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Hojjati SH, Babajani-Feremi A. Seeing beyond the symptoms: biomarkers and brain regions linked to cognitive decline in Alzheimer's disease. Front Aging Neurosci 2024; 16:1356656. [PMID: 38813532 PMCID: PMC11135344 DOI: 10.3389/fnagi.2024.1356656] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Accepted: 04/08/2024] [Indexed: 05/31/2024] Open
Abstract
Objective Early Alzheimer's disease (AD) diagnosis remains challenging, necessitating specific biomarkers for timely detection. This study aimed to identify such biomarkers and explore their associations with cognitive decline. Methods A cohort of 1759 individuals across cognitive aging stages, including healthy controls (HC), mild cognitive impairment (MCI), and AD, was examined. Utilizing nine biomarkers from structural MRI (sMRI), diffusion tensor imaging (DTI), and positron emission tomography (PET), predictions were made for Mini-Mental State Examination (MMSE), Clinical Dementia Rating Scale Sum of Boxes (CDRSB), and Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS). Biomarkers included four sMRI (e.g., average thickness [ATH]), four DTI (e.g., mean diffusivity [MD]), and one PET Amyloid-β (Aβ) measure. Ensemble regression tree (ERT) technique with bagging and random forest approaches were applied in four groups (HC/MCI, HC/AD, MCI/AD, and HC/MCI/AD). Results Aβ emerged as a robust predictor of cognitive scores, particularly in late-stage AD. Volumetric measures, notably ATH, consistently correlated with cognitive scores across early and late disease stages. Additionally, ADAS demonstrated links to various neuroimaging biomarkers in all subject groups, highlighting its efficacy in monitoring brain changes throughout disease progression. ERT identified key brain regions associated with cognitive scores, such as the right transverse temporal region for Aβ, left and right entorhinal cortex, left inferior temporal gyrus, and left middle temporal gyrus for ATH, and the left uncinate fasciculus for MD. Conclusion This study underscores the importance of an interdisciplinary approach in understanding AD mechanisms, offering potential contributions to early biomarker development.
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Affiliation(s)
- Seyed Hani Hojjati
- Department of Radiology, Weill Cornell Medicine, Brain Health Imaging Institute, New York, NY, United States
| | - Abbas Babajani-Feremi
- Department of Neurology, University of Florida, Gainesville, FL, United States
- Magnetoencephalography (MEG) Lab, The Norman Fixel Institute of Neurological Diseases, University of Florida Health, Gainesville, FL, United States
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2
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Wu J, Su Y, Chen Y, Zhu W, Reiman EM, Caselli RJ, Chen K, Thompson PM, Wang J, Wang Y. A Surface-Based Federated Chow Test Model for Integrating APOE Status, Tau Deposition Measure, and Hippocampal Surface Morphometry. J Alzheimers Dis 2023; 93:1153-1168. [PMID: 37182882 PMCID: PMC10329869 DOI: 10.3233/jad-230034] [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: 05/16/2023]
Abstract
BACKGROUND Alzheimer's disease (AD) is the most common type of age-related dementia, affecting 6.2 million people aged 65 or older according to CDC data. It is commonly agreed that discovering an effective AD diagnosis biomarker could have enormous public health benefits, potentially preventing or delaying up to 40% of dementia cases. Tau neurofibrillary tangles are the primary driver of downstream neurodegeneration and subsequent cognitive impairment in AD, resulting in structural deformations such as hippocampal atrophy that can be observed in magnetic resonance imaging (MRI) scans. OBJECTIVE To build a surface-based model to 1) detect differences between APOE subgroups in patterns of tau deposition and hippocampal atrophy, and 2) use the extracted surface-based features to predict cognitive decline. METHODS Using data obtained from different institutions, we develop a surface-based federated Chow test model to study the synergistic effects of APOE, a previously reported significant risk factor of AD, and tau on hippocampal surface morphometry. RESULTS We illustrate that the APOE-specific morphometry features correlate with AD progression and better predict future AD conversion than other MRI biomarkers. For example, a strong association between atrophy and abnormal tau was identified in hippocampal subregion cornu ammonis 1 (CA1 subfield) and subiculum in e4 homozygote cohort. CONCLUSION Our model allows for identifying MRI biomarkers for AD and cognitive decline prediction and may uncover a corner of the neural mechanism of the influence of APOE and tau deposition on hippocampal morphology.
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Affiliation(s)
- Jianfeng Wu
- School of Computing and Augmented Intelligence, Arizona State University, Tempe, USA
| | - Yi Su
- Banner Alzheimer’s Institute, Phoenix, USA
| | - Yanxi Chen
- School of Computing and Augmented Intelligence, Arizona State University, Tempe, USA
| | - Wenhui Zhu
- School of Computing and Augmented Intelligence, Arizona State University, Tempe, USA
| | | | | | - Kewei Chen
- Banner Alzheimer’s Institute, Phoenix, USA
| | - Paul M. Thompson
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, University of Southern California, Marina del Rey, USA
| | - Junwen Wang
- Division of Applied Oral Sciences & Community Dental Care, Faculty of Dentistry, The University of Hong Kong, Hong Kong SAR, China
| | - Yalin Wang
- School of Computing and Augmented Intelligence, Arizona State University, Tempe, USA
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3
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Nakaya M, Sato N, Matsuda H, Maikusa N, Shigemoto Y, Sone D, Yamao T, Ogawa M, Kimura Y, Chiba E, Ohnishi M, Kato K, Okita K, Tsukamoto T, Yokoi Y, Sakata M, Abe O. Free water derived by multi-shell diffusion MRI reflects tau/neuroinflammatory pathology in Alzheimer's disease. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2022; 8:e12356. [PMID: 36304723 PMCID: PMC9594557 DOI: 10.1002/trc2.12356] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Revised: 08/03/2022] [Accepted: 08/20/2022] [Indexed: 11/23/2022]
Abstract
Introduction Free-water (FW) imaging, a new analysis method for diffusion magnetic resonance imaging (MRI), can indicate neuroinflammation and degeneration. We evaluated FW in Alzheimer's disease (AD) using tau/inflammatory and amyloid positron emission tomography (PET). Methods Seventy-one participants underwent multi-shell diffusion MRI, 18F-THK5351 PET, 11C-Pittsburgh compound B PET, and neuropsychological assessments. They were categorized into two groups: healthy controls (HCs) (n = 40) and AD-spectrum group (AD-S) (n = 31) using the Centiloid scale with amyloid PET and cognitive function. We analyzed group comparisons in FW and PET, correlations between FW and PET, and correlation analysis with neuropsychological scores. Results In AD-S group, there was a significant positive correlation between FW and 18F-THK5351 in the temporal lobes. In addition, there were negative correlations between FW and cognitive function in the temporal lobe and cingulate gyrus, and negative correlations between 18F-THK5351 and cognitive function in the same regions. Discussion FW imaging could be a biomarker for tau in AD alongside clinical correlations.
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Affiliation(s)
- Moto Nakaya
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
- Department of RadiologyGraduate School of MedicineUniversity of TokyoHongoBunkyo‐kuTokyoJapan
| | - Noriko Sato
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
| | - Hiroshi Matsuda
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
- Drug Discovery and Cyclotron Research CenterSouthern TOHOKU Research Institute for NeuroscienceKoriyamaJapan
| | - Norihide Maikusa
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
| | - Yoko Shigemoto
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
| | - Daichi Sone
- Department of PsychiatryThe Jikei University School of MedicineTokyoJapan
- Integrative Brain Imaging CenterNational Center of Neurology and PsychiatryTokyoJapan
| | - Tensho Yamao
- Department of Radiological SciencesSchool of Health SciencesFukushima Medical UniversityFukushimaJapan
| | - Masayo Ogawa
- Integrative Brain Imaging CenterNational Center of Neurology and PsychiatryTokyoJapan
| | - Yukio Kimura
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
| | - Emiko Chiba
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
| | - Masahiro Ohnishi
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
| | - Koichi Kato
- Integrative Brain Imaging CenterNational Center of Neurology and PsychiatryTokyoJapan
| | - Kyoji Okita
- Integrative Brain Imaging CenterNational Center of Neurology and PsychiatryTokyoJapan
| | - Tadashi Tsukamoto
- Department of NeurologyNational Center of Neurology and PsychiatryKodairaTokyoJapan
| | - Yuma Yokoi
- Department of PsychiatryNational Center of Neurology and PsychiatryKodairaTokyoJapan
| | - Masuhiro Sakata
- Department of PsychiatryNational Center of Neurology and PsychiatryKodairaTokyoJapan
| | - Osamu Abe
- Department of RadiologyGraduate School of MedicineUniversity of TokyoHongoBunkyo‐kuTokyoJapan
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Gagliardi G, Vannini P. Episodic Memory Impairment Mediates the Loss of Awareness in Mild Cognitive Impairment. Front Aging Neurosci 2022; 13:802501. [PMID: 35126092 PMCID: PMC8814670 DOI: 10.3389/fnagi.2021.802501] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 12/30/2021] [Indexed: 11/16/2022] Open
Abstract
INTRODUCTION Loss of awareness is a common symptom in Alzheimer's Disease (AD) and responsible for a significant loss of functional abilities. The mechanisms underlying loss of awareness in AD is unknown, although previous findings have implicated dysfunction of primary executive functioning (EF) or episodic memory (EM) to be the cause. Therefore, our main study objective was to explore the involvement of EF and EM dysfunction in amyloid-related loss of awareness across the clinical spectrum of AD. METHODS A total of 895 participants (362 clinically normal [CN], 422 people with mild cognitive impairment [MCI] and 111 with dementia) from the Alzheimer's Disease Neuroimaging Initiative were used for the analyses. A sub-analysis was performed in 202 participants who progressed in their clinical diagnosis from CN to MCI or MCI to dementia as well as dementia patients. Mediation models were used in each clinical group with awareness (assessed with the Everyday Cognitive function questionnaire) as a dependent variable to determine whether EF and/or EM would mediate the effect of amyloid on awareness. We also ran these analyses with subjective and informant complaints as dependent variables. Direct correlations between all variables were also performed. RESULTS We found evidence for a decline in awareness across the groups, with increased awareness observed in the CN group and decreased awareness observed in the MCI and dementia groups. Our results showed that EM, and not EF, partially mediated the relationship between amyloid and awareness such that greater amyloid and lower EM performance was associated with lower awareness. When analyzing each group separately, this finding was only observed in the MCI group and in the group containing progressors and dementia patients. When repeating the analyses for subjective and informant complaints separately, the results were replicated only for the informant's complaints. DISCUSSION Our results demonstrate that decline in EM and, to a lesser degree, EF, mediate the effect of amyloid on awareness. In line with previous studies demonstrating the development of anosognosia in the prodromal stage, our findings suggest that decreased awareness is the result of an inability for the participant to update his/her insight into his/her cognitive performance (i.e., demonstrating a petrified self).
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Affiliation(s)
- Geoffroy Gagliardi
- Neurology, Brigham and Women's Hospital, Boston, MA, United States
- Neurology, Massachusetts General Hospital, Boston, MA, United States
- Harvard Medical School, Cambridge, MA, United States
| | - Patrizia Vannini
- Neurology, Brigham and Women's Hospital, Boston, MA, United States
- Neurology, Massachusetts General Hospital, Boston, MA, United States
- Harvard Medical School, Cambridge, MA, United States
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5
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Jung NY, Shin JH, Kim HJ, Jang H, Moon SH, Kim SJ, Kim Y, Cho SH, Kim KW, Kim JP, Jung YH, Kim ST, Kim EJ, Na DL, Vogel JW, Lee S, Seong JK, Seo SW. Distinctive Mediating Effects of Subcortical Structure Changes on the Relationships Between Amyloid or Vascular Changes and Cognitive Decline. Front Neurol 2021; 12:762251. [PMID: 34950100 PMCID: PMC8688398 DOI: 10.3389/fneur.2021.762251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2021] [Accepted: 11/04/2021] [Indexed: 11/13/2022] Open
Abstract
Objective: We investigated the mediation effects of subcortical volume change in the relationship of amyloid beta (Aβ) and lacune with cognitive function in patients with mild cognitive impairment (MCI). Methods: We prospectively recruited 101 patients with MCI who were followed up with neuropsychological tests, MRI, or Pittsburgh compound B (PiB) PET for 3 years. The mediation effect of subcortical structure on the association of PiB or lacunes with cognitive function was analyzed using mixed effects models. Results: Volume changes in the amygdala and hippocampus partially mediated the effect of PiB changes on memory function (direct effect = -0.168/-0.175, indirect effect = -0.081/-0.077 for amygdala/hippocampus) and completely mediated the effect of PiB changes on clinical dementia rating scale sum of the box (CDR-SOB) (indirect effect = 0.082/0.116 for amygdala/hippocampus). Volume changes in the thalamus completely mediated the effect of lacune on memory, frontal executive functions, and CDR-SOB (indirect effect = -0.037, -0.056, and 0.047, respectively). Conclusions: Our findings provide a better understanding of the distinct role of subcortical structures in the mediation of the relationships of amyloid or vascular changes with a decline in specific cognitive domains.
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Affiliation(s)
- Na-Yeon Jung
- Department of Neurology, Pusan National University Yangsan Hospital, Pusan National University School of Medicine and Research Institute for Convergence of Biomedical Science and Technology, Yangsan, South Korea
| | - Jeong-Hyeon Shin
- School of Biomedical Engineering, Korea University, Seoul, South Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.,Neuroscience Center, Samsung Medical Center, Seoul, South Korea
| | - Hyemin Jang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.,Neuroscience Center, Samsung Medical Center, Seoul, South Korea
| | - Seung Hwan Moon
- Department of Nuclear Medicine, Samsung Medical Center, Seoul, South Korea
| | - Seung Joo Kim
- Department of Neurology, Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, Changwon, South Korea
| | - Yeshin Kim
- Department of Neurology, Kangwon National University College of Medicine, Chuncheon-si, South Korea
| | - Soo Hyun Cho
- Department of Neurology, Chonnam National University Medical School and Hospital, Gwangju, South Korea
| | - Ko Woon Kim
- Department of Neurology, Chonbuk National University Medical School and Hospital, Jeonju, South Korea
| | - Jun Pyo Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.,Neuroscience Center, Samsung Medical Center, Seoul, South Korea
| | - Young Hee Jung
- Department of Neurology, Myongji Hospital, College of Medicine, Hanyang University, Goyang, South Korea
| | - Sung Tae Kim
- Department of Radiology, Samsung Medical Center, Seoul, South Korea
| | - Eun-Joo Kim
- Department of Neurology, Pusan National University Hospital, Pusan National University School of Medicine, Pusan, South Korea
| | - Duk L Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.,Neuroscience Center, Samsung Medical Center, Seoul, South Korea
| | - Jacob W Vogel
- Montreal Neurological Institute, McGill University, Montrèal, QC, Canada
| | - Sangjin Lee
- Graduate School, Department of Statistics, Pusan National University, Busan, South Korea
| | - Joon-Kyung Seong
- School of Biomedical Engineering, Korea University, Seoul, South Korea
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.,Neuroscience Center, Samsung Medical Center, Seoul, South Korea
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6
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Wu J, Dong Q, Zhang J, Su Y, Wu T, Caselli RJ, Reiman EM, Ye J, Lepore N, Chen K, Thompson PM, Wang Y. Federated Morphometry Feature Selection for Hippocampal Morphometry Associated Beta-Amyloid and Tau Pathology. Front Neurosci 2021; 15:762458. [PMID: 34899166 PMCID: PMC8655732 DOI: 10.3389/fnins.2021.762458] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2021] [Accepted: 11/01/2021] [Indexed: 12/03/2022] Open
Abstract
Amyloid-β (Aβ) plaques and tau protein tangles in the brain are now widely recognized as the defining hallmarks of Alzheimer's disease (AD), followed by structural atrophy detectable on brain magnetic resonance imaging (MRI) scans. One of the particular neurodegenerative regions is the hippocampus to which the influence of Aβ/tau on has been one of the research focuses in the AD pathophysiological progress. This work proposes a novel framework, Federated Morphometry Feature Selection (FMFS) model, to examine subtle aspects of hippocampal morphometry that are associated with Aβ/tau burden in the brain, measured using positron emission tomography (PET). FMFS is comprised of hippocampal surface-based feature calculation, patch-based feature selection, federated group LASSO regression, federated screening rule-based stability selection, and region of interest (ROI) identification. FMFS was tested on two Alzheimer's Disease Neuroimaging Initiative (ADNI) cohorts to understand hippocampal alterations that relate to Aβ/tau depositions. Each cohort included pairs of MRI and PET for AD, mild cognitive impairment (MCI), and cognitively unimpaired (CU) subjects. Experimental results demonstrated that FMFS achieves an 89× speedup compared to other published state-of-the-art methods under five independent hypothetical institutions. In addition, the subiculum and cornu ammonis 1 (CA1 subfield) were identified as hippocampal subregions where atrophy is strongly associated with abnormal Aβ/tau. As potential biomarkers for Aβ/tau pathology, the features from the identified ROIs had greater power for predicting cognitive assessment and for survival analysis than five other imaging biomarkers. All the results indicate that FMFS is an efficient and effective tool to reveal associations between Aβ/tau burden and hippocampal morphometry.
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Affiliation(s)
- Jianfeng Wu
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, United States
| | - Qunxi Dong
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, United States
- Institute of Engineering Medicine, Beijing Institute of Technology, Beijing, China
| | - Jie Zhang
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, United States
| | - Yi Su
- Banner Alzheimer’s Institute, Phoenix, AZ, United States
| | - Teresa Wu
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, United States
| | - Richard J. Caselli
- Department of Neurology, Mayo Clinic Arizona, Scottsdale, AZ, United States
| | - Eric M. Reiman
- Banner Alzheimer’s Institute, Phoenix, AZ, United States
| | - Jieping Ye
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, United States
| | - Natasha Lepore
- CIBORG Lab, Department of Radiology, Children’s Hospital Los Angeles, Los Angeles, CA, United States
| | - Kewei Chen
- Banner Alzheimer’s Institute, Phoenix, AZ, United States
| | - Paul M. Thompson
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, University of Southern California, Marina del Rey, CA, United States
| | - Yalin Wang
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, United States
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7
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Lindstrom MR, Chavez MB, Gross-Sable EA, Hayden EY, Teplow DB. From reaction kinetics to dementia: A simple dimer model of Alzheimer's disease etiology. PLoS Comput Biol 2021; 17:e1009114. [PMID: 34280181 PMCID: PMC8321409 DOI: 10.1371/journal.pcbi.1009114] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 07/29/2021] [Accepted: 05/25/2021] [Indexed: 11/19/2022] Open
Abstract
Oligomers of the amyloid β-protein (Aβ) have been implicated in the pathogenesis of Alzheimer's disease (AD) through their toxicity towards neurons. Understanding the process of oligomerization may contribute to the development of therapeutic agents, but this has been difficult due to the complexity of oligomerization and the metastability of the oligomers thus formed. To understand the kinetics of oligomer formation, and how that relates to the progression of AD, we developed models of the oligomerization process. Here, we use experimental data from cell viability assays and proxies for rate constants involved in monomer-dimer-trimer kinetics to develop a simple mathematical model linking Aβ assembly to oligomer-induced neuronal degeneration. This model recapitulates the rapid growth of disease incidence with age. It does so through incorporation of age-dependent changes in rates of Aβ monomer production and elimination. The model also describes clinical progression in genetic forms of AD (e.g., Down's syndrome), changes in hippocampal volume, AD risk after traumatic brain injury, and spatial spreading of the disease due to foci in which Aβ production is elevated. Continued incorporation of clinical and basic science data into the current model will make it an increasingly relevant model system for doing theoretical calculations that are not feasible in biological systems. In addition, terms in the model that have particularly large effects are likely to be especially useful therapeutic targets.
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Affiliation(s)
- Michael R. Lindstrom
- Department of Mathematics, University of California, Los Angeles, California, United States of America
| | - Manuel B. Chavez
- Department of Mathematics, University of California, Los Angeles, California, United States of America
| | - Elijah A. Gross-Sable
- Department of Mathematics, University of California, Los Angeles, California, United States of America
| | - Eric Y. Hayden
- Department of Neurology, David Geffen School of Medicine at the University of California, Los Angeles, California, United States of America
| | - David B. Teplow
- Department of Neurology, David Geffen School of Medicine at the University of California, Los Angeles, California, United States of America
- Molecular Biology Institute and Brain Research Institute, University of California, Los Angeles, California, United States of America
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8
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Narbutas J, Chylinski D, Van Egroo M, Bahri MA, Koshmanova E, Besson G, Muto V, Schmidt C, Luxen A, Balteau E, Phillips C, Maquet P, Salmon E, Vandewalle G, Bastin C, Collette F. Positive Effect of Cognitive Reserve on Episodic Memory, Executive and Attentional Functions Taking Into Account Amyloid-Beta, Tau, and Apolipoprotein E Status. Front Aging Neurosci 2021; 13:666181. [PMID: 34122044 PMCID: PMC8194490 DOI: 10.3389/fnagi.2021.666181] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Accepted: 04/20/2021] [Indexed: 01/01/2023] Open
Abstract
Studies exploring the simultaneous influence of several physiological and environmental factors on domain-specific cognition in late middle-age remain scarce. Therefore, our objective was to determine the respective contribution of modifiable risk/protective factors (cognitive reserve and allostatic load) on specific cognitive domains (episodic memory, executive functions, and attention), taking into account non-modifiable factors [sex, age, and genetic risk for Alzheimer's disease (AD)] and AD-related biomarker amount (amyloid-beta and tau/neuroinflammation) in a healthy late-middle-aged population. One hundred and one healthy participants (59.4 ± 5 years; 68 women) were evaluated for episodic memory, executive and attentional functioning via neuropsychological test battery. Cognitive reserve was determined by the National Adult Reading Test. The allostatic load consisted of measures of lipid metabolism and sympathetic nervous system functioning. The amyloid-beta level was assessed using positron emission tomography in all participants, whereas tau/neuroinflammation positron emission tomography scans and apolipoprotein E genotype were available for 58 participants. Higher cognitive reserve was the main correlate of better cognitive performance across all domains. Moreover, age was negatively associated with attentional functioning, whereas sex was a significant predictor for episodic memory, with women having better performance than men. Finally, our results did not show clear significant associations between performance over any cognitive domain and apolipoprotein E genotype and AD biomarkers. This suggests that domain-specific cognition in late healthy midlife is mainly determined by a combination of modifiable (cognitive reserve) and non-modifiable factors (sex and age) rather than by AD biomarkers and genetic risk for AD.
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Affiliation(s)
- Justinas Narbutas
- GIGA Institute, Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
- Psychology and Neuroscience of Cognition Research Unit, Faculty of Psychology and Educational Sciences, University of Liège, Liège, Belgium
| | - Daphne Chylinski
- GIGA Institute, Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
| | - Maxime Van Egroo
- GIGA Institute, Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
| | - Mohamed Ali Bahri
- GIGA Institute, Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
| | - Ekaterina Koshmanova
- GIGA Institute, Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
| | - Gabriel Besson
- GIGA Institute, Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
| | - Vincenzo Muto
- GIGA Institute, Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
| | - Christina Schmidt
- GIGA Institute, Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
- Psychology and Neuroscience of Cognition Research Unit, Faculty of Psychology and Educational Sciences, University of Liège, Liège, Belgium
| | - André Luxen
- GIGA Institute, Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
| | - Evelyne Balteau
- GIGA Institute, Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
| | - Christophe Phillips
- GIGA Institute, Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
| | - Pierre Maquet
- GIGA Institute, Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
- Department of Neurology, CHU de Liège, Liège, Belgium
| | - Eric Salmon
- GIGA Institute, Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
- Psychology and Neuroscience of Cognition Research Unit, Faculty of Psychology and Educational Sciences, University of Liège, Liège, Belgium
- Department of Neurology, CHU de Liège, Liège, Belgium
| | - Gilles Vandewalle
- GIGA Institute, Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
| | - Christine Bastin
- GIGA Institute, Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
- Psychology and Neuroscience of Cognition Research Unit, Faculty of Psychology and Educational Sciences, University of Liège, Liège, Belgium
| | - Fabienne Collette
- GIGA Institute, Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
- Psychology and Neuroscience of Cognition Research Unit, Faculty of Psychology and Educational Sciences, University of Liège, Liège, Belgium
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9
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Pelkmans W, Legdeur N, Ten Kate M, Barkhof F, Yaqub MM, Holstege H, van Berckel BNM, Scheltens P, van der Flier WM, Visser PJ, Tijms BM. Amyloid-β, cortical thickness, and subsequent cognitive decline in cognitively normal oldest-old. Ann Clin Transl Neurol 2021; 8:348-358. [PMID: 33421355 PMCID: PMC7886045 DOI: 10.1002/acn3.51273] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2020] [Revised: 11/16/2020] [Accepted: 11/19/2020] [Indexed: 12/14/2022] Open
Abstract
Objective To investigate the relationship between amyloid‐β (Aβ) deposition and markers of brain structure on cognitive decline in oldest‐old individuals with initial normal cognition. Methods We studied cognitive functioning in four domains at baseline and change over time in fifty‐seven cognitively intact individuals from the EMIF‐AD 90+ study. Predictors were Aβ status determined by [18F]‐flutemetamol PET (normal = Aβ − vs. abnormal = Aβ+), cortical thickness in 34 regions and hippocampal volume. Mediation analyses were performed to test whether effects of Aβ on cognitive decline were mediated by atrophy of specific anatomical brain areas. Results Subjects had a mean age of 92.7 ± 2.9 years, of whom 19 (33%) were Aβ+. Compared to Aβ−, Aβ+ individuals showed steeper decline on memory (β ± SE = −0.26 ± 0.09), and processing speed (β ± SE = −0.18 ± 0.08) performance over 1.5 years (P < 0.05). Furthermore, medial and lateral temporal lobe atrophy was associated with steeper decline in memory and language across individuals. Mediation analyses revealed that part of the memory decline observed in Aβ+ individuals was mediated through parahippocampal atrophy. Interpretation These results show that Aβ abnormality even in the oldest old with initially normal cognition is not part of normal aging, but is associated with a decline in cognitive functioning. Other pathologies may also contribute to decline in the oldest old as cortical thickness predicted cognitive decline similarly in individuals with and without Aβ pathology.
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Affiliation(s)
- Wiesje Pelkmans
- Alzheimer Center Amsterdam, Department of Neurology I Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Nienke Legdeur
- Alzheimer Center Amsterdam, Department of Neurology I Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Mara Ten Kate
- Alzheimer Center Amsterdam, Department of Neurology I Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.,Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.,Queen Square Institute of Neurology and Centre for Medical Image Computing, UCL, London, UK
| | - Maqsood M Yaqub
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Henne Holstege
- Alzheimer Center Amsterdam, Department of Neurology I Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.,Department of Clinical Genetics, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Bart N M van Berckel
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology I Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Department of Neurology I Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.,Department of Epidemiology & Biostatistics, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Pieter Jelle Visser
- Alzheimer Center Amsterdam, Department of Neurology I Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.,Department of Psychiatry & Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands.,Department of Neurobiology, Care Sciences and Society, Division of Neurogeriatrics, Karolinska Institutet, Stockholm, Sweden
| | - Betty M Tijms
- Alzheimer Center Amsterdam, Department of Neurology I Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
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10
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Spatial patterns of correlation between cortical amyloid and cortical thickness in a tertiary clinical population with memory deficit. Sci Rep 2020; 10:20717. [PMID: 33244036 PMCID: PMC7693188 DOI: 10.1038/s41598-020-77503-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Accepted: 11/11/2020] [Indexed: 12/28/2022] Open
Abstract
To estimate regional Alzheimer disease (AD) pathology burden clinically, analysis methods that enable tracking brain amyloid or tau positron emission tomography (PET) with magnetic resonance imaging (MRI) measures are needed. We therefore developed a robust MRI analysis method to identify brain regions that correlate linearly with regional amyloid burden in congruent PET images. This method was designed to reduce data variance and improve the sensitivity of the detection of cortical thickness-amyloid correlation by using whole brain modeling, nonlinear image coregistration, and partial volume correction. Using this method, a cross-sectional analysis of 75 tertiary memory clinic AD patients was performed to test our hypothesis that regional amyloid burden and cortical thickness are inversely correlated in medial temporal neocortical regions. Medial temporal cortical thicknesses were not correlated with their regional amyloid burden, whereas cortical thicknesses in the lateral temporal, lateral parietal, and frontal regions were inversely correlated with amyloid burden. This study demonstrates the robustness of our technique combining whole brain modeling, nonlinear image coregistration, and partial volume correction to track the differential correlation between regional amyloid burden and cortical thinning in specific brain regions. This method could be used with amyloid and tau PET to assess corresponding cortical thickness changes.
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11
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McDonough IM, Festini SB, Wood MM. Risk for Alzheimer's disease: A review of long-term episodic memory encoding and retrieval fMRI studies. Ageing Res Rev 2020; 62:101133. [PMID: 32717407 DOI: 10.1016/j.arr.2020.101133] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2020] [Revised: 05/21/2020] [Accepted: 07/18/2020] [Indexed: 02/06/2023]
Abstract
Many risk factors have been identified that predict future progression to Alzheimer's disease (AD). However, clear links have yet to be made between these risk factors and how they affect brain functioning in early stages of AD. We conducted a narrative review and a quantitative analysis to better understand the relationship between nine categories of AD risk (i.e., brain pathology, genetics/family history, vascular health, head trauma, cognitive decline, engagement in daily life, late-life depression, sex/gender, and ethnoracial group) and task-evoked fMRI activity during episodic memory in cognitively-normal older adults. Our narrative review revealed widespread regional alterations of both greater and lower brain activity with AD risk. Nevertheless, our quantitative analysis revealed that a subset of studies converged on two patterns: AD risk was associated with (1) greater brain activity in frontal and parietal regions, but (2) reduced brain activity in hippocampal and occipital regions. The brain regions affected depended on the assessed memory stage (encoding or retrieval). Although the results clearly indicate that AD risks impact brain activity, we caution against using fMRI as a diagnostic tool for AD at the current time because the above consistencies were present among much variability, even among the same risk factor.
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Affiliation(s)
- Ian M McDonough
- Department of Psychology, The University of Alabama, BOX 870348, Tuscaloosa, AL 35487, USA.
| | - Sara B Festini
- Department of Psychology, University of Tampa, 401 W Kennedy Blvd. Tampa, FL 33606, USA
| | - Meagan M Wood
- Department of Psychology, Valdosta State University, 1500 N. Patterson Street, Valdosta, GA 31698, USA
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12
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Parker TD, Cash DM, Lane CA, Lu K, Malone IB, Nicholas JM, James S, Keshavan A, Murray‐Smith H, Wong A, Buchanan SM, Keuss SE, Sudre CH, Thomas DL, Crutch SJ, Fox NC, Richards M, Schott JM. Amyloid β influences the relationship between cortical thickness and vascular load. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2020; 12:e12022. [PMID: 32313829 PMCID: PMC7163924 DOI: 10.1002/dad2.12022] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Revised: 11/30/2019] [Accepted: 01/02/2020] [Indexed: 11/18/2022]
Abstract
INTRODUCTION Cortical thickness has been proposed as a biomarker of Alzheimer's disease (AD)- related neurodegeneration, but the nature of its relationship with amyloid beta (Aβ) deposition and white matter hyperintensity volume (WMHV) in cognitively normal adults is unclear. METHODS We investigated the influences of Aβ status (negative/positive) and WMHV on cortical thickness in 408 cognitively normal adults aged 69.2 to 71.9 years who underwent 18F-Florbetapir positron emission tomography (PET) and structural magnetic resonance imaging (MRI). Two previously defined Alzheimer's disease (AD) cortical signature regions and the major cortical lobes were selected as regions of interest (ROIs) for cortical thickness. RESULTS Higher WMHV, but not Aβ status, predicted lower cortical thickness across all participants, in all ROIs. Conversely, when Aβ-positive participants were considered alone, higher WMHV predicted higher cortical thickness in a temporal AD-signature region. DISCUSSION WMHV may differentially influence cortical thickness depending on the presence or absence of Aβ, potentially reflecting different pathological mechanisms.
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Affiliation(s)
- Thomas D. Parker
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | - David M. Cash
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | - Christopher A. Lane
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | - Kirsty Lu
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | - Ian B. Malone
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | - Jennifer M. Nicholas
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
- Department of Medical StatisticsLondon School of Hygiene and Tropical MedicineLondonUK
| | | | - Ashvini Keshavan
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | - Heidi Murray‐Smith
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCLLondonUK
| | - Sarah M. Buchanan
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | - Sarah E. Keuss
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | - Carole H. Sudre
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
- Department of Medical Physics and Biomedical EngineeringUCLLondonUK
| | - David L. Thomas
- Leonard Wolfson Experimental Neurology Centre, Queen Square Institute of NeurologyUCLLondonUK
- Neuroradiological Academic Unit, Department of Brain Repair and RehabilitationUCL Queen Square Institute of NeurologyLondonUK
| | - Sebastian J. Crutch
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | - Nick C. Fox
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | | | - Jonathan M. Schott
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
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13
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Dupont PS, Bocti C, Joannette M, Lavallée MM, Nikelski J, Vallet GT, Chertkow H, Joubert S. Amyloid burden and white matter hyperintensities mediate age-related cognitive differences. Neurobiol Aging 2020; 86:16-26. [DOI: 10.1016/j.neurobiolaging.2019.08.025] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2018] [Revised: 08/07/2019] [Accepted: 08/09/2019] [Indexed: 12/17/2022]
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14
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McDonough IM, Popp TE. Linear and nonlinear relationships between cognitive subdomains of ability discrepancy and Alzheimer's disease biomarkers. Neuropsychology 2019; 34:211-226. [PMID: 31789566 DOI: 10.1037/neu0000606] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
OBJECTIVE Substantial research indicates that fluid and crystallized abilities are highly correlated throughout the adult life span. However, recent proposals suggest that a large discrepancy between these two abilities, defined as crystallized performance minus fluid performance, indicates heightened risk for Alzheimer's disease (AD). METHOD In 266 cognitively healthy older adults, the present study tested linear and quadratic relationships between an ability discrepancy score and early AD neuropathology indexed via in vivo measures of beta-amyloid deposition and cortical thickness in AD-vulnerable regions. We also tested the extent that alternative forms of this ability discrepancy measure (e.g., subdomain discrepancies, verbal-visual discrepancies) and an episodic memory composite might also be sensitive markers of early AD pathology. RESULTS An overall ability discrepancy was linearly and positively correlated with beta- amyloid. A quadratic relationship was found between the overall ability discrepancy score and cortical thickness such that a small positive correlation was found at lower discrepancy levels (fluid > crystallized), but at higher discrepancy levels (crystallized > fluid) a negative relationship was found (i.e., an inverted-U pattern). Similar patterns were found across each subdomain of cognition, but the effects were weaker than the overall ability discrepancy score. Importantly, inclusion of episodic memory (the gold standard) did not alter any of the effects, suggesting that an ability discrepancy confers unique predictiveness of AD biomarkers. CONCLUSIONS These findings replicate previous findings and increase the confidence in their usefulness to predict AD biomarkers. Longitudinal validation is needed to clearly relate an ability discrepancy to specific stages of preclinical AD. (PsycINFO Database Record (c) 2020 APA, all rights reserved).
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15
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Ofori E, DeKosky ST, Febo M, Colon-Perez L, Chakrabarty P, Duara R, Adjouadi M, Golde TE, Vaillancourt DE. Free-water imaging of the hippocampus is a sensitive marker of Alzheimer's disease. Neuroimage Clin 2019; 24:101985. [PMID: 31470214 PMCID: PMC6722298 DOI: 10.1016/j.nicl.2019.101985] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2019] [Revised: 06/30/2019] [Accepted: 08/14/2019] [Indexed: 11/25/2022]
Abstract
Validating sensitive markers of hippocampal degeneration is fundamental for understanding neurodegenerative conditions such as Alzheimer's disease. In this paper, we test the hypothesis that free-water in the hippocampus will be more sensitive to early stages of cognitive decline than hippocampal volume, and that free-water in hippocampus will increase across distinct clinical stages of Alzheimer's disease. We examined two separate cohorts (N = 126; N = 112) of cognitively normal controls, early and late mild cognitive impairment (MCI), and Alzheimer's disease. Demographic, clinical, diffusion-weighted and T1-weighted imaging, and positron emission tomography (PET) imaging were assessed. Results indicated elevated hippocampal free-water in early MCI individuals compared to controls across both cohorts. In contrast, there was no difference in volume of these regions between controls and early MCI. ADNI free-water values in the hippocampus was associated with low CSF AB1-42 levels and high global amyloid PET values. Free-water imaging of the hippocampus can serve as an early stage marker for AD and provides a complementary measure of AD neurodegeneration using non-invasive imaging.
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Affiliation(s)
- Edward Ofori
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville FL 32611, United States of America; College of Health Solutions, Arizona State University, Phoenix, AZ, United States of America.
| | - Steven T DeKosky
- Department of Neurology, McKnight Brain Institute, University of Florida, Gainesville FL 32611, United States of America
| | - Marcelo Febo
- Department of Psychiatry, University of Florida, Gainesville FL 32611, United States of America; Department of Neuroscience, University of Florida, Gainesville FL 32611, United States of America
| | - Luis Colon-Perez
- Department of Psychiatry, University of Florida, Gainesville FL 32611, United States of America
| | - Paramita Chakrabarty
- Department of Neuroscience, University of Florida, Gainesville FL 32611, United States of America; Center for Translational Research in Neurodegenerative Diseases, University of Florida, Gainesville FL 32611, United States of America
| | - Ranjan Duara
- Wein Center for Alzheimer's Disease and Memory Disorders, Mount Sinai Medical Center, Miami Beach, FL 33140, United States of America
| | - Malek Adjouadi
- Center for Advanced Technology and Education, Florida International University, Miami, FL 33174, United States of America
| | - Todd E Golde
- Department of Neuroscience, University of Florida, Gainesville FL 32611, United States of America; Center for Translational Research in Neurodegenerative Diseases, University of Florida, Gainesville FL 32611, United States of America
| | - David E Vaillancourt
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville FL 32611, United States of America; Department of Neurology, University of Florida, Gainesville FL-32611, United States of America; Department of Biomedical Engineering, University of Florida, Gainesville FL-32611, United States of America
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16
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Examining the identification of age-related atrophy between T1 and T1 + T2-FLAIR cortical thickness measurements. Sci Rep 2019; 9:11288. [PMID: 31375692 PMCID: PMC6677836 DOI: 10.1038/s41598-019-47294-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2019] [Accepted: 07/10/2019] [Indexed: 11/10/2022] Open
Abstract
Cortical thickness is traditionally derived from T1-weighted MRI images. Recent studies have shown an improvement in segmentation with the combination of T1 + T2-FLAIR images. MRI data from 54 adults (mean: 71 years, 65–81 years, 48% females) that are part of an ongoing cohort study were analyzed to investigate whether T1 + T2-FLAIR cortical thickness measurements were superior to those derived from T1-weighted images in identifying age-related atrophy. T1-weighted and T2-FLAIR MRI images were processed through FreeSurfer v6.0. Data was extracted using the Desikan-Killiany (DKT) atlas. FreeSurfer’s GUI QDEC examined age-related atrophy. Nonparametric tests, effect sizes, and Pearson correlations examined differences between T1-only and T1 + T2-FLAIR cortical thickness data. These analyses demonstrated that T1 + T2-FLAIR processed images significantly improved the segmentation of gray matter (chi-square x2, p < 0.05) and demonstrated significantly thicker cortical thickness means (p < 0.05) with medium to large effect sizes. Significant regions of age-related cortical atrophy were identified within the T1 + T2-FLAIR data (FDR corrected, p < 0.05). This is in contrast to the T1-only data where no regions survived FDR correction. In summary, T1 + T2-FLAIR data were associated with significant improvement in cortical segmentation and the identification of age-related cortical atrophy. Future studies should consider employing this imaging strategy to obtain cortical thickness measurements sensitive to age-related changes.
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17
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Tahmi M, Bou-Zeid W, Razlighi QR. A Fully Automatic Technique for Precise Localization and Quantification of Amyloid-β PET Scans. J Nucl Med 2019; 60:1771-1779. [PMID: 31171596 DOI: 10.2967/jnumed.119.228510] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2019] [Accepted: 05/29/2019] [Indexed: 11/16/2022] Open
Abstract
Spatial heterogeneity in the accumulation of amyloid-β plaques throughout the brain during asymptomatic as well as clinical stages of Alzheimer disease calls for precise localization and quantification of this protein using PET imaging. To address this need, we have developed and evaluated a technique that quantifies the extent of amyloid-β pathology on a millimeter-by-millimeter scale in the brain with unprecedented precision using data from PET scans. Methods: An intermodal and intrasubject registration with normalized mutual information as the cost function was used to transform all FreeSurfer neuroanatomic labels into PET image space, which were subsequently used to compute regional SUV ratio (SUVR). We have evaluated our technique using postmortem histopathologic staining data from 52 older participants as the standard-of-truth measurement. Results: Our method resulted in consistently and significantly higher SUVRs in comparison to the conventional method in almost all regions of interest. A 2-way ANOVA revealed a significant main effect of method as well as a significant interaction effect of method on the relationship between computed SUVR and histopathologic staining score. Conclusion: These findings suggest that processing the amyloid-β PET data in subjects' native space can improve the accuracy of the computed SUVRs, as they are more closely associated with the histopathologic staining data than are the results of the conventional approach.
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Affiliation(s)
- Mouna Tahmi
- Department of Neurology, Columbia University Medical Center, New York, New York; and
| | - Wassim Bou-Zeid
- Department of Neurology, Columbia University Medical Center, New York, New York; and
| | - Qolamreza R Razlighi
- Department of Neurology, Columbia University Medical Center, New York, New York; and.,Department of Biomedical Engineering, Columbia University, New York, New York
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18
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Zuelsdorff ML, Koscik RL, Okonkwo OC, Peppard PE, Hermann BP, Sager MA, Johnson SC, Engelman CD. Social support and verbal interaction are differentially associated with cognitive function in midlife and older age. NEUROPSYCHOLOGY, DEVELOPMENT, AND COGNITION. SECTION B, AGING, NEUROPSYCHOLOGY AND COGNITION 2019; 26:144-160. [PMID: 29241403 PMCID: PMC6003840 DOI: 10.1080/13825585.2017.1414769] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/04/2016] [Accepted: 12/04/2017] [Indexed: 12/13/2022]
Abstract
Social engagement is associated with healthy aging and preserved cognition. Two dimensions of engagement, verbal interactions and perceived support, likely impact cognition via distinct mechanistic pathways. We explored the cognitive benefit of each construct among enrollees (N = 1,052, mean age = 60.2 years) in the Wisconsin Registry for Alzheimer's Prevention study, who provide neuropsychological and sociobehavioral data at two-year intervals. Outcomes included six cognitive factor scores representing key domains of executive function and memory. Key predictors included self-reported perceived social support and weekly verbal interaction. Results indicated that after adjusting for lifestyle covariates, social support was positively associated with Speed and Flexibility and that verbal interactions were associated with Verbal Learning and Memory. These findings suggest that support, which may buffer stress, and verbal interaction, an accessible, aging-friendly form of environmental enrichment, are uniquely beneficial. Both are integral in the design of clinical and community interventions and programs that promote successful aging.
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Affiliation(s)
- Megan L Zuelsdorff
- a Alzheimer's Disease Research Center , University of Wisconsin School of Medicine and Public Health , Madison , WI , USA
- b Center for Demography of Health and Aging, University of Wisconsin - Madison , Madison , WI , USA
| | - Rebecca L Koscik
- c University of Wisconsin - Madison , Madison , WI , USA
- d Wisconsin Alzheimer's Institute , University of Wisconsin School of Medicine and Public Health , Madison , WI , USA
| | - Ozioma C Okonkwo
- a Alzheimer's Disease Research Center , University of Wisconsin School of Medicine and Public Health , Madison , WI , USA
- c University of Wisconsin - Madison , Madison , WI , USA
- d Wisconsin Alzheimer's Institute , University of Wisconsin School of Medicine and Public Health , Madison , WI , USA
- e Geriatric Research Education and Clinical Center , William S. Middleton Memorial VA Hospital , Madison , WI , USA
| | - Paul E Peppard
- c University of Wisconsin - Madison , Madison , WI , USA
- f Department of Population Health Sciences , University of Wisconsin School of Medicine and Public Health , Madison , WI , USA
| | - Bruce P Hermann
- a Alzheimer's Disease Research Center , University of Wisconsin School of Medicine and Public Health , Madison , WI , USA
- c University of Wisconsin - Madison , Madison , WI , USA
- d Wisconsin Alzheimer's Institute , University of Wisconsin School of Medicine and Public Health , Madison , WI , USA
- g Department of Neurology , University of Wisconsin School of Medicine and Public Health , Madison , WI , USA
| | - Mark A Sager
- c University of Wisconsin - Madison , Madison , WI , USA
- d Wisconsin Alzheimer's Institute , University of Wisconsin School of Medicine and Public Health , Madison , WI , USA
| | - Sterling C Johnson
- a Alzheimer's Disease Research Center , University of Wisconsin School of Medicine and Public Health , Madison , WI , USA
- c University of Wisconsin - Madison , Madison , WI , USA
- d Wisconsin Alzheimer's Institute , University of Wisconsin School of Medicine and Public Health , Madison , WI , USA
- e Geriatric Research Education and Clinical Center , William S. Middleton Memorial VA Hospital , Madison , WI , USA
| | - Corinne D Engelman
- a Alzheimer's Disease Research Center , University of Wisconsin School of Medicine and Public Health , Madison , WI , USA
- c University of Wisconsin - Madison , Madison , WI , USA
- d Wisconsin Alzheimer's Institute , University of Wisconsin School of Medicine and Public Health , Madison , WI , USA
- f Department of Population Health Sciences , University of Wisconsin School of Medicine and Public Health , Madison , WI , USA
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Baker JE, Lim YY, Jaeger J, Ames D, Lautenschlager NT, Robertson J, Pietrzak RH, Snyder PJ, Villemagne VL, Rowe CC, Masters CL, Maruff P. Episodic Memory and Learning Dysfunction Over an 18-Month Period in Preclinical and Prodromal Alzheimer’s Disease. J Alzheimers Dis 2018; 65:977-988. [DOI: 10.3233/jad-180344] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Jenalle E. Baker
- The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
- Cooperative Research Centre for Mental Health, Carlton, Victoria, Australia
| | - Yen Ying Lim
- The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
| | - Judith Jaeger
- CognitionMetrics, LLC., Wilmington, DE, USA
- Albert Einstein College of Medicine, Bronx, NY, USA
| | - David Ames
- National Ageing Research Institute, Parkville, VIC, Australia
- Department of Psychiatry, Academic Unit for Psychiatry of Old Age, The University of Melbourne, St. George’s Hospital, Kew, VIC, Australia
| | - Nicola T. Lautenschlager
- Department of Psychiatry, Academic Unit for Psychiatry of Old Age, The University of Melbourne, St. George’s Hospital, Kew, VIC, Australia
| | - Joanne Robertson
- The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
| | - Robert H. Pietrzak
- U.S. Department of Veterans Affairs National Center for Posttraumatic Stress Disorder, Clinical Neurosciences Division, VA Connecticut Healthcare System, West Haven, CT, USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Peter J. Snyder
- Ryan Institute for Neuroscience, University of Rhode Island, Kingston, RI, USA
| | - Victor L. Villemagne
- The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
- Department of Nuclear Medicine and Centre for PET, Austin Health, Heidelberg, VIC, Australia
- Department of Medicine, Austin Health, The University of Melbourne, Heidelberg, VIC, Australia
| | - Christopher C. Rowe
- Department of Nuclear Medicine and Centre for PET, Austin Health, Heidelberg, VIC, Australia
- Department of Medicine, Austin Health, The University of Melbourne, Heidelberg, VIC, Australia
| | - Colin L. Masters
- The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
| | - Paul Maruff
- The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
- Cogstate Ltd., Melbourne, VIC, Australia
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20
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Yun HJ, Moon SH, Kim HJ, Lockhart SN, Choe YS, Lee KH, Na DL, Lee JM, Seo SW. Centiloid method evaluation for amyloid PET of subcortical vascular dementia. Sci Rep 2017; 7:16322. [PMID: 29176753 PMCID: PMC5701176 DOI: 10.1038/s41598-017-16236-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2017] [Accepted: 10/27/2017] [Indexed: 11/08/2022] Open
Abstract
Reference region selection is important for proper amyloid PET analysis, especially in subcortical vascular dementia (SVaD) patients. We investigated reference region differences between SVaD and Alzheimer's disease (AD) using Centiloid scores. In 57 [C-11] Pittsburgh compound B (PiB) positive (+) AD and 23 PiB (+) SVaD patients, we assessed standardized PiB uptake and Centiloid scores in disease-specific cortical regions, with several reference regions: cerebellar gray (CG), whole cerebellum (WC), WC with brainstem (WC + B), pons, and white matter (WM). We calculated disease group differences from young controls (YC) and YC variance according to reference region. SVaD patients showed large effect sizes (Cohen's d > 0.8) using all reference regions. WM and pons showed larger YC variances than other regions. Findings were similar for AD patients. CG, WC, and WC + B, but not WM or pons, are reliable reference regions for amyloid imaging analysis in SVaD.
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Affiliation(s)
- Hyuk Jin Yun
- Department of Biomedical Engineering, Hanyang University, Seoul, 04763, Korea
- Fetal Neonatal Neuroimaging and Developmental Science Center, Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, 02115, MA, USA
| | - Seung Hwan Moon
- Department of Nuclear Medicine, Sungkyunkwan University School of Medicine, Seoul, 06351, Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Korea
- Neuroscience Center, Samsung Medical Center, Seoul, 06351, Korea
| | - Samuel N Lockhart
- Helen Wills Neuroscience Institute, University of California, Berkeley, 94720, CA, USA
- Department of Internal Medicine, Division of Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, 27157, NC, USA
| | - Yearn Seong Choe
- Department of Nuclear Medicine, Sungkyunkwan University School of Medicine, Seoul, 06351, Korea
| | - Kyung Han Lee
- Department of Nuclear Medicine, Sungkyunkwan University School of Medicine, Seoul, 06351, Korea
| | - Duk L Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Korea
- Neuroscience Center, Samsung Medical Center, Seoul, 06351, Korea
- Department of Health Sciences and Technology, Sungkyunkwan University, Seoul, 06351, Korea
| | - Jong-Min Lee
- Department of Biomedical Engineering, Hanyang University, Seoul, 04763, Korea.
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Korea.
- Neuroscience Center, Samsung Medical Center, Seoul, 06351, Korea.
- Department of Health Sciences and Technology, Sungkyunkwan University, Seoul, 06351, Korea.
- Department of Clinical Research Design and Evaluation, SAIHST, Sungkyunkwan University, Seoul, 06351, Korea.
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Cortical β-amyloid burden, gray matter, and memory in adults at varying APOE ε4 risk for Alzheimer's disease. Neurobiol Aging 2017; 61:207-214. [PMID: 29111487 DOI: 10.1016/j.neurobiolaging.2017.09.027] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2017] [Revised: 09/03/2017] [Accepted: 09/26/2017] [Indexed: 01/16/2023]
Abstract
Models of preclinical Alzheimer's disease (AD) propose that cerebral amyloidosis leads to neurodegeneration and subsequent cognitive decline. This study investigated whether APOE genotype is related to β-amyloid (Aβ) burden in brain regions preferentially affected by AD and whether Aβ burden is associated with gray-matter (GM) fraction (as a marker of neurodegeneration) and episodic memory performance in cognitively normal middle-aged individuals at varying genetic risk for AD. Three groups of cognitively normal participants aged 50-65 years with a first-degree family history of AD (APOE genotype ε4ε4 [n = 15], ε3ε4 [n = 15], and ε3ε3 [n = 15]) underwent [11C]PiB positron emission tomography scans to quantify cortical Aβ, brain magnetic resonance imaging, and neuropsychological testing. APOE ε4ε4 participants demonstrated significantly higher cortical Aβ burden than APOE ε3ε3 (p < 0.001). Furthermore, cortical Aβ burden was inversely associated with cortical GM fraction (p = 0.017) but not episodic memory performance. In cognitively normal, middle-aged individuals, Aβ burden is significantly associated with GM fraction but not episodic memory performance. These findings are consistent with models of preclinical AD in which neurodegeneration occurs before manifest cognitive decline.
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Affiliation(s)
- Manja Koch
- aHarvard T.H. Chan School of Public Health, Department of Nutrition bChanning Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
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Baker JE, Lim YY, Pietrzak RH, Hassenstab J, Snyder PJ, Masters CL, Maruff P. Cognitive impairment and decline in cognitively normal older adults with high amyloid-β: A meta-analysis. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2016; 6:108-121. [PMID: 28239636 PMCID: PMC5315443 DOI: 10.1016/j.dadm.2016.09.002] [Citation(s) in RCA: 120] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
INTRODUCTION This meta-analysis aimed to characterize the nature and magnitude of amyloid (Aβ)-related cognitive impairment and decline in cognitively normal (CN) older individuals. METHOD MEDLINE Ovid was searched from 2012 to June 2016 for studies reporting relationships between cerebrospinal fluid or positron emission tomography (PET) Aβ levels and cognitive impairment (cross-sectional) and decline (longitudinal) in CN older adults. Neuropsychological data were classified into domains of episodic memory, executive function, working memory, processing speed, visuospatial function, semantic memory, and global cognition. Type of Aβ measure, how Aβ burden was analyzed, inclusion of control variables, and clinical criteria used to exclude participants, were considered as moderators. Random-effects models were used for analyses with effect sizes expressed as Cohen's d. RESULTS A total of 38 studies met inclusion criteria contributing 30 cross-sectional (N = 5005) and 14 longitudinal (N = 2584) samples. Aβ-related cognitive impairment was observed for global cognition (d = 0.32), visuospatial function (d = 0.25), processing speed (d = 0.18), episodic memory, and executive function (both d's = 0.15), with decline observed for global cognition (d = 0.30), semantic memory (d = 0.28), visuospatial function (d = 0.25), and episodic memory (d = 0.24). Aβ-related impairment was moderated by age, amyloid measure, type of analysis, and inclusion of control variables and decline moderated by amyloid measure, type of analysis, inclusion of control variables, and exclusion criteria used. DISCUSSION CN older adults with high Aβ show a small general cognitive impairment and small to moderate decline in episodic memory, visuospatial function, semantic memory, and global cognition.
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Affiliation(s)
- Jenalle E. Baker
- The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
- CRC for Mental Health, Carlton South, Victoria, Australia
| | - Yen Ying Lim
- The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
- Cogstate Ltd., Melbourne, Victoria, Australia
| | - Robert H. Pietrzak
- U.S. Department of Veterans Affairs National Center for Posttraumatic Stress Disorder, Clinical Neurosciences Division, VA Connecticut Healthcare System, West Haven, CT, USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Jason Hassenstab
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
- Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Peter J. Snyder
- Department of Neurology, Warren Alpert School of Medicine, Brown University, Providence, RI, USA
- Department of Neurology, Rhode Island Hospital & Alpert Medical School of Brown University, Providence, RI, USA
| | - Colin L. Masters
- The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
| | - Paul Maruff
- The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
- CRC for Mental Health, Carlton South, Victoria, Australia
- Cogstate Ltd., Melbourne, Victoria, Australia
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Detecting cognitive changes in preclinical Alzheimer's disease: A review of its feasibility. Alzheimers Dement 2016; 13:468-492. [PMID: 27702618 DOI: 10.1016/j.jalz.2016.06.2365] [Citation(s) in RCA: 117] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2016] [Revised: 05/31/2016] [Accepted: 06/18/2016] [Indexed: 11/23/2022]
Abstract
Significant progress has been made in characterizing the biological changes occurring in preclinical Alzheimer's disease (AD). Cognitive dysfunction has been viewed, however, as a late-stage phenomenon, despite increasing evidence that changes may be detected in the decades preceding dementia. In the absence of comprehensive evidence-based guidelines for preclinical cognitive assessment, longitudinal cohort and neuroimaging studies have been reviewed to determine the temporal order and brain biomarker correlates of specific cognitive functions. Episodic memory decline was observed to be the most salient cognitive function, correlating with high levels of amyloid deposition and hypoconnectivity across large-scale brain networks. Prospective studies point to early decline in both episodic and semantic memory processing as well as executive functions in the predementia period. The cognitive tests have, however, been principally those used to diagnose dementia. New procedures are required which target more finely the medial temporal lobe subregions first affected by clinically silent AD pathology.
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Longitudinal brain structural changes in preclinical Alzheimer's disease. Alzheimers Dement 2016; 13:499-509. [DOI: 10.1016/j.jalz.2016.08.010] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2016] [Revised: 08/22/2016] [Accepted: 08/23/2016] [Indexed: 01/30/2023]
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DADM: The first 2 years of the Alzheimer Association's open access journal to support the research and development of novel biomarkers and diagnostic approaches. Alzheimers Dement 2016; 12:755-7. [PMID: 27370207 DOI: 10.1016/j.jalz.2016.06.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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Wennberg AMV, Spira AP, Pettigrew C, Soldan A, Zipunnikov V, Rebok GW, Roses AD, Lutz MW, Miller MM, Thambisetty M, Albert MS. Blood glucose levels and cortical thinning in cognitively normal, middle-aged adults. J Neurol Sci 2016; 365:89-95. [PMID: 27206882 DOI: 10.1016/j.jns.2016.04.017] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2015] [Revised: 04/04/2016] [Accepted: 04/11/2016] [Indexed: 01/06/2023]
Abstract
Type II diabetes mellitus (DM) increases risk for cognitive decline and is associated with brain atrophy in older demented and non-demented individuals. We investigated (1) the cross-sectional association between fasting blood glucose level and cortical thickness in a sample of largely middle-aged, cognitively normal adults, and (2) whether these associations were modified by genes associated with both lipid processing and dementia. To explore possible modifications by genetic status, we investigated the interaction between blood glucose levels and the apolipoprotein E (APOE) ε4 allele and the translocase of the outer mitochondrial membrane (TOMM) 40 '523 genotype on cortical thickness. Cortical thickness measures were based on mean thickness in a subset of a priori-selected brain regions hypothesized to be vulnerable to atrophy in Alzheimer's disease (AD) (i.e., 'AD vulnerable regions'). Participants included 233 cognitively normal subjects in the BIOCARD study who had a measure of fasting blood glucose and cortical thickness measures, quantified by magnetic resonance imaging (MRI) scans. After adjustment for age, sex, race, education, depression, and medical conditions, higher blood glucose was associated with thinner parahippocampal gyri (B=-0.002; 95% CI -0.004, -0.0004) and temporal pole (B=-0.002; 95% CI -0.004, -0.0001), as well as reduced average thickness over AD vulnerable regions (B=-0.001; 95% CI -0.002, -0.0001). There was no evidence for greater cortical thinning in ε4 carriers of the APOE gene or in APOE ε3/3 individuals carrying the TOMM40 VL/VL genotypes. When individuals with glucose levels in the diabetic range (≥126mg/dL), were excluded from the analysis, the associations between glucose levels and cortical thickness were no longer significant. These findings suggest that glucose levels in the diabetic range are associated with reduced cortical thickness in AD vulnerable regions as early as middle age.
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Affiliation(s)
- Alexandra M V Wennberg
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe St., Baltimore, MD 21205, United States.
| | - Adam P Spira
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe St., Baltimore, MD 21205, United States; Department of Psychiatry and Behavioral Science, Johns Hopkins School of Medicine, 733 N. Broadway, Baltimore, MD 21205, United States; Johns Hopkins Center on Aging and Health, 2024 E. Monument St., Baltimore, MD 21205, United States.
| | - Corinne Pettigrew
- Department of Neurology, Johns Hopkins School of Medicine, 733 N. Broadway, Baltimore, MD 21205, United States.
| | - Anja Soldan
- Department of Neurology, Johns Hopkins School of Medicine, 733 N. Broadway, Baltimore, MD 21205, United States.
| | - Vadim Zipunnikov
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe St., Baltimore, MD 21205, United States; Johns Hopkins Center on Aging and Health, 2024 E. Monument St., Baltimore, MD 21205, United States.
| | - George W Rebok
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe St., Baltimore, MD 21205, United States; Department of Psychiatry and Behavioral Science, Johns Hopkins School of Medicine, 733 N. Broadway, Baltimore, MD 21205, United States; Johns Hopkins Center on Aging and Health, 2024 E. Monument St., Baltimore, MD 21205, United States.
| | - Allen D Roses
- Department of Neurology, Duke University School of Medicine, 8 Searle Center Dr., Durham, NC 27703, United States.
| | - Michael W Lutz
- Department of Neurology, Duke University School of Medicine, 8 Searle Center Dr., Durham, NC 27703, United States.
| | - Michael M Miller
- Department of Biomedical Engineering, Johns Hopkins University, 3400 N. Charles St., Baltimore, MD 21218, United States.
| | - Madhav Thambisetty
- Unit of Clinical and Translational Neuroscience, National Institute on Aging, 251 Bayview Blvd, Baltimore, MD 21224, United States.
| | - Marilyn S Albert
- Department of Neurology, Johns Hopkins School of Medicine, 733 N. Broadway, Baltimore, MD 21205, United States.
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Kassubek J, Müller HP. Computer-based magnetic resonance imaging as a tool in clinical diagnosis in neurodegenerative diseases. Expert Rev Neurother 2016; 16:295-306. [PMID: 26807776 DOI: 10.1586/14737175.2016.1146590] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Magnetic resonance imaging (MRI) is one of the core elements within the differential diagnostic work-up of patients with neurodegenerative diseases such as dementia syndromes, Parkinsonian syndromes, and motor neuron diseases. Currently, computerized MRI analyses are not routinely used for individual diagnosis; however, they have improved the anatomical understanding of pathomorphological alterations in various neurodegenerative diseases by quantitative comparisons between patients and controls at the group level. For multiparametric MRI protocols, including T1-weighted MRI, diffusion-weighted imaging, and intrinsic functional connectivity MRI, the potential as a surrogate marker is a subject of investigation. The additional value of MRI with respect to diagnosis at the individual level and for future disease-modifying multicentre trials remains to be defined. Here, we give an overview of recent applications of multiparametric MRI to patients with various neurodegenerative diseases. Starting from applications at the group level, continuous progress of a transfer to individual diagnostic classification is ongoing.
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Affiliation(s)
- Jan Kassubek
- a Department of Neurology , University of Ulm , Ulm , Germany
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Clark LR, Racine AM, Koscik RL, Okonkwo OC, Engelman CD, Carlsson CM, Asthana S, Bendlin BB, Chappell R, Nicholas CR, Rowley HA, Oh JM, Hermann BP, Sager MA, Christian BT, Johnson SC. Beta-amyloid and cognitive decline in late middle age: Findings from the Wisconsin Registry for Alzheimer's Prevention study. Alzheimers Dement 2016; 12:805-14. [PMID: 26806386 DOI: 10.1016/j.jalz.2015.12.009] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2015] [Revised: 10/23/2015] [Accepted: 12/07/2015] [Indexed: 12/11/2022]
Abstract
INTRODUCTION The present study investigated the relationship between beta-amyloid (Aβ) and cognition in a late middle-aged cohort at risk for Alzheimer's disease (AD). METHODS One eighty-four participants (mean age = 60; 72% parental history of AD) completed a [C-11]Pittsburgh compound B positron emission tomography scan and serial cognitive evaluations. A global measure of Aβ burden was calculated, and composite scores assessing learning, delayed memory, and executive functioning were computed. RESULTS Higher Aβ was associated with classification of psychometric mild cognitive impairment (MCI) at follow-up (P < .01). Linear mixed effects regression results indicated higher Aβ was associated with greater rates of decline in delayed memory (P < .01) and executive functioning (P < .05). Apolipoprotein E (APOE) ε4 status moderated the relationship between Aβ and cognitive trajectories (P values <.01). DISCUSSION In individuals at risk for AD, greater Aβ in late middle age is associated with increased likelihood of MCI at follow-up and steeper rates of cognitive decline.
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Affiliation(s)
- Lindsay R Clark
- Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
| | - Annie M Racine
- Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Institute on Aging, University of Wisconsin-Madison, Madison, WI, USA; Neuroscience and Public Policy Program, University of Wisconsin-Madison, Madison, WI, USA
| | - Rebecca L Koscik
- Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Ozioma C Okonkwo
- Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Geriatric Research Education and Clinical Center, Wm. S. Middleton Veterans Hospital, Madison, WI, USA
| | - Corinne D Engelman
- Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Department of Population Health Sciences, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Cynthia M Carlsson
- Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Geriatric Research Education and Clinical Center, Wm. S. Middleton Veterans Hospital, Madison, WI, USA
| | - Sanjay Asthana
- Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Geriatric Research Education and Clinical Center, Wm. S. Middleton Veterans Hospital, Madison, WI, USA
| | - Barbara B Bendlin
- Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Geriatric Research Education and Clinical Center, Wm. S. Middleton Veterans Hospital, Madison, WI, USA
| | - Rick Chappell
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, USA; Department of Statistics, University of Wisconsin-Madison, Madison, WI, USA
| | - Christopher R Nicholas
- Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Geriatric Research Education and Clinical Center, Wm. S. Middleton Veterans Hospital, Madison, WI, USA
| | - Howard A Rowley
- Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Jennifer M Oh
- Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Geriatric Research Education and Clinical Center, Wm. S. Middleton Veterans Hospital, Madison, WI, USA
| | - Bruce P Hermann
- Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Mark A Sager
- Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Bradley T Christian
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin-Madison, Madison, WI, USA; Department of Psychiatry, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Sterling C Johnson
- Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Geriatric Research Education and Clinical Center, Wm. S. Middleton Veterans Hospital, Madison, WI, USA; Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin-Madison, Madison, WI, USA
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PET Imaging of Epigenetic Influences on Alzheimer's Disease. Int J Alzheimers Dis 2015; 2015:575078. [PMID: 26600964 PMCID: PMC4633540 DOI: 10.1155/2015/575078] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2015] [Revised: 09/20/2015] [Accepted: 10/01/2015] [Indexed: 12/25/2022] Open
Abstract
The precise role of environment-gene interactions (epigenetics) in the development and progression of Alzheimer's disease (AD) is unclear. This review focuses on the premise that radiotracer-specific PET imaging allows clinicians to visualize epigenetically influenced events and that such imaging may provide new, valuable insights for preventing, diagnosing, and treating AD. Current understanding of the role of epigenetics in AD and the principles underlying the use of PET radiotracers for in vivo diagnosis are reviewed. The relative efficacies of various PET radiotracers for visualizing the epigenetic influences on AD and their use for diagnosis are discussed. For example, [18F]FAHA demonstrates sites of differential HDAC activity, [18F]FDG indirectly illuminates sites of neuronal hypomethylation, and the carbon-11 isotope-containing Pittsburgh compound B ([11C]PiB) images amyloid-beta plaque deposits. A definitive AD diagnosis is currently achievable only by postmortem histological observation of amyloid-beta plaques and tau neurofibrillary tangles. Therefore, reliable in vivo neuroimaging techniques could provide opportunities for early diagnosis and treatment of AD.
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