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Roemer SN, Brendel M, Gnörich J, Malpetti M, Zaganjori M, Quattrone A, Gross M, Steward A, Dewenter A, Wagner F, Dehsarvi A, Ferschmann C, Wall S, Palleis C, Rauchmann BS, Katzdobler S, Jäck A, Stockbauer A, Fietzek UM, Bernhardt AM, Weidinger E, Zwergal A, Stöcklein S, Perneczky R, Barthel H, Sabri O, Levin J, Höglinger GU, Franzmeier N. Subcortical tau is linked to hypoperfusion in connected cortical regions in 4-repeat tauopathies. Brain 2024; 147:2428-2439. [PMID: 38842726 DOI: 10.1093/brain/awae174] [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: 10/17/2023] [Revised: 02/07/2024] [Accepted: 04/28/2024] [Indexed: 06/07/2024] Open
Abstract
Four-repeat (4R) tauopathies are neurodegenerative diseases characterized by cerebral accumulation of 4R tau pathology. The most prominent 4R tauopathies are progressive supranuclear palsy (PSP) and corticobasal degeneration characterized by subcortical tau accumulation and cortical neuronal dysfunction, as shown by PET-assessed hypoperfusion and glucose hypometabolism. Yet, there is a spatial mismatch between subcortical tau deposition patterns and cortical neuronal dysfunction, and it is unclear how these two pathological brain changes are interrelated. Here, we hypothesized that subcortical tau pathology induces remote neuronal dysfunction in functionally connected cortical regions to test a pathophysiological model that mechanistically links subcortical tau accumulation to cortical neuronal dysfunction in 4R tauopathies. We included 51 Aβ-negative patients with clinically diagnosed PSP variants (n = 26) or corticobasal syndrome (n = 25) who underwent structural MRI and 18F-PI-2620 tau-PET. 18F-PI-2620 tau-PET was recorded using a dynamic one-stop-shop acquisition protocol to determine an early 0.5-2.5 min post tracer-injection perfusion window for assessing cortical neuronal dysfunction, as well as a 20-40 min post tracer-injection window to determine 4R-tau load. Perfusion-PET (i.e. early window) was assessed in 200 cortical regions, and tau-PET was assessed in 32 subcortical regions of established functional brain atlases. We determined tau epicentres as subcortical regions with the highest 18F-PI-2620 tau-PET signal and assessed the connectivity of tau epicentres to cortical regions of interest using a resting-state functional MRI-based functional connectivity template derived from 69 healthy elderly controls from the ADNI cohort. Using linear regression, we assessed whether: (i) higher subcortical tau-PET was associated with reduced cortical perfusion; and (ii) cortical perfusion reductions were observed preferentially in regions closely connected to subcortical tau epicentres. As hypothesized, higher subcortical tau-PET was associated with overall lower cortical perfusion, which remained consistent when controlling for cortical tau-PET. Using group-average and subject-level PET data, we found that the seed-based connectivity pattern of subcortical tau epicentres aligned with cortical perfusion patterns, where cortical regions that were more closely connected to the tau epicentre showed lower perfusion. Together, subcortical tau-accumulation is associated with remote perfusion reductions indicative of neuronal dysfunction in functionally connected cortical regions in 4R-tauopathies. This suggests that subcortical tau pathology may induce cortical dysfunction, which may contribute to clinical disease manifestation and clinical heterogeneity.
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Affiliation(s)
- Sebastian N Roemer
- Department of Neurology, University Hospital, LMU Munich, 81377 Munich, Germany
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, 81377 Munich, Germany
| | - Matthias Brendel
- Munich Cluster for Systems Neurology (SyNergy), 81377 Munich, Germany
- Department of Nuclear Medicine, University Hospital, LMU Munich, 81377 Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), 81377 Munich, Germany
| | - Johannes Gnörich
- Department of Nuclear Medicine, University Hospital, LMU Munich, 81377 Munich, Germany
| | - Maura Malpetti
- Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 1TN, UK
| | - Mirlind Zaganjori
- Department of Nuclear Medicine, University Hospital, LMU Munich, 81377 Munich, Germany
| | - Andrea Quattrone
- Institute of Neurology, Magna Graecia University, 88100 Catanzaro, Italy
| | - Mattes Gross
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, 81377 Munich, Germany
- Department of Nuclear Medicine, University Hospital, LMU Munich, 81377 Munich, Germany
| | - Anna Steward
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, 81377 Munich, Germany
| | - Anna Dewenter
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, 81377 Munich, Germany
| | - Fabian Wagner
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, 81377 Munich, Germany
| | - Amir Dehsarvi
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, 81377 Munich, Germany
| | - Christian Ferschmann
- Department of Nuclear Medicine, University Hospital, LMU Munich, 81377 Munich, Germany
| | - Stephan Wall
- Department of Nuclear Medicine, University Hospital, LMU Munich, 81377 Munich, Germany
| | - Carla Palleis
- Department of Neurology, University Hospital, LMU Munich, 81377 Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), 81377 Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), 81377 Munich, Germany
| | - Boris S Rauchmann
- Department of Neuroradiology, University Hospital, LMU Munich, 81377 Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, 80336 Munich, Germany
| | - Sabrina Katzdobler
- Department of Neurology, University Hospital, LMU Munich, 81377 Munich, Germany
| | - Alexander Jäck
- Department of Neurology, University Hospital, LMU Munich, 81377 Munich, Germany
| | - Anna Stockbauer
- Department of Neurology, University Hospital, LMU Munich, 81377 Munich, Germany
| | - Urban M Fietzek
- Department of Neurology, University Hospital, LMU Munich, 81377 Munich, Germany
| | - Alexander M Bernhardt
- Department of Neurology, University Hospital, LMU Munich, 81377 Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), 81377 Munich, Germany
| | - Endy Weidinger
- Department of Neurology, University Hospital, LMU Munich, 81377 Munich, Germany
| | - Andreas Zwergal
- Department of Neurology, University Hospital, LMU Munich, 81377 Munich, Germany
- German Center for Vertigo and Balance Disorders (DSGZ), University Hospital, LMU Munich, 81377 Munich, Germany
| | - Sophia Stöcklein
- Department of Radiology, University Hospital, LMU Munich, 81377 Munich, Germany
| | - Robert Perneczky
- Munich Cluster for Systems Neurology (SyNergy), 81377 Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), 81377 Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, 80336 Munich, Germany
- Ageing Epidemiology (AGE) Research Unit, School of Public Health, Imperial College London, London SW7 2BX, UK
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield S10 2HQ, UK
| | - Henryk Barthel
- Department of Nuclear Medicine, University Hospital of Leipzig, 04103 Leipzig, Germany
| | - Osama Sabri
- Department of Nuclear Medicine, University Hospital of Leipzig, 04103 Leipzig, Germany
| | - Johannes Levin
- Department of Neurology, University Hospital, LMU Munich, 81377 Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), 81377 Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), 81377 Munich, Germany
| | - Günter U Höglinger
- Department of Neurology, University Hospital, LMU Munich, 81377 Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), 81377 Munich, Germany
| | - Nicolai Franzmeier
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, 81377 Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), 81377 Munich, Germany
- Department of Psychiatry and Neurochemistry, University of Gothenburg, The Sahlgrenska Academy, Institute of Neuroscience and Physiology, SE 413 90 Mölndal and Gothenburg, Sweden
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Sato SD, Shah VA, Fettrow T, Hall KG, Tays GD, Cenko E, Roy A, Clark DJ, Ferris DP, Hass CJ, Manini TM, Seidler RD. Resting state brain network segregation is associated with walking speed and working memory in older adults. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.07.592861. [PMID: 38766046 PMCID: PMC11100712 DOI: 10.1101/2024.05.07.592861] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Older adults exhibit larger individual differences in walking ability and cognitive function than young adults. Characterizing intrinsic brain connectivity differences in older adults across a wide walking performance spectrum may provide insight into the mechanisms of functional decline in some older adults and resilience in others. Thus, the objectives of this study were to: (1) determine whether young adults and high- and low-functioning older adults show group differences in brain network segregation, and (2) determine whether network segregation is associated with working memory and walking function in these groups. The analysis included 21 young adults and 81 older adults. Older adults were further categorized according to their physical function using a standardized assessment; 54 older adults had low physical function while 27 were considered high functioning. Structural and functional resting state magnetic resonance images were collected using a Siemens Prisma 3T scanner. Working memory was assessed with the NIH Toolbox list sorting test. Walking speed was assessed with a 400 m-walk test at participants' self-selected speed. We found that network segregation in mobility-related networks (sensorimotor, vestibular, and visual networks) was higher in younger adults compared to older adults. There were no group differences in laterality effects on network segregation. We found multivariate associations between working memory and walking speed with network segregation scores. Higher right anterior cingulate cortex network segregation was associated with higher working memory function. Higher right sensorimotor, right vestibular, right anterior cingulate cortex, and lower left anterior cingulate cortex network segregation was associated with faster walking speed. These results are unique and significant because they demonstrate higher network segregation is largely related to higher physical function and not age alone.
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Affiliation(s)
- Sumire D Sato
- Department of Applied Kinesiology and Physiology, University of Florida, Gainesville, FL, USA
| | - Valay A Shah
- Department of Applied Kinesiology and Physiology, University of Florida, Gainesville, FL, USA
| | - Tyler Fettrow
- Department of Applied Kinesiology and Physiology, University of Florida, Gainesville, FL, USA
- NASA Langley Research Center, Hampton, VA, USA
| | - Kristina G Hall
- Department of Applied Kinesiology and Physiology, University of Florida, Gainesville, FL, USA
| | - Grant D Tays
- Department of Applied Kinesiology and Physiology, University of Florida, Gainesville, FL, USA
| | - Erta Cenko
- Department of Epidemiology, College of Public Health and Health Professions, and College of Medicine, University of Florida, Gainesville, FL, USA
| | - Arkaprava Roy
- Department of Biostatistics, University of Florida, Gainesville, FL, USA
| | - David J Clark
- Department of Neurology, University of Florida, Gainesville, FL, USA
- Brain Rehabilitation Research Center, Malcom Randall VA Medical Center, Gainesville, FL, USA
| | - Daniel P Ferris
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA
| | - Chris J Hass
- Department of Applied Kinesiology and Physiology, University of Florida, Gainesville, FL, USA
| | - Todd M Manini
- Department of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, FL, USA
| | - Rachael D Seidler
- Department of Applied Kinesiology and Physiology, University of Florida, Gainesville, FL, USA
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Chan DC, Kim C, Kang RY, Kuhn MK, Beidler LM, Zhang N, Proctor EA. Cytokine expression patterns predict suppression of vulnerable neural circuits in a mouse model of Alzheimer's disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.17.585383. [PMID: 38559177 PMCID: PMC10979954 DOI: 10.1101/2024.03.17.585383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Alzheimer's disease is a neurodegenerative disorder characterized by progressive amyloid plaque accumulation, tau tangle formation, neuroimmune dysregulation, synapse an neuron loss, and changes in neural circuit activation that lead to cognitive decline and dementia. Early molecular and cellular disease-instigating events occur 20 or more years prior to presentation of symptoms, making them difficult to study, and for many years amyloid-β, the aggregating peptide seeding amyloid plaques, was thought to be the toxic factor responsible for cognitive deficit. However, strategies targeting amyloid-β aggregation and deposition have largely failed to produce safe and effective therapies, and amyloid plaque levels poorly correlate with cognitive outcomes. However, a role still exists for amyloid-β in the variation in an individual's immune response to early, soluble forms of aggregates, and the downstream consequences of this immune response for aberrant cellular behaviors and creation of a detrimental tissue environment that harms neuron health and causes changes in neural circuit activation. Here, we perform functional magnetic resonance imaging of awake, unanesthetized Alzheimer's disease mice to map changes in functional connectivity over the course of disease progression, in comparison to wild-type littermates. In these same individual animals, we spatiotemporally profile the immune milieu by measuring cytokines, chemokines, and growth factors across various brain regions and over the course of disease progression from pre-pathology through established cognitive deficit. We identify specific signatures of immune activation predicting hyperactivity followed by suppression of intra- and then inter-regional functional connectivity in multiple disease-relevant brain regions, following the pattern of spread of amyloid pathology.
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Affiliation(s)
- Dennis C Chan
- Department of Neurosurgery, Penn State College of Medicine, Hershey, PA, USA
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA, USA
- Department of Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
- Center for Neural Engineering, Pennsylvania State University, University Park, PA, USA
- Center for Neurotechnology in Mental Health Research, Pennsylvania State University, University Park, PA, USA
| | - ChaeMin Kim
- Department of Neurosurgery, Penn State College of Medicine, Hershey, PA, USA
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA, USA
| | - Rachel Y Kang
- Department of Neurosurgery, Penn State College of Medicine, Hershey, PA, USA
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA, USA
| | - Madison K Kuhn
- Department of Neurosurgery, Penn State College of Medicine, Hershey, PA, USA
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA, USA
- Department of Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
- Center for Neural Engineering, Pennsylvania State University, University Park, PA, USA
| | - Lynne M Beidler
- Department of Neurosurgery, Penn State College of Medicine, Hershey, PA, USA
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA, USA
| | - Nanyin Zhang
- Department of Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
- Center for Neural Engineering, Pennsylvania State University, University Park, PA, USA
- Center for Neurotechnology in Mental Health Research, Pennsylvania State University, University Park, PA, USA
| | - Elizabeth A Proctor
- Department of Neurosurgery, Penn State College of Medicine, Hershey, PA, USA
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA, USA
- Department of Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
- Center for Neural Engineering, Pennsylvania State University, University Park, PA, USA
- Department of Engineering Science & Mechanics, Pennsylvania State University, University Park, PA, USA
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Raykov PP, Knights E, Cam-Can, Henson RN. Does functional system segregation mediate the effects of lifestyle on cognition in older adults? Neurobiol Aging 2024; 134:126-134. [PMID: 38070445 PMCID: PMC10789480 DOI: 10.1016/j.neurobiolaging.2023.11.009] [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: 06/20/2023] [Revised: 11/22/2023] [Accepted: 11/22/2023] [Indexed: 01/02/2024]
Abstract
Healthy aging is typically accompanied by cognitive decline. Previous work has shown that engaging in multiple, non-work activities during midlife can have a protective effect on cognition several decades later, rendering it less dependent on brain structural health; the definition of "cognitive reserve". Other work has shown that increasing age is associated with reduced segregation of large-scale brain functional networks. Here we tested the hypothesis that functional segregation (SyS) mediates this effect of middle-aged lifestyle on late-life cognition. We used fMRI data from three tasks in the CamCAN dataset, together with cognitive data on fluid intelligence, episodic memory, and retrospective lifestyle data from the Lifetime of Experiences Questionnaire (LEQ). In all three tasks, we showed that SyS related to fluid intelligence even after adjusting for the (nonlinear) age effects. However, we found no evidence that SyS in late-life mediated the relationship between non-specific (non-occupation) midlife activities and either measure of cognition in late-life. Thus, the brain correlates of cognitive reserve arising from mid-life activities remain to be discovered.
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Affiliation(s)
- Petar P Raykov
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, UK.
| | - Ethan Knights
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, UK
| | - Cam-Can
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, UK; Department of Psychiatry, University of Cambridge, UK
| | - Richard N Henson
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, UK; Department of Psychiatry, University of Cambridge, UK
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Reas ET, Triebswetter C, Banks SJ, McEvoy LK. Effects of APOE2 and APOE4 on brain microstructure in older adults: modification by age, sex, and cognitive status. Alzheimers Res Ther 2024; 16:7. [PMID: 38212861 PMCID: PMC10782616 DOI: 10.1186/s13195-023-01380-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: 08/25/2023] [Accepted: 12/30/2023] [Indexed: 01/13/2024]
Abstract
BACKGROUND APOE4 is the strongest genetic risk factor for sporadic Alzheimer's disease (AD), whereas APOE2 confers protection. However, effects of APOE on neurodegeneration in cognitively intact individuals, and how these associations evolve with cognitive decline, are unclear. Furthermore, few studies have evaluated whether effects of APOE on neurodegenerative changes are modified by other AD key risk factors including age and sex. METHODS Participants included older adults (57% women; 77 ± 7 years) from the Rancho Bernardo Study of Health Aging and the University of California San Diego Alzheimer's Disease Research Center, including 192 cognitively normal (CN) individuals and 33 with mild cognitive impairment. Participants underwent diffusion MRI, and multicompartment restriction spectrum imaging (RSI) metrics were computed in white matter, gray matter, and subcortical regions of interest. Participants were classified as APOE4 carriers, APOE2 carriers, and APOE3 homozygotes. Analysis of covariance among CN (adjusting for age, sex, and scanner) assessed differences in brain microstructure by APOE, as well as interactions between APOE and sex. Analyses across all participants examined interactions between APOE4 and cognitive status. Linear regressions assessed APOE by age interactions. RESULTS Among CN, APOE4 carriers showed lower entorhinal cortex neurite density than non-carriers, whereas APOE2 carriers showed lower cingulum neurite density than non-carriers. Differences in entorhinal microstructure by APOE4 and in entorhinal and cingulum microstructure by APOE2 were present for women only. Age correlated with lower entorhinal restricted isotropic diffusion among APOE4 non-carriers, whereas age correlated with lower putamen restricted isotropic diffusion among APOE4 carriers. Differences in microstructure between cognitively normal and impaired participants were stronger for APOE4-carriers in medial temporal regions, thalamus, and global gray matter, but stronger for non-carriers in caudate. CONCLUSIONS The entorhinal cortex may be an early target of neurodegenerative changes associated with APOE4 in presymptomatic individuals, whereas APOE2 may support beneficial white matter and entorhinal microstructure, with potential sex differences that warrant further investigation. APOE modifies microstructural patterns associated with aging and cognitive impairment, which may advance the development of biomarkers to distinguish microstructural changes characteristic of normal brain aging, APOE-dependent pathways, and non-AD etiologies.
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Affiliation(s)
- Emilie T Reas
- Department of Neurosciences, University of California, San Diego, Mail Code 0841, UCSD,9500 Gilman Dr., La Jolla, San Diego, CA, 92093-0841, USA.
| | - Curtis Triebswetter
- Department of Neurosciences, University of California, San Diego, Mail Code 0841, UCSD,9500 Gilman Dr., La Jolla, San Diego, CA, 92093-0841, USA
| | - Sarah J Banks
- Department of Neurosciences, University of California, San Diego, Mail Code 0841, UCSD,9500 Gilman Dr., La Jolla, San Diego, CA, 92093-0841, USA
| | - Linda K McEvoy
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
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Franzmeier N, Dehsarvi A, Steward A, Biel D, Dewenter A, Roemer SN, Wagner F, Groß M, Brendel M, Moscoso A, Arunachalam P, Blennow K, Zetterberg H, Ewers M, Schöll M. Elevated CSF GAP-43 is associated with accelerated tau accumulation and spread in Alzheimer's disease. Nat Commun 2024; 15:202. [PMID: 38172114 PMCID: PMC10764818 DOI: 10.1038/s41467-023-44374-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: 08/08/2023] [Accepted: 12/11/2023] [Indexed: 01/05/2024] Open
Abstract
In Alzheimer's disease, amyloid-beta (Aβ) triggers the trans-synaptic spread of tau pathology, and aberrant synaptic activity has been shown to promote tau spreading. Aβ induces aberrant synaptic activity, manifesting in increases in the presynaptic growth-associated protein 43 (GAP-43), which is closely involved in synaptic activity and plasticity. We therefore tested whether Aβ-related GAP-43 increases, as a marker of synaptic changes, drive tau spreading in 93 patients across the aging and Alzheimer's spectrum with available CSF GAP-43, amyloid-PET and longitudinal tau-PET assessments. We found that (1) higher GAP-43 was associated with faster Aβ-related tau accumulation, specifically in brain regions connected closest to subject-specific tau epicenters and (2) that higher GAP-43 strengthened the association between Aβ and connectivity-associated tau spread. This suggests that GAP-43-related synaptic changes are linked to faster Aβ-related tau spread across connected regions and that synapses could be key targets for preventing tau spreading in Alzheimer's disease.
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Affiliation(s)
- Nicolai Franzmeier
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany.
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.
- University of Gothenburg, The Sahlgrenska Academy, Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Mölndal and Gothenburg, Sweden.
| | - Amir Dehsarvi
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Anna Steward
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Davina Biel
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Anna Dewenter
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Sebastian Niclas Roemer
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Fabian Wagner
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Mattes Groß
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Matthias Brendel
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Alexis Moscoso
- University of Gothenburg, The Sahlgrenska Academy, Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Mölndal and Gothenburg, Sweden
| | - Prithvi Arunachalam
- University of Gothenburg, The Sahlgrenska Academy, Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Mölndal and Gothenburg, Sweden
| | - Kaj Blennow
- University of Gothenburg, The Sahlgrenska Academy, Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Mölndal and Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- University of Gothenburg, The Sahlgrenska Academy, Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Mölndal and Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, 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
| | - Michael Ewers
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Michael Schöll
- University of Gothenburg, The Sahlgrenska Academy, Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Mölndal and Gothenburg, Sweden
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK
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7
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Veitch DP, Weiner MW, Miller M, Aisen PS, Ashford MA, Beckett LA, Green RC, Harvey D, Jack CR, Jagust W, Landau SM, Morris JC, Nho KT, Nosheny R, Okonkwo O, Perrin RJ, Petersen RC, Rivera Mindt M, Saykin A, Shaw LM, Toga AW, Tosun D. The Alzheimer's Disease Neuroimaging Initiative in the era of Alzheimer's disease treatment: A review of ADNI studies from 2021 to 2022. Alzheimers Dement 2024; 20:652-694. [PMID: 37698424 PMCID: PMC10841343 DOI: 10.1002/alz.13449] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 07/27/2023] [Accepted: 08/01/2023] [Indexed: 09/13/2023]
Abstract
The Alzheimer's Disease Neuroimaging Initiative (ADNI) aims to improve Alzheimer's disease (AD) clinical trials. Since 2006, ADNI has shared clinical, neuroimaging, and cognitive data, and biofluid samples. We used conventional search methods to identify 1459 publications from 2021 to 2022 using ADNI data/samples and reviewed 291 impactful studies. This review details how ADNI studies improved disease progression understanding and clinical trial efficiency. Advances in subject selection, detection of treatment effects, harmonization, and modeling improved clinical trials and plasma biomarkers like phosphorylated tau showed promise for clinical use. Biomarkers of amyloid beta, tau, neurodegeneration, inflammation, and others were prognostic with individualized prediction algorithms available online. Studies supported the amyloid cascade, emphasized the importance of neuroinflammation, and detailed widespread heterogeneity in disease, linked to genetic and vascular risk, co-pathologies, sex, and resilience. Biological subtypes were consistently observed. Generalizability of ADNI results is limited by lack of cohort diversity, an issue ADNI-4 aims to address by enrolling a diverse cohort.
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Affiliation(s)
- Dallas P. Veitch
- Department of Veterans Affairs Medical CenterNorthern California Institute for Research and Education (NCIRE)San FranciscoCaliforniaUSA
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA
| | - Michael W. Weiner
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA
- Department of Radiology and Biomedical ImagingUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of MedicineUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of Psychiatry and Behavioral SciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Melanie Miller
- Department of Veterans Affairs Medical CenterNorthern California Institute for Research and Education (NCIRE)San FranciscoCaliforniaUSA
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA
| | - Paul S. Aisen
- Alzheimer's Therapeutic Research InstituteUniversity of Southern CaliforniaSan DiegoCaliforniaUSA
| | - Miriam A. Ashford
- Department of Veterans Affairs Medical CenterNorthern California Institute for Research and Education (NCIRE)San FranciscoCaliforniaUSA
| | - Laurel A. Beckett
- Division of BiostatisticsDepartment of Public Health SciencesUniversity of CaliforniaDavisCaliforniaUSA
| | - Robert C. Green
- Division of GeneticsDepartment of MedicineBrigham and Women's HospitalBroad Institute Ariadne Labs and Harvard Medical SchoolBostonMassachusettsUSA
| | - Danielle Harvey
- Division of BiostatisticsDepartment of Public Health SciencesUniversity of CaliforniaDavisCaliforniaUSA
| | | | - William Jagust
- Helen Wills Neuroscience InstituteUniversity of California BerkeleyBerkeleyCaliforniaUSA
| | - Susan M. Landau
- Helen Wills Neuroscience InstituteUniversity of California BerkeleyBerkeleyCaliforniaUSA
| | - John C. Morris
- Knight Alzheimer's Disease Research CenterWashington University School of MedicineSaint LouisMissouriUSA
- Department of NeurologyWashington University School of MedicineSaint LouisMissouriUSA
- Department of Pathology and ImmunologyWashington University School of MedicineSaint LouisMissouriUSA
| | - Kwangsik T. Nho
- Department of Radiology and Imaging Sciences and the Indiana Alzheimer's Disease Research CenterIndiana University School of MedicineIndianapolisIndianaUSA
- Center for Computational Biology and BioinformaticsIndiana University School of MedicineIndianapolisIndianaUSA
| | - Rachel Nosheny
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA
- Department of Psychiatry and Behavioral SciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Ozioma Okonkwo
- Wisconsin Alzheimer's Disease Research Center and Department of MedicineUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Richard J. Perrin
- Knight Alzheimer's Disease Research CenterWashington University School of MedicineSaint LouisMissouriUSA
- Department of NeurologyWashington University School of MedicineSaint LouisMissouriUSA
- Department of Pathology and ImmunologyWashington University School of MedicineSaint LouisMissouriUSA
| | | | - Monica Rivera Mindt
- Department of PsychologyLatin American and Latino Studies InstituteAfrican and African American StudiesFordham UniversityNew YorkNew YorkUSA
- Department of NeurologyIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Andrew Saykin
- Department of Radiology and Imaging Sciences and the Indiana Alzheimer's Disease Research CenterIndiana University School of MedicineIndianapolisIndianaUSA
- Department of Medical and Molecular GeneticsIndiana University School of MedicineIndianapolisIndianaUSA
| | - Leslie M. Shaw
- Department of Pathology and Laboratory Medicine and the PENN Alzheimer's Disease Research CenterCenter for Neurodegenerative ResearchPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Arthur W. Toga
- Laboratory of Neuro ImagingInstitute of Neuroimaging and InformaticsKeck School of Medicine of University of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Duygu Tosun
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA
- Department of Radiology and Biomedical ImagingUniversity of CaliforniaSan FranciscoCaliforniaUSA
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8
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Zhang Z, Chan MY, Han L, Carreno CA, Winter-Nelson E, Wig GS. Dissociable Effects of Alzheimer's Disease-Related Cognitive Dysfunction and Aging on Functional Brain Network Segregation. J Neurosci 2023; 43:7879-7892. [PMID: 37714710 PMCID: PMC10648516 DOI: 10.1523/jneurosci.0579-23.2023] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 09/03/2023] [Accepted: 09/11/2023] [Indexed: 09/17/2023] Open
Abstract
Alzheimer's disease (AD) is associated with changes in large-scale functional brain network organization. Individuals with AD exhibit less segregated resting-state brain networks compared with individuals without dementia. However, declines in brain network segregation are also evident as adult individuals grow older. Determining whether these observations reflect unique or overlapping alterations on the functional connectome of the brain is essential for understanding the impact of AD on network organization and incorporating measures of functional brain network organization toward AD characterization. Relationships between AD dementia severity and participant's age on resting-state brain system segregation were examined in 326 cognitively healthy and 275 cognitively impaired human individuals recruited through the Alzheimer's Disease Neuroimaging Initiative (ADNI) (N = 601; age range, 55-96 years; 320 females). Greater dementia severity and increasing age were independently associated with lower brain system segregation. Further, dementia versus age relationships with brain network organization varied according to the processing roles of brain systems and types of network interactions. Aging was associated with alterations to association systems, primarily among within-system relationships. Conversely, dementia severity was associated with alterations that included both association systems and sensory-motor systems and was most prominent among cross-system interactions. Dementia-related network alterations were evident regardless of the presence of cortical amyloid burden, revealing that the measures of functional network organization are unique from this marker of AD-related pathology. Collectively, these observations demonstrate the specific and widespread alterations in the topological organization of large-scale brain networks that accompany AD and highlight functionally dissociable brain network vulnerabilities associated with AD-related cognitive dysfunction versus aging.SIGNIFICANCE STATEMENT Alzheimer's disease (AD)-associated cognitive dysfunction is hypothesized to be a consequence of brain network damage. It is unclear exactly how brain network alterations vary with dementia severity and whether they are distinct from alterations associated with aging. We evaluated functional brain network organization measured at rest among individuals who varied in age and dementia status. AD and aging exerted dissociable impacts on the brain's functional connectome. AD-associated brain network alterations were widespread and involved systems that subserve not only higher-order cognitive operations, but also sensory and motor operations. Notably, AD-related network alterations were independent of amyloid pathology. The research furthers our understanding of AD-related brain dysfunction and motivates refining existing frameworks of dementia characterization with measures of functional network organization.
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Affiliation(s)
- Ziwei Zhang
- Center for Vital Longevity and School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, Texas 75235
| | - Micaela Y Chan
- Center for Vital Longevity and School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, Texas 75235
| | - Liang Han
- Center for Vital Longevity and School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, Texas 75235
| | - Claudia A Carreno
- Center for Vital Longevity and School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, Texas 75235
| | - Ezra Winter-Nelson
- Center for Vital Longevity and School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, Texas 75235
| | - Gagan S Wig
- Center for Vital Longevity and School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, Texas 75235
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas 75390
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9
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Sintini I, Graff-Radford J, Schwarz CG, Machulda MM, Singh NA, Carlos AF, Senjem ML, Jack CR, Lowe VJ, Josephs KA, Whitwell JL. Longitudinal rates of atrophy and tau accumulation differ between the visual and language variants of atypical Alzheimer's disease. Alzheimers Dement 2023; 19:4396-4406. [PMID: 37485642 PMCID: PMC10592409 DOI: 10.1002/alz.13396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 05/19/2023] [Accepted: 06/19/2023] [Indexed: 07/25/2023]
Abstract
INTRODUCTION Atypical variants of Alzheimer's disease (AD) include the visual variant, known as posterior cortical atrophy (PCA), and the language variant, known as logopenic progressive aphasia (LPA). Clinically, rates of disease progression differ between them. METHODS We evaluated 34 PCA and 29 LPA participants. Structural magnetic resonance imaging and 18 F-flortaucipir positron emission tomography were performed at baseline and at 1-year follow-up. Rates of change in tau uptake and grey matter volumes were compared between PCA and LPA with linear mixed-effects models and voxel-based analyses. RESULTS PCA had faster rates of occipital atrophy. LPA had faster rates of left temporal atrophy and faster rates of tau accumulation in the parietal, right temporal, and occipital lobes. Age was negatively associated with rates of atrophy and tau accumulation. DISCUSSION Longitudinal patterns of neuroimaging abnormalities differed between PCA and LPA, although with divergent results for tau accumulation and atrophy. HIGHLIGHTS The language variant of Alzheimer's disease accumulates tau faster than the visual variant. Each variant shows faster rates of atrophy than the other in its signature regions. Age negatively influences rates of atrophy and tau accumulation in both variants.
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Affiliation(s)
- Irene Sintini
- Department of Radiology, Mayo Clinic, Rochester, MN, USA, 55905
| | | | | | - Mary M. Machulda
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester MN, USA, 55905
| | | | - Arenn F. Carlos
- Department of Neurology, Mayo Clinic, Rochester, MN, USA, 55905
| | - Matthew L. Senjem
- Department of Radiology, Mayo Clinic, Rochester, MN, USA, 55905
- Department of Information Technology, Mayo Clinic, Rochester, MN, USA, 55905
| | | | - Val J. Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN, USA, 55905
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10
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Mijalkov M, Veréb D, Canal-Garcia A, Hinault T, Volpe G, Pereira JB. Nonlinear changes in delayed functional network topology in Alzheimer's disease: relationship with amyloid and tau pathology. Alzheimers Res Ther 2023; 15:112. [PMID: 37328909 DOI: 10.1186/s13195-023-01252-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 05/31/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND Alzheimer's disease is a neurodegenerative disorder associated with the abnormal deposition of pathological processes, such as amyloid-ß and tau, which produces nonlinear changes in the functional connectivity patterns between different brain regions across the Alzheimer's disease continuum. However, the mechanisms underlying these nonlinear changes remain largely unknown. Here, we address this question using a novel method based on temporal or delayed correlations and calculate new whole-brain functional networks to tackle these mechanisms. METHODS To assess our method, we evaluated 166 individuals from the ADNI database, including amyloid-beta negative and positive cognitively normal subjects, patients with mild cognitive impairment, and patients with Alzheimer's disease dementia. We used the clustering coefficient and the global efficiency to measure the functional network topology and assessed their relationship with amyloid and tau pathology measured by positron emission tomography, as well as cognitive performance using tests measuring memory, executive function, attention, and global cognition. RESULTS Our study found nonlinear changes in the global efficiency, but not in the clustering coefficient, showing that the nonlinear changes in functional connectivity are due to an altered ability of brain regions to communicate with each other through direct paths. These changes in global efficiency were most prominent in early disease stages. However, later stages of Alzheimer's disease were associated with widespread network disruptions characterized by changes in both network measures. The temporal delays required for the detection of these changes varied across the Alzheimer's disease continuum, with shorter delays necessary to detect changes in early stages and longer delays necessary to detect changes in late stages. Both global efficiency and clustering coefficient showed quadratic associations with pathological amyloid and tau burden as well as cognitive decline. CONCLUSIONS This study suggests that global efficiency is a more sensitive indicator of network changes in Alzheimer's disease when compared to clustering coefficient. Both network properties were associated with pathology and cognitive performance, demonstrating their relevance in clinical settings. Our findings provide an insight into the mechanisms underlying nonlinear changes in functional network organization in Alzheimer's disease, suggesting that it is the lack of direct connections that drives these functional changes.
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Affiliation(s)
- Mite Mijalkov
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
| | - Dániel Veréb
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Anna Canal-Garcia
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Thomas Hinault
- Normandie Univ, Unicaen, PSL, Université Paris, EPHE, Inserm, U1077, CHU de Caen, Centre Cyceron, 14000, Caen, France
| | - Giovanni Volpe
- Department of Physics, Goteborg University, Goteborg, Sweden
| | - Joana B Pereira
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
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