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Jing C, Kong M, Ng KP, Xu L, Ma G, Ba M. Hippocampal volume maximally modulates the relationship between subsyndromal symptomatic depression and cognitive impairment in non-demented older adults. J Affect Disord 2024; 367:640-646. [PMID: 39245222 DOI: 10.1016/j.jad.2024.09.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Revised: 07/29/2024] [Accepted: 09/05/2024] [Indexed: 09/10/2024]
Abstract
BACKGROUND Subsyndromal symptomatic depression (SSD) is associated with an elevated risk of cognitive impairment in non-demented older adults. Given that hippocampal and middle temporal gyrus atrophy have been shown to cause SSD, our study aimed to investigate the effect of hippocampal volume on the association between SSD and cognitive impairment. METHODS 338 non-demented older adults from the ADNI (Alzheimer's Disease Neuroimaging Initiative) cohort who underwent cognitive assessments, questionnaires on depressive symptoms and MRI brain were studied. SSD group is defined as a score of 1-5 based on Geriatric Depression Scale scores. We conducted causal mediation analyses to investigate the effect of hippocampal volume on cognitive performance cross-sectionally. RESULTS The SSD group displayed lower left and right hippocampal volume (p<0.01) than the non-SSD group. SSD was linked to poorer cognition and smaller hippocampal volume. We found that hippocampal volume partially mediated the effect of SSD on cognitive performance including the global cognition and the cognitive section of Alzheimer's Disease Assessment Scale, with mediation percentages ranging from 6.45 % to 30.46 %. In addition, we found that the thickness of the left middle temporal, right entorhinal and right fusiform gyrus, brain regions linked to AD, mediate the relationship between SSD and cognition with mediation percentages ranging from 8.67 % to 21.44 %. LIMITATIONS Our article didn't differentiate between mild cognitive impairment and normal population. CONCLUSION The associations of SSD and cognitive impairment are linked to alterations in Alzheimer's Disease related brain regions.
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Affiliation(s)
- Chenxi Jing
- Department of Neurology, the Affiliated Yantai Yuhuangding Hospital of Qingdao University, Shandong 264000, China
| | - Min Kong
- Department of Neurology, Yantaishan Hospital, Yantai City, Shandong 264000, China
| | - Kok Pin Ng
- Department of Neurology, National Neuroscience Institute, Singapore, Singapore; Duke-NUS Medical School, Singapore, Singapore
| | - Lijuan Xu
- Department of Neurology, the Affiliated Yantai Yuhuangding Hospital of Qingdao University, Shandong 264000, China
| | - Guozhao Ma
- Department of Neurology, East Hospital, Tongji University School of Medicine, Shanghai 200120, China.
| | - Maowen Ba
- Department of Neurology, the Affiliated Yantai Yuhuangding Hospital of Qingdao University, Shandong 264000, China; Yantai Regional Sub Center of National Center for Clinical Medical Research of Neurological Diseases, Shandong, China; Shandong Provincial Key Laboratory of Neuroimmune Interaction and Regulation, China.
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2
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Alarjani M, Almarri B. Multivariate pattern analysis of medical imaging-based Alzheimer's disease. Front Med (Lausanne) 2024; 11:1412592. [PMID: 39099597 PMCID: PMC11294205 DOI: 10.3389/fmed.2024.1412592] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2024] [Accepted: 06/06/2024] [Indexed: 08/06/2024] Open
Abstract
Alzheimer's disease (AD) is a devastating brain disorder that steadily worsens over time. It is marked by a relentless decline in memory and cognitive abilities. As the disease progresses, it leads to a significant loss of mental function. Early detection of AD is essential to starting treatments that can mitigate the progression of this disease and enhance patients' quality of life. This study aims to observe AD's brain functional connectivity pattern to extract essential patterns through multivariate pattern analysis (MVPA) and analyze activity patterns across multiple brain voxels. The optimized feature extraction techniques are used to obtain the important features for performing the training on the models using several hybrid machine learning classifiers for performing binary classification and multi-class classification. The proposed approach using hybrid machine learning classification has been applied to two public datasets named the Open Access Series of Imaging Studies (OASIS) and the AD Neuroimaging Initiative (ADNI). The results are evaluated using performance metrics, and comparisons have been made to differentiate between different stages of AD using visualization tools.
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Affiliation(s)
| | - Badar Almarri
- Department of Computer Science, College of Computer Sciences and Information Technology, King Faisal University, Al-Hofuf, Saudi Arabia
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3
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Tsiakiri A, Bakirtzis C, Plakias S, Vlotinou P, Vadikolias K, Terzoudi A, Christidi F. Predictive Models for the Transition from Mild Neurocognitive Disorder to Major Neurocognitive Disorder: Insights from Clinical, Demographic, and Neuropsychological Data. Biomedicines 2024; 12:1232. [PMID: 38927439 PMCID: PMC11201179 DOI: 10.3390/biomedicines12061232] [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: 04/27/2024] [Revised: 05/27/2024] [Accepted: 05/29/2024] [Indexed: 06/28/2024] Open
Abstract
Neurocognitive disorders (NCDs) are progressive conditions that severely impact cognitive function and daily living. Understanding the transition from mild to major NCD is crucial for personalized early intervention and effective management. Predictive models incorporating demographic variables, clinical data, and scores on neuropsychological and emotional tests can significantly enhance early detection and intervention strategies in primary healthcare settings. We aimed to develop and validate predictive models for the progression from mild NCD to major NCD using demographic, clinical, and neuropsychological data from 132 participants over a two-year period. Generalized Estimating Equations were employed for data analysis. Our final model achieved an accuracy of 83.7%. A higher body mass index and alcohol drinking increased the risk of progression from mild NCD to major NCD, while female sex, higher praxis abilities, and a higher score on the Geriatric Depression Scale reduced the risk. Here, we show that integrating multiple factors-ones that can be easily examined in clinical settings-into predictive models can improve early diagnosis of major NCD. This approach could facilitate timely interventions, potentially mitigating the progression of cognitive decline and improving patient outcomes in primary healthcare settings. Further research should focus on validating these models across diverse populations and exploring their implementation in various clinical contexts.
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Affiliation(s)
- Anna Tsiakiri
- Neurology Department, School of Medicine, Democritus University of Thrace, 68100 Alexandroupolis, Greece; (A.T.); (K.V.); (A.T.)
| | - Christos Bakirtzis
- B’ Department of Neurology and the MS Center, School of Medicine, AHEPA University Hospital, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece;
| | - Spyridon Plakias
- Department of Physical Education and Sport Science, University of Thessaly, 41500 Trikala, Greece;
| | - Pinelopi Vlotinou
- Department of Occupational Therapy, University of West Attica, 12243 Athens, Greece;
| | - Konstantinos Vadikolias
- Neurology Department, School of Medicine, Democritus University of Thrace, 68100 Alexandroupolis, Greece; (A.T.); (K.V.); (A.T.)
| | - Aikaterini Terzoudi
- Neurology Department, School of Medicine, Democritus University of Thrace, 68100 Alexandroupolis, Greece; (A.T.); (K.V.); (A.T.)
| | - Foteini Christidi
- Neurology Department, School of Medicine, Democritus University of Thrace, 68100 Alexandroupolis, Greece; (A.T.); (K.V.); (A.T.)
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4
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Wang J, Hill‐Jarrett T, Buto P, Pederson A, Sims KD, Zimmerman SC, DeVost MA, Ferguson E, Lacar B, Yang Y, Choi M, Caunca MR, La Joie R, Chen R, Glymour MM, Ackley SF. Comparison of approaches to control for intracranial volume in research on the association of brain volumes with cognitive outcomes. Hum Brain Mapp 2024; 45:e26633. [PMID: 38433682 PMCID: PMC10910271 DOI: 10.1002/hbm.26633] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 01/30/2024] [Accepted: 02/07/2024] [Indexed: 03/05/2024] Open
Abstract
Most neuroimaging studies linking regional brain volumes with cognition correct for total intracranial volume (ICV), but methods used for this correction differ across studies. It is unknown whether different ICV correction methods yield consistent results. Using a brain-wide association approach in the MRI substudy of UK Biobank (N = 41,964; mean age = 64.5 years), we used regression models to estimate the associations of 58 regional brain volumetric measures with eight cognitive outcomes, comparing no correction and four ICV correction approaches. Approaches evaluated included: no correction; dividing regional volumes by ICV (proportional approach); including ICV as a covariate in the regression (adjustment approach); and regressing the regional volumes against ICV in different normative samples and using calculated residuals to determine associations (residual approach). We used Spearman-rank correlations and two consistency measures to quantify the extent to which associations were inconsistent across ICV correction approaches for each possible brain region and cognitive outcome pair across 2320 regression models. When the association between brain volume and cognitive performance was close to null, all approaches produced similar estimates close to the null. When associations between a regional volume and cognitive test were not null, the adjustment and residual approaches typically produced similar estimates, but these estimates were inconsistent with results from the crude and proportional approaches. For example, when using the crude approach, an increase of 0.114 (95% confidence interval [CI]: 0.103-0.125) in fluid intelligence was associated with each unit increase in hippocampal volume. However, when using the adjustment approach, the increase was 0.055 (95% CI: 0.043-0.068), while the proportional approach showed a decrease of -0.025 (95% CI: -0.035 to -0.014). Different commonly used methods to correct for ICV yielded inconsistent results. The proportional method diverges notably from other methods and results were sometimes biologically implausible. A simple regression adjustment for ICV produced biologically plausible associations.
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Affiliation(s)
- Jingxuan Wang
- Department of Epidemiology and BiostatisticsUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of EpidemiologyBoston UniversityBostonMassachusettsUSA
| | | | - Peter Buto
- Department of Epidemiology and BiostatisticsUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of EpidemiologyBoston UniversityBostonMassachusettsUSA
| | - Annie Pederson
- Department of Epidemiology and BiostatisticsUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of EpidemiologyBoston UniversityBostonMassachusettsUSA
| | - Kendra D. Sims
- Department of Epidemiology and BiostatisticsUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of EpidemiologyBoston UniversityBostonMassachusettsUSA
| | - Scott C. Zimmerman
- Department of Epidemiology and BiostatisticsUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Michelle A. DeVost
- Department of Epidemiology and BiostatisticsUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Erin Ferguson
- Department of Epidemiology and BiostatisticsUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Benjamin Lacar
- Bakar Computational Health Sciences InstituteUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Yulin Yang
- Department of Epidemiology and BiostatisticsUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Minhyuk Choi
- Department of Epidemiology and BiostatisticsUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Michelle R. Caunca
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Renaud La Joie
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Ruijia Chen
- Department of Epidemiology and BiostatisticsUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - M. Maria Glymour
- Department of EpidemiologyBoston UniversityBostonMassachusettsUSA
| | - Sarah F. Ackley
- Department of EpidemiologyBoston UniversityBostonMassachusettsUSA
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5
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Setiadi TM, Marsman JBC, Martens S, Tumati S, Opmeer EM, Reesink FE, De Deyn PP, Atienza M, Aleman A, Cantero JL. Alterations in Gray Matter Structural Networks in Amnestic Mild Cognitive Impairment: A Source-Based Morphometry Study. J Alzheimers Dis 2024; 101:61-73. [PMID: 39093069 PMCID: PMC11380280 DOI: 10.3233/jad-231196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/04/2024]
Abstract
Background Amnestic mild cognitive impairment (aMCI), considered as the prodromal stage of Alzheimer's disease, is characterized by isolated memory impairment and cerebral gray matter volume (GMV) alterations. Previous structural MRI studies in aMCI have been mainly based on univariate statistics using voxel-based morphometry. Objective We investigated structural network differences between aMCI patients and cognitively normal older adults by using source-based morphometry, a multivariate approach that considers the relationship between voxels of various parts of the brain. Methods Ninety-one aMCI patients and 80 cognitively normal controls underwent structural MRI and neuropsychological assessment. Spatially independent components (ICs) that covaried between participants were estimated and a multivariate analysis of covariance was performed with ICs as dependent variables, diagnosis as independent variable, and age, sex, education level, and site as covariates. Results aMCI patients exhibited reduced GMV in the precentral, temporo-cerebellar, frontal, and temporal network, and increased GMV in the left superior parietal network compared to controls (pFWER < 0.05, Holm-Bonferroni correction). Moreover, we found that diagnosis, more specifically aMCI, moderated the positive relationship between occipital network and Mini-Mental State Examination scores (pFWER < 0.05, Holm-Bonferroni correction). Conclusions Our results showed GMV alterations in temporo-fronto-parieto-cerebellar networks in aMCI, extending previous results obtained with univariate approaches.
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Affiliation(s)
- Tania M Setiadi
- Department of Biomedical Sciences of Cells & Systems, Cognitive Neuroscience Center, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Jan-Bernard C Marsman
- Department of Biomedical Sciences of Cells & Systems, Cognitive Neuroscience Center, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Sander Martens
- Department of Biomedical Sciences of Cells & Systems, Cognitive Neuroscience Center, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Shankar Tumati
- Department of Biomedical Sciences of Cells & Systems, Cognitive Neuroscience Center, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Neuropsychopharmacology Research Group, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Esther M Opmeer
- Department of Biomedical Sciences of Cells & Systems, Cognitive Neuroscience Center, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Department of Health and Welfare, Windesheim University of Applied Sciences, Zwolle, The Netherlands
| | - Fransje E Reesink
- Department of Neurology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Peter P De Deyn
- Department of Neurology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Laboratory of Neurochemistry and Behavior, Experimental Neurobiology Group, University of Antwerp, Antwerp, Belgium
| | - Mercedes Atienza
- Laboratory of Functional Neuroscience, Pablo de Olavide University, Seville, Spain
- CIBER de Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - André Aleman
- Department of Biomedical Sciences of Cells & Systems, Cognitive Neuroscience Center, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Department of Psychology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Jose L Cantero
- Laboratory of Functional Neuroscience, Pablo de Olavide University, Seville, Spain
- CIBER de Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
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Zhang J, Cao X, Li X, Li X, Hao M, Xia Y, Huang H, Jørgensen TSH, Agogo GO, Wang L, Zhang X, Gao X, Liu Z. Associations of Midlife Dietary Patterns with Incident Dementia and Brain Structure: Findings from the UK Biobank Study. Am J Clin Nutr 2023:S0002-9165(23)48900-9. [PMID: 37150507 DOI: 10.1016/j.ajcnut.2023.05.007] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2022] [Revised: 04/28/2023] [Accepted: 05/02/2023] [Indexed: 05/09/2023] Open
Abstract
BACKGROUND At present, the results on the associations between dietary patterns and the risk of dementia are inconsistent, and studies on the associations between dietary patterns and brain structures are limited. OBJECTIVE We aimed to investigate the associations of midlife dietary patterns with incident dementia and brain structures. METHODS Based on the UK Biobank Study, we investigated the 1) prospective associations of four healthy dietary pattern indices (healthy plant-based diet index [hPDI], Mediterranean diet score [MDS], Recommended food score [RFS], and Mediterranean-Dietary Approaches to Stop Hypertension Intervention [DASH] Intervention for Neurodegenerative Delay Diet [MIND]) with incident dementia (identified using linked hospital data; N = 114,684; mean age, 56.8 years; 55.5% females) using Cox proportional-hazards regressions and the 2) cross-sectional associations of these dietary pattern indices with brain structures (estimated using magnetic resonance imaging; N = 18,214; mean age, 55.9 years; 53.1% females) using linear regressions. A series of covariates were adjusted, and several sensitivity analyses were conducted. RESULTS A total of 481 (0.42%) participants developed dementia during the average 9.4-year follow-up. Although the associations were not statistically significant, all dietary patterns exerted protective effects against incident dementia (all hazard ratios < 1). Furthermore, higher dietary pattern indices were significantly associated with larger regional brain volumes, including volumes of gray matter in the parietal and temporal cortices and volumes of the hippocampus and thalamus. The main results were confirmed via sensitivity analyses. CONCLUSIONS Greater adherence to hPDI, MDS, RFS, and MIND was individually associated with larger brain volumes in specific regions. This study shows a comprehensive picture of the consistent associations of midlife dietary patterns with the risk of dementia and brain health, underscoring the potential benefits of a healthy diet in the prevention of dementia.
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Affiliation(s)
- Jingyun Zhang
- Department of Big Data in Health Science School of Public Health and Center for Clinical Big Data and Analytics of the Second Affiliated Hospital, Zhejiang University School of Medicine, the Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou 310058, Zhejiang, China
| | - Xingqi Cao
- Department of Big Data in Health Science School of Public Health and Center for Clinical Big Data and Analytics of the Second Affiliated Hospital, Zhejiang University School of Medicine, the Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou 310058, Zhejiang, China
| | - Xin Li
- Welch Center for Prevention, Epidemiology, and Clinical Research Department of Epidemiology, Johns Hopkins University, Baltimore, MD 21287, USA
| | - Xueqin Li
- Department of Big Data in Health Science School of Public Health and Center for Clinical Big Data and Analytics of the Second Affiliated Hospital, Zhejiang University School of Medicine, the Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou 310058, Zhejiang, China
| | - Meng Hao
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Shanghai 200433, China
| | - Yang Xia
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang 110004, China
| | - Huiqian Huang
- Clinical Research Center, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang, China
| | - Terese Sara Høj Jørgensen
- Section of Social Medicine, Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Øster Farimagsgade 5, PO Box 2099, Copenhagen DK-1014, Denmark
| | - George O Agogo
- StatsDecide Analytics and Consulting Ltd, P.O.Box 17438-20100, Nakuru, Kenya
| | - Liang Wang
- Department of Public Health, Robbins College of Human Health and Sciences, Baylor University, Waco, TX 76711, USA
| | - Xuehong Zhang
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Xiang Gao
- Department of Nutrition and Food Hygiene, School of Public Health, Fudan University, Shanghai 200032, China
| | - Zuyun Liu
- Department of Big Data in Health Science School of Public Health and Center for Clinical Big Data and Analytics of the Second Affiliated Hospital, Zhejiang University School of Medicine, the Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou 310058, Zhejiang, China.
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7
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Mulyadi AW, Jung W, Oh K, Yoon JS, Lee KH, Suk HI. Estimating explainable Alzheimer's disease likelihood map via clinically-guided prototype learning. Neuroimage 2023; 273:120073. [PMID: 37037063 DOI: 10.1016/j.neuroimage.2023.120073] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Revised: 03/03/2023] [Accepted: 03/30/2023] [Indexed: 04/12/2023] Open
Abstract
Identifying Alzheimer's disease (AD) involves a deliberate diagnostic process owing to its innate traits of irreversibility with subtle and gradual progression. These characteristics make AD biomarker identification from structural brain imaging (e.g., structural MRI) scans quite challenging. Using clinically-guided prototype learning, we propose a novel deep-learning approach through eXplainable AD Likelihood Map Estimation (XADLiME) for AD progression modeling over 3D sMRIs. Specifically, we establish a set of topologically-aware prototypes onto the clusters of latent clinical features, uncovering an AD spectrum manifold. Considering this pseudo map as an enriched reference, we employ an estimating network to approximate the AD likelihood map over a 3D sMRI scan. Additionally, we promote the explainability of such a likelihood map by revealing a comprehensible overview from clinical and morphological perspectives. During the inference, this estimated likelihood map served as a substitute for unseen sMRI scans for effectively conducting the downstream task while providing thorough explainable states.
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Affiliation(s)
- Ahmad Wisnu Mulyadi
- Department of Brain and Cognitive Engineering, Korea University, Seoul 02841, Republic of Korea
| | - Wonsik Jung
- Department of Brain and Cognitive Engineering, Korea University, Seoul 02841, Republic of Korea
| | - Kwanseok Oh
- Department of Artificial Intelligence, Korea University, Seoul 02841, Republic of Korea
| | - Jee Seok Yoon
- Department of Brain and Cognitive Engineering, Korea University, Seoul 02841, Republic of Korea
| | - Kun Ho Lee
- Gwangju Alzheimer's & Related Dementia Cohort Research Center, Chosun University, Gwangju 61452, Republic of Korea; Department of Biomedical Science, Chosun University, Gwangju 61452, Republic of Korea; Korea Brain Research Institute, Daegu 41062, Republic of Korea
| | - Heung-Il Suk
- Department of Artificial Intelligence, Korea University, Seoul 02841, Republic of Korea; Department of Brain and Cognitive Engineering, Korea University, Seoul 02841, Republic of Korea.
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Deoni SCL, Burton P, Beauchemin J, Cano-Lorente R, De Both MD, Johnson M, Ryan L, Huentelman MJ. Neuroimaging and verbal memory assessment in healthy aging adults using a portable low-field MRI scanner and a web-based platform: results from a proof-of-concept population-based cross-section study. Brain Struct Funct 2023; 228:493-509. [PMID: 36352153 PMCID: PMC9646260 DOI: 10.1007/s00429-022-02595-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 11/01/2022] [Indexed: 11/10/2022]
Abstract
Consumer wearables and health monitors, internet-based health and cognitive assessments, and at-home biosample (e.g., saliva and capillary blood) collection kits are increasingly used by public health researchers for large population-based studies without requiring intensive in-person visits. Alongside reduced participant time burden, remote and virtual data collection allows the participation of individuals who live long distances from hospital or university research centers, or who lack access to transportation. Unfortunately, studies that include magnetic resonance neuroimaging are challenging to perform remotely given the infrastructure requirements of MRI scanners, and, as a result, they often omit socially, economically, and educationally disadvantaged individuals. Lower field strength systems (< 100 mT) offer the potential to perform neuroimaging at a participant's home, enabling more accessible and equitable research. Here we report the first use of a low-field MRI "scan van" with an online assessment of paired-associate learning (PAL) to examine associations between brain morphometry and verbal memory performance. In a sample of 67 individuals, 18-93 years of age, imaged at or near their home, we show expected white and gray matter volume trends with age and find significant (p < 0.05 FWE) associations between PAL performance and hippocampus, amygdala, caudate, and thalamic volumes. High-quality data were acquired in 93% of individuals, and at-home scanning was preferred by all individuals with prior MRI at a hospital or research setting. Results demonstrate the feasibility of remote neuroimaging and cognitive data collection, with important implications for engaging traditionally under-represented communities in neuroimaging research.
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Affiliation(s)
- Sean C L Deoni
- Maternal, Newborn, and Child Health Discovery & Tools, Bill & Melinda Gates Foundation, 500 5th Ave, Seattle, WA, 98109, USA.
| | - Phoebe Burton
- Advanced Baby Imaging Lab, Rhode Island Hospital, Providence, RI, USA
- Department of Pediatrics, Warren Alpert Medical School at Brown University, Providence, RI, USA
| | - Jennifer Beauchemin
- Advanced Baby Imaging Lab, Rhode Island Hospital, Providence, RI, USA
- Department of Pediatrics, Warren Alpert Medical School at Brown University, Providence, RI, USA
| | - Rosa Cano-Lorente
- Advanced Baby Imaging Lab, Rhode Island Hospital, Providence, RI, USA
- Department of Pediatrics, Warren Alpert Medical School at Brown University, Providence, RI, USA
| | | | | | - Lee Ryan
- Department of Psychology, University of Arizona, Tucson, AZ, USA
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N-acetyl-aspartate and Myo-inositol as Markers of White Matter Microstructural Organization in Mild Cognitive Impairment: Evidence from a DTI- 1H-MRS Pilot Study. Diagnostics (Basel) 2023; 13:diagnostics13040654. [PMID: 36832141 PMCID: PMC9955118 DOI: 10.3390/diagnostics13040654] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 02/06/2023] [Accepted: 02/07/2023] [Indexed: 02/12/2023] Open
Abstract
We implemented a multimodal approach to examine associations between structural and neurochemical changes that could signify neurodegenerative processes related to mild cognitive impairment (MCI). Fifty-nine older adults (60-85 years; 22 MCI) underwent whole-brain structural 3T MRI (T1W, T2W, DTI) and proton magnetic resonance spectroscopy (1H-MRS). The regions of interest (ROIs) for 1H-MRS measurements were the dorsal posterior cingulate cortex, left hippocampal cortex, left medial temporal cortex, left primary sensorimotor cortex, and right dorsolateral prefrontal cortex. The findings revealed that subjects in the MCI group showed moderate to strong positive associations between the total N-acetylaspartate to total creatine and the total N-acetylaspartate to myo-inositol ratios in the hippocampus and dorsal posterior cingulate cortex and fractional anisotropy (FA) of WM tracts crossing these regions-specifically, the left temporal tapetum, right corona radiata, and right posterior cingulate gyri. In addition, negative associations between the myo-inositol to total creatine ratio and FA of the left temporal tapetum and right posterior cingulate gyri were observed. These observations suggest that the biochemical integrity of the hippocampus and cingulate cortex is associated with a microstructural organization of ipsilateral WM tracts originating in the hippocampus. Specifically, elevated myo-inositol might be an underlying mechanism for decreased connectivity between the hippocampus and the prefrontal/cingulate cortex in MCI.
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10
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Cheong Y, Nishitani S, Yu J, Habata K, Kamiya T, Shiotsu D, Omori IM, Okazawa H, Tomoda A, Kosaka H, Jung M. The effects of epigenetic age and its acceleration on surface area, cortical thickness, and volume in young adults. Cereb Cortex 2022; 32:5654-5663. [PMID: 35196707 DOI: 10.1093/cercor/bhac043] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 01/20/2022] [Accepted: 01/21/2022] [Indexed: 01/25/2023] Open
Abstract
DNA methylation age has been used in recent studies as an epigenetic marker of accelerated cellular aging, whose contribution to the brain structural changes was lately acknowledged. We aimed to characterize the association of epigenetic age (i.e. estimated DNA methylation age) and its acceleration with surface area, cortical thickness, and volume in healthy young adults. Using the multi-tissue method (Horvath S. DNA methylation age of human tissues and cell types. 2013. Genome Biol 14), epigenetic age was computed with saliva sample. Epigenetic age acceleration was derived from residuals after adjusting epigenetic age for chronological age. Multiple regression models were computed for 148 brain regions for surface area, cortical thickness, and volume using epigenetic age or accelerated epigenetic age as a predictor and controlling for sex. Epigenetic age was associated with surface area reduction of the left insula. It was also associated with cortical thinning and volume reduction in multiple regions, with prominent changes of cortical thickness in the left temporal regions and of volume in the bilateral orbital gyri. Finally, accelerated epigenetic age was negatively associated with right cuneus gyrus volume. Our findings suggest that understanding the mechanisms of epigenetic age acceleration in young individuals may yield valuable insights into the relationship between epigenetic aging and the cortical change and on the early development of neurocognitive pathology among young adults.
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Affiliation(s)
- Yongjeon Cheong
- Cognitive Science Research Group, Korea Brain Research Institute, Daegu 41062, South Korea
| | - Shota Nishitani
- Research Center for Child Mental Development, University of Fukui, Eiheiji, Fukui 910-1193, Japan.,Division of Developmental Higher Brain Functions, United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University, and University of Fukui, Osaka 565-0871, Japan
| | - Jinyoung Yu
- Cognitive Science Research Group, Korea Brain Research Institute, Daegu 41062, South Korea
| | - Kaie Habata
- Department of Neuropsychiatry, University of Fukui, 23-3 Matsuokashimoaizuki, Eiheiji, Fukui 910-1193, Japan
| | - Taku Kamiya
- Department of Neuropsychiatry, University of Fukui, 23-3 Matsuokashimoaizuki, Eiheiji, Fukui 910-1193, Japan
| | - Daichi Shiotsu
- Department of Neuropsychiatry, University of Fukui, 23-3 Matsuokashimoaizuki, Eiheiji, Fukui 910-1193, Japan
| | - Ichiro M Omori
- Department of Neuropsychiatry, University of Fukui, 23-3 Matsuokashimoaizuki, Eiheiji, Fukui 910-1193, Japan
| | - Hidehiko Okazawa
- Department of Neuropsychiatry, University of Fukui, 23-3 Matsuokashimoaizuki, Eiheiji, Fukui 910-1193, Japan.,Biomedical Imaging Research Center, University of Fukui, Eiheiji, Fukui 910-1193, Japan
| | - Akemi Tomoda
- Research Center for Child Mental Development, University of Fukui, Eiheiji, Fukui 910-1193, Japan.,Division of Developmental Higher Brain Functions, United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University, and University of Fukui, Osaka 565-0871, Japan
| | - Hirotaka Kosaka
- Research Center for Child Mental Development, University of Fukui, Eiheiji, Fukui 910-1193, Japan.,Division of Developmental Higher Brain Functions, United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University, and University of Fukui, Osaka 565-0871, Japan.,Department of Neuropsychiatry, University of Fukui, 23-3 Matsuokashimoaizuki, Eiheiji, Fukui 910-1193, Japan
| | - Minyoung Jung
- Cognitive Science Research Group, Korea Brain Research Institute, Daegu 41062, South Korea
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11
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Tomassini S, Sbrollini A, Covella G, Sernani P, Falcionelli N, Müller H, Morettini M, Burattini L, Dragoni AF. Brain-on-Cloud for automatic diagnosis of Alzheimer's disease from 3D structural magnetic resonance whole-brain scans. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2022; 227:107191. [PMID: 36335750 DOI: 10.1016/j.cmpb.2022.107191] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 10/13/2022] [Accepted: 10/17/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND AND OBJECTIVE Alzheimer's disease accounts for approximately 70% of all dementia cases. Cortical and hippocampal atrophy caused by Alzheimer's disease can be appreciated easily from a T1-weighted structural magnetic resonance scan. Since a timely therapeutic intervention during the initial stages of the syndrome has a positive impact on both disease progression and quality of life of affected subjects, Alzheimer's disease diagnosis is crucial. Thus, this study relies on the development of a robust yet lightweight 3D framework, Brain-on-Cloud, dedicated to efficient learning of Alzheimer's disease-related features from 3D structural magnetic resonance whole-brain scans by improving our recent convolutional long short-term memory-based framework with the integration of a set of data handling techniques in addition to the tuning of the model hyper-parameters and the evaluation of its diagnostic performance on independent test data. METHODS For this objective, four serial experiments were conducted on a scalable GPU cloud service. They were compared and the hyper-parameters of the best experiment were tuned until reaching the best-performing configuration. In parallel, two branches were designed. In the first branch of Brain-on-Cloud, training, validation and testing were performed on OASIS-3. In the second branch, unenhanced data from ADNI-2 were employed as independent test set, and the diagnostic performance of Brain-on-Cloud was evaluated to prove its robustness and generalization capability. The prediction scores were computed for each subject and stratified according to age, sex and mini mental state examination. RESULTS In its best guise, Brain-on-Cloud is able to discriminate Alzheimer's disease with an accuracy of 92% and 76%, sensitivity of 94% and 82%, and area under the curve of 96% and 92% on OASIS-3 and independent ADNI-2 test data, respectively. CONCLUSIONS Brain-on-Cloud shows to be a reliable, lightweight and easily-reproducible framework for automatic diagnosis of Alzheimer's disease from 3D structural magnetic resonance whole-brain scans, performing well without segmenting the brain into its portions. Preserving the brain anatomy, its application and diagnostic ability can be extended to other cognitive disorders. Due to its cloud nature, computational lightness and fast execution, it can also be applied in real-time diagnostic scenarios providing prompt clinical decision support.
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Affiliation(s)
- Selene Tomassini
- Department of Information Engineering, Engineering Faculty, Università Politecnica delle Marche (UnivPM), Ancona, Italy.
| | - Agnese Sbrollini
- Department of Information Engineering, Engineering Faculty, Università Politecnica delle Marche (UnivPM), Ancona, Italy.
| | - Giacomo Covella
- Department of Information Engineering, Engineering Faculty, Università Politecnica delle Marche (UnivPM), Ancona, Italy.
| | - Paolo Sernani
- Department of Information Engineering, Engineering Faculty, Università Politecnica delle Marche (UnivPM), Ancona, Italy.
| | - Nicola Falcionelli
- Department of Information Engineering, Engineering Faculty, Università Politecnica delle Marche (UnivPM), Ancona, Italy.
| | - Henning Müller
- Information Systems Institute, University of Applied Sciences Western Switzerland (HES-SO), Sierre, Switzerland.
| | - Micaela Morettini
- Department of Information Engineering, Engineering Faculty, Università Politecnica delle Marche (UnivPM), Ancona, Italy.
| | - Laura Burattini
- Department of Information Engineering, Engineering Faculty, Università Politecnica delle Marche (UnivPM), Ancona, Italy.
| | - Aldo Franco Dragoni
- Department of Information Engineering, Engineering Faculty, Università Politecnica delle Marche (UnivPM), Ancona, Italy.
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12
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Wu-Chung EL, Leal SL, Denny BT, Cheng SL, Fagundes CP. Spousal caregiving, widowhood, and cognition: A systematic review and a biopsychosocial framework for understanding the relationship between interpersonal losses and dementia risk in older adulthood. Neurosci Biobehav Rev 2022; 134:104487. [PMID: 34971701 PMCID: PMC8925984 DOI: 10.1016/j.neubiorev.2021.12.010] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Revised: 11/23/2021] [Accepted: 12/06/2021] [Indexed: 01/18/2023]
Abstract
Accumulating research suggests that stressful life events, especially those that threaten close intimate bonds, are associated with an increased risk of dementia. Grieving the loss of a spouse, whether in the form of caregiving or after the death, ranks among 'life's most significant stressors', evoking intense psychological and physiological distress. Despite numerous studies reporting elevated dementia risk or poorer cognition among spousal caregivers and widow(er)s compared to controls, no review has summarized findings across cognitive outcomes (i.e., dementia incidence, cognitive impairment rates, cognitive performance) or proposed a theoretical model for understanding the links between partner loss and abnormal cognitive decline. The current systematic review summarizes findings across 64 empirical studies. Overall, both cross-sectional and longitudinal studies revealed an adverse association between partner loss and cognitive outcomes. In turn, we propose a biopsychosocial model of cognitive decline that explains how caregiving and bereavement may position some to develop cognitive impairment or Alzheimer's disease and related dementias. More longitudinal studies that focus on the biopsychosocial context of caregivers and widow(er)s are needed.
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Affiliation(s)
- E Lydia Wu-Chung
- Department of Psychological Sciences, Rice University, Houston, TX, United States.
| | - Stephanie L Leal
- Department of Psychological Sciences, Rice University, Houston, TX, United States
| | - Bryan T Denny
- Department of Psychological Sciences, Rice University, Houston, TX, United States
| | - Samantha L Cheng
- Department of Psychological Sciences, Rice University, Houston, TX, United States
| | - Christopher P Fagundes
- Department of Psychological Sciences, Rice University, Houston, TX, United States; Department of Behavioral Science, The University of Texas MD Anderson Cancer Center, Houston, TX, United States; Department of Psychiatry & Behavioral Sciences, Baylor College of Medicine, Houston, TX, United States
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13
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Li W, Yang D, Yan C, Chen M, Li Q, Zhu W, Wu G. Characterizing Network Selectiveness to the Dynamic Spreading of Neuropathological Events in Alzheimer's Disease. J Alzheimers Dis 2022; 86:1805-1816. [PMID: 35253761 PMCID: PMC9482760 DOI: 10.3233/jad-215596] [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: 11/15/2022]
Abstract
BACKGROUND Mounting evidence shows that the neuropathological burdens manifest preference in affecting brain regions during the dynamic progression of Alzheimer's disease (AD). Since the distinct brain regions are physically wired by white matter fibers, it is reasonable to hypothesize the differential spreading pattern of neuropathological burdens may underlie the wiring topology, which can be characterized using neuroimaging and network science technologies. OBJECTIVE To study the dynamic spreading patterns of neuropathological events in AD. METHODS We first examine whether hub nodes with high connectivity in the brain network (assemble of white matter wirings) are susceptible to a higher level of pathological burdens than other regions that are less involved in the process of information exchange in the network. Moreover, we propose a novel linear mixed-effect model to characterize the multi-factorial spreading process of neuropathological burdens from hub nodes to non-hub nodes, where age, sex, and APOE4 indicators are considered as confounders. We apply our statistical model to the longitudinal neuroimaging data of amyloid-PET and tau-PET, respectively. RESULTS Our meta-data analysis results show that 1) AD differentially affects hub nodes with a significantly higher level of pathology, and 2) the longitudinal increase of neuropathological burdens on non-hub nodes is strongly correlated with the connectome distance to hub nodes rather than the spatial proximity. CONCLUSION The spreading pathway of AD neuropathological burdens might start from hub regions and propagate through the white matter fibers in a prion-like manner.
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Affiliation(s)
- Wenchao Li
- Intelligent Information Processing Laboratory, Hangzhou Dianzi University, Hangzhou, China
| | - Defu Yang
- Intelligent Information Processing Laboratory, Hangzhou Dianzi University, Hangzhou, China
- Research Center for Healthcare Data Science, Zhejiang Lab, Hangzhou, Zhejiang, China
| | - Chenggang Yan
- Intelligent Information Processing Laboratory, Hangzhou Dianzi University, Hangzhou, China
| | - Minghan Chen
- Department of Computer Science, Wake Forest University, Winston-Salem, NC, USA
| | - Quefeng Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Wentao Zhu
- Research Center for Healthcare Data Science, Zhejiang Lab, Hangzhou, Zhejiang, China
| | - Guorong Wu
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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14
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Amyloid Burden in Alzheimer's Disease Patients Is Associated with Alterations in Circadian Rhythm. Dement Neurocogn Disord 2021; 20:99-107. [PMID: 34795773 PMCID: PMC8585536 DOI: 10.12779/dnd.2021.20.4.99] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Revised: 10/23/2021] [Accepted: 10/24/2021] [Indexed: 11/27/2022] Open
Abstract
Background and Purpose In this study we evaluated the relationship between amyloid-beta (Aβ) deposition and 3 aspects of sleep quality in a group of clinically diagnosed Alzheimer's disease (AD) patients. Methods We used self-report questionnaires to assess the quality of sleep using 3 previously established surveys: the Glasgow Sleep Effort Scale (GSES), the Pittsburgh Sleep Quality Index (PSQI), and the Morningness-Eveningness Questionnaire (MEQ). These questionnaires focused on the sleep effort, sleep efficiency, and circadian rhythm patterns of each participant. Also, we evaluated the regional distribution of Aβ in the brain by amyloid positron emission tomography-computed tomography (PET-CT) standardized uptake value ratios (SUVRs) in healthy normal (HN), mild cognitive impairment (MCI), and AD dementia groups. The MCI and AD dementia groups were combined to form the group with cognitive impairment due to AD (CIAD). Results GSES and MEQ scores differed significantly between the HN, MCI, and AD dementia groups (p<0.037), whereas PSQI scores were similar across the groups (p=0.129). GSES and MEQ scores also differed between the HN and CIAD groups (p<0.018). Circadian rhythm scores positively correlated with amyloid PET-CT SUVR in posterior cingulate cortices (p<0.049). Conclusions Sleep effort and abnormal shifts in circadian rhythm were more significant in the CIAD group than in the HN group. At the same time, HN subjects had minimal sleep disturbance, irrespective of clinical status. Thus, alterations in circadian rhythm may be indicative of neurodegeneration due to Aβ deposition.
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15
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Zhao H, Cheng J, Liu T, Jiang J, Koch F, Sachdev PS, Basser PJ, Wen W. Orientational changes of white matter fibers in Alzheimer's disease and amnestic mild cognitive impairment. Hum Brain Mapp 2021; 42:5397-5408. [PMID: 34412149 PMCID: PMC8519856 DOI: 10.1002/hbm.25628] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Accepted: 08/07/2021] [Indexed: 12/13/2022] Open
Abstract
White matter abnormalities represent early neuropathological events in neurodegenerative diseases such as Alzheimer's disease (AD), investigating these white matter alterations would likely provide valuable insights into pathological changes over the course of AD. Using a novel mathematical framework called "Director Field Analysis" (DFA), we investigated the geometric microstructural properties (i.e., splay, bend, twist, and total distortion) in the orientation of white matter fibers in AD, amnestic mild cognitive impairment (aMCI), and cognitively normal (CN) individuals from the Alzheimer's Disease Neuroimaging Initiative 2 database. Results revealed that AD patients had extensive orientational changes in the bilateral anterior thalamic radiation, corticospinal tract, inferior and superior longitudinal fasciculus, inferior fronto-occipital fasciculus, and uncinate fasciculus in comparison with CN. We postulate that these orientational changes of white matter fibers may be partially caused by the expansion of lateral ventricle, white matter atrophy, and gray matter atrophy in AD. In contrast, aMCI individuals showed subtle orientational changes in the left inferior longitudinal fasciculus and right uncinate fasciculus, which showed a significant association with the cognitive performance, suggesting that these regions may be preferential vulnerable to breakdown by neurodegenerative brain disorders, thereby resulting in the patients' cognitive impairment. To our knowledge, this article is the first to examine geometric microstructural changes in the orientation of white matter fibers in AD and aMCI. Our findings demonstrate that the orientational information of white matter fibers could provide novel insight into the underlying biological and pathological changes in AD and aMCI.
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Affiliation(s)
- Haichao Zhao
- Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical EngineeringBeihang UniversityBeijingChina
| | - Jian Cheng
- Beijing Advanced Innovation Center for Big Data‐Based Precision MedicineBeihang UniversityBeijingChina
| | - Tao Liu
- Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical EngineeringBeihang UniversityBeijingChina
- Beijing Advanced Innovation Center for Big Data‐Based Precision MedicineBeihang UniversityBeijingChina
| | - Jiyang Jiang
- Centre for Healthy Brain Ageing, School of Psychiatry (CHeBA)University of New South WalesSydneyNew South WalesAustralia
| | - Forrest Koch
- Centre for Healthy Brain Ageing, School of Psychiatry (CHeBA)University of New South WalesSydneyNew South WalesAustralia
| | - Perminder S. Sachdev
- Centre for Healthy Brain Ageing, School of Psychiatry (CHeBA)University of New South WalesSydneyNew South WalesAustralia
| | - Peter J. Basser
- Section on Quantitative Imaging and Tissue SciencesNIBIB, NICHD, National Institutes of HealthBethesdaMaryland
| | - Wei Wen
- Centre for Healthy Brain Ageing, School of Psychiatry (CHeBA)University of New South WalesSydneyNew South WalesAustralia
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16
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Nezhadmoghadam F, Martinez-Torteya A, Treviño V, Martínez E, Santos A, Tamez-Peña J, Alzheimer's Disease Neuroimaging Initiative. Robust Discovery of Mild Cognitive Impairment Subtypes and Their Risk of Alzheimer's Disease Conversion Using Unsupervised Machine Learning and Gaussian Mixture Modeling. Curr Alzheimer Res 2021; 18:595-606. [PMID: 34488612 DOI: 10.2174/1567205018666210831145825] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Revised: 05/30/2021] [Accepted: 06/30/2021] [Indexed: 11/22/2022]
Abstract
BACKGROUND Alzheimer's Disease (AD) is an irreversible, progressive brain disorder that slowly destroys memory and thinking skills. The ability to correctly predict the diagnosis of Alzheimer's disease in its earliest stages can help physicians make more informed clinical decisions on therapy plans. OBJECTIVE This study aimed to determine whether the unsupervised discovering of latent classes of subjects with Mild Cognitive Impairment (MCI) may be useful in finding different prodromal AD stages and/or subjects with a low MCI to AD conversion risk. METHODS Total 18 features relevant to the MCI to AD conversion process led to the identification of 681 subjects with early MCI. Subjects were divided into training (70%) and validation (30%) sets. Subjects from the training set were analyzed using consensus clustering, and Gaussian Mixture Models (GMM) were used to describe the latent classes. The discovered GMM predicted the latent class of the validation set. Finally, descriptive statistics, rates of conversion, and Odds Ratios (OR) were computed for each discovered class. RESULTS Through consensus clustering, we discovered three different clusters among MCI subjects. The three clusters were associated with low-risk (OR = 0.12, 95%CI = 0.04 to 0.3|), medium-risk (OR = 1.33, 95%CI = 0.75 to 2.37), and high-risk (OR = 3.02, 95%CI = 1.64 to 5.57) of converting from MCI to AD, with the high-risk and low-risk groups highly contrasting. Hence, prodromal AD subjects were present in only two clusters. CONCLUSION We successfully discovered three different latent classes among MCI subjects with varied risks of MCI-to-AD conversion through consensus clustering. Two of the discovered classes may represent two different prodromal presentations of Alzheimer´s disease.
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Affiliation(s)
- Fahimeh Nezhadmoghadam
- Tecnologico de Monterrey, School of Engineering and Sciences, Ave. Eugenio Garza Sada 2501, Monterrey, N.L., 64849, Mexico
| | - Antonio Martinez-Torteya
- Universidad de Monterrey, School of Engineering and Technologies, Av. Ignacio Morones Prieto 4500, San Pedro Garza García 66238, Mexico
| | - Victor Treviño
- Tecnologico de Monterrey, School of Medicine and Health Sciences, Ave. Ignacio Morones Prieto 3000, Sertoma, Monterrey, N.L, 64710, Mexico
| | - Emmanuel Martínez
- Tecnologico de Monterrey, School of Medicine and Health Sciences, Ave. Ignacio Morones Prieto 3000, Sertoma, Monterrey, N.L, 64710, Mexico
| | - Alejandro Santos
- Tecnologico de Monterrey, School of Medicine and Health Sciences, Ave. Ignacio Morones Prieto 3000, Sertoma, Monterrey, N.L, 64710, Mexico
| | - Jose Tamez-Peña
- Tecnologico de Monterrey, School of Medicine and Health Sciences, Ave. Ignacio Morones Prieto 3000, Sertoma, Monterrey, N.L, 64710, Mexico
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17
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El-Gamal FEZA, Elmogy M, Mahmoud A, Shalaby A, Switala AE, Ghazal M, Soliman H, Atwan A, Alghamdi NS, Barnes GN, El-Baz A. A Personalized Computer-Aided Diagnosis System for Mild Cognitive Impairment (MCI) Using Structural MRI (sMRI). SENSORS (BASEL, SWITZERLAND) 2021; 21:5416. [PMID: 34450858 PMCID: PMC8400990 DOI: 10.3390/s21165416] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 07/28/2021] [Accepted: 08/03/2021] [Indexed: 12/31/2022]
Abstract
Alzheimer's disease (AD) is a neurodegenerative disorder that targets the central nervous system (CNS). Statistics show that more than five million people in America face this disease. Several factors hinder diagnosis at an early stage, in particular, the divergence of 10-15 years between the onset of the underlying neuropathological changes and patients becoming symptomatic. This study surveyed patients with mild cognitive impairment (MCI), who were at risk of conversion to AD, with a local/regional-based computer-aided diagnosis system. The described system allowed for visualization of the disorder's effect on cerebral cortical regions individually. The CAD system consists of four steps: (1) preprocess the scans and extract the cortex, (2) reconstruct the cortex and extract shape-based features, (3) fuse the extracted features, and (4) perform two levels of diagnosis: cortical region-based followed by global. The experimental results showed an encouraging performance of the proposed system when compared with related work, with a maximum accuracy of 86.30%, specificity 88.33%, and sensitivity 84.88%. Behavioral and cognitive correlations identified brain regions involved in language, executive function/cognition, and memory in MCI subjects, which regions are also involved in the neuropathology of AD.
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Affiliation(s)
- Fatma El-Zahraa A. El-Gamal
- Bioengineering Department, University of Louisville, Louisville, KY 40292, USA; (F.E.-Z.A.E.-G.); (A.M.); (A.S.); (A.E.S.); (A.E.-B.)
- Information Technology Department, Faculty of Computers and Information, Mansoura University, Mansoura 35516, Egypt; (M.E.); (H.S.); (A.A.)
| | - Mohammed Elmogy
- Information Technology Department, Faculty of Computers and Information, Mansoura University, Mansoura 35516, Egypt; (M.E.); (H.S.); (A.A.)
| | - Ali Mahmoud
- Bioengineering Department, University of Louisville, Louisville, KY 40292, USA; (F.E.-Z.A.E.-G.); (A.M.); (A.S.); (A.E.S.); (A.E.-B.)
| | - Ahmed Shalaby
- Bioengineering Department, University of Louisville, Louisville, KY 40292, USA; (F.E.-Z.A.E.-G.); (A.M.); (A.S.); (A.E.S.); (A.E.-B.)
| | - Andrew E. Switala
- Bioengineering Department, University of Louisville, Louisville, KY 40292, USA; (F.E.-Z.A.E.-G.); (A.M.); (A.S.); (A.E.S.); (A.E.-B.)
| | - Mohammed Ghazal
- Department of Electrical and Computer Engineering, Abu Dhabi University, Abu Dhabi 59911, United Arab Emirates;
| | - Hassan Soliman
- Information Technology Department, Faculty of Computers and Information, Mansoura University, Mansoura 35516, Egypt; (M.E.); (H.S.); (A.A.)
| | - Ahmed Atwan
- Information Technology Department, Faculty of Computers and Information, Mansoura University, Mansoura 35516, Egypt; (M.E.); (H.S.); (A.A.)
| | - Norah Saleh Alghamdi
- College of Computer and Information Science, Princess Nourah Bint Abdulrahman University, Riyadh 11564, Saudi Arabia
| | - Gregory Neal Barnes
- Department of Neurology, University of Louisville, Louisville, KY 40292, USA;
| | - Ayman El-Baz
- Bioengineering Department, University of Louisville, Louisville, KY 40292, USA; (F.E.-Z.A.E.-G.); (A.M.); (A.S.); (A.E.S.); (A.E.-B.)
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18
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Porto MF, Benitez-Agudelo JC, Aguirre-Acevedo DC, Barceló-Martinez E, Allegri RF. Diagnostic accuracy of the UDS 3.0 neuropsychological battery in a cohort with Alzheimer's disease in Colombia. APPLIED NEUROPSYCHOLOGY-ADULT 2021; 29:1543-1551. [PMID: 33761292 DOI: 10.1080/23279095.2021.1897007] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
BACKGROUND Alzheimer's disease (AD) is a neurodegenerative disease that causes a gradual loss of cognitive functions and limits daily activities performance. Early diagnosis of AD is essential to start timely treatment. This study aimed to validate the Uniform Data Set neuropsychological battery version 3.0 (UDS 3.0) in a Colombian cohort. METHODS This study is a cross-sectional type, consecutive, incidental, with 143 persons, divided into two groups: 48 diagnosed AD cases and 95 healthy controls, between the ages of 50 and 80+, and between 1 and 19+ years of education. RESULTS The results indicate differences between the control group and the AD group in most battery tests. A significant correlation was found between the Montreal Cognitive Assessment (MoCA), Multilingual Naming Test (MINT), Craft Story, Benson Figure Test, P-word and F-word Phonemic Fluency Test, and their respective reference tests. Cutoff points were found based on the Youden index for each sub-test. The results indicate that all sub-tests are above the reference line of the ROC curve. CONCLUSION The use of the UDS 3.0 in Colombia would help improving clinical diagnostic routes because of its high accuracy and high correlation with tests that measure general impairment; it has good sensitivity and specificity, and it can be a useful tool for AD.
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Affiliation(s)
- Maria F Porto
- Department of Psychology, Universidad de la Costa, Barranquilla, Colombia
| | - Juan Camilo Benitez-Agudelo
- Department of Psychology, Universidad de la Costa, Barranquilla, Colombia.,Research and Development Department, Instituto Colombiano de Neuropedagogía, ICN, Barranquilla, Colombia
| | | | - Ernesto Barceló-Martinez
- Department of Psychology, Universidad de la Costa, Barranquilla, Colombia.,Research and Development Department, Instituto Colombiano de Neuropedagogía, ICN, Barranquilla, Colombia
| | - Ricardo F Allegri
- Department of Psychology, Universidad de la Costa, Barranquilla, Colombia.,Department of Cognitive Neurology, Instituto de Investigaciones Neurológicas FLENI, Buenos Aires, Argentina
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19
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Mladenovic Djordjevic AN, Kapetanou M, Loncarevic-Vasiljkovic N, Todorovic S, Athanasopoulou S, Jovic M, Prvulovic M, Taoufik E, Matsas R, Kanazir S, Gonos ES. Pharmacological intervention in a transgenic mouse model improves Alzheimer's-associated pathological phenotype: Involvement of proteasome activation. Free Radic Biol Med 2021; 162:88-103. [PMID: 33279620 PMCID: PMC7889698 DOI: 10.1016/j.freeradbiomed.2020.11.038] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Revised: 11/23/2020] [Accepted: 11/28/2020] [Indexed: 12/16/2022]
Abstract
Alzheimer's disease (AD) is the most common form of dementia worldwide, characterized by a progressive decline in a variety of cognitive and non-cognitive functions. The amyloid beta protein cascade hypothesis places the formation of amyloid beta protein aggregates on the first position in the complex pathological cascade leading to neurodegeneration, and therefore AD might be considered to be a protein-misfolding disease. The Ubiquitin Proteasome System (UPS), being the primary protein degradation mechanism with a fundamental role in the maintenance of proteostasis, has been identified as a putative therapeutic target to delay and/or to decelerate the progression of neurodegenerative disorders that are characterized by accumulated/aggregated proteins. The purpose of this study was to test if the activation of proteasome in vivo can alleviate AD pathology. Specifically by using two compounds with complementary modes of proteasome activation and documented antioxidant and redox regulating properties in the 5xFAD transgenic mice model of AD, we ameliorated a number of AD related deficits. Shortly after proteasome activation we detected significantly reduced amyloid-beta load correlated with improved motor functions, reduced anxiety and frailty level. Essentially, to our knowledge this is the first report to demonstrate a dual activation of the proteasome and its downstream effects. In conclusion, these findings open up new directions for future therapeutic potential of proteasome-mediated proteolysis enhancement.
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Affiliation(s)
- Aleksandra N Mladenovic Djordjevic
- Department for Neurobiology, Institute for Biological Research "Sinisa Stankovic", National Institute of Republic of Serbia, University of Belgrade, Boulevard Despota Stefana, 142, 11000, Belgrade, Serbia.
| | - Marianna Kapetanou
- Institute of Chemical Biology, National Hellenic Research Foundation, 48 Vassileos Constantinou Ave., 11635, Athens, Greece
| | - Natasa Loncarevic-Vasiljkovic
- Department for Neurobiology, Institute for Biological Research "Sinisa Stankovic", National Institute of Republic of Serbia, University of Belgrade, Boulevard Despota Stefana, 142, 11000, Belgrade, Serbia; Molecular Nutrition and Health Lab, CEDOC - Centro de Estudos de Doenças Crónicas, NOVA Medical School / Faculdade de Ciências Médicas, Universidade Nova de Lisboa, Edifício CEDOC II, Rua Câmara Pestana 6, 1150-082, Lisboa, Portugal
| | - Smilja Todorovic
- Department for Neurobiology, Institute for Biological Research "Sinisa Stankovic", National Institute of Republic of Serbia, University of Belgrade, Boulevard Despota Stefana, 142, 11000, Belgrade, Serbia
| | - Sofia Athanasopoulou
- Institute of Chemical Biology, National Hellenic Research Foundation, 48 Vassileos Constantinou Ave., 11635, Athens, Greece; Department of Biology, Faculty of Medicine, University of Thessaly, Biopolis, 41500, Larissa, Greece
| | - Milena Jovic
- Department for Neurobiology, Institute for Biological Research "Sinisa Stankovic", National Institute of Republic of Serbia, University of Belgrade, Boulevard Despota Stefana, 142, 11000, Belgrade, Serbia
| | - Milica Prvulovic
- Department for Neurobiology, Institute for Biological Research "Sinisa Stankovic", National Institute of Republic of Serbia, University of Belgrade, Boulevard Despota Stefana, 142, 11000, Belgrade, Serbia
| | - Era Taoufik
- Laboratory of Cellular and Molecular Neurobiology-Stem Cells, Department of Neurobiology, Hellenic Pasteur Institute, 127 Vasilissis Sofias Avenue, 11521, Athens, Greece
| | - Rebecca Matsas
- Laboratory of Cellular and Molecular Neurobiology-Stem Cells, Department of Neurobiology, Hellenic Pasteur Institute, 127 Vasilissis Sofias Avenue, 11521, Athens, Greece
| | - Selma Kanazir
- Department for Neurobiology, Institute for Biological Research "Sinisa Stankovic", National Institute of Republic of Serbia, University of Belgrade, Boulevard Despota Stefana, 142, 11000, Belgrade, Serbia
| | - Efstathios S Gonos
- Institute of Chemical Biology, National Hellenic Research Foundation, 48 Vassileos Constantinou Ave., 11635, Athens, Greece.
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20
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Holton CM, Hanley N, Shanks E, Oxley P, McCarthy A, Eastwood BJ, Murray TK, Nickerson A, Wafford KA. Longitudinal changes in EEG power, sleep cycles and behaviour in a tau model of neurodegeneration. ALZHEIMERS RESEARCH & THERAPY 2020; 12:84. [PMID: 32669112 PMCID: PMC7364634 DOI: 10.1186/s13195-020-00651-0] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Accepted: 07/03/2020] [Indexed: 01/13/2023]
Abstract
Background Disturbed sleep is associated with cognitive decline in neurodegenerative diseases such as Alzheimer’s disease (AD) and frontotemporal dementia (FTD). The progressive sequence of how neurodegeneration affects aspects of sleep architecture in conjunction with behavioural changes is not well understood. Methods We investigated changes in sleep architecture, spectral power and circadian rhythmicity in the tet-off rTg4510 mouse overexpressing human P301L tau within the same subjects over time. Doxycycline-induced transgene-suppressed rTg4510 mice, tTa carriers and wild-type mice were used as comparators. Spectral power and sleep stages were measured from within the home cage environment using EEG electrodes. In addition, locomotor activity and performance during a T-maze task were measured. Results Spectral power in the delta and theta bands showed a time-dependent decrease in rTg4510 mice compared to all other groups. After the initial changes in spectral power, wake during the dark period increased whereas NREM and number of REM sleep bouts decreased in rTg4510 compared to wild-type mice. Home cage locomotor activity in the dark phase significantly increased in rTg4510 compared to wild-type mice by 40 weeks of age. Peak-to-peak circadian rhythm amplitude and performance in the T-maze was impaired throughout the experiment independent of time. At 46 weeks, rTG4510 mice had significant degeneration in the hippocampus and cortex whereas doxycycline-treated rTG4510 mice were protected. Pathology significantly correlated with sleep and EEG outcomes, in addition to locomotor and cognitive measures. Conclusions We show that reduced EEG spectral power precedes reductions in sleep and home cage locomotor activity in a mouse model of tauopathy. The data shows increasing mutant tau changes sleep architecture, EEG properties, behaviour and cognition, which suggest tau-related effects on sleep architecture in patients with neurodegenerative diseases.
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Affiliation(s)
- C M Holton
- Eli Lilly and Company, Erl Wood Manor, Windlesham, Surrey, GU20 6PH, UK
| | - N Hanley
- Eli Lilly and Company, Erl Wood Manor, Windlesham, Surrey, GU20 6PH, UK
| | - E Shanks
- Eli Lilly and Company, Erl Wood Manor, Windlesham, Surrey, GU20 6PH, UK
| | - P Oxley
- Eli Lilly and Company, Erl Wood Manor, Windlesham, Surrey, GU20 6PH, UK
| | - A McCarthy
- Eli Lilly and Company, Erl Wood Manor, Windlesham, Surrey, GU20 6PH, UK
| | - B J Eastwood
- Eli Lilly and Company, Erl Wood Manor, Windlesham, Surrey, GU20 6PH, UK
| | - T K Murray
- Eli Lilly and Company, Erl Wood Manor, Windlesham, Surrey, GU20 6PH, UK
| | - A Nickerson
- Eli Lilly and Company, Erl Wood Manor, Windlesham, Surrey, GU20 6PH, UK
| | - K A Wafford
- Eli Lilly and Company, Erl Wood Manor, Windlesham, Surrey, GU20 6PH, UK.
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21
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Abrol A, Bhattarai M, Fedorov A, Du Y, Plis S, Calhoun V. Deep residual learning for neuroimaging: An application to predict progression to Alzheimer's disease. J Neurosci Methods 2020; 339:108701. [PMID: 32275915 PMCID: PMC7297044 DOI: 10.1016/j.jneumeth.2020.108701] [Citation(s) in RCA: 52] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2019] [Revised: 01/03/2020] [Accepted: 03/25/2020] [Indexed: 01/22/2023]
Abstract
BACKGROUND The unparalleled performance of deep learning approaches in generic image processing has motivated its extension to neuroimaging data. These approaches learn abstract neuroanatomical and functional brain alterations that could enable exceptional performance in classification of brain disorders, predicting disease progression, and localizing brain abnormalities. NEW METHOD This work investigates the suitability of a modified form of deep residual neural networks (ResNet) for studying neuroimaging data in the specific application of predicting progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD). Prediction was conducted first by training the deep models using MCI individuals only, followed by a domain transfer learning version that additionally trained on AD and controls. We also demonstrate a network occlusion based method to localize abnormalities. RESULTS The implemented framework captured non-linear features that successfully predicted AD progression and also conformed to the spectrum of various clinical scores. In a repeated cross-validated setup, the learnt predictive models showed highly similar peak activations that corresponded to previous AD reports. COMPARISON WITH EXISTING METHODS The implemented architecture achieved a significant performance improvement over the classical support vector machine and the stacked autoencoder frameworks (p < 0.005), numerically better than state-of-the-art performance using sMRI data alone (> 7% than the second-best performing method) and within 1% of the state-of-the-art performance considering learning using multiple neuroimaging modalities as well. CONCLUSIONS The explored frameworks reflected the high potential of deep learning architectures in learning subtle predictive features and utility in critical applications such as predicting and understanding disease progression.
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Affiliation(s)
- Anees Abrol
- Joint (GSU/GaTech/Emory) Center for Transational Research in Neuroimaging and Data Science, Atlanta, GA, 30303, USA; The Mind Research Network, 1101 Yale Blvd NE, Albuquerque, NM, 87106, USA; Department of Electrical and Computer Engineering, The University of New Mexico, Albuquerque, NM, 87131, USA.
| | - Manish Bhattarai
- Department of Electrical and Computer Engineering, The University of New Mexico, Albuquerque, NM, 87131, USA; Los Alamos National Laboratory, Los Alamos, NM, 87545, USA
| | - Alex Fedorov
- Joint (GSU/GaTech/Emory) Center for Transational Research in Neuroimaging and Data Science, Atlanta, GA, 30303, USA; The Mind Research Network, 1101 Yale Blvd NE, Albuquerque, NM, 87106, USA; Department of Electrical and Computer Engineering, The University of New Mexico, Albuquerque, NM, 87131, USA
| | - Yuhui Du
- Joint (GSU/GaTech/Emory) Center for Transational Research in Neuroimaging and Data Science, Atlanta, GA, 30303, USA; The Mind Research Network, 1101 Yale Blvd NE, Albuquerque, NM, 87106, USA; School of Computer and Information Technology, Shanxi University, Taiyuan, China
| | - Sergey Plis
- Joint (GSU/GaTech/Emory) Center for Transational Research in Neuroimaging and Data Science, Atlanta, GA, 30303, USA; The Mind Research Network, 1101 Yale Blvd NE, Albuquerque, NM, 87106, USA
| | - Vince Calhoun
- Joint (GSU/GaTech/Emory) Center for Transational Research in Neuroimaging and Data Science, Atlanta, GA, 30303, USA; The Mind Research Network, 1101 Yale Blvd NE, Albuquerque, NM, 87106, USA; Department of Electrical and Computer Engineering, The University of New Mexico, Albuquerque, NM, 87131, USA
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22
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Smith CD, Van Eldik LJ, Jicha GA, Schmitt FA, Nelson PT, Abner EL, Kryscio RJ, Murphy RR, Andersen AH. Brain structure changes over time in normal and mildly impaired aged persons. AIMS Neurosci 2020; 7:120-135. [PMID: 32607416 PMCID: PMC7321765 DOI: 10.3934/neuroscience.2020009] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Accepted: 05/08/2020] [Indexed: 01/25/2023] Open
Abstract
Structural brain changes in aging are known to occur even in the absence of dementia, but the magnitudes and regions involved vary between studies. To further characterize these changes, we analyzed paired MRI images acquired with identical protocols and scanner over a median 5.8-year interval. The normal study group comprised 78 elders (25M 53F, baseline age range 70–78 years) who underwent an annual standardized expert assessment of cognition and health and who maintained normal cognition for the duration of the study. We found a longitudinal grey matter (GM) loss rate of 2.56 ± 0.07 ml/year (0.20 ± 0.04%/year) and a cerebrospinal fluid (CSF) expansion rate of 2.97 ± 0.07 ml/year (0.22 ± 0.04%/year). Hippocampal volume loss rate was higher than the GM and CSF global rates, 0.0114 ± 0.0004 ml/year (0.49 ± 0.04%/year). Regions of greatest GM loss were posterior inferior frontal lobe, medial parietal lobe and dorsal cerebellum. Rates of GM loss and CSF expansion were on the low end of the range of other published values, perhaps due to the relatively good health of the elder volunteers in this study. An additional smaller group of 6 subjects diagnosed with MCI at baseline were followed as well, and comparisons were made with the normal group in terms of both global and regional GM loss and CSF expansion rates. An increased rate of GM loss was found in the hippocampus bilaterally for the MCI group.
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Affiliation(s)
- Charles D Smith
- Department of Neurology, University of Kentucky College of Medicine, Lexington, Kentucky, USA.,Magnetic Resonance Imaging and Spectroscopy Center, University of Kentucky, Lexington, Kentucky, USA
| | - Linda J Van Eldik
- Alzheimer's Disease Center, Sanders-Brown Center on Aging, University of Kentucky, Lexington, Kentucky, USA.,Department of Neuroscience, University of Kentucky, Lexington, Kentucky, USA
| | - Gregory A Jicha
- Department of Neurology, University of Kentucky College of Medicine, Lexington, Kentucky, USA.,Alzheimer's Disease Center, Sanders-Brown Center on Aging, University of Kentucky, Lexington, Kentucky, USA
| | - Frederick A Schmitt
- Department of Neurology, University of Kentucky College of Medicine, Lexington, Kentucky, USA.,Alzheimer's Disease Center, Sanders-Brown Center on Aging, University of Kentucky, Lexington, Kentucky, USA
| | - Peter T Nelson
- Alzheimer's Disease Center, Sanders-Brown Center on Aging, University of Kentucky, Lexington, Kentucky, USA.,Department of Pathology and Laboratory Medicine, University of Kentucky, Lexington, Kentucky, USA
| | - Erin L Abner
- Alzheimer's Disease Center, Sanders-Brown Center on Aging, University of Kentucky, Lexington, Kentucky, USA.,Department of Epidemiology, University of Kentucky, Lexington, Kentucky, USA
| | - Richard J Kryscio
- Alzheimer's Disease Center, Sanders-Brown Center on Aging, University of Kentucky, Lexington, Kentucky, USA.,Department of Statistics, University of Kentucky, Lexington, Kentucky, USA
| | - Ronan R Murphy
- Department of Neurology, University of Kentucky College of Medicine, Lexington, Kentucky, USA.,Alzheimer's Disease Center, Sanders-Brown Center on Aging, University of Kentucky, Lexington, Kentucky, USA
| | - Anders H Andersen
- Magnetic Resonance Imaging and Spectroscopy Center, University of Kentucky, Lexington, Kentucky, USA.,Department of Neuroscience, University of Kentucky, Lexington, Kentucky, USA
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Lucchelli F, Saetti MC, Spinnler H. Degenerative Amnesia for Past Public Events: An Attempt to Measure Storage and Retrieval. J Alzheimers Dis 2019; 66:1083-1094. [PMID: 30400092 DOI: 10.3233/jad-180436] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
A still unsettled issue of amnesia concerns the differential contributions to recall impairment of the underlying retrieval and storage abilities. The aim of the present study was to disentangle and to measure such roles in the recall of past public events comparing patients with degenerative amnesia and healthy elderly. The experiment included 44 healthy elderly and two groups of participants with degenerative amnesia, namely 17 patients with amnestic mild cognitive impairment and 22 mild Alzheimer's disease patients. Recall of famous past public events was assessed by means of a 52-item questionnaire standardized for the Italian population. A latent-variable approach was adopted in order to infer the contributions of retrieval and storage to the recall performances. A stochastic model was adopted, which in a previous study of recall of recent and remote past public events in healthy elderly succeeded to prove reduced retrieval efficiency for more recent events. The results of the present study suggest that retrieval is more fragile than storage in all three experimental groups. A storage impairment turned out only in the Alzheimer's disease group, where it was limited to more recent memories. In view of the combined roles of the hippocampus and cortex in past memory processing, our results are consistent with the hypothesis that the degenerative process primarily impairs the strategic memory search. However, the sufficiency criterion of the adopted Markov model fell short of significance. Due to this statistical shortcoming, our conclusions, though consistent with the clinical predictions, are to be taken as provisional.
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Affiliation(s)
| | - Maria Cristina Saetti
- Department of Pathophysiology and Transplantation, University of Milan, Neurology Unit, IRCCS Foundation Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Hans Spinnler
- Department of Health Sciences, University of Milan, Milan, Italy
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24
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Yueniwati Y, Wangsadjaja C, Yulidani IG, Rianawati SB, Al Rasyid H. The Role of Brain Magnetic Resonance Imaging (MRI) as an Early Detector of Cognitive Impairment. J Neurosci Rural Pract 2019; 9:350-353. [PMID: 30069090 PMCID: PMC6050795 DOI: 10.4103/jnrp.jnrp_542_17] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Abstract
Background: Along with the increase of the health and prosperity level will affect the life expectancy in Indonesia, there has also been an increase in degenerative disease cases. One of the problems arises is cognitive impairment. The mild version of this impairment is often associated with the increase risk that will eventually lead to dementia. Therefore, early detection of this impairment is necessary. Objective: This study is aimed at proving the correlation between Fazekas scale on brain MRI and MoCA-Ina score in defining the degree of cognitive impairment. Methods: This study employed observational analytic design and cross sectional study for its data collection method. The Fazekas scale on brain MRI of 32 patients was read by 3 radiologist, while the MoCA-Ina scoring was done by a competent neurologist. Both tests were done double blindly. Later on, the correlation between Fazekas scale and MoCA-Ina score would be assessed using Spearman Correlation. Results: Statistical calculation conducted using Spearman Correlation reveals that the coefficient is -0.519 with significant score (P) 0.002, which is smaller than α: 0.05. Therefore, it can be concluded that there is a strong negative correlation between Fazekas scale and MoCA-Ina score. Conclusion: Fazekas scale evaluation on brain MRI is necessary to be performed as it helps predicting the decline of one's cognitive function, so that an early therapy can be acted upon to prevent dementia in the future.
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Affiliation(s)
- Yuyun Yueniwati
- Department of Radiology, Faculty of Medicine, University of Brawijaya, Malang, Indonesia
| | - Charles Wangsadjaja
- Department of Radiology, Faculty of Medicine, University of Brawijaya, Malang, Indonesia
| | - Islana Gadis Yulidani
- Department of Radiology, Faculty of Medicine, University of Brawijaya, Malang, Indonesia
| | - Sri Budhi Rianawati
- Department of Neurology, Faculty of Medicine, University of Brawijaya, Malang, Indonesia
| | - Harun Al Rasyid
- Department of Public Health, Faculty of Medicine, University of Brawijaya, Malang, Indonesia
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25
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Galts CP, Bettio LE, Jewett DC, Yang CC, Brocardo PS, Rodrigues ALS, Thacker JS, Gil-Mohapel J. Depression in neurodegenerative diseases: Common mechanisms and current treatment options. Neurosci Biobehav Rev 2019; 102:56-84. [DOI: 10.1016/j.neubiorev.2019.04.002] [Citation(s) in RCA: 71] [Impact Index Per Article: 14.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2018] [Revised: 02/22/2019] [Accepted: 04/02/2019] [Indexed: 12/19/2022]
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26
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Bartel F, Visser M, de Ruiter M, Belderbos J, Barkhof F, Vrenken H, de Munck JC, van Herk M. Non-linear registration improves statistical power to detect hippocampal atrophy in aging and dementia. Neuroimage Clin 2019; 23:101902. [PMID: 31233953 PMCID: PMC6595082 DOI: 10.1016/j.nicl.2019.101902] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2018] [Revised: 05/01/2019] [Accepted: 06/16/2019] [Indexed: 12/25/2022]
Abstract
OBJECTIVE To compare the performance of different methods for determining hippocampal atrophy rates using longitudinal MRI scans in aging and Alzheimer's disease (AD). BACKGROUND Quantifying hippocampal atrophy caused by neurodegenerative diseases is important to follow the course of the disease. In dementia, the efficacy of new therapies can be partially assessed by measuring their effect on hippocampal atrophy. In radiotherapy, the quantification of radiation-induced hippocampal volume loss is of interest to quantify radiation damage. We evaluated plausibility, reproducibility and sensitivity of eight commonly used methods to determine hippocampal atrophy rates using test-retest scans. MATERIALS AND METHODS Manual, FSL-FIRST, FreeSurfer, multi-atlas segmentation (MALF) and non-linear registration methods (Elastix, NiftyReg, ANTs and MIRTK) were used to determine hippocampal atrophy rates on longitudinal T1-weighted MRI from the ADNI database. Appropriate parameters for the non-linear registration methods were determined using a small training dataset (N = 16) in which two-year hippocampal atrophy was measured using test-retest scans of 8 subjects with low and 8 subjects with high atrophy rates. On a larger dataset of 20 controls, 40 mild cognitive impairment (MCI) and 20 AD patients, one-year hippocampal atrophy rates were measured. A repeated measures ANOVA analysis was performed to determine differences between controls, MCI and AD patients. For each method we calculated effect sizes and the required sample sizes to detect one-year volume change between controls and MCI (NCTRL_MCI) and between controls and AD (NCTRL_AD). Finally, reproducibility of hippocampal atrophy rates was assessed using within-session rescans and expressed as an average distance measure DAve, which expresses the difference in atrophy rate, averaged over all subjects. The same DAve was used to determine the agreement between different methods. RESULTS Except for MALF, all methods detected a significant group difference between CTRL and AD, but none could find a significant difference between the CTRL and MCI. FreeSurfer and MIRTK required the lowest sample sizes (FreeSurfer: NCTRL_MCI = 115, NCTRL_AD = 17 with DAve = 3.26%; MIRTK: NCTRL_MCI = 97, NCTRL_AD = 11 with DAve = 3.76%), while ANTs was most reproducible (NCTRL_MCI = 162, NCTRL_AD = 37 with DAve = 1.06%), followed by Elastix (NCTRL_MCI = 226, NCTRL_AD = 15 with DAve = 1.78%) and NiftyReg (NCTRL_MCI = 193, NCTRL_AD = 14 with DAve = 2.11%). Manually measured hippocampal atrophy rates required largest sample sizes to detect volume change and were poorly reproduced (NCTRL_MCI = 452, NCTRL_AD = 87 with DAve = 12.39%). Atrophy rates of non-linear registration methods also agreed best with each other. DISCUSSION AND CONCLUSION Non-linear registration methods were most consistent in determining hippocampal atrophy and because of their better reproducibility, methods, such as ANTs, Elastix and NiftyReg, are preferred for determining hippocampal atrophy rates on longitudinal MRI. Since performances of non-linear registration methods are well comparable, the preferred method would mostly depend on computational efficiency.
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Affiliation(s)
- F Bartel
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands.
| | - M Visser
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - M de Ruiter
- Division of Psychosocial Research and Epidemiology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - J Belderbos
- Department of Radiotherapy, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - F Barkhof
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands; UCL institutes of Neurology and healthcare engineering, London, United Kingdom
| | - H Vrenken
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - J C de Munck
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - M van Herk
- Manchester Cancer Research Centre, Division of Cancer Science, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Sciences Centre, Manchester, United Kingdom
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27
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Zhang Y, Wang Y, Guo Y, Liao J, Tu Z, Lu Y, Ding K, Tortorella MD, He J. Identification and synthesis of low-molecular weight cholecystokinin B receptor (CCKBR) agonists as mediators of long-term synaptic potentiation. Med Chem Res 2019. [DOI: 10.1007/s00044-019-02292-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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28
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Mahinrad S, Bulk M, van der Velpen I, Mahfouz A, van Roon-Mom W, Fedarko N, Yasar S, Sabayan B, van Heemst D, van der Weerd L. Natriuretic Peptides in Post-mortem Brain Tissue and Cerebrospinal Fluid of Non-demented Humans and Alzheimer's Disease Patients. Front Neurosci 2018; 12:864. [PMID: 30534047 PMCID: PMC6275179 DOI: 10.3389/fnins.2018.00864] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2018] [Accepted: 11/05/2018] [Indexed: 12/13/2022] Open
Abstract
Animal studies suggest the involvement of natriuretic peptides (NP) in several brain functions that are known to be disturbed during Alzheimer's disease (AD). However, it remains unclear whether such findings extend to humans. In this study, we aimed to: (1) map the gene expression and localization of NP and their receptors (NPR) in human post-mortem brain tissue; (2) compare the relative amounts of NP and NPR between the brain tissue of AD patients and non-demented controls, and (3) compare the relative amounts of NP between the cerebrospinal fluid (CSF) of AD patients and non-demented controls. Using the publicly available Allen Human Brain Atlas dataset, we mapped the gene expression of NP and NPR in healthy humans. Using immunohistochemistry, we visualized the localization of NP and NPR in the frontal cortex of AD patients (n = 10, mean age 85.8 ± 6.2 years) and non-demented controls (mean age = 80.2 ± 9.1 years). Using Western blotting and ELISA, we quantified the relative amounts of NP and NPR in the brain tissue and CSF of these AD patients and non-demented controls. Our results showed that NP and NPR genes were ubiquitously expressed throughout the brain in healthy humans. NP and NPR were present in various cellular structures including in neurons, astrocyte-like structures, and cerebral vessels in both AD patients and non-demented controls. Furthermore, we found higher amounts of NPR type-A in the brain of AD patients (p = 0.045) and lower amounts of NP type-B in the CSF of AD patients (p = 0.029). In conclusion, this study shows the abundance of NP and NPR in the brain of humans suggesting involvement of NP in various brain functions. In addition, our findings suggest alterations of NP levels in the brain of AD patients. The role of NP in the development and progression of AD remains to be elucidated.
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Affiliation(s)
- Simin Mahinrad
- Department of Internal Medicine, Section Gerontology and Geriatrics, Leiden University Medical Center, Leiden, Netherlands
- Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Marjolein Bulk
- Department of Radiology, Leiden University Medical Center, Leiden, Netherlands
- Department of Human Genetics, Leiden University Medical Center, Leiden, Netherlands
- Percuros BV, Leiden, Netherlands
| | - Isabelle van der Velpen
- Department of Internal Medicine, Section Gerontology and Geriatrics, Leiden University Medical Center, Leiden, Netherlands
| | - Ahmed Mahfouz
- Leiden Computational Biology Center, Leiden University Medical Center, Leiden, Netherlands
- Delft Bioinformatics Lab, Delft University of Technology, Delft, Netherlands
| | - Willeke van Roon-Mom
- Department of Human Genetics, Leiden University Medical Center, Leiden, Netherlands
| | - Neal Fedarko
- Clinical Research Core Laboratory, Johns Hopkins Institute for Clinical and Translational Research, Baltimore, MD, United States
| | - Sevil Yasar
- Department of Medicine, School of Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - Behnam Sabayan
- Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Diana van Heemst
- Department of Internal Medicine, Section Gerontology and Geriatrics, Leiden University Medical Center, Leiden, Netherlands
| | - Louise van der Weerd
- Department of Radiology, Leiden University Medical Center, Leiden, Netherlands
- Department of Human Genetics, Leiden University Medical Center, Leiden, Netherlands
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29
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Canadas RF, Ren T, Tocchio A, Marques AP, Oliveira JM, Reis RL, Demirci U. Tunable anisotropic networks for 3-D oriented neural tissue models. Biomaterials 2018; 181:402-414. [DOI: 10.1016/j.biomaterials.2018.07.055] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2018] [Revised: 07/24/2018] [Accepted: 07/28/2018] [Indexed: 02/06/2023]
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30
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Eliassen CF, Reinvang I, Selnes P, Fladby T, Hessen E. Convergent Results from Neuropsychology and from Neuroimaging in Patients with Mild Cognitive Impairment. Dement Geriatr Cogn Disord 2018; 43:144-154. [PMID: 28152536 DOI: 10.1159/000455832] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/04/2017] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND/AIMS To investigate the correspondence between neuropsychological single measures and variation in fludeoxyglucose positron emission tomography (FDG PET) glucose metabolism and magnetic resonance imaging (MRI) cortical thickness in mild cognitive impairment (MCI) patients. METHODS Forty-two elderly controls and 73 MCI subjects underwent FDG PET and MRI scanning. Backward regression analyses with PET and MRI regions were used as dependent variables, while Rey Auditory Verbal Memory Test (RAVLT) recall, Trail Making Test B (TMT B), and a composite test score (RAVLT learning and immediate recall, TMT A, COWAT, and letter-number sequencing) were used as predictor variables. RESULTS The composite score predicted variation in cortical metabolism; supplementary analyses showed that TMT B was significantly correlated with PET metabolism as well. RAVLT and TMT B were significant predictors of variation in MRI cortical thickness. CONCLUSION Our results indicate that RAVLT and TMT B are sensitive to variation in Alzheimer disease neuroimaging markers.
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31
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Loewenstein DA, Curiel RE, DeKosky S, Rosselli M, Bauer R, Grieg-Custo M, Penate A, Li C, Lizagarra G, Golde T, Adjouadi M, Duara R. Recovery from Proactive Semantic Interference and MRI Volume: A Replication and Extension Study. J Alzheimers Dis 2018; 59:131-139. [PMID: 28598850 DOI: 10.3233/jad-170276] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
BACKGROUND The rise in incidence of Alzheimer's disease (AD) has led to efforts to advance early detection of the disease during its preclinical stages. To achieve this, the field needs to develop more sensitive cognitive tests that relate to biological markers of disease pathology. Failure to recover from proactive interference (frPSI) is one such cognitive marker that is associated with volumetric reductions in the hippocampus, precuneus, and other AD-prone regions, and to amyloid load in the brain. OBJECTIVE The current study attempted to replicate and extend our previous findings that frPSI is a sensitive marker of early AD, and related to a unique pattern of volumetric loss in AD prone areas. METHODS Three different memory measures were examined relative to volumetric loss and cortical thickness among 45 participants with amnestic mild cognitive impairment. RESULTS frPSI was uniquely associated with reduced volumes in the hippocampus (r = 0.50) precuneus (r = 0.41), and other AD prone regions, replicating previous findings. Strong associations between frPSI and lower entorhinal cortex volumes and cortical thickness (r≥0.60) and precuneus (r = 0.50) were also observed. CONCLUSION Unique and strong associations between volumetric reductions and frPSI as observed by Loewenstein and colleagues were replicated. Together with cortical thickness findings, these results indicate that frPSI is worthy of further study as a sensitive and early cognitive marker of AD.
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Affiliation(s)
- David A Loewenstein
- Center on Aging and Department of Psychiatry and Behavioral Sciences, Miller School of Medicine, University ofMiami, Miami, FL, USA.,Wien Center for Alzheimer's Disease and Memory Disorders Mount Sinai Medical Center, Miami Beach, FL, USA
| | - Rosie E Curiel
- Center on Aging and Department of Psychiatry and Behavioral Sciences, Miller School of Medicine, University ofMiami, Miami, FL, USA.,Wien Center for Alzheimer's Disease and Memory Disorders Mount Sinai Medical Center, Miami Beach, FL, USA
| | - Steven DeKosky
- Department of Neurology, University of Florida, Gainesville, FL, USA
| | - Monica Rosselli
- Department of Psychology, Florida Atlantic University, Boca Raton, FL, USA
| | - Russell Bauer
- Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA.,Department of Neurology, University of Florida, Gainesville, FL, USA
| | - Maria Grieg-Custo
- Wien Center for Alzheimer's Disease and Memory Disorders Mount Sinai Medical Center, Miami Beach, FL, USA
| | - Ailyn Penate
- Center on Aging and Department of Psychiatry and Behavioral Sciences, Miller School of Medicine, University ofMiami, Miami, FL, USA.,Wien Center for Alzheimer's Disease and Memory Disorders Mount Sinai Medical Center, Miami Beach, FL, USA
| | - Chunfei Li
- Department of Electricaland Computer Engineering, Center for Advanced Technology andEducation, College of Engineering and Computing, Florida International University, Miami, FL, USA
| | - Gabriel Lizagarra
- Department of Electricaland Computer Engineering, Center for Advanced Technology andEducation, College of Engineering and Computing, Florida International University, Miami, FL, USA
| | - Todd Golde
- Department of Neurology, University of Florida, Gainesville, FL, USA
| | - Malek Adjouadi
- Department of Electricaland Computer Engineering, Center for Advanced Technology andEducation, College of Engineering and Computing, Florida International University, Miami, FL, USA
| | - Ranjan Duara
- Wien Center for Alzheimer's Disease and Memory Disorders Mount Sinai Medical Center, Miami Beach, FL, USA.,Department of Neurology, University of Florida, Gainesville, FL, USA.,Center for Translational Research In Neurodegenerative Diseases, University of Florida, Gainesville, FL, USA.,Herbert Wertheim College of Medicine, Florida International University, Miami, FL, USA
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Manual segmentation of the fornix, fimbria, and alveus on high-resolution 3T MRI: Application via fully-automated mapping of the human memory circuit white and grey matter in healthy and pathological aging. Neuroimage 2018; 170:132-150. [DOI: 10.1016/j.neuroimage.2016.10.027] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2016] [Revised: 10/14/2016] [Accepted: 10/17/2016] [Indexed: 01/18/2023] Open
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Classification of Alzheimer's and MCI Patients from Semantically Parcelled PET Images: A Comparison between AV45 and FDG-PET. Int J Biomed Imaging 2018; 2018:1247430. [PMID: 29736165 PMCID: PMC5875062 DOI: 10.1155/2018/1247430] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2017] [Revised: 02/02/2018] [Accepted: 02/12/2018] [Indexed: 02/01/2023] Open
Abstract
Early identification of dementia in the early or late stages of mild cognitive impairment (MCI) is crucial for a timely diagnosis and slowing down the progression of Alzheimer's disease (AD). Positron emission tomography (PET) is considered a highly powerful diagnostic biomarker, but few approaches investigated the efficacy of focusing on localized PET-active areas for classification purposes. In this work, we propose a pipeline using learned features from semantically labelled PET images to perform group classification. A deformable multimodal PET-MRI registration method is employed to fuse an annotated MNI template to each patient-specific PET scan, generating a fully labelled volume from which 10 common regions of interest used for AD diagnosis are extracted. The method was evaluated on 660 subjects from the ADNI database, yielding a classification accuracy of 91.2% for AD versus NC when using random forests combining features from cross-sectional and follow-up exams. A considerable improvement in the early versus late MCI classification accuracy was achieved using FDG-PET compared to the AV-45 compound, yielding a 72.5% rate. The pipeline demonstrates the potential of exploiting longitudinal multiregion PET features to improve cognitive assessment.
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Loewenstein DA, Curiel RE, Wright C, Sun X, Alperin N, Crocco E, Czaja SJ, Raffo A, Penate A, Melo J, Capp K, Gamez M, Duara R. Recovery from Proactive Semantic Interference in Mild Cognitive Impairment and Normal Aging: Relationship to Atrophy in Brain Regions Vulnerable to Alzheimer's Disease. J Alzheimers Dis 2018; 56:1119-1126. [PMID: 28106554 DOI: 10.3233/jad-160881] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
BACKGROUND There is growing evidence that proactive semantic interference (PSI) and failure to recover from PSI may represent early features of Alzheimer's disease (AD). OBJECTIVE This study investigated the association between PSI, recovery from PSI, and reduced MRI volumes in AD signature regions among cognitively impaired and unimpaired older adults. METHODS Performance on the LASSI-L (a novel test of PSI and recovery from PSI) and regional brain volumetric measures were compared between 38 cognitively normal (CN) elders and 29 older participants with amnestic mild cognitive impairment (MCI). The relationship between MRI measures and performance on the LASSI-L as well as traditional memory and non-memory cognitive measures was also evaluated in both diagnostic groups. RESULTS Relative to traditional neuropsychological measures, MCI patients' failure to recover from PSI was associated with reduced volumes in the hippocampus (rs = 0.48), precuneus (rs = 0.50); rostral middle frontal lobules (rs = 0.54); inferior temporal lobules (rs = 0.49), superior parietal lobules (rs = 0.47), temporal pole (rs = 0.44), and increased dilatation of the inferior lateral ventricle (rs = -0.49). For CN elders, only increased inferior lateral ventricular size was associated with vulnerability to PSI (rs = -0.49), the failure to recover from PSI (rs = -0.57), and delayed recall on the Hopkins Verbal Learning Test-Revised (rs = -0.48). DISCUSSION LASSI-L indices eliciting failure to recover from PSI were more highly associated with more MRI regional biomarkers of AD than other traditional cognitive measures. These results as well as recent amyloid imaging studies with otherwise cognitively normal subjects, suggest that recovery from PSI may be a sensitive marker of preclinical AD and deserves further investigation.
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Affiliation(s)
- David A Loewenstein
- Department of Psychiatry and Behavioral Sciences and Center on Aging, Miller School of Medicine, University of Miami, Miami, FL, USA.,Wien Center for Alzheimer's Disease and Memory Disorders Mount Sinai Medical Center, Miami Beach, FL, USA
| | - Rosie E Curiel
- Department of Psychiatry and Behavioral Sciences and Center on Aging, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Clinton Wright
- Department of Neurology, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Xiaoyan Sun
- Department of Neurology, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Noam Alperin
- Department of Radiology, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Elzabeth Crocco
- Department of Psychiatry and Behavioral Sciences and Center on Aging, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Sara J Czaja
- Department of Psychiatry and Behavioral Sciences and Center on Aging, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Arlene Raffo
- Department of Psychiatry and Behavioral Sciences and Center on Aging, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Ailyn Penate
- Department of Psychiatry and Behavioral Sciences and Center on Aging, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Jose Melo
- Department of Psychiatry and Behavioral Sciences and Center on Aging, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Kimberly Capp
- Department of Psychology, Nova Southeastern University, Fort Lauderdale, FL, USA
| | - Monica Gamez
- Department of Psychology, Nova Southeastern University, Fort Lauderdale, FL, USA
| | - Ranjan Duara
- Wien Center for Alzheimer's Disease and Memory Disorders Mount Sinai Medical Center, Miami Beach, FL, USA.,Herbert Wertheim College of Medicine, Florida International University, Miami, FL, USA
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Crocco EA, Loewenstein DA, Curiel RE, Alperin N, Czaja SJ, Harvey PD, Sun X, Lenchus J, Raffo A, Peñate A, Melo J, Sang L, Valdivia R, Cardenas K. A novel cognitive assessment paradigm to detect Pre-mild cognitive impairment (PreMCI) and the relationship to biological markers of Alzheimer's disease. J Psychiatr Res 2018; 96:33-38. [PMID: 28957712 PMCID: PMC6132245 DOI: 10.1016/j.jpsychires.2017.08.015] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/17/2017] [Revised: 06/20/2017] [Accepted: 08/18/2017] [Indexed: 11/15/2022]
Abstract
OBJECTIVE A number of older adults obtain normal scores on formal cognitive tests, but present clinical concerns that raise suspicion of cognitive decline. Despite not meeting full criteria for Mild Cognitive Impairment (MCI), these PreMCI states confer risk for progression to Alzheimer's disease (AD). This investigation addressed a pressing need to identify cognitive measures that are sensitive to PreMCI and are associated with brain biomarkers of neurodegeneration. METHOD Participants included 49 older adults with a clinical history suggestive of cognitive decline but normal scores on an array of neuropsychological measures, thus not meeting formal criteria for MCI. The performance of these PreMCI participants were compared to 117 cognitively normal (CN) elders on the LASSI-L, a cognitive stress test that uniquely assesses the failure to recover from proactive semantic interference effects (frPSI). Finally, a subset of these individuals had volumetric analyses based on MRI scans. RESULTS PreMCI participants evidenced greater LASSI- L deficits, particularly with regards to frPSI and delayed recall, relative to the CN group. No differences on MRI measures were observed. Controlling for false discovery rate (FDR), frPSI was uniquely related to increased dilatation of the inferior lateral ventricle and decreased MRI volumes in the hippocampus, precuneus, superior parietal region, and other AD prone areas. In contrast, other LASSI-L indices and standard memory tests were not related to volumetric findings. CONCLUSIONS Despite equivalent performance on traditional memory measures, the frPSI distinguished between PreMCI and CN elders and was associated with reductions in brain volume in numerous AD-relevant brain regions.
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Affiliation(s)
- Elizabeth A Crocco
- Department of Psychiatry and Behavioral Sciences, Center on Aging, Miller School of Medicine, University of Miami, United States
| | - David A Loewenstein
- Department of Psychiatry and Behavioral Sciences, Center on Aging, Miller School of Medicine, University of Miami, United States.
| | - Rosie E Curiel
- Department of Psychiatry and Behavioral Sciences, Center on Aging, Miller School of Medicine, University of Miami, United States
| | - Noam Alperin
- Department of Neurology, Miller School of Medicine, University of Miami, United States
| | - Sara J Czaja
- Department of Psychiatry and Behavioral Sciences, Center on Aging, Miller School of Medicine, University of Miami, United States
| | - Philip D Harvey
- Department of Psychiatry and Behavioral Sciences, Center on Aging, Miller School of Medicine, University of Miami, United States; Research Service, Bruce W. Carter VA Medical Center, Miami, FL, United States
| | - Xiaoyan Sun
- Department of Neurology, Miller School of Medicine, University of Miami, United States
| | - Joshua Lenchus
- Department of Medicine, Miller School of Medicine, University of Miami, United States
| | - Arlene Raffo
- Department of Psychiatry and Behavioral Sciences, Center on Aging, Miller School of Medicine, University of Miami, United States
| | - Ailyn Peñate
- Department of Psychiatry and Behavioral Sciences, Center on Aging, Miller School of Medicine, University of Miami, United States
| | - Jose Melo
- Department of Psychiatry and Behavioral Sciences, Center on Aging, Miller School of Medicine, University of Miami, United States
| | - Lee Sang
- Department of Radiology, Miller School of Medicine, University of Miami, United States
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Yang W, Chen X, Cohen DS, Rosin ER, Toga AW, Thompson PM, Huang X. Classification of MRI and psychological testing data based on support vector machine. Int J Clin Exp Med 2017; 10:16004-16026. [PMID: 29445429 PMCID: PMC5808983] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Alzheimer's disease (AD) is a progressive, and often fatal, brain disease that causes neurodegeneration, resulting in memory loss as well as other cognitive and behavioral problems. Here, we propose a novel multimodal method combining independent components from MRI measures and clinical assessments to distinguish Alzheimer's patients or mild cognitive impairment (MCI) subjects from healthy elderly controls. 70 AD subjects (mean age: 77.15 ± 6.2 years), 98 MCI subjects (mean age: 76.91 ± 5.7 years), and 150 HC subjects (mean age: 75.69 ± 3.8 years) were analyzed. Our method includes the following steps: pre-processing, estimating the number of independent components from the MR image data, extracting effective voxels for classification, and classification using a support vector machine (SVM)-based classifier. As a result, with regards to classifying AD from healthy controls, we achieved a classification accuracy of 97.7%, sensitivity of 99.2%, and specificity of 96.7%; for differentiating MCI from healthy controls, we achieved a classification accuracy of 87.8%, a sensitivity of 86.0%, and a specificity of 89.6; these results are better than those obtained with clinical measurements alone (accuracy of 79.5%, sensitivity of 74.0%, and specificity of 85.1%). We found that (1) both AD patients and MCI subjects showed brain tissue loss, but the volumes of gray matter loss in MCI subjects was far less, supporting the notion that MCI is a prodromal stage of AD; and (2) combining gray matter features from MRI and three commonly used measures of mental status, cognitive function improved classification accuracy, sensitivity, and specificity compared with classification using only independent components or clinical measurements.
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Affiliation(s)
- Wenlu Yang
- Department of Electrical Engineering, Information Engineering College, Shanghai Maritime University, Shanghai, China
| | - Xinyun Chen
- Department of Electrical Engineering, Information Engineering College, Shanghai Maritime University, Shanghai, China
| | - David S Cohen
- Neurochemistry Laboratory, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Eric R Rosin
- Neurochemistry Laboratory, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Arthur W Toga
- Laboratory of Neuro Imaging, The Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - Paul M Thompson
- Laboratory of Neuro Imaging, The Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - Xudong Huang
- Neurochemistry Laboratory, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
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Gonzales MM, Insel PS, Nelson C, Tosun D, Mattsson N, Mueller SG, Sacuiu S, Bickford D, Weiner MW, Mackin RS. Cortical Atrophy is Associated with Accelerated Cognitive Decline in Mild Cognitive Impairment with Subsyndromal Depression. Am J Geriatr Psychiatry 2017; 25:980-991. [PMID: 28629965 PMCID: PMC10079284 DOI: 10.1016/j.jagp.2017.04.011] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/02/2016] [Revised: 03/10/2017] [Accepted: 04/18/2017] [Indexed: 12/11/2022]
Abstract
OBJECTIVES To investigate the association between cognitive decline and cortical atrophy in individuals with mild cognitive impairment (MCI) and chronic subsyndromal symptoms of depression (SSD) over a 4-year period. DESIGN Prospective cohort study. SETTING Multicenter, clinic-based. PARTICIPANTS Within the Alzheimer's Disease Neuroimaging Initiative repository, the Neuropsychiatric Inventory was used to identify individuals with MCI and stable endorsement (SSD group N = 32) or no endorsement (non-SSD group N = 69) of depressive symptoms across time points. MEASUREMENTS Repeated measures of cognitive outcomes, cortical atrophy, and their associations were evaluated with mixed effects models adjusting for age, education, sex, and APOE genotype. RESULTS The SSD group demonstrated accelerated decline on measures of global cognition (Alzheimer Disease Assessment Scale; df = 421, t = 2.242, p = 0.025), memory (Wechsler Memory Scale-Revised Logical Memory II; df = 244, t = -2.525, p = 0.011), information processing speed (Trail Making Test Parts A [df = 421, t = 2.376, p = 0.018] and B [df = 421, t = 2.533, p = 0.012]), and semantic fluency (Category Fluency; df = 424, t = -2.418, p = 0.016), as well as accelerated frontal lobe (df = 341, t = -2.648, p = 0.008) and anterior cingulate (df = 341, t = -3.786, p < 0.001) atrophy. No group differences were observed for rate of decline on measures of attention, learning, and confrontation naming or for rate of atrophy in any other regions. Accelerated frontal lobe and anterior cingulate atrophy was associated with cognitive decline on measures of global cognition, information processing speed, and semantic fluency (all p < 0.05), but not memory. CONCLUSIONS Individuals with chronic SSD may represent an MCI subgroup that is highly vulnerable to accelerated cognitive decline, an effect that may be governed by frontal lobe and anterior cingulate atrophy.
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Affiliation(s)
- Mitzi M Gonzales
- Department of Mental Health, V.A. Northern California Health Care System, Martinez, CA
| | - Philip S Insel
- Center for Imaging of Neurodegenerative Diseases, Veterans Administration Medical Center, San Francisco, CA
| | - Craig Nelson
- Departments of Psychiatry, University of California, San Francisco, CA
| | - Duygu Tosun
- Center for Imaging of Neurodegenerative Diseases, Veterans Administration Medical Center, San Francisco, CA; Department of Radiology, University of California, San Francisco, CA
| | - Niklas Mattsson
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden; Department of Neurology, Skane University Hospital, Lund, Sweden
| | - Susanne G Mueller
- Center for Imaging of Neurodegenerative Diseases, Veterans Administration Medical Center, San Francisco, CA; Department of Radiology, University of California, San Francisco, CA
| | - Simona Sacuiu
- Institute of Neuroscience, Physiology, Sahlgrenska Academy, University of Gothenburg, Sweden
| | - David Bickford
- Departments of Psychiatry, University of California, San Francisco, CA
| | - Michael W Weiner
- Center for Imaging of Neurodegenerative Diseases, Veterans Administration Medical Center, San Francisco, CA; Departments of Psychiatry, University of California, San Francisco, CA; Department of Radiology, University of California, San Francisco, CA; Department of Medicine, University of California, San Francisco, CA
| | - R Scott Mackin
- Center for Imaging of Neurodegenerative Diseases, Veterans Administration Medical Center, San Francisco, CA; Departments of Psychiatry, University of California, San Francisco, CA.
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Zufferey V, Donati A, Popp J, Meuli R, Rossier J, Frackowiak R, Draganski B, von Gunten A, Kherif F. Neuroticism, depression, and anxiety traits exacerbate the state of cognitive impairment and hippocampal vulnerability to Alzheimer's disease. ALZHEIMER'S & DEMENTIA: DIAGNOSIS, ASSESSMENT & DISEASE MONITORING 2017; 7:107-114. [PMID: 28653033 PMCID: PMC5476972 DOI: 10.1016/j.dadm.2017.05.002] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Introduction Certain personality traits are associated with higher risk of Alzheimer's disease, similar to cognitive impairment. The identification of biological markers associated with personality in mild cognitive impairment could advance the early detection of Alzheimer's disease. Methods We used hierarchical multivariate linear models to quantify the interaction between personality traits, state of cognitive impairment, and MRI biomarkers (gray matter brain volume, gray matter mean water diffusion) in the medial temporal lobe (MTL). Results Over and above a main effect of cognitive state, the multivariate linear model showed significant interaction between cognitive state and personality traits predicting MTL abnormality. The interaction effect was mainly driven by neuroticism and its facets (anxiety, depression, and stress) and was associated with right-left asymmetry and an anterior to posterior gradient in the MTL. Discussion Our results support the hypothesis that personality traits can alter the vulnerability and pathoplasticity of disease and therefore modulate related biomarker expression.
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Affiliation(s)
- Valérie Zufferey
- Laboratoire de Recherche en Neuroimagerie (LREN), Département des neurosciences cliniques, Centre Hospitalier Universitaire Vaudois, Université de Lausanne, Lausanne, Switzerland
- Service of Old Age Psychiatry, Department of Psychiatry, Centre Hospitalier Universitaire Vaudois, Prilly-Lausanne, Switzerland
| | - Alessia Donati
- Service of Old Age Psychiatry, Department of Psychiatry, Centre Hospitalier Universitaire Vaudois, Prilly-Lausanne, Switzerland
| | - Julius Popp
- Service of Old Age Psychiatry, Department of Psychiatry, Centre Hospitalier Universitaire Vaudois, Prilly-Lausanne, Switzerland
| | - Reto Meuli
- Department of Diagnostic and Interventional Radiology, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland
| | - Jérôme Rossier
- Faculty of Social and Political Sciences, Institute of Psychology, University of Lausanne, Lausanne, Switzerland
| | - Richard Frackowiak
- Laboratoire de Recherche en Neuroimagerie (LREN), Département des neurosciences cliniques, Centre Hospitalier Universitaire Vaudois, Université de Lausanne, Lausanne, Switzerland
| | - Bogdan Draganski
- Laboratoire de Recherche en Neuroimagerie (LREN), Département des neurosciences cliniques, Centre Hospitalier Universitaire Vaudois, Université de Lausanne, Lausanne, Switzerland
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Armin von Gunten
- Service of Old Age Psychiatry, Department of Psychiatry, Centre Hospitalier Universitaire Vaudois, Prilly-Lausanne, Switzerland
| | - Ferath Kherif
- Laboratoire de Recherche en Neuroimagerie (LREN), Département des neurosciences cliniques, Centre Hospitalier Universitaire Vaudois, Université de Lausanne, Lausanne, Switzerland
- Corresponding author. Tel.: +41 314 95 93; Fax: +41 21 314 1256.
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Effects of mild cognitive impairment on emotional scene memory. Neuropsychologia 2017; 96:240-248. [PMID: 28089697 DOI: 10.1016/j.neuropsychologia.2017.01.011] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2016] [Revised: 01/02/2017] [Accepted: 01/10/2017] [Indexed: 11/24/2022]
Abstract
Young and older adults experience benefits in attention and memory for emotional compared to neutral information, but this memory benefit is greatly diminished in Alzheimer's disease (AD). Little is known about whether this impairment arises early or late in the time course between healthy aging and AD. This study compared memory for positive, negative, and neutral items with neutral backgrounds between patients with mild cognitive impairment (MCI) and healthy older adults. We also used a divided attention condition in older adults as a possible model for the deficits observed in MCI patients. Results showed a similar pattern of selective memory for emotional items while forgetting their backgrounds in older adults and MCI patients, but MCI patients had poorer memory overall. Dividing attention during encoding disproportionately reduced memory for backgrounds (versus items) relative to a full attention condition. Participants performing in the lower half on the divided attention task qualitatively and quantitatively mirrored the results in MCI patients. Exploratory analyses comparing lower- and higher-performing MCI patients showed that only higher-performing MCI patients had the characteristic scene memory pattern observed in healthy older adults. Together, these results suggest that the effects of emotion on memory are relatively well preserved for patients with MCI, although emotional memory patterns may start to be altered once memory deficits become more pronounced.
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Goes VF, Mello-Carpes PB, de Oliveira LO, Hack J, Magro M, Bonini JS. Evaluation of dysphagia risk, nutritional status and caloric intake in elderly patients with Alzheimer's. Rev Lat Am Enfermagem 2016; 22:317-24. [PMID: 26107841 PMCID: PMC4292605 DOI: 10.1590/0104-1169.3252.2418] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2013] [Accepted: 12/19/2013] [Indexed: 11/25/2022] Open
Abstract
Objective to evaluate the risk of dysphagia and its relationship with the stage of
Alzheimer's Disease, as well as the relationship between the risk of
dysphagia and nutritional status and caloric intake in elderly people with
Alzheimer's disease. Methods the sample consisted of 30 subjects of both genders with probable
Alzheimer's disease. The stage of the disease, nutritional status, energy
intake, and risk of dysphagia were assessed. Results it was found that increased risk of dysphagia is associated with the advance
in the stages of Alzheimer's disease and that even patients in the early
stages of disease have a slight risk of developing dysphagia. No association
was found between nutritional status and the risk of dysphagia. High levels
of inadequate intake of micronutrients were also verified in the patients.
Conclusion an association between dysphagia and the development of Alzheimer's disease
was found. The results indicate the need to monitor the presence of
dysphagia and the micronutrient intake in patients with Alzheimer's
disease.
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Affiliation(s)
| | | | | | - Jaqueline Hack
- Departamento de Nutrição, Universidade Estadual do Centro-Oeste, Guarapuava, PR, Brasil
| | - Marcela Magro
- Departamento de Nutrição, Universidade Estadual do Centro-Oeste, Guarapuava, PR, Brasil
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Mondragón JD, Celada-Borja C, Barinagarrementeria-Aldatz F, Burgos-Jaramillo M, Barragán-Campos HM. Hippocampal Volumetry as a Biomarker for Dementia in People with Low Education. Dement Geriatr Cogn Dis Extra 2016; 6:486-499. [PMID: 27920792 PMCID: PMC5122988 DOI: 10.1159/000449424] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Background/Aims To evaluate the relationship between hippocampal volume and cognitive decline in patients with dementia due to probable Alzheimer's disease (AD), amnestic mild cognitive impairment (aMCI) and education, and the possible relationship between cognitive reserve and education in this population. Methods From February 2013 to October 2015, 76 patients (25 men, 51 women) were classified according to the NIA-AA diagnostic criteria. We used two 3.0-tesla MRI scanners and performed manual hippocampal volumetry. Results Twenty-six patients were found to have AD, 20 aMCI and 30 had normal aging (NA). The mean normalized hippocampal volume in age-, sex- and education (years)-matched subjects was 2.38 ± 0.51 cm3 in AD (p < 0.001), 2.91 ± 0.78 cm3 in aMCI (p = 0.019) and 3.07 ± 0.76 cm3 in NA. Conclusion Psychometric test (MMSE and MoCA) scores had a good to strong positive correlation with statistically significant differences in the entire population and healthy subjects but not among dementia patients and lower educational level groups. The patients with low education had greater hippocampal volumes, which is in line with the cognitive reserve theory; lower-educated individuals can tolerate less neuropathology and will thus show less atrophy at a similar level of cognitive performance than higher-educated subjects.
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Affiliation(s)
- Jaime D Mondragón
- Unidad de Resonancia Magnética, Instituto de Neurobiología, UNAM-Campus Juriquilla, Querétaro, Mexico
| | - César Celada-Borja
- Instituto Nacional de Psiquiatría Ramón de la Fuente Muñiz, Ciudad de México, Mexico
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Porat S, Goukasian N, Hwang KS, Zanto T, Do T, Pierce J, Joshi S, Woo E, Apostolova LG. Dance Experience and Associations with Cortical Gray Matter Thickness in the Aging Population. Dement Geriatr Cogn Dis Extra 2016; 6:508-517. [PMID: 27920794 PMCID: PMC5123027 DOI: 10.1159/000449130] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
INTRODUCTION We investigated the effect dance experience may have on cortical gray matter thickness and cognitive performance in elderly participants with and without mild cognitive impairment (MCI). METHODS 39 cognitively normal and 48 MCI elderly participants completed a questionnaire regarding their lifetime experience with music, dance, and song. Participants identified themselves as either dancers or nondancers. All participants received structural 1.5-tesla MRI scans and detailed clinical and neuropsychological evaluations. An advanced 3D cortical mapping technique was then applied to calculate cortical thickness. RESULTS Despite having a trend-level significantly thinner cortex, dancers performed better in cognitive tasks involving learning and memory, such as the California Verbal Learning Test-II (CVLT-II) short delay free recall (p = 0.004), the CVLT-II long delay free recall (p = 0.003), and the CVLT-II learning over trials 1-5 (p = 0.001). DISCUSSION Together, these results suggest that dance may result in an enhancement of cognitive reserve in aging, which may help avert or delay MCI.
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Affiliation(s)
- Shai Porat
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, Calif, USA
- Mary S. Easton Center for Alzheimer's Disease Research, Los Angeles, Calif, USA
| | - Naira Goukasian
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, Calif, USA
- Mary S. Easton Center for Alzheimer's Disease Research, Los Angeles, Calif, USA
| | - Kristy S. Hwang
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, Calif, USA
- Mary S. Easton Center for Alzheimer's Disease Research, Los Angeles, Calif, USA
- Oakland University William Beaumont School of Medicine, Rochester, Mich., USA
| | - Theodore Zanto
- Department of Neurology, UCSF, San Francisco, Calif, USA
| | - Triet Do
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, Calif, USA
- Mary S. Easton Center for Alzheimer's Disease Research, Los Angeles, Calif, USA
| | - Jonathan Pierce
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, Calif, USA
- Mary S. Easton Center for Alzheimer's Disease Research, Los Angeles, Calif, USA
| | - Shantanu Joshi
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, Calif, USA
| | - Ellen Woo
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, Calif, USA
- Mary S. Easton Center for Alzheimer's Disease Research, Los Angeles, Calif, USA
| | - Liana G. Apostolova
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, Calif, USA
- Mary S. Easton Center for Alzheimer's Disease Research, Los Angeles, Calif, USA
- Department of Neurology, Indiana University, Indianapolis, Ind, USA
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Innes KE, Selfe TK, Khalsa DS, Kandati S. A randomized controlled trial of two simple mind-body programs, Kirtan Kriya meditation and music listening, for adults with subjective cognitive decline: Feasibility and acceptability. Complement Ther Med 2016; 26:98-107. [DOI: 10.1016/j.ctim.2016.03.002] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2015] [Revised: 03/01/2016] [Accepted: 03/02/2016] [Indexed: 12/14/2022] Open
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Sacuiu S, Insel PS, Mueller S, Tosun D, Mattsson N, Jack CR, DeCarli C, Petersen R, Aisen PS, Weiner MW, Mackin RS. Chronic Depressive Symptomatology in Mild Cognitive Impairment Is Associated with Frontal Atrophy Rate which Hastens Conversion to Alzheimer Dementia. Am J Geriatr Psychiatry 2016; 24:126-35. [PMID: 26238228 PMCID: PMC4973623 DOI: 10.1016/j.jagp.2015.03.006] [Citation(s) in RCA: 52] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2014] [Revised: 03/07/2015] [Accepted: 03/24/2015] [Indexed: 12/11/2022]
Abstract
OBJECTIVE Investigate the association of chronic depressive symptomatology (chrDS) with cortical atrophy rates and conversion to Alzheimer dementia (AD) over 3 years in mild cognitive impairment (MCI). METHODS In a multicenter, clinic-based study, MCI elderly participants were selected from the Alzheimer's Disease Neuroimaging Initiative repository, based on availability of both serial structural magnetic resonance imaging and chrDS endorsed on three depression-related items from the Neuropsychiatric Inventory Questionnaire (chrDS N = 32 or no depressive symptoms N = 62) throughout follow-up. Clinical and laboratory investigations were performed every 6 months during the first 2 years and yearly thereafter (median follow-up: 3 years; interquartile range: 1.5-4.0 years). Cortical atrophy rates in 16 predefined frontotemporoparietal regions affected in major depression and AD and the rate of incident AD at follow-up. RESULTS ChrDS in a single domain amnestic MCI sample were associated with accelerated cortical atrophy in the frontal lobe and anterior cingulate but not with atrophy rates in temporomedial or other AD-affected regions. During follow-up, 38 participants (42.7%) developed AD. Participants with chrDS had 60% shorter conversion time to AD than those without depressive symptoms. This association remained significant in survival models adjusted for temporomedial atrophy rates and showed the same trend in models adjusted for frontal cortical atrophy rate, which all increased the risk of AD. CONCLUSION Our results suggest that chrDS associated with progressive atrophy of frontal regions may represent an additional risk factor for conversion to dementia in MCI as opposite to representing typical prodromal AD symptomatology.
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Affiliation(s)
- Simona Sacuiu
- Center for Imaging of Neurodegenerative Diseases (CIND) at the Veterans Affairs Medical Center (VAMC) San Francisco and Department of Radiology and Biomedical Imaging (DRBI) at University of California San Francisco (UCSF), CA, USA and Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Sweden
| | | | | | - Duygu Tosun
- CIND at VAMC San Francisco and DRBI at UCSF, CA, USA
| | - Niklas Mattsson
- CIND at VAMC San Francisco and DRBI at UCSF, CA, USA and Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Sweden
| | | | - Charles DeCarli
- Department of Neurology and Center for Neuroscience, University of California at Davis, Sacramento, CA, USA
| | - Ronald Petersen
- Mayo Alzheimer’s Disease Research Center and Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Paul S. Aisen
- Department of Neurosciences, University of California, San Diego, CA, USA
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Blood and CSF biomarkers in brain subcortical ischemic vascular disease: Involved pathways and clinical applicability. J Cereb Blood Flow Metab 2016; 36:55-71. [PMID: 25899297 PMCID: PMC4758557 DOI: 10.1038/jcbfm.2015.68] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2015] [Revised: 03/20/2015] [Accepted: 03/21/2015] [Indexed: 12/26/2022]
Abstract
Vascular dementia is the second most common type of dementia after Alzheimer’s disease (AD). Subcortical ischemic vascular disease refers to a form of vascular cognitive impairment characterized by the presence of diffuse white matter hyperintensities (WMHs) and multiple lacunar infarcts. These neuroimaging findings are mainly caused by cerebral small-vessel disease (cSVD) and relate to aging and cognitive impairment, but they can also be silent and highly prevalent in otherwise healthy individuals. We aimed to review studies on blood and cerebrospinal fluid (CSF) markers related to the presence of WMHs and lacunar infarcts that have been conducted in the past in large population-based studies and in high-risk selected patients (such as those with vascular risk factors, vascular cognitive impairment, or AD). Relevant associations with the presence and progression of cSVD have been described in the blood for markers related to inflammatory processes, endothelial damage and coagulation/fibrinolysis processes, etc. Also, different combinations of CSF markers might help to differentiate between etiologic types of dementia. In the future, to translate these findings into clinical practice and use biomarkers to early diagnosis and monitoring vascular cognitive impairment would require the replication of candidate markers in large-scale, multicenter, and prospectively designed studies.
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Abstract
This chapter will focus on the descriptive, analytic, and intervention-oriented epidemiology of dementia and its most frequent etiologic type due to Alzheimer's disease. The chapter opens with a brief presentation of the concept of dementia, followed by the presentation of dementia of the Alzheimer type (DAT), including natural history, clinical manifestation, neuropathology, medical prognosis, and management. Further, the chapter presents the prevalence and incidence of dementia, with special consideration of secular trends in prevalence and incidence of DAT, and prognosis of the socioeconomic impact of dementia. Thereafter the main risk factors for DAT are covered. The chapter also addresses the results of ongoing therapeutic and preventive intervention trials for DAT. Finally, the future challenges of the epidemiology of dementia with a focus on the impact of the new diagnostic criteria for neurocognitive disorders, as well as the development of biomarkers for DAT and other types of dementia, will be briefly discussed.
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Affiliation(s)
- S F Sacuiu
- Department of Neuropsychiatry, Sahlgrenska University Hospital and Department of Psychiatry and Neurochemistry, University of Gothenburg Institute of Neuroscience and Physiology, Gothenburg, Sweden.
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Ben Ahmed O, Mizotin M, Benois-Pineau J, Allard M, Catheline G, Ben Amar C. Alzheimer's disease diagnosis on structural MR images using circular harmonic functions descriptors on hippocampus and posterior cingulate cortex. Comput Med Imaging Graph 2015; 44:13-25. [DOI: 10.1016/j.compmedimag.2015.04.007] [Citation(s) in RCA: 56] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2014] [Revised: 02/21/2015] [Accepted: 04/27/2015] [Indexed: 01/18/2023]
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Bertoux M, O'Callaghan C, Flanagan E, Hodges JR, Hornberger M. Fronto-Striatal Atrophy in Behavioral Variant Frontotemporal Dementia and Alzheimer's Disease. Front Neurol 2015; 6:147. [PMID: 26191038 PMCID: PMC4486833 DOI: 10.3389/fneur.2015.00147] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2015] [Accepted: 06/18/2015] [Indexed: 11/17/2022] Open
Abstract
Behavioral variant frontotemporal dementia (bvFTD) has only recently been associated with significant striatal atrophy, whereas the striatum appears to be relatively preserved in Alzheimer’s disease (AD). Considering the critical role the striatum has in cognition and behavior, striatal degeneration, together with frontal atrophy, could be responsible of some characteristic symptoms in bvFTD and emerges therefore as promising novel diagnostic biomarker to distinguish bvFTD and AD. Previous studies have, however, only taken either cortical or striatal atrophy into account when comparing the two diseases. In this study, we establish for the first time a profile of fronto-striatal atrophy in 23 bvFTD and 29 AD patients at presentation, based on the structural connectivity of striatal and cortical regions. Patients are compared to 50 healthy controls by using a novel probabilistic connectivity atlas, which defines striatal regions by their cortical white-matter connectivity, allowing us to explore the degeneration of the frontal and striatal regions that are functionally linked. Comparisons with controls revealed that bvFTD showed substantial fronto-striatal atrophy affecting the ventral as well as anterior and posterior dorso-lateral prefrontal cortices and the related striatal subregions. In contrast, AD showed few fronto-striatal atrophy, despite having significant posterior dorso-lateral prefrontal degeneration. Direct comparison between bvFTD and AD revealed significantly more atrophy in the ventral striatal–ventromedial prefrontal cortex regions in bvFTD. Consequently, deficits in ventral fronto-striatal regions emerge as promising novel and efficient diagnosis biomarker for bvFTD. Future investigations into the contributions of these fronto-striatal loops on bvFTD symptomology are needed to develop simple diagnostic and disease tracking algorithms.
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Affiliation(s)
- Maxime Bertoux
- Neurosciences Research Australia (NeuRA) , Randwick, NSW , Australia ; Department of Clinical Neurosciences, University of Cambridge , Cambridge , UK
| | - Claire O'Callaghan
- Neurosciences Research Australia (NeuRA) , Randwick, NSW , Australia ; School of Medical Sciences, University of New South Wales , Sydney, NSW , Australia
| | - Emma Flanagan
- Neurosciences Research Australia (NeuRA) , Randwick, NSW , Australia ; School of Medical Sciences, University of New South Wales , Sydney, NSW , Australia
| | - John R Hodges
- Neurosciences Research Australia (NeuRA) , Randwick, NSW , Australia
| | - Michael Hornberger
- Neurosciences Research Australia (NeuRA) , Randwick, NSW , Australia ; Department of Clinical Neurosciences, University of Cambridge , Cambridge , UK ; School of Medical Sciences, University of New South Wales , Sydney, NSW , Australia
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Influence of controlled encoding and retrieval facilitation on memory performance in patients with different profiles of mild cognitive impairment. J Neurol 2015; 262:938-48. [DOI: 10.1007/s00415-015-7662-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2014] [Revised: 01/28/2015] [Accepted: 01/30/2015] [Indexed: 11/26/2022]
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Allemang-Grand R, Scholz J, Ellegood J, Cahill L, Laliberté C, Fraser P, Josselyn S, Sled J, Lerch J. Altered brain development in an early-onset murine model of Alzheimer's disease. Neurobiol Aging 2015; 36:638-47. [DOI: 10.1016/j.neurobiolaging.2014.08.032] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2014] [Revised: 08/25/2014] [Accepted: 08/28/2014] [Indexed: 01/19/2023]
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