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Yao C, Shan Y, Cui B, Chen Z, Bi S, Wang T, Yan S, Lu J. Hyperconnectivity and Connectome Gradient Dysfunction of Cerebello-Thalamo-Cortical Circuitry in Alzheimer's Disease Spectrum Disorders. CEREBELLUM (LONDON, ENGLAND) 2025; 24:43. [PMID: 39913059 DOI: 10.1007/s12311-025-01792-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 01/17/2025] [Indexed: 02/07/2025]
Abstract
Cerebellar functional connectivity changes have been reported in Alzheimer's disease (AD), but a comprehensive framework integrating these findings is lacking. This retrospective study investigates the cerebello-thalamo-cortical (CTC) circuit in AD, using functional gradient analysis to elucidate deficits and potential biomarkers. We analyzed data from 246 participants enrolled in the Alzheimer's Disease Neuroimaging Initiative (ADNI-3; NCT02854033), including 58 with AD, 103 with mild cognitive impairment (MCI), and 85 cognitively normal (CN) controls, matched for age and sex. All individuals underwent comprehensive neuropsychological assessments (MMSE, MoCA, ADAS-Cog) and MRI scans. We extracted mean time series for 270 brain regions (an extended Power atlas) and computed pairwise functional connectivity, focusing on CTC circuitry. Thalamic and cerebellar connectivity gradients were derived using voxel-wise correlation matrices and the BrainSpace toolbox, defining thalamic and cerebellar masks from the Melbourne subcortical atlas and AAL atlas, respectively. ANCOVA with post hoc analyses, controlling for age and sex, was conducted to assess abnormal CTC connectivity across AD, MCI, and CN groups. LASSO regression identified edges within the CTC circuitry that significantly differed between AD and CN, MCI and CN, AD and MCI, as well as was used to construct Logistic classification model. Pearson correlations were performed to examine relationships between mean CTC connectivity, individual edges, and cognitive scores (MMSE, MoCA, ADAS-Cog). To explore the hierarchical organization of the thalamus and cerebellum, global gradient distributions were compared across groups using two-sample Kolmogorov-Smirnov tests. Additionally, ANCOVA was applied to compare subfield- and functional-level gradients of the thalamus and cerebellum among AD, MCI, and CN. False discovery rate (FDR) corrections were used, setting the statistical significance threshold was set at P < 0.05. AD and MCI individuals exhibited increased CTC connectivity compared to CN (all P < 0.05). Average CTC connectivity did not correlate with cognitive scores (P > 0.05), but specific CTC edges were correlated. LASSO regression identified 20 discriminative edges, achieving high accuracy in AD-CN classification (AUC = 0.92 training, AUC = 0.80 test). Thalamic and cerebellar gradient distributions differed significantly across groups (all P < 0.05), with specific regions showing distinct gradient scores. Five cerebellar functional networks exhibited decreased gradient scores. Significant CTC hyperconnectivity in AD and MCI compared with CN suggests early thalamic and cerebellar dysregulation. Classification analyses effectively distinguished AD vs. CN but were moderate for MCI vs. CN and limited for MCI vs. AD. Gradient analyses revealed global- and subfield-level disruptions in AD, emphasizing the role of thalamic and cerebellar interactions in cognitive decline and offering potential diagnostic markers and therapeutic targets.
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Affiliation(s)
- Chenyang Yao
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
- Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Yi Shan
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
- Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Bixiao Cui
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
- Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Zhigeng Chen
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
- Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Sheng Bi
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
- Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Tao Wang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
- Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Shaozhen Yan
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital Capital Medical University, Beijing, China.
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China.
- Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China.
| | - Jie Lu
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital Capital Medical University, Beijing, China.
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China.
- Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China.
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Xue C, Zheng D, Ruan Y, Guo W, Hu J. Alteration in temporal-cerebellar effective connectivity can effectively distinguish stable and progressive mild cognitive impairment. Front Aging Neurosci 2024; 16:1442721. [PMID: 39267723 PMCID: PMC11390694 DOI: 10.3389/fnagi.2024.1442721] [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: 06/02/2024] [Accepted: 08/20/2024] [Indexed: 09/15/2024] Open
Abstract
Background Stable mild cognitive impairment (sMCI) and progressive mild cognitive impairment (pMCI) represent two distinct subtypes of mild cognitive impairment (MCI). Early and effective diagnosis and accurate differentiation between sMCI and pMCI are crucial for administering targeted early intervention and preventing cognitive decline. This study investigated the intrinsic dysconnectivity patterns in sMCI and pMCI based on degree centrality (DC) and effective connectivity (EC) analyses, with the goal of uncovering shared and distinct neuroimaging mechanisms between subtypes. Methods Resting-state functional magnetic resonance imaging combined with DC analysis was used to explore the functional connectivity density in 42 patients with sMCI, 31 patients with pMCI, and 82 healthy control (HC) participants. Granger causality analysis was used to assess changes in EC based on the significant clusters found in DC. Furthermore, correlation analysis was conducted to examine the associations between altered DC/EC values and cognitive function. Receiver operating characteristic curve analysis was performed to determine the accuracy of abnormal DC and EC values in distinguishing sMCI from pMCI. Results Compared with the HC group, both pMCI and sMCI groups exhibited increased DC in the left inferior temporal gyrus (ITG), left posterior cerebellum lobe (CPL), and right cerebellum anterior lobe (CAL), along with decreased DC in the left medial frontal gyrus. Moreover, the sMCI group displayed reduced EC from the right CAL to bilateral CPL, left superior temporal gyrus, and bilateral caudate compared with HC. pMCI demonstrated elevated EC from the right CAL to left ITG, which was linked to episodic memory and executive function. Notably, the EC from the right CAL to the right ITG effectively distinguished sMCI from pMCI, with sensitivity, specificity, and accuracy of 0.5806, 0.9512, and 0.828, respectively. Conclusion This study uncovered shared and distinct alterations in DC and EC between sMCI and pMCI, highlighting their involvement in cognitive function. Of particular significance are the unidirectional EC disruptions from the cerebellum to the temporal lobe, which serve as a discriminating factor between sMCI and pMCI and provide a new perspective for understanding the temporal-cerebellum. These findings offer novel insights into the neural circuit mechanisms involving the temporal-cerebellum connection in MCI.
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Affiliation(s)
- Chen Xue
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Darui Zheng
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Yiming Ruan
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Wenxuan Guo
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Jun Hu
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
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Yang C, Liu G, Chen X, Le W. Cerebellum in Alzheimer's disease and other neurodegenerative diseases: an emerging research frontier. MedComm (Beijing) 2024; 5:e638. [PMID: 39006764 PMCID: PMC11245631 DOI: 10.1002/mco2.638] [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: 10/30/2023] [Revised: 06/04/2024] [Accepted: 06/12/2024] [Indexed: 07/16/2024] Open
Abstract
The cerebellum is crucial for both motor and nonmotor functions. Alzheimer's disease (AD), alongside other dementias such as vascular dementia (VaD), Lewy body dementia (DLB), and frontotemporal dementia (FTD), as well as other neurodegenerative diseases (NDs) like Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), Huntington's disease (HD), and spinocerebellar ataxias (SCA), are characterized by specific and non-specific neurodegenerations in central nervous system. Previously, the cerebellum's significance in these conditions was underestimated. However, advancing research has elevated its profile as a critical node in disease pathology. We comprehensively review the existing evidence to elucidate the relationship between cerebellum and the aforementioned diseases. Our findings reveal a growing body of research unequivocally establishing a link between the cerebellum and AD, other forms of dementia, and other NDs, supported by clinical evidence, pathological and biochemical profiles, structural and functional neuroimaging data, and electrophysiological findings. By contrasting cerebellar observations with those from the cerebral cortex and hippocampus, we highlight the cerebellum's distinct role in the disease processes. Furthermore, we also explore the emerging therapeutic potential of targeting cerebellum for the treatment of these diseases. This review underscores the importance of the cerebellum in these diseases, offering new insights into the disease mechanisms and novel therapeutic strategies.
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Affiliation(s)
- Cui Yang
- Institute of Neurology Sichuan Provincial People's Hospital School of Medicine University of Electronic Science and Technology of China Chengdu China
| | - Guangdong Liu
- Institute of Neurology Sichuan Provincial People's Hospital School of Medicine University of Electronic Science and Technology of China Chengdu China
| | - Xi Chen
- Institute of Neurology Sichuan Provincial People's Hospital School of Medicine University of Electronic Science and Technology of China Chengdu China
| | - Weidong Le
- Institute of Neurology Sichuan Provincial People's Hospital School of Medicine University of Electronic Science and Technology of China Chengdu China
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Arleo A, Bareš M, Bernard JA, Bogoian HR, Bruchhage MMK, Bryant P, Carlson ES, Chan CCH, Chen LK, Chung CP, Dotson VM, Filip P, Guell X, Habas C, Jacobs HIL, Kakei S, Lee TMC, Leggio M, Misiura M, Mitoma H, Olivito G, Ramanoël S, Rezaee Z, Samstag CL, Schmahmann JD, Sekiyama K, Wong CHY, Yamashita M, Manto M. Consensus Paper: Cerebellum and Ageing. CEREBELLUM (LONDON, ENGLAND) 2024; 23:802-832. [PMID: 37428408 PMCID: PMC10776824 DOI: 10.1007/s12311-023-01577-7] [Citation(s) in RCA: 23] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 06/08/2023] [Indexed: 07/11/2023]
Abstract
Given the key roles of the cerebellum in motor, cognitive, and affective operations and given the decline of brain functions with aging, cerebellar circuitry is attracting the attention of the scientific community. The cerebellum plays a key role in timing aspects of both motor and cognitive operations, including for complex tasks such as spatial navigation. Anatomically, the cerebellum is connected with the basal ganglia via disynaptic loops, and it receives inputs from nearly every region in the cerebral cortex. The current leading hypothesis is that the cerebellum builds internal models and facilitates automatic behaviors through multiple interactions with the cerebral cortex, basal ganglia and spinal cord. The cerebellum undergoes structural and functional changes with aging, being involved in mobility frailty and related cognitive impairment as observed in the physio-cognitive decline syndrome (PCDS) affecting older, functionally-preserved adults who show slowness and/or weakness. Reductions in cerebellar volume accompany aging and are at least correlated with cognitive decline. There is a strongly negative correlation between cerebellar volume and age in cross-sectional studies, often mirrored by a reduced performance in motor tasks. Still, predictive motor timing scores remain stable over various age groups despite marked cerebellar atrophy. The cerebello-frontal network could play a significant role in processing speed and impaired cerebellar function due to aging might be compensated by increasing frontal activity to optimize processing speed in the elderly. For cognitive operations, decreased functional connectivity of the default mode network (DMN) is correlated with lower performances. Neuroimaging studies highlight that the cerebellum might be involved in the cognitive decline occurring in Alzheimer's disease (AD), independently of contributions of the cerebral cortex. Grey matter volume loss in AD is distinct from that seen in normal aging, occurring initially in cerebellar posterior lobe regions, and is associated with neuronal, synaptic and beta-amyloid neuropathology. Regarding depression, structural imaging studies have identified a relationship between depressive symptoms and cerebellar gray matter volume. In particular, major depressive disorder (MDD) and higher depressive symptom burden are associated with smaller gray matter volumes in the total cerebellum as well as the posterior cerebellum, vermis, and posterior Crus I. From the genetic/epigenetic standpoint, prominent DNA methylation changes in the cerebellum with aging are both in the form of hypo- and hyper-methylation, and the presumably increased/decreased expression of certain genes might impact on motor coordination. Training influences motor skills and lifelong practice might contribute to structural maintenance of the cerebellum in old age, reducing loss of grey matter volume and therefore contributing to the maintenance of cerebellar reserve. Non-invasive cerebellar stimulation techniques are increasingly being applied to enhance cerebellar functions related to motor, cognitive, and affective operations. They might enhance cerebellar reserve in the elderly. In conclusion, macroscopic and microscopic changes occur in the cerebellum during the lifespan, with changes in structural and functional connectivity with both the cerebral cortex and basal ganglia. With the aging of the population and the impact of aging on quality of life, the panel of experts considers that there is a huge need to clarify how the effects of aging on the cerebellar circuitry modify specific motor, cognitive, and affective operations both in normal subjects and in brain disorders such as AD or MDD, with the goal of preventing symptoms or improving the motor, cognitive, and affective symptoms.
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Affiliation(s)
- Angelo Arleo
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, 17 rue Moreau, F-75012, Paris, France
| | - Martin Bareš
- First Department of Neurology, Faculty of Medicine, Masaryk University and St. Anne's Teaching Hospital, Brno, Czech Republic
- Department of Neurology, School of Medicine, University of Minnesota, Minneapolis, USA
| | - Jessica A Bernard
- Department of Psychological and Brain Sciences, Texas A&M University, 4235 TAMU, College Station, TX, 77843, USA
- Texas A&M Institute for Neuroscience, Texas A&M University, College Station, TX, USA
| | - Hannah R Bogoian
- Department of Psychology, Georgia State University, Atlanta, GA, USA
| | - Muriel M K Bruchhage
- Department of Psychology, Stavanger University, Institute of Social Sciences, Kjell Arholms Gate 41, 4021, Stavanger, Norway
- King's College London, Institute of Psychiatry, Psychology and Neuroscience, Centre for Neuroimaging Sciences, Box 89, De Crespigny Park, London, PO, SE5 8AF, UK
- Rhode Island Hospital, Department for Diagnostic Imaging, 1 Hoppin St, Providence, RI, 02903, USA
- Department of Paediatrics, Warren Alpert Medical School of Brown University, 222 Richmond St, Providence, RI, 02903, USA
| | - Patrick Bryant
- Freie Universität Berlin, Fachbereich Mathematik und Informatik, Arnimallee 12, 14195, Berlin, Germany
| | - Erik S Carlson
- Department of Psychiatry and Behavioural Sciences, University of Washington, Seattle, WA, USA
- Geriatric Research, Education and Clinical Center, Veteran's Affairs Medical Center, Puget Sound, Seattle, WA, USA
| | - Chetwyn C H Chan
- Department of Psychology, The Education University of Hong Kong, New Territories, Tai Po, Hong Kong, China
| | - Liang-Kung Chen
- Center for Healthy Longevity and Aging Sciences, National Yang Ming Chiao Tung University College of Medicine, Taipei, Taiwan
- Center for Geriatric and Gerontology, Taipei Veterans General Hospital, Taipei, Taiwan
- Taipei Municipal Gan-Dau Hospital (managed by Taipei Veterans General Hospital), Taipei, Taiwan
| | - Chih-Ping Chung
- Center for Healthy Longevity and Aging Sciences, National Yang Ming Chiao Tung University College of Medicine, Taipei, Taiwan
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Vonetta M Dotson
- Department of Psychology, Georgia State University, Atlanta, GA, USA
- Gerontology Institute, Georgia State University, Atlanta, GA, USA
| | - Pavel Filip
- Department of Neurology, Charles University, First Faculty of Medicine and General University Hospital, Prague, Czech Republic
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN, USA
| | - Xavier Guell
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Laboratory for Neuroanatomy and Cerebellar Neurobiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Christophe Habas
- CHNO Des Quinze-Vingts, INSERM-DGOS CIC 1423, 28 rue de Charenton, 75012, Paris, France
- Université Versailles St Quentin en Yvelines, Paris, France
| | - Heidi I L Jacobs
- School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, PO BOX 616, 6200, MD, Maastricht, The Netherlands
- Faculty of Psychology and Neuroscience, Department of Cognitive Neuroscience, Maastricht University, PO BOX 616, 6200, MD, Maastricht, The Netherlands
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Tatia M C Lee
- State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, China
- Laboratory of Neuropsychology and Human Neuroscience, Department of Psychology, The University of Hong Kong, Hong Kong, China
| | - Maria Leggio
- Department of Psychology, Sapienza University of Rome, Rome, Italy
- Ataxia Laboratory, I.R.C.C.S. Santa Lucia Foundation, Rome, Italy
| | - Maria Misiura
- Department of Psychology, Georgia State University, Atlanta, GA, USA
| | - Hiroshi Mitoma
- Department of Medical Education, Tokyo Medical University, Tokyo, Japan
| | - Giusy Olivito
- Department of Psychology, Sapienza University of Rome, Rome, Italy
- Ataxia Laboratory, I.R.C.C.S. Santa Lucia Foundation, Rome, Italy
| | - Stephen Ramanoël
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, 17 rue Moreau, F-75012, Paris, France
- Université Côte d'Azur, LAMHESS, Nice, France
| | - Zeynab Rezaee
- Noninvasive Neuromodulation Unit, Experimental Therapeutics & Pathophysiology Branch, National Institute of Mental Health, NIH, Bethesda, USA
| | - Colby L Samstag
- Department of Psychiatry and Behavioural Sciences, University of Washington, Seattle, WA, USA
- Geriatric Research, Education and Clinical Center, Veteran's Affairs Medical Center, Puget Sound, Seattle, WA, USA
| | - Jeremy D Schmahmann
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Laboratory for Neuroanatomy and Cerebellar Neurobiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Ataxia Center, Cognitive Behavioural neurology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Kaoru Sekiyama
- Graduate School of Advanced Integrated Studies in Human Survivability, Kyoto University, Kyoto, Japan
| | - Clive H Y Wong
- Department of Psychology, The Education University of Hong Kong, New Territories, Tai Po, Hong Kong, China
| | - Masatoshi Yamashita
- Research Center for Child Mental Development, University of Fukui, Fukui, Japan
- United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Osaka, Japan
| | - Mario Manto
- Service de Neurologie, Médiathèque Jean Jacquy, CHU-Charleroi, Charleroi, Belgium.
- Service des Neurosciences, University of Mons, Mons, Belgium.
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Mousa D, Zayed N, Yassine IA. Correlation transfer function analysis as a biomarker for Alzheimer brain plasticity using longitudinal resting-state fMRI data. Sci Rep 2023; 13:21559. [PMID: 38057476 PMCID: PMC10700324 DOI: 10.1038/s41598-023-48693-2] [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: 03/26/2023] [Accepted: 11/29/2023] [Indexed: 12/08/2023] Open
Abstract
Neural plasticity is the ability of the brain to alter itself functionally and structurally as a result of its experience. However, longitudinal changes in functional connectivity of the brain are still unrevealed in Alzheimer's disease (AD). This study aims to discover the significant connections (SCs) between brain regions for AD stages longitudinally using correlation transfer function (CorrTF) as a new biomarker for the disease progression. The dataset consists of: 29 normal controls (NC), and 23, 24, and 23 for early, late mild cognitive impairments (EMCI, LMCI), and ADs, respectively, along three distant visits. The brain was divided into 116 regions using the automated anatomical labeling atlas, where the intensity time series is calculated, and the CorrTF connections are extracted for each region. Finally, the standard t-test and ANOVA test were employed to investigate the SCs for each subject's visit. No SCs, along three visits, were found For NC subjects. The most SCs were mainly directed from cerebellum in case of EMCI and LMCI. Furthermore, the hippocampus connectivity increased in LMCI compared to EMCI whereas missed in AD. Additionally, the patterns of longitudinal changes among the different AD stages compared to Pearson Correlation were similar, for SMC, VC, DMN, and Cereb networks, while differed for EAN and SN networks. Our findings define how brain changes over time, which could help detect functional changes linked to each AD stage and better understand the disease behavior.
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Affiliation(s)
- Doaa Mousa
- Computers and Systems Department, Electronics Research Institute, Cairo, Egypt.
| | - Nourhan Zayed
- Computers and Systems Department, Electronics Research Institute, Cairo, Egypt
- Mechanical Engineering Department, The British University in Egypt, Cairo, Egypt
| | - Inas A Yassine
- Systems and Biomedical Engineering Department, Cairo University, Giza, Egypt
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Yin Z, Wang Z, Li Y, Zhou J, Chen Z, Xia M, Zhang X, Wu J, Zhao L, Liang F. Neuroimaging studies of acupuncture on Alzheimer's disease: a systematic review. BMC Complement Med Ther 2023; 23:63. [PMID: 36823586 PMCID: PMC9948384 DOI: 10.1186/s12906-023-03888-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Accepted: 02/14/2023] [Indexed: 02/25/2023] Open
Abstract
BACKGROUND Acupuncture effectively improves cognitive function in Alzheimer's disease (AD). Many neuroimaging studies have found significant brain alterations after acupuncture treatment of AD, but the underlying central modulation mechanism is unclear. OBJECTIVE This review aims to provide neuroimaging evidence to understand the central mechanisms of acupuncture in patients with AD. METHODS Relevant neuroimaging studies about acupuncture for AD were retrieved from eight English and Chinese medicine databases (PubMed, Embase, Cochrane Library, Web of Science, SinoMed, CNKI, WF, VIP) and other resources from inception of databases until June 1, 2022, and their methodological quality was assessed using RoB 2.0 and ROBINS - I. Brain neuroimaging information was extracted to investigate the potential neural mechanism of acupuncture for AD. Descriptive statistics were used for data analysis. RESULTS Thirteen neuroimaging studies involving 275 participants were included in this review, and the overall methodological quality of included studies was moderate. The approaches applied included task-state functional magnetic resonance imaging (ts-fMRI; n = 9 studies) and rest-state functional magnetic resonance imaging (rs-fMRI; n = 4 studies). All studies focused on the instant effect of acupuncture on the brains of AD participants, including the cingulate gyrus, middle frontal gyrus, and cerebellum, indicating that acupuncture may regulate the default mode, central executive, and frontoparietal networks. CONCLUSION This study provides evidence of the neural mechanisms underlying the effect of acupuncture on AD involving cognitive- and motor-associated networks. However, this evidence is still in the preliminary investigation stage. Large-scale, well-designed, multimodal neuroimaging trials are still required to provide comprehensive insight into the central mechanism underlying the effect of acupuncture on AD. (Systematic review registration at PROSPERO, No. CRD42022331527).
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Affiliation(s)
- Zihan Yin
- School of Acu-Mox and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Acupuncture Clinical Research Center of Sichuan Province, Chengdu, China
| | - Ziqi Wang
- the Fourth People's Hospital of Chengdu, Chengdu, China
| | - Yaqin Li
- School of Acu-Mox and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Jun Zhou
- School of Acu-Mox and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Zhenghong Chen
- School of Acu-Mox and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Acupuncture Clinical Research Center of Sichuan Province, Chengdu, China
| | - Manze Xia
- School of Acu-Mox and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Acupuncture Clinical Research Center of Sichuan Province, Chengdu, China
| | - Xinyue Zhang
- School of Acu-Mox and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Acupuncture Clinical Research Center of Sichuan Province, Chengdu, China
| | - Jiajing Wu
- School of Nursing, Zunyi Medical University, Zunyi, China
| | - Ling Zhao
- School of Acu-Mox and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
- Acupuncture Clinical Research Center of Sichuan Province, Chengdu, China.
| | - Fanrong Liang
- School of Acu-Mox and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
- Acupuncture Clinical Research Center of Sichuan Province, Chengdu, China.
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Rajabli F, Beecham GW, Hendrie HC, Baiyewu O, Ogunniyi A, Gao S, Kushch NA, Lipkin-Vasquez M, Hamilton-Nelson KL, Young JI, Dykxhoorn DM, Nuytemans K, Kunkle BW, Wang L, Jin F, Liu X, Feliciano-Astacio BE, Alzheimer’s Disease Sequencing Project, Alzheimer’s Disease Genetic Consortium, Schellenberg GD, Dalgard CL, Griswold AJ, Byrd GS, Reitz C, Cuccaro ML, Haines JL, Pericak-Vance MA, Vance JM. A locus at 19q13.31 significantly reduces the ApoE ε4 risk for Alzheimer's Disease in African Ancestry. PLoS Genet 2022; 18:e1009977. [PMID: 35788729 PMCID: PMC9286282 DOI: 10.1371/journal.pgen.1009977] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2021] [Revised: 07/15/2022] [Accepted: 05/27/2022] [Indexed: 11/18/2022] Open
Abstract
African descent populations have a lower Alzheimer disease risk from ApoE ε4 compared to other populations. Ancestry analysis showed that the difference in risk between African and European populations lies in the ancestral genomic background surrounding the ApoE locus (local ancestry). Identifying the mechanism(s) of this protection could lead to greater insight into the etiology of Alzheimer disease and more personalized therapeutic intervention. Our objective is to follow up the local ancestry finding and identify the genetic variants that drive this risk difference and result in a lower risk for developing Alzheimer disease in African ancestry populations. We performed association analyses using a logistic regression model with the ApoE ε4 allele as an interaction term and adjusted for genome-wide ancestry, age, and sex. Discovery analysis included imputed SNP data of 1,850 Alzheimer disease and 4,331 cognitively intact African American individuals. We performed replication analyses on 63 whole genome sequenced Alzheimer disease and 648 cognitively intact Ibadan individuals. Additionally, we reproduced results using whole-genome sequencing of 273 Alzheimer disease and 275 cognitively intact admixed Puerto Rican individuals. A further comparison was done with SNP imputation from an additional 8,463 Alzheimer disease and 11,365 cognitively intact non-Hispanic White individuals. We identified a significant interaction between the ApoE ε4 allele and the SNP rs10423769_A allele, (β = -0.54,SE = 0.12,p-value = 7.50x10-6) in the discovery data set, and replicated this finding in Ibadan (β = -1.32,SE = 0.52,p-value = 1.15x10-2) and Puerto Rican (β = -1.27,SE = 0.64,p-value = 4.91x10-2) individuals. The non-Hispanic Whites analyses showed an interaction trending in the "protective" direction but failing to pass a 0.05 significance threshold (β = -1.51,SE = 0.84,p-value = 7.26x10-2). The presence of the rs10423769_A allele reduces the odds ratio for Alzheimer disease risk from 7.2 for ApoE ε4/ε4 carriers lacking the A allele to 2.1 for ApoE ε4/ε4 carriers with at least one A allele. This locus is located approximately 2 mB upstream of the ApoE locus, in a large cluster of pregnancy specific beta-1 glycoproteins on chromosome 19 and lies within a long noncoding RNA, ENSG00000282943. This study identified a new African-ancestry specific locus that reduces the risk effect of ApoE ε4 for developing Alzheimer disease. The mechanism of the interaction with ApoEε4 is not known but suggests a novel mechanism for reducing the risk for ε4 carriers opening the possibility for potential ancestry-specific therapeutic intervention.
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Affiliation(s)
- Farid Rajabli
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America
| | - Gary W. Beecham
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, Florida, United States of America
| | - Hugh C. Hendrie
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, Indiana, United States of America
| | | | | | - Sujuan Gao
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, Indiana, United States of America
| | - Nicholas A. Kushch
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America
| | - Marina Lipkin-Vasquez
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America
| | - Kara L. Hamilton-Nelson
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America
| | - Juan I. Young
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, Florida, United States of America
| | - Derek M. Dykxhoorn
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, Florida, United States of America
| | - Karen Nuytemans
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, Florida, United States of America
| | - Brian W. Kunkle
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, Florida, United States of America
| | - Liyong Wang
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, Florida, United States of America
| | - Fulai Jin
- Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Xiaoxiao Liu
- Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, Ohio, United States of America
| | | | | | - Gerard D. Schellenberg
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States of America
| | - Clifton L. Dalgard
- Department of Anatomy, Physiology & Genetics, Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States of America
| | - Anthony J. Griswold
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, Florida, United States of America
| | - Goldie S. Byrd
- Maya Angelou Center for Health Equity, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Christiane Reitz
- Gertrude H. Sergievsky Center, Taub Institute for Research on the Aging Brain, Departments of Neurology, Psychiatry, and Epidemiology, College of Physicians and Surgeons, Columbia University, New York, New York State, United States of America
| | - Michael L. Cuccaro
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, Florida, United States of America
| | - Jonathan L. Haines
- Department of Population & Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University School of Medicine, Cleveland, Ohio, United States of America
| | - Margaret A. Pericak-Vance
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, Florida, United States of America
| | - Jeffery M. Vance
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, Florida, United States of America
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8
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Um YH, Wang SM, Kang DW, Kim NY, Lim HK. Subcortical and Cerebellar Neural Correlates of Prodromal Alzheimer’s Disease with Prolonged Sleep Latency. J Alzheimers Dis 2022; 86:565-578. [PMID: 35068468 PMCID: PMC9028620 DOI: 10.3233/jad-215460] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Background: Despite the important associations among sleep, Alzheimer’s disease (AD), subcortical structures, and the cerebellum, structural and functional magnetic resonance imaging (MRI) with regard to these regions and sleep on patients in AD trajectory are scarce. Objective: This study aimed to evaluate the influence of prolonged sleep latency on the structural and functional alterations in the subcortical and cerebellar neural correlates in amyloid-β positive amnestic mild cognitive impairment patients (Aβ+aMCI). Methods: A total of 60 patients with aMCI who were identified as amyloid positive ([18F] flutemetamol+) were recruited in the study, 24 patients with normal sleep latency (aMCI-n) and 36 patients prolonged sleep latency (aMCI-p). Cortical thickness and volumes between the two groups were compared. Volumetric analyses were implemented on the brainstem, thalamus, and hippocampus. Subcortical and cerebellar resting state functional connectivity (FC) differences were measured between the both groups through seed-to-voxel analysis. Additionally, group x Aβ interactive effects on FC values were tested with a general linear model. Result: There was a significantly decreased brainstem volume in aMCI-p subjects. We observed a significant reduction of the locus coeruleus (LC) FC with frontal, temporal, insular cortices, hippocampus, and left thalamic FC with occipital cortex. Moreover, the LC FC with occipital cortex and left hippocampal FC with frontal cortex were increased in aMCI-p subjects. In addition, there was a statistically significant group by regional standardized uptake value ratio interactions discovered in cerebro-cerebellar networks. Conclusion: The aforementioned findings suggest that prolonged sleep latency may be a detrimental factor in compromising structural and functional correlates of subcortical structures and the cerebellum, which may accelerate AD pathophysiology.
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Affiliation(s)
- Yoo Hyun Um
- Department of Psychiatry, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Sheng-Min Wang
- Department of Psychiatry, Yeouido St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Dong Woo Kang
- Department of Psychiatry, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Nak-Young Kim
- Department of Psychiatry, Keyo Hospital, Keyo Medical Foundation, Uiwang, Republic of Korea
| | - Hyun Kook Lim
- Department of Psychiatry, Yeouido St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
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