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Thanaraju A, Marzuki AA, Chan JK, Wong KY, Phon-Amnuaisuk P, Vafa S, Chew J, Chia YC, Jenkins M. Structural and functional brain correlates of socioeconomic status across the life span: A systematic review. Neurosci Biobehav Rev 2024; 162:105716. [PMID: 38729281 DOI: 10.1016/j.neubiorev.2024.105716] [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] [Received: 01/28/2024] [Revised: 04/08/2024] [Accepted: 05/06/2024] [Indexed: 05/12/2024]
Abstract
It is well-established that higher socioeconomic status (SES) is associated with improved brain health. However, the effects of SES across different life stages on brain structure and function is still equivocal. In this systematic review, we aimed to synthesise findings from life course neuroimaging studies that investigated the structural and functional brain correlates of SES across the life span. The results indicated that higher SES across different life stages were independently and cumulatively related to neural outcomes typically reflective of greater brain health (e.g., increased cortical thickness, grey matter volume, fractional anisotropy, and network segregation) in adult individuals. The results also demonstrated that the corticolimbic system was most commonly impacted by socioeconomic disadvantages across the life span. This review highlights the importance of taking into account SES across the life span when studying its effects on brain health. It also provides directions for future research including the need for longitudinal and multimodal research that can inform effective policy interventions tailored to specific life stages.
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Affiliation(s)
- Arjun Thanaraju
- Department of Biological Sciences, School of Medical and Life Sciences, Sunway University, Malaysia.
| | - Aleya A Marzuki
- Department for Psychiatry and Psychotherapy, Medical School and University Hospital, Eberhard Karls University of Tübingen, Germany
| | - Jee Kei Chan
- Department of Psychology, Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Malaysia
| | - Kean Yung Wong
- Sensory Neuroscience and Nutrition Lab, University of Otago, New Zealand
| | - Paveen Phon-Amnuaisuk
- Department of Psychology, Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Malaysia
| | - Samira Vafa
- Department of Psychology, School of Medical and Life Sciences, Sunway University, Malaysia
| | - Jactty Chew
- Department of Biological Sciences, School of Medical and Life Sciences, Sunway University, Malaysia
| | - Yook Chin Chia
- Department of Medical Sciences, School of Medical and Life Sciences, Sunway University, Malaysia
| | - Michael Jenkins
- Department of Psychology, School of Medical and Life Sciences, Sunway University, Malaysia
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Biesbroek JM, Coenen M, DeCarli C, Fletcher EM, Maillard PM, Barkhof F, Barnes J, Benke T, Chen CPLH, Dal‐Bianco P, Dewenter A, Duering M, Enzinger C, Ewers M, Exalto LG, Franzmeier N, Hilal S, Hofer E, Koek HL, Maier AB, McCreary CR, Papma JM, Paterson RW, Pijnenburg YAL, Rubinski A, Schmidt R, Schott JM, Slattery CF, Smith EE, Sudre CH, Steketee RME, Teunissen CE, van den Berg E, van der Flier WM, Venketasubramanian N, Venkatraghavan V, Vernooij MW, Wolters FJ, Xin X, Kuijf HJ, Biessels GJ. Amyloid pathology and vascular risk are associated with distinct patterns of cerebral white matter hyperintensities: A multicenter study in 3132 memory clinic patients. Alzheimers Dement 2024; 20:2980-2989. [PMID: 38477469 PMCID: PMC11032573 DOI: 10.1002/alz.13765] [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: 10/30/2023] [Revised: 01/30/2024] [Accepted: 01/31/2024] [Indexed: 03/14/2024]
Abstract
INTRODUCTION White matter hyperintensities (WMH) are associated with key dementia etiologies, in particular arteriolosclerosis and amyloid pathology. We aimed to identify WMH locations associated with vascular risk or cerebral amyloid-β1-42 (Aβ42)-positive status. METHODS Individual patient data (n = 3,132; mean age 71.5 ± 9 years; 49.3% female) from 11 memory clinic cohorts were harmonized. WMH volumes in 28 regions were related to a vascular risk compound score (VRCS) and Aß42 status (based on cerebrospinal fluid or amyloid positron emission tomography), correcting for age, sex, study site, and total WMH volume. RESULTS VRCS was associated with WMH in anterior/superior corona radiata (B = 0.034/0.038, p < 0.001), external capsule (B = 0.052, p < 0.001), and middle cerebellar peduncle (B = 0.067, p < 0.001), and Aß42-positive status with WMH in posterior thalamic radiation (B = 0.097, p < 0.001) and splenium (B = 0.103, p < 0.001). DISCUSSION Vascular risk factors and Aß42 pathology have distinct signature WMH patterns. This regional vulnerability may incite future studies into how arteriolosclerosis and Aß42 pathology affect the brain's white matter. HIGHLIGHTS Key dementia etiologies may be associated with specific patterns of white matter hyperintensities (WMH). We related WMH locations to vascular risk and cerebral Aβ42 status in 11 memory clinic cohorts. Aβ42 positive status was associated with posterior WMH in splenium and posterior thalamic radiation. Vascular risk was associated with anterior and infratentorial WMH. Amyloid pathology and vascular risk have distinct signature WMH patterns.
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Bachmann D, von Rickenbach B, Buchmann A, Hüllner M, Zuber I, Studer S, Saake A, Rauen K, Gruber E, Nitsch RM, Hock C, Treyer V, Gietl A. White matter hyperintensity patterns: associations with comorbidities, amyloid, and cognition. Alzheimers Res Ther 2024; 16:67. [PMID: 38561806 PMCID: PMC10983708 DOI: 10.1186/s13195-024-01435-6] [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: 10/27/2023] [Accepted: 03/23/2024] [Indexed: 04/04/2024]
Abstract
BACKGROUND White matter hyperintensities (WMHs) are often measured globally, but spatial patterns of WMHs could underlie different risk factors and neuropathological and clinical correlates. We investigated the spatial heterogeneity of WMHs and their association with comorbidities, Alzheimer's disease (AD) risk factors, and cognition. METHODS In this cross-sectional study, we studied 171 cognitively unimpaired (CU; median age: 65 years, range: 50 to 89) and 51 mildly cognitively impaired (MCI; median age: 72, range: 53 to 89) individuals with available amyloid (18F-flutementamol) PET and FLAIR-weighted images. Comorbidities were assessed using the Cumulative Illness Rating Scale (CIRS). Each participant's white matter was segmented into 38 parcels, and WMH volume was calculated in each parcel. Correlated principal component analysis was applied to the parceled WMH data to determine patterns of WMH covariation. Adjusted and unadjusted linear regression models were used to investigate associations of component scores with comorbidities and AD-related factors. Using multiple linear regression, we tested whether WMH component scores predicted cognitive performance. RESULTS Principal component analysis identified four WMH components that broadly describe FLAIR signal hyperintensities in posterior, periventricular, and deep white matter regions, as well as basal ganglia and thalamic structures. In CU individuals, hypertension was associated with all patterns except the periventricular component. MCI individuals showed more diverse associations. The posterior and deep components were associated with renal disorders, the periventricular component was associated with increased amyloid, and the subcortical gray matter structures was associated with sleep disorders, endocrine/metabolic disorders, and increased amyloid. In the combined sample (CU + MCI), the main effects of WMH components were not associated with cognition but predicted poorer episodic memory performance in the presence of increased amyloid. No interaction between hypertension and the number of comorbidities on component scores was observed. CONCLUSION Our study underscores the significance of understanding the regional distribution patterns of WMHs and the valuable insights that risk factors can offer regarding their underlying causes. Moreover, patterns of hyperintensities in periventricular regions and deep gray matter structures may have more pronounced cognitive implications, especially when amyloid pathology is also present.
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Affiliation(s)
- Dario Bachmann
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland.
- Department of Health Sciences and Technology, ETH Zürich, 8093, Zurich, Switzerland.
| | | | - Andreas Buchmann
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
| | - Martin Hüllner
- Department of Nuclear Medicine, University Hospital of Zurich, University of Zurich, 8091, Zurich, Switzerland
| | - Isabelle Zuber
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
| | - Sandro Studer
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
| | - Antje Saake
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
| | - Katrin Rauen
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
- Department of Geriatric Psychiatry, Psychiatric Hospital Zurich, 8032, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich, 8057, Zurich, Switzerland
| | - Esmeralda Gruber
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
| | - Roger M Nitsch
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
- Neurimmune AG, 8952, Zurich, Schlieren, Switzerland
| | - Christoph Hock
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
- Neurimmune AG, 8952, Zurich, Schlieren, Switzerland
| | - Valerie Treyer
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
- Department of Nuclear Medicine, University Hospital of Zurich, University of Zurich, 8091, Zurich, Switzerland
| | - Anton Gietl
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
- Department of Geriatric Psychiatry, Psychiatric Hospital Zurich, 8032, Zurich, Switzerland
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Pradeep A, Raghavan S, Przybelski SA, Preboske G, Schwarz CG, Lowe VJ, Knopman DS, Petersen RC, Jack CR, Graff-Radford J, Cogswell PM, Vemuri P. Can white matter hyperintensities based Fazekas visual assessment scales inform about Alzheimer's disease pathology in the population? RESEARCH SQUARE 2024:rs.3.rs-4017874. [PMID: 38558965 PMCID: PMC10980106 DOI: 10.21203/rs.3.rs-4017874/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Background White matter hyperintensities (WMH) are considered hallmark features of cerebral small vessel disease and have recently been linked to Alzheimer's disease pathology. Their distinct spatial distributions, namely periventricular versus deep WMH, may differ by underlying age-related and pathobiological processes contributing to cognitive decline. We aimed to identify the spatial patterns of WMH using the 4-scale Fazekas visual assessment and explore their differential association with age, vascular health, Alzheimer's imaging markers, namely amyloid and tau burden, and cognition. Because our study consisted of scans from GE and Siemens scanners with different resolutions, we also investigated inter-scanner reproducibility and combinability of WMH measurements on imaging. Methods We identified 1144 participants from the Mayo Clinic Study of Aging consisting of older adults from Olmsted County, Minnesota with available structural magnetic resonance imaging (MRI), amyloid, and tau positron emission tomography (PET). WMH distribution patterns were assessed on FLAIR-MRI, both 2D axial and 3D, using Fazekas ratings of periventricular and deep WMH severity. We compared the association of periventricular and deep WMH scales with vascular risk factors, amyloid-PET and tau-PET standardized uptake value ratio, WMH volume, and cognition using Pearson partial correlation after adjusting for age. We also evaluated vendor compatibility and reproducibility of the Fazekas scales using intraclass correlations (ICC). Results Periventricular and deep WMH measurements showed similar correlations with age, cardiometabolic conditions score (vascular risk), and cognition, (p < 0.001). Both periventricular WMH and deep WMH showed weak associations with amyloidosis (R = 0.07, p = < 0.001), and none with tau burden. We found substantial agreement between data from the two scanners for Fazekas measurements (ICC = 0.78). The automated WMH volume had high discriminating power for identifying participants with Fazekas ≥ 2 (area under curve = 0.97). Conclusion Our study investigates risk factors underlying WMH spatial patterns and their impact on global cognition, with no discernible differences between periventricular and deep WMH. We observed minimal impact of amyloidosis on WMH severity. These findings, coupled with enhanced inter-scanner reproducibility of WMH data, suggest the combinability of inter-scanner data assessed by harmonized protocols in the context of vascular contributions to cognitive impairment and dementia biomarker research.
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Badji A, Cedres N, Muehlboeck JS, Khan W, Dhollander T, Barroso J, Ferreira D, Westman E. In vivo microstructural heterogeneity of white matter and cognitive correlates in aging using tissue compositional analysis of diffusion magnetic resonance imaging. Hum Brain Mapp 2024; 45:e26618. [PMID: 38414286 PMCID: PMC10899800 DOI: 10.1002/hbm.26618] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 12/03/2023] [Accepted: 12/24/2023] [Indexed: 02/29/2024] Open
Abstract
BACKGROUND Age-related cognitive decline is linked to changes in the brain, particularly the deterioration of white matter (WM) microstructure that accelerates after the age of 60. WM deterioration is associated with mild cognitive impairment and dementia, but the origin and role of white matter signal abnormalities (WMSA) seen in standard MRI remain debated due to their heterogeneity. This study explores the potential of single-shell 3-tissue constrained spherical deconvolution (SS3T-CSD), a novel technique that models diffusion data in terms of gray matter (TG ), white matter (Tw ), and cerebrospinal fluid (TC ), to differentiate WMSA from normal-appearing white matter and better understand the interplay between changes in WM microstructure and decline in cognition. METHODS A total of 189 individuals from the GENIC cohort were included. MRI data, including T1-weighted and diffusion images, were obtained. Preprocessing steps were performed on the diffusion MRI data, followed by the SS3T-CSD. WMSA were segmented using FreeSurfer. Statistical analyses were conducted to assess the association between age, WMSA volume, 3-tissue signal fractions (Tw , TG , and TC ), and neuropsychological variables. RESULTS Participants above 60 years old showed worse cognitive performance and processing speed compared to those below 60 (p < .001). Age was negatively associated with Tw in normal-appearing white matter (p < .001) and positively associated with TG in both WMSA (p < .01) and normal-appearing white matter (p < .001). Age was also significantly associated with WMSA volume (p < .001). Higher processing speed was associated with lower Tw and higher TG , in normal-appearing white matter (p < .01 and p < .001, respectively), as well as increased WMSA volume (p < .001). Similarly, lower MMSE scores correlated with lower Tw and higher TG in normal-appearing white matter (p < .05). High cholesterol and hypertension were associated with higher WMSA volume (p < .05). CONCLUSION The microstructural heterogeneity within normal-appearing white matter and WMSA is associated with increasing age and cognitive variation, in cognitively unimpaired individuals. Furthermore, the 3-tissue signal fractions are more specific to potential white matter alterations than conventional MRI measures such as WMSA volume. These findings also support the view that the WMSA volumes may be more influenced by vascular risk factors than the 3-tissue metrics. Finally, the 3-tissue metrics were able to capture associations with cognitive tests and therefore capable of capturing subtle pathological changes in the brain in individuals who are still within the normal range of cognitive performance.
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Affiliation(s)
- Atef Badji
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Nira Cedres
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Facultad de Ciencias de la Salud, Universidad Fernando Pessoa Canarias, Las Palmas de Gran Canaria, España
| | - J-Sebastian Muehlboeck
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Wasim Khan
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Thijs Dhollander
- Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Jose Barroso
- Facultad de Ciencias de la Salud, Universidad Fernando Pessoa Canarias, Las Palmas de Gran Canaria, España
| | - Daniel Ferreira
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Facultad de Ciencias de la Salud, Universidad Fernando Pessoa Canarias, Las Palmas de Gran Canaria, España
| | - Eric Westman
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
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Chen Y, Lu P, Wu S, Yang J, Liu W, Zhang Z, Xu Q. CD163-Mediated Small-Vessel Injury in Alzheimer's Disease: An Exploration from Neuroimaging to Transcriptomics. Int J Mol Sci 2024; 25:2293. [PMID: 38396970 PMCID: PMC10888773 DOI: 10.3390/ijms25042293] [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: 01/10/2024] [Revised: 02/10/2024] [Accepted: 02/11/2024] [Indexed: 02/25/2024] Open
Abstract
Patients with Alzheimer's disease (AD) often present with imaging features indicative of small-vessel injury, among which, white-matter hyperintensities (WMHs) are the most prevalent. However, the underlying mechanism of the association between AD and small-vessel injury is still obscure. The aim of this study is to investigate the mechanism of small-vessel injury in AD. Differential gene expression analyses were conducted to identify the genes related to WMHs separately in mild cognitive impairment (MCI) and cognitively normal (CN) subjects from the ADNI database. The WMH-related genes identified in patients with MCI were considered to be associated with small-vessel injury in early AD. Functional enrichment analyses and a protein-protein interaction (PPI) network were performed to explore the pathway and hub genes related to the mechanism of small-vessel injury in MCI. Subsequently, the Boruta algorithm and support vector machine recursive feature elimination (SVM-RFE) algorithm were performed to identify feature-selection genes. Finally, the mechanism of small-vessel injury was analyzed in MCI from the immunological perspectives; the relationship of feature-selection genes with various immune cells and neuroimaging indices were also explored. Furthermore, 5×FAD mice were used to demonstrate the genes related to small-vessel injury. The results of the logistic regression analyses suggested that WMHs significantly contributed to MCI, the early stage of AD. A total of 276 genes were determined as WMH-related genes in patients with MCI, while 203 WMH-related genes were obtained in CN patients. Among them, only 15 genes overlapped and were thus identified as the crosstalk genes. By employing the Boruta and SVM-RFE algorithms, CD163, ALDH3B1, MIR22HG, DTX2, FOLR2, ALDH2, and ZNF23 were recognized as the feature-selection genes linked to small-vessel injury in MCI. After considering the results from the PPI network, CD163 was finally determined as the critical WMH-related gene in MCI. The expression of CD163 was correlated with fractional anisotropy (FA) values in regions that are vulnerable to small-vessel injury in AD. The immunostaining and RT-qPCR results from the verifying experiments demonstrated that the indicators of small-vessel injury presented in the cortical tissue of 5×FAD mice and related to the upregulation of CD163 expression. CD163 may be the most pivotal candidates related to small-vessel injury in early AD.
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Affiliation(s)
- Yuewei Chen
- Health Management Center, Renji Hospital of Medical School, Shanghai Jiao Tong University, Shanghai 200127, China; (Y.C.); (P.L.); (W.L.)
- Department of Neurology, Renji Hospital of Medical School, Shanghai Jiao Tong University, Shanghai 200127, China
- Renji-UNSW CHeBA (Centre for Healthy Brain Ageing of University of New South Wales) Neurocognitive Center, Renji Hospital of Medical School, Shanghai Jiao Tong University, Shanghai 200127, China
| | - Peiwen Lu
- Health Management Center, Renji Hospital of Medical School, Shanghai Jiao Tong University, Shanghai 200127, China; (Y.C.); (P.L.); (W.L.)
- Renji-UNSW CHeBA (Centre for Healthy Brain Ageing of University of New South Wales) Neurocognitive Center, Renji Hospital of Medical School, Shanghai Jiao Tong University, Shanghai 200127, China
| | - Shengju Wu
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Jie Yang
- Health Management Center, Renji Hospital of Medical School, Shanghai Jiao Tong University, Shanghai 200127, China; (Y.C.); (P.L.); (W.L.)
- Department of Neurology, Renji Hospital of Medical School, Shanghai Jiao Tong University, Shanghai 200127, China
- Renji-UNSW CHeBA (Centre for Healthy Brain Ageing of University of New South Wales) Neurocognitive Center, Renji Hospital of Medical School, Shanghai Jiao Tong University, Shanghai 200127, China
| | - Wanwan Liu
- Health Management Center, Renji Hospital of Medical School, Shanghai Jiao Tong University, Shanghai 200127, China; (Y.C.); (P.L.); (W.L.)
| | - Zhijun Zhang
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Qun Xu
- Health Management Center, Renji Hospital of Medical School, Shanghai Jiao Tong University, Shanghai 200127, China; (Y.C.); (P.L.); (W.L.)
- Department of Neurology, Renji Hospital of Medical School, Shanghai Jiao Tong University, Shanghai 200127, China
- Renji-UNSW CHeBA (Centre for Healthy Brain Ageing of University of New South Wales) Neurocognitive Center, Renji Hospital of Medical School, Shanghai Jiao Tong University, Shanghai 200127, China
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Farkhondeh V, DeCarli C. White matter hyperintensities in diverse populations: A systematic review of literature in the United States. CEREBRAL CIRCULATION - COGNITION AND BEHAVIOR 2024; 6:100204. [PMID: 38298455 PMCID: PMC10828602 DOI: 10.1016/j.cccb.2024.100204] [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] [Received: 08/14/2023] [Revised: 12/20/2023] [Accepted: 01/11/2024] [Indexed: 02/02/2024]
Abstract
As the United States' (US) elderly population becomes increasingly diverse, it is imperative that research studies address cognitive health in diverse populations of older Americans. White Matter Hyperintensities (WMH) are useful imaging findings that can be studied in elderly individuals and have been linked to an increased risk of neurological conditions, such as stroke, cognitive impairment, and dementia. We performed a systematic review of literature using PubMed sources to compile all the studies that investigated the prevalence of ethnic and racial differences of WMH burden amongst diverse groups in the US. We identified 23 unique articles that utilized 16 distinct cohorts of which 94 % were prospective, longitudinal studies that included community-based and family-based populations. The overall results were heterogenous in all aspects of data collection and analysis, limiting our ability to run meta-analyses and draw definitive conclusions. General observations suggest increased vascular risk on African American populations, contributing to greater WMH burden in that population. Overall, the findings of this study indicate a need for a standardized approach to investigating WMH in efforts to measure its clinical impact on diverse populations.
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Affiliation(s)
- Vista Farkhondeh
- Department of Neurology, University of California, Davis School of Medicine, Sacramento, CA, United States
- Imaging of Dementia and Aging Laboratory and Center for Neurosciences, Davis, CA, United States
| | - Charles DeCarli
- Department of Neurology, University of California, Davis School of Medicine, Sacramento, CA, United States
- Imaging of Dementia and Aging Laboratory and Center for Neurosciences, Davis, CA, United States
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Cho E, Granger J, Theall B, Lemoine N, Calvert D, Marucci J, Mullenix S, O'Neal H, Jacome T, Irving BA, Johannsen NM, Carmichael O, Spielmann G. Blood and MRI biomarkers of mild traumatic brain injury in non-concussed collegiate football players. Sci Rep 2024; 14:665. [PMID: 38182718 PMCID: PMC10770029 DOI: 10.1038/s41598-023-51067-3] [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] [Received: 10/27/2023] [Accepted: 12/30/2023] [Indexed: 01/07/2024] Open
Abstract
Football has one of the highest incidence rates of mild traumatic brain injury (mTBI) among contact sports; however, the effects of repeated sub-concussive head impacts on brain structure and function remain under-studied. We assessed the association between biomarkers of mTBI and structural and functional MRI scans over an entire season among non-concussed NCAA Division I linemen and non-linemen. Concentrations of S100B, GFAP, BDNF, NFL, and NSE were assessed in 48 collegiate football players (32 linemen; 16 non-linemen) before the start of pre-season training (pre-camp), at the end of pre-season training (pre-season), and at the end of the competitive season (post-season). Changes in brain structure and function were assessed in a sub-sample of 11 linemen and 6 non-linemen using structural and functional MRI during the execution of Stroop and attention network tasks. S100B, GFAP and BDNF concentrations were increased at post-season compared to pre-camp in linemen. White matter hyperintensities increased in linemen during pre-season camp training compared to pre-camp. This study showed that the effects of repeated head impacts are detectable in the blood of elite level non-concussed collegiate football players exposed to low-moderate impacts to the heads, which correlated with some neurological outcomes without translating to clinically-relevant changes in brain anatomy or function.
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Affiliation(s)
- Eunhan Cho
- School of Kinesiology, Louisiana State University, Huey P. Long Fieldhouse, Baton Rouge, LA, 70803, USA
| | - Joshua Granger
- School of Kinesiology, Louisiana State University, Huey P. Long Fieldhouse, Baton Rouge, LA, 70803, USA
| | - Bailey Theall
- School of Kinesiology, Louisiana State University, Huey P. Long Fieldhouse, Baton Rouge, LA, 70803, USA
| | | | | | | | | | - Hollis O'Neal
- Louisiana State University Health Sciences Center, Baton Rouge, LA, 70803, USA
- Our Lady of the Lake, Baton Rouge, LA, 70810, USA
| | - Tomas Jacome
- Our Lady of the Lake, Baton Rouge, LA, 70810, USA
| | - Brian A Irving
- School of Kinesiology, Louisiana State University, Huey P. Long Fieldhouse, Baton Rouge, LA, 70803, USA
- Pennington Biomedical Research Center, Baton Rouge, LA, 70808, USA
| | - Neil M Johannsen
- School of Kinesiology, Louisiana State University, Huey P. Long Fieldhouse, Baton Rouge, LA, 70803, USA
- Pennington Biomedical Research Center, Baton Rouge, LA, 70808, USA
| | - Owen Carmichael
- Pennington Biomedical Research Center, Baton Rouge, LA, 70808, USA
| | - Guillaume Spielmann
- School of Kinesiology, Louisiana State University, Huey P. Long Fieldhouse, Baton Rouge, LA, 70803, USA.
- Pennington Biomedical Research Center, Baton Rouge, LA, 70808, USA.
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Zhang Z, Lim MJR. Incident Dementia After Spontaneous Intracerebral Hemorrhage. J Alzheimers Dis 2024; 99:41-51. [PMID: 38640161 DOI: 10.3233/jad-240111] [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: 04/21/2024]
Abstract
Post-stroke cognitive impairment and dementia (PSCID) is a complication that affects long-term functional outcomes after stroke. Studies on dementia after long-term follow-up in stroke have focused predominantly on ischemic stroke, which may be different from the development of dementia after spontaneous intracerebral hemorrhage (ICH). In this review, we summarize the existing data and hypotheses on the development of dementia after spontaneous ICH, review the management of post-ICH dementia, and suggest areas for future research. Dementia after spontaneous ICH has a cumulative incidence of up to 32.0-37.4% at 5 years post-ICH. Although the pathophysiology of post-ICH dementia has not been fully understood, two main theoretical frameworks can be considered: 1) the triggering role of ICH (both primary and secondary brain injury) in precipitating cognitive decline and dementia; and 2) the contributory role of pre-existing brain pathology (including small vessel disease and neurodegenerative pathology), reduced cognitive reserve, and genetic factors predisposing to cognitive dysfunction. These pathophysiological pathways may have synergistic effects that converge on dysfunction of the neurovascular unit and disruptions in functional connectivity leading to dementia post-ICH. Management of post-ICH dementia may include screening and monitoring, cognitive therapy, and pharmacotherapy. Non-invasive brain stimulation is an emerging therapeutic modality under investigation for safety and efficacy. Our review highlights that there remains a paucity of data and standardized reporting on incident dementia after spontaneous ICH. Further research is imperative for determining the incidence, risk factors, and pathophysiology of post-ICH dementia, in order to identify new therapies for the treatment of this debilitating condition.
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Affiliation(s)
- Zheting Zhang
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
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Kamal F, Morrison C, Dadar M. Investigating the relationship between sleep disturbances and white matter hyperintensities in older adults on the Alzheimer's disease spectrum. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2024; 16:e12553. [PMID: 38476639 PMCID: PMC10927930 DOI: 10.1002/dad2.12553] [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] [Received: 05/01/2023] [Revised: 12/15/2023] [Accepted: 01/19/2024] [Indexed: 03/14/2024]
Abstract
INTRODUCTION While studies report that sleep disturbance can have negative effects on brain vasculature, its impact on cerebrovascular diseases such as white matter hyperintensities (WMHs) in beta-amyloid-positive older adults remains unexplored. METHODS Sleep disturbance, WMH burden, and cognition in normal controls (NCs), and individuals with mild cognitive impairment (MCI) and Alzheimer's disease (AD), were examined at baseline and longitudinally. A total of 912 amyloid-positive participants were included (198 NC, 504 MCI, and 210 AD). RESULTS Individuals with AD reported more sleep disturbances than NC and MCI participants. Those with sleep disturbances had more WMHs than those without sleep disturbances in the AD group. Mediation analysis revealed an effect of regional WMH burden on the relationship between sleep disturbance and future cognition. DISCUSSION These results suggest that WMH burden and sleep disturbance increase from aging to AD. Sleep disturbance decreases cognition through increases in WMH burden. Improved sleep could mitigate the impact of WMH accumulation and cognitive decline.
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Affiliation(s)
- Farooq Kamal
- Department of PsychiatryMcGill UniversityMontrealQuebecCanada
- Douglas Mental Health University InstituteMontrealQuebecCanada
| | | | - Mahsa Dadar
- Department of PsychiatryMcGill UniversityMontrealQuebecCanada
- Douglas Mental Health University InstituteMontrealQuebecCanada
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11
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Busby N, Newman-Norlund R, Wilmskoetter J, Johnson L, Rorden C, Gibson M, Roth R, Wilson S, Fridriksson J, Bonilha L. Longitudinal Progression of White Matter Hyperintensity Severity in Chronic Stroke Aphasia. Arch Rehabil Res Clin Transl 2023; 5:100302. [PMID: 38163020 PMCID: PMC10757197 DOI: 10.1016/j.arrct.2023.100302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2024] Open
Abstract
Objective To determine whether longitudinal progression of small vessel disease in chronic stroke survivors is associated with longitudinal worsening of chronic aphasia severity. Design A longitudinal retrospective study. Severity of white matter hyperintensities (WMHs) as a marker for small vessel disease was assessed on fluid-attenuated inversion recovery (FLAIR) scans using the Fazekas scale, with ratings for deep WMHs (DWMHs) and periventricular WMHs (PVHs). Setting University research laboratories. Participants This study includes data from 49 chronic stroke survivors with aphasia (N=49; 15 women, 34 men, age range=32-81 years, >6 months post-stroke, stroke type: [46 ischemic, 3 hemorrhagic], community dwelling). All participants completed the Western Aphasia Battery-Revised (WAB) and had FLAIR scans at 2 timepoints (average years between timepoints: 1.87 years, SD=3.21 years). Interventions Not applicable. Main Outcome Measures Change in white matter hyperintensity severity (calculated using the Fazekas scale) and change in aphasia severity (difference in Western Aphasia Battery scores) were calculated between timepoints. Separate stepwise regression models were used to identify predictors of WMH severity change, with lesion volume, age, time between timepoints, body mass index (BMI), and presence of diabetes as independent variables. Additional stepwise regression models investigated predictors of change in aphasia severity, with PVH change, DWMH change, lesion volume, time between timepoints, and age as independent predictors. Results 22.5% of participants (11/49) had increased WMH severity. Increased BMI was associated with increases in PVH severity (P=.007), whereas the presence of diabetes was associated with increased DWMH severity (P=.002). Twenty-five percent of participants had increased aphasia severity which was significantly associated with increased severity of PVH (P<.001, 16.8% variance explained). Conclusion Increased small vessel disease burden is associated with contributing to chronic changes in aphasia severity. These findings support the idea that good cardiovascular risk factor control may play an important role in the prevention of long-term worsening of aphasic symptoms.
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Affiliation(s)
- Natalie Busby
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC
| | | | - Janina Wilmskoetter
- Department of Neurology, Medical University of South Carolina, Charleston, SC
| | - Lisa Johnson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC
| | - Chris Rorden
- Department of Psychology, University of South Carolina, Columbia, SC
| | - Makayla Gibson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC
| | - Rebecca Roth
- Department of Neurology, Emory University, Atlanta, GA
| | - Sarah Wilson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC
| | - Julius Fridriksson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC
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12
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Dilliott AA, Berberian SA, Sunderland KM, Binns MA, Zimmer J, Ozzoude M, Scott CJM, Gao F, Lang AE, Breen DP, Tartaglia MC, Tan B, Swartz RH, Rogaeva E, Borrie M, Finger E, Fischer CE, Frank A, Freedman M, Kumar S, Pasternak S, Pollock BG, Rajji TK, Tang-Wai DF, Abrahao A, Turnbull J, Zinman L, Casaubon L, Dowlatshahi D, Hassan A, Mandzia J, Sahlas D, Saposnik G, Grimes D, Marras C, Steeves T, Masellis M, Farhan SMK, Bartha R, Symons S, Hegele RA, Black SE, Ramirez J. Rare neurovascular genetic and imaging markers across neurodegenerative diseases. Alzheimers Dement 2023; 19:5583-5595. [PMID: 37272523 DOI: 10.1002/alz.13316] [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] [Received: 03/03/2023] [Revised: 05/09/2023] [Accepted: 05/10/2023] [Indexed: 06/06/2023]
Abstract
INTRODUCTION Cerebral small vessel disease (SVD) is common in patients with cognitive impairment and neurodegenerative diseases such as Alzheimer's and Parkinson's. This study investigated the burden of magnetic resonance imaging (MRI)-based markers of SVD in patients with neurodegenerative diseases as a function of rare genetic variant carrier status. METHODS The Ontario Neurodegenerative Disease Research Initiative study included 520 participants, recruited from 14 tertiary care centers, diagnosed with various neurodegenerative diseases and determined the carrier status of rare non-synonymous variants in five genes (ABCC6, COL4A1/COL4A2, NOTCH3/HTRA1). RESULTS NOTCH3/HTRA1 were found to significantly influence SVD neuroimaging outcomes; however, the mechanisms by which these variants contribute to disease progression or worsen clinical correlates are not yet understood. DISCUSSION Further studies are needed to develop genetic and imaging neurovascular markers to enhance our understanding of their potential contribution to neurodegenerative diseases.
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Affiliation(s)
- Allison A Dilliott
- Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montréal, Quebec, Canada
| | - Stephanie A Berberian
- Dr. Sandra Black Centre for Brain Resilience and Recovery, LC Campbell Cognitive Neurology, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Kelly M Sunderland
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada
| | - Malcolm A Binns
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada
- Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Julia Zimmer
- Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montréal, Quebec, Canada
| | - Miracle Ozzoude
- Dr. Sandra Black Centre for Brain Resilience and Recovery, LC Campbell Cognitive Neurology, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, Ontario, Canada
| | - Christopher J M Scott
- Dr. Sandra Black Centre for Brain Resilience and Recovery, LC Campbell Cognitive Neurology, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Fuqiang Gao
- Dr. Sandra Black Centre for Brain Resilience and Recovery, LC Campbell Cognitive Neurology, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Anthony E Lang
- Edmond J. Safra Program in Parkinson's Disease and the Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, Toronto, Ontario, Canada
| | - David P Breen
- Centre for Clinical Brain Sciences, University of Edinburgh; Anne Rowling Regenerative Neurology Clinic, University of Edinburgh; Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Maria C Tartaglia
- Edmond J. Safra Program in Parkinson's Disease and the Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, Toronto, Ontario, Canada
- Division of Neurology, Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada
| | - Brian Tan
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada
| | - Richard H Swartz
- Dr. Sandra Black Centre for Brain Resilience and Recovery, LC Campbell Cognitive Neurology, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
- Department of Medicine (Neurology), Sunnybrook Health Sciences and University of Toronto, Ontario, Canada
- Heart and Stroke Foundation Canadian Partnership for Stroke Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Ekaterina Rogaeva
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, Ontario, Canada
| | - Michael Borrie
- Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
- St. Joseph's Healthcare Centre, London, Ontario, Canada
| | - Elizabeth Finger
- Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - Corinne E Fischer
- Keenan Research Centre for Biomedical Science, St. Michael's Hospital, Toronto, Ontario, Canada
| | - Andrew Frank
- Department of Medicine (Neurology), University of Ottawa Brain and Mind Research Institute and Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
- Bruyère Research Institute, Ottawa, Ontario, Canada
| | - Morris Freedman
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada
- Department of Medicine (Neurology), Baycrest Health Sciences, Mt. Sinai Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Sanjeev Kumar
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
- Adult Neurodevelopment and Geriatric Psychiatry, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Stephen Pasternak
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - Bruce G Pollock
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
- Adult Neurodevelopment and Geriatric Psychiatry, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Tarek K Rajji
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
- Adult Neurodevelopment and Geriatric Psychiatry, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Toronto Dementia Research Alliance, University of Toronto, Toronto, Ontario, Canada
| | - David F Tang-Wai
- Department of Medicine (Neurology), Sunnybrook Health Sciences and University of Toronto, Ontario, Canada
| | - Agessandro Abrahao
- Department of Medicine (Neurology), Sunnybrook Health Sciences and University of Toronto, Ontario, Canada
| | - John Turnbull
- Division of Neurology, Department of Medicine, Hamilton Health Sciences, McMaster University, Hamilton, Canada
| | - Lorne Zinman
- Department of Medicine (Neurology), Sunnybrook Health Sciences and University of Toronto, Ontario, Canada
| | - Leanne Casaubon
- Department of Medicine (Neurology), Sunnybrook Health Sciences and University of Toronto, Ontario, Canada
| | - Dar Dowlatshahi
- Department of Medicine (Neurology), University of Ottawa Brain and Mind Research Institute and Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
| | - Ayman Hassan
- Thunder Bay Regional Health Research Institute, Thunder Bay, Ontario, Canada
| | - Jennifer Mandzia
- Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - Demetrios Sahlas
- Division of Neurology, Department of Medicine, Hamilton Health Sciences, McMaster University, Hamilton, Canada
| | - Gustavo Saposnik
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada
- Division of Neurology, Department of Medicine, St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada
| | - David Grimes
- Department of Medicine (Neurology), University of Ottawa Brain and Mind Research Institute and Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
| | - Connie Marras
- Edmond J. Safra Program in Parkinson's Disease and the Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, Toronto, Ontario, Canada
| | - Thomas Steeves
- Division of Neurology, Department of Medicine, St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Mario Masellis
- Dr. Sandra Black Centre for Brain Resilience and Recovery, LC Campbell Cognitive Neurology, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
- Department of Medicine (Neurology), Sunnybrook Health Sciences and University of Toronto, Ontario, Canada
| | - Sali M K Farhan
- Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montréal, Quebec, Canada
| | - Robert Bartha
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - Sean Symons
- Department of Medical Imaging, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Robert A Hegele
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - Sandra E Black
- Dr. Sandra Black Centre for Brain Resilience and Recovery, LC Campbell Cognitive Neurology, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada
- Department of Medicine (Neurology), Sunnybrook Health Sciences and University of Toronto, Ontario, Canada
- Heart and Stroke Foundation Canadian Partnership for Stroke Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Joel Ramirez
- Dr. Sandra Black Centre for Brain Resilience and Recovery, LC Campbell Cognitive Neurology, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
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Shirzadi Z, Schultz SA, Yau WYW, Joseph-Mathurin N, Fitzpatrick CD, Levin R, Kantarci K, Preboske GM, Jack CR, Farlow MR, Hassenstab J, Jucker M, Morris JC, Xiong C, Karch CM, Levey AI, Gordon BA, Schofield PR, Salloway SP, Perrin RJ, McDade E, Levin J, Cruchaga C, Allegri RF, Fox NC, Goate A, Day GS, Koeppe R, Chui HC, Berman S, Mori H, Sanchez-Valle R, Lee JH, Rosa-Neto P, Ruthirakuhan M, Wu CY, Swardfager W, Benzinger TLS, Sohrabi HR, Martins RN, Bateman RJ, Johnson KA, Sperling RA, Greenberg SM, Schultz AP, Chhatwal JP. Etiology of White Matter Hyperintensities in Autosomal Dominant and Sporadic Alzheimer Disease. JAMA Neurol 2023; 80:1353-1363. [PMID: 37843849 PMCID: PMC10580156 DOI: 10.1001/jamaneurol.2023.3618] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 06/26/2023] [Indexed: 10/17/2023]
Abstract
Importance Increased white matter hyperintensity (WMH) volume is a common magnetic resonance imaging (MRI) finding in both autosomal dominant Alzheimer disease (ADAD) and late-onset Alzheimer disease (LOAD), but it remains unclear whether increased WMH along the AD continuum is reflective of AD-intrinsic processes or secondary to elevated systemic vascular risk factors. Objective To estimate the associations of neurodegeneration and parenchymal and vessel amyloidosis with WMH accumulation and investigate whether systemic vascular risk is associated with WMH beyond these AD-intrinsic processes. Design, Setting, and Participants This cohort study used data from 3 longitudinal cohort studies conducted in tertiary and community-based medical centers-the Dominantly Inherited Alzheimer Network (DIAN; February 2010 to March 2020), the Alzheimer's Disease Neuroimaging Initiative (ADNI; July 2007 to September 2021), and the Harvard Aging Brain Study (HABS; September 2010 to December 2019). Main Outcome and Measures The main outcomes were the independent associations of neurodegeneration (decreases in gray matter volume), parenchymal amyloidosis (assessed by amyloid positron emission tomography), and vessel amyloidosis (evidenced by cerebral microbleeds [CMBs]) with cross-sectional and longitudinal WMH. Results Data from 3960 MRI sessions among 1141 participants were included: 252 pathogenic variant carriers from DIAN (mean [SD] age, 38.4 [11.2] years; 137 [54%] female), 571 older adults from ADNI (mean [SD] age, 72.8 [7.3] years; 274 [48%] female), and 318 older adults from HABS (mean [SD] age, 72.4 [7.6] years; 194 [61%] female). Longitudinal increases in WMH volume were greater in individuals with CMBs compared with those without (DIAN: t = 3.2 [P = .001]; ADNI: t = 2.7 [P = .008]), associated with longitudinal decreases in gray matter volume (DIAN: t = -3.1 [P = .002]; ADNI: t = -5.6 [P < .001]; HABS: t = -2.2 [P = .03]), greater in older individuals (DIAN: t = 6.8 [P < .001]; ADNI: t = 9.1 [P < .001]; HABS: t = 5.4 [P < .001]), and not associated with systemic vascular risk (DIAN: t = 0.7 [P = .40]; ADNI: t = 0.6 [P = .50]; HABS: t = 1.8 [P = .06]) in individuals with ADAD and LOAD after accounting for age, gray matter volume, CMB presence, and amyloid burden. In older adults without CMBs at baseline, greater WMH volume was associated with CMB development during longitudinal follow-up (Cox proportional hazards regression model hazard ratio, 2.63; 95% CI, 1.72-4.03; P < .001). Conclusions and Relevance The findings suggest that increased WMH volume in AD is associated with neurodegeneration and parenchymal and vessel amyloidosis but not with elevated systemic vascular risk. Additionally, increased WMH volume may represent an early sign of vessel amyloidosis preceding the emergence of CMBs.
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Affiliation(s)
- Zahra Shirzadi
- Massachusetts General Hospital, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | - Stephanie A. Schultz
- Massachusetts General Hospital, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | - Wai-Ying W. Yau
- Massachusetts General Hospital, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | | | - Colleen D. Fitzpatrick
- Massachusetts General Hospital, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | - Raina Levin
- Massachusetts General Hospital, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, Minnesota
| | | | | | | | - Jason Hassenstab
- Washington University in St Louis School of Medicine, St Louis, Missouri
| | - Mathias Jucker
- Department of Cellular Neurology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Tübingen, Germany
| | - John C. Morris
- Washington University in St Louis School of Medicine, St Louis, Missouri
| | - Chengjie Xiong
- Washington University in St Louis School of Medicine, St Louis, Missouri
| | - Celeste M. Karch
- Washington University in St Louis School of Medicine, St Louis, Missouri
| | | | - Brian A. Gordon
- Washington University in St Louis School of Medicine, St Louis, Missouri
| | - Peter R. Schofield
- Neuroscience Research Australia, Sydney, New South Wales, Australia
- School of Biomedical Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | | | - Richard J. Perrin
- Washington University in St Louis School of Medicine, St Louis, Missouri
| | - Eric McDade
- Washington University in St Louis School of Medicine, St Louis, Missouri
| | - Johannes Levin
- Department of Neurology, Ludwig-Maximilians-Universität München, German Center for Neurodegenerative Diseases, site Munich, Munich Cluster for Systems Neurology, Munich, Germany
| | - Carlos Cruchaga
- Washington University in St Louis School of Medicine, St Louis, Missouri
| | | | - Nick C. Fox
- UK Dementia Research Institute, University College London, London, United Kingdom
| | - Alison Goate
- Washington University in St Louis School of Medicine, St Louis, Missouri
| | - Gregory S. Day
- Department of Neurology, Mayo Clinic, Jacksonville, Florida
| | - Robert Koeppe
- Department of Radiology, University of Michigan, Ann Arbor
| | - Helena C. Chui
- Keck School of Medicine, University of Southern California, Los Angeles
| | - Sarah Berman
- Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Hiroshi Mori
- Osaka Metropolitan University Medical School, Osaka, Nagaoka Sutoku University, Osaka City, Niigata, Japan
| | | | - Jae-Hong Lee
- Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
| | - Pedro Rosa-Neto
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Myuri Ruthirakuhan
- Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Che-Yuan Wu
- Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Walter Swardfager
- Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | | | - Hamid R. Sohrabi
- Centre for Healthy Ageing, School of Psychology, Health Future Institute, Murdoch University, Perth, Western Australia, Australia
| | - Ralph N. Martins
- School of Medical and Health Sciences, Edith Cowan University, Perth, Western Australia, Australia
| | - Randall J. Bateman
- Washington University in St Louis School of Medicine, St Louis, Missouri
| | - Keith A. Johnson
- Massachusetts General Hospital, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | - Reisa A. Sperling
- Massachusetts General Hospital, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | - Steven M. Greenberg
- Massachusetts General Hospital, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | - Aaron P. Schultz
- Massachusetts General Hospital, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | - Jasmeer P. Chhatwal
- Massachusetts General Hospital, Brigham and Women’s Hospital, Harvard Medical School, Boston
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Busby N, Wilson S, Wilmskoetter J, Newman-Norlund R, Sayers S, Newman-Norlund S, Roth R, Rorden C, Fridriksson J, Bonilha L. White matter hyperintensity load mediates the relationship between age and cognition. Neurobiol Aging 2023; 132:56-66. [PMID: 37729770 DOI: 10.1016/j.neurobiolaging.2023.08.007] [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: 04/25/2023] [Revised: 08/14/2023] [Accepted: 08/21/2023] [Indexed: 09/22/2023]
Abstract
To elucidate the relationship between age and cognitive decline, it is important to consider structural brain changes such as white matter hyperintensities (WMHs), which are common in older age and may affect behavior. Therefore, we aimed to investigate if WMH load is a mediator of the relationship between age and cognitive decline. Healthy participants (N = 166, 20-80 years) completed the Montreal Cognitive Assessment (MoCA). WMHs were manually delineated on FLAIR scans. Mediation analysis was conducted to determine if WMH load mediates the relationship between age and cognition. Older age was associated with worse cognition (p < 0.001), but this was an indirect effect: older participants had more WMHs, and, in turn, increased WMH load was associated with worse MoCA scores. WMH load mediates the relationship between age and cognitive decline. Importantly, this relationship was not moderated by age (i.e., increased WMH severity is associated with poorer MoCA scores irrespective of age). Across all ages, high cholesterol was associated with increased WMH severity.
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Affiliation(s)
- Natalie Busby
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA.
| | - Sarah Wilson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA
| | - Janina Wilmskoetter
- Department of Health and Rehabilitation Sciences, Medical University of South Carolina, Charleston, SC, USA
| | | | - Sara Sayers
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA
| | - Sarah Newman-Norlund
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA
| | - Rebecca Roth
- Department of Neurology, Emory University, Atlanta, GA, USA
| | - Chris Rorden
- Department of Psychology, University of South Carolina, Columbia, SC, USA
| | - Julius Fridriksson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA
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15
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Coenen M, Biessels GJ, DeCarli C, Fletcher EF, Maillard PM, Barkhof F, Barnes J, Benke T, Boomsma JMF, P L H Chen C, Dal-Bianco P, Dewenter A, Duering M, Enzinger C, Ewers M, Exalto LG, Franzmeier N, Groeneveld O, Hilal S, Hofer E, Koek HL, Maier AB, McCreary CR, Papma JM, Paterson RW, Pijnenburg YAL, Rubinski A, Schmidt R, Schott JM, Slattery CF, Smith EE, Sudre CH, Steketee RME, van den Berg E, van der Flier WM, Venketasubramanian N, Vernooij MW, Wolters FJ, Xin X, Biesbroek JM, Kuijf HJ. Spatial distributions of white matter hyperintensities on brain MRI: A pooled analysis of individual participant data from 11 memory clinic cohorts. Neuroimage Clin 2023; 40:103547. [PMID: 38035457 PMCID: PMC10698002 DOI: 10.1016/j.nicl.2023.103547] [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] [Received: 08/27/2023] [Revised: 11/03/2023] [Accepted: 11/21/2023] [Indexed: 12/02/2023]
Abstract
INTRODUCTION The spatial distribution of white matter hyperintensities (WMH) on MRI is often considered in the diagnostic evaluation of patients with cognitive problems. In some patients, clinicians may classify WMH patterns as "unusual", but this is largely based on expert opinion, because detailed quantitative information about WMH distribution frequencies in a memory clinic setting is lacking. Here we report voxel wise 3D WMH distribution frequencies in a large multicenter dataset and also aimed to identify individuals with unusual WMH patterns. METHODS Individual participant data (N = 3525, including 777 participants with subjective cognitive decline, 1389 participants with mild cognitive impairment and 1359 patients with dementia) from eleven memory clinic cohorts, recruited through the Meta VCI Map Consortium, were used. WMH segmentations were provided by participating centers or performed in Utrecht and registered to the Montreal Neurological Institute (MNI)-152 brain template for spatial normalization. To determine WMH distribution frequencies, we calculated WMH probability maps at voxel level. To identify individuals with unusual WMH patterns, region-of-interest (ROI) based WMH probability maps, rule-based scores, and a machine learning method (Local Outlier Factor (LOF)), were implemented. RESULTS WMH occurred in 82% of voxels from the white matter template with large variation between subjects. Only a small proportion of the white matter (1.7%), mainly in the periventricular areas, was affected by WMH in at least 20% of participants. A large portion of the total white matter was affected infrequently. Nevertheless, 93.8% of individual participants had lesions in voxels that were affected in less than 2% of the population, mainly located in subcortical areas. Only the machine learning method effectively identified individuals with unusual patterns, in particular subjects with asymmetric WMH distribution or with WMH at relatively rarely affected locations despite common locations not being affected. DISCUSSION Aggregating data from several memory clinic cohorts, we provide a detailed 3D map of WMH lesion distribution frequencies, that informs on common as well as rare localizations. The use of data-driven analysis with LOF can be used to identify unusual patterns, which might serve as an alert that rare causes of WMH should be considered.
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Affiliation(s)
- Mirthe Coenen
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, Utrecht, the Netherlands.
| | - Geert Jan Biessels
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, Utrecht, the Netherlands
| | - Charles DeCarli
- Department of Neurology, University of California at Davis, USA
| | - Evan F Fletcher
- Department of Neurology, University of California at Davis, USA
| | | | - Frederik Barkhof
- Radiology & Nuclear Medicine, Amsterdam UMC, Location Vrije Universiteit, the Netherlands; UCL Institute of Neurology, London, UK
| | - Josephine Barnes
- Dementia Research Centre, UCL Queen Square Institute of Neurology, UCL, London, UK
| | - Thomas Benke
- Clinic of Neurology, Medical University Innsbruck, Austria
| | - Jooske M F Boomsma
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| | - Christopher P L H Chen
- Department of Pharmacology, National University of Singapore, Singapore, Singapore; Memory, Aging and Cognition Center, National University Health System, Singapore, Singapore
| | | | - Anna Dewenter
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Marco Duering
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany; Medical Image Analysis Center (MIAC) and Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Christian Enzinger
- Division of General Neurology, Department of Neurology, Medical University Graz, Austria; Division of Neuroradiology, Interventional and Vascular Radiology, Department of Radiology, Medical University of Graz, Austria
| | - Michael Ewers
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Lieza G Exalto
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, Utrecht, the Netherlands
| | - Nicolai Franzmeier
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany; Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Onno Groeneveld
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, Utrecht, the Netherlands; Department of Neurology, Isala, Meppel, the Netherlands
| | - Saima Hilal
- Department of Pharmacology, National University of Singapore, Singapore, Singapore; Memory, Aging and Cognition Center, National University Health System, Singapore, Singapore; Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Edith Hofer
- Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Austria; Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Austria
| | - Huiberdina L Koek
- Department of Geriatric Medicine, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Andrea B Maier
- Memory, Aging and Cognition Center, National University Health System, Singapore, Singapore; Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Centre for Healthy Longevity, @AgeSingapore, National University Health System, Singapore; Department of Clinical Neurosciences and Radiology and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Cheryl R McCreary
- Department of Clinical Neurosciences and Radiology and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Janne M Papma
- Alzheimer Center Erasmus MC, Erasmus MC University Medical Center, Rotterdam, the Netherlands; Department of Neurology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - Ross W Paterson
- Dementia Research Centre, UCL Queen Square Institute of Neurology, UCL, London, UK
| | - Yolande A L Pijnenburg
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| | - Anna Rubinski
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Reinhold Schmidt
- Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Austria
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, UCL, London, UK
| | - Catherine F Slattery
- Dementia Research Centre, UCL Queen Square Institute of Neurology, UCL, London, UK
| | - Eric E Smith
- Department of Clinical Neurosciences and Radiology and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Carole H Sudre
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK; Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Rebecca M E Steketee
- Alzheimer Center Erasmus MC, Erasmus MC University Medical Center, Rotterdam, the Netherlands; Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - Esther van den Berg
- Alzheimer Center Erasmus MC, Erasmus MC University Medical Center, Rotterdam, the Netherlands; Department of Neurology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| | - Narayanaswamy Venketasubramanian
- Memory, Aging and Cognition Center, National University Health System, Singapore, Singapore; Raffles Neuroscience Center, Raffles Hospital, Singapore, Singapore
| | - Meike W Vernooij
- Alzheimer Center Erasmus MC, Erasmus MC University Medical Center, Rotterdam, the Netherlands; Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, the Netherlands; Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - Frank J Wolters
- Alzheimer Center Erasmus MC, Erasmus MC University Medical Center, Rotterdam, the Netherlands; Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, the Netherlands; Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - Xu Xin
- Department of Pharmacology, National University of Singapore, Singapore, Singapore; Memory, Aging and Cognition Center, National University Health System, Singapore, Singapore
| | - J Matthijs Biesbroek
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, Utrecht, the Netherlands; Department of Neurology, Diakonessenhuis Hospital, Utrecht, the Netherlands
| | - Hugo J Kuijf
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands
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Eloyan A, Thangarajah M, An N, Borowski BJ, Reddy AL, Aisen P, Dage JL, Foroud T, Ghetti B, Griffin P, Hammers D, Iaccarino L, Jack CR, Kirby K, Kramer J, Koeppe R, Kukull WA, La Joie R, Mundada NS, Murray ME, Nudelman K, Rumbaugh M, Soleimani-Meigooni DN, Toga A, Touroutoglou A, Atri A, Day GS, Duara R, Graff-Radford NR, Honig LS, Jones DT, Masdeu J, Mendez MF, Musiek E, Onyike CU, Rogalski E, Salloway S, Sha S, Turner RS, Wingo TS, Wolk DA, Womack K, Beckett L, Gao S, Carrillo MC, Rabinovici G, Apostolova LG, Dickerson B, Vemuri P. White matter hyperintensities are higher among early-onset Alzheimer's disease participants than their cognitively normal and early-onset nonAD peers: Longitudinal Early-onset Alzheimer's Disease Study (LEADS). Alzheimers Dement 2023; 19 Suppl 9:S89-S97. [PMID: 37491599 PMCID: PMC10808262 DOI: 10.1002/alz.13402] [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: 03/03/2023] [Revised: 05/23/2023] [Accepted: 05/24/2023] [Indexed: 07/27/2023]
Abstract
INTRODUCTION We compared white matter hyperintensities (WMHs) in early-onset Alzheimer's disease (EOAD) with cognitively normal (CN) and early-onset amyloid-negative cognitively impaired (EOnonAD) groups in the Longitudinal Early-Onset Alzheimer's Disease Study. METHODS We investigated the role of increased WMH in cognition and amyloid and tau burden. We compared WMH burden of 205 EOAD, 68 EOnonAD, and 89 CN participants in lobar regions using t-tests and analyses of covariance. Linear regression analyses were used to investigate the association between WMH and cognitive impairment and that between amyloid and tau burden. RESULTS EOAD showed greater WMHs compared with CN and EOnonAD participants across all regions with no significant differences between CN and EOnonAD groups. Greater WMHs were associated with worse cognition. Tau burden was positively associated with WMH burden in the EOAD group. DISCUSSION EOAD consistently showed higher WMH volumes. Overall, greater WMHs were associated with worse cognition and higher tau burden in EOAD. HIGHLIGHTS This study represents a comprehensive characterization of WMHs in sporadic EOAD. WMH volumes are associated with tau burden from positron emission tomography (PET) in EOAD, suggesting WMHs are correlated with increasing burden of AD. Greater WMH volumes are associated with worse performance on global cognitive tests. EOAD participants have higher WMH volumes compared with CN and early-onset amyloid-negative cognitively impaired (EOnonAD) groups across all brain regions.
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Affiliation(s)
- Ani Eloyan
- Department of Biostatistics, Center for Statistical Sciences, Brown University, Providence, Rhode Island, USA, 02903
| | - Maryanne Thangarajah
- Department of Biostatistics, Center for Statistical Sciences, Brown University, Providence, Rhode Island, USA, 02903
| | - Na An
- Department of Biostatistics, Center for Statistical Sciences, Brown University, Providence, Rhode Island, USA, 02903
| | - Bret J. Borowski
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA, 55905
| | - Ashritha L. Reddy
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA, 55905
| | - Paul Aisen
- Alzheimer’s Therapeutic Research Institute, University of Southern California, San Diego, California, USA, 92121
| | - Jeffrey L. Dage
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
| | - Bernardino Ghetti
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
- Department of Pathology & Laboratory Medicine Indiana University School of Medicine, Indianapolis, Indiana, USA, 02912
| | - Percy Griffin
- Medical & Scientific Relations Division, Alzheimer’s Association, Chicago, Illinois, USA, 60603
| | - Dustin Hammers
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
| | - Leonardo Iaccarino
- Department of Neurology, University of California – San Francisco, San Francisco, California, USA, 94143
| | - Clifford R. Jack
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
| | - Kala Kirby
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
| | - Joel Kramer
- Department of Neurology, University of California – San Francisco, San Francisco, California, USA, 94143
| | - Robert Koeppe
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA, 48109
| | - Walter A. Kukull
- Department of Epidemiology, University of Washington, Seattle, Washington, USA, 98195
| | - Renaud La Joie
- Department of Neurology, University of California – San Francisco, San Francisco, California, USA, 94143
| | - Nidhi S Mundada
- Department of Neurology, University of California – San Francisco, San Francisco, California, USA, 94143
| | - Melissa E. Murray
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, USA, 32224
| | - Kelly Nudelman
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
| | - Malia Rumbaugh
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
| | | | - Arthur Toga
- Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Los Angeles, California, USA, 90033
| | - Alexandra Touroutoglou
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA, 02114
| | - Alireza Atri
- Banner Sun Health Research Institute, Sun City, Arizona, USA, 85351
| | - Gregory S. Day
- Department of Neurology, Mayo Clinic, Jacksonville, Florida, USA, 32224
| | - Ranjan Duara
- Wien Center for Alzheimer’s Disease and Memory Disorders, Mount Sinai Medical Center, Miami, Florida, USA, 33140
| | | | - Lawrence S. Honig
- Taub Institute and Department of Neurology, Columbia University Irving Medical Center, New York, New York, USA,10032
| | - David T. Jones
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA, 55905
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA, 55905
| | - Joseph Masdeu
- Nantz National Alzheimer Center, Houston Methodist and Weill Cornell Medicine, Houston, Texas, USA, 77030
| | - Mario F. Mendez
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA, 90095
| | - Erik Musiek
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA, 63108
| | - Chiadi U. Onyike
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA, 21205
| | - 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, 60611
| | - Stephen Salloway
- Department of Neurology, Alpert Medical School, Brown University, Providence, Rhode Island, USA, 02912
| | - Sharon Sha
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, California, USA, 94304
| | - Raymond S. Turner
- Department of Neurology, Georgetown University, Washington D.C., USA, 20007
| | - Thomas S. Wingo
- Department of Neurology and Human Genetics, Emory University School of Medicine, Atlanta, Georgia, USA, 30322
| | - David A. Wolk
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA, 19104
| | - Kyle Womack
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA, 63108
| | - Laurel Beckett
- Department of Public Health Sciences, University of California – Davis, Davis, California, USA, 95616
| | - Sujuan Gao
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
| | - Maria C. Carrillo
- Medical & Scientific Relations Division, Alzheimer’s Association, Chicago, Illinois, USA, 60603
| | - Gil Rabinovici
- Department of Neurology, University of California – San Francisco, San Francisco, California, USA, 94143
| | - Liana G. Apostolova
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine Indianapolis, Indianapolis, Indiana, USA, 46202
| | - Brad Dickerson
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA, 02114
| | - Prashanthi Vemuri
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA, 55905
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Meade CS, Bell RP, Towe SL, Lascola CD, Al‐Khalil K, Gibson MJ. Cocaine use is associated with cerebral white matter hyperintensities in HIV disease. Ann Clin Transl Neurol 2023; 10:1633-1646. [PMID: 37475160 PMCID: PMC10502656 DOI: 10.1002/acn3.51854] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Revised: 06/16/2023] [Accepted: 07/09/2023] [Indexed: 07/22/2023] Open
Abstract
BACKGROUND White matter hyperintensities (WMH), a marker of cerebral small vessel disease and predictor of cognitive decline, are observed at higher rates in persons with HIV (PWH). The use of cocaine, a potent central nervous system stimulant, is disproportionately common in PWH and may contribute to WMH. METHODS The sample included of 110 PWH on antiretroviral therapy. Fluid-attenuated inversion recovery (FLAIR) and T1-weighted anatomical MRI scans were collected, along with neuropsychological testing. FLAIR images were processed using the Lesion Segmentation Toolbox. A hierarchical regression model was run to investigate predictors of WMH burden [block 1: demographics; block 2: cerebrovascular disease (CVD) risk; block 3: lesion burden]. RESULTS The sample was 20% female and 79% African American with a mean age of 45.37. All participants had persistent HIV viral suppression, and the median CD4+ T-cell count was 750. Nearly a third (29%) currently used cocaine regularly, with an average of 23.75 (SD = 20.95) days in the past 90. In the hierarchical linear regression model, cocaine use was a significant predictor of WMH burden (β = .28). WMH burden was significantly correlated with poorer cognitive function (r = -0.27). Finally, higher WMH burden was significantly associated with increased serum concentrations of interferon-γ-inducible protein 10 (IP-10) but lower concentrations of myeloperoxidase (MPO); however, these markers did not differ by COC status. CONCLUSIONS WMH burden is associated with poorer cognitive performance in PWH. Cocaine use and CVD risk independently contribute to WMH, and addressing these conditions as part of HIV care may mitigate brain injury underlying neurocognitive impairment.
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Affiliation(s)
- Christina S. Meade
- Department of Psychiatry and Behavioral SciencesDuke University School of MedicineDurhamNorth Carolina27710USA
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth Carolina27710USA
| | - Ryan P. Bell
- Department of Psychiatry and Behavioral SciencesDuke University School of MedicineDurhamNorth Carolina27710USA
| | - Sheri L. Towe
- Department of Psychiatry and Behavioral SciencesDuke University School of MedicineDurhamNorth Carolina27710USA
| | - Christopher D. Lascola
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth Carolina27710USA
- Department of RadiologyDuke University School of MedicineDurhamNorth Carolina27710USA
| | - Kareem Al‐Khalil
- Department of Psychiatry and Behavioral SciencesDuke University School of MedicineDurhamNorth Carolina27710USA
| | - Matthew J. Gibson
- Department of Psychiatry and Behavioral SciencesDuke University School of MedicineDurhamNorth Carolina27710USA
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Kamal F, Morrison C, Maranzano J, Zeighami Y, Dadar M. White Matter Hyperintensity Trajectories in Patients With Progressive and Stable Mild Cognitive Impairment. Neurology 2023; 101:e815-e824. [PMID: 37407262 PMCID: PMC10449435 DOI: 10.1212/wnl.0000000000207514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 04/25/2023] [Indexed: 07/07/2023] Open
Abstract
BACKGROUND AND OBJECTIVES White matter hyperintensities (WMH) are pathologic brain changes that are associated with increased age and cognitive decline. However, the association of WMH burden with amyloid positivity and conversion to dementia in people with mild cognitive impairment (MCI) is unclear. The aim of this study was to expand on this research by examining whether change in WMH burden over time differs in amyloid-negative (Aβ-) and amyloid-positive (Aβ+) people with MCI who either remain stable or convert to dementia. To examine this question, we compared regional WMH burden in 4 groups: Aβ+ progressor, Aβ- progressor, Aβ+ stable, and Aβ- stable. METHODS Participants with MCI from the Alzheimer Disease Neuroimaging Initiative were included if they had APOE ɛ4 status and if amyloid measures were available to determine amyloid status (i.e., Aβ+, or Aβ-). Participants with a baseline diagnosis of MCI and who had APOE ɛ4 information and amyloid measures were included. An average of 5.7 follow-up time points per participant were included, with a total of 5,054 follow-up time points with a maximum follow-up duration of 13 years. Differences in total and regional WMH burden were examined using linear mixed-effects models. RESULTS A total of 820 participants (55-90 years of age) were included in the study (Aβ+ progressor, n = 239; Aβ- progressor, n = 22; Aβ+ stable, n = 343; Aβ- stable, n = 216). People who were Aβ- stable exhibited reduced baseline WMH compared with Aβ+ progressors and people who were Aβ+ stable at all regions of interest (β belongs to 0.20-0.33, CI belongs to 0.03-0.49, p < 0.02), except deep WMH. When examining longitudinal results, compared with people who were Aβ- stable, all groups had steeper accumulation in WMH burden with Aβ+ progressors (β belongs to -0.03 to 0.06, CI belongs to -0.05 to 0.09, p < 0.01) having the largest increase (i.e., largest increase in WMH accumulation over time). DISCUSSION These results indicate that WMH accumulation contributes to conversion to dementia in older adults with MCI who are Aβ+ and Aβ-.
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Affiliation(s)
- Farooq Kamal
- From the Department of Psychiatry (F.K., Y.Z., M.D.), McGill University; Douglas Mental Health University Institute (F.K., Y.Z., M.D.); Department of Neurology and Neurosurgery (C.M., J.M.), Faculty of Medicine, and McConnell Brain Imaging Centre (C.M.), Montreal Neurological Institute, McGill University; and Department of Anatomy (J.M.), University of Quebec in Trois-Rivières, Canada.
| | - Cassandra Morrison
- From the Department of Psychiatry (F.K., Y.Z., M.D.), McGill University; Douglas Mental Health University Institute (F.K., Y.Z., M.D.); Department of Neurology and Neurosurgery (C.M., J.M.), Faculty of Medicine, and McConnell Brain Imaging Centre (C.M.), Montreal Neurological Institute, McGill University; and Department of Anatomy (J.M.), University of Quebec in Trois-Rivières, Canada
| | - Josefina Maranzano
- From the Department of Psychiatry (F.K., Y.Z., M.D.), McGill University; Douglas Mental Health University Institute (F.K., Y.Z., M.D.); Department of Neurology and Neurosurgery (C.M., J.M.), Faculty of Medicine, and McConnell Brain Imaging Centre (C.M.), Montreal Neurological Institute, McGill University; and Department of Anatomy (J.M.), University of Quebec in Trois-Rivières, Canada
| | - Yashar Zeighami
- From the Department of Psychiatry (F.K., Y.Z., M.D.), McGill University; Douglas Mental Health University Institute (F.K., Y.Z., M.D.); Department of Neurology and Neurosurgery (C.M., J.M.), Faculty of Medicine, and McConnell Brain Imaging Centre (C.M.), Montreal Neurological Institute, McGill University; and Department of Anatomy (J.M.), University of Quebec in Trois-Rivières, Canada
| | - Mahsa Dadar
- From the Department of Psychiatry (F.K., Y.Z., M.D.), McGill University; Douglas Mental Health University Institute (F.K., Y.Z., M.D.); Department of Neurology and Neurosurgery (C.M., J.M.), Faculty of Medicine, and McConnell Brain Imaging Centre (C.M.), Montreal Neurological Institute, McGill University; and Department of Anatomy (J.M.), University of Quebec in Trois-Rivières, Canada
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19
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Garnier-Crussard A, Cotton F, Krolak-Salmon P, Chételat G. White matter hyperintensities in Alzheimer's disease: Beyond vascular contribution. Alzheimers Dement 2023; 19:3738-3748. [PMID: 37027506 DOI: 10.1002/alz.13057] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 02/15/2023] [Accepted: 03/03/2023] [Indexed: 04/09/2023]
Abstract
White matter hyperintensities (WMH), frequently seen in older adults, are usually considered vascular lesions, and participate in the vascular contribution to cognitive impairment and dementia. However, emerging evidence highlights the heterogeneity of WMH pathophysiology, suggesting that non-vascular mechanisms could also be involved, notably in Alzheimer's disease (AD). This led to the alternative hypothesis that in AD, part of WMH may be secondary to AD-related processes. The current perspective brings together the arguments from different fields of research, including neuropathology, neuroimaging and fluid biomarkers, and genetics, in favor of this alternative hypothesis. Possible underlying mechanisms leading to AD-related WMH, such as AD-related neurodegeneration or neuroinflammation, are discussed, as well as implications for diagnostic criteria and management of AD. We finally discuss ways to test this hypothesis and remaining challenges. Acknowledging the heterogeneity of WMH and the existence of AD-related WMH may improve personalized diagnosis and care of patients.
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Affiliation(s)
- Antoine Garnier-Crussard
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders," Neuropresage Team, Cyceron, Caen, France
- Clinical and Research Memory Center of Lyon, Lyon Institute For Aging, Hospices Civils de Lyon, Villeurbanne, France
- Eduwell team, Lyon Neuroscience Research Center (CRNL), INSERM U1028, CNRS UMR5292, UCBL1, Lyon, France
| | - François Cotton
- Radiology Department, Centre Hospitalier Lyon-Sud, Hospices Civils de Lyon, Pierre-Bénite, France
- CREATIS, INSERM U1044, CNRS UMR 5220, UCBL1, Villeurbanne, France
| | - Pierre Krolak-Salmon
- Clinical and Research Memory Center of Lyon, Lyon Institute For Aging, Hospices Civils de Lyon, Villeurbanne, France
- Eduwell team, Lyon Neuroscience Research Center (CRNL), INSERM U1028, CNRS UMR5292, UCBL1, Lyon, France
| | - Gaël Chételat
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders," Neuropresage Team, Cyceron, Caen, France
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Twait EL, Min B, Beran M, Vonk JMJ, Geerlings MI. The cross-sectional association between amyloid burden and white matter hyperintensities in older adults without cognitive impairment: A systematic review and meta-analysis. Ageing Res Rev 2023; 88:101952. [PMID: 37178806 DOI: 10.1016/j.arr.2023.101952] [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: 01/04/2023] [Revised: 05/08/2023] [Accepted: 05/09/2023] [Indexed: 05/15/2023]
Abstract
Alzheimer's disease (AD) is the most common cause of dementia, characterized by the aggregation of amyloid-beta (Aβ) proteins into plaques. Individuals with AD frequently show mixed pathologies, often caused by cerebral small vessel disease (CSVD), resulting in lesions such as white matter hyperintensities (WMH). The current systematic review and meta-analysis investigated the cross-sectional relationship between amyloid burden and WMH in older adults without objective cognitive impairment. A systematic search performed in PubMed, Embase, and PsycINFO yielded 13 eligible studies. Aβ was assessed using PET, CSF, or plasma measurements. Two meta-analyses were performed: one on Cohen's d metrics and one on correlation coefficients. The meta-analyses revealed an overall weighted small-to-medium Cohen's d of 0.55 (95% CI: 0.31-0.78) in CSF, an overall correlation of 0.31 (0.09-0.50) in CSF, and a large Cohen's d of 0.96 (95% CI: 0.66-1.27) in PET. Only two studies assessed this relationship in plasma, with an effect size of - 0.20 (95% CI: -0.75 to 0.34). These findings indicate a relationship between both amyloid and vascular pathologies in cognitively normal adults in PET and CSF. Future studies should assess the possible relationship of blood amyloid-beta and WMH for broader identification of at risk individuals showing mixed pathology in preclinical stages.
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Affiliation(s)
- Emma L Twait
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands; Amsterdam UMC, Location Vrije Universiteit, Department of General Practice, Amsterdam, The Netherlands; Research Institute Amsterdam Public Health, Research Programme Aging & Later life, and Research Programme Personalized Medicine, Amsterdam, The Netherlands
| | - Britt Min
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands; Bachelor Program Biomedical Sciences, Faculty of Medicine, Utrecht University, Utrecht, The Netherlands
| | - Magdalena Beran
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands; School for Cardiovascular Disease (CARIM), Department of Internal Medicine, Maastricht University, Maastricht, The Netherlands
| | - Jet M J Vonk
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands; Department of Neurology, Memory and Aging Center, University of California San Francisco (UCSF), San Francisco, CA, USA
| | - Mirjam I Geerlings
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands; Research Institute Amsterdam Public Health, Research Programme Aging & Later life, and Research Programme Personalized Medicine, Amsterdam, The Netherlands; Research Institute Amsterdam Neuroscience, Research Programme Neurodegeneration, and Research Programme Mood, Anxiety, Psychosis, Stress, and Sleep, Amsterdam, The Netherlands; Amsterdam UMC, location University of Amsterdam, Department of General Practice, Amsterdam, The Netherlands.
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21
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Li M, Gao Y, Lawless RD, Xu L, Zhao Y, Schilling KG, Ding Z, Anderson AW, Landman BA, Gore JC. Changes in white matter functional networks across late adulthood. Front Aging Neurosci 2023; 15:1204301. [PMID: 37455933 PMCID: PMC10347529 DOI: 10.3389/fnagi.2023.1204301] [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: 04/12/2023] [Accepted: 06/14/2023] [Indexed: 07/18/2023] Open
Abstract
Introduction The aging brain is characterized by decreases in not only neuronal density but also reductions in myelinated white matter (WM) fibers that provide the essential foundation for communication between cortical regions. Age-related degeneration of WM has been previously characterized by histopathology as well as T2 FLAIR and diffusion MRI. Recent studies have consistently shown that BOLD (blood oxygenation level dependent) effects in WM are robustly detectable, are modulated by neural activities, and thus represent a complementary window into the functional organization of the brain. However, there have been no previous systematic studies of whether or how WM BOLD signals vary with normal aging. We therefore performed a comprehensive quantification of WM BOLD signals across scales to evaluate their potential as indicators of functional changes that arise with aging. Methods By using spatial independent component analysis (ICA) of BOLD signals acquired in a resting state, WM voxels were grouped into spatially distinct functional units. The functional connectivities (FCs) within and among those units were measured and their relationships with aging were assessed. On a larger spatial scale, a graph was reconstructed based on the pair-wise connectivities among units, modeling the WM as a complex network and producing a set of graph-theoretical metrics. Results The spectral powers that reflect the intensities of BOLD signals were found to be significantly affected by aging across more than half of the WM units. The functional connectivities (FCs) within and among those units were found to decrease significantly with aging. We observed a widespread reduction of graph-theoretical metrics, suggesting a decrease in the ability to exchange information between remote WM regions with aging. Discussion Our findings converge to support the notion that WM BOLD signals in specific regions, and their interactions with other regions, have the potential to serve as imaging markers of aging.
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Affiliation(s)
- Muwei Li
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Yurui Gao
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States
| | - Richard D. Lawless
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, United States
| | - Lyuan Xu
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, United States
| | - Yu Zhao
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Kurt G. Schilling
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Zhaohua Ding
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, United States
- Department of Computer Science, Vanderbilt University, Nashville, TN, United States
| | - Adam W. Anderson
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States
| | - Bennett A. Landman
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, United States
| | - John C. Gore
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States
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22
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Bernal J, Schreiber S, Menze I, Ostendorf A, Pfister M, Geisendörfer J, Nemali A, Maass A, Yakupov R, Peters O, Preis L, Schneider L, Herrera AL, Priller J, Spruth EJ, Altenstein S, Schneider A, Fliessbach K, Wiltfang J, Schott BH, Rostamzadeh A, Glanz W, Buerger K, Janowitz D, Ewers M, Perneczky R, Rauchmann BS, Teipel S, Kilimann I, Laske C, Munk MH, Spottke A, Roy N, Dobisch L, Dechent P, Scheffler K, Hetzer S, Wolfsgruber S, Kleineidam L, Schmid M, Berger M, Jessen F, Wirth M, Düzel E, Ziegler G. Arterial hypertension and β-amyloid accumulation have spatially overlapping effects on posterior white matter hyperintensity volume: a cross-sectional study. Alzheimers Res Ther 2023; 15:97. [PMID: 37226207 DOI: 10.1186/s13195-023-01243-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 05/09/2023] [Indexed: 05/26/2023]
Abstract
BACKGROUND White matter hyperintensities (WMH) in subjects across the Alzheimer's disease (AD) spectrum with minimal vascular pathology suggests that amyloid pathology-not just arterial hypertension-impacts WMH, which in turn adversely influences cognition. Here we seek to determine the effect of both hypertension and Aβ positivity on WMH, and their impact on cognition. METHODS We analysed data from subjects with a low vascular profile and normal cognition (NC), subjective cognitive decline (SCD), and amnestic mild cognitive impairment (MCI) enrolled in the ongoing observational multicentre DZNE Longitudinal Cognitive Impairment and Dementia Study (n = 375, median age 70.0 [IQR 66.0, 74.4] years; 178 female; NC/SCD/MCI 127/162/86). All subjects underwent a rich neuropsychological assessment. We focused on baseline memory and executive function-derived from multiple neuropsychological tests using confirmatory factor analysis-, baseline preclinical Alzheimer's cognitive composite 5 (PACC5) scores, and changes in PACC5 scores over the course of three years (ΔPACC5). RESULTS Subjects with hypertension or Aβ positivity presented the largest WMH volumes (pFDR < 0.05), with spatial overlap in the frontal (hypertension: 0.42 ± 0.17; Aβ: 0.46 ± 0.18), occipital (hypertension: 0.50 ± 0.16; Aβ: 0.50 ± 0.16), parietal lobes (hypertension: 0.57 ± 0.18; Aβ: 0.56 ± 0.20), corona radiata (hypertension: 0.45 ± 0.17; Aβ: 0.40 ± 0.13), optic radiation (hypertension: 0.39 ± 0.18; Aβ: 0.74 ± 0.19), and splenium of the corpus callosum (hypertension: 0.36 ± 0.12; Aβ: 0.28 ± 0.12). Elevated global and regional WMH volumes coincided with worse cognitive performance at baseline and over 3 years (pFDR < 0.05). Aβ positivity was negatively associated with cognitive performance (direct effect-memory: - 0.33 ± 0.08, pFDR < 0.001; executive: - 0.21 ± 0.08, pFDR < 0.001; PACC5: - 0.29 ± 0.09, pFDR = 0.006; ΔPACC5: - 0.34 ± 0.04, pFDR < 0.05). Splenial WMH mediated the relationship between hypertension and cognitive performance (indirect-only effect-memory: - 0.05 ± 0.02, pFDR = 0.029; executive: - 0.04 ± 0.02, pFDR = 0.067; PACC5: - 0.05 ± 0.02, pFDR = 0.030; ΔPACC5: - 0.09 ± 0.03, pFDR = 0.043) and WMH in the optic radiation partially mediated that between Aβ positivity and memory (indirect effect-memory: - 0.05 ± 0.02, pFDR = 0.029). CONCLUSIONS Posterior white matter is susceptible to hypertension and Aβ accumulation. Posterior WMH mediate the association between these pathologies and cognitive dysfunction, making them a promising target to tackle the downstream damage related to the potentially interacting and potentiating effects of the two pathologies. TRIAL REGISTRATION German Clinical Trials Register (DRKS00007966, 04/05/2015).
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Affiliation(s)
- Jose Bernal
- Institute of Cognitive Neurology and Dementia Research, Otto-Von-Guericke University Magdeburg, Magdeburg, Germany.
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany.
| | - Stefanie Schreiber
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
- Department of Neurology, Medical Faculty, University Hospital Magdeburg, Magdeburg, Germany
| | - Inga Menze
- Institute of Cognitive Neurology and Dementia Research, Otto-Von-Guericke University Magdeburg, Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
| | - Anna Ostendorf
- Institute of Cognitive Neurology and Dementia Research, Otto-Von-Guericke University Magdeburg, Magdeburg, Germany
| | - Malte Pfister
- Department of Neurology, Medical Faculty, University Hospital Magdeburg, Magdeburg, Germany
| | - Jonas Geisendörfer
- Department of Neurology, Medical Faculty, University Hospital Magdeburg, Magdeburg, Germany
| | - Aditya Nemali
- Institute of Cognitive Neurology and Dementia Research, Otto-Von-Guericke University Magdeburg, Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
| | - Anne Maass
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
| | - Renat Yakupov
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
| | - Oliver Peters
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Zu Berlin-Institute of Psychiatry and Psychotherapy, Berlin, Germany
| | - Lukas Preis
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Zu Berlin-Institute of Psychiatry and Psychotherapy, Berlin, Germany
| | - Luisa Schneider
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Zu Berlin-Institute of Psychiatry and Psychotherapy, Berlin, Germany
| | - Ana Lucia Herrera
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Zu Berlin-Institute of Psychiatry and Psychotherapy, Berlin, Germany
| | - Josef Priller
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Berlin, Germany
- School of Medicine, Department of Psychiatry and Psychotherapy, Technical University of Munich, Munich, Germany
- University of Edinburgh and UK DRI, Edinburgh, UK
| | - Eike Jakob Spruth
- 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
| | - Anja Schneider
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Clinic for Neurodegenerative Diseases and Geriatric Psychiatry, University of Bonn, Bonn, Germany
| | - Klaus Fliessbach
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Clinic for Neurodegenerative Diseases and Geriatric Psychiatry, University of Bonn, Bonn, Germany
| | - Jens Wiltfang
- German Center for Neurodegenerative Diseases (DZNE), Goettingen, Germany
- Department of Psychiatry and Psychotherapy, University Medical Center Goettingen, University of Goettingen, Goettingen, Germany
- Neurosciences and Signaling Group, Institute of Biomedicine (iBiMED), Department of Medical Sciences, University of Aveiro, Aveiro, Portugal
| | - Björn H Schott
- German Center for Neurodegenerative Diseases (DZNE), Goettingen, Germany
- Department of Psychiatry and Psychotherapy, University Medical Center Goettingen, University of Goettingen, Goettingen, Germany
| | - Ayda Rostamzadeh
- Department of Psychiatry, University of Cologne, Cologne, Germany
| | - Wenzel Glanz
- Institute of Cognitive Neurology and Dementia Research, Otto-Von-Guericke University Magdeburg, Magdeburg, Germany
| | - Katharina Buerger
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Daniel Janowitz
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Michael Ewers
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Robert Perneczky
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy) Munich, Munich, Germany
- Ageing Epidemiology Research Unit (AGE), School of Public Health, Imperial College London, London, UK
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
| | - Boris-Stephan Rauchmann
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Stefan Teipel
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany
- Department of Psychosomatic Medicine, Rostock University Medical Center, Rostock, Germany
| | - Ingo Kilimann
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany
- Department of Psychosomatic Medicine, Rostock University Medical Center, Rostock, Germany
| | - Christoph Laske
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
- Section for Dementia Research, Hertie Institute for Clinical Brain Research and Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Matthias H Munk
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
- Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Annika Spottke
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Clinic for Neurodegenerative Diseases and Geriatric Psychiatry, University of Bonn, Bonn, Germany
| | - Nina Roy
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Laura Dobisch
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
| | - Peter Dechent
- MR-Research in Neurosciences, Department of Cognitive Neurology, Georg-August-University Goettingen, Göttingen, Germany
| | - Klaus Scheffler
- Department for Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany
| | - Stefan Hetzer
- Berlin Center for Advanced Neuroimaging, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Steffen Wolfsgruber
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Clinic for Neurodegenerative Diseases and Geriatric Psychiatry, University of Bonn, Bonn, Germany
| | - Luca Kleineidam
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Clinic for Neurodegenerative Diseases and Geriatric Psychiatry, University of Bonn, Bonn, Germany
| | - Matthias Schmid
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Institute for Medical Biometry, Informatics and Epidemiology, University Hospital Bonn, Bonn, Germany
| | - Moritz Berger
- Institute for Medical Biometry, Informatics and Epidemiology, University Hospital Bonn, 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
| | - Miranka Wirth
- German Center for Neurodegenerative Diseases (DZNE), Tatzberg 41, Dresden, 01307, Germany.
| | - Emrah Düzel
- Institute of Cognitive Neurology and Dementia Research, Otto-Von-Guericke University Magdeburg, Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
- Institute of Cognitive Neuroscience, University College London, London, UK
| | - Gabriel Ziegler
- Institute of Cognitive Neurology and Dementia Research, Otto-Von-Guericke University Magdeburg, Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
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Botz J, Lohner V, Schirmer MD. Spatial patterns of white matter hyperintensities: a systematic review. Front Aging Neurosci 2023; 15:1165324. [PMID: 37251801 PMCID: PMC10214839 DOI: 10.3389/fnagi.2023.1165324] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 04/24/2023] [Indexed: 05/31/2023] Open
Abstract
Background White matter hyperintensities are an important marker of cerebral small vessel disease. This disease burden is commonly described as hyperintense areas in the cerebral white matter, as seen on T2-weighted fluid attenuated inversion recovery magnetic resonance imaging data. Studies have demonstrated associations with various cognitive impairments, neurological diseases, and neuropathologies, as well as clinical and risk factors, such as age, sex, and hypertension. Due to their heterogeneous appearance in location and size, studies have started to investigate spatial distributions and patterns, beyond summarizing this cerebrovascular disease burden in a single metric-its volume. Here, we review the evidence of association of white matter hyperintensity spatial patterns with its risk factors and clinical diagnoses. Design/methods We performed a systematic review in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) Statement. We used the standards for reporting vascular changes on neuroimaging criteria to construct a search string for literature search on PubMed. Studies written in English from the earliest records available until January 31st, 2023, were eligible for inclusion if they reported on spatial patterns of white matter hyperintensities of presumed vascular origin. Results A total of 380 studies were identified by the initial literature search, of which 41 studies satisfied the inclusion criteria. These studies included cohorts based on mild cognitive impairment (15/41), Alzheimer's disease (14/41), Dementia (5/41), Parkinson's disease (3/41), and subjective cognitive decline (2/41). Additionally, 6 of 41 studies investigated cognitively normal, older cohorts, two of which were population-based, or other clinical findings such as acute ischemic stroke or reduced cardiac output. Cohorts ranged from 32 to 882 patients/participants [median cohort size 191.5 and 51.6% female (range: 17.9-81.3%)]. The studies included in this review have identified spatial heterogeneity of WMHs with various impairments, diseases, and pathologies as well as with sex and (cerebro)vascular risk factors. Conclusion The results show that studying white matter hyperintensities on a more granular level might give a deeper understanding of the underlying neuropathology and their effects. This motivates further studies examining the spatial patterns of white matter hyperintensities.
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Affiliation(s)
- Jonas Botz
- Computational Neuroradiology, Department of Neuroradiology, University Hospital Bonn, Bonn, Germany
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, Germany
| | - Valerie Lohner
- Cardiovascular Epidemiology of Aging, Department of Cardiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Markus D. Schirmer
- Computational Neuroradiology, Department of Neuroradiology, University Hospital Bonn, Bonn, Germany
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
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24
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Lu Y, Jarrahi A, Moore N, Bartoli M, Brann DW, Baban B, Dhandapani KM. Inflammaging, cellular senescence, and cognitive aging after traumatic brain injury. Neurobiol Dis 2023; 180:106090. [PMID: 36934795 PMCID: PMC10763650 DOI: 10.1016/j.nbd.2023.106090] [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: 01/10/2023] [Revised: 03/01/2023] [Accepted: 03/16/2023] [Indexed: 03/19/2023] Open
Abstract
Traumatic brain injury (TBI) is associated with mortality and morbidity worldwide. Accumulating pre-clinical and clinical data suggests TBI is the leading extrinsic cause of progressive neurodegeneration. Neurological deterioration after either a single moderate-severe TBI or repetitive mild TBI often resembles dementia in aged populations; however, no currently approved therapies adequately mitigate neurodegeneration. Inflammation correlates with neurodegenerative changes and cognitive dysfunction for years post-TBI, suggesting a potential association between immune activation and both age- and TBI-induced cognitive decline. Inflammaging, a chronic, low-grade sterile inflammation associated with natural aging, promotes cognitive decline. Cellular senescence and the subsequent development of a senescence associated secretory phenotype (SASP) promotes inflammaging and cognitive aging, although the functional association between senescent cells and neurodegeneration is poorly defined after TBI. In this mini-review, we provide an overview of the pre-clinical and clinical evidence linking cellular senescence with poor TBI outcomes. We also discuss the current knowledge and future potential for senotherapeutics, including senolytics and senomorphics, which kill and/or modulate senescent cells, as potential therapeutics after TBI.
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Affiliation(s)
- Yujiao Lu
- Department of Neurosurgery, Medical College of Georgia, Augusta University, Augusta, GA 30912, United States of America.
| | - Abbas Jarrahi
- Department of Neurosurgery, Medical College of Georgia, Augusta University, Augusta, GA 30912, United States of America
| | - Nicholas Moore
- Department of Neurosurgery, Medical College of Georgia, Augusta University, Augusta, GA 30912, United States of America
| | - Manuela Bartoli
- Department of Ophthalmology, Medical College of Georgia, Augusta University, Augusta, GA 30912, United States of America
| | - Darrell W Brann
- Department of Neurosurgery, Medical College of Georgia, Augusta University, Augusta, GA 30912, United States of America
| | - Babak Baban
- Department of Oral Biology and Diagnostic Services, Dental College of Georgia, Augusta University, Augusta, GA 30912, United States of America
| | - Krishnan M Dhandapani
- Department of Neurosurgery, Medical College of Georgia, Augusta University, Augusta, GA 30912, United States of America.
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Kamal F, Morrison C, Dadar M. Investigating the relationship between sleep disturbances and white matter hyperintensities in older adults on the Alzheimer's disease spectrum. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.04.13.23288544. [PMID: 37131746 PMCID: PMC10153314 DOI: 10.1101/2023.04.13.23288544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Background While studies report that sleep disturbance can have negative effects on brain vasculature, its impact on cerebrovascular disease such as white matter hyperintensities (WMHs) in beta-amyloid positive older adults remains unexplored. Methods Linear regressions, mixed effects models, and mediation analysis examined the crosssectional and longitudinal associations between sleep disturbance, cognition, and WMH burden, and cognition in normal controls (NCs), mild cognitive impairment (MCI), and Alzheimer's disease (AD) at baseline and longitudinally. Results People with AD reported more sleep disturbance than NC and MCI. AD with sleep disturbance had more WMHs than AD without sleep disturbances. Mediation analysis revealed an effect of regional WMH burden on the relationship between sleep disturbance and future cognition. Conclusion These results suggest that WMH burden and sleep disturbance increases from aging to AD. Sleep disturbance decreases cognition through increases in WMH burden. Improved sleep could mitigate the impact of WMH accumulation and cognitive decline.
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Affiliation(s)
- Farooq Kamal
- Department of Psychiatry, McGill University, Montreal, Quebec, H3A 1A1, Canada
- Douglas Mental Health University Institute, Montreal, Quebec, H4H 1R3, Canada
| | - Cassandra Morrison
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, H3A 2B4, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, H3A 2B4, Canada
| | - Mahsa Dadar
- Department of Psychiatry, McGill University, Montreal, Quebec, H3A 1A1, Canada
- Douglas Mental Health University Institute, Montreal, Quebec, H4H 1R3, Canada
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26
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Li Z, Wang W, Sang F, Zhang Z, Li X. White matter changes underlie hypertension-related cognitive decline in older adults. Neuroimage Clin 2023; 38:103389. [PMID: 37004321 PMCID: PMC10102561 DOI: 10.1016/j.nicl.2023.103389] [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] [Received: 02/03/2023] [Revised: 03/18/2023] [Accepted: 03/25/2023] [Indexed: 03/31/2023]
Abstract
Hypertension has been well recognized as a risk factor for cognitive impairment and dementia. Although the underlying mechanisms of hypertension-affected cognitive deterioration are not fully understood, white matter changes (WMCs) seem to play an important role. WMCs include low microstructural integrity and subsequent white matter macrostructural lesions, which are common on brain imaging in hypertensive patients and are critical for multiple cognitive domains. This article provides an overview of the impact of hypertension on white matter microstructural and macrostructural changes and its link to cognitive dysfunction. Hypertension may induce microstructural changes in white matter, especially for the long-range fibers such as anterior thalamic radiation (ATR) and inferior fronto-occipital fasciculus (IFOF), and then macrostructural abnormalities affecting different lobes, especially the periventricular area. Different regions' WMCs would further exert different effects to specific cognitive domains and accelerate brain aging. As a modifiable risk factor, hypertension might provide a new perspective for alleviating and delaying cognitive impairment.
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Affiliation(s)
- Zilin Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Aging Brain Rejuvenation Initiative Centre, Beijing Normal University, Beijing 100875, China
| | - Wenxiao Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Aging Brain Rejuvenation Initiative Centre, Beijing Normal University, Beijing 100875, China
| | - Feng Sang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Aging Brain Rejuvenation Initiative Centre, Beijing Normal University, Beijing 100875, China
| | - Zhanjun Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Aging Brain Rejuvenation Initiative Centre, Beijing Normal University, Beijing 100875, China
| | - Xin Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Aging Brain Rejuvenation Initiative Centre, Beijing Normal University, Beijing 100875, China.
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27
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Chan K, Fischer C, Maralani PJ, Black SE, Moody AR, Khademi A. Alzheimer's and vascular disease classification using regional texture biomarkers in FLAIR MRI. Neuroimage Clin 2023; 38:103385. [PMID: 36989851 PMCID: PMC10074987 DOI: 10.1016/j.nicl.2023.103385] [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] [Received: 12/03/2022] [Revised: 03/20/2023] [Accepted: 03/21/2023] [Indexed: 03/30/2023]
Abstract
Interactions between subcortical vascular disease and dementia due to Alzheimer's disease (AD) are unclear, and clinical overlap between the diseases makes diagnosis challenging. Existing studies have shown regional microstructural changes specific to each disease, and that textures in fluid-attenuated inversion recovery (FLAIR) MRI images may characterize abnormalities in tissue microstructure. This work aims to investigate regional FLAIR biomarkers that can differentiate dementia cohorts with and without subcortical vascular disease. FLAIR and diffusion MRI (dMRI) volumes were obtained in 65 mild cognitive impairment (MCI), 21 AD, 44 subcortical vascular MCI (scVMCI), 22 Mixed etiology, and 48 healthy elderly patients. FLAIR texture and intensity biomarkers were extracted from the normal appearing brain matter (NABM), WML penumbra, blood supply territory (BST), and white matter tract regions of each patient. All FLAIR biomarkers were correlated to dMRI metrics in each region and global WML load, and biomarker means between groups were compared using ANOVA. Binary classifications were performed using Random Forest classifiers to investigate the predictive nature of the regional biomarkers, and SHAP feature analysis was performed to further investigate optimal regions of interest for differentiating disease groups. The regional FLAIR biomarkers were strongly correlated to MD, while all biomarker regions but white matter tracts were strongly correlated to WML burden. Classification between Mixed disease and healthy, AD, and scVMCI patients yielded accuracies of 97%, 81%, and 72% respectively using WM tract biomarkers. Classification between scVMCI and healthy, MCI, and AD patients yielded accuracies of 89%, 84%, and 79% respectively using penumbra biomarkers. Only the classification between AD and healthy patients had optimal results using NABM biomarkers. This work presents novel regional FLAIR biomarkers that may quantify white matter degeneration related to subcortical vascular disease, and which indicate that investigating degeneration in specific regions may be more important than assessing global WML burden in vascular disease groups.
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Affiliation(s)
- Karissa Chan
- Electrical, Computer and Biomedical Engineering Department, Toronto Metropolitan University, 350 Victoria St., Toronto, ON M5B 2K3, Canada; Institute for Biomedical Engineering, Science Tech (iBEST), A Partnership Between St. Michael's Hospital and Toronto Metropolitan University, 209 Victoria St., Toronto, ON M5B 1T8, Canada.
| | - Corinne Fischer
- Institute of Medical Science, University of Toronto, 1 King's College Circle, Toronto, ON M5S 1A8, Canada; Keenan Research Center for Biomedical Science, St. Michael's Hospital, Unity Health Network, 30 Bond St., Toronto, ON M5B 1W8, Canada; Department of Psychiatry, Faculty of Medicine, University of Toronto, 250 College Street, Toronto, ON M5T 1R8, Canada.
| | - Pejman Jabehdar Maralani
- Department of Medical Imaging, University of Toronto, 263 McCaul St., Toronto, ON M5T 1W7, Canada.
| | - Sandra E Black
- Institute of Medical Science, University of Toronto, 1 King's College Circle, Toronto, ON M5S 1A8, Canada; Horvitz Brain Sciences Research Program, Sunnybrook Research Institute, 2075 Bayview Avenue, Toronto, ON M4N 3M5, Canada; Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Toronto, ON M4N 3M5, Canada; L.C. Campbell Cognitive Neurology Research Unit, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Toronto, ON M4N 3M5, Canada.
| | - Alan R Moody
- Department of Medical Imaging, University of Toronto, 263 McCaul St., Toronto, ON M5T 1W7, Canada.
| | - April Khademi
- Electrical, Computer and Biomedical Engineering Department, Toronto Metropolitan University, 350 Victoria St., Toronto, ON M5B 2K3, Canada; Keenan Research Center for Biomedical Science, St. Michael's Hospital, Unity Health Network, 30 Bond St., Toronto, ON M5B 1W8, Canada; Institute for Biomedical Engineering, Science Tech (iBEST), A Partnership Between St. Michael's Hospital and Toronto Metropolitan University, 209 Victoria St., Toronto, ON M5B 1T8, Canada; Rotman Research Institute, Baycrest Hospital, 3560 Bathurst Street, Toronto, ON M6A 2E1, Canada.
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28
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Alban SL, Lynch KM, Ringman JM, Toga AW, Chui HC, Sepehrband F, Choupan J. The association between white matter hyperintensities and amyloid and tau deposition. Neuroimage Clin 2023; 38:103383. [PMID: 36965457 PMCID: PMC10060905 DOI: 10.1016/j.nicl.2023.103383] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 02/09/2023] [Accepted: 03/16/2023] [Indexed: 03/22/2023]
Abstract
White matter hyperintensities (WMHs) frequently occur in Alzheimer's Disease (AD) and have a contribution from ischemia, though their relationship with β-amyloid and cardiovascular risk factors (CVRFs) is not completely understood. We used AT classification to categorize individuals based on their β-amyloid and tau pathologies, then assessed the effects of β-amyloid and tau on WMH volume and number. We then determined regions in which β-amyloid and WMH accumulation were related. Last, we analyzed the effects of various CVRFs on WMHs. As secondary analyses, we observed effects of age and sex differences, atrophy, cognitive scores, and APOE genotype. PET, MRI, FLAIR, demographic, and cardiovascular health data was collected from the Alzheimer's Disease Neuroimaging Initiative (ADNI-3) (N = 287, 48 % male). Participants were categorized as A + and T + if their Florbetapir SUVR and Flortaucipir SUVR were above 0.79 and 1.25, respectively. WMHs were mapped on MRI using a deep convolutional neural network (Sepehrband et al., 2020). CVRF scores were based on history of hypertension, systolic and diastolic blood pressure, pulse rate, respiration rate, BMI, and a cumulative score with 6 being the maximum score. Regression models and Pearson correlations were used to test associations and correlations between variables, respectively, with age, sex, years of education, and scanner manufacturer as covariates of no interest. WMH volume percent was significantly associated with global β-amyloid (r = 0.28, p < 0.001), but not tau (r = 0.05, p = 0.25). WMH volume percent was higher in individuals with either A + or T + pathology compared to controls, particularly within in the A+/T + group (p = 0.007, Cohen's d = 0.4, t = -2.5). Individual CVRFs nor cumulative CVRF scores were associated with increased WMH volume. Finally, the regions where β-amyloid and WMH count were most positively associated were the middle temporal region in the right hemisphere (r = 0.18, p = 0.002) and the fusiform region in the left hemisphere (r = 0.017, p = 0.005). β-amyloid and WMH have a clear association, though the mechanism facilitating this association is still not fully understood. The associations found between β-amyloid and WMH burden emphasizes the relationship between β-amyloid and vascular lesion formation while factors like CVRFs, age, and sex affect AD development through various mechanisms. These findings highlight potential causes and mechanisms of AD as targets for future preventions and treatments. Going forward, a larger emphasis may be placed on β-amyloid's vascular effects and the implications of impaired brain clearance in AD.
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Affiliation(s)
- Sierra L Alban
- Laboratory of NeuroImaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Kirsten M Lynch
- Laboratory of NeuroImaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - John M Ringman
- Alzheimer's Disease Research Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Arthur W Toga
- Laboratory of NeuroImaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Alzheimer's Disease Research Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Helena C Chui
- Alzheimer's Disease Research Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Farshid Sepehrband
- Laboratory of NeuroImaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jeiran Choupan
- Laboratory of NeuroImaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; NeuroScope Inc., Scarsdale, NY, USA
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29
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Chuang KC, Ramakrishnapillai S, Madden K, St Amant J, McKlveen K, Gwizdala K, Dhullipudi R, Bazzano L, Carmichael O. Brain effective connectivity and functional connectivity as markers of lifespan vascular exposures in middle-aged adults: The Bogalusa Heart Study. Front Aging Neurosci 2023; 15:1110434. [PMID: 36998317 PMCID: PMC10043334 DOI: 10.3389/fnagi.2023.1110434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Accepted: 02/22/2023] [Indexed: 03/16/2023] Open
Abstract
IntroductionEffective connectivity (EC), the causal influence that functional activity in a source brain location exerts over functional activity in a target brain location, has the potential to provide different information about brain network dynamics than functional connectivity (FC), which quantifies activity synchrony between locations. However, head-to-head comparisons between EC and FC from either task-based or resting-state functional MRI (fMRI) data are rare, especially in terms of how they associate with salient aspects of brain health.MethodsIn this study, 100 cognitively-healthy participants in the Bogalusa Heart Study aged 54.2 ± 4.3years completed Stroop task-based fMRI, resting-state fMRI. EC and FC among 24 regions of interest (ROIs) previously identified as involved in Stroop task execution (EC-task and FC-task) and among 33 default mode network ROIs (EC-rest and FC-rest) were calculated from task-based and resting-state fMRI using deep stacking networks and Pearson correlation. The EC and FC measures were thresholded to generate directed and undirected graphs, from which standard graph metrics were calculated. Linear regression models related graph metrics to demographic, cardiometabolic risk factors, and cognitive function measures.ResultsWomen and whites (compared to men and African Americans) had better EC-task metrics, and better EC-task metrics associated with lower blood pressure, white matter hyperintensity volume, and higher vocabulary score (maximum value of p = 0.043). Women had better FC-task metrics, and better FC-task metrics associated with APOE-ε4 3–3 genotype and better hemoglobin-A1c, white matter hyperintensity volume and digit span backwards score (maximum value of p = 0.047). Better EC rest metrics associated with lower age, non-drinker status, and better BMI, white matter hyperintensity volume, logical memory II total score, and word reading score (maximum value of p = 0.044). Women and non-drinkers had better FC-rest metrics (value of p = 0.004).DiscussionIn a diverse, cognitively healthy, middle-aged community sample, EC and FC based graph metrics from task-based fMRI data, and EC based graph metrics from resting-state fMRI data, were associated with recognized indicators of brain health in differing ways. Future studies of brain health should consider taking both task-based and resting-state fMRI scans and measuring both EC and FC analyses to get a more complete picture of functional networks relevant to brain health.
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Affiliation(s)
- Kai-Cheng Chuang
- Department of Physics & Astronomy, Louisiana State University, Baton Rouge, LA, United States
- Pennington Biomedical Research Center, Baton Rouge, LA, United States
- *Correspondence: Kai-Cheng Chuang,
| | - Sreekrishna Ramakrishnapillai
- Pennington Biomedical Research Center, Baton Rouge, LA, United States
- Department of Electrical and Computer Engineering, Louisiana State University, Baton Rouge, LA, United States
| | - Kaitlyn Madden
- Pennington Biomedical Research Center, Baton Rouge, LA, United States
| | - Julia St Amant
- Pennington Biomedical Research Center, Baton Rouge, LA, United States
| | - Kevin McKlveen
- Pennington Biomedical Research Center, Baton Rouge, LA, United States
| | - Kathryn Gwizdala
- Pennington Biomedical Research Center, Baton Rouge, LA, United States
| | | | - Lydia Bazzano
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, United States
| | - Owen Carmichael
- Pennington Biomedical Research Center, Baton Rouge, LA, United States
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30
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Golas AC, Salwierz P, Rajji TK, Bowie CR, Butters MA, Fischer CE, Flint AJ, Herrmann N, Mah L, Mulsant BH, Pollock BG, Taghdiri F, Wang W, Tartaglia MC. Assessing the Role of Past Depression in Patients with Mild Cognitive Impairment, with and without Biomarkers for Alzheimer's Disease. J Alzheimers Dis 2023; 92:1219-1227. [PMID: 36911939 DOI: 10.3233/jad-221097] [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: 03/12/2023]
Abstract
Major depressive disorder (MDD) is a risk factor for Alzheimer's disease (AD). Cerebrovascular disease (CVD) is implicated in MDD and AD. Our study compared participants with AD positive and negative cerebrospinal fluid (CSF) biomarkers on neuropsychological performance, remitted MDD status, and CVD burden. Next, we compared AD-CSF biomarkers and white matter hyperintensities (WMH) burden among three groups: mild cognitive impairment (MCI) (n = 12), MCI with remitted MDD (MDD+MCI) (n = 12), and remitted MDD alone (MDD) (n = 7). Few participants (18%) with MCI+MDD exhibited AD(+) biomarkers. Nearly all participants had moderate-severe WMH. WMH may contribute to cognitive impairment or depression in MCI patients with AD(-) biomarkers.
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Affiliation(s)
- Angela C Golas
- Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Patrick Salwierz
- Centre for Addiction and Mental Health, Toronto, ON, Canada.,Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, ON, Canada.,Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Tarek K Rajji
- Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.,Toronto Dementia Research Alliance, University of Toronto, Toronto, ON, Canada
| | - Christopher R Bowie
- Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychology, Queen's University, Kingston, ON, Canada
| | - Meryl A Butters
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Corinne E Fischer
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.,Keenan Research Centre for Biomedical Science, St. Michael's Hospital, Toronto, ON, Canada
| | - Alastair J Flint
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.,University Health Network, Toronto, ON, Canada
| | - Nathan Herrmann
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.,Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Linda Mah
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.,Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada
| | - Benoit H Mulsant
- Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Bruce G Pollock
- Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Foad Taghdiri
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, ON, Canada
| | - Wei Wang
- Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - M Carmela Tartaglia
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, ON, Canada.,Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada
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31
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Graciani AL, Gutierre MU, Coppi AA, Arida RM, Gutierre RC. MYELIN, AGING, AND PHYSICAL EXERCISE. Neurobiol Aging 2023; 127:70-81. [PMID: 37116408 DOI: 10.1016/j.neurobiolaging.2023.03.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 03/22/2023] [Accepted: 03/24/2023] [Indexed: 04/03/2023]
Abstract
Myelin sheath is a structure in neurons fabricated by oligodendrocytes and Schwann cells responsible for increasing the efficiency of neural synapsis, impulse transmission, and providing metabolic support to the axon. They present morpho-functional changes during health aging as deformities of the sheath and its fragmentation, causing an increased load on microglial phagocytosis, with Alzheimer's disease aggravating. Physical exercise has been studied as a possible protective agent for the nervous system, offering benefits to neuroplasticity. In this regard, studies in animal models for Alzheimer's and depression reported the efficiency of physical exercise in protecting against myelin degeneration. A reduction of myelin damage during aging has also been observed in healthy humans. Physical activity promotes oligodendrocyte proliferation and myelin preservation during old age, although some controversies remain. In this review, we will address how effective physical exercise can be as a protective agent of the myelin sheath against the effects of aging in physiological and pathological conditions.
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32
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Pietrasik W, Cribben I, Olsen F, Malykhin N. Diffusion tensor imaging of superficial prefrontal white matter in healthy aging. Brain Res 2023; 1799:148152. [PMID: 36343726 DOI: 10.1016/j.brainres.2022.148152] [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: 06/06/2022] [Revised: 09/27/2022] [Accepted: 10/31/2022] [Indexed: 11/06/2022]
Abstract
The prefrontal cortex (PFC) is a heterogenous structure that is highly susceptible to the effects of aging. Few studies have investigated age effects on the superficial white matter (WM) contained within the PFC using in-vivo magnetic resonance imaging (MRI). This study used diffusion tensor imaging (DTI) tractography to examine the effects of age, sex, and intracranial volume (ICV) on superficial WM within specific PFC subregions, and to model the relationships with age using higher order polynomial regression modelling. PFC WM of 140 healthy individuals, aged 18-85, was segmented into medial and lateral orbitofrontal, medial prefrontal, and dorsolateral prefrontal subregions. Differences due to age in microstructural parameters such as fractional anisotropy (FA), axial and radial diffusivities, and macrostructural measures of tract volumes, fiber counts, average fiber lengths, and average number of fibers per voxel were examined. We found that most prefrontal subregions demonstrated age effects, with decreases in FA, tract volume, and fiber counts, and increases in all diffusivity measures. Age relationships were mostly non-linear, with higher order regressions chosen in most cases. Declines in PFC FA began at the onset of adulthood while the greatest changes in diffusivity and volume did not occur until middle age. The effects of age were most prominent in medial tracts while the lateral orbitofrontal tracts were less affected. Significant effects of sex and ICV were also observed in certain parameters. The patterns mostly followed myelination order, with late-myelinating prefrontal subregions experiencing earlier and more pronounced age effects, further supporting the frontal theory of aging.
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Affiliation(s)
- Wojciech Pietrasik
- Department of Biomedical Engineering, Faculty of Medicine & Dentistry, University of Alberta, Edmonton, Alberta, Canada; Neuroscience and Mental Health Institute, Faculty of Medicine & Dentistry, University of Alberta, Edmonton, Alberta, Canada
| | - Ivor Cribben
- Neuroscience and Mental Health Institute, Faculty of Medicine & Dentistry, University of Alberta, Edmonton, Alberta, Canada; Department of Accounting & Business Analytics, Alberta School of Business, University of Alberta, Edmonton, Alberta, Canada
| | - Fraser Olsen
- Department of Biomedical Engineering, Faculty of Medicine & Dentistry, University of Alberta, Edmonton, Alberta, Canada
| | - Nikolai Malykhin
- Neuroscience and Mental Health Institute, Faculty of Medicine & Dentistry, University of Alberta, Edmonton, Alberta, Canada; Department of Psychiatry, Faculty of Medicine & Dentistry, University of Alberta, Edmonton, Alberta, Canada.
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33
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Newton P, Tchounguen J, Pettigrew C, Lim C, Lin Z, Lu H, Moghekar A, Albert M, Soldan A. Regional White Matter Hyperintensities and Alzheimer's Disease Biomarkers Among Older Adults with Normal Cognition and Mild Cognitive Impairment. J Alzheimers Dis 2023; 92:323-339. [PMID: 36744337 PMCID: PMC10041440 DOI: 10.3233/jad-220846] [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] [Accepted: 12/29/2022] [Indexed: 02/04/2023]
Abstract
BACKGROUND Alzheimer's disease (AD) frequently co-occurs with other brain pathologies. Recent studies suggest there may be a mechanistic link between AD and small vessel cerebrovascular disease (CVD), as opposed to simply the overlap of two disorders. OBJECTIVE We investigated the cross-sectional relationship between white matter hyperintensity (WMH) volumes (markers of CVD) and cerebrospinal fluid (CSF) biomarkers of AD. METHODS WMH volumes were assessed globally and regionally (i.e., frontal, parietal, temporal, occipital, and limbic). CSF AD biomarkers (i.e., Aβ 40, Aβ 42, Aβ 42/Aβ 40 ratio, phosphorylated tau-181 [p-tau181], and total tau [t-tau]) were measured among 152 non-demented individuals (134 cognitively unimpaired and 18 with mild cognitive impairment (MCI)). RESULTS Linear regression models showed that among all subjects, higher temporal WHM volumes were associated with AD biomarkers (higher levels of p-tau181, t-tau, and Aβ 40), particularly among APOE ɛ 4 carriers (independent of Aβ 42 levels). Higher vascular risk scores were associated with greater parietal and frontal WMH volumes (independent of CSF AD biomarker levels). Among subjects with MCI only, parietal WMH volumes were associated with a lower level of Aβ 42/Aβ 40. In addition, there was an association between higher global WMH volumes and higher CSF t-tau levels among younger participants versus older ones (∼<65 versus 65+ years), independent of Aβ 42/Aβ 40 and p-tau181. CONCLUSION These findings suggest that although WMH are primarily related to systemic vascular risk and neurodegeneration (i.e., t-tau), AD-specific pathways may contribute to the formation of WMH in a regionally-specific manner, with neurofibrillary tangles (i.e., p-tau) playing a role in temporal WMHs and amyloid (i.e., Aβ 42/Aβ 40) in parietal WMHs.
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Affiliation(s)
- Princess Newton
- Department of Neuroscience, Johns Hopkins University, Baltimore, MD, USA
| | | | - Corinne Pettigrew
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Chantelle Lim
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Zixuan Lin
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Hanzhang Lu
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Abhay Moghekar
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Marilyn Albert
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Anja Soldan
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - the BIOCARD Research Team
- Department of Neuroscience, Johns Hopkins University, Baltimore, MD, USA
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
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34
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Phuah CL, Chen Y, Strain JF, Yechoor N, Laurido-Soto OJ, Ances BM, Lee JM. Association of Data-Driven White Matter Hyperintensity Spatial Signatures With Distinct Cerebral Small Vessel Disease Etiologies. Neurology 2022; 99:e2535-e2547. [PMID: 36123127 PMCID: PMC9754646 DOI: 10.1212/wnl.0000000000201186] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 07/15/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Topographical distribution of white matter hyperintensities (WMH) are hypothesized to vary by cerebrovascular risk factors. We used an unbiased pattern discovery approach to identify distinct WMH spatial patterns and investigate their association with different WMH etiologies. METHODS We performed a cross-sectional study on participants of the Alzheimer's Disease Neuroimaging Initiative (ADNI) to identify spatially distinct WMH distribution patterns using voxel-based spectral clustering analysis of aligned WMH probability maps. We included all participants from the ADNI Grand Opportunity/ADNI 2 study with available baseline 2D-FLAIR MRI scans, without history of stroke or presence of infarction on imaging. We evaluated the associations of these WMH spatial patterns with vascular risk factors, amyloid-β PET, and imaging biomarkers of cerebral amyloid angiopathy (CAA), characterizing different forms of cerebral small vessel disease (CSVD) using multivariable regression. We also used linear regression models to investigate whether WMH spatial distribution influenced cognitive impairment. RESULTS We analyzed MRI scans of 1,046 ADNI participants with mixed vascular and amyloid-related risk factors (mean age 72.9, 47.7% female, 31.4% hypertensive, 48.3% with abnormal amyloid PET). We observed unbiased partitioning of WMH into 5 unique spatial patterns: deep frontal, periventricular, juxtacortical, parietal, and posterior. Juxtacortical WMH were independently associated with probable CAA, deep frontal WMH were associated with risk factors for arteriolosclerosis (hypertension and diabetes), and parietal WMH were associated with brain amyloid accumulation, consistent with an Alzheimer disease (AD) phenotype. Juxtacortical, deep frontal, and parietal WMH spatial patterns were associated with cognitive impairment. Periventricular and posterior WMH spatial patterns were unrelated to any disease phenotype or cognitive decline. DISCUSSION Data-driven WMH spatial patterns reflect discrete underlying etiologies including arteriolosclerosis, CAA, AD, and normal aging. Global measures of WMH volume may miss important spatial distinctions. WMH spatial signatures may serve as etiology-specific imaging markers, helping to resolve WMH heterogeneity, identify the dominant underlying pathologic process, and improve prediction of clinical-relevant trajectories that influence cognitive decline.
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Affiliation(s)
- Chia-Ling Phuah
- From the Department of Neurology (C.-L.P., Y.C., J.F.S., N.Y., O.J.L.-S., B.M.A., J.-M.L.), Washington University School of Medicine & Barnes-Jewish Hospital, St. Louis, MO; NeuroGenomics and Informatics Center (C.-L.P.), Washington University School of Medicine, St. Louis, MO; Mallinckrodt Institute of Radiology (J.-M.L.), Washington University School of Medicine, St. Louis, MO; and Department of Biomedical Engineering (J.-M.L.), Washington University School of Medicine, St. Louis, MO
| | - Yasheng Chen
- From the Department of Neurology (C.-L.P., Y.C., J.F.S., N.Y., O.J.L.-S., B.M.A., J.-M.L.), Washington University School of Medicine & Barnes-Jewish Hospital, St. Louis, MO; NeuroGenomics and Informatics Center (C.-L.P.), Washington University School of Medicine, St. Louis, MO; Mallinckrodt Institute of Radiology (J.-M.L.), Washington University School of Medicine, St. Louis, MO; and Department of Biomedical Engineering (J.-M.L.), Washington University School of Medicine, St. Louis, MO
| | - Jeremy F Strain
- From the Department of Neurology (C.-L.P., Y.C., J.F.S., N.Y., O.J.L.-S., B.M.A., J.-M.L.), Washington University School of Medicine & Barnes-Jewish Hospital, St. Louis, MO; NeuroGenomics and Informatics Center (C.-L.P.), Washington University School of Medicine, St. Louis, MO; Mallinckrodt Institute of Radiology (J.-M.L.), Washington University School of Medicine, St. Louis, MO; and Department of Biomedical Engineering (J.-M.L.), Washington University School of Medicine, St. Louis, MO
| | - Nirupama Yechoor
- From the Department of Neurology (C.-L.P., Y.C., J.F.S., N.Y., O.J.L.-S., B.M.A., J.-M.L.), Washington University School of Medicine & Barnes-Jewish Hospital, St. Louis, MO; NeuroGenomics and Informatics Center (C.-L.P.), Washington University School of Medicine, St. Louis, MO; Mallinckrodt Institute of Radiology (J.-M.L.), Washington University School of Medicine, St. Louis, MO; and Department of Biomedical Engineering (J.-M.L.), Washington University School of Medicine, St. Louis, MO
| | - Osvaldo J Laurido-Soto
- From the Department of Neurology (C.-L.P., Y.C., J.F.S., N.Y., O.J.L.-S., B.M.A., J.-M.L.), Washington University School of Medicine & Barnes-Jewish Hospital, St. Louis, MO; NeuroGenomics and Informatics Center (C.-L.P.), Washington University School of Medicine, St. Louis, MO; Mallinckrodt Institute of Radiology (J.-M.L.), Washington University School of Medicine, St. Louis, MO; and Department of Biomedical Engineering (J.-M.L.), Washington University School of Medicine, St. Louis, MO
| | - Beau M Ances
- From the Department of Neurology (C.-L.P., Y.C., J.F.S., N.Y., O.J.L.-S., B.M.A., J.-M.L.), Washington University School of Medicine & Barnes-Jewish Hospital, St. Louis, MO; NeuroGenomics and Informatics Center (C.-L.P.), Washington University School of Medicine, St. Louis, MO; Mallinckrodt Institute of Radiology (J.-M.L.), Washington University School of Medicine, St. Louis, MO; and Department of Biomedical Engineering (J.-M.L.), Washington University School of Medicine, St. Louis, MO
| | - Jin-Moo Lee
- From the Department of Neurology (C.-L.P., Y.C., J.F.S., N.Y., O.J.L.-S., B.M.A., J.-M.L.), Washington University School of Medicine & Barnes-Jewish Hospital, St. Louis, MO; NeuroGenomics and Informatics Center (C.-L.P.), Washington University School of Medicine, St. Louis, MO; Mallinckrodt Institute of Radiology (J.-M.L.), Washington University School of Medicine, St. Louis, MO; and Department of Biomedical Engineering (J.-M.L.), Washington University School of Medicine, St. Louis, MO.
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He R, Qin Y, Zhou X, Liu Z, Xu Q, Guo J, Yan X, Tang B, Zeng S, Sun Q. The effect of regional white matter hyperintensities on essential tremor subtypes and severity. Front Aging Neurosci 2022; 14:933093. [PMID: 36325187 PMCID: PMC9621611 DOI: 10.3389/fnagi.2022.933093] [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: 04/30/2022] [Accepted: 09/20/2022] [Indexed: 11/16/2022] Open
Abstract
Objectives To investigate the effect of regional white matter hyperintensities (WMHs) on Essential tremor (ET) subtypes and to explore the association between WMHs load and the severity of motor and non-motor symptoms in patients with ET. Methods A cohort of 176 patients with ET (including 86 patients with pure ET and 90 patients with ET plus) and 91 normal controls (NC) was consecutively recruited. Demographic, clinical, and imaging characteristics were compared between individuals with pure ET, ET plus, and NC. The cross-sectional association among regional WMHs and the severity of tremor and non-motor symptoms were assessed within each group. Results Compared with the pure ET subgroup, the ET plus subgroup demonstrated higher TETRAS scores, NMSS scores, and lower MMSE scores (all P < 0.05). Periventricular and lobar WMHs' loads of pure ET subgroup intermediated between NC subjects and ET plus subgroup. WMHs in the frontal horn independently increased the odds of ET (OR = 1.784, P < 0.001). The age (P = 0.021), WMHs in the frontal lobe (P = 0.014), and WMHs in the occipital lobe (P = 0.020) showed a significant impact on TETRAS part II scores in the ET plus subgroup. However, only the disease duration was positively associated with TETRAS part II scores in patients with pure ET (P = 0.028). In terms of non-motor symptoms, NMSS scores of total patients with ET were associated with disease duration (P = 0.029), TETRAS part I scores (P = 0.017), and WMH scores in the frontal lobe (P = 0.033). MMSE scores were associated with age (P = 0.027), body mass index (P = 0.006), education level (P < 0.001), and WMHs in the body of the lateral ventricle (P = 0.005). Conclusion Our results indicated that the WMHs in the frontal horn could lead to an increased risk of developing ET. WMHs may be used to differentiate pure ET and ET plus. Furthermore, WMHs in the frontal and occipital lobes are strong predictors of worse tremor severity in the ET plus subgroup. Regional WMHs are associated with cognitive impairment in patients with ET.
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Affiliation(s)
- Runcheng He
- Department of Geriatric Neurology, Xiangya Hospital, Central South University, Changsha, China
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Yan Qin
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Xun Zhou
- Department of Geriatric Neurology, Xiangya Hospital, Central South University, Changsha, China
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Zhenhua Liu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, China
| | - Qian Xu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, China
| | - Jifeng Guo
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, China
| | - Xinxiang Yan
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, China
| | - Beisha Tang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, China
| | - Sheng Zeng
- Department of Geriatrics, The Second Xiangya Hospital, Central South University, Changsha, China
- Sheng Zeng
| | - Qiying Sun
- Department of Geriatric Neurology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, China
- *Correspondence: Qiying Sun
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36
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Moni F, Petersen ME, Zhang F, Lao PJ, Zimmerman ME, Gu Y, Gutierrez J, Rizvi B, Laing KK, Igwe KC, Sathishkumar M, Keator D, Andrews H, Krinsky-McHale S, Head E, Lee JH, Lai F, Yassa MA, Rosas HD, Silverman W, Lott IT, Schupf N, O’Bryant S, Brickman AM. Probing the proteome to explore potential correlates of increased Alzheimer's-related cerebrovascular disease in adults with Down syndrome. Alzheimers Dement 2022; 18:1744-1753. [PMID: 35212182 PMCID: PMC9399305 DOI: 10.1002/alz.12627] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Revised: 01/16/2022] [Accepted: 01/25/2022] [Indexed: 01/28/2023]
Abstract
Cerebrovascular disease is associated with symptoms and pathogenesis of Alzheimer's disease (AD) among adults with Down syndrome (DS). The cause of increased dementia-related cerebrovascular disease in DS is unknown. We explored whether protein markers of neuroinflammation are associated with markers of cerebrovascular disease among adults with DS. Participants from the Alzheimer's disease in Down syndrome (ADDS) study with magnetic resonance imaging (MRI) scans and blood biomarker data were included. Support vector machine (SVM) analyses examined the relationship of blood-based proteomic biomarkers with MRI-defined cerebrovascular disease among participants characterized as having cognitive decline (n = 36, mean age ± SD = 53 ± 6.2) and as being cognitively stable (n = 78, mean age = 49 ± 6.4). Inflammatory and AD markers were associated with cerebrovascular disease, particularly among symptomatic individuals. The pattern suggested relatively greater inflammatory involvement among cognitively stable individuals and greater AD involvement among those with cognitively decline. The findings help to generate hypotheses that both inflammatory and AD markers are implicated in cerebrovascular disease among those with DS and point to potential mechanistic pathways for further examination.
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Affiliation(s)
- Fahmida Moni
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
| | - Melissa E. Petersen
- Department of Family Medicine and Institute for Translational Research, University of North Texas Health Science Center, Fort Worth, Texas, USA
| | - Fan Zhang
- Department of Family Medicine and Institute for Translational Research, University of North Texas Health Science Center, Fort Worth, Texas, USA
| | - Patrick J. Lao
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
| | | | - Yian Gu
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
- Department of Family Medicine and Institute for Translational Research, University of North Texas Health Science Center, Fort Worth, Texas, USA
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, USA
| | - José Gutierrez
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
| | - Batool Rizvi
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
| | - Krystal K. Laing
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
| | - Kay C. Igwe
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
| | - Mithra Sathishkumar
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, California, USA
- Department of Neurobiology and Behavior, University of California, Irvine, California, USA
| | - David Keator
- Department of Neurobiology and Behavior, University of California, Irvine, California, USA
| | - Howard Andrews
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
| | - Sharon Krinsky-McHale
- Department of Psychology, New York State Institute for Basic Research in Developmental Disabilities, New York, New York, USA
| | - Elizabeth Head
- Department of Pathology and Laboratory Medicine, University of California Irvine, Irvine, California, USA
| | - Joseph H. Lee
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, USA
- Gertrude H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
| | - Florence Lai
- Department of Neurology, Massachusetts General Hospital, Harvard University, Boston, Massachusetts, USA
| | - Michael A. Yassa
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, California, USA
- Department of Neurobiology and Behavior, University of California, Irvine, California, USA
| | - H. Diana Rosas
- Department of Neurology, Massachusetts General Hospital, Harvard University, Boston, Massachusetts, USA
- Department of Radiology, Athinoula Martinos Center, Massachusetts General Hospital, Harvard University, Charlestown, Massachusetts, USA
| | - Wayne Silverman
- Department of Pediatrics, University of California, Irvine, California, USA
| | - Ira T. Lott
- Department of Pediatrics, University of California, Irvine, California, USA
| | - Nicole Schupf
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, USA
- Gertrude H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
| | - Sid O’Bryant
- Department of Family Medicine and Institute for Translational Research, University of North Texas Health Science Center, Fort Worth, Texas, USA
| | - Adam M. Brickman
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
- Gertrude H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
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Caçoilo A, Rusinek H, Weickenmeier J. 3D finite-element brain modeling of lateral ventricular wall loading to rationalize periventricular white matter hyperintensity locations. ENGINEERING WITH COMPUTERS 2022; 38:3939-3955. [PMID: 37485473 PMCID: PMC10361695 DOI: 10.1007/s00366-022-01700-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 06/19/2022] [Indexed: 07/25/2023]
Abstract
Aging-related periventricular white matter hyperintensities (pvWMHs) are a common observation in medical images of the aging brain. The underlying tissue damage is part of the complex pathophysiology associated with age-related microstructural changes and cognitive decline. PvWMH formation is linked to blood-brain barrier dysfunction from cerebral small vessel disease as well as the accumulation of cerebrospinal fluid in periventricular tissue due to progressive denudation of the ventricular wall. In need of a unifying theory for pvWMH etiology, image-based finite-element modeling is used to demonstrate that ventricular expansion from age-related cerebral atrophy and hemodynamic loading leads to maximum mechanical loading of the ventricular wall in the same locations that show pvWMHs. Ventricular inflation, induced via pressurization of the ventricular wall, creates significant ventricular wall stretch and stress on the ependymal cells lining the wall, that are linked to cerebrospinal fluid leaking from the lateral ventricles into periventricular white matter tissue. Eight anatomically accurate 3D brain models of cognitively healthy subjects with a wide range of ventricular shapes are created. For all models, our simulations show that mechanomarkers of mechanical wall loading are consistently highest in pvWMHs locations (p < 0.05). Maximum principal strain, the ependymal cell thinning ratio, and wall curvature are on average 14%, 8%, and 24% higher in pvWMH regions compared to the remaining ventricular wall, respectively. Computational modeling provides a powerful framework to systematically study pvWMH formation and growth with the goal to develop pharmacological interventions in the future.
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Affiliation(s)
- Andreia Caçoilo
- Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, USA
| | - Henry Rusinek
- Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Johannes Weickenmeier
- Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, USA
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38
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Juttukonda MR, Stephens KA, Yen YF, Howard CM, Polimeni JR, Rosen BR, Salat DH. Oxygen extraction efficiency and white matter lesion burden in older adults exhibiting radiological evidence of capillary shunting. J Cereb Blood Flow Metab 2022; 42:1933-1943. [PMID: 35673981 PMCID: PMC9536117 DOI: 10.1177/0271678x221105986] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Revised: 04/19/2022] [Accepted: 05/14/2022] [Indexed: 01/18/2023]
Abstract
White matter lesions (WML) have been linked to cognitive decline in aging as well as in Alzheimer's disease. While hypoperfusion is frequently considered a cause of WMLs due to the resulting reduction in oxygen availability to brain tissue, such reductions could also be caused by impaired oxygen exchange. Here, we tested the hypothesis that venous hyperintense signal (VHS) in arterial spin labeling (ASL) magnetic resonance imaging (MRI) may represent a marker of impaired oxygen extraction in aging older adults. In participants aged 60-80 years (n = 30), we measured cerebral blood flow and VHS with arterial spin labeling, maximum oxygen extraction fraction (OEFmax) with dynamic susceptibility contrast, and WML volume with T1-weighted MRI. We found a significant interaction between OEFmax and VHS presence on WML volume (p = 0.02), where lower OEFmax was associated with higher WML volume in participants with VHS, and higher OEFmax was associated with higher WML volume in participants without VHS. These results indicate that VHS in perfusion-weighted ASL data may represent a distinct cerebrovascular aging pattern involving oxygen extraction inefficiency as well as hypoperfusion.
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Affiliation(s)
- Meher R Juttukonda
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Kimberly A Stephens
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
| | - Yi-Fen Yen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Casey M Howard
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
| | - Jonathan R Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
- Division of Health Sciences and Technology, Harvard-Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Bruce R Rosen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
- Division of Health Sciences and Technology, Harvard-Massachusetts Institute of Technology, Cambridge, MA, USA
| | - David H Salat
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
- Neuroimaging Research for Veterans Center, VA Boston Healthcare System, Boston, MA, USA
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Association of Serum GFAP with Functional and Neurocognitive Outcome in Sporadic Small Vessel Disease. Biomedicines 2022; 10:biomedicines10081869. [PMID: 36009416 PMCID: PMC9405121 DOI: 10.3390/biomedicines10081869] [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: 05/30/2022] [Revised: 07/27/2022] [Accepted: 07/31/2022] [Indexed: 11/25/2022] Open
Abstract
Cerebrospinal fluid (CSF) and serum biomarkers are critical for clinical decision making in neurological diseases. In cerebral small vessel disease (CSVD), white matter hyperintensities (WMH) are an important neuroimaging biomarker, but more blood-based biomarkers capturing different aspects of CSVD pathology are needed. In 42 sporadic CSVD patients, we prospectively analysed WMH on magnetic resonance imaging (MRI) and the biomarkers neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), chitinase3-like protein 1 (CHI3L1), Tau and Aβ1-42 in CSF and NfL and GFAP in serum. GFAP and CHI3L1 expression was studied in post-mortem brain tissue in additional cases. CSVD cases with higher serum NfL and GFAP levels had a higher modified Rankin Scale (mRS) and NIHSS score and lower CSF Aβ1-42 levels, whereas the CSF NfL and CHI3L1 levels were positively correlated with the WMH load. Moreover, the serum GFAP levels significantly correlated with the neurocognitive functions. Pathological analyses in CSVD revealed a high density of GFAP-immunoreactive fibrillary astrocytic processes in the periventricular white matter and clusters of CHI3L1-immunoreactive astrocytes in the basal ganglia and thalamus. Thus, besides NfL, serum GFAP is a highly promising fluid biomarker of sporadic CSVD, because it does not only correlate with the clinical severity but also correlates with the cognitive function in patients.
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Lehrer EJ, Jones BM, Dickstein DR, Green S, Germano IM, Palmer JD, Laack N, Brown PD, Gondi V, Wefel JS, Sheehan JP, Trifiletti DM. The Cognitive Effects of Radiotherapy for Brain Metastases. Front Oncol 2022; 12:893264. [PMID: 35847842 PMCID: PMC9279690 DOI: 10.3389/fonc.2022.893264] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 05/27/2022] [Indexed: 12/24/2022] Open
Abstract
Brain metastases are the most common intracranial neoplasm and are seen in upwards of 10-30% of patients with cancer. For decades, whole brain radiation therapy (WBRT) was the mainstay of treatment in these patients. While WBRT is associated with excellent rates of intracranial tumor control, studies have demonstrated a lack of survival benefit, and WBRT is associated with higher rates of cognitive deterioration and detrimental effects on quality of life. In recent years, strategies to mitigate this risk, such as the incorporation of memantine and hippocampal avoidance have been employed with improved results. Furthermore, stereotactic radiosurgery (SRS) has emerged as an appealing treatment option over the last decade in the management of brain metastases and is associated with superior cognitive preservation and quality of life when compared to WBRT. This review article evaluates the pathogenesis and impact of cranial irradiation on cognition in patients with brain metastases, as well as current and future risk mitigation techniques.
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Affiliation(s)
- Eric J. Lehrer
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Brianna M. Jones
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Daniel R. Dickstein
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Sheryl Green
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Isabelle M. Germano
- Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Joshua D. Palmer
- Department of Radiation Oncology, Ohio State University Wexner Medical Center, Columbus, OH, United States
| | - Nadia Laack
- Department of Radiation Oncology, Mayo Clinic, Rochester, MN, United States
| | - Paul D. Brown
- Department of Radiation Oncology, Mayo Clinic, Rochester, MN, United States
| | - Vinai Gondi
- Department of Radiation Oncology, Northwestern Medicine Cancer Center Warrenville and Proton Center, Warrenville, IL, United States
| | - Jeffrey S. Wefel
- Department of Radiation Oncology, MD Anderson Cancer Center, Houston, TX, United States
| | - Jason P. Sheehan
- Department of Neurological Surgery, University of Virginia, Charlottesville, VA, United States
| | - Daniel M. Trifiletti
- Department of Radiation Oncology, Mayo Clinic, Jacksonville, FL, United States
- *Correspondence: Daniel M. Trifiletti,
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Incremental diagnostic value of 18F-Fluetemetamol PET in differential diagnoses of Alzheimer's Disease-related neurodegenerative diseases from an unselected memory clinic cohort. Sci Rep 2022; 12:10385. [PMID: 35725910 PMCID: PMC9209498 DOI: 10.1038/s41598-022-14532-z] [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: 04/08/2022] [Accepted: 06/08/2022] [Indexed: 11/08/2022] Open
Abstract
To evaluate the incremental diagnostic value of 18F-Flutemetamol PET following MRI measurements on an unselected prospective cohort collected from a memory clinic. A total of 84 participants was included in this study. A stepwise study design was performed including initial analysis (based on clinical assessments), interim analysis (revision of initial analysis post-MRI) and final analysis (revision of interim analysis post-18F-Flutemetamol PET). At each time of evaluation, every participant was categorized into SCD, MCI or dementia syndromal group and further into AD-related, non-AD related or non-specific type etiological subgroup. Post 18F-Flutemetamol PET, the significant changes were seen in the syndromal MCI group (57%, p < 0.001) involving the following etiological subgroups: AD-related MCI (57%, p < 0.01) and non-specific MCI (100%, p < 0.0001); and syndromal dementia group (61%, p < 0.0001) consisting of non-specific dementia subgroup (100%, p < 0.0001). In the binary regression model, amyloid status significantly influenced the diagnostic results of interim analysis (p < 0.01). 18F-Flutemetamol PET can have incremental value following MRI measurements, particularly reflected in the change of diagnosis of individuals with unclear etiology and AD-related-suspected patients due to the role in complementing AD-related pathological information.
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Brain imaging abnormalities in mixed Alzheimer's and subcortical vascular dementia. Neurol Sci 2022:1-14. [PMID: 35614521 DOI: 10.1017/cjn.2022.65] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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Kwon HS, Ko JS, Lee JH, Kwon KY, Han JH. A Positive Association between the Atherogenic Index of Plasma and White Matter Hyperintensity. Korean J Fam Med 2022; 43:193-198. [PMID: 35610965 PMCID: PMC9136501 DOI: 10.4082/kjfm.21.0129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 09/15/2021] [Accepted: 02/14/2022] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND White matter hyperintensity (WMH) is a risk factor for dementia and ischemic stroke. The atherogenic index of plasma (AIP) is a simple and cost-effective marker for the prediction of various vascular diseases. In this study, we evaluated the relationship between AIP and WMH in adults without cerebrovascular accidents. METHODS We analyzed the data of 281 adults, aged ≥26 years, who underwent brain magnetic resonance imaging (MRI) at the health promotion center of an education hospital between January 2014 and December 2018. Participants were divided into three categories according to tertiles of the AIP scores (T1: <0.20; T2: 0.20-0.48; and T3: >0.48). WMH was defined as a modified Fazekas scale score of 1-3 on brain MRI. A cubic spline curve was used to determine the linearity of the relationship between AIP and WMH. Multiple logistic regression analysis was used to evaluate the relationship between the AIP and WMH. RESULTS The prevalence of WMH was 45.7% in T1, 57.0% in T2, and 66.0% in T3 (T3 vs. T1, P for post-hoc analysis=0.005). The increased odds of WMH were associated with increased AIP. The odds ratio (OR) with a 95% confidence interval (CI) for WMH of T2 and T3 compared with T1 were 1.57 (0.88-2.80) and 2.30 (1.28-4.14), respectively. After adjusting for confounding variables, the OR with a 95% CI for WMH in the T2 and T3 groups vs. the referent T1 were 1.55 (0.76-3.13) and 2.27 (1.06-4.84), respectively. CONCLUSION AIP is independently and positively associated with WMH in a healthy population.
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Affiliation(s)
- Hyun-Suk Kwon
- Department of Family Medicine, Nowon Eulji Medical Center, Eulji University School of Medicine, Seoul, Korea
| | - Jun-Seong Ko
- Department of Family Medicine, Nowon Eulji Medical Center, Eulji University School of Medicine, Seoul, Korea
| | - Jun-Hyuk Lee
- Department of Family Medicine, Nowon Eulji Medical Center, Eulji University School of Medicine, Seoul, Korea
| | - Kil-Young Kwon
- Department of Family Medicine, Nowon Eulji Medical Center, Eulji University School of Medicine, Seoul, Korea
| | - Jee-Hye Han
- Department of Family Medicine, Nowon Eulji Medical Center, Eulji University School of Medicine, Seoul, Korea
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44
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Freeze WM, Zanon Zotin MC, Scherlek AA, Perosa V, Auger CA, Warren AD, van der Weerd L, Schoemaker D, Horn MJ, Gurol ME, Gokcal E, Bacskai BJ, Viswanathan A, Greenberg SM, Reijmer YD, van Veluw SJ. Corpus callosum lesions are associated with worse cognitive performance in cerebral amyloid angiopathy. Brain Commun 2022; 4:fcac105. [PMID: 35611313 PMCID: PMC9123849 DOI: 10.1093/braincomms/fcac105] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2021] [Revised: 02/20/2022] [Accepted: 04/21/2022] [Indexed: 11/19/2022] Open
Abstract
The impact of vascular lesions on cognition is location dependent. Here, we assessed the contribution of small vessel disease lesions in the corpus callosum to vascular cognitive impairment in cerebral amyloid angiopathy, as a model for cerebral small vessel disease. Sixty-five patients with probable cerebral amyloid angiopathy underwent 3T magnetic resonance imaging, including a diffusion tensor imaging scan, and neuropsychological testing. Microstructural white-matter integrity was quantified by fractional anisotropy and mean diffusivity. Z-scores on individual neuropsychological tests were averaged into five cognitive domains: information processing speed, executive functioning, memory, language and visuospatial ability. Corpus callosum lesions were defined as haemorrhagic (microbleeds or larger bleeds) or ischaemic (microinfarcts, larger infarcts and diffuse fluid-attenuated inversion recovery hyperintensities). Associations between corpus callosum lesion presence, microstructural white-matter integrity and cognitive performance were examined with multiple regression models. The prevalence of corpus callosum lesions was confirmed in an independent cohort of memory clinic patients with and without cerebral amyloid angiopathy (n = 82). In parallel, we assessed corpus callosum lesions on ex vivo magnetic resonance imaging in cerebral amyloid angiopathy patients (n = 19) and controls (n = 5) and determined associated tissue abnormalities with histopathology. A total number of 21 corpus callosum lesions was found in 19/65 (29%) cerebral amyloid angiopathy patients. Corpus callosum lesion presence was associated with reduced microstructural white-matter integrity within the corpus callosum and in the whole-brain white matter. Patients with corpus callosum lesions performed significantly worse on all cognitive domains except language, compared with those without corpus callosum lesions after correcting for age, sex, education and time between magnetic resonance imaging and neuropsychological assessment. This association was independent of the presence of intracerebral haemorrhage, whole-brain fractional anisotropy and mean diffusivity, and white-matter hyperintensity volume and brain volume for the domains of information processing speed and executive functioning. In the memory clinic patient cohort, corpus callosum lesions were present in 14/54 (26%) patients with probable and 2/8 (25%) patients with possible cerebral amyloid angiopathy, and in 3/20 (15%) patients without cerebral amyloid angiopathy. In the ex vivo cohort, corpus callosum lesions were present in 10/19 (53%) patients and 2/5 (40%) controls. On histopathology, ischaemic corpus callosum lesions were associated with tissue loss and demyelination, which extended beyond the lesion core. Together, these data suggest that corpus callosum lesions are a frequent finding in cerebral amyloid angiopathy, and that they independently contribute to cognitive impairment through strategic microstructural disruption of white-matter tracts.
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Affiliation(s)
- Whitney M. Freeze
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Neuropsychology and Psychiatry, Maastricht University, Maastricht, The Netherlands
| | - Maria Clara Zanon Zotin
- Department of Neurology, J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA, USA
- Department of Medical Imaging, Hematology and Clinical Oncology, Ribeirão Preto Medical School, USP, SP, Brazil
| | - Ashley A. Scherlek
- MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Valentina Perosa
- Department of Neurology, J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Corinne A. Auger
- MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Andrew D. Warren
- Department of Neurology, J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Louise van der Weerd
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | | | - Mitchell J. Horn
- Department of Neurology, J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - M. Edip Gurol
- Department of Neurology, J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Elif Gokcal
- Department of Neurology, J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Brian J. Bacskai
- MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Anand Viswanathan
- Department of Neurology, J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Steven M. Greenberg
- Department of Neurology, J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Yael D. Reijmer
- Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Susanne J. van Veluw
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Neurology, J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA, USA
- MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital, Charlestown, MA 02129, USA
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Angoff R, Himali JJ, Maillard P, Aparicio HJ, Vasan RS, Seshadri S, Beiser AS, Tsao CW. Relations of Metabolic Health and Obesity to Brain Aging in Young to Middle-Aged Adults. J Am Heart Assoc 2022; 11:e022107. [PMID: 35229662 PMCID: PMC9075324 DOI: 10.1161/jaha.121.022107] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Accepted: 01/18/2022] [Indexed: 11/23/2022]
Abstract
Background We aimed to evaluate the association between metabolic health and obesity and brain health measured via magnetic resonance imaging and neurocognitive testing in community dwelling adults. Methods and Results Framingham Heart Study Third Generation Cohort members (n=2170, 46±9 years of age, 54% women) without prevalent diabetes, stroke, dementia, or other neurologic conditions were grouped by metabolic unhealthiness (≥2 criteria for metabolic syndrome) and obesity (body mass index ≥30 kg/m2): metabolically healthy (MH) nonobese, MH obese, metabolically unhealthy (MU) nonobese, and MU obese. We evaluated the relationships of these groups with brain structure (magnetic resonance imaging) and function (neurocognitive tests). In multivariable-adjusted analyses, metabolically unhealthy individuals (MU nonobese and MU obese) had lower total cerebral brain volume compared with the MH nonobese referent group (both P<0.05). Additionally, the MU obese group had greater white matter hyperintensity volume (P=0.004), whereas no association was noted between white matter hyperintensity volume and either groups of metabolic health or obesity alone. Obese individuals had less favorable cognitive scores: MH obese had lower scores on global cognition, Logical Memory-Delayed Recall and Similarities tests, and MU obese had lower scores on Similarities and Visual Reproductions-Delayed tests (all P≤0.04). MU and obese groups had higher free water content and lower fractional anisotropy in several brain regions, consistent with loss of white matter integrity. Conclusions In this cross-sectional cohort study of younger to middle-aged adults, poor metabolic health and obesity were associated with structural and functional evidence of brain aging. Improvement in metabolic health and obesity may present opportunities to improve long-term brain health.
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Affiliation(s)
- Rebecca Angoff
- Cardiovascular DivisionBeth Israel Deaconess Medical Center and Harvard Medical SchoolBostonMA
| | - Jayandra J. Himali
- Department of NeurologySchool of MedicineBoston UniversityBostonMA
- The Department of BiostatisticsBoston UniversityBostonMA
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative DiseasesUniversity of Texas Health Sciences CenterSan AntonioTX
- The Framingham Heart StudyFraminghamMA
| | - Pauline Maillard
- Department of Neurology and Center for NeuroscienceUniversity of California at DavisDavisCA
| | - Hugo J. Aparicio
- Department of NeurologySchool of MedicineBoston UniversityBostonMA
- The Framingham Heart StudyFraminghamMA
| | - Ramachandran S. Vasan
- Department of MedicineSchool of MedicineBoston UniversityBostonMA
- Department of EpidemiologyBoston UniversityBostonMA
- The Framingham Heart StudyFraminghamMA
| | - Sudha Seshadri
- Department of NeurologySchool of MedicineBoston UniversityBostonMA
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative DiseasesUniversity of Texas Health Sciences CenterSan AntonioTX
- Department of Population Health SciencesUniversity of Texas Health Science CenterSan AntonioTX
- The Framingham Heart StudyFraminghamMA
| | - Alexa S. Beiser
- Department of NeurologySchool of MedicineBoston UniversityBostonMA
- The Department of BiostatisticsBoston UniversityBostonMA
- The Framingham Heart StudyFraminghamMA
| | - Connie W. Tsao
- Cardiovascular DivisionBeth Israel Deaconess Medical Center and Harvard Medical SchoolBostonMA
- The Framingham Heart StudyFraminghamMA
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46
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Dadar M, Manera AL, Ducharme S, Collins DL. White matter hyperintensities are associated with grey matter atrophy and cognitive decline in Alzheimer's disease and frontotemporal dementia. Neurobiol Aging 2021; 111:54-63. [PMID: 34968832 DOI: 10.1016/j.neurobiolaging.2021.11.007] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Revised: 10/21/2021] [Accepted: 11/26/2021] [Indexed: 01/18/2023]
Abstract
White matter hyperintensities (WMHs) are commonly assumed to represent non-specific cerebrovascular disease comorbid to neurodegenerative processes, rather than playing a synergistic role. We compared the impact of WMHs on grey matter (GM) atrophy and cognition in normal aging (n = 571), mild cognitive impairment (MCI, n = 551), Alzheimer's dementia (AD, n = 212), fronto-temporal dementia (FTD, n = 125), and Parkinson's disease (PD, n = 271). Longitudinal data were obtained from ADNI, FTLDNI, and PPMI datasets. Mixed-effects models were used to compare WMHs and GM atrophy between patients and controls and assess the impact of WMHs on GM atrophy and cognition. MCI, AD, and FTD patients had significantly higher WMH loads than controls. WMHs were related to GM atrophy in insular and parieto-occipital regions in MCI/AD, and frontal regions and basal ganglia in FTD. In addition, WMHs contributed to more severe cognitive deficits in AD and FTD compared to controls, whereas their impact in MCI and PD was not significantly different from controls. These results suggest potential synergistic effects between WMHs and proteinopathies in the neurodegenerative process in MCI, AD and FTD.
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Affiliation(s)
- Mahsa Dadar
- NeuroImaging and Surgical Tools Laboratory, Montreal Neurological Institute, McGill University, Montreal, QC, Canada; McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada.
| | - Ana Laura Manera
- NeuroImaging and Surgical Tools Laboratory, Montreal Neurological Institute, McGill University, Montreal, QC, Canada; McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Simon Ducharme
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada; Department of Psychiatry, Douglas Mental Health University Institute and Douglas Research Centre, McGill University, Montreal, QC, Canada
| | - D Louis Collins
- NeuroImaging and Surgical Tools Laboratory, Montreal Neurological Institute, McGill University, Montreal, QC, Canada; McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
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47
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McAleese KE, Miah M, Graham S, Hadfield GM, Walker L, Johnson M, Colloby SJ, Thomas AJ, DeCarli C, Koss D, Attems J. Frontal white matter lesions in Alzheimer's disease are associated with both small vessel disease and AD-associated cortical pathology. Acta Neuropathol 2021; 142:937-950. [PMID: 34608542 PMCID: PMC8568857 DOI: 10.1007/s00401-021-02376-2] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2021] [Revised: 09/26/2021] [Accepted: 09/27/2021] [Indexed: 12/22/2022]
Abstract
Cerebral white matter lesions (WML) encompass axonal loss and demyelination and are assumed to be associated with small vessel disease (SVD)-related ischaemia. However, our previous study in the parietal lobe white matter revealed that WML in Alzheimer's disease (AD) are linked with degenerative axonal loss secondary to the deposition of cortical AD pathology. Furthermore, neuroimaging data suggest that pathomechanisms for the development of WML differ between anterior and posterior lobes with AD-associated degenerative mechanism driving posterior white matter disruption, and both AD-associated degenerative and vascular mechanisms contributed to anterior matter disruption. In this pilot study, we used human post-mortem brain tissue to investigate the composition and aetiology of frontal WML from AD and non-demented controls to determine if frontal WML are SVD-associated and to reveal any regional differences in the pathogenesis of WML. Frontal WML tissue sections from 40 human post-mortem brains (AD, n = 19; controls, n = 21) were quantitatively assessed for demyelination, axonal loss, cortical hyperphosphorylated tau (HPτ) and amyloid-beta (Aβ) burden, and arteriolosclerosis as a measure of SVD. Biochemical assessment included Wallerian degeneration-associated protease calpain and the myelin-associated glycoprotein to proteolipid protein ratio as a measure of ante-mortem ischaemia. Arteriolosclerosis severity was found to be associated with and a significant predictor of frontal WML severity in both AD and non-demented controls. Interesting, frontal axonal loss was also associated with HPτ and calpain levels were associated with increasing Aβ burden in the AD group, suggestive of an additional degenerative influence. To conclude, this pilot data suggest that frontal WML in AD may result from both increased arteriolosclerosis and AD-associated degenerative changes. These preliminary findings in combination with previously published data tentatively indicate regional differences in the aetiology of WML in AD, which should be considered in the clinical diagnosis of dementia subtypes: posterior WML maybe associated with degenerative mechanisms secondary to AD pathology, while anterior WML could be associated with both SVD-associated and degenerative mechanisms.
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Affiliation(s)
- Kirsty E McAleese
- Translation and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK.
| | - Mohi Miah
- Translation and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Sophie Graham
- Translation and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Georgina M Hadfield
- Translation and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Lauren Walker
- Translation and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Mary Johnson
- Translation and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Sean J Colloby
- Translation and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Alan J Thomas
- Translation and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Charles DeCarli
- Department of Neurology, University of California, Davis, CA, USA
| | - David Koss
- Translation and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Johannes Attems
- Translation and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
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48
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Chen J, Mikheev AV, Yu H, Gruen MD, Rusinek H, Ge Y. Bilateral Distance Partition of Periventricular and Deep White Matter Hyperintensities: Performance of the Method in the Aging Brain. Acad Radiol 2021; 28:1699-1708. [PMID: 33127308 DOI: 10.1016/j.acra.2020.07.039] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Revised: 07/26/2020] [Accepted: 07/27/2020] [Indexed: 02/07/2023]
Abstract
RATIONALE AND OBJECTIVES Periventricular and deep white matter hyperintensities (WMHs) in the elderly have been reported with distinctive roles in the progression of cognitive decline and dementia. However, the definition of these two subregions of WMHs is arbitrary and varies across studies. Here, we evaluate three partition methods for WMH subregions, including two widely used conventional methods (CV & D10) and one novel method based on bilateral distance (BD). MATERIALS AND METHODS The three partition methods were assessed on the MRI scans of 60 subjects, with 20 normal control, 20 mild cognitive impairment, and 20 Alzheimer's disease (AD). Resulting WMH subregional volumes were (1) compared among different partition methods and subject groups, and (2) tested for clinical associations with cognition and dementia. Inter-rater, intrarater, and interscan reproducibility of WMHs volumes were tested on 12 randomly selected subjects from the 60. RESULTS For all three partition methods, increased periventricular WMHs were found for AD subjects over normal control. For BD and D10, but not CV method, increased Periventricular WMHs were found for AD subjects over mild cognitive impairment. Significant correlations were found between PVWMHs and Mini-Mental State Examination, Montreal Cognitive Assessment, and Clinical Dementia Rating scores. Furthermore, PVWMHs under BD partition showed higher correlations than D10 and CV. High intrarater and interscan reproducibility (ICCA = 0.998 and 0.992 correspondingly) and substantial inter-rater reproducibility (ICCA = 0.886) were detected. CONCLUSION Different WMH partition methods showed comparable diagnostic abilities. The proposed BD method showed advantages in quantifying PVWMH over conventional CV and D10 methods, in terms of higher consistency, larger contrast, and higher diagnosis accuracy. Furthermore, the PVWMH under BD partition showed stronger clinical correlations than conventional methods.
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Affiliation(s)
- Jingyun Chen
- Department of Neurology, New York University Grossman School of Medicine, 145 E 32 St Rm 514, New York, NY 10016; Department of Radiology, New York University Grossman School of Medicine, New York, NY.
| | - Artem V Mikheev
- Department of Radiology, New York University Grossman School of Medicine, New York, NY
| | - Han Yu
- Department of Neurology, New York University Grossman School of Medicine, 145 E 32 St Rm 514, New York, NY 10016; Teachers College, Columbia University, New York, NY
| | - Matthew D Gruen
- Department of Physics, University of California Los Angeles, Los Angeles, CA
| | - Henry Rusinek
- Department of Radiology, New York University Grossman School of Medicine, New York, NY
| | - Yulin Ge
- Department of Radiology, New York University Grossman School of Medicine, New York, NY
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49
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Li X, Zhao Y, Jiang J, Cheng J, Zhu W, Wu Z, Jing J, Zhang Z, Wen W, Sachdev PS, Wang Y, Liu T, Li Z. White matter hyperintensities segmentation using an ensemble of neural networks. Hum Brain Mapp 2021; 43:929-939. [PMID: 34704337 PMCID: PMC8764480 DOI: 10.1002/hbm.25695] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Accepted: 10/08/2021] [Indexed: 11/30/2022] Open
Abstract
White matter hyperintensities (WMHs) represent the most common neuroimaging marker of cerebral small vessel disease (CSVD). The volume and location of WMHs are important clinical measures. We present a pipeline using deep fully convolutional network and ensemble models, combining U‐Net, SE‐Net, and multi‐scale features, to automatically segment WMHs and estimate their volumes and locations. We evaluated our method in two datasets: a clinical routine dataset comprising 60 patients (selected from Chinese National Stroke Registry, CNSR) and a research dataset composed of 60 patients (selected from MICCAI WMH Challenge, MWC). The performance of our pipeline was compared with four freely available methods: LGA, LPA, UBO detector, and U‐Net, in terms of a variety of metrics. Additionally, to access the model generalization ability, another research dataset comprising 40 patients (from Older Australian Twins Study and Sydney Memory and Aging Study, OSM), was selected and tested. The pipeline achieved the best performance in both research dataset and the clinical routine dataset with DSC being significantly higher than other methods (p < .001), reaching .833 and .783, respectively. The results of model generalization ability showed that the model trained on the research dataset (DSC = 0.736) performed higher than that trained on the clinical dataset (DSC = 0.622). Our method outperformed widely used pipelines in WMHs segmentation. This system could generate both image and text outputs for whole brain, lobar and anatomical automatic labeling WMHs. Additionally, software and models of our method are made publicly available at https://www.nitrc.org/projects/what_v1.
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Affiliation(s)
- Xinxin Li
- Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, China.,BioMind Technology AI Center, China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Beijng, China
| | - Yu Zhao
- Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, China
| | - Jiyang Jiang
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, UNSW, Sydney, New South Wales, Australia
| | - Jian Cheng
- Beijing Advanced Innovation Center for Big Data-Based Precision Medicin, School of Computer Science and Engineering, Beihang University, Beijing, China
| | - Wanlin Zhu
- Neuroimaging Center of Excellence, China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijng, China
| | - Zhenzhou Wu
- BioMind Technology AI Center, China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Beijng, China
| | - Jing Jing
- Neuroimaging Center of Excellence, China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijng, China
| | - Zhe Zhang
- Neuroimaging Center of Excellence, China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijng, China
| | - Wei Wen
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, UNSW, Sydney, New South Wales, Australia.,Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, New South Wales, Australia
| | - Perminder S Sachdev
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, UNSW, Sydney, New South Wales, Australia.,Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, New South Wales, Australia
| | - Yongjun Wang
- Neuroimaging Center of Excellence, China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijng, China
| | - Tao Liu
- Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, China.,Beijing Advanced Innovation Center for Big Data-Based Precision Medicin, School of Computer Science and Engineering, Beihang University, Beijing, China
| | - Zixiao Li
- Neuroimaging Center of Excellence, China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijng, China.,Vascular Neurology, Department of Neurology, Beijing TianTan Hospital, Capital Medical University, Beijing, China.,Chinese Institute for Brain Research, Beijing, China.,Research Unit of Artificial Intelligence in Cerebrovascular Disease, Chinese Academy of Medical Sciences, Beijing, China
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50
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Fiford CM, Sudre CH, Young AL, Macdougall A, Nicholas J, Manning EN, Malone IB, Walsh P, Goodkin O, Pemberton HG, Barkhof F, Alexander DC, Cardoso MJ, Biessels GJ, Barnes J. Presumed small vessel disease, imaging and cognition markers in the Alzheimer's Disease Neuroimaging Initiative. Brain Commun 2021; 3:fcab226. [PMID: 34661106 PMCID: PMC8514859 DOI: 10.1093/braincomms/fcab226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Revised: 06/22/2021] [Accepted: 06/25/2021] [Indexed: 01/18/2023] Open
Abstract
MRI-derived features of presumed cerebral small vessel disease are frequently found in Alzheimer's disease. Influences of such markers on disease-progression measures are poorly understood. We measured markers of presumed small vessel disease (white matter hyperintensity volumes; cerebral microbleeds) on baseline images of newly enrolled individuals in the Alzheimer's Disease Neuroimaging Initiative cohort (GO and 2) and used linear mixed models to relate these to subsequent atrophy and neuropsychological score change. We also assessed heterogeneity in white matter hyperintensity positioning within biomarker abnormality sequences, driven by the data, using the Subtype and Stage Inference algorithm. This study recruited both sexes and included: controls: [n = 159, mean(SD) age = 74(6) years]; early and late mild cognitive impairment [ns = 265 and 139, respectively, mean(SD) ages =71(7) and 72(8) years, respectively]; Alzheimer's disease [n = 103, mean(SD) age = 75(8)] and significant memory concern [n = 72, mean(SD) age = 72(6) years]. Baseline demographic and vascular risk-factor data, and longitudinal cognitive scores (Mini-Mental State Examination; logical memory; and Trails A and B) were collected. Whole-brain and hippocampal volume change metrics were calculated. White matter hyperintensity volumes were associated with greater whole-brain and hippocampal volume changes independently of cerebral microbleeds (a doubling of baseline white matter hyperintensity was associated with an increase in atrophy rate of 0.3 ml/year for brain and 0.013 ml/year for hippocampus). Cerebral microbleeds were found in 15% of individuals and the presence of a microbleed, as opposed to none, was associated with increases in atrophy rate of 1.4 ml/year for whole brain and 0.021 ml/year for hippocampus. White matter hyperintensities were predictive of greater decline in all neuropsychological scores, while cerebral microbleeds were predictive of decline in logical memory (immediate recall) and Mini-Mental State Examination scores. We identified distinct groups with specific sequences of biomarker abnormality using continuous baseline measures and brain volume change. Four clusters were found; Group 1 showed early Alzheimer's pathology; Group 2 showed early neurodegeneration; Group 3 had early mixed Alzheimer's and cerebrovascular pathology; Group 4 had early neuropsychological score abnormalities. White matter hyperintensity volumes becoming abnormal was a late event for Groups 1 and 4 and an early event for 2 and 3. In summary, white matter hyperintensities and microbleeds were independently associated with progressive neurodegeneration (brain atrophy rates) and cognitive decline (change in neuropsychological scores). Mechanisms involving white matter hyperintensities and progression and microbleeds and progression may be partially separate. Distinct sequences of biomarker progression were found. White matter hyperintensity development was an early event in two sequences.
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Affiliation(s)
- Cassidy M Fiford
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, Queen Square, London WC1N 3BG, UK
| | - Carole H Sudre
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, Queen Square, London WC1N 3BG, UK
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- Centre for Medical Image Computing, University College London, London WC1V 6LJ, UK
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Health Sciences, University College London, London WC1E 3HB, UK
| | - Alexandra L Young
- Centre for Medical Image Computing, University College London, London WC1V 6LJ, UK
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 3AF, UK
| | - Amy Macdougall
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, Queen Square, London WC1N 3BG, UK
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK
| | - Jennifer Nicholas
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, Queen Square, London WC1N 3BG, UK
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK
| | - Emily N Manning
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, Queen Square, London WC1N 3BG, UK
| | - Ian B Malone
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, Queen Square, London WC1N 3BG, UK
| | - Phoebe Walsh
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, Queen Square, London WC1N 3BG, UK
| | - Olivia Goodkin
- Centre for Medical Image Computing, University College London, London WC1V 6LJ, UK
| | - Hugh G Pemberton
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, Queen Square, London WC1N 3BG, UK
- Centre for Medical Image Computing, University College London, London WC1V 6LJ, UK
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam Neuroscience, 1081 HV Amsterdam, The Netherlands
- UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- UCL Institute of Healthcare Engineering, London WC1E 6DH, UK
| | - Daniel C Alexander
- Centre for Medical Image Computing, University College London, London WC1V 6LJ, UK
| | - M Jorge Cardoso
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Geert Jan Biessels
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, 3584 CG Utrecht, The Netherlands
| | - Josephine Barnes
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, Queen Square, London WC1N 3BG, UK
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