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Vos SJB, Delvenne A, Jack CR, Thal DR, Visser PJ. The clinical importance of suspected non-Alzheimer disease pathophysiology. Nat Rev Neurol 2024; 20:337-346. [PMID: 38724589 DOI: 10.1038/s41582-024-00962-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/04/2024] [Indexed: 06/06/2024]
Abstract
The development of biomarkers for Alzheimer disease (AD) has led to the origin of suspected non-AD pathophysiology (SNAP) - a heterogeneous biomarker-based concept that describes individuals with normal amyloid and abnormal tau and/or neurodegeneration biomarker status. In this Review, we describe the origins of the SNAP construct, along with its prevalence, diagnostic and prognostic implications, and underlying neuropathology. As we discuss, SNAP can be operationalized using different biomarker modalities, which could affect prevalence estimates and reported characteristics of SNAP in ways that are not yet fully understood. Moreover, the underlying aetiologies that lead to a SNAP biomarker profile, and whether SNAP is the same in people with and without cognitive impairment, remains unclear. Improved insight into the clinical characteristics and pathophysiology of SNAP is of major importance for research and clinical practice, as well as for trial design to optimize care and treatment of individuals with SNAP.
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Affiliation(s)
- Stephanie J B Vos
- Department of Psychiatry and Neuropsychology, Alzheimer Centrum Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands.
| | - Aurore Delvenne
- Department of Psychiatry and Neuropsychology, Alzheimer Centrum Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Dietmar R Thal
- Laboratory for Neuropathology, Department of Imaging and Pathology and Leuven Brain Institute, KU Leuven, Leuven, Belgium
- Department of Pathology, University Hospital Leuven, Leuven, Belgium
| | - Pieter Jelle Visser
- Department of Psychiatry and Neuropsychology, Alzheimer Centrum Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
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Li JQ, Song JH, Suckling J, Wang YJ, Zuo CT, Zhang C, Gao J, Song YQ, Xie AM, Tan L, Yu JT. Disease trajectories in older adults with non-AD pathologic change and comparison with Alzheimer's disease pathophysiology: A longitudinal study. Neurobiol Aging 2024; 134:106-114. [PMID: 38056216 DOI: 10.1016/j.neurobiolaging.2023.11.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 11/06/2023] [Accepted: 11/06/2023] [Indexed: 12/08/2023]
Abstract
Based on the 'AT(N)' system, individuals with normal amyloid biomarkers but abnormal tauopathy or neurodegeneration biomarkers are classified as non-Alzheimer's disease (AD) pathologic change. This study aimed to assess the long-term clinical and cognitive trajectories of individuals with non-AD pathologic change among older adults without dementia, comparing them to those with normal AD biomarkers and AD pathophysiology. Analyzing Alzheimer's Disease Neuroimaging Initiative data, we evaluated clinical outcomes and conversion risk longitudinally using mixed effects models and multivariate Cox proportional hazard models. We found that compared to individuals with A-T-N-, those with abnormal tauopathy or neurodegeneration biomarkers (A-T + N-, A-T-N + , and A-T + N + ) had a faster rate of cognitive decline and disease progression. Individuals with A-T + N + had a faster rate of decline than those with A-T + N-. Additionally, in individuals with the same baseline tauopathy and neurodegeneration biomarker status, the presence of baseline amyloid could accelerate cognitive decline and clinical progression. These findings provide a foundation for future studies on non-AD pathologic change and its comparison with AD pathophysiology.
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Affiliation(s)
- Jie-Qiong Li
- Department of Neurology, the Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong, China.
| | - Jing-Hui Song
- Department of Neurology, the Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong, China
| | - John Suckling
- Department of Psychiatry, University of Cambridge, Cambridge CB2 1TN, UK; Medical Research Council and Wellcome Trust Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge CB2 1TN, UK; Cambridgeshire and Peterborough NHS Trust, UK
| | - Yan-Jiang Wang
- Department of Neurology and Center for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing 400042, China
| | - Chuan-Tao Zuo
- PET Center, Huashan Hospital, Fudan University, Shanghai 200433, China
| | - Can Zhang
- Genetics and Aging Research Unit, Mass GeneralInstitute for Neurodegenerative Diseases (MIND), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Charlestown 02138, MA 02129-2060, USA
| | - Jing Gao
- Department of Neurology, the Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong, China
| | - Yu-Qiang Song
- Department of Neurology, the Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong, China
| | - An-Mu Xie
- Department of Neurology, the Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital,Qingdao University, Qingdao 266000, Shandong, China
| | - Jin-Tai Yu
- Department of Neurology and National Center for NeurologicalDisorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai 200040, China.
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Plassman BL, Ford CB, Smith VA, DePasquale N, Burke JR, Korthauer L, Ott BR, Belanger E, Shepherd-Banigan ME, Couch E, Jutkowitz E, O’Brien EC, Sorenson C, Wetle TT, Van Houtven CH. Elevated Amyloid-β PET Scan and Cognitive and Functional Decline in Mild Cognitive Impairment and Dementia of Uncertain Etiology. J Alzheimers Dis 2024; 97:1161-1171. [PMID: 38306055 PMCID: PMC11034799 DOI: 10.3233/jad-230950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2024]
Abstract
BACKGROUND Elevated amyloid-β (Aβ) on positron emission tomography (PET) scan is used to aid diagnosis of Alzheimer's disease (AD), but many prior studies have focused on patients with a typical AD phenotype such as amnestic mild cognitive impairment (MCI). Little is known about whether elevated Aβ on PET scan predicts rate of cognitive and functional decline among those with MCI or dementia that is clinically less typical of early AD, thus leading to etiologic uncertainty. OBJECTIVE We aimed to investigate whether elevated Aβ on PET scan predicts cognitive and functional decline over an 18-month period in those with MCI or dementia of uncertain etiology. METHODS In 1,028 individuals with MCI or dementia of uncertain etiology, we evaluated the association between elevated Aβ on PET scan and change on a telephone cognitive status measure administered to the participant and change in everyday function as reported by their care partner. RESULTS Individuals with either MCI or dementia and elevated Aβ (66.6% of the sample) showed greater cognitive decline compared to those without elevated Aβ on PET scan, whose cognition was relatively stable over 18 months. Those with either MCI or dementia and elevated Aβ were also reported to have greater functional decline compared to those without elevated Aβ, even though the latter group showed significant care partner-reported functional decline over time. CONCLUSIONS Elevated Aβ on PET scan can be helpful in predicting rates of both cognitive and functional decline, even among cognitively impaired individuals with atypical presentations of AD.
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Affiliation(s)
- Brenda L. Plassman
- Department of Psychiatry and Behavioral Sciences, School of Medicine, Duke University, Durham, NC, USA
- Department of Neurology, School of Medicine, Duke University, NC, USA
| | - Cassie B. Ford
- Department of Population Health Sciences, Duke University, Durham, NC, USA
| | - Valerie A. Smith
- Department of Population Health Sciences, Duke University, Durham, NC, USA
- Department of Medicine, Division of General Internal Medicine, Duke University, Durham, NC, USA
- Durham ADAPT, Durham Veterans Affairs Medical Center, Durham, NC, USA
| | - Nicole DePasquale
- Department of Medicine, Division of General Internal Medicine, Duke University, Durham, NC, USA
| | - James R. Burke
- Department of Psychiatry and Behavioral Sciences, School of Medicine, Duke University, Durham, NC, USA
- Department of Neurology, School of Medicine, Duke University, NC, USA
| | - Laura Korthauer
- Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, RI, USA
| | - Brian R. Ott
- Department of Neurology, Alpert Medical School of Brown University, Providence, RI, USA
| | - Emmanuelle Belanger
- Department of Health Services Policy and Practice, School of Public Health, Brown University, Providence, RI, USA
| | - Megan E. Shepherd-Banigan
- Department of Population Health Sciences, Duke University, Durham, NC, USA
- Durham ADAPT, Durham Veterans Affairs Medical Center, Durham, NC, USA
- Duke-Margolis Center for Health Policy, Durham, NC, USA
| | - Elyse Couch
- Department of Health Services Policy and Practice, School of Public Health, Brown University, Providence, RI, USA
| | - Eric Jutkowitz
- Department of Health Services Policy and Practice, School of Public Health, Brown University, Providence, RI, USA
| | - Emily C. O’Brien
- Department of Population Health Sciences, Duke University, Durham, NC, USA
| | - Corinna Sorenson
- Department of Population Health Sciences, Duke University, Durham, NC, USA
- Duke-Margolis Center for Health Policy, Durham, NC, USA
- Sanford School of Public Policy, Duke University, Durham, NC, USA
| | - Terrie T. Wetle
- Department of Health Services Policy and Practice, School of Public Health, Brown University, Providence, RI, USA
- Center for Gerontology and Healthcare Research, Brown University School of Public Health, Providence, RI, USA
| | - Courtney H. Van Houtven
- Department of Population Health Sciences, Duke University, Durham, NC, USA
- Durham ADAPT, Durham Veterans Affairs Medical Center, Durham, NC, USA
- Duke-Margolis Center for Health Policy, Durham, NC, USA
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Wu KY, Lin KJ, Chen CH, Liu CY, Wu YM, Yen TC, Hsiao IT. Atrophy, hypometabolism and implication regarding pathology in late-life major depression with suspected non-alzheimer pathophysiology (SNAP). Biomed J 2023; 46:100589. [PMID: 36914051 PMCID: PMC10749882 DOI: 10.1016/j.bj.2023.03.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 07/16/2022] [Accepted: 03/08/2023] [Indexed: 03/13/2023] Open
Abstract
BACKGROUND A substantial proportion of individuals with late-life major depression could be classified as having a suspected non-Alzheimer disease pathophysiology (SNAP), as indicated by a negative test for the biomarker β-amyloid (Aβ-) but a positive test for neurodegeneration (ND+). This study investigated the clinical features, characteristic patterns of brain atrophy and hypometabolism, and implications regarding pathology in this population. METHODS Forty-six amyloid-negative patients with late-life major depressive disorder (MDD) patients, including 23 SNAP (Aβ-/ND+) and 23 Aβ-/ND- MDD subjects, and 22 Aβ-/ND-healthy control subjects were included in this study. Voxel-wise group comparisons between the SNAP MDD, Aβ-/ND- MDD and control subjects were performed, adjusting for age, gender and level of education. For exploratory comparisons, 8 Aβ+/ND- and 4 Aβ+/ND + MDD patients were included in the Supplementary Material. RESULTS The SNAP MDD patients had atrophy extending to regions outside the hippocampus, predominately in the medial temporal, dorsomedial and ventromedial prefrontal cortex; hypometabolism involving a large portion of the lateral and medial prefrontal cortex in addition to the bilateral temporal, parietal and precuneus cortex within typical Alzheimer disease regions were observed. Metabolism ratios of the inferior to the medial temporal lobe were significantly elevated in the SNAP MDD patients. We further discussed the implications with regards to underlying pathologies. CONCLUSION The present study demonstrated characteristic patterns of atrophy and hypometabolism in patients with late-life major depression with SNAP. Identifying individuals with SNAP MDD may provide insights into currently unspecified neurodegenerative processes. Future refinement of neurodegeneration biomarkers is essential in order to identify potential pathological correlates while in vivo reliable pathological biomarkers are not forthcoming.
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Affiliation(s)
- Kuan-Yi Wu
- Department of Psychiatry, Chang Gung Memorial Hospital, Taoyuan, Taiwan; College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Kun-Ju Lin
- Department of Nuclear Medicine and Center for Advanced Molecular Imaging and Translation, Chang Gung Memorial Hospital, Taoyuan, Taiwan; Department of Medical Imaging and Radiological Sciences and Healthy Aging Research Center, Chang Gung University, Taoyuan, Taiwan; Neuroscience Research Center, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Chia-Hsiang Chen
- Department of Psychiatry, Chang Gung Memorial Hospital, Taoyuan, Taiwan; College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Chia-Yih Liu
- Department of Psychiatry, Chang Gung Memorial Hospital, Taoyuan, Taiwan; College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Yi-Ming Wu
- Department of Radiology, Chang Gung Memorial Hospital, Taoyuan, Taiwan
| | - Tzu-Chen Yen
- Department of Nuclear Medicine and Center for Advanced Molecular Imaging and Translation, Chang Gung Memorial Hospital, Taoyuan, Taiwan; Department of Medical Imaging and Radiological Sciences and Healthy Aging Research Center, Chang Gung University, Taoyuan, Taiwan; APRINOIA Therapeutics Inc., Taipei, Taiwan
| | - Ing-Tsung Hsiao
- Department of Nuclear Medicine and Center for Advanced Molecular Imaging and Translation, Chang Gung Memorial Hospital, Taoyuan, Taiwan; Department of Medical Imaging and Radiological Sciences and Healthy Aging Research Center, Chang Gung University, Taoyuan, Taiwan.
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Guehl NJ, Dhaynaut M, Hanseeuw BJ, Moon SH, Lois C, Thibault E, Fu JF, Price JC, Johnson KA, El Fakhri G, Normandin MD. Measurement of Cerebral Perfusion Indices from the Early Phase of [ 18F]MK6240 Dynamic Tau PET Imaging. J Nucl Med 2023; 64:968-975. [PMID: 36997330 PMCID: PMC10241011 DOI: 10.2967/jnumed.122.265072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 01/26/2023] [Accepted: 01/26/2023] [Indexed: 04/01/2023] Open
Abstract
6-(fluoro-18F)-3-(1H-pyrrolo[2,3-c]pyridin-1-yl)isoquinolin-5-amine ([18F]MK6240) has high affinity and selectivity for hyperphosphorylated tau and readily crosses the blood-brain barrier. This study investigated whether the early phase of [18F]MK6240 can be used to provide a surrogate index of cerebral perfusion. Methods: Forty-nine subjects who were cognitively normal (CN), had mild cognitive impairment (MCI), or had Alzheimer's disease (AD) underwent paired dynamic [18F]MK6240 and [11C]Pittsburgh compound B (PiB) PET, as well as structural MRI to obtain anatomic information. Arterial blood samples were collected in a subset of 24 subjects for [18F]MK6240 scans to derive metabolite-corrected arterial input functions. Regional time-activity curves were extracted using atlases available in the Montreal Neurologic Institute template space and using FreeSurfer. The early phase of brain time-activity curves was analyzed using a 1-tissue-compartment model to obtain a robust estimate of the rate of transfer from plasma to brain tissue, K 1 (mL⋅cm-3⋅min-1), and the simplified reference tissue model 2 was investigated for noninvasive estimation of the relative delivery rate, R 1 (unitless). A head-to-head comparison with R 1 derived from [11C]PiB scans was performed. Grouped differences in R 1 were evaluated among CN, MCI, and AD subjects. Results: Regional K 1 values suggested a relatively high extraction fraction. R 1 estimated noninvasively from simplified reference tissue model 2 agreed well with R 1 calculated indirectly from the blood-based compartment modeling (r = 0.99; mean difference, 0.024 ± 0.027), suggesting that robust estimates were obtained. R 1 measurements obtained with [18F]MK6240 correlated strongly and overall agreed well with those obtained from [11C]PiB (r = 0.93; mean difference, -0.001 ± 0.068). Statistically significant differences were observed in regional R 1 measurements among CN, MCI, and AD subjects, notably in the temporal and parietal cortices. Conclusion: Our results provide evidence that the early phase of [18F]MK6240 images may be used to derive a useful index of cerebral perfusion. The early and late phases of a [18F]MK6240 dynamic acquisition may thus offer complementary information about the pathophysiologic mechanisms of the disease.
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Affiliation(s)
- Nicolas J Guehl
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts;
| | - Maeva Dhaynaut
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Bernard J Hanseeuw
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
- Department of Neurology, Cliniques Universitaires Saint-Luc, Université Catholique de Louvain, Brussels, Belgium; and
| | - Sung-Hyun Moon
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Cristina Lois
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Emma Thibault
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Jessie Fanglu Fu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Julie C Price
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Keith A Johnson
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Georges El Fakhri
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Marc D Normandin
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
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Li JQ, Song JH, Suckling J, Wang YJ, Zuo CT, Zhang C, Gao J, Song YQ, Xie AM, Tan L, Yu JT. Disease trajectories in elders with suspected non-Alzheimer's pathophysiology and its comparison with Alzheimer's disease pathophysiology: a longitudinal study. RESEARCH SQUARE 2023:rs.3.rs-2744271. [PMID: 37034751 PMCID: PMC10081361 DOI: 10.21203/rs.3.rs-2744271/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/01/2023]
Abstract
Background According to the new 'AT(N)' system, those with a normal amyloid biomarker but with abnormal tauopathy or biomarkers of neurodegeneration or neuronal injury, have been labeled suspected non-Alzheimer's pathophysiology (SNAP). We aimed to estimate the long-term clinical and cognitive trajectories of SNAP individuals in non-demented elders and its comparison with individual in the Alzheimer's disease (AD) pathophysiology using 'AT(N)' system. Methods We included individuals with available baseline cerebrospinal fluid (CSF) Aβ (A), CSF phosphorylated tau examination (T) and 18F-uorodeoxyglucose PET or volumetric magnetic resonance imaging (N) from the Alzheimer's Disease Neuroimaging Initiative database. Longitudinal change in clinical outcomes are assessed using linear mixed effects models. Conversion risk from cognitively normal (CN) to cognitively impairment, and conversion from mild cognitive impairment (MCI) to dementia are assessed using multivariate Cox proportional hazard models. Results Totally, 366 SNAP individuals were included (114 A-T-N-, 154 A-T + N-, 54 A-T-N + and 44 A-T + N+) of whom 178 were CN and 188 were MCI. Compared with A-T-N-, CN elders with A-T + N-, A-T-N + and A-T + N + had a faster rate of ADNI-MEM score decline. Moreover, CN older individuals with A-T + N + also had a faster rate of decline in ADNI-MEM score than those with A-T + N- individuals. MCI patients with A-T + N + had a faster rate of ADNI-MEM and ADNI-EF decline and hippocampal volume loss compared with A-T-N- and A-T + N- profiles. CN older individuals with A-T + N + had an increased risk of conversion to cognitive impairment (CDR-GS ≥ 0.5) compared with A-T + N- and A-T-N-. In MCI patients, A-T + N + also had an increased risk of conversion to dementia compared with A-T + N- and A-T-N-. Compared with A-T + N-, CN elders and MCI patients with A + T + N- and A + T + N + had a faster rate of ADNI-MEM score, ADNI-EF score decline, and hippocampal volume loss. CN individuals with A + T + N + had a faster rate of ADNI-EF score decline compare with A-T + N + individuals. Moreover, MCI patients with A + T + N + also had a faster rate of decline in ADNI-MEM score, ADNI-EF score and hippocampal volume loss than those with A-T + N + individuals. Conclusions The findings from clinical, imaging and biomarker studies on SNAP, and its comparison with AD pathophysiology offered an important foundation for future studies.
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Affiliation(s)
| | | | | | | | | | - Can Zhang
- Massachusetts General Hospital, Harvard Medical School
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Zuo Q, Lu L, Wang L, Zuo J, Ouyang T. Constructing brain functional network by Adversarial Temporal-Spatial Aligned Transformer for early AD analysis. Front Neurosci 2022; 16:1087176. [PMID: 36518529 PMCID: PMC9742604 DOI: 10.3389/fnins.2022.1087176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 11/10/2022] [Indexed: 09/19/2023] Open
Abstract
Introduction The brain functional network can describe the spontaneous activity of nerve cells and reveal the subtle abnormal changes associated with brain disease. It has been widely used for analyzing early Alzheimer's disease (AD) and exploring pathological mechanisms. However, the current methods of constructing functional connectivity networks from functional magnetic resonance imaging (fMRI) heavily depend on the software toolboxes, which may lead to errors in connection strength estimation and bad performance in disease analysis because of many subjective settings. Methods To solve this problem, in this paper, a novel Adversarial Temporal-Spatial Aligned Transformer (ATAT) model is proposed to automatically map 4D fMRI into functional connectivity network for early AD analysis. By incorporating the volume and location of anatomical brain regions, the region-guided feature learning network can roughly focus on local features for each brain region. Also, the spatial-temporal aligned transformer network is developed to adaptively adjust boundary features of adjacent regions and capture global functional connectivity patterns of distant regions. Furthermore, a multi-channel temporal discriminator is devised to distinguish the joint distributions of the multi-region time series from the generator and the real sample. Results Experimental results on the Alzheimer's Disease Neuroimaging Initiative (ADNI) proved the effectiveness and superior performance of the proposed model in early AD prediction and progression analysis. Discussion To verify the reliability of the proposed model, the detected important ROIs are compared with clinical studies and show partial consistency. Furthermore, the most significant altered connectivity reflects the main characteristics associated with AD. Conclusion Generally, the proposed ATAT provides a new perspective in constructing functional connectivity networks and is able to evaluate the disease-related changing characteristics at different stages for neuroscience exploration and clinical disease analysis.
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Affiliation(s)
- Qiankun Zuo
- School of Information Engineering, Hubei University of Economics, Wuhan, China
- CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, and the SIAT Branch, Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen, China
| | - Libin Lu
- School of Mathematics and Computer Science, Wuhan Polytechnic University, Wuhan, China
| | - Lin Wang
- CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, and the SIAT Branch, Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen, China
- Guangdong-Hong Kong-Macau Joint Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen, China
| | - Jiahui Zuo
- State Key Laboratory of Petroleum Resource and Prospecting, and Unconventional Petroleum Research Institute, China University of Petroleum, Beijing, China
| | - Tao Ouyang
- State Key Laboratory of Geomechanics and Geotechnical Engineering, Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, Wuhan, China
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Kumar A, Janelidze S, Stomrud E, Palmqvist S, Hansson O, Mattsson-Carlgren N. β-Amyloid-Dependent and -Independent Genetic Pathways Regulating CSF Tau Biomarkers in Alzheimer Disease. Neurology 2022; 99:e476-e487. [PMID: 35641311 PMCID: PMC9421595 DOI: 10.1212/wnl.0000000000200605] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Accepted: 03/11/2022] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Abnormal metabolism of β-amyloid (Aβ) and soluble phosphorylated tau (P-tau), as well as neurodegeneration, are key components of Alzheimer disease (AD), but it is unclear how these different processes are related to genetic risk factors for AD. METHODS In the Swedish BioFINDER study, we tested associations between a priori defined polygenic risk scores (PRSs) for AD (excluding single-nucleotide polymorphism [SNP] within the APOE region in the main analysis) and biomarkers in CSF (total tau [T-tau] and P-tau181; Aβ1-38, Aβ1-40, Aβ1-42, and Aβ1-42/1-40; and neurofilament light [NfL]) in cognitively unimpaired (CU) individuals (n = 751), and in patients with mild cognitive impairment (MCI) (n = 212) and AD dementia (n = 150). Results were validated in the Alzheimer's Disease Neuroimaging Initiative data set with 777 individuals (AD = 119, MCI = 442, and CU = 216). RESULTS PRSs with SNPs significant at p < 5e-03 (∼1,742 variants) were associated with higher CSF P-tau181 (β = 0.13, p = 5.6e-05) and T-tau (β = 0.12, p = 4.3e-04). The associations between PRS and tau measures were partly attenuated but remained significant after adjusting for Aβ status. Aβ pathology mediated 37% of the effect of this PRS on tau levels. Aβ-dependent and Aβ-independent subsets of the PRS were identified and characterized. There were also associations between PRSs and CSF Aβ biomarkers with nominal significance, but not when corrected for multiple comparisons. There were no associations between PRSs and CSF NfL. DISCUSSION Genetic pathways implicated in causing AD are related to altered levels of soluble tau through both Aβ-dependent and Aβ-independent mechanisms, which may have relevance for anti-tau drug development.
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Affiliation(s)
- Atul Kumar
- From the Clinical Memory Research Unit (A.K., S.J., E.S., S.P., O.H., N.M.-C.), Department of Clinical Sciences, Lund University, Malmö; Memory Clinic (E.S., S.P., O.H.), Skåne University Hospital, Malmö; Department of Neurology (N.M.-C.), Skåne University Hospital, Lund; and Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University, Sweden.
| | - Shorena Janelidze
- From the Clinical Memory Research Unit (A.K., S.J., E.S., S.P., O.H., N.M.-C.), Department of Clinical Sciences, Lund University, Malmö; Memory Clinic (E.S., S.P., O.H.), Skåne University Hospital, Malmö; Department of Neurology (N.M.-C.), Skåne University Hospital, Lund; and Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University, Sweden
| | - Erik Stomrud
- From the Clinical Memory Research Unit (A.K., S.J., E.S., S.P., O.H., N.M.-C.), Department of Clinical Sciences, Lund University, Malmö; Memory Clinic (E.S., S.P., O.H.), Skåne University Hospital, Malmö; Department of Neurology (N.M.-C.), Skåne University Hospital, Lund; and Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University, Sweden
| | - Sebastian Palmqvist
- From the Clinical Memory Research Unit (A.K., S.J., E.S., S.P., O.H., N.M.-C.), Department of Clinical Sciences, Lund University, Malmö; Memory Clinic (E.S., S.P., O.H.), Skåne University Hospital, Malmö; Department of Neurology (N.M.-C.), Skåne University Hospital, Lund; and Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University, Sweden
| | - Oskar Hansson
- From the Clinical Memory Research Unit (A.K., S.J., E.S., S.P., O.H., N.M.-C.), Department of Clinical Sciences, Lund University, Malmö; Memory Clinic (E.S., S.P., O.H.), Skåne University Hospital, Malmö; Department of Neurology (N.M.-C.), Skåne University Hospital, Lund; and Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University, Sweden
| | - Niklas Mattsson-Carlgren
- From the Clinical Memory Research Unit (A.K., S.J., E.S., S.P., O.H., N.M.-C.), Department of Clinical Sciences, Lund University, Malmö; Memory Clinic (E.S., S.P., O.H.), Skåne University Hospital, Malmö; Department of Neurology (N.M.-C.), Skåne University Hospital, Lund; and Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University, Sweden
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Wu KY, Lin KJ, Chen CH, Liu CY, Wu YM, Chen CS, Yen TC, Hsiao IT. Decreased Cerebral Amyloid-β Depositions in Patients With a Lifetime History of Major Depression With Suspected Non-Alzheimer Pathophysiology. Front Aging Neurosci 2022; 14:857940. [PMID: 35721010 PMCID: PMC9204309 DOI: 10.3389/fnagi.2022.857940] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Accepted: 04/11/2022] [Indexed: 11/19/2022] Open
Abstract
Cerebral amyloid-β (Aβ) depositions in depression in old age are controversial. A substantial proportion of individuals with late-life major depressive disorder (MDD) could be classified as having suspected non-Alzheimer’s disease pathophysiology (SNAP) by a negative test for the biomarker amyloid-β (Aβ−) but positive neurodegeneration (ND+). This study aimed to evaluate subthreshold Aβ loads in amyloid-negative MDD, particularly in SNAP MDD patients. This study included 46 amyloid-negative MDD patients: 23 SNAP (Aβ−/ND+) MDD and 23 Aβ−/ND− MDD, and 22 Aβ−/ND− control subjects. All subjects underwent 18F-florbetapir PET, FDG-PET, and MRI. Regions of interest (ROIs) and voxel-wise group comparisons were performed with adjustment for age, gender, and level of education. The SNAP MDD patients exhibited significantly deceased 18F-florbetapir uptakes in most cortical regions but not the parietal and precuneus cortex, as compared with the Aβ−/ND− MDD and control subjects (FDR correction, p < 0.05). No correlations of neuropsychological tests or depression characteristics with global cortical uptakes, but significant positive correlations between cognitive functions and adjusted hippocampal volumes among different groups were observed. The reduced Aβ depositions in the amyloid-negative MDD patients might be attributed mainly to the SNAP MDD patients. Our results indicated that meaningfully low amounts of subclinical Aβ might contain critical information on the non-amyloid-mediated pathogenesis.
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Affiliation(s)
- Kuan-Yi Wu
- Department of Psychiatry, Chang Gung Memorial Hospital, College of Medicine, Chang Gung University, Taoyuan City, Taiwan
| | - Kun-Ju Lin
- Department of Nuclear Medicine, Center for Advanced Molecular Imaging and Translation, Chang Gung Memorial Hospital, Taoyuan City, Taiwan
- Department of Medical Imaging and Radiological Sciences, College of Medicine and Healthy Aging Research Center, Chang Gung University, Taoyuan City, Taiwan
- Neuroscience Research Center, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan City, Taiwan
| | - Chia-Hsiang Chen
- Department of Psychiatry, Chang Gung Memorial Hospital, College of Medicine, Chang Gung University, Taoyuan City, Taiwan
| | - Chia-Yih Liu
- Department of Psychiatry, Chang Gung Memorial Hospital, College of Medicine, Chang Gung University, Taoyuan City, Taiwan
| | - Yi-Ming Wu
- Department of Radiology, Chang Gung Memorial Hospital, Taoyuan City, Taiwan
| | - Cheng-Sheng Chen
- Department of Psychiatry, Kaohsiung Medical University Hospital, College of Medicine, Kaohsiung Medical University, Kaohsiung City, Taiwan
| | - Tzu-Chen Yen
- Department of Nuclear Medicine, Center for Advanced Molecular Imaging and Translation, Chang Gung Memorial Hospital, Taoyuan City, Taiwan
- Department of Medical Imaging and Radiological Sciences, College of Medicine and Healthy Aging Research Center, Chang Gung University, Taoyuan City, Taiwan
| | - Ing-Tsung Hsiao
- Department of Nuclear Medicine, Center for Advanced Molecular Imaging and Translation, Chang Gung Memorial Hospital, Taoyuan City, Taiwan
- Department of Medical Imaging and Radiological Sciences, College of Medicine and Healthy Aging Research Center, Chang Gung University, Taoyuan City, Taiwan
- Neuroscience Research Center, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan City, Taiwan
- *Correspondence: Ing-Tsung Hsiao,
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10
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Saridin FN, Chew KA, Reilhac A, Giyanwali B, Villaraza SG, Tanaka T, Scheltens P, van der Flier WM, Chen CLH, Hilal S. Cerebrovascular disease in Suspected Non-Alzheimer's Pathophysiology and cognitive decline over time. Eur J Neurol 2022; 29:1922-1929. [PMID: 35340085 DOI: 10.1111/ene.15337] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2022] [Revised: 03/15/2022] [Accepted: 03/19/2022] [Indexed: 11/29/2022]
Abstract
BACKGROUND The underlying cause of cognitive decline in individuals who are positive for biomarkers of neurodegeneration (N) but negative for biomarkers of amyloid-beta (A), designated as Suspected Non-Alzheimer's Pathophysiology (SNAP), remains unclear. We evaluate whether cerebrovascular disease (CeVD) is more prevalent in those with SNAP compared to A-N- and A+N+ individuals and whether CeVD is associated with cognitive decline over time in SNAP patients. METHODS A total of 216 individuals from a prospective memory clinic cohort [mean (SD) age, 72.7(7.3) years, 100 women (56.5%)] were included and were diagnosed as no cognitive impairment (NCI), cognitive impairment no dementia (CIND), Alzheimer's dementia (AD) or Vascular dementia (VaD). All individuals underwent clinical evaluation and neuropsychological assessment annually for up to 5 years. [11 C]-PiB or [18 F]-Flutafuranol-PET imaging was performed to ascertain amyloid-beta status. MRI was performed to assess neurodegeneration as measured by medial temporal atrophy≥2, as well as significant CeVD (sCeVD) burden, defined by cortical infarct count≥1, Fazekas-score≥2, lacune count≥2 or cerebral microbleed count≥2. RESULTS Of the 216 individuals, 50(23.1%) A-N+ were (SNAP), 93(43.1%) A-N-, 36(16.7%) A+N- and 37(17.1%) A+N+. A+N+ individuals were significantly older, while A+N+ and SNAP individuals were more likely to have dementia. The SNAP group had a higher prevalence of sCeVD (90.0%) compared to A-N-. Moreover, SNAP individuals with sCeVD had significantly steeper decline in global cognition compared to A-N- over 5 years (P=0.042). CONCLUSIONS These findings suggest that CeVD is a contributing factor to cognitive decline in SNAP. Therefore, SNAP-individuals should be carefully assessed and treated for CeVD.
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Affiliation(s)
- Francis Nicole Saridin
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.,Memory Aging & Cognition Centre, National University Health System, Singapore
| | - Kimberly Ann Chew
- Memory Aging & Cognition Centre, National University Health System, Singapore
| | - Anthonin Reilhac
- Clinical Imaging Research Centre, National University of Singapore, Singapore
| | - Bibek Giyanwali
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | | | - Tomotaka Tanaka
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Phillip Scheltens
- Department of Neurology & Alzheimer Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| | - Wiesje M van der Flier
- Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, Netherlands
| | - Christopher Li Hsian Chen
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.,Memory Aging & Cognition Centre, National University Health System, Singapore.,Department of Psychological Medicine, National University Hospital, Singapore
| | - Saima Hilal
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.,Memory Aging & Cognition Centre, National University Health System, Singapore.,Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
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11
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Das SR, Lyu X, Duong MT, Xie L, McCollum L, de Flores R, DiCalogero M, Irwin DJ, Dickerson BC, Nasrallah IM, Yushkevich PA, Wolk DA. Tau-Atrophy Variability Reveals Phenotypic Heterogeneity in Alzheimer's Disease. Ann Neurol 2021; 90:751-762. [PMID: 34617306 PMCID: PMC8841129 DOI: 10.1002/ana.26233] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2021] [Revised: 09/27/2021] [Accepted: 09/27/2021] [Indexed: 01/02/2023]
Abstract
OBJECTIVE Tau neurofibrillary tangles (T) are the primary driver of downstream neurodegeneration (N) and subsequent cognitive impairment in Alzheimer's disease (AD). However, there is substantial variability in the T-N relationship - manifested in higher or lower atrophy than expected for level of tau in a given brain region. The goal of this study was to determine if region-based quantitation of this variability allows for identification of underlying modulatory factors, including polypathology. METHODS Cortical thickness (N) and 18 F-Flortaucipir SUVR (T) were computed in 104 gray matter regions from a cohort of cognitively-impaired, amyloid-positive (A+) individuals. Region-specific residuals from a robust linear fit between SUVR and cortical thickness were computed as a surrogate for T-N mismatch. A summary T-N mismatch metric defined using residuals were correlated with demographic and imaging-based modulatory factors, and to partition the cohort into data-driven subgroups. RESULTS The summary T-N mismatch metric correlated with underlying factors such as age and burden of white matter hyperintensity lesions. Data-driven subgroups based on clustering of residuals appear to represent different biologically relevant phenotypes, with groups showing distinct spatial patterns of higher or lower atrophy than expected. INTERPRETATION These data support the notion that a measure of deviation from a normative relationship between tau burden and neurodegeneration across brain regions in individuals on the AD continuum captures variability due to multiple underlying factors, and can reveal phenotypes, which if validated, may help identify possible contributors to neurodegeneration in addition to tau, which may ultimately be useful for cohort selection in clinical trials. ANN NEUROL 2021;90:751-762.
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Affiliation(s)
- Sandhitsu R Das
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Xueying Lyu
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Michael Tran Duong
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Long Xie
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Lauren McCollum
- Department of Medicine, University of Tennessee, Knoxville, TN, USA
| | - Robin de Flores
- Université de Caen Normandie, INSERM UMRS U1237, Caen, France
| | - Michael DiCalogero
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - David J Irwin
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Ilya M Nasrallah
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Paul A Yushkevich
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - David A Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
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12
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Yoon B, Guo T, Provost K, Korman D, Ward TJ, Landau SM, Jagust WJ. Abnormal tau in amyloid PET negative individuals. Neurobiol Aging 2021; 109:125-134. [PMID: 34715443 DOI: 10.1016/j.neurobiolaging.2021.09.019] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 09/03/2021] [Accepted: 09/22/2021] [Indexed: 12/14/2022]
Abstract
We examined the characteristics of individuals with biomarker evidence of tauopathy but without β-amyloid (Aβ) (A-T+) in relation to individuals with (A+T+) and without (A-T-) evidence of Alzheimer's disease (AD). We included 561 participants with Aβ and tau PET from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We compared A-T- (n = 316), A-T+ (n = 63), and A+T+ (n = 182) individuals on demographics, amyloid, tau, hippocampal volumes, and cognition. A-T+ individuals were low on apolipoprotein E ɛ4 prevalence (17%) and had no evidence of subtly elevated brain Aβ within the negative range. The severity of tau deposition, hippocampal atrophy, and cognitive dysfunction in the A-T+ group was intermediate between A-T- and A+T+ (all p < 0.001). Tau uptake patterns in A-T+ individuals were heterogeneous, but approximately 29% showed tau deposition in the medial temporal lobe only, consistent with primary age-related tauopathy and an additional 32% showed a pattern consistent with AD. A-T+ individuals also share other features that are characteristic of AD such as cognitive impairment and neurodegeneration, but this group is heterogeneous and likely reflects more than one disorder.
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Affiliation(s)
- Bora Yoon
- Department of Neurology, Konyang University Hospital, Konyang University, College of Medicine, Daejeon, Korea.
| | - Tengfei Guo
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA; Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Karine Provost
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Deniz Korman
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
| | - Tyler J Ward
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
| | - Susan M Landau
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA; Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
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13
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Wisse LEM, de Flores R, Xie L, Das SR, McMillan CT, Trojanowski JQ, Grossman M, Lee EB, Irwin D, Yushkevich PA, Wolk DA. Pathological drivers of neurodegeneration in suspected non-Alzheimer's disease pathophysiology. ALZHEIMERS RESEARCH & THERAPY 2021; 13:100. [PMID: 33990226 PMCID: PMC8122549 DOI: 10.1186/s13195-021-00835-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Accepted: 04/26/2021] [Indexed: 11/16/2022]
Abstract
Background Little is known about the heterogeneous etiology of suspected non-Alzheimer’s pathophysiology (SNAP), a group of subjects with neurodegeneration in the absence of β-amyloid. Using antemortem MRI and pathological data, we investigated the etiology of SNAP and the association of neurodegenerative pathologies with structural medial temporal lobe (MTL) measures in β-amyloid-negative subjects. Methods Subjects with antemortem MRI and autopsy data were selected from ADNI (n=63) and the University of Pennsylvania (n=156). Pathological diagnoses and semi-quantitative scores of MTL tau, neuritic plaques, α-synuclein, and TDP-43 pathology and MTL structural MRI measures from antemortem T1-weighted MRI scans were obtained. β-amyloid status (A+/A−) was determined by CERAD score and neurodegeneration status (N+/N−) by hippocampal volume. Results SNAP reflects a heterogeneous group of pathological diagnoses. In ADNI, SNAP (A−N+) had significantly more neuropathological diagnoses than A+N+. In the A− group, tau pathology was associated with hippocampal, entorhinal cortex, and Brodmann area 35 volume/thickness and TDP-43 pathology with hippocampal volume. Conclusion SNAP had a heterogeneous profile with more mixed pathologies than A+N+. Moreover, a role for TDP-43 and tau pathology in driving MTL neurodegeneration in the absence of β-amyloid was supported. Supplementary Information The online version contains supplementary material available at 10.1186/s13195-021-00835-2.
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Affiliation(s)
- L E M Wisse
- Department of Diagnostic Radiology, Lund University, Remissgatan 4, Room 14-520, 222 42, Lund, Sweden. .,Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, Philadelphia, USA. .,Penn Memory Center, Department of Neurology, University of Pennsylvania, Philadelphia, USA.
| | - R de Flores
- Université Normandie, Inserm, Université de Caen-Normandie, Inserm UMR-S U1237, GIP Cyceron, Caen, France
| | - L Xie
- Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, Philadelphia, USA.,Penn Memory Center, Department of Neurology, University of Pennsylvania, Philadelphia, USA
| | - S R Das
- Penn Memory Center, Department of Neurology, University of Pennsylvania, Philadelphia, USA
| | - C T McMillan
- Penn FTD Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - J Q Trojanowski
- Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, PA, USA
| | - M Grossman
- Penn FTD Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - E B Lee
- Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, PA, USA
| | - D Irwin
- Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, PA, USA
| | - P A Yushkevich
- Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - D A Wolk
- Penn Memory Center, Department of Neurology, University of Pennsylvania, Philadelphia, USA
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14
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Babulal GM, Roe CM, Stout SH, Rajasekar G, Wisch JK, Benzinger TLS, Morris JC, Ances BM. Depression is Associated with Tau and Not Amyloid Positron Emission Tomography in Cognitively Normal Adults. J Alzheimers Dis 2021; 74:1045-1055. [PMID: 32144985 DOI: 10.3233/jad-191078] [Citation(s) in RCA: 54] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
BACKGROUND Depression is also common with older age. Alzheimer's disease (AD) studies suggest that both cerebrospinal fluid and positron emission tomography (PET) amyloid biomarkers are associated with more depressive symptoms in cognitively normal older adults. The recent availability of tau radiotracers offers the ability to examine in vivo tauopathy. It is unclear if the tau biomarker is associated with depression diagnosis. OBJECTIVE We examined if tau and amyloid imaging were associated with a depression diagnosis among cognitively normal adults (Clinical Dementia Rating = 0) and whether antidepressants modified this relationship. METHODS Among 301 participants, logistic regression models evaluated whether in vivo PET tau was associated with depression, while another model tested the interaction between PET tau and antidepressant use. A second set of models substituted PET amyloid for PET tau. A diagnosis of depression (yes/no) was made during an annual clinical assessment by a clinician. Antidepressant use (yes/no) was determined by comparing medications the participants used to a list of 30 commonly used antidepressants. All models adjusted for age, sex, education, race, and apolipoprotein ɛ4. Similar models explored the association between the biomarkers and depressive symptoms. RESULTS Participants with elevated tau were twice as likely to be depressed. Antidepressant use modified this relationship where participants with elevated tau who were taking antidepressants had greater odds of being depressed. Relatedly, elevated amyloid was not associated with depression. CONCLUSIONS Our results demonstrate that tau, not amyloid, was associated with a depression diagnosis. Additionally, antidepressant use interacts with tau to increase the odds of depression among cognitively normal adults.
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Affiliation(s)
- Ganesh M Babulal
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University, St. Louis, MO, USA.,Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Catherine M Roe
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University, St. Louis, MO, USA.,Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Sarah H Stout
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University, St. Louis, MO, USA.,Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Ganesh Rajasekar
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University, St. Louis, MO, USA.,Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Julie K Wisch
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Tammie L S Benzinger
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University, St. Louis, MO, USA.,Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA.,Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA.,Department of Neurosurgery, Washington University School of Medicine, St. Louis, MO, USA
| | - John C Morris
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University, St. Louis, MO, USA.,Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA.,Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA.,Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA.,Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, USA.,Department of Physical Therapy, Washington University School of Medicine, St. Louis, MO, USA.,Department of Occupational Therapy, Washington University School of Medicine, St. Louis, MO, USA
| | - Beau M Ances
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University, St. Louis, MO, USA.,Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA.,Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
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15
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Wong BYX, Yong TT, Lim L, Tan JY, Ng ASL, Ting SKS, Hameed S, Ng KP, Zhou JH, Kandiah N. Medial Temporal Atrophy in Amyloid-Negative Amnestic Type Dementia Is Associated with High Cerebral White Matter Hyperintensity. J Alzheimers Dis 2020; 70:99-106. [PMID: 31177215 DOI: 10.3233/jad-181261] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
BACKGROUND Non-amyloid mechanisms behind neurodegeneration and cognition impairment are unclear. Cerebrovascular disease (CVD) may play an important role in suspected non-Alzheimer's pathophysiology (SNAP), especially in Asia. OBJECTIVE To examine the association between CVD and medial temporal lobe atrophy (MTA) in amyloid-β negative patients with mild amnestic type dementia. METHODS Thirty-six mild dementia patients with complete neuropsychological, cerebrospinal fluid (CSF) biomarker, and neuroimaging information were included. Only patients with clinically significant MTA were recruited. Patients were categorized based on their CSF Aβ levels. Neuroimaging and neuropsychological variables were analyzed. RESULTS Despite comparable MTA between Aβ positive and negative patients, Aβ-negative patients had significantly greater white matter hyperintensities (WMH; Total Fazekas Rating) than their Aβ-positive counterparts (6.42 versus 4.19, p = 0.03). A larger proportion of Aβ-negative patients also had severe and confluent WMH. Regression analyses controlling for baseline characteristics yielded consistent results. CONCLUSION Our findings demonstrate that MTA is associated with greater CVD burden among Aβ-negative patients with amnestic type dementia. CVD may be an important mechanism behind hippocampal atrophy. This has implications on clinical management strategies, where measures to reduce CVD may slow neurodegeneration and disease progression.
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Affiliation(s)
| | - Ting Ting Yong
- Department of Neurology, National Neuroscience Institute, Singapore, Singapore
| | - Levinia Lim
- Department of Neurology, National Neuroscience Institute, Singapore, Singapore
| | - Jayne Yi Tan
- Department of Neurology, National Neuroscience Institute, Singapore, Singapore
| | - Adeline Su Lyn Ng
- Department of Neurology, National Neuroscience Institute, Singapore, Singapore
| | | | - Shahul Hameed
- Department of Neurology, National Neuroscience Institute, Singapore, Singapore
| | - Kok Pin Ng
- Department of Neurology, National Neuroscience Institute, Singapore, Singapore
| | - Juan Helen Zhou
- Center for Cognitive Neuroscience, Neuroscience and Behavioral Disorders Program, Duke-NUS Medical School, Singapore, Singapore
| | - Nagaendran Kandiah
- Department of Neurology, National Neuroscience Institute, Singapore, Singapore.,Duke-NUS Medical School, Singapore, Singapore
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16
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Li WW, Wang Z, Fan DY, Shen YY, Chen DW, Li HY, Li L, Yang H, Liu YH, Bu XL, Jin WS, Zeng F, Xu ZQ, Yu JT, Chen LY, Wang YJ. Association of Polygenic Risk Score with Age at Onset and Cerebrospinal Fluid Biomarkers of Alzheimer's Disease in a Chinese Cohort. Neurosci Bull 2020; 36:696-704. [PMID: 32072450 DOI: 10.1007/s12264-020-00469-8] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2019] [Accepted: 12/25/2019] [Indexed: 02/06/2023] Open
Abstract
To evaluate whether the polygenic profile modifies the development of sporadic Alzheimer's disease (sAD) and pathological biomarkers in cerebrospinal fluid (CSF), 462 sAD patients and 463 age-matched cognitively normal (CN) controls were genotyped for 35 single-nucleotide polymorphisms (SNPs) that are significantly associated with sAD. Then, the alleles found to be associated with sAD were used to build polygenic risk score (PRS) models to represent the genetic risk. Receiver operating characteristic (ROC) analyses and the Cox proportional hazards model were used to evaluate the predictive value of PRS for the sAD risk and age at onset. We measured the CSF levels of Aβ42, Aβ42/Aβ40, total tau (T-tau), and phosphorylated tau (P-tau) in a subgroup (60 sAD and 200 CN participants), and analyzed their relationships with the PRSs. We found that 14 SNPs, including SNPs in the APOE, BIN1, CD33, EPHA1, SORL1, and TOMM40 genes, were associated with sAD risk in our cohort. The PRS models built with these SNPs showed potential for discriminating sAD patients from CN controls, and were able to predict the incidence rate of sAD and age at onset. Furthermore, the PRSs were correlated with the CSF levels of Aβ42, Aβ42/Aβ40, T-tau, and P-tau. Our study suggests that PRS models hold promise for assessing the genetic risk and development of AD. As genetic risk profiles vary among populations, large-scale genome-wide sequencing studies are urgently needed to identify the genetic risk loci of sAD in Chinese populations to build accurate PRS models for clinical practice.
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Affiliation(s)
- Wei-Wei Li
- Department of Neurology and Centre for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, 400042, China
| | - Zhen Wang
- Department of Anaesthesiology, Daping Hospital, Third Military Medical University, Chongqing, 400042, China
| | - Dong-Yu Fan
- Department of Neurology and Centre for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, 400042, China
| | - Ying-Ying Shen
- Department of Neurology and Centre for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, 400042, China
| | - Dong-Wan Chen
- Department of Neurology and Centre for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, 400042, China
| | - Hui-Yun Li
- Department of Neurology and Centre for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, 400042, China
| | - Ling Li
- Department of Neurology and Centre for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, 400042, China
| | - Heng Yang
- Department of Neurology and Centre for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, 400042, China
| | - Yu-Hui Liu
- Department of Neurology and Centre for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, 400042, China
| | - Xian-Le Bu
- Department of Neurology and Centre for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, 400042, China
| | - Wang-Sheng Jin
- Department of Neurology and Centre for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, 400042, China
| | - Fan Zeng
- Department of Neurology and Centre for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, 400042, China
| | - Zhi-Qiang Xu
- Department of Neurology and Centre for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, 400042, China
| | - Jin-Tai Yu
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Li-Yong Chen
- Department of Anaesthesiology, Daping Hospital, Third Military Medical University, Chongqing, 400042, China.
| | - Yan-Jiang Wang
- Department of Neurology and Centre for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, 400042, China. .,Chongqing Key Laboratory of Aging and Diseases, Chongqing, 400042, China. .,Centre for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China.
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17
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Weigand AJ, Bangen KJ, Thomas KR, Delano-Wood L, Gilbert PE, Brickman AM, Bondi MW. Is tau in the absence of amyloid on the Alzheimer's continuum?: A study of discordant PET positivity. Brain Commun 2019; 2:fcz046. [PMID: 32051933 PMCID: PMC7001143 DOI: 10.1093/braincomms/fcz046] [Citation(s) in RCA: 49] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Revised: 11/15/2019] [Accepted: 11/25/2019] [Indexed: 12/14/2022] Open
Abstract
The amyloid cascade model of Alzheimer’s disease posits the primacy of amyloid beta deposition preceding tau-mediated neurofibrillary tangle formation. The amyloid-tau-neurodegeneration biomarker-only diagnostic framework similarly requires the presence of amyloid beta for a diagnosis on the Alzheimer’s continuum. However, medial temporal lobe tau pathology in the absence of amyloid beta is frequently observed at autopsy in cognitively normal individuals, a phenomenon that may reflect a consequence of aging and has been labelled ‘primary age-related tauopathy’. Alternatively, others argue that this tauopathy reflects an early stage of the developmental continuum leading to Alzheimer’s disease. We used positron emission tomography imaging to investigate amyloid beta and tau positivity and associations with cognition to better inform the conceptualization of biomarker changes in Alzheimer’s pathogenesis. Five hundred twenty-three individuals from the Alzheimer’s Disease Neuroimaging Initiative who had undergone flortaucipir positron emission tomography imaging were selected to derive positron emission tomography positivity thresholds using conditional inference decision tree regression. A subsample of 301 individuals without dementia (i.e. those with normal cognition or mild cognitive impairment) had also undergone florbetapir positron emission tomography imaging within 12 months and were categorized into one of the four groups based on cortical amyloid and Braak stage I/II tau positivity: A−/T−, A+/T−, A−/T+, or A+/T+. Tau positivity in the absence of amyloid beta positivity (i.e. A−/T+) comprised the largest group, representing 45% of the sample. In contrast, only 6% of the sample was identified as A+/T−, and the remainder of the sample fell into A−/T− (22%) or A+/T+ (27%) categories. A−/T− and A+/T− groups had the best cognitive performances across memory, language and executive function; the A−/T+ group showed small-to-moderate relative decreases in cognition; and the A+/T+ group had the worst cognitive performances. Furthermore, there were negative associations between Braak stage I/II tau values and all cognitive domains only in the A−/T+ and A+/T+ groups, with strongest associations for the A+/T+ group. Among our sample of older adults across the Alzheimer’s pathological spectrum, 7-fold fewer individuals have positron emission tomography evidence of amyloid beta pathology in the absence of tau pathology than the converse, challenging prevailing models of amyloid beta’s primacy in Alzheimer’s pathogenesis. Given that cognitive performance in the A−/T+ group was poorer than in individuals without either pathology, our results suggest that medial temporal lobe tau without cortical amyloid beta may reflect an early stage on the Alzheimer’s pathological continuum.
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Affiliation(s)
- Alexandra J Weigand
- San Diego State University/University of California San Diego Joint Doctoral Program, San Diego, CA 92182, USA
| | - Katherine J Bangen
- VA San Diego Healthcare System, San Diego, CA 92161, USA.,Department of Psychiatry, University of California, San Diego, CA 92161, USA
| | - Kelsey R Thomas
- VA San Diego Healthcare System, San Diego, CA 92161, USA.,Department of Psychiatry, University of California, San Diego, CA 92161, USA
| | - Lisa Delano-Wood
- VA San Diego Healthcare System, San Diego, CA 92161, USA.,Department of Psychiatry, University of California, San Diego, CA 92161, USA
| | - Paul E Gilbert
- Department of Psychology, San Diego State University, San Diego, CA 92182, USA
| | - Adam M Brickman
- Department of Neurology, Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
| | - Mark W Bondi
- VA San Diego Healthcare System, San Diego, CA 92161, USA.,Department of Psychiatry, University of California, San Diego, CA 92161, USA
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18
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The A/T/N model applied through imaging biomarkers in a memory clinic. Eur J Nucl Med Mol Imaging 2019; 47:247-255. [PMID: 31792573 DOI: 10.1007/s00259-019-04536-9] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Accepted: 09/12/2019] [Indexed: 12/14/2022]
Abstract
PURPOSE The A/T/N model is a research framework proposed to investigate Alzheimer's disease (AD) pathological bases (i.e., amyloidosis A, neurofibrillary tangles T, and neurodegeneration N). The application of this system on clinical populations is still limited. The aim of the study is to evaluate the topography of T distribution by 18F-flortaucipir PET in relation to A and N and to describe the A/T/N status through imaging biomarkers in memory clinic patients. METHODS Eighty-one patients with subjective and objective cognitive impairment were classified as A+/A- and N+/N- through amyloid PET and structural MRI. Tau deposition was compared across A/N subgroups at voxel level. T status was defined through a global cut point based on A/N subgroups and subjects were categorized following the A/T/N model. RESULTS A+N+ and A+N- subgroups showed higher tau burden compared to A-N- group, with A+N- showing significant deposition limited to the medial and lateral temporal regions. Global cut point discriminated A+N+ and A+N- from A-N- subjects. On A/T/N classification, 23% of patients showed a negative biomarker profile, 58% fell within the Alzheimer's continuum, and 19% of the sample was characterized by non-AD pathologic change. CONCLUSION Medial and lateral temporal regions represent a site of significant tau accumulation in A+ subjects and possibly a useful marker of early clinical changes. This is the first study in which the A/T/N model is applied using 18F-flortaucipir PET in a memory clinic population. The majority of patients showed a profile consistent with the Alzheimer's continuum, while a minor percentage showed a profile suggestive of possible other neurodegenerative diseases. These results support the applicability of the A/T/N model in clinical practice.
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19
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Zhao Y, Tudorascu DL, Lopez OL, Cohen AD, Mathis CA, Aizenstein HJ, Price JC, Kuller LH, Kamboh MI, DeKosky ST, Klunk WE, Snitz BE. Amyloid β Deposition and Suspected Non-Alzheimer Pathophysiology and Cognitive Decline Patterns for 12 Years in Oldest Old Participants Without Dementia. JAMA Neurol 2019; 75:88-96. [PMID: 29114732 DOI: 10.1001/jamaneurol.2017.3029] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Importance The prevalence of pathologic conditions of the brain associated with Alzheimer disease increases strongly with age. Little is known about the distribution and clinical significance of preclinical biomarker staging in the oldest old, when most individuals without dementia are likely to have positive biomarkers. Objective To compare the patterns of long-term cognitive decline in multiple domains by preclinical biomarker status in the oldest old without dementia. Design, Setting, and Participants A longitudinal observational study with a mean (SD) of 12.2 (2.2) years (range 7.2-15.1 years) of follow-up was conducted in an academic medical center from August 24, 2000, to January 14, 2016, including and extending observations from the Ginkgo Evaluation of Memory study. A total of 197 adults who had completed the Ginkgo Evaluation of Memory study, were free of dementia, and were able to undergo magnetic resonance imaging were eligible for a neuroimaging study in 2009. Of these patients, 175 were included in the present analyses; 140 (80%) were cognitively normal and 35 (20%) had mild cognitive impairment. Main Outcomes and Measures Biomarker groups included amyloid β negative (Aβ-)/neurodegeneration negative (ND-), amyloid β positive (Aβ+)/ND-, Aβ-/neurodegeneration positive (ND+), and Aβ+/ND+ based on Pittsburgh Compound B retention and hippocampal volume in 2009. Participants completed baseline neuropsychological testing from 2000 to 2002 and annual testing from 2004 to 2016. Domains included memory, executive function, language, visual-spatial reasoning, and attention and psychomotor speed. Slopes of decline were evaluated with linear mixed models adjusted for age, sex, and years of education. Results Of the 175 participants (71 women and 104 men), at imaging, mean (SD) age was 86.0 (2.9) years (range, 82-95 years). A total of 42 participants (24.0%) were Aβ-/ND-, 32 (18.3%) were Aβ+/ND-, 35 (20.0%) were Aβ-/ND+, and 66 (37.7%) were Aβ+/ND+. On all cognitive measures, the Aβ+/ND+ group showed the steepest decline. Compared with the Aβ-/ND- group, the amyloid deposition alone (Aβ+/ND-) group showed faster decline on tests of verbal and visual memory (-0.3513; 95% CI, -0.5269 to -0.1756), executive function (0.0158; 95% CI, 0.0013-0.0303), and language (-0.1934; 95% CI, -0.3520 to -0.0348). The Aβ-/ND+ group showed faster visual memory decline than the Aβ-/ND- reference group (-0.3007; 95% CI, -0.4736 to -0.1279). Conclusions and Relevance In the oldest old without dementia, presence of either or both Aβ and hippocampal atrophy is typical (>75%). Isolated hippocampal volume atrophy is associated only with greater decline in memory. However, isolated Aβ is associated with decline in memory plus language and executive functions. These findings suggest different underlying pathophysiologic processes in the Aβ+/ND- and Aβ-/ND+ groups.
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Affiliation(s)
- Yujing Zhao
- School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Dana L Tudorascu
- Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Oscar L Lopez
- Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania.,Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Ann D Cohen
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Chester A Mathis
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Howard J Aizenstein
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Julie C Price
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania.,now with the Department of Radiology, Massachusetts General Hospital, Boston
| | - Lewis H Kuller
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - M Ilyas Kamboh
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania
| | | | - William E Klunk
- Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania.,Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Beth E Snitz
- Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania
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Abstract
Technologies for imaging the pathophysiology of Alzheimer disease (AD) now permit studies of the relationships between the two major proteins deposited in this disease - amyloid-β (Aβ) and tau - and their effects on measures of neurodegeneration and cognition in humans. Deposition of Aβ in the medial parietal cortex appears to be the first stage in the development of AD, although tau aggregates in the medial temporal lobe (MTL) precede Aβ deposition in cognitively healthy older people. Whether aggregation of tau in the MTL is the first stage in AD or a fairly benign phenomenon that may be transformed and spread in the presence of Aβ is a major unresolved question. Despite a strong link between Aβ and tau, the relationship between Aβ and neurodegeneration is weak; rather, it is tau that is associated with brain atrophy and hypometabolism, which, in turn, are related to cognition. Although there is support for an interaction between Aβ and tau resulting in neurodegeneration that leads to dementia, the unknown nature of this interaction, the strikingly different patterns of brain Aβ and tau deposition and the appearance of neurodegeneration in the absence of Aβ and tau are challenges to this model that ultimately must be explained.
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21
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Nakamura A, Cuesta P, Fernández A, Arahata Y, Iwata K, Kuratsubo I, Bundo M, Hattori H, Sakurai T, Fukuda K, Washimi Y, Endo H, Takeda A, Diers K, Bajo R, Maestú F, Ito K, Kato T. Electromagnetic signatures of the preclinical and prodromal stages of Alzheimer's disease. Brain 2019. [PMID: 29522156 PMCID: PMC5920328 DOI: 10.1093/brain/awy044] [Citation(s) in RCA: 97] [Impact Index Per Article: 19.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Biomarkers useful for the predementia stages of Alzheimer’s disease are needed. Electroencephalography and magnetoencephalography (MEG) are expected to provide potential biomarker candidates for evaluating the predementia stages of Alzheimer’s disease. However, the physiological relevance of EEG/MEG signal changes and their role in pathophysiological processes such as amyloid-β deposition and neurodegeneration need to be elucidated. We evaluated 28 individuals with mild cognitive impairment and 38 cognitively normal individuals, all of whom were further classified into amyloid-β-positive mild cognitive impairment (n = 17, mean age 74.7 ± 5.4 years, nine males), amyloid-β-negative mild cognitive impairment (n = 11, mean age 73.8 ± 8.8 years, eight males), amyloid-β-positive cognitively normal (n = 13, mean age 71.8 ± 4.4 years, seven males), and amyloid-β-negative cognitively normal (n = 25, mean age 72.5 ± 3.4 years, 11 males) individuals using Pittsburgh compound B-PET. We measured resting state MEG for 5 min with the eyes closed, and investigated regional spectral patterns of MEG signals using atlas-based region of interest analysis. Then, the relevance of the regional spectral patterns and their associations with pathophysiological backgrounds were analysed by integrating information from Pittsburgh compound B-PET, fluorodeoxyglucose-PET, structural MRI, and cognitive tests. The results demonstrated that regional spectral patterns of resting state activity could be separated into several types of MEG signatures as follows: (i) the effects of amyloid-β deposition were expressed as the alpha band power augmentation in medial frontal areas; (ii) the delta band power increase in the same region was associated with disease progression within the Alzheimer’s disease continuum and was correlated with entorhinal atrophy and an Alzheimer’s disease-like regional decrease in glucose metabolism; and (iii) the global theta power augmentation, which was previously considered to be an Alzheimer’s disease-related EEG/MEG signature, was associated with general cognitive decline and hippocampal atrophy, but was not specific to Alzheimer’s disease because these changes could be observed in the absence of amyloid-β deposition. The results suggest that these MEG signatures may be useful as unique biomarkers for the predementia stages of Alzheimer’s disease.
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Affiliation(s)
- Akinori Nakamura
- Department of Clinical and Experimental Neuroimaging, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Pablo Cuesta
- Department of Clinical and Experimental Neuroimaging, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan.,Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Complutense University of Madrid and Technical University of Madrid, Madrid, 28223, Spain.,Electrical Engineering and Bioengineering Lab, Department of Industrial Engineering, University of La Laguna, Tenerife, 38200, Spain
| | - Alberto Fernández
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Complutense University of Madrid and Technical University of Madrid, Madrid, 28223, Spain.,Department of Psychiatry, Faculty of Medicine, Complutense University of Madrid, Madrid, 28040, Spain
| | - Yutaka Arahata
- National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan.,Innovation Center for Clinical Research, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Kaori Iwata
- Department of Clinical and Experimental Neuroimaging, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Izumi Kuratsubo
- Innovation Center for Clinical Research, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Masahiko Bundo
- Department of Clinical and Experimental Neuroimaging, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan.,National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Hideyuki Hattori
- National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Takashi Sakurai
- National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Koji Fukuda
- National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Yukihiko Washimi
- National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Hidetoshi Endo
- National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Akinori Takeda
- National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Kersten Diers
- Department of Psychology, Technische Universität Dresden, Dresden, 01069, Germany
| | - Ricardo Bajo
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Complutense University of Madrid and Technical University of Madrid, Madrid, 28223, Spain
| | - Fernando Maestú
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Complutense University of Madrid and Technical University of Madrid, Madrid, 28223, Spain.,Department of Basic Psychology II, Complutense University of Madrid, Madrid, 28223, Spain
| | - Kengo Ito
- Department of Clinical and Experimental Neuroimaging, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan.,National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan.,Innovation Center for Clinical Research, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Takashi Kato
- Department of Clinical and Experimental Neuroimaging, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan.,National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
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22
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Teylan M, Besser LM, Crary JF, Mock C, Gauthreaux K, Thomas NM, Chen YC, Kukull WA. Clinical diagnoses among individuals with primary age-related tauopathy versus Alzheimer's neuropathology. J Transl Med 2019; 99:1049-1055. [PMID: 30710118 PMCID: PMC6609478 DOI: 10.1038/s41374-019-0186-0] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Revised: 11/05/2018] [Accepted: 11/19/2018] [Indexed: 01/27/2023] Open
Abstract
Primary age-related tauopathy (PART) is increasingly recognized as a pathologic entity distinct from Alzheimer's disease (AD). Given that the diagnosis of PART is an autopsy diagnosis, it is unclear how PART is perceived in clinical practice. Thus, we investigated the presumptive primary and contributing diagnoses in individuals who had cognitive impairment while alive and who met neuropathologic criteria for PART at autopsy. We also compared these clinical diagnoses for people with PART to those with AD neuropathology (ADNP). We used data on 1354 participants from the National Alzheimer's Coordinating Center, restricting to those with no neuritic plaques (PART) or moderate/frequent neuritic plaques (ADNP); clinical visit within two years of autopsy; and mild cognitive impairment (MCI) or dementia at last visit. To assess if PART participants were less likely to receive a clinical diagnosis of AD at their last visit prior to autopsy, we used logistic regression, controlling for age, sex, education, and APOE ε4 status. There were 161 PART individuals (n = 49 MCI; n = 112 dementia) and 1193 individuals with ADNP (n = 75 MCI; n = 1118 dementia). Primary clinical diagnosis of AD was more common in those with ADNP (MCI: 69%; demented: 86%) than PART (MCI: 57%; demented: 52%). In the adjusted analysis, primary and contributing clinical diagnoses of AD remained less likely in PART vs. ADNP participants with dementia (OR: 0.22, 95% CI: 0.13-0.38). This study suggests that clinicians recognize a distinction in the clinical presentation between PART and ADNP, diagnosing AD less frequently in those with PART. Nonetheless, clinical AD was diagnosed greater than 50% of the time in PART participants with MCI or dementia. Ante-mortem criteria for diagnosis of PART need to be established, as PART is a neuropathological entity that is distinct from AD and has its own clinical and cognitive outcomes.
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Affiliation(s)
- Merilee Teylan
- National Alzheimer's Coordinating Center, Department of Epidemiology, University of Washington, Seattle, WA, USA.
| | - Lilah M Besser
- Institute for Healthy Aging and Lifespan Studies, School of Urban and Regional Planning, Florida Atlantic University, Boca Raton, FL, USA
| | - John F Crary
- Departments of Pathology and Neuroscience, Friedman Brain Institute, Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Charles Mock
- National Alzheimer's Coordinating Center, Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Kathryn Gauthreaux
- National Alzheimer's Coordinating Center, Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Nicole M Thomas
- National Alzheimer's Coordinating Center, Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Yen-Chi Chen
- National Alzheimer's Coordinating Center, Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Walter A Kukull
- National Alzheimer's Coordinating Center, Department of Epidemiology, University of Washington, Seattle, WA, USA
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23
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Mormino EC, Papp KV. Amyloid Accumulation and Cognitive Decline in Clinically Normal Older Individuals: Implications for Aging and Early Alzheimer's Disease. J Alzheimers Dis 2019; 64:S633-S646. [PMID: 29782318 DOI: 10.3233/jad-179928] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
The aberrant accumulation of the amyloid protein is a critical and early event in the Alzheimer's disease (AD) cascade. Given the early involvement of this pathological process, it is not surprising that many clinically normal (CN) older individuals demonstrate evidence of abnormal Aβ at postmortem examination and in vivo using either CSF or PET imaging. Converging evidence across multiple research groups suggests that the presence of abnormal Aβ among CN individuals is associated with elevated risk of future clinical impairment and cognitive decline. Amyloid positivity in conjunction with biomarkers of neuronal injury offers further insight into which CN are most at risk for short-term decline. Although in its infancy, tau PET has demonstrated early increases among Aβ+ that will likely be an important indicator of risk among CN. Overall, the detection of early Aβ among CN individuals has provided an important opportunity to understand the contributions of this pathology to age-related cognitive decline and to explore early intervention with disease modifying strategies.
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Affiliation(s)
- Elizabeth C Mormino
- Department of Neurology and Neurological Sciences, Stanford University, Palo Alto, CA, USA
| | - Kathryn V Papp
- Department of Neurology, Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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24
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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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25
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Biomarker profiles of Alzheimer's disease and dynamic of the association between cerebrospinal fluid levels of β-amyloid peptide and tau. PLoS One 2019; 14:e0217026. [PMID: 31086391 PMCID: PMC6516653 DOI: 10.1371/journal.pone.0217026] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Accepted: 05/02/2019] [Indexed: 02/07/2023] Open
Abstract
Objective To investigate the relationship between cerebrospinal fluid (CSF) β-amyloid peptide (Aβ42) and CSF Tau in a large population of patients referred to memory clinics for investigation of cognitive dysfunction. Methods We analyzed Alzheimer’s disease (AD) biomarkers in CSF taken from 3565 patients referred to 18 French memory clinics. Patients were classified into four profiles according to levels of CSF biomarkers (A: amyloidosis, N: neurodegeneration). The association between CSF Tau and CSF Aβ42 were analyzed using general linear regression models, in the overall population and stratified by biomarkers profiles. We compared linear and quadratic models using Akaike information criterion. We also assessed change in biomarker profiles in a subset of patients who had 2 assessments of biomarkers. Results CSF Tau was negatively associated with CSF Aβ42 in the overall population, following a non-linear quadratic model. However, the nature of this association was different in the 4 profiles: positive association in A-N- profile, negative association in A-N+ and A+N+ profiles, lack of association in A+N- patients. When considering patients with longitudinal data on profiles, 36% of those initially classified as A-N+ evolved to an A+N+ profile. Conclusions The nature of the association between CSF Aβ42 and CFS Tau depends on the A/N profiles of patients. These results suggest an increase in CSF Aβ42 early in the disease before its decline while tau pathology progresses, this pattern is particularly observed in non-APOE4 subjects. This phenomenon may explain why some patients with neurodegeneration only markers convert to an AD profile (A+N+) over time.
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26
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Probabilistic disease progression modeling to characterize diagnostic uncertainty: Application to staging and prediction in Alzheimer's disease. Neuroimage 2019; 190:56-68. [DOI: 10.1016/j.neuroimage.2017.08.059] [Citation(s) in RCA: 57] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2017] [Revised: 08/07/2017] [Accepted: 08/23/2017] [Indexed: 12/30/2022] Open
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27
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Soldan A, Pettigrew C, Fagan AM, Schindler SE, Moghekar A, Fowler C, Li QX, Collins SJ, Carlsson C, Asthana S, Masters CL, Johnson S, Morris JC, Albert M, Gross AL. ATN profiles among cognitively normal individuals and longitudinal cognitive outcomes. Neurology 2019; 92:e1567-e1579. [PMID: 30842300 DOI: 10.1212/wnl.0000000000007248] [Citation(s) in RCA: 65] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2018] [Accepted: 11/27/2018] [Indexed: 12/31/2022] Open
Abstract
OBJECTIVE To examine the long-term cognitive trajectories of individuals with normal cognition at baseline and distinct amyloid/tau/neurodegeneration (ATN) profiles. METHODS Pooling data across 4 cohort studies, 814 cognitively normal participants (mean baseline age = 59.6 years) were classified into 8 ATN groups using baseline CSF levels of β-amyloid 1-42 as a measure of amyloid (A), phosphorylated tau 181 as a measure of tau (T), and total tau as a measure of neurodegeneration (N). Cognitive performance was measured using a previously validated global factor score and with the Mini-Mental State Examination. We compared the cognitive trajectories across groups using growth curve models (mean follow-up time = 7 years). RESULTS Using different model formulations and cut points for determining biomarker abnormality, only the group with abnormal levels of amyloid, tau, and neurodegeneration (A+T+N+) showed consistently greater cognitive decline than the group with normal levels of all biomarkers (A-T-N-). Replicating prior findings using the 2011 National Institute on Aging-Alzheimer's Association/suspected non-Alzheimer disease pathophysiology schema, only individuals with abnormal levels of both amyloid and phosphorylated tau 181 or total tau (stage 2) showed greater cognitive decline than those with normal biomarker levels (stage 0). CONCLUSION The results are consistent with the hypothesis that both elevated brain amyloid and neurofibrillary tangles are necessary to observe accelerated neurodegeneration, which in turn leads to cognitive decline.
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Affiliation(s)
- Anja Soldan
- From the Department of Neurology (A.S., C.P., A.M., M.A.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.M.F., S.E.S., J.C.M.), Washington University School of Medicine, St. Louis, MO; Florey Institute of Neuroscience and Mental Health (C.F., Q.-X.L., S.J.C., C.L.M.), the University of Melbourne, Australia; Geriatric Research Education and Clinical Center (C.C., S.A., S.J.), Wm. S. Middleton Memorial VA Hospital and Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison; and Center on Aging and Health and Department of Epidemiology (A.L.G.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
| | - Corinne Pettigrew
- From the Department of Neurology (A.S., C.P., A.M., M.A.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.M.F., S.E.S., J.C.M.), Washington University School of Medicine, St. Louis, MO; Florey Institute of Neuroscience and Mental Health (C.F., Q.-X.L., S.J.C., C.L.M.), the University of Melbourne, Australia; Geriatric Research Education and Clinical Center (C.C., S.A., S.J.), Wm. S. Middleton Memorial VA Hospital and Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison; and Center on Aging and Health and Department of Epidemiology (A.L.G.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Anne M Fagan
- From the Department of Neurology (A.S., C.P., A.M., M.A.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.M.F., S.E.S., J.C.M.), Washington University School of Medicine, St. Louis, MO; Florey Institute of Neuroscience and Mental Health (C.F., Q.-X.L., S.J.C., C.L.M.), the University of Melbourne, Australia; Geriatric Research Education and Clinical Center (C.C., S.A., S.J.), Wm. S. Middleton Memorial VA Hospital and Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison; and Center on Aging and Health and Department of Epidemiology (A.L.G.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Suzanne E Schindler
- From the Department of Neurology (A.S., C.P., A.M., M.A.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.M.F., S.E.S., J.C.M.), Washington University School of Medicine, St. Louis, MO; Florey Institute of Neuroscience and Mental Health (C.F., Q.-X.L., S.J.C., C.L.M.), the University of Melbourne, Australia; Geriatric Research Education and Clinical Center (C.C., S.A., S.J.), Wm. S. Middleton Memorial VA Hospital and Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison; and Center on Aging and Health and Department of Epidemiology (A.L.G.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Abhay Moghekar
- From the Department of Neurology (A.S., C.P., A.M., M.A.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.M.F., S.E.S., J.C.M.), Washington University School of Medicine, St. Louis, MO; Florey Institute of Neuroscience and Mental Health (C.F., Q.-X.L., S.J.C., C.L.M.), the University of Melbourne, Australia; Geriatric Research Education and Clinical Center (C.C., S.A., S.J.), Wm. S. Middleton Memorial VA Hospital and Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison; and Center on Aging and Health and Department of Epidemiology (A.L.G.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Christopher Fowler
- From the Department of Neurology (A.S., C.P., A.M., M.A.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.M.F., S.E.S., J.C.M.), Washington University School of Medicine, St. Louis, MO; Florey Institute of Neuroscience and Mental Health (C.F., Q.-X.L., S.J.C., C.L.M.), the University of Melbourne, Australia; Geriatric Research Education and Clinical Center (C.C., S.A., S.J.), Wm. S. Middleton Memorial VA Hospital and Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison; and Center on Aging and Health and Department of Epidemiology (A.L.G.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Qiao-Xin Li
- From the Department of Neurology (A.S., C.P., A.M., M.A.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.M.F., S.E.S., J.C.M.), Washington University School of Medicine, St. Louis, MO; Florey Institute of Neuroscience and Mental Health (C.F., Q.-X.L., S.J.C., C.L.M.), the University of Melbourne, Australia; Geriatric Research Education and Clinical Center (C.C., S.A., S.J.), Wm. S. Middleton Memorial VA Hospital and Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison; and Center on Aging and Health and Department of Epidemiology (A.L.G.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Steven J Collins
- From the Department of Neurology (A.S., C.P., A.M., M.A.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.M.F., S.E.S., J.C.M.), Washington University School of Medicine, St. Louis, MO; Florey Institute of Neuroscience and Mental Health (C.F., Q.-X.L., S.J.C., C.L.M.), the University of Melbourne, Australia; Geriatric Research Education and Clinical Center (C.C., S.A., S.J.), Wm. S. Middleton Memorial VA Hospital and Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison; and Center on Aging and Health and Department of Epidemiology (A.L.G.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Cynthia Carlsson
- From the Department of Neurology (A.S., C.P., A.M., M.A.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.M.F., S.E.S., J.C.M.), Washington University School of Medicine, St. Louis, MO; Florey Institute of Neuroscience and Mental Health (C.F., Q.-X.L., S.J.C., C.L.M.), the University of Melbourne, Australia; Geriatric Research Education and Clinical Center (C.C., S.A., S.J.), Wm. S. Middleton Memorial VA Hospital and Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison; and Center on Aging and Health and Department of Epidemiology (A.L.G.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Sanjay Asthana
- From the Department of Neurology (A.S., C.P., A.M., M.A.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.M.F., S.E.S., J.C.M.), Washington University School of Medicine, St. Louis, MO; Florey Institute of Neuroscience and Mental Health (C.F., Q.-X.L., S.J.C., C.L.M.), the University of Melbourne, Australia; Geriatric Research Education and Clinical Center (C.C., S.A., S.J.), Wm. S. Middleton Memorial VA Hospital and Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison; and Center on Aging and Health and Department of Epidemiology (A.L.G.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Colin L Masters
- From the Department of Neurology (A.S., C.P., A.M., M.A.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.M.F., S.E.S., J.C.M.), Washington University School of Medicine, St. Louis, MO; Florey Institute of Neuroscience and Mental Health (C.F., Q.-X.L., S.J.C., C.L.M.), the University of Melbourne, Australia; Geriatric Research Education and Clinical Center (C.C., S.A., S.J.), Wm. S. Middleton Memorial VA Hospital and Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison; and Center on Aging and Health and Department of Epidemiology (A.L.G.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Sterling Johnson
- From the Department of Neurology (A.S., C.P., A.M., M.A.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.M.F., S.E.S., J.C.M.), Washington University School of Medicine, St. Louis, MO; Florey Institute of Neuroscience and Mental Health (C.F., Q.-X.L., S.J.C., C.L.M.), the University of Melbourne, Australia; Geriatric Research Education and Clinical Center (C.C., S.A., S.J.), Wm. S. Middleton Memorial VA Hospital and Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison; and Center on Aging and Health and Department of Epidemiology (A.L.G.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - John C Morris
- From the Department of Neurology (A.S., C.P., A.M., M.A.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.M.F., S.E.S., J.C.M.), Washington University School of Medicine, St. Louis, MO; Florey Institute of Neuroscience and Mental Health (C.F., Q.-X.L., S.J.C., C.L.M.), the University of Melbourne, Australia; Geriatric Research Education and Clinical Center (C.C., S.A., S.J.), Wm. S. Middleton Memorial VA Hospital and Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison; and Center on Aging and Health and Department of Epidemiology (A.L.G.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Marilyn Albert
- From the Department of Neurology (A.S., C.P., A.M., M.A.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.M.F., S.E.S., J.C.M.), Washington University School of Medicine, St. Louis, MO; Florey Institute of Neuroscience and Mental Health (C.F., Q.-X.L., S.J.C., C.L.M.), the University of Melbourne, Australia; Geriatric Research Education and Clinical Center (C.C., S.A., S.J.), Wm. S. Middleton Memorial VA Hospital and Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison; and Center on Aging and Health and Department of Epidemiology (A.L.G.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Alden L Gross
- From the Department of Neurology (A.S., C.P., A.M., M.A.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.M.F., S.E.S., J.C.M.), Washington University School of Medicine, St. Louis, MO; Florey Institute of Neuroscience and Mental Health (C.F., Q.-X.L., S.J.C., C.L.M.), the University of Melbourne, Australia; Geriatric Research Education and Clinical Center (C.C., S.A., S.J.), Wm. S. Middleton Memorial VA Hospital and Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison; and Center on Aging and Health and Department of Epidemiology (A.L.G.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
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Rabin JS, Perea RD, Buckley RF, Neal TE, Buckner RL, Johnson KA, Sperling RA, Hedden T. Global White Matter Diffusion Characteristics Predict Longitudinal Cognitive Change Independently of Amyloid Status in Clinically Normal Older Adults. Cereb Cortex 2019; 29:1251-1262. [PMID: 29425267 PMCID: PMC6499008 DOI: 10.1093/cercor/bhy031] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2017] [Revised: 01/08/2018] [Indexed: 02/07/2023] Open
Abstract
White matter degradation has been proposed as one possible explanation for age-related cognitive decline. In the present study, we examined 2 main questions: 1) Do diffusion characteristics predict longitudinal change in cognition independently or synergistically with amyloid status? 2) Are the effects of diffusion characteristics on longitudinal cognitive change tract-specific or global in nature? Cognitive domains of executive function, episodic memory, and processing speed were measured annually (mean follow-up = 3.93 ± 1.25 years). Diffusion tensor imaging and Pittsburgh Compound-B positron emission tomography were performed at baseline in 265 clinically normal older adults (aged 63-90). Tract-specific diffusion was measured as the mean fractional anisotropy (FA) for 9 major white matter tracts. Global diffusion was measured as the mean FA across the 9 white matter tracts. Linear mixed models demonstrated independent, rather than synergistic, effects of global FA and amyloid status on cognitive decline. After controlling for amyloid status, lower global FA was associated with worse longitudinal performance in episodic memory and processing speed, but not executive function. After accounting for global FA, none of the individual tracts predicted a significant change in cognitive performance. These findings suggest that global, rather than tract-specific, diffusion characteristics predict longitudinal cognitive decline independently of amyloid status.
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Affiliation(s)
- Jennifer S Rabin
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Rodrigo D Perea
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Rachel F Buckley
- Florey Institutes of Neuroscience and Mental Health, Melbourne and Melbourne School of Psychological Science, University of Melbourne, Melbourne, Australia
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Taylor E Neal
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Randy L Buckner
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychology and Center for Brain Science, Harvard University, Cambridge, MA, USA
| | - Keith A Johnson
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Center for Alzheimer Research and Treatment, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Nuclear Medicine and Molecular Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Reisa A Sperling
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Center for Alzheimer Research and Treatment, Brigham and Women’s Hospital, Boston, MA, USA
| | - Trey Hedden
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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29
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Sperling RA, Mormino EC, Schultz AP, Betensky RA, Papp KV, Amariglio RE, Hanseeuw BJ, Buckley R, Chhatwal J, Hedden T, Marshall GA, Quiroz YT, Donovan NJ, Jackson J, Gatchel JR, Rabin JS, Jacobs H, Yang HS, Properzi M, Kirn DR, Rentz DM, Johnson KA. The impact of amyloid-beta and tau on prospective cognitive decline in older individuals. Ann Neurol 2019; 85:181-193. [PMID: 30549303 PMCID: PMC6402593 DOI: 10.1002/ana.25395] [Citation(s) in RCA: 124] [Impact Index Per Article: 24.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2018] [Revised: 12/09/2018] [Accepted: 12/10/2018] [Indexed: 12/20/2022]
Abstract
OBJECTIVES Amyloid-beta (Aβ) and tau pathologies are commonly observed among clinically normal older individuals at postmortem and can now be detected with in vivo neuroimaging. The association and interaction of these proteinopathies with prospective cognitive decline in normal aging and preclinical Alzheimer's disease (AD) remains to be fully elucidated. METHODS One hundred thirty-seven older individuals (age = 76.3 ± 6.22 years) participating in the Harvard Aging Brain Study underwent Aβ (11 C-Pittsburgh compound B) and tau (18 F-flortaucipir) positron emission tomography (PET) with prospective neuropsychological assessments following PET imaging (mean number of cognitive visits = 2.8 ± 1.1). Tau and Aβ PET measures were assessed in regions of interest (ROIs) as well as vertex-wise map analyses. Cognitive change was evaluated with Memory and Executive Function composites. RESULTS Higher levels of Aβ and tau were both associated with greater memory decline, but not with change in executive function. Higher cortical Aβ was associated with higher tau levels in all ROIs, independent of age, and very elevated levels of tau were observed primarily in clinically normal with elevated Aβ. A significant interaction between tau and Aβ was observed in both ROI and map-level analyses, such that rapid prospective memory decline was observed in participants who had high levels of both pathologies. INTERPRETATION Our results are consistent with the supposition that both Aβ and tau are necessary for memory decline in the preclinical stages of AD. These findings may be relevant for disambiguating aging and early cognitive manifestations of AD, and to inform secondary prevention trials in preclinical AD. Ann Neurol 2019;00:1-3 ANN NEUROL 2019;85:181-193.
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Affiliation(s)
- Reisa A Sperling
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Elizabeth C Mormino
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Department of Neurology, Stanford Medical School, Palo Alto, CA
| | - Aaron P Schultz
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Rebecca A Betensky
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Kathryn V Papp
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Rebecca E Amariglio
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Bernard J Hanseeuw
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Rachel Buckley
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Florey Institute, University of Melbourne, Parkville, Victoria, Australia
| | - Jasmeer Chhatwal
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Trey Hedden
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Gad A Marshall
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Yakeel T Quiroz
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Nancy J Donovan
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Jonathan Jackson
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Jennifer R Gatchel
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Division of Geriatric Psychiatry, McLean Hospital, Harvard Medical School, Belmont, MA
| | - Jennifer S Rabin
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Heidi Jacobs
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Hyun-Sik Yang
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Michael Properzi
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Dylan R Kirn
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Dorene M Rentz
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Keith A Johnson
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Division of Molecular Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA
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30
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Leuzy A, Chiotis K, Lemoine L, Gillberg PG, Almkvist O, Rodriguez-Vieitez E, Nordberg A. Tau PET imaging in neurodegenerative tauopathies-still a challenge. Mol Psychiatry 2019; 24:1112-1134. [PMID: 30635637 PMCID: PMC6756230 DOI: 10.1038/s41380-018-0342-8] [Citation(s) in RCA: 372] [Impact Index Per Article: 74.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2018] [Revised: 10/19/2018] [Accepted: 11/26/2018] [Indexed: 12/14/2022]
Abstract
The accumulation of pathological misfolded tau is a feature common to a collective of neurodegenerative disorders known as tauopathies, of which Alzheimer's disease (AD) is the most common. Related tauopathies include progressive supranuclear palsy (PSP), corticobasal syndrome (CBS), Down's syndrome (DS), Parkinson's disease (PD), and dementia with Lewy bodies (DLB). Investigation of the role of tau pathology in the onset and progression of these disorders is now possible due the recent advent of tau-specific ligands for use with positron emission tomography (PET), including first- (e.g., [18F]THK5317, [18F]THK5351, [18F]AV1451, and [11C]PBB3) and second-generation compounds [namely [18F]MK-6240, [18F]RO-948 (previously referred to as [18F]RO69558948), [18F]PI-2620, [18F]GTP1, [18F]PM-PBB3, and [18F]JNJ64349311 ([18F]JNJ311) and its derivative [18F]JNJ-067)]. In this review we describe and discuss findings from in vitro and in vivo studies using both initial and new tau ligands, including their relation to biomarkers for amyloid-β and neurodegeneration, and cognitive findings. Lastly, methodological considerations for the quantification of in vivo ligand binding are addressed, along with potential future applications of tau PET, including therapeutic trials.
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Affiliation(s)
- Antoine Leuzy
- 0000 0004 1937 0626grid.4714.6Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Konstantinos Chiotis
- 0000 0004 1937 0626grid.4714.6Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden ,0000 0000 9241 5705grid.24381.3cTheme Neurology, Karolinska University Hospital, Stockholm, Sweden
| | - Laetitia Lemoine
- 0000 0004 1937 0626grid.4714.6Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Per-Göran Gillberg
- 0000 0004 1937 0626grid.4714.6Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Ove Almkvist
- 0000 0004 1937 0626grid.4714.6Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden ,0000 0004 1936 9377grid.10548.38Department of Psychology, Stockholm University, Stockholm, Sweden
| | - Elena Rodriguez-Vieitez
- 0000 0004 1937 0626grid.4714.6Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Agneta Nordberg
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden. .,Theme Aging, Karolinska University Hospital, Stockholm, Sweden.
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31
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Questions concerning the role of amyloid-β in the definition, aetiology and diagnosis of Alzheimer's disease. Acta Neuropathol 2018; 136:663-689. [PMID: 30349969 PMCID: PMC6208728 DOI: 10.1007/s00401-018-1918-8] [Citation(s) in RCA: 129] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2018] [Revised: 09/28/2018] [Accepted: 09/30/2018] [Indexed: 12/29/2022]
Abstract
The dominant hypothesis of Alzheimer’s disease (AD) aetiology, the neuropathological guidelines for diagnosing AD and the majority of high-profile therapeutic efforts, in both research and in clinical practice, have been built around one possible causal factor, amyloid-β (Aβ). However, the causal link between Aβ and AD remains unproven. Here, in the context of a detailed assessment of historical and contemporary studies, we raise critical questions regarding the role of Aβ in the definition, diagnosis and aetiology of AD. We illustrate that a holistic view of the available data does not support an unequivocal conclusion that Aβ has a central or unique role in AD. Instead, the data suggest alternative views of AD aetiology are potentially valid, at this time. We propose that an unbiased way forward for the field, beyond the current Aβ-centric approach, without excluding a role for Aβ, is required to come to an accurate understanding of AD dementia and, ultimately, an effective treatment.
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32
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Buckley RF, Mormino EC, Amariglio RE, Properzi MJ, Rabin JS, Lim YY, Papp KV, Jacobs HIL, Burnham S, Hanseeuw BJ, Doré V, Dobson A, Masters CL, Waller M, Rowe CC, Maruff P, Donohue MC, Rentz DM, Kirn D, Hedden T, Chhatwal J, Schultz AP, Johnson KA, Villemagne VL, Sperling RA. Sex, amyloid, and APOE ε4 and risk of cognitive decline in preclinical Alzheimer's disease: Findings from three well-characterized cohorts. Alzheimers Dement 2018; 14:1193-1203. [PMID: 29803541 PMCID: PMC6131023 DOI: 10.1016/j.jalz.2018.04.010] [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: 12/01/2017] [Revised: 03/19/2018] [Accepted: 04/10/2018] [Indexed: 12/19/2022]
Abstract
INTRODUCTION Our objective was to investigate the effect of sex on cognitive decline within the context of amyloid β (Aβ) burden and apolipoprotein E genotype. METHODS We analyzed sex-specific effects on Aβ-positron emission tomography, apolipoprotein, and rates of change on the Preclinical Alzheimer Cognitive Composite-5 across three cohorts, such as the Alzheimer's Disease Neuroimaging Initiative, Australian Imaging, Biomarker and Lifestyle, and Harvard Aging Brain Study (n = 755; clinical dementia rating = 0; age (standard deviation) = 73.6 (6.5); female = 55%). Mixed-effects models of cognitive change by sex, Aβ-positron emission tomography, and apolipoprotein ε4 were examined with quadratic time effects over a median of 4 years of follow-up. RESULTS Apolipoprotein ε4 prevalence and Aβ burden did not differ by sex. Sex did not directly influence cognitive decline. Females with higher Aβ exhibited faster decline than males. Post hoc contrasts suggested that females who were Aβ and apolipoprotein ε4 positive declined faster than their male counterparts. DISCUSSION Although Aβ did not differ by sex, cognitive decline was greater in females with higher Aβ. Our findings suggest that sex may play a modifying role on risk of Alzheimer's disease-related cognitive decline.
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Affiliation(s)
- Rachel F. Buckley
- The Florey Institute, The University of Melbourne, Victoria, Australia
- Melbourne School of Psychological Science, University of Melbourne, Victoria, Australia
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women’s Hospital, Boston, Massachusetts, USA
| | | | - Rebecca E. Amariglio
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women’s Hospital, Boston, Massachusetts, USA
| | - Michael J. Properzi
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Jennifer S. Rabin
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Yen Ying Lim
- The Florey Institute, The University of Melbourne, Victoria, Australia
| | - Kathryn V. Papp
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women’s Hospital, Boston, Massachusetts, USA
| | - Heidi I. L. Jacobs
- Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Boston, MA
- Faculty of Health, Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, Maastricht, The Netherlands
| | - Samantha Burnham
- The Australian eHealth Research Centre, CSIRO Health & Biosecurity, Victoria, Australia
| | - Bernard J. Hanseeuw
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women’s Hospital, Boston, Massachusetts, USA
- Department of Neurology, Cliniques Universitaires Saint-Luc, Institute of Neuroscience, Université Catholique de Louvain, 10 Avenue Hippocrate, 1200 Brussels, Belgium
| | - Vincent Doré
- The Australian eHealth Research Centre, CSIRO Health & Biosecurity, Queensland, Australia
| | - Annette Dobson
- The University of Queensland, School of Public Health, Faculty of Medicine, Queensland, Australia
| | - Colin L. Masters
- The Florey Institute, The University of Melbourne, Victoria, Australia
| | - Michael Waller
- The University of Queensland, School of Public Health, Faculty of Medicine, Queensland, Australia
| | - Christopher C. Rowe
- Department of Nuclear Medicine and Centre for PET, Austin Health, Victoria, Australia
- The Department of Medicine, Austin Health, The University of Melbourne, Victoria, Australia
| | | | - Michael C. Donohue
- Department of Neurology, University of Southern California, San Diego, California, USA Words: 4122
| | - Dorene M. Rentz
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women’s Hospital, Boston, Massachusetts, USA
| | - Dylan Kirn
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women’s Hospital, Boston, Massachusetts, USA
| | - Trey Hedden
- Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Boston, MA
| | - Jasmeer Chhatwal
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Aaron P. Schultz
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women’s Hospital, Boston, Massachusetts, USA
| | - Keith A. Johnson
- Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Boston, MA
| | - Victor L. Villemagne
- Department of Nuclear Medicine and Centre for PET, Austin Health, Victoria, Australia
- The Department of Medicine, Austin Health, The University of Melbourne, Victoria, Australia
| | - Reisa A. Sperling
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women’s Hospital, Boston, Massachusetts, USA
| | | | - the Australian Imaging, Biomarker and Lifestyle study of ageing
- Corresponding author: Rachel F. Buckley, PhD, Address: Department of Neurology, Level 10, Athinoula A. Martinos Center for Biomedical Imaging, 149 13th St, Charlestown, MA, USA 02129,
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Abstract
OBJECTIVES The present study investigated the independent and synergistic effects of amyloid beta (Aβ1-42) and phosphorylated tau (Ptau) pathologies on neuropsychological profiles and trajectories in cognitively normal older adults. METHODS Alzheimer's Disease Neuroimaging Initiative participants identified as cognitively normal at baseline underwent longitudinal assessment (N=518; 0, 12, 24, 36 months), baseline lumbar puncture and follow-up cognitive exams. Cerebral spinal fluid (CSF) biomarker profiles (Aβ-Ptau-, Aβ+Ptau-, Aβ-Ptau+, Aβ+Ptau+) were compared on baseline profiles and trajectories for memory (Rey Auditory Verbal Learning Test), attention/executive function (Trail Making Test, A and B), language (Animal Fluency, Vegetable Fluency, Boston Naming Test) and processing speed (Digit Symbol) using multilevel models. RESULTS The Aβ+Ptau+ group exhibited significantly worse baseline performance on tests of memory and executive function relative to the Aβ-Ptau+ and Aβ-Ptau- groups. The Aβ+Ptau- group fell between the Aβ+Ptau+ participants and the Aβ-Ptau- and Aβ-Ptau+ groups on all three cognitive domains and exhibited worse baseline executive function. The Aβ-Ptau+ group performed worse than Aβ-Ptau- participants on processing speed. Over 36-month follow-up, the Aβ+Ptau+ group exhibited the greatest declines in memory and semantic fluency compared to all other groups. CONCLUSIONS Cognitively normal older adults with both Aβ and Ptau pathology exhibited the weakest profile, marked by the worst memory decline compared to the other groups. Other subtle changes in this group included declines in executive function and semantic fluency. Those with Ptau pathology alone showed slowed processing speed, and those with Aβ pathology alone showed worse attention and executive function compared to biomarker negative participants. (JINS, 2018, 24, 693-702).
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Affiliation(s)
- Jean K. Ho
- Department of Psychology, University of Southern California, Los Angeles, CA, USA
| | - Daniel A. Nation
- Department of Psychology, University of Southern California, Los Angeles, CA, USA
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Das SR, Xie L, Wisse LEM, Ittyerah R, Tustison NJ, Dickerson BC, Yushkevich PA, Wolk DA. Longitudinal and cross-sectional structural magnetic resonance imaging correlates of AV-1451 uptake. Neurobiol Aging 2018; 66:49-58. [PMID: 29518752 PMCID: PMC5924615 DOI: 10.1016/j.neurobiolaging.2018.01.024] [Citation(s) in RCA: 53] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2017] [Revised: 01/30/2018] [Accepted: 01/31/2018] [Indexed: 01/14/2023]
Abstract
We examined the relationship between in vivo estimates of tau deposition as measured by 18F-AV-1451 tau positron emission tomography imaging and cross-sectional cortical thickness, as well as rates of antecedent cortical thinning measured from magnetic resonance imaging in individuals with and without evidence of cerebral amyloid in 63 participants from the Alzheimer's Disease Neuroimaging Initiative study, including 32 cognitively normal individuals (mean age 74 years), 27 patients with mild cognitive impairment (mean age 76.8 years), and 4 patients diagnosed with Alzheimer's disease (mean age 80 years). We hypothesized that structural measures would correlate with 18F-AV-1451 in a spatially local manner and that this correlation would be stronger for longitudinal compared to cross-sectional measures of cortical thickness and in those with cerebral amyloid versus those without. Cross-sectional and longitudinal estimates of voxelwise atrophy were made from whole brain maps of cortical thickness and rates of thickness change. In amyloid-β-positive individuals, the correlation of voxelwise atrophy across the whole brain with a summary measure of medial temporal lobe (MTL) 18F-AV-1451 uptake demonstrated strong local correlations in the MTL with longitudinal atrophy that was weaker in cross-sectional analysis. Similar effects were seen in correlations between 31 bilateral cortical regions of interest. In addition, several nonlocal correlations between atrophy and 18F-AV-1451 uptake were observed, including association between MTL atrophy and 18F-AV-1451 uptake in parietal lobe regions of interest such as the precuneus. Amyloid-β-negative individuals only showed weaker correlations in data uncorrected for multiple comparisons. While these data replicate previous reports of associations between 18F-AV-1451 uptake and cross-sectional structural measures, the current results demonstrate a strong relationship with longitudinal measures of atrophy. These data support the notion that in vivo measures of tau pathology are tightly linked to the rate of neurodegenerative change.
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Affiliation(s)
- Sandhitsu R Das
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA; Penn Image Computing and Science Laboratory, University of Pennsylvania, Philadelphia, PA, USA; Penn Memory Center, University of Pennsylvania, Philadelphia, PA, USA; Penn Alzheimer's Disease Core Center, University of Pennsylvania, Philadelphia, PA, USA.
| | - Long Xie
- Penn Image Computing and Science Laboratory, University of Pennsylvania, Philadelphia, PA, USA; Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Laura E M Wisse
- Penn Image Computing and Science Laboratory, University of Pennsylvania, Philadelphia, PA, USA; Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Ranjit Ittyerah
- Penn Image Computing and Science Laboratory, University of Pennsylvania, Philadelphia, PA, USA; Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Nicholas J Tustison
- Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, VA, USA
| | - Bradford C Dickerson
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Paul A Yushkevich
- Penn Image Computing and Science Laboratory, University of Pennsylvania, Philadelphia, PA, USA; Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - David A Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA; Penn Memory Center, University of Pennsylvania, Philadelphia, PA, USA; Penn Alzheimer's Disease Core Center, University of Pennsylvania, Philadelphia, PA, USA
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Lewczuk P, Riederer P, O’Bryant SE, Verbeek MM, Dubois B, Visser PJ, Jellinger KA, Engelborghs S, Ramirez A, Parnetti L, Jack CR, Teunissen CE, Hampel H, Lleó A, Jessen F, Glodzik L, de Leon MJ, Fagan AM, Molinuevo JL, Jansen WJ, Winblad B, Shaw LM, Andreasson U, Otto M, Mollenhauer B, Wiltfang J, Turner MR, Zerr I, Handels R, Thompson AG, Johansson G, Ermann N, Trojanowski JQ, Karaca I, Wagner H, Oeckl P, van Waalwijk van Doorn L, Bjerke M, Kapogiannis D, Kuiperij HB, Farotti L, Li Y, Gordon BA, Epelbaum S, Vos SJB, Klijn CJM, Van Nostrand WE, Minguillon C, Schmitz M, Gallo C, Mato AL, Thibaut F, Lista S, Alcolea D, Zetterberg H, Blennow K, Kornhuber J, Riederer P, Gallo C, Kapogiannis D, Mato AL, Thibaut F. Cerebrospinal fluid and blood biomarkers for neurodegenerative dementias: An update of the Consensus of the Task Force on Biological Markers in Psychiatry of the World Federation of Societies of Biological Psychiatry. World J Biol Psychiatry 2018; 19:244-328. [PMID: 29076399 PMCID: PMC5916324 DOI: 10.1080/15622975.2017.1375556] [Citation(s) in RCA: 184] [Impact Index Per Article: 30.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
In the 12 years since the publication of the first Consensus Paper of the WFSBP on biomarkers of neurodegenerative dementias, enormous advancement has taken place in the field, and the Task Force takes now the opportunity to extend and update the original paper. New concepts of Alzheimer's disease (AD) and the conceptual interactions between AD and dementia due to AD were developed, resulting in two sets for diagnostic/research criteria. Procedures for pre-analytical sample handling, biobanking, analyses and post-analytical interpretation of the results were intensively studied and optimised. A global quality control project was introduced to evaluate and monitor the inter-centre variability in measurements with the goal of harmonisation of results. Contexts of use and how to approach candidate biomarkers in biological specimens other than cerebrospinal fluid (CSF), e.g. blood, were precisely defined. Important development was achieved in neuroimaging techniques, including studies comparing amyloid-β positron emission tomography results to fluid-based modalities. Similarly, development in research laboratory technologies, such as ultra-sensitive methods, raises our hopes to further improve analytical and diagnostic accuracy of classic and novel candidate biomarkers. Synergistically, advancement in clinical trials of anti-dementia therapies energises and motivates the efforts to find and optimise the most reliable early diagnostic modalities. Finally, the first studies were published addressing the potential of cost-effectiveness of the biomarkers-based diagnosis of neurodegenerative disorders.
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Affiliation(s)
- Piotr Lewczuk
- Department of Psychiatry and Psychotherapy, Universitätsklinikum Erlangen, and Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
- Department of Neurodegeneration Diagnostics, Medical University of Białystok, and Department of Biochemical Diagnostics, University Hospital of Białystok, Białystok, Poland
| | - Peter Riederer
- Center of Mental Health, Clinic and Policlinic of Psychiatry, Psychosomatics and Psychotherapy, University Hospital Würzburg, Würzburg, Germany
| | - Sid E. O’Bryant
- Institute for Healthy Aging, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Marcel M. Verbeek
- Department of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Radboud Alzheimer Center, Nijmegen, The Netherlands
- Department of Laboratory Medicine, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Radboud Alzheimer center, Nijmegen, The Netherlands
| | - Bruno Dubois
- Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Salpêtrièrie Hospital, INSERM UMR-S 975 (ICM), Paris 6 University, Paris, France
| | - Pieter Jelle Visser
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, The Netherlands
- Department of Neurology, Alzheimer Centre, Amsterdam Neuroscience VU University Medical Centre, Amsterdam, The Netherlands
| | | | - Sebastiaan Engelborghs
- Reference Center for Biological Markers of Dementia (BIODEM), University of Antwerp, Antwerp, Belgium
- Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Middelheim and Hoge Beuken, Antwerp, Belgium
| | - Alfredo Ramirez
- Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany
- Institute of Human Genetics, University of Bonn, Bonn, Germany
- Department of Psychiatry and Psychotherapy, University of Cologne, Cologne, Germany
| | - Lucilla Parnetti
- Section of Neurology, Center for Memory Disturbances, Lab of Clinical Neurochemistry, University of Perugia, Perugia, Italy
| | | | - Charlotte E. Teunissen
- Neurochemistry Lab and Biobank, Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center Amsterdam, Amsterdam, The Netherlands
| | - Harald Hampel
- AXA Research Fund & UPMC Chair, Sorbonne Universités, Université Pierre et Marie Curie (UPMC) Paris 06, Inserm, CNRS, Institut du Cerveau et de la Moelle Épinière (ICM), Département de Neurologie, Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Hôpital Pitié-Salpêtrière, Boulevard de l’hôpital, Paris, France
| | - Alberto Lleó
- Department of Neurology, Institut d’Investigacions Biomèdiques Sant Pau - Hospital de Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, CIBERNED, Spain
| | - Frank Jessen
- Department of Psychiatry and Psychotherapy, University of Cologne, Cologne, Germany
- German Center for Neurodegenerative Disorders (DZNE), Bonn, Germany
| | - Lidia Glodzik
- Center for Brain Health, Department of Psychiatry, NYU Langone Medical Center, New York, NY, USA
| | - Mony J. de Leon
- Center for Brain Health, Department of Psychiatry, NYU Langone Medical Center, New York, NY, USA
| | - Anne M. Fagan
- Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, Saint Louis, MO, USA
| | - José Luis Molinuevo
- Barcelonabeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
- Alzheimer’s Disease and Other Cognitive Disorders Unit, Hospital Clínic, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Willemijn J. Jansen
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, The Netherlands
| | - Bengt Winblad
- Karolinska Institutet, Department NVS, Center for Alzheimer Research, Division of Neurogeriatrics, Huddinge, Sweden
| | - Leslie M. Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ulf Andreasson
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Markus Otto
- Department of Neurology, University of Ulm, Ulm, Germany
| | - Brit Mollenhauer
- Paracelsus-Elena-Klinik, Kassel and University Medical Center Göttingen, Department of Neurology, Göttingen, Germany
| | - Jens Wiltfang
- Department of Psychiatry & Psychotherapy, University of Göttingen, Göttingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany
- iBiMED, Medical Sciences Department, University of Aveiro, Aveiro, Portugal
| | - Martin R. Turner
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Inga Zerr
- German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany
- Clinical Dementia Centre, Department of Neurology, University Medical School, Göttingen, Germany
| | - Ron Handels
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, The Netherlands
- Karolinska Institutet, Department NVS, Center for Alzheimer Research, Division of Neurogeriatrics, Huddinge, Sweden
| | | | - Gunilla Johansson
- Karolinska Institutet, Department NVS, Center for Alzheimer Research, Division of Neurogeriatrics, Huddinge, Sweden
| | - Natalia Ermann
- Department of Psychiatry and Psychotherapy, Universitätsklinikum Erlangen, and Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - John Q. Trojanowski
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ilker Karaca
- Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany
| | - Holger Wagner
- Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany
| | - Patrick Oeckl
- Department of Neurology, University of Ulm, Ulm, Germany
| | - Linda van Waalwijk van Doorn
- Department of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Radboud Alzheimer Center, Nijmegen, The Netherlands
- Department of Laboratory Medicine, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Radboud Alzheimer center, Nijmegen, The Netherlands
| | - Maria Bjerke
- Reference Center for Biological Markers of Dementia (BIODEM), University of Antwerp, Antwerp, Belgium
| | - Dimitrios Kapogiannis
- Laboratory of Neurosciences, National Institute on Aging/National Institutes of Health (NIA/NIH), Baltimore, MD, USA
| | - H. Bea Kuiperij
- Department of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Radboud Alzheimer Center, Nijmegen, The Netherlands
- Department of Laboratory Medicine, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Radboud Alzheimer center, Nijmegen, The Netherlands
| | - Lucia Farotti
- Section of Neurology, Center for Memory Disturbances, Lab of Clinical Neurochemistry, University of Perugia, Perugia, Italy
| | - Yi Li
- Center for Brain Health, Department of Psychiatry, NYU Langone Medical Center, New York, NY, USA
| | - Brian A. Gordon
- Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA
- Department of Radiology, Washington University School of Medicine, Saint Louis, MO, USA
| | - Stéphane Epelbaum
- Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Salpêtrièrie Hospital, INSERM UMR-S 975 (ICM), Paris 6 University, Paris, France
| | - Stephanie J. B. Vos
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, The Netherlands
| | - Catharina J. M. Klijn
- Department of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Radboud Alzheimer Center, Nijmegen, The Netherlands
| | | | - Carolina Minguillon
- Barcelonabeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
| | - Matthias Schmitz
- German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany
- Clinical Dementia Centre, Department of Neurology, University Medical School, Göttingen, Germany
| | - Carla Gallo
- Departamento de Ciencias Celulares y Moleculares/Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Andrea Lopez Mato
- Chair of Psychoneuroimmunoendocrinology, Maimonides University, Buenos Aires, Argentina
| | - Florence Thibaut
- Department of Psychiatry, University Hospital Cochin-Site Tarnier 89 rue d’Assas, INSERM 894, Faculty of Medicine Paris Descartes, Paris, France
| | - Simone Lista
- AXA Research Fund & UPMC Chair, Sorbonne Universités, Université Pierre et Marie Curie (UPMC) Paris 06, Inserm, CNRS, Institut du Cerveau et de la Moelle Épinière (ICM), Département de Neurologie, Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Hôpital Pitié-Salpêtrière, Boulevard de l’hôpital, Paris, France
| | - Daniel Alcolea
- Department of Neurology, Institut d’Investigacions Biomèdiques Sant Pau - Hospital de Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, CIBERNED, Spain
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Johannes Kornhuber
- Department of Psychiatry and Psychotherapy, Universitätsklinikum Erlangen, and Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
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Teipel SJ, Cavedo E, Lista S, Habert MO, Potier MC, Grothe MJ, Epelbaum S, Sambati L, Gagliardi G, Toschi N, Greicius MD, Dubois B, Hampel H. Effect of Alzheimer's disease risk and protective factors on cognitive trajectories in subjective memory complainers: An INSIGHT-preAD study. Alzheimers Dement 2018; 14:1126-1136. [PMID: 29792873 DOI: 10.1016/j.jalz.2018.04.004] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2017] [Revised: 01/16/2018] [Accepted: 04/09/2018] [Indexed: 10/16/2022]
Abstract
INTRODUCTION Cognitive change in people at risk of Alzheimer's disease (AD) such as subjective memory complainers is highly variable across individuals. METHODS We used latent class growth modeling to identify distinct classes of nonlinear trajectories of cognitive change over 2 years follow-up from 265 subjective memory complainers individuals (age 70 years and older) of the INSIGHT-preAD cohort. We determined the effect of cortical amyloid load, hippocampus and basal forebrain volumes, and education on the cognitive trajectory classes. RESULTS Latent class growth modeling identified distinct nonlinear cognitive trajectories. Education was associated with higher performing trajectories, whereas global amyloid load and basal forebrain atrophy were associated with lower performing trajectories. DISCUSSION Distinct classes of cognitive trajectories were associated with risk and protective factors of AD. These associations support the notion that the identified cognitive trajectories reflect different risk for AD that may be useful for selecting high-risk individuals for intervention trials.
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Affiliation(s)
- Stefan J Teipel
- German Center for Neurodegenerative Diseases (DZNE)-Rostock/Greifswald, Rostock, Germany; Department of Psychosomatic Medicine, University of Rostock, Rostock, Germany.
| | - Enrica Cavedo
- AXA Research Fund & Sorbonne Université Chair, Paris, France; Sorbonne Université, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Hôpital de la Pitié-Salpêtrière, Paris, France; Institut du Cerveau et de la Moelle Épiniére (ICM), INSERM U 1127, CNRS UMR 7225, Paris, France; Institut de la Mémoire et de la Maladie d'Alzheimer (IM2A), Département de Neurologie, Hôpital de la Pitié-Salpêtrière, AP-HP, Paris, France; IRCCS Centro San Giovanni di Dio-Fatebenefratelli, Brescia, Italy
| | - Simone Lista
- AXA Research Fund & Sorbonne Université Chair, Paris, France; Sorbonne Université, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Hôpital de la Pitié-Salpêtrière, Paris, France; Institut du Cerveau et de la Moelle Épiniére (ICM), INSERM U 1127, CNRS UMR 7225, Paris, France; Institut de la Mémoire et de la Maladie d'Alzheimer (IM2A), Département de Neurologie, Hôpital de la Pitié-Salpêtrière, AP-HP, Paris, France
| | - Marie-Odile Habert
- Département de Médecine Nucléaire, Hôpital de la Pitié-Salpêtrière, AP-HP, Paris, France; Laboratoire d'Imagerie Biomédicale, Sorbonne Universités, UPMC Univ Paris 06, Inserm U 1146, CNRS UMR 7371, Paris, France
| | - Marie-Claude Potier
- ICM Institut du Cerveau et de la Moelle épinière, CNRS UMR7225, INSERM U1127, UPMC, Hôpital de la Pitié-Salpêtrière, Paris, France
| | - Michel J Grothe
- German Center for Neurodegenerative Diseases (DZNE)-Rostock/Greifswald, Rostock, Germany; Department of Psychosomatic Medicine, University of Rostock, Rostock, Germany
| | - Stephane Epelbaum
- Sorbonne Université, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Hôpital de la Pitié-Salpêtrière, Paris, France
| | - Luisa Sambati
- Sorbonne Université, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Hôpital de la Pitié-Salpêtrière, Paris, France
| | - Geoffroy Gagliardi
- Sorbonne Université, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Hôpital de la Pitié-Salpêtrière, Paris, France
| | - Nicola Toschi
- Department of Biomedicine and Prevention, University of Rome "Tor Vergata", Rome, Italy; Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Michael D Greicius
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Bruno Dubois
- Sorbonne Université, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Hôpital de la Pitié-Salpêtrière, Paris, France
| | - Harald Hampel
- AXA Research Fund & Sorbonne Université Chair, Paris, France; Sorbonne Université, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Hôpital de la Pitié-Salpêtrière, Paris, France; Institut du Cerveau et de la Moelle Épiniére (ICM), INSERM U 1127, CNRS UMR 7225, Paris, France; Institut de la Mémoire et de la Maladie d'Alzheimer (IM2A), Département de Neurologie, Hôpital de la Pitié-Salpêtrière, AP-HP, Paris, France
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Chung JK, Plitman E, Nakajima S, Caravaggio F, Iwata Y, Gerretsen P, Kim J, Takeuchi H, Shinagawa S, Patel R, Chakravarty MM, Graff-Guerrero A. Hippocampal and Clinical Trajectories of Mild Cognitive Impairment with Suspected Non-Alzheimer's Disease Pathology. J Alzheimers Dis 2018; 58:747-762. [PMID: 28505977 DOI: 10.3233/jad-170201] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Suspected non-Alzheimer's disease pathology (SNAP) characterizes individuals showing neurodegeneration (e.g., hypometabolism) without amyloid-β (Aβ). Findings from previous studies regarding clinical and structural trajectories of SNAP are inconsistent. Using data from the Alzheimer's Disease Neuroimaging Initiative, patients with amnestic mild cognitive impairment (MCI) were categorized into four groups: amyloid positive with hypometabolism (Aβ+ND+), amyloid only (Aβ+ND-), neither amyloid nor hypometabolism (Aβ-ND-), and SNAP (Aβ-ND+). Aβ+ND+(n = 33), Aβ+ND-(n = 32), and Aβ-ND-(n = 36) were matched to SNAP for age, gender, apolipoprotein E4 (apoE4) genotype, and scores on the Montreal Cognitive Assessment. Elderly controls (n = 40) were also matched to SNAP for age, gender, and apoE4 genotype. Longitudinal changes were compared across groups in terms of hippocampal volume, clinical symptoms, daily functioning, and cognitive functioning over a 2-year period. At baseline, no difference in cognition and functioning was observed between SNAP and Aβ+groups. SNAP showed worse clinical symptoms and impaired functioning at baseline compared to Aβ-ND-and controls. Two years of follow-up showed no differences in hippocampal volume changes between SNAP and any of the comparison groups. SNAP showed worse functional deterioration in comparison to Aβ-ND-and controls. However, Aβ+ND+ showed more severe changes in clinical symptoms in comparison to SNAP. Thus, patients with MCI and SNAP showed 1) more severe functional deterioration compared to Aβ-ND-and controls, 2) no differences with Aβ+ND-, and 3) less cognitive deterioration than Aβ+ND+. Future studies should investigate what causes SNAP, which is different from typical AD pathology and biomarker cascades.
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Affiliation(s)
- Jun Ku Chung
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Canada.,Multimodal Imaging Group - Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Canada
| | - Eric Plitman
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Canada.,Multimodal Imaging Group - Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Canada
| | - Shinichiro Nakajima
- Multimodal Imaging Group - Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Canada.,Department of Psychiatry, University of Toronto, Toronto, Canada.,Department of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan.,Geriatric Mental Health Division, Centre for Addiction and Mental Health, Toronto, Canada
| | - Fernando Caravaggio
- Multimodal Imaging Group - Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Canada.,Department of Psychiatry, University of Toronto, Toronto, Canada
| | - Yusuke Iwata
- Multimodal Imaging Group - Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Canada.,Department of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan
| | - Philip Gerretsen
- Multimodal Imaging Group - Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Canada.,Department of Psychiatry, University of Toronto, Toronto, Canada.,Geriatric Mental Health Division, Centre for Addiction and Mental Health, Toronto, Canada
| | - Julia Kim
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Canada.,Multimodal Imaging Group - Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Canada
| | - Hiroyoshi Takeuchi
- Department of Psychiatry, University of Toronto, Toronto, Canada.,Department of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan
| | | | - Raihaan Patel
- Cerebral Imaging Centre, Douglas Mental Health Institute, McGill University, Montreal, QC, Canada.,Department of Psychiatry and Biomedical Engineering, McGill University, Montreal, QC, Canada
| | - M Mallar Chakravarty
- Cerebral Imaging Centre, Douglas Mental Health Institute, McGill University, Montreal, QC, Canada.,Department of Psychiatry and Biomedical Engineering, McGill University, Montreal, QC, Canada
| | - Ariel Graff-Guerrero
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Canada.,Multimodal Imaging Group - Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Canada.,Department of Psychiatry, University of Toronto, Toronto, Canada.,Department of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan.,Geriatric Mental Health Division, Centre for Addiction and Mental Health, Toronto, Canada
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Fliessbach K, Schneider A. [Biomarker-based diagnostics of Alzheimer's disease : Concept of suspected non-Alzheimer pathology]. DER NERVENARZT 2018; 89:345-358. [PMID: 29423820 DOI: 10.1007/s00115-018-0488-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
In the field of prodromal Alzheimer's disease biomarker-based diagnostics are becoming increasingly more important. Unclear biomarker constellations, such as suspected non-Alzheimer pathology (SNAP) can lead to diagnostic and prognostic uncertainty. The use of biomarker-based research criteria in the clinical routine is therefore not without problems. Despite sometimes contradictory findings it appears to be nearly certain that the biomarker constellation of SNAP indicates an increased risk of progression to dementia, at least in patients with mild cognitive deficits (MCI). This article discusses the prognostic implications of a SNAP result and the diagnostic and prognostic problems of biomarker-based diagnostic criteria are presented based on the SNAP.
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Affiliation(s)
- K Fliessbach
- Klinik für Neurodegenerative Erkrankungen und Gerontopsychiatrie, Universitätsklinik Bonn, Sigmund-Freud-Str. 25, 53127, Bonn, Deutschland
- Deutsches Zentrum für Neurodegenerative Erkrankungen, DZNE, Sigmund-Freud-Str. 27, 53127, Bonn, Deutschland
| | - A Schneider
- Klinik für Neurodegenerative Erkrankungen und Gerontopsychiatrie, Universitätsklinik Bonn, Sigmund-Freud-Str. 25, 53127, Bonn, Deutschland.
- Deutsches Zentrum für Neurodegenerative Erkrankungen, DZNE, Sigmund-Freud-Str. 27, 53127, Bonn, Deutschland.
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Wisse LEM, Das SR, Davatzikos C, Dickerson BC, Xie SX, Yushkevich PA, Wolk DA. Defining SNAP by cross-sectional and longitudinal definitions of neurodegeneration. NEUROIMAGE-CLINICAL 2018; 18:407-412. [PMID: 29487798 PMCID: PMC5816023 DOI: 10.1016/j.nicl.2018.02.008] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/12/2017] [Revised: 12/20/2017] [Accepted: 02/06/2018] [Indexed: 12/23/2022]
Abstract
Introduction Suspected non-Alzheimer's pathophysiology (SNAP) is a biomarker driven designation that represents a heterogeneous group in terms of etiology and prognosis. SNAP has only been identified by cross-sectional neurodegeneration measures, whereas longitudinal measures might better reflect “active” neurodegeneration and might be more tightly linked to prognosis. We compare neurodegeneration defined by cross-sectional ‘hippocampal volume’ only (SNAP/L−) versus both cross-sectional and longitudinal ‘hippocampal atrophy rate’ (SNAP/L+) and investigate how these definitions impact prevalence and the clinical and biomarker profile of SNAP in Mild Cognitive Impairment (MCI). Methods 276 MCI patients from ADNI-GO/2 were designated amyloid “positive” (A+) or “negative” (A−) based on their florbetapir scan and neurodegeneration ‘positive’ or ‘negative’ based on cross-sectional hippocampal volume and longitudinal hippocampal atrophy rate. Results 74.1% of all SNAP participants defined by the cross-sectional definition of neurodegeneration also met the longitudinal definition of neurodegeneration, whereas 25.9% did not. SNAP/L+ displayed larger white matter hyperintensity volume, a higher conversion rate to dementia over 5 years and a steeper decline on cognitive tasks compared to SNAP/L− and the A- CN group. SNAP/L− had more abnormal values on neuroimaging markers and worse performance on cognitive tasks than the A- CN group, but did not show a difference in dementia conversion rate or longitudinal cognition. Discussion Using a longitudinal definition of neurodegeneration in addition to a cross-sectional one identifies SNAP participants with significant cognitive decline and a worse clinical prognosis for which cerebrovascular disease may be an important driver. 74.1% of SNAP subjects also met the criteria for longitudinal neurodegeneration (L+). SNAP/L+ had a larger WMH volume compared to the SNAP/L− group and the A- CN group. SNAP/L+ showed a higher conversion rate and steeper cognitive decline than A- CN. SNAP/L− showed similar conversion rate and cognitive decline as A- CN.
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Affiliation(s)
- L E M Wisse
- Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, 3700 Hamilton Walk, Philadelphia, PA 19104, USA.
| | - S R Das
- Penn Memory Center, Department of Neurology, 3700 Hamilton Walk, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - C Davatzikos
- Center for Biomedical Image Computing and Analytics, 3700 Hamilton Walk, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - B C Dickerson
- Department of Psychiatry and Neurology Services, Massachusetts General Hospital, Harvard Medical School, Building 149 13th Street, Charlestown, MA 02129, USA
| | - S X Xie
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
| | - P A Yushkevich
- Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, 3700 Hamilton Walk, Philadelphia, PA 19104, USA
| | - D A Wolk
- Penn Memory Center, Department of Neurology, 3700 Hamilton Walk, University of Pennsylvania, Philadelphia, PA 19104, USA
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Rubí S, Noguera A, Tarongí S, Oporto M, García A, Vico H, Espino A, Picado M, Mas A, Peña C, Amer G. Concordance between brain 18 F-FDG PET and cerebrospinal fluid biomarkers in diagnosing Alzheimer's disease. Rev Esp Med Nucl Imagen Mol 2018. [DOI: 10.1016/j.remnie.2017.10.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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d'Oleire Uquillas F, Jacobs HIL, Hanseeuw B, Marshall GA, Properzi M, Schultz AP, LaPoint MR, Johnson KA, Sperling RA, Vannini P. Interactive versus additive relationships between regional cortical thinning and amyloid burden in predicting clinical decline in mild AD and MCI individuals. NEUROIMAGE-CLINICAL 2017; 17:388-396. [PMID: 29159051 PMCID: PMC5683806 DOI: 10.1016/j.nicl.2017.10.034] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/25/2017] [Revised: 09/09/2017] [Accepted: 10/28/2017] [Indexed: 11/13/2022]
Abstract
The biological mechanisms that link Beta-amyloid (Aβ) plaque deposition, neurodegeneration, and clinical decline in Alzheimer's disease (AD) dementia, have not been completely elucidated. Here we studied whether amyloid accumulation and neurodegeneration, independently or interactively, predict clinical decline over time in a group of memory impaired older individuals [diagnosed with either amnestic mild cognitive impairment (MCI), or mild AD dementia]. We found that baseline Aβ-associated cortical thinning across clusters encompassing lateral and medial temporal and parietal cortices was related to higher baseline Clinical Dementia Rating Sum-of-Boxes (CDR-SB). Baseline Aβ-associated cortical thinning also predicted CDR-SB over time. Notably, the association between CDR-SB change and cortical thickness values from the right lateral temporo-parietal cortex and right precuneus was driven by individuals with high Aβ burden. In contrast, the association between cortical thickness in the medial temporal lobe (MTL) and clinical decline was similar for individuals with high or low Aβ burden. Furthermore, amyloid pathology was a stronger predictor for clinical decline than MTL thickness. While this study validates previous findings relating AD biomarkers of neurodegeneration to clinical impairment, here we show that regions outside the MTL may be more vulnerable and specific to AD dementia. Additionally, excluding mild AD individuals revealed that these relationships remained, suggesting that lower cortical thickness values in specific regions, vulnerable to amyloid pathology, predict clinical decline already at the prodromal stage. Aβ burden is associated with cortical thinning in a pattern consistent with AD. Interaction between Aβ and neocortical thinning predicts clinical decline. MTL thickness predicts clinical decline regardless of Aβ burden. Amyloid pathology is a stronger predictor for clinical decline than MTL thickness.
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Affiliation(s)
| | - Heidi I L Jacobs
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Bernard Hanseeuw
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA; Department of Neurology, Saint-Luc University Hospital, Institute of Neuroscience, Université Catholique de Louvain, Brussels, Belgium
| | - Gad A Marshall
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Michael Properzi
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Aaron P Schultz
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Molly R LaPoint
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Keith A Johnson
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA; Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Reisa A Sperling
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA; Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Patrizia Vannini
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA; Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
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Chung JK, Plitman E, Nakajima S, Caravaggio F, Shinagawa S, Iwata Y, Gerretsen P, Kim J, Takeuchi H, Patel R, Chakravarty MM, Strafella A, Graff-Guerrero A. The Effects of Cortical Hypometabolism and Hippocampal Atrophy on Clinical Trajectories in Mild Cognitive Impairment with Suspected Non-Alzheimer's Pathology: A Brief Report. J Alzheimers Dis 2017; 60:341-347. [PMID: 28826178 DOI: 10.3233/jad-170098] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
The clinical and structural trajectories of suspected non-Alzheimer' pathology (SNAP) remain elusive due to its heterogeneous etiology. Baseline and longitudinal clinical (global cognition, daily functioning, symptoms of dementia, and learning memory) and hippocampal volume trajectories over two years were compared between patients with amnestic mild cognitive impairment (aMCI) with SNAP with reduced hippocampal volumes (SNAP+HIPPO) and aMCI patients with SNAP without reduced hippocampal volumes. SNAP+HIPPO showed overall worse baseline cognitive functions. Longitudinally, SNAP+HIPPO showed faster deterioration of clinical symptoms of dementia. Having both hippocampal atrophy and cortical hypometabolism without amyloid pathology may exacerbate symptoms of dementia in aMCI.
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Affiliation(s)
- Jun Ku Chung
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, ON, Canada.,Multimodal Imaging Group - Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Eric Plitman
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, ON, Canada.,Multimodal Imaging Group - Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Shinichiro Nakajima
- Multimodal Imaging Group - Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Department of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan.,Geriatric Mental Health Division, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Fernando Caravaggio
- Multimodal Imaging Group - Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | | | - Yusuke Iwata
- Multimodal Imaging Group - Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan
| | - Philip Gerretsen
- Multimodal Imaging Group - Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Geriatric Mental Health Division, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Julia Kim
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, ON, Canada.,Multimodal Imaging Group - Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Hiroyoshi Takeuchi
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Department of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan
| | - Raihaan Patel
- Cerebral Imaging Centre, Douglas Mental Health Institute, McGill University, Montreal, QC, Canada.,Department of Psychiatry and Biomedical Engineering, McGill University, Montreal, QC, Canada
| | - M Mallar Chakravarty
- Cerebral Imaging Centre, Douglas Mental Health Institute, McGill University, Montreal, QC, Canada.,Department of Psychiatry and Biomedical Engineering, McGill University, Montreal, QC, Canada
| | - Antonio Strafella
- Research Imaging Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, ON, Canada.,Division of Brain, Imaging and Behaviour - Systems Neuroscience, Krembil Research Institute, UHN, University of Toronto, Toronto, ON, Canada.,Morton and Gloria Shulman Movement Disorder Unit and E.J. Safra Parkinson Disease Program, Neurology Division, Department of Medicine, Toronto Western Hospital, UHN, University of Toronto, Toronto, ON, Canada
| | - Ariel Graff-Guerrero
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, ON, Canada.,Multimodal Imaging Group - Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Department of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan.,Geriatric Mental Health Division, Centre for Addiction and Mental Health, Toronto, ON, Canada
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LaPoint MR, Chhatwal JP, Sepulcre J, Johnson KA, Sperling RA, Schultz AP. The association between tau PET and retrospective cortical thinning in clinically normal elderly. Neuroimage 2017; 157:612-622. [PMID: 28545932 PMCID: PMC5772972 DOI: 10.1016/j.neuroimage.2017.05.049] [Citation(s) in RCA: 68] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2017] [Revised: 05/12/2017] [Accepted: 05/21/2017] [Indexed: 10/19/2022] Open
Abstract
Tau pathology has been associated with neuronal loss at autopsy, but the temporal evolution of tau pathology and atrophy remains unclear. Here, we investigate the association between cross-sectional AV-1451-PET as a marker of tau pathology and cortical thickness cross-sectionally. We also investigated retrospective rates of cortical thinning over the three years preceding the AV-1451 scan in a clinically normal cohort of 103 older adults from the Harvard Aging Brain Study. Tau measurements were Geometric Transfer Matrix partial volume corrected standardized uptake value ratios (SUVRs) with a cerebellar gray reference region. Thirty-four FreeSurfer-defined cortical regions of interest (ROIs) were used for both thickness and AV-1451 in each hemisphere, with seven additional volumetric ROIs. We examined "local" relationships between AV-1451 and cortical thickness in the same ROI, as well as inferior temporal AV-1451 and all thickness ROIs. All models included baseline age and sex, both interacting with time in retrospective longitudinal models, as covariates. Cross-sectional models controlled for the number of days between the two scans. Cross-sectional local comparisons revealed significant associations between elevated AV-1451 and thinner cortical ROIs predominantly in temporal regions, while analyses associating inferior temporal AV-1451 with all cortical ROIs showed a widespread pattern of significant relationships, which was strongest in temporal and parietal cortices. In our retrospective longitudinal analyses, we saw significant relationships in temporal and parietal regions. Significant local relationships were seen in right superior temporal, middle temporal, temporal pole, and fusiform, as well as the left cuneus and banks of the left superior temporal sulcus. Significant relationships between inferior temporal AV-1451 and faster thinning were observed in right temporal regions (middle temporal and fusiform) and bilateral parahippocampal cortices. We observed significant negative relationships between local and inferior temporal AV-1451 signal and both cross-sectional cortical thickness and rates of thinning in lateral and medial temporal regions. This is an important early step toward elucidating the relationship between tau pathology and retrospective longitudinal atrophy in aging and preclinical AD.
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Affiliation(s)
- Molly R LaPoint
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, and the Martinos Center for Biomedical Imaging, 149/10.008 13th Street, Charlestown, MA 02129, USA
| | - Jasmeer P Chhatwal
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, and the Martinos Center for Biomedical Imaging, 149/10.008 13th Street, Charlestown, MA 02129, USA
| | - Jorge Sepulcre
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA 02115, USA
| | - Keith A Johnson
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, and the Martinos Center for Biomedical Imaging, 149/10.008 13th Street, Charlestown, MA 02129, USA; Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, 220 Longwood Ave, Boston, MA 02115, USA; Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA 02115, USA.
| | - Reisa A Sperling
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, and the Martinos Center for Biomedical Imaging, 149/10.008 13th Street, Charlestown, MA 02129, USA; Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, 220 Longwood Ave, Boston, MA 02115, USA; Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA 02115, USA
| | - Aaron P Schultz
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, and the Martinos Center for Biomedical Imaging, 149/10.008 13th Street, Charlestown, MA 02129, USA
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Schreiber S, Schreiber F, Lockhart SN, Horng A, Bejanin A, Landau SM, Jagust WJ. Alzheimer Disease Signature Neurodegeneration and APOE Genotype in Mild Cognitive Impairment With Suspected Non-Alzheimer Disease Pathophysiology. JAMA Neurol 2017; 74:650-659. [PMID: 28319241 DOI: 10.1001/jamaneurol.2016.5349] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Importance There are conflicting results claiming that Alzheimer disease signature neurodegeneration may be more, less, or similarly advanced in individuals with β-amyloid peptide (Aβ)-negative (Aβ-) suspected non-Alzheimer disease pathophysiology (SNAP) than in Aβ-positive (Aβ+) counterparts. Objective To examine patterns of neurodegeneration in individuals with SNAP compared with their Aβ+ counterparts. Design, Setting, and Participants A longitudinal cohort study was conducted among individuals with mild cognitive impairment (MCI) and cognitively normal individuals receiving care at Alzheimer's Disease Neuroimaging Initiative sites in the United States and Canada for a mean follow-up period of 30.5 months from August 1, 2005, to June 30, 2015. Several neurodegeneration biomarkers and longitudinal cognitive function were compared between patients with distinct SNAP (Aβ- and neurodegeneration-positive [Aβ-N+]) subtypes and their Aβ+N+ counterparts. Main Outcomes and Measures Participants were classified according to the results of their florbetapir F-18 (Aβ) positron emission tomography and their Alzheimer disease-associated neurodegeneration status (temporoparietal glucose metabolism determined by fluorodeoxyglucose F 18 [FDG]-labeled positron emission tomography and/or hippocampal volume [HV] determined by magnetic resonance imaging: participants with subthreshold HV values were regarded as exhibiting hippocampal volume atrophy [HV+], while subthreshold mean FDG values were considered as FDG hypometabolism [FDG+]). Results The study comprised 265 cognitively normal individuals (135 women and 130 men; mean [SD] age, 75.5 [6.7] years) and 522 patients with MCI (225 women and 297 men; mean [SD] age, 72.6 [7.8] years). A total of 469 individuals with MCI had data on neurodegeneration biomarkers; of these patients, 107 were Aβ-N+ (22.8%; 63 FDG+, 82 HV+, and 38 FDG+HV+) and 187 were Aβ+N+ (39.9%; 135 FDG+, 147 HV+, and 95 FDG+HV+ cases). A total of 209 cognitively normal participants had data on neurodegeneration biomarkers; of these, 52 were Aβ-N+ (24.9%; 30 FDG+, 33 HV+, and 11 FDG+HV+) and 37 were Aβ+N+ (17.7%; 22 FDG+, 26 HV+, and 11 FDG+HV+). Compared with their Aβ+ counterparts, all patients with MCI SNAP subtypes displayed better preservation of temporoparietal FDG metabolism (mean [SD] FDG: Aβ-N+, 1.25 [0.11] vs Aβ+N+, 1.19 [0.11]), less severe atrophy of the lateral temporal lobe, and lower mean (SD) cerebrospinal fluid levels of tau (59.2 [32.8] vs 111.3 [56.4]). In MCI with SNAP, sustained glucose metabolism and gray matter volume were associated with disproportionately low APOE ε4 (Aβ-N+, 18.7% vs Aβ+N+, 70.6%) and disproportionately high APOE ε2 (18.7% vs 4.8%) carrier prevalence. Slower cognitive decline and lower rates of progression to Alzheimer disease (Aβ-N+, 6.5% vs Aβ+N+, 32.6%) were also seen in patients with MCI with SNAP subtypes compared with their Aβ+ counterparts. In cognitively normal individuals, neurodegeneration biomarkers did not differ between Aβ-N+ and Aβ+N+ cases. Conclusions and Relevance In MCI with SNAP, low APOE ε4 and high APOE ε2 carrier prevalence may account for differences in neurodegeneration patterns between Aβ-N+ and Aβ+N+ cases independent from the neuroimaging biomarker modality used to define neurodegeneration associated with Alzheimer disease.
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Affiliation(s)
- Stefanie Schreiber
- Helen Wills Neuroscience Institute, University of California, Berkeley2Department of Neurology, Otto-Von-Guericke University, Magdeburg, Germany3German Center for Neurodegenerative Diseases, Magdeburg, Germany
| | - Frank Schreiber
- Department of Neurology, Otto-Von-Guericke University, Magdeburg, Germany3German Center for Neurodegenerative Diseases, Magdeburg, Germany4Institute of Control Engineering, Technische Universität Braunschweig, Braunschweig, Germany
| | - Samuel N Lockhart
- Helen Wills Neuroscience Institute, University of California, Berkeley
| | - Andy Horng
- Helen Wills Neuroscience Institute, University of California, Berkeley
| | - Alexandre Bejanin
- Memory and Aging Center, Department of Neurology, University of California, San Francisco
| | - Susan M Landau
- Helen Wills Neuroscience Institute, University of California, Berkeley6Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, California
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California, Berkeley6Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, California
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Concordance between brain 18F-FDG PET and cerebrospinal fluid biomarkers in diagnosing Alzheimer's disease. Rev Esp Med Nucl Imagen Mol 2017. [PMID: 28645685 DOI: 10.1016/j.remn.2017.05.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
OBJECTIVES Cortical posterior hypometabolism on PET imaging with 18F-FDG (FDG-PET), and altered levels of Aß1-42 peptide, total Tau (tTau) and phosphorylated Tau (pTau) proteins in cerebrospinal fluid (CSF) are established diagnostic biomarkers in Alzheimer's disease (AD). An evaluation has been made of the concordance and relationship between the results of FDG-PET and CSF biomarkers in symptomatic patients with suspected AD. MATERIAL AND METHODS A retrospective review was carried out on 120 patients with cognitive impairment referred to our Cognitive Neurology Unit, and who were evaluated by brain FDG-PET and a lumbar puncture for CSF biomarkers. In order to calculate their Kappa coefficient of concordance, the result of the FDG-PET and the set of the three CSF biomarkers in each patient was classified as normal, inconclusive, or AD-compatible. The relationship between the results of both methods was further assessed using logistic regression analysis, including the Aß1-42, tTau and pTau levels as quantitative predictors, and the FDG-PET result as the dependent variable. RESULTS The weighted Kappa coefficient between FDG-PET and CSF biomarkers was 0.46 (95% CI: 0.35-0.57). Logistic regression analysis showed that the Aß1-42 and tTau values together were capable of discriminating an FDG-PET result metabolically suggestive of AD from one non-suggestive of AD, with a 91% sensitivity and 93% specificity at the cut-off line Aß1-42=44+1.3×tTau. CONCLUSIONS The level of concordance between FDG-PET and CSF biomarkers was moderate, indicating their complementary value in diagnosing AD. The Aß1-42 and tTau levels in CSF help to predict the patient FDG-PET cortical metabolic status.
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Kielb S, Rogalski E, Weintraub S, Rademaker A. Objective features of subjective cognitive decline in a United States national database. Alzheimers Dement 2017; 13:1337-1344. [PMID: 28586648 DOI: 10.1016/j.jalz.2017.04.008] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2016] [Revised: 04/10/2017] [Accepted: 04/28/2017] [Indexed: 12/23/2022]
Abstract
INTRODUCTION Functional and cognitive features of subjective cognitive decline (SCD) were identified in a longitudinal database from the National Alzheimer's Coordinating Center. METHODS Cognitively normal older adults with (SCD+) and without (SCD-) self-reported memory complaints (N = 3915) were compared on (1) baseline Functional Assessment Questionnaire ratings, (2) baseline scores and longitudinal rate of change estimates from nine neuropsychological tests, and (3) final clinical diagnoses. RESULTS SCD+ had higher baseline ratings of functional impairment, reduced episodic memory practice effects and poorer performance on neuropsychological tests of psychomotor speed and language, and higher frequencies of mild cognitive impairment and dementia diagnoses at the end of follow-up compared with the SCD-group. DISCUSSION Subtle clinical features of SCD identified in this large cohort are difficult to detect at the individual level. More sensitive tests are needed to identify those with SCD who are vulnerable to cognitive decline and dementia.
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Affiliation(s)
- Stephanie Kielb
- Cognitive Neurology and Alzheimer's Disease Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA; Department of Psychiatry and Behavioral Sciences, Division of Clinical Psychology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
| | - Emily Rogalski
- Cognitive Neurology and Alzheimer's Disease Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Sandra Weintraub
- Cognitive Neurology and Alzheimer's Disease Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA; Department of Psychiatry and Behavioral Sciences, Division of Clinical Psychology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA; Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Alfred Rademaker
- Cognitive Neurology and Alzheimer's Disease Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA; Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
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Jack CR, Wiste HJ, Weigand SD, Therneau TM, Knopman DS, Lowe V, Vemuri P, Mielke MM, Roberts RO, Machulda MM, Senjem ML, Gunter JL, Rocca WA, Petersen RC. Age-specific and sex-specific prevalence of cerebral β-amyloidosis, tauopathy, and neurodegeneration in cognitively unimpaired individuals aged 50-95 years: a cross-sectional study. Lancet Neurol 2017; 16:435-444. [PMID: 28456479 PMCID: PMC5516534 DOI: 10.1016/s1474-4422(17)30077-7] [Citation(s) in RCA: 228] [Impact Index Per Article: 32.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2016] [Revised: 02/09/2017] [Accepted: 03/06/2017] [Indexed: 12/21/2022]
Abstract
BACKGROUND A new classification for biomarkers in Alzheimer's disease and cognitive ageing research is based on grouping the markers into three categories: amyloid deposition (A), tauopathy (T), and neurodegeneration or neuronal injury (N). Dichotomising these biomarkers as normal or abnormal results in eight possible profiles. We determined the clinical characteristics and prevalence of each ATN profile in cognitively unimpaired individuals aged 50 years and older. METHODS All participants were in the Mayo Clinic Study of Aging, a population-based study that uses a medical records linkage system to enumerate all individuals aged 50-89 years in Olmsted County, MN, USA. Potential participants are randomly selected, stratified by age and sex, and invited to participate in cognitive assessments; individuals without medical contraindications are invited to participate in brain imaging studies. Participants who were judged clinically as having no cognitive impairment and underwent multimodality imaging between Oct 11, 2006, and Oct 5, 2016, were included in the current study. Participants were classified as having normal (A-) or abnormal (A+) amyloid using amyloid PET, normal (T-) or abnormal (T+) tau using tau PET, and normal (N-) or abnormal (N+) neurodegeneration or neuronal injury using cortical thickness assessed by MRI. We used the cutoff points of standard uptake value ratio (SUVR) 1·42 (centiloid 19) for amyloid PET, 1·23 SUVR for tau PET, and 2·67 mm for MRI cortical thickness. Age-specific and sex-specific prevalences of the eight groups were determined using multinomial models combining data from 435 individuals with amyloid PET, tau PET, and MRI assessments, and 1113 individuals who underwent amyloid PET and MRI, but not tau PET imaging. FINDINGS The numbers of participants in each profile group were 165 A-T-N-, 35 A-T+N-, 63 A-T-N+, 19 A-T+N+, 44 A+T-N-, 25 A+T+N-, 35 A+T-N+, and 49 A+T+N+. Age differed by ATN group (p<0·0001), ranging from a median 58 years (IQR 55-64) in A-T-N- and 57 years (54-64) in A-T+N- to a median 80 years (75-84) in A+T-N+ and 79 years (73-87) in A+T+N+. The number of APOE ε4 carriers differed by ATN group (p=0·04), with carriers roughly twice as frequent in each A+ group versus the corresponding A- group. White matter hyperintensity volume (p<0·0001) and cognitive performance (p<0·0001) also differed by ATN group. Tau PET and neurodegeneration biomarkers were discordant in most individuals who would be categorised as stage 2 or 3 preclinical Alzheimer's disease (A+T+N-, A+T-N+, and A+T+N+; 86% at age 65 years and 51% at age 80 years) or with suspected non-Alzheimer's pathophysiology (A-T+N-, A-T-N+, and A-T+N+; 92% at age 65 years and 78% at age 80 years). From age 50 years, A-T-N- prevalence declined and A+T+N+ and A-T+N+ prevalence increased. In both men and women, A-T-N- was the most prevalent until age late 70s. After about age 80 years, A+T+N+ was most prevalent. By age 85 years, more than 90% of men and women had one or more biomarker abnormalities. INTERPRETATION Biomarkers of fibrillar tau deposition can be included with those of β-amyloidosis and neurodegeneration or neuronal injury to more fully characterise the heterogeneous pathological profiles in the population. Both amyloid- dependent and amyloid-independent pathological profiles can be identified in the cognitively unimpaired population. The prevalence of each ATN group changed substantially with age, with progression towards more biomarker abnormalities among individuals who remained cognitively unimpaired. FUNDING National Institute on Aging (part of the US National Institutes of Health), the Alexander Family Professorship of Alzheimer's Disease Research, the Mayo Clinic, and the GHR Foundation.
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Affiliation(s)
| | - Heather J Wiste
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Stephen D Weigand
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Terry M Therneau
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | | | - Val Lowe
- Department of Nuclear Medicine, Mayo Clinic, Rochester, MN, USA
| | | | - Michelle M Mielke
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA; Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Rosebud O Roberts
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA; Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Mary M Machulda
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - Matthew L Senjem
- Department of Information Technology, Mayo Clinic, Rochester, MN, USA
| | - Jeffrey L Gunter
- Department of Information Technology, Mayo Clinic, Rochester, MN, USA
| | - Walter A Rocca
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA; Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Ronald C Petersen
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA; Department of Neurology, Mayo Clinic, Rochester, MN, USA
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Abstract
Ageing is associated with changes in the nervous system with consequent alterations in some neurological examination findings: understanding what is 'normal' at different ages is essential when evaluating patients. In seminal papers published in 1931, Dr MacDonald Critchley summarised his observations and the prevailing evidence on the effects of ageing on, among others, sensation, reflexes, ocular function, olfaction, movement and cognition. In this review, these observations are re-evaluated in light of contemporary evidence. Factors influencing the measurement and interpretation of these clinical findings are then discussed, including reproducibility, the influence of comorbidities, secular trends, how 'normality' should best be defined, the problems of extrapolating group data to individuals and the influence of presymptomatic neurodegenerative disease states. The case is made that context is critical, and that combining life course data with detailed clinical and biomarker phenotyping is required to understand the determinants of normal neurological function associated with ageing.
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Schott JM. Imaging the ageing brain: identifying early disease or opening Pandora's box? Lancet Neurol 2017; 16:411-413. [PMID: 28456480 DOI: 10.1016/s1474-4422(17)30116-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2017] [Accepted: 03/22/2017] [Indexed: 11/26/2022]
Affiliation(s)
- Jonathan M Schott
- Dementia Research Centre, University College London Institute of Neurology, London WC1N 3BG, UK.
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Saint-Aubert L, Lemoine L, Chiotis K, Leuzy A, Rodriguez-Vieitez E, Nordberg A. Tau PET imaging: present and future directions. Mol Neurodegener 2017; 12:19. [PMID: 28219440 PMCID: PMC5319037 DOI: 10.1186/s13024-017-0162-3] [Citation(s) in RCA: 202] [Impact Index Per Article: 28.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2016] [Accepted: 02/15/2017] [Indexed: 12/15/2022] Open
Abstract
Abnormal aggregation of tau in the brain is a major contributing factor in various neurodegenerative diseases. The role of tau phosphorylation in the pathophysiology of tauopathies remains unclear. Consequently, it is important to be able to accurately and specifically target tau deposits in vivo in the brains of patients. The advances of molecular imaging in the recent years have now led to the recent development of promising tau-specific tracers for positron emission tomography (PET), such as THK5317, THK5351, AV-1451, and PBB3. These tracers are now available for clinical assessment in patients with various tauopathies, including Alzheimer's disease, as well as in healthy subjects. Exploring the patterns of tau deposition in vivo for different pathologies will allow discrimination between neurodegenerative diseases, including different tauopathies, and monitoring of disease progression. The variety and complexity of the different types of tau deposits in the different diseases, however, has resulted in quite a challenge for the development of tau PET tracers. Extensive work remains in order to fully characterize the binding properties of the tau PET tracers, and to assess their usefulness as an early biomarker of the underlying pathology. In this review, we summarize recent findings on the most promising tau PET tracers to date, discuss what has been learnt from these findings, and offer some suggestions for the next steps that need to be achieved in a near future.
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Affiliation(s)
- Laure Saint-Aubert
- Department NVS, Center for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Karolinska Institutet, Novum 5th floor, 141 57, Huddinge, Sweden
| | - Laetitia Lemoine
- Department NVS, Center for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Karolinska Institutet, Novum 5th floor, 141 57, Huddinge, Sweden
| | - Konstantinos Chiotis
- Department NVS, Center for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Karolinska Institutet, Novum 5th floor, 141 57, Huddinge, Sweden
| | - Antoine Leuzy
- Department NVS, Center for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Karolinska Institutet, Novum 5th floor, 141 57, Huddinge, Sweden
| | - Elena Rodriguez-Vieitez
- Department NVS, Center for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Karolinska Institutet, Novum 5th floor, 141 57, Huddinge, Sweden
| | - Agneta Nordberg
- Department NVS, Center for Alzheimer Research, Division of Translational Alzheimer Neurobiology, Karolinska Institutet, Novum 5th floor, 141 57, Huddinge, Sweden. .,Department of Geriatric Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden.
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