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Janssen E, van Dalen JW, Cai M, Jacob MA, Marques J, Duering M, Richard E, Tuladhar AM, de Leeuw FE, Hilkens N. Visit-to-visit blood pressure variability and progression of white matter hyperintensities over 14 years. Blood Press 2024; 33:2314498. [PMID: 38477113 DOI: 10.1080/08037051.2024.2314498] [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: 12/01/2023] [Accepted: 01/31/2024] [Indexed: 03/14/2024]
Abstract
Purpose: There is evidence that blood pressure variability (BPV) is associated with cerebral small vessel disease (SVD) and may therefore increase the risk of stroke and dementia. It remains unclear if BPV is associated with SVD progression over years. We examined whether visit-to-visit BPV is associated with white matter hyperintensity (WMH) progression over 14 years and MRI markers after 14 years. Materials and methods: We included participants with SVD from the Radboud University Nijmegen Diffusion tensor Magnetic resonance-imaging Cohort (RUNDMC) who underwent baseline assessment in 2006 and follow-up in 2011, 2015 and 2020. BPV was calculated as coefficient of variation (CV) of BP at all visits. Association between WMH progression rates over 14 years and BPV was examined using linear-mixed effects (LME) model. Regression models were used to examine association between BPV and MRI markers at final visit in participants. Results: A total of 199 participants (60.5 SD 6.6 years) who underwent four MRI scans and BP measurements were included, with mean follow-up of 13.7 (SD 0.5) years. Systolic BPV was associated with higher progression of WMH (β = 0.013, 95% CI 0.005 - 0.022) and higher risk of incident lacunes (OR: 1.10, 95% CI 1.01-1.21). There was no association between systolic BPV and grey and white matter volumes, Peak Skeleton of Mean Diffusivity (PSMD) or microbleed count after 13.7 years. Conclusions: Visit-to-visit systolic BPV is associated with increased progression of WMH volumes and higher risk of incident lacunes over 14 years in participants with SVD. Future studies are needed to examine causality of this association.
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Affiliation(s)
- Esther Janssen
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jan Willem van Dalen
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Mengfei Cai
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, PR China
| | - Mina A Jacob
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - José Marques
- Center for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
| | - Marco Duering
- Department of Biomedical Engineering, Medical Image Analysis Center (MIAC AG) and qbig, University of Basel, Basel, Switzerland
| | - Edo Richard
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Public and Occupational Health, AMC, Amsterdam Public Health Research Institute, Amsterdam University Medical Center, Amsterdam, the Netherlands
| | - Anil M Tuladhar
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Frank-Erik de Leeuw
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Nina Hilkens
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
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Qian Z, Wang Z, Li B, Meng X, Kuang Z, Li Y, Yang Y, Ye K. Thy1-ApoE4/C/EBPβ double transgenic mice act as a sporadic model with Alzheimer's disease. Mol Psychiatry 2024; 29:3040-3055. [PMID: 38658772 PMCID: PMC11449781 DOI: 10.1038/s41380-024-02565-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 04/10/2024] [Accepted: 04/15/2024] [Indexed: 04/26/2024]
Abstract
Early onset familial Alzheimer's disease (FAD) with APP, PS1/2 (presenilins) mutation accounts for only a small portion of AD cases, and most are late-onset sporadic. However, majority of AD mouse models are developed to mimic the genetic cause of human AD by overexpressing mutated forms of human APP, PS1/2, and/or Tau protein, though there is no Tau mutation in AD, and no single mouse model recapitulates all aspects of AD pathology. Here, we report Thy1-ApoE4/C/EBPβ double transgenic mouse model that demonstrates key AD pathologies in an age-dependent manner in absence of any human APP or PS1/2 mutation. Using the clinical diagnosis criteria, we show that this mouse model exhibits tempo-spatial features in AD patient brains, including progressive cognitive decline associated with brain atrophy, which is accompanied with extensive neuronal degeneration. Remarkably, the mice display gradual Aβ aggregation and neurofibrillary tangles formation in the brain validated by Aβ PET and Tau PET. Moreover, the mice reveal widespread neuroinflammation as shown in AD brains. Hence, Thy1-ApoE4/C/EBPβ mouse model acts as a sporadic AD mouse model, reconstituting the major AD pathologies.
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Affiliation(s)
- Zhengjiang Qian
- Faculty of Life and Health Sciences, Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institute of Advanced Technology (SIAT), Chinese Academy of Sciences, Shenzhen, 518055, Guangdong, China
| | - ZhiHao Wang
- Department of Neurology, Renmin Hospital of Wuhan University, Wuhan, Hubei Province, 430060, China
| | - Bowei Li
- Shenzhen Institute of Advanced Technology, University of Chinese Academy of Science, Shenzhen, Guangdong Province, 518055, China
| | - Xin Meng
- Faculty of Life and Health Sciences, Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institute of Advanced Technology (SIAT), Chinese Academy of Sciences, Shenzhen, 518055, Guangdong, China
| | - Zhonghua Kuang
- Paul C. Lauterbur Research Center for Biomedical Imaging, Institute of Biomedical and Health Engineering, Shenzhen Institute of Advanced Technology (SIAT), Chinese Academy of Sciences, Shenzhen, 518055, Guangdong, China
| | - Yanjiao Li
- Faculty of Life and Health Sciences, Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institute of Advanced Technology (SIAT), Chinese Academy of Sciences, Shenzhen, 518055, Guangdong, China
| | - Yongfeng Yang
- Paul C. Lauterbur Research Center for Biomedical Imaging, Institute of Biomedical and Health Engineering, Shenzhen Institute of Advanced Technology (SIAT), Chinese Academy of Sciences, Shenzhen, 518055, Guangdong, China
| | - Keqiang Ye
- Faculty of Life and Health Sciences, Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institute of Advanced Technology (SIAT), Chinese Academy of Sciences, Shenzhen, 518055, Guangdong, China.
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Denning AE, Ittyerah R, Levorse LM, Sadeghpour N, Athalye C, Chung E, Ravikumar S, Dong M, Duong MT, Li Y, Ilesanmi A, Sreepada LP, Sabatini P, Lowe M, Bahena A, Zablah J, Spencer BE, Watanabe R, Kim B, Sørensen MH, Khandelwal P, Brown C, Hrybouski S, Xie SX, de Flores R, Robinson JL, Schuck T, Ohm DT, Arezoumandan S, Porta S, Detre JA, Insausti R, Wisse LEM, Das SR, Irwin DJ, Lee EB, Wolk DA, Yushkevich PA. Association of quantitative histopathology measurements with antemortem medial temporal lobe cortical thickness in the Alzheimer's disease continuum. Acta Neuropathol 2024; 148:37. [PMID: 39227502 PMCID: PMC11371872 DOI: 10.1007/s00401-024-02789-9] [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: 05/08/2024] [Revised: 08/07/2024] [Accepted: 08/15/2024] [Indexed: 09/05/2024]
Abstract
The medial temporal lobe (MTL) is a hotspot for neuropathology, and measurements of MTL atrophy are often used as a biomarker for cognitive decline associated with neurodegenerative disease. Due to the aggregation of multiple proteinopathies in this region, the specific relationship of MTL atrophy to distinct neuropathologies is not well understood. Here, we develop two quantitative algorithms using deep learning to measure phosphorylated tau (p-tau) and TDP-43 (pTDP-43) pathology, which are both known to accumulate in the MTL and are associated with MTL neurodegeneration. We focus on these pathologies in the context of Alzheimer's disease (AD) and limbic predominant age-related TDP-43 encephalopathy (LATE) and apply our deep learning algorithms to distinct histology sections, on which MTL subregions were digitally annotated. We demonstrate that both quantitative pathology measures show high agreement with expert visual ratings of pathology and discriminate well between pathology stages. In 140 cases with antemortem MR imaging, we compare the association of semi-quantitative and quantitative postmortem measures of these pathologies in the hippocampus with in vivo structural measures of the MTL and its subregions. We find widespread associations of p-tau pathology with MTL subregional structural measures, whereas pTDP-43 pathology had more limited associations with the hippocampus and entorhinal cortex. Quantitative measurements of p-tau pathology resulted in a significantly better model of antemortem structural measures than semi-quantitative ratings and showed strong associations with cortical thickness and volume. By providing a more granular measure of pathology, the quantitative p-tau measures also showed a significant negative association with structure in a severe AD subgroup where semi-quantitative ratings displayed a ceiling effect. Our findings demonstrate the advantages of using quantitative neuropathology to understand the relationship of pathology to structure, particularly for p-tau, and motivate the use of quantitative pathology measurements in future studies.
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Affiliation(s)
- Amanda E Denning
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
| | - Ranjit Ittyerah
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Lisa M Levorse
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Chinmayee Athalye
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Eunice Chung
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Sadhana Ravikumar
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Mengjin Dong
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Michael Tran Duong
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Yue Li
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Ademola Ilesanmi
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Lasya P Sreepada
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Philip Sabatini
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - MaKayla Lowe
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Alejandra Bahena
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Jamila Zablah
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Barbara E Spencer
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Ryohei Watanabe
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Neurodegenerative Disease Research, Institute On Aging, University of Pennsylvania, Philadelphia, PA, USA
| | - Boram Kim
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Neurodegenerative Disease Research, Institute On Aging, University of Pennsylvania, Philadelphia, PA, USA
| | - Maja Højvang Sørensen
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Neurodegenerative Disease Research, Institute On Aging, University of Pennsylvania, Philadelphia, PA, USA
| | - Pulkit Khandelwal
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Christopher Brown
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Sharon X Xie
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, USA
| | - Robin de Flores
- UMR-S U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, INSERM, Caen-Normandie University, GIP Cyceron, Caen, France
| | - John L Robinson
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Neurodegenerative Disease Research, Institute On Aging, University of Pennsylvania, Philadelphia, PA, USA
| | - Theresa Schuck
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Neurodegenerative Disease Research, Institute On Aging, University of Pennsylvania, Philadelphia, PA, USA
| | - Daniel T Ohm
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Sanaz Arezoumandan
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Sílvia Porta
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Neurodegenerative Disease Research, Institute On Aging, University of Pennsylvania, Philadelphia, PA, USA
| | - John A Detre
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Ricardo Insausti
- Human Neuroanatomy Lab, University of Castilla La Mancha, Albacete, Spain
| | - Laura E M Wisse
- Department of Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Sandhitsu R Das
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - David J Irwin
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Edward B Lee
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Neurodegenerative Disease Research, Institute On Aging, University of Pennsylvania, Philadelphia, PA, USA
| | - David A Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Paul A Yushkevich
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
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Dallaire-Théroux C, Smith C, Duchesne S. Clinical Predictors of Postmortem Amyloid and Nonamyloid Cerebral Small Vessel Disease in Middle-Aged to Older Adults. Neurol Clin Pract 2024; 14:e200271. [PMID: 38525067 PMCID: PMC10959170 DOI: 10.1212/cpj.0000000000200271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 01/09/2024] [Indexed: 03/26/2024]
Abstract
Background and Objectives Sporadic cerebral small vessel disease (CSVD) is a class of important pathologic processes known to affect the aging brain and to contribute to cognitive impairment. We aimed to identify clinical risk factors associated with postmortem CSVD in middle-aged to older adults. Methods We developed and tested risk models for their predictive accuracy of a pathologic diagnosis of nonamyloid CSVD and cerebral amyloid angiopathy (CAA) in a retrospective sample of 160 autopsied cases from the Edinburgh Brain Bank. Individuals aged 40 years and older covering the spectrum of healthy aging and common forms of dementia (i.e., highly-prevalent etiologies such as Alzheimer disease (AD), vascular cognitive impairment (VCI), and mixed dementia) were included. We performed binomial logistic regression models using sample splitting and cross-validation methods. Demographics, lifestyle habits, traditional vascular risk factors, chronic medical conditions, APOE4, and cognitive status were assessed as potential predictors. Results Forty percent of our sample had a clinical diagnosis of dementia (AD = 33, VCI = 26 and mixed = 5) while others were cognitively healthy (n = 96). The mean age at death was 73.8 (SD 14.1) years, and 40% were female. The presence of none-to-mild vs moderate-to-severe nonamyloid CSVD was predicted by our model with good accuracy (area under the curve [AUC] = 0.84, sensitivity [SEN] = 72%, specificity [SPE] = 95%), with the most significant clinical predictors being age, history of cerebrovascular events, and cognitive impairment. The presence of CAA pathology was also predicted with high accuracy (AUC = 0.86, SEN = 93%, SPE = 79%). Significant predictors included alcohol intake, history of cerebrovascular events, and cognitive impairment. In a subset of atypical dementias (n = 24), our models provided poor predictive performance for both nonamyloid CSVD (AUC = 0.50) and CAA (AUC = 0.43). Discussion CSVD pathology can be predicted with high accuracy based on clinical factors in patients within the spectrum of AD, VCI, and normal aging. Whether this prediction can be enhanced by the addition of fluid and neuroimaging biomarkers warrants additional study. Improving our understanding of clinical determinants of vascular brain health may lead to novel strategies in the prevention and treatment of vascular etiologies contributing to cognitive decline. Classification of Evidence This study provides Class II evidence that selected clinical factors accurately distinguish between middle-aged to older adults with and without cerebrovascular small vessel disease (amyloid and nonamyloid) pathology.
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Affiliation(s)
- Caroline Dallaire-Théroux
- CERVO Brain Research Center (CD-T, SD); Faculty of Medicine (CD-T), Université Laval; Department of Neurological Sciences (CD-T), Centre Hospitalier Universitaire de Québec, Canada; Academic Neuropathology (CS), Centre for Clinical Brain Sciences, University of Edinburgh, United Kingdom; and Department of Radiology and Nuclear Medicine (SD), Faculty of Medicine, Université Laval, Quebec City, Canada
| | - Colin Smith
- CERVO Brain Research Center (CD-T, SD); Faculty of Medicine (CD-T), Université Laval; Department of Neurological Sciences (CD-T), Centre Hospitalier Universitaire de Québec, Canada; Academic Neuropathology (CS), Centre for Clinical Brain Sciences, University of Edinburgh, United Kingdom; and Department of Radiology and Nuclear Medicine (SD), Faculty of Medicine, Université Laval, Quebec City, Canada
| | - Simon Duchesne
- CERVO Brain Research Center (CD-T, SD); Faculty of Medicine (CD-T), Université Laval; Department of Neurological Sciences (CD-T), Centre Hospitalier Universitaire de Québec, Canada; Academic Neuropathology (CS), Centre for Clinical Brain Sciences, University of Edinburgh, United Kingdom; and Department of Radiology and Nuclear Medicine (SD), Faculty of Medicine, Université Laval, Quebec City, Canada
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Satizabal CL, Beiser AS, Fletcher E, Seshadri S, DeCarli C. A novel neuroimaging signature for ADRD risk stratification in the community. Alzheimers Dement 2024; 20:1881-1893. [PMID: 38147416 PMCID: PMC10984488 DOI: 10.1002/alz.13600] [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: 02/06/2023] [Revised: 11/20/2023] [Accepted: 11/21/2023] [Indexed: 12/28/2023]
Abstract
INTRODUCTION Early risk stratification for clinical dementia could lead to preventive therapies. We identified and validated a magnetic resonance imaging (MRI) signature for Alzheimer's disease (AD) and related dementias (ARDR). METHODS An MRI ADRD signature was derived from cortical thickness maps in Framingham Heart Study (FHS) participants with AD dementia and matched controls. The signature was related to the risk of ADRD and cognitive function in FHS. Results were replicated in the University of California Davis Alzheimer's Disease Research Center (UCD-ADRC) cohort. RESULTS Participants in the bottom quartile of the signature had more than three times increased risk for ADRD compared to those in the upper three quartiles (P < 0.001). Greater thickness in the signature was related to better general cognition (P < 0.01) and episodic memory (P = 0.01). Results replicated in UCD-ADRC. DISCUSSION We identified a robust neuroimaging biomarker for persons at increased risk of ADRD. Other cohorts will further test the validity of this biomarker.
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Affiliation(s)
- Claudia L. Satizabal
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health Sciences CenterSan AntonioTexasUSA
- Department of NeurologyBoston University School of MedicineBostonMassachusettsUSA
- The Framingham Heart StudyFraminghamMassachusettsUSA
| | - Alexa S. Beiser
- Department of NeurologyBoston University School of MedicineBostonMassachusettsUSA
- The Framingham Heart StudyFraminghamMassachusettsUSA
- Department of BiostatisticsBoston University School of Public HealthBostonMassachusettsUSA
| | - Evan Fletcher
- IDeA LaboratoryDepartment of NeurologyUniversity of California DavisDavisCaliforniaUSA
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health Sciences CenterSan AntonioTexasUSA
- Department of NeurologyBoston University School of MedicineBostonMassachusettsUSA
- The Framingham Heart StudyFraminghamMassachusettsUSA
| | - Charles DeCarli
- IDeA LaboratoryDepartment of NeurologyUniversity of California DavisDavisCaliforniaUSA
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Zhou J, Zhao M, Yang Z, Chen L, Liu X. Exploring the Value of MRI Measurement of Hippocampal Volume for Predicting the Occurrence and Progression of Alzheimer's Disease Based on Artificial Intelligence Deep Learning Technology and Evidence-Based Medicine Meta-Analysis. J Alzheimers Dis 2024; 97:1275-1288. [PMID: 38277290 DOI: 10.3233/jad-230733] [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: 01/28/2024]
Abstract
BACKGROUND Alzheimer's disease (AD), a major dementia cause, lacks effective treatment. MRI-based hippocampal volume measurement using artificial intelligence offers new insights into early diagnosis and intervention in AD progression. OBJECTIVE This study, involving 483 AD patients, 756 patients with mild cognitive impairment (MCI), and 968 normal controls (NC), investigated the predictive capability of MRI-based hippocampus volume measurements for AD risk using artificial intelligence and evidence-based medicine. METHODS Utilizing data from ADNI and OASIS-brains databases, three convolutional neural networks (InceptionResNetv2, Densenet169, and SEResNet50) were employed for automated AD classification based on structural MRI imaging. A multitask deep learning model and a densely connected 3D convolutional network were utilized. Additionally, a systematic meta-analysis explored the value of MRI-based hippocampal volume measurement in predicting AD occurrence and progression, drawing on 23 eligible articles from PubMed and Embase databases. RESULTS InceptionResNetv2 outperformed other networks, achieving 99.75% accuracy and 100% AUC for AD-NC classification and 99.16% accuracy and 100% AUC for MCI-NC classification. Notably, at a 512×512 size, InceptionResNetv2 demonstrated a classification accuracy of 94.29% and an AUC of 98% for AD-NC and 97.31% accuracy and 98% AUC for MCI-NC. CONCLUSIONS The study concludes that MRI-based hippocampal volume changes effectively predict AD onset and progression, facilitating early intervention and prevention.
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Affiliation(s)
- Jianguo Zhou
- Department of Radiology, Lianyungang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Lianyungang, China
| | - Mingli Zhao
- Department of Radiology, The Fourth People's Hospital of Lianyungang Affiliated to Nanjing Medical University Kangda, Lianyungang, China
| | - Zhou Yang
- Department of Rehabilitation, Lianyungang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Lianyungang, China
| | - Liping Chen
- Department of Rehabilitation, Lianyungang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Lianyungang, China
| | - Xiaoli Liu
- Department of Rehabilitation, Lianyungang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Lianyungang, China
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Wu KY, Lin KJ, Chen CH, Liu CY, Wu YM, Yen TC, Hsiao IT. Atrophy, hypometabolism and implication regarding pathology in late-life major depression with suspected non-alzheimer pathophysiology (SNAP). Biomed J 2023; 46:100589. [PMID: 36914051 PMCID: PMC10749882 DOI: 10.1016/j.bj.2023.03.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 07/16/2022] [Accepted: 03/08/2023] [Indexed: 03/13/2023] Open
Abstract
BACKGROUND A substantial proportion of individuals with late-life major depression could be classified as having a suspected non-Alzheimer disease pathophysiology (SNAP), as indicated by a negative test for the biomarker β-amyloid (Aβ-) but a positive test for neurodegeneration (ND+). This study investigated the clinical features, characteristic patterns of brain atrophy and hypometabolism, and implications regarding pathology in this population. METHODS Forty-six amyloid-negative patients with late-life major depressive disorder (MDD) patients, including 23 SNAP (Aβ-/ND+) and 23 Aβ-/ND- MDD subjects, and 22 Aβ-/ND-healthy control subjects were included in this study. Voxel-wise group comparisons between the SNAP MDD, Aβ-/ND- MDD and control subjects were performed, adjusting for age, gender and level of education. For exploratory comparisons, 8 Aβ+/ND- and 4 Aβ+/ND + MDD patients were included in the Supplementary Material. RESULTS The SNAP MDD patients had atrophy extending to regions outside the hippocampus, predominately in the medial temporal, dorsomedial and ventromedial prefrontal cortex; hypometabolism involving a large portion of the lateral and medial prefrontal cortex in addition to the bilateral temporal, parietal and precuneus cortex within typical Alzheimer disease regions were observed. Metabolism ratios of the inferior to the medial temporal lobe were significantly elevated in the SNAP MDD patients. We further discussed the implications with regards to underlying pathologies. CONCLUSION The present study demonstrated characteristic patterns of atrophy and hypometabolism in patients with late-life major depression with SNAP. Identifying individuals with SNAP MDD may provide insights into currently unspecified neurodegenerative processes. Future refinement of neurodegeneration biomarkers is essential in order to identify potential pathological correlates while in vivo reliable pathological biomarkers are not forthcoming.
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Affiliation(s)
- Kuan-Yi Wu
- Department of Psychiatry, Chang Gung Memorial Hospital, Taoyuan, Taiwan; College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Kun-Ju Lin
- Department of Nuclear Medicine and Center for Advanced Molecular Imaging and Translation, Chang Gung Memorial Hospital, Taoyuan, Taiwan; Department of Medical Imaging and Radiological Sciences and Healthy Aging Research Center, Chang Gung University, Taoyuan, Taiwan; Neuroscience Research Center, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Chia-Hsiang Chen
- Department of Psychiatry, Chang Gung Memorial Hospital, Taoyuan, Taiwan; College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Chia-Yih Liu
- Department of Psychiatry, Chang Gung Memorial Hospital, Taoyuan, Taiwan; College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Yi-Ming Wu
- Department of Radiology, Chang Gung Memorial Hospital, Taoyuan, Taiwan
| | - Tzu-Chen Yen
- Department of Nuclear Medicine and Center for Advanced Molecular Imaging and Translation, Chang Gung Memorial Hospital, Taoyuan, Taiwan; Department of Medical Imaging and Radiological Sciences and Healthy Aging Research Center, Chang Gung University, Taoyuan, Taiwan; APRINOIA Therapeutics Inc., Taipei, Taiwan
| | - Ing-Tsung Hsiao
- Department of Nuclear Medicine and Center for Advanced Molecular Imaging and Translation, Chang Gung Memorial Hospital, Taoyuan, Taiwan; Department of Medical Imaging and Radiological Sciences and Healthy Aging Research Center, Chang Gung University, Taoyuan, Taiwan.
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Niedowicz DM, Katsumata Y, Nelson PT. In severe ADNC, hippocampi with comorbid LATE-NC and hippocampal sclerosis have substantially more astrocytosis than those with LATE-NC or hippocampal sclerosis alone. J Neuropathol Exp Neurol 2023; 82:987-994. [PMID: 37935530 PMCID: PMC10658353 DOI: 10.1093/jnen/nlad085] [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: 11/09/2023] Open
Abstract
Limbic-predominant age-related TDP-43 encephalopathy neuropathologic change (LATE-NC) and hippocampal sclerosis of aging (HS-A) pathologies are found together at autopsy in ∼20% of elderly demented persons. Although astrocytosis is known to occur in neurodegenerative diseases, it is currently unknown how the severity of astrocytosis is correlated with the common combinations of pathologies in aging brains. To address this knowledge gap, we analyzed a convenience sample of autopsied subjects from the University of Kentucky Alzheimer's Disease Research Center community-based autopsy cohort. The subjects were stratified into 5 groups (n = 51 total): pure ADNC, ADNC + LATE-NC, ADNC + HS-A, ADNC + LATE-NC + HS-A, and low-pathology controls. Following GFAP immunostaining and digital slide scanning with a ScanScope, we measured GFAP-immunoreactive astrocytosis. The severities of GFAP-immunoreactive astrocytosis in hippocampal subfield CA1 and subiculum were compared between groups. The group with ADNC + LATE-NC + HS-A had the most astrocytosis as operationalized by either any GFAP+ or strong GFAP+ immunoreactivity in both CA1 and subiculum. In comparison to that pathologic combination, ADNC + HS or ADNC + LATE-NC alone showed lower astrocytosis. Pure ADNC had only marginally increased astrocytosis in CA1 and subiculum, in comparison to low-pathology controls. We conclude that there appeared to be pathogenetic synergy such that ADNC + LATE-NC + HS-A cases had relatively high levels of astrocytosis in the hippocampal formation.
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Złotek M, Kurowska A, Herbet M, Piątkowska-Chmiel I. GLP-1 Analogs, SGLT-2, and DPP-4 Inhibitors: A Triad of Hope for Alzheimer's Disease Therapy. Biomedicines 2023; 11:3035. [PMID: 38002034 PMCID: PMC10669527 DOI: 10.3390/biomedicines11113035] [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: 10/22/2023] [Revised: 11/07/2023] [Accepted: 11/10/2023] [Indexed: 11/26/2023] Open
Abstract
Alzheimer's is a prevalent, progressive neurodegenerative disease marked by cognitive decline and memory loss. The disease's development involves various pathomechanisms, including amyloid-beta accumulation, neurofibrillary tangles, oxidative stress, inflammation, and mitochondrial dysfunction. Recent research suggests that antidiabetic drugs may enhance neuronal survival and cognitive function in diabetes. Given the well-documented correlation between diabetes and Alzheimer's disease and the potential shared mechanisms, this review aimed to comprehensively assess the potential of new-generation anti-diabetic drugs, such as GLP-1 analogs, SGLT-2 inhibitors, and DPP-4 inhibitors, as promising therapeutic approaches for Alzheimer's disease. This review aims to comprehensively assess the potential therapeutic applications of novel-generation antidiabetic drugs, including GLP-1 analogs, SGLT-2 inhibitors, and DPP-4 inhibitors, in the context of Alzheimer's disease. In our considered opinion, antidiabetic drugs offer a promising avenue for groundbreaking developments and have the potential to revolutionize the landscape of Alzheimer's disease treatment.
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Affiliation(s)
| | | | | | - Iwona Piątkowska-Chmiel
- Department of Toxicology, Faculty of Pharmacy, Medical University of Lublin, Jaczewskiego 8b Street, 20-090 Lublin, Poland; (M.Z.); (A.K.); (M.H.)
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10
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Alosco ML, Tripodis Y, Baucom ZH, Adler CH, Balcer LJ, Bernick C, Mariani ML, Au R, Banks SJ, Barr WB, Wethe JV, Cantu RC, Coleman MJ, Dodick DW, McClean MD, McKee AC, Mez J, Palmisano JN, Martin B, Hartlage K, Lin AP, Koerte IK, Cummings JL, Reiman EM, Stern RA, Shenton ME, Bouix S. White matter hyperintensities in former American football players. Alzheimers Dement 2023; 19:1260-1273. [PMID: 35996231 PMCID: PMC10351916 DOI: 10.1002/alz.12779] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Revised: 06/24/2022] [Accepted: 07/27/2022] [Indexed: 11/11/2022]
Abstract
INTRODUCTION The presentation, risk factors, and etiologies of white matter hyperintensities (WMH) in people exposed to repetitive head impacts are unknown. We examined the burden and distribution of WMH, and their association with years of play, age of first exposure, and clinical function in former American football players. METHODS A total of 149 former football players and 53 asymptomatic unexposed participants (all men, 45-74 years) completed fluid-attenuated inversion recovery magnetic resonance imaging, neuropsychological testing, and self-report neuropsychiatric measures. Lesion Segmentation Toolbox estimated WMH. Analyses were performed in the total sample and stratified by age 60. RESULTS In older but not younger participants, former football players had greater total, frontal, temporal, and parietal log-WMH compared to asymptomatic unexposed men. In older but not younger former football players, greater log-WMH was associated with younger age of first exposure to football and worse executive function. DISCUSSION In older former football players, WMH may have unique presentations, risk factors, and etiologies. HIGHLIGHTS Older but not younger former football players had greater total, frontal, temporal, and parietal lobe white matter hyperintensities (WMH) compared to same-age asymptomatic unexposed men. Younger age of first exposure to football was associated with greater WMH in older but not younger former American football players. In former football players, greater WMH was associated with worse executive function and verbal memory.
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Affiliation(s)
- Michael L. Alosco
- Boston University Alzheimer’s Disease Research Center, Boston University CTE Center, Department of Neurology, Boston University School of Medicine, Boston, MA
| | - Yorghos Tripodis
- Boston University Alzheimer’s Disease Research Center, Boston University CTE Center, Boston University School of Medicine, Boston, MA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Zachary H. Baucom
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Charles H. Adler
- Department of Neurology, Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale, AZ
| | - Laura J. Balcer
- Departments of Neurology, Population Health and Ophthalmology, NYU Grossman School of Medicine, New York, NY
| | - Charles Bernick
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV
- Department of Neurology, University of Washington, Seattle, WA
| | - Megan L. Mariani
- Boston University Alzheimer’s Disease Research Center, Boston University CTE Center, Boston University School of Medicine, Boston, MA
| | - Rhoda Au
- Boston University Alzheimer’s Disease Research Center, Boston University CTE Center, Department of Neurology, Boston University School of Medicine, Boston, MA
- Framingham Heart Study, Framingham, MA
- Slone Epidemiology Center, Boston University, Boston, MA
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA
| | - Sarah J. Banks
- Departments of Neuroscience and Psychiatry, University of California, San Diego, CA
| | - William B. Barr
- Department of Neurology, NYU Grossman School of Medicine, New York, NY
| | - Jennifer V. Wethe
- Department of Psychiatry and Psychology, Mayo Clinic School of Medicine, Mayo Clinic Arizona, Scottsdale, AZ
| | - Robert C. Cantu
- Boston University Alzheimer’s Disease Research Center, Boston University CTE Center, Department of Neurology, Boston University School of Medicine, Boston, MA
| | - Michael J. Coleman
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Boston, MA
| | - David W. Dodick
- Department of Neurology, Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale, AZ
| | - Michael D. McClean
- Department of Environmental Health, Boston University School of Public Health, Boston, MA
| | - Ann C. McKee
- Boston University Alzheimer’s Disease Research Center, Boston University CTE Center, Department of Neurology, Boston University School of Medicine, Boston, MA
- VA Boston Healthcare System, Boston, MA
| | - Jesse Mez
- Boston University Alzheimer’s Disease Research Center, Boston University CTE Center, Department of Neurology, Boston University School of Medicine, Boston, MA
- Framingham Heart Study, Framingham, MA
| | - Joseph N. Palmisano
- Biostatistics and Epidemiology Data Analytics Center (BEDAC), Boston University School of Public Health, Boston, MA
| | - Brett Martin
- Biostatistics and Epidemiology Data Analytics Center (BEDAC), Boston University School of Public Health, Boston, MA
| | - Kaitlin Hartlage
- Biostatistics and Epidemiology Data Analytics Center (BEDAC), Boston University School of Public Health, Boston, MA
| | - Alexander P. Lin
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Boston, MA
- Center for Clinical Spectroscopy, Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - Inga K. Koerte
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Boston, MA
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwigs-Maximilians-Universität, Munich, Germany
| | - Jeffrey L. Cummings
- Chambers-Grundy Center for Transformative Neuroscience, Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas, Las Vegas, NV
| | - Eric M. Reiman
- Banner Alzheimer’s Institute, University of Arizona, Arizona State University, Translational Genomics Research Institute, and Arizona Alzheimer’s Consortium, Phoenix, AZ
| | - Robert A. Stern
- Boston University Alzheimer’s Disease Research Center, Boston University CTE Center, Department of Neurology, Boston University School of Medicine, Boston, MA
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA
- Department of Neurosurgery, Boston University School of Medicine, Boston, MA
| | - Martha E. Shenton
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Boston, MA
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - Sylvain Bouix
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Boston, MA
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Ortega-Cruz D, Eugenio Iglesias J, Rabano A, Strange B. Hippocampal sclerosis of aging at post-mortem is evident on MRI more than a decade prior. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.08.531683. [PMID: 36945448 PMCID: PMC10028863 DOI: 10.1101/2023.03.08.531683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2023]
Abstract
INTRODUCTION Hippocampal sclerosis of aging (HS) is an important component of combined dementia neuropathology. However, the temporal evolution of its histologically-defined features is unknown. We investigated pre-mortem longitudinal hippocampal atrophy associated with HS, as well as with other dementia-associated pathologies. METHODS We analyzed hippocampal volumes from MRI segmentations in 64 dementia patients with longitudinal MRI follow-up and post-mortem neuropathological evaluation, including HS assessment in the hippocampal head and body. RESULTS Significant HS-associated hippocampal volume changes were observed thoughout the evaluated timespan, up to 11.75 years before death. These changes were independent of age and Alzheimer’s Disease (AD) burden, and specifically driven by CA1 and subiculum. AD burden, but not HS, significantly associated with the rate of hippocampal atrophy. DISCUSSION HS-associated volume changes are detectable on MRI earlier than 10 years before death. These findings could contribute to the derivation of volumetric cut-offs for in vivo differentiation between HS and AD.
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Affiliation(s)
- Diana Ortega-Cruz
- Laboratory for Clinical Neuroscience, Center for Biomedical Technology, Universidad Politécnica de Madrid, IdISSC, Madrid, Spain
- Alzheimer’s Disease Research Unit, CIEN Foundation, Queen Sofia Foundation Alzheimer Center, Madrid, Spain
| | - Juan Eugenio Iglesias
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Boston, MA, USA
- Centre for Medical Image Computing, University College London, London, UK
| | - Alberto Rabano
- Alzheimer’s Disease Research Unit, CIEN Foundation, Queen Sofia Foundation Alzheimer Center, Madrid, Spain
| | - Bryan Strange
- Laboratory for Clinical Neuroscience, Center for Biomedical Technology, Universidad Politécnica de Madrid, IdISSC, Madrid, Spain
- Alzheimer’s Disease Research Unit, CIEN Foundation, Queen Sofia Foundation Alzheimer Center, Madrid, Spain
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12
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Canário NS, Jorge LP, Santana IJ, Castelo-Branco MS. Hemispheric Patterns of Recruitment of Object Processing Regions in Early Alzheimer's Disease: A Study Along the Entire Ventral Stream. J Alzheimers Dis 2023; 91:1151-1164. [PMID: 36565110 PMCID: PMC9912740 DOI: 10.3233/jad-220055] [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] [Indexed: 12/24/2022]
Abstract
BACKGROUND Investigation of neural response patterns along the entire network of functionally defined object recognition ventral stream regions in Alzheimer's disease (AD) is surprisingly lacking. OBJECTIVE We aimed to investigate putative functional reorganization along a wide-ranging network of known regions in the ventral visual stream in mild AD. METHODS Overall we investigated 6 regions of interest (5 of which were not investigated before), in 19 AD patients and 19 controls, in both hemispheres along the ventral visual stream: Fusiform Face Area, Fusiform Body Area, Extrastriate Body Area, Lateral Occipital Cortex, Parahippocampal Place Area, and Visual Word Form Area, while assessing object recognition performance. RESULTS We found group differences in dprime measures for all object categories, corroborating generalized deficits in object recognition. Concerning neural responses, we found region dependent group differences respecting a priori expected Hemispheric asymmetries. Patients showed significantly decreased BOLD responses in the right hemisphere-biased Fusiform Body Area, and lower left hemisphere responses in the Visual Word Form Area (with a priori known left hemispheric bias), consistent with deficits in body shape and word/pseudoword processing deficits. This hemispheric dominance related effects were preserved when controlling for performance differences. Whole brain analysis during the recognition task showed enhanced activity in AD group of left dorsolateral prefrontal cortex, left cingulate gyrus, and in the posterior cingulate cortex- a hotspot of amyloid-β accumulation. CONCLUSION These findings demonstrate region dependent respecting hemispheric dominance patterns activation changes in independently localized selective regions in mild AD, accompanied by putative compensatory activity of frontal and cingular networks.
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Affiliation(s)
- Nádia S. Canário
- Coimbra Institute for Biomedical Imaging and Translational Research, University of Coimbra, Coimbra, Portugal,
Institute for Nuclear Sciences Applied to Health, University of Coimbra, Coimbra, Portugal
| | - Lília P. Jorge
- Coimbra Institute for Biomedical Imaging and Translational Research, University of Coimbra, Coimbra, Portugal,
Institute for Nuclear Sciences Applied to Health, University of Coimbra, Coimbra, Portugal
| | - Isabel J. Santana
- Department of Neurology, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal,Faculty of Medicine, University of Coimbra, Coimbra, Portugal,
Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal
| | - Miguel S. Castelo-Branco
- Coimbra Institute for Biomedical Imaging and Translational Research, University of Coimbra, Coimbra, Portugal,
Institute for Nuclear Sciences Applied to Health, University of Coimbra, Coimbra, Portugal,Faculty of Medicine, University of Coimbra, Coimbra, Portugal,Correspondence to: M. Castelo-Branco, MD, PhD, Faculdade de Medicina, Polo de Ciências da Saúde da Universidade de Coimbra, Azinhaga de Santa Comba, Celas 3000-548, Coimbra, Portugal. Tel.: +351 239488514; E-mail:
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13
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Kim JR. Oligomerization by co-assembly of β-amyloid and α-synuclein. Front Mol Biosci 2023; 10:1153839. [PMID: 37021111 PMCID: PMC10067735 DOI: 10.3389/fmolb.2023.1153839] [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: 01/30/2023] [Accepted: 03/07/2023] [Indexed: 04/07/2023] Open
Abstract
Aberrant self-assembly of an intrinsically disordered protein is a pathological hallmark of protein misfolding diseases, such as Alzheimer's and Parkinson's diseases (AD and PD, respectively). In AD, the 40-42 amino acid-long extracellular peptide, β-amyloid (Aβ), self-assembles into oligomers, which eventually aggregate into fibrils. A similar self-association of the 140 amino acid-long intracellular protein, α-synuclein (αS), is responsible for the onset of PD pathology. While Aβ and αS are primarily extracellular and intracellular polypeptides, respectively, there is evidence of their colocalization and pathological overlaps of AD and PD. This evidence has raised the likelihood of synergistic, toxic protein-protein interactions between Aβ and αS. This mini review summarizes the findings of studies on Aβ-αS interactions related to enhanced oligomerization via co-assembly, aiming to provide a better understanding of the complex biology behind AD and PD and common pathological mechanisms among the major neurodegenerative diseases.
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14
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Kwak K, Stanford W, Dayan E. Identifying the regional substrates predictive of Alzheimer's disease progression through a convolutional neural network model and occlusion. Hum Brain Mapp 2022; 43:5509-5519. [PMID: 35904092 PMCID: PMC9704798 DOI: 10.1002/hbm.26026] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 06/02/2022] [Accepted: 07/08/2022] [Indexed: 01/15/2023] Open
Abstract
Progressive brain atrophy is a key neuropathological hallmark of Alzheimer's disease (AD) dementia. However, atrophy patterns along the progression of AD dementia are diffuse and variable and are often missed by univariate methods. Consequently, identifying the major regional atrophy patterns underlying AD dementia progression is challenging. In the current study, we propose a method that evaluates the degree to which specific regional atrophy patterns are predictive of AD dementia progression, while holding all other atrophy changes constant using a total sample of 334 subjects. We first trained a dense convolutional neural network model to differentiate individuals with mild cognitive impairment (MCI) who progress to AD dementia versus those with a stable MCI diagnosis. Then, we retested the model multiple times, each time occluding different regions of interest (ROIs) from the model's testing set's input. We also validated this approach by occluding ROIs based on Braak's staging scheme. We found that the hippocampus, fusiform, and inferior temporal gyri were the strongest predictors of AD dementia progression, in agreement with established staging models. We also found that occlusion of limbic ROIs defined according to Braak stage III had the largest impact on the performance of the model. Our predictive model reveals the major regional patterns of atrophy predictive of AD dementia progression. These results highlight the potential for early diagnosis and stratification of individuals with prodromal AD dementia based on patterns of cortical atrophy, prior to interventional clinical trials.
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Affiliation(s)
- Kichang Kwak
- Biomedical Research Imaging CenterUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
| | - William Stanford
- Neuroscience Curriculum, Biological and Biomedical Sciences ProgramUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
| | - Eran Dayan
- Biomedical Research Imaging CenterUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
- Neuroscience Curriculum, Biological and Biomedical Sciences ProgramUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
- Department of RadiologyUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
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15
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Schoemaker D, Zanon Zotin MC, Chen K, Igwe KC, Vila-Castelar C, Martinez J, Baena A, Fox-Fuller JT, Lopera F, Reiman EM, Brickman AM, Quiroz YT. White matter hyperintensities are a prominent feature of autosomal dominant Alzheimer’s disease that emerge prior to dementia. Alzheimers Res Ther 2022; 14:89. [PMID: 35768838 PMCID: PMC9245224 DOI: 10.1186/s13195-022-01030-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Accepted: 06/06/2022] [Indexed: 11/10/2022]
Abstract
Abstract
Background
To promote the development of effective therapies, there is an important need to characterize the full spectrum of neuropathological changes associated with Alzheimer’s disease. In line with this need, this study examined white matter abnormalities in individuals with early-onset autosomal dominant Alzheimer’s disease, in relation to age and symptom severity.
Methods
This is a cross-sectional analysis of data collected in members of a large kindred with a PSEN1 E280A mutation. Participants were recruited between September 2011 and July 2012 from the Colombian Alzheimer’s Prevention Initiative registry. The studied cohort comprised 50 participants aged between 20 and 55 years, including 20 cognitively unimpaired mutation carriers, 9 cognitively impaired mutation carriers, and 21 non-carriers. Participants completed an MRI, a lumbar puncture for cerebrospinal fluid collection, a florbetapir PET scan, and neurological and neuropsychological examinations. The volume of white matter hyperintensities (WMH) was compared between cognitively unimpaired carriers, cognitively impaired carriers, and non-carriers. Relationships between WMH, age, and cognitive performance were further examined in mutation carriers.
Results
The mean (SD) age of participants was 35.8 (9.6) years and 64% were women. Cardiovascular risk factors were uncommon and did not differ across groups. Cognitively impaired carriers [median, 6.37; interquartile range (IQR), 9.15] had an increased volume of WMH compared to both cognitively unimpaired carriers [median, 0.85; IQR, 0.79] and non-carriers [median, 1.07; IQR, 0.71]. In mutation carriers, the volume of WMH strongly correlated with cognition and age, with evidence for an accelerated rate of changes after the age of 43 years, 1 year earlier than the estimated median age of symptom onset. In multivariable regression models including cortical amyloid retention, superior parietal lobe cortical thickness, and cerebrospinal fluid phospho-tau, the volume of WMH was the only biomarker independently and significantly contributing to the total explained variance in cognitive performance.
Conclusions
The volume of WMH is increased among individuals with symptomatic autosomal-dominant Alzheimer’s disease, begins to increase prior to clinical symptom onset, and is an independent determinant of cognitive performance in this group. These findings suggest that WMH are a key component of autosomal-dominant Alzheimer’s disease that is closely related to the progression of clinical symptoms.
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Raikes AC, Hernandez GD, Matthews DC, Lukic AS, Law M, Shi Y, Schneider LS, Brinton RD. Exploratory imaging outcomes of a phase 1b/2a clinical trial of allopregnanolone as a regenerative therapeutic for Alzheimer's disease: Structural effects and functional connectivity outcomes. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2022; 8:e12258. [PMID: 35310526 PMCID: PMC8919249 DOI: 10.1002/trc2.12258] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 12/18/2021] [Accepted: 12/21/2021] [Indexed: 01/14/2023]
Abstract
Introduction Allopregnanolone (ALLO), an endogenous neurosteroid, promoted neurogenesis and oligogenesis and restored cognitive function in animal models of Alzheimer's disease (AD). Based on these discovery research findings, we conducted a randomized-controlled phase 1b/2a multiple ascending dose trial of ALLO in persons with early AD (NCT02221622) to assess safety, tolerability, and pharmacokinetics. Exploratory imaging outcomes to determine whether ALLO impacted hippocampal structure, white matter integrity, and functional connectivity are reported. Methods Twenty-four individuals participated in the trial (n = 6 placebo; n = 18 ALLO) and underwent brain magnetic resonance imaging (MRI) before and after 12 weeks of treatment. Hippocampal atrophy rate was determined from volumetric MRI, computed as rate of change, and qualitatively assessed between ALLO and placebo sex, apolipoprotein E (APOE) ε4 allele, and ALLO dose subgroups. White matter microstructural integrity was compared between placebo and ALLO using fractional and quantitative anisotropy (QA). Changes in local, inter-regional, and network-level functional connectivity were also compared between groups using resting-state functional MRI. Results Rate of decline in hippocampal volume was slowed, and in some cases reversed, in the ALLO group compared to placebo. Gain of hippocampal volume was evident in APOE ε4 carriers (range: 0.6% to 7.8% increased hippocampal volume). Multiple measures of white matter integrity indicated evidence of preserved or improved integrity. ALLO significantly increased fractional anisotropy (FA) in 690 of 690 and QA in 1416 of 1888 fiber tracts, located primarily in the corpus callosum, bilateral thalamic radiations, and bilateral corticospinal tracts. Consistent with structural changes, ALLO strengthened local, inter-regional, and network level functional connectivity in AD-vulnerable regions, including the precuneus and posterior cingulate, and network connections between the default mode network and limbic system. Discussion Indicators of regeneration from previous preclinical studies and these exploratory MRI-based outcomes from this phase 1b/2a clinical cohort support advancement to a phase 2 proof-of-concept efficacy clinical trial of ALLO as a regenerative therapeutic for mild AD (REGEN-BRAIN study; NCT04838301).
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Affiliation(s)
- Adam C. Raikes
- Center for Innovation in Brain ScienceUniversity of ArizonaTucsonArizonaUSA
| | | | - Dawn C. Matthews
- Departments of Pharmacology and Neurology, College of MedicineADM DiagnosticsNorthbrookIllinoisUSA
| | - Ana S. Lukic
- Departments of Pharmacology and Neurology, College of MedicineADM DiagnosticsNorthbrookIllinoisUSA
| | - Meng Law
- Department of RadiologyAlfred HealthDepartment of Neuroscience and Computer Systems EngineeringMonash UniversityMelbourneAustralia
| | - Yonggang Shi
- Stevens Neuroimaging and Informatics InstituteKeck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Lon S. Schneider
- Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Roberta D. Brinton
- Center for Innovation in Brain ScienceUniversity of ArizonaTucsonArizonaUSA
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Woodworth DC, Sheikh-Bahaei N, Scambray KA, Phelan MJ, Perez-Rosendahl M, Corrada MM, Kawas CH, Sajjadi SA. Dementia is associated with medial temporal atrophy even after accounting for neuropathologies. Brain Commun 2022; 4:fcac052. [PMID: 35350552 PMCID: PMC8952251 DOI: 10.1093/braincomms/fcac052] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 12/30/2021] [Accepted: 03/03/2022] [Indexed: 11/18/2022] Open
Abstract
Brain atrophy is associated with degenerative neuropathologies and the clinical status of dementia. Whether dementia is associated with atrophy independent of neuropathologies is not known. In this study, we examined the pattern of atrophy associated with dementia while accounting for the most common dementia-related neuropathologies. We used data from National Alzheimer's Coordinating Center (n = 129) and Alzheimer's Disease Neuroimaging Initiative (n = 47) participants with suitable in vivo 3D-T1w MRI and autopsy data. We determined dementia status at the visit closest to MRI. We examined the following dichotomized neuropathological variables: Alzheimer's disease neuropathology, hippocampal sclerosis, Lewy bodies, cerebral amyloid angiopathy and atherosclerosis. Voxel-based morphometry identified areas associated with dementia after accounting for neuropathologies. Identified regions of interest were further analysed. We used multiple linear regression models adjusted for neuropathologies and demographic variables. We also examined models with dementia and Clinical Dementia Rating sum of the boxes as the outcome and explored the potential mediating effect of medial temporal lobe structure volumes on the relationship between pathology and cognition. We found strong associations for dementia with volumes of the hippocampus, amygdala and parahippocampus (semi-partial correlations ≥ 0.28, P < 0.0001 for all regions in National Alzheimer's Coordinating Center; semi-partial correlations ≥ 0.35, P ≤ 0.01 for hippocampus and parahippocampus in Alzheimer's Disease Neuroimaging Initiative). Dementia status accounted for more unique variance in atrophy in these structures (∼8%) compared with neuropathological variables; the only exception was hippocampal sclerosis which accounted for more variance in hippocampal atrophy (10%). We also found that the volumes of the medial temporal lobe structures contributed towards explaining the variance in Clinical Dementia Rating sum of the boxes (ranging from 5% to 9%) independent of neuropathologies and partially mediated the association between Alzheimer's disease neuropathology and cognition. Even after accounting for the most common neuropathologies, dementia still had among the strongest associations with atrophy of medial temporal lobe structures. This suggests that atrophy of the medial temporal lobe is most related to the clinical status of dementia rather than Alzheimer's disease or other neuropathologies, with the potential exception of hippocampal sclerosis.
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Affiliation(s)
- Davis C. Woodworth
- Department of Neurology, University of California, Irvine, CA, USA
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, CA, USA
| | - Nasim Sheikh-Bahaei
- Department of Radiology, University of Southern California, Los Angeles, CA, USA
| | - Kiana A. Scambray
- Department of Neurology, University of California, Irvine, CA, USA
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, CA, USA
| | - Michael J. Phelan
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, CA, USA
| | - Mari Perez-Rosendahl
- Department of Neurology, University of California, Irvine, CA, USA
- Department of Pathology and Laboratory Medicine, University of California, Irvine, CA, USA
| | - María M. Corrada
- Department of Neurology, University of California, Irvine, CA, USA
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, CA, USA
- Department of Epidemiology, University of California, Irvine, CA, USA
| | - Claudia H. Kawas
- Department of Neurology, University of California, Irvine, CA, USA
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, CA, USA
- Department of Neurobiology and Behavior, University of California, Irvine, CA, USA
| | - Seyed Ahmad Sajjadi
- Department of Neurology, University of California, Irvine, CA, USA
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, CA, USA
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18
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Uretsky M, Bouix S, Killiany RJ, Tripodis Y, Martin B, Palmisano J, Mian AZ, Buch K, Farris C, Daneshvar DH, Dwyer B, Goldstein L, Katz D, Nowinski C, Cantu R, Kowall N, Huber BR, Stern RA, Alvarez VE, Stein TD, McKee A, Mez J, Alosco ML. Association Between Antemortem FLAIR White Matter Hyperintensities and Neuropathology in Brain Donors Exposed to Repetitive Head Impacts. Neurology 2022; 98:e27-e39. [PMID: 34819338 PMCID: PMC8726571 DOI: 10.1212/wnl.0000000000013012] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Accepted: 09/29/2021] [Indexed: 01/18/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Late neuropathologies of repetitive head impacts from contact sports can include chronic traumatic encephalopathy (CTE) and white matter degeneration. White matter hyperintensities (WMH) on fluid-attenuated inversion recovery (FLAIR) MRI scans are often viewed as microvascular disease from vascular risk, but might have unique underlying pathologies and risk factors in the setting of repetitive head impacts. We investigated the neuropathologic correlates of antemortem WMH in brain donors exposed to repetitive head impacts. The association between WMH and repetitive head impact exposure and informant-reported cognitive and daily function were tested. METHODS This imaging-pathologic correlation study included symptomatic male decedents exposed to repetitive head impacts. Donors had antemortem FLAIR scans from medical records and were without evidence of CNS neoplasm, large vessel infarcts, hemorrhage, or encephalomalacia. WMH were quantified using log-transformed values for total lesion volume (TLV), calculated using the lesion prediction algorithm from the Lesion Segmentation Toolbox. Neuropathologic assessments included semiquantitative ratings of white matter rarefaction, cerebrovascular disease, hyperphosphorylated tau (p-tau) severity (CTE stage, dorsolateral frontal cortex), and β-amyloid (Aβ). Among football players, years of play was a proxy for repetitive head impact exposure. Retrospective informant-reported cognitive and daily function were assessed using the Cognitive Difficulties Scale (CDS) and Functional Activities Questionnaire (FAQ). Regression models controlled for demographics, diabetes, hypertension, and MRI resolution. Statistical significance was defined as p ≤ 0.05. RESULTS The sample included 75 donors: 67 football players and 8 nonfootball contact sport athletes or military veterans. Dementia was the most common MRI indication (64%). Fifty-three (70.7%) had CTE at autopsy. Log TLV was associated with white matter rarefaction (odds ratio [OR] 2.32, 95% confidence interval [CI] 1.03, 5.24; p = 0.04), arteriolosclerosis (OR 2.38, 95% CI 1.02, 5.52; p = 0.04), CTE stage (OR 2.58, 95% CI 1.17, 5.71; p = 0.02), and dorsolateral frontal p-tau severity (OR 3.03, 95% CI 1.32, 6.97; p = 0.01). There was no association with Aβ. More years of football play was associated with log TLV (unstandardized β 0.04, 95% CI 0.01, 0.06; p = 0.01). Greater log TLV correlated with higher FAQ (unstandardized β 4.94, 95% CI 0.42, 8.57; p = 0.03) and CDS scores (unstandardized β 15.35, 95% CI -0.27, 30.97; p = 0.05). DISCUSSION WMH might capture long-term white matter pathologies from repetitive head impacts, including those from white matter rarefaction and p-tau, in addition to microvascular disease. Prospective imaging-pathologic correlation studies are needed. CLASSIFICATION OF EVIDENCE This study provides Class IV evidence of associations between FLAIR white matter hyperintensities and neuropathologic changes (white matter rarefaction, arteriolosclerosis, p-tau accumulation), years of American football play, and reported cognitive symptoms in symptomatic brain donors exposed to repetitive head impacts.
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Affiliation(s)
- Madeline Uretsky
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Sylvain Bouix
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Ronald J Killiany
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Yorghos Tripodis
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Brett Martin
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Joseph Palmisano
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Asim Z Mian
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Karen Buch
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Chad Farris
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Daniel H Daneshvar
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Brigid Dwyer
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Lee Goldstein
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Douglas Katz
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Christopher Nowinski
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Robert Cantu
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Neil Kowall
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Bertrand Russell Huber
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Robert A Stern
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Victor E Alvarez
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Thor D Stein
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Ann McKee
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Jesse Mez
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA
| | - Michael L Alosco
- From the Boston University Alzheimer's Disease Research Center and CTE Center, Department of Neurology (M.U., R.J.K., Y.T., D.H.D., B.D., L.G., D.K., C.N., R.C., N.K., B.R.H., R.A.S., V.E.A., T.D.S., A.M., J.M., M.L.A.), Department of Anatomy and Neurobiology (R.J.K., R.A.S.), Center for Biomedical Imaging (R.J.K.), Department of Radiology (A.Z.M., C.F.), Framingham Heart Study (C.F., T.D.S., A.M., J.M.), Department of Pathology and Laboratory Medicine (L.G., N.K., T.D.S., A.M.), Department of Psychiatry (L.G.), Department of Ophthalmology (L.G.), and Department of Neurosurgery (R.C., R.A.S.), Boston University School of Medicine; Department of Psychiatry, Psychiatry Neuroimaging Laboratory (S.B.), Brigham and Women's Hospital, Harvard Medical School; Department of Biostatistics (Y.T.) and Biostatistics and Epidemiology Data Analytics Center (B.M., J.P.), Boston University School of Public Health; Departments of Radiology (K.B.) and Physical Medicine & Rehabilitation (D.H.D.), Massachusetts General Hospital, Boston; Braintree Rehabilitation Hospital (B.D., D.K.); Department of Biomedical, Electrical & Computer Engineering (L.G.), Boston University College of Engineering; Concussion Legacy Foundation (C.N., R.C.), Boston; Department of Neurosurgery (R.C.), Emerson Hospital, Concord; VA Boston Healthcare System (B.R.H., V.E.A., T.D.S., A.M.), US Department of Veterans Affairs, Jamaica Plain; National Center for PTSD (B.R.H., V.E.A.), VA Boston Healthcare, Jamaica Plain; and Department of Veterans Affairs Medical Center (V.E.A., T.D.S., A.M.), Bedford, MA.
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Webster JM, Grabowski TJ, Madhyastha TM, Gibbons LE, Keene CD, Latimer CS. Leveraging Neuroimaging Tools to Assess Precision and Accuracy in an Alzheimer's Disease Neuropathologic Sampling Protocol. Front Neurosci 2021; 15:693242. [PMID: 34483821 PMCID: PMC8416420 DOI: 10.3389/fnins.2021.693242] [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: 04/10/2021] [Accepted: 07/29/2021] [Indexed: 02/02/2023] Open
Abstract
INTRODUCTION The study of Alzheimer's disease investigates topographic patterns of degeneration in the context of connected networks comprised of functionally distinct domains using increasingly sophisticated molecular techniques. Therefore, obtaining high precision and accuracy of neuropathologic tissue sampling will enhance the reliability of molecular studies and contribute to the understanding of Alzheimer's disease pathology. Neuroimaging tools can help assess these aspects of current sampling protocols as well as contribute directly to their improvement. METHODS Using a virtual sampling method on magnetic resonance images (MRIs) from 35 participants (21 women), we compared the precision and accuracy of traditional neuropathologic vs. neuroimaging-guided sampling. The impact of the resulting differences was assessed by evaluating the functional connectivity pattern of regions selected by each approach. RESULTS Virtual sampling using the traditional neuropathologic approach had low neuroanatomical precision and accuracy for all cortical regions tested. Neuroimaging-guided strategies narrowed these gaps. Discrepancies in the location of traditional and neuroimaging-guided samples corresponded to differences in fMRI measures of functional connectivity. DISCUSSION Integrating neuroimaging tools with the neuropathologic assessment will improve neuropathologic-neuroimaging correlations by helping to ensure specific functional domains are accurately sampled for quantitative molecular neuropathologic applications. Our neuroimaging-based simulation of current sampling practices provides a benchmark of precision and accuracy against which to measure improvements when using novel tissue sampling approaches. Our results suggest that relying on gross landmarks alone to select samples at autopsy leads to significant variability, even when sampled by the same neuropathologist. Further, this exercise highlights how sampling precision could be enhanced if neuroimaging were integrated with the standard neuropathologic assessment. More accurate targeting and improved biological homogeneity of sampled brain tissue will facilitate the interpretation of neuropathological analyses in AD and the downstream research applications of brain tissue from biorepositories.
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Affiliation(s)
- Jason M. Webster
- Department of Radiology, University of Washington, Seattle, WA, United States
| | - Thomas J. Grabowski
- Department of Radiology, University of Washington, Seattle, WA, United States,Department of Neurology, University of Washington, Seattle, WA, United States
| | - Tara M. Madhyastha
- Department of Radiology, University of Washington, Seattle, WA, United States
| | - Laura E. Gibbons
- Department of Medicine, University of Washington, Seattle, WA, United States
| | - C. Dirk Keene
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, United States
| | - Caitlin S. Latimer
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, United States,*Correspondence: Caitlin S. Latimer,
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Wisse LEM, Ravikumar S, Ittyerah R, Lim S, Lane J, Bedard ML, Xie L, Das SR, Schuck T, Grossman M, Lee EB, Tisdall MD, Prabhakaran K, Detre JA, Mizsei G, Trojanowski JQ, Artacho-Pérula E, de Iñiguez de Onzono Martin MM, M Arroyo-Jiménez M, Muñoz Lopez M, Molina Romero FJ, P Marcos Rabal M, Cebada Sánchez S, Delgado González JC, de la Rosa Prieto C, Córcoles Parada M, Wolk DA, Irwin DJ, Insausti R, Yushkevich PA. Downstream effects of polypathology on neurodegeneration of medial temporal lobe subregions. Acta Neuropathol Commun 2021; 9:128. [PMID: 34289895 PMCID: PMC8293481 DOI: 10.1186/s40478-021-01225-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Accepted: 07/06/2021] [Indexed: 12/14/2022] Open
Abstract
The medial temporal lobe (MTL) is a nidus for neurodegenerative pathologies and therefore an important region in which to study polypathology. We investigated associations between neurodegenerative pathologies and the thickness of different MTL subregions measured using high-resolution post-mortem MRI. Tau, TAR DNA-binding protein 43 (TDP-43), amyloid-β and α-synuclein pathology were rated on a scale of 0 (absent)-3 (severe) in the hippocampus and entorhinal cortex (ERC) of 58 individuals with and without neurodegenerative diseases (median age 75.0 years, 60.3% male). Thickness measurements in ERC, Brodmann Area (BA) 35 and 36, parahippocampal cortex, subiculum, cornu ammonis (CA)1 and the stratum radiatum lacunosum moleculare (SRLM) were derived from 0.2 × 0.2 × 0.2 mm3 post-mortem MRI scans of excised MTL specimens from the contralateral hemisphere using a semi-automated approach. Spearman's rank correlations were performed between neurodegenerative pathologies and thickness, correcting for age, sex and hemisphere, including all four proteinopathies in the model. We found significant associations of (1) TDP-43 with thickness in all subregions (r = - 0.27 to r = - 0.46), and (2) tau with BA35 (r = - 0.31) and SRLM thickness (r = - 0.33). In amyloid-β and TDP-43 negative cases, we found strong significant associations of tau with ERC (r = - 0.40), BA35 (r = - 0.55), subiculum (r = - 0.42) and CA1 thickness (r = - 0.47). This unique dataset shows widespread MTL atrophy in relation to TDP-43 pathology and atrophy in regions affected early in Braak stageing and tau pathology. Moreover, the strong association of tau with thickness in early Braak regions in the absence of amyloid-β suggests a role of Primary Age-Related Tauopathy in neurodegeneration.
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Affiliation(s)
- L E M Wisse
- Department of Diagnostic Radiology, Lund University, Klinikgatan 13b, Lund, Sweden.
- Department of Radiology, University of Pennsylvania, Philadelphia, USA.
| | - S Ravikumar
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - R Ittyerah
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - S Lim
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - J Lane
- Department of Neurology, University of Pennsylvania, Philadelphia, USA
| | - M L Bedard
- Department of Pharmacology, University of North Carolina At Chapel Hill, Chapel Hill, USA
| | - L Xie
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - S R Das
- Department of Neurology, University of Pennsylvania, Philadelphia, USA
| | - T Schuck
- Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, USA
| | - M Grossman
- Department of Neurology, University of Pennsylvania, Philadelphia, USA
| | - E B Lee
- Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, USA
| | - M D Tisdall
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - K Prabhakaran
- Department of Neurology, University of Pennsylvania, Philadelphia, USA
| | - J A Detre
- Department of Neurology, University of Pennsylvania, Philadelphia, USA
| | - G Mizsei
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - J Q Trojanowski
- Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, USA
| | - E Artacho-Pérula
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, University of Castilla La Mancha, Albacete, Spain
| | | | - M M Arroyo-Jiménez
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, University of Castilla La Mancha, Albacete, Spain
| | - M Muñoz Lopez
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, University of Castilla La Mancha, Albacete, Spain
| | - F J Molina Romero
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, University of Castilla La Mancha, Albacete, Spain
| | - M P Marcos Rabal
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, University of Castilla La Mancha, Albacete, Spain
| | - S Cebada Sánchez
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, University of Castilla La Mancha, Albacete, Spain
| | - J C Delgado González
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, University of Castilla La Mancha, Albacete, Spain
| | - C de la Rosa Prieto
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, University of Castilla La Mancha, Albacete, Spain
| | - M Córcoles Parada
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, University of Castilla La Mancha, Albacete, Spain
| | - D A Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia, USA
| | - D J Irwin
- Department of Neurology, University of Pennsylvania, Philadelphia, USA
- Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, USA
| | - R Insausti
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, University of Castilla La Mancha, Albacete, Spain
| | - P A Yushkevich
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
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21
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Williams CM, Peyre H, Toro R, Ramus F. Neuroanatomical norms in the UK Biobank: The impact of allometric scaling, sex, and age. Hum Brain Mapp 2021; 42:4623-4642. [PMID: 34268815 PMCID: PMC8410561 DOI: 10.1002/hbm.25572] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 06/03/2021] [Accepted: 06/11/2021] [Indexed: 12/18/2022] Open
Abstract
Few neuroimaging studies are sufficiently large to adequately describe population‐wide variations. This study's primary aim was to generate neuroanatomical norms and individual markers that consider age, sex, and brain size, from 629 cerebral measures in the UK Biobank (N = 40,028). The secondary aim was to examine the effects and interactions of sex, age, and brain allometry—the nonlinear scaling relationship between a region and brain size (e.g., total brain volume)—across cerebral measures. Allometry was a common property of brain volumes, thicknesses, and surface areas (83%) and was largely stable across age and sex. Sex differences occurred in 67% of cerebral measures (median |β| = .13): 37% of regions were larger in males and 30% in females. Brain measures (49%) generally decreased with age, although aging effects varied across regions and sexes. While models with an allometric or linear covariate adjustment for brain size yielded similar significant effects, omitting brain allometry influenced reported sex differences in variance. Finally, we contribute to the reproducibility of research on sex differences in the brain by replicating previous studies examining cerebral sex differences. This large‐scale study advances our understanding of age, sex, and brain allometry's impact on brain structure and provides data for future UK Biobank studies to identify the cerebral regions that covary with specific phenotypes, independently of sex, age, and brain size.
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Affiliation(s)
- Camille Michèle Williams
- Laboratoire de Sciences Cognitives et Psycholinguistique, Département d'Études Cognitives, École Normale Supérieure, EHESS, CNRS, PSL University, Paris, France
| | - Hugo Peyre
- Laboratoire de Sciences Cognitives et Psycholinguistique, Département d'Études Cognitives, École Normale Supérieure, EHESS, CNRS, PSL University, Paris, France.,INSERM UMR 1141, Paris Diderot University, Paris, France.,Department of Child and Adolescent Psychiatry, Robert Debré Hospital, APHP, Paris, France
| | - Roberto Toro
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR 3571 CNRS, Paris, France.,Center for Research and Interdisciplinarity (CRI), INSERM U1284, Paris, France.,Université de Paris, Paris, France
| | - Franck Ramus
- Laboratoire de Sciences Cognitives et Psycholinguistique, Département d'Études Cognitives, École Normale Supérieure, EHESS, CNRS, PSL University, Paris, France
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Lou B, Jiang Y, Li C, Wu PY, Li S, Qin B, Chen H, Wang R, Wu B, Chen M. Quantitative Analysis of Synthetic Magnetic Resonance Imaging in Alzheimer's Disease. Front Aging Neurosci 2021; 13:638731. [PMID: 33912023 PMCID: PMC8072384 DOI: 10.3389/fnagi.2021.638731] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Accepted: 03/18/2021] [Indexed: 12/15/2022] Open
Abstract
Objectives: The purpose of this study was to evaluate the feasibility and whether synthetic MRI can benefit diagnosis of Alzheimer’s disease (AD). Materials and Methods: Eighteen patients and eighteen age-matched normal controls (NCs) underwent MR examination. The mini-mental state examination (MMSE) scores were obtained from all patients. The whole brain volumetric characteristics, T1, T2, and proton density (PD) values of different cortical and subcortical regions were obtained. The volumetric characteristics and brain regional relaxation values between AD patients and NCs were compared using independent-samples t-test. The correlations between these quantitative parameters and MMSE score were assessed by the Pearson correlation in AD patients. Results: Although the larger volume of cerebrospinal fluid (CSF), lower brain parenchymal volume (BPV), and the ratio of brain parenchymal volume to intracranial volume (BPV/ICV) were found in AD patients compared with NCs, there were no significant differences (p > 0.05). T1 values of right insula cortex and T2 values of left hippocampus and right insula cortex were significantly higher in AD patients than in NCs, but T1 values of left caudate showed a reverse trend (p < 0.05). As the MMSE score decreased in AD patients, the BPV and BPV/ICV decreased, while the volume of CSF and T1 values of bilateral insula cortex and bilateral hippocampus as well as T2 values of bilateral hippocampus increased (p < 0.05). Conclusion: Synthetic MRI not only provides more information to differentiate AD patients from normal controls, but also reflects the disease severity of AD.
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Affiliation(s)
- Baohui Lou
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Yuwei Jiang
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Chunmei Li
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | | | - Shuhua Li
- Department of Neurology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Bin Qin
- Department of Neurology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Haibo Chen
- Department of Neurology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Rui Wang
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Bing Wu
- GE Healthcare, Beijing, China
| | - Min Chen
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
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23
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Ohm DT, Fought AJ, Martersteck A, Coventry C, Sridhar J, Gefen T, Weintraub S, Bigio E, Mesulam M, Rogalski E, Geula C. Accumulation of neurofibrillary tangles and activated microglia is associated with lower neuron densities in the aphasic variant of Alzheimer's disease. Brain Pathol 2021; 31:189-204. [PMID: 33010092 PMCID: PMC7855834 DOI: 10.1111/bpa.12902] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 08/27/2020] [Accepted: 09/28/2020] [Indexed: 12/15/2022] Open
Abstract
The neurofibrillary tangles (NFT) and amyloid-ß plaques (AP) that comprise Alzheimer's disease (AD) neuropathology are associated with neurodegeneration and microglial activation. Activated microglia exist on a dynamic spectrum of morphologic subtypes that include resting, surveillant microglia capable of converting to activated, hypertrophic microglia closely linked to neuroinflammatory processes and AD neuropathology in amnestic AD. However, quantitative analyses of microglial subtypes and neurons are lacking in non-amnestic clinical AD variants, including primary progressive aphasia (PPA-AD). PPA-AD is a language disorder characterized by cortical atrophy and NFT densities concentrated to the language-dominant hemisphere. Here, a stereologic investigation of five PPA-AD participants determined the densities and distributions of neurons and microglial subtypes to examine how cellular changes relate to AD neuropathology and may contribute to cortical atrophy. Adjacent series of sections were immunostained for neurons (NeuN) and microglia (HLA-DR) from bilateral language and non-language regions where in vivo cortical atrophy and Thioflavin-S-positive APs and NFTs were previously quantified. NeuN-positive neurons and morphologic subtypes of HLA-DR-positive microglia (i.e., resting [ramified] microglia and activated [hypertrophic] microglia) were quantified using unbiased stereology. Relationships between neurons, microglia, AD neuropathology, and cortical atrophy were determined using linear mixed models. NFT densities were positively associated with hypertrophic microglia densities (P < 0.01) and inversely related to neuron densities (P = 0.01). Hypertrophic microglia densities were inversely related to densities of neurons (P < 0.01) and ramified microglia (P < 0.01). Ramified microglia densities were positively associated with neuron densities (P = 0.02) and inversely related to cortical atrophy (P = 0.03). Our findings provide converging evidence of divergent roles for microglial subtypes in patterns of neurodegeneration, which includes hypertrophic microglia likely driving a neuroinflammatory response more sensitive to NFTs than APs in PPA-AD. Moreover, the accumulation of both NFTs and activated hypertrophic microglia in association with low neuron densities suggest they may collectively contribute to focal neurodegeneration characteristic of PPA-AD.
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Affiliation(s)
- Daniel T. Ohm
- Mesulam Center for Cognitive Neurology and Alzheimer’s DiseaseNorthwestern University Feinberg School of MedicineChicagoIL
| | - Angela J. Fought
- Department of Preventive MedicineNorthwestern University Feinberg School of MedicineChicagoIL
| | - Adam Martersteck
- Mesulam Center for Cognitive Neurology and Alzheimer’s DiseaseNorthwestern University Feinberg School of MedicineChicagoIL
| | - Christina Coventry
- Mesulam Center for Cognitive Neurology and Alzheimer’s DiseaseNorthwestern University Feinberg School of MedicineChicagoIL
| | - Jaiashre Sridhar
- Mesulam Center for Cognitive Neurology and Alzheimer’s DiseaseNorthwestern University Feinberg School of MedicineChicagoIL
| | - Tamar Gefen
- Mesulam Center for Cognitive Neurology and Alzheimer’s DiseaseNorthwestern University Feinberg School of MedicineChicagoIL
- Department of Psychiatry and Behavioral SciencesNorthwestern University Feinberg School of MedicineChicagoIL
| | - Sandra Weintraub
- Mesulam Center for Cognitive Neurology and Alzheimer’s DiseaseNorthwestern University Feinberg School of MedicineChicagoIL
- Department of Psychiatry and Behavioral SciencesNorthwestern University Feinberg School of MedicineChicagoIL
| | - Eileen Bigio
- Mesulam Center for Cognitive Neurology and Alzheimer’s DiseaseNorthwestern University Feinberg School of MedicineChicagoIL
- Department of PathologyNorthwestern University Feinberg School of MedicineChicagoIL
| | - M.‐Marsel Mesulam
- Mesulam Center for Cognitive Neurology and Alzheimer’s DiseaseNorthwestern University Feinberg School of MedicineChicagoIL
- Department of NeurologyNorthwestern University Feinberg School of MedicineChicagoIL
| | - Emily Rogalski
- Mesulam Center for Cognitive Neurology and Alzheimer’s DiseaseNorthwestern University Feinberg School of MedicineChicagoIL
- Department of Psychiatry and Behavioral SciencesNorthwestern University Feinberg School of MedicineChicagoIL
| | - Changiz Geula
- Mesulam Center for Cognitive Neurology and Alzheimer’s DiseaseNorthwestern University Feinberg School of MedicineChicagoIL
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24
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Ostrovska SS, Liholetov EО, Pavlova VV, Derkach АK, Shevchenko IF, Adegova LY. RELATIONSHIP BETWEEN ALZHEIMER’S DISEASE, CEREBROVASCULAR AND CARDIOVASCULAR DISEASES (literature review). BULLETIN OF PROBLEMS BIOLOGY AND MEDICINE 2021. [DOI: 10.29254/2077-4214-2021-1-159-302-307] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Affiliation(s)
- S. S. Ostrovska
- Dnipro Medical Institute of Traditional and Alternative Medicine (Dnipro)
| | - E. О. Liholetov
- Dnipro Medical Institute of Traditional and Alternative Medicine (Dnipro)
| | - V. V. Pavlova
- Dnipro Medical Institute of Traditional and Alternative Medicine (Dnipro)
| | - А. K. Derkach
- Dnipro Medical Institute of Traditional and Alternative Medicine (Dnipro)
| | - I. F. Shevchenko
- Dnipro Medical Institute of Traditional and Alternative Medicine (Dnipro)
| | - L. Y. Adegova
- Dnipro Medical Institute of Traditional and Alternative Medicine (Dnipro)
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25
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Teipel SJ, Fritz HC, Grothe MJ. Neuropathologic features associated with basal forebrain atrophy in Alzheimer disease. Neurology 2020; 95:e1301-e1311. [PMID: 32631924 PMCID: PMC7538215 DOI: 10.1212/wnl.0000000000010192] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Accepted: 03/09/2020] [Indexed: 12/14/2022] Open
Abstract
OBJECTIVE To study the neuropathologic correlates of cholinergic basal forebrain (BF) atrophy as determined using antemortem MRI in the Alzheimer disease (AD) spectrum. METHODS We determined associations between BF volume from antemortem MRI brain scans and postmortem assessment of neuropathologic features, including neuritic plaques, neurofibrillary tangles (NFTs), Lewy body (LB) pathology, and TDP-43, in 64 cases of the Alzheimer's Disease Neuroimaging Initiative cohort. For comparison, we assessed neuropathologic features associated with hippocampal and parahippocampal gyrus atrophy. In addition to region of interest-based analysis, we determined the association of neuropathologic features with whole brain gray matter volume using regionally unbiased voxel-based volumetry. RESULTS BF atrophy was associated with Thal amyloid phases (95% confidence interval [CI] -0.49 to -0.01, p = 0.049) and presence of LB pathology (95% CI -0.54 to -0.06, p = 0.015), as well as with the degree of LB pathology within the nucleus basalis Meynert (95% CI -0.54 to -0.07, p = 0.025). These effects were no longer significant after false discovery rate (FDR) correction. Hippocampal atrophy was significantly associated with the presence of TDP-43 pathology (95% CI -0.61 to -0.17, p = 0.003; surviving FDR correction), in addition to dentate gyrus NFT load (95% CI -0.49 to -0.01, p = 0.044; uncorrected). Voxel-based analysis confirmed spatially restricted effects of Thal phases and presence of LB pathology on BF volume. CONCLUSIONS These findings indicate that neuropathologic correlates of regional atrophy differ substantially between different brain regions that are typically involved in AD-related neurodegeneration, including different susceptibilities to common comorbid pathologies.
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Affiliation(s)
- Stefan J Teipel
- From the German Center for Neurodegenerative Diseases (DZNE) (S.J.T., M.J.G.); Department of Psychosomatic Medicine (S.J.T., H.-C.F.), University Medicine Rostock, Germany; and Instituto de Biomedicina de Sevilla (IBiS) (M.J.G.), Unidad de Trastornos del Movimiento, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Spain.
| | - H-Christian Fritz
- From the German Center for Neurodegenerative Diseases (DZNE) (S.J.T., M.J.G.); Department of Psychosomatic Medicine (S.J.T., H.-C.F.), University Medicine Rostock, Germany; and Instituto de Biomedicina de Sevilla (IBiS) (M.J.G.), Unidad de Trastornos del Movimiento, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Spain
| | - Michel J Grothe
- From the German Center for Neurodegenerative Diseases (DZNE) (S.J.T., M.J.G.); Department of Psychosomatic Medicine (S.J.T., H.-C.F.), University Medicine Rostock, Germany; and Instituto de Biomedicina de Sevilla (IBiS) (M.J.G.), Unidad de Trastornos del Movimiento, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Spain
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26
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Modified Visual Magnetic Resonance Scale and Neuropsychometric Corelations in Alzheimer's disease. ANADOLU KLINIĞI TIP BILIMLERI DERGISI 2020. [DOI: 10.21673/anadoluklin.737253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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27
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de Flores R, Wisse LE, Das SR, Xie L, McMillan CT, Trojanowski JQ, Robinson JL, Grossman M, Lee E, Irwin DJ, Yushkevich PA, Wolk DA. Contribution of mixed pathology to medial temporal lobe atrophy in Alzheimer's disease. Alzheimers Dement 2020; 16:843-852. [PMID: 32323446 PMCID: PMC7715004 DOI: 10.1002/alz.12079] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Revised: 01/13/2020] [Accepted: 02/15/2020] [Indexed: 12/14/2022]
Abstract
INTRODUCTION It is unclear how different proteinopathies (tau, transactive response DNA-binding protein 43 [TDP-43], amyloid β [Aβ], and α-synuclein) contribute to atrophy within medial temporal lobe (MTL) subregions in Alzheimer's disease (AD). METHODS We utilized antemortem structural magnetic resonance imaging (MRI) data to measure MTL substructures and examined the relative contribution of tau, TDP-43, Aβ, and α-synuclein measured in post-mortem tissue from 92 individuals with intermediate to high AD neuropathology. Receiver-operating characteristic (ROC) curves were analyzed for each subregion in order to discriminate TDP-43-negative and TDP-43-positive patients. RESULTS TDP-43 was strongly associated with anterior MTL regions, whereas tau was relatively more associated with the posterior hippocampus. Among the MTL regions, the anterior hippocampus showed the highest area under the ROC curve (AUC). DISCUSSION We found specific contributions of different pathologies on MTL substructure in this population with AD neuropathology. The anterior hippocampus may be a relevant region to detect concomitant TDP-43 pathology in the MTL of patients with AD.
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Affiliation(s)
- Robin de Flores
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Laura E.M. Wisse
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Sandhitsu R. Das
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Long Xie
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Corey T. McMillan
- Penn FTD Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - John Q. Trojanowski
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - John L. Robinson
- Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Murray Grossman
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Penn FTD Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Edward Lee
- Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - David J. Irwin
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Penn FTD Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Paul A. Yushkevich
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - David A. Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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28
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Patel H, Aggarwal NT, Rao A, Bryant E, Sanghani RM, Byrnes M, Kalra D, Dairaghi L, Braun L, Gabriel S, Volgman AS. Microvascular Disease and Small-Vessel Disease: The Nexus of Multiple Diseases of Women. J Womens Health (Larchmt) 2020; 29:770-779. [PMID: 32074468 PMCID: PMC7307673 DOI: 10.1089/jwh.2019.7826] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
Microvascular disease, or small-vessel disease, is a multisystem disorder with a common pathophysiological basis that differentially affects various organs in some patients. The prevalence of small-vessel disease in the heart has been found to be higher in women compared with men. Additionally, other diseases prominently affecting women, including heart failure with preserved ejection fraction, Takotsubo cardiomyopathy, cerebral small-vessel disease, preeclampsia, pulmonary arterial hypertension (PAH), endothelial dysfunction in diabetes, diabetic cardiomyopathy, rheumatoid arthritis, systemic lupus erythematosus, and systemic sclerosis, may have a common etiologic linkage related to microvascular disease. To the best of our knowledge this is the first article to investigate this potential linkage. We sought to identify various diseases with a shared pathophysiology involving microvascular/endothelial dysfunction that primarily affect women, and their potential implications for disease management. Advanced imaging technologies, such as magnetic resonance imaging and positron-emission tomography, enable the detection and increased understanding of microvascular dysfunction in various diseases. Therapies that improve endothelial function, such as those used in PAH, may also be associated with benefits across the full spectrum of microvascular dysfunction. A shared pathology across multiple organ systems highlights the need for a collaborative, multidisciplinary approach among medical subspecialty practitioners who care for women with small-vessel disease. Such an approach may lead to accelerated research in diseases that affect women and their quality of life.
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Affiliation(s)
- Hena Patel
- Department of Cardiology, Rush Medical College, Rush University, Chicago, Illinois
| | - Neelum T Aggarwal
- Department of Neurological Sciences, Rush Alzheimer's Disease Center, Rush Medical College, Rush University, Chicago, Illinois
| | - Anupama Rao
- Department of Cardiology, Rush Medical College, Rush University, Chicago, Illinois
| | | | - Rupa M Sanghani
- Department of Cardiology, Rush Medical College, Rush University, Chicago, Illinois
| | - Mary Byrnes
- Clinical Nursing, Rush Medical College, Rush University, Chicago, Illinois
| | - Dinesh Kalra
- Department of Cardiology, Rush Medical College, Rush University, Chicago, Illinois
| | - Leigh Dairaghi
- Rush Medical College, Rush University, Chicago, Illinois
| | - Lynne Braun
- Rush College of Nursing and Medicine, Rush University, Chicago, Illinois
| | - Sherine Gabriel
- Department of Rheumatology, Rush Medical College, Rush University, Chicago, Illinois
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29
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Klohs J. An Integrated View on Vascular Dysfunction in Alzheimer's Disease. NEURODEGENER DIS 2020; 19:109-127. [PMID: 32062666 DOI: 10.1159/000505625] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Accepted: 12/23/2019] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Cerebrovascular disease is a common comorbidity in patients with Alzheimer's disease (AD). It is believed to contribute additively to the cognitive impairment and to lower the threshold for the development of dementia. However, accumulating evidence suggests that dysfunction of the cerebral vasculature and AD neuropathology interact in multiple ways. Vascular processes even proceed AD neuropathology, implicating a causal role in the etiology of AD. Thus, the review aims to provide an integrated view on vascular dysfunction in AD. SUMMARY In AD, the cerebral vasculature undergoes pronounced cellular, morphological and structural changes, which alters regulation of blood flow, vascular fluid dynamics and vessel integrity. Stiffening of central blood vessels lead to transmission of excessive pulsatile energy to the brain microvasculature, causing end-organ damage. Moreover, a dysregulated hemostasis and chronic vascular inflammation further impede vascular function, where its mediators interact synergistically. Changes of the cerebral vasculature are triggered and driven by systemic vascular abnormalities that are part of aging, and which can be accelerated and aggravated by cardiovascular diseases. Key Messages: In AD, the cerebral vasculature is the locus where multiple pathogenic processes converge and contribute to cognitive impairment. Understanding the molecular mechanism and pathophysiology of vascular dysfunction in AD and use of vascular blood-based and imaging biomarker in clinical studies may hold promise for future prevention and therapy of the disease.
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Affiliation(s)
- Jan Klohs
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland, .,Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland,
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30
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Application of KPCA and AdaBoost algorithm in classification of functional magnetic resonance imaging of Alzheimer’s disease. Neural Comput Appl 2020. [DOI: 10.1007/s00521-020-04707-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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31
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Candreva J, Chau E, Rice ME, Kim JR. Interactions between Soluble Species of β-Amyloid and α-Synuclein Promote Oligomerization while Inhibiting Fibrillization. Biochemistry 2019; 59:425-435. [PMID: 31854188 DOI: 10.1021/acs.biochem.9b00655] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Aggregations of β-amyloid (Aβ) and α-synuclein (αS) into oligomeric and fibrillar assemblies are the pathological hallmarks of Alzheimer's and Parkinson's diseases, respectively. Although Aβ and αS affect different regions of the brain and are separated at the cellular level, there is evidence of their eventual interaction in the pathology of both disorders. Characterization of interactions of Aβ and αS at various stages of their aggregation pathways could reveal mechanisms and therapeutic targets for the prevention and cure of these neurodegenerative diseases. In this study, we comprehensively examined the interactions and their molecular manifestations using an array of characterization tools. We show for the first time that αS monomers and oligomers, but not αS fibrils, inhibit Aβ fibrillization while promoting oligomerization of Aβ monomers and stabilizing preformed Aβ oligomers via coassembly, as judged by Thioflavin T fluorescence, transmission electron microscopy, and SDS- and native-PAGE with fluorescently labeled peptides/proteins. In contrast, soluble Aβ species, such as monomers and oligomers, aggregate into fibrils, when incubated alone under the otherwise same condition. Our study provides evidence that the interactions with αS soluble species, responsible for the effects, are mediated primarily by the C-terminus of Aβ, when judged by competitive immunoassays using antibodies recognizing various fragments of Aβ. We also show that the C-terminus of Aβ is a primary site for its interaction with αS fibrils. Collectively, these data demonstrate aggregation state-specific interactions between αS and Aβ and offer insight into a molecular basis of synergistic biological effects between the two polypeptides.
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Affiliation(s)
- Jason Candreva
- Department of Chemical and Biomolecular Engineering , New York University , 6 MetroTech Center , Brooklyn , New York 11201 , United States
| | - Edward Chau
- Department of Chemical and Biomolecular Engineering , New York University , 6 MetroTech Center , Brooklyn , New York 11201 , United States
| | - Margaret E Rice
- Departments of Neurosurgery, and Neuroscience and Physiology , New York University School of Medicine , New York , New York 10016 , United States
| | - Jin Ryoun Kim
- Department of Chemical and Biomolecular Engineering , New York University , 6 MetroTech Center , Brooklyn , New York 11201 , United States
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32
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Dallaire-Théroux C, Beheshti I, Potvin O, Dieumegarde L, Saikali S, Duchesne S. Braak neurofibrillary tangle staging prediction from in vivo MRI metrics. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2019; 11:599-609. [PMID: 31517022 PMCID: PMC6731211 DOI: 10.1016/j.dadm.2019.07.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
INTRODUCTION Alzheimer's disease diagnosis requires postmortem visualization of amyloid and tau deposits. As brain atrophy can provide assessment of consequent neurodegeneration, our objective was to predict postmortem neurofibrillary tangles (NFT) from in vivo MRI measurements. METHODS All participants with neuroimaging and neuropathological data from the Alzheimer's Disease Neuroimaging Initiative, the National Alzheimer's Coordinating Center and the Rush Memory and Aging Project were selected (n = 186). Two hundred and thirty two variables were extracted from last MRI before death using FreeSurfer. Nonparametric correlation analysis and multivariable support vector machine classification were performed to provide a predictive model of Braak NFT staging. RESULTS We demonstrated that 59 of our MRI variables, mostly temporal lobe structures, were significantly associated with Braak NFT stages (P < .005). We obtained a 62.4% correct classification rate for discrimination between transentorhinal, limbic, and isocortical groups. DISCUSSION Structural neuroimaging may therefore be considered as a potential biomarker for early detection of Alzheimer's disease-associated neurofibrillary degeneration.
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Affiliation(s)
- Caroline Dallaire-Théroux
- CERVO Brain Research Center, Quebec City, Quebec, Canada
- Faculty of Medicine, Université Laval, Quebec City, Quebec, Canada
| | - Iman Beheshti
- CERVO Brain Research Center, Quebec City, Quebec, Canada
| | - Olivier Potvin
- CERVO Brain Research Center, Quebec City, Quebec, Canada
| | | | - Stephan Saikali
- Faculty of Medicine, Université Laval, Quebec City, Quebec, Canada
- Department of pathology, Centre Hospitalier Universitaire de Quebec, Quebec City, Quebec, Canada
| | - Simon Duchesne
- CERVO Brain Research Center, Quebec City, Quebec, Canada
- Faculty of Medicine, Université Laval, Quebec City, Quebec, Canada
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Bejanin A, Murray ME, Martin P, Botha H, Tosakulwong N, Schwarz CG, Senjem ML, Chételat G, Kantarci K, Jack CR, Boeve BF, Knopman DS, Petersen RC, Giannini C, Parisi JE, Dickson DW, Whitwell JL, Josephs KA. Antemortem volume loss mirrors TDP-43 staging in older adults with non-frontotemporal lobar degeneration. Brain 2019; 142:3621-3635. [PMID: 31562527 PMCID: PMC6821218 DOI: 10.1093/brain/awz277] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2019] [Revised: 06/26/2019] [Accepted: 07/15/2019] [Indexed: 12/13/2022] Open
Abstract
Over the past decade, the transactive response DNA-binding protein of 43 kDa (TDP-43) has been recognized as a major protein in normal and pathological ageing, increasing the risk of cognitive impairment and dementia. In conditions distinct from the frontotemporal lobar degenerations, TDP-43 appears to progress in a stereotypical pattern. In the present study, we aimed at providing a better understanding of the effects of TDP-43 and other age-related neuropathologies on cross-sectional grey matter volume in a cohort of non-FTLD subjects. We included 407 individuals with an antemortem MRI and post-mortem brain tissue from the Mayo Clinic Alzheimer's Disease Research Center, Mayo Clinic Alzheimer's Disease Patient Registry, or the Mayo Clinic Study of Aging. All individuals were assigned pathological stages for TDP-43, tau, amyloid-β, Lewy bodies, argyrophilic grain disease and vascular pathologies. Robust regressions were performed in regions of interest and voxel-wise to explore the relationships between TDP-43 stages and grey matter volume while controlling for other pathologies. Grey matter volumes adjusted for pathological and demographic variables were also computed for each TDP-43-positive case to further characterize the sequential involvement of brain structures associated with TDP-43, irrespective of the TDP-43 staging scheme. Robust regressions showed that the extent of TDP-43 pathology was associated with the extent of grey matter atrophy. Specifically, we found that the volume in medial temporal regions (i.e. amygdala, entorhinal cortex, hippocampus) decreased progressively with advancing TDP-43 stages. Importantly, these effects were of similar magnitude to those related to tau stages. Additional analyses using adjusted grey matter volume demonstrated a sequential pattern of volume loss associated with TDP-43, starting within the medial temporal lobe, followed by early involvement of the temporal pole, and eventually encompassing additional temporal and frontal regions. Altogether, this study demonstrates the major and independent contribution of TDP-43 pathology on neurodegeneration and provides further insight into the regional distribution of TDP-43 in non-FTLD subjects. Along with previous studies, these findings emphasized the importance of targeting TDP-43 in future clinical trials to prevent its detrimental effect on grey matter volume and, eventually, cognition.
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Affiliation(s)
- Alexandre Bejanin
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
- Inserm, Inserm UMR-S U1237, Université de Caen-Normandie, GIP Cyceron, Caen, France
| | | | - Peter Martin
- Health Science Research, Mayo Clinic, Rochester, MN, USA
| | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | | | | | - Matthew L Senjem
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
- Department of Information Technology, Mayo Clinic, Rochester, MN, USA
| | - Gael Chételat
- Inserm, Inserm UMR-S U1237, Université de Caen-Normandie, GIP Cyceron, Caen, France
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | | | | | | | | | - Caterina Giannini
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Joseph E Parisi
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
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Ohm DT, Fought AJ, Rademaker A, Kim G, Sridhar J, Coventry C, Gefen T, Weintraub S, Bigio E, Mesulam MM, Rogalski E, Geula C. Neuropathologic basis of in vivo cortical atrophy in the aphasic variant of Alzheimer's disease. Brain Pathol 2019; 30:332-344. [PMID: 31446630 DOI: 10.1111/bpa.12783] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2019] [Accepted: 08/16/2019] [Indexed: 12/22/2022] Open
Abstract
The neuropathologic basis of in vivo cortical atrophy in clinical dementia syndromes remains poorly understood. This includes primary progressive aphasia (PPA), a language-based dementia syndrome characterized by asymmetric cortical atrophy. The neurofibrillary tangles (NFTs) and amyloid-ß plaques (APs) of Alzheimer's disease (AD) can cause PPA, but a quantitative investigation of the relationships between NFTs, APs and in vivo cortical atrophy in PPA-AD is lacking. The present study measured cortical atrophy from corresponding bilateral regions in five PPA-AD participants with in vivo magnetic resonance imaging scans 7-30 months before death and acquired stereologic estimates of NFTs and dense-core APs visualized with the Thioflavin-S stain. Linear mixed models accounting for repeated measures and stratified by hemisphere and region (language vs. non-language) were used to determine the relationships between cortical atrophy and AD neuropathology and their regional selectivity. Consistent with the aphasic profile of PPA, left language regions displayed more cortical atrophy (P = 0.01) and NFT densities (P = 0.02) compared to right language homologues. Left language regions also showed more cortical atrophy (P < 0.01) and NFT densities (P = 0.02) than left non-language regions. A subset of data was analyzed to determine the predilection of AD neuropathology for neocortical regions compared to entorhinal cortex in the left hemisphere, which showed that the three most atrophied language regions had greater NFT (P = 0.04) and AP densities (P < 0.01) than the entorhinal cortex. These results provide quantitative evidence that NFT accumulation in PPA selectively targets the language network and may not follow the Braak staging of neurofibrillary degeneration characteristic of amnestic AD. Only NFT densities, not AP densities, were positively associated with cortical atrophy within left language regions (P < 0.01) and right language homologues (P < 0.01). Given previous findings from amnestic AD, the current study of PPA-AD provides converging evidence that NFTs are the principal determinants of atrophy and clinical phenotypes associated with AD.
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Affiliation(s)
- Daniel T Ohm
- Mesulam Center for Cognitive Neurology and Alzheimer's Disease, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611
| | - Angela J Fought
- Mesulam Center for Cognitive Neurology and Alzheimer's Disease, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611.,Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611
| | - Alfred Rademaker
- Mesulam Center for Cognitive Neurology and Alzheimer's Disease, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611.,Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611
| | - Garam Kim
- Mesulam Center for Cognitive Neurology and Alzheimer's Disease, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611
| | - Jaiashre Sridhar
- Mesulam Center for Cognitive Neurology and Alzheimer's Disease, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611
| | - Christina Coventry
- Mesulam Center for Cognitive Neurology and Alzheimer's Disease, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611
| | - Tamar Gefen
- Mesulam Center for Cognitive Neurology and Alzheimer's Disease, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611.,Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611
| | - Sandra Weintraub
- Mesulam Center for Cognitive Neurology and Alzheimer's Disease, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611.,Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611
| | - Eileen Bigio
- Mesulam Center for Cognitive Neurology and Alzheimer's Disease, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611.,Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611
| | - Marek Marsel Mesulam
- Mesulam Center for Cognitive Neurology and Alzheimer's Disease, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611.,Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611
| | - Emily Rogalski
- Mesulam Center for Cognitive Neurology and Alzheimer's Disease, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611.,Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611
| | - Changiz Geula
- Mesulam Center for Cognitive Neurology and Alzheimer's Disease, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611
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Puzo C, Labriola C, Sugarman MA, Tripodis Y, Martin B, Palmisano JN, Steinberg EG, Stein TD, Kowall NW, McKee AC, Mez J, Killiany RJ, Stern RA, Alosco ML. Independent effects of white matter hyperintensities on cognitive, neuropsychiatric, and functional decline: a longitudinal investigation using the National Alzheimer's Coordinating Center Uniform Data Set. Alzheimers Res Ther 2019; 11:64. [PMID: 31351489 PMCID: PMC6661103 DOI: 10.1186/s13195-019-0521-0] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2019] [Accepted: 07/14/2019] [Indexed: 01/18/2023]
Abstract
BACKGROUND Longitudinal investigations are needed to improve understanding of the contributions of cerebral small vessel disease to the clinical manifestation of Alzheimer's disease, particularly in the early disease stages. This study leveraged the National Alzheimer's Coordinating Center Uniform Data Set to longitudinally examine the association between white matter hyperintensities and neuropsychological, neuropsychiatric, and functional decline among participants with normal cognition. METHODS The sample included 465 participants from the National Alzheimer's Coordinating Center Uniform Data Set who had quantitated volume of white matter hyperintensities from fluid-attenuated inversion recovery MRI, had normal cognition at the time of their MRI, and were administered the National Alzheimer's Coordinating Center Uniform Data Set neuropsychological test battery within 1 year of study evaluation and had at least two post-MRI time points of clinical data. Neuropsychiatric status was assessed by the Geriatric Depression Scale-15 and Neuropsychiatric Inventory-Questionnaire. Clinical Dementia Rating Sum of Boxes defined functional status. For participants subsequently diagnosed with mild cognitive impairment (MCI) or dementia, their impairment must have been attributed to Alzheimer's disease (AD) to evaluate the relationships between WMH and the clinical presentation of AD. RESULTS Of the 465 participants, 56 converted to MCI or AD dementia (average follow-up = 5 years). Among the 465 participants, generalized estimating equations controlling for age, sex, race, education, APOE ε4, and total brain and hippocampal volume showed that higher baseline log-white matter hyperintensities predicted accelerated decline on the following neuropsychological tests in rank order of effect size: Trails B (p < 0.01), Digit Symbol Coding (p < 0.01), Logical Memory Immediate Recall (p = 0.02), Trail Making A (p < 0.01), and Semantic Fluency (p < 0.01). White matter hyperintensities predicted increases in Clinical Dementia Rating Sum of Boxes (p < 0.01) and Geriatric Depression Scale-15 scores (p = 0.01). Effect sizes were comparable to total brain and hippocampal volume. White matter hyperintensities did not predict diagnostic conversion. All effects also remained after including individuals with non-AD suspected etiologies for those who converted to MCI or dementia. CONCLUSIONS In this baseline cognitively normal sample, greater white matter hyperintensities were associated with accelerated cognitive, neuropsychiatric, and functional decline independent of traditional risk factors and MRI biomarkers for Alzheimer's disease.
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Affiliation(s)
- Christian Puzo
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
| | - Caroline Labriola
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
| | - Michael A Sugarman
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
| | - Yorghos Tripodis
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Brett Martin
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
- Biostatistics and Epidemiology Data Analytics Center, Boston University School of Public Health, Boston, MA, USA
| | - Joseph N Palmisano
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
- Biostatistics and Epidemiology Data Analytics Center, Boston University School of Public Health, Boston, MA, USA
| | - Eric G Steinberg
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
| | - Thor D Stein
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
- Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, USA
- VA Boston Healthcare System, U.S. Department of Veteran Affairs, Jamaica Plain, USA
| | - Neil W Kowall
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, USA
- VA Boston Healthcare System, U.S. Department of Veteran Affairs, Jamaica Plain, USA
| | - Ann C McKee
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, USA
- VA Boston Healthcare System, U.S. Department of Veteran Affairs, Jamaica Plain, USA
| | - Jesse Mez
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Ronald J Killiany
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, USA
- Center for Biomedical Imaging, Boston University School of Medicine, Boston, USA
| | - Robert A Stern
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Departments of Neurosurgery and Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, USA
| | - Michael L Alosco
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA.
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA.
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Ye C, Albert M, Brown T, Bilgel M, Hsu J, Ma T, Caffo B, Miller MI, Mori S, Oishi K. Extended multimodal whole-brain anatomical covariance analysis: detection of disrupted correlation networks related to amyloid deposition. Heliyon 2019; 5:e02074. [PMID: 31372540 PMCID: PMC6656959 DOI: 10.1016/j.heliyon.2019.e02074] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2018] [Revised: 04/22/2019] [Accepted: 07/08/2019] [Indexed: 01/27/2023] Open
Abstract
Background An anatomical covariance analysis (ACA) enables to elucidate inter-regional connections on a group basis, but little is known about the connections among white matter structures or among gray and white matter structures. Effect of including multiple magnetic resonance imaging (MRI) modalities into ACA framework in detecting white-to-white or gray-to-white connections is yet to be investigated. New method Proposed extended anatomical covariance analysis (eACA), analyzes correlations among gray and white matter structures (multi-structural) in various types of imaging modalities (T1-weighted images, T2 maps obtained from dual-echo sequences, and diffusion tensor images (DTI)). To demonstrate the capability to detect a disruption of the correlation network affected by pathology, we applied the eACA to two groups of cognitively-normal elderly individuals, one with (PiB+) and one without (PiB-) amyloid deposition in their brains. Results The volume of each anatomical structure was symmetric and functionally related structures formed a cluster. The pseudo-T2 value was highly homogeneous across the entire cortex in the PiB- group, while a number of physiological correlations were altered in the PiB + group. The DTI demonstrated unique correlation network among structures within the same phylogenetic portions of the brain that were altered in the PiB + group. Comparison with Existing Method The proposed eACA expands the concept of existing ACA to the connections among the white matter structures. The extension to other image modalities expands the way in which connectivity may be detected. Conclusion The eACA has potential to evaluate alterations of the anatomical network related to pathological processes.
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Affiliation(s)
- Chenfei Ye
- Department of Electronics and Information, Harbin Institute of Technology at Shenzhen, Shenzhen, Guangdong Province, China.,The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,Peng Cheng Laboratory, Shenzhen, Guangdong, China
| | - Marilyn Albert
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,The Johns Hopkins Alzheimer's Disease Research Center, Baltimore, MD, USA
| | - Timothy Brown
- Center for Imaging Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Murat Bilgel
- Laboratory of Behavioral Neuroscience, Intramural Research Program, National Institute on Aging, Baltimore, MD, USA
| | - Johnny Hsu
- Peng Cheng Laboratory, Shenzhen, Guangdong, China
| | - Ting Ma
- Department of Electronics and Information, Harbin Institute of Technology at Shenzhen, Shenzhen, Guangdong Province, China.,Peng Cheng Laboratory, Shenzhen, Guangdong, China
| | - Brian Caffo
- Department of Biostatistics, Johns Hopkins University, Baltimore, MD, USA
| | - Michael I Miller
- Center for Imaging Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Susumu Mori
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Kenichi Oishi
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
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Radiologic evidence that hypothalamic gliosis is improved after bariatric surgery in obese women with type 2 diabetes. Int J Obes (Lond) 2019; 44:178-185. [PMID: 31201362 PMCID: PMC7366782 DOI: 10.1038/s41366-019-0399-8] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/24/2018] [Revised: 04/10/2019] [Accepted: 05/06/2019] [Indexed: 12/31/2022]
Abstract
BACKGROUND/OBJECTIVES Hypothalamic neurons play a major role in the control of body mass. Obese subjects present radiologic signs of gliosis in the hypothalamus, which may reflect the damage or loss of neurons involved in whole-body energy homeostasis. It is currently unknown if hypothalamic gliosis (1) differs between obese nondiabetic (ND) and obese diabetic subjects (T2D) or (2) is modified by extensive body mass reduction via Roux-n-Y gastric bypass (RYGB). SUBJECTS/METHODS Fifty-five subjects (all female) including lean controls (CT; n = 13), ND (n = 28), and T2D (n = 14) completed at least one study visit. Subjects underwent anthropometrics and a multi-echo MRI sequence to measure mean bilateral T2 relaxation time in the mediobasal hypothalamus (MBH) and two reference regions (amygdala and putamen). The obese groups underwent RYGB and were re-evaluated 9 months later. Analyses were by linear mixed models. RESULTS Analyses of T2 relaxation time at baseline showed a group by region interaction only in the MBH (P < 0.0001). T2D had longer T2 relaxation times compared to either CT or ND groups. To examine the effects of RYGB on hypothalamic gliosis a three-way (group by region by time) mixed effects model adjusted for age was executed. Group by region (P < 0.0001) and region by time (P = 0.0005) interactions were significant. There was a reduction in MBH relaxation time by RYGB, and, although the T2D group still had higher T2 relaxation time overall compared to the ND group, the T2D group had significantly lower T2 relaxation time after surgery and the ND group showed a trend. The degree of reduction in MBH T2 relaxation time by RYGB was unrelated to clinical outcomes. CONCLUSION T2 relaxation times, a marker of hypothalamic gliosis, are higher in obese women with T2D and are reduced by RYGB-induced weight loss.
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Alosco ML, Sugarman MA, Besser LM, Tripodis Y, Martin B, Palmisano JN, Kowall NW, Au R, Mez J, DeCarli C, Stein TD, McKee AC, Killiany RJ, Stern RA. A Clinicopathological Investigation of White Matter Hyperintensities and Alzheimer's Disease Neuropathology. J Alzheimers Dis 2019; 63:1347-1360. [PMID: 29843242 DOI: 10.3233/jad-180017] [Citation(s) in RCA: 49] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
BACKGROUND White matter hyperintensities (WMH) on magnetic resonance imaging (MRI) have been postulated to be a core feature of Alzheimer's disease. Clinicopathological studies are needed to elucidate and confirm this possibility. OBJECTIVE This study examined: 1) the association between antemortem WMH and autopsy-confirmed Alzheimer's disease neuropathology (ADNP), 2) the relationship between WMH and dementia in participants with ADNP, and 3) the relationships among cerebrovascular disease, WMH, and ADNP. METHODS The sample included 82 participants from the National Alzheimer's Coordinating Center's Data Sets who had quantitated volume of WMH from antemortem FLAIR MRI and available neuropathological data. The Clinical Dementia Rating (CDR) scale (from MRI visit) operationalized dementia status. ADNP+ was defined by moderate to frequent neuritic plaques and Braak stage III-VI at autopsy. Cerebrovascular disease neuropathology included infarcts or lacunes, microinfarcts, arteriolosclerosis, atherosclerosis, and cerebral amyloid angiopathy. RESULTS 60/82 participants were ADNP+. Greater volume of WMH predicted increased odds for ADNP (p = 0.037). In ADNP+ participants, greater WMH corresponded with increased odds for dementia (CDR≥1; p = 0.038). WMH predicted cerebral amyloid angiopathy, microinfarcts, infarcts, and lacunes (ps < 0.04). ADNP+ participants were more likely to have moderate-severe arteriolosclerosis and cerebral amyloid angiopathy compared to ADNP-participants (ps < 0.04). CONCLUSIONS This study found a direct association between total volume of WMH and increased odds for having ADNP. In patients with Alzheimer's disease, FLAIR MRI WMH may be able to provide key insight into disease severity and progression. The association between WMH and ADNP may be explained by underlying cerebrovascular disease.
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Affiliation(s)
- Michael L Alosco
- Boston University Alzheimer's Disease Center, Boston University School of Medicine, Boston, MA, USA.,Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Michael A Sugarman
- Boston University Alzheimer's Disease Center, Boston University School of Medicine, Boston, MA, USA.,Department of Neuropsychology, Edith Nourse Rogers Memorial Veterans Hospital, Bedford, MA, USA
| | - Lilah M Besser
- National Alzheimer's Coordinating Center, University of Washington, Seattle, WA, USA
| | - Yorghos Tripodis
- Boston University Alzheimer's Disease Center, Boston University School of Medicine, Boston, MA, USA.,Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Brett Martin
- Boston University Alzheimer's Disease Center, Boston University School of Medicine, Boston, MA, USA.,Biostatistics and Epidemiology Data Analytics Center, Boston University School of Public Health, Boston, MA, USA
| | - Joseph N Palmisano
- Boston University Alzheimer's Disease Center, Boston University School of Medicine, Boston, MA, USA.,Biostatistics and Epidemiology Data Analytics Center, Boston University School of Public Health, Boston, MA, USA
| | - Neil W Kowall
- Boston University Alzheimer's Disease Center, Boston University School of Medicine, Boston, MA, USA.,Department of Neurology, Boston University School of Medicine, Boston, MA, USA.,Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, MA, USA.,Neurology Service, VA Boston Healthcare System, Boston, MA, USA
| | - Rhoda Au
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA.,Framingham Heart Study, National Heart, Lung, and Blood Institute, Framingham, MA, USA.,Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA.,Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA
| | - Jesse Mez
- Boston University Alzheimer's Disease Center, Boston University School of Medicine, Boston, MA, USA.,Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Charles DeCarli
- Department of Neurology, University of California at Davis Health System, Sacramento, CA, USA
| | - Thor D Stein
- Boston University Alzheimer's Disease Center, Boston University School of Medicine, Boston, MA, USA.,Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, MA, USA.,U.S. Department of Veteran Affairs, VA Boston Healthcare System, Boston, MA, USA.,Department of Veterans Affairs Medical Center, Bedford, MA, USA
| | - Ann C McKee
- Boston University Alzheimer's Disease Center, Boston University School of Medicine, Boston, MA, USA.,Department of Neurology, Boston University School of Medicine, Boston, MA, USA.,Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, MA, USA.,U.S. Department of Veteran Affairs, VA Boston Healthcare System, Boston, MA, USA.,Department of Veterans Affairs Medical Center, Bedford, MA, USA
| | - Ronald J Killiany
- Boston University Alzheimer's Disease Center, Boston University School of Medicine, Boston, MA, USA.,Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA.,Center for Biomedical Imaging, Boston University School of Medicine, Boston, MA, USA
| | - Robert A Stern
- Boston University Alzheimer's Disease Center, Boston University School of Medicine, Boston, MA, USA.,Department of Neurology, Boston University School of Medicine, Boston, MA, USA.,Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA.,Department of Neurosurgery, Boston University School of Medicine, Boston, MA, USA
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Lowe VJ, Lundt ES, Albertson SM, Przybelski SA, Senjem ML, Parisi JE, Kantarci K, Boeve B, Jones DT, Knopman D, Jack CR, Dickson DW, Petersen RC, Murray ME. Neuroimaging correlates with neuropathologic schemes in neurodegenerative disease. Alzheimers Dement 2019; 15:927-939. [PMID: 31175025 DOI: 10.1016/j.jalz.2019.03.016] [Citation(s) in RCA: 52] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2018] [Revised: 02/05/2019] [Accepted: 03/07/2019] [Indexed: 11/16/2022]
Abstract
INTRODUCTION Neuroimaging biomarkers are important for early diagnosis of Alzheimer's disease, and comparing multimodality neuroimaging to autopsy data is essential. METHODS We compared the pathologic findings from a prospective autopsy cohort (n = 100) to Pittsburgh compound B PET (PiB-PET), 18F-fluorodeoxyglucose PET (FDG-PET), and MRI. Correlations between neuroimaging biomarkers and neuropathologic schemes were assessed. RESULTS PiB-PET showed strong correlations with Thal amyloid phase and Consortium to Establish a Registry for Alzheimer's Disease score and categorized 44% of Thal phase 1 participants as positive. FDG-PET and MRI correlated modestly with Braak tangle stage in Alzheimer's type pathology. A subset of participants with "none" or "sparse" neuritic plaque scores had elevated PiB-PET signal due to diffuse amyloid plaque. Participants with findings characterized as "suspected non-Alzheimer's pathophysiology" represented 15% of the group. DISCUSSION PiB-PET is associated with Alzheimer's disease, neuritic plaques, and diffuse plaques. FDG-PET and MRI have modest correlation with neuropathologic schemes. Participants with findings characterized as suspected non-Alzheimer's pathophysiology most commonly had primary age-related tauopathy.
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Affiliation(s)
- Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN, USA.
| | - Emily S Lundt
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | | | | | - Matthew L Senjem
- Department of Information Technology, Mayo Clinic, Rochester, MN, USA
| | - Joseph E Parisi
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA; Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Bradley Boeve
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - David T Jones
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - David Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
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Nelson PT, Dickson DW, Trojanowski JQ, Jack CR, Boyle PA, Arfanakis K, Rademakers R, Alafuzoff I, Attems J, Brayne C, Coyle-Gilchrist ITS, Chui HC, Fardo DW, Flanagan ME, Halliday G, Hokkanen SRK, Hunter S, Jicha GA, Katsumata Y, Kawas CH, Keene CD, Kovacs GG, Kukull WA, Levey AI, Makkinejad N, Montine TJ, Murayama S, Murray ME, Nag S, Rissman RA, Seeley WW, Sperling RA, White III CL, Yu L, Schneider JA. Limbic-predominant age-related TDP-43 encephalopathy (LATE): consensus working group report. Brain 2019; 142:1503-1527. [PMID: 31039256 PMCID: PMC6536849 DOI: 10.1093/brain/awz099] [Citation(s) in RCA: 851] [Impact Index Per Article: 170.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2019] [Revised: 02/10/2019] [Accepted: 02/25/2019] [Indexed: 12/18/2022] Open
Abstract
We describe a recently recognized disease entity, limbic-predominant age-related TDP-43 encephalopathy (LATE). LATE neuropathological change (LATE-NC) is defined by a stereotypical TDP-43 proteinopathy in older adults, with or without coexisting hippocampal sclerosis pathology. LATE-NC is a common TDP-43 proteinopathy, associated with an amnestic dementia syndrome that mimicked Alzheimer's-type dementia in retrospective autopsy studies. LATE is distinguished from frontotemporal lobar degeneration with TDP-43 pathology based on its epidemiology (LATE generally affects older subjects), and relatively restricted neuroanatomical distribution of TDP-43 proteinopathy. In community-based autopsy cohorts, ∼25% of brains had sufficient burden of LATE-NC to be associated with discernible cognitive impairment. Many subjects with LATE-NC have comorbid brain pathologies, often including amyloid-β plaques and tauopathy. Given that the 'oldest-old' are at greatest risk for LATE-NC, and subjects of advanced age constitute a rapidly growing demographic group in many countries, LATE has an expanding but under-recognized impact on public health. For these reasons, a working group was convened to develop diagnostic criteria for LATE, aiming both to stimulate research and to promote awareness of this pathway to dementia. We report consensus-based recommendations including guidelines for diagnosis and staging of LATE-NC. For routine autopsy workup of LATE-NC, an anatomically-based preliminary staging scheme is proposed with TDP-43 immunohistochemistry on tissue from three brain areas, reflecting a hierarchical pattern of brain involvement: amygdala, hippocampus, and middle frontal gyrus. LATE-NC appears to affect the medial temporal lobe structures preferentially, but other areas also are impacted. Neuroimaging studies demonstrated that subjects with LATE-NC also had atrophy in the medial temporal lobes, frontal cortex, and other brain regions. Genetic studies have thus far indicated five genes with risk alleles for LATE-NC: GRN, TMEM106B, ABCC9, KCNMB2, and APOE. The discovery of these genetic risk variants indicate that LATE shares pathogenetic mechanisms with both frontotemporal lobar degeneration and Alzheimer's disease, but also suggests disease-specific underlying mechanisms. Large gaps remain in our understanding of LATE. For advances in prevention, diagnosis, and treatment, there is an urgent need for research focused on LATE, including in vitro and animal models. An obstacle to clinical progress is lack of diagnostic tools, such as biofluid or neuroimaging biomarkers, for ante-mortem detection of LATE. Development of a disease biomarker would augment observational studies seeking to further define the risk factors, natural history, and clinical features of LATE, as well as eventual subject recruitment for targeted therapies in clinical trials.
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Affiliation(s)
| | | | | | | | | | - Konstantinos Arfanakis
- Rush University Medical Center, Chicago, IL, USA
- Illinois Institute of Technology, Chicago, IL, USA
| | | | | | | | | | | | - Helena C Chui
- University of Southern California, Los Angeles, CA, USA
| | | | | | - Glenda Halliday
- The University of Sydney Brain and Mind Centre and Central Clinical School Faculty of Medicine and Health, Sydney, Australia
| | | | | | | | | | | | | | - Gabor G Kovacs
- Institute of Neurology Medical University of Vienna, Vienna, Austria
| | | | | | | | | | - Shigeo Murayama
- Tokyo Metropolitan Geriatric Hospital and Institute of Gerontology, Tokyo, Japan
| | | | - Sukriti Nag
- Rush University Medical Center, Chicago, IL, USA
| | | | | | | | | | - Lei Yu
- Rush University Medical Center, Chicago, IL, USA
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41
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Bartos A, Gregus D, Ibrahim I, Tintěra J. Brain volumes and their ratios in Alzheimer´s disease on magnetic resonance imaging segmented using Freesurfer 6.0. Psychiatry Res Neuroimaging 2019; 287:70-74. [PMID: 31003044 DOI: 10.1016/j.pscychresns.2019.01.014] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2018] [Revised: 12/21/2018] [Accepted: 01/21/2019] [Indexed: 11/17/2022]
Abstract
Ratios between opposing volumes from brain magnetic resonance imaging (MRI) can provide additional information to volumes in Alzheimer's disease (AD). Brain three-dimensional MPRAGE MRI at 3T were segmented into 44 regions using FreeSurfer v6 in 75 participants. The region's size in absolute volumes and relative proportions to the whole brain volume were compared between 39 AD patients and 36 age-, education- and sex-matched normal controls (NC). Volumes of the most atrophied parts were related to the opposing volumes of the most enlarged parts as ratios. The most atrophic structures in AD were both hippocampi. By contrast, the greatest enlargements in AD were inferior parts of both lateral ventricles. The best ratio for each side was the hippocampo-horn proportion calculated as ratio: the hippocampus / (the hippocampus + inferior lateral ventricle). Its optimal cut-off of 74% yielded sensitivity of 74% and specificity of 78% on the left and sensitivity of 74% and specificity of 78% on the right. The hippocampo-horn proportion is another measure to evaluate the degree of hippocampal atrophy on brain MRI in percentages. It has a potential to be simplified into a comparison of two-dimensional corresponding areas or a visual assessment.
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Affiliation(s)
- Ales Bartos
- National Institute of Mental Health, Topolová 748, Klecany 250 67, Czechia; Charles University, Third Faculty of Medicine, University Hospital Královské Vinohrady, Department of Neurology, AD Center, Šrobárova 50, 100 34 Prague 10, Czechia.
| | - David Gregus
- National Institute of Mental Health, Topolová 748, Klecany 250 67, Czechia; Charles University, Third Faculty of Medicine, University Hospital Královské Vinohrady, Department of Neurology, AD Center, Šrobárova 50, 100 34 Prague 10, Czechia
| | | | - Jaroslav Tintěra
- National Institute of Mental Health, Topolová 748, Klecany 250 67, Czechia; Institute of Clinical and Experimental Medicine, Czechia
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42
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Alber J, Alladi S, Bae HJ, Barton DA, Beckett LA, Bell JM, Berman SE, Biessels GJ, Black SE, Bos I, Bowman GL, Brai E, Brickman AM, Callahan BL, Corriveau RA, Fossati S, Gottesman RF, Gustafson DR, Hachinski V, Hayden KM, Helman AM, Hughes TM, Isaacs JD, Jefferson AL, Johnson SC, Kapasi A, Kern S, Kwon JC, Kukolja J, Lee A, Lockhart SN, Murray A, Osborn KE, Power MC, Price BR, Rhodius-Meester HF, Rondeau JA, Rosen AC, Rosene DL, Schneider JA, Scholtzova H, Shaaban CE, Silva NC, Snyder HM, Swardfager W, Troen AM, van Veluw SJ, Vemuri P, Wallin A, Wellington C, Wilcock DM, Xie SX, Hainsworth AH. White matter hyperintensities in vascular contributions to cognitive impairment and dementia (VCID): Knowledge gaps and opportunities. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2019; 5:107-117. [PMID: 31011621 PMCID: PMC6461571 DOI: 10.1016/j.trci.2019.02.001] [Citation(s) in RCA: 249] [Impact Index Per Article: 49.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
White matter hyperintensities (WMHs) are frequently seen on brain magnetic resonance imaging scans of older people. Usually interpreted clinically as a surrogate for cerebral small vessel disease, WMHs are associated with increased likelihood of cognitive impairment and dementia (including Alzheimer's disease [AD]). WMHs are also seen in cognitively healthy people. In this collaboration of academic, clinical, and pharmaceutical industry perspectives, we identify outstanding questions about WMHs and their relation to cognition, dementia, and AD. What molecular and cellular changes underlie WMHs? What are the neuropathological correlates of WMHs? To what extent are demyelination and inflammation present? Is it helpful to subdivide into periventricular and subcortical WMHs? What do WMHs signify in people diagnosed with AD? What are the risk factors for developing WMHs? What preventive and therapeutic strategies target WMHs? Answering these questions will improve prevention and treatment of WMHs and dementia.
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Affiliation(s)
- Jessica Alber
- Department of Biomedical and Pharmaceutical Sciences, George & Anne Ryan Institute for Neuroscience, University of Rhode Island, Kingston, RI, USA
| | - Suvarna Alladi
- Department of Neurology, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India
| | - Hee-Joon Bae
- Cerebrovascular Disease Center, Seoul National University Bundang Hospital, Seongnam, Korea
| | - David A. Barton
- Department of Psychiatry, University of Melbourne, Melbourne, Australia
| | - Laurel A. Beckett
- Department of Public Health Sciences, School of Medicine University of California, Davis, CA, USA
| | | | - Sara E. Berman
- Wisconsin Alzheimer's Disease Research Center, Medical Scientist Training Program, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Geert Jan Biessels
- Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus Institute, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Sandra E. Black
- Department of Medicine, University of Toronto, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Isabelle Bos
- Department of Psychiatry & Neuropsychology, Alzheimer Centre Limburg, School for Mental Health & Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Gene L. Bowman
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Institute for Aging Research, Hebrew SeniorLife, Boston, MA, USA
- Department of Neurology, Oregon Health & Science University, Portland, OR, USA
| | | | - Adam M. Brickman
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Brandy L. Callahan
- Department of Psychology, University of Calgary & Hotchkiss Brain Institute, Calgary, AB, Canada
| | - Roderick A. Corriveau
- Department of Psychology, University of Calgary & Hotchkiss Brain Institute, Calgary, AB, Canada
| | - Silvia Fossati
- Departments of Neurology and Psychiatry, NYU School of Medicine, New York, NY, USA
| | - Rebecca F. Gottesman
- Division of Cerebrovascular Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Deborah R. Gustafson
- Section for NeuroEpidemiology, State University of New York - Downstate Medical Center, Brooklyn, NY, USA
| | | | - Kathleen M. Hayden
- Department of Social Sciences and Health Policy, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Alex M. Helman
- University of Kentucky, Sanders-Brown Center on Aging, Lexington, KY, USA
| | - Timothy M. Hughes
- Department of Internal Medicine – Section of Gerontology and Geriatric Medicine, and Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Jeremy D. Isaacs
- St George's University of London and Department of Neurology, St George's University Hospitals NHS Foundation Trust, London, UK
| | - Angela L. Jefferson
- Vanderbilt Memory & Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Sterling C. Johnson
- Department of Medicine-Geriatrics, Institute on Aging, University of Wisconsin-Madison, Madison, WI, USA
| | - Alifiya Kapasi
- Department of Pathology (Neuropathology), Rush Alzheimer's Disease Center, Chicago, IL, USA
| | - Silke Kern
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
| | - Jay C. Kwon
- Department of Neurology, Changwon Fatima Hospital, Changwon, Korea
| | - Juraj Kukolja
- Department of Neurology and Clinical Neurophysiology, Helios University Hospital Wuppertal, Wuppertal, Germany
| | - Athene Lee
- Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, RI, USA
| | - Samuel N. Lockhart
- Department of Internal Medicine – Section of Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Anne Murray
- Berman Center for Outcomes and Clinical Research, 20298 Minneapolis Medical Research Foundation, Minneapolis, MN, USA
| | - Katie E. Osborn
- Vanderbilt Memory & Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Melinda C. Power
- Department of Epidemiology and Biostatistics, Milken Institute School of Public Health, George Washington University, Washington, DC, USA
| | - Brittani R. Price
- Sanders Brown Center on Aging, University of Kentucky, Lexington, KY, USA
| | - Hanneke F.M. Rhodius-Meester
- Alzheimer Center, Department of Neurology, VU University Medical Centre, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | | | - Allyson C. Rosen
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Douglas L. Rosene
- Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, USA
| | - Julie A. Schneider
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago IL, USA
| | | | - C. Elizabeth Shaaban
- Department of Epidemiology, Graduate School of Public Health & Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA, USA
| | - Narlon C.B.S. Silva
- School of Kinesiology, Western Centre for Public Health & Family Medicine, London, ON, Canada
| | - Heather M. Snyder
- Division of Medical and Scientific Relations, Alzheimer's Association, Chicago, IL, USA
| | - Walter Swardfager
- Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Aron M. Troen
- Institute of Biochemistry Food Science and Nutrition, The Robert H. Smith Faculty of Agriculture Food and Environment, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Susanne J. van Veluw
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Anders Wallin
- Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden
| | - Cheryl Wellington
- Department of Pathology and Laboratory Medicine, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada
| | - Donna M. Wilcock
- Sanders-Brown Center on Aging, Department of Physiology, University of Kentucky, Lexington, KY, USA
| | - Sharon Xiangwen Xie
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, USA
| | - Atticus H. Hainsworth
- Molecular & Clinical Sciences Research Institute, St George's University of London and Department of Neurology, St George's University Hospitals NHS Foundation Trust, London, UK
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Venturelli M, Pedrinolla A, Boscolo Galazzo I, Fonte C, Smania N, Tamburin S, Muti E, Crispoltoni L, Stabile A, Pistilli A, Rende M, Pizzini FB, Schena F. Impact of Nitric Oxide Bioavailability on the Progressive Cerebral and Peripheral Circulatory Impairments During Aging and Alzheimer's Disease. Front Physiol 2018; 9:169. [PMID: 29593548 PMCID: PMC5861210 DOI: 10.3389/fphys.2018.00169] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2018] [Accepted: 02/20/2018] [Indexed: 11/19/2022] Open
Abstract
Advanced aging, vascular dysfunction, and nitric oxide (NO) bioavailability are recognized risk factors for Alzheimer's disease (AD). However, the contribution of AD, per se, to this putative pathophysiological mechanism is still unclear. To better answer this point, we quantified cortical perfusion with arterial spin labeling (PVC-CBF), measured ultrasound internal carotid (ICA), and femoral (FA) artery blood flow in a group of patients with similar age (~78 years) but different cognitive impairment (i.e., mild cognitive impairment MCI, mild AD-AD1, moderate AD-AD2, and severe AD-AD3) and compared them to young and healthy old (aged-matched) controls. NO-metabolites and passive leg-movement (PLM) induced hyperemia were used to assess systemic vascular function. Ninety-eight individuals were recruited for this study. PVC-CBF, ICA, and FA blood flow were markedly (range of 9–17%) and significantly (all p < 0.05) reduced across the spectrum from YG to OLD, MCI, AD1, AD2, AD3 subjects. Similarly, plasma level of nitrates and the values of PLM were significantly reduced (range of 8–26%; p < 0.05) among the six groups. Significant correlations were retrieved between plasma nitrates, PLM and PVC-CBF, CA, and FA blood flow. This integrative and comprehensive approach to vascular changes in aging and AD showed progressive changes in NO bioavailability and cortical, extracranial, and peripheral circulation in patients with AD and suggested that they are directly associated with AD and not to aging. Moreover, these results suggest that AD-related impairments of circulation are progressive and not confined to the brain. The link between cardiovascular and the central nervous systems degenerative processes in patients at different severity of AD is likely related to the depletion of NO.
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Affiliation(s)
- Massimo Venturelli
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | | | | | - Cristina Fonte
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy.,Neuromotor and Cognitive Rehabilitation Research Centre, University of Verona, Verona, Italy
| | - Nicola Smania
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy.,Neuromotor and Cognitive Rehabilitation Research Centre, University of Verona, Verona, Italy
| | - Stefano Tamburin
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | | | - Lucia Crispoltoni
- Department of Surgical and Biomedical Sciences, Section of Human Anatomy, School of Medicine, University of Perugia, Perugia, Italy
| | - Annamaria Stabile
- Department of Surgical and Biomedical Sciences, Section of Human Anatomy, School of Medicine, University of Perugia, Perugia, Italy
| | - Alessandra Pistilli
- Department of Surgical and Biomedical Sciences, Section of Human Anatomy, School of Medicine, University of Perugia, Perugia, Italy
| | - Mario Rende
- Department of Surgical and Biomedical Sciences, Section of Human Anatomy, School of Medicine, University of Perugia, Perugia, Italy
| | - Francesca B Pizzini
- Neuroradiology, Department of Diagnostics and Pathology, Verona University Hospital, Verona, Italy
| | - Federico Schena
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
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44
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Guo H, Siu W, D’Arcy RCN, Black SE, Grajauskas LA, Singh S, Zhang Y, Rockwood K, Song X. MRI assessment of whole-brain structural changes in aging. Clin Interv Aging 2017; 12:1251-1270. [PMID: 28848333 PMCID: PMC5557118 DOI: 10.2147/cia.s139515] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
PURPOSE One of the central features of brain aging is the accumulation of multiple age-related structural changes, which occur heterogeneously in individuals and can have immediate or potential clinical consequences. Each of these deficits can coexist and interact, producing both independent and additive impacts on brain health. Many of the changes can be visualized using MRI. To collectively assess whole-brain structural changes, the MRI-based Brain Atrophy and Lesion Index (BALI) has been developed. In this study, we validate this whole-brain health assessment approach using several clinical MRI examinations. MATERIALS AND METHODS Data came from three independent studies: the Alzheimer's Disease Neuroimaging Initiative Phase II (n=950; women =47.9%; age =72.7±7.4 years); the National Alzheimer's Coordinating Center (n=722; women =55.1%; age =72.7±9.9 years); and the Tianjin Medical University General Hospital Research database on older adults (n=170; women =60.0%; age =62.9±9.3 years). The 3.0-Tesla MRI scans were evaluated using the BALI rating scheme on the basis of T1-weighted (T1WI), T2-weighted (T2WI), T2-weighted fluid-attenuated inversion recovery (T2-FLAIR), and T2*-weighted gradient-recalled echo (T2*GRE) images. RESULTS Atrophy and lesion changes were commonly seen in each MRI test. The BALI scores based on different sequences were highly correlated (Spearman r2>0.69; P<0.00001). They were associated with age (r2>0.29; P<0.00001) and differed by cognitive status (χ2>26.48, P<0.00001). T2-FLAIR revealed a greater level of periventricular (χ2=29.09) and deep white matter (χ2=26.65, P<0.001) lesions than others, but missed revealing certain dilated perivascular spaces that were seen in T2WI (P<0.001). Microhemorrhages occurred in 15.3% of the sample examined and were detected using only T2*GRE. CONCLUSION The T1WI- and T2WI-based BALI evaluations consistently identified the burden of aging and dementia-related decline of structural brain health. Inclusion of additional MRI tests increased lesion differentiation. Further research is to integrate MRI tests for a clinical tool to aid the diagnosis and intervention of brain aging.
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Affiliation(s)
- Hui Guo
- Health Sciences and Innovation, ImageTech Laboratory, Fraser Health Authority, Surrey, BC, Canada
- Department of Diagnostic Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - William Siu
- Health Sciences and Innovation, ImageTech Laboratory, Fraser Health Authority, Surrey, BC, Canada
- Department of Medical Imaging, Fraser Health Authority, Surrey
| | - Ryan CN D’Arcy
- Health Sciences and Innovation, ImageTech Laboratory, Fraser Health Authority, Surrey, BC, Canada
- Departments of Applied Sciences and Computing Science, Simon Fraser University, Burnaby, BC
| | - Sandra E Black
- Department of Medicine (Neurology)
- LC Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre & University of Toronto, Toronto, ON
| | - Lukas A Grajauskas
- Health Sciences and Innovation, ImageTech Laboratory, Fraser Health Authority, Surrey, BC, Canada
- Departments of Applied Sciences and Computing Science, Simon Fraser University, Burnaby, BC
| | - Sonia Singh
- Department of Family Medicine, University of British Columbia, Vancouver, BC
- Department of Research and Evaluation, Fraser Health, Surrey, BC
| | - Yunting Zhang
- Department of Diagnostic Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Kenneth Rockwood
- Department of Medicine (Geriatric Medicine), Dalhousie University
- Centre for Healthcare of the Elderly, Nova Scotia Health Authority, Halifax, NS, Canada
| | - Xiaowei Song
- Health Sciences and Innovation, ImageTech Laboratory, Fraser Health Authority, Surrey, BC, Canada
- Departments of Applied Sciences and Computing Science, Simon Fraser University, Burnaby, BC
- Department of Medicine (Geriatric Medicine), Dalhousie University
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45
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Callahan BL, Bierstone D, Stuss DT, Black SE. Adult ADHD: Risk Factor for Dementia or Phenotypic Mimic? Front Aging Neurosci 2017; 9:260. [PMID: 28824421 PMCID: PMC5540971 DOI: 10.3389/fnagi.2017.00260] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2017] [Accepted: 07/21/2017] [Indexed: 12/21/2022] Open
Abstract
Attention-deficit hyperactivity disorder (ADHD) has historically been considered a disorder of childhood and adolescence. However, it is now recognized that ADHD symptoms persist into adulthood in up to 60% of individuals. Some of the cognitive symptoms that characterize ADHD (inability to provide sustained attention or mental effort, difficulty organizing or multi-tasking, forgetfulness) may closely resemble symptoms of prodromal dementia, also often referred to as mild cognitive impairment (MCI), particularly in patients over age 50. In addition to the overlap in cognitive symptoms, adults with ADHD and those with MCI may also share a number of behavioral and psychiatric symptoms, including sleep disturbances, depression, and anxiety. As a result, both syndromes may be difficult to distinguish clinically in older patients, particularly those who present to memory clinics with subjective cognitive complaints and fear the onset of a neurodegenerative process: is it ADHD, MCI, or both? Currently, it is unclear whether ADHD is associated with incipient dementia or is being misdiagnosed as MCI due to symptom overlap, as there exist data supporting either possibility. Here, we aim to elucidate this issue by outlining three hypothetical ways in which ADHD and MCI might relate to each other, providing an overview of the evidence relevant to each hypothesis, and delineating areas for future research. This is a question of considerable importance, with implications for improved diagnostic specificity of early dementia, improved accuracy of disease prevalence estimates, and better identification of individuals for targeted treatment.
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Affiliation(s)
- Brandy L Callahan
- Department of Psychology, University of CalgaryCalgary, AB, Canada.,Hotchkiss Brain InstituteCalgary, AB, Canada.,Sunnybrook Health Sciences Centre, Sunnybrook Research InstituteToronto, ON, Canada
| | - Daniel Bierstone
- LC Campbell Cognitive Neurology Research Unit, Sunnybrook Health Sciences CentreToronto, ON, Canada.,Faculty of Medicine, University of TorontoToronto, ON, Canada
| | - Donald T Stuss
- Faculty of Medicine, University of TorontoToronto, ON, Canada.,Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute and University of TorontoToronto, ON, Canada
| | - Sandra E Black
- Sunnybrook Health Sciences Centre, Sunnybrook Research InstituteToronto, ON, Canada.,LC Campbell Cognitive Neurology Research Unit, Sunnybrook Health Sciences CentreToronto, ON, Canada.,Faculty of Medicine, University of TorontoToronto, ON, Canada.,Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute and University of TorontoToronto, ON, Canada.,Heart and Stroke Foundation Canadian Partnership in Stroke Recovery, Sunnybrook Health Sciences CentreToronto, ON, Canada.,Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre and University of TorontoToronto, ON, Canada
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