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Flaherty R, Sui YV, Masurkar AV, Betensky RA, Rusinek H, Lazar M. Diffusion imaging markers of accelerated aging of the lower cingulum in subjective cognitive decline. Front Neurol 2024; 15:1360273. [PMID: 38784911 PMCID: PMC11111894 DOI: 10.3389/fneur.2024.1360273] [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: 12/22/2023] [Accepted: 04/29/2024] [Indexed: 05/25/2024] Open
Abstract
Introduction Alzheimer's Disease (AD) typically starts in the medial temporal lobe, then develops into a neurodegenerative cascade which spreads to other brain regions. People with subjective cognitive decline (SCD) are more likely to develop dementia, especially in the presence of amyloid pathology. Thus, we were interested in the white matter microstructure of the medial temporal lobe in SCD, specifically the lower cingulum bundle that leads into the hippocampus. Diffusion tensor imaging (DTI) has been shown to differentiate SCD participants who will progress to mild cognitive impairment from those who will not. However, the biology underlying these DTI metrics is unclear, and results in the medial temporal lobe have been inconsistent. Methods To better characterize the microstructure of this region, we applied DTI to cognitively normal participants in the Cam-CAN database over the age of 55 with cognitive testing and diffusion MRI available (N = 325, 127 SCD). Diffusion MRI was processed to generate regional and voxel-wise diffusion tensor values in bilateral lower cingulum white matter, while T1-weighted MRI was processed to generate regional volume and cortical thickness in the medial temporal lobe white matter, entorhinal cortex, temporal pole, and hippocampus. Results SCD participants had thinner cortex in bilateral entorhinal cortex and right temporal pole. No between-group differences were noted for any of the microstructural metrics of the lower cingulum. However, correlations with delayed story recall were significant for all diffusion microstructure metrics in the right lower cingulum in SCD, but not in controls, with a significant interaction effect. Additionally, the SCD group showed an accelerated aging effect in bilateral lower cingulum with MD, AxD, and RD. Discussion The diffusion profiles observed in both interaction effects are suggestive of a mixed neuroinflammatory and neurodegenerative pathology. Left entorhinal cortical thinning correlated with decreased FA and increased RD, suggestive of demyelination. However, right entorhinal cortical thinning also correlated with increased AxD, suggestive of a mixed pathology. This may reflect combined pathologies implicated in early AD. DTI was more sensitive than cortical thickness to the associations between SCD, memory, and age. The combined effects of mixed pathology may increase the sensitivity of DTI metrics to variations with age and cognition.
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Affiliation(s)
- Ryn Flaherty
- Center for Advanced Imaging Innovation and Research, Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States
- Vilcek Institute of Graduate Biomedical Sciences, New York University Grossman School of Medicine, New York, NY, United States
| | - Yu Veronica Sui
- Center for Advanced Imaging Innovation and Research, Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States
| | - Arjun V. Masurkar
- Department of Neurology, New York University Grossman School of Medicine, New York, NY, United States
- Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, United States
| | - Rebecca A. Betensky
- Department of Biostatistics, New York University School of Global Public Health, New York, NY, United States
| | - Henry Rusinek
- Center for Advanced Imaging Innovation and Research, Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY, United States
| | - Mariana Lazar
- Center for Advanced Imaging Innovation and Research, Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States
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Paban V, Mheich A, Spieser L, Sacher M. A multidimensional model of memory complaints in older individuals and the associated hub regions. Front Aging Neurosci 2023; 15:1324309. [PMID: 38187362 PMCID: PMC10771290 DOI: 10.3389/fnagi.2023.1324309] [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: 10/19/2023] [Accepted: 11/27/2023] [Indexed: 01/09/2024] Open
Abstract
Memory complaints are highly prevalent among middle-aged and older adults, and they are frequently reported in individuals experiencing subjective cognitive decline (SCD). SCD has received increasing attention due to its implications for the early detection of dementia. This study aims to advance our comprehension of individuals with SCD by elucidating potential cognitive/psychologic-contributing factors and characterizing cerebral hubs within the brain network. To identify these potential contributing factors, a structural equation modeling approach was employed to investigate the relationships between various factors, such as metacognitive beliefs, personality, anxiety, depression, self-esteem, and resilience, and memory complaints. Our findings revealed that self-esteem and conscientiousness significantly influenced memory complaints. At the cerebral level, analysis of delta and theta electroencephalographic frequency bands recorded during rest was conducted to identify hub regions using a local centrality metric known as betweenness centrality. Notably, our study demonstrated that certain brain regions undergo changes in their hub roles in response to the pathology of SCD. Specifically, the inferior temporal gyrus and the left orbitofrontal area transition into hubs, while the dorsolateral prefrontal cortex and the middle temporal gyrus lose their hub function in the presence of SCD. This rewiring of the neural network may be interpreted as a compensatory response employed by the brain in response to SCD, wherein functional connectivity is maintained or restored by reallocating resources to other regions.
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Affiliation(s)
- Véronique Paban
- Aix-Marseille Université, CNRS, LNC (Laboratoire de Neurosciences Cognitives–UMR 7291), Marseille, France
| | - A. Mheich
- CHUV-Centre Hospitalier Universitaire Vaudois, Service des Troubles du Spectre de l’Autisme et Apparentés, Lausanne University Hospital, Lausanne, Switzerland
| | - L. Spieser
- Aix-Marseille Université, CNRS, LNC (Laboratoire de Neurosciences Cognitives–UMR 7291), Marseille, France
| | - M. Sacher
- University of Toulouse Jean-Jaurès, CNRS, LCLLE (Laboratoire Cognition, Langues, Langage, Ergonomie–UMR 5263), Toulouse, France
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Zhvania M, Japaridze N, Tizabi Y, Lomidze N, Pochkhidze N, Rzayev F, Gasimov E. Differential effects of aging on hippocampal ultrastructure in male vs. female rats. Biogerontology 2023; 24:925-935. [PMID: 37515624 DOI: 10.1007/s10522-023-10052-z] [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: 04/28/2023] [Accepted: 07/09/2023] [Indexed: 07/31/2023]
Abstract
Age-related decline in physical and cognitive functions are facts of life that do not affect everyone to the same extent. We had reported earlier that such cognitive decline is both sex- and context-dependent. Moreover, age-associated ultrastructural changes were observed in the hippocampus of male rats. In this study, we sought to determine potential differences in ultrastructural changes between male and female rats at various stages of life. We performed quantitative electron microscopic evaluation of hippocampal CA1 region, an area intimately involved in cognitive behavior, in both male and female adolescent, adult and old Wistar rats. Specifically, we measured the number of docking synaptic vesicles in axo-dendritic synapses, the length of active zone as well as the total number of synaptic vesicles. Distinct age- and sex-dependent effects were observed in several parameters. Thus, adult female rats had the lowest synaptic active zone compared to both adolescent and old female rats. Moreover, the same parameter was significantly lower in adult and old female rats compared to their male counterparts. On the other hand, old male rats had significantly lower number of total synaptic vesicles compared to both adolescent and adult male rats as well as compared to their female counterparts. Taken together, it may be suggested that age- and sex-dependent ultrastructural changes in the hippocampus may underlie at least some of the differences in cognitive functions among these groups.
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Affiliation(s)
- Mzia Zhvania
- School of Natural Sciences and Medicine, Ilia State University, 3/5 K. Cholokashvili Avenue, 0162, Tbilisi, Georgia.
- Department of Brain Ultrastructure and Nanoarchitecture, Ivane Beritashvili Center of Experimental Biomedicine, Tbilisi, Georgia.
| | - Nadezhda Japaridze
- Department of Brain Ultrastructure and Nanoarchitecture, Ivane Beritashvili Center of Experimental Biomedicine, Tbilisi, Georgia
- New Vision University, Tbilisi, Georgia
| | - Yousef Tizabi
- Department of Pharmacology, Howard University College of Medicine, Washington, DC, USA
| | - Nino Lomidze
- School of Natural Sciences and Medicine, Ilia State University, 3/5 K. Cholokashvili Avenue, 0162, Tbilisi, Georgia
- Department of Brain Ultrastructure and Nanoarchitecture, Ivane Beritashvili Center of Experimental Biomedicine, Tbilisi, Georgia
| | - Nino Pochkhidze
- School of Natural Sciences and Medicine, Ilia State University, 3/5 K. Cholokashvili Avenue, 0162, Tbilisi, Georgia
- Department of Brain Ultrastructure and Nanoarchitecture, Ivane Beritashvili Center of Experimental Biomedicine, Tbilisi, Georgia
| | - Fuad Rzayev
- Department of Histology, Embryology and Cytology, Azerbaijan Medical University, Baku, Azerbaijan
| | - Eldar Gasimov
- Department of Histology, Embryology and Cytology, Azerbaijan Medical University, Baku, Azerbaijan
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Göschel L, Kurz L, Dell'Orco A, Köbe T, Körtvélyessy P, Fillmer A, Aydin S, Riemann LT, Wang H, Ittermann B, Grittner U, Flöel A. 7T amygdala and hippocampus subfields in volumetry-based associations with memory: A 3-year follow-up study of early Alzheimer's disease. Neuroimage Clin 2023; 38:103439. [PMID: 37253284 PMCID: PMC10236463 DOI: 10.1016/j.nicl.2023.103439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 05/09/2023] [Accepted: 05/15/2023] [Indexed: 06/01/2023]
Abstract
INTRODUCTION The hippocampus is the most prominent single region of interest (ROI) for the diagnosis and prediction of Alzheimer's disease (AD). However, its suitability in the earliest stages of cognitive decline, i.e., subjective cognitive decline (SCD), remains uncertain which warrants the pursuit of alternative or complementary regions. The amygdala might be a promising candidate, given its implication in memory as well as other psychiatric disorders, e.g. depression and anxiety, which are prevalent in SCD. In this 7 tesla (T) magnetic resonance imaging (MRI) study, we aimed to compare the contribution of volumetric measurements of the hippocampus, the amygdala, and their respective subfields, for early diagnosis and prediction in an AD-related study population. METHODS Participants from a longitudinal study were grouped into SCD (n = 29), mild cognitive impairment (MCI, n = 23), AD (n = 22) and healthy control (HC, n = 31). All participants underwent 7T MRI at baseline and extensive neuropsychological testing at up to three visits (baseline n = 105, 1-year n = 78, 3-year n = 39). Analysis of covariance (ANCOVA) was used to assess group differences of baseline volumes of the amygdala and the hippocampus and their subfields. Linear mixed models were used to estimate the effects of baseline volumes on yearly changes of a z-scaled memory score. All models were adjusted to age, sex and education. RESULTS Compared to the HC group, individuals with SCD showed smaller amygdala ROI volumes (range across subfields -11% to -1%), but not hippocampus ROI volumes (-2% to 1%) except for the hippocampus-amygdala-transition-area (-7%). However, cross-sectional associations between baseline memory and volumes were smaller for amygdala ROIs (std. ß [95% CI] ranging between 0.16 [0.08; 0.25] and 0.46 [0.31; 0.60]) than hippocampus ROIs (between 0.32 [0.19; 0.44] and 0.53 [0.40; 0.67]). Further, the association of baseline volumes with yearly memory change in the HC and SCD groups was similarly weak for amygdala ROIs and hippocampus ROIs. In the MCI group, volumes of amygdala ROIs were associated with a relevant yearly memory decline [95% CI] ranging between -0.12 [-0.24; 0.00] and -0.26 [-0.42; -0.09] for individuals with 20% smaller volumes than the HC group. However, effects were stronger for hippocampus ROIs with a corresponding yearly memory decline ranging between -0.21 [-0.35; -0.07] and -0.31 [-0.50; -0.13]. CONCLUSION Volumes of amygdala ROIs, as determined by 7T MRI, might contribute to objectively and non-invasively identify patients with SCD, and thus aid early diagnosis and treatment of individuals at risk to develop dementia due to AD, however associations with other psychiatric disorders should be evaluated in further studies. The amygdala's value in the prediction of longitudinal memory changes in the SCD group remains questionable. Primarily in patients with MCI, memory decline over 3 years appears to be more strongly associated with volumes of hippocampus ROIs than amygdala ROIs.
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Affiliation(s)
- Laura Göschel
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology, Charitéplatz 1, 10117 Berlin, Germany; Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, NCRC - Neuroscience Clinical Research Center, Charitéplatz 1, 10117 Berlin, Germany.
| | - Lea Kurz
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology, Charitéplatz 1, 10117 Berlin, Germany; Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, NCRC - Neuroscience Clinical Research Center, Charitéplatz 1, 10117 Berlin, Germany
| | - Andrea Dell'Orco
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology, Charitéplatz 1, 10117 Berlin, Germany; Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, NCRC - Neuroscience Clinical Research Center, Charitéplatz 1, 10117 Berlin, Germany; Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neuroradiology, Charitéplatz 1, 10117 Berlin, Germany
| | - Theresa Köbe
- Deutsches Zentrum für Luft- und Raumfahrt e.V. Projektträger (DLR-PT), Berlin, Germany
| | - Peter Körtvélyessy
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology, Charitéplatz 1, 10117 Berlin, Germany; German Center for Neurodegenerative Diseases (DZNE), site Magdeburg, Leipziger Strasse 44, 39120 Magdeburg, Germany
| | - Ariane Fillmer
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Semiha Aydin
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Layla Tabea Riemann
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany; Institute for Applied Medical Informatics, University Hospital Hamburg-Eppendorf, Hamburg, Germany
| | - Hui Wang
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology, Charitéplatz 1, 10117 Berlin, Germany; Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, NCRC - Neuroscience Clinical Research Center, Charitéplatz 1, 10117 Berlin, Germany; Department of Neurology and Pain Treatment, Immanuel Klinik Rüdersdorf, University Hospital of the Brandenburg Medical School Theodor Fontane, Rüdersdorf bei Berlin, Germany
| | - Bernd Ittermann
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Ulrike Grittner
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Biometry and Clinical Epidemiology, Charitéplatz 1, 10117 Berlin, Germany
| | - Agnes Flöel
- Department of Neurology, University Medicine Greifswald, Greifswald, Germany; German Center for Neurodegenerative Diseases (DZNE), Standort Rostock/Greifswald, Germany
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Rivas-Fernández MÁ, Lindín M, Zurrón M, Díaz F, Lojo-Seoane C, Pereiro AX, Galdo-Álvarez S. Neuroanatomical and neurocognitive changes associated with subjective cognitive decline. Front Med (Lausanne) 2023; 10:1094799. [PMID: 36817776 PMCID: PMC9932036 DOI: 10.3389/fmed.2023.1094799] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Accepted: 01/17/2023] [Indexed: 02/05/2023] Open
Abstract
Introduction Subjective Cognitive Decline (SCD) can progress to mild cognitive impairment (MCI) and Alzheimer's disease (AD) dementia and thus may represent a preclinical stage of the AD continuum. However, evidence about structural changes observed in the brain during SCD remains inconsistent. Materials and methods This cross-sectional study aimed to evaluate, in subjects recruited from the CompAS project, neurocognitive and neurostructural differences between a group of forty-nine control subjects and forty-nine individuals who met the diagnostic criteria for SCD and exhibited high levels of subjective cognitive complaints (SCCs). Structural magnetic resonance imaging was used to compare neuroanatomical differences in brain volume and cortical thickness between both groups. Results Relative to the control group, the SCD group displayed structural changes involving frontal, parietal, and medial temporal lobe regions of critical importance in AD etiology and functionally related to several cognitive domains, including executive control, attention, memory, and language. Conclusion Despite the absence of clinical deficits, SCD may constitute a preclinical entity with a similar (although subtle) pattern of neuroanatomical changes to that observed in individuals with amnestic MCI or AD dementia.
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Affiliation(s)
- Miguel Ángel Rivas-Fernández
- Department of Clinical Psychology and Psychobiology, Universidade de Santiago de Compostela, Santiago de Compostela, Spain,Cognitive Neuroscience Research Group, Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
| | - Mónica Lindín
- Department of Clinical Psychology and Psychobiology, Universidade de Santiago de Compostela, Santiago de Compostela, Spain,Cognitive Neuroscience Research Group, Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
| | - Montserrat Zurrón
- Department of Clinical Psychology and Psychobiology, Universidade de Santiago de Compostela, Santiago de Compostela, Spain,Cognitive Neuroscience Research Group, Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
| | - Fernando Díaz
- Department of Clinical Psychology and Psychobiology, Universidade de Santiago de Compostela, Santiago de Compostela, Spain,Cognitive Neuroscience Research Group, Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
| | - Cristina Lojo-Seoane
- Cognitive Neuroscience Research Group, Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain,Department of Developmental and Educational Psychology, Universidade de Santiago de Compostela, Santiago de Compostela, Spain
| | - Arturo X. Pereiro
- Cognitive Neuroscience Research Group, Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain,Department of Developmental and Educational Psychology, Universidade de Santiago de Compostela, Santiago de Compostela, Spain
| | - Santiago Galdo-Álvarez
- Department of Clinical Psychology and Psychobiology, Universidade de Santiago de Compostela, Santiago de Compostela, Spain,Cognitive Neuroscience Research Group, Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain,*Correspondence: Santiago Galdo-Álvarez,
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Krebs C, Brill E, Minkova L, Federspiel A, Kellner-Weldon F, Wyss P, Teunissen CE, van Harten AC, Seydell-Greenwald A, Klink K, Züst MA, Brem AK, Klöppel S. Investigating Compensatory Brain Activity in Older Adults with Subjective Cognitive Decline. J Alzheimers Dis 2023; 93:107-124. [PMID: 36970895 DOI: 10.3233/jad-221001] [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: 05/09/2023]
Abstract
BACKGROUND Preclinical Alzheimer's disease (AD) is one possible cause of subjective cognitive decline (SCD). Normal task performance despite ongoing neurodegeneration is typically considered as neuronal compensation, which is reflected by greater neuronal activity. Compensatory brain activity has been observed in frontal as well as parietal regions in SCD, but data are scarce, especially outside the memory domain. OBJECTIVE To investigate potential compensatory activity in SCD. Such compensatory activity is particularly expected in participants where blood-based biomarkers indicated amyloid positivity as this implies preclinical AD. METHODS 52 participants with SCD (mean age: 71.00±5.70) underwent structural and functional neuroimaging (fMRI), targeting episodic memory and spatial abilities, and a neuropsychological assessment. The estimation of amyloid positivity was based on plasma amyloid-β and phosphorylated tau (pTau181) measures. RESULTS Our fMRI analyses of the spatial abilities task did not indicate compensation, with only three voxels exceeding an uncorrected threshold at p < 0.001. This finding was not replicated in a subset of 23 biomarker positive individuals. CONCLUSION Our results do not provide conclusive evidence for compensatory brain activity in SCD. It is possible that neuronal compensation does not manifest at such an early stage as SCD. Alternatively, it is possible that our sample size was too small or that compensatory activity may be too heterogeneous to be detected by group-level statistics. Interventions based on the individual fMRI signal should therefore be explored.
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Affiliation(s)
- Christine Krebs
- University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
- Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland
| | - Esther Brill
- University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
- Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland
- Graduate School for Health Sciences, University of Bern, Bern, Switzerland
| | - Lora Minkova
- University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Andrea Federspiel
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Ber, Bern, Switzerland
| | - Frauke Kellner-Weldon
- Section Neuroradiology of the Department of Radiology, Cantonal Hospital Lucerne, Lucerne, Switzerland
| | - Patric Wyss
- University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Charlotte E Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Vrije University, Amsterdam, the Netherlands
| | - Argonde C van Harten
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | | | - Katharina Klink
- University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Marc A Züst
- University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Anna-Katharine Brem
- University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
- Department of Old Age Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Stefan Klöppel
- University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
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Chiu SI, Fan LY, Lin CH, Chen TF, Lim WS, Jang JSR, Chiu MJ. Machine Learning-Based Classification of Subjective Cognitive Decline, Mild Cognitive Impairment, and Alzheimer's Dementia Using Neuroimage and Plasma Biomarkers. ACS Chem Neurosci 2022; 13:3263-3270. [PMID: 36378559 DOI: 10.1021/acschemneuro.2c00255] [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: 11/16/2022] Open
Abstract
Alzheimer's disease (AD) progresses relentlessly from the preclinical to the dementia stage. The process begins decades before the diagnosis of dementia. Therefore, it is crucial to detect early manifestations to prevent cognitive decline. Recent advances in artificial intelligence help tackle the complex high-dimensional data encountered in clinical decision-making. In total, we recruited 206 subjects, including 69 cognitively unimpaired, 40 subjective cognitive decline (SCD), 34 mild cognitive impairment (MCI), and 63 AD dementia (ADD). We included 3 demographic, 1 clinical, 18 brain-image, and 3 plasma biomarker (Aß1-42, Aß1-40, and tau protein) features. We employed the linear discriminant analysis method for feature extraction to make data more distinguishable after dimension reduction. The sequential forward selection method was used for feature selection to identify the 12 best features for machine learning classifiers. We used both random forest and support vector machine as classifiers. The area under the receiver operative curve (AUROC) was close to 0.9 between diseased (combining ADD and MCI) and the controls. AUROC was higher than 0.85 between SCD and controls, 0.90 between MCI and SCD, and above 0.85 between ADD and MCI. We can differentiate between adjacent phases of the AD spectrum with blood biomarkers and brain MR images with the help of machine learning algorithms.
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Affiliation(s)
- Shu-I Chiu
- Department of Computer Science, National Chengchi University, Taipei 116302, Taiwan
| | - Ling-Yun Fan
- Queensland Brain Institute, University of Queensland, St Lucia, QLD 4067, Australia.,Departments of Neurology, National Taiwan University Hospital Bei-Hu Branch, Taipei 108206, Taiwan
| | - Chin-Hsien Lin
- Department of Neurology, College of Medicine, National Taiwan University Hospital, National Taiwan University, Taipei 100225, Taiwan
| | - Ta-Fu Chen
- Department of Neurology, College of Medicine, National Taiwan University Hospital, National Taiwan University, Taipei 100225, Taiwan
| | - Wee Shin Lim
- Department of Computer Science and Information Engineering, National Taiwan University, Taipei 106319, Taiwan
| | - Jyh-Shing Roger Jang
- Department of Computer Science and Information Engineering, National Taiwan University, Taipei 106319, Taiwan
| | - Ming-Jang Chiu
- Department of Neurology, College of Medicine, National Taiwan University Hospital, National Taiwan University, Taipei 100225, Taiwan.,Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei 106319, Taiwan.,Graduate Institute of Brain and Mind Sciences, National Taiwan University, Taipei 100233, Taiwan.,Graduate Institute of Psychology, National Taiwan University, Taipei 106319, Taiwan
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8
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Chen R, Cai G, Xu S, Sun Q, Luo J, Wang Y, Li M, Lin H, Liu J. Body mass index related to executive function and hippocampal subregion volume in subjective cognitive decline. Front Aging Neurosci 2022; 14:905035. [PMID: 36062154 PMCID: PMC9428252 DOI: 10.3389/fnagi.2022.905035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Accepted: 07/25/2022] [Indexed: 11/18/2022] Open
Abstract
Objective This study aims to explore whether body mass index (BMI) level affects the executive function and hippocampal subregion volume of subjective cognitive decline (SCD). Materials and methods A total of 111 participants were included in the analysis, including SCD (38 of normal BMI, 27 of overweight and obesity) and normal cognitive control (NC) (29 of normal BMI, 17 of overweight and obesity). All subjects underwent the Chinese version of the Stroop Color-Word Test (SCWT) to measure the executive function and a high-resolution 3D T1 structural image acquisition. Two-way ANOVA was used to examine the differences in executive function and gray matter volume in hippocampal subregions under different BMI levels between the SCD and NC. Result The subdimensions of executive function in which different BMI levels interact with SCD and NC include inhibition control function [SCWT C-B reaction time(s): F (1,104) = 5.732, p = 0.018], and the hippocampal subregion volume of CA1 [F (1,99) = 8.607, p = 0.004], hippocampal tail [F (1,99) = 4.077, p = 0.046], and molecular layer [F (1,99) = 6.309, p = 0.014]. After correction by Bonferroni method, the population × BMI interaction only had a significant effect on the CA1 (p = 0.004). Further analysis found that the SCWT C-B reaction time of SCD was significantly longer than NC no matter whether it is at the normal BMI level [F (1,104) = 4.325, p = 0.040] or the high BMI level [F (1,104) = 21.530, p < 0.001], and the inhibitory control function of SCD was worse than that of NC. In the normal BMI group, gray matter volume in the hippocampal subregion (CA1) of SCD was significantly smaller than that of NC [F (1,99) = 4.938, p = 0.029]. For patients with SCD, the high BMI group had worse inhibitory control function [F (1,104) = 13.499, p < 0.001] and greater CA1 volume compared with the normal BMI group [F (1,99) = 7.619, p = 0.007]. Conclusion The BMI level is related to the inhibition control function and the gray matter volume of CA1 subregion in SCD. Overweight seems to increase the gray matter volume of CA1 in the elderly with SCD, but it is not enough to compensate for the damage to executive function caused by the disease. These data provide new insights into the relationship between BMI level and executive function of SCD from the perspective of imaging.
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Affiliation(s)
- Ruilin Chen
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, China
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Guiyan Cai
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, China
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Shurui Xu
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, China
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Qianqian Sun
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Jia Luo
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Yajun Wang
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, China
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Ming Li
- Affiliated Rehabilitation Hospital, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Hui Lin
- Department of Physical Education, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Jiao Liu
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, China
- Fujian Key Laboratory of Rehabilitation Technology, Fuzhou, China
- Traditional Chinese Medicine Rehabilitation Research Center of State Administration of Traditional Chinese Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
- Key Laboratory of Orthopedics and Traumatology of Traditional Chinese Medicine and Rehabilitation, Ministry of Education, Fujian University of Traditional Chinese Medicine, Fuzhou, China
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9
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Stanwell P, Iverson GL, Van Patten R, Castellani RJ, McCrory P, Gardner AJ. Examining for Cavum Septum Pellucidum and Ventricular Enlargement in Retired Elite-Level Rugby League Players. Front Neurol 2022; 13:817709. [PMID: 35493804 PMCID: PMC9044485 DOI: 10.3389/fneur.2022.817709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 02/11/2022] [Indexed: 11/13/2022] Open
Abstract
ObjectiveA cavum septum pellucidum (CSP) has been reported as a visible brain anomaly in normal individuals as well in some former combat and collision sport athletes. The appearance of CSP with fenestrations and ventricular enlargement are considered associated features of the neuropathological diagnosis of chronic traumatic encephalopathy. The current study examined CSP anatomic features and lateral ventricle size in retired elite rugby league players and controls.MethodsForty-one retired rugby league players and 41 healthy community controls, similar in age and education, underwent structural MRI scans. CSP grade, CSP length, corpus callosum septal length, and Evans' ratio (for lateral ventricle size) were rated by two of the current study authors. All participants also self-reported concussion exposure histories, depressive symptoms, daytime sleepiness, and impulsivity. They completed a neuropsychological test battery assessing premorbid intellectual functioning, attention, processing speed, language, visuospatial skills, memory, and aspects of executive functioning.ResultsThe two raters had high agreement for CSP grade (Cohen's κ = 0.80), CSP length [intraclass correlation (ICC) = 0.99], corpus callosum septal length (ICC = 0.73), the CSP/septal ratio (ICC = 0.99), and the Evans' ratio (ICC = 0.75). Twenty-five retired players (61.0%) had an abnormal CSP compared to 17 controls [41.5%; χ(1, 82)2 = 3.12, p = 0.08, odds ratio = 2.21]. The CSP/septal ratio was larger for retired players than for the controls. The Evans' ratio did not differ between the two groups. In the retired rugby league players (n = 41), those with normal (n = 16) and abnormal (n = 25) CSP grades did not differ across age, age of first exposure to collision sport, years of sport exposure, concussion history, or 23 clinical and cognitive variables.ConclusionThis study revealed a difference in the size of the CSP between retired professional rugby league players and controls. There was no significant difference in the size of the ventricles between the two groups. There were no significant differences between those with vs. without an abnormal CSP on age of first exposure to rugby league, years of exposure to repetitive neurotrauma, number of lifetime concussions, depression, impulsivity, perceived cognitive decline, or on any neuropsychological test.
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Affiliation(s)
- Peter Stanwell
- Priority Research Centre for Stroke and Brain Injury, School of Health Sciences, University of Newcastle, Callaghan, NSW, Australia
- *Correspondence: Peter Stanwell
| | - Grant L. Iverson
- Department of Physical Medicine and Rehabilitation, Harvard Medical School, Boston, MA, United States
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Charlestown, MA, United States
- Spaulding Research Institute, Charlestown, MA, United States
- MassGeneral Hospital for Children Sports Concussion Program, Boston, MA, United States
- Home Base, A Red Sox Foundation and Massachusetts General Hospital Program, Charlestown, MA, United States
| | - Ryan Van Patten
- Department of Physical Medicine and Rehabilitation, Harvard Medical School, Boston, MA, United States
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Charlestown, MA, United States
- Providence Veterans Administration Medical Center, Providence, RI, United States
- Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, RI, United States
| | - Rudolph J. Castellani
- Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
| | - Paul McCrory
- The Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia
| | - Andrew J. Gardner
- Priority Research Centre for Stroke and Brain Injury, School of Medicine and Public Health, The University of Newcastle, Callaghan, NSW, Australia
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
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10
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Huang Y, Huang L, Wang Y, Liu Y, Lo CYZ, Guo Q. Differential associations of visual memory with hippocampal subfields in subjective cognitive decline and amnestic mild cognitive impairment. BMC Geriatr 2022; 22:153. [PMID: 35209845 PMCID: PMC8876393 DOI: 10.1186/s12877-022-02853-7] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2021] [Accepted: 02/16/2022] [Indexed: 01/16/2023] Open
Abstract
Background Although previous studies have demonstrated that the hippocampus plays a role in verbal memory, the role of hippocampal subfields in visual memory is uncertain, especially in those with preclinical Alzheimer's disease (AD). This study aimed to examine relationships between hippocampal subfield volumes and visual memory in SCD (subjective cognitive decline) and aMCI (amnestic mild cognitive impairment). Methods The study sample included 47 SCD patients, 62 aMCI patients, and 51 normal controls (NCs) and was recruited from Shanghai Jiao Tong University Affiliated Sixth People's Hospital. Visual memory was measured by the subtests of BVMT-R (Brief Visuospatial Memory Test-Revised), PLT (Pictorial Learning Test), DMS (Delayed Matching to Sample), and PAL (Paired Associates Learning). Hippocampal subfield volumes were estimated using FreeSurfer software (version 6.0). We modeled the association between visual memory and relative hippocampal subfield volumes (dividing by estimated total intracranial volume) using Pearson's correlation and linear regression. Results Compared with the NC group, patients with SCD did not find any relative hippocampal subregion atrophy, and the aMCI group found atrophy in CA1, molecular layer, subiculum, GC-ML-DG, CA4, and CA3. After adjusting for covariates (age, sex, and APOE ε4 status) and FDR (false discovery rate) correction of p (q values) < 0.05, in NC group, DMS delay matching scores were significant and negatively associated with presubiculum (r = -0.399, FDR q = 0.024); in SCD group, DMS delay matching scores were negatively associated with CA3 (r = -0.378, FDR q = 0.048); in the aMCI group, BVMT-R immediate recall scores were positively associated with CA1, molecular layer, subiculum, and GC-ML-DG (r = 0.360–0.374, FDR q < 0.036). Stepwise linear regression analysis confirmed the association. Conclusions Our results indicate a different and specific correction of visual memory with relative hippocampal subfield volumes between SCD and aMCI. The correlations involved different and more subfields as cognitive decline. Whether these associations predict future disease progression needs dynamic longitudinal studies. Supplementary Information The online version contains supplementary material available at 10.1186/s12877-022-02853-7.
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Affiliation(s)
- Yanlu Huang
- Department of Gerontology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Lin Huang
- Department of Gerontology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Yifan Wang
- Department of Gerontology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Yuchen Liu
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
| | - Chun-Yi Zac Lo
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China.
| | - Qihao Guo
- Department of Gerontology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China.
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11
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Measurement of Subjective Cognitive Decline (SCD) Using Korean-Everyday Cognition (K-ECog) as a Screening Tool: a Feasibility Study. Dement Neurocogn Disord 2021; 20:80-88. [PMID: 34795771 PMCID: PMC8585529 DOI: 10.12779/dnd.2021.20.4.80] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 10/15/2021] [Accepted: 10/15/2021] [Indexed: 11/27/2022] Open
Abstract
Background and Purpose Everyday Cognition (ECog) has been widely used to differentiate individuals with mild cognitive impairment (MCI) and dementia from normal elderly individuals. It has also been used to assess subjective cognitive decline (SCD). This study investigated the feasibility of using ECog as a screening measure for SCD in community-dwelling elderly individuals. Methods The participants included 84 older adults with and 93 without SCD living in the community. These 2 groups were classified based on their response (“yes” or “no”) to the question “Do you perceive memory or cognitive difficulties?” All participants were evaluated using the Korean-Mini Mental State Examination (K-MMSE), Short form of the Geriatric Depression Scale (SGDS), and the Korean version of Everyday Cognition (K-ECog). Results The scores of all participants were within the normal range on the K-MMSE and SGDS. The total K-MMSE score did not differ significantly between the 2 groups after controlling for age, education, and depression. The scores of SCD group were significantly higher than those of the non-SCD group for memory, language, and executive function: planning domains, as well as K-ECog total score. Receiver operating characteristic curve analysis revealed that the K-ECog total score was effective in moderately differentiating between subjects with and without SCD (area under the curve: 0.73). Conclusions ECog is a feasible and useful screening measure for SCD in older adults living in the community, and can be used to assess the full spectrum of cognitive and functional deficits, ranging from SCD to MCI and dementia.
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12
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Scarth M, Rissanen I, Scholten RJPM, Geerlings MI. Biomarkers of Alzheimer's Disease and Cerebrovascular Lesions and Clinical Progression in Patients with Subjective Cognitive Decline: A Systematic Review. J Alzheimers Dis 2021; 83:1089-1111. [PMID: 34397412 DOI: 10.3233/jad-210218] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
BACKGROUND Early identification of Alzheimer's disease (AD) may be extremely beneficial for delaying disease progression. Subjective cognitive decline (SCD) may be an early indicator of AD pathology. Not all individuals with SCD will eventually develop AD, making it critical to identify biomarkers during the SCD stage which indicate likely clinical progression. OBJECTIVE The present review aims to summarize available data on structural MRI and cerebrospinal fluid (CSF) biomarkers and their association with clinical progression to mild cognitive impairment (MCI) or AD in people with SCD. METHODS Database searches were conducted using Embase and PubMed until June 2020. Longitudinal studies assessing biomarkers in individuals with SCD and assessing clinical progression to MCI/AD were included. Two assessors performed data extraction and assessed the risk of bias in the included studies. Data were synthesized narratively. RESULTS An initial search identified 1,065 papers; after screening and review 14 studies were included. Sample size of the included studies ranged from 28-674, mean age was 60.0-68.6 years, and 10.2%-52%of participants converted to MCI/AD. Lower levels of CSF Aβ 42 were consistently associated with clinical progression. Combination measures identifying an AD-like profile of Aβ 42 and tau levels were strongly associated with clinical progression. Biomarkers identified with structural MRI were less conclusive, as some studies found significant associations while others did not. CONCLUSION Biomarkers may be able to predict clinical progression in those with cognitive complaints. Aβ 42, or combinations of Aβ 42 and tau may be useful biomarkers in identifying individuals with SCD who will progress to MCI/AD.
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Affiliation(s)
- Morgan Scarth
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands
| | - Ina Rissanen
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands
| | - Rob J P M Scholten
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands
| | - Mirjam I Geerlings
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands
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