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Behrendt T, Quisilima JI, Bielitzki R, Behrens M, Glazachev OS, Brigadski T, Leßmann V, Schega L. Brain-Derived neurotrophic factor and inflammatory biomarkers are unaffected by acute and chronic intermittent hypoxic-hyperoxic exposure in geriatric patients: a randomized controlled trial. Ann Med 2024; 56:2304650. [PMID: 38253008 PMCID: PMC10810628 DOI: 10.1080/07853890.2024.2304650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 11/24/2023] [Indexed: 01/24/2024] Open
Abstract
BACKGROUND Animal and human studies have shown that exposure to hypoxia can increase brain-derived neurotrophic factor (BDNF) protein transcription and reduce systematic inflammatory cytokine response. Therefore, the aim of this study was to investigate the acute and chronic effects of intermittent hypoxic-hyperoxic exposure (IHHE) prior to aerobic exercise on BDNF, interleukin-6 (IL-6), and C-reactive protein (CRP) blood levels in geriatric patients. PATIENTS AND METHODS Twenty-five geriatric patients (83.1 ± 5.0 yrs, 71.1 ± 10.0 kg, 1.8 ± 0.9 m) participated in a placebo-controlled, single-blinded trial and were randomly assigned to either an intervention (IG) or control group (CG) performing an aerobic cycling training (17 sessions, 20 min·session-1, 3 sessions·week-1). Prior to aerobic cycling exercise, the IG was additionally exposed to IHHE for 30 min, whereas the CG received continuous normoxic air. Blood samples were taken immediately before (pre-exercise) and 10 min (post-exercise) after the first session as well as 48 h (post-training) after the last session to determine serum (BDNFS) and plasma BDNF (BDNFP), IL-6, and CRP levels. Intervention effects were analyzed using a 2 x 2 analysis of covariance with repeated measures. Results were interpreted based on effect sizes with a medium effect considered as meaningful (ηp2 ≥ 0.06, d ≥ 0.5). RESULTS CRP was moderately higher (d = 0.51) in the CG compared to the IG at baseline. IHHE had no acute effect on BDNFS (ηp2 = 0.01), BDNFP (ηp2 < 0.01), BDNF serum/plasma-ratio (ηp2 < 0.01), IL-6 (ηp2 < 0.01), or CRP (ηp2 = 0.04). After the 6-week intervention, an interaction was found for BDNF serum/plasma-ratio (ηp2 = 0.06) but not for BDNFS (ηp2 = 0.04), BDNFP (ηp2 < 0.01), IL-6 (ηp2 < 0.01), or CRP (ηp2 < 0.01). BDNF serum/plasma-ratio increased from pre-exercise to post-training (d = 0.67) in the CG compared to the IG (d = 0.51). A main effect of time was found for BDNFP (ηp2 = 0.09) but not for BDNFS (ηp2 = 0.02). Within-group post-hoc analyses revealed a training-related reduction in BDNFP in the IG and CG by 46.1% (d = 0.73) and 24.7% (d = 0.57), respectively. CONCLUSION The addition of 30 min IHHE prior to 20 min aerobic cycling seems not to be effective to increase BDNFS and BDNFP or to reduce IL-6 and CRP levels in geriatric patients after a 6-week intervention.The study was retrospectively registered at drks.de (DRKS-ID: DRKS00025130).
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Affiliation(s)
- Tom Behrendt
- Department of Sport Science, Chair for Health and Physical Activity, Otto-von-Guericke University Magdeburg, Magdeburg, Germany
| | - Jessica Ibanez Quisilima
- Department of Sport Science, Chair for Health and Physical Activity, Otto-von-Guericke University Magdeburg, Magdeburg, Germany
| | - Robert Bielitzki
- Department of Sport Science, Chair for Health and Physical Activity, Otto-von-Guericke University Magdeburg, Magdeburg, Germany
| | - Martin Behrens
- University of Applied Sciences for Sport and Management Potsdam, Potsdam, Germany
| | - Oleg S. Glazachev
- Department of Human Physiology, Institute of Clinical Medicine, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Tanja Brigadski
- Department of Informatics and Microsystem Technology, University of Applied Sciences Kaiserslautern, Zweibrücken, Germany
| | - Volkmar Leßmann
- Institute of Physiology, Otto-von-Guericke University Magdeburg, Medical Faculty, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
| | - Lutz Schega
- Department of Sport Science, Chair for Health and Physical Activity, Otto-von-Guericke University Magdeburg, Magdeburg, Germany
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Rodríguez-Fernández B, Sánchez-Benavides G, Genius P, Minguillon C, Fauria K, De Vivo I, Navarro A, Molinuevo JL, Gispert JD, Sala-Vila A, Vilor-Tejedor N, Crous-Bou M. Association between telomere length and cognitive function among cognitively unimpaired individuals at risk of Alzheimer's disease. Neurobiol Aging 2024; 141:140-150. [PMID: 38936230 DOI: 10.1016/j.neurobiolaging.2024.05.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 05/23/2024] [Accepted: 05/24/2024] [Indexed: 06/29/2024]
Abstract
INTRODUCTION Leukocyte telomere length (LTL) is an objective biomarker of biological aging, and it is proposed to play a crucial role in Alzheimer's disease (AD) risk. We aimed at evaluating the cross-sectional association between LTL and cognitive performance in middle-aged cognitively unimpaired individuals at increased risk of AD. METHODS A total of 1520 participants from the ALFA cohort were included. Relative telomere length was measured in leukocytes through qPCR. LTL was residualized against age and sex, and associations with cognitive performance were assessed in short and long groups based on residualized LTL (rLTL). Interactions with sex and genetic risk of AD were tested. RESULTS Non-linear associations were found between LTL and episodic memory (EM). Better EM was associated with longer rLTL among women in the short rLTL group. DISCUSSION Results suggest a potential role of telomeres in the cognitive aging process with sex-specific patterns.
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Affiliation(s)
- Blanca Rodríguez-Fernández
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, C/ de Wellington, 30, Barcelona 08005, Spain; IMIM - Hospital del Mar Medical Research Institute, C/ del Dr. Aiguader, 88, 2nd floor, Campus Mar, Barcelona 08003, Spain; Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, C/ del Dr. Aiguader, 88, Barcelona 08003, Spain; Universitat Autònoma de Barcelona, 08193, Cerdanyola del Vallès, Barcelona, Spain
| | - Gonzalo Sánchez-Benavides
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, C/ de Wellington, 30, Barcelona 08005, Spain; IMIM - Hospital del Mar Medical Research Institute, C/ del Dr. Aiguader, 88, 2nd floor, Campus Mar, Barcelona 08003, Spain; Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBER-FES). Instituto de Salud Carlos III, C/ Monforte de Lemos 3-5. Pabellón 11, Planta 0, Madrid 28029, Spain
| | - Patricia Genius
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, C/ de Wellington, 30, Barcelona 08005, Spain; IMIM - Hospital del Mar Medical Research Institute, C/ del Dr. Aiguader, 88, 2nd floor, Campus Mar, Barcelona 08003, Spain; Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, C/ del Dr. Aiguader, 88, Barcelona 08003, Spain
| | - Carolina Minguillon
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, C/ de Wellington, 30, Barcelona 08005, Spain; IMIM - Hospital del Mar Medical Research Institute, C/ del Dr. Aiguader, 88, 2nd floor, Campus Mar, Barcelona 08003, Spain; Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBER-FES). Instituto de Salud Carlos III, C/ Monforte de Lemos 3-5. Pabellón 11, Planta 0, Madrid 28029, Spain
| | - Karine Fauria
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, C/ de Wellington, 30, Barcelona 08005, Spain; Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBER-FES). Instituto de Salud Carlos III, C/ Monforte de Lemos 3-5. Pabellón 11, Planta 0, Madrid 28029, Spain
| | - Immaculata De Vivo
- Department of Epidemiology, Harvard T.H. Chan School of Public Health. School of Public Health 2, 677 Huntington Ave, Boston, MA 02115, USA; Channing Division of Network Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Arcadi Navarro
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, C/ de Wellington, 30, Barcelona 08005, Spain; Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, C/ del Dr. Aiguader, 88, Barcelona 08003, Spain; Institute of Evolutionary Biology (CSIC-UPF), Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Pg. Marítim de la Barceloneta, 37, Barcelona 08003, Spain; Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Jose Luis Molinuevo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, C/ de Wellington, 30, Barcelona 08005, Spain
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, C/ de Wellington, 30, Barcelona 08005, Spain; IMIM - Hospital del Mar Medical Research Institute, C/ del Dr. Aiguader, 88, 2nd floor, Campus Mar, Barcelona 08003, Spain; Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina. Instituto de Salud Carlos III, C/ Monforte de Lemos 3-5. Pabellón 11, Planta 0, Madrid 28029, Spain; Centro Nacional de Investigaciones Cardiovasculares (CNIC), C. de Melchor Fernández Almagro, 3, Madrid 28029, Spain
| | - Aleix Sala-Vila
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, C/ de Wellington, 30, Barcelona 08005, Spain; IMIM - Hospital del Mar Medical Research Institute, C/ del Dr. Aiguader, 88, 2nd floor, Campus Mar, Barcelona 08003, Spain
| | - Natalia Vilor-Tejedor
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, C/ de Wellington, 30, Barcelona 08005, Spain; IMIM - Hospital del Mar Medical Research Institute, C/ del Dr. Aiguader, 88, 2nd floor, Campus Mar, Barcelona 08003, Spain; Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, C/ del Dr. Aiguader, 88, Barcelona 08003, Spain; Department of Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands; Universitat Pompeu Fabra, C/ de Ramon Trias Fargas, 25, 27, Barcelona 08005, Spain.
| | - Marta Crous-Bou
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, C/ de Wellington, 30, Barcelona 08005, Spain; Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBER-FES). Instituto de Salud Carlos III, C/ Monforte de Lemos 3-5. Pabellón 11, Planta 0, Madrid 28029, Spain; Department of Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands; Catalan Institute of Oncology (ICO)-Bellvitge Biomedical Research Center (IDIBELL), Hospital Duran i Reynals, Avinguda de la Granvia de l'Hospitalet, 199-203, L'Hospitalet de Llobregat, Barcelona 08908, Spain.
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Yang H, Chen Y, Tao Q, Shi W, Tian Y, Wei Y, Li S, Zhang Y, Han S, Cheng J. Integrative molecular and structural neuroimaging analyses of the interaction between depression and age of onset: A multimodal magnetic resonance imaging study. Prog Neuropsychopharmacol Biol Psychiatry 2024; 134:111052. [PMID: 38871019 DOI: 10.1016/j.pnpbp.2024.111052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/08/2024] [Revised: 05/30/2024] [Accepted: 06/10/2024] [Indexed: 06/15/2024]
Abstract
Depression is a neurodevelopmental disorder that exhibits progressive gray matter volume (GMV) atrophy. Research indicates that brain development is influential in depression-induced GMV alterations. However, the interaction between depression and age of onset is not well understood by the underlying molecular and neuropathological mechanisms. Thus, 152 first-episode depression individuals and matched 130 healthy controls (HCs) were recruited to undergo T1-weighted high-resolution magnetic resonance imaging for this study. By two-way ANOVA, age and diagnosis were used as factors when analyzing the interaction of GMV in the participants. Then, spatial correlations between neurotransmitter maps and factor-related volume maps are established. Results illustrate a pronounced antagonistic interaction between depression and age of onset in the right insula, superior temporal gyrus, anterior cingulate gyrus, and orbitofrontal gyrus. Depression-caused reductions in GMV are mainly distributed in thalamic-limbic-cortical regions, regardless of age. For the main effect of age, adults exhibit brain atrophy in frontal, cerebellum, parietal, and temporal lobe structures. Cross-modal correlations showed that GMV changes in the interactive regions were linked with the serotonergic system and dopaminergic systems. Summarily, our results reveal the interaction between depression and age of onset in neurobiological mechanisms, which provide hints for future treatment of different ages of depression.
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Affiliation(s)
- Huiting Yang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, Zhengzhou, China; Henan Engineering Technology Research Center for detection and application of brain function, Zhengzhou, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, Zhengzhou, China; Henan key laboratory of imaging intelligence research, Zhengzhou, China; Henan Engineering Research Center of Brain Function Development and Application, Zhengzhou, China
| | - Yuan Chen
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, Zhengzhou, China; Henan Engineering Technology Research Center for detection and application of brain function, Zhengzhou, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, Zhengzhou, China; Henan key laboratory of imaging intelligence research, Zhengzhou, China; Henan Engineering Research Center of Brain Function Development and Application, Zhengzhou, China
| | - Qiuying Tao
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, Zhengzhou, China; Henan Engineering Technology Research Center for detection and application of brain function, Zhengzhou, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, Zhengzhou, China; Henan key laboratory of imaging intelligence research, Zhengzhou, China; Henan Engineering Research Center of Brain Function Development and Application, Zhengzhou, China
| | - Wenqing Shi
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, Zhengzhou, China; Henan Engineering Technology Research Center for detection and application of brain function, Zhengzhou, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, Zhengzhou, China; Henan key laboratory of imaging intelligence research, Zhengzhou, China; Henan Engineering Research Center of Brain Function Development and Application, Zhengzhou, China
| | - Ya Tian
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, Zhengzhou, China; Henan Engineering Technology Research Center for detection and application of brain function, Zhengzhou, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, Zhengzhou, China; Henan key laboratory of imaging intelligence research, Zhengzhou, China; Henan Engineering Research Center of Brain Function Development and Application, Zhengzhou, China
| | - Yarui Wei
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, Zhengzhou, China; Henan Engineering Technology Research Center for detection and application of brain function, Zhengzhou, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, Zhengzhou, China; Henan key laboratory of imaging intelligence research, Zhengzhou, China; Henan Engineering Research Center of Brain Function Development and Application, Zhengzhou, China
| | - Shuying Li
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, Zhengzhou, China; Henan Engineering Technology Research Center for detection and application of brain function, Zhengzhou, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, Zhengzhou, China; Henan key laboratory of imaging intelligence research, Zhengzhou, China; Henan Engineering Research Center of Brain Function Development and Application, Zhengzhou, China.
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, Zhengzhou, China; Henan Engineering Technology Research Center for detection and application of brain function, Zhengzhou, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, Zhengzhou, China; Henan key laboratory of imaging intelligence research, Zhengzhou, China; Henan Engineering Research Center of Brain Function Development and Application, Zhengzhou, China.
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, Zhengzhou, China; Henan Engineering Technology Research Center for detection and application of brain function, Zhengzhou, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, Zhengzhou, China; Henan key laboratory of imaging intelligence research, Zhengzhou, China; Henan Engineering Research Center of Brain Function Development and Application, Zhengzhou, China.
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Buzi G, Eustache F, Droit-Volet S, Desaunay P, Hinault T. Towards a neurodevelopmental cognitive perspective of temporal processing. Commun Biol 2024; 7:987. [PMID: 39143328 PMCID: PMC11324894 DOI: 10.1038/s42003-024-06641-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2024] [Accepted: 07/26/2024] [Indexed: 08/16/2024] Open
Abstract
The ability to organize and memorize the unfolding of events over time is a fundamental feature of cognition, which develops concurrently with the maturation of the brain. Nonetheless, how temporal processing evolves across the lifetime as well as the links with the underlying neural substrates remains unclear. Here, we intend to retrace the main developmental stages of brain structure, function, and cognition linked to the emergence of timing abilities. This neurodevelopmental perspective aims to untangle the puzzling trajectory of temporal processing aspects across the lifetime, paving the way to novel neuropsychological assessments and cognitive rehabilitation strategies.
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Affiliation(s)
- Giulia Buzi
- Inserm, U1077, EPHE, UNICAEN, Normandie Université, PSL Université Paris, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine (NIMH), Caen, France
| | - Francis Eustache
- Inserm, U1077, EPHE, UNICAEN, Normandie Université, PSL Université Paris, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine (NIMH), Caen, France
| | - Sylvie Droit-Volet
- Université Clermont Auvergne, LAPSCO, CNRS, UMR 6024, Clermont-Ferrand, France
| | - Pierre Desaunay
- Inserm, U1077, EPHE, UNICAEN, Normandie Université, PSL Université Paris, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine (NIMH), Caen, France
- Service de Psychiatrie de l'enfant et de l'adolescent, CHU de Caen, Caen, France
| | - Thomas Hinault
- Inserm, U1077, EPHE, UNICAEN, Normandie Université, PSL Université Paris, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine (NIMH), Caen, France.
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Liu C, Cai Q, Gou Y, Liu Y, Kang M, Hui J, Zhou R, Shi P, Wang B, Zhang F. Association of accelerated biological aging with brain volumes: A cross-sectional study. J Affect Disord 2024; 364:188-193. [PMID: 39147148 DOI: 10.1016/j.jad.2024.08.078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Revised: 07/10/2024] [Accepted: 08/12/2024] [Indexed: 08/17/2024]
Abstract
BACKGROUND Multiple epidemiological studies have observed the connection between aging and brain volumes. The concept of accelerated biological aging (BA) is more powerful for observing the degree of aging of an individual than chronologic age (CA). The objective of this study is to explore the relationship between BA and brain volumes. METHODS BA was measured from clinical traits using two blood-chemistry algorithms, the Klemera-Doubal method (KDM) and the PhenoAge. The two age acceleration biomarkers were calculated by the residuals from regressing CA, termed "KDM-acceleration" and "PhenoAge-acceleration". Brain volumes were from brain magnetic resonance imaging (MRI) data. After adjustment for confounding factors, general linear regression models were used to examine associations between KDM-acceleration and PhenoAge-acceleration and brain volumes, respectively. Additionally, we stratified participants by sex, age, and the four quartiles of the Townsend Deprivation Index (TDI) for extra subgroup analysis. RESULTS 14,725 participants with available information were enrolled. After full adjustment, we observed negative associations between KDM-acceleration and brain volumes, such as gray matter (β = -0.029), white matter (β = -0.021), gray and white matter (β = -0.026), and hippocampus (β = -0.011 for left and β = -0.014 for right). There were also negative associations between PhenoAge-acceleration and brain volumes, such as white matter (β = -0.008), gray and white matter (β = -0.010), thalamus (β = -0.012 for left and β = -0.012 for right). In the subgroup analysis stratified by sex, age, and the four quartiles of TDI, the association between KDM-acceleration and PhenoAge-acceleration and brain volumes still existed. In subgroup analyses, the variation in associations suggests that socioeconomic and biological factors may differentially influence brain aging. CONCLUSIONS Our research indicated that more advanced BA was associated with less brain tissue.
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Affiliation(s)
- Chen Liu
- Key Laboratory of Environment and Endemic Diseases of National Health Commission of China, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Qingqing Cai
- Key Laboratory of Environment and Endemic Diseases of National Health Commission of China, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Yifan Gou
- Key Laboratory of Environment and Endemic Diseases of National Health Commission of China, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Ye Liu
- Key Laboratory of Environment and Endemic Diseases of National Health Commission of China, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Meijuan Kang
- Key Laboratory of Environment and Endemic Diseases of National Health Commission of China, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Jingni Hui
- Key Laboratory of Environment and Endemic Diseases of National Health Commission of China, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Ruixue Zhou
- Key Laboratory of Environment and Endemic Diseases of National Health Commission of China, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Panxing Shi
- Key Laboratory of Environment and Endemic Diseases of National Health Commission of China, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Bingyi Wang
- Key Laboratory of Environment and Endemic Diseases of National Health Commission of China, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Feng Zhang
- Key Laboratory of Environment and Endemic Diseases of National Health Commission of China, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China.
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Criel Y, Depuydt E, Miatton M, Santens P, van Mierlo P, De Letter M. Cortical Generators and Connections Underlying Phoneme Perception: A Mismatch Negativity and P300 Investigation. Brain Topogr 2024:10.1007/s10548-024-01065-z. [PMID: 38958833 DOI: 10.1007/s10548-024-01065-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Accepted: 06/19/2024] [Indexed: 07/04/2024]
Abstract
The cortical generators of the pure tone MMN and P300 have been thoroughly studied. Their nature and interaction with respect to phoneme perception, however, is poorly understood. Accordingly, the cortical sources and functional connections that underlie the MMN and P300 in relation to passive and active speech sound perception were identified. An inattentive and attentive phonemic oddball paradigm, eliciting a MMN and P300 respectively, were administered in 60 healthy adults during simultaneous high-density EEG recording. For both the MMN and P300, eLORETA source reconstruction was performed. The maximal cross-correlation was calculated between ROI-pairs to investigate inter-regional functional connectivity specific to passive and active deviant processing. MMN activation clusters were identified in the temporal (insula, superior temporal gyrus and temporal pole), frontal (rostral middle frontal and pars opercularis) and parietal (postcentral and supramarginal gyrus) cortex. Passive discrimination of deviant phonemes was aided by a network connecting right temporoparietal cortices to left frontal areas. For the P300, clusters with significantly higher activity were found in the frontal (caudal middle frontal and precentral), parietal (precuneus) and cingulate (posterior and isthmus) cortex. Significant intra- and interhemispheric connections between parietal, cingulate and occipital regions constituted the network governing active phonemic target detection. A predominantly bilateral network was found to underly both the MMN and P300. While passive phoneme discrimination is aided by a fronto-temporo-parietal network, active categorization calls on a network entailing fronto-parieto-cingulate cortices. Neural processing of phonemic contrasts, as reflected by the MMN and P300, does not appear to show pronounced lateralization to the language-dominant hemisphere.
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Affiliation(s)
- Yana Criel
- Department of Rehabilitation Sciences, Ghent University, Ghent, Belgium.
| | - Emma Depuydt
- Medical Imaging and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | - Marijke Miatton
- Department of Neurology, Ghent University Hospital, Ghent, Belgium
- Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Patrick Santens
- Department of Neurology, Ghent University Hospital, Ghent, Belgium
- Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Pieter van Mierlo
- Medical Imaging and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | - Miet De Letter
- Department of Rehabilitation Sciences, Ghent University, Ghent, Belgium
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Lee HK, Basak C, Grant SJ, Ray NR, Skolasinska PA, Oehler C, Qin S, Sun A, Smith ET, Sherard GH, Rivera-Dompenciel A, Merzenich M, Voss MW. The Effects of Computerized Cognitive Training in Older Adults' Cognitive Performance and Biomarkers of Structural Brain Aging. J Gerontol B Psychol Sci Soc Sci 2024; 79:gbae075. [PMID: 38686621 PMCID: PMC11165429 DOI: 10.1093/geronb/gbae075] [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: 07/24/2023] [Indexed: 05/02/2024] Open
Abstract
OBJECTIVES Cognitive training (CT) has been investigated as a means of delaying age-related cognitive decline in older adults. However, its impact on biomarkers of age-related structural brain atrophy has rarely been investigated, leading to a gap in our understanding of the linkage between improvements in cognition and brain plasticity. This study aimed to explore the impact of CT on cognitive performance and brain structure in older adults. METHODS One hundred twenty-four cognitively normal older adults recruited from 2 study sites were randomly assigned to either an adaptive CT (n = 60) or a casual game training (active control, AC, n = 64). RESULTS After 10 weeks of training, CT participants showed greater improvements in the overall cognitive composite score (Cohen's d = 0.66, p < .01) with nonsignificant benefits after 6 months from the completion of training (Cohen's d = 0.36, p = .094). The CT group showed significant maintenance of the caudate volume as well as significant maintained fractional anisotropy in the left internal capsule and in left superior longitudinal fasciculus compared to the AC group. The AC group displayed an age-related decrease in these metrics of brain structure. DISCUSSION Results from this multisite clinical trial demonstrate that the CT intervention improves cognitive performance and helps maintain caudate volume and integrity of white matter regions that are associated with cognitive control, adding to our understanding of the changes in brain structure contributing to changes in cognitive performance from adaptive CT. CLINICAL TRIAL REGISTRATION NCT03197454.
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Affiliation(s)
- Hyun Kyu Lee
- Department of Research and Development, Posit Science Corporation, San Francisco, California, USA
| | | | - Sarah-Jane Grant
- Department of Research and Development, Posit Science Corporation, San Francisco, California, USA
| | - Nicholas R Ray
- Department of Psychology, University of Texas at Dallas, Dallas, Texas, USA
| | | | - Chris Oehler
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, Iowa, USA
| | - Shuo Qin
- Department of Psychology, University of Texas at Dallas, Dallas, Texas, USA
| | - Andrew Sun
- Department of Psychology, University of Texas at Dallas, Dallas, Texas, USA
| | - Evan T Smith
- Department of Psychology, University of Texas at Dallas, Dallas, Texas, USA
| | - G Hulon Sherard
- Department of Psychology, University of Texas at Dallas, Dallas, Texas, USA
| | | | - Mike Merzenich
- Department of Research and Development, Posit Science Corporation, San Francisco, California, USA
| | - Michelle W Voss
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, Iowa, USA
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8
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Musich M, Beversdorf DQ, McCrae CS, Curtis AF. Subjective-Objective Sleep Discrepancy in a Predominately White and Educated Older Adult Population: Examining the Associations With Cognition and Insomnia. J Gerontol B Psychol Sci Soc Sci 2024; 79:gbae074. [PMID: 38679960 DOI: 10.1093/geronb/gbae074] [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: 10/31/2023] [Indexed: 05/01/2024] Open
Abstract
OBJECTIVES This study examined associations between various cognitive domains and sleep discrepancy (self-reported vs objectively measured sleep), and evaluated interactive associations with insomnia status (non-insomnia vs insomnia). METHODS Older adults (N = 65, Mage = 68.72, SD = 5.06, 43 insomnia/22 non-insomnia) aged 60+ reported subjective sleep (7 days of sleep diaries), objective sleep assessment (one-night polysomnography, PSG, via Sleep Profiler during the 7-day period), and completed cognitive tasks (National Institutes of Health Toolbox-Cognition Battery) measuring attention and processing speed, working memory, inhibitory control, cognitive flexibility, and episodic memory. The sleep diary variable corresponding to the same one night of PSG was used to calculate the sleep discrepancy (diary minus PSG parameter) variables for total sleep time (TST), sleep onset latency, wake after sleep onset, and sleep efficiency. Regression analyses determined independent and interactive (with insomnia status) associations between cognition and sleep discrepancy, controlling for age, sex, apnea-hypopnea index, and sleep medication usage. RESULTS Working memory interacted with insomnia status in associations with sleep discrepancy related to TST and sleep efficiency. In those with insomnia, worse working memory was associated with shorter self-reported TST (p = .008) and lower sleep efficiency (p = .04) than PSG measured. DISCUSSION In older adults with insomnia, worse working memory may be a contributing factor to sleep discrepancy. Future investigations of underlying neurophysiological factors and consideration of other objective sleep measures (actigraphy) are warranted. Prospective findings may help determine whether sleep discrepancy is a potential marker of future cognitive decline.
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Affiliation(s)
- Madison Musich
- Department of Psychological Sciences, University of Missouri-Columbia, Columbia, Missouri, USA
| | - David Q Beversdorf
- Department of Psychological Sciences, University of Missouri-Columbia, Columbia, Missouri, USA
- Departments of Radiology and Neurology, University of Missouri-Columbia, Columbia, Missouri, USA
| | | | - Ashley F Curtis
- College of Nursing, University of South Florida, Tampa, Florida, USA
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9
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Burmistrov DE, Gudkov SV, Franceschi C, Vedunova MV. Sex as a Determinant of Age-Related Changes in the Brain. Int J Mol Sci 2024; 25:7122. [PMID: 39000227 PMCID: PMC11241365 DOI: 10.3390/ijms25137122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2024] [Revised: 06/25/2024] [Accepted: 06/26/2024] [Indexed: 07/16/2024] Open
Abstract
The notion of notable anatomical, biochemical, and behavioral distinctions within male and female brains has been a contentious topic of interest within the scientific community over several decades. Advancements in neuroimaging and molecular biological techniques have increasingly elucidated common mechanisms characterizing brain aging while also revealing disparities between sexes in these processes. Variations in cognitive functions; susceptibility to and progression of neurodegenerative conditions, notably Alzheimer's and Parkinson's diseases; and notable disparities in life expectancy between sexes, underscore the significance of evaluating aging within the framework of gender differences. This comprehensive review surveys contemporary literature on the restructuring of brain structures and fundamental processes unfolding in the aging brain at cellular and molecular levels, with a focus on gender distinctions. Additionally, the review delves into age-related cognitive alterations, exploring factors influencing the acceleration or deceleration of aging, with particular attention to estrogen's hormonal support of the central nervous system.
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Affiliation(s)
- Dmitriy E. Burmistrov
- Prokhorov General Physics Institute of the Russian Academy of Sciences, 38 Vavilova St., 119991 Moscow, Russia;
| | - Sergey V. Gudkov
- Prokhorov General Physics Institute of the Russian Academy of Sciences, 38 Vavilova St., 119991 Moscow, Russia;
- Institute of Biology and Biomedicine, Lobachevsky State University of Nizhny Novgorod, 23 Gagarin Ave., 603022 Nizhny Novgorod, Russia
| | - Claudio Franceschi
- Institute of Biology and Biomedicine, Lobachevsky State University of Nizhny Novgorod, 23 Gagarin Ave., 603022 Nizhny Novgorod, Russia
| | - Maria V. Vedunova
- Institute of Biology and Biomedicine, Lobachevsky State University of Nizhny Novgorod, 23 Gagarin Ave., 603022 Nizhny Novgorod, Russia
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10
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Duan H, Shi R, Kang J, Banaschewski T, Bokde ALW, Büchel C, Desrivières S, Flor H, Grigis A, Garavan H, Gowland PA, Heinz A, Brühl R, Martinot JL, Martinot MLP, Artiges E, Nees F, Papadopoulos Orfanos D, Poustka L, Hohmann S, Holz N, Fröhner JH, Smolka MN, Vaidya N, Walter H, Whelan R, Schumann G, Lin X, Feng J. Population clustering of structural brain aging and its association with brain development. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.01.09.24301030. [PMID: 38260410 PMCID: PMC10802651 DOI: 10.1101/2024.01.09.24301030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Structural brain aging has demonstrated strong inter-individual heterogeneity and mirroring patterns with brain development. However, due to the lack of large-scale longitudinal neuroimaging studies, most of the existing research focused on the cross-sectional changes of brain aging. In this investigation, we present a data-driven approach that incorporate both cross-sectional changes and longitudinal trajectories of structural brain aging and identified two brain aging patterns among 37,013 healthy participants from UK Biobank. Participants with accelerated brain aging also demonstrated accelerated biological aging, cognitive decline and increased genetic susceptibilities to major neuropsychiatric disorders. Further, by integrating longitudinal neuroimaging studies from a multi-center adolescent cohort, we validated the "last in, first out" mirroring hypothesis and identified brain regions with manifested mirroring patterns between brain aging and brain development. Genomic analyses revealed risk loci and genes contributing to accelerated brain aging and delayed brain development, providing molecular basis for elucidating the biological mechanisms underlying brain aging and related disorders.
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Affiliation(s)
- Haojing Duan
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
| | - Runye Shi
- School of Data Science, Fudan University, Shanghai, China
| | - Jujiao Kang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | | | - Sylvane Desrivières
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Herta Flor
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
- Department of Psychology, School of Social Sciences, University of Mannheim, 68131 Mannheim, Germany
| | - Antoine Grigis
- NeuroSpin, CEA, Université Paris-Saclay, F-91191 Gif-sur-Yvette, France
| | - Hugh Garavan
- Departments of Psychiatry and Psychology, University of Vermont, 05405 Burlington, Vermont, USA
| | - Penny A Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, United Kingdom
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Rüdiger Brühl
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U1299 "Developmental Trajectories and Psychiatry", Université Paris-Saclay, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli, Gif-sur-Yvette, France
- Psychiatry Department, EPS Barthélémy Durand, Etampes; France
| | - Marie-Laure Paillère Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U1299 "Developmental Trajectories and Psychiatry", Université Paris-Saclay, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli, Gif-sur-Yvette, France
- AP-HP. Sorbonne Université, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Paris, France
| | - Eric Artiges
- Institut National de la Santé et de la Recherche Médicale, INSERM U1299 "Developmental Trajectories and Psychiatry", Université Paris-Saclay, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli, Gif-sur-Yvette, France
- Psychiatry Department, EPS Barthélémy Durand, Etampes; France
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
- Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig-Holstein Kiel University, Kiel, Germany
| | | | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, von-Siebold-Str. 5, 37075, Göttingen, Germany
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Nathalie Holz
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Juliane H Fröhner
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Michael N Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Nilakshi Vaidya
- Department of Psychiatry and Neurosciences, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität BerlinHumboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Ireland
| | - Gunter Schumann
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Department of Psychiatry and Neurosciences, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität BerlinHumboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- Centre for Population Neuroscience and Stratified Medicine (PONS Centre), ISTBI, Fudan University, Shanghai, China
- Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin Berlin, Germany
| | - Xiaolei Lin
- School of Data Science, Fudan University, Shanghai, China
- Huashan Institute of Medicine, Huashan Hospital affiliated to Fudan University, Shanghai, China
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
- School of Data Science, Fudan University, Shanghai, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- Zhangjiang Fudan International Innovation Center, Shanghai, China
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK
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11
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Jansen MG, Zwiers MP, Marques JP, Chan KS, Amelink JS, Altgassen M, Oosterman JM, Norris DG. The Advanced BRain Imaging on ageing and Memory (ABRIM) data collection: Study design, data processing, and rationale. PLoS One 2024; 19:e0306006. [PMID: 38905233 PMCID: PMC11192316 DOI: 10.1371/journal.pone.0306006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Accepted: 06/07/2024] [Indexed: 06/23/2024] Open
Abstract
To understand the neurocognitive mechanisms that underlie heterogeneity in cognitive ageing, recent scientific efforts have led to a growing public availability of imaging cohort data. The Advanced BRain Imaging on ageing and Memory (ABRIM) project aims to add to these existing datasets by taking an adult lifespan approach to provide a cross-sectional, normative database with a particular focus on connectivity, myelinization and iron content of the brain in concurrence with cognitive functioning, mechanisms of reserve, and sleep-wake rhythms. ABRIM freely shares MRI and behavioural data from 295 participants between 18-80 years, stratified by age decade and sex (median age 52, IQR 36-66, 53.20% females). The ABRIM MRI collection consists of both the raw and pre-processed structural and functional MRI data to facilitate data usage among both expert and non-expert users. The ABRIM behavioural collection includes measures of cognitive functioning (i.e., global cognition, processing speed, executive functions, and memory), proxy measures of cognitive reserve (e.g., educational attainment, verbal intelligence, and occupational complexity), and various self-reported questionnaires (e.g., on depressive symptoms, pain, and the use of memory strategies in daily life and during a memory task). In a sub-sample (n = 120), we recorded sleep-wake rhythms using an actigraphy device (Actiwatch 2, Philips Respironics) for a period of 7 consecutive days. Here, we provide an in-depth description of our study protocol, pre-processing pipelines, and data availability. ABRIM provides a cross-sectional database on healthy participants throughout the adult lifespan, including numerous parameters relevant to improve our understanding of cognitive ageing. Therefore, ABRIM enables researchers to model the advanced imaging parameters and cognitive topologies as a function of age, identify the normal range of values of such parameters, and to further investigate the diverse mechanisms of reserve and resilience.
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Affiliation(s)
- Michelle G. Jansen
- Donders Centre for Cognition, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Marcel P. Zwiers
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Jose P. Marques
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Kwok-Shing Chan
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Jitse S. Amelink
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Radboud University, Nijmegen, the Netherlands
| | - Mareike Altgassen
- Department of Psychology, Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Joukje M. Oosterman
- Donders Centre for Cognition, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - David G. Norris
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
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12
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Pang Y, Cai Y, Xia Z, Gao X. Predicting brain age using Tri-UNet and various MRI scale features. Sci Rep 2024; 14:13742. [PMID: 38877107 PMCID: PMC11178849 DOI: 10.1038/s41598-024-63998-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Accepted: 06/04/2024] [Indexed: 06/16/2024] Open
Abstract
In the process of human aging, significant age-related changes occur in brain tissue. To assist individuals in assessing the degree of brain aging, screening for disease risks, and further diagnosing age-related diseases, it is crucial to develop an accurate method for predicting brain age. This paper proposes a multi-scale feature fusion method called Tri-UNet based on the U-Net network structure, as well as a brain region information fusion method based on multi-channel input networks. These methods address the issue of insufficient image feature learning in brain neuroimaging data. They can effectively utilize features at different scales of MRI and fully leverage feature information from different regions of the brain. In the end, experiments were conducted on the Cam-CAN dataset, resulting in a minimum Mean Absolute Error (MAE) of 7.46. The results demonstrate that this method provides a new approach to feature learning at different scales in brain age prediction tasks, contributing to the advancement of the field and holding significance for practical applications in the context of elderly education.
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Affiliation(s)
- Yu Pang
- School of Science, Jilin Institute of Chemical Technology, Jilin, 130000, China.
| | - Yihuai Cai
- School of Science, Jilin Institute of Chemical Technology, Jilin, 130000, China.
| | - Zonghui Xia
- Faculty of Artificial Intelligence in Education, Central China Normal University, Wuhan, 430079, China
| | - Xujie Gao
- School of Information Science and Technology, Beijing Forestry University, Beijing, 100083, China
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13
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Gaynor AM, Gazes Y, Haynes CR, Babukutty RS, Habeck C, Stern Y, Gu Y. Childhood engagement in cognitively stimulating activities moderates relationships between brain structure and cognitive function in adulthood. Neurobiol Aging 2024; 138:36-44. [PMID: 38522385 DOI: 10.1016/j.neurobiolaging.2024.02.010] [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: 06/30/2023] [Revised: 02/16/2024] [Accepted: 02/21/2024] [Indexed: 03/26/2024]
Abstract
Greater engagement in cognitively stimulating activities (CSA) during adulthood has been shown to protect against neurocognitive decline, but no studies have investigated whether CSA during childhood protects against effects of brain changes on cognition later in life. The current study tested the moderating role of childhood CSA in the relationships between brain structure and cognitive performance during adulthood. At baseline (N=250) and 5-year follow-up (N=204) healthy adults aged 20-80 underwent MRI to assess four structural brain measures and completed neuropsychological tests to measure three cognitive domains. Participants were categorized into low and high childhood CSA based on self-report questionnaires. Results of multivariable linear regressions analyzing interactions between CSA, brain structure, and cognition showed that higher childhood CSA was associated with a weaker relationship between cortical thickness and memory at baseline, and attenuated the effects of change in cortical thickness and brain volume on decline in processing speed over time. These findings suggest higher CSA during childhood may mitigate the effects of brain structure changes on cognitive function later in life.
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Affiliation(s)
- Alexandra M Gaynor
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, NY, United States; Cognitive Neuroscience Division, Department of Neurology, Columbia University, New York, NY, United States; Montclair State University, Department of Psychology, Montclair, NJ, United States
| | - Yunglin Gazes
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, NY, United States; Cognitive Neuroscience Division, Department of Neurology, Columbia University, New York, NY, United States; Gertrude H. Sergievsky Center, Columbia University, New York, NY, United States
| | - Caleb R Haynes
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, NY, United States; Cognitive Neuroscience Division, Department of Neurology, Columbia University, New York, NY, United States
| | - Reshma S Babukutty
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, NY, United States; Cognitive Neuroscience Division, Department of Neurology, Columbia University, New York, NY, United States
| | - Christian Habeck
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, NY, United States; Cognitive Neuroscience Division, Department of Neurology, Columbia University, New York, NY, United States; Gertrude H. Sergievsky Center, Columbia University, New York, NY, United States
| | - Yaakov Stern
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, NY, United States; Cognitive Neuroscience Division, Department of Neurology, Columbia University, New York, NY, United States; Gertrude H. Sergievsky Center, Columbia University, New York, NY, United States; Department of Psychiatry, Columbia University, New York, NY, United States
| | - Yian Gu
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, NY, United States; Cognitive Neuroscience Division, Department of Neurology, Columbia University, New York, NY, United States; Gertrude H. Sergievsky Center, Columbia University, New York, NY, United States; Department of Epidemiology, Joseph P. Mailman School of Public Health, Columbia University, New York, NY, United States.
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14
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Fjell AM. Aging Brain from a Lifespan Perspective. Curr Top Behav Neurosci 2024. [PMID: 38797799 DOI: 10.1007/7854_2024_476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Research during the last two decades has shown that the brain undergoes continuous changes throughout life, with substantial heterogeneity in age trajectories between regions. Especially, temporal and prefrontal cortices show large changes, and these correlate modestly with changes in the corresponding cognitive abilities such as episodic memory and executive function. Changes seen in normal aging overlap with changes seen in neurodegenerative conditions such as Alzheimer's disease; differences between what reflects normal aging vs. a disease-related change are often blurry. This calls for a dimensional view on cognitive decline in aging, where clear-cut distinctions between normality and pathology cannot be always drawn. Although much progress has been made in describing typical patterns of age-related changes in the brain, identifying risk and protective factors, and mapping cognitive correlates, there are still limits to our knowledge that should be addressed by future research. We need more longitudinal studies following the same participants over longer time intervals with cognitive testing and brain imaging, and an increased focus on the representativeness vs. selection bias in neuroimaging research of aging.
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Affiliation(s)
- Anders Martin Fjell
- Department of Psychology, Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway.
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15
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Zahr NM. Alcohol Use Disorder and Dementia: A Review. Alcohol Res 2024; 44:03. [PMID: 38812709 PMCID: PMC11135165 DOI: 10.35946/arcr.v44.1.03] [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] [Indexed: 05/31/2024] Open
Abstract
PURPOSE By 2040, 21.6% of Americans will be over age 65, and the population of those older than age 85 is estimated to reach 14.4 million. Although not causative, older age is a risk factor for dementia: every 5 years beyond age 65, the risk doubles; approximately one-third of those older than age 85 are diagnosed with dementia. As current alcohol consumption among older adults is significantly higher compared to previous generations, a pressing question is whether drinking alcohol increases the risk for Alzheimer's disease or other forms of dementia. SEARCH METHODS Databases explored included PubMed, Web of Science, and ScienceDirect. To accomplish this narrative review on the effects of alcohol consumption on dementia risk, the literature covered included clinical diagnoses, epidemiology, neuropsychology, postmortem pathology, neuroimaging and other biomarkers, and translational studies. Searches conducted between January 12 and August 1, 2023, included the following terms and combinations: "aging," "alcoholism," "alcohol use disorder (AUD)," "brain," "CNS," "dementia," "Wernicke," "Korsakoff," "Alzheimer," "vascular," "frontotemporal," "Lewy body," "clinical," "diagnosis," "epidemiology," "pathology," "autopsy," "postmortem," "histology," "cognitive," "motor," "neuropsychological," "magnetic resonance," "imaging," "PET," "ligand," "degeneration," "atrophy," "translational," "rodent," "rat," "mouse," "model," "amyloid," "neurofibrillary tangles," "α-synuclein," or "presenilin." When relevant, "species" (i.e., "humans" or "other animals") was selected as an additional filter. Review articles were avoided when possible. SEARCH RESULTS The two terms "alcoholism" and "aging" retrieved about 1,350 papers; adding phrases-for example, "postmortem" or "magnetic resonance"-limited the number to fewer than 100 papers. Using the traditional term, "alcoholism" with "dementia" resulted in 876 citations, but using the currently accepted term "alcohol use disorder (AUD)" with "dementia" produced only 87 papers. Similarly, whereas the terms "Alzheimer's" and "alcoholism" yielded 318 results, "Alzheimer's" and "alcohol use disorder (AUD)" returned only 40 citations. As pertinent postmortem pathology papers were published in the 1950s and recent animal models of Alzheimer's disease were created in the early 2000s, articles referenced span the years 1957 to 2024. In total, more than 5,000 articles were considered; about 400 are herein referenced. DISCUSSION AND CONCLUSIONS Chronic alcohol misuse accelerates brain aging and contributes to cognitive impairments, including those in the mnemonic domain. The consensus among studies from multiple disciplines, however, is that alcohol misuse can increase the risk for dementia, but not necessarily Alzheimer's disease. Key issues to consider include the reversibility of brain damage following abstinence from chronic alcohol misuse compared to the degenerative and progressive course of Alzheimer's disease, and the characteristic presence of protein inclusions in the brains of people with Alzheimer's disease, which are absent in the brains of those with AUD.
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Affiliation(s)
- Natalie M Zahr
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California. Center for Health Sciences, SRI International, Menlo Park, California
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16
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Shimada R, Kibayashi K. Trends in mortality rates and correlations between intracranial injuries and external causes: A Japanese population study. PLoS One 2024; 19:e0300846. [PMID: 38718046 PMCID: PMC11078349 DOI: 10.1371/journal.pone.0300846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 03/05/2024] [Indexed: 05/12/2024] Open
Abstract
The age-standardized incidence of head trauma in 2016 was 369 per 100,000 people worldwide. The Western Pacific region, including Japan, had the highest incidence. This study aimed to extract ICD-10 code data for intracranial injury (S06) and external causes of morbidity and mortality (V01-Y89), analyze their characteristics and interrelationships, and contribute to these diseases' prevention, treatment, and prognosis. The number of deaths according to injury type and external cause type of intracranial injury published by the Japanese government was statistically analyzed using JoinPoint, and univariate distribution and multivariate correlation were conducted using JMP Software. From 1999-2021, there was a downward trend in the number of deaths because of intracranial injuries: mortality from intracranial injuries was higher among those aged ≥65 years. Conversely, mortality from intracranial injuries was lower among those aged ≤14 years. Among deaths from intracranial injury, mortality from diffuse brain injury and traumatic subdural hemorrhage was more common. Among deaths from external causes of intracranial injury, mortality from falls, transport accidents, and other unforeseen accidents was more common. Mortality because of intracranial injuries increased significantly during the 2011 Great East Japan Earthquake. For some age groups and sexes, there were significant inverse correlations of mortality with traumatic subdural hemorrhage and traumatic subarachnoid hemorrhage for transport accidents, intentional self-harm and assault, and diffuse brain injury and focal brain injury for falls. We believe that the data presented in this study will be useful for preventing and treating intracranial injuries and for developing administrative measures to reduce intracranial injuries.
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Affiliation(s)
- Ryo Shimada
- Department of Forensic Medicine, School of Medicine, Tokyo Women’s Medical University, Tokyo, Japan
| | - Kazuhiko Kibayashi
- Department of Forensic Medicine, School of Medicine, Tokyo Women’s Medical University, Tokyo, Japan
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17
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Cui F, Li H, Cao Y, Wang W, Zhang D. The Association between Dietary Protein Intake and Sources and the Rate of Longitudinal Changes in Brain Structure. Nutrients 2024; 16:1284. [PMID: 38732531 PMCID: PMC11085529 DOI: 10.3390/nu16091284] [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: 03/21/2024] [Revised: 04/24/2024] [Accepted: 04/24/2024] [Indexed: 05/13/2024] Open
Abstract
Few studies have examined dietary protein intake and sources, in combination with longitudinal changes in brain structure markers. Our study aimed to examine the association between dietary protein intake and different sources of dietary protein, with the longitudinal rate of change in brain structural markers. A total of 2723 and 2679 participants from the UK Biobank were separately included in the analysis. The relative and absolute amounts of dietary protein intake were calculated using a 24 h dietary recall questionnaire. The longitudinal change rates of brain structural biomarkers were computed using two waves of brain imaging data. The average interval between the assessments was three years. We utilized multiple linear regression to examine the association between dietary protein and different sources and the longitudinal changes in brain structural biomarkers. Restrictive cubic splines were used to explore nonlinear relationships, and stratified and sensitivity analyses were conducted. Increasing the proportion of animal protein in dietary protein intake was associated with a slower reduction in the total hippocampus volume (THV, β: 0.02524, p < 0.05), left hippocampus volume (LHV, β: 0.02435, p < 0.01) and right hippocampus volume (RHV, β: 0.02544, p < 0.05). A higher intake of animal protein relative to plant protein was linked to a lower atrophy rate in the THV (β: 0.01249, p < 0.05) and LHV (β: 0.01173, p < 0.05) and RHV (β: 0.01193, p < 0.05). Individuals with a higher intake of seafood exhibited a higher longitudinal rate of change in the HV compared to those that did not consume seafood (THV, β: 0.004514; p < 0.05; RHV, β: 0.005527, p < 0.05). In the subgroup and sensitivity analyses, there were no significant alterations. A moderate increase in an individual's intake and the proportion of animal protein in their diet, especially from seafood, is associated with a lower atrophy rate in the hippocampus volume.
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Affiliation(s)
- Fusheng Cui
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao 266021, China; (F.C.); (H.L.); (D.Z.)
| | - Huihui Li
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao 266021, China; (F.C.); (H.L.); (D.Z.)
| | - Yi Cao
- Biomedical Center, Qingdao University, Qingdao 266021, China
| | - Weijing Wang
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao 266021, China; (F.C.); (H.L.); (D.Z.)
| | - Dongfeng Zhang
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao 266021, China; (F.C.); (H.L.); (D.Z.)
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18
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Kang P, Wang AZX. Microbiota-gut-brain axis: the mediator of exercise and brain health. PSYCHORADIOLOGY 2024; 4:kkae007. [PMID: 38756477 PMCID: PMC11096970 DOI: 10.1093/psyrad/kkae007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 04/04/2024] [Accepted: 04/16/2024] [Indexed: 05/18/2024]
Abstract
The brain controls the nerve system, allowing complex emotional and cognitive activities. The microbiota-gut-brain axis is a bidirectional neural, hormonal, and immune signaling pathway that could link the gastrointestinal tract to the brain. Over the past few decades, gut microbiota has been demonstrated to be an essential component of the gastrointestinal tract that plays a crucial role in regulating most functions of various body organs. The effects of the microbiota on the brain occur through the production of neurotransmitters, hormones, and metabolites, regulation of host-produced metabolites, or through the synthesis of metabolites by the microbiota themselves. This affects the host's behavior, mood, attention state, and the brain's food reward system. Meanwhile, there is an intimate association between the gut microbiota and exercise. Exercise can change gut microbiota numerically and qualitatively, which may be partially responsible for the widespread benefits of regular physical activity on human health. Functional magnetic resonance imaging (fMRI) is a non-invasive method to show areas of brain activity enabling the delineation of specific brain regions involved in neurocognitive disorders. Through combining exercise tasks and fMRI techniques, researchers can observe the effects of exercise on higher brain functions. However, exercise's effects on brain health via gut microbiota have been little studied. This article reviews and highlights the connections between these three interactions, which will help us to further understand the positive effects of exercise on brain health and provide new strategies and approaches for the prevention and treatment of brain diseases.
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Affiliation(s)
- Piao Kang
- Department of Endocrinology and Metabolism, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
- Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
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19
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Zając-Lamparska L, Zabielska-Mendyk E, Zapała D, Augustynowicz P. Compensatory brain activity pattern is not present in older adults during the n-back task performance-Findings based on EEG frequency analysis. Front Psychol 2024; 15:1371035. [PMID: 38666231 PMCID: PMC11043891 DOI: 10.3389/fpsyg.2024.1371035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Accepted: 03/15/2024] [Indexed: 04/28/2024] Open
Abstract
Introduction Cognitive ability is one of the most important enablers for successful aging. At the same time, cognitive decline is a well-documented phenomenon accompanying the aging process. Nevertheless, it is acknowledged that aging can also be related to positive processes that allow one to compensate for the decline. These processes include the compensatory brain activity of older adults primarily investigated using fMRI and PET. To strengthen the cognitive interpretation of compensatory brain activity in older adults, we searched for its indicators in brain activity measured by EEG. Methods The study sample comprised 110 volunteers, including 50 older adults (60-75 years old) and 60 young adults (20-35 years old) who performed 1-back, 2-back, and 3-back tasks while recording the EEG signal. The study analyzed (1) the level of cognitive performance, including sensitivity index, the percentage of correct answers to the target, and the percentage of false alarm errors; (2) theta and alpha power for electrodes located in the frontal-midline (Fz, AF3, AF4, F3, F4, FC1, and FC2) and the centro-parietal (CP1, CP2, P3, P4, and Pz) areas. Results Cognitive performance was worse in older adults than in young adults, which manifested in a significantly lower sensitivity index and a significantly higher false alarm error rate at all levels of the n-back task difficulty. Simultaneously, performance worsened with increasing task difficulty regardless of age. Significantly lower theta power in the older participants was observed at all difficulty levels, even at the lowest one, where compensatory activity was expected. At the same time, at this difficulty level, cognitive performance was worse in older adults than in young adults, which could reduce the chances of observing compensatory brain activity. The significant decrease in theta power observed in both age groups with rising task difficulty can reflect a declining capacity for efficient cognitive functioning under increasing demands rather than adapting to this increase. Moreover, in young adults, alpha power decreased to some extent with increasing cognitive demand, reflecting adaptation to them, while in older adults, no analogous pattern was observed. Discussion In conclusion, based on the results of the current study, the presence of compensatory activity in older adults cannot be inferred.
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Affiliation(s)
- Ludmiła Zając-Lamparska
- Department of General and Human Development Psychology, Faculty of Psychology, Kazimierz Wielki University, Bydgoszcz, Poland
| | - Emilia Zabielska-Mendyk
- Department of Experimental Psychology, Institute of Psychology, The John Paul II Catholic University of Lublin, Lublin, Poland
| | - Dariusz Zapała
- Department of Experimental Psychology, Institute of Psychology, The John Paul II Catholic University of Lublin, Lublin, Poland
| | - Paweł Augustynowicz
- Department of Experimental Psychology, Institute of Psychology, The John Paul II Catholic University of Lublin, Lublin, Poland
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20
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Lin CL, Lane HY, Sun CK, Chen MH, Lee CY, Li L, Lee JJ, Yeh PY. Effects of chronic daily headache with subclinical depression on brain volume: A systematic review and meta-analysis. Eur J Pain 2024. [PMID: 38563383 DOI: 10.1002/ejp.2270] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 03/13/2024] [Accepted: 03/18/2024] [Indexed: 04/04/2024]
Abstract
BACKGROUND AND OBJECTIVE The relationship between chronic daily headache (CDH), depression symptoms, and brain volume remains unclear. METHODS To investigate the effects of CDH on brain volume and the impact of depressive symptoms (DSs) as well as the effects of demography and medication overuse, PubMed, Embase, and Web of Science databases were systematically searched using appropriate keyword strings to retrieve observational studies from inception to May 2023. RESULTS Two distinct comparisons were made in CDH patients: (1) those with DSs versus their pain-free counterparts and (2) those without DSs versus pain-free controls. The first comprised nine studies enrolling 225 CDH patients with DSs and 234 controls. Beck depression inventory, Hamilton depression scale, and Hospital anxiety/depression scale were used to assess DSs, revealing significantly more DSs in CDH patients with DSs compared to their controls (all p < 0.05). Besides, the second analysed four studies involving 117 CDH patients without DSs and 155 comparators. Compared to CDH patients without DSs, those with DSs had a smaller brain volume than controls (p = 0.03). Furthermore, CDH patients with DSs who did not overuse medications showed a smaller right cerebral cortical volume than overusers (p = 0.003). A significant inverse correlation between female prevalence and brain volume (p = 0.02) was revealed using regression analysis. CONCLUSIONS Pain-induced persistent depressive symptoms not only incur structural alterations but also encompass affective-motivational changes, involving medication use and gender-specific health concerns. SIGNIFICANCE This study highlighted the importance of an integrated CDH treatment, emphasizing psychological interventions for the affective-motivational component alongside pain management.
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Affiliation(s)
- Chih-Lung Lin
- Department of Neurosurgery, Asia University Hospital, Taichung, Taiwan
- Department of Occupational Therapy, College of Medical and Health Science, Asia University, Taichung, Taiwan
| | - Hsien-Yuan Lane
- Graduate Institute of Biomedical Sciences, China Medical University, Taichung, Taiwan
- Department of Psychiatry and Brain Disease Research Center, China Medical University Hospital, Taichung, Taiwan
- Department of Psychology, College of Medical and Health Science, Asia University, Taichung, Taiwan
| | - Cheuk-Kwan Sun
- Department of Emergency Medicine, E-Da Dachang Hospital, I-Shou University, Kaohsiung City, Taiwan
- School of Medicine for International Students, College of Medicine, I-Shou University, Kaohsiung City, Taiwan
| | - Meng-Hsiang Chen
- Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
- Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Chiao-Yu Lee
- Department of Psychology, College of Medical and Health Science, Asia University, Taichung, Taiwan
| | - Lin Li
- Department of Psychology, College of Medical and Health Science, Asia University, Taichung, Taiwan
| | - Jia-Jie Lee
- Department of Psychology, College of Medical and Health Science, Asia University, Taichung, Taiwan
| | - Pin-Yang Yeh
- Department of Psychology, College of Medical and Health Science, Asia University, Taichung, Taiwan
- Clinical Psychology Center, Asia University Hospital, Taichung, Taiwan
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21
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Bongratz F, Rickmann AM, Wachinger C. Neural deformation fields for template-based reconstruction of cortical surfaces from MRI. Med Image Anal 2024; 93:103093. [PMID: 38281362 DOI: 10.1016/j.media.2024.103093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 12/19/2023] [Accepted: 01/22/2024] [Indexed: 01/30/2024]
Abstract
The reconstruction of cortical surfaces is a prerequisite for quantitative analyses of the cerebral cortex in magnetic resonance imaging (MRI). Existing segmentation-based methods separate the surface registration from the surface extraction, which is computationally inefficient and prone to distortions. We introduce Vox2Cortex-Flow (V2C-Flow), a deep mesh-deformation technique that learns a deformation field from a brain template to the cortical surfaces of an MRI scan. To this end, we present a geometric neural network that models the deformation-describing ordinary differential equation in a continuous manner. The network architecture comprises convolutional and graph-convolutional layers, which allows it to work with images and meshes at the same time. V2C-Flow is not only very fast, requiring less than two seconds to infer all four cortical surfaces, but also establishes vertex-wise correspondences to the template during reconstruction. In addition, V2C-Flow is the first approach for cortex reconstruction that models white matter and pial surfaces jointly, therefore avoiding intersections between them. Our comprehensive experiments on internal and external test data demonstrate that V2C-Flow results in cortical surfaces that are state-of-the-art in terms of accuracy. Moreover, we show that the established correspondences are more consistent than in FreeSurfer and that they can directly be utilized for cortex parcellation and group analyses of cortical thickness.
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Affiliation(s)
- Fabian Bongratz
- Laboratory for Artificial Intelligence in Medical Imaging, Department of Radiology, Technical University of Munich, Munich 81675, Germany; Munich Center for Machine Learning, Munich, Germany.
| | - Anne-Marie Rickmann
- Laboratory for Artificial Intelligence in Medical Imaging, Department of Radiology, Technical University of Munich, Munich 81675, Germany; Department of Child and Adolescent Psychiatry, Ludwig-Maximilians-University, Munich 80336, Germany
| | - Christian Wachinger
- Laboratory for Artificial Intelligence in Medical Imaging, Department of Radiology, Technical University of Munich, Munich 81675, Germany; Department of Child and Adolescent Psychiatry, Ludwig-Maximilians-University, Munich 80336, Germany; Munich Center for Machine Learning, Munich, Germany
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22
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Capogna E, Sørensen Ø, Watne LO, Roe J, Strømstad M, Idland AV, Halaas NB, Blennow K, Zetterberg H, Walhovd KB, Fjell AM, Vidal-Piñeiro D. Subtypes of brain change in aging and their associations with cognition and Alzheimer's disease biomarkers. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.04.583291. [PMID: 38496633 PMCID: PMC10942348 DOI: 10.1101/2024.03.04.583291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Structural brain changes underly cognitive changes in older age and contribute to inter-individual variability in cognition. Here, we assessed how changes in cortical thickness, surface area, and subcortical volume, are related to cognitive change in cognitively unimpaired older adults using structural magnetic resonance imaging (MRI) data-driven clustering. Specifically, we tested (1) which brain structural changes over time predict cognitive change in older age (2) whether these are associated with core cerebrospinal fluid (CSF) Alzheimer's disease (AD) biomarkers phosphorylated tau (p-tau) and amyloid-β (Aβ42), and (3) the degree of overlap between clusters derived from different structural features. In total 1899 cognitively healthy older adults (50 - 93 years) were followed up to 16 years with neuropsychological and structural MRI assessments, a subsample of which (n = 612) had CSF p-tau and Aβ42 measurements. We applied Monte-Carlo Reference-based Consensus clustering to identify subgroups of older adults based on structural brain change patterns over time. Four clusters for each brain feature were identified, representing the degree of longitudinal brain decline. Each brain feature provided a unique contribution to brain aging as clusters were largely independent across modalities. Cognitive change and baseline cognition were best predicted by cortical area change, whereas higher levels of p-tau and Aβ42 were associated with changes in subcortical volume. These results provide insights into the link between changes in brain morphology and cognition, which may translate to a better understanding of different aging trajectories.
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Affiliation(s)
- Elettra Capogna
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, 0373 Oslo, Norway
| | - Øystein Sørensen
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, 0373 Oslo, Norway
| | - Leiv Otto Watne
- Department of Geriatric Medicine, Akershus University Hospital, Lørenskog, Norway
- Institute of Clinical Medicine, Campus Ahus, University of Oslo, Oslo, Norway
| | - James Roe
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, 0373 Oslo, Norway
| | - Marie Strømstad
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, 0373 Oslo, Norway
| | - Ane Victoria Idland
- Oslo Delirium Research Group, Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway
| | - Nathalie Bodd Halaas
- Oslo Delirium Research Group, Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, Campus UllevÅl, University of Oslo, Oslo, Norway
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, the Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Paris Brain Institute, ICM, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
- Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine, and Department of Neurology, Institute on Aging and Brain Disorders, University of Science and Technology of China and First Affiliated Hospital of USTC, Hefei, P.R. China
| | - Henrik Zetterberg
- Institute of Neuroscience and Physiology, the Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Center for Neurodegenerative Diseases, Hong Kong, China
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Kristine Beate Walhovd
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, 0373 Oslo, Norway
- Computational Radiology and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Anders Martin Fjell
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, 0373 Oslo, Norway
- Computational Radiology and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Didac Vidal-Piñeiro
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, 0373 Oslo, Norway
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23
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Baumgartner NW, Kao SC. Size or Strength? how components of muscle relate to behavioral and neuroelectric measures of executive function independent of aerobic fitness. Brain Cogn 2024; 175:106139. [PMID: 38364518 DOI: 10.1016/j.bandc.2024.106139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2023] [Revised: 01/06/2024] [Accepted: 02/04/2024] [Indexed: 02/18/2024]
Abstract
While previous research has linked cognitive function with resistance exercise, the nuanced links between muscle strength, mass, and neuroelectric function are less understood. Therefore, this study investigated the association of muscle strength and mass with inhibitory control (IC), working memory (WM), and related neuroelectric activity. A total of 123 18-50-year-old adults completed maximal aerobic capacity and strength tests, a body composition scan, and IC and WM tasks while the N2 and P3 components of event-related potentials were recorded. Bivariate correlations revealed aerobic fitness, strength, and mass were associated with behavioral and neuroelectric outcomes. After accounting for age, sex, and aerobic fitness, strength was associated with intra-individual response time variability, accuracy, and P3 latency during WM. Muscle mass was associated with N2 latency during IC. While relationships with behavioral outcomes did not persist after controlling for the opposite muscle outcome, greater strength and mass were related to shorter P3 latency during WM and shorter N2 latency during IC, respectively. These results provide initial evidence that muscle outcomes are associated with executive function and neuroelectric processing speed, suggesting distinct contributions of strength and mass to cognition. This work highlights the significance of maintaining muscle strength and mass alongside aerobic fitness for optimal cognitive health.
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Affiliation(s)
- Nicholas W Baumgartner
- Department of Health and Kinesiology, Purdue University, West Lafayette, Indiana, United States
| | - Shih-Chun Kao
- Department of Health and Kinesiology, Purdue University, West Lafayette, Indiana, United States.
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24
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Li M, Schilling KG, Gao F, Xu L, Choi S, Gao Y, Zu Z, Anderson AW, Ding Z, Landman BA, Gore JC. Quantification of mediation effects of white matter functional characteristics on cognitive decline in aging. Cereb Cortex 2024; 34:bhae114. [PMID: 38517178 PMCID: PMC10958767 DOI: 10.1093/cercor/bhae114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 02/29/2024] [Accepted: 03/03/2024] [Indexed: 03/23/2024] Open
Abstract
Cognitive decline with aging involves multifactorial processes, including changes in brain structure and function. This study focuses on the role of white matter functional characteristics, as reflected in blood oxygenation level-dependent signals, in age-related cognitive deterioration. Building on previous research confirming the reproducibility and age-dependence of blood oxygenation level-dependent signals acquired via functional magnetic resonance imaging, we here employ mediation analysis to test if aging affects cognition through white matter blood oxygenation level-dependent signal changes, impacting various cognitive domains and specific white matter regions. We used independent component analysis of resting-state blood oxygenation level-dependent signals to segment white matter into coherent hubs, offering a data-driven view of white matter's functional architecture. Through correlation analysis, we constructed a graph network and derived metrics to quantitatively assess regional functional properties based on resting-state blood oxygenation level-dependent fluctuations. Our analysis identified significant mediators in the age-cognition relationship, indicating that aging differentially influences cognitive functions by altering the functional characteristics of distinct white matter regions. These findings enhance our understanding of the neurobiological basis of cognitive aging, highlighting the critical role of white matter in maintaining cognitive integrity and proposing new approaches to assess interventions targeting cognitive decline in older populations.
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Affiliation(s)
- Muwei Li
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, United States
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, United States
| | - Kurt G Schilling
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, United States
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, United States
| | - Fei Gao
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China
| | - Lyuan Xu
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, United States
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN 37235, United States
| | - Soyoung Choi
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, United States
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, United States
| | - Yurui Gao
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, United States
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37240, United States
| | - Zhongliang Zu
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, United States
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, United States
| | - Adam W Anderson
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, United States
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37240, United States
| | - Zhaohua Ding
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, United States
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN 37235, United States
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37240, United States
- Department of Computer Science, Vanderbilt University, Nashville, TN 37240, United States
| | - Bennett A Landman
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, United States
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, United States
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN 37235, United States
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37240, United States
- Department of Computer Science, Vanderbilt University, Nashville, TN 37240, United States
| | - John C Gore
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, United States
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, United States
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37240, United States
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25
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Shu L, Yan H, Wu Y, Yan T, Yang L, Zhang S, Chen Z, Liao Q, Yang L, Xiao B, Ye M, Lv S, Wu M, Zhu X, Hu P. Explainable machine learning in outcome prediction of high-grade aneurysmal subarachnoid hemorrhage. Aging (Albany NY) 2024; 16:4654-4669. [PMID: 38431285 PMCID: PMC10968679 DOI: 10.18632/aging.205621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 01/29/2024] [Indexed: 03/05/2024]
Abstract
OBJECTIVE Accurate prognostic prediction in patients with high-grade aneruysmal subarachnoid hemorrhage (aSAH) is essential for personalized treatment. In this study, we developed an interpretable prognostic machine learning model for high-grade aSAH patients using SHapley Additive exPlanations (SHAP). METHODS A prospective registry cohort of high-grade aSAH patients was collected in one single-center hospital. The endpoint in our study is a 12-month follow-up outcome. The dataset was divided into training and validation sets in a 7:3 ratio. Machine learning algorithms, including Logistic regression model (LR), support vector machine (SVM), random forest (RF), and extreme gradient boosting (XGBoost), were employed to develop a prognostic prediction model for high-grade aSAH. The optimal model was selected for SHAP analysis. RESULTS Among the 421 patients, 204 (48.5%) exhibited poor prognosis. The RF model demonstrated superior performance compared to LR (AUC = 0.850, 95% CI: 0.783-0.918), SVM (AUC = 0.862, 95% CI: 0.799-0.926), and XGBoost (AUC = 0.850, 95% CI: 0.783-0.917) with an AUC of 0.867 (95% CI: 0.806-0 .929). Primary prognostic features identified through SHAP analysis included higher World Federation of Neurosurgical Societies (WFNS) grade, higher modified Fisher score (mFS) and advanced age, were found to be associated with 12-month unfavorable outcome, while the treatment of coiling embolization for aSAH drove the prediction towards favorable prognosis. Additionally, the SHAP force plot visualized individual prognosis predictions. CONCLUSIONS This study demonstrated the potential of machine learning techniques in prognostic prediction for high-grade aSAH patients. The features identified through SHAP analysis enhance model interpretability and provide guidance for clinical decision-making.
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Affiliation(s)
- Lei Shu
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi, China
- Jiangxi Key Laboratory of Neurological Tumors and Cerebrovascular Diseases, Nanchang 330006, Jiangxi, China
- Jiangxi Health Commission Key Laboratory of Neurological Medicine, Nanchang 330006, Jiangxi, China
- Institute of Neuroscience, Nanchang University, Nanchang 330006, Jiangxi, China
| | - Hua Yan
- Department of Emergency, Affiliated Hospital of Panzhihua University, Panzhihua 617000, Sichuan, China
| | - Yanze Wu
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi, China
- Jiangxi Key Laboratory of Neurological Tumors and Cerebrovascular Diseases, Nanchang 330006, Jiangxi, China
- Jiangxi Health Commission Key Laboratory of Neurological Medicine, Nanchang 330006, Jiangxi, China
- Institute of Neuroscience, Nanchang University, Nanchang 330006, Jiangxi, China
| | - Tengfeng Yan
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi, China
- Jiangxi Key Laboratory of Neurological Tumors and Cerebrovascular Diseases, Nanchang 330006, Jiangxi, China
- Jiangxi Health Commission Key Laboratory of Neurological Medicine, Nanchang 330006, Jiangxi, China
- Institute of Neuroscience, Nanchang University, Nanchang 330006, Jiangxi, China
| | - Li Yang
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi, China
- Jiangxi Key Laboratory of Neurological Tumors and Cerebrovascular Diseases, Nanchang 330006, Jiangxi, China
- Jiangxi Health Commission Key Laboratory of Neurological Medicine, Nanchang 330006, Jiangxi, China
- Institute of Neuroscience, Nanchang University, Nanchang 330006, Jiangxi, China
| | - Si Zhang
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi, China
- Jiangxi Key Laboratory of Neurological Tumors and Cerebrovascular Diseases, Nanchang 330006, Jiangxi, China
- Jiangxi Health Commission Key Laboratory of Neurological Medicine, Nanchang 330006, Jiangxi, China
- Institute of Neuroscience, Nanchang University, Nanchang 330006, Jiangxi, China
| | - Zhihao Chen
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi, China
- Jiangxi Key Laboratory of Neurological Tumors and Cerebrovascular Diseases, Nanchang 330006, Jiangxi, China
- Jiangxi Health Commission Key Laboratory of Neurological Medicine, Nanchang 330006, Jiangxi, China
- Institute of Neuroscience, Nanchang University, Nanchang 330006, Jiangxi, China
| | - Qiuye Liao
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi, China
- Jiangxi Key Laboratory of Neurological Tumors and Cerebrovascular Diseases, Nanchang 330006, Jiangxi, China
- Jiangxi Health Commission Key Laboratory of Neurological Medicine, Nanchang 330006, Jiangxi, China
- Institute of Neuroscience, Nanchang University, Nanchang 330006, Jiangxi, China
| | - Lu Yang
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi, China
- Jiangxi Key Laboratory of Neurological Tumors and Cerebrovascular Diseases, Nanchang 330006, Jiangxi, China
- Jiangxi Health Commission Key Laboratory of Neurological Medicine, Nanchang 330006, Jiangxi, China
- Institute of Neuroscience, Nanchang University, Nanchang 330006, Jiangxi, China
| | - Bing Xiao
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi, China
| | - Minhua Ye
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi, China
| | - Shigang Lv
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi, China
| | - Miaojing Wu
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi, China
| | - Xingen Zhu
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi, China
- Jiangxi Key Laboratory of Neurological Tumors and Cerebrovascular Diseases, Nanchang 330006, Jiangxi, China
- Jiangxi Health Commission Key Laboratory of Neurological Medicine, Nanchang 330006, Jiangxi, China
- Institute of Neuroscience, Nanchang University, Nanchang 330006, Jiangxi, China
| | - Ping Hu
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi, China
- Jiangxi Key Laboratory of Neurological Tumors and Cerebrovascular Diseases, Nanchang 330006, Jiangxi, China
- Jiangxi Health Commission Key Laboratory of Neurological Medicine, Nanchang 330006, Jiangxi, China
- Institute of Neuroscience, Nanchang University, Nanchang 330006, Jiangxi, China
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Snytte J, Setton R, Mwilambwe-Tshilobo L, Natasha Rajah M, Sheldon S, Turner GR, Spreng RN. Structure-Function Interactions in the Hippocampus and Prefrontal Cortex Are Associated with Episodic Memory in Healthy Aging. eNeuro 2024; 11:ENEURO.0418-23.2023. [PMID: 38479810 PMCID: PMC10972739 DOI: 10.1523/eneuro.0418-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 12/11/2023] [Accepted: 12/15/2023] [Indexed: 04/01/2024] Open
Abstract
Aging comes with declines in episodic memory. Memory decline is accompanied by structural and functional alterations within key brain regions, including the hippocampus and lateral prefrontal cortex, as well as their affiliated default and frontoparietal control networks. Most studies have examined how structural or functional differences relate to memory independently. Here we implemented a multimodal, multivariate approach to investigate how interactions between individual differences in structural integrity and functional connectivity relate to episodic memory performance in healthy aging. In a sample of younger (N = 111; mean age, 22.11 years) and older (N = 78; mean age, 67.29 years) adults, we analyzed structural MRI and multiecho resting-state fMRI data. Participants completed measures of list recall (free recall of words from a list), associative memory (cued recall of paired words), and source memory (cued recall of the trial type, or the sensory modality in which a word was presented). The findings revealed that greater structural integrity of the posterior hippocampus and middle frontal gyrus were linked with a pattern of increased within-network connectivity, which together were related to better associative and source memory in older adulthood. Critically, older adults displayed better memory performance in the context of decreased hippocampal volumes when structural differences were accompanied by functional reorganization. This functional reorganization was characterized by a pruning of connections between the hippocampus and the limbic and frontoparietal control networks. Our work provides insight into the neural mechanisms that underlie age-related compensation, revealing that the functional architecture associated with better memory performance in healthy aging is tied to the structural integrity of the hippocampus and prefrontal cortex.
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Affiliation(s)
- Jamie Snytte
- Department of Psychology, McGill University, Montreal, Quebec H3A 1G1, Canada
| | - Roni Setton
- Department of Psychology, Harvard University, Cambridge, Massachusetts 02138
| | - Laetitia Mwilambwe-Tshilobo
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, Pennsylvania 19104
- Department of Psychology, Princeton University, Princeton, New Jersey 08540
| | - M Natasha Rajah
- Department of Psychology, McGill University, Montreal, Quebec H3A 1G1, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - Signy Sheldon
- Department of Psychology, McGill University, Montreal, Quebec H3A 1G1, Canada
| | - Gary R Turner
- Department of Psychology, York University, Toronto, Ontario M3J 1P3, Canada
| | - R Nathan Spreng
- Department of Psychology, McGill University, Montreal, Quebec H3A 1G1, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec H3A 1A1, Canada
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec H3A 2B4, Canada
- McConnell Brain Imaging Centre, McGill University, Montreal, Quebec H3A 2B4, Canada
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27
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Wang X, Chen Q, Liu Y, Sun J, Li J, Zhao P, Cai L, Liu W, Yang Z, Wang Z, Lv H. Causal relationship between multiparameter brain MRI phenotypes and age: evidence from Mendelian randomization. Brain Commun 2024; 6:fcae077. [PMID: 38529357 PMCID: PMC10963122 DOI: 10.1093/braincomms/fcae077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 01/05/2024] [Accepted: 02/29/2024] [Indexed: 03/27/2024] Open
Abstract
To explore the causal relationship between age and brain health (cortical atrophy, white matter integrity, white matter hyperintensities and cerebral microbleeds in various brain regions) related multiparameter imaging features using two-sample Mendelian randomization. Age was determined as chronological age of the subject. Cortical volume, white matter micro-integrity, white matter hyperintensity volume and cerebral microbleeds of each brain region were included as phenotypes for brain health. Age and imaging of brain health related genetic data were analysed to determine the causal relationship using inverse-variance weighted model, validated by heterogeneity and horizontal pleiotropy variables. Age is causally related to increased volumes of white matter hyperintensities (β = 0.151). For white matter micro-integrity, fibres of the inferior cerebellar peduncle (axial diffusivity β = -0.128, orientation dispersion index β = 0.173), cerebral peduncle (axial diffusivity β = -0.136), superior fronto-occipital fasciculus (isotropic volume fraction β = 0.163) and fibres within the limbic system were causally deteriorated. We also detected decreased cortical thickness of multiple frontal and temporal regions (P < 0.05). Microbleeds were not related with aging (P > 0.05). Aging is a threat of brain health, leading to cortical atrophy mainly in the frontal lobes, as well as the white matter degeneration especially abnormal hyperintensity and deteriorated white matter integrity around the hippocampus.
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Affiliation(s)
- Xinghao Wang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
| | - Qian Chen
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
| | - Yawen Liu
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
| | - Jing Sun
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
| | - Jia Li
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
| | - Pengfei Zhao
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
| | - Linkun Cai
- School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China
| | - Wenjuan Liu
- Department of Radiology, Aerospace Center Hospital, Beijing 100089, China
- Peking University Aerospace School of Clinical Medicine, Beijing 100089, China
| | - Zhenghan Yang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
| | - Zhenchang Wang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
| | - Han Lv
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
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28
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Toyonaga T, Khattar N, Wu Y, Lu Y, Naganawa M, Gallezot JD, Matuskey D, Mecca AP, Pittman B, Dias M, Nabulsi NB, Finnema SJ, Chen MK, Arnsten A, Radhakrishnan R, Skosnik PD, D'Souza DC, Esterlis I, Huang Y, van Dyck CH, Carson RE. The regional pattern of age-related synaptic loss in the human brain differs from gray matter volume loss: in vivo PET measurement with [ 11C]UCB-J. Eur J Nucl Med Mol Imaging 2024; 51:1012-1022. [PMID: 37955791 DOI: 10.1007/s00259-023-06487-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 10/21/2023] [Indexed: 11/14/2023]
Abstract
PURPOSE Aging is a major societal concern due to age-related functional losses. Synapses are crucial components of neural circuits, and synaptic density could be a sensitive biomarker to evaluate brain function. [11C]UCB-J is a positron emission tomography (PET) ligand targeting synaptic vesicle glycoprotein 2A (SV2A), which can be used to evaluate brain synaptic density in vivo. METHODS We evaluated age-related changes in gray matter synaptic density, volume, and blood flow using [11C]UCB-J PET and magnetic resonance imaging (MRI) in a wide age range of 80 cognitive normal subjects (21-83 years old). Partial volume correction was applied to the PET data. RESULTS Significant age-related decreases were found in 13, two, and nine brain regions for volume, synaptic density, and blood flow, respectively. The prefrontal cortex showed the largest volume decline (4.9% reduction per decade: RPD), while the synaptic density loss was largest in the caudate (3.6% RPD) and medial occipital cortex (3.4% RPD). The reductions in caudate are consistent with previous SV2A PET studies and likely reflect that caudate is the site of nerve terminals for multiple major tracts that undergo substantial age-related neurodegeneration. There was a non-significant negative relationship between volume and synaptic density reductions in 16 gray matter regions. CONCLUSION MRI and [11]C-UCB-J PET showed age-related decreases of gray matter volume, synaptic density, and blood flow; however, the regional patterns of the reductions in volume and SV2A binding were different. Those patterns suggest that MR-based measures of GM volume may not be directly representative of synaptic density.
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Affiliation(s)
- Takuya Toyonaga
- PET Center, Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, 06520, USA.
| | - Nikkita Khattar
- PET Center, Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, 06520, USA
| | - Yanjun Wu
- PET Center, Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, 06520, USA
| | - Yihuan Lu
- PET Center, Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, 06520, USA
| | - Mika Naganawa
- PET Center, Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, 06520, USA
| | - Jean-Dominique Gallezot
- PET Center, Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, 06520, USA
| | - David Matuskey
- PET Center, Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, 06520, USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Neurology, Yale University School of Medicine, New Haven, CT, USA
| | - Adam P Mecca
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Alzheimer's Disease Research Unit, Yale University School of Medicine, New Haven, CT, USA
| | - Brian Pittman
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Mark Dias
- PET Center, Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, 06520, USA
| | - Nabeel B Nabulsi
- PET Center, Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, 06520, USA
| | - Sjoerd J Finnema
- PET Center, Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, 06520, USA
| | - Ming-Kai Chen
- PET Center, Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, 06520, USA
| | - Amy Arnsten
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychology, Yale University School of Medicine, New Haven, CT, USA
| | - Rajiv Radhakrishnan
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Patrick D Skosnik
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Bouvé College of Health Sciences, Northeastern University Schools of Nursing & Pharmacy/Pharmaceutical Sciences, Boston, MA, USA
| | - Deepak Cyril D'Souza
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Irina Esterlis
- PET Center, Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, 06520, USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Yiyun Huang
- PET Center, Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, 06520, USA
| | - Christopher H van Dyck
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Neurology, Yale University School of Medicine, New Haven, CT, USA
- Alzheimer's Disease Research Unit, Yale University School of Medicine, New Haven, CT, USA
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT, USA
| | - Richard E Carson
- PET Center, Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, 06520, USA
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29
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Durazzo TC, Stephens LH, Meyerhoff DJ. Regional cortical thickness recovery with extended abstinence after treatment in those with alcohol use disorder. Alcohol 2024; 114:51-60. [PMID: 37657667 PMCID: PMC10902196 DOI: 10.1016/j.alcohol.2023.08.011] [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: 05/23/2023] [Revised: 07/31/2023] [Accepted: 08/22/2023] [Indexed: 09/03/2023]
Abstract
Several cross-sectional investigations reported widespread cortical thinning in those with alcohol use disorder (AUD). The few longitudinal studies investigating cortical thickness changes during abstinence are limited to the first month of sobriety. Consequently, cortical thickness changes during extended abstinence in those with AUD is unclear. In this study, AUD participants were studied at approximately 1 week (n = 68), 1 month (n = 88), and 7.3 months (n = 40) of abstinence. Forty-five never-smoking controls (CON) completed a baseline study, and 15 were reassessed after approximately 9.6 months. Participants completed magnetic resonance imaging studies at 1.5T, and cortical thickness for 34 bilateral regions of interest (ROI) was quantitated with FreeSurfer. AUD participants demonstrated significant linear thickness increases in 25/34 ROI over 7.3 months of abstinence. The rate of change from 1 week to 1 month was greater than 1 month to 7.3 months in 19/34 ROIs. Proatherogenic conditions were associated with lower thickness recovery in anterior frontal, inferior parietal, and lateral/mesial temporal regions. After 7.3 months of abstinence, AUD participants were statistically equivalent to CON on cortical thickness in 24/34 ROIs; the cortical thickness differences between AUD and CON in the banks superior temporal gyrus, post central, posterior cingulate, superior parietal, supramarginal, and superior frontal cortices were driven by thinner cortices in AUD with proatherogenic conditions relative to CON. In actively smoking AUD, increasing pack-years was associated with decreasing thickness recovery primarily in the anterior frontal ROIs. Widespread bilateral cortical thickness recovery over 7.3 months of abstinence was the central finding for this AUD cohort. The longitudinal and cross-sectional findings for AUD with proatherogenic suggests alterations in perfusion or vascular integrity may relate to structural recovery in those with AUD. These results support the adaptive and beneficial effects of sustained sobriety on brain structural recovery in people with AUD.
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Affiliation(s)
- Timothy C Durazzo
- Sierra-Pacific Mental Illness Research and Education Clinical Centers, Veterans Administration Palo Alto Health Care System, Palo Alto, CA, United States; Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, United States.
| | - Lauren H Stephens
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Dieter J Meyerhoff
- Center for Imaging of Neurodegenerative Diseases (CIND), San Francisco Veterans Administration Medical Center, San Francisco, CA, United States; Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, United States
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30
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Krämer C, Stumme J, da Costa Campos L, Dellani P, Rubbert C, Caspers J, Caspers S, Jockwitz C. Prediction of cognitive performance differences in older age from multimodal neuroimaging data. GeroScience 2024; 46:283-308. [PMID: 37308769 PMCID: PMC10828156 DOI: 10.1007/s11357-023-00831-4] [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: 03/02/2023] [Accepted: 05/17/2023] [Indexed: 06/14/2023] Open
Abstract
Differences in brain structure and functional and structural network architecture have been found to partly explain cognitive performance differences in older ages. Thus, they may serve as potential markers for these differences. Initial unimodal studies, however, have reported mixed prediction results of selective cognitive variables based on these brain features using machine learning (ML). Thus, the aim of the current study was to investigate the general validity of cognitive performance prediction from imaging data in healthy older adults. In particular, the focus was with examining whether (1) multimodal information, i.e., region-wise grey matter volume (GMV), resting-state functional connectivity (RSFC), and structural connectivity (SC) estimates, may improve predictability of cognitive targets, (2) predictability differences arise for global cognition and distinct cognitive profiles, and (3) results generalize across different ML approaches in 594 healthy older adults (age range: 55-85 years) from the 1000BRAINS study. Prediction potential was examined for each modality and all multimodal combinations, with and without confound (i.e., age, education, and sex) regression across different analytic options, i.e., variations in algorithms, feature sets, and multimodal approaches (i.e., concatenation vs. stacking). Results showed that prediction performance differed considerably between deconfounding strategies. In the absence of demographic confounder control, successful prediction of cognitive performance could be observed across analytic choices. Combination of different modalities tended to marginally improve predictability of cognitive performance compared to single modalities. Importantly, all previously described effects vanished in the strict confounder control condition. Despite a small trend for a multimodal benefit, developing a biomarker for cognitive aging remains challenging.
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Affiliation(s)
- Camilla Krämer
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- Institute for Anatomy I, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Johanna Stumme
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- Institute for Anatomy I, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Lucas da Costa Campos
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- Institute for Anatomy I, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Paulo Dellani
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- Institute for Anatomy I, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Christian Rubbert
- Department of Diagnostic and Interventional Radiology, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Julian Caspers
- Department of Diagnostic and Interventional Radiology, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Svenja Caspers
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- Institute for Anatomy I, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Christiane Jockwitz
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany.
- Institute for Anatomy I, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
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31
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Norling AM, Gerstenecker A, Bolding MS, Hoef LV, Buford T, Walden R, An H, Ying C, Myers T, Jones BS, Del Bene V, Lazar RM. Effects of a brief HIIT intervention on cognitive performance in older women. GeroScience 2024; 46:1371-1384. [PMID: 37581755 PMCID: PMC10828265 DOI: 10.1007/s11357-023-00893-4] [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: 06/19/2023] [Accepted: 07/25/2023] [Indexed: 08/16/2023] Open
Abstract
Cardiorespiratory fitness (CRF) mitigates age-related decline in cognition and brain volume. Little is known, however, about the effects of high-intensity interval training (HIIT) on cognitive aging and the relationship between HIIT, cognition, hippocampal subfield volumes, and cerebral oxygen extraction fraction (OEF). Older sedentary women participated in an 8-week HIIT intervention. We conducted cognitive assessments, fitness assessments (VO2max), MRI scans: asymmetric spin echo oxygen extraction fraction (ASE-OEF), high-resolution multiple image co-registration and averaging (HR-MICRA) imaging, and transcranial Doppler ultrasonography before and after the intervention. VO2max increased from baseline (M = 19.36, SD = 2.84) to follow-up (M = 23.25, SD = 3.61), Z = - 2.93, p < .001, r = 0.63. Composite cognitive (Z = - 2.05, p = 0.041), language (Z = - 2.19, p = 0.028), and visuospatial memory (Z = - 2.22, p = 0.026), z-scores increased significantly. Hippocampal subfield volumes CA1 and CA3 dentate gyrus and subiculum decreased non-significantly (all p > 0.05); whereas a significant decrease in CA2 (Z = - 2.045, p = 0.041, r = 0.436) from baseline (M = 29.51; SD = 24.50) to follow-up (M = 24.50; SD = 13.38) was observed. Right hemisphere gray matter was correlated with language z-scores (p = 0.025; r = 0.679). The subiculum was correlated with attention (p = 0.047; r = 0.618) and verbal memory (p = 0.020; r = 0.700). The OEF and CBF were unchanged at follow-up (all p > .05). Although we observed cognitive improvements following 8 weeks of our HIIT intervention, they were not explained by hippocampal, OEF, or CBF changes.
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Affiliation(s)
- Amani M Norling
- Department of Neurology, University of Alabama at Birmingham, 650 Sparks Center, 1720 7Th Avenue South, Birmingham, AL, 35294, USA.
- Department of Psychology, University of Alabama at Birmingham, Birmingham, AL, USA.
- Evelyn F. McKnight Brain Institute, University of Alabama at Birmingham, Birmingham, AL, USA.
| | - Adam Gerstenecker
- Department of Neurology, University of Alabama at Birmingham, 650 Sparks Center, 1720 7Th Avenue South, Birmingham, AL, 35294, USA
- Evelyn F. McKnight Brain Institute, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Mark S Bolding
- Evelyn F. McKnight Brain Institute, University of Alabama at Birmingham, Birmingham, AL, USA
- Department of Radiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Lawrence Ver Hoef
- Department of Neurology, University of Alabama at Birmingham, 650 Sparks Center, 1720 7Th Avenue South, Birmingham, AL, 35294, USA
| | - Thomas Buford
- Center for Exercise Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Randall Walden
- School of Engineering, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Hongyu An
- Mallinckrodt Institute of Radiology, Washington University of Medicine in St. Louis, St. Louis, MO, USA
| | - Chunwei Ying
- Mallinckrodt Institute of Radiology, Washington University of Medicine in St. Louis, St. Louis, MO, USA
| | - Terina Myers
- Department of Neurology, University of Alabama at Birmingham, 650 Sparks Center, 1720 7Th Avenue South, Birmingham, AL, 35294, USA
- Evelyn F. McKnight Brain Institute, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Benjamin S Jones
- Department of Neurology, University of Alabama at Birmingham, 650 Sparks Center, 1720 7Th Avenue South, Birmingham, AL, 35294, USA
| | - Victor Del Bene
- Department of Neurology, University of Alabama at Birmingham, 650 Sparks Center, 1720 7Th Avenue South, Birmingham, AL, 35294, USA
- Evelyn F. McKnight Brain Institute, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Ronald M Lazar
- Department of Neurology, University of Alabama at Birmingham, 650 Sparks Center, 1720 7Th Avenue South, Birmingham, AL, 35294, USA
- Evelyn F. McKnight Brain Institute, University of Alabama at Birmingham, Birmingham, AL, USA
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Marzi C, Giannelli M, Barucci A, Tessa C, Mascalchi M, Diciotti S. Efficacy of MRI data harmonization in the age of machine learning: a multicenter study across 36 datasets. Sci Data 2024; 11:115. [PMID: 38263181 PMCID: PMC10805868 DOI: 10.1038/s41597-023-02421-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 07/27/2023] [Indexed: 01/25/2024] Open
Abstract
Pooling publicly-available MRI data from multiple sites allows to assemble extensive groups of subjects, increase statistical power, and promote data reuse with machine learning techniques. The harmonization of multicenter data is necessary to reduce the confounding effect associated with non-biological sources of variability in the data. However, when applied to the entire dataset before machine learning, the harmonization leads to data leakage, because information outside the training set may affect model building, and potentially falsely overestimate performance. We propose a 1) measurement of the efficacy of data harmonization; 2) harmonizer transformer, i.e., an implementation of the ComBat harmonization allowing its encapsulation among the preprocessing steps of a machine learning pipeline, avoiding data leakage by design. We tested these tools using brain T1-weighted MRI data from 1740 healthy subjects acquired at 36 sites. After harmonization, the site effect was removed or reduced, and we showed the data leakage effect in predicting individual age from MRI data, highlighting that introducing the harmonizer transformer into a machine learning pipeline allows for avoiding data leakage by design.
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Affiliation(s)
- Chiara Marzi
- Department of Statistics, Computer Science and Applications "Giuseppe Parenti", University of Florence, 50134, Florence, Italy
- "Nello Carrara" Institute of Applied Physics (IFAC), National Research Council (CNR), 50019, Sesto Fiorentino, Florence, Italy
| | - Marco Giannelli
- Unit of Medical Physics, Pisa University Hospital "Azienda Ospedaliero-Universitaria Pisana", 56126, Pisa, Italy
| | - Andrea Barucci
- "Nello Carrara" Institute of Applied Physics (IFAC), National Research Council (CNR), 50019, Sesto Fiorentino, Florence, Italy
| | - Carlo Tessa
- Radiology Unit Apuane e Lunigiana, Azienda USL Toscana Nord Ovest, 54100, Massa, Italy
| | - Mario Mascalchi
- Department of Experimental and Clinical Biomedical Sciences "Mario Serio", University of Florence, 50139, Florence, Italy
- Division of Epidemiology and Clinical Governance, Institute for Study, Prevention and netwoRk in Oncology (ISPRO), 50139, Florence, Italy
| | - Stefano Diciotti
- Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi" - DEI, University of Bologna, 47522, Cesena, Italy.
- Alma Mater Research Institute for Human-Centered Artificial Intelligence, University of Bologna, 40121, Bologna, Italy.
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Bröhl T, Rings T, Pukropski J, von Wrede R, Lehnertz K. The time-evolving epileptic brain network: concepts, definitions, accomplishments, perspectives. FRONTIERS IN NETWORK PHYSIOLOGY 2024; 3:1338864. [PMID: 38293249 PMCID: PMC10825060 DOI: 10.3389/fnetp.2023.1338864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Accepted: 12/19/2023] [Indexed: 02/01/2024]
Abstract
Epilepsy is now considered a network disease that affects the brain across multiple levels of spatial and temporal scales. The paradigm shift from an epileptic focus-a discrete cortical area from which seizures originate-to a widespread epileptic network-spanning lobes and hemispheres-considerably advanced our understanding of epilepsy and continues to influence both research and clinical treatment of this multi-faceted high-impact neurological disorder. The epileptic network, however, is not static but evolves in time which requires novel approaches for an in-depth characterization. In this review, we discuss conceptual basics of network theory and critically examine state-of-the-art recording techniques and analysis tools used to assess and characterize a time-evolving human epileptic brain network. We give an account on current shortcomings and highlight potential developments towards an improved clinical management of epilepsy.
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Affiliation(s)
- Timo Bröhl
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany
- Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Bonn, Germany
| | - Thorsten Rings
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany
- Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Bonn, Germany
| | - Jan Pukropski
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany
| | - Randi von Wrede
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany
| | - Klaus Lehnertz
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany
- Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Bonn, Germany
- Interdisciplinary Center for Complex Systems, University of Bonn, Bonn, Germany
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Chen J, Li T, Zhao B, Chen H, Yuan C, Garden GA, Wu G, Zhu H. The interaction effects of age, APOE and common environmental risk factors on human brain structure. Cereb Cortex 2024; 34:bhad472. [PMID: 38112569 PMCID: PMC10793588 DOI: 10.1093/cercor/bhad472] [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: 05/04/2023] [Revised: 10/09/2023] [Accepted: 11/06/2023] [Indexed: 12/21/2023] Open
Abstract
Mounting evidence suggests considerable diversity in brain aging trajectories, primarily arising from the complex interplay between age, genetic, and environmental risk factors, leading to distinct patterns of micro- and macro-cerebral aging. The underlying mechanisms of such effects still remain unclear. We conducted a comprehensive association analysis between cerebral structural measures and prevalent risk factors, using data from 36,969 UK Biobank subjects aged 44-81. Participants were assessed for brain volume, white matter diffusivity, Apolipoprotein E (APOE) genotypes, polygenic risk scores, lifestyles, and socioeconomic status. We examined genetic and environmental effects and their interactions with age and sex, and identified 726 signals, with education, alcohol, and smoking affecting most brain regions. Our analysis revealed negative age-APOE-ε4 and positive age-APOE-ε2 interaction effects, respectively, especially in females on the volume of amygdala, positive age-sex-APOE-ε4 interaction on the cerebellar volume, positive age-excessive-alcohol interaction effect on the mean diffusivity of the splenium of the corpus callosum, positive age-healthy-diet interaction effect on the paracentral volume, and negative APOE-ε4-moderate-alcohol interaction effects on the axial diffusivity of the superior fronto-occipital fasciculus. These findings highlight the need of considering age, sex, genetic, and environmental joint effects in elucidating normal or abnormal brain aging.
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Affiliation(s)
- Jie Chen
- Department of Biostatistics, University of North Carolina at Chapel Hill, 135 Dauer Drive, Chapel Hill NC 27514, United States
| | - Tengfei Li
- Department of Radiology, School of Medicine, University of North Carolina at Chapel Hill, 101 Manning Drive, Chapel Hill, NC 27514, United States
- Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, 125 Mason Farm Road, Chapel Hill, NC 27599, United States
| | - Bingxin Zhao
- Department of Statistics and Data Science, The Wharton School, University of Pennsylvania, 265 South 37th Street, 3rd & 4th Floors, Philadelphia, PA 19104-1686, United States
| | - Hui Chen
- School of Public Health, Zhejiang University School of Medicine, 866 Yuhangtang Rd, Hangzhou 310058, China
| | - Changzheng Yuan
- School of Public Health, Zhejiang University School of Medicine, 866 Yuhangtang Rd, Hangzhou 310058, China
- Department of Nutrition, Harvard T H Chan School of Public Health, 665 Huntington Avenue Boston, MA, 02115, United States
| | - Gwenn A Garden
- Department of Neurology, School of Medicine, University of North Carolina at Chapel Hill, 170 Manning Drive Chapel Hill, NC 27599-7025, United States
| | - Guorong Wu
- Department of Psychiatry, School of Medicine, University of North Carolina at Chapel Hill, 101 Manning Drive, Chapel Hill, NC 27514, United States
- Departments of Statistics and Operations Research, University of North Carolina at Chapel Hill, 318 E Cameron Ave #3260, Chapel Hill, NC 27599, United States
- Departments of Computer Science, University of North Carolina at Chapel Hill, 201 South Columbia Street, Chapel Hill, NC 27599, United States
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, 116 Manning Dr, Chapel Hill, NC 27599, United States
- Carolina Institute for Developmental Disabilities, 101 Renee Lynne Ct, Carrboro, NC 27510, United States
| | - Hongtu Zhu
- Department of Biostatistics, University of North Carolina at Chapel Hill, 135 Dauer Drive, Chapel Hill NC 27514, United States
- Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, 125 Mason Farm Road, Chapel Hill, NC 27599, United States
- Departments of Statistics and Operations Research, University of North Carolina at Chapel Hill, 318 E Cameron Ave #3260, Chapel Hill, NC 27599, United States
- Departments of Computer Science, University of North Carolina at Chapel Hill, 201 South Columbia Street, Chapel Hill, NC 27599, United States
- Departments of Genetics, University of North Carolina at Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC 27514, United States
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Scharf C, Koschutnig K, Zussner T, Fink A, Tilp M. Twelve weeks of physical exercise breaks with coordinative exercises at the workplace increase the sulcal depth and decrease gray matter volume in brain structures related to visuomotor processes. Brain Struct Funct 2024; 229:63-74. [PMID: 38070007 PMCID: PMC10827861 DOI: 10.1007/s00429-023-02732-w] [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: 03/17/2023] [Accepted: 11/03/2023] [Indexed: 01/31/2024]
Abstract
Physical exercise can evoke changes in the brain structure. Consequently, these can lead to positive impacts on brain health. However, physical exercise studies including coordinative exercises are rare. Therefore, in this study, we investigated how 12 weeks of physical exercise breaks (PEBs) with coordinative exercises, focusing mainly on juggling tasks, affected the brain structure. The participants were randomly allocated to an intervention group (IG, n = 16; 42.8 ± 10.2 years) and a control group (CG, n = 9; 44.2 ± 12.3 years). The IG performed the PEBs with coordinative exercises twice per week for 15-20 min per session. Before the intervention, after 6 weeks of the intervention, and after 12 weeks of the intervention, participants underwent a high-resolution 3T T1-weighted magnetic resonance imagining scan. Juggling performance was assessed by measuring the time taken to perform a three-ball cascade. A surface-based analysis revealed an increase in vertex-wise cortical depth in a cluster including the inferior parietal lobe after 6 and 12 weeks of training in the IG. After 12 weeks, the IG showed a decrease in gray matter (GM) volume in a cluster primarily involving the right insula and the right operculum. The changes in the GM volume were related to improvements in juggling performance. No significant changes were found for the CG. To conclude, the present study showed that regular engagement in PEBs with coordinative exercises led to changes in brain structures strongly implicated in visuomotor processes involving hand and arm movements.
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Affiliation(s)
- Carina Scharf
- Institute of Human Movement Science, Sport and Health, University of Graz, Mozartgasse 14, 8010, Graz, Austria.
| | - Karl Koschutnig
- Institute of Psychology, University of Graz, Universitätsplatz 2, 8010, Graz, Austria
| | - Thomas Zussner
- Institute of Psychology, University of Graz, Universitätsplatz 2, 8010, Graz, Austria
| | - Andreas Fink
- Institute of Psychology, University of Graz, Universitätsplatz 2, 8010, Graz, Austria
| | - Markus Tilp
- Institute of Human Movement Science, Sport and Health, University of Graz, Mozartgasse 14, 8010, Graz, Austria
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Rothmann LM, Tondo LP, Borelli WV, Esper NB, Portolan ET, Franco AR, Portuguez MW, Ferreira PE, Bittencourt AML, Soder RB, Viola TW, da Costa JC, Grassi-Oliveira R. The cortical thickness of tricenarian cocaine users assembles features of an octogenarian brain. J Neurosci Res 2024; 102:e25287. [PMID: 38284862 DOI: 10.1002/jnr.25287] [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: 08/17/2023] [Revised: 11/29/2023] [Accepted: 12/09/2023] [Indexed: 01/30/2024]
Abstract
It has been suggested that substance use disorders could lead to accelerated biological aging, but only a few neuroimaging studies have investigated this hypothesis so far. In this cross-sectional study, structural neuroimaging was performed to measure cortical thickness (CT) in tricenarian adults with cocaine use disorder (CUD, n1 = 30) and their age-paired controls (YC, n1 = 30), and compare it with octogenarian elder controls (EC, n1 = 20). We found that CT in the right fusiform gyrus was similar between CUD and EC, thinner than the expected values of YC. We also found that regarding CT of the right inferior temporal gyrus, right inferior parietal cortex, and left superior parietal cortex, the CUD group exhibited parameters that fell in between EC and YC groups. Finally, CT of the right pars triangularis bordering with orbitofrontal gyrus, right superior temporal gyrus, and right precentral gyrus were reduced in CUD when contrasted with YC, but those areas were unrelated to CT of EC. Despite the 50-year age gap between our age groups, CT of tricenarian cocaine users assembles features of an octogenarian brain, reinforcing the accelerated aging hypothesis in CUD.
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Affiliation(s)
- Leonardo Melo Rothmann
- Translational Neuropsychiatry Unit, Department of Clinical Medicine, Graduate School of Health, Aarhus University, Aarhus, Denmark
- Brain Institute (BraIns), Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
- Graduate Program in Medicine and Health Sciences, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
| | - Lucca Pizzato Tondo
- Brain Institute (BraIns), Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
| | | | | | - Eduardo Tavares Portolan
- Brain Institute (BraIns), Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
- School of Medicine, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
| | - Alexandre Rosa Franco
- Center for the Developing Brain, Child Mind Institute, New York, New York, USA
- Nathan S. Kline Institute for Psychiatric Research, Orangeburg, New York, USA
- Department of Psychiatric, Grossman School of Medicine, New York University, New York, New York, USA
| | - Mirna Wetters Portuguez
- Brain Institute (BraIns), Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
- Graduate Program in Medicine and Health Sciences, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
- School of Medicine, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
| | - Pedro Eugênio Ferreira
- Brain Institute (BraIns), Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
| | | | - Ricardo Bernardi Soder
- Brain Institute (BraIns), Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
- School of Medicine, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
| | - Thiago Wendt Viola
- Brain Institute (BraIns), Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
- Graduate Program in Medicine and Health Sciences, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
- School of Medicine, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
| | - Jaderson Costa da Costa
- Brain Institute (BraIns), Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
- Graduate Program in Medicine and Health Sciences, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
- School of Medicine, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
| | - Rodrigo Grassi-Oliveira
- Translational Neuropsychiatry Unit, Department of Clinical Medicine, Graduate School of Health, Aarhus University, Aarhus, Denmark
- Brain Institute (BraIns), Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
- Graduate Program in Medicine and Health Sciences, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
- School of Medicine, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
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Otero P, Cotardo T, Blanco V, Torres ÁJ, Simón MA, Bueno AM, Vázquez FL. A randomized controlled pilot study of a cognitive-behavioral video game intervention for the promotion of active aging. Digit Health 2024; 10:20552076241233139. [PMID: 38384369 PMCID: PMC10880542 DOI: 10.1177/20552076241233139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2023] [Accepted: 01/30/2024] [Indexed: 02/23/2024] Open
Abstract
Background Due to the accessibility barriers of in-person programs for active aging, the development of programs that use innovative technologies is needed. Video games can be an engaging tool for disseminating active aging interventions. Objective The objective of this pilot study was to analyze the feasibility of a cognitive-behavioral intervention to promote active aging administered through a video game. Methods Fifty-five participants (63.6% women, mean age = 53.0 years) were randomly assigned to a cognitive-behavioral intervention to promote active aging administered through an interactive multimedia online video game with a complementary app (CBI-V; n = 29) or to a control group that received nonspecific online information (CG; n = 26). Results Only 3.6% of the participants dropped out of the study (6.9% in CBI-V and 0.0% in CG; without significant differences between groups). The mean number of modules completed was 7.6 (SD = 0.9) out of 8 in the CBI-V and 7.9 (SD = 0.5) in the control group (CG), without significant between-group differences. In the CBI-V, the mean total time dedicated to the game was 516.8 min (SD = 94.3), including 143.2 min (SD = 31.6) of cognitive training tasks, and the mean of completed tasks was 206.2 (SD = 33.7) out of 259. Participants were highly engaged (M = 39.9, SD = 8.6) and satisfied (M = 25.8, SD = 4.5) with the intervention. After the intervention, the CBI-V group significantly improved on SF-36 dimensions of General Health (p = .0386), Vitality (p = .0283), Social Functioning (p = .0130), and Physical Summary Index (p = .0370) compared to the CG, with medium effect sizes (d = 0.56-0.75). Conclusions The results demonstrate the feasibility of the video game intervention to promote active aging and encourage conducting a large-scale randomized controlled trial.
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Affiliation(s)
- Patricia Otero
- Department of Psychology, University of A Coruña, A Coruña, Spain
| | - Tania Cotardo
- Department of Clinical Psychology and Psychobiology, University of Santiago de Compostela, Santiago de Compostela, Spain
| | - Vanessa Blanco
- Department of Evolutionary and Educational Psychology, University of Santiago de Compostela, Santiago de Compostela, Spain
| | - Ángela J. Torres
- Department of Psychiatry, Radiology, Public Health, Nursing and Medicine, University of Santiago de Compostela, Santiago de Compostela, Spain
| | - Miguel A. Simón
- Department of Psychology, University of A Coruña, A Coruña, Spain
| | - Ana M. Bueno
- Department of Psychology, University of A Coruña, A Coruña, Spain
| | - Fernando L. Vázquez
- Department of Clinical Psychology and Psychobiology, University of Santiago de Compostela, Santiago de Compostela, Spain
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Benítez-Burraco A, Ivanova O. Language in healthy and pathological ageing: Methodological milestones and challenges. INTERNATIONAL JOURNAL OF LANGUAGE & COMMUNICATION DISORDERS 2024; 59:4-12. [PMID: 38149881 DOI: 10.1111/1460-6984.13003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/28/2023]
Affiliation(s)
- Antonio Benítez-Burraco
- Department of Spanish, Linguistics and Theory of Literature (Linguistics), Faculty of Philology, University of Seville, Sevilla, Spain
| | - Olga Ivanova
- Spanish Language Department, Faculty of Philology, University of Salamanca/Institute of Neuroscience of Castilla y León (INCYL), Salamanca, Spain
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Johansen T, Øyeflaten I, Eriksen HR, Lyby PS, Dittrich WH, Holsen I, Jakobsen H, Jensen C. Changes in memory and attention during and after occupational rehabilitation: A longitudinal study. Work 2024; 77:949-961. [PMID: 37781841 DOI: 10.3233/wor-230027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/03/2023] Open
Abstract
BACKGROUND There is need for more knowledge about the relationship between work and cognitive functioning in sick-listed individuals. OBJECTIVE This study investigated whether the degree of work participation is relevant for recovery of cognitive functioning in sick-listed individuals. METHODS 177 occupational rehabilitation participants and 70 controls participated in a non-randomised, longitudinal study. Participants completed computerised cognitive tests targeting sustained attention and working memory at start and end of rehabilitation and 3 and 12 months after rehabilitation. The change score performance in attention and memory between start and end, start and 3 months and 12 months was compared in individuals on sick leave 100-75%, 74-40% and 39-0% (three sick leave groups) of the time in the year after rehabilitation, and a control group not being on sick leave. Fixed effect analysis of covariance adjusting for education and work ability was used. RESULTS The sick leave group 100-75% had significantly lower score on work ability compared to the other groups at baseline. The main findings indicated that the sick leave group 39-0% improved significantly more in sustained attention compared to the sick leave group 100-75% between start and end of rehabilitation and from start of rehabilitation to 3 and 12 months after. CONCLUSION The degree of work participation seems relevant to recovery of the cognitive function sustained attention in sick-listed individuals. These findings encourage work rehabilitation clinicians, work consultants and employers to develop RTW plans which take into account that graded employment influence cognitive functioning.
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Affiliation(s)
- Thomas Johansen
- Norwegian National Advisory Unit on Occupational Rehabilitation, Rauland, Norway
| | - Irene Øyeflaten
- Norwegian National Advisory Unit on Occupational Rehabilitation, Rauland, Norway
- NORCE, Norwegian Research Centre, Bergen, Norway
| | - Hege R Eriksen
- Department of Sport, Food and Natural Sciences, Western Norway University of Applied Sciences, Bergen, Norway
| | | | - Winand H Dittrich
- FOM Hochschule, KCI Competence Center for Behavioral Economics, Frankfurt, Germany
| | - Inge Holsen
- Red Cross Haugland Rehabilitation Center, Flekke, Norway
| | | | - Chris Jensen
- Norwegian National Advisory Unit on Occupational Rehabilitation, Rauland, Norway
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Thavabalasingam S, Aashat S, Palombo DJ, Verfaellie M, Lee ACH. Investigating the impact of healthy aging on memory for temporal duration and order. NEUROPSYCHOLOGY, DEVELOPMENT, AND COGNITION. SECTION B, AGING, NEUROPSYCHOLOGY AND COGNITION 2024; 31:75-96. [PMID: 36082443 DOI: 10.1080/13825585.2022.2120178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Accepted: 08/27/2022] [Indexed: 06/15/2023]
Abstract
Temporal information, including information about temporal order and duration, is a fundamental component of event sequence memory. While previous research has demonstrated that aging can have a detrimental effect on memory for temporal order, there has been limited insight into the effect of aging on memory for durations, particularly within the context of sequences. In the current study, neurologically healthy young and older participants were administered two temporal match-mismatch tasks: one in which they were instructed on each trial to compare the temporal order or duration information of stimulus sequences presented first in a study phase and then, after a short delay, in a test phase (event sequence task); and a second in which participants were required to compare single durations or sequences of durations across study and test phases of each trial (pinwheel task). Consistent with the literature, the older participants were significantly poorer compared to their younger counterparts at making temporal order match-mismatch judgments in the event sequence task. In addition to this, data from both tasks suggested that the older adults were also less accurate at match-mismatch judgments based on duration information, with tentative evidence from the pinwheel task to suggest that this age-related effect was most prominent when the duration information was presented within a sequence. We suggest that age-related changes to medial temporal and frontal lobe function may contribute to changes in memory for temporal information in older adults, given the importance of these regions to event sequence memory.
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Affiliation(s)
| | - Supreet Aashat
- Department of Psychology (Scarborough), University of Toronto, Toronto, Ontario, Canada
| | - Daniela J Palombo
- Department of Psychology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Mieke Verfaellie
- Memory Disorders Research Center, VA Boston Healthcare System, Boston, MA, USA
- Department of Psychiatry, Boston University School of Medicine, Boston, MA, USA
| | - Andy C H Lee
- Rotman Research Institute, Baycrest Centre, Toronto, Ontario, Canada
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Hendriks J, Mutsaerts HJ, Joules R, Peña-Nogales Ó, Rodrigues PR, Wolz R, Burchell GL, Barkhof F, Schrantee A. A systematic review of (semi-)automatic quality control of T1-weighted MRI scans. Neuroradiology 2024; 66:31-42. [PMID: 38047983 PMCID: PMC10761394 DOI: 10.1007/s00234-023-03256-0] [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: 09/28/2023] [Accepted: 11/16/2023] [Indexed: 12/05/2023]
Abstract
PURPOSE Artifacts in magnetic resonance imaging (MRI) scans degrade image quality and thus negatively affect the outcome measures of clinical and research scanning. Considering the time-consuming and subjective nature of visual quality control (QC), multiple (semi-)automatic QC algorithms have been developed. This systematic review presents an overview of the available (semi-)automatic QC algorithms and software packages designed for raw, structural T1-weighted (T1w) MRI datasets. The objective of this review was to identify the differences among these algorithms in terms of their features of interest, performance, and benchmarks. METHODS We queried PubMed, EMBASE (Ovid), and Web of Science databases on the fifth of January 2023, and cross-checked reference lists of retrieved papers. Bias assessment was performed using PROBAST (Prediction model Risk Of Bias ASsessment Tool). RESULTS A total of 18 distinct algorithms were identified, demonstrating significant variations in methods, features, datasets, and benchmarks. The algorithms were categorized into rule-based, classical machine learning-based, and deep learning-based approaches. Numerous unique features were defined, which can be roughly divided into features capturing entropy, contrast, and normative measures. CONCLUSION Due to dataset-specific optimization, it is challenging to draw broad conclusions about comparative performance. Additionally, large variations exist in the used datasets and benchmarks, further hindering direct algorithm comparison. The findings emphasize the need for standardization and comparative studies for advancing QC in MR imaging. Efforts should focus on identifying a dataset-independent measure as well as algorithm-independent methods for assessing the relative performance of different approaches.
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Affiliation(s)
- Janine Hendriks
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Location VUmc, PK -1, De Boelelaan 1117, Amsterdam, 1081 HV, The Netherlands.
| | - Henk-Jan Mutsaerts
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Location VUmc, PK -1, De Boelelaan 1117, Amsterdam, 1081 HV, The Netherlands
| | | | | | | | - Robin Wolz
- IXICO Plc, London, EC1A 9PN, UK
- Imperial College London, London, SW7 2BX, UK
| | - George L Burchell
- Medical Library, Vrije Universiteit Amsterdam, Amsterdam, 1081 HV, The Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Location VUmc, PK -1, De Boelelaan 1117, Amsterdam, 1081 HV, The Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, WC1N 3BG, UK
| | - Anouk Schrantee
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Location AMC, Amsterdam, 1105 AZ, The Netherlands
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42
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Filippi M, Cividini C, Basaia S, Spinelli EG, Castelnovo V, Leocadi M, Canu E, Agosta F. Age-related vulnerability of the human brain connectome. Mol Psychiatry 2023; 28:5350-5358. [PMID: 37414925 DOI: 10.1038/s41380-023-02157-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 06/05/2023] [Accepted: 06/22/2023] [Indexed: 07/08/2023]
Abstract
Multifactorial models integrating brain variables at multiple scales are warranted to investigate aging and its relationship with neurodegeneration. Our aim was to evaluate how aging affects functional connectivity of pivotal regions of the human brain connectome (i.e., hubs), which represent potential vulnerability 'stations' to aging, and whether such effects influence the functional and structural changes of the whole brain. We combined the information of the functional connectome vulnerability, studied through an innovative graph-analysis approach (stepwise functional connectivity), with brain cortical thinning in aging. Using data from 128 cognitively normal participants (aged 20-85 years), we firstly investigated the topological functional network organization in the optimal healthy condition (i.e., young adults) and observed that fronto-temporo-parietal hubs showed a highly direct functional connectivity with themselves and among each other, while occipital hubs showed a direct functional connectivity within occipital regions and sensorimotor areas. Subsequently, we modeled cortical thickness changes over lifespan, revealing that fronto-temporo-parietal hubs were among the brain regions that changed the most, whereas occipital hubs showed a quite spared cortical thickness across ages. Finally, we found that cortical regions highly functionally linked to the fronto-temporo-parietal hubs in healthy adults were characterized by the greatest cortical thinning along the lifespan, demonstrating that the topology and geometry of hub functional connectome govern the region-specific structural alterations of the brain regions.
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Affiliation(s)
- Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Vita-Salute San Raffaele University, Milan, Italy.
| | - Camilla Cividini
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Silvia Basaia
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Edoardo G Spinelli
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Veronica Castelnovo
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Michela Leocadi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Elisa Canu
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Federica Agosta
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
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43
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Hardy CC, Korstanje R. Aging and urinary control: Alterations in the brain-bladder axis. Aging Cell 2023; 22:e13990. [PMID: 37740454 PMCID: PMC10726905 DOI: 10.1111/acel.13990] [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: 07/12/2023] [Revised: 08/29/2023] [Accepted: 09/05/2023] [Indexed: 09/24/2023] Open
Abstract
Age-associated alterations in bladder control affect millions of older adults, with a heavy burden added to families both economically and in quality of life. Therapeutic options are limited with poor efficacy in older adults, lending to a growing need to address the gaps in our current understanding of urinary tract aging. This review summarizes the current knowledge of age-associated alterations in the structure and function of the brain-bladder axis and identifies important gaps in the field that have yet to be addressed. Urinary aging is associated with decreased tissue responsiveness, decreased control over the voiding reflex, signaling dysfunction along the brain-bladder axis, and structural changes within the bladder wall. Studies are needed to improve our understanding of how age affects the brain-bladder axis and identify genetic targets that correlate with functional outcomes.
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44
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Wallace D, Cooper NR, Sel A, Russo R. Do non-traumatic stressful life events and ageing negatively impact working memory performance and do they interact to further impair working memory performance? PLoS One 2023; 18:e0290635. [PMID: 38019767 PMCID: PMC10686508 DOI: 10.1371/journal.pone.0290635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2022] [Accepted: 08/13/2023] [Indexed: 12/01/2023] Open
Abstract
Stress and normal ageing produce allostatic load, which may lead to difficulties with cognition thereby degrading quality of life. The current study's objective was to assess whether ageing and cumulative stress interact to accelerate cognitive decline. With 60 participants, Marshall et al. found that ageing and cumulative stress interact significantly to impair working memory performance in older adults, suggesting vulnerability to the cumulative effects of life events beyond 60 years old. To replicate and extend this finding, we increased the sample size by conducting 3 independent studies with 156 participants and improved the statistical methods by conducting an iterative Bayesian meta-analysis with Bayes factors. Bayes factors deliver a more comprehensive result because they provide evidence for either the null hypothesis (H0), the alternative hypothesis (H1) or for neither hypothesis due to evidence not being sufficiently sensitive. Young (18-35 yrs) and older (60-85 yrs) healthy adults were categorised as high or low stress based on their life events score derived from the Life Events Scale for Students or Social Readjustment Rating Scale, respectively. We measured accuracy and reaction time on a 2-back working memory task to provide: a) Bayes factors and b) Bayesian meta-analysis, which iteratively added each study's effect sizes to evaluate the overall strength of evidence that ageing, cumulative stress and/or the combination of the two detrimentally affect working memory performance. Using a larger sample (N = 156 vs. N = 60) and a more powerful statistical approach, we did not replicate the robust age by cumulative stress interaction effect found by Marshall et al.. The effects of ageing and cumulative stress also fell within the anecdotal range (⅓
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Affiliation(s)
- Denise Wallace
- Department of Psychology and Centre for Brain Science, University of Essex, Colchester, Essex, United Kingdom
| | - Nicholas R. Cooper
- Department of Psychology and Centre for Brain Science, University of Essex, Colchester, Essex, United Kingdom
| | - Alejandra Sel
- Department of Psychology and Centre for Brain Science, University of Essex, Colchester, Essex, United Kingdom
| | - Riccardo Russo
- Department of Psychology and Centre for Brain Science, University of Essex, Colchester, Essex, United Kingdom
- Department of Behavioral and Brain Sciences, University of Pavia, Pavia, Italy
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45
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Marzola P, Melzer T, Pavesi E, Gil-Mohapel J, Brocardo PS. Exploring the Role of Neuroplasticity in Development, Aging, and Neurodegeneration. Brain Sci 2023; 13:1610. [PMID: 38137058 PMCID: PMC10741468 DOI: 10.3390/brainsci13121610] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 11/16/2023] [Accepted: 11/18/2023] [Indexed: 12/24/2023] Open
Abstract
Neuroplasticity refers to the ability of the brain to reorganize and modify its neural connections in response to environmental stimuli, experience, learning, injury, and disease processes. It encompasses a range of mechanisms, including changes in synaptic strength and connectivity, the formation of new synapses, alterations in the structure and function of neurons, and the generation of new neurons. Neuroplasticity plays a crucial role in developing and maintaining brain function, including learning and memory, as well as in recovery from brain injury and adaptation to environmental changes. In this review, we explore the vast potential of neuroplasticity in various aspects of brain function across the lifespan and in the context of disease. Changes in the aging brain and the significance of neuroplasticity in maintaining cognitive function later in life will also be reviewed. Finally, we will discuss common mechanisms associated with age-related neurodegenerative processes (including protein aggregation and accumulation, mitochondrial dysfunction, oxidative stress, and neuroinflammation) and how these processes can be mitigated, at least partially, by non-invasive and non-pharmacologic lifestyle interventions aimed at promoting and harnessing neuroplasticity.
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Affiliation(s)
- Patrícia Marzola
- Department of Morphological Sciences and Graduate Neuroscience Program, Center of Biological Sciences, Federal University of Santa Catarina, Florianopolis 88040-900, SC, Brazil; (P.M.); (T.M.); (E.P.)
| | - Thayza Melzer
- Department of Morphological Sciences and Graduate Neuroscience Program, Center of Biological Sciences, Federal University of Santa Catarina, Florianopolis 88040-900, SC, Brazil; (P.M.); (T.M.); (E.P.)
| | - Eloisa Pavesi
- Department of Morphological Sciences and Graduate Neuroscience Program, Center of Biological Sciences, Federal University of Santa Catarina, Florianopolis 88040-900, SC, Brazil; (P.M.); (T.M.); (E.P.)
| | - Joana Gil-Mohapel
- Division of Medical Sciences, University of Victoria, Victoria, BC V8P 5C2, Canada
- Island Medical Program, Faculty of Medicine, University of British Columbia, Victoria, BC V8P 5C2, Canada
| | - Patricia S. Brocardo
- Department of Morphological Sciences and Graduate Neuroscience Program, Center of Biological Sciences, Federal University of Santa Catarina, Florianopolis 88040-900, SC, Brazil; (P.M.); (T.M.); (E.P.)
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46
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Madden DJ, Merenstein JL. Quantitative susceptibility mapping of brain iron in healthy aging and cognition. Neuroimage 2023; 282:120401. [PMID: 37802405 PMCID: PMC10797559 DOI: 10.1016/j.neuroimage.2023.120401] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 09/14/2023] [Accepted: 09/30/2023] [Indexed: 10/10/2023] Open
Abstract
Quantitative susceptibility mapping (QSM) is a magnetic resonance imaging (MRI) technique that can assess the magnetic properties of cerebral iron in vivo. Although brain iron is necessary for basic neurobiological functions, excess iron content disrupts homeostasis, leads to oxidative stress, and ultimately contributes to neurodegenerative disease. However, some degree of elevated brain iron is present even among healthy older adults. To better understand the topographical pattern of iron accumulation and its relation to cognitive aging, we conducted an integrative review of 47 QSM studies of healthy aging, with a focus on five distinct themes. The first two themes focused on age-related increases in iron accumulation in deep gray matter nuclei versus the cortex. The overall level of iron is higher in deep gray matter nuclei than in cortical regions. Deep gray matter nuclei vary with regard to age-related effects, which are most prominent in the putamen, and age-related deposition of iron is also observed in frontal, temporal, and parietal cortical regions during healthy aging. The third theme focused on the behavioral relevance of iron content and indicated that higher iron in both deep gray matter and cortical regions was related to decline in fluid (speed-dependent) cognition. A handful of multimodal studies, reviewed in the fourth theme, suggest that iron interacts with imaging measures of brain function, white matter degradation, and the accumulation of neuropathologies. The final theme concerning modifiers of brain iron pointed to potential roles of cardiovascular, dietary, and genetic factors. Although QSM is a relatively recent tool for assessing cerebral iron accumulation, it has significant promise for contributing new insights into healthy neurocognitive aging.
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Affiliation(s)
- David J Madden
- Brain Imaging and Analysis Center, Duke University Medical Center, Box 3918, Durham, NC 27710, USA; Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27710, USA; Center for Cognitive Neuroscience, Duke University, Durham, NC 27708, USA.
| | - Jenna L Merenstein
- Brain Imaging and Analysis Center, Duke University Medical Center, Box 3918, Durham, NC 27710, USA
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47
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Aksnes M, Capogna E, Vidal-Piñeiro D, Chaudhry FA, Myrstad M, Idland AV, Halaas NB, Dakhil S, Blennow K, Zetterberg H, Walhovd KB, Watne LO, Fjell AM. Matrix metalloproteinases are associated with brain atrophy in cognitively unimpaired individuals. Neurobiol Aging 2023; 131:11-23. [PMID: 37549446 DOI: 10.1016/j.neurobiolaging.2023.05.012] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 04/28/2023] [Accepted: 05/20/2023] [Indexed: 08/09/2023]
Abstract
Matrix metalloproteinases (MMPs) and their tissue inhibitors (TIMPs) have been linked to age-related neurodegeneration and Alzheimer's disease (AD), but their role in normal aging is poorly understood. We used linear mixed models to determine if baseline or rate of yearly change in cerebrospinal fluid (CSF) levels of MMP-2; MMP-3; MMP-10; TIMP-123 (composite of TIMP-1, TIMP-2, and TIMP-3); or TIMP-4 predicted changes in bilateral entorhinal cortex thickness, hippocampal volume, or lateral ventricle volume in cognitively unimpaired individuals. We also assessed effects on the CSF AD biomarkers amyloid-β42 and phosphorylated tau181. Low baseline levels of MMP-3 predicted larger ventricle volumes and more entorhinal cortex thinning. Increased CSF MMP-2 levels over time predicted more entorhinal thinning, hippocampal atrophy, and ventricular expansion, while increased TIMP-123 over time predicted ventricular expansion. No MMP/TIMPs predicted changes in CSF AD biomarkers. Notably, we show for the first time that longitudinal increases in MMP-2 and TIMP-123 levels may predict age-associated brain atrophy. In conclusion, MMPs and TIMPs may play a role in brain atrophy in cognitively unimpaired aging.
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Affiliation(s)
- Mari Aksnes
- Department of Geriatric Medicine, University of Oslo, Oslo, Norway.
| | - Elettra Capogna
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo, Norway
| | - Didac Vidal-Piñeiro
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo, Norway
| | - Farrukh Abbas Chaudhry
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Marius Myrstad
- Department of Internal Medicine, Bærum Hospital, Vestre Viken Hospital Trust, Gjettum, Norway; Department of Medical Research, Bærum Hospital, Vestre Viken Hospital Trust, Gjettum, Norway
| | - Ane-Victoria Idland
- Oslo Delirium Research Group, Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway
| | - Nathalie Bodd Halaas
- Oslo Delirium Research Group, Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway
| | - Shams Dakhil
- Oslo Delirium Research Group, Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway; Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, the Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- Institute of Neuroscience and Physiology, the Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK; UK Dementia Research Institute at UCL, London, UK; Hong Center for Neurodegenerative Diseases, Hong Kong, China; Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Kristine Beate Walhovd
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo, Norway; Computational Radiology and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Leiv Otto Watne
- Department of Geriatric Medicine, Akershus University Hospital, Lørenskog, Norway; Institute of Clinical Medicine, Campus Ahus, University of Oslo, Oslo, Norway
| | - Anders Martin Fjell
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo, Norway; Computational Radiology and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
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48
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Fjell AM, Sørensen Ø, Wang Y, Amlien IK, Baaré WFC, Bartrés-Faz D, Bertram L, Boraxbekk CJ, Brandmaier AM, Demuth I, Drevon CA, Ebmeier KP, Ghisletta P, Kievit R, Kühn S, Madsen KS, Mowinckel AM, Nyberg L, Sexton CE, Solé-Padullés C, Vidal-Piñeiro D, Wagner G, Watne LO, Walhovd KB. No phenotypic or genotypic evidence for a link between sleep duration and brain atrophy. Nat Hum Behav 2023; 7:2008-2022. [PMID: 37798367 PMCID: PMC10663160 DOI: 10.1038/s41562-023-01707-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Accepted: 08/31/2023] [Indexed: 10/07/2023]
Abstract
Short sleep is held to cause poorer brain health, but is short sleep associated with higher rates of brain structural decline? Analysing 8,153 longitudinal MRIs from 3,893 healthy adults, we found no evidence for an association between sleep duration and brain atrophy. In contrast, cross-sectional analyses (51,295 observations) showed inverse U-shaped relationships, where a duration of 6.5 (95% confidence interval, (5.7, 7.3)) hours was associated with the thickest cortex and largest volumes relative to intracranial volume. This fits converging evidence from research on mortality, health and cognition that points to roughly seven hours being associated with good health. Genome-wide association analyses suggested that genes associated with longer sleep for below-average sleepers were linked to shorter sleep for above-average sleepers. Mendelian randomization did not yield evidence for causal impacts of sleep on brain structure. The combined results challenge the notion that habitual short sleep causes brain atrophy, suggesting that normal brains promote adequate sleep duration-which is shorter than current recommendations.
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Affiliation(s)
- Anders M Fjell
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway.
- Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway.
| | - Øystein Sørensen
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
| | - Yunpeng Wang
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
| | - Inge K Amlien
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
| | - William F C Baaré
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital-Amager and Hvidovre, Copenhagen, Denmark
| | - David Bartrés-Faz
- Departament de Medicina, Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona, Barcelona, Spain
- Institut de Neurociències, Universitat de Barcelona, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pii Sunyer, Barcelona, Spain
| | - Lars Bertram
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
| | - Carl-Johan Boraxbekk
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital-Amager and Hvidovre, Copenhagen, Denmark
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
- Department of Radiation Sciences, Diagnostic Radiology, Umeå University, Umeå, Sweden
- Institute of Sports Medicine Copenhagen, Copenhagen University Hospital Bispebjerg, Copenhagen, Denmark
| | - Andreas M Brandmaier
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
- Department of Psychology, MSB Medical School Berlin, Berlin, Germany
| | - Ilja Demuth
- Department of Endocrinology and Metabolic Diseases (including Division of Lipid Metabolism), Biology of Aging Working Group, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Berlin Institute of Health Center for Regenerative Therapies, Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Christian A Drevon
- Vitas AS, Oslo, Norway
- Department of Nutrition, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, Oslo, Norway
| | | | - Paolo Ghisletta
- Faculty of Psychology and Educational Sciences, University of Geneva, Geneva, Switzerland
- UniDistance Suisse, Brig, Switzerland
- Swiss National Centre of Competence in Research LIVES, University of Geneva, Geneva, Switzerland
| | - Rogier Kievit
- Cognitive Neuroscience Department, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Simone Kühn
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
- Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Kathrine Skak Madsen
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital-Amager and Hvidovre, Copenhagen, Denmark
- Radiography, Department of Technology, University College Copenhagen, Copenhagen, Denmark
| | - Athanasia M Mowinckel
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
| | - Lars Nyberg
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
| | - Claire E Sexton
- Department of Psychiatry, University of Oxford, Oxford, UK
- Global Brain Health Institute, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- Alzheimer's Association, Chicago, IL, USA
| | - Cristina Solé-Padullés
- Departament de Medicina, Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona, Barcelona, Spain
- Institut de Neurociències, Universitat de Barcelona, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pii Sunyer, Barcelona, Spain
| | - Didac Vidal-Piñeiro
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
| | - Gerd Wagner
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Leiv Otto Watne
- Oslo Delirium Research Group, Department of Geriatric Medicine, University of Oslo, Oslo, Norway
- Department of Geriatric Medicine, Akershus University Hospital, Lørenskog, Norway
| | - Kristine B Walhovd
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
- Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
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49
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Karl V, Rohe T. Structural brain changes in emotion recognition across the adult lifespan. Soc Cogn Affect Neurosci 2023; 18:nsad052. [PMID: 37769357 PMCID: PMC10627307 DOI: 10.1093/scan/nsad052] [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: 10/13/2022] [Revised: 06/22/2023] [Accepted: 09/19/2023] [Indexed: 09/30/2023] Open
Abstract
Emotion recognition (ER) declines with increasing age, yet little is known whether this observation is based on structural brain changes conveyed by differential atrophy. To investigate whether age-related ER decline correlates with reduced grey matter (GM) volume in emotion-related brain regions, we conducted a voxel-based morphometry analysis using data of the Human Connectome Project-Aging (N = 238, aged 36-87) in which facial ER was tested. We expected to find brain regions that show an additive or super-additive age-related change in GM volume indicating atrophic processes that reduce ER in older adults. The data did not support our hypotheses after correction for multiple comparisons. Exploratory analyses with a threshold of P < 0.001 (uncorrected), however, suggested that relationships between GM volume and age-related general ER may be widely distributed across the cortex. Yet, small effect sizes imply that only a small fraction of the decline of ER in older adults can be attributed to local GM volume changes in single voxels or their multivariate patterns.
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Affiliation(s)
- Valerie Karl
- Institute of Psychology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen 91054, Germany
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo 0424, Norway
- PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo 0373, Norway
| | - Tim Rohe
- Institute of Psychology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen 91054, Germany
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50
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Zeng Y, Guo R, Cao S, Yang H. Causal associations between blood lipids and brain structures: a Mendelian randomization study. Cereb Cortex 2023; 33:10901-10908. [PMID: 37718242 DOI: 10.1093/cercor/bhad334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Revised: 08/26/2023] [Accepted: 08/27/2023] [Indexed: 09/19/2023] Open
Abstract
The potential causal association between dyslipidemia and brain structures remains unclear. Therefore, this study aimed to investigate whether circulating lipids are causally associated with brain structure alterations using Mendelian randomization analysis. Genome-wide association study summary statistics of blood lipids and brain structures were obtained from publicly available databases. Inverse-variance weighted method was used as the primary method to assess causality. In addition, four additional Mendelian randomization methods (MR-Egger, weighted median, simple mode, and weighted mode) were applied to supplement inverse-variance weighted. Furthermore, Cochrane's Q test, MR-Egger intercept test, MR-PRESSO global test, and leave-one-out analysis were performed for sensitivity analyses. After Bonferroni corrections, two causal associations were finally identified: elevated non-high-density lipoprotein cholesterol level leads to higher average cortical thickness (β = 0.0066 mm, 95% confidence interval: 0.0045-0.0087 mm, P = 0.001); and elevated high-density lipoprotein cholesterol level leads to higher inferior temporal surface area (β = 18.6077 mm2, 95% confidence interval: 11.9835-25.2320 mm2, P = 0.005). Four additional Mendelian randomization methods indicated parallel results. Sensitivity tests demonstrated the stability. Overall, the present study showed causal relationships between several lipid profiles and specific brain structures, providing new insights into the link between dyslipidemia and neurological disorders.
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Affiliation(s)
- Youjie Zeng
- Department of Anesthesiology, Third Xiangya Hospital, Central South University, Changsha, Hunan 410013, China
| | - Ren Guo
- Department of Pharmacy, Third Xiangya Hospital, Central South University, Changsha, Hunan 410013, China
| | - Si Cao
- Department of Anesthesiology, Third Xiangya Hospital, Central South University, Changsha, Hunan 410013, China
| | - Heng Yang
- Department of Neurology, Third Xiangya Hospital, Central South University, Changsha, Hunan 410013, China
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