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Wybitul M, Buchmann A, Langer N, Hock C, Treyer V, Gietl A. Trajectories of amyloid beta accumulation - Unveiling the relationship with APOE genotype and cognitive decline. Neurobiol Aging 2024; 139:44-53. [PMID: 38593527 DOI: 10.1016/j.neurobiolaging.2024.03.007] [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: 10/23/2023] [Revised: 03/18/2024] [Accepted: 03/24/2024] [Indexed: 04/11/2024]
Abstract
Amyloid beta (Aβ) follows a sigmoidal time function with varying accumulation rates. We studied how the position on this function, reflected by different Aβ accumulation phases, influences APOE ɛ4's association with Aβ and cognitive decline in 503 participants without dementia using Aβ-PET imaging over 5.3-years. First, Aβ load and accumulation were analyzed irrespective of phases using linear mixed regression. Generally, ɛ4 carriers displayed a higher Aβ load. Moreover, Aβ normal (Aβ-) ɛ4 carriers demonstrated higher accumulation. Next, we categorized accumulation phases as "decrease", "stable", or "increase" based on trajectory shapes. After excluding the Aβ-/decrease participants from the initial regression, the difference in accumulation attributable to genotype among Aβ- individuals was no longer significant. Further analysis revealed that in increase phases, Aβ accumulation was higher among noncarriers, indicating a genotype-related timeline shift. Finally, cognitive decline was analyzed across phases and was already evident in the Aβ-/increase phase. Our results encourage early interventions for ɛ4 carriers and imply that monitoring accumulating Aβ- individuals might help identify those at risk for cognitive decline.
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Affiliation(s)
- Maha Wybitul
- Institute for Regenerative Medicine, Faculty of Medicine, University of Zurich, Schlieren 8952, Switzerland; Department of Psychology, Faculty of Philosophy, University of Zurich, Zurich 8050, Switzerland
| | - Andreas Buchmann
- Institute for Regenerative Medicine, Faculty of Medicine, University of Zurich, Schlieren 8952, Switzerland
| | - Nicolas Langer
- Methods of Plasticity Research, Department of Psychology, University of Zurich, Zurich 8050, Switzerland
| | - Christoph Hock
- Institute for Regenerative Medicine, Faculty of Medicine, University of Zurich, Schlieren 8952, Switzerland; Neurimmune, Schlieren 8952, Switzerland
| | - Valerie Treyer
- Institute for Regenerative Medicine, Faculty of Medicine, University of Zurich, Schlieren 8952, Switzerland; Department of Nuclear Medicine, University of Zurich, Zurich 8091, Switzerland.
| | - Anton Gietl
- Institute for Regenerative Medicine, Faculty of Medicine, University of Zurich, Schlieren 8952, Switzerland; University Hospital for Geriatric Psychiatry, Zurich 8008, Switzerland
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Liu Z, Shi D, Cai Y, Li A, Lan G, Sun P, Liu L, Zhu Y, Yang J, Zhou Y, Guo L, Zhang L, Deng S, Chen S, Yu X, Chen X, Zhao R, Wang Q, Ran P, Xu L, Zhou L, Sun K, Wang X, Peng Q, Han Y, Guo T. Pathophysiology characterization of Alzheimer's disease in South China's aging population: for the Greater-Bay-Area Healthy Aging Brain Study (GHABS). Alzheimers Res Ther 2024; 16:84. [PMID: 38627753 PMCID: PMC11020808 DOI: 10.1186/s13195-024-01458-z] [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: 10/28/2023] [Accepted: 04/12/2024] [Indexed: 04/19/2024]
Abstract
INTRODUCTION The Guangdong-Hong Kong-Macao Greater-Bay-Area of South China has an 86 million population and faces a significant challenge of Alzheimer's disease (AD). However, the characteristics and prevalence of AD in this area are still unclear due to the rarely available community-based neuroimaging AD cohort. METHODS Following the standard protocols of the Alzheimer's Disease Neuroimaging Initiative, the Greater-Bay-Area Healthy Aging Brain Study (GHABS) was initiated in 2021. GHABS participants completed clinical assessments, plasma biomarkers, genotyping, magnetic resonance imaging (MRI), β-amyloid (Aβ) positron emission tomography (PET) imaging, and tau PET imaging. The GHABS cohort focuses on pathophysiology characterization and early AD detection in the Guangdong-Hong Kong-Macao Greater Bay Area. In this study, we analyzed plasma Aβ42/Aβ40 (A), p-Tau181 (T), neurofilament light, and GFAP by Simoa in 470 Chinese older adults, and 301, 195, and 70 had MRI, Aβ PET, and tau PET, respectively. Plasma biomarkers, Aβ PET, tau PET, hippocampal volume, and temporal-metaROI cortical thickness were compared between normal control (NC), subjective cognitive decline (SCD), mild cognitive impairment (MCI), and dementia groups, controlling for age, sex, and APOE-ε4. The prevalence of plasma A/T profiles and Aβ PET positivity were also determined in different diagnostic groups. RESULTS The aims, study design, data collection, and potential applications of GHABS are summarized. SCD individuals had significantly higher plasma p-Tau181 and plasma GFAP than the NC individuals. MCI and dementia patients showed more abnormal changes in all the plasma and neuroimaging biomarkers than NC and SCD individuals. The frequencies of plasma A+/T+ (NC; 5.9%, SCD: 8.2%, MCI: 25.3%, dementia: 64.9%) and Aβ PET positivity (NC: 25.6%, SCD: 22.5%, MCI: 47.7%, dementia: 89.3%) were reported. DISCUSSION The GHABS cohort may provide helpful guidance toward designing standard AD community cohorts in South China. This study, for the first time, reported the pathophysiology characterization of plasma biomarkers, Aβ PET, tau PET, hippocampal atrophy, and AD-signature cortical thinning, as well as the prevalence of Aβ PET positivity in the Guangdong-Hong Kong-Macao Greater Bay Area of China. These findings provide novel insights into understanding the characteristics of abnormal AD pathological changes in South China's older population.
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Affiliation(s)
- Zhen Liu
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Dai Shi
- Neurology Medicine Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, 518000, China
| | - Yue Cai
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Anqi Li
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Guoyu Lan
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Pan Sun
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Lin Liu
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Yalin Zhu
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Jie Yang
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Yajing Zhou
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Lizhi Guo
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Laihong Zhang
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Shuqing Deng
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Shuda Chen
- Neurology Medicine Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, 518000, China
| | - Xianfeng Yu
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China
| | - Xuhui Chen
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
- Department of Neurology, Peking University Shenzhen Hospital, Shenzhen, 518000, China
| | - Ruiyue Zhao
- Department of Nuclear Medicine, The First Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510120, China
| | - Qingyong Wang
- Department of Neurology, University of Chinese Academy of Sciences-Shenzhen Hospital, Shenzhen, 518107, China
| | - Pengcheng Ran
- Department of Nuclear Medicine, Guangdong Hospital of Traditional Chinese Medicine, Guangzhou, 510120, China
| | - Linsen Xu
- Department of Medical Imaging, University of Chinese Academy of Sciences-Shenzhen Hospital, Shenzhen, 518106, China
| | - Liemin Zhou
- Neurology Medicine Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, 518000, China
| | - Kun Sun
- Institute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen, 518132, China
| | - Xinlu Wang
- Department of Nuclear Medicine, The First Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510120, China
| | - Qiyu Peng
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Ying Han
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China
- School of Biomedical Engineering, Hainan University, Haikou, 570228, China
- Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, 100053, China
- National Clinical Research Center for Geriatric Diseases, Beijing, 100053, China
| | - Tengfei Guo
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China.
- Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, Shenzhen, 518055, China.
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Wiesman AI, Gallego-Rudolf J, Villeneuve S, Baillet S, Wilson TW. Alignments between cortical neurochemical systems, proteinopathy and neurophysiological alterations along the Alzheimer's disease continuum. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.13.24305551. [PMID: 38645027 PMCID: PMC11030470 DOI: 10.1101/2024.04.13.24305551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Two neuropathological hallmarks of Alzheimer's disease (AD) are the accumulation of amyloid-β (Aβ) proteins and alterations in cortical neurophysiological signaling. Despite parallel research indicating disruption of multiple neurotransmitter systems in AD, it has been unclear whether these two phenomena are related to the neurochemical organization of the cortex. We leveraged task-free magnetoencephalography and positron emission tomography, with a cortical atlas of 19 neurotransmitters to study the alignment and interactions between alterations of neurophysiological signaling, Aβ deposition, and the neurochemical gradients of the human cortex. In patients with amnestic mild cognitive impairment (N = 18) and probable AD (N = 20), we found that changes in rhythmic, but not arrhythmic, cortical neurophysiological signaling relative to healthy controls (N = 20) are topographically aligned with cholinergic, serotonergic, and dopaminergic neurochemical systems. These neuro-physio-chemical alignments are related to the severity of cognitive and behavioral impairments. We also found that cortical Aβ plaques are preferentially deposited along neurochemical boundaries, and mediate how beta-band rhythmic cortical activity maps align with muscarinic acetylcholine receptors. Finally, we show in an independent dataset that many of these alignments manifest in the asymptomatic stages of cortical Aβ accumulation (N = 33; N = 71 healthy controls), particularly the Aβ-neurochemical alignments (57.1%) and neuro-physio-chemical alignments in the alpha frequency band (62.5%). Overall, the present study demonstrates that the expression of pathology in pre-clinical and clinical AD aligns topographically with the cortical distribution of chemical neuromodulator systems, scaling with clinical severity and with implications for potential pharmacotherapeutic pathways.
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Yu M, Risacher SL, Nho KT, Wen Q, Oblak AL, Unverzagt FW, Apostolova LG, Farlow MR, Brosch JR, Clark DG, Wang S, Deardorff R, Wu YC, Gao S, Sporns O, Saykin AJ. Spatial transcriptomic patterns underlying amyloid-β and tau pathology are associated with cognitive dysfunction in Alzheimer's disease. Cell Rep 2024; 43:113691. [PMID: 38244198 PMCID: PMC10926093 DOI: 10.1016/j.celrep.2024.113691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 11/29/2023] [Accepted: 01/03/2024] [Indexed: 01/22/2024] Open
Abstract
Amyloid-β (Aβ) and tau proteins accumulate within distinct neuronal systems in Alzheimer's disease (AD). Although it is not clear why certain brain regions are more vulnerable to Aβ and tau pathologies than others, gene expression may play a role. We study the association between brain-wide gene expression profiles and regional vulnerability to Aβ (gene-to-Aβ associations) and tau (gene-to-tau associations) pathologies by leveraging two large independent AD cohorts. We identify AD susceptibility genes and gene modules in a gene co-expression network with expression profiles specifically related to regional vulnerability to Aβ and tau pathologies in AD. In addition, we identify distinct biochemical pathways associated with the gene-to-Aβ and the gene-to-tau associations. These findings may explain the discordance between regional Aβ and tau pathologies. Finally, we propose an analytic framework, linking the identified gene-to-pathology associations to cognitive dysfunction in AD at the individual level, suggesting potential clinical implication of the gene-to-pathology associations.
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Affiliation(s)
- Meichen Yu
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana University Network Science Institute, Bloomington, IN, USA.
| | - Shannon L Risacher
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Kwangsik T Nho
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana University Network Science Institute, Bloomington, IN, USA
| | - Qiuting Wen
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Adrian L Oblak
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Frederick W Unverzagt
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Liana G Apostolova
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Martin R Farlow
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Jared R Brosch
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - David G Clark
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Sophia Wang
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Rachael Deardorff
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Yu-Chien Wu
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Sujuan Gao
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Olaf Sporns
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana University Network Science Institute, Bloomington, IN, USA; Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Andrew J Saykin
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana University Network Science Institute, Bloomington, IN, USA.
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Wang M, Wang Z, Yu Y, Zhao D, Shen Z, Wei F. From teeth to brain: dental caries causally affects the cortical thickness of the banks of the superior temporal sulcus. BMC Oral Health 2024; 24:124. [PMID: 38263072 PMCID: PMC10807149 DOI: 10.1186/s12903-024-03899-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Accepted: 01/15/2024] [Indexed: 01/25/2024] Open
Abstract
OBJECTIVES Dental caries is one of the most prevalent oral diseases and causes of tooth loss. Cross-sectional studies observed epidemiological associations between dental caries and brain degeneration disorders, while it is unknown whether dental caries causally affect the cerebral structures. This study tested whether genetically proxied DMFS (the sum of Decayed, Missing, and Filled tooth Surfaces) causally impacts the brain cortical structure using Mendelian randomization (MR). METHODS The summary-level GWAS meta-analysis data from the GLIDE consortium were used for DMFS, including 26,792 participants. ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) consortium GWAS summary data of 51,665 patients were used for brain structure. This study estimated the causal effects of DMFS on the surface area (SA) and thickness (TH) of the global cortex and functional cortical regions accessed by magnetic resonance imaging (MRI). Inverse-variance weighted (IVW) was used as the primary estimate, the MR pleiotropy residual sum and outlier (MR-PRESSO), the MR-Egger intercept test, and leave-one-out analyses were used to examine the potential horizontal pleiotropy. RESULTS Genetically proxied DMFS decreases the TH of the banks of the superior temporal sulcus (BANSSTS) with or without global weighted (weighted, β = - 0.0277 mm, 95% CI: - 0.0470 mm to - 0.0085 mm, P = 0.0047; unweighted, β = - 0.0311 mm, 95% CI: - 0.0609 mm to - 0.0012 mm, P = 0.0412). The causal associations were robust in various sensitivity analyses. CONCLUSIONS Dental caries causally decrease the cerebral cortical thickness of the BANKSSTS, a cerebral cortical region crucial for language-related functions, and is the most affected brain region in Alzheimer's disease. This investigation provides the first evidence that dental caries causally affects brain structure, proving the existence of teeth-brain axes. This study also suggested that clinicians should highlight the causal effects of dental caries on brain disorders during the diagnosis and treatments, the cortical thickness of BANKSSTS is a promising diagnostic measurement for dental caries-related brain degeneration.
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Affiliation(s)
- Mengqiao Wang
- Department of Orthodontics, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University, Jinan, China
- Shandong Key Laboratory of Oral Tissue Regeneration & Shandong Engineering Research Center of Dental Materials and Oral Tissue Regeneration & Shandong Provincial Clinical Research Center for Oral Diseases, Jinan, China
| | - Ziyao Wang
- Department of Orthodontics, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University, Jinan, China
- Shandong Key Laboratory of Oral Tissue Regeneration & Shandong Engineering Research Center of Dental Materials and Oral Tissue Regeneration & Shandong Provincial Clinical Research Center for Oral Diseases, Jinan, China
| | - Yajie Yu
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital/Institute of Mental Health, The Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, 100191, China
| | - Delu Zhao
- Department of Orthodontics, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University, Jinan, China
- Shandong Key Laboratory of Oral Tissue Regeneration & Shandong Engineering Research Center of Dental Materials and Oral Tissue Regeneration & Shandong Provincial Clinical Research Center for Oral Diseases, Jinan, China
| | - Zhiyuan Shen
- Department of Oral and Maxillofacial Surgery, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University, Jinan, China
- Shandong Key Laboratory of Oral Tissue Regeneration & Shandong Engineering Research Center of Dental Materials and Oral Tissue Regeneration & Shandong Provincial Clinical Research Center for Oral Diseases, Jinan, China
| | - Fulan Wei
- Department of Orthodontics, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University, Jinan, China.
- Shandong Key Laboratory of Oral Tissue Regeneration & Shandong Engineering Research Center of Dental Materials and Oral Tissue Regeneration & Shandong Provincial Clinical Research Center for Oral Diseases, Jinan, China.
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Wang D, Xu K, Dang M, Sang F, Chen K, Zhang Z, Li X. Multi-domain cognition dysfunction accompanies frontoparietal and temporal amyloid accumulation in the elderly. Cereb Cortex 2023; 33:11329-11338. [PMID: 37859548 DOI: 10.1093/cercor/bhad369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 09/18/2023] [Accepted: 09/19/2023] [Indexed: 10/21/2023] Open
Abstract
It is helpful to understand the pathology of Alzheimer's disease by exploring the relationship between amyloid-β accumulation and cognition. The study explored the relationship between regional amyloid-β accumulation and multiple cognitions and study their application value in the Alzheimer's disease diagnosis. 135 participants completed 18F-florbetapir Positron Emission Tomography (PET), structural MRI, and a cognitive battery. Partial correlation was used to examine the relationship between global and regional amyloid-β accumulation and cognitions. Then, a support vector machine was applied to determine whether cognition-related accumulation regions can adequately distinguish the cognitively normal controls (76 participants) and mild cognitive impairment (30 participants) groups or mild cognitive impairment and Alzheimer's disease (29 participants) groups. The result showed that amyloid-β accumulation regions were mainly located in the frontoparietal cortex, calcarine fissure, and surrounding cortex and temporal pole regions. Episodic memory-related regions included the frontoparietal cortices; executive function-related regions included the frontoparietal, temporal, and occipital cortices; and processing speed-related regions included the frontal and occipital cortices. Support vector machine analysis showed that only episodic memory-related amyloid-β accumulation regions had better classification performance during the progression of Alzheimer's disease. Assessing regional changes in amyloid, particularly in frontoparietal regions, can aid in the early detection of amyloid-related decline in cognitive function.
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Affiliation(s)
- Dandan Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19, Xinjiekouwai St, Haidian District, Beijing, 100875, P.R. China
- Beijing Aging Brain Rejuvenation Initiative (BABRI) Center, Beijing Normal University, No. 19, Xinjiekouwai St, Haidian District, Beijing, 100875, P.R. China
| | - Kai Xu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19, Xinjiekouwai St, Haidian District, Beijing, 100875, P.R. China
- Beijing Aging Brain Rejuvenation Initiative (BABRI) Center, Beijing Normal University, No. 19, Xinjiekouwai St, Haidian District, Beijing, 100875, P.R. China
- School of Artificial Intelligence, Beijing Normal University, No. 19, Xinjiekouwai St, Haidian District, Beijing, 100875, P.R. China
| | - Mingxi Dang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19, Xinjiekouwai St, Haidian District, Beijing, 100875, P.R. China
- Beijing Aging Brain Rejuvenation Initiative (BABRI) Center, Beijing Normal University, No. 19, Xinjiekouwai St, Haidian District, Beijing, 100875, P.R. China
| | - Feng Sang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19, Xinjiekouwai St, Haidian District, Beijing, 100875, P.R. China
- Beijing Aging Brain Rejuvenation Initiative (BABRI) Center, Beijing Normal University, No. 19, Xinjiekouwai St, Haidian District, Beijing, 100875, P.R. China
| | - Kewei Chen
- Beijing Aging Brain Rejuvenation Initiative (BABRI) Center, Beijing Normal University, No. 19, Xinjiekouwai St, Haidian District, Beijing, 100875, P.R. China
- Banner Alzheimer's Institute, Phoenix, AZ 85006, United States
| | - Zhanjun Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19, Xinjiekouwai St, Haidian District, Beijing, 100875, P.R. China
- Beijing Aging Brain Rejuvenation Initiative (BABRI) Center, Beijing Normal University, No. 19, Xinjiekouwai St, Haidian District, Beijing, 100875, P.R. China
| | - Xin Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19, Xinjiekouwai St, Haidian District, Beijing, 100875, P.R. China
- Beijing Aging Brain Rejuvenation Initiative (BABRI) Center, Beijing Normal University, No. 19, Xinjiekouwai St, Haidian District, Beijing, 100875, P.R. China
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Burnham SC, Iaccarino L, Pontecorvo MJ, Fleisher AS, Lu M, Collins EC, Devous MD. A review of the flortaucipir literature for positron emission tomography imaging of tau neurofibrillary tangles. Brain Commun 2023; 6:fcad305. [PMID: 38187878 PMCID: PMC10768888 DOI: 10.1093/braincomms/fcad305] [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: 05/04/2023] [Revised: 09/13/2023] [Accepted: 11/14/2023] [Indexed: 01/09/2024] Open
Abstract
Alzheimer's disease is defined by the presence of β-amyloid plaques and neurofibrillary tau tangles potentially preceding clinical symptoms by many years. Previously only detectable post-mortem, these pathological hallmarks are now identifiable using biomarkers, permitting an in vivo definitive diagnosis of Alzheimer's disease. 18F-flortaucipir (previously known as 18F-T807; 18F-AV-1451) was the first tau positron emission tomography tracer to be introduced and is the only Food and Drug Administration-approved tau positron emission tomography tracer (Tauvid™). It has been widely adopted and validated in a number of independent research and clinical settings. In this review, we present an overview of the published literature on flortaucipir for positron emission tomography imaging of neurofibrillary tau tangles. We considered all accessible peer-reviewed literature pertaining to flortaucipir through 30 April 2022. We found 474 relevant peer-reviewed publications, which were organized into the following categories based on their primary focus: typical Alzheimer's disease, mild cognitive impairment and pre-symptomatic populations; atypical Alzheimer's disease; non-Alzheimer's disease neurodegenerative conditions; head-to-head comparisons with other Tau positron emission tomography tracers; and technical considerations. The available flortaucipir literature provides substantial evidence for the use of this positron emission tomography tracer in assessing neurofibrillary tau tangles in Alzheimer's disease and limited support for its use in other neurodegenerative disorders. Visual interpretation and quantitation approaches, although heterogeneous, mostly converge and demonstrate the high diagnostic and prognostic value of flortaucipir in Alzheimer's disease.
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Affiliation(s)
| | | | | | | | - Ming Lu
- Avid, Eli Lilly and Company, Philadelphia, PA 19104, USA
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Christopher-Hayes NJ, Embury CM, Wiesman AI, May PE, Schantell M, Johnson CM, Wolfson SL, Murman DL, Wilson TW. Piecing it together: atrophy profiles of hippocampal subfields relate to cognitive impairment along the Alzheimer's disease spectrum. Front Aging Neurosci 2023; 15:1212197. [PMID: 38020776 PMCID: PMC10644116 DOI: 10.3389/fnagi.2023.1212197] [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: 04/25/2023] [Accepted: 10/13/2023] [Indexed: 12/01/2023] Open
Abstract
Introduction People with Alzheimer's disease (AD) experience more rapid declines in their ability to form hippocampal-dependent memories than cognitively normal healthy adults. Degeneration of the whole hippocampal formation has previously been found to covary with declines in learning and memory, but the associations between subfield-specific hippocampal neurodegeneration and cognitive impairments are not well characterized in AD. To improve prognostic procedures, it is critical to establish in which hippocampal subfields atrophy relates to domain-specific cognitive declines among people along the AD spectrum. In this study, we examine high-resolution structural magnetic resonance imaging (MRI) of the medial temporal lobe and extensive neuropsychological data from 29 amyloid-positive people on the AD spectrum and 17 demographically-matched amyloid-negative healthy controls. Methods Participants completed a battery of neuropsychological exams including select tests of immediate recollection, delayed recollection, and general cognitive status (i.e., performance on the Mini-Mental State Examination [MMSE] and Montreal Cognitive Assessment [MoCA]). Hippocampal subfield volumes (CA1, CA2, CA3, dentate gyrus, and subiculum) were measured using a dedicated MRI slab sequence targeting the medial temporal lobe and used to compute distance metrics to quantify AD spectrum-specific atrophic patterns and their impact on cognitive outcomes. Results Our results replicate prior studies showing that CA1, dentate gyrus, and subiculum hippocampal subfield volumes were significantly reduced in AD spectrum participants compared to amyloid-negative controls, whereas CA2 and CA3 did not exhibit such patterns of atrophy. Moreover, degeneration of the subiculum along the AD spectrum was linked to a significant decline in general cognitive status measured by the MMSE, while degeneration scores of the CA1 and dentate gyrus were more widely associated with declines on the MMSE and tests of learning and memory. Discussion These findings provide evidence that subfield-specific patterns of hippocampal degeneration, in combination with cognitive assessments, may constitute a sensitive prognostic approach and could be used to better track disease trajectories among individuals on the AD spectrum.
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Affiliation(s)
- Nicholas J. Christopher-Hayes
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, United States
- Center for Mind and Brain, University of California, Davis, CA, United States
| | - Christine M. Embury
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, United States
- Department of Psychology, University of Nebraska at Omaha, Omaha, NE, United States
| | - Alex I. Wiesman
- Montreal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Pamela E. May
- Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, NE, United States
| | - Mikki Schantell
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, United States
- College of Medicine, UNMC, Omaha, NE, United States
| | | | | | - Daniel L. Murman
- Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, NE, United States
- Memory Disorders and Behavioral Neurology Program, UNMC, Omaha, NE, United States
| | - Tony W. Wilson
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, United States
- College of Medicine, UNMC, Omaha, NE, United States
- Department of Pharmacology and Neuroscience, Creighton University, Omaha, NE, United States
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9
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Yu M, Risacher SL, Nho KT, Wen Q, Oblak AL, Unverzagt FW, Apostolova LG, Farlow MR, Brosch JR, Clark DG, Wang S, Deardorff R, Wu YC, Gao S, Sporns O, Saykin AJ. Spatial transcriptomic patterns underlying regional vulnerability to amyloid-β and tau pathologies and their relationships to cognitive dysfunction in Alzheimer's disease. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.08.12.23294017. [PMID: 37645867 PMCID: PMC10462206 DOI: 10.1101/2023.08.12.23294017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
Amyloid-β (Aβ) and tau proteins accumulate within distinct neuronal systems in Alzheimer's disease (AD). Although it is not clear why certain brain regions are more vulnerable to Aβ and tau pathologies than others, gene expression may play a role. We studied the association between brain-wide gene expression profiles and regional vulnerability to Aβ (gene-to-Aβ associations) and tau (gene-to-tau associations) pathologies leveraging two large independent cohorts (n = 715) of participants along the AD continuum. We identified several AD susceptibility genes and gene modules in a gene co-expression network with expression profiles related to regional vulnerability to Aβ and tau pathologies in AD. In particular, we found that the positive APOE -to-tau association was only seen in the AD cohort, whereas patients with AD and frontotemporal dementia shared similar positive MAPT -to-tau association. Some AD candidate genes showed sex-dependent negative gene-to-Aβ and gene-to-tau associations. In addition, we identified distinct biochemical pathways associated with the gene-to-Aβ and the gene-to-tau associations. Finally, we proposed a novel analytic framework, linking the identified gene-to-pathology associations to cognitive dysfunction in AD at the individual level, suggesting potential clinical implication of the gene-to-pathology associations. Taken together, our study identified distinct gene expression profiles and biochemical pathways that may explain the discordance between regional Aβ and tau pathologies, and filled the gap between gene-to-pathology associations and cognitive dysfunction in individual AD patients that may ultimately help identify novel personalized pathogenetic biomarkers and therapeutic targets. One Sentence Summary We identified replicable cognition-related associations between regional gene expression profiles and selectively regional vulnerability to amyloid-β and tau pathologies in AD.
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10
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Park CJ, Kim SY, Kim JH, Son NH, Park JY, Jeong YH, Kim HJ, Park J, Kim WJ. Evaluation of glymphatic system activity using diffusion tensor image analysis along the perivascular space and amyloid PET in older adults with objectively normal cognition: a preliminary study. Front Aging Neurosci 2023; 15:1221667. [PMID: 37577357 PMCID: PMC10413261 DOI: 10.3389/fnagi.2023.1221667] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 07/10/2023] [Indexed: 08/15/2023] Open
Abstract
Objectives Diffusion tensor image analysis along the perivascular space (DTI-ALPS) is a recently introduced method for the assessment of the glymphatic system without the need for contrast injection. The purpose of our study was to assess the glymphatic system in cognitively normal older adults with or without subjective cognitive decline (SCD) using DTI-ALPS, and correlating with amyloid PET. Design and participants To evaluate the glymphatic system in cognitively normal older adults using DTI-ALPS, we built a prospective cohort including a total of 123 objectively cognitively normal older adults with or without SCD. The ALPS index was calculated from DTI MRI and was assessed by correlating it with standardized uptake value ratios (SUVRs) from amyloid PET and clinically relevant variables. The study subjects were also divided into amyloid "positive" and "negative" groups based on the result of amyloid PET, and the ALPS indices between those two groups were compared. Results The ALPS index was not significantly different between the normal and SCD groups (P = 0.897). The mean ALPS index from the amyloid positive and amyloid negative group was 1.31 and 1.35, respectively, which showed no significant difference (P = 0.308). Among the SUVRs from variable cortices, that of the paracentral cortex was negatively correlated with the ALPS index (r = -0.218, P = 0.016). Multivariate linear regression revealed that older age (coefficient, -0.007) and higher SUVR from the paracentral cortex (coefficient, -0.101) were two independent variables with a significant association with a lower ALPS index (P = 0.015 and 0.045, respectively). Conclusion DTI-ALPS may not be useful for evaluation of the glymphatic system in subjects with SCD. Older age was significantly associated with lower ALPS index. Greater amyloid deposition in the paracentral cortex was significantly associated with lower glymphatic activity in cognitively normal older adults. These results should be validated in future studies on the relationships between ALPS index and other fundamental compartments in glymphatic system, such as perivenous space and the meningeal lymphatic vessels.
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Affiliation(s)
- Chae Jung Park
- Department of Radiology, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin-si, Gyeonggi-do, Republic of Korea
| | - Sang-Young Kim
- MR Clinical Science, Philips Healthcare Korea, Seoul, Republic of Korea
| | - Jun Hwee Kim
- Department of Radiology, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin-si, Gyeonggi-do, Republic of Korea
| | - Nak-Hoon Son
- Department of Statistics, Keimyung University, Daegu, Republic of Korea
| | - Jin Young Park
- Institute of Behavioral Science in Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
- Department of Psychiatry, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin-si, Gyeonggi-do, Republic of Korea
- Center for Digital Health, Yongin Severance Hospital, Yonsei University Health System, Yongin-si, Gyeonggi-do, Republic of Korea
| | - Yong Hyu Jeong
- Department of Nuclear Medicine, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin-si, Gyeonggi-do, Republic of Korea
| | - Hyun Jeong Kim
- Department of Nuclear Medicine, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin-si, Gyeonggi-do, Republic of Korea
| | - Jaesub Park
- Institute of Behavioral Science in Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
- Department of Psychiatry, National Health Insurance Service Ilsan Hospital, Goyang-si, Gyeonggi-do, Republic of Korea
| | - Woo Jung Kim
- Institute of Behavioral Science in Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
- Department of Psychiatry, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin-si, Gyeonggi-do, Republic of Korea
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11
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Mak E, Zhang L, Tan CH, Reilhac A, Shim HY, Wen MOQ, Wong ZX, Chong EJY, Xu X, Stephenson M, Venketasubramanian N, Zhou JH, O’Brien JT, Chen CLH. Longitudinal associations between β-amyloid and cortical thickness in mild cognitive impairment. Brain Commun 2023; 5:fcad192. [PMID: 37483530 PMCID: PMC10358322 DOI: 10.1093/braincomms/fcad192] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 05/25/2023] [Accepted: 07/03/2023] [Indexed: 07/25/2023] Open
Abstract
How beta-amyloid accumulation influences brain atrophy in Alzheimer's disease remains contentious with conflicting findings. We aimed to elucidate the correlations of regional longitudinal atrophy with cross-sectional regional and global amyloid in individuals with mild cognitive impairment and no cognitive impairment. We hypothesized that greater cortical thinning over time correlated with greater amyloid deposition, particularly within Alzheimer's disease characteristic regions in mild cognitive impairment, and weaker or no correlations in those with no cognitive impairment. 45 patients with mild cognitive impairment and 12 controls underwent a cross-sectional [11C]-Pittsburgh Compound B PET and two retrospective longitudinal structural imaging (follow-up: 23.65 ± 2.04 months) to assess global/regional amyloid and regional cortical thickness, respectively. Separate linear mixed models were constructed to evaluate relationships of either global or regional amyloid with regional cortical thinning longitudinally. In patients with mild cognitive impairment, regional amyloid in the right banks of the superior temporal sulcus was associated with longitudinal cortical thinning in the right medial orbitofrontal cortex (P = 0.04 after False Discovery Rate correction). In the mild cognitive impairment group, greater right banks amyloid burden and less cortical thickness in the right medial orbitofrontal cortex showed greater visual and verbal memory decline over time, which was not observed in controls. Global amyloid was not associated with longitudinal cortical thinning in any locations in either group. Our findings indicate an increasing influence of amyloid on neurodegeneration and memory along the preclinical to prodromal spectrum. Future multimodal studies that include additional biomarkers will be well-suited to delineate the interplay between various pathological processes and amyloid and memory decline, as well as clarify their additive or independent effects along the disease deterioration.
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Affiliation(s)
- Elijah Mak
- Correspondence to: Elijah Mak, PhD Department of Psychiatry, University of Cambridge Hills Road, Cambridge, Cambridgeshire, CB20QQ, United Kingdom E-mail:
| | | | - Chin Hong Tan
- Division of Psychology, Nanyang Technological University, Singapore, 637331, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore
| | - Anthonin Reilhac
- Clinical Imaging Research Centre, the Agency for Science, Technology and Research, and National University of Singapore, Singapore, 117599, Singapore
| | - Hee Youn Shim
- Memory Aging and Cognition Centre, Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore
| | - Marcus Ong Qin Wen
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore
| | - Zi Xuen Wong
- Memory Aging and Cognition Centre, Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore
- Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore
| | - Eddie Jun Yi Chong
- Memory Aging and Cognition Centre, Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore
- Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore
| | - Xin Xu
- Memory Aging and Cognition Centre, Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore
- School of Public Health, and the 2nd Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 311100, China
| | - Mary Stephenson
- Centre for Translational MR Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117549, Singapore
| | | | - Juan Helen Zhou
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore
- Centre for Translational MR Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117549, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 119077, Singapore
| | - John T O’Brien
- Department of Psychiatry, University of Cambridge, Cambridge, CB2 2QQ, United Kingdom
| | - Christopher Li-Hsian Chen
- Memory Aging and Cognition Centre, Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore
- Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore
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12
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Lee ES, Lee P, Kim MS, Chang SK, Jo SW, Lee SA, Kang SY. Cortical mean diffusivity is reliable in measuring brain abnormalities in drug-naïve essential tremor patients. Clin Neurol Neurosurg 2023; 230:107796. [PMID: 37236003 DOI: 10.1016/j.clineuro.2023.107796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 04/30/2023] [Accepted: 05/20/2023] [Indexed: 05/28/2023]
Abstract
OBJECTIVE Essential tremor (ET) is a common movement disorder, but the pathogenesis is poorly understood. Several associated brain areas were reported with inconsistent results due to heterogeneous populations. It is necessary to analyze a more homogeneous patient group. METHODS We recruited 25 drug-naïve ET patients and 36 age- and sex-matched controls. All participants were right-handed. ET. ET was defined according to diagnostic criteria of the Consensus Statement of the Movement Disorder Society on Tremor. ET patients were divided into sporadic (SET) and familial ET (FET). We assessed tremor severity in ET. The cortical microstructural changes were compared between ET patients and controls using mean diffusivity (MD) of diffusion tensor imaging, and cortical thickness. The correlation of tremor severity with the cortical MD and thickness were respectively analyzed. RESULTS MD values were increased in the insular, precuneus, medial orbitofrontal, posterior, and isthmus cingulate and temporo-occipital areas in ET. In comparison between SET and FET, MD values were higher in the superior and caudal middle frontal, postcentral, and temporo-occipital regions in FET. The cortical thickness of ET patients was more increased in the left lingual gyrus and lower in the right bankssts gyrus. We could not find any correlation of tremor severity with the MD values in ET patients. Still, there was a positive correlation with the cortical thickness of the frontal and parietal areas. CONCLUSIONS Our results support the idea that ET is a disorder that disrupts widespread brain regions and indicates that cortical MD may be more sensitive to measure brain abnormalities than cortical thickness.
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Affiliation(s)
- Eek-Sung Lee
- Department of Neurology, Soonchunhyang University Bucheon Hospital, Bucheon, the Republic of Korea
| | - Peter Lee
- KAIST Institute for Health Science and Technology, Korea Advanced Institute of Science and Technology, Daejeon, the Republic of Korea
| | - Min Seung Kim
- Department of Neurology, Dongtan Sacred Heart Hospital Hallym University College of Medicine, Hwaseong, the Republic of Korea
| | - Suk Ki Chang
- Department of Radiology, Hallym University Dongtan Sacred Heart Hospital, Hwaseong, the Republic of Korea
| | - Sang Won Jo
- Department of Radiology, Hallym University Dongtan Sacred Heart Hospital, Hwaseong, the Republic of Korea
| | - Seun Ah Lee
- Department of Radiology, Hallym University Dongtan Sacred Heart Hospital, Hwaseong, the Republic of Korea
| | - Suk Yun Kang
- Department of Neurology, Dongtan Sacred Heart Hospital Hallym University College of Medicine, Hwaseong, the Republic of Korea.
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13
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Sacchi L, Contarino VE, Siggillino S, Carandini T, Fumagalli GG, Pietroboni AM, Arcaro M, Fenoglio C, Orunesu E, Castellani M, Casale S, Conte G, Liu C, Triulzi F, Galimberti D, Scarpini E, Arighi A. Banks of the Superior Temporal Sulcus in Alzheimer's Disease: A Pilot Quantitative Susceptibility Mapping Study. J Alzheimers Dis 2023:JAD230095. [PMID: 37182885 DOI: 10.3233/jad-230095] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
BACKGROUND Brain iron homeostasis is disrupted in neurodegeneration and areas of iron overload partially overlap with regions of amyloid and tau burden in Alzheimer's disease (AD). Previous studies demonstrated alterations in brain iron accumulation in AD using quantitative susceptibility mapping (QSM). OBJECTIVE Here, we investigate brain alterations of QSM values in AD and non-AD patients as compared to healthy controls (HC) in the superior temporal sulcus and its banks (BANKSSTS), one of the top AD-affected regions. METHODS Thirty-four patients who underwent brain MRI including a multi-echo gradient-echo sequence were subdivided into AD (n = 19) and non-AD (n = 15) groups according to their clinical profile, CSF (Aβ 42/40) and/or amyloid-PET status. Ten HC were also included. QSM values were extracted from left and right BANKSSTS and compared among groups. Correlation and binomial regression analyses between QSM values and CSF-AD biomarkers were conducted. RESULTS QSM in left BANKSSTS was significantly different among groups (p = 0.003, H = 11.40), being higher in AD. QSM values in left BANKSSTS were correlated with Aβ 42 (rho -0.55, p = 0.005), Aβ 42/40 (rho -0.66, p < 0.001), pTau (rho 0.63, p < 0.001), tTau (rho 0.56, p = 0.005), tTau/Aβ 42 (rho 0.68, p < 0.001) and pTau/Aβ 42 (rho 0.71, p < 0.001). No correlations between QSM values and amyloid-PET SUVR in the left BANKSSTS were found. QSM values in left BANKSSTS showed good accuracy in discriminating AD (AUC = 0.80, CI95 % [0.66-0.93]). Higher QSM values were independent predictors of Aβ 42 (B = 0.63, p = 0.032), Aβ 42/40 (B = 0.81, p = 0.028), pTau (B = 0.96, p = 0.046), tTau (B = 0.55, p = 0.027), and tTau/Aβ 42 (B = 1.13, p = 0.042) positivity. CONCLUSION Our preliminary data support the potential role of increased QSM values in the left BANKSSTS as an auxiliary imaging biomarker in AD diagnosis.
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Affiliation(s)
- Luca Sacchi
- Department of Biomedical, Surgical and Dental Sciences, University of Milan, Milan, Italy
| | - Valeria Elisa Contarino
- Department of Neuroradiology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Silvia Siggillino
- Department of Neuroradiology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Tiziana Carandini
- Neurodegenerative Diseases Unit, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Milan, Italy
| | | | - Anna Margherita Pietroboni
- Neurodegenerative Diseases Unit, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Milan, Italy
| | - Marina Arcaro
- Neurodegenerative Diseases Unit, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Milan, Italy
| | - Chiara Fenoglio
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Eva Orunesu
- Nuclear Medicine Unit, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Milan, Italy
| | - Massimo Castellani
- Nuclear Medicine Unit, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Milan, Italy
| | - Silvia Casale
- Department of Neuroradiology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Giorgio Conte
- Department of Neuroradiology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Chunlei Liu
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
| | - Fabio Triulzi
- Department of Neuroradiology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Daniela Galimberti
- Department of Biomedical, Surgical and Dental Sciences, University of Milan, Milan, Italy
- Neurodegenerative Diseases Unit, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Milan, Italy
| | - Elio Scarpini
- Neurodegenerative Diseases Unit, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Milan, Italy
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Andrea Arighi
- Neurodegenerative Diseases Unit, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Milan, Italy
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Schmicker M, Frühling I, Menze I, Glanz W, Müller P, Noesselt T, Müller NG. The Potential Role of Gustatory Function as an Early Diagnostic Marker for the Risk of Alzheimer’s Disease in Subjective Cognitive Decline. J Alzheimers Dis Rep 2023; 7:249-262. [PMID: 37090958 PMCID: PMC10116167 DOI: 10.3233/adr220092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 02/23/2023] [Indexed: 04/07/2023] Open
Abstract
Background: Patients with subjective cognitive decline (SCD) report memory deterioration and are at an increased risk of converting to Alzheimer’s disease (AD) although psychophysical testing does not reveal any cognitive deficit. Objective: Here, gustatory function is investigated as a potential predictor for an increased risk of progressive cognitive decline indicating higher AD risk in SCD. Methods: Measures of smell and taste perception as well as neuropsychological data were assessed in patients with subjective cognitive decline (SCD): Subgroups with an increased likelihood of the progression to preclinical AD (SCD+) and those with a lower likelihood (SCD–) were compared to healthy controls (HC), patients with mild cognitive impairment and AD patients. The Sniffin’ Sticks test contained 12 items with different qualities and taste was measured with 32 taste stripes (sweet, salty, bitter, sour) of different concentration. Results: Only taste was able to distinguish between HC/SCD– and SCD+ patients. Conclusion: This study provides a first hint of taste as a more sensitive marker than smell for detecting preclinical AD in SCD. Longitudinal observation of cognition and pathology are necessary to further evaluate taste perception as a predictor of pathological objective decline in cognition.
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Affiliation(s)
- Marlen Schmicker
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
- Institute of Cognitive Neurology and Dementia Research, Otto von Guericke University, Magdeburg, Germany
| | - Insa Frühling
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
- Medical Faculty, Otto von Guericke University, Magdeburg, Germany
| | - Inga Menze
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
- Institute of Cognitive Neurology and Dementia Research, Otto von Guericke University, Magdeburg, Germany
| | - Wenzel Glanz
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Patrick Müller
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
- Medical Faculty, Otto von Guericke University, Magdeburg, Germany
- University Clinic for Cardiology and Angiology, Medical Faculty, Otto von Guericke University, Magdeburg, Germany
- Center for Intervention and Research on adaptive and maladaptive brain Circuits underlying mental health (C-I-R-C)
| | - Toemme Noesselt
- Biological Psychology, Faculty of Natural Science, Otto von Guericke University, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Otto von Guericke University, Magdeburg, Germany
| | - Notger G. Müller
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
- Medical Faculty, Otto von Guericke University, Magdeburg, Germany
- Research Group Degenerative and Chronic Diseases, Movement, Faculty of Health Sciences Brandenburg, University of Potsdam, Potsdam, Germany
- Center for Behavioral Brain Sciences, Otto von Guericke University, Magdeburg, Germany
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15
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Groechel RC, Tripodis Y, Alosco ML, Mez J, Qiu WQ, Mercier G, Goldstein L, Budson AE, Kowall N, Killiany RJ. Annualized changes in rate of amyloid deposition and neurodegeneration are greater in participants who become amyloid positive than those who remain amyloid negative. Neurobiol Aging 2023; 127:33-42. [PMID: 37043881 DOI: 10.1016/j.neurobiolaging.2023.03.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 03/01/2023] [Accepted: 03/06/2023] [Indexed: 03/12/2023]
Abstract
This study longitudinally examined participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) who underwent a conversion in amyloid-beta (Aβ) status in comparison to a group of ADNI participants who did not show a change in amyloid status over the same follow-up period. Participants included 136 ADNI dementia-free participants with 2 florbetapir positron emission tomography (PET) scans. Of these participants, 68 showed amyloid conversion as measured on florbetapir PET, and the other 68 did not. Amyloid converters and non-converters were chosen to have representative demographic data (age, education, sex, diagnostic status, and race). The amyloid converter group showed increased prevalence of APOE ε4 (p < 0.001), greater annualized percent volume loss in selected magnetic resonance imaging (MRI) regions (p < 0.05), lower cerebrospinal fluid Aβ1-42 (p < 0.001), and greater amyloid retention (as measured by standard uptake value ratios) on florbetapir PET scans (p < 0.001) in comparison to the non-converter group. These results provide compelling evidence that important neuropathological changes are occurring alongside amyloid conversion.
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Chatterjee P, Doré V, Pedrini S, Krishnadas N, Thota R, Bourgeat P, Ikonomovic MD, Rainey-Smith SR, Burnham SC, Fowler C, Taddei K, Mulligan R, Ames D, Masters CL, Fripp J, Rowe CC, Martins RN, Villemagne VL. Plasma Glial Fibrillary Acidic Protein Is Associated with 18F-SMBT-1 PET: Two Putative Astrocyte Reactivity Biomarkers for Alzheimer's Disease. J Alzheimers Dis 2023; 92:615-628. [PMID: 36776057 PMCID: PMC10041433 DOI: 10.3233/jad-220908] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
Abstract
BACKGROUND Astrocyte reactivity is an early event along the Alzheimer's disease (AD) continuum. Plasma glial fibrillary acidic protein (GFAP), posited to reflect astrocyte reactivity, is elevated across the AD continuum from preclinical to dementia stages. Monoamine oxidase-B (MAO-B) is also elevated in reactive astrocytes observed using 18F-SMBT-1 PET in AD. OBJECTIVE The objective of this study was to evaluate the association between the abovementioned astrocyte reactivity biomarkers. METHODS Plasma GFAP and Aβ were measured using the Simoa ® platform in participants who underwent brain 18F-SMBT-1 and Aβ-PET imaging, comprising 54 healthy control (13 Aβ-PET+ and 41 Aβ-PET-), 11 mild cognitively impaired (3 Aβ-PET+ and 8 Aβ-PET-) and 6 probable AD (5 Aβ-PET+ and 1 Aβ-PET-) individuals. Linear regressions were used to assess associations of interest. RESULTS Plasma GFAP was associated with 18F-SMBT-1 signal in brain regions prone to early Aβ deposition in AD, such as the supramarginal gyrus (SG), posterior cingulate (PC), lateral temporal (LT) and lateral occipital cortex (LO). After adjusting for age, sex, APOE ɛ4 genotype, and soluble Aβ (plasma Aβ 42/40 ratio), plasma GFAP was associated with 18F-SMBT-1 signal in the SG, PC, LT, LO, and superior parietal cortex (SP). On adjusting for age, sex, APOE ɛ4 genotype and insoluble Aβ (Aβ-PET), plasma GFAP was associated with 18F-SMBT-1 signal in the SG. CONCLUSION There is an association between plasma GFAP and regional 18F-SMBT-1 PET, and this association appears to be dependent on brain Aβ load.
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Affiliation(s)
- Pratishtha Chatterjee
- Macquarie Medical School, Macquarie University, North Ryde, New South Wales, Australia.,School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, Australia
| | - Vincent Doré
- The Australian eHealth Research Centre, CSIRO, Brisbane, Queensland, Australia.,Department of Molecular Imaging & Therapy, Austin Health, Heidelberg, Victoria, Australia
| | - Steve Pedrini
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, Australia.,Australian Alzheimer's Research Foundation, Sarich Neuroscience Research Institute, Nedlands, Western Australia, Australia
| | - Natasha Krishnadas
- Department of Molecular Imaging & Therapy, Austin Health, Heidelberg, Victoria, Australia.,The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Rohith Thota
- Macquarie Medical School, Macquarie University, North Ryde, New South Wales, Australia.,School of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, New South Wales, Australia
| | - Pierrick Bourgeat
- Health and Biosecurity Flagship, The Australian eHealth Research Centre, Queensland, Australia
| | - Milos D Ikonomovic
- Department of Neurology, University of Pittsburgh, Pennsylvania, PA, USA.,Geriatric Research Education and Clinical Center, VA Pittsburgh Healthcare System, Pittsburgh, Pennsylvania, PA, USA
| | - Stephanie R Rainey-Smith
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, Australia.,Centre for Healthy Ageing, Health Futures Institute, Murdoch University, Murdoch, Western Australia, Australia.,Australian Alzheimer's Research Foundation, Sarich Neuroscience Research Institute, Nedlands, Western Australia, Australia.,School of Psychological Science, University of Western Australia, Crawley, Western Australia, Australia
| | - Samantha C Burnham
- Health and Biosecurity Flagship, The Australian eHealth Research Centre, Queensland, Australia
| | - Christopher Fowler
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Kevin Taddei
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, Australia.,Australian Alzheimer's Research Foundation, Sarich Neuroscience Research Institute, Nedlands, Western Australia, Australia
| | - Rachel Mulligan
- Department of Molecular Imaging & Therapy, Austin Health, Heidelberg, Victoria, Australia
| | - David Ames
- National Ageing Research Institute, Parkville, Victoria, Australia.,Academic Unit for Psychiatry of Old Age, University of Melbourne, Melbourne, Victoria, Australia
| | - Colin L Masters
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Jürgen Fripp
- The Australian eHealth Research Centre, CSIRO, Brisbane, Queensland, Australia
| | - Christopher C Rowe
- Department of Molecular Imaging & Therapy, Austin Health, Heidelberg, Victoria, Australia.,The Florey Department of Neuroscience and Mental Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Ralph N Martins
- Macquarie Medical School, Macquarie University, North Ryde, New South Wales, Australia.,School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, Australia.,Australian Alzheimer's Research Foundation, Sarich Neuroscience Research Institute, Nedlands, Western Australia, Australia.,School of Psychiatry and Clinical Neurosciences, University of Western Australia, Crawley, Western Australia, Australia
| | - Victor L Villemagne
- Department of Molecular Imaging & Therapy, Austin Health, Heidelberg, Victoria, Australia.,Department of Psychiatry, University of Pittsburgh, Pennsylvania, PA, USA
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Cai Y, Du J, Li A, Zhu Y, Xu L, Sun K, Ma S, Guo T. Initial levels of β-amyloid and tau deposition have distinct effects on longitudinal tau accumulation in Alzheimer's disease. Alzheimers Res Ther 2023; 15:30. [PMID: 36750884 PMCID: PMC9903587 DOI: 10.1186/s13195-023-01178-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Accepted: 01/30/2023] [Indexed: 02/09/2023]
Abstract
BACKGROUND To better assist with the design of future clinical trials for Alzheimer's disease (AD) and aid in our understanding of the disease's symptomatology, it is essential to clarify what roles β-amyloid (Aβ) plaques and tau tangles play in longitudinal tau accumulation inside and outside the medial temporal lobe (MTL) as well as how age, sex, apolipoprotein E (APOE) ε4 (APOE-ε4), and Klotho-VS heterozygosity (KL-VShet) modulate these relationships. METHODS We divided the 325 Aβ PET-positive (A+) participants into two groups, A+/T- (N = 143) and A+/T+ (N = 182), based on the threshold (1.25) of the temporal meta-ROI 18F-flortaucipir (FTP) standardized uptake value ratio (SUVR). We then compared the baseline and slopes of A+/T- and A+/T+ individuals' Aβ plaques and temporal meta-ROI tau tangles with those of A-/T- cognitively unimpaired individuals (N = 162) without neurodegeneration. In addition, we looked into how baseline Aβ and tau may predict longitudinal tau increases and how age, sex, APOE-ε4, and KL-VShet affect these associations. RESULTS In entorhinal, amygdala, and parahippocampal (early tau-deposited regions of temporal meta-ROI), we found that baseline Aβ and tau deposition were positively linked to more rapid tau increases in A+/T- participants. However, in A+/T+ individuals, the longitudinal tau accumulation in fusiform, inferior temporal, and middle temporal cortices (late tau-deposited regions of temporal meta-ROI) was primarily predicted by the level of tau tangles. Furthermore, compared to older participants (age ≥ 65), younger individuals (age < 65) exhibited faster Aβ-dependent but slower tau-related tau accumulations. Additionally, compared to the KL-VShet- group, KL-VShet+ individuals showed a significantly lower rate of tau accumulation associated with baseline entorhinal tau in fusiform and inferior temporal regions. CONCLUSION These findings offer novel perspectives to the design of AD clinical trials and aid in understanding the tau accumulation inside and outside MTL in AD. In particular, decreasing Aβ plaques might be adequate for A+/T- persons but may not be sufficient for A+/T+ individuals in preventing tau propagation and subsequent downstream pathological changes associated with tau.
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Affiliation(s)
- Yue Cai
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
- Tsinghua Shenzhen International Graduate School (SIGS), Tsinghua University, Shenzhen, 518055, China
| | - Jing Du
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Anqi Li
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Yalin Zhu
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Linsen Xu
- Department of Medical Imaging, University of Chinese Academy of Sciences-Shenzhen Hospital, Shenzhen, 518106, China
| | - Kun Sun
- Institute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen, 518132, China
| | - Shaohua Ma
- Tsinghua Shenzhen International Graduate School (SIGS), Tsinghua University, Shenzhen, 518055, China
| | - Tengfei Guo
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China.
- Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, Shenzhen, 518055, China.
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18
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NiftyPAD - Novel Python Package for Quantitative Analysis of Dynamic PET Data. Neuroinformatics 2023; 21:457-468. [PMID: 36622500 PMCID: PMC10085912 DOI: 10.1007/s12021-022-09616-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/30/2022] [Indexed: 01/10/2023]
Abstract
Current PET datasets are becoming larger, thereby increasing the demand for fast and reproducible processing pipelines. This paper presents a freely available, open source, Python-based software package called NiftyPAD, for versatile analyses of static, full or dual-time window dynamic brain PET data. The key novelties of NiftyPAD are the analyses of dual-time window scans with reference input processing, pharmacokinetic modelling with shortened PET acquisitions through the incorporation of arterial spin labelling (ASL)-derived relative perfusion measures, as well as optional PET data-based motion correction. Results obtained with NiftyPAD were compared with the well-established software packages PPET and QModeling for a range of kinetic models. Clinical data from eight subjects scanned with four different amyloid tracers were used to validate the computational performance. NiftyPAD achieved [Formula: see text] correlation with PPET, with absolute difference [Formula: see text] for linearised Logan and MRTM2 methods, and [Formula: see text] correlation with QModeling, with absolute difference [Formula: see text] for basis function based SRTM and SRTM2 models. For the recently published SRTM ASL method, which is unavailable in existing software packages, high correlations with negligible bias were observed with the full scan SRTM in terms of non-displaceable binding potential ([Formula: see text]), indicating reliable model implementation in NiftyPAD. Together, these findings illustrate that NiftyPAD is versatile, flexible, and produces comparable results with established software packages for quantification of dynamic PET data. It is freely available ( https://github.com/AMYPAD/NiftyPAD ), and allows for multi-platform usage. The modular setup makes adding new functionalities easy, and the package is lightweight with minimal dependencies, making it easy to use and integrate into existing processing pipelines.
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19
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Daamen M, Scheef L, Li S, Grothe MJ, Gaertner FC, Buchert R, Buerger K, Dobisch L, Drzezga A, Essler M, Ewers M, Fliessbach K, Herrera Melendez AL, Hetzer S, Janowitz D, Kilimann I, Krause BJ, Lange C, Laske C, Munk MH, Peters O, Priller J, Ramirez A, Reimold M, Rominger A, Rostamzadeh A, Roeske S, Roy N, Scheffler K, Schneider A, Spottke A, Spruth EJ, Teipel SJ, Wagner M, Düzel E, Jessen F, Boecker H. Cortical Amyloid Burden Relates to Basal Forebrain Volume in Subjective Cognitive Decline. J Alzheimers Dis 2023; 95:1013-1028. [PMID: 37638433 DOI: 10.3233/jad-230141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/29/2023]
Abstract
BACKGROUND Atrophy of cholinergic basal forebrain (BF) nuclei is a frequent finding in magnetic resonance imaging (MRI) volumetry studies that examined patients with prodromal or clinical Alzheimer's disease (AD), but less clear for individuals in earlier stages of the clinical AD continuum. OBJECTIVE To examine BF volume reductions in subjective cognitive decline (SCD) participants with AD pathologic changes. METHODS The present study compared MRI-based BF volume measurements in age- and sex-matched samples of N = 24 amyloid-positive and N = 24 amyloid-negative SCD individuals, based on binary visual ratings of Florbetaben positron emission tomography (PET) measurements. Additionally, we assessed associations of BF volume with cortical amyloid burden, based on semiquantitative Centiloid (CL) analyses. RESULTS Group differences approached significance for BF total volume (p = 0.061) and the Ch4 subregion (p = 0.059) only, showing the expected relative volume reductions for the amyloid-positive subgroup. There were also significant inverse correlations between BF volumes and CL values, which again were most robust for BF total volume and the Ch4 subregion. CONCLUSIONS The results are consistent with the hypothesis that amyloid-positive SCD individuals, which are considered to represent a transitional stage on the clinical AD continuum, already show incipient alterations of BF integrity. The negative association with a continuous measure of cortical amyloid burden also suggests that this may reflect an incremental process. Yet, further research is needed to evaluate whether BF changes already emerge at "grey zone" levels of amyloid accumulation, before amyloidosis is reliably detected by PET visual readings.
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Affiliation(s)
- Marcel Daamen
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Lukas Scheef
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department for Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany
- RheinAhrCampus, University of Applied Sciences Koblenz, Remagen, Germany
| | - Shumei Li
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Michel J Grothe
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Seville, Spain
| | | | - Ralph Buchert
- Department of Nuclear Medicine, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Katharina Buerger
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
- Institute for Stroke and Dementia Research (ISD), University Hospital, Ludwig-Maximilian University Munich, Munich, Germany
| | - Laura Dobisch
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Alexander Drzezga
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Nuclear Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- Institute of Neuroscience and Medicine (INM-2), Molecular Organization of the Brain, Forschungszentrum Jülich, Jülich, Germany
| | - Markus Essler
- Department of Nuclear Medicine, University Hospital Bonn, Bonn, Germany
| | - Michael Ewers
- Institute for Clinical Radiology, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Klaus Fliessbach
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurodegenerative Disease and Geriatric Psychiatry, University Hospital Bonn, Bonn, Germany
| | - Ana Lucia Herrera Melendez
- Institute of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Stefan Hetzer
- Berlin Center of Advanced Neuroimaging, Charité -Universitätsmedizin Berlin, Berlin, Germany
| | - Daniel Janowitz
- Institute for Stroke and Dementia Research (ISD), University Hospital, Ludwig-Maximilian University Munich, Munich, Germany
| | - Ingo Kilimann
- German Center for Neurodegenerative Diseases (DZNE), Rostock/Greifswald, Germany
- Department of Psychosomatic Medicine, Rostock University Medical Center, Rostock, Germany
| | - Bernd Joachim Krause
- Department of Nuclear Medicine, Rostock University Medical Centre, Rostock, Germany
| | - Catharina Lange
- Department of Nuclear Medicine, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Christoph Laske
- German Center for Neurodegenerative Diseases (DZNE), Tuebingen, Germany
- Section for Dementia Research, Hertie Institute for Clinical Brain Research and Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Matthias H Munk
- German Center for Neurodegenerative Diseases (DZNE), Tuebingen, Germany
- Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Oliver Peters
- Institute of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
| | - Josef Priller
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
- Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Psychiatry and Psychotherapy, School of Medicine, Technical University of Munich, Munich, Germany
- University of Edinburgh and UK Dementia Research Institute, Edinburgh, UK
| | - Alfredo Ramirez
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurodegenerative Disease and Geriatric Psychiatry, University Hospital Bonn, Bonn, Germany
- Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
- Department of Psychiatry and Psychotherapy, Division of Neurogenetics and Molecular Psychiatry, Faculty of Medicine and University Hospital Cologne, University of Cologne, Medical Faculty, Cologne, Germany
- Department of Psychiatry & Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, San Antonio, TX, USA
| | - Matthias Reimold
- Department of Nuclear Medicine and Clinical Molecular Imaging, Eberhard-Karls-University, Tübingen, Germany
| | - Axel Rominger
- Department of Nuclear Medicine, Ludwig-Maximilian-University Munich, Munich, Germany
- Department of Nuclear Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Ayda Rostamzadeh
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Sandra Roeske
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Nina Roy
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Klaus Scheffler
- Department for Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany
| | - Anja Schneider
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurodegenerative Disease and Geriatric Psychiatry, University Hospital Bonn, Bonn, Germany
| | - Annika Spottke
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurology, University Hospital Bonn, Bonn, Germany
| | - Eike Jakob Spruth
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
- Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Stefan J Teipel
- German Center for Neurodegenerative Diseases (DZNE), Rostock/Greifswald, Germany
- Department of Psychosomatic Medicine, Rostock University Medical Center, Rostock, Germany
| | - Michael Wagner
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurodegenerative Disease and Geriatric Psychiatry, University Hospital Bonn, Bonn, Germany
| | - Emrah Düzel
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
- Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University, Magdeburg, Germany
| | - Frank Jessen
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Henning Boecker
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department for Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany
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20
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Li A, Du J, Cai Y, Chen X, Sun K, Guo T. Body Mass Index Decrease Has a Distinct Association with Alzheimer's Disease Pathophysiology in APOE ɛ4 Carriers and Non-Carriers. J Alzheimers Dis 2023; 96:643-655. [PMID: 37840490 DOI: 10.3233/jad-230446] [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: 10/17/2023]
Abstract
BACKGROUND Body mass index (BMI) changes may be related to Alzheimer's disease (AD) alterations, but it is unclear how the apolipoprotein E ɛ4 (APOE ɛ4) allele affects their association. OBJECTIVE To explore the association of BMI changes with AD pathologies in APOE ɛ4 carriers and non-carriers. METHODS In 862 non-demented ADNI participants with≥2 BMI measurements, we investigated the relationships between BMI slopes and longitudinal changes in amyloid-β (Aβ) accumulation, neurodegeneration and cognition, and follow-up tau deposition in different Aβ and APOE ɛ4 statuses. RESULTS In Aβ+ APOE ɛ4 non-carriers, faster BMI declines were associated with faster rates of Aβ accumulation (standardized β (βstd) = -0.29, p = 0.001), AD meta regions of interest (metaROI) hypometabolism (βstd = 0.23, p = 0.026), memory declines (βstd = 0.17, p = 0.029), executive function declines (βstd = 0.19, p = 0.011), and marginally faster Temporal-metaROI cortical thinning (βstd = 0.15, p = 0.067) and higher follow-up Temporal-metaROI tau deposition (βstd = -0.17, p = 0.059). Among Aβ- individuals, faster BMI decreases were related to faster Aβ accumulation (βstd = -0.25, p = 0.023) in APOE ɛ4 carriers, whereas predicted faster declines in memory and executive function in both APOE ɛ4 carriers (βstd = 0.25, p = 0.008; βstd = 0.32, p = 0.001) and APOE ɛ4 non-carriers (βstd = 0.11, p = 0.030; βstd = 0.12, p = 0.026). CONCLUSIONS This study highlights the significance of tracking BMI data in older adults by providing novel insights into how body weight fluctuations and APOE ɛ4 interact with AD pathology and cognitive decline.
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Affiliation(s)
- Anqi Li
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen, China
| | - Jing Du
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen, China
| | - Yue Cai
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen, China
| | - Xuhui Chen
- Department of Neurology, Peking University Shenzhen Hospital, Shenzhen, China
| | - Kun Sun
- Institute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen, China
| | - Tengfei Guo
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen, China
- Institute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen, China
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21
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Demirbilek O, Rekik I. Predicting the evolution trajectory of population-driven connectional brain templates using recurrent multigraph neural networks. Med Image Anal 2023; 83:102649. [PMID: 36257134 DOI: 10.1016/j.media.2022.102649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 09/28/2022] [Accepted: 09/30/2022] [Indexed: 11/05/2022]
Abstract
The mapping of the time-dependent evolution of the human brain connectivity using longitudinal and multimodal neuroimaging datasets provides insights into the development of neurological disorders and the way they alter the brain morphology, structure and function over time. Recently, the connectional brain template (CBT) was introduced as a compact representation integrating a population of brain multigraphs, where two brain regions can have multiple connections, into a single graph. Given a population of brain multigraphs observed at a baseline timepoint t1, we aim to learn how to predict the evolution of the population CBT at follow-up timepoints t>t1. Such model will allow us to foresee the evolution of the connectivity patterns of healthy and disordered individuals at the population level. Here we present recurrent multigraph integrator network (ReMI-Net⋆) to forecast population templates at consecutive timepoints from a given single timepoint. In particular, we unprecedentedly design a graph neural network architecture to model the changes in the brain multigraph and identify the biomarkers that differentiate between the typical and atypical populations. Addressing such issues is of paramount importance in diagnosing neurodegenerative disorders at early stages and promoting new clinical studies based on the pinned-down biomarker brain regions or connectivities. In this paper, we demonstrate the design and use of the ReMI-Net⋆ model, which learns both the multigraph node level and time level dependencies concurrently. Thanks to its novel graph convolutional design and normalization layers, ReMI-Net⋆ predicts well-centered, discriminative, and topologically sound connectional templates over time. Additionally, the results show that our model outperforms all benchmarks and state-of-the-art methods by comparing and discovering the atypical connectivity alterations over time. Our ReMI-Net⋆ code is available on GitHub at https://github.com/basiralab/ReMI-Net-Star.
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Affiliation(s)
- Oytun Demirbilek
- BASIRA lab, Faculty of Computer and Informatics, Istanbul Technical University, Istanbul, Turkey
| | - Islem Rekik
- BASIRA lab, Faculty of Computer and Informatics, Istanbul Technical University, Istanbul, Turkey; School of Science and Engineering, Computing, University of Dundee, UK.
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22
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Jiang J, Sheng C, Chen G, Liu C, Jin S, Li L, Jiang X, Han Y. Glucose metabolism patterns: A potential index to characterize brain ageing and predict high conversion risk into cognitive impairment. GeroScience 2022; 44:2319-2336. [PMID: 35581512 PMCID: PMC9616982 DOI: 10.1007/s11357-022-00588-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Accepted: 05/07/2022] [Indexed: 12/28/2022] Open
Abstract
Exploring individual hallmarks of brain ageing is important. Here, we propose the age-related glucose metabolism pattern (ARGMP) as a potential index to characterize brain ageing in cognitively normal (CN) elderly people. We collected 18F-fluorodeoxyglucose (18F-FDG) PET brain images from two independent cohorts: the Alzheimer's Disease Neuroimaging Initiative (ADNI, N = 127) and the Xuanwu Hospital of Capital Medical University, Beijing, China (N = 84). During follow-up (mean 80.60 months), 23 participants in the ADNI cohort converted to cognitive impairment. ARGMPs were identified using the scaled subprofile model/principal component analysis method, and cross-validations were conducted in both independent cohorts. A survival analysis was further conducted to calculate the predictive effect of conversion risk by using ARGMPs. The results showed that ARGMPs were characterized by hypometabolism with increasing age primarily in the bilateral medial superior frontal gyrus, anterior cingulate and paracingulate gyri, caudate nucleus, and left supplementary motor area and hypermetabolism in part of the left inferior cerebellum. The expression network scores of ARGMPs were significantly associated with chronological age (R = 0.808, p < 0.001), which was validated in both the ADNI and Xuanwu cohorts. Individuals with higher network scores exhibited a better predictive effect (HR: 0.30, 95% CI: 0.1340 ~ 0.6904, p = 0.0068). These findings indicate that ARGMPs derived from CN participants may represent a novel index for characterizing brain ageing and predicting high conversion risk into cognitive impairment.
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Affiliation(s)
- Jiehui Jiang
- Institute of Biomedical Engineering, School of Information and Communication Engineering, Shanghai University, Shanghai, 200444, China.
| | - Can Sheng
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China
| | - Guanqun Chen
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China
| | - Chunhua Liu
- Institute of Biomedical Engineering, School of Information and Communication Engineering, Shanghai University, Shanghai, 200444, China
| | - Shichen Jin
- Institute of Biomedical Engineering, School of Information and Communication Engineering, Shanghai University, Shanghai, 200444, China
| | - Lanlan Li
- Institute of Biomedical Engineering, School of Information and Communication Engineering, Shanghai University, Shanghai, 200444, China
| | - Xueyan Jiang
- School of Biomedical Engineering, Hainan University, Haikou, 570228, China
- German Centre for Neurodegenerative Disease, Clinical Research Group, Venusberg Campus 1, 53121, Bonn, Germany
| | - Ying Han
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China.
- School of Biomedical Engineering, Hainan University, Haikou, 570228, China.
- Centre of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, 100053, China.
- National Clinical Research Centre for Geriatric Disorders, Beijing, 100053, China.
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23
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Heeman F, Yaqub M, Hendriks J, van Berckel BNM, Collij LE, Gray KR, Manber R, Wolz R, Garibotto V, Wimberley C, Ritchie C, Barkhof F, Gispert JD, Vállez García D, Lopes Alves I, Lammertsma AA. Impact of cerebral blood flow and amyloid load on SUVR bias. EJNMMI Res 2022; 12:29. [PMID: 35553267 PMCID: PMC9098761 DOI: 10.1186/s13550-022-00898-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Accepted: 04/25/2022] [Indexed: 11/17/2022] Open
Abstract
Background Despite its widespread use, the semi-quantitative standardized uptake value ratio (SUVR) may be biased compared with the distribution volume ratio (DVR). This bias may be partially explained by changes in cerebral blood flow (CBF) and is likely to be also dependent on the extent of the underlying amyloid-β (Aβ) burden. This study aimed to compare SUVR with DVR and to evaluate the effects of underlying Aβ burden and CBF on bias in SUVR in mainly cognitively unimpaired participants. Participants were scanned according to a dual-time window protocol, with either [18F]flutemetamol (N = 90) or [18F]florbetaben (N = 31). The validated basisfunction-based implementation of the two-step simplified reference tissue model was used to derive DVR and R1 parametric images, and SUVR was calculated from 90 to 110 min post-injection, all with the cerebellar grey matter as reference tissue. First, linear regression and Bland–Altman analyses were used to compare (regional) SUVR with DVR. Then, generalized linear models were applied to evaluate whether (bias in) SUVR relative to DVR could be explained by R1 for the global cortical average (GCA), precuneus, posterior cingulate, and orbitofrontal region. Results Despite high correlations (GCA: R2 ≥ 0.85), large overestimation and proportional bias of SUVR relative to DVR was observed. Negative associations were observed between both SUVR or SUVRbias and R1, albeit non-significant. Conclusion The present findings demonstrate that bias in SUVR relative to DVR is strongly related to underlying Aβ burden. Furthermore, in a cohort consisting mainly of cognitively unimpaired individuals, the effect of relative CBF on bias in SUVR appears limited. EudraCT Number: 2018-002277-22, registered on: 25-06-2018. Supplementary Information The online version contains supplementary material available at 10.1186/s13550-022-00898-8.
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Affiliation(s)
- Fiona Heeman
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands.
| | - Maqsood Yaqub
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Janine Hendriks
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Bart N M van Berckel
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Lyduine E Collij
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | | | | | | | - Valentina Garibotto
- NIMTLab, Faculty of Medicine, Geneva University, Geneva, Switzerland.,Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals, Geneva, Switzerland
| | - Catriona Wimberley
- Edinburgh Imaging, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Craig Ritchie
- Edinburgh Imaging, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Frederik Barkhof
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands.,UCL, Institutes of Neurology and Healthcare Engineering, London, UK
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Centre, Pasqual Maragall Foundation, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain.,Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - David Vállez García
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Isadora Lopes Alves
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Adriaan A Lammertsma
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
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24
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Veitch DP, Weiner MW, Aisen PS, Beckett LA, DeCarli C, Green RC, Harvey D, Jack CR, Jagust W, Landau SM, Morris JC, Okonkwo O, Perrin RJ, Petersen RC, Rivera‐Mindt M, Saykin AJ, Shaw LM, Toga AW, Tosun D, Trojanowski JQ. Using the Alzheimer's Disease Neuroimaging Initiative to improve early detection, diagnosis, and treatment of Alzheimer's disease. Alzheimers Dement 2022; 18:824-857. [PMID: 34581485 PMCID: PMC9158456 DOI: 10.1002/alz.12422] [Citation(s) in RCA: 47] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Revised: 06/08/2021] [Accepted: 06/09/2021] [Indexed: 02/06/2023]
Abstract
INTRODUCTION The Alzheimer's Disease Neuroimaging Initiative (ADNI) has accumulated 15 years of clinical, neuroimaging, cognitive, biofluid biomarker and genetic data, and biofluid samples available to researchers, resulting in more than 3500 publications. This review covers studies from 2018 to 2020. METHODS We identified 1442 publications using ADNI data by conventional search methods and selected impactful studies for inclusion. RESULTS Disease progression studies supported pivotal roles for regional amyloid beta (Aβ) and tau deposition, and identified underlying genetic contributions to Alzheimer's disease (AD). Vascular disease, immune response, inflammation, resilience, and sex modulated disease course. Biologically coherent subgroups were identified at all clinical stages. Practical algorithms and methodological changes improved determination of Aβ status. Plasma Aβ, phosphorylated tau181, and neurofilament light were promising noninvasive biomarkers. Prognostic and diagnostic models were externally validated in ADNI but studies are limited by lack of ethnocultural cohort diversity. DISCUSSION ADNI has had a profound impact in improving clinical trials for AD.
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Affiliation(s)
- Dallas P. Veitch
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA,Department of Veterans Affairs Medical CenterNorthern California Institute for Research and Education (NCIRE)San FranciscoCaliforniaUSA
| | - Michael W. Weiner
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA,Department of RadiologyUniversity of California, San FranciscoSan FranciscoCaliforniaUSA,Department of MedicineUniversity of California, San FranciscoSan FranciscoCaliforniaUSA,Department of PsychiatryUniversity of California, San FranciscoSan FranciscoCaliforniaUSA,Department of NeurologyUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
| | - Paul S. Aisen
- Alzheimer's Therapeutic Research InstituteUniversity of Southern CaliforniaSan DiegoCaliforniaUSA
| | - Laurel A. Beckett
- Division of Biostatistics, Department of Public Health SciencesUniversity of California DavisDavisCaliforniaUSA
| | - Charles DeCarli
- Department of Neurology and Center for NeuroscienceUniversity of California DavisDavisCaliforniaUSA
| | - Robert C. Green
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Broad Institute, Ariadne Labsand Harvard Medical SchoolBostonMassachusettsUSA
| | - Danielle Harvey
- Division of Biostatistics, Department of Public Health SciencesUniversity of California DavisDavisCaliforniaUSA
| | | | - William Jagust
- Helen Wills Neuroscience InstituteUniversity of California BerkeleyBerkeleyCaliforniaUSA
| | - Susan M. Landau
- Helen Wills Neuroscience InstituteUniversity of California BerkeleyBerkeleyCaliforniaUSA
| | - John C. Morris
- Knight Alzheimer's Disease Research CenterWashington University School of MedicineSaint LouisMissouriUSA
| | - Ozioma Okonkwo
- Wisconsin Alzheimer's Disease Research Center and Department of MedicineUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Richard J. Perrin
- Knight Alzheimer's Disease Research CenterWashington University School of MedicineSaint LouisMissouriUSA,Department of NeurologyWashington University School of MedicineSaint LouisMissouriUSA,Department of Pathology and ImmunologyWashington University School of MedicineSaint LouisMissouriUSA
| | | | | | - Andrew J. Saykin
- Department of Radiology and Imaging Sciences and Indiana Alzheimer's Disease Research CenterIndiana University School of MedicineIndianapolisIndianaUSA,Department of Medical and Molecular GeneticsIndiana University School of MedicineIndianapolisIndianaUSA
| | - Leslie M. Shaw
- Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Research, School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Arthur W. Toga
- Laboratory of Neuroimaging, USC Stevens Institute of Neuroimaging and Informatics, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Duygu Tosun
- Department of RadiologyUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
| | - John Q. Trojanowski
- Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Research, School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
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25
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APOE-ε4 modulates the association among plasma Aβ 42/Aβ 40, vascular diseases, neurodegeneration and cognitive decline in non-demented elderly adults. Transl Psychiatry 2022; 12:128. [PMID: 35351867 PMCID: PMC8964707 DOI: 10.1038/s41398-022-01899-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 03/03/2022] [Accepted: 03/11/2022] [Indexed: 01/18/2023] Open
Abstract
Including apolipoprotein E-ε4 (APOE-ε4) status and older age into consideration may increase the accuracy of plasma Aβ42/Aβ40 detecting Aβ+ individuals, but the rationale behind this remains to be fully understood. Besides, both Aβ pathology and vascular diseases are related to neurodegeneration and cognitive decline, but it is still not fully understood how APOE-ε4 modulates these relationships. In this study, we examined 241 non-demented Alzheimer's Disease Neuroimaging Initiative participants to investigate the associations among age, white matter hyperintensities (WMH), hypertension, hyperlipidemia, body mass index (BMI), plasma Aβ42/Aβ40 measured by liquid chromatography tandem mass spectrometry, and 18F-florbetapir Aβ PET as well as their prediction of longitudinal adjusted hippocampal volume (aHCV) and cognition in APOE-ε4 carriers and non-carriers. We found older age predicted faster WMH increase (p = 0.024) and cortical Aβ accumulation (p = 0.043) in APOE-ε4 non-carriers only, whereas lower plasma Aβ42/Aβ40 predicted faster cortical Aβ accumulation (p < 0.018) regardless of APOE-ε4 status. While larger WMH and underweight predicted (p < 0.05) faster decreases in aHCV and cognition in APOE-ε4 non-carriers, lower plasma Aβ42/Aβ40 predicted (p < 0.031) faster decreases in aHCV and cognition in APOE-ε4 carriers. Higher Aβ PET also predicted faster rates of aHCV (p = 0.010) in APOE-ε4 carriers only, but was related to faster rates of cognitive decline (p < 0.022) regardless of APOE-ε4 status. These findings may provide novel insights into understanding different mechanisms underlie neurodegeneration and cognitive decline in non-demented elderly adults with and without APOE-ε4 allele, which may help the design of anti-Alzheimer's clinical trials.
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26
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Genome-wide association study identifies APOE locus influencing plasma p-tau181 levels. J Hum Genet 2022; 67:459-463. [DOI: 10.1038/s10038-022-01026-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 02/10/2022] [Accepted: 02/15/2022] [Indexed: 11/09/2022]
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27
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Jiang C, Wang Q, Xie S, Chen Z, Fu L, Peng Q, Liang Y, Guo H, Guo T. OUP accepted manuscript. Brain Commun 2022; 4:fcac084. [PMID: 35441134 PMCID: PMC9014538 DOI: 10.1093/braincomms/fcac084] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 12/21/2021] [Accepted: 03/29/2022] [Indexed: 11/14/2022] Open
Affiliation(s)
- Chenyang Jiang
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen 518132, China
| | - Qingyong Wang
- Department of Neurology, University of Chinese Academy of Sciences-Shenzhen Hospital, Shenzhen 518107, China
| | - Siwei Xie
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen 518132, China
| | - Zhicheng Chen
- Institute of Chemical Biology, Shenzhen Bay Laboratory, Shenzhen 518132, China
| | - Liping Fu
- Department of Nuclear Medicine, China-Japan Friendship Hospital, 2 Yinghuayuan Dongjie, Beijing 100029, China
| | - Qiyu Peng
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen 518132, China
| | - Ying Liang
- Department of Nuclear Medicine, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen 518116, China
| | - Hongbo Guo
- Department of Neurosurgery, Zhujiang Hospital, Southern Medical University, Guangzhou 510282, China
| | - Tengfei Guo
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen 518132, China
- Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, Shenzhen 518055, China
- Correspondence to: Tengfei Guo, PhD Institute of Biomedical Engineering Shenzhen Bay Laboratory, No.5 Kelian Road Shenzhen 518132, China E-mail:
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28
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Weihs A, Frenzel S, Garvert L, Kühn L, Wittfeld K, Ewert R, Fietze I, Penzel T, Stubbe B, Szentkirályi A, Wulms N, Völzke H, Grabe HJ. The relationship between Alzheimer's‐related brain atrophy patterns and sleep macro‐architecture. ALZHEIMER'S & DEMENTIA: DIAGNOSIS, ASSESSMENT & DISEASE MONITORING 2022; 14:e12371. [PMID: 36381559 PMCID: PMC9652484 DOI: 10.1002/dad2.12371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 10/05/2022] [Accepted: 10/06/2022] [Indexed: 11/15/2022]
Abstract
Introduction Sleep is increasingly recognized as a major risk factor for neurodegenerative disorders such as Alzheimer's disease (AD). Methods Using an magnetic resonance imaging (MRI)-based AD score based on clinical data from the Alzheimer's Disease Neuroimaging Initiative 1 (ADNI1) case-control cohort, we investigated the associations between polysomnography-based sleep macro-architecture and AD-related brain atrophy patterns in 712 pre-symptomatic, healthy subjects from the population-based Study of Health in Pomerania. Results We identified a robust inverse association between slow-wave sleep and the AD marker (estimate: -0.019; 95% confidence interval: -0.03 to -0.0076; false discovery rate [FDR] = 0.0041), as well as with gray matter (GM) thicknesses in typical individual cortical AD-signature regions. No effects were identified regarding rapid eye movement or non-rapid eye movement (NREM) stage 2 sleep, and NREM stage 1 was positively associated with GM thickness, mainly in the prefrontal cortical regions. Discussion There is a cross-sectional relationship between AD-related neurodegenerative patterns and the proportion of sleep spent in slow-wave sleep.
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Affiliation(s)
- Antoine Weihs
- Department of Psychiatry and Psychotherapy University Medicine Greifswald Greifswald Mecklenburg‐Vorpommern Germany
| | - Stefan Frenzel
- Department of Psychiatry and Psychotherapy University Medicine Greifswald Greifswald Mecklenburg‐Vorpommern Germany
| | - Linda Garvert
- Department of Psychiatry and Psychotherapy University Medicine Greifswald Greifswald Mecklenburg‐Vorpommern Germany
| | - Luise Kühn
- Department of Psychiatry and Psychotherapy University Medicine Greifswald Greifswald Mecklenburg‐Vorpommern Germany
| | - Katharina Wittfeld
- Department of Psychiatry and Psychotherapy University Medicine Greifswald Greifswald Mecklenburg‐Vorpommern Germany
- German Centre for Neurodegenerative Diseases (DZNE) Site Rostock/Greifswald Greifswald Mecklenburg‐Vorpommern Germany
| | - Ralf Ewert
- Department of Internal Medicine B–Cardiology Pneumology, Infectious Diseases Intensive Care Medicine University Medicine Greifswald Greifswald Mecklenburg‐Vorpommern Germany
| | - Ingo Fietze
- Interdisciplinary Centre of Sleep Medicine CC 12 University Hospital Charité Berlin Berlin Germany
- The Fourth People's hospital of Guangyuan Guangyuan City Sichuan China
| | - Thomas Penzel
- Interdisciplinary Centre of Sleep Medicine CC 12 University Hospital Charité Berlin Berlin Germany
| | - Beate Stubbe
- Department of Internal Medicine B–Cardiology Pneumology, Infectious Diseases Intensive Care Medicine University Medicine Greifswald Greifswald Mecklenburg‐Vorpommern Germany
| | - András Szentkirályi
- Institute of Epidemiology and Social Medicine University of Muenster Muenster Nordrhein‐Westfalen Germany
| | - Niklas Wulms
- Institute of Epidemiology and Social Medicine University of Muenster Muenster Nordrhein‐Westfalen Germany
| | - Henry Völzke
- Institute for Community Medicine Department SHIP/Clinical Epidemiological Research University Medicine Greifswald Greifswald Mecklenburg‐Vorpommern Germany
- German Centre for Cardiovascular Research (DZHK) Partner Site Greifswald Greifswald Mecklenburg‐Vorpommern Germany
| | - Hans J. Grabe
- Department of Psychiatry and Psychotherapy University Medicine Greifswald Greifswald Mecklenburg‐Vorpommern Germany
- German Centre for Neurodegenerative Diseases (DZNE) Site Rostock/Greifswald Greifswald Mecklenburg‐Vorpommern Germany
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29
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Hazan J, Alston D, Fox NC, Howard R. Practical application of Alzheimer's Disease Neuroimaging Initiative plasma P-tau181 reference data to support diagnosis of Alzheimer's disease. Int J Geriatr Psychiatry 2021; 37. [PMID: 34997780 DOI: 10.1002/gps.5670] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 12/18/2021] [Indexed: 11/10/2022]
Abstract
OBJECTIVES To assess plasma phosphorylated tau181 (p-tau181) levels in Alzheimer's disease (AD), cognitively impaired non-AD participants (CI non-AD) and Control participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset that could potentially act as reference data for clinic diagnoses of AD. METHODS Data from 1558 participants (649 AD participants, 445 CI non-AD participants and 464 controls) were examined, comparing p-tau181 levels between Controls, AD and other dementias, stratified by age. RESULTS There were significant differences in plasma p-tau181 values between Controls and those with AD at all ages up to 85 years. There were also significant differences between AD and CI non-AD participants up to the age of 85 years. CONCLUSIONS Plasma P-tau181 may be a useful tool in the diagnosis of AD in those clinical settings where biomarkers have traditionally been less used. P-tau181 may be less useful as an aid to diagnosis in the very oldest-old. Further work is needed to establish the feasibility and utility of this biomarker within dementia diagnosis services not led by Neurologists, such as UK National Health Service Memory Services.
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Affiliation(s)
- Jemma Hazan
- Division of Psychiatry, University College London, London, UK
| | - Duncan Alston
- Institute of Neurology, University College London, London, UK
| | - Nick C Fox
- Institute of Neurology, University College London, London, UK
| | - Robert Howard
- Division of Psychiatry, University College London, London, UK
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30
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Zhang L, Shen Q, Liao H, Li J, Wang T, Zi Y, Zhou F, Song C, Mao Z, Wang M, Cai S, Tan C. Aberrant Changes in Cortical Complexity in Right-Onset Versus Left-Onset Parkinson's Disease in Early-Stage. Front Aging Neurosci 2021; 13:749606. [PMID: 34819848 PMCID: PMC8606890 DOI: 10.3389/fnagi.2021.749606] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 10/05/2021] [Indexed: 11/17/2022] Open
Abstract
There is increasing evidence to show that motor symptom lateralization in Parkinson’s disease (PD) is linked to non-motor features, progression, and prognosis of the disease. However, few studies have reported the difference in cortical complexity between patients with left-onset of PD (LPD) and right-onset of PD (RPD). This study aimed to investigate the differences in the cortical complexity between early-stage LPD and RPD. High-resolution T1-weighted magnetic resonance images of the brain were acquired in 24 patients with LPD, 34 patients with RPD, and 37 age- and sex-matched healthy controls (HCs). Cortical complexity including gyrification index, fractal dimension (FD), and sulcal depth was analyzed using surface-based morphometry via CAT12/SPM12. Familywise error (FWE) peak-level correction at p < 0.05 was performed for significance testing. In patients with RPD, we found decreased mean FD and mean sulcal depth in the banks of the left superior temporal sulcus (STS) compared with LPD and HCs. The mean FD in the left superior temporal gyrus (STG) was decreased in RPD compared with HCs. However, in patients with LPD, we did not identify significantly abnormal cortical complex change compared with HCs. Moreover, we observed that the mean FD in STG was negatively correlated with the 17-item Hamilton Depression Scale (HAMD) among the three groups. Our findings support the specific influence of asymmetrical motor symptoms in cortical complexity in early-stage PD and reveal that the banks of left STS and left STG might play a crucial role in RPD.
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Affiliation(s)
- Lin Zhang
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Qin Shen
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Haiyan Liao
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Junli Li
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Tianyu Wang
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China.,Department of Radiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yuheng Zi
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Fan Zhou
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Chendie Song
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Zhenni Mao
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Min Wang
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Sainan Cai
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Changlian Tan
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
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31
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Guo T, Landau SM, Jagust WJ. Age, vascular disease, and Alzheimer's disease pathologies in amyloid negative elderly adults. ALZHEIMERS RESEARCH & THERAPY 2021; 13:174. [PMID: 34654465 PMCID: PMC8520216 DOI: 10.1186/s13195-021-00913-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Accepted: 10/03/2021] [Indexed: 02/04/2023]
Abstract
Background We recently reported that CSF phosphorylated tau (p-Tau181) relative to Aβ40 (CSF p-Tau/Aβ40 ratio) was less noisy and increased associations with Alzheimer’s disease (AD) biomarkers compared to CSF p-Tau181 alone. While elevations of CSF p-Tau/Aβ40 can occur in amyloid-β (Aβ) negative (Aβ-) individuals, the factors associated with these elevations and their role in neurodegeneration and cognitive decline are unknown. We aim to explore factors associated with elevated tau in CSF, and how these elevated tau are related to neurodegeneration and cognitive decline in the absence of Aβ positivity. Methods We examined relationships between CSF p-Tau/Aβ40, and CSF Aβ42/Aβ40, Aβ PET, and white matter hyperintensities (WMH) as well as vascular risk factors in 149 cognitively unimpaired and 52 impaired individuals who were presumably not on the Alzheimer’s disease (AD) pathway due to negative Aβ status on both CSF and PET. Subgroups had 18F-fluorodeoxyglucose (FDG) PET and adjusted hippocampal volume (aHCV), and longitudinal measures of CSF, aHCV, FDG PET, and cognition data, so we examined CSF p-Tau/Aβ40 associations with these measures as well. Results Elevated CSF p-Tau/Aβ40 was associated with older age, male sex, greater WMH, and hypertension as well as a pattern of hippocampal atrophy and temporoparietal hypometabolism characteristic of AD. Lower CSF Aβ42/Aβ40, higher WMH, and hypertension but not age, sex, Aβ PET, APOE-ε4 status, body mass index, smoking, and hyperlipidemia at baseline predicted CSF p-Tau/Aβ40 increases over approximately 5 years of follow-up. The relationship between CSF p-Tau/Aβ40 and subsequent cognitive decline was partially or fully explained by neurodegenerative measurements. Conclusions These data provide surprising clues as to the etiology and significance of tau pathology in the absence of Aβ. It seems likely that, in addition to age, both cerebrovascular disease and subthreshold levels of Aβ are related to this tau accumulation. Crucially, this phenotype of CSF tau elevation in amyloid-negative individuals share features with AD such as a pattern of metabolic decline and regional brain atrophy. Supplementary Information The online version contains supplementary material available at 10.1186/s13195-021-00913-5.
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Affiliation(s)
- Tengfei Guo
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China.
| | - Susan M Landau
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, 94720, USA.,Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, 94720, USA.,Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
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Staging tau pathology with tau PET in Alzheimer's disease: a longitudinal study. Transl Psychiatry 2021; 11:483. [PMID: 34537810 PMCID: PMC8449785 DOI: 10.1038/s41398-021-01602-5] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/10/2021] [Revised: 07/31/2021] [Accepted: 09/02/2021] [Indexed: 01/02/2023] Open
Abstract
A biological research framework to define Alzheimer' disease with dichotomized biomarker measurement was proposed by National Institute on Aging-Alzheimer's Association (NIA-AA). However, it cannot characterize the hierarchy spreading pattern of tau pathology. To reflect in vivo tau progression using biomarker, we constructed a refined topographic 18F-AV-1451 tau PET staging scheme with longitudinal clinical validation. Seven hundred and thirty-four participants with baseline 18F-AV-1451 tau PET (baseline age 73.9 ± 7.7 years, 375 female) were stratified into five stages by a topographic PET staging scheme. Cognitive trajectories and clinical progression were compared across stages with or without further dichotomy of amyloid status, using linear mixed-effect models and Cox proportional hazard models. Significant cognitive decline was first observed in stage 1 when tau levels only increased in transentorhinal regions. Rates of cognitive decline and clinical progression accelerated from stage 2 to stage 3 and stage 4. Higher stages were also associated with greater CSF phosphorylated tau and total tau concentrations from stage 1. Abnormal tau accumulation did not appear with normal β-amyloid in neocortical regions but prompt cognitive decline by interacting with β-amyloid in temporal regions. Highly accumulated tau in temporal regions independently led to cognitive deterioration. Topographic PET staging scheme have potentials in early diagnosis, predicting disease progression, and studying disease mechanism. Characteristic tau spreading pattern in Alzheimer's disease could be illustrated with biomarker measurement under NIA-AA framework. Clinical-neuroimaging-neuropathological studies in other cohorts are needed to validate these findings.
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Dartora CM, Borelli WV, Koole M, Marques da Silva AM. Cognitive Decline Assessment: A Review From Medical Imaging Perspective. Front Aging Neurosci 2021; 13:704661. [PMID: 34489675 PMCID: PMC8416532 DOI: 10.3389/fnagi.2021.704661] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Accepted: 07/19/2021] [Indexed: 11/13/2022] Open
Abstract
Aging is a complex process that involves changes at both molecular and morphological levels. However, our understanding of how aging affects brain anatomy and function is still poor. In addition, numerous biomarkers and imaging markers, usually associated with neurodegenerative diseases such as Alzheimer's disease (AD), have been clinically used to study cognitive decline. However, the path of cognitive decline from healthy aging to a mild cognitive impairment (MCI) stage has been studied only marginally. This review presents aspects of cognitive decline assessment based on the imaging differences between individuals cognitively unimpaired and in the decline spectrum. Furthermore, we discuss the relationship between imaging markers and the change in their patterns with aging by using neuropsychological tests. Our goal is to delineate how aging has been studied by using medical imaging tools and further explore the aging brain and cognitive decline. We find no consensus among the biomarkers to assess the cognitive decline and its relationship with the cognitive decline trajectory. Brain glucose hypometabolism was found to be directly related to aging and indirectly to cognitive decline. We still need to understand how to quantify an expected hypometabolism during cognitive decline during aging. The Aβ burden should be longitudinally studied to achieve a better consensus on its association with changes in the brain and cognition decline with aging. There exists a lack of standardization of imaging markers that highlight the need for their further improvement. In conclusion, we argue that there is a lot to investigate and understand cognitive decline better and seek a window for a suitable and effective treatment strategy.
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Affiliation(s)
- Caroline Machado Dartora
- School of Medicine, Pontifical Catholic University of Rio Grande do Sul, PUCRS, Porto Alegre, Brazil
| | - Wyllians Vendramini Borelli
- Neurology Department, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil.,Brain Institute of Rio Grande do Sul, BraIns, Porto Alegre, Brazil
| | - Michel Koole
- Nuclear Medicine and Molecular Imaging, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
| | - Ana Maria Marques da Silva
- School of Medicine, Pontifical Catholic University of Rio Grande do Sul, PUCRS, Porto Alegre, Brazil.,Brain Institute of Rio Grande do Sul, BraIns, Porto Alegre, Brazil.,Medical Image Computing Laboratory, School of Technology, Pontifical Catholic University of Rio Grande do Sul, PUCRS, Porto Alegre, Brazil
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Mallon DH, Malhotra P, Naik M, Edison P, Perry R, Carswell C, Win Z. The role of amyloid PET in patient selection for extra-ventricular shunt insertion for the treatment of idiopathic normal pressure hydrocephalus: A pooled analysis. J Clin Neurosci 2021; 90:325-331. [PMID: 34275571 DOI: 10.1016/j.jocn.2021.06.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Accepted: 06/14/2021] [Indexed: 11/30/2022]
Abstract
BACKGROUND Idiopathic Normal Pressure Hydrocephalus (iNPH) can be effectively treated through shunt insertion. However, most shunted patients experience little or no clinical benefit, which suggests suboptimal patient selection. While contentious, multiple studies have reported poorer shunt outcomes associated with concomitant Alzheimer's disease. Prompted by this observation, multiple studies have assessed the role of amyloid PET, a specific test for Alzheimer's disease, in patient selection for shunting. METHODS A comprehensive literature search was performed to identify studies that assessed the association between amyloid PET result and the clinical response to shunting in patients with suspected iNPH. Pooled diagnostic statistics were calculated. RESULTS Across three relevant studies, a total of 38 patients with suspected iNPH underwent amyloid PET imaging and shunt insertion. Twenty-three patients had a positive clinical response to shunting. 18/28 (64.3%) of patients with a negative amyloid PET and 5/10 (50%) with a positive amyloid PET had a positive response to shunting. The pooled sensitivity, specificity and accuracy was 33.3%, 76.2% and 58.3%. None of these statistics reached statistical significance. CONCLUSION The results of this pooled analysis do not support the selection of patients with suspected iNPH for shunting on the basis of amyloid PET alone. However, due to small cohort sizes and weakness in study design, further high-quality studies are required to properly determine the role of amyloid PET in assessing this complex patient group.
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Affiliation(s)
- Dermot H Mallon
- Imperial College Healthcare NHS Trust, Charing Cross Hospital, London, UK; Imperial College London, Charing Cross Hospital, London, UK.
| | - Paresh Malhotra
- Imperial College Healthcare NHS Trust, Charing Cross Hospital, London, UK
| | - Mitesh Naik
- Imperial College Healthcare NHS Trust, Charing Cross Hospital, London, UK
| | - Paul Edison
- Imperial College Healthcare NHS Trust, Charing Cross Hospital, London, UK; Imperial College London, Charing Cross Hospital, London, UK
| | - Richard Perry
- Imperial College Healthcare NHS Trust, Charing Cross Hospital, London, UK
| | - Christopher Carswell
- Imperial College Healthcare NHS Trust, Charing Cross Hospital, London, UK; Imperial College London, Charing Cross Hospital, London, UK
| | - Zarni Win
- Imperial College Healthcare NHS Trust, Charing Cross Hospital, London, UK
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Pfeil J, Hoenig MC, Doering E, van Eimeren T, Drzezga A, Bischof GN. Unique regional patterns of amyloid burden predict progression to prodromal and clinical stages of Alzheimer's disease. Neurobiol Aging 2021; 106:119-129. [PMID: 34284259 PMCID: PMC8461082 DOI: 10.1016/j.neurobiolaging.2021.06.014] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 05/22/2021] [Accepted: 06/15/2021] [Indexed: 01/21/2023]
Abstract
Although beta-amyloid (Aβ) positivity has shown to be associated with higher risk of progression to Alzheimer's disease (AD) in mild cognitive impairment (MCI), information on the time to conversion to manifest dementia cannot be readily deduced from this binary classification. Here, we assessed if regional patterns of Aβ deposition measured with 18F-florbetapir may serve as biomarker for progression risk in Aβ-positive cognitively normal (CN) and MCI patients, including clinical follow-up data and cerebrospinal fluid (CSF) biomarkers. Voxel-wise group comparisons between age and sex-matched Aβ-positive groups (i.e., CN-stables [n = 38] vs. CN-to-MCI/AD progressors [n = 38], MCI-stables [n = 104] versus MCI-to-AD progressors [n = 104]) revealed higher Aβ burden in precuneus, subcortical, and parietal regions in CN-to-MCI/AD progressors and cingulate, temporal, and frontal regions in MCI-to-AD progressors. Importantly, these regional patterns predicted progression to advanced stages on the AD spectrum in the short and the long-term beyond global Aβ burden and CSF biomarkers. These results suggest that distinct regional patterns of Aβ burden are a valuable biomarker for risk of disease progression in CN and MCI.
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Affiliation(s)
- Julia Pfeil
- Department of Nuclear Medicine, Multimodal Neuroimaging Group, University of Cologne, University Hospital of Cologne, Cologne, Germany.
| | - Merle C Hoenig
- Department of Nuclear Medicine, Multimodal Neuroimaging Group, University of Cologne, University Hospital of Cologne, Cologne, Germany; Research Center Juelich, Institute for Neuroscience and Medicine II, Molecular Organization of the Brain, Juelich, Germany
| | - Elena Doering
- Department of Nuclear Medicine, Multimodal Neuroimaging Group, University of Cologne, University Hospital of Cologne, Cologne, Germany; German Center for Neurodegenerative Diseases, Bonn/Cologne, Germany
| | - Thilo van Eimeren
- Department of Nuclear Medicine, Multimodal Neuroimaging Group, University of Cologne, University Hospital of Cologne, Cologne, Germany; German Center for Neurodegenerative Diseases, Bonn/Cologne, Germany; University of Cologne, University Hospital of Cologne, Department of Neurology, Cologne, Germany
| | - Alexander Drzezga
- Department of Nuclear Medicine, Multimodal Neuroimaging Group, University of Cologne, University Hospital of Cologne, Cologne, Germany; Research Center Juelich, Institute for Neuroscience and Medicine II, Molecular Organization of the Brain, Juelich, Germany; German Center for Neurodegenerative Diseases, Bonn/Cologne, Germany
| | - Gérard N Bischof
- Department of Nuclear Medicine, Multimodal Neuroimaging Group, University of Cologne, University Hospital of Cologne, Cologne, Germany
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36
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Longitudinal plasma phosphorylated tau 181 tracks disease progression in Alzheimer's disease. Transl Psychiatry 2021; 11:356. [PMID: 34120152 PMCID: PMC8197760 DOI: 10.1038/s41398-021-01476-7] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Revised: 05/19/2021] [Accepted: 05/27/2021] [Indexed: 11/08/2022] Open
Abstract
To assess plasma phosphorylated tau181 (p-tau181) as a progression biomarker in Alzheimer's disease (AD), we examined longitudinal plasma p-tau181 of 1184 participants (403 cognitively normal (CN), 560 patients with mild cognitive impairment (MCI), and 221 with AD dementia) from Alzheimer's Disease Neuroimaging Initiative (ADNI). The plasma p-tau level was increased at baseline for MCI and AD dementia (mean: CN, 15.4 pg/mL; MCI, 18.4 pg/mL; AD dementia, 23.7 pg/mL; P < 0.001) and increased significantly over time at preclinical (Aβ-positive CN), prodromal (Aβ-positive MCI), and dementia (Aβ-positive dementia) stage of AD. A longitudinal increase of plasma p-tau181 was associated with abnormal cerebrospinal fluid biomarker levels (low Aβ42, high phosphorylated tau, and high total tau, all P < 0.001), amyloid accumulation (P < 0.001) and hypometabolism (P = 0.002) on positron emission tomography, atrophy in structure imaging (small hippocampal (P = 0.030), middle temporal (P = 0.008), and whole brain (P = 0.027) volume, and large ventricular volume (P = 0.008)), and deteriorated cognitive performance (global cognition and memory, language, executive function, and visuospatial function, all P < 0.050) at baseline. Furthermore, longitudinal plasma p-tau181 correlated with concurrent changes of nearly all these AD-related hallmarks and faster increase in plasma p-tau181 correlated with faster worsening cognition in all diagnostic groups. Importantly, most associations remained significant in Aβ-positive group and became non-significant in Aβ-negative group. Longitudinal analyses of plasma p-tau181 suggest its potential as a noninvasive biomarker to track disease progression in AD and to monitor effects of disease-modifying therapeutics in clinical trials.
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Bao W, Xie F, Zuo C, Guan Y, Huang YH. PET Neuroimaging of Alzheimer's Disease: Radiotracers and Their Utility in Clinical Research. Front Aging Neurosci 2021; 13:624330. [PMID: 34025386 PMCID: PMC8134674 DOI: 10.3389/fnagi.2021.624330] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2020] [Accepted: 02/23/2021] [Indexed: 12/14/2022] Open
Abstract
Alzheimer's Disease (AD), the leading cause of senile dementia, is a progressive neurodegenerative disorder affecting millions of people worldwide and exerting tremendous socioeconomic burden on all societies. Although definitive diagnosis of AD is often made in the presence of clinical manifestations in late stages, it is now universally believed that AD is a continuum of disease commencing from the preclinical stage with typical neuropathological alterations appearing decades prior to its first symptom, to the prodromal stage with slight symptoms of amnesia (amnestic mild cognitive impairment, aMCI), and then to the terminal stage with extensive loss of basic cognitive functions, i.e., AD-dementia. Positron emission tomography (PET) radiotracers have been developed in a search to meet the increasing clinical need of early detection and treatment monitoring for AD, with reference to the pathophysiological targets in Alzheimer's brain. These include the pathological aggregations of misfolded proteins such as β-amyloid (Aβ) plagues and neurofibrillary tangles (NFTs), impaired neurotransmitter system, neuroinflammation, as well as deficient synaptic vesicles and glucose utilization. In this article we survey the various PET radiotracers available for AD imaging and discuss their clinical applications especially in terms of early detection and cognitive relevance.
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Affiliation(s)
- Weiqi Bao
- PET Center, Huanshan Hospital, Fudan University, Shanghai, China
| | - Fang Xie
- PET Center, Huanshan Hospital, Fudan University, Shanghai, China
| | - Chuantao Zuo
- PET Center, Huanshan Hospital, Fudan University, Shanghai, China
| | - Yihui Guan
- PET Center, Huanshan Hospital, Fudan University, Shanghai, China
| | - Yiyun Henry Huang
- Department of Radiology and Biomedical Imaging, PET Center, Yale University School of Medicine, New Haven, CT, United States
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38
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Guo T, Korman D, Baker SL, Landau SM, Jagust WJ. Longitudinal Cognitive and Biomarker Measurements Support a Unidirectional Pathway in Alzheimer's Disease Pathophysiology. Biol Psychiatry 2021; 89:786-794. [PMID: 32919611 PMCID: PMC9682985 DOI: 10.1016/j.biopsych.2020.06.029] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Revised: 06/29/2020] [Accepted: 06/29/2020] [Indexed: 11/19/2022]
Abstract
BACKGROUND Amyloid-β (Aβ) likely plays a primary role in Alzheimer's disease pathogenesis, but longitudinal Aβ, tau, and neurodegeneration (A/T/N) measurements in the same individuals have rarely been examined to verify the temporal dynamics of these biomarkers. METHODS In this study, we investigated the temporal ordering of Aβ, tau, and neurodegeneration using longitudinal biomarkers in nondemented elderly individuals. A total of 395 cognitively unimpaired individuals and 204 individuals with mild cognitive impairment (320 [53%] were female) were classified into 8 A±/T±/N± categories according to the abnormal (+)/normal (-) status of Aβ (18F-florbetapir or 18F-florbetaben) positron emission tomography (PET), 18F-flortaucipir PET, and adjusted hippocampal volume (aHCV). Follow-up Aβ PET, tau PET, and aHCV measurements at 0.6 to 4.1 years were available for 35% to 63% of the sample. Baseline Aβ, tau, and aHCV were compared between different A/T/N profiles. We investigated the associations of baseline and longitudinal Aβ, tau, and neurodegeneration in relation to one another continuously. RESULTS Among T- participants, tau was higher for A+/T-/N- individuals compared with the A-/T-/N- group (p = .02). Among N- participants, neurodegeneration was worse among A+/T+/N- individuals compared with the A-/T-/N- group (p = .001). High baseline Aβ was associated (p < .001) with subsequent tau increase and high baseline tau was associated (p = .002) with subsequent aHCV decrease, whereas high tau and low aHCV at baseline were not associated with subsequent Aβ increase. CONCLUSIONS These findings define a sequence of pathological events in Alzheimer's disease that support a current model of Alzheimer's disease pathogenesis in which Aβ appears early, followed by deposition of abnormal tau aggregates and subsequent neurodegeneration.
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Affiliation(s)
- Tengfei Guo
- Helen Wills Neuroscience Institute, University of California, Berkeley, California; Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, California.
| | - Deniz Korman
- Helen Wills Neuroscience Institute, University of California, Berkeley, California
| | - Suzanne L Baker
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, California
| | - Susan M Landau
- Helen Wills Neuroscience Institute, University of California, Berkeley, California; Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, California
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California, Berkeley, California; Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, California
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39
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Bullich S, Roé-Vellvé N, Marquié M, Landau SM, Barthel H, Villemagne VL, Sanabria Á, Tartari JP, Sotolongo-Grau O, Doré V, Koglin N, Müller A, Perrotin A, Jovalekic A, De Santi S, Tárraga L, Stephens AW, Rowe CC, Sabri O, Seibyl JP, Boada M. Early detection of amyloid load using 18F-florbetaben PET. ALZHEIMERS RESEARCH & THERAPY 2021; 13:67. [PMID: 33773598 PMCID: PMC8005243 DOI: 10.1186/s13195-021-00807-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 03/10/2021] [Indexed: 03/26/2023]
Abstract
BACKGROUND A low amount and extent of Aβ deposition at early stages of Alzheimer's disease (AD) may limit the use of previously developed pathology-proven composite SUVR cutoffs. This study aims to characterize the population with earliest abnormal Aβ accumulation using 18F-florbetaben PET. Quantitative thresholds for the early (SUVRearly) and established (SUVRestab) Aβ deposition were developed, and the topography of early Aβ deposition was assessed. Subsequently, Aβ accumulation over time, progression from mild cognitive impairment (MCI) to AD dementia, and tau deposition were assessed in subjects with early and established Aβ deposition. METHODS The study population consisted of 686 subjects (n = 287 (cognitively normal healthy controls), n = 166 (subjects with subjective cognitive decline (SCD)), n = 129 (subjects with MCI), and n = 101 (subjects with AD dementia)). Three categories in the Aβ-deposition continuum were defined based on the developed SUVR cutoffs: Aβ-negative subjects, subjects with early Aβ deposition ("gray zone"), and subjects with established Aβ pathology. RESULTS SUVR using the whole cerebellum as the reference region and centiloid (CL) cutoffs for early and established amyloid pathology were 1.10 (13.5 CL) and 1.24 (35.7 CL), respectively. Cingulate cortices and precuneus, frontal, and inferior lateral temporal cortices were the regions showing the initial pathological tracer retention. Subjects in the "gray zone" or with established Aβ pathology accumulated more amyloid over time than Aβ-negative subjects. After a 4-year clinical follow-up, none of the Aβ-negative or the gray zone subjects progressed to AD dementia while 91% of the MCI subjects with established Aβ pathology progressed. Tau deposition was infrequent in those subjects without established Aβ pathology. CONCLUSIONS This study supports the utility of using two cutoffs for amyloid PET abnormality defining a "gray zone": a lower cutoff of 13.5 CL indicating emerging Aβ pathology and a higher cutoff of 35.7 CL where amyloid burden levels correspond to established neuropathology findings. These cutoffs define a subset of subjects characterized by pre-AD dementia levels of amyloid burden that precede other biomarkers such as tau deposition or clinical symptoms and accelerated amyloid accumulation. The determination of different amyloid loads, particularly low amyloid levels, is useful in determining who will eventually progress to dementia. Quantitation of amyloid provides a sensitive measure in these low-load cases and may help to identify a group of subjects most likely to benefit from intervention. TRIAL REGISTRATION Data used in this manuscript belong to clinical trials registered in ClinicalTrials.gov ( NCT00928304 , NCT00750282 , NCT01138111 , NCT02854033 ) and EudraCT (2014-000798-38).
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Affiliation(s)
- Santiago Bullich
- Life Molecular Imaging GmbH, Tegeler Str. 6-7, 13353, Berlin, Germany.
| | - Núria Roé-Vellvé
- Life Molecular Imaging GmbH, Tegeler Str. 6-7, 13353, Berlin, Germany
| | - Marta Marquié
- Fundació ACE Institut Català de Neurociències Aplicades, Research Center and Memory Unit - Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Susan M Landau
- Helen Wills Neuroscience Institute, University of California, Berkeley and Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Henryk Barthel
- Department of Nuclear Medicine, University Hospital Leipzig, Leipzig, Germany
| | - Victor L Villemagne
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.,Departments of Medicine and Molecular Imaging, University of Melbourne, Austin Health, Melbourne, Victoria, Australia
| | - Ángela Sanabria
- Fundació ACE Institut Català de Neurociències Aplicades, Research Center and Memory Unit - Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Juan Pablo Tartari
- Fundació ACE Institut Català de Neurociències Aplicades, Research Center and Memory Unit - Universitat Internacional de Catalunya (UIC), Barcelona, Spain
| | - Oscar Sotolongo-Grau
- Fundació ACE Institut Català de Neurociències Aplicades, Research Center and Memory Unit - Universitat Internacional de Catalunya (UIC), Barcelona, Spain
| | - Vincent Doré
- Departments of Medicine and Molecular Imaging, University of Melbourne, Austin Health, Melbourne, Victoria, Australia.,The Australian e-Health Research Centre, Health and Biosecurity, CSIRO, Melbourne, Victoria, Australia
| | - Norman Koglin
- Life Molecular Imaging GmbH, Tegeler Str. 6-7, 13353, Berlin, Germany
| | - Andre Müller
- Life Molecular Imaging GmbH, Tegeler Str. 6-7, 13353, Berlin, Germany
| | - Audrey Perrotin
- Life Molecular Imaging GmbH, Tegeler Str. 6-7, 13353, Berlin, Germany
| | | | | | - Lluís Tárraga
- Fundació ACE Institut Català de Neurociències Aplicades, Research Center and Memory Unit - Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Andrew W Stephens
- Life Molecular Imaging GmbH, Tegeler Str. 6-7, 13353, Berlin, Germany
| | - Christopher C Rowe
- Departments of Medicine and Molecular Imaging, University of Melbourne, Austin Health, Melbourne, Victoria, Australia
| | - Osama Sabri
- Department of Nuclear Medicine, University Hospital Leipzig, Leipzig, Germany
| | | | - Mercè Boada
- Fundació ACE Institut Català de Neurociències Aplicades, Research Center and Memory Unit - Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
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Abstract
Amyloid-β (Aβ) PET imaging has now been available for over 15 years. The ability to detect Aβ in vivo has greatly improved the clinical and research landscape of Alzheimer's disease (AD) and other neurodegenerative conditions. Aβ imaging provides very reliable, accurate, and reproducible measurements of regional and global Aβ burden in the brain. It has proved invaluable in anti-Aβ therapy trials, and is now recognized as a powerful diagnostic tool. The appropriate use of Aβ PET, when combined with comprehensive clinical evaluation by a dementia-trained specialist, can improve the accuracy of a clinical diagnosis of AD and substantially alter management. It can assist in differentiating AD from other neurodegenerative conditions, often by its ability to rule out the presence of Aβ. When combined with tau imaging, further increase in specificity for the diagnosis of AD can be achieved. The integration of Aβ PET, in conjunction with biomarkers of tau, neurodegeneration and neuroinflammation, into large, longitudinal, observational cohort studies continues to increase our understanding of the development of AD. Its incorporation into clinical trials has been pivotal in defining the most effective anti-Aβ biological therapies and optimal dosing so that effective disease modifying therapy now appears imminent. Aβ deposition is a gradual and protracted process, permitting a wide treatment window for anti-Aβ therapies and Aβ PET has made trials in this preclinical AD period feasible. Continuing improvement in Aβ tracer target to background ratio is allowing trials in earlier AD that tailor drug dosage to Aβ level. The quest to standardize quantification and define universally applicable thresholds for all Aβ tracers has produced the Centiloid method. Centiloid values that correlate well with neuropathologic findings and prognosis have been identified. Rapid cloud-based automated individual scan analysis is now possible and does not require MRI. Challenges remain, particularly around cross camera standardized uptake value ratio variation that need to be addressed. This review will compare available Aβ radiotracers, discuss approaches to quantification, as well as the clinical and research applications of Aβ PET.
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Affiliation(s)
- Natasha Krishnadas
- Florey Department of Neurosciences and Mental Health, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Victoria, Australia; Department of Molecular Imaging & Therapy, Austin Health, Victoria, Australia
| | - Victor L Villemagne
- Department of Molecular Imaging & Therapy, Austin Health, Victoria, Australia
| | - Vincent Doré
- Department of Molecular Imaging & Therapy, Austin Health, Victoria, Australia; Health and Biosecurity Flagship, The Australian eHealth Research Centre, CSIRO, Victoria, Australia
| | - Christopher C Rowe
- Department of Molecular Imaging & Therapy, Austin Health, Victoria, Australia; The Australian Dementia Network (ADNeT), Melbourne, Australia; The University of Melbourne, Victoria, Australia.
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Villemagne VL, Lopresti BJ, Doré V, Tudorascu D, Ikonomovic MD, Burnham S, Minhas D, Pascoal TA, Mason NS, Snitz B, Aizenstein H, Mathis CA, Lopez O, Rowe CC, Klunk WE, Cohen AD. What Is T+? A Gordian Knot of Tracers, Thresholds, and Topographies. J Nucl Med 2020; 62:614-619. [PMID: 33384320 DOI: 10.2967/jnumed.120.245423] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Accepted: 12/16/2020] [Indexed: 11/16/2022] Open
Abstract
In this review we examine, in the context of the amyloid, tau, and neurodegeneration framework, the available evidence and potential alternatives on how to establish tau positivity (T+) for multiple tau-imaging tracers in order to reach a consensus on normal and abnormal tau imaging values that can be universally implemented in clinical research and therapeutic trials.
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Affiliation(s)
- Victor L Villemagne
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania .,Department of Medicine, University of Melbourne, Melbourne, Victoria, Australia.,School of Medical and Health Sciences, Edith Cowan University, Perth, Washington, Australia
| | - Brian J Lopresti
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Vincent Doré
- Department of Molecular Imaging and Therapy, Austin Health, Melbourne, Victoria, Australia.,CSIRO Health and Biosecurity, Melbourne, Victoria, Australia
| | - Dana Tudorascu
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Milos D Ikonomovic
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.,Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania; and
| | - Samantha Burnham
- CSIRO Health and Biosecurity, Melbourne, Victoria, Australia.,Center for Alzheimer Research and Treatment, Brigham and Women's Hospital and Massachusetts General Hospital, Boston, Massachusetts
| | - Davneet Minhas
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Tharick A Pascoal
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - N Scott Mason
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Beth Snitz
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Howard Aizenstein
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Chester A Mathis
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Oscar Lopez
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Christopher C Rowe
- Department of Medicine, University of Melbourne, Melbourne, Victoria, Australia.,Department of Molecular Imaging and Therapy, Austin Health, Melbourne, Victoria, Australia
| | - William E Klunk
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.,Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania; and
| | - Ann D Cohen
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
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42
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Haghani A, Thorwald M, Morgan TE, Finch CE. The APOE gene cluster responds to air pollution factors in mice with coordinated expression of genes that differs by age in humans. Alzheimers Dement 2020; 17:175-190. [PMID: 33215813 DOI: 10.1002/alz.12230] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Revised: 10/26/2020] [Accepted: 10/26/2020] [Indexed: 12/13/2022]
Abstract
Little is known of gene-environment interactions for Alzheimer's disease (AD) risk factors. Apolipoprotein E (APOE) and neighbors on chromosome 19q13.3 have variants associated with risks of AD, but with unknown mechanism. This study describes novel links among the APOE network, air pollution, and age-related diseases. Mice exposed to air pollution nano-sized particulate matter (nPM) had coordinate responses of Apoe-Apoc1-Tomm40 in the cerebral cortex. In humans, the AD vulnerable hippocampus and amygdala had stronger age decline in APOE cluster expression than the AD-resistant cerebellum and hypothalamus. Using consensus weighted gene co-expression network, we showed that APOE has a conserved co-expressed network in rodent and primate brains. SOX1, which has AD-associated single nucleotide polymorphisms, was among the co-expressed genes in the human hippocampus. Humans and mice shared 87% of potential binding sites for transcription factors in APOE cluster promoter, suggesting similar inducibility and a novel link among environment, APOE cluster, and risk of AD.
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Affiliation(s)
- Amin Haghani
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, California, USA.,Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Max Thorwald
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, California, USA
| | - Todd E Morgan
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, California, USA
| | - Caleb E Finch
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, California, USA.,Dornsife College, University of Southern California, Los Angeles, California, USA
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43
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Yue L, Hu D, Zhang H, Wen J, Wu Y, Li W, Sun L, Li X, Wang J, Li G, Wang T, Shen D, Xiao S. Prediction of 7-year's conversion from subjective cognitive decline to mild cognitive impairment. Hum Brain Mapp 2020; 42:192-203. [PMID: 33030795 PMCID: PMC7721238 DOI: 10.1002/hbm.25216] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 09/11/2020] [Accepted: 09/14/2020] [Indexed: 11/16/2022] Open
Abstract
Subjective cognitive decline (SCD) is a high‐risk yet less understood status before developing Alzheimer's disease (AD). This work included 76 SCD individuals with two (baseline and 7 years later) neuropsychological evaluations and a baseline T1‐weighted structural MRI. A machine learning‐based model was trained based on 198 baseline neuroimaging (morphometric) features and a battery of 25 clinical measurements to discriminate 24 progressive SCDs who converted to mild cognitive impairment (MCI) at follow‐up from 52 stable SCDs. The SCD progression was satisfactorily predicted with the combined features. A history of stroke, a low education level, a low baseline MoCA score, a shrunk left amygdala, and enlarged white matter at the banks of the right superior temporal sulcus were found to favor the progression. This is to date the largest retrospective study of SCD‐to‐MCI conversion with the longest follow‐up, suggesting predictable far‐future cognitive decline for the risky populations with baseline measures only. These findings provide valuable knowledge to the future neuropathological studies of AD in its prodromal phase.
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Affiliation(s)
- Ling Yue
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China.,Alzheimer's Disease and Related Disorders Center of Shanghai Jiaotong University, Shanghai, China
| | - Dan Hu
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Han Zhang
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Junhao Wen
- ARAMIS Lab, ICM, Inserm U1127, Paris, France.,CNRS UMR 7225, Paris, France.,Sorbonne University, Paris, France.,Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Ye Wu
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Wei Li
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China.,Alzheimer's Disease and Related Disorders Center of Shanghai Jiaotong University, Shanghai, China
| | - Lin Sun
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China.,Alzheimer's Disease and Related Disorders Center of Shanghai Jiaotong University, Shanghai, China
| | - Xia Li
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China.,Alzheimer's Disease and Related Disorders Center of Shanghai Jiaotong University, Shanghai, China
| | - Jinghua Wang
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China.,Alzheimer's Disease and Related Disorders Center of Shanghai Jiaotong University, Shanghai, China
| | - Guanjun Li
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China.,Alzheimer's Disease and Related Disorders Center of Shanghai Jiaotong University, Shanghai, China
| | - Tao Wang
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China.,Alzheimer's Disease and Related Disorders Center of Shanghai Jiaotong University, Shanghai, China
| | - Dinggang Shen
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.,Department of Brain and Cognitive Engineering, Korea University, Seongbuk-gu, Seoul, Republic of Korea
| | - Shifu Xiao
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China.,Alzheimer's Disease and Related Disorders Center of Shanghai Jiaotong University, Shanghai, China
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44
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Guo T, Korman D, La Joie R, Shaw LM, Trojanowski JQ, Jagust WJ, Landau SM. Normalization of CSF pTau measurement by Aβ 40 improves its performance as a biomarker of Alzheimer's disease. Alzheimers Res Ther 2020; 12:97. [PMID: 32799929 PMCID: PMC7429887 DOI: 10.1186/s13195-020-00665-8] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Accepted: 08/04/2020] [Indexed: 02/07/2023]
Abstract
BACKGROUND Alzheimer's disease (AD)-related tauopathy can be measured with CSF phosphorylated tau (pTau) and tau PET. We aim to investigate the associations between these measurements and their relative ability to predict subsequent disease progression. METHODS In 219 cognitively unimpaired and 122 impaired Alzheimer's Disease Neuroimaging Initiative participants with concurrent amyloid-β (Aβ) PET (18F-florbetapir or 18F-florbetaben), 18F-flortaucipir (FTP) PET, CSF measurements, structural MRI, and cognition, we examined inter-relationships between these biomarkers and their predictions of subsequent FTP and cognition changes. RESULTS The use of a CSF pTau/Aβ40 ratio eliminated positive associations we observed between CSF pTau alone and CSF Aβ42 in the normal Aβ range likely reflecting individual differences in CSF production rather than pathology. Use of the CSF pTau/Aβ40 ratio also increased expected associations with Aβ PET, FTP PET, hippocampal volume, and cognitive decline compared to pTau alone. In Aβ+ individuals, abnormal CSF pTau/Aβ40 only individuals (26.7%) were 4 times more prevalent (p < 0.001) than abnormal FTP only individuals (6.8%). Furthermore, among individuals on the AD pathway, CSF pTau/Aβ40 mediates the association between Aβ PET and FTP PET accumulation, but FTP PET is more closely linked to subsequent cognitive decline than CSF pTau/Aβ40. CONCLUSIONS Together, these findings suggest that CSF pTau/Aβ40 may be a superior measure of tauopathy compared to CSF pTau alone, and CSF pTau/Aβ40 enables detection of tau accumulation at an earlier stage than FTP among Aβ+ individuals.
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Affiliation(s)
- Tengfei Guo
- Helen Wills Neuroscience Institute, University of California, 132 Barker Hall, Berkeley, CA, 94720, USA.
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
| | - Deniz Korman
- Helen Wills Neuroscience Institute, University of California, 132 Barker Hall, Berkeley, CA, 94720, USA
| | - Renaud La Joie
- Memory & Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Leslie M Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - John Q Trojanowski
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California, 132 Barker Hall, Berkeley, CA, 94720, USA
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Susan M Landau
- Helen Wills Neuroscience Institute, University of California, 132 Barker Hall, Berkeley, CA, 94720, USA
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
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45
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Park DC, Abner EL. Amyloid deposits in the banks (of the superior temporal sulcus) yield a high return about memory futures. Neurology 2020; 94:603-604. [PMID: 32188764 DOI: 10.1212/wnl.0000000000009213] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Affiliation(s)
- Denise C Park
- From the Center for Vital Longevity (D.C.P.), School of Behavioral and Brain Sciences, University of Texas at Dallas; Department of Psychiatry (D.C.P.), University of Texas Southwestern Medical Center, Dallas; and Sanders-Brown Center on Aging (E.L.A.) and Department of Epidemiology (E.L.A.), University of Kentucky, Lexington.
| | - Erin L Abner
- From the Center for Vital Longevity (D.C.P.), School of Behavioral and Brain Sciences, University of Texas at Dallas; Department of Psychiatry (D.C.P.), University of Texas Southwestern Medical Center, Dallas; and Sanders-Brown Center on Aging (E.L.A.) and Department of Epidemiology (E.L.A.), University of Kentucky, Lexington
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