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Na HK, Shin JH, Kim SW, Seo S, Kim WR, Kang JM, Lee SY, Cho J, Byun J, Okamura N, Seong JK, Noh Y. Diverging Relationships among Amyloid, Tau, and Brain Atrophy in Early-Onset and Late-Onset Alzheimer's Disease. Yonsei Med J 2024; 65:434-447. [PMID: 39048319 PMCID: PMC11284308 DOI: 10.3349/ymj.2023.0308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 01/20/2024] [Accepted: 01/23/2024] [Indexed: 07/27/2024] Open
Abstract
PURPOSE Alzheimer's disease (AD) dementia may not be a single disease entity. Early-onset AD (EOAD) and late-onset AD (LOAD) have been united under the same eponym of AD until now, but disentangling the heterogeneity according to the age of sonset has been a major tenet in the field of AD research. MATERIALS AND METHODS Ninety-nine patients with AD (EOAD, n=54; LOAD, n=45) and 66 cognitively normal controls completed both [18F]THK5351 and [18F]flutemetamol (FLUTE) positron emission tomography scans along with structural magnetic resonance imaging and detailed neuropsychological tests. RESULTS EOAD patients had higher THK retention in the precuneus, parietal, and frontal lobe, while LOAD patients had higher THK retention in the medial temporal lobe. Intravoxel correlation analyses revealed that EOAD presented narrower territory of local FLUTE-THK correlation, while LOAD presented broader territory of correlation extending to overall parieto-occipito-temporal regions. EOAD patients had broader brain areas which showed significant negative correlations between cortical thickness and THK retention, whereas in LOAD, only limited brain areas showed significant correlation with THK retention. In EOAD, most of the cognitive test results were correlated with THK retention. However, a few cognitive test results were correlated with THK retention in LOAD. CONCLUSION LOAD seemed to show gradual increase in tau and amyloid, and those two pathologies have association to each other. On the other hand, in EOAD, tau and amyloid may develop more abruptly and independently. These findings suggest LOAD and EOAD may have different courses of pathomechanism.
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Affiliation(s)
- Han Kyu Na
- Department of Neurology, Yonsei University College of Medicine, Seoul, Korea
| | - Jeong-Hyeon Shin
- Bio Medical Research Center, Bio Medical & Health Division, Korea Testing Laboratory, Daegu, Korea
| | - Sung-Woo Kim
- School of Biomedical Engineering, Korea University, Seoul, Korea
| | - Seongho Seo
- Neuroscience Research Institute, Gachon University, Incheon, Korea
- Department of Electronic Engineering, Pai Chai University, Daejeon, Korea
| | - Woo-Ram Kim
- Neuroscience Research Institute, Gachon University, Incheon, Korea
| | - Jae Myeong Kang
- Department of Psychiatry, Gachon University Gil Medical Center, Incheon, Korea
| | - Sang-Yoon Lee
- Department of Neuroscience, College of Medicine, Gachon University, Incheon, Korea
| | - Jaelim Cho
- Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, Korea
| | - Justin Byun
- Department of Rehabilitation Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Nobuyuki Okamura
- Division of Pharmacology, Faculty of Medicine, Tohoku Medical and Pharmaceutical University, Sendai, Japan
| | - Joon-Kyung Seong
- School of Biomedical Engineering, Korea University, Seoul, Korea
- Department of Artificial Intelligence, Korea University, Seoul, Korea.
| | - Young Noh
- Neuroscience Research Institute, Gachon University, Incheon, Korea
- Department of Neurology, Gil Medical Center, Gachon University College of Medicine, Incheon, Korea.
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Sheng J, Xin Y, Zhang Q, Yang Z, Wang L, Zhang Q, Wang B. Novel Alzheimer's disease subtypes based on functional brain connectivity in human connectome project. Sci Rep 2024; 14:14821. [PMID: 38937574 PMCID: PMC11211325 DOI: 10.1038/s41598-024-65846-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Accepted: 06/25/2024] [Indexed: 06/29/2024] Open
Abstract
The pathogenesis of Alzheimer's disease (AD) remains unclear, but revealing individual differences in functional connectivity (FC) may provide insights and improve diagnostic precision. A hierarchical clustering-based autoencoder with functional connectivity was proposed to categorize 82 AD patients from the Alzheimer's Disease Neuroimaging Initiative. Compared to directly performing clustering, using an autoencoder to reduce the dimensionality of the matrix can effectively eliminate noise and redundant information in the data, extract key features, and optimize clustering performance. Subsequently, subtype differences in clinical and graph theoretical metrics were assessed. Results indicate a significant inter-subject heterogeneity in the degree of FC disruption among AD patients. We have identified two neurophysiological subtypes: subtype I exhibits widespread functional impairment across the entire brain, while subtype II shows mild impairment in the Limbic System region. What is worth noting is that we also observed significant differences between subtypes in terms of neurocognitive assessment scores associations with network functionality, and graph theory metrics. Our method can accurately identify different functional disruptions in subtypes of AD, facilitating personalized treatment and early diagnosis, ultimately improving patient outcomes.
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Affiliation(s)
- Jinhua Sheng
- School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, 310018, China.
- Key Laboratory of Intelligent Image Analysis for Sensory and Cognitive Health, Ministry of Industry and Information Technology of China, Hangzhou, 310018, China.
| | - Yu Xin
- School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, 310018, China
- Key Laboratory of Intelligent Image Analysis for Sensory and Cognitive Health, Ministry of Industry and Information Technology of China, Hangzhou, 310018, China
| | - Qiao Zhang
- Beijing Hospital, Beijing, 100730, China
- National Center of Gerontology, Beijing, 100730, China
- Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Ze Yang
- School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, 310018, China
- Key Laboratory of Intelligent Image Analysis for Sensory and Cognitive Health, Ministry of Industry and Information Technology of China, Hangzhou, 310018, China
| | - Luyun Wang
- School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, 310018, China
- Key Laboratory of Intelligent Image Analysis for Sensory and Cognitive Health, Ministry of Industry and Information Technology of China, Hangzhou, 310018, China
| | - Qian Zhang
- School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, 310018, China
- Key Laboratory of Intelligent Image Analysis for Sensory and Cognitive Health, Ministry of Industry and Information Technology of China, Hangzhou, 310018, China
| | - Binbing Wang
- School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, 310018, China
- Key Laboratory of Intelligent Image Analysis for Sensory and Cognitive Health, Ministry of Industry and Information Technology of China, Hangzhou, 310018, China
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Diamond BR, Sridhar J, Maier J, Martersteck AC, Rogalski EJ. SuperAging functional connectomics from resting-state functional MRI. Brain Commun 2024; 6:fcae205. [PMID: 38978723 PMCID: PMC11228547 DOI: 10.1093/braincomms/fcae205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Revised: 04/12/2024] [Accepted: 06/17/2024] [Indexed: 07/10/2024] Open
Abstract
Understanding the relationship between functional connectivity (FC) of higher-order neurocognitive networks and age-related cognitive decline is a complex and evolving field of research. Decreases in FC have been associated with cognitive decline in persons with Alzheimer's disease and related dementias (ADRD). However, the contributions of FC have been less straightforward in typical cognitive aging. Some investigations suggest relatively robust FC within neurocognitive networks differentiates unusually successful cognitive aging from average aging, while others do not. Methodologic limitations in data processing and varying definitions of 'successful aging' may have contributed to the inconsistent results to date. The current study seeks to address previous limitations by optimized MRI methods to examine FC in the well-established SuperAging phenotype, defined by age and cognitive performance as individuals 80 and older with episodic memory performance equal to or better than 50-to-60-year-olds. Within- and between-network FC of large-scale neurocognitive networks were compared between 24 SuperAgers and 16 cognitively average older-aged control (OACs) with stable cognitive profiles using resting-state functional MRI (rs-fMRI) from a single visit. Group classification was determined based on measures of episodic memory, executive functioning, verbal fluency and picture naming. Inclusion criteria required stable cognitive status across two visits. First, we investigated the FC within and between seven resting-state networks from a common atlas parcellation. A separate index of network segregation was also compared between groups. Second, we investigated the FC between six subcomponents of the default mode network (DMN), the neurocognitive network commonly associated with memory performance and disrupted in persons with ADRD. For each analysis, FCs were compared across groups using two-sample independent t-tests and corrected for multiple comparisons. There were no significant between-group differences in demographic characteristics including age, sex and education. At the group-level, within-network FC, between-network FC, and segregation measurements of seven large-scale networks, including subcomponents of the DMN, were not a primary differentiator between cognitively average aging and SuperAging phenotypes. Thus, FC within or between large-scale networks does not appear to be a primary driver of the exceptional memory performance observed in SuperAgers. These results have relevance for differentiating the role of FC changes associated with cognitive aging from those associated with ADRD.
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Affiliation(s)
- Bram R Diamond
- Mesulam Center for Cognitive Neurology and Alzheimer's Disease, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
- Healthy Aging & Alzheimer's Research Care (HAARC) Center, Department of Neurology, The University of Chicago, Chicago, IL 60637, USA
| | - Jaiashre Sridhar
- Mesulam Center for Cognitive Neurology and Alzheimer's Disease, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Jessica Maier
- Department of Psychology, Florida State University, 1107 W Call St, Tallahassee, FL 32304, USA
| | - Adam C Martersteck
- Healthy Aging & Alzheimer's Research Care (HAARC) Center, Department of Neurology, The University of Chicago, Chicago, IL 60637, USA
| | - Emily J Rogalski
- Healthy Aging & Alzheimer's Research Care (HAARC) Center, Department of Neurology, The University of Chicago, Chicago, IL 60637, USA
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L'esperance OJ, McGhee J, Davidson G, Niraula S, Smith AS, Sosunov A, Yan SS, Subramanian J. Functional connectivity favors aberrant visual network c-Fos expression accompanied by cortical synapse loss in a mouse model of Alzheimer's disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.01.05.522900. [PMID: 36712054 PMCID: PMC9881957 DOI: 10.1101/2023.01.05.522900] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
While Alzheimer's disease (AD) has been extensively studied with a focus on cognitive networks, sensory network dysfunction has received comparatively less attention despite compelling evidence of its significance in both Alzheimer's disease patients and mouse models. We recently found that neurons in the primary visual cortex of an AD mouse model expressing human amyloid protein precursor with the Swedish and Indiana mutations (hAPP mutations) exhibit aberrant c-Fos expression and altered synaptic structures at a pre-amyloid plaque stage. However, it is unclear whether aberrant c-Fos expression and synaptic pathology vary across the broader visual network and to what extent c-Fos abnormality in the cortex is inherited through functional connectivity. Using both sexes of 4-6-month AD model mice with hAPP mutations (J20[PDGF-APPSw, Ind]), we found that cortical regions of the visual network show aberrant c-Fos expression and impaired experience-dependent modulation while subcortical regions do not. Interestingly, the average network-wide functional connectivity strength of a brain region in wild type (WT) mice significantly predicts its aberrant c-Fos expression, which in turn correlates with impaired experience-dependent modulation in the AD model. Using in vivo two-photon and ex vivo imaging of presynaptic termini, we observed a subtle yet selective weakening of excitatory cortical synapses in the visual cortex. Intriguingly, the change in the size distribution of cortical boutons in the AD model is downscaled relative to those in WT mice, suggesting that synaptic weakening may reflect an adaptation to aberrant activity. Our observations suggest that cellular and synaptic abnormalities in the AD model represent a maladaptive transformation of the baseline physiological state seen in WT conditions rather than entirely novel and unrelated manifestations.
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Seoane S, van den Heuvel M, Acebes Á, Janssen N. The subcortical default mode network and Alzheimer's disease: a systematic review and meta-analysis. Brain Commun 2024; 6:fcae128. [PMID: 38665961 PMCID: PMC11043657 DOI: 10.1093/braincomms/fcae128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 02/28/2024] [Accepted: 04/09/2024] [Indexed: 04/28/2024] Open
Abstract
The default mode network is a central cortical brain network suggested to play a major role in several disorders and to be particularly vulnerable to the neuropathological hallmarks of Alzheimer's disease. Subcortical involvement in the default mode network and its alteration in Alzheimer's disease remains largely unknown. We performed a systematic review, meta-analysis and empirical validation of the subcortical default mode network in healthy adults, combined with a systematic review, meta-analysis and network analysis of the involvement of subcortical default mode areas in Alzheimer's disease. Our results show that, besides the well-known cortical default mode network brain regions, the default mode network consistently includes subcortical regions, namely the thalamus, lobule and vermis IX and right Crus I/II of the cerebellum and the amygdala. Network analysis also suggests the involvement of the caudate nucleus. In Alzheimer's disease, we observed a left-lateralized cluster of decrease in functional connectivity which covered the medial temporal lobe and amygdala and showed overlap with the default mode network in a portion covering parts of the left anterior hippocampus and left amygdala. We also found an increase in functional connectivity in the right anterior insula. These results confirm the consistency of subcortical contributions to the default mode network in healthy adults and highlight the relevance of the subcortical default mode network alteration in Alzheimer's disease.
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Affiliation(s)
- Sara Seoane
- Department of Complex Traits Genetics, Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam 1081 HV, The Netherlands
- Institute of Biomedical Technologies (ITB), University of La Laguna, Tenerife 38200, Spain
- Instituto Universitario de Neurociencia (IUNE), University of La Laguna, Tenerife 38200, Spain
| | - Martijn van den Heuvel
- Department of Complex Traits Genetics, Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam 1081 HV, The Netherlands
- Department of Child and Adolescent Psychiatry and Psychology, Section Complex Trait Genetics, Amsterdam Neuroscience, Vrije Universiteit Medical Center, Amsterdam UMC, Amsterdam 1081 HV, The Netherlands
| | - Ángel Acebes
- Institute of Biomedical Technologies (ITB), University of La Laguna, Tenerife 38200, Spain
- Department of Basic Medical Sciences, University of La Laguna, Tenerife 38200, Spain
| | - Niels Janssen
- Institute of Biomedical Technologies (ITB), University of La Laguna, Tenerife 38200, Spain
- Instituto Universitario de Neurociencia (IUNE), University of La Laguna, Tenerife 38200, Spain
- Department of Cognitive, Social and Organizational Psychology, University of La Laguna, Tenerife 38200, Spain
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Wang Y, Li Q, Yao L, He N, Tang Y, Chen L, Long F, Chen Y, Kemp GJ, Lui S, Li F. Shared and differing functional connectivity abnormalities of the default mode network in mild cognitive impairment and Alzheimer's disease. Cereb Cortex 2024; 34:bhae094. [PMID: 38521993 DOI: 10.1093/cercor/bhae094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 02/19/2024] [Accepted: 02/21/2024] [Indexed: 03/25/2024] Open
Abstract
Alzheimer's disease (AD) and mild cognitive impairment (MCI) both show abnormal resting-state functional connectivity (rsFC) of default mode network (DMN), but it is unclear to what extent these abnormalities are shared. Therefore, we performed a comprehensive meta-analysis, including 31 MCI studies and 20 AD studies. MCI patients, compared to controls, showed decreased within-DMN rsFC in bilateral medial prefrontal cortex/anterior cingulate cortex (mPFC/ACC), precuneus/posterior cingulate cortex (PCC), right temporal lobes, and left angular gyrus and increased rsFC between DMN and left inferior temporal gyrus. AD patients, compared to controls, showed decreased rsFC within DMN in bilateral mPFC/ACC and precuneus/PCC and between DMN and left inferior occipital gyrus and increased rsFC between DMN and right dorsolateral prefrontal cortex. Conjunction analysis showed shared decreased rsFC in mPFC/ACC and precuneus/PCC. Compared to MCI, AD had decreased rsFC in left precuneus/PCC and between DMN and left inferior occipital gyrus and increased rsFC in right temporal lobes. MCI and AD share a decreased within-DMN rsFC likely underpinning episodic memory deficits and neuropsychiatric symptoms, but differ in DMN rsFC alterations likely related to impairments in other cognitive domains such as language, vision, and execution. This may throw light on neuropathological mechanisms in these two stages of dementia.
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Affiliation(s)
- Yaxuan Wang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular lmaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, No. 37 Guo Xue Alley, Wuhou District, Chengdu 610041, Sichuan Province, P.R. China
| | - Qian Li
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular lmaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, No. 37 Guo Xue Alley, Wuhou District, Chengdu 610041, Sichuan Province, P.R. China
| | - Li Yao
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular lmaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, No. 37 Guo Xue Alley, Wuhou District, Chengdu 610041, Sichuan Province, P.R. China
| | - Ning He
- Department of Psychiatry, West China Hospital of Sichuan University, No. 37 Guo Xue Alley, Wuhou District, Chengdu 610041, Sichuan, P.R. China
| | - Yingying Tang
- Department of Neurology, West China Hospital of Sichuan University, No. 37 Guo Xue Alley, Wuhou District, Chengdu 610041, Sichuan, P.R. China
| | - Lizhou Chen
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular lmaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, No. 37 Guo Xue Alley, Wuhou District, Chengdu 610041, Sichuan Province, P.R. China
| | - Fenghua Long
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular lmaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, No. 37 Guo Xue Alley, Wuhou District, Chengdu 610041, Sichuan Province, P.R. China
| | - Yufei Chen
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular lmaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, No. 37 Guo Xue Alley, Wuhou District, Chengdu 610041, Sichuan Province, P.R. China
| | - Graham J Kemp
- Institute of Life Course and Medical Sciences, University of Liverpool, 6 West Derby Street, Liverpool L7 8TX, United Kingdom
| | - Su Lui
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular lmaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, No. 37 Guo Xue Alley, Wuhou District, Chengdu 610041, Sichuan Province, P.R. China
| | - Fei Li
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular lmaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, No. 37 Guo Xue Alley, Wuhou District, Chengdu 610041, Sichuan Province, P.R. China
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Herrejon IA, Jackson TB, Hicks TH, Bernard JA. Functional Connectivity Differences in Distinct Dentato-Cortical Networks in Alzheimer's Disease and Mild Cognitive Impairment. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.02.578249. [PMID: 38352603 PMCID: PMC10862898 DOI: 10.1101/2024.02.02.578249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
Recent research has implicated the cerebellum in Alzheimer's disease (AD), and cerebrocerebellar network connectivity is emerging as a possible contributor to symptom severity. The cerebellar dentate nucleus (DN) has parallel motor and non-motor sub-regions that project to motor and frontal regions of the cerebral cortex, respectively. These distinct dentato-cortical networks have been delineated in the non-human primate and human brain. Importantly, cerebellar regions prone to atrophy in AD are functionally connected to atrophied regions of the cerebral cortex, suggesting that dysfunction perhaps occurs at a network level. Investigating functional connectivity (FC) alterations of the DN is a crucial step in understanding the cerebellum in AD and in mild cognitive impairment (MCI). Inclusion of this latter group stands to provide insights into cerebellar contributions prior to diagnosis of AD. The present study investigated FC differences in dorsal (dDN) and ventral (vDN) DN networks in MCI and AD relative to cognitively normal participants (CN) and relationships between FC and behavior. Our results showed patterns indicating both higher and lower functional connectivity in both dDN and vDN in AD compared to CN. However, connectivity in the AD group was lower when compared to MCI. We argue that these findings suggest that the patterns of higher FC in AD may act as a compensatory mechanism. Additionally, we found associations between the individual networks and behavior. There were significant interactions between dDN connectivity and motor symptoms. However, both DN seeds were associated with cognitive task performance. Together, these results indicate that cerebellar DN networks are impacted in AD, and this may impact behavior. In concert with the growing body of literature implicating the cerebellum in AD, our work further underscores the importance of investigations of this region. We speculate that much like in psychiatric diseases such as schizophrenia, cerebellar dysfunction results in negative impacts on thought and the organization therein. Further, this is consistent with recent arguments that the cerebellum provides crucial scaffolding for cognitive function in aging. Together, our findings stand to inform future clinical work in the diagnosis and understanding of this disease.
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Affiliation(s)
- Ivan A. Herrejon
- Department of Psychological and Brain Sciences Texas A&M University
| | - T. Bryan Jackson
- Department of Psychological and Brain Sciences Texas A&M University
- Vanderbilt Memory and Alzheimer’s Center Vanderbilt University Medical Center
| | - Tracey H. Hicks
- Department of Psychological and Brain Sciences Texas A&M University
| | - Jessica A. Bernard
- Department of Psychological and Brain Sciences Texas A&M University
- Texas A&M Institute for Neuroscience Texas A&M University
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Biswas R, Sripada S. Causal functional connectivity in Alzheimer's disease computed from time series fMRI data. Front Comput Neurosci 2023; 17:1251301. [PMID: 38169714 PMCID: PMC10758424 DOI: 10.3389/fncom.2023.1251301] [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: 07/01/2023] [Accepted: 11/28/2023] [Indexed: 01/05/2024] Open
Abstract
Functional connectivity between brain regions is known to be altered in Alzheimer's disease and promises to be a biomarker for early diagnosis. Several approaches for functional connectivity obtain an un-directed network representing stochastic associations (correlations) between brain regions. However, association does not necessarily imply causation. In contrast, Causal Functional Connectivity (CFC) is more informative, providing a directed network representing causal relationships between brain regions. In this paper, we obtained the causal functional connectome for the whole brain from resting-state functional magnetic resonance imaging (rs-fMRI) recordings of subjects from three clinical groups: cognitively normal, mild cognitive impairment, and Alzheimer's disease. We applied the recently developed Time-aware PC (TPC) algorithm to infer the causal functional connectome for the whole brain. TPC supports model-free estimation of whole brain CFC based on directed graphical modeling in a time series setting. We compared the CFC outcome of TPC with that of other related approaches in the literature. Then, we used the CFC outcomes of TPC and performed an exploratory analysis of the difference in strengths of CFC edges between Alzheimer's and cognitively normal groups, based on edge-wise p-values obtained by Welch's t-test. The brain regions thus identified are found to be in agreement with literature on brain regions impacted by Alzheimer's disease, published by researchers from clinical/medical institutions.
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Affiliation(s)
- Rahul Biswas
- Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, United States
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Touroutoglou A, Katsumi Y, Brickhouse M, Zaitsev A, Eckbo R, Aisen P, Beckett L, Dage JL, Eloyan A, Foroud T, Ghetti B, Griffin P, Hammers D, Jack CR, Kramer JH, Iaccarino L, Joie RL, Mundada NS, Koeppe R, Kukull WA, Murray ME, Nudelman K, Polsinelli AJ, Rumbaugh M, Soleimani-Meigooni DN, Toga A, Vemuri P, Atri A, Day GS, Duara R, Graff-Radford NR, Honig LS, Jones DT, Masdeu JC, Mendez MF, Musiek E, Onyike CU, Riddle M, Rogalski E, Salloway S, Sha S, Turner RS, Wingo TS, Wolk DA, Womack K, Carrillo MC, Rabinovici GD, Apostolova LG, Dickerson BC. The Sporadic Early-onset Alzheimer's Disease Signature Of Atrophy: Preliminary Findings From The Longitudinal Early-onset Alzheimer's Disease Study (LEADS) Cohort. Alzheimers Dement 2023; 19 Suppl 9:S74-S88. [PMID: 37850549 PMCID: PMC10829523 DOI: 10.1002/alz.13466] [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: 03/23/2023] [Revised: 07/13/2023] [Accepted: 07/18/2023] [Indexed: 10/19/2023]
Abstract
INTRODUCTION Magnetic resonance imaging (MRI) research has advanced our understanding of neurodegeneration in sporadic early-onset Alzheimer's disease (EOAD) but studies include small samples, mostly amnestic EOAD, and have not focused on developing an MRI biomarker. METHODS We analyzed MRI scans to define the sporadic EOAD-signature atrophy in a small sample (n = 25) of Massachusetts General Hospital (MGH) EOAD patients, investigated its reproducibility in the large longitudinal early-onset Alzheimer's disease study (LEADS) sample (n = 211), and investigated the relationship of the magnitude of atrophy with cognitive impairment. RESULTS The EOAD-signature atrophy was replicated across the two cohorts, with prominent atrophy in the caudal lateral temporal cortex, inferior parietal lobule, and posterior cingulate and precuneus cortices, and with relative sparing of the medial temporal lobe. The magnitude of EOAD-signature atrophy was associated with the severity of cognitive impairment. DISCUSSION The EOAD-signature atrophy is a reliable and clinically valid biomarker of AD-related neurodegeneration that could be used in clinical trials for EOAD. HIGHLIGHTS We developed an early-onset Alzheimer's disease (EOAD)-signature of atrophy based on magnetic resonance imaging (MRI) scans. EOAD signature was robustly reproducible across two independent patient cohorts. EOAD signature included prominent atrophy in parietal and posterior temporal cortex. The EOAD-signature atrophy was associated with the severity of cognitive impairment. EOAD signature is a reliable and clinically valid biomarker of neurodegeneration.
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Affiliation(s)
- Alexandra Touroutoglou
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Yuta Katsumi
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Michael Brickhouse
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Alexander Zaitsev
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Ryan Eckbo
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Paul Aisen
- Alzheimer's Therapeutic Research Institute, University of Southern California, San Diego, California, USA
| | - Laurel Beckett
- Department of Public Health Sciences, University of California - Davis, Davis, California, USA
| | - Jeffrey L Dage
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Ani Eloyan
- Department of Biostatistics, Center for Statistical Sciences, Brown University, Providence, Rhode Island, USA
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Bernardino Ghetti
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Percy Griffin
- Medical & Scientific Relations Division, Alzheimer's Association, Chicago, Illinois, USA
| | - Dustin Hammers
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Joel H Kramer
- Department of Neurology, University of California - San Francisco, San Francisco, California, USA
| | - Leonardo Iaccarino
- Department of Neurology, University of California - San Francisco, San Francisco, California, USA
| | - Renaud La Joie
- Department of Neurology, University of California - San Francisco, San Francisco, California, USA
| | - Nidhi S Mundada
- Department of Neurology, University of California - San Francisco, San Francisco, California, USA
| | - Robert Koeppe
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Walter A Kukull
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Melissa E Murray
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, USA
| | - Kelly Nudelman
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Angelina J Polsinelli
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Malia Rumbaugh
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | | | - Arthur Toga
- Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Los Angeles, California, USA
| | | | - Alireza Atri
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | - Gregory S Day
- Department of Neurology, Mayo Clinic in Florida, Jacksonville, Florida, USA
| | - Ranjan Duara
- Wien Center for Alzheimer's Disease and Memory Disorders, Mount Sinai Medical Center, Miami, Florida, USA
| | | | - Lawrence S Honig
- Taub Institute and Department of Neurology, Columbia University Irving Medical Center, New York, New York, USA
| | - David T Jones
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Joseph C Masdeu
- Nantz National Alzheimer Center, Houston Methodist and Weill Cornell Medicine, Houston, Texas, USA
| | - Mario F Mendez
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Erik Musiek
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Chiadi U Onyike
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Meghan Riddle
- Department of Neurology, Alpert Medical School, Brown University, Providence, Rhode Island, USA
| | - Emily Rogalski
- Department of Psychiatry and Behavioral Sciences, Mesulam Center for Cognitive Neurology and Alzheimer's Disease, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Stephen Salloway
- Department of Neurology, Alpert Medical School, Brown University, Providence, Rhode Island, USA
| | - Sharon Sha
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, California, USA
| | - R Scott Turner
- Department of Neurology, Georgetown University, Washington, D.C., USA
| | - Thomas S Wingo
- Department of Neurology and Human Genetics, Emory University School of Medicine, Atlanta, Georgia, USA
| | - David A Wolk
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Kyle Womack
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Maria C Carrillo
- Medical & Scientific Relations Division, Alzheimer's Association, Chicago, Illinois, USA
| | - Gil D Rabinovici
- Department of Neurology, University of California - San Francisco, San Francisco, California, USA
| | - Liana G Apostolova
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine Indianapolis, Indianapolis, Indiana, USA
| | - Bradford C Dickerson
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
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10
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Seath P, Macedo-Orrego LE, Velayudhan L. Clinical characteristics of early-onset versus late-onset Alzheimer's disease: a systematic review and meta-analysis. Int Psychogeriatr 2023:1-17. [PMID: 37431284 DOI: 10.1017/s1041610223000509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/12/2023]
Abstract
OBJECTIVES A number of studies have compared Alzheimer's disease (AD), the commonest form of dementia, based on their age of onset, i.e. before the age of 65 years (early-onset AD, EO-AD) to those developing after 65 years of age (late-onset AD, LO-AD), but the differences are not clear. We performed a systematic review and meta-analysis to compare clinical characteristics between EO-AD and LO-AD. DESIGN, MEASUREMENTS, AND PARTICIPANTS Medline, Embase, PsycINFO, and CINAHL databases were systematically searched for studies comparing time to diagnosis, cognitive scores, annual cognitive decline, activities of daily living (ADLs), neuropsychiatric symptoms (NPS), quality of life (QoL), and survival time for EO-AD and LO-AD patients. RESULTS Forty-two studies were included (EO-AD participants n = 5,544; LO-AD participants n = 16,042). An inverse variance method with random effects models was used to calculate overall effect estimates for each outcome. People with EO-AD had significantly poorer baseline cognitive performance and faster cognitive decline but longer survival times than people with LO-AD. There was no evidence that EO-AD patients differ from people with LO-AD in terms of symptom onset to diagnosis time, ADLs, and NPS. There were insufficient data to estimate overall effects of differences in QoL in EO-AD compared to LO-AD. CONCLUSIONS Our findings suggest that EO-AD differs from LO-AD in baseline cognition, cognitive decline, and survival time but otherwise has similar clinical characteristics to LO-AD. Larger studies using standardized questionnaires focusing on the clinical presentations are needed to better understand the impact of age of onset in AD.
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Affiliation(s)
- Paige Seath
- Academic Psychiatry Division, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Luis Enrique Macedo-Orrego
- Departamento de Psiquiatría, Universidad Nacional Mayor de San Marcos, Lima, Peru
- Departamento de atencion especializada de adultos mayores, Instituto Nacional de Salud Mental, Lima, Peru
| | - Latha Velayudhan
- Academic Psychiatry Division, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- South London and Maudsley NHS Foundation Trust, London, UK
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11
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Gunawardena R, Sarrigiannis PG, Blackburn DJ, He F. Kernel-based Nonlinear Manifold Learning for EEG-based Functional Connectivity Analysis and Channel Selection with Application to Alzheimer's Disease. Neuroscience 2023:S0306-4522(23)00253-1. [PMID: 37301505 DOI: 10.1016/j.neuroscience.2023.05.033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 05/15/2023] [Accepted: 05/29/2023] [Indexed: 06/12/2023]
Abstract
Dynamical, causal, and cross-frequency coupling analysis using the electroencephalogram (EEG) has gained significant attention for diagnosing and characterizing neurological disorders. Selecting important EEG channels is crucial for reducing computational complexity in implementing these methods and improving classification accuracy. In neuroscience, measures of (dis)similarity between EEG channels are often used as functional connectivity (FC) features, and important channels are selected via feature selection. Developing a generic measure of (dis)similarity is important for FC analysis and channel selection. In this study, learning of (dis)similarity information within the EEG is achieved using kernel-based nonlinear manifold learning. The focus is on FC changes and, thereby, EEG channel selection. Isomap and Gaussian Process Latent Variable Model (Isomap-GPLVM) are employed for this purpose. The resulting kernel (dis)similarity matrix is used as a novel measure of linear and nonlinear FC between EEG channels. The analysis of EEG from healthy controls (HC) and patients with mild to moderate Alzheimer's disease (AD) are presented as a case study. Classification results are compared with other commonly used FC measures. Our analysis shows significant differences in FC between bipolar channels of the occipital region and other regions (i.e. parietal, centro-parietal, and fronto-central) between AD and HC groups. Furthermore, our results indicate that FC changes between channels along the fronto-parietal region and the rest of the EEG are important in diagnosing AD. Our results and its relation to functional networks are consistent with those obtained from previous studies using fMRI, resting-state fMRI and EEG.
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Affiliation(s)
- Rajintha Gunawardena
- Centre for Computational Science and Mathematical Modelling, Coventry University, Coventry, CV1 5FB, UK
| | | | - Daniel J Blackburn
- Department of Neuroscience, The University of Sheffield, Sheffield, S10 2HQ, UK
| | - Fei He
- Centre for Computational Science and Mathematical Modelling, Coventry University, Coventry, CV1 5FB, UK.
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12
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Is non-invasive brain stimulation effective for cognitive enhancement in Alzheimer's disease? An updated meta-analysis. Clin Neurophysiol 2022; 144:23-40. [PMID: 36215904 DOI: 10.1016/j.clinph.2022.09.010] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 08/30/2022] [Accepted: 09/18/2022] [Indexed: 11/23/2022]
Abstract
OBJECTIVE Alzheimer's disease dementia (AD) and its preclinical stage, mild cognitive impairment (MCI), are critical issues confronting the aging society. Non-invasive brain stimulation (NIBS) techniques have the potential to be effective tools for enhancing cognitive functioning. The main objective of our meta-analysis was to quantify and update the status of the efficacy of repetitive Transcranial Magnetic Stimulation (rTMS) and Transcranial Direct Current Stimulation (tDCS) when applied in AD and MCI. METHODS The systematic literature search was conducted in PubMed and Web of Science according to PRISMA statement. RESULTS Pooled effect sizes (Hedges' g) from 32 studies were analyzed using random effect models. We found both, rTMS and tDCS to have significant immediate cognition-enhancing effect in AD with rTMS inducing also beneficial long-term effects. We found no evidence for synergistic effect of cognitive training with NIBS. CONCLUSIONS In AD a clinical recommendation can be made for NEURO-ADTM system and for high-frequency rTMS over the left dorsolateral prefrontal cortex (DLPFC) as probably effective protocols (B-level of evidence) and for anodal tDCS over the left DLPFC as a possibly effective. SIGNIFICANCE According to scientific literature, NIBS may be an effective method for improving cognition in AD and possibly in MCI.
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13
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Durieux J, Rombouts SARB, de Vos F, Koini M, Wilderjans TF. Clusterwise Independent Component Analysis (C-ICA): Using fMRI resting state networks to cluster subjects and find neurofunctional subtypes. J Neurosci Methods 2022; 382:109718. [PMID: 36209940 DOI: 10.1016/j.jneumeth.2022.109718] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 08/18/2022] [Accepted: 09/29/2022] [Indexed: 11/05/2022]
Abstract
BACKGROUND FMRI resting state networks (RSNs) are used to characterize brain disorders. They also show extensive heterogeneity across patients. Identifying systematic differences between RSNs in patients, i.e. discovering neurofunctional subtypes, may further increase our understanding of disease heterogeneity. Currently, no methodology is available to estimate neurofunctional subtypes and their associated RSNs simultaneously. NEW METHOD We present an unsupervised learning method for fMRI data, called Clusterwise Independent Component Analysis (C-ICA). This enables the clustering of patients into neurofunctional subtypes based on differences in shared ICA-derived RSNs. The parameters are estimated simultaneously, which leads to an improved estimation of subtypes and their associated RSNs. RESULTS In five simulation studies, the C-ICA model is successfully validated using both artificially and realistically simulated data (N = 30-40). The successful performance of the C-ICA model is also illustrated on an empirical data set consisting of Alzheimer's disease patients and elderly control subjects (N = 250). C-ICA is able to uncover a meaningful clustering that partially matches (balanced accuracy = .72) the diagnostic labels and identifies differences in RSNs between the Alzheimer and control cluster. COMPARISON WITH OTHER METHODS Both in the simulation study and the empirical application, C-ICA yields better results compared to competing clustering methods (i.e., a two step clustering procedure based on single subject ICA's and a Group ICA plus dual regression variant thereof) that do not simultaneously estimate a clustering and associated RSNs. Indeed, the overall mean adjusted Rand Index, a measure for cluster recovery, equals 0.65 for C-ICA and ranges from 0.27 to 0.46 for competing methods. CONCLUSIONS The successful performance of C-ICA indicates that it is a promising method to extract neurofunctional subtypes from multi-subject resting state-fMRI data. This method can be applied on fMRI scans of patient groups to study (neurofunctional) subtypes, which may eventually further increase understanding of disease heterogeneity.
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Affiliation(s)
- Jeffrey Durieux
- Methodology and Statistics Unit, Institute of Psychology, Faculty of Social and Behavioural Sciences, Leiden University, Leiden, The Netherlands; Leiden Institute for Brain and Cognition (LIBC), Leiden, The Netherlands; Econometric Institute, Erasmus University Rotterdam, The Netherlands.
| | - Serge A R B Rombouts
- Methodology and Statistics Unit, Institute of Psychology, Faculty of Social and Behavioural Sciences, Leiden University, Leiden, The Netherlands; Leiden Institute for Brain and Cognition (LIBC), Leiden, The Netherlands; Department of Radiology, Leiden University Medical Center, The Netherlands
| | - Frank de Vos
- Methodology and Statistics Unit, Institute of Psychology, Faculty of Social and Behavioural Sciences, Leiden University, Leiden, The Netherlands; Leiden Institute for Brain and Cognition (LIBC), Leiden, The Netherlands; Department of Radiology, Leiden University Medical Center, The Netherlands
| | - Marisa Koini
- Department of Neurology, Medical University of Graz, Austria
| | - Tom F Wilderjans
- Methodology and Statistics Unit, Institute of Psychology, Faculty of Social and Behavioural Sciences, Leiden University, Leiden, The Netherlands; Leiden Institute for Brain and Cognition (LIBC), Leiden, The Netherlands; Research Group of Quantitative Psychology and Individual Differences, Faculty of Psychology and Educational Sciences, KU Leuven, Leuven, Belgium; Department of Clinical Psychology, Vrije Universiteit Amsterdam, Netherlands
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14
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Cheyuo C, Germann J, Yamamoto K, Vetkas A, Loh A, Sarica C, Milano V, Zemmar A, Flouty O, Harmsen IE, Hodaie M, Kalia SK, Tang-Wai D, Lozano AM. Connectomic neuromodulation for Alzheimer's disease: A systematic review and meta-analysis of invasive and non-invasive techniques. Transl Psychiatry 2022; 12:490. [PMID: 36411282 PMCID: PMC9678946 DOI: 10.1038/s41398-022-02246-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 10/24/2022] [Accepted: 10/28/2022] [Indexed: 11/23/2022] Open
Abstract
Deep brain stimulation (DBS) and non-invasive neuromodulation are currently being investigated for treating network dysfunction in Alzheimer's Disease (AD). However, due to heterogeneity in techniques and targets, the cognitive outcome and brain network connectivity remain unknown. We performed a systematic review, meta-analysis, and normative functional connectivity to determine the cognitive outcome and brain networks of DBS and non-invasive neuromodulation in AD. PubMed, Embase, and Web of Science were searched using three concepts: dementia, brain connectome, and brain stimulation, with filters for English, human studies, and publication dates 1980-2021. Additional records from clinicaltrials.gov were added. Inclusion criteria were AD study with DBS or non-invasive neuromodulation and a cognitive outcome. Exclusion criteria were less than 3-months follow-up, severe dementia, and focused ultrasound intervention. Bias was assessed using Centre for Evidence-Based Medicine levels of evidence. We performed meta-analysis, with subgroup analysis based on type and age at neuromodulation. To determine the patterns of neuromodulation-induced brain network activation, we performed normative functional connectivity using rsfMRI of 1000 healthy subjects. Six studies, with 242 AD patients, met inclusion criteria. On fixed-effect meta-analysis, non-invasive neuromodulation favored baseline, with effect size -0.40(95% [CI], -0.73, -0.06, p = 0.02), while that of DBS was 0.11(95% [CI] -0.34, 0.56, p = 0.63), in favor of DBS. In patients ≥65 years old, DBS improved cognitive outcome, 0.95(95% [CI] 0.31, 1.58, p = 0.004), whereas in patients <65 years old baseline was favored, -0.17(95% [CI] -0.93, 0.58, p = 0.65). Functional connectivity regions were in the default mode (DMN), salience (SN), central executive (CEN) networks, and Papez circuit. The subgenual cingulate and anterior limb of internal capsule (ALIC) showed connectivity to all targets of neuromodulation. This meta-analysis provides level II evidence of a difference in response of AD patients to DBS, based on age at intervention. Brain stimulation in AD may modulate DMN, SN, CEN, and Papez circuit, with the subgenual cingulate and ALIC as potential targets.
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Affiliation(s)
- Cletus Cheyuo
- grid.231844.80000 0004 0474 0428Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON Canada
| | - Jurgen Germann
- grid.231844.80000 0004 0474 0428Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON Canada ,grid.231844.80000 0004 0474 0428Krembil Research Institute, Toronto, ON Canada
| | - Kazuaki Yamamoto
- grid.231844.80000 0004 0474 0428Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON Canada ,Functional Neurosurgery Center, Shonan Fujisawa Tokushukai Hospital, Fujisawa, Kanagawa Japan
| | - Artur Vetkas
- grid.231844.80000 0004 0474 0428Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON Canada ,grid.412269.a0000 0001 0585 7044Neurology Clinic, Department of Neurosurgery, Tartu University Hospital, University of Tartu, Tartu, Estonia
| | - Aaron Loh
- grid.231844.80000 0004 0474 0428Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON Canada
| | - Can Sarica
- grid.231844.80000 0004 0474 0428Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON Canada
| | - Vanessa Milano
- grid.414997.60000 0004 0450 2040JFK Neuroscience Institute, Edison, NJ USA
| | - Ajmal Zemmar
- grid.266623.50000 0001 2113 1622Department of Neurosurgery, University of Louisville, School of Medicine, Louisville, KY USA
| | - Oliver Flouty
- grid.170693.a0000 0001 2353 285XDepartment of Neurosurgery, University of South Florida, College of Medicine, Tampa, FL USA
| | - Irene E. Harmsen
- grid.231844.80000 0004 0474 0428Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON Canada
| | - Mojgan Hodaie
- grid.231844.80000 0004 0474 0428Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON Canada ,grid.231844.80000 0004 0474 0428Krembil Research Institute, Toronto, ON Canada
| | - Suneil K. Kalia
- grid.231844.80000 0004 0474 0428Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON Canada ,grid.231844.80000 0004 0474 0428Krembil Research Institute, Toronto, ON Canada
| | - David Tang-Wai
- grid.17063.330000 0001 2157 2938Department of Neurology, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON Canada
| | - Andres M. Lozano
- grid.231844.80000 0004 0474 0428Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON Canada ,grid.231844.80000 0004 0474 0428Krembil Research Institute, Toronto, ON Canada
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15
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Hyperconnectivity matters in early-onset Alzheimer's disease: a resting-state EEG connectivity study. Neurophysiol Clin 2022; 52:459-471. [DOI: 10.1016/j.neucli.2022.10.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Revised: 10/17/2022] [Accepted: 10/21/2022] [Indexed: 11/11/2022] Open
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16
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Bolton CJ, Tam JW. Differential Involvement of the Locus Coeruleus in Early- and Late-Onset Alzheimer's Disease: A Potential Mechanism of Clinical Differences? J Geriatr Psychiatry Neurol 2022; 35:733-739. [PMID: 34496652 DOI: 10.1177/08919887211044755] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Sporadic early-onset Alzheimer's disease (sEOAD) is often associated with atypical clinical features, yet the cause of this heterogeneity remains unclear. This study investigated post-mortem atrophy of the locus coeruleus (LC) in sEOAD and late-onset Alzheimer's disease (LOAD). Levels of LC atrophy, as estimated by pathologist-rating of hypopigmentation, were compared between sEOAD (n = 115) and LOAD (n = 672) participants while controlling for other measures of pathological progression. Subsequent analyses compared low vs. high LC atrophy sEOAD subgroups on neuropsychological test performance. Results show nearly 4 times greater likelihood of higher LC atrophy in sEOAD as compared to LOAD (p < .005). sEOAD participants with greater LC atrophy displayed significantly worse performance on various baseline measures of attentional functioning (p < .05), despite similar global cognition (p = .25). These findings suggest the LC is an important potential driver of clinical and pathological heterogeneity in sEOAD.
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Affiliation(s)
- Corey J Bolton
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA.,Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Joyce W Tam
- Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago, IL, USA
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17
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Sirkis DW, Bonham LW, Johnson TP, La Joie R, Yokoyama JS. Dissecting the clinical heterogeneity of early-onset Alzheimer's disease. Mol Psychiatry 2022; 27:2674-2688. [PMID: 35393555 PMCID: PMC9156414 DOI: 10.1038/s41380-022-01531-9] [Citation(s) in RCA: 43] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 03/07/2022] [Accepted: 03/16/2022] [Indexed: 12/14/2022]
Abstract
Early-onset Alzheimer's disease (EOAD) is a rare but particularly devastating form of AD. Though notable for its high degree of clinical heterogeneity, EOAD is defined by the same neuropathological hallmarks underlying the more common, late-onset form of AD. In this review, we describe the various clinical syndromes associated with EOAD, including the typical amnestic phenotype as well as atypical variants affecting visuospatial, language, executive, behavioral, and motor functions. We go on to highlight advances in fluid biomarker research and describe how molecular, structural, and functional neuroimaging can be used not only to improve EOAD diagnostic acumen but also enhance our understanding of fundamental pathobiological changes occurring years (and even decades) before the onset of symptoms. In addition, we discuss genetic variation underlying EOAD, including pathogenic variants responsible for the well-known mendelian forms of EOAD as well as variants that may increase risk for the much more common forms of EOAD that are either considered to be sporadic or lack a clear autosomal-dominant inheritance pattern. Intriguingly, specific pathogenic variants in PRNP and MAPT-genes which are more commonly associated with other neurodegenerative diseases-may provide unexpectedly important insights into the formation of AD tau pathology. Genetic analysis of the atypical clinical syndromes associated with EOAD will continue to be challenging given their rarity, but integration of fluid biomarker data, multimodal imaging, and various 'omics techniques and their application to the study of large, multicenter cohorts will enable future discoveries of fundamental mechanisms underlying the development of EOAD and its varied clinical presentations.
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Affiliation(s)
- Daniel W Sirkis
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Luke W Bonham
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, 94158, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Taylor P Johnson
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Jennifer S Yokoyama
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, 94158, USA.
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, 94158, USA.
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18
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Blujus JK, Korthauer LE, Awe E, Frahmand M, Driscoll I. BDNF and KIBRA Polymorphisms Are Related to Altered Resting State Network Connectivity in Middle Age. J Alzheimers Dis 2022; 88:323-334. [PMID: 35599479 DOI: 10.3233/jad-215477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Disease-modifying treatments for Alzheimer's disease (AD) may be more successful if interventions occur early, prior to significant neurodegeneration and subsequent to the onset of clinical symptoms, potentially during middle age. Polymorphisms within BDNF, COMT, and KIBRA have been implicated in AD and relate to episodic memory and executive functioning, two domains that decline early in AD. OBJECTIVE The purpose of the current study was to use an endophenotype approach to examine in healthy, non-demented middle-aged adults the association between polymorphisms in BDNF, COMT, and KIBRA and functional connectivity within networks related to episodic memory and executive function (i.e., default mode network (DMN), executive control network (ECN), and frontoparietal network (FPN)). METHODS Resting state networks were identified using independent component analysis and spatial maps with associated time courses were extracted using a dual regression approach. RESULTS Functional connectivity within the DMN was associated with polymorphisms in BDNF (rs11030096, rs1491850) and KIBRA (rs1030182, rs6555791, rs6555802) (ps < 0.05), ECN connectivity was associated with polymorphisms in KIBRA (rs10475878, rs6555791) (ps < 0.05), and FPN connectivity was associated with KIBRA rs6555791 (p < 0.05). There were no COMT-related differences in functional connectivity of any of the three networks investigated (ps > 0.05). CONCLUSION Our study demonstrates that in middle age, polymorphisms in BDNF and KIBRA are associated with altered functional connectivity in networks that are affected early in AD. Future preclinical work should consider these polymorphisms to further elucidate their role in pathological aging and to aid in the identification of biomarkers.
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Affiliation(s)
| | - Laura Elizabeth Korthauer
- Department of Psychology, University of Wisconsin-Milwaukee, Milwaukee, WI, USA.,Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, RI, USA.,Department of Psychiatry, Rhode Island Hospital, Providence, RI, USA
| | - Elizabeth Awe
- Department of Psychology, University of Wisconsin-Milwaukee, Milwaukee, WI, USA.,Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Marijam Frahmand
- Department of Psychology, University of Wisconsin-Milwaukee, Milwaukee, WI, USA
| | - Ira Driscoll
- Department of Psychology, University of Wisconsin-Milwaukee, Milwaukee, WI, USA
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19
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Xu N, LaGrow TJ, Anumba N, Lee A, Zhang X, Yousefi B, Bassil Y, Clavijo GP, Khalilzad Sharghi V, Maltbie E, Meyer-Baese L, Nezafati M, Pan WJ, Keilholz S. Functional Connectivity of the Brain Across Rodents and Humans. Front Neurosci 2022; 16:816331. [PMID: 35350561 PMCID: PMC8957796 DOI: 10.3389/fnins.2022.816331] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Accepted: 02/14/2022] [Indexed: 12/15/2022] Open
Abstract
Resting-state functional magnetic resonance imaging (rs-fMRI), which measures the spontaneous fluctuations in the blood oxygen level-dependent (BOLD) signal, is increasingly utilized for the investigation of the brain's physiological and pathological functional activity. Rodents, as a typical animal model in neuroscience, play an important role in the studies that examine the neuronal processes that underpin the spontaneous fluctuations in the BOLD signal and the functional connectivity that results. Translating this knowledge from rodents to humans requires a basic knowledge of the similarities and differences across species in terms of both the BOLD signal fluctuations and the resulting functional connectivity. This review begins by examining similarities and differences in anatomical features, acquisition parameters, and preprocessing techniques, as factors that contribute to functional connectivity. Homologous functional networks are compared across species, and aspects of the BOLD fluctuations such as the topography of the global signal and the relationship between structural and functional connectivity are examined. Time-varying features of functional connectivity, obtained by sliding windowed approaches, quasi-periodic patterns, and coactivation patterns, are compared across species. Applications demonstrating the use of rs-fMRI as a translational tool for cross-species analysis are discussed, with an emphasis on neurological and psychiatric disorders. Finally, open questions are presented to encapsulate the future direction of the field.
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Affiliation(s)
- Nan Xu
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | - Theodore J. LaGrow
- Electrical and Computer Engineering, Georgia Tech, Atlanta, GA, United States
| | - Nmachi Anumba
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | - Azalea Lee
- Neuroscience Graduate Program, Emory University, Atlanta, GA, United States
- Emory University School of Medicine, Atlanta, GA, United States
| | - Xiaodi Zhang
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | - Behnaz Yousefi
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | - Yasmine Bassil
- Neuroscience Graduate Program, Emory University, Atlanta, GA, United States
| | - Gloria P. Clavijo
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | | | - Eric Maltbie
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | - Lisa Meyer-Baese
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | - Maysam Nezafati
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | - Wen-Ju Pan
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | - Shella Keilholz
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
- Neuroscience Graduate Program, Emory University, Atlanta, GA, United States
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20
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Pini L, Wennberg AM, Salvalaggio A, Vallesi A, Pievani M, Corbetta M. Breakdown of specific functional brain networks in clinical variants of Alzheimer's disease. Ageing Res Rev 2021; 72:101482. [PMID: 34606986 DOI: 10.1016/j.arr.2021.101482] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 09/24/2021] [Accepted: 09/29/2021] [Indexed: 02/07/2023]
Abstract
Alzheimer's disease (AD) is characterized by different clinical entities. Although AD phenotypes share a common molecular substrate (i.e., amyloid beta and tau accumulation), several clinicopathological differences exist. Brain functional networks might provide a macro-scale scaffolding to explain this heterogeneity. In this review, we summarize the evidence linking different large-scale functional network abnormalities to distinct AD phenotypes. Specifically, executive deficits in early-onset AD link with the dysfunction of networks that support sustained attention and executive functions. Posterior cortical atrophy relates to the breakdown of visual and dorsal attentional circuits, while the primary progressive aphasia variant of AD may be associated with the dysfunction of the left-lateralized language network. Additionally, network abnormalities might provide in vivo signatures for distinguishing proteinopathies that mimic AD, such as TAR DNA binding protein 43 related pathologies. These network differences vis-a-vis clinical syndromes are more evident in the earliest stage of AD. Finally, we discuss how these findings might pave the way for new tailored interventions targeting the most vulnerable brain circuit at the optimal time window to maximize clinical benefits.
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21
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Zhao Y, Caffo B, Luo X. Principal regression for high dimensional covariance matrices. Electron J Stat 2021; 15:4192-4235. [PMID: 35782590 PMCID: PMC9248851 DOI: 10.1214/21-ejs1887] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/15/2024]
Abstract
This manuscript presents an approach to perform generalized linear regression with multiple high dimensional covariance matrices as the outcome. In many areas of study, such as resting-state functional magnetic resonance imaging (fMRI) studies, this type of regression can be utilized to characterize variation in the covariance matrices across units. Model parameters are estimated by maximizing a likelihood formulation of a generalized linear model, conditioning on a well-conditioned linear shrinkage estimator for multiple covariance matrices, where the shrinkage coefficients are proposed to be shared across matrices. Theoretical studies demonstrate that the proposed covariance matrix estimator is optimal achieving the uniformly minimum quadratic loss asymptotically among all linear combinations of the identity matrix and the sample covariance matrix. Under certain regularity conditions, the proposed estimator of the model parameters is consistent. The superior performance of the proposed approach over existing methods is illustrated through simulation studies. Implemented to a resting-state fMRI study acquired from the Alzheimer's Disease Neuroimaging Initiative, the proposed approach identified a brain network within which functional connectivity is significantly associated with Apolipoprotein E ε4, a strong genetic marker for Alzheimer's disease.
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Affiliation(s)
- Yi Zhao
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine
| | - Brian Caffo
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health
| | - Xi Luo
- Department of Biostatistics and Data Science, The University of Texas Health Science Center at Houston
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22
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Xia N, Li Y, Xue Y, Li W, Zhang Z, Wen C, Li J, Ye Q. Intravoxel incoherent motion diffusion-weighted imaging in the characterization of Alzheimer's disease. Brain Imaging Behav 2021; 16:617-626. [PMID: 34480258 DOI: 10.1007/s11682-021-00538-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/08/2021] [Indexed: 10/20/2022]
Abstract
OBJECTIVES Alzheimer's disease (AD) is the most common type of dementia, and characterizing brain changes in AD is important for clinical diagnosis and prognosis. This study was designed to evaluate the classification performance of intravoxel incoherent motion (IVIM) diffusion-weighted imaging in differentiating between AD patients and normal control (NC) subjects and to explore its potential effectiveness as a neuroimaging biomarker. METHODS Thirty-one patients with probable AD and twenty NC subjects were included in the prospective study. IVIM data were subjected to postprocessing, and parameters including the apparent diffusion coefficient (ADC), slow diffusion coefficient (Ds), fast diffusion coefficient (Df), perfusion fraction (fp) and Df*fp were calculated. The classification model was developed and confirmed with cross-validation (group A/B) using Support Vector Machine (SVM). Correlations between IVIM parameters and Mini-Mental State Examination (MMSE) scores in AD patients were investigated using partial correlation analysis. RESULTS Diffusion MRI revealed significant region-specific differences that aided in differentiating AD patients from controls. Among the analyzed regions and parameters, the Df of the right precuneus (PreR) (ρ = 0.515; P = 0.006) and the left cerebellum (CL) (ρ = 0.429; P = 0.026) demonstrated significant associations with the cognitive function of AD patients. An area under the receiver operating characteristics curve (AUC) of 0.84 (95% CI: 0.66, 0.99) was calculated for the validation in dataset B after the prediction model was trained on dataset A. When the datasets were reversed, an AUC of 0.90 (95% CI: 0.75, 1.00) was calculated for the validation in dataset A, after the prediction model trained in dataset B. CONCLUSION IVIM imaging is a promising method for the classification of AD and NC subjects, and IVIM parameters of precuneus and cerebellum might be effective biomarker for the diagnosis of AD.
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Affiliation(s)
- Nengzhi Xia
- Department of Radiology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, People's Republic of China
| | - Yanxuan Li
- Department of Radiology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, People's Republic of China
| | - Yingnan Xue
- Department of Radiology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, People's Republic of China
| | - Weikang Li
- Department of Radiology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, People's Republic of China
| | - Zhenhua Zhang
- Department of Radiology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, People's Republic of China
| | - Caiyun Wen
- Department of Radiology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, People's Republic of China
| | - Jiance Li
- Department of Radiology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, People's Republic of China
| | - Qiong Ye
- Department of Radiology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, People's Republic of China. .,High Magnetic Field Laboratory, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, People's Republic of China.
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23
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Quattrini G, Marizzoni M, Pizzini FB, Galazzo IB, Aiello M, Didic M, Soricelli A, Albani D, Romano M, Blin O, Forloni G, Golay X, Jovicich J, Nathan PJ, Richardson JC, Salvatore M, Frisoni GB, Pievani M. Convergent and Discriminant Validity of Default Mode Network and Limbic Network Perfusion in Amnestic Mild Cognitive Impairment Patients. J Alzheimers Dis 2021; 82:1797-1808. [PMID: 34219733 DOI: 10.3233/jad-210531] [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] [Indexed: 11/15/2022]
Abstract
BACKGROUND Previous studies reported default mode network (DMN) and limbic network (LIN) brain perfusion deficits in patients with amnestic mild cognitive impairment (aMCI), frequently a prodromal stage of Alzheimer's disease (AD). However, the validity of these measures as AD markers has not yet been tested using MRI arterial spin labeling (ASL). OBJECTIVE To investigate the convergent and discriminant validity of DMN and LIN perfusion in aMCI. METHODS We collected core AD markers (amyloid-β 42 [Aβ42], phosphorylated tau 181 levels in cerebrospinal fluid [CSF]), neurodegenerative (hippocampal volumes and CSF total tau), vascular (white matter hyperintensities), genetic (apolipoprotein E [APOE] status), and cognitive features (memory functioning on Paired Associate Learning test [PAL]) in 14 aMCI patients. Cerebral blood flow (CBF) was extracted from DMN and LIN using ASL and correlated with AD features to assess convergent validity. Discriminant validity was assessed carrying out the same analysis with AD-unrelated features, i.e., somatomotor and visual networks' perfusion, cerebellar volume, and processing speed. RESULTS Perfusion was reduced in the DMN (F = 5.486, p = 0.039) and LIN (F = 12.678, p = 0.004) in APOE ɛ4 carriers compared to non-carriers. LIN perfusion correlated with CSF Aβ42 levels (r = 0.678, p = 0.022) and memory impairment (PAL, number of errors, r = -0.779, p = 0.002). No significant correlation was detected with tau, neurodegeneration, and vascular features, nor with AD-unrelated features. CONCLUSION Our results support the validity of DMN and LIN ASL perfusion as AD markers in aMCI, indicating a significant correlation between CBF and amyloidosis, APOE ɛ4, and memory impairment.
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Affiliation(s)
- Giulia Quattrini
- Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.,Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Moira Marizzoni
- Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.,Laboratory of Biological Psychiatry, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Francesca B Pizzini
- Radiology, Department of Diagnostic and Public Health, University of Verona, Verona, Italy
| | | | | | - Mira Didic
- Aix-Marseille Univ, INSERM, INS, Instit Neurosci des Syst, Marseille, France.,APHM, Timone, Service de Neurologie et Neuropsychologie, Hôpital Timone Adultes, Marseille, France
| | - Andrea Soricelli
- IRCCS SDN, Napoli, Italy.,Department of Sport Sciences, University of Naples Parthenope, Naples, Italy
| | - Diego Albani
- Neuroscience Department, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milano, Italy
| | - Melissa Romano
- Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Olivier Blin
- Aix-Marseille Univ, INSERM, INS, Instit Neurosci des Syst, DHUNE, Ap-Hm, Marseille, France
| | - Gianluigi Forloni
- Neuroscience Department, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milano, Italy
| | - Xavier Golay
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Jorge Jovicich
- Center for Mind/Brain Sciences - CIMeC, University of Trento, Rovereto, Italy
| | - Pradeep J Nathan
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Jill C Richardson
- Neurosciences Therapeutic Area, GlaxoSmithKline R&D, Gunnels Wood Road, Stevenage, United Kingdom
| | | | - Giovanni B Frisoni
- Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Michela Pievani
- Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
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24
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Kucikova L, Goerdten J, Dounavi ME, Mak E, Su L, Waldman AD, Danso S, Muniz-Terrera G, Ritchie CW. Resting-state brain connectivity in healthy young and middle-aged adults at risk of progressive Alzheimer's disease. Neurosci Biobehav Rev 2021; 129:142-153. [PMID: 34310975 DOI: 10.1016/j.neubiorev.2021.07.024] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Revised: 05/18/2021] [Accepted: 07/21/2021] [Indexed: 11/15/2022]
Abstract
Functional brain connectivity of the resting-state networks has gained recent attention as a possible biomarker of Alzheimer's Disease (AD). In this paper, we review the literature of functional connectivity differences in young adults and middle-aged cognitively intact individuals with non-modifiable risk factors of AD (n = 17). We focus on three main intrinsic resting-state networks: The Default Mode network, Executive network, and the Salience network. Overall, the evidence from the literature indicated early vulnerability of functional connectivity across different at-risk groups, particularly in the Default Mode Network. While there was little consensus on the interpretation on directionality, the topography of the findings showed frequent overlap across studies, especially in regions that are characteristic of AD (i.e., precuneus, posterior cingulate cortex, and medial prefrontal cortex areas). We conclude that while resting-state functional connectivity markers have great potential to identify at-risk individuals, implementing more data-driven approaches, further longitudinal and cross-validation studies, and the analysis of greater sample sizes are likely to be necessary to fully establish the effectivity and utility of resting-state network-based analyses.
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Affiliation(s)
- Ludmila Kucikova
- Edinburgh Dementia Prevention and Centre for Clinical Brain Sciences, Edinburgh Medical School, University of Edinburgh, Edinburgh, United Kingdom.
| | - Jantje Goerdten
- Department of Epidemiological Methods and Etiological Research, Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany
| | - Maria-Eleni Dounavi
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Elijah Mak
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Li Su
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Adam D Waldman
- Edinburgh Dementia Prevention and Centre for Clinical Brain Sciences, Edinburgh Medical School, University of Edinburgh, Edinburgh, United Kingdom
| | - Samuel Danso
- Edinburgh Dementia Prevention and Centre for Clinical Brain Sciences, Edinburgh Medical School, University of Edinburgh, Edinburgh, United Kingdom
| | - Graciela Muniz-Terrera
- Edinburgh Dementia Prevention and Centre for Clinical Brain Sciences, Edinburgh Medical School, University of Edinburgh, Edinburgh, United Kingdom
| | - Craig W Ritchie
- Edinburgh Dementia Prevention and Centre for Clinical Brain Sciences, Edinburgh Medical School, University of Edinburgh, Edinburgh, United Kingdom
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25
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Chumin EJ, Risacher SL, West JD, Apostolova LG, Farlow MR, McDonald BC, Wu YC, Saykin AJ, Sporns O. Temporal stability of the ventral attention network and general cognition along the Alzheimer's disease spectrum. Neuroimage Clin 2021; 31:102726. [PMID: 34153687 PMCID: PMC8220588 DOI: 10.1016/j.nicl.2021.102726] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Revised: 05/24/2021] [Accepted: 06/09/2021] [Indexed: 02/01/2023]
Abstract
Understanding the interrelationships of clinical manifestations of Alzheimer's disease (AD) and functional connectivity (FC) as the disease progresses is necessary for use of FC as a potential neuroimaging biomarker. Degradation of resting-state networks in AD has been observed when FC is estimated over the entire scan, however, the temporal dynamics of these networks are less studied. We implemented a novel approach to investigate the modular structure of static (sFC) and time-varying (tvFC) connectivity along the AD spectrum in a two-sample Discovery/Validation design (n = 80 and 81, respectively). Cortical FC networks were estimated across 4 diagnostic groups (cognitively normal, subjective cognitive decline, mild cognitive impairment, and AD) for whole scan (sFC) and with sliding window correlation (tvFC). Modularity quality (across a range of spatial scales) did not differ in either sFC or tvFC. For tvFC, group differences in temporal stability within and between multiple resting state networks were observed; however, these differences were not consistent between samples. Correlation analyses identified a relationship between global cognition and temporal stability of the ventral attention network, which was reproduced in both samples. While the ventral attention system has been predominantly studied in task-evoked designs, the relationship between its intrinsic dynamics at-rest and general cognition along the AD spectrum highlights its relevance regarding clinical manifestation of the disease.
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Affiliation(s)
- Evgeny J. Chumin
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA,Indiana University Network Science Institute, Bloomington, IN, USA,Indiana Alzheimer’s Disease Research Center, IUSM, Indianapolis, IN, USA,Corresponding author at: Psychology Building 308, 1101 E 10th St, Bloomington, IN 47405, USA.
| | - Shannon L. Risacher
- Indiana University Network Science Institute, Bloomington, IN, USA,Department of Radiology and Imaging Sciences, Indiana University School of Medicine (IUSM), Indianapolis, IN, USA,Indiana Alzheimer’s Disease Research Center, IUSM, Indianapolis, IN, USA,Department of Neurology, IUSM, Indianapolis, IN, USA
| | - John D. West
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine (IUSM), Indianapolis, IN, USA,Indiana Alzheimer’s Disease Research Center, IUSM, Indianapolis, IN, USA
| | - Liana G. Apostolova
- Indiana University Network Science Institute, Bloomington, IN, USA,Department of Radiology and Imaging Sciences, Indiana University School of Medicine (IUSM), Indianapolis, IN, USA,Indiana Alzheimer’s Disease Research Center, IUSM, Indianapolis, IN, USA,Department of Neurology, IUSM, Indianapolis, IN, USA
| | - Martin R. Farlow
- Indiana Alzheimer’s Disease Research Center, IUSM, Indianapolis, IN, USA,Department of Neurology, IUSM, Indianapolis, IN, USA
| | - Brenna C. McDonald
- Indiana University Network Science Institute, Bloomington, IN, USA,Department of Radiology and Imaging Sciences, Indiana University School of Medicine (IUSM), Indianapolis, IN, USA,Indiana Alzheimer’s Disease Research Center, IUSM, Indianapolis, IN, USA,Department of Neurology, IUSM, Indianapolis, IN, USA
| | - Yu-Chien Wu
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine (IUSM), Indianapolis, IN, USA,Indiana Alzheimer’s Disease Research Center, IUSM, Indianapolis, IN, USA
| | - Andrew J. Saykin
- Indiana University Network Science Institute, Bloomington, IN, USA,Department of Radiology and Imaging Sciences, Indiana University School of Medicine (IUSM), Indianapolis, IN, USA,Indiana Alzheimer’s Disease Research Center, IUSM, Indianapolis, IN, USA,Department of Neurology, IUSM, Indianapolis, IN, USA
| | - Olaf Sporns
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA,Indiana University Network Science Institute, Bloomington, IN, USA,Department of Radiology and Imaging Sciences, Indiana University School of Medicine (IUSM), Indianapolis, IN, USA,Indiana Alzheimer’s Disease Research Center, IUSM, Indianapolis, IN, USA
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26
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Özbek Y, Fide E, Yener GG. Resting-state EEG alpha/theta power ratio discriminates early-onset Alzheimer's disease from healthy controls. Clin Neurophysiol 2021; 132:2019-2031. [PMID: 34284236 DOI: 10.1016/j.clinph.2021.05.012] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Revised: 03/12/2021] [Accepted: 05/17/2021] [Indexed: 11/17/2022]
Abstract
OBJECTIVES The present study aims to compare early-onset Alzheimer's disease (EOAD) patients with healthy controls (HC), and late-onset Alzheimer's disease (LOAD) patients using resting-state delta, theta, alpha, and beta oscillations and provide a cut-off score of alpha/theta ratio to discriminate individuals with EOAD and young HC. METHODS Forty-seven individuals with EOAD, 51 individuals with LOAD, and demographically-matched 49 young and 51 older controls were included in the study. Spectral-power analysis using Fast-Fourier Transformation (FFT) is performed on resting-state electroencephalography (EEG) data. Delta, theta, alpha, and beta oscillations compared between groups and Receiver Operating Characteristic (ROC) curve analysis was conducted. RESULTS Compared to healthy controls individuals with EOAD showed an increase in slow frequency bands and a decrease in fast frequency bands. Frontal alpha/theta power ratio is the best discriminating value between EOAD and young HC with the sensitivity and specificity greater than 80% with area under the curve (AUC) 0.881. CONCLUSIONS EOAD display more widespread and severe electrophysiological abnormalities than LOAD and HC which may reflect more pronounced pathological burden and cholinergic deficits in EOAD. Additionally, the alpha/theta ratio can discriminate EOAD and young HC successfully. SIGNIFICANCE This study is the first to report that resting-state EEG power can be a promising marker for diagnostic accuracy between EOAD and healthy controls.
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Affiliation(s)
- Yağmur Özbek
- Department of Neurosciences, Institute of Health Sciences, Dokuz Eylul University, Izmir, Turkey
| | - Ezgi Fide
- Department of Neurosciences, Institute of Health Sciences, Dokuz Eylul University, Izmir, Turkey
| | - Görsev G Yener
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir, Turkey; Izmir University of Economics, Faculty of Medicine, Izmir, Turkey.
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27
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Luo X, Wang S, Jiaerken Y, Li K, Zeng Q, Zhang R, Wang C, Xu X, Wu D, Huang P, Zhang M. Distinct fiber-specific white matter reductions pattern in early- and late-onset Alzheimer's disease. Aging (Albany NY) 2021; 13:12410-12430. [PMID: 33930871 PMCID: PMC8148465 DOI: 10.18632/aging.202702] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Accepted: 02/08/2021] [Indexed: 01/31/2023]
Abstract
Background: The underlying white matter impairment in patients with early and late-onset Alzheimer’s disease (EOAD and LOAD) is still unclear, and this might due to the complex AD pathology. Methods: We included 31 EOAD, 45 LOAD, and 64 younger, 46 elder controls in our study to undergo MRI examinations. Fiber density (FD) and fiber bundle cross-section (FC) were measured using fixel-based analysis based on diffusion weighted images. On whole brain and tract-based level, we compared these parameters among different groups (p<0.05, FWE corrected). Moreover, we verified our results in another independent dataset using the same analyses. Results: Compared to young healthy controls, EOAD had significantly lower FD in the splenium of corpus callosum, limbic tracts, cingulum bundles, and posterior thalamic radiation, and higher FC in the splenium of corpus callosum, dorsal cingulum and posterior thalamic radiation. On the other hand, LOAD had lower FD and FC as well. Importantly, a similar pattern was found in the independent validation dataset. Among all groups, both the FD and FC were associated with cognitive function. Furthermore, FD of fornix column and body, and FC of ventral cingulum were associated with composite amyloid and tau level (r=-0.34 and -0.53, p<0.001) respectively. Conclusions: EOAD and LOAD were characterized by distinct white matter impairment patterns, which may be attributable to their different neuropathologies.
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Affiliation(s)
- Xiao Luo
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Shuyue Wang
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Yeerfan Jiaerken
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Kaicheng Li
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Qingze Zeng
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Ruiting Zhang
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Chao Wang
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaopei Xu
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Peiyu Huang
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Minming Zhang
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
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28
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Olivieri P, Hamelin L, Lagarde J, Hahn V, Guichart-Gomez E, Roué-Jagot C, Sarazin M. Characterization of the initial complaint and care pathways prior to diagnosis in very young sporadic Alzheimer's disease. ALZHEIMERS RESEARCH & THERAPY 2021; 13:90. [PMID: 33926533 PMCID: PMC8086269 DOI: 10.1186/s13195-021-00829-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/26/2020] [Accepted: 04/12/2021] [Indexed: 12/25/2022]
Abstract
BACKGROUND Very-early-onset Alzheimer's disease (young-AD) differentiates from late-onset AD (old-AD) by a predominant involvement of the parietal neocortex leading to atypical presentations. The diagnosis of AD is often not the first to be mentioned in such young patients. METHODS We retrospectively reviewed the initial complaint and care pathways of 66 sporadic young-AD (age < 62) and 30 old-AD patients (age > 65) and compared their neuropsychological profiles at the time of diagnosis (based on clinical-biological criteria) with 44 amyloid-negative controls. RESULTS The initial complaint of young-AD was non-cognitive and mimicked a burnout in 32% of cases. Their main cognitive complaints were memory (38% vs 87% in old-AD) and language (17% vs 13%) impairment. The referral to a psychiatrist prior to AD diagnosis was more frequent in young-AD than in old-AD (26% vs 0%). At the time of diagnosis, young-AD were at a more severe stage of dementia than old-AD (24% vs 10% with CDR ≥ 1) but had less anosognosia. CONCLUSIONS Better identifying the initial signs of very-early-onset AD is crucial to improve the early diagnosis and develop new treatments.
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Affiliation(s)
- Pauline Olivieri
- Department of Neurology of Memory and Language, GHU Paris Psychiatry and Neurosciences, Hôpital Sainte Anne, 1 rue Cabanis, F-75014, Paris, France. .,Université de Paris, F-75006, Paris, France. .,Université Paris-Saclay, BioMaps, CEA, CNRS, Inserm, F-91401, Orsay, France.
| | - Lorraine Hamelin
- Department of Neurology of Memory and Language, GHU Paris Psychiatry and Neurosciences, Hôpital Sainte Anne, 1 rue Cabanis, F-75014, Paris, France.,Université de Paris, F-75006, Paris, France.,Université Paris-Saclay, BioMaps, CEA, CNRS, Inserm, F-91401, Orsay, France
| | - Julien Lagarde
- Department of Neurology of Memory and Language, GHU Paris Psychiatry and Neurosciences, Hôpital Sainte Anne, 1 rue Cabanis, F-75014, Paris, France.,Université de Paris, F-75006, Paris, France.,Université Paris-Saclay, BioMaps, CEA, CNRS, Inserm, F-91401, Orsay, France
| | - Valérie Hahn
- Department of Neurology of Memory and Language, GHU Paris Psychiatry and Neurosciences, Hôpital Sainte Anne, 1 rue Cabanis, F-75014, Paris, France
| | - Elodie Guichart-Gomez
- Department of Neurology of Memory and Language, GHU Paris Psychiatry and Neurosciences, Hôpital Sainte Anne, 1 rue Cabanis, F-75014, Paris, France
| | - Carole Roué-Jagot
- Department of Neurology of Memory and Language, GHU Paris Psychiatry and Neurosciences, Hôpital Sainte Anne, 1 rue Cabanis, F-75014, Paris, France
| | - Marie Sarazin
- Department of Neurology of Memory and Language, GHU Paris Psychiatry and Neurosciences, Hôpital Sainte Anne, 1 rue Cabanis, F-75014, Paris, France.,Université de Paris, F-75006, Paris, France.,Université Paris-Saclay, BioMaps, CEA, CNRS, Inserm, F-91401, Orsay, France
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29
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Zhou J, Li K, Luo X, Zeng Q, Jiaerken Y, Wang S, Xu X, Liu X, Li Z, Zhang T, Fu Y, Zhao S, Huang P, Zhang M. Distinct impaired patterns of intrinsic functional network centrality in patients with early- and late-onset Alzheimer's disease. Brain Imaging Behav 2021; 15:2661-2670. [PMID: 33844192 DOI: 10.1007/s11682-021-00470-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2019] [Accepted: 03/04/2021] [Indexed: 10/21/2022]
Abstract
Early-onset Alzheimer's disease (EOAD) involves multiple cognitive domains and shows more rapid progression than late-onset Alzheimer's disease (LOAD). However, the difference in pathogenesis between EOAD and LOAD is still unclear. Accordingly, we applied intrinsic network analysis to explore the potential neuropathological mechanism underlying distinct clinical phenotypes. According to the cut-off age of 65, we included 20 EOAD patients, 20 LOAD patients, and 36 age-matched controls (19 young and 17 old controls). We employed resting-state functional MRI and network centrality analysis to explore the local (degree centrality (DC)) and global (eigenvector centrality (EC)) functional integrity. Two-sample t-test analysis was performed, with gray matter volume, age, gender, and education as covariates. Furthermore, we performed a correlation analysis between network metrics and cognition. Compared to young controls, EOAD patients exhibited lower DC in the middle temporal gyrus (MTG), parahippocampal gyrus (PHG), superior temporal gyrus (STG), and lower EC in the MTG, PHG, and postcentral gyrus. In contrast, LOAD patients exhibited lower DC in the STG and anterior cingulum gyrus and higher DC in the middle frontal gyrus compared to old controls. No significant difference in EC was observed in LOAD patients. Furthermore, both DC and EC correlated with cognitive performance. Our study demonstrated divergent functional network impairments in EOAD and LOAD patients. EOAD patients showed more complex network damage involving both local and global centrality properties, while LOAD patients mainly featured local functional connectivity changes. Such centrality impairments are related to poor cognition, especially regarding memory performance.
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Affiliation(s)
- Jiong Zhou
- Department of Neurology, 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Kaicheng Li
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, No.88 Jie-fang Road, Shang-cheng District, Hangzhou, 310009, China
| | - Xiao Luo
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, No.88 Jie-fang Road, Shang-cheng District, Hangzhou, 310009, China
| | - Qingze Zeng
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, No.88 Jie-fang Road, Shang-cheng District, Hangzhou, 310009, China
| | - Yerfan Jiaerken
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, No.88 Jie-fang Road, Shang-cheng District, Hangzhou, 310009, China
| | - Shuyue Wang
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, No.88 Jie-fang Road, Shang-cheng District, Hangzhou, 310009, China
| | - Xiaopei Xu
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, No.88 Jie-fang Road, Shang-cheng District, Hangzhou, 310009, China
| | - Xiaocao Liu
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, No.88 Jie-fang Road, Shang-cheng District, Hangzhou, 310009, China
| | - Zheyu Li
- Department of Neurology, 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Tianyi Zhang
- Department of Neurology, 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Yanv Fu
- Department of Neurology, 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Shuai Zhao
- Department of Neurology, 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Peiyu Huang
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, No.88 Jie-fang Road, Shang-cheng District, Hangzhou, 310009, China.
| | - Minming Zhang
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, No.88 Jie-fang Road, Shang-cheng District, Hangzhou, 310009, China.
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30
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Pini L, Geroldi C, Galluzzi S, Baruzzi R, Bertocchi M, Chitò E, Orini S, Romano M, Cotelli M, Rosini S, Magnaldi S, Morassi M, Cobelli M, Bonvicini C, Archetti S, Zanetti O, Frisoni GB, Pievani M. Age at onset reveals different functional connectivity abnormalities in prodromal Alzheimer's disease. Brain Imaging Behav 2021; 14:2594-2605. [PMID: 31903525 DOI: 10.1007/s11682-019-00212-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Age at symptom onset (AAO) underlies different Alzheimer's disease (AD) clinical variants: late-onset AD (LOAD) is characterized by memory deficits, while early-onset AD (EOAD) presents predominantly with non-memory symptoms. The involvement of different neural networks may explain these distinct clinical phenotypes. In this study, we tested the hypothesis of an early and selective involvement of neural networks based on AAO in AD. Twenty memory clinic patients with prodromal AD (i.e., mild cognitive impairment with an AD-like cerebrospinal fluid profile) and 30 healthy controls underwent a cognitive evaluation and a resting state functional MRI exam. Independent component analysis was performed to assess functional connectivity (FC) in the following networks: default mode, frontoparietal, limbic, visual, and sensorimotor. Patients were stratified into late-onset (pLOAD) and early-onset (pEOAD) prodromal AD according to the AAO and controls were stratified into younger and older groups accordingly. Decreased FC within the default mode and the limbic networks was observed in pLOAD, while pEOAD showed lower FC in the frontoparietal and visual networks. The sensorimotor network did not show differences between groups. A significant association was found between memory and limbic network FC in pLOAD, and between executive functions and frontoparietal network FC in pEOAD, although the latter association did not survive multiple comparison correction. Our findings indicate that aberrant connectivity in memory networks is associated with pLOAD, while networks underlying executive and visuo-spatial functions are affected in pEOAD. These findings are in line with the hypothesis that the pathophysiological mechanisms underlying EOAD and LOAD are distinct.
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Affiliation(s)
- Lorenzo Pini
- Laboratory Alzheimer's Neuroimaging & Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, via Pilastroni 4, 25125, Brescia, Italy.,Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Cristina Geroldi
- Alzheimer's Unit - Memory Clinic, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Samantha Galluzzi
- Laboratory Alzheimer's Neuroimaging & Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, via Pilastroni 4, 25125, Brescia, Italy
| | - Roberta Baruzzi
- Laboratory Alzheimer's Neuroimaging & Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, via Pilastroni 4, 25125, Brescia, Italy
| | - Monica Bertocchi
- Alzheimer's Unit - Memory Clinic, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Eugenia Chitò
- Alzheimer's Unit - Memory Clinic, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Stefania Orini
- Alzheimer's Unit - Memory Clinic, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Melissa Romano
- Laboratory Alzheimer's Neuroimaging & Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, via Pilastroni 4, 25125, Brescia, Italy
| | - Maria Cotelli
- Neuropsychology Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Sandra Rosini
- Neuropsychology Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Silvia Magnaldi
- Radiology, Department of Health Services, Santa Maria degli Angeli Hospital, Pordenone, Italy
| | - Mauro Morassi
- Department of Radiology, Fondazione Poliambulanza, Brescia, Italy
| | - Milena Cobelli
- Department of Radiology, Fondazione Poliambulanza, Brescia, Italy
| | - Cristian Bonvicini
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Silvana Archetti
- Department of Laboratory Diagnostic, Biotechnology Laboratory, ASST Spedali Civili Brescia, Brescia, Italy
| | - Orazio Zanetti
- Alzheimer's Unit - Memory Clinic, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Giovanni B Frisoni
- Laboratory Alzheimer's Neuroimaging & Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, via Pilastroni 4, 25125, Brescia, Italy.,Memory Clinic and LANVIE Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Michela Pievani
- Laboratory Alzheimer's Neuroimaging & Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, via Pilastroni 4, 25125, Brescia, Italy.
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31
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Amaefule CO, Dyrba M, Wolfsgruber S, Polcher A, Schneider A, Fliessbach K, Spottke A, Meiberth D, Preis L, Peters O, Incesoy EI, Spruth EJ, Priller J, Altenstein S, Bartels C, Wiltfang J, Janowitz D, Bürger K, Laske C, Munk M, Rudolph J, Glanz W, Dobisch L, Haynes JD, Dechent P, Ertl-Wagner B, Scheffler K, Kilimann I, Düzel E, Metzger CD, Wagner M, Jessen F, Teipel SJ. Association between composite scores of domain-specific cognitive functions and regional patterns of atrophy and functional connectivity in the Alzheimer's disease spectrum. Neuroimage Clin 2020; 29:102533. [PMID: 33360018 PMCID: PMC7770965 DOI: 10.1016/j.nicl.2020.102533] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Revised: 11/24/2020] [Accepted: 12/12/2020] [Indexed: 02/06/2023]
Abstract
BACKGROUND Cognitive decline has been found to be associated with gray matter atrophy and disruption of functional neural networks in Alzheimer's disease (AD) in structural and functional imaging (fMRI) studies. Most previous studies have used single test scores of cognitive performance among monocentric cohorts. However, cognitive domain composite scores could be more reliable than single test scores due to the reduction of measurement error. Adopting a multicentric resting state fMRI (rs-fMRI) and cognitive domain approach, we provide a comprehensive description of the structural and functional correlates of the key cognitive domains of AD. METHOD We analyzed MRI, rs-fMRI and cognitive domain score data of 490 participants from an interim baseline release of the multicenter DELCODE study cohort, including 54 people with AD, 86 with Mild Cognitive Impairment (MCI), 175 with Subjective Cognitive Decline (SCD), and 175 Healthy Controls (HC) in the AD-spectrum. Resulting cognitive domain composite scores (executive, visuo-spatial, memory, working memory and language) from the DELCODE neuropsychological battery (DELCODE-NP), were previously derived using confirmatory factor analysis. Statistical analyses examined the differences between diagnostic groups, and the association of composite scores with regional atrophy and network-specific functional connectivity among the patient subgroup of SCD, MCI and AD. RESULT Cognitive performance, atrophy patterns and functional connectivity significantly differed between diagnostic groups in the AD-spectrum. Regional gray matter atrophy was positively associated with visuospatial and other cognitive impairments among the patient subgroup in the AD-spectrum. Except for the visual network, patterns of network-specific resting-state functional connectivity were positively associated with distinct cognitive impairments among the patient subgroup in the AD-spectrum. CONCLUSION Consistent associations between cognitive domain scores and both regional atrophy and network-specific functional connectivity (except for the visual network), support the utility of a multicentric and cognitive domain approach towards explicating the relationship between imaging markers and cognition in the AD-spectrum.
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Affiliation(s)
| | - Martin Dyrba
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany
| | - Steffen Wolfsgruber
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany; Department of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital, Bonn, Germany
| | | | - Anja Schneider
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany; Department of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital, Bonn, Germany
| | - Klaus Fliessbach
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany; Department of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital, Bonn, Germany
| | - Annika Spottke
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany; Department of Neurology, University Hospital Bonn, Bonn, Germany
| | - Dix Meiberth
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany; Department of Psychiatry, University of Cologne, Cologne, Germany
| | - Lukas Preis
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany; Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany
| | - Oliver Peters
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany; Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany
| | - Enise I Incesoy
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany; Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany
| | - Eike J Spruth
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany; Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Josef Priller
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany; Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Slawek Altenstein
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany; Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Claudia Bartels
- Department of Psychiatry and Psychotherapy, University Medical Center Goettingen (UMG), Goettingen, Germany
| | - Jens Wiltfang
- German Center for Neurodegenerative Diseases (DZNE), Goettingen, Germany; Department of Psychiatry and Psychotherapy, University Medical Center Goettingen (UMG), Goettingen, Germany; Neurosciences and Signaling Group, Institute of Biomedicine (iBiMED), Department of Medical Sciences, University of Aveiro, Aveiro, Portugal
| | - Daniel Janowitz
- Institute for Stroke and Dementia Research (ISD), University Hospital, Ludwig Maximilians University, Munich, Germany
| | - Katharina Bürger
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany; Institute for Stroke and Dementia Research (ISD), University Hospital, Ludwig Maximilians University, Munich, Germany
| | - Christoph Laske
- German Center for Neurodegenerative Diseases (DZNE), Tuebingen, Germany; Section for Dementia Research, Hertie Institute for Clinical Brain Research and Department of Psychiatry and Psychotherapy, University of Tuebingen, Tuebingen, Germany
| | - Matthias Munk
- Section for Dementia Research, Hertie Institute for Clinical Brain Research and Department of Psychiatry and Psychotherapy, University of Tuebingen, Tuebingen, Germany
| | - Janna Rudolph
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Wenzel Glanz
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Laura Dobisch
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - John D Haynes
- Bernstein Center for Computational Neuroscience, Charité - Universitätsmedizin, Berlin, Germany
| | - Peter Dechent
- MR-Research in Neurology and Psychiatry, Georg-August-University Goettingen, Germany
| | - Birgit Ertl-Wagner
- Institute for Clinical Radiology, Ludwig Maximilians University, Munich, Germany
| | - Klaus Scheffler
- Department for Biomedical Magnetic Resonance, University of Tuebingen, Tuebingen, Germany
| | - Ingo Kilimann
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany; Department of Psychosomatic Medicine, Rostock University Medical Center, Rostock, Germany
| | - Emrah Düzel
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany; Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University, Magdeburg, Germany
| | - Coraline D Metzger
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany; Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University, Magdeburg, Germany; Department of Psychiatry and Psychotherapy, Otto-von-Guericke University, Magdeburg, Germany
| | - Michael Wagner
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany; Department of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital, Bonn, Germany
| | - Frank Jessen
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany; Department of Psychiatry, University of Cologne, Cologne, Germany; Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - Stefan J Teipel
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany; Department of Psychosomatic Medicine, Rostock University Medical Center, Rostock, Germany
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Bolton CJ, Tam JW. Differential Involvement of the Locus Coeruleus in Early- and Late-Onset Alzheimer's Disease: A Potential Mechanism of Clinical Differences? MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2020:2020.11.01.20224139. [PMID: 33173930 PMCID: PMC7654926 DOI: 10.1101/2020.11.01.20224139] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Early-onset Alzheimer's disease (EOAD) has been associated with an increased likelihood of atypical clinical manifestations such as attentional impairment, yet the cause of this heterogeneity remains unclear. The locus coeruleus (LC) is implicated early in Alzheimer's disease pathology and is associated with attentional functioning. This study investigated post-mortem atrophy of the LC in EOAD and late-onset Alzheimer's disease (LOAD) in a large, well-characterized sample. Results show nearly four times greater likelihood of higher LC atrophy in EOAD as compared to LOAD after controlling for other measures of pathological progression ( p < .005). Follow-up analyses within the EOAD group revealed that compared to those who displayed mild or no LC atrophy at autopsy, those with moderate-severe atrophy of the LC displayed significantly worse performance on various baseline measures of attentional functioning ( p < .05), despite similar overall cognition ( p = .25). These findings suggest the LC is an important potential driver of clinical and pathological heterogeneity in EOAD.
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Affiliation(s)
- Corey J. Bolton
- Vanderbilt Memory & Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
- Deparment of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Joyce W. Tam
- Deparment of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago, IL, USA
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33
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Foran AM, Mathias JL, Bowden SC. Effectiveness of sorting tests for detecting cognitive decline in older adults with dementia and other common neurodegenerative disorders: A meta-analysis. Neurosci Biobehav Rev 2020; 120:442-454. [PMID: 33091417 DOI: 10.1016/j.neubiorev.2020.10.013] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2019] [Revised: 10/12/2020] [Accepted: 10/14/2020] [Indexed: 12/13/2022]
Abstract
The demand for simple, accurate and time-efficient screens to detect cognitive decline at point-of-care is increasing. Sorting tests are often used to detect the 'executive' deficits that are commonly associated with behavioural-variant frontotemporal dementia (bvFTD), but their potential for use as a cognitive screen with older adults is unclear. A comprehensive search of four databases identified 142 studies that compared the sorting test performance (e.g. WCST, DKEFS-ST) of adults with a common neurodegenerative disorder (e.g. Alzheimer's disease, vascular dementia, bvFTD, Parkinson's disease) and cognitively-healthy controls. Hedges' g effect sizes were used to compare the groups on five common test scores (Category, Total, Perseveration, Error, Description). The neurodegenerative disorders (combined) showed large deficits on all scores (g -1.0 to -1.3), with dementia (combined subtypes) performing more poorly (g -1.2 to -2.1), although bvFTD was not disproportionately worse than the other dementias. Overall, sorting tests detected the cognitive impairments caused by common neurodegenerative disorders, especially dementia, highlighting their potential suitability as a cognitive screen for older adults.
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Affiliation(s)
- A M Foran
- School of Psychology, University of Adelaide, Adelaide, South Australia, 5005, Australia.
| | - J L Mathias
- School of Psychology, University of Adelaide, Adelaide, South Australia, 5005, Australia.
| | - S C Bowden
- Melbourne School of Psychological Sciences, University of Melbourne, Parkville, Victoria, 3010, Australia
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Muñoz-Moreno E, Tudela R, López-Gil X, Soria G. Brain connectivity during Alzheimer's disease progression and its cognitive impact in a transgenic rat model. Netw Neurosci 2020; 4:397-415. [PMID: 32537533 PMCID: PMC7286303 DOI: 10.1162/netn_a_00126] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Accepted: 01/10/2020] [Indexed: 12/12/2022] Open
Abstract
The research of Alzheimer's disease (AD) in its early stages and its progression till symptomatic onset is essential to understand the pathology and investigate new treatments. Animal models provide a helpful approach to this research, since they allow for controlled follow-up during the disease evolution. In this work, transgenic TgF344-AD rats were longitudinally evaluated starting at 6 months of age. Every 3 months, cognitive abilities were assessed by a memory-related task and magnetic resonance imaging (MRI) was acquired. Structural and functional brain networks were estimated and characterized by graph metrics to identify differences between the groups in connectivity, its evolution with age, and its influence on cognition. Structural networks of transgenic animals were altered since the earliest stage. Likewise, aging significantly affected network metrics in TgF344-AD, but not in the control group. In addition, while the structural brain network influenced cognitive outcome in transgenic animals, functional network impacted how control subjects performed. TgF344-AD brain network alterations were present from very early stages, difficult to identify in clinical research. Likewise, the characterization of aging in these animals, involving structural network reorganization and its effects on cognition, opens a window to evaluate new treatments for the disease.
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Affiliation(s)
- Emma Muñoz-Moreno
- Experimental 7T MRI Unit, Institut d'Investigacions Bimediques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Raúl Tudela
- Experimental 7T MRI Unit, Institut d'Investigacions Bimediques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Xavier López-Gil
- Experimental 7T MRI Unit, Institut d'Investigacions Bimediques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Guadalupe Soria
- Experimental 7T MRI Unit, Institut d'Investigacions Bimediques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
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35
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Functional Connectivity in Neurodegenerative Disorders: Alzheimer's Disease and Frontotemporal Dementia. Top Magn Reson Imaging 2020; 28:317-324. [PMID: 31794504 DOI: 10.1097/rmr.0000000000000223] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Neurodegenerative disorders are a growing cause of morbidity and mortality worldwide. Onset is typically insidious and clinical symptoms of behavioral change, memory loss, or cognitive dysfunction may not be evident early in the disease process. Efforts have been made to discover biomarkers that allow for earlier diagnosis of neurodegenerative disorders, to initiate treatment that may slow the course of clinical deterioration. Neuronal dysfunction occurs earlier than clinical symptoms manifest. Thus, assessment of neuronal function using functional brain imaging has been examined as a potential biomarker. While most early studies used task-functional magnetic resonance imaging (fMRI), with the more recent technique of resting-state fMRI, "intrinsic" relationships between brain regions or brain networks have been studied in greater detail in neurodegenerative disorders. In Alzheimer's disease, the most common neurodegenerative disorder, and frontotemporal dementia, another of the common dementias, specific brain networks may be particularly susceptible to dysfunction. In this review, we highlight the major findings of functional connectivity assessed by resting state fMRI in Alzheimer's disease and frontotemporal dementia.
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36
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Abstract
PURPOSE OF REVIEW Early-onset Alzheimer disease (AD) is defined as having an age of onset younger than 65 years. While early-onset AD is often overshadowed by the more common late-onset AD, recognition of the differences between early- and late-onset AD is important for clinicians. RECENT FINDINGS Early-onset AD comprises about 5% to 6% of cases of AD and includes a substantial percentage of phenotypic variants that differ from the usual amnestic presentation of typical AD. Characteristics of early-onset AD in comparison to late-onset AD include a larger genetic predisposition (familial mutations and summed polygenic risk), more aggressive course, more frequent delay in diagnosis, higher prevalence of traumatic brain injury, less memory impairment and greater involvement of other cognitive domains on presentation, and greater psychosocial difficulties. Neuroimaging features of early-onset AD in comparison to late-onset AD include greater frequency of hippocampal sparing and posterior neocortical atrophy, increased tau burden, and greater connectomic changes affecting frontoparietal networks rather than the default mode network. SUMMARY Early-onset AD differs substantially from late-onset AD, with different phenotypic presentations, greater genetic predisposition, and differences in neuropathologic burden and topography. Early-onset AD more often presents with nonamnestic phenotypic variants that spare the hippocampi and with greater tau burden in posterior neocortices. The early-onset AD phenotypic variants involve different neural networks than typical AD. The management of early-onset AD is similar to that of late-onset AD but with special emphasis on targeting specific cognitive areas and more age-appropriate psychosocial support and education.
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37
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Vanhoutte M, Semah F, Leclerc X, Sillaire AR, Jaillard A, Kuchcinski G, Delbeuck X, Fahmi R, Pasquier F, Lopes R. Three-year changes of cortical 18F-FDG in amnestic vs. non-amnestic sporadic early-onset Alzheimer's disease. Eur J Nucl Med Mol Imaging 2019; 47:304-318. [PMID: 31606833 DOI: 10.1007/s00259-019-04519-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Accepted: 08/30/2019] [Indexed: 11/27/2022]
Abstract
PURPOSE To examine and compare longitudinal changes of cortical glucose metabolism in amnestic and non-amnestic sporadic forms of early-onset Alzheimer's disease and assess potential associations with neuropsychological performance over a 3-year period time. METHODS Eighty-two participants meeting criteria for early-onset (< 65 years) sporadic form of probable Alzheimer's disease and presenting with a variety of clinical phenotypes (47 amnestic and 35 non-amnestic forms) were included at baseline and followed up for 1.44 ± 1.23 years. All of the participants underwent a work-up at baseline and every year during the follow-up period, which includes clinical examination, neuropsychological testing, genotyping, cerebrospinal fluid biomarker assays, and structural MRI and 18F-FDG PET. Vertex-wise partial volume-corrected glucose metabolic maps across the entire cortical surface were generated and longitudinally assessed together with the neuropsychological scores using linear mixed-effects modeling as a function of amnestic and non-amnestic sporadic forms of early-onset Alzheimer's disease. RESULTS Similar evolution patterns of glucose metabolic decline between amnestic and non-amnestic forms were observed in widespread neocortical cortices. However, only non-amnestic forms appeared to have a greater reduction of glucose metabolism in lateral orbitofrontal and bilateral medial temporal cortices associated with more severe declines of neuropsychological performance compared with amnestic forms. Furthermore, results suggest that glucose metabolic decline in amnestic forms would progress along an anterior-to-posterior axis, whereas glucose metabolic decline in non-amnestic forms would progress along a posterior-to-anterior axis. CONCLUSIONS We found differences in spatial distribution and temporal trajectory of glucose metabolic decline between amnestic and non-amnestic early-onset Alzheimer's disease groups, suggesting that one might want to consider treating the two forms of the disease as two separate entities.
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Affiliation(s)
- Matthieu Vanhoutte
- Inserm U1171, CHU Lille, University of Lille, F-59000, Lille, France. .,Department of Nuclear Medicine, CHU Lille, F-59000, Lille, France. .,Department of Neuroradiology, CHU Lille, F-59000, Lille, France.
| | - Franck Semah
- Inserm U1171, CHU Lille, University of Lille, F-59000, Lille, France.,Department of Nuclear Medicine, CHU Lille, F-59000, Lille, France
| | - Xavier Leclerc
- Inserm U1171, CHU Lille, University of Lille, F-59000, Lille, France.,Department of Neuroradiology, CHU Lille, F-59000, Lille, France
| | - Adeline Rollin Sillaire
- Department of Neurology, CHU Lille, F-59000, Lille, France.,Inserm U1171, CHU Lille, Memory Center, DISTALZ, University of Lille, F-59000, Lille, France
| | - Alice Jaillard
- Inserm U1171, CHU Lille, University of Lille, F-59000, Lille, France.,Department of Nuclear Medicine, CHU Lille, F-59000, Lille, France
| | - Grégory Kuchcinski
- Inserm U1171, CHU Lille, University of Lille, F-59000, Lille, France.,Department of Neuroradiology, CHU Lille, F-59000, Lille, France
| | - Xavier Delbeuck
- Inserm U1171, CHU Lille, Memory Center, DISTALZ, University of Lille, F-59000, Lille, France.,Department of Neuropsychology, CHU Lille, F-59000, Lille, France
| | - Rachid Fahmi
- Siemens Medical Solutions USA, Inc., Molecular Imaging, Knoxville, TN, USA
| | - Florence Pasquier
- Department of Neurology, CHU Lille, F-59000, Lille, France.,Inserm U1171, CHU Lille, Memory Center, DISTALZ, University of Lille, F-59000, Lille, France
| | - Renaud Lopes
- Inserm U1171, CHU Lille, University of Lille, F-59000, Lille, France.,Department of Neuroradiology, CHU Lille, F-59000, Lille, France
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38
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Chen Y, Liu P, Wang Y, Peng G. Neural Mechanisms of Visual Dysfunction in Posterior Cortical Atrophy. Front Neurol 2019; 10:670. [PMID: 31293507 PMCID: PMC6603128 DOI: 10.3389/fneur.2019.00670] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Accepted: 06/07/2019] [Indexed: 11/13/2022] Open
Abstract
Posterior cortical atrophy (PCA) is characterized predominantly by visual dysfunction that arises from bilateral impairments in occipital, parietal, and temporal regions of the brain. PCA is clinically identified based primarily on visual symptoms and neuroimaging findings. Region-specific gray and white matter deficits have been discussed in detail, and are associated with clinical manifestations that present with similar patterns of perfusion and metabolic findings. Here, we discuss both structural and functional changes in the ventral and dorsal visual streams along with their underlying relationships. We also discuss the most recent developments in neuroimaging characteristics and summarize correlations between distinct neuroimaging presentations.
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Affiliation(s)
- Yi Chen
- Department of Neurology, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Ping Liu
- Department of Neurology, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yunyun Wang
- Department of Neurology, Shengzhou People's Hospital, Shengzhou, China
| | - Guoping Peng
- Department of Neurology, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- *Correspondence: Guoping Peng
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39
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Pasquini L, Rahmani F, Maleki-Balajoo S, La Joie R, Zarei M, Sorg C, Drzezga A, Tahmasian M. Medial Temporal Lobe Disconnection and Hyperexcitability Across Alzheimer's Disease Stages. J Alzheimers Dis Rep 2019; 3:103-112. [PMID: 31259307 PMCID: PMC6597961 DOI: 10.3233/adr-190121] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
The posteromedial cortex (PMC) and medial temporal lobes (MTL) are two brain regions particularly vulnerable in Alzheimer’s disease (AD). We have reviewed the spatiotemporal patterns of amyloid-β and tau accumulation, local MTL functional alterations and MTL-PMC network reconfiguration, and propose a model to relate these elements to each other. Functional and structural MTL-PMC disconnection happen concomitant with amyloid-β plaques and neurofibrillary tau accumulation within these same regions. Ongoing disconnection is accompanied by dysfunctional intrinsic local MTL circuit hyperexcitability, which exacerbates across distinct clinical stages of AD. Our overarching model proposes a sequence of events relating the spatiotemporal patterns of amyloid-β and tau accumulation to MTL-PMC disconnection and local MTL hyperexcitability. We hypothesize that cortical PMC amyloid-β pathology induces long-range information processing deficits through functional and structural MTL-PMC dysconnectivity at early disease stages, which in turn drives local MTL circuit hyperexcitability. Intrinsic local MTL circuit hyperexcitability subsequently accelerates local age-related tau deposition, facilitating tau spread from the MTL to the PMC, eventually resulting in extensive structural degeneration of white and grey matter as the disease advances. We hope that the present model may inform future longitudinal studies needed to test the proposed sequence of events.
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Affiliation(s)
- Lorenzo Pasquini
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, USA
| | - Farzaneh Rahmani
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Somayeh Maleki-Balajoo
- Department of Biomedical Engineering, Electrical Engineering Faculty, K.N. Toosi University of Technology, Tehran, Iran.,Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran
| | - Renaud La Joie
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, USA
| | - Mojtaba Zarei
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran
| | - Christian Sorg
- Departments of Neuroradiology, Klinikum rechts der Isar, Technische Universität München, Munich, Germany.,Departments of Psychiatry, Klinikum rechts der Isar, Technische Universität München, Munich, Germany.,TUM-Neuroimaging Center (TUM-NIC), Technische Universität München, Munich, Germany
| | - Alexander Drzezga
- Department of Nuclear Medicine, University Hospital of Cologne, Cologne, Germany
| | - Masoud Tahmasian
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran
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40
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Bagattini C, Mutanen TP, Fracassi C, Manenti R, Cotelli M, Ilmoniemi RJ, Miniussi C, Bortoletto M. Predicting Alzheimer's disease severity by means of TMS-EEG coregistration. Neurobiol Aging 2019; 80:38-45. [PMID: 31077959 DOI: 10.1016/j.neurobiolaging.2019.04.008] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2019] [Revised: 04/04/2019] [Accepted: 04/08/2019] [Indexed: 12/12/2022]
Abstract
Clinical manifestations of Alzheimer's disease (AD) are associated with a breakdown in large-scale communication, such that AD may be considered as a "disconnection syndrome." An established method to test effective connectivity is the combination of transcranial magnetic stimulation with electroencephalography (TMS-EEG) because the TMS-induced cortical response propagates to distant anatomically connected regions. To investigate whether prefrontal connectivity alterations may predict disease severity, we explored the relationship of dorsolateral prefrontal cortex connectivity (derived from TMS-EEG) with cognitive decline (measured with Mini Mental State Examination and a face-name association memory task) in 26 patients with AD. The amplitude of TMS-EEG evoked component P30, which was found to be generated in the right superior parietal cortex, predicted Mini Mental State Examination and face-name memory scores: higher P30 amplitudes predicted poorer cognitive and memory performances. The present results indicate that advancing disease severity might be associated with effective connectivity increase involving long-distance frontoparietal connections, which might represent a maladaptive pathogenic mechanism reflecting a damaged excitatory-inhibitory balance between anterior and posterior regions.
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Affiliation(s)
- Chiara Bagattini
- Cognitive Neuroscience Section, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.
| | - Tuomas P Mutanen
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland; Centre for Cognitive Neuroimaging, University of Glasgow, Glasgow, UK
| | - Claudia Fracassi
- Cognitive Neuroscience Section, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Rosa Manenti
- Neuropsychology Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Maria Cotelli
- Neuropsychology Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Risto J Ilmoniemi
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
| | - Carlo Miniussi
- Cognitive Neuroscience Section, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy; Center for Mind/Brain Sciences- CIMeC, University of Trento, Rovereto, Italy
| | - Marta Bortoletto
- Cognitive Neuroscience Section, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
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41
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Pini L, Manenti R, Cotelli M, Pizzini FB, Frisoni GB, Pievani M. Non-Invasive Brain Stimulation in Dementia: A Complex Network Story. NEURODEGENER DIS 2019; 18:281-301. [PMID: 30695786 DOI: 10.1159/000495945] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2018] [Accepted: 11/30/2018] [Indexed: 11/19/2022] Open
Abstract
Non-invasive brain stimulation (NIBS) is emerging as a promising rehabilitation tool for a number of neurodegenerative diseases. However, the therapeutic mechanisms of NIBS are not completely understood. In this review, we will summarize NIBS results in the context of brain imaging studies of functional connectivity and metabolites to gain insight into the possible mechanisms underlying recovery. We will briefly discuss how the clinical manifestations of common neurodegenerative disorders may be related with aberrant connectivity within large-scale neural networks. We will then focus on recent studies combining resting-state functional magnetic resonance imaging with NIBS to delineate how stimulation of different brain regions induce complex network modifications, both at the local and distal level. Moreover, we will review studies combining magnetic resonance spectroscopy and NIBS to investigate how microscale changes are related to modifications of large-scale networks. Finally, we will re-examine previous NIBS studies in dementia in light of this network perspective. A better understanding of NIBS impact on the functionality of large-scale brain networks may be useful to design beneficial treatments for neurodegenerative disorders.
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Affiliation(s)
- Lorenzo Pini
- Laboratory Alzheimer's Neuroimaging & Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.,Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Rosa Manenti
- Neuropsychology Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Maria Cotelli
- Neuropsychology Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Francesca B Pizzini
- Neuroradiology, Department of Diagnostics and Pathology, Verona University Hospital, Verona, Italy
| | - Giovanni B Frisoni
- Laboratory Alzheimer's Neuroimaging & Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.,University Hospitals and University of Geneva, Geneva, Switzerland
| | - Michela Pievani
- Laboratory Alzheimer's Neuroimaging & Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy,
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42
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Risacher SL, Saykin AJ. Neuroimaging in aging and neurologic diseases. HANDBOOK OF CLINICAL NEUROLOGY 2019; 167:191-227. [PMID: 31753134 DOI: 10.1016/b978-0-12-804766-8.00012-1] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Neuroimaging biomarkers for neurologic diseases are important tools, both for understanding pathology associated with cognitive and clinical symptoms and for differential diagnosis. This chapter explores neuroimaging measures, including structural and functional measures from magnetic resonance imaging (MRI) and molecular measures primarily from positron emission tomography (PET), in healthy aging adults and in a number of neurologic diseases. The spectrum covers neuroimaging measures from normal aging to a variety of dementias: late-onset Alzheimer's disease [AD; including mild cognitive impairment (MCI)], familial and nonfamilial early-onset AD, atypical AD syndromes, posterior cortical atrophy (PCA), logopenic aphasia (lvPPA), cerebral amyloid angiopathy (CAA), vascular dementia (VaD), sporadic and familial behavioral-variant frontotemporal dementia (bvFTD), semantic dementia (SD), progressive nonfluent aphasia (PNFA), frontotemporal dementia with motor neuron disease (FTD-MND), frontotemporal dementia with amyotrophic lateral sclerosis (FTD-ALS), corticobasal degeneration (CBD), progressive supranuclear palsy (PSP), dementia with Lewy bodies (DLB), Parkinson's disease (PD) with and without dementia, and multiple systems atrophy (MSA). We also include a discussion of the appropriate use criteria (AUC) for amyloid imaging and conclude with a discussion of differential diagnosis of neurologic dementia disorders in the context of neuroimaging.
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Affiliation(s)
- Shannon L Risacher
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Andrew J Saykin
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, United States.
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43
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Li KC, Luo X, Zeng QZ, Xu XJ, Huang PY, Shen ZJ, Xu JJ, Zhou J, Zhang MM. Distinct Patterns of Interhemispheric Connectivity in Patients With Early- and Late-Onset Alzheimer's Disease. Front Aging Neurosci 2018; 10:261. [PMID: 30237764 PMCID: PMC6136638 DOI: 10.3389/fnagi.2018.00261] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2018] [Accepted: 08/14/2018] [Indexed: 12/18/2022] Open
Abstract
Background: Early-onset Alzheimer’s disease (EOAD) presents a different clinical profile than late-onset Alzheimer’s disease (LOAD). Neuroimaging studies have demonstrated that patients with EOAD present more atrophy and functional disconnection than LOAD patients. However, it remains unknown whether the interhemispheric functional disconnection or its underlying structural impairment contributes to the different clinical profiles of EOAD and LOAD. Methods: According to the arbitrary cut-off age of 65, we included 22 EOAD patients, 27 LOAD patients and 38 healthy controls (further divided into 21 relatively young and 17 old controls). Participants underwent resting-state functional MRI, diffusion tensor imaging (DTI) and comprehensive neuropsychological assessments. We used voxel-mirrored homotopic connectivity (VMHC) to examine interhemispheric functional connectivity. Then, we calculated the diffusion index based on tract-based spatial statistics (TBSS). Two-sample t-tests were used to assess the interhemispheric connectivity differences between each patient group and its corresponding control group. Results: We found that the EOAD patients had lower VMHC in the hippocampus, parahippocampal gyrus (PHG), superior temporal gyrus (STG) and inferior parietal cortex (IPC) than did controls. Consistently, the EOAD patients exhibited white matter (WM) tract impairment in the posterior regions. On the other hand, the LOAD patients displayed increased VMHC and impaired WM tracts in the frontal region. Correlation analyses showed that VMHC in the IPC was related to executive function in the EOAD patients (r = −0.67, P < 0.05). Conclusion: In contrast to the LOAD patients, patients with EOAD exhibited more widely disrupted interhemispheric functional and structural connectivity, which overlapped well across brain regions. In addition, for the EOAD patients, decreased interhemispheric connectivity related to executive deficits. Our study suggested that different interhemispheric connectivity damage patterns may contribute to the distinct clinical profiles in EOAD and LOAD.
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Affiliation(s)
- Kai-Cheng Li
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiao Luo
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Qing-Ze Zeng
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiao-Jun Xu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Pei-Yu Huang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Zhu-Jing Shen
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Jing-Jing Xu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Jiong Zhou
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Min-Ming Zhang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
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44
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Castellazzi G, Debernard L, Melzer TR, Dalrymple-Alford JC, D'Angelo E, Miller DH, Gandini Wheeler-Kingshott CAM, Mason DF. Functional Connectivity Alterations Reveal Complex Mechanisms Based on Clinical and Radiological Status in Mild Relapsing Remitting Multiple Sclerosis. Front Neurol 2018; 9:690. [PMID: 30177910 PMCID: PMC6109785 DOI: 10.3389/fneur.2018.00690] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2018] [Accepted: 07/30/2018] [Indexed: 11/13/2022] Open
Abstract
Resting state functional MRI (rs-fMRI) has provided important insights into functional reorganization in subjects with Multiple Sclerosis (MS) at different stage of disease. In this cross-sectional study we first assessed, by means of rs-fMRI, the impact of overall T2 lesion load (T2LL) and MS severity score (MSSS) on resting state networks (RSNs) in 62 relapsing remitting MS (RRMS) patients with mild disability (MSSS < 3). Independent Component Analysis (ICA) followed by dual regression analysis confirmed functional connectivity (FC) alterations of many RSNs in RRMS subjects compared to healthy controls. The anterior default mode network (DMNa) and the superior precuneus network (PNsup) showed the largest areas of decreased FC, while the sensory motor networks area M1 (SMNm1) and the medial visual network (MVN) showed the largest areas of increased FC. In order to better understand the nature of these alterations as well as the mechanisms of functional alterations in MS we proposed a method, based on linear regression, that takes into account FC changes and their correlation with T2LL and MSSS. Depending on the sign of the correlation between FC and T2LL, and furthermore the sign of the correlation with MSSS, we suggested the following possible underlying mechanisms to interpret altered FC: (1) FC reduction driven by MS lesions, (2) "true" functional compensatory mechanism, (3a) functional compensation attempt, (3b) "false" functional compensation, (4a) neurodegeneration, (4b) pre-symptomatic condition (damage precedes MS clinical manifestation). Our data shows areas satisfying 4 of these 6 conditions (i.e., 1,2,3b,4b), supporting the suggestion that increased FC has a complex nature that may exceed the simplistic assumption of an underlying compensatory mechanism attempting to limit the brain damage caused by MS progression. Exploring differences between RRMS subjects with short disease duration (MSshort) and RRMS with similar disability but longer disease duration (MSlong), we found that MSshort and MSlong were characterized by clearly distinct pattern of FC, involving predominantly sensory and cognitive networks respectively. Overall, these results suggest that the analysis of FC alterations in multiple large-scale networks in relation to radiological (T2LL) and clinical (MSSS, disease duration) status may provide new insights into the pathophysiology of relapse onset MS evolution.
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Affiliation(s)
- Gloria Castellazzi
- NMR Research Unit, Department of Neuroinflammation, Queen Square MS Centre, UCL Institute of Neurology, London, United Kingdom.,Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | - Laetitia Debernard
- New Zealand Brain Research Institute, Christchurch, New Zealand.,Department of Medicine, University of Otago, Christchurch, New Zealand
| | - Tracy R Melzer
- New Zealand Brain Research Institute, Christchurch, New Zealand.,Department of Medicine, University of Otago, Christchurch, New Zealand.,Brain Research New Zealand, Auckland, New Zealand
| | - John C Dalrymple-Alford
- New Zealand Brain Research Institute, Christchurch, New Zealand.,Brain Research New Zealand, Auckland, New Zealand.,Department of Psychology, University of Canterbury, Christchurch, New Zealand
| | - Egidio D'Angelo
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.,Brain Connectivity Center, IRCCS Mondino Foundation, Pavia, Italy
| | - David H Miller
- NMR Research Unit, Department of Neuroinflammation, Queen Square MS Centre, UCL Institute of Neurology, London, United Kingdom.,New Zealand Brain Research Institute, Christchurch, New Zealand.,Department of Medicine, University of Otago, Christchurch, New Zealand
| | - Claudia A M Gandini Wheeler-Kingshott
- NMR Research Unit, Department of Neuroinflammation, Queen Square MS Centre, UCL Institute of Neurology, London, United Kingdom.,Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.,Brain MRI 3T Center, IRCCS Mondino Foundation, Pavia, Italy
| | - Deborah F Mason
- New Zealand Brain Research Institute, Christchurch, New Zealand.,Department of Medicine, University of Otago, Christchurch, New Zealand.,Department of Neurology, Christchurch Hospital, Christchurch, New Zealand
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45
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Sánchez SM, Abulafia C, Duarte-Abritta B, de Guevara MSL, Castro MN, Drucaroff L, Sevlever G, Nemeroff CB, Vigo DE, Loewenstein DA, Villarreal MF, Guinjoan SM. Failure to Recover from Proactive Semantic Interference and Abnormal Limbic Connectivity in Asymptomatic, Middle-Aged Offspring of Patients with Late-Onset Alzheimer's Disease. J Alzheimers Dis 2018; 60:1183-1193. [PMID: 28984601 DOI: 10.3233/jad-170491] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
BACKGROUND We have obtained previous evidence of limbic dysfunction in middle-aged, asymptomatic offspring of late-onset Alzheimer's disease (LOAD) patients, and failure to recover from proactive semantic interference has been shown to be a sensitive cognitive test in other groups at risk for LOAD. OBJECTIVE To assess the effects of specific proactive semantic interference deficits as they relate to functional magnetic resonance imaging (fMRI) neocortical and limbic functional connectivity in middle aged offspring of individuals with LOAD (O-LOAD) and age-equivalent controls. METHODS We examined 21 O-LOAD and 20 controls without family history of neurodegenerative disorders (CS) on traditional measures of cognitive functioning and the LASSI-L, a novel semantic interference test uniquely sensitive to the failure to recover from proactive interference (frPSI). Cognitive tests then were correlated to fMRI connectivity of seeds located in entorhinal cortex and anterodorsal thalamic nuclei among O-LOAD and CS participants. RESULTS Relative to CS, O-LOAD participants evidenced lower connectivity between entorhinal cortex and orbitofrontal, anterior cingulate, and anterior temporal cortex. In the offspring of LOAD patients, LASSI-L measures of frPSI were inversely associated with connectivity between anterodorsal thalamus and contralateral posterior cingulate. Intrusions on the task related to frPSI were inversely correlated with a widespread connectivity network involving hippocampal, insular, posterior cingulate, and dorsolateral prefrontal cortices, along with precunei and anterior thalamus in this group. Different patterns of connectivity associated with frPSI were observed among controls. CONCLUSION The present results suggest that both semantic interference deficits and connectivity abnormalities might reflect limbic circuit dysfunction as a very early clinical signature of LOAD pathology, as previously demonstrated for other limbic phenotypes, such as sleep and circadian alterations.
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Affiliation(s)
- Stella M Sánchez
- Service of Psychiatry, FLENI Foundation, Buenos Aires, Argentina.,National Council for Scientific and Technological Research (CONICET), Argentina.,Department of Physics (FCEyN), University of Buenos Aires, Argentina
| | - Carolina Abulafia
- Service of Psychiatry, FLENI Foundation, Buenos Aires, Argentina.,National Council for Scientific and Technological Research (CONICET), Argentina.,Institute for Biomedical Research (BIOMED), Pontifical Catholic University of Argentina, and The National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
| | | | - M Soledad Ladrón de Guevara
- Service of Psychiatry, FLENI Foundation, Buenos Aires, Argentina.,National Council for Scientific and Technological Research (CONICET), Argentina
| | - Mariana N Castro
- Service of Psychiatry, FLENI Foundation, Buenos Aires, Argentina.,National Council for Scientific and Technological Research (CONICET), Argentina.,Department of Psychiatry and Mental Health, University of Buenos Aires School of Medicine, Argentina
| | - Lucas Drucaroff
- Service of Psychiatry, FLENI Foundation, Buenos Aires, Argentina.,National Council for Scientific and Technological Research (CONICET), Argentina.,Department of Psychiatry and Mental Health, University of Buenos Aires School of Medicine, Argentina
| | - Gustavo Sevlever
- Department of Neuropathology and Molecular Biology, FLENI Foundation, Buenos Aires, Argentina
| | - Charles B Nemeroff
- Department of Psychiatry and Behavioral Sciences and Center on Aging, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Daniel E Vigo
- National Council for Scientific and Technological Research (CONICET), Argentina.,Institute for Biomedical Research (BIOMED), Pontifical Catholic University of Argentina, and The National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
| | - David A Loewenstein
- Department of Psychiatry and Behavioral Sciences and Center on Aging, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Mirta F Villarreal
- Service of Psychiatry, FLENI Foundation, Buenos Aires, Argentina.,National Council for Scientific and Technological Research (CONICET), Argentina.,Department of Physics (FCEyN), University of Buenos Aires, Argentina
| | - Salvador M Guinjoan
- Service of Psychiatry, FLENI Foundation, Buenos Aires, Argentina.,National Council for Scientific and Technological Research (CONICET), Argentina.,Department of Psychiatry and Mental Health, University of Buenos Aires School of Medicine, Argentina.,Neurophysiology I, University of Buenos Aires School of Psychology, Argentina
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46
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Sitnikova TA, Hughes JW, Ahlfors SP, Woolrich MW, Salat DH. Short timescale abnormalities in the states of spontaneous synchrony in the functional neural networks in Alzheimer's disease. NEUROIMAGE-CLINICAL 2018; 20:128-152. [PMID: 30094163 PMCID: PMC6077178 DOI: 10.1016/j.nicl.2018.05.028] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/12/2017] [Revised: 04/20/2018] [Accepted: 05/20/2018] [Indexed: 10/28/2022]
Abstract
Alzheimer's disease (AD) is a prevalent neurodegenerative condition that can lead to severe cognitive and functional deterioration. Functional magnetic resonance imaging (fMRI) revealed abnormalities in AD in intrinsic synchronization between spatially separate regions in the so-called default mode network (DMN) of the brain. To understand the relationship between this disruption in large-scale synchrony and the cognitive impairment in AD, it is critical to determine whether and how the deficit in the low frequency hemodynamic fluctuations recorded by fMRI translates to much faster timescales of memory and other cognitive processes. The present study employed magnetoencephalography (MEG) and a Hidden Markov Model (HMM) approach to estimate spontaneous synchrony variations in the functional neural networks with high temporal resolution. In a group of cognitively healthy (CH) older adults, we found transient (mean duration of 150-250 ms) network activity states, which were visited in a rapid succession, and were characterized by spatially coordinated changes in the amplitude of source-localized electrophysiological oscillations. The inferred states were similar to those previously observed in younger participants using MEG, and the estimated cortical source distributions of the state-specific activity resembled the classic functional neural networks, such as the DMN. In patients with AD, inferred network states were different from those of the CH group in short-scale timing and oscillatory features. The state of increased oscillatory amplitudes in the regions overlapping the DMN was visited less often in AD and for shorter periods of time, suggesting that spontaneous synchronization in this network was less likely and less stable in the patients. During the visits to this state, in some DMN nodes, the amplitude change in the higher-frequency (8-30 Hz) oscillations was less robust in the AD than CH group. These findings highlight relevance of studying short-scale temporal evolution of spontaneous activity in functional neural networks to understanding the AD pathophysiology. Capacity of flexible intrinsic synchronization in the DMN may be crucial for memory and other higher cognitive functions. Our analysis yielded metrics that quantify distinct features of the neural synchrony disorder in AD and may offer sensitive indicators of the neural network health for future investigations.
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Affiliation(s)
- Tatiana A Sitnikova
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA; Harvard Medical School, Boston, MA 02115, USA.
| | - Jeremy W Hughes
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA.
| | - Seppo P Ahlfors
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA; Harvard Medical School, Boston, MA 02115, USA.
| | - Mark W Woolrich
- Oxford Center for Human Brain Activity, University of Oxford, Oxford OX3 7JX, UK.
| | - David H Salat
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA; Harvard Medical School, Boston, MA 02115, USA.
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47
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Chen H, Su F, Ye Q, Wang Z, Shu H, Bai F. The Dose-Dependent Effects of Vascular Risk Factors on Dynamic Compensatory Neural Processes in Mild Cognitive Impairment. Front Aging Neurosci 2018; 10:131. [PMID: 29867442 PMCID: PMC5951955 DOI: 10.3389/fnagi.2018.00131] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2017] [Accepted: 04/20/2018] [Indexed: 01/14/2023] Open
Abstract
Background/Objectives: Mild cognitive impairment (MCI) has been associated with risk for Alzheimer's Disease (AD). Previous investigations have suggested that vascular risk factors (VRFs) were associated with cognitive decline and AD pathogenesis, and the intervention of VRFs may be a possible way to prevent dementia. However, in MCI, little is known about the potential impacts of VRFs on neural networks and their neural substrates, which may be a neuroimaging biomarker of the disease progression. Methods: 128 elderly Han Chinese participants (67 MCI subjects and 61 matched normal elderly) with or without VRFs (hypertension, diabetes mellitus, hypercholesterolemia, smoking and alcohol drinking) underwent the resting-state functional magnetic resonance imaging (fMRI) and neuropsychological tests. We obtained the default mode network (DMN) to identify alterations in MCI with the varying number of the VRF and analyzed the significant correlation with behavioral performance. Results: The effects of VRF on the DMN were primarily in bilateral dorsolateral prefrontal cortex (DLPFC) (i.e., middle frontal gyrus). Normal elderly showed the gradually increased functional activity of DLPFC, while a fluctuant activation of DLPFC was displayed in MCI with the growing number of the VRF. Interestingly, the left DLPFC further displayed significantly dynamic correlation with executive function as the variation of VRF loading. Initial level of compensation was observed in normal aging and none-vascular risk factor (NVRF) MCI, while these compensatory neural processes were suppressed in One-VRF MCI and were subsequently re-aroused in Over-One-VRF MCI. Conclusions: These findings suggested that the dose-dependent effects of VRF on DLPFC were highlighted in MCI, and the dynamic compensatory neural processes that fluctuated along with variations of VRF loading could be key role in the progression of MCI.
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Affiliation(s)
- Haifeng Chen
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Fan Su
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Qing Ye
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Zan Wang
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Hao Shu
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Feng Bai
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
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Peterson AC, Li CSR. Noradrenergic Dysfunction in Alzheimer's and Parkinson's Diseases-An Overview of Imaging Studies. Front Aging Neurosci 2018; 10:127. [PMID: 29765316 PMCID: PMC5938376 DOI: 10.3389/fnagi.2018.00127] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2017] [Accepted: 04/16/2018] [Indexed: 12/31/2022] Open
Abstract
Noradrenergic dysfunction contributes to cognitive impairment in Alzheimer's Disease (AD) and Parkinson's Disease (PD). Conventional therapeutic strategies seek to enhance cholinergic and dopaminergic neurotransmission in AD and PD, respectively, and few studies have examined noradrenergic dysfunction as a target for medication development. We review the literature of noradrenergic dysfunction in AD and PD with a focus on human imaging studies that implicate the locus coeruleus (LC) circuit. The LC sends noradrenergic projections diffusely throughout the cerebral cortex and plays a critical role in attention, learning, working memory, and cognitive control. The LC undergoes considerable degeneration in both AD and PD. Advances in magnetic resonance imaging have facilitated greater understanding of how structural and functional alteration of the LC may contribute to cognitive decline in AD and PD. We discuss the potential roles of the noradrenergic system in the pathogenesis of AD and PD with an emphasis on postmortem anatomical studies, structural MRI studies, and functional MRI studies, where we highlight changes in LC connectivity with the default mode network (DMN). LC degeneration may accompany deficient capacity in suppressing DMN activity and increasing saliency and task control network activities to meet behavioral challenges. We finish by proposing potential and new directions of research to address noradrenergic dysfunction in AD and PD.
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Affiliation(s)
- Andrew C Peterson
- Frank H. Netter MD School of Medicine, Quinnipiac University, North Haven, CT, United States.,Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
| | - Chiang-Shan R Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States.,Department of Neuroscience, Yale University School of Medicine, New Haven, CT, United States.,Interdepartmental Neuroscience Program, Yale University School of Medicine, New Haven, CT, United States
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What We Know About the Brain Structure-Function Relationship. Behav Sci (Basel) 2018; 8:bs8040039. [PMID: 29670045 PMCID: PMC5946098 DOI: 10.3390/bs8040039] [Citation(s) in RCA: 65] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2018] [Revised: 04/11/2018] [Accepted: 04/16/2018] [Indexed: 11/21/2022] Open
Abstract
How the human brain works is still a question, as is its implication with brain architecture: the non-trivial structure–function relationship. The main hypothesis is that the anatomic architecture conditions, but does not determine, the neural network dynamic. The functional connectivity cannot be explained only considering the anatomical substrate. This involves complex and controversial aspects of the neuroscience field and that the methods and methodologies to obtain structural and functional connectivity are not always rigorously applied. The goal of the present article is to discuss about the progress made to elucidate the structure–function relationship of the Central Nervous System, particularly at the brain level, based on results from human and animal studies. The current novel systems and neuroimaging techniques with high resolutive physio-structural capacity have brought about the development of an integral framework of different structural and morphometric tools such as image processing, computational modeling and graph theory. Different laboratories have contributed with in vivo, in vitro and computational/mathematical models to study the intrinsic neural activity patterns based on anatomical connections. We conclude that multi-modal techniques of neuroimaging are required such as an improvement on methodologies for obtaining structural and functional connectivity. Even though simulations of the intrinsic neural activity based on anatomical connectivity can reproduce much of the observed patterns of empirical functional connectivity, future models should be multifactorial to elucidate multi-scale relationships and to infer disorder mechanisms.
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50
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Hohenfeld C, Werner CJ, Reetz K. Resting-state connectivity in neurodegenerative disorders: Is there potential for an imaging biomarker? Neuroimage Clin 2018; 18:849-870. [PMID: 29876270 PMCID: PMC5988031 DOI: 10.1016/j.nicl.2018.03.013] [Citation(s) in RCA: 145] [Impact Index Per Article: 24.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2017] [Revised: 02/06/2018] [Accepted: 03/14/2018] [Indexed: 12/14/2022]
Abstract
Biomarkers in whichever modality are tremendously important in diagnosing of disease, tracking disease progression and clinical trials. This applies in particular for disorders with a long disease course including pre-symptomatic stages, in which only subtle signs of clinical progression can be observed. Magnetic resonance imaging (MRI) biomarkers hold particular promise due to their relative ease of use, cost-effectiveness and non-invasivity. Studies measuring resting-state functional MR connectivity have become increasingly common during recent years and are well established in neuroscience and related fields. Its increasing application does of course also include clinical settings and therein neurodegenerative diseases. In the present review, we critically summarise the state of the literature on resting-state functional connectivity as measured with functional MRI in neurodegenerative disorders. In addition to an overview of the results, we briefly outline the methods applied to the concept of resting-state functional connectivity. While there are many different neurodegenerative disorders cumulatively affecting a substantial number of patients, for most of them studies on resting-state fMRI are lacking. Plentiful amounts of papers are available for Alzheimer's disease (AD) and Parkinson's disease (PD), but only few works being available for the less common neurodegenerative diseases. This allows some conclusions on the potential of resting-state fMRI acting as a biomarker for the aforementioned two diseases, but only tentative statements for the others. For AD, the literature contains a relatively strong consensus regarding an impairment of the connectivity of the default mode network compared to healthy individuals. However, for AD there is no considerable documentation on how that alteration develops longitudinally with the progression of the disease. For PD, the available research points towards alterations of connectivity mainly in limbic and motor related regions and networks, but drawing conclusions for PD has to be done with caution due to a relative heterogeneity of the disease. For rare neurodegenerative diseases, no clear conclusions can be drawn due to the few published results. Nevertheless, summarising available data points towards characteristic connectivity alterations in Huntington's disease, frontotemporal dementia, dementia with Lewy bodies, multiple systems atrophy and the spinocerebellar ataxias. Overall at this point in time, the data on AD are most promising towards the eventual use of resting-state fMRI as an imaging biomarker, although there remain issues such as reproducibility of results and a lack of data demonstrating longitudinal changes. Improved methods providing more precise classifications as well as resting-state network changes that are sensitive to disease progression or therapeutic intervention are highly desirable, before routine clinical use could eventually become a reality.
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Affiliation(s)
- Christian Hohenfeld
- RWTH Aachen University, Department of Neurology, Aachen, Germany; JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Forschungszentrum Jülich GmbH and RWTH Aachen University, Aachen, Germany
| | - Cornelius J Werner
- RWTH Aachen University, Department of Neurology, Aachen, Germany; RWTH Aachen University, Section Interdisciplinary Geriatrics, Aachen, Germany
| | - Kathrin Reetz
- RWTH Aachen University, Department of Neurology, Aachen, Germany; JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Forschungszentrum Jülich GmbH and RWTH Aachen University, Aachen, Germany.
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