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Malla S, Bryant AG, Jayakumar R, Woost B, Wolf N, Li A, Das S, van Veluw SJ, Bennett RE. Molecular profiling of frontal and occipital subcortical white matter hyperintensities in Alzheimer's disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.13.598845. [PMID: 38915516 PMCID: PMC11195168 DOI: 10.1101/2024.06.13.598845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
White matter hyperintensities (WMHs) are commonly detected on T2-weighted magnetic resonance imaging (MRI) scans, occurring in both typical aging and Alzheimer's disease. Despite their frequent appearance and their association with cognitive decline, the molecular factors contributing to WMHs remain unclear. In this study, we investigated the transcriptomic profiles of two commonly affected brain regions with coincident AD pathology-frontal subcortical white matter (frontal-WM) and occipital subcortical white matter (occipital-WM)-and compared with age-matched healthy controls. Through RNA-sequencing in frontal- and occipital-WM bulk tissues, we identified an upregulation of genes associated with brain vasculature function in AD white matter. To further elucidate vasculature-specific transcriptomic features, we performed RNA-seq analysis on blood vessels isolated from these white matter regions, which revealed an upregulation of genes related to protein folding pathways. Finally, comparing gene expression profiles between AD individuals with high- versus low-WMH burden showed an increased expression of pathways associated with immune function. Taken together, our study characterizes the diverse molecular profiles of white matter changes in AD compared to normal aging and provides new mechanistic insights processes underlying AD-related WMHs.
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Affiliation(s)
- Sulochan Malla
- Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Annie G Bryant
- Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
- School of Physics, The University of Sydney, Sydney, Australia
| | - Rojashree Jayakumar
- Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
| | - Benjamin Woost
- Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
| | - Nina Wolf
- Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
| | - Andrew Li
- Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
| | - Sudeshna Das
- Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Susanne J van Veluw
- Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Rachel E Bennett
- Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
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Bachmann D, von Rickenbach B, Buchmann A, Hüllner M, Zuber I, Studer S, Saake A, Rauen K, Gruber E, Nitsch RM, Hock C, Treyer V, Gietl A. White matter hyperintensity patterns: associations with comorbidities, amyloid, and cognition. Alzheimers Res Ther 2024; 16:67. [PMID: 38561806 PMCID: PMC10983708 DOI: 10.1186/s13195-024-01435-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 03/23/2024] [Indexed: 04/04/2024]
Abstract
BACKGROUND White matter hyperintensities (WMHs) are often measured globally, but spatial patterns of WMHs could underlie different risk factors and neuropathological and clinical correlates. We investigated the spatial heterogeneity of WMHs and their association with comorbidities, Alzheimer's disease (AD) risk factors, and cognition. METHODS In this cross-sectional study, we studied 171 cognitively unimpaired (CU; median age: 65 years, range: 50 to 89) and 51 mildly cognitively impaired (MCI; median age: 72, range: 53 to 89) individuals with available amyloid (18F-flutementamol) PET and FLAIR-weighted images. Comorbidities were assessed using the Cumulative Illness Rating Scale (CIRS). Each participant's white matter was segmented into 38 parcels, and WMH volume was calculated in each parcel. Correlated principal component analysis was applied to the parceled WMH data to determine patterns of WMH covariation. Adjusted and unadjusted linear regression models were used to investigate associations of component scores with comorbidities and AD-related factors. Using multiple linear regression, we tested whether WMH component scores predicted cognitive performance. RESULTS Principal component analysis identified four WMH components that broadly describe FLAIR signal hyperintensities in posterior, periventricular, and deep white matter regions, as well as basal ganglia and thalamic structures. In CU individuals, hypertension was associated with all patterns except the periventricular component. MCI individuals showed more diverse associations. The posterior and deep components were associated with renal disorders, the periventricular component was associated with increased amyloid, and the subcortical gray matter structures was associated with sleep disorders, endocrine/metabolic disorders, and increased amyloid. In the combined sample (CU + MCI), the main effects of WMH components were not associated with cognition but predicted poorer episodic memory performance in the presence of increased amyloid. No interaction between hypertension and the number of comorbidities on component scores was observed. CONCLUSION Our study underscores the significance of understanding the regional distribution patterns of WMHs and the valuable insights that risk factors can offer regarding their underlying causes. Moreover, patterns of hyperintensities in periventricular regions and deep gray matter structures may have more pronounced cognitive implications, especially when amyloid pathology is also present.
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Affiliation(s)
- Dario Bachmann
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland.
- Department of Health Sciences and Technology, ETH Zürich, 8093, Zurich, Switzerland.
| | | | - Andreas Buchmann
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
| | - Martin Hüllner
- Department of Nuclear Medicine, University Hospital of Zurich, University of Zurich, 8091, Zurich, Switzerland
| | - Isabelle Zuber
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
| | - Sandro Studer
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
| | - Antje Saake
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
| | - Katrin Rauen
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
- Department of Geriatric Psychiatry, Psychiatric Hospital Zurich, 8032, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich, 8057, Zurich, Switzerland
| | - Esmeralda Gruber
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
| | - Roger M Nitsch
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
- Neurimmune AG, 8952, Zurich, Schlieren, Switzerland
| | - Christoph Hock
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
- Neurimmune AG, 8952, Zurich, Schlieren, Switzerland
| | - Valerie Treyer
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
- Department of Nuclear Medicine, University Hospital of Zurich, University of Zurich, 8091, Zurich, Switzerland
| | - Anton Gietl
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
- Department of Geriatric Psychiatry, Psychiatric Hospital Zurich, 8032, Zurich, Switzerland
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Iandolo R, Avci E, Bommarito G, Sandvig I, Rohweder G, Sandvig A. Characterizing upper extremity fine motor function in the presence of white matter hyperintensities: A 7 T MRI cross-sectional study in older adults. Neuroimage Clin 2024; 41:103569. [PMID: 38281363 PMCID: PMC10839532 DOI: 10.1016/j.nicl.2024.103569] [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: 07/10/2023] [Revised: 01/19/2024] [Accepted: 01/21/2024] [Indexed: 01/30/2024]
Abstract
BACKGROUND White matter hyperintensities (WMH) are a prevalent radiographic finding in the aging brain studies. Research on WMH association with motor impairment is mostly focused on the lower-extremity function and further investigation on the upper-extremity is needed. How different degrees of WMH burden impact the network of activation recruited during upper limb motor performance could provide further insight on the complex mechanisms of WMH pathophysiology and its interaction with aging and neurological disease processes. METHODS 40 healthy elderly subjects without a neurological/psychiatric diagnosis were included in the study (16F, mean age 69.3 years). All subjects underwent ultra-high field 7 T MRI including structural and finger tapping task-fMRI. First, we quantified the WMH lesion load and its spatial distribution. Secondly, we performed a data-driven stratification of the subjects according to their periventricular and deep WMH burdens. Thirdly, we investigated the distribution of neural recruitment and the corresponding activity assessed through BOLD signal changes among different brain regions for groups of subjects. We clustered the degree of WMH based on location, numbers, and volume into three categories; ranging from mild, moderate, and severe. Finally, we explored how the spatial distribution of WMH, and activity elicited during task-fMRI relate to motor function, measured with the 9-Hole Peg Test. RESULTS Within our population, we found three subgroups of subjects, partitioned according to their periventricular and deep WMH lesion load. We found decreased activity in several frontal and cingulate cortex areas in subjects with a severe WMH burden. No statistically significant associations were found when performing the brain-behavior statistical analysis for structural or functional data. CONCLUSION WMH burden has an effect on brain activity during fine motor control and the activity changes are associated with varying degrees of the total burden and distributions of WMH lesions. Collectively, our results shed new light on the potential impact of WMH on motor function in the context of aging and neurodegeneration.
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Affiliation(s)
- Riccardo Iandolo
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
| | - Esin Avci
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
| | - Giulia Bommarito
- Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Ioanna Sandvig
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Gitta Rohweder
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway; Stroke Unit, Department of Medicine, St Olav's University Hospital, Trondheim, Norway
| | - Axel Sandvig
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway; Department of Neurology and Clinical Neurophysiology, St. Olav's University Hospital, Trondheim, Norway; Department of Clinical Neurosciences, Division of Neuro, Head and Neck, Umeå University Hospital, Umeå, Sweden; Department of Community Medicine and Rehabilitation, Umeå University Hospital, Umeå, Sweden.
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Duchesne J, Carrière I, Artero S, Brickman AM, Maller J, Meslin C, Chen J, Vienneau D, de Hoogh K, Jacquemin B, Berr C, Mortamais M. Ambient Air Pollution Exposure and Cerebral White Matter Hyperintensities in Older Adults: A Cross-Sectional Analysis in the Three-City Montpellier Study. ENVIRONMENTAL HEALTH PERSPECTIVES 2023; 131:107013. [PMID: 37878794 PMCID: PMC10599635 DOI: 10.1289/ehp12231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 09/28/2023] [Accepted: 10/04/2023] [Indexed: 10/27/2023]
Abstract
BACKGROUND Growing epidemiological evidence suggests an adverse relationship between exposure to air pollutants and cognitive health, and this could be related to the effect of air pollution on vascular health. OBJECTIVE We aim to evaluate the association between air pollution exposure and a magnetic resonance imaging (MRI) marker of cerebral vascular burden, white matter hyperintensities (WMH). METHODS This cross-sectional analysis used data from the French Three-City Montpellier study. Randomly selected participants 65-80 years of age underwent an MRI examination to estimate their total and regional cerebral WMH volumes. Exposure to fine particulate matter (PM 2.5 ), nitrogen dioxide (NO 2 ), and black carbon (BC) at the participants' residential address during the 5 years before the MRI examination was estimated with land use regression models. Multinomial and binomial logistic regression assessed the associations between exposure to each of the three pollutants and categories of total and lobar WMH volumes. RESULTS Participants' (n = 582 ) median age at MRI was 70.7 years [interquartile range (IQR): 6.1], and 52% (n = 300 ) were women. Median exposure to air pollution over the 5 years before MRI acquisition was 24.3 (IQR: 1.7) μ g / m 3 for PM 2.5 , 48.9 (14.6) μ g / m 3 for NO 2 , and 2.66 (0.60) 10 - 5 / m for BC. We found no significant association between exposure to the three air pollutants and total WMH volume. We found that PM 2.5 exposure was significantly associated with higher risk of temporal lobe WMH burden [odds ratio (OR) for an IQR increase = 1.82 (95% confidence interval: 1.41, 2.36) for the second volume tercile, 2.04 (1.59, 2.61) for the third volume tercile, reference: first volume tercile]. Associations for other regional WMH volumes were inconsistent. CONCLUSION In this population-based study in older adults, PM 2.5 exposure was associated with increased risk of high WMH volume in the temporal lobe, strengthening the evidence on PM 2.5 adverse effect on the brain. Further studies looking at different markers of cerebrovascular damage are still needed to document the potential vascular effects of air pollution. https://doi.org/10.1289/EHP12231.
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Affiliation(s)
- Jeanne Duchesne
- Institute for Neurosciences of Montpellier (INM), University of Montpellier, Inserm, Montpellier, France
| | - Isabelle Carrière
- Institute for Neurosciences of Montpellier (INM), University of Montpellier, Inserm, Montpellier, France
| | - Sylvaine Artero
- Institute of Functional Genomics (IGF), University of Montpellier, CNRS, Inserm, Montpellier, France
| | - Adam M. Brickman
- Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, The Gertrude H. Sergievsky Center, Department of Neurology, Columbia University, New York, New York, USA
| | - Jerome Maller
- Monash Alfred Psychiatry Research Centre, Melbourne, Victoria, Australia
- General Electric Healthcare, Richmond, Victoria, Australia
| | - Chantal Meslin
- Centre for Mental Health Research, Australian National University, Canberra, Australia
| | - Jie Chen
- Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, the Netherlands
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Danielle Vienneau
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
| | - Kees de Hoogh
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
| | - Bénédicte Jacquemin
- Irset Institut de Recherche en Santé, Environnement et Travail, UMR-S 1085, Inserm, University of Rennes, EHESP, Rennes, France
| | - Claudine Berr
- Institute for Neurosciences of Montpellier (INM), University of Montpellier, Inserm, Montpellier, France
| | - Marion Mortamais
- Institute for Neurosciences of Montpellier (INM), University of Montpellier, Inserm, Montpellier, France
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Tap L, Vernooij MW, Wolters F, van den Berg E, Mattace-Raso FUS. New horizons in cognitive and functional impairment as a consequence of cerebral small vessel disease. Age Ageing 2023; 52:afad148. [PMID: 37585592 PMCID: PMC10431695 DOI: 10.1093/ageing/afad148] [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: 03/21/2023] [Revised: 06/06/2023] [Indexed: 08/18/2023] Open
Abstract
Cerebral small vessel disease (cSVD) is a frequent finding in imaging of the brain in older adults, especially in the concomitance of cardiovascular disease risk factors. Despite the well-established link between cSVD and (vascular) cognitive impairment (VCI), it remains uncertain how and when these vascular alterations lead to cognitive decline. The extent of acknowledged markers of cSVD is at best modestly associated with the severity of clinical symptoms, but technological advances increasingly allow to identify and quantify the extent and perhaps also the functional impact of cSVD more accurately. This will facilitate a more accurate diagnosis of VCI, against the backdrop of concomitant other neurodegenerative pathology, and help to identify persons with the greatest risk of cognitive and functional deterioration. In this study, we discuss how better assessment of cSVD using refined neuropsychological and comprehensive geriatric assessment as well as modern image analysis techniques may improve diagnosis and possibly the prognosis of VCI. Finally, we discuss new avenues in the treatment of cSVD and outline how these contemporary insights into cSVD can contribute to optimise screening and treatment strategies in older adults with cognitive impairment and multimorbidity.
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Affiliation(s)
- Lisanne Tap
- Department of Internal Medicine, Section of Geriatric Medicine and Alzheimer Center Erasmus MC, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Meike W Vernooij
- Department of Radiology and Nuclear Medicine and Alzheimer Center Erasmus MC, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Frank Wolters
- Department of Epidemiology and Alzheimer Center Erasmus MC, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Esther van den Berg
- Department of Neurology and Alzheimer Center Erasmus MC, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Francesco U S Mattace-Raso
- Department of Internal Medicine, Section of Geriatric Medicine and Alzheimer Center Erasmus MC, Erasmus MC University Medical Center, Rotterdam, The Netherlands
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Mohanannair Geethadevi G, Quinn TJ, George J, Anstey KJ, Bell JS, Sarwar MR, Cross AJ. Multi-domain prognostic models used in middle-aged adults without known cognitive impairment for predicting subsequent dementia. Cochrane Database Syst Rev 2023; 6:CD014885. [PMID: 37265424 PMCID: PMC10239281 DOI: 10.1002/14651858.cd014885.pub2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
BACKGROUND Dementia, a global health priority, has no current cure. Around 50 million people worldwide currently live with dementia, and this number is expected to treble by 2050. Some health conditions and lifestyle behaviours can increase or decrease the risk of dementia and are known as 'predictors'. Prognostic models combine such predictors to measure the risk of future dementia. Models that can accurately predict future dementia would help clinicians select high-risk adults in middle age and implement targeted risk reduction. OBJECTIVES Our primary objective was to identify multi-domain prognostic models used in middle-aged adults (aged 45 to 65 years) for predicting dementia or cognitive impairment. Eligible multi-domain prognostic models involved two or more of the modifiable dementia predictors identified in a 2020 Lancet Commission report and a 2019 World Health Organization (WHO) report (less education, hearing loss, traumatic brain injury, hypertension, excessive alcohol intake, obesity, smoking, depression, social isolation, physical inactivity, diabetes mellitus, air pollution, poor diet, and cognitive inactivity). Our secondary objectives were to summarise the prognostic models, to appraise their predictive accuracy (discrimination and calibration) as reported in the development and validation studies, and to identify the implications of using dementia prognostic models for the management of people at a higher risk for future dementia. SEARCH METHODS We searched MEDLINE, Embase, PsycINFO, CINAHL, and ISI Web of Science Core Collection from inception until 6 June 2022. We performed forwards and backwards citation tracking of included studies using the Web of Science platform. SELECTION CRITERIA: We included development and validation studies of multi-domain prognostic models. The minimum eligible follow-up was five years. Our primary outcome was an incident clinical diagnosis of dementia based on validated diagnostic criteria, and our secondary outcome was dementia or cognitive impairment determined by any other method. DATA COLLECTION AND ANALYSIS Two review authors independently screened the references, extracted data using a template based on the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies (CHARMS), and assessed risk of bias and applicability of included studies using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). We synthesised the C-statistics of models that had been externally validated in at least three comparable studies. MAIN RESULTS: We identified 20 eligible studies; eight were development studies and 12 were validation studies. There were 14 unique prognostic models: seven models with validation studies and seven models with development-only studies. The models included a median of nine predictors (range 6 to 34); the median number of modifiable predictors was five (range 2 to 11). The most common modifiable predictors in externally validated models were diabetes, hypertension, smoking, physical activity, and obesity. In development-only models, the most common modifiable predictors were obesity, diabetes, hypertension, and smoking. No models included hearing loss or air pollution as predictors. Nineteen studies had a high risk of bias according to the PROBAST assessment, mainly because of inappropriate analysis methods, particularly lack of reported calibration measures. Applicability concerns were low for 12 studies, as their population, predictors, and outcomes were consistent with those of interest for this review. Applicability concerns were high for nine studies, as they lacked baseline cognitive screening or excluded an age group within the range of 45 to 65 years. Only one model, Cardiovascular Risk Factors, Ageing, and Dementia (CAIDE), had been externally validated in multiple studies, allowing for meta-analysis. The CAIDE model included eight predictors (four modifiable predictors): age, education, sex, systolic blood pressure, body mass index (BMI), total cholesterol, physical activity and APOEƐ4 status. Overall, our confidence in the prediction accuracy of CAIDE was very low; our main reasons for downgrading the certainty of the evidence were high risk of bias across all the studies, high concern of applicability, non-overlapping confidence intervals (CIs), and a high degree of heterogeneity. The summary C-statistic was 0.71 (95% CI 0.66 to 0.76; 3 studies; very low-certainty evidence) for the incident clinical diagnosis of dementia, and 0.67 (95% CI 0.61 to 0.73; 3 studies; very low-certainty evidence) for dementia or cognitive impairment based on cognitive scores. Meta-analysis of calibration measures was not possible, as few studies provided these data. AUTHORS' CONCLUSIONS We identified 14 unique multi-domain prognostic models used in middle-aged adults for predicting subsequent dementia. Diabetes, hypertension, obesity, and smoking were the most common modifiable risk factors used as predictors in the models. We performed meta-analyses of C-statistics for one model (CAIDE), but the summary values were unreliable. Owing to lack of data, we were unable to meta-analyse the calibration measures of CAIDE. This review highlights the need for further robust external validations of multi-domain prognostic models for predicting future risk of dementia in middle-aged adults.
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Affiliation(s)
| | - Terry J Quinn
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Johnson George
- Centre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Melbourne, Australia
- Faculty of Medicine, Nursing and Health Sciences, School of Public Health and Preventive Medicine, Melbourne, Australia
| | - Kaarin J Anstey
- School of Psychology, The University of New South Wales, Sydney, Australia
- Ageing Futures Institute, The University of New South Wales, Sydney, Australia
| | - J Simon Bell
- Centre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Melbourne, Australia
| | - Muhammad Rehan Sarwar
- Centre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Melbourne, Australia
| | - Amanda J Cross
- Centre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Melbourne, Australia
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Pan Y, Shen J, Cai X, Chen H, Zong G, Zhu W, Jing J, Liu T, Jin A, Wang Y, Meng X, Yuan C, Wang Y. Adherence to a healthy lifestyle and brain structural imaging markers. Eur J Epidemiol 2023:10.1007/s10654-023-00992-8. [PMID: 37060500 DOI: 10.1007/s10654-023-00992-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 03/13/2023] [Indexed: 04/16/2023]
Abstract
Previous research has linked specific modifiable lifestyle factors to age-related cognitive decline in adults. Little is known about the potential role of an overall healthy lifestyle in brain structure. We examined the association of adherence to a healthy lifestyle with a panel of brain structural markers among 2,413 participants in PolyvasculaR Evaluation for Cognitive Impairment and vaScular Events (PRECISE) study in China and 19,822 participants in UK Biobank (UKB). A healthy lifestyle score (0-5) was constructed based on five modifiable lifestyle factors: diet, physical activity, smoking, alcohol consumption, and body mass index. Validated multimodal neuroimaging markers were derived from brain magnetic resonance imaging. In the cross-sectional analysis of PRECISE, participants who adopted four or five low-risk lifestyle factors had larger total brain volume (TBV; β = 0.12, 95% CI: - 0.02, 0.26; p-trend = 0.05) and gray matter volume (GMV; β = 0.16, 95% CI: 0.01, 0.30; p-trend = 0.05), smaller white matter hyperintensity volume (WMHV; β = - 0.35, 95% CI: - 0.50, - 0.20; p-trend < 0.001) and lower odds of lacune (Odds Ratio [OR] = 0.48, 95% CI: 0.22, 1.08; p-trend = 0.03), compared to those with zero or one low-risk factors. Meanwhile, in the prospective analysis in UKB (with a median of 7.7 years' follow-up), similar associations were observed between the number of low-risk lifestyle factors (4-5 vs. 0-1) and TBV (β = 0.22, 95% CI: 0.16, 0.28; p-trend < 0.001), GMV (β = 0.26, 95% CI: 0.21, 0.32; p-trend < 0.001), white matter volume (WMV; β = 0.08, 95% CI: 0.01, 0.15; p-trend = 0.001), hippocampus volume (β = 0.15, 95% CI: 0.08, 0.22; p-trend < 0.001), and WMHV burden (β = - 0.23, 95% CI: - 0.29, - 0.17; p-trend < 0.001). Those with four or five low-risk lifestyle factors showed approximately 2.0-5.8 years of delay in aging of brain structure. Adherence to a healthier lifestyle was associated with a lower degree of neurodegeneration-related brain structural markers in middle-aged and older adults.
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Affiliation(s)
- Yuesong Pan
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Jie Shen
- School of Public Health, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xueli Cai
- Department of Neurology, Lishui Hospital, Zhejiang University School of Medicine, Lishui, China
| | - Hui Chen
- School of Public Health, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Geng Zong
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Wanlin Zhu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Jing Jing
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Tao Liu
- Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, China
- Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beijing, China
| | - Aoming Jin
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yilong Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Xia Meng
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Changzheng Yuan
- School of Public Health, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, USA.
| | - Yongjun Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
- China National Clinical Research Center for Neurological Diseases, Beijing, China.
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China.
- Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China.
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Trofimova O, Latypova A, DiDomenicantonio G, Lutti A, de Lange AMG, Kliegel M, Stringhini S, Marques-Vidal P, Vaucher J, Vollenweider P, Strippoli MPF, Preisig M, Kherif F, Draganski B. Topography of associations between cardiovascular risk factors and myelin loss in the ageing human brain. Commun Biol 2023; 6:392. [PMID: 37037939 PMCID: PMC10086032 DOI: 10.1038/s42003-023-04741-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 03/21/2023] [Indexed: 04/12/2023] Open
Abstract
Our knowledge of the mechanisms underlying the vulnerability of the brain's white matter microstructure to cardiovascular risk factors (CVRFs) is still limited. We used a quantitative magnetic resonance imaging (MRI) protocol in a single centre setting to investigate the cross-sectional association between CVRFs and brain tissue properties of white matter tracts in a large community-dwelling cohort (n = 1104, age range 46-87 years). Arterial hypertension was associated with lower myelin and axonal density MRI indices, paralleled by higher extracellular water content. Obesity showed similar associations, though with myelin difference only in male participants. Associations between CVRFs and white matter microstructure were observed predominantly in limbic and prefrontal tracts. Additional genetic, lifestyle and psychiatric factors did not modulate these results, but moderate-to-vigorous physical activity was linked to higher myelin content independently of CVRFs. Our findings complement previously described CVRF-related changes in brain water diffusion properties pointing towards myelin loss and neuroinflammation rather than neurodegeneration.
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Affiliation(s)
- Olga Trofimova
- Laboratory for Research in Neuroimaging LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Adeliya Latypova
- Laboratory for Research in Neuroimaging LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Giulia DiDomenicantonio
- Laboratory for Research in Neuroimaging LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Antoine Lutti
- Laboratory for Research in Neuroimaging LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Ann-Marie G de Lange
- Laboratory for Research in Neuroimaging LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Department of Psychology, University of Oslo, Oslo, Norway
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Matthias Kliegel
- Department of Psychology, University of Geneva, Geneva, Switzerland
| | - Silvia Stringhini
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
- Institute of Social and Preventive Medicine, Lausanne University Hospital, Lausanne, Switzerland
- Unit of Population Epidemiology, Division of Primary Care Medicine, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Pedro Marques-Vidal
- Department of Medicine, Internal Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Julien Vaucher
- Department of Medicine, Internal Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Peter Vollenweider
- Department of Medicine, Internal Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Marie-Pierre F Strippoli
- Center for Research in Psychiatric Epidemiology and Psychopathology, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Martin Preisig
- Center for Research in Psychiatric Epidemiology and Psychopathology, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Ferath Kherif
- Laboratory for Research in Neuroimaging LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Bogdan Draganski
- Laboratory for Research in Neuroimaging LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
- Neurology Department, Max-Planck-Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
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9
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Gregory S, Pullen H, Ritchie CW, Shannon OM, Stevenson EJ, Muniz-Terrera G. Mediterranean diet and structural neuroimaging biomarkers of Alzheimer's and cerebrovascular disease: A systematic review. Exp Gerontol 2023; 172:112065. [PMID: 36529364 DOI: 10.1016/j.exger.2022.112065] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 11/23/2022] [Accepted: 12/13/2022] [Indexed: 12/23/2022]
Abstract
Previous studies have demonstrated an association between adherence to the Mediterranean diet (MedDiet) and better cognitive performance, lower incidence of dementia and lower Alzheimer's disease biomarker burden. The aim of this systematic review was to evaluate the evidence base for MedDiet associations with hippocampal volume and white matter hyperintensity volume (WMHV). We searched systematically for studies reporting on MedDiet and hippocampal volume or WMHV in MedLine, EMBASE, CINAHL and PsycInfo. Searches were initially carried out on 21st July 2021 with final searches run on 23rd November 2022. Risk of bias was assessed using the NIH Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. Of an initial 112 papers identified, seven papers were eligible for inclusion in the review reporting on 21,933 participants. Four studies reported on hippocampal volume, with inconclusive or no associations seen with MedDiet adherence. Two studies found a significant association between higher MedDiet adherence and lower WMHV, while two other studies found no significant associations. Overall these results highlight a gap in our knowledge about the associations between the MedDiet and AD and cerebrovascular related structural neuroimaging findings.
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Affiliation(s)
- Sarah Gregory
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.
| | - Hannah Pullen
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.
| | - Craig W Ritchie
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; Brain Health Scotland, UK.
| | - Oliver M Shannon
- Faculty of Medical Sciences, Human Nutrition Research Centre, Newcastle University, Newcastle Upon Tyne, UK.
| | - Emma J Stevenson
- Faculty of Medical Sciences, Human Nutrition Research Centre, Newcastle University, Newcastle Upon Tyne, UK.
| | - Graciela Muniz-Terrera
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; Social Medicine, Ohio University, OH, USA.
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10
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Tayler HM, MacLachlan R, Güzel Ö, Miners JS, Love S. Elevated late-life blood pressure may maintain brain oxygenation and slow amyloid-β accumulation at the expense of cerebral vascular damage. Brain Commun 2023; 5:fcad112. [PMID: 37113314 PMCID: PMC10128877 DOI: 10.1093/braincomms/fcad112] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 02/16/2023] [Accepted: 04/03/2023] [Indexed: 04/29/2023] Open
Abstract
Hypertension in midlife contributes to cognitive decline and is a modifiable risk factor for dementia. The relationship between late-life hypertension and dementia is less clear. We have investigated the relationship of blood pressure and hypertensive status during late life (after 65 years) to post-mortem markers of Alzheimer's disease (amyloid-β and tau loads); arteriolosclerosis and cerebral amyloid angiopathy; and to biochemical measures of ante-mortem cerebral oxygenation (the myelin-associated glycoprotein:proteolipid protein-1 ratio, which is reduced in chronically hypoperfused brain tissue, and the level of vascular endothelial growth factor-A, which is upregulated by tissue hypoxia); blood-brain barrier damage (indicated by an increase in parenchymal fibrinogen); and pericyte content (platelet-derived growth factor receptor β, which declines with pericyte loss), in Alzheimer's disease (n = 75), vascular (n = 20) and mixed dementia (n = 31) cohorts. Systolic and diastolic blood pressure measurements were obtained retrospectively from clinical records. Non-amyloid small vessel disease and cerebral amyloid angiopathy were scored semiquantitatively. Amyloid-β and tau loads were assessed by field fraction measurement in immunolabelled sections of frontal and parietal lobes. Homogenates of frozen tissue from the contralateral frontal and parietal lobes (cortex and white matter) were used to measure markers of vascular function by enzyme-linked immunosorbent assay. Diastolic (but not systolic) blood pressure was associated with the preservation of cerebral oxygenation, correlating positively with the ratio of myelin-associated glycoprotein to proteolipid protein-1 and negatively with vascular endothelial growth factor-A in both the frontal and parietal cortices. Diastolic blood pressure correlated negatively with parenchymal amyloid-β in the parietal cortex. In dementia cases, elevated late-life diastolic blood pressure was associated with more severe arteriolosclerosis and cerebral amyloid angiopathy, and diastolic blood pressure correlated positively with parenchymal fibrinogen, indicating blood-brain barrier breakdown in both regions of the cortex. Systolic blood pressure was related to lower platelet-derived growth factor receptor β in controls in the frontal cortex and in dementia cases in the superficial white matter. We found no association between blood pressure and tau. Our findings demonstrate a complex relationship between late-life blood pressure, disease pathology and vascular function in dementia. We suggest that hypertension helps to reduce cerebral ischaemia (and may slow amyloid-β accumulation) in the face of increasing cerebral vascular resistance, but exacerbates vascular pathology.
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Affiliation(s)
- Hannah M Tayler
- Dementia Research Group, Institute of Clinical Neurosciences, Bristol Medical School, University of Bristol, Bristol, BS10 5NB, UK
| | - Robert MacLachlan
- Dementia Research Group, Institute of Clinical Neurosciences, Bristol Medical School, University of Bristol, Bristol, BS10 5NB, UK
| | - Özge Güzel
- Dementia Research Group, Institute of Clinical Neurosciences, Bristol Medical School, University of Bristol, Bristol, BS10 5NB, UK
| | - J Scott Miners
- Dementia Research Group, Institute of Clinical Neurosciences, Bristol Medical School, University of Bristol, Bristol, BS10 5NB, UK
| | - Seth Love
- Correspondence to: Seth Love South West Dementia Brain Bank, University of Bristol Learning & Research Level 1, Southmead Hospital, Bristol, BS10 5NB, UK E-mail:
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11
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Phuah CL, Chen Y, Strain JF, Yechoor N, Laurido-Soto OJ, Ances BM, Lee JM. Association of Data-Driven White Matter Hyperintensity Spatial Signatures With Distinct Cerebral Small Vessel Disease Etiologies. Neurology 2022; 99:e2535-e2547. [PMID: 36123127 PMCID: PMC9754646 DOI: 10.1212/wnl.0000000000201186] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 07/15/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Topographical distribution of white matter hyperintensities (WMH) are hypothesized to vary by cerebrovascular risk factors. We used an unbiased pattern discovery approach to identify distinct WMH spatial patterns and investigate their association with different WMH etiologies. METHODS We performed a cross-sectional study on participants of the Alzheimer's Disease Neuroimaging Initiative (ADNI) to identify spatially distinct WMH distribution patterns using voxel-based spectral clustering analysis of aligned WMH probability maps. We included all participants from the ADNI Grand Opportunity/ADNI 2 study with available baseline 2D-FLAIR MRI scans, without history of stroke or presence of infarction on imaging. We evaluated the associations of these WMH spatial patterns with vascular risk factors, amyloid-β PET, and imaging biomarkers of cerebral amyloid angiopathy (CAA), characterizing different forms of cerebral small vessel disease (CSVD) using multivariable regression. We also used linear regression models to investigate whether WMH spatial distribution influenced cognitive impairment. RESULTS We analyzed MRI scans of 1,046 ADNI participants with mixed vascular and amyloid-related risk factors (mean age 72.9, 47.7% female, 31.4% hypertensive, 48.3% with abnormal amyloid PET). We observed unbiased partitioning of WMH into 5 unique spatial patterns: deep frontal, periventricular, juxtacortical, parietal, and posterior. Juxtacortical WMH were independently associated with probable CAA, deep frontal WMH were associated with risk factors for arteriolosclerosis (hypertension and diabetes), and parietal WMH were associated with brain amyloid accumulation, consistent with an Alzheimer disease (AD) phenotype. Juxtacortical, deep frontal, and parietal WMH spatial patterns were associated with cognitive impairment. Periventricular and posterior WMH spatial patterns were unrelated to any disease phenotype or cognitive decline. DISCUSSION Data-driven WMH spatial patterns reflect discrete underlying etiologies including arteriolosclerosis, CAA, AD, and normal aging. Global measures of WMH volume may miss important spatial distinctions. WMH spatial signatures may serve as etiology-specific imaging markers, helping to resolve WMH heterogeneity, identify the dominant underlying pathologic process, and improve prediction of clinical-relevant trajectories that influence cognitive decline.
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Affiliation(s)
- Chia-Ling Phuah
- From the Department of Neurology (C.-L.P., Y.C., J.F.S., N.Y., O.J.L.-S., B.M.A., J.-M.L.), Washington University School of Medicine & Barnes-Jewish Hospital, St. Louis, MO; NeuroGenomics and Informatics Center (C.-L.P.), Washington University School of Medicine, St. Louis, MO; Mallinckrodt Institute of Radiology (J.-M.L.), Washington University School of Medicine, St. Louis, MO; and Department of Biomedical Engineering (J.-M.L.), Washington University School of Medicine, St. Louis, MO
| | - Yasheng Chen
- From the Department of Neurology (C.-L.P., Y.C., J.F.S., N.Y., O.J.L.-S., B.M.A., J.-M.L.), Washington University School of Medicine & Barnes-Jewish Hospital, St. Louis, MO; NeuroGenomics and Informatics Center (C.-L.P.), Washington University School of Medicine, St. Louis, MO; Mallinckrodt Institute of Radiology (J.-M.L.), Washington University School of Medicine, St. Louis, MO; and Department of Biomedical Engineering (J.-M.L.), Washington University School of Medicine, St. Louis, MO
| | - Jeremy F Strain
- From the Department of Neurology (C.-L.P., Y.C., J.F.S., N.Y., O.J.L.-S., B.M.A., J.-M.L.), Washington University School of Medicine & Barnes-Jewish Hospital, St. Louis, MO; NeuroGenomics and Informatics Center (C.-L.P.), Washington University School of Medicine, St. Louis, MO; Mallinckrodt Institute of Radiology (J.-M.L.), Washington University School of Medicine, St. Louis, MO; and Department of Biomedical Engineering (J.-M.L.), Washington University School of Medicine, St. Louis, MO
| | - Nirupama Yechoor
- From the Department of Neurology (C.-L.P., Y.C., J.F.S., N.Y., O.J.L.-S., B.M.A., J.-M.L.), Washington University School of Medicine & Barnes-Jewish Hospital, St. Louis, MO; NeuroGenomics and Informatics Center (C.-L.P.), Washington University School of Medicine, St. Louis, MO; Mallinckrodt Institute of Radiology (J.-M.L.), Washington University School of Medicine, St. Louis, MO; and Department of Biomedical Engineering (J.-M.L.), Washington University School of Medicine, St. Louis, MO
| | - Osvaldo J Laurido-Soto
- From the Department of Neurology (C.-L.P., Y.C., J.F.S., N.Y., O.J.L.-S., B.M.A., J.-M.L.), Washington University School of Medicine & Barnes-Jewish Hospital, St. Louis, MO; NeuroGenomics and Informatics Center (C.-L.P.), Washington University School of Medicine, St. Louis, MO; Mallinckrodt Institute of Radiology (J.-M.L.), Washington University School of Medicine, St. Louis, MO; and Department of Biomedical Engineering (J.-M.L.), Washington University School of Medicine, St. Louis, MO
| | - Beau M Ances
- From the Department of Neurology (C.-L.P., Y.C., J.F.S., N.Y., O.J.L.-S., B.M.A., J.-M.L.), Washington University School of Medicine & Barnes-Jewish Hospital, St. Louis, MO; NeuroGenomics and Informatics Center (C.-L.P.), Washington University School of Medicine, St. Louis, MO; Mallinckrodt Institute of Radiology (J.-M.L.), Washington University School of Medicine, St. Louis, MO; and Department of Biomedical Engineering (J.-M.L.), Washington University School of Medicine, St. Louis, MO
| | - Jin-Moo Lee
- From the Department of Neurology (C.-L.P., Y.C., J.F.S., N.Y., O.J.L.-S., B.M.A., J.-M.L.), Washington University School of Medicine & Barnes-Jewish Hospital, St. Louis, MO; NeuroGenomics and Informatics Center (C.-L.P.), Washington University School of Medicine, St. Louis, MO; Mallinckrodt Institute of Radiology (J.-M.L.), Washington University School of Medicine, St. Louis, MO; and Department of Biomedical Engineering (J.-M.L.), Washington University School of Medicine, St. Louis, MO.
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12
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Gregory S, Saunders S, Ritchie CW. Science disconnected: the translational gap between basic science, clinical trials, and patient care in Alzheimer's disease. THE LANCET. HEALTHY LONGEVITY 2022; 3:e797-e803. [PMID: 36356629 DOI: 10.1016/s2666-7568(22)00219-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Revised: 08/22/2022] [Accepted: 09/08/2022] [Indexed: 11/09/2022] Open
Abstract
Both research and clinical practice have traditionally centred on the dementia syndrome of Alzheimer's disease rather than its preclinical and prodromal stages. However, there is a strong scientific and ethical impetus to shift focus to earlier disease stages to improve brain health outcomes and help to keep affected individuals symptom-free (dementia-free) for as long as possible. We provide an overview of recent advancements in early detection, drug development, and trial methodology that should be utilised in the development of new therapies for use in brain health clinics. We propose a triad approach to Alzheimer's disease clinical trials, encompassing (1) experimental medicine studies to gather greater knowledge of disease mechanisms, (2) a more comprehensive platform of phase 2 learning trials to inform phase 3 confirmatory trials, and (3) precision medicine involving smaller subgroups of patients with shared characteristics. This triad would ensure that treatment targets are identified accurately, trial methodology focuses on at-risk populations, and sensitive outcome measures capture potential treatment effects. Clinical services around the world must embrace the brain health clinic model so that neurodegenerative diseases can be detected in their earliest phase to quicken drug development pipelines and potentially improve prognosis.
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Affiliation(s)
- Sarah Gregory
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, Outpatient Department 2, Western General Hospital, University of Edinburgh, Edinburgh, UK.
| | - Stina Saunders
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, Outpatient Department 2, Western General Hospital, University of Edinburgh, Edinburgh, UK
| | - Craig W Ritchie
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, Outpatient Department 2, Western General Hospital, University of Edinburgh, Edinburgh, UK; Brain Health Scotland, Edinburgh, UK
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13
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Kim H, Devanand DP, Carlson S, Goldberg TE. Apolipoprotein E Genotype e2: Neuroprotection and Its Limits. Front Aging Neurosci 2022; 14:919712. [PMID: 35912085 PMCID: PMC9329577 DOI: 10.3389/fnagi.2022.919712] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 06/09/2022] [Indexed: 11/21/2022] Open
Abstract
In this review, we comprehensively, qualitatively, and critically synthesized several features of APOE-e2, a known APOE protective variant, including its associations with longevity, cognition, and neuroimaging, and neuropathology, all in humans. If e2’s protective effects—and their limits—could be elucidated, it could offer therapeutic windows for Alzheimer’s disease (AD) prevention or amelioration. Literature examining e2 within the years 1994–2021 were considered for this review. Studies on human subjects were selectively reviewed and were excluded if observation of e2 was not specified. Effects of e2 were compared with e3 and e4, separately and as a combined non-e2 group. Our examination of existing literature indicated that the most robust protective role of e2 is in longevity and AD neuropathologies, but e2’s effect on cognition and other AD imaging markers (brain structure, function, and metabolism) were inconsistent, thus inconclusive. Notably, e2 was associated with greater risk of non-AD proteinopathies and a disadvantageous cerebrovascular profile. We identified multiple methodological shortcomings of the literature on brain function and cognition that could have contributed to inconsistent and potentially misleading findings. We make careful interpretations of existing findings and provide directions for research strategies that could effectively examine the independent and unbiased effect of e2 on AD risk.
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Affiliation(s)
- Hyun Kim
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, United States
- Department of Geriatric Psychiatry, New York State Psychiatric Institute, New York, NY, United States
| | - Davangere P. Devanand
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, United States
- Department of Geriatric Psychiatry, New York State Psychiatric Institute, New York, NY, United States
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, United States
| | - Scott Carlson
- Department of Geriatric Psychiatry, New York State Psychiatric Institute, New York, NY, United States
| | - Terry E. Goldberg
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, United States
- Department of Geriatric Psychiatry, New York State Psychiatric Institute, New York, NY, United States
- Department of Anesthesiology, Columbia University Irving Medical Center, New York, NY, United States
- *Correspondence: Terry E. Goldberg,
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14
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Su C, Yang X, Wei S, Zhao R. Association of Cerebral Small Vessel Disease With Gait and Balance Disorders. Front Aging Neurosci 2022; 14:834496. [PMID: 35875801 PMCID: PMC9305071 DOI: 10.3389/fnagi.2022.834496] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Accepted: 06/14/2022] [Indexed: 12/27/2022] Open
Abstract
Cerebral small vessel disease (CSVD) is a common cerebrovascular disease and an important cause of gait and balance disorders. Gait and balance disorders can further lead to an increased risk of falls and a decreased quality of life. CSVD can damage gait and balance function by affecting cognitive function or directly disrupting motor pathways, and different CSVD imaging features have different characteristics of gait and balance impairment. In this article, the correlation between different imaging features of sporadic CSVD and gait and balance disorders has been reviewed as follows, which can provide beneficial help for standardized management of CSVD.
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15
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Wang J, Zhou Y, He Y, Li Q, Zhang W, Luo Z, Xue R, Lou M. Impact of different white matter hyperintensities patterns on cognition: A cross-sectional and longitudinal study. Neuroimage Clin 2022; 34:102978. [PMID: 35255417 PMCID: PMC8897653 DOI: 10.1016/j.nicl.2022.102978] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 02/27/2022] [Accepted: 02/28/2022] [Indexed: 11/03/2022]
Abstract
OBJECTIVES White matter hyperintensities (WMH) are highly prevalent in older adults and considered to be a contributor to cognition impairment. However, the strategic WMH lesion distribution related to cognitive impairment is still debated. The aim of this study was to characterize the spatial patterns of WMH associated with cognitive impairment and explore its risk factors. METHODS We retrospectively analyzed patients who underwent T2 fluid attenuated inversion recovery (FLAIR) and mini-mental state examination (MMSE) in two centers. WHM was classified into four patterns based on T2 FLAIR as follows: (1) multiple subcortical spots (multi-spots); (2) peri-basal ganglia (peri-BG); (3) anterior subcortical patches (anterior SC patches); and (4) posterior subcortical patches (posterior SC patches). We cross-sectionally and longitudinally estimated associations between different WMH patterns and all-cause dementia and cognitive decline. Multivariable logistic regression analysis was followed to identify risk factors of WMH patterns related to cognitive impairment. RESULTS A total of 442 patients with WMH were enrolled, with average age of 71.6 ± 11.3 years, and MMSE score of 24.1 ± 5.4. Among them, 281 (63.6%), 66 (14.9%), 163 (36.9%) and 197 (44.6%) patients presented multi-spots, peri-BG, anterior SC patches and posterior SC patches, respectively. Patients with anterior SC patches were more likely to have all-cause dementia in cross-sectional study (OR 2.002; 95% CI 1.098-3.649; p = 0.024), and have cognitive decline in longitudinal analysis (OR 3.029; 95% CI 1.270-7.223; p = 0.012). Four patterns of WMH referred to different cognitive domains, and anterior SC patches had the most significant and extensive impact on cognition after Bonferroni multiple comparison correction (all p < 0.0125). In addition, older age (OR 1.054; 95% CI 1.027-1.082; p < 0.001), hypertension (OR 1.956; 95% CI 1.145-3.341; p = 0.014), higher percentage of neutrophils (OR 1.046; 95% CI 1.014-1.080; p = 0.005) and lower concentration of hemoglobin (OR 0.983; 95% CI 0.967-1.000; p = 0.044) were risk factors for the presence of anterior SC patches. CONCLUSIONS Different patterns of subcortical leukoaraiosis visually identified on MRI might have different impacts on cognitive impairment. Further studies should be undertaken to validate this simple visual classification of WMH in different population.
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Affiliation(s)
- Junjun Wang
- Department of Neurology, the Second Affiliated Hospital of Zhejiang University, School of Medicine. 88# Jiefang Road, Hangzhou, China; Department of Neurology, Zhejiang Hospital, #12 Lingyin Road, Hangzhou, China
| | - Ying Zhou
- Department of Neurology, the Second Affiliated Hospital of Zhejiang University, School of Medicine. 88# Jiefang Road, Hangzhou, China
| | - Yaode He
- Department of Neurology, the Second Affiliated Hospital of Zhejiang University, School of Medicine. 88# Jiefang Road, Hangzhou, China
| | - Qingqing Li
- Department of Neurology, the Second Affiliated Hospital of Zhejiang University, School of Medicine. 88# Jiefang Road, Hangzhou, China
| | - Wenhua Zhang
- Department of Neurology, the Second Affiliated Hospital of Zhejiang University, School of Medicine. 88# Jiefang Road, Hangzhou, China
| | - Zhongyu Luo
- Department of Neurology, the Second Affiliated Hospital of Zhejiang University, School of Medicine. 88# Jiefang Road, Hangzhou, China
| | - Rui Xue
- Department of Neurology, the Second Affiliated Hospital of Zhejiang University, School of Medicine. 88# Jiefang Road, Hangzhou, China
| | - Min Lou
- Department of Neurology, the Second Affiliated Hospital of Zhejiang University, School of Medicine. 88# Jiefang Road, Hangzhou, China.
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16
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Lorenzini L, Ansems LT, Lopes Alves I, Ingala S, Vállez García D, Tomassen J, Sudre C, Salvadó G, Shekari M, Operto G, Brugulat-Serrat A, Sánchez-Benavides G, ten Kate M, Tijms B, Wink AM, Mutsaerts HJMM, den Braber A, Visser PJ, van Berckel BNM, Gispert JD, Barkhof F, Collij LE, Beteta A, Brugulat A, Cacciaglia R, Cañas A, Deulofeu C, Cumplido I, Dominguez R, Emilio M, Fauria K, Fuentes S, Hernandez L, Huesa G, Huguet J, Marne P, Menchón T, Polo A, Pradas S, Rodriguez-Fernandez B, Sala-Vila A, Sánchez-Benavides G, Soteras A, Vilanova M. Regional associations of white matter hyperintensities and early cortical amyloid pathology. Brain Commun 2022; 4:fcac150. [PMID: 35783557 PMCID: PMC9246276 DOI: 10.1093/braincomms/fcac150] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 04/11/2022] [Accepted: 06/09/2022] [Indexed: 11/13/2022] Open
Abstract
Abstract
White matter hyperintensities (WMHs) have a heterogeneous aetiology, associated with both vascular risk factors and amyloidosis due to Alzheimer’s disease. While spatial distribution of both amyloid and WM lesions carry important information for the underlying pathogenic mechanisms, the regional relationship between these two pathologies and their joint contribution to early cognitive deterioration remains largely unexplored.
We included 662 non-demented participants from three Amyloid Imaging to Prevent Alzheimer’s disease (AMYPAD)-affiliated cohorts: EPAD-LCS (N = 176), ALFA+ (N = 310), and EMIF-AD PreclinAD Twin60++ (N = 176). Using PET imaging, cortical amyloid burden was assessed regionally within early accumulating regions (medial orbitofrontal, precuneus, and cuneus) and globally, using the Centiloid method. Regional WMH volume was computed using Bayesian Model Selection. Global associations between WMH, amyloid, and cardiovascular risk scores (Framingham and CAIDE) were assessed using linear models. Partial least square (PLS) regression was used to identify regional associations. Models were adjusted for age, sex, and APOE-e4 status. Individual PLS scores were then related to cognitive performance in 4 domains (attention, memory, executive functioning, and language).
While no significant global association was found, the PLS model yielded two components of interest. In the first PLS component, a fronto-parietal WMH pattern was associated with medial orbitofrontal–precuneal amyloid, vascular risk, and age. Component 2 showed a posterior WMH pattern associated with precuneus-cuneus amyloid, less related to age or vascular risk. Component 1 was associated with lower performance in all cognitive domains, while component 2 only with worse memory.
In a large pre-dementia population, we observed two distinct patterns of regional associations between WMH and amyloid burden, and demonstrated their joint influence on cognitive processes. These two components could reflect the existence of vascular-dependent and -independent manifestations of WMH-amyloid regional association that might be related to distinct primary pathophysiology.
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Affiliation(s)
- Luigi Lorenzini
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience , Amsterdam , The Netherlands
| | - Loes T Ansems
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience , Amsterdam , The Netherlands
| | - Isadora Lopes Alves
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience , Amsterdam , The Netherlands
| | - Silvia Ingala
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience , Amsterdam , The Netherlands
| | - David Vállez García
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience , Amsterdam , The Netherlands
| | - Jori Tomassen
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC , Amsterdam , The Netherlands
| | - Carole Sudre
- Centre for Medical Image Computing (CMIC), Departments of Medical Physics & Biomedical Engineering and Computer Science, University College London , UK
- MRC Unit for Lifelong Health and Ageing - University College London , UK
- School of Biomedical Engineering , King’s College London UK
| | - Gemma Salvadó
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation , Barcelona , Spain
- IMIM (Hospital del Mar Medical Research Institute) , Barcelona , Spain
| | - Mahnaz Shekari
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation , Barcelona , Spain
- IMIM (Hospital del Mar Medical Research Institute) , Barcelona , Spain
- Universitat Pompeu Fabra , Barcelona , Spain
| | - Gregory Operto
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation , Barcelona , Spain
- IMIM (Hospital del Mar Medical Research Institute) , Barcelona , Spain
- Centro de Investigación Biomédica en Red de Fragilidad Y Envejecimiento Saludable (CIBERFES) , Madrid , Spain
| | - Anna Brugulat-Serrat
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation , Barcelona , Spain
- IMIM (Hospital del Mar Medical Research Institute) , Barcelona , Spain
- Centro de Investigación Biomédica en Red de Fragilidad Y Envejecimiento Saludable (CIBERFES) , Madrid , Spain
- Atlantic Fellow for Equity in Brain Health at the University of California San Francisco , SanFrancisco, California , USA
| | - Gonzalo Sánchez-Benavides
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation , Barcelona , Spain
- IMIM (Hospital del Mar Medical Research Institute) , Barcelona , Spain
- Centro de Investigación Biomédica en Red de Fragilidad Y Envejecimiento Saludable (CIBERFES) , Madrid , Spain
| | - Mara ten Kate
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience , Amsterdam , The Netherlands
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC , Amsterdam , The Netherlands
| | - Betty Tijms
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC , Amsterdam , The Netherlands
| | - Alle Meije Wink
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience , Amsterdam , The Netherlands
| | - Henk J M M Mutsaerts
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience , Amsterdam , The Netherlands
| | - Anouk den Braber
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC , Amsterdam , The Netherlands
- Department. of Biological Psychology, Vrije Universiteit Amsterdam, Neuroscience Amsterdam , Amsterdam , The Netherlands
| | - Pieter Jelle Visser
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC , Amsterdam , The Netherlands
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University , Maastricht , The Netherlands
| | - Bart N M van Berckel
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience , Amsterdam , The Netherlands
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation , Barcelona , Spain
- IMIM (Hospital del Mar Medical Research Institute) , Barcelona , Spain
- Universitat Pompeu Fabra , Barcelona , Spain
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales Y Nanomedicina , Madrid , Spain
| | - Frederik Barkhof
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience , Amsterdam , The Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London , London , UK
| | - Lyduine E Collij
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience , Amsterdam , The Netherlands
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17
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Low A, Prats-Sedano MA, Stefaniak JD, McKiernan EF, Carter SF, Douvani ME, Mak E, Su L, Stupart O, Muniz G, Ritchie K, Ritchie CW, Markus HS, O'Brien JT. CAIDE dementia risk score relates to severity and progression of cerebral small vessel disease in healthy midlife adults: the PREVENT-Dementia study. J Neurol Neurosurg Psychiatry 2022; 93:481-490. [PMID: 35135868 PMCID: PMC9016254 DOI: 10.1136/jnnp-2021-327462] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Accepted: 12/27/2021] [Indexed: 12/12/2022]
Abstract
BACKGROUND Markers of cerebrovascular disease are common in dementia, and may be present before dementia onset. However, their clinical relevance in midlife adults at risk of future dementia remains unclear. We investigated whether the Cardiovascular Risk Factors, Ageing and Dementia (CAIDE) risk score was associated with markers of cerebral small vessel disease (SVD), and if it predicted future progression of SVD. We also determined its relationship to systemic inflammation, which has been additionally implicated in dementia and SVD. METHODS Cognitively healthy midlife participants were assessed at baseline (n=185) and 2-year follow-up (n=158). To assess SVD, we quantified white matter hyperintensities (WMH), enlarged perivascular spaces (EPVS), microbleeds and lacunes. We derived composite scores of SVD burden, and subtypes of hypertensive arteriopathy and cerebral amyloid angiopathy. Inflammation was quantified using serum C-reactive protein (CRP) and fibrinogen. RESULTS At baseline, higher CAIDE scores were associated with all markers of SVD and inflammation. Longitudinally, CAIDE scores predicted greater total (p<0.001), periventricular (p<0.001) and deep (p=0.012) WMH progression, and increased CRP (p=0.017). Assessment of individual CAIDE components suggested that markers were driven by different risk factors (WMH/EPVS: age/hypertension, lacunes/deep microbleeds: hypertension/obesity). Interaction analyses demonstrated that higher CAIDE scores amplified the effect of age on SVD, and the effect of WMH on poorer memory. CONCLUSION Higher CAIDE scores, indicating greater risk of dementia, predicts future progression of both WMH and systemic inflammation. Findings highlight the CAIDE score's potential as both a prognostic and predictive marker in the context of cerebrovascular disease, identifying at-risk individuals who might benefit most from managing modifiable risk.
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Affiliation(s)
- Audrey Low
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Maria A Prats-Sedano
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - James D Stefaniak
- Division of Neuroscience and Experimental Psychology, The University of Manchester, Manchester, UK
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | | | - Stephen F Carter
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Maria-Eleni Douvani
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Elijah Mak
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Li Su
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Department of Neuroscience, The University of Sheffield, Sheffield, UK
| | - Olivia Stupart
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Graciela Muniz
- Centre for Dementia Prevention, University of Edinburgh, Edinburgh, UK
| | - Karen Ritchie
- Centre for Dementia Prevention, University of Edinburgh, Edinburgh, UK
- INSERM, Montpellier, France
| | - Craig W Ritchie
- Centre for Dementia Prevention, University of Edinburgh, Edinburgh, UK
| | - Hugh S Markus
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - John Tiernan O'Brien
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK
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18
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Jiménez-Balado J, Corlier F, Habeck C, Stern Y, Eich T. Effects of white matter hyperintensities distribution and clustering on late-life cognitive impairment. Sci Rep 2022; 12:1955. [PMID: 35121804 PMCID: PMC8816933 DOI: 10.1038/s41598-022-06019-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 01/20/2022] [Indexed: 11/29/2022] Open
Abstract
White matter hyperintensities (WMH) are a key hallmark of subclinical cerebrovascular disease and are known to impair cognition. Here, we parcellated WMH using a novel system that segments WMH based on both lobar regions and distance from the ventricles, dividing the brain into a coordinate system composed of 36 distinct parcels ('bullseye' parcellation), and then investigated the effect of distribution on cognition using two different analytic approaches. Data from a well characterized sample of healthy older adults (58 to 84 years) who were free of dementia were included. Cognition was evaluated using 12 computerized tasks, factored onto 4 indices representing episodic memory, speed of processing, fluid reasoning and vocabulary. We first assessed the distribution of WMH according to the bullseye parcellation and tested the relationship between WMH parcellations and performance across the four cognitive domains. Then, we used a data-driven approach to derive latent variables within the WMH distribution, and tested the relation between these latent components and cognitive function. We observed that different, well-defined cognitive constructs mapped to specific WMH distributions. Speed of processing was correlated with WMH in the frontal lobe, while in the case of episodic memory, the relationship was more ubiquitous, involving most of the parcellations. A principal components analysis revealed that the 36 bullseye regions factored onto 3 latent components representing the natural aggrupation of WMH: fronto-parietal periventricular (WMH principally in the frontal and parietal lobes and basal ganglia, especially in the periventricular region); occipital; and temporal and juxtacortical WMH (involving WMH in the temporal lobe, and at the juxtacortical region from frontal and parietal lobes). We found that fronto-parietal periventricular and temporal & juxtacortical WMH were independently associated with speed of processing and episodic memory, respectively. These results indicate that different cognitive impairment phenotypes might present with specific WMH distributions. Additionally, our study encourages future research to consider WMH classifications using parcellations systems other than periventricular and deep localizations.
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Affiliation(s)
- Joan Jiménez-Balado
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA
| | - Fabian Corlier
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA
| | - Christian Habeck
- Department of Neurology, Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Yaakov Stern
- Department of Neurology, Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Teal Eich
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA.
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19
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Tu MC, Chung HW, Hsu YH, Yang JJ, Wu WC. Stage-Dependent Cerebral Blood Flow and Leukoaraiosis Couplings in Subcortical Ischemic Vascular Disease and Alzheimer's Disease. J Alzheimers Dis 2022; 86:729-739. [PMID: 35124651 PMCID: PMC9028753 DOI: 10.3233/jad-215405] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Background: Alzheimer’s disease (AD) and subcortical ischemic vascular disease (SIVD) have both been associated with white matter hyperintensities (WMHs) and altered cerebral blood flow (CBF) although the etiology of AD is still unclear. Objective: To test the hypothesis that CBF and WMHs have differential effects on cognition and that the relationship between CBF and WMHs changes with the subtypes and stages of dementia. Methods: Forty-two patients with SIVD, 50 patients with clinically-diagnosed AD, and 30 cognitively-normal subjects were included. Based on the Clinical Dementia Rating (CDR), the patients were dichotomized into early-stage (CDR = 0.5) and late-stage (CDR = 1 or 2) groups. CBF and WMH metrics were derived from magnetic resonance imaging and correlated with cognition. Results: Hierarchical linear regression revealed that CBF metrics had distinct contribution to global cognition, memory, and attention, whereas WMH metrics had distinct contribution to executive function (all p < 0.05). In SIVD, the WMHs in frontotemporal areas correlated with the CBF in bilateral thalami at the early stage; the correlation then became between the WMHs in basal ganglia and the CBF in frontotemporal areas at the late stage. A similar corticosubcortical coupling was observed in AD but involved fewer areas. Conclusion: A stage-dependent coupling between CBF and WMHs was identified in AD and SIVD, where the extent of cortical WMHs correlated with subcortical CBF for CDR = 0.5, whereas the extent of subcortical WMHs correlated with cortical CBF for CDR = 1–2.
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Affiliation(s)
- Min-Chien Tu
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan.,Department of Neurology, Taichung Tzu Chi Hospital, Taichung, Taiwan.,Department of Neurology, Tzu Chi University, Hualien, Taiwan
| | - Hsiao-Wen Chung
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan
| | - Yen-Hsuan Hsu
- Department of Psychology, National Chung Cheng University, Chiayi, Taiwan.,Center for Innovative Research on Aging Society, National Chung Cheng University, Chiayi, Taiwan
| | - Jir-Jei Yang
- Department of Radiology, Taichung Tzu Chi Hospital, Taichung, Taiwan
| | - Wen-Chau Wu
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan.,Institute of Medical Device and Imaging, National Taiwan University, Taipei, Taiwan
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20
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Five years of exercise intervention at different intensities and development of white matter hyperintensities in community dwelling older adults, a Generation 100 sub-study. Aging (Albany NY) 2022; 14:596-622. [PMID: 35042832 PMCID: PMC8833118 DOI: 10.18632/aging.203843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Accepted: 01/04/2022] [Indexed: 11/30/2022]
Abstract
We investigated if a five-year supervised exercise intervention with moderate-intensity continuous training (MICT) or high-intensity interval training (HIIT) versus control; physical activity according to national guidelines, attenuated the growth of white matter hyperintensities (WMH). We hypothesized that supervised exercise, in particular HIIT, reduced WMH growth. Older adults from the general population participating in the RCT Generation 100 Study were scanned at 3T MRI at baseline (age 70–77), and after 1-, 3- and 5-years. At each follow-up, cardiorespiratory fitness was measured with ergospirometry, and physical activity plus clinical data collected. Manually delineated total WMH, periventricular (PWMH), deep (DWMH), and automated total white matter hypointensity volumes were obtained. No group by time interactions were present in linear mixed model analyses with the different WMH measurements as outcomes. In the combined exercise (MICT&HIIT) group, a significant group by time interaction was uncovered for PWMH volume, with a larger increase in the MICT&HIIT group. Cardiorespiratory fitness at the follow-ups or change in cardiorespiratory fitness over time were not associated with any WMH measure. Contrary to our hypothesis, taking part in MICT or HIIT over a five-year period did not attenuate WMH growth compared to being in a control group following national physical activity guidelines.
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21
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Saunders S, Ritchie CW, Russ TC, Muniz-Terrera G, Milne R. Assessing and disclosing test results for ‘mild cognitive impairment’: the perspective of old age psychiatrists in Scotland. BMC Geriatr 2022; 22:50. [PMID: 35022025 PMCID: PMC8754072 DOI: 10.1186/s12877-021-02693-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Accepted: 11/15/2021] [Indexed: 03/11/2023] Open
Abstract
Abstract
Background
Mild cognitive impairment (MCI) is a condition that exists between normal healthy ageing and dementia with an uncertain aetiology and prognosis. This uncertainty creates a complex dynamic between the clinicians’ conception of MCI, what is communicated to the individual about their condition, and how the individual responds to the information conveyed to them. The aim of this study was to explore clinicians’ views around the assessment and communication of MCI in memory clinics.
Method
As part of a larger longitudinal study looking at patients’ adjustment to MCI disclosure, we interviewed Old Age Psychiatrists at the five participating sites across Scotland. The study obtained ethics approvals and the interviews (carried out between Nov 2020–Jan 2021) followed a semi-structured schedule focusing on [1] how likely clinicians are to use the term MCI with patients; [2] what tests clinicians rely on and how much utility they see in them; and [3] how clinicians communicate risk of progression to dementia. The interviews were voice recorded and were analysed using reflective thematic analysis.
Results
Initial results show that most clinicians interviewed (Total N = 19) considered MCI to have significant limitations as a diagnostic term. Nevertheless, most clinicians reported using the term MCI (n = 15/19). Clinical history was commonly described as the primary aid in the diagnostic process and also to rule out functional impairment (which was sometimes corroborated by Occupational Therapy assessment). All clinicians reported using the Addenbrooke’s Cognitive Examination-III as a primary assessment tool. Neuroimaging was frequently found to have minimal usefulness due to the neuroradiological reports being non-specific.
Conclusion
Our study revealed a mixture of approaches to assessing and disclosing test results for MCI. Some clinicians consider the condition as a separate entity among neurodegenerative disorders whereas others find the term unhelpful due to its uncertain prognosis. Clinicians report a lack of specific and sensitive assessment methods for identifying the aetiology of MCI in clinical practice. Our study demonstrates a broad range of views and therefore variability in MCI risk disclosure in memory assessment services which may impact the management of individuals with MCI.
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22
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Igwe KC, Lao PJ, Vorburger RS, Banerjee A, Rivera A, Chesebro A, Laing K, Manly JJ, Brickman AM. Automatic quantification of white matter hyperintensities on T2-weighted fluid attenuated inversion recovery magnetic resonance imaging. Magn Reson Imaging 2022; 85:71-79. [PMID: 34662699 PMCID: PMC8818099 DOI: 10.1016/j.mri.2021.10.007] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Revised: 08/20/2021] [Accepted: 10/12/2021] [Indexed: 01/03/2023]
Abstract
White matter hyperintensities (WMH) are areas of increased signal visualized on T2-weighted fluid attenuated inversion recovery (FLAIR) brain magnetic resonance imaging (MRI) sequences. They are typically attributed to small vessel cerebrovascular disease in the context of aging. Among older adults, WMH are associated with risk of cognitive decline and dementia, stroke, and various other health outcomes. There has been increasing interest in incorporating quantitative WMH measurement as outcomes in clinical trials, observational research, and clinical settings. Here, we present a novel, fully automated, unsupervised detection algorithm for WMH segmentation and quantification. The algorithm uses a robust preprocessing pipeline, including brain extraction and a sample-specific mask that incorporates spatial information for automatic false positive reduction, and a half Gaussian mixture model (HGMM). The method was evaluated in 24 participants with varying degrees of WMH (4.9-78.6 cm3) from a community-based study of aging and dementia with dice coefficient, sensitivity, specificity, correlation, and bias relative to the ground truth manual segmentation approach performed by two expert raters. Results were compared with those derived from commonly used available WMH segmentation packages, including SPM lesion probability algorithm (LPA), SPM lesion growing algorithm (LGA), and Brain Intensity AbNormality Classification Algorithm (BIANCA). The HGMM algorithm derived WMH values that had a dice score of 0.87, sensitivity of 0.89, and specificity of 0.99 compared to ground truth. White matter hyperintensity volumes derived with HGMM were strongly correlated with ground truth values (r = 0.97, p = 3.9e-16), with no observable bias (-1.1 [-2.6, 0.44], p-value = 0.16). Our novel algorithm uniquely uses a robust preprocessing pipeline and a half-Gaussian mixture model to segment WMH with high agreement with ground truth for large scale studies of brain aging.
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Affiliation(s)
- Kay C. Igwe
- Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA.,Gertrude H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA
| | - Patrick J. Lao
- Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA.,Gertrude H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA.,Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA
| | - Robert S. Vorburger
- Institute of Applied Simulation, School of Life Sciences and Facility Management, Zurich University of Applied Sciences, Wädenswil, 8820, Switzerland
| | - Arit Banerjee
- Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA.,Gertrude H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA
| | - Andres Rivera
- Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA.,Gertrude H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA
| | - Anthony Chesebro
- Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA.,Gertrude H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA
| | - Krystal Laing
- Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA.,Gertrude H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA
| | - Jennifer J. Manly
- Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA.,Gertrude H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA.,Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA
| | - Adam M. Brickman
- Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA.,Gertrude H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA.,Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032 USA.,Corresponding author Adam M. Brickman, PhD, Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, PS Box 16, 630 West 168th Street, New York, NY 10032, Tel: 212 342 1348, Fax: 212 342 1838,
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23
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de Silva E, Sudre CH, Barnes J, Scelsi MA, Altmann A. Polygenic coronary artery disease association with brain atrophy in the cognitively impaired. Brain Commun 2022; 4:fcac314. [PMID: 36523268 PMCID: PMC9746681 DOI: 10.1093/braincomms/fcac314] [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: 02/11/2022] [Revised: 09/09/2022] [Accepted: 11/28/2022] [Indexed: 12/03/2022] Open
Abstract
While a number of low-frequency genetic variants of large effect size have been shown to underlie both cardiovascular disease and dementia, recent studies have highlighted the importance of common genetic variants of small effect size, which, in aggregate, are embodied by a polygenic risk score. We investigate the effect of polygenic risk for coronary artery disease on brain atrophy in Alzheimer's disease using whole-brain volume and put our findings in context with the polygenic risk for Alzheimer's disease and presumed small vessel disease as quantified by white-matter hyperintensities. We use 730 subjects from the Alzheimer's disease neuroimaging initiative database to investigate polygenic risk score effects (beyond APOE) on whole-brain volumes, total and regional white-matter hyperintensities and amyloid beta across diagnostic groups. In a subset of these subjects (N = 602), we utilized longitudinal changes in whole-brain volume over 24 months using the boundary shift integral approach. Linear regression and linear mixed-effects models were used to investigate the effect of white-matter hyperintensities at baseline as well as Alzheimer's disease-polygenic risk score and coronary artery disease-polygenic risk score on whole-brain atrophy and whole-brain atrophy acceleration, respectively. All genetic associations were examined under the oligogenic (P = 1e-5) and the more variant-inclusive polygenic (P = 0.5) scenarios. Results suggest no evidence for a link between the polygenic risk score and markers of Alzheimer's disease pathology at baseline (when stratified by diagnostic group). However, both Alzheimer's disease-polygenic risk score and coronary artery disease-polygenic risk score were associated with longitudinal decline in whole-brain volume (Alzheimer's disease-polygenic risk score t = 3.3, P FDR = 0.007 over 24 months in healthy controls) and surprisingly, under certain conditions, whole-brain volume atrophy is statistically more correlated with cardiac polygenic risk score than Alzheimer's disease-polygenic risk score (coronary artery disease-polygenic risk score t = 2.1, P FDR = 0.04 over 24 months in the mild cognitive impairment group). Further, in our regional analysis of white-matter hyperintensities, Alzheimer's disease-polygenic risk score beyond APOE is predictive of white-matter volume in the occipital lobe in Alzheimer's disease subjects in the polygenic regime. Finally, the rate of change of brain volume (or atrophy acceleration) may be sensitive to Alzheimer's disease-polygenic risk beyond APOE in healthy individuals (t = 2, P = 0.04). For subjects with mild cognitive impairment, beyond APOE, a more inclusive polygenic risk score including more variants, shows coronary artery disease-polygenic risk score to be more predictive of whole-brain volume atrophy, than an oligogenic approach including fewer larger effect size variants.
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Affiliation(s)
- Eric de Silva
- Centre for Medical Image Computing, University College London, London, UK.,NIHR University College London Hospitals Biomedical Research Centre, London, UK
| | - Carole H Sudre
- Centre for Medical Image Computing, University College London, London, UK.,MRC Unit for Lifelong Health and Ageing, University College London, London, UK.,School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Josephine Barnes
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Marzia A Scelsi
- Centre for Medical Image Computing, University College London, London, UK
| | - Andre Altmann
- Centre for Medical Image Computing, University College London, London, UK
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McAleese KE, Miah M, Graham S, Hadfield GM, Walker L, Johnson M, Colloby SJ, Thomas AJ, DeCarli C, Koss D, Attems J. Frontal white matter lesions in Alzheimer's disease are associated with both small vessel disease and AD-associated cortical pathology. Acta Neuropathol 2021; 142:937-950. [PMID: 34608542 PMCID: PMC8568857 DOI: 10.1007/s00401-021-02376-2] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2021] [Revised: 09/26/2021] [Accepted: 09/27/2021] [Indexed: 12/22/2022]
Abstract
Cerebral white matter lesions (WML) encompass axonal loss and demyelination and are assumed to be associated with small vessel disease (SVD)-related ischaemia. However, our previous study in the parietal lobe white matter revealed that WML in Alzheimer's disease (AD) are linked with degenerative axonal loss secondary to the deposition of cortical AD pathology. Furthermore, neuroimaging data suggest that pathomechanisms for the development of WML differ between anterior and posterior lobes with AD-associated degenerative mechanism driving posterior white matter disruption, and both AD-associated degenerative and vascular mechanisms contributed to anterior matter disruption. In this pilot study, we used human post-mortem brain tissue to investigate the composition and aetiology of frontal WML from AD and non-demented controls to determine if frontal WML are SVD-associated and to reveal any regional differences in the pathogenesis of WML. Frontal WML tissue sections from 40 human post-mortem brains (AD, n = 19; controls, n = 21) were quantitatively assessed for demyelination, axonal loss, cortical hyperphosphorylated tau (HPτ) and amyloid-beta (Aβ) burden, and arteriolosclerosis as a measure of SVD. Biochemical assessment included Wallerian degeneration-associated protease calpain and the myelin-associated glycoprotein to proteolipid protein ratio as a measure of ante-mortem ischaemia. Arteriolosclerosis severity was found to be associated with and a significant predictor of frontal WML severity in both AD and non-demented controls. Interesting, frontal axonal loss was also associated with HPτ and calpain levels were associated with increasing Aβ burden in the AD group, suggestive of an additional degenerative influence. To conclude, this pilot data suggest that frontal WML in AD may result from both increased arteriolosclerosis and AD-associated degenerative changes. These preliminary findings in combination with previously published data tentatively indicate regional differences in the aetiology of WML in AD, which should be considered in the clinical diagnosis of dementia subtypes: posterior WML maybe associated with degenerative mechanisms secondary to AD pathology, while anterior WML could be associated with both SVD-associated and degenerative mechanisms.
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Affiliation(s)
- Kirsty E McAleese
- Translation and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK.
| | - Mohi Miah
- Translation and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Sophie Graham
- Translation and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Georgina M Hadfield
- Translation and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Lauren Walker
- Translation and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Mary Johnson
- Translation and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Sean J Colloby
- Translation and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Alan J Thomas
- Translation and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Charles DeCarli
- Department of Neurology, University of California, Davis, CA, USA
| | - David Koss
- Translation and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Johannes Attems
- Translation and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
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25
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Heger IS, Deckers K, Schram MT, Stehouwer CDA, Dagnelie PC, van der Kallen CJH, Koster A, Eussen SJPM, Jansen JFA, Verhey FRJ, van Boxtel MPJ, Köhler S. Associations of the Lifestyle for Brain Health Index With Structural Brain Changes and Cognition: Results From the Maastricht Study. Neurology 2021; 97:e1300-e1312. [PMID: 34433680 PMCID: PMC8480401 DOI: 10.1212/wnl.0000000000012572] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Accepted: 07/01/2021] [Indexed: 11/15/2022] Open
Abstract
Background and Objectives Observational research has shown that a substantial proportion of all dementia cases worldwide are attributable to modifiable risk factors. Dementia risk scores might be useful to identify high-risk individuals and monitor treatment adherence. The objective of this study was to investigate whether a dementia risk score, the Lifestyle for Brain Health (LIBRA) index, is associated with MRI markers and cognitive functioning/impairment in the general population. Methods Cross-sectional data were used from the observational population-based cohort of The Maastricht Study. The weighted compound score of LIBRA (including 12 dementia risk and protective factors, e.g., hypertension, physical inactivity) was calculated, with higher scores indicating higher dementia risk. Standardized volumes of white matter, gray matter, and CSF (as proxy for general brain atrophy), white matter hyperintensities, and presence of cerebral small vessel disease were derived from 3T MRI. Cognitive functioning was tested in 3 domains: memory, information processing speed, and executive function and attention. Values ≤1.5 SDs below the average were defined as cognitive impairment. Multiple regression analyses and structural equation modeling were used, adjusted for age, sex, education, intracranial volume, and type 2 diabetes. Results Participants (n = 4,164; mean age 59 years; 49.7% men) with higher LIBRA scores (mean 1.19, range −2.7 to 9.2), denoting higher dementia risk, had higher volumes of white matter hyperintensities (β = 0.051, p = 0.002) and lower scores on information processing speed (β = −0.067, p = 0.001) and executive function and attention (β = −0.065, p = 0.004). Only in men, associations between LIBRA score and volumes of gray matter (β = −0.093, p < 0.001) and CSF (β = 0.104, p < 0.001) and memory (β = −0.054, p = 0.026) were found. White matter hyperintensities and CSF volume partly mediated the association between LIBRA score and cognition. Discussion Higher health- and lifestyle-based dementia risk is associated with markers of general brain atrophy, cerebrovascular pathology, and worse cognition, suggesting that LIBRA meaningfully summarizes individual lifestyle-related brain health. Improving LIBRA factors on an individual level might improve population brain health. Sex differences in lifestyle-related pathology and cognition need to be further explored. Classification of Evidence This study provides Class II evidence that higher LIBRA scores are significantly associated with lower scores in some cognitive domains and a higher risk of cognitive impairment.
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Affiliation(s)
- Irene S Heger
- From the School for Mental Health and Neuroscience (I.S.H., K.D., M.T.S., J.F.A.J., F.R.J.V., M.P.J.v.B., S.K.), Department of Psychiatry and Neuropsychology (I.S.H., K.D., F.R.J.V., M.P.J.v.B., S.K.), School for Cardiovascular Diseases (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K., S.J.P.M.E.), Care and Public Health Research Institute (A.K.), Department of Social Medicine (A.K.), and Department of Epidemiology (S.J.P.M.E.), Maastricht University; and Heart and Vascular Center (M.T.S.), Department of Internal Medicine (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K.), and Department of Radiology (J.F.A.J.), Maastricht University Medical Center+, the Netherlands.
| | - Kay Deckers
- From the School for Mental Health and Neuroscience (I.S.H., K.D., M.T.S., J.F.A.J., F.R.J.V., M.P.J.v.B., S.K.), Department of Psychiatry and Neuropsychology (I.S.H., K.D., F.R.J.V., M.P.J.v.B., S.K.), School for Cardiovascular Diseases (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K., S.J.P.M.E.), Care and Public Health Research Institute (A.K.), Department of Social Medicine (A.K.), and Department of Epidemiology (S.J.P.M.E.), Maastricht University; and Heart and Vascular Center (M.T.S.), Department of Internal Medicine (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K.), and Department of Radiology (J.F.A.J.), Maastricht University Medical Center+, the Netherlands
| | - Miranda T Schram
- From the School for Mental Health and Neuroscience (I.S.H., K.D., M.T.S., J.F.A.J., F.R.J.V., M.P.J.v.B., S.K.), Department of Psychiatry and Neuropsychology (I.S.H., K.D., F.R.J.V., M.P.J.v.B., S.K.), School for Cardiovascular Diseases (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K., S.J.P.M.E.), Care and Public Health Research Institute (A.K.), Department of Social Medicine (A.K.), and Department of Epidemiology (S.J.P.M.E.), Maastricht University; and Heart and Vascular Center (M.T.S.), Department of Internal Medicine (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K.), and Department of Radiology (J.F.A.J.), Maastricht University Medical Center+, the Netherlands
| | - Coen D A Stehouwer
- From the School for Mental Health and Neuroscience (I.S.H., K.D., M.T.S., J.F.A.J., F.R.J.V., M.P.J.v.B., S.K.), Department of Psychiatry and Neuropsychology (I.S.H., K.D., F.R.J.V., M.P.J.v.B., S.K.), School for Cardiovascular Diseases (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K., S.J.P.M.E.), Care and Public Health Research Institute (A.K.), Department of Social Medicine (A.K.), and Department of Epidemiology (S.J.P.M.E.), Maastricht University; and Heart and Vascular Center (M.T.S.), Department of Internal Medicine (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K.), and Department of Radiology (J.F.A.J.), Maastricht University Medical Center+, the Netherlands
| | - Pieter C Dagnelie
- From the School for Mental Health and Neuroscience (I.S.H., K.D., M.T.S., J.F.A.J., F.R.J.V., M.P.J.v.B., S.K.), Department of Psychiatry and Neuropsychology (I.S.H., K.D., F.R.J.V., M.P.J.v.B., S.K.), School for Cardiovascular Diseases (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K., S.J.P.M.E.), Care and Public Health Research Institute (A.K.), Department of Social Medicine (A.K.), and Department of Epidemiology (S.J.P.M.E.), Maastricht University; and Heart and Vascular Center (M.T.S.), Department of Internal Medicine (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K.), and Department of Radiology (J.F.A.J.), Maastricht University Medical Center+, the Netherlands
| | - Carla J H van der Kallen
- From the School for Mental Health and Neuroscience (I.S.H., K.D., M.T.S., J.F.A.J., F.R.J.V., M.P.J.v.B., S.K.), Department of Psychiatry and Neuropsychology (I.S.H., K.D., F.R.J.V., M.P.J.v.B., S.K.), School for Cardiovascular Diseases (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K., S.J.P.M.E.), Care and Public Health Research Institute (A.K.), Department of Social Medicine (A.K.), and Department of Epidemiology (S.J.P.M.E.), Maastricht University; and Heart and Vascular Center (M.T.S.), Department of Internal Medicine (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K.), and Department of Radiology (J.F.A.J.), Maastricht University Medical Center+, the Netherlands
| | - Annemarie Koster
- From the School for Mental Health and Neuroscience (I.S.H., K.D., M.T.S., J.F.A.J., F.R.J.V., M.P.J.v.B., S.K.), Department of Psychiatry and Neuropsychology (I.S.H., K.D., F.R.J.V., M.P.J.v.B., S.K.), School for Cardiovascular Diseases (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K., S.J.P.M.E.), Care and Public Health Research Institute (A.K.), Department of Social Medicine (A.K.), and Department of Epidemiology (S.J.P.M.E.), Maastricht University; and Heart and Vascular Center (M.T.S.), Department of Internal Medicine (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K.), and Department of Radiology (J.F.A.J.), Maastricht University Medical Center+, the Netherlands
| | - Simone J P M Eussen
- From the School for Mental Health and Neuroscience (I.S.H., K.D., M.T.S., J.F.A.J., F.R.J.V., M.P.J.v.B., S.K.), Department of Psychiatry and Neuropsychology (I.S.H., K.D., F.R.J.V., M.P.J.v.B., S.K.), School for Cardiovascular Diseases (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K., S.J.P.M.E.), Care and Public Health Research Institute (A.K.), Department of Social Medicine (A.K.), and Department of Epidemiology (S.J.P.M.E.), Maastricht University; and Heart and Vascular Center (M.T.S.), Department of Internal Medicine (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K.), and Department of Radiology (J.F.A.J.), Maastricht University Medical Center+, the Netherlands
| | - Jacobus F A Jansen
- From the School for Mental Health and Neuroscience (I.S.H., K.D., M.T.S., J.F.A.J., F.R.J.V., M.P.J.v.B., S.K.), Department of Psychiatry and Neuropsychology (I.S.H., K.D., F.R.J.V., M.P.J.v.B., S.K.), School for Cardiovascular Diseases (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K., S.J.P.M.E.), Care and Public Health Research Institute (A.K.), Department of Social Medicine (A.K.), and Department of Epidemiology (S.J.P.M.E.), Maastricht University; and Heart and Vascular Center (M.T.S.), Department of Internal Medicine (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K.), and Department of Radiology (J.F.A.J.), Maastricht University Medical Center+, the Netherlands
| | - Frans R J Verhey
- From the School for Mental Health and Neuroscience (I.S.H., K.D., M.T.S., J.F.A.J., F.R.J.V., M.P.J.v.B., S.K.), Department of Psychiatry and Neuropsychology (I.S.H., K.D., F.R.J.V., M.P.J.v.B., S.K.), School for Cardiovascular Diseases (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K., S.J.P.M.E.), Care and Public Health Research Institute (A.K.), Department of Social Medicine (A.K.), and Department of Epidemiology (S.J.P.M.E.), Maastricht University; and Heart and Vascular Center (M.T.S.), Department of Internal Medicine (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K.), and Department of Radiology (J.F.A.J.), Maastricht University Medical Center+, the Netherlands
| | - Martin P J van Boxtel
- From the School for Mental Health and Neuroscience (I.S.H., K.D., M.T.S., J.F.A.J., F.R.J.V., M.P.J.v.B., S.K.), Department of Psychiatry and Neuropsychology (I.S.H., K.D., F.R.J.V., M.P.J.v.B., S.K.), School for Cardiovascular Diseases (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K., S.J.P.M.E.), Care and Public Health Research Institute (A.K.), Department of Social Medicine (A.K.), and Department of Epidemiology (S.J.P.M.E.), Maastricht University; and Heart and Vascular Center (M.T.S.), Department of Internal Medicine (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K.), and Department of Radiology (J.F.A.J.), Maastricht University Medical Center+, the Netherlands
| | - Sebastian Köhler
- From the School for Mental Health and Neuroscience (I.S.H., K.D., M.T.S., J.F.A.J., F.R.J.V., M.P.J.v.B., S.K.), Department of Psychiatry and Neuropsychology (I.S.H., K.D., F.R.J.V., M.P.J.v.B., S.K.), School for Cardiovascular Diseases (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K., S.J.P.M.E.), Care and Public Health Research Institute (A.K.), Department of Social Medicine (A.K.), and Department of Epidemiology (S.J.P.M.E.), Maastricht University; and Heart and Vascular Center (M.T.S.), Department of Internal Medicine (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K.), and Department of Radiology (J.F.A.J.), Maastricht University Medical Center+, the Netherlands
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26
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Lloret A, Esteve D, Lloret MA, Monllor P, López B, León JL, Cervera-Ferri A. Is Oxidative Stress the Link Between Cerebral Small Vessel Disease, Sleep Disruption, and Oligodendrocyte Dysfunction in the Onset of Alzheimer's Disease? Front Physiol 2021; 12:708061. [PMID: 34512381 PMCID: PMC8424010 DOI: 10.3389/fphys.2021.708061] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Accepted: 07/28/2021] [Indexed: 01/07/2023] Open
Abstract
Oxidative stress is an early occurrence in the development of Alzheimer’s disease (AD) and one of its proposed etiologic hypotheses. There is sufficient experimental evidence supporting the theory that impaired antioxidant enzymatic activity and increased formation of reactive oxygen species (ROS) take place in this disease. However, the antioxidant treatments fail to stop its advancement. Its multifactorial condition and the diverse toxicological cascades that can be initiated by ROS could possibly explain this failure. Recently, it has been suggested that cerebral small vessel disease (CSVD) contributes to the onset of AD. Oxidative stress is a central hallmark of CSVD and is depicted as an early causative factor. Moreover, data from various epidemiological and clinicopathological studies have indicated a relationship between CSVD and AD where endothelial cells are a source of oxidative stress. These cells are also closely related to oligodendrocytes, which are, in particular, sensitive to oxidation and lead to myelination being compromised. The sleep/wake cycle is another important control in the proliferation, migration, and differentiation of oligodendrocytes, and sleep loss reduces myelin thickness. Moreover, sleep plays a crucial role in resistance against CSVD, and poor sleep quality increases the silent markers of this vascular disease. Sleep disruption is another early occurrence in AD and is related to an increase in oxidative stress. In this study, the relationship between CSVD, oligodendrocyte dysfunction, and sleep disorders is discussed while focusing on oxidative stress as a common occurrence and its possible role in the onset of AD.
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Affiliation(s)
- Ana Lloret
- INCLIVA, CIBERFES, Department of Physiology, Faculty of Medicine, University of Valencia, Valencia, Spain
| | - Daniel Esteve
- INCLIVA, CIBERFES, Department of Physiology, Faculty of Medicine, University of Valencia, Valencia, Spain
| | - Maria Angeles Lloret
- Department of Clinical Neurophysiology, Hospital Clínico Universitario de Valencia, Valencia, Spain
| | - Paloma Monllor
- INCLIVA, CIBERFES, Department of Physiology, Faculty of Medicine, University of Valencia, Valencia, Spain
| | - Begoña López
- Department of Neurology, Hospital Clínico Universitario de Valencia, Valencia, Spain
| | - José Luis León
- Departament of Neuroradiology, Ascires Biomedical Group, Hospital Clinico Universitario, Valencia, Spain
| | - Ana Cervera-Ferri
- Department of Anatomy and Human Embryology, University of Valencia, Valencia, Spain
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27
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Park M, Baik K, Lee YG, Kang SW, Jung JH, Jeong SH, Lee PH, Sohn YH, Ye BS. Implication of Small Vessel Disease MRI Markers in Alzheimer's Disease and Lewy Body Disease. J Alzheimers Dis 2021; 83:545-556. [PMID: 34366356 DOI: 10.3233/jad-210669] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
BACKGROUND Small vessel disease (SVD) magnetic resonance imaging (MRI) markers including deep and periventricular white matter hyperintensities (PWMH), lacunes, and microbleeds are frequently observed in Alzheimer's disease (AD) and Lewy body disease (LBD), but their implication has not been clearly elucidated. OBJECTIVE To investigate the implication of SVD MRI markers in cognitively impaired patients with AD and/or LBD. METHODS We consecutively recruited 57 patients with pure AD-related cognitive impairment (ADCI), 49 with pure LBD-related cognitive impairment (LBCI), 45 with mixed ADCI/LBCI, and 34 controls. All participants underwent neuropsychological tests, brain MRI, and amyloid positron emission tomography. SVD MRI markers including the severity of deep and PWMH and the number of lacunes and microbleeds were visually rated. The relationships among vascular risk factors, SVD MRI markers, ADCI, LBCI, and cognitive scores were investigated after controlling for appropriate covariates. RESULTS LBCI was associated with more severe PWMH, which was conversely associated with an increased risk of LBCI independently of vascular risk factors and ADCI. PWMH was associated with attention and visuospatial dysfunction independently of vascular risk factors, ADCI, and LBCI. Both ADCI and LBCI were associated with more lobar microbleeds, but not with deep microbleeds. CONCLUSION Our findings suggest that PWMH could reflect degenerative process related with LBD, and both AD and LBD independently increase lobar microbleeds.
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Affiliation(s)
- Mincheol Park
- Department of Neurology, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Kyoungwon Baik
- Department of Neurology, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Young-Gun Lee
- Department of Neurology, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Sung Woo Kang
- Department of Neurology, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Jin Ho Jung
- Department of Neurology, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Seong Ho Jeong
- Department of Neurology, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Phil Hyu Lee
- Department of Neurology, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Young H Sohn
- Department of Neurology, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Byoung Seok Ye
- Department of Neurology, Yonsei University College of Medicine, Seoul, Republic of Korea
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28
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Zee B, Wong Y, Lee J, Fan Y, Zeng J, Lam B, Wong A, Shi L, Lee A, Kwok C, Lai M, Mok V, Lau A. Machine-learning method for localization of cerebral white matter hyperintensities in healthy adults based on retinal images. Brain Commun 2021; 3:fcab124. [PMID: 34222872 PMCID: PMC8249101 DOI: 10.1093/braincomms/fcab124] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2020] [Revised: 03/26/2021] [Accepted: 04/14/2021] [Indexed: 11/12/2022] Open
Abstract
Retinal vessels are known to be associated with various cardiovascular and cerebrovascular disease outcomes. Recent research has shown significant correlations between retinal characteristics and the presence of cerebral small vessel disease as measured by white matter hyperintensities from cerebral magnetic resonance imaging. Early detection of age-related white matter changes using retinal images is potentially helpful for population screening and allow early behavioural and lifestyle intervention. This study investigates the ability of the machine-learning method for the localization of brain white matter hyperintensities. All subjects were age 65 or above without any history of stroke and dementia and recruited from local community centres and community networks. Subjects with known retinal disease or disease influencing vessel structure in colour retina images were excluded. All subjects received MRI on the brain, and age-related white matter changes grading was determined from MRI as the primary endpoint. The presence of age-related white matter changes on each of the six brain regions was also studied. Retinal images were captured using a fundus camera, and the analysis was done based on a machine-learning approach. A total of 240 subjects are included in the study. The analysis of various brain regions included the left and right sides of frontal lobes, parietal–occipital lobes and basal ganglia. Our results suggested that data from both eyes are essential for detecting age-related white matter changes in the brain regions, but the retinal parameters useful for estimation of the probability of age-related white matter changes in each of the brain regions may differ for different locations. Using a classification and regression tree approach, we also found that at least three significant heterogeneous subgroups of subjects were identified to be essential for the localization of age-related white matter changes. Namely those with age-related white matter changes in the right frontal lobe, those without age-related white matter changes in the right frontal lobe but with age-related white matter changes in the left parietal–occipital lobe, and the rest of the subjects. Outcomes such as risks of severe grading of age-related white matter changes and the proportion of hypertension were significantly related to these subgroups. Our study showed that automatic retinal image analysis is a convenient and non-invasive screening tool for detecting age-related white matter changes and cerebral small vessel disease with good overall performance. The localization analysis for various brain regions shows that the classification models on each of the six brain regions can be done, and it opens up potential future clinical application.
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Affiliation(s)
- Benny Zee
- Centre for Clinical Research and Biostatistics, Jockey Club School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong, China.,Clinical Trials and Biostatistics Lab, CUHK Shenzhen Research Institute, Shenzhen, China
| | - Yanny Wong
- Margaret KL Cheung Research Centre for Management of Parkinsonism, Therese Pei Fong Chow Research Centre for Prevention of Dementia and Gerald Choa Neuroscience Centre, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong, China.,Division of Neurology, Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong, China
| | - Jack Lee
- Centre for Clinical Research and Biostatistics, Jockey Club School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong, China.,Clinical Trials and Biostatistics Lab, CUHK Shenzhen Research Institute, Shenzhen, China
| | - Yuhua Fan
- Department of Neurology, First Affiliated Hospital of Sun Yat-Sen University, Guangdong, China.,Key Laboratory for Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department, National Key Discipline, Guangzhou 510080, China
| | - Jinsheng Zeng
- Department of Neurology, First Affiliated Hospital of Sun Yat-Sen University, Guangdong, China.,Key Laboratory for Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department, National Key Discipline, Guangzhou 510080, China
| | - Bonnie Lam
- Margaret KL Cheung Research Centre for Management of Parkinsonism, Therese Pei Fong Chow Research Centre for Prevention of Dementia and Gerald Choa Neuroscience Centre, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong, China.,Division of Neurology, Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong, China
| | - Adrian Wong
- Margaret KL Cheung Research Centre for Management of Parkinsonism, Therese Pei Fong Chow Research Centre for Prevention of Dementia and Gerald Choa Neuroscience Centre, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong, China.,Division of Neurology, Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong, China
| | - Lin Shi
- BrainNow Research Institute, Shenzhen, Guangdong Province, China.,Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, Hong Kong, China
| | - Allen Lee
- Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong, China
| | - Chloe Kwok
- Centre for Clinical Research and Biostatistics, Jockey Club School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong, China
| | - Maria Lai
- Centre for Clinical Research and Biostatistics, Jockey Club School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong, China
| | - Vincent Mok
- Margaret KL Cheung Research Centre for Management of Parkinsonism, Therese Pei Fong Chow Research Centre for Prevention of Dementia and Gerald Choa Neuroscience Centre, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong, China.,Division of Neurology, Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong, China
| | - Alexander Lau
- Margaret KL Cheung Research Centre for Management of Parkinsonism, Therese Pei Fong Chow Research Centre for Prevention of Dementia and Gerald Choa Neuroscience Centre, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong, China.,Division of Neurology, Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong, China
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Pålhaugen L, Sudre CH, Tecelao S, Nakling A, Almdahl IS, Kalheim LF, Cardoso MJ, Johnsen SH, Rongve A, Aarsland D, Bjørnerud A, Selnes P, Fladby T. Brain amyloid and vascular risk are related to distinct white matter hyperintensity patterns. J Cereb Blood Flow Metab 2021; 41:1162-1174. [PMID: 32955960 PMCID: PMC8054718 DOI: 10.1177/0271678x20957604] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
White matter hyperintensities (WMHs) are associated with vascular risk and Alzheimer's disease. In this study, we examined relations between WMH load and distribution, amyloid pathology and vascular risk in 339 controls and cases with either subjective (SCD) or mild cognitive impairment (MCI). Regional deep (DWMH) and periventricular (PWMH) WMH loads were determined using an automated algorithm. We stratified on Aβ1-42 pathology (Aβ+/-) and analyzed group differences, as well as associations with Framingham Risk Score for cardiovascular disease (FRS-CVD) and age. Occipital PWMH (p = 0.001) and occipital DWMH (p = 0.003) loads were increased in SCD-Aβ+ compared with Aβ- controls. In MCI-Aβ+ compared with Aβ- controls, there were differences in global WMH (p = 0.003), as well as occipital DWMH (p = 0.001) and temporal DWMH (p = 0.002) loads. FRS-CVD was associated with frontal PWMHs (p = 0.003) and frontal DWMHs (p = 0.005), after adjusting for age. There were associations between global and all regional WMH loads and age. In summary, posterior WMH loads were increased in SCD-Aβ+ and MCI-Aβ+ cases, whereas frontal WMHs were associated with vascular risk. The differences in WMH topography support the use of regional WMH load as an early-stage marker of etiology.
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Affiliation(s)
- Lene Pålhaugen
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway.,Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Carole H Sudre
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.,Dementia Research Centre, Institute of Neurology, University College London, London, UK.,Department of Medical Physics, University College London, London, UK
| | - Sandra Tecelao
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway
| | | | - Ina S Almdahl
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Geriatric Psychiatry, Oslo University Hospital, Oslo, Norway
| | - Lisa F Kalheim
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - M Jorge Cardoso
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.,Dementia Research Centre, Institute of Neurology, University College London, London, UK.,Department of Medical Physics, University College London, London, UK
| | - Stein H Johnsen
- Department of Neurology, University Hospital of North Norway, Tromsø, Norway.,Department of Clinical Medicine, Brain and Circulation Research Group, UiT The Arctic University of Norway, Tromsø, Norway
| | - Arvid Rongve
- Department of Research and Innovation, Haugesund Hospital, Haugesund, Norway.,Department of Clinical Medicine (K1), University of Bergen, Bergen, Norway
| | - Dag Aarsland
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway.,Department of Old Age Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,Center for Age-Related Diseases, Stavanger University Hospital, Stavanger, Norway
| | - Atle Bjørnerud
- Department of Diagnostic Physics, Oslo University Hospital, Oslo, Norway.,Department of Physics, University of Oslo, Oslo, Norway
| | - Per Selnes
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway.,Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Tormod Fladby
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway.,Institute of Clinical Medicine, University of Oslo, Oslo, Norway
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30
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Patterns of white matter hyperintensities associated with cognition in middle-aged cognitively healthy individuals. Brain Imaging Behav 2021; 14:2012-2023. [PMID: 31278650 PMCID: PMC7572336 DOI: 10.1007/s11682-019-00151-2] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
White matter hyperintensities (WMH) are commonly detected in the brain of elderly individuals and have been associated with a negative impact on multiple cognitive domains. We aim to investigate the impact of global and regional distribution of WMH on episodic memory and executive function in middle-aged cognitively unimpaired participants [N = 561 (45–75 years)] enriched for Alzheimer’s disease risk factors. WMH were automatically segmented from FLAIR, T1 and FSE MR images. WMH load was calculated both globally and regionally. At each cerebral lobe, regional WMH load was measured at four equidistant layers extending from the lateral ventricles to juxtacortical areas. Cognition was measured by The Memory Binding Test (MBT) and WAIS-IV subtests. Global composite z-scores were calculated for the two cognitive domains. Association between global and regional WMH measurements were sought against cognitive measures, both in global composite scores and in individual subtests. We adjusted cognition and WMH burden for the main sociodemographic (age, sex and education) and genetic factors (APOE-ε4). Memory and executive function were significantly associated with global WMH load. Regionally, lower executive performance was mainly associated with higher deep WMH load in frontal areas and, to a lower degree, in occipital, parietal and temporal regions. Lower episodic memory performance was correlated with higher WMH burden in deep frontal and occipital areas. Our novel methodological approach of regional analysis allowed us to reveal the association between cognition and WMH in strategic brain locations. Our results suggest that, even a small WMH load can impact cognition in cognitively unimpaired middle-aged subjects.
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31
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Sala-Vila A, Arenaza-Urquijo EM, Sánchez-Benavides G, Suárez-Calvet M, Milà-Alomà M, Grau-Rivera O, González-de-Echávarri JM, Crous-Bou M, Minguillón C, Fauria K, Operto G, Falcón C, Salvadó G, Cacciaglia R, Ingala S, Barkhof F, Schröder H, Scarmeas N, Gispert JD, Molinuevo JL. DHA intake relates to better cerebrovascular and neurodegeneration neuroimaging phenotypes in middle-aged adults at increased genetic risk of Alzheimer disease. Am J Clin Nutr 2021; 113:1627-1635. [PMID: 33733657 PMCID: PMC8168359 DOI: 10.1093/ajcn/nqab016] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Accepted: 01/11/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND The number of APOE-ε4 alleles is a major nonmodifiable risk factor for sporadic Alzheimer disease (AD). There is increasing evidence on the benefits of dietary DHA (22:6n-3) before the onset of AD symptoms, particularly in APOE-ε4 carriers. Brain alterations in the preclinical stage can be detected by structural MRI. OBJECTIVES We aimed, in middle-aged cognitively unimpaired individuals at increased risk of AD, to cross-sectionally investigate whether dietary DHA intake relates to cognitive performance and to MRI-based markers of cerebral small vessel disease and AD-related neurodegeneration, exploring the effect modification by APOE-ε4 status. METHODS In 340 participants of the ALFA (ALzheimer and FAmilies) study, which is enriched for APOE-ε4 carriership (n = 122, noncarriers; n = 157, 1 allele; n = 61, 2 alleles), we assessed self-reported DHA intake through an FFQ. We measured cognitive performance by administering episodic memory and executive function tests. We performed high-resolution structural MRI to assess cerebral small vessel disease [white matter hyperintensities (WMHs) and cerebral microbleeds (CMBs)] and AD-related brain atrophy (cortical thickness in an AD signature). We constructed regression models adjusted for potential confounders, exploring the interaction DHA × APOE-ε4. RESULTS We observed no significant associations between DHA and cognitive performance or WMH burden. We observed a nonsignificant inverse association between DHA and prevalence of lobar CMBs (OR: 0.446; 95% CI: 0.195, 1.018; P = 0.055). DHA was found to be significantly related to greater cortical thickness in the AD signature in homozygotes but not in nonhomozygotes (P-interaction = 0.045). The association strengthened when analyzing homozygotes and nonhomozygotes matched for risk factors. CONCLUSIONS In cognitively unimpaired APOE-ε4 homozygotes, dietary DHA intake related to structural patterns that may result in greater resilience to AD pathology. This is consistent with the current hypothesis that those subjects at highest risk would obtain the largest benefits from DHA supplementation in the preclinical stage.This trial was registered at clinicaltrials.gov as NCT01835717.
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Affiliation(s)
| | - Eider M Arenaza-Urquijo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain,Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain,Center for Biomedical Research Network on Frailty and Healthy Aging (CIBERFES), Madrid, Spain
| | - Gonzalo Sánchez-Benavides
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain,Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain,Center for Biomedical Research Network on Frailty and Healthy Aging (CIBERFES), Madrid, Spain
| | - Marc Suárez-Calvet
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain,Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain,Center for Biomedical Research Network on Frailty and Healthy Aging (CIBERFES), Madrid, Spain,Neurology Service, Hospital del Mar, Barcelona, Spain
| | - Marta Milà-Alomà
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain,Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain,Center for Biomedical Research Network on Frailty and Healthy Aging (CIBERFES), Madrid, Spain
| | - Oriol Grau-Rivera
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain,Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain,Neurology Service, Hospital del Mar, Barcelona, Spain
| | - José M González-de-Echávarri
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain,Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain,Center for Biomedical Research Network on Frailty and Healthy Aging (CIBERFES), Madrid, Spain
| | - Marta Crous-Bou
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain,Center for Biomedical Research Network on Frailty and Healthy Aging (CIBERFES), Madrid, Spain,Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA,Unit of Nutrition and Cancer, Cancer Epidemiology Research Program, Catalan Institute of Oncology (ICO)–Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain
| | - Carolina Minguillón
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain,Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
| | - Karine Fauria
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
| | - Grégory Operto
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain,Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain,Center for Biomedical Research Network on Frailty and Healthy Aging (CIBERFES), Madrid, Spain
| | - Carles Falcón
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain,Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain,Center for Biomedical Research Network on Bioengineering, Biomaterials, and Nanomedicine (CIBERBBN), Madrid, Spain,Department of Experimental and Health Sciences, Pompeu Fabra University, Barcelona, Spain
| | - Gemma Salvadó
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain,Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain,Center for Biomedical Research Network on Frailty and Healthy Aging (CIBERFES), Madrid, Spain
| | - Raffaele Cacciaglia
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain,Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain,Center for Biomedical Research Network on Frailty and Healthy Aging (CIBERFES), Madrid, Spain
| | - Silvia Ingala
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands,Institute of Neurology, University College London, London, United Kingdom,Institute of Healthcare Engineering, University College London, London, United Kingdom
| | - Helmut Schröder
- Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain,Center for Biomedical Research Network on Epidemiology and Public Health (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
| | - Nikolaos Scarmeas
- 1st Department of Neurology, Aiginition Hospital, National and Kapodistrian University of Athens Medical School, Athens, Greece,Department of Neurology, The Gertrude H Sergievsky Center, Taub Institute for Research in Alzheimer's Disease and the Aging Brain, Columbia University, New York, NY, USA
| | - Juan-Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain,Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain,Center for Biomedical Research Network on Bioengineering, Biomaterials, and Nanomedicine (CIBERBBN), Madrid, Spain,Department of Experimental and Health Sciences, Pompeu Fabra University, Barcelona, Spain
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32
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Ozzoude M, Ramirez J, Raamana PR, Holmes MF, Walker K, Scott CJM, Gao F, Goubran M, Kwan D, Tartaglia MC, Beaton D, Saposnik G, Hassan A, Lawrence-Dewar J, Dowlatshahi D, Strother SC, Symons S, Bartha R, Swartz RH, Black SE. Cortical Thickness Estimation in Individuals With Cerebral Small Vessel Disease, Focal Atrophy, and Chronic Stroke Lesions. Front Neurosci 2020; 14:598868. [PMID: 33381009 PMCID: PMC7768006 DOI: 10.3389/fnins.2020.598868] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Accepted: 11/24/2020] [Indexed: 01/18/2023] Open
Abstract
BACKGROUND Regional changes to cortical thickness in individuals with neurodegenerative and cerebrovascular diseases (CVD) can be estimated using specialized neuroimaging software. However, the presence of cerebral small vessel disease, focal atrophy, and cortico-subcortical stroke lesions, pose significant challenges that increase the likelihood of misclassification errors and segmentation failures. PURPOSE The main goal of this study was to examine a correction procedure developed for enhancing FreeSurfer's (FS's) cortical thickness estimation tool, particularly when applied to the most challenging MRI obtained from participants with chronic stroke and CVD, with varying degrees of neurovascular lesions and brain atrophy. METHODS In 155 CVD participants enrolled in the Ontario Neurodegenerative Disease Research Initiative (ONDRI), FS outputs were compared between a fully automated, unmodified procedure and a corrected procedure that accounted for potential sources of error due to atrophy and neurovascular lesions. Quality control (QC) measures were obtained from both procedures. Association between cortical thickness and global cognitive status as assessed by the Montreal Cognitive Assessment (MoCA) score was also investigated from both procedures. RESULTS Corrected procedures increased "Acceptable" QC ratings from 18 to 76% for the cortical ribbon and from 38 to 92% for tissue segmentation. Corrected procedures reduced "Fail" ratings from 11 to 0% for the cortical ribbon and 62 to 8% for tissue segmentation. FS-based segmentation of T1-weighted white matter hypointensities were significantly greater in the corrected procedure (5.8 mL vs. 15.9 mL, p < 0.001). The unmodified procedure yielded no significant associations with global cognitive status, whereas the corrected procedure yielded positive associations between MoCA total score and clusters of cortical thickness in the left superior parietal (p = 0.018) and left insula (p = 0.04) regions. Further analyses with the corrected cortical thickness results and MoCA subscores showed a positive association between left superior parietal cortical thickness and Attention (p < 0.001). CONCLUSION These findings suggest that correction procedures which account for brain atrophy and neurovascular lesions can significantly improve FS's segmentation results and reduce failure rates, thus maximizing power by preventing the loss of our important study participants. Future work will examine relationships between cortical thickness, cerebral small vessel disease, and cognitive dysfunction due to neurodegenerative disease in the ONDRI study.
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Affiliation(s)
- Miracle Ozzoude
- LC Campbell Cognitive Neurology Research, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Joel Ramirez
- LC Campbell Cognitive Neurology Research, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | | | - Melissa F. Holmes
- LC Campbell Cognitive Neurology Research, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Kirstin Walker
- LC Campbell Cognitive Neurology Research, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Christopher J. M. Scott
- LC Campbell Cognitive Neurology Research, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Fuqiang Gao
- LC Campbell Cognitive Neurology Research, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Maged Goubran
- LC Campbell Cognitive Neurology Research, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Donna Kwan
- Centre for Neuroscience Studies, Queens University, Kingston, ON, Canada
| | - Maria C. Tartaglia
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, ON, Canada
- Division of Neurology, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - Derek Beaton
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada
| | - Gustavo Saposnik
- Stroke Outcomes and Decision Neuroscience Research Unit, Division of Neurology, St. Michael’s Hospital, University of Toronto, Toronto, ON, Canada
| | - Ayman Hassan
- Thunder Bay Regional Health Research Institute, Thunder Bay, ON, Canada
| | | | - Dariush Dowlatshahi
- Department of Medicine (Neurology), Ottawa Hospital Research Institute, University of Ottawa, Ottawa, ON, Canada
| | - Stephen C. Strother
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Sean Symons
- Department of Medical Imaging, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Robert Bartha
- Centre for Functional and Metabolic Mapping, Department of Medical Biophysics, Robarts Research Institute, University of Western Ontario, London, ON, Canada
| | - Richard H. Swartz
- Department of Medicine (Neurology), Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Sandra E. Black
- LC Campbell Cognitive Neurology Research, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
- Department of Medicine (Neurology), Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
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Common Brain Structural Alterations Associated with Cardiovascular Disease Risk Factors and Alzheimer's Dementia: Future Directions and Implications. Neuropsychol Rev 2020; 30:546-557. [PMID: 33011894 DOI: 10.1007/s11065-020-09460-6] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2019] [Accepted: 09/24/2020] [Indexed: 01/18/2023]
Abstract
Recent reports suggest declines in the age-specific risk of Alzheimer's dementia in higher income Western countries. At the same time, investigators believe that worldwide trends of increasing mid-life modifiable risk factors [e.g., cardiovascular disease (CVD) risk factors] coupled with the growth of the world's oldest age groups may nonetheless lead to an increase in Alzheimer's dementia. Thus, understanding the overlap in neuroanatomical profiles associated with CVD risk factors and AD may offer more relevant targets for investigating ways to reduce the growing dementia epidemic than current targets specific to isolated AD-related neuropathology. We hypothesized that a core group of common brain structural alterations exist between CVD risk factors and Alzheimer's dementia. Two co-authors conducted independent literature reviews in PubMed using search terms for CVD risk factor burden (separate searches for 'cardiovascular disease risk factors', 'hypertension', and 'Type 2 diabetes') and 'aging' or 'Alzheimer's dementia' with either 'grey matter volumes' or 'white matter'. Of studies that reported regionally localized results, we found support for our hypothesis, determining 23 regions commonly associated with both CVD risk factors and Alzheimer's dementia. Within this context, we outline future directions for research as well as larger cerebrovascular implications for these commonalities. Overall, this review supports previous as well as more recent calls for the consideration that both vascular and neurodegenerative factors contribute to the pathogenesis of dementia.
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34
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Porcu M, Operamolla A, Scapin E, Garofalo P, Destro F, Caneglias A, Suri JS, Falini A, Defazio G, Marrosu F, Saba L. Effects of White Matter Hyperintensities on Brain Connectivity and Hippocampal Volume in Healthy Subjects According to Their Localization. Brain Connect 2020; 10:436-447. [DOI: 10.1089/brain.2020.0774] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Affiliation(s)
- Michele Porcu
- Department of Radiology, Azienda Ospedaliera Universitaria di Cagliari, University of Cagliari, Cagliari, Italy
| | - Annunziata Operamolla
- Department of Radiology, Azienda Ospedaliera Universitaria di Cagliari, University of Cagliari, Cagliari, Italy
| | - Elisa Scapin
- Department of Radiology, Azienda Ospedaliera Universitaria di Cagliari, University of Cagliari, Cagliari, Italy
| | - Paolo Garofalo
- Department of Radiology, Azienda Ospedaliera Universitaria di Cagliari, University of Cagliari, Cagliari, Italy
| | - Francesco Destro
- Department of Radiology, Azienda Ospedaliera Universitaria di Cagliari, University of Cagliari, Cagliari, Italy
| | - Alessandro Caneglias
- Department of Radiology, Azienda Ospedaliera Universitaria di Cagliari, University of Cagliari, Cagliari, Italy
| | - Jasjit S. Suri
- Stroke Monitoring and Diagnostic Division, AtheroPoint™ LLC, Roseville, California, USA
| | - Andrea Falini
- Department of Neuroradiology, Università Vita-Salute San Raffaele, Milan, Italy
| | - Giovanni Defazio
- Department of Neurology, Azienda Ospedaliera Universitaria di Cagliari, University of Cagliari, Cagliari, Italy
| | - Francesco Marrosu
- Stroke Monitoring and Diagnostic Division, AtheroPoint™ LLC, Roseville, California, USA
| | - Luca Saba
- Department of Radiology, Azienda Ospedaliera Universitaria di Cagliari, University of Cagliari, Cagliari, Italy
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35
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Veldsman M, Kindalova P, Husain M, Kosmidis I, Nichols TE. Spatial distribution and cognitive impact of cerebrovascular risk-related white matter hyperintensities. Neuroimage Clin 2020; 28:102405. [PMID: 32971464 PMCID: PMC7511743 DOI: 10.1016/j.nicl.2020.102405] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Revised: 08/03/2020] [Accepted: 08/25/2020] [Indexed: 02/01/2023]
Abstract
OBJECTIVES White matter hyperintensities (WMHs) are considered macroscale markers of cerebrovascular burden and are associated with increased risk of vascular cognitive impairment and dementia. However, the spatial location of WMHs has typically been considered in broad categories of periventricular versus deep white matter. The spatial distribution of WHMs associated with individual cerebrovascular risk factors (CVR), controlling for frequently comorbid risk factors, has not been systematically investigated at the population level in a healthy ageing cohort. Furthermore, there is an inconsistent relationship between total white matter hyperintensity load and cognition, which may be due to the confounding of several simultaneous risk factors in models based on smaller cohorts. METHODS We examined trends in individual CVR factors on total WMH burden in 13,680 individuals (aged 45-80) using data from the UK Biobank. We estimated the spatial distribution of white matter hyperintensities associated with each risk factor and their contribution to explaining total WMH load using voxel-wise probit regression and univariate linear regression. Finally, we explored the impact of CVR-related WMHs on speed of processing using regression and mediation analysis. RESULTS Contrary to the assumed dominance of hypertension as the biggest predictor of WMH burden, we show associations with a number of risk factors including diabetes, heavy smoking, APOE ε4/ε4 status and high waist-to-hip ratio of similar, or greater magnitude to hypertension. The spatial distribution of WMHs varied considerably with individual cerebrovascular risk factors. There were independent effects of visceral adiposity, as measured by waist-to-hip ratio, and carriage of the APOE ε4 allele in terms of the unique spatial distribution of CVR-related WMHs. Importantly, the relationship between total WMH load and speed of processing was mediated by waist-to-hip ratio suggesting cognitive consequences to WMHs associated with excessive visceral fat deposition. CONCLUSION Waist-to-hip ratio, diabetes, heavy smoking, hypercholesterolemia and homozygous APOE ε4 status are important risk factors, beyond hypertension, associated with WMH total burden and warrant careful control across ageing. The spatial distribution associated with different risk factors may provide important clues as to the pathogenesis and cognitive consequences of WMHs. High waist-to-hip ratio is a key risk factor associated with slowing in speed of processing. With global obesity levels rising, focused management of visceral adiposity may present a useful strategy for the mitigation of cognitive decline in ageing.
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Affiliation(s)
- Michele Veldsman
- Wellcome Centre for Integrative Neuroscience, Department of Experimental Psychology, University of Oxford, UK
| | | | - Masud Husain
- Wellcome Centre for Integrative Neuroscience, Department of Experimental Psychology, University of Oxford, UK
| | - Ioannis Kosmidis
- Department of Statistics, University of Warwick, UK; The Alan Turing Institute, London, UK
| | - Thomas E Nichols
- Department of Statistics, University of Warwick, UK; Big Data Institute, Nuffield Department of Population Health, University of Oxford, UK
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36
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Kim HW, Hong J, Jeon JC. Cerebral Small Vessel Disease and Alzheimer's Disease: A Review. Front Neurol 2020; 11:927. [PMID: 32982937 PMCID: PMC7477392 DOI: 10.3389/fneur.2020.00927] [Citation(s) in RCA: 51] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Accepted: 07/17/2020] [Indexed: 12/12/2022] Open
Abstract
Alzheimer's disease (AD) is the most common cause of dementia. Despite this, clear pathophysiology for AD has not been confirmed, and effective treatments are still not available. As AD results in a complex disease process for cognitive decline, various theories have been suggested as the cause of AD. Recently, cerebral small vessel disease (SVD) has been suggested to contribute to the pathogenesis of AD, as well as contributing to vascular dementia. Cerebral SVD refers to a varied group of diseases that affect cerebral small arteries and microvessels. These can be seen as white matter hyperintensities, cerebral microbleeds, and lacunes on magnetic resonance imaging. Data from epidemiological and clinical-pathological studies have found evidence of the relationship between cerebral SVD and AD. This review aims to discuss the complex relationship between cerebral SVD and AD. Recent reports that evaluate the association between these diseases will be reviewed.
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Affiliation(s)
- Hae Won Kim
- Department of Nuclear Medicine, Keimyung University Dongsan Medical Center, Daegu, South Korea
| | - Jeongho Hong
- Department of Neurology, Keimyung University Dongsan Medical Center, Daegu, South Korea
| | - Jae Cheon Jeon
- Institute for Medical Science, Keimyung University School of Medicine, Daegu, South Korea
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Barbera M, Kulmala J, Lisko I, Pietilä E, Rosenberg A, Hallikainen I, Hallikainen M, Laatikainen T, Lehtisalo J, Neuvonen E, Rusanen M, Soininen H, Tuomilehto J, Ngandu T, Solomon A, Kivipelto M. Third follow-up of the Cardiovascular Risk Factors, Aging and Dementia (CAIDE) cohort investigating determinants of cognitive, physical, and psychosocial wellbeing among the oldest old: the CAIDE85+ study protocol. BMC Geriatr 2020; 20:238. [PMID: 32650731 PMCID: PMC7350760 DOI: 10.1186/s12877-020-01617-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Accepted: 06/15/2020] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND The oldest old is the fastest growing age group worldwide and the most prone to severe disability, especially in relation to loss of cognitive function. Improving our understanding of the predictors of cognitive, physical and psychosocial wellbeing among the oldest old can result in substantial benefits for the individuals and for the society as a whole. The Cardiovascular Risk Factors, Aging and Dementia (CAIDE) study investigated risk factors and determinants of cognitive impairment in a population-based longitudinal cohort, which was first examined between 1972 and 1992, when individuals were in their midlife, and re-assessed in 1998 and 2005-2009. Most of the study participants are currently aged 85 years or older. We aim to re-examine the cohort's survivors and gain further insights on the mechanisms underlying both cognitive and overall healthy ageing at old age. METHODS CAIDE85+ is the third follow-up of the CAIDE study participants. All individuals still alive and living in the Kuopio and Joensuu areas of Eastern Finland, from the original CAIDE cohort (two random samples, N = 2000 + ~ 900), will be invited to a re-examination. The assessment includes self-reported data related to basic demographics and lifestyle, as well as psychosocial and physical health status. Cognitive and physical evaluations are also conducted. Blood biomarkers relevant for dementia and ageing are assessed. Primary outcomes are the measurements related to cognition and daily life functioning (CERAD, Trail Making Test-A, Letter-Digit Substitution Test, Clinical Dementia Rating and Activities of Daily Living). Secondary endpoints of the study are outcomes related to physical health status, psychosocial wellbeing, as well as age-related health indicators. DISCUSSION Through a follow-up of more than 40 years, CAIDE85+ will provide invaluable information on the risk and protective factors that contribute to cognitive and physical health, as well as ageing and longevity. STUDY REGISTRATION The present study protocol has been registered at https://clinicaltrials.gov/ (registration nr NCT03938727 , date 03.05.2019).
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Affiliation(s)
- Mariagnese Barbera
- Institute of Clinical Medicine, Department of Neurology, University of Eastern Finland, P.O. Box 1627, 70211, Kuopio, Finland.
| | - Jenni Kulmala
- Public Health Promotion Unit, Finnish Institute for Health and Welfare, P.O. Box 30, 00271, Helsinki, Finland.,School of Health Care and Social Work, Seinäjoki University of Applied Sciences, Seinäjoki, Finland.,Division of Clinical Geriatrics, Center for Alzheimer Research, Care Sciences and Society (NVS), Karolinska Institutet, Karolinska Universitetssjukhuset, Karolinska Vägen 37 A, QA32, Stockholm, Sweden
| | - Inna Lisko
- Division of Clinical Geriatrics, Center for Alzheimer Research, Care Sciences and Society (NVS), Karolinska Institutet, Karolinska Universitetssjukhuset, Karolinska Vägen 37 A, QA32, Stockholm, Sweden
| | - Eija Pietilä
- Institute of Clinical Medicine, Department of Neurology, University of Eastern Finland, P.O. Box 1627, 70211, Kuopio, Finland
| | - Anna Rosenberg
- Institute of Clinical Medicine, Department of Neurology, University of Eastern Finland, P.O. Box 1627, 70211, Kuopio, Finland
| | - Ilona Hallikainen
- Institute of Clinical Medicine, Department of Neurology, University of Eastern Finland, P.O. Box 1627, 70211, Kuopio, Finland
| | - Merja Hallikainen
- Institute of Clinical Medicine, Department of Neurology, University of Eastern Finland, P.O. Box 1627, 70211, Kuopio, Finland
| | - Tiina Laatikainen
- Public Health Promotion Unit, Finnish Institute for Health and Welfare, P.O. Box 30, 00271, Helsinki, Finland.,Institute of Public Health and Clinical Nutrition, University of Eastern Finland, P.O. Box 1627, 70211, Kuopio, Finland.,Joint Municipal Authority for North Karelia Social and Health Services (Siun Sote), Central Hospital, Tikkamäentie 16, 80210, Joensuu, Finland
| | - Jenni Lehtisalo
- Institute of Clinical Medicine, Department of Neurology, University of Eastern Finland, P.O. Box 1627, 70211, Kuopio, Finland.,Public Health Promotion Unit, Finnish Institute for Health and Welfare, P.O. Box 30, 00271, Helsinki, Finland
| | - Elisa Neuvonen
- Institute of Clinical Medicine, Department of Neurology, University of Eastern Finland, P.O. Box 1627, 70211, Kuopio, Finland
| | - Minna Rusanen
- Institute of Clinical Medicine, Department of Neurology, University of Eastern Finland, P.O. Box 1627, 70211, Kuopio, Finland.,Public Health Promotion Unit, Finnish Institute for Health and Welfare, P.O. Box 30, 00271, Helsinki, Finland.,Neurocenter Finland, Department of Neurology, Kuopio University Hospital, Puijonlaaksontie 2, 70210, Kuopio, Finland
| | - Hilkka Soininen
- Institute of Clinical Medicine, Department of Neurology, University of Eastern Finland, P.O. Box 1627, 70211, Kuopio, Finland.,Neurocenter Finland, Department of Neurology, Kuopio University Hospital, Puijonlaaksontie 2, 70210, Kuopio, Finland
| | - Jaakko Tuomilehto
- Public Health Promotion Unit, Finnish Institute for Health and Welfare, P.O. Box 30, 00271, Helsinki, Finland.,Department of Public Health, University of Helsinki, PO BOX 20, 00014, Helsinki, Finland.,Diabetes Research Group, King Abdulaziz University, Jeddah, 21589, Saudi Arabia
| | - Tiia Ngandu
- Public Health Promotion Unit, Finnish Institute for Health and Welfare, P.O. Box 30, 00271, Helsinki, Finland.,Division of Clinical Geriatrics, Center for Alzheimer Research, Care Sciences and Society (NVS), Karolinska Institutet, Karolinska Universitetssjukhuset, Karolinska Vägen 37 A, QA32, Stockholm, Sweden
| | - Alina Solomon
- Institute of Clinical Medicine, Department of Neurology, University of Eastern Finland, P.O. Box 1627, 70211, Kuopio, Finland.,Division of Clinical Geriatrics, Center for Alzheimer Research, Care Sciences and Society (NVS), Karolinska Institutet, Karolinska Universitetssjukhuset, Karolinska Vägen 37 A, QA32, Stockholm, Sweden
| | - Miia Kivipelto
- Institute of Clinical Medicine, Department of Neurology, University of Eastern Finland, P.O. Box 1627, 70211, Kuopio, Finland.,Division of Clinical Geriatrics, Center for Alzheimer Research, Care Sciences and Society (NVS), Karolinska Institutet, Karolinska Universitetssjukhuset, Karolinska Vägen 37 A, QA32, Stockholm, Sweden.,Institute of Public Health and Clinical Nutrition, University of Eastern Finland, P.O. Box 1627, 70211, Kuopio, Finland.,Ageing Epidemiology Research Unit, School of Public Health, Imperial College London, Charing Cross Hospital, St Dunstan's Road, London, W6 8RP, UK
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38
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Wang W, Zhao F, Ma X, Perry G, Zhu X. Mitochondria dysfunction in the pathogenesis of Alzheimer's disease: recent advances. Mol Neurodegener 2020; 15:30. [PMID: 32471464 PMCID: PMC7257174 DOI: 10.1186/s13024-020-00376-6] [Citation(s) in RCA: 540] [Impact Index Per Article: 135.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2019] [Accepted: 04/24/2020] [Indexed: 12/22/2022] Open
Abstract
Alzheimer's disease (AD) is one of the most prevalent neurodegenerative diseases, characterized by impaired cognitive function due to progressive loss of neurons in the brain. Under the microscope, neuronal accumulation of abnormal tau proteins and amyloid plaques are two pathological hallmarks in affected brain regions. Although the detailed mechanism of the pathogenesis of AD is still elusive, a large body of evidence suggests that damaged mitochondria likely play fundamental roles in the pathogenesis of AD. It is believed that a healthy pool of mitochondria not only supports neuronal activity by providing enough energy supply and other related mitochondrial functions to neurons, but also guards neurons by minimizing mitochondrial related oxidative damage. In this regard, exploration of the multitude of mitochondrial mechanisms altered in the pathogenesis of AD constitutes novel promising therapeutic targets for the disease. In this review, we will summarize recent progress that underscores the essential role of mitochondria dysfunction in the pathogenesis of AD and discuss mechanisms underlying mitochondrial dysfunction with a focus on the loss of mitochondrial structural and functional integrity in AD including mitochondrial biogenesis and dynamics, axonal transport, ER-mitochondria interaction, mitophagy and mitochondrial proteostasis.
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Affiliation(s)
- Wenzhang Wang
- Department of Pathology, Case Western Reserve University, 2103 Cornell Road, Cleveland, OH, 44106, USA.
| | - Fanpeng Zhao
- Department of Pathology, Case Western Reserve University, 2103 Cornell Road, Cleveland, OH, 44106, USA
| | - Xiaopin Ma
- Department of Pathology, Case Western Reserve University, 2103 Cornell Road, Cleveland, OH, 44106, USA
| | - George Perry
- College of Sciences, University of Texas at San Antonio, San Antonio, TX, USA.
| | - Xiongwei Zhu
- Department of Pathology, Case Western Reserve University, 2103 Cornell Road, Cleveland, OH, 44106, USA.
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39
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Hiremath N, Kate M, Mohimen A, Kesavadas C, Sylaja PN. Risk factors of white matter hyperintensities in South Asian patients with transient ischemic attack and minor stroke. Neuroradiology 2020; 62:1279-1284. [PMID: 32385557 DOI: 10.1007/s00234-020-02429-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2020] [Accepted: 04/02/2020] [Indexed: 10/24/2022]
Abstract
PURPOSE Aging and increased burden of cardiovascular risk factors are associated with severity of white matter hyperintensity (WMH). We assessed the burden and risk factor profile of WMHs in South Asian patients with transient ischemic attack (TIA) and minor stroke. METHODS Patients with acute ischemic stroke with the National Institute of Health stroke scale (NIHSS) score ≤ 5 who underwent MRI were included. The severity of WMHs was assessed based on age-related white matter change (ARWMC) scale (0-30). A score of > 8 or more was considered moderate-severe involvement. Logistic regression analysis was performed to assess the association with risk factors. RESULTS A total of 424 patients with a mean ± SD age of 57.4 ± 14.5 years [females, 108 (25.5%)] were analyzed. Fifty-four (12.7%) patients had moderate or severe WMHs (ARWMC score > 8). Age (OR 1.03, 95% CI 1.01-1.06; p = 0.004), hypertension (OR 2.3, 95% CI 1.1-5.1; p = 0.03) and smoking tobacco (OR 2.8, 95% CI 1.4-5.6; p = 0.003) were independently associated with ARWMC score > 8. The median (IQR) regional score in patients with ARWMC score > 8 was maximum in frontal areas 4 (4-6, p < 0.0001) and parietooccipital areas 4.5(4-6, p < 0.0001). The presence of microbleeds (OR 6.3, 95% CI 3.1-12.7; p < 0.0001) was independently associated with ARWMC score > 8. CONCLUSION South Asian patients with TIA and minor stroke are relatively young, and few patients have moderate and severe WMHs. Hypertension and tobacco smoking increases the risk of WMH. Targeting modifiable risk factors may reduce the burden of WMHs and vascular dementia.
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Affiliation(s)
- Nikhil Hiremath
- Comprehensive Stroke Care Program, Department of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology (SCTIMST), Thiruvananthapuram, Kerala, 695011, India
| | - Mahesh Kate
- Department of Clinical Neurosciences, Alberta Health Services, Edmonton, Canada
| | - Aneesh Mohimen
- Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India
| | - Chandrasekharan Kesavadas
- Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India
| | - P N Sylaja
- Comprehensive Stroke Care Program, Department of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology (SCTIMST), Thiruvananthapuram, Kerala, 695011, India.
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40
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Geng Z, Wu X, Wang L, Zhou S, Tian Y, Wang K, Wei L. Reduced delayed reward selection by Alzheimer’s disease and mild cognitive impairment patients during intertemporal decision-making. J Clin Exp Neuropsychol 2020; 42:298-306. [PMID: 31914851 DOI: 10.1080/13803395.2020.1711873] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Affiliation(s)
- Zhi Geng
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Xingqi Wu
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Lu Wang
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Shanshan Zhou
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
- Collaborative Innovation Centre of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Yanghua Tian
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
- Collaborative Innovation Centre of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Kai Wang
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
- Collaborative Innovation Centre of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Ling Wei
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
- Collaborative Innovation Centre of Neuropsychiatric Disorders and Mental Health, Hefei, China
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41
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Brugulat-Serrat A, Salvadó G, Operto G, Cacciaglia R, Sudre CH, Grau-Rivera O, Suárez-Calvet M, Falcon C, Sánchez-Benavides G, Gramunt N, Minguillon C, Fauria K, Barkhof F, Molinuevo JL, Gispert JD. White matter hyperintensities mediate gray matter volume and processing speed relationship in cognitively unimpaired participants. Hum Brain Mapp 2019; 41:1309-1322. [PMID: 31778002 PMCID: PMC7267988 DOI: 10.1002/hbm.24877] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2019] [Revised: 10/25/2019] [Accepted: 11/14/2019] [Indexed: 12/17/2022] Open
Abstract
White matter hyperintensities (WMH) have been extensively associated with cognitive impairment and reductions in gray matter volume (GMv) independently. This study explored whether WMH lesion volume mediates the relationship between cerebral patterns of GMv and cognition in 521 (mean age 57.7 years) cognitively unimpaired middle‐aged individuals. Episodic memory (EM) was measured with the Memory Binding Test and executive functions (EF) using five WAIS‐IV subtests. WMH were automatically determined from T2 and FLAIR sequences and characterized using diffusion‐weighted imaging (DWI) parameters. WMH volume was entered as a mediator in a voxel‐wise mediation analysis relating GMv and cognitive performance (with both EM and EF composites and the individual tests independently). The mediation model was corrected by age, sex, education, number of Apolipoprotein E (APOE)‐ε4 alleles and total intracranial volume. We found that even at very low levels of WMH burden in the cohort (median volume of 3.2 mL), higher WMH lesion volume was significantly associated with a widespread pattern of lower GMv in temporal, frontal, and cerebellar areas. WMH mediated the relationship between GMv and EF, mainly driven by processing speed, but not EM. DWI parameters in these lesions were compatible with incipient demyelination and axonal loss. These findings lead to the reflection on the relevance of the control of cardiovascular risk factors in middle‐aged individuals as a valuable preventive strategy to reduce or delay cognitive decline.
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Affiliation(s)
- Anna Brugulat-Serrat
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Gemma Salvadó
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Grégory Operto
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Raffaele Cacciaglia
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Carole H Sudre
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.,Dementia Research Centre, UCL, London, UK.,Centre for Medical Imaging Computing, Faculty of Engineering, University College London, London, UK
| | - Oriol Grau-Rivera
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Servei de Neurologia, Hospital del Mar, Barcelona, Spain
| | - Marc Suárez-Calvet
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Servei de Neurologia, Hospital del Mar, Barcelona, Spain
| | - Carles Falcon
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain
| | - Gonzalo Sánchez-Benavides
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | | | - Carolina Minguillon
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Karine Fauria
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Frederik Barkhof
- Centre for Medical Imaging Computing, Faculty of Engineering, University College London, London, UK.,Brain Repair and Rehabilitation, UCL Institute of Neurology, London, UK.,Radiology & Nuclear Medicine, VU University Medical Centre, Amsterdam, Netherland
| | - José L Molinuevo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Universitat Pompeu Fabra, Barcelona, Spain
| | - Juan D Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain.,Universitat Pompeu Fabra, Barcelona, Spain
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