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A 5-year longitudinal evaluation in patients with mild cognitive impairment by 11C-PIB PET/CT: a visual analysis. Nucl Med Commun 2019; 40:525-531. [PMID: 30973840 DOI: 10.1097/mnm.0000000000001004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
OBJECTIVE The aim of this study was to evaluate the cerebral amyloid distribution in patients with mild cognitive impairment (MCI), assessed by carbon-11-Pittsburgh compound B (C-PIB) PET/CT, after 5 years of follow-up. PATIENTS AND METHODS Ten amnestic MCI (A-MCI) and four nonamnestic (NA-MCI) patients were studied by C-PIB PET/CT and re-evaluated 5 years later by a new C-PIB PET/CT. PET/CT scans were acquired 60-90 min after the administration of 555 MBq C-PIB and analyzed visually, to obtain a score of the cerebral cortical C-PIB retention in the frontal, basal ganglia (BG), temporoparietal (TP), occipital, posterior cingulate, and cerebellum areas. Initial and 5-year follow-up C-PIB retentions were compared. RESULTS Initially, 9/10 A-MCI patients were C-PIB positive and one was C-PIB negative. All four NA-MCI patients were C-PIB negative. Of the C-PIB-positive A-MCI patients, seven progressed to Alzheimer's disease dementia (AD-D), one to mixed dementia and one remained as A-MCI. The C-PIB-negative A-MCI patient remained as A-MCI. Of the four C-PIB-negative NA-MCI, one progressed to semantic dementia. All changes in C-PIB retention were of low intensity. The A-MCI patients who progressed to AD-D (n=7) showed an increase in C-PIB retention in the frontal (5/7), BG (3/7), TP (3/7), occipital (1/7), and posterior cingulate (1/7) regions. The A-MCI patient who progressed to mix dementia showed an increase in C-PIB retention in the frontal region. The C-PIB-positive A-MCI patient who remained as A-MCI showed an increase in C-PIB retention in the frontal, BG, and TP areas. The amyloid deposition in the anterior part of the brain (frontal, TP, and BG) increased more than that in the posterior part (occipital and precuneus) (7/9 vs. 2/9; P<0.05). CONCLUSION PIB retention increased predominantly in the frontal, BG, and TP areas. C-PIB-positive A-MCI patients mostly progressed to AD-D, showing similar topographic changes in their cerebral C-PIB pattern than the patient who remained as A-MCI.
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202
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Meyer PF, McSweeney M, Gonneaud J, Villeneuve S. AD molecular: PET amyloid imaging across the Alzheimer's disease spectrum: From disease mechanisms to prevention. PROGRESS IN MOLECULAR BIOLOGY AND TRANSLATIONAL SCIENCE 2019; 165:63-106. [PMID: 31481172 DOI: 10.1016/bs.pmbts.2019.05.001] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
The advent of amyloid-beta (Aβ) positron emission tomography (PET) imaging has transformed the field of Alzheimer's disease (AD) by enabling the quantification of cortical Aβ accumulation and propagation in vivo. This revolutionary tool has made it possible to measure direct associations between Aβ and other AD biomarkers, to identify factors that influence Aβ accumulation and to redefine entry criteria into clinical trials as well as measure drug target engagement. This chapter summarizes the main findings on the associations of Aβ with other biomarkers of disease progression across the AD spectrum. It discusses investigations of the timing at which Aβ pathology starts to accumulate, demonstrates the clinical utility of Aβ PET imaging and discusses some ethical implications. Finally, it presents genetic and potentially modifiable lifestyle factors that might influence Aβ accumulation and therefore be targets for AD prevention.
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Affiliation(s)
- Pierre-François Meyer
- Centre for Studies on the Prevention of Alzheimer's Disease, Douglas Mental Health University Institute, Montréal, Canada; McGill University, Montréal, Canada
| | - Melissa McSweeney
- Centre for Studies on the Prevention of Alzheimer's Disease, Douglas Mental Health University Institute, Montréal, Canada; McGill University, Montréal, Canada
| | - Julie Gonneaud
- Centre for Studies on the Prevention of Alzheimer's Disease, Douglas Mental Health University Institute, Montréal, Canada; McGill University, Montréal, Canada
| | - Sylvia Villeneuve
- Centre for Studies on the Prevention of Alzheimer's Disease, Douglas Mental Health University Institute, Montréal, Canada; McGill University, Montréal, Canada.
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203
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NIA-AA Research Framework: Toward a biological definition of Alzheimer's disease. Alzheimers Dement 2019; 14:535-562. [PMID: 29653606 PMCID: PMC5958625 DOI: 10.1016/j.jalz.2018.02.018] [Citation(s) in RCA: 5465] [Impact Index Per Article: 1093.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2018] [Revised: 02/21/2018] [Accepted: 02/27/2018] [Indexed: 02/06/2023]
Abstract
In 2011, the National Institute on Aging and Alzheimer’s Association created separate diagnostic recommendations for the preclinical, mild cognitive impairment, and dementia stages of Alzheimer’s disease. Scientific progress in the interim led to an initiative by the National Institute on Aging and Alzheimer’s Association to update and unify the 2011 guidelines. This unifying update is labeled a “research framework” because its intended use is for observational and interventional research, not routine clinical care. In the National Institute on Aging and Alzheimer’s Association Research Framework, Alzheimer’s disease (AD) is defined by its underlying pathologic processes that can be documented by postmortem examination or in vivo by biomarkers. The diagnosis is not based on the clinical consequences of the disease (i.e., symptoms/signs) in this research framework, which shifts the definition of AD in living people from a syndromal to a biological construct. The research framework focuses on the diagnosis of AD with biomarkers in living persons. Biomarkers are grouped into those of β amyloid deposition, pathologic tau, and neurodegeneration [AT(N)]. This ATN classification system groups different biomarkers (imaging and biofluids) by the pathologic process each measures. The AT(N) system is flexible in that new biomarkers can be added to the three existing AT(N) groups, and new biomarker groups beyond AT(N) can be added when they become available. We focus on AD as a continuum, and cognitive staging may be accomplished using continuous measures. However, we also outline two different categorical cognitive schemes for staging the severity of cognitive impairment: a scheme using three traditional syndromal categories and a six-stage numeric scheme. It is important to stress that this framework seeks to create a common language with which investigators can generate and test hypotheses about the interactions among different pathologic processes (denoted by biomarkers) and cognitive symptoms. We appreciate the concern that this biomarker-based research framework has the potential to be misused. Therefore, we emphasize, first, it is premature and inappropriate to use this research framework in general medical practice. Second, this research framework should not be used to restrict alternative approaches to hypothesis testing that do not use biomarkers. There will be situations where biomarkers are not available or requiring them would be counterproductive to the specific research goals (discussed in more detail later in the document). Thus, biomarker-based research should not be considered a template for all research into age-related cognitive impairment and dementia; rather, it should be applied when it is fit for the purpose of the specific research goals of a study. Importantly, this framework should be examined in diverse populations. Although it is possible that β-amyloid plaques and neurofibrillary tau deposits are not causal in AD pathogenesis, it is these abnormal protein deposits that define AD as a unique neurodegenerative disease among different disorders that can lead to dementia. We envision that defining AD as a biological construct will enable a more accurate characterization and understanding of the sequence of events that lead to cognitive impairment that is associated with AD, as well as the multifactorial etiology of dementia. This approach also will enable a more precise approach to interventional trials where specific pathways can be targeted in the disease process and in the appropriate people.
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204
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Bischof GN, Jacobs HIL. Subthreshold amyloid and its biological and clinical meaning: Long way ahead. Neurology 2019; 93:72-79. [PMID: 31167933 DOI: 10.1212/wnl.0000000000007747] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Accepted: 03/26/2019] [Indexed: 01/22/2023] Open
Abstract
The development of in vivo imaging of the pathologic hallmark of Alzheimer disease (AD), β-amyloid (Aβ), altered the framing of its pathophysiology and formulation of inclusion criteria for clinical trials. Recent evidence suggests that in vivo measures of Aβ deposition below a threshold indicative of Aβ positivity carry critical information on future cognitive decline and accumulation of AD pathology, potentially already at a younger age. Here, we integrate the existing literature on histopathology of Aβ and its convergence and divergence with in vivo Aβ imaging. The evidence presented amounts to a reconceptualization, in which we advocate for a closer look into Aβ accumulation rates in earlier life, the factors that promote accumulation, comparative studies with different markers of Aβ, and longitudinal designs to elucidate when AD pathology rises and how it shifts from benign to malignant stages that ultimately define AD. These efforts open a new window of opportunity for disease-modifying interventions.
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Affiliation(s)
- Gérard N Bischof
- From the Multimodal Imaging Group (G.N.B.), Department of Nuclear Medicine, University Hospital Cologne, Germany; Cognitive Neuroscience (H.I.L.J.), Faculty of Psychology and Neuroscience, and School for Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Alzheimer Centre Limburg, Maastricht University, the Netherlands; and Department of Radiology, Division of Nuclear Medicine and Molecular Imaging, Harvard Medical School, Massachusetts General Hospital, Boston.
| | - Heidi I L Jacobs
- From the Multimodal Imaging Group (G.N.B.), Department of Nuclear Medicine, University Hospital Cologne, Germany; Cognitive Neuroscience (H.I.L.J.), Faculty of Psychology and Neuroscience, and School for Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Alzheimer Centre Limburg, Maastricht University, the Netherlands; and Department of Radiology, Division of Nuclear Medicine and Molecular Imaging, Harvard Medical School, Massachusetts General Hospital, Boston
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205
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Putcha D, Brickhouse M, Touroutoglou A, Collins JA, Quimby M, Wong B, Eldaief M, Schultz A, El Fakhri G, Johnson K, Dickerson BC, McGinnis SM. Visual cognition in non-amnestic Alzheimer's disease: Relations to tau, amyloid, and cortical atrophy. Neuroimage Clin 2019; 23:101889. [PMID: 31200149 PMCID: PMC6562373 DOI: 10.1016/j.nicl.2019.101889] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2019] [Revised: 05/28/2019] [Accepted: 06/01/2019] [Indexed: 12/15/2022]
Abstract
Heterogeneity within the Alzheimer's disease (AD) syndromic spectrum is typically classified in a domain-specific manner (e.g., language vs. visual cognitive function). The central aim of this study was to investigate whether impairment in visual cognitive tasks thought to be subserved by posterior cortical dysfunction in non-amnestic AD presentations is associated with tau, amyloid, or neurodegeneration in those regions using 18F-AV-1451 and 11C-PiB positron emission tomography (PET) and magnetic resonance imaging (MRI). Sixteen amyloid-positive patients who met criteria for either Posterior Cortical Atrophy (PCA; n = 10) or logopenic variant Primary Progressive Aphasia (lvPPA; n = 6) were studied. All participants underwent a structured clinical assessment, neuropsychological battery, structural MRI, amyloid PET, and tau PET. The neuropsychological battery included two visual cognitive tests: VOSP Number Location and Benton Facial Recognition. Surface-based whole-cortical general linear models were used to first explore the similarities and differences between these biomarkers in the two patient groups, and then to assess their regional associations with visual cognitive test performance. The results show that these two variants of AD have both dissociable and overlapping areas of tau and atrophy, but amyloid is distributed with a stereotyped localization in both variants. Performance on both visual cognitive tests were associated with tau and atrophy in the right lateral and medial occipital association cortex, superior parietal cortex, and posterior ventral occipitotemporal cortex. No cortical associations were observed with amyloid PET. We further demonstrate that cortical atrophy has a partially mediating effect on the association between tau pathology and visual cognitive task performance. Our findings show that non-amnestic variants of AD have partially dissociable spatial patterns of tau and atrophy that localize as expected based on symptoms, but similar patterns of amyloid. Further, we demonstrate that impairments of visual cognitive dysfunction are strongly associated with tau in visual cortical regions and mediated in part by atrophy.
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Affiliation(s)
- Deepti Putcha
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
| | - Michael Brickhouse
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Alexandra Touroutoglou
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Jessica A Collins
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Megan Quimby
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Bonnie Wong
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Mark Eldaief
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Aaron Schultz
- Alzheimer's Disease Research Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Georges El Fakhri
- Gordon Center for Medical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Keith Johnson
- Alzheimer's Disease Research Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Gordon Center for Medical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Bradford C Dickerson
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Alzheimer's Disease Research Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Scott M McGinnis
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
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206
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Rahayel S, Bocti C, Sévigny Dupont P, Joannette M, Lavallée MM, Nikelski J, Chertkow H, Joubert S. Subcortical amyloid load is associated with shape and volume in cognitively normal individuals. Hum Brain Mapp 2019; 40:3951-3965. [PMID: 31148327 DOI: 10.1002/hbm.24680] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2018] [Revised: 05/09/2019] [Accepted: 05/21/2019] [Indexed: 01/18/2023] Open
Abstract
Amyloid-beta (Aβ) deposition is one of the main hallmarks of Alzheimer's disease. The study assessed the associations between cortical and subcortical 11 C-Pittsburgh Compound B (PiB) retention, namely, in the hippocampus, amygdala, putamen, caudate, pallidum, and thalamus, and subcortical morphology in cognitively normal individuals. We recruited 104 cognitive normal individuals who underwent extensive neuropsychological assessment, PiB-positron emission tomography (PET) scan, and 3-T magnetic resonance imaging (MRI) acquisition of T1-weighted images. Global, cortical, and subcortical regional PiB retention values were derived from each scan and subcortical morphology analyses were performed to investigate vertex-wise local surface and global volumes, including the hippocampal subfields volumes. We found that subcortical regional Aβ was associated with the surface of the hippocampus, thalamus, and pallidum, with changes being due to volume and shape. Hippocampal Aβ was marginally associated with volume of the whole hippocampus as well as with the CA1 subfield, subiculum, and molecular layer. Participants showing higher subcortical Aβ also showed worse cognitive performance and smaller hippocampal volumes. In contrast, global and cortical PiB uptake did not associate with any subcortical metrics. This study shows that subcortical Aβ is associated with subcortical surface morphology in cognitively normal individuals. This study highlights the importance of quantifying subcortical regional PiB retention values in these individuals.
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Affiliation(s)
- Shady Rahayel
- Department of Psychology, Université de Montréal, Montreal, Canada.,Research Centre, Institut universitaire de gériatrie de Montréal, Montreal, Canada
| | - Christian Bocti
- Department of Neurology, Université de Sherbrooke, Sherbrooke, Canada
| | - Pénélope Sévigny Dupont
- Department of Psychology, Université de Montréal, Montreal, Canada.,Research Centre, Institut universitaire de gériatrie de Montréal, Montreal, Canada
| | - Maude Joannette
- Department of Psychology, Université de Montréal, Montreal, Canada.,Research Centre, Institut universitaire de gériatrie de Montréal, Montreal, Canada
| | - Marie Maxime Lavallée
- Department of Psychology, Université de Montréal, Montreal, Canada.,Research Centre, Institut universitaire de gériatrie de Montréal, Montreal, Canada
| | - Jim Nikelski
- Lady Davis Institute for Medical Research, Jewish General Hospital, McGill University, Montreal, Canada
| | - Howard Chertkow
- Lady Davis Institute for Medical Research, Jewish General Hospital, McGill University, Montreal, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
| | - Sven Joubert
- Department of Psychology, Université de Montréal, Montreal, Canada.,Research Centre, Institut universitaire de gériatrie de Montréal, Montreal, Canada
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207
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Kreisl WC, Jin P, Lee S, Dayan ER, Vallabhajosula S, Pelton G, Luchsinger JA, Pradhaban G, Devanand DP. Odor Identification Ability Predicts PET Amyloid Status and Memory Decline in Older Adults. J Alzheimers Dis 2019; 62:1759-1766. [PMID: 29614678 DOI: 10.3233/jad-170960] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
BACKGROUND Odor identification deficits occur in Alzheimer's disease (AD), as measured by the 40-item University of Pennsylvania Smell Identification Test (UPSIT). OBJECTIVE To determine if UPSIT scores predict amyloid-β (Aβ) status, determined by 11C-Pittsburgh Compound B PET. We also compared UPSIT scores to Aβ status in predicting future memory decline. METHODS Subjects were recruited into a longitudinal clinical prediction study. We analyzed data from those who had UPSIT, cognitive testing, PIB PET, and at least 12 months' clinical follow-up. Forty-six amnestic mild cognitive impairment patients and 25 cognitively normal controls were included. Amyloid-positivity was defined as composite PIB standardized uptake value ratio >1.5. Logistic regression and Receiver Operating Characteristic Curve analyses tested the predictive utility of impaired olfaction (defined as UPSIT score <35) and amyloid-positivity for memory decline. RESULTS High UPSIT scores predicted absence of amyloidosis on PET, with negative predictive value of 100%. Positive predictive value of low UPSIT scores on positive Aβ status was only 41%. Both low UPSIT score (OR = 4.301, 95% CI = 1.248, 14.821, p = 0.021) and positive PET scan (OR = 20.898, 95% CI = 2.222, 196.581, p = 0.008) predicted memory decline. CONCLUSION Individuals with high UPSIT scores are less likely to have cerebral amyloidosis or experience memory decline. Therefore, UPSIT has potential as a screening tool to determine utility of Aβ PET in clinical practice or enrollment in clinical trials. Low UPSIT score is a non-specific marker of neurodegeneration that could indicate further workup in patients with memory complaints.
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Affiliation(s)
| | - Peng Jin
- Division of Biostatistics, Columbia University Medical Center, New York, NY, USA
| | - Seonjoo Lee
- Division of Biostatistics, Columbia University Medical Center, New York, NY, USA
| | - Ezra R Dayan
- Taub Institute, Columbia University Medical, New York, NY, USA
| | | | - Gregory Pelton
- Department of Psychiatry, Columbia University Medical Center, New York, NY, USA
| | - José A Luchsinger
- Departments of Medicine and Epidemiology, Columbia University Medical Center, New York, NY, USA
| | | | - D P Devanand
- Department of Psychiatry, Columbia University Medical Center, New York, NY, USA
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208
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Kim J, Ghadery C, Cho SS, Mihaescu A, Christopher L, Valli M, Houle S, Strafella AP. Network Patterns of Beta-Amyloid Deposition in Parkinson's Disease. Mol Neurobiol 2019; 56:7731-7740. [PMID: 31111400 DOI: 10.1007/s12035-019-1625-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Accepted: 04/24/2019] [Indexed: 01/07/2023]
Abstract
Beta-amyloid (Aβ) in the brain is a key pathological feature of certain neurodegenerative diseases. Recent studies using graph theory have shown that Aβ brain networks are of pathological significance in Alzheimer's disease (AD). However, the characteristics of Aβ brain networks in Parkinson's disease (PD) are unknown. In the present study using positron emission tomography (PET) with [11C]-Pittsburgh compound B (PiB), we applied a graph theory-based analysis to assess the topological properties of Aβ brain network in PD patients with and without Aβ burden (PiB-positive and PiB-negative, respectively) and healthy controls with Aβ burden. We found that the PD PiB-positive group demonstrated significantly lower value in global efficiency and modularity compared with PD PiB-negative group. The less robust modular structure indicates the tendency of having increased inter-modular connections than intra-modular connectivity (i.e., reduced segregation). Results of hub organization showed that relative to PD PiB-negative group, different hubs were identified in the PiB-positive group, which were located mainly within the default mode network. Overall, our findings suggest disturbances in Aβ topological organization characterized by abnormal network integration and segregation in PD patients with Aβ burden. The stronger inter-modular connectivity observed in the PD PiB-positive group may suggest the spreading pattern of Aβ between modules in those PD patients with elevated PiB burden, thus providing insight into the beta-amyloidopathy of PD.
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Affiliation(s)
- Jinhee Kim
- Research Imaging Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada. .,Division of Brain, Imaging and Behaviour - Systems Neuroscience, Krembil Research Institute, University Health Network, University of Toronto, Toronto, Ontario, Canada.
| | - Christine Ghadery
- Research Imaging Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada.,Division of Brain, Imaging and Behaviour - Systems Neuroscience, Krembil Research Institute, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Sang Soo Cho
- Research Imaging Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada.,Division of Brain, Imaging and Behaviour - Systems Neuroscience, Krembil Research Institute, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Alexander Mihaescu
- Research Imaging Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada.,Division of Brain, Imaging and Behaviour - Systems Neuroscience, Krembil Research Institute, University Health Network, University of Toronto, Toronto, Ontario, Canada.,Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Leigh Christopher
- Research Imaging Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada.,Division of Brain, Imaging and Behaviour - Systems Neuroscience, Krembil Research Institute, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Mikaeel Valli
- Research Imaging Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada.,Division of Brain, Imaging and Behaviour - Systems Neuroscience, Krembil Research Institute, University Health Network, University of Toronto, Toronto, Ontario, Canada.,Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Sylvain Houle
- Research Imaging Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada
| | - Antonio P Strafella
- Research Imaging Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada.,Division of Brain, Imaging and Behaviour - Systems Neuroscience, Krembil Research Institute, University Health Network, University of Toronto, Toronto, Ontario, Canada.,Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada.,Morton and Gloria Shulman Movement Disorder Unit and E.J. Safra Parkinson Disease Program, Neurology Division, Department of Medicine, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada
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209
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Ismail R, Parbo P, Hansen KV, Schaldemose JL, Dalby RB, Tietze A, Kjeldsen PL, Cour SH, Qvist P, Gottrup H, Eskildsen SF, Brooks DJ. Abnormal Amyloid Load in Mild Cognitive Impairment: The Effect of Reducing the PiB‐PET Threshold. J Neuroimaging 2019; 29:499-505. [DOI: 10.1111/jon.12629] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2019] [Revised: 04/29/2019] [Accepted: 04/30/2019] [Indexed: 11/26/2022] Open
Affiliation(s)
- Rola Ismail
- Department of Clinical Medicine, PET‐CentreAarhus University Denmark
| | - Peter Parbo
- Department of Nuclear Medicine and PET Centre Aarhus University Hospital Denmark
| | - Kim V. Hansen
- Department of Clinical Medicine, PET‐CentreAarhus University Denmark
| | | | - Rikke B. Dalby
- Center of Functionally Integrative Neuroscience (CFIN)Aarhus University Denmark
| | - Anna Tietze
- Institute of NeuroradiologyCharite–Universitätsmedizin Berlin Germany
| | | | - Sanne Hage Cour
- Department of BiomedicineCentre for Integrative Sequencing iSEQ, Aarhus University Denmark
| | - Per Qvist
- Department of BiomedicineCentre for Integrative Sequencing iSEQ, Aarhus University Denmark
| | - Hanne Gottrup
- Department of NeurologyAarhus University Hospital Denmark
| | - Simon F. Eskildsen
- Center of Functionally Integrative Neuroscience (CFIN)Aarhus University Denmark
| | - David J. Brooks
- Department of Clinical Medicine, PET‐CentreAarhus University Denmark
- Institute of NeuroscienceUniversity of Newcastle upon Tyne UK
- Department of MedicineImperial College London UK
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210
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High amyloid burden is associated with fewer specific words during spontaneous speech in individuals with subjective cognitive decline. Neuropsychologia 2019; 131:184-192. [PMID: 31075283 DOI: 10.1016/j.neuropsychologia.2019.05.006] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2018] [Revised: 05/03/2019] [Accepted: 05/06/2019] [Indexed: 12/29/2022]
Abstract
Self-perceived word-finding difficulties are common in aging individuals as well as in Alzheimer's Disease (AD). Language and speech deficits are difficult to objectify with neuropsychological assessments. We therefore aimed to investigate whether amyloid, an early AD pathological hallmark, is associated with speech-derived semantic complexity. We included 63 individuals with subjective cognitive decline (age 64 ± 8, MMSE 29 ± 1), with amyloid status (positron emission tomography [PET] scans n = 59, or Aβ1-42 cerebrospinal fluid [CSF] n = 4). Spontaneous speech was recorded using three open-ended tasks (description of cookie theft picture, abstract painting and a regular Sunday), transcribed verbatim and subsequently, linguistic parameters were extracted using T-scan computational software, including specific words (content words, frequent, concrete and abstract nouns, and fillers), lexical complexity (lemma frequency, Type-Token-Ratio) and syntactic complexity (Developmental Level scale). Nineteen individuals (30%) had high levels of amyloid burden, and there were no differences between groups on conventional neuropsychological tests. Using multinomial regression with linguistic parameters (in tertiles), we found that high amyloid burden is associated with fewer concrete nouns (ORmiddle (95%CI): 7.6 (1.4-41.2), ORlowest: 6.7 (1.2-37.1)) and content words (ORlowest: 6.3 (1.0-38.1). In addition, we found an interaction for education between high amyloid burden and more abstract nouns. In conclusion, high amyloid burden was modestly associated with fewer specific words, but not with syntactic complexity, lexical complexity or conventional neuropsychological tests, suggesting that subtle spontaneous speech deficits might occur in preclinical AD.
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211
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Ossenkoppele R, Iaccarino L, Schonhaut DR, Brown JA, La Joie R, O'Neil JP, Janabi M, Baker SL, Kramer JH, Gorno-Tempini ML, Miller BL, Rosen HJ, Seeley WW, Jagust WJ, Rabinovici GD. Tau covariance patterns in Alzheimer's disease patients match intrinsic connectivity networks in the healthy brain. NEUROIMAGE-CLINICAL 2019; 23:101848. [PMID: 31077982 PMCID: PMC6510968 DOI: 10.1016/j.nicl.2019.101848] [Citation(s) in RCA: 60] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/26/2018] [Revised: 04/02/2019] [Accepted: 05/01/2019] [Indexed: 01/06/2023]
Abstract
According to the network model of neurodegeneration, the spread of pathogenic proteins occurs selectively along connected brain regions. We tested in vivo whether the distribution of filamentous tau (measured with [18F]flortaucipir-PET), fibrillar amyloid-β ([11C]PIB-PET) and glucose hypometabolism ([18F]FDG-PET) follows the intrinsic functional organization of the healthy brain. We included 63 patients with Alzheimer's disease (AD; 30 male, 63 ± 8 years) who underwent [18F]flortaucipir, [11C]PIB and [18F]FDG PET, and 1000 young adults (427 male, 21 ± 3 years) who underwent task-free fMRI. We selected six predefined disease epicenters as seeds for whole-brain voxelwise covariance analyses to compare correlated patterns of tracer uptake across AD patients against fMRI intrinsic connectivity patterns in young adults. We found a striking convergence between [18F]flortaucipir covariance patterns and intrinsic connectivity maps (range Spearman rho's: 0.32-0.78, p < .001), which corresponded with expected functional networks (range goodness-of-fit: 3.8-8.2). The topography of amyloid-β covariance patterns was more diffuse and less network-specific, while glucose hypometabolic patterns were more spatially restricted than tau but overlapped with functional networks. These findings suggest that the spatial patterns of tau and glucose hypometabolism observed in AD resemble the functional organization of the healthy brain, supporting the notion that tau pathology spreads through circumscribed brain networks and drives neurodegeneration.
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Affiliation(s)
- Rik Ossenkoppele
- Memory and Aging Center, University of California San Francisco, San Francisco, CA 94143, USA; Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA 94720, USA; Department of Neurology & Alzheimer Center, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam 1081 HZ, the Netherlands.
| | - Leonardo Iaccarino
- Memory and Aging Center, University of California San Francisco, San Francisco, CA 94143, USA
| | - Daniel R Schonhaut
- Memory and Aging Center, University of California San Francisco, San Francisco, CA 94143, USA; Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA 94720, USA
| | - Jesse A Brown
- Memory and Aging Center, University of California San Francisco, San Francisco, CA 94143, USA
| | - Renaud La Joie
- Memory and Aging Center, University of California San Francisco, San Francisco, CA 94143, USA; Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA 94720, USA
| | - James P O'Neil
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Mustafa Janabi
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Suzanne L Baker
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Joel H Kramer
- Memory and Aging Center, University of California San Francisco, San Francisco, CA 94143, USA
| | | | - Bruce L Miller
- Memory and Aging Center, University of California San Francisco, San Francisco, CA 94143, USA
| | - Howard J Rosen
- Memory and Aging Center, University of California San Francisco, San Francisco, CA 94143, USA
| | - William W Seeley
- Memory and Aging Center, University of California San Francisco, San Francisco, CA 94143, USA; Department of Pathology, University of California San Francisco, San Francisco, CA 94143, USA
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA 94720, USA; Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Gil D Rabinovici
- Memory and Aging Center, University of California San Francisco, San Francisco, CA 94143, USA; Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA 94720, USA
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212
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Duara R, Loewenstein DA, Lizarraga G, Adjouadi M, Barker WW, Greig-Custo MT, Rosselli M, Penate A, Shea YF, Behar R, Ollarves A, Robayo C, Hanson K, Marsiske M, Burke S, Ertekin-Taner N, Vaillancourt D, De Santi S, Golde T, St D. Effect of age, ethnicity, sex, cognitive status and APOE genotype on amyloid load and the threshold for amyloid positivity. NEUROIMAGE-CLINICAL 2019; 22:101800. [PMID: 30991618 PMCID: PMC6447735 DOI: 10.1016/j.nicl.2019.101800] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/22/2018] [Revised: 02/08/2019] [Accepted: 03/26/2019] [Indexed: 11/30/2022]
Abstract
The threshold for amyloid positivity by visual assessment on PET has been validated by comparison to amyloid load measured histopathologically and biochemically at post mortem. As such, it is now feasible to use qualitative visual assessment of amyloid positivity as an in-vivo gold standard to determine those factors which can modify the quantitative threshold for amyloid positivity. We calculated quantitative amyloid load, measured as Standardized Uptake Value Ratios (SUVRs) using [18-F]florbetaben PET scans, for 159 Hispanic and non-Hispanic participants, who had been classified clinically as Cognitively Normal (CN), Mild Cognitive Impairment (MCI) or Dementia (DEM). PET scans were visually rated as amyloid positive (A+) or negative (A-), and these judgments were used as the gold standard with which to determine (using ROC analyses) the SUVR threshold for amyloid positivity considering factors such as age, ethnicity (Hispanic versus non-Hispanic), gender, cognitive status, and apolipoprotein E ε4 carrier status. Visually rated scans were A+ for 11% of CN, 39.0% of MCI and 70% of DEM participants. The optimal SUVR threshold for A+ among all participants was 1.42 (sensitivity = 94%; specificity = 92.5%), but this quantitative threshold was higher among E4 carriers (SUVR = 1.52) than non-carriers (SUVR = 1.31). While mean SUVRs did not differ between Hispanic and non-Hispanic participants;, a statistically significant interaction term indicated that the effect of E4 carrier status on amyloid load was greater among non-Hispanics than Hispanics. Visual assessment, as the gold standard for A+, facilitates determination of the effects of various factors on quantitative thresholds for amyloid positivity. A continuous relationship was found between amyloid load and global cognitive scores, suggesting that any calculated threshold for the whole group, or a subgroup, is artefactual and that the lowest calculated threshold may be optimal for the purposes of early diagnosis and intervention. Demographic factors did not affect the threshold for amyloid positivity. Cognitive status did not affect this threshold for amyloid positivity. APOE4 carriers had a higher threshold for amyloid positivity than non-carriers. Among APOE4 carriers, non-Hispanics had higher amyloid load than non- Hispanics. There was a continuous relationship between amyloid load and cognitive status.
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Affiliation(s)
- R Duara
- Florida ADRC, USA; Mount Sinai Medical Center, Miami Beach, USA; College of Engineering and Computing, Florida International University, Miami, FL, USA; University of Florida College of Medicine, Gainesville, FL, USA.
| | - D A Loewenstein
- Florida ADRC, USA; Mount Sinai Medical Center, Miami Beach, USA; Miller School of Medicine, University of Miami, Miami, FL, USA
| | - G Lizarraga
- Florida ADRC, USA; College of Engineering and Computing, Florida International University, Miami, FL, USA
| | - M Adjouadi
- Florida ADRC, USA; College of Engineering and Computing, Florida International University, Miami, FL, USA
| | - W W Barker
- Florida ADRC, USA; Mount Sinai Medical Center, Miami Beach, USA
| | - M T Greig-Custo
- Florida ADRC, USA; Mount Sinai Medical Center, Miami Beach, USA
| | - M Rosselli
- Florida ADRC, USA; Florida Atlantic University, USA
| | - A Penate
- Florida ADRC, USA; Mount Sinai Medical Center, Miami Beach, USA
| | - Y F Shea
- Mount Sinai Medical Center, Miami Beach, USA; Department of Medicine, University of Hong Kong, Hong Kong
| | - R Behar
- Florida ADRC, USA; Mount Sinai Medical Center, Miami Beach, USA
| | - A Ollarves
- Florida ADRC, USA; Mount Sinai Medical Center, Miami Beach, USA
| | - C Robayo
- Florida ADRC, USA; Mount Sinai Medical Center, Miami Beach, USA
| | - K Hanson
- Florida ADRC, USA; University of Florida College of Medicine, Gainesville, FL, USA
| | - M Marsiske
- Florida ADRC, USA; University of Florida College of Medicine, Gainesville, FL, USA; University of Florida, College of Public Health and Health Professions, USA
| | - S Burke
- Florida ADRC, USA; Robert Stempel College of Public Health & Social Work, Florida International University, Miami, FL, USA
| | - N Ertekin-Taner
- Mayo Clinic Florida, Department of Neurology, Jacksonville, FL, USA; Mayo Clinic Florida, Department of Neuroscience, Jacksonville, FL, USA
| | - D Vaillancourt
- Florida ADRC, USA; University of Florida College of Medicine, Gainesville, FL, USA
| | | | - T Golde
- Florida ADRC, USA; University of Florida College of Medicine, Gainesville, FL, USA
| | - DeKosky St
- Florida ADRC, USA; University of Florida College of Medicine, Gainesville, FL, USA
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213
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Baker SL, Harrison TM, Maass A, La Joie R, Jagust WJ. Effect of Off-Target Binding on 18F-Flortaucipir Variability in Healthy Controls Across the Life Span. J Nucl Med 2019; 60:1444-1451. [PMID: 30877180 DOI: 10.2967/jnumed.118.224113] [Citation(s) in RCA: 81] [Impact Index Per Article: 16.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2018] [Accepted: 02/20/2019] [Indexed: 02/04/2023] Open
Abstract
Measuring early tau accumulation is important in studying aging and Alzheimer disease and is only as accurate as the signal-to-noise ratio of the tracer. Along with aggregated tau in the form of neurofibrillary tangles, 18F-flortaucipir has been reported to bind to neuromelanin, monoamine oxidase, calcifications, iron, leptomeningeal melanocytes, and microhemorrages. Although 18F-flortaucipir successfully differentiates healthy controls (HCs) from subjects with Alzheimer disease, variability exists in the cortical signal in amyloid-negative HCs. We aimed to explore the relationship between off-target binding signal and variability in the cortical signal in HCs. Methods: Subjects (n = 139) received 11C-Pittsburgh compound B (PIB) and 18F-flortaucipir PET scans and a magnetization-prepared rapid gradient echo MRI scan. PET frames were realigned and coregistered to the MR images, which were segmented using FreeSurfer. In amyloid-negative HCs (n = 90; age range, 21-94 y), 7 nonspecific or off-target binding regions were considered: caudate, pallidum, putamen, thalamus, cerebellar white matter, hemispheric white matter, and choroid plexus. These regions of interest were assigned to 3 similarly behaving groups using principle components analysis, exploratory factor analysis, and Pearson correlations for caudate, putamen, and pallidum (also correlated with age); thalamus and white matter; and choroid plexus. In amyloid-negative HCs with 11C-PIB and 18F-flortaucipir scans, correlations were calculated between white and gray matter before and after partial-volume correction. Results: The correlation between white and gray matter disappeared after partial-volume correction in 11C-PIB (r 2 = 0) but persisted for 18F-flortaucipir (r 2 = 0.27), demonstrating that the correlation between white and gray matter signal in 18F-flortaucipir is not solely due to partial-volume effects. A linear regression showed that off-target signal from putamen and thalamus together explained 64% of the variability in the cortical signal in amyloid-negative HCs (not seen in amyloid-positive HCs). Variability in amyloid-negative HCs but not amyloid-positive HCs correlated with white matter signal (unrelated to partial-volume effects) and age-related off-target signal (possibly related to iron load). Conclusion: The noise in the 18F-flortaucipir measurement could pose challenges when studying early tau accumulation.
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Affiliation(s)
| | - Theresa M Harrison
- Helen Wills Neuroscience Institute, University of California-Berkeley, Berkeley, California
| | - Anne Maass
- Helen Wills Neuroscience Institute, University of California-Berkeley, Berkeley, California.,German Center for Neurodegenerative Diseases, Magdeburg, Germany; and
| | - Renaud La Joie
- Memory and Aging Center, University of California-San Francisco, San Francisco, California
| | - William J Jagust
- Lawrence Berkeley National Laboratory, Berkeley, California.,Helen Wills Neuroscience Institute, University of California-Berkeley, Berkeley, California
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214
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Amyloid PET and cognitive decline in cognitively normal individuals: the SCIENCe project. Neurobiol Aging 2019; 79:50-58. [PMID: 31026622 DOI: 10.1016/j.neurobiolaging.2019.02.020] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Revised: 02/08/2019] [Accepted: 02/27/2019] [Indexed: 12/18/2022]
Abstract
We examined the relationships between amyloid-β PET and concurrent and longitudinal cognitive performance in 107 cognitively normal individuals with subjective cognitive decline (age: 64 ± 8 years, 44% female, Mini-Mental State Examination score 29 ± 1). All underwent 90-minute dynamic [18F]florbetapir PET scanning and longitudinal neuropsychological tests with a mean follow-up of 3.4 ± 3.0 years. Receptor parametric mapping was used to calculate [18F]florbetapir binding potential (BPND), and we performed linear mixed models to assess the relationships between global [18F]florbetapir BPND and neuropsychological performance. Higher [18F]florbetapir BPND was related to lower concurrent Mini-Mental State Examination (β ± SE: -1.69 ± 0.63 p < 0.01) and to steeper rate of decline on tasks capturing memory (Rey Auditory Verbal Learning Task immediate [β ± SE -1.81 ± 0.81, p < 0.05] and delayed recall [β ± SE -1.19 ± 0.34, p < 0.01]), attention/executive functions (Stroop II [color] [β ± SE -0.02 ± 0.01, p < 0.05], Stroop III [word-color] [β ± SE -0.03 ± 0.02, p < 0.05]), and language (category fluency [β ± SE -0.04 ± 0.01, p < 0.01]). These findings suggest that higher amyloid-β load in cognitively normal individuals with subjective cognitive decline from a memory clinic is associated with lower concurrent global cognition and with faster rate of decline in a variety of cognitive domains.
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215
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He M, Baker SL, Shah VD, Lockhart SN, Jagust WJ. Scan-Time Corrections for 80-100-min Standardizetd Uptake Volume Ratios to Measure the 18F-AV-1451 Tracer for Tau Imaging. IEEE TRANSACTIONS ON MEDICAL IMAGING 2019; 38:697-709. [PMID: 30235119 PMCID: PMC6475617 DOI: 10.1109/tmi.2018.2870441] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
The 18F-AV-1451 PET tracer binds to tau, an Alzheimer's disease biomarker. The standardized uptake value ratio (SUVR) 80-100 min window is widely used to quantify tau binding, although 18F-AV-1451 continues increasing relative to a reference region in regions with tau deposition. Left uncorrected, acquisition time inaccuracies can lead to errors from -4% to 6% in 20-min SUVR measurements in subjects with Alzheimer's disease. In 40 subjects with scans from 75-115 min following 18F-AV-1451 injection, we created 20-min reconstructions (4×5 min) of start-times ranging from 75-85 min, as proxies of offset scans and calculated the mean in regions of interest (ROIs). We developed a segmented least squares (SLS) method to obtain error-minimizing weighting coefficients for 18F-AV-1451 ROIs that best predict SUVR 80-100 from weighted means of SUVRs from offset start-times. We compared residual errors of our SLS method to those in: 1) uncorrected offset 20-min-SUVRs; 2) the mean of five-min frames within the 80-100 window; and 3) a least-squares interpolation method. We evaluated errors induced by start-time offset on SUVRs for each method. TheSLS, which corrected using least-squares coefficients of 5-min components, consistently reduced errors across all offset starttimes. Effect size analysis for simulated clinical longitudinal 18F-AV-1451 drug trials showed that uncorrected 20-min offset SUVRs would require up to 20% more participants to detect treatment effects compared with using SLS. Correction of SUVR scan-time errors by SLS minimizes errors compared with other correction methods and may be extended to other scanners and tracers.
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216
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Jeon SY, Byun MS, Yi D, Lee JH, Choe YM, Ko K, Sohn BK, Choi HJ, Lee JY, Lee DY. Influence of hypertension on brain amyloid deposition and Alzheimer's disease signature neurodegeneration. Neurobiol Aging 2019; 75:62-70. [DOI: 10.1016/j.neurobiolaging.2018.11.001] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2018] [Revised: 11/07/2018] [Accepted: 11/08/2018] [Indexed: 02/01/2023]
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217
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De Leon J, Mandelli ML, Nolan A, Miller ZA, Mead C, Watson C, Welch AE, Henry ML, Bourakova V, La Joie R, Bajorek LP, Grinberg L, Rabinovici G, Miller BL, Gorno-Tempini ML. Atypical clinical features associated with mixed pathology in a case of non-fluent variant primary progressive aphasia. Neurocase 2019; 25:39-47. [PMID: 31033382 PMCID: PMC6759324 DOI: 10.1080/13554794.2019.1609522] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
A 66-year-old woman presented with agrammatism and apraxia of speech, meeting criteria for non-fluent/agrammatic variant primary progressive aphasia (nfvPPA). However, three years later, she developed frontal/executive, short-term phonological memory, visuospatial, and visual memory deficits suggesting involvement of multiple brain networks. Multimodal neuroimaging showed damage of both fronto-striatal and posterior brain regions. She was found to have multiple pathological processes: corticobasal degeneration (CBD), Alzheimer's disease (AD), and TAR DNA-binding protein (TDP)-43 type A. We hypothesize that cognitive and neuroimaging findings consistent with damage to multiple brain networks, each associated with vulnerability to certain molecular disease subtypes, could indicate mixed pathology.
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Affiliation(s)
- Jessica De Leon
- a Memory and Aging Center, Department of Neurology , University of California , San Francisco , CA , USA
| | - Maria Luisa Mandelli
- a Memory and Aging Center, Department of Neurology , University of California , San Francisco , CA , USA
| | - Amber Nolan
- a Memory and Aging Center, Department of Neurology , University of California , San Francisco , CA , USA
| | - Zachary A Miller
- a Memory and Aging Center, Department of Neurology , University of California , San Francisco , CA , USA
| | - Christie Mead
- b PGSP-Stanford Psy.D. Consortium , Palo Alto University , Palo Alto , CA , USA
| | - Christa Watson
- a Memory and Aging Center, Department of Neurology , University of California , San Francisco , CA , USA
| | - Ariane E Welch
- a Memory and Aging Center, Department of Neurology , University of California , San Francisco , CA , USA
| | - Maya L Henry
- c Department of Communication Sciences and Disorders , University of Texas at Austin , Austin, TX , USA
| | - Viktoriya Bourakova
- a Memory and Aging Center, Department of Neurology , University of California , San Francisco , CA , USA
| | - Renaud La Joie
- a Memory and Aging Center, Department of Neurology , University of California , San Francisco , CA , USA
| | - Lynn P Bajorek
- a Memory and Aging Center, Department of Neurology , University of California , San Francisco , CA , USA
| | - Lea Grinberg
- a Memory and Aging Center, Department of Neurology , University of California , San Francisco , CA , USA
| | - Gil Rabinovici
- a Memory and Aging Center, Department of Neurology , University of California , San Francisco , CA , USA
| | - Bruce L Miller
- a Memory and Aging Center, Department of Neurology , University of California , San Francisco , CA , USA
| | - Maria Luisa Gorno-Tempini
- a Memory and Aging Center, Department of Neurology , University of California , San Francisco , CA , USA
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218
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La Joie R, Ayakta N, Seeley WW, Borys E, Boxer AL, DeCarli C, Doré V, Grinberg LT, Huang E, Hwang JH, Ikonomovic MD, Jack C, Jagust WJ, Jin LW, Klunk WE, Kofler J, Lesman-Segev OH, Lockhart SN, Lowe VJ, Masters CL, Mathis CA, McLean CL, Miller BL, Mungas D, O'Neil JP, Olichney JM, Parisi JE, Petersen RC, Rosen HJ, Rowe CC, Spina S, Vemuri P, Villemagne VL, Murray ME, Rabinovici GD. Multisite study of the relationships between antemortem [ 11C]PIB-PET Centiloid values and postmortem measures of Alzheimer's disease neuropathology. Alzheimers Dement 2019; 15:205-216. [PMID: 30347188 PMCID: PMC6368897 DOI: 10.1016/j.jalz.2018.09.001] [Citation(s) in RCA: 144] [Impact Index Per Article: 28.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2018] [Revised: 07/08/2018] [Accepted: 09/03/2018] [Indexed: 10/28/2022]
Abstract
INTRODUCTION We sought to establish the relationships between standard postmortem measures of AD neuropathology and antemortem [11C]PIB-positron emission tomography ([11C]PIB-PET) analyzed with the Centiloid (CL) method, a standardized scale for Aβ-PET quantification. METHODS Four centers contributed 179 participants encompassing a broad range of clinical diagnoses, PET data, and autopsy findings. RESULTS CL values increased with each CERAD neuritic plaque score increment (median -3 CL for no plaques and 92 CL for frequent plaques) and nonlinearly with Thal Aβ phases (increases were detected starting at phase 2) with overlap between scores/phases. PET-pathology associations were comparable across sites and unchanged when restricting the analyses to the 56 patients who died within 2 years of PET. A threshold of 12.2 CL detected CERAD moderate-to-frequent neuritic plaques (area under the curve = 0.910, sensitivity = 89.2%, specificity = 86.4%), whereas 24.4 CL identified intermediate-to-high AD neuropathological changes (area under the curve = 0.894, sensitivity = 84.1%, specificity = 87.9%). DISCUSSION Our study demonstrated the robustness of a multisite Centiloid [11C]PIB-PET study and established a range of pathology-based CL thresholds.
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Affiliation(s)
- Renaud La Joie
- Memory & Aging Center, Department of Neurology, University of California, San Francisco, CA, USA.
| | - Nagehan Ayakta
- Memory & Aging Center, Department of Neurology, University of California, San Francisco, CA, USA; Helen Wills Neuroscience Institute, University of California Berkeley, CA, USA
| | - William W Seeley
- Memory & Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Ewa Borys
- Department of Pathology, Stritch School of Medicine, Loyola University, Maywood, IL, USA
| | - Adam L Boxer
- Memory & Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Charles DeCarli
- Department of Neurology, University of California, Davis, CA, USA
| | - Vincent Doré
- Department of Molecular Imaging & Therapy, Centre for PET, Austin Health, Heidelberg, Victoria, Australia
| | - Lea T Grinberg
- Memory & Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Eric Huang
- Memory & Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Ji-Hye Hwang
- Memory & Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Milos D Ikonomovic
- Department of Neurology, University of Pittsburgh, PA, USA; Department of Psychiatry, University of Pittsburgh, PA, USA
| | - Clifford Jack
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California Berkeley, CA, USA
| | - Lee-Way Jin
- Alzheimer's Disease Center, Department of Pathology, University of California Davis, CA, USA
| | - William E Klunk
- Department of Neurology, University of Pittsburgh, PA, USA; Department of Psychiatry, University of Pittsburgh, PA, USA; Alzheimer's Disease Research Center, University of Pittsburgh, PA, USA
| | - Julia Kofler
- Department of Pathology, University of Pittsburgh, Pennsylvania, USA
| | - Orit H Lesman-Segev
- Memory & Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Samuel N Lockhart
- Helen Wills Neuroscience Institute, University of California Berkeley, CA, USA; Department of Internal Medicine, Division of Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Val J Lowe
- Department of Nuclear Medicine, Mayo Clinic, Rochester, MN, USA
| | - Colin L Masters
- The Florey Institute, The University of Melbourne, Melbourne, Victoria, Australia
| | | | - Catriona L McLean
- Department of Anatomical Pathology, Alfred Hospital, Melbourne, Australia
| | - Bruce L Miller
- Memory & Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Daniel Mungas
- Department of Neurology, University of California, Davis, CA, USA
| | - James P O'Neil
- Helen Wills Neuroscience Institute, University of California Berkeley, CA, USA; Biomedical Isotope Facility, MBIB Division, Lawrence Berkeley National Laboratory, CA, USA
| | - John M Olichney
- Department of Neurology, University of California, Davis, CA, USA
| | - Joseph E Parisi
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA; Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | | | - Howard J Rosen
- Memory & Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Christopher C Rowe
- Department of Molecular Imaging & Therapy, Centre for PET, Austin Health, Heidelberg, Victoria, Australia
| | - Salvatore Spina
- Memory & Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | | | - Victor L Villemagne
- Department of Molecular Imaging & Therapy, Centre for PET, Austin Health, Heidelberg, Victoria, Australia; The Florey Institute, The University of Melbourne, Melbourne, Victoria, Australia
| | | | - Gil D Rabinovici
- Memory & Aging Center, Department of Neurology, University of California, San Francisco, CA, USA; Helen Wills Neuroscience Institute, University of California Berkeley, CA, USA
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219
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Tsai RM, Bejanin A, Lesman-Segev O, LaJoie R, Visani A, Bourakova V, O’Neil JP, Janabi M, Baker S, Lee SE, Perry DC, Bajorek L, Karydas A, Spina S, Grinberg LT, Seeley WW, Ramos EM, Coppola G, Gorno-Tempini ML, Miller BL, Rosen HJ, Jagust W, Boxer AL, Rabinovici GD. 18F-flortaucipir (AV-1451) tau PET in frontotemporal dementia syndromes. Alzheimers Res Ther 2019; 11:13. [PMID: 30704514 PMCID: PMC6357510 DOI: 10.1186/s13195-019-0470-7] [Citation(s) in RCA: 107] [Impact Index Per Article: 21.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2018] [Accepted: 01/17/2019] [Indexed: 12/13/2022]
Abstract
BACKGROUND The tau positron emission tomography (PET) ligand 18F-flortaucipir binds to paired helical filaments of tau in aging and Alzheimer's disease (AD), but its utility in detecting tau aggregates in frontotemporal dementia (FTD) is uncertain. METHODS We performed 18F-flortaucipir imaging in patients with the FTD syndromes (n = 45): nonfluent variant primary progressive aphasia (nfvPPA) (n = 11), corticobasal syndrome (CBS) (n = 10), behavioral variant frontotemporal dementia (bvFTD) (n = 10), semantic variant primary progressive aphasia (svPPA) (n = 2) and FTD associated pathogenic genetic mutations microtubule-associated protein tau (MAPT) (n = 6), chromosome 9 open reading frame 72 (C9ORF72) (n = 5), and progranulin (GRN) (n = 1). All patients underwent MRI and β-amyloid biomarker testing via 11C-PiB or cerebrospinal fluid. 18F-flortaucipir uptake in patients was compared to 53 β-amyloid negative normal controls using voxelwise and pre-specified region of interest approaches. RESULTS On qualitative assessment, patients with nfvPPA showed elevated 18F-flortacupir binding in the left greater than right inferior frontal gyrus. Patients with CBS showed elevated binding in frontal white matter, with higher cortical gray matter uptake in a subset of β-amyloid-positive patients. Five of ten patients with sporadic bvFTD demonstrated increased frontotemporal binding. MAPT mutation carriers had elevated 18F-flortaucipir retention primarily, but not exclusively, in mutations with Alzheimer's-like neurofibrillary tangles. However, tracer retention was also seen in patients with svPPA, and the mutations C9ORF72, GRN predicted to have TDP-43 pathology. Quantitative region-of-interest differences between patients and controls were seen only in inferior frontal gyrus in nfvPPA and left insula and bilateral temporal poles in MAPT carriers. No significant regional differences were found in CBS or sporadic bvFTD. Two patients underwent postmortem neuropathological examination. A patient with C9ORF72, TDP-43-type B pathology, and incidental co-pathology of scattered neurofibrillary tangles in the middle frontal, inferior temporal gyrus showed corresponding mild 18F-flortaucipir retention without additional uptake matching the widespread TDP-43 type B pathology. A patient with sporadic bvFTD demonstrated punctate inferior temporal and hippocampus tracer retention, corresponding to the area of severe argyrophilic grain disease pathology. CONCLUSIONS 18F-flortaucipir in patients with FTD and predicted tauopathy or TDP-43 pathology demonstrated limited sensitivity and specificity. Further postmortem pathological confirmation and development of FTD tau-specific ligands are needed.
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Affiliation(s)
- Richard M. Tsai
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - Alexandre Bejanin
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - Orit Lesman-Segev
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - Renaud LaJoie
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - Adrienne Visani
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - Viktoriya Bourakova
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - James P. O’Neil
- Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, USA
| | - Mustafa Janabi
- Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, USA
| | - Suzanne Baker
- Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, USA
| | - Suzee E. Lee
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - David C. Perry
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - Lynn Bajorek
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - Anna Karydas
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - Salvatore Spina
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - Lea T. Grinberg
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - William W. Seeley
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - Eliana M. Ramos
- Departments of Psychiatry and Neurology, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles, CA USA
| | - Giovanni Coppola
- Departments of Psychiatry and Neurology, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles, CA USA
| | - Maria Luisa Gorno-Tempini
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - Bruce L. Miller
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - Howard J. Rosen
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - William Jagust
- Helen Wills Neuroscience Institute, University of California at Berkeley, Berkeley, USA
- Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, USA
| | - Adam L. Boxer
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
| | - Gil D. Rabinovici
- Memory and Aging Center, University of California at San Francisco, 675 Nelson Rising Lane, Suite 190, San Francisco, CA USA
- Helen Wills Neuroscience Institute, University of California at Berkeley, Berkeley, USA
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Sakr FA, Grothe MJ, Cavedo E, Jelistratova I, Habert MO, Dyrba M, Gonzalez-Escamilla G, Bertin H, Locatelli M, Lehericy S, Teipel S, Dubois B, Hampel H. Applicability of in vivo staging of regional amyloid burden in a cognitively normal cohort with subjective memory complaints: the INSIGHT-preAD study. ALZHEIMERS RESEARCH & THERAPY 2019; 11:15. [PMID: 30704537 PMCID: PMC6357385 DOI: 10.1186/s13195-019-0466-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/21/2018] [Accepted: 01/07/2019] [Indexed: 01/12/2023]
Abstract
BACKGROUND Current methods of amyloid PET interpretation based on the binary classification of global amyloid signal fail to identify early phases of amyloid deposition. A recent analysis of 18F-florbetapir PET data from the Alzheimer's disease Neuroimaging Initiative cohort suggested a hierarchical four-stage model of regional amyloid deposition that resembles neuropathologic estimates and can be used to stage an individual's amyloid burden in vivo. Here, we evaluated the validity of this in vivo amyloid staging model in an independent cohort of older people with subjective memory complaints (SMC). We further examined its potential association with subtle cognitive impairments in this population at elevated risk for Alzheimer's disease (AD). METHODS The monocentric INSIGHT-preAD cohort includes 318 cognitively intact older individuals with SMC. All individuals underwent 18F-florbetapir PET scanning and extensive neuropsychological testing. We projected the regional amyloid uptake signal into the previously proposed hierarchical staging model of in vivo amyloid progression. We determined the adherence to this model across all cases and tested the association between increasing in vivo amyloid stage and cognitive performance using ANCOVA models. RESULTS In total, 156 participants (49%) showed evidence of regional amyloid deposition, and all but 2 of these (99%) adhered to the hierarchical regional pattern implied by the in vivo amyloid progression model. According to a conventional binary classification based on global signal (SUVRCereb = 1.10), individuals in stages III and IV were classified as amyloid-positive (except one in stage III), but 99% of individuals in stage I and even 28% of individuals in stage II were classified as amyloid-negative. Neither in vivo amyloid stage nor conventional binary amyloid status was significantly associated with cognitive performance in this preclinical cohort. CONCLUSIONS The proposed hierarchical staging scheme of PET-evidenced amyloid deposition generalizes well to data from an independent cohort of older people at elevated risk for AD. Future studies will determine the prognostic value of the staging approach for predicting longitudinal cognitive decline in older individuals at increased risk for AD.
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Affiliation(s)
- Fatemah A Sakr
- Department of Psychosomatic Medicine, Clinical Dementia Research, Faculty of Medicine, Rostock University, Rostock, Germany. .,German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany.
| | - Michel J Grothe
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany
| | - Enrica Cavedo
- AXA Research Fund and Sorbonne University Chair, Paris, France.,Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l'hôpital, F-75013, Paris, France.,Brain and Spine Institute (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l'hôpital, F-75013, Paris, France.,Department of Neurology, Institute of Memory and Alzheimer's Disease (IM2A), Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l'hôpital, F-75013, Paris, France.,Qynapse, Paris, France
| | | | - Marie-Odile Habert
- Sorbonne University, UPMC University Paris 06, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, F-75013, Paris, France.,Multi-center Neuroimaging Platform.,Department of Nuclear Medicine, Pitié-Salpêtrière Hospital, AP-HP, F-75013, Paris, France
| | - Martin Dyrba
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany
| | - Gabriel Gonzalez-Escamilla
- Department of Neurology, University Medical Center of the Johannes-Gutenberg-University Mainz, Langenbeck str, 155131, Mainz, Germany
| | | | - Maxime Locatelli
- Sorbonne University, UPMC University Paris 06, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, F-75013, Paris, France.,Multi-center Neuroimaging Platform.,Department of Nuclear Medicine, Pitié-Salpêtrière Hospital, AP-HP, F-75013, Paris, France
| | - Stephane Lehericy
- Brain and Spine Institute (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l'hôpital, F-75013, Paris, France.,Multi-center Neuroimaging Platform.,Centre de NeuroImagerie de Recherche (CENIR), Institut du Cerveau et de la Moelle Epiniere (ICM), Paris, France.,Department of Neuroradiology, Salpêtriere Hospital, Paris, France
| | - Stefan Teipel
- Department of Psychosomatic Medicine, Clinical Dementia Research, Faculty of Medicine, Rostock University, Rostock, Germany.,German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany
| | - Bruno Dubois
- Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l'hôpital, F-75013, Paris, France.,Brain and Spine Institute (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l'hôpital, F-75013, Paris, France.,Department of Neurology, Institute of Memory and Alzheimer's Disease (IM2A), Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l'hôpital, F-75013, Paris, France
| | - Harald Hampel
- AXA Research Fund and Sorbonne University Chair, Paris, France.,Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l'hôpital, F-75013, Paris, France.,Brain and Spine Institute (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l'hôpital, F-75013, Paris, France.,Department of Neurology, Institute of Memory and Alzheimer's Disease (IM2A), Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l'hôpital, F-75013, Paris, France
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Verfaillie SCJ, Timmers T, Slot RER, van der Weijden CWJ, Wesselman LMP, Prins ND, Sikkes SAM, Yaqub M, Dols A, Lammertsma AA, Scheltens P, Ossenkoppele R, van Berckel BNM, van der Flier WM. Amyloid-β Load Is Related to Worries, but Not to Severity of Cognitive Complaints in Individuals With Subjective Cognitive Decline: The SCIENCe Project. Front Aging Neurosci 2019; 11:7. [PMID: 30760996 PMCID: PMC6362417 DOI: 10.3389/fnagi.2019.00007] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2018] [Accepted: 01/10/2019] [Indexed: 02/05/2023] Open
Abstract
Objective: Subjective cognitive decline (SCD) is associated with an increased risk of Alzheimer's Disease (AD). Early disease processes, such as amyloid-β aggregation measured with quantitative PET, may help to explain the phenotype of SCD. The aim of this study was to investigate whether quantitative amyloid-β load is associated with both self- and informant-reported cognitive complaints and memory deficit awareness in individuals with SCD. Methods: We included 106 SCD patients (mean ± SD age: 64 ± 8, 45%F) with 90 min dynamic [18F]florbetapir PET scans. We used the following questionnaires to assess SCD severity: cognitive change index (CCI, self and informant reports; 2 × 20 items), subjective cognitive functioning (SCF, four items), and five questions "Do you have complaints?" (yes/no) for memory, attention, organization and language), and "Does this worry you? (yes/no)." The Rivermead Behavioral Memory Test (RBMT)-Stories (immediate and delayed recall) was used to assess objective episodic memory. To investigate the level of self-awareness, we calculated a memory deficit awareness index (Z-transformed (inverted self-reported CCI minus episodic memory); higher index, heightened self-awareness) and a self-proxy index (Z-transformed self- minus informant-reported CCI). Mean cortical [18F]florbetapir binding potential (BPND) was derived from the PET data. Logistic and linear regression analyses, adjusted for age, sex, education, and depressive symptoms, were used to investigate associations between BPND and measures of SCD. Results: Higher mean cortical [18F]florbetapir BPND was associated with SCD-related worries (odds ratio = 1.76 [95%CI = 1.07 ± 2.90]), but not with other SCD questionnaires (informant and self-report CCI or SCF, total scores or individual items, all p > 0.05). In addition, higher mean cortical [18F]florbetapir BPND was associated with a higher memory deficit awareness index (Beta = 0.55), with an interaction between BPND and education (p = 0.002). There were no associations between [18F]florbetapir BPND and self-proxy index (Beta = 0.11). Conclusion: Amyloid-β deposition was associated with SCD-related worries and heightened memory deficit awareness (i.e., hypernosognosia), but not with severity of cognitive complaints. Our findings indicate that worries about self-perceived decline may reflect an early symptom of amyloid-β related pathology rather than subjective cognitive functioning.
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Affiliation(s)
- Sander C J Verfaillie
- Department of Neurology and Alzheimer Center, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Tessa Timmers
- Department of Neurology and Alzheimer Center, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Rosalinde E R Slot
- Department of Neurology and Alzheimer Center, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Chris W J van der Weijden
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Linda M P Wesselman
- Department of Neurology and Alzheimer Center, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Niels D Prins
- Department of Neurology and Alzheimer Center, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Sietske A M Sikkes
- Department of Neurology and Alzheimer Center, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Amsterdam Neuroscience, Amsterdam, Netherlands.,Department of Epidemiology and Biostatistics, Amsterdam Neuroscience, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Maqsood Yaqub
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Annemiek Dols
- Department of Neurology and Alzheimer Center, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Amsterdam Neuroscience, Amsterdam, Netherlands.,Department of Old Age Psychiatry, Amsterdam Neuroscience, GGZ inGeest, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Adriaan A Lammertsma
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Philip Scheltens
- Department of Neurology and Alzheimer Center, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Rik Ossenkoppele
- Department of Neurology and Alzheimer Center, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Amsterdam Neuroscience, Amsterdam, Netherlands.,Clinical Memory Research Unit, Lund University, Malmö, Sweden
| | - Bart N M van Berckel
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Wiesje M van der Flier
- Department of Neurology and Alzheimer Center, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Amsterdam Neuroscience, Amsterdam, Netherlands.,Department of Epidemiology and Biostatistics, Amsterdam Neuroscience, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
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222
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Kamil RJ, Bilgel M, Wong DF, Resnick SM, Agrawal Y. Vestibular Function and Beta-Amyloid Deposition in the Baltimore Longitudinal Study of Aging. Front Aging Neurosci 2018; 10:408. [PMID: 30618715 PMCID: PMC6297212 DOI: 10.3389/fnagi.2018.00408] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2018] [Accepted: 11/28/2018] [Indexed: 12/02/2022] Open
Abstract
Beta-amyloid (Aβ) plaque deposition is a key feature of Alzheimer’s disease (AD), and occurs years before the onset of symptoms. Aβ plaque deposition has been shown to be present in ~30% of cognitively normal older adults using amyloid C-11 labeled Pittsburgh Compound B (11C-PiB) Positron Emission Tomography (PET) imaging. Prior studies have reported a link between reduced vestibular function and poorer cognition in healthy older adults. It is unknown whether vestibular impairment occurs in association with AD pathology among individuals in the preclinical phase of AD, which could contribute to the observed association between vestibular and cognitive function in healthy older adults. Using the Baltimore Longitudinal Study of Aging (BLSA), we analyzed the association between a comprehensive set of vestibular function measures and PiB status in 98 healthy participants with a mean age of 77.3 (±8.26). We did not observe a significant relationship between any vestibular function measure and PiB status in cognitively-intact older adults in the BLSA. This finding suggests that Aβ deposition does not explain the observed association between reduced vestibular function and poorer cognition in healthy older adults.
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Affiliation(s)
- Rebecca J Kamil
- Department of Otolaryngology-Head and Neck Surgery, Johns Hopkins University, Baltimore, MD, United States
| | - Murat Bilgel
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, United States
| | - Dean F Wong
- Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, United States
| | - Susan M Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, United States
| | - Yuri Agrawal
- Department of Otolaryngology-Head and Neck Surgery, Johns Hopkins University, Baltimore, MD, United States.,Department of Otolaryngology-Head and Neck Surgery, Division of Otology, Neurotology, and Skull Base Surgery, Johns Hopkins University, Baltimore, MD, United States
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223
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Cohen AD, Landau SM, Snitz BE, Klunk WE, Blennow K, Zetterberg H. Fluid and PET biomarkers for amyloid pathology in Alzheimer's disease. Mol Cell Neurosci 2018; 97:3-17. [PMID: 30537535 DOI: 10.1016/j.mcn.2018.12.004] [Citation(s) in RCA: 53] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2018] [Accepted: 12/05/2018] [Indexed: 02/04/2023] Open
Abstract
Alzheimer's disease (AD) is characterized by amyloid plaques and tau pathology (neurofibrillary tangles and neuropil threads). Amyloid plaques are primarily composed of aggregated and oligomeric β-amyloid (Aβ) peptides ending at position 42 (Aβ42). The development of fluid and PET biomarkers for Alzheimer's disease (AD), has allowed for detection of Aβ pathology in vivo and marks a major advancement in understanding the role of Aβ in Alzheimer's disease (AD). In the recent National Institute on Aging and Alzheimer's Association (NIA-AA) Research Framework, AD is defined by the underlying pathology as measured in patients during life by biomarkers (Jack et al., 2018), while clinical symptoms are used for staging of the disease. Therefore, sensitive, specific and robust biomarkers to identify brain amyloidosis are central in AD research. Here, we discuss fluid and PET biomarkers for Aβ and their application.
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Affiliation(s)
- Ann D Cohen
- Department of Psychiatry, University of Pittsburgh School of Medicine, United States of America.
| | - Susan M Landau
- Neurology Helen Wills Neuroscience Institute, University of California, Berkeley, United States of America; Lawrence Berkeley National Laboratory, Molecular Biophysics and Integrated Bioimaging Functional Imaging Department, Life Sciences Division, United States of America
| | - Beth E Snitz
- Department of Neurology, University of Pittsburgh School of Medicine, United States of America
| | - William E Klunk
- Department of Psychiatry, University of Pittsburgh School of Medicine, United States of America
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Molndal, Sweden; Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, University College, London, United Kingdom of Great Britain and Northern Ireland
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Molndal, Sweden; Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, University College, London, United Kingdom of Great Britain and Northern Ireland; Department of Molecular Neuroscience, UCL Institute of Neurology, United Kingdom of Great Britain and Northern Ireland; UK Dementia Research Institute at UCL, United Kingdom of Great Britain and Northern Ireland
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Surendranathan A, Su L, Mak E, Passamonti L, Hong YT, Arnold R, Vázquez Rodríguez P, Bevan-Jones WR, Brain SAE, Fryer TD, Aigbirhio FI, Rowe JB, O’Brien JT. Early microglial activation and peripheral inflammation in dementia with Lewy bodies. Brain 2018; 141:3415-3427. [PMID: 30403785 PMCID: PMC6262214 DOI: 10.1093/brain/awy265] [Citation(s) in RCA: 87] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2018] [Revised: 07/31/2018] [Accepted: 09/05/2018] [Indexed: 12/17/2022] Open
Abstract
Inflammation is increasingly recognized as part of the pathology of neurodegenerative conditions such as Alzheimer's disease and Parkinson's disease, but its role in dementia with Lewy bodies remains unclear. Using multimodal imaging and peripheral cytokine analysis, we therefore investigated central and peripheral inflammation in this common form of dementia. Nineteen participants with probable dementia with Lewy bodies and 16 similarly aged controls underwent 3 T MRI and PET imaging with 11C-PK11195, a marker of microglial activation in vivo. Peripheral blood inflammatory cytokines were also measured in all subjects, as well as in an additional 10 controls, using the Mesoscale Human Cytokine 36 plex panel and additional assays for high sensitivity c-reactive protein, tumour necrosis factor receptor 1, IL-34, YKL-40 (chitinase-3-like protein 1) and colony stimulating factor 1. To test for the presence of in vivo amyloid, 11C-Pittsburgh compound B PET imaging was also performed in 16 of the dementia with Lewy body participants. Microglial activation was elevated in dementia with Lewy bodies subjects with mild disease when compared to those with moderate/severe impairment, where disease severity was indexed by cognitive performance on the revised Addenbrooke's Cognitive Examination. In patients, strong correlations were found between cognitive performance and 11C-PK11195 non-displaceable binding potential in several regions including the caudate nucleus (R = 0.83, P = 0.00008) and cuneus (R = 0.77, P = 0.0005). Several inflammatory cytokines were altered in the patients compared to controls, with elevated macrophage inflammatory protein-3 (P = 0.001), IL-17A (P = 0.008) and IL-2 (P = 0.046) and reduced IL-8 (P = 0.024). There was no correlation between cortical 11C-Pittsburgh compound B standardized uptake value ratio and clinical features, regional 11C-PK11195 binding or peripheral cytokine levels. Nor was there any regional correlation between 11C-PK11195 non-displaceable binding potentials and 11C-Pittsburgh compound B standardized uptake value ratios. Our findings provide evidence for both central and peripheral inflammatory changes in dementia with Lewy bodies, with microglial activation occurring early in the disease in key regions known to be associated with pathology, before declining as cognition declines. Raised peripheral cytokines associated with T cell function further suggest a role for the adaptive immune system in the pathogenesis of the disease.
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Affiliation(s)
| | - Li Su
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Sino-Britain Centre for Cognition and Ageing Research, Faculty of Psychology, Southwest University, Chongqing, China
| | - Elijah Mak
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Luca Passamonti
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Young T Hong
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - Robert Arnold
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | | | | | | | - Tim D Fryer
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - Franklin I Aigbirhio
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - James B Rowe
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - John T O’Brien
- Department of Psychiatry, University of Cambridge, Cambridge, UK
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Knezevic D, Verhoeff NPL, Hafizi S, Strafella AP, Graff-Guerrero A, Rajji T, Pollock BG, Houle S, Rusjan PM, Mizrahi R. Imaging microglial activation and amyloid burden in amnestic mild cognitive impairment. J Cereb Blood Flow Metab 2018; 38:1885-1895. [PMID: 29135331 PMCID: PMC6259323 DOI: 10.1177/0271678x17741395] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Amnestic mild cognitive impairment (aMCI) is defined as a transitional state between normal aging and Alzheimer's disease (AD). Given the replicated finding of increased microglial activation in AD, we sought to investigate whether microglial activation is also elevated in aMCI and whether it is related to amyloid beta (Aβ) burden in-vivo . Eleven aMCI participants and 14 healthy volunteers completed positron emission tomography (PET) scans with [18F]-FEPPA and [11C]-PIB. Given the known sensitivity in affinity of second-generation TSPO radioligands, participants were genotyped for the TSPO polymorphism and only high-affinity binders were included. Dynamic [18F]-FEPPA PET images were analyzed using the 2-tissue compartment model with arterial plasma input function. Additionally, a supplementary method, the standardized uptake value ratio (SUVR), was explored. [11C]-PIB PET images were analyzed using the Logan graphical method. aMCI participants had significantly higher [11C]-PIB binding in the cortical regions. No significant differences in [18F]-FEPPA binding were observed between aMCI participants and healthy volunteers. In the aMCI group, [18F]-FEPPA and [11C]-PIB bindings were correlated in the hippocampus. There were no correlations between our PET measures and cognition. Our findings demonstrate that while Aβ burden is evident in the aMCI stage, microglial activation may not be present.
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Affiliation(s)
- Dunja Knezevic
- 1 University of Toronto, Toronto, Ontario, Canada.,2 Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Nicolaas Paul Lg Verhoeff
- 1 University of Toronto, Toronto, Ontario, Canada.,3 Baycrest Health Sciences, Toronto, Ontario, Canada
| | - Sina Hafizi
- 1 University of Toronto, Toronto, Ontario, Canada
| | - Antonio P Strafella
- 1 University of Toronto, Toronto, Ontario, Canada.,2 Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,4 Toronto Western Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Ariel Graff-Guerrero
- 1 University of Toronto, Toronto, Ontario, Canada.,2 Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Tarek Rajji
- 1 University of Toronto, Toronto, Ontario, Canada.,2 Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Bruce G Pollock
- 1 University of Toronto, Toronto, Ontario, Canada.,2 Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Sylvain Houle
- 1 University of Toronto, Toronto, Ontario, Canada.,2 Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Pablo M Rusjan
- 1 University of Toronto, Toronto, Ontario, Canada.,2 Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Romina Mizrahi
- 1 University of Toronto, Toronto, Ontario, Canada.,2 Centre for Addiction and Mental Health, Toronto, Ontario, Canada
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226
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ten Kate M, Ingala S, Schwarz AJ, Fox NC, Chételat G, van Berckel BNM, Ewers M, Foley C, Gispert JD, Hill D, Irizarry MC, Lammertsma AA, Molinuevo JL, Ritchie C, Scheltens P, Schmidt ME, Visser PJ, Waldman A, Wardlaw J, Haller S, Barkhof F. Secondary prevention of Alzheimer's dementia: neuroimaging contributions. Alzheimers Res Ther 2018; 10:112. [PMID: 30376881 PMCID: PMC6208183 DOI: 10.1186/s13195-018-0438-z] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2018] [Accepted: 10/10/2018] [Indexed: 02/06/2023]
Abstract
BACKGROUND In Alzheimer's disease (AD), pathological changes may arise up to 20 years before the onset of dementia. This pre-dementia window provides a unique opportunity for secondary prevention. However, exposing non-demented subjects to putative therapies requires reliable biomarkers for subject selection, stratification, and monitoring of treatment. Neuroimaging allows the detection of early pathological changes, and longitudinal imaging can assess the effect of interventions on markers of molecular pathology and rates of neurodegeneration. This is of particular importance in pre-dementia AD trials, where clinical outcomes have a limited ability to detect treatment effects within the typical time frame of a clinical trial. We review available evidence for the use of neuroimaging in clinical trials in pre-dementia AD. We appraise currently available imaging markers for subject selection, stratification, outcome measures, and safety in the context of such populations. MAIN BODY Amyloid positron emission tomography (PET) is a validated in-vivo marker of fibrillar amyloid plaques. It is appropriate for inclusion in trials targeting the amyloid pathway, as well as to monitor treatment target engagement. Amyloid PET, however, has limited ability to stage the disease and does not perform well as a prognostic marker within the time frame of a pre-dementia AD trial. Structural magnetic resonance imaging (MRI), providing markers of neurodegeneration, can improve the identification of subjects at risk of imminent decline and hence play a role in subject inclusion. Atrophy rates (either hippocampal or whole brain), which can be reliably derived from structural MRI, are useful in tracking disease progression and have the potential to serve as outcome measures. MRI can also be used to assess comorbid vascular pathology and define homogeneous groups for inclusion or for subject stratification. Finally, MRI also plays an important role in trial safety monitoring, particularly the identification of amyloid-related imaging abnormalities (ARIA). Tau PET to measure neurofibrillary tangle burden is currently under development. Evidence to support the use of advanced MRI markers such as resting-state functional MRI, arterial spin labelling, and diffusion tensor imaging in pre-dementia AD is preliminary and requires further validation. CONCLUSION We propose a strategy for longitudinal imaging to track early signs of AD including quantitative amyloid PET and yearly multiparametric MRI.
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Affiliation(s)
- Mara ten Kate
- Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands
- Alzheimer Center & Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, PO Box 7056, 1007 MB Amsterdam, the Netherlands
| | - Silvia Ingala
- Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands
| | - Adam J. Schwarz
- Takeda Pharmaceuticals Comparny, Cambridge, MA USA
- Eli Lilly and Company, Indianapolis, Indiana USA
| | - Nick C. Fox
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
| | - Gaël Chételat
- Institut National de la Santé et de la Recherche Médicale, Inserm UMR-S U1237, Université de Caen-Normandie, GIP Cyceron, Caen, France
| | - Bart N. M. van Berckel
- Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands
| | - Michael Ewers
- Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-Universität LMU, Munich, Germany
| | | | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
| | | | | | - Adriaan A. Lammertsma
- Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands
| | - José Luis Molinuevo
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
| | - Craig Ritchie
- Centre for Dementia Prevention, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Philip Scheltens
- Alzheimer Center & Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, PO Box 7056, 1007 MB Amsterdam, the Netherlands
| | | | - Pieter Jelle Visser
- Alzheimer Center & Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, PO Box 7056, 1007 MB Amsterdam, the Netherlands
| | - Adam Waldman
- Centre for Dementia Prevention, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Joanna Wardlaw
- Centre for Dementia Prevention, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Dementia Research Centre, University of Edinburgh, Edinburgh, UK
| | - Sven Haller
- Affidea Centre de Diagnostic Radiologique de Carouge, Geneva, Switzerland
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands
- Insititutes of Neurology and Healthcare Engineering, University College London, London, UK
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Amyloid burden identifies neuropsychological phenotypes at increased risk of progression to Alzheimer's disease in mild cognitive impairment patients. Eur J Nucl Med Mol Imaging 2018; 46:288-296. [PMID: 30244387 PMCID: PMC6333718 DOI: 10.1007/s00259-018-4149-2] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2018] [Accepted: 08/26/2018] [Indexed: 02/06/2023]
Abstract
Purpose The extent of amyloid burden associated with cognitive impairment in amnestic mild cognitive impairment is unknown. The primary aim of the study was to determine the extent to which amyloid burden is associated to the cognitive impairment. The secondary objective was to test the relationship between amyloid accumulation and memory or cognitive impairment. Materials and methods In this prospective study 66 participants with amnestic mild cognitive impairment underwent clinical, neuropsychological and PET amyloid imaging tests. Composite scores assessing memory and non-memory domains were used to identify two clinical classes of neuropsychological phenotypes expressing different degree of cognitive impairment. Detection of amyloid status and definition of optimal amyloid ± cutoff for discrimination relied on unsupervised k-means clustering method. Results Threshold for identifying low and high amyloid retention groups was of SUVr = 1.3. Aß + participants showed poorer global cognitive and episodic memory performance than subjects with low amyloid deposition. Aß positivity significantly identified individuals with episodic memory impairment with a sensitivity and specificity of 80 and 79%, (χ2 = 21.48; P < 0.00001). Positive and negative predictive values were 82 and 76%, respectively. Amyloid deposition increased linearly as function of memory impairment with a rate of 0.13/ point of composite memory score (R = −44, P = 0.0003). Conclusion The amyloid burden of SUVr = 1.3 allows early identification of subjects with episodic memory impairment which might predict progression from MCI to Alzheimer’s disease. Trial registration EudraCT 2015-001184-39.
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228
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Dyrba M, Grothe MJ, Mohammadi A, Binder H, Kirste T, Teipel SJ. Comparison of Different Hypotheses Regarding the Spread of Alzheimer’s Disease Using Markov Random Fields and Multimodal Imaging. J Alzheimers Dis 2018; 65:731-746. [DOI: 10.3233/jad-161197] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Martin Dyrba
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Rostock, Germany
| | - Michel J. Grothe
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Rostock, Germany
| | - Abdolreza Mohammadi
- Department of Methodology and Statistics, Tilburg University, Tilburg, The Netherlands
| | - Harald Binder
- Institute of Medical Biostatistics, Epidemiology and Informatics, University Medical Center, Johannes Gutenberg University, Mainz, Germany
| | - Thomas Kirste
- Mobile Multimedia Information Systems Group (MMIS), University of Rostock, Rostock, Germany
| | - Stefan J. Teipel
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Rostock, Germany
- Clinic for Psychosomatic and Psychotherapeutic Medicine, University Medical Center Rostock, Rostock, Germany
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229
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Synergistic interaction between APOE and family history of Alzheimer's disease on cerebral amyloid deposition and glucose metabolism. ALZHEIMERS RESEARCH & THERAPY 2018; 10:84. [PMID: 30134963 PMCID: PMC6106945 DOI: 10.1186/s13195-018-0411-x] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2017] [Accepted: 07/23/2018] [Indexed: 02/07/2023]
Abstract
Background Recently, the field of gene-gene or gene-environment interaction research appears to have gained growing interest, although it is seldom investigated in Alzheimer’s disease (AD). Hence, the current study aims to investigate interaction effects of the key genetic and environmental risks—the apolipoprotein ε4 allele (APOE4) and family history of late-onset AD (FH)—on AD-related brain changes in cognitively normal (CN) middle-aged and older adults. Methods [11C] Pittsburg compound-B (PiB) positron emission tomography (PET) imaging as well as [18F] fluoro-2-deoxyglucose (FDG) PET that were simultaneously taken with T1-weighted magnetic resonance imaging (MRI) were obtained from 268 CNs from the Korean Brain Aging Study for Early Diagnosis and Prediction of AD (KBASE). Composite standardized uptake value ratios were obtained from PiB-PET and FDG-PET images in the AD signature regions of interests (ROIs) and analyzed. Voxel-wise analyses were also performed to examine detailed regional changes not captured by the ROI analyses. Results A significant synergistic interaction effect was found between the APOE4 and FH on amyloid-beta (Aβ) deposition in the AD signature ROIs as well as other regions. Synergistic interaction effects on cerebral glucose metabolism were observed in the regions not captured by the AD signature ROIs, particularly in the medial temporal regions. Conclusions Strong synergistic effects of APOE4 and FH on Aβ deposition and cerebral glucose metabolism in CN adults indicate possible gene-to-gene or gene-to-environment interactions that are crucial for pathogenesis of AD involving Aβ. Other unspecified risk factors—genes and/or environmental—that are captured by the positive FH status might either coexpress or interact with APOE4 to alter AD-related brain changes in CN. Healthy people with both FH and APOE4 need more attention for AD prevention. Electronic supplementary material The online version of this article (10.1186/s13195-018-0411-x) contains supplementary material, which is available to authorized users.
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230
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Song Z, Farrell ME, Chen X, Park DC. Longitudinal accrual of neocortical amyloid burden is associated with microstructural changes of the fornix in cognitively normal adults. Neurobiol Aging 2018; 68:114-122. [PMID: 29602495 PMCID: PMC5993596 DOI: 10.1016/j.neurobiolaging.2018.02.021] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2017] [Revised: 02/20/2018] [Accepted: 02/21/2018] [Indexed: 02/02/2023]
Abstract
The fornix and parahippocampal cingulum are 2 major limbic tracts in the core memory network of the hippocampus. Although these fiber tracts are known to degrade with Alzheimer's disease (AD), little is known about their vulnerability in the asymptomatic phase of AD. In this longitudinal study of cognitively normal adults, we assessed amyloid-beta (Aβ) plaques using positron emission tomography and white matter microstructure using diffusion tensor imaging. We found that an increase of neocortical Aβ burden over time was associated with an increase of radial diffusivity in the fornix but not in the parahippocampal cingulum. The effect of increasing neocortical Aβ burden on the fornix remained significant after controlling for baseline measures, head motion, global brain atrophy, regional Aβ burden in the hippocampus, or microstructural changes in the global white matter. In addition, microstructural changes in the fornix were not associated with decline of episodic memory or other cognitive abilities. Our findings suggest that microstructural changes in the fornix may be an early sign in the asymptomatic phase of AD.
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Affiliation(s)
- Zhuang Song
- Center for Vital Longevity, University of Texas at Dallas, Dallas, TX, USA.
| | - Michelle E Farrell
- Center for Vital Longevity, University of Texas at Dallas, Dallas, TX, USA
| | - Xi Chen
- Center for Vital Longevity, University of Texas at Dallas, Dallas, TX, USA
| | - Denise C Park
- Center for Vital Longevity, University of Texas at Dallas, Dallas, TX, USA; Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
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231
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Verfaillie SCJ, Slot RER, Dicks E, Prins ND, Overbeek JM, Teunissen CE, Scheltens P, Barkhof F, van der Flier WM, Tijms BM. A more randomly organized grey matter network is associated with deteriorating language and global cognition in individuals with subjective cognitive decline. Hum Brain Mapp 2018; 39:3143-3151. [PMID: 29602212 PMCID: PMC6055627 DOI: 10.1002/hbm.24065] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2017] [Revised: 03/12/2018] [Accepted: 03/20/2018] [Indexed: 11/23/2022] Open
Abstract
OBJECTIVES Grey matter network disruptions in Alzheimer's disease (AD) are associated with worse cognitive impairment cross-sectionally. Our aim was to investigate whether indications of a more random network organization are associated with longitudinal decline in specific cognitive functions in individuals with subjective cognitive decline (SCD). EXPERIMENTAL DESIGN We included 231 individuals with SCD who had annually repeated neuropsychological assessment (3 ± 1 years; n = 646 neuropsychological investigations) available from the Amsterdam Dementia Cohort (54% male, age: 63 ± 9, MMSE: 28 ± 2). Single-subject grey matter networks were extracted from baseline 3D-T1 MRI scans and we computed basic network (size, degree, connectivity density) and higher-order (path length, clustering, betweenness centrality, normalized path length [lambda] and normalized clustering [gamma]) parameters at whole brain and/or regional levels. We tested associations of network parameters with baseline and annual cognition (memory, attention, executive functioning, language composite scores, and global cognition [all domains with MMSE]) using linear mixed models, adjusted for age, sex, education, scanner and total gray matter volume. PRINCIPAL OBSERVATIONS Lower network size was associated with steeper decline in language (β ± SE = 0.12 ± 0.05, p < 0.05FDR). Higher-order network parameters showed no cross-sectional associations. Lower gamma and lambda values were associated with steeper decline in global cognition (gamma: β ± SE = 0.06 ± 0.02); lambda: β ± SE = 0.06 ± 0.02), language (gamma: β ± SE = 0.11 ± 0.04; lambda: β ± SE = 0.12 ± 0.05; all p < 0.05FDR). Lower path length values in precuneus and fronto-temporo-occipital cortices were associated with a steeper decline in global cognition. CONCLUSIONS A more randomly organized grey matter network was associated with a steeper decline of cognitive functioning, possibly indicating the start of cognitive impairment.
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Affiliation(s)
- Sander C. J. Verfaillie
- Department of Neurology and Alzheimer CenterVU University Medical Center, AmsterdamThe Netherlands
| | - Rosalinde E. R. Slot
- Department of Neurology and Alzheimer CenterVU University Medical Center, AmsterdamThe Netherlands
| | - Ellen Dicks
- Department of Neurology and Alzheimer CenterVU University Medical Center, AmsterdamThe Netherlands
| | - Niels D. Prins
- Department of Neurology and Alzheimer CenterVU University Medical Center, AmsterdamThe Netherlands
| | - Jozefien M. Overbeek
- Department of Neurology and Alzheimer CenterVU University Medical Center, AmsterdamThe Netherlands
| | | | - Philip Scheltens
- Department of Neurology and Alzheimer CenterVU University Medical Center, AmsterdamThe Netherlands
| | - Frederik Barkhof
- Department of Radiology & Nuclear MedicineVU University Medical Center, AmsterdamThe Netherlands
- Institutes of Neurology and Healthcare EngineeringUCLLondonUnited Kingdom
| | - Wiesje M. van der Flier
- Department of Neurology and Alzheimer CenterVU University Medical Center, AmsterdamThe Netherlands
- Department of Epidemiology & BiostatisticsVU University Medical Center, AmsterdamThe Netherlands
| | - Betty M. Tijms
- Department of Neurology and Alzheimer CenterVU University Medical Center, AmsterdamThe Netherlands
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232
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Molecular imaging in dementia: Past, present, and future. Alzheimers Dement 2018; 14:1522-1552. [DOI: 10.1016/j.jalz.2018.06.2855] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2017] [Revised: 06/02/2018] [Accepted: 06/03/2018] [Indexed: 12/14/2022]
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233
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Fredericks CA, Sturm VE, Brown JA, Hua AY, Bilgel M, Wong DF, Resnick SM, Seeley WW. Early affective changes and increased connectivity in preclinical Alzheimer's disease. ALZHEIMER'S & DEMENTIA: DIAGNOSIS, ASSESSMENT & DISEASE MONITORING 2018; 10:471-479. [PMID: 30302368 PMCID: PMC6174255 DOI: 10.1016/j.dadm.2018.06.002] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Introduction Affective changes precede cognitive decline in mild Alzheimer's disease and may relate to increased connectivity in a “salience network” attuned to emotionally significant stimuli. The trajectory of affective changes in preclinical Alzheimer's disease, and its relationship to this network, is unknown. Methods One hundred one cognitively normal older adults received longitudinal assessments of affective symptoms, then amyloid-PET. We hypothesized amyloid-positive individuals would show enhanced emotional reactivity associated with salience network connectivity. We tested whether increased global connectivity in key regions significantly related to affective changes. Results In participants later found to be amyloid positive, emotional reactivity increased with age, and interpersonal warmth declined in women. These individuals showed higher global connectivity within the right insula and superior temporal sulcus; higher superior temporal sulcus connectivity predicted increasing emotional reactivity and decreasing interpersonal warmth. Conclusions Affective changes should be considered an early preclinical feature of Alzheimer's disease. These changes may relate to higher functional connectivity in regions critical for social-emotional processing.
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Affiliation(s)
- Carolyn A. Fredericks
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
- Corresponding author. Tel.: 650 721 5357; Fax: 650 725 0390.
| | - Virginia E. Sturm
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Jesse A. Brown
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Alice Y. Hua
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Murat Bilgel
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA
| | - Dean F. Wong
- Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, USA
| | - Susan M. Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA
| | - William W. Seeley
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
- Department of Pathology, University of California, San Francisco, CA, USA
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234
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Harrison TM, Maass A, Baker SL, Jagust WJ. Brain morphology, cognition, and β-amyloid in older adults with superior memory performance. Neurobiol Aging 2018; 67:162-170. [PMID: 29665578 PMCID: PMC5955827 DOI: 10.1016/j.neurobiolaging.2018.03.024] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2017] [Revised: 02/22/2018] [Accepted: 03/21/2018] [Indexed: 02/04/2023]
Abstract
The mechanisms underlying superior cognitive performance in some older adults are poorly understood. We used a multimodal approach to characterize imaging and cognitive features of 26 successful agers (SA; defined by superior episodic memory ability) and 103 typical older adults. Cortical thickness was greater in multiple regions in SA including right anterior cingulate and prefrontal cortex and was related to baseline memory performance. Similarly, hippocampal volume was greater in SA and associated with baseline memory. SA also had lower white matter hypointensity volumes and faster processing speed. While PiB burden did not differ, there was a significant group interaction in the relationship between age and PiB such that older SA individuals were less likely to have high brain β-amyloid. Over time, memory performance in typical older adults declined more rapidly than in SA, although there was limited evidence for different rates of brain atrophy. These findings indicate that superior memory in aging is related to greater cortical and white matter integrity as well as slower decline in memory performance.
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Affiliation(s)
| | - Anne Maass
- Helen Wills Neuroscience Institute, UC Berkeley, Berkeley, CA, USA; German Center for Neurodegenerative Diseases, Magdeburg, Germany
| | | | - William J Jagust
- Helen Wills Neuroscience Institute, UC Berkeley, Berkeley, CA, USA; Lawrence Berkeley National Laboratory, Berkeley, CA, USA
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Pascoal TA, Mathotaarachchi S, Shin M, Park AY, Mohades S, Benedet AL, Kang MS, Massarweh G, Soucy JP, Gauthier S, Rosa-Neto P. Amyloid and tau signatures of brain metabolic decline in preclinical Alzheimer's disease. Eur J Nucl Med Mol Imaging 2018; 45:1021-1030. [PMID: 29396637 PMCID: PMC5915512 DOI: 10.1007/s00259-018-3933-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2017] [Accepted: 01/02/2018] [Indexed: 01/18/2023]
Abstract
PURPOSE We aimed to determine the amyloid (Aβ) and tau biomarker levels associated with imminent Alzheimer's disease (AD) - related metabolic decline in cognitively normal individuals. METHODS A threshold analysis was performed in 120 cognitively normal elderly individuals by modelling 2-year declines in brain glucose metabolism measured with [18F]fluorodeoxyglucose ([18F]FDG) as a function of [18F]florbetapir Aβ positron emission tomography (PET) and cerebrospinal fluid phosphorylated tau biomarker thresholds. Additionally, using a novel voxel-wise analytical framework, we determined the sample sizes needed to test an estimated 25% drugeffect with 80% of power on changes in FDG uptake over 2 years at every brain voxel. RESULTS The combination of [18F]florbetapir standardized uptake value ratios and phosphorylated-tau levels more than one standard deviation higher than their respective thresholds for biomarker abnormality was the best predictor of metabolic decline in individuals with preclinical AD. We also found that a clinical trial using these thresholds would require as few as 100 individuals to test a 25% drug effect on AD-related metabolic decline over 2 years. CONCLUSIONS These results highlight the new concept that combined Aβ and tau thresholds can predict imminent neurodegeneration as an alternative framework with a high statistical power for testing the effect of disease-modifying therapies on [18F]FDG uptake decline over a typical 2-year clinical trial period in individuals with preclinical AD.
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Affiliation(s)
- Tharick A Pascoal
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, 6875 La Salle Blvd - FBC room 3149, Montreal, QC, H4H 1R3, Canada
| | - Sulantha Mathotaarachchi
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, 6875 La Salle Blvd - FBC room 3149, Montreal, QC, H4H 1R3, Canada
| | - Monica Shin
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, 6875 La Salle Blvd - FBC room 3149, Montreal, QC, H4H 1R3, Canada
| | - Ah Yeon Park
- Statistical Laboratory, University of Cambridge, Cambridge, UK
| | - Sara Mohades
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, 6875 La Salle Blvd - FBC room 3149, Montreal, QC, H4H 1R3, Canada
| | - Andrea L Benedet
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, 6875 La Salle Blvd - FBC room 3149, Montreal, QC, H4H 1R3, Canada
| | - Min Su Kang
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, 6875 La Salle Blvd - FBC room 3149, Montreal, QC, H4H 1R3, Canada
| | | | - Jean-Paul Soucy
- Montreal Neurological Institute, Montreal, Canada
- PERFORM Centre, Concordia University, Montreal, Canada
| | - Serge Gauthier
- Alzheimer's Disease Research Unit, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Canada
| | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, 6875 La Salle Blvd - FBC room 3149, Montreal, QC, H4H 1R3, Canada.
- Montreal Neurological Institute, Montreal, Canada.
- Alzheimer's Disease Research Unit, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Canada.
- Department of Neurology and Neurosurgery, McGill University, Montreal, Canada.
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Berry AS, Shah VD, Jagust WJ. The Influence of Dopamine on Cognitive Flexibility Is Mediated by Functional Connectivity in Young but Not Older Adults. J Cogn Neurosci 2018; 30:1330-1344. [PMID: 29791298 DOI: 10.1162/jocn_a_01286] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Dopaminergic signaling in striatum is strongly implicated in executive functions including cognitive flexibility. However, there is a paucity of multimodal research in humans defining the nature of relationships between endogenous dopamine, striatal network activity, and cognition. Here, we measured dopamine synthesis capacity in young and older adults using the PET tracer 6-[18F]fluoro-l- m-tyrosine and examined its relationship with cognitive performance and functional connectivity during an fMRI study of task switching. Aging is associated with alteration in dopamine function, including profound losses in dopamine receptors but an apparent elevation in dopamine synthesis. A compensatory benefit of upregulated dopamine synthesis in aging has not been established. Across young and older adults, we found that cognitive flexibility (low behavioral switch cost) was associated with stronger task-related functional connectivity within canonical fronto-striato-thalamic circuits connecting left inferior frontal gyrus, dorsal caudate nucleus (DCA) and ventral lateral/ventral anterior thalamic nuclei. In young adults, functional connectivity mediated the influence of DCA dopamine synthesis capacity on switch cost. For older adults, these relationships were modified such that DCA synthesis capacity and connectivity interacted to influence switch cost. Older adults with most elevated synthesis capacity maintained the pattern of connectivity-cognition relationships observed in youth, whereas these relationships were not evident for older adults with low synthesis capacity. Together, these findings suggest a role of dopamine in tuning striatal circuits to benefit executive function in young adults and clarify the functional impact of elevated dopamine synthesis capacity in aging.
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237
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Neural correlates of episodic memory in the Memento cohort. ALZHEIMERS & DEMENTIA-TRANSLATIONAL RESEARCH & CLINICAL INTERVENTIONS 2018; 4:224-233. [PMID: 29955665 PMCID: PMC6021546 DOI: 10.1016/j.trci.2018.03.010] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Introduction The free and cued selective reminding test is used to identify memory deficits in mild cognitive impairment and demented patients. It allows assessing three processes: encoding, storage, and recollection of verbal episodic memory. Methods We investigated the neural correlates of these three memory processes in a large cohort study. The Memento cohort enrolled 2323 outpatients presenting either with subjective cognitive decline or mild cognitive impairment who underwent cognitive, structural MRI and, for a subset, fluorodeoxyglucose–positron emission tomography evaluations. Results Encoding was associated with a network including parietal and temporal cortices; storage was mainly associated with entorhinal and parahippocampal regions, bilaterally; retrieval was associated with a widespread network encompassing frontal regions. Discussion The neural correlates of episodic memory processes can be assessed in large and standardized cohorts of patients at risk for Alzheimer's disease. Their relation to pathophysiological markers of Alzheimer's disease remains to be studied. This is the largest cohort ever to be used in the study of the morpho-metabolic correlates of episodic memory in human, ensuring the validity of the obtained results. We found that encoding of information is linked to a posterior network previously evidenced to support working memory. The storage process was mainly supported in our study by medial temporal regions. Spontaneous retrieval of stimuli implicated broad neural networks including the frontal regions. These associations were particularly strong in APOE ε4 carriers suggesting that the free and selective reminding test is useful to detect Alzheimer's disease at an early stage.
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238
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Knopman DS, Lundt ES, Therneau TM, Vemuri P, Lowe VJ, Kantarci K, Gunter JL, Senjem ML, Mielke MM, Machulda MM, Roberts RO, Boeve BF, Jones DT, Petersen RC, Jack CR. Joint associations of β-amyloidosis and cortical thickness with cognition. Neurobiol Aging 2018; 65:121-131. [PMID: 29471214 PMCID: PMC5871603 DOI: 10.1016/j.neurobiolaging.2018.01.017] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2017] [Revised: 01/12/2018] [Accepted: 01/22/2018] [Indexed: 01/24/2023]
Abstract
In 1164 cognitively unimpaired persons, aged 50-95 years, from the population-based Mayo Clinic Study of Aging, we examined the relationships of baseline cognition and cognitive changes across the full range of cortical thickness of an Alzheimer signature region of interest and global β-amyloid levels measured by Pittsburgh compound B positron emission tomography (PIB PET) standardized uptake value ratio (SUVR). In machine-learning models accounting for both biomarkers simultaneously, worsening biomarker values were additive and associated with lower baseline global cognition and greater subsequent decline in global cognition. Associations between Alzheimer's disease signature cortical thickness or PIB PET β-amyloid SUVR and baseline cognition were mainly linear. Lower Alzheimer's disease signature cortical thickness values across the entire range of thickness predicted future decline in global cognitive scores, demonstrating its close relationship to cognitive functioning. PIB PET β-amyloid SUVR also predicted cognitive decline across its full range, even when cortical thickness was accounted for. PIB PET β-amyloid's relationship to cognitive decline was nonlinear, more prominent at lower β-amyloid levels and less prominent at higher β-amyloid levels.
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Affiliation(s)
- David S Knopman
- Department of Neurology, Mayo Clinic and Foundation, Rochester, MN, USA; Mayo Clinic Alzheimer's Disease Research Center, Mayo Clinic and Foundation, Rochester, MN, USA.
| | - Emily S Lundt
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Terry M Therneau
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Prashanthi Vemuri
- Mayo Clinic Alzheimer's Disease Research Center, Mayo Clinic and Foundation, Rochester, MN, USA; Department of Radiology, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Val J Lowe
- Mayo Clinic Alzheimer's Disease Research Center, Mayo Clinic and Foundation, Rochester, MN, USA; Department of Radiology, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Kejal Kantarci
- Mayo Clinic Alzheimer's Disease Research Center, Mayo Clinic and Foundation, Rochester, MN, USA; Department of Radiology, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Jeffrey L Gunter
- Department of Radiology, Mayo Clinic and Foundation, Rochester, MN, USA; Department of Information Technology, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Matthew L Senjem
- Department of Radiology, Mayo Clinic and Foundation, Rochester, MN, USA; Department of Information Technology, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Michelle M Mielke
- Department of Neurology, Mayo Clinic and Foundation, Rochester, MN, USA; Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Mary M Machulda
- Mayo Clinic Alzheimer's Disease Research Center, Mayo Clinic and Foundation, Rochester, MN, USA; Division of Psychology, Department of Psychiatry, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Rosebud O Roberts
- Department of Neurology, Mayo Clinic and Foundation, Rochester, MN, USA; Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Bradley F Boeve
- Department of Neurology, Mayo Clinic and Foundation, Rochester, MN, USA; Mayo Clinic Alzheimer's Disease Research Center, Mayo Clinic and Foundation, Rochester, MN, USA
| | - David T Jones
- Department of Neurology, Mayo Clinic and Foundation, Rochester, MN, USA; Mayo Clinic Alzheimer's Disease Research Center, Mayo Clinic and Foundation, Rochester, MN, USA; Department of Radiology, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Ronald C Petersen
- Department of Neurology, Mayo Clinic and Foundation, Rochester, MN, USA; Mayo Clinic Alzheimer's Disease Research Center, Mayo Clinic and Foundation, Rochester, MN, USA; Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Clifford R Jack
- Mayo Clinic Alzheimer's Disease Research Center, Mayo Clinic and Foundation, Rochester, MN, USA; Department of Radiology, Mayo Clinic and Foundation, Rochester, MN, USA
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239
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Subthreshold Amyloid Predicts Tau Deposition in Aging. J Neurosci 2018; 38:4482-4489. [PMID: 29686045 DOI: 10.1523/jneurosci.0485-18.2018] [Citation(s) in RCA: 86] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2018] [Revised: 03/20/2018] [Accepted: 03/27/2018] [Indexed: 01/09/2023] Open
Abstract
Current approaches to the early detection of Alzheimer's disease (AD) rely upon classifying individuals as "positive" or "negative" for biomarkers related to the core pathology of β-amyloid (Aβ). However, the accumulation of Aβ begins slowly, years before biomarkers become abnormal. We used longitudinal [11C] Pittsburgh Compound B PET scanning and neuropsychological assessment to investigate the earliest changes in AD pathology and how it affects memory in cognitively normal older humans (N = 71; mean age 75 years; 35% male). We used [18F] AV-1451 PET scanning at the end of the observation period to measure subsequent tau deposition in a subset of our sample (N = 37). We found evidence for an inverted-U relationship between baseline Aβ levels and Aβ slope in asymptomatic older adults, suggesting a slowing of Aβ accumulation even in cognitively normal adults. In participants who were nominally amyloid negative, both the rate of amyloid accumulation and the baseline levels of Aβ predicted early tau deposition in cortical Braak regions associated with AD. Amyloid measures were only sensitive to memory decline as baseline levels of Aβ increased, suggesting that pathological accumulation occurs before impacting memory. These findings support the necessity of early intervention with amyloid-lowering therapies even in those who are amyloid negative.SIGNIFICANCE STATEMENT The progressive nature of Alzheimer's disease (AD) necessitates the earliest possible detection of pathological or cognitive change if disease progression is to be slowed. We examined cognitively normal older adults in whom AD pathology is starting to develop, with the goal of early detection of AD pathology or cognitive changes. We found amyloid measures to be sensitive early on in predicting subsequent early tau deposition. Further, it appears that rates of amyloid accumulation already begin to slow in preclinical AD, suggesting that it is a relatively late stage of AD progression. Thus, it is crucial to examine older adults early, before amyloid levels have saturated, to intervene to slow disease progression.
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240
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Longitudinal outcomes of amyloid positive versus negative amnestic mild cognitive impairments: a three-year longitudinal study. Sci Rep 2018; 8:5557. [PMID: 29615677 PMCID: PMC5883059 DOI: 10.1038/s41598-018-23676-w] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2017] [Accepted: 03/12/2018] [Indexed: 12/28/2022] Open
Abstract
We aimed to compare the longitudinal outcome of amnestic mild cognitive impairment (aMCI) patients with significant Pittsburgh Compound B uptake [PiB(+) aMCI] and those without [PiB(−) aMCI]. Cerebral β-amyloid was measured in 47 patients with aMCI using PiB-positron emission tomography (PET) (31 PiB(+) aMCI and 16 PiB(−) aMCI). Clinical (N = 47) and neuropsychological follow-up (N = 37), and follow-up with brain magnetic resonance imaging (N = 38) and PiB-PET (N = 30) were performed for three years. PiB(+) aMCI had a higher risk of progression to dementia (hazard ratio = 3.74, 95% CI = 1.21–11.58) and faster rate of cortical thinning in the bilateral precuneus and right medial and lateral temporal cortices compared to PiB(−) aMCI. Among six PiB(−) aMCI patients who had regional PiB uptake ratio >1.5 in the posterior cingulate cortex (PCC), three (50.0%) progressed to dementia, and two of them had global PiB uptake ratio >1.5 at the follow-up PiB-PET. Our findings suggest that amyloid imaging is important for predicting the prognosis of aMCI patients, and that it is necessary to pay more attention to PiB(−) aMCI with increased regional PiB uptake in the PCC.
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241
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Sharma RA, Varga AW, Bubu OM, Pirraglia E, Kam K, Parekh A, Wohlleber M, Miller MD, Andrade A, Lewis C, Tweardy S, Buj M, Yau PL, Sadda R, Mosconi L, Li Y, Butler T, Glodzik L, Fieremans E, Babb JS, Blennow K, Zetterberg H, Lu SE, Badia SG, Romero S, Rosenzweig I, Gosselin N, Jean-Louis G, Rapoport DM, de Leon MJ, Ayappa I, Osorio RS. Obstructive Sleep Apnea Severity Affects Amyloid Burden in Cognitively Normal Elderly. A Longitudinal Study. Am J Respir Crit Care Med 2018; 197:933-943. [PMID: 29125327 PMCID: PMC6020410 DOI: 10.1164/rccm.201704-0704oc] [Citation(s) in RCA: 164] [Impact Index Per Article: 27.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2017] [Accepted: 11/09/2017] [Indexed: 12/13/2022] Open
Abstract
RATIONALE Recent evidence suggests that obstructive sleep apnea (OSA) may be a risk factor for developing mild cognitive impairment and Alzheimer's disease. However, how sleep apnea affects longitudinal risk for Alzheimer's disease is less well understood. OBJECTIVES To test the hypothesis that there is an association between severity of OSA and longitudinal increase in amyloid burden in cognitively normal elderly. METHODS Data were derived from a 2-year prospective longitudinal study that sampled community-dwelling healthy cognitively normal elderly. Subjects were healthy volunteers between the ages of 55 and 90, were nondepressed, and had a consensus clinical diagnosis of cognitively normal. Cerebrospinal fluid amyloid β was measured using ELISA. Subjects received Pittsburgh compound B positron emission tomography scans following standardized procedures. Monitoring of OSA was completed using a home sleep recording device. MEASUREMENTS AND MAIN RESULTS We found that severity of OSA indices (AHIall [F1,88 = 4.26; P < 0.05] and AHI4% [F1,87 = 4.36; P < 0.05]) were associated with annual rate of change of cerebrospinal fluid amyloid β42 using linear regression after adjusting for age, sex, body mass index, and apolipoprotein E4 status. AHIall and AHI4% were not associated with increases in ADPiB-mask (Alzheimer's disease vulnerable regions of interest Pittsburg compound B positron emission tomography mask) most likely because of the small sample size, although there was a trend for AHIall (F1,28 = 2.96, P = 0.09; and F1,28 = 2.32, not significant, respectively). CONCLUSIONS In a sample of cognitively normal elderly, OSA was associated with markers of increased amyloid burden over the 2-year follow-up. Sleep fragmentation and/or intermittent hypoxia from OSA are likely candidate mechanisms. If confirmed, clinical interventions for OSA may be useful in preventing amyloid build-up in cognitively normal elderly.
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Affiliation(s)
- Ram A. Sharma
- Center for Brain Health, Department of Psychiatry, and
| | - Andrew W. Varga
- Division of Pulmonary, Critical Care and Sleep Medicine, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Omonigho M. Bubu
- Department of Epidemiology and Biostatistics, College of Public Health, University of South Florida, Tampa, Florida
| | | | - Korey Kam
- Division of Pulmonary, Critical Care and Sleep Medicine, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Ankit Parekh
- College of Engineering, The University of Iowa, Iowa City, Iowa
| | | | | | | | - Clifton Lewis
- Center for Brain Health, Department of Psychiatry, and
| | | | - Maja Buj
- Center for Brain Health, Department of Psychiatry, and
| | - Po L. Yau
- Center for Brain Health, Department of Psychiatry, and
| | - Reem Sadda
- Harlem Hospital–Columbia University Medical Center, New York, New York
| | - Lisa Mosconi
- Center for Brain Health, Department of Psychiatry, and
| | - Yi Li
- Center for Brain Health, Department of Psychiatry, and
| | - Tracy Butler
- Center for Brain Health, Department of Psychiatry, and
| | - Lidia Glodzik
- Center for Brain Health, Department of Psychiatry, and
| | - Els Fieremans
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York
| | - James S. Babb
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York
| | - Kaj Blennow
- Institute of Neuroscience and Psychiatry, Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- Institute of Neuroscience and Psychiatry, Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Molecular Neuroscience, UCL Institute of Neurology, Queen Square, London, United Kingdom
| | - Shou E. Lu
- Department of Biostatistics, Rutgers School of Public Health, Piscataway, New Jersey
| | - Sandra G. Badia
- Sleep Unit, Respiratory Department, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
- Institute for Biomedical Research Sant Pau, CIBERSAM, Barcelona, Spain
- Department of Clinical Psychology and Psychobiology, University of Barcelona, Barcelona, Spain
| | - Sergio Romero
- Biomedical Engineering Research Centre, Department of Automatic Control, Universitat Politècnica de Catalunya, Barcelona, Spain
- CIBER de Bioingeniería, Biomateriales y Nanomedicina, Barcelona, Spain
| | - Ivana Rosenzweig
- Sleep and Brain Plasticity Centre, Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- Sleep Disorders Centre, Guy’s and St. Thomas’ Hospital, GSTT NHS Trust, London, United Kingdom
| | - Nadia Gosselin
- Center for Advanced Research in Sleep Medicine, Hospital du Sacre-Coeur de Montreal, Montreal, Quebec, Canada; and
- Department of Psychology, Universite de Montreal, Montreal, Quebec, Canada
| | - Girardin Jean-Louis
- Center for Healthful Behavior Change, Division of Health and Behavior, Department of Population Health, New York University Langone Medical Center, New York, New York
| | - David M. Rapoport
- Division of Pulmonary, Critical Care and Sleep Medicine, Icahn School of Medicine at Mount Sinai, New York, New York
| | | | - Indu Ayappa
- Division of Pulmonary, Critical Care and Sleep Medicine, Icahn School of Medicine at Mount Sinai, New York, New York
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Ten Kate M, Visser PJ, Bakardjian H, Barkhof F, Sikkes SAM, van der Flier WM, Scheltens P, Hampel H, Habert MO, Dubois B, Tijms BM. Gray Matter Network Disruptions and Regional Amyloid Beta in Cognitively Normal Adults. Front Aging Neurosci 2018; 10:67. [PMID: 29599717 PMCID: PMC5863592 DOI: 10.3389/fnagi.2018.00067] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2017] [Accepted: 02/27/2018] [Indexed: 01/03/2023] Open
Abstract
The accumulation of amyloid plaques is one of the earliest pathological changes in Alzheimer's disease (AD) and may occur 20 years before the onset of symptoms. Examining associations between amyloid pathology and other early brain changes is critical for understanding the pathophysiological underpinnings of AD. Alterations in gray matter networks might already start at early preclinical stages of AD. In this study, we examined the regional relationship between amyloid aggregation measured with positron emission tomography (PET) and gray matter network measures in elderly subjects with subjective memory complaints. Single-subject gray matter networks were extracted from T1-weigthed structural MRI in cognitively normal subjects (n = 318, mean age 76.1 ± 3.5, 64% female, 28% amyloid positive). Degree, clustering, path length and small world properties were computed. Global and regional amyloid load was determined using [18F]-Florbetapir PET. Associations between standardized uptake value ratio (SUVr) values and network measures were examined using linear regression models. We found that higher global SUVr was associated with lower clustering (β = -0.12, p < 0.05), and small world values (β = -0.16, p < 0.01). Associations were most prominent in orbito- and dorsolateral frontal and parieto-occipital regions. Local SUVr values showed less anatomical variability and did not convey additional information beyond global amyloid burden. In conclusion, we found that in cognitively normal elderly subjects, increased global amyloid pathology is associated with alterations in gray matter networks that are indicative of incipient network breakdown towards AD dementia.
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Affiliation(s)
- Mara Ten Kate
- Alzheimer Center & Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, Netherlands
| | - Pieter Jelle Visser
- Alzheimer Center & Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, Netherlands.,Department of Psychiatry & Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Hovagim Bakardjian
- Département de Neurologie, Pitié-Salpêtrière University Hospital, Institut de la Mémoire et de la Maladie d'Alzheimer, Paris, France.,Institut du Cerveau et la Moelle Epinière (ICM)/Brain and Spine Institute, Pitié-Salpêtrière Hospital, Sorbonne Universities, Pierre and Marie Curie University, Paris, France
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, Netherlands.,Institutes of Neurology and Healthcare Engineering, University College London, London, United Kingdom
| | - Sietske A M Sikkes
- Alzheimer Center & Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, Netherlands.,Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center & Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, Netherlands.,Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, Netherlands
| | - Philip Scheltens
- Alzheimer Center & Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, Netherlands
| | - Harald Hampel
- Département de Neurologie, Pitié-Salpêtrière University Hospital, Institut de la Mémoire et de la Maladie d'Alzheimer, Paris, France.,Institut du Cerveau et la Moelle Epinière (ICM)/Brain and Spine Institute, Pitié-Salpêtrière Hospital, Sorbonne Universities, Pierre and Marie Curie University, Paris, France.,AXA Research Fund & Sorbonne University Chair, Paris, France.,Sorbonne University, GRC no. 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Paris, France
| | - Marie-Odile Habert
- Nuclear Medicine Department, Laboratoire d'Imagerie Biomédicale, Sorbonne Universités, Pitié-Salpêtrière University Hospital, Paris, France
| | - Bruno Dubois
- Département de Neurologie, Pitié-Salpêtrière University Hospital, Institut de la Mémoire et de la Maladie d'Alzheimer, Paris, France.,Institut du Cerveau et la Moelle Epinière (ICM)/Brain and Spine Institute, Pitié-Salpêtrière Hospital, Sorbonne Universities, Pierre and Marie Curie University, Paris, France
| | - Betty M Tijms
- Alzheimer Center & Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, Netherlands
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Hwang JY, Byun MS, Choe YM, Lee JH, Yi D, Choi JW, Hwang SH, Lee YJ, Lee DY. Moderating effect of APOE ε4 on the relationship between sleep-wake cycle and brain β-amyloid. Neurology 2018; 90:e1167-e1173. [PMID: 29490913 DOI: 10.1212/wnl.0000000000005193] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2016] [Accepted: 12/22/2017] [Indexed: 01/21/2023] Open
Abstract
OBJECTIVES To clarify the relationships between sleep-wake cycle and cerebral β-amyloid (Aβ) deposition in cognitively normal (CN) older adults, focusing primarily on the moderating effects of the APOE ε4 allele. METHODS The present study included 133 CN older adults who participated in the Korean Brain Aging Study for Early Diagnosis & Prediction of Alzheimer's Disease cohort. All participants underwent [11C] Pittsburgh compound B-PET imaging to quantify Aβ deposition in the brain and blood sampling for APOE genotyping. Sleep and circadian parameters were measured using actigraphy for 8 consecutive days. RESULTS The APOE ε4 allele had moderating effects on the associations of sleep latency (SL), mesor, and acrophase with cerebral Aβ deposition, and the interactions between APOE ε4 status and SL and between APOE ε4 status and acrophase remained significant after adjusting for multiple comparisons. In APOE ε4 noncarriers, shorter SL, higher mesor, and advanced acrophase were associated with Aβ positivity. In contrast, APOE ε4 carriers showed a relationship between delayed acrophase and Aβ accumulation that approached but did not reach significance. After the Bonferroni correction, the associations of shorter SL and higher mesor with Aβ positivity remained significant for APOE ε4 noncarriers. CONCLUSIONS Our findings suggest that the APOE ε4 allele may act as a moderator in the relationship between the sleep-wake cycle and Aβ accumulation in CN older adults. Thus, APOE ε4 status needs to be considered as a key factor when designing related research or interventions.
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Affiliation(s)
- Jeong Yeon Hwang
- From the Department of Psychiatry (Y.J.L., D.Y.L.), Seoul National University College of Medicine (J.Y.H.); Medical Research Center, Institute of Human Behavioral Medicine (M.S.B., D.Y.L.), Seoul National University; Department of Neuropsychiatry (Y.M.C.), University of Ulsan College of Medicine, Ulsan University Hospital; Department of Psychiatry (J.-W.C.), Eulji General Hospital; Department of Neuropsychiatry (J.H.L., Y.J.L., D.Y.L.), Center for Sleep and Chronobiology (Y.J.L.), Seoul National University Hospital; and Health Service Group (S.H.H.), Samsung Electronics, Co., Ltd., Suwon, Republic of Korea
| | - Min Soo Byun
- From the Department of Psychiatry (Y.J.L., D.Y.L.), Seoul National University College of Medicine (J.Y.H.); Medical Research Center, Institute of Human Behavioral Medicine (M.S.B., D.Y.L.), Seoul National University; Department of Neuropsychiatry (Y.M.C.), University of Ulsan College of Medicine, Ulsan University Hospital; Department of Psychiatry (J.-W.C.), Eulji General Hospital; Department of Neuropsychiatry (J.H.L., Y.J.L., D.Y.L.), Center for Sleep and Chronobiology (Y.J.L.), Seoul National University Hospital; and Health Service Group (S.H.H.), Samsung Electronics, Co., Ltd., Suwon, Republic of Korea
| | - Young Min Choe
- From the Department of Psychiatry (Y.J.L., D.Y.L.), Seoul National University College of Medicine (J.Y.H.); Medical Research Center, Institute of Human Behavioral Medicine (M.S.B., D.Y.L.), Seoul National University; Department of Neuropsychiatry (Y.M.C.), University of Ulsan College of Medicine, Ulsan University Hospital; Department of Psychiatry (J.-W.C.), Eulji General Hospital; Department of Neuropsychiatry (J.H.L., Y.J.L., D.Y.L.), Center for Sleep and Chronobiology (Y.J.L.), Seoul National University Hospital; and Health Service Group (S.H.H.), Samsung Electronics, Co., Ltd., Suwon, Republic of Korea
| | - Jun Ho Lee
- From the Department of Psychiatry (Y.J.L., D.Y.L.), Seoul National University College of Medicine (J.Y.H.); Medical Research Center, Institute of Human Behavioral Medicine (M.S.B., D.Y.L.), Seoul National University; Department of Neuropsychiatry (Y.M.C.), University of Ulsan College of Medicine, Ulsan University Hospital; Department of Psychiatry (J.-W.C.), Eulji General Hospital; Department of Neuropsychiatry (J.H.L., Y.J.L., D.Y.L.), Center for Sleep and Chronobiology (Y.J.L.), Seoul National University Hospital; and Health Service Group (S.H.H.), Samsung Electronics, Co., Ltd., Suwon, Republic of Korea
| | - Dahyun Yi
- From the Department of Psychiatry (Y.J.L., D.Y.L.), Seoul National University College of Medicine (J.Y.H.); Medical Research Center, Institute of Human Behavioral Medicine (M.S.B., D.Y.L.), Seoul National University; Department of Neuropsychiatry (Y.M.C.), University of Ulsan College of Medicine, Ulsan University Hospital; Department of Psychiatry (J.-W.C.), Eulji General Hospital; Department of Neuropsychiatry (J.H.L., Y.J.L., D.Y.L.), Center for Sleep and Chronobiology (Y.J.L.), Seoul National University Hospital; and Health Service Group (S.H.H.), Samsung Electronics, Co., Ltd., Suwon, Republic of Korea
| | - Jae-Won Choi
- From the Department of Psychiatry (Y.J.L., D.Y.L.), Seoul National University College of Medicine (J.Y.H.); Medical Research Center, Institute of Human Behavioral Medicine (M.S.B., D.Y.L.), Seoul National University; Department of Neuropsychiatry (Y.M.C.), University of Ulsan College of Medicine, Ulsan University Hospital; Department of Psychiatry (J.-W.C.), Eulji General Hospital; Department of Neuropsychiatry (J.H.L., Y.J.L., D.Y.L.), Center for Sleep and Chronobiology (Y.J.L.), Seoul National University Hospital; and Health Service Group (S.H.H.), Samsung Electronics, Co., Ltd., Suwon, Republic of Korea
| | - Su Hwan Hwang
- From the Department of Psychiatry (Y.J.L., D.Y.L.), Seoul National University College of Medicine (J.Y.H.); Medical Research Center, Institute of Human Behavioral Medicine (M.S.B., D.Y.L.), Seoul National University; Department of Neuropsychiatry (Y.M.C.), University of Ulsan College of Medicine, Ulsan University Hospital; Department of Psychiatry (J.-W.C.), Eulji General Hospital; Department of Neuropsychiatry (J.H.L., Y.J.L., D.Y.L.), Center for Sleep and Chronobiology (Y.J.L.), Seoul National University Hospital; and Health Service Group (S.H.H.), Samsung Electronics, Co., Ltd., Suwon, Republic of Korea
| | - Yu Jin Lee
- From the Department of Psychiatry (Y.J.L., D.Y.L.), Seoul National University College of Medicine (J.Y.H.); Medical Research Center, Institute of Human Behavioral Medicine (M.S.B., D.Y.L.), Seoul National University; Department of Neuropsychiatry (Y.M.C.), University of Ulsan College of Medicine, Ulsan University Hospital; Department of Psychiatry (J.-W.C.), Eulji General Hospital; Department of Neuropsychiatry (J.H.L., Y.J.L., D.Y.L.), Center for Sleep and Chronobiology (Y.J.L.), Seoul National University Hospital; and Health Service Group (S.H.H.), Samsung Electronics, Co., Ltd., Suwon, Republic of Korea.
| | - Dong Young Lee
- From the Department of Psychiatry (Y.J.L., D.Y.L.), Seoul National University College of Medicine (J.Y.H.); Medical Research Center, Institute of Human Behavioral Medicine (M.S.B., D.Y.L.), Seoul National University; Department of Neuropsychiatry (Y.M.C.), University of Ulsan College of Medicine, Ulsan University Hospital; Department of Psychiatry (J.-W.C.), Eulji General Hospital; Department of Neuropsychiatry (J.H.L., Y.J.L., D.Y.L.), Center for Sleep and Chronobiology (Y.J.L.), Seoul National University Hospital; and Health Service Group (S.H.H.), Samsung Electronics, Co., Ltd., Suwon, Republic of Korea
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Higashi T, Nishii R, Kagawa S, Kishibe Y, Takahashi M, Okina T, Suzuki N, Hasegawa H, Nagahama Y, Ishizu K, Oishi N, Kimura H, Watanabe H, Ono M, Saji H, Yamauchi H. 18F-FPYBF-2, a new F-18-labelled amyloid imaging PET tracer: first experience in 61 volunteers and 55 patients with dementia. Ann Nucl Med 2018; 32:206-216. [PMID: 29388083 PMCID: PMC5852179 DOI: 10.1007/s12149-018-1236-1] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2018] [Accepted: 01/23/2018] [Indexed: 11/28/2022]
Abstract
Objective Recently, we developed a benzofuran derivative for the imaging of β-amyloid plaques, 5-(5-(2-(2-(2-18F-fluoroethoxy)ethoxy)ethoxy)benzofuran-2-yl)-N-methylpyridin-2-amine (18F-FPYBF-2) (Ono et al., J Med Chem 54:2971–9, 2011). The aim of this study was to assess the feasibility of 18F-FPYBF-2 as an amyloid imaging PET tracer in a first clinical study with healthy volunteers and patients with various dementia and in comparative dual tracer study using 11C-Pittsburgh Compound B (11C-PiB). Methods 61 healthy volunteers (age: 53.7 ± 13.1 years old; 19 male and 42 female; age range 24–79) and 55 patients with suspected dementia [Alzheimer’s Disease (AD); early AD: n = 19 and moderate stage AD: n = 8, other dementia: n = 9, mild cognitive impairment (MCI): n = 16, cognitively normal: n = 3] for first clinical study underwent static head PET/CT scan using 18F−FPYBF-2 at 50–70 min after injection. 13 volunteers and 14 patients also underwent dynamic PET scan at 0–50 min at the same instant. 16 subjects (volunteers: n = 5, patients with dementia: n = 11) (age: 66.3 ± 14.2 years old; 10 males and 6 females) were evaluated for comparative study (50–70 min after injection) using 18F-FPYBF-2 and 11C-PiB on separate days, respectively. Quantitative analysis of mean cortical uptake was calculated using Mean Cortical Index of SUVR (standardized uptake value ratio) based on the established method for 11C-PiB analysis using cerebellar cortex as control. Results Studies with healthy volunteers showed that 18F-FPYBF-2 uptake was mainly observed in cerebral white matter and that average Mean Cortical Index at 50–70 min was low and stable (1.066 ± 0.069) basically independent from age or gender. In patients with AD, 18F-FPYBF-2 uptake was observed both in cerebral white and gray matter, and Mean Cortical Index was significantly higher (early AD: 1.288 ± 0.134, moderate AD: 1.342 ± 0.191) than those of volunteers and other dementia (1.018 ± 0.057). In comparative study, the results of 18F-FPYBF-2 PET/CT were comparable with those of 11C-PiB, and the Mean Cortical Index (18F-FPYBF-2: 1.173 ± 0.215; 11C-PiB: 1.435 ± 0.474) showed direct proportional relationship with each other (p < 0.0001). Conclusions Our first clinical study suggest that 18F-FPYBF-2 is a useful PET tracer for the evaluation of β-amyloid deposition and that quantitative analysis of Mean Cortical Index of SUVR is a reliable diagnostic tool for the diagnosis of AD. Electronic supplementary material The online version of this article (10.1007/s12149-018-1236-1) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Tatsuya Higashi
- Shiga Medical Center Research Institute, Moriyama, Japan. .,Department of Molecular Imaging and Theranostics, National Institute of Radiological Sciences (NIRS), National Institutes for Quantum and Radiological Science and Technology (QST), Chiba, Japan.
| | - Ryuichi Nishii
- Shiga Medical Center Research Institute, Moriyama, Japan.,Department of Molecular Imaging and Theranostics, National Institute of Radiological Sciences (NIRS), National Institutes for Quantum and Radiological Science and Technology (QST), Chiba, Japan
| | - Shinya Kagawa
- Shiga Medical Center Research Institute, Moriyama, Japan
| | | | | | - Tomoko Okina
- Department of Geriatric Medicine, Shiga General Hospital, Moriyama, Japan
| | - Norio Suzuki
- Department of Geriatric Medicine, Shiga General Hospital, Moriyama, Japan
| | - Hiroshi Hasegawa
- Department of Geriatric Medicine, Shiga General Hospital, Moriyama, Japan
| | | | - Koichi Ishizu
- Shiga Medical Center Research Institute, Moriyama, Japan.,Human Health Sciences, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Naoya Oishi
- Research and Educational Unit of Leaders for Integrated Medical System, Center for the Promotion of Interdisciplinary Education and Research, Kyoto University, Kyoto, Japan
| | - Hiroyuki Kimura
- Department of Analytical and Bioinorganic Chemistry, Kyoto Pharmaceutical University, Kyoto, Japan
| | - Hiroyuki Watanabe
- Department of Patho-Functional Bioanalysis, Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto, Japan
| | - Masahiro Ono
- Department of Patho-Functional Bioanalysis, Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto, Japan
| | - Hideo Saji
- Department of Patho-Functional Bioanalysis, Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto, Japan
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Pereira JB, Strandberg TO, Palmqvist S, Volpe G, van Westen D, Westman E, Hansson O. Amyloid Network Topology Characterizes the Progression of Alzheimer's Disease During the Predementia Stages. Cereb Cortex 2018; 28:340-349. [PMID: 29136123 PMCID: PMC6454565 DOI: 10.1093/cercor/bhx294] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2017] [Revised: 10/09/2017] [Indexed: 12/12/2022] Open
Abstract
There is increasing evidence showing that the accumulation of the amyloid-β (Aβ) peptide into extracellular plaques is a central event in Alzheimer's disease (AD). These abnormalities can be detected as lowered levels of Aβ42 in the cerebrospinal fluid (CSF) and are followed by increased amyloid burden on positron emission tomography (PET) several years before the onset of dementia. The aim of this study was to assess amyloid network topology in nondemented individuals with early stage Aβ accumulation, defined as abnormal CSF Aβ42 levels and normal Florbetapir PET (CSF+/PET-), and more advanced Aβ accumulation, defined as both abnormal CSF Aβ42 and Florbetapir PET (CSF+/PET+). The amyloid networks were built using correlations in the mean 18F-florbetapir PET values between 72 brain regions and analyzed using graph theory analyses. Our findings showed an association between early amyloid stages and increased covariance as well as shorter paths between several brain areas that overlapped with the default-mode network (DMN). Moreover, we found that individuals with more advanced amyloid accumulation showed more widespread changes in brain regions both within and outside the DMN. These findings suggest that amyloid network topology could potentially be used to assess disease progression in the predementia stages of AD.
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Affiliation(s)
- Joana B Pereira
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden
| | - Tor Olof Strandberg
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, MalmöSweden
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Department of Neurology, Skåne University Hospital, Sweden
| | - Giovanni Volpe
- Department of Physics, Göteborg University, Göteborg, Sweden
| | - Danielle van Westen
- Department of Clinical Sciences Lund, Diagnostic Radiology, Lund University, Lund, Sweden
- Imaging and Function, Skåne University Health Care, Lund, Sweden
| | - Eric Westman
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, MalmöSweden
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Arnemann KL, Stöber F, Narayan S, Rabinovici GD, Jagust WJ. Metabolic brain networks in aging and preclinical Alzheimer's disease. Neuroimage Clin 2017; 17:987-999. [PMID: 29527500 PMCID: PMC5842784 DOI: 10.1016/j.nicl.2017.12.037] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2017] [Revised: 12/05/2017] [Accepted: 12/27/2017] [Indexed: 11/12/2022]
Abstract
Metabolic brain networks can provide insight into the network processes underlying progression from healthy aging to Alzheimer's disease. We explore the effect of two Alzheimer's disease risk factors, amyloid-β and ApoE ε4 genotype, on metabolic brain networks in cognitively normal older adults (N = 64, ages 69-89) compared to young adults (N = 17, ages 20-30) and patients with Alzheimer's disease (N = 22, ages 69-89). Subjects underwent MRI and PET imaging of metabolism (FDG) and amyloid-β (PIB). Normal older adults were divided into four subgroups based on amyloid-β and ApoE genotype. Metabolic brain networks were constructed cross-sectionally by computing pairwise correlations of metabolism across subjects within each group for 80 regions of interest. We found widespread elevated metabolic correlations and desegregation of metabolic brain networks in normal aging compared to youth and Alzheimer's disease, suggesting that normal aging leads to widespread loss of independent metabolic function across the brain. Amyloid-β and the combination of ApoE ε4 led to less extensive elevated metabolic correlations compared to other normal older adults, as well as a metabolic brain network more similar to youth and Alzheimer's disease. This could reflect early progression towards Alzheimer's disease in these individuals. Altered metabolic brain networks of older adults and those at the highest risk for progression to Alzheimer's disease open up novel lines of inquiry into the metabolic and network processes that underlie normal aging and Alzheimer's disease.
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Affiliation(s)
- Katelyn L Arnemann
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, United States.
| | - Franziska Stöber
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, United States; Leibniz Institute for Neurobiology, Magdeburg, Germany; Clinic for Radiology and Nuclear Medicine, Otto-von-Guericke University, Magdeburg, Germany
| | - Sharada Narayan
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, United States
| | - Gil D Rabinovici
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, United States; Memory and Aging Center, University of California San Francisco, San Francisco, CA, United States
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, United States; Division of Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
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La Joie R, Bejanin A, Fagan AM, Ayakta N, Baker SL, Bourakova V, Boxer AL, Cha J, Karydas A, Jerome G, Maass A, Mensing A, Miller ZA, O'Neil JP, Pham J, Rosen HJ, Tsai R, Visani AV, Miller BL, Jagust WJ, Rabinovici GD. Associations between [ 18F]AV1451 tau PET and CSF measures of tau pathology in a clinical sample. Neurology 2017; 90:e282-e290. [PMID: 29282337 DOI: 10.1212/wnl.0000000000004860] [Citation(s) in RCA: 104] [Impact Index Per Article: 14.9] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2017] [Accepted: 10/04/2017] [Indexed: 01/26/2023] Open
Abstract
OBJECTIVE To assess the relationships between fluid and imaging biomarkers of tau pathology and compare their diagnostic utility in a clinically heterogeneous sample. METHODS Fifty-three patients (28 with clinical Alzheimer disease [AD] and 25 with non-AD clinical neurodegenerative diagnoses) underwent β-amyloid (Aβ) and tau ([18F]AV1451) PET and lumbar puncture. CSF biomarkers (Aβ42, total tau [t-tau], and phosphorylated tau [p-tau]) were measured by multianalyte immunoassay (AlzBio3). Receiver operator characteristic analyses were performed to compare discrimination of Aβ-positive AD from non-AD conditions across biomarkers. Correlations between CSF biomarkers and PET standardized uptake value ratios (SUVR) were assessed using skipped Pearson correlation coefficients. Voxelwise analyses were run to assess regional CSF-PET associations. RESULTS [18F]AV1451-PET cortical SUVR and p-tau showed excellent discrimination between Aβ-positive AD and non-AD conditions (area under the curve 0.92-0.94; ≤0.83 for other CSF measures), and reached 83% classification agreement. In the full sample, cortical [18F]AV1451 was associated with all CSF biomarkers, most strongly with p-tau (r = 0.75 vs 0.57 for t-tau and -0.49 for Aβ42). When restricted to Aβ-positive patients with AD, [18F]AV1451 SUVR correlated modestly with p-tau and t-tau (both r = 0.46) but not Aβ42 (r = 0.02). On voxelwise analysis, [18F]AV1451 correlated with CSF p-tau in temporoparietal cortices and with t-tau in medial prefrontal regions. Within AD, Mini-Mental State Examination scores were associated with [18F]AV1451-PET, but not CSF biomarkers. CONCLUSION [18F]AV1451-PET and CSF p-tau had comparable value for differential diagnosis. Correlations were robust in a heterogeneous clinical group but attenuated (although significant) in AD, suggesting that fluid and imaging biomarkers capture different aspects of tau pathology. CLASSIFICATION OF EVIDENCE This study provides Class III evidence that, in a clinical sample of patients with a variety of suspected neurodegenerative diseases, both CSF p-tau and [18F]AV1451 distinguish AD from non-AD conditions.
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Affiliation(s)
- Renaud La Joie
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley.
| | - Alexandre Bejanin
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Anne M Fagan
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Nagehan Ayakta
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Suzanne L Baker
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Viktoriya Bourakova
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Adam L Boxer
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Jungho Cha
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Anna Karydas
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Gina Jerome
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Anne Maass
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Ashley Mensing
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Zachary A Miller
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - James P O'Neil
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Julie Pham
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Howard J Rosen
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Richard Tsai
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Adrienne V Visani
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Bruce L Miller
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - William J Jagust
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
| | - Gil D Rabinovici
- From the Memory and Aging Center (R.L.J., A.B., N.A., V.B., A.L.B., J.C., A.K., A.M., Z.A.M., J.P., H.J.R., R.T., A.V., B.L.M., G.D.R.), University of California San Francisco; Knight Alzheimer's Disease Research Center (A.M.F., G.J.), Department of Neurology (A.M.F., G.J.), and The Hope Center for Neurological Disorders (A.M.F., G.J.), Washington University in St. Louis, MO; Molecular Biophysics and Integrated Bioimaging Division (S.L.B., J.P.O., W.J.J.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Helen Wills Neuroscience Institute (A.M., W.J.J., G.D.R.), University of California Berkeley
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Buckley RF, Hanseeuw B, Schultz AP, Vannini P, Aghjayan SL, Properzi MJ, Jackson JD, Mormino EC, Rentz DM, Sperling RA, Johnson KA, Amariglio RE. Region-Specific Association of Subjective Cognitive Decline With Tauopathy Independent of Global β-Amyloid Burden. JAMA Neurol 2017; 74:1455-1463. [PMID: 28973551 DOI: 10.1001/jamaneurol.2017.2216] [Citation(s) in RCA: 110] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Importance The ability to explore associations between reports of subjective cognitive decline (SCD) and biomarkers of early Alzheimer disease (AD) pathophysiologic processes (accumulation of neocortical β-amyloid [Aβ] and tau) provides an important opportunity to understand the basis of SCD and AD risk. Objective To examine associations between SCD and global Aβ and tau burdens in regions of interest in clinically healthy older adults. Design, Setting, and Participants This imaging substudy of the Harvard Aging Brain Study included 133 clinically healthy older participants (Clinical Dementia Rating Scale global scores of 0) participating in the Harvard Aging Brain Study who underwent cross-sectional flortaucipir F 18 (previously known as AV 1451, T807) positron emission tomography (FTP-PET) imaging for tau and Pittsburgh compound B carbon 11-labeled PET (PiB-PET) imaging for Aβ. The following 2 regions for tau burden were identified: the entorhinal cortex, which exhibits early signs of tauopathy, and the inferior temporal region, which is more closely associated with AD-related pathologic mechanisms. Data were collected from June 11, 2012, through April 7, 2016. Main Outcomes and Measures Subjective cognitive decline was measured using a previously published method of z-transforming subscales from the Memory Functioning Questionnaire, the Everyday Cognition battery, and a 7-item questionnaire. The Aβ level was measured according to a summary distribution volume ratio of frontal, lateral temporal and parietal, and retrosplenial PiB-PET tracer uptake. The FTP-PET measures were computed as standardized uptake value ratios. Linear regression models focused on main and interactive effects of Aβ, entorhinal cortical, and inferior temporal tau on SCD, controlling for age, sex, educational attainment, and Geriatric Depression Scale score. Results Of the 133 participants, 75 (56.3%) were women and 58 (43.6%) were men; mean (SD) age was 76 (6.9) years (range, 55-90 years). Thirty-nine participants (29.3%) exhibited a high Aβ burden. Greater SCD was associated with increasing entorhinal cortical tau burden (β = 0.35; 95% CI, 0.19-.52; P < .001) and Aβ burden (β = 0.24; 95% CI, 0.08-.40; P = .005), but not inferior temporal tau burden (β = 0.10; 95% CI, -0.08 to 0.28; P = .27). This association between entorhinal cortical tau burden and SCD was largely unchanged after accounting for Aβ burden (β = 0.36; 95% CI, 0.15-.58; P = .001), and no interaction influenced SCD (β = -0.36; 95% CI, -0.34 to 0.09; P = .25). An exploratory post hoc whole-brain analysis also indicated that SCD was predominantly associated with greater tau burden in the entorhinal cortex. Conclusions and Relevance Subjective cognitive decline is indicative of accumulation of early tauopathy in the medial temporal lobe, specifically in the entorhinal cortex, and to a lesser extent, elevated global levels of Aβ. Our findings suggest multiple underlying pathways that motivate SCD that do not necessarily interact to influence SCD endorsement. As such, multiple biological factors must be considered when assessing SCD in clinically healthy older adults.
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Affiliation(s)
- Rachel F Buckley
- Florey Institutes of Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia.,Melbourne School of Psychological Science, University of Melbourne, Australia.,Athinoula A. Martinos Center for Biomedical Imaging, Department of Neurology, Massachusetts General Hospital, Charlestown.,Department of Radiology, Harvard Medical School, Boston, Massachusetts
| | - Bernard Hanseeuw
- Department of Radiology, Harvard Medical School, Boston, Massachusetts.,Department of Radiology, Massachusetts General Hospital, Boston.,now affiliated with Department of Neurology, Cliniques Universitaires Saint-Luc, Institute of Neuroscience, Université Catholique de Louvain, Brussels, Belgium
| | - Aaron P Schultz
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Neurology, Massachusetts General Hospital, Charlestown.,Department of Radiology, Massachusetts General Hospital, Boston.,Department of Psychiatry, Massachusetts General Hospital, Boston
| | - Patrizia Vannini
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Neurology, Massachusetts General Hospital, Charlestown.,Department of Radiology, Harvard Medical School, Boston, Massachusetts.,Department of Radiology, Massachusetts General Hospital, Boston
| | - Sarah L Aghjayan
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts
| | - Michael J Properzi
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Neurology, Massachusetts General Hospital, Charlestown
| | - Jonathan D Jackson
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Neurology, Massachusetts General Hospital, Charlestown.,Department of Radiology, Harvard Medical School, Boston, Massachusetts.,Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts
| | - Elizabeth C Mormino
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Neurology, Massachusetts General Hospital, Charlestown.,Department of Radiology, Harvard Medical School, Boston, Massachusetts
| | - Dorene M Rentz
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Neurology, Massachusetts General Hospital, Charlestown.,Department of Radiology, Harvard Medical School, Boston, Massachusetts.,Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts
| | - Reisa A Sperling
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Neurology, Massachusetts General Hospital, Charlestown.,Department of Radiology, Harvard Medical School, Boston, Massachusetts.,Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts
| | - Keith A Johnson
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Neurology, Massachusetts General Hospital, Charlestown.,Department of Radiology, Harvard Medical School, Boston, Massachusetts.,Department of Radiology, Massachusetts General Hospital, Boston.,Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts.,Division of Nuclear Medicine and Molecular Imaging, Massachusetts General Hospital, Boston
| | - Rebecca E Amariglio
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Neurology, Massachusetts General Hospital, Charlestown.,Department of Radiology, Harvard Medical School, Boston, Massachusetts.,Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts
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250
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Schreiner SJ, Kirchner T, Narkhede A, Wyss M, Van Bergen JMG, Steininger SC, Gietl A, Leh SE, Treyer V, Buck A, Pruessmann KP, Nitsch RM, Hock C, Henning A, Brickman AM, Unschuld PG. Brain amyloid burden and cerebrovascular disease are synergistically associated with neurometabolism in cognitively unimpaired older adults. Neurobiol Aging 2017; 63:152-161. [PMID: 29310864 DOI: 10.1016/j.neurobiolaging.2017.12.004] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2017] [Revised: 11/16/2017] [Accepted: 12/04/2017] [Indexed: 01/08/2023]
Abstract
Alzheimer's disease (AD) is the most common cause of cognitive dysfunction in older adults. The pathological hallmarks of AD such as beta amyloid (Aβ) aggregation and neurometabolic change, as indicated by altered myo-inositol (mI) and N-acetylaspartate (NAA) levels, typically precede the onset of cognitive dysfunction by years. Furthermore, cerebrovascular disease occurs early in AD, but the interplay between vascular and neurometabolic brain change is largely unknown. Thirty cognitively normal older adults (age = 70 ± 5.6 years, Mini-Mental State Examination = 29.2 ± 1) received 11-C-Pittsburgh Compound B positron emission tomography for estimating Aβ-plaque density, 7 Tesla fluid-attenuated inversion recovery magnetic resonance imaging for quantifying white matter hyperintensity volume as a marker of small vessel cerebrovascular disease and high-resolution magnetic resonance spectroscopic imaging at 7 Tesla, based on free induction decay acquisition localized by outer volume suppression to investigate tissue-specific neurometabolism in the posterior cingulate and precuneus. Aβ (β = 0.45, p = 0.018) and white matter hyperintensities (β = 0.40, p = 0.046) were independently and interactively (β = -0.49, p = 0.026) associated with a higher ratio of mI over NAA (mI/NAA) in the posterior cingulate and precuneus gray matter but not in the white matter. Our data suggest that cerebrovascular disease and Aβ burden are synergistically associated with AD-related gray matter neurometabolism in older adults.
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Affiliation(s)
- Simon J Schreiner
- Institute for Regenerative Medicine, University of Zurich, Schlieren, Switzerland; Hospital for Psychogeriatric Medicine, University of Zurich, Zurich, Switzerland
| | - Thomas Kirchner
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Atul Narkhede
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Department of Neurology, College of Physicians and Surgeons, Columbia University, NY
| | - Michael Wyss
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Jiri M G Van Bergen
- Institute for Regenerative Medicine, University of Zurich, Schlieren, Switzerland; Hospital for Psychogeriatric Medicine, University of Zurich, Zurich, Switzerland
| | - Stephanie C Steininger
- Institute for Regenerative Medicine, University of Zurich, Schlieren, Switzerland; Hospital for Psychogeriatric Medicine, University of Zurich, Zurich, Switzerland
| | - Anton Gietl
- Institute for Regenerative Medicine, University of Zurich, Schlieren, Switzerland; Hospital for Psychogeriatric Medicine, University of Zurich, Zurich, Switzerland
| | - Sandra E Leh
- Institute for Regenerative Medicine, University of Zurich, Schlieren, Switzerland; Hospital for Psychogeriatric Medicine, University of Zurich, Zurich, Switzerland
| | - Valerie Treyer
- Institute for Regenerative Medicine, University of Zurich, Schlieren, Switzerland; Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Alfred Buck
- Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Klaas P Pruessmann
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Roger M Nitsch
- Institute for Regenerative Medicine, University of Zurich, Schlieren, Switzerland; Hospital for Psychogeriatric Medicine, University of Zurich, Zurich, Switzerland
| | - Christoph Hock
- Institute for Regenerative Medicine, University of Zurich, Schlieren, Switzerland; Hospital for Psychogeriatric Medicine, University of Zurich, Zurich, Switzerland
| | - Anke Henning
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland; Max Planck Institute for Biological Cybernetics, Tubingen, Germany
| | - Adam M Brickman
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Department of Neurology, College of Physicians and Surgeons, Columbia University, NY.
| | - Paul G Unschuld
- Institute for Regenerative Medicine, University of Zurich, Schlieren, Switzerland; Hospital for Psychogeriatric Medicine, University of Zurich, Zurich, Switzerland
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