showed that IU mediated the effects of lower family income and lower caste status (in students’ sample only) on religiousness and its dimensions; higher caste status had a direct effect on religiousness (and its dimensions), and; among the sub-factors of IU, only prospective IU affected religiousness. Thus, along with showing that IU is a mediator of the effects of lower family income and lower caste status on religiousness, the present study supports the contention that religiousness is a latent variable that varied factors can independently initiate. Moreover, the present study suggests a nuanced model of the relationship between the hierarchical caste system and religiousness.
Collapse
Affiliation(s)
- Sanjay Kumar
- Department of Psychology, D.A.V. College, Muzaffarnagar, India
- * E-mail: (SK); (MV)
| | - Martin Voracek
- Faculty of Psychology, Department of Cognition, Emotion, and Methods in Psychology, University of Vienna, Vienna¸ Austria
- * E-mail: (SK); (MV)
| |
Collapse
|
8
|
Noel SC, Fortin-Hamel L, Haque M, Scott ME. Maternal gastrointestinal nematode infection enhances spatial memory of uninfected juvenile mouse pups. Sci Rep 2022; 12:9796. [PMID: 35697723 PMCID: PMC9192650 DOI: 10.1038/s41598-022-13971-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 05/31/2022] [Indexed: 11/17/2022] Open
Abstract
The developing brain is particularly vulnerable to factors including maternal infection during pregnancy. Establishment of neural networks critical for memory and cognition begins during the perinatal period, when Heligmosomoides bakeri, a gastrointestinal (GI) nematode restricted to the maternal mouse intestine, has been shown to upregulate expression of long-term potentiation genes in the young rodent pup brain. We explored the impact of maternal infection during pregnancy and early lactation on the spatial behavior of uninfected male and female juvenile mice. Pre-weaned pups of H. bakeri infected dams exhibited less exploratory behaviour compared to pups of uninfected dams on postnatal day (PD) 16 but not PD 17, possibly reflecting a transient fear of an unfamiliar environment and/or a brief neurodevelopmental delay. Our two spatial memory tests show for the first time an enhancement of spatial memory in response to maternal nematode infection regardless of pup sex. At PD 17, pups of infected dams expressed object location memories after 3 h in the Object Location Test whereas offspring of uninfected mothers did not. In addition, at PD 34, juveniles of infected mothers retained their ability to find the escape hole in the Barnes Maze Test for one week whereas offspring from uninfected mothers did not. This finding is even more striking given that spatial memory was positively associated with pup length, yet this maternal infection impaired linear growth of pups. Thus, the positive impact of maternal infection on spatial memory countered any impairment associated with the shorter length of the pups. Overall, these novel findings indicate that a maternal GI nematode infection during pregnancy and lactation positively influences the spatial memory of uninfected juvenile offspring with potential fitness implications for the next generation.
Collapse
Affiliation(s)
- Sophia C Noel
- Institute of Parasitology, McGill University (Macdonald Campus), 21,111 Lakeshore Road, Ste-Anne de Bellevue, Quebec, H9X 3V9, Canada
| | - Liana Fortin-Hamel
- Institute of Parasitology, McGill University (Macdonald Campus), 21,111 Lakeshore Road, Ste-Anne de Bellevue, Quebec, H9X 3V9, Canada
| | - Manjurul Haque
- Institute of Parasitology, McGill University (Macdonald Campus), 21,111 Lakeshore Road, Ste-Anne de Bellevue, Quebec, H9X 3V9, Canada
| | - Marilyn E Scott
- Institute of Parasitology, McGill University (Macdonald Campus), 21,111 Lakeshore Road, Ste-Anne de Bellevue, Quebec, H9X 3V9, Canada.
| |
Collapse
|
9
|
Zapata I, Lilly ML, Herron ME, Serpell JA, Alvarez CE. Genetic testing of dogs predicts problem behaviors in clinical and nonclinical samples. BMC Genomics 2022; 23:102. [PMID: 35130840 PMCID: PMC8819838 DOI: 10.1186/s12864-022-08351-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Accepted: 01/25/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Very little is known about the etiology of personality and psychiatric disorders. Because the core neurobiology of many such traits is evolutionarily conserved, dogs present a powerful model. We previously reported genome scans of breed averages of ten traits related to fear, anxiety, aggression and social behavior in multiple cohorts of pedigree dogs. As a second phase of that discovery, here we tested the ability of markers at 13 of those loci to predict canine behavior in a community sample of 397 pedigree and mixed-breed dogs with individual-level genotype and phenotype data. RESULTS We found support for all markers and loci. By including 122 dogs with veterinary behavioral diagnoses in our cohort, we were able to identify eight loci associated with those diagnoses. Logistic regression models showed subsets of those loci could predict behavioral diagnoses. We corroborated our previous findings that small body size is associated with many problem behaviors and large body size is associated with increased trainability. Children in the home were associated with anxiety traits; illness and other animals in the home with coprophagia; working-dog status with increased energy and separation-related problems; and competitive dogs with increased aggression directed at familiar dogs, but reduced fear directed at humans and unfamiliar dogs. Compared to other dogs, Pit Bull-type dogs were not defined by a set of our markers and were not more aggressive; but they were strongly associated with pulling on the leash. Using severity-threshold models, Pit Bull-type dogs showed reduced risk of owner-directed aggression (75th quantile) and increased risk of dog-directed fear (95th quantile). CONCLUSIONS Our association analysis in a community sample of pedigree and mixed-breed dogs supports the interbreed mapping. The modeling shows some markers are predictive of behavioral diagnoses. Our findings have broad utility, including for clinical and breeding purposes, but we caution that thorough understanding is necessary for their interpretation and use.
Collapse
Affiliation(s)
- Isain Zapata
- Department of Veterinary Clinical Sciences, The Ohio State University College of Veterinary Medicine, Columbus, OH, 43210, USA. .,Department of Biomedical Sciences, Rocky Vista University College of Osteopathic Medicine, Parker, CO, 80134, USA.
| | - M Leanne Lilly
- Department of Veterinary Clinical Sciences, The Ohio State University College of Veterinary Medicine, Columbus, OH, 43210, USA
| | - Meghan E Herron
- Department of Veterinary Clinical Sciences, The Ohio State University College of Veterinary Medicine, Columbus, OH, 43210, USA
| | - James A Serpell
- Department of Clinical Sciences & Advanced Medicine, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Carlos E Alvarez
- Department of Veterinary Clinical Sciences, The Ohio State University College of Veterinary Medicine, Columbus, OH, 43210, USA. .,Center for Clinical and Translational Research, The Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, OH, 43205, USA. .,Department of Pediatrics, The Ohio State University College of Medicine, Columbus, OH, 43210, USA.
| |
Collapse
|
10
|
Frenzel S, Bis JC, Gudmundsson EF, O’Donnell A, Simino J, Yaqub A, Bartz TM, Brusselle GGO, Bülow R, DeCarli CS, Ewert R, Gharib SA, Ghosh S, Gireud-Goss M, Gottesman RF, Ikram MA, Knopman DS, Launer LJ, London SJ, Longstreth W, Lopez OL, Melo van Lent D, O’Connor G, Satizabal CL, Shrestha S, Sigurdsson S, Stubbe B, Talluri R, Vasan RS, Vernooij MW, Völzke H, Wiggins KL, Yu B, Beiser AS, Gudnason V, Mosley T, Psaty BM, Wolters FJ, Grabe HJ, Seshadri S. Associations of Pulmonary Function with MRI Brain Volumes: A Coordinated Multi-Study Analysis. J Alzheimers Dis 2022; 90:1073-1083. [PMID: 36213999 PMCID: PMC9712227 DOI: 10.3233/jad-220667] [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] [Accepted: 09/02/2022] [Indexed: 11/15/2022]
Abstract
BACKGROUND Previous studies suggest poor pulmonary function is associated with increased burden of cerebral white matter hyperintensities and brain atrophy among elderly individuals, but the results are inconsistent. OBJECTIVE To study the cross-sectional associations of pulmonary function with structural brain variables. METHODS Data from six large community-based samples (N = 11,091) were analyzed. Spirometric measurements were standardized with respect to age, sex, height, and ethnicity using reference equations of the Global Lung Function Initiative. Associations of forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), and their ratio FEV1/FVC with brain volume, gray matter volume, hippocampal volume, and volume of white matter hyperintensities were investigated using multivariable linear regressions for each study separately and then combined using random-effect meta-analyses. RESULTS FEV1 and FVC were positively associated with brain volume, gray matter volume, and hippocampal volume, and negatively associated with white matter hyperintensities volume after multiple testing correction, with little heterogeneity present between the studies. For instance, an increase of FVC by one unit was associated with 3.5 ml higher brain volume (95% CI: [2.2, 4.9]). In contrast, results for FEV1/FVC were more heterogeneous across studies, with significant positive associations with brain volume, gray matter volume, and hippocampal volume, but not white matter hyperintensities volume. Associations of brain variables with both FEV1 and FVC were consistently stronger than with FEV1/FVC, specifically with brain volume and white matter hyperintensities volume. CONCLUSION In cross-sectional analyses, worse pulmonary function is associated with smaller brain volumes and higher white matter hyperintensities burden.
Collapse
Affiliation(s)
- Stefan Frenzel
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Joshua C. Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | | | - Adrienne O’Donnell
- Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Jeannette Simino
- Gertrude C. Ford Memory Impairment and Neurodegenerative Dementia (MIND) Center, University of Mississippi Medical Center, Jackson, MS, USA
- Department of Data Science, John D. Bower School of Population Health, University of Mississippi Medical Center, Jackson, MS, USA
| | - Amber Yaqub
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Traci M. Bartz
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Guy G. O. Brusselle
- Department of Respiratory Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Robin Bülow
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Charles S. DeCarli
- Department of Neurology and Center for Neuroscience, University of California at Davis, Sacramento, CA, USA
- Imaging of Dementia and Aging (IDeA) Laboratory, Department of Neurology, University of California-Davis, Davis, CA, USA
| | - Ralf Ewert
- Department of Internal Medicine B, Cardiology, Intensive Care, Pulmonary Medicine and Infectious Diseases, University Medicine Greifswald, Greifswald, Germany
| | - Sina A. Gharib
- Center for Lung Biology, Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Saptaparni Ghosh
- Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University Schoolof Medicine, Boston, MA, USA
| | - Monica Gireud-Goss
- Glenn Biggs Institute for Alzheimer and Neurodegenerative Diseases, The University of Texas Health Science Center at San Antonio, SanAntonio, TX, USA
| | - Rebecca F. Gottesman
- Stroke, Cognition, and Neuroepidemiology (SCAN) section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - M. Arfan Ikram
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | | | - Lenore J. Launer
- Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, Bethesda, MD, USA
| | - Stephanie J. London
- Epidemiology Branch, National Institute of Environmental Health Sciences (NIEHS), National Institutes of Health (NIH), Department of Health and Human Services (DHHS), Research Triangle Park, NC, USA
| | - W.T. Longstreth
- Department of Neurology, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Oscar L. Lopez
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Debora Melo van Lent
- Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University Schoolof Medicine, Boston, MA, USA
- Glenn Biggs Institute for Alzheimer and Neurodegenerative Diseases, The University of Texas Health Science Center at San Antonio, SanAntonio, TX, USA
| | - George O’Connor
- Framingham Heart Study, Framingham, MA, USA
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Claudia L. Satizabal
- Glenn Biggs Institute for Alzheimer and Neurodegenerative Diseases, The University of Texas Health Science Center at San Antonio, SanAntonio, TX, USA
- Department of Population Health Sciences, The University of Texas Health Science Center at San Antonio, SanAntonio, TX, USA
| | - Srishti Shrestha
- Gertrude C. Ford Memory Impairment and Neurodegenerative Dementia (MIND) Center, University of Mississippi Medical Center, Jackson, MS, USA
- Department of Neurology, School of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | | | - Beate Stubbe
- Department of Internal Medicine B, Cardiology, Intensive Care, Pulmonary Medicine and Infectious Diseases, University Medicine Greifswald, Greifswald, Germany
| | - Rajesh Talluri
- Department of Data Science, John D. Bower School of Population Health, University of Mississippi Medical Center, Jackson, MS, USA
| | - Ramachandran S. Vasan
- Framingham Heart Study, Framingham, MA, USA
- Section of Preventive Medicine and Epidemiology, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
| | - Meike W. Vernooij
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Kerri L. Wiggins
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Bing Yu
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Alexa S. Beiser
- Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Department of Neurology, Boston School of Medicine, Boston, MA, USA
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Thomas Mosley
- Gertrude C. Ford Memory Impairment and Neurodegenerative Dementia (MIND) Center, University of Mississippi Medical Center, Jackson, MS, USA
- Department of Neurology, School of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
- Department of Medicine, School of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Frank J. Wolters
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Hans J. Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Disease (DZNE), partner site Rostock/Greifswald, Germany
| | - Sudha Seshadri
- Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University Schoolof Medicine, Boston, MA, USA
- Glenn Biggs Institute for Alzheimer and Neurodegenerative Diseases, The University of Texas Health Science Center at San Antonio, SanAntonio, TX, USA
- Department of Neurology, The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| |
Collapse
|
11
|
Sex-related associations between body height and cognitive impairment among low-income elderly adults in rural China: a population-based cross-sectional study. Biol Sex Differ 2021; 12:65. [PMID: 34872609 PMCID: PMC8647306 DOI: 10.1186/s13293-021-00408-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Accepted: 11/10/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Body height is a marker of childhood health and cumulative net nutrition during growth periods. However, sex-specific associations between body height and cognitive impairment are not well known in northern rural China. METHODS We assessed sex differences in the association between body height and cognitive impairment in a low-income elderly population in rural China. A population-based cross-sectional study was conducted from April 2014 to August 2014 to collect basic information from elderly residents aged 60 years and older in rural areas of Tianjin, China. Body height and Mini Mental State Examination (MMSE) scores were measured, and the relationships between these variables were assessed. RESULTS A total of 1081 residents with a mean age of 67.7 years were enrolled in this study. After adjusting for age, educational attainment, smoking status, drinking status, and the presence of hypertension, diabetes, and hypercholesterolemia, higher body height was found to be associated with a decreased prevalence of cognitive impairment in elderly men. Each 1-dm increase in height was associated with a 37% decrease in the prevalence of cognitive impairment. However, there was no significant association between body height and cognitive impairment among elderly women. CONCLUSION In conclusion, shorter body height was related to cognitive impairment independently of age, educational attainment, lifestyle factors, and health-related comorbid factors among low-income elderly men in rural China. Accordingly, shorter elderly men may be targeted for effective dementia prevention in rural China.
Collapse
|
12
|
Luo L, Xie F, Wang Y, Qin LQ, Yin JY, Wan Z. Taller adult height is associated with better performance of cognitive trajectories in Chinese over 45 years old: Evidence from the China Health and Retirement Longitudinal Study. Geriatr Gerontol Int 2021; 21:732-740. [PMID: 34134174 DOI: 10.1111/ggi.14203] [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: 01/31/2021] [Revised: 05/07/2021] [Accepted: 05/15/2021] [Indexed: 11/28/2022]
Abstract
AIM The association between adult height and follow-up cognition requires an update in China. We aimed to examine the association between baseline height and follow-up cognitive trajectories in Chinese subjects from the China Health and Retirement Longitudinal Study (CHARLS). METHODS A total of 6508 adults aged 45 years or older from the CHARLS were included for analysis. Latent class growth modeling was used to determine cognitive trajectories of 2011, 2013 and 2015. Multivariable linear regression and logistic regression models were used to examine the association between baseline adult height and cognitive performance and trajectories, respectively. RESULTS At baseline, an increment of 1 SD (8.3 cm) of height was associated with a higher global cognitive score (β = 0.492, 95% CI, 0.348-0.636), verbal episodic memory (β = 0.155, 95% CI, 0.086-0.224) and mental status (β = 0.337, 95% CI, 0.225-0.449). These associations were still observed even when stratified by sex. Prospectively, for females, the third quartile of height level (i.e., 155 to 158 cm) was associated with a better global cognitive function trajectory (OR = 1.627, P = 0.001, P for trend = 0.009) and mental status trajectory (OR = 1.456, P = 0.012, P for trend = 0.047); and the tallest height level (i.e., 159 cm or taller) was related to a better verbal episodic memory trajectory (OR = 1.574, P = 0.017). For males, no associations were observed. CONCLUSION Increased stature might be associated with better cognitive trajectories for subjects in China. Geriatr Gerontol Int 2021; 21: 732-740.
Collapse
Affiliation(s)
- Lan Luo
- School of Public Health, Soochow University, Suzhou, China
| | - Fangfei Xie
- The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, China
| | - Yun Wang
- The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, China
| | - Li-Qiang Qin
- School of Public Health, Soochow University, Suzhou, China
| | - Jie-Yun Yin
- School of Public Health, Soochow University, Suzhou, China
| | - Zhongxiao Wan
- School of Public Health, Soochow University, Suzhou, China
| |
Collapse
|
13
|
Chen Y, Dubey P, Müller HG, Bruchhage M, Wang JL, Deoni S. Modeling sparse longitudinal data in early neurodevelopment. Neuroimage 2021; 237:118079. [PMID: 34000395 DOI: 10.1016/j.neuroimage.2021.118079] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2020] [Revised: 04/09/2021] [Accepted: 04/12/2021] [Indexed: 11/15/2022] Open
Abstract
Early childhood is a period marked by rapid brain growth accompanied by cognitive and motor development. However, it remains unclear how early developmental skills relate to neuroanatomical growth across time with no growth quantile trajectories of typical brain development currently available to place and compare individual neuroanatomical development. Even though longitudinal neuroimaging data have become more common, they are often sparse, making dynamic analyses at subject level a challenging task. Using the Principal Analysis through Conditional Expectation (PACE) approach geared towards sparse longitudinal data, we investigate the evolution of gray matter, white matter and cerebrospinal fluid volumes in a cohort of 446 children between the ages of 1 and 120 months. For each child, we calculate their dynamic age-varying association between the growing brain and scores that assess cognitive functioning, applying the functional varying coefficient model. Using local Fréchet regression, we construct age-varying growth percentiles to reveal the evolution of brain development across the population. To further demonstrate its utility, we apply PACE to predict individual trajectories of brain development.
Collapse
Affiliation(s)
- Yaqing Chen
- Department of Statistics, University of California, Davis, Davis, CA, 95616, USA
| | - Paromita Dubey
- Department of Statistics, Stanford University, Stanford, CA, 94305, USA
| | - Hans-Georg Müller
- Department of Statistics, University of California, Davis, Davis, CA, 95616, USA
| | - Muriel Bruchhage
- Advanced Baby Imaging Lab, Hasbro Children's Hospital, Rhode Island Hospital, Providence, RI, 02903, USA; Department of Pediatrics, Warren Alpert Medical School at Brown University, Providence, RI, 02912, USA
| | - Jane-Ling Wang
- Department of Statistics, University of California, Davis, Davis, CA, 95616, USA
| | - Sean Deoni
- Advanced Baby Imaging Lab, Hasbro Children's Hospital, Rhode Island Hospital, Providence, RI, 02903, USA; Department of Pediatrics, Warren Alpert Medical School at Brown University, Providence, RI, 02912, USA; Department of Radiology, Warren Alpert Medical School at Brown University, Providence, RI, 02912, USA; Maternal, Newborn, and Child Health Discovery & Tools, Bill & Melinda Gates Foundation, Seattle, WA, USA.
| |
Collapse
|
14
|
Multivariate Patterns of Brain-Behavior-Environment Associations in the Adolescent Brain and Cognitive Development Study. Biol Psychiatry 2021; 89:510-520. [PMID: 33109338 PMCID: PMC7867576 DOI: 10.1016/j.biopsych.2020.08.014] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2020] [Revised: 08/17/2020] [Accepted: 08/19/2020] [Indexed: 12/15/2022]
Abstract
BACKGROUND Adolescence is a critical developmental stage. A key challenge is to characterize how variation in adolescent brain organization relates to psychosocial and environmental influences. METHODS We used canonical correlation analysis to discover distinct patterns of covariation between measures of brain organization (brain morphometry, intracortical myelination, white matter integrity, and resting-state functional connectivity) and individual, psychosocial, and environmental factors in a nationally representative U.S. sample of 9623 individuals (aged 9-10 years, 49% female) participating in the Adolescent Brain and Cognitive Development (ABCD) study. RESULTS These analyses identified 14 reliable modes of brain-behavior-environment covariation (canonical rdiscovery = .21 to .49, canonical rtest = .10 to .39, pfalse discovery rate corrected < .0001). Across modes, neighborhood environment, parental characteristics, quality of family life, perinatal history, cardiometabolic health, cognition, and psychopathology had the most consistent and replicable associations with multiple measures of brain organization; positive and negative exposures converged to form patterns of psychosocial advantage or adversity. These showed modality-general, respectively positive or negative, associations with brain structure and function with little evidence of regional specificity. Nested within these cross-modal patterns were more specific associations between prefrontal measures of morphometry, intracortical myelination, and functional connectivity with affective psychopathology, cognition, and family environment. CONCLUSIONS We identified clusters of exposures that showed consistent modality-general associations with global measures of brain organization. These findings underscore the importance of understanding the complex and intertwined influences on brain organization and mental function during development and have the potential to inform public health policies aiming toward interventions to improve mental well-being.
Collapse
|
15
|
Effects of hand preference on digit lengths and digit ratios among children and adults. Early Hum Dev 2020; 151:105204. [PMID: 33059164 DOI: 10.1016/j.earlhumdev.2020.105204] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2020] [Revised: 09/28/2020] [Accepted: 09/29/2020] [Indexed: 01/21/2023]
Abstract
BACKGROUND Prenatal sex hormones may not exclusively determine effects of hand preference on digit ratios. Genetic determination is an alternative possibility. AIM To study the likelihood of similar effects of hand preference on digit lengths and digit ratios. METHODS We selected similar numbers of left-handers and right-handers in samples of kindergarten children (N = 101, age range: 3.5-7 years) and adults (N = 189, age range: 17-28 years) and measured digit lengths (excluding the thumb) directly on the palmar hand. RESULTS Compared to right-handers, left-handers had longer digits and lower third-to-fourth (3D:4D) digit ratios among children, whereas an opposite pattern of handedness differences occurred among adults. CONCLUSIONS Effects of hand preference on digit lengths and ratios might be genetically/ontogenetically determined. Also discussed are implications of this set of findings for digit ratio research.
Collapse
|
16
|
Mitchell BL, Cuéllar-Partida G, Grasby KL, Campos AI, Strike LT, Hwang LD, Okbay A, Thompson PM, Medland SE, Martin NG, Wright MJ, Rentería ME. Educational attainment polygenic scores are associated with cortical total surface area and regions important for language and memory. Neuroimage 2020; 212:116691. [PMID: 32126298 DOI: 10.1016/j.neuroimage.2020.116691] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2019] [Revised: 02/06/2020] [Accepted: 02/26/2020] [Indexed: 02/01/2023] Open
Abstract
It is well established that higher cognitive ability is associated with larger brain size. However, individual variation in intelligence exists despite brain size and recent studies have shown that a simple unifactorial view of the neurobiology underpinning cognitive ability is probably unrealistic. Educational attainment (EA) is often used as a proxy for cognitive ability since it is easily measured, resulting in large sample sizes and, consequently, sufficient statistical power to detect small associations. This study investigates the association between three global (total surface area (TSA), intra-cranial volume (ICV) and average cortical thickness) and 34 regional cortical measures with educational attainment using a polygenic scoring (PGS) approach. Analyses were conducted on two independent target samples of young twin adults with neuroimaging data, from Australia (N = 1097) and the USA (N = 723), and found that higher EA-PGS were significantly associated with larger global brain size measures, ICV and TSA (R2 = 0.006 and 0.016 respectively, p < 0.001) but not average thickness. At the regional level, we identified seven cortical regions-in the frontal and temporal lobes-that showed variation in surface area and average cortical thickness over-and-above the global effect. These regions have been robustly implicated in language, memory, visual recognition and cognitive processing. Additionally, we demonstrate that these identified brain regions partly mediate the association between EA-PGS and cognitive test performance. Altogether, these findings advance our understanding of the neurobiology that underpins educational attainment and cognitive ability, providing focus points for future research.
Collapse
Affiliation(s)
- Brittany L Mitchell
- Department of Genetics & Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia; School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia.
| | - Gabriel Cuéllar-Partida
- The University of Queensland Diamantina Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Katrina L Grasby
- Department of Genetics & Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Adrian I Campos
- Department of Genetics & Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia; Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Lachlan T Strike
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Liang-Dar Hwang
- The University of Queensland Diamantina Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Aysu Okbay
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging & Informatics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Sarah E Medland
- Department of Genetics & Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Nicholas G Martin
- Department of Genetics & Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia; School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia
| | - Margaret J Wright
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia; Centre for Advanced Imaging, The University of Queensland, Brisbane, QLD, Australia
| | - Miguel E Rentería
- Department of Genetics & Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia; School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia
| |
Collapse
|
17
|
Zarnani K, Nichols TE, Alfaro-Almagro F, Fagerlund B, Lauritzen M, Rostrup E, Smith SM. Discovering markers of healthy aging: a prospective study in a Danish male birth cohort. Aging (Albany NY) 2019; 11:5943-5974. [PMID: 31480020 PMCID: PMC6738442 DOI: 10.18632/aging.102151] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2019] [Accepted: 07/31/2019] [Indexed: 01/23/2023]
Abstract
There is a pressing need to identify markers of cognitive and neural decline in healthy late-midlife participants. We explored the relationship between cross-sectional structural brain-imaging derived phenotypes (IDPs) and cognitive ability, demographic, health and lifestyle factors (non-IDPs). Participants were recruited from the 1953 Danish Male Birth Cohort (N=193). Applying an extreme group design, members were selected in 2 groups based on cognitive change between IQ at age ~20y (IQ-20) and age ~57y (IQ-57). Subjects showing the highest (n=95) and lowest (n=98) change were selected (at age ~57) for assessments on multiple IDPs and non-IDPs. We investigated the relationship between 453 IDPs and 70 non-IDPs through pairwise correlation and multivariate canonical correlation analysis (CCA) models. Significant pairwise associations included positive associations between IQ-20 and gray-matter volume of the temporal pole. CCA identified a richer pattern - a single "positive-negative" mode of population co-variation coupling individual cross-subject variations in IDPs to an extensive range of non-IDP measures (r = 0.75, Pcorrected < 0.01). Specifically, this mode linked higher cognitive performance, positive early-life social factors, and mental health to a larger brain volume of several brain structures, overall volume, and microstructural properties of some white matter tracts. Interestingly, both statistical models identified IQ-20 and gray-matter volume of the temporal pole as important contributors to the inter-individual variation observed. The converging patterns provide novel insight into the importance of early adulthood intelligence as a significant marker of late-midlife neural decline and motivates additional study.
Collapse
Affiliation(s)
- Kiyana Zarnani
- Functional Imaging Unit, Department of Clinical Physiology, Nuclear Medicine and PET, Copenhagen University Hospital Rigshospitalet, Glostrup, Denmark.,Center for Healthy Aging, University of Copenhagen, Copenhagen, Denmark.,Department of Neuroscience, University of Copenhagen, Copenhagen, Denmark.,Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Thomas E Nichols
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.,Oxford Big Data Institute, Li Ka Shing, Centre For Health Information and Discovery, Nuffield Department of Population Health University of Oxford, Oxford, UK.,Department of Statistics, University of Warwick, Coventry, UK
| | - Fidel Alfaro-Almagro
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Birgitte Fagerlund
- Center for Neuropsychiatric Schizophrenia Research, Mental Health Center, Glostrup, Denmark.,Department of Psychology, University of Copenhagen, Copenhagen, Denmark
| | - Martin Lauritzen
- Center for Healthy Aging, University of Copenhagen, Copenhagen, Denmark.,Department of Neuroscience, University of Copenhagen, Copenhagen, Denmark.,Department of Clinical Medicine, Glostrup, Denmark
| | - Egill Rostrup
- Center for Healthy Aging, University of Copenhagen, Copenhagen, Denmark.,Center for Neuropsychiatric Schizophrenia Research, Mental Health Center, Glostrup, Denmark.,Department of Psychology, University of Copenhagen, Copenhagen, Denmark
| | - Stephen M Smith
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| |
Collapse
|
18
|
Jäncke L, Liem F, Merillat S. Weak correlations between body height and several brain metrics in healthy elderly subjects. Eur J Neurosci 2019; 50:3578-3589. [DOI: 10.1111/ejn.14501] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2019] [Revised: 06/18/2019] [Accepted: 06/27/2019] [Indexed: 01/06/2023]
Affiliation(s)
- Lutz Jäncke
- Division Neuropsychology Institute of Psychology University of Zurich Zurich Switzerland
- University Research Priority Program (URPP) “Dynamics of Healthy Aging” University of Zurich Zurich Switzerland
| | - Franz Liem
- Division Neuropsychology Institute of Psychology University of Zurich Zurich Switzerland
- University Research Priority Program (URPP) “Dynamics of Healthy Aging” University of Zurich Zurich Switzerland
| | - Susan Merillat
- Division Neuropsychology Institute of Psychology University of Zurich Zurich Switzerland
- University Research Priority Program (URPP) “Dynamics of Healthy Aging” University of Zurich Zurich Switzerland
| |
Collapse
|