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Zhang J, Li L, Ji R, Shang D, Wen X, Hu J, Wang Y, Wu D, Zhang L, He F, Ye X, Luo B. NODDI Identifies Cognitive Associations with In Vivo Microstructural Changes in Remote Cortical Regions and Thalamocortical Pathways in Thalamic Stroke. Transl Stroke Res 2023:10.1007/s12975-023-01221-w. [PMID: 38049671 DOI: 10.1007/s12975-023-01221-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 11/23/2023] [Accepted: 11/27/2023] [Indexed: 12/06/2023]
Abstract
The roles of cerebral structures distal to isolated thalamic infarcts in cognitive deficits remain unclear. We aimed to identify the in vivo microstructural characteristics of remote gray matter (GM) and thalamic pathways and elucidate their roles across cognitive domains. Patients with isolated ischemic thalamic stroke and healthy controls underwent neuropsychological assessment and magnetic resonance imaging. Neurite orientation dispersion and density imaging (NODDI) was modeled to derive the intracellular volume fraction (VFic) and orientation dispersion index. Fiber density (FD) was determined by constrained spherical deconvolution, and tensor-derived fractional anisotropy (FA) was calculated. Voxel-wise GM analysis and thalamic pathway tractography were performed. Twenty-six patients and 26 healthy controls were included. Patients exhibited reduced VFic in remote GM regions, including ipsilesional insular and temporal subregions. The microstructural metrics VFic, FD, and FA within ipsilesional thalamic pathways decreased (false discovery rate [FDR]-p < 0.05). Noteworthy associations emerged as VFic within insular cortices (ρ = -0.791 to -0.630; FDR-p < 0.05) and FD in tracts connecting the thalamus and insula (ρ = 0.830 to 0.971; FDR-p < 0.001) were closely associated with executive function. The VFic in Brodmann area 52 (ρ = -0.839; FDR-p = 0.005) and FA within its thalamic pathway (ρ = -0.799; FDR-p = 0.003) correlated with total auditory memory scores. In conclusion, NODDI revealed neurite loss in remote normal-appearing GM regions and ipsilesional thalamic pathways in thalamic stroke. Reduced cortical dendritic density and axonal density of thalamocortical tracts in specific subregions were associated with improved cognitive functions. Subacute microstructural alterations beyond focal thalamic infarcts might reflect beneficial remodeling indicating post-stroke plasticity.
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Affiliation(s)
- Jie Zhang
- Department of Neurology, Brain Medical Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, 310003, Hangzhou, China
- Center for Rehabilitation Medicine, Rehabilitation and Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, 310014, China
| | - Lingling Li
- Department of Neurology, Dongyang People's Hospital, Wenzhou Medical University, Dongyang, 322109, China
| | - Renjie Ji
- Department of Neurology, Brain Medical Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, 310003, Hangzhou, China
| | - Desheng Shang
- Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China
| | - Xinrui Wen
- Department of Neurology, Brain Medical Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, 310003, Hangzhou, China
| | - Jun Hu
- Department of Neurology, Brain Medical Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, 310003, Hangzhou, China
| | - Yingqiao Wang
- Center for Rehabilitation Medicine, Rehabilitation and Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, 310014, China
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, 310027, China
| | - Li Zhang
- Department of Neurology, Brain Medical Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, 310003, Hangzhou, China
- Center for Rehabilitation Medicine, Rehabilitation and Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, 310014, China
| | - Fangping He
- Department of Neurology, Brain Medical Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, 310003, Hangzhou, China
| | - Xiangming Ye
- Center for Rehabilitation Medicine, Rehabilitation and Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, 310014, China
| | - Benyan Luo
- Department of Neurology, Brain Medical Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, 310003, Hangzhou, China.
- MOE Frontier Science Center for Brain Science & Brain-Machine Integration, Zhejiang University, Hangzhou, 310003, China.
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Kim H, Alvin Ang TF, Thomas RJ, Lyons MJ, Au R. Long-term blood pressure patterns in midlife and dementia in later life: Findings from the Framingham Heart Study. Alzheimers Dement 2023; 19:4357-4366. [PMID: 37394941 PMCID: PMC10597747 DOI: 10.1002/alz.13356] [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: 03/06/2023] [Revised: 05/08/2023] [Accepted: 05/09/2023] [Indexed: 07/04/2023]
Abstract
INTRODUCTION Long-term blood pressure (BP) measures, such as visit-to-visit BP variability (BPV) and cumulative BP, are strong indicators of cardiovascular risks. This study modeled up to 20 years of BP patterns representative of midlife by using BPV and cumulative BP, then examined their associations with development of dementia in later life. METHODS For 3201 individuals from the Framingham Heart Study, multivariate logistic regression analyses were performed to examine the association between long-term BP patterns during midlife and the development of dementia (ages ≥ 65). RESULTS After adjusting for covariates, every quartile increase in midlife cumulative BP was associated with a sequential increase in the risk of developing dementia (e.g., highest quartile of cumulative systolic blood pressure had approximately 2.5-fold increased risk of all-cause dementia). BPV was not significantly associated with dementia. DISCUSSION Findings suggest that cumulative BP over the course of midlife predicts risk of dementia in later life. HIGHLIGHTS Long-term blood pressure (BP) patterns are strong indicators of vascular risks. Cumulative BP and BP variability (BPV) were used to reflect BP patterns across midlife. High cumulative BP in midlife is associated with increased dementia risk. Visit-to-visit BPV was not associated with the onset of dementia.
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Affiliation(s)
- Hyun Kim
- Dept. of Psychological & Brain Sciences, Boston University, 900 Commonwealth Ave # 2, Boston, MA 02215, USA
- Framingham Heart Study, Boston University School of Medicine, 72 E. Concord St Housman (R), Boston MA 02118
| | - Ting Fang Alvin Ang
- Framingham Heart Study, Boston University School of Medicine, 72 E. Concord St Housman (R), Boston MA 02118
- Department of Anatomy and Neurobiology, Boston University School of Medicine, 72 E. Concord St Housman (R), Boston MA 02118
| | - Robert J. Thomas
- Department of Medicine, Division of Pulmonary, Critical Care & Sleep, Beth Israel Deaconess Medical Center, Harvard Medical School, 330 Brookline Avenue Shapiro 7 Boston, MA 02215
| | - Michael J. Lyons
- Dept. of Psychological & Brain Sciences, Boston University, 900 Commonwealth Ave # 2, Boston, MA 02215, USA
| | - Rhoda Au
- Framingham Heart Study, Boston University School of Medicine, 72 E. Concord St Housman (R), Boston MA 02118
- Department of Anatomy and Neurobiology, Boston University School of Medicine, 72 E. Concord St Housman (R), Boston MA 02118
- Dept. of Neurology, Medicine and Alzheimer’s Disease Research Center, Boston University School of Medicine, 72 E. Concord St, Boston MA 02118
- Dept. of Epidemiology, Boston University School of Public Health, 715 Albany St.Boston, MA 02118
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Jiang R, Calhoun VD, Noble S, Sui J, Liang Q, Qi S, Scheinost D. A functional connectome signature of blood pressure in >30 000 participants from the UK biobank. Cardiovasc Res 2023; 119:1427-1440. [PMID: 35875865 PMCID: PMC10262183 DOI: 10.1093/cvr/cvac116] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 06/07/2022] [Accepted: 07/01/2022] [Indexed: 11/12/2022] Open
Abstract
AIMS Elevated blood pressure (BP) is a prevalent modifiable risk factor for cardiovascular diseases and contributes to cognitive decline in late life. Despite the fact that functional changes may precede irreversible structural damage and emerge in an ongoing manner, studies have been predominantly informed by brain structure and group-level inferences. Here, we aim to delineate neurobiological correlates of BP at an individual level using machine learning and functional connectivity. METHODS AND RESULTS Based on whole-brain functional connectivity from the UK Biobank, we built a machine learning model to identify neural representations for individuals' past (∼8.9 years before scanning, N = 35 882), current (N = 31 367), and future (∼2.4 years follow-up, N = 3 138) BP levels within a repeated cross-validation framework. We examined the impact of multiple potential covariates, as well as assessed these models' generalizability across various contexts.The predictive models achieved significant correlations between predicted and actual systolic/diastolic BP and pulse pressure while controlling for multiple confounders. Predictions for participants not on antihypertensive medication were more accurate than for currently medicated patients. Moreover, the models demonstrated robust generalizability across contexts in terms of ethnicities, imaging centres, medication status, participant visits, gender, age, and body mass index. The identified connectivity patterns primarily involved the cerebellum, prefrontal, anterior insula, anterior cingulate cortex, supramarginal gyrus, and precuneus, which are key regions of the central autonomic network, and involved in cognition processing and susceptible to neurodegeneration in Alzheimer's disease. Results also showed more involvement of default mode and frontoparietal networks in predicting future BP levels and in medicated participants. CONCLUSION This study, based on the largest neuroimaging sample currently available and using machine learning, identifies brain signatures underlying BP, providing evidence for meaningful BP-associated neural representations in connectivity profiles.
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Affiliation(s)
- Rongtao Jiang
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT 06510, USA
| | - Vince D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Emory University and Georgia State University, Atlanta, GA 30303, USA
| | - Stephanie Noble
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT 06510, USA
| | - Jing Sui
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Emory University and Georgia State University, Atlanta, GA 30303, USA
| | - Qinghao Liang
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA
| | - Shile Qi
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Emory University and Georgia State University, Atlanta, GA 30303, USA
| | - Dustin Scheinost
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT 06510, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT 06520, USA
- Department of Statistics & Data Science, Yale University, New Haven, CT 06520, USA
- Child Study Center, Yale School of Medicine, New Haven, CT 06510, USA
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Iadecola C, Smith EE, Anrather J, Gu C, Mishra A, Misra S, Perez-Pinzon MA, Shih AY, Sorond FA, van Veluw SJ, Wellington CL. The Neurovasculome: Key Roles in Brain Health and Cognitive Impairment: A Scientific Statement From the American Heart Association/American Stroke Association. Stroke 2023; 54:e251-e271. [PMID: 37009740 PMCID: PMC10228567 DOI: 10.1161/str.0000000000000431] [Citation(s) in RCA: 28] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/04/2023]
Abstract
BACKGROUND Preservation of brain health has emerged as a leading public health priority for the aging world population. Advances in neurovascular biology have revealed an intricate relationship among brain cells, meninges, and the hematic and lymphatic vasculature (the neurovasculome) that is highly relevant to the maintenance of cognitive function. In this scientific statement, a multidisciplinary team of experts examines these advances, assesses their relevance to brain health and disease, identifies knowledge gaps, and provides future directions. METHODS Authors with relevant expertise were selected in accordance with the American Heart Association conflict-of-interest management policy. They were assigned topics pertaining to their areas of expertise, reviewed the literature, and summarized the available data. RESULTS The neurovasculome, composed of extracranial, intracranial, and meningeal vessels, as well as lymphatics and associated cells, subserves critical homeostatic functions vital for brain health. These include delivering O2 and nutrients through blood flow and regulating immune trafficking, as well as clearing pathogenic proteins through perivascular spaces and dural lymphatics. Single-cell omics technologies have unveiled an unprecedented molecular heterogeneity in the cellular components of the neurovasculome and have identified novel reciprocal interactions with brain cells. The evidence suggests a previously unappreciated diversity of the pathogenic mechanisms by which disruption of the neurovasculome contributes to cognitive dysfunction in neurovascular and neurodegenerative diseases, providing new opportunities for the prevention, recognition, and treatment of these conditions. CONCLUSIONS These advances shed new light on the symbiotic relationship between the brain and its vessels and promise to provide new diagnostic and therapeutic approaches for brain disorders associated with cognitive dysfunction.
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Sorond FA, Gorelick PB. Brain Reserve, Resilience, and Cognitive Stimulation Across the Lifespan: How Do These Factors Influence Risk of Cognitive Impairment and the Dementias? Clin Geriatr Med 2023; 39:151-160. [PMID: 36404028 DOI: 10.1016/j.cger.2022.08.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
In the absence of effective treatments for dementia, maintaining cognitive health in old age is one of the major challenges facing aging societies. Interventions for cognitive health that are tailored to the person are more likely to bring the best benefits with a minimum burden. We review the existing literature on this topic and discuss the role of the primary care physician.
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Affiliation(s)
- Farzaneh A Sorond
- Department of Neurology, Division of Stroke, Northwestern University, Feinberg School of Medicine, 625 North Michigan Avenue, 11th Floor, Chicago, IL 60611, USA.
| | - Philip B Gorelick
- Department of Neurology, Division of Stroke, Northwestern University, Feinberg School of Medicine, 625 North Michigan Avenue, 11th Floor, Chicago, IL 60611, USA
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Ávila-Villanueva M, Marcos Dolado A, Gómez-Ramírez J, Fernández-Blázquez M. Brain Structural and Functional Changes in Cognitive Impairment Due to Alzheimer’s Disease. Front Psychol 2022; 13:886619. [PMID: 35800946 PMCID: PMC9253821 DOI: 10.3389/fpsyg.2022.886619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 05/10/2022] [Indexed: 11/23/2022] Open
Abstract
Cognitive neuropsychology seeks a potential alignment between structural and functional brain features to explain physiological or pathological processes, such as Alzheimer’s disease (AD). Several structural and functional brain changes occurring during the disease, including cognitive impairment, are found at the end of the patient’s life, but we need to know more about what happens before its onset. In order to do that, we need earlier biomarkers at preclinical stages, defined by those biomarkers, to prevent the cognitive impairment. In this minireview, we have tried to describe the structural and functional changes found at different stages during AD, focusing on those features taking place before clinical diagnosis.
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Affiliation(s)
- Marina Ávila-Villanueva
- Research in Alzheimer’s Disease, Departamento de Psicología Experimental, Procesos Cognitivos y Logopedia Universidad Complutense de Madrid (UCM), Madrid, Spain
- *Correspondence: Marina Ávila-Villanueva,
| | - Alberto Marcos Dolado
- Servicio de Neurología, Hospital Clínico San Carlos, Madrid, Spain
- Instituto de Investigación Sanitaria del Hospital Clínico San Carlos, Madrid, Spain
| | - Jaime Gómez-Ramírez
- Instituto de Investigación e Innovación Biomédica de Cádiz, Universidad de Cádiz, Cádiz, Spain
| | - Miguel Fernández-Blázquez
- Departamento de Psicología Biológica y de la Salud, Facultad de Psicología, Universidad Autónoma de Madrid, Madrid, Spain
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Kleiman MJ, Chang LC, Galvin JE. The Brain Health Platform: Combining Resilience, Vulnerability, and Performance to Assess Brain Health and Risk of Alzheimer's Disease and Related Disorders. J Alzheimers Dis 2022; 90:1817-1830. [PMID: 36336936 PMCID: PMC10515193 DOI: 10.3233/jad-220927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
BACKGROUND It is difficult to assess brain health status and risk of cognitive impairment, particularly at the initial evaluation. To address this, we developed the Brain Health Platform to quantify brain health and identify Alzheimer's disease and related disorders (ADRD) risk factors by combining a measure of brain health: the Resilience Index (RI), a measure of risk of ADRD; the Vulnerability Index (VI); and the Number-Symbol Coding Task (NSCT), a measure of brain performance. OBJECTIVE The Brain Health Platform is intended to be easily and quickly administered, providing an overview of a patient's risk of developing future impairment based on modifiable and non-modifiable factors as well as current cognitive performance. METHODS This cross-sectional study comprehensively evaluated 230 participants (71 controls, 71 mild cognitive impairment, 88 ADRD). VI and RI scores were derived from physical assessments, lifestyle questionnaires, demographics, medical history, and neuropsychological examination including the NSCT. RESULTS Individuals with abnormal scores were 95.7% likely to be impaired, with a misclassification rate of 9.7%. The combined model had excellent discrimination (AUC:0.923±0.053; p < 0.001), performing better than the Montreal Cognitive Assessment. CONCLUSION The Brain Health Platform combines measures of resilience, vulnerability, and performance to provide a cross-sectional snapshot of overall brain health. The Brain Health Platform can effectively and accurately identify even the very mildest impairments due to ADRD, leveraging brief yet powerful and actionable indices of brain health and risk that could be used to develop personalized, precision medicine-like interventions.
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Affiliation(s)
- Michael J. Kleiman
- Comprehensive Center for Brain Health, Department of Neurology, University of Miami Miller School of Medicine, Boca Raton, FL, USA
| | - Lun-Ching Chang
- Department of Mathematical Sciences, Florida Atlantic University, Boca Raton, FL, USA
| | - James E. Galvin
- Comprehensive Center for Brain Health, Department of Neurology, University of Miami Miller School of Medicine, Boca Raton, FL, USA
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