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Sun Y, Xia W, Wei R, Dai Z, Sun X, Zhu J, Song B, Wang H. Quantitative Analysis of White Matter Hyperintensities as a Predictor of 1-Year Risk for Ischemic Stroke Recurrence. Neurol Ther 2024; 13:1467-1482. [PMID: 39136813 PMCID: PMC11393268 DOI: 10.1007/s40120-024-00652-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2024] [Accepted: 07/25/2024] [Indexed: 09/14/2024] Open
Abstract
INTRODUCTION This study evaluates the role of quantitative characteristics of white matter hyperintensities (WMHs) in predicting the 1-year recurrence risk of ischemic stroke. METHODS We conducted a retrospective analysis of 1061 patients with ischemic stroke from January 2018 to April 2021. WMHs were automatically segmented using a cluster-based method to quantify their volume and number of clusters (NoC). Additionally, two radiologists independently rated periventricular and deep WMHs using the Fazekas scale. The cohort was divided into a training set (70%) and a testing set (30%). We employed Cox proportional hazards models to develop predictors based on quantitative WMH characteristics, Fazekas scores, and clinical factors, and compared their performance using the concordance index (C-index). RESULTS A total of 180 quantitative variables related to WMHs were extracted. A higher NoC in deep white matter and brainstem, advanced age (> 90 years old), specific stroke subtypes, and absence of discharge antiplatelets showed stronger associations with the risk of ischemic stroke recurrence within 1 year. The nomogram incorporating quantitative WMHs data showed superior discrimination compared to those based on the Fazekas scale or clinical factors alone, with C-index values of 0.709 versus 0.647 and 0.648, respectively, in the testing set. Notably, a combined model including both WMHs and clinical factors achieved the highest predictive accuracy, with a C-index of 0.735 in the testing set. CONCLUSION Quantitative assessment of WMHs provides a valuable neuro-imaging tool for enhancing the prediction of ischemic stroke recurrence risk.
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Affiliation(s)
- Yi Sun
- Department of Radiology, Minhang Hospital, Fudan University, 170 Xinsong Road, Shanghai, 201199, People's Republic of China
| | - Wenping Xia
- Department of Radiology, Ningbo Yinzhou No. 2 Hospital, Ningbo, China
| | - Ran Wei
- Department of Radiology, Minhang Hospital, Fudan University, 170 Xinsong Road, Shanghai, 201199, People's Republic of China
| | - Zedong Dai
- Department of Radiology, Minhang Hospital, Fudan University, 170 Xinsong Road, Shanghai, 201199, People's Republic of China
| | - Xilin Sun
- Department of Radiology, Minhang Hospital, Fudan University, 170 Xinsong Road, Shanghai, 201199, People's Republic of China
| | - Jie Zhu
- Department of Radiology, Minhang Hospital, Fudan University, 170 Xinsong Road, Shanghai, 201199, People's Republic of China
| | - Bin Song
- Department of Radiology, Minhang Hospital, Fudan University, 170 Xinsong Road, Shanghai, 201199, People's Republic of China.
| | - Hao Wang
- Department of Radiology, Minhang Hospital, Fudan University, 170 Xinsong Road, Shanghai, 201199, People's Republic of China.
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Lu J, Wang J, Wu J, Zhang H, Ma X, Zhu Y, Wang J, Yang Y, Xiao Z, Li M, Zhou X, Ju Z, Xu Q, Ge J, Ding D, Yen TC, Zuo C, Guan Y, Zhao Q. Pilot implementation of the revised criteria for staging of Alzheimer's disease by the Alzheimer's Association Workgroup in a tertiary memory clinic. Alzheimers Dement 2024. [PMID: 39287564 DOI: 10.1002/alz.14245] [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: 06/07/2024] [Revised: 08/15/2024] [Accepted: 08/15/2024] [Indexed: 09/19/2024]
Abstract
INTRODUCTION We aimed to evaluate the feasibility of the 2024 Alzheimer's Association Workgroup's integrated clinical-biological staging scheme in outpatient settings within a tertiary memory clinic. METHODS The 2018 syndromal cognitive staging system, coupled with a binary biomarker classification, was implemented for 236 outpatients with cognitive concerns. The 2024 numeric clinical staging framework, incorporating biomarker staging, was specifically applied to 154 individuals within the Alzheimer's disease (AD) continuum. RESULTS The 2024 staging scheme accurately classified 95.5% AD. Among these, 56.5% exhibited concordant clinical and biological stages (canonical), 34.7% demonstrated more advanced clinical stages than biologically expected (susceptible), and 8.8% displayed the inverse pattern (resilient). The susceptible group was characterized by a higher burden of neurodegeneration and inflammation than anticipated from tau, whereas the resilient group showed the opposite. DISCUSSION The 2024 staging scheme is generally feasible. A discrepancy between clinical and biological stages is relatively frequent among symptomatic patients with AD. HIGHLIGHTS The 2024 AA staging scheme is generally feasible in a tertiary memory clinic. A discrepancy between clinical and biological stages is relatively frequent in AD. The mismatch may be influenced by a non-specific pathological process involved in AD. Individual profiles like aging and lifestyles may contribute to such a mismatch. Matched and mismatched cases converge toward similar clinical outcomes.
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Affiliation(s)
- Jiaying Lu
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Xuhui District, Shanghai, China
| | - Jing Wang
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Xuhui District, Shanghai, China
| | - Jie Wu
- Department and Institute of Neurology, Huashan Hospital, Fudan University, Jingan District, Shanghai, China
| | - Huiwei Zhang
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Xuhui District, Shanghai, China
| | - Xiaoxi Ma
- Department and Institute of Neurology, Huashan Hospital, Fudan University, Jingan District, Shanghai, China
| | - Yuhua Zhu
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Xuhui District, Shanghai, China
| | - Jie Wang
- Department and Institute of Neurology, Huashan Hospital, Fudan University, Jingan District, Shanghai, China
| | - Yunhao Yang
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Xuhui District, Shanghai, China
| | - Zhenxu Xiao
- Department and Institute of Neurology, Huashan Hospital, Fudan University, Jingan District, Shanghai, China
| | - Ming Li
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Xuhui District, Shanghai, China
| | - Xiaowen Zhou
- Department and Institute of Neurology, Huashan Hospital, Fudan University, Jingan District, Shanghai, China
| | - Zizhao Ju
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Xuhui District, Shanghai, China
| | - Qian Xu
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Xuhui District, Shanghai, China
| | - Jingjie Ge
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Xuhui District, Shanghai, China
| | - Ding Ding
- Department and Institute of Neurology, Huashan Hospital, Fudan University, Jingan District, Shanghai, China
- National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Jingan District, Shanghai, China
- National Center for Neurological Disorders, Huashan Hospital, Fudan University, Jingan District, Shanghai, China
| | - Tzu-Chen Yen
- APRINOIA Therapeutics Co. Ltd, Suzhou Industrial Park, Suzhou, China
| | - Chuantao Zuo
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Xuhui District, Shanghai, China
- National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Jingan District, Shanghai, China
- National Center for Neurological Disorders, Huashan Hospital, Fudan University, Jingan District, Shanghai, China
- Human Phenome Institute, Fudan University, Pudong District, Shanghai, China
| | - Yihui Guan
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Xuhui District, Shanghai, China
- National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Jingan District, Shanghai, China
- National Center for Neurological Disorders, Huashan Hospital, Fudan University, Jingan District, Shanghai, China
| | - Qianhua Zhao
- Department and Institute of Neurology, Huashan Hospital, Fudan University, Jingan District, Shanghai, China
- National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Jingan District, Shanghai, China
- National Center for Neurological Disorders, Huashan Hospital, Fudan University, Jingan District, Shanghai, China
- MOE Frontiers Center for Brain Science, Fudan University, Xuhui District, Shanghai, China
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Li TR, Li BL, Xu XR, Zhong J, Wang TS, Liu FQ. Association of white matter hyperintensities with cognitive decline and neurodegeneration. Front Aging Neurosci 2024; 16:1412735. [PMID: 39328245 PMCID: PMC11425965 DOI: 10.3389/fnagi.2024.1412735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2024] [Accepted: 08/28/2024] [Indexed: 09/28/2024] Open
Abstract
Background The relationship between white matter hyperintensities (WMH) and the core features of Alzheimer's disease (AD) remains controversial. Further, due to the prevalence of co-pathologies, the precise role of WMH in cognition and neurodegeneration also remains uncertain. Methods Herein, we analyzed 1803 participants with available WMH volume data, extracted from the ADNI database, including 756 cognitively normal controls, 783 patients with mild cognitive impairment (MCI), and 264 patients with dementia. Participants were grouped according to cerebrospinal fluid (CSF) pathology (A/T profile) severity. Linear regression analysis was applied to evaluate the factors associated with WMH volume. Modeled by linear mixed-effects, the increase rates (Δ) of the WMH volume, cognition, and typical neurodegenerative markers were assessed. The predictive effectiveness of WMH volume was subsequently tested using Cox regression analysis, and the relationship between WMH/ΔWMH and other indicators such as cognition was explored through linear regression analyses. Furthermore, we explored the interrelationship among amyloid-β deposition, cognition, and WMH using mediation analysis. Results Higher WMH volume was associated with older age, lower CSF amyloid-β levels, hypertension, and smoking history (all p ≤ 0.001), as well as cognitive status (MCI, p < 0.001; dementia, p = 0.008), but not with CSF tau levels. These results were further verified in any clinical stage, except hypertension and smoking history in the dementia stage. Although WMH could not predict dementia conversion, its increased levels at baseline were associated with a worse cognitive performance and a more rapid memory decline. Longitudinal analyses showed that baseline dementia and positive amyloid-β status were associated with a greater accrual of WMH volume, and a higher ΔWMH was also correlated with a faster cognitive decline. In contrast, except entorhinal cortex thickness, the WMH volume was not found to be associated with any other neurodegenerative markers. To a lesser extent, WMH mediates the relationship between amyloid-β and cognition. Conclusion WMH are non-specific lesions that are associated with amyloid-β deposition, cognitive status, and a variety of vascular risk factors. Despite evidence indicating only a weak relationship with neurodegeneration, early intervention to reduce WMH lesions remains a high priority for preserving cognitive function in the elderly.
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Affiliation(s)
- Tao-Ran Li
- Department of Neurology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, China
| | - Bai-Le Li
- Department of Hematology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, China
- Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Xin-Ran Xu
- Department of Neurology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, China
| | - Jin Zhong
- Department of Neurology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, China
| | - Tai-Shan Wang
- Department of Neurology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, China
- Department of Neurology, Yangzhou Friendship Hospital, Yangzhou, China
| | - Feng-Qi Liu
- Department of Neurology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, China
- Department of Hematology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, China
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Gebre RK, Graff-Radford J, Ramanan VK, Raghavan S, Hofrenning EI, Przybelski SA, Nguyen AT, Lesnick TG, Gunter JL, Algeciras-Schimnich A, Knopman DS, Machulda MM, Vassilaki M, Lowe VJ, Jack CR, Petersen RC, Vemuri P. Can integration of Alzheimer's plasma biomarkers with MRI, cardiovascular, genetics, and lifestyle measures improve cognition prediction? Brain Commun 2024; 6:fcae300. [PMID: 39291164 PMCID: PMC11406552 DOI: 10.1093/braincomms/fcae300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 07/13/2024] [Accepted: 09/03/2024] [Indexed: 09/19/2024] Open
Abstract
There is increasing interest in Alzheimer's disease related plasma biomarkers due to their accessibility and scalability. We hypothesized that integrating plasma biomarkers with other commonly used and available participant data (MRI, cardiovascular factors, lifestyle, genetics) using machine learning (ML) models can improve individual prediction of cognitive outcomes. Further, our goal was to evaluate the heterogeneity of these predictors across different age strata. This longitudinal study included 1185 participants from the Mayo Clinic Study of Aging who had complete plasma analyte work-up at baseline. We used the Quanterix Simoa immunoassay to measure neurofilament light, Aβ1-42 and Aβ1-40 (used as Aβ42/Aβ40 ratio), glial fibrillary acidic protein, and phosphorylated tau 181 (p-tau181). Participants' brain health was evaluated through gray and white matter structural MRIs. The study also considered cardiovascular factors (hyperlipidemia, hypertension, stroke, diabetes, chronic kidney disease), lifestyle factors (area deprivation index, body mass index, cognitive and physical activities), and genetic factors (APOE, single nucleotide polymorphisms, and polygenic risk scores). An ML model was developed to predict cognitive outcomes at baseline and decline (slope). Three models were created: a base model with groups of risk factors as predictors, an enhanced model included socio-demographics, and a final enhanced model by incorporating plasma and socio-demographics into the base models. Models were explained for three age strata: younger than 65 years, 65-80 years, and older than 80 years, and further divided based on amyloid positivity status. Regardless of amyloid status the plasma biomarkers showed comparable performance (R² = 0.15) to MRI (R² = 0.18) and cardiovascular measures (R² = 0.10) when predicting cognitive decline. Inclusion of cardiovascular or MRI measures with plasma in the presence of socio-demographic improved cognitive decline prediction (R² = 0.26 and 0.27). For amyloid positive individuals Aβ42/Aβ40, glial fibrillary acidic protein and p-tau181 were the top predictors of cognitive decline while Aβ42/Aβ40 was prominent for amyloid negative participants across all age groups. Socio-demographics explained a large portion of the variance in the amyloid negative individuals while the plasma biomarkers predominantly explained the variance in amyloid positive individuals (21% to 37% from the younger to the older age group). Plasma biomarkers performed similarly to MRI and cardiovascular measures when predicting cognitive outcomes and combining them with either measure resulted in better performance. Top predictors were heterogeneous between cross-sectional and longitudinal cognition models, across age groups, and amyloid status. Multimodal approaches will enhance the usefulness of plasma biomarkers through careful considerations of a study population's socio-demographics, brain and cardiovascular health.
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Affiliation(s)
- Robel K Gebre
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Vijay K Ramanan
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | | | | | - Scott A Przybelski
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | - Aivi T Nguyen
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA
| | - Timothy G Lesnick
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | | | | | - David S Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Mary M Machulda
- Department of Psychology, Mayo Clinic, Rochester, MN 55905, USA
| | - Maria Vassilaki
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
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de Havenon A, Gottesman RF, Willamson JD, Rost N, Sharma R, Li V, Littig L, Stulberg E, Falcone GJ, Prabhakaran S, Schneider ALC, Sheth KN, Pajewski NM, Brickman AM. White matter hyperintensity on MRI and plasma Aβ42/40 ratio additively increase the risk of cognitive impairment in hypertensive adults. Alzheimers Dement 2024. [PMID: 39229896 DOI: 10.1002/alz.14126] [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: 04/11/2024] [Revised: 06/04/2024] [Accepted: 06/18/2024] [Indexed: 09/05/2024]
Abstract
INTRODUCTION Dementia often involves comorbid Alzheimer's and vascular pathology, but their combined impact warrants additional study. METHODS We analyzed the Systolic Blood Pressure Intervention Trial and categorized white matter hyperintensity (WMH) volume into highest versus lowest/mid tertile and the amyloid beta (Aβ)42/40 ratio into lowest versus mid/highest ratio tertile. Using these binary variables, we created four exposure categories: (1) combined low risk, (2) Aβ risk, (3) WMH risk, and (4) combined high risk. RESULTS In the cohort of 467 participants (mean age 69.7 ± 7.1, 41.8% female, 31.9% nonwhite or Hispanic) during 4.8 years of follow-up and across the four exposure categories the rates of cognitive impairment were 5.3%, 7.8%, 11.8%, and 22.6%. Compared to the combined low-risk category, the adjusted hazard ratio for cognitive impairment was 4.12 (95% confidence interval, 1.71 to 9.94) in the combined high-risk category. DISCUSSION This study emphasizes the potential impact of therapeutic approaches to dementia prevention that target both vascular and amyloid pathology. HIGHLIGHTS White matter hyperintensity (WMH) and plasma amyloid (Aβ42/40) are additive risk factors for the development of cognitive impairment in the SPRINT MIND trial. Individuals in the high-risk categories of both WMH and Aβ42/40 had a near fivefold increase in risk of cognitive impairment during 4.8 years of follow-up on average. These findings suggest that treatment strategies targeting both vascular health and amyloid burden warrant further research.
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Affiliation(s)
- Adam de Havenon
- Department of Neurology, Center for Brain and Mind Health, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Rebecca F Gottesman
- National Institute of Neurological Disorders and Stroke, Bethesda, Maryland, USA
| | - Jeff D Willamson
- Department of Internal Medicine, Wake Forrest University School of Medicine, Winston-Salem, North Carolina, USA
| | - Natalia Rost
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Richa Sharma
- Department of Neurology, Center for Brain and Mind Health, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Vivian Li
- Department of Neurology, Center for Brain and Mind Health, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Lauren Littig
- Department of Neurology, Center for Brain and Mind Health, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Eric Stulberg
- Department of Neurology, University of Utah, Salt Lake City, Utah, USA
| | - Guido J Falcone
- Department of Neurology, Center for Brain and Mind Health, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Shyam Prabhakaran
- Department of Neurology, University of Chicago, Chicago, Illinois, USA
| | - Andrea L C Schneider
- Department of Neurology, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Kevin N Sheth
- Department of Neurology, Center for Brain and Mind Health, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Nicholas M Pajewski
- Department of Biostatistics and Data Science, Wake Forrest University School of Medicine, Winston-Salem, North Carolina, USA
| | - Adam M Brickman
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, and the Department of Neurology, Columbia University, New York, New York, USA
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Lahiri D, Seixas-Lima B, Roncero C, Verhoeff NP, Freedman M, Al-Shamaa S, Chertkow H. CAPS: a simple clinical tool for β-amyloid positivity prediction in clinical Alzheimer syndrome. Front Neurol 2024; 15:1422681. [PMID: 39206291 PMCID: PMC11349651 DOI: 10.3389/fneur.2024.1422681] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Accepted: 07/29/2024] [Indexed: 09/04/2024] Open
Abstract
Introduction With the advent of anti-β-amyloid therapies, clinical distinction between Aβ + and Aβ- in cognitive impairment is becoming increasingly important for stratifying referral and better utilization of biomarker assays. Methods Cognitive profile, rate of decline, neuropsychiatric inventory questionnaire (NPI-Q), and imaging characteristics were collected from 52 subjects with possible/probable AD. Results Participants with Aβ+ status had lower baseline MMSE scores (24.50 vs. 26.85, p = 0.009) and higher total NPI-Q scores (2.73 vs. 1.18, p < 0.001). NPI-Q score was found to be the only independent predictor for β-amyloid positivity (p = 0.008). A simple scoring system, namely Clinical β-Amyloid Positivity Prediction Score (CAPS), was developed by using the following parameters: NPI-Q, rapidity of cognitive decline, and white matter microangiopathy. Data from 48 participants were included in the analysis of accuracy of CAPS. CAP Score of 3 or 4 successfully classified Aβ + individuals in 86.7% cases. Discussion Clinical β-Amyloid Positivity Prediction Score is a simple clinical tool for use in primary care and memory clinic settings to predict β-amyloid positivity in individuals with clinical Alzheimer Syndrome can potentially facilitate referral for Anti Aβ therapies.
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Affiliation(s)
- Durjoy Lahiri
- Baycrest Academy for Research and Education/Rotman Research Institute, University of Toronto, Toronto, ON, Canada
- Department of Neurology, Institute of Neurosciences Kolkata, Kolkata, India
| | - Bruna Seixas-Lima
- Baycrest Academy for Research and Education/Rotman Research Institute, University of Toronto, Toronto, ON, Canada
| | - Carlos Roncero
- Baycrest Academy for Research and Education/Rotman Research Institute, University of Toronto, Toronto, ON, Canada
| | - Nicolaas Paul Verhoeff
- Baycrest Academy for Research and Education/Rotman Research Institute, University of Toronto, Toronto, ON, Canada
| | - Morris Freedman
- Baycrest Academy for Research and Education/Rotman Research Institute, University of Toronto, Toronto, ON, Canada
| | - Sarmad Al-Shamaa
- Baycrest Academy for Research and Education/Rotman Research Institute, University of Toronto, Toronto, ON, Canada
| | - Howard Chertkow
- Baycrest Academy for Research and Education/Rotman Research Institute, University of Toronto, Toronto, ON, Canada
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Chandio BQ, Villalon-Reina JE, Nir TM, Thomopoulos SI, Feng Y, Benavidez S, Jahanshad N, Harezlak J, Garyfallidis E, Thompson PM. Amyloid, Tau, and APOE in Alzheimer's Disease: Impact on White Matter Tracts. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.05.606560. [PMID: 39149378 PMCID: PMC11326207 DOI: 10.1101/2024.08.05.606560] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
Alzheimer's disease (AD) is characterized by cognitive decline and memory loss due to the abnormal accumulation of amyloid-beta (Aβ) plaques and tau tangles in the brain; its onset and progression also depend on genetic factors such as the apolipoprotein E (APOE) genotype. Understanding how these factors affect the brain's neural pathways is important for early diagnostics and interventions. Tractometry is an advanced technique for 3D quantitative assessment of white matter tracts, localizing microstructural abnormalities in diseased populations in vivo. In this work, we applied BUAN (Bundle Analytics) tractometry to 3D diffusion MRI data from 730 participants in ADNI3 (phase 3 of the Alzheimer's Disease Neuroimaging Initiative; age range: 55-95 years, 349M/381F, 214 with mild cognitive impairment, 69 with AD, and 447 cognitively healthy controls). Using along-tract statistical analysis, we assessed the localized impact of amyloid, tau, and APOE genetic variants on the brain's neural pathways. BUAN quantifies microstructural properties of white matter tracts, supporting along-tract statistical analyses that identify factors associated with brain microstructure. We visualize the 3D profile of white matter tract associations with tau and amyloid burden in Alzheimer's disease; strong associations near the cortex may support models of disease propagation along neural pathways. Relative to the neutral genotype, APOE ϵ3/ϵ3, carriers of the AD-risk conferring APOE ϵ4 genotype show microstructural abnormalities, while carriers of the protective ϵ2 genotype also show subtle differences. Of all the microstructural metrics, mean diffusivity (MD) generally shows the strongest associations with AD pathology, followed by axial diffusivity (AxD) and radial diffusivity (RD), while fractional anisotropy (FA) is typically the least sensitive metric. Along-tract microstructural metrics are sensitive to tau and amyloid accumulation, showing the potential of diffusion MRI to track AD pathology and map its impact on neural pathways.
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Affiliation(s)
- Bramsh Qamar Chandio
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Julio E. Villalon-Reina
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Talia M. Nir
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Sophia I. Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Yixue Feng
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Sebastian Benavidez
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | | | | | - Paul M. Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
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Morcillo-Nieto AO, Zsadanyi SE, Arriola-Infante JE, Carmona-Iragui M, Montal V, Pegueroles J, Aranha MR, Vaqué-Alcázar L, Padilla C, Benejam B, Videla L, Barroeta I, Fernandez S, Altuna M, Giménez S, González-Ortiz S, Bargalló N, Ribas L, Arranz J, Torres S, Iulita MF, Belbin O, Camacho V, Alcolea D, Lleó A, Fortea J, Bejanin A. Characterization of white matter hyperintensities in Down syndrome. Alzheimers Dement 2024. [PMID: 39087352 DOI: 10.1002/alz.14146] [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: 03/06/2024] [Revised: 06/20/2024] [Accepted: 07/02/2024] [Indexed: 08/02/2024]
Abstract
INTRODUCTION In Down syndrome (DS), white matter hyperintensities (WMHs) are highly prevalent, yet their topography and association with sociodemographic data and Alzheimer's disease (AD) biomarkers remain largely unexplored. METHODS In 261 DS adults and 131 euploid controls, fluid-attenuated inversion recovery magnetic resonance imaging scans were segmented and WMHs were extracted in concentric white matter layers and lobar regions. We tested associations with AD clinical stages, sociodemographic data, cerebrospinal fluid (CSF) AD biomarkers, and gray matter (GM) volume. RESULTS In DS, total WMHs arose at age 43 and showed stronger associations with age than in controls. WMH volume increased along the AD continuum, particularly in periventricular regions, and frontal, parietal, and occipital lobes. Associations were found with CSF biomarkers and temporo-parietal GM volumes. DISCUSSION WMHs increase 10 years before AD symptom onset in DS and are closely linked with AD biomarkers and neurodegeneration. This suggests a direct connection to AD pathophysiology, independent of vascular risks. HIGHLIGHTS White matter hyperintensities (WMHs) increased 10 years before Alzheimer's disease symptom onset in Down syndrome (DS). WMHs were strongly associated in DS with the neurofilament light chain biomarker. WMHs were more associated in DS with gray matter volume in parieto-temporal areas.
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Affiliation(s)
- Alejandra O Morcillo-Nieto
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Sara E Zsadanyi
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Jose E Arriola-Infante
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Maria Carmona-Iragui
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Barcelona Down Medical Center, Fundació Catalana de Síndrome de Down, Barcelona, Spain
| | - Victor Montal
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Barcelona Supercomputing Center, Barcelona, Spain
| | - Jordi Pegueroles
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Mateus Rozalem Aranha
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Lídia Vaqué-Alcázar
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Department of Medicine, Faculty of Medicine and Health Sciences, Institute of Neurosciences, University of Barcelona, Barcelona, Spain. Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Concepción Padilla
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Estudis de Ciències de la Salut, Universitat Oberta de Catalunya, Barcelona, Spain
| | - Bessy Benejam
- Barcelona Down Medical Center, Fundació Catalana de Síndrome de Down, Barcelona, Spain
| | - Laura Videla
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Barcelona Down Medical Center, Fundació Catalana de Síndrome de Down, Barcelona, Spain
| | - Isabel Barroeta
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Susana Fernandez
- Barcelona Down Medical Center, Fundació Catalana de Síndrome de Down, Barcelona, Spain
| | - Miren Altuna
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Fundación CITA-Alzheimer Fundazia, Donostia, Spain
| | - Sandra Giménez
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Multidisciplinary Sleep Unit, Respiratory Department, Hospital de la Santa Creu i Sant Pau, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Barcelona, Spain
| | - Sofía González-Ortiz
- Neuroradiology Section, Radiology Department, Diagnostic Image Center, Hospital Clínic de Barcelona, Universitat de Barcelona, Barcelona, Spain
| | - Núria Bargalló
- Neuroradiology Section, Radiology Department, Diagnostic Image Center, Hospital Clínic de Barcelona, Universitat de Barcelona, Barcelona, Spain
- Magnetic Resonance Image Core Facility, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Laia Ribas
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Javier Arranz
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Soraya Torres
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Maria Florencia Iulita
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Olivia Belbin
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Valle Camacho
- Nuclear Medicine Department, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Daniel Alcolea
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Alberto Lleó
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Juan Fortea
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Barcelona Down Medical Center, Fundació Catalana de Síndrome de Down, Barcelona, Spain
| | - Alexandre Bejanin
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
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9
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Liu S, Luo X, Chong JSX, Jiaerken Y, Youn SH, Zhang M, Zhou JH. Brain structure, amyloid, and behavioral features for predicting clinical progression in subjective cognitive decline. Hum Brain Mapp 2024; 45:e26765. [PMID: 38958401 PMCID: PMC11220833 DOI: 10.1002/hbm.26765] [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: 10/09/2023] [Revised: 05/28/2024] [Accepted: 06/10/2024] [Indexed: 07/04/2024] Open
Abstract
As a potential preclinical stage of Alzheimer's dementia, subjective cognitive decline (SCD) reveals a higher risk of future cognitive decline and conversion to dementia. However, it has not been clear whether SCD status increases the clinical progression of older adults in the context of amyloid deposition, cerebrovascular disease (CeVD), and psychiatric symptoms. We identified 99 normal controls (NC), 15 SCD individuals who developed mild cognitive impairment in the next 2 years (P-SCD), and 54 SCD individuals who did not (S-SCD) from ADNI database with both baseline and 2-year follow-up data. Total white matter hyperintensity (WMH), WMH in deep (DWMH) and periventricular (PWMH) regions, and voxel-wise grey matter volumes were compared among groups. Furthermore, using structural equation modelling method, we constructed path models to explore SCD-related brain changes longitudinally and to determine whether baseline SCD status, age, and depressive symptoms affect participants' clinical outcomes. Both SCD groups showed higher baseline amyloid PET SUVR, baseline PWMH volumes, and larger increase of PWMH volumes over time than NC. In contrast, only P-SCD had higher baseline DWMH volumes and larger increase of DWMH volumes over time than NC. No longitudinal differences in grey matter volume and amyloid was observed among NC, S-SCD, and P-SCD. Our path models demonstrated that SCD status contributed to future WMH progression. Further, baseline SCD status increases the risk of future cognitive decline, mediated by PWMH; baseline depressive symptoms directly contribute to clinical outcomes. In conclusion, both S-SCD and P-SCD exhibited more severe CeVD than NC. The CeVD burden increase was more pronounced in P-SCD. In contrast with the direct association of depressive symptoms with dementia severity progression, the effects of SCD status on future cognitive decline may manifest via CeVD pathologies. Our work highlights the importance of multi-modal longitudinal designs in understanding the SCD trajectory heterogeneity, paving the way for stratification and early intervention in the preclinical stage. PRACTITIONER POINTS: Both S-SCD and P-SCD exhibited more severe CeVD at baseline and a larger increase of CeVD burden compared to NC, while the burden was more pronounced in P-SCD. Baseline SCD status increases the risk of future PWMH and DWMH volume accumulation, mediated by baseline PWMH and DWMH volumes, respectively. Baseline SCD status increases the risk of future cognitive decline, mediated by baseline PWMH, while baseline depression status directly contributes to clinical outcome.
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Grants
- U01 AG024904 NIA NIH HHS
- W81XWH-12-2-0012 DoD Alzheimer's Disease Neuroimaging Initiative (Department of Defense)
- A20G8b0102 Research, Innovation and Enterprise (RIE) 2020 Advanced Manufacturing and Engineering (AME) Programmatic Fund (Agency for Science, Technology and Research (A*STAR), Singapore)
- NMRC/OFLCG19May-0035 National Medical Research Council, Singapore
- NMRC/CIRG/1485/2018 National Medical Research Council, Singapore
- NMRC/CSA-SI/0007/2016 National Medical Research Council, Singapore
- NMRC/MOH-00707-01 National Medical Research Council, Singapore
- NMRC/CG/435M009/2017-NUH/NUHS National Medical Research Council, Singapore
- CIRG21nov-0007 National Medical Research Council, Singapore
- HLCA23Feb-0004 National Medical Research Council, Singapore
- Yong Loo Lin School of Medicine Research Core Funding (National University of Singapore, Singapore)
- 82271936 National Natural Science Foundation of China
- 2022ZQ057 Zhejiang Provincial Administration of Traditional Chinese Medicine - Youth Talent Fund Project
- MOE-T2EP40120-0007 Ministry of Education, Singapore
- T2EP2-0223-0025 Ministry of Education, Singapore
- MOE-T2EP20220-0001 Ministry of Education, Singapore
- Alzheimer's Disease Neuroimaging Initiative (National Institutes of Health)
- DoD Alzheimer's Disease Neuroimaging Initiative (Department of Defense)
- National Medical Research Council, Singapore
- National Natural Science Foundation of China
- Ministry of Education, Singapore
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Affiliation(s)
- Siwei Liu
- Centre for Sleep and CognitionCentre for Translational Magnetic Resonance Research, Yong Loo Lin School of MedicineNational University of SingaporeSingaporeSingapore
- Human Potential Translational Research ProgramDepartment of MedicineNational University of SingaporeSingaporeSingapore
| | - Xiao Luo
- Department of Radiology, Second Affiliated HospitalZhejiang University School of MedicineHangzhouChina
| | - Joanna Su Xian Chong
- Centre for Sleep and CognitionCentre for Translational Magnetic Resonance Research, Yong Loo Lin School of MedicineNational University of SingaporeSingaporeSingapore
- Human Potential Translational Research ProgramDepartment of MedicineNational University of SingaporeSingaporeSingapore
| | - Yeerfan Jiaerken
- Department of Radiology, Second Affiliated HospitalZhejiang University School of MedicineHangzhouChina
| | - Shim Hee Youn
- Centre for Sleep and CognitionCentre for Translational Magnetic Resonance Research, Yong Loo Lin School of MedicineNational University of SingaporeSingaporeSingapore
- Human Potential Translational Research ProgramDepartment of MedicineNational University of SingaporeSingaporeSingapore
| | - Minming Zhang
- Department of Radiology, Second Affiliated HospitalZhejiang University School of MedicineHangzhouChina
| | - Juan Helen Zhou
- Centre for Sleep and CognitionCentre for Translational Magnetic Resonance Research, Yong Loo Lin School of MedicineNational University of SingaporeSingaporeSingapore
- Human Potential Translational Research ProgramDepartment of MedicineNational University of SingaporeSingaporeSingapore
- Department of Electrical and Computer EngineeringIntegrative Sciences and Engineering Programme (ISEP), NUS Graduate SchoolNational University of SingaporeSingaporeSingapore
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10
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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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11
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Lee JK, Raghavan S, Christenson LR, Frank RD, Kantarci K, Rocca WA, Vemuri P, Mielke MM. Longitudinal associations of reproductive factors and exogeneous estrogens with neuroimaging biomarkers of Alzheimer's disease and cerebrovascular disease. Alzheimers Dement 2024; 20:4613-4624. [PMID: 38859736 PMCID: PMC11247693 DOI: 10.1002/alz.13890] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 04/02/2024] [Accepted: 04/22/2024] [Indexed: 06/12/2024]
Abstract
INTRODUCTION Female-specific reproductive factors and exogeneous estrogen use are associated with cognition in later life. However, the underlying mechanisms are not understood. The present study aimed to investigate the effect of reproductive factors on neuroimaging biomarkers of Alzheimer's disease (AD) and cerebrovascular pathologies. METHODS We evaluated 389 females (median age of 71.7 years) enrolled in the Mayo Clinic Study of Aging with reproductive history data and longitudinal magnetic resonance imaging (MRI) scans. We used linear mixed effect models to examine the associations between reproductive factors and changes in neuroimaging measures. RESULTS Ever hormonal contraception (HC) use was longitudinally associated with higher fractional anisotropy across the corpus callosum, lower white matter hyperintensity (WMH) volume, and greater cortical thickness in an AD meta-region of interest (ROI). The initiation of menopausal hormone therapy (MHT) > 5 years post menopause was associated with higher WMH volume. DISCUSSION HC use and initiation of MHT >5 years post menopause were generally associated with neuroimaging biomarkers of cerebrovascular pathologies. HIGHLIGHTS Hormonal contraception use was associated with better brain white matter (WM) integrity. Initiation of menopausal hormone therapy >5 years post menopause was associated with worsening brain WM integrity. Hormonal contraception use was associated with greater cortical thickness. Ages at menarche and menopause and number of pregnancies were not associated with imaging measures. There were few associations between reproductive factors or exogenous estrogens and amyloid or tau PET.
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Affiliation(s)
- Jillian K Lee
- Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
| | | | - Luke R Christenson
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA
| | - Ryan D Frank
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Walter A Rocca
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
- Women's Health Research Center, Mayo Clinic, Rochester, Minnesota, USA
| | | | - Michelle M Mielke
- Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
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12
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Mielke MM, Frank RD, Christenson LR, Reid RI, Fields JA, Knyazhanskaya ZE, Kara F, Vemuri P, Rocca WA, Kantarci K. Premenopausal bilateral oophorectomy and brain white matter brain integrity in later-life. Alzheimers Dement 2024; 20:5054-5061. [PMID: 38899634 PMCID: PMC11247692 DOI: 10.1002/alz.13852] [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: 11/30/2023] [Revised: 03/18/2024] [Accepted: 03/20/2024] [Indexed: 06/21/2024]
Abstract
INTRODUCTION Premenopausal bilateral oophorectomy (PBO) is associated with later-life cognition, but the underlying brain changes remain unclear. We assessed the impact of PBO and PBO age on white matter integrity. METHODS Female participants with regional diffusion tensor imaging (DTI) metrics of fractional anisotropy (FA) and mean diffusivity (MD) were included (22 with PBO < 40 years; 43 with PBO 40-45 years; 39 with PBO 46-49 years; 907 referents without PBO < 50 years). Linear regression models adjusted for age and apolipoprotein E (APOE) genotype. RESULTS Females with PBO < 40 years, compared to referents, had lower FA and higher MD in the anterior corona radiata, genu of the corpus collosum, inferior fronto-occipital fasciculus, superior occipital, and superior temporal white matter. Females who underwent PBO between 45 and 49 also had some changes in white matter integrity. DISCUSSION Females who underwent PBO < 40 years had reduced white matter integrity across multiple regions in later-life. These results are important for females considering PBO for noncancerous conditions. HIGHLIGHTS Females with premenopausal bilateral oophorectomy (PBO) < 40 years had lower FA versus referents. Females with PBO < 40 years had higher MD in many regions versus referents. Adjusting for estrogen replacement therapy use did not attenuate results. Females with PBO 45-49 years also had some white matter changes versus referents.
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Affiliation(s)
- Michelle M. Mielke
- Department of Epidemiology and PreventionWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Ryan D. Frank
- Department of Quantitative Health SciencesMayo ClinicRochesterMinnesotaUSA
| | | | | | - Julie A. Fields
- Division of Neurocognitive DisordersDepartment of Psychiatry and PsychologyMayo ClinicRochesterMinnesotaUSA
| | | | - Firat Kara
- Department of RadiologyMayo ClinicRochesterMinnesotaUSA
| | | | - Walter A. Rocca
- Department of Quantitative Health SciencesMayo ClinicRochesterMinnesotaUSA
- Department of NeurologyMayo ClinicRochesterMinnesotaUSA
- Women's Health Research CenterMayo ClinicRochesterMinnesotaUSA
| | - Kejal Kantarci
- Department of RadiologyMayo ClinicRochesterMinnesotaUSA
- Women's Health Research CenterMayo ClinicRochesterMinnesotaUSA
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13
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Shir D, Graff-Radford J, Fought AJ, Lesnick TG, Przybelski SA, Vassilaki M, Lowe VJ, Knopman DS, Machulda MM, Petersen RC, Jack CR, Mielke MM, Vemuri P. Complex relationships of socioeconomic status with vascular and Alzheimer's pathways on cognition. Neuroimage Clin 2024; 43:103634. [PMID: 38909419 PMCID: PMC11253683 DOI: 10.1016/j.nicl.2024.103634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Revised: 06/12/2024] [Accepted: 06/14/2024] [Indexed: 06/25/2024]
Abstract
INTRODUCTION AD and CVD, which frequently co-occur, are leading causes of age-related cognitive decline. We assessed how demographic factors, socioeconomic status (SES) as indicated by education and occupation, vascular risk factors, and a range of biomarkers associated with both CVD (including white matter hyperintensities [WMH], diffusion MRI abnormalities, infarctions, and microbleeds) and AD (comprising amyloid-PET and tau-PET) collectively influence cognitive function. METHODS In this cross-sectional population study, structural equation models were utilized to understand these associations in 449 participants (mean age (SD) = 74.5 (8.4) years; 56% male; 7.5% cognitively impaired). RESULTS (1) Higher SES had a protective effect on cognition with mediation through the vascular pathway. (2) The effect of amyloid directly on cognition and through tau was 11-fold larger than the indirect effect of amyloid on cognition through WMH. (3) There is a significant effect of vascular risk on tau deposition. DISCUSSION The utilized biomarkers captured the impact of CVD and AD on cognition. The overall effect of vascular risk and SES on these biomarkers are complex and need further investigation.
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Affiliation(s)
- Dror Shir
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Angela J Fought
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | - Timothy G Lesnick
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | - Scott A Przybelski
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | - Maria Vassilaki
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - David S Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Mary M Machulda
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, 55905 USA
| | - Ronald C Petersen
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA; Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Michelle M Mielke
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA; Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC, 27101, USA
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14
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Zhang J, Chen H, Wang J, Huang Q, Xu X, Wang W, Xu W, Guan Y, Liu J, Wardlaw JM, Deng Y, Xie F, Li B. Linking white matter hyperintensities to regional cortical thinning, amyloid deposition, and synaptic density loss in Alzheimer's disease. Alzheimers Dement 2024; 20:3931-3942. [PMID: 38648354 PMCID: PMC11180938 DOI: 10.1002/alz.13845] [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: 12/30/2023] [Revised: 02/16/2024] [Accepted: 03/21/2024] [Indexed: 04/25/2024]
Abstract
INTRODUCTION We investigated the association between white matter hyperintensities (WMH) and regional cortical thickness, amyloid and tau deposition, and synaptic density in the WMH-connected cortex using multimodal images. METHODS We included 107 participants (59 with Alzheimer's disease [AD]; 27 with mild cognitive impairment; 21 cognitively normal controls) with amyloid beta (Aβ) positivity on amyloid positron emission tomography (PET). The cortex connected to WMH was identified using probabilistic tractography. RESULTS We found that WMH connected to the cortex with more severe regional degeneration as measured by cortical thickness, Aβ and tau deposition, and synaptic vesicle glycoprotein 2 A (SV2A) density using 18F-SynVesT-1 PET. In addition, higher ratios of Aβ in the deep WMH-connected versus WMH-unconnected cortex were significantly related to lower cognitive scores. Last, the cortical thickness of WMH-connected cortex reduced more than WMH-unconnected cortex over 12 months. DISCUSSION Our results suggest that WMH may be associated with AD-intrinsic processes of degeneration, in addition to vascular mechanisms. HIGHLIGHTS We studied white matter hyperintensities (WMHs) and WMH-connected cortical changes. WMHs are associated with more severe regional cortical degeneration. Findings suggest WMHs may be associated with Alzheimer's disease-intrinsic processes of degeneration.
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Affiliation(s)
- Junfang Zhang
- Department of Neurology & Institute of NeurologyRuijin Hospital affiliated with Shanghai Jiao Tong University School of MedicineShanghaiChina
- Clinical Neuroscience CenterRuijin Hospital LuWan BranchShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Haijuan Chen
- Department of Neurology & Institute of NeurologyRuijin Hospital affiliated with Shanghai Jiao Tong University School of MedicineShanghaiChina
- Clinical Neuroscience CenterRuijin Hospital LuWan BranchShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Jie Wang
- PET CenterHuashan HospitalFudan UniversityShanghaiChina
| | - Qi Huang
- PET CenterHuashan HospitalFudan UniversityShanghaiChina
| | - Xiaomeng Xu
- Department of Neurology & Institute of NeurologyRuijin Hospital affiliated with Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Wenjing Wang
- Department of Neurology & Institute of NeurologyRuijin Hospital affiliated with Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Wei Xu
- Department of Neurology & Institute of NeurologyRuijin Hospital affiliated with Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Yihui Guan
- PET CenterHuashan HospitalFudan UniversityShanghaiChina
| | - Jun Liu
- Department of Neurology & Institute of NeurologyRuijin Hospital affiliated with Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Joanna M Wardlaw
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUK
- UK Dementia Research InstituteUniversity of EdinburghEdinburghUK
| | - Yulei Deng
- Department of Neurology & Institute of NeurologyRuijin Hospital affiliated with Shanghai Jiao Tong University School of MedicineShanghaiChina
- Clinical Neuroscience CenterRuijin Hospital LuWan BranchShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Fang Xie
- PET CenterHuashan HospitalFudan UniversityShanghaiChina
| | - Binyin Li
- Department of Neurology & Institute of NeurologyRuijin Hospital affiliated with Shanghai Jiao Tong University School of MedicineShanghaiChina
- Clinical Neuroscience CenterRuijin Hospital LuWan BranchShanghai Jiao Tong University School of MedicineShanghaiChina
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Li M, Yu R, Wang X, Zhao Y, Song Q, Wang Q, Fu C, Mishra SR, Shrestha N, Virani SS, Zhu D. Association between ABO genotypes and risk of dementia and neuroimaging markers: roles of sex and APOE status. Front Neurol 2024; 15:1391010. [PMID: 38863509 PMCID: PMC11165032 DOI: 10.3389/fneur.2024.1391010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Accepted: 05/14/2024] [Indexed: 06/13/2024] Open
Abstract
Background Whether the relationships between ABO blood genotypes (AA, AO, BB, BO, AB, and OO) and dementia are modified by gender and APOE status has been unclear. Methods We used data from the UK Biobank, a population-based cohort study of 487,425 individuals. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CI) between ABO genotypes and risk of dementia. Multivariable linear regression models were used to estimate the relationship between ABO genotypes and MRI-based brain indices. Results Overall, 487,425 participants were included at baseline. After 34 million person-years follow up, 7,548 patients developed all-cause dementia. Before stratifying by sex and APOE status, compared to OO genotype, BB genotype was associated with increased risk of all-cause dementia (1.36, 1.03-1.80) and other types dementia (1.65, 1.20-2.28). After stratifying by sex, only in males, BB genotype was associated with higher risk of all-cause dementia (1.44, 1.02-2.09) and other types of dementia (1.95, 1.30-2.93). AB genotype in males was also associated with increased AD (1.34, 1.04-1.72). After further stratifying by APOE e4 status, BB genotype with two APOE e4 alleles showed even stronger association with all-cause dementia 4.29 (1.57, 11.72) and other types dementia (5.49, 1.70-17.69) in males. Also in males, AA genotype with one APOE e4 was associated with increased risks of all-cause dementia (1.27, 1.04-1.55), AD (1.45, 1.09-1.94) and other types dementia (1.40, 1.08-1.81). Linear regression models showed that in both sexes with APOE e4, AA genotype was associated with reduced total grey matter volume. Conclusion Sex and APOE e4 carrier status modified the association between ABO genotypes and risk of dementia. In males, BB genotype was consistently associated with increased risk of dementia, especially in those with two APOE e4 alleles. Also, in males with one APOE e4, AA genotype might be linked to higher risk of dementia.
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Affiliation(s)
- Meiling Li
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Ruihong Yu
- Department of Disinfection and Sterilization, Pingyin Center for Disease Control and Prevention, Jinan, China
| | - Xiaoyi Wang
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Yanqing Zhao
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Qixiang Song
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Qi Wang
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Chunying Fu
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Shiva Raj Mishra
- NHMRC Clinical Trials Center, University of Sydney, Sydney, NSW, Australia
- Westmead Applied Research Centre (WARC), Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
| | - Nipun Shrestha
- NHMRC Clinical Trials Center, University of Sydney, Sydney, NSW, Australia
| | - Salim S. Virani
- Section of Global Research, The Aga Khan University, Karachi, Pakistan
| | - Dongshan Zhu
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
- Center for Clinical Epidemiology and Evidence-Based Medicine, Shandong University, Jinan, China
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Patel V, Edison P. Cardiometabolic risk factors and neurodegeneration: a review of the mechanisms underlying diabetes, obesity and hypertension in Alzheimer's disease. J Neurol Neurosurg Psychiatry 2024; 95:581-589. [PMID: 38290839 PMCID: PMC11103343 DOI: 10.1136/jnnp-2023-332661] [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: 09/25/2023] [Accepted: 01/09/2024] [Indexed: 02/01/2024]
Abstract
A growing body of evidence suggests that cardiometabolic risk factors play a significant role in Alzheimer's disease (AD). Diabetes, obesity and hypertension are highly prevalent and can accelerate neurodegeneration and perpetuate the burden of AD. Insulin resistance and enzymes including insulin degrading enzymes are implicated in AD where breakdown of insulin is prioritised over amyloid-β. Leptin resistance and inflammation demonstrated by higher plasma and central nervous system levels of interleukin-6 (IL-6), IL-1β and tumour necrosis factor-α, are mechanisms connecting obesity and diabetes with AD. Leptin has been shown to ameliorate AD pathology and enhance long-term potentiation and hippocampal-dependent cognitive function. The renin-aldosterone angiotensin system, involved in hypertension, has been associated with AD pathology and neurotoxic reactive oxygen species, where angiotensin binds to specific angiotensin-1 receptors in the hippocampus and cerebral cortex. This review aims to consolidate the evidence behind putative processes stimulated by obesity, diabetes and hypertension, which leads to increased AD risk. We focus on how novel knowledge can be applied clinically to facilitate recognition of efficacious treatment strategies for AD.
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Affiliation(s)
- Vijay Patel
- Department of Brain Sciences, Imperial College London, London, UK
| | - Paul Edison
- Department of Brain Sciences, Imperial College London, London, UK
- Cardiff University, Cardiff, UK
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Li H, Cui F, Wang T, Wang W, Zhang D. The impact of sunlight exposure on brain structural markers in the UK Biobank. Sci Rep 2024; 14:10313. [PMID: 38705875 PMCID: PMC11070413 DOI: 10.1038/s41598-024-59633-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2024] [Accepted: 04/12/2024] [Indexed: 05/07/2024] Open
Abstract
Sunlight is closely intertwined with daily life. It remains unclear whether there are associations between sunlight exposure and brain structural markers. General linear regression analysis was used to compare the differences in brain structural markers among different sunlight exposure time groups. Stratification analyses were performed based on sex, age, and diseases (hypertension, stroke, diabetes). Restricted cubic spline was performed to examine the dose-response relationship between natural sunlight exposure and brain structural markers, with further stratification by season. A negative association of sunlight exposure time with brain structural markers was found in the upper tertile compared to the lower tertile. Prolonged natural sunlight exposure was associated with the volumes of total brain (β: - 0.051, P < 0.001), white matter (β: - 0.031, P = 0.023), gray matter (β: - 0.067, P < 0.001), and white matter hyperintensities (β: 0.059, P < 0.001). These associations were more pronounced in males and individuals under the age of 60. The results of the restricted cubic spline analysis showed a nonlinear relationship between sunlight exposure and brain structural markers, with the direction changing around 2 h of sunlight exposure. This study demonstrates that prolonged exposure to natural sunlight is associated with brain structural markers change.
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Affiliation(s)
- Huihui Li
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, No. 308 Ningxia Road, QingdaoShandong Province, 266071, China
| | - Fusheng Cui
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, No. 308 Ningxia Road, QingdaoShandong Province, 266071, China
| | - Tong Wang
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, No. 308 Ningxia Road, QingdaoShandong Province, 266071, China
| | - Weijing Wang
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, No. 308 Ningxia Road, QingdaoShandong Province, 266071, China.
| | - Dongfeng Zhang
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, No. 308 Ningxia Road, QingdaoShandong Province, 266071, China.
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Sintini I, Singh NA, Li D, Mielke MM, Machulda MM, Schwarz CG, Senjem ML, Jack CR, Lowe VJ, Graff‐Radford J, Josephs KA, Whitwell JL. Plasma glial fibrillary acidic protein in the visual and language variants of Alzheimer's disease. Alzheimers Dement 2024; 20:3679-3686. [PMID: 38528318 PMCID: PMC11095421 DOI: 10.1002/alz.13713] [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: 09/25/2023] [Revised: 01/02/2024] [Accepted: 01/03/2024] [Indexed: 03/27/2024]
Abstract
INTRODUCTION Glial fibrillary acidic protein (GFAP) in plasma is a proxy for astrocytic activity and is elevated in amyloid-β (Aβ)-positive individuals, making GFAP a potential blood-based biomarker for Alzheimer's disease (AD). METHODS We assessed plasma GFAP in 72 Aβ-positive participants diagnosed with the visual or language variant of AD who underwent Aβ- and tau-PET. Fifty-nine participants had follow-up imaging. Linear regression was applied on GFAP and imaging quantities. RESULTS GFAP did not correlate with Aβ- or tau-PET cross-sectionally. There was a limited positive correlation between GFAP and rates of tau accumulation, particularly in the language variant of AD, although associations were weaker after removing one outlier patient with the highest GFAP level. DISCUSSION Among Aβ-positive AD participants with atypical presentations, plasma GFAP did not correlate with levels of AD pathology on PET, suggesting that the associations between GFAP and AD pathology might plateau during the advanced phase of the disease.
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Affiliation(s)
- Irene Sintini
- Department of RadiologyMayo ClinicRochesterMinnesotaUSA
| | | | - Danni Li
- Department of Laboratory Medicine and PathologyUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Michelle M. Mielke
- Department of Epidemiology and PreventionWake Forest UniversityWinston‐SalemNorth CarolinaUSA
| | - Mary M. Machulda
- Department of Psychiatry and PsychologyMayo ClinicRochesterMinnesotaUSA
| | | | | | | | - Val J. Lowe
- Department of RadiologyMayo ClinicRochesterMinnesotaUSA
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Brett BL, Klein AP, Vazirnia P, Omidfar S, Guskiewicz KK, McCrea M, Meier T. White Matter Hyperintensities and Microstructural Alterations in Contact Sport Athletes from Adolescence to Early Midlife. J Neurotrauma 2024. [PMID: 38661548 DOI: 10.1089/neu.2023.0609] [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] [Indexed: 04/26/2024] Open
Abstract
Studies have demonstrated associations between cumulative concussion and repetitive head impact exposure (RHI) via contact sports with white matter (WM) alterations later in life. The course of WM changes associated with exposure earlier in the lifespan are unclear. This study investigated alterations in white matter (WM hyperintensity [WMH] volume and microstructural changes) associated with concussion and RHI exposure from adolescence to early midlife, as well as the interaction between exposure and age-cohort (i.e., adolescent/young adult compared to early midlife athlete cohorts) on WM outcomes. Participating football players included an adolescent/young adulthood cohort (n=82; Mage=18.41.7) and an early midlife cohort (37 former collegiate players approximately 15-years removed from sport; Mage=37.71.4). Years of football participation and number of prior concussions were exposures of interest. White matter outcomes included log-transformed manually segmented total WMH volume and neurite orientation dispersion and density imaging metrics of microstructure/organization (isotropic volume fraction[Viso], intra-cellular volume fraction[Vic], and orientation dispersion[OD]). Regression models were fit to test effects of concussion history, years of football participation, and age-cohort by years of football participation with WM outcomes. Spearman's correlations assessed associations between significant WM metrics and measures of cognitive and psychological function. A significant age-cohort by years of participation effect was observed for whole brain white matter OD, B=-0.002, SE=0.001, p=0.001. The interaction was driven by a negative association between years of participation and OD within the younger cohort, B=-0.001, SE=0.0004, p=0.008, whereas a positive association between participation and OD in the early midlife cohort, B=0.001, SE=0.0003, p=0.039, was observed. Follow-up ROI analyses showed significant interaction effects for OD in the body of the corpus callosum, genu of the corpus callosum, cingulum, inferior fronto-occipital fasciculus, superior longitudinal fasciculus, posterior thalamic radiation (ps<0.05). Greater concussion history was significantly associated with greater Viso in the early midlife cohort, B=0.001, SE= 0.0002, p=0.010. Years of participation and concussion history were not associated with WMH volume, ps>0.05. Performance on a measure of executive function was significantly associated with years of participation, =.34, p=.04, and a trend was observed for OD, =.28, p=.09 in the early midlife cohort only. The global characterization of white matter changes associated with years of football participation were broadly similar and stable from adolescence through early midlife (i.e., microstructural alterations, but not macroscopic lesions). An inverse association between years of participation and orientation dispersion across age-cohorts may represent a process of initial recovery/reorganization proximal to sport, followed by later reduction of white matter coherence.
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Affiliation(s)
- Benjamin L Brett
- Medical College of Wisconsin, 5506, Neurosurgery and Neurology, 8701 W Watertown Plank Rd, Milwaukee, Wisconsin, United States, 53226;
| | - Andrew P Klein
- Medical College of Wisconsin, 5506, Radiology, 9200 West Wisconsin Ave, Milwaukee, Wisconsin, United States, 53226;
| | - Parsia Vazirnia
- Medical College of Wisconsin, 5506, Milwaukee, Wisconsin, United States;
| | - Samantha Omidfar
- Medical College of Wisconsin, 5506, Milwaukee, Wisconsin, United States;
| | - Kevin K Guskiewicz
- University of North Carolina, Exercise and Sport Science, CB#8700, Chapel Hill, North Carolina, United States, 27599-8700;
| | - Michael McCrea
- Medical College of Wisconsin, Neurosurgery, Hub for Collaborative Medicine, 8701 Watertown Plank Road, Milwaukee, Wisconsin, United States, 53226;
| | - Timothy Meier
- Medical College of Wisconsin, Neurosurgery, 8701 Watertown Plank Road, Milwaukee, Wisconsin, United States, 53226;
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20
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Hong H, Chen Y, Liu W, Luo X, Zhang M. Distinct patterns of voxel- and connection-based white matter hyperintensity distribution and associated factors in early-onset and late-onset Alzheimer's disease. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2024; 16:e12585. [PMID: 38651161 PMCID: PMC11033836 DOI: 10.1002/dad2.12585] [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: 11/08/2023] [Revised: 02/12/2024] [Accepted: 03/15/2024] [Indexed: 04/25/2024]
Abstract
Introduction The distribution of voxel- and connection-based white matter hyperintensity (WMH) patterns in early-onset Alzheimer's disease (EOAD) and late-onset Alzheimer's disease (LOAD), as well as factors associated with these patterns, remain unclear. Method We analyzed the WMH distribution patterns in EOAD and LOAD at the voxel and connection levels, each compared with their age-matched cognitively unimpaired participants. Linear regression assessed the independent effects of amyloid and vascular risk factors on WMH distribution patterns in both groups. Results Patients with EOAD showed increased WMH burden in the posterior region at the voxel level, and in occipital region tracts and visual network at the connection level, compared to controls. LOAD exhibited extensive involvement across various brain areas in both levels. Amyloid accumulation was associated WMH distribution in the early-onset group, whereas the late-onset group demonstrated associations with both amyloid and vascular risk factors. Discussion EOAD showed posterior-focused WMH distribution pattern, whereas LOAD was with a wider distribution. Amyloid accumulation was associated with connection-based WMH patterns in both early-onset and late-onset groups, with additional independent effects of vascular risk factors in late-onset group. Highlights Both early-onset Alzheimer's disease (EOAD) and late-onset AD (LOAD) showed increased white matter hyperintensity (WMH) volume compared with their age-matched cognitively unimpaired participants.EOAD and LOAD exhibited distinct patterns of WMH distribution, with EOAD showing a posterior-focused pattern and LOAD displaying a wider distribution across both voxel- and connection-based levels.In both EOAD and LOAD, amyloid accumulation was associated with connection-based WMH patterns, with additional independent effects of vascular risk factors observed in LOAD.
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Affiliation(s)
- Hui Hong
- Department of RadiologyThe Second Affiliated Hospital of Zhejiang UniversitySchool of MedicineHangzhouChina
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
| | - Yutong Chen
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
| | - Weiran Liu
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
| | - Xiao Luo
- Department of RadiologyThe Second Affiliated Hospital of Zhejiang UniversitySchool of MedicineHangzhouChina
| | - Minming Zhang
- Department of RadiologyThe Second Affiliated Hospital of Zhejiang UniversitySchool of MedicineHangzhouChina
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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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22
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Levy SA, Misiura MB, Grant JG, Adrien TV, Taiwo Z, Armstrong R, Dotson VM. Depression, Vascular Burden, and Dementia Prevalence in Late Middle-Aged and Older Black Adults. J Gerontol B Psychol Sci Soc Sci 2024; 79:gbae009. [PMID: 38374692 PMCID: PMC10926943 DOI: 10.1093/geronb/gbae009] [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: 06/20/2023] [Indexed: 02/21/2024] Open
Abstract
OBJECTIVES Late-life depression and white matter hyperintensities (WMH) have been linked to increased dementia risk. However, there is a dearth of literature examining these relationships in Black adults. We investigated whether depression or WMH volume are associated with a higher likelihood of dementia diagnosis in a sample of late middle-aged to older Black adults, and whether dementia prevalence is highest in individuals with both depression and higher WMH volume. METHODS Secondary data analysis involved 443 Black participants aged 55+ with brain imaging within 1 year of baseline visit in the National Alzheimer's Coordinating Center Uniform Data Set. Chi-square analyses and logistic regression models controlling for demographic variables examined whether active depression in the past 2 years, WMH volume, or their combination were associated with higher odds of all-cause dementia. RESULTS Depression and higher WMH volume were associated with a higher prevalence of dementia. These associations remained after controlling for demographic factors, as well as vascular disease burden. Dementia risk was highest in the depression/high WMH volume group compared to the depression-only group, high WMH volume-only group, and the no depression/low WMH volume group. Post hoc analyses comparing the Black sample to a demographically matched non-Hispanic White sample showed associations of depression and the combination of depression and higher WMH burden with dementia were greater in Black compared to non-Hispanic White individuals. DISCUSSION Results suggest late-life depression and WMH have independent and joint relationships with dementia and that Black individuals may be particularly at risk due to these factors.
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Affiliation(s)
- Shellie-Anne Levy
- Department of Clinical and Health Psychology, The Center for Cognitive Aging and Memory, University of Florida, Gainesville, Florida, USA
- The Center for Cognitive Aging and Memory, University of Florida, Gainesville, Florida, USA
| | - Maria B Misiura
- Department of Psychology, Georgia State University, Atlanta, Georgia, USA
| | - Jeremy G Grant
- Department of Clinical and Health Psychology, The Center for Cognitive Aging and Memory, University of Florida, Gainesville, Florida, USA
| | - Tamare V Adrien
- Department of Clinical and Health Psychology, The Center for Cognitive Aging and Memory, University of Florida, Gainesville, Florida, USA
| | - Zinat Taiwo
- Department of Rehabilitation Psychology and Neuropsychology, TIRR Memorial Hermann, Houston, Texas, USA
- H. Ben Taub Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, Texas, USA
| | - Rebecca Armstrong
- Department of Clinical and Health Psychology, The Center for Cognitive Aging and Memory, University of Florida, Gainesville, Florida, USA
| | - Vonetta M Dotson
- Department of Psychology, Georgia State University, Atlanta, Georgia, USA
- Gerontology Institute, Georgia State University, Atlanta, Georgia, USA
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23
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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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25
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Coomans EM, van Westen D, Binette AP, Strandberg O, Spotorno N, Serrano GE, Beach TG, Palmqvist S, Stomrud E, Ossenkoppele R, Hansson O. Interactions between vascular burden and amyloid-β pathology on trajectories of tau accumulation. Brain 2024; 147:949-960. [PMID: 37721482 PMCID: PMC10907085 DOI: 10.1093/brain/awad317] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2023] [Revised: 08/02/2023] [Accepted: 09/07/2023] [Indexed: 09/19/2023] Open
Abstract
Cerebrovascular pathology often co-exists with Alzheimer's disease pathology and can contribute to Alzheimer's disease-related clinical progression. However, the degree to which vascular burden contributes to Alzheimer's disease pathological progression is still unclear. This study aimed to investigate interactions between vascular burden and amyloid-β pathology on both baseline tau tangle load and longitudinal tau accumulation. We included 1229 participants from the Swedish BioFINDER-2 Study, including cognitively unimpaired and impaired participants with and without biomarker-confirmed amyloid-β pathology. All underwent baseline tau-PET (18F-RO948), and a subset (n = 677) underwent longitudinal tau-PET after 2.5 ± 1.0 years. Tau-PET uptake was computed for a temporal meta-region-of-interest. We focused on four main vascular imaging features and risk factors: microbleeds; white matter lesion volume; stroke-related events (infarcts, lacunes and haemorrhages); and the Framingham Heart Study Cardiovascular Disease risk score. To validate our in vivo results, we examined 1610 autopsy cases from an Arizona-based neuropathology cohort on three main vascular pathological features: cerebral amyloid angiopathy; white matter rarefaction; and infarcts. For the in vivo cohort, primary analyses included age-, sex- and APOE ɛ4-corrected linear mixed models between tau-PET (outcome) and interactions between time, amyloid-β and each vascular feature (predictors). For the neuropathology cohort, age-, sex- and APOE ɛ4-corrected linear models between tau tangle density (outcome) and an interaction between plaque density and each vascular feature (predictors) were performed. In cognitively unimpaired individuals, we observed a significant interaction between microbleeds and amyloid-β pathology on greater baseline tau load (β = 0.68, P < 0.001) and longitudinal tau accumulation (β = 0.11, P < 0.001). For white matter lesion volume, we did not observe a significant independent interaction effect with amyloid-β on tau after accounting for microbleeds. In cognitively unimpaired individuals, we further found that stroke-related events showed a significant negative interaction with amyloid-β on longitudinal tau (β = -0.08, P < 0.001). In cognitively impaired individuals, there were no significant interaction effects between cerebrovascular and amyloid-β pathology at all. In the neuropathology dataset, the in vivo observed interaction effects between cerebral amyloid angiopathy and plaque density (β = 0.38, P < 0.001) and between infarcts and plaque density (β = -0.11, P = 0.005) on tau tangle density were replicated. To conclude, we demonstrated that cerebrovascular pathology-in the presence of amyloid-β pathology-modifies tau accumulation in early stages of Alzheimer's disease. More specifically, the co-occurrence of microbleeds and amyloid-β pathology was associated with greater accumulation of tau aggregates during early disease stages. This opens the possibility that interventions targeting microbleeds may attenuate the rate of tau accumulation in Alzheimer's disease.
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Affiliation(s)
- Emma M Coomans
- Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, 1081HV Amsterdam, The Netherlands
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, SE-222 42 Lund, Sweden
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081HV Amsterdam, The Netherlands
| | - Danielle van Westen
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, SE-222 42 Lund, Sweden
| | - Alexa Pichet Binette
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, SE-222 42 Lund, Sweden
| | - Olof Strandberg
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, SE-222 42 Lund, Sweden
| | - Nicola Spotorno
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, SE-222 42 Lund, Sweden
| | - Geidy E Serrano
- Banner Sun Health Research Institute, Sun City, AZ 85351, USA
| | - Thomas G Beach
- Banner Sun Health Research Institute, Sun City, AZ 85351, USA
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, SE-222 42 Lund, Sweden
- Memory Clinic, Skåne University Hospital, SE-205 02 Malmö, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, SE-222 42 Lund, Sweden
- Memory Clinic, Skåne University Hospital, SE-205 02 Malmö, Sweden
| | - Rik Ossenkoppele
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081HV Amsterdam, The Netherlands
- Memory Clinic, Skåne University Hospital, SE-205 02 Malmö, Sweden
- Amsterdam Neuroscience, Neurodegeneration, 1071HV Amsterdam, The Netherlands
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, SE-222 42 Lund, Sweden
- Memory Clinic, Skåne University Hospital, SE-205 02 Malmö, Sweden
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26
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Pavuluri K, Huston J, Ehman RL, Manduca A, Jack CR, Senjem ML, Vemuri P, Murphy MC. Associations between vascular health, brain stiffness and global cognitive function. Brain Commun 2024; 6:fcae073. [PMID: 38505229 PMCID: PMC10950054 DOI: 10.1093/braincomms/fcae073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 12/19/2023] [Accepted: 02/27/2024] [Indexed: 03/21/2024] Open
Abstract
Vascular brain injury results in loss of structural and functional connectivity and leads to cognitive impairment. Its various manifestations, including microinfarcts, microhaemorrhages and white matter hyperintensities, result in microstructural tissue integrity loss and secondary neurodegeneration. Among these, tissue microstructural alteration is a relatively early event compared with atrophy along the aging and neurodegeneration continuum. Understanding its association with cognition may provide the opportunity to further elucidate the relationship between vascular health and clinical outcomes. Magnetic resonance elastography offers a non-invasive approach to evaluate tissue mechanical properties, providing a window into the microstructural integrity of the brain. This retrospective study evaluated brain stiffness as a potential biomarker for vascular brain injury and its role in mediating the impact of vascular dysfunction on cognitive impairment. Seventy-five participants from the Mayo Clinic Study of Aging underwent brain imaging using a 3T MR imager with a spin-echo echo-planar imaging sequence for magnetic resonance elastography and T1- and T2-weighted pulse sequences. This study evaluated the effects of vascular biomarkers (white matter hyperintensities and cardiometabolic condition score) on brain stiffness using voxelwise analysis. Partial correlation analysis explored associations between brain stiffness, white matter hyperintensities, cardiometabolic condition and global cognition. Mediation analysis determined the role of stiffness in mediating the relationship between vascular biomarkers and cognitive performance. Statistical significance was set at P-values < 0.05. Diagnostic accuracy of magnetic resonance elastography stiffness for white matter hyperintensities and cardiometabolic condition was evaluated using receiver operator characteristic curves. Voxelwise linear regression analysis indicated white matter hyperintensities negatively correlate with brain stiffness, specifically in periventricular regions with high white matter hyperintensity levels. A negative association between cardiovascular risk factors and stiffness was also observed across the brain. No significant patterns of stiffness changes were associated with amyloid load. Global stiffness (µ) negatively correlated with both white matter hyperintensities and cardiometabolic condition when all other covariables including amyloid load were controlled. The positive correlation between white matter hyperintensities and cardiometabolic condition weakened and became statistically insignificant when controlling for other covariables. Brain stiffness and global cognition were positively correlated, maintaining statistical significance after adjusting for all covariables. These findings suggest mechanical alterations are associated with cognitive dysfunction and vascular brain injury. Brain stiffness significantly mediated the indirect effects of white matter hyperintensities and cardiometabolic condition on global cognition. Local cerebrovascular diseases (assessed by white matter hyperintensities) and systemic vascular risk factors (assessed by cardiometabolic condition) impact brain stiffness with spatially and statistically distinct effects. Global brain stiffness is a significant mediator between vascular disease measures and cognitive function, highlighting the value of magnetic resonance elastography-based mechanical assessments in understanding this relationship.
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Affiliation(s)
| | - John Huston
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Richard L Ehman
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Armando Manduca
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
- Department of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine, Rochester, MN 55905, USA
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Matthew L Senjem
- Department of Information Technology, Mayo Clinic, Rochester, MN 55905, USA
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Twait EL, Gerritsen L, Moonen JEF, Verberk IMW, Teunissen CE, Visser PJ, van der Flier WM, Geerlings MI. Plasma Markers of Alzheimer's Disease Pathology, Neuronal Injury, and Astrocytic Activation and MRI Load of Vascular Pathology and Neurodegeneration: The SMART-MR Study. J Am Heart Assoc 2024; 13:e032134. [PMID: 38353228 PMCID: PMC11010072 DOI: 10.1161/jaha.123.032134] [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: 08/24/2023] [Accepted: 10/23/2023] [Indexed: 02/21/2024]
Abstract
BACKGROUND Two of the main causes for dementia are Alzheimer's disease (AD) and vascular pathology, with most patients showing mixed pathology. Plasma biomarkers for Alzheimer's disease-related pathology have recently emerged, including Aβ (amyloid-beta), p-tau (phosphorylated tau), NfL (neurofilament light), and GFAP (glial fibrillary acidic protein). There is a current gap in the literature regarding whether there is an association between these plasma biomarkers with vascular pathology and neurodegeneration. METHODS AND RESULTS Cross-sectional data from 594 individuals (mean [SD] age: 64 [8] years; 17% female) were included from the SMART-MR (Second Manifestations of Arterial Disease-Magnetic Resonance) study, a prospective cohort study of individuals with a history of arterial disease. Plasma markers were assessed using single molecular array assays (Quanterix). Magnetic resonance imaging markers included white matter hyperintensity volume, presence of infarcts (yes/no), total brain volume, and hippocampal volume assessed on 1.5T magnetic resonance imaging. Linear regressions were performed for each standardized plasma marker with white matter hyperintensity volume, total brain volume, and hippocampal volume as separate outcomes, correcting for age, sex, education, and intracranial volume. Logistic regressions were performed for the presence of lacunar and cortical infarcts. Higher p-tau181 was associated with larger white matter hyperintensity volume (b per SD increase=0.16 [95% CI, 0.06-0.26], P=0.015). Higher NfL (b=-5.63, [95% CI, -8.95 to -2.31], P=0.015) was associated with lower total brain volume and the presence of infarcts (odds ratio [OR], 1.42 [95% CI, 1.13-1.78], P=0.039). Higher GFAP levels were associated with cortical infarcts (OR, 1.45 [95% CI, 1.09-1.92], P=0.010). CONCLUSIONS Plasma biomarkers that have been associated with tau pathology, axonal injury, and astrocytic activation are related to magnetic resonance imagingmarkers of vascular pathology and neurodegeneration in patients with manifest arterial disease.
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Affiliation(s)
- Emma L. Twait
- Julius Center for Health Sciences and Primary CareUniversity Medical Center Utrecht and Utrecht UniversityUtrechtThe Netherlands
- Amsterdam UMC location Vrije Universiteit Amsterdam, Department of General PracticeAmsterdamThe Netherlands
- Amsterdam Public Health, Aging & Later Life, and Personalized MedicineAmsterdamThe Netherlands
- Amsterdam Neuroscience, Neurodegeneration, and Mood, Anxiety, Psychosis, Stress, and SleepAmsterdamThe Netherlands
| | - Lotte Gerritsen
- Department of PsychologyUtrecht UniversityUtrechtThe Netherlands
| | - Justine E. F. Moonen
- Alzheimer Center Amsterdam, Amsterdam UMC location Vrije Universiteit Amsterdam, Neurology, Epidemiology and Data ScienceAmsterdamThe Netherlands
- Amsterdam Neuroscience, NeurodegenerationAmsterdamThe Netherlands
| | - Inge M. W. Verberk
- Amsterdam Neuroscience, NeurodegenerationAmsterdamThe Netherlands
- Amsterdam UMC location Vrije Universiteit Amsterdam, Neurochemistry Laboratory, Department of Laboratory Medicine,AmsterdamThe Netherlands
| | - Charlotte E. Teunissen
- Amsterdam Neuroscience, NeurodegenerationAmsterdamThe Netherlands
- Amsterdam UMC location Vrije Universiteit Amsterdam, Neurochemistry Laboratory, Department of Laboratory Medicine,AmsterdamThe Netherlands
| | - Pieter Jelle Visser
- Alzheimer Center Amsterdam, Amsterdam UMC location Vrije Universiteit Amsterdam, Neurology, Epidemiology and Data ScienceAmsterdamThe Netherlands
- Amsterdam Neuroscience, NeurodegenerationAmsterdamThe Netherlands
| | - Wiesje M. van der Flier
- Alzheimer Center Amsterdam, Amsterdam UMC location Vrije Universiteit Amsterdam, Neurology, Epidemiology and Data ScienceAmsterdamThe Netherlands
- Amsterdam Neuroscience, NeurodegenerationAmsterdamThe Netherlands
- Amsterdam UMC location Vrije Universiteit Amsterdam, Epidemiology and Data ScienceAmsterdamThe Netherlands
| | - Mirjam I. Geerlings
- Julius Center for Health Sciences and Primary CareUniversity Medical Center Utrecht and Utrecht UniversityUtrechtThe Netherlands
- Amsterdam Public Health, Aging & Later Life, and Personalized MedicineAmsterdamThe Netherlands
- Amsterdam Neuroscience, Neurodegeneration, and Mood, Anxiety, Psychosis, Stress, and SleepAmsterdamThe Netherlands
- Amsterdam UMC location University of Amsterdam, Department of General PracticeAmsterdamThe Netherlands
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28
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Chen Y, Lu P, Wu S, Yang J, Liu W, Zhang Z, Xu Q. CD163-Mediated Small-Vessel Injury in Alzheimer's Disease: An Exploration from Neuroimaging to Transcriptomics. Int J Mol Sci 2024; 25:2293. [PMID: 38396970 PMCID: PMC10888773 DOI: 10.3390/ijms25042293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 02/10/2024] [Accepted: 02/11/2024] [Indexed: 02/25/2024] Open
Abstract
Patients with Alzheimer's disease (AD) often present with imaging features indicative of small-vessel injury, among which, white-matter hyperintensities (WMHs) are the most prevalent. However, the underlying mechanism of the association between AD and small-vessel injury is still obscure. The aim of this study is to investigate the mechanism of small-vessel injury in AD. Differential gene expression analyses were conducted to identify the genes related to WMHs separately in mild cognitive impairment (MCI) and cognitively normal (CN) subjects from the ADNI database. The WMH-related genes identified in patients with MCI were considered to be associated with small-vessel injury in early AD. Functional enrichment analyses and a protein-protein interaction (PPI) network were performed to explore the pathway and hub genes related to the mechanism of small-vessel injury in MCI. Subsequently, the Boruta algorithm and support vector machine recursive feature elimination (SVM-RFE) algorithm were performed to identify feature-selection genes. Finally, the mechanism of small-vessel injury was analyzed in MCI from the immunological perspectives; the relationship of feature-selection genes with various immune cells and neuroimaging indices were also explored. Furthermore, 5×FAD mice were used to demonstrate the genes related to small-vessel injury. The results of the logistic regression analyses suggested that WMHs significantly contributed to MCI, the early stage of AD. A total of 276 genes were determined as WMH-related genes in patients with MCI, while 203 WMH-related genes were obtained in CN patients. Among them, only 15 genes overlapped and were thus identified as the crosstalk genes. By employing the Boruta and SVM-RFE algorithms, CD163, ALDH3B1, MIR22HG, DTX2, FOLR2, ALDH2, and ZNF23 were recognized as the feature-selection genes linked to small-vessel injury in MCI. After considering the results from the PPI network, CD163 was finally determined as the critical WMH-related gene in MCI. The expression of CD163 was correlated with fractional anisotropy (FA) values in regions that are vulnerable to small-vessel injury in AD. The immunostaining and RT-qPCR results from the verifying experiments demonstrated that the indicators of small-vessel injury presented in the cortical tissue of 5×FAD mice and related to the upregulation of CD163 expression. CD163 may be the most pivotal candidates related to small-vessel injury in early AD.
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Affiliation(s)
- Yuewei Chen
- Health Management Center, Renji Hospital of Medical School, Shanghai Jiao Tong University, Shanghai 200127, China; (Y.C.); (P.L.); (W.L.)
- Department of Neurology, Renji Hospital of Medical School, Shanghai Jiao Tong University, Shanghai 200127, China
- Renji-UNSW CHeBA (Centre for Healthy Brain Ageing of University of New South Wales) Neurocognitive Center, Renji Hospital of Medical School, Shanghai Jiao Tong University, Shanghai 200127, China
| | - Peiwen Lu
- Health Management Center, Renji Hospital of Medical School, Shanghai Jiao Tong University, Shanghai 200127, China; (Y.C.); (P.L.); (W.L.)
- Renji-UNSW CHeBA (Centre for Healthy Brain Ageing of University of New South Wales) Neurocognitive Center, Renji Hospital of Medical School, Shanghai Jiao Tong University, Shanghai 200127, China
| | - Shengju Wu
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Jie Yang
- Health Management Center, Renji Hospital of Medical School, Shanghai Jiao Tong University, Shanghai 200127, China; (Y.C.); (P.L.); (W.L.)
- Department of Neurology, Renji Hospital of Medical School, Shanghai Jiao Tong University, Shanghai 200127, China
- Renji-UNSW CHeBA (Centre for Healthy Brain Ageing of University of New South Wales) Neurocognitive Center, Renji Hospital of Medical School, Shanghai Jiao Tong University, Shanghai 200127, China
| | - Wanwan Liu
- Health Management Center, Renji Hospital of Medical School, Shanghai Jiao Tong University, Shanghai 200127, China; (Y.C.); (P.L.); (W.L.)
| | - Zhijun Zhang
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Qun Xu
- Health Management Center, Renji Hospital of Medical School, Shanghai Jiao Tong University, Shanghai 200127, China; (Y.C.); (P.L.); (W.L.)
- Department of Neurology, Renji Hospital of Medical School, Shanghai Jiao Tong University, Shanghai 200127, China
- Renji-UNSW CHeBA (Centre for Healthy Brain Ageing of University of New South Wales) Neurocognitive Center, Renji Hospital of Medical School, Shanghai Jiao Tong University, Shanghai 200127, China
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29
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Raghavan S, Przybelski SA, Lesnick TG, Fought AJ, Reid RI, Gebre RK, Windham BG, Algeciras‐Schimnich A, Machulda MM, Vassilaki M, Knopman DS, Jack CR, Petersen RC, Graff‐Radford J, Vemuri P. Vascular risk, gait, behavioral, and plasma indicators of VCID. Alzheimers Dement 2024; 20:1201-1213. [PMID: 37932910 PMCID: PMC10916988 DOI: 10.1002/alz.13540] [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: 07/11/2023] [Revised: 10/06/2023] [Accepted: 10/11/2023] [Indexed: 11/08/2023]
Abstract
INTRODUCTION Cost-effective screening tools for vascular contributions to cognitive impairment and dementia (VCID) has significant implications. We evaluated non-imaging indicators of VCID using magnetic resonance imaging (MRI)-measured white matter (WM) damage and hypothesized that these indicators differ based on age. METHODS In 745 participants from the Mayo Clinic Study of Aging (≥50 years of age) with serial WM assessments from diffusion MRI and fluid-attenuated inversion recovery (FLAIR)-MRI, we examined associations between baseline non-imaging indicators (demographics, vascular risk factors [VRFs], gait, behavioral, plasma glial fibrillary acidic protein [GFAP], and plasma neurofilament light chain [NfL]) and WM damage across three age tertiles. RESULTS VRFs and gait were associated with diffusion changes even in low age strata. All measures (VRFs, gait, behavioral, plasma GFAP, plasma NfL) were associated with white matter hyperintensities (WMHs) but mainly in intermediate and high age strata. DISCUSSION Non-imaging indicators of VCID were related to WM damage and may aid in screening participants and assessing outcomes for VCID. HIGHLIGHTS Non-imaging indicators of VCID can aid in prediction of MRI-measured WM damage but their importance differed by age. Vascular risk and gait measures were associated with early VCID changes measured using diffusion MRI. Plasma markers explained variability in WMH across age strata. Most non-imaging measures explained variability in WMH and vascular WM scores in intermediate and older age groups. The framework developed here can be used to evaluate new non-imaging VCID indicators proposed in the future.
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Affiliation(s)
| | | | - Timothy G. Lesnick
- Department of Quantitative Health SciencesMayo ClinicRochesterMinnesotaUSA
| | - Angela J. Fought
- Department of Quantitative Health SciencesMayo ClinicRochesterMinnesotaUSA
| | - Robert I. Reid
- Department of Information TechnologyMayo ClinicRochesterMinnesotaUSA
| | | | - B. Gwen Windham
- Department of MedicineUniversity of Mississippi Medical CenterJacksonUSA
| | | | | | - Maria Vassilaki
- Department of Quantitative Health SciencesMayo ClinicRochesterMinnesotaUSA
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30
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Shir D, Corriveau-Lecavalier N, Graff-Radford J, Machulda MM, Knopman DS, Petersen RC, Nguyen AT, Dickson DW, Jones DT. Case report: pre-symptomatic clinical and metabolic profile in posterior cortical atrophy and dementia with Lewy bodies. Neurocase 2024; 30:1-7. [PMID: 38758704 PMCID: PMC11243756 DOI: 10.1080/13554794.2024.2348223] [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: 11/03/2023] [Accepted: 04/15/2024] [Indexed: 05/19/2024]
Abstract
A research participant was monitored over nearly two decades at Mayo Clinic, undergoing annual neurologic assessments, neuropsychological tests, and multimodal imaging. Initially, he was cognitively normal but developed symptoms consistent with Posterior Cortical Atrophy (PCA) during the study. Early tests indicated mild, yet normal-range declines in language and visuospatial skills. FDG-PET scans revealed increased metabolism in posterior brain regions long before symptoms appeared. Advanced analysis using a novel in-house machine-learning tool predicted concurrent Alzheimer's disease and dementia with Lewy bodies. Autopsy confirmed a mixed neurodegenerative condition with significant Alzheimer's pathology and dense neocortical Lewy bodies. This case underscores the value of longitudinal imaging in predicting complex neurodegenerative diseases, offering vital insights into the early neurocognitive changes associated with PCA and dementia with Lewy bodies.
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Affiliation(s)
- Dror Shir
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Nick Corriveau-Lecavalier
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, 55905, USA
| | | | - Mary M. Machulda
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, 55905, USA
| | | | - Ronald C. Petersen
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Aivi T. Nguyen
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | | | - David T. Jones
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
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31
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da Silva SP, de Castro CCM, Rabelo LN, Engelberth RC, Fernández-Calvo B, Fiuza FP. Neuropathological and sociodemographic factors associated with the cortical amyloid load in aging and Alzheimer's disease. GeroScience 2024; 46:621-643. [PMID: 37870702 PMCID: PMC10828279 DOI: 10.1007/s11357-023-00982-4] [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: 06/06/2023] [Accepted: 10/10/2023] [Indexed: 10/24/2023] Open
Abstract
Alzheimer's disease (AD) is the leading cause of dementia and is characterized by a progressive decline in cognitive abilities. A pathological hallmark of AD is a region-specific accumulation of the amyloid-beta protein (Aβ). Here, we explored the association between regional Aβ deposition, sociodemographic, and local biochemical factors. We quantified the Aβ burden in postmortem cortical samples from parietal (PCx) and temporal (TCx) regions of 27 cognitively unimpaired (CU) and 15 AD donors, aged 78-100 + years. Histological images of Aβ immunohistochemistry and local concentrations of pathological and inflammatory proteins were obtained at the "Aging, Dementia and TBI Study" open database. We used the area fraction fractionator stereological methodology to quantify the Aβ burden in the gray and white matter within each cortical region. We found higher Aβ burdens in the TCx of AD octogenarians compared to CU ones. We also found higher Aβ loads in the PCx of AD nonagenarians than in AD octogenarians. Moreover, AD women exhibited increased Aβ deposition compared to CU women. Interestingly, we observed a negative correlation between education years and Aβ burden in the white matter of both cortices in CU samples. In AD brains, the Aβ40, Aβ42, and pTau181 isoforms of Aβ and Tau proteins were positively correlated with the Aβ burden. Additionally, in the TCx of AD donors, the proinflammatory cytokine TNFα showed a positive correlation with the Aβ load. These novel findings contribute to understanding the interplay between sociodemographic characteristics, local inflammatory signaling, and the development of AD-related pathology in the cerebral cortex.
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Affiliation(s)
- Sayonara P da Silva
- Graduate Program in Neuroengineering, Edmond and Lily Safra International Institute of Neuroscience, Santos Dumont Institute, Macaíba, RN, 59280-000, Brazil
| | - Carla C M de Castro
- Graduate Program in Neuroengineering, Edmond and Lily Safra International Institute of Neuroscience, Santos Dumont Institute, Macaíba, RN, 59280-000, Brazil
| | - Lívia N Rabelo
- Graduate Program in Neuroengineering, Edmond and Lily Safra International Institute of Neuroscience, Santos Dumont Institute, Macaíba, RN, 59280-000, Brazil
- Laboratory of Neurochemical Studies, Department of Physiology and Behavior, Biosciences Center, Federal University of Rio Grande Do Norte, Natal, Brazil
| | - Rovena C Engelberth
- Laboratory of Neurochemical Studies, Department of Physiology and Behavior, Biosciences Center, Federal University of Rio Grande Do Norte, Natal, Brazil
| | - Bernardino Fernández-Calvo
- Department of Psychology, University of Córdoba, Córdoba, Spain
- Maimonides Biomedical Research Institute of Córdoba (IMIBIC), Córdoba, Spain
- Reina Sofia University Hospital, Córdoba, Spain
- Department of Psychology, Federal University of Paraíba, João Pessoa, Brazil
| | - Felipe P Fiuza
- Graduate Program in Neuroengineering, Edmond and Lily Safra International Institute of Neuroscience, Santos Dumont Institute, Macaíba, RN, 59280-000, Brazil.
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32
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Huang J, Biessels GJ, de Leeuw FE, Ii Y, Skoog I, Mok V, Chen C, Hilal S. Cerebral microinfarcts revisited: Detection, causes, and clinical relevance. Int J Stroke 2024; 19:7-15. [PMID: 37470314 DOI: 10.1177/17474930231187979] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/21/2023]
Abstract
Cerebral microinfarcts (CMIs) are small ischemic lesions invisible to the naked eye at brain autopsy, while the larger ones (0.5-4 mm in diameter) have been visualized in-vivo on magnetic resonance imaging (MRI). CMIs can be detected on diffusion-weighted imaging (DWI) as incidental small DWI-positive lesions (ISDPLs) and on structural MRI for those confined to the cortex and in the chronic phase. ISDPLs may evolve into old cortical-CMIs, white matter hyperintensities or disappear depending on their location and size. Novel techniques in neuropathology and neuroimaging facilitate the detection of CMIs, which promotes understanding of these lesions. CMIs have heterogeneous causes, involving both cerebral small- and large-vessel disease as well as heart diseases such as atrial fibrillation and congestive heart failure. The underlying mechanisms incorporate vascular remodeling, inflammation, blood-brain barrier leakage, penetrating venule congestion, cerebral hypoperfusion, and microembolism. CMIs lead to clinical outcomes, including cognitive decline, a higher risk of stroke and mortality, and accelerated neurobehavioral disturbances. It has been suggested that CMIs can impair brain function and connectivity beyond the microinfarct core and are also associated with perilesional and global cortical atrophy. This review aims to summarize recent progress in studies involving both cortical-CMIs and ISDPLs since 2017, including their detection, etiology, risk factors, MRI correlates, and clinical consequences.
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Affiliation(s)
- Jiannan Huang
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
| | - Geert Jan Biessels
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Frank-Erik de Leeuw
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Yuichiro Ii
- Department of Neurology, Mie University Graduate School of Medicine, Tsu, Japan
- Department of Neuroimaging and Pathophysiology, Mie University School of Medicine, Tsu, Japan
| | - Ingmar Skoog
- Institute of Neuroscience and Physiology and Centre for Ageing and Health, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Psychiatry Cognition and Old Age Psychiatry, Sahlgrenska University Hospital, Region Västra Götaland, Mölndal, Sweden
| | - Vincent Mok
- Division of Neurology, Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong
- Lau Tat-chuen Research Centre of Brain Degenerative Diseases in Chinese and Li Ka Shing Institute of Health Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Christopher Chen
- Memory Aging and Cognition Centre, National University Health System, Singapore
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Saima Hilal
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
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Byun JY, Lee MK, Jung SL. Diagnostic Performance Using a Combination of MRI Findings for Evaluating Cognitive Decline. JOURNAL OF THE KOREAN SOCIETY OF RADIOLOGY 2024; 85:184-196. [PMID: 38362402 PMCID: PMC10864162 DOI: 10.3348/jksr.2023.0065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 06/26/2023] [Accepted: 07/08/2023] [Indexed: 02/17/2024]
Abstract
Purpose We investigated potentially promising imaging findings and their combinations in the evaluation of cognitive decline. Materials and Methods This retrospective study included 138 patients with subjective cognitive impairments, who underwent brain MRI. We classified the same group of patients into Alzheimer's disease (AD) and non-AD groups, based on the neuropsychiatric evaluation. We analyzed imaging findings, including white matter hyperintensity (WMH) and cerebral microbleeds (CMBs), using the Kruskal-Wallis test for group comparison, and receiver operating characteristic (ROC) curve analysis for assessing the diagnostic performance of imaging findings. Results CMBs in the lobar or deep locations demonstrated higher prevalence in the patients with AD compared to those in the non-AD group. The presence of lobar CMBs combined with periventricular WMH (area under the ROC curve [AUC] = 0.702 [95% confidence interval: 0.599-0.806], p < 0.001) showed the highest performance in differentiation of AD from non-AD group. Conclusion Combinations of imaging findings can serve as useful additive diagnostic tools in the assessment of cognitive decline.
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Boots EA, Frank RD, Fan WZ, Christianson TJ, Kremers WK, Stricker JL, Machulda MM, Fields JA, Hassenstab J, Graff-Radford J, Vemuri P, Jack CR, Knopman DS, Petersen RC, Stricker NH. Continuous Associations between Remote Self-Administered Cognitive Measures and Imaging Biomarkers of Alzheimer's Disease. J Prev Alzheimers Dis 2024; 11:1467-1479. [PMID: 39350394 PMCID: PMC11436415 DOI: 10.14283/jpad.2024.99] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2024]
Abstract
BACKGROUND Easily accessible and self-administered cognitive assessments that can aid early detection for Alzheimer's disease (AD) dementia risk are critical for timely intervention. OBJECTIVES/DESIGN This cross-sectional study investigated continuous associations between Mayo Test Drive (MTD) - a remote, self-administered, multi-device compatible, web-based cognitive assessment - and AD-related imaging biomarkers. PARTICIPANTS/SETTING 684 adults from the Mayo Clinic Study of Aging and Mayo Clinic Alzheimer's Disease Research Center participated (age=70.4±11.2, 49.7% female). Participants were predominantly cognitively unimpaired (CU; 94.0%). MEASUREMENTS Participants completed (1) brain amyloid and tau PET scans and MRI scans for hippocampal volume (HV) and white matter hyperintensities (WMH); (2) MTD remotely, consisting of the Stricker Learning Span and Symbols Test which combine into an MTD composite; and (3) in-person neuropsychological assessment including measures to obtain Mayo Preclinical Alzheimer's disease Cognitive Composite (Mayo-PACC) and Global-z. Multiple regressions adjusted for age, sex, and education queried associations between imaging biomarkers and scores from remote and in-person cognitive measures. RESULTS Lower performances on MTD were associated with greater amyloid, entorhinal tau, and global tau PET burden, lower HV, and higher WMH. Mayo-PACC and Global-z were associated with all imaging biomarkers except global tau PET burden. MCI/Dementia participants showed lower performance on all MTD measures compared to CU with large effect sizes (Hedge's g's=1.65-2.02), with similar findings for CU versus MCI only (Hedge's g's=1.46-1.83). CONCLUSION MTD is associated with continuous measures of AD-related imaging biomarkers, demonstrating ability to detect subtle cognitive change using a brief, remote assessment in predominantly CU individuals and criterion validity for MTD.
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Affiliation(s)
- E A Boots
- Nikki H. Stricker, Ph.D., ABPP-CN, Mayo Clinic, 200 First Street SW, Rochester, MN 55905; 507-284-2649 (phone), 507-284-4158 (fax), (email)
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Shirzadi Z, Schultz SA, Yau WYW, Joseph-Mathurin N, Fitzpatrick CD, Levin R, Kantarci K, Preboske GM, Jack CR, Farlow MR, Hassenstab J, Jucker M, Morris JC, Xiong C, Karch CM, Levey AI, Gordon BA, Schofield PR, Salloway SP, Perrin RJ, McDade E, Levin J, Cruchaga C, Allegri RF, Fox NC, Goate A, Day GS, Koeppe R, Chui HC, Berman S, Mori H, Sanchez-Valle R, Lee JH, Rosa-Neto P, Ruthirakuhan M, Wu CY, Swardfager W, Benzinger TLS, Sohrabi HR, Martins RN, Bateman RJ, Johnson KA, Sperling RA, Greenberg SM, Schultz AP, Chhatwal JP. Etiology of White Matter Hyperintensities in Autosomal Dominant and Sporadic Alzheimer Disease. JAMA Neurol 2023; 80:1353-1363. [PMID: 37843849 PMCID: PMC10580156 DOI: 10.1001/jamaneurol.2023.3618] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 06/26/2023] [Indexed: 10/17/2023]
Abstract
Importance Increased white matter hyperintensity (WMH) volume is a common magnetic resonance imaging (MRI) finding in both autosomal dominant Alzheimer disease (ADAD) and late-onset Alzheimer disease (LOAD), but it remains unclear whether increased WMH along the AD continuum is reflective of AD-intrinsic processes or secondary to elevated systemic vascular risk factors. Objective To estimate the associations of neurodegeneration and parenchymal and vessel amyloidosis with WMH accumulation and investigate whether systemic vascular risk is associated with WMH beyond these AD-intrinsic processes. Design, Setting, and Participants This cohort study used data from 3 longitudinal cohort studies conducted in tertiary and community-based medical centers-the Dominantly Inherited Alzheimer Network (DIAN; February 2010 to March 2020), the Alzheimer's Disease Neuroimaging Initiative (ADNI; July 2007 to September 2021), and the Harvard Aging Brain Study (HABS; September 2010 to December 2019). Main Outcome and Measures The main outcomes were the independent associations of neurodegeneration (decreases in gray matter volume), parenchymal amyloidosis (assessed by amyloid positron emission tomography), and vessel amyloidosis (evidenced by cerebral microbleeds [CMBs]) with cross-sectional and longitudinal WMH. Results Data from 3960 MRI sessions among 1141 participants were included: 252 pathogenic variant carriers from DIAN (mean [SD] age, 38.4 [11.2] years; 137 [54%] female), 571 older adults from ADNI (mean [SD] age, 72.8 [7.3] years; 274 [48%] female), and 318 older adults from HABS (mean [SD] age, 72.4 [7.6] years; 194 [61%] female). Longitudinal increases in WMH volume were greater in individuals with CMBs compared with those without (DIAN: t = 3.2 [P = .001]; ADNI: t = 2.7 [P = .008]), associated with longitudinal decreases in gray matter volume (DIAN: t = -3.1 [P = .002]; ADNI: t = -5.6 [P < .001]; HABS: t = -2.2 [P = .03]), greater in older individuals (DIAN: t = 6.8 [P < .001]; ADNI: t = 9.1 [P < .001]; HABS: t = 5.4 [P < .001]), and not associated with systemic vascular risk (DIAN: t = 0.7 [P = .40]; ADNI: t = 0.6 [P = .50]; HABS: t = 1.8 [P = .06]) in individuals with ADAD and LOAD after accounting for age, gray matter volume, CMB presence, and amyloid burden. In older adults without CMBs at baseline, greater WMH volume was associated with CMB development during longitudinal follow-up (Cox proportional hazards regression model hazard ratio, 2.63; 95% CI, 1.72-4.03; P < .001). Conclusions and Relevance The findings suggest that increased WMH volume in AD is associated with neurodegeneration and parenchymal and vessel amyloidosis but not with elevated systemic vascular risk. Additionally, increased WMH volume may represent an early sign of vessel amyloidosis preceding the emergence of CMBs.
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Affiliation(s)
- Zahra Shirzadi
- Massachusetts General Hospital, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | - Stephanie A. Schultz
- Massachusetts General Hospital, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | - Wai-Ying W. Yau
- Massachusetts General Hospital, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | | | - Colleen D. Fitzpatrick
- Massachusetts General Hospital, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | - Raina Levin
- Massachusetts General Hospital, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, Minnesota
| | | | | | | | - Jason Hassenstab
- Washington University in St Louis School of Medicine, St Louis, Missouri
| | - Mathias Jucker
- Department of Cellular Neurology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Tübingen, Germany
| | - John C. Morris
- Washington University in St Louis School of Medicine, St Louis, Missouri
| | - Chengjie Xiong
- Washington University in St Louis School of Medicine, St Louis, Missouri
| | - Celeste M. Karch
- Washington University in St Louis School of Medicine, St Louis, Missouri
| | | | - Brian A. Gordon
- Washington University in St Louis School of Medicine, St Louis, Missouri
| | - Peter R. Schofield
- Neuroscience Research Australia, Sydney, New South Wales, Australia
- School of Biomedical Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | | | - Richard J. Perrin
- Washington University in St Louis School of Medicine, St Louis, Missouri
| | - Eric McDade
- Washington University in St Louis School of Medicine, St Louis, Missouri
| | - Johannes Levin
- Department of Neurology, Ludwig-Maximilians-Universität München, German Center for Neurodegenerative Diseases, site Munich, Munich Cluster for Systems Neurology, Munich, Germany
| | - Carlos Cruchaga
- Washington University in St Louis School of Medicine, St Louis, Missouri
| | | | - Nick C. Fox
- UK Dementia Research Institute, University College London, London, United Kingdom
| | - Alison Goate
- Washington University in St Louis School of Medicine, St Louis, Missouri
| | - Gregory S. Day
- Department of Neurology, Mayo Clinic, Jacksonville, Florida
| | - Robert Koeppe
- Department of Radiology, University of Michigan, Ann Arbor
| | - Helena C. Chui
- Keck School of Medicine, University of Southern California, Los Angeles
| | - Sarah Berman
- Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Hiroshi Mori
- Osaka Metropolitan University Medical School, Osaka, Nagaoka Sutoku University, Osaka City, Niigata, Japan
| | | | - Jae-Hong Lee
- Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
| | - Pedro Rosa-Neto
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Myuri Ruthirakuhan
- Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Che-Yuan Wu
- Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Walter Swardfager
- Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | | | - Hamid R. Sohrabi
- Centre for Healthy Ageing, School of Psychology, Health Future Institute, Murdoch University, Perth, Western Australia, Australia
| | - Ralph N. Martins
- School of Medical and Health Sciences, Edith Cowan University, Perth, Western Australia, Australia
| | - Randall J. Bateman
- Washington University in St Louis School of Medicine, St Louis, Missouri
| | - Keith A. Johnson
- Massachusetts General Hospital, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | - Reisa A. Sperling
- Massachusetts General Hospital, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | - Steven M. Greenberg
- Massachusetts General Hospital, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | - Aaron P. Schultz
- Massachusetts General Hospital, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | - Jasmeer P. Chhatwal
- Massachusetts General Hospital, Brigham and Women’s Hospital, Harvard Medical School, Boston
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Li Y, Kalpouzos G, Bäckman L, Qiu C, Laukka EJ. Association of white matter hyperintensity accumulation with domain-specific cognitive decline: a population-based cohort study. Neurobiol Aging 2023; 132:100-108. [PMID: 37776581 DOI: 10.1016/j.neurobiolaging.2023.08.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2023] [Revised: 08/28/2023] [Accepted: 08/29/2023] [Indexed: 10/02/2023]
Abstract
We investigated the association of load and accumulation of white matter hyperintensities (WMHs) with rate of cognitive decline. This population-based study included 510 dementia-free people (age ≥60 years) who had repeated measures of global and regional (lobar, deep, periventricular) WMHs up to 6 years (from 2001-2003 to 2007-2010) and repeated measures of cognitive function (episodic memory, semantic memory, category fluency, letter fluency, executive function, perceptual speed) up to 15 years (from 2001-2004 to 2016-2019). We found that greater baseline loads of global and regional WMHs were associated with faster decline in letter fluency, perceptual speed, and global cognition. Furthermore, faster accumulation of global, deep, and periventricular WMHs was related to accelerated cognitive decline, primarily in perceptual speed. These data show that WMHs are associated with decline in perceptual speed rather than episodic or semantic memory and that cognitive change is more vulnerable to WMH accumulations in deep and periventricular regions.
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Affiliation(s)
- Yuanjing Li
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Grégoria Kalpouzos
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Lars Bäckman
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Chengxuan Qiu
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden.
| | - Erika J Laukka
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden; Stockholm Gerontology Research Center, Stockholm, Sweden.
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Burnham SC, Iaccarino L, Pontecorvo MJ, Fleisher AS, Lu M, Collins EC, Devous MD. A review of the flortaucipir literature for positron emission tomography imaging of tau neurofibrillary tangles. Brain Commun 2023; 6:fcad305. [PMID: 38187878 PMCID: PMC10768888 DOI: 10.1093/braincomms/fcad305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 09/13/2023] [Accepted: 11/14/2023] [Indexed: 01/09/2024] Open
Abstract
Alzheimer's disease is defined by the presence of β-amyloid plaques and neurofibrillary tau tangles potentially preceding clinical symptoms by many years. Previously only detectable post-mortem, these pathological hallmarks are now identifiable using biomarkers, permitting an in vivo definitive diagnosis of Alzheimer's disease. 18F-flortaucipir (previously known as 18F-T807; 18F-AV-1451) was the first tau positron emission tomography tracer to be introduced and is the only Food and Drug Administration-approved tau positron emission tomography tracer (Tauvid™). It has been widely adopted and validated in a number of independent research and clinical settings. In this review, we present an overview of the published literature on flortaucipir for positron emission tomography imaging of neurofibrillary tau tangles. We considered all accessible peer-reviewed literature pertaining to flortaucipir through 30 April 2022. We found 474 relevant peer-reviewed publications, which were organized into the following categories based on their primary focus: typical Alzheimer's disease, mild cognitive impairment and pre-symptomatic populations; atypical Alzheimer's disease; non-Alzheimer's disease neurodegenerative conditions; head-to-head comparisons with other Tau positron emission tomography tracers; and technical considerations. The available flortaucipir literature provides substantial evidence for the use of this positron emission tomography tracer in assessing neurofibrillary tau tangles in Alzheimer's disease and limited support for its use in other neurodegenerative disorders. Visual interpretation and quantitation approaches, although heterogeneous, mostly converge and demonstrate the high diagnostic and prognostic value of flortaucipir in Alzheimer's disease.
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Affiliation(s)
| | | | | | | | - Ming Lu
- Avid, Eli Lilly and Company, Philadelphia, PA 19104, USA
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Lv K, Liu Y, Chen Y, Buch S, Wang Y, Yu Z, Wang H, Zhao C, Fu D, Wang H, Wang B, Zhang S, Luo Y, Haacke EM, Shen W, Chai C, Xia S. The iron burden of cerebral microbleeds contributes to brain atrophy through the mediating effect of white matter hyperintensity. Neuroimage 2023; 281:120370. [PMID: 37716591 DOI: 10.1016/j.neuroimage.2023.120370] [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: 11/11/2022] [Revised: 05/04/2023] [Accepted: 09/08/2023] [Indexed: 09/18/2023] Open
Abstract
The goal of this work was to explore the total iron burden of cerebral microbleeds (CMBs) using a semi-automatic quantitative susceptibility mapping and to establish its effect on brain atrophy through the mediating effect of white matter hyperintensities (WMH). A total of 95 community-dwelling people were enrolled. Quantitative susceptibility mapping (QSM) combined with a dynamic programming algorithm (DPA) was used to measure the characteristics of 1309 CMBs. WMH were evaluated according to the Fazekas scale, and brain atrophy was assessed using a 2D linear measurement method. Histogram analysis was used to explore the distribution of CMBs susceptibility, volume, and total iron burden, while a correlation analysis was used to explore the relationship between volume and susceptibility. Stepwise regression analysis was used to analyze the risk factors for CMBs and their contribution to brain atrophy. Mediation analysis was used to explore the interrelationship between CMBs and brain atrophy. We found that the frequency distribution of susceptibility of the CMBs was Gaussian in nature with a mean of 201 ppb and a standard deviation of 84 ppb; however, the volume and total iron burden of CMBs were more Rician in nature. A weak but significant correlation between the susceptibility and volume of CMBs was found (r = -0.113, P < 0.001). The periventricular WMH (PVWMH) was a risk factor for the presence of CMBs (number: β = 0.251, P = 0.014; volume: β = 0.237, P = 0.042; total iron burden: β = 0.238, P = 0.020) and was a risk factor for brain atrophy (third ventricle width: β = 0.325, P = 0.001; Evans's index: β = 0.323, P = 0.001). PVWMH had a significant mediating effect on the correlation between CMBs and brain atrophy. In conclusion, QSM along with the DPA can measure the total iron burden of CMBs. PVWMH might be a risk factor for CMBs and may mediate the effect of CMBs on brain atrophy.
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Affiliation(s)
- Ke Lv
- Department of Radiology, First Central Clinical College, Tianjin Medical University, Tianjin, China
| | - Yanzhen Liu
- Department of Radiology, Tianjin Chest Hospital, Tianjin, China
| | - Yongsheng Chen
- Department of Neurology, Wayne State University, Detroit, MI, USA
| | - Sagar Buch
- Department of Neurology, Wayne State University, Detroit, MI, USA
| | - Ying Wang
- Magnetic Resonance Innovations, Inc., Bingham Farms, MI, USA; Department of Radiology, Wayne State University, Detroit, MI, USA
| | - Zhuo Yu
- Department of Radiology, First Central Clinical College, Tianjin Medical University, Tianjin, China
| | - Huiying Wang
- The School of Medicine, Nankai University, Tianjin, China
| | - Chenxi Zhao
- Department of Radiology, First Central Clinical College, Tianjin Medical University, Tianjin, China
| | - Dingwei Fu
- Department of Radiology, The Second Affiliated Hospital of Wannan Medical College, Wuhu, Anhui Province, China
| | - Huapeng Wang
- Department of Radiology, First Central Clinical College, Tianjin Medical University, Tianjin, China
| | - Beini Wang
- Department of Radiology, First Central Clinical College, Tianjin Medical University, Tianjin, China
| | | | - Yu Luo
- Department of Radiology, Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Fourth People's Hospital Affiliated to Tongji University School of Medicine, Shanghai, China
| | - E Mark Haacke
- Department of Neurology, Wayne State University, Detroit, MI, USA; Magnetic Resonance Innovations, Inc., Bingham Farms, MI, USA; Department of Radiology, Wayne State University, Detroit, MI, USA; Department of Biomedical Engineering, Wayne State University, Detroit, MI, USA
| | - Wen Shen
- Department of Radiology, Tianjin Institute of Imaging Medicine, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
| | - Chao Chai
- Department of Radiology, Tianjin Institute of Imaging Medicine, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China.
| | - Shuang Xia
- Department of Radiology, Tianjin Institute of Imaging Medicine, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China.
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Eloyan A, Thangarajah M, An N, Borowski BJ, Reddy AL, Aisen P, Dage JL, Foroud T, Ghetti B, Griffin P, Hammers D, Iaccarino L, Jack CR, Kirby K, Kramer J, Koeppe R, Kukull WA, La Joie R, Mundada NS, Murray ME, Nudelman K, Rumbaugh M, Soleimani-Meigooni DN, Toga A, Touroutoglou A, Atri A, Day GS, Duara R, Graff-Radford NR, Honig LS, Jones DT, Masdeu J, Mendez MF, Musiek E, Onyike CU, Rogalski E, Salloway S, Sha S, Turner RS, Wingo TS, Wolk DA, Womack K, Beckett L, Gao S, Carrillo MC, Rabinovici G, Apostolova LG, Dickerson B, Vemuri P. White matter hyperintensities are higher among early-onset Alzheimer's disease participants than their cognitively normal and early-onset nonAD peers: Longitudinal Early-onset Alzheimer's Disease Study (LEADS). Alzheimers Dement 2023; 19 Suppl 9:S89-S97. [PMID: 37491599 PMCID: PMC10808262 DOI: 10.1002/alz.13402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 05/23/2023] [Accepted: 05/24/2023] [Indexed: 07/27/2023]
Abstract
INTRODUCTION We compared white matter hyperintensities (WMHs) in early-onset Alzheimer's disease (EOAD) with cognitively normal (CN) and early-onset amyloid-negative cognitively impaired (EOnonAD) groups in the Longitudinal Early-Onset Alzheimer's Disease Study. METHODS We investigated the role of increased WMH in cognition and amyloid and tau burden. We compared WMH burden of 205 EOAD, 68 EOnonAD, and 89 CN participants in lobar regions using t-tests and analyses of covariance. Linear regression analyses were used to investigate the association between WMH and cognitive impairment and that between amyloid and tau burden. RESULTS EOAD showed greater WMHs compared with CN and EOnonAD participants across all regions with no significant differences between CN and EOnonAD groups. Greater WMHs were associated with worse cognition. Tau burden was positively associated with WMH burden in the EOAD group. DISCUSSION EOAD consistently showed higher WMH volumes. Overall, greater WMHs were associated with worse cognition and higher tau burden in EOAD. HIGHLIGHTS This study represents a comprehensive characterization of WMHs in sporadic EOAD. WMH volumes are associated with tau burden from positron emission tomography (PET) in EOAD, suggesting WMHs are correlated with increasing burden of AD. Greater WMH volumes are associated with worse performance on global cognitive tests. EOAD participants have higher WMH volumes compared with CN and early-onset amyloid-negative cognitively impaired (EOnonAD) groups across all brain regions.
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Affiliation(s)
- Ani Eloyan
- Department of Biostatistics, Center for Statistical Sciences, Brown University, Providence, Rhode Island, USA, 02903
| | - Maryanne Thangarajah
- Department of Biostatistics, Center for Statistical Sciences, Brown University, Providence, Rhode Island, USA, 02903
| | - Na An
- Department of Biostatistics, Center for Statistical Sciences, Brown University, Providence, Rhode Island, USA, 02903
| | - Bret J. Borowski
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA, 55905
| | - Ashritha L. Reddy
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA, 55905
| | - Paul Aisen
- Alzheimer’s Therapeutic Research Institute, University of Southern California, San Diego, California, USA, 92121
| | - Jeffrey L. Dage
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
| | - Bernardino Ghetti
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
- Department of Pathology & Laboratory Medicine Indiana University School of Medicine, Indianapolis, Indiana, USA, 02912
| | - Percy Griffin
- Medical & Scientific Relations Division, Alzheimer’s Association, Chicago, Illinois, USA, 60603
| | - Dustin Hammers
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
| | - Leonardo Iaccarino
- Department of Neurology, University of California – San Francisco, San Francisco, California, USA, 94143
| | - Clifford R. Jack
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
| | - Kala Kirby
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
| | - Joel Kramer
- Department of Neurology, University of California – San Francisco, San Francisco, California, USA, 94143
| | - Robert Koeppe
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA, 48109
| | - Walter A. Kukull
- Department of Epidemiology, University of Washington, Seattle, Washington, USA, 98195
| | - Renaud La Joie
- Department of Neurology, University of California – San Francisco, San Francisco, California, USA, 94143
| | - Nidhi S Mundada
- Department of Neurology, University of California – San Francisco, San Francisco, California, USA, 94143
| | - Melissa E. Murray
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, USA, 32224
| | - Kelly Nudelman
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
| | - Malia Rumbaugh
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
| | | | - Arthur Toga
- Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Los Angeles, California, USA, 90033
| | - Alexandra Touroutoglou
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA, 02114
| | - Alireza Atri
- Banner Sun Health Research Institute, Sun City, Arizona, USA, 85351
| | - Gregory S. Day
- Department of Neurology, Mayo Clinic, Jacksonville, Florida, USA, 32224
| | - Ranjan Duara
- Wien Center for Alzheimer’s Disease and Memory Disorders, Mount Sinai Medical Center, Miami, Florida, USA, 33140
| | | | - Lawrence S. Honig
- Taub Institute and Department of Neurology, Columbia University Irving Medical Center, New York, New York, USA,10032
| | - David T. Jones
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA, 55905
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA, 55905
| | - Joseph Masdeu
- Nantz National Alzheimer Center, Houston Methodist and Weill Cornell Medicine, Houston, Texas, USA, 77030
| | - Mario F. Mendez
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA, 90095
| | - Erik Musiek
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA, 63108
| | - Chiadi U. Onyike
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA, 21205
| | - Emily Rogalski
- Department of Psychiatry and Behavioral Sciences, Mesulam Center for Cognitive Neurology and Alzheimer’s Disease, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA, 60611
| | - Stephen Salloway
- Department of Neurology, Alpert Medical School, Brown University, Providence, Rhode Island, USA, 02912
| | - Sharon Sha
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, California, USA, 94304
| | - Raymond S. Turner
- Department of Neurology, Georgetown University, Washington D.C., USA, 20007
| | - Thomas S. Wingo
- Department of Neurology and Human Genetics, Emory University School of Medicine, Atlanta, Georgia, USA, 30322
| | - David A. Wolk
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA, 19104
| | - Kyle Womack
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA, 63108
| | - Laurel Beckett
- Department of Public Health Sciences, University of California – Davis, Davis, California, USA, 95616
| | - Sujuan Gao
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
| | - Maria C. Carrillo
- Medical & Scientific Relations Division, Alzheimer’s Association, Chicago, Illinois, USA, 60603
| | - Gil Rabinovici
- Department of Neurology, University of California – San Francisco, San Francisco, California, USA, 94143
| | - Liana G. Apostolova
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine Indianapolis, Indianapolis, Indiana, USA, 46202
| | - Brad Dickerson
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA, 02114
| | - Prashanthi Vemuri
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA, 55905
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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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Park H, Kim H, Kwak S, Youm Y, Chey J. Association between Loneliness and Memory Function through White Matter Hyperintensities in Older Adults: The Moderating Role of Gender. Behav Sci (Basel) 2023; 13:869. [PMID: 37887519 PMCID: PMC10604491 DOI: 10.3390/bs13100869] [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: 09/07/2023] [Revised: 10/16/2023] [Accepted: 10/19/2023] [Indexed: 10/28/2023] Open
Abstract
Loneliness has an important impact on memory function in late life. However, the neural mechanism by which loneliness detrimentally influences memory function remains elusive. Furthermore, it remains unclear whether the association between loneliness and memory function varies by gender. The current study aimed to investigate the neural mechanism underlying the association between loneliness and episodic memory function and explore whether it varies with gender among cognitively normal older adults. A total of 173 community-dwelling adults aged 60 years or older from the Korean Social Life, Health, and Aging Project (KSHAP) study (mean age = 71.87) underwent an assessment of loneliness, neuropsychological testing, and structural magnetic resonance imaging. The association between loneliness and episodic memory function was mediated by the volume of white matter hyperintensities (WMHs), but not by hippocampal or gray matter volumes. In addition, the association between loneliness and memory function through WMHs was significantly moderated by gender; specifically, the indirect effect was significant among men but not among women. The study suggests that WMHs may be a potential neurological mechanism that causes late-life memory dysfunction associated with loneliness in older men. The findings underscore the need for gender-specific interventions to mitigate memory impairment associated with late-life loneliness, with significant public health implications.
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Affiliation(s)
- Hyeyoung Park
- Department of Psychology, Seoul National University, Seoul 08826, Republic of Korea; (H.P.); (H.K.)
| | - Hairin Kim
- Department of Psychology, Seoul National University, Seoul 08826, Republic of Korea; (H.P.); (H.K.)
| | - Seyul Kwak
- Department of Psychology, Pusan National University, Busan 46241, Republic of Korea;
| | - Yoosik Youm
- Department of Sociology, Yonsei University, Seoul 03722, Republic of Korea;
| | - Jeanyung Chey
- Department of Psychology, Seoul National University, Seoul 08826, Republic of Korea; (H.P.); (H.K.)
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Wei C, Yu X, Chen Y, Yang T, Li S, Li J, Chen X. Can Patients with Asymptomatic/Mild Illness and Moderate Illness COVID-19 Have White Matter Damage? Int J Gen Med 2023; 16:4585-4593. [PMID: 37840824 PMCID: PMC10576465 DOI: 10.2147/ijgm.s434968] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 10/04/2023] [Indexed: 10/17/2023] Open
Abstract
Background and Purpose Studies have shown that severe coronavirus pandemic 2019 infection could lead to white matter hyperintensities, but the relationship between asymptomatic/mild illness and moderate illness coronavirus pandemic 2019 and white matter hyperintensities remains largely unknown. This study aimed to investigate the relationship between asymptomatic/mild illness and moderate illness coronavirus pandemic 2019 and the risk of white matter hyperintensities. Methods Hospitalized patients who were confirmed to have coronavirus pandemic 2019 for the first time were enrolled. Fazekas scores were used for assessment of the severity of white matter hyperintensities. We also rated the 90-day functional outcome after discharge. Results Of the 157 enrolled patients, 124 (78.98%) coronavirus pandemic 2019 patients were classified as having asymptomatic or mild illness, and 33 (21.02%) were classified as having moderate illness. The results showed that the Fazekas scale scores at baseline (periventricular white matter hyperintensities, 1.31±1.16 vs 2.06±1.20; Deep white matter hyperintensities, 1.04±0.97 vs 1.73±1.13 P <0.01) and at follow-up (periventricular white matter hyperintensities, 1.38±1.21 vs 2.09±1.21; Deep white matter hyperintensities, 1.13±1.04 vs 1.79±1.14 P <0.01) were lower in patients with symptomatic or mild illness than in those with moderate illness. Moreover, no significant difference (7.26% vs 3.03%; P =0.377) was observed between the two divided groups in terms of white matter hyperintensities progression. Conclusion Our findings suggest that moderate COVID-19 is related to severe white matter hyperintensities compared with asymptomatic/mild illness but not to the progression of white matter hyperintensities.
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Affiliation(s)
- Cunsheng Wei
- Department of Neurology, Affiliated Jiangning Hospital with Nanjing Medical University, Nanjing, Jiangsu, 211100, People’s Republic of China
| | - Xiaorong Yu
- Department of Neurology, Affiliated Jiangning Hospital with Nanjing Medical University, Nanjing, Jiangsu, 211100, People’s Republic of China
| | - Yuan Chen
- Department of Neurology, Affiliated Jiangning Hospital with Nanjing Medical University, Nanjing, Jiangsu, 211100, People’s Republic of China
| | - Tingting Yang
- Department of Neurology, Affiliated Jiangning Hospital with Nanjing Medical University, Nanjing, Jiangsu, 211100, People’s Republic of China
| | - Shenghua Li
- Department of Neurology, Affiliated Jiangning Hospital with Nanjing Medical University, Nanjing, Jiangsu, 211100, People’s Republic of China
| | - Junrong Li
- Department of Neurology, Affiliated Jiangning Hospital with Nanjing Medical University, Nanjing, Jiangsu, 211100, People’s Republic of China
| | - Xuemei Chen
- Department of Neurology, Affiliated Jiangning Hospital with Nanjing Medical University, Nanjing, Jiangsu, 211100, People’s Republic of China
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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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Dougherty RJ, Wanigatunga AA, An Y, Tian Q, Simonsick EM, Albert MS, Resnick SM, Schrack JA. Walking energetics and white matter hyperintensities in mid-to-late adulthood. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12501. [PMID: 38026756 PMCID: PMC10646278 DOI: 10.1002/dad2.12501] [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: 06/13/2023] [Revised: 10/11/2023] [Accepted: 10/22/2023] [Indexed: 12/01/2023]
Abstract
INTRODUCTION White matter hyperintensities (WMHs) increase with age and contribute to cognitive and motor function decline. Energy costs for mobility worsen with age, as the energetic cost of walking increases and energetic capacity declines. We examined the cross-sectional associations of multiple measures of walking energetics with WMHs in mid- to late-aged adults. METHODS A total of 601 cognitively unimpaired adults (mean age 66.9 ± 15.3 years, 54% women) underwent brain magnetic resonance imaging scans and completed standardized slow- and peak-paced walking assessments with metabolic measurement (V̇O2). T1-weighted scans and fluid-attenuated inversion recovery images were used to quantify WMHs. Separate multivariable linear regression models examined associations adjusted for covariates. RESULTS Lower slow-paced V̇O2 (B = 0.07; P = 0.030), higher peak-paced V̇O2 (B = -0.10; P = 0.007), and lower cost-to-capacity ratio (B = .12; P < 0.0001) were all associated with lower WMH volumes. DISCUSSION The cost-to-capacity ratio, which describes the percentage of capacity required for ambulation, was the walking energetic measure most strongly associated with WMHs.
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Affiliation(s)
- Ryan J. Dougherty
- Department of NeurologyJohns Hopkins School of MedicineBaltimoreMarylandUSA
- Center on Aging and HealthJohns Hopkins UniversityBaltimoreMarylandUSA
| | - Amal A. Wanigatunga
- Center on Aging and HealthJohns Hopkins UniversityBaltimoreMarylandUSA
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
| | - Yang An
- Intramural Research ProgramNational Institute on AgingBaltimoreMarylandUSA
| | - Qu Tian
- Intramural Research ProgramNational Institute on AgingBaltimoreMarylandUSA
| | | | - Marilyn S. Albert
- Department of NeurologyJohns Hopkins School of MedicineBaltimoreMarylandUSA
| | - Susan M. Resnick
- Intramural Research ProgramNational Institute on AgingBaltimoreMarylandUSA
| | - Jennifer A. Schrack
- Center on Aging and HealthJohns Hopkins UniversityBaltimoreMarylandUSA
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
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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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Hammond TC, Green SJ, Jacobs Y, Chlipala GE, Xing X, Heil S, Chen A, Aware C, Flemister A, Stromberg A, Balchandani P, Lin AL. Gut microbiome association with brain imaging markers, APOE genotype, calcium and vegetable intakes, and obesity in healthy aging adults. Front Aging Neurosci 2023; 15:1227203. [PMID: 37736325 PMCID: PMC10510313 DOI: 10.3389/fnagi.2023.1227203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 08/17/2023] [Indexed: 09/23/2023] Open
Abstract
Introduction Advanced age is a significant factor in changes to brain physiology and cognitive functions. Recent research has highlighted the critical role of the gut microbiome in modulating brain functions during aging, which can be influenced by various factors such as apolipoprotein E (APOE) genetic variance, body mass index (BMI), diabetes, and dietary intake. However, the associations between the gut microbiome and these factors, as well as brain structural, vascular, and metabolic imaging markers, have not been well explored. Methods We recruited 30 community dwelling older adults between age 55-85 in Kentucky. We collected the medical history from the electronic health record as well as the Dietary Screener Questionnaire. We performed APOE genotyping with an oral swab, gut microbiome analysis using metagenomics sequencing, and brain structural, vascular, and metabolic imaging using MRI. Results Individuals with APOE e2 and APOE e4 genotypes had distinct microbiota composition, and higher level of pro-inflammatory microbiota were associated higher BMI and diabetes. In contrast, calcium- and vegetable-rich diets were associated with microbiota that produced short chain fatty acids leading to an anti-inflammatory state. We also found that important gut microbial butyrate producers were correlated with the volume of the thalamus and corpus callosum, which are regions of the brain responsible for relaying and processing information. Additionally, putative proinflammatory species were negatively correlated with GABA production, an inhibitory neurotransmitter. Furthermore, we observed that the relative abundance of bacteria from the family Eggerthellaceae, equol producers, was correlated with white matter integrity in tracts connecting the brain regions related to language, memory, and learning. Discussion These findings highlight the importance of gut microbiome association with brain health in aging population and could have important implications aimed at optimizing healthy brain aging through precision prebiotic, probiotic or dietary interventions.
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Affiliation(s)
- Tyler C. Hammond
- Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY, United States
- Department of Neuroscience, University of Kentucky, Lexington, KY, United States
| | - Stefan J. Green
- Genomics and Microbiome Core Facility, Rush University, Chicago, IL, United States
| | - Yael Jacobs
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - George E. Chlipala
- Research Informatics Core, University of Illinois Chicago, Chicago, IL, United States
| | - Xin Xing
- Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY, United States
- Department of Computer Science, University of Kentucky, Lexington, KY, United States
- Roy Blunt NextGen Precision Health, University of Missouri, Columbia, MO, United States
- Department of Radiology, University of Missouri, Columbia, MO, United States
| | - Sally Heil
- School of Medicine, University of Missouri, Columbia, MO, United States
| | - Anna Chen
- Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY, United States
| | - Chetan Aware
- Roy Blunt NextGen Precision Health, University of Missouri, Columbia, MO, United States
- Department of Radiology, University of Missouri, Columbia, MO, United States
| | - Abeoseh Flemister
- Roy Blunt NextGen Precision Health, University of Missouri, Columbia, MO, United States
- Department of Radiology, University of Missouri, Columbia, MO, United States
| | - Arnold Stromberg
- Dr. Bing Zhang Department of Statistics, University of Kentucky, Lexington, KY, United States
| | - Priti Balchandani
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Ai-Ling Lin
- Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY, United States
- Roy Blunt NextGen Precision Health, University of Missouri, Columbia, MO, United States
- Department of Radiology, University of Missouri, Columbia, MO, United States
- Institute for Data Science and Informatics, University of Missouri, Columbia, MO, United States
- Division of Biological Sciences, University of Missouri, Columbia, MO, United States
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Badji A, Youwakim J, Cooper A, Westman E, Marseglia A. Vascular cognitive impairment - Past, present, and future challenges. Ageing Res Rev 2023; 90:102042. [PMID: 37634888 DOI: 10.1016/j.arr.2023.102042] [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: 01/26/2023] [Revised: 08/22/2023] [Accepted: 08/23/2023] [Indexed: 08/29/2023]
Abstract
Vascular cognitive impairment (VCI) is a lifelong process encompassing a broad spectrum of cognitive disorders, ranging from subtle or mild deficits to prodromal and fully developed dementia, originating from cerebrovascular lesions such as large and small vessel disease. Genetic predisposition and environmental exposure to risk factors such as unhealthy lifestyles, hypertension, cardiovascular disease, and metabolic disorders will synergistically interact, yielding biochemical and structural brain changes, ultimately culminating in VCI. However, little is known about the pathological processes underlying VCI and the temporal dynamics between risk factors and disease mechanisms (biochemical and structural brain changes). This narrative review aims to provide an evidence-based summary of the link between individual vascular risk/disorders and cognitive dysfunction and the potential structural and biochemical pathophysiological processes. We also discuss some key challenges for future research on VCI. There is a need to shift from individual risk factors/disorders to comorbid vascular burden, identifying and integrating imaging and fluid biomarkers, implementing a life-course approach, considering possible neuroprotective influences of positive life exposures, and addressing biological sex at birth and gender differences. Finally, this review highlights the need for future researchers to leverage and integrate multidimensional data to advance our understanding of the mechanisms and pathophysiology of VCI.
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Affiliation(s)
- Atef Badji
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Theme Inflammation and Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Jessica Youwakim
- Department of Pharmacology and Physiology, Université de Montréal, Montreal, QC, Canada; Centre interdisciplinaire de recherche sur le cerveau et l'apprentissage (CIRCA), Montreal, QC, Canada; Groupe de Recherche sur la Signalisation Neuronal et la Circuiterie (SNC), Montreal, QC, Canada
| | - Alexandra Cooper
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Eric Westman
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Anna Marseglia
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.
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Hoost SS, Brickman AM, Manly JJ, Honig LS, Gu Y, Sanchez D, Reyes-Dumeyer D, Lantigua RA, Kang MS, Dage JL, Mayeux R. Effects of Vascular Risk Factors on the Association of Blood-Based Biomarkers with Alzheimer's Disease. MEDICAL RESEARCH ARCHIVES 2023; 11:10.18103/mra.v11i9.4468. [PMID: 38037598 PMCID: PMC10688358 DOI: 10.18103/mra.v11i9.4468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/02/2023]
Abstract
Background Comorbidities may influence the levels of blood-based biomarkers for Alzheimer's disease (AD). We investigated whether differences in risk factors or comorbid conditions might explain the discordance between clinical diagnosis and biomarker classifications in a multi-ethnic cohort of elderly individuals. Aims To evaluate the relationship of medical conditions and other characteristics, including body mass index (BMI), vascular risk factors, and head injury, with cognitive impairment and blood-based biomarkers of AD, phosphorylated tau (P-tau 181, P-tau 217), in a multi-ethnic cohort. Methods Three-hundred individuals, aged 65 and older, were selected from a prospective community-based cohort for equal representation among three racial/ethnic groups: non-Hispanic White, Hispanic/Latino and African American/Black. Participants were classified into four groups based on absence (Asym) or presence (Sym) of cognitive impairment and low (NEG) or high (POS) P-tau 217 or P-tau 181 levels, determined previously in the same cohort: (Asym/NEG, Asym/POS, Sym/NEG, Sym/POS). We examined differences in individual characteristics across the four groups. We performed post-hoc analysis examining the differences across biomarker and cognitive status. Results P-tau 217 or P-tau 181 positive individuals had lower BMI than P-tau negative participants, regardless of symptom status. Symptomatic and asymptomatic participants did not differ in terms of BMI. BMI was not a mediator of the effect of P-tau 217 or P-tau 181 on dementia. Frequencies of other risk factors did not differ between the four groups of individuals. Conclusions Participants with higher levels of P-tau 217 or P-tau 181 consistent with AD had lower BMI regardless of whether the individual was symptomatic. These findings suggest that weight loss may change with AD biomarker levels before onset of cognitive decline. They do not support BMI as a confounding variable. Further longitudinal studies could explore the relationship of risk factors with clinical diagnoses and biomarkers.
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Affiliation(s)
- SS Hoost
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, and the New York Presbyterian Hospital, New York, NY
| | - AM Brickman
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY
- G.H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, and the New York Presbyterian Hospital, New York, NY
| | - JJ Manly
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY
- G.H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, and the New York Presbyterian Hospital, New York, NY
| | - LS Honig
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY
- G.H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, and the New York Presbyterian Hospital, New York, NY
| | - Y Gu
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY
- G.H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, and the New York Presbyterian Hospital, New York, NY
| | - D Sanchez
- G.H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, and the New York Presbyterian Hospital, New York, NY
| | - D Reyes-Dumeyer
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY
- G.H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, and the New York Presbyterian Hospital, New York, NY
| | - RA Lantigua
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY
- G.H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY
- Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, and the New York Presbyterian Hospital, New York, NY
| | - MS Kang
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY
| | - JL Dage
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine Indianapolis IN
| | - R Mayeux
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY
- G.H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, and the New York Presbyterian Hospital, New York, NY
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McKay NS, Gordon BA, Hornbeck RC, Dincer A, Flores S, Keefe SJ, Joseph-Mathurin N, Jack CR, Koeppe R, Millar PR, Ances BM, Chen CD, Daniels A, Hobbs DA, Jackson K, Koudelis D, Massoumzadeh P, McCullough A, Nickels ML, Rahmani F, Swisher L, Wang Q, Allegri RF, Berman SB, Brickman AM, Brooks WS, Cash DM, Chhatwal JP, Day GS, Farlow MR, la Fougère C, Fox NC, Fulham M, Ghetti B, Graff-Radford N, Ikeuchi T, Klunk W, Lee JH, Levin J, Martins R, Masters CL, McConathy J, Mori H, Noble JM, Reischl G, Rowe C, Salloway S, Sanchez-Valle R, Schofield PR, Shimada H, Shoji M, Su Y, Suzuki K, Vöglein J, Yakushev I, Cruchaga C, Hassenstab J, Karch C, McDade E, Perrin RJ, Xiong C, Morris JC, Bateman RJ, Benzinger TLS. Positron emission tomography and magnetic resonance imaging methods and datasets within the Dominantly Inherited Alzheimer Network (DIAN). Nat Neurosci 2023; 26:1449-1460. [PMID: 37429916 PMCID: PMC10400428 DOI: 10.1038/s41593-023-01359-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 05/15/2023] [Indexed: 07/12/2023]
Abstract
The Dominantly Inherited Alzheimer Network (DIAN) is an international collaboration studying autosomal dominant Alzheimer disease (ADAD). ADAD arises from mutations occurring in three genes. Offspring from ADAD families have a 50% chance of inheriting their familial mutation, so non-carrier siblings can be recruited for comparisons in case-control studies. The age of onset in ADAD is highly predictable within families, allowing researchers to estimate an individual's point in the disease trajectory. These characteristics allow candidate AD biomarker measurements to be reliably mapped during the preclinical phase. Although ADAD represents a small proportion of AD cases, understanding neuroimaging-based changes that occur during the preclinical period may provide insight into early disease stages of 'sporadic' AD also. Additionally, this study provides rich data for research in healthy aging through inclusion of the non-carrier controls. Here we introduce the neuroimaging dataset collected and describe how this resource can be used by a range of researchers.
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Affiliation(s)
| | | | | | - Aylin Dincer
- Washington University in St. Louis, St. Louis, MO, USA
| | - Shaney Flores
- Washington University in St. Louis, St. Louis, MO, USA
| | - Sarah J Keefe
- Washington University in St. Louis, St. Louis, MO, USA
| | | | | | | | | | - Beau M Ances
- Washington University in St. Louis, St. Louis, MO, USA
| | | | | | - Diana A Hobbs
- Washington University in St. Louis, St. Louis, MO, USA
| | | | | | | | | | | | | | - Laura Swisher
- Washington University in St. Louis, St. Louis, MO, USA
| | - Qing Wang
- Washington University in St. Louis, St. Louis, MO, USA
| | | | | | - Adam M Brickman
- Columbia University Irving Medical Center, New York, NY, USA
| | - William S Brooks
- Neuroscience Research Australia, Sydney, New South Wales, Australia
| | - David M Cash
- UK Dementia Research Institute at University College London, London, UK
- University College London, London, UK
| | - Jasmeer P Chhatwal
- Massachusetts General and Brigham & Women's Hospitals, Harvard Medical School, Boston, MA, USA
| | | | | | - Christian la Fougère
- Department of Radiology, University of Tübingen, Tübingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Nick C Fox
- UK Dementia Research Institute at University College London, London, UK
- University College London, London, UK
| | - Michael Fulham
- Royal Prince Alfred Hospital, Sydney, New South Wales, Australia
| | | | | | | | | | | | - Johannes Levin
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Ralph Martins
- Edith Cowan University, Joondalup, Western Australia, Australia
| | | | | | | | - James M Noble
- Columbia University Irving Medical Center, New York, NY, USA
| | - Gerald Reischl
- Department of Radiology, University of Tübingen, Tübingen, Germany
| | | | | | - Raquel Sanchez-Valle
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, IDIBAPS, University of Barcelona, Barcelona, Spain
| | - Peter R Schofield
- Neuroscience Research Australia, Sydney, New South Wales, Australia
- School of Biomedical Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | | | | | - Yi Su
- Banner Alzheimer's Institute, Phoenix, AZ, USA
| | | | - Jonathan Vöglein
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
- Department of Neurology, Ludwig-Maximilians-Universität München, München, Germany
| | - Igor Yakushev
- School of Medicine, Technical University of Munich, Munich, Germany
| | | | | | - Celeste Karch
- Washington University in St. Louis, St. Louis, MO, USA
| | - Eric McDade
- Washington University in St. Louis, St. Louis, MO, USA
| | | | | | - John C Morris
- Washington University in St. Louis, St. Louis, MO, USA
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50
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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: 19] [Impact Index Per Article: 19.0] [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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