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Pradeep A, Raghavan S, Przybelski SA, Preboske GM, 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? Alzheimers Res Ther 2024; 16:157. [PMID: 38987827 PMCID: PMC11234605 DOI: 10.1186/s13195-024-01525-5] [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: 03/05/2024] [Accepted: 07/02/2024] [Indexed: 07/12/2024]
Abstract
BACKGROUND White matter hyperintensities (WMH) are considered hallmark features of cerebral small vessel disease and have recently been linked to Alzheimer's disease (AD) 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, AD 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 a population-based sample 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, automated 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 = 0.82 and 0.74). The automated WMH volume had high discriminating power for identifying participants with Fazekas ≥ 2 (area under curve = 0.97) and showed poor correlation with amyloid and tau PET markers similar to the visual grading. CONCLUSION Our study investigated 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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Affiliation(s)
| | - Sheelakumari Raghavan
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Scott A Przybelski
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, 55905, USA
| | - Gregory M Preboske
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Christopher G Schwarz
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Val J Lowe
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - David S Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN, 55905, USA
| | | | - Clifford R Jack
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | | | - Petrice M Cogswell
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Prashanthi Vemuri
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
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Li K, Wang S, Luo X, Zeng Q, Liu X, Hong L, Li J, Hong H, Xu X, Zhang Y, Jiaerken Y, Zhang R, Xie L, Xu S, Zhang X, Chen Y, Liu Z, Zhang M, Huang P. Associations of Alzheimer's Disease Pathology and Small Vessel Disease With Cerebral White Matter Degeneration: A Tract-Based MR Diffusion Imaging Study. J Magn Reson Imaging 2024; 60:268-278. [PMID: 37737474 DOI: 10.1002/jmri.29022] [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: 06/04/2023] [Revised: 09/02/2023] [Accepted: 09/05/2023] [Indexed: 09/23/2023] Open
Abstract
BACKGROUND White matter (WM) degeneration is a key feature of Alzheimer's disease (AD). However, the underlying mechanism remains unclear. PURPOSE To investigate how amyloid-β (Aβ), tau, and small vascular disease (SVD) jointly affect WM degeneration in subjects along AD continuum. STUDY TYPE Retrospective. SUBJECTS 152 non-demented participants (age: 55.8-91.6, male/female: 66/86) from the ADNI database were included, classified into three groups using the A (Aβ)/T (tau)/N pathological scheme (Group 1: A-T-; Group 2: A+T-; Group 3: A+T+) based on positron emission tomography data. FIELD STRENGTH/SEQUENCE 3T; T1-weighted images, T2-weighted fluid-attenuated inversion recovery images, T2*-weighted images, diffusion-weighted spin-echo echo-planar imaging sequence (54 diffusion directions). ASSESSMENT Free-water diffusion model (generated parameters: free water, FW; tissue fractional anisotropy, FAt; tissue mean diffusivity, MDt); SVD total score; Neuropsychological tests. STATISTICAL TESTS Linear regression analysis was performed to investigate the independent contribution of AD (Aβ and tau) and SVD pathologies to diffusion parameters in each fiber tract, first in the entire population and then in each subgroup. We also investigated associations between diffusion parameters and cognitive functions. The level of statistical significance was set at p < 0.05 (false discovery rate corrected). RESULTS In the entire population, we found that: 1) Increased FW was significantly associated with SVD and tau, while FAt and MDt were significantly associated with Aβ and tau; 2) The spatial pattern of fiber tracts related to a certain pathological marker is consistent with the known distribution of that pathology; 3) Subgroup analysis showed that Group 2 and 3 had more alterations of FAt and MDt associated with Aβ and tau; 4) Diffusion imaging indices showed significant associations with cognitive score in all domains except memory. DATA CONCLUSION WM microstructural injury was associated with both AD and SVD pathologies, showing compartment-specific, tract-specific, and stage-specific WM patterns. EVIDENCE LEVEL 1 TECHNICAL EFFICACY: Stage 3.
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Affiliation(s)
- Kaicheng Li
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Shuyue Wang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiao Luo
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Qingze Zeng
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaocao Liu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Luwei Hong
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Jixuan Li
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Hui Hong
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaopei Xu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Yao Zhang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Yeerfan Jiaerken
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Ruiting Zhang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Linyun Xie
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Shan Xu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xinyi Zhang
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Yanxing Chen
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Zhirong Liu
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
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Wang J, Wang Y, Cai X, Xia W, Zhu J. A Review: Visuospatial Dysfunction in Patients with the Cerebral Small Vessel Disease. Neuroscience 2024; 552:47-53. [PMID: 38880241 DOI: 10.1016/j.neuroscience.2024.06.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2024] [Revised: 06/06/2024] [Accepted: 06/10/2024] [Indexed: 06/18/2024]
Abstract
Cerebral small vessel disease (CSVD) impairs visuospatial function, and this is one of the most obvious areas of cognitive impairment in CSVD. So, recognizing, monitoring, and treating visuospatial dysfunction are all important to the prognosis of CSVD. This review discussed the anatomical and pathological mechanisms, clinical recognition (scales, imaging, and biomarkers), and treatment of cognitive impairment especially visuospatial dysfunction in CSVD.
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Affiliation(s)
- Jiaxing Wang
- Department of Neurology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Youmeng Wang
- Department of Neurology, Fuyang People's Hospital, Fuyang, China
| | - Xiuying Cai
- Department of Neurology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Wei Xia
- Department of Ophthalmology, The First Affiliated Hospital of Soochow University, Suzhou, China.
| | - Juehua Zhu
- Department of Neurology, The First Affiliated Hospital of Soochow University, Suzhou, China.
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Coenen M, de Kort FA, Weaver NA, Kuijf HJ, Aben HP, Bae HJ, Bordet R, Chen CP, Dewenter A, Doeven T, Dondaine T, Duering M, Fang R, van der Giessen RS, Kim J, Kim BJ, de Kort PL, Koudstaal PJ, Lee M, Lim JS, Lopes R, van Oostenbrugge RJ, Staals J, Yu KH, Biessels GJ, Biesbroek JM. Strategic white matter hyperintensity locations associated with post-stroke cognitive impairment: A multicenter study in 1568 stroke patients. Int J Stroke 2024:17474930241252530. [PMID: 38651756 DOI: 10.1177/17474930241252530] [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: 04/25/2024]
Abstract
BACKGROUND Post-stroke cognitive impairment (PSCI) occurs in up to 50% of stroke survivors. Presence of pre-existing vascular brain injury, in particular the extent of white matter hyperintensities (WMH), is associated with worse cognitive outcome after stroke, but the role of WMH location in this association is unclear. AIMS We determined if WMH in strategic white matter tracts explain cognitive performance after stroke. METHODS Individual patient data from nine ischemic stroke cohorts with magnetic resonance imaging (MRI) were harmonized through the Meta VCI Map consortium. The association between WMH volumes in strategic tracts and domain-specific cognitive functioning (attention and executive functioning, information processing speed, language and verbal memory) was assessed using linear mixed models and lasso regression. We used a hypothesis-driven design, primarily addressing four white matter tracts known to be strategic in memory clinic patients: the left and right anterior thalamic radiation, forceps major, and left inferior fronto-occipital fasciculus. RESULTS The total study sample consisted of 1568 patients (39.9% female, mean age = 67.3 years). Total WMH volume was strongly related to cognitive performance on all four cognitive domains. WMH volume in the left anterior thalamic radiation was significantly associated with cognitive performance on attention and executive functioning and information processing speed and WMH volume in the forceps major with information processing speed. The multivariable lasso regression showed that these associations were independent of age, sex, education, and total infarct volume and had larger coefficients than total WMH volume. CONCLUSION These results show tract-specific relations between WMH volume and cognitive performance after ischemic stroke, independent of total WMH volume. This implies that the concept of strategic lesions in PSCI extends beyond acute infarcts and also involves pre-existing WMH. DATA ACCESS STATEMENT The Meta VCI Map consortium is dedicated to data sharing, following our guidelines.
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Affiliation(s)
- Mirthe Coenen
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Floor As de Kort
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Nick A Weaver
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Hugo J Kuijf
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Hugo P Aben
- Department of Neurology, Elisabeth Tweesteden Hospital, Tilburg, The Netherlands
| | - Hee-Joon Bae
- Department of Neurology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Republic of Korea
| | - Régis Bordet
- Lille Neuroscience & Cognition (LilNCog)-U1172, Université Lille, Inserm, CHU Lille, Lille, France
| | - Christopher Plh Chen
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Memory, Ageing and Cognition Center, National University Health System, Singapore
| | - Anna Dewenter
- Institute for Stroke and Dementia Research (ISD), LMU University Hospital, LMU Munich, Munich, Germany
| | - Thomas Doeven
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Thibaut Dondaine
- Lille Neuroscience & Cognition (LilNCog)-U1172, Université Lille, Inserm, CHU Lille, Lille, France
| | - Marco Duering
- Institute for Stroke and Dementia Research (ISD), LMU University Hospital, LMU Munich, Munich, Germany
- Medical Image Analysis Center (MIAC), Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Rong Fang
- Institute for Stroke and Dementia Research (ISD), LMU University Hospital, LMU Munich, Munich, Germany
| | | | - Jonguk Kim
- Department of Neurology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Republic of Korea
- Department of Neurology, School of Medicine, Inha University, Incheon, Republic of Korea
| | - Beom Joon Kim
- Department of Neurology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Republic of Korea
| | - Paul Lm de Kort
- Department of Neurology, Elisabeth Tweesteden Hospital, Tilburg, The Netherlands
| | - Peter J Koudstaal
- Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Minwoo Lee
- Department of Neurology, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang, Republic of Korea
| | - Jae-Sung Lim
- Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Renaud Lopes
- Lille Neuroscience & Cognition (LilNCog)-U1172, Université Lille, Inserm, CHU Lille, Lille, France
| | | | - Julie Staals
- Department of Neurology, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Kyung-Ho Yu
- Department of Neurology, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang, Republic of Korea
| | - Geert Jan Biessels
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - J Matthijs Biesbroek
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
- Department of Neurology, Diakonessenhuis Hospital, Utrecht, The Netherlands
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Xhima K, Ottoy J, Gibson E, Zukotynski K, Scott C, Feliciano GJ, Adamo S, Kuo PH, Borrie MJ, Chertkow H, Frayne R, Laforce R, Noseworthy MD, Prato FS, Sahlas DJ, Smith EE, Sossi V, Thiel A, Soucy J, Tardif J, Goubran M, Black SE, Ramirez J. Distinct spatial contributions of amyloid pathology and cerebral small vessel disease to hippocampal morphology. Alzheimers Dement 2024; 20:3687-3695. [PMID: 38574400 PMCID: PMC11095424 DOI: 10.1002/alz.13791] [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: 09/30/2023] [Revised: 01/22/2024] [Accepted: 02/09/2024] [Indexed: 04/06/2024]
Abstract
INTRODUCTION Cerebral small vessel disease (SVD) and amyloid beta (Aβ) pathology frequently co-exist. The impact of concurrent pathology on the pattern of hippocampal atrophy, a key substrate of memory impacted early and extensively in dementia, remains poorly understood. METHODS In a unique cohort of mixed Alzheimer's disease and moderate-severe SVD, we examined whether total and regional neuroimaging measures of SVD, white matter hyperintensities (WMH), and Aβ, as assessed by 18F-AV45 positron emission tomography, exert additive or synergistic effects on hippocampal volume and shape. RESULTS Frontal WMH, occipital WMH, and Aβ were independently associated with smaller hippocampal volume. Frontal WMH had a spatially distinct impact on hippocampal shape relative to Aβ. In contrast, hippocampal shape alterations associated with occipital WMH spatially overlapped with Aβ-vulnerable subregions. DISCUSSION Hippocampal degeneration is differentially sensitive to SVD and Aβ pathology. The pattern of hippocampal atrophy could serve as a disease-specific biomarker, and thus guide clinical diagnosis and individualized treatment strategies for mixed dementia.
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Affiliation(s)
- Kristiana Xhima
- Dr. Sandra E. Black Centre for Brain Resilience and RecoveryLC Campbell Cognitive Neurology, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of TorontoTorontoOntarioCanada
| | - Julie Ottoy
- Dr. Sandra E. Black Centre for Brain Resilience and RecoveryLC Campbell Cognitive Neurology, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of TorontoTorontoOntarioCanada
| | - Erin Gibson
- Dr. Sandra E. Black Centre for Brain Resilience and RecoveryLC Campbell Cognitive Neurology, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of TorontoTorontoOntarioCanada
| | - Katherine Zukotynski
- Dr. Sandra E. Black Centre for Brain Resilience and RecoveryLC Campbell Cognitive Neurology, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of TorontoTorontoOntarioCanada
- Departments of Medicine and RadiologyMcMaster UniversityHamiltonOntarioCanada
- Department of Medical ImagingSchulich School of Medicine and Dentistry, Western UniversityLondonOntarioCanada
| | - Christopher Scott
- Dr. Sandra E. Black Centre for Brain Resilience and RecoveryLC Campbell Cognitive Neurology, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of TorontoTorontoOntarioCanada
| | - Ginelle J. Feliciano
- Dr. Sandra E. Black Centre for Brain Resilience and RecoveryLC Campbell Cognitive Neurology, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of TorontoTorontoOntarioCanada
| | - Sabrina Adamo
- Dr. Sandra E. Black Centre for Brain Resilience and RecoveryLC Campbell Cognitive Neurology, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of TorontoTorontoOntarioCanada
| | - Phillip H. Kuo
- Departments of Medical Imaging, Medicine, Biomedical EngineeringUniversity of ArizonaTucsonArizonaUSA
| | - Michael J. Borrie
- Schulich School of Medicine and DentistryWestern UniversityLondonOntarioCanada
| | - Howard Chertkow
- Rotman Research InstituteBaycrest Health SciencesTorontoOntarioCanada
| | - Richard Frayne
- Departments of Radiology and Clinical NeuroscienceHotchkiss Brain Institute, University of CalgaryCalgaryAlbertaCanada
| | - Robert Laforce
- Clinique Interdisciplinaire de Mémoire, Département des Sciences NeurologiquesUniversité Laval, Quebec CityQuebecCanada
| | - Michael D. Noseworthy
- Departments of Medicine and RadiologyMcMaster UniversityHamiltonOntarioCanada
- Department of Electrical and Computer EngineeringMcMaster UniversityHamiltonOntarioCanada
| | - Frank S. Prato
- Schulich School of Medicine and DentistryWestern UniversityLondonOntarioCanada
| | | | - Eric E. Smith
- Department of Clinical Neurosciences and Hotchkiss Brain InstituteUniversity of CalgaryCalgaryAlbertaCanada
| | - Vesna Sossi
- Physics and Astronomy Department and DM Center for Brain HealthUniversity of British ColumbiaVancouverBritish ColumbiaCanada
| | - Alexander Thiel
- Department of Neurology and NeurosurgeryMcGill UniversityMontrealQuebecCanada
| | - Jean‐Paul Soucy
- Montreal Neurological InstituteMcGill UniversityMontrealQuebecCanada
| | | | - Maged Goubran
- Dr. Sandra E. Black Centre for Brain Resilience and RecoveryLC Campbell Cognitive Neurology, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of TorontoTorontoOntarioCanada
- Department of Medical BiophysicsUniversity of TorontoTorontoOntarioCanada
- Physical Sciences Platform, Sunnybrook Research InstituteUniversity of TorontoTorontoOntarioCanada
| | - Sandra E. Black
- Dr. Sandra E. Black Centre for Brain Resilience and RecoveryLC Campbell Cognitive Neurology, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of TorontoTorontoOntarioCanada
- Division of NeurologyDepartment of MedicineUniversity of TorontoTorontoOntarioCanada
| | - Joel Ramirez
- Dr. Sandra E. Black Centre for Brain Resilience and RecoveryLC Campbell Cognitive Neurology, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of TorontoTorontoOntarioCanada
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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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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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Cha WJ, Yi D, Ahn H, Byun MS, Chang YY, Choi JM, Kim K, Choi H, Jung G, Kang KM, Sohn CH, Lee YS, Kim YK, Lee DY. Association between brain amyloid deposition and longitudinal changes of white matter hyperintensities. Alzheimers Res Ther 2024; 16:50. [PMID: 38454444 PMCID: PMC10918927 DOI: 10.1186/s13195-024-01417-8] [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: 11/04/2023] [Accepted: 02/20/2024] [Indexed: 03/09/2024]
Abstract
BACKGROUND Growing evidence suggests that not only cerebrovascular disease but also Alzheimer's disease (AD) pathological process itself cause cerebral white matter degeneration, resulting in white matter hyperintensities (WMHs). Some preclinical evidence also indicates that white matter degeneration may precede or affect the development of AD pathology. This study aimed to clarify the direction of influence between in vivo AD pathologies, particularly beta-amyloid (Aβ) and tau deposition, and WMHs through longitudinal approach. METHODS Total 282 older adults including cognitively normal and cognitively impaired individuals were recruited from the Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer's Disease (KBASE) cohort. The participants underwent comprehensive clinical and neuropsychological assessment, [11C] Pittsburgh Compound B PET for measuring Aβ deposition, [18F] AV-1451 PET for measuring tau deposition, and MRI scans with fluid-attenuated inversion recovery image for measuring WMH volume. The relationships between Aβ or tau deposition and WMH volume were examined using multiple linear regression analysis. In this analysis, baseline Aβ or tau were used as independent variables, and change of WMH volume over 2 years was used as dependent variable to examine the effect of AD pathology on increase of WMH volume. Additionally, we set baseline WMH volume as independent variable and longitudinal change of Aβ or tau deposition for 2 years as dependent variables to investigate whether WMH volume could precede AD pathologies. RESULTS Baseline Aβ deposition, but not tau deposition, had significant positive association with longitudinal change of WMH volume over 2 years. Baseline WMH volume was not related with any of longitudinal change of Aβ or tau deposition for 2 years. We also found a significant interaction effect between baseline Aβ deposition and sex on longitudinal change of WMH volume. Subsequent subgroup analyses showed that high baseline Aβ deposition was associated with increase of WMH volume over 2 years in female, but not in male. CONCLUSIONS Our findings suggest that Aβ deposition accelerates cerebral WMHs, particularly in female, whereas white matter degeneration appears not influence on longitudinal Aβ increase. The results also did not support any direction of influence between tau deposition and WMHs.
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Affiliation(s)
- Woo-Jin Cha
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Dahyun Yi
- Institute of Human Behavioral Medicine, Medical Research Center, Seoul National University, Seoul, Republic of Korea
| | - Hyejin Ahn
- Interdisciplinary program of cognitive science, Seoul National University College of Humanities, Seoul, Republic of Korea
| | - Min Soo Byun
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Yoon Young Chang
- Department of Psychiatry, Inje University Sanggye Paik Hospital, Seoul, Republic of Korea
| | - Jung-Min Choi
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Kyungtae Kim
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Hyeji Choi
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Gijung Jung
- Institute of Human Behavioral Medicine, Medical Research Center, Seoul National University, Seoul, Republic of Korea
| | - Koung Mi Kang
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Chul-Ho Sohn
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Yun-Sang Lee
- Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Yu Kyeong Kim
- Department of Nuclear Medicine, Seoul Metropolitan Government-Seoul National University Boramae Medical Center, Seoul, Republic of Korea
| | - Dong Young Lee
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea.
- Institute of Human Behavioral Medicine, Medical Research Center, Seoul National University, Seoul, Republic of Korea.
- Interdisciplinary program of cognitive science, Seoul National University College of Humanities, Seoul, Republic of Korea.
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea.
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9
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Lim J, Lee K, Kim BJ, Ryu W, Chung J, Gwak D, Lee JS, Kim S, Ko E, Lee J, Han M, Smith EE, Kim D, Bae H. Nonhypertensive White Matter Hyperintensities in Stroke: Risk Factors, Neuroimaging Characteristics, and Prognosis. J Am Heart Assoc 2023; 12:e030515. [PMID: 38014679 PMCID: PMC10727348 DOI: 10.1161/jaha.123.030515] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/08/2023] [Accepted: 11/03/2023] [Indexed: 11/29/2023]
Abstract
BACKGROUND This study explored the risk factors, neuroimaging features, and prognostic implications of nonhypertensive white matter hyperintensity (WMH) in patients with acute ischemic stroke and transient ischemic attack. METHODS AND RESULTS We included 2283 patients with hypertension and 1003 without from a pool of 10 602. Associations of moderate-to-severe WMH with known risk factors, functional outcome, and a composite of recurrent stroke, myocardial infarction, and all-cause mortality were evaluated. A subset of 351 patients without hypertension and age- and sex-matched pairs with hypertension and moderate-to-severe WMH was created for a detailed topographic examination of WMH, lacunes, and microbleeds. Approximately 35% of patients without hypertension and 65% of patients with hypertensive stroke exhibited moderate-to-severe WMH. WMH was associated with age, female sex, and previous stroke, irrespective of hypertension. In patients without hypertension, WMH was associated with initial systolic blood pressure and was more common in the anterior temporal region. In patients with hypertension, WMH was associated with small vessel occlusion as a stroke mechanism and was more frequent in the periventricular region near the posterior horn of the lateral ventricle. The higher prevalence of occipital microbleeds in patients without hypertension and deep subcortical lacunes in patients with hypertension were also observed. Associations of moderate-to-severe WMH with 3-month functional outcome and 1-year cumulative incidence of the composite outcome were significant (both P<0.01), although the latter lost significance after adjustments. The associations between WMH and outcomes were consistent across hypertensive status. CONCLUSIONS One-third of patients without hypertension with stroke have moderate-to-severe WMH. The pathogenesis of WMH may differ between patients without and with hypertension, but its impact on outcome appears similar.
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Affiliation(s)
- Jae‐Sung Lim
- Department of Neurology, Asan Medical CenterUniversity of Ulsan College of MedicineSeoulRepublic of Korea
| | - Keon‐Joo Lee
- Department of NeurologyKorea University Guro Hospital, Korea University College of MedicineSeoulRepublic of Korea
| | - Beom Joon Kim
- Department of NeurologySeoul National University Bundang Hospital, Seoul National University College of MedicineSeongnamRepublic of Korea
| | | | - Jinyong Chung
- Medical Science Research CenterDongguk University Medical CenterGoyangRepublic of Korea
| | - Dong‐Seok Gwak
- Department of NeurologyDongguk University Ilsan Hospital, Dongguk University College of MedicineGoyangRepublic of Korea
| | - Ji Sung Lee
- Clinical Research CenterAsan Institute for Life Sciences, Asan Medical CenterSeoulRepublic of Korea
| | - Seong‐Eun Kim
- Department of NeurologySeoul National University Bundang Hospital, Seoul National University College of MedicineSeongnamRepublic of Korea
| | - Eunvin Ko
- Department of BiostatisticsKorea UniversitySeoulRepublic of Korea
| | - Juneyoung Lee
- Department of BiostatisticsKorea UniversitySeoulRepublic of Korea
| | - Moon‐Ku Han
- Department of NeurologySeoul National University Bundang Hospital, Seoul National University College of MedicineSeongnamRepublic of Korea
| | - Eric E. Smith
- Department of Clinical Neuroscience and Hotchkiss Brain Institute, Cumming School of MedicineUniversity of CalgaryCalgaryCanada
| | - Dong‐Eog Kim
- Department of NeurologyDongguk University Ilsan Hospital, Dongguk University College of MedicineGoyangRepublic of Korea
| | - Hee‐Joon Bae
- Department of NeurologySeoul National University Bundang Hospital, Seoul National University College of MedicineSeongnamRepublic of Korea
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10
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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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11
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Bollack A, Pemberton HG, Collij LE, Markiewicz P, Cash DM, Farrar G, Barkhof F. Longitudinal amyloid and tau PET imaging in Alzheimer's disease: A systematic review of methodologies and factors affecting quantification. Alzheimers Dement 2023; 19:5232-5252. [PMID: 37303269 DOI: 10.1002/alz.13158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 04/21/2023] [Accepted: 04/25/2023] [Indexed: 06/13/2023]
Abstract
Deposition of amyloid and tau pathology can be quantified in vivo using positron emission tomography (PET). Accurate longitudinal measurements of accumulation from these images are critical for characterizing the start and spread of the disease. However, these measurements are challenging; precision and accuracy can be affected substantially by various sources of errors and variability. This review, supported by a systematic search of the literature, summarizes the current design and methodologies of longitudinal PET studies. Intrinsic, biological causes of variability of the Alzheimer's disease (AD) protein load over time are then detailed. Technical factors contributing to longitudinal PET measurement uncertainty are highlighted, followed by suggestions for mitigating these factors, including possible techniques that leverage shared information between serial scans. Controlling for intrinsic variability and reducing measurement uncertainty in longitudinal PET pipelines will provide more accurate and precise markers of disease evolution, improve clinical trial design, and aid therapy response monitoring.
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Affiliation(s)
- Ariane Bollack
- Department of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing (CMIC), University College London, London, UK
| | - Hugh G Pemberton
- Department of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing (CMIC), University College London, London, UK
- GE Healthcare, Amersham, UK
- UCL Queen Square Institute of Neurology, London, UK
| | - Lyduine E Collij
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, location VUmc, Amsterdam, The Netherlands
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Pawel Markiewicz
- Department of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing (CMIC), University College London, London, UK
| | - David M Cash
- UCL Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute at University College London, London, UK
| | | | - Frederik Barkhof
- Department of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing (CMIC), University College London, London, UK
- UCL Queen Square Institute of Neurology, London, UK
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, location VUmc, Amsterdam, The Netherlands
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12
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Sin MK, Zamrini E, Ahmed A, Nho K, Hajjar I. Anti-Amyloid Therapy, AD, and ARIA: Untangling the Role of CAA. J Clin Med 2023; 12:6792. [PMID: 37959255 PMCID: PMC10647766 DOI: 10.3390/jcm12216792] [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: 09/20/2023] [Revised: 10/22/2023] [Accepted: 10/24/2023] [Indexed: 11/15/2023] Open
Abstract
Anti-amyloid therapies (AATs), such as anti-amyloid monoclonal antibodies, are emerging treatments for people with early Alzheimer's disease (AD). AATs target amyloid β plaques in the brain. Amyloid-related imaging abnormalities (ARIA), abnormal signals seen on magnetic resonance imaging (MRI) of the brain in patients with AD, may occur spontaneously but occur more frequently as side effects of AATs. Cerebral amyloid angiopathy (CAA) is a major risk factor for ARIA. Amyloid β plays a key role in the pathogenesis of AD and of CAA. Amyloid β accumulation in the brain parenchyma as plaques is a pathological hallmark of AD, whereas amyloid β accumulation in cerebral vessels leads to CAA. A better understanding of the pathophysiology of ARIA is necessary for early detection of those at highest risk. This could lead to improved risk stratification and the ultimate reduction of symptomatic ARIA. Histopathological confirmation of CAA by brain biopsy or autopsy is the gold standard but is not clinically feasible. MRI is an available in vivo tool for detecting CAA. Cerebrospinal fluid amyloid β level testing and amyloid PET imaging are available but do not offer specificity for CAA vs amyloid plaques in AD. Thus, developing and testing biomarkers as reliable and sensitive screening tools for the presence and severity of CAA is a priority to minimize ARIA complications.
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Affiliation(s)
- Mo-Kyung Sin
- College of Nursing, Seattle University, Seattle, WA 98122, USA
| | | | - Ali Ahmed
- VA Medical Center, Washington, DC 20242, USA;
| | - Kwangsik Nho
- School of Medicine, Indianna University, Indianapolis, IN 46202, USA;
| | - Ihab Hajjar
- School of Medicine, University of Texas Southwestern, Dallas, TX 75390, USA;
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13
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Ali DG, Bahrani AA, El Khouli RH, Gold BT, Jiang Y, Zachariou V, Wilcock DM, Jicha GA. White matter hyperintensities influence distal cortical β-amyloid accumulation in default mode network pathways. Brain Behav 2023; 13:e3209. [PMID: 37534614 PMCID: PMC10570488 DOI: 10.1002/brb3.3209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Revised: 07/19/2023] [Accepted: 07/22/2023] [Indexed: 08/04/2023] Open
Abstract
BACKGROUND AND PURPOSE Cerebral small vessel disease (SVD) has been suggested to contribute to the pathogenesis of Alzheimer's disease (AD). Yet, the role of SVD in potentially contributing to AD pathology is unclear. The main objective of this study was to test the hypothesis that WMHs influence amyloid β (Aβ) levels within connected default mode network (DMN) tracts and cortical regions in cognitively unimpaired older adults. METHODS Regional standard uptake value ratios (SUVr) from Aβ-PET and white matter hyperintensity (WMH) volumes from three-dimensional magnetic resonance imaging FLAIR images were analyzed across a sample of 72 clinically unimpaired (mini-mental state examination ≥26), older adults (mean age 74.96 and standard deviation 8.13) from the Alzheimer's Disease Neuroimaging Initiative (ADNI3). The association of WMH volumes in major fiber tracts projecting from cortical DMN regions and Aβ-PET SUVr in the connected cortical DMN regions was analyzed using linear regression models adjusted for age, sex, ApoE, and total brain volumes. RESULTS The regression analyses demonstrate that increased WMH volumes in the superior longitudinal fasciculus were associated with increased regional SUVr in the inferior parietal lobule (p = .011). CONCLUSION The findings suggest that the relation between Aβ in parietal cortex is associated with SVD in downstream white matter (WM) pathways in preclinical AD. The biological relationships and interplay between Aβ and WM microstructure alterations that precede overt WMH development across the continuum of AD progression warrant further study.
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Affiliation(s)
- Doaa G. Ali
- Sanders‐Brown Center on Aging, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Behavioral Science, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Ahmed A. Bahrani
- Sanders‐Brown Center on Aging, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Neurology, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Riham H. El Khouli
- Department of Radiology, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Brian T. Gold
- Sanders‐Brown Center on Aging, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Neuroscience, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Yang Jiang
- Sanders‐Brown Center on Aging, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Behavioral Science, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Valentinos Zachariou
- Department of Neuroscience, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Donna M. Wilcock
- Sanders‐Brown Center on Aging, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Physiology, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Gregory A. Jicha
- Sanders‐Brown Center on Aging, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Behavioral Science, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Neurology, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
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14
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Whitman ET, Ryan CP, Abraham WC, Addae A, Corcoran DL, Elliott ML, Hogan S, Ireland D, Keenan R, Knodt AR, Melzer TR, Poulton R, Ramrakha S, Sugden K, Williams BS, Zhou J, Hariri AR, Belsky DW, Moffitt TE, Caspi A. A blood biomarker of accelerated aging in the body associates with worse structural integrity in the brain: replication across three cohorts. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.09.06.23295140. [PMID: 37732266 PMCID: PMC10508789 DOI: 10.1101/2023.09.06.23295140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/22/2023]
Abstract
Biological aging is the correlated decline of multi-organ system integrity central to the etiology of many age-related diseases. A novel epigenetic measure of biological aging, DunedinPACE, is associated with cognitive dysfunction, incident dementia, and mortality. Here, we tested for associations between DunedinPACE and structural MRI phenotypes in three datasets spanning midlife to advanced age: the Dunedin Study (age=45 years), the Framingham Heart Study Offspring Cohort (mean age=63 years), and the Alzheimer's Disease Neuroimaging Initiative (mean age=75 years). We also tested four additional epigenetic measures of aging: the Horvath clock, the Hannum clock, PhenoAge, and GrimAge. Across all datasets (total N observations=3,380; total N individuals=2,322), faster DunedinPACE was associated with lower total brain volume, lower hippocampal volume, and thinner cortex. In two datasets, faster DunedinPACE was associated with greater burden of white matter hyperintensities. Across all measures, DunedinPACE and GrimAge had the strongest and most consistent associations with brain phenotypes. Our findings suggest that single timepoint measures of multi-organ decline such as DunedinPACE could be useful for gauging nervous system health.
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Affiliation(s)
- Ethan T Whitman
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Calen P Ryan
- Butler Columbia Aging Center, Columbia University Mailman School of Public Health, New York, USA
| | | | - Angela Addae
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - David L Corcoran
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Maxwell L Elliott
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA, USA
| | - Sean Hogan
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - David Ireland
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Ross Keenan
- Brain Research New Zealand-Rangahau Roro Aotearoa, Centre of Research Excellence, Universities of Auckland and Otago, New Zealand
- Christchurch Radiology Group, Christchurch, New Zealand
| | - Annchen R Knodt
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Tracy R Melzer
- Brain Research New Zealand-Rangahau Roro Aotearoa, Centre of Research Excellence, Universities of Auckland and Otago, New Zealand
- Department of Medicine, University of Otago, Christchurch, New Zealand
| | - Richie Poulton
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Sandhya Ramrakha
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Karen Sugden
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | | | - Jiayi Zhou
- Butler Columbia Aging Center, Columbia University Mailman School of Public Health, New York, USA
| | - Ahmad R Hariri
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Daniel W Belsky
- Butler Columbia Aging Center, Columbia University Mailman School of Public Health, New York, USA
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, USA
| | - Terrie E Moffitt
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
- Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
- King's College London, Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, & Neuroscience, London, UK
- PROMENTA, Department of Psychology, University of Oslo, Norway
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
| | - Avshalom Caspi
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
- Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
- King's College London, Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, & Neuroscience, London, UK
- PROMENTA, Department of Psychology, University of Oslo, Norway
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
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15
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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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16
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Shaji S, Palanisamy R, Swaminathan R. Structural irregularities in MR corpus callosal images and their association with cerebrospinal fluid biomarkers in Mild Cognitive Impairments. Neurosci Lett 2023; 810:137329. [PMID: 37301466 DOI: 10.1016/j.neulet.2023.137329] [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: 01/14/2023] [Revised: 05/15/2023] [Accepted: 06/05/2023] [Indexed: 06/12/2023]
Abstract
In this study, irregularity measures from MR images of corpus callosal brain structures in healthy and Mild Cognitive Impairment (MCI) conditions are extracted and their association with Cerebrospinal Fluid (CSF) biomarkers are analyzed. For this, MR images of healthy controls, Early MCI (EMCI) and Late MCI (LMCI) subjects are considered from a public database. The considered images are preprocessed and corpus callosal structure is segmented. Structural irregularity measures are extracted from the segmented regions using Fourier analysis. Statistical tests are performed to identify the significant features which can characterize the MCI stages. Association of these measures with CSF amyloid beta and tau concentrations are further investigated. Results demonstrate that Fourier spectral analysis is able to characterize the non-periodic variations in the corpus callosal structures of healthy, EMCI and LMCI MR images. The callosal irregularity measures increase as the disease progresses from healthy to LMCI. Phosphorylated tau concentrations in CSF demonstrate a positive correlation with irregularity measures across the diagnostic groups. Significant association of callosal measures and amyloid beta levels are found to be absent in MCI stages. As corpus callosal structural irregularities due to early MCI condition and their association with CSF markers remain uncharacterized in the literature, this study seems to be clinically significant for the timely intervention of pre-symptomatic MCI stages.
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Affiliation(s)
- Sreelakshmi Shaji
- Non-Invasive Imaging and Diagnostic Laboratory, Biomedical Engineering Group, Department of Applied Mechanics, Indian Institute of Technology Madras, Chennai, India.
| | - Rohini Palanisamy
- Indian Institute of Information Technology, Design and Manufacturing, Kancheepuram, Chennai, India.
| | - Ramakrishnan Swaminathan
- Non-Invasive Imaging and Diagnostic Laboratory, Biomedical Engineering Group, Department of Applied Mechanics, Indian Institute of Technology Madras, Chennai, India.
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17
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Wang L, Kolobaric A, Aizenstein H, Lopresti B, Tudorascu D, Snitz B, Klunk W, Wu M. Identifying sex-specific risk architectures for predicting amyloid deposition using neural networks. Neuroimage 2023; 275:120147. [PMID: 37156449 PMCID: PMC10905666 DOI: 10.1016/j.neuroimage.2023.120147] [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: 02/06/2023] [Revised: 04/08/2023] [Accepted: 04/28/2023] [Indexed: 05/10/2023] Open
Abstract
In older adults without dementia, White Matter Hyperintensities (WMH) in MRI have been shown to be highly associated with cerebral amyloid deposition, measured by the Pittsburgh compound B (PiB) PET. However, the relation to age, sex, and education in explaining this association is not well understood. We use the voxel counts of regional WMH, age, one-hot encoded sex, and education to predict the regional PiB using a multilayer perceptron with only rectilinear activations using mean squared error. We then develop a novel, robust metric to understand the relevance of each input variable for prediction. Our observations indicate that sex is the most relevant predictor of PiB and that WMH is not relevant for prediction. These results indicate that there is a sex-specific risk architecture for Aβ deposition.
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Affiliation(s)
- Linghai Wang
- University of Pittsburgh, Pittsburgh, Pennsylvania, United States.
| | | | - Howard Aizenstein
- University of Pittsburgh, Pittsburgh, Pennsylvania, United States; Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, United States; School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States
| | - Brian Lopresti
- University of Pittsburgh, Pittsburgh, Pennsylvania, United States
| | - Dana Tudorascu
- Department of Biostatistics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States
| | - Beth Snitz
- University of Pittsburgh, Pittsburgh, Pennsylvania, United States
| | - William Klunk
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, United States; School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States
| | - Minjie Wu
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, United States
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18
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Høilund-Carlsen PF, Revheim ME, Costa T, Kepp KP, Castellani RJ, Perry G, Alavi A, Barrio JR. FDG-PET versus Amyloid-PET Imaging for Diagnosis and Response Evaluation in Alzheimer's Disease: Benefits and Pitfalls. Diagnostics (Basel) 2023; 13:2254. [PMID: 37443645 DOI: 10.3390/diagnostics13132254] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 06/29/2023] [Accepted: 06/30/2023] [Indexed: 07/15/2023] Open
Abstract
In June 2021, the US Federal Drug and Food Administration (FDA) granted accelerated approval for the antibody aducanumab and, in January 2023, also for the antibody lecanemab, based on a perceived drug-induced removal of cerebral amyloid-beta as assessed by amyloid-PET and, in the case of lecanemab, also a presumption of limited clinical efficacy. Approval of the antibody donanemab is awaiting further data. However, published trial data indicate few, small and uncertain clinical benefits, below what is considered "clinically meaningful" and similar to the effect of conventional medication. Furthermore, a therapy-related decrease in the amyloid-PET signal may also reflect increased cell damage rather than simply "amyloid removal". This interpretation is more consistent with increased rates of amyloid-related imaging abnormalities and brain volume loss in treated patients, relative to placebo. We also challenge the current diagnostic criteria for AD based on amyloid-PET imaging biomarkers and recommend that future anti-AD therapy trials apply: (1) diagnosis of AD based on the co-occurrence of cognitive decline and decreased cerebral metabolism assessed by FDA-approved FDG-PET, (2) therapy efficacy determined by favorable effect on cognitive ability, cerebral metabolism by FDG-PET, and brain volumes by MRI, and (3) neuropathologic examination of all deaths occurring in these trials.
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Affiliation(s)
- Poul F Høilund-Carlsen
- Department of Nuclear Medicine, Odense University Hospital, 5000 Odense C, Denmark
- Research Unit of Clinical Physiology and Nuclear Medicine, Department of Clinical Research, University of Southern Denmark, 5230 Odense M, Denmark
| | - Mona-Elisabeth Revheim
- The Intervention Centre, Division of Technology and Innovation, Oslo University Hospital, 0372 Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, 0313 Oslo, Norway
| | - Tommaso Costa
- GDS, Department of Psychology, Koelliker Hospital, University of Turin, 10124 Turin, Italy
- FOCUS Lab, Department of Psychology, University of Turin, 10124 Turin, Italy
| | - Kasper P Kepp
- Section of Biophysical and Biomedicinal Chemistry, DTU Chemistry, Technical University of Denmark, 2800 Kongens Lyngby, Denmark
| | - Rudolph J Castellani
- Department of Pathology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - George Perry
- Department of Neuroscience, Developmental and Regenerative Biology and Genetics of Neurodegeneration, Departments of Psychiatry and Neuroscience, University of Texas at San Antonio, San Antonio, TX 78249, USA
| | - Abass Alavi
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jorge R Barrio
- Department of Molecular and Medical Pharmacology, David Geffen UCLA School of Medicine, Los Angeles, CA 90095, USA
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19
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Coenen M, Kuijf HJ, Huenges Wajer IMC, Duering M, Wolters FJ, Fletcher EF, Maillard PM, Barkhof F, Barnes J, Benke T, Boomsma JMF, Chen CPLH, Dal-Bianco P, Dewenter A, Enzinger C, Ewers M, Exalto LG, Franzmeier N, Groeneveld O, Hilal S, Hofer E, Koek DL, Maier AB, McCreary CR, Padilla CS, Papma JM, Paterson RW, Pijnenburg YAL, Rubinski A, Schmidt R, Schott JM, Slattery CF, Smith EE, Steketee RME, Sudre CH, van den Berg E, van der Flier WM, Venketasubramanian N, Vernooij MW, Xin X, DeCarli C, Biessels GJ, Biesbroek JM. Strategic white matter hyperintensity locations for cognitive impairment: A multicenter lesion-symptom mapping study in 3525 memory clinic patients. Alzheimers Dement 2023; 19:2420-2432. [PMID: 36504357 DOI: 10.1002/alz.12827] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 09/07/2022] [Accepted: 09/13/2022] [Indexed: 12/14/2022]
Abstract
INTRODUCTION Impact of white matter hyperintensities (WMH) on cognition likely depends on lesion location, but a comprehensive map of strategic locations is lacking. We aimed to identify these locations in a large multicenter study. METHODS Individual patient data (n = 3525) from 11 memory clinic cohorts were harmonized. We determined the association of WMH location with attention and executive functioning, information processing speed, language, and verbal memory performance using voxel-based and region of interest tract-based analyses. RESULTS WMH in the left and right anterior thalamic radiation, forceps major, and left inferior fronto-occipital fasciculus were significantly related to domain-specific impairment, independent of total WMH volume and atrophy. A strategic WMH score based on these tracts inversely correlated with performance in all domains. DISCUSSION The data show that the impact of WMH on cognition is location-dependent, primarily involving four strategic white matter tracts. Evaluation of WMH location may support diagnosing vascular cognitive impairment. HIGHLIGHTS We analyzed white matter hyperintensities (WMH) in 3525 memory clinic patients from 11 cohorts The impact of WMH on cognition depends on location We identified four strategic white matter tracts A single strategic WMH score was derived from these four strategic tracts The strategic WMH score was an independent determinant of four cognitive domains.
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Affiliation(s)
- Mirthe Coenen
- Department of Neurology and Neurosurgery, UMC Utrecht, Brain Center, Utrecht, The Netherlands
| | - Hugo J Kuijf
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Irene M C Huenges Wajer
- Department of Neurology and Neurosurgery, UMC Utrecht, Brain Center, Utrecht, The Netherlands
- Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, The Netherlands
| | - 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
| | - Frank J Wolters
- Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Alzheimer Center Erasmus MC, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Evan F Fletcher
- Department of Neurology, University of California at Davis, Davis, California, USA
| | - Pauline M Maillard
- Department of Neurology, University of California at Davis, Davis, California, USA
| | - Frederik Barkhof
- Radiology & Nuclear Medicine, Amsterdam UMC, location Vrije Universiteit, Amsterdam, 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, 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
| | - Peter Dal-Bianco
- Department of Neurology, Medical University Vienna, Vienna, Austria
| | - Anna Dewenter
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Christian Enzinger
- Division of General Neurology, Department of Neurology, Medical University Graz, Graz, Austria
- Division of Neuroradiology, Interventional and Vascular Radiology, Department of Radiology, Medical University of Graz, 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
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Nicolai Franzmeier
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Onno Groeneveld
- Department of Neurology and Neurosurgery, UMC Utrecht, Brain Center, Utrecht, The Netherlands
- Department of Neurology, Isala MS Centre, Isala Hospital, 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, Graz, Austria
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria
| | - Dineke 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
- Department of Medicine, National University of Singapore, Singapore, Singapore
| | - Cheryl R McCreary
- Department of Clinical Neurosciences and Radiology and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Catarina S Padilla
- Department of Neurology and Neurosurgery, UMC Utrecht, Brain Center, Utrecht, The Netherlands
| | - 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, 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
| | - Rebecca M E Steketee
- Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Alzheimer Center Erasmus MC, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Carole H Sudre
- MRC Unit for Lifelong Health and Ageing, the Centre for Medical Image Computing, UCL, London, UK
| | - 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
- Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Alzheimer Center Erasmus MC, 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
| | - Charles DeCarli
- Department of Neurology, University of California at Davis, Davis, California, USA
| | - Geert Jan Biessels
- Department of Neurology and Neurosurgery, UMC Utrecht, Brain Center, Utrecht, The Netherlands
| | - J Matthijs Biesbroek
- Department of Neurology and Neurosurgery, UMC Utrecht, Brain Center, Utrecht, The Netherlands
- Department of Neurology, Diakonessenhuis Hospital, Utrecht, The Netherlands
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20
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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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21
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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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22
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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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23
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Ali DG, Abner EL, Bahrani AA, El Khouli R, Gold BT, Jiang Y, Wilcock DM, Jicha GA. Amyloid-PET and White Matter Hyperintensities Have Independent Effects on Baseline Cognitive Function and Synergistic Effects on Longitudinal Executive Function. Brain Sci 2023; 13:brainsci13020218. [PMID: 36831761 PMCID: PMC9953773 DOI: 10.3390/brainsci13020218] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 01/21/2023] [Accepted: 01/23/2023] [Indexed: 01/31/2023] Open
Abstract
Co-occurrence of beta amyloid (Aβ) and white matter hyperintensities (WMHs) increase the risk of dementia and both are considered biomarkers of preclinical dementia. Moderation and mediation modeling were used to define the interplay between global and regional Aβ and WMHs measures in relation to executive function (EF) and memory composite scores outcomes at baseline and after approximately 2 years across a sample of 714 clinically normal participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI 2). The moderation regression analysis showed additive effects of Aβ and WMHs over baseline memory and EF scores (p = 0.401 and 0.061, respectively) and synergistic effects over follow-up EF (p < 0.05). Through mediation analysis, the data presented demonstrate that WMHs effects, mediated by global and regional amyloid burden, are responsible for baseline cognitive performance deficits in memory and EF. These findings suggest that Aβ and WMHs contribute to baseline cognition independently while WMHs volumes exert effects on baseline cognitive performance directly and through influences on Aβ accumulation.
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Affiliation(s)
- Doaa G. Ali
- Sanders-Brown Center on Aging, College of Medicine, University of Kentucky, Lexington, KY 40506, USA
- Department of Behavioral Science, College of Medicine, University of Kentucky, Lexington, KY 40506, USA
- Correspondence:
| | - Erin L. Abner
- Sanders-Brown Center on Aging, College of Medicine, University of Kentucky, Lexington, KY 40506, USA
- Department of Epidemiology, College of Public Health, University of Kentucky, Lexington, KY 40536, USA
| | - Ahmed A. Bahrani
- Sanders-Brown Center on Aging, College of Medicine, University of Kentucky, Lexington, KY 40506, USA
- Department of Neurology, College of Medicine, University of Kentucky, Lexington, KY 40506, USA
| | - Riham El Khouli
- Department of Radiology, College of Medicine, University of Kentucky, Lexington, KY 40536, USA
| | - Brian T. Gold
- Sanders-Brown Center on Aging, College of Medicine, University of Kentucky, Lexington, KY 40506, USA
- Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY 40536, USA
| | - Yang Jiang
- Sanders-Brown Center on Aging, College of Medicine, University of Kentucky, Lexington, KY 40506, USA
- Department of Behavioral Science, College of Medicine, University of Kentucky, Lexington, KY 40506, USA
| | - Donna M. Wilcock
- Sanders-Brown Center on Aging, College of Medicine, University of Kentucky, Lexington, KY 40506, USA
- Department of Physiology, College of Medicine, University of Kentucky, Lexington, KY 40506, USA
| | - Gregory A. Jicha
- Sanders-Brown Center on Aging, College of Medicine, University of Kentucky, Lexington, KY 40506, USA
- Department of Behavioral Science, College of Medicine, University of Kentucky, Lexington, KY 40506, USA
- Department of Neurology, College of Medicine, University of Kentucky, Lexington, KY 40506, USA
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24
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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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25
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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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26
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Ottoy J, Ozzoude M, Zukotynski K, Adamo S, Scott C, Gaudet V, Ramirez J, Swardfager W, Cogo-Moreira H, Lam B, Bhan A, Mojiri P, Kang MS, Rabin JS, Kiss A, Strother S, Bocti C, Borrie M, Chertkow H, Frayne R, Hsiung R, Laforce RJ, Noseworthy MD, Prato FS, Sahlas DJ, Smith EE, Kuo PH, Sossi V, Thiel A, Soucy JP, Tardif JC, Black SE, Goubran M. Vascular burden and cognition: Mediating roles of neurodegeneration and amyloid PET. Alzheimers Dement 2022; 19:1503-1517. [PMID: 36047604 DOI: 10.1002/alz.12750] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 06/06/2022] [Accepted: 06/10/2022] [Indexed: 11/06/2022]
Abstract
It remains unclear to what extent cerebrovascular burden relates to amyloid beta (Aβ) deposition, neurodegeneration, and cognitive dysfunction in mixed disease populations with small vessel disease and Alzheimer's disease (AD) pathology. In 120 subjects, we investigated the association of vascular burden (white matter hyperintensity [WMH] volumes) with cognition. Using mediation analyses, we tested the indirect effects of WMH on cognition via Aβ deposition (18 F-AV45 positron emission tomography [PET]) and neurodegeneration (cortical thickness or 18 F fluorodeoxyglucose PET) in AD signature regions. We observed that increased total WMH volume was associated with poorer performance in all tested cognitive domains, with the strongest effects observed for semantic fluency. These relationships were mediated mainly via cortical thinning, particularly of the temporal lobe, and to a lesser extent serially mediated via Aβ and cortical thinning of AD signature regions. WMH volumes differentially impacted cognition depending on lobar location and Aβ status. In summary, our study suggests mainly an amyloid-independent pathway in which vascular burden affects cognitive function via localized neurodegeneration. HIGHLIGHTS: Alzheimer's disease often co-exists with vascular pathology. We studied a unique cohort enriched for high white matter hyperintensities (WMH). High WMH related to cognitive impairment of semantic fluency and executive function. This relationship was mediated via temporo-parietal atrophy rather than metabolism. This relationship was, to lesser extent, serially mediated via amyloid beta and atrophy.
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Affiliation(s)
- Julie Ottoy
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Miracle Ozzoude
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Katherine Zukotynski
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada.,Departments of Medicine and Radiology, McMaster University, Hamilton, Ontario, Canada.,Department of Medical Imaging, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada.,Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Sabrina Adamo
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Christopher Scott
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Vincent Gaudet
- Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Ontario, Canada
| | - Joel Ramirez
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Walter Swardfager
- Department of Pharmacology & Toxicology, University of Toronto, Toronto, Ontario, Canada
| | - Hugo Cogo-Moreira
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada.,Department of Education, ICT and Learning, Østfold University College, Halden, Norway
| | - Benjamin Lam
- Department of Medicine (Division of Neurology), University of Toronto, Toronto, Ontario, Canada
| | - Aparna Bhan
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Parisa Mojiri
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Min Su Kang
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada.,Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.,Physical Sciences Platform, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Jennifer S Rabin
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, Ontario, Canada.,Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.,Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada.,Rehabilitation Sciences Institute, University of Toronto, Toronto, Ontario, Canada
| | - Alex Kiss
- Department of Research Design and Biostatistics, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Stephen Strother
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.,The Rotman Research Institute Baycrest, University of Toronto, Toronto, Ontario, Canada
| | - Christian Bocti
- Département de Médecine, Université de Sherbrooke, Sherbrooke, Quebec, Canada
| | - Michael Borrie
- Lawson Health Research Institute, Western University, London, Ontario, Canada
| | - Howard Chertkow
- Jewish General Hospital and Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Richard Frayne
- Departments of Radiology and Clinical Neuroscience, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Robin Hsiung
- Physics and Astronomy Department and DM Center for Brain Health, University of British Columbia, Vancouver, British Columbia, Canada
| | - Robert Jr Laforce
- Clinique Interdisciplinaire de Mémoire, Département des Sciences Neurologiques, Université Laval, Quebec City, Quebec, Canada
| | - Michael D Noseworthy
- Department of Electrical and Computer Engineering, McMaster University, Hamilton, Ontario, Canada
| | - Frank S Prato
- Lawson Health Research Institute, Western University, London, Ontario, Canada
| | | | - Eric E Smith
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Phillip H Kuo
- Department of Medical Imaging, Medicine, and Biomedical Engineering, University of Arizona, Tucson, Arizona, USA
| | - Vesna Sossi
- Physics and Astronomy Department and DM Center for Brain Health, University of British Columbia, Vancouver, British Columbia, Canada
| | - Alexander Thiel
- Jewish General Hospital and Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Jean-Paul Soucy
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Jean-Claude Tardif
- Montreal Heart Institute, Université de Montréal, Montreal, Quebec, Canada
| | - Sandra E Black
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada.,Department of Medicine (Division of Neurology), University of Toronto, Toronto, Ontario, Canada.,Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Maged Goubran
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada.,Physical Sciences Platform, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
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APOE-ε4 modulates the association among plasma Aβ 42/Aβ 40, vascular diseases, neurodegeneration and cognitive decline in non-demented elderly adults. Transl Psychiatry 2022; 12:128. [PMID: 35351867 PMCID: PMC8964707 DOI: 10.1038/s41398-022-01899-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 03/03/2022] [Accepted: 03/11/2022] [Indexed: 01/18/2023] Open
Abstract
Including apolipoprotein E-ε4 (APOE-ε4) status and older age into consideration may increase the accuracy of plasma Aβ42/Aβ40 detecting Aβ+ individuals, but the rationale behind this remains to be fully understood. Besides, both Aβ pathology and vascular diseases are related to neurodegeneration and cognitive decline, but it is still not fully understood how APOE-ε4 modulates these relationships. In this study, we examined 241 non-demented Alzheimer's Disease Neuroimaging Initiative participants to investigate the associations among age, white matter hyperintensities (WMH), hypertension, hyperlipidemia, body mass index (BMI), plasma Aβ42/Aβ40 measured by liquid chromatography tandem mass spectrometry, and 18F-florbetapir Aβ PET as well as their prediction of longitudinal adjusted hippocampal volume (aHCV) and cognition in APOE-ε4 carriers and non-carriers. We found older age predicted faster WMH increase (p = 0.024) and cortical Aβ accumulation (p = 0.043) in APOE-ε4 non-carriers only, whereas lower plasma Aβ42/Aβ40 predicted faster cortical Aβ accumulation (p < 0.018) regardless of APOE-ε4 status. While larger WMH and underweight predicted (p < 0.05) faster decreases in aHCV and cognition in APOE-ε4 non-carriers, lower plasma Aβ42/Aβ40 predicted (p < 0.031) faster decreases in aHCV and cognition in APOE-ε4 carriers. Higher Aβ PET also predicted faster rates of aHCV (p = 0.010) in APOE-ε4 carriers only, but was related to faster rates of cognitive decline (p < 0.022) regardless of APOE-ε4 status. These findings may provide novel insights into understanding different mechanisms underlie neurodegeneration and cognitive decline in non-demented elderly adults with and without APOE-ε4 allele, which may help the design of anti-Alzheimer's clinical trials.
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28
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Brown SS, Mak E, Clare I, Grigorova M, Beresford-Webb J, Walpert M, Jones E, Hong YT, Fryer TD, Coles JP, Aigbirhio FI, Tudorascu D, Cohen A, Christian BT, Handen BL, Klunk WE, Menon DK, Nestor PJ, Holland AJ, Zaman SH. Support vector machine learning and diffusion-derived structural networks predict amyloid quantity and cognition in adults with Down's syndrome. Neurobiol Aging 2022; 115:112-121. [PMID: 35418341 DOI: 10.1016/j.neurobiolaging.2022.02.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 02/23/2022] [Accepted: 02/24/2022] [Indexed: 10/18/2022]
Abstract
Down's syndrome results from trisomy of chromosome 21, a genetic change which also confers a probable 100% risk for the development of Alzheimer's disease neuropathology (amyloid plaque and neurofibrillary tangle formation) in later life. We aimed to assess the effectiveness of diffusion-weighted imaging and connectomic modelling for predicting brain amyloid plaque burden, baseline cognition and longitudinal cognitive change using support vector regression. Ninety-five participants with Down's syndrome successfully completed a full Pittsburgh Compound B (PiB) PET-MR protocol and memory assessment at two timepoints. Our findings indicate that graph theory metrics of node degree and strength based on the structural connectome are effective predictors of global amyloid deposition. We also show that connection density of the structural network at baseline is a promising predictor of current cognitive performance. Directionality of effects were mainly significant reductions in the white matter connectivity in relation to both PiB+ status and greater rate of cognitive decline. Taken together, these results demonstrate the integral role of the white matter during neuropathological progression and the utility of machine learning methodology for non-invasively evaluating Alzheimer's disease prognosis.
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29
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Shafer AT, Williams OA, Perez E, An Y, Landman BA, Ferrucci L, Resnick SM. Accelerated decline in white matter microstructure in subsequently impaired older adults and its relationship with cognitive decline. Brain Commun 2022; 4:fcac051. [PMID: 35356033 PMCID: PMC8963308 DOI: 10.1093/braincomms/fcac051] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Revised: 01/03/2022] [Accepted: 02/25/2022] [Indexed: 11/12/2022] Open
Abstract
Little is known about a longitudinal decline in white matter microstructure and its associations with cognition in preclinical dementia. Longitudinal diffusion tensor imaging and neuropsychological testing were performed in 50 older adults who subsequently developed mild cognitive impairment or dementia (subsequently impaired) and 200 cognitively normal controls. Rates of white matter microstructural decline were compared between groups using voxel-wise linear mixed-effects models. Associations between change in white matter microstructure and cognition were examined. Subsequently impaired individuals had a faster decline in fractional anisotropy in the right inferior fronto-occipital fasciculus and bilateral splenium of the corpus callosum. A decline in right inferior fronto-occipital fasciculus fractional anisotropy was related to a decline in verbal memory, visuospatial ability, processing speed and mini-mental state examination. A decline in bilateral splenium fractional anisotropy was related to a decline in verbal fluency, processing speed and mini-mental state examination. Accelerated regional white matter microstructural decline is evident during the preclinical phase of mild cognitive impairment/dementia and is related to domain-specific cognitive decline.
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Affiliation(s)
- Andrea T. Shafer
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD 21224, USA,Correspondence to: Andrea T. Shafer 251 Bayview Blvd., Baltimore MD 21224, USA E-mail:
| | - Owen A. Williams
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD 21224, USA,Department of Experimental Psychology, University of Oxford, Oxford, UK
| | - Evian Perez
- San Juan Bautista School of Medicine, Caguas, Puerto Rico
| | - Yang An
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD 21224, USA
| | | | - Luigi Ferrucci
- Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, Baltimore, MD 21224, USA
| | - Susan M. Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD 21224, USA,Correspondence may also be addressed to: Susan M. Resnick E-mail:
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30
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Lee KH, Kang KM. Association between Cerebral Small Vessel and Alzheimer’s Disease. JOURNAL OF THE KOREAN SOCIETY OF RADIOLOGY 2022; 83:486-507. [PMID: 36238505 PMCID: PMC9514514 DOI: 10.3348/jksr.2022.0041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 05/15/2022] [Accepted: 05/16/2022] [Indexed: 11/15/2022]
Abstract
뇌소혈관질환은 뇌 자기공명영상에서 흔히 관찰되는 혈관성 변화로 뇌백질 고신호강도, 뇌미세출혈, 열공성 경색, 혈관주위공간 등을 포함한다. 이러한 혈관성 변화가 알츠하이머병(Alzheimer’s disease; 이하 AD)의 발병 및 진행과 관련되어 있고, 대표 병리인 베타 아밀로이드 및 타우 단백의 침착과도 연관되어 있다는 증거들이 축적되고 있다. 혈관성 변화는 생활 습관 개선이나 약물 치료를 통해 예방과 개선이 가능하기 때문에 뇌소혈관질환과 AD 및 AD 생체지표의 관련성을 연구하는 것이 중요하다. 본 종설에서는 AD와 AD 생체지표에 대해 간략히 소개하고, AD와 혈관성 변화의 관련성에 대해 축적된 증거들을 제시한 다음, 뇌소혈관질환의 병태 생리와 MR 영상 소견을 설명하고자 한다. 또 뇌소혈관질환과 AD 진단의 위험도 및 AD 생체지표와의 관련성에 대한 기존 연구 결과들을 정리하고자 한다.
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Affiliation(s)
- Kyung Hoon Lee
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
| | - Koung Mi Kang
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
- Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
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31
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Ungvari Z, Toth P, Tarantini S, Prodan CI, Sorond F, Merkely B, Csiszar A. Hypertension-induced cognitive impairment: from pathophysiology to public health. Nat Rev Nephrol 2021; 17:639-654. [PMID: 34127835 PMCID: PMC8202227 DOI: 10.1038/s41581-021-00430-6] [Citation(s) in RCA: 169] [Impact Index Per Article: 56.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/21/2021] [Indexed: 02/06/2023]
Abstract
Hypertension affects two-thirds of people aged >60 years and significantly increases the risk of both vascular cognitive impairment and Alzheimer's disease. Hypertension compromises the structural and functional integrity of the cerebral microcirculation, promoting microvascular rarefaction, cerebromicrovascular endothelial dysfunction and neurovascular uncoupling, which impair cerebral blood supply. In addition, hypertension disrupts the blood-brain barrier, promoting neuroinflammation and exacerbation of amyloid pathologies. Ageing is characterized by multifaceted homeostatic dysfunction and impaired cellular stress resilience, which exacerbate the deleterious cerebromicrovascular effects of hypertension. Neuroradiological markers of hypertension-induced cerebral small vessel disease include white matter hyperintensities, lacunar infarcts and microhaemorrhages, all of which are associated with cognitive decline. Use of pharmaceutical and lifestyle interventions that reduce blood pressure, in combination with treatments that promote microvascular health, have the potential to prevent or delay the pathogenesis of vascular cognitive impairment and Alzheimer's disease in patients with hypertension.
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Affiliation(s)
- Zoltan Ungvari
- Vascular Cognitive Impairment and Neurodegeneration Program, Center for Geroscience and Healthy Brain Aging, Department of Biochemistry and Molecular Biology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- International Training Program in Geroscience, Doctoral School of Basic and Translational Medicine/Department of Public Health, Semmelweis University, Budapest, Hungary
- Department of Health Promotion Sciences, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Peter Toth
- Vascular Cognitive Impairment and Neurodegeneration Program, Center for Geroscience and Healthy Brain Aging, Department of Biochemistry and Molecular Biology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- International Training Program in Geroscience, Doctoral School of Basic and Translational Medicine/Department of Public Health, Semmelweis University, Budapest, Hungary
- Department of Neurosurgery, Medical School, University of Pecs, Pecs, Hungary
| | - Stefano Tarantini
- Vascular Cognitive Impairment and Neurodegeneration Program, Center for Geroscience and Healthy Brain Aging, Department of Biochemistry and Molecular Biology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- International Training Program in Geroscience, Doctoral School of Basic and Translational Medicine/Department of Public Health, Semmelweis University, Budapest, Hungary
- Department of Health Promotion Sciences, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Calin I Prodan
- Department of Neurology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Veterans Affairs Medical Center, Oklahoma City, OK, USA
| | - Farzaneh Sorond
- Department of Neurology, Division of Stroke and Neurocritical Care, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Bela Merkely
- Heart and Vascular Center, Semmelweis University, Budapest, Hungary
| | - Anna Csiszar
- Vascular Cognitive Impairment and Neurodegeneration Program, Center for Geroscience and Healthy Brain Aging, Department of Biochemistry and Molecular Biology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
- International Training Program in Geroscience, Doctoral School of Basic and Translational Medicine/Institute of Clinical Experimental Research, Semmelweis University, Budapest, Hungary.
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32
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Xia Y, Yassi N, Raniga P, Bourgeat P, Desmond P, Doecke J, Ames D, Laws SM, Fowler C, Rainey-Smith SR, Martins R, Maruff P, Villemagne VL, Masters CL, Rowe CC, Fripp J, Salvado O. Comorbidity of Cerebrovascular and Alzheimer's Disease in Aging. J Alzheimers Dis 2021; 78:321-334. [PMID: 32986666 DOI: 10.3233/jad-200419] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
BACKGROUND Cerebrovascular disease often coexists with Alzheimer's disease (AD). While both diseases share common risk factors, their interrelationship remains unclear. Increasing the understanding of how cerebrovascular changes interact with AD is essential to develop therapeutic strategies and refine biomarkers for early diagnosis. OBJECTIVE We investigate the prevalence and risk factors for the comorbidity of amyloid-β (Aβ) and cerebrovascular disease in the Australian Imaging, Biomarkers and Lifestyle Study of Ageing, and further examine their cross-sectional association. METHODS A total of 598 participants (422 cognitively normal, 89 with mild cognitive impairment, 87 with AD) underwent positron emission tomography and structural magnetic resonance imaging for assessment of Aβ deposition and cerebrovascular disease. Individuals were categorized based on the comorbidity status of Aβ and cerebrovascular disease (V) as Aβ-V-, Aβ-V+, Aβ+V-, or Aβ+V+. RESULTS Advancing age was associated with greater likelihood of cerebrovascular disease, high Aβ load and their comorbidity. Apolipoprotein E ɛ4 carriage was only associated with Aβ positivity. Greater total and regional WMH burden were observed in participants with AD. However, no association were observed between Aβ and WMH measures after stratification by clinical classification, suggesting that the observed association between AD and cerebrovascular disease was driven by the common risk factor of age. CONCLUSION Our observations demonstrate common comorbid condition of Aβ and cerebrovascular disease in later life. While our study did not demonstrate a convincing cross-sectional association between Aβ and WMH burden, future longitudinal studies are required to further confirm this.
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Affiliation(s)
- Ying Xia
- The Australian e-Health Research Centre, CSIRO Health and Biosecurity, Brisbane, QLD, Australia
| | - Nawaf Yassi
- Department of Medicine and Neurology, Melbourne Brain Centre at The Royal Melbourne Hospital, University of Melbourne, Parkville, VIC, Australia.,Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Australia.,The Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia
| | - Parnesh Raniga
- The Australian e-Health Research Centre, CSIRO Health and Biosecurity, Brisbane, QLD, Australia
| | - Pierrick Bourgeat
- The Australian e-Health Research Centre, CSIRO Health and Biosecurity, Brisbane, QLD, Australia
| | - Patricia Desmond
- Department of Radiology, The Royal Melbourne Hospital, University of Melbourne, Parkville, VIC, Australia
| | - James Doecke
- The Australian e-Health Research Centre, CSIRO Health and Biosecurity, Brisbane, QLD, Australia
| | - David Ames
- National Ageing Research Institute, Parkville, VIC, Australia.,Academic Unit for Psychiatry of Old Age, University of Melbourne, Parkville, VIC, Australia
| | - Simon M Laws
- Centre of Excellence for Alzheimer's Disease Research and Care, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia.,School of Pharmacy and Biomedical Sciences, Faculty of Health Sciences, Curtin Health Innovation Research Institute, Curtin University, Bentley, Western Australia, WA, Australia.,Sir James McCusker Alzheimer's Disease Research Unit, Hollywood Private Hospital, Perth, WA, Australia
| | - Christopher Fowler
- The Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia
| | - Stephanie R Rainey-Smith
- Centre of Excellence for Alzheimer's Disease Research and Care, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia.,Sir James McCusker Alzheimer's Disease Research Unit, Hollywood Private Hospital, Perth, WA, Australia
| | - Ralph Martins
- Centre of Excellence for Alzheimer's Disease Research and Care, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia.,Sir James McCusker Alzheimer's Disease Research Unit, Hollywood Private Hospital, Perth, WA, Australia
| | - Paul Maruff
- The Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia.,Cog State Ltd, Melbourne, VIC, Australia
| | - Victor L Villemagne
- The Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia.,Department of Nuclear Medicine and Centre for PET, Austin Health, Heidelberg, VIC, Australia.,Department of Medicine, Austin Health, University of Melbourne, Heidelberg, VIC, Australia
| | - Colin L Masters
- The Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia
| | - Christopher C Rowe
- Department of Nuclear Medicine and Centre for PET, Austin Health, Heidelberg, VIC, Australia.,Department of Medicine, Austin Health, University of Melbourne, Heidelberg, VIC, Australia
| | - Jurgen Fripp
- The Australian e-Health Research Centre, CSIRO Health and Biosecurity, Brisbane, QLD, Australia
| | - Olivier Salvado
- The Australian e-Health Research Centre, CSIRO Health and Biosecurity, Brisbane, QLD, Australia.,CSIRO Data61, Brisbane, QLD, Australia
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33
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Wong FCC, Saffari SE, Yatawara C, Ng KP, Kandiah N. Influence of White Matter Hyperintensities on Baseline and Longitudinal Amyloid-β in Cognitively Normal Individuals. J Alzheimers Dis 2021; 84:91-101. [PMID: 34511497 DOI: 10.3233/jad-210333] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND The associations between small vessel disease (SVD) and cerebrospinal amyloid-β1-42 (Aβ1-42) pathology have not been well-elucidated. OBJECTIVE Baseline (BL) white matter hyperintensities (WMH) were examined for associations with month-24 (M24) and longitudinal Aβ1-42 change in cognitively normal (CN) subjects. The interaction of WMH and Aβ1-42 on memory and executive function were also examined. METHODS This study included 72 subjects from the Alzheimer's Disease Neuroimaging Initiative. Multivariable linear regression models evaluated associations between baseline WMH/intracranial volume ratio, M24 and change in Aβ1-42 over two years. Linear mixed effects models evaluated interactions between BL WMH/ICV and Aβ1-42 on memory and executive function. RESULTS Mean age of the subjects (Nmales = 36) = 73.80 years, SD = 6.73; mean education years = 17.1, SD = 2.4. BL WMH was significantly associated with M24 Aβ1-42 (p = 0.008) and two-year change in Aβ1-42 (p = 0.006). Interaction between higher WMH and lower Aβ1-42 at baseline was significantly associated with worse memory at baseline and M24 (p = 0.003). CONCLUSION BL WMH was associated with M24 and longitudinal Aβ1-42 change in CN. The interaction between higher WMH and lower Aβ1-42 was associated with poorer memory. Since SVD is associated with longitudinal Aβ1-42 pathology, and the interaction of both factors is linked to poorer cognitive outcomes, the mitigation of SVD may be correlated with reduced amyloid pathology and milder cognitive deterioration in Alzheimer's disease.
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Affiliation(s)
| | - Seyed Ehsan Saffari
- Department of Neurology, National Neuroscience Institute, Singapore, Singapore.,Centre for Quantitative Medicine, Duke-NUS Medical School, National University of Singapore, Singapore, Singapore
| | - Chathuri Yatawara
- Department of Neurology, National Neuroscience Institute, Singapore, Singapore
| | - Kok Pin Ng
- Department of Neurology, National Neuroscience Institute, Singapore, Singapore.,Duke-NUS Medical School, Singapore, Singapore.,Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Nagaendran Kandiah
- Department of Neurology, National Neuroscience Institute, Singapore, Singapore.,Duke-NUS Medical School, Singapore, Singapore.,Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
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34
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Lagarde J, Olivieri P, Bottlaender M, Sarazin M. Diagnosi clinicolaboratoristica della malattia di Alzheimer. Neurologia 2021. [DOI: 10.1016/s1634-7072(21)45320-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
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35
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Garnier-Crussard A, Bougacha S, Wirth M, Dautricourt S, Sherif S, Landeau B, Gonneaud J, De Flores R, de la Sayette V, Vivien D, Krolak-Salmon P, Chételat G. White matter hyperintensity topography in Alzheimer's disease and links to cognition. Alzheimers Dement 2021; 18:422-433. [PMID: 34322985 PMCID: PMC9292254 DOI: 10.1002/alz.12410] [Citation(s) in RCA: 56] [Impact Index Per Article: 18.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 06/09/2021] [Accepted: 06/09/2021] [Indexed: 01/18/2023]
Abstract
Introduction White matter hyperintensities (WMH) are often described in Alzheimer's disease (AD), but their topography and specific relationships with cognition remain unclear. Methods Regional WMH were estimated in 54 cognitively impaired amyloid beta–positive AD (Aβpos‐AD), compared to 40 cognitively unimpaired amyloid beta–negative older controls (Aβneg‐controls) matched for vascular risk factors. The cross‐sectional association between regional WMH volume and cognition was assessed within each group, controlling for cerebral amyloid burden, global cortical atrophy, and hippocampal atrophy. Results WMH volume was larger in Aβpos‐AD compared to Aβneg‐controls in all regions, with the greatest changes in the splenium of the corpus callosum (S‐CC). In Aβpos‐AD patients, larger total and regional WMH volume, especially in the S‐CC, was strongly associated with decreased cognition. Discussion WMH specifically contribute to lower cognition in AD, independently from amyloid deposition and atrophy. This study emphasizes the clinical relevance of WMH in AD, especially posterior WMH, and most notably S‐CC WMH.
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Affiliation(s)
- Antoine Garnier-Crussard
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders,", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France.,Clinical and Research Memory Center of Lyon, Lyon Institute For Elderly, Hospices Civils de Lyon, Lyon, France.,University of Lyon, Lyon, France
| | - Salma Bougacha
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders,", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - Miranka Wirth
- German Center for Neurodegenerative Diseases (DZNE), Dresden, Germany
| | - Sophie Dautricourt
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders,", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France.,Department of Neurology, CHU de Caen, Caen, France
| | - Siya Sherif
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders,", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - Brigitte Landeau
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders,", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - Julie Gonneaud
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders,", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - Robin De Flores
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders,", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - Vincent de la Sayette
- Department of Neurology, CHU de Caen, Caen, France.,Normandie Univ, UNICAEN, PSL Université, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, NIMH, Caen, France
| | - Denis Vivien
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders,", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France.,Department of Clinical Research, CHU de Caen, Caen, France
| | - Pierre Krolak-Salmon
- Clinical and Research Memory Center of Lyon, Lyon Institute For Elderly, Hospices Civils de Lyon, Lyon, France.,University of Lyon, Lyon, France.,Neuroscience Research Centre of Lyon, INSERM 1048, CNRS 5292, Lyon, France
| | - Gaël Chételat
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders,", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
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36
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Chen Y, Wang X, Guan L, Wang Y. Role of White Matter Hyperintensities and Related Risk Factors in Vascular Cognitive Impairment: A Review. Biomolecules 2021; 11:biom11081102. [PMID: 34439769 PMCID: PMC8391787 DOI: 10.3390/biom11081102] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Revised: 07/24/2021] [Accepted: 07/25/2021] [Indexed: 02/06/2023] Open
Abstract
White matter hyperintensities (WMHs) of presumed vascular origin are one of the imaging markers of cerebral small-vessel disease, which is prevalent in older individuals and closely associated with the occurrence and development of cognitive impairment. The heterogeneous nature of the imaging manifestations of WMHs creates difficulties for early detection and diagnosis of vascular cognitive impairment (VCI) associated with WMHs. Because the underlying pathological processes and biomarkers of WMHs and their development in cognitive impairment remain uncertain, progress in prevention and treatment is lagging. For this reason, this paper reviews the status of research on the features of WMHs related to VCI, as well as mediators associated with both WMHs and VCI, and summarizes potential treatment strategies for the prevention and intervention in WMHs associated with VCI.
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Affiliation(s)
- Yiyi Chen
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China; (Y.C.); (X.W.)
- China National Clinical Research Center for Neurological Diseases, Beijing 100070, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing 100070, China
- Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing 100070, China
| | - Xing Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China; (Y.C.); (X.W.)
- China National Clinical Research Center for Neurological Diseases, Beijing 100070, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing 100070, China
- Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing 100070, China
- Department of Neurology, Chongqing University Central Hospital, Chongqing Emergency Medical Center, Chongqing 400000, China
| | - Ling Guan
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China; (Y.C.); (X.W.)
- China National Clinical Research Center for Neurological Diseases, Beijing 100070, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing 100070, China
- Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing 100070, China
- Correspondence: (L.G.); (Y.W.)
| | - Yilong Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China; (Y.C.); (X.W.)
- China National Clinical Research Center for Neurological Diseases, Beijing 100070, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing 100070, China
- Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing 100070, China
- Correspondence: (L.G.); (Y.W.)
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37
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Caprihan A, Raja R, Hillmer LJ, Erhardt EB, Prestopnik J, Thompson J, Adair JC, Knoefel JE, Rosenberg GA. A double-dichotomy clustering of dual pathology dementia patients. CEREBRAL CIRCULATION - COGNITION AND BEHAVIOR 2021; 2:100011. [PMID: 34746872 PMCID: PMC8570532 DOI: 10.1016/j.cccb.2021.100011] [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: 01/16/2021] [Revised: 03/22/2021] [Accepted: 03/27/2021] [Indexed: 12/02/2022]
Abstract
INTRODUCTION Subcortical ischemic vascular disease (SIVD) and Alzheimer's disease (AD) related dementia can coexist in older subjects, leading to mixed dementia (MX). Identification of dementia sub-groups is important for designing proper treatment plans and clinical trials. METHOD An Alzheimer's disease severity (ADS) score and a vascular disease severity (VDS) score are calculated from CSF and MRI biomarkers, respectively. These scores, being sensitive to different Alzheimer's and vascular disease processes are combined orthogonally in a double-dichotomy plot. This formed an objective basis for clustering the subjects into four groups, consisting of AD, SIVD, MX and leukoaraiosis (LA). The relationship of these four groups is examined with respect to cognitive assessments and clinical diagnosis. RESULTS Cluster analysis had at least 83% agreement with the clinical diagnosis for groups based either on Alzheimer's or on vascular sensitive biomarkers, and a combined agreement of 68.8% for clustering the four groups. The VDS score was correlated to executive function (r = -0.28, p < 0.01) and the ADS score to memory function (r = -0.35, p < 0.002) after adjusting for age, sex, and education. In the subset of patients for which the cluster scores and clinical diagnoses agreed, the correlations were stronger (VDS score-executive function: r = -0.37, p < 0.006 and ADS score-memory function: r = -0.58, p < 0.0001). CONCLUSIONS The double-dichotomy clustering based on imaging and fluid biomarkers offers an unbiased method for identifying mixed dementia patients and selecting better defined sub-groups. Differential correlations with neuropsychological tests support the hypothesis that the categories of dementia represent different etiologies.
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Affiliation(s)
| | - Rajikha Raja
- The Mind Research Network, Albuquerque, NM, United States
- Department of Radiology, University of Arkansas for Medical Sciences, Little Rock, AR, United States
| | - Laura J. Hillmer
- Department of Neurology, University of New Mexico, Albuquerque, NM, United States
| | - Erik Barry Erhardt
- Departments of Mathematics and Statistics, University of New Mexico, Albuquerque, NM, United States
| | - Jill Prestopnik
- Department of Neurology, University of New Mexico, Albuquerque, NM, United States
| | - Jeffrey Thompson
- Department of Neurology, University of New Mexico, Albuquerque, NM, United States
| | - John C Adair
- Department of Neurology, University of New Mexico, Albuquerque, NM, United States
| | - Janice E. Knoefel
- Department of Neurology, University of New Mexico, Albuquerque, NM, United States
| | - Gary A. Rosenberg
- Department of Neurology, University of New Mexico, Albuquerque, NM, United States
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38
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Gaubert M, Lange C, Garnier-Crussard A, Köbe T, Bougacha S, Gonneaud J, de Flores R, Tomadesso C, Mézenge F, Landeau B, de la Sayette V, Chételat G, Wirth M. Topographic patterns of white matter hyperintensities are associated with multimodal neuroimaging biomarkers of Alzheimer's disease. ALZHEIMERS RESEARCH & THERAPY 2021; 13:29. [PMID: 33461618 PMCID: PMC7814451 DOI: 10.1186/s13195-020-00759-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Accepted: 12/23/2020] [Indexed: 12/26/2022]
Abstract
Background White matter hyperintensities (WMH) are frequently found in Alzheimer’s disease (AD). Commonly considered as a marker of cerebrovascular disease, regional WMH may be related to pathological hallmarks of AD, including beta-amyloid (Aβ) plaques and neurodegeneration. The aim of this study was to examine the regional distribution of WMH associated with Aβ burden, glucose hypometabolism, and gray matter volume reduction. Methods In a total of 155 participants (IMAP+ cohort) across the cognitive continuum from normal cognition to AD dementia, FLAIR MRI, AV45-PET, FDG-PET, and T1 MRI were acquired. WMH were automatically segmented from FLAIR images. Mean levels of neocortical Aβ deposition (AV45-PET), temporo-parietal glucose metabolism (FDG-PET), and medial-temporal gray matter volume (GMV) were extracted from processed images using established AD meta-signature templates. Associations between AD brain biomarkers and WMH, as assessed in region-of-interest and voxel-wise, were examined, adjusting for age, sex, education, and systolic blood pressure. Results There were no significant associations between global Aβ burden and region-specific WMH. Voxel-wise WMH in the splenium of the corpus callosum correlated with greater Aβ deposition at a more liberal threshold. Region- and voxel-based WMH in the posterior corpus callosum, along with parietal, occipital, and frontal areas, were associated with lower temporo-parietal glucose metabolism. Similarly, lower medial-temporal GMV correlated with WMH in the posterior corpus callosum in addition to parietal, occipital, and fontal areas. Conclusions This study demonstrates that local white matter damage is correlated with multimodal brain biomarkers of AD. Our results highlight modality-specific topographic patterns of WMH, which converged in the posterior white matter. Overall, these cross-sectional findings corroborate associations of regional WMH with AD-typical Aß deposition and neurodegeneration.
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Affiliation(s)
- Malo Gaubert
- German Center for Neurodegenerative Diseases, Dresden, Germany.,Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, LMU University Hospital Munich, Ludwig-Maximilians-Universität, Munich, Germany
| | - Catharina Lange
- German Center for Neurodegenerative Diseases, Dresden, Germany. .,Department of Nuclear Medicine, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany.
| | - Antoine Garnier-Crussard
- Inserm UMR-S U1237, Caen-Normandie University, GIP Cyceron, Caen, France.,Clinical and Research Memory Center of Lyon, Lyon Institute for Elderly, Hospices Civils de Lyon, Lyon, France
| | - Theresa Köbe
- German Center for Neurodegenerative Diseases, Dresden, Germany
| | - Salma Bougacha
- Inserm UMR-S U1237, Caen-Normandie University, GIP Cyceron, Caen, France
| | - Julie Gonneaud
- Inserm UMR-S U1237, Caen-Normandie University, GIP Cyceron, Caen, France
| | - Robin de Flores
- Inserm UMR-S U1237, Caen-Normandie University, GIP Cyceron, Caen, France
| | - Clémence Tomadesso
- Inserm UMR-S U1237, Caen-Normandie University, GIP Cyceron, Caen, France
| | - Florence Mézenge
- Inserm UMR-S U1237, Caen-Normandie University, GIP Cyceron, Caen, France
| | - Brigitte Landeau
- Inserm UMR-S U1237, Caen-Normandie University, GIP Cyceron, Caen, France
| | - Vincent de la Sayette
- Normandy University, UNICAEN, PSL Research University, EPHE, INSERM, U1077, CHU of Caen, Neuropsychology and Imaging of Human Memory, Caen, France
| | - Gaël Chételat
- Department of Nuclear Medicine, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany.
| | - Miranka Wirth
- German Center for Neurodegenerative Diseases, Dresden, Germany.
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Raghavan S, Przybelski SA, Reid RI, Graff-Radford J, Lesnick TG, Zuk SM, Knopman DS, Machulda MM, Mielke MM, Petersen RC, Jack CR, Vemuri P. Reduced fractional anisotropy of the genu of the corpus callosum as a cerebrovascular disease marker and predictor of longitudinal cognition in MCI. Neurobiol Aging 2020; 96:176-183. [PMID: 33022474 PMCID: PMC7722208 DOI: 10.1016/j.neurobiolaging.2020.09.005] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Revised: 08/25/2020] [Accepted: 09/01/2020] [Indexed: 12/29/2022]
Abstract
Our goal was to evaluate the utility of diffusion tensor imaging (DTI) for predicting future cognitive decline in mild cognitive impairment (MCI) in conjunction with Alzheimer's disease (AD) biomarkers (amyloid positron emission tomography and AD signature neurodegeneration) in 132 MCI individuals ≥60 year old with structural magnetic resonance imaging, DTI, amyloid positron emission tomography, and at least one clinical follow-up. We used mixed-effect models to evaluate the prognostic ability of fractional anisotropy of the genu of the corpus callosum (FA-Genu), as a cerebrovascular disease marker, for predicting cognitive decline along with AD biomarkers. We contrasted the value of white matter hyperintensities, a traditional cerebrovascular disease marker as well as FA in the hippocampal cingulum bundle with the FA-Genu models. FA-Genu significantly predicted cognitive decline even after accounting for AD biomarkers. WMH was not associated with cognitive decline in the model with both WMH and FA-Genu. DTI specifically FA-Genu provides unique complementary information to AD biomarkers and has significant utility for prediction of cognitive decline in MCI.
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Affiliation(s)
| | | | - Robert I Reid
- Information Technology, Mayo Clinic, Rochester, MN, USA
| | | | | | - Samantha M Zuk
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | | | | | - Michelle M Mielke
- Health Sciences Research, Mayo Clinic, Rochester, MN, USA; Department of Neurology, Mayo Clinic, Rochester, MN, USA
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40
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Salvadores N, Gerónimo-Olvera C, Court FA. Axonal Degeneration in AD: The Contribution of Aβ and Tau. Front Aging Neurosci 2020; 12:581767. [PMID: 33192476 PMCID: PMC7593241 DOI: 10.3389/fnagi.2020.581767] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Accepted: 09/09/2020] [Indexed: 12/25/2022] Open
Abstract
Alzheimer's disease (AD) represents the most common age-related neurodegenerative disorder, affecting around 35 million people worldwide. Despite enormous efforts dedicated to AD research over decades, there is still no cure for the disease. Misfolding and accumulation of Aβ and tau proteins in the brain constitute a defining signature of AD neuropathology, and mounting evidence has documented a link between aggregation of these proteins and neuronal dysfunction. In this context, progressive axonal degeneration has been associated with early stages of AD and linked to Aβ and tau accumulation. As the axonal degeneration mechanism has been starting to be unveiled, it constitutes a promising target for neuroprotection in AD. A comprehensive understanding of the mechanism of axonal destruction in neurodegenerative conditions is therefore critical for the development of new therapies aimed to prevent axonal loss before irreversible neuronal death occurs in AD. Here, we review current evidence of the involvement of Aβ and tau pathologies in the activation of signaling cascades that can promote axonal demise.
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Affiliation(s)
- Natalia Salvadores
- Center for Integrative Biology, Faculty of Sciences, Universidad Mayor, Santiago, Chile.,Fondap Geroscience Center for Brain Health and Metabolism, Santiago, Chile
| | - Cristian Gerónimo-Olvera
- Center for Integrative Biology, Faculty of Sciences, Universidad Mayor, Santiago, Chile.,Fondap Geroscience Center for Brain Health and Metabolism, Santiago, Chile
| | - Felipe A Court
- Center for Integrative Biology, Faculty of Sciences, Universidad Mayor, Santiago, Chile.,Fondap Geroscience Center for Brain Health and Metabolism, Santiago, Chile.,Buck Institute for Research on Aging, Novato, CA, United States
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41
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Kim HW, Hong J, Jeon JC. Cerebral Small Vessel Disease and Alzheimer's Disease: A Review. Front Neurol 2020; 11:927. [PMID: 32982937 PMCID: PMC7477392 DOI: 10.3389/fneur.2020.00927] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Accepted: 07/17/2020] [Indexed: 12/12/2022] Open
Abstract
Alzheimer's disease (AD) is the most common cause of dementia. Despite this, clear pathophysiology for AD has not been confirmed, and effective treatments are still not available. As AD results in a complex disease process for cognitive decline, various theories have been suggested as the cause of AD. Recently, cerebral small vessel disease (SVD) has been suggested to contribute to the pathogenesis of AD, as well as contributing to vascular dementia. Cerebral SVD refers to a varied group of diseases that affect cerebral small arteries and microvessels. These can be seen as white matter hyperintensities, cerebral microbleeds, and lacunes on magnetic resonance imaging. Data from epidemiological and clinical-pathological studies have found evidence of the relationship between cerebral SVD and AD. This review aims to discuss the complex relationship between cerebral SVD and AD. Recent reports that evaluate the association between these diseases will be reviewed.
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Affiliation(s)
- Hae Won Kim
- Department of Nuclear Medicine, Keimyung University Dongsan Medical Center, Daegu, South Korea
| | - Jeongho Hong
- Department of Neurology, Keimyung University Dongsan Medical Center, Daegu, South Korea
| | - Jae Cheon Jeon
- Institute for Medical Science, Keimyung University School of Medicine, Daegu, South Korea
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